[Federal Register Volume 83, Number 165 (Friday, August 24, 2018)]
[Proposed Rules]
[Pages 42986-43500]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2018-16820]
[[Page 42985]]
Vol. 83
Friday,
No. 165
August 24, 2018
Part II
Book 2 of 2 Books
Pages 42985-43500
Department of Transportation
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National Highway Traffic Safety Administration
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49 CFR Parts 523, 531, 533, et al.
Environmental Protection Agency
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40 CFR Parts 85 and 86
The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model
Years 2021-2026 Passenger Cars and Light Trucks; Proposed Rule
Federal Register / Vol. 83 , No. 165 / Friday, August 24, 2018 /
Proposed Rules
[[Page 42986]]
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DEPARTMENT OF TRANSPORTATION
National Highway Traffic Safety Administration
49 CFR Parts 523, 531, 533, 536, and 537
ENVIRONMENTAL PROTECTION AGENCY
40 CFR Parts 85 and 86
[NHTSA-2018-0067; EPA-HQ-OAR-2018-0283; FRL-9981-74-OAR]
RIN 2127-AL76; RIN 2060-AU09
The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for
Model Years 2021-2026 Passenger Cars and Light Trucks
AGENCY: Environmental Protection Agency and National Highway Traffic
Safety Administration.
ACTION: Notice of proposed rulemaking.
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SUMMARY: The National Highway Traffic Safety Administration (NHTSA) and
the Environmental Protection Agency (EPA) are proposing the ``Safer
Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-
2026 Passenger Cars and Light Trucks'' (SAFE Vehicles Rule). The SAFE
Vehicles Rule, if finalized, would amend certain existing Corporate
Average Fuel Economy (CAFE) and tailpipe carbon dioxide emissions
standards for passenger cars and light trucks and establish new
standards, all covering model years 2021 through 2026. More
specifically, NHTSA is proposing new CAFE standards for model years
2022 through 2026 and amending its 2021 model year CAFE standards
because they are no longer maximum feasible standards, and EPA is
proposing to amend its carbon dioxide emissions standards for model
years 2021 through 2025 because they are no longer appropriate and
reasonable in addition to establishing new standards for model year
2026. The preferred alternative is to retain the model year 2020
standards (specifically, the footprint target curves for passenger cars
and light trucks) for both programs through model year 2026, but
comment is sought on a range of alternatives discussed throughout this
document. Compared to maintaining the post-2020 standards set forth in
2012, current estimates indicate that the proposed SAFE Vehicles Rule
would save over 500 billion dollars in societal costs and reduce
highway fatalities by 12,700 lives (over the lifetimes of vehicles
through MY 2029). U.S. fuel consumption would increase by about half a
million barrels per day (2-3 percent of total daily consumption,
according to the Energy Information Administration) and would impact
the global climate by 3/1000th of one degree Celsius by 2100, also when
compared to the standards set forth in 2012.
DATES: Comments: Comments are requested on or before October 23, 2018.
Under the Paperwork Reduction Act, comments on the information
collection provisions must be received by the Office of Management and
Budget (OMB) on or before October 23, 2018. See the SUPPLEMENTARY
INFORMATION section on ``Public Participation,'' below, for more
information about written comments.
Public Hearings: NHTSA and EPA will jointly hold three public
hearings in Washington, DC; the Detroit, MI area; and in the Los
Angeles, CA area. The agencies will announce the specific dates and
addresses for each hearing location in a supplemental Federal Register
notice. The agencies will accept oral and written comments to the
rulemaking documents, and NHTSA will also accept comments to the Draft
Environmental Impact Statement (DEIS) at these hearings. The hearings
will start at 10 a.m. local time and continue until everyone has had a
chance to speak. See the SUPPLEMENTARY INFORMATION section on ``Public
Participation,'' below, for more information about the public hearings.
ADDRESSES: You may send comments, identified by Docket No. EPA-HQ-OAR-
2018-0283 and/or NHTSA-2018-0067, by any of the following methods:
Federal eRulemaking Portal: http://www.regulations.gov.
Follow the instructions for sending comments.
Fax: EPA: (202) 566-9744; NHTSA: (202) 493-2251.
Mail:
[cir] EPA: Environmental Protection Agency, EPA Docket Center (EPA/
DC), Air and Radiation Docket, Mail Code 28221T, 1200 Pennsylvania
Avenue NW, Washington, DC 20460, Attention Docket ID No. EPA-HQ-OAR-
2018-0283. In addition, please mail a copy of your comments on the
information collection provisions for the EPA proposal to the Office of
Information and Regulatory Affairs, Office of Management and Budget
(OMB), Attn: Desk Officer for EPA, 725 17th St. NW, Washington, DC
20503.
[cir] NHTSA: Docket Management Facility, M-30, U.S. Department of
Transportation, West Building, Ground Floor, Rm. W12-140, 1200 New
Jersey Avenue SE, Washington, DC 20590.
Hand Delivery:
[cir] EPA: Docket Center (EPA/DC), EPA West, Room B102, 1301
Constitution Avenue NW, Washington, DC, Attention Docket ID No. EPA-HQ-
OAR-2018-0283. Such deliveries are only accepted during the Docket's
normal hours of operation, and special arrangements should be made for
deliveries of boxed information.
[cir] NHTSA: West Building, Ground Floor, Rm. W12-140, 1200 New
Jersey Avenue SE, Washington, DC 20590, between 9 a.m. and 4 p.m.
Eastern Time, Monday through Friday, except Federal holidays.
Instructions: All submissions received must include the agency name
and docket number or Regulatory Information Number (RIN) for this
rulemaking. All comments received will be posted without change to
http://www.regulations.gov, including any personal information
provided. For detailed instructions on sending comments and additional
information on the rulemaking process, see the ``Public Participation''
heading of the SUPPLEMENTARY INFORMATION section of this document.
Docket: For access to the dockets to read background documents or
comments received, go to http://www.regulations.gov, and/or:
For EPA: EPA Docket Center (EPA/DC), EPA West, Room 3334,
1301 Constitution Avenue NW, Washington, DC 20460. The Public Reading
Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday,
excluding legal holidays. The telephone number for the Public Reading
Room is (202) 566-1744.
For NHTSA: Docket Management Facility, M-30, U.S.
Department of Transportation, West Building, Ground Floor, Rm. W12-140,
1200 New Jersey Avenue SE, Washington, DC 20590. The Docket Management
Facility is open between 9 a.m. and 4 p.m. Eastern Time, Monday through
Friday, except Federal holidays.
FOR FURTHER INFORMATION CONTACT: EPA: Christopher Lieske, Office of
Transportation and Air Quality, Assessment and Standards Division,
Environmental Protection Agency, 2000 Traverwood Drive, Ann Arbor, MI
48105; telephone number: (734) 214-4584; fax number: (734) 214-4816;
email address: [email protected], or contact the Assessment
and Standards Division, email address: [email protected]. NHTSA:
James Tamm, Office of Rulemaking, Fuel Economy Division, National
Highway Traffic Safety Administration, 1200 New Jersey Avenue SE,
Washington, DC 20590; telephone number: (202) 493-0515.
[[Page 42987]]
SUPPLEMENTARY INFORMATION:
I. Overview of Joint NHTSA/EPA Proposal
II. Technical Foundation for NPRM Analysis
III. Proposed CAFE and CO2 Standards for MYs 2021-2026
IV. Alternative CAFE and GHG Standards Considered for MYs 2021/22-
2026
V. Proposed Standards, the Agencies' Statutory Obligations, and Why
the Agencies Propose To Choose Them Over the Alternatives
VI. Preemption of State and Local Laws
VII. Impacts of the Proposed CAFE and CO2 Standards
VIII. Impacts of Alternative CAFE and CO2 Standards
Considered for MYs 2021/22-2026
IX. Vehicle Classification
X. Compliance and Enforcement
XI. Public Participation
XII. Regulatory Notices and Analyses
I. Overview of Joint NHTSA/EPA Proposal
A. Executive Summary
In this notice, the National Highway Traffic Safety Administration
(NHTSA) and the Environmental Protection Agency (EPA) (collectively,
``the agencies'') are proposing the ``Safer Affordable Fuel-Efficient
(SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light
Trucks'' (SAFE Vehicles Rule). The proposed SAFE Vehicles Rule would
set Corporate Average Fuel Economy (CAFE) and carbon dioxide
(CO2) emissions standards, respectively, for passenger cars
and light trucks manufactured for sale in the United States in model
years (MYs) 2021 through 2026.\1\ CAFE and CO2 standards
have the power to transform the vehicle fleet and affect Americans'
lives in significant, if not always immediately obvious, ways. The
proposed SAFE Vehicles Rule seeks to ensure that government action on
these standards is appropriate, reasonable, consistent with law,
consistent with current and foreseeable future economic realities, and
supported by a transparent assessment of current facts and data.
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\1\ NHTSA sets CAFE standards under the Energy Policy and
Conservation Act of 1975 (EPCA), as amended by the Energy
Independence and Security Act of 2007 (EISA). EPA sets
CO2 standards under the Clean Air Act (CAA).
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The agencies must act to propose and finalize these standards and
do not have discretion to decline to regulate. Congress requires NHTSA
to set CAFE standards for each model year.\2\ Congress also requires
EPA to set emissions standards for light-duty vehicles if EPA has made
an ``endangerment finding'' that the pollutant in question--in this
case, CO2--``cause[s] or contribute[s] to air pollution
which may reasonably be anticipated to endanger public health or
welfare.'' \3\ NHTSA and EPA are proposing these standards concurrently
because tailpipe CO2 emissions standards are directly and
inherently related to fuel economy standards,\4\ and if finalized,
these rules would apply concurrently to the same fleet of vehicles. By
working together to develop these proposals, the agencies reduce
regulatory burden on industry and improve administrative efficiency.
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\2\ 49 U.S.C. 32902.
\3\ 42 U.S.C. 7521, see also 74 FR 66495 (Dec. 15, 2009)
(``Endangerment and Cause or Contribute Findings for Greenhouse
Gases under Section 202(a) of the Clean Air Act'').
\4\ See, e.g., 75 FR 25324, at 25327 (May 7, 2010) (``The
National Program is both needed and possible because the
relationship between improving fuel economy and reducing tailpipe
CO2 emissions is a very direct and close one. The amount
of those CO2 emissions is essentially constant per gallon
combusted of a given type of fuel. Thus, the more fuel efficient a
vehicle is, the less fuel it burns to travel a given distance. The
less fuel it burns, the less CO2 it emits in traveling
that distance. [citation omitted] While there are emission control
technologies that reduce the pollutants (e.g., carbon monoxide)
produced by imperfect combustion of fuel by capturing or converting
them to other compounds, there is no such technology for
CO2. Further, while some of those pollutants can also be
reduced by achieving a more complete combustion of fuel, doing so
only increases the tailpipe emissions of CO2. Thus, there
is a single pool of technologies for addressing these twin problems,
i.e., those that reduce fuel consumption and thereby reduce
CO2 emissions as well.'')
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Consistent with both agencies' statutes, this proposal is entirely
de novo, based on an entirely new analysis reflecting the best and most
up-to-date information available to the agencies at the time of this
rulemaking. The agencies worked together in 2012 to develop CAFE and
CO2 standards for MYs 2017 and beyond; in that rulemaking
action, EPA set CO2 standards for MYs 2017-2025, while NHTSA
set final CAFE standards for MYs 2017-2021 and also put forth
``augural'' CAFE standards for MYs 2022-2025, consistent with EPA's
CO2 standards for those model years. EPA's CO2
standards for MYs 2022-2025 were subject to a ``mid-term evaluation,''
by which EPA bound itself through regulation to re-evaluate the
CO2 standards for those model years and to undertake to
develop new CO2 standards through a regulatory process if it
concluded that the previously finalized standards were no longer
appropriate. EPA regulations on the mid-term evaluation process
required EPA to issue a Final Determination no later than April 1, 2018
on whether the GHG standards for MY 2022-2025 light-duty vehicles
remain appropriate under section 202(a) of the Clean Air Act.\5\ The
regulations also required the issuance of a draft Technical Assessment
Report (TAR) by November 15, 2017, an opportunity for public comment on
the draft TAR, and, before making a Final Determination, an opportunity
for public comment on whether the GHG standards for MY 2022-2025 remain
appropriate. In July 2016, the draft TAR was issued for public comment
jointly by the EPA, NHTSA, and the California Air Resources Board
(CARB).\6\ Following the draft TAR, EPA published a Proposed
Determination for public comment on December 6, 2016 and provided less
than 30 days for public comments over major holidays.\7\ EPA published
the January 2017 Determination on EPA's website and regulations.gov
finding that the MY 2022-2025 standards remained appropriate.\8\
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\5\ 40 CFR 86.1818-12(h)(1); see also 77 FR 62624 (Oct. 15,
2012).
\6\ 81 FR 49217 (Jul. 27, 2016).
\7\ 81 FR 87927 (Dec. 6, 2016).
\8\ Docket item EPA-HQ-OAR-2015-0827-6270 (EPA-420-R-17-001).
This conclusion generated a significant amount of public concern.
See, e.g., Letter from Auto Alliance to Scott Pruitt, Administrator,
Environmental Protection Agency (Feb. 21, 2017); Letter from Global
Automakers to Scott Pruitt, Administrator, Environmental Protection
Agency (Feb. 21, 2017).
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On March 15, 2017, President Trump announced a restoration of the
original mid-term review timeline. The President made clear in his
remarks, ``[i]f the standards threatened auto jobs, then commonsense
changes'' would be made in order to protect the economic viability of
the U.S. automotive industry.'' \9\ In response to the President's
direction, EPA announced in a March 22, 2017, Federal Register notice,
its intention to reconsider the Final Determination of the mid-term
evaluation of GHGs emissions standards for MY 2022-2025 light-duty
vehicles.\10\ The Administrator stated that EPA would coordinate its
reconsideration with the rulemaking process to be undertaken by NHTSA
regarding CAFE standards for cars and light trucks for the same model
years.
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\9\ See https://www.whitehouse.gov/briefings-statements/remarks-president-trump-american-center-mobility-detroit-mi/.
\10\ 82 FR 14671 (Mar. 22, 2017).
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On August 21, 2017, EPA published a notice in the Federal Register
announcing the opening of a 45-day public comment period and inviting
stakeholders to submit any additional comments, data, and information
they believed were relevant to the Administrator's reconsideration of
the
[[Page 42988]]
January 2017 Determination.\11\ EPA held a public hearing in Washington
DC on September 6, 2017.\12\ EPA received more than 290,000 comments in
response to the August 21, 2017 notice.\13\
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\11\ 82 FR 39551 (Aug. 21, 2017).
\12\ 82 FR 39976 (Aug. 23, 2017).
\13\ The public comments, public hearing transcript, and other
information relevant to the Mid-term Evaluation are available in
docket EPA-HQ-OAR-2015-0827.
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EPA has since concluded, based on more recent information, that
those standards are no longer appropriate.\14\ NHTSA's ``augural'' CAFE
standards for MYs 2022-2025 were not final in 2012 because Congress
prohibits NHTSA from finalizing new CAFE standards for more than five
model years in a single rulemaking.\15\ NHTSA was therefore obligated
from the beginning to undertake a new rulemaking to set CAFE standards
for MYs 2022-2025.
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\14\ 83 FR 16077 (Apr. 2, 2018).
\15\ 49 U.S.C. 32902.
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The proposed SAFE Vehicles Rule begins the rulemaking process for
both agencies to establish new standards for MYs 2022-2025 passenger
cars and light trucks. Standards are concurrently being proposed for MY
2026 in order to provide regulatory stability for as many years as is
legally permissible for both agencies together.
Separately, the proposed SAFE Vehicles Rule includes revised
standards for MY 2021 passenger cars and light trucks. The information
now available and the current analysis suggest that the CAFE standards
previously set for MY 2021 are no longer maximum feasible, and the
CO2 standards previously set for MY 2021 are no longer
appropriate. Agencies always have authority under the Administrative
Procedure Act to revisit previous decisions in light of new facts, as
long as they provide notice and an opportunity for comment, and it is
plainly the best practice to do so when changed circumstances so
warrant.\16\
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\16\ See FCC v. Fox Television, 556 U.S. 502 (2009).
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Thus, the proposed SAFE Vehicles Rule would maintain the CAFE and
CO2 standards applicable in MY 2020 for MYs 2021-2026, while
taking comment on a wide range of alternatives, including different
stringencies and retaining existing CO2 standards and the
augural CAFE standards.\17\ Table I-4 below presents those
alternatives. We note further that prior to MY 2021, CO2
targets include adjustments reflecting the use of automotive
refrigerants with reduced global warming potential (GWP) and/or the use
of technologies that reduce the refrigerant leaks, and optionally
offsets for nitrous oxide and methane emissions. In the interests of
harmonizing with the CAFE program, EPA is proposing to exclude air
conditioning refrigerants and leakage, and nitrous oxide and methane
emissions for compliance with CO2 standards after model year
2020 but seeks comment on whether to retain these element, and reinsert
A/C leakage offsets, and remain disharmonized with the CAFE program.
EPA also seeks comment on whether to change existing methane and
nitrous oxide standards that were finalized in the 2012 rule.
Specifically, EPA seeks information from the public on whether those
existing standards are appropriate, or whether they should be revised
to be less stringent or more stringent based on any updated data.
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\17\ Note: This does not mean that the miles per gallon and
grams per mile levels that were estimated for the MY 2020 fleet in
2012 would be the ``standards'' going forward into MYs 2021-2026.
Both NHTSA and EPA set CAFE and CO2 standards,
respectively, as mathematical functions based on vehicle footprint.
These mathematical functions that are the actual standards are
defined as ``curves'' that are separate for passenger cars and light
trucks, under which each vehicle manufacturer's compliance
obligation varies depending on the footprints of the cars and trucks
that it ultimately produces for sale in a given model year. It is
the MY 2020 CAFE and CO2 curves which we propose would
continue to apply to the passenger car and light truck fleets for
MYs 2021-2026. The mpg and g/mi values which those curves would
eventually require of the fleets in those model years would be known
for certain only at the ends of each of those model years. While it
is convenient to discuss CAFE and CO2 standards as a set
``mpg,'' ``g/mi,'' or ``mpg-e'' number, attempting to define those
values today will end up being inaccurate.
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While actual requirements will ultimately vary for automakers
depending upon their individual fleet mix of vehicles, many
stakeholders will likely be interested in the current estimate of what
the MY 2020 CAFE and CO2 curves would translate to, in terms
of miles per gallon (mpg) and grams per mile (g/mi), in MYs 2021-2026.
These estimates are shown in the following tables.
BILLING CODE 4910-59-P
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[GRAPHIC] [TIFF OMITTED] TP24AU18.001
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BILLING CODE 4910-59-C
In the tables above, estimated required CO2 increases
between MY 2020 and MY 2021 because, again, EPA is proposing to exclude
CO2-equivalent emission improvements associated with air
conditioning refrigerants and leakage (and, optionally, offsets for
nitrous oxide and methane emissions) after model year 2020.
As explained above, the agencies are taking comment on a wide range
of alternatives and have specifically modeled eight alternatives
(including the proposed alternative) and the current requirements
(i.e., baseline/no-action). The modeled alternatives are provided
below:
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\18\ Carbon dioxide equivalent of air conditioning refrigerant
leakage, nitrous oxide and methane emissions are included for
compliance with the EPA standards for all MYs under the baseline/no
action alternative. Carbon dioxide equivalent is calculated using
the Global Warming Potential (GWP) of each of the emissions.
\19\ Beginning in MY 2021, the proposal provides that the GWP
equivalents of air conditioning refrigerant leakage, nitrous oxide
and methane emissions would no longer be able to be included with
the tailpipe CO2 for compliance with tailpipe
CO2 standards.
[GRAPHIC] [TIFF OMITTED] TP24AU18.002
Summary of Rationale
Since finalizing the agencies' previous joint rulemaking in 2012
titled ``Final Rule for Model Year 2017 and Later Light-Duty Vehicle
Greenhouse Gas Emission and Corporate Average Fuel Economy Standards,''
and even since EPA's 2016 and early 2017 ``mid-term evaluation''
process, the agencies have gathered new information, and have performed
new analysis. That new information and analysis has led the
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agencies to the tentative conclusion that holding standards constant at
MY 2020 levels through MY 2026 is maximum feasible, for CAFE purposes,
and appropriate, for CO2 purposes.
Technologies have played out differently in the fleet from what the
agencies assumed in 2012.
The technology to improve fuel economy and reduce CO2
emissions has not changed dramatically since prior analyses were
conducted: A wide variety of technologies are still available to
accomplish the goals of the programs, and a wide variety of
technologies would likely be used by industry to accomplish these
goals. There remains no single technology that the majority of vehicles
made by the majority of manufacturers can implement at low cost without
affecting other vehicle attributes that consumers value more than fuel
economy and CO2 emissions. Even when used in combination,
technologies that can improve fuel economy and reduce CO2
emissions still need to (1) actually work together and (2) be
acceptable to consumers and avoid sacrificing other vehicle attributes
while also avoiding undue increases in vehicle cost. Optimism about the
costs and effectiveness of many individual technologies, as compared to
recent prior rounds of rulemaking, is somewhat tempered; a clearer
understanding of what technologies are already on vehicles in the fleet
and how they are being used, again as compared to recent prior rounds
of rulemaking, means that technologies that previously appeared to
offer significant ``bang for the buck'' may no longer do so.
Additionally, in light of the reality that vehicle manufacturers may
choose the relatively cost-effective technology option of vehicle
lightweighting for a wide array of vehicles and not just the largest
and heaviest, it is now recognized that as the stringency of standards
increases, so does the likelihood that higher stringency will increase
on-road fatalities. As it turns out, there is no such thing as a free
lunch.\20\
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\20\ Mankiw, N. Gregory, Principles of Macroeconomics, Sixth
Edition, 2012, at 4.
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Technology that can improve both fuel economy and/or performance
may not be dedicated solely to fuel economy.
As fleet-wide fuel efficiency has improved over time, additional
improvements have become both more complicated and more costly. There
are two primary reasons for this phenomenon. First, as discussed, there
is a known pool of technologies for improving fuel economy and reducing
CO2 emissions. Many of these technologies, when actually
implemented on vehicles, can be used to improve other vehicle
attributes such as ``zero to 60'' performance, towing, and hauling,
etc., either instead of or in addition to improving fuel economy and
reducing CO2 emissions. As one example, a V6 engine can be
turbocharged and downsized so that it consumes only as much fuel as an
inline 4-cylinder engine, or it can be turbocharged and downsized so
that it consumes less fuel than it would originally have consumed (but
more than the inline 4-cylinder would) while also providing more low-
end torque. As another example, a vehicle can be lightweighted so that
it consumes less fuel than it would originally have consumed, or so
that it consumes the same amount of fuel it would originally have
consumed but can carry more content, like additional safety or
infotainment equipment. Manufacturers employing ``fuel-saving/
emissions-reducing'' technologies in the real world make decisions
regarding how to employ that technology such that fewer than 100% of
the possible fuel-saving/emissions-reducing benefits result. They do
this because this is what consumers want, and more so than exclusively
fuel economy improvements.
This makes actual fuel economy gains more expensive.
Thus, even though the technologies may be largely the same,
previous assumptions about how much fuel can be saved or how much
emissions can be reduced by employing various technologies may not have
played out as prior analyses suggested, meaning that previous
assumptions about how much it would cost to save that much fuel or
reduce that much in emissions fall correspondingly short. For example,
the agencies assumed in the 2010 final rule that dual clutch
transmissions would be widely used to improve fuel economy due to
expectations of strong effectiveness and very low cost: In practice,
dual clutch transmissions had significant customer acceptance issues,
and few manufacturers employ them in the U.S. market today.\21\ The
agencies included some ``technologies'' in the 2012 final rule analysis
that were defined ambiguously and/or in ways that precluded observation
in the known (MYs 2008 and 2010) fleets, likely leading to double
counting in cases where the known vehicles already reflected the
assumed efficiency improvement. For example, the agencies assumed that
transmission ``shift optimizers'' would be available and fairly widely
used in MYs 2017-2025, but involving software controls, a
``technology'' not defined in a way that would be observed in the fleet
(unlike, for example, a dual clutch transmission).
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\21\ In fact, one manufacturer saw enough customer pushback that
it launched a buyback program. See, e.g., Steve Lehto, ``What you
need to know about the settlement for Ford Powershift owners,'' Road
and Track, Oct. 19, 2017. Available at https://www.roadandtrack.com/car-culture/a10316276/what-you-need-to-know-about-the-proposed-settlement-for-ford-powershift-owners/ (last accessed Jul. 2, 2018).
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To be clear, this is no one's ``fault''--the CAFE and
CO2 standards do not require manufacturers to use particular
technologies in particular ways, and both agencies' past analyses
generally sought to illustrate technology paths to compliance that were
assumed to be as cost-effective as possible. If manufacturers choose
different paths for reasons not accounted for in regulatory analysis,
or choose to use technologies differently from what the agencies
previously assumed, it does not necessarily mean that the analyses were
unreasonable when performed. It does mean, however, that the fleet
ought to be reflected as it stands today, with the technology it has
and as that technology has been used, and consider what technology
remains on the table at this point, whether and when it can
realistically be available for widespread use in production, and how
much it would cost to implement.
Incremental additional fuel economy benefits are subject to
diminishing returns.
As fleet-wide fuel efficiency improves and CO2 emissions
are reduced, the incremental benefit of continuing to improve/reduce
inevitably decreases. This is because, as the base level of fuel
economy improves, fewer gallons are saved from subsequent incremental
improvements. Put simply, a one mpg increase for vehicles with low fuel
economy will result in far greater savings than an identical 1 mpg
increase for vehicles with higher fuel economy, and the cost for
achieving a one-mpg increase for low fuel economy vehicles is far less
than for higher fuel economy vehicles. This means that improving fuel
economy is subject to diminishing returns. Annual fuel consumption can
be calculated as follows:
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For purposes of illustration, assume a vehicle owner who drives a
light vehicle 15,000 miles per year (a typical assumption for
analytical purposes).\22\ If that owner trades in a vehicle with fuel
economy of 15 mpg for one with fuel economy of 20 mpg, the owner's
annual fuel consumption would drop from 1,000 gallons to 750 gallons--
saving 250 gallons annually. If, however, that owner were to trade in a
vehicle with fuel economy of 30 mpg for one with fuel economy of 40
mpg, the owner's annual gasoline consumption would drop from 500
gallons/year to 375 gallons/year--only 125 gallons even though the mpg
improvement is twice as large. Going from 40 to 50 mpg would save only
75 gallons/year. Yet, each additional fuel economy improvement becomes
much more expensive as the low-hanging fruit of low-cost technological
improvement options are picked.\23\ Automakers, who must nonetheless
continue adding technology to improve fuel economy and reduce
CO2 emissions, will either sacrifice other performance
attributes or raise the price of vehicles--neither of which is
attractive to most consumers.
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\22\ A different vehicle-miles-traveled (VMT) assumption would
change the absolute numbers in the example, but would not change the
mathematical principles. Today's analysis uses mileage accumulation
schedules that average about 15,000 miles annually over the first
six years of vehicle operation.
\23\ The examples in the text above are presented in mpg because
that is a metric which should be readily understandable to most
readers, but the example would hold true for grams of CO2
per mile as well. If a vehicle emits 300 g/mi CO2, a 20
percent improvement is 60 g/mi, so that the vehicle would emit 240
g/mi. At 180 g/mi, a 20% improvement is 36 g/mi, so the vehicle
would get 144 g/mi. In order to continue achieving similarly large
(on an absolute basis) emissions reductions, mathematics require the
percentage reduction to continue increasing.
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If fuel prices are high, the value of those gallons may be enough
to offset the cost of further fuel economy improvements, but (1) the
most recent reference case projections in the Energy Information
Administration's (EIA's) Annual Energy Outlook (AEO 2017 and AEO 2018)
do not indicate particularly high fuel prices in the foreseeable
future, given underlying assumptions,\24\ and (2) as the baseline level
of fuel economy continues to increase, the marginal cost of the next
gallon saved similarly increases with the cost of the technologies
required to meet the savings. The following figure illustrates the fact
that fuel savings and corresponding avoided costs diminish with
increasing fuel economy, showing the same basic pattern as a 2014
illustration developed by EIA.\25\
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\24\ The U.S. Energy Information Administration (EIA) is the
statistical and analytical agency within the U.S. Department of
Energy (DOE). EIA is the nation's premiere source of energy
information, and every fuel economy rulemaking since 2002 (and every
joint CAFE and CO2 rulemaking since 2009) has applied
fuel price projections from EIA's Annual Energy Outlook (AEO). AEO
projections, documentation, and underlying data and estimates are
available at https://www.eia.gov/outlooks/aeo/.
\25\ Today in Energy: Fuel economy improvements show diminishing
returns in fuel savings, U.S. Energy Information Administration
(Jul. 11, 2014), https://www.eia.gov/todayinenergy/detail.php?id=17071.
[GRAPHIC] [TIFF OMITTED] TP24AU18.004
[[Page 42993]]
This effect is mathematical in nature and long-established, but
when combined with relatively low fuel prices potentially through 2050,
and the likelihood that a large majority of American consumers could
consequently continue to place a higher value on vehicle attributes
other than fuel economy, it makes manufacturers' ability to sell light
vehicles with ever-higher fuel economy and ever-lower carbon dioxide
emissions increasingly difficult. Put more simply, if gas is cheap and
each additional improvement saves less gas anyway, most consumers would
rather spend their money on attributes other than fuel economy when
they are considering a new vehicle purchase, whether that is more
safety technology, a better infotainment package, a more powerful
powertrain, or other features (or, indeed, they may prefer to spend the
savings on something other than automobiles). Manufacturers trying to
sell consumers more fuel economy in such circumstances may convince
consumers who place weight on efficiency and reduced carbon emissions,
but consumers decide for themselves what attributes are worth to them.
And while some contend that consumers do not sufficiently consider or
value future fuel savings when making vehicle purchasing decisions,\26\
information regarding the benefits of higher fuel economy has never
been made more readily available than today, with a host of online
tools and mandatory prominent disclosures on new vehicles on the
Monroney label showing fuel savings compared to average vehicles. This
is not a question of ``if you build it, they will come.'' Despite the
widespread availability of fuel economy information, and despite
manufacturers building and marketing vehicles with higher fuel economy
and increasing their offerings of hybrid and electric vehicles, in the
past several years as gas prices have remained low, consumer
preferences have shifted markedly away from higher-fuel-economy smaller
and midsize passenger vehicles toward crossovers and truck-based
utility vehicles.\27\ Some consumers plainly value fuel economy and low
CO2 emissions above other attributes, and thanks in part to
CAFE and CO2 standards, they have a plentiful selection of
high-fuel economy and low CO2-emitting vehicles to choose
from, but those consumers represent a relatively small percentage of
buyers.
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\26\ In docket numbers EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068,
see comments submitted by, e.g., Consumer Federation of America
(NHTSA-2016-0068-0054, at p. 57, et seq.) and the Environmental
Defense Fund (EPA-HQ-OAR-2015-0827-4086, at p. 18, et seq.).
\27\ Carey, N. Lured by rising SUV sales, automakers flood
market with models, Reuters (Mar. 29, 2018), available at https://www.reuters.com/article/us-autoshow-new-york-suvs/lured-by-rising-suv-sales-automakers-flood-market-with-models-idUSKBN1H50KI (last
accessed Jun. 13, 2018). Many commentators have recently argued that
manufacturers are deliberately increasing vehicle footprint size in
order to get ``easier'' CAFE and CO2 standards. This
misunderstands, somewhat, how the footprint-based standards work.
While it is correct that larger-footprint vehicles have less
stringent ``targets,'' the difficulty of compliance rests in how far
above or below those vehicles are as compared to their targets, and
more specifically, whether the manufacturer is selling so many
vehicles that are far short of their targets that they cannot
average out to compliant levels through other vehicles sold that
beat their targets. For example, under the CAFE program, a
manufacturer building a fleet of larger-footprint vehicles may have
an objectively lower mpg-value compliance obligation than a
manufacturer building a more mixed fleet, but it may still be more
challenging for the first manufacturer to reach its compliance
obligation if it is selling only very-low-mpg variants at any given
footprint. There is only so much that increasing footprint makes it
``easier'' for a manufacturer to reach compliance.
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Changed petroleum market has supported a shift in consumer
preferences.
In 2012, the agencies projected fuel prices would rise
significantly, and the United States would continue to rely heavily
upon imports of oil, subjecting the country to heightened risk of price
shocks.\28\ Things have changed significantly since 2012, with fuel
prices significantly lower than anticipated, and projected to remain
low through 2050. Furthermore, the global petroleum market has shifted
dramatically with the United States taking advantage of its own oil
supplies through technological advances that allow for cost-effective
extraction of shale oil. The U.S. is now the world's largest oil
producer and expected to become a net petroleum exporter in the next
decade.\29\
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\28\ The 2012 final rule analysis relied on the Energy
Information Administration's Annual Energy Outlook 2012 Early
Release, which assumed significantly higher fuel prices than the AEO
2017 (or AEO 2018) currently available. See 77 FR 62624, 62715 (Oct.
15, 2012) for the 2012 final rule's description of the fuel price
estimates used.
\29\ Annual Energy Outlook 2018, U.S. Energy Information
Administration, at 53 (Feb. 6, 2018), https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf.
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At least partially in response to lower fuel prices, consumers have
moved more heavily into crossovers, sport utility vehicles and pickup
trucks, than anticipated at the time of the last rulemaking. Because
standards are based on footprint and specified separately for passenger
cars and light trucks, these shifts do not necessarily pose compliance
challenges by themselves, but they tend to reduce the overall average
fuel economy rates and increase the overall average CO2
emission rates of the new vehicle fleet. Consumers are also
demonstrating a preference for more powerful engines and vehicles with
higher seating positions and ride height (and accompanying mass
increase relative to footprint) \30\--all of which present challenges
for achieving increased fuel economy levels and lower CO2
emission rates.
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\30\ See id.
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The Consequence of Unreasonable Fuel Economy and CO2 Standards:
Increased vehicle prices keep consumers in older, dirtier, and less
safe vehicles.
Consumers tend to avoid purchasing things that they neither want or
need. The analysis in today's proposal moves closer to being able to
represent this fact through an improved model for vehicle scrappage
rates. While neither this nor a sales response model, also included in
today's analysis, nor the combination of the two, are consumer choice
models, today's analysis illustrates market-wide impacts on the sale of
new vehicles and the retention of used vehicles. Higher vehicle prices,
which result from more-stringent fuel economy standards, have an effect
on consumer purchasing decisions. As prices increase, the market-wide
incentive to extract additional travel from used vehicles increases.
The average age of the in-service fleet has been increasing, and when
fleet turnover slows, not only does it take longer for fleet-wide fuel
economy and CO2 emissions to improve, but also safety
improvements, criteria pollutant emissions improvements, many other
vehicle attributes that also provide societal benefits take longer to
be reflected in the overall U.S. fleet as well because of reduced
turnover. Raising vehicle prices too far, too fast, such as through
very stringent fuel economy and CO2 emissions standards
(especially considering that, on a fleet-wide basis, new vehicle sales
and turnover do not appear strongly responsive to fuel economy), has
effects beyond simply a slowdown in sales. Improvements over time have
better longer-term effects simply by not alienating consumers, as
compared to great leaps forward that drive people out of the new car
market or into vehicles that do not meet their needs. The industry has
achieved tremendous gains in fuel economy over the past decade, and
these increases will continue at least through 2020.
Along with these gains, there have also been tremendous increases
in vehicle prices, as new vehicles become increasingly unaffordable--
with the average new vehicle transaction price
[[Page 42994]]
recently exceeding $36,000--up by more than $3,000 since 2014
alone.\31\ In fact, a recent independent study indicated that the
average new car price is unaffordable to median-income families in
every metropolitan region in the United States except one: Washington,
DC.\32\ That analysis used the historically accepted approach that
consumers should make a down-payment of at least 20% of a vehicle's
purchase price, finance for no longer than four years, and make
payments of 10% or less of the consumer's annual income to car payments
and insurance. But the market looks nothing like that these days, with
average financing terms of 68 months, and an increasing proportion
exceeding 72 or even 84 months.\33\ Longer financing terms may allow a
consumer to keep their monthly payment affordable but can have serious
potential financial consequences. Longer-term financing leads
(generally) to higher interest rates, larger finance charges and total
consumer costs, and a longer period of time with negative equity. In
2012, the agencies expected prices to increase under the standards
announced at that time. The agencies estimated that, compared to a
continuation of the model year 2016 standards, the standards issued
through model year 2025 would eventually increase average prices by
about $1,500-$1,800.\34\ \35\ \36\ Circumstances have changed, the
analytical methods and inputs have been updated (including updates to
address issues still present in analyses published in 2016, 2017, and
early 2018), and today, the analysis suggests that, compared to the
proposed standards today, the previously-issued standards would
increase average vehicle prices by about $2,100. While today's estimate
is similar in magnitude to the 2012 estimate, it is relative to a
baseline that includes increases in stringency between MY 2016 and MY
2020. Compared to leaving vehicle technology at MY 2016 levels, today's
analysis shows the previously-issued standards through model year 2025
could eventually increase average vehicle prices by approximately
$2,700. A pause in continued increases in fuel economy standards, and
cost increases attributable thereto, is appropriate.
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\31\ See, e.g., Average New-Car Prices Rise Nearly 4 Percent for
January 2018 On Shifting Sales Mix, According To Kelley Blue Book,
Kelley Blue Book, https://mediaroom.kbb.com/2018-02-01-Average-New-Car-Prices-Rise-Nearly-4-Percent-For-January-2018-On-Shifting-Sales-Mix-According-To-Kelley-Blue-Book (last accessed Jun. 15, 2018).
\32\ Bell, C. What's an `affordable' car where you live? The
answer may surprise you, Bankrate.com (Jun. 28, 2017), available at
https://www.bankrate.com/auto/new-car-affordability-survey/ (last
accessed Jun. 15, 2018).
\33\ Average Auto Loan Interest Rates: 2018 Facts and Figures,
ValuePenguin, available at https://www.valuepenguin.com/auto-loans/average-auto-loan-interest-rates (last accessed Jun. 15, 2018).
\34\ 77 FR 62624, 62666 (Oct. 15, 2012).
\35\ The $1,500 figure reported in 2012 by NHTSA reflected
application of carried-forward credits in model year 2025, rather
than an achieved CAFE level that could be sustainably compliant
beyond 2025 (with standards remaining at 2025 levels). As for the
2016 draft TAR, NHTSA has since updated its modeling approach to
extend far enough into the future that any unsustainable credit
deficits are eliminated. Like analyses published by EPA in 2016,
2017, and early 2018, the $1,800 figure reported in 2012 by EPA did
not reflect either simulation of manufacturers' multiyear plans to
progress from the initial MY 2008 fleet to the MY 2025 fleet or any
accounting for manufacturers' potential application of banked
credits. Today's analysis of both CAFE and CO2 standards
accounts explicitly for multiyear planning and credit banking.
\36\ While EPA did not refer to the reported $1,800 as an
estimate of the increase in average prices, because EPA did not
assume that manufacturers would reduce profit margins, the $1,800
estimate is appropriately interpreted as an estimate of the average
increase in vehicle prices.
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[[Page 42995]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.005
Preferred Alternative
For all of these reasons, the agencies are proposing to maintain
the MY 2020 fuel economy and CO2 emissions standards for MYs
2021-2026. Our goal is to establish standards that promote both energy
conservation and safety, in light of what is technologically feasible
and economically practicable, as directed by Congress.
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\37\ Data on new vehicle prices are from U.S. Bureau of Economic
Analysis, National Income and Product Accounts, Supplemental Table
7.2.5S, Auto and Truck Unit Sales, Production, Inventories,
Expenditures, and Price (https://www.bea.gov/iTable/iTable.cfm?reqid=19&step=2#reqid=19&step=3&isuri=1&1921=underlying&1903=2055, last accessed Jul. 20, 2018). Median Household Income data
are from U.S. Census Bureau, Table A-1, Households by Total Money
Income, Race, and Hispanic Origin of Householder: 1967 to 2016
(https://www.census.gov/data/tables/2017/demo/income-poverty/p60-259.html, last accessed Jul. 20, 2018).
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Energy Conservation
EPCA requires that NHTSA, when determining the maximum feasible
levels of CAFE standards, consider the need of the Nation to conserve
energy. However, EPCA also requires that NHTSA consider other factors,
such as technological feasibility and economic practicability. The
analysis suggests that, compared to the standards issued previously for
MYs 2021-2025, today's proposed rule will eventually (by the early
2030s) increase U.S. petroleum consumption by about 0.5 million barrels
per day--about two to three percent of projected total U.S.
consumption. While significant, this additional petroleum consumption
is, from an economic perspective, dwarfed by the cost savings also
projected to result from today's proposal, as indicated by the
consideration of net benefits appearing below.
Safety Benefits From Preferred Alternative
Today's proposed rule is anticipated to prevent more than 12,700
on-road fatalities \38\ and significantly more injuries as compared to
the standards set forth in the 2012 final rule over the lifetimes of
vehicles as more new, safer vehicles are purchased than the current
(and augural) standards. A large portion of these safety benefits will
come from improved fleet turnover as more consumers will be able to
afford newer and safer vehicles.
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\38\ Over the lifetime of vehicles through MY 2029.
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Recent NHTSA analysis shows that the proportion of passengers
killed in a vehicle 18 or more model years old is nearly double that of
a vehicle three model years old or newer.\39\ As the average car on the
road is approaching 12 years old, apparently the oldest in our
history,\40\ major safety benefits will occur by reducing fleet age.
Other safety benefits will occur from other areas such as avoiding the
increased driving
[[Page 42996]]
that would otherwise result from higher fuel efficiency (known as the
rebound effect) and avoiding the mass reductions in passenger cars that
might otherwise be required to meet the standards established in
2012.\41\ Together these and other factors lead to estimated annual
fatalities under the proposed standards that are significantly reduced
\42\ relative to those that would occur under current (and augural)
standards.
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\39\ Passenger Vehicle Occupant Injury Severity by Vehicle Age
and Model Year in Fatal Crashes, Traffic Safety Facts Research Note,
DOT HS 812 528. Washington, DC: National Highway Traffic Safety
Administration. April 2018.
\40\ See, e.g., IHS Markit, Vehicles Getting Older: Average Age
of Light Cars and Trucks in U.S. Rises Again in 2016 to 11.5 years,
IHS Markit Says, IHS Markit (Nov. 22, 2016), http://news.ihsmarkit.com/press-release/automotive/vehicles-getting-older-average-age-light-cars-and-trucks-us-rises-again-201 (``. . .
consumers are continuing the trend of holding onto their vehicles
longer than ever. As of the end of 2015, the average length of
ownership measured a record 79.3 months, more than 1.5 months longer
than reported in the previous year. For used vehicles, it is nearly
66 months. Both are significantly longer lengths of ownership since
the same measure a decade ago.'').
\41\ The agencies are specifically requesting comment on the
appropriateness and level of the effects of the rebound effect. The
agencies also seek comment on changes as compared to the 2012
modeling relating to mass reduction assumptions. During that
rulemaking, the analysis limited the amount of mass reduction
assumed for certain vehicles, which impacted the results regarding
potential for adverse safety effects, even while acknowledging that
manufacturers would not necessarily choose to avoid mass reductions
in the ways that the agencies assumed. See, 77 FR 623624, 62763
(Oct. 15, 2012). By choosing where and how to limit assumed mass
reduction, the 2012 rule's safety analysis reduced the projected
apparent risk to safety associated with aggressive fuel economy and
CO2 targets. That specific assumption has been removed
for today's analysis.
\42\ The reduction in annual fatalities varies each calendar
year, averaging 894 fewer fatalities annually for the CAFE program
and 1,150 fewer fatalities for the CO2 program over
calendar years 2036-2045.
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The Preferred Alternative Would Have Negligible Environmental Impacts
on Air Quality
Improving fleet turnover will result in consumers getting into
newer and cleaner vehicles, accelerating the rate at which older, more-
polluting vehicles are removed from the roadways. Also, reducing fuel
economy (relative to levels that would occur under previously-issued
standards) would increase the marginal cost of driving newer vehicles,
reducing mileage accumulated by those vehicles, and reducing
corresponding emissions. On the other hand, increasing fuel consumption
would increase emissions resulting from petroleum refining and related
``upstream'' processes. Our analysis shows that none of the regulatory
alternatives considered in this proposal would noticeably impact net
emissions of smog-forming or other ``criteria'' or toxic air
pollutants, as illustrated by the following graph. That said, the
resultant tailpipe emissions reductions should be especially beneficial
to highly trafficked corridors.
[GRAPHIC] [TIFF OMITTED] TP24AU18.006
Climate Change Impacts From Preferred Alternative
The estimated effects of this proposal in terms of fuel savings and
CO2 emissions, again perhaps somewhat counter-intuitively,
is relatively small as compared to the 2012 final rule.\43\ NHTSA's
Environmental Impact Statement performed for this rulemaking shows that
the preferred alternative would result in 3/1,000ths of a degree
Celsius increase in global average temperatures by 2100, relative to
the standards finalized in 2012. On a net CO2 basis, the
results are similarly minimal. The following graph compares the
estimated atmospheric CO2 concentration (789.76 ppm) in 2100
under the proposed standards to the estimated level (789.11 ppm) under
the standards set forth in 2012--or an 8/100ths of a percentage
increase:
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\43\ Counter-intuitiveness is relative, however. The estimated
effects of the 2012 final rule on climate were similarly small in
magnitude, as shown in the Final EIS accompanying that rule and
available on NHTSA's website.
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[[Page 42997]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.007
Net Benefits From Preferred Alternative
Maintaining the MY 2020 curves for MYs 2021-2026 will save American
consumers, the auto industry, and the public a considerable amount of
money as compared to if EPA retained the previously-set CO2
standards and NHTSA finalized the augural standards. This was
identified as the preferred alternative, in part, because it maximizes
net benefits compared to the other alternatives analyzed, recognizing
the statutory considerations for both agencies. Comment is sought on
whether this is an appropriate basis for selection.
[[Page 42998]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.008
These estimates, reported as changes relative to impacts under the
standards issued in 2012, account for impacts on vehicles produced
during model years 2016-2029, as well as (through changes in
utilization) vehicles produced in earlier model years, throughout those
vehicles' useful lives. Reported values are in 2016 dollars, and
reflect three-percent and seven-percent discount rates. Under CAFE
standards, costs are estimated to decrease by $502 billion overall at a
three-percent discount rate ($335 billion at a seven-percent discount
rate); benefits are estimated to decrease by $326 billion at a three-
percent discount rate ($204 billion at a seven-percent discount rate).
Thus, net benefits are estimated to increase by $176 billion at a
three-percent discount rate and $132 billion at a seven-percent
discount rate. The estimated impacts under CO2 standards are
similar, with net benefits estimated to increase by $201 billion at a
three-percent discount rate and $141 billion at a seven-percent
discount rate.
Compliance Flexibilities
This proposal also seeks comment on a variety of changes to NHTSA's
and EPA's compliance programs for CAFE and CO2 as well as
related programs. Compliance flexibilities can generally be grouped
into two categories. The first category are those compliance
flexibilities that reduce unnecessary compliance costs and provide for
a more efficient program. The second category of compliance
flexibilities are those that distort the market--such as by
incentivizing the implementation of one type of technology by providing
credit for compliance in excess of real-world fuel savings.
Both programs provide for the generation of credits based upon
fleet-wide over-compliance, provide for adjustments to the test
measured value of each individual vehicle based upon the implementation
of certain fuel saving technologies, and provide additional incentives
for the implementation of certain preferred technologies (regardless of
actual fuel savings). Auto manufacturers and others have petitioned for
a host of additional adjustment- and incentive-type flexibilities,
where there is not always consumer interest in the technologies to be
incentivized nor is there necessarily clear fuel-saving and emissions-
reducing benefit to be derived from that incentivization. The agencies
seek comment on all of those requests as part of this proposal.
Over-compliance credits, which can be built up in part through use
of the above-described per-vehicle adjustments and incentives, can be
saved and either applied retroactively to accounts for previous non-
compliance, or carried forward to mitigate future non-compliance. Such
credits can also be traded to other automakers for cash or for other
credits for different fleets. But such trading is not pursued openly.
Under the CAFE program, the public is not made aware of inter-automaker
trades, nor are shareholders. And even the agencies are not informed of
the price of credits. With the exception of statutorily-mandated
credits, the agencies seek comment on all aspects of the current
system. The agencies are particularly interested in comments on
flexibilities that may distort the market.
[[Page 42999]]
The agencies seek comment as to whether some adjustments and non-
statutory incentives and other provisions should be eliminated and
stringency levels adjusted accordingly. In general, well-functioning
banking and trading provisions increase market efficiency and reduce
the overall costs of compliance with regulatory objectives. The
agencies request comment on whether the current system as implemented
might need improvements to achieve greater efficiencies. We seek
comment on specific programmatic changes that could improve compliance
with current standards in the most efficient way, ranging from
requiring public disclosure of some or all aspects of credit trades, to
potentially eliminating credit trading in the CAFE program. We request
commenters to provide any data, evidence, or existing literature to
help agency decision-making.
One National Standard
Setting appropriate and maximum feasible fuel economy and tailpipe
CO2 emissions standards requires regulatory efficiency. This
proposal addresses a fundamental and unnecessary complication in the
currently-existing regulatory framework, which is the regulation of GHG
emissions from passenger cars and light trucks by the State of
California through its GHG standards and Zero Emission Vehicle (ZEV)
mandate and subsequent adoption of these standards by other States.
Both EPCA and the CAA preempt State regulation of motor vehicle
emissions (in EPCA's case, standards that are related to fuel economy
standards). The CAA gives EPA the authority to waive preemption for
California under certain circumstances. EPCA does not provide for a
waiver of preemption under any circumstances. In short, the agencies
propose to maintain one national standard--a standard that is set
exclusively by the Federal government.
Proposed Withdrawal of California's Clean Air Act Preemption Waiver
EPA granted a waiver of preemption to California in 2013 for its
``Advanced Clean Car'' regulations, composed of its GHG standards, its
``Low Emission Vehicle (LEV)'' program and the ZEV program,\44\ and, as
allowed under the CAA, a number of other States adopted California's
standards.\45\ The CAA states that EPA shall not grant a waiver of
preemption if EPA finds that California's determination that its
standards are, in the aggregate, at least as protective of public
health and welfare as applicable Federal standards, is arbitrary and
capricious; that California does not need its own standards to meet
compelling or extraordinary conditions; or that such California
standards and accompanying enforcement procedures are not consistent
with Section 202(a) of the CAA. In this proposal, EPA is proposing to
withdraw the waiver granted to California in 2013 for the GHG and ZEV
requirements of its Advanced Clean Cars program, in light of all of
these factors.
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\44\ 78 FR 2112 (Jan. 9, 2013).
\45\ CAA Section 177, 42 U.S.C. 7507.
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Attempting to solve climate change, even in part, through the
Section 209 waiver provision is fundamentally different from that
section's original purpose of addressing smog-related air quality
problems. When California was merely trying to solve its air quality
issues, there was a relatively-straightforward technology solution to
the problems, implementation of which did not affect how consumers
lived and drove. Section 209 allowed California to pursue additional
reductions to address its notorious smog problems by requiring more
stringent standards, and allowed California and other States that
failed to comply with Federal air quality standards to make progress
toward compliance. Trying to reduce carbon emissions from motor
vehicles in any significant way involves changes to the entire vehicle,
not simply the addition of a single or a handful of control
technologies. The greater the emissions reductions are sought, the
greater the likelihood that the characteristics and capabilities of the
vehicle currently sought by most American consumers will have to change
significantly. Yet, even decades later, California continues to be in
widespread non-attainment with Federal air quality standards.\46\ In
the past decade, California has disproportionately focused on GHG
emissions. Parts of California have a real and significant local air
pollution problem, but CO2 is not part of that local
problem.
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\46\ See California Nonattainment/Maintenance Status for Each
County by Year for All Criteria Pollutants, current as of May 31,
2018, at https://www3.epa.gov/airquality/greenbook/anayo_ca.html
(last accessed June 15, 2018).
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California's Tailpipe CO2 Emissions Standards and ZEV
Mandate Conflict With EPCA
Moreover, California regulation of tailpipe CO2
emissions, both through its GHG standards and ZEV program, conflicts
directly and indirectly with EPCA and the CAFE program. EPCA expressly
preempts State standards related to fuel economy. Tailpipe
CO2 standards, whether in the form of fleet-wide
CO2 limits or in the form of requirements that manufacturers
selling vehicles in California sell a certain number of low- and no-
tailpipe-CO2 emissions vehicles as part of their overall
sales, are unquestionably related to fuel economy standards. Standards
that control tailpipe CO2 emissions are de facto fuel
economy standards because CO2 is a direct and inevitable
byproduct of the combustion of carbon-based fuels to make energy, and
the vast majority of the energy that powers passenger cars and light
trucks comes from carbon-based fuels.
Improving fuel economy means getting the vehicle to go farther on a
gallon of gas; a vehicle that goes farther on a gallon of gas produces
less CO2 per unit of distance; therefore, improving fuel
economy necessarily reduces tailpipe CO2 emissions, and
reducing CO2 emissions necessarily improves fuel economy.
EPCA therefore necessarily preempts California's Advanced Clean Cars
program to the extent that it regulates or prohibits tailpipe
CO2 emissions. Section VI of this proposal, below, discusses
the CAA waiver and EPCA preemption in more detail.
Eliminating California's regulation of fuel economy pursuant to
Congressional direction will provide benefits to the American public.
The automotive industry will, appropriately, deal with fuel economy
standards on a national basis--eliminating duplicative regulatory
requirements. Further, elimination of California's ZEV program will
allow automakers to develop such vehicles in response to consumer
demand instead of regulatory mandate. This regulatory mandate has
required automakers to spend tens of billions of dollars to develop
products that a significant majority of consumers have not adopted, and
consequently to sell such products at a loss. All of this is paid for
through cross subsidization by increasing prices of other vehicles not
just in California and other States that have adopted California's ZEV
mandate, but throughout the country.
Request for Comment
The agencies look forward to all comments on this proposal, and
wish to emphasize that obtaining public input is extremely important to
us in selecting from among the alternatives in a final rule. While the
agencies and the Administration met with a variety of stakeholders
prior to issuance of this proposal, those meetings have not resulted in
a predetermined final rule outcome. The Administrative Procedure Act
requires that agencies provide the
[[Page 43000]]
public with adequate notice of a proposed rule followed by a meaningful
opportunity to comment on the rule's content. The agencies are
committed to following that directive.
II. Technical Foundation for NPRM Analysis
A. Basics of CAFE and CO2 Standards Analysis
The agencies' analysis of CAFE and CO2 standards
involves two basic elements: first, estimating ways each manufacturer
could potentially respond to a given set of standards in a manner that
considers potential consumer response; and second, estimating various
impacts of those responses. Estimating manufacturers' potential
responses involves simulating manufacturers' decision-making processes
regarding the year-by-year application of fuel-saving technologies to
specific vehicles. Estimating impacts involves calculating resultant
changes in new vehicle costs, estimating a variety of costs (e.g., for
fuel) and effects (e.g., CO2 emissions from fuel combustion)
occurring as vehicles are driven over their lifetimes before eventually
being scrapped, and estimating the monetary value of these effects.
Estimating impacts also involves consideration of the response of
consumers--e.g., whether consumers will purchase the vehicles and in
what quantities. Both of these basic analytical elements involve the
application of many analytical inputs.
The agencies' analysis uses the CAFE model to estimate
manufacturers' potential responses to new CAFE and CO2
standards and to estimate various impacts of those responses. The model
makes use of many inputs, values of which are developed outside of the
model and not by the model. For example, the model applies fuel prices;
it does not estimate fuel prices. The model does not determine the form
or stringency of the standards; instead, the model applies inputs
specifying the form and stringency of standards to be analyzed and
produces outputs showing effects of manufacturers working to meet those
standards, which become the basis for comparing between different
potential stringencies.
DOT's Volpe National Transportation Systems Center (often simply
referred to as the ``Volpe Center'') develops, maintains, and applies
the model for NHTSA. NHTSA has used the CAFE model to perform analyses
supporting every CAFE rulemaking since 2001, and the 2016 rulemaking
regarding heavy-duty pickup and van fuel consumption and GHG emissions
also used the CAFE model for analysis.\47\
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\47\ While this rulemaking employed the CAFE model for analysis,
EPA and DOT used different versions of the CAFE model for
establishing their respective standards, and EPA also used the EPA
MOVES model. See 81 FR 73478, 73743 (Oct. 25, 2016).
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DOT recently arranged for a formal peer review of the model. In
general, reviewers' comments strongly supported the model's conceptual
basis and implementation, and commenters provided several specific
recommendations. DOT staff agreed with many of these recommendations
and have worked to implement them wherever practicable. Implementing
some of them would require considerable further research, development,
and testing, and will be considered going forward. For a handful of
other recommendations, DOT staff disagreed, often finding the
recommendations involved considerations (e.g., other policies, such as
those involving fuel taxation) beyond the model itself or were based on
concerns with inputs rather than how the model itself functioned. A
report available in the docket for this rulemaking presents peer
reviewers' detailed comments and recommendations, and provides DOT's
detailed responses.\48\
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\48\ Docket No. NHTSA-2018-0067.
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The agencies also use four DOE and DOE-sponsored models to develop
inputs to the CAFE model, including three developed and maintained by
DOE's Argonne National Laboratory. The agencies use the DOE Energy
Information Administration's (EIA's) National Energy Modeling System
(NEMS) to estimate fuel prices,\49\ and used Argonne's Greenhouse
gases, Regulated Emissions, and Energy use in Transportation (GREET)
model to estimate emissions rates from fuel production and distribution
processes.\50\ DOT also sponsored DOE/Argonne to use their Autonomie
full-vehicle simulation system to estimate the fuel economy impacts for
roughly a million combinations of technologies and vehicle types.\51\
\52\
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\49\ See https://www.eia.gov/outlooks/aeo/info_nems_archive.php.
Today's notice uses fuel prices estimated using the Annual Energy
Outlook (AEO) 2017 version of NEMS (see https://www.eia.gov/outlooks/archive/aeo17/ and https://www.eia.gov/outlooks/aeo/data/browser/#/?id=3-AEO2017&cases=ref2017&sourcekey=0).
\50\ Information regarding GREET is available at https://greet.es.anl.gov/index.php. Availability of NEMS is discussed at
https://www.eia.gov/outlooks/aeo/info_nems_archive.php. Today's
notice uses fuel prices estimated using the AEO 2017 version of
NEMS.
\51\ As part of the Argonne simulation effort, individual
technology combinations simulated in Autonomie were paired with
Argonne's BatPAC model to estimate the battery cost associated with
each technology combination based on characteristics of the
simulated vehicle and its level of electrification. Information
regarding Argonne's BatPAC model is available at http://www.cse.anl.gov/batpac/.
\52\ Additionally, the impact of engine technologies on fuel
consumption, torque, and other metrics was characterized using GT
POWER simulation modeling in combination with other engine modeling
that was conducted by IAV Automotive Engineering, Inc. (IAV). The
engine characterization ``maps'' resulting from this analysis were
used as inputs for the Autonomie full-vehicle simulation modeling.
Information regarding GT Power is available at https://www.gtisoft.com/gt-suite-applications/propulsion-systems/gt-power-engine-simulation-software.
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EPA developed two models after 2009, referred to as the ``ALPHA''
and ``OMEGA'' models, which provide some of the same capabilities as
the Autonomie and CAFE models. EPA applied the OMEGA model to conduct
analysis of GHG standards promulgated in 2010 and 2012, and the ALPHA
and OMEGA models to conduct analysis discussed in the above-mentioned
2016 Draft TAR and Proposed and Final Determinations regarding
standards beyond 2021. In an August 2017 notice, the agencies requested
comments on, among other things, whether EPA should use alternative
methodologies and modeling, including DOE/Argonne's Autonomie full-
vehicle simulation tool and DOT's CAFE model.\53\
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\53\ 82 FR 39533 (Aug. 21, 2017).
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Having reviewed comments on the subject and having considered the
matter fully, the agencies have determined it is reasonable and
appropriate to use DOE/Argonne's model for full-vehicle simulation, and
to use DOT's CAFE model for analysis of regulatory alternatives. EPA
interprets Section 202(a) of the CAA as giving the agency broad
discretion in how it develops and sets GHG standards for light-duty
vehicles. Nothing in Section 202(a) mandates that EPA use any specific
model or set of models for analysis of potential CO2
standards for light-duty vehicles. EPA weighs many factors when
determining appropriate levels for CO2 standards, including
the cost of compliance (see Section 202(a)(2)), lead time necessary for
compliance (also Section 202(a)(2)), safety (see NRDC v. EPA, 655 F.2d
318, 336 n. 31 (D.C. Cir. 1981) and other impacts on consumers,\54\ and
energy impacts associated with use of the technology.\55\ Using the
CAFE model
[[Page 43001]]
allows consideration of the following factors: the CAFE model
explicitly evaluates the cost of compliance for each manufacturer, each
fleet, and each model year; it accounts for lead time necessary for
compliance by directly incorporating estimated manufacturer production
cycles for every vehicle in the fleet, ensuring that the analysis does
not assume vehicles can be redesigned to incorporate more technology
without regard to lead time considerations; it provides information on
safety effects associated with different levels of standards and
information about many other impacts on consumers, and it calculates
energy impacts (i.e., fuel saved or consumed) as a primary function,
besides being capable of providing information about many other factors
within EPA's broad CAA discretion to consider.
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\54\ Since its earliest Title II regulations, EPA has considered
the safety of pollution control technologies. See 45 FR 14496, 14503
(1980).
\55\ See George E. Warren Corp. v. EPA, 159 F.3d 616, 623-624
(D.C. Cir. 1998) (ordinarily permissible for EPA to consider factors
not specifically enumerated in the Act).
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Because the CAFE model simulates a wide range of actual constraints
and practices related to automotive engineering, planning, and
production, such as common vehicle platforms, sharing of engines among
different vehicle models, and timing of major vehicle redesigns, the
analysis produced by the CAFE model provides a transparent and
realistic basis to show pathways manufacturers could follow over time
in applying new technologies, which helps better assess impacts of
potential future standards. Furthermore, because the CAFE model also
accounts fully for regulatory compliance provisions (now including
CO2 compliance provisions), such as adjustments for reduced
refrigerant leakage, production ``multipliers'' for some specific types
of vehicles (e.g., PHEVs), and carried-forward (i.e., banked) credits,
the CAFE model provides a transparent and realistic basis to estimate
how such technologies might be applied over time in response to CAFE or
CO2 standards.
There are sound reasons for the agencies to use the CAFE model
going forward in this rulemaking. First, the CAFE and CO2
fact analyses are inextricably linked. Furthermore, the analysis
produced by the CAFE model and DOE/Argonne's Autonomie addresses
several analytical needs. The CAFE model provides an explicit year-by-
year simulation of manufacturers' application of technology to their
products in response to a year-by-year progression of CAFE standards
and accounts for sharing of technologies and the implications for
timing, scope, and limits on the potential to optimize powertrains for
fuel economy. In the real world, standards actually are specified on a
year-by-year basis, not simply some single year well into the future,
and manufacturers' year-by-year plans involve some vehicles ``carrying
forward'' technology from prior model years and some other vehicles
possibly applying ``extra'' technology in anticipation of standards in
ensuing model years, and manufacturers' planning also involves applying
credits carried forward between model years. Furthermore, manufacturers
cannot optimize the powertrain for fuel economy on every vehicle model
configuration--for example, a given engine shared among multiple
vehicle models cannot practicably be split into different versions for
each configuration of each model, each with a slightly different
displacement. The CAFE model is designed to account for these real-
world factors.
Considering the technological heterogeneity of manufacturers'
current product offerings, and the wide range of ways in which the many
fuel economy-improving/CO2 emissions-reducing technologies
included in the analysis can be combined, the CAFE model has been
designed to use inputs that provide an estimate of the fuel economy
achieved for many tens of thousands of different potential combinations
of fuel-saving technologies. Across the range of technology classes
encompassed by the analysis fleet, today's analysis involves more than
a million such estimates. While the CAFE model requires no specific
approach to developing these inputs, the National Academy of Sciences
(NAS) has recommended, and stakeholders have commented, that full-
vehicle simulation provides the best balance between realism and
practicality. DOE/Argonne has spent several years developing, applying,
and expanding means to use distributed computing to exercise its
Autonomie full-vehicle simulation tool over the scale necessary for
realistic analysis of CAFE or average CO2 standards. This
scalability and related flexibility (in terms of expanding the set of
technologies to be simulated) makes Autonomie well-suited for
developing inputs to the CAFE model.
Additionally, DOE/Argonne's Autonomie also has a long history of
development and widespread application by a much wider range of users
in government, academia, and industry. Many of these users apply
Autonomie to inform funding and design decisions. These real-world
exercises have contributed significantly to aspects of Autonomie
important to producing realistic estimates of fuel economy levels and
CO2 emission rates, such as estimation and consideration of
performance, utility, and driveability metrics (e.g., towing
capability, shift business, frequency of engine on/off transitions).
This steadily increasing realism has, in turn, steadily increased
confidence in the appropriateness of using Autonomie to make
significant investment decisions. Notably, DOE uses Autonomie for
analysis supporting budget priorities and plans for programs managed by
its Vehicle Technologies Office (VTO). Considering the advantages of
DOE/Argonne's Autonomie model, it is reasonable and appropriate to use
Autonomie to estimate fuel economy levels and CO2 emission
rates for different combinations of technologies as applied to
different types of vehicles.
Commenters have also suggested that the CAFE model's graphical user
interface (GUI) facilitates others' ability to use the model quickly--
and without specialized knowledge or training--and to comment
accordingly.\56\ For today's proposal, DOT has significantly expanded
and refined this GUI, providing the ability to observe the model's
real-time progress much more closely as it simulates year-by-year
compliance with either CAFE or CO2 standards.\57\ Although
the model's ability to produce realistic results is independent of the
model's GUI, it is anticipated the CAFE model's GUI will facilitate
stakeholders' meaningful review and comment during the comment period.
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\56\ From Docket Number EPA-HQ-OAR-2015-0827, see Comment by
Global Automakers, Docket ID EPA-HQ-OAR-2015-0827-9728, at 34.
\57\ The updated GUI provides a range of graphs updated in real
time as the model operates. These graphs can be used to monitor fuel
economy or CO2 ratings of vehicles in manufacturers'
fleets and to monitor year-by-year CAFE (or average CO2
ratings), costs, avoided fuel outlays, and avoided CO2-
related damages for specific manufacturers and/or specific fleets
(e.g., domestic passenger car, light truck). Because these graphs
update as the model progresses, they should greatly increase users'
understanding of the model's approach to considerations such as
multiyear planning, payment of civil penalties, and credit use.
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Beyond these general considerations, several specific related
technical comments and considerations underlie the agencies' decision
in this area, as discussed, where applicable, in the remainder of this
Section.
Other commenters expressed a number of concerns with whether DOT's
CAFE model could be used for CAA analysis. Many of these concerns
focused on inputs used by the CAFE model for prior rulemaking
analyses.\58\ \59\ \60\ Because inputs are
[[Page 43002]]
exogenous to any model, they do not determine whether it would be
reasonable and appropriate for EPA to use DOT's model for analysis.
Other concerns focused on characteristics of the CAFE model that were
developed to better align the model with EPCA and EISA; the model has
been revised to accommodate both EPCA/EISA and CAA analysis, as
explained further below. Some commenters also argued that use of any
models other than ALPHA and OMEGA for CAA analysis would constitute an
arbitrary and capricious delegation of EPA's decision-making authority
to DOT, if DOT models are used for analysis instead. These comments
were made prior to the development of the CAA analysis function in the
CAFE model, and, moreover, appear to conflate the analytical tool used
to inform decision-making with the action of making the decision. As
explained elsewhere in this document and as made repeatedly clear over
the past several rulemakings, the CAFE model neither sets standards nor
dictates where and how to set standards; it simply informs as to the
effects of setting different levels of standards. In this rulemaking,
EPA will be making its own decisions regarding what CO2
standards would be appropriate under the CAA. The CAA does not require
EPA to create a specific model or use a specific model of its own
creation in setting GHG standards. The fact EPA's decision may be
informed by non-EPA-created models does not, in any way, constitute a
delegation of its statutory power to set standards or decision-making
authority.\61\ Arguing to the contrary would suggest, for example, that
EPA's decision would be invalid because it relied on EIA's Annual
Energy Outlook for fuel prices rather than developing its own model for
estimating future trends in fuel prices. Yet, all Federal agencies that
have occasion to use forecasts of future fuel prices regularly (and
appropriately) defer to EIA's expertise in this area and rely on EIA's
NEMS-based analysis in the AEO, even when those same agencies are using
EIA's forecasts to inform their own decision-making.
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\58\ For example, EDF's recent comments (EDF at 12, Docket ID.
EPA-HQ-OAR-2015-0827-9203) stated ``the data that NHTSA needs to
input into its model is sensitive confidential business information
that is not transparent and cannot be independently verified . . .''
and claimed ``the OMEGA model's focus on direct technological inputs
and costs--as opposed to industry self-reported data--ensures the
model more accurately characterizes the true feasibility and cost
effectiveness of deploying greenhouse gas reducing technologies.''
Neither statement is correct, as nothing about either the CAFE or
OMEGA model either obviates or necessitates the use of CBI to
develop inputs.
\59\ In recent comments (CARB at 28, Docket ID. EPA-HQ-OAR-2015-
0827-9197), CARB stated ``another promising technology entering the
market was not even included in the NHTSA compliance modeling'' and
that EPA assumes a five-year redesign cycle, whereas NHTSA assumes a
six to seven-year cycle.'' Though presented as criticisms of the
models, these comments--at least with respect to the CAFE model--
actually concern model inputs. NHTSA did not agree with CARB about
the commercialization potential of the engine technology in question
(``Atkinson 2'') and applied model inputs accordingly. Also, rather
than applying a one-size-fits-all assumption regarding redesign
cadence, NHTSA developed estimates specific to each vehicle model
and applied these as model inputs.
\60\ NRDC's recent comments (NRDC at 37, Docket ID. EPA-HQ-OAR-
2015-0827-9826) state EPA should not use the CAFE model because it
``allows manufacturers to pay civil penalties in lieu of meeting the
standards, an alternative compliance pathway currently allowed under
EISA and EPCA.'' While the CAFE model can simulate civil penalty
payment, NRDC's comment appears to overlook the fact that this
result depends on model inputs; the inputs can easily be specified
such that the CAFE model will set aside civil penalty payment as an
alternative to compliance.
\61\ ``[A] federal agency may turn to an outside entity for
advice and policy recommendations, provided the agency makes the
final decisions itself.'' U.S. Telecom. Ass'n v. FCC, 359 F.3d 554,
565-66 (D.C. Cir. 2004). To the extent commenters meant to suggest
outside parties have a reliance interest in EPA using ALPHA and
OMEGA to set standards, EPA does not agree a reliance interest is
properly placed on an analytical methodology (as opposed to on the
standards themselves). Even if it were, all parties that closely
examined ALPHA and OMEGA-based analyses in the past either also
simultaneously closely examined CAFE and Autonomie-based analyses in
the past, or were fully capable of doing so, and thus, should face
no additional difficulty now they have only one set of models and
inputs/outputs to examine.
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Moreover, DOT's CAFE model with inputs from DOE/Argonne's Autonomie
model has produced analysis supporting rulemaking under the CAA. In
2015, EPA proposed new GHG standards for MY 2021-2027 heavy-duty
pickups and vans, finalizing standards in 2016. Supporting the NPRM and
final rule, EPA relied on analysis implemented by DOT using DOT's CAFE
model, and DOT used inputs developed by DOE/Argonne using DOE/Argonne's
Autonomie model.
The following sections provide a brief technical overview of the
CAFE model, including changes NHTSA made to the model since 2012,
before discussing inputs to the model and then diving more deeply into
how the model works. For more information on the latter topic, see the
CAFE model documentation July 2018 draft, available in the docket for
this rulemaking and on NHTSA's website.
1. Brief Technical Overview of the Model
The CAFE model is designed to simulate compliance with a given set
of CAFE or CO2 standards for each manufacturer selling
vehicles in the United States. The model begins with a representation
of the current (for today's analysis, model year 2016) vehicle model
offerings for each manufacturer that includes the specific engines and
transmissions on each model variant, observed sales volumes, and all
fuel economy improvement technology that is already present on those
vehicles. From there it adds technology, in response to the standards
being considered, in a way that minimizes the cost of compliance and
reflects many real-world constraints faced by automobile manufacturers.
After simulating compliance, the model calculates impacts of the
simulated standard: technology costs, fuel savings (both in gallons and
dollars), CO2 reductions, social costs and benefits, and
safety impacts.
Today's analysis reflects several changes made to the CAFE model
since 2012, when NHTSA used the model to estimate the effects, costs,
and benefits of final CAFE standards for light-duty vehicles produced
during MYs 2017-2021 and augural standards for MYs 2022-2025. Key
changes relevant to this analysis include the following:
Expansion of model inputs, procedures, and outputs to
accommodate technologies not included in prior analyses,
Updated approach to estimating the combined effect of
fuel-saving technologies using large scale simulation modeling,
Modules that dynamically estimate new vehicle sales and
existing vehicle scrappage in response to changes to new vehicle prices
that result from manufacturers' compliance actions,
A safety module that estimates the changes in light-duty
traffic fatalities resulting from changes to vehicle exposure, vehicle
retirement rates, and reductions in vehicle mass to improve fuel
economy,
Disaggregation of each manufacturer's fleet into separate
``domestic'' passenger car and ``import'' passenger car fleets to
better represent the statutory requirements of the CAFE program,
Changes to the algorithm used to apply technologies,
enabling more explicit accounting of shared vehicle components
(engines, transmissions, platforms) and ``inheritance'' of major
technology within or across powertrains and/or platforms over time,
An industry labor quantity module, which estimates net
changes in the amount of U.S. automobile labor for dealerships, Tier 1
and 2 supplier companies, and original equipment manufacturers (OEMs),
Cost estimation of batteries for electrification
technologies incorporates an updated version of Argonne National
Laboratory's BatPAC (battery) model for hybrid electric vehicles
(HEVs), plug-in
[[Page 43003]]
hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs),
consistent with how we estimate effectiveness for those values,
Expanded accounting for CAFE credits carried over from
years prior to those included in the analysis (a.k.a. ``banked''
credits) and application to future CAFE deficits to better evaluate
anticipated manufacturer responses to proposed standards,\62\
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\62\ While EPCA/EISA precludes NHTSA from considering
manufacturers' potential use of credits in model years for which the
agency is establishing new standards, NHTSA considers credit use in
earlier model years. Also, as allowed by NEPA, NHTSA's EISs present
results of analysis that considers manufacturers' potential use of
credits in all model years, including those for which the agency is
establishing new standards.
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The ability to represent a manufacturer's preference for
fine payment (rather than achieving full compliance exclusively through
fuel economy improvements) on a year-by-year basis,
Year-by-year simulation of how manufacturers could comply
with EPA's CO2 standards, including
[cir] Calculation of vehicle models' CO2 emission rates
before and after application of fuel-saving (and, therefore,
CO2-reducing) technologies,
[cir] Calculation of manufacturers' fleet average CO2
emission rates,
[cir] Calculation of manufacturers' fleet average CO2
emission rates under attribute-based CO2 standards,
[cir] Accounting for adjustments to average CO2 emission
rates reflecting reduction of air conditioner refrigerant leakage,
[cir] Accounting for the treatment of alternative fuel vehicles for
CO2 compliance,
[cir] Accounting for production ``multipliers'' for PHEVs, BEVs,
compressed natural gas (CNG) vehicles, and fuel cell vehicles (FCVs),
[cir] Accounting for transfer of CO2 credits between
regulated fleets,
[cir] Accounting for carried-forward (a.k.a. ``banked'')
CO2 credits, including credits from model years earlier than
modeled explicitly.
2. Sensitivity Cases and Why We Examine Them
Today's notice presents estimated impacts of the proposed CAFE and
CO2 standards defining the proposals, relative to a baseline
``no action'' regulatory alternative under which the standards
announced in 2012 remain in place through MY 2025 and continue
unchanged thereafter. Relative to this same baseline, today's notice
also presents analysis estimating impacts under a range of other
regulatory alternatives the agencies are considering. All but one
involve different standards, and three involve a gradual
discontinuation of CAFE and GHG adjustments reflecting the application
of technologies that improve air conditioner efficiency or, in other
ways, improve fuel economy under conditions not represented by long-
standing fuel economy test procedures. Like the baseline no action
alternative, all of these alternatives are more stringent than the
preferred alternative. Section III and Section IV describe the
preferred and other regulatory alternatives, respectively.
These alternatives were examined because they will be considered as
options for the final rule. The agencies seek comment on these
alternatives, seek any relevant data and information, and will review
responses. That review could lead to the selection of one of the other
regulatory alternatives for the final rule or some combination of the
other regulatory alternatives (e.g., combining passenger cars standards
from one alternative with light truck standards from a different
alternative).
Because outputs depend on inputs (e.g., the results of the analysis
in terms of quantities and kinds of technologies required to meet
different levels of standards, and the societal and private benefits
associated with manufacturers meeting different levels of standards
depend on input data, estimates, and assumptions), the analysis also
explores the sensitivity of results to many of these inputs. For
example, the net benefits of any regulatory alternative will depend
strongly on fuel prices well beyond 2025. Fuel prices a decade and more
from now are not knowable with certainty. The sensitivity analysis
involves repeating the ``central'' or ``reference case'' analysis under
alternative inputs (e.g., higher fuel prices in one case, lower fuel
prices in another case), and exploring changes in analytical results,
which is discussed further in the agencies' Preliminary Regulatory
Impact Analysis (PRIA) accompanying today's notice.
B. Developing the Analysis Fleet for Assessing Costs, Benefits, and
Effects of Alternative CAFE Standards
The following sections describe what the analysis fleet is and why
it is used, how it was developed for this NPRM, and the analysis-fleet-
related topics on which comment is sought.
1. Purpose of Developing and Using an Analysis Fleet
The starting point for the evaluation of the potential feasibility
of different stringency levels for future CAFE and CO2
standards is the analysis fleet, which is a snapshot of the recent
vehicle market. The analysis fleet provides a snapshot to project what
vehicles will exist in future model years covered by the standards and
what technologies they will have, and then evaluate what additional
technologies can feasibly be applied to those vehicles in a cost-
effective way to raise their fuel economy and lower their
CO2 emission levels.\63\
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\63\ The CAFE model does not generate compliance paths a
manufacturer should, must, or will deploy. It is intended as a tool
to demonstrate a compliance pathway a manufacturer could choose. It
is almost certain all manufacturers will make compliance choices
differing from those projected in the CAFE model.
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Part of reflecting what vehicles will exist in future model years
is knowing which vehicles are produced by which manufacturers, how many
of each are sold, and whether they are passenger cars or light trucks.
This is important because it improves our understanding of the overall
impacts of different levels of CAFE and CO2 standards;
overall impacts result from industry's response to standards, and
industry's response is made up of individual manufacturer responses to
the standards in light of the overall market and their individual
assessment of consumer acceptance. Having an accurate picture of
manufacturers' existing fleets (and the vehicle models in them) that
will be subject to future standards helps us better understand
individual manufacturer responses to those future standards in addition
to potential changes in those standards.
Another part of reflecting what vehicles will exist in future model
years is knowing what technologies are already on those vehicles.
Accounting for technologies already being on vehicles helps avoid
``double-counting'' the value of those technologies, by assuming they
are still available to be applied to improve fuel economy and reduce
CO2 emissions. It also promotes more realistic
determinations of what additional technologies can feasibly be applied
to those vehicles: if a manufacturer has already started down a
technological path to fuel economy or performance improvements, we do
not assume it will completely abandon that path because that would be
unrealistic and would not accurately represent manufacturer responses
to standards. Each vehicle model (and configurations of each model) in
the analysis fleet, therefore, has a comprehensive list of its
technologies, which is important because different configurations may
have different technologies applied to
[[Page 43004]]
them.\64\ Additionally, the analysis accounts for platforms within
manufacturers' fleets, recognizing platforms will share technologies,
and the vehicles that make up that platform should receive (or not
receive) additional technological improvements together. The specific
engineering characteristics of each model/configuration are available
in the aforementioned input file.\65\ For the regulatory alternatives
considered in today's proposal, estimates of rates at which various
technologies might be expected to penetrate manufacturers' fleets (and
the overall market) are summarized below in Sections VI and VII, and in
Chapter 6 of the accompanying PRIA and in detailed model output files
available at NHTSA's website. A solid characterization of a recent
model year as an analytical starting point helps to realistically
estimate ways manufacturers could potentially respond to different
levels of standards, and the modeling strives to realistically simulate
how manufacturers could progress from that starting point.
Nevertheless, manufacturers can respond in many ways beyond those
represented in the analysis (e.g., applying other technologies,
shifting production volumes, changing vehicle footprint), such that it
is impossible to predict with any certainty exactly how each
manufacturer will respond. Therefore, recent trends in manufacturer
performance and technology application, although of interest in terms
of understanding manufacturers' current compliance positions, are not
in themselves innately indicative of future potential.
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\64\ Considering each vehicle model/configuration also improves
the ability to consider the differential impacts of different levels
of potential standards on different manufacturers, since all vehicle
model/configurations ``start'' at different places, in terms of the
technologies they already have and how those technologies are used.
\65\ Available with the model and other input files supporting
today's announcement at https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system.
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Yet, another part of reflecting what vehicles will exist in future
model years is having reasonable real-world assumptions about when
certain technologies can be applied to vehicles. Each vehicle model/
configuration in the analysis fleet also has information about its
redesign schedule, i.e., the last year it was redesigned and when the
agencies expect it to be redesigned again. Redesign schedules are a key
part of manufacturers' business plans, as each new product can cost
more than $1.0B and involve a significant portion of a manufacturer's
scarce research, development, and manufacturing and equipment budgets
and resources.\66\ Manufacturers have repeatedly told the agencies that
sustainable business plans require careful management of resources and
capital spending, and that the length of time each product remains in
production is crucial to recouping the upfront product development and
plant/equipment costs, as well as the capital needed to fund the
development and manufacturing equipment needed for future products.
Because the production volume of any given vehicle model varies within
a manufacturer's product line and also varies among different
manufacturers, redesign schedules typically vary for each model and
manufacturer. Some (relatively few) technological improvements are
small enough they can be applied in any model year; others are major
enough they can only be cost-effectively applied at a vehicle redesign,
when many other things about the vehicle are already changing. Ensuring
the CAFE model makes technological improvements to vehicles only when
it is feasible to do so also helps the analysis better represent
manufacturer responses to different levels of standards.
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\66\ Shea, T. Why Does It Cost So Much For Automakers To Develop
New Models?, Autoblog (Jul. 27, 2010), https://www.autoblog.com/2010/07/27/why-does-it-cost-so-much-for-automakers-to-develop-new-models/.
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A final important aspect of reflecting what vehicles will exist in
future model years and potential manufacturer responses to standards is
estimating how future sales might change in response to different
potential standards. If potential future standards appear likely to
have major effects in terms of shifting production from cars to trucks
(or vice versa), or in terms of shifting sales between manufacturers or
groups of manufacturers, that is important for the agencies to
consider. For previous analyses, the CAFE model used a static forecast
contained in the analysis fleet input file, which specified changes in
production volumes over time for each vehicle model/configuration. This
approach yielded results that, in terms of production volumes, did not
change between scenarios or with changes in important model inputs. For
example, very stringent standards with very high technology costs would
result in the same estimated production volumes as less stringent
standards with very low technology costs.
New for today's proposal, the CAFE model begins with the first-year
production volumes (i.e., MY 2016 for today's analysis) and adjusts
ensuing sales mix year by year (between cars and trucks, and between
manufacturers) endogenously as part of the analysis, rather than using
external forecasts of future car/truck split and future manufacturer
sales volumes. This leads the model to produce different estimates of
future production volumes under different standards and in response to
different inputs, reflecting the expectation that regulatory standards
and other external factors will, in fact, impact the market.
The input file for the CAFE model characterizing the analysis fleet
\67\ includes a large amount of data about vehicle models/
configurations, their technological characteristics, the manufacturers
and fleets to which they belong, and initial prices and production
volumes which provide the starting points for projection (by the sales
model) to ensuing model years. The following sections discuss aspects
of how the analysis fleet was built for this proposal and seek comment
on those topics.
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\67\ Available with the model and other input files supporting
today's announcement at https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system.
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2. Source Data for Building the Analysis Fleet
The source data for the vehicle models/configurations in the
analysis fleet and their technologies is a central input for the
analysis. The sections below discuss pros and cons of different
potential sources and what was used for this proposal.
(a) Use of Confidential Business Information Versus Publicly-Releasable
Sources
Since 2001, CAFE analysis has used either confidential, forward-
estimating product plans from manufacturers, or publicly available data
on vehicles already sold, as a starting point for determining what
technologies can be applied to what vehicles in response to potential
different levels of standards. These two sources present a tradeoff.
Confidential product plans comprehensively represent what vehicles a
manufacturer expects to produce in coming years, accounting for plans
to introduce new vehicles and fuel-saving technologies and, for
example, plans to discontinue other vehicles and even brands. This
information can be very thorough and can improve the accuracy of the
analysis, but for competitive reasons, most of this information must be
redacted prior to publication with rulemaking documentation. This makes
it difficult for public commenters to reproduce the analysis for
themselves as
[[Page 43005]]
they develop their comments. Some non-industry commenters have also
expressed concern manufacturers would have an incentive in the
submitted plans to (deliberately or not) underestimate their future
fuel economy capabilities and overstate their expectations about, for
example, the levels of performance of future vehicle models in order to
affect the analysis. Since 2010, EPA and NHTSA have based analysis
fleets almost exclusively on information from commercial and public
sources, starting with CAFE compliance data and adding information from
other sources.
An analysis fleet based primarily on public sources can be released
to the public, solving the issue of commenters being unable to
reproduce the overall analysis when they want to. However, industry
commenters have argued such an analysis fleet cannot accurately reflect
manufacturers actual plans to apply fuel-saving technologies (e.g.,
manufacturers may apply turbocharging to improve not just fuel economy,
but also to improve vehicle performance) or manufacturers' plans to
change product offerings by introducing some vehicles and brands and
discontinuing other vehicles and brands, precisely because that
information is typically confidential business information (CBI). A
fully-publicly-releasable analysis fleet holds vehicle characteristics
unchanged over time and arguably lacks some level of accuracy when
projected into the future. For example, over time, manufacturers
introduce new products and even entire brands. On the other hand, plans
announced in press releases do not always ultimately bear out, nor do
commercially-available third-party forecasts. Assumptions could be made
about these issues to improve the accuracy of a publicly-releasable
analysis fleet, but concerns include that this information would either
be largely incorrect, or information would be released that
manufacturers would consider CBI. We seek comment on how to address
this issue going forward, recognizing the competing interests involved
and also recognizing typical timeframes for CAFE and CO2
standards rulemakings.
(b) Use of MY 2016 CAFE Compliance Data Versus Other Starting Points
Based on the assumption that a publicly-available analysis fleet
continues to be desirable, for this NPRM, an analysis fleet was
constructed starting with CAFE compliance information from
manufacturers.\68\ Information from MY 2016 was chosen as the
foundation for today's analysis fleet because, at the time the
rulemaking analysis was initiated, the 2016 fleet represented the most
up-to-date information available in terms of individual vehicle models
and configurations, production technology levels, and production
volumes. If MY 2017 data had been used while this analysis was being
developed, the agencies would have needed to use product planning
information that could not be made available to the public until a
later date.
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\68\ CO2 emissions rates are directly related to fuel
economy levels, and the CAFE model uses the latter to calculate the
former.
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The analysis fleet was initially developed with 2016 mid-model year
compliance data because final compliance data was not available at that
time, and the timing provided manufacturers the opportunity to review
and comment on the characterization of their vehicles in the fleet.
With a view toward developing an accurate characterization of the 2016
fleet to serve as an analytical starting point, corrections and updates
to mid-year data (e.g., to production estimates) were sought, in
addition to corroboration or correction of technical information
obtained from commercial and other sources (to the extent that
information was not included in compliance data), although future
product planning information from manufacturers (e.g., future product
offerings, products to be discontinued) was not requested, as most
manufacturers view such information as CBI. Manufacturers offered a
range of corrections to indicate engineering characteristics (e.g.,
footprint, curb weight, transmission type) of specific vehicle model/
configurations, as well as updates to fuel economy and production
volume estimates in mid-year reporting. After following up on a case-
by-case basis to investigate significant differences, the analysis
fleet was updated.
Sales, footprint, and fuel economy values with final compliance
data were also updated if that data was available. In a few cases,
final production and fuel economy values may be slightly different for
specific model year 2016 vehicle models and configurations than are
indicated in today's analysis; however, other vehicle characteristics
(e.g., footprint, curb weight, technology content) important to the
analysis should be accurate. While some commenters have, in the past,
raised concerns that non-final CAFE compliance data is subject to
change, the potential for change is likely not significant enough to
merit using final data from an earlier model year reflecting a more
outdated fleet. Moreover, even ostensibly final CAFE compliance data
can sometimes be subject to later revision (e.g., if errors in fuel
economy tests are discovered), and the purpose of today's analysis is
not to support enforcement actions but rather to provide a realistic
assessment of manufacturers' potential responses to future standards.
Manufacturers integrated a significant amount of new technology in
the MY 2016 fleet, and this was especially true for newly-designed
vehicles launched in MY 2016. While subsequent fleets will involve even
further application of technology, using available data for MY 2016
provides the most realistic detailed foundation for analysis that can
be made available publicly in full detail, allowing stakeholders to
independently reproduce the analysis presented in this proposal.
Insofar as future product offerings are likely to be more similar to
vehicles produced in 2016 than to vehicles produced in earlier model
years, using available data regarding the 2016 model year provides the
most realistic, publicly releasable foundation for constructing a
forecast of the future vehicle market for this proposal.
A number of comments to the Draft TAR, EPA's Proposed
Determination, and EPA's 2017 Request for Comment \69\ stated that the
most up-to-date analysis fleet possible should be used, because a more
up-to-date analysis fleet will better capture how manufacturers apply
technology and will account better for vehicle model/configuration
introductions and deletions.\70\ On the other hand, some commenters
suggested that because manufacturers continue improving vehicle
performance and utility over time, an older analysis fleet should be
used to estimate how the fleet could have evolved had manufacturers
applied all technological potential to
[[Page 43006]]
fuel economy rather than continuing to improve vehicle performance and
utility.\71\ Because manufacturers change and improve product offerings
over time, conducting analysis with an older analysis fleet (or with a
fleet using fuel economy levels and CO2 emissions rates that
have been adjusted to reflect an assumed return to levels of
performance and utility typical of some past model year) would miss
this real-world trend. While such an analysis could demonstrate what
industry could do if, for example, manufacturers devoted all
technological improvements toward raising fuel economy and reducing
CO2 emissions (and if consumers decided to purchase these
vehicles), we do not believe it would be consistent with a transparent
examination of what effects different levels of standards would have on
individual manufacturers and the fleet as a whole.
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\69\ 82 FR 39551 (Aug. 21, 2017).
\70\ For example, in 2016 comments to dockets EPA-HQ-OAR-2015-
0827 and NHTSA-2016-0068, the Alliance of Automobile Manufacturers
commented that ``the Alliance supports the use of the most recent
data available in establishing the baseline fleet, and therefore
believes that NHTSA's selection [of, at the time, model year 2015]
was more appropriate for the Draft TAR.'' (Alliance at 82, Docket
ID. EPA-HQ-OAR-2015-0827-4089) Global Automakers commented that ``a
one-year difference constitutes a technology change-over for up to
20% of a manufacturer's fleet. It was also generally understood by
industry and the agencies that several new, and potentially
significant, technologies would be implemented in MY 2015. The use
of an older, outdated baseline can have significant impacts on the
modeling of subsequent Reference Case and Control Case
technologies.'' (Global Automakers at A-10, Docket ID. EPA-HQ-OAR-
2015-0827-4009).
\71\ For example, in 2016 comments to dockets EPA-HQ-OAR-2015-
0827 and NHTSA-2016-0068, UCS stated ``in modeling technology
effectiveness and use, the agencies should use 2010 levels of
performance as the baseline.'' (UCS at 4, Docket ID. EPA-HQ-OAR-
2015-0827-4016).
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Generally, all else being equal, using a newer analysis fleet will
produce more realistic estimates of impacts of potential new standards
than using an outdated analysis fleet. However, among relatively
current options, a balance must be struck between, on one hand, inputs'
freshness, and on the other, inputs' completeness and accuracy.\72\
During assembly of the inputs for today's analysis, final compliance
data was available for the MY 2015 model year but not in a few cases
for MY 2016. However, between mid-year compliance information and
manufacturers' specific updates discussed above, a robust and detailed
characterization of the MY 2016 fleet was developed. However, while
information continued to develop regarding the MY 2017 and, to a lesser
extent MY 2018 and even MY 2019 fleets, this information was--even in
mid-2017--too incomplete and inconsistent to be assembled with
confidence into an analysis fleet for modeling supporting deliberations
regarding today's proposal.
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\72\ Comments provided through a recent peer review of the CAFE
model recognize the need for this balance. For example, referring to
NHTSA's 2016 analysis documented in the draft TAR, one of the peer
reviewers commented as follows: ``The NHTSA decision to use MY 2015
data is wise. In the TAR they point out that a MY 2016 foundation
would require the use of confidential data, which is less desirable.
Clearly they would also have a qualitative vision of the MY 2016
landscape while employing MY 2015 as a foundation. Although MY 2015
data may still be subject to minor revision, this is unlikely to
impact the predictive ability of the model . . . A more complex
alternative approach might be to employ some 2016 changes in
technology, and attempt a blend of MY 2015 and MY 2016, while
relying of estimation gained from only MY 2015 for sales. This
approach may add some relevancy in terms of technology, but might
introduce substantial error in terms of sales.''
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In short, the 2016 fleet was, in fact, the most up-to-date fleet
that could be produced for this NPRM. Moreover, during late 2016 and
early 2017, nearly all manufacturers provided comments on the
characterization of their vehicles in the analysis fleet, and many
provided specific feedback about their vehicles, including aerodynamic
drag coefficients, tire rolling resistance values, transmission
efficiencies, and other information used in the analysis. NHTSA worked
with manufacturers to clarify and correct some information and
integrated the information into a single input file for use in the CAFE
model. Accordingly, the current analysis fleet is reasonable to use for
purposes of the NPRM analysis.
As always, however, ways to improve the analysis fleet used for
subsequent modeling to evaluate potential new CAFE and CO2
standards will undergo continuous consideration. As described above,
the compliance data is only the starting point for developing the
analysis fleet; much additional information comes directly from
manufacturers (such as details about technologies, platforms, engines,
transmissions, and other vehicle information, that may not be present
in compliance data), and other information must come from commercial
and public sources (for example, fleet-wide information like market
share, because individual manufacturers do not provide this kind of
information). If newer compliance data (i.e., MY 2017) becomes
available and can be analyzed during the pendency of this rulemaking,
and if all of the other necessary steps can be performed, the analysis
fleet will be updated, as feasible, and made publicly available. The
agencies seek comment on the option used today and any other options,
as well as on the tradeoffs between, on one hand, fidelity with
manufacturers' actual plans and, on the other, the ability to make
detailed analysis inputs and outputs publicly available.
(c) Observed Technology Content of 2016 Fleet
As explained above, the analysis fleet is defined not only by the
vehicle models/configurations it contains but also by the technologies
on those vehicles. Each vehicle model/configuration in the analysis
fleet has an associated list of observed technologies and equipment
that can improve fuel economy and reduce CO2 emissions.\73\
With a portfolio of descriptive technologies arranged by manufacturer
and model, the analysis fleet can be summarized and project how
vehicles in that fleet may improve over time via the application of
additional technology.
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\73\ These technologies are generally grouped into the following
categories: Vehicle technologies include mass reduction, aerodynamic
drag reduction, low rolling resistance tires, and others. Engine
technologies include engine attributes describing fuel type, engine
aspiration, valvetrain configuration, compression ratio, number of
cylinders, size of displacement, and others. Transmission
technologies include different transmission arrangements like
manual, 6-speed automatic, 8-speed automatic, continuously variable
transmission, and dual-clutch transmissions. Hybrid and electric
powertrains may complement traditional engine and transmission
designs or replace them entirely.
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In many cases, vehicle technology is clearly observable from the
2016 compliance data (e.g., compliance data indicates clearly which
vehicles have turbochargers and which have continuously variable
transmissions), but in some cases technology levels are less
observable. For the latter, like levels of mass reduction, the analysis
categorized levels of technology already used in a given vehicle.
Similarly, engineering judgment was used to determine if higher mass
reduction levels may be used practicably and safely in a given vehicle.
Either in mid-year compliance data for MY 2016 or, separately and
at the agencies' invitation (as discussed above), most manufacturers
identified most of the technology already present in each of their MY
2016 vehicle model/configurations. This information was not as complete
for all manufacturers' products as needed for today's analysis, so in
some cases, information was supplemented with publicly available data,
typically from manufacturer media sites. In limited cases,
manufacturers did not supply information, and information from
commercial and publicly available sources was used.
(d) Mapping Technology Content of 2016 Fleet to Argonne Technology
Effectiveness Simulation Work
While each vehicle model/configuration in the analysis fleet has
its list of observed technologies and equipment, the ways in which
manufacturers apply technologies and equipment do not always coincide
perfectly with how the analysis characterizes the various technologies
that improve fuel economy and reduce CO2 emissions. To
improve how the observed vehicle fleet ``fits into'' the analysis, each
vehicle model/configuration is ``mapped'' to the full-
[[Page 43007]]
vehicle simulation modeling \74\ by Argonne National Laboratory that is
used to estimate the effectiveness of the fuel economy-improving/
CO2 emissions-reducing technologies considered. Argonne
produces full-vehicle simulation modeling for many combinations of
technologies, on many types of vehicles, but it did not simulate
literally every single vehicle model/configuration in the analysis
fleet because it would be impractical to assemble the requisite
detailed information--much of which would likely only be provided on a
confidential basis--specific to each vehicle model/configuration and
because the scale of the simulation effort would correspondingly
increase by at least two orders of magnitude. Instead, Argonne
simulated 10 different vehicle types, corresponding to the ``technology
classes'' generally used in CAFE analysis over the past several
rulemakings (e.g., small car, small performance car, pickup truck,
etc.). Each of those 10 different vehicle types was assigned a set of
``baseline characteristics,'' to which Argonne added combinations of
fuel-saving technologies and then ran simulations to determine the fuel
economy achieved when applying each combination of technologies to that
vehicle type given its baseline characteristics. These inputs,
discussed at greater length in Sections II.D and II.G, provide the
basis for the CAFE model's estimation of fuel economy levels and
CO2 emission rates.
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\74\ Full-vehicle simulation modeling uses software and physics
models to compute and estimate energy use of a vehicle during
explicit driving conditions. Section II.D below contains more
information on the Argonne work for this analysis.
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In the analysis fleet, inputs assign each specific vehicle model/
configuration to a technology class, and once there, map to the
simulation within that technology class most closely matching the
combination of observed technologies and equipment on that vehicle.\75\
This mapping to a specific simulation result most closely representing
a given vehicle model/configuration's initial technology ``state''
enables the CAFE model to estimate the same vehicle model/
configuration's fuel economy after application of some other
combination of technologies, leading to an alternative technology
state.
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\75\ Mapping vehicle model/configurations in the analysis fleet
to Argonne simulations was generally straightforward, but
occasionally the mapping was complicated by factors like a vehicle
model/configuration being a great match for simulations within more
than one technology class (in which case, the model/configuration
was assigned to the technology class that it best matched), or when
technologies on the model/configuration were difficult to observe
directly (like friction reduction or parasitic loss characteristics
of a transmission, in which case the agencies relied on
manufacturer-reported data or CBI to help map the vehicle to a
simulation).
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(e) Shared Vehicle Platforms, Engines, and Transmissions
Another aspect of characterizing vehicle model/configurations in
the analysis fleet is based on whether they share a ``platform'' with
other vehicle model/configurations. A ``platform'' refers to engineered
underpinnings shared on several differentiated products. Manufacturers
share and standardize components, systems, tooling, and assembly
processes within their products (and occasionally with the products of
another manufacturer) to cost-effectively maintain vibrant
portfolios.\76\
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\76\ The concept of platform sharing has evolved with time.
Years ago, manufacturers rebadged vehicles and offered luxury
options only on premium nameplates (and manufacturers shared some
vehicle platforms in limited cases). Today, manufacturers share
parts across highly differentiated vehicles with different body
styles, sizes, and capabilities that may share the same platform.
For instance, the Honda Civic and Honda CR-V share many parts and
are built on the same platform. Engineers design chassis platforms
with the ability to vary wheelbase, ride height, and even driveline
configuration. Assembly lines can produce hatchbacks and sedans to
cost-effectively utilize manufacturing capacity and respond to
shifts in market demand. Engines made on the same line may power
small cars or mid-size sport utility vehicles. Additionally,
although the agencies' analysis, like past CAFE analyses, considers
vehicles produced for sale in the U.S., the agency notes these
platforms are not constrained to vehicle models built for sale in
the United States; many manufacturers have developed, and use,
global platforms, and the total number of platforms is decreasing
across the industry. Several automakers (for example, General Motors
and Ford) either plan to, or already have, reduced their number of
platforms to less than 10 and account for the overwhelming majority
of their production volumes on that small number of platforms.
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Vehicle model/configurations derived from the same platform are so
identified in the analysis fleet. Many manufacturers' use of vehicle
platforms is well documented in the public record and widely recognized
among the vehicle engineering community. Engineering knowledge,
information from trade publications, and feedback from manufacturers
and suppliers was also used to assign vehicle platforms in the analysis
fleet.
When the CAFE model is deciding where and how to add technology to
vehicles, if one vehicle on the platform receives new technology, other
vehicles on the platform also receive the technology as part of their
next major redesign or refresh.\77\ Similar to vehicle platforms,
manufacturers create engines that share parts.\78\ One engine family
may appear on many vehicles on a platform, and changes to that engine
may or may not carry through to all the vehicles. Some engines are
shared across a range of different vehicle platforms. Vehicle model/
configurations in the analysis fleet that share engines belonging to
the same platform are also identified as such.
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\77\ The CAFE model assigns mass reduction technology at a
platform level, but many other technologies may be assigned and
shared at a vehicle nameplate or vehicle model level.
\78\ For instance, manufacturers may use different piston
strokes on a common engine block or bore out common engine block
castings with different diameters to create engines with an array of
displacements. Head assemblies for different displacement engines
may share many components and manufacturing processes across the
engine family. Manufacturers may finish crankshafts with the same
tools, to similar tolerances. Engines on the same architecture may
share pistons, connecting rods, and the same engine architecture may
include both six and eight cylinder engines.
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It is important to note that manufacturers define common engines
differently. Some manufacturers consider engines as ``common'' if the
engines shared an architecture, components, or manufacturing processes.
Other manufacturers take a narrower definition, and only assume
``common'' engines if the parts in the engine assembly are the same. In
some cases, manufacturers designate each engine in each application as
a unique powertrain.\79\ Engine families for each manufacturer were
tabulated and assigned \80\ based on data-driven criteria. If engines
shared a common cylinder count and configuration, displacement,
valvetrain, and fuel type, those engines may have been considered
together. Additionally, if the compression ratio, horsepower, and
displacement of engines were only slightly different, those engines
were considered to be the same for the purposes of redesign and
sharing. Vehicles in the analysis fleet with the same engine family
will therefore adopt engine technology in a coordinated fashion.\81\ By
grouping engines together, the CAFE model controls future engine
families to retain reasonable powertrain complexity.\82\
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\79\ For instance, a manufacturer may have listed two engines
for a pair that share designs for the engine block, the crank shaft,
and the head because the accessory drive components, oil pans, and
engine calibrations differ between the two. In practice, many
engines share parts, tooling, and assembly resources, and
manufacturers often coordinate design updates between two similar
engines.
\80\ Engine family is referred to in the analysis as an ``engine
code.''
\81\ Specifically, if such vehicles have different design
schedules (i.e., refresh and redesign schedules), and a subset of
vehicles using a given engine add engine technologies in the course
of a redesign or refresh that occurs in an early model year (e.g.,
2018), other vehicles using the same engine ``inherit'' these
technologies at the soonest ensuing refresh or redesign. This is
consistent with a view that, over time, most manufacturers are
likely to find it more practicable to shift production to a new
version of an engine than to indefinitely continue production of
both the new engine and a ``legacy'' engine.
\82\ This does mean, however, that for manufacturers that
submitted highly atomized engine and transmission portfolios, there
is a practical cap on powertrain complexity and the ability of the
manufacturer to optimize the displacement of (a.k.a. ``right size'')
engines perfectly for each vehicle configuration.
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Like with engines, manufacturers often use transmissions that are
the same or similar on multiple vehicles.\83\ To reflect this reality,
shared transmissions were considered for manufacturers as appropriate.
To define common transmissions, the agencies considered transmission
type (manual, automatic, dual-clutch, continuously variable), number of
gears, and vehicle architecture (front-wheel-drive, rear-wheel-drive,
all-wheel-drive based on a front-wheel-drive platform, or all-wheel-
drive based on a rear-wheel-drive platform). If vehicles shared these
attributes, these transmissions were grouped for the analysis. Vehicles
in the analysis fleet with the same transmission configuration \84\
will adopt transmission technology together, as described above.\85\
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\83\ Manufacturers may produce transmissions that have nominally
different machining to castings, or manufacturers may produce
transmissions that are internally identical, except for final output
gear ratio. In some cases, manufacturers sub-contract with suppliers
that deliver whole transmissions. In other cases, manufacturers form
joint-ventures to develop shared transmissions, and these
transmission platforms may be offered in many vehicles across
manufacturers. Manufacturers use supplier and joint-venture
transmissions to a greater extent than engines.
\84\ Transmission configurations are referred to in the analysis
as ``transmission codes.''
\85\ Similar to the inheritance approach outlined for engines,
if one vehicle application of a shared transmission family upgraded
the transmission, other vehicle applications also upgraded the
transmission at the next refresh or redesign year.
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Having all vehicles that share a platform (or engines that are part
of a family) adopt fuel economy-improving/CO2 emissions-
reducing technologies together, subject to refresh/redesign
constraints, reflects the real-world considerations described above but
also overlooks some decisions manufacturers might make in the real
world in response to market pull, meaning that even though the analysis
fleet is incredibly complex, it is also over-simplified in some
respects compared to the real world. For example, the CAFE model does
not currently attempt to simulate the potential for a manufacturer to
shift the application of technologies to improve performance rather
than fuel economy. Therefore, the model's representation of the
``inheritance'' of technology can lead to estimates a manufacturer
might eventually exceed fuel economy
[[Page 43012]]
standards as technology continues to propagate across shared platforms
and engines. In the past, there were some examples of extended periods
during which some manufacturers exceeded one or both of the CAFE and/or
GHG standards, but in plenty of other examples, manufacturers chose to
introduce (or even reintroduce) technological complexity into their
vehicle lineups in response to buyer preferences. Going forward, and
recognizing the recent trend for consolidating platforms, it seems
likely manufacturers will be more likely to choose efficiency over
complexity in this regard; therefore, the potential should be lower
that today's analysis turns out to be over-simplified compared to the
real world.
Options will be considered to further refine the representation of
sharing and inheritance of technology, possibly including model
revisions to account for tradeoffs between fuel economy and performance
when applying technology. Please provide comments on the sharing and
inheritance-related aspects of the analysis fleet and the CAFE model
along with information that would support refinement of the current
approach or development and implementation of alternative approaches.
(f) Estimated Product Design Cycles
Another aspect of characterizing vehicle model/configurations in
the analysis fleet is based on when they can next be refreshed or
redesigned. Redesign schedules play an important role in determining
when new technologies may be applied. Many technologies that improve
fuel economy and reduce CO2 emissions may be difficult to
incorporate without a major product redesign. Therefore, each vehicle
model in the analysis fleet has an associated redesign schedule, and
the CAFE model uses that schedule to restrict significant advances in
some technologies (like major mass reduction) to redesign years, while
allowing manufacturers to include minor advances (such as improved tire
rolling resistance) during a vehicle ``refresh,'' or a smaller update
made to a vehicle, which can happen between redesigns. In addition to
refresh and redesign schedules associated with vehicle model/
configurations, vehicles that share a platform subsequently have
platform-wide refresh and redesign schedules for mass reduction
technologies.
To develop the refresh/redesign cycles used for the MY 2016
vehicles in the analysis fleet, information from commercially available
sources was used to project redesign cycles through MY 2022, as for
NHTSA's analysis for the Draft TAR published in 2016.\86\ Commercially
available sources' estimates through MY 2022 are generally supported by
detailed consideration of public announcements plus related
intelligence from suppliers and other sources, and recognize that
uncertainty increases considerably as the forecasting horizon is
extended. For MYs 2023-2035, in recognition of that uncertainty,
redesign schedules were extended considering past pacing for each
product, estimated schedules through MY 2022, and schedules for other
products in the same technology classes. As mentioned above,
potentially confidential forward-looking information was not requested
from manufacturers; nevertheless, all manufacturers had an opportunity
to review the estimates of product-specific redesign schedules, a few
manufacturers provided related forecasts and, for the most part, that
information corroborated the estimates.
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\86\ In some cases, data from commercially available sources was
found to be incomplete or inconsistent with other available
information. For instance, commercially available sources identified
some newly imported vehicles as new platforms, but the international
platform was midway through the product lifecycle. While new to the
U.S. market, treating these vehicles as new entrants would have
resulted in artificially short redesign cycles if carried forward,
in some cases. Similarly, commercially available sources labeled
some product refreshes as redesigns, and vice versa. In these
limited cases, the data was revised to be consistent with other
available information or typical redesign and refresh schedules, for
the purpose of the CAFE modeling. In these limited cases, the
forecast time between redesigns and refreshes was updated to match
the observed past product timing.
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Some commenters suggested supplanting these estimated redesign
schedules with estimates applying faster cycles (e.g., four to five
years), and this approach was considered for the analysis.\87\ Some
manufacturers tend to operate with faster redesign cycles and may
continue to do so, and manufacturers tend to redesign some products
more frequently than others. However, especially considering that
information presented by manufacturers largely supports estimates
discussed above, applying a ``one size fits all'' acceleration of
redesign cycles would likely not improve the analysis; instead, doing
so would likely reduce consistency with the real world, especially for
light trucks. Moreover, if some manufacturers accelerate redesigns in
response to new standards, doing so would likely involve costs (greater
levels of stranded capital, reduced opportunity to benefit from
``learning''-related cost reductions) greater than reflected in other
inputs to the analysis. However, a wider range of technologies can
practicably be applied during mid-cycle ``freshenings'' than has been
represented by past analyses, and this part of the analysis has been
expanded, as discussed below in Section II.D.\88\ Also, in the
sensitivity analysis supporting today's proposal and presented in
Chapter 13 of the PRIA, one case involving faster redesign schedules
and one involving slower redesign schedules has been analyzed.
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\87\ In response to the EPA's August 21, 2017, Request for
Comments (docket numbers EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068),
see, e.g., CARB at 28 (Docket ID. EPA-HQ-OAR-2015-0827-9197), EDF at
12 (Docket ID. EPA-HQ-OAR-2015-0827-9203), and NRDC, et. al. at 29-
33 (Docket ID. EPA-HQ-OAR-2015-0827-9826).
\88\ NRDC, et al., at 32.
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Manufacturers use diverse strategies with respect to when, and how
often they update vehicle designs. While most vehicles have been
redesigned sometime in the last five years, many vehicles have not. In
particular, vehicles with lower annual sales volumes tend to be
redesigned less frequently, perhaps giving manufacturers more time to
amortize the investment needed to bring the product to market. In some
cases, manufacturers continue to produce and sell vehicles designed
more than a decade ago.
[[Page 43013]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.012
BILLING CODE 4910-59-P
Each manufacturer may use different strategies throughout their
product portfolio, and a component of each strategy may include the
timing of refresh and redesign cycles. Table II-3 below summarizes the
average time between redesigns, by manufacturer, by vehicle technology
class.\89\ Dashes mean the manufacturer has no volume in that vehicle
technology class in the MY 2016 analysis fleet. Across the industry,
manufacturers average 6.5 years between product redesigns.
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\89\ Technology class, or tech class, refers to a group of fuel-
economy simulations of similar vehicles. As explained, each vehicle
is assigned to a representative simulation to estimate technology
effectiveness for purposes of the analysis.
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[[Page 43014]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.013
There are a few notable observations from this table. Pick-up
trucks have much longer redesign schedules (7.8 years on average) than
small cars (5.5 years on average). Some manufacturers redesign vehicles
often (every 5.2 years in the case of Hyundai), while other
manufacturers redesign vehicles less often (FCA waits on average 8.6
years between vehicle redesigns). Across the industry, light-duty
vehicle designs last for about 6.5 years.
Even if two manufacturers have similar redesign cadence, the model
years in which the redesigns occur may still be different and dependent
on where each of the manufacturer's products are in their life cycle.
Table II-4 summarizes the average age of manufacturers' offering by
vehicle technology class. A value of ``0.0'' means that every vehicle
for a manufacturer in that vehicle technology class, represented in the
MY 2016 analysis fleet was new in MY 2016. Across the industry,
manufacturers redesigned MY 2016 vehicles an average of 3.2 years
earlier.
[[Page 43015]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.014
BILLING CODE 4910-59-C
Based on historical observations and refresh/redesign schedule
forecasts, careful consideration to redesign cycles for each
manufacturer and each vehicle is important. Simply assuming every
vehicle is redesigned by 2021 and by 2025 is not appropriate, as this
would misrepresent both the likely timing of redesigns and the likely
time between redesigns in most cases.
C. Development of Footprint-Based Curve Shapes
As in the past four CAFE rulemakings, the most recent two of which
included related standards for CO2 emissions, NHTSA and EPA
are proposing to set attribute-based CAFE standards that are defined by
a mathematical function of vehicle footprint, which has observable
correlation with fuel economy and vehicle emissions. EPCA, as amended
by EISA, expressly requires that CAFE standards for passenger cars and
light trucks be based on one or more vehicle attributes related to fuel
economy and be expressed in the form of a mathematical function.\90\
While the CAA includes no specific requirements regarding GHG
regulation, EPA has chosen to adopt standards consistent with the EPCA/
EISA requirements in the interest of simplifying compliance for the
industry since 2010.\91\ Section II.C.1 describes the advantages of
attribute standards, generally. Section II.C.2 explains the agencies'
specific decision to use vehicle footprint as the attribute over which
to vary stringency for past and current rules. Section II.C.3 discusses
the policy considerations in selecting the specific mathematical
function. Section II.C.4 discusses the methodologies used to develop
current attribute-based standards, and the agencies' current proposal
to continue to do so for MYs 2022-2026. Section II.C.5 discusses the
methodologies used to reconsider the mathematical function for the
proposed standards.
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\90\ 49 U.S.C. 32902(a)(3)(A).
\91\ Such an approach is permissible under section 202(a) of the
CAA, and EPA has used the attribute-based approach in issuing
standards under analogous provisions of the CAA.
---------------------------------------------------------------------------
1. Why attribute-based standards, and what are the benefits?
Under attribute-based standards, every vehicle model has fuel
economy and CO2 targets, the levels of which depend on the
level of that vehicle's determining attribute (for this proposed rule,
footprint is the determining attribute, as discussed below). The
manufacturer's fleet average performance is calculated by the harmonic
production-weighted average of those targets, as defined below:
[[Page 43016]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.015
Here, i represents a given model \92\ in a manufacturer's fleet,
Productioni represents the U.S. production of that model, and Targeti
represents the target as defined by the attribute-based standards. This
means no vehicle is required to meet its target; instead, manufacturers
are free to balance improvements however they deem best within (and,
given credit transfers, at least partially across) their fleets.
---------------------------------------------------------------------------
\92\ If a model has more than one footprint variant, here each
of those variants is treated as a unique model, i, since each
footprint variant will have a unique target.
---------------------------------------------------------------------------
The idea is to select the shape of the mathematical function
relating the standard to the fuel economy-related attribute to reflect
the trade-offs manufacturers face in producing more of that attribute
over fuel efficiency (due to technological limits of production and
relative demand of each attribute). If the shape captures these trade-
offs, every manufacturer is more likely to continue adding fuel
efficient technology across the distribution of the attribute within
their fleet, instead of potentially changing the attribute--and other
correlated attributes, including fuel economy--as a part of their
compliance strategy. Attribute-based standards that achieve this have
several advantages.
First, assuming the attribute is a measurement of vehicle size,
attribute-based standards reduce the incentive for manufacturers to
respond to CAFE standards by reducing vehicle size in ways harmful to
safety.\93\ Larger vehicles, in terms of mass and/or crush space,
generally consume more fuel, but are also generally better able to
protect occupants in a crash.\94\ Because each vehicle model has its
own target (determined by a size-related attribute), properly fitted
attribute-based standards provide little, if any, incentive to build
smaller vehicles simply to meet a fleet-wide average, because smaller
vehicles are subject to more stringent compliance targets.
---------------------------------------------------------------------------
\93\ The 2002 NAS Report described at length and quantified the
potential safety problem with average fuel economy standards that
specify a single numerical requirement for the entire industry. See
Transportation Research Board and National Research Council. 2002.
Effectiveness and Impact of Corporate Average Fuel Economy (CAFE)
Standards, Washington, DC: The National Academies Press (``2002 NAS
Report'') at 5, finding 12, available at https://www.nap.edu/catalog/10172/effectiveness-and-impact-of-corporate-average-fuel-economy-cafe-standards (last accessed June 15, 2018). Ensuing
analyses, including by NHTSA, support the fundamental conclusion
that standards structured to minimize incentives to downsize all but
the largest vehicles will tend to produce better safety outcomes
than flat standards.
\94\ Bento, A., Gillingham, K., & Roth, K. (2017). The Effect of
Fuel Economy Standards on Vehicle Weight Dispersion and Accident
Fatalities. NBER Working Paper No. 23340. Available at http://www.nber.org/papers/w23340 (last accessed June 15, 2018).
---------------------------------------------------------------------------
Second, attribute-based standards, if properly fitted, better
respect heterogeneous consumer preferences than do single-valued
standards. As discussed above, a single-valued standard encourages a
fleet mix with a larger share of smaller vehicles by creating
incentives for manufacturers to use downsizing the average vehicle in
their fleet (possibly through fleet mixing) as a compliance strategy,
which may result in manufacturers building vehicles for compliance
reasons that consumers do not want. Under a size-related, attribute-
based standard, reducing the size of the vehicle is a less viable
compliance strategy because smaller vehicles have more stringent
regulatory targets. As a result, the fleet mix under such standards is
more likely to reflect aggregate consumer demand for the size-related
attribute used to determine vehicle targets.
Third, attribute-based standards provide a more equitable
regulatory framework across heterogeneous manufacturers who may each
produce different shares of vehicles along attributes correlated with
fuel economy.\95\ A single, industry-wide CAFE standard imposes
disproportionate cost burden and compliance challenges on manufacturers
who produce more vehicles with attributes inherently correlated with
lower fuel economy--i.e. manufacturers who produce, on average, larger
vehicles. As discussed above, retaining the ability for manufacturers
to produce vehicles which respect heterogeneous market preferences is
an important consideration. Since manufacturers may target different
markets as a part of their business strategy, ensuring that these
manufacturers do not incur a disproportionate share of the regulatory
cost burden is an important part of conserving consumer choices within
the market.
---------------------------------------------------------------------------
\95\ 2002 NAS Report at 4-5, finding 10.
---------------------------------------------------------------------------
2. Why footprint as the attribute?
It is important that the CAFE and CO2 standards be set
in a way that does not encourage manufacturers to respond by selling
vehicles that are less safe. Vehicle size is highly correlated with
vehicle safety--for this reason, it is important to choose an attribute
correlated with vehicle size (mass or some dimensional measure). Given
this consideration, there are several policy and technical reasons why
footprint is considered to be the most appropriate attribute upon which
to base the standards, even though other vehicle size attributes
(notably, curb weight) are more strongly correlated with fuel economy
and emissions.
First, mass is strongly correlated with fuel economy; it takes a
certain amount of energy to move a certain amount of mass. Footprint
has some positive correlation with frontal surface area, likely a
negative correlation with aerodynamics, and therefore fuel economy, but
the relationship is less deterministic. Mass and crush space
(correlated with footprint) are both important safety considerations.
As discussed below and in the accompanying PRIA, NHTSA's research of
historical crash data indicates that holding footprint constant, and
decreasing the mass of the largest vehicles, will have a net positive
safety impact to drivers overall, while holding footprint constant and
decreasing the mass of the smallest vehicles will have a net decrease
in fleetwide safety. Properly fitted footprint-based standards provide
little, if any, incentive to build smaller vehicles to meet CAFE and
CO2 standards, and therefore help minimize the impact of
standards on overall fleet safety.
Second, it is important that the attribute not be easily
manipulated in a manner that does not achieve the goals of EPCA or
other goals, such as safety. Although weight is more strongly
correlated with fuel economy than footprint, there is less risk of
manipulation (changing the attribute(s) to achieve a more favorable
target) by increasing footprint under footprint-based standards than
there would be by increasing vehicle mass under weight-based standards.
It is relatively easy for a manufacturer to add enough weight to a
vehicle to decrease its applicable fuel economy target a significant
amount, as compared to increasing vehicle
[[Page 43017]]
footprint, which is a much more complicated change that typically takes
place only with a vehicle redesign.
Further, some commenters on the MY 2011 CAFE rulemaking were
concerned that there would be greater potential for gaming under multi-
attribute standards, such as those that also depend on weight, torque,
power, towing capability, and/or off-road capability. As discussed in
NHTSA's MY 2011 CAFE final rule,\96\ it is anticipated that the
possibility of gaming is lowest with footprint-based standards, as
opposed to weight-based or multi-attribute-based standards.
Specifically, standards that incorporate weight, torque, power, towing
capability, and/or off-road capability in addition to footprint would
not only be more complex, but by providing degrees of freedom with
respect to more easily-adjusted attributes, they could make it less
certain that the future fleet would actually achieve the projected
average fuel economy and CO2 levels. This is not to say that
a footprint-based system will eliminate gaming, or that a footprint-
based system will eliminate the possibility that manufacturers will
change vehicles in ways that compromise occupant protection, but
footprint-based standards achieve the best balance among affected
considerations. Please provide comments on whether vehicular footprint
is the most suitable attribute upon which to base standards.
---------------------------------------------------------------------------
\96\ See 74 FR at 14359 (Mar. 30, 2009).
---------------------------------------------------------------------------
3. What mathematical function should be used to specify footprint-based
standards?
In requiring NHTSA to ``prescribe by regulation separate average
fuel economy standards for passenger and non-passenger automobiles
based on 1 or more vehicle attributes related to fuel economy and
express each standard in the form of a mathematical function'', EPCA/
EISA provides ample discretion regarding not only the selection of the
attribute(s), but also regarding the nature of the function. The CAA
provides no specific direction regarding CO2 regulation, and
EPA has continued to harmonize this aspect of its CO2
regulations with NHTSA's CAFE regulations. The relationship between
fuel economy (and GHG emissions) and footprint, though directionally
clear (i.e., fuel economy tends to decrease and CO2 emissions tend to
increase with increasing footprint), is theoretically vague, and
quantitatively uncertain; in other words, not so precise as to a priori
yield only a single possible curve.
The decision of how to specify this mathematical function therefore
reflects some amount of judgment. The function can be specified with a
view toward achieving different environmental and petroleum reduction
goals, encouraging different levels of application of fuel-saving
technologies, avoiding any adverse effects on overall highway safety,
reducing disparities of manufacturers' compliance burdens, and
preserving consumer choice, among other aims. The following are among
the specific technical concerns and resultant policy tradeoffs the
agencies have considered in selecting the details of specific past and
future curve shapes:
Flatter standards (i.e., curves) increase the risk that
both the size of vehicles will be reduced, potentially compromising
highway safety, and reducing any utility consumers would have gained
from a larger vehicle.
Steeper footprint-based standards may create incentives to
upsize vehicles, potentially oversupplying vehicles of certain
footprints beyond what consumers would naturally demand, and thus
increasing the possibility that fuel savings and CO2
reduction benefits will be forfeited artificially.
Given the same industry-wide average required fuel economy
or CO2 standard, flatter standards tend to place greater
compliance burdens on full-line manufacturers.
Given the same industry-wide average required fuel economy
or CO2 standard, dramatically steeper standards tend to
place greater compliance burdens on limited-line manufacturers
(depending of course, on which vehicles are being produced).
If cutpoints are adopted, given the same industry-wide
average required fuel economy, moving small-vehicle cutpoints to the
left (i.e., up in terms of fuel economy, down in terms of
CO2 emissions) discourages the introduction of small
vehicles, and reduces the incentive to downsize small vehicles in ways
that could compromise overall highway safety.
If cutpoints are adopted, given the same industry-wide
average required fuel economy, moving large-vehicle cutpoints to the
right (i.e., down in terms of fuel economy, up in terms of
CO2 emissions) better accommodates the design requirements
of larger vehicles -- especially large pickups -- and extends the size
range over which downsizing is discouraged.
4. What mathematical functions have been used previously, and why?
Notwithstanding the aforementioned discretion under EPCA/EISA, data
should inform consideration of potential mathematical functions, but
how relevant data is defined and interpreted, and the choice of
methodology for fitting a curve to that data, can and should include
some consideration of specific policy goals. This section summarizes
the methodologies and policy concerns that were considered in
developing previous target curves (for a complete discussion see the
2012 FRIA).
As discussed below, the MY 2011 final curves followed a constrained
logistic function defined specifically in the final rule.\97\ The MYs
2012-2021 final standards and the MYs 2022-2025 augural standards are
defined by constrained linear target functions of footprint, as shown
below: \98\
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\97\ See 74 FR 14196, 14363-14370 (Mar. 30, 2009) for NHTSA
discussion of curve fitting in the MY 2011 CAFE final rule.
\98\ The right cutpoint for the light truck curve was moved
further to the right for MYs 2017-2021, so that more possible
footprints would fall on the sloped part of the curve. In order to
ensure that, for all possible footprints, future standards would be
at least as high as MY 2016 levels, the final standards for light
trucks for MYs 2017-2021 is the maximum of the MY 2016 target curves
and the target curves for the give MY standard. This is defined
further in the 2012 final rule. See 77 FR 62624, at 62699-700 (Oct.
15, 2012).
[GRAPHIC] [TIFF OMITTED] TP24AU18.016
Here, Target is the fuel economy target applicable to vehicles of a
given footprint in square feet (Footprint). The upper asymptote, a, and
the lower asymptote, b, are specified in mpg; the reciprocal of these
values represent the lower and upper asymptotes, respectively, when the
curve is instead specified in gallons per mile (gpm). The
[[Page 43018]]
slope, c, and the intercept, d, of the linear portion of the curve are
specified as gpm per change in square feet, and gpm, respectively.
The min and max functions will take the minimum and maximum values
within their associated parentheses. Thus, the max function will first
find the maximum of the fitted line at a given footprint value and the
lower asymptote from the perspective of gpm. If the fitted line is
below the lower asymptote it is replaced with the floor, which is also
the minimum of the floor and the ceiling by definition, so that the
target in mpg space will be the reciprocal of the floor in mpg space,
or simply, a. If, however, the fitted line is not below the lower
asymptote, the fitted value is returned from the max function and the
min function takes the minimum value of the upper asymptote (in gpm
space) and the fitted line. If the fitted value is below the upper
asymptote, it is between the two asymptotes and the fitted value is
appropriately returned from the min function, making the overall target
in mpg the reciprocal of the fitted line in gpm. If the fitted value is
above the upper asymptote, the upper asymptote is returned is returned
from the min function, and the overall target in mpg is the reciprocal
of the upper asymptote in gpm space, or b.
In this way curves specified as constrained linear functions are
specified by the following parameters:
a = upper limit (mpg)
b = lower limit (mpg)
c = slope (gpm per sq. ft.)
d = intercept (gpm)
The slope and intercept are specified as gpm per sq. ft. and gpm
instead of mpg per sq. ft. and mpg because fuel consumption and
emissions appear roughly linearly related to gallons per mile (the
reciprocal of the miles per gallon).
(a) NHTSA in MY 2008 and MY 2011 CAFE (Constrained Logistic)
For the MY 2011 CAFE rule, NHTSA estimated fuel economy levels by
footprint from the MY 2008 fleet after normalization for differences in
technology,\99\ but did not make adjustments to reflect other vehicle
attributes (e.g., power-to-weight ratios). Starting with the
technology-adjusted passenger car and light truck fleets, NHTSA used
minimum absolute deviation (MAD) regression without sales weighting to
fit a logistic form as a starting point to develop mathematical
functions defining the standards. NHTSA then identified footprints at
which to apply minimum and maximum values (rather than letting the
standards extend without limit) and transposed these functions
vertically (i.e., on a gallons-per-mile basis, uniformly downward) to
produce the promulgated standards. In the preceding rule, for MYs 2008-
2011 light truck standards, NHTSA examined a range of potential
functional forms, and concluded that, compared to other considered
forms, the constrained logistic form provided the expected and
appropriate trend (decreasing fuel economy as footprint increases), but
avoided creating ``kinks'' the agency was concerned would provide
distortionary incentives for vehicles with neighboring footprints.\100\
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\99\ See 74 FR 14196, 14363-14370 (Mar. 30, 2009) for NHTSA
discussion of curve fitting in the MY 2011 CAFE final rule.
\100\ See 71 FR 17556, 17609-17613 (Apr. 6, 2006) for NHTSA
discussion of ``kinks'' in the MYs 2008-2011 light truck CAFE final
rule (there described as ``edge effects''). A ``kink,'' as used
here, is a portion of the curve where a small change in footprint
results in a disproportionally large change in stringency.
---------------------------------------------------------------------------
(b) MYs 2012-2016 Standards (Constrained Linear)
For the MYs 2012-2016 rule, potential methods for specifying
mathematical functions to define fuel economy and CO2
standards were reevaluated. These methods were fit to the same MY 2008
data as the MY 2011 standard. Considering these further specifications,
the constrained logistic form, if applied to post-MY 2011 standards,
would likely contain a steep mid-section that would provide undue
incentive to increase the footprint of midsize passenger cars.\101\ A
range of methods to fit the curves would have been reasonable, and a
minimum absolute deviation (MAD) regression without sales weighting on
a technology-adjusted car and light truck fleet was used to fit a
linear equation. This equation was used as a starting point to develop
mathematical functions defining the standards. Footprints were then
identified at which to apply minimum and maximum values (rather than
letting the standards extend without limit). Finally, these
constrained/piecewise linear functions were transposed vertically
(i.e., on a gpm or CO2 basis, uniformly downward) by
multiplying the initial curve by a single factor for each MY standard
to produce the final attribute-based targets for passenger cars and
light trucks described in the final rule.\102\ These transformations
are typically presented as percentage improvements over a previous MY
target curve.
---------------------------------------------------------------------------
\101\ 75 FR at 25362.
\102\ See generally 74 FR at 49491-96; 75 FR at 25357-62.
---------------------------------------------------------------------------
(c) MYs 2017 and Beyond Standards (Constrained Linear)
The mathematical functions finalized in 2012 for MYs 2017 and
beyond changed somewhat from the functions for the MYs 2012-2016
standards. These changes were made to both address comments from
stakeholders, and to further consider some of the technical concerns
and policy goals judged more preeminent under the increased uncertainty
of the impacts of finalizing and proposing standards for model years
further into the future.\103\ Recognizing the concerns raised by full-
line OEMs, it was concluded that continuing increases in the stringency
of the light truck standards would be more feasible if the light truck
curve for MYs 2017 and beyond was made steeper than the MY 2016 truck
curve and the right (large footprint) cut-point was extended only
gradually to larger footprints. To accommodate these considerations,
the 2012 final rule finalized the slope fit to the MY 2008 fleet using
a sales-weighted, ordinary least-squares regression, using a fleet that
had technology applied to make the technology application across the
fleet more uniform, and after adjusting the data for the effects of
weight-to-footprint. Information from an updated MY 2010 fleet was also
considered to support this decision. As the curve was vertically
shifted (with fuel economy specified as mpg instead of gpm or
CO2 emissions) upwards, the right cutpoint was progressively
moved for the light truck curves with successive model years, reaching
the final endpoint for MY 2021; this is further discussed and shown in
Chapter 4.3 of the PRIA.
---------------------------------------------------------------------------
\103\ The MYs 2012-2016 final standards were signed April 1st,
2010--putting 6.5 years between its signing and the last affected
model year, while the MYs 2017-2021 final standards were signed
August 28th, 2012--giving just more than nine years between signing
and the last affected final standards.
---------------------------------------------------------------------------
5. Reconsidering the Mathematical Functions for This Proposal
(a) Why is it important to reconsider the mathematical functions?
By shifting the developed curves by a single factor, it is assumed
that the underlying relationship of fuel consumption (in gallons per
mile) to vehicle footprint does not change significantly from the model
year data used to fit the curves to the range of model years for which
the shifted curve shape is applied to develop the standards. However,
it must be recognized that the relationship
[[Page 43019]]
between vehicle footprint and fuel economy is not necessarily constant
over time; newly developed technologies, changes in consumer demand,
and even the curves themselves could, if unduly susceptible to gaming,
influence the observed relationships between the two vehicle
characteristics. For example, if certain technologies are more
effective or more marketable for certain types of vehicles, their
application may not be uniform over the range of vehicle footprints.
Further, if market demand has shifted between vehicle types, so that
certain vehicles make up a larger share of the fleet, any underlying
technological or market restrictions which inform the average shape of
the curves could change. That is, changes in the technology or market
restrictions themselves, or a mere re-weighting of different vehicles
types, could reshape the fit curves.
For the above reasons, the curve shapes were reconsidered using the
newest available data, from MY 2016. With a view toward corroboration
through different techniques, a range of descriptive statistical
analyses were conducted that do not require underlying engineering
models of how fuel economy and footprint might be expected to be
related, and a separate analysis that uses vehicle simulation results
as the basis to estimate the relationship from a perspective more
explicitly informed by engineering theory was conducted as well.
Despite changes in the new vehicle fleet both in terms of technologies
applied and in market demand, the underlying statistical relationship
between footprint and fuel economy has not changed significantly since
the MY 2008 fleet used for the 2012 final rule; therefore, it is
proposed to continue to use the curve shapes fit in 2012. The analysis
and reasoning supporting this decision follows.
(b) What statistical analyses did NHTSA consider?
In considering how to address the various policy concerns discussed
above, data from the MY 2016 fleet was considered, and a number of
descriptive statistical analyses (i.e., involving observed fuel economy
levels and footprints) using various statistical methods, weighting
schemes, and adjustments to the data to make the fleets less
technologically heterogeneous were performed. There were several
adjustments to the data that were common to all of the statistical
analyses considered.
With a view toward isolating the relationship between fuel economy
and footprint, the few diesels in the fleet were excluded, as well as
the limited number of vehicles with partial or full electric
propulsion; when the fleet is normalized so that technology is more
homogenous, application of these technologies is not allowed. This is
consistent with the methodology used in the 2012 final rule.
The above adjustments were applied to all statistical analyses
considered, regardless of the specifics of each of the methods,
weights, and technology level of the data, used to view the
relationship of vehicle footprint and fuel economy. Table II-5, below,
summarizes the different assumptions considered and the key attributes
of each. The analysis was performed considering all possible
combinations of these assumptions, producing a total of eight footprint
curves.
[GRAPHIC] [TIFF OMITTED] TP24AU18.017
[[Page 43020]]
(1) Current Technology Level Curves
The ``current technology'' level curves exclude diesels and
vehicles with electric propulsion, as discussed above, but make no
other changes to each model year fleet. Comparing the MY 2016 curves to
ones built under the same methodology from previous model year fleets
shows whether the observed curve shape has changed significantly over
time as standards have become more stringent. Importantly, these curves
will include any market forces which make technology application
variable over the distribution of footprint. These market forces will
not be present in the ``maximum technology'' level curves: By making
technology levels homogenous, this variation is removed. The current
technology level curves built using both regression types and both
regression weight methodologies from the MY 2008, MY 2010, and MY 2016
fleets, shown in more detail in Chapter 4.4.2.1 of the PRIA, support
the curve slopes finalized in the 2012 final rule. The curves built
from most methodologies using each fleet generally shift, but remain
very similar in slope. This suggests that the relationship of footprint
to fuel economy, including both technology and market limits, has not
significantly changed.
(2) Maximum Technology Level Curves
As in prior rulemakings, technology differences between vehicle
models were considered to be a significant factor producing uncertainty
regarding the relationship between fuel consumption and footprint.
Noting that attribute-based standards are intended to encourage the
application of additional technology to improve fuel efficiency and
reduce CO2 emissions across the distribution of footprint in
the fleet, approaches were considered in which technology application
is simulated for purposes of the curve fitting analysis in order to
produce fleets that are less varied in technology content. This
approach helps reduce ``noise'' (i.e., dispersion) in the plot of
vehicle footprints and fuel consumption levels and identify a more
technology-neutral relationship between footprint and fuel consumption.
The results of updated analysis for maximum technology level curves are
also shown in Chapter 4.4.2.2 of the PRIA. Especially if vehicles
progress over time toward more similar size-specific efficiency,
further removing variation in technology application both better
isolates the relationship between fuel consumption and footprint and
further supports the curve slopes finalized in the 2012 final rule.
(c) What other methodologies were considered?
The methods discussed above are descriptive in nature, using
statistical analysis to relate observed fuel economy levels to observed
footprints for known vehicles. As such, these methods are clearly based
on actual data, answering the question ``how does fuel economy appear
to be related to footprint?'' However, being independent of explicit
engineering theory, they do not answer the question ``how might one
expect fuel economy to be related to footprint?'' Therefore, as an
alternative to the above methods, an alternative methodology was also
developed and applied that, using full-vehicle simulation, comes closer
to answer the second question, providing a basis to either corroborate
answers to the first, or suggest that further investigation could be
important.
As discussed in the 2012 final rule, several manufacturers have
confidentially shared with the agencies what they described as
``physics-based'' curves, with each OEM showing significantly different
shapes for the footprint-fuel economy relationships. This variation
suggests that manufacturers face different curves given the other
attributes of the vehicles in their fleets (i.e., performance
characteristics) and/or that their curves reflected different levels of
technology application. In reconsidering the shapes of the proposed MYs
2021-2026 standards, a similar estimation of physics-based curves
leveraging third-party simulation work form Argonne National
Laboratories (ANL) was developed. Estimating physics-based curves
better ensures that technology and performance are held constant for
all footprints; augmenting a largely statistical analysis with an
analysis that more explicitly incorporates engineering theory helps to
corroborate that the relationship between fuel economy and footprint is
in fact being characterized.
Tractive energy is the amount of energy it will take to move a
vehicle.\104\ Here, tractive energy effectiveness is defined as the
share of the energy content of fuel consumed which is converted into
mechanical energy and used to move a vehicle--for internal combustion
engine (ICE) vehicles, this will vary with the relative efficiency of
specific engines. Data from ANL simulations suggest that the limits of
tractive energy effectiveness are approximately 25% for vehicles with
internal combustion engines which do not possess ISG, other hybrid,
plug-in, pure electric, or fuel cell technology.
---------------------------------------------------------------------------
\104\ Thomas, J. ``Drive Cycle Powertrain Efficiencies and
Trends Derived from EPA Vehicle Dynamometer Results,'' SAE Int. J.
Passeng. Cars--Mech. Syst. 7(4):2014, doi:10.4271/2014-01-2562.
Available at https://www.sae.org/publications/technical-papers/content/2014-01-2562/ (last accessed June 15, 2018).
---------------------------------------------------------------------------
A tractive energy prediction model was also developed to support
today's proposal. Given a vehicle's mass, frontal area, aerodynamic
drag coefficient, and rolling resistance as inputs, the model will
predict the amount of tractive energy required for the vehicle to
complete the Federal test cycle. This model was used to predict the
tractive energy required for the average vehicle of a given footprint
\105\ and ``body technology package'' to complete the cycle. The body
technology packages considered are defined in Table II-6, below. Using
the absolute tractive energy predicted and tractive energy
effectiveness values spanning possible ICE engines, fuel economy values
were then estimated for different body technology packages and engine
tractive energy effectiveness values.
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\105\ The mass reduction curves used elsewhere in this analysis
were used to predict the mass of a vehicle with a given footprint,
body style box, and mass reduction level. The `Body style Box' is 1
for hatchbacks and minivans, 2 for pickups, and 3 for sedans, and is
an important predictor of aerodynamic drag. Mass is an essential
input in the tractive energy calculation.
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[[Page 43021]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.018
Chapter 6 of the PRIA shows the resultant CAFE levels estimated for
the vehicle classes ANL simulated for this analysis, at different
footprint values and by vehicle ``box.'' Pickups are considered 1-box,
hatchbacks and minivans are 2-box, and sedans are 3-box. These
estimates are compared with the MY 2021 standards finalized in 2012.
The general trend of the simulated data points follows the pattern of
the previous MY 2021 standards for all technology packages and tractive
energy effectiveness values presented in the PRIA. The tractive energy
curves are intended to validate the curve shapes against a physics-
based alternative, and the analysis suggests that the curve shapes
track the physical relationship between fuel economy and tractive
energy for different footprint values.
Physical limitations are not the only forces manufacturers face;
they must also produce vehicles that consumers will purchase. For this
reason, in setting future standards, the analysis will continue to
consider information from statistical analyses that do not homogenize
technology applications in addition to statistical analyses which do,
as well as a tractive energy analysis similar to the one presented
above.
The relationship between fuel economy and footprint remains
directionally discernable but quantitatively uncertain. Nevertheless,
each standard must commit to only one function. Approaching the
question ``how is fuel economy related to footprint'' from different
directions and applying different approaches will provide the greatest
confidence that the single function defining any given standard
appropriately and reasonably reflects the relationship between fuel
economy and footprint. Please provide comments on this tentative
conclusion and the above discussion.
D. Characterization of Current and Anticipated Fuel-Saving Technologies
The analysis evaluates a wide array of technologies manufacturers
could use to improve the fuel economy of new vehicles, in both the near
future and the timeframe of this proposed rulemaking, to meet the fuel
economy and CO2 standards proposed in this rulemaking. The
analysis evaluated costs for these technologies, and looked at how
these costs may change over time. The analysis also considered how
fuel-saving technologies may be used on many types of vehicles (ranging
from small cars to trucks) and how the technologies may perform in
improving fuel economy and CO2 emissions in combination with
other technologies. With cost and effectiveness estimates for
technologies, the analysis can forecast how manufacturers may respond
to potential standards and can estimate the associated costs and
benefits related to technology and equipment changes. This assists the
assessment of technological feasibility and is a building block for the
consideration of economic practicability of potential standards.
NHTSA, EPA, and CARB issued the Draft Technical Assessment Report
(Draft TAR) \106\ as the first step in the EPA MTE process. The Draft
TAR provided an opportunity for the agencies to share with the public
updated technical analysis relevant to development of future standards.
For this NPRM, the analysis relies on portions of the analysis
presented in the Draft TAR, along with new information that has been
gathered and developed since conducting that analysis, and the
significant, substantive input that was received during the public
comment period.
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\106\ Available at https://www.nhtsa.gov/staticfiles/rulemaking/pdf/cafe/Draft-TAR-Final.pdf (last accessed June 15, 2018).
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The Draft TAR considered many technologies previously assessed in
the 2012 final rule.\107\ In some cases, manufacturers have nearly
universally adopted a technology in today's new vehicle fleet (for
example, electric power steering). In other cases, manufacturers
occasionally use a technology in today's new vehicle fleet (like
turbocharged engines). For a few technologies considered in the 2012
rulemaking, manufacturers began implementing the technologies but have
since largely pivoted to other technologies due to consumer acceptance
issues (for instance, in some cases drivability and performance feel
issues associated with dual clutch transmissions without a torque
converter) or limited commercial success. The analysis utilizes new
information as manufacturers' use of technologies evolves.
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\107\ 77 FR 62624 (Oct. 15, 2012).
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Some of the emerging technologies described in the Draft TAR were
not included in this analysis, but this includes some additional
technologies not previously considered. As industry invents and
develops new fuel-savings technologies, and as suppliers and
manufacturers produce and apply the technologies, and as consumers
react to the new technologies, efforts are continued to learn more
about the capabilities and limitations of new technologies. While a
technology is in early development, theoretical constructs, limited
access to test data, and CBI is relied on to assess the technology.
After manufacturers commercialize the technology and bring products to
market, the technology may be studied in more detail, which generally
leads to the most reliable information about the technology. In
addition, once in production, the technology is represented in the fuel
economy and CO2 status of the baseline fleet. The technology
analysis is kept as current as possible in light of the ongoing
technology development and implementation in the automotive industry.
Some technology assumptions have been updated since the MYs 2017-
2025 final rule and, in many cases, since the 2016 Draft TAR. In some
cases, EPA and NHTSA presented different analytical approaches in the
Draft TAR; the analysis is now presented using the
[[Page 43022]]
same direct manufacturing costs, retail costs, and learning rates. In
addition, the effectiveness of fuel-economy technologies is now
assessed based on the same assumptions, and with the same tools.
Finally, manufacturers' response to stringency alternatives is forecast
with the same simulation model.
Since the 2017 and later final rule, many cost assessments,
including tear down studies, were funded and completed, and presented
as part of the Draft TAR analysis. These studies evaluated
transmissions, engines, hybrid technologies, and mass reduction.\108\
As a result, the analysis uses updated cost estimates for many
technologies, some of which have been updated since the Draft TAR. In
addition to those studies, the analysis also leveraged research reports
from other organizations to assess costs.\109\ Today's analysis also
updates the costs to 2016 dollars, as in many cases technology costs
were estimated several years ago.
---------------------------------------------------------------------------
\108\ FEV prepared several cost analysis studies for EPA on
subjects ranging from advanced 8-speed transmissions to belt
alternator starter, or Start/Stop systems. NHTSA also contracted
with Electricore, EDAG, and Southwest Research on teardown studies
evaluating mass reduction and transmissions. The 2015 NAS report on
fuel economy technologies for light-duty vehicles also evaluated the
agencies' technology costs developed based on these teardown
studies, and the technology costs used in this proposal were updated
accordingly. These studies are discussed in detail in Chapter 6 of
the PRIA accompanying this proposal.
\109\ For example, the agencies relied on reports from the
Department of Energy's Office of Energy Efficiency & Renewable
Energy's Vehicle Technologies Office. More information on that
office is available at https://www.energy.gov/eere/vehicles/vehicle-technologies-office. Other agency reports that were relied on for
technology or other information are referenced throughout this
proposal and accompanying PRIA.
---------------------------------------------------------------------------
The analysis uses an updated, peer-reviewed model developed by ANL
for the Department of Energy to provide a more rigorous estimate for
battery costs. The new battery model provides an estimate future for
battery costs for hybrids, plug-in hybrids, and electric vehicles,
taking into account the different battery design characteristics and
taking into account the size of the battery for different
applications.\110\
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\110\ For instance, battery electric vehicles with high levels
of mass reduction may use a smaller battery than a comparable
vehicle with less mass reduction technology and still deliver the
same range on a charge.
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In the Draft TAR, two possible methodologies to estimate indirect
costs from direct manufacturing costs, described as ``indirect cost
multipliers'' and ``retail price equivalent'' were presented. Both of
these methodologies attempted to relate the price of parts for fuel-
saving technologies to a retail price. Today's analysis utilizes the
direct manufacturing costs (DMC) and the retail price equivalent (RPE)
methodology published in the Draft TAR.
Two tools to estimate effectiveness of fuel-saving technologies
were used in the Draft TAR, and for today's analysis, only one tool was
used (Autonomie).\111\ Previously, EPA developed ``ALPHA'', an in-house
model that estimated fuel-savings for technologies, which provided a
foundation for EPA's analysis. EPA's ``ALPHA'' results were used to
calibrate a much simpler ``Lumped Parameter Model'' that was developed
by EPA to estimate technology effectiveness for many technologies. The
Lumped Parameter Model (LPM) approximated simulation modeling results
instead of directly using the results and lead to less accurate
estimates of technology effectiveness. Many stakeholders questioned the
efficacy of the Lumped Parameter Model and ALPHA assumptions and
outputs in combination,\112\ especially as the tool was used to
evaluate increasingly heterogeneous combinations of technologies in the
baseline fleet.\113\ For today's analysis, EPA and NHTSA used an
updated version of the Autonomie model--an improved version of what
NHTSA presented in the 2016 Draft TAR--to assess technology
effectiveness of technologies and combinations of technologies. The
Department of Energy's ANL developed Autonomie and the underpinning
model assumptions leveraged research from the DOE's Vehicle
Technologies Office and feedback from the public. Autonomie is
commercially available and widely used; third parties such as
suppliers, automakers, and academic researchers (who publish findings
in peer reviewed academic journals) commonly use the Autonomie
simulation software.
---------------------------------------------------------------------------
\111\ ANL's Full-Vehicle Simulation Autonomie Model is discussed
in Chapter 6 of the PRIA and in the ANL Model Documentation
available at Docket No. NHTSA-2018-0067.
\112\ At NHTSA-2016-0068-0082, p. 49, FCA provided the following
comments, ``FCA believes EPA is overestimating the benefits of
technology. As the LPM is calibrated to those projections, so too is
the LPM too optimistic.'' FCA also shared the chart, ``LPM vs.
Actual for 8 Speed Transmissions.''
\113\ See e.g., Automotive News ``CAFE math gets trickier as
industry innovates'' (Kulisch), March 26, 2018.
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Similarly for today's analysis, only one tool is used. Previously,
EPA developed ``OMEGA,'' a tool that looked at costs of technologies
and effectiveness of technologies (as estimated by EPA's Lumped
Parameter Model or ALPHA), and applied cost effective technologies to
manufacturers' fleets in response to potential standards. Many
stakeholders commented that the OMEGA model oversimplified fleet-wide
analysis, resulting in significant shortcomings.\114\ For instance,
OMEGA assumed manufacturers would redesign all vehicles in the fleet by
2021, and then again by 2025; stakeholders purported that these
assumptions did not reflect practical constraints in many
manufacturers' business models.\115\ Additionally, stakeholders
commented that OMEGA did not adequately take into consideration common
parts like shared engines, shared transmissions, and engineering
platforms. The CAFE model does consider refresh and redesign cycles and
parts sharing. The CAFE model can evaluate responses to any policy
alternative on a year-by-year basis, as required by EPCA/EISA \116\ and
as allowed by the CAA, and can also account for manufacturers' year-by-
year plans that involve ``carrying forward'' technology from prior
model years, and some other vehicles possibly applying ``extra''
technology in anticipation of standards in ensuing model years. For
today's analysis, an updated version of the CAFE model is used--an
improved version of what NHTSA presented in the 2016 Draft TAR--to
assess manufacturers' response to policy alternatives. See Section
II.A.1 above for further discussion of the decision to use the CAFE
model for the NPRM analysis.
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\114\ The Alliance of Automobile Manufacturers commented that
``the OMEGA model is over-optimized and unrealistic . . . many of
these issues either are not present or are accounted for in DOT's
Volpe model. The Alliance therefore recommends that EPA focus on
ensuring needs specific to its regulatory analysis are appropriately
addressed in the Volpe model.'' Alliance at 48 (Docket ID. EPA-HQ-
OAR-2015-0827-9194).
\115\ For example, FCA provided the following comments: ``EPA's
expectation of 10-20% mass reduction rates across 70% of FCA's
fleet, which includes a 70% truck mix, is simply unreasonable as the
magnitude of change would require complete product redesigns in less
than eight years shortening existing production needed to amortize
the large capital cost involved.'' FCA at 19 (Docket ID. EPA-HQ-OAR-
2015-0827-6160).
\116\ 49 U.S.C. 32902(b)(2)(B).
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Each aforementioned change is discussed briefly in the remainder of
this section and in much greater detail in Chapter 6 of the PRIA. A
brief summary of the technologies considered in this proposal is
discussed below. Please provide comments on all aspects of the analysis
as discussed here and as detailed in the PRIA.
[[Page 43023]]
1. Data Sources and Processes for Developing Individual Technology
Assumptions
Technology assumptions were developed that provide a foundation for
conducting a fleet-wide compliance analysis. As part of this effort,
the analysis estimated technology costs, projected technology
effectiveness values, and identified possible limitations for some
fuel-saving technologies. There is a preference to use values developed
from careful review of commercialized technologies; however, in some
cases for technologies that are new, and are not yet for sale in any
vehicle, the analysis relied on information from other sources,
including CBI and third-party research reports and publications. Many
emerging technologies are still being evaluated for the analysis
supporting the final rule, including those that are currently emerging.
For today's analysis, one set of cost assumptions, one set of
effectiveness values (developed with one tool), and one set of
assumptions about the limitations of some technologies are presented.
Many sources of data were evaluated, in addition to many stakeholder
comments received on the Draft TAR. Throughout the process of
developing the assumptions for today's analysis, the preferred approach
was to harmonize on sources and methodologies that were data-driven and
reproducible in independent verification, produced using tools utilized
by OEMs, suppliers, and academic institutions, and using tools that
could support both CAFE and CO2 analysis. A single set of
assumptions also facilitates and focuses public comment by reducing
burden on stakeholders who seek to review all of the supporting
documentation for this proposal.
(a) Technology Costs
The analysis estimated present and future costs for fuel-saving
technologies, taking into consideration the type of vehicle, or type of
engine if technology costs vary by application. Cost estimates were
developed based on three main inputs. First, direct manufacturing costs
(DMC), or the component costs of the physical parts and systems, were
considered, with estimated costs assuming high volume production. DMCs
generally do not include the indirect costs of tools, capital
equipment, and financing costs, nor do they cover indirect costs like
engineering, sales, and administrative support. Second, indirect costs
via a scalar markup of direct manufacturing costs (the retail price
equivalent, or RPE) was taken into account. Finally, costs for
technologies may change over time as industry streamlines design and
manufacturing processes. Potential cost improvements with learning
effects (LE) were also considered. The retail cost of equipment in any
future year is estimated to be equal to the product of the DMC, RPE,
and LE. Considering the retail cost of equipment, instead of merely
direct manufacturing costs, is important to account for the real-world
price effects of a technology, as well as market realities. Absent
government mandate, a manufacturer will not undertake expensive
development and support costs to implement technologies without
realistic prospects of consumer willingness to pay enough for such
technology to allow for the manufacturer to recover its investment.
(1) Direct Manufacturing Costs
In many instances, the analysis used agency-sponsored tear-down
studies of vehicles and parts to estimate the direct manufacturing
costs of individual technologies. In the simplest cases, the studies
produced results that confirmed third-party industry estimates, and
aligned with confidential information provided by manufacturers and
suppliers. In cases with a large difference between the tear-down study
results and credible independent sources, study assumptions were
scrutinized, and sometimes the analysis was revised or updated
accordingly.\117\ Studies were conducted on vehicles and technologies
that would cover a breadth of fuel-savings technologies, but because
tear-down studies can be time-intensive and expensive, the agencies did
not sponsor teardown studies for every technology. For some
technologies, independent tear-down studies were also utilized, in
addition to other publications and confidential business
information.\118\ Due to the variety of technologies and their
applications, a detailed tear-down study could not be conducted for
every technology, including pre-production technologies.
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\117\ For instance, in previous analysis, EPA referenced an old
study that purported the first 7-10% of mass reduction to be
``free'' or at a significant ``cost savings'' to for many vehicles
and many manufacturers.
\118\ The analysis referenced studies from private businesses
and business analysts for emerging technologies and for off-the-
shelf technologies that were commercially mature.
---------------------------------------------------------------------------
Many fuel-saving technologies were considered that are pre-
production, or sold in very small pilot volumes. For emerging
technologies that could be applied in the rulemaking timeframe, a tear-
down study cannot be conducted to assess costs because the product is
not yet in the marketplace for evaluation. In these cases, third-party
estimates and confidential information from suppliers and manufacturers
are relied upon; however, there are some common pitfalls with relying
on confidential business information to estimate costs. The agencies
and the source may have had incongruent or incompatible definitions of
``baseline.'' \119\ The source may have provided direct manufacturer
costs at a date many years in the future, and assumed very high
production volumes, important caveats to consider for agency analysis.
In addition, a source, under no contractual obligation to the agencies,
may provide incomplete and/or misleading information. In other cases,
intellectual property considerations and strategic business
partnerships may have contributed to a manufacturer's cost information
and could be difficult to account for in the model as not all
manufacturer's may have access to proprietary technologies at stated
costs. New information is carefully evaluated in light of these common
pitfalls, especially regarding emerging technologies. The analysis used
third-party, forward looking information for advanced cylinder
deactivation and variable compression ratio engines, and while these
cost estimates may be cursory (as is the case with many emerging
technologies prior to commercialization), the agencies took care to use
early information provided fairly and reasonably. While costs for fuel-
saving technologies reflect the best estimates available today,
technology cost estimates will likely change in the future as
technologies are deployed and as production is expanded. For emerging
technologies, the best information available at the time of the
analysis was utilized, and cost assumptions will continue to be
updated.
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\119\ ``Baseline'' here refers to a reference part, piece of
equipment, or engineering system that efficiency improvements and
costs are relative to.
---------------------------------------------------------------------------
(2) Indirect Costs
As explained above, in addition to direct manufacturing costs, the
analysis estimates and considers indirect manufacturing costs. To
estimate indirect costs, direct manufacturing costs are multiplied by a
factor to represent the average price for fuel-saving technologies at
retail. This factor, referred to as the retail price equivalence (RPE),
accounts for indirect costs like engineering, sales, and administrative
support, as well as other overhead costs, business expenses, warranty
costs, and return on capital
[[Page 43024]]
considerations. This approach to the RPE remains unchanged from the RPE
approach NHTSA presented in the Draft TAR.
The RPE was chosen for this analysis instead of indirect cost
multipliers (ICM) because it provides the best estimate of indirect
costs. For a more detailed discussion of the approach to indirect
costs, see PRIA Chapter 9.
(3) Stranded Capital Costs
Past analyses accounted for costs associated with stranded capital
when fuel economy standards caused a technology to be replaced before
its costs were fully amortized. The idea behind stranded capital is
that manufacturers amortize research, development, and tooling expenses
over many years, especially for engines and transmissions. The
traditional production life-cycles for transmissions and engines have
been a decade or longer. If a manufacturer launches or updates a
product with fuel-saving technology, and then later replaces that
technology with an unrelated or different fuel-saving technology before
the equipment and research and development investments have been fully
paid off, there will be unrecouped, or stranded, capital costs.
Quantifying stranded capital costs attempted to account for such lost
investments. In the Draft TAR analysis, there were only a few
technologies for a few manufacturers that were projected to have
stranded capital costs.
As more technologies are included in this analysis, and as the CAFE
model has been expanded to account for platform and engine sharing and
updated with redesign and refresh cycles, accounting for stranded
capital has become increasingly complex. Separately, the fact that
manufacturers may be shifting their investment strategies in ways that
may affect stranded capital calculations was considered. For instance,
Ford and General Motors agreed to jointly develop next generation
transmission technologies,\120\ and some suppliers sell similar
transmissions to multiple manufacturers. These arrangements allow
manufacturers to share in capital expenditures, or amortize expenses
more quickly. Manufacturers increasingly share parts on vehicles around
the globe, achieving greater scale and greatly affecting tooling
strategies and costs. Given these trends in the industry and their
uncertain effect on capital amortization, and given the difficulty of
handling this uncertainty in the CAFE model, this analysis does not
account for stranded capital. However, these trends will be monitored
to assess the role of stranded capital moving forward.
---------------------------------------------------------------------------
\120\ See, e.g., Nick Bunkley, Ford to invest $1.4 billion to
build 10-speed transmissions for 2017 F-150, Automotive News (Apr.
26, 2016), http://www.autonews.com/article/20160426/OEM01/160429878/
ford-to-invest-$1.4-billion-to-build-10-speed-transmissions-for-
2017.
---------------------------------------------------------------------------
The analysis continues to rely on projected refresh and redesign
cycles in the CAFE model to moderate the cadence for technology
adoption and limit the occurrence of stranded capital and the need to
account for it. Stranded capital is an important consideration to
appropriately account for costs if there is too rapid of a turnover for
certain technologies.
(4) Cost Learning
Manufacturers make improvements to production processes over time,
often resulting in lower costs. Today's analysis estimates cost
learning by considering Wright's learning theory, which states that as
every time cumulative volume for a product doubles, the cost lowers by
a scalar factor. The analysis accounts for learning effects with model
year-based cost learning forecasts for each technology that reduce
direct manufacturing costs over time. Historical use of technologies
were evaluated, and industry forecasts were reviewed to estimate future
volumes for the purpose of developing the model year-based technology
cost learning curves. The CAFE model does not dynamically update
learning curves, based on compliance pathways chosen in simulation.
As discussed above, cost inputs to the CAFE model incorporate
estimates of volume-based learning. As an alternative approach, Volpe
Center staff have considered modifications such that the CAFE model
would calculate degrees of volume-based learning dynamically,
responding to the model's application of affected technologies. While
it is intuitive that the degree of cost reduction achieved through
experience producing a given technology should depend on the actual
accumulated experience (i.e., volume) producing that technology, staff
have thus far found such dynamic implementation in the CAFE model
infeasible. Insufficient data has been available regarding
manufacturers' historical application of specific technology. Also,
insofar as underlying direct manufacturing costs already make some
assumptions about volume and scale, insufficient information is
currently available to determine how to dynamically adjust these
underlying costs. It should be noted that if learning responds
dynamically to volume, and volume responds dynamically to learning, an
internally consistent model solution would likely require iteration of
the CAFE model to seek a stable solution within the model's
representation multiyear planning. Thus far, these challenges suggest
it would be infeasible to calculate degrees of volume-based learning in
a manner that responds dynamically to modeled technology application.
Nevertheless, the agencies invite comment on the issue, and seek data
and methods that would provide the basis for a practicable approach to
doing so.
Today's analysis also updates the way learning effects apply to
costs. In the Draft TAR analysis, NHTSA applied learning curves only to
the incremental direct manufacturing costs or costs over the previous
technology on the tech tree. In practice, two things were observed: (1)
If the incremental direct manufacturing costs were positive,
technologies could not become less expensive than their predecessors on
the tech tree, and (2) absolute costs over baseline technology depended
on the learning curves of root technologies on the tech tree. Today's
analysis applies learning effects to the incremental cost over the null
technology state on the tech tree. After this step, the analysis
calculates year-by-year incremental costs over preceding technologies
on the tech tree to create the CAFE model inputs.
Direct manufacturing costs and learning effects for many
technologies were reviewed by evaluating historical use of technologies
and industry forecasts to estimate future volumes. This approach
produced reasonable estimates for technologies already in production.
For technologies not yet in production in MY 2016, the cumulative
volume in MY 2016 is zero, because manufacturers have not yet produced
the technologies. For pre-production cost estimates, the analysis often
relies on confidential business information sources to predict future
costs. Many sources for pre-production cost estimates include
significant learning effects, often providing cost estimates assuming
high volume production, and often for a timeframe late in the first
production generation or early in the second generation of the
technology. Rapid doubling and re-doubling of a low cumulative volume
base with Wright's learning curves can provide unrealistic cost
estimates. In addition, direct manufacturing cost projections can vary
depending on the initial production volume assumed. Direct costs with
learning were carefully examined, and adjustments were made to the
starting
[[Page 43025]]
point for those technologies on the learning curve to better align with
the assumptions used for the initial direct cost estimate. See PRIA
Chapter 9 for more detailed information on cost learning.
(b) Technology Effectiveness
(1) Technology Effectiveness Simulation Modeling
Full-vehicle simulation modeling was used to estimate the fuel
economy improvements manufacturers could make to their fleet by adding
new technologies, taking into account MY 2016 vehicle specifications,
as well as how combinations of technologies interact. Full-vehicle
simulation modeling uses computer software and physics-based models to
predict how combinations of technologies perform together.
The simulation and modeling requires detailed specifications for
each technology that describes its efficiency and performance-related
characteristics. Those specifications generally come from design
specifications, laboratory measurements, simulation or modeling, and
may involve additional analysis. For example, the analysis used engine
maps showing fuel use vs. engine torque vs. engine speed, and
transmission maps taking into account gear efficiency for a range of
loads and speeds. With physics-based technology specifications, full-
vehicle simulation modeling can be used to estimate technology
effectiveness for various combinations and permutations of technologies
for many vehicle classes. To develop the specifications used for the
simulation and modeling, laboratory test data was evaluated for
production and pre-production technologies, technical publications,
manufacturer and supplier CBI, and simulation modeling of specific
technologies. Evaluating recently introduced production products to
inform the technology effectiveness models of emerging technologies is
preferred because doing so allows for a more reliable analysis of
incremental improvements over previous technologies; however, some
technologies were considered that are not yet in production. As
technologies evolve and new applications emerge, this work will be
continued and may include additional technologies and/or updated
modeling for the final rule. The details of new and emerging
technologies are discussed in PRIA Chapter 6.
Using full-vehicle simulation modeling has two primary advantages
over using single or limited point estimates for fuel efficiency
improvements of technologies. First, technology effectiveness often
differs significantly depending on the type of vehicle and the other
technologies that are on the vehicle, and this is shown in full-vehicle
simulations. Different technologies may provide different fuel economy
improvements depending on whether they are implemented alone or in
tandem with other technologies. Single point estimates often
oversimplify these important, complex relationships and lead to less
accurate effectiveness estimates. Also, because manufacturers often
implement a number of fuel-saving technologies simultaneously at
vehicle redesigns, it is generally difficult to isolate the effect of
individual technologies using laboratory measurement of production
vehicles alone. Simulation modeling offers the opportunity to isolate
the effects of individual technologies by using a single or small
number of baseline configurations and incrementally adding technologies
to those baseline configurations. This provides a consistent reference
point for the incremental effectiveness estimates for each technology
and for combinations of technologies for each vehicle type and reduces
potential double counting or undercounting technology effectiveness.
Note: It is most important that the incremental effectiveness of each
technology and combinations be accurate and relative to a consistent
baseline, because it is the incremental effectiveness that is applied
to each vehicle model/configuration in the MY 2016 baseline fleet (and
to each vehicle model/configuration's absolute fuel economy value) to
determine the absolute fuel economy of the model/configuration with the
additional technology. The absolute fuel economy values of the
simulation modeling runs by themselves are used only to determine the
incremental effectiveness and are never used directly to assign an
absolute fuel economy value to any vehicle model/configuration for the
rulemaking analysis. Therefore, commenters on technology effectiveness
should be specific about the incremental effectiveness of technologies
relative to other specifically defined technologies. The fuel economy
of a specific vehicle or simulation modeling run in isolation may be
less useful.
Second, full-vehicle simulation modeling requires explicit
specifications and assumptions for each technology; therefore, these
assumptions can be presented for public review and comment. For
instance, transmission gear efficiencies, shift logic, and gear ratios
are explicitly stated as model inputs and are available for review and
comment. For today's analysis, every effort was made to make the input
specifications and modeling assumptions available for review and
comment. PRIA Chapter 6 and referenced documents provide more detailed
information.
Technology development and application will be monitored to acquire
more information for the final rule. The agencies may update the
analysis for the final rule based on comments and/or new information
that becomes available.
Today's analysis utilizes effectiveness estimates for technologies
developed using Autonomie software,\121\ a physics-based full-vehicle
simulation tool developed and maintained by the Department of Energy's
ANL. Autonomie has a long history of development and widespread
application by users in industry, academia, research institutions and
government.\122\ Real-world use has contributed significantly to
aspects of Autonomie important to producing realistic estimates of fuel
economy and CO2 emission rates, such as estimation and
consideration of performance, utility, and driveability metrics (e.g.,
towing capability, shift business, frequency of engine on/off
transitions). This steadily increasing realism has, in turn, steadily
increased confidence in the appropriateness of using Autonomie to make
significant investment decisions. Notably, DOE uses Autonomie for
analysis supporting budget priorities and plans for programs managed by
its Vehicle Technologies Office (VTO) and to decide among competing
vehicle technology R&D projects.
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\121\ More information about Autonomie is available at https://www.anl.gov/technology/project/autonomie-automotive-system-design
(last accessed June 21, 2018).
\122\ ANL Model Documentation, ``A Detailed Vehicle Simulation
Process To Support CAFE Standards'' ANL/ESD-18/6.
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In the 2015 National Academies of Science (NAS) study of fuel
economy improving technologies, the Committee recommended that the
agencies use full-vehicle simulation to improve the analysis method of
estimating technology effectiveness.\123\ The committee acknowledged
that developing and executing tens or hundreds of thousands of
constantly changing vehicle packages models in
[[Page 43026]]
real-time is extremely challenging. While initially this approach was
not considered practical to implement, a process developed by Argonne
in collaboration with NHTSA and the DOT Volpe Center has succeeded in
enabling large scale simulation modeling. For more details about the
Autonomie simulation model and its submodels and inputs, see PRIA
Chapter 6.2.
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\123\ National Research Council. 2015. Cost, Effectiveness, and
Deployment of Fuel Economy Technologies for Light-Duty Vehicles.
Washington, DC: The National Academies Press [hereinafter ``2015 NAS
Report''] at pg. 263, available at https://www.nap.edu/catalog/21744/cost-effectiveness-and-deployment-of-fuel-economy-technologies-for-light-duty-vehicles (last accessed June 21, 2018).
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Today's analysis modeled more than 50 fuel economy-improving
technologies, and combinations thereof, on 10 vehicle types (an
increase from five vehicle types in NHTSA's Draft TAR analysis). While
10 vehicle types may seem like a small number, a large portion of the
production volume in the MY 2016 fleet have specifications that are
very similar, especially in highly competitive segments (for instance,
many mid-sized sedans, many small SUVs, and many large SUVs coalesce
around similar specifications, respectively), and baseline simulations
have been aligned around these modal specifications. The sequential
addition of these technologies generated more than 100,000 unique
technology combinations per vehicle class. The analysis included 10
technology classes, so more than one million full-vehicle simulations
were run. In addition, simulation modeling was conducted to determine
the appropriate amount of engine downsizing needed to maintain baseline
performance across all modeled vehicle performance metrics when
advanced mass reduction technology or advanced engine technology was
applied, so these simulations take into account performance neutrality,
given logical engine down-sizing opportunities associated with specific
technologies.
Some baseline vehicle assumptions used in the simulation modeling
were updated based on public comment and the assessment of the MY 2016
production fleet. The analysis included updated assumptions about curb
weight, component inertia, as well as technology properties like
baseline rolling resistance, aerodynamic drag coefficients, and frontal
areas. Many of the assumptions are aligned with published research from
the Department of Energy's Vehicle Technologies Office and other
independent sources.\124\ Additional transmission technologies and more
levels of aerodynamic technologies than NHTSA presented in the Draft
TAR analysis were also added for today's analysis. Having additional
technologies allowed the agencies to assign baselines and estimate
fuel-savings opportunities with more precision.
---------------------------------------------------------------------------
\124\ Pannone, G. ``Technical Analysis of Vehicle Load Reduction
Potential for Advanced Clear Cars,'' April 29, 2015. Available at
https://www.arb.ca.gov/research/apr/past/13-313.pdf (last accessed
June 21, 2018).
---------------------------------------------------------------------------
The 10 vehicle types (referred to as ``technology classes'' in the
modeling documentation) are shown in Table II-7. Each vehicle type
(technology class) represented a large segment of vehicles, such as
medium cars, small SUVs, and medium performance SUVs.\125\ Baseline
parameters were defined with ANL for each technology class, including
baseline curb weight, time required to accelerate from stop to 60 miles
per hour, time required to accelerate from 50 miles per hour to 80
miles per hour, ability of the vehicle to maintain constant 65 miles
per hour speed on a six percent upgrade, and (for some classes)
assumptions about towing capability.
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\125\ Separate technology classes were created for high
performance and low performance vehicles to better account for
performance diversity across the fleet.
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[[Page 43027]]
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From these baseline specifications, incremental combinations of
fuel saving technologies were applied. As the combinations of
technologies change, so too may predicted performance.
The analysis attempts to maintain performance by resizing engines
at a few specific incremental technology steps. Steps from one
technology to another typically associated with a major vehicle
redesign, or engine redesign, were identified, and engine resizing was
restricted only to these steps. The analysis allowed engine resizing
when mass reduction of 10% or greater was applied to the vehicle glider
mass,\126\ and when one powertrain architecture was replaced with
another architecture.\127\ The analysis resized engines to the extent
that performance was maintained for the least capable performance
criteria to maintain vehicle utility for that criteria; therefore,
sometimes other performance attributes may improve. For instance, the
amount of engine resizing may be determined based on its high speed
acceleration time if it is the least capable criteria, but that
resizing may also improve the low speed acceleration time.\128\ The
analysis did not re-size the engine in response to adding technologies
that have small effects on vehicle performance. For instance, if a
vehicle's weight is reduced by a small amount causing the 0-60 mile per
hour time to improve slightly, the analysis would not resize the
engine. Manufacturers have repeatedly told the agencies that the high
costs for redesign and the increased manufacturing complexity that
would result from resizing engines for such small changes in the
vehicle preclude doing so. The analysis should not, in fact, include
engine resizing with the application of every technology or for
combinations of technologies that drive small performance changes so
that the analysis better reflects what is feasible for manufacturers to
do.\129\
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\126\ The vehicle glider is defined here as the vehicle without
the engine, transmission, and driveline. See PRIA Chapter 6.3 for
further information.
\127\ Some engine and accessory technologies may be added to an
engine without an engine architecture change. For instance,
manufacturers may adapt, but not replace engine architectures to
include cylinder deactivation, variable valve lift, belt-integrated
starter generators, and other basic technologies. However, switching
from a naturally aspirated engine to a turbo-downsized engine is an
engine architecture change typically associated with a major
redesign and radical change in engine displacement.
\128\ The simulation database, or summary of simulation outputs,
includes all of the estimated performance metrics for each
combination of technology as modeled.
\129\ For instance, a vehicle would not get a modestly bigger
engine if the vehicle comes with floor mats, nor would the vehicle
get a modestly smaller engine without floor mats. This example
demonstrates small levels of mass reduction. If manufacturers
resized engines for small changes, manufacturers would have
dramatically more part complexity, potentially losing economies of
scale.
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2. CAFE model
The CAFE model is designed to simulate compliance with a given set
of CAFE or CO2 standards for each manufacturer that sells
vehicles in the United States. The model begins with a
[[Page 43028]]
representation of the MY 2016 vehicle model offerings for each
manufacturer that includes the specific engines and transmissions on
each model variant, observed sales volumes, and all fuel economy
improving technology that is already present on those vehicles. From
there the model adds technology, in response to the standards being
considered, in a way that minimizes the cost of compliance and reflects
many real-world constraints faced by automobile manufacturers. The
model addresses fleet year-by-year compliance, taking into
consideration vehicle refresh and redesign schedules and shared
platforms, engines, and transmissions among vehicles.
As a result of simulating compliance, the CAFE model provides the
technology pathways that manufacturers could use to comply with
regulations, including how technologies could be applied to each of
their vehicle model/configurations in response to a given set of
standards. The model calculates the impacts of the simulated standard:
Technology costs, fuel savings (both in gallons and dollars),
CO2 reductions, social costs and benefits, and safety
impacts.
The current analysis reflects several changes made to the CAFE
model since 2012, when NHTSA used the model to estimate the effects,
costs, and benefits of final CAFE standards for light-duty vehicles
produced during MYs 2017-2021 and augural standards for MYs 2022-2025.
The changes are discussed in Section II.A.1, above, and PRIA Chapter 6.
3. Assumptions About Individual Technology Cost and Effectiveness
Values
Cost and effectiveness values were estimated for each technology
included in the analysis, with a summary list of all technologies
provided in Table II-1 (List of Technologies with Data Sources for
Technology Assignments) of Preamble Chapter II.B, above. In all, more
than 50 technologies were considered in today's analysis, and the
analysis evaluated many combinations of these technologies on many
applications. Potential issues in assessing technology effectiveness
and cost were identified, including:
Baseline (MY 2016) vehicle technology level assessed as
too low, or too high. Compliance information was extensively reviewed
and supplemented with available literature on many MY 2016 vehicle
models. Manufacturers could also review the baseline technology
assignments for their vehicles, and the analysis incorporates feedback
received from manufacturers.
Technology costs too low or too high. Tear down cost
studies, CBI, literature, and the 2015 NAS study information were
referenced to estimate technology costs. In cases that one technology
appeared exemplary on cost and effectiveness relative to all other
technologies, information was acquired from additional sources to
confirm or reject assumptions. Cost assumptions for emerging
technologies are continuously being evaluated.
Technology effectiveness too high or too low in
combination with other vehicle technologies. Technology effectiveness
was evaluated using the Autonomie full-vehicle simulation modeling,
taking into account the impact of other technologies on the vehicle and
the vehicle type. Inputs and modeling for the analysis took into
account laboratory test data for production and some pre-production
technologies, technical publications, manufacturer and supplier CBI,
and simulation modeling of specific technologies. Evaluating recently
introduced production products to inform the technology effectiveness
models of emerging technologies was preferred; however, some
technologies that are not yet in production were considered, via CBI.
Simulation modeling used carefully chosen baseline configurations to
provide a consistent, reasonable reference point for the incremental
effectiveness estimates.
Vehicle performance not considered or applied in an
infeasible manner. Performance criteria, including low speed
acceleration (0-60 mph time), high speed acceleration (50-80 mph time),
towing, and gradeability (six percent grade at 65 mph) were also
considered. In the simulation modeling, resizing was applied to achieve
the same performance level as the baseline for the least capable
performance criteria but only with significant design changes. The
analysis struck a balance by employing a frequency of engine downsizing
that took product complexity and economies of scale into account.
Availability of technologies for production application
too soon or too late. A number of technologies were evaluated that are
not yet in production. CBI was gathered on the maturity and timing of
these technologies and the likely cadence at which manufacturers might
adopt these technologies.
Product complexity and design cadence constraints too low
or too high. Product platforms, refresh and redesign cycles, shared
engines, and shared transmissions were also considered in the analysis.
Product complexity and the cadence of product launches were matched to
historical values for each manufacturer.
Customer acceptance under estimated or over estimated.
Resale prices for hybrid vehicles, electric vehicles, and internal
combustion engine vehicles were evaluated to assess consumer
willingness to pay for those technologies. The analysis accounts for
the differential in the cost for those technologies and the amount
consumers have actually paid for those technologies. Separately, new
dual-clutch transmissions and manual transmissions were applied to
vehicles already equipped with these transmission architectures.
Please provide comments on all assumptions for fuel economy and
CO2 technology costs, effectiveness, availability, and
applicability to vehicles in the fleet.
The technology effectiveness modeling results show effectiveness of
a technology often varies with the type of vehicle and the other
technologies that are on the vehicle. Figure II-1 and Figure II-2 show
the range of effectiveness for each technology for the range of vehicle
types and technology combinations included in this NPRM analysis. The
data reflect the change in effectiveness for applying each technology
by itself while all other technologies are held unchanged. The data
show the improvement in fuel consumption (in gallons per mile) and
tailpipe CO2 over the combined 2-cycle test procedures. For
many technologies, effectiveness values ranged widely; only a few
technologies for which effectiveness may be reasonably represented as a
fixed offset were identified.
For engine technologies, the effectiveness improvement range is
relative to a comparably equipped vehicle with only variable valve
timing (VVT) on the engine. For automatic transmission technologies,
the effectiveness improvement range is over a 5-speed automatic
transmission. For manual transmission technologies, the effectiveness
improvement range is over a 5-speed manual transmission. For road load
technologies like aerodynamics, rolling resistance, and mass reduction,
the effectiveness improvement ranges are relative to the least advanced
technology state, respectively. For hybrid and electric drive systems
that wholly replace an engine and transmission, the effectiveness
improvement ranges are relative to a comparably equipped vehicle with a
basic engine with VVT only and a 5-speed automatic transmission. For
hybrid or electrification technologies that complement other advanced
engine
[[Page 43029]]
and transmission technologies, the effectiveness improvement ranges are
relative to a comparably equipped vehicle without the hybrid or
electrification technologies (for instance, parallel strong hybrids and
belt integrated starter generators retain engine technologies, such as
a turbo charged engine or an Atkinson cycle engine). Many technologies
have a wide range of estimated effectiveness values. Figure II-3 below
shows a hierarchy of technologies discussed.
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[[Page 43031]]
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4. Engine Technologies
There are a number of engine technologies that manufacturers can
use to improve fuel economy and CO2. Some engine
technologies can be incorporated into existing engines with minor or
moderate changes to the engines, but many engine technologies require
an entirely new engine architecture.
In this section and for this analysis, the terms ``basic engine
technologies'' and ``advanced engine technologies'' are used only to
define how the CAFE model applies a specific engine technology and
handles incremental costs and effectiveness improvements. ``Basic
engine technologies'' refer to technologies that, in many cases, can be
adapted to an existing engine with minor or moderate changes to the
engine. ``Advanced engine technologies'' refer to technologies that
generally require significant changes or an entirely new engine
architecture. In the CAFE model, basic engine technologies may be
applied in combination with other basic engine technologies; advanced
engine technologies (defined by an engine map) stand alone as an
exclusive engine technology. The words ``basic'' and ``advanced'' are
not meant to confer any information about the level of sophistication
of the technology. Also, many advanced engine technology
[[Page 43032]]
definitions include some basic engine technologies, but these basic
technologies are already accounted for in the costs and effectiveness
values of the advance engine. The ``basic engine technologies'' need
not be (and are not) applied in addition to the ``advanced engine
technologies'' in the CAFE model.
Engines come in a wide variety of shapes, sizes, and
configurations, and the incremental engine costs and effectiveness
values often depend on engine architecture. The agencies modeled single
overhead cam (SOHC), dual overhead cam (DOHC), and overhead valve (OHV)
engines separately to account for differences in engine architecture.
The agencies adjusted costs for some engine technologies based on the
number of cylinders and number of banks in the engine, and the agencies
evaluated many production engines to better understand how costs and
capabilities may vary with engine configuration. Table II-8, Table II-
9, Table II-10 below shows the summary of absolute costs \130\ for
different technologies.
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\130\ ``Absolute'' being in reference to cost above the lowest
level of technology considered in simulations. For instance, an
engine of the same architecture with no VVT, VVL, SGDI, or DEAC.
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[[Page 43034]]
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[[Page 43035]]
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Many types of production powertrains were reviewed and tested for
this analysis, and engine maps were developed for each combination of
[[Page 43036]]
engine technologies. For a given engine configuration, some production
engines may be less efficient than the engine maps presented in the
analysis, and some may be more efficient. Developing engine maps that
reasonably represented most vehicles equipped with the engine
technology, and that are in production today, was the preferred
approach for this analysis. Additionally, some advanced engines were
included in the simulation that are not yet in production. The engine
maps for these engines were either based on CBI or were theoretical.
The most recently released production engines are still being reviewed,
and the analysis may include updated engine maps in the future or add
entirely new engine maps to the analysis if either action could improve
the quality of the fleet-wide analysis.
Stakeholders provided many comments on the engine maps that were
presented in the Draft TAR. These comments were considered, and today's
analysis utilizes several engine maps that were updated since the Draft
TAR. Most notably, for turbocharged and downsized engines, the engine
maps were adjusted in high torque, low speed operating conditions to
address engine knock with regular octane fuel to align with the fuel
octane that manufacturers recommend be used for the majority of
vehicles. In the Draft TAR, NHTSA assumed high octane fuel to develop
engine maps. See the discussion below and in PRIA Chapter 6.3 for more
details. Please provide comment on the appropriateness of assuming the
use of lower octane fuels.
(a) ``Basic'' Engine Technologies
The four ``basic'' engine technologies in today's model are
Variable Valve Timing (VVT), Variable Valve Lift (VVL), Stoichiometric
Gasoline Direct Injection (SGDI), and basic Cylinder Deactivation
(DEAC). Over the last decade, manufacturers upgraded many engines with
these engine technologies. Implementing these technologies involves
changes to the cylinder head of the engine, but the engine block,
crankshaft, pistons, and connecting rods require few, if any, changes.
In today's analysis, manufacturers may apply the four basic engine
technologies in various combinations, just as manufacturers have done
recently.
(1) Variable Valve Timing (VVT)
Variable Valve Timing (VVT) is a family of valve-train designs that
dynamically adjusts the timing of the intake valves, exhaust valves, or
both, in relation to piston position. This family of technologies
reduces pumping losses. VVT is nearly universally used in the MY 2016
fleet.
(2) Variable Valve Lift (VVL)
Variable Valve Lift (VVL) dynamically adjusts the travel of the
valves to optimize airflow over a broad range of engine operating
conditions. The technology increases effectiveness by reducing pumping
losses and may improve efficiency by affecting in-cylinder charge (fuel
and air mixture), motion, and combustion.
(3) Stoichiometric Gasoline Direct Injection (SGDI)
Stoichiometric Gasoline Direct Injection (SGDI) sprays fuel at high
pressure directly into the combustion chamber, which provides cooling
of the in-cylinder charge via in-cylinder fuel vaporization to improve
spark knock tolerance and enable an increase in compression ratio and/
or more optimal spark timing for improved efficiency. SGDI appears in
about half of basic engines produced in MY 2016, and the technology is
used in many advanced engines as well.
(4) Basic Cylinder Deactivation (DEAC)
Basic Cylinder Deactivation (DEAC) disables intake and exhaust
valves and prevents fuel injection into some cylinders during light-
load operation. The engine runs temporarily as though it were a smaller
engine, which reduces pumping losses and improves efficiency.
Manufacturers typically disable one-cylinder bank with basic cylinder
deactivation. In the MY 2016 fleet, manufacturers used DEAC on V6, V8,
V10, and V12 engines on OHV, SOHC, and DOHC engine configurations. With
some engine configurations in some operating conditions, DEAC creates
noise-vibration-and-harshness (NVH) challenges. NVH challenges are
significant for V6 and I4 DEAC configurations. For I4 engine
configurations, manufacturers can operate the DEAC function of an
engine in very few operating conditions, with limited potential to save
fuel. No manufacturers sold I4 DEAC engines in the MY 2016 fleet.
Typically, the smaller the engine displacement, the less opportunity
DEAC provides to improve fuel consumption.
Manufacturers and suppliers continue to evaluate more improved
versions of cylinder deactivation, including advanced cylinder
deactivation and pairing basic cylinder deactivation with turbo charged
engines. No manufacturers produced such technologies in the MY 2016
fleet. Advanced cylinder deactivation and turbo technologies were
modeled and considered separately in today's analysis.
(b) ``Advanced'' Engine Technologies
The analysis included ``advanced'' engine technologies that can
deliver high levels of effectiveness but often require a significant
engine design change or a new engine architecture. In the CAFE model,
``basic'' engine technologies may be considered in combination and
applied before advanced engine technologies. ``Advanced'' engine
technologies generally include one or more basic engine technologies in
the simulation, without the need to layer on ``basic'' engine
technologies on top of ``advanced'' engines. Once an advanced engine
technology is applied, the model does not reconsider the basic engine
technologies. The characterization of each advanced engine technology
takes into account the prerequisite technologies.
Many of the newest advanced engine technologies improve
effectiveness over their predecessors, but the engines may also include
sophisticated materials or manufacturing processes that contribute to
efficiency improvements. For instance, one recently introduced turbo
charged engine uses sodium filled valve stems.\131\ Another recently
introduced high compression ratio engine uses a sophisticated laser
cladding process to manufacture valve seats and improve airflow.\132\
To fully consider these advancements (and their potential benefits),
the incremental costs of these technologies, as well as the
effectiveness improvements, must be accounted for.
---------------------------------------------------------------------------
\131\ See Honda, ``2018 Honda Accord Press Kit--Powertrain,''
Oct. 2, 2017. Available at http://news.honda.com/newsandviews/article.aspx?g=honda-automobiles&id=9932-en. (last accessed June 21,
2018).
\132\ Hakariya et al., ``The New Toyota Inline 4-Cylinder 2.5L
Gasoline Engine,'' SAE Technical Paper 2017-01-1021 (Mar. 28, 2017),
available at https://www.sae.org/publications/technical-papers/content/2017-01-1021/.
---------------------------------------------------------------------------
(1) Turbocharged Engines
Turbo engines recover energy from hot exhaust gas and compress
intake air, thereby increasing available airflow and increasing
specific power level. Due to specific power improvements on turbo
engines, engine displacement can be downsized. The downsizing reduces
pumping losses and improves fuel economy at lower loads. For the NPRM
analysis, a level of downsizing is assumed to be applied that achieves
performance similar to the baseline naturally-aspirated engine. This
assumes manufacturers would apply the benefits toward improved fuel
economy
[[Page 43037]]
and not trade off fuel economy improvements to increase overall vehicle
performance. In practice, manufacturers have often also improved some
vehicle performance attributes at the expense of not maximizing
potential fuel economy improvements.
Manufacturers may develop engines to operate on varying levels of
boost,\133\ with higher levels of boost achieving higher engine
specific power and enabling greater levels of engine downsizing and
corresponding reductions in pumping losses for improved efficiency.
However, engines operating at higher boost levels are generally more
susceptible to engine knock,\134\ especially at higher torques and low
engine speeds. Additionally, engines with higher boost levels typically
require larger induction and exhaust system components, dissipate
greater amounts of heat, and with greater levels of engine downsizing
have increased challenges with turbo lag.\135\ For these reasons, three
levels of turbo downsizing technologies are separately modeled in this
analysis.
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\133\ Boost refers to the degree to which the turbocharger
compresses the intake air for the engine, which may affect the
specific power of the engine.
\134\ Knock refers to rapid uncontrolled combustion in the
cylinder part way through the combustion process, which can create
an audible sound and can damage the engine.
\135\ Turbo lag refers to the delay time between power demanded
and power delivered; it is typically associated with rapid
accelerations from a stopped vehicle at idle.
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The analysis also modeled turbocharged engines with parallel hybrid
technology. In simulations with high stringencies, many manufacturers
produced turbo-hybrid electric vehicles. In the MY 2016 fleet, of the
vehicles that use parallel hybrid technology, many use turbocharged
engines.
Since the Draft TAR, the turbo family engine maps were updated to
reflect operation on 87 AKI regular octane fuel.\136\ In the Draft TAR,
turbo engine maps were developed assuming premium fuel. For this
rulemaking analyses, pathways to improving fuel economy and
CO2 are analyzed, while also maintaining vehicle
performance, capability, and other attributes. This includes assuming
there is no change in the fuel octane required to operate the vehicle.
Using 87 AKI regular octane fuel is consistent with the fuel octane
that manufacturers specify for the majority of vehicles, and enables
the modeling to account for important design and calibration issues
associated with regular octane fuel. Using the updated criteria assures
the NPRM analysis reflects real-world constraints faced by
manufacturers to assure engine durability, and acceptable drivability,
noise and harshness, and addresses the over-estimation of potential
fuel economy improvements related to the fuel octane assumptions, which
did not fully account for these constraints, in the Draft TAR. Compared
with the NHTSA analysis in the Draft TAR, these engine maps adjust the
fuel use at high torque and low speed operation and at high speed
operation to fully account for knock limitations with regular octane
fuel.
---------------------------------------------------------------------------
\136\ Specifically, 87 Anti-Knock Index (AKI) Tier 3
certification fuel. 87 AKI is also known as 87 (R+M)/2 or 87
(Research Octane + Motor Octane)/2.
---------------------------------------------------------------------------
The analysis assumes engine downsizing with the addition of turbo
technology. For instance, in the simulations, manufacturers may have
replaced a naturally-aspirated V8 engine with a turbo V6 engine, and
manufacturers may have replaced a naturally-aspirated V6 engine with a
turbo I4 engine. When manufacturers reduced the number of banks or
cylinders of an engine, some cost savings is projected due to fewer
cylinders and fewer valves. Such cost savings is projected to help
offset the additional costs of turbo charger specific hardware, making
turbo downsizing a very attractive technology progression for some
engines.\137\
---------------------------------------------------------------------------
\137\ In particular, the step from a naturally-aspirated V6 to a
turbo I4 was particularly cost effective in agency simulations.
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(a) TURBO1
Level 1 Turbo Charging (TURBO1) adds a turbo charger to a DOHC
engine with SGDI, VVT, and continuously VVL. The engine operates at up
to 18 bar brake mean effective pressure (BMEP).
Manufacturers used Turbo1 technology in a little less than a
quarter of the MY 2016 fleet with particularly high concentrations in
premium vehicles.
(b) TURBO2
Level 2 Turbo Charging (TURBO2) operates at up to 24 bar BMEP. The
step from Turbo1 to Turbo2 is accompanied with additional displacement
downsizing for reduced pumping losses. Very few manufacturers have
Turbo2 technology in the MY 2016 fleet.
(c) CEGR1
Turbo Charging with Cooled Exhaust Gas Recirculation (CEGR1)
improves the knock resistance of Turbo2 engines by mixing cooled inert
exhaust gases into the engine's air intake. That allows greater boost
levels, more optimal spark timing for improved fuel economy, and
performance and greater engine downsizing for lower pumping losses.
CEGR1 technology is used in only a few vehicles in the MY 2016 fleet,
and many of these vehicles include high-performance utility either for
towing or acceleration.
(a) Turbocharged Engine Technologies Not Considered
Previous analyses considered turbo charged engines with even higher
BMEP than today's Turbo2 and CEGR1 technologies, but today's analysis
does not present 27 bar BMEP turbo engines. Turbo engines with very
high BMEP have demonstrated limited potential to improve fuel economy
due to practical limitations on engine downsizing and tradeoffs with
launch performance and drivability. Based on the analysis, and based on
CBI, CEGR2 turbo engine technology was not included in this NPRM
analysis.
(2) High Compression Ratio Engines (Atkinson Cycle Engines)
Atkinson cycle gasoline engines use changes in valve timing (e.g.,
late-intake-valve-closing or LIVC) to reduce the effective compression
ratio while maintaining the expansion ratio. This approach allows a
reduction in top-dead-center (TDC) clearance ratio (e.g., increase in
``mechanical'' or ``physical'' compression ratio) to increase the
effective expansion ratio without increasing the effective compression
ratio to a point that knock-limited operation is encountered.
Increasing the expansion ratio in this manner improves thermal
efficiency but also lowers peak BMEP, particularly at lower engine
speeds.
Often knock concerns for these engines limit applications in high
load, low RPM conditions. Some manufacturers have mitigated knock
concerns by lowering back pressure with long, intricate exhaust
systems, but these systems must balance knock performance with
emissions tradeoffs, and the increased size of the exhaust manifold can
pose packaging concerns, particularly on V-engine configurations.\138\
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\138\ Some HCR1 4-cylinder (I-4) engines use an intricate 4-2-1
exhaust manifold to lower backpressure and to improve engine
efficiency. Manufacturers sometimes fitted such an exhaust system
into a front-wheel-drive vehicle with an I-4 engine by using a high
underbody tunnel or rearward dashpanel (trading off some interior
space), but packaging such systems on rear-wheel-drive vehicles may
pose challenges, especially if the engine has two banks and would
therefore require room for two such exhaust manifolds.
---------------------------------------------------------------------------
Only a few manufacturers produced internal combustion engine
vehicles with Atkinson cycle engines in MY
[[Page 43038]]
2016; however, these engines are commonly paired with hybrid electric
vehicle technologies due to the synergy of peak efficiency of Atkinson
cycle engines and immediate torque from electric motors in strong
hybrids. Atkinson cycle engines are very common on power split hybrids
and are sometimes observed as part of a parallel hybrid system or plug-
in hybrid system.
Atkinson cycle engines played a prominent role in EPA's January
2017 final determination, which has since been withdrawn. Today's
analysis recognizes that the technology is not suitable for many
vehicles due to performance, emissions and packaging issues, and/or the
extensive capital and resources that would be required for
manufacturers to shift from other powertrain technology pathways (such
as turbocharging and downsizing) to standalone Atkinson cycle engine
technology.
(a) HCR1
A number of Asian manufacturers have launched Atkinson cycle
engines in smaller vehicles that do not use hybrid technologies. These
production engines have been benchmarked to characterize HCR1
technology for today's analysis.
Today's analysis restricted the application of stand-alone Atkinson
cycle engines in the CAFE model in some cases. The engines benchmarked
for today's analysis were not suitable for MY 2016 baseline vehicle
models that have 8-cylinder engines and in many cases 6-cylinder
engines.
(b) HCR2
EPA conceptualized a ``future'' Atkinson cycle engine and published
the theoretical engine map in an SAE paper.139 140 For this
engine, EPA staff began with a best-in-class 2.0L Atkinson cycle engine
and then increased the efficiency of the engine map further, through
the theoretical application of additional technologies in combination,
like cylinder deactivation, engine friction reduction, and cooled
exhaust gas recirculation. This engine remains entirely speculative, as
no production engine as outlined in the EPA SAE paper has ever been
commercially produced or even produced as a prototype in a lab setting.
Furthermore, the engine map has not been validated with hardware and
bench data, even on a prototype level (as no such engine exists to test
to validate the engine map).
---------------------------------------------------------------------------
\139\ Ellies, B., Schenk, C., and Dekraker, P., ``Benchmarking
and Hardware-in-the-Loop Operation of a 2014 MAZDA SkyActiv 2.0L
13:1 Compression Ratio Engine,'' SAE Technical Paper 2016-01-1007,
2016. Available at https://www.sae.org/publications/technical-papers/content/2016-01-1007/.
\140\ Lee, S., Schenk, C., and McDonald, J., ``Air Flow
Optimization and Calibration in High-Compression-Ratio Naturally
Aspirated SI Engines with Cooled-EGR,'' SAE Technical Paper 2016-01-
0565, 2016. Available at https://www.sae.org/publications/technical-papers/content/2016-01-0565/.
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Previously, EPA relied heavily on the HCR2 (or sometimes referred
to as ATK2 in previous EPA analysis) engine as a cost effective pathway
to compliance for stringent alternatives, but many engine experts
questioned its technical feasibility and near term commercial
practicability. Stakeholders asked for the engine to be removed from
compliance simulations until the performance could be validated with
engine hardware.\141\ \142\ While for the Draft TAR, the agencies ran
full-vehicle simulations with the theoretical engine map and made these
available in the CAFE model, HCR2 technology as described in EPA's SAE
paper was not included in today's analysis because there has been no
observable physical demonstration of the speculative technology, and
many questions remain about its practicability as specified, especially
in high load, low engine speed operating conditions. Simulations with
EPA's HCR2 engine map produce results that approach (and sometimes
exceed) diesel powertrain efficiency.\143\ Given the prominence of this
unproven technology in previous rule-makings, the CAFE model may be
configured to consider the application of HCR2 technology for reference
only.
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\141\ At NHTSA-2016-0068-0082, FCA recommended, ``Remove ATK2
from OMEGA model until the performance is validated.'', p. viii. And
FCA stated, ``ATK2--High Compression engines coupled with Cylinder
Deactivation and Cooled EGR are unlikely to deliver modeled results,
meet customer needs, or be ready for commercial application.'', p.
6-9.
\142\ At Docket ID No EPA-HQ-OAR-2015-0827-6156, The Alliance of
Automobile Manufacturers commented, ``[There] is no current example
of combined Atkinson, plus cooled EGR, plus cylinder deactivation
technology in the present fleet to verify EPA's modeled benefits and
. . . EPA could not provide physical test results replicating its
modeled benefits of these combined technologies,'' p. 40.
\143\ Thomas, J. ``Drive Cycle Powertrain Efficiencies and
Trends Derived from EPA Vehicle Dynamometer Results,'' SAE Int. J.
Passeng. Cars--Mech. Syst. 7(4):2014. Available at https://www.sae.org/publications/technical-papers/content/2014-01-2562/.
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As new engines emerge that achieve high thermal efficiency,
questions may be raised as to whether the HCR2 engine is a simulation
proxy for the new engine technology. It is important to conduct a
thorough evaluation of the actual new production engines to measure the
brake specific fuel consumption and to characterize the improvements
attributable to friction and thermal efficiency before drawing
conclusions. Using vehicle level data may misrepresent or conflate
complex interactions between a high thermal efficiency engine, engine
friction reduction, accessory load improvements, transmission
technologies, mass reduction, aerodynamics, rolling resistance, and
other vehicle technologies. For instance, some of the newest high
compression ratio engines show improved thermal efficiency, in large
part due to improved accessory loads or reduced parasitic losses from
accessory systems.\144\ The CAFE model allows for incremental
improvement over existing HCR1 technologies with the addition of
improved accessory devices (IACC), a technology that is available to be
applied on many baseline MY 2016 vehicles with HCR1 engines and may be
applied as part of a pathway of compliance to further improve the
effectiveness of existing HCR1 engines.
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\144\ For instance, the MY 2018 2.5L Camry engine that uses HCR
technology also reduces parasitic losses with a variable capacity
oil pump.
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(c) Emerging Gasoline Engine Technologies
Manufacturers and suppliers continue to invest in many emerging
engine technologies, and some of these technologies are on the cusp of
commercialization. Often, manufacturers submit information about new
engine technologies that they may soon bring into production. When this
happens, a collaborative effort is undertaken with suppliers and
manufacturers to learn as much as possible and sometimes begin
simulation modeling efforts. Bench data, or performance data for
preproduction vehicles and engines, is usually closely held
confidential business information. To properly characterize the
technologies, it is often necessary to wait until the engine
technologies are in production to study them.
(1) Advanced Cylinder Deactivation (ADEAC)
Advanced cylinder deactivation systems (or rolling or dynamic
cylinder deactivation systems) allows a further degree of cylinder
deactivation than DEAC. The technology allows the engine to vary the
percentage of cylinders deactivated and the sequence in which cylinders
are deactivated, essentially providing ``displacement on demand'' for
low load operations, so long as the calibration avoids certain
frequencies.
[[Page 43039]]
ADEAC systems may be integrated into the valvetrains with moderate
modifications on OHV engines. However, while the ADEAC operating
concept remains the same on DOHC engines, the valvetrain hardware
configuration is very different, and application on DOHC engines is
projected to be more costly per cylinder due to the valvetrain
differences.
Some preproduction 8-cylinder OHV prototype vehicles were briefly
evaluated for this analysis, but no production versions of the
technology have been studied.
Today's analysis relied on CBI to estimate costs and effectiveness
values of ADEAC. Since no engine map was available at the time of the
NPRM analysis, ADEAC was estimated to improve a basic engine with VVL,
VVT, SGDI, and DEAC by three percent (for 4 cylinder engines) six
percent (for engines with more than 4 cylinders).
ADEAC systems will continue to be studied as production begins.
(2) Variable Compression Ratio Engines (VCR)
Engines using variable compression ratio (VCR) technology appear to
be at a production-intent stage of development but also appear to be
targeted primarily towards limited production, high performance and
very high BMEP (27-30 bar) applications. Variable compression ratio
engines work by changing the length of the piston stroke of the engine
to operate at a more optimal compression ratio and improve thermal
efficiency over the full range of engine operating conditions.
A number of manufacturers and suppliers provided information about
VCR technologies, and several design concepts were reviewed that could
achieve a similar functional outcome. In addition to design concept
differences, intellectual property ownership complicates the ability of
the agencies to define a VCR hardware system that could be widely
adopted across the industry.
For today's analysis, VCR engines have a spot on the technology
simulation tree, but VCR is not actively used in the NPRM simulation.
Reasonable representations of costs and technology characterizations
remain open questions for VCR engine technology and the analysis.
NHTSA is sponsoring work to develop engine maps for additional
combinations of technologies. Some of these technologies being
researched presently, including VCR, may be used in the analysis
supporting the final rule. Please provide comment on variable
compression ratio engine technology. Should VCR technology be employed
in the timeframe of this proposed rulemaking? Why or why not? Do
commenters believe VCR technology will see widespread adoption in the
US vehicle fleet? Why or why not? What vehicle segments may it best be
suited for, and which segments would it not be best suited for? Why or
why not? What cost and effectiveness values should be used if VCR is
modeled for analysis? Please provide supporting data. Additionally,
please provide any comments on the sponsored work related to VCR,
described further in PRIA Chapter 6.3.
(3) Compression Ignition Gasoline Engines (SpCCI, HCCI)
For many years, engine developers, researchers, manufacturers have
explored ways to achieve the inherent efficiency of a diesel engine
while maintaining the operating characteristics of a gasoline engine. A
potential pathway for striking this balance is utilizing compression
ignition for gasoline fueled engines, more commonly referred to as
Homogeneous Charge Compression Ignition (HCCI).
Ongoing, periodic discussions with manufacturers on future fuel
saving technologies and powertrain plans have, generally, included HCCI
as a long-term strategy. The technology appears to always be a strong
consideration as, in theory, it provides the ``best of both worlds,''
meaning a way to provide diesel engine efficiency with gasoline engine
performance and emissions levels.
Developments in both the research and the potential production
implementation of HCCI for the US market is continually assessed. In
2017, a significant, potentially production breakthrough was announced
by Mazda regarding a gasoline-fueled engine employing Spark Controlled
Compression Ignition (SpCCI), where HCCI is employed for a portion of
its normal operation and spark ignition is used at other times.\145\
Soon after, Mazda publicly stated they plan to introduce this engine as
part of the Skyactiv family of engines in 2019.\146\
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\145\ Mazda Next-Generation Technology--Press Information, Mazda
USA (Oct. 24, 2017), https://insidemazda.mazdausa.com/press-release/mazda-next-generation-technology-press-information/ (last visited
Apr. 13, 2018).
\146\ Mazda introduces updated 2019 CX-3 at 2018 New York
International Auto Show, Mazda USA (Mar. 28, 2018), https://insidemazda.mazdausa.com/press-release/mazda-introduces-2019-cx-3-2018-new-york-auto-show/ (last visited Apr. 13, 2018).
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However, HCCI was not included in the simulation and vehicle fleet
modeling for past rulemakings, and is not included in this NPRM
analysis, primarily because effectiveness, cost, and mass market
implementation readiness data are not available.
Please comment on the potential use of HCCI technology in the
timeframe covered by this rule. More specifically, should HCCI be
included in the final rulemaking analysis for this proposed rulemaking?
Why or why not? Please provide supporting data, including effectiveness
values, costs in relation varying engine types and applications, and
production timing that supports the timeframe of this rulemaking.
(d) Diesel Engines
Diesel engines have several characteristics that give superior fuel
efficiency, including reduced pumping losses due to lack of (or greatly
reduced) throttling, high pressure direct injection of fuel, a
combustion cycle that operates at a higher compression ratio, and a
very lean air/fuel mixture relative to an equivalent-performance
gasoline engine. This technology requires additional enablers, such as
a NOX adsorption catalyst system or a urea/ammonia selective
catalytic reduction system for control of NOX emissions
during lean (excess air) operation.
(e) Alternative Fuel Engines
(1) Compressed Natural Gas (CNG)
Compressed Natural Gas (CNG) engines use compressed natural gas as
a fuel source. The fuel storage and supply systems for these engines
differ tremendously from gasoline, diesel, and flex fuel vehicles.
(2) Flex Fuel Engines
Flex fuel engines can run on regular gasoline and fuel blended with
ethanol. These vehicles may require additional equipment in the fuel
system to effectively supply different blends of fuel to the engine.
(f) Lubrication and Friction Reduction
Low-friction lubricants including low viscosity and advanced low
friction lubricant oils are now available (and widely used). If
manufacturers choose to make use of these lubricants, they may need to
make engine changes and conduct durability testing to accommodate the
lubricants. The level of low friction lubricants exceeded 85%
penetration in the MY 2016 fleet.
Reduction of engine friction can be achieved through low-tension
piston rings, roller cam followers, improved material coatings, more
optimal thermal management, piston surface treatments, and other
improvements in the design of
[[Page 43040]]
engine components and subsystems that improve efficient engine
operation.
Manufacturers have already widely adopted both lubrication and
friction reduction technologies. This analysis includes advanced engine
maps that already assume application of low-friction lubricants and
engine friction reduction technologies. Therefore, additional friction
reduction is not considered in today's analysis.
The use and commercial development of improved lubricants and
friction reduction components will continue to be monitored, including
conical boring and oblong cylinders, and future analyses may be updated
if new information becomes available.
5. Fuel Octane
(a) What is fuel octane level?
Gasoline octane levels are an integral part of potential engine
performance. According the United States Energy Information
Administration (EIA), octane ratings are measures of fuel stability.
These ratings are based on the pressure at which a fuel will
spontaneously combust (auto-ignite) in a testing engine.\147\
Spontaneous combustion is an undesired condition that will lead to
serious engine damage and costly repairs for consumers if not properly
managed. The higher an octane number, the more stable the fuel,
mitigating the potential for spontaneous combustion, also commonly
known as ``knock.'' Modern engine control systems are sophisticated and
allow manufacturers to detect when ``knock'' occurs during engine
operation. These control systems are designed to adjust operating
parameters to reduce or eliminate ``knock'' once detected.
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\147\ U.S. Energy Information Administration, What is Octane?,
https://www.eia.gov/energyexplained/index.cfm?page=gasoline_home#tab2 (last visited Mar. 19, 2018).
---------------------------------------------------------------------------
In the United States, consumers are typically able to select from
three distinct grades of fuel, each of which provides a different
octane rating. The octane levels can vary from region to region, but on
the majority, the octane levels offered are regular (the lowest octane
fuel-generally 87 Anti-Knock Index (AKI) also expressed as (the average
of Research Octane + Motor Octane), midgrade (the middle range octane
fuel-generally 89-90 AKI), and premium (the highest octane fuel-
generally 91-94 AKI).\148\ At higher elevations, the lowest octane
rating available can drop to 85 AKI.\149\
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\148\ Id.
\149\ See e.g., U.S. Department of Energy and U.S. Environmental
Protection Agency, What is 85 octane, and is it safe to use in my
vehicle?, https://www.fueleconomy.gov/feg/octane.shtml#85 (last
visited Mar. 19, 2018). 85 octane fuel is available in high-
elevation regions where the barometric pressure is lower causing
naturally-aspirated engines to operate with less air and, therefore,
at lower torque and power. This creates less benefit and need for
higher octane fuels as compared to at lower elevations where engine
airflow, torque, and power levels are higher.
---------------------------------------------------------------------------
Currently, throughout the United States, pump fuel is a blend of
90% gasoline and 10% ethanol. It is standard practice for refiners to
manufacture gasoline and ship it, usually via pipelines, to bulk fuel
terminals across the country. In many cases, refiners supply lower
octane fuels than the minimum 87-octane required by law to these
terminals. The terminals then perform blending operations to bring the
fuel octane level up to the minimum required by law, and higher. In
some cases, typically to lowest fuel grade, the ``base fuel'' is
blended with ethanol, which has a typical octane rating of
approximately 113. For example, in 2013, the State of Nebraska Ethanol
Board defined requirements for refiners to 84-octane gas for blending
to achieve 87-octane prior to final dispensing to consumers.\150\
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\150\ Nebraska Ethanol Board, Oil Refiners Change Nebraska Fuel
Components, Nebraska.gov, http://ethanol.nebraska.gov/wordpress/oil-refiners-change-nebraska-fuel-components/ (last visited Mar. 19,
2018).
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(b) Fuel Octane Level and Engine Performance
A typical, overarching goal of optimal spark-ignited engine design
and operation is to maximize the greatest amount of energy from the
fuel available, without manifesting detrimental impacts to the engine
over its expected operating conditions. Design factors, such as
compression ratio, intake and exhaust value control specifications,
combustion chamber and piston characteristics, among others, are all
impacted by octane (stability) of the fuel consumers are anticipated to
use.\151\
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\151\ Additionally, PRIA Chapter 6 contains a brief discussion
of fuel properties, octane levels used for engine simulation and in
real-world testing, and how octane levels can impact performance
under these test conditions.
---------------------------------------------------------------------------
Vehicle manufacturers typically develop their engines and engine
control system calibrations based on the fuel available to consumers.
In many cases, manufacturers may recommend a fuel grade for best
performance and to prevent potential damage. In some cases,
manufacturers may require a specific fuel grade for both best
performance and/or to prevent potential engine damage.
Consumers, though, may or may not choose to follow the
recommendation or requirement for a specific fuel grade. Additionally,
regional fuel availability could also limit consumer choice, or, in the
case of higher elevation regions, present an opportunity for consumers
to use a fuel grade that is below the minimum recommended. As such,
vehicle manufacturers employ strategies for scenarios where a lower
than recommended, or required, fuel grade is used, mitigating engine
damage over the life of a vehicle.
When knock (also referred to as detonation) is encountered during
engine operation, at the most basic level, non-turbo charged engines
can reduce or eliminate knock by adjusting the timing of the spark that
ignites the fuel, as well as the amounts of fuel injected at each
intake stroke (``fueling''). In turbo-charged applications, boost
levels are typically reduced along with spark timing and fueling
adjustments. Past rulemakings have also discussed other techniques that
may be employed to allow higher compression ratios, more optimal spark
timing to be used without knock, such as the addition of cooled exhaust
gas recirculation (EGR). Regardless of the type of spark-ignition
engine or technology employed, reducing or preventing knock results in
the loss of potential power output, creating a ``knock-limited''
constraint on performance and efficiency.
Despite limits imposed by available fuel grades, manufacturers
continue to make progress in extracting more power and efficiency from
spark-ignited engines. Production engines are safely operating with
regular 87 AKI fuel with compression ratios and boost levels once
viewed as only possible with premium fuel. According to the Department
of Energy, the average gasoline octane level has remained fundamentally
flat starting in the early 1980's and decreased slightly starting in
the early 2000s. During this time, however, the average compression
ratio for the U.S. fleet has increased from 8.4 to 10.52, a more than
20% increase, yielding the statement that, ``There is some concern that
in the future, auto manufacturers will reach the limit of technological
increases in compression ratios without further increases in the octane
of the fuel.'' \152\
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\152\ Fact of the Week, Fact #940: August 29, 2016 Diverging
Trends of Engine Compression Ratio and Gasoline Octane Rating, U.S.
Department of Energy, https://www.energy.gov/eere/vehicles/fact-940-august-29-2016-diverging-trends-engine-compression-ratio-and-gasoline-octane (last visited Mar. 21, 2018).
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As such, manufacturers are still limited by the available fuel
grades to consumers and the need to safeguard the durability of their
products for all of the available fuels; thus, the potential
[[Page 43041]]
improvement in the design of spark-ignition engines continues to be
overshadowed by the fuel grades available to consumers.
(c) Potential of Higher Octane Fuels
Automakers and advocacy groups have expressed support for increases
to fuel octane levels for the U.S. market and are actively
participating in Department of Energy research programs on the
potential of higher octane fuel usage.153 154 Some positions
for potential future octane levels include advocacy for today's premium
grade becoming the base grade of fuel available, which could enable low
cost design changes that would improve fuel economy and CO2.
Challenges associated with this approach include the increased fuel
cost to consumers who drive vehicles designed for current regular
octane grade fuel that would not benefit from the use of the higher
cost higher octane fuel. The net costs for a shift to higher octane
fuel would persist well into the future. Net benefits for the
transition would not be achieved until current regular octane fuel is
not available in the North American market, causing manufacturers to
redesign all engines to operate the higher octane fuel, and then after
those vehicles have been in production a sufficient number of model
years to largely replace the current on-road vehicle fleet. The
transition to net positive benefits could take many years.
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\153\ Mark Phelan, High octane gas coming--but you'll pay more
for it, Detroit Free Press (Apr. 25, 2017), https://www.freep.com/story/money/cars/mark-phelan/2017/04/25/new-gasoline-promises-lower-emissions-higher-mpg-and-cost-octane-society-of-automotive-engineers/100716174/.
\154\ The octane game: Auto industry lobbies for 95 as new
regular, Automotive News (April 17, 2018), http://www.autonews.com/article/20180417/BLOG06/180419780/the-octane-game-auto-industry-lobbies-for-95-as-new-regular.
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In anticipation of this proposed rulemaking, organizations such as
the High Octane Low Carbon Alliance (HOLC) and the Fuel Freedom
Foundation (FFA), have shared their positions on the potential for
making higher octane fuels available for the U.S. market. Other
stakeholders also commented to past NHTSA rulemakings and/or the Draft
TAR regarding the potential for increasing octane levels for the U.S.
market.
In the meetings with HOLC and the FFA, the groups advocated for the
potential benefits high octane fuels could provide via the blending of
non-petroleum feedstocks to increase octane levels available at the
pump. The groups' positions on benefits took both a technical approach
by suggesting an octane level of 100 is desired for the marketplace, as
well as, the benefits from potential increased national energy security
by reduced dependencies on foreign petroleum.
(d) Fuel Octane--Request for Comments
Please comment on the potential benefits, or dis-benefits, of
considering the impacts of increased fuel octane levels available to
consumers for purposes of the model. More specifically, please comment
on how increasing fuel octane levels would play a role in product
offerings and engine technologies. Are there potential improvements to
fuel economy and CO2 reductions from higher octane fuels?
Why or why not? What is an ideal octane level for mass-market
consumption balanced against cost and potential benefits? What are the
negatives associated with increasing the available octane levels and,
potentially, eliminating today's lower octane fuel blends? Please
provide supporting data for your position(s).
6. Transmission Technologies
Transmissions transmit torque from the engine to the wheels.
Transmissions may improve fuel efficiency primarily through two
mechanisms: (1) Transmissions with more gears allow the engine to
operate more regularly at the most efficient speed-load points, and (2)
transmissions may have improvements in friction (gears, bearings,
seals, and so on), or improvements in shift efficiency that help the
transmission transfer torque more efficiently, lowering parasitic
losses. These mechanisms are very different, so full-vehicle simulation
is helpful to understand how a transmission may work with complementary
equipment to improve fuel economy.
Today's analysis significantly increased the number of
transmissions modeled in full-vehicle simulations, attempting to more
closely align the Department of Energy full-vehicle simulations with
existing vehicles. Previously, EPA included just five transmissions
\155\ by vehicle class in their analysis, and often EPA represented
upgrades among manual, automatic, continuously variable, and dual
clutch transmissions with the same effectiveness \156\ and cost values
\157\ within a vehicle class. Today's analysis simulated nearly 20
transmissions, with explicit assumptions about gear ratios, gear
efficiencies, gear spans, shift logic, and transmission
architecture.158 159 This analysis improves transparency by
making clear the assumptions underlying the transmissions in the full-
vehicle simulations and by increasing the number of transmissions
simulated since the Draft TAR. Methods will be continuously evaluated
to improve transmission models in full-vehicle simulations. For the box
plots of effectiveness values, as shown in the PRIA Chapter 6, all
automatic transmissions are relative to a 5-speed automatic, and all
manual transmissions are relative to a 5-speed manual. Table II-11
below shows the absolute costs of transmission used for this analysis
including learning and retail price equivalent.
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\155\ Null, TRX11, TRX12, TRX21, TRX22.
\156\ Draft TAR, p. 5-297 through 5-298 summarizes effectiveness
values previously assumed for stepping between transmission
technologies (Null, TRX11, TRX12, TRX21, TRX22).
\157\ Draft TAR, p. 5-299. ``For future vehicles, it was assumed
that the costs for transitioning from one technology level (TRX11-
TRX22) to another level is the same for each transmission type (AT,
AMT, DCT, and CVT).''
\158\ See PRIA Chapter 6.3.
\159\ Ehsan, I.S., Moawad, A., Kim, N., & Rousseau, A. ``A
Detailed Vehicle Simulation Process To Support CAFE Standards.''
ANL/ESD-18/6. Energy Systems Division, Argonne National Laboratory.
2018.
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[[Page 43042]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.026
(a) Automatic Transmissions
Five-, six-, seven-, eight-, nine- and ten-speed automatic
transmissions are optimized by changing the gear ratios to enable the
engine to operate in a more efficient operating range over a broader
range of vehicle operating conditions. While a six speed transmission
application was most prevalent for the MYs 2012-2016 final rule, eight
and higher speed transmissions were more prevalent in the MY 2016
fleet.
``L2'' and ``L3'' transmissions designate improved gear efficiency
and reduced parasitic losses. Few transmissions in the MY 2016 fleet
have achieved ``L2'' efficiency, and the highest level of transmission
efficiencies modeled are assumed to be available in MY 2022.
(1) Continuously Variable Transmissions
Continuously variable transmission (CVT) commonly uses V-shaped
pulleys connected by a metal belt rather than gears to provide ratios
for operation. Unlike manual and automatic transmissions with fixed
transmission ratios, continuously variable transmissions can provide
fully variable and an infinite number of transmission
[[Page 43043]]
ratios that enable the engine to operate in a more efficient operating
range over a broader range of vehicle operating conditions. In this
NPRM, two levels of CVTs are considered for future vehicles. The second
level CVT would have a wider transmission ratio, increased torque
capacity, improvements in oil pump efficiency, lubrication
improvements, and friction reduction. While CVTs work well with light
loads, the technology as modeled is not suitable for larger vehicles
such as trucks and large SUVs.
(2) Dual Clutch Transmissions
Dual clutch or automated shift manual transmissions (DCT) are
similar to manual transmissions except for the vehicle controls
shifting and launch functions. A dual-clutch automated shift manual
transmission uses separate clutches for even-numbered and odd-numbered
gears, so the next expected gear is pre-selected, which allows for
faster and smoother shifting. The 2012-2016 final rule limited DCT
applications to a maximum of 6-speeds. Both 6-speed and 8-speed DCT
transmissions are considered in today's proposal.
Dual clutch transmissions are very effective transmission
technologies, and previous rule-making projected rapid, and wide
adoption into the fleet. However, early DCT product launches in the
U.S. market experienced shift harshness and poor launch performance,
resulting in customer satisfaction issues--some so extreme as to prompt
vehicle buyback campaigns.\160\ Most manufacturers are not using DCTs
in the U.S. market due to the customer satisfaction issues.
Manufacturers used DCTs in about three percent of the MY 2016 fleet.
Today's analysis limits the application of improved DCTs to vehicles
that already use DCTs. Many of these vehicles are imported performance
products.
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\160\ Ford Powershift Transmission Settlement, http://fordtransmissionsettlement.com/ (last visited June 21, 2018).
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(b) Manual Transmissions
Manual 6- and 7-speed transmissions offer an additional gear ratio,
sometimes with a higher overdrive gear ratio, over a 5-speed manual
transmission. Similar to automatic transmissions, more gears often
means the engine may operate in the efficient zone more frequently.
7. Vehicle Technologies
As discussed earlier in Section II.D.1.b)(1), several technologies
were considered for this analysis, and Table II-12, Table II-13, and
Table II-14 below shows the full list of vehicle technologies analyzed
and the associated absolute cost.\161\
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\161\ Mass reduction costs are in $/lb.
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[[Page 43044]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.027
[[Page 43045]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.028
[[Page 43046]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.029
(a) Reduced Rolling Resistance
Lower-rolling-resistance tires have characteristics that reduce
frictional losses associated with the energy dissipated mainly in the
deformation of the tires under load, thereby improving fuel economy and
reducing CO2 emissions. New for this proposal, and also
marking an advance over low rolling resistance tires considered during
the heavy duty greenhouse gas rulemaking,\162\ is a second level of
lower rolling resistance tires that reduce frictional losses even
further. The first level of low rolling resistance tires will have 10%
rolling resistance reduction while the second level would have 20%
rolling resistance reduction. In this NPRM, baseline vehicle reference
rolling resistance values were determined based on the MY 2016 vehicles
rather than the MY 2008 vehicles used in the 2012 final rule. Rolling
resistance values were assigned based on CBI shared by manufacturers.
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\162\ See 76 FR 57106, at 57207, 57229 (Sep. 15, 2011).
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In some cases, low rolling resistance tires can affect traction,
which may be untenable for some high performance vehicles. For cars and
SUVs with more than 405 horsepower, the analysis restricted the
application of the highest levels of rolling resistance. For cars and
SUVs with more than 500 horsepower, the analysis restricted the
application of any additional rolling resistance technology.
(b) Reduced Aerodynamic Drag Coefficient
Aerodynamic drag reduction can be achieved via two approaches,
either by reducing the drag coefficients or reducing vehicle frontal
area. To reduce the drag coefficient, skirts, air dams, underbody
covers, and more aerodynamic side view mirrors can be applied. In the
MY 2017-2025 final rule and the 2016 Draft TAR, the analysis included
two levels of aerodynamic technologies. The second level included
active grille shutters, rear visors, and larger under body panels. This
NPRM expanded the aerodynamic drag improvements from two levels to four
to provide more discrete levels. The NPRM levels are 5%, 10%, 15%, and
20%
[[Page 43047]]
improvement relative to baseline reference vehicles. The agencies
relied on the wind tunnel testing performed by National Research
Council (NRC), Canada, Transport Canada (TC), and Environment and
Climate Change, Canada (ECCC) to quantify the aerodynamic drag impacts
of various OEM aerodynamic technologies and to explore the improvement
potential of these technologies by expanding the capability and/or
improving the design of MY 2016 state-of-the-art aerodynamic
treatments. The agencies estimated the level of aerodynamic drag in
each vehicle model in the MY 2016 baseline fleet and gathered CBI on
aerodynamic drag coefficients, so each vehicle has an appropriate
initial value for further improvements.
Notably, today's analysis assumes aerodynamic drag reduction can
only come from reduction in the aerodynamic drag coefficient and not
from reduction of frontal area.\163\ For some bodystyles, the agencies
have no evidence that manufacturers may be able to achieve 15% or 20%
aerodynamic drag coefficient reduction relative to baseline for some
bodystyles (for instance, with pickup trucks) due to form drag
limitions. Previously, EPA analysis assumed some vehicles from all
bodystyles could (and would) reduce aerodynamic forces by 20%, which in
some cases led to future pickup trucks having aerodynamic drag
coefficients better than some of today's typical cars, if frontal area
were held constant. While ANL created full-vehicle simulations for
trucks with 20% drag reduction, those simulations were not used in the
CAFE modeling. That level of drag reduction is likely not
technologically feasible with today's technology, and the analysis
accordingly restricted the application of advanced levels of
aerodynamics in some instances, such as in this case, due to bodystyle
form drag limitations. Separate from form drag limitations, some high
performance vehicles already use advanced aerodynamics technologies to
generate down force, and sometimes these applications must trade-off
between aerodynamic drag coefficient reduction and down force. Today's
analysis does not apply 15% or 20% aerodynamic drag coefficient
reduction to cars and SUVs with more than 405 horsepower.
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\163\ EPA previously assumed that manufacturers could reduce
frontal area as well as aerodynamic drag coefficient to achieve 20%
aerodynamic force reduction relative to ``Null'' or initial
aerodynamic technology level; however, reducing frontal area would
likely degrade other utility features like interior volume, or
ingress/egress.
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(c) Mass Reduction
Mass Reduction can be achieved in many ways, such as material
substitution, design optimization, part consolidation, improving
manufacturing process, etc. The analysis utilizes mass reduction levels
of 5, 10, 15, and 20% relative to a reference glider vehicle for each
vehicle subsegment. For HEV, PHEV, and BEV vehicles, net mass reduction
was considered, including the mass reduction applied to the glider and
the added mass of electrification components. An extensive discussion
of mass reduction technologies as well as the cost of mass reduction is
located in Chapter 6.3 of the PRIA. The analysis included an estimated
level of mass reduction technology in each vehicle model in the MY 2016
baseline fleet so that each vehicle model has an appropriate initial
value for further improvements.
(d) Low Drag Brakes (LDB)
Low-drag brakes reduce the sliding friction of disc brake pads on
rotors when the brakes are not engaged because the brake pads are
pulled away from the rotors.
(e) Secondary Axle Disconnect (SAX)
Front or secondary axle disconnect for all-wheel drive systems
provides a torque distribution disconnect between front and rear axles
when torque is not required for the non-driving axle. This results in
the reduction of associated parasitic energy losses.
8. Electrification Technologies
For this NPRM, the analysis of electrification technologies relies
primarily on research published by the Department of Energy, ANL.\164\
ANL's assumptions regarding all hybrid systems, including belt-
integrated starter generators, strong parallel and series hybrids,
plug-in hybrids,\165\ and battery electric vehicles, and most projected
technology costs were adopted for this analysis. In addition, the most
recent ANL BatPaC model is used to estimate battery costs. Table II-15
and Table II-16 below show the absolute costs of all electrification
technologies estimated for this NPRM analysis relative to a basic
internal combustion engine vehicle with a 5-speed automatic
transmission.\166\
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\164\ Moawad et al., Assessment of vehicle sizing, energy
consumption, and cost through large-scale simulation of advanced
engine technologies, Argonne National Laboratory (March 2016),
available at https://www.autonomie.net/pdfs/Report%20ANL%20ESD-1528%20-%20Assessment%20of%20Vehicle%20Sizing,%20Energy%20Consumption%20and%20Cost%20through%20Large%20Scale%20Simulation%20of%20Advanced%20Vehicle%20Technologies%20-%201603.pdf.
\165\ Notably all power split hybrids, and all plug-in hybrid
vehicles were assumed to be paired with a high compression ratio
internal combustion engine for this analysis.
\166\ Note: These costs do not include value loss for HEVs,
PHEVs, and BEVs. Powertrain hardware between cars and small SUV's is
often similar, especially if technology is used vehicles on the same
platform; however, battery pack sizes may vary meaningfully to
deliver similar range in different applications.
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[[Page 43048]]
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[GRAPHIC] [TIFF OMITTED] TP24AU18.031
[[Page 43049]]
(a) Hybrid Technologies
(1) 12-Volt Stop-Start
12-volt Stop-Start, sometimes referred to as idle-stop or 12-volt
micro hybrid, is the most basic hybrid system that facilitates idle-
stop capability. These systems typically incorporate an enhanced
performance battery and other features such as electric transmission
pump and cooling pump to maintain vehicle systems during idle-stop.
(2) Higher Voltage Stop-Start/Belt Integrated Starter Generator
Higher Voltage Stop-Start/Belt Integrated Starter Generator (BISG),
sometimes referred to as a mild hybrid system, provides idle-stop
capability and uses a higher voltage battery with increased energy
capacity over typical automotive batteries. The higher system voltage
allows the use of a smaller, more powerful electric motor. This system
replaces a standard alternator with an enhanced power, higher voltage,
higher efficiency starter-alternator, that is belt driven and that can
recover braking energy while the vehicle slows down (regenerative
braking). Today's analysis assumes 48V systems on cars and small SUVs
and high voltage systems for large SUVs and trucks. Future analysis may
reference the application and operation of 48V systems on large SUVs
and trucks, if applicable.
(3) Integrated Motor Assist (IMA)/Crank Integrated Starter Generator
Integrated Motor Assist (IMA)/Crank integrated starter generator
(CISG) provides idle-stop capability and uses a high voltage battery
with increased energy capacity over typical automotive batteries. The
higher system voltage allows the use of a smaller, more powerful
electric motor and reduces the weight of the wiring harness. This
system replaces a standard alternator with an enhanced power, higher
voltage, higher efficiency starter alternator that is crankshaft-
mounted and can recover braking energy while the vehicle slows down
(regenerative braking).
(4) P2 Hybrid
P2 Hybrid (SHEVP2) is a newly emerging hybrid technology that uses
a transmission-integrated electric motor placed between the engine and
a gearbox or CVT, much like the IMA system described above except with
a wet or dry separation clutch that is used to decouple the motor/
transmission from the engine. In addition, a P2 hybrid would typically
be equipped with a larger electric machine. Disengaging the clutch
allows all-electric operation and more efficient brake-energy recovery.
Engaging the clutch allows efficient coupling of the engine and
electric motor and, when combined with a DCT transmission, reduces
gear-train losses relative to power-split or 2-mode hybrid systems.
Battery costs are now considered separately from other HEV hardware.
P2 Hybrid systems typically rely on the internal combustion engine
to deliver high, sustained power levels. While many vehicles may use
HCR1 engines as part of a hybrid powertrain, HCR1 engines may not be
suitable for all vehicles, especially high performance vehicles, or
vehicles designed to carry or tow large loads. Many manufacturers may
prefer turbo engines (with high specific power output) for P2 Hybrid
systems.
(5) Power-Split Hybrid
Power-split Hybrid (SHEVPS) is a hybrid electric drive system that
replaces the traditional transmission with a single planetary gearset
and a motor/generator. This motor/generator uses the engine to either
charge the battery or supply additional power to the drive motor. A
second, more powerful motor/generator is permanently connected to the
vehicle's final drive and always turns with the wheels. The planetary
gear splits engine power between the first motor/generator and the
drive motor to either charge the battery or supply power to the wheels.
The power-split hybrid technology is included in this analysis as an
enabling technology supporting this proposal, (the agencies evaluate
the P2 hybrid technology discussed above where power-split hybrids
might otherwise have been appropriate). As stated above, battery costs
are now considered separately from other HEV hardware. Power-split
hybrid technology as modeled in this analysis is not suitable for large
vehicles that must handle high loads.
The ANL Autonomie simulations assumed all power-split hybrids use a
high compression ratio engine. Therefore, all vehicles equipped with
SHEVPS technology in the CAFE model inputs and simulations are assumed
to have high compression ratio engines.
(6) Plug-in Hybrid Electric
Plug-in hybrid electric vehicles (PHEV) are hybrid electric
vehicles with the means to charge their battery packs from an outside
source of electricity (usually the electric grid). These vehicles have
larger battery packs with more energy storage and a greater capability
to be discharged than other hybrid electric vehicles. They also use a
control system that allows the battery pack to be substantially
depleted under electric-only or blended mechanical/electric operation
and batteries that can be cycled in charge sustaining operation at a
lower state of charge than is typical of other hybrid electric
vehicles. These vehicles are sometimes referred to as Range Extended
Electric Vehicles (REEV). In this NPRM analysis, PHEVs with two all-
electric ranges--both a 30 mile and a 50 mile all-electric range--have
been included as potential technologies. Again, battery costs are now
considered separately from other PHEV hardware.
The ANL Autonomie simulations assumed all PHEVs use a high
compression ratio engine. Therefore, all vehicles equipped with PHEV
technology in the CAFE model inputs and simulations are assumed to have
high compression ratio engines. In practice, many PHEVs recently
introduced in the marketplace use turbo-charged engines in the PHEV
system, and this is particularly true for PHEVs produced by European
manufacturers and for other PHEV performance vehicle applications.
Please provide comment on the modeling of PHEV systems. Should
turbo PHEVs be considered instead, or in addition to high compression
ratio PHEVs? Why or why not? What vehicle segments may turbo PHEVs best
be suited for, and which segments would it not be best suited for? What
vehicle segments may high compression ratio PHEVs best be suited for,
and which segments would it not be best suited for? Similarly, the
analysis currently considers PHEVs with 30-mile and 50-mile all-
electric range, and should other ranges be considered? For instance, a
20-mile all-electic range may decrease the battery pack size, and hence
the battery pack cost relative to a 30-mile all-electric range system,
while still providing electric-vehicle functionality in many
applications. Do commenters believe PHEV technology will see widespread
adoption in the US vehicle fleet? Why or why not? Please provide
supporting data.
(b) Full Electrification and Fuel Cell Vehicles
(1) Battery Electric
Electric vehicles (EV) are equipped with all-electric drive and
with systems powered by energy-optimized batteries charged primarily
from grid electricity. EVs with range of 200 miles have been included
as a potential technology in this NPRM. Battery costs are now
considered separately from other EV hardware.
[[Page 43050]]
(2) Fuel Cell Electric
Fuel cell electric vehicles (FCEVs) utilize a full electric drive
platform but consume electricity generated by an onboard fuel cell and
hydrogen fuel. Fuel cells are electrochemical devices that directly
convert reactants (hydrogen and oxygen via air) into electricity, with
the potential of achieving more than twice the efficiency of
conventional internal combustion engines. High pressure gaseous
hydrogen storage tanks are used by most automakers for FCEVs. The high
pressure tanks are similar to those used for compressed gas storage in
more than 10 million CNG vehicles worldwide, except that they are
designed to operate at a higher pressure (350 bar or 700 bar vs. 250
bar for CNG). FCEVs are currently produced in limited numbers and are
available in limited geographic areas.
(c) Electric Vehicle Infrastructure
BEVs and PHEVs may be charged at home or elsewhere. Home chargers
may access electricity from a regular wall outlet, or they may require
special equipment to be installed at the home. Commercial chargers may
sometimes be found at businesses or other travel locations. These
chargers often may supply power to the vehicle at a faster rate of
charge but often require significant capital investment to install.
Time to charge, and availability and convenience of charging are
significant factors for plug-in vehicle operators. For many consumers,
accessible charging stations present inconveniences that may deter the
adoption of battery electric and plug-in hybrid vehicles.
More detail about charging and charging infrastructure, including a
discussion of potential electric vehicle impacts on the electric grid,
is available in the PRIA, Chapter 6. For today's analysis, costs for
installing chargers and charge convenience is not taken into account in
the CAFE model. Also, today's analysis assumes HEVs, PHEVs, and BEVs
have the same survival rates and mileage accumulation schedules as
vehicles with conventional powertrains, and that HEVs, PHEVs, and BEVs
never receive replacement batteries before being scrapped. The agencies
invite comment on these assumptions and on data and practicable methods
to implement any alternatives.
9. Accessory Technologies
Two accessory technologies, electric power steering (EPS) and
improved accessories (IACC) (accessory technologies categorized for the
2012 rule) were considered in this analysis, and are described
below.\167\ Table II-17 and Table II-18 below shows the estimated
absolute costs including learning effects and retail price equivalent
utilized in today's analysis.
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\167\ For further discussion of accessory technologies, see
Chapter 6 of the PRIA accompanying this NPRM.
[GRAPHIC] [TIFF OMITTED] TP24AU18.032
[GRAPHIC] [TIFF OMITTED] TP24AU18.033
(a) Electric Power Steering (EPS)
Electric power steering (EPS)/Electrohydraulic power steering
(EHPS) is an electrically-assisted steering system that has advantages
over traditional hydraulic power steering because it replaces a
continuously operated hydraulic pump, thereby reducing parasitic losses
from the accessory drive. Manufacturers have informed the agencies that
full EPS systems are being developed for all types of light-duty
vehicles, including large trucks. However, this analysis applies the
EHPS technology to large trucks and the EPS technology to all other
light-duty vehicles.
[[Page 43051]]
(b) Improved Accessories (IACC)
Improved accessories (IACC) may include high efficiency
alternators, electrically driven (i.e., on-demand) water pumps,
variable geometry oil pumps, cooling fans, a mild regeneration
strategy, and high efficiency alternators. It excludes other electrical
accessories such as electric oil pumps and electrically driven air
conditioner compressors. In the MY 2017-2025 final rule, two levels of
IACC were offered as a technology path (a low improvement level and a
high improvement level). Since much of the market has incorporated some
of these technologies in the MY 2016 fleet, the analysis assumes all
vehicles have incorporated what was previously the low level, so only
the high level remains as an option for some vehicles.
10. Other Technologies Considered but Not Included in This Aanalysis
Manufacturers, suppliers, and researchers continue to create a
diverse set of fuel economy technologies. Many high potential
technologies that are still in the early stages of the development and
commercialization process are still being evaluated for any final
analysis. Due to uncertainties in the cost and capabilities of emerging
technologies, some new and pre-production technologies are not yet a
part of the CAFE model simulation. Evaluating and benchmarking
promising fuel economy technologies continues to be a priority as
commercial development matures.
(a) Engine Technologies
Variable compression ratio (VCR)--varies the compression
ratio and swept volume by changing the piston stroke on all cylinders.
Manufacturers accomplish this by changing the effective length of the
piston connecting rod, with some prototypes having a range of 8:1 to
14:1 compression ratio. In turbocharged form, early publications
suggest VCR may be possible to deliver up to 35% improved efficiency
over the existing equivalent-output naturally-aspirated engine.\168\
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\168\ See e.g., VC--Turbo--The world's first production-ready
variable compression ratio engine, Nissan Motor Corporation (Dec.
13, 2017), https://newsroom.nissan-global.com/releases/release-917079cb4af478a2d26bf8e5ac00ae49-vc-turbo-the-worlds-first-production-ready-variable-compression-ratio-engine.
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Opposed-piston engine--sometimes known as opposed-piston
opposed-cylinder (OPOC), operates with two pistons per cylinder working
in opposite reciprocal motion and running on a two-stroke combustion
cycle. It has no cylinder head or valvetrain but requires a
turbocharger and supercharger for engine breathing. The efficiency may
be significantly higher than MY 2016 turbocharged gasoline engines with
competitive costs. This engine architecture could run on many fuels,
including gasoline and diesel. Packaging constraints, emissions
compliance, and performance across a wide range of operating conditions
remain as open considerations. No production vehicles have been
publicly announced, and multiple manufacturers continue to evaluate the
technology.169 170
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\169\ Murphy, T. Achates: Opposed-Piston Engine makers tooling
up, Wards Auto (Jan. 23, 2017), http://wardsauto.com/engines/achates-opposed-piston-engine-makers-tooling.
\170\ Our Formula, Achates Power, http://achatespower.com/our-formula/opposed-piston/ (last visited June 21, 2018).
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Dual-fuel--engine concepts such as reactivity controlled
compression ignition (RCCI) combine multiple fuels (e.g. gasoline and
diesel) in cylinder to improve brake thermal efficiency while reducing
NOX and particulate emissions. This technology is still in
the research phase.\171\
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\171\ Robert Wagner, Enabling the Next Generation of High
Efficiency Engines, Oak Ridge National Laboratory, U.S. Department
of Energy (2012), available at https://www.energy.gov/sites/prod/files/2014/03/f8/deer12_wagner_0.pdf.
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Smart accessory technologies--can improve fuel efficiency
through smarter controls of existing systems given imminent or expected
controls inputs in real world driving conditions. For instance, a
vehicle could adjust the use of accessory systems to conserve energy
and fuel as a vehicle approaches a red light. Vehicle connectivity and
sensors can further refine the operation for more benefit and smoother
operation.\172\
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\172\ EfficientDynamics--The intelligent route to lower
emissions, BMW Group (2007), https://www.bmwgroup.com/content/dam/bmw-group-websites/bmwgroup_com/responsibility/downloads/en/2007/Alex_ED__englische_Version.pdf.
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High Compression Miller Cycle Engine with Variable
Geometry Turbocharger or Electric Supercharger--Atkinson cycle gasoline
engines with sophisticated forced induction system that requires
advanced controls. The benefits of these technologies provide better
control of EGR rates and boost which is achieved with electronically
controlled turbocharger or supercharger. The electric version of this
technology which incorporates 48V is called E-boost.173 174
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\173\ Volkswagen at the 37th Vienna Motor Symposium, Volkswagen
(Apr. 28, 2016), https://www.volkswagen-media-services.com/en/detailpage/-/detail/Volkswagen-at-the-37th-Vienna-Motor-Symposium/view/3451577/5f5a4dcc90111ee56bcca439f2dcc518?p_p_auth=M2yfP3Ze.
\174\ These engines may be considered in the analysis supporting
the final rule, but these engine maps were not available in time for
the NPRM analysis. Please see Chapter 6.3 of the PRIA accompanying
this proposal for more information.
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(b) Electrified Vehicle Powertrain
Advanced battery chemistries--many emerging battery
technologies promise to eventually improve the cost, safety, charging
time, and durability in comparison to the MY 2016 automotive lithium-
ion batteries. For instance, many view solid state batteries as a
promising medium-term automotive technology. Solid state batteries
replace the battery's liquid electrolyte with a solid electrolyte to
potentially improve safety, power and energy density, durability, and
cost. Some variations use ceramic, polymer, or sulfide-based solid
electrolytes. Multiple automakers and suppliers are exploring the
technology and possible commercialization that may occur in the early
2020s.175 176 177
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\175\ Schmitt, B. Ultrafast-Charging Solid-State EV Batteries
Around The Corner, Toyota Confirms, Forbes (Jul. 25, 2017), https://www.forbes.com/sites/bertelschmitt/2017/07/25/ultrafast-charging-solid-state-ev-batteries-around-the-corner-toyota-confirms/#5736630244bb.
\176\ Moving toward clean mobility, Robert Bosch GmbH, https://www.bosch.com/explore-and-experience/moving-toward-clean-mobility/
(last visited June 21, 2018).
\177\ Reuters Staff, Honda considers developing all solid-state
EV batteries, Reuters (Dec. 21, 2017), https://www.reuters.com/article/us-honda-nissan/honda-considers-developing-all-solid-state-ev-batteries-idUSKBN1EF0FM.
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Supercapacitors/Ultracapacitors--An electrical energy
storage device with higher power density but lower energy density than
batteries. Advanced capacitors may reduce battery degradation
associated with charge and discharge cycles, with some tradeoffs to
cost and engineering complexity. Supercapacitors/Ultracapacitors are
currently not used in parallel or as a standalone traction motor energy
storage device.\178\
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\178\ Burke, A. & Zhao,H. Applications of Supercapacitors in
Electric and Hybrid Vehicles, Institute of Transportation Studies
University of California, Davis (Apr. 2015), available at https://steps.ucdavis.edu/wp-content/uploads/2017/05/2015-UCD-ITS-RR-15-09-1.pdf.
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Motor/Drivetrain:
[cir] Lower-cost magnets for Brushless Direct Current (BLDC)
motors--BLDC motor technology, common in hybrid and battery electric
vehicles, uses rare earth magnets. By substituting and eliminating rare
earths from the magnets, motor cost can be significantly reduced. This
technology is announced, but not yet in production. The capability and
material configuration of these systems remains a closely guarded trade
secret.\179\
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\179\ Buckland, K. & Sano, N. Toyota Readies Cheaper Electric
Motor by Halving Rare Earth Use, Bloomberg (Feb, 20, 2018), https://www.bloomberg.com/news/articles/2018-02-20/toyota-readies-cheaper-electric-motor-by-halving-rare-earth-use.
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[[Page 43052]]
[cir] Integrated multi-phase integrated electric vehicle
drivetrains. Research has been conducted on 6-phase and 9-phase
integrated systems to potentially reduce cost and improve power
density. Manufacturers may improve system power density through
integration of the motor, inverter, control, and gearing. These systems
are in the research phase.180 181
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\180\ Burkhardt, Y., Spagnolo, A., Lucas, P., Zavesky, M., &
Brockerhoff, P. ``Design and analysis of a highly integrated 9-phase
drivetrain for EV applications '' 20 November 2014. DOI. 10.1109/
ICELMACH.2014.6960219. IEEE xplore.
\181\ Patel, V., Wang, J., Nugraha, D., Vuletic, R., & Tousen,
J. ``Enhanced Availability of Drivetrain Through Novel Multi-Phase
Permanent Magnet Machine Drive'' 2016. IEEE Transactions on
Industrial Electronics Pages. 469-480.
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(c) Transmission Technologies
Beltless CVT--Most MY 2016, commercially available CVTs
rely on belt technology. A new architecture of CVT replaces belts or
pulleys with a continuously variable variator, which is a special type
of planetary set with balls and rings instead of gears. The technology
promises to improve efficiency, handle higher torques, and change modes
more quickly. This technology may be commercially available as early as
2020.\182\
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\182\ Murphy, T. Planets Aligning for Dana's VariGlide Beltless
CVT, Wards Auto (Aug. 22, 2017), http://wardsauto.com/technology/planets-aligning-dana-s-variglide-beltless-cvt.
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Multi-speed electric motor transmission--MY 2016 battery
electric vehicle transmissions are single-speed. Multiple gears can
allow for more torque multiplication at lower speeds or a downsized
electric machine, increased efficiency, and higher top speed. Two-speed
transmission designs are available but not currently in
production.\183\
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\183\ Faid, S. A Highly Efficient Two Speed Transmission for
Electric Vehicles (May 2015), available at http://www.evs28.org/event_file/event_file/1/pfile/EVS28_Saphir_Faid.pdf.
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(d) Energy-Harvesting Technology
Vehicle waste heat recovery systems--Internal combustion
engines convert the majority of the fuel's energy to heat.
Thermoelectric generators and heat pipes can convert this heat to
electricity.\184\ Thermoelectric generators, often made of
semiconductors, have been tested by automakers but have traditionally
not been implemented due to low efficiency and high cost.\185\ These
systems are not yet in production.
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\184\ Orr et al., A review of car waste heat recovery systems
utilising thermoelectric generators and heat pipes, 101 Applied
Thermal Engineering 490-495 (May 25, 2016).
\185\ Patel, P. Powering Your Car with Waste Heat, MIT
Technology Review (May 25, 2011), https://www.technologyreview.com/s/424092/powering-your-car-with-waste-heat/.
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Suspension energy recovery--Multiple electromechanical and
electrohydraulic suspension technologies exist that can convert motion
from uneven roads into electricity.186 187 These
technologies are limited to luxury vehicles with limited production
volumes. This technology is not produced in 2016 but planned for
production as early as 2018.\188\
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\186\ Baeuml, B. et al., The Chassis of the Future, Schaeffler,
https://www.schaeffler.com/remotemedien/media/_shared_media/08_media_library/01_publications/schaeffler_2/symposia_1/downloads_11/Schaeffler_Kolloquium_2014_27_en.pdf (last visited June
21, 2018).
\187\ Advanced Suspension, Tenneco, http://www.tenneco.com/overview/rc_advanced_suspension/ (last visited June 21, 2018).
\188\ Audi A8 Active Chassis, Audi, https://www.audi.com/en/innovation/design/more_personal_comfort_a8_active_chassis.html (last
visited June 21, 2018).
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11. Air Conditioning Efficiency and Off-Cycle Technologies
(a) Air Conditioning Efficiency Technologies
Air conditioning (A/C) is a virtually standard automotive
accessory, with more than 95% of new cars and light trucks sold in the
United States equipped with mobile air conditioning (MAC) systems. Most
of the additional air conditioning related load on an engine is due to
the compressor, which pumps the refrigerant around the system loop. The
less the compressor operates or the more efficiently it operates, the
less load the compressor places on the engine, and the better fuel
consumption will be. This high penetration means A/C systems can
significantly impact energy consumed by the light duty vehicle fleet.
Vehicle manufacturers can generate credits for improved A/C systems
under EPA's GHG program and receive a fuel consumption improvement
value (FCIV) equal to the value of the benefit not captured on the 2-
cycle test under NHTSA's CAFE program.\189\ Table II-19 provides a
``menu'' of qualifying A/C technologies, with the magnitude of each
improvement value or credit estimated based on the expected reduction
in CO2 emissions from the technology.\190\ NHTSA converts
the improvement in grams per mile to a FCIV for each vehicle for
purposes of measuring CAFE compliance. As part of a manufacturer's
compliance data, manufacturers will provide information about which
off-cycle technologies are present on which vehicles (see Section X for
further discussion of reporting off-cycle technology information).
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\189\ 77 FR 62624, 62720 (Oct. 15, 2012).
\190\ 40 CFR 86.1868-12 (2016).
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The 2012 final rule for MYs 2017 and later outlined two test
procedures to determine credit or FCIV eligibility for A/C efficiency
menu credits, the idle test, and the AC17 test. The idle test,
performed while the vehicle is at idle, determined the additional
CO2 generated at idle when the A/C system is operated.\191\
The AC17 test is a four-part performance test that combines the
existing SC03 driving cycle, the fuel economy highway test cycle, and a
pre-conditioning cycle, and solar soak period.\192\ Manufacturers could
use the idle test or AC17 test to determine improvement values for MYs
2014-2016, while for MYs 2017 and later, the AC17 test is the exclusive
test that manufacturers can use to demonstrate eligibility for menu A/C
improvement values.
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\191\ 75 FR 25324, 25431 (May 7, 2010). The A/C CO2
Idle Test is run with and without the A/C system cooling the
interior cabin while the vehicle's engine is operating at idle and
with the system under complete control of the engine and climate
control system.
\192\ 77 FR 62624, 62723 (Oct. 15, 2012).
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In MYs 2020 and later, manufacturers will use the AC17 test to
demonstrate eligibility for A/C credits and to partially quantify the
amount of the credit earned. AC17 test results equal to or greater than
the menu value will allow manufacturers to claim the full menu value
for the credit. A test result less than the menu value will limit the
amount of credit to that demonstrated on the AC17 test. In addition,
for MYs 2017 and beyond, A/C fuel consumption improvement values will
be available for CAFE calculations, whereas efficiency credits were
previously only available for GHG compliance. The agencies proposed
these changes in the 2012 final rule for MYs 2017 and later largely as
a result of new data collected, as well as the extensive technical
comments submitted on the proposal.\193\
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\193\ Id.
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The pre-defined technology menu and associated car and light truck
credit value is shown in Table II-19 below. The regulations include a
definition of each technology that must be met to be eligible for the
menu credit.\194\ Manufacturers are not required to submit any other
emissions data or information beyond meeting the definition and useful
life requirements \195\ to use the pre-defined
[[Page 43053]]
credit value. Manufacturers' use of menu-based credits for A/C
efficiency is subject to a regulatory cap: 5.7 g/mi for cars and trucks
through MY 2016 and separate caps of 5.0 g/mi for cars and 7.2g/mi for
trucks for later MYs.\196\
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\194\ Id. at 62725.
\195\ Lifetime vehicle miles travelled (VMT) for MY 2017-2025
are 195,264 miles and 225,865 miles for passenger cars and light
trucks, respectively. The manufacturer must also demonstrate that
the off-cycle technology is effective for the full useful life of
the vehicle. Unless the manufacturer demonstrates that the
technology is not subject to in-use deterioration, the manufacturer
must account for the deterioration in their analysis.
\196\ 40 CFR 86.1868-12(b)(2) (2016).
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In the 2012 final rule for MYs 2017 and later, the agencies
estimated that manufacturers would employ significant advanced A/C
technologies throughout their fleets to improve fuel economy, and this
was reflected in the stringency of the standards.\197\ Many
manufacturers have since incorporated A/C technology throughout their
fleets, and the utilization of advanced A/C technologies has become a
significant contributor to industry compliance plans. As summarized in
the EPA Manufacturer Performance Report for the 2016 model year,\198\
15 auto manufacturers included A/C efficiency credits as part of their
compliance demonstration in the 2016 MY. These amounted to more than 12
million Mg of fuel consumption improvement values of the total net fuel
consumption improvement values reported. This is equivalent to
approximately four grams per mile across the 2016 fleet. Accordingly, a
significant amount of new information about A/C technology and the
efficacy of test procedures has become available since the 2012 final
rule.
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\197\ See e.g., 77 FR 62623, 62803-62806 (Oct. 15, 2012).
\198\ See Greenhouse Gas Emission Standards for Light-Duty
Vehicles: Manufacturer Performance Report for the 2016 Model Year
(EPA Report 420-R18-002), U.S. EPA (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGIA.pdf.
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The sections below provide a brief history of the AC17 test
procedure for evaluating A/C efficiency improving technology and
discuss stakeholder comments on the AC17 test procedure approach and
discuss A/C efficiency technology valuation through the off-cycle
program.
[[Page 43054]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.034
(1) Evaluation of the AC17 Test Procedure Since the Draft TAR
In developing the AC17 test procedure, the agencies sought to
develop a test procedure that could more reliably generate an
appropriate fuel consumption improvement value based on an ``A'' to
``B'' comparison, that is, a comparison of substantially similar
vehicles in which one has the technology and the other does not.\199\
The agencies believe that the AC17 test procedure is more capable of
detecting the effect of more efficient A/C components and controls
strategies during a transient drive cycle rather than during just idle
(as measured in the old idle test procedure). As described above and in
the 2012 final rule,\200\ the AC17 test is a four-part performance test
that combines the existing SC03 driving
[[Page 43055]]
cycle, the fuel economy highway cycle, as well as a pre-conditioning
cycle, and a solar soak period.
---------------------------------------------------------------------------
\199\ For an explanation of how the agencies, in collaboration
with stakeholders, developed the AC17 test procedure, see the 2017
and later final rule at 77 FR 62624, 62723 (Oct. 15, 2012).
\200\ See 77 FR 62624, 62723 (Oct. 15, 2012); Joint Technical
Support Document: Final Rulemaking for 2017-2025 Light-Duty Vehicle
Greenhouse Gas Emission and Corporate Average Fuel Economy
Standards, U.S. EPA, National Highway Traffic Safety Administration
at 5-40 (August 2012) .
---------------------------------------------------------------------------
The agencies received several comments on the Draft TAR evaluation
of the AC17 test procedure. FCA commented generally that A/C efficiency
technologies ``are not showing their full effect on this AC17 test as
most technologies provide benefit at different temperatures and
humidity conditions in comparison to a standard test conditions. All of
these technologies are effective at different levels at different
conditions. So there is not one size fits all in this very complex
testing approach. Selecting one test that captures benefits of all of
these conditions has not been possible.'' \201\
---------------------------------------------------------------------------
\201\ See Comment by FCA US LLC, Docket ID NHTSA 2016-0068-0082,
at 123-124.
---------------------------------------------------------------------------
The agencies acknowledge that any single test procedure is unlikely
to equally capture the real-world effect of every potential technology
in every potential use case. Both the agencies and stakeholders
understood this difficulty when developing the AC17 test procedure.
While no test is perfect, the AC17 test procedure represents an
industry best effort at identifying a test that would greatly improve
upon the idle test by capturing a greater range of operating
conditions. General industry evaluation of the AC17 test procedure is
in agreement that the test achieves this objective.
FCA also noted that ``[i]t is a major problem to find a baseline
vehicle that is identical to the new vehicle but without the new A/C
technology. This alone makes the test unworkable.'' \202\ The agencies
disagree this makes the test unworkable. The regulation describes the
baseline vehicle as a ``similar'' vehicle, selected with good
engineering judgment (such that the test comparison is not unduly
affected by other differences). Also, OEMs expressed confidence in
using A-to-B testing to qualify for fuel consumption improvement values
for software-based A/C efficiency technologies. While hardware
technologies may pose a greater challenge in locating a sufficiently
similar ``A'' baseline vehicle, the engineering analysis provision
under 40 CFR 86.1868-12(g)(2) provides an alternative to locating and
performing an AC17 test on such a vehicle. Further, as the USCAR
program in general and the GM Denso SAS compressor application
specifically have shown, the test is able to resolve small differences
in CO2 effectiveness (1.3 grams in the latter case) when
carefully conducted.
---------------------------------------------------------------------------
\202\ Id. at 124.
---------------------------------------------------------------------------
Commenters on the Draft TAR also expressed a desire for
improvements in the process by which manufacturers without an ``A''
vehicle (for the A-to-B comparison) could apply under the engineering
analysis provision, such as development of standardized engineering
analysis and bench testing procedures that could support such
applications. For example, Toyota requested that ``EPA consider an
optional method for validation via an engineering analysis, as is
currently being developed by industry.'' \203\ Similarly, the Alliance
commented that, ``[t]he future success of the MAC credit program in
generating emissions reductions will depend to a large extent on the
manner in which it is administered by EPA, especially with respect to
making the AC17 A-to-B provisions function smoothly, without becoming a
prohibitive obstacle to fully achieving the MAC indirect credits.''
\204\
---------------------------------------------------------------------------
\203\ See Comment by Toyota (revised), Docket ID NHTSA-2016-
0068-0088, at 23.
\204\ See Comment by Alliance of Automobile Manufacturers,
Docket ID EPA-HQ-OAR-2015-0827-4089 and NHTSA-2016-0068-0072, at
160.
---------------------------------------------------------------------------
As described in the Draft TAR, in 2016, USCAR members initiated a
Cooperative Research Program (CRP) through the Society of Automotive
Engineers (SAE) to develop bench testing standards for the four
hardware technologies in the fuel consumption improvement value menu
(blower motor control, internal heat exchanger, improved evaporators
and condensers, and oil separator). The intent of the program is to
streamline the process of conducting bench testing and engineering
analysis in support of an application for A/C credits under 40 CFR part
86.1868-12(g)(2), by creating uniform standards for bench testing and
for establishing the expected GHG effect of the technology in a vehicle
application.
An update to the list of SAE standards under development originally
presented in the Draft TAR is listed in Table II-20. Since completion
of the Draft TAR, work has continued on these standards, which appear
to be nearing completion. The agencies seek comment with the latest
completion of these SAE standards.
[GRAPHIC] [TIFF OMITTED] TP24AU18.035
(2) A/C Efficiency Technology Valuation Through the Off-Cycle Program
The A/C technology menu, discussed at length above, includes
several A/C efficiency-improving technologies that were well defined
and had been quantified for effectiveness at the time of the 2012 final
rule for MYs 2017 and beyond. Manufacturers claimed the vast majority
of A/C efficiency credits to date by utilizing technologies on the
menu; however, the agencies recognize that manufacturers will develop
additional technologies that are not currently listed on the menu.
These additional A/C efficiency-improving technologies are eligible for
fuel consumption improvement values on a case-by-case basis under the
off-cycle program. Approval under the off-cycle program also requires
``A-to-B'' comparison testing under the AC17 test, that is, testing
substantially similar vehicles in which one has the technology and the
other does not.
To date, the agencies have received one type off-cycle application
for an A/C efficiency technology. In December 2014, General Motors
submitted an off-cycle application for the Denso SAS A/
[[Page 43056]]
C compressor with variable crankcase suction valve technology,
requesting an off-cycle GHG credit of 1.1 grams CO2 per
mile. In December 2017, BMW of North America, Ford Motor Company,
Hyundai Motor Company, and Toyota petitioned and received approval to
receive the off-cycle improvement value for the same A/C efficiency
technology.205 206 EPA, in consultation with NHTSA,
evaluated the applications and found methodologies described therein
were sound and appropriate.\207\ Accordingly, the agencies approved the
fuel economy improvement value applications.
---------------------------------------------------------------------------
\205\ EPA Decision Document: Off-Cycle Credits for BMW Group,
Ford Motor Company, and Hyundai Motor Company, U.S. EPA (Dec. 2017),
available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TF06.pdf.
\206\ Alternative Method for Calculating Off-cycle Credits under
the Light-Duty Vehicle Greenhouse Gas Emissions Program:
Applications from General Motors and Toyota Motor North America, 83
FR 8262 (Feb. 26, 2018).
\207\ Id.
---------------------------------------------------------------------------
The agencies received additional stakeholder comments on the off-
cycle approval process as an alternate route to receiving A/C
technology credit values. The Alliance requested that EPA ``simplify
and standardize the procedures for claiming off-cycle credits for the
new MAC technologies that have been developed since the creation of the
MAC indirect credit menu.'' \208\ Other commenters noted the importance
of continuing to incentivize further innovation in A/C efficiency
technologies as new technologies emerge that are not listed on the menu
or when manufacturers begin to reach regulatory caps. The commenters
suggested that EPA should consider adding new A/C efficiency
technologies to the menu and/or update the fuel consumption improvement
values for technology already listed on the menu, particularly in cases
where manufacturers can show through an off-cycle application that the
technology actually deserves more credit than that listed on the menu.
For example, Toyota commented that ``the incentive values for A/C
efficiency should be updated along with including new technologies
being deployed.'' \209\
---------------------------------------------------------------------------
\208\ Comment by Alliance of Automobile Manufacturers, Docket ID
EPA-HQ-OAR-2015-0827-4089 and NHTSA-2016-0068-0072, at 152.
\209\ Comment by Toyota (revised), Docket ID NHTSA-2016-0068-
0088, at 23.
---------------------------------------------------------------------------
The agencies note that some of these comments are directed towards
the off-cycle technology approval process generally, which is described
in more detail in Section X of this preamble. Regarding the A/C
technology menu specifically, the agencies do anticipate that new A/C
technologies not currently on the menu will emerge over the time frame
of the MY 2021-2026 standards. This proposal requests comment on adding
one additional A/C technology to the menu--the A/C compressor with
variable crankcase suction valve technology, discussed below (and also
one off-cycle technology, discussed below). The agencies also request
comment on whether to change any fuel economy improvement values
currently assigned to technologies on the menu.
Next, as mentioned above, the menu-based improvement values for A/C
efficiency established in the 2012 final rule for MYs 2017 and by end
are subject to a regulatory cap. The rule set a cap of 5.7 g/mi for
cars and trucks through MY 2016 and separate caps of 5.0 g/mi for cars
and 7.2g/mi for trucks for later MYs.\210\ Several commenters asked EPA
to reconsider the applicability of the cap to non-menu A/C efficiency
technologies claimed through the off-cycle process and questioned the
applicability of this cap on several different grounds. These comments
appear to be in response to a Draft TAR passage that stated:
``Applications for A/C efficiency credits made under the off-cycle
credit program rather than the A/C credit program will continue to be
subject to the A/C efficiency credit cap'' (Draft TAR, p. 5-210). The
agencies considered these comments and present clarification below. As
additional context, the 2012 TSD states:
---------------------------------------------------------------------------
\210\ 40 C.F.R Sec. 86.1868-12(b)(2) (2016).
``. . . air conditioner efficiency is an off-cycle technology.
It is thus appropriate [. . .] to employ the standard off-cycle
credit approval process [to pursue a larger credit than the menu
value]. Utilization of bench tests in combination with dynamometer
tests and simulations [. . .] would be an appropriate alternate
method of demonstrating and quantifying technology credits (up to
the maximum level of credits allowed for A/C efficiency) [emphasis
added]. A manufacturer can choose this method even for technologies
that are not currently included in the menu.'' \211\
---------------------------------------------------------------------------
\211\ Joint Technical Support Document: Final Rulemaking for
2017-2025 Light-Duty Vehicle Greenhouse Gas Emission and Corporate
Average Fuel Economy Standards, U.S. EPA, National Highway Traffic
Safety Administration at 5-58 (August 2012).
---------------------------------------------------------------------------
This suggests the concept of placing a limit on total A/C fuel
consumption improvement values, even when some are granted under the
off-cycle program, is not entirely new and that EPA considered the menu
cap as being appropriate at the time.
A/C regulatory caps specified under 40 CFR 86.1868-12(b)(2) apply
to A/C efficiency menu-based improvement values and are not part of the
off-cycle regulation (40 CFR 86.1869-12). However, it should be noted
that off-cycle applications submitted via the public process pathway
are decided individually on merits through a process involving public
notice and opportunity for comment. In deciding whether to approve or
deny a request, the agencies may take into account any factors deemed
relevant, including such issues as the realization of claimed fuel
consumption improvement value in real-world use. Such considerations
could include synergies or interactions among applied technologies,
which could potentially be addressed by application of some form of cap
or other applicable limit, if warranted. Therefore, applying for A/C
efficiency fuel consumption improvement values through the off-cycle
provisions in 40 CFR 86.1869-12 should not be seen as a route to
unlimited A/C fuel consumption improvement values. The agencies discuss
air conditioning efficiency improvement values further in Section X of
this NPRM.
(b) Off-Cycle Technologies
``Off-cycle'' emission reductions and fuel consumption improvements
can be achieved by employing off-cycle technologies resulting in real-
world benefits but where that benefit is not adequately captured on the
test procedures used to demonstrate compliance with fuel economy
emission standards. EPA initially included off-cycle technology credits
in the MY 2012-2016 rule and revised the program in the MY 2017-2025
rule.\212\ NHTSA adopted equivalent off-cycle fuel consumption
improvement values for MYs 2017 and later in the MY 2017-2025
rule.\213\
---------------------------------------------------------------------------
\212\ 77 FR 62624, 62832 (Oct. 15, 2012).
\213\ Id. at 62839.
---------------------------------------------------------------------------
Manufacturers can demonstrate the value of off-cycle technologies
in three ways: First, they may select fuel economy improvement values
and CO2 credit values from a pre-defined ``menu'' for off-
cycle technologies that meet certain regulatory specifications. As part
of a manufacturer's compliance data, manufacturers will provide
information about which off-cycle technologies are present on which
vehicles.
The pre-defined list of technologies and associated off-cycle
light-duty vehicle fuel economy improvement values and GHG credits is
shown in Table II-21 and Table II-22 below.\214\ A
[[Page 43057]]
definition of each technology equipment must meet to be eligible for
the menu credit is included at 40 CFR 86.1869-12(b)(4). Manufacturers
are not required to submit any other emissions data or information
beyond meeting the definition and useful life requirements to use the
pre-defined credit value. Credits based on the pre-defined list are
subject to an annual manufacturer fleet-wide cap of 10 g/mile.
---------------------------------------------------------------------------
\214\ For a description of each technology and the derivation of
the pre-defined credit levels, see Chapter 5 of the Joint Technical
Support Document: Final Rulemaking for 2017-2025 Light-Duty Vehicle
Greenhouse Gas Emission and Corporate Average Fuel Economy
Standards, U.S. EPA, National Highway Traffic Safety Administration
(August 2012).
[GRAPHIC] [TIFF OMITTED] TP24AU18.036
Manufacturers can also perform their own 5-cycle testing and submit
test results to the agencies with a request explaining the off-cycle
technology. The additional three test cycles have different operating
conditions including high speeds, rapid accelerations, high temperature
with A/C operation and cold temperature, enabling improvements to be
measured for technologies that do not impact operation on the 2-cycle
tests. Credits determined according to this methodology do not undergo
public review.
The third pathway allows manufacturers to seek EPA approval to use
an alternative methodology for determining the value of an off-cycle
technology. This option is only available if the benefit of the
technology cannot be adequately demonstrated using the 5-cycle
methodology. Manufacturers may also use this option to demonstrate
reductions that exceed
[[Page 43058]]
those available via use of the predetermined menu list. The
manufacturer must also demonstrate that the off-cycle technology is
effective for the full useful life of the vehicle. Unless the
manufacturer demonstrates that the technology is not subject to in-use
deterioration, the manufacturer must account for the deterioration in
their analysis.
Manufacturers must develop a methodology for demonstrating the
benefit of the off-cycle technology, and EPA makes the methodology
available for public comment prior to an EPA determination, in
consultation with NHTSA, on whether to allow the use of the methodology
to measure improvements. The data needed for this demonstration may be
extensive.
Several manufacturers have requested and been granted use of
alternative test methodologies for measuring improvements. In 2013,
Mercedes requested off-cycle credits for the following off-cycle
technologies in use or planned for implementation in the 2012-2016
model years: Stop-start systems, high-efficiency lighting, infrared
glass glazing, and active seat ventilation. EPA approved methodologies
for Mercedes to determine these off-cycle credits in September
2014.\215\ Subsequently, FCA, Ford, and GM requested off-cycle credits
using this same methodology. FCA and Ford submitted applications for
off-cycle credits from high efficiency exterior lighting, solar
reflective glass/glazing, solar reflective paint, and active seat
ventilation. Ford's application also demonstrated off-cycle benefits
from active aerodynamic improvements (grille shutters), active
transmission warm-up, active engine warm-up technologies, and engine
idle stop-start. GM's application described real-world benefits of an
air conditioning compressor with variable crankcase suction valve
technology. EPA approved the credits for FCA, Ford, and GM in September
2015.\216\ Note, however, that although EPA granted the use of
alternative methodologies to determine credit values, manufacturers
have yet to report credits to EPA based on those alternative
methodologies.
---------------------------------------------------------------------------
\215\ EPA Decision Document: Mercedes-Benz Off-cycle Credits for
MYs 2012-2016, U.S. EPA (Sept. 2014), available at https://nepis.epa.gov/Exe/ZyPDF.cgi/P100KB8U.PDF?Dockey=P100KB8U.PDF.
\216\ EPA Decision Document: Off-cycle Credits for Fiat Chrysler
Automobiles, Ford Motor Company, and General Motors Corporation,
U.S. EPA (Sept. 2015), available at https://nepis.epa.gov/Exe/ZyPDF.cgi/P100N19E.PDF?Dockey=P100N19E.PDF.
---------------------------------------------------------------------------
As discussed below, all three methods have been used by
manufacturers to generate off-cycle improvement values and credits.
(1) Use of Off-Cycle Technologies to Date
Manufacturers used a wide array of off-cycle technologies in MY
2016 to generate off-cycle GHG credits using the pre-defined menu.
Table II-23 below shows the percent of each manufacturer's production
volume using each menu technology reported to EPA for MY 2016 by
manufacturer. Table II-24 shows the g/mile benefit each manufacturer
reported across its fleet from each off-cycle technology. Like Table
II-23, Table II-24 provides the mix of technologies used in MY 2016 by
manufacturer and the extent to which each technology benefits each
manufacturer's fleet. Fuel consumption improvement values for off-cycle
technologies were not available in the CAFE program until MY 2017;
therefore, only GHG off-cycle credits have been generated by
manufacturers thus far.
[[Page 43059]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.037
[[Page 43060]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.038
In 2016, manufacturers generated the vast majority of credits using
the pre-defined menu.\217\ Although MY 2014 was the first year that
manufacturers could generate credits using pre-defined menu values,
manufacturers have acted quickly to generate substantial off-cycle
improvements. FCA and Jaguar Land Rover generated the most off-cycle
credits on a fleet-wide basis, reporting credits equivalent to
approximately 6 g/mile and 5 g/mile, respectively. Several other
manufacturers report fleet-wide credits in the range of approximately 1
to 4 g/mile. In MY 2016, the fleet total across manufacturers equaled
approximately 2.5 g/mile. The agencies
[[Page 43061]]
expect that as manufacturers continue expanding their use of off-cycle
technologies, the fleet-wide effects will continue to grow with some
manufacturers potentially approaching the 10 g/mile fleet-wide cap.
---------------------------------------------------------------------------
\217\ Thus far, the agencies have only granted one manufacturer
(GM) off-cycle credits for technology based on 5-cycle testing.
These credits are for an off-cycle technology used on certain GM
gasoline-electric hybrid vehicles, an auxiliary electric pump, which
keeps engine coolant circulating in cold weather while the vehicle
is stopped and the engine is off, thus allowing the engine stop-
start system to be active more frequently in cold weather.
---------------------------------------------------------------------------
E. Development of Economic Assumptions and Information Used as Inputs
to the Analysis
1. Purpose of Developing Economic Assumptions for Use in Modeling
Analysis
(a) Overall Framework of Costs and Benefits
It is important to report the benefits and costs of this proposed
action in a format that conveys useful information about how those
impacts are generated and that also distinguishes the impacts of those
economic consequences for private businesses and households from the
effects on the remainder of the U.S. economy. A reporting format will
accomplish the first objective to the extent that it clarifies the
benefits and costs of the proposed action's impacts on car and light
truck producers, illustrates how these are transmitted to buyers of new
vehicles, shows the action's collateral economic effects on owners of
used cars and light trucks, and identifies how these impacts create
costs and benefits for the remainder of the U.S. economy. It will
achieve the second objective by showing clearly how the economy-wide or
``social'' benefits and costs of the proposed action are composed of
its direct effects on vehicle producers, buyers, and users, plus the
indirect or ``external'' benefits and costs it creates for the general
public.
Table II-25 through Table II-28 present the economic benefits and
costs of the proposed action to reduce CAFE and CO2
emissions standards for model years 2021-26 at three percent and seven
percent discount rates in a format that is intended to meet these
objectives. Note: They include costs which are transfers between
different economic actors--these will appear as both a cost and a
benefit in equal amounts (to separate affected parties). Societal cost
and benefit values shown elsewhere in this document do not show costs
which are transfers for the sake of simplicity but report the same net
societal costs and benefits. As it indicates, the proposed action first
reduces costs to manufacturers for adding technology necessary to
enable new cars and light trucks to comply with fuel economy and
emission regulations (line 1). It may also reduce fine payments by
manufacturers who would have failed to comply with the more demanding
baseline standards. Manufacturers are assumed to transfer these cost
savings on to buyers by charging lower prices (line 5); although this
reduces their revenues (line 3), on balance, the reduction in
compliance costs and lower sales revenue leaves them financially
unaffected (line 4).
[[Page 43062]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.039
[[Page 43063]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.040
[[Page 43064]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.041
[[Page 43065]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.042
[[Page 43066]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.043
As the tables show, most impacts of the proposed action will fall
on the businesses and individuals who design, manufacture, and sell (at
retail and wholesale) cars and light trucks, the consumers who
purchase, drive, and subsequently sell or trade-in new models (and
ultimately bear the cost of fuel economy technology), and owners of
used cars and light trucks produced during model years prior to those
covered by this action. Compared to the baseline standards, if the
preferred alternative is finalized, buyers of new cars and light trucks
will benefit from
[[Page 43067]]
their lower purchase prices and financing costs (line 5). They will
also avoid the increased risks of being injured in crashes that would
have resulted from manufacturers' efforts to reduce the weight of new
models to comply with the baseline standards, which represents another
benefit from reducing stringency vis-[agrave]-vis the baseline (line
6).
At the same time, new cars and light trucks will offer lower fuel
economy with more lenient standards in place, and this imposes various
costs on their buyers and users. Drivers will experience higher costs
as a consequence of new vehicles' increased fuel consumption (line 7),
and from the added inconvenience of more frequent refueling stops
required by their reduced driving range (line 8). They will also forego
some mobility benefits as they use newly-purchased cars and light
trucks less in response to their higher fueling costs, although this
loss will be almost fully offset by the fuel and other costs they save
by driving less (line 9). On balance, consumers of new cars and light
trucks produced during the model years subject to this proposed action
will experience significant economic benefits (line 10).
By lowering prices for new cars and light trucks, this proposed
action will cause some owners of used vehicles to retire them from
service earlier than they would otherwise have done, and replace them
with new models. In effect, it will transfer some driving that would
have been done in used cars and light trucks under the baseline
scenario to newer and safer models, thus reducing costs for injuries
(both fatal and less severe) and property damages sustained in motor
vehicle crashes. This improvement in safety results from the fact that
cars and light trucks have become progressively more protective in
crashes over time (and also slightly less prone to certain types of
crashes, such as rollovers). Thus, shifting some travel from older to
newer models reduces injuries and damages sustained by drivers and
passengers because they are traveling in inherently safer vehicles and
not because it changes the risk profiles of drivers themselves. This
reduction in injury risks and other damage costs produces benefits to
owners and drivers of older cars and light trucks. This also results in
benefits in terms of improved fuel economy and significant reductions
of emissions from newer vehicles (line 11).
Table II-27 through Table II-28 also show that the changes in fuel
consumption and vehicle use resulting from this proposed action will in
turn generate both benefits and costs to the remainder of the U.S.
economy. These impacts are ``external,'' in the sense that they are by-
products of decisions by private firms and individuals that alter
vehicle use and fuel consumption but are experienced broadly throughout
the U.S. economy rather than by the firms and individuals who
indirectly cause them. Increased refining and consumption of petroleum-
based fuel will increase emissions of carbon dioxide and other
greenhouse gases that theoretically contribute to climate change, and
some of the resulting (albeit uncertain) increase in economic damages
from future changes in the global climate will be borne throughout the
U.S. economy (line 13). Similarly, added fuel production and use will
increase emissions of more localized air pollutants (or their chemical
precursors), and the resulting increase in the U.S. population's
exposure to harmful levels of these pollutants will lead to somewhat
higher costs from its adverse effects on health (line 14). On the other
hand, it is expected that the proposed standards, by reducing new
vehicle prices relative to the baseline, will accelerate fleet turnover
to cleaner, safer, more efficient vehicles (as compared to used
vehicles that might otherwise continue to be driven or purchased).
As discussed in PRIA Section 9.8, increased consumption and imports
of crude petroleum for refining higher volumes of gasoline and diesel
will also impose some external costs throughout the U.S. economy, in
the form of potential losses in production and costs for businesses and
households to adjust rapidly to sudden changes in energy prices (line
15 of the table), although these costs should be tempered by increasing
U.S. oil production.\218\ Reductions in driving by buyers of new cars
and light trucks in response to their higher operating costs will also
reduce the external costs associated with their contributions to
traffic delays and noise levels in urban areas, and these additional
benefits will be experienced throughout much of the U.S. economy (line
17). Finally, some of the higher fuel costs to buyers of new cars and
light trucks will consist of increased fuel taxes; this increase in
revenue will enable Federal and State government agencies to provide
higher levels of road capacity or maintenance, producing benefits for
all road and transit users (line 18).
---------------------------------------------------------------------------
\218\ Note: This output was based upon the EIA Annual Energy
Outlook from 2017. The 2018 Annual Energy Outlook projects the U.S.
will be a net exporter by around 2029, with net exports peaking at
around 0.5 mbd circa 2040. See Annual Energy Outlook 2018, U.S.
Energy Information Administration, at 53 (Feb, 6, 2018), https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf. Furthermore, pursuant to
Executive Order 13783 (Promoting Energy Independence and Economy
Growth), agencies are expected to review and revise or rescind
policies that unduly burden the development of domestic energy
resources beyond what is necessary to protect the public interest or
otherwise comply with the law. Therefore, it is reasonable to
anticipate further increases in domestic production of petroleum.
The agencies may update the analysis and table to account for this
revised information.
---------------------------------------------------------------------------
On balance, Table II-27 through Table II-28 show that the U.S.
economy as a whole will experience large net economic benefits from the
proposed action (line 22). While the proposal to establish less
stringent CAFE and GHG emission standards will produce net external
economic costs, as the increase in environmental and energy security
externalities outweighs external benefits from reduced driving and
higher fuel tax revenue (line 19), the table also shows that combined
benefits to vehicle manufacturers, buyers, and users of cars and light
trucks, and the general public (line 20), including the value of the
lives saved and injuries avoided, will greatly outweigh the combined
economic costs they experience as a consequence of this proposed action
(line 21).
The finding that this action to reduce the stringency of
previously-established CAFE and GHG standards will create significant
net economic benefits--when it was initially claimed that establishing
those standards would also generate large economic benefits to vehicle
buyers and others throughout the economy--is notable. This contrast
with the earlier finding is explained by the availability of updated
information on the costs and effectiveness of technologies that will
remain available to improve fuel economy in model years 2021 and
beyond, the fleet-wide consequences for vehicle use, fuel consumption,
and safety from requiring higher fuel economy (that is, considering
these consequences for used cars and light trucks as well as new ones),
and new estimates of some external costs of fuel in petroleum use.
2. Macroeconomic Assumptions That Affect the Benefit Cost Analysis
Unlike previous CAFE and GHG rulemaking analyses, the economic
context in which the alternatives are simulated is more explicit. While
both this analysis and previous analyses contained fuel price
projections from the Annual Energy Outlook, which has embedded
assumptions about future macroeconomic conditions, this analysis
requires explicit assumptions about future GDP growth, labor force
participation, and interest rates in order to evaluate the
alternatives.
[[Page 43068]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.044
The analysis simulates compliance through MY 2032 explicitly and
must consider the full useful lives of those vehicles, approximately 40
years, in order to estimate their lifetime mileage accumulation and
fuel consumption. This means that any macroeconomic forecast
influencing those factors must cover a similar span of years. Due to
the long time horizon, a source that regularly produces such lengthy
forecasts of these factors was selected:
[[Page 43069]]
the 2017 OASDI Trustees Report from the U.S. Social Security
Administration. While Table-II-29 only displays assumptions through CY
2050, the remaining years merely continue the trends present in the
table.
The analysis once again uses fuel price projections from the 2017
Annual Energy Outlook.\219\ The projections by fuel calendar year and
fuel type are presented in Table-II-30, in real 2016 dollars. Fuel
prices in this analysis affect not only the value of each gallon of
fuel consumed but relative valuation of fuel-saving technologies
demanded by the market as a result of their associated fuel savings.
---------------------------------------------------------------------------
\219\ The central analysis supporting today's proposal uses
reference case estimates of fuel prices reported in the Energy
Information Administration's (EIA's) Annual Energy Outlook 2017 (AEO
2017). Today's proposal also examines the sensitivity of this
analysis to changes in key inputs, including fuel prices, and
includes cases that apply fuel prices from the AEO 2017 low oil
price and high oil price cases. The reference case prices are
considerably lower than AEO 2011-based reference cases prices
applied in the 2012 rulemaking, and this is one of several important
changes in circumstances supporting revision of previously-issued
standards.
After significant portions of today's analysis had already been
completed, EIA released AEO 2018, which reports reference case fuel
prices about 10% higher than reported in AEO 2017, though still well
below the above-mentioned prices from AEO 2011. The sensitivity
analysis therefore includes a case that applies fuel prices from the
AEO 2018 reference case. The AEO 2018 low oil price case reports
fuel prices somewhat higher than the AEO 2017 low oil price case,
and the AEO 2018 high oil price case reports fuel prices very
similar to the AEO 2017 high oil price case. Adding the AEO 2018 low
and high oil price cases to the sensitivity analysis would thus have
provided little, if any, additional insight into the sensitivity of
the analysis to fuel prices. As shown in the summary of the
sensitivity analysis, results obtained applying AEO 2018-based fuel
prices are similar to those obtained applying AEO 2017-based fuel
prices. For example, net benefits between the two are about five
percent different, especially considering that decisions regarding
future standards are not single-factor decisions, but rather reflect
a balancing of factors, applying AEO 2018-based fuel prices would
not materially change the extent to which today's analysis supports
the selection of the preferred alternative.
Like other inputs to the analysis, fuel prices will be updated
for the analysis supporting the final rule after consideration of
related new information and public comment.
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[[Page 43070]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.045
3. New Vehicle Sales and Employment Assumptions
In all previous CAFE and GHG rulemaking analyses, static fleet
forecasts that were based on a combination of manufacturer compliance
data, public data sources, and proprietary forecasts were used. When
simulating compliance with regulatory alternatives, the analysis
projected identical sales across the alternatives, for each
manufacturer down to the make/model level where the exact same number
of each model variant was simulated to be sold in a given model year
under both the least stringent alternative (typically the
[[Page 43071]]
baseline) and the most stringent alternative considered. To the extent
that an alternative matched the assumptions made in the production of
the proprietary forecast, using a static fleet based upon those
assumptions may have been warranted. However, it seems intuitive that
any sufficiently large span of regulatory alternatives would contain
alternatives for which that static forecast was unrepresentative. A
number of commenters have encouraged consideration of the potential
impact of CAFE/GHG standards on new vehicle prices and sales, and the
changes to compliance strategies that those shifts could
necessitate.\220\ In particular, the continued growth of the utility
vehicle segment creates compliance challenges within some
manufacturers' fleets as sales volumes shift from one region of the
footprint curve to another.
---------------------------------------------------------------------------
\220\ See e.g., Comment by Alliance of Automobile Manufacturers,
Docket ID EPA-HQ-OAR-2015-0827-4089 and NHTSA-2016-0068-0072.
---------------------------------------------------------------------------
Any model of sales response must satisfy two requirements: It must
be appropriate for use in the CAFE model, and it must be
econometrically reasonable. The first of these requirements implies
that any variable used in the estimation of the econometric model, must
also be available as a forecast throughout the duration of the years
covered by the simulations (this analysis explicitly simulates
compliance through MY 2032). Some values the model calculates
endogenously, making them available in future years for sales
estimation, but others must be known in advance of the simulation. As
the CAFE model simulates compliance, it accumulates technology costs
across the industry and over time. By starting with the last known
transaction price and adding the accumulated technology cost to that
value, the model is able to represent the average selling price in each
future model year assuming that manufacturers are able to pass all of
their compliance costs on to buyers of new vehicles. Other variables
used in the estimation must enter the model as inputs prior to the
start of the compliance simulation.
(a) How do car and light truck buyers value improved fuel economy?
How potential buyers value improvements in the fuel economy of new
cars and light trucks is an important issue in assessing the benefits
and costs of government regulation. If buyers fully value the savings
in fuel costs that result from higher fuel economy, manufacturers will
presumably supply any improvements that buyers demand, and vehicle
prices will fully reflect future fuel cost savings consumers would
realize from owning--and potentially re-selling--more fuel-efficient
models. In this case, more stringent fuel economy standards will impose
net costs on vehicle owners and can only result in social benefits by
correcting externalities, since consumers would already fully
incorporate private savings into their purchase decisions. If instead
consumers systematically undervalue the cost savings generated by
improvements in fuel economy when choosing among competing models, more
stringent fuel economy standards will also lead manufacturers to adopt
improvements in fuel economy that buyers might not choose despite the
cost savings they offer.
The potential for car buyers to forego improvements in fuel economy
that offer savings exceeding their initial costs is one example of what
is often termed the ``energy-efficiency gap.'' This appearance of such
a gap, between the level of energy efficiency that would minimize
consumers' overall expenses and what they actually purchase, is
typically based on engineering calculations that compare the initial
cost for providing higher energy efficiency to the discounted present
value of the resulting savings in future energy costs.
There has long been an active debate about why such a gap might
arise and whether it actually exists. Economic theory predicts that
individuals will purchase more energy-efficient products only if the
savings in future energy costs they offer promise to offset their
higher initial costs. However, the additional cost of a more energy-
efficient product includes more than just the cost of the technology
necessary to improve its efficiency; it also includes the opportunity
cost of any other desirable features that consumers give up when they
choose the more efficient alternative. In the context of vehicles,
whether the expected fuel savings outweigh the opportunity cost of
purchasing a model offering higher fuel economy will depend on how much
its buyer expects to drive, his or her expectations about future fuel
prices, the discount rate he or she uses to value future expenses, the
expected effect on resale value, and whether more efficient models
offer equivalent attributes such as performance, carrying capacity,
reliability, quality, or other characteristics.
Published literature has offered little consensus about consumers'
willingness-to-pay for greater fuel economy, and whether it implies
over-, under- or full-valuation of the expected fuel savings from
purchasing a model with higher fuel economy. Most studies have relied
on car buyers' purchasing behavior to estimate their willingness-to-pay
for future fuel savings; a typical approach has been to use ``discrete
choice'' models that relate individual buyers' choices among competing
vehicles to their purchase prices, fuel economy, and other attributes
(such as performance, carrying capacity, and reliability), and to infer
buyers' valuation of higher fuel economy from the relative importance
of purchase prices and fuel economy.\221\ Empirical estimates using
this approach span a wide range, extending from substantial
undervaluation of fuel savings to significant overvaluation, thus
making it difficult to draw solid conclusions about the influence of
fuel economy on vehicle buyers' choices (see Helfand & Wolverton, 2011;
Green (2010) for detailed reviews of these cross-sectional studies).
Because a vehicle's price is often correlated with its other attributes
(both measured and unobserved), analysts have often used instrumental
variables or other approaches to address endogeneity and other
resulting concerns (e.g., Barry, et al. 1995).
---------------------------------------------------------------------------
\221\ In a typical vehicle choice model, the ratio of estimated
coefficients on fuel economy--or more commonly, fuel cost per mile
driven--and purchase price is used to infer the dollar value buyers
attach to slightly higher fuel economy.
---------------------------------------------------------------------------
Despite these efforts, more recent research has criticized these
cross-sectional studies; some have questioned the effectiveness of the
instruments they use (Allcott & Greenstone, 2012), while others have
observed that coefficients estimated using non-linear statistical
methods can be sensitive to the optimization algorithm and starting
values (Knittel & Metaxoglou, 2014). Collinearity (i.e., high
correlations) among vehicle attributes--most notably among fuel
economy, performance or power, and vehicle size--and between vehicles'
measured and unobserved features also raises questions about the
reliability and interpretation of coefficients that may conflate the
value of fuel economy with other attributes (Sallee, et al., 2016;
Busse, et al., 2013; Allcott & Wozny, 2014; Allcott & Greenstone, 2012;
Helfand & Wolverton, 2011).
In an effort to overcome shortcomings of past analyses, three
recently published studies rely on panel data from sales of individual
vehicle models to improve their reliability in identifying the
association between vehicles' prices and their fuel economy (Sallee, et
al. 2016; Allcott & Wozny, 2014; Busse, et al., 2013). Although they
differ in certain details, each of these
[[Page 43072]]
analyses relates changes over time in individual models' selling prices
to fluctuations in fuel prices, differences in their fuel economy, and
increases in their age and accumulated use, which affects their
expected remaining life, and thus their market value. Because a
vehicle's future fuel costs are a function of both its fuel economy and
expected gasoline prices, changes in fuel prices have different effects
on the market values of vehicles with different fuel economy; comparing
these effects over time and among vehicle models reveals the fraction
of changes in fuel costs that is reflected in changes in their selling
prices (Allcott & Wozny, 2014). Using very large samples of sales
enables these studies to define vehicle models at an extremely
disaggregated level, which enables their authors to isolate differences
in their fuel economy from the many other attributes, including those
that are difficult to observe or measure, that affect their sale
prices.\222\
---------------------------------------------------------------------------
\222\ These studies rely on individual vehicle transaction data
from dealer sales and wholesale auctions, which includes actual sale
prices and allows their authors to define vehicle models at a highly
disaggregated level. For instance, Allcott & Wozny (2014)
differentiate vehicles by manufacturer, model or nameplate, trim
level, body type, fuel economy, engine displacement, number of
cylinders, and ``generation'' (a group of successive model years
during which a model's design remains largely unchanged). All three
studies include transactions only through mid-2008 to limit the
effect of the recession on vehicle prices. To ensure that the
vehicle choice set consists of true substitutes, Allcott & Wozny
(2014) define the choice set as all gasoline-fueled light-duty cars,
trucks, SUVs, and minivans that are less than 25 years old (i.e.,
they exclude vehicles where the substitution elasticity is expected
to be small). Sallee et al. (2016) exclude diesels, hybrids, and
used vehicles with less than 10,000 or more than 100,000 miles.
---------------------------------------------------------------------------
These studies point to a somewhat narrower range of estimates than
suggested by previous cross-sectional studies; more importantly, they
consistently suggest that buyers value a large proportion--and perhaps
even all--of the future savings that models with higher fuel economy
offer.\223\ Because they rely on estimates of fuel costs over vehicles'
expected remaining lifetimes, these studies' estimates of how buyers
value fuel economy are sensitive to the strategies they use to isolate
differences among individual models' fuel economy, as well as to their
assumptions about buyers' discount rates and gasoline price
expectations, among others. Since Anderson et al. (2013) find evidence
that consumers expect future gasoline prices to resemble current
prices, we use this assumption to compare the findings of the three
studies and examine how their findings vary with the discount rates
buyers apply to future fuel savings.\224\
---------------------------------------------------------------------------
\223\ Killian & Sims (2006) and Sawhill (2008) rely on similar
longitudinal approaches to examine consumer valuation of fuel
economy except that they use average values or list prices instead
of actual transaction prices. Since these studies remain
unpublished, their empirical results are subject to change, and they
are excluded from this discussion.
\224\ Each of the studies makes slightly different assumptions
about appropriate discount rates. Sallee et al. (2016) use five
percent in their base specification, while Allcott & Wozny (2014)
rely on six percent. As some authors note, a five to six percent
discount rate is consistent with current interest rates on car
loans, but they also acknowledge that borrowing rates could be
higher in some cases, which could be justify higher discount rates.
Rather than assuming a specific discount rate, Busse et al. (2013)
directly estimate implicit discount rates at which future fuel costs
would be fully internalized; they find discount rates of six to 21%
for used cars and one to 13% for new cars at assumed demand
elasticities ranging from -2 to -3. Their estimates can be
translated into the percent of fuel costs internalized by consumers,
assuming a particular discount rate. To make these results more
directly comparable to the other two studies, we assume a range of
discount rates and uses the authors' spreadsheet tool to translate
their results into the percent of fuel costs internalized into the
purchase price at each rate. Because Busse et al. (2013) estimate
the effects of future fuel costs on vehicle prices separately by
fuel economy quartile, these results depend on which quartiles of
the fuel economy distribution are compared; our summary shows
results using the full range of quartile comparisons.
---------------------------------------------------------------------------
As Table 1 indicates, Allcott & Wozny (2014) find that consumers
incorporate 55% of future fuel costs into vehicle purchase decisions at
a six percent discount rate, when their expectations for future
gasoline prices are assumed to reflect prevailing prices at the time of
their purchases. With the same expectation about future fuel prices,
the authors report that consumers would fully value fuel costs only if
they apply discount rates of 24% or higher. However, these authors'
estimates are closer to full valuation when using gasoline price
forecasts that mirror oil futures markets because the petroleum market
expected prices to fall during this period (this outlook reduces the
discounted value of a vehicle's expected remaining lifetime fuel
costs). With this expectation, Allcott & Wozny (2014) find that buyers
value 76% of future cost savings (discounted at six percent) from
choosing a model that offers higher fuel economy, and that a discount
rate of 15% would imply that they fully value future cost savings.
Sallee et al. (2016) begin with the perspective that buyers fully
internalize future fuel costs into vehicles' purchase prices and cannot
reliably reject that hypothesis; their base specification suggests that
changes in vehicle prices incorporate slightly more than 100% of
changes in future fuel costs. For discount rates of five to six
percent, the Busse et al. (2013) results imply that vehicle prices
reflect 60 to 100% of future fuel costs. As Table II-31 suggests,
higher private discount rates move all of the estimates closer to full
valuation or to over-valuation, while lower discount rates imply less
complete valuation in all three studies.
[[Page 43073]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.046
The studies also explore the sensitivity of the results to other
parameters that could influence their results. Busse et al. (2013) and
Allcott & Wozny (2014) find that relying on data that suggest lower
annual vehicle use or survival probabilities, which imply that vehicles
will not last as long, moves their estimates closer to full valuation,
an unsurprising result because both reduce the changes in expected
future fuel costs caused by fuel price fluctuations. Allcott & Wozny's
(2014) base results rely on an instrumental variables estimator that
groups miles-per-gallon (MPG) into two quantiles to mitigate potential
attenuation bias due to measurement error in fuel economy, but they
find that greater disaggregation of the MPG groups implies greater
undervaluation (for example, it reduces the 55% estimated reported in
Table 1 to 49%). Busse et al. (2013) allow gasoline prices to vary
across local markets in their main specification; using national
average gasoline prices, an approach more directly comparable to the
other studies, results in estimates that are closer to or above full
valuation. Sallee et al. (2016) find modest undervaluation by vehicle
fleet operators or manufacturers making large-scale purchases, compared
to retail dealer sales (i.e., 70 to 86%).
Since they rely predominantly on changes in vehicles' prices
between repeat sales, most of the valuation estimates reported in these
studies apply most directly to buyers of used vehicles. Only Busse et
al. (2013) examine new vehicle sales; they find that consumers value
between 75 to 133% of future fuel costs for new vehicles, a higher
range than they estimate for used vehicles. Allcott & Wozny (2014)
examine how their estimates vary by vehicle age and find that
fluctuations in purchase prices of younger vehicles imply that buyers
whose fuel price expectations mirror the petroleum futures market value
a higher fraction of future fuel costs: 93% for one- to three-year-old
vehicles, compared to their estimate of 76% for all used vehicles
assuming the same price expectation.\225\
---------------------------------------------------------------------------
\225\ Allcott & Wozny (2014) and Sallee, et al. (2016) also find
that future fuel costs for older vehicles are substantially
undervalued (26-30%). The pattern of Allcott and Wozny's results for
different vehicle ages is similar when they use retail transaction
prices (adjusted for customer cash rebates and trade-in values)
instead of wholesale auction prices, although the degree of
valuation falls substantially in all age cohorts with the smaller,
retail price based sample.
---------------------------------------------------------------------------
Accounting for differences in their data and estimation procedures,
the three studies described here suggest that car buyers who use
discount rates of five to six percent value at least half--and perhaps
all--of the savings in future fuel costs they expect from choosing
models that offer higher fuel economy. Perhaps more important in
assessing the case for regulating fuel economy, one study suggests that
buyers of new cars and light trucks value three-quarters or more of the
savings in future fuel costs they anticipate from purchasing higher-mpg
models, although this result is based on more limited information.
In contrast, previous regulatory analyses of fuel economy standards
implicitly assumed that buyers undervalue even more of the benefits
they would experience from purchasing models with higher fuel economy
so that without increases in fuel economy standards little improvement
would occur, and the entire value of fuel savings from raising CAFE
standards represented private benefits to car and light truck buyers
themselves. For instance, in the EPA analysis of the 2017-2025 model
year greenhouse gas emission standards, fuel savings alone added up to
$475 billion (at three percent discount rate) over the lifetime of the
vehicles, far outweighing the compliance costs: $150 billion). The
assertion that buyers were unwilling to take voluntary advantage of
this opportunity implies that collectively, they must have valued less
than a third ($150 billion/$475 billion = 32%) of the fuel savings that
would have resulted from those standards.\226\ The evidence
[[Page 43074]]
reviewed here makes that perspective extremely difficult to justify and
would call into question any analysis that claims to show large private
net benefits for vehicle buyers.
---------------------------------------------------------------------------
\226\ In fact, those earlier analyses assumed that new car and
light truck buyers attach relatively little value to higher fuel
economy, since their baseline scenarios assumed that fuel economy
levels would not increase in the absence of progressively tighter
standards.
---------------------------------------------------------------------------
What analysts assume about consumers' vehicle purchasing behavior,
particularly about potential buyers' perspectives on the value of
increased fuel economy, clearly matters a great deal in the context of
benefit-cost analysis for fuel economy regulation. In light of recent
evidence on this question, a more nuanced approach than assuming that
buyers drastically undervalue benefits from higher fuel economy, and
that as a consequence, these benefits are unlikely to be realized
without stringent fuel economy standards, seems warranted. One possible
approach would be to use a baseline scenario where fuel economy levels
of new cars and light trucks reflected full (or nearly so) valuation of
fuel savings by potential buyers in order to reveal whether setting
fuel economy standards above market-determined levels could produce net
social benefits. Another might be to assume that, unlike in the
agencies' previous analyses, where buyers were assumed to greatly
undervalue higher fuel economy under the baseline but to value it fully
under the proposed standards, buyers value improved fuel economy
identically under both the baseline scenario and with stricter CAFE
standards in place. The agencies ask for comment on these and any
alternative approaches they should consider for valuing fuel savings,
new peer-reviewed evidence on vehicle buyers' behavior that casts light
on how they value improved fuel economy, the appropriate private
discount rate to apply to future fuel savings, and thus the degree to
which private fuel savings should be considered as private benefits of
increasing fuel economy standards.
(b) Sales Data and Relevant Macroeconomic Factors
Developing a procedure to predict the effects of changes in prices
and attributes of new vehicles is complicated by the fact that their
sales are highly pro-cyclical--that is, they are very sensitive to
changes in macroeconomic conditions--and also statistically ``noisy,''
because they reflect the transient effects of other factors such as
consumers' confidence in the future, which can be difficult to observe
and measure accurately. At the same time, their average sales price
tends to move in parallel with changes in economic growth; that is,
average new vehicle prices tend to be higher when the total number of
new vehicles sold is increasing and lower when the total number of new
sales decreases (typically during periods of low economic growth or
recessions). Finally, counts of the total number of new cars and light
trucks that are sold do not capture shifts in demand among vehicle size
classes or body styles (``market segments''); nor do they measure
changes in the durability, safety, fuel economy, carrying capacity,
comfort, or other aspects of vehicles' quality.
The historical series of new light-duty vehicle sales exhibits
cyclic behavior over time that is most responsive to larger cycles in
the macro economy--but has not increased over time in the same way the
population, for example, has. While U.S. population has grown over 35
percent since 1980, the registered vehicle population has grown at an
even faster pace--nearly doubling between 1980 and 2015.\227\ But
annual vehicle sales did not grow at a similar pace -even accounting
for the cyclical nature of the industry. Total new light-duty sales
prior to the 2008 recession climbed as high as 16 million, though
similarly high sales years occurred in the 1980's and 1990's as well.
In fact, when considering a 10-year moving average to smooth out the
effect of cycles, most 10-year averages between 1992 and 2015 are
within a few percent of the 10-year average in 1992. And although
average transaction prices for new vehicles have been rising steadily
since the recession ended, prices are not yet at historical highs when
adjusted for inflation. The period of highest inflation-adjusted
transaction prices occurred from 1996-2006, when the average
transaction price for a new light-duty vehicle was consistently higher
than the price in 2015.
---------------------------------------------------------------------------
\227\ There are two measurements of the size of the registered
vehicle population that are considered to be authoritative. One is
produced by the Federal Highway Adminstration, and the other by R.L.
Polk (now part of IHS). The Polk measurement shows fleet growth
between 1980 and 2015 of about 85%, while the FHWA measurement shows
a slower growth rate over that period; only about 60%. Both are
still considerably larger than the growth in new vehicle sales over
the same period.
---------------------------------------------------------------------------
In an attempt to overcome these analytical challenges, various
approaches were experimented with to predict the response of new
vehicle sales to the changes in prices, fuel economy, and other
features. These included treating new vehicle demand as a product of
changes in total demand for vehicle ownership and demand necessary to
replace used vehicles that are retired, analyzing total expenditures to
purchase new cars and light trucks in conjunction with the total number
sold, and other approaches. However, none of these methods offered a
significant improvement over estimating the total number of vehicles
sold directly from its historical relationship to directly measurable
factors such as their average sales price, macroeconomic variables such
as GDP or Personal Disposable Income, U.S. labor force participation,
and regularly published surveys of consumer sentiment or confidence.
Quarterly, rather than annual data on total sales of new cars and
light trucks, their average selling price, and macroeconomic variables
was used to develop an econometric model of sales, in order to increase
the number of observations and more accurately capture the causal
effects of individual explanatory variables. Applying conventional data
diagnostics for time-series economic data revealed that most variables
were non-stationary (i.e., they reflected strong underlying time
trends) and displayed unit roots, and statistical tests revealed co-
integration between the total vehicle sales--the model's dependent
variable--and most candidate explanatory variables.
(c) Current Estimation of Sales Impacts
To address the complications of the time series data, the analysis
estimated an autoregressive distributed-lag (ARDL) model that employs a
combination of lagged values of its dependent variable--in this case,
last year's and the prior year's vehicle sales--and the change in
average vehicle price, quarterly changes in the U.S. GDP growth rate,
as well as current and lagged values of quarterly estimates of U.S.
labor force participation. The number of lagged values of each
explanatory variable to include was determined empirically (using the
Bayesian information criterion), by examining the effects of including
different combinations of their lagged values on how well the model
``explained'' historical variation in car and light truck sales.
The results of this approach were encouraging: The model's
predictions fit the historical data on sales well, each of its
explanatory variables displayed the expected effect on sales, and
analysis of its unexplained residual terms revealed little evidence of
autocorrelation or other indications of statistical problems. The model
coefficients suggest that positive GDP growth rates and increases in
labor force participation are both indicators of increases in new
vehicle sales, while positive changes in average new vehicle price
reduce new sales. However, the magnitude of the
[[Page 43075]]
coefficient on change in average price is not as determinative of total
sales as the other variables.
Based on the model, a $1,000 increase in the average new vehicle
price causes approximately 170,000 lost units in the first year,
followed by a reduction of another 600,000 units over the next ten
years as the initial sales decrease propagates over time through the
lagged variables and their coefficients. The price elasticity of new
car and light truck sales implied by alternative estimates of the
model's coefficients ranged from -0.2 to -0.3--meaning that changes in
their prices have moderate effects on total sales--which contrasts with
estimates of higher sensitivity to prices implied by some models.\228\
The analysis was unable to incorporate any measure of new car and light
truck fuel economy in the model that added to its ability to explain
historical variation in sales, even after experimenting with
alternative measures of such as the unweighted and sales-weighted
averages fuel economy of models sold in each quarter, the level of fuel
economy they were required to achieve, and the change in their fuel
economy from previous periods.
---------------------------------------------------------------------------
\228\ Effects on the used car market are accounted for
separately.
---------------------------------------------------------------------------
Despite the evidence in the literature, summarized above, that
consumers value most, if not all, of the fuel economy improvements when
purchasing new vehicles, the model described here operates at too high
a level of aggregation to capture these preferences. By modeling the
total number of new vehicles sold in a given year, it is necessary to
quantify important measures, like sales price or fuel economy, by
averages. Our model operates at a high level of aggregation, where the
average fuel economy represents an average across many vehicle types,
usage profiles, and fuel economy levels. In this context, the average
fuel economy was not a meaningful value with respect to its influence
on the total number of new vehicles sold. A number of recent studies
have indeed shown that consumers value fuel savings (almost) fully.
Those studies are frequently based on large datasets that are able to
control for all other vehicle attributes through a variety of
econometric techniques. They represent micro-level decisions, where a
buyer is (at least theoretically) choosing between a more or less
efficient version of a pickup truck (for example) that is otherwise
identical. In an aggregate sense, the average is not comparable to the
decision an individual consumer faces.
Estimating the sales response at the level of total new vehicle
sales likely fails to address valid concerns about changes to the
quality or attributes of new vehicles sold--both over time and in
response to price increases resulting from CAFE standards. However,
attempts to address such concerns would require significant additional
data, new statistical approaches, and structural changes to the CAFE
model over several years. It is also the case that using absolute
changes in the average price may be more limited than another
characterization of price that relies on distributions of household
income over time or percentage change in the new vehicle price. The
former would require forecasting a deeply uncertain quantity many years
into the future, and the latter only become relevant once the
simulation moves beyond the magnitude of observed price changes in the
historical series. Future versions of this model may use a different
characterization of cost that accounts for some of these factors if
their inclusion improves the model estimation and corresponding
forecast projections are available.
The changes in selling prices, fuel economy, and other features of
cars and light trucks produced during future model years that result
from manufacturers' responses to lower CAFE and GHG emission standards
are likely to affect both sales of individual models and the total
number of new vehicles sold. Because the values of changes in fuel
economy and other features to potential buyers are not completely
understood; however, the magnitude, and possibly even the direction, of
their effect on sales of new vehicles is difficult to anticipate. On
balance, it is reasonable to assume that the changes in prices, fuel
economy, and other attributes expected to result from their proposed
action to amend and establish fuel economy and GHG emission standards
are likely to increase total sales of new cars and light trucks during
future model years. Please provide comment on the relationship between
price increases, fuel economy, and new vehicle sales, as well as
methods to appropriately account for these relationships.
(d) Projecting New Vehicle Sales and Comparisons to Other Forecasts
The purpose of the sales response model is to allow the CAFE model
to simulate new vehicle sales in a given future model year, accounting
for the impact of a regulatory alternative's stringency on new vehicle
prices (in a macro-economic context that is identical across
alternatives). In order to accomplish this, it is important that the
model of sales response be dynamically stable, meaning that it responds
to shocks not by ``exploding,'' increasing or decreasing in a way that
is unbounded, but rather returns to a stable path, allowing the shock
to dissipate. The CAFE model uses the sales model described above to
dynamically project future sales; after the first year of the
simulation, lagged values of new vehicle sales are those that were
produced by the model itself rather than observed. The sales response
model constructed here uses two lagged dependent variables and simple
econometric conditions determine if the model is dynamically stable.
The coefficients of the one-year lag and the two-year lag,
[beta]1 and [beta]2, respectively must satisfy
three conditions. Their sum must be less than one, [beta]2 -
[beta]1 <1, and the absolute value of [beta]2
must be less than one. The coefficients of this model satisfy all three
conditions.
Using the Augural CAFE standards as the baseline, it is possible to
produce a series of future total sales as shown in Table-II-32. For
comparison, the table includes the calculated total light-duty sales of
a proprietary forecast purchased to support the 2016 Draft TAR
analysis, the total new light-duty sales in EIA's 2017 Annual Energy
Outlook, and a (short) forecast published in the Center for Automotive
Research's Q4 2017 Automotive Outlook. All of the forecasts in Table-
II-32 assume the Augural Standards are in place through MY 2025, though
assumptions about the costs required to comply with them likely differ.
As the table shows, despite differences among them, the dynamically
produced sales projection from the CAFE model is not qualitatively
different from the others.
[[Page 43076]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.047
While this forecast projects a relatively high, but flat, level of
new vehicle sales into the future, it is worth noting that it continues
another trend observed in the historical data. The time series of
annual new vehicle sales is volatile from year to year, but multi-year
averages are less so being sufficient to wash out the variation
associated with them peaks and valleys of the series. Despite the fact
that the moving average annual new vehicle sales has been growing over
the last four decades, it has not kept pace with U.S. population
growth. Data from the Federal Reserve Bank of St. Louis shows that the
per-capita sales of new vehicles peaked in 1986 and has declined more
than 25% from this peak to today's level.\231\ While the sales
projection in Table-II-32 would represent a historically high average
of new vehicle sales over the analysis period, it would not be
sufficient to reverse the trend of declining per-capita sales of new
vehicles during the analysis period, though it would continue the trend
at a slower rate.
---------------------------------------------------------------------------
\229\ Out of necessity, the analysis in today's rule conflates
production year (or ``model year'') and calendar year. The volumes
cited in the CAFE model forecast represent forecasted production
volumes for those model years, while the other represent calendar
year sales (rather than production)--during which two, or possibly
three, different model year vehicles are sold. In the long run, the
difference is not important. In the early years, there are likely to
be discrepancies.
\230\ U.S. Total Sales by Make, Automotive News, http://www.autonews.com/section/datalist18 (last visited June 22, 2018).
\231\ Mislinski, J. Light Vehicle Sales Per Capita: Our Latest
Look at the Long-Term Trend, Advisor Perspectives (June 1, 2018),
https://www.advisorperspectives.com/dshort/updates/2018/05/01/light-vehicle-sales-per-capita-our-latest-look-at-the-long-term-trend.
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In addition to the statistical model that estimates the response of
total new vehicle sales to changes in the average new vehicle price,
the CAFE model incorporates a dynamic fleet share model that modifies
the light truck (and, symmetrically, passenger car) share of the new
vehicle market. A version of this model first appeared in the 2012
final rule, when this fleet share component was introduced to ensure
greater internal consistency within inputs in the uncertainty analysis.
For today's analysis, this dynamic fleet share is enabled throughout
the analysis of alternatives.
The dynamic fleet share model is a series of difference equations
that determine the relative share of light trucks and passenger cars
based on the average fuel economy of each, the fuel price, and average
vehicle attributes like horsepower and vehicle mass (the latter of
which explicitly evolves as a result of the compliance simulation).
While this model was taken from EIA's National Energy Modeling System
(NEMS), it is applied at a different level. Rather than apply the
shares based on the regulatory class distinction, the CAFE model
applies the shares to body-style. This is done to account for the
large-scale shift in recent years to crossover utility vehicles that
have model variants in both the passenger car and light truck
regulatory fleets. The agencies have always modified their static
forecasts of new vehicle sales to reflect the PC/LT split present in
the Annual Energy Outlook; this integration continues that approach in
a way that ensures greater internal consistency when simulating
multiple regulatory alternatives (and conducting sensitivity analysis
on any of the factors that influence fleet share).
(e) Vehicle Choice Models as an Alternative Method To Estimate New
Vehicle Sales
Another potential option to estimate future new vehicle sales would
be to use a full consumer choice model. The agencies simulate
compliance with CAFE and CO2 standards for each manufacturer
using a disaggregated representation of its regulated vehicle fleets.
This means that each manufacturer may have hundreds of vehicle model
variants (e.g., the Honda Civic with the 6-cylinder engine, and the
Honda Civic with the 4-cylinder engine would each be treated as
different, in some ways, during the compliance simulation).\232\ While
the analysis accounts for a wide variety of attributes across these
vehicles, only a few of them change during the compliance simulation.
However, all of those attributes are relevant in the context of
consumer choice models.
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\232\ For more detail about the compliance simulation and
manufacturer fleet representation, see Section II.G.
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Aside from the computational intensity of simulating new vehicle
sales at the level of individual models--for all manufacturers, under
each regulatory alternative, over the next decade or more--it would be
necessary to include additional relationships
[[Page 43077]]
about how consumers trade off among vehicle attributes, which types of
consumers prefer which types of attributes (and how much), and how
manufacturers might strategically price these modified vehicles. This
requires a strategic pricing model, which each manufacturer has and
would likely be unwilling to share. Some of this strategic pricing
behavior occurs on small time-scale through the use of dealer
incentives, rebates on specific models, and creative financing offers.
When simulating compliance at the annual scale, it is effectively
impossible to account for these types of strategic decisions.
It is also true consumers have heterogeneous preferences that
change over time and determine willingness-to-pay for a variety of
vehicle attributes. These preferences change in response to marketing,
distribution, pricing, and product strategies that manufacturers may
change over time. With enough data, a consumer choice model could
stratify new vehicle buyers into types and attempt to measure the
strength of each type's preference for fuel economy, acceleration,
safety rating, perceived quality and reliability, interior volume, or
comfort. However, other factors also influence customers' purchase
decision, and some of these can be challenging to model. Consumer
proximity to dealerships, quality of service and customer experience at
dealerships, availability and terms of financing, and basic product
awareness may significantly factor into sales success.
Manufacturers' marketing choices may significantly and
unpredictably affect sales. Ad campaigns may increase awareness in the
market, and campaigns may reposition consumers' perception of the
brands and products. For example, in 2011 the Volkswagen Passat
featured an ad with a child in a Darth Vader costume (and showcased
remote start technology on the Passat). In MY 2012, Kia established the
Kia Soul with party rocking, hip-hop hamster commercials showcasing
push-button ignition, a roomy interior, and design features in the
brake lights. Both commercials raised awareness and highlighted basic
product features. Each commercial also impressed demographic groups
with pop culture references, product placement, and co-branding. While
the marketing budget of individual manufacturers may help a consumer
choice model estimate market share for a given brand, estimating the
impact of a given campaign on new sales is more challenging as
consumers make purchasing decisions based upon their own needs and
desires.
Modelers must understand how consumers and commercial buyers select
vehicles in order to effectively develop and implement a consumer
choice model in a compliance simulation. Consumers purchase vehicles
for a variety of reasons such as family need, need for more space, new
technology, changes to income and affordability of a new vehicle,
improved fuel economy, operating costs of current vehicles, and others.
Once committed to buying a vehicle, consumers use different processes
to narrow down their shopping list. Consumer choice decision attributes
include factors both related and not related to the vehicle design. The
vehicle's utility for those attributes is researched across many
different information sources as listed in the table below.
[GRAPHIC] [TIFF OMITTED] TP24AU18.048
An objective, attribute-based consumer choice model could lead to
projected swings in manufacturer market shares and individual model
volumes. The current approach simulates compliance for each
manufacturer assuming that it produces the same set of vehicles that it
produced in the initial year of the simulation (MY 2016 in today's
analysis). If a consumer choice model were to drive projected sales of
a given vehicle model below some threshold, as consumers have done in
the real market, the simulation currently has no way to generate a new
vehicle model to take its place. As demand changes across specific
market segments and models, manufacturers adapt by supplying new
vehicle nameplates and models (e.g., the proliferation of crossover
utility vehicles in recent years). Absent that flexibility in the
compliance simulation, even the more accurate consumer choice model may
produce unrealistic projections of future sales volumes at the model,
segment, or manufacturer level.
Comment is sought on the development and use of potential consumer
choice model in compliance simulations. Comment is also sought on the
appropriate breadth, depth, and complexity of considerations in a
consumer choice model.
(f) Industry Employment Baseline (Including Multiplier Effect) and Data
Description
In the first two joint CAFE/CO2 rulemakings, the
agencies considered an analysis of industry employment impacts in some
form in setting both CAFE and emissions standards; NHTSA conducted an
industry employment analysis in part to determine whether the standards
the agency set were economically practicable, that is, whether the
standards were ``within the financial capability of the industry, but
not so stringent as to'' lead to ``adverse economic consequences, such
as a significant loss of jobs or unreasonable elimination of consumer
choice.'' \233\ EPA similarly conducted an industry employment analysis
under the broad authority granted to the agency under the Clean Air
Act.\234\ Both agencies recognized the uncertainties inherent in
estimating industry employment impacts; in fact, both agencies
dedicated a substantial amount of discussion to uncertainty in industry
employment analyses in the 2012 final rule for MYs 2017 and
beyond.\235\ Notwithstanding these uncertainties, CAFE and
CO2 standards do impact industry labor hours, and providing
the best analysis practicable better informs stakeholders
[[Page 43078]]
and the public about the standards' impact than would omitting any
estimates of potential labor impacts.
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\233\ 67 FR 77015, 77021 (Dec. 16, 2002).
\234\ See George E. Warren Corp. v. EPA, 159 F.3d 616, 623-624
(D.C. Cir. 1998) (ordinarily permissible for EPA to consider factors
not specifically enumerated in the Act).
\235\ See 77 FR 62624, 62952, 63102 (Oct. 15, 2012).
---------------------------------------------------------------------------
Today many of the effects that were previously qualitatively
identified, but not considered, are quantified. For instance, in the
PRIA for the 2017-2025 rule EPA identified ``demand effects,'' ``cost
effects,'' and ``factor shift effects'' as important considerations for
industry labor, but the analysis did not attempt to quantify either the
demand effect or the factor shift effect.\236\ Today's industry labor
analysis quantifies direct labor changes that were qualitatively
discussed previously.
---------------------------------------------------------------------------
\236\ Regulatory Impact Analysis: Final Rulemaking for 2017-2025
Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate
Average Fuel Economy Standards, U.S. EPA at 8-24 to 8-32 (Aug.
2012).
---------------------------------------------------------------------------
Previous analyses and new methodologies to consider direct labor
effects on the automotive sector in the United States were improved
upon and developed. Potential changes that were evaluated include (1)
dealership labor related to new light duty vehicle unit sales; (2)
changes in assembly labor for vehicles, for engines and for
transmissions related to new vehicle unit sales; and (3) changes in
industry labor related to additional fuel savings technologies,
accounting for new vehicle unit sales. All automotive labor effects
were estimated and reported at a national level,\237\ in job-years,
assuming 2,000 hours of labor per job-year.
---------------------------------------------------------------------------
\237\ The agencies recognize a few local production facilities
may contribute meaningfully to local economies, but the analysis
reported only on national effects.
---------------------------------------------------------------------------
The analysis estimated labor effects from the forecasted CAFE model
technology costs and from review of automotive labor for the MY 2016
fleet. For each vehicle in the CAFE model analysis, the locations for
vehicle assembly, engine assembly, and transmission assembly and
estimated labor in MY 2016 were recorded. The percent U.S. content for
each vehicle was also recorded. Not all parts are made in the United
States, so the analysis also took into account the percent U.S. content
for each vehicle as manufacturers add fuel-savings technologies. As
manufacturers added fuel-economy technologies in the CAFE model
simulations, the analysis assumed percent U.S. content would remain
constant in the future, and that the U.S. labor added would be
proportional to U.S. content. From this foundation, the analysis
forecasted automotive labor effects as the CAFE model added fuel
economy technology and adjusted future sales for each vehicle.
The analysis also accounts for sales projections in response to the
different regulatory alternatives; the labor analysis considers changes
in new vehicle prices and new vehicle sales (for further discussion of
the sales model, see Section 2.E). As vehicle prices rise, the analysis
expected consumers to purchase fewer vehicles than they would have at
lower prices. As manufacturers sell fewer vehicles, the manufacturers
may need less labor to produce the vehicles and less labor to sell the
vehicles. However, as manufacturers add equipment to each new vehicle,
the manufacturers will require human resources to develop, sell, and
produce additional fuel-saving technologies. The analysis also accounts
for the potential that new standards could shift the relative shares of
passenger cars and light trucks in the overall fleet (see Section 2.E);
insofar as different vehicles involved different amounts of labor, this
shifting impacts the quantity of estimated labor. The CAFE model
automotive labor analysis takes into account reduction in vehicle
sales, shifts in the mix of passenger cars and light trucks, and
addition of fuel-savings technologies.
For today's analysis, it was assumed that some observations about
the production of MY 2016 vehicles would carry forward, unchanged into
the future. For instance, assembly plants would remain the same as MY
2016 for all products now, and in the future. The analysis assumed
percent U.S. content would remain constant, even as manufacturers
updated vehicles and introduced new fuel-saving technologies. It was
assumed that assembly labor hours per unit would remain at estimated MY
2016 levels for vehicles, engines, and transmissions, and the factor
between direct assembly labor and parts production jobs would remain
the same. When considering shifts from one technology to another, the
analysis assumed revenue per employee at suppliers and original
equipment manufacturers would remain in line with MY 2016 levels, even
as manufacturers added fuel-saving technologies and realized cost
reductions from learning.
The analysis focused on automotive labor because adjacent
employment factors and consumer spending factors for other goods and
services are uncertain and difficult to predict. The analysis did not
consider how direct labor changes may affect the macro economy and
possibly change employment in adjacent industries. For instance, the
analysis did not consider possible labor changes in vehicle maintenance
and repair, nor did it consider changes in labor at retail gas
stations. The analysis did not consider possible labor changes due to
raw material production, such as production of aluminum, steel, copper
and lithium, nor did the agencies consider possible labor impacts due
to changes in production of oil and gas, ethanol, and electricity. The
analysis did not analyze effects of how consumers could spend money
saved due to improved fuel economy, nor did the analysis assess the
effects of how consumers would pay for more expensive fuel savings
technologies at the time of purchase; either could affect consumption
of other goods and services, and hence affect labor in other
industries. The effects of increased usage of car-sharing, ride-
sharing, and automated vehicles were not analyzed. The analysis did not
estimate how changes in labor from any industry could affect gross
domestic product and possibly affect other industries as a result.
Finally, no assumptions were made about full-employment or not
full-employment and the availability of human resources to fill
positions. When the economy is at full employment, a fuel economy
regulation is unlikely to have much impact on net overall U.S.
employment; instead, labor would primarily be shifted from one sector
to another. These shifts in employment impose an opportunity cost on
society, approximated by the wages of the employees, as regulation
diverts workers from other activities in the economy. In this
situation, any effects on net employment are likely to be transitory as
workers change jobs (e.g., some workers may need to be retrained or
require time to search for new jobs, while shortages in some sectors or
regions could bid up wages to attract workers). On the other hand, if a
regulation comes into effect during a period of high unemployment, a
change in labor demand due to regulation may affect net overall U.S.
employment because the labor market is not in equilibrium. Schmalansee
and Stavins point out that net positive employment effects are possible
in the near term when the economy is at less than full employment due
to the potential hiring of idle labor resources by the regulated sector
to meet new requirements (e.g., to install new equipment) and new
economic activity in sectors related to the regulated sector longer
run, the net effect on employment is more difficult to predict and will
depend on the way in which the related industries respond to the
regulatory requirements. For that reason, this analysis does not
include multiplier effects but instead focuses on
[[Page 43079]]
labor impacts in the most directly affected industries. Those sectors
are likely to face the most concentrated labor impacts.
Comment is sought on these assumptions and approaches in the labor
analysis.
4. Estimating Labor for Fuel Economy Technologies, Vehicle Components,
Final Assembly, and Retailers
The following sections discuss the approaches to estimating factors
related to dealership labor, final assembly labor and parts production,
and fuel economy technology labor.
(a) Dealership Labor
The analysis evaluated dealership labor related to new light-duty
vehicle sales, and estimated the labor hours per new vehicle sold at
dealerships, including labor from sales, finance, insurance, and
management. The effect of new car sales on the maintenance, repair, and
parts department labor is expected to be limited, as this need is based
on the vehicle miles traveled of the total fleet. To estimate the labor
hours at dealerships per new vehicle sold, the National Automobile
Dealers Association 2016 Annual Report, which provides franchise dealer
employment by department and function, was referenced.\238\ The
analysis estimated that slightly less than 20% of dealership employees'
work relates to new car sales (versus approximately 80% in service,
parts, and used car sales), and that on average dealership employees
working on new vehicle sales labor for 27.8 hours per new vehicle sold.
---------------------------------------------------------------------------
\238\ NADA Data 2016: Annaul Financial Profile of America's
Franchised New-Car Dealerships, National Automobile Dealers
Association, https://www.nada.org/2016NADAdata/ (last visited June
22, 2018).
---------------------------------------------------------------------------
(b) Final Assembly Labor and Parts Production
How the quantity of assembly labor and parts production labor for
MY 2016 vehicles would increase or decrease in the future as new
vehicle unit sales increased or decreased was estimated.
Specific assembly locations for final vehicle assembly, engine
assembly, and transmission assembly for each MY 2016 vehicle were
identified. In some cases, manufacturers assembled products in more
than one location, and the analysis identified such products and
considered parallel production in the labor analysis.
The analysis estimated industry average direct assembly labor per
vehicle (30 hours), per engine (four hours), and per transmission (five
hours) based on a sample of U.S. assembly plant employment and
production statistics and other publicly available information. The
analysis recognizes that some plants may use less labor than the
analysis estimates to produce the vehicle, the engine, or the
transmission, and other plants may have used more labor. The analysis
used the assembly locations and industry averages for labor per unit to
estimate U.S. assembly labor hours for each vehicle. U.S. assembly
labor hours per vehicle ranged from as high as 39 hours if the
manufacturer assembled the vehicle, engine, and transmission at U.S.
plants, to as low as zero hours if the manufacturer imported the
vehicle, engine, and transmission.
The analysis also considered labor for part production in addition
to labor for final assembly. Motor vehicle and equipment manufacturing
labor statistics from the U.S. Census Bureau, the Bureau of Labor
Statistics,\239\ and other publicly available sources were surveyed.
Based on these sources, the analysis noted that the historical average
ratio of vehicle assembly manufacturing employment to employment for
total motor vehicle and equipment manufacturing for new vehicles
remained roughly constant over the period from 2001 through 2013, at a
ratio of 5.26. Observations from 2001-2013 spanned many years, many
combinations of technologies and technology trends, and many economic
conditions, yet the ratio remained about the same. Accordingly, the
analysis scaled up estimated U.S. assembly labor hours by a factor of
5.26 to consider U.S. parts production labor in addition to assembly
labor for each vehicle.
---------------------------------------------------------------------------
\239\ NAICS Code 3361, 3363.
---------------------------------------------------------------------------
The industry estimates for vehicle assembly labor and parts
production labor for each vehicle scaled up or down as unit sales
scaled up or down over time in the CAFE model.
(c) Fuel Economy Technology Labor
As manufacturers spend additional dollars on fuel-saving
technologies, parts suppliers and manufacturers require human resources
to bring those technologies to market. Manufacturers may add, shift, or
replace employees in ways that are difficult for the agencies to
predict in response to adding fuel-savings technologies; however, it is
expected that the revenue per labor hour at original equipment
manufacturers (OEMs) and suppliers will remain about the same as in MY
2016 even as industry includes additional fuel-saving technology.
To estimate the average revenue per labor hour at OEMs and
suppliers, the analysis looked at financial reports from publicly
traded automotive businesses.\240\ Based on recent figures, it was
estimated that OEMs would add one labor year per $633,066 revenue \241\
and that suppliers would add one labor year per $247,648 in
revenue.\242\ These global estimates are applied to all revenues, and
U.S. content is applied as a later adjustment. In today's analysis, it
was assumed these ratios would remain constant for all technologies
rather than that the increased labor costs would be shifted toward
foreign countries. Comment is sought on the realism of this assumption.
---------------------------------------------------------------------------
\240\ The analysis considered suppliers that won the Automotive
News ``PACE Award'' from 2013-2017, covering more than 40 suppliers,
more than 30 of which are publicly traded companies. Automotive News
gives ``PACE Awards'' to innovative manufacturers, with most recent
winners earning awards for new fuel-savings technologies.
\241\ The analysis assumed incremental OEM revenue as the retail
price equivalent for technologies, adjusting for changes in sales
volume.
\242\ The analysis assumed incremental supplier revenue as the
technology cost for technologies before retail price equivalent
mark-up, adjusting for changes in sales volume.
---------------------------------------------------------------------------
(d) Labor Calculations
The analysis estimated the total labor as the sum of three
components: Dealership hours, final assembly and parts production, and
labor for fuel-economy technologies (at OEM's and suppliers). The CAFE
model calculated additional labor hours for each vehicle, based on
current vehicle manufacturing locations and simulation outputs for
additional technologies, and sales changes. The analysis applied some
constants to all vehicles,\243\ but other constants were vehicle
specific,\244\ or year specific for a vehicle.\245\
---------------------------------------------------------------------------
\243\ The analysis applied the same assumptions to all
manufacturers for annual labor hours per employee, dealership hours
per unit sold, OEM revenue per employee, supplier revenue per
employee, and factor for the jobs multiplier.
\244\ The analysis made vehicle specific assumptions about
percent U.S. content and U.S. assembly employment hours.
\245\ The analysis estimated technology cost for each vehicle,
for each year based on the technology content applied in the CAFE
model, year-by-year.
---------------------------------------------------------------------------
While a multiplier effect of all U.S. automotive related jobs on
non-auto related U.S. jobs was not considered for today's analysis, the
analysis did program a ``global multiplier'' that can be used to scale
up or scale down the total labor hours. This multiplier exists in the
parameters file, and for today's analysis the analysis set the value at
1.00.
5. Additional Costs and Benefits Incurred by New Vehicle Buyers
Some costs of purchasing and owning a new or used vehicle scale
with the
[[Page 43080]]
value of the vehicle. Where fuel economy standards increase the
transaction price of vehicles, they will affect both the absolute
amount paid in sales tax and the average amount of financing required
to purchase the vehicle. Further, where they increase the MSRP, they
increase the appraised value upon which both value-related registration
fees and a portion of insurance premiums are based. The analysis
assumes that the transaction price is a set share of the MSRP, which
allows calculation of these factors as shares of MSRP. Below the
assumptions made about how each of these additional costs of vehicle
purchase and ownership scale with the MSRP and how the analysis arrived
at these assumptions are discussed.
(a) Sales Taxes
The analysis took auto sales taxes by state \246\ and weighted them
by population by state to determine a national weighted-average sales
tax of 5.46%. The analysis sought to weight sales taxes by new vehicle
sales by state; however, such data were unavailable. It is recognized
that for this purpose, new vehicle sales by state is a superior
weighting mechanism to Census population; in effort to approximate new
vehicle sales by state, a study of the change in new vehicle
registrations (using R.L. Polk data) by state across recent years was
conducted, resulting in a corresponding set of weights. Use of the
weights derived from the study of vehicle registration data resulted in
a national weighted-average sales tax rate almost identical to that
resulting from the use of Census population estimates as weights, just
slightly above 5.5%. The analysis opted to utilize Census population
rather than the registration-based proxy of new vehicle sales as the
basis for computing this weighted average, as the end results were
negligibly different and the analytical approach involving new vehicle
registrations had not been as thoroughly reviewed. Note: Sales taxes
and registration fees are transfer payments between consumers and the
Federal government and are therefore not considered a cost in the
societal perspective. However, these costs are considered as additional
costs in the private consumer perspective.
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\246\ See Car Tax by State, FactoryWarrantyList.com, http://www.factorywarrantylist.com/car-tax-by-state.html (last visited June
22, 2018). Note: County, city, and other municipality-specific taxes
were excluded from weighted averages, as the variation in locality
taxes within states, lack of accessible documentation of locality
rates, and lack of availability of weights to apply to locality
taxes complicate the ability to reliably analyze the subject at this
level of detail. Localities with relatively high automobile sales
taxes may have relatively fewer auto dealerships, as consumers would
endeavor to purchase vehicles in areas with lower locality taxes,
therefore reducing the effect of the exclusion of municipality-
specific taxes from this analysis.
---------------------------------------------------------------------------
(b) Financing Costs
The analysis assumes 85% of automobiles are financed based on
Experian's quarter 4, 2016 ``State of the Automotive Finance Market,''
which notes that 85.2% of 2016 new vehicles were financed, as were
85.9% of 2015 new vehicle purchases.\247\ The analysis used data from
Wards Automotive and JD Power on the average transaction price of new
vehicle purchases, average financed new auto beginning principal, and
the average incentive as a percent of MSRP to compute the ratio of the
average financed new auto principal to the average new vehicle MSRP for
calendar years 2011-2016. Table-II-34 shows that the average financed
auto principal is between 82 and 84% of the average new vehicle MSRP.
Using the assumption that 85% of new vehicle purchases involve some
financing, the average share of the MSRP financed for all vehicles
purchased, including non-financed transactions, rather than only those
that are financed, was computed. Table-II-34 shows that this share
ranges between 70 and 72%. From this, the analysis assumed that on an
aggregate level, including all new vehicle purchases, 70% of the value
of all vehicles' MSRP is financed. It is likely that the share financed
is correlated with the MSRP of the new vehicle purchased, but for
simplification purposes, it is assumed that 70% of all vehicle costs
are financed, regardless of the MSRP of the vehicle. In measurements of
the impacts on the average consumer, this assumption will not affect
the outcome of our calculation, though this assumption will matter for
any discussions about how many, or which, consumers bear the brunt of
the additional cost of owning more expensive new vehicles. For sake of
simplicity, the model also assumes that increasing the cost of new
vehicles will not change the share of new vehicle MSRP that is
financed; the relatively constant share from 2011-2016 when the average
MSRP of a vehicle increased 10% supports this assumption. It is
recognized that this is not indicative of average individual consumer
transactions but provides a useful tool to analyze the aggregate
marketplace.
---------------------------------------------------------------------------
\247\ Zabritski, M. State of the Automotive Finance Market: A
look at loans and leases in Q4 2016, Experian, https://www.experian.com/assets/automotive/quarterly-webinars/2016-Q4-SAFM-revised.pdf (last visited June 22, 2018).
[GRAPHIC] [TIFF OMITTED] TP24AU18.049
From Wards Auto data, the average 48- and 60-month new auto
interest rates were 4.25% in 2016, and the average finance term length
for new autos was 68 months. It is recognized that longer financing
terms generally include higher interest rates. The share financed,
interest rate, and finance term length are added as inputs in the
[[Page 43081]]
parameters file so that they are easier to update in the future. Using
these inputs the model computes the stream of financing payments paid
for the average financed purchases as the following:
[GRAPHIC] [TIFF OMITTED] TP24AU18.050
Note: The above assumes the interest is distributed evenly over the
period, when in reality more of the interest is paid during the
beginning of the term. However, the incremental amount calculated as
attributable to the standard will represent the difference in the
annual payments at the time that they are paid, assuming that a
consumer does not repay early. This will represent the expected change
in the stream of financing payments at the time of financing.
The above stream does not equate to the average amount paid to
finance the purchase of a new vehicle. In order to compute this amount,
the share of financed transactions at each interest rate and term
combination would have to be known. Without having projections of the
full distribution of the auto finance market into the future, the above
methodology reasonably accounts for the increased amount of financing
costs due to the purchase of a more expensive vehicle, on an average
basis taking into account non-financed transactions. Financing payments
are also assumed to be an intertemporal transfer of wealth for a
consumer; for this reason, it is not included in the societal cost and
benefit analysis. However, because it is an additional cost paid by the
consumer, it is calculated as a part of the private consumer welfare
analysis.
It is recognized that increased finance terms, combined with rising
interest rates, lead to a longer period of time before a consumer will
have positive equity in the vehicle to trade in toward the purchase of
a newer vehicle. This has impacts in terms of consumers either trading
vehicles with negative equity (thereby increasing the amount financed
and potentially subjecting the consumer to higher interest rates and/or
rendering the consumer unable to obtaining financing) or delaying the
replacement of the vehicle until they achieve suitably positive equity
to allow for a trade. Comment is sought on the effect these
developments will have on the new vehicle market, both in general, and
in light of increased stringency of fuel economy and GHG emission
standards. Comment is also sought on whether and how the model should
account for consumer decisions to purchase a used vehicle instead of a
new vehicle based upon increased new vehicle prices in response to
increased CAFE standard stringency.
(c) Insurance Costs
More expensive vehicles will require more expensive collision and
comprehensive (e.g., fire and theft) car insurance. Actuarially fair
insurance premiums for these components of value-based insurance will
be the amount an insurance company will pay out in the case of an
incident type weighted by the risk of that type of incident occurring.
It is expected that the same driver in the same vehicle type will have
the same risk of occurrence for the entirety of a vehicle's life so
that the share of the value of a vehicle paid out should be constant
over the life of a vehicle. However, the value of vehicles will decline
at some depreciation rate so that the absolute amount paid in value-
related insurance will decline as the vehicle depreciates. This is
represented in the model as the following stream of expected collision
and comprehensive insurance payments:
[GRAPHIC] [TIFF OMITTED] TP24AU18.051
To utilize the above framework, estimates of the share of MSRP paid
on collision and comprehensive insurance and of annual vehicle
depreciations are needed to implement the above equation. Wards has
data on the average annual amount paid by model year for new light
trucks and passenger cars on collision, comprehensive and damage and
liability insurance for model years 1992-2003; for model years 2004-
2016, they only offer the total amount paid for insurance premiums. The
share of total insurance premiums paid for collision and comprehensive
coverage was computed for 1979-2003. For cars the share ranges from 49
to 55%, with the share tending to be largest towards the end of the
series. For trucks the share ranges from 43 to 61%, again, with the
share increasing towards the end of the series. It is assumed that for
model years 2004-2016, 60% of insurance premiums for trucks, and 55%
for cars, is paid for collision and comprehensive. Using these shares
the absolute amount paid for collision and comprehensive coverage for
cars and trucks is computed. Then each regulatory class in the fleet is
weighted by share to estimate the overall average amount paid for
collision and comprehensive insurance by model year as shown in Table-
II-35. The average share of the initial MSRP paid in collision and
comprehensive insurance by model year is then computed. The average
share paid for model years 2010-2016 is 1.83% of the initial MSRP. This
is used as the share of the value of a new vehicle paid for collision
and comprehensive in the future.
[[Page 43082]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.052
2017 data from Fitch Black Book was used as a source for vehicle
depreciation rates; two- to six-year-old vehicles in 2016 had an
average annual depreciation rate of 17.3%.\248\ It is assumed that
future depreciation rates will be like recent depreciation, and the
analysis used the same assumed depreciation. Table-II-36 shows the
cumulative share of the initial MSRP of a vehicle assumed to be paid in
collision and comprehensive insurance in five-year age increments under
this depreciation assumption, conditional on a vehicle surviving to
that age--that is, the expected insurance payments at the time of
purchase will be weighted by the probability of surviving to that age.
If a vehicle lives to 10 years, 9.9% of the initial MSRP is expected to
be paid in collision and comprehensive payments; by 20 years 11.9% of
the initial MSRP; finally, if a vehicle lives to age 40, 12.4% of the
initial MSRP. As can be seen, the majority of collision and
comprehensive payments are paid by the time the vehicle is 10 years
old.
---------------------------------------------------------------------------
\248\ Fitch Ratings Vehicle Depreciation Report February 2017,
Black Book, http://www.blackbook.com/wp-content/uploads/2017/02/Final-February-Fitch-Report.pdf (last visited June 22, 2018).
[GRAPHIC] [TIFF OMITTED] TP24AU18.053
The increase in insurance premiums resulting from an increase in
the average value of a vehicle is a result of an increase in the
expected amount insurance companies will have to pay out in the case of
damage occurring to the driver's vehicle. In this way, it is a cost to
the private consumer, attributable to the CAFE standard that caused the
price increase.
(d) Consumer Acceptance of Specific Technologies
In previous rulemaking analyses, NHTSA imposed an economic cost of
lost welfare to buyers of advanced electric vehicles. NHTSA chose to
model a 75-mile EV for early adopters, who we assume would not be
concerned with the lower range, and a 150-mile EV for the broader
market. The initial five percent of EV sales were assumed to go to
early adopters, with the remainder being 150-mile EVs. The broader
market was assumed to have some lower utility for the 150-mile EV, due
to the lower driving range between refueling events relative to a
conventional vehicle. Thus, an additional social cost of about $3,500
per vehicle was assigned to the EV150 to capture the lost utility to
consumers.\249\ Additionally, NHTSA imposed a ``relative value loss''
of 1.94% of the vehicle's MSRP to reflect the economic value of the
difference between the useful life of a conventional ICE and the 150-
mile EV when it reaches a 55% battery capacity (as a result of battery
deteroriation).\250\ In subsequent analyses (the 2016 Draft TAR
analysis and today's analysis), NHTSA removed the low-range EVs from
its technology set due to both weak consumer demand for low-range EVs
in the marketplace and subsequent technology advances that make 200-
mile EVs a more practical option for new EVs produced in future model
years. The exclusion of low-range EVs in the technology set reduced the
need to account for consumer welfare losses
[[Page 43083]]
attributable to reduced driving range. While the sensitivity analysis
explores some potential for continuing consumer value loss, even in the
improved electrified powertrain vehicles, the central analysis assumes
that no value loss exists for electrified powertrains. However, ongoing
low sales volumes and a growing body of literature suggest that
consumer welfare losses may still exist if manufacturers are forced to
produce electric vehicles in place of vehicles with internal combustion
engines (forcing sacrifices to cargo capacity or driving range) in
order to comply with standards. This topic will receive ongoing
investigation and revision before the publication of the final rule.
Please provide comments and any relevant data that would help to inform
the estimation of implementation of any value loss related to
sacrificed attributes in electric vehicles.
---------------------------------------------------------------------------
\249\ Based on Michael K. Hidrue, George R. Parsons, Willett
Kempton, Meryl P. Gardner, Willingness to pay for electric vehicles
and their attributes, Resource and Energy Economics,Volume 33, Issue
3, 2011, Pages 686-705.
\250\ The vehicle was assumed to be retired once the capacity
reached 55 percent of its initial capacity, and the residual
lifetime miles from that point forward were valued, discounted, and
expressed as a fraction of initial MSRP.
---------------------------------------------------------------------------
One reason it was necessary to account for welfare losses from
reduced driving range in this way is that, in previous rulemakings, the
agencies implicitly assumed that every vehicle in the forecast would be
produced and purchased and that manufacturers would pass on the entire
incremental cost of fuel-saving technologies to new car (and truck)
buyers. However, many stakeholders commented that consumers are not
willing to pay the full incremental costs for hybrids, plug-in hybrids,
and battery electric vehicles.\251\ For this analysis, consumer
willingness to pay for HEVs, PHEVs, BEVs relative to comparable ICE
vehicles was investigated. The analysis compared the estimated price
premium the electrified vehicles command in the used car market and
estimated the willingness to pay premium for new vehicles with
electrification technologies at age zero relative to their internal
combustion engine counterparts. For the analysis, the willingness to
pay was compared with the expected incremental cost to produce
electrification technologies. Manufacturers also contributed
confidential business information about the costs, revenues, and
profitability of their electrified vehicle lines. The CBI provided a
valuable check on the empirical work described below. As a result of
this examination, we no longer assume manufacturers can pass on the
entire incremental cost of hybrid, plug-in hybrid, and battery electric
vehicles to buyers of those vehicles. The difference between the
buyer's willingness-to-pay for those technologies, and the cost to
produce them, must be recovered from buyers of other vehicles in a
manufacturer's product portfolio or sacrificed from its profits, or
sacrificed from dealership profits, or supplemented with State or
Federal incentives (or, some combination of the four).
---------------------------------------------------------------------------
\251\ See e.g., Comment by Alliance of Automobile Manufacturers,
Docket ID EPA-HQ-OAR-2015-0827-4089 and NHTSA-2016-0068-0072.
---------------------------------------------------------------------------
Using data from the used vehicle market, statistical models were
fit to estimate consumer willingness to pay for new vehicles with
varying levels of electrification relative to comparable internal
combustion engine vehicles was evaluated in four steps. The analysis
(1) gathered used car fair market value for select vehicles; (2)
developed regression models to estimate the portion of vehicle
depreciation rate attributable to the vehicle nameplate and the portion
attributable to the vehicle's technology content at each age (using
fixed effects for nameplates and specific electrification
technologies); (3) estimated the value of vehicles at age zero (i.e.,
when the vehicles were new); and (4) compared new vehicle values for
comparable vehicles across different electrification levels (i.e.,
internal combustion, HEV, PHEV, and BEV) to estimate willingness-to-pay
for the electric technology relative to an ICE.
The dataset used for estimation consisted of vehicle attribute data
from Edmunds and transaction data from Kelley Blue Book published
online in June and July of 2017 for select vehicles of interest.\252\
\253\ The dataset was constructed to contain pairs of vehicles that
were nearly the same, except for type of powertrain (internal
combustion versus some amount of electrification). For instance, the
dataset contained used vehicle prices for the Honda Accord and Honda
Accord Hybrid, Toyota Camry and Toyota Camry Hybrid, Ford Fusion and
Ford Fusion Hybrid, Kia Soul and Kia Soul EV, and so on for several
model years. In some cases, the manufacturer produced no identically
equivalent internal combustion engine vehicle, so a similar internal
combustion vehicle produced by the same manufacturer was used as the
point of comparison. For example, the Nissan Leaf was paired with the
Nissan Versa, as well as the Toyota Prius and Toyota Corolla. Only
vehicles available for private sale, and in good vehicle condition were
included in the analysis.\254\ The dataset contains fewer observations
for PHEVs and BEVs because manufacturers have produced fewer examples
of vehicles with these technologies, compared to HEV and ICE vehicles.
In all of these cases, trim level and options packages were matched
between ICE and electric powertrains to minimize the degree of non-
powertrain difference between vehicle pairs. The resale price data
spanned many model years, but most observations in the dataset
represent MY 2013 through MY 2016.
---------------------------------------------------------------------------
\252\ See Edmunds, https://www.edmunds.com/ (last visited June
22, 2018). Edmunds publishes automotive data, reviews, and advice.
\253\ See Kelley Blue Book, https://www.kbb.com/ (last visited
June 22, 2018). Kelley Blue Book, part of Cox Automotive's
Autotrader brand, provides automotive research, reviews, and advice,
including estimated market values of new and used vehicles.
\254\ It is possible ``good'' vehicles for all ages may have
inadvertently introduced a small bias in the sample, as a ``good''
conditioning rating on a vehicle just a year or two old may not be
in average condition relative to other vehicles of the vintage, but
a ``good'' rating for a much older car may reflect an impeccably
maintained vehicle.
---------------------------------------------------------------------------
The regression models used to estimate the transaction price (or
``Value'') as a function of age, control for the type of powertrain
(ICE, HEV, PHEV, and BEV) and nameplate to account for their impact on
the value of the vehicle as it ages.\255\ The regression takes the
following form, with ICE, HEV, PHEV, and BEV binary variables (0, or
1), and age defined as 2017 minus the model year was used:
---------------------------------------------------------------------------
\255\ In the case of electrified vehicles with no internal
combustion engine equivalent, the analysis grouped like vehicle
pairs together under the same nameplate fixed effects (or
FENameplate). Tesla vehicles have no internal combustion
engine equivalent, and the used vehicle market for Tesla has not
cleared in the same way because of a variety of unique business
factors (previously, Tesla guaranteed resale value prices for their
products, which was a factory incentive program that only recently
ended, no longer applying to vehicles sold after July 1, 2016).
These two factors impaired the quality of used Tesla data for the
purposes of the analysis, so the agencies excluded Tesla vehicles
from today's analysis on customer willingness-to-pay for electrified
vehicles.
1n(Value = ,[beta]1(ICE * Age) + [beta]2(HEV *
Age) + [beta]3(PHEV * Age) + [beta]4(BEV * Age) +
[beta]5(HEV) + [beta]6(PHEV) +
---------------------------------------------------------------------------
[beta]7(BEV) + FENameplate
For each observation in the dataset, the ``Value'' at age zero is
determined by setting the age variable to zero and solving.
[GRAPHIC] [TIFF OMITTED] TP24AU18.333
[[Page 43084]]
The estimated willingness-to-pay for electrified powertrain
packages over an internal combustion engine in an otherwise similar
vehicle is computed as the difference between their estimated initial
values, using the functions above. These pair-wise differences are
averaged to estimate a price premium for new vehicles with HEV, PHEV,
and BEV technologies. This analysis suggests that consumers are willing
to pay more for new electrified vehicles than their new internal engine
combustion counterparts, but only a little more, and not necessarily
enough to cover the relatively large projected incremental cost to
produce these vehicles. Specifically, the analysis estimated consumers
are willing to pay between $2,000 and $3,000 more for the electrified
powertrains considered here than their internal combustion engine
counterparts.
[GRAPHIC] [TIFF OMITTED] TP24AU18.054
Table-II-37 illustrates the variation in willingness-to-pay by
electrification level (although the statistical model did not
distinguish between PHEV30 and PHEV50 due to the small number of
available operations for plug-in hybrids). As the table demonstrates,
the difference between the median and mean predicted price premium for
PHEVs is significant. The limited number of PHEV observations were not
uniformly distributed among the nameplates present, and some of the
luxury vehicles in the set retained value in a way that skewed the
average. The CBI acquired from manufacturers was more consistent with
the mean than median value (except for the PHEVs).
Additionally, the Kelley Blue Book data suggest that the used
electrified vehicles were often worth less than their used internal
combustion engine counterpart vehicles after a few years of use.\256\
As Table-II-38 illustrates, the value of the price premium shrinks as
the vehicles age and depreciate. Using the statistical model, we
estimate that strong hybrids hold less than $100 of the initial price
premium by age eight (on average). While the battery electric vehicles
appear to be worth less than their ICE counterparts by age eight, there
is limited data about this emerging segment of the new vehicle market.
These independently-produced results using publicly available data were
in line with manufacturers' reported confidential business information.
---------------------------------------------------------------------------
\256\ The analysis did not identify an underlying reason for
this observation, but the agencies posit for discussion purposes
there could be some interaction between maintenance costs and
batteries or maintenance costs and low volume vehicles.
Alternatively, new electrified vehicles may be superior to previous
generation vehicles, and new electrified vehicles may be offered at
lower prices still because of a variety of market conditions.
[GRAPHIC] [TIFF OMITTED] TP24AU18.055
The ``technology cost burden'' numbers used in today's analysis
represent the amount of a given technology's incremental cost that
manufacturers are unable to pass along to the buyer of a given vehicle
at the time of purchase. The burden is defined as the difference
between estimated willingness-to-pay, itself a combination of the
estimated values and confidential business information received from
manufacturers any tax credits that can be passed through in the price,
and the cost of the technology. In general, the incremental
willingness-to-pay falls well short of the costs currently projected
for HEVs, PHEVs, and BEVs; for example, BEV technology can add roughly
$18,000 in equipment costs to the vehicle after standard retail price
equivalent markups (with a large portion of those costs being
batteries), but the estimated willingness-to-pay is only about $3,000.
While tax credits offset some, if not most of that difference for PHEVs
and BEVs, there is some residual amount that buyers of new electrified
vehicles are currently unwilling to cover, and that must either come
from forgone profits or be passed
[[Page 43085]]
along to buyers of other vehicles in a manufacturer's portfolio.
Manufacturers may be able to recover some or all of these costs by
charging higher prices for their other models, in which case it will
represent a welfare loss to buyers of other vehicles (even if not to
buyers of HEVs, PHEVs, or BEVs themselves). To the extent that they are
unable to do so and must absorb part or all of these costs, their
profits will decline, and in effect this cost will be borne by their
investors. In practice, the analysis estimates benefits and costs to
car and light truck manufacturers and buyers under the assumption that
each manufacturer recovers all technology costs and civil penalties it
incurs from buyers via higher average prices for the models it produces
and sells, although sufficient information to support specific
assumptions about price increases for individual models is not present.
In effect, this means that any part of a manufacturer's costs to
convert specific models to electric drive technologies that it cannot
recover by charging higher prices to their buyers will be borne
collectively by buyers of the other models they produce. Each of those
buyers is in effect assumed to pay a slight premium (or ``markup'')
over the manufacturer's cost to produce the models they purchase
(including the cost of any technology used to improve its fuel
economy), this premium on average is modeled to recover the full cost
of technology applied to all vehicles to improve the fuel economy of
the fleet. So, even though electrified vehicles are modeled as if their
buyers are unwilling to pay the full cost of the technology associated
with their fuel economy improvement, the price borne by the average new
vehicle buyer represents the average incremental technology cost for
all applied technology, the sum of all technology costs divided by the
number of units sold, across all classes, for each manufacturer.
The willingness-to-pay analysis described above relies on used
vehicle data that is widely available to the public. Market tracking
services update used vehicle price estimates regularly as fuel prices
and other market conditions change, making the data easy to update in
the future as market conditions change. The used vehicle data also
account for consumer willingness-to-pay absent State and Federal
rebates at the time of sale, which are reflected in both the initial
purchase price of the vehicle and its later value in the used vehicle
market. As such, the analysis would continue to be relevant even if
incentive programs for vehicle electrification change or phase out in
the future. By considering a variety of nameplates and body styles
produced by several manufacturers, this analysis produces average
willingness-to-pay estimates that can be applied to the whole industry.
By evaluating matched pairs of vehicles from the same manufacturer, the
analysis accounts for many additional factors that may be tied to the
brand, rather than the technology, and influence the fair market price
of vehicles. In particular, the data inherently include customer
valuations for fuel-savings and vehicle maintenance schedules, as well
as other factors like noise-vibration-and-harshness, interior
space,\257\ and fueling convenience in the context of the vehicles
considered.
---------------------------------------------------------------------------
\257\ Often HEVs and PHEVs place batteries in functional storage
space, such as the trunk or floor storage bins, thereby forcing
consumers to trade-off fuel-savings with other functional vehicle
attributes.
---------------------------------------------------------------------------
There are some limitations to this approach. There are currently
few observations of PHEV and BEV technologies in the data, and most of
the observations for BEVs are sedans and small cars, the values for
which are extrapolated to other market segments. Additionally, the used
vehicle data supporting these estimates inherently includes both older
and newer generations of technology, so the historical regression may
be slow to react to rapid changes in the new vehicle marketplace. As
new vehicle nameplates emerge, and existing nameplates improve their
implementation of electrification technologies, this model will require
re-estimation to determine how these new entrants impact the estimated
industry average willingness-to-pay.
Additionally, the willingness-to-pay analysis does not consider
electric vehicles with no direct ICE counterpart. For example, today's
evaluation does not consider Tesla because the Tesla brand has no ICE
equivalent, and because the free-market prices for used Tesla vehicles
have been difficult (if not impossible) to obtain, primarily due to
factory guaranteed resale values (which is a program that still affects
the used market for many Tesla vehicles). Still, Tesla vehicles have a
large share of the BEV market by both unit sales and dollar sales, it
may be possible to include Tesla data in a future update to this
analysis. Similarly, the analysis did not include ICE vehicles with no
similar HEV, PHEV, or BEV nameplate or counterpart, so the analysis
presented here looks at a small portion of all transactions and is more
likely to include fuel efficient models where market demand for hybrid
(or higher) versions may exist. One possible alternative is to rely on
new vehicle transaction prices to estimate consumer willingness-to-pay
for new vehicles with certain attributes. However, new vehicle
transaction data is highly proprietary and difficult to obtain in a
form that may be disclosed to the public.
While estimating willingness-to-pay for electrification
technologies from depreciation and MSRP data is appealing, many
manufacturers handle MSRP and pricing strategies differently, with some
preferring to deviate only a little from sticker price and others
preferring to offer high discounts. There is evidence of large
differences between MSRP and effective market prices to consumers for
many vehicles, especially BEVs.
Please provide comments on methods and data used to evaluate
consumer willingness-to-pay for electrification technologies.
(e) Refueling Surplus
Direct estimates of the value of extended vehicle range are not
available in the literature, so the reduction in the required annual
number of refueling cycles due to improved fuel economy was calculated
and the economic value of the resulting benefits assessed. Chief among
these benefits is the time that owners save by spending less time both
in search of fueling stations and in the act of pumping and paying for
fuel.
The economic value of refueling time savings was calculated by
applying DOT-recommended valuations for travel time savings to
estimates of how much time is saved.\258\ The value of travel time
depends on average hourly valuations of personal and business time,
which are functions of total hourly compensation costs to employers.
The total hourly compensation cost to employers, inclusive of benefits,
in 2010$ is $29.68.\259\ Table-II-39 below demonstrates the approach to
estimating the value of travel time ($/hour) for both urban and rural
(intercity) driving. This approach relies on the use of DOT-recommended
weights that assign a lesser valuation to personal travel time than to
business travel time, as well as
[[Page 43086]]
weights that adjust for the distribution between personal and business
travel.
---------------------------------------------------------------------------
\258\ See https://www.transportation.gov/sites/dot.gov/files/docs/ValueofTravelTimeMemorandum.pdf (last accessed July 3, 2018).
\259\ Total hourly employer compensation costs for 2010 (average
of quarterly observations across all occupations for all civilians).
See https://www.bls.gov/ncs/ect/tables.htm (last accessed July 3,
2018).
[GRAPHIC] [TIFF OMITTED] TP24AU18.056
The estimates of the hourly value of urban and rural travel time
($15.67 and $21.93, respectively) shown in Table-II-39 above must be
adjusted to account for the nationwide ratio of urban to rural driving.
By applying this adjustment (as shown in Table-II-40 below), an overall
estimate of the hourly value of travel time--independent of urban or
rural status--may be produced.
---------------------------------------------------------------------------
\260\ Time spent on personal travel during rural (intercity)
travel is valued at a greater rate than that of urban travel. There
are several reasons behind the divergence in these values: (1) Time
is scarcer on a long trip; (2) a long trip involves complementary
expenditures on travel, lodging, food, and entertainment because
time at the destination is worth such high costs.
Note: The calculations above assume only one adult occupant per
vehicle. To fully estimate the average value of vehicle travel time,
the presence of additional adult passengers during refueling trips
must be accounted for. The analysis applies such an adjustment as
shown in Table-II-40; this adjustment is performed separately for
passenger cars and for light trucks, yielding occupancy-adjusted
valuations of vehicle travel time during refueling trips for each
---------------------------------------------------------------------------
fleet.
Note: Children (persons under age 16) are excluded from average
vehicle occupancy counts, as it is assumed that the opportunity cost
of children's time is zero.
[[Page 43087]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.057
The analysis estimated the amount of refueling time saved using
(preliminary) survey data gathered as part of our 2010-2011 National
Automotive Sampling System's Tire Pressure Monitoring System (TPMS)
study.\263\ The study was conducted at fueling stations nationwide, and
researchers made observations regarding a variety of characteristics of
thousands of individual fueling station visits from August 2010 through
April 2011.\264\ Among these characteristics of fueling station visits
is the total amount of time spent pumping and paying for fuel. From a
separate sample (also part of the TPMS study), researchers conducted
interviews at the pump to gauge the distances that drivers travel in
transit to and from fueling stations, how long that transit takes, and
how many gallons of fuel are being purchased.
---------------------------------------------------------------------------
\261\ See Travel Monitoring, Traffic Volume Trends, U.S.
Department of Transportation Federal Highway Administration, https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm (last
visited June 22, 2018). Weights used for urban versus rural travel
are computed using cumulative 2011 estimates of urban versus rural
miles driven provided by the Federal Highway Administration.
\262\ Source: National Automotive Sampling System 2010-2011 Tire
Pressure Monitoring System (TPMS) study. See next page for further
background on the TPMS study. TPMS data are preliminary at this
time, and rates are subject to change pending availability of
finalized TPMS data. Average occupancy rates shown here are specific
to refueling trips and do not include children under 16 years of
age.
\263\ TPMS data are preliminary and not yet published. Estimates
derived from TPMS data are therefore preliminary and subject to
change. Observational and interview data are from distinct
subsamples, each consisting of approximately 7,000 vehicles. For
more information on the National Automotive Sampling System and to
access TPMS data when they are made available, see http://www.nhtsa.gov/NASS.
\264\ The data collection period for the TPMS study ranged from
October 10, 2010, through April 15, 2011.
---------------------------------------------------------------------------
This analysis of refueling benefits considers only those refueling
trips which interview respondents indicated the primary reason was due
to a low reading on the gas gauge.\265\ This restriction was imposed so
as to exclude drivers who refuel on a fixed (e.g., weekly) schedule and
may be unlikely to alter refueling patterns as a result of increased
driving range. The relevant TPMS survey data on average refueling trip
characteristics are presented below in Table-II-41.
---------------------------------------------------------------------------
\265\ Approximately 60% of respondents indicated ``gas tank
low'' as the primary reason for the refueling trip in question.
[GRAPHIC] [TIFF OMITTED] TP24AU18.058
As an illustration of how the value of extended refueling range was
estimated, assume a small light truck model has an average fuel tank
size of approximately 20 gallons and a baseline actual on-road fuel
economy of 24 mpg (its assumed level in the absence of a higher CAFE
standard for the given model year). TPMS survey data indicate that
drivers who indicated the primary reason for their refueling trips was
a low reading on the gas gauge typically refuel when their tanks are
35% full (i.e. as shown in Table-II-41, with 7.0 gallons in reserve,
and the consumer purchases 13 gallons). By this measure, a typical
driver would have an effective driving range of 312 miles (= 13.0
gallons x 24
[[Page 43088]]
mpg) before he or she is likely to refuel. Increasing this model's
actual on-road fuel economy from 24 to 25 mpg would therefore extend
its effective driving range to 325 miles (= 13.0 gallons x 25 mpg).
Assuming that the truck is driven 12,000 miles/year,\266\ this one mpg
improvement in actual on-road fuel economy reduces the expected number
of refueling trips per year from 38.5 (= 12,000 miles per year/312
miles per refueling) to 36.9 (= 12,000 miles per year/325 miles per
refueling), or by 1.6 refuelings per year. If a typical fueling cycle
for a light truck requires a total of 6.83 minutes, then the annual
value of time saved due to that one mpg improvement would amount to
$3.97 (= (6.83/60) x $21.81 x 1.6).
---------------------------------------------------------------------------
\266\ 2009 National Household Travel Survey (NHTS), U.S
Department of Transportation Federal Highway Administration at 48
(June 2011), available at http://nhts.ornl.gov/2009/pub/stt.pdf.
12,000 miles/year is an approximation of a light duty vehicle's
annual mileage during its initial decade of use (the period in which
the bulk of benefits are realized). The CAFE model estimates VMT by
model year and vehicle age, taking into account the rebound effect,
secular growth rates in VMT, and fleet survivability; these
complexities are omitted in the above example for simplicity.
---------------------------------------------------------------------------
In the central analysis, this calculation was repeated for each
future calendar year that light-duty vehicles of each model year
affected by the standards considered in this rule would remain in
service. The resulting cumulative lifetime valuations of time savings
account for both the reduction over time in the number of vehicles of a
given model year that remain in service and the reduction in the number
of miles (VMT) driven by those that stay in service. The analysis also
adjusts the value of time savings that will occur in future years both
to account for expected annual growth in real wages \267\ and to apply
a discount rate to determine the net present value of time saved.\268\
A further adjustment is made to account for evidence from the
interview-based portion of the TPMS study which suggests that 40% of
refueling trips are for reasons other than a low reading on the gas
gauge. It is therefore assumed that only 60% of the theoretical
refueling time savings will be realized, as it was assumed that owners
who refuel on a fixed schedule will continue to do. Based on peer
reviewer comments to NHTSA's initial implementation of refueling time
savings (subsequent to the CAFE NPRM issued in 2011), the analysis of
refueling time savings was updated for the final rule to reflect peer
reviewer suggestions.\269\ Beyond updating time values to current
dollars, that analysis has been used, unchanged, in today's analysis as
well.
---------------------------------------------------------------------------
\267\ See The Economics Daily, The compensation-productivity
gap, U.S. Department of Labor Bureau of Labor Statistics (Feb. 24,
2011), http://www.bls.gov/opub/ted/2011/ted_20110224.htm. A 1.1%
annual rate of growth in real wages is used to adjust the value of
travel time per vehicle ($/hour) for future years for which a given
model is expected to remain in service. This rate is supported by a
BLS analysis of growth in real wages from 2000-2009.
\268\ Note: Here, as elsewhere in the analysis, discounting is
applied on an annual basis from CY 2017.
\269\ Peer review materials, peer reviewer backgrounds,
comments, and NHTSA responses for this prior assessment are
available at Docket NHTSA-2012-0001.
---------------------------------------------------------------------------
Because a reduction in the expected number of annual refueling
trips leads to a decrease in miles driven to and from fueling stations,
the value of consumers' fuel savings associated with this decrease can
also be calculated. As shown in Table-II-41, the typical incremental
round-trip mileage per refueling cycle is 1.08 miles for light trucks
and 0.97 miles for passenger cars. Going back to the earlier example of
a light truck model, a decrease of 1.6 in the number of refuelings per
year leads to a reduction of 1.73 miles driven per year (= 1.6
refuelings x 1.08 miles driven per refueling). Again, if this model's
actual on-road fuel economy was 24 mpg, the reduction in miles driven
yields an annual savings of approximately 0.07 gallons of fuel (= 1.73
miles/24 mpg), which at $3.25/gallon \270\ results in a savings of
$0.23 per year to the owner.
Note: This example is illustrative only of the approach used to
quantify this benefit. In practice, the societal value of this
benefit excludes fuel taxes (as they are transfer payments) from the
calculation and is modeled using fuel price forecasts specific to
each year the given fleet will remain in service.
\270\ Estimate of $3.25/gallon is the forecasted cost per gallon
(including taxes, as individual consumers consider reduced tax
expenditures to be savings) for motor gasoline in 2025. Source of
price projections: U.S. Energy Information Administration, Annual
Energy Outlook Early 2018.
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The annual savings to each consumer shown in the above example may
seem like a small amount, but the reader should recognize that the
valuation of the cumulative lifetime benefit of this savings to owners
is determined separately for passenger car and light truck fleets and
then aggregated to show the net benefit across all light-duty vehicles,
which is much more significant at the macro level. Calculations of
benefits realized in future years are adjusted for expected real growth
in the price of gasoline, for the decline in the number of vehicles of
a given model year that remain in service as they age, for the decrease
in the number of miles (VMT) driven by those that stay in service, and
for the percentage of refueling trips that occur for reasons other than
a low reading on the gas gauge; a discount rate is also applied in the
valuation of future benefits. Using this direct estimation approach to
quantify the value of this benefit by model year was considered;
however, it was concluded that the value of this benefit is implicitly
captured in the separate measure of overall valuation of fuel savings.
Therefore, direct estimates of this benefit are not added to net
benefits calculations. It is noted that there are other benefits
resulting from the reduction in miles driven to and from fueling
stations, such as a reduction in greenhouse gas emissions--
CO2 in particular--which, as per the case of fuel savings
discussed in the preceding paragraph, are implicitly accounted for
elsewhere.
Special mention must be made with regard to the value of refueling
time savings benefits to owners of electric and plug-in electric (both
referred to here as EV) vehicles. EV owners who routinely drive daily
distances that do not require recharging on-the-go may eliminate the
need for trips to fueling or charging stations. It is likely that early
adopters of EVs will factor this benefit into their purchasing
decisions and maintain driving patterns that require once-daily at-home
recharging (a process which generally takes five to eleven hours for a
full charge) \271\ for those EV owners who have purchased and installed
a Level Two charging station to a high-voltage outlet at their home or
parking place. However, EV owners who regularly or periodically need to
drive distances further than the fully-charged EV range may need to
recharge at fixed locations. A distributed network of charging stations
(e.g., in parking lots, at parking meters) may allow some EV owners to
recharge their vehicles while at work or while shopping, yet the
lengthy charging cycles of current charging technology may pose a cost
to owners due to the value of time spent waiting for EVs to charge and
potential EV shoppers who do not have access to charging at home (e.g.,
because they live in an apartment without a vehicle charging station,
only
[[Page 43089]]
have street parking, or have garages with insufficient voltage).
Moreover, EV owners who primarily recharge their vehicles at home will
still experience some level of inconvenience due to their vehicle being
either unavailable for unplanned use or to its range being limited
during this time should they interrupt the charging process. Therefore,
at present EVs hold potential in offering significant time savings but
only to owners with driving patterns optimally suited for EV
characteristics. If fast-charging technologies emerge and a widespread
network of fast-charging stations is established, it is expected that a
larger segment of EV vehicle owners will fully realize the potential
refueling time savings benefits that EVs offer. This is an area of
significant uncertainty.
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\271\ See generally All-New Nissan Leaf Range & Charging, Nissan
USA, https://www.nissanusa.com/vehicles/electric-cars/leaf/range-charging.html (last visited June 22, 2018); Home Charging
Calculator, Tesla, https://www.tesla.com/support/home-charging-calculator (last visited June 22, 2018); 2018 Chevrolet Bolt EV, GM,
https://media.gm.com/content/media/us/en/chevrolet/vehicles/bolt-ev/2018/_jcr_content/iconrow/textfile/file.res/2018-Chevrolet-Bolt-EV-Product-Guide.pdf (last visited June 22, 2018).
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6. Vehicle Use and Survival
To properly account for the average value of consumer and societal
costs and benefits associated with vehicle usage under various CAFE and
GHG alternatives, it is necessary to estimate the portion of these
costs and benefits that will occur at each age (or calendar year) for
each model year cohort. Doing so requires some estimate of how many
miles the average vehicle of a given type \272\ is expected to drive at
each age and what share of the initial model year cohort is expected to
remain at each age. The first estimates are referred to as the vehicle
miles travelled (VMT) schedules and the second as the survival rate
schedules. In this section the data sources and general methodologies
used to develop these two essential inputs are briefly discussed. More
complete discussions of the development of both the VMT schedules and
the survival rate schedules are present in the PRIA Chapter 8.
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\272\ Type here refers to the following body styles: Pickups,
vans/SUVs, and other cars.
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(a) Updates to Vehicle Miles Traveled Schedules Since 2012 FR
The MY 2017-2021 FRM built estimates of average lifetime mileage
accumulation by body style and age using the 2009 National Household
Travel Survey (NHTS), which surveys odometer readings of the vehicles
present from the approximately 113,000 households sampled.
Approximately 210,000 vehicles were in the sample of self-reported
odometer readings collected between April 2008 and April 2009. This
represents a sample size of less than one percent of the more than 250
million light-duty vehicles registered in 2008 and 2009. The NHTS
sample is now 10 years old and taken during the Great Recession. The
2017 NHTS was not available at the time of this rulemaking. Because of
the age of the last available NHTS and the unusual economic conditions
under which it was collected, NHTSA built the new schedule using a
similar method from a proprietary dataset collected in the fall of
2015. This new data source has the advantages of both being newer, a
larger sample, and collected by a third party.
(1) Data Sources and Estimation (Polk Odometer Data)
To develop new mileage accumulation schedules for vehicles
regulated under the CAFE program (classes 1-3), NHTSA purchased a data
set of vehicle odometer readings from IHS/Polk (Polk). Polk collects
odometer readings from registered vehicles when they encounter
maintenance facilities, state inspection programs, or interactions with
dealerships and OEMs--these readings are more likely to be precise than
the self-reported odometer readings collected in the NHTS. The average
odometer readings in the data set NHTSA purchased are based on more
than 74 million unique odometer readings across 16 model years (2000-
2015) and vehicle classes present in the data purchase (all registered
vehicles less than 14,000 lbs. GVW). This sample represents
approximately 28% of the light-duty vehicles registered in 2015, and
thus has the benefit of not only being a newer, but also, a larger,
sample.
Comparably to the NHTS, the Polk data provide a measure of the
cumulative lifetime vehicle miles traveled (VMT) for vehicles, at the
time of measurement, aggregated by the following parameters: Make,
model, model year, fuel type, drive type, door count, and ownership
type (commercial or personal). Within each of these subcategories they
provide the average odometer reading, the number of odometer readings
in the sample from which Polk calculated the averages, and the total
number of that subcategory of vehicles in operation.
In estimating the VMT models, each data point was weighted (make/
model classification) by the share of each make/model in the total
population of the corresponding vehicle body style. This weighting
ensures that the predicted odometer readings, by body style and model
year, represent each vehicle classification among observed vehicles
(i.e., the vehicles for which Polk has odometer readings), based on
each vehicles' representation in the registered vehicle population of
its body style. Implicit in this weighting scheme is the assumption
that the samples used to calculate each average odometer reading by
make, model, and model year are representative of the total population
of vehicles of that type. Several indicators suggest that this is a
reasonable assumption.
First, the majority of vehicle make/models is well-represented in
the sample. For more than 85% of make/model combinations, the average
odometer readings are collected for 20% or more of the total
population. Most make/model observations have sufficient sample sizes,
relative to their representation in the vehicle population, to produce
meaningful average odometer totals at that level. Second, we considered
whether the representativeness of the odometer sample varies by vehicle
age because VMT schedules in the CAFE model are specific to each age.
It is possible that, for some of those models, an insufficient number
of odometer readings is recorded to create an average that is likely to
be representative of all of those models in operation for a given year.
For all model years other than 2015, approximately 95% or more of
vehicles types are represented by at least five percent of their
population. For this reason, observations from all model years, other
than 2015, were included in the estimation of the new VMT schedules.
Because model years are sold in in the Fall of the previous
calendar year, throughout the same calendar year, and even into the
following calendar year--not all registered vehicles of a make/model/
model year will have been registered for at least a year (or more)
until age three. The result is that some MY 2014 vehicles may have been
driven for longer than one year, and some less, at the time the
odometer was observed. In order to consider this in the definition of
age, an age of a vehicle is assigned to be the difference between the
average reading date of a make/model and the average first registration
date of that make/model. The result is that the continuous age variable
reflects the amount of time that a car has been registered at the time
of odometer reading and presumably the time span that the car has
accumulated the miles.
After creating the ``age'' variable, the analysis fits the make/
model lifetime VMT data points to a weighted quartic polynomial
regression of the age of the vehicle (stratified by vehicle body
styles). The predicted values of the quartic regressions are used to
calculate the marginal annual VMT by age for each body style by
calculating differences in estimated lifetime mileage accumulation by
age. However, the Polk data acquired by NHTSA only contains
[[Page 43090]]
observations for vehicles newer than 16 years of age. In order to
estimate the schedule for vehicles older than the age 15 vehicles in
the Polk data, information about that portion of the schedule from the
VMT schedules used in both the 2017-2021 Final Light Duty Rule and
2019-2025 Medium-Duty NPRM was combined. The light-duty schedules were
derived from the survey data contained in the 2009 National Household
Travel Survey (NHTS).
From the old schedules, the annual VMT is expected to be decreasing
for all ages. Towards the end of the sample, the predictions for annual
VMT increase. In order to force the expected monotonicity, a triangular
smoothing algorithm is performed until the schedule is monotonic. This
performs a weighted average which weights the observations close to the
observation more than those farther from it. The result is a monotonic
function, that predicts similar lifetime VMT for the sample span as the
original function. Because the analysis does not have data beyond 15
years of age, it is not able to correctly capture that part of the
annual VMT curve using only the new dataset. For this reason, trends in
the old data to extrapolate the new schedule for ages beyond the sample
range are used.
To use the VMT information from the newer data source for ages
outside of the sample, final in-sample age (15 years) are used as a
seed and then applied to the proportional trend from the old schedules
to extrapolate the new schedules out to age 40. To do this, the annual
percentage difference in VMT of the old schedule for ages 15-40 is
calculated. The same annual percentage difference in VMT is applied to
the new schedule to extend beyond the final in-sample value. This
assumes that the overall proportional trend in the outer years is
correctly modeled in the old VMT schedule and imposes this same trend
for the outer years of the new schedule. The extrapolated schedules are
the final input for the VMT schedules in the CAFE model. PRIA Chapter 8
contains a lengthier discussion of both the data source and the
methodology used to create the new schedules.
(2) Using New Schedules in the CAFE Model/Analysis
While the Polk registration data set contains odometer readings for
individual vehicles, the CAFE model tabulates ``mileage accumulation''
schedules, which relate average annual miles driven to vehicle age,
based on vehicles' body style. For the purposes of VMT accounting, the
CAFE model classifies vehicles in the analysis fleet as being one of
the following: Passenger car, SUV, pickup truck, passenger van, or
medium-duty pickup/van.\273\ In order to use the Polk data to develop
VMT schedules for each of these vehicle classes in the CAFE model, a
mapping between the classification of each model in the Polk data and
the classes in the CAFE model was first constructed. This mapping
enabled separate tabulations of average annual miles driven at each age
for each of the vehicle classes included in the CAFE model.
---------------------------------------------------------------------------
\273\ Though not included in today's analysis, corresponding
schedules for heavy-duty pickups and vans were developed using the
same methodology.
---------------------------------------------------------------------------
The only revision made to the mappings used to construct the new
VMT schedules was to merge the SUV and passenger van body styles into a
single class. These body styles were merged because there were very few
examples of vans--only 38 models were in use during 2014, where every
other body style had at least three times as many models. Further, as
shown in the PRIA Chapter 8, there was not a significant difference
between the 2009 NHTS van and SUV mileage schedules, nor was there a
significant difference between the schedules built with the two body
styles merged or kept separate using the 2015 Polk data. Merging these
body styles does not change the workings of the CAFE model in any way,
and the merged schedule is simply entered as an input for both vans and
SUVs.
Although there is a single VMT by age schedule used as an input for
each body style, the assumptions about the rebound effect require that
this schedule be scaled for future analysis years to reflect changes in
the cost of travel from the time the Polk sample was originally
collected. These changes result from both changes in fuel prices
between the time the sample was collected and any future analysis year
and differences in fuel economy between the vehicles included in the
sample used to build the mileage schedules and the future-year vehicles
analyzed within the CAFE Model simulation.
As discussed in Section 0, recent literature supports a 20%
``rebound effect'' for light-duty vehicle use, which represents an
elasticity of annual use with respect to fuel cost per mile of -0.2.
Because fuel cost per mile is calculated as fuel price per gallon
divided by fuel economy (in miles per gallon), this same elasticity
applies to changes in fuel cost per mile that result from variation in
fuel prices or differences in fuel economy. It suggests that a five
percent reduction in the cost per mile of travel for vehicles of a
certain body style will result in a one percent increase in the average
number of miles they are driven annually.
The average cost per mile (CPM) of a vehicle of a given age and
vehicle style in CY 2016 (the first analysis year of the simulation)
was used as the reference point to calculate the rebound effect within
the CAFE model. However, this does not perfectly align with the time of
the collection of the Polk dataset. The Polk data were collected in
2015 (so that 2014 fuel prices were the last to influence sampled
vehicles' odometer readings), and represents the average odometer
reading at a single point in time for age (model year) included in the
cross-section. We use the difference in the average odometer reading
for each vintage during 2014 to calculate the number of miles vehicles
are driven at each age (see PRIA Chapter 8 for specific details on the
analysis). For example, we interpret the difference in the average
odometer reading between the five- and six-year-old vehicles of a given
body style as the average number of miles they are driven during the
year when they were five years old. However, vehicles produced during
different model years do not have the same average fuel economy, so it
is important to consider the average fuel economy of each vintage (or
model year) used to measure mileage accumulation at a given age when
scaling VMT for the rebound calculation.
The first step in doing so is to adjust for any change in average
annual use that would have been caused by differences in fuel prices
between CYs 2014 and 2016. This is done by scaling the original
schedules of annual VMT by age tabulated from the Polk sample using the
following equation:
[[Page 43091]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.059
Here, the average fuel economy for vehicles of a given body style
and age refers to a different MY in 2016 than it did in 2014; for
example, a MY 2014 vehicle had reached age two vehicle during CY 2016,
whereas a 2012 model year vehicle was age two during CY 2014.
To estimate the average annual use of vehicles of a specified body
type and age during future calendar years under a specific regulatory
alternative, the CAFE model adjusts the resulting estimates of vehicle
use by age for that body type during CY 2016 to reflect (1) the
projected change in fuel prices from 2016 to each future calendar year;
and (2) the difference between the average fuel economy for vehicles of
that body type and age during a future calendar year and the average
fuel economy for vehicles of that same body type and age during 2016.
These two factors combine to determine the average fuel cost per mile
for vehicles of that body type and age during each future calendar year
and the average fuel cost per mile for vehicles of that same body type
and age during 2016.
The elasticity of annual vehicle use with respect to fuel cost per
mile is applied to the difference between these two values because
vehicle use is assumed to respond identically to differences in fuel
cost per mile that result from changes in fuel prices or from
differences in fuel economy. The model then repeats this calculation
for each calendar year during the lifetimes of vehicles of other body
types, and subsequently repeats this entire set of calculations for
each regulatory alternative under consideration. The resulting
differences in average annual use of vehicles of each body type at each
age interact with the number estimated to remain in use at that age to
determine total annual VMT by vehicles of each body type.
This adjustment is defined by the equation below:
[GRAPHIC] [TIFF OMITTED] TP24AU18.060
This equation uses the observed cost per mile of a vehicle of each
age and style in CY 2016 as the reference point for all future calendar
years. That is, the reference fuel price is fixed at 2016 levels, and
the reference fuel economy of vehicles of each age is fixed to the
average fuel economy of the vintage that had reached that age in 2016.
For example, the reference CPM for a one-year-old SUV is always the CPM
of the average MY 2015 SUV in CY 2016, and the CPM for a two-year-old
SUV is always the CPM of the average MYv2014 SUV in CY 2016.
This referencing ensures that the model's estimates of annual
mileage accumulation for future calendar years reflect differences in
the CPM of vehicles of each given type and age relative to CPM
resulting from the average fuel economy of vehicles of that type and
age and observed fuel prices during the year when the mileage
accumulation schedules were originally measured. This is consistent
with a definition of the rebound effect as the elasticity of annual
vehicle use with respect to changes in the fuel cost per mile of
travel, regardless of the source of changes in fuel cost per mile.
Alternative forms of referencing are possible, but none can guarantee
that projected future vehicle use will respond to both projected
changes in fuel prices and differences in individual models' fuel
economy among regulatory alternatives.
The mileage estimates described above are a crucial input in the
CAFE model's calculation of fuel consumption and savings, energy
security benefits, consumer surplus from cheaper travel, recovered
refueling time, tailpipe emissions, and changes in crashes, fatalities,
noise and congestion.
(3) Comparison to other VMT projections (2012 FR, AEO average lifetime
miles, totals?)
Across all body styles and ages, the previous VMT schedules
estimate higher average annual VMT than the updated schedules. Table-
II--42 compares the lifetime VMT under the 2009 NHTS and the 2015 Polk
dataset. The 40-year lifetime VMT gives the
[[Page 43092]]
expected lifetime VMT of a vehicle conditional on surviving to age 40.
The new schedules predict between 24 and 31% fewer miles for a 40-year
old vehicle depending on the body style. The new schedules predict that
the average 40-year old vehicle will drive between approximately 260k
and 280k miles depending on the body style versus between approximately
350k and 380k for the previous schedules.
The static survival-weighted lifetime VMT represents the expected
number of miles the average vehicle of each body style will drive,
weighting by the likelihood it survives to each age using the previous
static scrappage schedules. The dynamic survival-weighted lifetime VMT
represents the expected number of miles driven by each body style,
weighting by the dynamic survival schedules under baseline
assumptions.\274\ There is a similar proportional reduction in expected
lifetime VMT under both survival assumptions, with the dynamic
scrappage model predicting lifetime mileage accumulation within 10,000
miles of the previous static model under both VMT schedules. The
expected lifetime mileage accumulation reduces between 13 and 15% under
the current VMT schedules when compared to the previous schedules--a
smaller proportional reduction than the unweighted lifetime
assumptions. Using the updated schedules, the expected lifetime mileage
accumulation is between approximately 150k and 170k miles depending on
the body style, rather than the approximately 180k to 210k miles under
the previous schedules. For more detail on when the mileage and
survival rates occur, chapter 8 of the PRIA gives the full VMT
schedules by age. The section below gives further estimates of how
lifetime VMT estimates vary under different assumptions within the
dynamic scrappage model.
[GRAPHIC] [TIFF OMITTED] TP24AU18.061
We have several reasons for preferring the new VMT schedules over
the prior iterations. Before discussing these reasons, it is important
to note that NHTSA uses the same general methodology in developing both
schedules. We consider data on average odometer readings by age and
body style collected once during a given window of time; we then
estimate a weighted polynomial function between vehicle age and
lifetime accumulation for a given vehicle style. As with the previous
schedules, we use the inter-annual differences as the estimate of
annual miles traveled for a given age.
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\274\ In estimating the dynamic survival rate to weight the
annual VMT schedules, we make the following input assumptions: The
reference vehicle is MY 2016, GDP growth rates and fuel prices are
our central estimates, and the future average new vehicle fuel
economies by body style and overall average new vehicle prices are
those simulated by the CAFE model when CAFE standards are omitted
(by setting standards at 1 mpg), such that only technologies that
pay back within 30 months are applied.
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The primary advantage of the current schedules is the data source.
The previous schedules are based on data that is outdated and self-
reported, while the observations from Polk are between five and seven
years newer than those in the NHTS and represent valid odometer
readings (rather than self-reported information). Further, the 2009
NHTS represents approximately one percent of the sample of vehicles
registered in 2008/2009, while the 2015 Polk dataset represents
approximately 30% of all registered light-duty vehicles; it is a much
larger dataset, and less likely to oversample certain vehicles.
Additionally, while the NHTS may be a representative sample of
households, it is less likely to be a representative sample of
vehicles. However, by properly accounting for vehicle population
weights in the new averages and models, we corrected for this issue in
the derivation of the new schedules.
Importantly, this methodology treats the cross-section of ages in a
single calendar year as a panel of the same model year vehicle, when in
reality each age represents a single model year, and not a true panel.
We have some concern that where the most heavily driven vehicles drop
out of the sample that the lifetime odometer readings will be lower
than they would be if the scrapped vehicles had been left in the
dataset without additional mileage accumulation. This would bias our
estimates of inter-annual mileage accumulation downward and may result
in an undervaluation of costs and benefits associated with additional
travel for vehicles of older ages. For the next VMT schedule iteration,
NHTSA intends to use panel data to test the magnitude of any attrition
effect that may exist. While this caveat is important, all previous
iterations were also built from a single calendar year cross-section
and contain the same inherent bias.
(b) How does CAFE affect vehicle retirement rates?
Lightly used vehicles are a close substitute for new vehicles;
thus, there is relationship between the two markets. As the price for
new vehicles increases, there is an upward shift in the demand for used
vehicles. As a result of the upward shift in the demand curve, the
equilibrium price and quantity of used vehicles both increase; the
value of used vehicles increases as a result. The decision to scrap or
maintain a used vehicle is closely linked with the value of the
vehicle; when the value is lesser than the cost to maintain the
vehicle, it will be scrapped. In general, as a result of new vehicle
price increases, the scrappage rate, or the proportion of vehicles
remaining on the road unregistered in a given year, of used vehicles
will decline. Because older vehicles are on average less efficient and
less safe, this will have important implications for the evaluations of
costs
[[Page 43093]]
and benefits of fuel economy standards, which increase the cost of new
vehicles and reduce the average cost per mile of fuel costs.
Fuel economy standards result in the application of more fuel
saving technologies for at least some models, which result in a higher
cost for manufacturers to produce otherwise identical vehicles. This
increase in production cost amounts to an upward shift in the supply
curve for new vehicles. This increases the equilibrium price and
reduces the quantity of vehicles demanded. While the cost of new
vehicles increases under increased fuel economy standards, the fuel
cost per mile of travel declines. Consumers will place some value on
the fuel savings associated with the additional technology, to the
extent that they value reduced operating expenses against the increased
price of a new vehicle, increased financing costs (and impediments to
obtaining financing), and increased insurance costs.
There is a trade-off between fuel economy and other attributes that
consumers value such as: Vehicle performance, interior volume, etc.
Where the additional value of fuel savings associated with a technology
is greater than any loss of value from trade-offs with other
attributes, the demand for new vehicles will also shift upwards. Where
the additional evaluation of fuel savings is lesser than any loss of
value from changes to other attributes, the demand will shift
downwards. Thus, the direction of the demand shift is unknown. However,
if we assume that manufacturers pass all costs associated with a model
off to the consumer of that vehicle, then the per vehicle profit
remains constant. If we also assume that manufacturers are good
predictors of the valuation and elasticity of certain vehicle
attributes, then we can assume that even if there is some positive
demand shift, it is not enough to increase demand above the original
equilibrium levels, or manufacturers would apply those technologies
even in the absence of regulation.
As noted above, the increase in the price of new vehicles will
result in increased demand for used vehicles as substitutes, extending
the expected age and lifetime vehicle miles travelled of less
efficient, and generally, less safe vehicles. The additional usage of
older vehicles will result in fewer gallons saved and more total on-
road fatalities under more stringent CAFE alternatives. For more on the
topic of safety, the relative safety of specific model year vehicles is
discussed in Section 0 of the preamble and PRIA Chapter 11. Both the
erosion of fuel savings and the increase in incremental fatalities will
decrease the societal net benefits of increasing new vehicle fuel
economy standards.
Our previous estimates of vehicle scrappage did not include a
dynamic response to new vehicle price, but recent literature has
continued to illustrate that this an omission which could rival the
rebound effect in magnitude (Jacobsen & van Bentham, 2015). For this
reason, we worked to develop an econometric survival model which
captures the effect of increasing the price of new vehicles on the
survival rate of used vehicles discussed in the following sections and
in more detail in the PRIA Chapter 8. We discuss the literature on
vehicle scrappage rate and discuss in the succeeding section. A brief
explanation of why we develop our own models and the data sources and
econometric estimations we use to do so, follows. We conclude the
discussion of the updates to vehicle survival estimates with a summary
of the results, a description of how we use them in the CAFE model, and
finally, how the updated schedules compare with the previous static
scrappage schedules.
(1) What does the literature say about the relationship?
(a) How Fuel Economy Standards Impact Vehicle Scrappage
The effects of differentiated regulation \275\ in the context of
fuel economy (particularly, emission standards only affecting new
vehicles) was discussed in detail in Gruenspecht (1981) and (1982), and
has since been coined the ``Gruenspecht effect.'' Gruenspecht
recognized that because fuel economy standards affect only new
vehicles, any increase in price (net of the portion of reduced fuel
savings valued by consumers) will increase the expected life of used
vehicles and reduce the number of new vehicles entering the fleet. In
this way, increased fuel economy standards slow the turnover of the
fleet and the entrance of any regulated attributes tied only to new
vehicles. Although Gruenspecht acknowledges that a structural model
which allows new vehicle prices to affect used vehicle scrappage only
through their effect on used vehicle prices would be preferable, the
data available on used vehicle prices was (and still is) limited.
Instead he tested his hypothesis in his 1981 dissertation using new
vehicle price and other determinants of used car prices as a reduced
form to approximate used car scrappage in response to increasing fuel
economy standards.
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\275\ Differentiated regulations are regulations affecting
segments of the market differently; here, it references the fact
that emission and fuel economy standards have largely only applied
to new and not used vehicles.
---------------------------------------------------------------------------
Greenspan & Cohen (1996) offer additional foundations from which to
think about vehicle stock and scrappage. Their work identifies two
types of scrappage: Engineering scrappage and cyclical scrappage.
Engineering scrappage represents the physical wear on vehicles, which
results in their being scrapped. Cyclical scrappage represents the
effects of macroeconomic conditions on the relative value of new and
used vehicles; under economic growth the demand for new vehicles
increases and the value of used vehicles declines, resulting in
increased scrappage. In addition to allowing new vehicle prices to
affect cyclical vehicle scrappage [agrave] la the Gruenspecht effect,
Greenspan and Cohen also note that engineering scrappage seems to
increase where EPA emission standards also increase; as more costs goes
towards compliance technologies, it becomes more expensive to maintain
and repair more complicated parts, and scrappage increases. In this
way, Greenspan and Cohen identify two ways that fuel economy standards
could affect vehicle scrappage: (1) Through increasing new vehicle
prices, thereby increasing used vehicle prices, and finally, reducing
on-road vehicle scrappage, and (2) by shifting resources towards fuel-
saving technologies--potentially reducing the durability of new
vehicles by making them more complex.
(b) Aggregate vs. Atomic Data Source in the Literature
One important distinction between the literatures on vehicles
scrappage is between those that use atomic vehicle data, data following
specific individual vehicles, and those that use some level of
aggregated data, data that counts the total number of vehicles of a
given type. The decision to scrap a vehicle is an atomic one--that is,
made on an individual vehicle basis. The decision relates to the cost
of maintaining a vehicle, and the value of the vehicle both on the used
car market, and as scrap metal. Generally, a used car owner will decide
to scrap a vehicle where the value of the vehicle is less than the
value of the vehicle as scrap metal plus the cost to maintain or repair
the vehicle. In other words, the owner gets more value from scrapping
the vehicle than continuing to drive it or from selling it.
Recent work is able to model scrappage as an atomic decision due to
the availability of a large database of used vehicle transactions.
Following works by other authors including:
[[Page 43094]]
Busse, Knittel, & Zettelmeyer (2013); Sallee, West, & Fan (2010);
Alcott & Wozny (2013); and Li, Timmins, & von Haefen (2009)--Jacobsen &
van Benthem (2015) considers the impact of changes in gasoline prices
on used vehicle values and scrappage rates. In turn, they consider the
impact of an increase in used vehicle values on the scrappage rate of
those vehicles. They find that increases in gasoline price result in a
reduction in the scrappage rate of the most fuel efficient vehicles and
an increase in the scrappage rate of the least fuel efficient vehicles.
This has important implications for the validity of the average fuel
economy values linked to model years and assumed to be constant over
the life of that model year fleet within this study. Future iterations
of this study could further investigate the relationship between fuel
economy, vehicle usage, and scrappage, as noted in other places in this
discussion.
While the decision to scrap a vehicle is made atomically, the data
available to NHTSA on scrappage rates and variables that influence
these scrappage rates are aggregate measures. This influences the best
available methods to measure the impacts of new vehicle prices on
existing vehicle scrappage. The result is that this study models
aggregate trends in vehicle scrappage and not the atomic decisions that
make up these trends. Many other works within the literature use the
same data source and general scrappage construct, such as: Walker
(1968); Park (1977), Greene & Chen (1981); Gruenspecht (1981);
Gruenspecht (1982); Feeney & Cardebring (1988); Greenspan & Cohen
(1996); Jacobsen & van Bentham (2015); and Bento, Roth, & Zhuo (2016)
all use the same aggregate vehicle registration data as the source to
compute vehicle scrappage.
Walker (1968) and Bento, Roth, & Zhuo (2016) use aggregate data to
directly compute the elasticity of scrappage from measures of used
vehicle prices. Walker (1968) uses the ratio of used vehicle Consumer
Price Index (CPI) to repair and maintenance CPI. Bento, Roth, & Zhuo
(2016) use used vehicle prices directly. While the direct measurement
of the elasticity of scrappage is preferable in a theoretical sense,
the CAFE model does not predict future values of used vehicles, only
future prices of new vehicles. For this reason, any model compatible
with the current CAFE model must estimate a reduced form similar to
Park (1977); Gruenspecht (1981); Greenspan & Cohen (1996), who use some
form of new vehicle prices or the ratio of new vehicle prices to
maintenance and repair prices to impute some measure of the effect of
new vehicle prices on vehicle scrappage.
(c) Historical Trends in Vehicle Durability
Waker (1968); Park (1977); Feeney & Cardebring (1988); Hamilton &
Macauley (1999); and Bento, Ruth, & Zhuo (2016) all note that vehicles
change in durability over time. Walker (1968) simply notes a
significant distinction in expected vehicle lifetimes pre- and post-
World War I. Park (1977) discusses a `durability factor' set by the
producer for each year so that different vintages and makes will have
varying expected lifecycles. Feeney & Cardebring (1988) show that
durability of vehicles appears to have generally increased over time
both in the U.S. and Swedish fleets using registration data from each
country. They also note that the changes in median lifetime between the
Swedish and U.S. fleet track well, with a 1.5 year lag in the U.S.
fleet. This lag is likely due to variation in how the data is
collected--the Swedish vehicle registry requires a title to unregister
a vehicle, and therefore gets immediate responses, where the U.S.
vehicle registry requires re-registration, which creates a lag in
reporting.
Hamilton & Macauley (1999) argue for a clear distinction between
embodied versus disembodied impacts on vehicle longevity. They define
embodied impacts as inherent durability similar to Park's producer
supplied `durability factor' and Greenspan's `engineering scrappage'
and disembodied effects those which are environmental, not unlike
Greenspan and Cohen's `cyclical scrappage.' They use calendar year and
vintage dummy variables to isolate the effects--concluding that the
environmental factors are greater than any pre-defined `durability
factor.' Some of their results could be due to some inflexibility of
assuming model year coefficients are constant over the life of a
vehicle, and there may be some correlation between the observed life of
the later model years of their sample and the `stagflation' \276\ of
the 1970's. Bento, Ruth, & Zhuo (2016) find that the average vehicle
lifetime has increased 27% from 1969 to 2014 by sub-setting their data
into three model year cohorts. To implement these findings in the
scrappage model incorporated into the CAFE model, this study takes
pains to estimate the effect of durability changes in such a way that
the historical durability trend can be projected into the future; for
this reason, a continuous `durability' factor as a function of model
year vintage is included.
---------------------------------------------------------------------------
\276\ Continued high inflation combined with high unemployment
and slow economic growth.
---------------------------------------------------------------------------
(d) Models of the Gruenspecht Effect Used in Other Policy Analyses
This is not the first estimation of the `Gruenspecht Effect' for
policy considerations. In their Technical Support Document (TSD) for
the 2004 proposal to reduce greenhouse gas emissions from motor
vehicles, California Air Resources Board (CARB) outlines how they
utilized the CARBITS vehicle transaction choice model in an attempt to
capture the effect of increasing new vehicle prices on vehicle
replacement rates. They consider data from the National Personal
Transportation Survey (NPTS) as a source of revealed preferences and a
University of California (UC) study as a source of stated preferences
for the purchase and sale of household fleets under different prices
and attributes (including fuel economy) of new vehicles.
The transaction choice model represents the addition and deletion
of a vehicle from a household fleet within a short period of time as a
``replacement'' of a vehicle, rather than as two separate actions.
Their final data set consists of 790 vehicle replacements, 292
additions, and 213 deletions; they do not include the deletions, but
assume any vehicle over 19 years old that is sold is scrapped. This
allows them to capture a slowing of vehicle replacement under higher
new vehicle prices, but because their model does not include deletions,
does not explicitly model vehicle scrappage, but assumes all vehicles
aged 20 and older are scrapped rather than resold. They calibrate the
model so that the overall fleet size is benchmarked to Emissions
FACtors (EMFAC) fleet predictions for the starting year; the simulation
then produces estimates that match the EMFAC predictions without
further calibration.
The CARB study captures the effect on new vehicle prices on the
fleet replacement rates and offers some precedence for including some
estimate of the Gruenspecht Effect. One important thing to note is that
because vehicles that exited the fleet without replacement were
excluded, the effect of new vehicle prices on scrappage rates where the
scrapped vehicle is not replaced is not captured. Because new and used
vehicles are substitutes, it is expected that used vehicle prices will
increase with new vehicle prices. Because higher used vehicle prices
will lower the number of vehicles whose cost of maintenance is higher
than their value, it is expected that not only will
[[Page 43095]]
replacements of used vehicles slow, but also, that some vehicles that
would have been scrapped without replacement under lower new vehicle
prices will now remain on the road because their value will have
increased. Aggregate measures of the Gruenspecht effect will include
changes to scrappage rates both from slower replacement rates, and
slower non-replacement scrappage rates.
(2) Description of Data Sources
NHTSA purchases proprietary data on the registered vehicle
population from IHS/Polk for safety analyses. IHS/Polk has annual
snapshots of registered vehicle counts beginning in calendar year (CY)
1975 and continuing until calendar year 2015. The data includes the
following regulatory classes as defined by NHTSA: Passenger cars, light
trucks (classes 1 and 2a), and medium and heavy-duty trucks (classes 2b
and 3). Polk separates these vehicles into another classification
scheme: Cars and trucks. Under their schema, pickups, vans, and SUVs
are treated as trucks, and all other body styles are included as cars.
In order to build scrappage models to support the model year (MY) 2021-
2026 light duty vehicle (LDV) standards, it was important to separate
these vehicle types in a way compatible with the existing CAFE model.
There were two compatible choices to aggregate scrappage rates: (1)
By regulatory class or (2) by body style. Because for NHTSA's purposes
vans/SUVs are sometimes classified as passenger cars and sometimes as
light trucks, and there was no quick way to reclassify some SUVs as
passenger cars within the Polk dataset, NHTSA chose to aggregate
survival schedules by body style. This approach is also preferable
because NHTSA uses body style specific lifetime VMT schedules. Vehicles
experience increased wear with use; many maintenance and repair events
are closely tied to the number of miles on a vehicle. The current
version of the CAFE model considers separate lifetime VMT schedules for
cars, vans/SUVs, pickups and classes 2b and 3 vehicles. These vehicles
are assumed to serve different purposes and, as a result, are modelled
to have different average lifetime VMT patterns. These different uses
likely also result in different lifetime scrappage patterns.
Once stratified into body style level buckets, the data can be
aggregated into population counts by vintage and age. These counts
represent the population of vehicles of a given body style and vintage
in a given calendar year. The difference between the counts of a given
vintage and vehicle type from one calendar year to the next is assumed
to represent the number of vehicles of that vintage and type scrapped
in a given year. There were a couple other important data
considerations for the calculations of the historical scrappage rates
not discussed here but discussed in detail in the PRIA Chapter 8.\277\
---------------------------------------------------------------------------
\277\ The first is any discontinuity caused by a change in how
Polk collected their data beginning in calendar year 2010, and the
second is the use of the adjustment described in Greenspan & Cohen
(1996).
---------------------------------------------------------------------------
For historical data on vehicle transaction prices, the models use
data from the National Automobile Dealers Association (NADA), which
records the average transaction price of all light-duty vehicles. These
transaction prices represent the prices consumers paid for new vehicles
but do not include any value of vehicles that may have been traded in
to dealers. Importantly, these transaction prices were not available by
vehicle body styles; thus, the models will miss any unique trends that
may have occurred for a particular vehicle body style. This may be
particularly relevant for pickup trucks, which observed considerable
average price increases as luxury and high option pickups entered the
market. Future models will further consider incorporating price series
that consider the price trends for cars, SUVs and vans, and pickups
separately.\278\
---------------------------------------------------------------------------
\278\ Note: Using historical data aggregated by body styles to
capture differences in price trends by body style does not require
the assertion technology costs are or are not borne by the body
style to which they are applied. If the body-style level average
price change is used, then the assumption is manufacturers do not
cross-subsidize across body styles, whereas if the average price
change is used then the assumption is they would proportion costs
equally for each vehicle. These are implementation questions to be
worked out once NHTSA has a historical data source separating price
series by body styles, but these do not matter in the current model
which only considers the average price of all light-duty vehicles.
---------------------------------------------------------------------------
The models use the NADA price series rather than the Bureau of
Labor Statistics (BLS) New Vehicle Consumer Price Index (CPI), used by
Park (1977) and Greenspan & Cohen (1997), because the BLS New Vehicle
CPI makes quality adjustments to the new vehicle prices. BLS assumes
that additions of safety and fuel economy equipment are a quality
adjustment to a vehicle model, which changes the good and should not be
represented as an increase in its price. While this is good for some
purposes, it presumes consumers fully value technologies that improve
fuel economy. Because it is the purpose to this study to measure
whether this is true, it is important that vehicle prices adjusted to
fully value fuel economy improving technologies, which would obscure
the ability to measure the preference for more fuel efficient and
expensive new vehicles, are not used. As further justification for
using the NADA price series over the BLS New Vehicle CPI, Park (1977)
cites a discontinuity found in the amount of quality adjustments made
to the series so that more adjustments are made over time. This could
further limit the ability for the BLS New Vehicle CPI to predict
changes in vehicle scrappage.
Vehicle scrappage rates are also influenced by fuel economy and
fuel prices. Historical data on the fuel economy by vehicle style from
model years 1979-2016 was obtained from the 2016 EPA Motor Trends
Report.\279\ The van/SUV fuel economy values represent a sales-weighted
harmonic average of the individual body styles. Fuel prices were
obtained from Department of Energy (DOE) historical values, and future
fuel prices within the CAFE model use the Annual Energy Outlook (AEO)
future oil price projections.\280\ From these values the average cost
per 100 miles of travel for the cohort of new vehicles in a given
calendar year and the average cost per 100 miles of travel for each
used model year cohort in that same calendar year are computed.\281\ It
is expected that as the new vehicle fleet becomes more efficient
(holding all other attributes constant) that it will be more desirable,
and the demand for used vehicles should decrease (increasing their
scrappage). As a given model year cohort becomes more expensive to
operate due to increases in fuel prices, it is expected the scrappage
of that model year will increase. It is perhaps worth noting that more
efficient model year vintages will be less susceptible to changes in
fuel prices, as
[[Page 43096]]
absolute changes in their cost per mile will be smaller. The functional
forms of the cost per mile measures are further discussed in the model
specification subsection 3 below.
---------------------------------------------------------------------------
\279\ Light-Duty Automotive Technology, Carbon Dioxide
Emissions, and Fuel Economy Trends: 1975 Through 2016, U.S. EPA
(Nov. 2016), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100PKK8.pdf.
\280\ Note: The central analysis uses the AEO reference fuel
price case, but sensitivity analysis also considers the possibility
of AEO's low and high fuel price cases.
\281\ Work by Jacobsen and van Bentham suggests that these
initial average fuel economy values may not represent the average
fuel economy of a model year cohort as it ages--mainly, they find
that the most fuel efficient vehicles scrap earlier than the least
fuel efficient models in a given cohort. This may be an important
consideration in future endeavors that work to link fuel economy,
vehicle miles travelled (VMT), and scrappage. Studies on ``the
rebound effect'' suggest that lowering the fuel cost per driven mile
increases the demand for VMT. With more miles, a vehicle will be
worth less as its perceived remaining useful life will be shorter;
this will result in the vehicle being more likely to be scrapped. A
rebound effect is included in the CAFE model, but because reliable
data on how average VMT by age has varied over calendar year and
model year vintage is not available, expected lifetime VMT is not
included within the current dynamic scrappage model.
---------------------------------------------------------------------------
Aggregate measures that cyclically affect the value of used
vehicles include macroeconomic factors like the real interest rate, the
GDP growth rate, unemployment rates, cost of maintenance and repairs,
and the value of a vehicle as scrap metal or as parts. Here only the
GDP growth rate is discussed, as this is the only measure included in
the final model. Extended reasoning as to why other variables are not
included in the final model in the PRIA Chapter 8 is offered, but the
discussion was omitted here for brevity in describing only the final
model. Generally economic growth will result in a higher demand for new
vehicles--cars in aggregate are normal goods--and a reduction in the
value of used vehicles. The result should be an increase in the
scrappage rate of existing vehicles so that we expect the GDP growth
rate to be an important predictor of vehicle scrappage rates.
NHTSA sourced the GDP growth rate from the 2017 OASDI Trustees
Report.\282\ The Trustees Report offers credible projections beyond
2032. Because the purpose of building this scrappage model is to
project vehicle survival rates under different fuel economy
alternatives and the current fuel economy projections go as far forward
as calendar year 2032, using a data set that encompasses projections at
least through 2032 is an essential characteristic of any source used
for this analysis.
---------------------------------------------------------------------------
\282\ The 2017 Annual Report of the Board of Trustees of the
Federal Old-Age and Survivors Insurance and Federal Disability
Insurance Trust Funds, Social Security Administration (2017),
available at https://www.ssa.gov/oact/tr/2017/tr2017.pdf.
---------------------------------------------------------------------------
(3) Summary of Model Estimation
The most predictive element of vehicle scrappage is what Greenspan
and Cohen deem `engineering scrappage.' This source of scrappage is
largely determined by the age of a vehicle and the durability of a
specific model year vintage. Vehicle scrappage typically follows a
roughly logistic function with age--that is, instantaneous scrappage
increases to some peak, and then declines, with age as noted in Walker
(1968); Park (1977); Greene & Chen (1981); Gruenspecht (1981); Feeney &
Cardebring (1988); Greenspan & Cohen (1996); Hamilton & Macauley
(1999); and Bento, Roth, & Zhuo (2016). Thus, this analysis also uses a
logistic function to capture this trend of vehicle scrappage with age
but allows non-linear terms to capture any skew to the logistic
relationship. Specific details about the final and considered forms of
engineering scrappage by body styles is presented in the PRIA Chapter
8.
The final and considered independent variables intended to capture
cyclical elements of vehicle scrappage and the considered forms of each
are discussed in PRIA Chapter 8; here only inclusion of the GDP growth
rate is discussed. The GDP growth rate is not a single-period effect;
both the current and previous GDP growth rates will affect vehicle
scrappage rates. A single year increase will affect scrappage
differently than a multi-period trend. For this reason, an optimal
number of lagged terms are included: The within-period GDP growth rate,
the previous period GDP growth rate, and the growth rate from two prior
years for the car model, while for vans/SUVs, and pickups, the current
and previous period GDP growth rate are sufficient.
Similarly, the considered model allows that one-period changes in
new vehicle prices will affect the used vehicle market differently than
a consistent trend in new vehicle prices. The optimal number of lags is
three so that the price trend from the current year and the three prior
years influences the demand for and scrappage of used vehicles. Note:
The average lease length is three years \283\ so that the price of an
average vehicle coming off lease is estimated to affect the scrappage
rate of used vehicles--this is a major source of the newest used
vehicles that enter the used car fleet. Further, because increases in
new vehicle prices due to increased stringency of CAFE standards is the
primary mechanism through which CAFE standards influence vehicle
scrappage and the CAFE Model assumes that usage, efficiency, and safety
vary with the age of the vehicle, particular attention is paid to the
form of this effect. It is important to know the likelihood of
scrappage by the age of the vehicle to correctly account for the
additional costs of additional fatalities and increased fuel
consumption from deferred scrappage. Thus, the influence of increasing
new vehicle prices is allowed to influence the demand for used vehicles
(and reduce their scrappage) differently for different ages of vehicles
in the scrappage model. We discuss both how we determined the correct
form and number of lags for each body style in PRIA Chapter 8.
---------------------------------------------------------------------------
\283\ See e.g., Edmunds January 2017 Lease Market Report,
Edmunds (Jan. 2017), https://dealers.edmunds.com/static/assets/articles/lease-report-jan-2017.pdf.
---------------------------------------------------------------------------
The final cyclical factor affecting vehicle scrappage in the
preferred model is the cost per 100 miles of travel both of new
vehicles and of the vehicle which is the subject of the decision to
scrap or not to scrap. The new vehicle cost per 100 miles is defined as
the ratio of the average fuel price faced by new vehicles in a given
calendar year and the average new vehicle fuel economy for 100 miles in
the same calendar year, and varies only with calendar year:
[GRAPHIC] [TIFF OMITTED] TP24AU18.062
The cost per 100 miles of the potentially scrapped vehicle is
described as the ratio of the average fuel price faced by that model
year vintage in a given calendar year and the average fuel economy for
100 miles of travel for that model year when it was new, and varies
both with calendar year and model year:
[GRAPHIC] [TIFF OMITTED] TP24AU18.063
[[Page 43097]]
The average per-gallon fuel price faced by a model year vintage in
a given calendar year is the annual average fuel price of all fuel
types present in that model year fleet for the given calendar year,
weighted by the share of each fuel type in that model year fleet. Or
the following, where FT represents the set of fuel types present in a
given model year vintage:
[GRAPHIC] [TIFF OMITTED] TP24AU18.064
For these variables, the best fit model includes the cost per mile
of both the new and the used vehicle for the current and prior year.
This is congruent with research that suggests consumers respond to
current fuel prices and fuel price changes. The selection process of
this form for the cost per mile and the implications is discussed in
PRIA Chapter 8.
There are a couple other controlling factors considered in our
final model. The 2009 Car Allowance Rebate System (CARS) is not
outlined here but is outlined in PRIA Chapter 8. This program aimed to
accelerate the retirement of less fuel efficient vehicles and replace
them with more fuel efficient vehicles. Further discussion of how this
is controlled for is located in PRIA Chapter 8. Finally, evidence of
autocorrelation was found, and including three lagged values of the
dependent variable addresses the concern. Treatment of autocorrelation
is discussed in PRIA Chapter 8.
One additional issue encountered in the estimations of scrappage
rates is that the models predict too many vehicles remain on the road
in the later years. This issue occurs because the data beyond age 15
are progressively more sparsely populated; vehicles over 15 years were
not captured in the Polk data until 1994, when each successive
collection year added an additional age of vehicles until 2005 when all
ages began to be collected. This means that for vehicles over the age
of 25 there are only 10 years of data. In order to correct for this
issue the fact that the final fleet share converges to roughly the same
share for most model years for a given vehicle type is used. The
predicted versus historical relationships seem to deviate beginning
around age 20; thus, for scrappage rates for vehicles beyond age 20 an
exponential decay function which guarantees that by age 40 the final
fleet share reaches the convergence level observed in the historical
data is applied. The application of the decay function and mathematical
definition is further defended in PRIA Chapter 8.
A sensitivity case is also developed to isolate the magnitude of
the Greunspecht effect. The impacts on costs and benefits are presented
in section VII.H.1 of this document. In order to isolate the effect,
the price of new vehicles is held constant at CY 2016 levels. The
specific methodology used to do so is described in detail in PRIA
Chapter 8, as is the leakage implied by comparing the reference and no
Gruenspecht effect sensitivity cases. It is important to note here that
the leakage calculated ranges between 12 and 18% across regulatory
alternatives. This is in line with Jacobsen & van Bentham (2015)
estimates which put leakage for their central case between 13 and 16%.
Their high gasoline price case is more in line this analysis' central
case--with fuel prices of $3/gallon--and predicts leakage of 21%. This
further validates the scrappage model effects against examples in the
literature.
The models used for this analysis are able to capture the
relationship for vehicle scrappage as it varies with age and how this
relationship changes with increases to new vehicle price, the cost per
mile of travel of new and used vehicles, and how the rate varies
cyclically with the GDP growth rate. It also controls for the CARS
program and checks the influence of a change in Polk's data collection
procedures. The goodness of fit measures and the plausibility of the
predictions of the model are discussed at some length in PRIA Chapter
8. In the next section, the impacts of updating the static scrappage
models to the dynamic models on average vehicle age and usage, by body
styles, and across different regulatory assumptions are discussed.
(c) What is the estimated effect on vehicle retirement and how do
results compare to previously estimated fleets and VMT?
The expected lifetime of a car estimated using the static scrappage
schedule from the 2012 final rule, both in years and miles, is between
the expected lifetime of the dynamic scrappage model in the absence of
CAFE standards and under the baseline standards. Estimated by the
dynamic scrappage model, the average vehicle is expected to live 15.1
years under the influence of only market demand for new technology, and
15.6 years under the baseline scenario, a four percent increase.
However, given the distribution of the mileage accumulation schedule by
age, this amounts only to a two percent increase in the expected
lifetime mileage accumulation of an individual vehicle. This range is
consistent with DOT expectations in terms of direction and magnitude.
The use of a static retirement schedule, while deemed a reasonable
approach in the past, is a limited representation of scrappage
behavior. It fails to account for increasing vehicle durability--
occurring for the last several decades--and the resulting increase in
average vehicle age in the on-road fleet, which has nearly doubled
since 1980.\284\ Thus, turning off the dynamic scrappage model
described above would not impose a perspective on the analysis that is
neutral with respect to observed scrappage behavior but would instead
represent a strong assumption that asserts important trends in the
historical record will abruptly cease or change direction.
---------------------------------------------------------------------------
\284\ Based on data from FHWA and IHS/Polk.
---------------------------------------------------------------------------
As discussed above, the dynamic scrappage model implemented to
support this proposal affects total fleet size through several
mechanisms. Although the model accounts for the influence of changes to
average new vehicle price and U.S. GDP growth, the most influential
mechanism, by far, is the observed trend of increasing vehicle
durability over successive model years. This phenomenon is prominently
discussed in the academic literature related to vehicle retirement,
where there is no disagreement about its existence or direction.\285\
In fact, when the CAFE model is exercised in a way that keeps average
new vehicle prices at (approximately) MY 2016 levels, the on-road fleet
grows from an initial level of 228 million in 2016 to 340 million in
2050, an increase of 49% over the 35-year period from 2016 to 2050.
---------------------------------------------------------------------------
\285\ Waker (1968); Park (1977); Feeney & Cardebring (1988);
Hamilton & Macauley (1999); and Bento, Ruth, & Zhuo (2016) note that
vehicles change in durability over time.
---------------------------------------------------------------------------
The historical data show the size of the registered vehicle
population (i.e., the on-road fleet) growing by about 60% in the 35
years between 1980 and
[[Page 43098]]
2015.\286\ In the 35 years between 2016 and 2050, our simulation shows
the on-road fleet growing from about 230 million vehicles to about 345
million vehicles when the market adopts only the amount of fuel
economy, which it naturally demands. The simulated growth over this
period is about 50% from today's level, rather than the 60% observed in
the historical data over the last 35 years. Under the baseline
regulatory scenario, the growth over the next 35 years is simulated to
be about 54%--still short of the observed growth over a comparable
period of time. In fact, the simulated annual growth rate in the size
of the on-road fleet in this analysis, about 1.3%, is lower than the
long-term average annual growth rate of about two percent dating back
to the 1970s.\287\
---------------------------------------------------------------------------
\286\ There are two measurements of the size of the registered
vehicle population that are considered to be authoritative. One is
produced by the Federal Highway Administration, and the other by
R.L. Polk (now part of IHS). The Polk measurement shows fleet growth
between 1980 and 2015 of about 85%, while the FHWA measurement shows
a slower growth rate over that period, only about 60%.
\287\ Based on calculations using Polk's National Vehicle
Population Profile (NVPP).
---------------------------------------------------------------------------
Additionally, there are inherent precision limitations in measuring
something as vast and complex as the registered vehicle population. For
decades, the two authoritative sources for the size of the on-road
fleet have been R.L. Polk (now IHS/Polk) and FHWA. For two decades
these two sources differed by more than 10% each year, only lately
converging to within a few percent of each other. These discrepancies
over the correct interpretation of the data by each source have
consistently represented differences of more than 10 million vehicles.
The total number of new vehicles projected to enter the fleet is
slightly higher than the historical trend (though the impact of the
great recession makes it hard to say by how much). More generally, the
projections used in the analysis cover long periods of time without
exhibiting the kinds of fluctuation that are present in the historical
record. For example, the forecast of GDP growth in our analysis posits
a world in which the United States sees uninterrupted positive annual
growth in real GDP for four decades. The longest such period in the
historical record is 17 years and still included several years of low
(but positive) growth during that interval.
Over such a long period of time, in the absence of deep insight
into the future of the U.S. auto industry, it is sensible to assume
that the trends observed over the course of decades are likely to
persist. Analyzing fuel economy standards requires an understanding of
the mechanisms that influence new vehicle sales, the size of the on-
road fleet, and vehicle miles traveled. It is upon these mechanisms
that the policy acts: Increasing/decreasing new vehicle prices changes
the rate at which new vehicles are sold, changing the attributes and
prices of these vehicles influences the rates at which all used
vehicles are retired, the overall size of the on-road fleet determines
the total amount of VMT, which in turn affects total fuel consumption,
fatalities, and other externalities. The fact that DOT's bottom-up
approach produces results in line with historical trends is both
expected and intended.
This is not to say that all details of this new approach will be
immediately intuitive for reviewers accustomed to results that do not
include a dynamic sales model or dynamic scrappage model, much less
results that combine the two. For example, some reviewers may observe
that today's analysis shows that, compared to the baseline standards,
the proposed standards produce a somewhat smaller on-road fleet (i.e.,
fewer vehicles in service) despite somewhat increased sales of new
vehicles (consistent with reduced new vehicle prices) and decreased
prices for used vehicles. While it might be natural to assume that
reduced prices of new vehicles and increased sales should lead to a
larger on-road fleet, in our modelling, the increased sales are more
than offset by the somewhat accelerated scrappage that accompanies the
estimated decrease in new vehicle prices. This outcome represents an
on-road fleet that is both smaller and a little younger on average
(relative to the baseline) and ``turns over'' more quickly.
To further test the validity of the scrappage model, a dynamic
forecast was constructed for calendar years 2005 through 2015 to see
how well it predicts the fleet size for this period. The last true
population the scrappage model ``sees'' is the 2005 registered vehicle
population. It then takes in known production volumes for the new model
year vehicles and dynamically estimates instantaneous scrappage rates
for all registered vehicles at each age for CYs 2006-2015, based only
on the observed exogenous values that inform the model (GDP growth
rate, observed new vehicle prices, and cost per mile of operation),
fleet attributes of the vehicles (body style, age, cost per mile of
operation), and estimated scrappage rates at earlier ages. Within this
exercise, the scrappage model relies on its own estimated values as the
previous scrappage rates at earlier ages, forcing any estimation errors
to propagate through to future years. This exercise is discussed
further in PRIA Chapter VII. While the years of the recession represent
a significant shock to the size of the fleet, briefly reversing many
years of annual growth, the model recovers quickly and produces results
within one percent of the actual fleet size, as it did prior to the
recession.
In order to compare the magnitudes of the sales and scrappage
effects across different fuel economy standards considered it is
important to define comparable measures. The sales effect in a single
calendar year is simply the difference in new vehicle sales across
alternatives. However, the scrappage effect in a single calendar year
is not simply the change in fleet size across regulatory alternatives.
The scrappage model predicts the probability that a vehicle will be
scrapped in the next year conditional on surviving to that age; the
absolute probability that a vehicle survives to a given age is
conditional on the scrappage effect for all previous analysis years. In
other words, if successive calendar years observe lower average new
vehicle prices, the effect of increased scrappage on fleet size will
accumulate with each successive calendar year--because fewer vehicles
survived to previous ages, the same probability of scrappage would
result in a smaller fleet size for the following year as well, though
fewer vehicles will have been scrapped than in the previous year.
To isolate the number of vehicles not scrapped in a single calendar
year because of the change in standards, the first step is to calculate
the number of vehicles scrapped in every calendar year for both the
proposed standards and the baseline; this is calculated by the inter-
annual change in the size of the used vehicle fleet (vehicles ages 1-
39) for each alternative. The difference in this measure across
regulatory alternatives represents the change in vehicle scrappage
because of a change in the standards. The resulting scrappage effect
for a single calendar year can be compared to the difference across
regulatory alternatives in new vehicle sales for the same calendar year
as a comparison of the relative magnitudes of the two effects. In most
years, under the proposed standards relative to the baseline standards,
the analysis shows that for each additional new vehicles sold, two to
four used vehicles are removed from the fleet. Over the time period of
the analysis these predicted differences in the numbers of vehicles
accumulate, resulting in a maximum of
[[Page 43099]]
seven million fewer vehicles by CY 2033 for the proposed CAFE standards
relative to the augural standards, and nine million fewer vehicles by
CY 2035 for the proposed GHG standards relative to the current GHG
standards. Tables 11-29 and 11-30 in the PRIA show the difference in
the fleet size by calendar year for the proposed standards relative to
the augural standards for the CAFE and GHG programs, respectively.
To understand why the sales and scrappage effects do not perfectly
offset each other to produce a constant fleet size across regulatory
alternatives it is important to remember that the decision to buy a new
vehicle and the decision to scrap a used vehicle are often not made by
the same household as a joint decision. The average length of initial
ownership for new vehicles is approximately 6.5 years (and increasing
over time). Cumulative scrappage up to age seven is typically less than
10%of the initial fleet. This suggests that most vehicles belong to
more than one household over the course of their lifetimes. The
household that is deciding whether or not to purchase a new vehicle is
rarely the same household deciding whether or not to scrap a vehicle.
So a vehicle not scrapped in a given year is seldom the direct
substitute for a new vehicle purchased by that household. Considering
this, it is not expected that for every additional vehicle scrapped,
there is also an additional new one sold, under the proposed standards
relative to the baseline standards.
Further, while sales and scrappage decisions are both influenced by
changes in new vehicle prices, the mechanism through which these
decisions change are different for the two effects. A decrease in
average new vehicle prices will directly increase the demand for new
vehicles along the same demand curve. This decrease in new vehicle
prices will cause a substitution towards new vehicles and away from
used vehicles, shifting the entire demand curve for used vehicles
downwards. This will decrease both the equilibrium prices of used
vehicles, as shown in Figure 8-16 of the PRIA. Since the decision to
scrap a vehicle in a given year is closely related to the difference
between the vehicle's value and the cost to maintain it, if the value
of a vehicle is lower than the cost to maintain it, the current owner
will not choose to maintain the vehicle for their own use or for resale
in the used car market, and the vehicle will be scrapped. That is, a
current owner will only supply a vehicle to the used car market if the
price of the vehicle is greater than the cost of supplying it. Lowering
the equilibrium price of used vehicles will lower the increase the
number of scrapped vehicles, lowering the supply of used vehicles, and
decreasing the equilibrium quantity. The change in new vehicle sales is
related to demand of new vehicles at a given price, but the change in
used vehicle scrappage is related to the shift in the demand curve for
used vehicles, and the resulting change in the quantity current owners
will supply; these effects are likely not exactly offsetting.
Our models indicate that the ratio of the magnitude of the
scrappage effect to the sales effect is greater than one so that the
fleet grows under more stringent scenarios. However, it is important to
remember that not all vehicles are driven equally; used vehicles are
estimated to deliver considerably less annual travel than new vehicles.
Further, used vehicles only have a portion of their original life left
so that it will take more than one used vehicle to replace the full
lifetime of a new vehicle, at least in the long-run. The result of the
lower annual VMT and shorter remaining lifetimes of used vehicles, is
that although the fleet is 1.5% bigger in CY 2050 for the augural
baseline than it is for the proposed standards, the total non-rebound
VMT for CY 2050 is 0.4% larger in the augural baseline than in the
proposed standards. This small increase in VMT is consistent with a
larger fleet size; if more used vehicles are supplied, there likely is
some small resulting increase in VMT.
Our models face some limitations, and work will continue toward
developing methods for estimating vehicle sales, scrappage, and mileage
accumulation. For example, our scrappage model assumes that the average
VMT for a vehicle of a particular vintage is fixed--that is, aside from
rebound effects, vehicles of a particular vintage drive the same amount
annually, regardless of changes to the average expected lifetimes. The
agencies seek comment on ways to further integrate the survival and
mileage accumulation schedules. Also, our analysis uses sales and
scrappage models that do not dynamically interact (though they are
based on similar sets of underlying factors); while both models are
informed by new vehicle prices, the model of vehicle sales does not
respond to the size and age profile of the on-road fleet, and the model
of vehicle scrappage rates does not respond to the quantity of new
vehicles sold. As one potential option for development, the potential
for an integrated model of sales and scrappage, or for a dynamic
connection between the two models will be considered. Comment is sought
on both the sales and scrappage models, on potential alternatives, and
on data and methods that may enable practicable integration of any
alternative models into the CAFE model.
7. Accounting for the Rebound Effect Caused by Higher Fuel Economy
(a) What is the rebound effect and how is it measured?
Amending and establishing fuel economy and GHG standards at a
lesser stringency than the augural standards for future model years
will lead to comparatively lower fuel economy for new cars and light
trucks, thus increasing the amount of fuel they consume in traveling
each mile than they would under the augural standard. The resulting
increase in their per-mile fuel and total driving costs will lead to a
reduction in the number of miles they are driven each year over their
lifetimes, and example of the rebound effect that is usually associated
with energy efficiency improvements working in reverse. The fuel
economy rebound effect--a specific example of the energy efficiency
rebound effect for the case of motor vehicles--refers to the well-
documented tendency of vehicles' use to increase when their fuel
economy is improved and the cost of driving each mile declines as a
result.
(b) What does the literature say about the magnitude of this effect?
Table-II-43 summarizes estimates of the fuel economy rebound effect
for light-duty vehicles from studies conducted through 2008, when the
agencies originally surveyed research on this subject.\288\ After
summarizing all of the estimates reported in published and other
publicly-available research available at that time, it distinguishes
among estimates based on the type of data used to develop them. As the
table reports, estimates of the rebound effect ranged from 6% to as
high as 75%, and the range spanned by published estimates was nearly as
wide (7-75%).
---------------------------------------------------------------------------
\288\ Complete references to the studies summarized in Table 8-2
are included in the PRIA, and many of the unpublished studies are
available in the docket for this rulemaking.
---------------------------------------------------------------------------
[[Page 43100]]
Most studies reported more than one empirical estimate, and the authors
of published studies typically identified the single estimate in which
they were most confident; these preferred estimates spanned only a
slightly narrower range (9-75%).
[GRAPHIC] [TIFF OMITTED] TP24AU18.065
Despite their wide range, these estimates displayed a strong
central tendency, as Table-II-43 also shows. The average values of all
estimates, those that were published, and authors' preferred estimates
from published studies were 22-23%, and the median estimates in each
category were close to these values, indicating nearly symmetric
distributions. The estimates in each category also clustered fairly
tightly around their respective average values, as shown by their
standard deviations in the table's last column. When classified by the
type of data they relied on, U.S. aggregate time-series data produced
slightly smaller values (averaging 18%) than did panel-type data for
individual states (23%) or household survey data (25%). In each
category, the median estimate was again quite close to the average
reported value, and comparing the standard deviations of estimates
based on each type of data again suggests a fairly tight scatter around
their respective means.
Of these studies, a then recently-published analysis by Small & Van
Dender (2007), which reported that the rebound effect appeared to be
declining over time in response to increasing income of drivers, was
singled out. These authors theorized that rising income increased the
opportunity cost of drivers' time, leading them to be less responsive
over time to reductions in the fuel cost of driving each mile. Small
and Van Dender reported that while the rebound effect averaged 22% over
the entire time period they analyzed (1967-2001), its value had
declined by half--or to 11%--during the last five years they studied
(1997-2001). Relying primarily on forecasts of its continued decline
over time, the analysis reduced the 20% rebound effect that NHTSA used
to analyze the effects of CAFE standards for light trucks produced
during model years 2005-07 and 2008-11 to 10% for their analysis of
CAFE and GHG standards for MY 2012-16 passenger cars and light trucks.
Table-II-44 summarizes estimates of the rebound effect reported in
research that has become available since the agencies' original survey,
which extended through 2008, and the following discussion briefly
summarizes the approaches used by these more recent studies. Bento et
al. (2009) combined demographic characteristics of more than 20,000
U.S. households, the manufacturer and model of each vehicle they owned,
and their annual usage of each vehicle from the 2001 National Household
Travel Survey with detailed data on fuel economy and other attributes
for each vehicle model obtained from commercial publications. The
authors aggregated vehicle models into 350 categories representing
combinations of manufacturer, vehicle type, and age, and use the
resulting data to estimate the parameters of a complex model of
households' joint choices of the number and types of vehicles to own,
and their annual use of each vehicle.
[[Page 43101]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.066
Bento et al. estimate the effect of vehicles' operating costs per
mile, including fuel costs, which depend in part on each vehicle's fuel
economy, as well as maintenance and insurance expenses, on households'
annual use of each vehicle they own. Combining the authors' estimates
of the elasticity of vehicle use with respect to per-mile operating
costs with the reported fraction of total operating costs accounted for
by fuel (slightly less than one-half) yields estimates of the rebound
effect. The resulting values vary by household composition, vehicle
size and type, and vehicle age, ranging from 21 to 38%, with a
composite estimate of 34% for all households, vehicle models, and ages.
The smallest values apply to new luxury cars, while the largest
estimates are for light trucks and households with children, but the
implied rebound effects differ little by vehicle age.
Barla et al. (2009) analyzed the responses of car and light truck
ownership, vehicle travel, and average fuel efficiency to variation in
fuel prices and aggregate economic activity (measured by gross product)
using panel-type data for the 10 Canadian provinces over the period
from 1990 through 2004. The authors estimated a system of equations for
these three variables using statistical procedures appropriate for
models where the variables of interest are simultaneously determined
(that is, where each variable is one of the factors explaining
variation in the others). This procedure enabled them to control for
the potential ``reverse influence'' of households' demand for vehicle
travel on their choices of how many vehicles to own and their fuel
efficiency levels when estimating the effect of variation in fuel
efficiency on vehicle use.
Their analysis found that provincial-level aggregate economic
activity had moderately strong effects on car and light truck ownership
and use but that fuel prices had only modest effects on driving and the
average fuel efficiency of the light-duty vehicle fleet. Each of these
effects became considerably stronger over the long term than in the
year when changes in economic activity and fuel prices initially
occurred, with three to five years typically required for behavioral
adjustments to stabilize. After controlling for the joint relationship
among vehicle ownership, driving demand, and the fuel efficiency of
cars and light trucks, Barla et al. estimated elasticities of average
vehicle use with respect to fuel efficiency that corresponded to a
rebound effect of eight percent in the short run, rising to nearly 20%
within five years. A notable feature of their analysis was that
variation in average fuel efficiency among the individual Canadian
provinces and over the time period they studied was adequate to
identify its effect on vehicle use, without the need to combine it with
variation in fuel prices in order to identify its effect.
Wadud et al. (2009) combine data on U.S. households' demographic
characteristics and expenditures on gasoline over the period 1984-2003
from the Consumer Expenditure Survey with data on gasoline prices and
an estimate of the average fuel economy of
[[Page 43102]]
vehicles owned by individual households (constructed from a variety of
sources). They employ these data to explore variation in the
sensitivity of individual households' gasoline consumption to
differences in income, gasoline prices, the number of vehicles owned by
each household, and their average fuel economy. Using an estimation
procedure intended to account for correlation among unmeasured
characteristics of households and among estimation errors for
successive years, the authors explore variation in the response of fuel
consumption to fuel economy and other variables among households in
different income categories and between those residing in urban and
rural areas.
Dividing U.S. households into five equally-sized income categories,
Wadud et al. estimate rebound effects ranging from 1-25%, with the
smallest estimates (8% and 1%) for the two lowest income categories,
and significantly larger estimates for the middle (18%) and two highest
income groups (18 and 25%). In a separate analysis, the authors
estimate rebound effects of seven percent for households of all income
levels residing in U.S. urban areas and 21% for rural households.
West & Pickrell (2011) analyzed data on more than 100,000
households and 300,000 vehicles from the 2009 Nationwide Household
Transportation Survey to explore how households owning multiple
vehicles chose which of them to use and how much to drive each one on
the day the household was surveyed. Their study focused on how the type
and fuel economy of each vehicle a household owned, as well as its
demographic characteristics and location, influenced household members'
decisions about whether and how much to drive each vehicle. They also
investigated whether fuel economy and fuel prices exerted similar
influences on vehicle use, and whether households owning more than one
vehicle tended to substitute use of one for another--or vary their use
of all of them similarly--in response to fluctuations in fuel prices
and differences in their vehicles' fuel economy.
Their estimates of the fuel economy rebound effect ranged from as
low as nine percent to as high as 34%, with their lowest estimates
typically applying to single-vehicle households and their highest
values to households owning three or more vehicles. They generally
found that differences in fuel prices faced by households who were
surveyed on different dates or who lived in different regions of the
U.S. explained more of the observed variation in daily vehicle use than
did differences in vehicles' fuel economy. West and Pickrell also found
that while the rebound effect for households' use of passenger cars
appeared to be quite large--ranging from 17% to nearly twice that
value--it was difficult to detect a consistent rebound effect for SUVs.
Anjovic & Haas (2012) examined variation in vehicle use and fuel
efficiency among six European nations over an extended period (1970-
2006), using an elaborate model and estimation procedure intended to
account for the existence of common underlying trends among the
variables analyzed and thus avoid identifying spurious or misleading
relationships among them. The six nations included in their analysis
were Austria, Germany, Denmark, France, Italy, and Sweden; the authors
also conducted similar analyses for the six nations combined. The
authors focused on the effects of average income levels, fuel prices,
and the fuel efficiency of each nation's fleet of cars on the total
distance they were driven each year and their total fuel energy
consumption. They also tested whether the responses of energy
consumption to rising and falling fuel prices appeared to be symmetric
in the different nations.
Anjovic and Haas report a long-run aggregate rebound effect of 44%
for the six nations their study included, with corresponding values for
individual nations ranging from a low of 19% (for Austria) to as high
as 56% (Italy). These estimates are based on the estimated response of
vehicle use to variation in average fuel cost per kilometer driven in
each of the six nations and for their combined total. Other information
reported in their study, however, suggests lower rebound effects; their
estimates of the response of total fuel energy consumption to fuel
efficiency appear to imply an aggregate rebound effect of 24% for the
six nations, with values ranging from as low as 0-3% (for Austria and
Denmark) to as high as 70% (Sweden), although the latter is very
uncertain. These results suggest that vehicle use in European nations
may be somewhat less sensitive to variation in driving costs caused by
changes in fuel efficiency than to changes in driving costs arising
from variation in fuel prices, but they find no evidence of asymmetric
responses of total fuel consumption to rising and falling prices. Using
data on household characteristics and vehicle use from the 2009
Nationwide Household Transportation Survey (NHTS), Su (2012) analyzes
the effects of locational and demographic factors on household vehicle
use and investigates how the magnitude of the rebound effect varies
with vehicles' annual use. Using variation in the fuel economy and per-
mile cost of and detailed controls for the demographic, economic, and
locational characteristics of the households that owned them (e.g.,
road and population density) and each vehicle's main driver (as
identified by survey respondents), the author employs specialized
regression methods to capture the variation in the rebound effect
across 10 different categories of vehicle use.
Su estimated the overall rebound effect for all vehicles in the
sample averaged 13%, and that its magnitude varied from 11-19% among
the 10 different categories of annual vehicle use. The smallest rebound
effects were estimated for vehicles at the two extremes of the
distribution of annual use--those driven comparatively little, and
those used most intensively--while the largest estimated effects
applied to vehicles that were driven slightly more than average.
Controlling for the possibility that high-mileage drivers respond to
the increased importance of fuel costs by choosing vehicles that offer
higher fuel economy narrowed the range of Su's estimated rebound
effects slightly (to 11-17%), but did not alter the finding that they
are smallest for lightly- and heavily-driven vehicles and largest for
those with slightly above average use.
Linn (2013) also uses the 2009 NHTS to develop a linear regression
approach to estimate the relationship between the VMT of vehicles
belonging to each household and a variety of different factors: Fuel
costs, vehicle characteristics other than fuel economy (e.g.,
horsepower, the overall ``quality'' of the vehicle), and household
characteristics (e.g., age, income). Linn reports a fuel economy
rebound effect with respect to VMT of between 20-40%.
One interesting result of the study is that when the fuel
efficiency of all vehicles increases, which would be the long-run
effect of rising fuel efficiency standards, two factors have opposing
effects on the VMT of a particular vehicle. First, VMT increases when
that vehicle's fuel efficiency increases. But the increase in the fuel
efficiency of the household's other vehicles causes the vehicle's own
VMT to decrease. Because the effect of a vehicle's own fuel efficiency
is larger than the other vehicles' fuel efficiency, VMT increases if
the fuel efficiency of all vehicles increases proportionately. Linn
also finds that VMT responds much more strongly to vehicle fuel economy
than to gasoline prices, which is at variance with the Hymel et al. and
Greene results discussed above.
[[Page 43103]]
Like Su and Linn, Liu et al. (2014) employed the 2009 NHTS to
develop an elaborate model of an individual household's choices about
how many vehicles to own, what types and ages of vehicles to purchase,
and how much combined driving to do using all of them. Their analysis
used a complex mathematical formulation and statistical methods to
represent and measure the interdependence among households' choices of
the number, types, and ages of vehicles to purchase, as well as how
intensively to use them.
Liu et al. employed their model to simulate variation in
households' total vehicle use to changes in their income levels,
neighborhood characteristics, and the per-mile fuel cost of driving
averaged over all vehicles each household owns. The complexity of the
relationships among the number of vehicles owned, their specific types
and ages, fuel economy levels, and use incorporated in their model
required them to measure these effects by introducing variation in
income, neighborhood attributes, and fuel costs, and observing the
response of households' annual driving. Their results imply a rebound
effect of approximately 40% in response to significant (25-50%)
variation in fuel costs, with almost exactly symmetrical responses to
increases and declines.
A study of the rebound effect by Frondel et al. (2012) used data
from travel diaries recorded by more than 2,000 German households from
1997 through 2009 to estimate alternative measures of the rebound
effect, and to explore variation in their magnitude among households.
Each household participating in the survey recorded its automobile
travel and fuel purchases over a period of one to three years and
supplied information on its composition and the personal
characteristics of each of its members. The authors converted
households' travel and fuel consumption to a monthly basis, and used
specialized estimation procedures (quantile and random-effects panel
regression) to analyze monthly variation in their travel and fuel use
in relation to differences in fuel prices, the fuel efficiency of each
vehicle a household owned, and the fuel cost per mile of driving each
vehicle.
Frondel et al. estimate four separate measures of the rebound
effect, three of which capture the response of vehicle use to variation
in fuel efficiency, fuel price, and fuel cost per mile traveled, and a
fourth capturing the response of fuel consumption to changes in fuel
price. Their first three estimates range from 42% to 57%, while their
fourth estimate corresponds to a rebound effect of 90%. Although their
analysis finds no significant variation of the rebound effect with
household income, vehicle ownership, or urban versus rural location, it
concludes that the rebound effect is substantially larger for
households that drive less (90%) than for those who use their vehicles
most intensively (56%).
Gillingham (2014) analyzed variation in the use of approximately
five million new vehicles sold in California from 2001 to 2003 during
the first several years after their purchase, focusing particularly on
how their use responded to geographic and temporal variation in fuel
prices. His sample consisted primarily of personal or household
vehicles (87%) but also included some that were purchased by
businesses, rental car companies, and government agencies. Using
county-level data, he analyzed the effect of differences in the monthly
average fuel price paid by their drivers on variation in their monthly
use and explored how that effect varied with drivers' demographic
characteristics and household incomes.
Gillingham's analysis did not include a measure of vehicles' fuel
economy or fuel cost per mile driven, so he could not measure the
rebound effect directly, but his estimates of the effect of fuel prices
on vehicle use correspond to a rebound effect of 22-23% (depending on
whether he controlled for the potential effect of gasoline demand on
its retail price). His estimation procedure and results imply that
vehicle use requires nearly two years to adjust fully to changes in
fuel prices. He found little variation in the sensitivity of vehicle
use to fuel prices among car buyers with different demographic
characteristics, although his results suggested that it increases with
their income levels.
Weber & Farsi (2014) analyzed variation in the use of more than
70,000 individual cars owned by Swiss households who were included in a
2010 survey of travel behavior. Their analysis focuses on the
simultaneous relationships among households' choices of the fuel
efficiency and size (weight) of the vehicles they own, and how much
they drive each one, although they recognize that fuel efficiency
cannot be chosen independently of vehicle weight. The authors employ a
model specification and statistical estimation procedures that account
for the likelihood that households intending to drive more will
purchase more fuel-efficient cars but may also choose more spacious and
comfortable--and thus heavier--models, which affects their fuel
efficiency indirectly, since heavier vehicles are generally less fuel-
efficient. The survey data they rely on includes both owners' estimates
of their annual use of each car and the distance it was actually driven
on a specific day; because they are not closely correlated, the authors
employ them as alternative measures of vehicle use to estimate the
rebound effect, but this restricts their sample to the roughly 8,100
cars for which both measures are available. Weber and Farsi's estimates
of the rebound effect are extremely large: 75% using estimated annual
driving and 81% when they measure vehicle use by actual daily driving.
Excluding vehicle size (weight) and limiting the choices that
households are assumed to consider simultaneously to just vehicles'
fuel efficiency and how much to drive approximately reverses these
estimates, but both are still very large. Using a simpler procedure
that does not account for the potential effect of driving demand on
households' choices among vehicle models of different size and fuel
efficiency produces much smaller values for the rebound effect: 37%
using annual driving and 19% using daily travel. The authors interpret
these latter estimates as likely to be too low because actual on-road
fuel efficiency has not improved as rapidly as suggested by the
manufacturer-reported measure they employ. This introduces an error in
their measure that may be related to a vehicle's age, and their more
complex estimation procedure may reduce its effect on their estimates.
Nevertheless, even their lower estimates exceed those from many other
studies of the rebound effect, as Table 8-2 shows.
Hymel, Small, & Van Dender (2010)--and more recently, Hymel & Small
(2015)--extended the simultaneous equations analysis of time-series and
state-level variation in vehicle use originally reported in Small & Van
Dender (2007) and to test the effect of including more recent data. As
in the original 2007 study, both subsequent extensions found that the
fuel economy rebound effect had declined over time in response to
increasing personal income and urbanization but had risen during
periods when fuel prices increased. Because they rely on the response
of vehicle use to fuel cost per mile to estimate the rebound effect,
however, none of these three studies is able to detect whether its
apparent decline in response to rising income levels over time truly
reflects its effect on drivers' responses to changing fuel economy--the
rebound effect itself--or simply captures the effect of rising income
on their sensitivity to fuel
[[Page 43104]]
prices.\289\ These updated studies each revised Small and Van Dender's
original estimate of an 11% rebound effect for 1997-2011 upward when
they included more recent experience: To 13% for the period 2001-04,
and subsequently to 18% for 2000-2009.
---------------------------------------------------------------------------
\289\ DeBorger et al. (2016) analyze the separate effects of
variation in household income on the sensitivity of their vehicle
use to fuel prices and the fuel economy of vehicles they own. Their
results imply the decline in the fuel economy rebound effect with
income reported in Small & Van Dender (2007) and its subsequent
extensions appears to result entirely from a reduction in drivers'
sensitivity to fuel prices as their incomes rise, rather than from
any effect of rising income on the sensitivity of vehicle use to
improving fuel economy; i.e., on the fuel economy rebound effect
itself.
---------------------------------------------------------------------------
In their 2015 update, Hymel and Small hypothesized that the recent
increase in the rebound effect could be traced to a combination of
expanded media coverage of changing fuel prices, increased price
volatility, and an asymmetric response by drivers to variation in fuel
costs. The authors estimated that about half of the apparent increase
in the rebound effect for recent years could be attributed to greater
volatility in fuel prices and more media coverage of sudden price
changes. Their results also suggest that households curtail their
vehicle use within the first year following an increase in fuel prices
and driving costs, while the increase in driving that occurs in
response to declining fuel prices--and by implication, to improvements
in fuel economy--occurs more slowly.
West et al. (2015) attempted to infer the fuel economy rebound
effect using data from Texas households who replaced their vehicles
with more fuel-efficient models under the 2009 ``Cash for Clunkers''
program, which offered sizeable financial incentives to do so. Under
the program, households that retired older vehicles with fuel economy
levels of 18 miles per gallon (MPG) or less were eligible for cash
incentives ranging from $3,500-4,000, while those retiring vehicles
with higher fuel economy were ineligible for such rebates. The authors
examined the fuel economy, other features, and subsequent use of new
vehicles households in Texas purchased to replace older models that
narrowly qualified for the program's financial incentives because their
fuel economy was only slightly below the 18 MPG threshold. They then
compared these to the fuel economy, features, and use of new vehicles
that demographically comparable households bought to replace older
models, but whose slightly higher fuel economy--19 MPG or above--made
them barely ineligible for the program.
The authors reported that the higher fuel economy of new models
that eligible households purchased in response to the generous
financial incentives offered under the ``Cash for Clunkers'' did not
prompt their buyers to use them more than the older, low-MPG vehicles
they replaced. They attributed this apparent absence of a fuel economy
rebound effect--which they described as an ``attribute-adjusted''
measure of its magnitude--to the fact that eligible households chose to
buy less expensive, smaller, and lower-performing models to replace
those they retired. Because these replacements offered lower-quality
transportation service, their buyers did not drive them more than the
vehicles they replaced.
The applicability of this result to the proposal's analysis is
doubtful because previous regulatory analyses assumed that
manufacturers could achieve required improvements in fuel economy
without compromising the performance, carrying and towing capacity,
comfort, or safety of cars and light trucks from recent model
years.\290\ While this may be technically true, doing so would come at
a combined greater cost. If this argument is correct, then amending
future standards at a reduced stringency from their previously-adopted
levels would lead to less driving attributable to rebound, and should
therefore not lead to artificial constraints in new vehicles' other
features that offset the reduction in their use stemming from lower
fuel economy.
---------------------------------------------------------------------------
\290\ As discussed, this does not mean attributes of future cars
and light trucks will be anything close to those manufacturers could
have offered if lower standards had remained in effect. Instead, the
agencies asserted features other than fuel economy could be
maintained at the levels offered in recent model years--that
features will not likely be removed, but may not be improved.
---------------------------------------------------------------------------
Most recently, De Borger et al. (2017) analyze the response of
vehicle use to changes in fuel economy among a sample of nearly 350,000
Danish households owning the same model vehicle, of which almost one-
third replaced it with a different model sometime during the period
from 2001 to 2011. By comparing the changes in households' driving from
the early years of this period to its later years among those who
replaced their vehicles during the intervening period to the changes in
driving among households who kept their original vehicles, the authors
attempted to isolate the effect of changes in fuel economy on vehicle
use from those of other factors. They measured the rebound effect as
the change in households' vehicle use in response to differences in the
fuel economy between vehicles they had owned previously and the new
models they purchased to replace them, over and above any change in
vehicle use among households who did not buy new cars (and thus saw no
change in fuel economy).
These authors' data enabled them to control for the effects of
changes over time in household characteristics and vehicle features
other than fuel economy that were likely to have contributed to
observed changes in vehicle use. They also employed complex statistical
methods to account for the fact that some households replacing their
vehicles may have done so in anticipation of changes in their driving
demands (rather than the reverse), as well as for the possibility that
some households who replaced their cars may have done so because their
driving behavior was more sensitive to fuel prices than other
households. Their estimates ranged from 8-10%, varying only minimally
among alternative model specifications and statistical estimation
procedures or in response to whether their sample was restricted to
households that replaced their vehicles or also included households
that kept their original vehicles throughout the period.\291\ Finally,
De Borger et al. found no evidence that the rebound effect is smaller
among lower-income households than among their higher-income
counterparts.
---------------------------------------------------------------------------
\291\ This latter result suggests their estimates were not
biased by any tendency for households whose demographic
characteristics, economic circumstances, or driving demands changed
over the period in ways that prompted them to replace their vehicles
with models offering different fuel economy.
---------------------------------------------------------------------------
(c) What value have the agencies assumed in this rule?
On the basis of all of the evidence summarized here, a fuel economy
rebound effect of 20% has been chosen to analyze the effects of the
proposed action. This is a departure from the 10% value used in
regulatory analyses for MYs 2012-2016 and previous analyses for MYs
2017-2025 CAFE and GHG standards and represents a return to the value
employed in the analyses for MYs 2005-2011 CAFE standards. There are
several reasons the estimate of the fuel economy rebound effect for
this analysis has been increased.
First, the 10% value is inconsistent with nearly all research on
the magnitude of the rebound effect, as Table-II-43 and Table-II-44
indicate. Instead, it is based almost exclusively
[[Page 43105]]
on the finding of the 2007 study by Small and Van Dender that the
rebound effect had been declining over time in response to drivers'
rising incomes and on extending that decline through future years using
an assumption of steady income growth. As indicated above, however,
subsequent extensions of Small and Van Dender's original research have
produced larger estimates of the rebound effect for recent years: While
their original study estimated the rebound effect at 11% for 1997-2001,
the 2010 update by Hymel, Small, and Van Dender reported a value of 13%
for 2004, and Hymel and Small's 2015 update estimated the rebound
effect at 18% for 2003-09. Further, the issues with state-level
measures of vehicle use, fuel consumption, and fuel economy identified
previously raise some doubt about the reliability of these studies'
estimates of the rebound effect.
At the same time, the continued increases in income that were
anticipated to produce a continued decline in the rebound effect have
not materialized. The income measure (real personal income per Capita)
used in these analyses has grown only approximately one percent
annually over the past two decades and is projected to grow at
approximately 1.5% for the next 30 years, in contrast to the two to
three percent annual growth assumed by the agencies when developing
earlier forecasts of the future rebound effect. Further, another recent
study by DeBorger et al. (2016) analyzed the separate effects of
variation in household income on the sensitivity of their vehicle use
to fuel prices and the fuel economy of vehicles they own. These
authors' results indicate that the decline in the fuel economy rebound
effect with income reported in Small & Van Dender (2007) and subsequent
research results entirely from a reduction in drivers' sensitivity to
fuel prices as their incomes rise rather than from any effect of rising
income on the sensitivity of vehicle use to fuel economy itself. This
latter measure, which DeBorger et al. find has not changed
significantly as incomes have risen over time, is the correct measure
of the fuel economy rebound effect, so their analysis calls into
question its assumed sensitivity to income.
Some studies of households' use of individual vehicles also find
that the fuel economy rebound effect increases with the number of
vehicles they own. Because vehicle ownership is strongly associated
with household income, this common finding suggests that the overall
value of the rebound effect is unlikely to decline with rising incomes
as the agencies had previously assumed. In addition, buyers of new cars
and light trucks belong disproportionately to higher-income households
that already own multiple vehicles, which further suggests that the
higher values of the rebound effect estimated by many studies for such
households are more relevant for analyzing use of newly-purchased cars
and light trucks.
Finally, research on the rebound effect conducted since the
agencies' original 2008 review of evidence almost universally reports
estimates in the 10-40% (and larger) range, as Table-II-43 shows. Thus,
the 20% rebound effect used in this analysis more accurately represents
the findings from both the studies considered in 2008 review and the
more recent analyses.
(1) What are the implications of the rebound effect for VMT?
The assumed rebound effect not only influences the use of new
vehicles in today's analysis but also affects the response of the
initial registered vehicle population to changes in fuel price
throughout their remaining useful lives. The fuel prices used in this
analysis are lower than the projections used to inform the 2012 Final
Rule but generally increase from today's level over time. As they do
so, the rebound effect acts as a price elasticity of demand for
travel--as the cost-per-mile of travel increases, owners of all
vehicles in the registered population respond by driving less. In
particular, they drive 20% less than the difference between the cost-
per-mile of travel when they were observed in calendar year 2016 and
the relevant cost-per-mile at any future age. For the new vehicles
subject to this proposal (and explicitly simulated by the CAFE model),
fuel economies increase relative to MY 2016 levels, and generally
improve enough to offset the effect of rising fuel prices--at least
during the years covered by the proposal. For those vehicles, the
difference between the initial cost-per-mile of travel and future
travel costs is negative. As the vehicles become less expensive to
operate, they are driven more (20% more than the difference between
initial and present travel costs, precisely). Of course, each of the
regulatory alternatives considered in the analysis would result in
lower fuel economy levels for vehicles produced in model year 2020 and
later than if the baseline standards remained in effect, so total VMT
is lower under these alternatives than under the baseline.
(2) What is the mobility benefit that accrues to vehicle owners?
The increase in travel associated with the rebound effect produces
additional benefits to vehicle owners, which reflect the value to
drivers and other vehicle occupants of the added (or more desirable)
social and economic opportunities that become accessible with
additional travel. As evidenced by the fact that they elect to make
more frequent or longer trips when the cost of driving declines, the
benefits from this added travel exceed drivers' added outlays for the
fuel it consumes (measured at the improved level of fuel economy
resulting from stricter CAFE standards). The amount by which the
benefits from this increased driving travel exceed its increased fuel
costs measures the net benefits they receive from the additional
travel, usually are referred to as increased consumer surplus.
NHTSA's analysis estimates the economic value of the decreased
consumer surplus provided by reduced driving using the conventional
approximation, which is one half of the product of the increase in
vehicle operating costs per vehicle-mile and the resulting decrease in
the annual number of miles driven. Because it depends on the extent of
the change in fuel economy, the value of economic impacts from
decreased vehicle use changes by model year and varies among
alternative CAFE standards.
(d) Societal Externalities Associated With CAFE Alternatives
(1) Energy Security Externalities
Higher U.S. fuel consumption will produce a corresponding increase
in the nation's demand for crude petroleum, which is traded actively in
a worldwide market. The U.S. accounts for a large enough share of
global oil consumption that the resulting boost in global demand will
raise its worldwide price. The increase in global petroleum prices that
results from higher U.S. demand causes a transfer of revenue to oil
producers worldwide from not only buyers of new cars and light trucks,
but also other consumers of petroleum products in the U.S. and
throughout the world, all of whom pay the higher price that results.
Although these effects will be tempered by growing U.S. oil
production, uncertainty in the long-term import-export balance makes it
difficult to precisely project how these effects might change in
response to that increased production. Growing U.S. petroleum
consumption will also increase potential costs to all U.S. petroleum
users from possible interruptions in the global supply of petroleum or
rapid increases in global oil prices, not all of which are borne by
[[Page 43106]]
the households or businesses who increase their petroleum consumption
(that is, they are partly ``external'' to petroleum users). If U.S.
demand for imported petroleum increases, it is also possible that
increased military spending to secure larger oil supplies from unstable
regions of the globe will be necessary.
These three effects are often referred to collectively as ``energy
security externalities'' resulting from U.S. petroleum consumption, and
increases in their magnitude are sometimes cited as potential social
costs of increased U.S. demand for oil. To the extent that they
represent real economic costs that would rise incrementally with
increases in U.S. petroleum consumption of the magnitude likely to
result from less stringent CAFE and GHG standards, these effects
represent potential additional costs of this proposed action. Chapter 7
of the Regulatory Impact Analysis for this proposed action defines each
of these energy security externalities in detail, assesses whether its
magnitude is likely to change as a consequence of this action, and
identifies whether that change represents a real economic cost or
benefit of this action.
(2) Environmental Externalities
The change in criteria pollutant emissions that result from changes
in vehicle usage and fuel consumption is estimated as part of this
analysis. Criteria air pollutants include carbon monoxide (CO),
hydrocarbon compounds (usually referred to as ``volatile organic
compounds,'' or VOC), nitrogen oxides (NOX), fine
particulate matter (PM2.5), and sulfur oxides
(SOX). These pollutants are emitted during vehicle storage
and use, as well as throughout the fuel production and distribution
system. While increases in domestic fuel refining, storage, and
distribution that result from higher fuel consumption will increase
emissions of these pollutants, reduced vehicle use associated with the
fuel economy rebound effect will decrease their emissions. The net
effect of less stringent CAFE standards on total emissions of each
criteria pollutant depends on the relative magnitudes of increases in
its emissions during fuel refining and distribution, and decreases in
its emissions resulting from additional vehicle use. Because the
relationship between emissions in fuel refining and vehicle use is
different for each criteria pollutant, the net effect of increased fuel
consumption from the proposed standards on total emissions of each
pollutant is likely to differ.
The social damage costs associated with changes in the emissions of
criteria pollutants and CO2 was calculated, attributing
benefits and costs to the regulatory alternatives considered based on
the sign of the change in each pollutant. In previous rulemakings, the
agencies have considered the social cost of CO2 emissions
from a global perspective, accumulating social costs for CO2
emissions based on adverse outcomes attributable to climate change in
any country. In this analysis, however, the costs of CO2
emissions and resulting climate damages from both domestic and global
perspectives were considered. Chapter 9 of the Regulatory Impact
Analysis provides a detailed discussion of how the agencies estimate
changes in emissions of criteria air pollutants and CO2 and
reports the values the agencies use to estimate benefits or costs
associated with those changes in emissions.
(3) Traffic Externalities (Congestion, Noise)
Increased vehicle use associated with the rebound effect also
contributes to increased traffic congestion and highway noise. To
estimate the economic costs associated with these consequences of added
driving, the estimates of per-mile congestion and noise costs caused by
increased use of automobiles and light trucks developed previously by
the Federal Highway Administration (FHWA) were applied. These values
are intended to measure the increased costs resulting from added
congestion and the delays it causes to other drivers and passengers and
noise levels contributed by automobiles and light trucks. NHTSA
previously employed these estimates in its analysis accompanying the MY
2011 final CAFE rule as well as in its analysis of the effects of
higher CAFE standards for MY 2012-16 and MY 2017-2021. After reviewing
the procedures used by FHWA to develop them and considering other
available estimates of these values and recognizing that no commenters
have addressed these costs directly in their comments on previous
rules, the values continue to be appropriate for use in this proposal.
For this analysis, FHWA's estimates of per-mile costs are multiplied by
the annual increases in automobile and light truck use from the rebound
effect to yield the estimated increases in total congestion and noise
externality costs during each year over the lifetimes of the cars and
light trucks in the on-road fleet. Due to the fact that this proposal
represents a decrease in stringency, the fuel economy rebound effect
results in fewer miles driven under the action alternatives relative to
the baseline, which generates savings in congestion and road noise
relative to the baseline.
F. Impact of CAFE Standards on Vehicle Safety
In past CAFE rulemakings, NHTSA has examined the effect of CAFE
standards on vehicle mass and the subsequent effect mass changes will
have on vehicle safety. While setting standards based on vehicle
footprint helps reduce potential safety impacts associated with CAFE
standards as compared to setting standards based on some other vehicle
attribute, footprint-based standards cannot entirely eliminate those
impacts. Although prior analyses noted that there could also be impacts
because of other factors besides mass changes, those impacts were not
estimated quantitatively.\292\ In this current analysis, the safety
analysis has been expanded to include a broader and more comprehensive
measure of safety impacts, as discussed below. A number of factors can
influence motor vehicle fatalities directly by influencing vehicle
design or indirectly by influencing consumer behavior. These factors
include:
---------------------------------------------------------------------------
\292\ NHTSA included a quantification of rebound-associated
safety impacts in its Draft TAR analysis, but because the scrappage
model is new for this rulemaking, did not include safety impacts
associated with the effect of standards on new vehicle prices and
thus on fleet turnover. The fact that the scrappage model did not
exist previously does not mean that the effects that it aims to show
were not important considerations, simply that the agency was unable
to account for them quantitatively prior to the current analysis.
---------------------------------------------------------------------------
(1) Changes, which affect the crashworthiness of vehicles impact
other vehicles or roadside objects, in vehicle mass made to reduce fuel
consumption. NHTSA's statistical analysis of historical crash data to
understand effects of vehicle mass and size on safety indicates
reducing mass in light trucks generally improves safety, while reducing
mass in passenger cars generally reduces safety. NHTSA's crash
simulation modeling of vehicle design concepts for reducing mass
revealed similar trends.\293\
---------------------------------------------------------------------------
\293\ DOT HS 812051a--Methodology for evaluating fleet
protection of new vehicle designs Application to lightweight vehicle
designs, DOT HS 812051b Methodology for evaluating fleet protection
of new vehicle designs_Appendices.
---------------------------------------------------------------------------
(2) The delay in the pace of consumer acquisition of newer safer
vehicles that results from higher vehicle prices associated with
technologies needed to meet higher CAFE standards. Because of a
combination of safety regulations and voluntary safety improvements,
passenger vehicles have become safer over time. Compared to prior
decades, fatality rates have declined significantly
[[Page 43107]]
because of technological safety improvements as well as behavioral
shifts such as increased seat belt use. The results of this analysis
project that vehicle prices will be nearly $1,900 higher under the
augural CAFE standards compared to the preferred alternative that would
hold stringency at MY 2020 levels in MYs 2021-2026. This will induce
some consumers to delay or forgo the purchase of newer safer vehicles
and slow the transition of the on-road fleet to one with the improved
safety available in newer vehicles. This same factor can also shift the
mix of passenger cars and light trucks.
(3) Increased driving because of better fuel economy. The ``rebound
effect'' predicts consumers will drive more when the cost of driving
declines. More stringent CAFE standards reduce vehicle operating costs,
and in response, some consumers may choose to drive more. Driving more
increases exposure to risks associated with on-road transportation, and
this added exposure translates into higher fatalities.
Although all three factors influence predicted fatality levels that
may occur, only two of them, the changes in vehicle mass and the
changes in the acquisition of safer vehicles--are actually imposed on
consumers by CAFE standards. The safety of vehicles has improved over
time and is expected to continue improving in the future commensurate
with the pace of safety technology innovation and implementation and
motor vehicle safety regulation. Safety improvements will likely
continue regardless of changes to CAFE standards. However, its pace may
be modified if manufacturers choose to delay or forgo investments in
safety technology because of the demand CAFE standards impose on
research, development, and manufacturing budgets. Increased driving
associated with rebound is a consumer choice. Improved CAFE will reduce
driving costs, but nothing in the higher CAFE standards compels
consumers to drive additional miles. If consumers choose to do so, they
are making a decision that the utility of more driving exceeds the
marginal operating costs as well as the added crash risk it entails.
Thus, while the predicted fatality impacts with all three factors
embedded into the model are measured, the fatalities associated with
consumer choice decisions are accounted for separately from those
resulting from technologies implemented in response to CAFE regulations
or economic limitations resulting from CAFE regulation. Only those
safety impacts associated with mass reduction and those resulting from
higher vehicle prices are directly attributed to CAFE standards.\294\
This is reflected monetarily by valuing extra rebound miles at the full
value of their added driving cost plus the added safety risk consumers
experience, which completely offsets the societal impact of any added
fatalities from this voluntary consumer choice.
---------------------------------------------------------------------------
\294\ It could be argued fatalities resulting from consumer's
decision to delay the purchase of newer safer vehicles is also a
market decision implying consumers fully accept the added safety
risk associated with this delay and value the time value of money
saved by the delayed purchase more than this risk. This scenario is
likely accurate for some purchasers. For others, the added cost may
represent a threshold price increase effectively preventing them
from being financially able to purchase a new vehicle. Presently
there is no way to determine the proportion of lost sales reflected
by these two scenarios. The added driving from the rebound effect
results from a positive benefit of CAFE, which reduces the cost of
driving. By contrast, the effect of retaining older vehicles longer
results from costs imposed on consumers, which potentially limit
their purchase options. Thus, fatalities are attributed to retaining
older vehicles due to CAFE but not those resulting from decisions to
drive more. Comments are sought on this assumption.
---------------------------------------------------------------------------
The safety component of CAFE analysis has evolved over time. In the
2012 final rule, the analysis accounted for the change in projected
fatalities attributable to mass reduction of new vehicles. The model
assumed that manufacturers would choose mass reduction as a compliance
method across vehicle classes such that the net effect of mass
reduction on fatalities was zero. However, in the 2016 draft Technical
Assessment Report, DOT made two consequential changes to the analysis
of fatalities associated with the CAFE standards. In particular, first,
the modelling assumed that mass reduction technology was available to
all vehicles, regardless of net safety impact, and second, it accounted
for the incremental safety costs associated with additional miles
traveled due to the rebound effect. The current analysis extends the
analysis to report incremental fatality impacts associated with
additional miles traveled due to the rebound effect, and identifies the
increase in fatalities associated with additional driving separately
from changes in fatalities attributable other sources.\295\
---------------------------------------------------------------------------
\295\ Drivers who travel additional miles are assumed to
experience benefits that at least offset the costs they incur in
doing so, including the increased safety risks they face. Thus while
the number of additional fatalities resulting from increased driving
is reported, the associated costs are not included among the social
costs of the proposal.
---------------------------------------------------------------------------
The current analysis adds another element: The effect that higher
new vehicle prices have on new vehicle sales and on used vehicle
scrappage, which influences total expected fatalities because older
vehicle vintages are associated with higher rates of involvement in
fatal crashes than newer vehicles. Finally, a dynamic fleet share model
also predicts the effects of changes in the standards on the share of
light trucks and passenger cars in future model year light-duty vehicle
fleets. Vehicles of different body styles have different rates of
involvement in fatal crashes, so that changing the share of each in the
projected future fleet has safety impacts; the implied safety effects
are captured in the current modelling. The agencies seek comment on
changes to the safety analysis made in this proposal, they seek
particular comment on the following changes:
(1) The sales scrappage models as independent models: Two
separate models capture the effects of new vehicle prices on new
vehicle demand and used vehicle retirement rates--the sales model
and the scrappage model, respectively. We seek public comment on the
methods used for each of these models, in particular we seek comment
on:
The assumptions and variables included in the independent
models
The techniques and data used to estimate the independent
models
The structure and implementation of the independent models
(2) Integration of the sales and scrappage models: The new sales
and scrappage models use many of the same predictors, but are not
directly integrated. We seek public comment on, and data supporting
whether integrating the two models is appropriate.
(3) Integration of the scrappage rates and mileage accumulation:
The current model assumes that annual mileage accumulation and
scrappage rates are independent of one another. We seek public
comment on the appropriateness of this assumption, and data that
would support developing an interaction between scrappage rates and
mileage accumulation, or testing whether such an interaction is
important to include.
(4) Increased risk of older vehicles: The observed increase in
crash and injury risk associated with older vehicles is likely due
to a combination of vehicle factors and driver factors. For example,
older vehicles are less crashworthy because in general they're
equipped with fewer or less modern safety features, and drivers of
older cars are on average younger and may be less skilled drivers or
less risk-averse than drivers of new vehicles. We fit a model which
includes both an age and vintage affect, but assume that the age
effect is entirely a result of changes in average driver
demographics, and not impacted by changes in CAFE or GHG standards.
We seek comment on this approach for attributing increased older
vehicle risk. Is the analysis likely to overestimate or
underestimate the safety benefits under the proposed alternative?
(5) Changes in the mix of light trucks and passenger cars: The
dynamic fleet share model predicts changes in the future share of
light truck and passenger car vehicles. Changes in the mix of
vehicles may result in
[[Page 43108]]
increased or decreased fatalities. Does the dynamic fleet share
model reasonably capture consumers' decisions about how they
substitute between different types and sizes of vehicles depending
on changes in fuel economy, relative and absolute prices, and other
vehicle attributes? We seek comment on whether our safety analysis
provides a reasonable estimate of the effects of changes in fleet
mix on future fatalities.
1. Impact of Weight Reduction on Safety
The primary goals of CAFE and CO2 standards are reducing
fuel consumption and CO2 emissions from the on-road light-
duty vehicle fleet; in addition to these intended effects, the
potential of the standards to affect vehicle safety is also
considered.\296\ As a safety agency, NHTSA has long considered the
potential for adverse safety consequences when establishing CAFE
standards, and under the CAA, EPA considers factors related to public
health and human welfare, including safety, in regulating emissions of
air pollutants from mobile sources.
---------------------------------------------------------------------------
\296\ In this rulemaking document, ``vehicle safety'' is defined
as societal fatality rates per vehicle mile of travel (VMT),
including fatalities to occupants of all vehicles involved in
collisions, plus any pedestrians. Injuries and property damage are
not within the scope of the statistical models discussed in this
section because of data limitations (e.g., limited information on
observed or potential relationships between safety standards and
injury and property damage outcomes, consistency of reported injury
severity levels). Rather, injuries and property damage are
represented within the CAFE model through adjustment factors based
on observed relationships between societal costs of fatalities and
societal injury and property damage costs.
---------------------------------------------------------------------------
Safety trade-offs associated with fuel economy increases have
occurred in the past, particularly before NHTSA CAFE standards were
attribute-based; past safety trade-offs may have occurred because
manufacturers chose at the time, in response to CAFE standards, to
build smaller and lighter vehicles. Although the agency now uses
attribute-based standards, in part to protect against excessive vehicle
downsizing, the agency must be mindful of the possibility of related
safety trade-offs in the future. In cases where fuel economy
improvements were achieved through reductions in vehicle size and mass,
the smaller, lighter vehicles did not fare as well in crashes as
larger, heavier vehicles, on average.
Historically, as shown in FARS data analyzed by NHTSA, the safest
cars generally have been heavy and large, while cars with the highest
fatal-crash rates have been light and small. The question, then, is
whether past is necessarily a prologue when it comes to potential
changes in vehicle size (both footprint and ``overhang'') and mass in
response to the more stringent future CAFE and GHG standards.
Manufacturers stated they will reduce vehicle mass as one of the
cost-effective means of increasing fuel economy and reducing
CO2 to meet standards, and this approach is incorporated
this expectation into the modeling analysis supporting the standards.
Because the analysis discerns a historical relationship between vehicle
mass, size, and safety, it is reasonable to assume these relationships
will continue in the future.
(a) Historical Analyses of Vehicle Mass and Safety
Researchers have been using statistical analysis to examine the
relationship of vehicle mass and safety in historical crash data for
many years and continue to refine their techniques. In the MY 2012-2016
final rule, the agencies stated we would conduct further study and
research into the interaction of mass, size, and safety to assist
future rulemakings and start to work collaboratively by developing an
interagency working group between NHTSA, EPA, DOE, and CARB to evaluate
all aspects of mass, size, and safety. The team would seek to
coordinate government-supported studies and independent research to the
greatest extent possible to ensure the work is complementary to
previous and ongoing research and to guide further research in this
area.
The agencies also identified three specific areas to direct
research in preparation for future CAFE/CO2 rulemaking
regarding statistical analysis of historical data. First, NHTSA would
contract with an independent institution to review statistical methods
NHTSA and DRI used to analyze historical data related to mass, size,
and safety, and to provide recommendations on whether existing or other
methods should be used for future statistical analysis of historical
data. This study would include a consideration of potential near
multicollinearity in the historical data and how best to address it in
a regression analysis. The 2010 NHTSA report (hereinafter 2010 Kahane
report) was also peer reviewed by two other experts in the safety
field--Farmer (Insurance Institute for Highway Safety) and Lie (Swedish
Transport Administration).\297\
---------------------------------------------------------------------------
\297\ All three peer reviews are available in Docket No. NHTSA-
2010-0152, Relationships Between Fatality Risk, Mass, and Footprint,
https://www.regulations.gov/docket?D=NHTSA-2010-0152.
---------------------------------------------------------------------------
Second, NHTSA and EPA, in consultation with DOE, would update the
MY 1991-1999 database where safety analyses in the NPRM and final rule
are based with newer vehicle data and create a common database that
could be made publicly available to address concerns that differences
in data were leading to different results in statistical analyses by
different researchers.
And third, to assess if the design of recent model year vehicles
incorporating various mass reduction methods affect relationships among
vehicle mass, size, and safety, the agencies sought to identify
vehicles using material substitution and smart design and to assess if
there is sufficient crash data involving those vehicles for statistical
analysis. If sufficient data exists, statistical analysis would be
conducted to compare the relationship among mass, size, and safety of
these smart design vehicles to vehicles of similar size and mass with
more traditional designs.
By the time of the MY 2017-2025 final rule, significant progress
was made on these tasks: The independent review of recent and updated
statistical analyses of the relationship between vehicle mass, size,
and crash fatality rates had been completed. NHTSA contracted with the
University of Michigan Transportation Research Institute (UMTRI) to
conduct this review, and the UMTRI team led by Green evaluated more
than 20 papers, including studies done by NHTSA's Kahane, Wenzel of the
U.S. Department of Energy's Lawrence Berkeley National Laboratory,
Dynamic Research, Inc., and others. UMTRI's basic findings are
discussed in Chapter 11 of the PRIA accompanying this NPRM.
Some commenters in recent CAFE rulemakings, including some vehicle
manufacturers, suggested designs and materials of more recent model
year vehicles may have weakened the historical statistical
relationships between mass, size, and safety. It was agreed that the
statistical analysis would be improved by using an updated database
reflecting more recent safety technologies, vehicle designs and
materials, and reflecting changes in the vehicle fleet. An updated
database was created and employed for assessing safety effects for that
final rule. The agencies also believed, as UMTRI found, different
statistical analyses may have produced different results because they
used slightly different datasets for their analyses.
To try to mitigate this issue and to support the current
rulemaking, NHTSA created a common, updated database for statistical
analysis consisting of crash data of model years 2000-2007 vehicles in
calendar years 2002-2008, as
[[Page 43109]]
compared to the database used in prior NHTSA analyses, which was based
on model years 1991-1999 vehicles in calendar years 1995-2000. The new
database was the most up-to-date possible, given the processing lead
time for crash data and the need for enough crash cases to permit
statistically meaningful analyses. NHTSA made the preliminary version
of the new database, which was the basis for NHTSA's 2011 preliminary
report (hereinafter 2011 Kahane report), available to the public in May
2011, and an updated version in April 2012 (used in NHTSA's 2012 final
report, hereinafter 2012 Kahane report),\298\ enabling other
researchers to analyze the same data and hopefully minimize
discrepancies in results because of inconsistencies across
databases.\299\
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\298\ Those databases are available at ftp://ftp.nhtsa.dot.gov/CAFE/.
\299\ See 75 FR 25324, 25395-25396 (May 7, 2010) (for a
discussion of planned statistical analyses).
---------------------------------------------------------------------------
Since the publication of the MYs 2017-2025 final rule, NHTSA has
sponsored, and is sponsoring, new studies and research to inform the
current CAFE and CO2 rulemaking. In addition, the National
Academy of Sciences published a new report in this area.\300\
Throughout the rulemaking process, NHTSA's goal is to publish as much
of our research as possible. In establishing standards, all available
data, studies, and information objectively without regard to whether
they were sponsored by the agencies, will be considered.
---------------------------------------------------------------------------
\300\ Cost, Effectiveness and Deployment of Fuel Economy
Technologies for Light-Duty Vehicles, National Academy of Sciences
(2015).
---------------------------------------------------------------------------
Undertaking these tasks has helped come closer to resolving ongoing
debates in statistical analysis research of historical crash data. It
is intended that these conclusions will be applied going forward in
future rulemakings, and it is believed the research will assist the
public discussion of the issues. Specific historical analyses (in
addition to NHTSA's own analysis) on vehicle mass and safety used to
support this rulemaking include:
The 2011 and 2013 NHTSA Workshops on Vehicle Mass, Size,
and Safety;
the University of Michigan Transportation Research
Institute (UMTRI) independent review of a set of statistical
relationships between vehicle curb weight, footprint variables (track
width, wheelbase), and fatality rates from vehicle crashes;
the 2012 Lawrence Berkeley National Laboratory (LBNL)
Phase 1 and Phase 2 reports on the sensitivity of NHTSA's baseline
results and casualty risk per VMT;
the 2012 DRI reports on, among other things, the effects
of mass reduction on crash frequency and fatality risk per crash;
LBNL's subsequent review of DRI's study;
the 2015 National Academy of Sciences Report; and
the 2017 NBER working paper analyzing the relationships
among traffic fatalities, CAFE standards, and distributions of MY 1989-
2005 light-duty vehicle curb weights.
A detailed discussion of each analysis is discussed in Chapter 11
of the PRIA accompanying this proposed rule.
(b) Recent NHTSA Analysis Supporting CAFE Rulemaking
As mentioned previously, NHTSA and EPA's 2012 joint final rule for
MYs 2017 and beyond set ``footprint-based'' standards, with footprint
being defined as roughly equal to the wheelbase multiplied by the
average of the front and rear track widths. Basing standards on vehicle
footprint ideally helps to discourage vehicle manufacturers from
downsizing their vehicles; the agencies set higher (more stringent)
mile per gallon (mpg) targets for smaller-footprint vehicles but would
not similarly discourage mass reduction that maintains footprint while
potentially improving fuel economy. Several technologies, such as
substitution of light, high-strength materials for conventional
materials during vehicle redesigns, have the potential to reduce weight
and conserve fuel while maintaining a vehicle's footprint and
maintaining or possibly improving the vehicle's structural strength and
handling.
In considering what technologies are available for improving fuel
economy, including mass reduction, an important corollary issue for
NHTSA to consider is the potential effect those technologies may have
on safety. NHTSA has thus far specifically considered the likely effect
of mass reduction that maintains footprint on fatal crashes. The
relationship between a vehicle's mass, size, and fatality risk is
complex, and it varies in different types of crashes. As mentioned
above, NHTSA, along with others, has been examining this relationship
for more than a decade.\301\
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\301\ A complete discussion of the historical analysis of
vehicle mass and safety is located in Chapter 10 of the PRIA
accompanying this proposed rulemaking.
---------------------------------------------------------------------------
The safety chapter of NHTSA's April 2012 final regulatory impact
analysis (FRIA) of CAFE standards for MY 2017-2021 passenger cars and
light trucks included a statistical analysis of relationships between
fatality risk, mass, and footprint in MY 2000-2007 passenger cars and
LTVs (light trucks and vans), based on calendar year (CY) 2002-2008
crash and vehicle-registration data; \302\ this analysis was also
detailed in the 2012 Kahane report.
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\302\ Kahane, C.J. Relationships Between Fatality Risk, Mass,
and Footprint in Model Year 2000-2007 Passenger Cars and LTVs--Final
Report, National Highway Traffic Safety Administration (Aug. 2012),
available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811665.
---------------------------------------------------------------------------
The principal findings and conclusions of the 2012 Kahane report
were mass reduction in the lighter cars, even while holding footprint
constant, would significantly increase fatality risk, whereas mass
reduction in the heavier LTVs would reduce societal fatality risk by
reducing the fatality risk of occupants of lighter vehicles colliding
with those heavier LTVs. NHTSA concluded, as a result, any reasonable
combination of mass reductions that held footprint constant in MY 2017-
2021 vehicles--concentrated, at least to some extent, in the heavier
LTVs and limited in the lighter cars--would likely be approximately
safety-neutral; it would not significantly increase fatalities and
might well decrease them.
NHTSA released a preliminary report (2016 Puckett and Kindelberger
report) on the relationship between fatality risk, mass, and footprint
in June 2016 in advance of the Draft TAR. The preliminary report
covered the same scope as the 2012 Kahane report, offering a detailed
description of the databases, modeling approach, and analytical results
on relationships among vehicle size, mass, and fatalities that informed
the Draft TAR. Results in the Draft TAR and the 2016 Puckett and
Kindelberger report are consistent with results in the 2012 Kahane
report; chiefly, societal effects of mass reduction are small, and mass
reduction concentrated in larger vehicles is likely to have a
beneficial effect on fatalities, while mass reduction concentrated in
smaller vehicles is likely to have a detrimental effect on fatalities.
For the 2016 Puckett and Kindelberger report and Draft TAR, NHTSA,
working closely with EPA and the DOE, performed an updated statistical
analysis of relationships between fatality rates, mass and footprint,
updating the crash and exposure databases to the latest available model
years. The agencies analyzed updated databases that included MY 2003-
2010 vehicles in CY 2005-2011 crashes. For this proposed
[[Page 43110]]
rule, databases are the most up-to-date possible (MY 2004-2011 vehicles
in CY 2006-2012), given the processing time for crash data and the need
for enough crash cases to permit statistically meaningful analyses. As
in previous analyses, NHTSA has made the new databases available to the
public on its website, enabling other researchers to analyze the same
data and hopefully minimizing discrepancies in results that would have
been because of inconsistencies across databases.
(c) Updated Analysis for This Rulemaking
The basic analytical method used to analyze the impacts of weight
reduction on safety in this proposed rule is the same as in NHTSA's
2012 Kahane report, 2016 Puckett and Kindelberger report, and the Draft
TAR: The agency analyzed cross sections of the societal fatality rate
per billion vehicle miles of travel (VMT) by mass and footprint, while
controlling for driver age, gender, and other factors, in separate
logistic regressions by vehicle class and crash type. ``Societal''
fatality rates include fatalities to occupants of all the vehicles
involved in the collisions, plus any pedestrians.
The temporal range of the data is now MY 2004-2011 vehicles in CY
2006-2012, updated from previous databases of MY 2000-2007 vehicles in
CY 2002-2008 (2012 Kahane Report) and MY 2003-2010 vehicles in CY 2005-
2011 (2016 Puckett and Kindelberger report and Draft TAR). NHTSA
purchased a file of odometer readings by make, model, and model year
from Polk that helped inform the agency's improved VMT estimates. As in
the 2012 Kahane report, 2016 Puckett and Kindelberger report, and the
Draft TAR, the vehicles are grouped into three classes: Passenger cars
(including both two-door and four-door cars); CUVs and minivans; and
truck-based LTVs.
There are nine types of crashes specified in the analysis. Single-
vehicle crashes include first-event rollovers, collisions with fixed
objects, and collisions with pedestrians, bicycles and motorcycles.
Two-vehicle crashes include collisions with: heavy-duty vehicles; car,
CUV, or minivan < 3,187 pounds (the median curb weight of other, non-
case, cars, CUVs and minivans in fatal crashes in the database); car,
CUV, or minivan >= 3,187 pounds; truck-based LTV < 4,360 pounds (the
median curb weight of other truck-based LTVs in fatal crashes in the
database); and truck-based LTV >= 4,360 pounds. An additional crash
type includes all other fatal crash types (e.g., collisions involving
more than two vehicles, animals, or trains). Splitting the ``other''
vehicles into a lighter and a heavier group permits more accurate
analyses of the mass effect in collisions of two light vehicles.
Grouping partner-vehicle CUVs and minivans with cars rather than LTVs
is more appropriate because their front-end profile and rigidity more
closely resembles a car than a typical truck-based LTV.
The curb weight of passenger cars is formulated, as in the 2012
Kahane report, 2016 Puckett and Kindelberger report, and Draft TAR, as
a two-piece linear variable to estimate one effect of mass reduction in
the lighter cars and another effect in the heavier cars. The boundary
between ``lighter'' and ``heavier'' cars is 3,201 pounds (which is the
median mass of MY 2004-2011 cars in fatal crashes in CY 2006-2012, up
from 3,106 for MY 2000-2007 cars in CY 2002-2008 in the 2012 NHTSA
safety database, and up from 3,197 for MY 2003-2010 cars in CY 2005-
2011 in the 2016 NHTSA safety database).
Likewise, for truck-based LTVs, curb weight is a two-piece linear
variable with the boundary at 5,014 pounds (again, the MY 2004-2011
median, higher than the median of 4,594 for MY 2000-2007 LTVs in CY
2002-2008 and the median of 4,947 for MY 2003-2010 LTVs in CY 2005-
2011). Curb weight is formulated as a simple linear variable for CUVs
and minivans. Historically, CUVs and minivans have accounted for a
relatively small share of new-vehicle sales over the range of the data,
resulting in less crash data available than for cars or truck-based
LTVs.
For a given vehicle class and weight range (if applicable),
regression coefficients for mass (while holding footprint constant) in
the nine types of crashes are averaged, weighted by the number of
baseline fatalities that would have occurred for the subgroup MY 2008-
2011 vehicles in CY 2008-2012 if these vehicles had all been equipped
with electronic stability control (ESC). The adjustment for ESC, a
feature of the analysis added in 2012, takes into account results will
be used to analyze effects of mass reduction in future vehicles, which
will all be ESC-equipped, as required by NHTSA's regulations.
Techniques developed in the 2011 (preliminary) and 2012 (final)
Kahane reports have been retained to test statistical significance and
to estimate 95 percent confidence bounds (sampling error) for mass
effects and to estimate the combined annual effect of removing 100
pounds of mass from every vehicle (or of removing different amounts of
mass from the various classes of vehicles), while holding footprint
constant.
NHTSA considered the near multicollinearity of mass and footprint
to be a major issue in the 2010 Kahane report \303\ and voiced concern
about inaccurately estimated regression coefficients.\304\ High
correlations between mass and footprint and variance inflation factors
(VIF) have not changed from MY 1991-1999 to MY 2004-2011; large
vehicles continued to be, on the average, heavier than small vehicles
to the same extent as in the previous decade.\305\
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\303\ Kahane, C. J. Relationships Between Fatality Risk, Mass,
and Footprint in Model Year 1991-1999 and Other Passenger Cars and
LTVs (Mar. 24, 2010), in Final Regulatory Impact Analysis: Corporate
Average Fuel Economy for MY 2012-MY 2016 Passenger Cars and Light
Trucks, National Highway Traffic Safety Administration (Mar. 2010)
at 464-542.
\304\ Van Auken and Green also discussed the issue in their
presentations at the NHTSA Workshop on Vehicle Mass-Size-Safety in
Washington, DC February 25, 2011. More information on the NHTSA
Workshop on Vehicle Mass-Size-Safety is available at https://one.nhtsa.gov/Laws-&-Regulations/CAFE-%E2%80%93-Fuel-Economy/NHTSA-Workshop-on-Vehicle-Mass%E2%80%93Size%E2%80%93Safety.
\305\ Greene, W. H. Econometric Analysis 266-68 (Macmillan
Publishing Company 2d ed. 1993); Paul D. Allison, Logistic
Regression Using the SAS System 48-51 (SAS Institute Inc. 2001). VIF
scores are in the 6-9 range for curb weight and footprint in NHTSA's
new database--i.e., in the somewhat unfavorable 2.5-10 range where
near multicollinearity begins to become a concern in logistic
regression analyses.
---------------------------------------------------------------------------
Nevertheless, multicollinearity appears to have become less of a
problem in the 2012 Kahane, 2016 Puckett and Kindelberger/Draft TAR,
and current NHTSA analyses. Ultimately, only three of the 27 core
models of fatality risk by vehicle type in the current analysis
indicate the potential presence of effects of multicollinearity, with
estimated effects of mass and footprint reduction greater than two
percent per 100-pound mass reduction and one-square-foot footprint
reduction, respectively; these three models include passenger cars and
CUVs in first-event rollovers, and CUVs in collisions with LTVs greater
than 4,360 pounds. This result is consistent with the 2016 Puckett and
Kindelberger report, which also found only three cases out of 27 models
with estimated effects of mass and footprint reduction greater than two
percent per 100-pound mass reduction and one-square-foot footprint
reduction.
Table II-45 presents the estimated percent increase in U.S.
societal fatality risk per 10 billion VMT for each 100-
[[Page 43111]]
pound reduction in vehicle mass, while holding footprint constant, for
each of the five vehicle classes:
[GRAPHIC] [TIFF OMITTED] TP24AU18.067
None of the estimated effects have 95-percent confidence bounds
that exclude zero, and thus are not statistically significant at the
95-percent confidence level. Two estimated effects are statistically
significant at the 85-percent level. Societal fatality risk is
estimated to: (1) Increase by 1.2 percent if mass is reduced by 100
pounds in the lighter cars; and (2) decrease by 0.61 percent if mass is
reduced by 100 pounds in the heavier truck-based LTVs. The estimated
increases in societal fatality risk for mass reduction in the heavier
cars and the lighter truck-based LTVs, and the estimated decrease in
societal fatality risk for mass reduction in CUVs and minivans are not
significant, even at the 85-percent confidence level.
Confidence bounds estimate only the sampling error internal to the
data used in the specific analysis that generated the point estimate.
Point estimates are also sensitive to the modification of components of
the analysis, as discussed at the end of this section. However, this
degree of uncertainty is methodological in nature rather than
statistical.
It is useful to compare the new results in Table II-45 to results
in the 2012 Kahane report (MY 2000-2007 vehicles in CY 2002-2008) and
the 2016 Puckett and Kindelberger report and Draft TAR (MY 2003-2010
vehicles in CY 2005-2011), presented in Table II-46 below:
---------------------------------------------------------------------------
\306\ Median curb weights in the 2012 Kahane report: 3,106
pounds for cars, 4,594 pounds for truck-based LTVs. Median curb
weights in the 2016 Puckett and Kindelberger report: 3,197 pounds
for cars, 4,947 pounds for truck-based LTVs.
[GRAPHIC] [TIFF OMITTED] TP24AU18.068
New results are directionally the same as in 2012; in the 2016
analysis, the estimate for lighter LTVs was of opposite sign (but small
magnitude). Consistent with the 2012 Kahane and 2016 Puckett and
Kindelberger reports, mass reductions in lighter cars are estimated to
lead to increases in fatalities, and mass reductions in heavier LTVs
are estimated to lead to decreases in fatalities. However, NHTSA does
not consider this conclusion to be definitive because of the relatively
wide confidence bounds of the estimates. The estimated mass effects are
similar among analyses for both classes of passenger cars; for all
reports, the estimate for lighter passenger cars is statistically
significant at the 85-percent confidence level, while the estimate for
heavier passenger cars is insignificant.
The estimated mass effect for heavier truck-based LTVs is stronger
in this analysis and in the 2016 Puckett and Kindelberger report than
in the 2012 Kahane report; both estimates are statistically significant
at the 85-percent confidence level, unlike the corresponding
insignificant estimate in the 2012 Kahane report. The estimated mass
effect for lighter truck-based LTVs is insignificant and positive in
this analysis and the 2012 Kahane report, while the corresponding
estimate in the 2016 Puckett and Kindelberger report was insignificant
and negative.
Vehicle mass continued an historical upward trend across the MYs in
the newest databases. The average (VMT-weighted) masses of passenger
cars and CUVs both increased by approximately three percent from MYs
2004 to 2011 (3,184 pounds to 3,289 pounds for passenger cars, and
3,821 pounds to 3,924 pounds for CUVs). Over the same period, the
average mass of minivans increased by six percent (from 4,204 pounds to
4,462 pounds), and the average mass of LTVs increased by 10% (from
4,819 pounds to 5,311 pounds).
[[Page 43112]]
Historical reasons for mass increases within vehicle classes include:
Manufacturers discontinuing lighter models; manufacturers re-designing
models to be heavier and larger; and shifting consumer preferences with
respect to cabin size and overall vehicle size.
The principal difference between heavier vehicles, especially
truck-based LTVs, and lighter vehicles, especially passenger cars, is
mass reduction has a different effect in collisions with another car or
LTV. When two vehicles of unequal mass collide, the change in velocity
(delta V) is greater in the lighter vehicle. Through conservation of
momentum, the degree to which the delta V in the lighter vehicle is
greater than in the heavier vehicle is proportional to the ratio of
mass in the heavier vehicle to mass in the lighter vehicle:
[GRAPHIC] [TIFF OMITTED] TP24AU18.069
Because fatality risk is a positive function of delta V, the
fatality risk in the lighter vehicle in two-vehicle collisions is also
higher. Removing some mass from the heavy vehicle reduces delta V in
the lighter vehicle, where fatality risk is higher, resulting in a
large benefit, offset by a small penalty because delta V increases in
the heavy vehicle where fatality risk is low--adding up to a net
societal benefit. Removing some mass from the lighter vehicle results
in a large penalty offset by a small benefit--adding up to net harm.
These considerations drive the overall result: Mass reduction is
associated with an increase in fatality risk in lighter cars, a
decrease in fatality risk in heavier LTVs, CUVs, and minivans, and has
smaller effects in the intermediate groups. Mass reduction may also be
harmful in a crash with a movable object such as a small tree, which
may break if hit by a high mass vehicle resulting in a lower delta V
than may occur if hit by a lower mass vehicle which does not break the
tree and therefore has a higher delta V. However, in some types of
crashes not involving collisions between cars and LTVs, especially
first-event rollovers and impacts with fixed objects, mass reduction
may not be harmful and may be beneficial. To the extent lighter
vehicles may respond more quickly to braking and steering, or may be
more stable because their center of gravity is lower, they may more
successfully avoid crashes or reduce the severity of crashes.
Farmer, Green, and Lie, who reviewed the 2010 Kahane report, again
peer-reviewed the 2011 Kahane report.\307\ In preparing his 2012 report
(along with the 2016 Puckett and Kindelberger report and Draft TAR),
Kahane also took into account Wenzel's \308\ assessment of the
preliminary report and its peer reviews, DRI's analyses published early
in 2012, and public comments such as the International Council on Clean
Transportation's comments submitted on NHTSA and EPA's 2010 notice of
joint rulemaking.\309\ These comments prompted supplementary analyses,
especially sensitivity tests, discussed at the end of this section.
---------------------------------------------------------------------------
\307\ Items 0035 (Lie), 0036 (Farmer) and 0037 (Green) in Docket
No. NHTSA-2010-0152.
\308\ Wenzel, T. An Analysis of the Relationship Between
Casualty Risk Per Crash and Vehicle Mass and Footprint for Model
Year 2000-2007 Light Duty Vehicles, Lawrence Berkeley National
Laboratory (Dec. 2011), available at http://eta-publications.lbl.gov/sites/default/files/lbnl-5695e.pdf; Tom Wenzel,
Lawrence Berkeley National Laboratory -Assessment of NHTSA Report
Relationships Btw Fatality Risk Mass and Footprint in MY 2000-2007
PC and LTV,'' Docket NHTSA-2010-0131-0315; and a peer review of
Wenzel's reports--Peer Review of LBNL Statistical Analysis of the
Effect of Vehicle Mass & Footprint Reduction on Safety (LBNL Phase 1
and 2 Reports), prepared for U.S. EPA (Feb. 2012), available at
Docket ID NHTSA-2010-0131-0328.
\309\ Comment by International Council on Clean Transportation,
Docket ID NHTSA-2010-0131-0258.
---------------------------------------------------------------------------
The regression results are best suited to predict the effect of a
small change in mass, leaving all other factors, including footprint,
the same. With each additional change from the current environment
(e.g., the scale of mass change, presence and prevalence of safety
features, demographic characteristics), the model may become less
accurate. It is recognized that the light-duty vehicle fleet in the MY
2021-2026 timeframe will be different from the MY 20042011 fleet
analyzed here.
Nevertheless, one consideration provides some basis for confidence
in applying regression results to estimate effects of relatively large
mass reductions or mass reductions over longer periods. This is NHTSA's
sixth evaluation of effects of mass reduction and/or downsizing,\310\
comprising
[[Page 43113]]
databases ranging from MYs 1985 to 2011.
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\310\ As outlined throughout this section, NHTSA's six related
studies include the new analysis supporting this rulemaking, and:
Kahane, C. J. Vehicle Weight, Fatality Risk and Crash Compatibility
of Model Year 1991-99 Passenger Cars and Light Trucks, National
Highway Traffic Safety Administration (Oct. 2003), available at
https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/809662;
Kahane, C. J. Relationships Between Fatality Risk, Mass, and
Footprint in Model Year 1991-1999 and Other Passenger Cars and LTVs
(Mar. 24, 2010), in Final Regulatory Impact Analysis: Corporate
Average Fuel Economy for MY 2012-MY 2016 Passenger Cars and Light
Trucks, National Highway Traffic Safety Administration (Mar. 2010)
at 464-542; Kahane, C. J. Relationships Between Fatality Risk, Mass,
and Footprint in Model Year 2000-2007 Passenger Cars and LTVs--
Preliminary Report, National Highway Traffic Safety Administration
(Nov. 2011), available at Docket ID NHTSA-2010-0152- 0023); Kahane,
C. J. Relationships Between Fatality Risk, Mass, and Footprint in
Model Year 2000-2007 Passenger Cars and LTVs: Final Report, NHTSA
Technical Report. Washington, DC: NHTSA, Report No. DOT-HS-811-665;
and Puckett, S. M., & Kindelberger, J. C. Relationships between
Fatality Risk, Mass, and Footprint in Model Year 2003-2010 Passenger
Cars and LTVs--Preliminary Report, National Highway Traffic Safety
Administration (June 2016), available at https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/2016-prelim-relationship-fatalityrisk-mass-footprint-2003-10.pdf.
---------------------------------------------------------------------------
Results of the six studies are not identical, but they have been
consistent to a point. During this time period, many makes and models
have increased substantially in mass, sometimes as much as 30-40%.\311\
If the statistical analysis has, over the past years, been able to
accommodate mass increases of this magnitude, perhaps it will also
succeed in modeling effects of mass reductions of approximately 10-20%,
should they occur in the future.
---------------------------------------------------------------------------
\311\ For example, one of the most popular models of small 4-
door sedans increased in curb weight from 1,939 pounds in MY 1985 to
2,766 pounds in MY 2007, a 43% increase. A high-sales mid-size sedan
grew from 2,385 to 3,354 pounds (41%); a best-selling pickup truck
from 3,390 to 4,742 pounds (40%) in the basic model with two-door
cab and rear-wheel drive; and a popular minivan from 2,940 to 3,862
pounds (31%).
---------------------------------------------------------------------------
(d) Calculation of MY 2021-2026 Safety Impact
Neither CAFE standards nor this analysis mandate mass reduction, or
mandate mass reduction occur in any specific manner. However, mass
reduction is one of the technology applications available to
manufacturers, and thus a degree of mass reduction is allowed within
the CAFE model to: (1) Determine capabilities of manufacturers; and (2)
to predict cost and fuel consumption effects of improved CAFE
standards.
The agency utilized the relationships between weight and safety
from the new NHTSA analysis, expressed as percentage increases in
fatalities per 100-pound weight reduction, and examined the weight
impacts assumed in this CAFE analysis. The effects of mass reduction on
safety were estimated relative to estimated baseline levels of safety
across vehicle classes and model years. To identify baseline levels of
safety, the agency examined effects of identifiable safety trends over
lifetimes of vehicles produced in each model year. The projected
effectiveness of existing and forthcoming safety technologies and
expected on-road fleet penetration of safety technologies were
incorporated into observed trends in fatality rates to estimate
baseline fatality rates in future years across vehicle classes and
model years.
The agency assumed safety trends will result in a reduction in the
target population of fatalities from which the vehicle mass impacts are
derived. Table II-47 through Table II-52 show results of NHTSA's
vehicle mass-size-safety analysis over the cumulative lifetime of MY
1977-2029 vehicles, for both the CAFE and GHG programs, based on the MY
2016 baseline fleet, accounting for the projected safety baselines. The
reported fatality impacts are undiscounted, but the monetized safety
impacts are discounted at three-percent and seven-percent discount
rates. The reported fatality impacts are estimated increases or
decreases in fatalities over the lifetime of the model year fleet. A
positive number means that fatalities are projected to increase; a
negative number (in parentheses) means that fatalities are projected to
decrease.
Results are driven extensively by the degree to which mass is
reduced in relatively light passenger cars and in relatively heavy
vehicles because their coefficients in the logistic regression analysis
have the most significant values. We assume any impact on fatalities
will occur over the lifetime of the vehicle, and the chance of a
fatality occurring in any particular year is directly related to the
weighted vehicle miles traveled in that year.
[[Page 43114]]
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[[Page 43119]]
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For all light-duty vehicles, mass changes are estimated to lead to
a decrease in fatalities over the cumulative lifetime of MY 1977-2029
vehicles in all alternatives evaluated. The effects of mass changes on
fatalities
[[Page 43120]]
range from a combined decrease (relative to the augural standards, the
baseline) of 12 fatalities for Alternative #7 to a combined decrease of
173 fatalities for Alternative #4. The difference in results by
alternative depends upon how much weight reduction is used in that
alternative and the types and sizes of vehicles to which the weight
reduction applies. The decreases in fatalities are driven by impacts
within passenger cars (decreases of between 17 and 281 fatalities) and
are offset by impacts within light trucks (increases of between 6 and
120 fatalities).
Additionally, social effects of increasing fatalities can be
monetized using NHTSA's estimated comprehensive cost per life of
$9,900,000 in 2016 dollars. This consists of a value of a statistical
life of $9.6 million in 2015 dollars plus external economic costs
associated with fatalities such as medical care, insurance
administration costs and legal costs, updated for inflation to 2016
dollars.
Typically, NHTSA would also estimate the effect on injuries and add
that to social costs of fatalities, but in this case NHTSA does not
have a model estimating the effect of vehicle mass on injuries. Blincoe
et al. estimates that fatalities account for 39.5% of total
comprehensive costs due to injury.\312\ If vehicle mass impacts non-
fatal injuries proportionally to its impact on fatalities, then total
costs would be approximately 2.53 (\1/0\.395) times the value of
fatalities alone or around $25.07 million per fatality. NHTSA has
selected this value as representative of the relationship between
fatality costs and injury costs because this approach is internally
consistent among NHTSA studies.
---------------------------------------------------------------------------
\312\ Blincoe, L. et al., The Economic and Social Impact of
Motor Vehicle Crashes, 2010 (Revised), National Highway Traffic
Safety Administration (May 2015), available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812013. The
estimate of 39.5% (see Table 1-8) is equal to the estimated value of
MAIS6 (fatal) injuries in vehicle incidents divided by the estimated
value of MAIS0-MAIS6 (non-fatal and fatal) injuries in vehicle
incidents.
---------------------------------------------------------------------------
Changes in vehicle mass are estimated to decrease social safety
costs over the lifetime of the nine model years by between $176 million
(for Alternative #7) and $2.7 billion (for Alternative #4) relative to
the augural standards at a three-percent discount rate and by between
$97 million and $1.6 billion at a seven-percent discount rate. The
estimated decreases in social safety costs are driven by estimated
decreases in costs associated with passenger cars, ranging from $264
million (for Alternative #7) to $4.4 billion (for Alternative #1)
relative to the Augural standards at a three-percent discount rate and
by between $146 million and $2.5 billion at a seven-percent discount
rate. The estimated decreases in costs associated with passenger cars
are offset by estimated increases in costs associated with light
trucks, ranging from $88 million (for Alternative #7) to $2.0 billion
(for Alternative #1) relative to the Augural standards at a three-
percent discount rate and by between $49 million and $1.3 billion at a
seven-percent discount rate.
Table II-53 through Table II-55 presents average annual estimated
safety effects of vehicle mass changes, for CYs 2035-2045:
[[Page 43121]]
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For all light-duty vehicles, mass changes are estimated to lead to
an average annual decrease in fatalities in all alternatives evaluated
for CYs 2035-2045. The effects of mass changes on fatalities range from
a combined
[[Page 43127]]
decrease (relative to the Augural standards) of 1 fatality per year for
Alternative #7 to a combined increase of 22 fatalities per year for
Alternative #1. The difference in the results by alternative depends
upon how much weight reduction is used in that alternative and the
types and sizes of vehicles to which the weight reduction applies. The
decreases in fatalities are generally driven by impacts within
passenger cars (decreases of between 1 and 33 fatalities per year
relative to the Augural standards) and are generally offset by impacts
within light trucks (increases of between 1 and 12 fatalities per
year).
Changes in vehicle mass are estimated to decrease average annual
social safety costs in CY 2035-2045 by between $2 million (for
Alternative #7) and $271 million (for Alternative #1) relative to the
Augural standards at a three-percent discount rate and by between $1
million and $111 million at a seven-percent discount rate. The
estimated decreases in social safety costs are generally driven by
estimated decreases in costs associated with passenger cars, decreasing
between $13 million (for Alternative #7) and $424 million (for
Alternative #1) relative to the Augural standards at a three-percent
discount rate and decreasing between $5 million and $175 million at a
seven-percent discount rate. The estimated decreases in costs
associated with passenger cars are generally offset by estimated
increases in costs associated with light trucks, decreasing between $11
million (for Alternative #7) and $153 million (for Alternative #1)
relative to the Augural standards at a three-percent discount rate and
decreasing between $5 million and $64 million at a seven-percent
discount rate.
To help illuminate effects at the model year level, Table II-59
presents the lifetime fatality impacts associated with vehicle mass
changes for passenger cars, light trucks, and all light-duty vehicles
by model year under Alternative #1, relative to the Augural standards
for the CAFE Program. Table II-59 presents an analogous table for the
GHG Program.
[[Page 43128]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.082
Under Alternative #1, passenger car fatalities associated with mass
changes are estimated to decrease generally from MY 2017 (decrease of
three fatalities) through MY 2029 (decrease of 36 fatalities), peaking
in MY 2025 (37 fatalities). Corresponding estimates of light truck
fatalities associated with mass changes are generally positive, ranging
from a decrease of one fatality in MYs 2017 and 2018 to an increase of
14 fatalities in MYs 2026 through 2029. Altogether, light-duty vehicle
fatality reductions associated with mass changes under Alternative #1
are
[[Page 43129]]
estimated to be concentrated among MY 2023 through MY 2029 vehicles
(146 out of 165, or 91% of net fatalities mitigated).
Table II-61 and Table II-62 present estimates of monetized lifetime
social safety costs associated with mass changes by model year at
three-percent and seven-percent discount rates, respectively for the
CAFE Program. Table II-63 and Table II-64 show comparable tables from
the perspective of the GHG Program.
[[Page 43130]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.083
[[Page 43131]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.084
Lifetime social safety costs are estimated to decrease generally by
model year, with decreases associated with passenger cars generally
offset partially by increases associated with light trucks. At a three-
percent discount
[[Page 43132]]
rate, decreases in lifetime social safety costs related to passenger
cars are estimated to range from $13 million for existing (MY 1977
through MY 2016) cars, to $230 million for MY 2025 cars. The
corresponding estimates at a seven-percent discount rate range from $7
million to $136 million. At a three-percent discount rate, impacts on
lifetime social safety costs related to light trucks are estimated to
range from a decrease of $5 million for MY 2017 light trucks to an
increase of $96 million for MY 2022 light trucks. The corresponding
estimates at a seven-percent discount rate range from $3 million to $65
million.
Consistent with the analysis of fatality impacts by model year in
Table II-61, decreases in lifetime social safety costs associated with
mass changes are generally concentrated in MY 2023 through MY 2029
light-duty vehicles under Alternative #1. At a three-percent discount
rate, 93% of the reduction in total lifetime costs ($872 million out of
$937 million) is attributed to MY 2023 through MY 2029 light-duty
vehicles; at a seven-percent discount rate, 97% of the reduction in
total lifetime costs ($486 million out of $501 million) is attributed
to MY 2023 through MY 2029 light-duty vehicles.
(e) Sensitivity Analyses
Table II-65 shows the principal findings and includes sampling-
error confidence bounds for the five parameters used in the CAFE model.
The confidence bounds represent the statistical uncertainty that is a
consequence of having less than a census of data. NHTSA's 2011, 2012,
and 2016 reports acknowledged another source of uncertainty: The
baseline statistical model can be varied by choosing different control
variables or redefining the vehicle classes or crash types, which for
example, could produce different point estimates.
Beginning with the 2012 Kahane report, NHTSA has provided results
of 11 plausible alternative models that serve as sensitivity tests of
the baseline model. Each alternative model was tested or proposed by:
Farmer (IIHS) or Green (UMTRI) in their peer reviews; Van Auken (DRI)
in his public comments; or Wenzel in his parallel research for DOE. The
2012 Kahane and 2016 Puckett and Kindelberger reports provide further
discussion of the models and the rationales behind them.
Alternative models use NHTSA's databases and regression-analysis
approach but differ from the baseline model in one or more explanatory
variables, assumptions, or data restrictions. NHTSA applied the 11
techniques to the latest databases to generate alternative CAFE model
coefficients. The range of estimates produced by the sensitivity tests
offers insight to the uncertainty inherent in the formulation of the
models, subject to the caveat these 11 tests are, of course, not an
exhaustive list of conceivable alternatives.
The baseline and alternative results follow, ordered from the
lowest to the highest estimated increase in societal risk per 100-pound
reduction for cars weighing less than 3,201 pounds:
[GRAPHIC] [TIFF OMITTED] TP24AU18.085
[[Page 43133]]
The sensitivity tests illustrate both the fragility and the
robustness of baseline estimates. On the one hand, the variation among
NHTSA's coefficients is quite large relative to the baseline estimate:
In the preceding example of cars < 3,201 pounds, the estimated
coefficients range from almost zero to almost double the baseline
estimate. This result underscores the key relationship that the
societal effect of mass reduction is small and, as Wenzel has said, it
``is overwhelmed by other known vehicle, driver, and crash factors.''
\313\ In other words, varying how to model some of these other vehicle,
driver, and crash factors, which is exactly what sensitivity tests do,
can appreciably change the estimate of the societal effect of mass
reduction.
---------------------------------------------------------------------------
\313\ Wenzel, T. Assessment of NHTSA's Report ``Relationships
Between Fatality Risk, Mass, and Footprint in Model Year 2000-2007
Passenger Cars and LTVs,'' Lawrence Berkeley National Laboratory at
iv (Nov. 2011), available at Docket ID NHTSA-2010-0152-0026.
---------------------------------------------------------------------------
On the other hand, variations are not particularly large in
absolute terms. The ranges of alternative estimates are generally in
line with the sampling-error confidence bounds for the baseline
estimates. Generally, in alternative models as in the baseline models,
mass reduction tends to be relatively more harmful in the lighter
vehicles and more beneficial in the heavier vehicles, just as they are
in the central analysis. In all models, the point estimate of NHTSA's
coefficient is positive for the lightest vehicle class, cars < 3,201
pounds. In nine out of 11 models, the point estimate is negative for
CUVs and minivans, and in eight out of 11 models the point estimate is
negative for LTVs >= 5,014 pounds.
(f) Fleet Simulation Model
NHTSA has traditionally used real world crash data as the basis for
projecting the future safety implications for regulatory changes.
However, because lightweight vehicle designs are introducing
fundamental changes to the structure of the vehicle, there is some
concern that historical safety trends may not apply. To address this
concern, NHTSA developed an approach to utilize lightweight vehicle
designs to evaluate safety in a subset of real-world representative
crashes. The methodology focused on frontal crashes because of the
availability of existing vehicle and occupant restraint models.
Representative crashes were simulated between baseline and lightweight
vehicles against a range of vehicles and roadside objects using two
different size belted driver occupants (adult male and small female)
only. No passenger(s) or unbelted driver occupants were considered in
this fleet simulation. The occupant injury risk from each simulation
was calculated and summed to obtain combined occupant injury risk. The
combined occupant injury risk was weighted according to the frequency
of real world occurrences to develop overall societal risk for baseline
and light-weighted vehicles. Note: The generic restraint system
developed and used in the baseline occupant simulations was also used
in the light-weighted vehicle occupant simulations as the purpose of
this fleet simulation was to understand changes in societal injury
risks because of mass reduction for different classes of vehicles in
frontal crashes. No modifications to the restraint systems were made
for light-weighted vehicle occupant simulations. Any modifications to
restraint systems to improve occupant injury risks or societal injury
risks in the light-weighted vehicle would have conflated results
without identifying effects of mass reduction only. The following
sections provide an overview of the fleet simulation study:
NHTSA contracted with George Washington University to develop a
fleet simulation model \314\ to study the impact and relationship of
light-weighted vehicle design with injuries and fatalities. In this
study, there were eight vehicles as follows:
---------------------------------------------------------------------------
\314\ Samaha, R. R. et al., Methodology for Evaluating Fleet
Protection of New Vehicle Designs: Application to Lightweight
Vehicle Designs, National Highway Traffic Safety Administration
(Aug. 2014), available at https://www.nhtsa.gov/crashworthiness/vehicle-aggressivity-and-fleet-compatibility-research (accessed by
clicking on the .zip file for DOT HS 812 051).
---------------------------------------------------------------------------
2001 model year Ford Taurus finite element model baseline
and two simple design variants included a 25% lighter vehicle while
maintaining the same vehicle front end stiffness and 25% overall
stiffer vehicle while maintaining the same overall vehicle mass.\315\
---------------------------------------------------------------------------
\315\ Samaha, R. R. et al., Methodology for Evaluating Fleet
Protection of New Vehicle Designs: Application to Lightweight
Vehicle Designs, appendices, National Highway Traffic Safety
Administration (Aug. 2014), available at https://www.nhtsa.gov/crashworthiness/vehicle-aggressivity-and-fleet-compatibility-research (accessed by clicking on the .zip file for DOT HS 812 051
[appendices are Part 2]).
---------------------------------------------------------------------------
2011 model year Honda Accord finite element baseline
vehicle and its 20% light-weight vehicle designed by Electricore. (This
mass reduction study was sponsored by NHTSA).\316\
---------------------------------------------------------------------------
\316\ Singh, H. et al., Update to future midsize lightweight
vehicle findings in response to manufacturer review and IIHS small-
overlap testing, National Highway Traffic Safety Administration
(Feb. 2016), available at https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/812237_lightweightvehiclereport.pdf.
---------------------------------------------------------------------------
2009/2010 model year Toyota Venza finite element baseline
vehicle and two design variants included a 20% light-weight vehicle
model (2010 Venza) (Low option mass reduction vehicle funded by EPA and
International Council on Clean Transportation (ICCT)) and a 35% light-
weight vehicle (2009 Venza) (High option mass reduction vehicle funded
by California Air Resources Board).\317\
---------------------------------------------------------------------------
\317\ Light-Duty Vehicle Mass Reduction and Cost Analysis --
Midsize Crossover Utility Vehicle, U.S. EPA (Aug. 2012), https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryID=230748.
---------------------------------------------------------------------------
Light weight vehicles were designed to have similar vehicle crash
pulses as baseline vehicles. More than 440 vehicle crash simulations
were conducted for the range of crash speeds and crash configurations
to generate crash pulse and intrusion data points. The crash pulse data
and intrusion data points will be used as inputs in the occupant
simulation models.
For vehicle to vehicle impact simulations, four finite element
models were chosen to represent the fleet. The partner vehicle models
were selected to represent a range of vehicle types and weights. It was
assumed vehicle models would reflect the crash response for all
vehicles of the same type, e.g. mid-size car. Only the safety or injury
risk for the driver in the target vehicle and in the partner vehicle
were evaluated in this study.
As noted, vehicle simulations generated vehicle deformations and
acceleration responses utilized to drive occupant restraint simulations
and predict the risk of injury to the head, neck, chest, and lower
extremities. In all, more than 1,520 occupant restraint simulations
were conducted to evaluate the risk of injury for mid-size male and
small female drivers.
The computed societal injury risk (SIR) for a target vehicle v in
frontal crashes is an aggregate of individual serious crash injury
risks weighted by real-world frequency of occurrence (v) of a frontal
crash incident. A crash incident corresponds to a crash with different
partners (Npartner) at a given impact speed (Pspeed), for a given
driver occupant size (Loccsize), in the target or partner vehicle (T/
P), in a given crash configuration (Mconfig), and in a single- or two-
vehicle crash (Kevent). CIR (v) represents the combined injury risk (by
body region) in a single crash incident. (v) designates the weighting
factor, i.e., percent of occurrence, derived from National Automotive
Sampling System Crashworthiness Data System (NASS CDS) for the crash
incident. A driver age group of 16 to 50
[[Page 43134]]
years old was chosen to provide a population with a similar, i.e., more
consistent, injury tolerance.
The fleet simulation was performed using the best available
engineering models, with base vehicle restraint and airbag settings, to
estimate societal risks of future lightweight vehicles. The range of
the predicted risks for the baseline vehicles is from 1.25% to 1.56%,
with an average of 1.39%, for the NASS frontal crashes that were
simulated. The change in driver injury risk between the baseline and
light-weighted vehicles will provide insight into the estimate of
modification needed in the restraint and airbag systems of lightweight
vehicles. If the difference extends beyond the expected baseline
vehicle restraint and airbag capability, then adjustments to the
structural designs would be needed. Results from the fleet simulation
study show the trend of increased societal injury risk for light-
weighted vehicle designs, as compared to their baselines, occurs for
both single vehicle and two-vehicle crashes. Results are listed in
Table II-66.
In general, the societal injury risk in the frontal crash
simulation associated with the small size driver is elevated when
compared to that of the mid-size driver. However, both occupant sizes
had reasonable injury risk in the simulated impact configurations
representative of the regulatory and consumer information testing.
NHTSA examined three methods for combining injuries with different body
regions. One observation was the baseline mid-size CUV model was more
sensitive to leg injuries.
[GRAPHIC] [TIFF OMITTED] TP24AU18.086
This study only looked at lightweight designs for a midsize sedan
and a mid-size CUV and did not examine safety implications for heavier
vehicles. The study was also limited to only frontal crash
configurations and considered just mid-size CUVs whereas the
statistical regression model considered all CUVs and all crash modes.
The change in the safety risk from the MY 2010 fleet simulation
study was directionally consistent with results for passenger cars from
NHTSA 2012 regression analysis study,\318\ which covered data for MY
2000-MY 2007. The NHTSA 2012 regression analysis study was updated in
2016 to reflect newer MY 2003 to MY 2010. Comparing the fleet
simulation societal risk to the 2016 update of the NHTSA 2012
regression analysis and the updated analysis used in this NPRM, the
risk assessment from the fleet simulation is similarly directionally
consistent with the passenger car risk assessment from the regression
analysis. As noted, fleet simulations were performed only in frontal
crash mode and did not consider other crash modes including rollover
crashes.\319\
---------------------------------------------------------------------------
\318\ The 2012 Kahane study considered only fatalities, whereas,
the fleet simulation study considered severe (AIS 3+) injuries and
fatalities (DOT HS 811 665).
\319\ The risk assessment for CUV in the regression model
combined CUVs and minivans in all crash modes and included belted
and unbelted occupants.
---------------------------------------------------------------------------
This fleet simulation study does not provide information that can
be used to modify coefficients derived for the NPRM regression analysis
because of the restricted types of crashes \320\ and vehicle designs.
As explained earlier, the fleet simulation study assumed restraint
equipment to be as in the baseline model, in which restraints/airbags
are not redesigned to be optimal with light-weighting.
---------------------------------------------------------------------------
\320\ The fleet simulation considered only frontal crashes.
---------------------------------------------------------------------------
2. Impact of Vehicle Scrappage and Sales Response on Fatalities
Previous versions of the CAFE model, and the accompanying
regulatory analyses relying on it, did not carry a representation of
the full on-road vehicle population, only those vehicles from model
years regulated under proposed (or final) standards. The omission of an
on-road fleet implicitly assumed the population of vehicles registered
at the time a set of CAFE standards is promulgated is not affected by
those standards. However, there are several mechanisms by which CAFE
standards can affect the existing vehicle
[[Page 43135]]
population. The most significant of these is deferred retirement of
older vehicles. CAFE standards force manufacturers to apply fuel saving
technologies to offered vehicles and then pass along the cost of those
technologies (to the extent possible) to buyers of new vehicles. These
price increases affect the length of loan terms and the desired length
of ownership for new vehicle buyers and can discourage some buyers on
the margin from buying a new vehicle in a given year. To the extent new
vehicle purchases offset pending vehicle retirements, delaying new
purchases in favor of continuing to use an aging vehicle affects the
overall safety of the on-road fleet even if the vehicle whose
retirement was delayed was not directly subject to a binding CAFE
standard in the model year during its production.
The sales response in the CAFE model acts to modify new vehicle
sales in two ways:
1. Changes in new vehicle prices either increase or decrease total
sales (passenger cars and light trucks combined) each year in the
context of forecasted macroeconomic conditions.
2. Changes in new vehicle attributes and fuel prices influence the
share of new vehicles sold that are light trucks, and therefore also
passenger cars.
These two responses change the total number of new vehicles sold in
each model year across regulatory alternatives and the relative
proportion of new vehicles that are passenger cars and light trucks.
This response has two effects on safety. The first response slows the
rate at which new vehicles, and their associated safety improvements,
enter the on-road population. The second response influences the mix of
vehicles on the road--with more stringent CAFE standards leading to a
higher share of light trucks sold in the new vehicle market, assuming
all else is equal. Light trucks have higher rates of fatal crashes when
interacting with passenger cars and, as earlier sections discussed,
different directional responses to mass reduction technology based on
the existing mass and body style of the vehicle.
The sales response and scrappage response influence safety outcomes
through the same basic mechanism, fleet turnover. In the case of the
scrappage response, delaying fleet turnover keeps drivers in older
vehicles likely to be less safe than newer model year vehicles that
could replace them. Similarly, delaying the sale of new vehicles can
force households to keep older vehicles in use longer, reallocate VMT
within their household fleet, and generally meet travel demand through
the use of older, less safe vehicles. As an illustration, if we
simplify by ignoring that the share of new vehicles that are passenger
cars changes with the stringency of the alternatives, simply changing
the number of new vehicles between scenarios affects the mileage
accumulation of the fleet and therefore all fleet level effects.
Reducing the number of new vehicles sold, relative to a baseline
forecasted value, reduces the size of the registered vehicle fleet that
is able to service the underlying demand for travel.
Consider a simple example where we show sales effects operating on
a micro-scale for a single household whose choices of whether to
purchase a new vehicle is affected by vehicle price. A household starts
with three vehicles, aged three, five, and eight years old. In a
scenario with no CAFE standards and therefore no related changes in
vehicle sales prices, the household buys a new car and scraps the
eight-year old car; the other two cars in the fleet each get a year
older. In a scenario where CAFE standards become more stringent causing
vehicle sales prices to increase, this household chooses to delay
buying a new car and each of their three existing cars gets a year
older. In both cases, all three vehicles (including the new car in the
first scenario, and the year-year-old car in the second scenario) have
to serve the family's travel demand.
The scrappage effect is visible in the household's vehicle fleet as
it moves from the first scenario to the second scenario with changes in
CAFE standards. In the second scenario, the nine-year-old car remains
in the household's fleet to service demand for travel, when it would
otherwise have been retired. While the scrappage effect can be
symmetrical to the sales effect, it need not be. The ``new car'' in the
scenario without CAFE standards could be a new vehicle from the current
model year or a used car that is of a newer vintage than the 8-year-old
vehicle it replaces. The latter instance is an effect of scrappage
decisions that do not directly affect new vehicle sales. Eventually,
new vehicles transition to the used car market, but that on average
take several years, and the shift is slow. At the household level, the
scrappage decision occurs in a single year, each year, for every
vehicle in the fleet. To the extent CAFE standards affect new vehicle
prices and fuel economies, relative to vehicles already owned,
scrappage could accelerate or decelerate depending upon the direction
(and magnitude) of the changes.
3. Safety Model
The analysis supporting the CAFE rule for MYs 2017 and beyond did
not account for differences in exposure or inherent safety risk as
vehicles aged throughout their useful lives. However, the relationship
between vehicle age and fatality risk is an important one. In a 2013
Research Note,\321\ NHTSA's National Center for Statistics and Analysis
concluded a driver of a vehicle that is four to seven years old is 10%
more likely to be killed in a crash than the driver of a vehicle zero
to three years old, accounting for the other factors related to the
crash. This trend continued for older vehicles more generally, with a
driver of a vehicle 18 years or older being 71% more likely to be
killed in a crash than a driver in a new vehicle. While there are more
registered vehicles that are zero to three years old than there are 20
years or older (nearly three times as many) because most of the
vehicles in earlier vintages are retired sooner, the average age of
vehicles in the United States is 11.6 years old and has risen
significantly in the past decade.\322\ This relationship reflects a
general trend visible in the Fatality Analysis Reporting System (FARS)
when looking at a series of calendar years: Newer vintages are safer
than older vintages, over time, at each age. This is likely because of
advancements in safety technology, like side-impact airbags, electronic
stability control, and (more recently) sophisticated crash avoidance
systems starting to work their way into the vehicle population. In
fact, the 2013 Research Note indicated that the percentage of occupants
fatally injured in fatal crashes increased with vehicle age: From 27%
for vehicles three or fewer years old, to 41% for vehicles 12-14 years
old, to 50% for vehicles 18 or more years old.
---------------------------------------------------------------------------
\321\ National Center for Statistics and Analysis, How Vehicle
Age and Model Year Relate to Driver Injury Severity in Fatal
Crashes, National Highway Traffic Safety Administration (Aug. 2013),
available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811825.
\322\ Based on data acquired from Ward's Automotive.
---------------------------------------------------------------------------
With an integrated fleet model now part of the analytical framework
for CAFE analysis, any effects on fleet turnover (either from delayed
vehicle retirement or deferred sales of new vehicles) will affect the
distribution of both ages and model years present in the on-road fleet.
Because each of these vintages carries with it inherent rates of fatal
crashes, and newer vintages are generally safer than older ones,
changing that distribution will change
[[Page 43136]]
the total number of on-road fatalities under each regulatory
alternative.
To estimate the empirical relationship between vehicle age, model
year vintage, and fatalities, DOT conducted a statistical analysis
linking data from the FARS database, a time series of Polk registration
data to represent the on-road vehicle population, and assumed per-
vehicle mileage accumulation rates (the derivation of which is
discussed in detail in PRIA Chapter 11). These data were used to
construct per-mile fatality rates that varied by vehicle vintage,
accounting for the influence of vehicle age. However, unlike the NCSA
study referenced above, any attempt to account for this relationship in
the CAFE analysis faces two challenges. The first challenge is the CAFE
model lacks the internal structure to account for other factors related
to observed fatal crashes--for example, vehicle speed, seat belt use,
drug use, or age of involved drivers or passengers. Vehicle
interactions are simply not modeled at this level; the safety analysis
in the CAFE model is statistical, using aggregate values to represent
the totality of fleet interactions over time. The second challenge is
perhaps the more significant of the two: The CAFE analysis is
inherently forward-looking. To implement a statistical model analogous
to the one developed by NCSA, the CAFE model would require forecasts of
all factors considered in the NCSA model--about vehicle speeds in
crashes, driver behavior, driver and passenger ages, vehicle vintages,
and so on. In particular, the model would require distributions (joint
distributions, in most cases) of these factors over a period of time
spanning decades. Any such forecasts would be highly uncertain and
would be likely to assume a continuation of current conditions.
Instead of trying to replicate the NCSA work at a similar level of
detail, DOT conducted a simpler statistical analysis to separate the
safety impact of the two factors the CAFE model explicitly accounts
for: The distribution of vehicle ages in the fleet and the number of
miles driven by those vehicles at each age. To accomplish this, DOT
used data from the FARS database at a lower level of resolution; rather
than looking at each crash and the specific factors that contributed to
its occurrence, staff looked at the total number of fatal crashes
involving light-duty vehicles over time with a focus on the influence
of vehicle age and vehicle vintage. When considering the number of
fatalities relative to the number of registered vehicles for a given
model year (without regard to the passenger car/light-truck
distinction, which has evolved over time and can create inconsistent
comparisons), a somewhat noisy pattern develops. Using data from
calendar year 1996 through 2015, some consistent stories develop. The
points in Figure II-4 represent the number of fatalities per registered
vehicle with darker circles associated with increasingly current
calendar years.
[GRAPHIC] [TIFF OMITTED] TP24AU18.087
As shown in Figure II-4, fatalities per registered vehicle have
generally declined over time across all vehicle ages (the darker points
representing newer vintages being closer to the x-axis) and, across
most recent calendar years, fatality rates (per registered vehicle)
start out at a low point, rise through age 15 or so, then decline
through age 30 (at which point little of the initial model year cohort
is still registered). While this pattern is evident in the registration
data, it is magnified by imposing a mileage accumulation schedule on
the registered population and examining fatalities per billion miles of
VMT.
The mileage accumulation schedule used in this analysis was
developed using odometer readings of vehicles aged 0-15 years in
calendar year 2015.
[[Page 43137]]
The years spanned by the FARS database cover all model years from
calendar year 1996 through 2015. Given that there is a significant
number of years between the older vehicles in the 1996 CY data and the
most recent model years in the odometer data the informed the mileage
accumulation schedules, staff applied an elasticity of -0.20 to the
change in the average cost per mile of vehicles over their lives. While
the older vehicles had lower fuel economies, which would be associated
with higher per-mile driving costs, they also (mostly) faced lower fuel
prices. This adjustment increased the mileage accumulation for older
vehicles, but not by large amounts. Because the CAFE model uses the
mileage accumulation schedule and applies it to all vehicles in the
fleet, it is necessary to use the same schedule to estimate per-mile
fatality rates in the statistical analysis--even if the schedule is
based on vehicles that look different than the oldest vehicles in the
FARS dataset.
When the per-vehicle fatality rates are converted into per-mile
fatality rates, the pattern observed in the registration comparison
becomes clearer. As Figure II-5 shows, the trend present in the
fatality data on a per-registration basis is even clearer on a per-mile
basis: Newer vintages are safer than older vintages, at each age, over
time.
[GRAPHIC] [TIFF OMITTED] TP24AU18.088
The shape of the curve in Figure II-5 suggests a polynomial
relationship between fatality rate and vehicle age, so DOT's
statistical model is based on that structure.
The final model is a weighted quartic polynomial regression (by
number of registered vehicles) on vehicle age with fixed effects for
the model years present in the dataset: \323\
---------------------------------------------------------------------------
\323\ Note: The dataset included MY 1975, but that fixed effect
is excluded from the set. The constant term acts as the fixed effect
for 1975 and all others are relative to that one.
[GRAPHIC] [TIFF OMITTED] TP24AU18.089
The coefficient estimates and model summary are in Table II-67.
[[Page 43138]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.090
[[Page 43139]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.091
This function is now embedded in the CAFE model, so the combination
of VMT per vehicle and the distribution of ages and model years present
in the on-road fleet determine the number of fatalities in a given
calendar year. The model reproduces the observed fatalities of a given
model year, at each age, reasonably well with more recent model years
(to which the VMT schedule is a better match) estimated with smaller
errors.
While the final specification was not the only one considered, the
fact this model was intended to live inside the CAFE model to
dynamically estimate fatalities for a dynamically changing on-road
vehicle population was a constraining factor.
(a) Predicting Future Safety Trends
The base model predicts a net increase in fatalities due primarily
to slower adoption of safer vehicles and added driving because of less
costly vehicle operating costs. In earlier calendar years, the
improvement in safety of the on-road fleet produces a net reduction in
fatalities, but from the mid-2020s forward, the baseline model predicts
no further increase in safety, and the added risk from more VMT and
older vehicles produces a net increase in fatalities. This model thus
reflects a conservative limitation; it implicitly assumes the trend
toward increasingly safe vehicles that has been apparent for the past 3
decades will flatten in mid-2020s. The agency does not assert this is
the most likely case. In fact, the development of advanced crash
avoidance technologies in recent years indicates some level of safety
improvement is almost certain to occur. The difficulty is for most of
these technologies, their effectiveness against fatalities and the pace
of their adoption are highly uncertain. Moreover, autonomous vehicles
offer the possibility of significantly reducing or eventually even
eliminating the effect of human error in crash causation, a
contributing factor in roughly 94% of all crashes. This conservative
assumption may cause the NPRM to understate the beneficial effect of
proposed standards on improving (reducing) the number of fatalities.
Advanced technologies that are currently deployed or in development
include:
Forward Collision Warning (FCW) systems are intended to passively
assist the driver in avoiding or mitigating the impact of rear-end
collisions (i.e., a vehicle striking the rear portion of a vehicle
traveling in the same direction directly in front of it). FCW uses
forward-looking vehicle detection capability, such as RADAR, LIDAR
(laser), camera, etc., to detect other vehicles ahead and use the
information from these sensors to warn the driver and to prevent
crashes. FCW systems provide an audible, visual, or haptic warning, or
any combination thereof, to alert the driver of an FCW-equipped vehicle
of a potential collision with another vehicle or vehicles in the
anticipated forward pathway of the vehicle.
Crash Imminent Braking (CIB) systems are intended to actively
assist the driver by mitigating the impact of rear-end collisions.
These safety systems have forward-looking vehicle detection capability
provided by sensing technologies such as RADAR, LIDAR, video camera,
etc. CIB systems mitigate crash severity by automatically applying the
vehicle's brakes shortly before the expected impact (i.e., without
requiring the driver to apply force to the brake pedal).
Dynamic Brake Support (DBS) is a technology that actively increases
the amount of braking provided to the driver during a rear-end crash
avoidance maneuver. If the driver has applied force to the brake pedal,
DBS uses forward-looking sensor data provided by technologies such as
RADAR, LIDAR, video cameras, etc. to assess the potential for a rear-
end crash. Should DBS ascertain a crash is likely (i.e., the sensor
data indicate the driver has not applied enough braking to avoid the
crash), DBS automatically intervenes. Although the manner in which DBS
has been implemented differs among vehicle manufacturers, the objective
of the interventions is largely the same: To supplement the driver's
commanded brake input by increasing the output of the foundation brake
system. In some situations, the increased braking provided by DBS may
allow the driver to avoid a crash. In other cases, DBS interventions
mitigate crash severity.
Pedestrian AEB (PAEB) systems provide automatic braking for
vehicles when pedestrians are in the forward path of travel and the
driver has taken insufficient action to avoid an imminent crash. Like
CIB, PAEB safety systems use information from forward-looking sensors
to automatically apply or supplement the brakes in certain driving
[[Page 43140]]
situations in which the system determines a pedestrian is in imminent
danger of being hit by the vehicle. Many PAEB systems use the same
sensors and technologies used by CIB and DBS.
Rear Automatic Braking feature means installed vehicle equipment
that has the ability to sense the presence of objects behind a
reversing vehicle, alert the driver of the presence of the object(s)
via auditory and visual alerts, and automatically engage the available
braking system(s) to stop the vehicle.
Semi-automatic Headlamp Beam Switching device provides either
automatic or manual control of headlamp beam switching at the option of
the driver. When the control is automatic, headlamps switch from the
upper beam to the lower beam when illuminated by headlamps on an
approaching vehicle and switch back to the upper beam when the road
ahead is dark. When the control is manual, the driver may obtain either
beam manually regardless of the conditions ahead of the vehicle.
Rear Turn Signal Lamp Color Turn signal lamps are the signaling
element of a turn signal system, which indicates the intention to turn
or change direction by giving a flashing light on the side toward which
the turn will be made. FMVSS No. 108 permits a rear turn signal lamp
color of amber or red.
Lane Departure Warning (LDW) system is a driver assistance system
that monitors lane markings on the road and alerts the driver when
their vehicle is about to drift beyond a delineated edge line of their
current travel lane.
Blind Spot Detection (BSD) systems uses digital camera imaging
technology or radar sensor technology to detect one or more vehicles in
either of the adjacent lanes that may not be apparent to the driver.
The system warns the driver of an approaching vehicle's presence to
help facilitate safe lane changes.
These technologies are either under development or are currently
being offered, typically in luxury vehicles, as either optional or
standard equipment.
To estimate baseline fatality rates in future years, NHTSA examined
predicted results from a previous NCSA study \324\ that measured the
effect of known safety regulations on fatality rates. This study relied
on statistical evaluations of the effectiveness of motor vehicle safety
technologies based on real world performance in the on-road vehicle
fleet to determine the effectiveness of each safety technology. These
effectiveness rates were applied to existing fatality target
populations and adjusted for current technology penetration in the on-
road fleet, taking into account the retirement of existing vehicles and
the pace of future penetration required to meet statutory compliance
requirements, as well as adjustments for overlapping target
populations. Based on these factors, as well as assumptions regarding
future VMT, the study predicted future fatality levels and rates.
Because the safety impact in the CAFE model independently predicts
future VMT, we removed the VMT growth rate from the NCSA study and
developed a prediction of vehicle fatality trends based only on the
penetration pace of new safety technologies into the on-road fleet.
These data were then normalized into relative safety factors with CY
2015 as the baseline (to match the baseline fatality year used in this
CAFE analysis). These factors were then converted into equivalent
fatality rates/100 million VMT by anchoring them to the 2015 fatality
rate/100 million VMT published by NHTSA. Figure II-6 below illustrates
the modelling output and projected fatality trend from the analysis of
the NCSA study, prior to adjustment to fatality rates/100 million VMT.
---------------------------------------------------------------------------
\324\ Blincoe, L. & Shankar, U. The Impact of Safety Standards
and Behavioral Trends on Motor Vehicle Fatality Rates, National
Highway Traffic Safety Administration (Jan. 2007), available at
https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/810777v3.pdf.
[GRAPHIC] [TIFF OMITTED] TP24AU18.092
[[Page 43141]]
This model was based on inputs representing the impact of
technology improvement through CY 2020. Projecting this trend beyond
2020 can be justified based on the continued transformation of the on-
road fleet to 100% inclusion of the known safety technologies. Based on
projections in the NCSA study, significant further technology
penetration can be expected in the on-road fleet for side impact
improvements (FMVSSS 214), electronic stability control (FMVSS 126),
upper interior head impact protection (FMVSS 301), tire pressure
monitoring systems (FMVSS 138), ejection mitigation (FMVSS 226), and
heavy truck stopping distance improvements (FMVSS 121). These
technologies were estimated to be installed in only 40-70% of the on-
road fleet as of CY 2020, implying further safety improvement well
beyond the 2020 calendar year.
The NCSA study focused on projections to reflect known technology
adaptation requirements, but it was conducted prior to the 2008
recession, which disrupted the economy and changed travel patterns
throughout the country. Thus, while the relative trends it predicts
seem reasonable, they cannot account for the real-world disruption and
recovery that occurred in the 2008-2015 timeframe. In addition, the
NCSA study did not attempt to adjust for safety impacts that may have
resulted from changes in the vehicle sales mix (vehicle types and sizes
creating different interactions in crashes), in commuting patterns, or
in shopping or socializing habits associated with internet access and
use. To address this, NHTSA also examined the actual change in the
fatality rate as measured by fatality counts and VMT estimates. Figure
II-7 below illustrates the actual fatality rates measured from 2000
through 2016 and the modeled fatality rate trend based on these
historical data.
[GRAPHIC] [TIFF OMITTED] TP24AU18.093
The effect of the recession and subsequent recovery can be seen in
chaotic shift in the fatality rate trend starting in 2008. The
generally gradual decline that had been occurring over the previous
decade was interrupted by a slowdown in the rate of change followed by
subsequent upward and downward shifts. More recently, the rate has
begun to increase. These shifts reflect some combination of factors not
captured in the NCSA analysis mentioned above. The significance of this
is that although there was a steady increase in the penetration of
safety technologies into the on-road fleet between 2008 and 2015, other
unknown factors offset their positive influence and eventually reversed
the trend in vehicle safety rates. Because of the upward shift over the
2014-2015 period, this model, which does not reflect technology trend
savings after 2015, will predict an upward shift of fatality rates
after 2020.
Predicting future safety trends has significant uncertainty.
Although further safety improvements are expected because of advanced
safety technologies such as automatic braking and eventually, fully
automated vehicles, the pace of development and extent of consumer
acceptance of these improvements is uncertain. Thus, two imperfect
models exist for predicting future safety trends. The NCSA model
reflects the expected trend from required technologies and indicates
continued improvement well beyond the 2020 timeframe, which is when the
historical fatality rate based model breaks down. By contrast, the
historical fatality rate model reflects shifts in safety not captured
by the NCSA model, but gives arguably implausible results after 2020.
It essentially represents a scenario in which economic, market, or
behavioral factors minimize or offset much of the potential impact of
future safety technology.
For the NPRM, the analysis examines a scenario projecting safety
improvements beyond 2015 using a simple average of the NCSA and
historical fatality rate models, accepting each as an illustration of
different and conflicting possible future scenarios. As
[[Page 43142]]
both models eventually curve up because of their quadratic form, each
models' results are flattened at the point where they begin to trend
upward. This occurs in 2045 for the NCSA model and in 2021 for the
historical model. The results are shown in Figure II-8 below. The
results indicate roughly a 19% reduction in fatality rates between 2015
and 2050. This is a slower pace than what has historically occurred
over the past several decades, but the biggest influence on historical
rates was significant improvement in safety belt use, which was below
10% in 1960 and had risen to roughly 70% by 2000, and is now more than
90%. Because belt use is now above 90%, further such improvements are
unlikely unless they come from new technologies.
[GRAPHIC] [TIFF OMITTED] TP24AU18.094
A difficulty with these trend models is they are based on calendar
year predictions, which are derived from the full on-road vehicle fleet
rather than the model year fleet, which is the basis for calculations
in the CAFE model. As such they are useful primarily as indicators that
vehicle safety has steadily improved over the past several decades, and
given the advanced safety technologies under current development, we
would expect some continuation of improvement in MY vehicle safety over
the near and mid-term future. To account for this, NHTSA approximated a
model year safety trend continuing through about 2035 (Figure II-9).
For this trend the agency used actual data from FARS to calculate the
change in fatality rates through 2007. The recession, which struck our
economy in 2008, distorted normal behavioral patterns and affected both
VMT and the mix of drivers and type of driving to an extent we do not
believe the recession era gives an accurate picture of the safety
trends inherent in the vehicles themselves. Therefore, beginning in
2008, NHTSA approximated a trend for safety improvement through about
MY 2035 to reflect the continued effect of improved safety technologies
such as advanced automatic braking, which manufacturers have announced
will be in all new vehicles by MY 2022. The agency recognize this is
only an estimate, and actual MY trends could be above or below this
line. NHTSA examined alternate trends in a sensitivity analysis and
request comments on the best way to address future safety trends.
NHTSA also notes although we project vehicles will continue to
become safer going forward to about 2035, we do not have corresponding
cost information for technologies enabling this improvement. In a
standard elasticity model, sales impacts are a function of the percent
change in vehicle price. Hypothetically, increasing the base price for
added safety technologies would decrease the impact of higher prices
due to impacts of CAFE standards on vehicle sales. The percentage
change in baseline price would decrease, which would mean a lower
elasticity effect, which would mean a lower impact on sales. NHTSA will
consider possible ways to address this issue before the final rule, and
we request comments on the need and/or practicability for such an
adjustment, as well as any data and other relevant information that
could support such an analysis of these costs, as well as the future
pace of technological adoption within the vehicle fleet.
[[Page 43143]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.095
(b) Adjusting for Behavioral Impacts
The influence of delayed purchases of new vehicles is estimated to
have the most significant effect on safety imposed by CAFE standards.
Because of a combination of safety regulations and voluntary safety
improvements, passenger vehicles have become safer over time. Compared
to prior decades, fatality rates have declined significantly because of
technological improvements, as well as behavioral shifts, such as
increased seat belt use. As these safer vehicles replace older less
safe vehicles in the fleet, the on-road fleet is replaced with vehicles
reflecting the improved fatality rates of newer, safer vehicles.
However, fatality rates associated with different model year vehicles
are influenced by the vehicle itself and by driver behavior. Over time,
used vehicles are purchased by drivers in different demographic
circumstances who also tend to have different behavioral
characteristics. Drivers of older vehicles, on average, tend to have
lower belt use rates, are more likely to drive inebriated, and are more
likely to drive over the speed limit. Additionally, older vehicles are
more likely to be driven on rural roadways, which typically have higher
speeds and produce more serious crashes. These relationships are
illustrated graphically in Chapter 11 of the PRIA accompanying this
proposed rule.
The behavior being modelled and ascribed to CAFE involves decisions
by drivers who are contemplating buying a new vehicle, and the purchase
of a newer vehicle will not in itself cause those drivers to suddenly
stop wearing seat belts, speed, drive under the influence, or shift
driving to different land use areas. The goal of this analysis is to
measure the effect of different vehicle designs that change by model
year. The modelling process for estimating safety essentially involves
substituting fatality rates of older MY vehicles for improved rates
that would have been experienced with a newer vehicle. Therefore, it is
important to control for behavioral aspects associated with vehicle age
so only vehicle design differences are reflected in the estimate of
safety impacts. To address this, the CAFE safety model was run to
control for vehicle age. That is, it does not reflect a decision to
replace an older model year vehicle that is, for example, 10 years old
with a new vehicle. Rather, it reflects the difference in the average
fatality rate of each model year across its entire lifespan. This will
account for most of the difference because of vehicle age, but it may
still reflect a bias caused by the upward trend in societal seat belt
use over time. Because of this secular trend, each subsequent model
year's useful life will occur under increasingly higher average seat
belt use rates. This could cause some level of behavioral safety
improvement to be ascribed to the model year instead of the driver
cohort. However, it is difficult to separate this effect from the belt
use impacts of changing driver cohorts as vehicles age.
Glassbrenner (2012) analyzed the effect of improved safety in newer
vehicles for model years 2001 through 2008. She developed several
statistical regression models that specifically controlled for most
behavioral factors to isolate model year vehicle characteristics.
However, her study did not specifically report the change in MY
fatality rates--rather, she reported total fatalities that could have
been saved in a baseline year (2008) had all vehicles in the on-road
fleet had the same safety features as the MY 2001 through MY 2008
vehicles. This study potentially provides a basis for comparison with
results of the CAFE safety estimates. To make this comparison, the CY
2008 passenger car and light truck fatalities total from FARS were
modified by subtracting the values found in Figure II-9 of her study.
This gives a stream of comparable hypothetical CY 2008 fatality totals
under progressively less safe model year designs. Results indicated
that had the 2008 on-road fleet been equipped with MY 2008 safety
equipment and vehicle characteristics, total fatalities would have been
reduced by 25% compared to vehicles that were actually on the road in
2008. Similar results were calculated for each model years' vehicle
characteristics back to 2001.
For comparison, predicted MY fatality rates were derived from the
CAFE safety model and applied to the CY 2008 VMT calculated by that
model. This gives an estimate of CY 2008 fatalities under each model
years' fatality rate, which, when compared to the predicted CY fatality
total, gives a trendline
[[Page 43144]]
comparable to the Glassbrenner trendline illustrating the change in MY
fatality rates. Both models are sensitive to the initial 2008 baseline
fatality total, and because the predicted CAFE total is somewhat lower
than the actual total, the agency ran a third trendline to examine the
influence of this difference. Results are shown in Figure II-10.
Using the corrected fatality count, but retaining the predicted VMT
changes the initial 2018 CY fatality rate to 12.62 (instead of 12.15)
and produces the result shown in Figure II-10. The CAFE model trendline
shifts up, which narrows the difference in early years but expands it
in later years. However, VMT and fatalities are linked in the CAFE
model, so the actual level of the MY safety predicted by the CAFE curve
has uncertainty. Perhaps the most meaningful result from this
comparison is the difference in slopes; the CAFE model predicts more
rapid change through 2006, but in the last few years change decreases.
This might reflect the trend in societal belt use, which rose steadily
through 2005 and levelled off. Later model years' fatality rates would
benefit from this trend while earlier model years would suffer. This
seems consistent with our using lifetime MY fatality rates to reflect
MY change rather than first year MY fatality rates (although even first
year rates would reflect this bias, but not as much).
[GRAPHIC] [TIFF OMITTED] TP24AU18.096
To provide another perspective on safety impacts, NHTSA accessed
data from a comprehensive study of the effects of safety technologies
on motor vehicle fatalities. Kahane (2015) \325\ examined all safety
effects of vehicle safety technologies from 1960 through 2012 and found
these technologies saved more than 600,000 lives during that time span.
Kahane is currently working under contract for NHTSA to update this
study through 2016. At NHTSA's request, Kahane accessed his database to
provide a measure of relative MY vehicle design safety by controlling
for seat belt use. The result was a MY safety index illustrating the
progress in vehicle safety by model year which isolates vehicle design
from the primary behavioral impact--seat belt usage. We normalized
Kahane's index to MY 1975 and did the same to the ``fixed effects'' we
are currently using from our safety model to compare the trends in MY
safety from the two methods. Results are shown in Figure II-11.
---------------------------------------------------------------------------
\325\ Kahane, C.J. Lives Saved by Safety Standards and
Associated Vehicle Safety Technologies, 1960-2012--Passenger Cars
and LTVs--with Reviews of 26 FMVSS and the Effectiveness of their
Associated Safety Technologies in Reducing Fatalities, Injuries, and
Crashes, National Highway Traffic Safety Administration (Jan. 2015),
available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812069.
---------------------------------------------------------------------------
[[Page 43145]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.097
From Figure II-11 both approaches show similar long-term downward
trends, but this model shows a steeper slope than Kahane's model. The
two models involve completely different approaches, so some difference
is to be expected. However, it is also possible this reflects different
methods used to isolate vehicle design safety from behavioral impacts.
As discussed previously, NHTSA addressed this issue by removing vehicle
age impacts from its model, whereas Kahane's model does it by
controlling for belt use. As noted previously, aside from the age
impact on belt use associated with the different demographics driving
older vehicles, there is a secular trend toward more belt use
reflecting the increase in societal awareness of belt use importance
over time. This trend is illustrated in Figure II-12 below.\326\
NHTSA's current approach removes the age trend in belt use, but it's
not clear whether it accounts for the full impacts of the secular trend
as well. If not, some portion of the gap between the two trendlines
could reflect behavioral impacts rather than vehicle design.
---------------------------------------------------------------------------
\326\ Note: The drop occurring in 1994 reflects a shift in the
basis for determining belt use rates. Effective in 1994, data were
reported from the National Occupant Protection Survey (NOPUS). Prior
to this, a conglomeration of state studies provided the basis. It is
likely the pre-NOPUS surveys produced inflated results, especially
in the 1991-1993 period.
---------------------------------------------------------------------------
These models (NHTSA, Glassbrenner, and Kahane) involve differing
approaches and assumptions contributing to uncertainty, and given this,
their differences are not surprising. It is encouraging they show
similar directional trends, reinforcing the basic concept we are
measuring. NHTSA recognizes predicting future fatality impacts, as well
as sales impacts that cause them, is a difficult and imprecise task.
NHTSA will continue to investigate this issue, and we seek comment on
these estimates as well as alternate methods for predicting the safety
effects associated with delayed new vehicle purchases.
[[Page 43146]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.098
4. Impact of Rebound Effect on Fatalities
Based on historical data, it is possible to calculate a baseline
fatality rate for vehicles of any model year vintage. By simply taking
the total number of vehicles involved in fatal accidents over all ages
for a model year and dividing by the cumulative VMT over the useful
life of every vehicle produced in that model year, one arrives at a
baseline hazard rate denominated in fatalities per billion miles. The
fatalities associated with vehicles produced in that model year are
then proportional to the cumulative lifetime VMT, where total
fatalities equal the product of the baseline hazard rate and VMT. A
more comprehensive discussion of the rebound effect and the basis for
calculating its impact on mileage and risk is in Chapter 8 of the PRIA
accompanying this proposed rule.
5. Adjustment for Non-Fatal Crashes
Fatalities estimated to be caused by various alternative CAFE
standards are valued as a societal cost within the CAFE models' cost/
benefit accounting. Their value is based on the comprehensive value of
a fatality derived from data in Blincoe et al. (2015), adjusted to 2016
economics and updated to reflect the official DOT guidance on the value
of a statistical life in 2016. This gives a societal value of $9.9
million for each fatality. The CAFE safety model estimates effects on
traffic fatalities but does not address corresponding effects on non-
fatal injuries and property damage that would result from the same
factors influencing fatalities. To address this, we developed an
adjustment factor that would account for these crashes.
Development of this factor is based on the assumption nonfatal
crashes will be affected by CAFE standards in proportion to their
nationwide incidence and severity. That is, NHTSA assumes the same
injury profile, the relative number of cases of each injury severity
level, that occur nationwide, will be increased or decreased because of
CAFE. The agency recognizes this may not be the case, but the agency
does not have data to support individual estimates across injury
severities. There are reasons why this may not be true. For example,
because older model year vehicles are generally less safe than newer
vehicles, fatalities may make up a larger portion of the total injury
picture than they do for newer vehicles. This would imply lower ratios
across the non-fatal injury and PDO profile and would imply our
adjustment may overstate total societal impacts. NHTSA requests
comments on this assumption and alternative methods to estimate injury
impacts.
The adjustment factor is derived from Tables 1-8 and I-3 in Blincoe
et al. (2015). Incidence in Table I-3 reflects the Abbreviated Injury
Scale (AIS), which ranks nonfatal injury severity based on an ascending
5 level scale with the most severe injuries ranked as level 5. More
information on the basis for these classifications is available from
the Association for the Advancement of Automotive Medicine at https://www.aaam.org/abbreviated-injury-scale-ais/.
Table 1-3 in Blincoe lists injured persons with their highest
(maximum) injury determining the AIS level (MAIS). This scale is
represented in terms of MAIS level, or maximum abbreviated injury
scale. MAIS0 refers to uninjured occupants in injury vehicles, MAIS1
are generally considered minor injuries, MAIS2 moderate injuries, MAIS3
serious injuries, MAIS4 severe injuries, and MAIS5 critical injuries.
PDO refers to property damage only crashes, and counts for PDOs refer
to vehicles in which no one was injured. From Table II-68, ratios of
injury incidence/fatality are derived for each injury severity level as
follows:
[[Page 43147]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.099
For each fatality that occurs nationwide in traffic crashes, there
are 561 vehicles involved in PDOs, 139 uninjured occupants in injury
vehicles, 105 minor injuries, 10 moderate injuries, 3 serious injuries,
and fractional numbers of the most serious categories which include
severe and critical nonfatal injuries. For each fatality ascribed to
CAFE it is assumed there will be nonfatal crashes in these same ratios.
Property damage costs associated with delayed new vehicle purchases
must be treated differently because crashes that subsequently occur
damage older used vehicles instead of newer vehicles. Used vehicles are
worth less and will cost less to repair, if they are repaired at all.
The consumer's property damage loss is thus reduced by longer retention
of these vehicles. To estimate this loss, average new and used vehicle
prices were compared. New vehicle transaction prices were estimated
from a study published by Kelley Blue Book.\327\ Based on these data,
the average new vehicle transaction price in January 2017 was $34,968.
Used vehicle transaction prices were obtained from Edmonds Used Vehicle
Market Report published in February of 2017.\328\ Edmonds data indicate
the average used vehicle transaction price was $19,189 in 2016. There
is a minor timing discrepancy in these data because the new vehicle
data represent January 2017, and the used vehicle price is for the
average over 2016. NHTSA was unable to locate exact matching data at
this time, but the agency believes the difference will be minor.
---------------------------------------------------------------------------
\327\ Press Release, Kelley Blue Book, New-Car Transaction
Prices Remain High, Up More Than 3 Percent Year-Over-Year in January
2017, According to Kelley Blue Book (Feb. 1, 2017), https://mediaroom.kbb.com/2017-02-01-New-Car-Transaction-Prices-Remain-High-Up-More-Than-3-Percent-Year-Over-Year-In-January-2017-According-To-Kelley-Blue-Book.
\328\ Edmunds Used Vehicle Market Report, Edmunds (Feb. 2017),
https://dealers.edmunds.com/static/assets/articles/2017_Feb_Used_Market_Report.pdf.
---------------------------------------------------------------------------
Based on these data, new vehicles are on average worth 82% more
than used vehicles. To estimate the effect of higher property damage
costs for newer vehicles on crashes, the per unit property damage costs
from Table I-9 in Blincoe et al. (2015) were multiplied by this factor.
Results are illustrated in Table II-69.
[GRAPHIC] [TIFF OMITTED] TP24AU18.100
The total property damage cost reduction was then calculated as a
function of the number of fatalities reduced or increased by CAFE as
follows:
[GRAPHIC] [TIFF OMITTED] TP24AU18.145
Where:
S = total property damage savings from retaining used vehicles
longer
F = change in fatalities estimated for CAFE due to retaining used
vehicles
r = ratio of nonfatal injuries or PDO vehicles to fatalities (F)
p = value of property damage prevented by retaining older vehicle
[[Page 43148]]
n = the 8 injury severity categories
The number of fatalities ascribed to CAFE because of older vehicle
retention was multiplied by the unit cost per fatality from Table I-9
in Blincoe et al. (2015) to determine the societal impact accounted for
by these fatalities.\329\ From Table I-8 in Blincoe et al. (2015),
NHTSA subtracted property damage costs from all injury severity levels
and recalculated the total comprehensive value of societal losses from
crashes. The agency then divided the portion of these crashes because
of fatalities by the resulting total to estimate the portion of crashes
excluding property damage that are accounted for by fatalities. Results
indicate fatalities accounted for approximately 40% of all societal
costs exclusive of property damage. NHTSA then divided the total cost
of the added fatalities by 0.4 to estimate the total cost of all
crashes prevented exclusive of the savings in property damage. After
subtracting the total savings in property damage from this value, we
divided the fatality cost by it to estimate that overall, fatalities
account for 43% of the total costs that would result from older vehicle
retention.
---------------------------------------------------------------------------
\329\ Note: These calculations used the original values in the
Blincoe et all (2015) tables without adjusting for economics. These
calculations produce ratios and are thus not sensitive to
adjustments for inflation.
---------------------------------------------------------------------------
For the fatalities that occur because of mass effects or to the
rebound effect, the calculation was more direct, a simple application
of the ratio of the portion of costs produced by fatalities. In this
case, there is no need to adjust for property damage because all
impacts were derived from the mix of vehicles in the on-road fleet.
Again, from Table I-8 in Blincoe et al (2015), we derive this ratio
based on all cost factors including property damage to be .36. These
calculations are summarized as follows:
[GRAPHIC] [TIFF OMITTED] TP24AU18.101
Where:
SV = Value of societal Impacts of all crashes
F = change in fatalities estimated for CAFE due to retaining used
vehicles
v = Comprehensive societal value of preventing 1 fatality
x = Percent of total societal loss from crashes excluding property
damage accounted for by fatalities
S = total property damage savings from retaining used vehicles
longer
M = change in fatalities due to changes in vehicle mass to meet CAFE
standards
c = Percent of total societal loss from all cost factors in all
crashes accounted for by fatalities
For purposes of application in the CAFE model, these two factors
were combined based on the relative contribution to total fatalities of
different factors. As noted, although a safety impact from the rebound
effect is calculated, these impacts are considered to be freely chosen
rather than imposed by CAFE and imply personal benefits at least equal
to the sum of their added costs and safety consequences. The impacts of
this nonfatal crash adjustment affect costs and benefits equally. When
considering safety impacts actually imposed by CAFE standards, only
those from mass changes and vehicle purchase delays are considered.
NHTSA has two different factors depending on which metric is
considered. The agency created these factors by weighting components by
the relative contribution to changes in fatalities associated with each
component. This process and results are shown in Table II-70. Note: For
the NPRM, NHTSA applied the average weighted factor to all fatalities.
This will tend to slightly overstate costs because of sales and
scrappage and understate costs associated with mass and rebound. The
agency will consider ways to adjust this minor discrepancy for the
final rule.
[GRAPHIC] [TIFF OMITTED] TP24AU18.102
Table II-71, Table II-72, Table II-73, and Table II-74 summarize
the safety effects of CAFE standards across the various alternatives
under the 3% and 7% discount rates. As noted in Section II.F.5,
societal impacts are valued using a $9.9 million value per statistical
life (VSL). Fatalities in these tables are undiscounted; only the
monetized societal impact is discounted.
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[[Page 43151]]
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[[Page 43153]]
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Table II-75 through Table II-78 summarize the safety effects of GHG
standards across the various alternatives under the 3% and 7% discount
rates. As noted in Section II.F.5, societal impacts are valued using a
$9.9 million value per statistical life (VSL). Fatalities in these
tables are undiscounted; only the monetized societal impact is
discounted.
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While NHTSA notes the value of rebound effect fatalities, as well
as total fatalities from all causes, the agency does not add rebound
effects to the other CAFE-related impacts because rebound-related
fatalities and injuries result from risk that is freely chosen and
offset by societal valuations that at a minimum exceed the aggregate
value of safety consequences plus added vehicle operating and
maintenance costs.\330\ These costs implicitly involve a cost and a
benefit that are offsetting. The relevant safety impacts attributable
to CAFE are highlighted in bold in the above tables.
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\330\ It would also include some level of consumer surplus,
which we have estimated using the standard triangular function. This
is discussed in Chapter 8.5.1 of the PRIA.
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G. How the Model Analyzes Different Potential CAFE and CO2 Standards
1. Specification of No-Action and Other Regulatory Alternatives
(a) Mathematical Functions Defining Passenger Car and Light Trucks
Standards for Each Model Year During 2016-2032
In the U.S. market, the stringency of CAFE and CO2
standards can influence the design of new vehicles offered for sale by
requiring manufacturers to produce increasingly fuel efficient vehicles
in order to meet program
[[Page 43159]]
requirements. This is also true in the CAFE model simulation, where the
standards can be defined with a great deal of flexibility to examine
the impact of different program specifications on the auto industry.
Standards are defined for each model year and can represent different
slopes that relate fuel economy to footprint, different regions of flat
slopes, and different rates of increase for each of three regulatory
classes covered by the CAFE program (domestic passenger cars, imported
passenger cars, and light trucks).
The CAFE model takes, as inputs, the coefficients of the
mathematical functions described in Sections III and IV. It uses these
coefficients and the function to which they belong to define the target
for each vehicle in the fleet, then computes the standard using the
harmonic average of the targets for each manufacturer and fleet. The
model also allows the user to define the extent and duration of various
compliance flexibilities (e.g., limits on the amount of credit that a
manufacturer may claim related to air conditioning efficiency
improvements or off-cycle fuel economy adjustments) as well as limits
on the number of years that CAFE credits may be carried forward or the
amount that may be transferred between a manufacturer's fleets.
(b) Off-Cycle and A/C Efficiency Adjustments Anticipated for Each Model
Year
Another aspect of credit accounting is partially implemented in the
CAFE model at this point--those related to the application of off-cycle
and A/C efficiency adjustments, which manufacturers earn by taking
actions such as special window glazing or using reflective paints that
provide fuel economy improvements in real-world operation but do not
produce measurable improvements in fuel consumption on the 2-cycle
test.
NHTSA's inclusion of off-cycle and A/C efficiency adjustments began
in MY 2017, while EPA has collected several years' worth of submissions
from manufacturers about off-cycle and A/C efficiency technology
deployment. Currently, the level of deployment can vary considerably by
manufacturer with several claiming extensive Fuel Consumption
Improvement Values (FCIV) for off-cycle and A/C efficiency technologies
and others almost none. The analysis of alternatives presented here
does not attempt to project how future off-cycle and A/C efficiency
technology use will evolve or speculate about the potential
proliferation of FCIV proposals submitted to the agencies. Rather, this
analysis uses the off-cycle credits submitted by each manufacturer for
MY 2017 compliance and carries these forward to future years with a few
exceptions. Several of the technologies described in Section II.D are
associated with A/C efficiency and off-cycle FCIVs. In particular,
stop-start systems, integrated starter generators, and full hybrids are
assumed to generate off-cycle adjustments when applied to vehicles to
improve their fuel economy. Similarly, higher levels of aerodynamic
improvements are assumed to include active grille shutters on the
vehicle, which also qualify for off-cycle FCIVs.
The analysis assumes that any off-cycle FCIVs that are associated
with actions outside of the technologies discussed in Section II.D
(either chosen from the pre-approved ``pick list,'' or granted in
response to individual manufacturer petitions) remain at the levels
claimed by manufacturers in MY 2017. Any additional A/C efficiency and
off-cycle adjustments that accrue as the result of explicit technology
application are calculated dynamically in each model year for each
alternative. The off-cycle FCIVs for each manufacturer and fleet,
denominated in grams CO2 per mile,\331\ are provided in
Table II-79.
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\331\ For the purpose of estimating their contribution to CAFE
compliance, the grams CO2/mile values in Table II-79 are
converted to gallons/mile and applied to a manufacturer's 2-cycle
CAFE performance. When calculating compliance with EPA's GHG
program, there is no conversion necessary (as standards are also
denominated in grams/mile).
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[[Page 43160]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.113
The model currently accounts for any off-cycle adjustments
associated with technologies that are included in the set of fuel-
saving technologies explicitly simulated as part of this proposal (for
example, start-stop systems that reduce fuel consumption during idle or
active grille shutters that improve aerodynamic drag at highway speeds)
and accumulates these adjustments up to the 10 g/mi cap. As a practical
matter, most of the adjustments for which manufacturers are claiming
off-cycle FCIV exist outside of the technology tree, so the cap is
rarely reached during compliance simulation. If those FCIVs become a
more important compliance mechanism, it may be necessary to model their
application explicitly. However, doing so will require data on which
vehicle models already possess these improvements as well as the cost
and expected value of applying them to other models in the future.
Comment is sought on both the data requirements and strategic decisions
associated with manufacturers' use of A/C efficiency and off-cycle
technologies to improve CAFE and CO2 compliance.
(c) Civil Penalty Rate and OEMs' Anticipated Willingness To Treat Civil
Penalties as a Program Flexibility
Throughout the history of the CAFE program, some manufacturers have
consistently achieved fuel economy levels below their standard. As in
previous versions of the CAFE model, the current version allows the
user to specify inputs identifying such manufacturers and to consider
their compliance decisions as if they are willing to pay civil
penalties for non-compliance with the CAFE program. The assumed civil
penalty rate in the current analysis is $5.50 per 1/10 of a mile per
gallon, per vehicle sold.
It is worth noting that treating a manufacturer as if they are
willing to pay civil penalties does not necessarily mean that it is
expected to pay penalties in reality. It merely implies that the
manufacturer will only apply fuel economy technology up to a point, and
then stop, regardless of whether or not its corporate average fuel
economy is above its standard. In practice, we expect that many of
these manufacturers will continue to be active in the credit market,
using trades with other manufacturers to transfer credits into specific
fleets that are challenged in any given year, rather than paying
penalties to resolve CAFE deficits. The CAFE model calculates the
amount of penalties paid by each manufacturer, but it does not simulate
trades between manufacturers. In practice, some (possibly most) of the
total estimated penalties may be a transfer from one OEM to another.
While the Energy Policy and Conservation Act (EPCA), as amended in
2007 by the Energy Independence and Security Act, prescribes these
specific civil penalty provisions for CAFE standards, the Clean Air Act
(CAA) does not contain similar provisions. Rather, the CAA's provisions
regarding noncompliance constitute a de facto prohibition against
selling vehicles failing to comply with emissions standards. Therefore,
inputs regarding civil penalties--including inputs regarding
manufacturers' potential willingness to treat civil penalty payment as
an economic choice--apply only to simulation of CAFE standards.
(d) Treatment of Credit Provisions for ``Standard Setting'' and
``Unconstrained'' Analyses
NHTSA may not consider the application of CAFE credits toward
compliance with new standards when establishing the standards
themselves.\332\ As such, this analysis considers 2020 to be the last
model year in which carried-forward or transferred credits can be
applied for the CAFE program. Beginning in model year 2021,
[[Page 43161]]
today's ``standard setting'' analysis is conducted assuming each fleet
must comply with the CAFE standard separately in every model year.
---------------------------------------------------------------------------
\332\ 49 U.S.C. 32902(h) (2007).
---------------------------------------------------------------------------
The ``unconstrained'' perspective acknowledges that these
flexibilities exist as part of the program and, while not considered in
NHTSA's decision of the preferred alternative, are important to
consider when attempting to estimate the real impact of any
alternative. Under the ``unconstrained'' perspective, credits may be
earned, transferred, and applied to deficits in the CAFE program
throughout the full range of model years in the analysis. The Draft
Environmental Impact Analysis (DEIS) accompanying today's NPRM presents
results of ``unconstrained'' modeling. Also, because the CAA provides
no direction regarding consideration of any CO2 credit
provisions, today's analysis includes simulation of carried-forward and
transferred CO2 credits in all model years.
(e) Treatment of AFVs for ``Standard Setting'' and ``Unconstrained''
Analyses
NHTSA is also prohibited from considering the possibility that a
manufacturer might produce alternatively fueled vehicles as a
compliance mechanism,\333\ taking advantage of credit provisions
related to AFVs that significantly increase their fuel economy for CAFE
compliance purposes. Under the ``standard setting'' perspective, these
technologies (pure battery electric vehicles and fuel cell vehicles
\334\) are not available in the compliance simulation to improve fuel
economy. Under the ``unconstrained'' perspective, such as is documented
in the DEIS, the CAFE model considers these technologies in the context
of all other available technologies and may apply them if they
represent cost-effective compliance pathways. However, under both
perspectives, the analysis continues to include dedicated AFVs that
already exist in the MY 2016 fleet (and their projected future volumes)
in CAFE calculations. Also, because the CAA provides no direction
regarding consideration of alternative fuels, today's analysis includes
simulation of the potential that some manufacturers might introduce new
AFVs in response to CO2 standards. To fully represent the
compliance benefit from such a response, NHTSA modified the CAFE model
to include the specific provisions related to AFVs under the
CO2 standards. In particular, the CAFE model now carries a
full representation of the production multipliers related to electric
vehicles, fuel cell vehicles, plug-in hybrids, and CNG vehicles, all of
which vary by year through MY 2021.
---------------------------------------------------------------------------
\333\ Id.
\334\ Dedicated compressed natural gas (CNG) vehicles should
also be excluded in this perspective but are not considered as a
compliance strategy under any perspective in this analysis.
---------------------------------------------------------------------------
2. Simulation of Manufacturers' [and Buyers'] Potential Responses to
Each Alternative
The CAFE model provides a way of estimating how manufacturers could
attempt to comply with a given CAFE standard by adding technology to
fleets that the agencies anticipate they will produce in future model
years. This exercise constitutes a simulation of manufacturers'
decisions regarding compliance with CAFE or CO2 standards.
This compliance simulation begins with the following inputs: (a)
The analysis fleet of vehicles from model year 2016 discussed above in
Section II.B, (b) fuel economy improving technology estimates discussed
above in Section II.D, (c) economic inputs discussed above in Section
II.E, and (d) inputs defining baseline and potential new CAFE
standards. For each manufacturer, the model applies technologies in
both a logical sequence and a cost-minimizing strategy in order to
identify a set of technologies the manufacturer could apply in response
to new CAFE or CO2 standards. The model applies technologies
to each of the projected individual vehicles in a manufacturer's fleet,
considering the combined effect of regulatory and market incentives
while attempting to account for manufacturers' production constraints.
Depending on how the model is exercised, it will apply technology until
one of the following occurs:
(1) The manufacturer's fleet achieves compliance \335\ with the
applicable standard and continuing to add technology in the current
model year would be attractive neither in terms of stand-alone
(i.e., absent regulatory need) cost-effectiveness nor in terms of
facilitating compliance in future model years;
---------------------------------------------------------------------------
\335\ When determining whether compliance has been achieved in
the CAFE program, existing CAFE credits that may be carried over
from prior model years or transferred between fleets are also used
to determine compliance status. For purposes of determining the
effect of maximum feasible CAFE standards, NHTSA cannot consider
these mechanisms for years being considered (though does so for
model years that are already final) and exercises the CAFE model
without enabling these options.
---------------------------------------------------------------------------
(2) The manufacturer ``exhausts'' available technologies; \336\
or
---------------------------------------------------------------------------
\336\ In a given model year, it is possible that production
constraints cause a manufacturer to ``run out'' of available
technology before achieving compliance with standards. This can
occur when: (a) An insufficient volume of vehicles are expected to
be redesigned, (b) vehicles have moved to the ends of each
(relevant) technology pathway, after which no additional options
exist, or (c) engineering aspects of available vehicles make
available technology inapplicable (e.g., secondary axle disconnect
cannot be applied to two-wheel drive vehicles).
---------------------------------------------------------------------------
(3) For manufacturers assumed to be willing to pay civil
penalties (in the CAFE program), the manufacturer reaches the point
at which doing so would be more cost-effective (from the
manufacturer's perspective) than adding further technology.
The model accounts explicitly for each model year, applying
technologies when vehicles are scheduled to be redesigned or freshened
and carrying forward technologies between model years once they are
applied (until, if applicable, they are superseded by other
technologies). The model then uses these simulated manufacturer fleets
to generate both a representation of the U.S. auto industry and to
modify a representation of the entire light-duty registered vehicle
population. From these fleets, the model estimates changes in physical
quantities (gallons of fuel, pollutant emissions, traffic fatalities,
etc.) and calculates the relative costs and benefits of regulatory
alternatives under consideration.
The CAFE model accounts explicitly for each model year, in turn,
because manufacturers actually ``carry forward'' most technologies
between model years, tending to concentrate the application of new
technology to vehicle redesigns or mid-cycle ``freshenings,'' and
design cycles vary widely among manufacturers and specific products.
Comments by manufacturers and model peer reviewers strongly support
explicit year-by-year simulation. Year-by-year accounting also enables
accounting for credit banking (i.e., carry-forward), as discussed
above, and at least four environmental organizations recently submitted
comments urging the agencies to consider such credits, citing NHTSA's
2016 results showing impacts of carried-forward credits.\337\ Moreover,
EPCA/EISA requires that NHTSA make a year-by-year determination of the
appropriate level of stringency and then set the standard at that
level, while ensuring ratable increases in average fuel economy through
MY 2020. The multi-year planning capability, (optional) simulation of
``market-driven overcompliance,'' and EPCA credit mechanisms (again,
for purposes of modeling the CAFE program) increase the model's ability
to simulate manufacturers' real-world behavior, accounting for the fact
that
[[Page 43162]]
manufacturers will seek out compliance paths for several model years at
a time, while accommodating the year-by-year requirement. This same
multi-year planning structure is used to simulate responses to
standards defined in grams CO2/mile, and utilizing the set
of specific credit provisions defined under EPA's program.
---------------------------------------------------------------------------
\337\ Comment by Environmental Law & Policy Center, Natural
Resources Defense Council (NRDC), Public Citizen, and Sierra Club,
Docket ID EPA-HQ-OAR-2015-0827-9826, at 28-29.
---------------------------------------------------------------------------
(a) Representation of Manufacturers' Production Constraints
After the light-duty rulemaking analysis accompanying the 2012
final rule that finalized NHTSA's standards through MY 2021, NHTSA
began work on changes to the CAFE model with the intention of better
reflecting constraints of product planning and cadence for which
previous analyses did not account.
(b) Product Cadence
Past comments on the CAFE model have stressed the importance of
product cadence--i.e., the development and periodic redesign and
freshening of vehicles--in terms of involving technical, financial, and
other practical constraints on applying new technologies, and DOT has
steadily made changes to both the CAFE model and its inputs with a view
toward accounting for these considerations. For example, early versions
of the model added explicit ``carrying forward'' of applied
technologies between model years, subsequent versions applied
assumptions that most technologies will be applied when vehicles are
freshened or redesigned, and more recent versions applied assumptions
that manufacturers would sometimes apply technology earlier than
``necessary'' in order to facilitate compliance with standards in
ensuing model years. Thus, for example, if a manufacturer is expected
to redesign many of its products in model years 2018 and 2023, and the
standard's stringency increases significantly in model year 2021, the
CAFE model will estimate the potential that the manufacturer will add
more technology than necessary for compliance in MY 2018, in order to
carry those product changes forward through the next redesign and
contribute to compliance with the MY 2021 standard. This explicit
simulation of multiyear planning plays an important role in determining
year-by-year analytical results.
As in previous iterations of CAFE rulemaking analysis, the
simulation of compliance actions that manufacturers might take is
constrained by the pace at which new technologies can be applied in the
new vehicle market. Operating at the Make/Model level (e.g., Toyota
Camry) allows the CAFE model to explicitly account for the fact that
individual vehicle models undergo significant redesigns relatively
infrequently. Many popular vehicle models are only redesigned every six
years or so, with some larger/legacy platforms (the old Ford Econoline
Vans, for example) stretching more than a decade between significant
redesigns. Engines, which are often shared among many different models
and platforms for a single manufacturer, can last even longer--eight to
ten years in most cases.
While these characterizations of product cadence are important to
any evaluation of the impacts of CAFE or CO2 standards, they
are not known with certainty--even by the manufacturers themselves over
time horizons as long as those covered by this analysis. However, lack
of certainty about redesign schedules is not license to ignore them.
Indeed, when manufacturers meet with the agencies to discuss
manufacturers' plans vis-[agrave]-vis CAFE and CO2
requirements, manufacturers typically present specific and detailed
year-by-year information that explicitly accounts for anticipated
redesigns. Such year-by-year analysis is also essential to
manufacturers' plans to make use of provisions (for CAFE, statutory and
specific) allowing credits to be carried forward to future model years,
carried back from future model years, transferred between regulated
fleets, and traded with other manufacturers. Manufacturers are never
certain about future plans, but they spend considerable effort
developing, continually adjusting, and implementing them.
For every model that appears in the MY 2016 analysis fleet, the
model years have been estimated in which future redesigns (and less
significant ``freshenings,'' which offer manufacturers the opportunity
to make less significant changes to models) will occur. These appear in
the market data file for each model variant. Mid-cycle freshenings
provide additional opportunities to add some technologies in years
where smaller shares of a manufacturer's portfolio is scheduled to be
redesigned. In addition, the analysis accounts for multiyear planning--
that is, the potential that manufacturers may apply ``extra''
technology in an early model year with many planned redesigns in order
to carry technology forward to facilitate compliance in a later model
year with fewer planned redesigns. Further, the analysis accounts for
the potential that manufacturers could earn CAFE and/or CO2
credits in some model years and use those credits in later model years,
thereby providing another compliance option in years with few planned
redesigns. Finally, it should be noted that today's analysis does not
account for future new products (or discontinued products)--past trends
suggest that some years in which an OEM had few redesigns may have been
years when that OEM introduced significant new products. Such changes
in product offerings can obviously be important to manufacturers'
compliance positions but cannot be systematically and transparently
accounted for with a fleet forecast extrapolated forward 10 or more
years from a largely-known fleet. While manufacturers' actual plans
reflect intentions to discontinue some products and introduce others,
those plans are considered CBI. Further research would be required in
order to determine whether and, if so, how it would be practicable to
simulate such decisions, especially without relying on CBI.
Additionally, each technology considered for application by the
CAFE model is assigned to either a ``refresh'' or ``redesign'' cadence
that dictates when it can be applied to a vehicle. Technologies that
are assigned to ``refresh/redesign'' can be applied at either a refresh
or redesign, while technologies that are assigned to ``redesign'' can
only be applied during a significant vehicle redesign. Table II-80 and
Table II-81 show the technologies available to manufacturers in the
compliance simulation, the level at which they are applied (described
in greater detail in the CAFE model documentation), whether they are
available outside of a vehicle redesign, and a short description of
each. A brief examination of the tables shows that most technologies
are only assumed to be available during a vehicle redesign--and nearly
all engine improvements are assumed to be available only during
redesign. In a departure from past CAFE analyses, all transmission
improvements are assumed to be available during refresh as well as
redesign. While there are past and recent examples of mid-cycle product
changes, it seems reasonable to expect that manufacturers will tend to
attempt to keep engineering and other costs down by applying most major
changes mainly during vehicle redesigns and some mostly modest changes
during product freshenings. As mentioned below, comment is sought on
the approach to account for product cadence.
(c) Component Sharing and Inheritance (Engines, Transmissions, and
Platforms)
In practice, manufacturers are limited in the number of engines and
transmissions that they produce.
[[Page 43163]]
Typically, a manufacturer produces a number of engines--perhaps six or
eight engines for a large manufacturer--and tunes them for slight
variants in output for a variety of car and truck applications.
Manufacturers limit complexity in their engine portfolio for much the
same reason as they limit complexity in vehicle variants: They face
engineering manpower limitations, and supplier, production, and service
costs that scale with the number of parts produced.
In previous analyses that used the CAFE model (with the exception
of the 2016 Draft TAR), engines and transmissions in individual vehicle
models were allowed relative freedom in technology application,
potentially leading to solutions that would, if followed, create many
more unique engines and transmissions than exist in the analysis fleet
(or in the market) for a given model year. This multiplicity likely
failed to sufficiently account for costs associated with such increased
complexity in the product portfolio and may have represented an
unrealistic diffusion of products for manufacturers that are
consolidating global production to increasingly smaller numbers of
shared engines and platforms.\338\ The lack of a constraint in this
area allowed the model to apply different levels of technology to the
engine in each vehicle in which it was present at the time that vehicle
was redesigned or refreshed, independent of what was done to other
vehicles using a previously identical engine.
---------------------------------------------------------------------------
\338\ 2015 NAS Report, at pg. 258-259.
---------------------------------------------------------------------------
One peer reviewer of the CAFE model recently commented, ``The
integration of inheritance and sharing of engines, transmissions, and
platforms across a manufacturer's light duty fleet and separately
across its light duty truck fleet is standard practice within the
industry.'' In the current version of the CAFE model, engines and
transmissions that are shared between vehicles must apply the same
levels of technology, in all technologies, dictated by engine or
transmission inheritance. This forced adoption is referred to as
``engine inheritance'' in the model documentation. In practice, the
model first chooses an ``engine leader'' among vehicles sharing the
same engine--the vehicle with the highest sales in MY 2016. If there is
a tie, the vehicle with the highest average MSRP is chosen,
representing the idea that manufacturers will choose to pilot the
newest technology on premium vehicles if possible. The model applies
the same logic with respect to the application of transmission changes.
After the model modifies the engine on the ``engine leader'' (or
``transmission leader''), the changes to that engine propagate through
to the other vehicles that share that engine (or transmission) in
subsequent years as those vehicles are redesigned. The CAFE model has
been modified to provide additional flexibility vis-[agrave]-vis
product cadence. In a recent public comment, NRDC noted:
EPA and NHTSA currently constrain their model to apply
significant fuel-efficient technologies mainly during a product-
redesign as opposed to product-refresh (or mid-cycle). This was
identified as one of the most sensitive assumptions affecting
overall program costs by NHTSA in the TAR. By constraining the
model, the agencies have likely under-estimated the ability of auto
manufacturers to incorporate some technologies during their product
refreshes. This is particularly true regarding the critical
powertrain technologies which are undergoing continuous improvement.
The agency should account for these trends and incorporate greater
flexibility for automakers--within their models--to incorporate more
mid-cycle enhancements.\339\
---------------------------------------------------------------------------
\339\ Comment by Environmental Law & Policy Center, Natural
Resources Defense Council (NRDC), Public Citizen, and Sierra Club,
Docket ID EPA-HQ-OAR-2015-0827-9826, at 32.
While engine redesigns are only applied to the engine leader when
it is redesigned in the model, followers may now inherit upgraded
engines (that they share with the leader) at either refresh or
redesign. All transmission changes, whether upgrades to the ``leader''
or inheritance to ``followers'' can occur at refresh as well as
redesign. This provides additional opportunities for technology
diffusion within manufacturers' product portfolios.
While ``follower'' vehicles are awaiting redesign (or, for
transmissions, refreshing as applicable), they carry a legacy version
of the shared engine or transmission. As one peer reviewer recently
stated, ``Most of the time a manufacturer will convert only a single
plant within a model year. Thus both the `old' and `new' variant of the
engine (or transmission) will produced for a finite number of years.''
\340\ The CAFE model currently carries no additional cost associated
with producing both earlier revisions of an engine and the updated
version simultaneously. Further research would be needed to determine
whether sufficient data is likely to be available to explicitly specify
and apply additional costs involved with continuing to produce an
existing engine or transmission for some vehicles that have not yet
progressed to a newer version of that engine or transmission. Comment
is sought on possible data sources and approaches that could be used to
represent any additional costs associated with phased introduction of
new engines or transmissions.
---------------------------------------------------------------------------
\340\ CAFE Model Peer Review, p. 19.
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There are some logical consequences of this approach, the first of
which is that forcing engine and transmission changes to propagate
through to other vehicles in this way effectively dictates the pace at
which new technology can be applied and limits the total number of
unique engines that the model simulates. In the past, NHTSA used
``phase-in caps'' (see discussion below) to limit the amount of
technology that can be applied to any vehicle in a given year. However,
by explicitly tying the engine changes to a specific vehicle's product
cadence, rather than letting the timing of changes vary across all the
vehicles that share an engine, the model ensures that an engine is only
changed when its leader is redesigned (at most). Given that most
vehicle redesign cycles are five to eight years, this approach still
represents shorter average lives than most engines in the market, which
tend to be in production for eight to ten years or more. It is also the
case that vehicles which share an engine in the analysis fleet (MY
2016, for this analysis) are assumed to share that same engine
throughout the analysis--unless one or both of them are converted to
power-split hybrids (or farther) on the electrification path. In the
market, this is not true--since a manufacturer will choose an engine
from among the engines it produces to fulfill the efficiency and power
demands of a vehicle model upon redesign. That engine need not be from
the same family of engines as the prior version of that vehicle. This
is a simplifying assumption in the model. While the model already
accommodates detailed inputs regarding redesign schedules for specific
vehicles and commercial information sources are available to inform
these inputs, further research would be needed to determine whether
design schedules for specific engines and transmissions can practicably
be simulated.
The CAFE model has implemented a similar structure to address
shared vehicle platforms. The term ``platform'' is used loosely in
industry but generally refers to a common structure shared by a group
of vehicle variants. The degree of commonality varies with some
platform variants exhibiting traditional ``badge engineering'' where
two products are differentiated by little more than insignias, while
other platforms may be used to produce a broad suite of vehicles that
bear little outer resemblance to one another.
[[Page 43164]]
Given the degree of commonality between variants of a single
platform, manufacturers do not have complete freedom to apply
technology to a vehicle: While some technologies (e.g. low rolling
resistance tires) are very nearly ``bolt-on'' technologies, others
involve substantial changes to the structure and design of the vehicle,
and therefore necessarily are constant among vehicles that share a
common platform. NHTSA has, therefore, modified the CAFE model such
that all mass reduction technologies are forced to be constant among
variants of a platform.
Within the analysis fleet, each vehicle is associated with a
specific platform. Similar to the application of engine and
transmission technologies, the CAFE model defines a platform ``leader''
as the vehicle variant of a given platform that has the highest level
of observed mass reduction present in the analysis fleet. If there is a
tie, the CAFE model begins mass reduction technology on the vehicle
with the highest sales in model year 2016. If there remains a tie, the
model begins by choosing the vehicle with the highest MSRP in MY 2016.
As the model applies technologies, it effectively levels up all
variants on a platform to the highest level of mass reduction
technology on the platform. So, if the platform leader is already at
MR3 in MY 2016, and a ``follower'' starts at MR0 in MY 2016, the
follower will get MR3 at its next redesign (unless the leader is
redesigned again before that time, and further increases the MR level
associated with that platform, then the follower would receive the new
MR level).
In the 2015 NPRM proposing new fuel consumption and GHG standards
for heavy-duty pickups and vans, NHTSA specifically requested comment
on the general use of shared engines, transmissions, and platforms
within CAFE rulemakings. While no commenter responded to this specific
request, comments from some environmental organizations cited examples
of technology sharing between light- and heavy-duty products. NHTSA has
continued to refine its implementation of an approach accounting for
shared engines, transmissions, and platforms, and again seeks comment
on the approach, recommendations regarding any other approaches, and
any information that would facilitate implementation of the agency's
current approach or any alternative approaches.
(d) Phase-In Caps
The CAFE model retains the ability to use phase-in caps (specified
in model inputs) as proxies for a variety of practical restrictions on
technology application, including the improvements described above.
Unlike vehicle-specific restrictions related to redesign, refreshes or
platforms/engines, phase-in caps constrain technology application at
the vehicle manufacturer level for a given model year. Introduced in
the 2006 version of the CAFE model, they were intended to reflect a
manufacturer's overall resource capacity available for implementing new
technologies (such as engineering research and development personnel
and financial resources), thereby ensuring that resource capacity is
accounted for in the modeling process.
Compared to prior analyses of light-duty standards, these model
changes result in some changes in the broad characteristics of the
model's application of technology to manufacturers' fleets. Since the
use of phase-in caps has been de-emphasized and manufacturer technology
deployment remains tied strongly to estimated product redesign and
freshening schedules, technology penetration rates may jump more
quickly as manufacturers apply technology to high-volume products in
their portfolio. As a result, the model will ignore a phase-in cap to
apply inherited technology to vehicles on shared engines,
transmissions, and platforms.
In previous CAFE rulemakings, redesign/refresh schedules and phase-
in caps were the primary mechanisms to reflect an OEM's limited pool of
available resources during the rulemaking time frame and the years
preceding it, especially in years where many models may be scheduled
for refresh or redesign. The newly-introduced representation of
platform-, engine-, and transmission-related considerations discussed
above augment the model's preexisting representation of redesign cycles
and eliminate the need to rely on phase-in caps. By design,
restrictions that enforce commonality of mass reduction on variants of
a platform, and those that enforce engine and transmission inheritance,
will result in fewer vehicle-technology combinations in a
manufacturer's future modeled fleet. The integration of shared
components and product cadence as a mechanism to control the pace of
technology application also more accurately represents each
manufacturer's unique position in the market and its existing
technology footprint, rather than a technology-specific phase-in cap
that is uniformly applied to all manufacturers in a given year. Comment
is sought regarding this shift away from relying on phase-in caps and,
if greater reliance on phase-in caps is recommended, what approach and
information can be used to define and apply these caps.
(e) Interactions Between Regulatory Classes
Like earlier versions, the current CAFE model provides the
capability for integrated analysis spanning different regulatory
classes, accounting both for standards that apply separately to
different classes and for interactions between regulatory classes.
Light vehicle CAFE and CO2 standards are specified
separately for passenger cars and light trucks. However, there is
considerable sharing between these two regulatory classes--where a
single engine, transmission, or platform can appear in both the
passenger car and light truck regulatory class. For example, some
sport-utility vehicles are offered in 2WD versions classified as
passenger cars and 4WD versions classified as light trucks. Integrated
analysis of manufacturers' passenger car and light truck fleets
provides the ability to account for such sharing and reduces the
likelihood of finding solutions that could involve introducing
impractical levels of complexity in manufacturers' product lines.
Additionally, integrated fleet analysis provides the ability to
simulate the potential that manufacturers could earn CAFE and
CO2 credits by over complying with the standard in one fleet
and use those credits toward compliance with the standard in another
fleet (i.e., to simulate credit transfers between regulatory classes).
While previous versions of the CAFE model have represented
manufacturers' fleets by drawing a distinction between passenger cars
and light trucks, the current version of the CAFE model adds a further
distinction, capturing the difference between passenger cars classified
as domestic passenger cars and those classified as imports. The CAFE
program regulates those passenger cars separately, and the current
version of the CAFE model simulates all three CAFE regulatory classes
separately: Domestic Passenger Cars (DC), Imported Passenger Cars (IC),
and Light Trucks (LT). CAFE regulations state that standards, fuel
economy levels, and compliance are all calculated separately for each
class. These requirements are specified explicitly by the Energy Policy
and Conservation Act (EPCA), with the 2007 Energy Independence and
Security Act (EISA) having added the requirement to enforce minimum
standards for domestic passenger cars. This update to the accounting
imposes two additional constraints on
[[Page 43165]]
manufacturers that sell vehicles in the U.S.: (1) The domestic minimum
floor, and (2) Limited transfers between cars classified as
``domestic'' versus those classified as ``imported.'' The domestic
minimum floor creates a threshold that every manufacturer's domestic
car fleet must exceed without the application of CAFE credits. If a
manufacturer's calculated standard is below the domestic minimum floor,
then the domestic floor is the binding constraint (even for
manufacturers that are assumed to be willing to pay fines for non-
compliance). The second constraint poses challenges for manufacturers
that sell cars from both the domestic and imported passenger car
categories.
While previous versions of the CAFE model considered those fleets
as a single fleet (i.e., passenger cars), the model now forces them to
comply separately and limits the volume of credits that can be shifted
between them for compliance. However, the CAA provides no direction
regarding compliance by domestic and imported vehicles; EPA has not
adopted provisions similar to the aforementioned EPCA/EISA requirements
and is not doing so today. Therefore, consistent with current and
proposed CO2 regulations, the CAFE model determines
compliance for manufacturers' overall passenger car fleets for EPA's
program.
During 2015-2016, a single version of the CAFE model was applied to
produce analyses supporting both a rulemaking regarding heavy-duty
pickups and vans (HD PUV) and the 2016 draft TAR regarding CAFE
standards for passenger cars and light trucks. Both analyses reflected
integrated analysis of the light-duty and HD PUV fleets, thereby
accounting for sharing between the fleets. However, for most OEMs, that
analysis showed considerably less sharing between light-duty and HD PUV
fleets than initially expected. Today's analysis includes only vehicles
subject to CAFE and light-duty CO2 standards, and the
agencies invite comment on whether integrated analysis of the two
fleets should be pursued further.
3. Technology Application Algorithm
(a) Technology Representation and Pathways
While some properties of the technologies included in the analysis
are specified by the user (e.g., cost of the technology), the set of
included technologies is part of the model itself, which contains the
information about the relationships between technologies.\341\ In
particular, the CAFE model contains the information about the sequence
of technologies, the paths on which they reside, any prerequisites
associated with a technology's application, and any exclusions that
naturally follow once it is applied.
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\341\ Unlike the 2012 Final Rule, where each technology had a
single effectiveness value for the CAFE analysis, technology
effectiveness in the current version of the CAFE model is based on
the ANL simulation project and defined for each combination of
technologies, resulting in more than 100,000 technology
effectiveness values for each of ten technology classes. This large
database is extracted locally the first time the model is run and
can be modified by the user in that location to reflect alternative
assumptions about technology effectiveness.
---------------------------------------------------------------------------
The ``application level'' describes the system of the vehicle to
which the technology is applied, which in turn determines the extent to
which that decision affects other vehicles in a manufacturer's fleet.
For example, if a technology is applied at the ``engine'' level, it
naturally affects all other vehicles that share that same engine
(though not until they themselves are redesigned, if it happens to be
in a future model year). Technologies applied at the ``vehicle'' level
can be applied to a vehicle model without impacting the other models
with which it shares components. Platform-level technologies affect all
of the vehicles on a given platform, which can easily span technology
classes, regulatory classes, and redesign cycles.
The ``application schedule'' identifies when manufacturers are
assumed to be able to apply a given technology--with many available
only during vehicle redesigns. The application schedule also accounts
for which technologies the CAFE model tracks but does not apply. These
enter as part of the analysis fleet (``Baseline Only''), and while they
are necessary for accounting related to cost and incremental fuel
economy improvement, they do not represent a choice that manufacturers
make in the model. As discussed in Section II.B, the analysis fleet
contains the information about each vehicle model, engine, and
transmission selected for simulation and defines the initial technology
state of the fleet relative to the sets of technologies in Table II-80
and Table II-81.
[[Page 43166]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.114
[[Page 43167]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.115
As Table II-80 and Table II-81 show, all of the engine technologies
may only be applied (for the first time) during redesign. New
transmissions can be applied during either refresh or redesign, except
for manual transmissions, which can only be upgraded during redesign.
Unlike previous versions of the model, which only allowed significant
changes to vehicle powertrains at redesign, this version allows
vehicles to inherit updates to shared components during refresh. For
example, assume Vehicle A and Vehicle B share Engine 1, and engine 1 is
redesigned as part of Vehicle A's redesign in MY 2020. Vehicle B is not
redesigned until 2025 but is refreshed in MY 2022. In the current
version of the CAFE model, Vehicle B would inherit the updated version
of Engine 1 when it is freshened in MY 2022. This change allows more
rapid diffusion of powertrain updates (for example) throughout a
manufacturer's portfolio and reduces the number of years during which a
manufacturer would build both new and legacy versions of the same
engine. Despite increasing the rate of technology diffusion, this
change still restricts the pace at which new engines (for example) can
be designed and built (i.e., no faster than the redesign schedule of
the ``leader'' vehicle to which they are tied). The only technology for
which
[[Page 43168]]
this does not hold is mass reduction improvements; these occur at the
platform level, and each model on that platform must be redesigned (not
merely refreshed) in order to receive the newest version of the
platform that contains the most current mass reduction technology.
The CAFE model defines several ``technology classes'' and
``technology pathways'' for logically grouping all available
technologies for application on a vehicle. Technology classes provide
costs and improvement factors shared by all vehicles with similar body
styles, curb weights, footprints, and engine types, while technology
pathways establish a logical progression of technologies on a vehicle
within a system or sub-system (e.g., engine technologies).
Technology classes, shown in Table-II-82, are a means for
specifying common technology input assumptions for vehicles that share
similar characteristics. Predominantly, these classes signify the
degree of applicability of each of the available technologies to a
specific class of vehicles and represent a specific set of Autonomie
simulations (conducted as part of the Argonne National Lab large-scale
simulation study) that determine the effectiveness of each technology
to improve fuel economy. The vehicle technology classes also define,
for each technology, the additional cost associated with
application.\342\ Like the TAR analysis, the model uses separate
technology classes for compact cars, midsize cars, small SUVs, large
SUVs, and pickup trucks. However, in this analysis, each of those
distinctions also has a ``performance'' version, that represents
another class with similar body style but higher levels of performance
attributes (for a total of 10 technology classes). As the model
simulates compliance, identifying technologies that can be applied to a
given manufacturer's product portfolio to improve fleet fuel economy,
it relies on the vehicle class to provide relevant cost and
effectiveness information for each vehicle model.
---------------------------------------------------------------------------
\342\ Inputs are specified to assign each vehicle in the
analysis fleet to one of these technology classes, as discussed in
Section II.B.
[GRAPHIC] [TIFF OMITTED] TP24AU18.116
The model defines technology pathways for grouping and establishing
a logical progression of technologies on a vehicle. Each pathway (or
path) is evaluated independently and in parallel, with technologies on
these paths being considered in sequential order. As the model
traverses each path, the costs and fuel economy improvements are
accumulated on an incremental basis with relation to the preceding
technology. The system stops examining a given path once a combination
of one or more technologies results in a ``best'' technology solution
for that path. After evaluating all paths, the model selects the most
cost-effective solution among all pathways. This parallel path approach
allows the modeling system to progress through technologies in any
given pathway without being unnecessarily prevented from considering
technologies in other paths.
Rather than rely on a specific set of technology combinations or
packages, the model considers the universe of applicable technologies,
dynamically identifying the most cost-effective combination of
technologies for each manufacturer's vehicle fleet based on each
vehicle's initial technology content and the assumptions about each
technology's effectiveness, cost, and interaction with all other
technologies both present and available.
(b) Technology Paths
The modeling system incorporates 16 technology pathways for
evaluation as shown in Table-II--83. Similar to individual
technologies, each path carries an intrinsic application level that
denotes the scope of applicability of all technologies present within
that path and whether the pathway is evaluated on one vehicle at a
time, or on a collection of vehicles that share the same platform,
engine, or transmission.
[[Page 43169]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.117
The technologies that comprise the five Engine-Level paths
available within the model are presented in Figure-II-13. Note: The
baseline-level technologies (SOHC, DOHC, OHV, and CNG) appear in gray
boxes. These technologies are used to inform the modeling system of the
initial engine's configuration and are not otherwise applicable during
the analysis. Additionally, the VCR path (intended to house fuel
economy improvements from variable compression ratio engines) was not
used in this analysis but is present within the model. Unlike earlier
versions of the CAFE model, that enforced strictly sequential
application of technologies like VVL and SGDI, this version of the CAFE
model allows basic engine technologies to be applied in any order once
an engine has VVT (the base state of all ANL simulations). Once the
model progresses past the basic engine path, it considers all of the
more advanced engine paths (Turbo, HCR, Diesel, and ADEAC)
simultaneously. They are assumed to be mutually exclusive. Once one
path is taken, it locks out the others to avoid situations where the
model could be perceived to force manufacturers to radically change
engine architecture with each redesign, incurring stranded capital
costs and lost opportunities for learning.
[GRAPHIC] [TIFF OMITTED] TP24AU18.118
For all pathways, the technologies are evaluated and applied to a
vehicle in sequential order, as shown from top to bottom. In some
cases, however, if a technology is deemed ineffective, the system will
bypass it and skip ahead to the next technology. If the modeling system
applies a technology that resides later in the pathway, it will
``backfill'' anything that was previously skipped in order to fully
account for costs and fuel economy improvements of the full
[[Page 43170]]
technology combination.\343\ For any technology that is already present
on a vehicle (either from the MY 2016 fleet or previously applied by
the model), the system skips over those technologies as well and
proceeds to the next. These skipped technologies, however, will not be
applied again during backfill.
---------------------------------------------------------------------------
\343\ More detail about how the Argonne simulation database was
integrated into the CAFE model can be found in PRIA Chapter 6.
---------------------------------------------------------------------------
While costs are still purely incremental, technology effectiveness
is no longer constructed that way. The non-sequential nature of the
basic engine technologies have no obvious preceding technology except
for VVT, the root of our engine path. It was a natural extension to
carry this approach to the other branches as well. The technology
effectiveness estimates are now an integrated part of the CAFE model
and represent a translation of the Argonne simulation database that
compares the fuel consumption of any combination of technologies
(across all paths) to the base vehicle (that has only VVT, 5-speed
automatic transmission, no electrification, and no body-level
improvements).\344\
---------------------------------------------------------------------------
\344\ This is true for all combinations other than those
containing manual transmissions. Because the model does not convert
automatic transmissions to manual transmissions, nor the inverse,
technology combinations containing manual transmissions use a
reference point identical to the base vehicle description, but
containing a 5-speed manual rather than automatic transmission.
---------------------------------------------------------------------------
The Basic Engine path begins with SOHC, DOHC, and OHV technologies
defining the initial configuration of the vehicle's engine. Since these
technologies are not available during modeling, the system evaluates
this pathway starting with VVT. Whenever a technology pathway forks
into two or more branch points, as the engine path does at the end of
the basic engine path, all of the branches are treated as mutually
exclusive. The model evaluates all technologies forming the branch
simultaneously and selects the most cost-effective for the application,
while disabling the unchosen remaining paths.
The technologies that make up the four Transmission-Level paths
defined by the modeling system are shown in Figure-II-14. The baseline-
level technologies (AT5, MT5 and CVT) appear in gray boxes and are only
used to represent the initial configuration of a vehicle's
transmission. For simplicity, all manual transmissions with five
forward gears or fewer have been assigned the MT5 technology in the
analysis fleet. Similarly, all automatic transmissions with five
forward gears or fewer have been assigned the AT5 technology. The model
preserves the initial configuration for as long as possible, and
prohibits manual transmissions from becoming automatic transmissions at
any point. Automatic transmissions may become CVT level 2 after
progressing though the 6-speed automatic. While the structure of the
model still allows automatic transmissions to consider the move to DCT,
in practice they are restricted from doing so in the market data file.
This allows vehicles that enter with a DCT to improve it (if
opportunities to do so exist) but does not allow automatic
transmissions to become DCTs, in recognition of low consumer enthusiasm
for the earlier versions the transmission that have been introduced
over the last decade. The model does not attempt to simulate
``reversion'' to less advanced transmission technologies, such as
replacing a 6-speed AT with a DCT and then replacing that DCT with a
10-speed AT. The agencies invite comment on whether or not the model
should be modified to simulate such ``reversion'' and, if so, how this
possible behavior might be practicably simulated.
[[Page 43171]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.119
The root of the Electrification path, shown in Figure-II-15, is a
conventional powertrain (CONV) with no electrification. The two strong
hybrid technologies (SHEVP2 and SHEVPS) on the Hybrid/Electric path,
are defined as stand-alone and mutually exclusive. These technologies
are not incremental over each other for cost or effectiveness and do
not follow a traditional progression logic present on other paths.
While the SHEVP2 represents a hybrid system paired with the existing
engine on a given vehicle, the SHEVPS removes and replaces that engine,
making it the larger architectural change of the two. In general, the
electrification technologies are applied as vehicle-level technologies,
meaning that the model applies them without affecting components that
might be shared with other vehicles. In the case of the more advanced
electrification technologies, where engines and transmissions are
removed or replaced, the model will choose a new vehicle to be the
leader on that component (if necessary) and will not force other
vehicles sharing that engine or transmission to become hybrids (or
EVs). In addition to the electrification technologies, there are two
electrical system improvements, electric power steering (EPS) and
accessory improvements (IACC), which were not part of the ANL
simulation project and are applied by the model as fixed percentage
improvements to all technology combinations in a particular technology
class. Their improvements are superseded by technologies in the other
electrification paths, BISG or CISG, in the case of EPS, and strong
hybrids (and above) in the case of IACC, which are assumed to include
those improvements already.
[[Page 43172]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.120
The technology paths related to load reduction of the vehicle are
shown in Figure-II-16. Of these, only the Mass Reduction (MR) path is
applied at the platform level, thus affecting all vehicles (across
classes and body styles) on a given platform. The remaining technology
paths are all applied at the vehicle level, and technologies within
each path are considered purely sequential. For mass reduction,
aerodynamic improvements, and reductions in rolling resistance, the
base level of each path is the ``zero state,'' in which a vehicle has
exhibited none of the improvements associated with the technology path.
In addition to choosing among possible engine, transmission, and
electrification improvements to improve a vehicle's fuel economy, the
CAFE model will consider technologies each of the possible load
improvement paths simultaneously.
[GRAPHIC] [TIFF OMITTED] TP24AU18.121
Even though the model evaluates each technology path independently,
some of the pathways are interconnected to allow for additional logical
progression and incremental accounting of technologies. For example,
the cost of
[[Page 43173]]
SHEVPS (power-split strong hybrid/electric) on the Hybrid/Electric path
is defined as incremental over the complete basic engine path (an
engine that contains VVT, VVL, SGDI, and DEAC), the AT5 (5-speed
automatic) technology on the Automatic Transmission path, and the CISG
(crank mounted integrated starter/generator) technology on the
Electrification path. For that reason, whenever the model evaluates the
SHEVPS technology for application on a vehicle, it ensures that, at a
minimum, all the aforementioned technologies (as well as their
predecessors) have already been applied on that vehicle. However, if it
becomes necessary for a vehicle to progress to the power-split hybrid,
the model will virtually apply the technologies associated with the
reference point in order to evaluate the attractiveness of
transitioning to the strong hybrid.
Of the 17 technology pathways present in the model, all Engine
paths, the Automatic Transmission path, the Electrification path, and
both Hybrid/Electric paths are logically linked for incremental
technology progression. Some of the technology pathways, as defined in
the model and shown in Figure-II-17, may not be compatible with a
vehicle given its state at the time of evaluation. For example, a
vehicle with a 6-speed automatic transmission will not be able to get
improvements from a Manual Transmission path. For this reason, the
model implements logic to explicitly disable certain paths whenever a
constraining technology from another path is applied on a vehicle. On
occasion, not all of the technologies present within a pathway may
produce compatibility constraints with another path. In such a case,
the model will selectively disable a conflicting pathway (or part of
the pathway) as required by the incompatible technology.
[GRAPHIC] [TIFF OMITTED] TP24AU18.122
For any interlinked technology pathways shown in Figure-II-17, the
model also disables all preceding technology paths whenever a vehicle
transitions to a succeeding pathway. For example, if the model applies
SHEVPS technology on a vehicle, the model disables the Turbo, HCR,
ADEAC, and Diesel Engine paths, as well as the Basic Engine, the
Automatic Transmission, and the Electrification paths (all of which
precede the Hybrid/Electric path).\345\ This implicitly forces vehicles
to always move in the direction of increasing technological
sophistication each time they are reevaluated by the model.
---------------------------------------------------------------------------
\345\ The only notable exception to this rule occurs whenever
SHEVP2 technology is applied on a vehicle. This technology may be
present in conjunction with any engine-level technology, and as
such, the Basic Engine path is not disabled upon application of
SHEVP2 technology, even though this pathway precedes the Hybrid/
Electric path.
---------------------------------------------------------------------------
4. Simulating Manufacturer Compliance With Standards
As a starting point, the model needs enough information to
represent each manufacturer covered by the program. As discussed above
in Section II.B, the MY 2016 analysis fleet contains information about
each manufacturer's:
Vehicle models offered for sale--their current (i.e.,
MY 2016) production volumes, manufacturer suggested retail prices
(MSRPs), fuel saving technology content (relative to the set of
technologies described in Table II-80 and Table II-81), and other
attributes (curb weight, drive type, assignment to technology class
and regulatory class),
Production constraints--product cadence of vehicle
models (i.e., schedule of model redesigns and ``freshenings''),
vehicle platform membership, degree of engine and/or transmission
sharing (for each model variant) with other vehicles in the fleet,
[[Page 43174]]
Compliance constraints and flexibilities--historical
preference for full compliance or penalty payment/credit
application, willingness to apply additional cost-effective fuel
saving technology in excess of regulatory requirements, projected
applicable flexible fuel credits, and current credit balance (by
model year and regulatory class) in first model year of simulation.
Each manufacturer's regulatory requirement represents the
production-weighted harmonic mean of their vehicle's targets in each
regulated fleet. This means that no individual vehicle has a
``standard,'' merely a target, and each manufacturer is free to
identify a compliance strategy that makes the most sense given its
unique combination of vehicle models, consumers, and competitive
position in the various market segments. As the CAFE model provides
flexibility when defining a set of regulatory standards, each
manufacturer's requirement is dynamically defined based on the
specification of the standards for any simulation and the distribution
of footprints within each fleet.
Given this information, the model attempts to apply technology to
each manufacturer's fleet in a manner than minimizes ``effective
costs.'' The effective cost captures more than the incremental cost of
a given technology; it represents the difference between their
incremental cost and the value of fuel savings to a potential buyer
over the first 30 months of ownership.\346\ In addition to the
technology cost and fuel savings, the effective cost also includes the
change in fines from applying a given technology and any estimated
welfare losses associated with the technology (e.g., earlier versions
of the CAFE model simulated low-range electric vehicles that produced a
welfare loss to buyers who valued standard operating ranges between re-
fueling events). The effective cost metric applied by the model does
not attempt to reflect all costs of vehicle ownership. Further research
would be required in order to support simulation that assumes buyers
behave as if they actually consider all ownership costs, and that
assumes manufacturers respond accordingly. The agencies will continue
to consider the metric applied to represent manufactuers' approach to
making decisions regarding the application of fuel-saving technologies
and invite comment regarding any practicable changes that might make
this aspect of the model even more realistic.
---------------------------------------------------------------------------
\346\ The length of time over which to value fuel savings in the
effective cost calculation is a model input that can be modified by
the user. This analysis uses 30 months' worth of fuel savings in the
effective cost calculation, using the price of fuel at the time of
vehicle purchase.
---------------------------------------------------------------------------
This construction allows the model to choose technologies that both
improve a manufacturer's regulatory compliance position and are most
likely to be attractive to its consumers. This also means that
different assumptions about future fuel prices will produce different
rankings of technologies when the model evaluates available
technologies for application. For example, in a high fuel price regime,
an expensive but very efficient technology may look attractive to
manufacturers because the value of the fuel savings is sufficiently
high to both counteract the higher cost of the technology and,
implicitly, satisfy consumer demand to balance price increases with
reductions in operating cost. Similarly, technologies for which there
exist consumer welfare losses (discussed in Section II.E) will be seen
as less attractive to manufacturers who may be concerned about their
ability to recover the full amount of the technology cost during the
sale of the vehicle. The model continues to add technology until a
manufacturer either: (a) Reaches compliance with regulatory standards
(possibly through the accumulation and application of overcompliance
credits), (b) reaches a point at which it is more cost effective to pay
penalties than to add more technology (for CAFE), or (c) reaches a
point beyond compliance where the manufacturer assumes its consumers
will be unwilling to pay for additional fuel saving/emissions reducing
technologies.
In general, the model adds technology for several reasons but
checks these sequentially. The model then applies any ``forced''
technologies. Currently, only VVT is forced to be applied to vehicles
at redesign since it is the root of the engine path and the reference
point for all future engine technology applications.\347\ The model
next applies any inherited technologies that were applied to a leader
vehicle and carried forward into future model years where follower
vehicles (on the shared system) are freshened or redesigned (and thus
eligible to receive the updated version of the shared component). In
practice, very few vehicle models enter without VVT, so inheritance is
typically the first step in the compliance loop. Then the model
evaluates the manufacturer's compliance status, applying all cost-
effective technologies regardless of compliance status (essentially any
technology for which the effective cost is negative). Then the model
applies expiring overcompliance credits (if allowed to under the
perspective of either the ``unconstrained'' or ``standard setting''
analysis, for CAFE purposes). At this point, the model checks the
manufacturer's compliance status again. If the manufacturer is still
not compliant (and is unwilling to pay civil penalties, again for
CAFE), the model will add technologies that are not cost-effective
until the manufacturer reaches compliance. If the manufacturer exhausts
opportunities to comply with the standard by improving fuel economy/
reducing emissions (typically due to a limited percentage of its fleet
being redesigned in that year), the model will apply banked CAFE or
CO2 credits to offset the remaining deficit. If no credits
exist to offset the remaining deficit, the model will reach back in
time to alter technology solutions in earlier model years.
---------------------------------------------------------------------------
\347\ As a practical matter, this affects very few vehicles.
More than 95% of vehicles in the market file either already have VVT
present or have surpassed the basic engine path through the
application of hybrids or electric vehicles.
---------------------------------------------------------------------------
The CAFE model implements multi-year planning by looking back,
rather than forward. When a manufacturer is unable to comply through
cost-effective (i.e., producing effective cost values less than zero)
technology improvements or credit application in a given year, the
model will ``reach back'' to earlier years and apply the most cost-
effective technologies that were not applied at that time and then
carry those technologies forward into the future and re-evaluate the
manufacturer's compliance position. The model repeats this process
until compliance in the current year is achieved, dynamically
rebuilding previous model year fleets and carrying them forward into
the future, accumulating CAFE or CO2 credits from over-
compliance with the standard wherever appropriate.
In a given model year, the model determines applicability of each
technology to each vehicle model, platform, engine, and transmission.
The compliance simulation algorithm begins the process of applying
technologies based on the CAFE or CO2 standards specified
during the current model year. This involves repeatedly evaluating the
degree of noncompliance, identifying the next ``best'' technology
(ranked by the effective cost discussed earlier) available on each of
the parallel technology paths described above and applying the best of
these. The algorithm combines some of the pathways, evaluating them
sequentially instead of in parallel, in order to ensure appropriate
incremental progression of technologies.
The algorithm first finds the best next applicable technology in
each of the technology pathways then selects the
[[Page 43175]]
best among these. For CAFE purposes, the model applies the technology
to the affected vehicles if a manufacturer is either unwilling to pay
penalties or if applying the technology is more cost-effective than
paying penalties. Afterwards, the algorithm reevaluates the
manufacturer's degree of noncompliance and continues application of
technology. Once a manufacturer reaches compliance (i.e., the
manufacturer would no longer need to pay penalties), the algorithm
proceeds to apply any additional technology determined to be cost-
effective (as discussed above). Conversely, if a manufacturer is
assumed to prefer to pay penalties, the algorithm only applies
technology up to the point where doing so is less costly than paying
penalties. The algorithm stops applying additional technology to this
manufacturer's products once no more cost-effective solutions are
encountered. This process is repeated for each manufacturer present in
the input fleet. It is then repeated again for each model year. Once
all model years have been processed, the compliance simulation
algorithm concludes. The process for CO2 standard compliance
simulation is similar, but without the option of penalty payment.
(a) Compliance Example
The following example will illustrate the features discussed above
for the CAFE program. While the example describes the actions that
General Motors takes to modify the Chevrolet Equinox in order to comply
with the augural standards (the baseline in this analysis), and the
logical consequences of these actions, a similar example would develop
if instead simulating compliance with the EPA standards for those
years. The structure of GM's fleet and the mechanisms at work in the
CAFE model are identical in both cases, but different features of each
program (unlimited credit transfers between fleets, for example) would
likely cause the model to choose different technology solutions.
At the start of the simulation in MY 2016, GM has 30 unique engines
shared across over 33 unique nameplates, 260 model variants, and three
regulatory classes. As discussed earlier, the CAFE model will attempt
to preserve that level of sharing across GM's fleets to avoid
introducing additional production complexity for which the agencies do
not estimate additional costs. An even smaller number of transmissions
(16) and platforms (12) are shared across the same set of nameplates,
model variants, and regulatory classes.
The Chevrolet Equinox is represented in the model inputs as a
single nameplate, with five model variants distinguished by the
presence of all-wheel drive and four distinct powertrain configurations
(two engines paired with two different transmissions). Across all five
model variants, GM produced above 220,000 units of the Equinox
nameplate. About 150,000 units of that production volume is regulated
as Domestic Passenger Car, with the remainder regulated as Light
Trucks. The easiest way to describe the actions taken by the CAFE model
is to focus on a single model variant of the Equinox (one row in the
market data file). The model variant of the Equinox with the highest
production volume, about 130,000 units in MY 2016, is vehicle code
110111.\348\ This unique model variant is the basis for the example.
However, because it is only one of five variants on the Equinox
nameplate, the modifications made to that model in the simulation will
affect the rest of the Equinox variants and other vehicles across all
fleets.
---------------------------------------------------------------------------
\348\ This numeric designation is not important to understand
the example but will allow an interested reader to identify the
vehicle in model outputs to either recreate the example or use it as
a template to create similar examples for other manufacturers and
vehicles.
---------------------------------------------------------------------------
The example Equinox variant is designated as an engine and platform
leader. As discussed earlier, this implies that modifications to its
engine (11031, a 2.4L I-4) are tied to the redesign cadence of this
Equinox, as are modifications to its platform (Theta/TE). The engine is
shared by the Buick LaCrosse, Regal, and Verano, and by the GMC Terrain
(as well as appearing in two other variants of the Equinox). So those
vehicles, if redesigned after this Equinox, will inherit changes to
engine 11031 when they are redesigned, carrying the legacy version of
the engine until then. Similarly, this Equinox shares its platform with
the Cadillac SRX and GMC Terrain, which will inherit changes made to
this platform when they are redesigned (if later than the Equinox, as
is the case with the SRX).
This specific Equinox is a transmission ``follower,'' getting
updates made to its transmission leader (the Chevrolet Malibu) when it
is freshened or redesigned. Additionally, two other variants of the
Equinox nameplate (the more powerful versions, containing a 3.6L V-6
engine) are not ``leaders'' on any of the primary components. Those
variants are built on the same platform as the example Equinox variant
but share their engine with the Buick Enclave and LaCrosse, the
Cadillac SRX and XTS,\349\ the Chevrolet Colorado, Impala and Traverse
(which is the designated ``leader''), and the GMC Acadia, Canyon, and
Terrain. This is an example of how shared and inherited components
interact with product cadence: when the Equinox nameplate is
redesigned, the CAFE model has more leverage over some variants than
others and cannot make changes to the engines of the variants of the
Equinox with V-6 unless that change is consistent with all of the other
nameplates just listed. The transmissions on the other variants of the
Equinox are similarly widely shared and represent the same kind of
production constraint just described with respect to the engine. When
accounting for the full set of engines, transmissions, and platforms
represented across the Equinox nameplate's five variants, components
are shared across all three regulatory classes.
---------------------------------------------------------------------------
\349\ The agencies recognized that GM last produced the Cadillac
SRX for MY 2016, and note this as one example of the limitations of
using an analysis fleet defined in terms of even a recent actual
model year. Section II.B discusses these tradeoffs, and the
tentative judgment that, as a foundation for analysis presented
here, it was better to develop the analysis fleet using the best
information available for MY 2016 than to have used manufacturers'
CBI to construct an analysis fleet that, though more current, would
have limited the agencies' ability to make public all analytical
inputs and outputs.
---------------------------------------------------------------------------
This example uses a ``standard setting'' perspective to minimize
the amount of credit generation and application, in order to focus on
the mechanics of technology application and component sharing. The
actions taken by the CAFE model when operating on the example Equinox
during GM's compliance simulation are shown in Table-II-84. In general,
the example Equinox begins the compliance simulation with the
technology observed in its MY 2016 incarnation--a 2.6L I-4 with VVT and
SGDI, a 6-speed automatic transmission, low rolling resistance tires
(ROLL20) and a 10% realized improvement in aerodynamic drag (AERO10).
In MY 2018, the Equinox is redesigned, at which time the engine adds
VVL and level-1 turbocharging. The transmission on the Malibu is
upgraded to an 8-speed automatic in 2018, which the Equinox also gets.
The platform, for which this Equinox is the designated leader, gets
level-4 mass reduction. The CAFE model also applies a few vehicle-level
technologies: low-drag brakes, electronic accessory improvements, and
additional aerodynamic improvements (AERO20). Upon refresh in MY 2021,
it acquires an upgraded 10-speed transmission (AT10) from the Malibu.
[[Page 43176]]
Then in MY 2025 it is redesigned again and upgrades the engine to
level-2 turbocharging, replaces the 10-speed automatic transmission
with a 8-speed automatic transmission, adds a P2 strong hybrid, and
further reduces the mass of the platform (MR5). Using an
``unconstrained'' perspective would possibly lead to additional actions
taken after MY 2025, where GM may have been simulated to use credits
earned in earlier model years to offset small, persistent CAFE deficits
in one or more fleets. In the ``standard setting'' perspective, that
forces compliance without the use of CAFE credits, this is not an
issue.
[GRAPHIC] [TIFF OMITTED] TP24AU18.123
The technology applications described in Table-II-84 have
consequences beyond the single variant of the Equinox shown in the
table. In particular, two other variants of the Equinox (both of which
are regulated as Light Trucks) get the upgraded engine, which they
share with the example, in MY 2018. Thus, this application of engine
technology to a single variant of the Equinox in the Domestic Car
fleet, ``spills over'' into the Light Truck fleet, generating
improvements in fuel economy and additional costs. Furthermore, the
Buick LaCrosse and Regal, and the GMC Terrain also get the same engine,
which they share with the example, in MY 2018. Those vehicles also span
the Domestic Car and Light Truck fleets. However, the Buick Verano,
which is not redesigned until MY 2019, continues with the legacy (i.e.,
MY 2016) version of the shared engine until it is redesigned. When it
inherits the new engine in MY 2019, it does so without modification;
the engine it inherits is the same one that was redesigned in MY 2018.
This means that the Verano will improve its fuel economy in MY 2019
when the new engine is inherited but only to the extent that the new
version of the engine is an improvement over the legacy version in the
context of the Verano's other technology (which it is--the Verano moves
from 32 MPG to 44 MPG when accounting for the other technologies added
during the MY 2019 redesign).
This same story continues with the diffusion of platform
improvements simulated by the CAFE model in MY 2018. The GMC Terrain is
simulated to be redesigned in MY 2018, in conjunction with the Equinox.
The performance variants of the Equinox, with a 3.5L V-6, also upgrade
their engines in MY 2018 (in conjunction with the estimated Chevrolet
Traverse redesign). However, when the Equinox is next redesigned in MY
2025, the engine shared with the Traverse is not upgraded again until
MY 2026, so the performance versions of the Equinox continue with the
2018 version of the engine throughout the remainder of the simulation.
While these inheritances and sharing dynamics are not a perfect
representation of each manufacturer's specific constraints, nor the
flexibilities available to shift strategies in real-time as a response
to changing market or regulatory conditions, they are a reasonable way
to consider the resource constraints that prohibit fleet-wide
technology diffusion over shorter windows than have been observed
historically and for which the agencies have no way to impose
additional costs.
Aside from the technology application and its consequences
throughout the GM product portfolio, discussed above, there are other
important conclusions to draw from the technology application example.
The first of these is that product cadence matters, and only by taking
a year-by-year perspective can this be seen. When the example Equinox
[[Page 43177]]
is redesigned in MY 2018, the CAFE model takes actions that cause the
redesigned Equinox to significantly exceed its fuel economy target.
While no single vehicle has a ``standard,'' having high volume vehicles
significantly below their individual targets can present compliance
challenges for manufacturers who must compensate by exceeding targets
on other vehicles. While the example Equinox exceeds its MY 2018 target
by almost 9 mpg, this version of the Equinox is not eligible to see
significant technology changes again before MY 2025 (except for the
transmission upgrade that occurs in MY 2021). Thus, the CAFE model is
redesigning the Equinox in MY 2018 with respect to future targets and
standards--this Equinox is nearly 2 mpg below its target in MY 2024
before being redesigned in MY 2025. This reflects a real challenge that
manufacturers face in the context of continually increasing CAFE
standards, and represents a clear example of why considering two model
year snapshots where all vehicles are assumed to be redesigned is
unrealistically simplistic. The MY 2018 version of the example Equinox
persists (with little change) through six model years and the standards
present in those years. This is one reason why the CAFE model, rather
than OMEGA, was chosen to examine the impacts of the proposed standards
in this analysis.
Another feature of note in Table-II-84 is the cost of applying
these technologies. The costs are all denominated in dollars and
represent incremental cost increases relative to the MY 2016 version of
the Equinox. Aside from the cost increase of over $5,000 in MY 2025
when the vehicle is converted to a strong hybrid, the incremental
technology costs display a consistent trend between application
events--decreasing steadily over time as the cost associated with each
given combination of technologies ``learns down.'' By MY 2032, even the
most expensive version of the example Equinox costs nearly $800 less to
produce than it did in MY 2025.
The technology application in the example occurs in the context of
GM's attempt to comply with the augural standards. As some of the
components on the Equinox nameplate are shared across all three
regulated fleets, Table-II-85 shows the compliance status of each fleet
in MYs 2016-2025. In MY 2017, the CAFE model applies expiring credits
to offset deficits in the DC and LT fleets. In MY 2028, when GM is
simulated to aggressively apply technology to the example Equinox, the
DC fleet exceeds its standard while the LT fleet still generates
deficits. The CAFE model offset that deficit with expiring (and
possibly transferred) credits. However, by MY 2020 the ``standard
setting'' perspective removes the option of using CAFE credits to
offset deficits and GM exceeds the standard in all three fleets, though
by almost 2 mpg in DC and LT. As the Equinox example showed, many of
the vehicles redesigned in MY 2020 will still be produced at the MY
2020 technology level in MY 2025 where GM is simulated to comply
exactly across all three fleets. Under an ``unconstrained''
perspective, the CAFE model would use the CAFE credits earned through
over-compliance with the standards in MYs 2020-2023 to offset deficits
created by under-compliance as the standards continued to increase,
pushing some technology application until later years when the
standards stabilized and those credits expired. The CAFE model
simulates compliance through MY 2032 to account for this behavior.
[[Page 43178]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.124
(b) Representation of OEMs' Potential Responsiveness to Buyers'
Willingness To Pay for Fuel Economy Improvements
The CAFE model simulates manufacturer responses to both regulatory
standards and technology availability. In order to do so, it requires
assumptions about how the industry views consumer demand for additional
fuel economy because manufacturer responses to potential standards
depend not just on what they think they are best off producing to
satisfy regulatory requirements (considering the consequences of not
satisfying those requirements), but also on what they think they can
sell, technology-wise, to consumers. In the 2012 final rule, the
agencies analyzed alternatives under the assumption that manufacturers
would not improve the fuel economy of new vehicles at all unless
compelled to do so by the existence of increasingly stringent CAFE and
GHG standards.\350\ This ``flat baseline'' assumption led the agencies
to attribute all of the fuel savings that occurred in the simulation
after MY 2016 to the proposed standards because none of the fuel
economy improvements were considered likely to occur in the absence of
increasing standards. However, this assumption contradicted much of the
literature on this topic and the industry's recent experience with CAFE
compliance, and for CAFE standards, the analysis published in 2016
applied a reference case estimate that manufacturers will treat all
technologies that pay for themselves within the first three years
[[Page 43179]]
of ownership (through reduced expenditures on fuel) as if the cost of
that technology were negative.\351\
---------------------------------------------------------------------------
\350\ See, e.g., 75 FR 62844, 75 FR 63105.
\351\ Draft TAR, p. 13-10, available at https://www.nhtsa.gov/staticfiles/rulemaking/pdf/cafe/Draft-TAR-Final.pdf (last accessed
June 15, 2018).
---------------------------------------------------------------------------
The industry has exceeded the required CAFE level for both
passenger cars and light trucks in the past; notably, by almost 5 mpg
during the fuel price spikes of the 2000s when CAFE standards for
passenger cars were still frozen at levels established for the 1990
model year.\352\ In fact, a number of manufacturers that traditionally
paid CAFE civil penalties even reached compliance during years with
sufficiently high fuel prices.\353\ The model attempts to account for
this observed consumer preference for fuel economy, above and beyond
that required by the regulatory standards, by allowing fuel price to
influence the ranking of technologies that the model considers when
modifying a manufacturer's fleet in order to achieve compliance. In
particular, the model ranks available technology not by cost, but by
``effective cost.''
---------------------------------------------------------------------------
\352\ NHTSA, Summary of Fuel Economy Performance, 2014,
available at https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/performance-summary-report-12152014-v2.pdf (last accessed June 27,
2018).
\353\ Ibid. Additional data available at https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Mfr_LIVE.html (last accessed June 27, 2018).
---------------------------------------------------------------------------
When the model chooses which technology to apply next, it
calculates the effective cost of available technologies and chooses the
technology with the lowest effective cost. The ``effective cost''
itself is a combination of the technology cost, the fuel savings that
would occur if that technology were applied to a given vehicle, the
resulting change in CAFE penalties (as appropriate), and the affected
volumes. User inputs determine how much fuel savings manufacturers
believe new car buyers will pay for (denominated in the number of years
before a technology ``pays back'' its cost).
Because the civil penalty provisions specified for CAFE in EPCA do
not apply to CO2 standards, the effective cost calculation
applied when simulating compliance with CO2 standards uses
an estimate of the potential value of CO2 credits. Including
a valuation of CO2 credits in the effective cost metric
provides a potential basis for future explicit modeling of credit
trading.\354\ Manufacturers, though, have thus far declined to disclose
the actual terms of CAFE or CO2 credit trades, so this
calculation currently uses the CAFE civil penalty rate as the basis to
estimate this value. It seems reasonable to assume that the CAFE civil
penalty rate likely sets an effective ceiling on the price of any
traded CAFE credits, and considering that each manufacturer can only
produce one fleet of vehicles for sale in the U.S., prices of
CO2 credits might reasonably be expected to be equivalent to
prices of CAFE credits. However, the current CAFE model does not
explicitly simulate credit trading; therefore, the change in the value
of CO2 credits should only capture the change in
manufacturer's own cost of compliance, so the compliance simulation
algorithm applies a ceiling at 0 (zero) to each calculated value of the
CO2 credits.\355\
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\354\ By treating all passenger cars and light trucks as being
manufactured by a single ``OEM,'' inputs to the CAFE model can be
structured to simulate perfect trading. However, competitive and
other factors make perfect trading exceedingly unlikely, and future
efforts will focus consideration on more plausible imperfect
trading.
\355\ Having the model continue to add technology in order to
build a surplus of credits as warranted by the estimated (whether
specified as a model input or calculated dynamically as a clearing
price) market value of credits would provide part of the basis for
having the model build the supply side of an explicitly-simulated
credit trading market.
---------------------------------------------------------------------------
Just as manufacturers' actual approaches to vehicle pricing are
closely held, manufacturers' actual future approaches to making
decisions about technology are not perfectly knowable. The CAFE model
is intended to illustrate ways manufacturers could respond to
standards, given a set of production constraints, not to predict how
they will respond. Alternatives to these ``effective cost'' metrics
have been considered and will continue to be considered. For example,
instead of using a dollar value, the model could use a ratio, such as
the net cost (technology cost minus fuel savings) of an application of
technology divided by corresponding quantity of avoided fuel
consumption or CO2 emissions. Any alternative metric has the
potential to shift simulated choices among technology application
options, and some metrics would be less suited to the CAFE model's
consideration of multiyear product planning, or less adaptable than
others to any future simulation of credit trading. Comment is sought
regarding the definition and application of criteria to select among
technology options and determine when to stop applying technology
(consider not only standards, but also factors such as fuel prices,
civil penalties for CAFE, and the potential value of credits for both
programs), and this aspect of the model may be further revised. Any
future revision to the effective cost would be considered in light of
manufacturers different compliance positions relative to the standards,
and in light of the likelihood that some OEMs will continue to use
civil penalties as a means to resolve CAFE deficits (at least for some
fleets).
While described in greater detail in the CAFE model documentation,
the effective cost reflects an assumption not about consumers' actual
willingness to pay for additional fuel economy but about what
manufacturers believe consumers are willing to pay. The reference case
estimate for today's analysis is that manufacturers will treat all
technologies that pay for themselves within the first 2\1/2\ years of
ownership (through reduced expenditures on fuel) as if the cost of that
technology were negative. Manufacturers have repeatedly indicated to
the agencies that new vehicle buyers are only willing to pay for fuel
economy-improving technology if it pays back within the first two to
three years of vehicle ownership.\356\ NHTSA has therefore incorporated
this assumption (of willingness to pay for technology that pays back
within 30 months) into today's analysis. Alternatives to this 30-month
estimate are considered in the sensitivity analysis included in today's
notice. In the current version of the model, this assumption holds
whether or not a manufacturer has already achieved compliance. This
means that the most cost-effective technologies (those that pay back
within the first 2\1/2\ years) are applied to new vehicles even in the
absence of regulatory pressure. However, because the value of fuel
savings depends upon the price of fuel, the model will add more
technology even without regulatory pressure when fuel prices are high
compared to simulations where fuel prices are assumed to be low. This
assumption is consistent with observed historical compliance behavior
(and consumer demand for fuel economy in the new vehicle market), as
discussed above.
---------------------------------------------------------------------------
\356\ This is supported by the 2015 NAS study, which found that
consumers seek to recoup added upfront purchasing costs within two
or three years. See 2015 NAS Report, at pg. 317.
---------------------------------------------------------------------------
One implication of this assumption is that futures with higher, or
lower, fuel prices produce different sets of attractive technologies
(and at different times). For example, if fuel prices were above $7/
gallon, many of the technologies in this analysis could pay for
themselves within the first year or two and would be applied at high
rates in all of the alternatives. Similarly, at the other extreme
(significantly reduced fuel prices), almost no additional fuel economy
would be observed.
[[Page 43180]]
While these assumptions about desired payback period and consumer
preferences for fuel economy may not affect the eventual level of
achieved CAFE and CO2 emissions in the later years of the
program, they will affect the amount of additional technology cost and
fuel savings that are attributable to the standard. The approach
currently only addresses the inherent trade-off between additional
technology cost and the value of fuel savings, but other costs could be
relevant as well. Further research would be required to support
simulations that assume buyers behave as if they consider all ownership
costs (e.g., additional excise taxes and insurance costs) at the time
of purchase and that manufacturers respond accordingly. Comment is
sought on the approach described above, the current values ascribed to
manufacturers' belief about consumer willingness-to-pay for fuel
economy, and practicable suggestions for future improvements and
refinements, considering the model's purpose and structure.
(c) Representation of Some OEMs' Willingness To Treat Civil Penalties
as a Program Flexibility
When considering technology applications to improve fleet fuel
economy, the model will add technology up to the point at which the
effective cost of the technology (which includes technology cost,
consumer fuel savings, consumer welfare changes, and the cost of
penalties for non-compliance with the standard) is less costly than
paying civil penalties or purchasing credits. Unlike previous versions
of the model, the current implementation further acknowledges that some
manufacturers experience transitions between product lines where they
rely heavily on credits (either carried forward from earlier model
years or acquired from other manufacturers) or simply pay penalties in
one or more fleets for some number of years. The model now allows the
user to specify, when appropriate for the regulatory program being
simulated, on a year-by-year basis, whether each manufacturer should be
considered as willing to pay penalties for non-compliance. This
provides additional flexibility, particularly in the early years of the
simulation. As discussed above, this assumption is best considered as a
method to allow a manufacturer to under-comply with its standard in
some model years--treating the civil penalty rate and payment option as
a proxy for other actions it may take that are not represented in the
CAFE model (e.g., purchasing credits from another manufacturer, carry-
back from future model years, or negotiated settlements with NHTSA to
resolve deficits).
In the current analysis, NHTSA has relied on past compliance
behavior and certified transactions in the credit market to designate
some manufacturers as being willing to pay CAFE penalties in some model
years. The full set of assumptions regarding manufacturer behavior with
respect to civil penalties is presented in Table-II-86, which shows all
manufacturers are assumed to be willing to pay civil penalties prior to
MY 2020. This is largely a reflection of either existing credit
balances (which manufacturers will use to offset CAFE deficits until
the credits reach their expiration dates) or assumed trades between
manufacturers that are likely to happen in the near-future based on
previous behavior. The manufacturers in the table whose names appear in
bold all had at least one regulated fleet (of three) whose CAFE was
below its standard in MY 2016. Because the analysis began with the MY
2016 fleet, and no technology can be added to vehicles that are already
designed and built, all manufacturers can generate civil penalties in
MY 2016. However, once a manufacturer is designated as unwilling to pay
penalties, the CAFE model will attempt to add technology to the
respective fleets to avoid shortfalls.
[GRAPHIC] [TIFF OMITTED] TP24AU18.125
[[Page 43181]]
Several of the manufacturers in Table-II-86 that are assumed to be
willing to pay civil penalties in the early years of the program have
no history of paying civil penalties. However, several of those
manufacturers have either bought or sold credits--or transferred
credits from one fleet to another to offset a shortfall in the
underperforming fleet. As the CAFE model does not simulate credit
trades between manufacturers, providing this additional flexibility in
the modeling avoids the outcome where the CAFE model applies more
technology than would be needed in the context of the full set of
compliance flexibilities at the industry level. By statute, NHTSA
cannot consider credit flexibilities when setting standards, so most
manufacturers (those without a history of civil penalty payment) are
assumed to comply with their standard through fuel economy improvements
for the model years being considered in this analysis. The notable
exception to this is FCA, who we expect will still satisfy the
requirements of the program through a combination of credit application
and civil penalties through MY 2025 before eventually complying
exclusively through fuel economy improvements in MY 2026.
As mentioned above, the CAA does not provide civil penalty
provisions similar to those specified in EPCA/EISA, and the above-
mentioned corresponding inputs apply only to simulation of compliance
with CAFE standards.
(d) Representation of CAFE and CO2 Credit Provisions
The model's approach to simulating compliance decisions accounts
for the potential to earn and use CAFE credits as provided by EPCA/
EISA. The model similarly accumulates and applies CO2
credits when simulating compliance with EPA's standards. Like past
versions, the current CAFE model can be used to simulate credit carry-
forward (a.k.a. banking) between model years and transfers between the
passenger car and light truck fleets but not credit carry-back (a.k.a.
borrowing) from future model years or trading between manufacturers.
Some manufacturers have made occasional use of credit carry-back
provisions, although the analysis does not assume use of carry-back as
a compliance strategy because of the risk in relying on future
improvements to offset earlier compliance deficits. Thus far, NHTSA has
not attempted to include simulation of credit carry-back or trading in
the CAFE model. Unlike past versions, the current CAFE model provides a
basis to specify (in model inputs) CAFE credits available from model
years earlier than those being simulated explicitly. For example, with
this analysis representing model years 2016-2032 explicitly, credits
earned in model year 2012 are made available for use through model year
2017 (given the current five-year limit on carry-forward of credits).
The banked credits are specific to both model year and fleet in which
they were earned. Comment and supporting information are invited
regarding whether and, if so, how the CAFE model and inputs might
practicably be modified to account for trading of credits between
manufacturers and/or carry-back of credits from later to earlier model
years.
As discussed in the CAFE model documentation, the model's default
logic attempts to maximize credit carry-forward--that is, to ``hold
on'' to credits for as long as possible. If a manufacturer needs to
cover a shortfall that occurs when insufficient opportunities exist to
add technology in order to achieve compliance with a standard, the
model will apply credits. Otherwise it carries forward credits until
they are about to expire, at which point it will use them before adding
technology that is not considered cost-effective. The model attempts to
use credits that will expire within the next three years as a means to
smooth out technology application over time to avoid both compliance
shortfalls and high levels of over-compliance that can result in a
surplus of credits. As further discussed in the CAFE model
documentation, model inputs can be used to adjust this logic to shift
the use of credits ahead by one or more model years. In general, the
logic used to generate credits and apply them to compensate for
compliance shortfalls, both in a given fleet and across regulatory
fleets, is an area that requires more attention in the next phase of
model development. While the current model correctly accounts for
credits earned when a manufacturer exceeds its standard in a given
year, the strategic decision of whether to earn additional credits to
bank for future years (in the current fleet or to transfer into another
regulatory fleet) and when to optimally apply them to deficits is
challenging to simulate. This will be an area of focus moving forward.
NHTSA introduced the CAFE Public Information Center \357\ to
provide public access to a range of information regarding the CAFE
program, including manufacturers' credit balances. However, there is a
data lag in the information presented on the CAFE PIC that may not
capture credit actions across the industry for as much as several
months. Additionally, CAFE credits that are traded between
manufacturers are adjusted to preserve the gallons saved that each
credit represents.\358\ The adjustment occurs at the time of
application rather than at the time the credits are traded. This means
that a manufacturer who has acquired credits through trade, but has not
yet applied them, may show a credit balance that is either considerably
higher or lower than the real value of the credits when they are
applied. For example, a manufacturer that buys 40 million credits from
Tesla, may show a credit balance in excess of 40 million. However, when
those credits are applied, they may be worth only 1/10 as much--making
that manufacturer's true credit balance closer to 4 million than 40
million.
---------------------------------------------------------------------------
\357\ CAFE Public Information Center, http://www.nhtsa.gov/CAFE_PIC/CAFE_PIC_Home.htm (last visited June 22, 2018).
\358\ GHG credits for EPA's program are denominated in metric
tons of CO2 rather than gram/mile compliance credits and
require no adjustment when traded between manufacturers or fleets.
---------------------------------------------------------------------------
Having reviewed credit balances (as of October 23, 2017) and
estimated the potential that some manufacturers could trade credits,
NHTSA developed inputs that make carried-forward credits available as
summarized in Table-II-87, Table-II-88, and Table-II-89, after
subtracting credits assumed to be traded to other manufacturers, adding
credits assumed to be acquired from other manufacturers through such
trades, and adjusting any traded credits (up or down) to reflect their
true value for the fleet and model year into which they were
traded.\359\ While the CAFE model will transfer expiring credits into
another fleet (e.g., moving expiring credits from the domestic car
credit bank into the light truck fleet), some of these credits were
moved in the initial banks to improve the efficiency of application and
to better reflect both the projected shortfalls of each manufacturer's
regulated fleets, and to represent observed behavior. For context, a
manufacturer that produces one million vehicles in a given fleet, and
experiences a shortfall of 2 mpg, would need 20 million credits to
completely offset the shortfall.
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\359\ The adjustments, which are based upon the standard, CAFE
and year of both the party originally earning the credits and the
party applying them, were implemented assuming the credits would be
applied to the model year in which they were set to expire. For
example, credits traded into a domestic passenger car fleet for MY
2014 were adjusted assuming they would be applied in the domestic
passenger car fleet for MY 2019.
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[[Page 43182]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.126
[GRAPHIC] [TIFF OMITTED] TP24AU18.127
[[Page 43183]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.128
In addition to the inclusion of these existing credit banks, the
CAFE model also updated its treatment of credits in the rulemaking
analysis. Congress has declared that NHTSA set CAFE standards at
maximum feasible levels for each model year under consideration without
consideration of the program's credit mechanisms. However, as CAFE
rulemakings have evaluated longer time periods in recent years, the
early actions taken by manufacturers required more nuanced
representation. Therefore, the CAFE model now allows a ``last year to
consider credits,'' set at the last year for which new standards are
not being considered (MY 2019 in this analysis). This allows the model
to replicate the practical application of existing credits toward CAFE
compliance in early years but to examine the impact of proposed
standards based solely on fuel economy improvements in all years for
which new standards are being considered. Comment is sought regarding
the model's representation of the CAFE and CO2 credit
provisions, recommendations regarding any other options, and any
information that could help to refine the current approach or develop
and implement an alternative approach.
The CAFE model has also been modified to include a similar
representation of existing credit banks in EPA's CO2
program. While the life of a CO2 credit, denominated in
metric tons CO2, has a five-year life, matching the lifespan
of CAFE credits, credits earned in the early years of the EPA program,
MY 2009-2011, may be used through MY 2021.\360\ The CAFE model was not
modified to allow exceptions to the life-span of compliance credits
treating them all as if they may be carried forward for no more than
five years, so the initial credit banks were modified to anticipate the
years in which those credits might be needed. The fact that MY 2016 is
simulated explicitly prohibited the inclusion of these banked credits
in MY 2016 (which could be carried forward from MY 2016 to MY 2021),
and thus underestimates the extent to which individual manufacturers,
and the industry as a whole, may rely on these early credits to comply
with EPA standards between MY 2016 and MY 2021. The credit banks with
which the simulations in this analysis were conducted are presented in
the following tables:
---------------------------------------------------------------------------
\360\ In response to comments, EPA placed limits on credits
earned in MY 2009, causing them to expire prior to this rule.
However, credits generated in MYs 2010-2011 may be carried forward,
or traded, and applied to deficits generated through MY 2021.
[[Page 43184]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.129
[GRAPHIC] [TIFF OMITTED] TP24AU18.130
While the CAFE model does not simulate the ability to trade credits
between manufacturers, it does simulate the strategic accumulation and
application of compliance credits, as well as the ability to transfer
credits between fleets to improve the compliance position of a less
efficient fleet by leveraging credits earned by a
[[Page 43185]]
more efficient fleet. The model prefers to hold on to earned compliance
credits within a given fleet, carrying them forward into the future to
offset potential future deficits. This assumption is consistent with
observed strategic behavior dating back to 2009.
From 2009 to present, no manufacturer has transferred CAFE credits
into a fleet to offset a deficit in the same year in which they were
earned. This has occurred with credits acquired from other
manufacturers via trade but not with a manufacturer's own credits.
Therefore, the current representation of credit transfers between
fleets--where the model prefers to transfer expiring, or soon-to-be-
expiring credits rather than newly earned credits--is both appropriate
and consistent with observed industry behavior.
This may not be the case for GHG standards, though it is difficult
to be certain at this point. The GHG program seeded the industry with a
large quantity of early compliance credits (earned in MYs 2009-2011
\361\) prior to the existence formal standards of the EPA program.
These early credits do not expire until 2021. So, for manufacturers
looking to offset deficits, it is more sensible to use current-year
credits that expire in the next five years, rather than draw down the
bank of credits that can be used until MY 2021. The first model year
for which earned credits outlive the initial bank is MY 2017, for which
final compliance actions and deficit resolutions are still pending.
Regardless, in order to accurately represent some of the observed
behavior in the GHG credit system, the CAFE model allows (and
encourages) within-year transfers between regulated fleets for the
purpose of simulating compliance with the GHG standards.
---------------------------------------------------------------------------
\361\ In response to public comment, EPA eliminated the use of
credits earned in MY 2009 for future model years. However, credits
earned in MY 2010 and MY 2011 remain.
---------------------------------------------------------------------------
In addition to more rigorous accounting of CAFE and CO2
credits, the model now also accounts for air conditioning efficiency
and off-cycle adjustments. NHTSA's program considers those adjustments
in a manufacturer's compliance calculation starting in MY 2017, and the
current model uses the adjustments claimed by each manufacturer in MY
2016 as the starting point for all future years. Because the air
conditioning and off-cycle adjustments are not credits in NHTSA's
program, but rather adjustments to compliance fuel economy (much like
the Flexible Fuel Vehicle adjustments that are due to phase out in MY
2019), they may be included under either a ``standard setting'' or
``unconstrained'' analysis perspective.
When the CAFE model simulates EPA's program, the treatment of A/C
efficiency and off-cycle credits is similar, but the model also
accounts for A/C leakage (which is not part of NHTSA's program). When
determining the compliance status of a manufacturer's fleet (in the
case of EPA's program, PC and LT are the only fleet distinctions), the
CAFE model weighs future compliance actions against the presence of
existing (and expiring) CO2 credits resulting from over-
compliance with earlier years' standards, A/C efficiency credits, A/C
leakage credits, and off-cycle credits.
5. Impacts on Each OEM and Overall Industry
(a) Technology Application and Penetration Rates
The CAFE model tracks and reports technology application and
penetration rates for each manufacturer, regulatory class, and model
year, calculated as the volume of vehicles with a given technology
divided by the total volume. The ``application rate'' accounts only for
those technologies applied by the model during the compliance
simulation, while the ``penetration rate'' accounts for the total
percentage of a technology present in a given fleet, whether applied by
the CAFE model or already present at the start of the simulation.
In addition to the aggregate representation of technology
penetration, the model also tracks each individual vehicle model on
which it has operated. Each row in the market data file (the
representation of vehicles offered for sale in MY 2016 in the U.S.,
discussed in detail in Section II.B.a and PRIA Chapter 6) contains a
record for every model year and every alternative, that identifies with
which technologies the vehicle started the simulation, which
technologies were applied, and whether those technologies were applied
directly or through inheritance (discussed above). Interested parties
may use these outputs to assess how the compliance simulation modified
any vehicle that was offered for sale in MY 2016 in response to a given
regulatory alternative.
(b) Required and Achieved CAFE and Average CO2 Levels
The model fully represents the required CAFE (and now,
CO2) levels for every manufacturer and every fleet. The
standard for each manufacturer is based on the harmonic average of
footprint targets (by volume) within a fleet, just as the standards
prescribe. Unlike earlier versions of the CAFE model, the current
version further disaggregates passenger cars into domestic and imported
classes (which manufacturers report to NHTSA and EPA as part of their
CAFE compliance submissions). This allows the CAFE model to more
accurately estimate the requirement on the two passenger car fleets,
represent the domestic passenger car floor (which must be exceeded by
every manufacturer's domestic fleet, without the use of credits, but
with the possibility of civil penalty payment), and allows it to
enforce the transfer cap limit that exists between domestic and
imported passenger cars, all for purposes of the CAFE program.
In calculating the achieved CAFE level, the model uses the
prescribed harmonic average of fuel economy ratings within a vehicle
fleet. Under an ``unconstrained'' analysis, or in a model year for
which standards are already final, it is possible for a manufacturer's
CAFE to fall below its required level without generating penalties
because the model will apply expiring or transferred credits to
deficits if it is strategically appropriate to do so. Consistent with
current EPA regulations, the model applies simple (not harmonic)
production-weighted averaging to calculate average CO2
levels.
(c) Costs
For each technology that the model adds to a given vehicle, it
accumulates cost. The technology costs are defined incrementally and
vary both over time and by technology class, where the same technology
may cost more to apply to larger vehicles as it involves more raw
materials or requires different specifications to preserve some
performance attributes. While learning-by-doing can bring down cost,
and should reasonably be implemented in the CAFE model as a rate of
cost reduction that is applied to the cumulative volume of a given
technology produced by either a single manufacturer or the industry as
a whole, in practice this notion is implemented as a function of time,
rather than production volume. Thus, depending upon where a given
technology starts along its learning curve, it may appear to be cost-
effective in later years where it was not in earlier years. As the
model carries forward technologies that it has already applied to
future model years, it similarly adjusts the costs of those
technologies based on their individual learning rates.
[[Page 43186]]
The other costs that manufacturers incur as a result of CAFE
standards are civil penalties resulting from non-compliance with CAFE
standards. The CAFE model accumulates costs of $5.50 per 1/10-MPG under
the standard, multiplied by the number of vehicles produced in that
fleet, in that model year. The model reports as the full ``regulatory
cost,'' the sum of total technology cost and total fines by the
manufacturer, fleet, and model year. As mentioned above, the relevant
EPCA/EISA provisions do not also appear in the CAA, so this option and
these costs apply only to simulated compliance with CAFE standards.
(d) Sales
In all previous versions of the CAFE model, the total number of
vehicles sold in any model year, in fact the number of each individual
vehicle model sold in each year, has been a static input that did not
vary in response to price increases induced by CAFE standards, nor
changes in fuel prices, or any other input to the model. The only way
to alter sales, was to update the entire forecast in the market input
file. However, in the 2012 final rule, NHTSA included a dynamic fleet
share model that was based on a module in the Energy Information
Administration's NEMS model. This fleet share model did not change the
size of the new vehicle fleet in any year, but it did change the share
of new vehicles that were classified as passenger cars (or light
trucks). That capability was not included in the central analysis but
was included in the uncertainty analysis, which looked at the baseline
and preferred alternative in the context of thousands of possible
future states of the world. As some of those futures contained extreme
cases of fuel prices, it was important to ensure consistent modeling
responses within that context. For example, at a gasoline price of $7/
gallon, it would be unrealistic to expect the new vehicle market's
light truck share to be the same as the future where gasoline cost $2/
gallon. The current model has slightly modified, and fully integrated,
the dynamic fleet share model. Every regulatory alternative and
sensitivity case considered in this analysis reflects a dynamically
responsive fleet mix in the new vehicle market.
While the dynamic fleet share model adjusts unit sales across body
styles (cars, SUVs, and trucks), it does not modify the total number of
new vehicles sold in a given year. The CAFE model now includes a
separate function to account for changes in the total number of new
vehicles sold in a given year (regardless of regulatory class or body
style), in response to certain macroeconomic inputs and changes in the
average new vehicle price. The price impact is modest relative to the
influence of the macroeconomic factors in the model. The combination of
these two models modify the total number of new vehicles, the share of
passenger cars and light trucks, and, as a consequence, the number of
each given model sold by a given manufacturer. However, these two
factors are insufficient to cause large changes to the composition of
any of a manufacturer's fleets. In order to significantly change the
mix of models produced within a given fleet, the CAFE model would
require a way to trade off the production of one vehicle versus another
both within a manufacturer's fleet and across the industry. While NHTSA
has experimented with fully-integrated consumer choice models, their
performance has yet to satisfy the requirements of a rulemaking
analysis.
There are multiple levels of sales impacts that could result from
increasing the prices of new vehicles across the industry. Any estimate
of impacts at the manufacturer, or model, level would be subject to an
assumed pricing strategy that spreads technology cost increases across
available models in a way that may cross-subsidize specific models or
segments at the expense of others. However, at the industry level, it
is reasonable to assume that all incremental technology costs can be
captured by the average price of a new vehicle. To the extent that this
factor influences the total number of new vehicles sold in a given
model year, it can be included in an empirical model of annual sales.
However, there is limited historical evidence that the average price of
a new vehicle is a strong determining factor in the total number of
annual new vehicle sales.
6. National Impacts
(a) Vehicle Stock and Fleet Turnover
The CAFE model carries a complete representation of the registered
vehicle population in each calendar year, starting with an aggregated
version of the most recent available data about the registered
population for the first year of the simulation. In this analysis, the
first model year considered is MY 2016, and the registered vehicle
population enters the model as it appeared at the end of calendar year
2015. The initial vehicle population is stratified by age (or model
year cohort) and regulatory class--to which the CAFE model assigns
average fuel economies based on the reported regulatory class industry
average compliance value in each model year (and class). Once the
simulation begins, new vehicles are added to the population from the
market data file and age throughout their useful lives during the
simulation, with some fraction of them being retired (or scrapped)
along the way. For example, in calendar year 2017, the new vehicles
(age zero) are MY 2017 vehicles (added by the CAFE model simulation and
represented at the same level of detail used to simulate compliance),
the age one vehicles are MY 2016 vehicles (added by the CAFE model
simulation), and the age two vehicles are MY 2015 vehicles (inherited
from the registered vehicle population and carried through the analysis
with less granularity). This national registered fleet is used to
calculate annual fuel consumption, vehicle miles traveled (VMT),
pollutant emissions, and safety impacts under each regulatory
alternative.
In addition to dynamically modifying the total number of new
vehicles sold, a dynamic model of vehicle retirement, or scrappage, has
also been implemented. The model implements the scrappage response by
defining the instantaneous scrappage rate at any age using two
functions. For ages less than 20, instantaneous scrappage is defined as
a function of vehicle age, new vehicle price, cost per mile of driving
(the ratio of fuel price and fuel economy), and a small number of
macroeconomic factors. For ages greater than 20, the instantaneous
scrappage rate is a simple exponential function of age. While the
scrappage response does not affect manufacturer compliance
calculations, it impacts the lifetime mileage accumulation (and thus
fuel savings) of all vehicles. Previous CAFE analyses have focused
exclusively on new vehicles, tracing the fuel consumption and social
costs of these vehicles throughout their useful lives; the scrappage
effect also impacts the registered vehicle fleet that exists when a set
of standards is implemented.
As new vehicles enter the registered population their retirement
rates are governed by the scrappage model, so are the vehicles already
registered at the start of model year 2016. To the extent that a given
set of CAFE or CO2 standards accelerates or decelerates the
retirement of those vehicles, additional fuel consumption and social
costs may accrue to those vehicles under that standard. The CAFE model
accounts for those costs and benefits, as well as tracking all of the
standard benefits and costs associated with the lifetimes of new
vehicles produced under the rule. For more detail about the derivation
of the scrappage functions, see Section
[[Page 43187]]
II.E, and PRIA Chapter 8. Comment is sought on the specification and
inclusion of these factors in the current model.
(b) Highway Travel
In support of prior CAFE rulemakings, the CAFE model accounted for
new travel that results from fuel economy improvements that reduce the
cost of driving. The magnitude of the increase in travel demand is
determined by the rebound effect. In both previous versions and the
current version of the CAFE model, the amount of travel demanded by the
existing fleet of vehicles is also responsive to the rebound effect
(representing the price elasticity of demand for travel)--increasing
when fuel prices decrease relative to the fuel price when the VMT on
which our mileage accumulation schedules were built was observed. Since
the fuel economy of those vehicles is already fixed, only the fuel
price influences their travel demand relative to the mileage
accumulation schedule and so is identical for all regulatory
alternatives.
While the average mileage accumulation per vehicle by age is not
influenced by the rebound effect in a way that differs by regulatory
alternative, three other factors influence total VMT in the model in a
way that produces different total mileage accumulation by regulatory
alternative. The first factor is the total industry sales response: New
vehicles are both driven more than older vehicles and are more fuel
efficient (thus producing more rebound miles). To the extent that more
(or fewer) of these new models enter the vehicle fleet in each model
year, total VMT will increase (or decrease) as a result. The second
factor is the dynamic fleet share model. The fleet share influences not
only the fuel economy distribution of the fleet, as light trucks are
less efficient than passenger cars on average, but the total miles are
influenced by fact that light trucks are driven more than passenger
cars as well. Both of the first two factors can magnify the influence
of the rebound effect on vehicles that go through the compliance
simulation (MY 2016-2032) in the manner discussed above and in Section
II.E. The third factor influencing total annual VMT is the scrappage
model. By modifying the retirement rates of on-road vehicles under each
regulatory alternative, the scrappage model either increases or
decreases the lifetime miles that accrue to vehicles in a given model
year cohort.
(c) Fuel Consumption and GHG Emissions
For every vehicle model in the market file, the model estimates the
VMT per vehicle (using the assumed VMT schedule, the vehicle fuel
economy, fuel price, and the rebound assumption). Those miles are
multiplied by the volume for each vehicle. Fuel consumption is the
product of miles driven and fuel economy, which can be tracked by model
year cohort in the model. Carbon dioxide emissions from vehicle
tailpipes are the simple product of gallons consumed and the carbon
content of each gallon.
In order to calculate calendar year fuel consumption, the model
needs to account for the inherited on-road fleet in addition to the
model year cohorts affected by this proposed rule. Using the VMT of the
average passenger car and light truck from each cohort, the model
computes the fuel consumption of each model year class of vehicles for
its age in a given CY. The sum across all ages (and thus, model year
cohorts) in a given CY provides estimated CY fuel consumption.
Rather than rely on the compliance values of fuel economy for
either historical vehicles or vehicles that go through the full
compliance simulation, the model applies an ``on-road gap'' to
represent the expected difference between fuel economy on the
laboratory test cycle and fuel economy under real-world operation. This
was a topic of interest in the recent peer review of the CAFE model.
While the model currently allows the user to specify an on-road gap
that varies by fuel type (gasoline, E85, diesel, electricity, hydrogen,
and CNG), it does not vary over time, by vehicle age, or by technology
combination. It is possible that the ``gap'' between laboratory fuel
economy and real-world fuel economy has changed over time, that fuel
economy degrades over time as a vehicle ages, or that specific
combinations of fuel-saving technologies have a larger discrepancy
between laboratory and real-world fuel economy than others. Further
research would be required to determine whether the model should
include a functional representation of the on-road gap to address these
various factors, and comment is sought on the data sources and
implementation strategies available to do so.
Because the model produces an estimate of the aggregate number of
gallons sold in each CY, it is possible to calculate both the total
expenditures on motor fuel and the total contribution to the Highway
Trust Fund (HTF) that result from that fuel consumption. The Federal
fuel excise tax is levied on every gallon of gasoline and diesel sold
in the U.S., with diesel facing a higher per-gallon tax rate. The model
uses a national perspective, where the state taxes present in the input
files represent an estimated average fuel tax across all U.S. states.
Accordingly, while the CAFE model cannot reasonably estimate potential
losses to state fuel tax revenue from increasingly the fuel economy of
new vehicles, it can do so for the HTF, and the agencies invite comment
on the proposed standards' implications for the HTF.
In addition to the tailpipe emissions of carbon dioxide, each
gallon of gasoline produced for consumption by the on-road fleet has
associated ``upstream'' emissions that occur in the extraction,
transportation, refining, and distribution of the fuel. The model
accounts for these emissions as well (on a per-gallon basis) and
reports them accordingly.
(d) Criteria Pollutant Emissions
The CAFE model uses the entire on-road fleet, calculated VMT
(discussed above), and emissions factors (which are an input to the
CAFE model, specified by model year and age) to calculate tailpipe
emissions associated with a given alternative. Just as it does for
additional GHG emissions associated with upstream emissions from fuel
production, the model captures criteria pollutants that occur during
other parts of the fuel life cycle. While this is typically a function
of the number of gallons of gasoline consumed (and miles driven, for
tailpipe criteria pollutant emissions), the CAFE model also estimates
electricity consumption and the associated upstream emissions (resource
extraction and generation, based on U.S. grid mix).
(e) Highway Fatalities
Earlier versions of the CAFE model accounted for the safety impacts
associated with reducing vehicle mass in order to improve fuel economy.
In particular, NHTSA's safety analysis estimated the additional
fatalities that would occur as a result of new vehicles getting
lighter, then interacting with the on-road vehicle population. In
general, taking mass out of the heaviest new vehicles improved safety
outcomes, while taking mass from the lightest new vehicles resulted in
a greater number of expected highway fatalities. However, the change in
fatalities did not adequately account for changes in exposure that
occur as a result of increased demand for travel as vehicles become
cheaper to operate. The current version of the model resolves that
[[Page 43188]]
limitation and addresses additional sources of fatalities that can
result from the implementation of CAFE or CO2 standards.
These are discussed in greater detail in Section 0 and PRIA Chapter 11.
NHTSA has observed that older vehicles in the population are
responsible for a disproportionate number of fatalities, both by number
of registrations and by number of miles driven. Accordingly, any factor
that causes the population of vehicles to turn over more slowly will
induce additional fatalities--as those older vehicles continue to be
driven, rather than being retired and replaced with newer (even if not
brand new) vehicle models. The scrappage effect, which delays (or
accelerates) the retirement of registered vehicles, impacts the number
of fatalities through this mechanism--importantly affecting not just
new vehicles sold from model years 2016-2032 but existing vehicles that
are already part of the on-road fleet. Similarly, to the extent that a
CAFE or CO2 alternative reduces new vehicle sales, it can
slow the transition from older vehicles to newer vehicles, reducing the
share of total vehicle miles that are driven by newer, more
technologically advanced vehicles. Accounting for the change in vehicle
miles traveled that occurs when vehicles become cheaper to operate has
led to a number of fatalities that can be attributed to the rebound
effect, independent of any changes to new vehicle mass, price, or
longevity.
The CAFE model now estimates fatalities by combining the effects
discussed above. In particular, the model estimates the fatality rate
per billion miles VMT for each model year vehicle in the population
(the newest of which are the new vehicles produced that model year).
This estimate is independent of regulatory class and varies only by
year (and not vehicle age). The estimated fatality rate is then
multiplied by the estimated VMT for each vehicle in the population and
the product of the change in curb weight and the relevant safety
coefficient, as in the equation below.
[GRAPHIC] [TIFF OMITTED] TP24AU18.131
For the vehicles in the historical fleet, meaning all those
vehicles that are already part of the registered vehicle population in
CY 2016, only the model year effect that determines the
``FatalityEstimate'' is relevant. However, each vehicle that is
simulated explicitly by the CAFE model, and is eligible to receive mass
reduction technologies, must also consider the change between its curb
weight and the threshold weights that are used to define safety
classes. For vehicles above the threshold, reducing vehicle mass can
have a smaller negative impact on fatalities (or even reduce
fatalities, in the case of the heaviest light trucks). The
``ChangePer100Lbs'' depends upon this difference. The sum of all
estimated fatalities for each model year vehicle in the on-road fleet
determines the reported fatalities, which can be summarized by either
model year or calendar year.
(f) Costs and Benefits
As the CAFE model simulates manufacturer compliance with regulatory
alternatives, it estimates and tracks a number of consequences that
generate social costs. The most obvious cost associated with the
program is the cost of additional fuel economy improving/CO2
emissions reducing technology that is added to new vehicles as a result
of the rule. However, the model does not inherently draw a distinction
between costs and benefits. For example, the model tracks fuel
consumption and the dollar value of fuel consumed. This is the cost of
travel under a given alternative (including the baseline). The ``cost''
or ``benefit'' associated with the value of fuel consumed is determined
by the reference point against which each alternative is considered.
The CAFE model reports absolute values for the amount of money spent on
fuel in the baseline, then reports the amount spent on fuel in the
alternatives relative to the baseline. If the baseline standard were
fixed at the current level, and an alternative achieves 100 mpg by
2025, the total expenditures on fuel in the alternative would be lower,
creating a fuel savings ``benefit.'' This analysis uses a baseline that
is more stringent than each alternative considered, so the incremental
fuel expenditures are greater for the alternatives than for the
baseline.
Other social costs and benefits emerge as the result of physical
phenomena, like tailpipe emissions or highway fatalities, which are the
result of changes in the composition and use of the on-road fleet. The
social costs associated with those quantities represent an economic
estimate of the social damages associated with the changes in each
quantity. The model tracks and reports each of these quantities by:
Model year and vehicle age (the combination of which can be used to
produce calendar year totals), regulatory class, fuel type, and social
discount rate.
The full list of potential costs and benefits is presented in
Table-II-92 as well as the population of vehicles that determines the
size of the factor (either new vehicles or all registered vehicles) and
the mechanism that determines the size of the effect (whether driven by
the number of miles driven, the number of gallons consumed, or the
number of vehicles produced).
[[Page 43189]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.132
III. Proposed CAFE and CO2 Standards for MYs 2021-2026
A. Form of the Standards
NHTSA and EPA are proposing that the form of the CAFE and
CO2 standards for MYs 2021-2026 would follow the form of
those standards in prior model years. NHTSA has specific statutory
requirements for the form of CAFE standards: Specifically, EPCA, as
amended by EISA, requires that CAFE standards be issued separately for
passenger cars and light trucks, and that each standard be specified as
a mathematical function expressed in terms of one or more vehicle
attributes related to fuel economy. Although the CAA does not have
comparable specific requirements for the form of CO2
standards for light-duty vehicles, EPA has concluded that it is
appropriate to set CO2 standards according to vehicle
footprint, consistent with the EPCA/EISA requirements, which simplifies
compliance for the industry.\362\
---------------------------------------------------------------------------
\362\ Such an approach is permissible under section 202(a) of
the CAA and EPA has used the attribute-based approach in issuing
standards under analogous provisions of the CAA.
---------------------------------------------------------------------------
For MYs since 2011 for CAFE and since 2012 for CO2,
standards have taken the form of fuel economy and CO2
targets expressed as functions of vehicle footprint (the product of
vehicle wheelbase and average track width). NHTSA and EPA continue to
believe that footprint is the most appropriate attribute on which to
base the proposed standards, as discussed in Section II.C. Under the
footprint-based standards, the function defines a CO2 or
fuel economy performance target for each unique footprint combination
within a car or truck model type. Using the functions, each
manufacturer thus will have a CAFE and CO2 average standard
for each year that is unique to each of its fleets,\363\ depending on
the footprints and production volumes of the vehicle models produced by
that manufacturer. A manufacturer will have separate footprint-based
standards for cars and for trucks. The functions are mostly sloped, so
that generally, larger vehicles (i.e., vehicles with larger footprints)
will be subject to lower CAFE mpg targets and higher CO2
grams/mile targets than smaller vehicles. This is because, generally
speaking, smaller vehicles are more capable of achieving higher levels
of fuel economy/lower levels of CO2 emissions, mostly
because they tend not to have to work as hard to perform their driving
task. Although a manufacturer's fleet average standards could be
estimated throughout the model year based on the projected production
volume of its vehicle fleet (and are estimated as part of EPA's
certification process), the standards to which the manufacturer must
comply will be determined by its final model year production figures. A
manufacturer's calculation of its fleet average standards as well as
its fleets' average performance at the end of the model year will thus
be based on the production-weighted average target and performance of
each model in its fleet.\364\
---------------------------------------------------------------------------
\363\ EPCA/EISA requires NHTSA to separate passenger cars into
domestic and import passenger car fleets whereas EPA combines all
passenger cars into one fleet.
\364\ As in prior rulemakings, a manufacturer may have some
vehicle models that exceed their target and some that are below
their target. Compliance with a fleet average standard is determined
by comparing the fleet average standard (based on the production-
weighted average of the target levels for each model) with fleet
average performance (based on the production-weighted average of the
performance of each model).
---------------------------------------------------------------------------
For passenger cars, consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as follows:
[[Page 43190]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.133
Where:
TARGETFE is the fuel economy target (in mpg) applicable to a
specific vehicle model type with a unique footprint combination,
a is a minimum fuel economy target (in mpg),
b is a maximum fuel economy target (in mpg),
c is the slope (in gallons per mile per square foot, or gpm, per
square foot) of a line relating fuel consumption (the inverse of
fuel economy) to footprint, and
d is an intercept (in gpm) of the same line.
Here, MIN and MAX are functions that take the minimum and maximum
values, respectively, of the set of included values. For example,
MIN[40,35] = 35 and MAX(40, 25) = 40, such that MIN[MAX(40, 25), 35] =
35.
For light trucks, also consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as follows:
[GRAPHIC] [TIFF OMITTED] TP24AU18.134
Where:
TARGETFE is the fuel economy target (in mpg) applicable to a
specific vehicle model type with a unique footprint combination,
a, b, c, and d are as for passenger cars, but taking values specific
to light trucks,
e is a second minimum fuel economy target (in mpg),
f is a second maximum fuel economy target (in mpg),
g is the slope (in gpm per square foot) of a second line relating
fuel consumption (the inverse of fuel economy) to footprint, and
h is an intercept (in gpm) of the same second line.
Although the general model of the target function equation is the
same for each vehicle category (passenger cars and light trucks) and
each model year, the parameters of the function equation differ for
cars and trucks. For MYs 2020-2026, the parameters are unchanged,
resulting in the same stringency in each of those model years.
Mathematical functions defining the proposed CO2 targets
are expressed as functions that are similar, with coefficients a-h
corresponding to those listed above.\365\ For passenger cars, EPA is
proposing to define CO2 targets as follows:
---------------------------------------------------------------------------
\365\ EPA regulations use a different but mathematically
equivalent approach to specify targets. Rather than using a function
with nested minima and maxima functions, EPA regulations specify
requirements separately for different ranges of vehicle footprint.
Because these ranges reflect the combined application of the listed
minima, maxima, and linear functions, it is mathematically
equivalent and more efficient to present the targets as in this
Section.
TARGETCO2 = MIN[b,MAX[a,c x FOOTPRINT + d]]
Where:
TARGETCO2 is the CO2 target (in grams per mile, or g/mi)
applicable to a specific vehicle model configuration,
a is a minimum CO2 target (in g/mi),
b is a maximum CO2 target (in g/mi),
c is the slope (in g/mi, per square foot) of a line relating
CO2 emissions to footprint, and
d is an intercept (in g/mi) of the same line.
For light trucks, CO2 targets are defined as follows:
TARGETCO2 = MIN[MIN[b, MAX[a,c x FOOTPRINT + d]], MIN[f,MAX[e, g x
FOOTPRINT + H]]
Where:
TARGETCO2 is the CO2 target (in g/mi) applicable to a
specific vehicle model configuration,
a, b, c, and d are as for passenger cars, but taking values specific
to light trucks,
e is a second minimum CO2 target (in g/mi),
f is a second maximum CO2 target (in g/mi),
g is the slope (in g/mi per square foot) of a second line relating
CO2 emissions to footprint, and
h is an intercept (in g/mi) of the same second line.
To be clear, as has been the case since the agencies began
establishing attribute-based standards, no vehicle need meet the
specific applicable fuel economy or CO2 targets, because
compliance with either CAFE or CO2 standards is determined
based on corporate average fuel economy or fleet average CO2
emission rates. The required CAFE level applicable to a given fleet in
a given model year is determined by calculating the production-weighted
harmonic average of fuel economy targets applicable to specific vehicle
model configurations in the fleet, as follows:
[GRAPHIC] [TIFF OMITTED] TP24AU18.135
Where:
CAFErequired is the CAFE level the fleet is required to achieve,
i refers to specific vehicle model/configurations in the fleet,
PRODUCTIONi is the number of model configuration i produced for sale
in the U.S., and
TARGETFE,i the fuel economy target (as defined above) for model
configuration i.
Similarly, the required average CO2 level applicable to
a given fleet in a given model year is determined by calculating the
production-weighted
[[Page 43191]]
average (not harmonic) of CO2 targets applicable to specific
vehicle model configurations in the fleet, as follows:
[GRAPHIC] [TIFF OMITTED] TP24AU18.136
Where:
CO2required is the average CO2 level the fleet is
required to achieve,
i refers to specific vehicle model/configurations in the fleet,
PRODUCTIONi is the number of model configuration i produced for sale
in the U.S., and
TARGETCO2,i is the CO2 target (as defined above) for
model configuration i.
Today's action would set standards that only apply to fuel economy
and CO2. EPA seeks comment on this approach.
Comment is sought on the proposed standards and on the analysis
presented here; we seek any relevant data and information and will
review responses. That review could lead to selection of one of the
other regulatory alternatives for the final rule.
B. Passenger Car Standards
For passenger cars, NHTSA and EPA are proposing CAFE and
CO2 standards, respectively, for MYs 2021-2026 that are
defined by the following coefficients:
[GRAPHIC] [TIFF OMITTED] TP24AU18.137
Section II.C above discusses in detail how the coefficients in
Table III-1 were developed for this proposal. The coefficients result
in the footprint-dependent targets shown graphically below for MYs
2021-2026. The MYs 2017-2020 standards are also shown for comparison.
[[Page 43192]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.138
[[Page 43193]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.139
While we do not know yet with certainty what CAFE and
CO2 levels will ultimately be required of individual
manufacturers, because those levels will depend on the mix of vehicles
that they produce for sale in future model years, based on the market
forecast of future sales that was used to examine today's proposed
standards, we currently estimate that the target functions shown above
would result in the following average required fuel economy and
CO2 emissions levels for individual manufacturers during MYs
2021-2026. Prior to MY 2021, average required CO2 levels
reflect underlying target functions (specified above) that reflect the
use of automotive refrigerants with reduced global warming potential
(GWP) and/or the use of technologies that reduce the refrigerant leaks.
EPA is proposing to exclude air conditioning refrigerants and leakage,
and nitrous oxide and methane GHGs from average performance
calculations after model year 2020; CO2 targets and
resultant fleet average requirements for model years 2021 and beyond do
not reflect these adjustments.
---------------------------------------------------------------------------
\366\ Prior to MY 2021, CO2 targets include
adjustments reflecting the use of automotive refrigerants with
reduced global warming potential (GWP) and/or the use of
technologies that reduce the refrigerant leaks and optionally
nitrous oxide and methane emissions. EPA is proposing to exclude air
conditioning refrigerants and leakage, and nitrous oxide and methane
GHGs from average performance calculations after model year 2020;
CO2 targets (and resultant fleet average requirements)
for model years 2021 and beyond do not reflect these adjustments.
---------------------------------------------------------------------------
EPA seeks comments on whether to proceed with this proposal to
discontinue accounting for A/C leakage, methane emissions, and nitrous
oxide emissions as part of the CO2 emissions standards to
provide for better harmony with the CAFE program, or whether to
continue to consider these factors toward compliance and retain that as
a feature that differs between the programs. A/C leakage credits, which
are accounted for in the baseline model, have been extensively
generated by manufacturers, and make up a portion of their compliance
with EPA's CO2 standards. In the 2016 MY, manufacturers
averaged six grams per mile equivalent in A/C leakage credits, ranging
from three grams per mile equivalent for Hyundai and Kia, to 17 grams
per mile equivalent for Jaguar Land Rover.\367\ As related to methane
(CH4) and nitrous oxide (N2O) emissions,
manufacturers averaged 0.1 grams per mile equivalent in deficits for
the 2016 MY, with deficits ranging from 0.1 grams per mile equivalent
for GM, Mazda, and Toyota, to 0.6 grams per mile equivalent for
Nissan.\368\
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\367\ Other manufacturers' A/C leakage credit grams per mile
equivalent include: BMW, Honda, Mistubishi, Nissan, Toyota, and
Volkswagen at 5 g/mi; Mercedes at 6 g/mi; Ford, GM, and Volvo at 7
g/mi; and FCA at 14 g/mi.
\368\ Other manufacturers' methane and nitrous oxide deficit
grams per mile equivalent include BMW at 0.2 g/mi, and Ford at 0.3
g/mi. FCA and Volkswagen numbers are not reported due to an ongoing
investigation and/or corrective actions.
---------------------------------------------------------------------------
EPA notes that since the 2010 rulemaking on this subject, the
agencies have accounted for the ability to apply A/C leakage credits by
increasing EPA's CO2 standard stringency by the average
anticipated amount of credits when compared to the CAFE stringency
requirements.\369\ For model years 2021-2025, the A/C leakage offset,
or
[[Page 43194]]
equivalent stringency increase compared to the CAFE standard, is 13.8
g/mi equivalent for passenger cars and 17.2 g/mi equivalent for light
trucks.\370\ For those model years, manufacturers are currently allowed
to apply A/C leakage credits capped at 18.8 g/mi equivalent for
passenger cars and 24.4 g/mi equivalent for light trucks.\371\
---------------------------------------------------------------------------
\369\ 75 FR 25330, May 7, 2010.
\370\ 77 FR 62805, Oct. 15, 2012.
\371\ 77 FR 62649, Oct. 15, 2012.
---------------------------------------------------------------------------
For methane and nitrous oxide emissions, as part of the MY 2012-
2016 rulemaking, EPA finalized standards to cap emissions of
N2O at 0.010 g/mile and CH4 at 0.030 g/mile for
MY 2012 and later vehicles.\372\ However, EPA also provided an optional
CO2-equivalent approach to address industry concerns about
technological feasibility and leadtime for the CH4 and
N2O standards for MY 2012-2016 vehicles. The CO2
equivalent standard option allowed manufacturers to fold all 2-cycle
weighted N2O and CH4 emissions, on a
CO2-equivalent basis, along with CO2, into their
CO2 emissions fleet average compliance level.\373\ EPA
estimated that on a CO2 equivalent basis, folding in all
N2O and CH4 emissions could add up to 3-4 g/mile
to a manufacturer's overall CO2 emissions level because the
equivalent standard must be used for the entire fleet, not just for
``problem vehicles.'' \374\ To address this added difficulty, EPA
amended the MY 2012-2016 standards to allow manufacturers to use
CO2 credits, on a CO2-equivalent basis, to meet
the light-duty N2O and CH4 standards in those
model years. EPA subsequently extended that same credit provision to MY
2017 and later vehicles. EPA seeks comment on whether to change
existing methane and nitrous oxide standards that were finalized in the
2012 rule. Specifically, EPA seeks information from the public on
whether the existing standards are appropriate, or whether they should
be revised to be less stringent or more stringent based on any updated
data.
---------------------------------------------------------------------------
\372\ 75 FR 25421-24, May 7, 2010.
\373\ 77 FR 62798, Oct. 15, 2012.
\374\ In the final rule for MYs 2012-2016, EPA acknowledged that
advanced diesel or lean-burn gasoline vehicles of the future may
face greater challenges meeting the CH4 and
N2O standards than the rest of the fleet. [See 75 FR
25422, May 7, 2010].
---------------------------------------------------------------------------
If the agency moves forward with its proposal to eliminate these
factors, EPA would consider whether it is appropriate to initiate a new
rulemaking to regulate these programs independently, which could
include an effective date that would result in no lapse in regulation
of A/C leakage or emissions of nitrous oxide and methane. If the agency
decides to retain the A/C leakage and nitrous oxide and methane
emissions provisions for CO2 compliance, it would likely re-
insert the current A/C leakage offset and increase the stringency
levels for CO2 compliance by the offset amounts described
above (i.e., 13.8 g/mi equivalent for passenger cars and 17.2 g/mi
equivalent for light trucks), and retain the current caps (i.e., 18.8
g/mi equivalent for passenger cars and 24.4 g/mi equivalent for light
trucks). The agency will publish an analysis of this alternative
approach in a memo to the docket for this rulemaking. The agency seeks
comment on whether the current offsets and caps would continue to be
appropriate in such circumstances or whether changes are warranted.
[GRAPHIC] [TIFF OMITTED] TP24AU18.140
We emphasize again that the values in these tables are estimates,
and not necessarily the ultimate levels with which each of these
manufacturers will have to comply, for the reasons described above.
C. Minimum Domestic Passenger Car Standards
EPCA has long required manufacturers to meet the passenger car CAFE
standard with both their domestically-manufactured and imported
passenger car fleets--that is, domestic and imported passenger car
fleets must comply separately with the passenger car CAFE standard in
each model year.\375\ In doing so, they may use whatever flexibilities
are available to them under the CAFE program, such as using credits
``carried forward'' from prior model years, transferred from another
fleet, or acquired from another manufacturer. On top of this
requirement, EISA expressly requires each manufacturer to meet a
minimum flat fuel economy standard for domestically manufactured
passenger cars.\376\ According to the statute, the minimum standard
shall be the greater of (A) 27.5 miles per gallon; or (B) 92% of the
average fuel economy projected by DOT for the combined domestic and
[[Page 43195]]
nondomestic passenger automobile fleets manufactured for sale in the
United States by all manufacturers in the model year, which projection
shall be published in the Federal Register when the standard for that
model year is promulgated.\377\ NHTSA discusses this requirement in
more detail in Section V.A.1 below.
---------------------------------------------------------------------------
\375\ 49 U.S.C. 32904(b) (2007).
\376\ Transferred or traded credits may not be used, pursuant to
49 U.S.C. 32903(g)(4) and (f)(2), to meet the domestically
manufactured passenger automobile minimum standard specified in 49
U.S.C. 32902(b)(4) and in 49 CFR 531.5(d).
\377\ 49 U.S.C. 32902(b)(4).
---------------------------------------------------------------------------
The following table lists the proposed minimum domestic passenger
car standards (which very likely will be updated for the final rule as
the agency updates its overall analysis and resultant projection),
highlighted as ``Preferred (Alternative 3)'' and calculates what those
standards would be under the no action alternative (as issued in 2012,
and as updated by today's analysis) and under the other alternatives
described and discussed further in Section IV, below.
[GRAPHIC] [TIFF OMITTED] TP24AU18.141
D. Light Truck Standards
For light trucks, NHTSA and EPA are proposing CAFE and
CO2 standards, respectively, for MYs 2021-2026 that are
defined by the following coefficients:
[GRAPHIC] [TIFF OMITTED] TP24AU18.142
[[Page 43196]]
Section II.C above discusses in detail how the coefficients in
Table III-4 were developed for this proposal. The coefficients result
in the footprint-dependent targets shown graphically below for MYs
2021-2026. The MYs 2017-2020 standards are also shown for comparison.
---------------------------------------------------------------------------
\378\ Prior to MY 2021, average achieved CO2 levels
include adjustments reflecting the use of automotive refrigerants
with reduced global warming potential (GWP) and/or the use of
technologies that reduce the refrigerant leaks. Because EPA is today
proposing to exclude air conditioning refrigerants and leakage, and
nitrous oxide and methane GHGs from average performance calculations
after MY 2020, CO2 targets and resultant fleet average
requirements for MYs 2021 and beyond do not reflect these
adjustments.
[GRAPHIC] [TIFF OMITTED] TP24AU18.143
[GRAPHIC] [TIFF OMITTED] TP24AU18.144
[[Page 43197]]
While we do not know yet with certainty what CAFE and
CO2 levels will ultimately be required of individual
manufacturers, because those levels will depend on the mix of vehicles
that they produce for sale in future model years, based on the market
forecast of future sales that were used to examine today's proposed
standards, we currently estimate that the target functions shown above
would result in the following average required fuel economy and
CO2 emissions levels for individual manufacturers during MYs
2021-2026. Prior to MY 2021, average required CO2 levels
reflect underlying target functions (specified above) that reflect the
use of automotive refrigerants with reduced global warming potential
(GWP) and/or the use of technologies that reduce the refrigerant leaks.
Because EPA is today proposing to exclude air conditioning refrigerants
and leakage, and nitrous oxide and methane GHGs from average
performance calculations after model year 2020, CO2 targets
and resultant fleet average requirements for model years 2021 and
beyond do not reflect these adjustments.
[GRAPHIC] [TIFF OMITTED] TP24AU18.146
We emphasize again the values in these tables are estimates and not
necessarily the ultimate levels with which each of these manufacturers
will have to comply for reasons described above.
IV. Alternative CAFE and GHG Standards Considered for MYs 2021/22-2026
Agencies typically consider regulatory alternatives in proposals as
a way of evaluating the comparative effects of different potential ways
of accomplishing their desired goal.\379\ Alternatives analysis begins
with a ``no-action'' alternative, typically described as what would
occur in the absence of any regulatory action. Today's proposal
includes a no-action alternative, described below, as well as seven
``action alternatives'' besides the proposal. The proposal may, in
places, be referred to as the ``preferred alternative,'' which is NEPA
parlance, but NHTSA and EPA intend ``proposal,'' ``proposed action,''
and ``preferred alternative'' to be used interchangeably for purposes
of this rulemaking.
---------------------------------------------------------------------------
\379\ As Section V.A.3 explains, NEPA requires agencies to
compare the potential environmental impacts of their proposed
actions to those of a reasonable range of alternatives. Executive
Orders 12866 and 13563 and OMB Circular A-4 also encourage agencies
to evaluate regulatory alternatives in their rulemaking analyses.
---------------------------------------------------------------------------
As discussed above in Chapter II, today's notice also presents the
results of analysis estimating impacts under a range of other
regulatory alternatives the agencies are considering. Aside from the
no-action alternative, NHTSA and EPA defined the different regulatory
alternatives in terms of percent-increases in CAFE and GHG stringency
from year to year. Under some alternatives, the rate of increase is the
same for both passenger cars and light trucks; under others, the rate
of increase differs. Two alternatives also involve a gradual
discontinuation of CAFE and average GHG adjustments reflecting the
application of technologies that improve air conditioner efficiency or,
in other ways, improve fuel economy under conditions not represented by
long-standing fuel economy test procedures. For increased harmonization
with NHTSA CAFE standards, which cannot account for such issues, under
Alternatives 1-8, EPA would regulate tailpipe CO2
independently of A/C refrigerant leakage, nitrous oxide and methane
emissions. Under the no action alternative, EPA would continue to
regulate A/C refrigerant leakage, nitrous oxide and methane emissions
under the overall CO2 standard.\380\ Like the baseline no-
action alternative, all of the alternatives are more stringent than the
preferred alternative.
---------------------------------------------------------------------------
\380\ For the CAFE program, carbon-based tailpipe emissions
(including CO2, CH4 and CO) are measured, and
fuel economy is calculated using a carbon balance equation. EPA uses
carbon-based emissions (CO2, CH4 and CO, the
same as for CAFE) to calculate tailpipe CO2 for its
standards. In addition, under the no action alternative EPA adds
CO2 equivalent (using Global Warming Potential (GWP)
adjustment) for AC refrigerant leakage and nitrous oxide and methane
emissions. The CAFE program does not include A/C refrigerant
leakage, nitrous oxide and methane emissions because they do not
impact fuel economy. Under Alternatives 1-8, the standards are
completely aligned for gasoline because compliance is based on
tailpipe CO2, CH4 and CO for both programs and
not emissions unrelated to fuel economy. Diesel and alternative fuel
vehicles would continue to be treated differently between the CAFE
and CO2 programs. While harmonization would be
significantly improved, standards would not be fully aligned because
of the small fraction of the fleet that uses diesel and alternative
fuels (e.g., about four percent of the MY 2016 fleet), as well as
differences involving EPCA/EISA provisions EPA, lacking any specific
direction under the CAA, has declined to adopt, such as minimum
standards for domestic passenger cars and limits on credit transfers
between regulated fleets.
---------------------------------------------------------------------------
EPA also seeks comment on retaining the existing credit program for
regulation of A/C refrigerant leakage, nitrous oxide, and methane
emissions as part of the CO2 standard.
The agencies have examined these alternatives because the agencies
intend to continue considering them as options for the final rule. The
agencies seek comment on these alternatives and on the analysis
presented here, seek any relevant data and information, and will review
responses. That review could lead the agencies to select one of the
[[Page 43198]]
other regulatory alternatives for the final rule.
A. What alternatives did NHTSA and EPA consider?
The table below shows the different alternatives evaluated in this
proposal.
[GRAPHIC] [TIFF OMITTED] TP24AU18.147
Also, as mentioned previously in Section III.B., EPA seeks comments
on whether to proceed with this proposal to discontinue accounting for
A/C leakage, methane emissions, and nitrous oxide emissions as part of
the CO2 emissions standards to provide for better harmony
with the CAFE program or whether to continue to consider these factors
toward compliance and retain that as a feature that differs between the
programs. EPA seeks comment on whether to change existing methane and
nitrous oxide standards that were finalized in the 2012 rule.
Specifically, EPA seeks information from the public on whether the
existing standards are appropriate, or whether they should be
[[Page 43199]]
revised to be less stringent or more stringent based on any updated
data.
---------------------------------------------------------------------------
\381\ Carbon dioxide equivalent of air conditioning refrigerant
leakage, nitrous oxide and methane emissions are included for
compliance with the EPA standards for all MYs under the baseline/no
action alternative. Carbon dioxide equivalent is calculated using
the Global Warming Potential (GWP) of each of the emissions.
\382\ Beginning in MY 2021, air conditioning refrigerant
leakage, nitrous oxide, and methane emissions may be regulated
independently by EPA. The GWP equivalent of each of the emissions
would no longer be included with the tailpipe CO2 for
compliance with tailpipe CO2 standards. A lengthier
discussion of this issue can be found in Section III.B.
---------------------------------------------------------------------------
Additionally, the agencies note that this proposal also seeks
comment on a number of additional compliance flexibilities for the
programs. See Section X below, and EPA specifically draws attention the
discussion of ``enhanced flexibilities'' in Section X.C.
B. Definition of Alternatives
1. No-Action Alternative
The No-Action Alternative applies the augural CAFE and final GHG
targets announced in 2012 for MYs 2021-2025. For MY 2026, this
alternative applies the same targets as for MY 2025. Carbon dioxide
equivalent of air conditioning refrigerant leakage, nitrous oxide, and
methane emissions are included for compliance with the EPA standards
for all model years under the baseline/no action alternative.
[GRAPHIC] [TIFF OMITTED] TP24AU18.148
[GRAPHIC] [TIFF OMITTED] TP24AU18.149
2. Alternative 1 (Proposed)
Alternative 1 holds the stringency of targets constant and MY 2020
levels through MY 2026. Beginning in MY 2021, air conditioning
refrigerant leakage, nitrous oxide, and methane emissions are no longer
included with the tailpipe CO2 for compliance with tailpipe
CO2 standards. Section III, above, defines this alternative
in greater detail.
3. Alternative 2
Alternative 2 increases the stringency of targets annually during
MYs 2021-2026 (on a gallon per mile basis, starting from MY 2020) by
0.5% for passenger cars and 0.5% for light trucks. Section III
describes the proposed standards included in the preferred alternative.
Beginning in MY 2021, air conditioning refrigerant leakage, nitrous
oxide, and methane emissions are no longer included with the tailpipe
CO2 for compliance with tailpipe CO2 standards.
[[Page 43200]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.150
4. Alternative 3
Alternative 3 phases out A/C and off-cycle adjustments and
increases the stringency of targets annually during MYs 2021-2026 (on a
gallon per mile basis, starting from MY 2020) by 0.5% for passenger
cars and 0.5% for light trucks. The cap on adjustments for AC
efficiency improvements declines from 6 grams per mile in MY 2021 to 5,
4, 3, 2, and 0 grams per mile in MYs 2022, 2023, 2024, 2025, and 2026,
respectively. The cap on adjustments for off-cycle improvements
declines from 10 grams per mile in MY 2021 to 8, 6, 4, 2, and 0 grams
per mile in MYs 2022, 2023, 2024, 2025, and 2026, respectively.
Beginning in MY 2021, air conditioning refrigerant leakage, nitrous
oxide, and methane emissions are no longer included with the tailpipe
CO2 for compliance with tailpipe CO2 standards.
[[Page 43201]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.151
5. Alternative 4
Alternative 4 increases the stringency of targets annually during
MYs 2021-2026 (on a gallon per mile basis, starting from MY 2020) by
1.0% for passenger cars and 2.0% for light trucks. Beginning in MY
2021, air conditioning refrigerant leakage, nitrous oxide, and methane
emissions are no longer included with the tailpipe CO2 for
compliance with tailpipe CO2 standards.
[[Page 43202]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.152
6. Alternative 5
Alternative 5 increases the stringency of targets annually during
MYs 2022-2026 (on a gallon per mile basis, starting from MY 2021) by
1.0% for passenger cars and 2.0% for light trucks. Beginning in MY
2021, air conditioning refrigerant leakage, nitrous oxide, and methane
emissions are no longer included with the tailpipe CO2 for
compliance with tailpipe CO2 standards, and MY 2021
CO2 targets are adjusted accordingly.
[[Page 43203]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.153
7. Alternative 6
Alternative 6 increases the stringency of targets annually during
MYs 2021-2026 (on a gallon per mile basis, starting from MY 2020) by
2.0% for passenger cars and 3.0% for light trucks. Beginning in MY
2021, air conditioning refrigerant leakage, nitrous oxide, and methane
emissions are no longer included with the tailpipe CO2 for
compliance with tailpipe CO2 standards.
[[Page 43204]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.154
8. Alternative 7
Alternative 7 phases out A/C and off-cycle adjustments and
increases the stringency of targets annually during MYs 2021-2026 (on a
gallon per mile basis, starting from MY 2020) by 1.0% for passenger
cars and 2.0% for light trucks. The cap on adjustments for AC
efficiency improvements declines from 6 grams per mile in MY 2021 to 5,
4, 3, 2, and 0 grams per mile in MYs 2022, 2023, 2024, 2025, and 2026,
respectively. The cap on adjustments for off-cycle improvements
declines from 10 grams per mile in MY 2021 to 8, 6, 4, 2, and 0 grams
per mile in MYs 2022, 2023, 2024, 2025, and 2026, respectively.
Beginning in MY 2021, air conditioning refrigerant leakage, nitrous
oxide, and methane emissions are no longer included with the tailpipe
CO2 for compliance with tailpipe CO2 standards.
[[Page 43205]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.155
9. Alternative 8
Alternative 8 increases the stringency of targets annually during
MYs 2022-2026 (on a gallon per mile basis, starting from MY 2021) by
2.0% for passenger cars and 3.0% for light trucks. Beginning in MY
2021, air conditioning refrigerant leakage, nitrous oxide, and methane
emissions are no longer included with the tailpipe CO2 for
compliance with tailpipe CO2 standards, and MY 2021
CO2 targets are adjusted accordingly.
[[Page 43206]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.156
V. Proposed Standards, the Agencies' Statutory Obligations, and Why the
Agencies Propose To Choose Them Over the Alternatives
A. NHTSA's Statutory Obligations and Why the Proposed Standards Appear
to be Maximum Feasible
1. EPCA, as Amended by EISA
EPCA, as amended by EISA, contains a number of provisions regarding
how NHTSA must set CAFE standards. NHTSA must establish separate CAFE
standards for passenger cars and light trucks \383\ for each model
year,\384\ and each standard must be the maximum feasible that NHTSA
believes the manufacturers can achieve in that model year.\385\ In
determining the maximum feasible level achievable by the manufacturers,
EPCA requires that NHTSA consider the four statutory factors of
technological feasibility, economic practicability, the effect of other
motor vehicle standards of the Government on fuel economy, and the need
of the United States to conserve energy.\386\ In addition, NHTSA has
the authority to (and traditionally does) consider other relevant
factors, such as the effect of the CAFE standards on motor vehicle
safety and consumer preferences.\387\ The ultimate determination of
what standards can be considered maximum feasible involves a weighing
and balancing of these factors, and the balance may shift depending on
the information before NHTSA about the expected circumstances in the
model years covered by the rulemaking. The agency's decision must also
support the overarching purpose of EPCA, energy conservation, while
balancing these factors.\388\
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\383\ 49 U.S.C. 32902(b)(1) (2007).
\384\ 49 U.S.C. 32902(a) (2007).
\385\ Id.
\386\ 49 U.S.C. 32902(f) (2007).
\387\ Both of these additional considerations also relate, to
some extent, to economic practicability, but NHTSA also has the
authority to consider them independently of that statutory factor.
\388\ Center for Biological Diversity v. NHTSA, 538 F. 3d 1172,
1197 (9th Cir. 2008) (``Whatever method it uses, NHTSA cannot set
fuel economy standards that are contrary to Congress' purpose in
enacting the EPCA--energy conservation.'')
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Besides the requirement that the standards be maximum feasible for
the fleet in question and the model year in question, EPCA/EISA also
contain
[[Page 43207]]
several other requirements as explained below.
(a) Lead Time
EPCA requires that NHTSA prescribe new CAFE standards at least 18
months before the beginning of each model year.\389\ For light-duty
vehicles, NHTSA has consistently interpreted the ``beginning of each
model year'' as September 1 of the CY prior, such that the beginning of
MY 2019 would be September 1, 2018. Thus, if the first year for which
NHTSA is proposing to set new standards in this NPRM is MY 2022, NHTSA
interprets this provision as requiring us to issue a final rule
covering MY 2022 standards no later than April 1, 2020.
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\389\ 49 U.S.C. 32902(a) (2007).
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For amendments to existing standards, EPCA requires that if the
amendments make an average fuel economy standard more stringent, at
least 18 months of lead time must be provided.\390\ EPCA contains no
lead time requirement unless amendments make an average fuel economy
standard less stringent. NHTSA therefore interprets EPCA as allowing
amendments to reduce a standard's stringency up until the beginning of
the model year in question. In this rulemaking, NHTSA is proposing to
amend the standards for model year 2021. Since the agency proposes to
reduce these standards, this action is not subject to a lead time
requirement.
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\390\ 49 U.S.C. 32902(g)(2) (2007).
---------------------------------------------------------------------------
(b) Separate Standards for Cars and Trucks, and Minimum Standards for
Domestic Passenger Cars
As discussed above, EPCA requires NHTSA to set separate CAFE
standards for passenger cars and light trucks for each model year.\391\
NHTSA interprets this requirement as preventing the agency from setting
a single combined CAFE standard for cars and trucks together, based on
the plain language of the statute. Congress originally intended
separate CAFE standards for cars and trucks to reflect the different
fuel economy capabilities of those different types of vehicles, and
over the history of the CAFE program, has never revised this
requirement. Even as many cars and trucks have come to resemble each
other more closely over time--many crossover and sport-utility models,
for example, come in versions today that may be subject to either the
car standards or the truck standards depending on their
characteristics--it is still accurate to say that vehicles with truck-
like characteristics such as 4 wheel drive, cargo-carrying capability,
etc., need to use more fuel per mile to perform those jobs than
vehicles without these characteristics. Thus, regardless of the plain
language of the statute, NHTSA believes that the different fuel economy
capabilities of cars and trucks would generally make separate standards
appropriate for these different types of vehicles.
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\391\ 49 U.S.C. 32902(b)(1) (2007).
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EPCA, as amended by EISA, also requires another separate standard
to be set for domestically-manufactured \392\ passenger cars. Unlike
under the standards for passenger cars and light trucks described
above, the compliance burden of the minimum domestic passenger car
standard is the same for all manufacturers; the statute clearly states
that any manufacturer's domestically-manufactured passenger car fleet
must meet the greater of either 27.5 mpg on average, or
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\392\ In the CAFE program, ``domestically-manufactured'' is
defined by Congress in 49 U.S.C. Sec. 32904(b). The specifics of
the definition are too many for a footnote, but roughly, a passenger
car is ``domestically manufactured'' as long as at least 75% of the
cost to the manufacturer is attributable to value added in the
United States, Canada, or Mexico, unless the assembly of the vehicle
is completed in Canada or Mexico and the vehicle is imported into
the United States more than 30 days after the end of the model year.
. . . 92 percent of the average fuel economy projected by the
Secretary for the combined domestic and non-domestic passenger
automobile fleets manufactured for sale in the United States by all
manufacturers in the model year, which projection shall be published
in the Federal Register when the standard for that model year is
promulgated in accordance with [49 U.S.C. 32902(b)].\393\
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\393\ 49 U.S.C. Sec. 32902(b)(4) (2007).
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Since that requirement was promulgated, the ``92 percent'' has
always been greater than 27.5 mpg. NHTSA published the 92-percent
minimum domestic passenger car standards for model years 2017-2025 at
49 CFR 531.5(d) as part of the 2012 final rule. For MYs 2022-2025,
531.5(e) states that these were to be applied if, when actually
proposing MY 2022 and subsequent standards, the previously identified
standards for those years are deemed maximum feasible, but if NHTSA
determines that the previously identified standards are not maximum
feasible, the 92-percent minimum domestic passenger car standards would
also change. This is consistent with the statutory language that the
92-percent standards must be determined at the time an overall
passenger car standard is promulgated and published in the Federal
Register. Thus, any time NHTSA establishes or changes a passenger car
standard for a model year, the minimum domestic passenger car standard
for that model year will also be evaluated or reevaluated and
established accordingly. NHTSA explained this in the rulemaking to
establish standards for MYs 2017 and beyond and received no
comments.\394\
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\394\ 77 FR 62624, 63028 (Oct. 15, 2012).
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The 2016 Alliance/Global petition for rulemaking asked NHTSA to
retroactively revise the 92-percent minimum domestic passenger car
standards for MYs 2012-2016 ``to reflect 92 percent of the required
average passenger car standard taking into account the fleet mix as it
actually occurred, rather than what was forecast.'' The petitioners
stated that doing so would be ``fully consistent with the statute.''
\395\
---------------------------------------------------------------------------
\395\ Automobile Alliance and Global Automakers Petition for
Direct Final Rule with Regard to Various Aspects of the Corporate
Average Fuel Economy Program and the Greenhouse Gas Program (June
20, 2016) at 5, 17-18, available at https://www.epa.gov/sites/production/files/2016-09/documents/petition_to_epa_from_auto_alliance_and_global_automakers.pdf
[hereinafter Alliance/Global Petition].
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NHTSA understands that determining the 92 percent value ahead of
the model year to which it applies, based on the information then
available to the agency, results in a different mpg number than if
NHTSA determined the 92 percent value based on the information
available at the end of the model year in question. NHTSA further
understands that determining the 92 percent value ahead of time can
make the domestic minimum passenger car standard more stringent than it
could be if it were determined at the end of the model year, if
manufacturers end up producing more larger-footprint passenger cars
than NHTSA originally anticipated.
Accordingly, NHTSA seeks comment on this request by Alliance/
Global. Additionally, recognizing the uncertainty inherent in
projecting specific mpg values far into the future, it is possible that
NHTSA could define the mpg values associated with a CAFE standard
(i.e., the footprint curve) as a range rather than as a single number.
For example, the sensitivity analysis included in this proposal and in
the accompanying PRIA could provide a basis for such an mpg range
``defining'' the passenger car standard in any given model year. If
NHTSA took that approach, 92 percent of that ``standard'' would also,
necessarily, be a range. We also seek comment on this or other similar
approaches.
(c) Attribute-Based and Defined by Mathematical Function
EISA requires NHTSA to set CAFE standards that are ``based on 1 or
more
[[Page 43208]]
attributes related to fuel economy and express[ed] . . . in the form of
a mathematical function.'' \396\ NHTSA has thus far based standards on
vehicle footprint and proposes to continue to do so for all the reasons
described in previous rulemakings. As in previous rulemakings, NHTSA
proposes to define the standards in the form of a constrained linear
function that generally sets higher (more stringent) targets for
smaller-footprint vehicles and lower (less stringent) targets for
larger-footprint vehicles. These footprint curves are discussed in much
greater detail in Section II.C above. We seek comment both on the
choice of footprint as the relevant attribute and on the rationale for
the constrained linear functions chosen to represent the standards.
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\396\ 49 U.S.C. 32902(b)(3)(A).
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(d) Number of Model Years for Which Standards May Be Set at a Time
EISA also states that NHTSA shall ``issue regulations under this
title prescribing average fuel economy standards for at least 1, but
not more than 5, model years.'' \397\ In the 2012 final rule, NHTSA
interpreted this provision as preventing the agency from setting final
standards for all of MYs 2017-2025 in a single rulemaking action, so
the MYs 2022-2025 standards were termed ``augural,'' meaning ``that
they represent[ed] the agency's current judgment, based on the
information available to the agency [then], of what levels of
stringency would be maximum feasible in those model years.'' \398\ That
said, NHTSA also repeatedly clarified that the augural standards were
in no way final standards and that a future de novo rulemaking would be
necessary in order to both propose and promulgate final standards for
MYs 2022-2025.
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\397\ 49 U.S.C. 32902(b)(3)(B).
\398\ 77 FR 62623, 62630 (Oct. 15, 2012).
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Today, NHTSA proposes to establish new standards for MYs 2022-2026
and to revise the previously-established final standards for MY 2021.
Legislative history suggests that Congress included the five year
maximum limitation so NHTSA would issue standards for a period of time
where it would have reasonably realistic estimates of market
conditions, technologies, and economic practicability (i.e., not set
standards too far into the future).\399\ However, the concerns Congress
sought to address by imposing those limitations are not present for
nearer model years where NHTSA already has existing standards.
Revisiting existing standards is contemplated by both 49 U.S.C.
32902(c) and 32902(g). We therefore believe that it is reasonable to
interpret section 32902(b)(3)(B) as applying only to the establishing
of new standards rather than to the combined action of establishing new
standards and amending existing standards.
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\399\ See 153 Cong. Rec. 2665 (Dec. 28, 2007).
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Moreover, we believe it would be an absurd result not intended by
Congress if the five year maximum limitation were interpreted to
prevent NHTSA from revising a previously-established standard that we
have determined to be beyond maximum feasible, while concurrently
setting five years of standards not so distant from today. The concerns
Congress sought to address are much starker when NHTSA is trying to
determine what standards would be maximum feasible 10 years from now as
compared to three years from now.
(e) Maximum Feasible
As discussed above, EPCA requires NHTSA to consider four factors in
determining what levels of CAFE standards would be maximum feasible,
and NHTSA presents in the sections below its understanding of what
those four factors mean. All factors should be considered, in the
manner appropriate, and then the maximum feasible standards should be
determined.
(1) Technological Feasibility
``Technological feasibility'' refers to whether a particular method
of improving fuel economy is available for deployment in commercial
application in the model year for which a standard is being
established. Thus, NHTSA is not limited in determining the level of new
standards to technology that is already being commercially applied at
the time of the rulemaking. For this proposal, NHTSA is considering a
wide range of technologies that improve fuel economy, subject to the
constraints of EPCA regarding how to treat alternative fueled vehicles,
and considering the need to account for which technologies have already
been applied to which vehicle model/configuration, and the need to
realistically estimate the cost and fuel economy impacts of each
technology. NHTSA has not attempted to account for every technology
that might conceivably be applied to improve fuel economy and considers
it unnecessary to do so given that many technologies address fuel
economy in similar ways.\400\ Technological feasibility and economic
practicability are often conflated, as will be covered further in the
following section. To be clear, whether a fuel-economy-improving
technology does or will exist (technological feasibility) is a
different question from what economic consequences could ensue if NHTSA
effectively requires that technology to become widespread in the fleet
and the economic consequences of the absence of consumer demand for
technology that are projected to be required (economic practicability).
It is therefore possible for standards to be technologically feasible
but still beyond the level that NHTSA determines to be maximum feasible
due to consideration of the other relevant factors.
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\400\ For example, NHTSA has not considered high-speed flywheels
as potential energy storage devices for hybrid vehicles; while such
flywheels have been demonstrated in the laboratory and even tested
in concept vehicles, commercially available hybrid vehicles
currently known to NHTSA use chemical batteries as energy storage
devices, and the agency has considered a range of hybrid vehicle
technologies that do so.
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(2) Economic Practicability
``Economic practicability'' has traditionally referred to whether a
standard is one ``within the financial capability of the industry, but
not so stringent as to'' lead to ``adverse economic consequences, such
as a significant loss of jobs or unreasonable elimination of consumer
choice.'' \401\ In evaluating economic practicability, NHTSA considers
the uncertainty surrounding future market conditions and consumer
demand for fuel economy alongside consumer demand for other vehicle
attributes. NHTSA has explained in the past that this factor can be
especially important during rulemakings in which the auto industry is
facing significantly adverse economic conditions (with corresponding
risks to jobs). Consumer acceptability is also a major component to
economic practicability,\402\ which can involve consideration of
anticipated consumer responses not just to increased vehicle cost, but
also to the way manufacturers may change vehicle models and vehicle
sales mix in response to CAFE standards. In attempting to determine the
economic practicability of attribute-based standards, NHTSA considers a
wide variety of elements, including the annual rate at which
manufacturers can increase the percentage of their fleet that employs a
particular type of fuel-saving technology,\403\ the specific fleet
mixes of
[[Page 43209]]
different manufacturers, and assumptions about the cost of standards to
consumers and consumers' valuation of fuel economy, among other things.
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\401\ 67 FR 77015, 77021 (Dec. 16, 2002).
\402\ See, e.g., Center for Auto Safety v. NHTSA (CAS), 793 F.2d
1322 (D.C. Cir. 1986) (Administrator's consideration of market
demand as component of economic practicability found to be
reasonable); Public Citizen v. NHTSA, 848 F.2d 256 (Congress
established broad guidelines in the fuel economy statute; agency's
decision to set lower standards was a reasonable accommodation of
conflicting policies).
\403\ For example, if standards effectively require
manufacturers to widely apply technologies that consumers do not
want, or to widely apply technologies before they are ready to be
widespread, NHTSA believes that these standards could potentially be
beyond economically practicable.
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Prior to the MYs 2005-2007 rulemaking under the non-attribute-based
(fixed value) CAFE standards, NHTSA generally sought to ensure the
economic practicability of standards in part by setting them at or near
the capability of the ``least capable manufacturer'' with a significant
share of the market, i.e., typically the manufacturer whose fleet mix
was, on average, the largest and heaviest, generally having the highest
capacity and capability so as to not limit the availability of those
types of vehicles to consumers. In the first several rulemakings
establishing attribute-based standards, NHTSA applied marginal cost-
benefit analysis, considering both overall societal impacts and overall
consumer impacts. Whether the standards maximize net benefits has thus
been a touchstone in the past for NHTSA's consideration of economic
practicability. Executive Order 12866, as amended by Executive Order
13563, states that agencies should ``select, in choosing among
alternative regulatory approaches, those approaches that maximize net
benefits . . .'' In practice, however, agencies, including NHTSA, must
consider situations in which the modeling of net benefits does not
capture all of the relevant considerations of feasibility. Therefore,
as in past rulemakings, NHTSA is considering net societal impacts, net
consumer impacts, and other related elements in the consideration of
economic practicability.
NHTSA's consideration of economic practicability depends on a
number of elements. Expected availability of capital to make
investments in new technologies matters; manufacturers' expected
ability to sell vehicles with certain technologies matters; likely
consumer choices matter and so forth. NHTSA's analysis of the impacts
of this proposal incorporates assumptions to capture aspects of
consumer preferences, vehicle attributes, safety, and other elements
relevant to an impacts estimate; however, it is difficult to capture
every such constraint. Therefore, it is well within the agency's
discretion to deviate from the level at which modeled net benefits are
maximized if the agency concludes that that level would not represent
the maximum feasible level for future CAFE standards. Economic
practicability is complex, and like the other factors must also be
considered in the context of the overall balancing and EPCA's
overarching purpose of energy conservation. Depending on the conditions
of the industry and the assumptions used in the agency's analysis of
alternative standards, NHTSA could well find that standards that
maximize net benefits, or that are higher or lower, could be at the
limits of economic practicability, and thus potentially the maximum
feasible level, depending on how the other factors are balanced.
While we discuss safety as a separate consideration, NHTSA also
considers safety as closely related to, and in some circumstances a
subcomponent of economic practicability. On a broad level,
manufacturers have finite resources to invest in research and
development. Investment into the development and implementation of fuel
saving technology necessarily comes at the expense of investing in
other areas such as safety technology. On a more direct level, when
making decisions on how to equip vehicles, manufacturers must balance
cost considerations to avoid pricing further consumers out of the
market. As manufacturers add technology to increase fuel efficiency,
they may decide against installing new safety equipment to reduce cost
increases. And as the price of vehicles increase beyond the reach of
more consumers, such consumers continue to drive or purchase older,
less safe vehicles. In assessing practicability, NHTSA also considers
the harm to the nation's economy caused by highway fatalities and
injuries.
(3) The Effect of Other Motor Vehicle Standards of the Government on
Fuel Economy
``The effect of other motor vehicle standards of the Government on
fuel economy'' involves analysis of the effects of compliance with
emission, safety, noise, or damageability standards on fuel economy
capability and thus on average fuel economy. In many past CAFE
rulemakings, NHTSA has said that it considers the adverse effects of
other motor vehicle standards on fuel economy. It said so because, from
the CAFE program's earliest years \404\ until recently, the effects of
such compliance on fuel economy capability over the history of the CAFE
program have been negative ones. For example, safety standards that
have the effect of increasing vehicle weight thereby lower fuel economy
capability, thus decreasing the level of average fuel economy that
NHTSA can determine to be feasible. NHTSA has considered the additional
weight that it estimates would be added in response to new safety
standards during the rulemaking timeframe.\405\ NHTSA has also
accounted for EPA's ``Tier 3'' standards for criteria pollutants in its
estimates of technology effectiveness.\406\
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\404\ 42 FR 63184, 63188 (Dec. 15, 1977). See also 42 FR 33534,
33537 (June 30, 1977).
\405\ PRIA, Chapter 5.
\406\ PRIA, Chapter 6.
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In the 2012 final rule establishing CAFE standards for MYs 2017-
2021, NHTSA also discussed whether EPA GHG standards and California GHG
standards should be considered and accounted for as ``other motor
vehicle standards of the Government.'' NHTSA recognized that ``To the
extent the GHG standards result in increases in fuel economy, they
would do so almost exclusively as a result of inducing manufacturers to
install the same types of technologies used by manufacturers in
complying with the CAFE standards.'' \407\ NHTSA concluded that ``the
agency had already considered EPA's [action] and the harmonization
benefits of the National Program in developing its own [action],'' and
that ``no further action was needed.'' \408\
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\407\ 77 FR 62624, 62669 (Oct. 15, 2012).
\408\ Id.
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Considering the issue afresh in this proposal, and looking only at
the words in the statute, obviously EPA's GHG standards applicable to
light-duty vehicles are literally ``other motor vehicle standards of
the Government,'' in that they are standards set by a Federal agency
that apply to motor vehicles. Basic chemistry makes fuel economy and
tailpipe CO2 emissions two sides of the same coin, as
discussed at length above, and when two agencies functionally regulate
both (because by regulating fuel economy, you regulate CO2
emissions, and vice versa), it would be absurd not to link their
standards.\409\ The global warming potential of N2O,
CH4, and HFC emissions are not closely linked with fuel
economy, but neither do they affect fuel economy capabilities. How,
then, should NHTSA consider EPA's various GHG standards?
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\409\ In fact, EPA includes tailpipe CH4, CO, and
CO2 in the measurement of tailpipe CO2 for GHG
compliance using a carbon balance equation so that the measurement
of tailpipe CO2 exactly aligns with the measurement of
fuel economy for the CAFE compliance.
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NHTSA is aware that some stakeholders believe that NHTSA's
obligation to set maximum feasible CAFE standards can best be executed
by letting EPA decide what GHG standards
[[Page 43210]]
are appropriate and reasonable under the CAA. NHTSA disagrees. While
EPA and NHTSA consider some similar factors under the CAA and EPCA/
EISA, respectively, they are not identical. Standards that are
appropriate under the CAA may not be ``maximum feasible'' under EPCA/
EISA, and vice versa. Moreover, considering EPCA's language in the
context in which it was written, it seems unreasonable to conclude that
Congress intended EPA to dictate CAFE stringency. In fact, Congress
clearly separated NHTSA's and EPA's responsibilities for CAFE under
EPCA by giving NHTSA authority to set standards and EPA authority to
measure and calculate fuel economy. If Congress had wanted EPA to set
CAFE standards, it could have given that authority to EPA in EPCA or at
any point since Congress amended EPCA.\410\
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\410\ We note, for instance, that EISA was passed after the
Massachusetts v. EPA decision by the Supreme Court. If Congress had
wanted to amend EPCA in light of that decision, they would have done
so at the time. They did not.
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NHTSA and EPA are obligated by Congress to exercise their own
independent judgment in fulfilling their statutory missions, even
though both agencies' regulations affect both fuel economy and
CO2 emissions. Because of this relationship, it is incumbent
on both agencies to coordinate and look to one another's actions to
avoid unreasonably burdening industry through inconsistent regulations,
but both agencies must be able to defend their programs on their own
merits. As with other recent CAFE and GHG rulemakings, the agencies are
continuing do all of these things in this proposal.
With regard to standards issued by the State of California, State
tailpipe standards (whether for greenhouse gases or for other
pollutants) do not qualify as ``other motor vehicle standards of the
Government'' under 49 U.S.C. 32902(f); therefore, NHTSA will not
consider them as such in proposing maximum feasible average fuel
economy standards. States may not adopt or enforce tailpipe greenhouse
gas emissions standards when such standards relate to fuel economy
standards and are therefore preempted under EPCA, regardless of whether
EPA granted any waivers under the Clean Air Act (CAA).\411\
---------------------------------------------------------------------------
\411\ This topic is discussed further in Section VI below.
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Preempted standards of a State or a political subdivision of a
State include, for example:
(1) A fuel economy standard; and
(2) A law or regulation that has the direct effect of a fuel
economy standard, but is not labeled as one (i.e., a State tailpipe
CO2 standard or prohibition on CO2 emissions).
NHTSA and EPA agree that state tailpipe greenhouse gas emissions
standards do not become Federal standards and qualify as ``other motor
vehicle standards of the Government,'' when subject to a CAA preemption
waiver. EPCA's legislative history supports this position.
EPCA, as initially passed in 1975, mandated average fuel economy
standards for passenger cars beginning with model year 1978. The law
required the Secretary of Transportation to establish, through
regulation, maximum feasible fuel economy standards \412\ for model
years 1981 through 1984 with the intent to provide steady increases to
achieve the standard established for 1985 and thereafter authorized the
Secretary to adjust that standard.
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\412\ As is the case today, EPCA required the Secretary to
determine ``maximum feasible average fuel economy'' after
considering technological feasibility, economic practicability, the
effect of other Federal motor vehicle standards on fuel economy, and
the need of the Nation to conserve energy. 15 U.S.C. 2002(e)
(recodified July 5, 1994).
---------------------------------------------------------------------------
For the statutorily-established standards for model years 1978-
1980, EPCA provided each manufacturer with the right to petition for
changes in the standards applicable to that manufacturer. A petitioning
manufacturer had the burden of demonstrating a ``Federal fuel economy
standards reduction'' was likely to exist for that manufacturer in one
or more of those model years and that it had made reasonable technology
choices. ``Federal standards,'' for that limited purpose, included not
only safety standards, noise emission standards, property loss
reduction standards, and emission standards issued under various
Federal statutes, but also ``emissions standards applicable by reason
of section 209(b) of [the CAA].'' \413\ (Emphasis added). Critically,
all definitions, processes, and required findings regarding a Federal
fuel economy standards reduction were located within a single self-
contained subsection of 15 U.S.C. 2002 that applied only to model years
1978-1980.\414\
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\413\ Section 202 of the CAA (42 U.S.C. 7521) requires EPA to
prescribe air pollutant emission standards for new vehicles; Section
209 of the CAA (42 U.S.C. 7543) preempts state emissions standards
but allows California to apply for a waiver of such preemption.
\414\ As originally enacted as part of Public Law 94-163, that
subsection was designated as section 502(d) of the Motor Vehicle
Information and Cost Savings Act.
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In 1994, Congress recodified EPCA. As part of this recodification,
the CAFE provisions were moved to Title 49 of the United States Code.
In doing so, unnecessary provisions were deleted. Specifically, the
recodification eliminated subsection (d). The House report on the
recodification declared that the subdivision was ``executed,'' and
described its purpose as ``[p]rovid[ing] for modification of average
fuel economy standards for model years 1978, 1979, and 1980.'' \415\ It
is generally presumed, when Congress includes text in one section and
not in another, that Congress knew what it was doing and made the
decision deliberately.
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\415\ H.R. Rep. No. 103-180, at 583-584, tbl. 2A.
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NHTSA has previously considered the impact of California's Low
Emission Vehicle standards in establishing fuel economy standards and
occasionally has done so under the ``other standards'' sections.\416\
During the 2012 rulemaking, NHTSA sought comment on the appropriateness
of considering California's tailpipe GHG emission standards in this
section and concluded that doing so was unnecessary.\417\ In light of
the legislative history discussed above, however, NHTSA now determines
that this was not appropriate. Notwithstanding the improper
categorization of such discussions, NHTSA may consider elements not
specifically designated as factors to be considered under EPCA, given
the breadth of such factors as technological feasibility and economic
practicability, and such consideration was appropriate.\418\
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\416\ See, e.g., 68 FR 16896, 71 FR 17643.
\417\ See 77 FR 62669.
\418\ See, e.g., discussion in Center for Automotive Safety v.
National Highway Traffic Safety Administration, et al., 793 F.2d.
1322 (D.C. Cir. 1986) at 1338, et seq., providing that NHTSA may
consider consumer demand in establishing standards, but not ``to
such an extent that it ignored the overarching goal of fuel
conservation. At the other extreme, a standard with harsh economic
consequences for the auto industry also would represent an
unreasonable balancing of EPCA's policies.''
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(4) The Need of the United States To Conserve Energy
``The need of the United States to conserve energy'' means ``the
consumer cost, national balance of payments, environmental, and foreign
policy implications of our need for large quantities of petroleum,
especially imported petroleum.'' \419\
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\419\ 42 FR 63184, 63188 (Dec. 15, 1977).
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(i) Consumer Costs and Fuel Prices
Fuel for vehicles costs money for vehicle owners and operators. All
else equal, consumers benefit from vehicles that need less fuel to
perform the same amount of work. Future fuel prices are a critical
input into the economic
[[Page 43211]]
analysis of potential CAFE standards because they determine the value
of fuel savings both to new vehicle buyers and to society, the amount
of fuel economy that the new vehicle market is likely to demand in the
absence of new standards, and they inform NHTSA about the ``consumer
cost . . . of our need for large quantities of petroleum.'' In this
proposal, NHTSA's analysis relies on fuel price projections from the
U.S. Energy Information Administration's (EIA) Annual Energy Outlook
(AEO) for 2017. Federal government agencies generally use EIA's price
projections in their assessment of future energy-related policies.
(ii) National Balance of Payments
Historically, the need of the United States to conserve energy has
included consideration of the ``national balance of payments'' because
of concerns that importing large amounts of oil created a significant
wealth transfer to oil-exporting countries and left the U.S.
economically vulnerable.\420\ As recently as 2009, nearly half the U.S.
trade deficit was driven by petroleum,\421\ yet this concern has
largely laid fallow in more recent CAFE actions, arguably in part
because other factors besides petroleum consumption have since played a
bigger role in the U.S. trade deficit. Given significant recent
increases in U.S. oil production and corresponding decreases in oil
imports, this concern seems likely to remain fallow for the foreseeable
future.\422\ Increasingly, changes in the price of fuel have come to
represent transfers between domestic consumers of fuel and domestic
producers of petroleum rather than gains or losses to foreign entities.
Some commenters have lately raised concerns about potential economic
consequences for automaker and supplier operations in the U.S. due to
disparities between CAFE standards at home and their counterpart fuel
economy/efficiency and GHG standards abroad. NHTSA finds these concerns
more relevant to technological feasibility and economic practicability
than to the national balance of payments. Moreover, to the extent that
an automaker decides to globalize a vehicle platform to meet more
stringent standards in other countries, that automaker would comply
with United States's standards and additionally generate
overcompensation credits that it can save for future years if facing
compliance concerns,or sell to other automakers. While CAFE standards
are set at maximum feasible rates, efforts of manufacturers to exceed
those standards are rewarded not only with additional credits but a
market advantage in that consumers who place a large weight on fuel
savings will find such vehicles that much more attractive.
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\420\ See 42 FR 63184, 63192 (Dec. 15, 1977) ``A major reason
for this need [to reduce petroleum consumption] is that the
importation of large quantities of petroleum creates serious balance
of payments and foreign policy problems. The United States currently
spends approximately $45 billion annually for imported petroleum.
But for this large expenditure, the current large U.S. trade deficit
would be a surplus.''
\421\ See Today in Energy: Recent improvements in petroleum
trade balance mitigate U.S. trade deficit, U.S. Energy Information
Administration (July 21, 2014), https://www.eia.gov/todayinenergy/detail.php?id=17191.
\422\ For an illustration of recent increases in U.S.
production, see, e.g., U.S. crude oil and liquid fuels production,
Short-Term Energy Outlook, U.S. Energy Information Administration
(June 2018), https://www.eia.gov/outlooks/steo/images/fig13.png.
While it could be argued that reducing oil consumption frees up more
domestically-produced oil for exports, and thereby raises U.S. GDP,
that is neither the focus of the CAFE program nor consistent with
Congress' original intent in EPCA. EIA's Annual Energy Outlook (AEO)
series provides midterm forecasts of production, exports, and
imports of petroleum products, and is available at https://www.eia.gov/outlooks/aeo/.
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(iii) Environmental Implications
Higher fleet fuel economy can reduce U.S. emissions of various
pollutants by reducing the amount of oil that is produced and refined
for the U.S. vehicle fleet but can also increase emissions by reducing
the cost of driving, which can result in increased vehicle miles
traveled (i.e., the rebound effect). Thus, the net effect of more
stringent CAFE standards on emissions of each pollutant depends on the
relative magnitudes of its reduced emissions in fuel refining and
distribution and increases in its emissions from vehicle use. Fuel
savings from CAFE standards also necessarily results in lower emissions
of CO2, the main GHG emitted as a result of refining,
distribution, and use of transportation fuels. Reducing fuel
consumption directly reduces CO2 emissions because the
primary source of transportation-related CO2 emissions is
fuel combustion in internal combustion engines.
NHTSA has considered environmental issues, both within the context
of EPCA and the context of the National Environmental Policy Act
(NEPA), in making decisions about the setting of standards since the
earliest days of the CAFE program. As courts of appeal have noted in
three decisions stretching over the last 20 years,\423\ NHTSA defined
``the need of the United States to conserve energy'' in the late 1970s
as including, among other things, environmental implications. In 1988,
NHTSA included climate change concepts in its CAFE notices and prepared
its first environmental assessment addressing that subject.\424\ It
cited concerns about climate change as one of its reasons for limiting
the extent of its reduction of the CAFE standard for MY 1989 passenger
cars.\425\ Since then, NHTSA has considered the effects of reducing
tailpipe emissions of CO2 in its fuel economy rulemakings
pursuant to the need of the United States to conserve energy by
reducing petroleum consumption.
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\423\ CAS, 793 F.2d 1322, 1325 n. 12 (D.C. Cir. 1986); Public
Citizen, 848 F.2d 256, 262-63 n. 27 (D.C. Cir. 1988) (noting that
``NHTSA itself has interpreted the factors it must consider in
setting CAFE standards as including environmental effects''); CBD,
538 F.3d 1172 (9th Cir. 2007).
\424\ 53 FR 33080, 33096 (Aug. 29, 1988).
\425\ 53 FR 39275, 39302 (Oct. 6, 1988).
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(iv) Foreign Policy Implications
U.S. consumption and imports of petroleum products impose costs on
the domestic economy that are not reflected in the market price for
crude petroleum or in the prices paid by consumers for petroleum
products such as gasoline. These costs include (1) higher prices for
petroleum products resulting from the effect of U.S. oil demand on
world oil prices, (2) the risk of disruptions to the U.S. economy
caused by sudden increases in the global price of oil and its resulting
impact of fuel prices faced by U.S. consumers, and (3) expenses for
maintaining the strategic petroleum reserve (SPR) to provide a response
option should a disruption in commercial oil supplies threaten the U.S.
economy, to allow the U.S. to meet part of its International Energy
Agency obligation to maintain emergency oil stocks, and to provide a
national defense fuel reserve.\426\ Higher U.S. consumption of crude
oil or refined petroleum products increases the magnitude of these
external economic costs, thus increasing the true economic cost of
supplying transportation fuels above the resource costs of producing
them. Conversely, reducing U.S. consumption of crude oil or refined
petroleum products (by reducing motor fuel use) can reduce these
external costs.
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\426\ While the U.S. maintains a military presence in certain
parts of the world to help secure global access to petroleum
supplies, that is neither the primary nor the sole mission of U.S.
forces overseas. Additionally, the scale of oil consumption
reductions associated with CAFE standards would be insufficient to
alter any existing military missions focused on ensuring the safe
and expedient production and transportation of oil around the globe.
See Chapter 7 of the PRIA for more information on this topic.
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While these costs are considerations, the United States has
significantly increased oil production capabilities in
[[Page 43212]]
recent years to the extent that the U.S. is currently producing enough
oil to satisfy nearly all of its energy needs and is projected to
continue to do so or become a net energy exporter. This has added new
stable supply to the global oil market and reduced the urgency of the
U.S. to conserve energy. We discuss this issue in more detail below.
(5) Factors That NHTSA Is Prohibited From Considering
EPCA also provides that in determining the level at which it should
set CAFE standards for a particular model year, NHTSA may not consider
the ability of manufacturers to take advantage of several EPCA
provisions that facilitate compliance with CAFE standards and thereby
reduce the costs of compliance.\427\ As discussed further in Section
X.B.1.c) below, NHTSA cannot consider compliance credits that
manufacturers earn by exceeding the CAFE standards and then use to
achieve compliance in years in which their measured average fuel
economy falls below the standards. NHTSA also cannot consider the use
of alternative fuels by dual fuel vehicles nor the availability of
dedicated alternative fuel vehicles in any model year. EPCA encourages
the production of alternative fuel vehicles by specifying that their
fuel economy is to be determined using a special calculation procedure
that results in those vehicles being assigned a higher fuel economy
level than they actually achieve.
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\427\ 49 U.S.C. 32902(h).
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The effect of the prohibitions against considering these statutory
flexibilities in setting the CAFE standards is that the flexibilities
remain voluntarily-employed measures. If NHTSA were instead to assume
manufacturer use of those flexibilities in setting new standards,
higher standards would appear less costly and therefore more feasible,
which would thus tend to require manufacturers to use those
flexibilities in order to meet higher standards. By keeping NHTSA from
including them in our stringency determination, the provision ensures
that these statutory credits remain true compliance flexibilities.
Additionally, for non-statutory incentives that NHTSA developed by
regulation, NHTSA does not consider these subject to the EPCA
prohibition on considering flexibilities, either. EPCA is very clear as
to which flexibilities are not to be considered. When the agency has
introduced additional flexibilities such as A/C efficiency and ``off-
cycle'' technology fuel economy improvement values, NHTSA has
considered those technologies as available in the analysis. Thus,
today's analysis includes assumptions about manufacturers' use of those
technologies, as detailed in Section X.B.1.c)(4)
(f) EPCA/EISA Requirements That No Longer Apply Post-2020
Congress amended EPCA through EISA to add two requirements not yet
discussed in this section relevant to determination of CAFE standards
during the years between MY 2011 and MY 2020 but not beyond. First,
Congress stated that, regardless of NHTSA's determination of what
levels of standards would be maximum feasible, standards must be set at
levels high enough to ensure that the combined U.S. passenger car and
light truck fleet achieves an average fuel economy level of not less
than 35 mpg no later than MY 2020.\428\ And second, between MYs 2011
and 2020, the standards must ``increase ratably'' in each model
year.\429\ Neither of these requirements apply after MY 2020, so given
that this rulemaking concerns the standards for MY 2021 and after, they
are not relevant to this rulemaking.
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\428\ 49 U.S.C. 32902(b)(2)(A).
\429\ 49 U.S.C. 32902(b)(2)(C).
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(g) Other Considerations in Determining Maximum Feasible Standards
NHTSA has historically considered the potential for adverse safety
consequences in setting CAFE standards. This practice has been
consistently approved in case law. As courts have recognized, ``NHTSA
has always examined the safety consequences of the CAFE standards in
its overall consideration of relevant factors since its earliest
rulemaking under the CAFE program.'' Competitive Enterprise Institute
v. NHTSA, 901 F.2d 107, 120 n. 11 (D.C. Cir. 1990) (``CEI-I'') (citing
42 FR 33534, 33551 (June 30, 1977)). The courts have consistently
upheld NHTSA's implementation of EPCA in this manner. See, e.g.,
Competitive Enterprise Institute v. NHTSA, 956 F.2d 321, 322 (D.C. Cir.
1992) (``CEI-II'') (in determining the maximum feasible fuel economy
standard, ``NHTSA has always taken passenger safety into account'')
(citing CEI-I, 901 F.2d at 120 n. 11); Competitive Enterprise Institute
v. NHTSA, 45 F.3d 481, 482-83 (D.C. Cir. 1995) (``CEI-III'') (same);
Center for Biological Diversity v. NHTSA, 538 F.3d 1172, 1203-04 (9th
Cir. 2008) (upholding NHTSA's analysis of vehicle safety issues
associated with weight in connection with the MYs 2008-2011 light truck
CAFE rulemaking). Thus, in evaluating what levels of stringency would
result in maximum feasible standards, NHTSA assesses the potential
safety impacts and considers them in balancing the statutory
considerations and to determine the maximum feasible level of the
standards.
The attribute-based standards that Congress requires NHTSA to set
help to mitigate the negative safety effects of the historical ``flat''
standards originally required in EPCA, in recent rulemakings, NHTSA
limited the consideration of mass reduction in lower weight vehicles in
its analysis, which impacted the resulting assessment of potential
adverse safety effects. That analytical approach did not reflect,
however, the likelihood that automakers may pursue the most cost
effective means of improving fuel efficiency to comply with CAFE
requirements. For this rulemaking, the modeling does not limit the
amount of mass reduction that is applied to any segment but rather
considers that automakers may apply mass reduction based upon cost-
effectiveness, similar to most other technologies. NHTSA does not, of
course, mandate the use of any particular technology by manufacturers
in meeting the standards. The current proposal, like the Draft TAR,
also considers the safety effect associated with the additional vehicle
miles traveled due to the rebound effect.
In this rulemaking, NHTSA is considering the effect of additional
expenses in fuel savings technology on the affordability of vehicles--
the likelihood that increased standards will result in consumers being
priced out of the new vehicle market and choosing to keep their
existing vehicle or purchase a used vehicle. Since new vehicles are
significantly safer than used vehicles, slowing fleet turnover to newer
vehicles results in older and less safe vehicles remaining on the roads
longer. This significantly affects the safety of the United States
light duty fleet, as described more fully in Section 0 above and in
Chapter 11 of the PRIA accompanying this proposal. Furthermore, as fuel
economy standards become more stringent, and more fuel efficient
vehicles are introduced into the fleet, fueling costs are reduced. This
results in consumers driving more miles, which results in more crashes
and increased highway fatalities.
2. Administrative Procedure Act
To be upheld under the ``arbitrary and capricious'' standard of
judicial review in the APA, an agency rule must be rational, based on
consideration of the relevant factors, and within the scope of
[[Page 43213]]
the authority delegated to the agency by the statute. The agency must
examine the relevant data and articulate a satisfactory explanation for
its action including a ``rational connection between the facts found
and the choice made.'' Burlington Truck Lines, Inc., v. United States,
371 U.S. 156, 168 (1962).
Statutory interpretations included in an agency's rule are subject
to the two-step analysis of Chevron, U.S.A. v. Natural Resources
Defense Council, 467 U.S. 837 (1984). Under step one, where a statute
``has directly spoken to the precise question at issue,'' id. at 842,
the court and the agency ``must give effect to the unambiguously
expressed intent of Congress,'' id. at 843. If the statute is silent or
ambiguous regarding the specific question, the court proceeds to step
two and asks ``whether the agency's answer is based on a permissible
construction of the statute.'' Id.
If an agency's interpretation differs from the one that it has
previously adopted, the agency need not demonstrate that the prior
position was wrong or even less desirable. Rather, the agency would
need only to demonstrate that its new position is consistent with the
statute and supported by the record and acknowledge that this is a
departure from past positions. The Supreme Court emphasized this in FCC
v. Fox Television, 556 U.S. 502 (2009). When an agency changes course
from earlier regulations, ``the requirement that an agency provide a
reasoned explanation for its action would ordinarily demand that it
display awareness that it is changing position,'' but ``need not
demonstrate to a court's satisfaction that the reasons for the new
policy are better than the reasons for the old one; it suffices that
the new policy is permissible under the statute, that there are good
reasons for it, and that the agency believes it to be better, which the
conscious change of course adequately indicates.'' \430\ The APA also
requires that agencies provide notice and comment to the public when
proposing regulations,\431\ as we are doing today.
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\430\ Ibid., 1181.
\431\ 5 U.S.C. 553.
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3. National Environmental Policy Act
As discussed above, EPCA requires NHTSA to determine the level at
which to set CAFE standards for each model year by considering the four
factors of technological feasibility, economic practicability, the
effect of other motor vehicle standards of the Government on fuel
economy, and the need of the United States to conserve energy. The
National Environmental Policy Act (NEPA) directs that environmental
considerations be integrated into that process.\432\ To accomplish that
purpose, NEPA requires an agency to compare the potential environmental
impacts of its proposed action to those of a reasonable range of
alternatives.
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\432\ NEPA is codified at 42 U.S.C. 4321-47.
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To explore the environmental consequences of this proposed rule in
depth, NHTSA has prepared a Draft Environmental Impact Statement
(``DEIS''). The purpose of an EIS is to ``provide full and fair
discussion of significant environmental impacts and [to] inform
decisionmakers and the public of the reasonable alternatives which
would avoid or minimize adverse impacts or enhance the quality of the
human environment.'' \433\
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\433\ 40 CFR 1502.1.
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NEPA is ``a procedural statute that mandates a process rather than
a particular result.'' Stewart Park & Reserve Coal., Inc. v. Slater,
352 F.3d 545, 557 (2d Cir. 2003). The agency's overall EIS-related
obligation is to ``take a `hard look' at the environmental consequences
before taking a major action.'' Baltimore Gas & Elec. Co. v. Natural
Resources Defense Council, Inc., 462 U.S. 87, 97 (1983). Significantly,
``[i]f the adverse environmental effects of the proposed action are
adequately identified and evaluated, the agency is not constrained by
NEPA from deciding that other values outweigh the environmental
costs.'' Robertson v. Methow Valley Citizens Council, 490 U.S. 332, 350
(1989).
The agency must identify the ``environmentally preferable''
alternative but need not adopt it. ``Congress in enacting NEPA . . .
did not require agencies to elevate environmental concerns over other
appropriate considerations.'' Baltimore Gas & Elec. Co. v. Natural
Resources Defense Council, Inc., 462 U.S. 87, 97 (1983). Instead, NEPA
requires an agency to develop alternatives to the proposed action in
preparing an EIS. 42 U.S.C. 4322(2)(C)(iii). The statute does not
command the agency to favor an environmentally preferable course of
action, only that it make its decision to proceed with the action after
taking a hard look at the environmental consequences.
We seek comment on the DEIS associated with this NPRM.
4. Evaluating the EPCA Factors and Other Considerations To Arrive at
the Proposed Standards
NHTSA well recognizes that the decision it proposes to make in
today's NPRM is different from the one made in the 2012 final rule that
established standards for MY 2021 and identified ``augural'' standard
levels for MYs 2022-2025. Not only do we believe that the facts before
us have changed, but we believe that those facts have changed
sufficiently that the balancing of the EPCA factors and other
considerations must also change. The standards we are proposing today
reflect that balancing.
The overarching purpose of EPCA is energy conservation; that fact
remains the same. Examining that phrasing afresh, Merriam-Webster
states that to ``conserve'' means, in relevant part, ``to keep in a
safe or sound state; especially, to avoid wasteful or destructive use
of.'' \434\ This is consistent with our understanding of Congress'
original intent for the CAFE program: To raise fleet-wide fuel economy
levels in response to the Arab oil embargo in the 1970s and protect the
country from further gasoline price shocks and supply shortages. Those
price shocks, while they were occurring, were disruptive to the U.S.
economy and significantly affected consumers' daily lives. Congress
therefore sought to keep U.S. energy consumption in a safe and sound
state for the sake of consumers and the economy and avoid such shocks
in the future.
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\434\ ``Conserve,'' Merriam-Webster, available at https://www.merriam-webster.com/dictionary/conserve (last visited June 25,
2018).
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Today, the conditions that led both to those price shocks and to
U.S. energy vulnerability overall have changed significantly. In the
late 1970s, the U.S. was a major oil importer and changes (intentional
or not) in the global oil supply had massive domestic consequences, as
Congress saw. While oil consumption exceeded domestic production for
many years after that, net energy imports peaked in 2005, and since
then, oil imports have declined while exports have increased.
The relationship between the U.S. and the global oil market has
changed for two principal reasons. The first reason is that the U.S.
now consumes a significantly smaller share of global oil production
than it did in the 1970s. At the time of the Arab oil embargo, the U.S.
consumed about 17 million barrels per day of the globe's approximately
55 million barrels per day.\435\ While OPEC (particularly Saudi Arabia)
still has the ability to influence global oil prices by imposing
discretionary supply restrictions, the greater diversity of both
suppliers and consumers since the 1970s has reduced the degree to which
[[Page 43214]]
a single actor (or small collection of actors) can impact the welfare
of individual consumers. Oil is a fungible global commodity, though
there are limits to the substitutability of different types of crude
for a given application. The global oil market can, to a large extent,
compensate for any producer that chooses not to sell to a given buyer
by shifting other supply toward that buyer. And while regional
proximity, comparability of crude oil, and foreign policy
considerations can make some transactions more or less attractive, as
long as exporters have a vested interest in preserving the stability
(both in terms of price and supply) of the global oil market,
coordinated, large-scale actions (like the multi-nation sanctions
against Iran in recent years) would be required to impose costs or
welfare losses on one specific player in the global market. As a
corollary to the small rise in U.S. petroleum consumption over the last
few decades, the oil intensity of U.S. GDP has continued to decline
since the Arab oil embargo, suggesting that U.S. GDP is less
susceptible to increases in global petroleum prices (sudden or
otherwise) than it was at the time of EPCA's passage or when these
policies were last considered in 2012. While the U.S. still has a
higher energy intensity of GDP than some other developed nations, our
energy intensity has been declining since 1950 (shrinking by about 60%
since 1950 and almost 30% between 1990 and 2015).\436\
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\435\ Short-Term Energy Outlook, U.S. Energy Information
Administration (June 2018), available at https://www.eia.gov/outlooks/steo/pdf/steo_full.pdf.
\436\ Today in Energy: Global energy intensity continues to
decline, U.S. Energy Information Administration (July 12, 106),
https://www.eia.gov/todayinenergy/detail.php?id=27032.
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The second factor that has changed the United States' relationship
to the global oil market is the changing U.S. reliance on imported oil
over the last decade. U.S. domestic oil production began rising in 2009
with more cost-effective drilling and production technologies.\437\
Domestic oil production became more cost-effective for two basic
reasons. First, technology improved: The use of horizontal drilling in
conjunction with hydraulic fracturing has greatly expanded the ability
of producers to profitably recover natural gas and oil from low-
permeability geologic plays--particularly, shale plays--and
consequently, oil production from shale plays has grown rapidly in
recent years.\438\ And second, rising global oil prices themselves made
using those technologies more feasible. As a hypothetical example, if
it costs $79 per barrel to extract oil from a shale play, when the
market price for that oil is $60 per barrel, it is not worth the
producer's cost to extract the oil; when the market price is $80 per
barrel, it becomes cost-effective.
---------------------------------------------------------------------------
\437\ Energy Explained, U.S. Energy Information Administration,
https://www.eia.gov/energyexplained/index.cfm (last visited June 25,
2018).
\438\ Review of Emerging Resources: U.S. Shale Gas and Shale Oil
Plays, U.S. Energy Information Administration (July 8, 2011),
https://www.eia.gov/analysis/studies/usshalegas/. Practical
application of horizontal drilling to oil production began in the
early 1980s, by which time the advent of improved downhole drilling
motors and the invention of other necessary supporting equipment,
materials, and technologies (particularly, downhole telemetry
equipment) had brought some applications within the realm of
commercial viability. EIA's AEO 2018 also projects that by the early
2040s, tight oil production will account for nearly 70% of total
U.S. production, up from 54% of the U.S. total in 2017. See also,
Tight oil remains the leading source of future U.S. crude oil
production, U.S. Energy Information Administration (Feb. 22, 2018),
https://www.eia.gov/todayinenergy/detail.php?id=35052.
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Recent analysis further suggests that the U.S. oil supply response
to a rise in global prices is much larger now due to the shale
revolution, as compared to what it was when U.S. production depended
entirely on conventional wells. Unconventional wells may be not only
capable of producing more oil over time but also may be capable of
responding faster to price shocks. One 2017 study concluded that ``The
long-run price responsiveness of supply is about 6 times larger for
tight oil on a per well basis, and about 9 times larger when also
accounting for the rise in unconventional-directed drilling.'' That
same study further found that ``Given a price rise to $80 per barrel,
U.S. oil production could rise by 0.5 million barrels per day in 6
months, 1.2 million in 1 year, 2 million in 2 years, and 3 million in 5
years.'' \439\ Some analysts suggest that shale drillers can respond
more quickly to market conditions because, unlike conventional
drillers, they do not need to spend years looking for new deposits,
because there are simply so many shale oil wells being drilled, and
because they are more productive (although their supply may be
exhausted more quickly than a conventional well, the sheer numbers
appear likely to make up for that concern).\440\ Some commenters
disagree and suggest that the best deposits are already known and
tapped.\441\ Other commenters raise the possibility that even if the
most productive deposits are already tapped, any rises in global oil
prices should spur technology development that improves output of less
productive deposits.\442\ Moreover, even if U.S. production increases
more slowly than, for example, EIA currently estimates, all increases
in U.S. production help to temper global prices and the risk of oil
shocks because they reduce the influence of other producing countries
who might experience supply interruptions due to geopolitical
instability or deliberately reduce supply in an effort to raise
prices.\443\
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\439\ Newell, R. G. & Prest, B.C. The Unconventional Oil Supply
Boom: Aggregate Price Response from Microdata, Working Paper 23973,
National Bureau of Economic Research (Oct. 2017), available at
http://www.nber.org/papers/w23973 (last visited June 25, 2018).
\440\ Ip, G. America's Emerging Petro Economy Flips the Impact
of Oil, Wall Street Journal (Feb. 21, 2018), available at https://www.wsj.com/articles/americas-emerging-petro-economy-flips-the-impact-of-oil-1519209000 (last visited June 25, 2018).
\441\ Olson, B. Shale Trailblazer Turns Skeptic on Soaring U.S.
Oil Production, Wall Street Journal (Mar. 5, 2018), available at
https://www.wsj.com/articles/shale-trailblazer-turns-skeptic-on-soaring-u-s-oil-production-1520257595.
\442\ LeBlanc, R. In the Sweet Spot: The Key to Shale, Wall
Street Journal (Mar. 6, 2018), available at http://partners.wsj.com/ceraweek/connection/sweet-spot-key-shale/.
\443\ Alessi, C. & Sider, A. U.S. Oil Output Expected to Surpass
Saudi Arabia, Rivaling Russia for Top Spot, Wall Street Journal
(Jan. 19, 2018), available at https://www.wsj.com/articles/u-s-crude-production-expected-to-surpass-saudi-arabia-in-2018-1516352405.
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These changes in U.S. oil intensity, production, and capacity
cannot entirely insulate consumers from the effects of price shocks at
the gas pump, because although domestic production may be able to
satisfy domestic energy demand, we cannot predict whether domestically
produced oil will be distributed domestically or more broadly to the
global market. But it appears that domestic supply may dampen the
magnitude, frequency, and duration of price shocks. As global per-
barrel oil prices rise, U.S. production is now much better able to (and
does) ramp up in response, pulling those prices back down.
Corresponding per-gallon gas prices may not fall overnight,\444\ but it
is foreseeable that they could moderate over time and likely respond
faster than prior to the shale revolution. EIA's Annual Energy Outlook
for 2018 acknowledges uncertainty regarding these new oil sources but
projects that while retail prices of gasoline and diesel will increase
between 2018 and 2050, annual average gasoline prices would not exceed
$4/gallon (in real dollars) during that timeframe under EIA's
``reference
[[Page 43215]]
case'' projection.\445\ The International Energy Agency (IEA)'s Oil
2018 report suggests some concern that excessive focus on investing in
U.S. shale oil production may increase price volatility after 2023 if
investment is not applied more broadly but also states that U.S. shale
oil is capable of and expected to respond quickly to rising prices in
the future, and that American influence on global oil markets is
expected to continue to rise.\446\ From the supply side, it is possible
that the oil market conditions that created the price shocks in the
1970s may no longer exist.
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\444\ To be clear, the fact that the risk of gasoline price
shocks may now be lower than in the past is different from arguing
that gasoline prices will never rise again at all. The Energy
Information Administration tracks and reports on pump prices around
the country, and we refer readers to their website for the most up-
to-date information. EIA projects under its ``reference case''
assumptions that the structural changes in the oil market will keep
prices below $4/gallon through 2050. Prices will foreseeably
continue to rise and fall with supply and demand changes; the
relevant question for the need of the U.S. to conserve energy is not
whether there will be any movement in prices but whether that
movement is likely to be sudden and large.
\445\ Annual Energy Outlook 2018, U.S. Energy Information
Administration (Feb. 6, 2018) at 57, 58, available at https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf. The U.S. Energy
Information Administration (EIA) is the statistical and analytical
agency within the U.S. Department of Energy (DOE). EIA is the
nation's premier source of energy information and every fuel economy
rulemaking since 2002 (and every joint CAFE and CO2
rulemaking since 2009) has applied fuel price projections from EIA's
Annual Energy Outlook (AEO). AEO projections, documentation, and
underlying data and estimates are available at https://www.eia.gov/outlooks/aeo/.
\446\ See Oil 2018: Analysis and Forecasts to 2023 Executive
Summary, International Energy Agency (2018), available at http://www.iea.org/Textbase/npsum/oil2018MRSsum.pdf (last visited June 25,
2018). See also Kent, S. & Puko, T. U.S. Will Be the World's Largest
Oil Producer by 2023, Says IEA, Wall Street Journal (Mar. 5, 2018),
available at https://www.wsj.com/articles/u-s-will-be-the-worlds-largest-oil-producer-by-2023-says-iea-1520236810 (reporting on
remarks at the 2018 CERAWeek energy conference by IEA Executive
Director Fatih Birol).
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Regardless of changes in the oil supply market, on the demand side,
conditions are also significantly different from the 1970s. If gasoline
prices increase suddenly and dramatically, in today's market American
consumers have more options for fuel-efficient new vehicles. Fuel-
efficient vehicles were available to purchasers in the 1970s, but they
were generally small entry-level vehicles with features that did not
meet the needs and preferences of many consumers. Today, most U.S.
households maintain a household vehicle fleet that serves a variety of
purposes and represents a variety of fuel efficiency levels.
Manufacturers have responded to fuel economy standards and to consumer
demand over the last decade to offer a wide array of fuel-efficient
vehicles in different segments and with a wide range of features. A
household may now respond to short-term increases in fuel price by
shifting vehicle miles traveled within their household fleet away from
less-efficient vehicles and toward models with higher fuel economy. A
similar option existed in the 1970s, though not as widely as today, and
vehicle owners in 2018 do not have to sacrifice as much utility as
owners did in the 1970s when making fuel-efficiency trade-offs within
their household fleets (or when replacing household vehicles at the
time of purchase). On a longer-term basis, if oil prices rise,
consumers have more options to invest in additional fuel economy when
purchasing new vehicles than at any other time in history.
Global oil demand conditions are also different than in previous
years. Countries that had very small markets for new light-duty
vehicles in the 1970s are now driving global production as their
economies improve and growing numbers of middle-class consumers are
able to purchase vehicles for personal use. The global increase in
drivers inevitably affects global oil demand, which affects oil prices.
However, these changes generally occur gradually over time, unlike a
disruption that causes a gasoline price shock. Market growth happens
relatively gradually and is subject to many different factors. Oil
supply markets likely have time to adjust to increases in demand from
higher vehicle sales in countries like China and India, and in fact,
those increases in demand may temper global prices by keeping
production increasing more steadily than if demand was less certain;
clear demand rewards increased production and encourages additional
resource development over time. It therefore seems unlikely that growth
in these vehicle markets could lead to gasoline price shocks. Moreover,
even as these vehicle markets grow, it is possible that these and other
vehicle markets may be moving away from petroleum usage under the
direction of their governments.\447\ If this occurs, global oil
production will fall in response to reduced global demand, but latent
production capacity would exist to offset the impacts of unexpected
supply interruptions and maintain a level of global production that is
accessible to petroleum consumers. This, too, would seem likely to
reduce the risk of gasoline price shocks.
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\447\ Lynes, M. Plug-in electric vehicles: future market
conditions and adoption rates, U.S. Energy Information
Administration (Oct. 23, 2017), https://www.eia.gov/outlooks/ieo/pev.php.
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Considering all of the above factors, if gasoline price shocks are
no longer as much of a threat as they were when EPCA was originally
passed, it seems reasonable to consider what the need of the United
States to conserve oil is today and going forward. Looking to the
discussion above on what factors are relevant to the need of the United
States to conserve oil, one may conclude that the U.S. is no longer as
dependent upon petroleum as the engine of economic prosperity as it was
when EPCA was passed. The national balance of payments considerations
are likely drastically less important than they were in the 1970s, at
least in terms of oil imports and vehicle fuel economy. Foreign policy
considerations appear to have shifted along with the supply shifts also
discussed above.
Whether and how environmental considerations create a need for CAFE
standards is, perhaps, more complicated. As discussed earlier in this
document, carbon dioxide is a direct byproduct of the combustion of
carbon-based fuels in vehicle engines.\448\ Many argue that it is
likely that human activities, especially emissions of greenhouse gases
like carbon dioxide, contribute to the observed climate warming since
the mid-20th century.\449\ Even taking that premise as given, it is
reasonable to ask whether rapid ongoing increases in CAFE stringency
(or even, for that matter, electric vehicle mandates) can sufficiently
address climate change to merit their costs. To ``conserve,'' again,
means ``to avoid wasteful or destructive use of.''
---------------------------------------------------------------------------
\448\ Depending on the energy source, it may also be a byproduct
of consumption of electricity by vehicles.
\449\ Climate Science Special Report: Fourth National Climate
Assessment, Volume I (Wuebbles, D.J. et al., eds. 2017), available
at https://science2017.globalchange.gov/ (last accessed Feb. 23,
2018).
---------------------------------------------------------------------------
Some commenters have argued essentially that any petroleum use is
destructive because it all adds incrementally to climate change. They
argue that as CAFE standards increase, petroleum use will decrease;
therefore CAFE standard stringency should increase as rapidly as
possible. Other commenters, recognizing that economic practicability is
also relevant, have argued essentially that because more stringent CAFE
standards produce less CO2 emissions, NHTSA should simply
set CAFE standards to increase at the most rapid of the alternative
rates that NHTSA cannot prove is economically impracticable. The
question here, again, is whether the additional fuel saved (and
CO2 emissions avoided) by more rapidly increasing CAFE
standards better satisfies the U.S.'s need to avoid destructive or
wasteful use of energy than more moderate approaches that more
appropiately balance other statutory considerations.
In the context of climate change, NHTSA believes it is hard to say
that increasing CAFE standards is necessary to avoid destructive or
wasteful use of energy as compared to somewhat-less-rapidly-increasing
CAFE standards. The most stringent of the regulatory
[[Page 43216]]
alternatives considered in the 2012 final rule and FRIA (under much
more optimistic assumptions about technology effectiveness), which
would have required a seven percent average annual fleetwide increase
in fuel economy for MYs 2017-2025 compared to MY 2016 standards, was
forecast to only decrease global temperatures in 2100 by 0.02 [deg]C in
2100. Under NHTSA's current proposal, we anticipate that global
temperatures would increase by 0.003 [deg]C in 2100 compared to the
augural standards. As reported in NHTSA's Draft EIS, compared to the
average global mean surface temperature for 1986-2005, global surface
temperatures are still forecast to increase by 3.484-3.487 [deg]C,
depending on the alternative. Because the impacts of any standards are
small, and in fact several-orders-of-magnitude smaller, as compared to
the overall forecast increases, this makes it hard for NHTSA to
conclude that the climate change effects potentially attributable to
the additional energy used, even over the full lifetimes of the
vehicles in question, is ``destructive or wasteful'' enough that the
``need of the U.S. to conserve energy'' requires NHTSA to place an
outsized emphasis on this consideration as opposed to others.\450\
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\450\ The question of whether or how rapidly to increase CAFE
stringency is different from the question of whether to set CAFE
standards at all. Massachusetts v. EPA, 549 U.S. 497 (2007)
(``Agencies, like legislatures, do not generally resolve massive
problems in one fell regulatory swoop.'')
---------------------------------------------------------------------------
Consumer costs are the remaining issue considered in the context of
the need of the U.S. to conserve energy. NHTSA has argued in the past,
somewhat paternalistically, that CAFE standards help to solve
consumers' ``myopia'' about the value of fuel savings they could
receive, when buying a new vehicle if they chose a more fuel-efficient
model. There has been extensive debate over how much consumers do (and/
or should) value fuel savings and fuel economy as an attribute in new
vehicles, and that debate is addressed in Section II.E. For purposes of
considering the need of the U.S. to conserve energy, the question of
consumer costs may be closer to whether U.S. consumers so need to save
money on fuel that they must be required to save substantially more
fuel (through purchasing a new vehicle made more fuel-efficient by more
stringent CAFE standards) than they would otherwise choose.
Again, when EPCA originally passed, Congress was trying to protect
U.S. consumers from the negative effects of another gasoline price
shock. It appears much more likely today that oil prices will rise only
moderately in the future and that price shocks are less likely.
Accordingly, it is reasonable to believe that U.S. consumers value
future fuel savings accurately and choose new vehicles based on that
view. This is particularly true, since Federal law requires that new
vehicles be posted with a window sticker providing estimated costs or
savings over a five year period compared to average new vehicles.\451\
Even if consumers do not explicitly think to themselves ``this new car
will save me $5,000 in fuel costs over its lifetime compared to that
other new car,'' gradual and relatively predictable fuel price
increases in the foreseeable future allow consumers to roughly estimate
the comparative value of fuel savings among vehicles and choose the
amount of fuel savings that they want, in light of the other vehicle
attributes they value. It seems, then, that consumer cost as an element
of the need of the U.S. to conserve energy is also less urgent in the
context of the structural changes in oil markets over the last several
years.
---------------------------------------------------------------------------
\451\ 49 CFR 575.401; 40 CFR 600.302-12.
---------------------------------------------------------------------------
Given the discussion above, NHTSA tentatively concludes that the
need of the U.S. to conserve energy may no longer function as assumed
in previous considerations of what CAFE standards would be maximum
feasible. The overall risks associated with the need of the U.S. to
conserve oil have entered a new paradigm with the risks substantially
lower today and projected into the future than when CAFE standards were
first issued and in the recent past. The effectiveness of CAFE
standards in reducing the demand for fuel combined with the increase in
domestic oil production have contributed significantly to the current
situation and outlook for the near- and mid-term future. The world has
changed, and the need of the U.S. to conserve energy, at least in the
context of the CAFE program, has also changed.
Of the other factors under 32902(g), the changes are perhaps less
significant. We continue to believe that technological feasibility, per
se, is not limiting during this rulemaking time frame. The technologies
considered in this analysis either are already in commercial production
or likely will be by MY 2021--some at great expense. Based on our
analysis, all of the alternatives appear as though they could narrowly
be considered technologically feasible, in that they could be achieved
based on the existence or the projected future existence of
technologies that could be incorporated on future vehicles. Any of the
alternatives could thus be achieved on a technical basis alone but only
if the level of resources that might be required to implement the
technologies is not considered. However, as discussed above, we no
longer view the need of the U.S. to conserve energy as nearly infinite,
which means that it no longer combines with boundless technological
feasibility to quickly push stringency upward.
The effect of other motor vehicle standards of the Government on
fuel economy is similarly not limiting during this rulemaking time
frame. As discussed above, the analysis projects that safety standards
will add some mass to new vehicles during this time frame and accounts
for Tier 3 compliance in estimates of technology effectiveness, but
neither of these things appear likely to make it significantly harder
for industry to comply with more stringent CAFE standards. In terms of
EPA's GHG standards, as also discussed above, NHTSA and EPA's
coordination in this proposal should make the two sets of standards
similarly binding, although differences in compliance provisions remain
such that which standards are more binding will vary somewhat between
manufacturers and over time.
The remaining factor to consider is economic practicability. NHTSA
has typically defined economic practicability, as discussed above, as
whether a given CAFE standard is ``within the financial capability of
the industry but not so stringent as'' to lead to ``adverse economic
consequences, such as a significant loss of jobs or unreasonable
elimination of consumer choice.'' As part of that definition, NHTSA
looks at a variety of elements that can lead to adverse economic
consequences. All of the alternatives considered today arguably raise
economic practicability issues. NHTSA believes there could be potential
for unreasonable elimination of consumer choice, loss of U.S. jobs, and
a number of adverse economic consequences under nearly all if not all
of the regulatory alternatives considered today.
If a potential CAFE standard requires manufacturers to add
technology to new vehicles that consumers do not want, or to skip
adding technology to new vehicles that consumers do want, it would seem
to present issues with elimination of consumer choice. Depending on the
extent and expense of required fuel saving technology, that elimination
of consumer choice could be unreasonable.
When deciding on which new vehicle to purchase, American consumers
[[Page 43217]]
generally tend not to be interested in better fuel economy above other
attributes, particularly when gasoline prices are low.\452\
Manufacturers have repeatedly indicated to the agencies that new
vehicle buyers are only willing to pay for fuel economy-improving
technology if it pays back within the first two to three years of
vehicle ownership.\453\ NHTSA has therefore incorporated this
assumption (of willingness to pay for technology that pays back within
30 months) into today's analysis. As a result, NHTSA's analysis finds
that the most cost-effective technology is applied with or without CAFE
(or CO2) standards, diminishing somewhat the incremental
cost-effectiveness of new CAFE standards.
---------------------------------------------------------------------------
\452\ See, e.g., Comment by Global Automakers, Docket ID NHTSA-
2016-0068-0062 (citing a 2014 study by Strategic Vision that found
that ``. . . generally, customers as a whole place a higher priority
on handling and ride than fuel economy.'').
\453\ This is supported by the 2015 NAS study, which found that
consumers seek to recoup added upfront purchasing costs within two
or three years. See 2015 NAS Report, at pg. 317.
---------------------------------------------------------------------------
Consumers not being interested in better fuel economy can take two
forms: First, it can dampen sales of vehicles with the additional
technology required to meet the standards, and second, it can increase
sales of vehicles that do not help manufacturers meet the standards
(such as vehicles that fall significantly short of their fuel economy
targets, due to higher levels of performance (e.g., larger, less
efficient engines) or other features). Over the last several years,
despite record sales overall, most manufacturers have been managing
their CAFE compliance obligations through use of credits,\454\ because
many consumers have chosen to buy vehicles that do not improve
manufacturers' compliance positions.
---------------------------------------------------------------------------
\454\ See CAFE Public Information Center, National Highway
Traffic Safety Administration, https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Mfr_LIVE.html (last visited June 25, 2018). Readers can
examine achieved versus required fuel economy by model year and by
individual manufacturer or by entire fleets. When a manufacturer's
achieved fuel economy falls short of required fuel economy but the
manufacturer has not paid civil penalties, the manufacturer is using
credits somehow to make up the shortfall.
---------------------------------------------------------------------------
Consumer decisions to purchase relatively low-fuel economy vehicles
might seem irrational if gasoline prices were expected to rebound in
the future, but current indicators suggest this is not particularly
likely. Although we know of no clear ``tipping point'' for gasoline
prices at which American consumers suddenly become more interested in
fuel economy over other attributes, In addition, EIA's latest AEO 2018
suggests, based on current assumptions, that per-gallon prices are
likely to stay under $4 through 2050.\455\ It therefore seems unlikely
that consumer preferences are going to change dramatically in the
foreseeable future and certainly not within the time frame of the
standards covered by this proposal.
---------------------------------------------------------------------------
\455\ As noted elsewhere in this proposal, the agencies based
analysis on AEO 2017 projections of, for instance, fuel prices, as
it was the best available information at the time the analysis was
conducted. As such, where possible, the agency incorporated latest
AEO 2018 projections into the discussion, in effort to re-confirm no
discernible impact to analysis results or to provide the best
possible information for the discussion.
---------------------------------------------------------------------------
Thus, if manufacturers are not currently able to sell higher-fuel
economy vehicles without heavy subsidization, particularly HEVs, PHEVs,
and EVs, it seems unlikely that their ability to do so will improve
unless consumer preferences change or fuel prices rise significantly,
either of which seem unlikely. Today's analysis indicates, perhaps
predictably, that electrification rates must increase as stringency
increases among the options the agencies are considering.
[[Page 43218]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.157
[[Page 43219]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.158
[[Page 43220]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.159
[[Page 43221]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.160
Manufacturers have commented to the agencies that ``Although
automakers are offering more of these models every year, with improved
technology and options, sales of these vehicles are not growing,''
noting that even for hybrid
[[Page 43222]]
vehicles, which require no adaptation by consumers (for example, to
range limits or refueling by charging), sales ``have declined from a
peak of a 3.1 percent share of the market (in 2013) to . . . 1.8
percent [in 2016].'' \456\ The same source further stated that this
decline was despite the technology being available in the market for
more than 15 years, and that in 2016, ``close to 75 percent of the
people who have traded in a hybrid or electric car to a dealer have
replaced it with a conventional (non-hybrid) gasoline-powered car.''
\457\ While some consumers continue to seek out hybrid and electric
vehicles, then, many other consumers seem uninterested in them, even
given the generous incentives and subsidies often available for
consumers in the form of tax credits, government rebates, High
Occupancy Vehicle Lane access, preferred and/or subsidized parking,
among others. Despite this broad ongoing lack of consumer interest, a
number of manufacturers nonetheless continue to increase their
offerings of these vehicles. At best, this trend seems economically
inefficient; more concerningly for economic practicability, it seems
likely to impact consumer choice (as discussed further below) in ways
that could weigh heavily on sales, jobs, and consumers themselves. We
seek comment on this issue.
---------------------------------------------------------------------------
\456\ Comment by Global Automakers, Docket ID NHTSA-2016-0068-
0062, citing IHS Global New Vehicle Registration Data for 2013,
2015, and January-June 2016.
\457\ Id. at B-6 and B-7, citing Matt Richtel, American Drivers
Regain Appetite for Gas Guzzlers, New York Times (June 24, 2016),
https://www.nytimes.com/2016/06/28/science/cars-gas-global-warming.html.
---------------------------------------------------------------------------
If the evidence indicates that hybrid sales are declining as
gasoline prices remain low, it seems reasonable to conclude that
consumers will not choose to buy more of them going forward as gasoline
prices are forecast to remain low. This is consistent with the analysis
discussed in Section II.E, that even while some consumers may be
willing to pay between $2,000 and $3,000 more for vehicles with
electrified technologies, that incremental willingness-to-pay falls
well short of the additional costs projected for HEVs, PHEVs, and EVs.
This trend may well extend beyond electrification technologies to other
technologies. When costs for fuel economy-improving technology exceed
the fuel savings, consumers may very well be unwilling to pay the full
cost for vehicles with higher fuel economy that would be increasingly
needed as to comply as the stringency of the alternatives increases.
If consumers are not willing to pay the full cost for vehicles with
higher fuel economy, it seems reasonably foreseeable that they will
consider vehicles made more expensive by higher CAFE standards to be
not ``available'' to them to purchase--or put more simply, that they
will be turned off by more expensive vehicles with technologies they do
not want, and seek instead to purchase cheaper vehicles without that
technology (or with different technologies, such as those that improve
performance or safety). Manufacturers have long cross-subsidized
vehicle models in their lineups in order to recoup costs in cases where
they do not believe they can pass the full costs of development and
production forward as price increases for the vehicle model in
question. Given that this cross-subsidization is ongoing, however, and
possibly deepening as manufacturers have had to meet increasingly
stringent CAFE standards over the past several years, it is unclear how
much additional distribution of costs could be supported by the market.
Certainly, if CAFE standards continue to increase in stringency as
gasoline prices stay relatively low and consumer willingness to pay for
significant additional fuel economy improvements remains
correspondingly low, then additional cross-subsidization of products to
try to ease those products into consumer acceptance seems likely to
impair consumer choice, insofar as the vehicles they want to buy will
cost more and may have technology for which they are unwilling to pay.
Models that have historically been able to bear higher percentages of
the cross-subsidization burden may not be able to bear much more--a
pickup truck buyer, for example, may eventually decide to purchase a
used vehicle, another type of vehicle, or a pickup made by a different
manufacturer rather than pay the extra cost that the manufacturer is
trying to recoup from higher-fuel economy vehicles that had to be
artificially discounted to be sold. We seek comment on the effect of
fuel economy standards on cross-subsidization across models.
Moreover, assuming that manufacturers try to pass the costs of
those technologies on to consumers in the form of higher new vehicle
prices, rather than absorbing them and hurting profitability, this can
affect consumers' ability to afford new vehicles. The analysis assumes
that the increased cost of meeting standards is passed on to consumers
through higher new vehicle prices, and looks at those increases as a
one-time payment. In the context of, for example, a $30,000 new
vehicle, another $2,000 may not seem significant to some readers. Yet
manufacturers and dealers have repeatedly commented to NHTSA that the
overall price of the vehicle is less relevant to the majority of
consumers than the monthly payment amount, which is a significant
factor in consumers' ability to purchase or lease a new vehicle.
Amortizing a $2,000 price increase over, for example, 48 months may
also not seem like a large amount to some readers, even accounting for
interest payments. Yet the corresponding up-front and monthly costs may
pose a challenge to low-income or credit-challenged purchasers. As
discussed previously, such increased costs will price many consumers
out of the market--leaving them to continue driving an older, less
safe, less efficient, and more polluting vehicle, or purchasing another
used vehicle that would likewise be less safe, less efficient, and more
polluting than an equivalent new vehicle.
For example, the average MY 2025 prices estimated here under the
baseline and proposed CAFE standards are about $34,800 and $32,750,
respectively (and $34,500 and $32,550 under the baseline and proposed
GHG standards). The buyer of a new MY 2025 vehicle might thus avoid the
following purchase and first-year ownership costs under the proposed
standards:
[[Page 43223]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.161
While the buyer of the average vehicle would also purchase somewhat
more fuel under the proposed standards, this difference might average
only five gallons per month during the first year of ownership.\462\
Some purchasers may consider it more important to avoid these very
certain (e.g., being reflected in signed contracts) cost savings than
the comparatively uncertain (because, e.g., some owners drive
considerably less than others, and may purchase fuel in small
increments as needed) fuel savings. For some low-income purchasers or
credit-challenged purchasers, the cost savings may make the difference
between being able or not to purchase the desired vehicle. As vehicles
get more expensive in response to higher CAFE standards, it will get
more and more difficult for manufacturers and dealers to continue
creating loan terms that both keep monthly payments low and do not
result in consumers still owing significant amounts of money on the
vehicle by the time they can be expected to be ready for a new vehicle.
---------------------------------------------------------------------------
\458\ Using down payment assumption of $4,056. See Press
Release, Edmunds, New Vehicle Prices Climb to All-Time High in
December (Jan. 3, 2018), https://www.edmunds.com/about/press/new-vehicle-prices-climb-to-all-time-high-in-december.html.
\459\ Using average rate of 5.46% (discussed above in Section
II.E).
\460\ Using average rate of 4.25% (discussed above in Section
II.E).
\461\ Using average rate of 1.83% (discussed above in Section
II.E).
\462\ Based on estimated sales volumes and average fuel
consumption discussed below in Section VI, and on average vehicle
survival and mileage accumulation rates (discussed above in Section
II.E) indicating that the average vehicle delivers about 11% of it
lifetime service (i.e., distance driven) during the first year of
operation.
---------------------------------------------------------------------------
Over the last decade, as vehicle sales have rebounded in the wake
of the recession, historically low interest rates and increases in the
average duration of financing terms have helped manufacturers and
dealers keep consumers' monthly payments low. These trends (low
interest rates and longer loan periods), along with pent-up demand for
new vehicles, have helped keep vehicle sales high. As interest rates
have increased, and most predict will continue to rise, monthly
payments will foreseeably increase, and the ability to offset such
increases by extending finance terms to account for increased finance
charges and vehicle prices due to CAFE standards is limited by the fact
that doing so increases the amount of time before consumers will have
positive equity in their vehicles (and able to trade in the vehicle for
a newer model). This reduces the mechanisms that manufacturers, captive
finance companies, dealers, and independent lenders have in order to
maintain sales at comparable levels. In other words, if vehicle sales
have not already hit the breaking point, they may be close.\463\ The
agencies seek comment on the impact that increased prices, interest
rates, and financing terms are likely to have on the new vehicle
market.
---------------------------------------------------------------------------
\463\ See, e.g., Comment by Global Automakers, Docket ID NHTSA-
2016-0068-0062, at 10 (``Current sales are a poor predictor of
future sales. Many of the macroeconomic factors that have
contributed to the current boom may not exist six to nine years into
the future [i.e., during the mid-2020s]. The low interest loans and
extended time loans that are now readily available may not be
available then. The automotive industry is a cyclical business, and
it appears to be near the top of a cycle now.'')
---------------------------------------------------------------------------
[[Page 43224]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.162
The increasing risk that manufacturers and dealers will hit a wall
in their ability to keep monthly payments low may fall
disproportionately on new and low-income buyers. To build on the
discussion above, manufacturers often purposely cross-subsidize the
prices of entry-level vehicles to keep monthly payments low and attract
new and young consumers to their brand. Higher CAFE standard stringency
leads to higher costs for technology across manufacturers' fleets,
meaning that more and more cross-subsidization becomes necessary to
maintain affordability for entry-level vehicle purchasers. While this
is clearly an economic issue for industry, it may also slow fleet-wide
improvement in vehicle characteristics like safety--both in terms of
manufacturers having to divert resources to adding technology to
vehicles that consumers do not want and then figuring out how to get
consumers to buy them and in terms of new vehicles potentially becoming
unaffordable for certain groups of consumers, meaning that they must
either defer new vehicle purchases or turn to the used vehicle market,
where levels of safety may not be comparable. We seek comment on these
considerations.
Alternatively, rather than or in addition to continuing to cross-
subsidize fuel economy improvements that consumers are unwilling to pay
for directly, manufacturers may choose to try to improve their
compliance position under higher CAFE standards by restricting sales of
certain vehicle models or options. If consumers tend to want the 6-
cylinder engine version of a vehicle rather than the 4-cylinder
version, for example, the manufacturer may choose to make fewer 6-
cylinders available. This solution, if chosen, would directly impact
consumer choice. It seems increasingly likely that this solution could
be chosen as CAFE stringency increases.
In terms of risks to employment, today's analysis focuses on
employment as a function of estimated changes in vehicle price in
response to different levels of standards and assumes that all cost
increases to vehicle models are passed forward to consumers in the form
of price increases for that vehicle model. As Section VII.C on today's
sales and employment analysis indicates, the sales function of the CAFE
model appears fairly accurate at predicting sales trends but does not
presume that sales are particularly responsive to changes in vehicle
price. We are concerned, however, that the sales model as it currently
functions may miss two key points about potential future sales and
employment effects.
First, the analysis does not account for the risk discussed above
that manufacturers and dealers may not be able to continue keeping
monthly new vehicle payments low, for a variety of reasons. Interest
rates and inflation may rise; further lengthening loan terms may not be
practical as they increase the period of time that the purchaser has
negative equity (which has secondary impacts described above). While
these may be not-entirely-negative things for the economy as a whole,
they would create negative pressure on vehicle sales or employment
associated with those sales.
Second, as the cost of compliance increases with CAFE stringency,
it is possible that manufacturers may shift
[[Page 43225]]
production overseas to locations where labor is cheaper. The CAFE
program contains no mandates with regard to where vehicles are
manufactured and arguably disincentivizes domestic production of
passenger cars through the minimum domestic passenger car standard. If
it becomes substantially more expensive for manufacturers to meet their
CAFE obligations, they may seek to cut costs wherever they can, which
could include layoffs or changing production locations.
There may be other adverse economic consequences besides those
discussed above. If manufacturers seek to avoid losing sales by
absorbing the additional costs of meeting higher CAFE standards, it is
foreseeable that absorbing those costs would hurt company profits. If
manufacturers choose that approach year after year to avoid losing
market share, continued falling profits would lead to negative earnings
reports and risks to companies' long-term viability. Thus, even if
sales levels are maintained despite higher standards, it seems possible
that industry could face adverse economic consequences.
More broadly, when gasoline prices stay relatively low (as they are
expected to remain through the lifetime of nearly all vehicles covered
by the rulemaking time frame), higher stringency standards are
increasingly less cost-beneficial. As shown and discussed in Section
VII.C, the analysis of consumer impacts shows that consumers recoup
only a portion of the costs associated with increasing stringency under
all of the alternatives. The fuel savings resulting from each of the
alternatives is substantially less than the costs associated with the
alternative, meaning that net savings for consumers improves as
stringency decreases. Figure V-2 below illustrates this trend.\464\
---------------------------------------------------------------------------
\464\ For the reader's reference, Alternatives 3 and 7 phase out
A/C and off-cycle procedures, while the other alternatives leave
those procedures unchanged. Phasing out these procedures increases
compliance costs and reduces net savings relative to leaving the
procedures unchanged, net savings to consumer with seven percent
discount rate.
[GRAPHIC] [TIFF OMITTED] TP24AU18.163
We recognize that this is a significantly different analytical
result from the 2012 final rule, which showed the opposite trend. Using
the projections available to the agencies for the 2012 rulemaking, all
of the alternatives considered in that rulemaking were projected to
have net savings to consumers and to society overall, and those net
savings improved as stringency increased. Put simply, the result is
different today from what it was in 2012 because the facts and the
analysis are also different. While the differences in the facts and the
analysis are described extensively in Section II above and in the PRIA
---------------------------------------------------------------------------
accompanying this proposal, a few noteworthy ones include:
In 2012, we assumed in the main analysis that
manufacturers would add no more technology than needed for
compliance, while today's analysis assumes logically that
manufacturers will add technologies that pay for themselves within
2.5 years, consistent with manufacturer information on payback
period.
In 2012, we measured impacts of the post-2017 standards
relative to compliance with pre-2017 standards, which meant that a
lot of cost-effective technology attributable to the 2017-2020
standards was ``counted'' toward the 2025 standards.
In 2012, we used analysis fleets based on 2008 or 2010
technology. Today's analysis uses a 2016-based analysis fleet.
These three points above mean that, overall, the current analysis
fleet reflects the application of much additional technology than the
2012-final-rule analysis fleet reflected. When technology is used by
the analysis fleet, it is ``unavailable'' to be used again for
compliance with future standards because the same technology cannot be
used twice (once by a manufacturer for its own reasons and then again
by the model to simulate manufacturer responses to higher standards).
Some of this would happen necessarily in an updated rulemaking because
a later-in-time analysis fleet inevitably includes more technology; in
this particular case, 2016 happened to be a somewhat technology-heavy
year, and 2008 and 2010 (the fleets used in 2012) arguably did not
reflect the state of technology in 2012 well.
Furthermore, readers should note the following changes:
[[Page 43226]]
Estimates of effectiveness and cost are different for a
number of technologies, as discussed in Section II above and in
Chapter 6 of the PRIA, and indirect costs are determined using the
RPE rather than the ICM;
Fuel prices forecasts are considerably lower in AEO
2017 than they were in AEO 2012;
The current analysis uses a rebound effect value of 20%
instead of 10%;
The current analysis newly accounts for price impacts
on fleet turnover;
The social cost of carbon is different and accounts
only for domestic (not international) impacts;
The current analysis does not attempt to purposely
limit the appearance of potential safety effects, and the value of a
statistical life is higher than in 2012.
All of these changes, together, mean that the standards under any
of the regulatory alternatives (compared to the preferred alternative)
are more expensive and have lower benefits than if they had been
calculated using the inputs and assumptions of the 2012 analysis. This,
in turn, helps lead the agency to a different conclusion about what
standards might be maximum feasible in the model years covered by the
rulemaking. NHTSA has thus both relied on new facts and circumstances
in developing today's proposal and reasonably rejected prior facts and
analyses relied on in the 2012 final rule.\465\
---------------------------------------------------------------------------
\465\ See Fox v. FCC, 556 U.S. at 514-515; see also NAHB v. EPA,
682 F.3d 1032 (D.C. Cir. 2012).
---------------------------------------------------------------------------
By directing NHTSA to determine maximum feasible standards by
considering the four factors, Congress recognized that ``maximum
feasible'' may change over time as the agency assessed the relative
importance of each factor.\466\ If one factor appears to be more
important than the others in the time frame to be covered by the
standards, it makes sense to give it more weight in the agency's
determination of maximum feasible standards for those model years. If
no factor appears to be particularly paramount, it makes sense to
determine maximum feasible standards by more generally weighing each
factor, as long as EPCA's direction to establish maximum feasible
standards continues to be fulfilled in a manner that does not undermine
energy conservation.
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\466\ If this were not accurate, it seems illogical that
Congress would have, at various times, set specific mpg goals for
the CAFE program (e.g., 35 mpg by 2020).
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NHTSA tentatively concludes that proposing CAFE standards that hold
the MY 2020 curves for passenger cars and light trucks constant through
MY 2026 would be the maximum feasible standards for those fleets and
would fulfill EPCA's overarching purpose of energy conservation in
light of the facts before the agency today and as we expect them to be
in the rulemaking time frame. In the 2012 final rule that established
CAFE standards for MYs 2017-2021, and presented augural CAFE standards
for MYs 2022-2025, NHTSA stated that ``maximum feasible standards would
be represented by the mpg levels that we could require of the industry
before we reach a tipping point that presents risk of significantly
adverse economic consequences.'' \467\ However, the context of that
rulemaking was meaningfully different from the current context. At that
time, NHTSA understood the need of the U.S. to conserve energy as
necessarily pushing the agency toward setting stricter and stricter
standards. Combining a then-paramount need of the U.S. to conserve
energy with the perception that technological feasibility should no
longer be seen as an important limiting factor, NHTSA then concluded
that only significant economic harm would be a basis for controlling
the pace at which CAFE stringency increased over time.
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\467\ 77 FR 62624, 63039 (Oct. 15, 2012).
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Today, the relative importance of the need of the U.S. to conserve
energy has changed when compared to the beginning of the CAFE program
and a great deal even since the 2012 rulemaking. As discussed above,
the effectiveness of CAFE standards in reducing the demand for fuel
combined with the increase in domestic oil production have contributed
significantly to the current situation and outlook for the near- and
mid-term future. The world has changed, and the need of the U.S. to
conserve energy may no longer disproportionately outhweigh other
statutorily-mandated considerations such as economic practicability--
even when considering fuel savings from potentially more-stringent
standards.
Thus, while more stringent standards may be possible, insofar as
production-ready technology exists that the industry could physically
employ to reach higher standards, it is not clear that higher standards
are now economically practicable in light of current U.S. consumer
needs to conserve energy. While vehicles can be built with advanced
fuel economy-improving technology, this does not mean that consumers
will buy the new vehicles that might be required to include such
technology; that industry could continue to subsidize their production
and sale; or that adverse economic consequences would not result from
doing so. The effect of other motor vehicle standards of the Government
is minimal when the two agencies regulating the same aspects of vehicle
performance are working together to develop those regulations.
Therefore, NHTSA views the determination of maximum feasible standards
as a question of the appropriateness of standards given that their
need--either from the societal-benefits perspective in terms of risk
associated with gasoline price shocks or other related catastrophes, or
from the private-benefits perspective in terms of consumer willingness
to purchase new vehicles with expensive technologies that may allow
them to save money on future fuel purchases--seems likely to remain low
for the foreseeable future.
When determining the maximum feasible standards, and in particular
the economic practicability of higher standards, we also note that the
proposed standards have the most positive effect on on-road safety as
compared to the alternatives considered. The analysis indicates that,
compared to the baseline standards defining the No-Action alternative,
any regulatory alternatives under consideration would improve overall
highway safety. Some of this estimated reduction is attributable to
vehicles, themselves, being generally safer if they do not apply as
much mass reduction to passenger cars as might be applied under the
baseline standards. Additionally, the analysis estimates that the
alternatives to the baseline standards would cause the fleet to turn
over to newer and safer vehicles, which will also be more fuel
efficient than the vehicles being replaced, more quickly than otherwise
anticipated. Furthermore, the analysis estimates that the alternatives
to the baseline standard would involve reduced overall demand for
highway travel. As discussed above in Section II.F, and in Chapter 11
of the accompanying PRIA, most of the estimated overall improvement in
highway safety from this proposal is attributable to reduced travel
demand (attributable to the rebound effect) and accelerated turnover to
safer vehicles. The trend in these results is clear, with the less
stringent alternatives producing the greatest estimated improvement in
highway safety and the proposed standards producing the most favorable
outcomes from a highway safety perspective. These considerations
bolster our determination that the proposed standards are maximum
feasible based upon current and projected technology for the model
years in question.
Standards that retain the MY 2020 curves through MY 2026 will save
fuel
[[Page 43227]]
beyond what the market would achieve on its own for vehicles
manufactured during the rulemaking time frame and will result in the
highest net benefits both for consumers and for society. Such standards
would avoid the risks identified in the discussion of economic
practicability for more stringent standards and are consistent with the
relatively lower need of the United States to conserve energy and the
impact that has on consumer choice. Moreover, as the fuel economy of
the new vehicle fleet improves over time, the marginal benefits of
continued improvements diminish, making the consumer willingness to
bear them and the economic practicability of them diminish. It is much
more expensive, and saves much less fuel, for a vehicle to improve from
40 to 50 mpg, than for a vehicle to improve from 15 to 20 mpg.\468\ If
obtaining the marginal benefits of new cars and their fuel economy
technologies becomes too expensive for consumers, some consumers will
choose to drive less efficient used vehicles longer.
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\468\ As the base level of fuel economy improves, there are
fewer gallons to be saved from improving further. A typical
assumption is that vehicles are driven 15,000 miles per year. A
vehicle that improves from 30 mpg to 40 mpg reduces its annual fuel
consumption from 500 gallons/year to 375 gallons/year at 15,000
miles/year or by 125 gallons. A vehicle that improves from 15 mpg to
20 mpg, on the other hand, reduces its annual fuel consumption from
1,000 gallons/year to 750 gallons/year--twice as much as the first
example, even though the mpg improvement is only half as large.
Going from 40 to 50 mpg would save only 75 gallons/year at 15,000
miles/year. If fuel prices are high, the value of those gallons may
be sufficient to offset the cost of improving further, but (1) EIA
does not currently anticipate particularly high fuel prices in the
foreseeable future, and (2) as the baseline level of fuel economy
continues to increase, the marginal cost of the next gallon saved
similarly increases with the cost of the technologies required to
meet the savings.
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NHTSA recognizes that the Ninth Circuit has previously held that
NHTSA must consider whether a ``backstop'' is necessary for the CAFE
standards based on the EPCA factors in 49 U.S.C. 32902(f), given that
the overarching purpose of EPCA is energy conservation.\469\ NHTSA and
EPA discussed the concept of backstops in the context of the modern
CAFE program (as opposed to the CAFE program at issue in the Ninth
Circuit decision) in the 2010 final rule establishing CAFE and GHG
standards for MYs 2012-2016. In that document, the agencies explained
that even if the statute did not preclude a backstop beyond what was
already provided for in the minimum domestic passenger car CAFE
standard and in the ``flat'' portions of the footprint curves at the
larger-footprint end, designing an appropriate backstop was likely to
be fairly complex and likely to undermine Congress' objective in
requiring attribute-based standards. See, particularly, 75 FR at 25369-
70 (May 7, 2010).
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\469\ CBD v. NHTSA, 508 F.3d 508, 537 (9th Cir. 2007), opinion
vacated and superseded on denial of reh'g, 538 F.3d 1172 (9th Cir.
2008).
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As in 2010, NHTSA believes that additional backstop standards are
not necessary. The current proposal is based on the agency's best
current understanding of the need of the U.S. to conserve energy now
and going forward, in light of changed circumstances and balanced
against the other EPCA factors. We seek comment on how an additional
backstop standard might be constructed that addresses the concerns
raised in the 2010 final rule and that also does not obviate the
agency's assessment of what CAFE levels would be maximum feasible.
We seek comment on all aspects of the above discussion.
B. EPA's Statutory Obligations and Why the Proposed Standards Appear To
Be Appropriate and Reasonable
1. Basis for the CO2 Standards Under Section 202(a) of the
Clean Air Act
Title II of the Clean Air Act (CAA) provides for comprehensive
regulation of mobile sources, authorizing EPA to regulate emissions of
air pollutants from all mobile source categories. Under Section 202(a)
\470\ and relevant case law, as discussed below, EPA considers such
issues as technology effectiveness, its cost (both per vehicle, per
manufacturer, and per consumer), the lead time necessary to implement
the technology, and based on this the feasibility and practicability of
potential standards; the impacts of potential standards on emissions
reductions of both GHGs and non-GHGs; the impacts of standards on oil
conservation and energy security; the impacts of standards on fuel
savings by consumers; the impacts of standards on the auto industry;
other energy impacts; as well as other relevant factors such as impacts
on safety.
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\470\ 42 U.S.C. 7521(a).
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This proposed rule would implement a specific provision from Title
II, section 202(a).\471\ Section 202(a)(1) of the Clean Air Act (CAA)
states that ``the Administrator shall by regulation prescribe (and from
time to time revise) . . . standards applicable to the emission of any
air pollutant from any class or classes of new motor vehicles . . . ,
which in his judgment cause, or contribute to, air pollution which may
reasonably be anticipated to endanger public health or welfare.'' If
EPA makes the appropriate endangerment and cause or contribute
findings, then section 202(a) authorizes EPA to issue standards
applicable to emissions of those pollutants. Indeed, EPA's obligation
to do so is mandatory: Coalition for Responsible Regulation, 684 F.3d
at 114; Massachusetts v. EPA, 549 U.S. at 533. Moreover, EPA's
mandatory legal duty to promulgate these emission standards derives
from ``a statutory obligation wholly independent of DOT's mandate to
promote energy efficiency.'' Massachusetts, 549 U.S. at 532.
Consequently, EPA has no discretion to decline to issue greenhouse
standards under section 202(a) or to defer issuing such standards due
to NHTSA's regulatory authority to establish fuel economy standards.
Rather, ``[j]ust as EPA lacks authority to refuse to regulate on the
grounds of NHTSA's regulatory authority, EPA cannot defer regulation on
that basis.'' Coalition for Responsible Regulation, 684 F.3d at 127.
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\471\ 42 U.S.C. 7521(a).
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Any standards under CAA section 202(a)(1) ``shall be applicable to
such vehicles . . . for their useful life.'' Emission standards set by
the EPA under CAA section 202(a)(1) are technology-based, as the levels
chosen must be premised on a finding of technological feasibility.
Thus, standards promulgated under CAA section 202(a) are to take effect
only after providing ``such period as the Administrator finds necessary
to permit the development and application of the requisite technology,
giving appropriate consideration to the cost of compliance within such
period'' (CAA section 202 (a)(2); see also NRDC v. EPA, 655 F. 2d 318,
322 (D.C. Cir. 1981)). EPA must consider costs to those entities which
are directly subject to the standards. Motor & Equipment Mfrs. Ass'n
Inc. v. EPA, 627 F. 2d 1095, 1118 (D.C. Cir. 1979). Thus, ``the
[s]ection 202(a)(2) reference to compliance costs encompasses only the
cost to the motor-vehicle industry to come into compliance with the new
emission standards.'' Coalition for Responsible Regulation, 684 F.3d at
128; see also id. at 126-27 (rejecting arguments that EPA was required
to consider or should have considered costs to other entities, such as
stationary sources, which are not directly subject to the emission
standards). EPA is afforded considerable discretion under section
202(a) when assessing issues of technical feasibility and availability
of lead time to implement new technology. Such determinations are
``subject to the
[[Page 43228]]
restraints of reasonableness,'' which ``does not open the door to
`crystal ball' inquiry.'' NRDC, 655 F. 2d at 328 (quoting International
Harvester Co. v. Ruckelshaus, 478 F. 2d 615, 629 (D.C. Cir. 1973)). In
developing such technology-based standards, EPA has the discretion to
consider different standards for appropriate groupings of vehicles
(``class or classes of new motor vehicles''), or a single standard for
a larger grouping of motor vehicles (NRDC, 655 F. 2d at 338). Finally,
with respect to regulation of vehicular greenhouse gas emissions, EPA
is not ``required to treat NHTSA's . . . regulations as establishing
the baseline for the [section 202(a) standards].'' Coalition for
Responsible Regulation, 684 F.3d at 127 (noting further that ``the
[section 202 (a)standards] provid[e] benefits above and beyond those
resulting from NHTSA's fuel-economy standards'').
Although standards under CAA section 202(a)(1) are technology-
based, they are not based exclusively on technological capability. EPA
has the discretion to consider and weigh various factors along with
technological feasibility, such as the cost of compliance (see section
202(a)(2)), lead time necessary for compliance (section 202(a)(2)),
safety (see NRDC, 655 F.2d at 336 n. 31) and other impacts on
consumers,\472\ and energy impacts associated with use of the
technology (see George E. Warren Corp. v. EPA, 159 F.3d 616, 623-624
(D.C. Cir. 1998) (ordinarily permissible for EPA to consider factors
not specifically enumerated in the Act)).
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\472\ Since its earliest Title II regulations, EPA has
considered the safety of pollution control technologies. See 45 FR
14496, 14503 (March 5, 1980). (``EPA would not require a particulate
control technology that was known to involve serious safety
problems. If during the development of the trap-oxidizer safety
problems are discovered, EPA would reconsider the control
requirements implemented by this rulemaking.'')
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In addition, EPA has clear authority to set standards under CAA
section 202(a) that are technology forcing when EPA considers that to
be appropriate but is not required to do so (as compared to standards
set under provisions such as section 202(a)(3) and section 213(a)(3)).
EPA has interpreted a similar statutory provision, CAA section 231, as
follows:
While the statutory language of section 231 is not identical to
other provisions in title II of the CAA that direct EPA to establish
technology-based standards for various types of engines, EPA
interprets its authority under section 231 to be somewhat similar to
those provisions that require us to identify a reasonable balance of
specified emissions reduction, cost, safety, noise, and other
factors. See, e.g., Husqvarna AB v. EPA, 254 F.3d 195 (D.C. Cir.
2001) (upholding EPA's promulgation of technology-based standards
for small non-road engines under section 213(a)(3) of the CAA).
However, EPA is not compelled under section 231 to obtain the
``greatest degree of emission reduction achievable'' as per sections
213 and 202 of the CAA, and so EPA does not interpret the Act as
requiring the agency to give subordinate status to factors such as
cost, safety, and noise in determining what standards are reasonable
for aircraft engines. Rather, EPA has greater flexibility under
section 231 in determining what standard is most reasonable for
aircraft engines, and is not required to achieve a ``technology
forcing'' result.\473\
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\473\ 70 FR 69664, 69676 (Nov. 17, 2005).
This interpretation was upheld as reasonable in NACAA v. EPA (489
F.3d 1221, 1230 (D.C. Cir. 2007)). CAA section 202(a) does not specify
the degree of weight to apply to each factor, and EPA accordingly has
discretion in choosing an appropriate balance among factors. See Sierra
Club v. EPA, 325 F.3d 374, 378 (D.C. Cir. 2003) (even where a provision
is technology-forcing, the provision ``does not resolve how the
Administrator should weigh all [the statutory] factors in the process
of finding the `greatest emission reduction achievable' ''); see also
Husqvarna AB v. EPA, 254 F. 3d 195, 200 (D.C. Cir. 2001) (great
discretion to balance statutory factors in considering level of
technology-based standard, and statutory requirement ``[to give]
appropriate consideration to the cost of applying . . . technology''
does not mandate a specific method of cost analysis); Hercules Inc. v.
EPA, 598 F. 2d 91, 106-07 (D.C. Cir. 1978) (``In reviewing a numerical
standard, we must ask whether the agency's numbers are within a `zone
of reasonableness,' not whether its numbers are precisely right'');
Permian Basin Area Rate Cases, 390 U.S. 747, 797 (1968) (same); Federal
Power Commission v. Conway Corp., 426 U.S. 271, 278 (1976) (same);
Exxon Mobil Gas Marketing Co. v. FERC, 297 F. 3d 1071, 1084 (D.C. Cir.
2002) (same).
As noted above, EPA has found that the elevated concentrations of
greenhouse gases in the atmosphere may reasonably be anticipated to
endanger public health and welfare.\474\ EPA defined the ``air
pollution'' referred to in CAA section 202(a) to be the combined mix of
six long-lived and directly emitted GHGs: Carbon dioxide
(CO2), methane (CH4), nitrous oxide
(N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs),
and sulfur hexafluoride (SF6). The EPA further found under
CAA section 202(a) that emissions of the single air pollutant defined
as the aggregate group of these same six greenhouse gases from new
motor vehicles and new motor vehicle engines contribute to air
pollution. As a result of these findings, section 202(a) requires EPA
to issue standards applicable to emissions of that air pollutant. New
motor vehicles and engines emit CO2, CH4,
N2O, and HFC. EPA has established standards and other
provisions that control emissions of CO2, HFCs,
N2O, and CH4. EPA has not set any standards for
PFCs or SF6 as they are not emitted by motor vehicles.
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\474\ 74 FR 66496 (Dec. 15, 2009).
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2. EPA's Tentative Conclusion That the Proposed CO2
Standards Are Appropriate and Reasonable
In this section, EPA discusses the factors, data and analysis the
Administrator has considered in the selection of the EPA's proposed
revised GHG emission standards for MYs 2021 and later. EPA requests
comment on all aspects of the proposed revised standards, including all
Alternatives discussed in this section and section IV of this preamble.
As discussed in Sections I and V.B of this preamble, the primary
purpose of Title II of the Clean Air Act is the protection of public
health and welfare. EPA's light-duty vehicle GHG standards serve this
purpose, as the GHG emissions from light-duty vehicles have been found
by EPA to endanger public health and welfare (see EPA's 2009
Endangerment Finding for on-highway motor vehicles), and the goal of
these standards is to reduce these emissions that contribute to climate
change.
CAA section 202(a)(2) states when setting emission standards for
new motor vehicles, the standards ``shall take effect after such period
as the Administrator finds necessary to permit the development and
application of the requisite technology, giving appropriate
consideration to the cost of compliance within such period.'' 42 U.S.C.
7521(a)(2). That is, when establishing emissions standards, the
Administrator must consider both the lead time necessary for the
development of technology which can be used to achieve the emissions
standards and the resulting costs of compliance on those entities that
are directly subject to the standards.
The Administrator is not limited to consideration of the factors
specified in CAA section 202(a)(2) when establishing standards for
light-duty vehicles. In addition to feasibility and cost of compliance,
the Administrator may (and historically has) considered such factors as
safety, energy use and security, degree of reduction of both GHG and
non-GHG pollutants,
[[Page 43229]]
technology cost-effectiveness, and costs and other impacts on
consumers. As discussed in prior rulemakings setting GHG
standards,\475\ EPA may establish technology-forcing standards under
section 202(a), but when it does so it must provide sufficient basis
for its belief that the industry can develop the needed technology in
the available time. However, EPA is not required to set technology-
forcing standards under section 202(a). Rather, because section 202(a),
unlike the text of section 202(a)(3) and section 213(a)(3),\476\ does
not specify that standards shall obtain ``the greatest degree of
emission reduction achievable,'' EPA retains considerable discretion
under section 202(a) in deciding how to weigh the various factors,
consistent with the language and purpose of the Clean Air Act, to
determine what standards are appropriate.
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\475\ See, e.g., 77 FR 62624, 62673 (Oct. 15, 2012).
\476\ Section 202(a)(3) provides that regulations applicable to
emissions of certain specified pollutants from heavy-duty vehicles
or engines ``shall contain standards which reflect the greatest
degree of emission reduction achievable through the application of
technology which the Administrator determines will be available . .
. giving appropriate consideration to cost, energy, and safety
factors associated with the application of such technology.'' 42
U.S.C. 7521(a)(3). Section 213(a)(3) contains a similar provision
for new nonroad engines and new nonroad vehicles (other than
locomotives or engines used in locomotives). 42 U.S.C. 7547(a)(3).
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The analysis of alternatives supports the Administrator's
consideration of a range of alternative standards, from the existing
standards to several alternatives that are less stringent.
Specifically, the analysis supports the consideration of this range of
alternative standards due to factors relevant under the EPA's authority
pursuant to section 202(a), such as GHG emissions reductions, the
necessary technology and associated lead-time, the costs of compliance
on automakers, the impact on consumers with respect to cost and vehicle
choice, and effects on safety. These factors, and the Administrator's
proposed conclusion, after consideration of these factors, indicate
that Alternative 1 represents the most appropriate standards for model
years 2021 and beyond are discussed further below.
(a) Consideration of the Development and Application of Technology To
Reduce CO2 Emissions
When EPA establishes emissions standards under section 202, it
considers both what technologies are currently available and what
technologies under development may become available. For today's
proposal, EPA takes note of the analysis of the potential penetration
into the future vehicle fleet of a wide range of technologies that both
reduce CO2 and improve fuel economy (see PRIA Chapter 6).
The majority of these technologies have already been developed, have
been commercialized, and are in-use on vehicles today. These
technologies include, but are not limited to, engine and transmission
technologies, vehicle mass reduction technologies, technologies to
reduce the vehicles' aerodynamic drag, and a range of electrification
technologies. The electrification technologies include 12-Volt stop-
start systems, 48-Volt mild hybrids, strong hybrid systems, plug-in
hybrid electric vehicles, and dedicated electric vehicles.
If the Administrator's consideration of the appropriateness of the
standards were based solely on an assessment of technology availability
and development, the Administrator might consider a wide range of
standards to be appropriate. As shown in Sections VII.B.2 and
VIII.B.1.b), and in PRIA Chapter 6.3.2, the projected penetration of
technologies varies across the Alternatives presented in today's
proposal. In general, the existing EPA standards are projected to
result in the highest penetration of advanced technologies, in
particular mild hybrid and strong hybrid technologies. Lower stringency
Alternatives in general are projected to result in lower penetration of
technologies, in particular for the mild hybrid and strong hybrid
technologies, with the Preferred Alternative projected to result in the
lowest level of electrification technology penetration. For example,
the existing CO2 standards are projected to require a
combined passenger car and truck fleet penetration of mild hybrids plus
strong hybrids of 58% of new vehicle sales in MY 2030, while
Alternative 8 projects a 34% penetration, Alternative 6 projects a 22%
penetration, Alternative 4 projects an 8% penetration, and the Proposed
Alternative (Alternative 1) projects a 4% penetration. These
technologies are available and in production today, and MY 2020 through
MY 2025 standards are still a number of years away. In light of the
wide range of existing technologies that have already been developed,
have been commercialized, and are in-use on vehicles today, including
those developed since the 2012 rule, technology availability,
development and application, if it were considered in isolation, is not
necessarily a limiting factor in the Administrator's selection of which
standards are appropriate within the range of the Alternatives
presented in this proposal. However, as described below, the
Administrator weighs technology availability along with several other
factors, including costs, emissions impacts, safety, and consumer
impacts in determining the appropriate standards under the Clean Air
Act.
(b) Consideration of the Cost of Compliance
EPA is required to consider costs in compliance before setting
standards under section 202(a). Compared to the proposed standards, the
EPA MY 2020-2025 standards announced in 2012 would cost the automotive
industry an estimated total of $260 billion for the vehicles produced
from MY 2016 through MY 2029, as shown in Table VIII-9. The additional
per-vehicle technology costs for these previously-issued standards
would be an estimated $2,260 in MY 2030, relative to the proposed
standards, as shown in Table VIII-31 and Table VIII-32. Especially
considering the change in reference point, these costs are considerably
larger than EPA projected in 2012. Less stringent standards would be
less burdensome. For example, compared to the proposed standards,
Alternative 8 is projected to increase the per-vehicle cost by $1,510
(also in MY 2030), Alternative 6 increases the per-vehicle costs by
$1,120, and Alternative 4 increases the per-vehicle costs by $490.
(c) Consideration of Costs to Consumers
In addition to the costs to the automotive industry described
above, which could be passed on to consumers, the analysis estimates
increased costs for the consumer for changes in maintenance, financing,
insurance, taxes, and other fees, as shown in Table VIII-31 and Table
VIII-32. Considering these additional costs, EPA's previously-issued
standards for MYs 2020-2025 would increase the projected per-vehicle
costs in MY 2030 to an estimated $2,810 relative to the proposed
standards, at a seven percent discount rate. The lower the increased
stringency of the Alternative, the lower the total per-vehicle costs
increase for the consumer. For example, Alternative 8 increases the
total costs for the consumer on a per-vehicle basis by $2,270 (in MY
2030 compared to the costs of the proposed standards), Alternative 6
increases the costs to the consumer by $1,400 per-vehicle, and
Alternative 4 increases the costs by $610 per-vehicle, all at a seven
percent discount rate.
The analysis also projects the fuel savings for the vehicle owner
over the life of the vehicles that come with lower levels of
CO2 emissions. For example, as
[[Page 43230]]
shown in Table VIII-32 (at a seven percent discount rate), for the
previously-announced EPA standards for MYs 2021-2025 (in MY 2030
compared to the costs of the proposed standards), the analysis projects
a per-vehicle life-time fuel savings, including retail taxes, of $1,510
per vehicle, as well as an additional savings to the consumer from
rebound driving and time saved refueling the vehicle of $610 per
vehicle, for a total savings of $2,120. However, these savings to the
consumer are not enough to offset the accompanying projected $2,810
increase in consumer costs. Compared to the proposed standards, the
previously-issued EPA standards for MYs 2021-2025 would increase net
costs to consumers by $690 over the lifetime of the MY 2030 vehicles.
This imbalance between costs and fuel savings contrasts sharply with
what EPA projected in 2012 when setting those standards then, and the
fuel savings is considerably smaller (this is due in large part to
lower current and projected fuel prices). Also, relative to the
proposed standards, and over the lifetime of MY 2030 vehicles, the
projected net cost increase to consumers from adopting Alternative 8 is
$300, Alternative 6 projects a net cost increase to consumers of $100,
Alternative 4 projects a net savings to consumers of $60, and
Alternative 2 projects a net savings to consumers of $10.
(d) Consideration of GHG Emissions
As discussed above, the purpose of CO2 standards
established under CAA Section 202 is to reduce GHG emissions, which
contribute to climate change. As shown in Table VIII-34, the analysis
projects that, compared to the baseline standards, the proposed
CO2 standards for MYs 2021-2026 would increase vehicle
CO2 emissions by 713 million metric tons (MMT) over the
lifetime of the vehicles produced from MY 1979 through MY 2029, with an
additional 159 MMT in CO2 reduction from upstream sources
for a total increase of 872 MMT. The modeling of proposed revised and
alternative standards projects that more stringent standards will
result in smaller increases in GHG emissions (also compared to the
baseline standards. Compared to the baseline standards, Alternative 8
is projected to increase CO2 emissions by 264 MMT from
combined vehicle tailpipe and upstream reductions over the lifetime of
the vehicles produced through MY 2029. Alternative 6 is projected to
increase CO2 emissions by 422 MMT, Alternative 4 by 649 MMT
of CO2, and Alternative 2 by 825 MMT of CO2.\477\
As noted above, the purpose of Title II emissions standards is to
protect the public health and welfare, and in establishing emissions
standards the Administrator is cognizant of the importance of this
goal. At the same time, as discussed above, unlike other provisions in
Title II, Section 202(a) does not require the Administrator to set
standards which result in the greatest degree of emissions control
achievable, though the Administrator has the discretion to do so. Thus,
in setting these standards, the Administrator takes into consideration
other factors discussed above and below, including not only
technological feasibility, lead-time, and the cost of compliance but
also potential impacts of vehicle emission standards on safety and
other impacts on consumers. Notwithstanding the fact that GHG emissions
reductions would be lower under today's proposal than for the existing
EPA standards, in light of the new assessment indicating higher vehicle
costs and associated impacts on consumers, and safety impacts, the
Administrator believes from a cost/benefit perspective that the
foregone GHG emission reduction benefits from the proposed standards
are warranted.
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\477\ This preamble and the PRIA document estimates annual GHG
emissions from light-duty vehicles under the baseline CO2
standards, the proposed standards, and the standards defined by each
of the other regulatory alternatives under consideration. For the
final rule issued in 2012, EPA estimated changes in atmospheric
CO2, global temperature, and sea level rise using GCAM
and MAGICC with outputs from its OMEGA model. Because the agencies
are now using the same model and inputs, outputs from NHTSA's DEIS
(that also used GCAM and MAGICC) were analyzed. Today's analysis
estimates that annual GHG emissions from light-duty vehicles under
the CO2 standards defined by each regulatory alternative
would be within about one percent of emissions under the
corresponding CAFE standards. Especially considering the
uncertainties involved in estimating future climate impacts, the
very similar estimates of future GHG emissions under CO2
standards and corresponding CAFE standards means that climate
impacts presented in NHTSA's draft EIS represent well the potential
climate impacts of the proposed and alternative CO2
standards.
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(e) Consideration of Consumer Choice
As discussed previously, the EPA CO2 standards are based
on vehicle footprint, and in general smaller footprint vehicles have
individual CO2 targets that are lower (more stringent) than
larger footprint vehicles. The passenger car fleet has footprint curves
that are distinct from the light-truck fleet. One of the goals EPA had
in designing the program with footprint-based standards, in considering
the shape, slope, and stringency of the footprint standard curves, and
in adopting many compliance flexibilities (e.g., the emissions
averaging, banking, and trading program; air-conditioning program
credits; flexibility in how to comply with the N2O and
methane standard; off-cycle credit program, etc.) was to maintain
consumer choice. The EPA standards are designed to require reductions
of CO2 emissions over time from the vehicle fleet as a whole
but also to provide sufficient flexibility to the automotive
manufacturers so that firms can produce vehicles which serve the needs
of their customers. EPA believes the past several model years in the
market place show the benefits of this approach. Automotive companies
have been able to reduce their fleet-wide CO2 emissions
while continuing to produce and sell the many diverse products that
serve the needs of consumers in the market, e.g., full-size pick-up
trucks with high towing capabilities, minivans, cross-over vehicles,
SUVs, and passenger cars; vehicles with off-road capabilities; luxury/
premium vehicles, supercars, performance vehicles, entry level
vehicles, etc.
At the same, the Administrator recognizes that automotive customers
are a diverse group, that automotive companies do not all compete for
the same segments of the market, and that increasing stringency in the
standards can be expected to have different effects not just on certain
vehicle segments but on certain manufacturers who have developed market
strategies around those vehicle segments. The Administrator further
recognizes that the diversity of the automotive customer base, combined
with the analysis, raises concerns that the existing standards, if they
are not adjusted, may not continue to fulfill the agency's goal of
providing sufficient manufacturer flexibility to meet consumer needs
and consumer choice preferences. The analysis projects that high
penetrations of hybridized vehicles would be required to achieve the
previously-issued EPA MYs 2021-2025 standards, specifically 37% mild
hybrid penetration and 21% strong hybrids for the new vehicle fleet in
MY 2030 (See Table VIII-24). For the passenger car fleet, the
projection is 20% mild hybrid and 24% strong hybrid, and for the light-
truck fleet 56% mild hybrid and 17% strong hybrid (See Table VIII-26
and Table VIII-28).
The Administrator is concerned that this projected level of
hybridization, and the associated vehicle costs, arising from the
existing standards may be too high from a consumer-choice perspective.
While consumers have benefited from improvements over several decades
in traditional vehicle technologies, such as advancements in
[[Page 43231]]
transmissions and internal combustion engines, advanced electrification
technologies are a departure from what consumers have traditionally
purchased. Strong hybrid and other advanced electrification
technologies have been available for many years (20 years for strong
hybrids and eight years for plug-in and all electric vehicles), and
sales levels have been relatively low, on the order of two to three
precent per year for strong hybrids.\478\ As discussed above, the
analysis projects that the 2012 EPA standards are projected to require
a significant increase in hybridization over the next 7 to 12 model
years. This large increase may require automotive companies to change
the choice of vehicle types and the utility of the vehicles available
to customers from what the companies would otherwise offer in the
absence of the existing standards.
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\478\ Light-Duty Automotive Technology, Carbon Dioxide
Emissions, and Fuel Economy Trends: 1975 Through 2017, U.S. EPA
Table 5.1 (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGDW.pdf.
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EPA notes that in the EPA's annual Manufacturer Performance Report
on the compliance status of the automotive companies for the EPA GHG
standards, EPA has reported that emissions trading has occurred a
number of times in the past several years.\479\ Through MY 2016, these
trades have included 12 firms, with five firms trading CO2
credits to seven firms, and thus far in the EPA GHG program credits
generated in MY 2010 through MY 2016 have been traded. This represents
about one-half of the automotive companies selling vehicles in the U.S.
market, but since several of these firms are small players, it is less
than half of the volume. In total, approximately 30 million Megagrams
of CO2 have been traded between firms, which is
approximately 10% of the MY 2016 industry-wide bank of credits. Credit
trading between firms can lower the costs of compliance for firms, both
for those selling and those purchasing credits, and this program
compliance flexibility is another tool by which auto firms can provide
the types of vehicle offerings that customers want. However, long-term
planning is an important consideration for automakers, and an OEM who
may want to purchase credits as part of a future compliance strategy
cannot be guaranteed they will be able to find credits.
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\479\ See Greenhouse Gas Emission Standards for Light-Duty
Vehicles: Manufacturer Performance Report for the 2016 Model Year
(EPA Report 420-R18-002), U.S. EPA (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGIA.pdf.
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The automotive industry is highly competitive, and firms may be
reluctant to base their future product strategy on an uncertain future
credit availability. As can be seen in Table VIII-24, the analysis
projects that lower levels of stringency (Alternatives 1-8) will
require lower penetrations of mild hybrids and strong hybrids as
compared to the 2012 EPA standards. For example, Alternative 8 projects
a 34% penetration of mild and strong hybrid new vehicle sales in MY
2030, Alternative 6 projects a 22% penetration of these technologies,
Alternative 4 projects an eight percent penetration, and Alternative 2
projects a four percent penetration of mild and strong hybrids in MY
2030. The EPA proposal, Alternative 1, projects a two percent
penetration of mild hybrids and a two percent penetration of strong
hybrids. These are levels similar to what auto manufacturers are
selling today, suggesting that auto companies will be able to produce
vehicles in the future that meet the full range of needs from
consumers, thus preserving consumer choice.
(f) Consideration of Safety
EPA has long considered the effects on safety of its emission
standards. See 45 FR 14496, 14503 (1980) (``EPA would not require a
particulate control technology that was known to involve serious safety
problems.''). More recently, EPA has considered the potential impacts
of emissions standards on safety in past rulemakings on GHG standards,
including the 2010 rule which established the 2012-2016 light-duty
vehicle GHG standards, and the 2012 rule which previously established
the 2017-2025 light-duty vehicle GHG standards. Indeed, section
202(a)(4)(A) specifically prohibits the use of an emission control
device, system or element of design that will cause or contribute to an
unreasonable risk to public health, welfare, or safety. 42 U.S.C.
7521(a)(4)(A).
The proposal's safety analysis projects that the 2012 EPA GHG
standards for MYs 2021 and later would increase vehicle fatalities due
to several reasons, namely increased vehicle prices resulting in
delayed turnover of the vehicle fleet to newer, safer vehicles,
increased fatalities and accidents due the rebound effect, and
passenger car mass reduction. The assessment is discussed in Section 0
of this preamble and is detailed in Chapter 11 of the PRIA. The
assessment projects that Alternative 1, which includes no change in the
GHG emissions standards for MY 2021 and later, would yield the lowest
number of vehicle fatalities. The analysis projects that, compared to
the proposed standards, the previously-issued EPA standards would
increase highway fatalities by 15,680 over the lifetime of vehicles
produced through MY 2029 (See Table VII-89).
EPA views the potential impacts of emission standards on safety as
an important consideration in determining the appropriate standards
under section 202. The analysis projects adverse impacts on safety that
are significantly different from the analysis included and considered
in the 2012 rule which established the MY 2021-25 GHG standards and the
2016 Draft Technical Assessment Report. As discussed previously in this
document, previous analyses limited the amount of mass reduction
assumed for certain vehicles, while acknowledging that manufacturers
would not necessarily choose to avoid mass reductions in the ways that
the agencies assumed. The current analysis eliminates this constraint.
The Administrator considers this difference to be a significant factor
indicating that it is appropriate to consider a range of alternative
revised standards, including Alternative 1, the preferred alternative.
(g) Balancing of Factors and EPA's Proposed Revised Standards for MY
2021 and Later
As discussed in this section, the Administrator is required to
consider a number of factors when establishing emission standards under
Section 202(a)(2) of the Clean Air Act: The standards ``shall take
effect after such period as the Administrator finds necessary to permit
the development and application of the requisite technology, giving
appropriate consideration to the cost of compliance within such
period.'' 42 U.S.C. 7521(a)(2). For this proposal, the Administrator
has considered a wide range of potential emission standards
(Alternatives 1 through 9), ranging from the existing EPA MY 2021 to MY
2025 standards, through a number of less stringent alternatives,
including Alternative 1, the preferred Alternative. In addition to
technological feasibility, lead-time, and the costs of compliance, the
Administrator has also considered the impact of various standards on
projected emissions reductions, consumer choice, and vehicle safety.
The Administrator believes the existing EPA standards for MY 2021 and
later, considered as a whole, are too stringent. The Administrator
gives particular consideration to the high projected costs of the
standards and the impact of the standards on vehicle safety. The
analysis projects that, compared to the proposed standards, the
previously-
[[Page 43232]]
issued EPA standards for MYs 2021-2025 would increase MY 2030
compliance costs by nearly $1,900 per vehicle. Although EPA projected a
similar cost \480\ increase in the 2012 rule announcing standards
through 2025, this prior estimate was relative to an indefinite
continuation of standards for MY 2016, and assuming that absent
regulation, manufacturers would not increase fuel economy at all. In
addition, as mentioned above, the analysis projects that, compared to
the proposed standards, the previously-issued EPA standards would
increase highway fatalities by 12,903 over the lifetime of vehicles
produced through MY 2029. In evaluating the other Alternatives under
consideration, the Administrator notes that Alternative 1 has the
lowest cost of compliance and the lowest number of fatalities. He also
notes that Alternative 1 will preserve consumer choice in the vehicle
market and will provide a relatively high net savings to consumers,
when assessing the increased costs of vehicles against fuel savings
over the lifetime of the vehicle.
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\480\ 77 FR 62624, 62665 (Oct. 15, 2012).
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The Administrator recognizes that Alternative 1 is projected to
result in less CO2 reductions compared to the existing EPA
standards and is not projected to achieve additional GHG reductions
beyond the MY 2020 standards. However, the Administrator notes that,
unlike other provisions in Title II referenced above, section 202(a)
does not require the Administrator to set standards which result in the
``greatest degree of emissions control achievable.'' In light of this
statutory discretion and the range of factors that the statute
authorizes and permits the Administrator to consider, and his
consideration of the factors discussed above, the EPA proposes to
conclude that maintaining the MY 2020 standards going forward is an
appropriate approach under section 202(a). Therefore, based on the data
and analysis detailed in this proposal, the Administrator is proposing
that the existing MY 2021 and later GHG standards are too stringent and
is proposing to revise the MY 2021 and later standards to maintain the
MY 2020 levels in subsequent model years. EPA requests comment on all
aspects of this proposal and supporting assessments, including the
Administrator's consideration of the relevant factors under section
202(a) of the Clean Air Act, the proposed Alternative 1, the
previously-established EPA GHG standards, and all of the Alternatives
discussed in section IV of this preamble.
VI. Preemption of State and Local Laws
Accomplishing the goals of EPCA requires a set of uniform national
fuel economy standards. Achieving this national standard requires the
agencies to clearly discuss the extent to which state and local
standards are expressly or impliedly preempted. As described herein,
doing so is fundamental to the effectiveness of the new proposed set of
fuel economy standards and to the critical importance of ensuring that
the proposed Federal standards will constitute uniform national
requirements, as Congress intended. This is also a fundamental reason
that EPA is proposing the withdrawal of CAA preemption waivers granted
to California relating to its GHG standards and Zero Emissions Vehicle
(ZEV) mandate.
A. Preemption Under the Energy Policy and Conservation Act
1. History of EPCA Preemption Discussions in Rulemakings
NHTSA has asserted the preemption of certain State emissions
standards under EPCA a number of times in CAFE rulemakings dating back
to 2002.\481\ The initial rulemaking discussion was prompted by a court
filing by the State of California claiming that NHTSA did not treat
California's Greenhouse Gas Emissions regulation as preempted.\482\
This continuous dialogue involves a variety of parties (i.e., the
states, the Federal government--especially EPA--and the general public)
and occurs through a variety of means, including several rulemaking
proceedings. After NHTSA first raised the issue of preemption in 2002
when proposing standards for MYs 2005-2007 light trucks, the agency
explored preemption at great length in response to extensive public
comment in its August 2005 NPRM and its April 2006 final rule for MYs
2008-2011 light trucks.
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\481\ 67 FR 77025 (December 16, 2002).
\482\ See Appellants Opening Brief filed on behalf Michael P.
Kenny in Central Valley Chrysler-Plymouth, Inc. et al. v. Michael P.
Kenny, No. 02-16395, at p. 33 (9th Cir. 2002).
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During the period between the NPRM and the final rule for MYs 2008-
2011 light trucks, California separately requested that the EPA grant a
waiver of CAA preemption, pursuant to Section 209 of that act, for its
Greenhouse Gas Emissions regulation. If EPA granted the waiver, the CAA
would under certain circumstances allow other states to adopt the same
regulation pursuant to CAA Section 177, without being preempted by the
CAA.
In 2007, the Supreme Court ruled in Massachusetts v. EPA that
carbon dioxide is an ``air pollutant'' within the meaning of the CAA
and thus potentially subject to regulation under that statute. The
Supreme Court did not consider the issue of preemption under EPCA of
state laws or regulations regulating CO2 tailpipe emissions
from automobiles, but it did address the relationship between EPA and
NHTSA rulemaking obligations.\483\ Later that year, two Federal
district courts in Vermont and California ruled that the GHG motor
vehicle emission standards adopted by those states were not preempted
under EPCA.\484\ Still later that year, Congress enacted EISA, amending
EPCA by mandating annual increases in passenger car and light truck
CAFE standards through MY 2020 and maximum feasible fuel economy
standards subsequently.\485\
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\483\ The Court reasoned that the fact that NHTSA ``sets mileage
standards in no way licenses EPA to shirk its environmental
responsibilities. EPA has been charged with protecting the public's
`health' and `welfare,' . . . a statutory obligation wholly
independent of DOT's mandate to promote energy efficiency. . . . The
two obligations may overlap, but there is no reason to think the two
agencies cannot both administer their obligations and yet avoid
inconsistency.'' Massachusetts v. EPA, 549 U.S. 497, 532 (2007).
\484\ Green Mountain Chrysler v. Crombie, 508 F.Supp.2d 295 (D.
Vt. 2007); Central Valley Chrysler-Jeep, Inc. v. Goldstene, 529
F.Supp.2d 1151 (E.D. Cal. 2007), as corrected (Mar. 26, 2008).
\485\ Public Law 110-140 (2007).
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In March 2008, EPA denied California's request for a waiver of CAA
preemption.\486\ In May 2008, NHTSA issued a proposal for MYs 2011-2015
standards, which included a significant discussion of EPCA preemption
and a proposed regulatory statement to provide that state vehicle
tailpipe CO2 standards are related to fuel economy and
therefore expressly preempted under EPCA, and that they conflict with
the goals and objectives of EPCA and therefore also impliedly
preempted.\487\ The Bush Administration did not issue a final rule for
MYs 2011-2015.
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\486\ 73 FR 12156 (Mar. 6, 2008).
\487\ 73 FR 24352 (May 2, 2008).
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A number of significant actions happened in quick succession at the
beginning of the prior Administration. The first day post-inauguration,
CARB petitioned for reconsideration of EPA's denial of a waiver of CAA
preemption for California's GHG emissions standards for 2009 and later
model year vehicles.\488\ Several days later, on January 26, 2009,
President Obama issued a memorandum requesting, among other things
(including
[[Page 43233]]
consideration of EPCA preemption in light of Massachusetts v. EPA and
other laws), that NHTSA's rulemaking be divided into two parts--one
regulation establishing standards for model year 2011 only, and another
for subsequent years. Less than two months after that memorandum, on
March 6, 2009, NHTSA issued its final rule for MY 2011 vehicles and
announced that it would consider EPCA preemption in subsequent
rulemakings.\489\ Then, on May 19, 2009, the White House announced a
coordinated program addressing motor vehicle fuel economy and
greenhouse gas emissions, to be known as the ``National Program,''
whereby NHTSA and EPA would jointly establish rules to harmonize
compliance requirements for manufacturers. As part of the National
Program, several manufacturers and their trade associations announced
their commitment to take several actions, including agreeing not to
contest forthcoming CAFE and GHG standards for MYs 2012-2016; not to
challenge any grant of a CAA preemption waiver for California's GHG
standards for certain model years; and to stay and then dismiss all
pending litigation challenging California's regulation of GHG
emissions, including litigation concerning EPCA preemption of state GHG
standards.\490\
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\488\ For background on CARB's petition, see EPA's Notice of
Decision Granting a Waiver of Clean Air Act Preemption for
California's 2009 and Subsequent Model Year Greenhouse Gas Emission
Standards for New Motor Vehicles, 74 FR 32744 (Jul. 8, 2009).
\489\ 74 FR 14196 (Mar. 6, 2009).
\490\ 75 FR 25324, 25328 (May 7, 2010).
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Less than two months later, in July 2009, EPA granted California's
January 2009 request for reconsideration of the CAA preemption waiver
denial, allowing California to establish its own GHG standards under
the CAA.\491\ In granting the preemption waiver, EPA acknowledged that
its analysis was based solely on CAA considerations and did not
``attempt to interpret or apply EPCA,'' concluding that ``EPA takes no
position regarding whether or not California's GHG standards are
preempted under EPCA.'' \492\
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\491\ 74 FR 32744 (Jul. 8, 2009).
\492\ 74 FR at 32783 (Jul. 8, 2009).
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In the subsequent MYs 2012-2016 CAFE rulemaking, NHTSA elected to
defer consideration of EPCA preemption concerns because of the
``consistent and coordinated Federal standards that apply nationally
under the National Program.'' \493\ Later, in establishing MYs 2017-
2021 CAFE standards, NHTSA pointed out that after finalization of the
MYs 2012-2016 CAFE standards, California amended its GHG regulations to
provide that manufacturers could elect to comply with the EPA GHG
requirements and be deemed to comply with California's standards, and
that this amendment facilitated the National Program by allowing a
manufacturer to ``meet all standards with a single national fleet.''
\494\ NHTSA, at the time, erroneously saw this as obviating
consideration of EPCA preemption. At the same time, the agency did not
address whether California's ZEV program would be preempted since it
has never been part of the National Program.
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\493\ 75 FR 25324, 25546 (May 7, 2010); see also 74 FR 49454,
49635 (Sep. 28, 2009).
\494\ 76 FR 74854, 74863 (Dec. 1, 2011).
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2. Preemption Analysis
Present circumstances require NHTSA to address the issue of
preemption. Despite past attempts by NHTSA and EPA to harmonize their
respective and related regulations, the automotive industry and U.S.
consumers now face regulatory uncertainty and increased costs, in no
small part as a result of California's separate GHG emissions and ZEV
program. NHTSA and EPA now seek to address these concerns with this
rulemaking proposal, in the interest of regulatory certainty and the
clear prospect for disharmony with conflicting state requirements.\495\
NHTSA is also guided by a desire to obtain comments from state and
local officials and other members of the public to inform fully the
agency's position on this important issue.\496\
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\495\ While California's ``deem to comply'' provision provided
some temporary relief from three different sets of standards, its
regulations still mandate that some manufacturers comply with
burdensome filing requirements and California may act to revoke the
provision. In fact, California is already seeking comment on
potentially changing the regulation to provide that manufacturers
would only be deemed to comply with CARB requirements if meeting the
currently-final EPA standards. See https://www.arb.ca.gov/msprog/levprog/leviii/leviii_dtc_notice05072018.pdf (last accessed May 17,
2018). Moreover, the ``deem to comply'' provision applies only to
tailpipe CO2 emissions requirements--not to the ZEV
program.
\496\ See also E.O. 13132 (Federalism); E.O. 12988 sec.
3(b)(1)(B) (Civil Justice Reform); 54 FR 11765 (Mar. 22, 1989); 58
FR 68274 (Dec. 23, 1993); and 70 FR 21844 (Apr. 27, 2005).
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(a) EPCA Preemption
EPCA's express preemption language is broad and clear:
When an average fuel economy standard prescribed under this
chapter is in effect, a State or a political subdivision of a State
may not adopt or enforce a law or regulation related to fuel economy
standards or average fuel economy standards for automobiles covered
by an average fuel economy standard under this chapter.\497\
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\497\ 49 U.S.C. 32919.
Unlike the CAA, EPCA does not allow for a waiver of preemption. Nor
does EPCA allow for states to establish or enforce an identical or
equivalent regulation. In a further indication of Congress' intent to
ensure that state regulatory schemes do not impinge upon EPCA's goals,
the statute preempts state laws merely related to fuel economy
standards or average fuel economy standards. Here, NHTSA intends to
assert preemption only over state requirements that directly affect
corporate average fuel economy.
The Supreme Court has interpreted similar statutory preemption
language on several occasions, concluding that a state law ``relates
to'' a Federal law if it ``has a connection with or refers to'' the
subject of the Federal law.\498\ The Court, citing similar Federal
statutory language, extended the application of the ``related to''
standard to the Airline Deregulation Act in Morales v. Trans World
Airlines, Inc.,\499\ concluding that,'' [f]or purposes of the present
case, the key phrase, obviously, is `relating to.' The ordinary meaning
of these words is a broad one--`to stand in some relation; to have
bearing or concern; to pertain; refer; to bring into association with
or connection with,' . . .--and the words thus express a broad pre-
emptive purpose.'' \500\ Courts look ``both to the objectives of the .
. . statute as a guide to the scope of the state law that Congress
understood would survive, [and] to the nature of the effect of the
state law on [the Federal standards].'' \501\
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\498\ Shaw v. Delta Airlines, Inc., 463 U.S. 85, 97 (1983)
(ERISA case).
\499\ 504 U.S. 374, 383-84 (1992).
\500\ Id. at 383.
\501\ California Div. of Labor Standards Enforcement v.
Dillingham Constr., N.A., Inc., 519 U.S. 316, 325 (1997), (quoting
N.Y Conference of Blue Cross & Blue Shield Plans v. Travelers Ins.
Co., 514 U.S. 645, 656 (1995)).
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One of Congress' objectives in EPCA was to create a national fuel
economy standard, as clearly expressed in 49 U.S.C. 32919(a). In
addition to the statute's plain language, which controls, the
legislative history of that provision further confirms that Congress
intended the provision to be broadly preemptive. As Congress debated
proposals that would eventually become EPCA, the Senate bill \502\
sought to preempt State laws only if they were ``inconsistent'' with
Federal fuel economy standards, labeling, or advertising, while the
House bill \503\ sought to preempt State laws only if they were not
``identical to'' a Federal requirement. The express preemption
provision, as enacted, preempts all State laws that relate to fuel
economy standards. No exception is made for State laws on the ground
that
[[Page 43234]]
they are consistent with or identical to Federal requirements.\504\
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\502\ S. 1883, 94th Cong., 1st Sess., Section 509.
\503\ H.R. 7014, 94th Cong., 1st Sess., Section 507 as
introduced, Section 509 as reported.
\504\ See 71 FR 17566, 17657 (April 6, 2006).
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In enacting EISA, Congress did not repeal or amend EPCA's express
preemption provision. Congress did, however, adopt a savings provision
regarding the effect of EISA, and the amendments made by it:
Nothing in this Act or an amendment made by this Act supersedes,
limits the authority provided or responsibility conferred by, or
authorizes any violation of any provision of law (including a
regulation), including any energy or environmental law or
regulation.
We understand this statutory language to prevent EISA from limiting
pre-existing authority or responsibility conferred by any law or from
authorizing violation of any law. By the same token, the savings
provision does not purport to expand pre-existing authority or
responsibility. Thus, to the extent that EPCA's express preemption
provision limited State authority and responsibility prior to the
enactment of EISA, it continues to limit such authority and
responsibility to the same extent after the enactment of EISA. We
recognize that the Congressional Record contains statements regarding
the savings provision indicating that certain members of Congress may
have considered this language as allowing California to set tailpipe
GHG emissions standards in contravention of EPCA's express preemption
provision. Note, however, that statements made on the floor of the
Senate or House before the votes on EISA cannot expand the scope of the
savings provision or even be used to ``clarify'' it, given the
unambiguous plain meaning of both the savings provision and EPCA's
express preemption provision. If Congress had wanted to narrow the
express preemption provision, it could have chosen to include such an
amendment in EISA. It did not.
(b) Tailpipe CO2 Emissions Regulations or Prohibitions are
Related to Fuel Economy Standards
This broad statutory preemption provision also necessarily governs
state regulations over greenhouse gas emissions. GHG emissions, and
particularly CO2 emissions, are mathematically linked to
fuel economy; therefore, regulations limiting tailpipe CO2
emissions are directly related to fuel economy.\505\ To summarize, most
light vehicles are powered by gasoline internal combustion engines. The
combustion of gasoline produces CO2 in amounts that can be
readily calculated. CO2 emissions are always and directly
linked to fuel consumption because CO2 is a necessary and
inevitable byproduct of burning gasoline. The more fuel a vehicle burns
or consumes, the more CO2 it emits. To the extent that light
vehicles are not powered by internal combustion engines, their use
generally involves some release of CO2 or other GHG
emissions, even if indirectly, associated with the vehicle performing
its work of traveling down the road. CNG and LPG vehicles release
CO2 during combustion. Even for battery-electric vehicles,
fossil fuels are used in at least some part of production of
electricity in virtually all parts of the country, and that electricity
is used to move the vehicles. And with hydrogen vehicles, methane
remains a major part of the generation of hydrogen fuel, which is also
used to move those vehicles. Carbon dioxide is thus a byproduct of
moving virtually if not literally all light-duty vehicles, and the
amount of CO2 released directly correlates to the amount of
fossil fuels used to power the vehicle so it can move.
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\505\ 71 FR at 17659, et seq.
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EPCA has specified since its inception that compliance with CAFE
standards is to be determined in accordance with test and calculation
procedures established by EPA.\506\ More specifically, the tests are to
be performed using ``the same procedures for passenger automobiles the
Administrator used for model year 1975 . . . procedures that give
comparable results.'' Under these procedures, compliance with the CAFE
standards is and has always been based on the rates of emission of
CO2, CO, and hydrocarbons from covered vehicles, but
primarily on the emission rates of CO2. In the measurement
and calculation of a given vehicle model's fuel economy for purposes of
determining a manufacturer's compliance with Federal fuel economy
standards, the role of CO2 is approximately 100 times
greater than the combined role of the other two relevant carbon exhaust
gases. Given that the amount of CO2, CO, and hydrocarbons
emitted from a vehicle's tailpipe relates directly to the amount of
fuel it consumes, EPA can reliably and accurately convert the amount of
those gases emitted by that vehicle into the miles per gallon achieved
by that vehicle. In recognizing that 1975 test procedures were
sufficient to measure fuel economy performance, Congress recognized the
direct relationship between CO2 emissions and fuel economy
standards, while in the same piece of legislation expressly preempting
state standards that are related to fuel economy standards, when
Federal fuel economy standards are in place.
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\506\ 49 U.S.C. 32904(c).
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In mandating Federal fuel economy standards under EPCA, Congress
has expressly preempted any state laws or regulations relating to fuel
economy standards. A state requirement limiting tailpipe CO2
emissions is such a law or regulation because it has the direct effect
of regulating fuel consumption.
Given that substantially reducing CO2 tailpipe emissions
from automobiles is unavoidably and overwhelmingly dependent upon
substantially increasing fuel economy through installation of engine
technologies, transmission technologies, accessory technologies,
vehicle technologies, and hybrid technologies, increases in fuel
economy inevitably produce commensurate reductions in CO2
tailpipe emissions. Since there is but one pool of technologies \507\
for reducing tailpipe CO2 emissions and increasing fuel
economy available now and for the foreseeable future, regulation of
CO2 emissions and fuel consumption are inextricably linked.
Such state regulations are therefore unquestionably ``related'' and
expressly preempted under 49 U.S.C. 32919.
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\507\ With the minor exception of regulating the carbon
intensity of fuels--an activity not preempted by EPCA.
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Moreover, state standards that have the effect of regulating
tailpipe CO2 emissions or fuel economy are likewise related
to fuel economy standards and likewise preempted. For instance, if a
state were to regulate all tailpipe GHG emissions from a vehicle, and
not just CO2, the state would nonetheless regulate tailpipe
CO2 emissions, since CO2 emissions comprise the
overwhelming majority of tailpipe carbon emissions. EPCA preempts such
a standard.
Likewise, a state law prohibiting all tailpipe emissions, carbon or
otherwise, from some or all vehicles sold in the state, would relate to
fuel economy standards and be preempted by EPCA, since the majority of
tailpipe emissions consist of CO2. We recognize that this
preempts state programs, such as California's ZEV mandate, that
establish requirements that a portion of a vehicle's fleet sold or
purchased consist of vehicles that produce no tailpipe emissions.
(c) Other GHG Emissions Requirements May Not Be Preempted by EPCA
While EPCA expressly preempts state tailpipe CO2
emission limits, some GHG emissions from vehicles have no
[[Page 43235]]
relation to fuel economy and are therefore outside the scope of EPCA
preemption. For instance, vehicle air conditioning units can cause GHG
emissions by leaking refrigerants when the system is recharged or when
it is crushed at the end of the vehicle's life. Since such emissions
have no bearing on a vehicle's fuel economy performance or tailpipe
CO2 emissions, states can pass laws specifically regulating
or even prohibiting such vehicular refrigerant leakage without relating
to fuel economy if doing so would be otherwise consistent with Federal
law. Therefore, EPCA would not preempt such laws, if narrowly drafted
so as not to include tailpipe CO2 emissions. If, however, a
state law sought to limit the combined GHG emissions from a motor
vehicle, in a manner that would include tailpipe CO2
emissions, EPCA would preempt that portion of the law limiting tailpipe
CO2 emissions.
Similarly, state safety requirements may have a merely incidental
impact on fuel economy and not relate to fuel economy. For instance, a
state may mandate that children traveling in motor vehicles sit in
child safety seats. Child safety seats add weight, and added weight has
an impact on fuel economy. This impact is merely incidental, however,
and does not directly relate to fuel economy standards.
Likewise, EPA has recognized that California may apply for a waiver
of CAA preemption for vehicle emissions, which must be granted in
certain circumstances. That said, EPCA does preempt any regulation
limiting or prohibiting CO2 emissions or all tailpipe
emissions, as such regulations have the effect of regulating
CO2 emissions and relate to fuel economy standards.\508\
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\508\ NHTSA notes that over the last decade CARB has complicated
its regulation of smog-forming emissions (the original purpose of
the Section 209 CAA waiver) by combining it with regulation of GHG
and, principally, CO2 emissions as well as the ZEV
mandate. Since EPCA prohibits state regulation of CO2
emissions, a state program that combines regulation of the two
groups of pollutants is preempted to the extent that the program
relates to fuel economy. A regulatory regime in which smog-forming
pollutants are addressed without also directly or indirectly
regulating fuel economy is not preempted under EPCA.
Additionally, NHTSA notes that some suggest that insofar as
carbon dioxide emissions cause global climate change, they
indirectly worsen air quality by (1) increasing formation of smog,
because the chemical process that forms ground-level ozone occurs
faster at higher temperatures, and (2) increasing ragweed pollen,
which can cause asthma attacks in allergy sufferers. Comment is
sought on the extent to which the zero-tailpipe-emissions vehicles
compelled to be sold by California's ZEV program reduce temperatures
in the parts of California which are in non-attainment for ozone and
which contain dense populations of allergy sufferers.
---------------------------------------------------------------------------
NHTSA invites comments on the extent to which a state standard can
have some incidental impact on fuel economy or CO2 emissions
without being ``related to'' fuel economy standards.
(d) A Waiver of CAA Preemption Does Not Affect, in Any Way, EPCA
Preemption
When a state establishes a standard related to fuel economy, it
does so in violation of EPCA's preemption statute and the standard is
therefore void ab initio.
Federal preemption is rooted in the Supremacy Clause of the U.S.
Constitution.\509\ Courts have long recognized that the Supremacy
Clause of the Constitution gives Congress the power to specifically
preempt State law.\510\ Broadly speaking, the United States Supreme
Court has long held that ``an act done in violation of a statutory
prohibition is void,'' \511\ and has specifically noted that such acts
are not merely ``voidable at the instance of the government'' but void
from the outset.\512\ The Ninth Circuit stated it more plainly: ``Under
Federal law, an act occurring in violation of a statutory mandate is
void ab initio.'' \513\ Discussing the Supremacy Clause, the Supreme
Court explicitly explained that, ``[i]t is basic to this constitutional
command that all conflicting state provisions be without effect.''
\514\ And at least one Federal Court of Appeals explicitly stated that
the Supremacy Clause means ``state laws that `interfere with, or are
contrary to the laws of Congress' are void ab initio.'' \515\
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\509\ U.S. Const. art VI, cl. 2.
\510\ See Gibbons v. Ogden, 22 U.S. 1 (1824).
\511\ Ewert v. Bluejacket, 259 U.S. 129, 138 (1922), quoting
Waskey v. Hammer, 223 U.S. 85, 94 (1912).
\512\ Waskey, 223 U.S. at 92.
\513\ Cabazon Band of Mission Indians v. City of Indio, Cal.,
694 F.2d 634, 637 (9th Cir. 1982).
\514\ Maryland v. Louisiana, 451 U.S. 725, 746 (1981) (citing
McCulloch v. Maryland, 4 Wheat. 316, 427 (1819)). Other courts have
used similar language to describe the impact of preemption. See,
e.g., Nathan Kimmel, Inc. v. DowElanco, 275 F.3d 1199, 1203 (9th
Cir. 2002) (explaining preempted state laws are ``without effect'');
Sweat v. Hull, 200 F.Supp.2d 1162, 1172 (D. Ariz. 2001) (explaining
preempted state laws are ``ineffective.'').
\515\ Antilles Cement Corp. v. Fortuno, 670 F.3d 310, 323 (1st
Cir. 2012) (quoting Gibbons v. Ogden, 22 U.S. (9 Wheat.) 1 (1824)).
---------------------------------------------------------------------------
While both the CAA and EPCA may preempt state laws limiting GHG
emissions from motor vehicles, avoiding preemption (by waiver or
otherwise) under one Federal law has no bearing on the other Federal
law's preemptive effect. Section 209 of the CAA, which provides for the
possible waiver of CAA preemption, makes clear that waiver of
preemption under that statute operates only to relieve ``application of
this section''--the preemption provision of the CAA--and not
application of other statutes.\516\ EPA and NHTSA tentatively agree
that a waiver under the CAA does not also waive EPCA preemption.
---------------------------------------------------------------------------
\516\ 42 U.S.C. 7543(b)(1) (emphasis added); see also 42 U.S.C.
7543(b)(3) (``compliance with such State standards shall be treated
as compliance with applicable Federal standards for purposes of this
subchapter'') (emphasis added).
---------------------------------------------------------------------------
The Vermont and California Federal district court decisions
mentioned above involved challenges to a California Air Resources Board
regulation establishing vehicle tailpipe GHG emission standards. The
courts concluded that EPCA did not preempt such standards. In both
decisions, the courts placed much weight upon the fact that California
had petitioned EPA for a waiver of CAA preemption pursuant to 42 U.S.C.
7543(b).
NHTSA and EPA do not agree with the district courts' express
preemption analyses. EPCA preempts state laws and regulations ``related
to fuel economy standards or average fuel economy standards for
automobiles covered by an average fuel economy standard.'' \517\ The
courts in Green Mountain Chrysler and Central Valley Chrysler-Jeep
recognized the relationship between CO2 emissions and fuel
economy. Nonetheless, they erroneously concluded that the ``related
to'' language in EPCA's preemption clause should be construed ``very
narrowly'' and adopted a novel interpretation of ``related to.'' \518\
The courts failed to recognize precedent providing broad effect to
other preemption statutes using terms similar to ``related to,'' as
discussed above.
---------------------------------------------------------------------------
\517\ 49 U.S.C. 32919(a) (emphasis added).
\518\ E.g., 529 F.Supp.2d at 1176.
---------------------------------------------------------------------------
(e) A Clean Air Act Waiver Does Not ``Federalize'' EPCA-Preempted State
Standards
The district court in Green Mountain Chrysler concluded that it
could resolve the challenge to Vermont's regulations without directly
considering the application of EPCA's preemption provision. The court
said that the dispute did not concern preemption but concerned
reconciling two different Federal statutes (EPCA and the CAA). In this
regard, the district court stated that if EPA approved California's
waiver petition (which had not yet occurred), then Vermont's GHG
regulations become ``other motor vehicle standards'' that NHTSA must
consider in setting
[[Page 43236]]
CAFE standards.\519\ In the court's view, once EPA grants a waiver,
compliance with California's standards is deemed to satisfy all Federal
standards--not just those of the CAA. In states that adopt California's
standards, compliance with that standard would be deemed to satisfy all
Federal standards as well. With this Federal accommodation of state
standards, the court concluded, Vermont's regulations would stand.
---------------------------------------------------------------------------
\519\ Green Mountain Chrysler, 508 F.Supp.2d at 398.
---------------------------------------------------------------------------
The court's premise that preemption provisions and principles do
not apply is not based on precedent and is not supported by applicable
law. In fact, the district court in Central Valley Chrysler-Jeep
recognized that ``[t]he Green Mountain court never actually offers a
legal foundation for the conclusion that a state regulation granted
waiver under [CAA] section 209 [42 U.S.C. 7543] is essentially a
federal regulation such that any conflict between the state regulation
and EPCA is a conflict between federal regulations.'' \520\ NHTSA and
EPA disagree with the conclusion of these decisions and reaffirm the
longstanding position that state standards regulating tailpipe GHG
emissions, such as the standards challenged in the California and
Vermont district court cases, are preempted by EPCA because they
``relate to'' fuel economy standards. We also note that those courts
failed to consider, much less give any weight to, NHTSA's views of
preemption, as the expert agency with authority over the Federal fuel
economy program.\521\ The United States opposed, as amicus curiae, the
Green Mountain Chrysler decision on appeal to the Second Circuit, but
the Second Circuit did not issue a decision on appeal \522\ due to the
automotive industry's withdrawal of appeals. As explained above, the
withdrawal of those appeals was a pre-condition to the 2010 issuance of
the final rule establishing the ``National Program'' of fuel economy
standards and GHG emission standards for MYs 2012-2016.
---------------------------------------------------------------------------
\520\ Central Valley Chrysler-Jeep, 529 F.Supp.2d at 1165.
Congress must state its intention clearly to accord a state law the
status of Federal law, which it did not do in either in Section
209(b) of the CAA or in EPCA. See, e.g., Indep. Cmty. Bankers Ass'n
v. Bd. of Governors, 820 F.2d 428, 436-37 (D.C. Cir. 1987)
(recognizing that, although Congress ``has the power to assimilate
state law,'' ``[s]uch decisions require an unequivocal congressional
expression'' because ``some [state] restrictions would in all
likelihood conflict with [other] existing Federal laws'').
\521\ See Geier v. American Honda Motor Co., 529 U.S. 861, 883
(2000) (``Congress has delegated to DOT authority to implement the
statute; the subject matter is technical; and the relevant history
and background are complex and extensive. The agency is likely to
have a thorough understanding of its own regulation and its
objectives and is `uniquely qualified' to comprehend the likely
impact of state requirements.''); Medtronic, Inc. v. Lohr, 518 U.S.
470, 496 (1996) (``agency is uniquely qualified to determine whether
a particular form of state law stands as an obstacle to the
accomplishment and execution of the full purposes and objectives of
Congress'') (internal quotation marks omitted).
\522\ See Proof Brief for the United States as Amicus Curiae,
07-4342-cv (2d Cir. filed Apr. 16, 2008).
---------------------------------------------------------------------------
In their appeals of the Green Mountain Chrysler decision, the
vehicle manufacturer associations argued that the operation of EPCA's
express preemption provision does not require that a conflict be shown
between the Federal and state standards, that the Federal and state
standards be identical, or that the Federal and state standards serve
the same purpose. We agree. The conflict principles of implied
preemption do not apply in fields where Congress has enacted an express
preemption provision prohibiting even the existence of state standards.
The statutory test, whether the state standards are ``related to'' the
Federal standards, is met by showing that the state GHG emission
standards are not simply related to, but actually the functional
equivalent of, the Federal fuel economy standards. The district court
itself recognized that ``there is a near-perfect correlation between
fuel consumed and carbon dioxide released.'' Neither the inclusion in
the state standard of emissions for which that relationship does not
exist, nor the assigning to the state standard of a purpose other than
energy conservation, diminishes the statutory implications of the state
standard's meeting the relatedness test. Those unrelated types of
emissions constitute a very low percentage of the overall tailpipe
emissions. Finally, while there are means of compliance with the state
standard other than improving fuel economy, their contributions to
compliance are minor. Improving fuel economy is the only feasible
method of achieving full compliance. Again, NHTSA and EPA agree.
The Central Valley Chrysler-Jeep court went further, noting that
while NHTSA is required to give consideration to ``other standards,''
including those ``promulgated by EPA,'' ``[t]here is no corresponding
duty by EPA to give consideration to EPCA's regulatory scheme. This
asymmetrical allocation by Congress of the duty to consider other
governmental regulations indicates that Congress intended that DOT,
through NHTSA, is to have the burden to conform its CAFE program under
EPCA to EPA's determination of what level of regulation is necessary to
secure public health and welfare.'' \523\
---------------------------------------------------------------------------
\523\ Central Valley Chrysler-Jeep, 529 F.Supp.2d at 1168.
---------------------------------------------------------------------------
In support of its position, the Central Valley Chrysler-Jeep found
persuasive the Green Mountain Chrysler court's view that California
emissions regulations under CAA Section 209 have always been considered
``other standards'' on fuel economy. As mentioned previously in the
discussion of the ``other standards'' to be considered as factors in
establishing maximum feasible fuel economy standards, EPCA, as
originally enacted, contained a specific self-contained provision that
provided that any manufacturer could apply to DOT for modification of
an average fuel economy standard for model years 1978 through 1980 if
it could show the likely existence of a ``Federal standards fuel
economy reduction,'' defined to include EPA-approved California
emissions standards that reduce fuel economy. The court reasoned that
``in 1975 when EPCA was passed, Congress unequivocally stated that
federal standards included EPA-approved California emissions
standards.'' \524\ However, when EPCA was recodified in 1994, ``all
reference to the modification process applicable for model years 1978
through 1980, including the categories of federal standards, was
omitted as executed.'' \525\ The court noted that the legislative
intent of the 1994 recodification was not intended to make a
substantive change to the law.\526\ Thus, the court concluded that
``[i]f the recodification worked no substantive change in the law, then
the term `other motor vehicle standards of the Government' continues to
include both emission standards issued by EPA and emission standards
for which EPA has issued a waiver under Section 209(b) of the CAA, as
it did when enacted in 1975.'' \527\
---------------------------------------------------------------------------
\524\ Central Valley Chrysler-Jeep, 529 F.Supp.2d at 1173
(quoting Green Mountain Chrysler, 508 F.Supp.2d at 345). EPCA
Section 502(d)(3)(D)(i) provided: ``Each of the following is a
category of Federal standards: . . . Emissions standards under
Section 202 of the Clean Air Act, and emissions standards applicable
by reason of Section 209(b) of such Act.''
\525\ Id.
\526\ Id.
\527\ Id.
---------------------------------------------------------------------------
NHTSA believes that the district court misread EPCA to the point of
turning it on its head. As discussed previously in this document, the
``federal standards'' definition discussed by the court existed in a
self-contained scheme allowing manufacturers to petition NHTSA for
modification of the fuel economy requirements only between 1978 and
[[Page 43237]]
1980, and thus has no application either at the time of the decision or
today. And even if that definition of ``federal standards'' were
applied to EPCA generally, NHTSA would balance that against other
factors enumerated in EPCA that it ``shall'' consider in setting
maximum feasible fuel economy standards. However, the district courts'
view is that this factor instead creates an ``obligation'' to
``harmonize'' CAFE standards with state emissions regulations under a
CAA Section 209 waiver.\528\ In other words, under the district courts'
opinions, a state standard controls what NHTSA does, and the agency
therefore has no further discretion to consider the other factors
Congress directed it to consider. Consistent with the legislative
history and NHTSA's long-standing interpretations, NHTSA interprets
EPCA, a statute which it administers in implementing the national fuel
economy program, as providing that the requirement to ``consider'' the
four EPCA statutory factors set forth in 49 U.S.C. 32902(f) does not
mean the agency is obligated to harmonize CAFE standards with state
tailpipe CO2 emissions standards. EPA concurs that a CAA
waiver does not also waive the effect of any other Federal law,
including EPCA.
---------------------------------------------------------------------------
\528\ Id. at 1170.
---------------------------------------------------------------------------
As discussed above in the ``other standards'' section of this
rulemaking, NHTSA further believes that the district courts in Green
Mountain Chrysler and Central Valley Chrysler-Jeep misconstrued the
provision in EPCA as enacted in 1975 that allowed manufacturers to
petition NHTSA to reduce CAFE standards that Congress had set for model
years 1978, 1979, and 1980 if there was a ``Federal standards fuel
economy reduction.'' \529\ This provision did not involve a factor to
be balanced in determining fuel economy standards. It provided for a
reduction in fuel economy standards for cars at a time when only
conventional pollutants were regulated. The provision was specifically
designed to address California's then-existing smog regulations,
particularly with regard to the additional weight (which other things
being equal reduces fuel economy) associated with catalytic converters.
In so doing, Congress recognized the potential interplay for three
model years between California's smog regulations and the possibility
that it could reduce Federal fuel economy standards for those model
years.\530\ Thus, EPCA went on to include ``Emissions standards under
Section 202 of the CAA, and emissions standards applicable by reason of
Section 209(b) of such Act'' in its list of ``categor[ies] of Federal
standards.'' \531\
---------------------------------------------------------------------------
\529\ Public Law 94-163 sec. 502(d), 89 Stat. 904-05.
\530\ See H.R. No. 94-340, at 87.
\531\ Id. Sec. 502(d)(3)(D).
---------------------------------------------------------------------------
Because California standards to combat smog (not GHG regulations)
``by reason of section 209(b)'' could be considered to reduce federal
fuel economy standards for three years, the district courts erroneously
believed that state CO2 regulations are somehow now
``federal'' standards under 49 U.S.C. 32902(f). On its face, this
language applied only to three long past model years and only to
reducing standards, not setting them. ``For purposes of this
subsection'' referred to section 502(d) of EPCA--not EPCA section
502(e) [now 49 U.S.C. 32902(f)] which sets forth the EPCA factor of
``the effect of other Federal motor vehicle standards on fuel
economy.'' After MY 1980, section 502(d) became obsolete. When EPCA was
recodified in 1994, section 502(d) was dropped as executed and
therefore surplusage. As the listing of Federal standards in 502(d)
never had any application outside that subsection and ceased to have
significance when that subsection became obsolete, it had and has no
bearing on the recodified version of EPCA. The recodification to
rescind this subsection, which had no substantive significance for 14
years, was entirely non-substantive.\532\
---------------------------------------------------------------------------
\532\ The recodification was ``[t]o revise, codify, and enact
without substantive change'' laws related to transportation. Public
Law 103-272 (emphasis added).
---------------------------------------------------------------------------
NHTSA believes that the district courts in Green Mountain Chrysler
and Central Valley Chrysler-Jeep sought to give a CAA waiver for the
California GHG regulation an effect far beyond the terms of the CAA
provision authorizing such a waiver. As discussed previously, the
courts overlooked the fact that the CAA itself makes clear that waiver
of preemption under that statute operates only to relieve application
of the CAA preemption statute.\533\ State GHG regulations, even if
subject to an EPA waiver, would remain regulations ``adopt[ed] or
enforc[ed]'' by ``a State or political subdivision of a State'' and
therefore would be subject to preemption by EPCA.\534\
---------------------------------------------------------------------------
\533\ 42 U.S.C. 7543(b)(1) (emphasis added); see also 42 U.S.C.
7543(b)(3) (``compliance with such State standards shall be treated
as compliance with applicable Federal standards for purposes of this
subchapter'') (emphasis added).
\534\ 49 U.S.C. 32919(a).
---------------------------------------------------------------------------
The courts' view suggests an apparent misunderstanding of the
underlying concerns and purposes of the requirement to consider other
standards. There is no hint in the histories of either EPCA or EISA of
an intent to give other standards special, much less superior, status
under EPCA. The limited concerns and purpose were to ensure that any
adverse effects of other standards on fuel economy considered in
connection with the fuel economy standards. Those concerns are evident
in a 1974 report, entitled ``Potential for Motor Vehicle Fuel Economy
Improvement,'' submitted to Congress by the Department of
Transportation and EPA.\535\ That report noted that the weight added by
safety standards would and one set of emissions standards might
temporarily reduce the level of achievable fuel economy.\536\ These
concerns can also be found in the congressional reports on EPCA.\537\
---------------------------------------------------------------------------
\535\ This report was prepared in compliance with Section 10 of
the Energy Supply and Environmental Coordination Act of 1974, Public
Law 93-319.
\536\ See id. at 6-8 and 91-93.
\537\ See page 22 of Senate Report 94-179, pages 88 and 90 of
House Report 94-340, and pages 155-7 of the Conference Report,
Senate Report 94-516.
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(f) State Tailpipe GHG Emissions Standards Conflict With EPCA and are
Therefore Preempted Impliedly
Notwithstanding that state standards limiting or prohibiting
tailpipe CO2 emissions are expressly preempted by EPCA, they
also clearly conflict with the objectives of EPCA and would therefore
also be impliedly preempted.
State regulation of CO2 emissions would frustrate
Congress' objectives in establishing the CAFE program and conflict with
NHTSA's efforts to implement the program in a manner consistent with
EPCA. While the overarching purpose of EPCA may be energy conservation,
Congress directed NHTSA to consider four factors in establishing
maximum feasible fuel economy standards. NHTSA balances these factors
to determine, through the CAFE program, the amount of energy the light-
duty vehicle fleet should conserve. Allowing a state to make a state-
specific determination for how much energy should be conserved (in the
same way that the CAFE program conserves energy) necessarily frustrates
NHTSA's efforts to make that determination for the country as a whole
because it sends the industry in different directions in order to try
to meet multiple standards at once rather than allowing the industry to
focus its resources and efforts on the path laid out at the Federal
level. This is particularly true when considering that when California
sets standards, other states can choose to adopt those
[[Page 43238]]
standards and thereby further increase the compliance complexity.
A critical objective of EPCA was to establish a single national
program to regulate vehicle fuel economy. Congress, in passing EPCA,
accomplished this objective by providing broad preemptive power
established in the language codified at 49 U.S.C. 32919(a). Other
congressional objectives underlying EPCA include avoiding serious
adverse economic effects on manufacturers and maintaining a reasonable
amount of consumer choice among a broad variety of vehicles. To guide
the agency toward the selection of standards meeting these competing
objectives, Congress specified four factors that NHTSA must consider in
determining the maximum feasible level of average fuel economy and thus
the level at which each standard must be set. As discussed above, since
the only practical way to reduce tailpipe CO2 emissions is
to improve fuel economy, it would be impossible for a state tailpipe
CO2 emissions standard to be adopted without interfering
with CAFE standards. If a state were to establish standards that have
the effect of requiring a lower level of fuel economy than CAFE
standards, those standards would be meaningless since they would not
reduce CO2 emissions. Instead, a State could only establish
a standard that has the effect of requiring a higher level of average
fuel economy. Setting standards that are more stringent than the fuel
economy standards promulgated under EPCA would upset the efforts of
NHTSA to balance and achieve Congress's competing goals. Setting a
standard above the level judged by NHTSA to be consistent with the
statutory consideration after careful consideration of these issues in
a rulemaking proceeding would negate the agency's careful analysis and
decision-making.
For the same reasons, a state regulation having the effect of
regulating tailpipe carbon dioxide emissions or fuel economy is
likewise impliedly preempted under 49 U.S.C. Chapter 329.
The Vermont and California district court decisions discussed above
addressed conflict preemption. The Green Mountain Chrysler court
concluded that the Vermont GHG standards presented no conflict
preemption concerns and rejected the contention that Vermont's GHG
regulations would conflict with Congress' intent that there be a
single, nationwide fuel economy standard and that those regulations
upset NHTSA's careful balancing of the EPCA statutory factors in its
rulemaking proceedings. In rejecting the manufacturers' arguments, the
court held that the Vermont standards do not create an obstacle to
achieving EPCA's goals because the Vermont standards are, in the
court's judgment, consistent with EPCA's standard setting criteria. In
reaching that conclusion, the court did not consider the impact of the
Vermont standards on the balancing done by NHTSA in setting CAFE
standards. For its part, the court in Central Valley Chrysler-Jeep
concluded that there was no conflict preemption, since if California's
standards were granted a waiver under CAA section 209 by EPA, they
would satisfy CAA objectives and be consistent with EPCA.\538\ The
court simply assumed consistency. If this assumption proved incorrect,
to the extent of any incompatibility between the two regimes, ``NHTSA
is empowered to revise its standards'' to take into account
California's regulations, according to that court.
---------------------------------------------------------------------------
\538\ 529 F.Supp.2d at 1179.
---------------------------------------------------------------------------
NHTSA disagreed with the two district court rulings at the time and
continues to do so now. We note that the Vermont decision was appealed
and briefed (including an Amicus Brief filed by the United States)
prior to the stay and withdrawal of the litigation pursuant to the
National Program arrangement described previously. NHTSA was not a
party to those cases and is not bound by these decisions. Those
erroneous decisions further support the need for NHTSA, as the agency
with expert authority to interpret EPCA, to reaffirm its longstanding
view of the preemption provision. Moreover, EPA, as the agency charged
with administering the CAA, further determines that CAA waivers do not
``federalize'' state standards; therefore, state standards directly
affecting fuel economy are subject to EPCA preemption even if there is
a CAA waiver in place.
(g) ZEV Mandates
Another form of EPCA-preempted state regulation is a zero-emission
vehicle (ZEV) mandate. Such laws require that a certain number or
percentage of vehicles sold or delivered for sale within a state must
be ZEVs, vehicles that produce neither smog-forming nor CO2
tailpipe emissions. ZEV mandates may require either that actual ZEVs be
sold or delivered for sale or provide for generation and application of
ZEV credits, which may or may not be traded. While NHTSA has not
previously commented on the relationship between the ZEV mandates and
the CAFE program because the only feasible means to eliminate tailpipe
CO2 emissions is by eliminating the use of petroleum fuel
(i.e., electric or fuel cell propulsion), and because the purpose of
the ZEV program is to affect fuel economy,\539\ ZEV mandates directly
relate to fuel economy and are thereby expressly preempted. ZEV
mandates are also intended to force the development and commercial
deployment of ZEVs--regardless of the technological feasibility or
economic practicability of doing so--putting the program entirely at
odds with critical factors that Congress required NHTSA to consider in
establishing fuel economy standards. Therefore, ZEV mandates also
interfere with achieving the goals of EPCA and are therefore impliedly
preempted.
---------------------------------------------------------------------------
\539\ See, e.g., Fact Sheet: 2003 Zero Emission Vehicle Program,
California Air Resources Board (March 18, 2004), available at
https://www.arb.ca.gov/msprog/zevprog/factsheets/2003zevchanges.pdf
(stating that one of the ``significant features of the April 2003
changes to the ZEV regulation'' included removal of ``all references
to fuel economy or efficiency,'' after a 2002 lawsuit asserting that
AT PZEV provisions pertaining to the fuel economy of hybrid electric
vehicles were preempted by EPCA).
---------------------------------------------------------------------------
California's ZEV mandate represents the most prominent example.
California initially launched its ZEV mandate in 1990 to force the
development and deployment of ZEVs to reduce smog-forming emissions. As
California's Low Emission Vehicle and EPA's Tier 3 standards for
criteria pollutant emissions have become increasingly stringent, the
greater impact of California's ZEV mandate is the reduction of tailpipe
GHG emissions. In its latest iteration the ZEV mandate no longer
focuses on tailpipe smog forming emissions, a fact that CARB
acknowledged in 2012 when applying for a waiver for its Advanced Clean
Car Program, in stating ``[t]here is no criteria emissions benefit from
including the ZEV proposal in terms of vehicle (tank-to-wheel or TTW)
emissions. The LEV III criteria pollutant fleet standard is responsible
for those emission reductions in the fleet; the fleet would become
cleaner regardless of the ZEV regulation because manufacturers would
adjust their compliance response to the standard by making less
polluting conventional vehicles.'' \540\
---------------------------------------------------------------------------
\540\ Docket No. EPA-HQ-OAR-2012-0562, Pp. 15-16.
---------------------------------------------------------------------------
In its current configuration, the ZEV mandate requires
manufacturers to generate credits based upon the number of vehicles
delivered for retail sale. Vehicles earn varying amounts of ZEV credits
depending upon technology and range, with some vehicles earning several
credits. Manufacturers delivering for sale certain plug-in hybrid
[[Page 43239]]
vehicles earn some limited ZEV credits, even though they are not truly
ZEVs, but such credits can only satisfy a portion of a manufacturer's
ZEV credit requirements. The credit requirements increase annually,
with the number of required credits equaling 4.5% of a manufacturer's
light duty vehicle sales in 2018, rising to 22% in 2025.\541\ To hit
this 22% credit requirement, a manufacturer would need to deliver for
sale ZEVs totaling somewhere between less than eight percent and 15.4%
of their light duty sales in California, per various projections.\542\
With advance notice, manufacturers may elect to use credits earned from
over-complying with vehicle tailpipe GHG emission requirements toward
partial satisfaction of the ZEV mandate.
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\541\ Cal. Code Regs. tit.13, sec. 1962.2(b).
\542\ The Air Resources Board initially projected that 15.4% of
new vehicles delivered for sale would consist of ZEVs. See., e.g.,
Staff Report: Initial Statement of Reasons 2012 Proposed Amendments
to the California Zero Emission Vehicle Program Regulations,
California Air Resources Board at 48 (Dec. 7, 2011), available at
https://www.arb.ca.gov/regact/2012/zev2012/zevisor.pdf (stating
``[b]y model year 2025, staff expects 15.4 percent of new sales will
be ZEVs and [Plug-In Hybrids].'') However, an increased supply of
credits and projected increases in battery electric range has
resulted in others projecting reduced required ZEV fleet
penetration. See, e.g., What is ZEV?, Union of Concerned Scientists
(Oct. 31, 2016), https://www.ucsusa.org/clean-vehicles/california-and-western-states/what-is-zev (projecting ``about 8 percent of
sales to be ZEVs'' in 2025).
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The EPA has granted a waiver of CAA preemption under Section 209 of
the CAA for California's Advanced Clean Car program, which includes
California's ZEV mandate in addition to California's GHG regulation and
LEV program. Nine other states have elected to adopt the ZEV mandate
pursuant to Section 177 of the CAA \543\--which, combined with
California, represent approximately 30% of United States light duty
vehicle sales annually.\544\ Manufacturers must satisfy the ZEV mandate
for each state. While, traditionally, manufacturers could apply credits
earned in one state to satisfy the requirements of another state, this
``travel'' provision is limited only to fuel cell electric vehicles
beginning with MY 2018.
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\543\ These states are Connecticut, Maine, Maryland,
Massachusetts, New Jersey, New York, Oregon, Rhode Island, and
Vermont.
\544\ See Automotive Retailing: State by State, National
Automobile Dealers Association, https://www.nada.org/statedata/
(last visited June 25, 2018) (estimating that these states
represented 28.6% of new motor vehicle registrations in 2016).
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Accordingly, manufacturers must endeavor to design, produce, and
deliver for sale significant numbers of vehicles that produce zero
tailpipe CO2 emissions within each state that has adopted
the California ZEV mandate. This involves implementation of some of the
most expensive and advanced technologies in the automotive industry,
regardless of consumer demand (which tends to be lower during periods
of sustained relatively-low gasoline prices). The California Air
Resources Board's own midterm review report for their Advanced Clean
Car program cites estimates from the 2016 Draft Technical Assessment
Report relating to the incremental vehicle costs of ZEVs over 2016
vehicles with internal combustion engines.\545\ While stating marginal
increased costs have fallen when compared to previous estimates, CARB
nevertheless still shows battery electric subcompact vehicles with 75
miles of range, for which consumer demand remains very low, as costing
$7,505 more than ones with an internal combustion engine, with large
cars costing $11,355 more. Battery electric subcompacts with a 200-mile
range, for which consumer demand is slightly higher than a 75-mile
range, were estimated to cost $12,001 more than comparable vehicles
with internal combustion engines, and large cars $16,746 more. Even
subcompact plug-in hybrids with 40 miles of electric range cost $9,260
more than internal combustion engine equivalents, and $13,991 more for
large cars. And as discussed above, consumers have not been willing to
pay the full cost of this technology--meaning manufacturers are likely
to spread the costs of the ZEV mandate to non-ZEV vehicles (and to
vehicles sold in other states). This expensive and market-distorting
mandate for manufacturers to eliminate vehicle tailpipe CO2
emissions (and thus petroleum fuel use) for part of their fleets has
always interfered with NHTSA's balancing of statutory factors in
establishing maximum feasible fuel economy standards, and increasing
ZEV credit requirements through 2025 make it all-the-more of an
obstacle to accomplishing EPCA's goal of establishing a coherent
national fuel economy program. Unlike NHTSA's CAFE program, the ZEV
mandate forces investment in specific technology (electric and fuel
cell technology) rather than allowing manufacturers to improve fuel
economy through more cost-effective technologies that better reflect
consumer demand.\546\ This appears to conflict directly with Congress'
intent that CAFE standards be performance-based rather than design
mandates. Moreover, by forcing manufacturers to design, produce, and
deliver for sale vehicles that produce no tailpipe CO2
emissions, the ZEV mandate forces further expensive investments in
fuel-saving technology than NHTSA has determined appropriate to require
in setting fuel economy standards.\547\ We seek comment on the extent
to which compliance with the ZEV mandate frustrates manufacturers'
efforts to comply with CAFE standards.
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\545\ California Air Resources Board, California's Advanced
Clean Cars Midterm Review, Appendix C, Zero Emission Vehicle and
Plug-in Hybrid Electric Vehicle Technology Assessment, Table 8, at
C-64 (Jan. 18, 2017), available at https://www.arb.ca.gov/msprog/acc/mtr/appendix_c.pdf.
\546\ 13 Cal. Code of Regulations 1962.2.
\547\ See, e.g., Alan, J., Hardman, S. & Carley, S. Cost
implications for automakers' compliance with emission standards from
Zero Emissions Vehicle mandate, TRB 2018 Annual Meeting paper
submittal, https://trid.trb.org/view/1495714 (last accessed June 28,
2018) (finding based on independent research that in 2025, costs
reach approximately $1,500 per vehicle on average to comply with
CAFE alone and increase to around $2,100 per vehicle on average to
comply with both CAFE and ZEV).
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For the reasons outlined above, the California ZEV mandate is
expressly and impliedly preempted by EPCA. While EPA had previously
granted a waiver of CAA preemption for California's Advanced Clean Car
Program, which includes the California ZEV mandate, this waiver has no
effect on EPCA preemption of the ZEV mandate, as described above.
3. Conclusion and Severability
Given the importance of an effective, smooth functioning national
program to regulate fuel economy and in light of the failure of two
Federal district courts to consider NHTSA's analysis and carefully
crafted position on preemption, NHTSA is considering taking the further
step of summarizing that position in an appendix to be added to the
parts in the Code of Federal Regulations setting forth the passenger
car and light truck CAFE standards. That proposed regulatory text may
be found at the end of this preamble.
NHTSA considers its proposed decision on the maximum feasible CAFE
standards for MY 2021-2026 to be severable from its decision on EPCA
preemption. Our proposed interpretation of 49 U.S.C. 32919 does not
depend on our decision to finalize and a court's decision to uphold,
the CAFE standards being proposed today under 49 U.S.C. 32902. NHTSA
solicits comment on the severability of these actions.
[[Page 43240]]
B. Preemption Under the Clean Air Act
1. Background
(a) Statutory Background: Clean Air Act Section 209(a) Preemption,
Section 209(b)(1) California Waiver, and Section 209(b)(1)(A)-(C)
Prohibitions on Waiver
EPA's regulation of new motor vehicles under Title II generally
preempts state standards in the same subject area. Section 209(a) of
the Act provides that:
``No State or any political subdivision thereof shall adopt or
attempt to enforce any standard relating to the control of emissions
from new motor vehicles or new motor vehicle engines subject to this
part. No State shall require certification, inspection or any other
approval relating to the control of emissions from any new motor
vehicle or new motor vehicle engine as condition precedent to the
initial retail sale, titling (if any), or registration of such motor
vehicle, motor vehicle engine, or equipment.'' \548\
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\548\ Clean Air Act (CAA) section 209(a), 42 U.S.C. 7543(a).
However, Title II affords special treatment to California: Subject
to certain conditions, it may obtain from EPA a waiver of section
209(a) preemption. Specifically, section 209(b)(1) of the Act requires
the Administrator, after an opportunity for public hearing, to waive
application of the prohibitions of section 209(a) to California, if
California determines that its State standards will be, in the
aggregate, at least as protective of public health and welfare as
applicable Federal standards.\549\ A waiver under section 209(b)(1)
allows California to ``adopt [and] enforce a[] standard relating to the
control of emissions from new motor vehicles or new motor vehicle
engines.'' CAA section 209(a), 42 U.S.C. 7543(a).
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\549\ CAA section 209(b), 42 U.S.C. 7543(b). The provision does
not identify California by name. Rather, it applies on its face to
``any State which has adopted standards (other than crankcase
emission standards) for the control of emissions from new motor
vehicles or new motor vehicle engines prior to March 30, 1966.''
California is the only State that meets this requirement. See S.
Rep. No. 90-403 at 632 (1967). This proposal refers interchangeably
to ``California'' and ``CARB'' (the California Air Resources Board).
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But California's ability to obtain a waiver is not unlimited. The
statute provides that ``no such waiver will be granted'' if the
Administrator finds any of the following: ``(A) [California's]
determination [that its standards in the aggregate will be at least as
protective] is arbitrary and capricious, (B) [California] does not need
such State standards to meet compelling and extraordinary conditions,
or (C) such State standards and accompanying enforcement procedures are
not consistent with section [202(a)].'' Section 209(b)(1)(A)-(C), 42
U.S.C. 7543(b)(1)(A-(C) (Emphasis added).\550\ Any one of these three
findings operates to forbid a waiver.
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\550\ As presented in the United States Code, the cross-
reference in prong (C) is to ``section 7521(a) of this title,''
i.e., CAA section 201(a), 42 U.S.C. 7521(a), which governs EPA's
administration of ``Emission standards for new motor vehicles or new
motor vehicle engines administration of ``Emissions standards for
new motor vehicles or new motor vehicle engines.''
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(1) EPA's Proposed Action
EPA is proposing to withdraw the January 9, 2013 waiver of
preemption for California's Advanced Clean Car (ACC) program, Zero
Emissions Vehicle (ZEV) mandate, and Greenhouse Gas (GHG) standards
that are applicable to new model year (MY) 2021 through 2025. 78 FR
2145 (January 9, 2013.) 551 552 EPA proposes to do so on
multiple grounds.
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\551\ This proposed action does not address whether the
statutory interpretations and their policy consequences laid out in
the proposal may have implications for past waivers granted to
California for other standards besides its GHG and ZEV standards.
EPA proposes to take this action in the context of this joint
rulemaking with NHTSA, and the California standards identified
herein are the focus of EPA's proposal. As circumstances require and
resources permit, EPA may in future actions consider whether this
proposal, if finalized, makes it appropriate or necessary to revisit
past grants of other waivers beyond those granted with respect to
California's GHG and ZEV program.
\552\ EPA proposes to withdraw the waiver for these model years
because these are the model years at issue in NHTSA's proposal. EPA
solicits comment on whether one or more of the grounds supporting
the proposed withdrawal of this waiver would also support
withdrawing other waivers that it has previously granted.
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First, EPA notes that elsewhere in this notice NHTSA has proposed
to find that California's GHG and ZEV standards are preempted under
EPCA. Although EPA has historically declined to consider as part of the
waiver process whether California standards are constitutional or
otherwise legal under other Federal statutes apart from the Clean Air
Act, EPA believes that this notice presents a unique situation and that
it is appropriate to consider the implications of NHTSA's proposed
conclusion as part of EPA's reconsideration of the waiver. In this
regard, EPA is proposing to conclude that state standards preempted
under EPCA cannot be afforded a valid waiver of preemption under CAA
209(b). Accordingly, EPA is proposing to conclude that if NHTSA
finalizes a determination that California's GHG and ZEV standards are
preempted, then it would be necessary to withdraw the waiver separate
and apart from the analysis under section 209(b)(1)(B), (C) that
follows.
Second, under section 209(b)(1)(B) (compelling and extraordinary
conditions), EPA proposes to find that California does not need its GHG
and ZEV standards to meet compelling and extraordinary conditions
because those standards address environmental problems that are not
particular or unique to California, that are not caused by emissions or
other factors particular or unique to California, and for which the
standards will not provide any remedy particular or unique to
California.
Third, under section 209(b)(1)(C) (consistency with section
202(a)), EPA proposes to find that California's GHG and ZEV standards
are inconsistent with section 202(a) because they are technologically
infeasible in that they provide sufficient lead time to permit the
development of necessary technology, giving appropriate consideration
to compliance costs.\553\
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\553\ Under section 209(b)(1)(C) of the CAA, EPA must deny
California's waiver request if EPA finds that California's standards
and accompanying enforcement procedures are not consistent with
section 202(a). Section 202(a) provides that an emission standard
shall take effect after such period of time as the Administrator
finds necessary to permit development and application of the
requisite technology, giving appropriate consideration to compliance
costs.
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EPA therefore proposes to make findings under sections 209(b)(1)(B)
and (C), either of which, as discussed above, independently triggers
the statutory prohibition that ``no such waiver will be granted.''
In addition, EPA proposes to conclude that States may not adopt
California's GHG standards pursuant to section 177 because the text,
context, and purpose of section 177 support the conclusion that this
provision is limited to providing States the ability, under certain
circumstances and with certain conditions, to adopt and enforce
standards designed to control criteria pollutants to address NAAQS
nonattainment.
(2) History of Waiver for California GHG and ZEV Standards, and
Associated Issues of Statutory Interpretation
In December 2005, California for the first time applied to EPA for
a preemption waiver for GHG standards for MY 2009 and following. EPA
denied this request in March 2008, relying on the second prong under
section 209(b)(1)(B) and finding that California did not need those
standards to meet compelling and extraordinary conditions. In doing so,
it noted that GHG standards, unlike prior standards for which
California had requested and received waivers, are designed to address
global air pollution problems--not air pollution problems specific to
California. 73 FR 12156, March 6, 2008.
[[Page 43241]]
Due to this new circumstance, EPA reconsidered its historic
interpretation and application of section 209(b)(1)(B). Although
today's proposal contains proposed findings under each prong of
209(b)(1), prong (B) was the only one at issue in the 2008 waiver
denial (and EPA's subsequent reversal), and it merits extended
discussion at the outset due to its central significance in the policy
and legal context and the history underlying today's proposal.
As a general matter, EPA had historically interpreted section
209(b)(1)(B) to require EPA to consider whether, to meet compelling and
extraordinary conditions in California, the state needs to have its own
separate new motor vehicle program in the aggregate.\554\ Under this
historical approach, EPA considered California's need for a separate
program as a whole, rather than California's need for the particular
aspect of the program for which California sought a waiver in any
particular instance. (Typically, prior to its ACC program waiver
request, California would seek a waiver for only particular aspects of
its new motor vehicle program.) In the 2008 GHG waiver denial, EPA
determined that this interpretation was inappropriate under the
circumstances.
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\554\ See, e.g., 49 FR 18887 (May 3, 1984).
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In its 2008 waiver denial, EPA proceeded under two alternative
constructions of the statute. Under both of these constructions, EPA
determined that it was a reasonable interpretation of section
209(b)(1)(B) to require a separate review of California's need for
standards designed to address a global air pollution problem and its
effects, as distinct from other portions of California's new motor
vehicle program, which up until then had been designed to address local
or regional air pollution problems.\555\ Under the first construction,
EPA found it relevant that elevated GHG concentrations in California
were similar to concentrations found elsewhere in the world, and that
local conditions in California, such as the local topography, the local
climate, and the significant number of motor vehicles in California,
were not the determining factors causing the elevated GHG
concentrations found in California and elsewhere. In sum, EPA found
that California did not need its GHG standards to meet ``compelling and
extraordinary conditions''--interpreting ``compelling and extraordinary
conditions'' to mean environmental problems with causes that were
specific to California--given that those standards were designed to
address global air pollution problems as compared to local or regional
air pollution problems caused specifically by certain conditions in
California.
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\555\ Criteria pollutants generally present public health and
environmental concern in proportion to their ambient local
concentration and California has long had unusually severe problems
in this regard.
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EPA in the 2008 waiver denial also applied a second, alternative
construction of section 209(b)(1)(B). Under this alternative
construction, EPA considered whether the impacts of climate change in
California were sufficiently different enough from the impacts felt in
the rest of the country such that California could be considered to
need its GHG standards to meet compelling and extraordinary
conditions--interpreting ``compelling and extraordinary conditions'' to
mean environmental effects specific to California.
The next year, following a presidential election and change in
administration, EPA reconsidered the 2008 denial at California's
request. On reconsideration, EPA reversed course and granted a waiver
for California's GHG standards. 74 FR 32744 (July 9, 2009). In granting
the waiver, EPA reverted to its historical interpretation of section
209(b)(1)(B), under which it had construed ``compelling and
extraordinary conditions'' to mean environmental problems caused by
conditions specific to California and/or effects experienced to a
unique degree or in a unique manner in California, and under which it
had evaluated California's need for its own, separate new motor vehicle
program as a whole, rather than California's need for the specific
aspects of its separate program for which it was seeking a waiver. In
reverting to this determination, the EPA necessarily determined that it
makes no difference whether California seeks a waiver to implement
separate standards in response to its own specific, local air pollution
problems, or whether California seeks a waiver to implement separate
standards designed to address a global air pollution problem.
Since 2009, EPA has continued to adhere to this interpretation and
application of section 209(b)(1)(B) when reviewing CARB's waiver
requests, regardless of whether the waiver was requested with regard to
standards designed to address traditional, local environmental
problems, or global climate issues. In this proposal, the EPA proposes
to determine that this reversion to the pre-2008 interpretation was not
appropriate.
On January 9, 2013, EPA granted CARB's request for a waiver of
preemption to enforce its ACC program regulations pursuant to CAA
section 209(b). 78 FR 2112. The ACC program is a single coordinated
package comprising regulations for ZEV and low-emission vehicles (LEV)
regulations,\556\ for new passenger cars, light-duty trucks, medium-
duty passenger vehicles, and certain heavy-duty vehicles, for MY 2015
through 2025. Thus, in terms of proportion, the ACC program is
comparable to the combined Federal Tier 3 Motor Vehicle Emissions
Standards and the 2017 and later MY Light-duty Vehicle GHG
Standards.\557\ According to CARB, the ACC program was intended to
address California's near and long-term smog issues as well as certain
specific GHG emission reduction goals.\558\ 78 FR 2114. See also 78 FR
2122, 2130-31.
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\556\ The LEV regulations in question include standards for both
GHG and criteria pollutants (including ozone and PM). Amendments for
the LEV III program included replacement of separate nonmethane
organic gas (NMOG) and oxides of nitrogen (NOX) standards
with combined NMOG plus NOX standards, which provides
automobile manufacturers with additional flexibility in meeting the
new stringent standards; an increase of full useful life durability
requirements from 120,000 miles to 150,000 miles, which guarantees
vehicles sustain these extremely low emission levels longer; a
backstop to assure continued production of super-ultra-low-emission
vehicles after partial-zero-emission vehicles (PZEVs) as a category
are moved from the ZEV regulations to the LEV regulations in 2018;
more stringent particulate matter (PM) standards for light- and
medium-duty vehicles, which will reduce the health effects and
premature deaths associated with these emissions; zero fuel
evaporative emission standards for PCs and LDTs, and more stringent
standards for medium- and heavy-duty vehicles (MDVs); and, more
stringent supplemental federal test procedure (SFTP) standards for
PC and LDTs, which reflect more aggressive real world driving and,
for the first time, require MDVs to meet SFTP standards. 78 FR 2114.
\557\ 78 FR 23641, April 22, 2016; 77 FR 62624, October 15,
2012.
\558\ ``The Advanced Clean Cars program . . . will reduce
criteria pollutants . . . and . . . help achieve attainment of air
quality standards; The Advanced Clean Cars Program will also reduce
greenhouse gases emissions as follows: by 2025, CO2
equivalent emissions will be reduced by 13 million metric tons (MMT)
per year, which is 12 percent from base line levels; the reduction
increases in 2035 to 31 MMT/year, a 27 percent reduction from
baseline levels; by 2050, the proposed regulation would reduce
emissions by more than 40 MMT/year, a reduction of 33 percent from
baseline levels; and viewed cumulatively over the life of the
regulation (2017-2050), the proposed Advanced Clean Cars regulation
will reduce by more than 850 MMT CO2-equivalent, which
will help achieve the State's climate change goals to reduce the
threat that climate change poses to California's public health,
water resources, agriculture industry, ecology and economy.'' 78 FR
2114. CARB Resolution 12-11, at 19, (January 26, 2012), available in
the docket for the January 2013 waiver action, Document No. EPA-HQ-
OAR-2012-0562, the docket for the ACC program waiver.
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The ACC program regulations impose multiple and varying complex
compliance obligations that have simultaneous, and sometimes
overlapping, deadlines with each
[[Page 43242]]
standard. These deadlines began in 2015 and are scheduled to be phased
in through 2025. For example, compliance with the GHG requirements
began in 2017 and will be phased-in through 2025. The implementation
schedule and the interrelationship of regulatory provisions with each
of the three standards together demonstrates that CARB intended that at
least the GHG and ZEV standards, if not also the LEV standards, would
be implemented as a cohesive program. For example, in its ACC waiver
request, CARB stated that the ``ZEV regulation must be considered in
conjunction with the proposed LEV III amendments. Vehicles produced as
a result of the ZEV regulation are part of a manufacturer's light-duty
fleet and are therefore included when calculating fleet averages for
compliance with the LEV III GHG amendments.'' CARB's Initial Statement
of Reasons at 62-63.\559\ CARB also noted ``[b]ecause the ZEVs have
ultra-low GHG emission levels that are far lower than non-ZEV
technology, they are a critical component of automakers' LEV III GHG
standard compliance strategies.'' Id. CARB further explained that ``the
ultra-low GHG ZEV technology is a major component of compliance with
the LEV III GHG fleet standards for the overall light duty fleet.'' Id.
CARB's request also repeatedly touted the GHG emissions benefits of the
ACC program.
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\559\ Available in the docket for the January 2013 waiver
decision, Docket No. EPA-HQ-OAR-2012-0562.
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Up until the ACC program waiver request, CARB had relied on the ZEV
requirements as a compliance option for reducing criteria pollutants.
Specifically, California first included the ZEV requirement as part of
its first LEV program, which was then known as LEV I, that mandated a
ZEV sales requirement that phased-in starting with the 1998 MY through
2003 MY. EPA issued a waiver of preemption for these regulations on
January 13, 1993 (58 FR 4166 (January 13, 1993). Since this initial
waiver of preemption, California has made multiple amendments to the
ZEV requirements and EPA has subsequently granted waivers for those
amendments. In the ACC program waiver request California also included
a waiver of preemption request for ZEV amendments that related to 2012
MY through 2017 MY and imposed new requirements for 2018 MY through
2025 MY (78 FR 2118-9). Regarding the ACC program ZEV requirements,
CARB's waiver request noted that there was no criteria emissions
benefit in terms of vehicle (tank-to-wheel--TTW) emissions because its
LEV III criteria pollutant fleet standard was responsible for those
emission reductions.\560\ CARB further noted that its ZEV regulation
was intended to focus primarily on zero emission drive--that is,
battery electric (BEVs), plug-in hybrid electric vehicles (PHEVs), and
hydrogen fuel cell vehicles (FCVs)--in order to move advanced, low GHG
vehicles from demonstration phase to commercialization (78 FR 2122,
2130-31). Specifically, for 2018 MY through 2025 MY, the ACC program
ZEV requirements mandate use of technologies such as BEVs, PHEVs and
FCVs, in up to 15% of a manufacturer's California fleet and in each of
the section 177 States by MY 2025 \561\ (78 FR 2114). Additionally, the
ACC program regulations provide various compliance flexibilities
allowing for substitution of compliance with one program requirement
for another. For instance, manufacturers may opt to over-comply with
the GHG fleet standard in order to offset a portion of their ZEV
compliance requirement for MY 2018 through 2021. Further, until MY
2018, sales of BEVs (since MY 2018, limited to FCVs) in California
count toward a manufacturer's credit requirement in section 177 States.
This is known as the ``travel provision'' (78 FR 2120).\562\ For their
part, the GHG emission regulations include an optional compliance
provision that allows manufacturers to demonstrate compliance with
CARB's GHG standards by complying with applicable Federal GHG
standards. This is known as the ``deemed to comply'' provision.\563\ A
complete description of the ACC program can be found in CARB's waiver
request, located in the docket for the January 2013 waiver action,
Docket No. EPA-HQ-OAR-2012-0562.
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\560\ CARB ACC waiver request at EPA-HQ-OAR-2012-0562-0004.
\561\ Under section 177, any State that has state implementation
plan provisions approved under part D of Subchapter I of the Act may
opt to adopt and enforce standards that are identical to standards
for which EPA has granted a waiver of preemption to California under
CAA section 209(b). EPA's longstanding interpretation of section
209(b) and its relationship with section 177 is that it is not
appropriate under section 209(b)(1)(C) to review California
regulations, submitted by CARB, through the prism of adopted or
potentially adopted regulations by section 177 States.
\562\ On March 11, 2013, the Association of Global Automakers
and Alliance of Automobile Manufacturers filed a petition for
reconsideration of the January 2013 waiver grant, requesting that
EPA reconsider the decision to grant a waiver for MYs 2018 through
2025 ZEV standards on technological feasibility grounds. Petitioners
also asked for consideration of the impact of the travel provision,
which they argue raise technological feasibility issues in section
177 States, as part of the agency's review under section
209(b)(1)(C). EPA continues to evaluate the petition.
\563\ On May 7, 2018, California issued a notice seeking
comments on ``potential alternatives to a potential clarification''
of this provision for MY vehicles that would be affected by
revisions to the Federal GHG standards. The notice is available at
https://www.arb.ca.gov/msprog/levprog/leviii/leviii_dtc_notice05072018.pdf.
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2. Statutory Provisions Applicable to the Proposed Action
Under section 209(b) of the Clean Air Act, EPA may reconsider a
grant of a waiver of preemption and withdraw same if the Administrator
makes any one of the three findings in section 209(b)(1)(A), (B) and
(C). EPA's authority to reconsider and withdraw the grant of a waiver
for the ACC program is implicit in section 209(b) given that the
authority to revoke a grant of authority is implied in the authority
for such a grant. Further support for EPA's authority is based on the
legislative history for section 209(b), and the judicial principle that
agencies possess inherent authority to reconsider their decisions.\564\
The legislative history from the 1967 CAA amendments where Congress
enacted the provisions now codified in section 209(a) and (b) provides
support for this view. The Administrator has ``the right . . . to
withdraw the waiver at any time [if] after notice and an opportunity
for public hearing he finds that the State of California no longer
complies with the conditions of the waiver.'' S. Rep. No. 50-403, at 34
(1967). Additionally, subject to certain limitations, administrative
agencies possess inherent authority to reconsider their decisions in
response to changed circumstances. It is well settled that EPA has
inherent authority to reconsider, revise, or repeal past decisions to
the extent permitted by law so long as the Agency provides a reasoned
explanation. This authority exists in part because EPA's
interpretations of the statutes it administers ``are not carved in
stone.'' Chevron U.S.A. Inc. v. NRDC, Inc., 467 U.S. 837, 863 (1984).
An agency ``must consider varying interpretations and the wisdom of its
policy on a continuing basis.'' Id. at 863-64. This is true when, as is
the case here, review is undertaken ``in response to . . . a change in
administration.'' National Cable & Telecommunications Ass'n v. Brand X
internet Services, 545 U.S. 967, 981 (2005). The EPA must also be
cognizant
[[Page 43243]]
where it is changing a prior position and articulate a reasoned basis
for the change. FCC v. Fox Television Stations, Inc., 556 U.S. 502, 515
(2009). This proposal reflects changed circumstances that have arisen
since the initial grant of the 2013 ACC program waiver of preemption.
They include the agency's reconsideration of California's record
support for, and EPA's decision and underlying statutory interpretation
on, California's need for GHG and ZEV standards, as well as costs and
technological feasibility considerations that differ from California's
assumptions and which were bases for agency conclusions that were made
at that time.
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\564\ In 2009, EPA reconsidered the 2008 GHG waiver denial at
CARB's request and granted it upon reconsideration. 72 FR 32744. The
EPA noted the authority to ``withdraw a waiver in the future if
circumstances make such action appropriate.'' See 74 FR 32780 n.222;
see also 32752-53 n.50 (citing 50 S. Rep. No. 403, at 33-34), 32755
n.74.
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When California submits a package of standards for EPA review
pursuant to CAA section 209, EPA has long interpreted the statute as
authorizing EPA to approve certain provisions and defer action on
others. EPA believes this approach of partially approving submissions
is implicit in section 209, particularly given the fact that EPA's
evaluation of the technological feasibility of standards is best
understood as in effect an evaluation of each standard for each year
(i.e., standards that are submitted together may vary substantially in
their effect and some may require longer lead time than others).
Furthermore, since California always retains the authority as a matter
of state law to determine whether to implement state standards for
which a waiver of preemption has been granted, we do not believe this
approach poses the risk that a partial approval could force California
to implement a program they would not have chosen had they anticipated
EPA's decision. EPA believes that because its authority to grant
waivers of preemption is best understood as applying on a granular
level--where the feasibility of compliance for a particular year can be
assessed--rather than being limited to approving or disapproving
preemption for an entire package of standards submitted together, it
follows that EPA's authority to withdraw the grant of waiver of
preemption should also apply on a granular level, i.e., for any model
year for which EPA concludes the conditions for waiver of preemption no
longer exist or for which it concludes that it erred in its prior
determination that one of the conditions triggering a denial a waiver
was not met. Further, because neither the Clean Air Act nor the
Administrative Procedure Act specify deadlines for reconsideration of
agency action, EPA may, issue a new final action to change a prior
action, taking into account statutory mandates and any applicable court
orders.\565\
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\565\ On March 11, 2013, EPA received a petition for
reconsideration from the Association of Global Automakers and
Alliance of Automobile Manufacturers of the decision to grant a
waiver for MYs 2018 through 2025 ZEV standards.
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EPA is proposing to withdraw the grant of a waiver of preemption
for California to enforce the GHG and ZEV standards of the ACC program
for MY 2021-2025. EPA proposes to withdraw due to separate proposed
findings under section 209(b)(1)(B), and (C).\566\
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\566\ Under this provision, a waiver is not permitted if (A) the
protectiveness determination of the State is arbitrary and
capricious; (B) the State does not need such State standards to meet
compelling and extraordinary conditions; or (C) such State standards
and accompanying enforcement procedures are not consistent with
section 202(a) of the Act.
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Under section 209(b)(1)(B), EPA is proposing to find that
California does not need its ZEV and GHG standards to meet compelling
and extraordinary conditions in California. EPA is proposing to find
that CARB does not need its own GHG and ZEV standards to meet
compelling and extraordinary conditions in California given that
``compelling and extraordinary conditions'' mean environmental problems
with causes and effects in California whereas GHG emissions present
global air pollution problems. Additionally, California does not need
the ZEV requirements to meet ``compelling and extraordinary''
conditions in California given that it allows manufacturers to generate
credits in section 177 states as a means to satisfy those
manufacturers' obligations to comply with the mandate that a certain
percentage of their vehicles sold in California be ZEV (or be credited
as such from sales in section 177 States).
Under section 209(b)(1)(C), EPA is proposing to find that CARB's
GHG and ZEV standards are not consistent with section 202(a) based on
changed circumstances since the January 2013 waiver. Specifically, the
agency is, in this action, jointly proposing with NHTSA revisions to
the Federal GHG and fuel economy standards based on proposed
conclusions that the current (or augural) standards for MY 2021 through
2025 are not feasible. The proposed findings in this notice call into
question CARB's projections and assumptions that underlay the
technological feasibility findings for its waiver application for the
GHG standards and thus the technological findings made by EPA in 2013
in connection with the grant of the waiver for the ACC program.
Similarly, with regard to ZEV standards, this notice also raises
questions as to CARB's technological projections for ZEV-type
technologies, which are a compliance option for both the ZEV mandate
and GHG standards. As also previously discussed, above, CARB's ZEV
regulations include the travel provision, which previously allowed
manufacturers to earn credit for ZEVs sold in California (which,
despite very slow ZEV sales, far outpaces any other State in these
sales) to comply with credit requirements in section 177 States.
Starting with MY 2018, this provision only applies to FCVs. When the
travel provision was adopted, it was anticipated that by MY 2018,
incentives of this type for BEV sales would no longer be necessary--
i.e., that consumers would adopt such vehicles on their own.
Unfortunately, there has been a serious lack of market penetration,
consumer demand levels, and lack of or slow development of necessary
infrastructure for any ZEVs--BEV or otherwise--in such States. This in
turn means that manufacturers' sales of ZEVs in section 177 States are
unlikely, contrary to CARB's projections in its submissions to support
its application for the ACC waiver, to generate sufficient credits to
satisfy those manufacturers' obligations to comply with the mandate
that a certain percentage of their vehicles sold in California be ZEV
(or be credited as such from sales in section 177 States). In short,
EPA is now of the view that CARB's projections and assumptions at the
time of the waiver request were overly ambitious and likely will not be
realized within the provided lead time. Thus, EPA is also proposing to
find that CARB's ZEV standards for MY 2021 through 2025, and the GHG
standards which rely on the ZEV requirement as a compliance option, are
technologically infeasible and therefore, not consistent with section
209(b)(1)(C).
As described above, EPA is proposing to withdraw the waiver with
respect to California's ZEV standards based on findings made pursuant
to sections 209(b)(1)(B) and 209(b)(1)(C). EPA is proposing to withdraw
the waiver with respect to California's GHG standards based on findings
made under these three prongs as well as a separate finding made under
section 209(b)(1)(B). Additionally, because the ZEV and GHG standards
are closely interrelated, as demonstrated by the description above of
their complex, overlapping compliance regimes, EPA is proposing to
withdraw the waiver of preemption for ZEV standards under the second
and third prongs of section 209(b)(1).
EPA believes that a finding made pursuant to any of the prongs of
section 209(b)(1) is an independent and
[[Page 43244]]
adequate ground to withdraw the waiver. In this regard, EPA notes that
the statute provides that ``No such waiver shall be granted if the
Administrator finds that--(B) the State does not need such State
standards to meet compelling and extraordinary conditions; or (C) such
State standards and accompanying enforcement procedures are not
consistent with section 202(a) of the Act.'' (Emphasis added.)
Consequently, a final waiver withdrawal decision that relies on more
than one of these provisions would present independent and severable
bases for the decision to withdraw. And, separate and apart from its
analysis under 209(b)(1)(A)-(C), EPA proposes to determine that if
NHTSA finalizes its proposed determination that EPCA preempts
California's standards, that would provide an independent and adequate
ground to withdraw the waiver for those standards. EPA proposes to
interpret section 209(b)(1) to only authorize it to waive CAA
preemption for standards that are not independently preempted by EPCA.
Additionally, under CAA section 177, States that have designated
nonattainment areas may opt to adopt and enforce standards that are
identical to standards for which EPA has granted a waiver of preemption
to California under CAA section 209(b). For States that have adopted
the ZEV standards, the consequence of any final withdrawal action would
be that they cannot implement these standards. (A State may not ``make
attempt[s] to enforce'' California standards for which EPA has not
waived preemption. Motor Vehicle Mfrs. Ass'n v. NYS Dep. of Envtl
Conservation, 17 F.3d 521, 534 (2d Cir. 1994)). Where states have
adopted CARB's ZEV and GHG standards into their SIPs, under section
177, the provisions of the SIP would continue to be enforceable until
revised. If this proposal is finalized, EPA may subsequently consider
whether to employ the appropriate provisions of the CAA to identify
provisions in section 177 states' SIPs that may require amendment and
to require submission of such amendments.
EPA is taking comments on all aspects of this proposal.
(a) Burden and Standard of Proof in Waiver Decisions
Here, the Administrator is proposing the withdrawal of a previously
granted waiver of preemption. As discussed in section III.A. below, EPA
proposes to find that there is clear and compelling evidence that
California's protectiveness determination for its ZEV and GHG standards
was arbitrary and capricious. Motor and Equip. Mfrs. Ass'n v. EPA, 627
F.2d 1095, 1112 (D.C. Cir. 1979) (MEMA I). Additionally, as discussed
in section III.B, below, EPA proposes to find that there is clear and
compelling evidence that California does not need its ZEV and GHG
standards to meet compelling and extraordinary conditions. Similarly,
as discussed in section III.C, below, there is clear and compelling
evidence that both the ZEV and GHG standards are not technologically
feasible.\567\
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\567\ EPA is assuming without agreeing that the burden of proof
requires clear and compelling evidence but believes a preponderance
of the evidence is the proper burden of proof. Regardless, EPA
firmly believes that it has clear and compelling evidence to support
the agency's statutory findings.
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In MEMA I, 627 F.2d 1095, the U.S. Court of Appeals for D.C.
Circuit found that ``the burden of proving [that California's
regulations do not comply with the CAA] is on whoever attacks them.
California must present its regulations and findings at the hearing and
thereafter the parties opposing the waiver request bear the burden of
persuading the Administrator that the waiver request should be
denied.'' \568\
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\568\ MEMA I, 627 F.2d at 1122.
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MEMA I dealt with a challenge brought by Motor and Equipment
Manufacturers Association against EPA's grant of a waiver of preemption
for California's accompanying enforcement procedures, which in this
instance were vehicle in-use maintenance regulations. The specific
challenge to EPA's action contested EPA's findings that section 209
allowed for a waiver of preemption for CARB's in-use maintenance
regulations. MEMA I also specifically considered the standards of proof
for two findings that EPA must make in order to grant a waiver for an
``accompanying enforcement procedure'' (as opposed to standards): (1)
Protectiveness in the aggregate and (2) consistency with section 202(a)
findings. The court instructed that ``the standard of proof must take
account of the nature of the risk of error involved in any given
decision, and it therefore varies with the finding involved. We need
not decide how this standard operates in every waiver decision.'' \569\
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\569\ Id.
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The court upheld the Agency's position that denying a waiver
required ``clear and compelling evidence'' to show that proposed
enforcement procedures undermine the protectiveness of California's
standards.\570\ The court noted that this standard of proof ``also
accords with the congressional intent to provide California with the
broadest possible discretion in setting regulations it finds protective
of the public health and welfare.'' \571\
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\570\ Id.
\571\ Id.
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With respect to the consistency finding, MEMA I did not articulate
a standard of proof applicable to all proceedings but found that the
opponents of the waiver were unable to meet their burden of proof even
if the standard were a mere preponderance of the evidence.
As the agency has consistently explained, although MEMA I did not
explicitly consider the standard of proof for ``standards,'' as
compared to ``accompanying enforcement procedures,'' nothing in the
opinion suggests that the court's analysis would not apply with equal
force to such determinations.\572\ Moreover, the normal standard of
proof in civil matters is a preponderance of the evidence.
International Harvester Co. v. Ruckelshaus, 478 F.2d 615, 643 (D.C.
Cir. 1979).
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\572\ 74 FR 32748.
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The role of the Administrator in considering California's
application for a preemption waiver is to make a reasonable evaluation
of the information in the record in coming to the waiver decision. The
Administrator is required to ``consider all evidence that passes the
threshold test of materiality and . . . thereafter assess such material
evidence against a standard of proof to determine whether the parties
favoring a denial of the waiver have shown that the factual
circumstances exist in which Congress intended a denial of the
waiver.'' \573\
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\573\ MEMA I, 627 F.2d at 1122.
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As the court in MEMA I stated, if the Administrator ignores
evidence demonstrating that the waiver should not be granted, or if he
seeks to overcome that evidence with unsupported assumptions of his
own, he runs the risk of having his waiver decision set aside as
``arbitrary and capricious.'' \574\ Therefore, the Administrator's
burden is to act ``reasonably.'' \575\
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\574\ Id. at 1126.
\575\ Id.
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The instant action involves a decision whether to withdraw a
previous grant of a waiver of preemption as compared to the initial
evaluation of and decision whether to grant a waiver request from
California. Specifically, as discussed in Section III, below, EPA is
proposing findings for the withdrawal of preemption for CARB's ACC
program under multiple criteria set out in section 209(b)(1). For
example, EPA is proposing to withdraw the waiver based
[[Page 43245]]
on considerations such as the nature of GHG concentrations as a global
air pollution problem, rather than a regional or local air pollution
problem, whether or not CARB's particular GHG standards actually would
reduce GHG emissions in California, whether a waiver for CARB's GHG
standards is permissible if those regulations are preempted by EPCA,
and the effect of technological infeasibility for the 2012 Federal GHG
standards for MY 2021-2025. Natural Resources Defense Council v. EPA,
655 F.2d 318, 331 (D.C. Cir. 1981) (``[T]here is substantial room for
deference to the EPA's expertise in projecting the likely course of
[technological] development.'') (Emphasis added.) EPA believes that
these are kinds of issues that extend well beyond the boundaries of
California's authority under section 209(b). EPA posits, therefore,
that the decision to withdraw the waiver would warrant exercise of the
Administrator's judgment.
Furthermore, that decision entails matters not only of policy
judgment but of statutory interpretation, chief among which is the
question of what is the appropriate inquiry under section 209(b)(1)
when the Administrator is faced with a request for a preemption waiver
for standards designed to address a global environmental problem. EPA
has previously expressed the view that certain waiver requests might
call for the Administrator to exercise judgment in determining
California's need for particular standards, under section 209(b)(1)(B).
Specifically, in the March 6, 2008 GHG waiver denial, EPA posited that
it was neither required nor appropriate for the Agency to defer to
California on the statutory interpretation of the Clean Air Act,
including the issue of the confines or limits of state authority
established by section 209(b)(1)(B), especially given that EPA's
evaluation of California's request for a waiver to enforce GHG
standards would relate to the limits of California's authority to
regulate GHG emissions from new motor vehicles, instead of particular
regulatory provisions that California was seeking to enforce. There,
EPA construed section 209(b)(1)(B) as calling for either a
consideration of environmental problems with causes that were specific
to California, or in the alternative, environmental effects specific to
California in comparison to the rest of the nation. EPA further
explained that this interpretation called for its own judgment because
it necessitated a determination of whether elevated concentrations of
GHGs lie within the confines of state air pollution programs as covered
by section 209(b)(1)(B). It would also be consistent with the GHG
waiver denial for EPA to exercise its own judgment in making the
requisite findings called for under section 209(b)(1)(B) in the instant
action.
EPA is, thus, soliciting comments on the appropriate burden and
standard of proof for withdrawing a previously issued waiver, taking
into consideration that different approaches may apply to the various
criteria of Section 209(b) and that EPA is not merely responsible for
evaluating a request by California and comments thereon but is
proposing withdrawal of a grant of preemption.
3. Discussion: Analysis Under Section 209(b)(1)(B), (C)
(a) Proposed Finding Under Section 209(b)(1)(B): California Does Not
Need its Standards To Meet Compelling and Extraordinary Conditions
(1) Introduction
Section 209(b)(1)(B) provides that no waiver of section 209(a)
preemption will be granted if the Administrator finds that California
does not need ``such standards to meet compelling and extraordinary
conditions.'' EPA is proposing to withdraw the grant of waiver of
preemption for CARB's GHG and ZEV standards for 2021 MY through 2025 MY
based on a finding that California does not need these standards to
meet compelling and extraordinary conditions, as contemplated under
section 209(b)(1)(B). As shown below, EPA is proposing to determine
that the ACC program GHG and ZEV standards are standards that would not
meaningfully address global air pollution problems posed by GHG
emissions in contrast to local or regional air pollution problem with
causal ties to conditions in California. As also shown below, EPA is
proposing to find that while potential conditions related to global
climate change in California could be substantial, they are not
sufficiently different from the potential conditions in the nation as a
whole to justify separate state standards under CAA section
209(b)(1)(B). Moreover, the GHG and ZEV standards would not have a
meaningful impact on the potential conditions related to global climate
change. EPA is thus proposing to find that California does not need GHG
standards to meet compelling and extraordinary conditions, as
contemplated under section 209(b)(1)(B). Additionally, California does
not need the ZEV requirements to meet ``compelling and extraordinary''
conditions in California given that it allows manufacturers to generate
credits in section 177 states as a means to satisfy those
manufacturers' obligations to comply with the mandate that a certain
percentage of their vehicles sold in California be ZEV (or be credited
as such from sales in section 177 States). This finding is premised on
agency review of the interpretation and application of section
209(b)(1)(B) in the January 2013 ACC waiver request. Thus, EPA is
required to articulate a reasoned basis for the change in its position.
FCC v. Fox Television Stations, Inc., 556 U.S. 502, 515 (2009).
(2) Historical Waiver Practices Under Section 209(b)(1)(B)
Up until the 2008 GHG waiver denial, EPA had interpreted section
209(b)(1)(B) as requiring a consideration of California's need for a
separate motor vehicle program designed to address local or regional
air pollution problems and not whether the specific standard that is
the subject of the waiver request is necessary to meet such conditions
(73 FR 12156; March 6, 2008). Additionally, California typically would
seek a waiver of particular aspects of its new motor vehicle program up
until the ACC program waiver request. In the 2008 GHG waiver denial,
which was a waiver request for only GHG emissions standards, however,
EPA determined that its prior interpretation of section 209(b)(1)(B)
was not appropriate for GHG standards because such standards are
designed to address global air pollution problems in contrast to local
or regional air pollution problems specific to and caused by conditions
specific to California (73 FR 12156-60).
In the 2008 denial, EPA further explained that its previous reviews
of California's waiver request under section 209(b)(1)(B) had usually
been cursory and undisputed, as the fundamental factors leading to
California's air pollution problems--geography, local climate
conditions (like thermal inversions), significance of the motor vehicle
population--had not changed over time and over different local and
regional air pollutants. These fundamental factors applied similarly
for all of California's air pollution problems that are local or
regional in nature.
In the 2008 denial, EPA noted that atmospheric concentrations of
GHG are substantially uniform across the globe, based on their long
atmospheric life and the resulting mixing in the atmosphere. Therefore,
with regard to atmospheric GHG concentrations and their environmental
effects, the California-specific causal factors that EPA had considered
when reviewing previous waiver applications under section
[[Page 43246]]
209(b)(1)(B)--the geography and climate of California, and the large
motor vehicle population in California, which were considered the
fundamental causes of the air pollution in California--do not have the
same relevance to the question at hand. The atmospheric concentration
of GHG in California is not affected by the geography and climate of
California. The long duration of these gases in the atmosphere means
they are well-mixed throughout the global atmosphere, such that their
concentrations over California and the U.S. are substantially the same
as the global average. The number of motor vehicles in California,
while still a notable percentage of the national total and still a
notable source of GHG emissions in the State, is not a significant
percentage of the global vehicle fleet and bears no closer relation to
the levels of GHG in the atmosphere over California than any other
comparable source or group of sources of GHG anywhere in the world.
Emissions of greenhouse gases from California cars do not generally
remain confined within California's local environment but instead
become one part of the global pool of GHG emissions, with this global
pool of emissions leading to a relatively homogenous concentration of
GHG over the globe. Thus, the emissions of motor vehicles in California
do not affect California's air pollution problem in any way different
from emissions from vehicles and other pollution sources all around the
world. Similarly, the emissions from California's cars do not only
affect the atmosphere in California but in fact become one part of the
global pool of GHG emissions that affect the atmosphere globally and
are distributed throughout the world, resulting in basically a uniform
global atmospheric concentration.
EPA then applied the reasoning laid out above to the GHG standards
at issue in the 2008 waiver denial. Having limited the meaning of this
provision to situations where the air pollution problem was local or
regional in nature, EPA found that California's GHG standards did not
meet this criterion.
In the 2008 waiver denial, EPA also applied an alternative
interpretation where EPA would consider effects of the global air
pollution problem in California in comparison to the effects on the
rest of the country and again addressed the GHG standards separately
from the rest of California's motor vehicle program. Under this
alternative interpretation, EPA considered whether impacts of global
climate change in California were sufficiently different from impacts
on the rest of the country such that California could be considered to
need its GHG standards to meet compelling and extraordinary conditions.
EPA determined that the waiver should be denied under this alternative
interpretation as well.
(3) Interpretation of Section 209(b)(1)(B)
Under section 209(b)(1)(B), EPA cannot grant a waiver request if
EPA finds that California ``does not need such State standards to meet
compelling and extraordinary conditions.'' The statute does not define
the phrase ``compelling and extraordinary conditions,'' and EPA
considers the text of section 209(b)(1)(B), and in particular the
meaning and scope of this phrase, to be ambiguous.
First, the provision is ambiguous with respect to the scope of
EPA's analysis. It is unclear whether EPA is meant to evaluate the
particular standard or standards at issue in the waiver request or all
of California's standards in the aggregate. Section 209(b)(1)(B)
references the need for ``such State standards.'' Section 209(b)(1)(B)
does not specifically employ terms that could only be construed as
calling for a standard-by-standard analysis or each individual
standard. For example, it does not contain phrases such as ``each State
standard'' or ``the State standard.'' Nor does the use of the plural
term ``standards'' definitively answer the question of the proper scope
of EPA's analysis, given that the variation in the use of singular and
plural form of a word in the same law \576\ is often insignificant and
a given waiver request typically encompasses multiple ``standards.''
Thus, while it is clear that ``such State standards'' refers at least
to all of the standards that are the subject of the particular waiver
request before the Administrator, that phrase can reasonably be
considered as referring either to the standards in the entire
California program, the program for similar vehicles, or the particular
standards for which California is requesting a waiver under the pending
request.
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\576\ ``Words [in Acts of Congress] importing the singular
include and apply to several persons.'' 1 U.S.C. 1.
---------------------------------------------------------------------------
There are reasons to doubt that the phrase ``such State standards''
in section 209(b)(1)(B) is intended to refer to all standards in
California's program, including all the standards it has historically
adopted and obtained waivers for previously. The waiver under 209(b) is
a waiver of, and is logically dependent on and presupposes the
existence of, the prohibition under 209(a), which forbids (absent a
waiver) any state to ``adopt or attempt to enforce any standard
[singular] relating to the control of emissions from new motor vehicles
or new motor vehicle engines subject to this part.'' (Emphasis added.)
States are forbidden from adopting a standard, singular; California
requests waivers seriatim by submitting a standard or package of
standards to EPA; follows that EPA considers those submissions as it
receives them, individually, not in the aggregate with all standards
for which it has previously granted waivers.
Furthermore, reading the phrase ``such State standards'' as
requiring EPA always and only to consider California's entire program
in the aggregate limits the application of the criterion. Once EPA had
determined that California needed its very first set of submitted
standards to meet extraordinary and compelling conditions, it is
unclear that EPA would ever have the discretion to determine that
California did not need any subsequent standards for which it sought a
successive waiver--unless EPA is authorized to consider a later
submission separate from its earlier finding. Moreover, up until the
ACC program waiver request, California's waiver request involved
individual standards or particular aspects of California's new motor
vehicle program.\577\ As previously explained, however, the ACC waiver
program could be considered as the entire new motor vehicle program for
California given that it is a single coordinated program comprising a
suite of standards that California intended to be a cohesive program
for addressing emissions from a wide variety of vehicles, specifically,
new passenger cars, light duty trucks, medium passenger vehicles, and
certain heavy duty vehicles.
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\577\ The 2009 and Subsequent MY GHG standards for New Motor
Vehicles, 73 FR 12156 (March 6, 2008); The On-Board diagnostics
system requirements (OBD II) 81 FR 78144 (November 7, 2016), The ZEV
program regulations 76 FR 61096 (October 3, 2011), 71 FR 78190
(December 26, 2006)) and the Heavy-duty Truck idling requirements 77
FR 9239 (February 16, 2012).
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The application of the phrase ``such State standards'' to state
standards in the aggregate may have appeared more reasonable in the
context of, for example, the 1984 PM waiver request, as opposed to the
present context, as it relates to an application for a waiver with
regard to GHG and ZEV standards.\578\ In the 1984 request, the agency
confronted the need for a reading of ``such State standards'' in
section 209(b)(1)(B) that would be consistent with the State's ``in the
aggregate, at least as protective'' finding under the root text of
209(b)(1),''
[[Page 43247]]
because Congress explicitly allows California to adopt some standards
that are less stringent than Federal standards. EPA explained that the
phrase ``in the aggregate'' was specifically aimed at allowing
California to adopt less stringent CO standards at the same time when
California wanted to adopt NOX standards that were tighter
than the Federal NOX standards, to address ozone
problems.\579\ California reasoned that a relaxed CO standard would
facilitate the technological feasibility of the desired more stringent
NOX standards. When evaluating that waiver request, EPA
noted that it would be inconsistent for Congress to allow EPA to look
at each air pollutant separately for purposes of determining compelling
and extraordinary conditions for that air pollution problem, while at
the same time allowing California to adopt standards for a particular
air pollutant that was less stringent than the Federal standards for
that same pollutant. EPA proposes to determine that the balance of
textual, contextual, purposive, and legislative-history evidence at
minimum supports the conclusion that it is ambiguous whether the
Administrator may consider whether California needs the particular
standard or standards under review to meet compelling and extraordinary
conditions.
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\578\ 49 FR 18887 (May 3, 1984).
\579\ The intent of the 1977 amendment was to accommodate
California's particular concern with NOX, which the State
regards as a more serious threat to public health and welfare than
carbon monoxide. California was eager to establish oxides of
nitrogen standards considerably higher than applicable Federal
standards, but technological developments posed the possibility that
emission control devices could not be constructed to meet both the
high California oxides of nitrogen standard and the high Federal
carbon monoxide standard. MEMA I, 627 F.2d at 1110 n.32.
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Second, the statute does not speak with precision as to the
substance of EPA's analysis. ``Compelling and extraordinary
conditions,'' as the history of the 2008 waiver denial and 2009
reconsideration and grant narrated above demonstrates, is a phrase
susceptible of multiple interpretations, particularly in the context of
GHG emissions and associated, global environmental problems. EPA
believes that the term ``extraordinary'' is most reasonably read to
refer to circumstances that are specific to California and the term is
reasonably interpreted to refer to circumstances that are primarily
responsible for causing the air pollution problems that the standards
are designed to address, such as thermal inversions resulting from
California's local geography and wind patterns. (Conditions that are
similar on a global scale are not ``extraordinary,'' especially where
``extraordinary'' conditions are a predicate for a local deviation from
national standards.) Support for this interpretation can be found in
pertinent legislative history that refers to California's ``peculiar
local conditions'' and ``unique problems.'' S. Rep. No. 403, 90th Cong.
1st Sess., at 32 (1967). This legislative history also indicates that
California is to demonstrate ``compelling and extraordinary
circumstances sufficiently different from the nation as a whole to
justify standards on automobile emissions which may, from time to time,
need to be more stringent than national standards.'' Id. (Emphasis
added.) EPA believes this is evidence of Congressional intent that
separate standards in California are justified only by a showing of
particular circumstances in California that are different from
circumstances in the nation as a whole to justify separate standards in
California. EPA thus, reads the term ``extraordinary'' in this
statutory context as referring primarily to factors that tend to
produce higher levels of pollution: Geographical and climatic
conditions (like thermal inversions) that in combination with large
numbers and high concentrations of automobiles, create serious air
pollution problems in California (73 FR 12156, 12159-60).
Additional relevant legislative history supports a decision to
examine California's need for GHG standards ``in the context of global
climate change.'' See, e.g., 73 FR 12161. Specifically, this
legislative history demonstrates that Congress did not justify this
provision based on the need for California to enact separate standards
to address pollution problems of a more national or global nature.
Rather relevant legislative history ``indicates that Congress allowed
waivers of preemption for California motor vehicle standards based on
the particular effects of local conditions in California on the air
pollution problems in California.'' Congress discussed ``the unique
problems faced in California as a result of its climate and
topography.'' H.R. Rep. No. 728, 90th Cong. 1st Sess., at 21 (1967).
See also Statement of Cong. Holifield (CA), 113 Cong. Rec. 30942-43
(1967). Congress also noted the large effect of local vehicle pollution
on such local problems. See, e.g., Statement of Cong. Bell (CA) 113
Cong. Rec. 30946. In particular, Congress focused on California's smog
problem, which is especially affected by local conditions and local
pollution. See Statement of Cong. Smith (CA) 113 Cong. Rec. 30940-41
(1967); Statement of Cong. Holifield (CA), id., at 30942. See also,
MEMA I, 627 F.2d at 1109 (noting the discussion of California's
``peculiar local conditions'' in the legislative history).
The EPA thus, believes that it is appropriate, in evaluating
California's need for a waiver under section 209(b)(1)(B), to examine
California's program as a whole to the extent that the problem is
designed to address local or regional air pollution problems,
particularly in light of the fact that the State's aggregate analysis
under the root text of 209(1)(b)(1) is designed in part to permit
California to adopt standards for some criteria pollutants that are
less stringent than the Federal standards as a trade-off for standards
for other criteria pollutants, where the levels of criteria pollutants
addressed by California's standards are caused by conditions specific
to California, and contribute primarily to environmental effects that
are specific to California. EPA could also review California's GHG
standards themselves even where, as in the instant ACC waiver package,
the waiver request is for a single coordinated package of requirements
and amendments that include standards designed to address global
environmental effects caused by a globally distributed a globally
distributed pollutant, such as GHGs as well as requirements for a
compliance mechanism that could likely address both criteria pollutants
and GHG emissions, which in this instance are the ZEV requirements. The
EPA further notes that in keeping with its pre-2008 interpretation, its
review of California's ACC program request under section 209(b)(1)(B)
was cursory and undisputed, given that view that the fundamental
factors leading to California's air pollution problems--geography,
local climate conditions (like thermal inversions), significance of the
motor vehicle population--had not changed over time and over different
local and regional air pollutants. Additionally, as previously
explained, up until the ACC program waiver, California had relied on
the ZEV requirements as a compliance mechanism for criteria pollutants
as compared to the ACC program, where CARB for the first time relied on
it for GHG emissions reductions. Here, as previously explained, CARB
specifically noted that that there was no criteria emissions benefit
for its ZEV standards in terms of vehicle emissions because its LEV III
criteria pollutant fleet standard was responsible for those emission
[[Page 43248]]
reductions.\580\ The EPA therefore, believes a review of the grant of
the ACC program waiver and the agency reasoning underpinning the grant
are appropriate at this time. As previously explained, an agency ``must
consider . . . the wisdom of its policy on a continuing basis.''
Chevron, 467 U.S. at 863-64. This is true when, as is the case here,
review is undertaken ``in response to . . . a change in
administration.'' Brand X Internet Services, 545 U.S. at 981. In sum,
EPA proposed to conclude that the pre-2008 interpretation of section
209(b)(1)(B) would allow for review of California's GHG standards in
themselves, given that the ACC program is a single coordinated motor
vehicle emission control program that is designed to address both
traditional, local environmental causes and effects (including via
criteria pollutants) and global air pollution problems. Thus, EPA is
proposing that at this time its review has led it to propose to
determine that California does not need its own GHG and ZEV standards,
to the extent California intended the ZEV requirements to serve as a
compliance option for GHG standards, because GHG emissions do not
present conditions specific to California--in the terms of the
legislative history discussed above, GHG emissions do not present
``unique problems'' in California as compared to the whole country. As
shown below, GHG emissions could be associated with potential adverse
effects in California, but EPA does not believe that these would be
sufficiently different from potential adverse effects in either coastal
States like Florida, Massachusetts, and Louisiana or the nation as a
whole, to constitute a ``need'' for separate state standards under
section 209(b)(1)(B). EPA is of the view, therefore, that GHG emissions
would not be associated with ``peculiar local conditions'' in
California that Congress alluded to in promulgating section
209(b)(1)(B). In the alternative, EPA is proposing to determine that
California does not need the ACC program GHG and ZEV standards to
address compelling and extraordinary conditions, because they will not
meaningfully address global air pollution problems like the kinds
associated with GHG emissions and would not have any meaningful impact
on potential adverse effects related to global climate change in
California. As shown below, based on this reading of section
209(b)(1)(B), the agency is proposing to find that GHG emissions
impacts cannot be considered ``compelling and extraordinary
conditions'' such that California ``need[s]'' separate GHG and ZEV
standards for new motor vehicles for MY 2021 through MY 2025.
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\580\ CARB ACC waiver request at EPA-HQ-OAR-2012-0562-0004.
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(4) Proposed Determination That California Does Not Need Its ACC
Program Regulations To Meet Compelling and Extraordinary Conditions
EPA is proposing to withdraw the waiver of preemption of the GHG
and ZEV standards on two alternative grounds: (1) California ``does not
need'' the standards ``to meet compelling and extraordinary
conditions,'' under section 209(b)(1)(B); (2) even if California does
have compelling and extraordinary conditions in the context of global
climate change, California does not ``need'' these standards under
section 209(b)(1)(B) because they will not meaningfully address global
air pollution problems of the sort associated with GHG emissions. EPA
is interpreting section 209(b)(1)(B) to permit the Agency to
specifically review California's need for GHG standards--i.e.,
standards for a globally distributed air pollutant which is of concern
for its connection to global environmental effects--as opposed to
reviewing California's need for its motor vehicle program as a whole
(including both its GHG-targeting and non-GHG-targeting components), in
part because the rest of California's ACC program consists of standards
that are designed to address local or regional air pollution problems.
Accordingly, EPA is proposing to find that GHG emitted by California
motor vehicles become part of the global pool of GHG emissions that
affect concentrations of GHGs on a uniform basis throughout the world.
The local climate and topography in California have no significant
impact on the long-term atmospheric concentrations of greenhouse gases
in California. More importantly, California's standards for GHG
emissions (both the GHG and ZEV standards) would not materially affect
global concentrations of GHG levels. Accordingly, even if EPA were to
assume California had compelling and extraordinary conditions that were
uniquely impacted by high levels of GHGs, California's GHG and ZEV
standards would not meaningfully address those concerns and conditions.
In the alternative, EPA believes that even if California has
compelling and extraordinary conditions, California does not need these
standards under section 209(b)(1)(B) because they will not meaningfully
address global air pollution problems like the kinds associated with
GHG emissions. EPA believes that the number of motor vehicles in
California bears no significant relationship to the levels of GHGs in
California. This is because GHGs emissions from cars located in
California are relatively small part of the global pool of GHG
emissions. Thus, GHG emissions of motor vehicles in California do not
affect California's conditions related to global climate change in any
way different from emissions from vehicles and other pollution sources
all around the world. Similarly, the GHG emissions from cars in
California become one part of the global pool of GHG emissions that
affect the atmosphere globally and are distributed throughout the
world, resulting in basically a uniform global atmospheric
concentration. This is in contrast to the kinds of motor vehicle
emissions normally associated with ozone levels, such as VOCs and
NOX, and the local climate and topography that in the past
have led to the conclusion that California has the need for state
standards to meet compelling and extraordinary conditions. Therefore,
California does not need its GHG and ZEV standards to ``meet'' the
conditions: a problem does not cause you to ``need'' something that
would not meaningfully address the problem.
In justifying the need for its GHG standards, CARB extensively
described climatic conditions in California. ``Record-setting fires,
deadly heat waves, destructive storm surges, loss of winter snowpack--
California has experienced all of these in the past decade and will
experience more in the coming decades. California's climate--much of
what makes the state so unique and prosperous--is already changing, and
those changes will only accelerate and intensify in the future. Extreme
weather will be increasingly common as a result of climate change. In
California, extreme events such as floods, heat waves, droughts and
severe storms will increase in frequency and intensity. Many of these
extreme events have the potential to dramatically affect human health
and well-being, critical infrastructure and natural systems'' (78 FR
2129). CARB also provided a summary report on the third assessment from
the California Climate Change Center (2012), which described dramatic
sea level rises and increases in temperatures (78 FR 2129). These are
similar, if not identical to, the justifications that EPA addressed and
rejected in the 2008 GHG waiver denial. Notably, in the 2008 denial EPA
observed that some of these events--increased temperatures, heat waves,
sea level rises, wildfires--were also
[[Page 43249]]
occurring across the U.S. (73 FR 12163, 12165-68). CARB further noted
that the South Coast and San Joaquin Valley Air Basins continue to
experience some of the worst air quality in the nation and continue to
be in non-attainment with the PM and ozone national ambient air quality
standards (78 FR 2128-9). The EPA has typically considered
nonattainment air quality in California as falling within the purview
of ``compelling and extraordinary conditions.'' California however, did
not indicate how the GHG standards would help California in the
attainment efforts for these areas. Moreover, as previously noted, the
ACC ZEV requirements are intended in part as a GHG compliance mechanism
for MYs 2018 through 2025.
EPA believes that any effects of global climate change would apply
to the nation, indeed the world, in ways similar to the conditions
noted in California.\581\ For instance, California's claims that it is
uniquely susceptible to certain risks because it is a coastal State
does not differentiate California from other coastal States such as
Massachusetts, Florida, and Louisiana.\582\ Any effects of global
climate change (e.g. water supply issues, increases in wildfires,
effects on agriculture) could certainly affect California. But those
effects would also affect other parts of the United States. Many parts
of the United States, especially western States, may have issues
related to drinking water (e.g., increased salinity) and wildfires, and
effects on agriculture; these occurrences are by no means limited to
California. These are issues of national, indeed international,
concern. Further, these are some of the effects that EPA considered as
bases for the section 202(a) GHG endangerment finding, which was a
prerequisite for the Federal GHG standards for motor vehicles.\583\ EPA
has also previously opined that evaluation of whether California's
standards are necessary to meet compelling and extraordinary conditions
is not contingent on or directly related to EPA's cause or contribution
finding for the section 202(a) GHG endangerment finding, which was a
completely different determination than whether California needs its
mobile source pollution program to meet compelling and extraordinary
conditions in California (79 FR 46256, 46262: August 7, 2014).
See also Utility Air Regulatory Group v. EPA, 134 S. Ct. 2427
(2014) (partially reversing the GHG ``Tailoring'' Rule on grounds that
the section 202(a) endangerment finding for GHG emissions from motor
vehicles did not compel regulation of all sources of GHG emissions
under the Prevention of Significant Deterioration and Title V permit
programs).
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\581\ IPCC. 2015. Intergovernmental Panel on Climate Change
(IPCC) Observed Climate Change Impacts Database, available at http://sedac.ipcc-data.org/ddc/observed_ar5/index.html.
\582\ They are also similar to previous claims marshalled by
Massachusetts over a decade ago. Massachusetts v. EPA, 549 U.S. 497,
522-24 (2007). According to Massachusetts, at the time, global sea
levels rose between 10 and 20 centimeters over the 20th century as a
result of global warming and had begun to swallow its coastal areas.
\583\ 74 FR 66496, 66517-19, 66533 (December 15, 2009).
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As also previously indicated, California is to demonstrate
``compelling and extraordinary circumstances sufficiently different
from the nation as a whole to justify standards on automobile emissions
which may, from time to time, need to be more stringent than national
standards.'' S. Rep. No. 403, 90th Cong. 1st Sess., at 32 (1967).
(Emphasis added.) EPA does not believe that these conditions, mentioned
above, merit separate GHG standards in California. Rather, these
effects, as previously explained, are widely shared and do not present
``unique problems'' with respect to the nature or degree of the effect
California would experience. In sum, EPA finds that any effects of
global climate change in California are not ``extraordinary'' as
compared to the rest of the country. EPA is thus, proposing to find
that CARB has not demonstrated that these negative impacts it
attributes to global climate change are ``extraordinary'' to merit
separate GHG and ZEV standards.
The ACC program waiver contained references to the potential GHG
benefits or attributes of CARB's GHG and ZEV standards program (78 FR
2114, 2130-2131). CARB repeatedly touted the benefits of both the ZEV
and GHG standards as it related to the GHG emissions reductions in
California. In one instance, CARB stated that the ACC program
regulations for the 2017 through 2025 MYs were designed to respond to
California's identified goals of reducing GHG emissions to 80% below
1990 levels by 2050 and in the near term to reduce GHG levels to 1990
levels by 2020 (78 FR 2114, 2130-31). CARB's Resolution 12-11, (January
26, 2012).\584\ In another instance, CARB noted that the ZEV regulation
amendments were intended to focus primarily on zero emission drive--
that is BEVs, FCVs, and PHEVs in order to move advanced, low GHG
vehicles from demonstration phase to commercialization (78 FR 2130).
CARB further noted that ``ZEVs have ultra-low GHG emission levels that
are far lower than non-ZEV technology'' (78 FR 2139). In yet another
instance, CARB relied on conclusions from the September 2010 Joint
Technical Assessment Report (TAR), which was developed by EPA, NHTSA,
and CARB, on effects of the ZEV requirements on GHG standards. This
report concluded that ``electric drive vehicles including hybrid(s) . .
. battery electric vehicles . . . plug-in hybrid(s) . . . and hydrogen
fuel cell vehicles . . . can dramatically reduce petroleum consumption
and GHG emissions compared to conventional technologies. The future
rate of penetration of these technologies into the vehicle fleet is not
only related to future GHG and corporate average fuel economy (CAFE)
standards, but also to future reductions in HEV/PHEV/EV battery costs,
[and] the overall performance and consumer demand for the advanced
technologies'' (78 FR 2142). But nowhere does CARB either show or
purport to show a causal connection between its GHG standards and
reducing any adverse effects of climate change in California. EPA does
not believe that identifying methods for reducing GHG emissions and
then noting the potential dangers of climate change are sufficient to
demonstrate that California needs its standards to meet compelling and
extraordinary circumstances as contemplated under section 209(b)(1)(B).
California also does not need the ZEV requirements to meet ``compelling
and extraordinary'' conditions in California given that the FCV
``travel provision'' allow manufacturers to generate credits in section
177 states as a means to satisfy those manufacturers' obligations to
comply with the mandate that a certain percentage of their vehicles
sold in California be ZEV (or be credited as such from sales in section
177 States). In sum, California did not quantify and demonstrate
climate benefits in California that may result from the GHG standards.
EPA therefore, proposes to find that it is not appropriate to waive
preemption for California to enforce its GHGs standards. EPA continues
to believe that any problems related to atmospheric concentrations of
GHG are global in nature and any reductions achieved as a result of
California's separate GHG standards will not accrue meaningful benefits
to California. Thus, GHG emissions raise issues that do not bear the
same causal link between local emissions and local benefits to health
and welfare in California as do local or
[[Page 43250]]
regional air pollution problems (such as criteria pollutants). EPA
further finds that atmospheric concentrations of GHGs are not the kind
of local or regional air pollution problem Congress intended to
identify in the second criterion of section 209(b)(1)(B). These
findings also apply to the ZEV provisions given that CARB, in a change
from prior practice, and as previously explained, cited its ZEV
standards as a means to reduce GHG emissions instead of criteria
pollutants for MY 2021 through MY 2025. Thus, EPA is proposing to
withdraw the waiver of preemption for the GHG and ZEV requirements for
MYs 2021 through 2025 because California does not need these provisions
to meet compelling and extraordinary conditions.
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\584\ Available in the docket for the January 2013 waiver
decision, Docket No. EPA-HQ-OAR-2012-0562.
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(b) Proposed Finding Under Section 209(b)(1)(C): California's Standards
Are Not Consistent With Section 202(a)
(1) Introduction
Under section 209(b)(1)(C), EPA cannot grant a waiver request if
EPA finds that California's ``standards and accompanying enforcement
procedures are not consistent with section 202(a) of the Act.'' \585\
The EPA is also proposing to find that both ZEV and GHG standards for
new MY 2021 through 2025 are not consistent with Section 202(a) of the
Clean Air Act, as contemplated by section 209(b)(1)(C). Specifically,
EPA is proposing to determine that there is inadequate lead time to
permit the development of technology necessary to meet those
requirements, giving appropriate consideration to cost of compliance
within the lead time provided in the 2013 waiver. This finding reflects
the assessments in today's proposal on the technological feasibility of
the Federal GHG standards for MY 2021 through 2025.\586\
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\585\ Section 202(a) provides that an emission standard shall
take effect after such period of time as the Administrator finds
necessary to permit development and application of the requisite
technology, giving appropriate consideration to compliance costs.
\586\ Although this section generally discusses the
technological feasibility of CARB's GHG standards for MY 2021-2025,
we believe the current Federal standards are sufficiently similar to
(if not less stringent than) the current California standards to
serve as an appropriate proxy for considering the technological
feasibility of the current California standards. Compare Cal. Code
Regs. Tit. 13, Sec. 1961.3 with 40 CFR 89.1818-12.
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As previously explained, the MY 2021 through 2025 Federal and CARB
GHG standards were the results of collaboration between CARB and EPA.
The respective standards are equally stringent and have the same lead
time. (78 FR 2135) CARB's GHG standards also rely on emerging
technology that are similar to the ones for the Federal GHG standards,
including ZEV-type technologies (78 FR 2136-7). Most importantly,
CARB's feasibility finding, and EPA's decision to grant the waiver,
noted a ``deemed to comply'' provision that allowed manufacturers of
advanced technology vehicles to comply with CARB GHG standards through
compliance with the Federal GHG standards as well as utilize the EPA
accounting provisions for these vehicles (78 FR 2136). Revisions to the
Federal GHG standards, in light of the technology development and
availability assessment for those standards, would therefore, implicate
the technological feasibility findings that served as the underpinning
for EPA's grant of CARB's GHG standards waiver.
Further, because EPA believes that the ZEV and GHG standards are
intertwined as shown in some of the program complexities discussed
above, EPA believes that this provides further justification for
withdrawing the waiver of preemption for both standards, under section
209(b)(1)(C). For example, in the waiver request CARB stated that the
``ZEV regulation must be considered in conjunction with the proposed
LEV III amendments. Vehicles produced as a result of the ZEV regulation
are part of a manufacturer's light-duty fleet and are therefore
included when calculating fleet averages for compliance with the LEV
III GHG amendments.'' CARB's Initial Statement of Reasons at 62-63,
which is in the docket for the waiver decision.\587\ CARB also noted
``[b]ecause the ZEVs have ultra-low GHG emission levels that are far
lower than non-ZEV technology, they are a critical component of
automakers' LEV III GHG standard compliance strategies.'' Id. CARB
further explained that ``the ultra-low GHG ZEV technology is a major
component of compliance with the LEV III GHG fleet standards for the
overall light duty fleet.'' Id.
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\587\ Docket ID No. EPA-HQ-OAR-2012-0562.
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Similarly, with regard to CARB's ZEV standards, EPA is now
cognizant that certain ZEV sales requirements mandated by CARB are
technologically infeasible within the provided lead-time for purposes
of CAA 209(b)(1)(C). Specifically, today's proposal also raises
questions as to CARB's technological projections for ZEV-type
technologies, which are a compliance option for both the ZEV mandate
and GHG standards. CARB's ZEV regulations also include the travel
provision, which allowed manufacturers of ZEVs sold in California to
count toward compliance in section 177 States, but which was limited to
FCVs starting with MY 2018. The manufacturer credit system was premised
on ever increasing numbers of ZEVs that would be sold in each of the
section 177 States. Challenges for ZEVs in these States include lack of
market penetration, consumer demand levels that are lower than
projections at the time of the grant of the ACC waiver in 2013, and
lack of or slow development of necessary infrastructure. This in turn
means that manufacturers in section 177 States are unlikely to meet
CARB's projections that their sales in those States will generate the
necessary credits as CARB projected to support the ZEV sales
requirement mandate in the lead time provided.
Today's proposal indicates challenges for the adoption of all ZEV
technologies such as lack of required infrastructure and a lower level
of consumer demand for FCVs in both California and individual section
177 States, and EPA believes it is now unlikely that manufacturers will
be able to generate requisite credits in section 177 States in the lead
time provided. In short, EPA is now of the view that CARB's projections
and assumptions that underlay its ACC program and its 2013 waiver
application were overly ambitious and likely will not be realized
within the provided lead time. Thus, EPA is also proposing to find that
CARB's ZEV standards for MY 2021 through 2025 are not technologically
feasible and therefore, are not consistent with section 209(b)(1)(C).
(2) Historical Waiver Practices Under Section 209(b)(1)(C)
In prior waivers of Federal preemption, under section 209(b), EPA
has explained that California's standards are not consistent with
section 202(a) if there is inadequate lead time to permit the
development of technology necessary to meet those requirements, given
appropriate consideration to the cost of compliance within that time.
California's accompanying enforcement procedures would also be
inconsistent with section 202(a) if the Federal and California test
procedures were inconsistent.
EPA also relies on two key decisions handed down by the U.S. Court
of Appeals for the D.C. Circuit for guidance regarding the lead time
requirements of section 202(a): Natural Resources Defense Council v.
EPA (NRDC), 655 F.2d 318 (D.C. Cir. 1981) (upholding EPA's lead time
projections for emerging technologies as reasonable), and International
Harvester v. Ruckelshaus (International Harvester), 478 F.2d 615 (D.C.
Cir. 1979)
[[Page 43251]]
(reversing EPA's refusal to extend compliance deadline where technology
was presently available on grounds that hardship would likely result if
it were a wrongful denial of compliance deadline extension.). EPA
further notes the court's conclusion in NRDC.
Given this time frame [a 1980 decision on 1985 model year
standards], we feel that there is substantial room for deference to
the EPA's expertise in projecting the likely course of development.
The essential question in this case is the pace of that development,
and absent a revolution in the study of industry, defense of such a
projection can never possess the inescapable logic of a mathematical
deduction. We think that the EPA will have demonstrated the
reasonableness of its basis for projection if it answers any
theoretical objections to the [projected control technology],
identifies the major steps necessary in refinement of the
technology, and offers plausible reasons for believing that each of
those steps can be completed in the time available.
NRDC, 655 F.2d at 331 (emphasis added).
With regard to appropriate lead time in the section 209(b) waiver
context, EPA considers whether adequate control technology is presently
available or already in existence and in use at the time CARB adopts
standards for which it seeks a waiver. If adequate control technology
is not presently available, EPA determines whether CARB has provided
adequate lead time for the development and application of necessary
technology prior to the effective date of applicable standards. As
explained above, considerations under this criterion include adequacy
of lead time, technological feasibility and costs as well as test
procedures consistency. Notably, there are similar considerations for
Federal standards setting under section 202(a). For example, in
adopting the MY 2017 through 2025 GHG standards, section 202(a)
required and EPA found in October 2012 that the MY 2017 through 2025
GHG standards are feasible in the lead time provided and that
technology costs were reasonable (77 FR 62671-73; October 15, 2012).
Even where technology is available, EPA can consider hardships that
could result to manufacturers from either a short lead time or not
granting a compliance extension. International Harvester, 478 F.2d at
626.
Where CARB relies on emerging technology (i.e., where technology is
unavailable at time of grant of waiver), EPA will review CARB's
prediction of future technological developments and determine whether
CARB has provided reasoned explanations for the time period selected.
Any projections by CARB would have to be subject to ``restraints of
reasonableness and does not open the door to crystal ball inquiry.''
NRDC v. EPA, 655 F.2d at 329. ``The Clean Air Act requires the EPA to
look to the future in setting standards, but the agency must also
provide a reasoned explanation of its basis for believing that its
projection is reliable.'' Id.
EPA will make a consistency finding where CARB provides for longer
lead time in instances in of emerging or unavailable technology at the
time CARB adopts its standards. In sum, EPA's review of CARB's
technological feasibility involves both evaluations of predictions for
future technological advances and presently available technology. EPA
also believes that a longer lead time would allow CARB ``modify its
standards if the actual future course of technology diverges from
expectation.'' Id.
As previously mentioned above, costs considerations are also tied
to the compliance timing for a particular standard and are thus,
relevant for purposes of the consistency determination called for by
the third waiver criterion under section 209(b)(1)(C). In evaluating
compliance costs for CARB standards, EPA considers the actual cost of
compliance in the time provided by applicable California regulations.
Compliance costs ``relates to the timing of standards and procedures.''
MEMA I, 627 F.2d at 1118 (emphasis in original). Where technology is
not presently available, EPA also considers the period necessary to
permit development and application of the requisite technology.
In terms of waiver practice, EPA has previously taken the position
that technology control costs must be excessive for EPA to find that
California's standards are inconsistent with section 202(a).\588\ (See
MEMA I, 627 F.2d at 1118 ``Congress wanted to avoid undue economic
disruption in the automotive manufacturing industry and also sought to
avoid doubling or tripling of the cost of motor vehicles to
purchasers.'') Consistent with this practice, in the ACC program
waiver, EPA contended that control costs for the ZEV standards were
``not excessive.'' ``Under EPA's traditional analysis of cost in the
waiver context, because [an incremental cost of $12,900 in MY 2020]
does not represent a `doubling or tripling' of the vehicle cost, such
cost is not excessive nor does it represent an infeasible standard''
(78 FR 2142). EPA now believes that its prior view that a doubling or
tripling of vehicle cost constitutes an excessive cost or represents an
infeasible standard was incorrect. Such a bright line (and extreme)
test is inappropriate. Instead, the agency should holistically consider
whether technology control costs are infeasible by considering the
availability of the technology, the reasonableness of costs associated
with adopting it within the required lead time, and consumer
acceptance.
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\588\ 74 FR 32744, 32774 (July 8, 2009); 47 FR 7306, 7309
(February 18, 1982); 46 FR 26371, 26373 (May 12, 1981), 43 FR 25735
(June 14, 1978).
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(3) Interpretation of Section 209(b)(1)(C)
EPA cannot grant a waiver, under section 209(b)(1)(C), if
California's ``standards and accompanying enforcement procedures are
not consistent with section [202(a)].'' Relevant legislative history
from the 1967 CAA amendments indicates that EPA is to grant a waiver
unless it finds that there is ``inadequate time to permit the
development of the necessary technology given the cost of compliance
within that time period.'' This is similar to language found in section
202(a), which is discussed below. Additional relevant legislative
history indicates that EPA is not to grant a waiver where ``California
standards are not consistent with the intent of section 202(a) of the
Act, including economic practicability and technological feasibility.''
The cross-reference to section 202(a) is an indication of the role EPA
plays in reviewing California's waiver request under section
209(b)(1)(C).
With regard to section 202(a), standards promulgated under section
202(a)(1) ``shall take effect after such period as the Administrator
finds necessary to permit the development and application of the
requisite technology, giving appropriate consideration to the cost of
compliance within such period.'' Section 202(a). Pertinent legislative
history from the 1970 and 1977 amendments indicate that EPA ``was
expected to press for the development and application of improved
technology rather than be limited by that which exists today.'' S. Rep.
No. 1196, 91st Cong., 2d Sess. 24 (1970); H.R. Rep. No. 294, 95th
Cong., 1st Sess. 273 (1977). In sum, EPA believes that section 202(a)
allows for a projection of lead time as to future technological
developments.
(4) Proposed Finding That California's Standards Are Not Consistent
With Section 202(a)
As previously mentioned, today's proposal now cast significant
doubts on EPA's predictions for future and timely availability of
emerging technologies for compliance with Federal GHG standards for MY
2021-2025. It highlights in
[[Page 43252]]
particular challenges for ZEV-type technologies, such as BEVs and
PHEVs, that California relied on as compliance options for the ZEV
mandate requirements and GHG standards. As also previously mentioned
CARB's GHG standards were developed jointly by EPA and CARB with the
result that CARB's GHG standards share a similar structure with EPA GHG
standards in terms of both lead time and stringency. For instance, the
methodology and underlying data used by CARB to assess technologies and
costs were similar to and, in many instances, the same as those used by
EPA to assess the Federal GHG standards (78 FR 2136). Also, the
technological feasibility analyses underlying CARB's standards were
based on several emerging technologies similar to control technologies
considered by EPA and NHTSA in evaluating Federal GHG standards for MYs
2021-2025. Id. Additionally, CARB's feasibility finding was premised on
a finding of reduced compliance costs and flexibility because of the
deemed to comply provisions, which allowed for compliance with Federal
GHG standards in lieu of California's standards.\589\ In sum, EPA's
findings of technological feasibility for the GHG and ZEV standards
were premised on the availability of both current and emerging
technologies in the lead-time CARB provided for new MY 2021-2025 motor
vehicles (78 FR 2138-2139, 2143). These kinds of control technologies
would include ZEV-type technologies, which are used as a compliance
option for CARB's GHG standards because their GHG emissions levels are
significantly lower than non-ZEV technology. As the NPRM discusses,
certain control technology would likely not be fully developed in time
for deployment in MY 2021 through 2025 motor vehicles.
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\589\ On May 7, 2018, California issued a notice seeking
comments on ``potential alternatives to a potential clarification''
of this provision for MY vehicles that would be affected by
revisions to the Federal GHG standards. The notice is available at:
https://www.arb.ca.gov/msprog/levprog/leviii/leviii_dtc_notice05072018.pdf. EPA proposes to determine that the
``deemed to comply'' provision in California's program does not
prevent EPA from finding that California's ZEV and GHG standards are
inconsistent with section 202(a), for two reasons. First, the
``deemed to comply'' provision is in flux; the state process that
may ``clarify[]'' it renders it unclear whether California will
continue to deem a program that may be revised as proposed in this
joint rulemaking to comply with its own program. Second, EPA
proposes to determine that a ``deemed to comply'' provision is
logically incompatible with a preemption waiver analysis. The entire
premise of 209(a) preemption and 209(b)(1) waivers is that
California's standards will differ from the Federal standards. If
``deemed to comply'' provisions in California's program prevented
EPA from determining that California's standards is inconsistent
with section 202(a), then those provisions' presence would prevent
EPA's analysis under this prong (209(b)(1)(C) from denying it a
waiver no matter the content of those standards.
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With regard to the ZEV standards, CARB's waiver request contained
projections and explanations for ZEVs that included projected sales of
FCVs in both California and section 177 States. Specifically, CARB's
projections, at the time, were that nearly every vehicle manufacturer
would be introducing BEVs and PHEVs within the next one to three years,
and five manufacturers would be commercially introducing FCVs by
2015.\590\ As explained above, the ZEV regulations contains the travel
provision that allow manufacturers to comply with the ZEV sales mandate
by generating credits for vehicle sales in section 177 States and vice
versa. At the grant of the ACC program waiver, EPA found CARB's
assumptions and projections appeared reasonable within the provided
lead time for MYs 2021 through 2025 (78 FR 2141-42).
---------------------------------------------------------------------------
\590\ CARB waiver request at 27-28, which can be found in Docket
ID No. EPA-HQ-OAR-2012-0562.
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Technological challenges may serve as basis for either a future
compliance deadline extension or modifications to the federal GHG
standards that would be consistent with today's proposal and would then
raise questions as to CARB's predictions and projections of
technological feasibility and costs. At this time, however, CARB has
shown no indication that it intends to either extend the compliance
deadline for or modify its standards by providing additional compliance
flexibilities. EPA believes it is reasonable, therefore, to consider
any expected hardship that would be posed to manufacturers if EPA does
not withdraw CARB's waiver. NRDC, 655 F.2d at 330. An early withdrawal
of the waiver would also provide a measure of certainty to all
manufacturers. `` `[T]the base hour for commencement of production is
relatively distant, and until that time the probable effect of a
relaxation of the standard would be to mitigate the consequences of any
strictness in the final rule, not to create new hardships.'' \591\
Further, from past experience with waivers for challenging standards,
EPA is aware that CARB has subsequently either modified compliance
deadlines or provided additional compliance flexibilities for such
standards.\592\ EPA also notes that even at the time of the waiver
request, CARB was already cognizant of challenges presented by both ZEV
and GHG standards. CARB noted that although several individual
technologies offered substantial CO2 reduction potential
many of the technologies had only limited deployment in new vehicle
models (78 FR 2136). CARB also extended the travel provisions beyond
2017 for FCVs due to insufficient refueling infrastructure in section
177 States as compared to other kinds of ZEV technologies (78 FR 2120;
CARB Resolution 12-11 at 15). EPA is, therefore, acting in anticipation
of the challenges presented by its GHG and ZEV standards. As previously
explained, a late modification or extension of time carries attendant
hardships for technologically advanced manufacturers who might have
made major investment commitments (International Harvester, 478 F.2d
615). EPA believes that today's proposal, when finalized, would be
sufficiently ahead of the compliance deadline for MY 2021 through 2025
and thus, manufacturers would not incur any hardships. Indeed, the
expectation is that the proposed withdrawal would provide notice to
manufacturers of the intended compliance deadline modifications for MYs
2021 through 2025.
---------------------------------------------------------------------------
\591\ Id. The ``hardships'' referred to are hardships that would
be created for manufacturers able to comply with the more stringent
standards being relaxed late in the process.
\592\ For example, CARB has made multiple revisions to its on-
Board diagnostics (OBD) (81 FR 78144 (November 7, 2016)) and the ZEV
program regulations (76 FR 61096 (October 3, 2011)).
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Finally, the agency is acting on the likelihood of increased
compliance costs as shown in today's proposal. (These are costs that
will likely be passed on to consumers in most instances.). As
previously explained, because compliance technologies that California
relied on for both ZEV and GHG standards are similar to the
technologies considered by EPA in evaluating the feasibility of
standards for MYs 2021 through 2025, economies of scale were expected
to drive down both manufacturing and technology costs. The EPA,
however, now expects that manufacturers may no longer be willing to
commit to investments for a limited market as compared to the broader
national market, which was contemplated by the federal and California
GHG standards.
Today's proposal also confirms slower pace of development of ZEV
technology and differences in projected manufacturing costs in states
that have adopted these standards under section 177 as well as lower
consumer demands for FCVs. The EPA also now expects that the pace of
technological developments as it relates to infrastructure for FCVs
will slow down.
[[Page 43253]]
The EPA is thus, proposing to find that CARB's ZEV standards for MYs
2021 through 2025 are technologically infeasible in the lead time
provided and therefore, that CARB's ZEV standards are not consistent
with section 202(a).
As previously mentioned EPA is proposing to withdraw the grant of
waiver for both standards on grounds that they are not consistent with
section 202(a). In light of all the foregoing, the agency finds that is
necessary and reasonable to reconsider the grant of waiver for CARB's
GHG and ZEV standards. EPA requests comments on all aspects of this
proposal, especially specific costs for the ZEV requirements as it
relates to MYs 2021 through 2025.
4. States Cannot Adopt California's GHG Standards for NAAQS
Nonattainment Purposes Under Section 177
As explained above, CAA section 177 provides that other States,
under certain circumstances and with certain conditions, may ``adopt
and enforce'' standards that are ``identical to the California
standards for which a waiver has been granted for [a given] model
year.'' 42 U.S.C. 7507. The EPA proposes to determine that this section
does not apply to CARB's GHG standards.
In this regard, the EPA notes that the section is titled ``New
motor vehicle emission standards in nonattainment areas'' and that its
application is limited to ``any State which has [state implementation]
plan provisions approved under this part''--i.e., under CAA title I
part D, which governs ``Plan requirements for nonattainment areas.''
Areas are only designated nonattainment with respect to criteria
pollutants for which EPA has issued a NAAQS, and nonattainment SIPs are
intended to assure that those areas attain the NAAQS. It would be
illogical to require approved nonattainment SIP provisions as a
predicate for allowing States to adopt California's standards if states
could use this authority to adopt California standards that addressed
environmental problems other than nonattainment of criteria pollutant
standards. Furthermore, the placement of section 177 in title I part D,
rather than title II (the location of the California waiver provision)
would make no sense if it functioned as a waiver applicable to all
subjects, as does the California-focused provision under section
209(b), rather than as a provision specifically targeting criteria
pollutants and nonattainment areas, as does the rest of title I part D.
Therefore, the text, context, and purpose of section 177 suggest,
and the EPA proposes to conclude, that it is limited to providing
States the ability, under certain circumstances and with certain
conditions, to adopt and enforce standards identical to those for which
California has obtained a waiver--provided that those standards are
designed to control criteria pollutants to address NAAQS nonattainment.
EPA solicits comment on how and when this new interpretation should be
adopted and implemented, if finalized (e.g., whether EPA should adopt
it as of the effective date of a final rule, or as of a later date,
such as model year 2021 or calendar year 2020, in order to allow
additional time for planning and transition).
5. Severability and Judicial Review
EPA considers its proposed decision on the appropriate federal
standards for light duty greenhouse gas vehicles for MY 2021-2025 to be
severable from its decision on withdrawing the ACC waiver, particularly
with respect to the requirements of CAA 209(b)(1)(B). Our proposed
interpretation of CAA 209(b)(1)(B), and our evaluation of the ACC
waiver under that provision, does not depend on our decision to
finalize, and a court's decision to uphold, the light duty vehicles
standards being proposed today under CAA 202(a). EPA solicits comment
on the severability of these actions, particularly with respect to the
other criteria of CAA 209(b).
Section 307(b)(1) of the CAA provides in which Federal courts of
appeal petitions of review of final actions by EPA must be filed. This
section provides, in part, that petitions for review must be filed in
the Court of Appeals for the District of Columbia Circuit if (i) the
Agency action consists of ``nationally applicable regulations
promulgated, or final action taken, by the Administrator,'' or (ii)
such action is locally or regionally applicable, but ``such action is
based on a determination of nationwide scope or effect and if in taking
such action the Administrator finds and publishes that such action is
based on such a determination.'' Separate and apart from whether a
court finds this action to be locally or regionally applicable, the
Administrator is proposing to find that any final action resulting from
this rulemaking is based on a determination of ``nationwide scope or
effect'' within the meaning of section 307(b)(1).
This decision, when finalized, will affect persons in California
and those manufacturers and/or owners/operators of new motor vehicles
nationwide who must comply with California's new motor vehicle
requirements. For instance, manufacturers may generate credits in
section 177 states as a means to satisfy those manufacturers'
obligations to comply with the mandate that a certain percentage of
their vehicles sold in California be ZEV (or be credited as such from
sales in section 177 States). In addition, because other states have
adopted aspects of California's ACC program this decision would also
affect those states and those persons in such states, which are located
in multiple EPA regions and federal circuits. For these reasons, EPA
determines and finds for purposes of section 307(b)(1) that any final
withdrawal action would be of national applicability, and also that
such action would be based on a determination of nationwide scope or
effect for purposes of section 307(b)(1). Pursuant to section
307(b)(1), judicial review of this final action may be sought only in
the United States Court of Appeals for the District of Columbia
Circuit. Judicial review of any final action may not be obtained in
subsequent enforcement proceedings, pursuant to section 307(b)(2).
VII. Impacts of the Proposed CAFE and CO[bdi2] Standards
A. Overview
New CAFE and CO2 standards will have a range of impacts.
EPCA/EISA and NEPA require DOT to consider such impacts when making
decisions about new CAFE standards, and the CAA requires EPA to do so
when making decisions about new emissions standards. Like past
rulemakings, today's announcement is supported by the analysis of many
potential impacts of new standards. Today's announcement proposes new
standards through model year 2026, explicitly estimates manufacturers'
responses to standards through model year 2029, and considers impacts,
throughout those vehicles' useful lives. The agencies do not know today
what would actually come to pass decades from now under the proposed
standards or under any of alternatives under consideration. The
analysis is thus properly interpreted not as a forecast, but rather as
an assessment--reflecting the best judgments regarding many different
factors--of impacts that could occur.\593\ As discussed below, the
analysis was conducted to explore the sensitivity of this assessment to
a variety of potential changes in key analytical inputs (e.g., fuel
prices).
---------------------------------------------------------------------------
\593\ ``Prediction is very difficult, especially if it's about
the future.'' Attributed to Niels Bohr, Nobel laureate in Physics.
---------------------------------------------------------------------------
This section summarizes various impacts of the preferred
alternative (i.e., the proposed standards) defined above in Section
III. The no-action alternative
[[Page 43254]]
defined in Section IV provides the baseline relative to which all
impacts are shown. Because the proposed standards (and other standards
considered below), being of a ``deregulatory'' nature, are less
stringent than the no-action alternative, all impacts are directionally
opposite impacts reported in recent CAFE and CO2
rulemakings. For example, while past rulemakings reported positive
values for fuel consumption avoided under new standards, today's
proposal reports negative values, as fuel consumption will be somewhat
greater under today's proposed standards than under standards defining
the baseline no-action alternative. Reported negative values for
avoided fuel consumption could also be properly interpreted as simply
``additional fuel consumption.'' Similarly, reported negative values
for costs could be properly interpreted as ``avoided costs'' or
``benefits,'' and reported negative values for benefits could be
properly interpreted as ``foregone benefits'' or ``costs.'' However,
today's notice retains reporting conventions consistent with past
rulemakings, anticipating that, compared to other options, doing so
will facilitate review by most stakeholders.
Today's analysis presents results for individual model years in two
different ways. The first way is similar to past rulemakings and shows
how manufacturers could respond in each model year under the proposed
standards and each alternative covering MYs 2021/2-2026. The second,
expanding on the information provided in past rulemakings, evaluates
incremental impacts of new standards proposed for each model year, in
turn. In past rulemaking analyses, NHTSA modeled year-by-year impacts
under the aggregation of standards applied in all model years, and EPA
modeled manufacturers' hypothetical compliance with a single model
years' standards in that model year. Especially considering multiyear
planning effects, neither approach provides a clear basis to attribute
impacts to specific standards first introduced in each of a series of
model years. For example, of the technology manufacturers applied in MY
2016, some would have been applied even under the MY 2014 standards,
and some were likely applied to position manufacturers toward
compliance with (including credit banking to be used toward) MY 2018
standards. Therefore, of the impacts attributable to the model year
2016 fleet, only a portion can be properly attributed to the MY 2016
standards, and the impacts of the MY 2016 standards involve fleets
leading up and extending well beyond MY 2016. Considering this, the
proposed standards were examined on an incremental basis, modeling each
new model year's standards over the entire span of included model
years, using those results as a baseline relative to which to measure
impacts attributable to the next model year's standards. For example,
incremental costs attributable to the standards proposed today for MY
2023 are calculated as follows:
COSTProposed,MY 2023 = (COSTProposed\through\MY 2023-COSTNo-
Action\through\MY 2023--(COSTProposed\through\MY 2022-COSTNo-
Action\through\MY 2022)
Where:
COSTProposed,MY 2023: Incremental technology cost during MYs 2017-
2030 and attributable to the standards proposed for MY 2023.
COSTProposed\through\MY 2022: Technology cost for MYs 2017-2030
under standards proposed through MY 2022.
COSTProposed\through\MY 2023: Technology cost for MYs 2017-2030
under standards proposed through MY 2023.
COSTNo-Action\through\MY 2022: Technology cost for MYs 2017-2030
under no-action alternative standards through MY 2022.
COSTNo-Action\through\MY 2023: Technology cost for MYs 2017-2030
under no-action alternative standards through MY 2023.
Additionally, today's analysis includes impacts on new vehicle
sales volumes and the use (i.e., survival) of vehicles of all model
years, such that standards introduced in a model year produce impacts
attributable to vehicles having been in operation for some time. For
example, as modeled here, standards for MY 2021 will impact the prices
of new vehicles starting in MY 2017, and those price impacts will
affect the survival of all vehicles still in operation in calendar
years 2017 and beyond (e.g., MY 2021 standards impact the operation of
MY 2007 vehicles in calendar year 2027). Therefore, while past
rulemaking analyses focused largely on impacts over the useful lives of
the explicitly modeled fleets, much of today's analysis considers all
model years through 2029, as operated, throughout those vehicles'
useful lives. For some impacts, such as on technology penetration
rates, average vehicle prices, and average vehicle ownership costs, the
focus was on the useful life of the MY 2030 fleet, as the simulation of
manufacturers' technology application and credit use (when included in
the analysis) continues to evolve after model year 2026, stabilizing by
model year 2030.
Effects were evaluated from four perspectives: The social
perspective, the manufacturer perspective, the private perspective, and
the physical perspective. The social perspective focuses on economic
benefits and costs, setting aside economic transfers such as fuel taxes
but including economic externalities such as the social cost of
CO2 emissions. The manufacturer perspective focuses on
average requirements and levels of performance (i.e., average fuel
economy level and CO2 emission rates), compliance costs, and
degrees of technology application. The private perspective focuses on
costs of vehicle purchase and ownership, including outlays for fuel
(and fuel taxes). The physical perspective focuses on national-scale
highway travel, fuel consumption, highway fatalities, and greenhouse
gas and criteria pollutant emissions.
This analysis does not explicitly identify ``co-benefits'' from its
proposed action to change fuel economy standards, as such a concept
would include all benefits other than cost savings to vehicle buyers.
Instead, it distinguishes between private benefits--which include
economic impacts on vehicle manufacturers, buyers of new cars and light
trucks, and owners (or users) of used cars and light trucks--and
external benefits, which represent indirect benefits (or costs) to the
remainder of the U.S. economy that stem from the proposal's effects on
the behavior of vehicle manufacturers, buyers, and users. In this
accounting framework, changes in fuel use and safety impacts resulting
from the proposal's effects on the number of used vehicles in use
represent an important component of its private benefits and costs,
despite the fact that previous analyses have failed to recognize these
effects. The agency's presentation of private costs and benefits from
its proposed action clearly distinguishes between those that would be
experienced by owners and users of cars and light trucks produced
during previous model years and those that would be experienced by
buyers and users of cars and light trucks produced during the model
years it would affect. Moreover, it clearly separates these into
benefits related to fuel consumption and those related to safety
consequences of vehicle use. This is more meaningful and informative
than simply identifying all impacts other than changes in fuel savings
to buyers of new vehicles as ``co-benefits.''
For the social perspective, the following effects for model years
through 2029 as operated throughout those vehicles' useful lives are
summarized:
Technology Costs: Incremental cost, as expected to be
paid by vehicle purchasers, of
[[Page 43255]]
fuel-saving technology beyond that added under the no-action
alternative.
Welfare Loss: Loss of value to vehicle owners resulting
from incremental increases in the numbers of strong and plug-in
hybrid electric vehicles (strong HEVs or SHEVs, and PHEVs) and/or
battery electric vehicles (BEVs), beyond increases occurring under
the no-action alternative. The loss of value is a function of the
factors that lead to different valuations for conventional and
electric versions of similar-size vehicles (e.g., differences in:
travel range, recharging time versus refueling time, performance,
and comfort).
Pre-tax Fuel Savings: Incremental savings, beyond those
achieved under the no-action alternative, in outlays for fuel
purchases, setting aside fuel taxes.
Mobility Benefit: Value of incremental travel, beyond
that occurring under the no-action alternative.
Refueling Benefit: Value of incremental reduction,
compared to the no-action alternative, of time spent refueling
vehicles.
Non-Rebound Fatality Costs: Social value of additional
fatalities, beyond those occurring under the no-action alternative,
setting aside any additional travel attributable to the rebound
effect.
Rebound Fatality Costs: Social value of additional
fatalities attributable to the rebound effect, beyond those
occurring under the no-action alternative.
Benefits Offsetting Rebound Fatality Costs: Assumed
further value, offsetting rebound fatality costs, of additional
travel attributed to the rebound effect.
Non-Rebound Non-Fatal Crash Costs: Social value of
additional crash-related losses (other than fatalities), beyond
those occurring under the no-action alternative, setting aside any
additional travel attributable to the rebound effect.
Rebound Non-Fatal Crash Costs: Social value of
additional crash-related losses (other than fatalities) attributable
to the rebound effect, beyond those occurring under the no-action
alternative.
Benefits Offsetting Rebound Non-Fatal Crash Costs:
Assumed further value, offsetting rebound non-fatal crash costs, of
additional travel attributed to the rebound effect.
Additional Congestion and Noise (Costs): Value of
additional congestion and noise resulting from incremental travel,
beyond that occurring under the no-action alternative.
Energy Security Benefit: Value of avoided economic
exposure to petroleum price ``shocks,'' the avoided exposure
resulting from incremental reduction of fuel consumption beyond that
occurring under the no-action alternative.
Avoided CO2 Damages (Benefits): Social value of
incremental reduction of CO2 emissions, compared to
emissions occurring under the no-action alternative.
Other Avoided Pollutant Damages (Benefits): Social
value of incremental reduction of criteria pollutant emissions,
compared to emissions occurring under the no-action alternative.
Total Costs: Sum of incremental technology costs,
welfare loss, fatality costs, non-fatal crash costs, and additional
congestion and noise costs.
Total Benefits: Sum of pretax fuel savings, mobility
benefits, refueling benefits, Benefits Offsetting Rebound Fatality
Costs, Benefits Offsetting Rebound Non-Fatal Crash Costs, energy
security benefits, and benefits from reducing emissions of
CO2, other GHGs, and criteria pollutants.
Net Benefits: Total benefits minus total costs.
Retrievable Electrificaiton Costs: The portion of HEV,
PHEV, and BEV technology costs which can be passed onto consumers,
using the willingness to pay analysis described above.
Electrification Tax Credits: Estimates of the portion
of HEV, PHEV, and BEV technology costs which are covered by federal
or state tax incentives.
Irretreivable Electrification Costs: The portion of
HEV, PHEV, and BEV technology costs OEM's must either absorb as a
profit loss, or cross-subsidize with the prices of internal
combustion engine (ICE) vehicles.
Total Electrification Costs: Total incremental
technology costs attributable to HEV, PHEV, or BEV vehicles.
For the manufacturer perspective, the following effects for the
aggregation of model years 2017-2029 are summarized:
Average Required Fuel Economy: Average of
manufacturers' CAFE requirements for indicated fleet(s) and model
year(s).
Percent Change in Stringency from Baseline: Percentage
difference between averages of fuel economy requirements under no-
action and indicated alternatives.
Average Required Fuel Economy: Industry-wide average of
fuel economy levels achieved by indicated fleet(s) in indicated
model year(s).
Percent Change in Stringency from Baseline: Percentage
difference between averages of fuel economy levels achieved under
no-action and indicated alternatives.
Total Technology Costs ($b): Cost of fuel-saving
technology beyond that applied under no-action alternative.
Total Civil Penalties ($b): Cost of civil penalties
(for the CAFE program) beyond those levied under no-action
alternative.
Total Regulatory Costs ($b): Sum of technology costs
and civil penalties.
Sales Change (millions): Change in number of vehicles
produced for sale in U.S., relative to the number estimated to be
produced under the no-action alternative.
Revenue Change ($b): Change in total revenues from
vehicle sales, relative to total revenues occurring under the no-
action alternative.
Curb Weight Reduction: Reduction of average curb
weight, relative to MY 2016.
Technology Penetration Rates: MY 2030 average
technology penetration rate for indicated ten technologies (three
engine technologies, advanced transmissions, and six degrees of
electrification).
Average Required CO2: Average of manufacturers'
CO2 requirements for indicated fleet(s) and model
year(s).
Percent Change in Stringency from Baseline: Percentage
difference between averages of CO2 requirements under no-
action and indicated alternatives.
Average Achieved CO2: Average of manufacturers'
CO2 emission rates for indicated fleet(s) and model
year(s).
For the private perspective, the following effects for the MY 2030
fleet are summarized:
Average Price Increase: Average increase in vehicle
price, relative to the average occurring under the no-action
alternative.
Welfare Loss (Costs): Average loss of value to vehicle
owners resulting from incremental increases in the numbers of strong
HEVs, PHEVs) and/or BEVs, beyond increases occurring under the no-
action alternative. The loss of value is a function of the factors
that lead to different valuations for conventional and electric
versions of similar-size vehicles (e.g., differences in: Travel
range, recharging time versus refueling time, performance, and
comfort).
Ownership Costs: Average increase in some other costs
of vehicle ownership (taxes, fees, financing), beyond increase
occurring under no-action alternative.
Fuel Savings: Average of fuel outlays (including taxes)
avoided over a vehicles' expected useful lives, compared to outlays
occurring under no-action alternative.
Mobility Benefit: Average incremental value of
additional travel over average vehicles' useful lives, compared to
travel occurring under no-action alternative.
Refueling Benefit: Average incremental value of avoided
time spent refueling over average vehicles' useful lives, compared
to time spent refueling under no-action alternative.
Total Costs: Sum of average price increase, welfare
loss, and ownership costs.
Total Benefits: Sum of fuel savings, mobility benefit,
and refueling benefit.
Net Benefits: Total benefits minus total costs.
For the physical perspective, the following effects for model years
through 2029 as operated throughout those vehicles' useful lives are
summarized:
Greenhouse gases include carbon dioxide
(CO2), methane (CH4), and nitrous oxide
(N2O), and values are reported separately for vehicles
(tailpipe) and upstream processes (combining fuel production,
distribution, and delivery) and shown as reductions relative to the
no-action alternative.
Criteria pollutants include carbon monoxide (CO),
volatile organic compounds (VOC), nitrogen oxides (NOX),
sulfur dioxide (SO2) and particulate matter (PM), and
values are shown as reductions relative to the no-action
alternative.
Fuel consumption aggregates all fuels, with
electricity, hydrogen, and compressed natural gas (CNG) included on
a gasoline-equivalent-gallon (GEG) basis, and values are shown as
reductions relative to the no-action alternative.
VMT, with rebound (billion miles): Increase in highway
travel (as vehicle miles traveled), relative to the no-action
alternative, and including the rebound effect.
[[Page 43256]]
VMT, without rebound (billion miles): Increase in
highway travel (as vehicle miles traveled), relative to the no-
action alternative, and excluding the rebound effect.
Fatalities, with rebound: Increase in highway
fatalities, relative to the no-action alternative, and including the
rebound effect.
Fatalities, without rebound: Increase in highway
fatalities, relative to the no-action alternative, and excluding the
rebound effect.
Fuel Consumption, with rebound (billion gallons):
Reduction of fuel consumption, relative to the no-action
alternative, and including the rebound effect.
Fuel Consumption, without rebound (billion gallons):
Reduction of fuel consumption, relative to the no-action
alternative, and excluding the rebound effect.
Below, this section tabulates results for each of these four
perspectives and does so separately for the proposed CAFE and
CO2 standards. More detailed results are presented in the
Preliminary Regulatory Impact Analysis (PRIA) accompanying today's
notice, and additional and more detailed analysis of environmental
impacts for CAFE regulatory alternatives is provided in the
corresponding Draft Environmental Impact Statement (DEIS). Underlying
CAFE model output files are available (along with input files, model,
source code, and documentation) on NHTSA's website.\594\ Summarizing
and tabulating results for presentation here involved considerable
``off model'' calculations (e.g., to combine results for selected model
years and calendar years, and to combine various components of social
and private costs and benefits); tools Volpe Center staff used to
perform these calculations are also available on NHTSA's website.\595\
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\594\ Compliance and Effects Modeling System, National Highway
Traffic Safety Administration, https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system (last
visited June 25, 2018).
\595\ These tools, available at the same location, are scripts
executed using R, a free software environment for statistical
computing. R is available through https://www.r-project.org/.
---------------------------------------------------------------------------
While the National Environmental Policy Act (NEPA) requires NHTSA
to prepare an EIS documenting estimating environmental impacts of the
regulatory alternatives under consideration in CAFE rulemakings, NEPA
does not require EPA to do so for EPA rulemakings. CO2
standards for each regulatory alternative being harmonized as practical
with corresponding CAFE standards, environmental impacts of GHG
standards should be directionally identical and similar in magnitude to
those of CAFE standards. Nevertheless, in this section, following the
series of tables below, today's announcement provides a more detailed
analysis of estimated impacts of the proposed CAFE and CO2
standards. Results presented herein for the CAFE standards differ
slightly from those presented in the DEIS; while, as discussed above,
EPCA/EISA requires that the Secretary determine the maximum feasible
levels of CAFE standards in manner that, as presented here, sets aside
the potential use of CAFE credits or application of alternative fuels
toward compliance with new standards, NEPA does not impose such
constraints on analysis presented in corresponding DEISs, and the DEIS
presents results of an ``unconstrained'' analysis that considers
manufacturers' potential application of alternative fuels and use of
CAFE credits.
In terms of all estimated impacts, including estimated costs and
benefits, results of today's analysis are different for CAFE and
CO2 standards. Differences arise because, even when the
mathematical functions defining fuel economy and CO2 targets
are ``harmonized,'' surrounding regulatory provisions may not be. For
example, while both CAFE and CO2 standards allow credits to
be transferred between fleets and traded between manufacturers, EPCA/
EISA places explicit and specific limits on the use of such credits,
such as by requiring that each domestic passenger car fleet meet a
minimum CAFE standard (as discussed above). The CAA provides no
specific direction regarding CO2 standards, and while EPA
has adopted many regulatory provisions harmonized with specific EPCA/
EISA provisions (e.g., separate standards for passenger cars and light
trucks), EPA has not adopted all such provisions. For example, EPA has
not adopted the EPCA/EISA provisions limiting transfers between
regulated fleet or requiring separate compliance by domestic and
imported passenger car fleets. Such differences introduce differences
between impacts estimated under CAFE standards and under CO2
standards. Also, as mentioned above, Congress has required that new
CAFE standards be considered in a manner that sets aside the potential
use of CAFE credits and the potential additional application of
alternative fuel vehicles (such as electric vehicles) during the model
years under consideration. Congress has provided no corresponding
direction regarding the analysis of potential CO2 standards,
and today's analysis does consider these potential responses to
CO2 standards.
As mentioned above, analysis was conducted to examine the
sensitivity of results to changes in key inputs. Following the detailed
consideration of potential environmental impacts, this section
concludes with a tabular summary of results of this sensitivity
analysis.
B. Impacts of Proposed Standards on Requirements, Performance, and
Costs to Manufacturers in Specific Model Years
As mentioned above, impacts are presented from two different
perspectives for today's proposal. From either perspective, overall
impacts are the same. The first perspective, following the approach
taken by NHTSA in past CAFE rulemakings, examines impacts of the
overall proposal--i.e., the entire series of year-by-year standards--on
each model year. This perspective is especially relevant to
understanding how the overall proposal may impact manufacturers in
terms of year-by-year compliance, technology pathways, and costs. The
second, presented below in Section VII.C, provides a clearer
characterization of the incremental impacts attributable to standards
introduced in each successive model year.
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C. Incremental Impacts of Standards Proposed for Each Model Year
As mentioned above, impacts are presented from two different
perspectives for today's proposal. From either perspective, overall
impacts are the same. The first perspective, taken above in VI.A,
examines impacts of the overall proposal -- i.e., the entire series of
year-by-year standards -- on each model year. The second perspective,
presented here, provides a clearer characterization of the incremental
impacts attributable to standards introduced in each successive model
year. For example, the standards proposed for MY 2023 are likely to
impact manufacturers' application of
[[Page 43309]]
technology in model years prior to MY 2023, as well as model years
after MY 2023. By conducting analysis that successively introduces
standards for each MY, in turn, isolates the incremental impacts
attributable to new standards introduced in each MY, considering the
entire span of MYs (1977-2029) included in the underlying modeling,
throughout those vehicles' useful lives. Tables appearing below
summarize results as aggregated across these model and calendar years.
Underlying model output files \596\ report physical impacts and
specific monetized costs and benefits attributable to each model year
in each calendar (thus providing information needed to, for example,
differentiate between impacts attributable to the MY 1977-2016 and MY
2017-2029 cohorts). The PRIA presents costs and benefits for individual
model years (with MY's 1977-2016 in a single bucket) for the preferred
alternative.
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\596\ Available at https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system.
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1. What are the Social Costs and Benefits of the Proposed Standards?
(a) CAFE Standards
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(b) CO2 Standards
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2. What are the private costs and benefits of the proposed standards,
relative to the no-action alternative?
(a) What are the impacts on producers of new vehicles?
(b) CAFE Standards
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(c) CO2 Standards
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(d) What are the impacts on buyers of new vehicles?
(e) CAFE Standards
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(f) CO2 Standards
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D. What are the Energy and Environmental Impacts?
Today's proposal directly involves the fuel economy and average
CO2 emissions of light-duty vehicles, and the proposal is
expected to most directly and significantly impact national fuel
consumption and CO2 emissions. Fuel economy and
CO2 emissions are so closely related that it is expected the
impacts on national fuel consumption and national CO2
emissions will track in virtual lockstep with each other.
Today's proposal does not directly involve pollutants such as
carbon monoxide, smog-forming pollutants (nitrogen oxides and unburned
hydrocarbons), final particles, or ``air toxics'' (e.g., formaldehyde,
acetaldehyde, benzene). While today's proposal is expected to
indirectly impact such emissions (by reducing travel demand and
accelerating fleet turnover to newer and cleaner vehicles on one hand
while, on the other, increasing activity at refineries and in the fuel
distribution system), it is expected that these impacts will be much
smaller than impacts on fuel use and CO2 emissions because
standards
[[Page 43325]]
for these other pollutants are independent of those for CO2
emissions.
Following decades of successful regulation of criteria pollutants
and air toxics, modern vehicles are already vastly cleaner than in the
past, and it is expected that new vehicles will continue to improve.
For example, the following chart shows trends in new vehicles' emission
rates for volatile organic compounds (VOCs) and nitrogen oxides
(NOX) -- the two motor vehicle criteria pollutants that
contribute to the formation of smog.
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Because new vehicles are so much cleaner than older models, it is
expected that under any of the alternatives considered here for fuel
economy and CO2 standards, emissions of smog-forming
pollutants would continue to decline nearly identically over the next
two decades. The following chart shows estimated total fuel
consumption, CO2 emissions, and smog-forming emissions under
the baseline and proposed standards (CAFE standards -- trends for
CO2 standards would be very similar), using units that allow
the three to be shown together:
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While the differences in fuel use and CO2 emissions
trends under the baseline and proposed standards are clear, the
corresponding difference in smog-forming emissions trends is too small
to discern. For these three measures, the following table shows
percentage differences between the amounts shown above:
[[Page 43327]]
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As indicated, for most of the coming two decades, it is estimated
that, even as fuel consumption and CO2 emissions would
increase under the proposed standards (compared to fuel consumption and
CO2 emissions under the baseline standards), smog-forming
pollution would actually decrease. During the two decades shown above,
it is estimated that the proposed standards would increase aggregate
fuel consumption and CO2 emissions by about four percent but
would decrease aggregate smog-forming pollution by about 0.1% (because
impacts of the reduced travel and accelerated fleet turnover would
outweigh those of increased refining and fuel distribution).
As the analysis affirms, while fuel economy and CO2
emissions are two sides (or, arguably, the same side) of the same coin,
fuel economy and CO2 are only incidentally related to
pollutants such as smog, and any positive or negative impacts of
today's notice on these other air quality problems would most likely be
far too small to observe.
The remainder of this section summarizes the impacts on fuel
consumption and emissions for both the proposed CAFE standards and the
proposed CO2 standards.
1. Energy and Warming Impacts
Section V discusses, among other things, the need of the Nation to
conserve energy, providing context for the estimated impacts on
national-scale fuel consumption summarized below. Corresponding to
these changes in fuel consumption, the agencies estimate that today's
proposal will impact CO2 emissions. CO2 is one of
several greenhouse gases that absorb infrared radiation, thereby
trapping heat and making the planet warmer. The most important
greenhouse gases directly emitted by human activities include carbon
dioxide (CO2), methane (CH4), nitrous oxide
(N2O), and several fluorine-containing halogenated
substances. Although CO2, CH4, and N2O
occur naturally in the atmosphere, human activities have changed their
atmospheric concentrations. From the pre-industrial era (i.e., ending
about 1750) to 2016, concentrations of these greenhouse gases have
increased globally by 44, 163, and 22%, respectively.\597\ The Draft
Environmental Impact Analysis (DEIS) accompanying today's notice
discusses potential impacts of greenhouse gases at greater length, and
also summaries analysis quantifying some of these impacts (e.g.,
average temperatures) for each of the considered regulatory
alternatives.
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\597\ Impacts and U.S. emissions of GHGs are discussed at
greater length in EPA's 2018 Inventory of U.S. Greenhouse Gas
Emissions and Sinks (EPA 430-R-18-003) (Apr. 12, 2018), available at
https://www.epa.gov/sites/production/files/2018-01/documents/2018_complete_report.pdf.
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(a) CAFE Standards
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(b) CO2 Standards
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2. How would the proposal impact emissions of criteria and toxic
pollutants?
Although this proposal focuses on standards for fuel economy and
CO2, it will also have an impact on criteria and air toxic
pollutant emissions, although as discussed above, it is expected that
incremental impacts on criteria and air toxic pollutant emissions would
be too small to observe under any of the regulatory alternatives under
consideration. Nevertheless, the following sections detail the criteria
pollutant and air toxic inventory impacts of this proposal; the
methodology used to calculate those impacts; the health and
environmental effects associated with the criteria and toxic air
pollutants that are being impacted by this proposal; the potential
impact of this proposal on concentrations of criteria and air toxic
pollutants in the ambient air; and other
[[Page 43330]]
unquantified health and environmental effects.
Today's analysis reflects the combined result of several underlying
impacts, all discussed above. CAFE and CO2 standards are
estimated to impacts new vehicle prices, fuel economy levels, and
CO2 emission rates. These changes are estimated to impact
the size and composition of the new vehicle fleet and to impact the
retention of older vehicles (i.e., vehicle survival and scrappage) that
tend to have higher criteria and toxic pollutant emission rates. Along
with the rebound effect, these lead to changes in the overall amount of
highway travel and the distribution among different vehicles in the on-
road fleet. Vehicular emissions depend on the overall amount of highway
travel and the distribution of that travel among different vehicles,
and emissions from ``upstream'' processes (e.g., petroleum refining,
electricity generation) depend on the total consumption of different
types of fuels for light-duty vehicles.
(a) Impacts
In addition to affecting fuel consumption and emissions of
greenhouse gases, this rule would influence ``non-GHG'' pollutants,
i.e., ``criteria'' air pollutants and their precursors, and air toxics.
The proposal would affect emissions of carbon monoxide (CO), fine
particulate matter (PM2.5), sulfur dioxide (SOX),
volatile organic compounds (VOC), nitrogen oxides (NOX),
benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and acrolein.
Consistent with the evaluation conducted for the Environmental Impact
Statement accompanying this NPRM, the agency analyzed criteria air
pollutant impacts in 2025 and 2035 (as a representation of future
program impacts). Estimates of these non-GHG emission impacts are shown
by pollutant in Table VII-80 through Table VII-87 and are broken down
by the two drivers of these changes: (a) ``downstream'' emission
changes, reflecting the estimated effects of VMT rebound (discussed in
Chapter 8.7 of the PRIA), changes in vehicle fleet age, changes in
vehicle emission standards, and changes in fuel consumption; and (b)
``upstream'' emission increases because of increased refining and
distribution of motor vehicle gasoline relative to the baseline.
Program impacts on criteria and toxics emissions are discussed below,
followed by individual discussions of the methodology used to calculate
each of these three sources of impacts.\598\
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\598\ The agencies have employed the same methodology in this
rulemaking to estimate the effect of each alternative on emissions
of PM and other criteria pollutants emissions as they have
previously applied in the other rulemakings under the National
Program. Briefly, emissions from vehicle use are estimated for each
calendar year of the analysis period by applying emission rates per
vehicle-mile of travel to estimates of VMT for cars and light trucks
produced during each model year making up the vehicle fleet. These
emission rates are derived from EPA's Motor Vehicle Emissions
Simulator (MOVES); they reflect normal increases in vehicles'
emission rates as they age and accumulate mileage, as well as
adopted and pending vehicle emission standards and regulations on
fuel composition. ``Upstream'' emissions from crude oil production,
fuel refining, and fuel distribution are estimated from the total
energy content of fuels produced and consumed (gasoline, diesel,
ethanol, and electricity), using separate emission factors per unit
of fuel energy for each phase of fuel production and distribution
derived from Argonne National Laboratories' Greenhouse Gases and
Regulated Emissions in Transportation (GREET) fuel cycle model. This
procedure accounts for differences in domestic emissions associated
with refining fuel from imported and domestically-supplied crude
petroleum, as well as from importing fuel that has been refined
outside the U.S. Economic damages caused by emissions from vehicle
use and from fuel production and distribution are monetized using
different per-ton values, which reflect differences in the locations
where emissions occur and resulting variation in population exposure
to their potential adverse health effects. However, we note that in
some other rules affecting tailpipe emissions of criteria
pollutants, EPA has employed more detailed methods for estimating
emissions associated with different phases of fuel production and
distribution, and has also used more detailed estimates of their
per-ton health damage costs that reflect variation in population
exposure to emissions occurring during different phases of fuel
production and distribution. The agencies will consider whether to
employ these more detailed procedures in their analysis supporting
the final rule.
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As shown in Table VII-80, it is estimated in 2025 the light duty
vehicle CAFE scenarios would result in reductions of NOX,
VOC, and CO, and increases in PM2.5 and SOx.\599\ For
NOx, VOC, and CO, it is estimated net reductions result from
lower downstream, or tailpipe emissions in the scenarios evaluated.
This is a result of reduced VMT rebound as well as fewer older vehicles
in the scenarios as compared to the baseline. Because the scenarios
result in greater fuel consumption than the baseline, however, upstream
emissions associated with fuel refining and distribution increase for
all pollutants in all scenarios as compared to the baseline. Tailpipe
emissions reductions for NOx, VOC, and CO more than compensate for this
increase in 2025. PM2.5 and SOx, tailpipe
emissions reductions are not great enough to compensate for increased
emissions from fuel refining and distribution and therefore an overall
increase in total PM2.5 and SOx is seen in 2025.
Similar results can be seen in Table VII-81 which shows results for the
CO2 target scenarios.
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\599\ While estimates for CY 2025 and 2035 are shown here,
estimates through 2050 are shown in PRIA Chapter 5.
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In 2035, Table VII-82 shows decreases in total CO result from all
CAFE scenarios, while NOX, VOC, SO2, and
PM2.5 increase. Tailpipe CO emissions reductions more than
offset increases in upstream CO emissions. For NOX, VOC,
SO2, and PM2.5 however, upstream emissions
increases are not offset by tailpipe NOX, VOC,
SO2, and PM2.5 emissions reductions. Similar
results can be seen in the CO2 target scenarios for 2035
shown in Table VII-83, with the exception that NOX emission
decrease for scenarios 1-4 and increase for scenarios 5-8. For all
criteria pollutants, the overall impact of the proposed program would
be small compared to total U.S. inventories across all sectors.
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As shown in Table VII-84 through Table VII-87, it is estimated that
the proposed program would result in small changes for air toxic
emissions compared to total U.S. inventories across all sectors. In
2025, it is estimated the scenarios evaluated would reduce total
acetaldehyde, acrolein, benzene, butadiene, and formaldehyde, toxics as
compared to the baseline. This result is caused by greater VMT rebound
miles assumed in the augural scenario and fewer rebound VMT in
scenarios 1-8, and fewer older vehicles in the scenarios as compared to
the baseline. Similarly, in 2035, acetaldehyde, benzene, butadiene,
acrolein, and formaldehyde would all be reduced as compared to the
baseline. As is the case with criteria emissions, upstream toxic
emissions generally increase in the evaluated scenarios as compared to
the baseline because of the greater amount of gasoline and diesel being
refined and distributed.
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(b) Methodology
For the downstream analysis, emission factors in grams per mile for
VOC, CO, NOX, PM2.5, and air toxics by vehicle
model year and age were taken from the current version of the EPA
``Motor Vehicle Emission Simulator'' (MOVES2014a) and multiplied in the
CAFE model by assumed VMT to estimate mass VOC, CO, NOX,
PM2.5, and air toxics emissions. Additional emissions from
light duty cars and trucks attributable to the rebound effect were also
calculated using the CAFE model. A more complete discussion of the
inputs, methodology, and results is contained in PRIA Chapter 6. This
proposal also assumes implementation of EPA's Tier 3 emission
standards.\600\ For a more detailed description of the method used to
estimate emissions, please refer to pages 104-106 of the CAFE model
documentation.
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\600\ See 79 FR 23414 (April 28, 2014). EPA's Tier 3 emissions
standards included standards for vehicle emissions and the sulfur
content of gasoline.
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For the purposes of this emission analysis, it is assumed that all
gasoline in the timeframe of the analysis is blended with 10% ethanol
(E10). While electric vehicles have zero tailpipe
[[Page 43335]]
emissions, it is assumed that manufacturers will plan for these
vehicles in their regulatory compliance strategy for non-GHG emissions
standards, and will not over-comply with those standards. Because the
Tier 3 emissions standards are fleet-average standards (for all
pollutants except formaldehyde and PM2.5), it is assumed
that if a manufacturer introduces EVs into its fleet, that it would
correspondingly compensate through changes to vehicles elsewhere in its
fleet, rather than meet an overall lower fleet-average emissions level.
Consequently, no tailpipe pollutant benefit (other than CO2,
formaldehyde, and PM2.5) is assumed. The analysis does not
estimate evaporative emissions from light-duty vehicles. Other factors
which may impact downstream non-GHG emissions, but are not estimated in
this analysis, include the potential for decreased criteria pollutant
emissions because of increased air conditioner efficiency; reduced
refueling emissions because of less frequent refueling events and
reduced annual refueling volumes resulting from the CO2
standards; and increased hot soak evaporative emissions because of the
likely increase in number of trips associated with VMT rebound modeled
in this proposal. In all, these additional analyses would likely result
in small changes relative to the national inventory.
To determine the impacts of increased fuel production on upstream
emissions, the impact of increased gasoline consumption by light-duty
vehicles on the extraction and transportation of crude oil, refining of
crude oil, and distribution and storage of finished gasoline was
estimated. To assess the resulting increases in domestic emissions, the
fraction of increased gasoline consumption that would be supplied by
additional domestic refining of gasoline, and the fraction of that
gasoline that would be refined from domestic crude oil was estimated.
Using NEMS, it was estimated that 50% of increased gasoline consumption
would be supplied by increased domestic refining and that 90% of this
additional refining would use imported crude petroleum. Emission
factors for most upstream emission sources are based on the DOE Argonne
National Laboratory's GREET 2017 model,\601\ but emission factors
developed by EPA were relied on for the air toxics estimated in this
analysis: benzene, 1,3-butadiene, acetaldehyde, acrolein, and
formaldehyde. These emission factors came from the MOVES 2014a model
and were incorporated into the CAFE model.
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\601\ Greenhouse Gas, Regulated Emissions, and Energy Use in
Transportation model (GREET), U.S. Department of Energy, Argonne
National Laboratory, https://greet.es.anl.gov/.
---------------------------------------------------------------------------
Emission factors for electricity upstream emissions were also based
on GREET 2017. GREET allows the user to either select a region of the
country for the electricity upstream emissions or to use the U.S.
average of electricity emissions. The regional emission factors reflect
the specific mix of fuels used to generate electricity in the selected
region. The U.S. mix provides an average of electricity-related
emissions (in grams per million Btu) in the U.S. in a given calendar
year. The GREET 2017 U.S. mix emission factors were used for the
analysis. In order to capture projected changes in upstream emissions
over time, upstream emission factors for gasoline, diesel, and
electricity were taken from the GREET 2017 model in five year
increments, beginning in 1995 and ending in 2040.
For the downstream analysis of emissions, there are a number of
uncertainties associated with the method, such as: Emission factors are
based on samples of tested vehicles and these samples may not represent
average emissions for the full in-use fleet; and there is considerable
uncertainty in estimating total vehicle use (VMT). For the upstream
analysis of emissions, there are uncertainties related to the
projection of emissions associated with fossil fuel extraction,
refining, and mode split for transportation of fuels. In addition,
projections for electricity-related upstream emissions are based on
assumptions about the fuels and technologies used to generate
electricity which may not represent actual conditions through 2050.
E. Health Effects of Non-GHG Pollutants
This section discusses health effects associated with exposure to
some of the criteria and air toxic pollutants impacted by the proposed
vehicle standards.
1. Particulate Matter
(a) Background
Particulate matter is a highly complex mixture of solid particles
and liquid droplets distributed among numerous atmospheric gases which
interact with solid and liquid phases. Particles range in size from
those smaller than 1 nanometer (10-9 meter) to more than 100
micrometers ([micro]m, or 10-6 meter) in diameter (for reference, a
typical strand of human hair is 70 [micro]m in diameter and a grain of
salt is approximately 100 [micro]m). Atmospheric particles can be
grouped into several classes according to their aerodynamic and
physical sizes. Generally, the three broad classes of particles include
ultrafine particles (UFPs, generally considered as particulates with a
diameter less than or equal to 0.1 [micro]m [typically based on
physical size, thermal diffusivity or electrical mobility]), ``fine''
particles (PM2.5; particles with a nominal mean aerodynamic
diameter less than or equal to 2.5 [micro]m), and ``thoracic''
particles (PM10; particles with a nominal mean aerodynamic
diameter less than or equal to 10 [micro]m).\602\ Particles that fall
within the size range between PM2.5 and PM10, are
referred to as ``thoracic coarse particles'' (PM10-2.5,
particles with a nominal mean aerodynamic diameter less than or equal
to 10 [micro]m and greater than 2.5 [micro]m). EPA currently has
standards that regulate PM2.5 and PM10.\603\
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\602\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. Figure 3-1.
\603\ Regulatory definitions of PM size fractions, and
information on reference and equivalent methods for measuring PM in
ambient air, are provided in 40 CFR parts 50, 53, and 58. With
regard to national ambient air quality standards (NAAQS) which
provide protection against health and welfare effects, the 24-hour
PM10 standard provides protection against effects
associated with short-term exposure to thoracic coarse particles
(i.e., PM10-2.5).
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Particles span many sizes and shapes and may consist of hundreds of
different chemicals. Particles are emitted directly from sources and
are also formed through atmospheric chemical reactions; the former are
often referred to as ``primary'' particles, and the latter as
``secondary'' particles. Particle concentration and composition varies
by time of year and location, and, in addition to differences in source
emissions, is affected by several weather-related factors, such as
temperature, clouds, humidity, and wind. A further layer of complexity
comes from particles' ability to shift between solid/liquid and gaseous
phases, which is influenced by concentration and meteorology,
especially temperature.
Fine particles are produced primarily by combustion processes and
by transformations of gaseous emissions (e.g., sulfur oxides
(SOX), oxides of nitrogen, and volatile organic compounds
(VOC)) in the atmosphere. The chemical and physical properties of
PM2.5 may vary greatly with time, region, meteorology, and
source category. Thus, PM2.5 may include a complex mixture
of different components including sulfates, nitrates, organic
compounds, elemental carbon and metal compounds. These particles can
remain in the atmosphere for days
[[Page 43336]]
to weeks and travel hundreds to thousands of kilometers.
(b) Health Effects of PM
Scientific studies show exposure to ambient PM is associated with a
broad range of health effects. These health effects are discussed in
detail in the 2009 Integrated Science Assessment for Particulate Matter
(PM ISA), which was used as the basis of the 2012 NAAQS.\604\ The PM
ISA summarizes health effects evidence for short- and long-term
exposures to PM2.5, PM10-2.5, and ultrafine
particles.\605\ The PM ISA concludes that human exposures to ambient
PM2.5 are associated with a number of adverse health effects
and characterizes the weight of evidence for broad health categories
(e.g., cardiovascular effects, respiratory effects, etc.).\606\ The
discussion below highlights the PM ISA's conclusions pertaining to
health effects associated with both short- and long-term PM exposures.
Further discussion of health effects associated with PM can also be
found in the rulemaking documents for the most recent review of the PM
NAAQS completed in 2012.607 608
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\604\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F.
\605\ The ISA also evaluated evidence for individual PM
components but did not reach causal determinations for components.
\606\ The causal framework draws upon the assessment and
integration of evidence from across epidemiological, controlled
human exposure, and toxicological studies, and the related
uncertainties that ultimately influence our understanding of the
evidence. This framework employs a five-level hierarchy that
classifies the overall weight of evidence and causality using the
following categorizations: Causal relationship, likely to be causal
relationship, suggestive of a causal relationship, inadequate to
infer a causal relationship, and not likely to be a causal
relationship (U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Table 1-3).
\607\ 78 FR 3103-3104 (Jan. 15, 2013).
\608\ 77 FR 38906-38911 (June 29, 2012).
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EPA has concluded that ``a causal relationship exists'' between
both long- and short-term exposures to PM2.5 and premature
mortality and cardiovascular effects and that ``a causal relationship
is likely to exist'' between long- and short-term PM2.5
exposures and respiratory effects. Further, there is evidence
``suggestive of a causal relationship'' between long-term
PM2.5 exposures and other health effects, including
developmental and reproductive effects (e.g., low birth weight, infant
mortality) and carcinogenic, mutagenic, and genotoxic effects (e.g.,
lung cancer mortality).\609\
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\609\ These causal inferences are based not only on the more
expansive epidemiological evidence available in this review but also
reflect consideration of important progress that has been made to
advance our understanding of a number of potential biologic modes of
action or pathways for PM-related cardiovascular and respiratory
effects (U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Chapter 5).
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As summarized in the final rule promulgating the 2012 PM NAAQS, and
discussed extensively in the 2009 PM ISA, the available scientific
evidence significantly strengthens the link between long- and short-
term exposure to PM2.5 and mortality, while providing
indications that the magnitude of the PM2.5-mortality
association with long-term exposures may be larger than previously
estimated.610 611 The strongest evidence comes from recent
studies investigating long-term exposure to PM2.5 and
cardiovascular-related mortality. The evidence supporting a causal
relationship between long-term PM2.5 exposure and mortality
also includes consideration of studies that demonstrated an improvement
in community health following reductions in ambient fine particles.
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\610\ 78 FR 3103-3104 (Jan. 15, 2013).
\611\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Chapter 6 (Section 6.5)
and Chapter 7 (Section 7.6).
---------------------------------------------------------------------------
The 2009 PM ISA examined the association between cardiovascular
effects and long-term PM2.5 exposures in multi-city
epidemiological studies conducted in the U.S. and Europe. These studies
have provided new evidence linking long-term exposure to
PM2.5 with an array of cardiovascular effects such as heart
attacks, congestive heart failure, stroke, and mortality. This evidence
is coherent with epidemiological studies of effects associated with
short-term exposure to PM2.5 that have observed associations
with a continuum of effects ranging from subtle changes in indicators
of cardiovascular health to serious clinical events, such as increased
hospitalizations and emergency department visits due to cardiovascular
disease and cardiovascular mortality.\612\
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\612\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Chapter 2 (Section 2.3.1
and 2.3.2) and Chapter 6.
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As detailed in the 2009 PM ISA, extended analyses of seminal
epidemiological studies, as well as more recent epidemiological studies
conducted in the U.S. and abroad, provide strong evidence of
respiratory-related morbidity effects associated with long-term
PM2.5 exposure. The strongest evidence for respiratory-
related effects is from studies that evaluated decrements in lung
function growth (in children), increased respiratory symptoms, and
asthma development. The strongest evidence from short-term
PM2.5 exposure studies has been observed for increased
respiratory-related emergency department visits and hospital admissions
for chronic obstructive pulmonary disease (COPD) and respiratory
infections.\613\
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\613\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Chapter 2 (Section 2.3.1
and 2.3.2) and Chapter 6.
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The body of scientific evidence detailed in the 2009 PM ISA is
still limited with respect to associations between long-term
PM2.5 exposures and developmental and reproductive effects
as well as cancer, mutagenic, and genotoxic effects. The strongest
evidence for an association between PM2.5 and developmental
and reproductive effects comes from epidemiological studies of low
birth weight and infant mortality, especially due to respiratory causes
during the post-neonatal period (i.e., 1 month to 12 months of
age).\614\ With regard to cancer effects, ``[m]ultiple epidemiologic
studies have shown a consistent positive association between
PM2.5 and lung cancer mortality, but studies have generally
not reported associations between PM2.5 and lung cancer
incidence.'' \615\
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\614\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Chapter 2 (Section 2.3.1
and 2.3.2) and Chapter 7.
\615\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. pg 2-13.
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In addition to evaluating the health effects attributed to short-
and long-term exposure to PM2.5, the 2009 PM ISA also
evaluated whether specific components or sources of PM2.5
are more strongly associated with specific health effects. The 2009 PM
ISA concluded that ``many [components] of PM can be linked with
differing health effects, and the evidence is not yet sufficient to
allow differentiation of those [components] or sources that are more
closely related to specific health outcomes.'' \616\
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\616\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. pg 2-26.
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For PM10-2.5, the 2009 PM ISA concluded that available
evidence was ``suggestive of a causal relationship'' between short-term
exposures to PM10-2.5 and cardiovascular effects (e.g.,
hospital admissions and Emergency Department (ED) visits, changes in
[[Page 43337]]
cardiovascular function), respiratory effects (e.g., ED visits and
hospital admissions, increase in markers of pulmonary inflammation),
and premature mortality. The scientific evidence was ``inadequate to
infer a causal relationship'' between long-term exposure to
PM10-2.5 and various health effects.617 618 619
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\617\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. Section 2.3.4 and Table
2-6.
\618\ 78 FR 3167-3168 (Jan. 15, 2013).
\619\ 77 FR 38947-38951 (June 29, 2012).
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For UFPs, the 2009 PM ISA concluded that the evidence was
``suggestive of a causal relationship'' between short-term exposures
and cardiovascular effects, including changes in heart rhythm and
vasomotor function (the ability of blood vessels to expand and
contract). It also concluded that there was evidence ``suggestive of a
causal relationship'' between short-term exposure to UFPs and
respiratory effects, including lung function and pulmonary
inflammation, with limited and inconsistent evidence for increases in
ED visits and hospital admissions. Scientific evidence was ``inadequate
to infer a causal relationship'' between short-term exposure to UFPs
and additional health effects including premature mortality as well as
long-term exposure to UFPs and all health outcomes
evaluated.620 621
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\620\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. Section 2.3.5 and Table
2-6.
\621\ 78 FR 3121 (Jan. 15, 2013).
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The 2009 PM ISA conducted an evaluation of specific groups within
the general population potentially at increased risk for experiencing
adverse health effects related to PM
exposures.622 623 624 625 The evidence detailed in the 2009
PM ISA expands our understanding of previously identified at-risk
populations and lifestages (i.e., children, older adults, and
individuals with pre-existing heart and lung disease) and supports the
identification of additional at-risk populations (e.g., persons with
lower socioeconomic status, genetic differences). Additionally, there
is emerging, though still limited, evidence for additional potentially
at-risk populations and lifestages, such as those with diabetes, people
who are obese, pregnant women, and the developing fetus.\626\
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\622\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. Chapter 8 and Chapter 2.
\623\ 77 FR 38890 (June 29, 2012).
\624\ 78 FR 3104 (Jan. 15, 2013).
\625\ U.S. EPA. (2011). Policy Assessment for the Review of the
PM NAAQS. U.S. Environmental Protection Agency, Washington, DC, EPA/
452/R-11-003. Section 2.2.1.
\626\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F. Chapter 8 and Chapter 2
(Section 2.4.1).
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2. Ozone
(a) Background
Ground-level ozone pollution is typically formed through reactions
involving VOC and NOX in the lower atmosphere in the
presence of sunlight. These pollutants, often referred to as ozone
precursors, are emitted by many types of sources, such as highway and
nonroad motor vehicles and engines, power plants, chemical plants,
refineries, makers of consumer and commercial products, industrial
facilities, and smaller area sources.
The science of ozone formation, transport, and accumulation is
complex. Ground-level ozone is produced and destroyed in a cyclical set
of chemical reactions, many of which are sensitive to temperature and
sunlight. When ambient temperatures and sunlight levels remain high for
several days and the air is relatively stagnant, ozone and its
precursors can build up and result in more ozone than typically occurs
on a single high-temperature day. Ozone and its precursors can be
transported hundreds of miles downwind from precursor emissions,
resulting in elevated ozone levels even in areas with low local VOC or
NOX emissions.
(b) Health Effects of Ozone
This section provides a summary of the health effects associated
with exposure to ambient concentrations of ozone.\627\ The information
in this section is based on the information and conclusions in the
February 2013 Integrated Science Assessment for Ozone (Ozone ISA),
which formed the basis for EPA's revision to the primary and secondary
standards in 2015.\628\ The Ozone ISA concludes that human exposures to
ambient concentrations of ozone are associated with a number of adverse
health effects and characterizes the weight of evidence for these
health effects.\629\ The discussion below highlights the Ozone ISA's
conclusions pertaining to health effects associated with both short-
term and long-term periods of exposure to ozone.
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\627\ Human exposure to ozone varies over time due to changes in
ambient ozone concentration and because people move between
locations which have notable different ozone concentrations. Also,
the amount of ozone delivered to the lung is not only influenced by
the ambient concentrations but also by the individuals breathing
route and rate.
\628\ U.S. EPA. Integrated Science Assessment of Ozone and
Related Photochemical Oxidants (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-10/076F, 2013. The ISA
is available at http://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=247492#Download.
\629\ The ISA evaluates evidence and draws conclusions on the
causal nature of relationship between relevant pollutant exposures
and health effects, assigning one of five ``weight of evidence''
determinations: Causal relationship, likely to be a causal
relationship, suggestive of, but not sufficient to infer, a causal
relationship, inadequate to infer a causal relationship, and not
likely to be a causal relationship. For more information on these
levels of evidence, please refer to Table II in the Preamble of the
ISA.
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For short-term exposure to ozone, the Ozone ISA concludes that
respiratory effects, including lung function decrements, pulmonary
inflammation, exacerbation of asthma, respiratory-related hospital
admissions, and mortality, are causally associated with ozone exposure.
It also concludes that cardiovascular effects, including decreased
cardiac function and increased vascular disease, and total mortality
are likely to be causally associated with short-term exposure to ozone,
and that evidence is suggestive of a causal relationship between
central nervous system effects and short-term exposure to ozone.
For long-term exposure to ozone, the Ozone ISA concludes that
respiratory effects, including new onset asthma, pulmonary inflammation
and injury, are likely to be causally related with ozone exposure. The
Ozone ISA characterizes the evidence as suggestive of a causal
relationship for associations between long-term ozone exposure and
cardiovascular effects, reproductive and developmental effects, central
nervous system effects and total mortality. The evidence is inadequate
to infer a causal relationship between chronic ozone exposure and
increased risk of lung cancer.
Finally, inter-individual variation in human responses to ozone
exposure can result in some groups being at increased risk for
detrimental effects in response to exposure. In addition, some groups
are at increased risk of exposure due to their activities, such as
outdoor workers or children. The Ozone ISA identified several groups
that are at increased risk for ozone-related health effects. These
groups are people with asthma, children and older adults, individuals
with reduced intake of certain nutrients (i.e., Vitamins C and E),
outdoor workers, and individuals having certain genetic variants
related to oxidative metabolism or inflammation. Ozone exposure during
childhood can have lasting effects through adulthood. Such effects
include altered function of the
[[Page 43338]]
respiratory and immune systems. Children absorb higher doses
(normalized to lung surface area) of ambient ozone, compared to adults,
due to their increased time spent outdoors, higher ventilation rates
relative to body size, and a tendency to breathe a greater fraction of
air through the mouth. Children also have a higher asthma prevalence
compared to adults.
3. Nitrogen Oxides
(a) Background
Oxides of nitrogen (NOX) refers to nitric oxide and
nitrogen dioxide (NO2). For the NOX NAAQS,
NO2 is the indicator. Most NO2 is formed in the
air through the oxidation of nitric oxide (NO) emitted when fuel is
burned at a high temperature. NOX is also a major
contributor to secondary PM2.5 formation. NOX and
VOC are the two major precursors of ozone.
(b) Health Effects of Nitrogen Oxides
The most recent review of the health effects of oxides of nitrogen
completed by EPA can be found in the 2016 Integrated Science Assessment
for Oxides of Nitrogen--Health Criteria (Oxides of Nitrogen ISA).\630\
The primary source of NO2 is motor vehicle emissions, and
ambient NO2 concentrations tend to be highly correlated with
other traffic-related pollutants. Thus, a key issue in characterizing
the causality of NO2-health effect relationships was
evaluating the extent to which studies supported an effect of
NO2 that is independent of other traffic-related pollutants.
EPA concluded that the findings for asthma exacerbation integrated from
epidemiologic and controlled human exposure studies provided evidence
that is sufficient to infer a causal relationship between respiratory
effects and short-term NO2 exposure. The strongest evidence
supporting an independent effect of NO2 exposure comes from
controlled human exposure studies demonstrating increased airway
responsiveness in individuals with asthma following ambient-relevant
NO2 exposures. The coherence of this evidence with
epidemiologic findings for asthma hospital admissions and ED visits as
well as lung function decrements and increased pulmonary inflammation
in children with asthma describe a plausible pathway by which
NO2 exposure can cause an asthma exacerbation. The 2016 ISA
for Oxides of Nitrogen also concluded that there is likely to be a
causal relationship between long-term NO2 exposure and
respiratory effects. This conclusion is based on new epidemiologic
evidence for associations of NO2 with asthma development in
children combined with biological plausibility from experimental
studies.
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\630\ U.S. EPA. Integrated Science Assessment for Oxides of
Nitrogen--Health Criteria (2016 Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-15/068, 2016.
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In evaluating a broader range of health effects, the 2016 ISA for
Oxides of Nitrogen concluded evidence is ``suggestive of, but not
sufficient to infer, a causal relationship'' between short-term
NO2 exposure and cardiovascular effects and mortality and
between long-term NO2 exposure and cardiovascular effects
and diabetes, birth outcomes, and cancer. In addition, the scientific
evidence is inadequate (insufficient consistency of epidemiologic and
toxicological evidence) to infer a causal relationship for long-term
NO2 exposure with fertility, reproduction, and pregnancy, as
well as with postnatal development. A key uncertainty in understanding
the relationship between these non-respiratory health effects and
short- or long-term exposure to NO2 is copollutant
confounding, particularly by other roadway pollutants. The available
evidence for non-respiratory health effects does not adequately address
whether NO2 has an independent effect or whether it
primarily represents effects related to other or a mixture of traffic-
related pollutants.
The 2016 ISA for Oxides of Nitrogen concluded that people with
asthma, children, and older adults are at increased risk for
NO2-related health effects. In these groups and lifestages,
NO2 is consistently related to larger effects on outcomes
related to asthma exacerbation, for which there is confidence in the
relationship with NO2 exposure.
4. Sulfur Oxides
(a) Background
Sulfur dioxide (SO2), a member of the sulfur oxide
(SOX) family of gases, is formed from burning fuels
containing sulfur (e.g., coal or oil derived), extracting gasoline from
oil, or extracting metals from ore. SO2 and its gas phase
oxidation products can dissolve in water droplets and further oxidize
to form sulfuric acid which reacts with ammonia to form sulfates, which
are important components of ambient PM.
(b) Health Effects of SO2
Information on the health effects of SO2 can be found in
the 2008 Integrated Science Assessment for Sulfur Oxides--Health
Criteria (SOX ISA).\631\ Short-term peaks (5-10 minutes) of
SO2 have long been known to cause adverse respiratory health
effects, particularly among individuals with asthma. In addition to
those with asthma (both children and adults), potentially at-risk
lifestages include all children and the elderly. During periods of
elevated ventilation, asthmatics may experience symptomatic
bronchoconstriction within minutes of exposure. Following an extensive
evaluation of health evidence from epidemiologic and laboratory
studies, EPA concluded that there is a causal relationship between
respiratory health effects and short-term exposure to SO2.
Separately, based on an evaluation of the epidemiologic evidence of
associations between short-term exposure to SO2 and
mortality, EPA concluded that the overall evidence is suggestive of a
causal relationship between short-term exposure to SO2 and
mortality.
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\631\ U.S. EPA. (2008). Integrated Science Assessment (ISA) for
Sulfur Oxides--Health Criteria (Final Report). EPA/600/R-08/047F.
Washington, DC: U.S. Environmental Protection Agency.
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5. Carbon Monoxide
(a) Background
Carbon monoxide is a colorless, odorless gas emitted from
combustion processes. Nationally, particularly in urban areas, the
majority of CO emissions to ambient air come from mobile sources.\632\
---------------------------------------------------------------------------
\632\ U.S. EPA, (2010). Integrated Science Assessment for Carbon
Monoxide (Final Report). U.S. Environmental Protection Agency,
Washington, DC, EPA/600/R-09/019F, 2010. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686. See Section
2.1.
---------------------------------------------------------------------------
(b) Health Effects of Carbon Monoxide
Information on the health effects of CO can be found in the January
2010 Integrated Science Assessment for Carbon Monoxide (CO ISA)
associated with the 2010 evaluation of the NAAQS.\633\ The CO ISA
presents conclusions regarding the presence of causal relationships
between CO exposure and categories of adverse health effects. This
section provides a summary of the health effects associated with
exposure to ambient concentrations of CO, along with the ISA
conclusions.\634\
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\633\ U.S. EPA, (2010). Integrated Science Assessment for Carbon
Monoxide (Final Report). U.S. Environmental Protection Agency,
Washington, DC, EPA/600/R-09/019F, 2010. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686.
\634\ Personal exposure includes contributions from many sources
and in many different environments. Total personal exposure to CO
includes both ambient and nonambient components; both components may
contribute to adverse health effects.
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[[Page 43339]]
Controlled human exposure studies of subjects with coronary artery
disease show a decrease in the time to onset of exercise-induced angina
(chest pain) and electrocardiogram changes following CO exposure. In
addition, epidemiologic studies observed associations between short-
term CO exposure and cardiovascular morbidity, particularly increased
emergency room visits and hospital admissions for coronary heart
disease (including ischemic heart disease, myocardial infarction, and
angina). Some epidemiologic evidence is also available for increased
hospital admissions and emergency room visits for congestive heart
failure and cardiovascular disease as a whole. The CO ISA concludes
that a causal relationship is likely to exist between short-term
exposures to CO and cardiovascular morbidity. It also concludes that
available data are inadequate to conclude that a causal relationship
exists between long-term exposures to CO and cardiovascular morbidity.
Animal studies show various neurological effects with in-utero CO
exposure. Controlled human exposure studies report central nervous
system and behavioral effects following low-level CO exposures,
although the findings have not been consistent across all studies. The
CO ISA concludes the evidence is suggestive of a causal relationship
with both short- and long-term exposure to CO and central nervous
system effects.
A number of studies cited in the CO ISA have evaluated the role of
CO exposure in birth outcomes such as preterm birth or cardiac birth
defects. There is limited epidemiologic evidence of a CO-induced effect
on preterm births and birth defects, with weak evidence for a decrease
in birth weight. Animal toxicological studies have found perinatal CO
exposure to affect birth weight, as well as other developmental
outcomes. The CO ISA concludes the evidence is suggestive of a causal
relationship between long-term exposures to CO and developmental
effects and birth outcomes.
Epidemiologic studies provide evidence of associations between
short-term CO concentrations and respiratory morbidity such as changes
in pulmonary function, respiratory symptoms, and hospital admissions. A
limited number of epidemiologic studies considered copollutants such as
ozone, SO2, and PM in two-pollutant models and found that CO
risk estimates were generally robust, although this limited evidence
makes it difficult to disentangle effects attributed to CO itself from
those of the larger complex air pollution mixture. Controlled human
exposure studies have not extensively evaluated the effect of CO on
respiratory morbidity. Animal studies at levels of 50-100 ppm CO show
preliminary evidence of altered pulmonary vascular remodeling and
oxidative injury. The CO ISA concludes that the evidence is suggestive
of a causal relationship between short-term CO exposure and respiratory
morbidity, and inadequate to conclude that a causal relationship exists
between long-term exposure and respiratory morbidity.
Finally, the CO ISA concludes that the epidemiologic evidence is
suggestive of a causal relationship between short-term concentrations
of CO and mortality. Epidemiologic evidence suggests an association
exists between short-term exposure to CO and mortality, but limited
evidence is available to evaluate cause-specific mortality outcomes
associated with CO exposure. In addition, the attenuation of CO risk
estimates which was often observed in copollutant models contributes to
the uncertainty as to whether CO is acting alone or as an indicator for
other combustion-related pollutants. The CO ISA also concludes that
there is not likely to be a causal relationship between relevant long-
term exposures to CO and mortality.
6. Diesel Exhaust
(a) Background
Diesel exhaust consists of a complex mixture composed of
particulate matter, carbon dioxide, oxygen, nitrogen, water vapor,
carbon monoxide, nitrogen compounds, sulfur compounds and numerous low-
molecular-weight hydrocarbons. A number of these gaseous hydrocarbon
components are individually known to be toxic, including aldehydes,
benzene and 1,3-butadiene. The diesel particulate matter present in
diesel exhaust consists mostly of fine particles (<2.5 [micro]m), of
which a significant fraction is ultrafine particles (< 0.1 [micro]m).
These particles have a large surface area which makes them an excellent
medium for adsorbing organics, and their small size makes them highly
respirable. Many of the organic compounds present in the gases and on
the particles, such as polycyclic organic matter, are individually
known to have mutagenic and carcinogenic properties.
Diesel exhaust varies significantly in chemical composition and
particle sizes between different engine types (heavy-duty, light-duty),
engine operating conditions (idle, acceleration, deceleration), and
fuel formulations (high/low sulfur fuel). Also, there are emissions
differences between on-road and nonroad engines because the nonroad
engines are generally of older technology. After being emitted in the
engine exhaust, diesel exhaust undergoes dilution as well as chemical
and physical changes in the atmosphere. The lifetime for some of the
compounds present in diesel exhaust ranges from hours to days.
(b) Health Effects of Diesel Exhaust
In EPA's 2002 Diesel Health Assessment Document (Diesel HAD),
exposure to diesel exhaust was classified as likely to be carcinogenic
to humans by inhalation from environmental exposures, in accordance
with the revised draft 1996/1999 EPA cancer
guidelines.635 636 A number of other agencies (National
Institute for Occupational Safety and Health, the International Agency
for Research on Cancer, the World Health Organization, California EPA,
and the U.S. Department of Health and Human Services) made similar
hazard classifications prior to 2002. EPA also concluded in the 2002
Diesel HAD that it was not possible to calculate a cancer unit risk for
diesel exhaust due to limitations in the exposure data for the
occupational groups or the absence of a dose-response relationship.
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\635\ U.S. EPA. (March 2005). Guidelines for Carcinogen Risk
Assessment EPA/630/P-03/001F, https://www.epa.gov/risk/guidelines-carcinogen-risk-assessment (Last accessed July 2018).
\636\ U.S. EPA (2002). Health Assessment Document for Diesel
Engine Exhaust. EPA/600/8-90/057F Office of Research and
Development, Washington, DC. Retrieved on March 17, 2009 from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060 (last accessed
July 2018). pp. 1-1 1-2.
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In the absence of a cancer unit risk, the Diesel HAD sought to
provide additional insight into the significance of the diesel exhaust
cancer hazard by estimating possible ranges of risk that might be
present in the population. An exploratory analysis was used to
characterize a range of possible lung cancer risk. The outcome was that
environmental risks of cancer from long-term diesel exhaust exposures
could plausibly range from as low as 10-5 to as high as 10-3. Because
of uncertainties, the analysis acknowledged that the risks could be
lower than 10-5, and a zero risk from diesel exhaust exposure could not
be ruled out.
Non-cancer health effects of acute and chronic exposure to diesel
exhaust emissions are also of concern to EPA. EPA derived a diesel
exhaust reference
[[Page 43340]]
concentration (RfC) from consideration of four well-conducted chronic
rat inhalation studies showing adverse pulmonary effects. The RfC is 5
[micro]g/m3 for diesel exhaust measured as diesel particulate matter.
This RfC does not consider allergenic effects such as those associated
with asthma or immunologic or the potential for cardiac effects. There
was emerging evidence in 2002, discussed in the Diesel HAD, that
exposure to diesel exhaust can exacerbate these effects, but the
exposure-response data were lacking at that time to derive an RfC based
on these then-emerging considerations. The EPA Diesel HAD states,
``With [diesel particulate matter] being a ubiquitous component of
ambient PM, there is an uncertainty about the adequacy of the existing
[diesel exhaust] noncancer database to identify all of the pertinent
[diesel exhaust]-caused noncancer health hazards.'' The Diesel HAD also
notes ``that acute exposure to [diesel exhaust] has been associated
with irritation of the eye, nose, and throat, respiratory symptoms
(cough and phlegm), and neurophysiological symptoms such as headache,
lightheadedness, nausea, vomiting, and numbness or tingling of the
extremities.'' The Diesel HAD noted that the cancer and noncancer
hazard conclusions applied to the general use of diesel engines then on
the market and as cleaner engines replace a substantial number of
existing ones, the applicability of the conclusions would need to be
reevaluated.
It is important to note that the Diesel HAD also briefly summarizes
health effects associated with ambient PM and discusses EPA's then-
annual PM2.5 NAAQS of 15 [micro]g/m3. In 2012, EPA revised
the annual PM2.5 NAAQS to 12 [micro]g/m3. There is a large
and extensive body of human data showing a wide spectrum of adverse
health effects associated with exposure to ambient PM, of which diesel
exhaust is an important component. The PM2.5 NAAQS is
designed to provide protection from the noncancer health effects and
premature mortality attributed to exposure to PM2.5. The
contribution of diesel PM to total ambient PM varies in different
regions of the country and also, within a region, from one area to
another. The contribution can be high in near-roadway environments, for
example, or in other locations where diesel engine use is concentrated.
Since 2002, several new studies have been published which continue
to report increased lung cancer risk with occupational exposure to
diesel exhaust from older engines. Of particular note since 2011 are
three new epidemiology studies which have examined lung cancer in
occupational populations, for example, truck drivers, underground
nonmetal miners and other diesel motor-related occupations. These
studies reported increased risk of lung cancer with exposure to diesel
exhaust with evidence of positive exposure-response relationships to
varying degrees.\637\ \638\ \639\ These newer studies (along with
others that have appeared in the scientific literature) add to the
evidence EPA evaluated in the 2002 Diesel HAD and further reinforces
the concern that diesel exhaust exposure likely poses a lung cancer
hazard. The findings from these newer studies do not necessarily apply
to newer technology diesel engines b the newer engines have large
reductions in the emission constituents compared to older technology
diesel engines.
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\637\ Garshick, E., Laden, F., Hart, J.E., Davis, M.E., Eisen,
E.A., & Smith T.J. 2012. Lung cancer and elemental carbon exposure
in trucking industry workers. Environmental Health Perspectives.
120(9): 1301-1306.
\638\ Silverman, D.T., Samanic, C.M., Lubin, J.H., Blair, A.E.,
Stewart, P.A., Vermeulen, R., & Attfield, M.D. (2012). The diesel
exhaust in miners study: a nested case-control study of lung cancer
and diesel exhaust. Journal of the National Cancer Institute.
\639\ Olsson, A.C., et al. ``Exposure to diesel motor exhaust
and lung cancer risk in a pooled analysis from case-control studies
in Europe and Canada.'' American Journal of Respiratory and Critical
Care Medicine 183(7). (2011): 941-948.
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In light of the growing body of scientific literature evaluating
the health effects of exposure to diesel exhaust, in June 2012 the
World Health Organization's International Agency for Research on Cancer
(IARC), a recognized international authority on the carcinogenic
potential of chemicals and other agents, evaluated the full range of
cancer-related health effects data for diesel engine exhaust. IARC
concluded that diesel exhaust should be regarded as ``carcinogenic to
humans.'' \640\ This designation was an update from its 1988 evaluation
that considered the evidence to be indicative of a ``probable human
carcinogen.''
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\640\ IARC [International Agency for Research on Cancer].
(2013). Diesel and gasoline engine exhausts and some nitroarenes.
IARC Monographs Volume 105. [Online at http://monographs.iarc.fr/ENG/Monographs/vol105/index.php].
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7. Air Toxics
(a) Background
Light-duty vehicle emissions contribute to ambient levels of air
toxics that are known or suspected human or animal carcinogens, or that
have noncancer health effects. The population experiences an elevated
risk of cancer and other noncancer health effects from exposure to the
class of pollutants known collectively as ``air toxics.'' \641\ These
compounds include, but are not limited to, benzene, 1,3-butadiene,
formaldehyde, acetaldehyde, acrolein, polycyclic organic matter, and
naphthalene. These compounds were identified as national or regional
risk drivers or contributors in the 2011 National-scale Air Toxics
Assessment and have significant inventory contributions from mobile
sources.\642\
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\641\ U.S. EPA. (2015) Summary of Results for the 2011 National-
Scale Assessment. http://www3.epa.gov/sites/production/files/2015-12/documents/2011-nata-summary-results.pdf.
\642\ U.S. EPA (2015) 2011 National Air Toxics Assessment.
http://www3.epa.gov/national-air-toxics-assessment/2011-national-air-toxics-assessment.
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(b) Benzene
EPA's Integrated Risk Information System (IRIS) database lists
benzene as a known human carcinogen (causing leukemia) by all routes of
exposure and concludes that exposure is associated with additional
health effects, including genetic changes in both humans and animals
and increased proliferation of bone marrow cells in mice.\643\ \644\
\645\ EPA states in its IRIS database that data indicate a causal
relationship between benzene exposure and acute lymphocytic leukemia
and suggest a relationship between benzene exposure and chronic non-
lymphocytic leukemia and chronic lymphocytic leukemia. EPA's IRIS
documentation for benzene also lists a range of 2.2 x 10-6 to 7.8 x 10-
6 per [micro]g/m3 as the unit risk estimate (URE) for benzene.\646\
\647\ The International Agency for Research on Cancer (IARC) has
determined that benzene is a human carcinogen and the U.S. Department
of Health and Human Services (DHHS) has characterized benzene as a
known human carcinogen.\648 649\
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\643\ U.S. EPA. (2000). Integrated Risk Information System File
for Benzene. This material is available electronically at: https://www.epa.gov/iris (Last accessed July 2018)
\644\ International Agency for Research on Cancer, IARC
monographs on the evaluation of carcinogenic risk of chemicals to
humans, Volume 29, some industrial chemicals and dyestuffs,
International Agency for Research on Cancer, World Health
Organization, Lyon, France 1982.
\645\ Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry,
V.A. (1992). Synergistic action of the benzene metabolite
hydroquinone on myelopoietic stimulating activity of granulocyte/
macrophage colony-stimulating factor in vitro, Proc. Natl. Acad.
Sci. 89:3691-3695.
\646\ A unit risk estimate is defined as the increase in the
lifetime risk of an individual who is exposed for a lifetime to 1
[micro]g/m3 benzene in air.
\647\ U.S. EPA. (2000). Integrated Risk Information System File
for Benzene. This material is available electronically at: http://www3.epa.gov/iris/subst/0276.htm.
\648\ International Agency for Research on Cancer (IARC).
(1987). Monographs on the evaluation of carcinogenic risk of
chemicals to humans, Volume 29, Supplement 7, Some industrial
chemicals and dyestuffs, World Health Organization, Lyon, France.
\649\ NTP. (2014). 13th Report on Carcinogens. Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public
Health Service, National Toxicology Program.
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[[Page 43341]]
A number of adverse noncancer health effects including blood
disorders, such as pre-leukemia and aplastic anemia, have also been
associated with long-term exposure to benzene. The most sensitive
noncancer effect observed in humans, based on current data, is the
depression of the absolute lymphocyte count in blood. EPA's inhalation
reference concentration (RfC) for benzene is 30 [micro]g/m3. The RfC is
based on suppressed absolute lymphocyte counts seen in humans under
occupational exposure conditions. In addition, recent work, including
studies sponsored by the Health Effects Institute, provides evidence
that biochemical responses are occurring at lower levels of benzene
exposure than previously known.\650\ \651\ \652\ \653\ EPA's IRIS
program has not yet evaluated these new data. EPA does not currently
have an acute reference concentration for benzene. The Agency for Toxic
Substances and Disease Registry (ATSDR) Minimal Risk Level (MRL) for
acute exposure to benzene is 29 [micro]g/m3 for 1-14 days exposure.
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\650\ Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.;
Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.; Rupa, D.;
Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok,
E.; Li, Y.; Mu, R.; Xu, B.; Zhang, X.; Li, K. (2003). HEI Report
115, Validation & Evaluation of Biomarkers in Workers Exposed to
Benzene in China.
\651\ Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et
al. (2002). Hematological changes among Chinese workers with a broad
range of benzene exposures. American. Journal of Industrial
Medicine. 42: 275-285.
\652\ Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al.
(2004). Hematotoxically in Workers Exposed to Low Levels of Benzene.
Science 306: 1774-1776.
\653\ Turtletaub, K.W. and Mani, C. (2003). Benzene metabolism
in rodents at doses relevant to human exposure from Urban Air.
Research Reports Health Effect Inst. Report No.113.
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(c) 1,3-Butadiene
EPA has characterized 1,3-butadiene as carcinogenic to humans by
inhalation.\654 655\ The IARC has determined that 1,3-butadiene is a
human carcinogen and the U.S. DHHS has characterized 1,3-butadiene as a
known human carcinogen.\656\ \657\ \658\ There are numerous studies
consistently demonstrating that 1,3-butadiene is metabolized into
genotoxic metabolites by experimental animals and humans. The specific
mechanisms of 1,3-butadiene-induced carcinogenesis are unknown;
however, the scientific evidence strongly suggests that the
carcinogenic effects are mediated by genotoxic metabolites. Animal data
suggest that females may be more sensitive than males for cancer
effects associated with 1,3-butadiene exposure; there are insufficient
data in humans from which to draw conclusions about sensitive
subpopulations. The URE for 1,3-butadiene is 3 x 10-5 per
[micro]g/m\3\.\659\ 1,3-butadiene also causes a variety of reproductive
and developmental effects in mice; no human data on these effects are
available. The most sensitive effect was ovarian atrophy observed in a
lifetime bioassay of female mice.\660\ Based on this critical effect
and the benchmark concentration methodology, an RfC for chronic health
effects was calculated at 0.9 ppb (approximately 2 [micro]g/m3).
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\654\ U.S. EPA. (2002). Health Assessment of 1,3-Butadiene.
Office of Research and Development, National Center for
Environmental Assessment, Washington Office, Washington, DC. Report
No. EPA600-P-98-001F. This document is available electronically at
http://www3.epa.gov/iris/supdocs/buta-sup.pdf.
\655\ U.S. EPA. (2002). ``Full IRIS Summary for 1,3-butadiene
(CASRN 106-99-0)'' Environmental Protection Agency, Integrated Risk
Information System (IRIS), Research and Development, National Center
for Environmental Assessment, Washington, DC http://www3.epa.gov/iris/subst/0139.htm.
\656\ International Agency for Research on Cancer (IARC).
(1999). Monographs on the evaluation of carcinogenic risk of
chemicals to humans, Volume 71, Re-evaluation of some organic
chemicals, hydrazine and hydrogen peroxide and Volume 97 (in
preparation), World Health Organization, Lyon, France.
\657\ International Agency for Research on Cancer (IARC).
(2008). Monographs on the evaluation of carcinogenic risk of
chemicals to humans, 1,3-Butadiene, Ethylene Oxide and Vinyl Halides
(Vinyl Fluoride, Vinyl Chloride and Vinyl Bromide) Volume 97, World
Health Organization, Lyon, France.
\658\ NTP. (2014). 13th Report on Carcinogens. Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public
Health Service, National Toxicology Program.
\659\ U.S. EPA. (2002). ``Full IRIS Summary for 1,3-butadiene
(CASRN 106-99-0)'' Environmental Protection Agency, Integrated Risk
Information System (IRIS), Research and Development, National Center
for Environmental Assessment, Washington, DC https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=139 (Last accessed
July 10, 2018).
\660\ Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996).
Subchronic toxicity of 4-vinylcyclohexene in rats and mice by
inhalation. Fundamental Applied Toxicology. 32:1-10.
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(d) Formaldehyde
In 1991, EPA concluded that formaldehyde is a carcinogen based on
nasal tumors in animal bioassays.\661\ An Inhalation URE for cancer and
a Reference Dose for oral noncancer effects were developed by the
agency and posted on the IRIS database. Since that time, the National
Toxicology Program (NTP) and International Agency for Research on
Cancer (IARC) have concluded that formaldehyde is a known human
carcinogen.\662\ \663\
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\661\ EPA. Integrated Risk Information System. Formaldehyde
(CASRN 50-00-0) https://cfpub.epa.gov/ncea/iris/iris_documents/documents/subst/0419_summary.pdf (Last accessed July 2018).
\662\ NTP. (2014). 13th Report on Carcinogens. Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public
Health Service, National Toxicology Program.
\663\ IARC Monographs on the Evaluation of Carcinogenic Risks to
Humans Volume 100F (2012): Formaldehyde.
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The conclusions by IARC and NTP reflect the results of
epidemiologic research published since 1991 in combination with
previous animal, human and mechanistic evidence. Research conducted by
the National Cancer Institute reported an increased risk of
nasopharyngeal cancer and specific lymph hematopoietic malignancies
among workers exposed to formaldehyde.\664\ \665\ \666\ A National
Institute of Occupational Safety and Health study of garment workers
also reported increased risk of death due to leukemia among workers
exposed to formaldehyde.\667\ Extended follow-up of a cohort of British
chemical workers did not report evidence of an increase in
nasopharyngeal or lymph hematopoietic cancers, but a continuing
statistically significant excess in lung cancers was reported.\668\
Finally, a study of embalmers reported formaldehyde exposures to be
associated with an increased risk of myeloid leukemia but not brain
cancer.\669\
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\664\ Hauptmann, M., Lubin, J. H., Stewart, P. A., Hayes, R. B.,
& Blair, A. 2003. Mortality from lymphohematopoetic malignancies
among workers in formaldehyde industries. Journal of the National
Cancer Institute 95: 1615-1623.
\665\ Hauptmann, M., Lubin, J. H., Stewart, P. A., Hayes, R. B.,
& Blair, A. 2004. Mortality from solid cancers among workers in
formaldehyde industries. American Journal of Epidemiology 159: 1117-
1130.
\666\ Beane Freeman, L. E., Blair, A., Lubin, J. H., Stewart, P.
A., Hayes, R. B., Hoover, R. N., & Hauptmann, M. 2009. Mortality
from lymph hematopoietic malignancies among workers in formaldehyde
industries: The National Cancer Institute cohort. Journal of the
National Cancer Institute. 101: 751-761.
\667\ Pinkerton, L. E. 2004. Mortality among a cohort of garment
workers exposed to formaldehyde: an update. Occupational
Environmental Medicine 61: 193-200.
\668\ Coggon, D., Harris, E. C. Poole, J., & Palmer, K. T. 2003.
Extended follow-up of a cohort of British chemical workers exposed
to formaldehyde. Journal of the National Cancer Institute. 95:1608-
1615.
\669\ Hauptmann, M., Stewart P. A., Lubin J. H., Beane Freeman,
L. E., Hornung, R. W., Herrick, R. F., Hoover, R. N., Fraumeni, J.
F., & Hayes, R. B. 2009. Mortality from lymph hematopoietic
malignancies and brain cancer among embalmers exposed to
formaldehyde. Journal of the National Cancer Institute 101:1696-
1708.
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Health effects of formaldehyde in addition to cancer were reviewed
by the Agency for Toxics Substances and
[[Page 43342]]
Disease Registry in 1999,\670\ supplemented in 2010,\671\ and by the
World Health Organization.\672\ These organizations reviewed the
scientific literature concerning health effects linked to formaldehyde
exposure to evaluate hazards and dose response relationships and
defined exposure concentrations for minimal risk levels (MRLs). The
health endpoints reviewed included sensory irritation of eyes and
respiratory tract, reduced pulmonary function, nasal histopathology,
and immune system effects. In addition, research on reproductive and
developmental effects and neurological effects were discussed along
with several studies that suggest that formaldehyde may increase the
risk of asthma, particularly in the young.
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\670\ ATSDR. 1999. Toxicological Profile for Formaldehyde, U.S.
Department of Health and Human Services (HHS), July 1999.
\671\ ATSDR. 2010. Addendum to the Toxicological Profile for
Formaldehyde. U.S. Department of Health and Human Services (HHS),
October 2010.
\672\ IPCS. 2002. Concise International Chemical Assessment
Document 40. Formaldehyde. World Health Organization.
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EPA released a draft Toxicological Review of Formaldehyde--
Inhalation Assessment through the IRIS program for peer review by the
National Research Council (NRC) and public comment in June 2010.\673\
The draft assessment reviewed more recent research from animal and
human studies on cancer and other health effects. The NRC released
their review report in April 2011.\674\ EPA is currently developing a
revised draft assessment in response to this review.
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\673\ EPA (U.S. Environmental Protection Agency). 2010.
Toxicological Review of Formaldehyde (CAS No. 50-00-0)--Inhalation
Assessment: In Support of Summary Information on the Integrated Risk
Information System (IRIS). External Review Draft. EPA/635/R-10/002A.
U.S. Environmental Protection Agency, Washington DC [online].
Available: http://cfpub.epa.gov/ncea/irs_drats/recordisplay.cfm?deid=223614.
\674\ NRC (National Research Council). 2011. Review of the
Environmental Protection Agency's Draft IRIS Assessment of
Formaldehyde. Washington DC: National Academies Press. http://books.nap.edu/openbook.php?record_id=13142.
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(e) Acetaldehyde
Acetaldehyde is classified in EPA's IRIS database as a probable
human carcinogen, based on nasal tumors in rats, and is considered
toxic by the inhalation, oral, and intravenous routes.\675\ The URE in
IRIS for acetaldehyde is 2.2 x 10\-6\ per [micro]g/m\3\.\676\
Acetaldehyde is reasonably anticipated to be a human carcinogen by the
U.S. DHHS in the 13th Report on Carcinogens and is classified as
possibly carcinogenic to humans (Group 2B) by the IARC.\677\ \678\
Acetaldehyde is currently listed on the IRIS Program Multi-Year Agenda
for reassessment within the next few years.
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\675\ U.S. EPA (1991). Integrated Risk Information System File
of Acetaldehyde. Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available
electronically at http://www3.epa.gov/iris/subst/0290.htm.
\676\ U.S. EPA (1991). Integrated Risk Information System File
of Acetaldehyde. This material is available electronically at http://www3.epa.gov/iris/subst/0290.htm.
\677\ NTP. (2014). 13th Report on Carcinogens. Research Triangle
Park, NC: U.S. Department of Health and Human Services, Public
Health Service, National Toxicology Program.
\678\ International Agency for Research on Cancer (IARC).
(1999). Re-evaluation of some organic chemicals, hydrazine, and
hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic
Risk of Chemical to Humans, Vol 71. Lyon, France.
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The primary noncancer effects of exposure to acetaldehyde vapors
include irritation of the eyes, skin, and respiratory tract.\679\ In
short-term (four week) rat studies, degeneration of olfactory
epithelium was observed at various concentration levels of acetaldehyde
exposure.\680\ \681\ Data from these studies were used by EPA to
develop an inhalation reference concentration of 9 [micro]g/m\3\. Some
asthmatics have been shown to be a sensitive subpopulation to
decrements in functional expiratory volume (FEV1 test) and
bronchoconstriction upon acetaldehyde inhalation.\682\
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\679\ U.S. EPA (1991). Integrated Risk Information System File
of Acetaldehyde. This material is available electronically at http://www3.epa.gov/iris/subst/0290.htm.
\680\ U.S. EPA. (2003). Integrated Risk Information System File
of Acrolein. Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available
electronically at http://www3.epa.gov/iris/subst/0364.htm.
\681\ Appleman, L.M., Woutersen, R. A., & Feron, V. J. (1982).
Inhalation toxicity of acetaldehyde in rats. I. Acute and subacute
studies. Toxicology. 23: 293-297.
\682\ Myou, S., Fujimura, M., Nishi, K., Ohka, T., & Matsuda, T.
(1993) Aerosolized acetaldehyde induces histamine-mediated
bronchoconstriction in asthmatics. Am. Rev. Respir. Dis. 148(4 Pt
1): 940-943.
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(f) Acrolein
EPA most recently evaluated the toxicological and health effects
literature related to acrolein in 2003 and concluded that the human
carcinogenic potential of acrolein could not be determined because the
available data were inadequate. No information was available on the
carcinogenic effects of acrolein in humans and the animal data provided
inadequate evidence of carcinogenicity.\683\ The IARC determined in
1995 that acrolein was not classifiable as to its carcinogenicity in
humans.\684\
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\683\ U.S. EPA. (2003). Integrated Risk Information System File
of Acrolein. Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available
at http://www3.epa.gov/iris/subst/0364.htm.
\684\ International Agency for Research on Cancer (IARC).
(1995). Monographs on the evaluation of carcinogenic risk of
chemicals to humans, Volume 63. Dry cleaning, some chlorinated
solvents and other industrial chemicals, World Health Organization,
Lyon, France.
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Lesions to the lungs and upper respiratory tract of rats, rabbits,
and hamsters have been observed after subchronic exposure to
acrolein.\685\ The agency has developed an RfC for acrolein of 0.02
[micro]g/m\3\ and an RfD of 0.5 [micro]g/kg-day.\686\
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\685\ U.S. EPA. (2003). Integrated Risk Information System File
of Acrolein. Office of Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available
at http://www3.epa.gov/iris/subst/0364.htm.
\686\ U.S. EPA. (2003). Integrated Risk Information System File
of Acrolein. Office of Research and Development, National Center for
Environmental Assessment, Washington, DC. This material is available
at http://www3.epa.gov/iris/subst/0364.htm.
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Acrolein is extremely acrid and irritating to humans when inhaled,
with acute exposure resulting in upper respiratory tract irritation,
mucus hypersecretion and congestion. The intense irritancy of this
carbonyl has been demonstrated during controlled tests in human
subjects, who suffer intolerable eye and nasal mucosal sensory
reactions within minutes of exposure.\687\ These data and additional
studies regarding acute effects of human exposure to acrolein are
summarized in EPA's 2003 Toxicological Review of Acrolein.\688\ Studies
in humans indicate that levels as low as 0.09 ppm (0.21 mg/m3) for five
minutes may elicit subjective complaints of eye irritation with
increasing concentrations leading to more extensive eye, nose and
respiratory symptoms. Acute exposures in animal studies report
bronchial hyper-responsiveness. Based on animal data (more pronounced
respiratory irritancy in mice with allergic airway disease in
comparison to non-diseased mice \689\) and demonstration of similar
effects in humans (e.g., reduction in
[[Page 43343]]
respiratory rate), individuals with compromised respiratory function
(e.g., emphysema, asthma) are expected to be at increased risk of
developing adverse responses to strong respiratory irritants such as
acrolein. EPA does not currently have an acute reference concentration
for acrolein. The available health effect reference values for acrolein
have been summarized by EPA and include an ATSDR MRL for acute exposure
to acrolein of 7 [micro]g/m\3\ for 1-14 days' exposure; and Reference
Exposure Level (REL) values from the California Office of Environmental
Health Hazard Assessment (OEHHA) for one-hour and 8-hour exposures of
2.5 [micro]g/m\3\ and 0.7 [micro]g/m\3\, respectively.\690\
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\687\ U.S. EPA. (2003) Toxicological review of acrolein in
support of summary information on Integrated Risk Information System
(IRIS) National Center for Environmental Assessment, Washington, DC.
EPA/635/R-03/003. p. 10. Available online at: http://www3.epa.gov/ncea/iris/toxreviews/0364tr.pdf.
\688\ U.S. EPA. (2003) Toxicological review of acrolein in
support of summary information on Integrated Risk Information System
(IRIS) National Center for Environmental Assessment, Washington, DC.
EPA/635/R-03/003. Available online at: https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=51977 (Last accessed July 10 2018).
\689\ Morris, J. B., Symanowicz, P. T., Olsen, J. E., et al.
(2003). Immediate sensory nerve-mediated respiratory responses to
irritants in healthy and allergic airway-diseased mice. Journal of
Applied Physiology. 94(4):1563-1571.
\690\ U.S. EPA. (2009). Graphical Arrays of Chemical-Specific
Health Effect Reference Values for Inhalation Exposures (Final
Report). U.S. Environmental Protection Agency, Washington, DC, EPA/
600/R-09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003 (last accessed July 10 2018).
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(g) Polycyclic Organic Matter
The term polycyclic organic matter (POM) defines a broad class of
compounds that includes the polycyclic aromatic hydrocarbon compounds
(PAHs). One of these compounds, naphthalene, is discussed separately
below. POM compounds are formed primarily from combustion and are
present in the atmosphere in gas and particulate form. Cancer is the
major concern from exposure to POM. Epidemiologic studies have reported
an increase in lung cancer in humans exposed to diesel exhaust, coke
oven emissions, roofing tar emissions, and cigarette smoke; all of
these mixtures contain POM compounds.\691\ \692\ Animal studies have
reported respiratory tract tumors from inhalation exposure to
benzo[a]pyrene and alimentary tract and liver tumors from oral exposure
to benzo[a]pyrene.\693\ In 1997 EPA classified seven PAHs
(benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene,
benzo[k]fluoranthene, dibenz[a,h]anthracene, and indeno[1,2,3-
cd]pyrene) as Group B2, probable human carcinogens.\694\ Since that
time, studies have found that maternal exposures to PAHs in a
population of pregnant women were associated with several adverse birth
outcomes, including low birth weight and reduced length at birth, as
well as impaired cognitive development in preschool children (three
years of age).\695\ \696\ These and similar studies are being evaluated
as a part of the ongoing IRIS reassessment of health effects associated
with exposure to benzo[a]pyrene.
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\691\ Agency for Toxic Substances and Disease Registry (ATSDR).
(1995). Toxicological profile for Polycyclic Aromatic Hydrocarbons
(PAHs). Atlanta, GA: U.S. Department of Health and Human Services,
Public Health Service. Available electronically at http://www.atsdr.cdc.gov/ToxProfiles/TP.asp?id=122&tid=25.
\692\ U.S. EPA (2002). Health Assessment Document for Diesel
Engine Exhaust. EPA/600/8-90/057F Office of Research and
Development, Washington DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=29060 (last accessed July 10 2018).
\693\ International Agency for Research on Cancer (IARC).
(2012). Monographs on the Evaluation of the Carcinogenic Risk of
Chemicals for Humans, Chemical Agents and Related Occupations. Vol.
100F. Lyon, France.
\694\ U.S. EPA (1997). Integrated Risk Information System File
of indeno (1,2,3-cd) pyrene. Research and Development, National
Center for Environmental Assessment, Washington, DC. This material
is available electronically at https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=2776 (Last accessed July 10 2018).
\695\ Perera, F. P., Rauh, V., Tsai, W. Y., et al. (2002).
Effect of transplacental exposure to environmental pollutants on
birth outcomes in a multiethnic population. Environmental Health
Perspectives. 111: 201-205.
\696\ Perera, F. P., Rauh, V., Whyatt, R. M., Tsai, W. Y., Tang,
D., Diaz, D., Hoepner, L., Barr, D., Tu, Y. H., Camann, D., &
Kinney, P. (2006). Effect of prenatal exposure to airborne
polycyclic aromatic hydrocarbons on neurodevelopment in the first 3
years of life among inner-city children. Environmental Health
Perspectives. 114: 1287-1292.
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(h) Naphthalene
Naphthalene is found in small quantities in gasoline and diesel
fuels. Naphthalene emissions have been measured in larger quantities in
both gasoline and diesel exhaust compared with evaporative emissions
from mobile sources, indicating it is primarily a product of
combustion. Acute (short-term) exposure of humans to naphthalene by
inhalation, ingestion, or dermal contact is associated with hemolytic
anemia and damage to the liver and the nervous system.\697\ Chronic
(long term) exposure of workers and rodents to naphthalene has been
reported to cause cataracts and retinal damage.\698\ EPA released an
external review draft of a reassessment of the inhalation
carcinogenicity of naphthalene based on a number of recent animal
carcinogenicity studies. The draft reassessment completed external peer
review.\699\ Based on external peer review comments received, a revised
draft assessment that considers all routes of exposure, as well as
cancer and noncancer effects, is under development. The external review
draft does not represent official agency opinion and was released
solely for the purposes of external peer review and public comment. The
National Toxicology Program listed naphthalene as ``reasonably
anticipated to be a human carcinogen'' in 2004 on the basis of
bioassays reporting clear evidence of carcinogenicity in rats and some
evidence of carcinogenicity in mice.\700\ California EPA has released a
new risk assessment for naphthalene, and the IARC has reevaluated
naphthalene and re-classified it as Group 2B: Possibly carcinogenic to
humans.\701\
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\697\ U. S. EPA. 1998. Toxicological Review of Naphthalene
(Reassessment of the Inhalation Cancer Risk), Environmental
Protection Agency, Integrated Risk Information System, Research and
Development, National Center for Environmental Assessment,
Washington, DC. This material is available electronically at https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/0436tr.pdf (last accessed July 10 2018).
\698\ U. S. EPA. 1998. Toxicological Review of Naphthalene
(Reassessment of the Inhalation Cancer Risk), Environmental
Protection Agency, Integrated Risk Information System, Research and
Development, National Center for Environmental Assessment,
Washington, DC. This material is available electronically at https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/0436tr.pdf (last accessed July 10 2018)
\699\ Oak Ridge Institute for Science and Education. (2004).
External Peer Review for the IRIS Reassessment of the Inhalation
Carcinogenicity of Naphthalene. August 2004. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=84403.
\700\ NTP. (2014). 13th Report on Carcinogens. U.S. Department
of Health and Human Services, Public Health Service, National
Toxicology Program.
\701\ International Agency for Research on Cancer (IARC).
(2002). Monographs on the Evaluation of the Carcinogenic Risk of
Chemicals for Humans. Vol. 82. Lyon, France.
---------------------------------------------------------------------------
Naphthalene also causes a number of chronic non-cancer effects in
animals, including abnormal cell changes and growth in respiratory and
nasal tissues. The current EPA IRIS assessment includes noncancer data
on hyperplasia and metaplasia in nasal tissue that form the basis of
the inhalation RfC of 3 [micro]g/m\3\.\702\ The ATSDR MRL for acute
exposure to naphthalene is 0.6 mg/kg/day.
---------------------------------------------------------------------------
\702\ U.S. EPA. (1998). Toxicological Review of Naphthalene.
Environmental Protection Agency, Integrated Risk Information System
(IRIS), Research and Development, National Center for Environmental
Assessment, Washington, DC https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/0436tr.pdf (last accessed July
10 2018).
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(i) Other Air Toxics
In addition to the compounds described above, other compounds in
gaseous hydrocarbon and PM emissions from motor vehicles will be
affected by this action. Mobile source air toxic compounds that will
potentially be impacted include ethylbenzene, propionaldehyde, toluene,
and xylene. Information regarding the health effects of these compounds
can be found in EPA's IRIS database.\703\
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\703\ U.S. EPA Integrated Risk Information System (IRIS)
database is available at: https://www.epa.gov/iris (last accessed
July 10 2018)
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[[Page 43344]]
(j) Exposure and Health Effects Associated With Traffic
Locations in close proximity to major roadways generally have
elevated concentrations of many air pollutants emitted from motor
vehicles. Hundreds of such studies have been published in peer-reviewed
journals, concluding that concentrations of CO, NO, NO2,
benzene, aldehydes, particulate matter, black carbon, and many other
compounds are elevated in ambient air within approximately 300-600
meters (approximately 1,000-2,000 feet) of major roadways. Highest
concentrations of most pollutants emitted directly by motor vehicles
are found at locations within 50 meters (approximately 165 feet) of the
edge of a roadway's traffic lanes.
A large-scale review of air quality measurements in the vicinity of
major roadways between 1978 and 2008 concluded that the pollutants with
the steepest concentration gradients in vicinities of roadways were CO,
ultrafine particles, metals, elemental carbon (EC), NO, NOX,
and several VOCs.\704\ These pollutants showed a large reduction in
concentrations within 100 meters downwind of the roadway. Pollutants
that showed more gradual reductions with distance from roadways
included benzene, NO2, PM2.5, and
PM10. In the review article, results varied based on the
method of statistical analysis used to determine the trend.
---------------------------------------------------------------------------
\704\ Karner, A. A., Eisinger, D. S., & Niemeier, D. A. (2010).
Near-roadway air quality: synthesizing the findings from real-world
data. Environmental Science Technology. 44: 5334-5344.
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For pollutants with relatively high background concentrations
relative to near-road concentrations, detecting concentration gradients
can be difficult. For example, many aldehydes have high background
concentrations as a result of photochemical breakdown of precursors
from many different organic compounds. This can make detection of
gradients around roadways and other primary emission sources difficult.
However, several studies have measured aldehydes in multiple weather
conditions and found higher concentrations of many carbonyls downwind
of roadways.\705\ \706\ These findings suggest a substantial roadway
source of these carbonyls.
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\705\ Liu, W., Zhang, J., Kwon, J. et al. (2006). Concentrations
and source characteristics of airborne carbonyl comlbs measured
outside urban residences. Journal of the Air Waste Management
Assocication 56: 1196-1204.
\706\ Cahill, T. M., Charles, M. J., & Seaman, V. Y. (2010).
Development and application of a sensitive method to determine
concentrations of acrolein and other carbonyls in ambient air.
Health Effects Institute Research Report 149.Available at https://www.healtheffects.org/publication/development-and-application-sensitive-method-determine-concentrations-acrolein-and-other (last
accessed July 10 2018)
---------------------------------------------------------------------------
In the past 15 years, many studies have been published with results
reporting that populations who live, work, or go to school near high-
traffic roadways experience higher rates of numerous adverse health
effects, compared to populations far away from major roads.\707\ In
addition, numerous studies have found adverse health effects associated
with spending time in traffic, such as commuting or walking along high-
traffic roadways; however, it is difficult to fully control for
confounding in such studies.\708\ \709\ \710\ \711\ The health outcomes
with the strongest evidence linking them with traffic-associated air
pollutants are respiratory effects, particularly in asthmatic children,
and cardiovascular effects.
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\707\ In the widely-used PubMed database of health publications,
between January 1, 1990 and August 18, 2011, 605 publications
contained the keywords ``traffic, pollution, epidemiology,'' with
approximately half the studies published after 2007.
\708\ Laden, F., Hart, J. E., Smith, T. J., Davis, M. E., &
Garshick, E. (2007) Cause-specific mortality in the unionized U.S.
trucking industry. Environmental Health Perspectives 115:1192-1196.
\709\ Peters, A., von Klot, S., Heier, M., Trentinaglia, I.,
H[ouml]rmann, A., Wichmann, H. E., & L[ouml]wel, H. (2004) Exposure
to traffic and the onset of myocardial infarction. New England
Journal of Medicine. 351: 1721-1730.
\710\ Zanobetti, A., Stone, P. H., Spelzer, F. E., Schwartz, J.
D., Coull, B. A., Suh, H. H., Nearling, B. D., Mittleman, M. A.,
Verrier, R. L., & Gold, D. R. (2009) T-wave alternans, air pollution
and traffic in high-risk subjects. American Journal of Cardiology.
104: 665-670.
\711\ Dubowsky Adar, S., Adamkiewicz, G., Gold, D. R., Schwartz,
J., Coull, B. A., & Suh, H. (2007) Ambient and microenvironmental
particles and exhaled nitric oxide before and after a group bus
trip. Environmental Health Perspectives. 115: 507-512.
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Numerous reviews of this body of health literature have been
published as well. In 2010, an expert panel of the Health Effects
Institute (HEI) published a review of hundreds of exposure,
epidemiology, and toxicology studies.\712\ The panel rated how the
evidence for each type of health outcome supported a conclusion of a
causal association with traffic-associated air pollution as either
``sufficient,'' ``suggestive but not sufficient,'' or ``inadequate and
insufficient.'' The panel categorized evidence of a causal association
for exacerbation of childhood asthma as ``sufficient.'' The panel
categorized evidence of a causal association for new onset asthma as
between ``sufficient'' and ``suggestive but not sufficient.''
``Suggestive of a causal association'' was how the panel categorized
evidence linking traffic-associated air pollutants with exacerbation of
adult respiratory symptoms and lung function decrement. It categorized
as ``inadequate and insufficient'' evidence of a causal relationship
between traffic-related air pollution and health care utilization for
respiratory problems, new onset adult asthma, chronic obstructive
pulmonary disease (COPD), nonasthmatic respiratory allergy, and cancer
in adults and children. Other literature reviews have been published
with conclusions generally similar to the HEI panel's.\713\ \714\ \715\
\716\ However, in 2014, researchers from the U.S. Centers for Disease
Control and Prevention (CDC) published a systematic review and meta-
analysis of studies evaluating the risk of childhood leukemia
associated with traffic exposure and reported positive associations
between ``postnatal'' proximity to traffic and leukemia risks, but no
such association for ``prenatal'' exposures.\717\
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\712\ Health Effects Institute Panel on the Health Effects of
Traffic-Related Air Pollution. (2010). Traffic-related air
pollution: A critical review of the literature on emissions,
exposure, and health effects. HEI Special Report 17. Available at
http://www.healtheffects.org.
\713\ Boothe, V. L. & Shendell, D. G. (2008). Potential health
effects associated with residential proximity to freeways and
primary roads: review of scientific literature, 1999-2006. Journal
of Environmental Health. 70: 33-41.
\714\ Salam, M. T., Islam, T., & Gilliland, F. D. (2008). Recent
evidence for adverse effects of residential proximity to traffic
sources on asthma. Curr Opin Pulm Med 14: 3-8.
\715\ Sun, X., Zhang, S., & Ma, X. (2014) No association between
traffic density and risk of childhood leukemia: a meta-analysis.
Asia Pacific Journal of Cancer Prevention. 15: 5229-5232.
\716\ Raaschou-Nielsen, O. & Reynolds, P. (2006). Air pollution
and childhood cancer: A review of the epidemiological literature.
International Journal of Cancer. 118: 2920-9.
\717\ Boothe, V. L., Boehmer, T. K., Wendel, A. M., & Yip, F. Y.
(2014) Residential traffic exposure and childhood leukemia: a
systematic review and meta-analysis. American Journal of
Preventative Medicine. 46: 413-422.
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Health outcomes with few publications suggest the possibility of
other effects still lacking sufficient evidence to draw definitive
conclusions. Among these outcomes with a small number of positive
studies are neurological impacts (e.g., autism and reduced cognitive
function) and reproductive outcomes (e.g., preterm
[[Page 43345]]
birth, low birth weight).\718\ \719\ \720\ \721\
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\718\ Volk, H. E., Hertz-Picciotto, I., Delwiche, L., et al.
(2011). Residential proximity to freeways and autism in the CHARGE
study. Environmental Health Perspectives. 119: 873-877.
\719\ Franco-Suglia, S., Gryparis, A., Wright, R. O., et al.
(2007). Association of black carbon with cognition among children in
a prospective birth cohort study. American Journal of Epidemiology.
doi: 10.1093/aje/kwm308. [Online at http://dx.doi.org].
\720\ Power, M. C., Weisskopf, M. G., Alexeef, S. E., et al.
(2011). Traffic-related air pollution and cognitive function in a
cohort of older men. Environmental Health Perspectives. 2011: 682-
687.
\721\ Wu, J., Wilhelm, M., Chung, J., et al. (2011). Comparing
exposure assessment methods for traffic-related air pollution in and
adverse pregnancy outcome study. Environmental Research. 111: 685-
6692.
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In addition to health outcomes, particularly cardiopulmonary
effects, conclusions of numerous studies suggest mechanisms by which
traffic-related air pollution affects health. Numerous studies indicate
that near-roadway exposures may increase systemic inflammation,
affecting organ systems, including blood vessels and lungs.\722\ \723\
\724\ \725\ Long-term exposures in near-road environments have been
associated with inflammation-associated conditions, such as
atherosclerosis and asthma.\726\ \727\ \728\
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\722\ Riediker, M. (2007). Cardiovascular effects of fine
particulate matter components in highway patrol officers. Inhal
Toxicol 19: 99-105. doi: 10.1080/08958370701495238 Available at
http://dx.doi.org.
\723\ Alexeef, S. E., Coull, B. A., Gryparis, A., et al. (2011).
Medium-term exposure to traffic-related air pollution and markers of
inflammation and endothelial function. Environmental Health
Perspectives. 119: 481-486. doi:10.1289/ehp.1002560 Available at
http://dx.doi.org.
\724\ Eckel, S. P., Berhane, K., Salam, M. T., et al. (2011).
Traffic-related pollution exposure and exhaled nitric oxide in the
Children's Health Study. Environmental Health Perspectives. (IN
PRESS). doi:10.1289/ehp.1103516. Available at http://dx.doi.org.
\725\ Zhang, J., McCreanor, J. E., Cullinan, P., et al. (2009).
Health effects of real-world exposure diesel exhaust in persons with
asthma. Res Rep Health Effects Inst 138. [Online at http://www.healtheffects.org].
\726\ Adar, S. D., Klein, R., Klein, E. K., et al. (2010). Air
pollution and the microvasculatory: a cross-sectional assessment of
in vivo retinal images in the population-based Multi-Ethnic Study of
Atherosclerosis. PLoS Med 7(11): E1000372. doi:10.1371/
journal.pmed.1000372. Available at http://dx.doi.org.
\727\ Kan, H., Heiss, G., Rose, K. M., et al. (2008).
Prospective analysis of traffic exposure as a risk factor for
incident coronary heart disease: the Atherosclerosis Risk in
Communities (ARIC) study. Environmental Health Perspectives. 116:
1463-1468. doi:10.1289/ehp.11290. Available at http://dx.doi.org.
\728\ McConnell, R., Islam, T., Shankardass, K., et al. (2010).
Childhood incident asthma and traffic-related air pollution at home
and school. Environmental Health Perspectives. 1021-1026.
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Several studies suggest that some factors may increase
susceptibility to the effects of traffic-associated air pollution.
Several studies have found stronger respiratory associations in
children experiencing chronic social stress, such as in violent
neighborhoods or in homes with high family stress.\729\ \730\ \731\
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\729\ Islam, T., Urban, R., Gauderman, W. J., et al. (2011).
Parental stress increases the detrimental effect of traffic exposure
on children's lung function. American Journal of Respiratory
Critical Care Medicine. (In press).
\730\ Clougherty, J. E., Levy, J. I., Kubzansky, L. D., et al.
(2007). Synergistic effects of traffic-related air pollution and
exposure to violence on urban asthma etiology. Environmental Health
Perspectives. 115: 1140-1146.
\731\ Chen, E., Schrier, H. M., Strunk, R. C., et al. (2008).
Chronic traffic-related air pollution and stress interact to predict
biologic and clinical outcomes in asthma. Environmental Health
Perspectives. 116: 970-5.
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The risks associated with residence, workplace, or schools near
major roads are of potentially high public health significance due to
the large population in such locations. According to the 2009 American
Housing Survey, more than 22 million homes (17% of all U.S. housing
units) were located within 300 feet of an airport, railroad, or highway
with four or more lanes. This corresponds to a population of more than
50 million U.S. residents in close proximity to high-traffic roadways
or other transportation sources. Based on 2010 Census data, a 2013
publication estimated that 19% of the U.S. population (more than 59
million people) lived within 500 meters of roads with at least 25,000
annual average daily traffic (AADT), while about 3.2% of the population
lived within 100 meters (about 300 feet) of such roads.\732\ Another
2013 study estimated that 3.7% of the U.S. population (about 11.3
million people) lived within 150 meters (about 500 feet) of interstate
highways or other freeways and expressways.\733\ On average,
populations near major roads have higher fractions of minority
residents and lower socioeconomic status. Furthermore, on average,
Americans spend more than an hour traveling each day, bringing nearly
all residents into a high-exposure microenvironment for part of the
day.
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\732\ Rowangould, G. M. (2013) A census of the U.S. near-roadway
population: public health and environmental justice considerations.
Transportation Research Part D 25: 59-67.
\733\ Boehmer, T. K., Foster, S. L., Henry, J. R., Woghiren-
Akinnifesi, E. L., & Yip, F. Y. (2013) Residential proximity to
major highways--United States, 2010. Morbidity and Mortality Weekly
Report 62 (3); 46-50.
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In light of these concerns, EPA has required through the NAAQS
process that air quality monitors be placed near high-traffic roadways
for determining concentrations of CO, NO2, and
PM2.5 (in addition to those existing monitors located in
neighborhoods and other locations farther away from pollution sources).
Near-roadway monitors for NO2 begin operation between 2014
and 2017 in Core Based Statistical Areas (CBSAs) with population of at
least 500,000. Monitors for CO and PM2.5 begin operation
between 2015 and 2017. These monitors will further our understanding of
exposure in these locations.
EPA and DOT continue to research near-road air quality, including
the types of pollutants found in high concentrations near major roads
and health problems associated with the mixture of pollutants near
roads.
8. Environmental Justice
Environmental justice (EJ) is a principle asserting that all people
deserve fair treatment and meaningful involvement with respect to
environmental laws, regulations, and policies. EPA seeks to provide the
same degree of protection from environmental health hazards for all
people. DOT shares this goal and is informed about the potential
environmental impacts of its rulemakings through its NEPA process (see
NHTSA's DEIS). As referenced below, numerous studies have found that
some environmental hazards are more prevalent in areas where non-white,
Hispanic and people with low socioeconomic status (SES) represent a
higher fraction of the population compared with the general population.
In addition, compared to non-Hispanic whites, some subpopulations
defined by race and ethnicity have been shown to have greater levels of
some health conditions during some life stages. For example, in 2014,
about 13% of Black, non-Hispanic and 24% of Puerto Rican children were
estimated to currently have asthma, compared with eight percent of
white, non-Hispanic children.\734\
---------------------------------------------------------------------------
\734\ http://www.cdc.gov/asthma/most_recent_data.htm.
---------------------------------------------------------------------------
As discussed in the DEIS, concentrations of many air pollutants are
elevated near high-traffic roadways. If minority populations and low-
income populations disproportionately live near such roads, then an
issue of EJ may be present. We reviewed existing scholarly literature
examining the potential for disproportionate exposure among people with
low SES, and we conducted our own evaluation of two national datasets:
The U.S. Census Bureau's American Housing Survey for calendar year 2009
and the U.S. Department of Education's database of school locations.
Publications that address EJ issues generally report that
populations living near major roadways (and other types of
[[Page 43346]]
transportation infrastructure) tend to be composed of larger fractions
of nonwhite residents. People living in neighborhoods near such sources
of air pollution also tend to be lower in income than people living
elsewhere. Numerous studies evaluating the demographics and
socioeconomic status of populations or schools near roadways have found
that they include a greater percentage of minority residents, as well
as lower SES (indicated by variables such as median household income).
Locations in these studies include Los Angeles, CA; Seattle, WA; Wayne
County, MI; Orange County, FL; and California \735\ \736\ \737\ \738\
\739\ \740\ Such disparities may be due to multiple factors.\741\
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\735\ Marshall, J. D. (2008) Environmental inequality: air
pollution exposures in California's South Coast Air Basin.
\736\ Su, J. G., Larson, T., Gould, T., Cohen, M., & Buzzelli,
M. (2010) Transboundary air pollution and environmental justice:
Vancouver and Seattle compared. GeoJournal 57: 595-608. doi:10.1007/
s10708-009-9269-6 [Online at http://dx.doi.org].
\737\ Chakraborty, J. & Zandbergen, P. A. (2007) Children at
risk: measuring racial/ethnic disparities in potential exposure to
air pollution at school and home. Journal of Epidemiol Community
Health 61: 1074-1079. doi: 10.1136/jech.2006.054130 [Online at
http://dx.doi.org].
\738\ Green, R. S., Smorodinsky, S., Kim, J. J., McLaughlin, R.,
& Ostro, B. (2003) Proximity of California public schools to busy
roads. Environmental Health Perspectives. 112: 61-66. doi:10.1289/
ehp.6566 [http://dx.doi.org].
\739\ Wu, Y. & Batterman, S. A. (2006) Proximity of schools in
Detroit, Michigan to automobile and truck traffic. Journal of
Exposure Science & Environmental Epidemiology. doi:10.1038/
sj.jes.7500484 [Online at http://dx.doi.org].
\740\ Su, J. G., Jerrett, M., de Nazelle, A., & Wolch, J. (2011)
Does exposure to air pollution in urban parks have socioeconomic,
racial, or ethnic gradients? Environmental Research. 111: 319-328.
\741\ Depro, B. & Timmins, C. (2008) Mobility and environmental
equity: do housing choices determine exposure to air pollution?
North Caroline State University Center for Environmental and
Resource Economic Policy
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People with low SES often live in neighborhoods with multiple
environmental stressors and higher rates of health risk factors,
including reduced health insurance coverage rates, higher smoking and
drug use rates, limited access to fresh food, visible neighborhood
violence, and elevated rates of obesity and some diseases such as
asthma, diabetes, and ischemic heart disease. Although questions
remain, several studies find stronger associations between air
pollution and health in locations with such chronic neighborhood
stress, suggesting that populations in these areas may be more
susceptible to the effects of air pollution.\742\ \743\ \744\ \745\
Household-level stressors such as parental smoking and relationship
stress also may increase susceptibility to the adverse effects of air
pollution.\746\ \747\
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\742\ Clougherty, J. E. & Kubzansky, L. D. (2009) A framework
for examining social stress and susceptibility to air pollution in
respiratory health. Environmental Health Perspectives. 117: 1351-
1358. Doi:10.1289/ehp.0900612 [Online at http://dx.doi.org].
\743\ Clougherty, J. E., Levy, J. I., Kubzansky, L. D., Ryan, P.
B., Franco Suglia, S., Jacobson Canner, M., & Wright, R. J. (2007)
Synergistic effects of traffic-related air pollution and exposure to
violence on urban asthma etiology. Environmental Health
Perspectives. 115: 1140-1146. doi:10.1289/ehp.9863 [Online at http://dx.doi.org].
\744\ Finkelstein, M. M., Jerrett, M., DeLuca, P., Finkelstein,
N., Verma, D. K., Chapman, K., & Sears, M. R. (2003) Relation
between income, air pollution and mortality: A cohort study.
Canadian Medical Association Journal. 169: 397-402.
\745\ Shankardass, K., McConnell, R., Jerrett, M., Milam, J.,
Richardson, J., & Berhane, K. (2009) Parental stress increases the
effect of traffic-related air pollution on childhood asthma
incidence. Proc National Academy of Science. 106: 12406-12411.
doi:10.1073/pnas.0812910106 [Online at http://dx.doi.org].
\746\ Lewis, A. S., Sax, S. N., Wason, S. C. & Campleman, S. L
(2011) Non-chemical stressors and cumulative risk assessment: an
overview of current initiatives and potential air pollutant
interactions. International Journal of Environmental Research in
Public Health. 8: 2020-2073. Doi:10.3390/ijerph8062020 [Online at
http://dx.doi.org].
\747\ Rosa, M. J., Jung, K. H., Perzanowski, M. S., Kelvin, E.
A., Darling, K.W., Camann, D. E., Chillrud, S. N., Whyatt, R. M.,
Kinney, P. L., Perera, F. P., & Miller, R. L. (2010) Prenatal
exposure to polycyclic aromatic hydrocarbons, environmental tobacco
smoke and asthma. Respiratory Medicine. (In press). doi:10.1016/
j.rmed.2010.11.022 [Online at http://dx.doi.org].
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Two national databases were analyzed that allowed evaluation of
whether homes and schools were located near a major road and whether
disparities in exposure may be occurring in these environments. The
American Housing Survey (AHS) includes descriptive statistics of over
70,000 housing units across the nation. The study survey is conducted
every two years by the U.S. Census Bureau. The second database we
analyzed was the U.S. Department of Education's Common Core of Data,
which includes enrollment and location information for schools across
the U.S.
In analyzing the 2009 AHS, the focus was on whether or not a
housing unit was located within 300 feet of ``4-or-more lane highway,
railroad, or airport.'' \748\ Whether there were differences between
households in such locations compared with those in locations farther
from these same transportation facilities was analyzed.\749\ Other
variables, such as land use category, region of country, and housing
type were included.
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\748\ This variable primarily represents roadway proximity.
According to the Central Intelligence Agency's World Factbook, in
2010, the United States had 6,506,204 km or roadways, 224,792 km of
railways, and 15,079 airports. Highways thus represent the
overwhelming majority of transportation facilities described by this
factor in the AHS.
\749\ Bailey, C. (2011) Demographic and Social Patterns in
Housing Units Near Large Highways and other Transportation Sources.
Memorandum to docket.
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In examining schools near major roadways, the Common Core of Data
(CCD) from the U.S. Department of Education, which includes information
on all public elementary and secondary schools and school districts
nationwide, was examined.\750\ To determine school proximities to major
roadways, a geographic information system (GIS) to map each school and
roadways based on the U.S. Census's TIGER roadway file was used.\751\
Non-white students were found to be overrepresented at schools within
200 meters of the largest roadways, and schools within 200 meters of
the largest roadways also had higher than expected numbers of students
eligible for free or reduced-price lunches. For example, Black students
represent 22% of students at schools located within 200 meters of a
primary road, whereas Black students represent 17% of students in all
U.S. schools. Hispanic students represent 30% of students at schools
located within 200 meters of a primary road, whereas Hispanic students
represent 22% of students in all U.S. schools.
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\750\ http://nces.ed.gov/ccd/.
\751\ Pedde, M. & Bailey, C. (2011) Identification of Schools
within 200 Meters of U.S. Primary and Secondary Roads. Memorandum to
the docket.
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Overall, there is substantial evidence that people who live or
attend school near major roadways are more likely to be non-white,
Hispanic ethnicity, and/or low SES. The emission reductions from these
proposed standards will likely result in widespread air quality
improvements, but the impact on pollution levels in close proximity to
roadways will be most direct. Thus, these proposed standards will
likely help in mitigating the disparity in racial, ethnic, and
economically based exposures.
9. Environmental Effects of Non-GHG Pollutants
(a) Visibility
Visibility can be defined as the degree to which the atmosphere is
transparent to visible light.\752\ Visibility impairment is caused by
light scattering and absorption by suspended particles and gases.
Visibility is important because it has direct significance to people's
enjoyment of daily activities in all parts of the country. Individuals
value good visibility for the well-being it provides
[[Page 43347]]
them directly, where they live and work, and in places where they enjoy
recreational opportunities. Visibility is also highly valued in
significant natural areas, such as national parks and wilderness areas,
and special emphasis is given to protecting visibility in these areas.
For more information on visibility see the final 2009 PM ISA.\753\
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\752\ National Research Council, (1993). Protecting Visibility
in National Parks and Wilderness Areas. National Academy of Sciences
Committee on Haze in National Parks and Wilderness Areas. National
Academy Press, Washington, DC. This book can be viewed on the
National Academy Press website at http://www.nap.edu/books/0309048443/html/.
\753\ U.S. EPA. (2009). Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F.
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EPA is working to address visibility impairment. Reductions in air
pollution from implementation of various programs associated with the
Clean Air Act Amendments of 1990 (CAAA) provisions have resulted in
substantial improvements in visibility and will continue to do so in
the future. Because trends in haze are closely associated with trends
in particulate sulfate and nitrate due to the relationship between
their concentration and light extinction, visibility trends have
improved as emissions of SO2 and NOX have
decreased over time due to air pollution regulations such as the Acid
Rain Program.\754\
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\754\ U.S. EPA. 2009 Final Report: Integrated Science Assessment
for Particulate Matter. U.S. Environmental Protection Agency,
Washington, DC, EPA/600/R-08/139F, 2009.
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In the Clean Air Act Amendments of 1977, Congress recognized
visibility's value to society by establishing a national goal to
protect national parks and wilderness areas from visibility impairment
caused by manmade pollution.\755\ In 1999, EPA finalized the regional
haze program to protect the visibility in Mandatory Class I Federal
areas.\756\ There are 156 national parks, forests and wilderness areas
categorized as Mandatory Class I Federal areas.\757\ These areas are
defined in CAA Section 162 as those national parks exceeding 6,000
acres, wilderness areas and memorial parks exceeding 5,000 acres, and
all international parks which were in existence on August 7, 1977.
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\755\ See Section 169(a) of the Clean Air Act.
\756\ 64 FR 35714 (July 1, 1999).
\757\ 62 FR 38680-38681 (July 18, 1997).
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EPA has also concluded that PM2.5 can cause adverse
effects on visibility in other areas that are not targeted by the
Regional Haze Rule, such as urban areas, depending on PM2.5
concentrations and other factors such as dry chemical composition and
relative humidity (i.e., an indicator of the water composition of the
particles).\758\ In December 2012, EPA revised the primary (health-
based) PM2.5 standards in order to increase public health
protection. As part of that same review, the EPA generally retained the
secondary (welfare-based) PM2.5 standards, concluding that
the target level of protection against PM-related visibility impairment
would be achieved in areas meeting the existing secondary standards for
PM2.5.
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\758\ 78 FR 3226, January 15, 2013.
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(b) Plant and Ecosystem Effects of Ozone
The welfare effects of ozone can be observed across a variety of
scales, i.e. subcellular, cellular, leaf, whole plant, population and
ecosystem. Ozone can produce both acute and chronic injury in sensitive
species depending on the concentration level and the duration of the
exposure.\759\ In those sensitive species,\760\ effects from repeated
exposure to ozone throughout the growing season of the plant tend to
accumulate, so that even low concentrations experienced for a longer
duration have the potential to create chronic stress on
vegetation.\761\ Ozone damage to sensitive species includes impaired
photosynthesis and visible injury to leaves. The impairment of
photosynthesis, the process by which the plant makes carbohydrates (its
source of energy and food), can lead to reduced crop yields, timber
production, and plant productivity and growth. Impaired photosynthesis
can also lead to a reduction in root growth and carbohydrate storage
below ground, resulting in other, more subtle plant and ecosystems
impacts.\762\ These latter impacts include increased susceptibility of
plants to insect attack, disease, harsh weather, interspecies
competition and overall decreased plant vigor. The adverse effects of
ozone on areas with sensitive species could potentially lead to species
shifts and loss from the affected ecosystems,\763\ resulting in a loss
or reduction in associated ecosystem goods and services. Additionally,
visible ozone injury to leaves can result in a loss of aesthetic value
in areas of special scenic significance like national parks and
wilderness areas and reduced use of sensitive ornamentals in
landscaping.\764\
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\759\ 73 FR 16486 (Mar. 27, 2008).
\760\ 73 FR 16491 (Mar. 27, 2008). Only a small percentage of
all the plant species growing within the U.S. (over 43,000 species
have been catalogued in the USDA PLANTS database) have been studied
with respect to ozone sensitivity.
\761\ The concentration at which ozone levels overwhelm a
plant's ability to detoxify or compensate for oxidant exposure
varies. Thus, whether a plant is classified as sensitive or tolerant
depends in part on the exposure levels being considered. Chapter 9,
Section 9.3.4 of U.S. EPA, 2013 Integrated Science Assessment for
Ozone and Related Photochemical Oxidants. Office of Research and
Development/National Center for Environmental Assessment. U.S.
Environmental Protection Agency. EPA 600/R-10/076F.
\762\ 73 FR 16492 (Mar. 27, 2008).
\763\ 73 FR 16493-16494 (Mar. 27, 2008). Ozone impacts could be
occurring in areas where plant species sensitive to ozone have not
yet been studied or identified.
\764\ 73 FR 16490-16497 (Mar. 27, 2008).
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The most recent Integrated Science Assessment (ISA) for Ozone
presents more detailed information on how ozone affects vegetation and
ecosystems.\765\ The ISA concludes that ambient concentrations of ozone
are associated with a number of adverse welfare effects and
characterizes the weight of evidence for different effects associated
with ozone.\766\ The ISA concludes that visible foliar injury effects
on some vegetation, reduced vegetation growth, reduced productivity in
terrestrial ecosystems, reduced yield and quality of some agricultural
crops, and alteration of below-ground biogeochemical cycles are
causally associated with exposure to ozone. It also concludes that
reduced carbon sequestration in terrestrial ecosystems, alteration of
terrestrial ecosystem water cycling, and alteration of terrestrial
community composition are likely to be causally associated with
exposure to ozone.
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\765\ U.S. EPA. Integrated Science Assessment of Ozone and
Related Photochemical Oxidants (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-10/076F, 2013. The ISA
is available at http://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=247492#Download.
\766\ The Ozone ISA evaluates the evidence associated with
different ozone related health and welfare effects, assigning one of
five ``weight of evidence'' determinations: Causal relationship,
likely to be a causal relationship, suggestive of a causal
relationship, inadequate to infer a causal relationship, and not
likely to be a causal relationship. For more information on these
levels of evidence, please refer to Table II of the ISA.
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(c) Atmospheric Deposition
Wet and dry deposition of ambient particulate matter delivers a
complex mixture of metals (e.g., mercury, zinc, lead, nickel, aluminum,
and cadmium), organic compounds (e.g., polycyclic organic matter,
dioxins, and furans), and inorganic compounds (e.g., nitrate, sulfate)
to terrestrial and aquatic ecosystems. The chemical form of the
compounds deposited depends on a variety of factors including ambient
conditions (e.g., temperature, humidity, oxidant levels) and the
sources of the material. Chemical and physical transformations of the
compounds occur in the atmosphere as well as the media onto which they
deposit. These transformations in turn influence the fate,
bioavailability and potential toxicity of these compounds.
Adverse impacts to human health and the environment can occur when
particulate matter is deposited to soils,
[[Page 43348]]
water, and biota.\767\ Deposition of heavy metals or other toxics may
lead to the human ingestion of contaminated fish, impairment of
drinking water, damage to terrestrial, freshwater and marine ecosystem
components, and limits to recreational uses. Atmospheric deposition has
been identified as a key component of the environmental and human
health hazard posed by several pollutants including mercury, dioxin and
PCBs.\768\
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\767\ U.S. EPA. Integrated Science Assessment for Particulate
Matter (Final Report). U.S. Environmental Protection Agency,
Washington, DC, EPA/600/R-08/139F, 2009.
\768\ U.S. EPA. (2000). Deposition of Air Pollutants to the
Great Waters: Third Report to Congress. Office of Air Quality
Planning and Standards. EPA-453/R-00-0005.
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The ecological effects of acidifying deposition and nutrient
enrichment are detailed in the Integrated Science Assessment for Oxides
of Nitrogen and Sulfur-Ecological Criteria.\769\ Atmospheric deposition
of nitrogen and sulfur contributes to acidification, altering
biogeochemistry and affecting animal and plant life in terrestrial and
aquatic ecosystems across the United States. The sensitivity of
terrestrial and aquatic ecosystems to acidification from nitrogen and
sulfur deposition is predominantly governed by geology. Prolonged
exposure to excess nitrogen and sulfur deposition in sensitive areas
acidifies lakes, rivers, and soils. Increased acidity in surface waters
creates inhospitable conditions for biota and affects the abundance and
biodiversity of fishes, zooplankton, macroinvertebrates, and ecosystem
function. Over time, acidifying deposition also removes essential
nutrients from forest soils, depleting the capacity of soils to
neutralize future acid loadings and negatively affecting forest
sustainability. Major effects in forests include a decline in sensitive
tree species, such as red spruce (Picea rubens) and sugar maple (Acer
saccharum). In addition to the role nitrogen deposition plays in
acidification, nitrogen deposition also leads to nutrient enrichment
and altered biogeochemical cycling. In aquatic systems increased
nitrogen can alter species assemblages and cause eutrophication. In
terrestrial systems nitrogen loading can lead to loss of nitrogen-
sensitive lichen species, decreased biodiversity of grasslands, meadows
and other sensitive habitats, and increased potential for invasive
species.
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\769\ NOX and SOX secondary ISA U.S. EPA.
Integrated Science Assessment (ISA) for Oxides of Nitrogen and
Sulfur Ecological Criteria (Final Report). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-08/082F, 2008.
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Building materials including metals, stones, cements, and paints
undergo natural weathering processes from exposure to environmental
elements (e.g., wind, moisture, temperature fluctuations, sunlight,
etc.). Pollution can worsen and accelerate these effects. Deposition of
PM is associated with both physical damage (materials damage effects)
and impaired aesthetic qualities (soiling effects). Wet and dry
deposition of PM can physically affect materials, adding to the effects
of natural weathering processes, by potentially promoting or
accelerating the corrosion of metals, by degrading paints and by
deteriorating building materials such as stone, concrete and
marble.\770\ The effects of PM are exacerbated by the presence of
acidic gases and can be additive or synergistic due to the complex
mixture of pollutants in the air and surface characteristics of the
material. Acidic deposition has been shown to have an effect on
materials including zinc/galvanized steel and other metal, carbonate
stone (as monuments and building facings), and surface coatings
(paints).\771\ The effects on historic buildings and outdoor works of
art are of particular concern because of the uniqueness and
irreplaceability of many of these objects.
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\770\ U.S. Environmental Protection Agency (U.S. EPA). 2009.
Integrated Science Assessment for Particulate Matter (Final Report).
EPA-600-R-08-139F. National Center for Environmental Assessment--RTP
Division. December. Available on the internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546.
\771\ Irving, P.M., e.d. 1991. Acid Deposition: State of Science
and Technology, Volume III, Terrestrial, Materials, Health, and
Visibility Effects, The U.S. National Acid Precipitation Assessment
Program, Chapter 24, page 24-76.
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(d) Environmental Effects of Air Toxics
Emissions from producing, transporting, and combusting fuel
contribute to ambient levels of pollutants that contribute to adverse
effects on vegetation. Volatile organic compounds, some of which are
considered air toxics, have long been suspected to play a role in
vegetation damage.\772\ In laboratory experiments, a wide range of
tolerance to VOCs has been observed.\773\ Decreases in harvested seed
pod weight have been reported for the more sensitive plants, and some
studies have reported effects on seed germination, flowering and fruit
ripening. Effects of individual VOCs or their role in conjunction with
other stressors (e.g., acidification, drought, temperature extremes)
have not been well studied. In a recent study of a mixture of VOCs
including ethanol and toluene on herbaceous plants, significant effects
on seed production, leaf water content, and photosynthetic efficiency
were reported for some plant species.\774\
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\772\ U.S. EPA. (1991). Effects of organic chemicals in the
atmosphere on terrestrial plants. EPA/600/3-91/001.
\773\ Cape J. N., Leith, I. D., Binnie, J., Content, J., Donkin,
M., Skewes, M., Price, D. N., Brown, A. R., & Sharpe, A. D. (2003).
Effects of VOCs on herbaceous plants in an open-top chamber
experiment. Environmental Pollution. 124:341-343.
\774\ Cape, J. N., Leith, I. D., Binnie, J., Content, J.,
Donkin, M., Skewes, M., Price, D. N., Brown, A. R., & Sharpe, A. D.
(2003). Effects of VOCs on herbaceous plants in an open-top chamber
experiment. Environmental Pollution. 124:341-343.
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Research suggests an adverse impact of vehicle exhaust on plants,
which has in some cases been attributed to aromatic compounds and in
other cases to nitrogen oxides.775 776 777
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\775\ Viskari E. L. (2000). Epicuticular wax of Norway spruce
needles as indicator of traffic pollutant deposition. Water, Air,
and Soil Pollution. 121:327-337.
\776\ Ugrekhelidze, D., Korte, F., & Kvesitadze, G. (1997).
Uptake and transformation of benzene and toluene by plant leaves.
Ecotox. Environ. Safety 37:24-29.
\777\ Kammerbauer H., Selinger, H, on Rommelt, R., Ziegler-Jons,
A., Knoppik, D., & Hock, B. (1987). Toxic components of motor
vehicle emissions for the spruce Picea abies. Environmental
Pollution. 48:235-243.
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F. Air Quality Impacts of Non-GHG Pollutants
Changes in emissions of non-GHG pollutants due to these rules will
impact air quality. Information on current air quality and the results
of our air quality modeling of the projected impacts of these rules are
summarized in the following section.
1. Current Concentrations of Non-GHG Pollutants
Nationally, levels of PM2.5, ozone, NOX,
SOX, CO, and air toxics have declined significantly in the
last 30 years and are continuing to drop as previously promulgated
regulations come into full effect. However, as of April 22, 2016, more
than 125 million people lived in counties designated nonattainment for
one or more of the NAAQS, and this figure does not include the people
living in areas with a risk of exceeding a NAAQS in the future. Many
Americans continue to be exposed to ambient concentrations of air
toxics at levels which have the potential to cause adverse health
effects. In addition, populations who live, work, or attend school near
major roads experience elevated exposure concentrations to a wide range
of air pollutants.
[[Page 43349]]
(a) Particulate Matter
There are two primary NAAQS for PM2.5: An annual
standard (12.0 micrograms per cubic meter ([mu]g/m3)) set in 2012 and a
24-hour standard (35 [mu]g/m3) set in 2006, and two secondary NAAQS for
PM2.5: An annual standard (15.0 [mu]g/m3) set in 1997 and a
24-hour standard (35 [mu]g/m3) set in 2006.
There are many areas of the country that are currently in
nonattainment for the annual and 24-hour primary PM2.5
NAAQS. As of April 22, 2016, more than 23 million people lived in the
seven areas that are still designated as nonattainment for the 1997
annual PM2.5 NAAQS. These PM2.5 nonattainment
areas are comprised of 33 full or partial counties. As of April 22,
2016, nine areas aredesignated as nonattainment for the 2012 annual
PM2.5 NAAQS; these areas are composed of 20 full or partial
counties with a population of more than 23 million. As of April 22,
2016, 16 areas are designated as nonattainment for the 2006 24-hour
PM2.5 NAAQS, these areas are composed of 46 full or partial
counties with a population of more than 32 million. In total, there are
currently 24 PM2.5 nonattainment areas with a population of
more than 39 million people.
The EPA has already adopted many mobile source emission control
programs that are expected to reduce ambient PM concentrations. As a
result of these and other federal, state and local programs, the number
of areas that fail to meet the PM2.5 NAAQS in the future is
expected to decrease. However, even with the implementation of all
current state and federal regulations, there are projected to be
counties violating the PM2.5 NAAQS well into the future.
States will need to meet the 2006 24-hour standards in the 2015-2019
timeframe and the 2012 primary annual standard in the 2021-2025
timeframe. Ozone
The primary and secondary NAAQS for ozone are eight-hour standards
with a level of 0.07 ppm. The most recent revision to the ozone
standards was in 2015; the previous eight-hour ozone primary standard,
set in 2008, had a level of 0.075 ppm. As of April 22, 2016, there were
44 ozone nonattainment areas for the 2008 ozone NAAQS, composed of 216
full or partial counties, with a population of more than 120 million.
States with ozone nonattainment areas are required to take action
to bring those areas into attainment. The attainment date assigned to
an ozone nonattainment area is based on the area's classification. The
attainment dates for areas designated nonattainment for the 2008 eight-
hour ozone NAAQS are in the 2015 to 2032 timeframe, depending on the
severity of the problem in each area. Nonattainment area attainment
dates associated with areas designated for the 2015 NAAQS will be in
the 2020-2037 timeframe, depending on the severity of the problem in
each area.
EPA has already adopted many emission control programs that are
expected to reduce ambient ozone levels. As a result of these and other
federal, state and local programs, eight-hour ozone levels are expected
to improve in the future. However, even with the implementation of all
current state and federal regulations, there are projected to be
counties violating the ozone NAAQS well into the future.
(b) Nitrogen Dioxide
On April 6, 2018, based on a review of the full body of scientific
evidence, EPA issued a decision to retain the current national ambient
air quality standards (NAAQS) for oxides of nitrogen (NOX).
The EPA has concluded that the current NAAQS protect the public health,
including the at-risk populations of older adults, children and people
with asthma, with an adequate margin of safety. The NAAQS for nitrogen
oxides are a one-hour standard at a level of 100 ppb based on the
three-year average of 98th percentile of the yearly distribution of
one-hour daily maximum concentrations, and an annual standard at a
level of 53 ppb.
(c) Sulfur Dioxide
The EPA is currently reviewing the primary SO2 NAAQS and
has proposed to retain the current primary standard (83 FR 26752, June
8, 2018), which is a one-hour standard of 75 ppb established in June
2010. The EPA has been finalizing the initial area designations for the
2010 SO2 NAAQS in phases and completed designations for most
of the country in December 2017. The EPA is under a court order to
finalize initial designations by December 31, 2020, for a remaining set
of about 50 areas where states have deployed new SO2
monitoring networks. As of July 2018, the EPA has designated 42 areas
as nonattainment for the 2010 SO2 NAAQS in actions taken in
2013, 2016, and 2017.\778\ There also remain nine nonattainment areas
for the primary annual SO2 NAAQS set in 1971.
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\778\ 78 FR 47191, 81 FR 45049, 81 FR 89870, 83 FR 1098, and 83
FR 14597.
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(d) Carbon Monoxide
There are two primary NAAQS for CO: An eight-hour standard (9 ppm)
and a one-hour standard (35 ppm). The primary NAAQS for CO were
retained in August 2011. There are currently no CO nonattainment areas;
as of September 27, 2010, all CO nonattainment areas have been
redesignated to attainment.
The past designations were based on the existing community-wide
monitoring network. EPA is making changes to the ambient air monitoring
requirements for CO. The new requirements are expected to result in
approximately 52 CO monitors operating near roads within 52 urban areas
by January 2015 (76 FR 54294, August 31, 2011).
(e) Diesel Exhaust PM
Because DPM is part of overall ambient PM and cannot be easily
distinguished from overall PM, we do not have direct measurements of
DPM in the ambient air. DPM concentrations are estimated using ambient
air quality modeling based on DPM emission inventories. DPM emission
inventories are computed as the exhaust PM emissions from mobile
sources combusting diesel or residual oil fuel. DPM concentrations were
recently estimated as part of the 2011 NATA. Areas with high
concentrations are clustered in the Northeast, Great Lake States,
California, and the Gulf Coast States and are also distributed
throughout the rest of the U.S. The median DPM concentration calculated
nationwide is 0.76 [mu]g/m3.
(f) Air Toxics
The most recent available data indicate that the majority of
Americans continue to be exposed to ambient concentrations of air
toxics at levels which have the potential to cause adverse health
effects. The levels of air toxics to which people are exposed vary
depending on where people live and work and the kinds of activities in
which they engage, as discussed in detail in EPA's most recent Mobile
Source Air Toxics Rule. According to the National Air Toxic Assessment
(NATA) for 2015, mobile sources were responsible for 50% of outdoor
anthropogenic toxic emissions and were the largest contributor to
cancer and noncancer risk from directly emitted pollutants. Mobile
sources are also large contributors to precursor emissions which react
to form air toxics. Formaldehyde is the largest contributor to cancer
risk of all 71 pollutants quantitatively assessed in the 2011
[[Page 43350]]
NATA. Mobile sources were responsible for more than 25% of primary
anthropogenic emissions of this pollutant in 2011 and are major
contributors to formaldehyde precursor emissions. Benzene is also a
large contributor to cancer risk, and mobile sources account for almost
80% of ambient exposure. Over the years, EPA has implemented a number
of mobile source and fuel controls which have resulted in VOC
reductions, which also reduced formaldehyde, benzene and other air
toxic emissions.
2. Air Quality Impacts of Non-GHG Pollutants
(a) Impacts of Proposed Standards on Future Ambient Concentrations of
PM2.5, Ozone and Air Toxics
Full-scale photochemical air quality modeling is necessary to
accurately project levels of criteria pollutants and air toxics. For
the final rule, a national-scale air quality modeling analysis will be
performed to analyze the impacts of the standards on PM2.5,
ozone, and selected air toxics (i.e., benzene, formaldehyde,
acetaldehyde, acrolein and 1,3-butadiene). The length of time needed to
prepare the necessary emissions inventories, in addition to the
processing time associated with the modeling itself, has precluded us
from performing air quality modeling for this proposal.
Section VI.D.2 of the preamble present projections of the changes
in criteria pollutant and air toxics emissions because of the proposed
vehicle standards; the basis for those estimates is set out in Chapter
10 of the PRIA. The atmospheric chemistry related to ambient
concentrations of PM2.5, ozone and air toxics is very
complex, and making predictions based solely on emissions changes is
extremely difficult.
3. Other Unquantified Health and Environmental Effects
In addition, the agencies seek comment on whether there are any
other health and environmental impacts associated with advancements in
technologies that should be considered. For example, the use of
technologies and other strategies to reduce fuel consumption and/or GHG
emissions could have effects on a vehicle's life-cycle impacts (e.g.,
materials usage, manufacturing, end of life disposal), beyond the
issues regarding fuel production and distribution (upstream) GHG
emissions discussed in Section VI.D.2. The agencies seek comment on any
studies or research in this area that should be considered in the
future to assess a fuller range of health and environmental impacts
from the light-duty vehicle fleet shifting to different technologies
and/or materials. At this point, it is unclear whether there is
sufficient information about the lifecycle impacts of the myriad of
available technologies, materials, and cradle-to-grave pathways to
conduct the type of detailed assessments that would be needed in a
regulatory context, but the agencies seek comment on any current or
future studies and research underway on this topic, and how such
analysis could practicably and in a balanced way be integrated in the
modeling, especially considering the characterization of specific
vehicles in the analysis fleet and the characterization of specific
technology options.
G. What are the impacts on the total fleet size, usage, and safety?
1. CAFE Standards
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H. What other impacts (quantitative and unquantifiable) will these
proposed standards have?
1. Sensitivity Analysis
As discussed at the beginning of this section, results presented
today reflect the agencies' best judgments regarding many different
factors. Based on analyses in past rulemakings, the agencies recognize
that some analytical inputs are especially uncertain, some are likely
to exert considerable influence over specific types of estimated
impacts, and some are likely to do so for the bulk of the analysis. To
explore the sensitivity of estimated impacts to changes in model
inputs, analysis was conducted using alternative values for a range of
different inputs. Results of this sensitivity analysis are summarized
below, and detailed model inputs and outputs are available on NHTSA's
website.\779\ Regulatory alternatives are identical across all cases,
except that one case includes an increase in civil penalty rate
starting in MY 2019; NHTSA may consider changing the civil penalty rate
in a separate regulatory action, and depending on the timing of any
such action, the final rule to follow today's proposal could reflect
the change.\780\ The following table lists the cases included in the
sensitivity analysis. The final rule could adopt any combination--or
none--of these alternatives as reference case inputs, and the agencies
invite comment on all of them.
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\779\ The CAFE model and all inputs and outputs supporting
today's proposal are available at https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system.
\780\ 83 FR 13904 (Apr. 2, 2018).
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The remaining tables in the section summarize various estimated
impacts as estimated for all of the cases included in the sensitivity
analysis.
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\781\ Climate-related economic damages caused by emissions of
GHGs other than CO2 were estimated by converting those
emissions to their (mass) equivalents in CO2 emissions
and applying the per-ton damage costs used to monetize
CO2 emissions. Specifically, emissions of methane
(CH4) and nitrous oxide (N2O) were converted
to their equivalent in CO2 emissions using the 100-year
Global Warming Potentials (GWPs) for those gases, which are 25 for
CH4 and 298 for N2O. These GWPs were estimated
by the United Nations Intergovernmental Panel on Climate Change in
its 4th Assessment Report (available at https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-10-2.html; last accessed July
19, 2018). An alternative approach would be to develop direct
estimates of the climate damage costs for these GHGs derived using
the same process that was used to estimate the SCC, described
previously in PRIA Chapter 8.11.2 and the Appendix to Chapter 8. For
comparison, using the alternative approach results in estmates which
average $256 per (metric) ton for CH4 and $2,820 for
N2O over the analysis period, or about 22% and 13% higher
than the values used in this sensitivity case. A detailed
description of the methods used to construct these alternative
values is available in the docket for this rule. The agency will
consider using this alternative approach in its analysis supporting
the final rule.
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VIII. Impacts of Alternative CAFE and CO2 Standards
Considered for MYs 2021/22-2026
As discussed above, a range of regulatory alternatives are being
considered. Section III defines the proposed preferred alternative, and
Section IV defines the no-action alternative as well as the other seven
alternatives. The potential impacts of each alternative in each case
relative to the no-action alternative were estimated. For the preferred
alternative, these impacts are presented above on an incremental basis,
such that the impacts attributed separately to standards proposed in
each model year. To facilitate comparison of different alternatives,
total estimated impacts (i.e., summing impacts attributable to all
model years' standards) were calculated under each alternative.
Tables in the remaining section summarize these estimated impacts
for each alternative, considering the same measures as shown above for
the preferred alternative. As for the preferred alternative, social
costs and benefits, private costs and benefits, and environmental and
energy impacts were evaluated, and were done so separately for CAFE and
CO2 standards defining each regulatory alternative. Also, as
for the preferred alternative, the compliance-related private costs and
benefits were evaluated separately for domestic and imported passenger
cars under CAFE standards but not under CO2 standards
because EPCA/EISA's requirement for separate compliance applies only to
CAFE standards.
This analysis does not explicitly identify ``co-benefits'' from its
proposed action to change fuel economy standards, as such a concept
would include all benefits other than cost savings to vehicle buyers.
Instead, it distinguishes between private benefits--which include
economic impacts on vehicle manufacturers, buyers of new cars and light
trucks, and owners (or users) of used cars and light trucks--and
external benefits, which represent indirect benefits (or costs) to the
[[Page 43370]]
remainder of the U.S. economy that stem from the proposal's effects on
the behavior of vehicle manufacturers, buyers, and users. In this
accounting framework, changes in fuel use and safety impacts resulting
from the proposal's effects on the number of used vehicles in use
represent an important component of its private benefits and costs,
despite the fact that previous analyses have failed to recognize these
effects. The agency's presentation of private costs and benefits from
its proposed action clearly distinguishes between those that would be
experienced by owners and users of cars and light trucks produced
during previous model years, and those that would be experienced by
buyers and users of cars and light trucks produced during the model
years it would affect. Moreover, it clearly separates these into
benefits related to fuel consumption and those related to safety
consequences of vehicle use. This is more meaningful and informative
than simply identifying all impacts other than changes in fuel savings
to buyers of new vehicles as ``co-benefits.''
Like the preferred alternative, all other alternatives involve
standards less stringent than the no-action alternative. Therefore, as
discussed above, incremental benefits and costs for each alternative
are negative--in other words, each alternative involves foregone
benefits and avoided costs. Environmental and energy impacts are
correspondingly negative, involving foregone avoided CO2
emissions and foregone avoided fuel consumption. For consistency with
past rulemakings, these are reported as negative values rather than as
additional CO2 emissions and additional fuel consumption.
As discussed above, more detailed results are available in the PRIA
and DEIS accompanying today's notice, as well as in underlying model
output files posted on NHTSA's website.
A. What are the social costs and benefits of each alternative, relative
to the no-action alternative?
1. CAFE Standards
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B. What are the private costs and benefits of each alternative,
relative to the no-action alternative?
1. What are the impacts on producers of new vehicles?
(a) CAFE Standards
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2. What are the impacts on buyers of new vehicles?
(a) CAFE Standards
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C. What are the energy and environmental impacts?
1. CAFE Standards
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D. What are the impacts on the total fleet size, usage, and safety?
1. CAFE Standards
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2. CO2 Standards
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E. What are the Impacts on Employment?
As discussed in Section II.E, the analysis includes estimates of
impacts on U.S. auto industry labor, considering the combined impact of
changes in sales volumes and changes in outlays for additional fuel-
saving technology. Note: This analysis does not consider the
possibility that potential new jobs and plants attributable to
increased stringency will not be located in the United States, or that
increased stringency will not lead to the relocation of current jobs or
plants to foreign countries. Compared to the no-action alternative
(i.e., the baseline standards), the proposed standards (alternative 1)
and other regulatory alternatives under consideration all involve
reduced regulatory costs expected to lead to reduced average vehicle
prices and, in turn, increased sales. While the increased sales
slightly increase estimated U.S. auto sector labor, because producing
and selling more vehicles uses additional U.S. labor, the reduced
outlays for fuel-saving technology slightly reduce estimated U.S. auto
sector labor, because manufacturing, integrating, and selling less
technology means using less labor to do so. Of course, this is
technology that may not otherwise be produced or deployed were it not
for regulatory mandate, and the additional costs of this technology
would be borne by a reduced number of consumers given reduction in
sales in response to increased prices. Today's analysis shows the
negative impact of reduced mandatory technology outlays outweighing the
positive impact of increased sales. However, both of these underlying
factors are subject to uncertainty. For example, if fuel-saving
technology that would have been applied under the baseline standards is
more likely to have come from foreign suppliers than estimated here,
less of the foregone labor to manufacture that technology would have
been U.S. labor. Also, if sales would be more positively impacted by
reduced vehicle prices than estimated here, correspondingly positive
impacts on U.S. auto sector labor could be magnified. Alternatively, if
manufacturers are able to deploy technology to improve vehicle
attributes that new car buyers prefer to fuel economy improvements,
both technology spending and vehicle sales would correspondingly
increase. As discussed above, the analysis of sales and employment may
be updated for the final rule, and it is expected that doing so could
possibly produce incremental changes opposite in sign from those
presented below. In particular, comment is sought on the potential for
changes in stringency to result in new jobs and plants being created in
foreign countries or for current United States jobs and plants to be
moved outside of the United States.
The employment analysis was focused on automotive labor because
adjacent employment factors and consumer spending factors for other
goods and services are uncertain and difficult to predict. How direct
labor changes may affect the macro economy and possibly change
employment in adjacent industries were not considered. For instance,
possible labor changes in vehicle maintenance and repair were not
considered, nor were changes in labor at retail gas stations
considered. Possible labor changes due to raw material production, such
as production of aluminum, steel, copper, and lithium were not
considered, nor were possible labor impacts due to changes in
production of oil and gas, ethanol, and electricity considered. Effects
of how consumers could spend money saved due to improved fuel economy
were not analyzed, nor were effects of how consumers would pay for more
expensive fuel savings technologies at the time of purchase analyzed;
either could affect consumption of other goods and services, and hence
affect labor in other industries. The effects of increased usage of
car-sharing, ride-sharing, and automated vehicles were not analyzed.
How changes in labor from any industry could affect gross domestic
product and possibly affect other industries as a result were not
estimated.
Also, no assumptions were made about full-employment or not full-
employment and the availability of human resources to fill positions.
When the economy is at full employment, a fuel economy regulation is
unlikely to have much impact on net overall U.S. employment; instead,
labor would primarily be shifted from one sector to another. These
shifts in employment impose an opportunity cost on society,
approximated by the wages of the employees, as regulation diverts
workers from other activities in the economy. In this situation, any
effects on net employment are likely to be transitory as workers change
jobs (e.g., some workers may need to be retrained or require time to
search for new jobs, while shortages in some sectors or regions could
bid up wages to attract workers). On the other hand, if a regulation
comes into effect during a period of high unemployment, a change in
labor demand due to regulation may affect net overall U.S. employment
because the labor market is not in equilibrium. Schmalansee and Stavins
point out that net positive employment effects are possible in the near
term when the economy is at less than full employment due to the
potential hiring of idle labor resources by the regulated sector to
meet new requirements (e.g., to install new equipment) and new economic
activity in sectors related to the regulated sector longer run, the net
effect on employment is more difficult to predict and will depend on
the way in which the related industries respond to the regulatory
requirements. For that reason, this analysis does not include
multiplier effects but instead focuses on labor impacts in the most
directly affected industries. Those sectors are likely to face the most
concentrated labor impacts.
The tables presented below summarize these results for regulatory
alternatives under consideration. While values are reported as
thousands of job-years, changes in labor utilization would not
necessarily involve the same number of changes in actual jobs, as auto
industry employers may use a range of strategies (e.g., shift changes,
overtime) beyond simply adding or eliminating jobs.
1. CAFE Standards
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2. CO2 Standards
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IX. Vehicle Classification
Vehicle classification, for purposes of the light-duty CAFE and
CO2 programs,\782\ refers to whether a vehicle is considered
to be a passenger automobile (car) or a non-passenger automobile (light
truck).\783\ As discussed above in Section III, passenger cars and
light trucks are subject to different fuel economy and CO2
standards as required by EPCA/
[[Page 43438]]
EISA and consistent with their different capabilities.
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\782\ See 40 CFR 86.1803-01. For the MYs 2012-2016 standards,
the MYs 2017-2025 standards, and this NPRM, EPA has agreed to use
NHTSA's regulatory definitions for determining which vehicles would
be subject to which CO2 standards.
\783\ EPCA uses the terms ``passenger automobile'' and ``non-
passenger automobile;'' NHTSA's regulation on vehicle
classification, 49 CFR part 523, further clarifies the EPCA
definitions and introduces the term ``light truck'' as a plainer
language alternative for ``non-passenger automobile.''
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In EPCA, Congress designated some vehicles as passenger automobiles
and some as non-passenger automobiles. Vehicles ``capable of off-
highway operation'' are, by statute, not passenger automobiles.
Determining ``off-highway operation'' is a two-part inquiry: First,
does the vehicle have 4-wheel drive, or is it over 6,000 pounds gross
vehicle weight rating (GVWR), and second, does the vehicle (that is
either 4-wheel drive or over 6,000 pounds GVWR) also have ``a
significant feature designed for off-highway operation,'' as defined by
DOT regulations.\784\ Additionally, vehicles that DOT ``decides by
regulation [are] manufactured primarily for transporting not more than
10 individuals'' are, by statute, passenger automobiles; that means
that certain vehicles that DOT decides by regulation are not
manufactured primarily for transporting not more than 10 passengers are
not passenger automobiles. NHTSA's regulation on vehicle
classification,\785\ contains requirements for vehicles to be
classified as light trucks either on the basis of off-highway
capability \786\ or on the basis of having ``truck-like
characteristics.'' \787\ Over time, NHTSA has refined the light truck
vehicle classification by revising its regulations and issuing legal
interpretations. However, based on agency observations of current
vehicle design trends, compliance testing and evaluation, and
discussions with stakeholders, NHTSA has become aware of vehicle
designs that complicate light truck classification determinations for
the CAFE and CO2 programs. When there is uncertainty as to
how vehicles should be classified, inconsistency in determining
manufacturers' compliance obligations can result, which is detrimental
to the predictability and fairness of the program. While the agency has
not assessed the magnitude of the classification issues and is not
proposing any vehicle reclassifications at this time, NHTSA is
interested in gathering more information from commenters on several of
the light truck classification criteria, and therefore seeks comment on
the issues discussed below.
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\784\ 49 U.S.C. 32901(a)(18).
\785\ 49 CFR part 523.
\786\ 49 CFR 523.5(b).
\787\ 49 CFR 523.5(a).
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A. Classification Based on ``truck-like characteristics''
One of the ``truck-like characteristics'' that allows manufacturers
to classify vehicles as light trucks is having at least three rows of
seats as standard equipment, as long as it also ``permit[s] expanded
use of the automobile for cargo-carrying purposes or other non-
passenger-carrying purposes through the removal or stowing of foldable
or pivoting seats so as to create a flat, leveled cargo surface
extending from the forwardmost point of installation of those seats to
the rear of the automobile's interior.'' \788\ NHTSA has identified two
issues thus far with this criterion that various manufacturers appear
to be approaching differently, which, again, could be causing
unfairness in compliance obligations. Both relate to how to measure the
cargo area when seats are moved out of the way. Given that the purpose
of this criterion is to ``permit expanded use of the automobile for
cargo-carrying purposes or other non-passenger-carrying purposes,'' the
less cargo space the vehicle design can provide, the harder it is for
NHTSA to agree that the vehicle is properly classified as a light
truck.
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\788\ 49 CFR 523.5(a)(5)(ii).
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The first issue is how to identify the ``forwardmost point of
installation'' and how the location impacts the available cargo floor
area and volume behind the seats. Seating configurations have evolved
considerably over the last 20 years, as minivan seats are now very
complex in design providing far more ergonomic functionality. For
example, the market demand for increased rear seat leg room and the
installation of rear seat air bag systems has resulted in the
introduction of adjustable second row seats--second-row seats that
remain upright, unable to articulate and stow into the vehicle floor.
These seats provide adjustable leg room by sliding forward or backward
on sliding tracks and aim to provide expanded cargo carrying room by
moving forward against the back of the front seats. Earlier seating
designs had fixed attachment points on the vehicle floor, and it was
easy to identify the ``forwardmost point of installation'' because it
was readily observable and did not change. When seats move forward and
backward on sliding tracks, the ``forwardmost point of installation''
is less readily identifiable. Some manufacturers have argued that the
forwardmost point of installation is the forwardmost point where the
seat attaches to the sliding track with the seat positioned at its
rearmost position on the track. This would allow vehicles with certain
second-row seat designs to be considered as meeting this criterion
(e.g., a second-row seat where the bottom cushion folds upward toward
its seatback, allowing the entire seat to slide forward up against the
back of the front seat, beyond the identified forwardmost point of
installation). Other approaches could include adjusting the seat to a
position that can accommodate a 75-percentile male dummy. Selecting any
of these positions will change the forwardmost point of installation
and could ultimately impact the flat floor surface area and cargo
volume, respectively. NHTSA seeks comment on how to determine the
reference point of the forwardmost point of installation of these seats
for vehicles to qualify as light trucks using this provision. Also,
should NHTSA establish a minimum amount of cargo surface area for seats
that remain within the vehicle?
The second issue is what makes a surface ``flat and leveled.'' Many
SUVs have three rows of designated seating positions, where the second
row has ``captain's seats'' (i.e., two independent bucket seats) rather
than the traditional bench-style seating more common when the provision
was added to NHTSA's regulation. When captain seats are folded down,
the seatback can form a flat surface for expanded cargo carrying
purposes, but the surface of the seatbacks may not be level (i.e., may
be angled at some angle slightly greater than 0[deg]), or may not be
level with the rest of the cargo area (i.e., horizontal surface of
folded seats is 0[deg] at a different height from horizontal surface of
cargo area behind the seats). Captain seats, when folded flat, may also
leave significant gaps around and between the seats. Some manufacturers
have opted to use plastic panels to level the surface and to covers the
gaps between seats, while others have left the space open and the
surface non-level. NHTSA therefore seeks comment on the following
questions related to the requirement for a flat leveled cargo surface:
Does the cargo surface need to be flat and level in
exactly the same plane, or does it fulfill the intent of the
criterion and provide appropriate cargo-carrying functionality for
the cargo surface to be other than flat and level in the same plane?
Does the cargo surface need to be flat and level across
the entire surface, or are (potentially large) gaps in that surface
consistent with the intent of the criterion and providing
appropriate cargo-carrying functionality? Should panels to fill gaps
be required?
Certain third row seats are located on top the rear
axle causing them to sit higher and closer to the vehicle roof. When
these seats fold flat the available cargo-carrying volume is
reduced. Is cargo-carrying functionality better ensured by setting a
minimum amount
[[Page 43439]]
of useable cargo-carrying volume in a vehicle when seats fold flat?
B. Issues that NHTSA has Observed Regarding Classification Based on
``off-road capability''
1. Measuring Vehicle Characteristics for Off-Highway Capability
For a vehicle to qualify as off-highway capable, in addition to
either having 4WD or a GVWR more than 6,000 pounds, the vehicle must
also have four out of five characteristics indicative of off-highway
operation. These characteristics include: \789\
\789\ 49 CFR 523.5(b)(2).
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An approach angle of not less than 28 degrees
A breakover angle of not less than 14 degrees
A departure angle of not less than 20 degrees
A running clearance of not less than 20 centimeters
Front and rear axle clearances of not less than 18
centimeters each
NHTSA's regulations require manufacturers to measure these
characteristics when a vehicle is at its curb weight, on a level
surface, with the front wheels parallel to the automobile's
longitudinal centerline, and the tires inflated to the manufacturer's
recommended cold inflation pressure.\790\ Given that the regulations
describe the vehicle's physical position and characteristics at time of
measurement, NHTSA previously assumed that manufacturers would use
physical measurements of vehicles. In practice, NHTSA has instead
received from manufacturers a mixture of angles and dimensions from
design models (i.e., the vehicle as designed, not as actually produced)
and/or physical vehicle measurements.\791\ When appropriate, the agency
will verify reported values by measuring production vehicles in the
field. NHTSA currently requires that manufacturers must use physical
vehicle measurements as the basis for values reported to the agency for
purposes of vehicle classification. NHTSA seeks comment on whether
regulatory changes are needed with respect to this issue.
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\790\ Id.
\791\ NHTSA previously encountered a similar issue when
manufacturers reported CAFE footprint information. In the October
2012 final rule, NHTSA clarified manufacturers must submit footprint
measurements based upon production values. 77 FR 63138 (October 15,
2012).
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2. Approach, Breakover, and Departure Angles
Approach angle, breakover angle, and departure angle are relevant
to determining off-highway capability. Large approach and departure
angles ensure the front and rear bumpers and valance panels have
sufficient clearance for obstacle avoidance while driving off-road. The
breakover angle ensures sufficient body clearance from rocks and other
objects located between the front and rear wheels while traversing
rough terrain. Both the approach and departure angles are derived from
a line tangent to the front (or rear) tire static loaded radius arc
extending from the ground near the center of the tire patch to the
lowest contact point on the front or rear of the vehicle. The term
``static loaded radius arc'' is based upon the definitions in SAE J1100
and J1544. The term is defined as the distance from wheel axis of
rotation to the supporting surface (ground) at a given load of the
vehicle and stated inflation pressure of the tire (manufacturer's
recommended cold inflation pressure).\792\
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\792\ 49 CFR 523.2.
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The static loaded radius arc is easy to measure, but the imaginary
line tangent to the static loaded radius arc is difficult to ascertain
in the field. The approach and departure angles are the angles between
the line tangent to the static loaded radius arc, as explained above,
and the level ground on which the test vehicle rests. Simpler
measurements, that provide good approximations for the approach and
departure angles, involve using a line tangent to the outside diameter
or perimeter of the tire, or a line that originates at the geometric
center of the tire contact patch, and extends to the lowest contact
point on the front or rear of the vehicle. The first method provides an
angle slightly greater than, and the second method provides an angle
slightly less than, the angle derived from the true static loaded
radius arc. When appropriate, the agency would like the ability to
measure these angles in the field to verify data submitted by the
manufacturers used to determine light truck classification decisions.
The agency understands that the term static loaded radius arc is
unclear to many manufacturers. NHTSA seeks comment on what the effect
would be if we replaced reference to the ``static loaded arc radius,''
with simpler terms like, ``outside perimeter of the tire,'' or
``geometric center of the tire contact patch.'' NHTSA would consider
using the outside perimeter of the tire as a reliable method for
ensuring repeatability and reproducibility and accepts that the
approach would provide slightly larger approach and departure angles,
thereby making it slightly easier to qualify as ``off-highway
capable.''
3. Running Clearance
NHTSA regulations define ``running clearance'' as ``the distance
from the surface on which an automobile is standing to the lowest point
on the automobile, excluding unsprung weight.'' \793\ Unsprung weight
includes the components (e.g., suspension, wheels, axles and other
components directly connected to the wheels and axles) that are
connected and translate with the wheels. Sprung weight, on the other
hand, includes all components fixed underneath the vehicle and
translate with the vehicle body (e.g., mufflers and subframes). To
clarify these requirements, NHTSA previously issued a letter of
interpretation stating that certain parts of a vehicle, such as tire
aero deflectors, which are made of flexible plastic, bend without
breaking, and return to their original position, would not count
against the 20-centimeter running clearance requirement.\794\ The
agency explained that this does not mean a vehicle with less than 20-
centimeters running clearance could be elevated by an upward force
bending the deflectors and then be considered as compliant with the
running clearance criterion, as it would be inconsistent with the
conditions listed in the introductory paragraph of 49 CFR 523.5(b)(2).
Further, NHTSA explained that without a flexible component installed,
the vehicle must meet the 20-centimeter running clearance along its
entire underside. This 20-centimeter clearance is required for all
sprung weight components.
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\793\ Id.
\794\ See letter to Mark D. Edie, Ford Motor Company, July 30,
2012. Available online at https://isearch.nhtsa.gov/files/11-000612%20M.Edie%20(Part%20523).htm (last accessed February 2, 2018).
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The agency is aware of vehicle designs that incorporate rigid
(i.e., inflexible) air dams, valance panels, exhaust pipes, and other
components, equipped as manufacturers' standard or optional equipment
(e.g., running boards and towing hitches), that likely do not meet the
20-centimeter running clearance requirement. Despite these rigid
features, it appears manufacturers are not taking these components into
consideration when making measurements. Additionally, we believe some
manufacturers may provide dimensions for their base vehicles without
considering optional or various trim level components that may reduce
the vehicle's ground clearance. Consistent with our approach to other
measurements, NHTSA believes that ground clearance, as well as all the
other suspension criteria for a light
[[Page 43440]]
truck determination, should use the measurements from vehicles with all
standard and optional equipment installed, at time of first retail
sale. The agency reiterates that the characteristics listed in 49 CFR
523.5(b)(2) are characteristics indicative of off-highway capability. A
fixed feature, such as an air dam, which does not flex and return to
its original state, or an exhaust, which could detach, inherently
interfere with the off-highway capability of these vehicles. If
manufacturers seek to classify these vehicles as light trucks under 49
CFR 523.5(b)(2) and the vehicles do not meet the four remaining
characteristics to demonstrate off-highway capability, they must be
classified as passenger cars. NHTSA seeks comment on the incorporation
of air dams, exhaust pipes, and other hanging component features--
especially those that are inflexible--and whether the agency should
consider amending its existing regulations to account for new vehicle
designs.
4. Front and Rear Axle Clearance
NHTSA regulations also state that front and rear axle clearances of
not less than 18 centimeters are another of the criteria that can be
used for designating a vehicle as off-highway capable.\795\ The agency
defines ``axle clearance'' as the vertical distance from the level
surface on which an automobile is standing to the lowest point on the
axle differential of the automobile.\796\
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\795\ 49 CFR 523.5(b)(2)(v).
\796\ 49 CFR 523.3.
---------------------------------------------------------------------------
The agency believes this definition may be outdated because of
vehicle design changes including axle system components and independent
front and rear suspension components. In the past, traditional light
trucks with and without 4WD systems had solid rear axles with center-
mounted differentials on the axle. For these trucks, the rear axle
differential was closer to the ground than any other axle or suspension
system component. This traditional axle design still exists today for
some trucks with a solid chassis (also known as body-on-frame
configuration). Today, many SUVs and CUVs that qualify as light trucks
are constructed with a unibody frame \797\ and have unsprung (e.g.,
control arms, tie rods, ball joints, struts, shocks, etc.) and sprung
components (e.g., the axle subframes) connected together as a part of
the axle assembly. These unsprung and sprung components are located
under the axles, making them lower to the ground than the axles and the
differential, and were not contemplated when NHTSA established the
definition and the allowable clearance for axles. The definition also
did not originally account for 2WD vehicles with GVWRs greater than
6,000 pounds that had one axle without a differential, such as the
model year 2018 Ford Expedition. Vehicles with axle components that are
low enough to interfere with the vehicle's ability to perform off-road
would seem inconsistent with the regulation's intent of ensuring off-
highway capability, as Congress sought.
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\797\ Unibody frames integrate the frame and body components
into a combined structure.
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NHTSA seeks comment on whether (and if so, how) to revise the
definition of axle clearance in light of these issues. NHTSA seeks
comment on what unsprung axle components should be considered when
determining a vehicle's axle clearance. Should the definition be
modified to account for axles without differentials? NHTSA also seeks
comment on whether the axle subframes surrounding the axle components
but affixed directly to the vehicle unibody, as sprung mass (lower to
the ground than the axles) should be considered in the allowable
running clearance discussed above. Finally, should NHTSA consider
replacing both the running and axle clearance criteria with a single
ground clearance criterion that considers all components underneath the
vehicle that impact a vehicle's off road capability?
X. Compliance and Enforcement
A. Overview
The CAFE and CO2 emissions standards are both fleet-
average standards, but for both programs, determining compliance
begins, conceptually, by testing vehicles on dynamometers in a
laboratory over pre-defined test cycles under controlled
conditions.\798\ A machine is connected to the vehicle's tailpipe while
it performs the test cycle, which collects and analyzes the resulting
exhaust gases; a vehicle that has no tailpipe emissions has its
performance measured differently, as discussed below. CO2
quantities, as one of the exhaust gases, can be evaluated directly for
vehicles that produce CO2 emissions directly. Fuel economy
is determined from the amount of CO2 emissions, because the
two are directly mathematically related.\799\ Manufacturers generally
perform their own testing, and EPA confirms and validates those results
by testing some number of vehicles at the National Vehicle and Fuel
Emissions Laboratory (NVFEL) in Ann Arbor, Michigan. The results of
this testing form the basis for determining a manufacturer's compliance
in a given model year: Each vehicle model's performance on the test
cycles is calculated; that performance is multiplied by the number of
vehicles of that model that were produced; that number, in turn, is
averaged with the performance and production volumes of the rest of the
vehicles in the manufacturer's fleet to calculate the fleet's overall
performance. That performance is then compared against the
manufacturer's unique compliance obligation, which is the harmonic
average of the fuel economy and CO2 targets for the
footprints of the vehicles in the manufacturer's fleet, also
harmonically averaged and production-weighted. Using fuel economy
targets to illustrate the concept, the following figure shows two
vehicle models produced in a model year for which passenger cars are
subject to a fuel economy target function that extends from about 30
mpg for the largest cars to about 41 mpg for the smallest cars:
---------------------------------------------------------------------------
\798\ For readers unfamiliar with this process, it is not unlike
running a car on a treadmill following a program--or more
specifically, two programs. 49 U.S.C. 32904(c) states that EPA must
``use the same procedures for passenger automobiles [that EPA] used
for model year 1975 (weighted 55 percent urban cycle and 45 percent
highway cycle), or procedures that give comparable results.'' Thus,
the ``programs'' are the ``urban cycle,'' or Federal Test Procedure
(abbreviated as ``FTP'') and the ``highway cycle,'' or Highway Fuel
Economy Test (abbreviated as ``HFET''), and they have not changed
substantively since 1975. Each cycle is a designated speed trace (of
vehicle speed versus time) that all certified vehicles must follow
during testing--the FTP is meant to roughly simulate stop and go
city driving, and the HFET is meant to roughly simulate steady
flowing highway driving at about 50 mph.
\799\ Technically, for the CAFE program, carbon-based tailpipe
emissions (including CO2, CH4, and CO) are
measured and fuel economy is calculated using a carbon balance
equation. EPA uses carbon-based emissions (CO2,
CH4, and CO, the same as for CAFE) to calculate tailpipe
CO2 equivalent for the tailpipe portion of its standards.
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[[Page 43441]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.290
If these are the only two vehicles the manufacturer produces, the
manufacturer's required CAFE level is determined by calculating the
sales-weighted harmonic average of the targets applicable at the
hatchback and sedan footprints (about 41 mpg for the hatchback and
about 33 mpg for the sedan), and the manufacturer's achieved CAFE level
is determined by calculating the sales-weighted harmonic average of the
hatchback and sedan fuel economy levels (48 mpg for the hatchback and
25 mpg for the sedan). Depending on the relative mix of hatchbacks and
sedans the manufacturer produces, the manufacturer produces a fleet for
which the required and achieved levels are equal, or produce a fleet
that either earns (if required CAFE is less than achieved CAFE) or
applies (if required CAFE is greater than achieved CAFE) CAFE credits.
Although the arithmetic is different for CO2 standards
(which do not involve harmonic averaging), the concept is the same.
There are thus two parts to the foundation of compliance with CAFE
and CO2 emissions standards: First, how well any given
vehicle model performs relative to its target, and second, how many of
each vehicle model a manufacturer sells. While no given model need
precisely meet its target (and virtually no model exactly meets its
target in the real world), if a manufacturer finds itself producing and
selling large numbers of vehicles that fall well short of their
targets, it will have to find a way of offsetting that shortfall,
either by increasing production of vehicles that exceed their targets,
or by taking advantage of compliance flexibilities. Given that
manufacturers typically need to sell vehicles that consumers want to
buy, their options for pursuing the former approach can often be
limited.
The CAFE and CO2 programs both offer a number of
compliance flexibilities, discussed in more detail below. Some
flexibilities are provided for by statute, and some have been
implemented voluntarily by the agencies through regulations. Compliance
flexibilities for the CAFE and CO2 programs have a great
deal of theoretical attractiveness: If properly constructed, they can
help to reduce overall regulatory costs while maintaining or improving
programmatic benefits. If poorly constructed, they may create
significant potential for market distortion (for instance, when
manufacturers, in response to an incentive to deploy a particular type
of technology, produce vehicles for which there is no natural market,
such vehicles must be discounted below their cost in order to
sell).\800\ Use of compliance flexibilities without sufficient
transparency may complicate the ability to understand manufacturers'
paths to compliance. Overly-complicated flexibility programs can result
in greater
[[Page 43442]]
expenditure of both private sector and government resources to track,
account for, and manage. Moreover, targeting flexibilities toward
specific technologies could theoretically distort the market. By these
means, compliance flexibilities could create an environment in which
entities are encouraged to invest in such government-favored
technologies and, unless those technologies are independently supported
by market forces, encourage rent seeking in order to protect, preserve,
and enhance profits that are parasitic on the distortions created by
government mandate. Further, to the extent that there is a market
demand for vehicles with lower CO2 emissions and higher fuel
economy, compliance flexibilities may create competitive disadvantages
for some manufacturers if they become overly reliant on flexibilities
rather than simply improving their vehicles to meet that market demand.
---------------------------------------------------------------------------
\800\ Manufacturers are currently required by the state of
California to produce certain percentages of their fleets with
certain types of technologies, partly in order to help California
meet self-imposed GHG reduction goals. While many manufacturers
publicly discuss their commitment to these technologies, consumer
interest in them thus far remains low despite often-large financial
incentives from both manufacturers and the Federal and State
governments in the form of tax credits. It is questionable whether
continuing to provide significant compliance incentives for
technologies that consumers appear not to want is an efficient means
to achieve either compliance or national goals (see, e.g., Congress'
phase-out of the AMFA dual-fueled vehicle incentive in EISA, 49
U.S.C. 32906).
---------------------------------------------------------------------------
If standards are set at levels that are appropriate/maximum
feasible, then the need for extensive compliance flexibilities should
be low. Comment is sought on whether and how each agency's existing
flexibilities might be amended, revised, or deleted to avoid these
potential negative effects. Specifically, comment is sought on the
appropriate level of compliance flexibility, including credit trading,
in a program that is correctly designed to be both appropriate and
feasible. Comment is sought on allowing all incentive-based adjustments
to expire except those that are mandated by statute, among other
possible simplifications to reduce market distortion, improve program
transparency and accountability, and improve overall performance of the
compliance programs.
[GRAPHIC] [TIFF OMITTED] TP24AU18.291
[[Page 43443]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.292
[[Page 43444]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.293
[[Page 43445]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.294
[[Page 43446]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.295
BILLING CODE 4910-59-C
It is further noted that compliance is a measure of how a
manufacturer's fleet performance compares to its individual compliance
obligation and is generally not a measure of how the manufacturer's
fleet performance compares to other manufacturers' fleets or to some
industry-wide number.\801\ This is because the standards are attribute-
based, per Congress (in the case of CAFE, at least), rather than a
single ``flat'' mpg or g/mi number which each manufacturer's fleet must
meet. This means that a manufacturer can produce, for example, much
larger-footprint vehicles than it was expected to produce when the
standards (i.e., the curves) were set and still be in compliance
because its fleet performance is better than its compliance obligation
given the footprints of the vehicles it ended up producing. This also
means that a manufacturer can produce plenty of small-footprint
vehicles and still fall short of its compliance obligation if enough of
its vehicles fall below their targets and the manufacturer has no other
way of making up the shortfall. Whether the vehicles a manufacturer
produces are large or small therefore has no impact on compliance--
compliance depends, instead, on the performance of a manufacturer's
vehicles relative to their targets, averaged across the fleet as a
whole.
---------------------------------------------------------------------------
\801\ The exception is the CAFE program's minimum standard for
domestically-manufactured passenger cars, see Section III and V
above and 49 U.S.C. 32902.
---------------------------------------------------------------------------
The following sections discuss NHTSA's compliance and enforcement
program, EPA's compliance and enforcement program, and seek comment on
a variety of options with respect to the compliance flexibilities
currently available under each program. More broadly, the agencies are
taking the opportunity with this rulemaking to seek comment and
suggestions relating
[[Page 43447]]
to the current flexibilities allowed under the existing CAFE and
tailpipe CO2 programs (including eliminating or expanding
existing flexibilities). The agencies also seek comment on several
outstanding petitions relating to existing or newly-proposed
flexibilities, and the current credit trading system.
B. NHTSA Compliance and Enforcement
NHTSA's CAFE enforcement program is largely dictated by statute. As
discussed earlier in this notice, each vehicle manufacturer is subject
to separate CAFE standards for passenger cars and light trucks, and for
the passenger car standards, a manufacturer's domestically-manufactured
and imported passenger car fleets are required to comply
separately.\802\ Additionally, domestically-manufactured passenger cars
are subject to the statutory minimum standard.\803\
---------------------------------------------------------------------------
\802\ 49 U.S.C. 32904(b).
\803\ 49 U.S.C. 32902(b)(4).
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EPA calculates the fuel economy level of each fleet produced by
each manufacturer, and transmits that information to NHTSA; \804\ that
calculation includes adjustments to the fuel economy of individual
vehicles depending on whether they have certain incentivized
technologies.\805\ Manufacturers also report early product projections
to NHTSA per EPCA's reporting requirements, and NHTSA relies upon both
this manufacturer data and EPA-validated data to conduct its own
enforcement of the CAFE program. NHTSA also periodically releases
public reports through its CAFE Public Information Center (PIC) to
share recent CAFE program data.\806\
---------------------------------------------------------------------------
\804\ 49 U.S.C. 32904(c)-(e). EPCA granted EPA authority to
establish fuel economy testing and calculation procedures; EPA uses
a two-year early certification process to qualify manufacturers to
start selling vehicles, coordinates manufacturer testing throughout
the model year, and validates manufacturer-submitted final test
results after the close of the model year.
\805\ For example, alternative fueled vehicles get special
calculations under EPCA (49 U.S.C. 32905-32906), and fuel economy
levels can also be adjusted to reflect air conditioning efficiency
and ``off-cycle'' improvements, as discussed below.
\806\ NHTSA CAFE Public Information Center, https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Home.htm.
---------------------------------------------------------------------------
NHTSA then determines the manufacturer's compliance with each
applicable standard and notifies manufacturers if any of their fleets
have fallen short. Manufacturers have the option of paying civil
penalties on any shortfall or can submit credit plans to NHTSA. Credits
can either be earned or purchased and can be used either in the year
they were earned or in several years prior and following, subject to
various statutory constraints.
EPCA and EISA specify several flexibilities that are available to
help manufacturers comply with CAFE standards. Some flexibilities are
defined by statute--for example, while Congress required that NHTSA
allow manufacturers to transfer credits earned for over-compliance from
their car fleet to their truck fleet and vice versa, Congress also
limited the amount by which manufacturers could increase their CAFE
levels using those transfers.\807\ NHTSA believes Congress balanced the
energy-saving purposes of the statute against the benefits of certain
flexibilities and incentives and intentionally placed some limits on
certain statutory flexibilities and incentives. NHTSA has done its best
in crafting the credit transfer and trading regulations authorized by
EISA to ensure that total fuel savings are preserved when manufacturers
exercise their statutorily-provided compliance flexibilities.
---------------------------------------------------------------------------
\807\ See 49 U.S.C. 32903(g).
---------------------------------------------------------------------------
NHTSA and EPA have previously developed other compliance
flexibilities for the CAFE program under EPA's EPCA authority to
calculate manufacturer's fuel economy levels. As finalized in the 2012
final rule for MYs 2017 and beyond, EPA provides manufacturers
``credits'' under EPA's program and fuel economy ``adjustments'' or
``improvement values'' under NHTSA's program for: (1) Technologies that
cannot be measured on the 2-cycle test procedure, i.e., ``off-cycle''
technologies; and (2) air conditioning (A/C) efficiency improvements
that also improve fuel economy that cannot be measured on the 2-cycle
test procedure. Additionally, the programs give manufacturers
compliance incentives for utilizing ``game changing'' technologies on
pickup trucks, such as pickup truck hybridization.
The following sections outline how NHTSA determines whether
manufacturers are in compliance with the CAFE standards for each model
year, and how manufacturers may use compliance flexibilities to comply,
or address non-compliance by paying civil penalties. As mentioned
above, some compliance flexibilities are prescribed by statute and some
are implemented through EPA's EPCA authority to measure fuel economy,
such as fuel consumption improvement values for air conditioning
efficiency and off-cycle technologies. This proposal includes language
updating and clarifying existing regulatory text in this area. Comment
is sought on these changes, as well as on the general efficacy of these
flexibilities and their role in the fuel economy and GHG programs.
Moreover, the following sections explain how manufacturers submit
data and information to the agency--NHTSA is proposing to implement a
new standardized template for manufacturers to use to submit CAFE data
to the agency, as well as standardized templates for reporting credit
transactions. Additionally, NHTSA is proposing to add requirements that
specify the precision of the fuel savings adjustment factor in 49 CFR
536.4. These new proposals are intended to streamline reporting and
data collection from manufacturers, in addition to helping the agency
use the best available data to inform CAFE program decision making.
Finally, NHTSA provides an overview of CAFE compliance data for MYs
2011 through 2018 to demonstrate how manufacturers have responded to
the progressively increasing CAFE standards for those years. NHTSA
believes that providing this data is important because it gives the
public a better understanding of current compliance trends and the
potential impacts that CAFE compliance in those model years may have on
the future model years addressed by this rulemaking.
This is, of course, only an overview description of CAFE
compliance. NHTSA also granted a petition for rulemaking in 2016
requesting a number of changes to compliance-related topics.\808\ The
responses to those requests are discussed below. In general, there is a
tentatively decision to deny most of the Alliance and Global's requests
as discussed in the sections that follow. Comment is sought on these
tentative decisions, including what impact granting any of these
individual requests could have on effective stringency and compliance
pathways.
---------------------------------------------------------------------------
\808\ 81 FR 95553 (Dec. 28, 2016).
---------------------------------------------------------------------------
1. Light-Duty CAFE
(a) How does NHTSA determine compliance?
(1) Manufacturers Submit Data to NHTSA and EPA Facilitates CAFE Testing
EPCA, as amended by EISA, requires a manufacturer to submit reports
to the Secretary of Transportation explaining whether the manufacturer
will comply with an applicable CAFE standard for the model year for
which the report is made; the actions a manufacturer has taken or
intends to take to comply with
[[Page 43448]]
the standard; and other information the Secretary requires by
regulation.\809\ A manufacturer must submit a report containing the
above information during the 30-day period before the beginning of each
model year, and during the 30-day period beginning the 180th day of the
model year.\810\ When a manufacturer decides it is unlikely to comply
with its CAFE standard, the manufacturer must report additional actions
it intends to take to comply and include a statement about whether
those actions are sufficient to ensure compliance.\811\
---------------------------------------------------------------------------
\809\ 49 U.S.C. 32907(a).
\810\ Id.
\811\ Id.
---------------------------------------------------------------------------
To implement these reporting requirements, NHTSA issued 49 CFR part
537, ``Automotive Fuel Economy Reports,'' which specifies three types
of CAFE reports that manufacturers must submit to comply. Manufacturers
must first submit a pre-model year (PMY) report containing a
manufacturer's projected compliance information for that upcoming model
year. The PMY report must be submitted before December 31st of the
calendar year prior to the corresponding model year. Manufacturers must
then submit a mid-model year (MMY) report containing updated
information from manufacturers based upon actual and projected
information known midway through the model year. The MMY report must be
submitted by July 31 of the given model year. Finally, manufacturers
must submit a supplementary report anytime the manufacturer needs to
correct previously submitted information.
Manufacturers submit both non-confidential and confidential
versions of CAFE reports to NHTSA. Confidential reports differ in that
they include estimated production sales information that is withheld
from public disclosure to protect each manufacturer's competitive sales
strategies.
Manufacturer reports include information on light-duty automobiles
and medium-duty passenger vehicles for each model year and describe
projected and actual fuel economy standards, fuel economy performance
values, production volumes, information on vehicle design features
(e.g., engine displacement and transmission class), and other vehicle
attribute characteristics (e.g., track width, wheelbase, and other off-
road features for light trucks). Beginning with MY 2017, manufacturers
may also provide projected information on any air-conditioning (A/C)
systems with improved efficiency, off-cycle technologies (e.g., stop-
start systems), and any hybrid/electric full-size pickup truck
technologies used each model year to calculate the average fuel economy
specified in 40 CFR 600.510-12(c). Manufacturers identify the makes and
model types \812\ equipped with each technology, which compliance
category those vehicles belong to, and the associated fuel economy
adjustment value for each technology. In some cases, NHTSA may require
manufacturers to provide supplemental information to justify or explain
the benefits of these technologies. NHTSA requires manufacturers to
provide detailed information on the model types using these
technologies to gain fuel economy benefits. These details are necessary
to facilitate NHTSA's technical analyses and to ensure the agency can
perform random enforcement audits when necessary.
---------------------------------------------------------------------------
\812\ NHTSA collects model type information based upon the EPA
definition for ``modet type'' in 40 CFR 600.002.
---------------------------------------------------------------------------
NHTSA uses PMY, MMY, and supplemental reports to help the agency
and manufacturers anticipate potential compliance issues as early as
possible, and help manufacturers plan compliance strategies. NHTSA also
uses the reports for auditing purposes, which helps manufacturers
correct errors prior to the end of the model year and accordingly,
submit accurate final reports to EPA. Additionally, NHTSA issues public
reports twice a year that provide a summary of manufacturers' final and
projected fleet fuel economy performances values.
Throughout the model year, NHTSA also conducts vehicle testing as
part of its footprint validation program, to confirm the accuracy of
track width and wheelbase measurements submitted in manufacturer's
reports.\813\ This helps the agency better understand how manufacturers
may adjust vehicle characteristics to change a vehicle's footprint
measurement, and thus its fuel economy target.
---------------------------------------------------------------------------
\813\ U.S. Department of Transportation, NHTSA, Laboratory Test
Procedure for 49 CFR part 537, Automobile Fuel Economy Attribute
Measurements (Mar. 30, 2009), available at http://www.nhtsa.gov/DOT/NHTSA/Vehicle%20Safety/Test%20Procedures/Associated%20Files/TP-537-01.pdf.
---------------------------------------------------------------------------
NHTSA ultimately determines a manufacturer's compliance based on
CAFE data EPA receives in final model year reports. EPA verifies the
information, accounting for NHTSA and EPA testing, and forwards the
information to NHTSA. A manufacturer's final model year report must be
submitted to EPA no later than 90 days after December 31 of the model
year.
(2) Proposed Changes to CAFE Reporting Requirements
NHTSA is proposing changes to CAFE reporting requirements with the
intent to streamline reporting and data collection from manufacturers,
in addition to helping the agency use the best available data to inform
CAFE program decision-making. The agency requests comments on the
following reporting requirements.
(i) Standardized CAFE Report Templates
In a 2015 rulemaking, NHTSA proposed to amend 49 CFR part 537 to
require a new data format for light-duty vehicle CAFE reports.\814\
NHTSA introduced a new standardized template for collecting
manufacturer's CAFE information under 49 CFR 537.7(b) and (c) in order
to ensure the accuracy and completeness of data collected and to better
align with the final data provided to EPA. NHTSA explained that for MYs
2013-2015, most manufacturer reports NHTSA received did not conform to
all of the requirements specified in 49 CFR part 537. For example,
NHTSA identified several instances where manufacturers' CAFE reports
included ``yes'' or ``no'' values in response to requests for a
vehicle's numerical ground clearance values.
---------------------------------------------------------------------------
\814\ 80 FR 40540 (Jul. 13, 2015).
---------------------------------------------------------------------------
Some manufacturers contend that the changes in reporting
requirements may be one source of confusion. NHTSA is aware that
manufacturers seem to be confused about what footprint data is required
because of the modification to the base tire definition \815\ in the
2012 final rule for MYs 2017 and beyond. Specifically, these
manufacturers fail to understand the required reporting information for
model types based upon footprint values. Beginning in MY 2013,
manufacturers were to provide attribute-based target standards in
consideration of the change in the base tire definition for each unique
model type and footprint combination of the manufacturer's automobiles.
NHTSA has found cases where manufacturers did not aggregate their model
types by each unique footprint combination. Likewise, NHTSA found other
errors in manufacturers' vehicle information submissions. A review of
the MY 2015 PMY reports showed that several manufacturers provided the
required information incorrectly.
---------------------------------------------------------------------------
\815\ 49 CFR 523.2.
---------------------------------------------------------------------------
Problems with inaccurate or missing data have become an even
greater issue for manufacturers planning to use the new procedures for
A/C efficiency and off-cycle technologies, and incentives
[[Page 43449]]
for advanced full-sized pickup trucks.\816\ Manufacturers seeking to
take advantage of the new procedures and incentives must provide
information on the model types equipped with the technologies. However,
NHTSA has identified and contacted several manufacturers that have
failed to submit the required information in their 2017 and 2018 PMY
reports.
---------------------------------------------------------------------------
\816\ NHTSA allows manufacturers to use these incentives for
complying with standards starting in MY 2017.
---------------------------------------------------------------------------
Therefore, as part of this rulemaking, NHTSA is proposing to adopt
a standardized template for reporting all required data for PMY, MMY,
and supplemental CAFE reports. The template will be available through
the CAFE Public Information Center (PIC) website. NHTSA is also
proposing to make the PMY and MMY reports exactly the same; many
manufacturers already submit PMY reports and then update the MMY
reports with the same type of information. NHTSA believes that this
approach will further simplify reporting for manufacturers. Further,
NHTSA is expanding its CAFE reporting requirements for manufacturers to
provide additional vehicle descriptors, common EPA carline codes, and
more information on emerging technologies. Additional data columns will
be included in the reporting template for manufacturers to identify
these emerging technologies.
NHTSA believes adopting a standardized template will ensure
manufacturers provide the agency with all the necessary data in a
simpler, compliant format. The template would organize the required
data in a standardized and consistent manner, adopt formats for values
consistent with those provided to EPA, and calculate manufacturer's
target standards. This will also help NHTSA code CAFE electronic data
for use in the agency's electronic database system. Overall, these
changes are anticipated to drastically reduce manufacturer and
government burden for reporting under both EPCA/EISA and the Paperwork
Reduction Act.\817\
---------------------------------------------------------------------------
\817\ 44 U.S.C. 3501 et seq.
---------------------------------------------------------------------------
NHTSA seeks comment on the use of a standardized reporting
template, or on any possible changes to the proposed standardized
template, which is located in NHTSA's docket for review. Information on
fuel consumption improvement technologies (i.e., off-cycle) in the
template will be collected at the vehicle model type level. NHTSA plans
to revise the template as part of the Paperwork Reduction Act process.
(ii) Standardized Credit Trade Documents
A credit trade is defined in 49 CFR 536.3 as the receipt by NHTSA
of an instruction from a credit holder to place its credits in the
account of another credit holder. Traded credits are moved from one
credit holder to the recipient credit holder within the same compliance
category for which the credits were originally earned. If a credit has
been traded to another credit holder and is subsequently traded back to
the originating manufacturer, it will be deemed not to have been traded
for compliance purposes. NHTSA does not administer trade negotiations
between manufacturers and when a trade document is received the
agreement must be issued jointly by the current credit holder and the
receiving party. NHTSA does not settle contractual or payment issues
between trading manufacturers.
NHTSA created its CAFE database to maintain credit accounts for
manufacturers and to track all credit transactions. Credit accounts
consist of a balance of credits in each compliance category and vintage
held by the holder. While maintaining accurate credit records is
essential, it has become a challenging task for the agency given the
recent increase in credit transactions. Manufacturers have requested
NHTSA approve trade or transfer requests not only in response to end-
of-model year shortfalls but also during the model year when purchasing
credits to bank for future model years.
To reduce the burden on all parties, encourage compliance, and
facilitate quicker NHTSA credit transaction approval, the agency is
proposing to add a required template to standardize the information
parties submit to NHTSA in reporting a credit transaction. Presently,
manufacturers are inconsistent in submitting the information required
by 49 CFR 536.8, creating difficulty for NHTSA in processing
transactions. The template NHTSA is proposing is a simple spreadsheet
that trading parties fill out. When completed, parties will be able to
click a button on the spreadsheet to generate a transaction letter for
the parties to sign and submit to NHTSA, along with the spreadsheet.
Using this template simplifies the credit transaction process, and
ensures that trading parties are following the requirements for a
credit transaction in 49 CFR 536.8(a).\818\
---------------------------------------------------------------------------
\818\ Submitting a properly completed template and accompanying
transaction letter will satisfy the trading requirements in 49 CFR
part 536.
---------------------------------------------------------------------------
Additionally, the template includes an acknowledgement of the
fraud/error provisions in 49 CFR 536.8(f), and the finality provisions
of 49 CFR 536.8(g). NHTSA seeks comment on this approach, as well as on
any changes to the template that may be necessary to better facilitate
manufacturer credit transaction requests. The agency's proposed
template is located in NHTSA's docket for review. The finalized
template would be available on the CAFE PIC site for manufacturers to
use.
(iii) Credit Transaction Information
Though entities are permitted to trade CAFE credits, there is
limited public information available on credit transactions.\819\ As
discussed earlier, NHTSA maintains an online CAFE database with
manufacturer and fleetwide compliance information that includes year-
by-year accounting of credit balances for each manufacturer. While
NHTSA maintains this database, the agency's regulations currently state
that it does not publish information on individual transactions,\820\
and historically, NHTSA has not required trading entities to submit
information regarding the compensation (whether financial, or in terms
of other credits) manufacturers receive in exchange for credits.\821\
Thus, NHTSA's public database offers sparse information to those
looking to determine the value of a credit.
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\819\ Manufacturers may generate credits, but non-manufacturers
may also hold or trade credits. Thus, the word ``entities'' is used
to refer to those that may be a party to a credit transaction.
\820\ 49 CFR 536.5(e)(1).
\821\ NHTSA understands that not all credits are exchanged for
monetary compensation. If NHTSA were to require entities to report
compensation exchanged for credits, it would not be limited to
reporting monetary compensation.
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The lack of information regarding credit transactions means
entities wishing to trade credits have little, if any, information to
determine the value of the credits they seek to buy or sell. It is
widely assumed that the civil penalty for noncompliance with CAFE
standards largely determines the value of a credit, because it is
logical to assume that manufacturers would not purchase credits if it
cost less to pay noncompliance penalties instead, but it is unknown how
other factors affect the value. For example, a credit nearing the end
of its five-model-year lifespan would theoretically be worth less than
a credit with its full five-model-year lifespan remaining. In the
latter case, the credit holder would value the credit more, as it can
be used for a longer period of time.
In the interest of facilitating a transparent, efficient credit
trading
[[Page 43450]]
market, NHTSA is considering modifying its regulations to require
trading parties to submit the amount of compensation exchanged for
credits, in addition to the parties trading and the number of credits
traded in a transaction. NHTSA is considering amending its regulations
to permit the agency to publish information on these specific
transactions. NHTSA seeks comment on requiring these disclosures when
trades occur.
(iv) Precision of the CAFE Credit Adjustment Factor
EPCA, as amended by EISA, required the Secretary of Transportation
to establish an adjustment factor to ensure total oil savings are
preserved when manufacturers trade credits.\822\ The adjustment factor
applies to credits traded between manufacturers and to credits
transferred across a manufacturer's compliance fleets.
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\822\ 49 U.S.C. Sec. 32903(f)(1).
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In establishing the adjustment factor, NHTSA did not specify the
exact precision of the output of the equation in 49 CFR 536.4(b).
NHTSA's standard practice has been round to the nearest four decimal
places (e.g., 0.0001) for the adjustment factor. However, in the
absence of a regulatory requirement, many manufacturers have contacted
NHTSA for guidance, and NHTSA has had to correct several credit
transaction requests. In some instances, manufacturers have had to
revise signed credit trade documents and submit additional trade
agreements to properly address credit shortages.
NHTSA is proposing to add requirements to 49 CFR 536.4 specifying
the precision of the adjustment factor by rounding to four decimal
places (e.g., 0.0001). NHTSA has also included equations for the
adjustment factor in its proposed credit transaction report template,
mentioned above, with the same level of precision. NHTSA seeks comment
on this approach.
(3) NHTSA Then Analyzes EPA-Certified CAFE Values for Compliance
After manufacturers complete certification testing and submit their
final compliance values to EPA, EPA verifies the data and issues final
CAFE reports to manufacturers and NHTSA. NHTSA then identifies the
manufacturers' compliance categories (i.e., domestic passenger car,
imported passenger car, and light truck fleets) that do not meet the
applicable CAFE standards. NHTSA uses EPA-verified data to compare
fleet average standards with actual fleet performance values in each
compliance category. Each vehicle a manufacturer produces has a fuel
economy target based on its footprint (footprint curves are discussed
above in Section II.C), and each compliance category has a CAFE
standard measured in miles per gallon (mpg). If a vehicle exceeds its
target, it is a ``credit generator,'' if it falls short of its target,
it is a ``credit loser.'' Averaging these vehicles across a compliance
category, accounting for volume, equals a fleet average. A manufacturer
complies with NHTSA's fuel economy standard if its fleet average
performance is greater than or equal to its required standard, or if it
is able to use available compliance flexibilities, described below in
Section X.B.1.e., to resolve any shortfall.
If the average fuel economy level of the vehicles in a compliance
category falls below the applicable fuel economy standard, NHTSA
provides written notification to the manufacturer that it has not met
that standard. The manufacturer is required to confirm the shortfall
and must either submit a plan indicating how it will allocate existing
credits, or if it does not have sufficient credits available in that
fleet, how it will earn, transfer and/or acquire credits, or pay the
appropriate civil penalty. The manufacturer must submit a credit
allocation plan or payment within 60 days of receiving agency
notification.
NHTSA approves a credit allocation plan unless it finds the
proposed credits are unavailable or that it is unlikely that the plan
will result in the manufacturer earning sufficient credits to offset
the projected shortfall. If a plan is approved, NHTSA revises the
manufacturer's credit account accordingly. If a plan is rejected, NHTSA
notifies the manufacturer and requests a revised plan or payment of the
appropriate penalty. Similarly, if the manufacturer is delinquent in
submitting a response within 60 days, NHTSA takes action to immediately
collect a civil penalty. If NHTSA receives and approves a
manufacturer's plan to carryback future earned credits within the
following three years in order to comply with current regulatory
obligations, NHTSA will defer levying fines for non-compliance until
the date(s) when the manufacturer's approved plan indicates that the
credits will be earned or acquired to achieve compliance. If the
manufacturer fails to acquire or earn sufficient credits by the plan
dates, NHTSA will initiate non-compliance proceedings.\823\
---------------------------------------------------------------------------
\823\ See generally 49 CFR part 536.
---------------------------------------------------------------------------
In the event that a manufacturer does not comply with a CAFE
standard even after the consideration of credits, EPCA provides that
the manufacturer is liable for a civil penalty.\824\ Presently, this
penalty rate is set at $5.50 for each tenth of a mpg that a
manufacturer's average fuel economy falls short of the standard for a
given model year multiplied by the total volume of those vehicles in
the affected compliance category manufactured for that model year.\825\
All penalties are paid to the U.S. Treasury and not to NHTSA itself.
---------------------------------------------------------------------------
\824\ 49 U.S.C. Sec. 32912.
\825\ NHTSA proposed retaining the $5.50 civil penalty rate in
an April 2018 NPRM. See 83 FR 13904 (Apr. 2, 2018).
---------------------------------------------------------------------------
(4) Civil Penalties for Non-Compliance
A manufacturer is liable to the Federal government for a civil
penalty if it does not comply with its applicable average fuel economy
standard, after considering credits available to the manufacturer.\826\
---------------------------------------------------------------------------
\826\ 49 U.S.C. Sec. Sec. 32911-12.
---------------------------------------------------------------------------
As previously mentioned, the potential civil penalty rate is
currently $5.50 for each tenth of a mpg that a manufacturer's average
fuel economy falls short of the average fuel economy standard for a
model year, multiplied by the total volume of those vehicles in the
compliance category.
[GRAPHIC] [TIFF OMITTED] TP24AU18.334
Since the inception of the CAFE program, NHTSA has collected a
total of $890,427,578 in CAFE civil penalty payments. Generally, import
manufacturers have paid significantly more in civil penalties than
domestic manufacturers, with the majority of payments made by import
manufacturers for passenger cars and
[[Page 43451]]
not light trucks. Import passenger car manufacturers paid a total of
$890,057,188 in CAFE fines while domestic manufacturers paid a total of
$370,390.
Prior to the CAFE credit trade and transfer program, several
manufacturers opted to pay civil penalties instead of complying with
CAFE standards. Since NHTSA introduced trading and transferring,
manufacturers have largely traded or transferred credits in lieu of
paying civil penalties. NHTSA assumes that buying and selling credits
is a more cost-effective strategy for manufacturers than paying civil
penalties, in part because it seems logical that the price of a credit
is directly related to the civil penalty rate and decreases as a credit
life diminishes.\827\ Prior to trading and transferring, on average,
manufacturers paid $29,075,899 in civil penalty payments annually (a
total of $814,125,176 from model years 1982 to 2010). Since trading and
transferring, manufacturers now pay an annual average of $15,260,480
each model year. The agency notes that five manufacturers have paid
civil penalties since 2011 totaling $76,302,402, and no civil penalty
payments were made in 2015. However, over the next several years, as
stringency increases, manufacturers are expected to have challenges
with CAFE standard compliance.
---------------------------------------------------------------------------
\827\ See 49 CFR 536.4 for NHTSA's regulations regarding CAFE
credits.
---------------------------------------------------------------------------
(b) What Exemptions and Exclusions does NHTSA allow?
(a) Emergency and Law Enforcement Vehicles
Under EPCA, manufacturers are allowed to exclude emergency vehicles
from their CAFE fleet \828\ and all manufacturers that produce
emergency vehicles have historically done so. NHTSA is not proposing
any changes to this exclusion.
---------------------------------------------------------------------------
\828\ 49 U.S.C. Sec. 32902(e).
---------------------------------------------------------------------------
(b) Small Volume Manufacturers
Per 49 U.S.C. 32902(d), NHTSA established requirements for exempted
small volume manufacturers in 49 CFR part 525, ``Exemptions from
Average Fuel Economy Standards.'' The small volume manufacturer
exemption is available for any manufacturer whose projected or actual
combined sales (whether in the United States or not) are fewer than
10,000 passenger automobiles in the model year two years before the
model year for which the manufacturer seeks to comply. The manufacturer
must submit a petition with information stating that the applicable
CAFE standard is more stringent than the maximum feasible average fuel
economy level that the manufacturer can achieve. NHTSA must then issue
by Federal Register notice an alternative average fuel economy standard
for the passenger automobiles manufactured by the exempted
manufacturer. The alternative standard is the maximum feasible average
fuel economy level for the manufacturers to which the alternative
standard applies. NHTSA is not proposing any changes to the small
volume manufacturer provision or alternative standards regulations in
this rulemaking.
(c) What compliance flexibilities and incentives are currently
available under the CAFE program and how do manufacturers use them?
There are several compliance flexibilities that manufacturers can
use to achieve compliance with CAFE standards beyond applying fuel
economy-improving technologies. Some compliance flexibilities are
statutorily mandated by Congress through EPCA and EISA, specifically
program credits, including the ability to carry-forward, carry-back,
trade and transfer credits, and special fuel economy calculations for
dual- and alternative-fueled vehicles (discussed in turn, below).
However, 49 U.S.C. 32902(h) expressly prohibits NHTSA from considering
the availability of statutorily-established credits (either for
building dual- or alternative-fueled vehicles or from accumulated
transfers or traders) in determining the level of the standards. Thus,
NHTSA may not raise CAFE standards because manufacturers have enough of
those credits to meet higher standards. This is an important difference
from EPA's authority under the CAA, which does not contain such a
restriction, and which flexibility EPA has assumed in the past in
determining appropriate levels of stringency for its program.
NHTSA also promulgated compliance flexibilities in response to
EPA's exercise of discretion under its EPCA authority to calculate fuel
economy levels for individual vehicles and for fleets. These compliance
flexibilities, which were first introduced in the 2012 rule for MYs
2017 and beyond, include air conditioning efficiency improvement and
``off cycle'' adjustments, and incentives for advanced technologies in
full size pick-up trucks, including incentives for mild and strong
hybrid electric full-size pickup trucks and performance-based
incentives in full-size pickup trucks. As explained above, comment is
sought on all of these adjustments and incentives.
(1) Program Credits and Credit Trading
Generating, trading, transfer, and applying CAFE credits is
fundamentally governed by statutory mandates defined by Congress. As
discussed above in Section X.B.1., program credits are generated when a
vehicle manufacturer's fleet over-complies with its determined standard
for a given model year, meaning its vehicle fleet achieved a higher
corporate average fuel economy value than the amount required by the
CAFE program for that model year. Conversely, if the fleet average CAFE
level does not meet the standard, the fleet would incur debits (also
referred to as a shortfall). A manufacturer whose fleet generates
credits in a given model year has several options for using those
credits, including credit carry-back, credit carry-forward, credit
transfers, and credit trading.
Credit ``carry-back'' means that manufacturers are able to use
credits to offset a deficit that had accrued in a prior model year,
while credit ``carry-forward'' means that manufacturers can bank
credits and use them towards compliance in future model years. EPCA, as
amended by EISA, requires NHTSA to allow manufacturers to carry back
credits for up to three model years, and to carry forward credits for
up to five model years.\829\ EPA also follows these same limitations
under its GHG program.\830\
---------------------------------------------------------------------------
\829\ 49 U.S.C. Sec. 32903(a).
\830\ As part of its 2017-2025 GHG program final rulemaking, EPA
did allow a one-time CO2 carry-forward beyond five years,
such that any credits generated from MYs 2010 through 2016 will be
able to be used to comply with light duty vehicle GHG standards at
any time through MY 2021.
---------------------------------------------------------------------------
Credit ``transfer'' means the ability of manufacturers to move
credits from their passenger car fleet to their light truck fleet, or
vice versa. As part of the EISA amendments to EPCA, NHTSA was required
to establish by regulation a CAFE credit transferring program, now
codified at 49 CFR part 536, to allow a manufacturer to transfer
credits between its car and truck fleets to achieve compliance with the
standards. For example, credits earned by overcompliance with a
manufacturer's car fleet average standard could be used to offset
debits incurred because of that manufacturer's not meeting the truck
fleet average standard in a given year. However, EISA imposed a cap on
the amount by which a manufacturer could raise its CAFE standards
through transferred credits: 1 mpg for MYs 2011-2013; 1.5 mpg for MYs
2014-2017; and 2 mpg for MYs 2018 and
[[Page 43452]]
beyond.\831\ These statutory limits will continue to apply to the
determination of compliance with the CAFE standards. EISA also
prohibits the use of transferred credits to meet the minimum domestic
passenger car fleet CAFE standard.\832\
---------------------------------------------------------------------------
\831\ 49 U.S.C. Sec. 32903(g)(3).
\832\ 49 U.S.C. Sec. 32903(g)(4).
---------------------------------------------------------------------------
In their 2016 petition for rulemaking, the Alliance of Automobile
Manufacturers and Global Automakers (Alliance/Global or Petitioners)
asked NHTSA to amend the definition of ``transfer'' as it pertains to
compliance flexibilities.\833\ In particular, Alliance/Global requested
that NHTSA add text to the definition of ``transfer'' stating that the
statutory transfer cap in 49 U.S.C. 32903(g)(3) applies when the
credits are transferred. Alliance/Global assert that adding this text
to the definition is consistent with NHTSA's prior position on this
issue.
---------------------------------------------------------------------------
\833\ Auto Alliance and Global Automakers Petition for
rulemaking on Corporate Average Fuel Economy (June 20, 2016) at 13.
---------------------------------------------------------------------------
In the 2012-2016 final rule, NHTSA stated:
NHTSA interprets EISA not to prohibit the banking of transferred
credits for use in later model years. Thus, NHTSA believes that the
language of EISA may be read to allow manufacturers to transfer
credits from one fleet that has an excess number of credits, within
the limits specified, to another fleet that may also have excess
credits instead of transferring only to a fleet that has a credit
shortfall. This would mean that a manufacturer could transfer a
certain number of credits each year and bank them, and then the
credits could be carried forward or back `without limit' later if
and when a shortfall ever occurred in that same fleet.\834\
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\834\ 75 FR 25666 (May 7, 2010).
Following that final rule, NHTSA clarified via interpretation that
the transfer cap from EISA does not limit how many credits may be
transferred in a given model year, but it does limit the application of
transferred credits to a compliance category in a model year.\835\
``Thus, manufacturers may transfer as many credits into a compliance
category as they wish, but transferred credits may not increase a
manufacturer's CAFE level beyond the statutory limits.'' \836\
---------------------------------------------------------------------------
\835\ See, letter from O. Kevin Vincent, Chief Counsel, NHTSA to
Tom Stricker, Toyota (July 5, 2011). Available online at https://isearch.nhtsa.gov/files/10-004142%20--%20Toyota%20CAFE%20credit%20transfer%20banking%20--%205%20Jul%2011%20final%20for%20signature.htm (last accessed Apr.
18, 2018).
\836\ Id.
---------------------------------------------------------------------------
NHTSA believes the transfer caps in 49 U.S.C. 32903(g)(3) are still
properly read to limit the application of credits in excess of those
values. NHTSA understands that the language in the 2012-2016 final rule
could be read to suggest that the transfer cap applies at the time
credits are transferred. However, NHTSA believes its subsequent
interpretation--that the transfer cap applies at the time the credits
are used--is a more appropriate, plain language reading of the statute.
While manufacturers have approached NHTSA with various interpretations
that would allow them to circumvent the EISA transfer cap, NHTSA
believes it is improper to ignore a transfer cap Congress clearly
articulated. Therefore, NHTSA proposes to deny Alliance/Global's
petition to revise the definition of ``transfer'' in 49 CFR 536.3.
Credit ``trading'' means the ability of manufacturers to sell
credits to, or purchase credits from, one another. EISA allowed NHTSA
to establish by regulation a CAFE credit trading program, also now
codified at 49 CFR part 536, to allow credits to be traded between
vehicle manufacturers. EISA also prohibits manufacturers from using
traded credits to meet the minimum domestic passenger car CAFE
standard.\837\
---------------------------------------------------------------------------
\837\ 49 U.S.C. Sec. 32903(f)(2).
---------------------------------------------------------------------------
Under 49 CFR part 536, credit holders (including, but not limited
to manufacturers) have credit accounts with NHTSA where they can, as
outlined above, hold credits, use them to achieve compliance with CAFE
standards, transfer credits between compliance categories, or trade
them. A credit may also be cancelled before its expiration date, if the
credit holder so chooses. Traded and transferred credits are subject to
an ``adjustment factor'' to ensure total oil savings are preserved, as
required by EISA. EISA also prohibits credits earned before MY 2011
from being traded or transferred.
As discussed above, NHTSA is concerned with the potential for
compliance flexibilities to have unintended consequences. Given that
the credit trading program is optional under EISA, comment is sought on
whether the credit trading provisions in 49 CFR part 536 should cease
to apply beginning in MY 2022.
(a) Fuel Savings Adjustment Factor
Under NHTSA's credit trading regulations, a fuel savings adjustment
factor is applied when trading occurs between manufacturers, but not
when a manufacturer carries credits forward or carries back credits
within their own fleet. The Alliance/Global requested that NHTSA
require manufacturers to apply the fuel savings adjustment factor when
credits are carried forward or carried back within the same fleet,
including for existing, unused credits.
Per EISA, total oil savings must be preserved in NHTSA's credit
trading program.\838\ The provisions for credit transferring within a
manufacturer's fleet \839\ do not include the same requirement;
however, NHTSA prescribed a fuel savings adjustment factor that applies
to both credit trades between manufacturers and credit transfers
between a manufacturer's compliance fleets.\840\
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\838\ 49 U.S.C. Sec. 32903(f)(1).
\839\ 49 U.S.C. Sec. 32903(g).
\840\ See 49 CFR 536.5. See also 74 FR 14430 (Mar. 30, 2009)
(Per NHTSA's final rule for MY 2011 Average Fuel Economy Standards
for Passenger Cars and Light Trucks, ``There is no other clear
expression of congressional intent in the text of the statute
suggesting that NHTSA would have authority to adjust transferred
credits, even in the interest of preserving oil savings. However,
the goal of the CAFE program is energy conservation; ultimately, the
U.S. would reap a greater benefit from ensuring that fuel oil
savings are preserved for both trades and transfers. Furthermore,
accounting for traded credits differently than for transferred
credits does add unnecessary burden on program enforcement. Thus,
NHTSA will adjust credits both when they are traded and when they
are transferred so that no loss in fuel savings occurs'').
---------------------------------------------------------------------------
When NHTSA initially considered the preservation of oil savings,
the agency explained how one credit is not necessarily equal to
another. For example, the fuel savings lost if the average fuel economy
of a manufacturer falls one-tenth of an mpg below the level of a
relatively low standard are greater than the average fuel savings
gained by raising the average fuel economy of a manufacturer one-tenth
of a mpg above the level of a relatively high CAFE standard.\841\ The
effect of applying the adjustment factor is to increase the value of
credits earned for exceeding a relatively low CAFE standard for credits
that are intended to be applied to a compliance category with a
relatively high CAFE standard, and to decrease the value of credits
earned for exceeding a relatively high CAFE standard for credits that
are intended to be applied to a compliance category with a relatively
low CAFE standard.
---------------------------------------------------------------------------
\841\ 74 FR 14432 (Mar. 30, 2009).
---------------------------------------------------------------------------
Alliance/Global stated that while carry forward and carry back
credits have been used for many years, the CAFE standards did not
change during the Congressional CAFE freeze, meaning credits earned
during those years were associated with the same amount of fuel savings
from year to year.\842\ Alliance/Global suggest that because there is
no longer a Congressional CAFE freeze, NHTSA should apply the
adjustment
[[Page 43453]]
factor when moving credits within a manufacturer's fleet.
---------------------------------------------------------------------------
\842\ Auto Alliance and Global Automakers Petition for
rulemaking on Corporate Average Fuel Economy (June 20, 2016) at 10.
---------------------------------------------------------------------------
NHTSA has tentatively decided to deny Alliance/Global's request to
apply the fuel savings adjustment factor to credits that are carried
forward or carried back within the same fleet, to the extent that the
request would impact credits carried forward or backward retroactively
within manufacturer's compliance fleets (i.e., credits that were
generated prior to MY 2021, when this rule takes effect). NHTSA has
tentatively determined that applying the adjustment factor to credits
earned in model years past would be inequitable. Manufacturers planned
compliance strategies based, at least in part, on how credits could be
carried forward and backward, including the lack of an adjustment
factor when credits are carried forward or backward within the same
fleet. Thus, retroactively stating that manufacturers must apply the
adjustment factor in this situation could disadvantage certain
manufacturers, and result in windfalls for other manufacturers.
However, NHTSA seeks comment on whether the agency should apply the
fuel savings adjustment factor to credits that are carried forward or
carried back within the same fleet beginning with MY 2021.
(b) VMT Estimates for Fuel Savings Adjustment Factor
NHTSA uses a vehicle miles traveled (VMT) estimate as part of its
fuel savings adjustment equation to ensure that when traded or
transferred credits are used, fuel economy credits are adjusted to
ensure fuel oil savings is preserved.\843\ For model years 2017-2025,
NHTSA finalized VMT values of 195,264 miles for passenger car credits,
and 225,865 miles for light truck credits.\844\ These VMT estimates
harmonized with those used in EPA's GHG program. For model years 2011-
2016, NHTSA estimated different VMTs by model year.
---------------------------------------------------------------------------
\843\ See 49 CFR Sec. 536.4(c).
\844\ 77 FR 63130 (Oct. 15, 2012).
---------------------------------------------------------------------------
Alliance/Global requested that NHTSA apply fixed VMT estimates to
the fuel savings adjustment factor for MYs 2011-2016, similar to how
NHTSA handles MYs 2017-2021. NHTSA rejected a similar request from the
Alliance in the 2017 and later rulemaking, citing lack of scope, and
expressing concern about the potential loss of fuel savings.\845\
---------------------------------------------------------------------------
\845\ Id.
---------------------------------------------------------------------------
Alliance/Global argue that data from MYs 2011-2016 demonstrate that
no fuel savings would have been lost, as NHTSA had originally been
concerned about. Alliance/Global assert that by not revising the MY
2012-2016 VMT estimates, credits earned during that timeframe were
undervalued. Therefore, Alliance/Global argue that NHTSA should
retroactively revise its VMT estimates to ``reflect better the real
world fuel economy results.'' \846\
---------------------------------------------------------------------------
\846\ Auto Alliance and Global Automakers Petition for
rulemaking on Corporate Average Fuel Economy (June 20, 2016) at 11.
---------------------------------------------------------------------------
Such retroactive adjustments could unfairly penalize manufacturers
for decisions they made based on the regulations as they existed at the
time. As Alliance/Global acknowledge, adjusting vehicle miles travelled
estimates would disproportionately affect manufacturers that have a
credit deficit and were part of EPA's Temporary Lead-time Allowance
Alternative Standards (TLAAS). The TLAAS program sunsets for model
years 2021 and later. Given some manufacturers would be
disproportionately harmed were we to accept Alliance/Global's
suggestion, NHTSA has tentatively decided to deny Alliance/Global's
request to retroactively change the agency's VMT schedules for model
years 2011-2016. Alliance/Global's suggestion that a TLAAS manufacturer
would be allowed to elect either approach does not change the fact that
manufacturers in the TLAAS program made production decisions based on
the regulations as understood at the time.
(2) Special Fuel Economy Calculations for Dual and Alternative Fueled
Vehicles
As discussed at length in prior rulemakings, EPCA, as amended by
EISA, encouraged manufacturers to build alternative-fueled and dual-
(or flexible-) fueled vehicles by providing special fuel economy
calculations for ``dedicated'' (that is, 100%) alternative fueled
vehicles and ``dual-fueled'' (that is, capable of running on either the
alternative fuel or gasoline/diesel) vehicles.
Dedicated alternative fuel automobiles include electric, fuel cell,
and compressed natural gas vehicles, among others. NHTSA's provisions
for dedicated alternative fuel vehicles in 49 U.S.C. 32905(a) state
that the fuel economy of any dedicated automobile manufactured after
1992 shall be measured based on the fuel content of the alternative
fuel used to operate the automobile. A gallon of liquid alternative
fuel used to operate a dedicated automobile is deemed to contain .15
gallon of fuel. Under EPCA, for dedicated alternative fuel vehicles,
there are no limits or phase-out for this special fuel economy
calculation, unlike for duel-fueled vehicles, as discussed below.
EPCA's statutory incentive for dual-fueled vehicles at 49 U.S.C.
32906 and the measurement methodology for dual-fueled vehicles at 49
U.S.C. 32905(b) and (d) expire in MY 2019; therefore, NHTSA had to
examine the future of these provisions in the 2017 and later CAFE
rulemaking.\847\ NHTSA and EPA concluded that it would be inappropriate
to measure duel-fueled vehicles' fuel economy like that of conventional
gasoline vehicles with no recognition of their alternative fuel
capability, which would be contrary to the intent of EPCA/EISA.
Accordingly, the agencies proposed that for MY 2020 and later vehicles,
the general provisions authorizing EPA to establish testing and
calculation procedures would provide discretion to set the CAFE
calculation procedures for those vehicles.\848\ The methodology for
EPA's approach is outlined in the 2012 final rule for MYs 2017 and
beyond at 77 FR 63128 (Oct. 15, 2012). NHTSA seeks comment on the
current approach.
---------------------------------------------------------------------------
\847\ 77 FR 62651 (Oct. 15, 2012).
\848\ 49 U.S.C. Sec. Sec. 32904(a), (c).
---------------------------------------------------------------------------
(3) Incentives for Advanced Technologies in Full Size Pickup Trucks
In the 2012 final rule for MYs 2017 and beyond, EPA finalized
criteria that would provide an adjustment to the fuel economy of a
manufacturer's full size pickup trucks if the manufacturer employed
certain defined hybrid technologies for a significant quantity of those
trucks.\849\ Additionally, EPA finalized an adjustment to the fuel
economy of a manufacturer's full sized pickup truck if it achieved a
fuel economy performance level significantly above the CAFE target for
its footprint.\850\ This performance-based incentive recognized that
not all manufacturers may have wished to pursue hybridization, and
aimed to reward manufacturers for applying fuel-saving technologies
above and beyond what they might otherwise have done. EPA provided the
incentive for its GHG program under its CAA authority, and for the CAFE
program under its EPCA authority, similar to the A/C efficiency and
off-cycle adjustment values described below.
---------------------------------------------------------------------------
\849\ 77 FR 62651 (Oct. 15, 2012).
\850\ Id.
---------------------------------------------------------------------------
EPA established limits on the vehicles eligible to qualify for
these credits; a truck must meet minimum criteria for bed size and
towing or payload
[[Page 43454]]
capacity, and there are minimum sales thresholds (in terms of a
percentage of a manufacturer's full-size pickup truck fleet) that a
manufacturer must satisfy in order to qualify for the incentives.
Additionally, the incentives phase out at different rates through
2025--the mild hybrid incentive phases out in MY 2021, the strong
hybrid incentive phases out in 2025, the 15% performance incentive (10
g/mi) credit phases out in MY 2021, and the 20% performance incentive
(20 g/mi) credit is available for a maximum of five years between MYs
2017-2025, provided the vehicle's CO2 emissions level does
not increase.\851\
---------------------------------------------------------------------------
\851\ 77 FR 62651-2 (Oct. 15, 2012).
---------------------------------------------------------------------------
At the time of developing this proposal, no manufacturer has
claimed these full-size pickup truck credits. Some vehicle
manufacturers have announced potential collaborations, research
projects, or possible future introduction these technologies for this
segment.\852\ Additionally, similar to the incentive for hybridized
pickup trucks, the agency is not aware of any vehicle manufacturers
currently benefiting from the performance-based incentive. Comment is
sought on whether to extend either the incentive for hybrid full size
pickup trucks or the performance-based incentive past the dates that
EPA specified in the 2012 final rule for MYs 2017 and beyond.
---------------------------------------------------------------------------
\852\ At the time of this proposal, there is awareness of some
vehicle models that may qualify in future years should manufacturers
choose to claim these credits. For example, the 2019 Ram 1500
introduces a mild hybrid ``eTorque'' system (Sam Abuelsamid, 2019
Ram 1500 Gets 48V Mild Hybrid On All Gas Engines, Forbes (Jan. 15,
2019), https://www.forbes.com/sites/samabuelsamid/2018/01/15/2019-ram-1500-gets-standard-48v-mild-hybrid-on-all-gas-engines/#2a0cc967e9e6); Ford is expected to introduce a hybrid F-150 (Keith
Naughton, How Ford plans to market the gasoline-electric F-150,
Automotive News (November 30, 2017), http://www.autonews.com/article/20171130/OEM05/171139990/ford-electric-f150-pickup-marketing; and the Workhorse W-15 system includes both an electric
battery pack and gasoline range extender (Workhorse W-15 Pickup,
http://workhorse.com/pickup/ (last accessed April 13, 2018).
---------------------------------------------------------------------------
(4) Air Conditioning Efficiency and Off-Cycle Adjustment Values
A/C efficiency and off-cycle fuel consumption improvement values
(FCIVs) are compliance flexibilities made available under NHTSA's CAFE
program through EPA's EPCA authority to calculate fuel economy levels
for individual vehicles and for fleets. NHTSA modified its regulations
in the 2012 final rule for MYs 2017 and beyond to reflect the fact that
certain flexibilities, including A/C efficiency improving technologies
and off-cycle technology fuel consumption improvement values (FCIVs),
may be used as part of the determination of a manufacturers' CAFE
level.\853\
---------------------------------------------------------------------------
\853\ 77 FR 63130-34 (Oct. 15, 2012). Instead of manufacturers
gaining credits as done under the GHG program, a direct adjustment
is made to the manufacturer's fuel economy fleet performance value.
---------------------------------------------------------------------------
A/C is a virtually standard automotive accessory, with more than
95% of new cars and light trucks sold in the United States equipped
with mobile air conditioning systems. A/C use places load on an engine,
which results in additional fuel consumption; the high penetration rate
of A/C systems throughout the light duty vehicle fleet means that they
can significantly impact the total energy consumed, as well as GHG
emissions resulting from refrigerant leakage.\854\ A number of methods
related to the A/C system components and their controls can be used to
improve A/C system efficiencies.\855\
---------------------------------------------------------------------------
\854\ Notably, however, manufacturers cannot claim CAFE-related
benefits for reducing A/C leakage or switching to an A/C refrigerant
with a lower global warming potential, because while these
improvements reduce GHGs consistent with the purpose of the CAA,
they generally do not relate to fuel economy and thus are not
relevant to the CAFE program.
\855\ The approach for recognizing potential A/C efficiency
gains is to utilize, in most cases, existing vehicle technology/
componentry but improve the energy efficiency of the technology
designs and operation. For example, most of the additional air
conditioning-related load on an engine is because of the compressor,
which pumps the refrigerant around the system loop. The less the
compressor operates, the less load the compressor places on the
engine resulting in less fuel consumption and CO2
emissions. Thus, optimizing compressor operation with cabin demand
using more sophisticated sensors, controls and control strategies,
is one path to improving the efficiency of the A/C system. For
further discussion of A/C efficiency technologies, see Section II.D
of this NPRM and Chapter 6 of the accompanying PRIA.
---------------------------------------------------------------------------
``Off-cycle'' technologies are those that reduce vehicle fuel
consumption and CO2 emissions but for which the fuel
consumption reduction benefits are not recognized under the 2-cycle
test procedure used to determine compliance with the fleet average
standards. The CAFE city and highway test cycles, also commonly
referred to together as the 2-cycle laboratory compliance tests (or 2-
cycle tests), were developed in the early 1970s when few vehicles were
equipped with A/C systems. The city test simulates city driving in the
Los Angeles area at that time. The highway test simulates driving on
secondary roads (not expressways). The cycles are effective in
measuring improvements in most fuel economy improving technologies;
however, they are unable to measure or underrepresent some fuel economy
improving technologies because of limitations in the test cycles.
For example, air conditioning is turned off during 2-cycle testing.
Any air conditioning system efficiency improvements that reduce load on
the engine and improve fuel economy cannot be measured on the tests.
Additionally, the city cycle includes less time at idle than today's
real world driving, and the highway cycle is relatively low speed
(average speed of 48 mph and peak speed of 60 mph). Other off-cycle
technologies that improve fuel economy at idle, such as stop start, and
those that improve fuel economy to the greatest extent at expressway
speeds, such as active grille shutters which improve aerodynamics,
receive less than their real-world benefits in the 2-cycle compliance
tests.
Since EPA established its GHG program for light duty vehicles,
NHTSA and EPA sought to harmonize their respective standards, despite
separate statutory authorities limiting what the agencies could and
could not consider. For example, for MYs 2012-2016, NHTSA was unable to
consider improvements manufacturers made to passenger car A/C
efficiency in calculating compliance.\856\ At that time, NHTSA stated
that the agency's statutory authority did not allow NHTSA to provide
test procedure flexibilities that would account for A/C system and off-
cycle fuel economy improvements.\857\ Thus, NHTSA calculated its
standards in a way that allowed manufacturers to comply with the CAFE
standards using 2-cycle procedures alone.
---------------------------------------------------------------------------
\856\ 74 FR 49700 (Sept. 28, 2009).
\857\ At that time, NHTSA stated ``[m]odernizing the passenger
car test procedures, or even providing similar credits, would not be
possible under EPCA as currently written.'' 75 FR 25557 (May 7,
2010).
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Of the two agencies, EPA was the first to establish an off-cycle
technology program. For MYs 2012-2016, EPA allowed manufacturers to
request off-cycle credits for ``new and innovative technologies that
achieve GHG reductions that are not reflected on current test
procedures . . .'' \858\ In the subsequent 2017 and beyond rulemaking,
off-cycle technology was no longer required to be new and innovative,
but rather only required to demonstrate improvements not reflected on
test procedures.
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\858\ 75 FR 25341 (May 7, 2010).
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At that time (starting with MY 2017), NHTSA considered off-cycle
technologies and A/C efficiency improvements when assessing compliance
with the CAFE program. Accounting for off-cycle technologies and A/C
efficiency improvements in the CAFE program allowed manufacturers to
design vehicles with improved fuel
[[Page 43455]]
economy, even if the improvements would not show up on the 2-cycle
compliance test. In adding off-cycle and A/C efficiency improvements to
NHTSA's program, the agency was able to harmonize with EPA, which began
accounting for these features in earlier GHG regulations.
(a) Distinguishing ``Credits'' From Air Conditioning Efficiency and
Off-Cycle Benefits
It is important to note some important differences between
consideration given to A/C efficiency improvement and off-cycle
technologies, and other flexibilities in the CAFE program. NHTSA
accounts for A/C efficiency and off-cycle improvements through EPA test
procedural changes that determine fuel consumption improvement values.
While regarded by some as ``credits'' either as shorthand, or because
there are many terms that overlap between NHTSA's CAFE program and
EPA's GHG program, NHTSA's CAFE program does not give manufacturers
credits for implementing more efficient A/C systems, or introducing
off-cycle technologies.\859\ That is, there is no bankable, tradable or
transferrable credit earned by a manufacturer for implementing more
efficient A/C systems or installing an off-cycle technology. In fact,
the only credits provided for in NHTSA's CAFE program are those earned
by overcompliance with a standard.\860\ What NHTSA does for off-cycle
technologies and A/C efficiency improvements is adjust individual
vehicle compliance values based on the fuel consumption improvement
values of these technologies. As a result, a manufacturer's vehicle as
a whole may exceed its fuel economy target, and be regarded as a
credit-generating vehicle.
---------------------------------------------------------------------------
\859\ This is not to be confused with EPA's parallel program,
which refers to the GHG's consideration of A/C improvements and off-
cycle technologies as ``credits.''
\860\ 49 U.S.C. 32903.
---------------------------------------------------------------------------
Illustrative of this confusion, in the 2016 Alliance/Global
petition, the Petitioners asked NHTSA to avoid imposing unnecessary
restrictions on the use of credits. Alliance/Global referenced language
from an EPA report that stated compliance is assessed by measuring the
tailpipe emissions of a manufacturer's vehicles, and then reducing
vehicle compliance values depending on A/C efficiency improvements and
off-cycle technologies.\861\ This language is consistent with NHTSA's
statement in the 2017 and later final rule, in which explained how the
agencies coordinate and apply off-cycle and A/C adjustments. ``There
will be separate improvement values for each type of credit, calculated
separately for cars and for trucks. These improvement values are
subtracted from the manufacturer's 2-cycle-based fleet fuel consumption
value to yield a final new fleet fuel consumption value, which would be
inverted to determine a final fleet fuel CAFE value.'' \862\
---------------------------------------------------------------------------
\861\ See Alliance/Global petition at 15.
\862\ 77 FR 62726 (Oct. 15, 2012).
---------------------------------------------------------------------------
Alliance/Global say because of this process, ``technology credits
earned in the current model year must be immediately applied toward any
deficits in the current model year. This approach forces manufacturers
to use their credits in a sub-optimal way, and can result in stranded
credits.'' \863\ As explained in this section, NHTSA does not issue
credits to manufacturers for improving A/C efficiency, nor does it
issue credits for implementing off-cycle technologies. EPA does adjust
fuel economy compliance values on a vehicle level for those vehicles
that implement A/C efficiency improvements and off-cycle technologies.
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\863\ Id. at 16.
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NHTSA therefore proposes to deny Alliance/Global's request because
what the petitioners \864\ refer to as ``technology credits'' are
actually fuel economy adjustment values applied to the fuel economy
measurement of individual vehicles. Thus, these adjustments are not
actually ``credits,'' per the definition of a ``credit'' in EPCA/EISA
and are not subject to the ``carry forward'' and ``carry back''
provisions in 49 U.S.C. 32903.
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\864\ The agencies also refer to A/C and off cycle technology
adjustment values as ``credits'' sporadically throughout their
regulations. The agencies propose to amend their respective
regulatory texts to reflect these are adjustments and not actual
credits that can be carried forward or back. For a further
discussion, see above.
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To alleviate confusion, and to ensure consistency in nomenclature,
NHTSA is proposing to update language in its regulations to reflect
that the use of the term ``credits'' to refer to A/C efficiency and
off-cycle technology adjustments--should actually be termed fuel
consumption improvement values (FCIVs).
(b) Petition Requests on A/C Efficiency and Off-Cycle Program
Administration
As discussed above, NHTSA and EPA jointly administer the off-cycle
program. The 2016 Alliance/Global petition requested that NHTSA and EPA
make various adjustments to the off-cycle program; specifically, the
petitioners requested that the agencies should:
re-affirm that technologies meeting the stated
definitions are entitled to the off-cycle credit at the values
stated in the regulation;
re-acknowledge that technologies shown to generate more
emissions reductions than the pre-approved amount are entitled to
additional credit;
confirm that technologies not in the null vehicle set
but which are demonstrated to provide emissions reductions benefits
constitute off-cycle credits; and
modify the off-cycle program to account for
unanticipated delays in the approval process by providing that
applications based on the 5-cycle methodology are to be deemed
approved if not acted upon by the agencies within a specified
timeframe (for instance 90 days), subject to any subsequent review
of accuracy and good faith.
With respect to Alliance/Global's request regarding off-cycle
technologies that demonstrate emissions reductions greater than what is
allowable from the menu, today's preferred alternative retains this
capability. As was the case for model years 2017-2021, a manufacturer
is still eligible for a fuel consumption improvement value other than
the default value provided for in the menu, provided the manufacturer
demonstrates the fuel economy improvement.\865\ This would include the
two-tiered process for demonstrating the CO2 reductions and
fuel economy improvement.\866\
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\865\ 77 FR 62837 (Oct. 15, 2012).
\866\ 40 CFR 86.1869-12.
---------------------------------------------------------------------------
The Alliance/Global's requests to streamline aspects of the A/C
efficiency and off-cycle programs in response to the issues outlined
above have been considered. Among other things, the Alliance/Global
requested the agencies consider providing for a default acceptance of
petitions for off-cycle credits, provided that all required information
has been provided, to accelerate the processing of off-cycle credit
requests. While it is agreed that any continuation of the A/C
efficiency and off-cycle program should incorporate programmatic
improvements, there are significant concerns with the concept of
default accepting petition requests that do not address program issues
like uncertainty in quantifying program benefits, or general program
administration. Comment is requested comment on these issues.
Additionally, for a discussion of the consideration of inclusion of
the off-cycle program in future CAFE and GHG standards, see Section
X.D.
[[Page 43456]]
(c) Petition Requests on Including Air-Conditioning Efficiency
Improvements in the CAFE Calculations for MYs 2010-2016
For model years 2012 through 2016, NHTSA was unable \867\ to
consider improvements manufacturers made to passenger car A/C
efficiency in calculating CAFE compliance. \868\ However, EPA did
consider passenger car improvements to A/C efficiency for this
timeframe. To allow manufacturers to build one fleet that complied with
both EPA and NHTSA standards, NHTSA adjusted its standards to account
for the differences borne out of A/C efficiency improvements.
Specifically, the agencies converted EPA's g/mi standards to NHTSA mpg
(CAFE) standards. Then, EPA then estimated the average amount of
improvement manufacturers were expected to earn via improved A/C
efficiency. From there, NHTSA took EPA's converted mpg standard and
subtracted the average improvement attributable to improvement in A/C
efficiency. NHTSA set its standard at this level to allow manufacturers
to comply with both standards with similar levels of technology.\869\
---------------------------------------------------------------------------
\867\ At that time, NHTSA stated ``[m]odernizing the passenger
car test procedures, or even providing similar credits, would not be
possible under EPCA as currently written.'' 75 FR 25557 (May 7,
2010).
\868\ 74 FR 49700 (Sept. 28, 2009).
\869\ Id.
---------------------------------------------------------------------------
In the Alliance/Global petition for rulemaking, the Petitioners
requested that NHTSA and EPA revisit the average efficiency benefit
calculated by EPA applicable to model years 2012 through 2016. The
Alliance/Global argued that A/C efficiency improvements were not
properly acknowledged in the CAFE program, and that manufacturers that
exceeded the A/C efficiency improvements estimated by the agencies. The
Petitioners request that EPA amend its regulations such that
manufacturers would be entitled to additional A/C efficiency
improvement benefits retroactively.
NHTSA has tentatively decided to retain the structure of the
existing A/C efficiency program, and not extend it to model years 2010
through 2016. Likewise, EPA has tentatively decided not to modify its
regulations to change the way A/C efficiency improvements are accounted
for. It is believed this is appropriate as manufacturers decided what
fuel economy-improving technologies to apply to vehicles based on the
standards as finalized in 2010.\870\ This included deciding whether to
apply traditional tailpipe technologies, or A/C efficiency
improvements, or both. Granting A/C efficiency adjustments to
manufacturers retroactively could result in arbitrarily varying levels
of adjustments granted to manufacturers, similar to the Alliance/Global
request regarding retroactive off-cycle adjustments. Thus, it is
tentatively believed the existing A/C efficiency improvement structure
for model years 2010 through 2016 should remain unchanged.
---------------------------------------------------------------------------
\870\ In the MY 2017 and beyond rulemaking, NHTSA reaffirmed its
position it would not extend A/C efficiency improvement benefits to
earlier model years. 77 FR 62720 (Oct. 15, 2012).
---------------------------------------------------------------------------
(d) Petition Requests on Including Off-Cycle Improvements in the CAFE
Calculations for MYs 2010-2016
As described above, NHTSA first allowed manufacturers to generate
off-cycle technology fuel consumption improvement values equivalent to
CO2 off-cycle credits in MY 2017.\871\ In finalizing the
rule covering MYs 2017 and beyond, NHTSA declined to retroactively
extend its off-cycle program to apply to model years 2012 through
2016,\872\ explaining ``NHTSA did not take [off-cycle credits] into
account when adopting the CAFE standards for those model years. As
such, extending the credit program to the CAFE program for those model
years would not be appropriate.'' \873\
---------------------------------------------------------------------------
\871\ 77 FR 62840 (Oct. 15, 2012).
\872\ See id.; EPA decided to extend provisions from its MY 2017
and beyond off-cycle program to the 2012-2016 model years.
\873\ Id.
---------------------------------------------------------------------------
The Alliance/Global petition for rulemaking asked NHTSA to
reconsider calculating fuel economy for model years 2010 through 2016
to include off-cycle adjustments allowed under EPA's program during
that period. The Petitioners argued that NHTSA incorrectly stated the
agency had taken off-cycle adjustments into consideration when setting
standards for model years 2017 through 2025, but not for model years
2010-2016. The Alliance/Global also argued that because neither NHTSA
nor EPA considered off-cycle adjustments in formulating the stringency
of the 2012-2016 standards, NHTSA should retroactively grant
manufacturers off-cycle adjustments for those model years as EPA did.
Doing so, they say, would maintain consistency between the agencies'
programs.
Pursuant to the Alliance/Global request, NHTSA has reconsidered the
idea of granting retroactive credits for model years 2010 through 2016.
For the reasons that follow, NHTSA has tentatively decided that
manufacturers should not be granted retroactive off-cycle adjustments
for model years 2010 through 2016.
Of the two agencies, EPA was the first to establish an off-cycle
technology program. For model years 2012 through 2016, EPA allowed
manufacturers to request off-cycle credits for ``new and innovative
technologies that achieve GHG reductions that are not reflected on
current test procedures. . .'' \874\ In the subsequent 2017 and beyond
rulemaking, NHTSA joined EPA and included an off-cycle program for CAFE
compliance.
---------------------------------------------------------------------------
\874\ 75 FR 25341, 25344 (May 7, 2010). EPA had also provided an
option for manufacturers to claim ``early'' off-cycle credits in the
2009-2011 time frame.
---------------------------------------------------------------------------
The Alliance/Global petition cites a statement in the 2012-2016
final rule as affirmation that NHTSA took off-cycle adjustments into
account in formulating the 2012-2016 stringencies, and therefore should
allow manufacturers earn off-cycle benefits in model years that have
already passed. In particular, Alliance/Global point to a general
statement where NHTSA, while discussing consideration of the effect of
other motor vehicle standards of the Government on fuel economy, stated
that that rulemaking resulted in consistent standards across the
program.\875\ The Alliance/Global petition appears to take this
statement as a blanket assertion that NHTSA's consideration of all
``relevant technologies'' included off-cycle technologies. To the
contrary, as quoted above, NHTSA explicitly stated it had not
considered these off-cycle technologies.\876\
---------------------------------------------------------------------------
\875\ Id.
\876\ Likewise, EPA stated it had not considered off-cycle
technologies in finalizing the 2012-2016 rule. ``Because these
technologies are not nearly so well developed and understood, EPA is
not prepared to consider them in assessing the stringency of the
CO2 standards.'' Id. at 25438.
---------------------------------------------------------------------------
The fact that NHTSA had not taken off-cycle adjustments into
consideration in setting its 2012-2016 standards makes granting this
request inappropriate. Doing so would result in a question as to
whether the 2012-2016 standards were maximum feasible under 49 U.S.C.
32902(b)(2)(B). If NHTSA had not considered industry's ability to earn
off-cycle adjustments--an incentive that allows manufacturers to
utilize technologies other than those that were being modeled as part
of NHTSA's analysis--the agency could have concluded more stringent
standards were maximum feasible. Additionally, granting off-cycle
adjustments to manufacturers retroactively raises questions of equity.
NHTSA issued its 2012-2016 standards without an off-cycle program, and
manufacturers had
[[Page 43457]]
no reason to suspect that NHTSA would allow the use off-cycle
technologies to meet fuel economy standards. Therefore, manufacturers
made fuel economy compliance decisions with the expectation that they
would have to meet fuel economy standards using on-cycle technologies.
Generating off-cycle adjustments retroactively would arbitrarily reward
(and potentially disadvantage other) manufacturers for compliance
decisions they made without the knowledge such technologies would be
eligible for NHTSA's off-cycle program. Thus, NHTSA has tentatively
decided to deny Alliance/Global's request for retroactive off-cycle
adjustments.
It is worth noting that in the model years 2017 and later
rulemaking, NHTSA and EPA did include off-cycle technologies in
establishing the stringency of the standards. As Alliance/Global note,
NHTSA and EPA limited their consideration to start-stop and active
aerodynamic features, because of limited technical information on these
technologies. At that time, the agencies stated they ``have virtually
no data on the cost, development time necessary, manufacturability, etc
[sic] of these technologies. The agencies thus cannot project that some
of these technologies are feasible within the 2017-2025 timeframe.''
\877\
---------------------------------------------------------------------------
\877\ Draft Joint Technical Support Document: Rulemaking for
2017-2025 Light-Duty Vehicle Greenhouse Gas Emission Standards and
Corporate Average Fuel Economy Standards (November 2011). P. 5-57.
---------------------------------------------------------------------------
(d) Light-Duty CAFE Compliance Data for MYs 2011-2018
This proposal examines how manufacturers could respond to potential
future CAFE and CO2 standards. For the reader's reference,
this section provides a brief overview of how manufacturers have
responded to the progressively increasing CAFE standards for MYs 2011-
2018. NHTSA uses data from CAFE reports submitted by manufacturers to
EPA or directly to NHTSA to evaluate compliance with the CAFE program.
The data for model years 2011 through 2016 include manufacturers' final
compliance data that has been verified by EPA.\878\ The data for model
years 2017 and 2018 include the most recent estimated projections from
manufacturers' pre- and mid-model year (PMY and MMY) reports required
by 49 CFR part 537. Because the PMY and MMY data do not reflect final
vehicle production levels, the final CAFE values may be different than
the manufacturers' PMY and MMY estimates. Model year 2011 was selected
as the start of the data because it represents the first compliance
model year where manufacturers are permitted to trade and transfer
credits. The overview of the data for model years 2011 to 2018 is
important because it gives the public an understanding of current
compliance trends and the potential impacts that these years may have
on the future model years addressed by this rulemaking.
---------------------------------------------------------------------------
\878\ Volkswagen's model year 2016 final EPA verified compliance
data is excluded due to ongoing enforcement activites by EPA and
NHTSA for Volkswagen diesel vehicles.
---------------------------------------------------------------------------
Figure X-2 through Figure X-5 provide a graphical overview of fuel
economy performance and standards for model years 2011 to 2018. There
are separate graphs for the total overall industry fleet and each of
the three compliance categories, domestic and import passenger cars and
light trucks. Fuel economy performance is compared against the overall
industry fuel economy standards for each model year. Fuel economy
performance values include any increases from dual-fueled vehicles and
for vehicles equipped with fuel consumption improving
technologies.\879\ \880\ Compliance reflects the actual fuel economy
performance of the fleet, and does not include the application of prior
model year or future model year credits for overcompliance.
---------------------------------------------------------------------------
\879\ Congress established the Alternative Motor Fuels Act
(AMFA) which allows manufacturers to increase their fleet fuel
economy performance values by producing dual fueled vehicles.
Incentives are allowed for building advanced technology vehicles
such as hybrids and electric vehicles, compressed natural gas
vehicles and building vehicles able to run on dual fuels such as E85
and gasoline. For model years 1993 through 2014, the maximum
increase in CAFE performance for a manufacturer attributable to dual
fueled vehicles is 1.2 miles per gallon for each model year and
thereafter decreases by 0.2 miles per gallon each model year until
ending in 2019 (see 49 U.S.C. 32906).
\880\ Under EPA's authoirity, NHTSA established provisions
starting in model year 2017 allowing manufacturers to increase fuel
economy performance using the fuel consumption benefits gained by
technolongies not accounted for during normal 2-cycle EPA compliance
testing (i.e, called off-cycle technologies for technologies such as
stop-start systems) as well as for AC systems with improved
efficiencies and for hybrid or electric full size pickup trucks.
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[[Page 43458]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.296
[GRAPHIC] [TIFF OMITTED] TP24AU18.297
[[Page 43459]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.298
[GRAPHIC] [TIFF OMITTED] TP24AU18.299
As shown in the figures, manufacturers fuel economy performance for
the total fleet (the combination of all vehicles produced for sale
during the model year) and for each compliance fleet are better than
CAFE standards through MY 2015. On average, the total fleet exceeds
CAFE standards by approximately 0.9 mpg for MYs 2011 to 2015.
Comparatively, domestic and import passenger cars exceeded standards on
average by 2.1 mpg and 2.3 mpg, respectively. On aveage, light truck
manufacturers fell short of standards by 0.3 mpg on average over MYs
2011-2015.
For MYs 2016-2018 the overall industry is or is estimated to fall
short of CAFE standards for the overall fleet and for light trucks and
for import passenger cars fleets individually. For MYs 2016-2018, the
total fleet has an average shortfall of 0.5 mpg. The largest individual
shortfalls are 1.4 mpg for the light truck fleet in MY 2016 and 2.8 mpg
for the import passenger car fleet in MY 2018. Domestic passenger car
fleets are
[[Page 43460]]
expected to continue to exceed CAFE standards. NHTSA expects that on an
overall industry basis, manufacturers will apply carry forward and
traded CAFE credits to cover the MY 2016-2018 noncompliances.
Figure X-6 provides a historical overview of the industry's use of
CAFE compliance flexibilities for addressing shortfalls. MY 2015 is the
latest model year for which CAFE compliance is complete. Historically,
manufacturers have generally resolved credit shortfalls first by
carrying forward any earned credits and then applying traded credits.
In model years 2014 and 2015, the amount of credit shortfalls are
almost the same as the amount of carryforward and traded credits.
Manufacturers occastionally carryback credits or opt to transfer earned
credits between their fleets to resolve compliance shortfalls. Trading
credits from another manufacturer and transferring them across fleets
occurs far more frequently. Also, credit trading has taken the place of
civil penalty payments for resolving compliance shortfalls. Only a
handful of manufacturers have had to make civil penalty payments since
the implementation of the credit trading program.\881\
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\881\ Only five manufacturers have paid CAFE civil penalties
since credit trading began in 2011. Predominately, Jaguar Land Rover
has paid the largest amount of civil penalties, followed by Volvo.
See Summary of CAFE Civil Penalties Collected, CAFE Public
Information Center, https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Fines_LIVE.html.
[GRAPHIC] [TIFF OMITTED] TP24AU18.300
2. Medium- and Heavy-Duty Technical Amendments
In today's rule, NHTSA is proposing to make minor technical
revisions to correct typographical mistakes and improper references
adopted in the agency's 2016 Phase 2 medium- and heavy-duty fuel
efficiency rulemaking.\882\ The proposed changes are as follows:
---------------------------------------------------------------------------
\882\ 81 FR 73478 (Oct. 25, 2016).
---------------------------------------------------------------------------
1. NHTSA heavy-duty vehicles and engine fuel consumption credit
equations. In each credit equation in 49 CFR 535.7, the minus-sign in
each multiplication factor was omitted in the final version of the rule
sent to the Federal Register. For example, the credit equation in Part
535.7(b)(1) should be specified as, Total MY Fleet FCC (gallons) =
(Std-Act) x (Volume) x (UL) x (10-\2\) instead of (10\2\) as
currently existing. NHTSA is proposing to correct these omissions.
2. The CO2 to gasoline conversion factor. In 49 CFR 535.6(a)(4)(ii)
and (d)(5)(ii), NHTSA provides the methodology and equations for
converting the CO2 FELs/FCLs for heavy-duty pickups vans
(gram per mile) and for engines (grams per hp-hr) to their gallon-of-
gasoline equivalence. In each equation, NHTSA is proposing to change
the conversion factor to 8,887 grams per gallon of gasoline fuel
instead of a factor of 8,877 as currently existing.
3. Curb weight definition. In 40 CFR 523.2, the reference in the
definition for curb weight is incorrect. NHTSA is proposing to correct
the definition to incorporate the EPA reference in 40 CFR 86.1803
instead of 49 CFR 571.3.
C. EPA Compliance and Enforcement
EPA is requesting comment on a variety of ``enhanced
flexibilities'' whereby EPA would make adjustments to current
incentives and credits provisions and potentially add new flexibility
opportunities to broaden the pathways manufacturers would have to meet
standards. Such an approach would support the increased application of
technologies that the automotive industry is developing and deploying
that could potentially lead to further long-term emissions reductions
and allow manufacturers to comply with standards while reducing costs.
One category of flexibilities such as off-cycle credits and credit
banking involve credits that are based on real world emissions
reductions and do not represent a loss of overall emissions benefits or
a reduction in program stringency, yet offer manufacturers with
potentially lower-cost or more efficient paths to compliance. Another
category of flexibilities described below as incentives, such as
incentives for advanced technologies, hybrid technologies, and
alternative fuels, do
[[Page 43461]]
result in a loss of emissions benefit and represent a reduction in the
effective stringency of the standards to the extent the incentives are
used by manufacturers. These incentives would help manufacturers meet a
numerically more stringent standard but would not reduce real-world
CO2 emissions compared to a lower stringency option with
fewer such incentives in the short term. A policy rationale for
providing such incentives, as EPA articulated in the 2012
rulemakings,\883\ is that such provisions could incentivize advanced
technologies with the potential to lead to greater GHG emissions
reductions in the longer-term, where such technologies today are
limited by higher costs, market barriers, infrastructure, and consumer
awareness. Such incentive approaches would also result in rewarding
automakers who invest in certain technological pathways, rather than
being technology neutral.
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\883\ See 77 FR 62810-62826, October 15, 2012.
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Automakers and other stakeholders have expressed support for this
type of approach. For example, Ford recently stated ``[w]e support
increasing clean car standards through 2025 and are not asking for a
rollback. We want one set of standards nationally, along with
additional flexibility to help us provide more affordable options for
our customers.'' \884\ Honda also recently stated their support for an
approach that would retain the existing standards while extending the
advanced technology multipliers for electrified vehicles, eliminate
automakers' responsibility for the impact of upstream emissions from
the electric grid, and accommodate more off-cycle technologies.\885\
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\884\ ``A Measure of Progress'' By Bill Ford, Executive
Chairman, Ford Motor Company, and Jim Hackett, President and CEO,
Ford Motor Company, March 27, 2018, https://medium.com/cityoftomorrow/a-measure-of-progress-bc34ad2b0ed.
\885\ Honda Release ``Our Perspective--Vehicle Greenhouse Gas
and Fuel Economy Standards,'' April 20, 2018, http://news.honda.com/newsandviews/pov.aspx?id=10275-en.
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EPA has received input from automakers and other stakeholders,
including suppliers and alternative fuels industries, supporting a
variety of program flexibilities.\886\ EPA requests comments on the
following and other flexibility concepts, including the scope of the
flexibilities and the range of model years over which such provisions
would be appropriate.
---------------------------------------------------------------------------
\886\ Memorandum to docket EPA-HQ-OAR-2018-0283 regarding
meetings with the Alliance of Automobile Manufacturers on April 16,
2018 and Global Automakers on April 17, 2018.
---------------------------------------------------------------------------
The concepts include but are not limited to:
Advanced Technology Incentives: The current EPA GHG program
provides incentives for electric vehicles, fuel cell vehicles, plug-in
hybrid vehicles, and natural gas vehicles. Currently, manufacturers are
able to use a 0 g/mile emissions factor for all electric powered
vehicles rather than having to account for the GHG emissions associated
with upstream electricity generation up to a per-manufacturer
cumulative production cap for MYs 2022-2025. The program also includes
multiplier incentives that allow manufacturers to count advanced
technology vehicles as more than one vehicle in the compliance
calculations. The current multipliers begin with MY 2017 and end after
MY 2021.\887\ Stakeholders have suggested that these incentives should
be expanded to further support the production of advanced technologies
by allowing manufacturers to continue to use the 0 g/mile emissions
factor for electric powered vehicles rather than having to account for
upstream electricity generation emissions and by extending and
potentially increasing the multiplier incentives. EPA is considering a
range of incentives to further encourage advanced technology vehicles.
Examples of possible incentives and an estimate of their impact on the
stringency of the standards is provided below. Global Automakers
recently recommended a multiplier of 3.5 for EVs and fuel cell vehicles
which falls within the range of the examples provided below.\888\ EPA
requests comments on extending or increasing advanced technology
incentives including the use of 0 g/mile emissions factor for electric
powered vehicles and multiplier incentives, including multipliers in
the range of 2-4.5.
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\887\ The current multipliers are for EV/FCVs: 2017-2019--2.0,
2020--1.75, 2021--1.5; for PHEVs and dedicated and dual fuel CNG
vehicles: 2017-2019--1.6, 2020--1.45, 2021--1.3.
\888\ Memorandum to docket EPA-HQ-OAR-2018-0283 regarding
meetings with the Alliance of Automobile Manufacturers on April 16,
2018 and Global Automakers on April 17, 2018.
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Hybrid Incentives: The current program includes incentives for
automakers to use strong and mild hybrids (or technologies that provide
similar emissions benefits) in full size pick-up truck vehicles,
provided the manufacturer meets specified production thresholds.
Currently, the strong hybrid per vehicle credit is 20 g/mile, available
through MY 2025, and the technology must be used on at least 10% of a
company's full-size pickups to receive the credit for the model year.
The program also includes a credit for mild hybrids of 10 g/mi during
MYs 2017-2021. To be eligible a manufacturer would have to show that
the mild hybrid technology is utilized in a specified portion of its
truck fleet beginning with at least 20% of a company's full-size pickup
production in MY 2017 and ramping up to at least 80% in MY 2021.
EPA received input from automakers that these incentives should be
extended and available to all light-duty trucks (e.g., cross-over
vehicles, minivans, sport utility vehicles, smaller-sized pick-ups) and
not only full size pick-up trucks. Automakers also recommended that the
program's production thresholds should be removed because they
discourage the application of technology since manufacturers cannot be
confident of achieving the sales thresholds. Some stakeholders have
also suggested an additional credit for strong and mild hybrid
passenger cars. EPA seeks comment on whether these incentives should be
expanded along the lines suggested by stakeholders. For example, Global
Automakers recommends a 20 g/mile credit for strong hybrid light trucks
and a 10 g/mile credit for strong hybrid passenger cars. These
incentives could lead to additional product offerings of strong
hybrids, and technologies that offer similar emissions reductions,
which could enable manufacturers to achieve additional long-term GHG
emissions reductions.
Off-cycle Emission Credits: Starting with MY 2008, EPA started
employing a ``five-cycle'' test methodology to measure fuel economy for
the fuel economy label.\889\ However, for GHG and CAFE compliance, EPA
continues to use the established ``two-cycle'' (city and highway test
cycles, also known as the FTP and HFET) test methodology. As learned
through development of the ``five-cycle'' methodology and prior
rulemakings, there are technologies that provide real-world GHG
emissions and fuel consumption improvements, but those improvements are
not fully reflected on the ``two-cycle'' test. EPA established the off-
cycle credit program to provide an incentive for technologies that
achieve CO2 reductions but normally would not be chosen as a
GHG control strategy, as their GHG benefits are not measured on the
specified 2-cycle test. Automakers as well as auto suppliers have
recommended several changes to the current off-cycle credits program to
help it achieve that goal.\890\
[[Page 43462]]
Automakers and suppliers have suggested changes including:
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\889\ https://www.epa.gov/vehicle-and-fuel-emissions-testing/dynamometer-drive-schedules.
\890\ ``Petition for Direct Final Rule with Regard to Various
Aspects of the Corporate Average Fuel Economy Program and the
Greenhouse Gas Program,'' Auto Alliance and Global Automakers, June
20, 2016.
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Streamlining the program in ways that would give auto
manufacturers more certainty and make it easier for manufacturers to
earn credits;
Expanding the current pre-defined off-cycle credit menu to
include additional technologies and increasing credit levels where
appropriate;
Eliminating or increasing the credit cap on the pre-
defined list of off-cycle technologies and revising the thermal
technology credit cap; and
A role for suppliers to seek approval of their
technologies.
Under EPA's existing regulations, there are three pathways by which
a manufacturer may accrue off-cycle technology credits. The first is a
predetermined list or ``menu'' of credit values for specific off-cycle
technologies that may be used beginning for MY 2014.\891\ This pathway
allows manufacturers to use conservative credit values established by
EPA for a wide range of off-cycle technologies, with minimal data
submittal or testing requirements. In cases where additional laboratory
testing can demonstrate emission benefits, a second pathway allows
manufacturers to use 5-cycle testing to demonstrate and justify off-
cycle CO2 credits.\892\ The additional emission tests allow
emission benefits to be demonstrated over some elements of real-world
driving not captured by the GHG compliance tests, including high
speeds, rapid accelerations, and cold temperatures. Under this pathway,
manufacturers submit test data to EPA, and EPA decides whether to
approve the off-cycle credits without soliciting public comment on the
data. The third and last pathway allows manufacturers to seek EPA
approval, through a notice and comment process, to use an alternative
methodology other than the menu of 5-cycle methodology for determining
the off-cycle technology CO2 credits.\893\
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\891\ See 40 CFR 86.1869-12(b).
\892\ See 40 CFR 86.1869-12(c).
\893\ See 40 CFR 86.1869-12(d).
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EPA requests comments on changes to the off-cycle process that
would streamline the program. Currently, under the third pathway,
manufacturers submit an application that includes their methodology to
be used to determine the off-cycle credit value and data that then
undergoes a public review and comment process prior to an EPA decision
regarding the application. Each manufacturer separately submits an
application to EPA that must go through a public review and comment
process even if the manufacturer uses a methodology previously approved
by EPA. For example, under the current program, multiple manufacturers
have submitted applications for high efficiency alternators and
advanced air conditioning compressors using similar methodologies and
producing similar levels of credits.
EPA requests comment on revising the regulations to allow all auto
manufacturers to make use of a methodology once it has been approved by
EPA without the subsequent applications from other manufacturers
undergoing the public review process. This would reduce redundancy
present in the current program. Manufacturers would need to provide EPA
with at least the same level of data and detail for the technology and
methodology as the firm that went through the public comment process.
EPA also requests comment on revising the regulations to allow EPA
to, in effect, add technologies to the pre-approved credit menu without
going through a subsequent rulemaking. For example, if one or more
manufacturers submit applications with sufficient supporting data for
the same or similar technology, the data from that application(s) could
potentially be used by EPA as the basis for adding technologies to the
menu. EPA is requesting comment on revising the regulations to allow
EPA to establish through a decision document a credit value, or
scalable value as appropriate, and technology definitions or other
criteria to be used for determining whether a technology qualifies for
the new menu credit. This streamlined process of adding a technology to
the menu would involve an opportunity for public review but not a
formal rulemaking to revise the regulations, allowing EPA to add
technologies to the menu in a timely manner, where EPA believes that
sufficient data exists to estimate an appropriate credit level for that
technology across the fleet. In this process, EPA could issue a
decision document, after considering public comments, making the new
menu credits available to all manufacturers (effectively adding the
technology to the menu without changing the regulations each time). By
adding technologies to the menu, EPA would eliminate the need for
manufacturers to subsequently submit individual applications for the
technologies after the first application was approved.
In addition, EPA requests comments on modifying the menu through
this current rulemaking to add technologies. As noted above, EPA has
received data from multiple manufacturers on high efficiency
alternators and advanced air conditioning compressors that could serve
as the basis for new menu credits for these technologies.\894\ EPA
requests comments on adding these technologies to the menu including
comments on credit level and appropriate definitions.\895\ EPA also
requests comments on other off-cycle technologies that EPA could
consider adding to the menu including supporting data that could serve
as the basis for the credit.
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\894\ https://www.epa.gov/vehicle-and-engine-certification/compliance-information-light-duty-greenhouse-gas-ghg-standards
\895\ See EPA Memorandum to Docket EPA-HQ-OAR-2018-0283
``Potential Off-cycle Menu Credit Levels and Definitions for High
Efficiency Alternators and Advanced Air Conditioning Compressors.''
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In 2014, EPA approved additional credits for Mercedes-Benz \896\
stop-start system through the off-cycle credit process based on data
submitted by Mercedes on fleet idle time and its system's real-world
effectiveness (i.e., how much of the time the system turns off the
engine when the vehicle is stopped). Multiple auto manufacturers have
requested that EPA revise the table menu value for stop-start
technology based solely on one input value EPA considered, idle time,
in the context of the Mercedes stop-start system, but no firms have
provided additional data on any of the other factors which go into the
consideration of a conservative value for stop-start systems. Systems
vary significantly in hardware, design, and calibration, leading to
wide variations in how much of the idle time the engine is actually
turned off. EPA has learned that some stop-start systems may be less
effective in the real world than the agency estimated in its 2012
rulemaking analysis, for example, due to systems having a disable
switch available to the driver, or stop-start systems be disabled under
certain temperature conditions or auxiliary loads, which would offset
the benefits of the higher idle time estimates. EPA requests additional
data from the OEMs, suppliers, and other stakeholders regarding a
comprehensive update to the stop-start off-cycle credit table value.
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\896\ ``EPA Decision Document: Mercedes-Benz Off-cycle Credits
for MY 2012-2016,'' EPA-420-R-14-025, September 2014.
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The menu currently includes a fleetwide cap on credits of 10 g/mile
\897\ to address the uncertainty surrounding the data and analysis used
as the basis of the menu credits. Some stakeholders have expressed
concern that the current
[[Page 43463]]
cap may constrain manufacturers ability in the future to fully utilize
the menu especially if the menu is expanded to include additional
technologies, as described above. For example, Global Automakers
suggested that the cap be raised from 10 g/mi to 15 g/mi. EPA requests
comments on increasing the current cap, for example from the current 10
g/mile to 15 g/mile to accommodate increased use of the menu. EPA also
requests comment on a concept that would replace the current menu cap
with an individual manufacturer cap that scales with the manufacturer's
average fleetwide target levels. The cap would be based on a percentage
of the manufacturer's fleetwide 2-cycle emissions performance, for
example at 5-10% of CO2 a manufacturer's emissions fleet
wide target. With a cap of five for a manufacturer with a 2-cycle
fleetwide average CO2 level of 200 g/mile, for example, the
cap would be 10 g/mile. EPA believes this may be a reasonable and more
technically correct approach for the caps, recognizing that in many
cases the emissions benefits of off-cycle technologies correlate with
the CO2 levels of the vehicles, providing more or less
emissions reductions depending on the CO2 levels of the
vehicles in the fleet. For example, applying stop-start to vehicles
with higher vehicle idle CO2 levels provide more emissions
reductions than when applied to vehicles with lower idle emissions.
This approach also would help account for the uncertainty associated
with the menu credits and help ensure that off-cycle menu credits do
not become an overwhelming portion of the manufacturers overall
emissions reduction strategy.
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\897\ 40 CFR 86.1869-12(b)(2).
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The current GHG rule contains a CO2 credit program for
improvements to the efficiency of the air conditioning system on light-
duty vehicles (see Sec. 86.1868-12). The total of A/C efficiency
credits is calculated by summing the individual credit values for each
efficiency improving technology used on a vehicle as specified in the
air conditioning credit menu. The total credit sum for each vehicle is
capped at 5.0 grams/mile for cars and 7.2 grams/mile for trucks.
Additionally, the off-cycle credit program (see Sec. 86.1869-12)
contains credit earning opportunities for technologies that reduce the
thermal loads on the vehicle from environmental conditions (solar
loads, parked interior ambient air temperature). These menu-based
thermal control credits have separate cap limits under the off-cycle
program of 3.0 grams/mile for cars and 4.3 grams/mile for trucks. The
AC efficiency technologies and the thermal control technologies
directly interact with each other because improved thermal control
results in reduced air conditioning loads of the more efficient air
conditioning technologies. Because of this interaction, an approach
that would remove the thermal control credit program from the off-cycle
credit program and combine them with the AC efficiency program would
seem appropriate to quantify the combined impact. Additionally, a cap
that reflects this combination of these two related programs may also
be appropriate. For example, if combined, the credit cap for thermal
controls and air conditioning efficiency could be the combined value of
the current individual program caps of 8.0 grams/mile for cars and 11.5
grams/mile for trucks. This combined A/C efficiency and thermal
controls cap would also apply to any additional thermal control or air
conditioning efficiency technology credit generated through other off-
cycle credit pathways. Also, by removing the thermal credits from the
off-cycle menu, they would no longer be counted against the menu cap
discussed above, representing a way to provide more room under the menu
cap for other off-cycle technologies. Comment is sought on this
approach and the appropriateness of the described per vehicle cap
limits above.
As mentioned above, EPA has heard from many suppliers and their
trade associations an interest in allowing suppliers to have a role in
seeking off-cycle credits for their technologies. EPA requests comment
on providing a pathway for suppliers, along with at least one auto OEM
partner, to submit off-cycle applications for EPA approval. Auto
manufacturers would remain entirely responsible for the full useful
life emissions performance of the off-cycle technology as is currently
the case, including, for example, existing responsibilities for defect
reporting and the prohibition on defeat devices. Under such an
approach, an application submitted by a supplier and vehicle
manufacturer would establish a credit and/or methodology for
demonstrating credits that all auto manufacturers could then use in
their subsequent applications. This process could include full-vehicle
simulation modeling that is compatible with EPA's ALPHA simulation
tool. EPA requests comment on requiring that the supplier be partnered
in a substantive way with one or more auto manufacturers to ensure that
there is a practical interest in the technology prior to investing
resources in the approval process. The supplier application would be
subject to public review and comment prior to an EPA decision. However,
once approved, the subsequent auto manufacturer applications requesting
credits based on the supplier methodology would not be subject to
public review. EPA also requests comments on a concept where supplier
(with at least one auto manufacturer partner) demonstrated credits
would be available provisionally for a limited period of time, allowing
manufacturers to implement the technology and collect data on their
vehicles in order to support a continuation of credits for the
technology in the longer term. Also, the provisional credits could be
included under the menu credit cap since they would be based on a
general analysis of the technology rather than manufacturer-specific
data. EPA requests comments on all aspects of this approach.
Incentives for Connected or Autonomous Vehicles: Connected and
autonomous vehicles have the potential to significantly impact vehicle
emissions in the future, with their aggregate impact being either
positive or negative, depending on a large number of vehicle-specific
and system-wide factors. Currently, connected or autonomous vehicles
would be eligible for credits under the off-cycle program if a
manufacturer provides data sufficient to demonstrate the real-world
emissions benefits of such technology. However, demonstrating the
incremental real-world benefits of these emerging technologies will be
challenging. Stakeholders have suggested that EPA should consider an
incentive for these technologies without requiring individual
manufacturers to demonstrate real world emissions benefits of the
technologies. EPA believes that any near-term incentive program should
include some demonstration that the technologies will be both truly new
and have some connection to overall environmental benefits. EPA
requests comment on such incentives as a way to facilitate increased
use of these technologies, including some level of assurance that they
will lead to future additional emissions reductions.
Among the possible approaches, the most basic credits could be
awarded to manufacturers that produce vehicles with connected or
automated technologies. For connected vehicles, a set amount of credit
could be provided for each vehicle capable of Vehicle-to-Vehicle (V2V)
or Vehicle-to-Infrastructure (V2I) communications. One possible example
is to provide a set amount of credit, using the off-cycle menu, for any
vehicle that can
[[Page 43464]]
communicate basic safety messages (as outlined in SAE J2735) to other
vehicles. The credits provided would be an incentive to enable future
transportation system efficiencies, as these technologies on an
individual vehicle are unlikely to impact emissions in any meaningful
way. However, if these technologies are dispersed widely across the
fleet they could, under some circumstances, lead to future emission
reductions, and an incentive available to manufacturers now could help
facilitate that transformation.
The rationale for providing credits for vehicle automation is
similar to that for connected vehicles. EPA could provide a set credit
for vehicles that achieve some specific threshold of automation,
perhaps based on the industry standard SAE definitions (SAE J3016).
Individual autonomous vehicles might achieve some emissions reductions,
but the impact may increase as larger numbers of autonomous vehicles
are on the road and can coordinate and provide system efficiencies.
Providing credits for autonomous vehicles, again through a set credit,
would provide manufacturers a clear incentive to bring these
technologies to market. It would be important for any such program to
incentivize only those approaches that could reasonably be expected to
provide additional contributions to overall emission reductions, taking
system effects into account. As above, EPA believes that any near-term
incentive program should include some demonstration that the
technologies are truly new and have some connection to environmental
benefits overall.
A number of stakeholders have also requested that EPA consider
credits for automated and connected vehicles that are placed in
ridesharing or other high mileage applications, where any potential
environmental benefits could be multiplied due to the high utilization
of these vehicles. That is, credits could take into account that the
per-mile emission reduction benefits would accrue across a larger
number of miles for shared-use vehicles. There are likely many possible
approaches that could accomplish this objective. As one example, a
manufacturer who owns or partners with a shared-use mobility entity
could receive credit for ensuring that their autonomous vehicles are
used throughout the life of the vehicle in shared-use fleets rather
than as personally owned vehicles. Such credits would be based off of
the assumption that total vehicle miles travelled would be higher and,
therefore, generate more emission reduction benefits, under the former
case. Credits could be based off of the CO2 emissions
reduction of the autonomous fleet, taking into account the higher VMT
of the shared-use fleet, relative to the average.
As suggested by this partial list of examples, a variety of
approaches would be possible to incentivize the use of these
technologies. EPA seeks comment on these and related approaches to
incentivize autonomous and connected vehicle technologies where they
would have the most beneficial effect on future emissions.
Credit Carry-forward: Currently, CO2 credits may be
carried forward, or banked, for five years, with the exception that MY
2010-2015 credits may be carried forward and used through MY 2021.
Automakers have suggested a variety of ways in which GHG credit life
could be extended under the Clean Air Act, including the ability for
automakers to carry-forward MY 2010 and later banked credits out to MY
2025, extending the life of credits beyond five years, or even
unlimited credit life where credits would not expire. EPA believes
longer credit life would provide manufacturers with additional
flexibility to further integrate banked credits into their product
plans, potentially reducing costs. EPA requests comments on extending
credit carry-forward beyond the current five years, including unlimited
credit life.
Natural Gas Vehicle Credits: Vehicles that are able to run on
compressed natural gas (CNG) currently are eligible for an advanced
technology multiplier credit for MYs 2017-2021. Dual-fueled natural gas
vehicles, which can run either on natural gas or on gasoline, are also
eligible for an advanced technology multiplier credit if the vehicles
meet minimum CNG range requirements. EPA received input from several
industry stakeholders who supported expanding these incentives to
further incentivize vehicles capable of operating on natural gas,
including treating incentives for natural gas vehicles on par with
those for electric vehicles and other advanced technologies, and
adjusting or removing the minimum range requirements for dual-fueled
CNG vehicles. EPA requests comments on these potential additional
incentives for natural gas fueled vehicles.
High Octane Blends: EPA received input from renewable fuel industry
stakeholders and from the automotive industry supporting high octane
blends as a way to enable GHG reducing technologies such as higher
compression ratio engines. Stakeholders suggested that mid-level (e.g.,
E30) high octane ethanol blends should be considered and that EPA
should consider requiring that mid-level blends be made available at
service stations. Higher octane gasoline could provide manufacturers
with more flexibility to meet more stringent standards by enabling
opportunities for use of lower CO2 emitting technologies
(e.g., higher compression ratio engines, improved turbocharging,
optimized engine combustion). EPA requests comment on if and how EPA
could support the production and use of higher octane gasoline
consistent with Title II of the Clean Air Act.
To illustrate how additional flexibilities would translate to a
reduction in the stringency of the standards, EPA analyzed several
examples as described below.\898\ The example flexibilities EPA
selected for this analysis are (1) removing the requirement to account
for upstream emissions associated with electricity use (i.e., extending
the 0 g/mile emissions factor), (2) a range of higher multipliers for
electric vehicles, and (3) additional credits for hybrids sold in the
light-truck fleet. EPA estimated what each additional flexibility could
contribute to estimate an equivalent percent per year CO2
standard reduction it would represent on a fleetwide basis. The
examples and results are provided in the table below for several
example technology sales penetration values (three and six percent for
battery electric vehicles, 10 and 20% for mild hybrid light-trucks,
five and 10% for strong hybrid light-trucks). These examples were
chosen to provide a sense of the relationship between the additional
flexibility and program stringency. For each example scenario, EPA made
a number of assumptions regarding the fleet penetration of the
technology, car/truck mix, and others, which are documented in the
docket. Additional flexibilities could be structured to provide a level
of overall stringency equivalent to the full range of the Alternatives
EPA is requesting comment on in this proposal, from the proposed
standards through more stringent alternatives described above in this
section, including the ``No Action'' alternative.
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\898\ Memorandum, ``Spreadsheet tool for the comparative
analysis of program stringencies for various light-duty vehicle GHG
footprint curves and compliance flexibilities combinations,'' July
2018, Kevin Bolon, EPA Office of Air and Radiation. Docket No. EPA-
HQ-OAR-2018-0283.
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[[Page 43465]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.301
Table X-6 shows three examples of scenarios for how enhanced
flexibilities could impact overall program stringency. Example A
reduces the stringency of the EPA CO2 standard from 4.7% per
year to 4.0% per year. Example C, which includes the maximum incentive
flexibilities shown in Table X-5, significantly reduces the EPA
CO2 program stringency from 4.7% per year to 0.8% per year.
Increasing the BEV multipliers or hybrid credits beyond those listed in
Table XX by EPA would have the effect of further reducing the
stringency of the standards. EPA requests comment on the potential use
of enhanced program flexibilities as an alternative approach to
establishing the appropriate CO2 standards for MY 2021-2025.
EPA solicits comment on the individual options for flexibilities
and on the potential for combining them as described in these example
scenarios. For example, EPA solicits comments on how to take these
flexibilities into account in considering the level of the standards
and whether, for a given level of overall stringency, the factors
discussed in Section V above, regarding EPA Justification for the
Proposed GHG Standards, would support a relatively less stringent
standard with fewer flexibilities or a relatively more stringent
standard with more flexibilities. EPA also solicits comment on whether
any flexibilities or combinations of flexibilities in particular are
more or less consistent with the Administrator's rationale for
proposing Alternative 1.
[[Page 43466]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.302
D. Should NHTSA and EPA continue to account for air conditioning
efficiency and off-cycle improvements?
As stated in the 2012 NPRM and final rules for MYs 2017 and beyond,
the purpose of the off-cycle improvement incentive is to encourage the
introduction and market penetration of off-cycle technologies that
achieve real-world benefits.\899\ In the 2012 NPRM, NHTSA stated,
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\899\ 77 FR 63134 (Oct. 15, 2012).
. . . because we and EPA do not believe that we can yet reasonably
predict an average amount by which manufacturers will take advantage
of [the off-cycle FCIV] opportunity, it did not seem reasonable for
the proposed standards to include it in our stringency determination
at this time. We expect to re-evaluate whether and how to include
off-cycle credits in determining maximum feasible standards as the
off-cycle technologies and how manufacturers may be expected to
employ them become better defined in the future.\900\
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\900\ 76 FR 75226 (Dec. 1, 2011).
By the 2012 final rule, NHTSA and EPA had determined that it was
appropriate, under EPA's EPCA authority for testing and calculation
procedures, for the agencies to provide a fuel economy adjustment
factor for off-cycle technologies.\901\ NHTSA assessed some amount of
off-cycle credits in the determination of the maximum feasible
standards for the MYs covered by that rulemaking.\902\
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\901\ 77 FR 62628, 62649-50 (Oct. 15, 2012).
\902\ 77 FR 62727, 63018 (Oct. 15, 2012).
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The Draft TAR included an extended discussion of the history and
technological underpinnings of the A/C efficiency and off-cycle FCIV
measurement procedures; \903\ however, there is a belief that it is
also appropriate to now revisit the basic question of, and accordingly
comment is sought on, how A/C efficiency and off-cycle credits and
FCIVs fit in setting maximum feasible CAFE standards under EPCA/EISA,
and GHG standards consistent with EPA's authority under the CAA. It is
believed that it would be prudent to revisit factors that EPA
identified in their first 2009 NPRM to establish GHG emissions
standards,\904\ such as how to best ensure that any off-cycle credits
(and associated FCIVs) applied for using manufacturer proposed and
agency approved test procedures are verifiable, reflect real-world
reductions, are based on repeatable test procedures, and are developed
through a transparent process along with appropriate opportunities for
public comment. Whether the program is still serving its originally
intended purpose is also a determination to be made.
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\903\ See Draft TAR at 5-207 et seq.
\904\ See 74 FR 49482 (Sept. 28, 2009).
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1. Why were alternatives that phased out the A/C efficiency and off-
cycle programs considered?
As part of this rulemaking, alternatives were considered that phase
out the A/C efficiency and off-cycle compliance flexibilities to
reassess the benefits and costs of including these flexibilities in the
agencies' respective programs. The A/C efficiency and off-cycle
programs have been the subject of discussion and debate since the MYs
2017 and beyond final rule. The Alliance of Automobile Manufacturers
and Global Automakers petitioned the agencies to streamline aspects of
both agencies' A/C efficiency and off-cycle programs as part of a 2016
request to more broadly harmonize the CAFE and GHG programs (further
discussion of the Alliance/Global petition is located above). On the
other hand, other stakeholders have questioned the purpose and efficacy
of the off-cycle credit program, specifically, whether the agencies are
accurately capturing technology benefits and whether the programs are
unrealistically inflating manufacturers' compliance values. There are
two factors that may be important to consider at this time, (1)
manufacturer's increasing use of A/C efficiency and off-cycle
technologies to achieve compliance in light of the program's increasing
complexity; and (2) the questions of whether the agencies are
accurately accounting for
[[Page 43467]]
A/C efficiency and off-cycle benefits. In response to comments that the
programs in their current form were actually impeding innovative
technology growth, in particular from manufacturers, the concept was
considered to, instead of continuing to grow the A/C efficiency and
off-cycle flexibilities, assess two alternatives that would set
standards without the availability of A/C efficiency and off-cycle
credits for compliance. Each of these issues will be expanded upon, in
turn.
(a) Manufacturers' Increasing Reliance on the A/C Efficiency and Off-
cycle Programs To Achieve Compliance
Since the 2012 final rule for MYs 2017 and beyond and the Draft
TAR, manufacturers have increasingly utilized A/C efficiency and off-
cycle technology to achieve either credits under the GHG program, or
fuel consumption improvement values (FCIVs) under the CAFE program. A/C
efficiency and off-cycle technology use ranges among manufacturers,
from some manufacturers claiming zero grams/mile (or the equivalent
under the CAFE program), to some manufacturers claiming 7 grams/mile in
MY 2016.\905\ Accordingly, with some manufacturers' potentially
reaching the credit cap (10 grams/mile) during the timeframe
contemplated by this rulemaking, if not before, considerations relating
to manufacturers' increasing reliance on the A/C efficiency and off-
cycle programs for compliance, and the agencies' administration of the
programs, are presented for discussion.
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\905\ See Greenhouse Gas Emission Standards for Light-Duty
Vehicles: Manufacturer Performance Report for the 2016 Model Year
(EPA Report 420-R18-002), U.S. EPA (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGIA.pdf.
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These issues have not been raised sua sponte; rather,
manufacturers' comments on the A/C efficiency and off-cycle programs
have been increasing recently in volume. Specifically, manufacturers
asserted in their 2016 comments to the Draft TAR that ``[s]ignificant
volumes of off-cycle credits will be essential for the industry in
order to comply with the GHG and CAFE standards through 2025.'' \906\
Similarly, in its request for the agencies to more fully incorporate
estimated costs for A/C efficiency and off-cycle technologies in their
analysis, ICCT noted that ``companies are clearly prioritizing [off-
cycle] technologies over more advanced test-cycle efficiency
technologies.'' \907\
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\906\ Comment by Alliance of Automobile Manufacturers, Docket ID
NHTSA-2016-0068-0095, at 162. It is important to note the Alliance
submitted this statement in context of the CAFE and GHG levels set
in the 2012 final rule for MYs 2017 and beyond. Specifically, the
Alliance asserted ``[t]he Agencies included off-cycle credits from
only two technologies in their analyses for setting the stringency
of the standards (engine stop start and active aerodynamic
features). However, because the fuel consumption benefits of many
other technologies were overestimated in the Agencies' analyses, and
the standards were therefore set at very challenging levels, off-
cycle technologies and the associated GHG and fuel economy benefits
are viewed by the industry as a critical area that must become a
major source of credits.''
\907\ Comment by ICCT, Docket ID EPA-HQ-OAR-2015-0827-4017, at
10.
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Concurrent with the Alliance/Global's petition for the agencies to
take action on various aspects of the A/C efficiency and off-cycle
programs, other stakeholders raised issues about the programs that
could be discussed at this time. For example, ACEEE commented on the
Draft TAR that ``an off-cycle technology that is common in current
vehicles and is not reflected in the stringency of the standards has no
place in the off-cycle credit program. The purpose of the program is to
incentivize adoption of fuel saving technology, not to provide
loopholes for manufacturers to achieve the standards on paper.'' \908\
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\908\ Comment by ACEEE, Docket ID NHTSA-2016-0068-0078, at 14.
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Compare these comments with EPA's 2017 Light-Duty Automotive
Technology, Carbon Dioxide Emissions, and Fuel Economy Trends: 1975
Through 2017 report, which estimated that A/C efficiency and off-cycle
credits could, at most, ``reduce adjusted MY 2016 CO2
tailpipe emission values by about 7 g/mi, which would translate to an
adjusted fuel economy increase of approximately 0.5 mpg.'' \909\ A/C
and off-cycle flexibilities allow manufacturers to optionally apply a
wide array of technologies to improve fuel economy. While the agencies
do not require or incentivize the adoption of any particular
technologies, the industry is in fact expanding its use of more cost-
effective A/C efficiency and off-cycle technologies rather than other
technology pathways. Accordingly comment is sought on how large of a
role A/C efficiency and off-cycle technology should play in
manufacturer compliance. Is an adjusted fuel economy increase of
approximately 0.5 mpg noteworthy?
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\909\ Light-Duty Automotive Technology, Carbon Dioxide
Emissions, and Fuel Economy Trends: 1975 Through 2017, U.S. EPA at
141 (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGDW.pdf.
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Next, when manufacturers are increasingly reliant on A/C efficiency
and off-cycle technology to achieve compliance, agency administration
of the flexibility becomes more significant. The Alliance commented
that the industry ``needs the off-cycle credit program to function
effectively to fulfill the significant role that will be needed for
generating large quantities of credits from [off-cycle] emission
reduction.'' \910\ Moreover, the Alliance pointed out that ``[l]imited
Agency resources have delayed the processing of [petitions for off-
cycle credits], and the delay impedes manufacturers' ability to plan
for compliance or make investment decisions.'' \911\ More specifically,
the Alliance commented that:
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\910\ Comment by Alliance of Automobile Manufacturers, Docket ID
NHTSA-2016-0068-0095, at 166.
\911\ Id. at 167.
[c]ase-by-case approvals for off-cycle credit applications is
excessively burdensome due to slow agency response and unnecessary
testing. The procedures for granting off-cycle GHG credits are not
being implemented per the provisions of the regulation and are not
functioning to the level necessary for industry for long-term
compliance. Without timely processing, EPA works against its stated
intent of `provid[ing] an incentive for CO2 and fuel
consumption reducing off-cycle technologies that would otherwise not
be developed because they do not offer a significant 2-cycle
benefit.' \912\
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\912\ Comment by Alliance of Automobile Manufacturers, Docket ID
EPA-HQ-OA-2017-0190.
Notably, the agencies' implementation of the off-cycle credit
provisions has been described as ``underperforming.'' \913\
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\913\ Comment by Alliance of Automobile Manufacturers, Docket ID
NHTSA-2016-0068-0095, at 166.
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The Alliance's ``primarily regulatory need'' as of the 2016 Draft
TAR was ``a renewed focus on removing all obstacles that are having the
unintended result of slowing investment and implementation of [credit]
technologies.'' \914\ The Alliance stated generally that ``[w]ith the
pre-approved credit list properly administered, the off-cycle program
can be expected to grow toward the credit caps that were established in
the regulation, and these credit caps will become binding constraints
for many or most automobile manufacturers. At that point, the credit
caps will be counterproductive since they will impede greater
implementation of the beneficial off-cycle technologies.'' \915\
Similarly in regards to the agencies' refusal to grant off-cycle
credits for technologies like driver assistance systems, the Alliance
stated that ``[t]he unintended consequence of this is that automakers
may not be able to continue to pursue technologies that do not
[[Page 43468]]
provide certainty in supporting vehicle compliance.'' \916\
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\914\ Id. at xiv.
\915\ Id. at 164.
\916\ Id. at 126.
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These comments highlight the challenges to assure improvement
values from A/C efficiency and off-cycle technologies reflect
verifiable, real-world fuel economy improvements, are attributable to
specific vehicle models, are based on repeatable test procedures and
are developed through a transparent process with appropriate
opportunities for public comment. There is a belief this process and
these considerations are important to assure the integrity and fairness
of the A/C and off-cycle procedures. The menu and 5-cycle test
methodologies are predefined and are not subject to the in-depth review
that proposed new test procedures are subject to. Comment is sought on
whether and how menu-based A/C and off-cycle credits should be
implemented.
(b) Potential for Benefits To Be Double Counted
Next, the potential for technology benefits to be over-counted is
worth mention, but it is noted that aspects of this issue are being
addressed in this rulemaking. As stated in the 2012 final rule for MYs
2017 and beyond, fuel saving technologies integral to basic vehicle
design (e.g., camless engines, variable compression ratio engines,
micro air/hydraulic launch assist devices, advanced transmissions)
should not be eligible for off-cycle credits. Specifically, ``[b]eing
integral, there is no need to provide an incentive for their use, and
(more important), these technologies would be incorporated regardless.
Granting credits would be a windfall.'' \917\ Assumedly, because these
technologies are integral to basic vehicle design, their benefit would
be appropriately captured on the 2-cycle tests and 5-cycle tests.
Similarly, ICCT commented that, ``[i]n theory, off-cycle credits are a
good idea, as they encourage real-world fuel consumption reduction for
technologies that are not fully included on the official test cycles.
However, real-world benefits only accrue if double-counting is avoided
and the amount of the real-world fuel consumption reduction is
accurately measured.'' \918\
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\917\ 77 FR 62732 (Oct. 15, 2012).
\918\ Comment by ICCT, Docket EPA-HQ-OAR-2015-0827-4017, at 10.
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Broadly, there is agreement with the concept that capturing real-
world driving behavior is essential to accurately measure the true
benefits of A/C efficiency and off-cycle technologies. One example
where this holds true is in particular component testing as measured
with the federal standardized testing procedure. For example, the
federal test procedures provide specific guidance on how a vehicle
should be installed on the dynamometer, if the vehicle's windows should
be open or closed, and the vehicle's tire pressure. On the other hand,
the regulations provide no specific guidance on how other components
should be tested so the agencies and manufacturers can most accurately
quantify benefits.
For example, to more accurately capture the benefit of a high
efficiency alternator on the 2-cycle or 5-cycle test, the vehicle would
need to run more systems that draw power from the alternator, like the
infotainment system or temperature controlled seats. There is not
guidance for these additional components in the tests as they are
currently performed due to the complexity of systems available in the
light duty vehicle market. Essentially, it is uncertain how to define
in regulations what component systems need to be on or off during
testing to accurately capture the benefit of component synergies.
Developing guidance on specific systems would also likely require a
significant amount of time and resources. Comment is sought on specific
technologies that may be receiving more benefit based on the current
test procedures, or more generally, any other issues related to
integrated component testing.
It is noted, however, that the optional 5-cycle test procedure for
determining A/C and off-cycle improvement values over-counts benefits.
The 5-cycle test procedure weighs the 2-cycle tests used for compliance
with three additional test cycles to better represent real-world
factors impacting fuel economy and GHG emissions, including higher
speeds and more aggressive driving, colder temperature operation, and
the use of air conditioning. However, the current regulations
erroneously do not require that the 2-cycle benefit be subtracted from
the 5-cycle benefit, resulting in a credit calculation that is
artificially too high and not reflecting actual real-world emission
reductions that were intended. Since the 5-cycle test procedures
include the 2-cycle tests used for compliance, it is believed the 2-
cycle benefit should be subtracted from the 5-cycle benefit to avoid
over-counting of benefits. Manufacturers interested in generating
credits under the 5-cycle pathway identified this issue to the
agencies, and have asked EPA to clarify the regulations. This issue is
discussed in Section X.C, above, and comment is sought on how to
implement this correction.
2. Why was the phase-out as modeled (e.g., year over year reductions in
available FCIVs) for certain alternatives proposed?
The CAFE model was used to assess the economic, technical, and
environmental impacts of alternatives that kept the A/C efficiency and
off-cycle programs as is and alternatives that phased those programs
out. As described fully in Section II.B, the CAFE model is a software
simulation that begins with a recently produced fleet of vehicles and
applies cost effective technologies to each manufacturers' fleet year-
by-year, taking into consideration vehicle refresh and redesign
schedules and common parts among vehicles. The CAFE model outputs
technology pathways that manufacturers could use to comply with the
proposed policy alternatives.
For this NPRM, the modeling analysis uses the off-cycle credits
submitted by each manufacturer for MY 2017 compliance and carries these
forward to future years with a few exceptions. Several technologies
described in Section II.D are associated with off-cycle credits. In
particular, stop-start systems, integrated starter generators, and full
hybrids are assumed to generate off-cycle credits when applied to
improve fuel economy. Similarly, higher levels of aerodynamic
improvements are assumed to require active grille shutters on the
vehicle, which also qualify for off-cycle credits. The analysis assumes
that any off-cycle credits that are associated with actions outside of
technologies discussed in Section II.D (either chosen from the pre-
approved menu or petitioned for separately) remain at levels identified
by manufacturers in MY 2017. Any additional off-cycle credits that
accrue as the result of explicit technology application are calculated
dynamically in each year, for each alternative. This method allows for
the capture of benefits and costs from A/C efficiency and off-cycle
technologies as compared to an alternative where those technologies are
not used for compliance purposes.
In considering potential future actions regarding the A/C
efficiency and off-cycle flexibilities, it was recognized that removing
the programs immediately would present a considerable challenge for
manufacturers. Based on compliance and mid-model year data for MY 2017,
the first model year that NHTSA accepted FCIVs for CAFE compliance,
manufacturers have reported A/C efficiency and off-cycle FCIVs at
[[Page 43469]]
noteworthy levels. EPA's MY 2016 Performance Report reported wide
penetration of FCIVs from menu technologies and noted some technologies
widely employed by OEMs included active grill shutters, glass or
glazing, and stop-start systems. Additional details of individual
manufacturers' MY 2016 performance and individual A/C and off-cycle
technology penetration can be found on EPA's website.\919\ Accordingly,
a phase-out was identified as a reasonable option for manufacturers to
come into compliance with GHG or fuel economy standards without using
A/C efficiency and off-cycle improvements for compliance.
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\919\ See Greenhouse Gas Emission Standards for Light-Duty
Vehicles: Manufacturer Performance Report for the 2016 Model Year
(EPA Report 420-R18-002), U.S. EPA (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGIA.pdf.
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Throughout the joint CAFE and GHG programs, the agencies have
phased out flexibility and incentive programs rather than ending those
programs abruptly, such as with the alternative fuel vehicle program
(as mandated by EISA) \920\ and the credit program for advanced
technologies in pickup trucks.\921\ Accordingly, an incremental
decrease in the maximum A/C efficiency and off-cycle FCIVs a
manufacturer can receive starting in MY 2022 and ending in MY 2026 was
modeled. Table X-7 below shows the incremental cap total starting in MY
2021 and reducing by the recommended value until MY 2026.
---------------------------------------------------------------------------
\920\ 49 U.S.C. 32906.
\921\ For further discussion of the advanced technology pickup
truck program, see Section X.B.1.e.4, above.
[GRAPHIC] [TIFF OMITTED] TP24AU18.303
The MY 2016 fleet final compliance data to identify the starting
point for the FCIV phase-out was reviewed.\922\ For A/C efficiency
technologies, 6 grams/mile was used as the starting point, which was
the highest FCIV a single manufacturer had received in MY 2016. For
off-cycle technologies, the maximum allowable cap of 10 gram/mile set
in the 2012 final rule for MYs 2017 and beyond was used. Although no
manufacturer had reached the 10 gram/mile cap as of MY 2016, there is a
belief that it is still feasible for some manufacturers to reach the
cap in MYs prior to 2021. Comment is invited on this methodology.
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\922\ See Greenhouse Gas Emission Standards for Light-Duty
Vehicles: Manufacturer Performance Report for the 2016 Model Year
(EPA Report 420-R18-002), U.S. EPA (Jan. 2018), available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100TGIA.pdf.
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3. What do the modeled alternatives show?
A lower \923\ and higher \924\ stringency alternative with and
without the A/C efficiency and off-cycle flexibilities were modeled to
see the impact on regulatory costs, average vehicle prices, societal
costs and benefits, average achieved fuel economy, and fuel
consumption, among other attributes. The alternatives and associated
impacts presented below are compared to a baseline where EPA's GHG
emissions standards for MYs 2022-2025 remain in effect and NHTSA's
augural CAFE standards would be in place (for further discussion of the
interpretation of what baseline is appropriate, see preamble Section
II.B and PRIA Chapter 6).
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\923\ Existing standards through MY 2020, then 0.5%/year
increases for both passenger cars and light trucks for MYs 2021-
2026.
\924\ Existing standards through MY 2020, then 2%/year increases
for passenger cars and 3%/year increases for light trucks, for MYs
2021-2026.
---------------------------------------------------------------------------
The modeling results indicated no significant change in the fleet
average achieved fuel economy, which is expected because the model only
applies technologies to a manufacturers' fleet until the standard is
met. However, the change in regulatory costs, average vehicle prices,
societal costs, and societal net benefits is noteworthy. Without A/C
efficiency and off-cycle technologies available, the CAFE model applied
more costly technologies to the fleet. This trend was less noticeable
with the low stringency alternative; however, the advanced technology
required to meet the high stringency alternative without A/C efficiency
or off-cycle technology was more expensive. Similarly, although the
CAFE model only applied technology to the fleet until the fleet met the
standards, alternatives that did not employ A/C efficiency and off-
cycle technologies saved more fuel and reduced GHG emissions more than
alternatives that did employ the A/C efficiency and off-cycle
technologies, and in significantly higher amounts for the higher
stringency alternative. On average, the modeling shows that phasing out
the A/C efficiency and off-cycle programs decreases fuel consumption
over the ``no change'' scenario but confirms that manufacturers will
have to apply costlier technology to meet the standards.
The slight difference in fleet performance under the different
alternatives confirms how the CAFE model considers the universe of
applicable technologies and
[[Page 43470]]
dynamically identifies the most cost-effective combination of
technologies for each manufacturer's vehicle fleet based on the
assumptions about each technology's effectiveness, cost, and
interaction with all other technologies. For further discussion of the
technology pathways employed in the CAFE model, please refer to Section
II.D above.
XI. Public Participation
NHTSA and EPA request comment on all aspects of this NPRM. This
section describes how you can participate in this process.
A. How do I prepare and submit comments?
In this NPRM, there are many issues common to both NHTSA's and
EPA's proposals. For the convenience of all parties, comments submitted
to the NHTSA docket will be considered comments to the EPA docket and
vice versa. An exception is that comments submitted to the NHTSA docket
on NHTSA's Draft Environmental Impact Statement (EIS) will not be
considered submitted to the EPA docket. Therefore, commenters only need
to submit comments to either one of the two agency dockets, although
they may submit comments to both if they so choose. Comments that are
submitted for consideration by only one agency should be identified as
such, and comments that are submitted for consideration by both
agencies should also be identified as such. Absent such identification,
each agency will exercise its best judgment to determine whether a
comment is submitted on its proposal.
Further instructions for submitting comments to either the NHTSA or
the EPA docket are described below.
NHTSA: Your comments must be written and in English. To ensure that
your comments are correctly filed in the docket, please include the
docket number NHTSA-2018-0067 in your comments. Your comments must not
be more than 15 pages long.\925\ NHTSA established this limit to
encourage you to write your primary comments in a concise fashion.
However, you may attach necessary additional documents to your
comments, and there is no limit on the length of attachments. If you
are submitting comments electronically as a PDF (Adobe) file, we ask
that the documents please be scanned using the Optical Character
Recognition (OCR) process, thus allowing the agencies to search and
copy certain portions of your submissions.\926\ Please note that
pursuant to the Data Quality Act, in order for substantive data to be
relied upon and used by the agency, it must meet the information
quality standards set forth in the OMB and DOT Data Quality Act
guidelines. Accordingly, we encourage you to consult the guidelines in
preparing your comments. OMB's guidelines may be accessed at https://www.gpo.gov/fdsys/pkg/FR-2002-02-22/pdf/R2-59.pdf. DOT's guidelines may
be accessed at https://www.transportation.gov/regulations/dot-information-dissemination-quality-guidelines.
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\925\ 49 CFR 553.21.
\926\ Optical character recognition (OCR) is the process of
converting an image of text, such as a scanned paper document or
electronic fax file, into computer-editable text.
---------------------------------------------------------------------------
EPA: Direct your comments to Docket ID No. EPA-HQ-OAR-2018-0283.
EPA's policy is that all comments received will be included in the
public docket without change and may be made available online at http://www.regulations.gov, including any personal information provided,
unless the comment includes information claimed to be Confidential
Business Information (CBI) or other information whose disclosure is
restricted by statute. Do not submit information that you consider to
be CBI or otherwise protected through http://www.regulations.gov or
email. The http://www.regulations.gov website is an ``anonymous
access'' system, which means EPA will not know your identity or contact
information unless you provide it in the body of your comment. If you
send an email comment directly to EPA without going through http://www.regulations.gov, your email address will be automatically captured
and included as part of the comment that is placed in the public docket
and made available on the internet. If you submit an electronic
comment, EPA recommends that you include your name and other contact
information in the body of your comment and with any disk or CD-ROM you
submit. If EPA cannot read your comment due to technical difficulties
and cannot contact you for clarification, EPA may not be able to
consider your comment. Electronic files should avoid the use of special
characters, any form of encryption, and be free of any defects or
viruses. For additional information about EPA's public docket visit the
EPA Docket Center homepage at https://www.epa.gov/dockets.
B. Tips for Preparing Your Comments
When submitting comments, please remember to:
Identify the rulemaking by docket number and other
identifying information (subject heading, Federal Register date and
page number).
Explain why you agree or disagree, suggest
alternatives, and substitute language for your requested changes.
Describe any assumptions and provide any technical
information and/or data that you used.
If you estimate potential costs or burdens, explain how
you arrived at your estimate in sufficient detail to allow for it to
be reproduced.
Provide specific examples to illustrate your concerns
and suggest alternatives.
Explain your views as clearly as possible, avoiding the
use of profanity or personal threats.
Make sure to submit your comments by the comment period
deadline identified in the DATES section above.
C. How can I be sure that my comments were received?
NHTSA: If you submit your comments to NHTSA's docket by mail and
wish DOT Docket Management to notify you upon its receipt of your
comments, please enclose a self-addressed, stamped postcard in the
envelope containing your comments. Upon receiving your comments, Docket
Management will return the postcard by mail.
D. How do I submit confidential business information?
Any confidential business information (CBI) submitted to one of the
agencies will also be available to the other agency. However, as with
all public comments, any CBI information only needs to be submitted to
either one of the agencies' dockets and it will be available to the
other. Following are specific instructions for submitting CBI to either
agency:
EPA: Do not submit CBI to EPA through http://www.regulations.gov or
email. Clearly mark the part or all of the information that you claim
to be CBI. For CBI information in a disk or CD-ROM that you mail to
EPA, mark the outside of the disk or CD-ROM as CBI and then identify
electronically within the disk or CD-ROM the specific information that
is claimed as CBI. In addition to one complete version of the comment
that includes information claimed as CBI, a copy of the comment that
does not contain CBI must be submitted for inclusion in the public
docket. Information so marked will not be disclosed except in
accordance with the procedures set forth in 40 CFR part 2.
NHTSA: If you wish to submit any information under a claim of
confidentiality, you should submit three copies of your complete
submission, including the information you claim to be confidential
business information, to the Chief Counsel, NHTSA, at the
[[Page 43471]]
address given above under FOR FURTHER INFORMATION CONTACT. When you
send a comment containing confidential business information, you should
include a cover letter setting forth the information specified in 49
CFR part 512.
In addition, you should submit a copy from which you have deleted
the claimed confidential business information to the Docket by one of
the methods set forth above.
E. Will the agencies consider late comments?
NHTSA and EPA will consider all comments received before the close
of business on the comment closing date indicated above under DATES. To
the extent practicable, we will also consider comments received after
that date. If interested persons believe that any information that the
agencies place in the docket after the issuance of the NPRM affects
their comments, they may submit comments after the closing date
concerning how the agencies should consider that information for the
final rule. However, the agencies' ability to consider any such late
comments in this rulemaking will be limited due to the time frame for
issuing a final rule.
If a comment is received too late for us to practicably consider in
developing a final rule, we will consider that comment as an informal
suggestion for future rulemaking action.
F. How can I read the comments submitted by other people?
You may read the materials placed in the dockets for this document
(e.g., the comments submitted in response to this document by other
interested persons) at any time by going to http://www.regulations.gov.
Follow the online instructions for accessing the dockets. You may also
read the materials at the EPA Docket Center or the DOT Docket
Management Facility by going to the street addresses given above under
ADDRESSES.
G. How do I participate in the public hearings?
NHTSA and EPA will jointly host two public hearings on the dates
and locations to be announced in a separate notice. At all hearings,
both agencies will accept comments on the rulemaking, and NHTSA will
also accept comments on the EIS.
NHTSA and EPA will conduct the hearings informally, and technical
rules of evidence will not apply. We will arrange for a written
transcript of each hearing, to be posted in the dockets as soon as it
is available, and keep the official record of each hearing open for 30
days following that hearing to allow you to submit supplementary
information.
XII. Regulatory Notices and Analyses
A. Executive Order 12866, Executive Order 13563
Executive Order 12866, ``Regulatory Planning and Review'' (58 FR
51735, Oct. 4, 1993), as amended by Executive Order 13563, ``Improving
Regulation and Regulatory Review'' (76 FR 3821, Jan. 21, 2011),
provides for making determinations whether a regulatory action is
``significant'' and therefore subject to the Office of Management and
Budget (OMB) review and to the requirements of the Executive Order.
Under section 3(f)(1) of Executive Order 12866, this action is an
``economically significant regulatory action'' because if adopted, it
is likely to have an annual effect on the economy of $100 million or
more. Accordingly, EPA and NHTSA submitted this action to the OMB for
review and any changes made in response to OMB recommendations have
been documented in the docket for this action. The benefits and costs
of this proposal are described above and in the Preliminary Regulatory
Impact Analysis (PRIA), which is located in the docket and on the
agencies' websites.
B. DOT Regulatory Policies and Procedures
The rule, if adopted, would also be significant within the meaning
of the Department of Transportation's Regulatory Policies and
Procedures. The benefits and costs of this proposal are described above
and in the PRIA, which is located in the docket and on NHTSA's website.
C. Executive Order 13771 (Reducing Regulation and Controlling
Regulatory Costs)
This proposed rule is expected to be an E.O. 13771 deregulatory
action. Details on the estimated cost savings of this proposed rule can
be found in PRIA, which is located in the docket and on the agencies'
websites.
D. Executive Order 13211 (Energy Effects)
Executive Order 13211 applies to any rule that: (1) Is determined
to be economically significant as defined under E.O. 12866, and is
likely to have a significant adverse effect on the supply,
distribution, or use of energy; or (2) that is designated by the
Administrator of the Office of Information and Regulatory Affairs as a
significant energy action. If the regulatory action meets either
criterion, the agencies must evaluate the adverse energy effects of the
proposed rule and explain why the proposed regulation is preferable to
other potentially effective and reasonably feasible alternatives
considered.
The proposed rule seeks to establish passenger car and light truck
fuel economy standards and greenhouse gas emissions standards. An
evaluation of energy effects of the proposed action and reasonably
feasible alternatives considered is provided in NHTSA's Draft EIS and
in the PRIA. To the extent that EPA's CO2 standards are
substantially related to fuel economy and accordingly, petroleum
consumption, the Draft EIS and PRIA analyses also provide an estimate
of impacts of EPA's proposed rule.
E. Environmental Considerations
1. National Environmental Policy Act (NEPA)
Concurrently with this NPRM, NHTSA is releasing a Draft
Environmental Impact Statement (Draft EIS), pursuant to the National
Environmental Policy Act, 42 U.S.C. 4321-4347, and implementing
regulations issued by the Council on Environmental Quality (CEQ), 40
CFR part 1500, and NHTSA, 49 CFR part 520. NHTSA prepared the Draft EIS
to analyze and disclose the potential environmental impacts of the
proposed CAFE standards and a range of alternatives. The Draft EIS
analyzes direct, indirect, and cumulative impacts and analyzes impacts
in proportion to their significance.
The Draft EIS describes potential environmental impacts to a
variety of resources. Resources that may be affected by the proposed
action and alternatives include fuel and energy use, air quality,
climate, land use and development, hazardous materials and regulated
wastes, historical and cultural resources, noise, and environmental
justice. The Draft EIS also describes how climate change resulting from
global GHG emissions (including the U.S. light duty transportation
sector under the Proposed Action and alternatives) could affect certain
key natural and human resources. Resource areas are assessed
qualitatively and quantitatively, as appropriate, in the Draft EIS.
NHTSA has considered the information contained in the Draft EIS as
part of developing its proposal. The Draft EIS is available for public
comment; instructions for the submission of comments are included
inside the document. NHTSA will simultaneously issue the Final
Environmental Impact Statement and Record of Decision, pursuant to 49
[[Page 43472]]
U.S.C. 304a(b), and U.S. Department of Transportation Final Guidance on
MAP-21 Section 1319 Accelerated Decisionmaking in Environmental Reviews
(http://www.dot.gov/sites/dot.gov/files/docs/MAP-21_1319_Final_Guidance.pdf) unless it is determined that statutory
criteria or practicability considerations preclude simultaneous
issuance. For additional information on NHTSA's NEPA analysis, please
see the Draft EIS.
2. Clean Air Act (CAA) as Applied to NHTSA's Action
The CAA (42 U.S.C. 7401 et seq.) is the primary Federal legislation
that addresses air quality. Under the authority of the CAA and
subsequent amendments, EPA has established National Ambient Air Quality
Standards (NAAQS) for six criteria pollutants, which are relatively
commonplace pollutants that can accumulate in the atmosphere as a
result of human activity. EPA is required to review each NAAQS every
five years and to revise those standards as may be appropriate
considering new scientific information.
The air quality of a geographic region is usually assessed by
comparing the levels of criteria air pollutants found in the ambient
air to the levels established by the NAAQS (taking into account, as
well, the other elements of a NAAQS: Averaging time, form, and
indicator). Concentrations of criteria pollutants within the air mass
of a region are measured in parts of a pollutant per million parts
(ppm) of air or in micrograms of a pollutant per cubic meter ([mu]g/
m\3\) of air present in repeated air samples taken at designated
monitoring locations using specified types of monitors. These ambient
concentrations of each criteria pollutant are compared to the levels,
averaging time, and form specified by the NAAQS in order to assess
whether the region's air quality is in attainment with the NAAQS.
When the measured concentrations of a criteria pollutant within a
geographic region are below those permitted by the NAAQS, EPA
designates the region as an attainment area for that pollutant, while
regions where concentrations of criteria pollutants exceed Federal
standards are called nonattainment areas. Former nonattainment areas
that are now in compliance with the NAAQS are designated as maintenance
areas. Each State with a nonattainment area is required to develop and
implement a State Implementation Plan (SIP) documenting how the region
will reach attainment levels within time periods specified in the CAA.
For maintenance areas, the SIP must document how the State intends to
maintain compliance with the NAAQS. When EPA revises a NAAQS, each
State must revise its SIP to address how it plans to attain the new
standard.
No Federal agency may ``engage in, support in any way or provide
financial assistance for, license or permit, or approve'' any activity
that does not ``conform'' to a SIP or Federal Implementation Plan after
EPA has approved or promulgated it.\927\ Further, no Federal agency may
``approve, accept, or fund'' any transportation plan, program, or
project developed pursuant to title 23 or chapter 53 of title 49,
U.S.C., unless the plan, program, or project has been found to
``conform'' to any applicable implementation plan in effect.\928\ The
purpose of these conformity requirements is to ensure that Federally
sponsored or conducted activities do not interfere with meeting the
emissions targets in SIPs, do not cause or contribute to new violations
of the NAAQS, and do not impede the ability of a State to attain or
maintain the NAAQS or delay any interim milestones. EPA has issued two
sets of regulations to implement the conformity requirements:
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\927\ 42 U.S.C. 7506(c)(1).
\928\ 42 U.S.C. 7506(c)(2).
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(1) The Transportation Conformity Rule \929\ applies to
transportation plans, programs, and projects that are developed,
funded, or approved under title 23 or chapter 53 of title 49, U.S.C.
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\929\ 40 CFR part 51, subpart T, and part 93, subpart A.
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(2) The General Conformity Rule \930\ applies to all other federal
actions not covered under transportation conformity. The General
Conformity Rule establishes emissions thresholds, or de minimis levels,
for use in evaluating the conformity of an action that results in
emissions increases.\931\ If the net increases of direct and indirect
emissions are lower than these thresholds, then the project is presumed
to conform and no further conformity evaluation is required. If the net
increases of direct and indirect emissions exceed any of these
thresholds, and the action is not otherwise exempt, then a conformity
determination is required. The conformity determination can entail air
quality modeling studies, consultation with EPA and state air quality
agencies, and commitments to revise the SIP or to implement measures to
mitigate air quality impacts.
---------------------------------------------------------------------------
\930\ 40 CFR part 51, subpart W, and part 93, subpart B.
\931\ 40 CFR 93.153(b).
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The proposed CAFE standards and associated program activities are
not developed, funded, or approved under title 23 or chapter 53 of
title 49, U.S.C. Accordingly, this action and associated program
activities are not subject to transportation conformity. Under the
General Conformity Rule, a conformity determination is required where a
Federal action would result in total direct and indirect emissions of a
criteria pollutant or precursor originating in nonattainment or
maintenance areas equaling or exceeding the rates specified in 40 CFR
93.153(b)(1) and (2). As explained below, NHTSA's proposed action
results in neither direct nor indirect emissions as defined in 40 CFR
93.152.
The General Conformity Rule defines direct emissions as ``those
emissions of a criteria pollutant or its precursors that are caused or
initiated by the Federal action and originate in a nonattainment or
maintenance area and occur at the same time and place as the action and
are reasonably foreseeable.'' \932\ Because NHTSA's action would set
fuel economy standards for light duty vehicles, it would cause no
direct emissions consistent with the meaning of the General Conformity
Rule.\933\
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\932\ 40 CFR 93.152.
\933\ Department of Transportation v. Public Citizen, 541 U.S.
752, 772 (2004) (``[T]he emissions from the Mexican trucks are not
`direct' because they will not occur at the same time or at the same
place as the promulgation of the regulations.''). NHTSA's action is
to establish fuel economy standards for MY 2021-2026 passenger car
and light trucks; any emissions increases would occur well after
promulgation of the final rule.
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Indirect emissions under the General Conformity Rule are ``those
emissions of a criteria pollutant or its precursors (1) That are caused
or initiated by the federal action and originate in the same
nonattainment or maintenance area but occur at a different time or
place as the action; (2) That are reasonably foreseeable; (3) That the
agency can practically control; and (4) For which the agency has
continuing program responsibility.'' \934\ Each element of the
definition must be met to qualify as indirect emissions. NHTSA has
determined that, for purposes of general conformity, emissions that may
result from the proposed fuel economy standards would not be caused by
NHTSA's action, but rather would occur because of subsequent activities
the agency cannot practically control. ``[E]ven if a Federal licensing,
rulemaking, or other approving action is a required initial step for a
subsequent activity that causes emissions, such initial steps do not
mean that a Federal agency can practically control any resulting
emissions.'' \935\
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\934\ 40 CFR 93.152.
\935\ 40 CFR 93.152.
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[[Page 43473]]
As the CAFE program uses performance-based standards, NHTSA cannot
control the technologies vehicle manufacturers use to improve the fuel
economy of passenger cars and light trucks. Furthermore, NHTSA cannot
control consumer purchasing (which affects average achieved fleetwide
fuel economy) and driving behavior (i.e., operation of motor vehicles,
as measured by VMT). It is the combination of fuel economy
technologies, consumer purchasing, and driving behavior that results in
criteria pollutant or precursor emissions. For purposes of analyzing
the environmental impacts of the proposal and alternatives under NEPA,
NHTSA has made assumptions regarding all of these factors. The agency's
Draft EIS predicts that increases in air toxic and criteria pollutants
would occur in some nonattainment areas under certain alternatives.
However, the proposed standards and alternatives do not mandate
specific manufacturer decisions, consumer purchasing, or driver
behavior, and NHTSA cannot practically control any of them.\936\
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\936\ See, e.g., Department of Transportation v. Public Citizen,
541 U.S. 752, 772-73 (2004); South Coast Air Quality Management
District v. Federal Energy Regulatory Commission, 621 F.3d 1085,
1101 (9th Cir. 2010).
---------------------------------------------------------------------------
In addition, NHTSA does not have the statutory authority to control
the actual VMT by drivers. As the extent of emissions is directly
dependent on the operation of motor vehicles, changes in any emissions
that result from NHTSA's proposed standards are not changes the agency
can practically control or for which the agency has continuing program
responsibility. Therefore, the proposed CAFE standards and alternative
standards considered by NHTSA would not cause indirect emissions under
the General Conformity Rule, and a general conformity determination is
not required.
3. National Historic Preservation Act (NHPA)
The NHPA (54 U.S.C. 300101 et seq.) sets forth government policy
and procedures regarding ``historic properties''--that is, districts,
sites, buildings, structures, and objects included on or eligible for
the National Register of Historic Places. Section 106 of the NHPA
requires federal agencies to ``take into account'' the effects of their
actions on historic properties.\937\ The agencies conclude that the
NHPA is not applicable to this proposal because the promulgation of
CAFE and GHG emissions standards for light duty vehicles is not the
type of activity that has the potential to cause effects on historic
properties. However, NHTSA includes a brief, qualitative discussion of
the impacts of the alternatives on historical and cultural resources in
Section 7.3 of the Draft EIS.
---------------------------------------------------------------------------
\937\ Section 106 is now codified at 54 U.S.C. 306108.
Implementing regulations for the Section 106 process are located at
36 CFR part 800.
---------------------------------------------------------------------------
4. Fish and Wildlife Conservation Act (FWCA)
The FWCA (16 U.S.C. 2901 et seq.) provides financial and technical
assistance to States for the development, revision, and implementation
of conservation plans and programs for nongame fish and wildlife. In
addition, the Act encourages all Federal departments and agencies to
utilize their statutory and administrative authorities to conserve and
to promote conservation of nongame fish and wildlife and their
habitats. The agencies conclude that the FWCA is not applicable to this
proposal because it does not involve the conservation of nongame fish
and wildlife and their habitats.
5. Coastal Zone Management Act (CZMA)
The Coastal Zone Management Act (16 U.S.C. 1451 et seq.) provides
for the preservation, protection, development, and (where possible)
restoration and enhancement of the nation's coastal zone resources.
Under the statute, States are provided with funds and technical
assistance in developing coastal zone management programs. Each
participating State must submit its program to the Secretary of
Commerce for approval. Once the program has been approved, any activity
of a Federal agency, either within or outside of the coastal zone, that
affects any land or water use or natural resource of the coastal zone
must be carried out in a manner that is consistent, to the maximum
extent practicable, with the enforceable policies of the State's
program.\938\
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\938\ 16 U.S.C. 1456(c)(1)(A).
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The agencies conclude that the CZMA is not applicable to this
proposal because it does not involve an activity within, or outside of,
the nation's coastal zones that affects any land or water use or
natural resource of the coastal zone. NHTSA has, however, conducted a
qualitative review in its Draft EIS of the related direct, indirect,
and cumulative impacts, positive or negative, of the alternatives on
potentially affected resources, including coastal zones.
6. Endangered Species Act (ESA)
Under Section 7(a)(2) of the ESA federal agencies must ensure that
actions they authorize, fund, or carry out are ``not likely to
jeopardize the continued existence'' of any federally listed threatened
or endangered species or result in the destruction or adverse
modification of the designated critical habitat of these species. 16
U.S.C. 1536(a)(2). If a federal agency determines that an agency action
may affect a listed species or designated critical habitat, it must
initiate consultation with the appropriate Service--the U.S. Fish and
Wildlife Service of the Department of the Interior and/or the National
Oceanic and Atmospheric Administration's National Marine Fisheries
Service of the Department of Commerce, depending on the species
involved--in order to ensure that the action is not likely to
jeopardize the species or destroy or adversely modify designated
critical habitat. See 50 CFR 402.14. Under this standard, the federal
agency taking action evaluates the possible effects of its action and
determines whether to initiate consultation. See 51 FR 19926, 19949
(June 3, 1986).
Pursuant to Section 7(a)(2) of the ESA, the agencies have
considered the effects of the proposed standards and have reviewed
applicable ESA regulations, case law, and guidance to determine what,
if any, impact there might be to listed species or designated critical
habitat. The agencies have considered issues related to emissions of
CO2 and other GHGs and issues related to non-GHG emissions.
Based on this assessment, the agencies have determined that the actions
of setting CAFE and GHG emissions standards does not require
consultation under Section 7(a)(2) of the ESA. Accordingly, NHTSA and
EPA have concluded its review of this action under Section 7 of the
ESA.
7. Floodplain Management (Executive Order 11988 and DOT Order 5650.2)
These Orders require Federal agencies to avoid the long- and short-
term adverse impacts associated with the occupancy and modification of
floodplains, and to restore and preserve the natural and beneficial
values served by floodplains. Executive Order 11988 also directs
agencies to minimize the impact of floods on human safety, health and
welfare, and to restore and preserve the natural and beneficial values
served by floodplains through evaluating the potential effects of any
actions the agency may take in a floodplain and ensuring that its
program
[[Page 43474]]
planning and budget requests reflect consideration of flood hazards and
floodplain management. DOT Order 5650.2 sets forth DOT policies and
procedures for implementing Executive Order 11988. The DOT Order
requires that the agency determine if a proposed action is within the
limits of a base floodplain, meaning it is encroaching on the
floodplain, and whether this encroachment is significant. If
significant, the agency is required to conduct further analysis of the
proposed action and any practicable alternatives. If a practicable
alternative avoids floodplain encroachment, then the agency is required
to implement it.
In this proposal, the agencies are not occupying, modifying and/or
encroaching on floodplains. The agencies, therefore, conclude that the
Orders are not applicable to this action. NHTSA has, however, conducted
a review of the alternatives on potentially affected resources,
including floodplains, in its Draft EIS.
8. Preservation of the Nation's Wetlands (Executive Order 11990 and DOT
Order 5660.1a)
These Orders require Federal agencies to avoid, to the extent
possible, undertaking or providing assistance for new construction
located in wetlands unless the agency head finds that there is no
practicable alternative to such construction and that the proposed
action includes all practicable measures to minimize harms to wetlands
that may result from such use. Executive Order 11990 also directs
agencies to take action to minimize the destruction, loss or
degradation of wetlands in ``conducting Federal activities and programs
affecting land use, including but not limited to water and related land
resources planning, regulating, and licensing activities.'' DOT Order
5660.1a sets forth DOT policy for interpreting Executive Order 11990
and requires that transportation projects ``located in or having an
impact on wetlands'' should be conducted to assure protection of the
Nation's wetlands. If a project does have a significant impact on
wetlands, an EIS must be prepared.
The agencies are not undertaking or providing assistance for new
construction located in wetlands. The agencies, therefore, conclude
that these Orders do not apply to this proposal. NHTSA has, however,
conducted a review of the alternatives on potentially affected
resources, including wetlands, in its Draft EIS.
9. Migratory Bird Treaty Act (MBTA), Bald and Golden Eagle Protection
Act (BGEPA), Executive Order 13186
The MBTA (16 U.S.C. 703-712) provides for the protection of certain
migratory birds by making it illegal for anyone to ``pursue, hunt,
take, capture, kill, attempt to take, capture, or kill, possess, offer
for sale, sell, offer to barter, barter, offer to purchase, purchase,
deliver for shipment, ship, export, import, cause to be shipped,
exported, or imported, deliver for transportation, transport or cause
to be transported, carry or cause to be carried, or receive for
shipment, transportation, carriage, or export'' any migratory bird
covered under the statute.\939\
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\939\ 16 U.S.C. 703(a).
---------------------------------------------------------------------------
The BGEPA (16 U.S.C. 668-668d) makes it illegal to ``take, possess,
sell, purchase, barter, offer to sell, purchase or barter, transport,
export or import'' any bald or golden eagles.\940\ Executive Order
13186, ``Responsibilities of Federal Agencies to Protect Migratory
Birds,'' helps to further the purposes of the MBTA by requiring a
Federal agency to develop a Memorandum of Understanding (MOU) with the
Fish and Wildlife Service when it is taking an action that has (or is
likely to have) a measurable negative impact on migratory bird
populations.
---------------------------------------------------------------------------
\940\ 16 U.S.C. 668(a).
---------------------------------------------------------------------------
The agencies conclude that the MBTA, BGEPA, and Executive Order
13186 do not apply to this proposal because there is no disturbance,
take, measurable negative impact, or other covered activity involving
migratory birds or bald or golden eagles involved in this rulemaking.
10. Department of Transportation Act (Section 4(f))
Section 4(f) of the Department of Transportation Act of 1966 (49
U.S.C. 303), as amended, is designed to preserve publicly owned park
and recreation lands, waterfowl and wildlife refuges, and historic
sites. Specifically, Section 4(f) provides that DOT agencies cannot
approve a transportation program or project that requires the use of
any publicly owned land from a public park, recreation area, or
wildlife or waterfowl refuge of national, State, or local significance,
or any land from a historic site of national, State, or local
significance, unless a determination is made that:
(1) There is no feasible and prudent alternative to the use of
land, and
(2) The program or project includes all possible planning to
minimize harm to the property resulting from the use.
These requirements may be satisfied if the transportation use of a
Section 4(f) property results in a de minimis impact on the area.
NHTSA concludes that Section 4(f) is not applicable to its proposal
because this rulemaking is not an approval of a transportation program
or project that requires the use of any publicly owned land.
11. Executive Order 12898: ``Federal Actions to Address Environmental
Justice in Minority Populations and Low-Income Populations''
Executive Order (E.O.) 12898 (59 FR 7629 (Feb. 16, 1994))
establishes federal executive policy on environmental justice. Its main
provision directs federal agencies, to the greatest extent practicable
and permitted by law, to make environmental justice part of their
mission by identifying and addressing, as appropriate,
disproportionately high and adverse human health or environmental
effects of their programs, policies, and activities on minority
populations and low-income populations in the United States.
With respect to GHG emissions, EPA has determined that this final
rule will not have disproportionately high and adverse human health or
environmental effects on minority or low-income populations because it
impacts the level of environmental protection for all affected
populations without having any disproportionately high and adverse
human health or environmental effects on any population, including any
minority or low-income population. The increases in CO2 and
other GHGs associated with the standards will affect climate change
projections, and EPA has estimated marginal increases in projected
global mean surface temperatures and sea-level rise in this NPRM.
Within settlements experiencing climate change, certain parts of the
population may be especially vulnerable; these include the poor, the
elderly, those already in poor health, the disabled, those living
alone, and/or indigenous populations dependent on one or a few
resources. However, the potential increases in climate change impacts
resulting from this rule are so small that the impacts are not
considered ``disproportionately high and adverse'' on these
populations.
For non-GHG co-pollutants such as ozone, PM2.5, and
toxics, EPA has concluded that reductions in downstream emissions would
have beneficial human health or environmental effects on near-road
populations. Therefore, the proposed rule would not result in
``disproportionately high and adverse''
[[Page 43475]]
human health or environmental effects regarding these pollutants on
minority and/or low income populations.
NHTSA has also evaluated whether its proposal would have
disproportionately high and adverse human health or environmental
effects on minority or low-income populations. The agency includes its
analysis in Section 7.5 (Environmental Justice) of its Draft EIS.
12. Executive Order 13045: ``Protection of Children from Environmental
Health Risks and Safety Risks''
This action is subject to E.O. 13045 (62 FR 19885, April 23, 1997)
because it is an economically significant regulatory action as defined
by E.O. 12866, and the agencies have reason to believe that the
environmental health or safety risks related to this action may have a
disproportionate effect on children. Specifically, children are more
vulnerable to adverse health effects related to mobile source
emissions, as well as to the potential long-term impacts of climate
change. Pursuant to E.O. 13045, NHTSA and EPA must prepare an
evaluation of the environmental health or safety effects of the planned
regulation on children and an explanation of why the planned regulation
is preferable to other potentially effective and reasonably feasible
alternatives considered by the agencies. Further, this analysis may be
included as part of any other required analysis.
This preamble and NHTSA's Draft EIS discuss air quality, climate
change, and their related environmental and health effects, noting
where these would disproportionately affect children. The Administrator
has also discussed the impact of climate-related health effects on
children in the Endangerment and Cause or Contribute Findings for
Greenhouse Gases Under Section 202(a) of the Clean Air Act (74 FR
66496, December 15, 2009). Additionally, this preamble explains why the
agencies' proposal is preferable to other alternatives considered.
Together, this preamble and NHTSA's Draft EIS satisfy the agencies'
responsibilities under E.O. 13045.
F. Regulatory Flexibility Act
Pursuant to the Regulatory Flexibility Act (5 U.S.C. 601 et seq.,
as amended by the Small Business Regulatory Enforcement Fairness Act
(SBREFA) of 1996), whenever an agency is required to publish a notice
of proposed rulemaking or final rule, it must prepare and make
available for public comment a regulatory flexibility analysis that
describes the effect of the rule on small entities (i.e., small
businesses, small organizations, and small governmental jurisdictions).
No regulatory flexibility analysis is required if the head of an agency
certifies the proposal will not have a significant economic impact on a
substantial number of small entities. SBREFA amended the Regulatory
Flexibility Act to require Federal agencies to provide a statement of
the factual basis for certifying that a proposal will not have a
significant economic impact on a substantial number of small entities.
The agencies considered the impacts of this notice under the
Regulatory Flexibility Act and certify that this rule would not have a
significant economic impact on a substantial number of small entities.
The following is the agencies' statement providing the factual basis
for this certification pursuant to 5 U.S.C. 605(b).
Small businesses are defined based on the North American Industry
Classification System (NAICS) code.\941\ One of the criteria for
determining size is the number of employees in the firm. For
establishments primarily engaged in manufacturing or assembling
automobiles, as well as light duty trucks, the firm must have less than
1,500 employees to be classified as a small business. This proposed
rule would affect motor vehicle manufacturers. There are 14 small
manufacturers of passenger cars and SUVs of electric, hybrid, and
internal combustion engines.
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\941\ Classified in NAICS under Subsector 336--Transportation
Equipment Manufacturing for Automobile Manufacturing (336111), Light
Truck (336112), and Heavy Duty Truck Manufacturing (336120). https://www.sba.gov/document/support-table-size-standards.
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[[Page 43476]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.304
NHTSA believes that the rulemaking would not have a significant
economic impact on the small vehicle manufacturers because under 49 CFR
part 525, passenger car manufacturers making less than 10,000 vehicles
per year can petition NHTSA to have alternative standards set for those
manufacturers. These manufacturers do not currently meet the 27.5 mpg
standard and must already petition the agency for relief. If the
standard is raised, it has no meaningful impact on these
manufacturers--they still must go through the same process and petition
for relief. Given there already is a mechanism for relieving burden on
small businesses, which is the purpose of the Regulatory Flexibility
Act, a regulatory flexibility analysis was not prepared.
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\942\ Number of employees as of March 2018, source:
Linkedin.com.
\943\ Rough estimate for model year 2017.
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EPA believes this rulemaking would not have a significant economic
impact on a substantial number of small entities under the Regulatory
Flexibility Act, as amended by the Small Business Regulatory
Enforcement Fairness Act. EPA is exempting from the CO2
standards any manufacturer, domestic or foreign, meeting SBA's size
definitions of small business as described in 13 CFR 121.201. EPA
adopted the same type of exemption for small businesses in the 2017 and
later rulemaking. EPA estimates that small entities comprise less than
0.1% of total annual vehicle sales and exempting them will have a
negligible impact on the CO2 emissions reductions from the
standards. Because EPA is exempting small businesses from the
CO2 standards, we are certifying that the rule will not have
a significant economic impact on a substantial number of small
entities. Therefore, EPA has not conducted a Regulatory Flexibility
Analysis or a SBREFA SBAR Panel for the rule.
EPA regulations allow small businesses to voluntarily waive their
small business exemption and optionally certify to the CO2
standards. This allows small entity manufacturers to earn
CO2 credits under the CO2 program, if their
actual fleetwide CO2 performance is better than their
fleetwide CO2 target standard. However, the exemption waiver
is optional for small entities and thus we believe that manufacturers
opt into the CO2 program if it is economically advantageous
for them to do so, for example in order to generate and sell
CO2 credits. Therefore, EPA believes this voluntary option
does not affect EPA's determination that the standards will impose no
significant adverse impact on small entities.
G. Executive Order 13132 (Federalism)
Executive Order 13132 requires federal agencies to develop an
accountable process to ensure ``meaningful and timely input by State
and local officials in the development of regulatory policies that have
federalism implications.'' The Order defines the term ``Policies that
have federalism implications'' to include regulations that have
``substantial direct effects on the States, on the relationship between
the national government and the States, or on the distribution of power
and responsibilities among the various levels of government.'' Under
the Order, agencies may not issue a regulation that has federalism
implications, that imposes substantial direct compliance costs, unless
the Federal government provides the funds necessary to pay the direct
compliance costs incurred by State and local governments, or the
agencies consult with State and local officials early in the process of
developing the proposed regulation. The agencies complied with Order's
requirements.
See Section VI above for further detail on the agencies' assessment
of the federalism implications of this proposal.
[[Page 43477]]
H. Executive Order 12988 (Civil Justice Reform)
Pursuant to Executive Order 12988, ``Civil Justice Reform,'' \944\
NHTSA has considered whether this rulemaking would have any retroactive
effect. This proposed rule does not have any retroactive effect.
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\944\ 61 FR 4729 (Feb. 7, 1996).
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I. Executive Order 13175 (Consultation and Coordination With Indian
Tribal Governments)
This proposed rule does not have tribal implications, as specified
in Executive Order 13175 (65 FR 67249, November 9, 2000). This rule
will be implemented at the Federal level and impose compliance costs
only on vehicle manufacturers. Thus, Executive Order 13175 does not
apply to this rule.
J. Unfunded Mandates Reform Act
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA)
requires Federal agencies to prepare a written assessment of the costs,
benefits, and other effects of a proposed or final rule that includes a
Federal mandate likely to result in the expenditure by State, local, or
tribal governments, in the aggregate, or by the private sector, of more
than $100 million in any one year (adjusted for inflation with base
year of 1995). Adjusting this amount by the implicit gross domestic
product price deflator for 2016 results in $148 million (111.416/75.324
= 1.48).\945\ Before promulgating a rule for which a written statement
is needed, section 205 of UMRA generally requires NHTSA and EPA to
identify and consider a reasonable number of regulatory alternatives
and adopt the least costly, most cost-effective, or least burdensome
alternative that achieves the objective of the rule. The provisions of
section 205 do not apply when they are inconsistent with applicable
law. Moreover, section 205 allows NHTSA and EPA to adopt an alternative
other than the least costly, most cost-effective, or least burdensome
alternative if the agency publishes with the proposed rule an
explanation of why that alternative was not adopted.
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\945\ Bureau of Economic Analysis, National Income and Product
Accounts (NIPA), Table 1.1.9 Implicit Price Deflators for Gross
Domestic Product. https://bea.gov/iTable/index_nipa.cfm.
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This proposed rule will not result in the expenditure by State,
local, or tribal governments, in the aggregate, of more than $148
million annually, but it will result in the expenditure of that
magnitude by vehicle manufacturers and/or their suppliers. In
developing this proposal, NHTSA and EPA considered a variety of
alternative average fuel economy standards lower and higher than those
proposed. The proposed fuel economy standards for MYs 2021-2026 are the
least costly, most cost-effective, and least burdensome alternative
that achieve the objective of the rule.
K. Regulation Identifier Number
The Department of Transportation assigns a regulation identifier
number (RIN) to each regulatory action listed in the Unified Agenda of
Federal Regulations. The Regulatory Information Service Center
publishes the Unified Agenda in April and October of each year. You may
use the RIN contained in the heading at the beginning of this document
to find this action in the Unified Agenda.
L. National Technology Transfer and Advancement Act
Section 12(d) of the National Technology Transfer and Advancement
Act (NTTAA) requires NHTSA and EPA to evaluate and use existing
voluntary consensus standards in its regulatory activities unless doing
so would be inconsistent with applicable law (e.g., the statutory
provisions regarding NHTSA's vehicle safety authority, or EPA's testing
authority) or otherwise impractical.\946\
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\946\ 15 U.S.C. 272.
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Voluntary consensus standards are technical standards developed or
adopted by voluntary consensus standards bodies. Technical standards
are defined by the NTTAA as ``performance-based or design-specific
technical specification and related management systems practices.''
They pertain to ``products and processes, such as size, strength, or
technical performance of a product, process or material.''
Examples of organizations generally regarded as voluntary consensus
standards bodies include the American Society for Testing and Materials
(ASTM), the Society of Automotive Engineers (SAE), and the American
National Standards Institute (ANSI). If the agencies do not use
available and potentially applicable voluntary consensus standards, we
are required by the Act to provide Congress, through OMB, an
explanation of the reasons for not using such standards.
For CO2 emissions, EPA is proposing to collect data over
the same tests that are used for the MY 2012-2016 CO2
standards and for the CAFE program. This will minimize the amount of
testing done by manufacturers, since manufacturers are already required
to run these tests. For A/C credits, EPA is proposing to use a
consensus methodology developed by the Society of Automotive Engineers
(SAE) and also a new A/C test. EPA knows of no consensus standard
available for the A/C test.
There are currently no voluntary consensus standards that NHTSA
administers relevant to today's proposed CAFE standards.
M. Department of Energy Review
In accordance with 49 U.S.C. 32902(j)(1), NHTSA submitted this
proposed rule to the Department of Energy for review.
N. Paperwork Reduction Act
The Paperwork Reduction Act (PRA) of 1995, Public Law 104-13,\947\
gives the Office of Management and Budget (OMB) authority to regulate
matters regarding the collection, management, storage, and
dissemination of certain information by and for the Federal government.
It seeks to reduce the total amount of paperwork handled by the
government and the public. The PRA requires Federal agencies to place a
notice in the Federal Register seeking public comment on the proposed
collection of information. NHTSA strives to reduce the public's
information collection burden hours each fiscal year by streamlining
external and internal processes.
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\947\ Codified at 44 U.S.C. 3501 et seq.
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To this end, NHTSA seeks to continue to collect information to
ensure compliance with its CAFE program. NHTSA intends to reinstate its
previously-approved collection of information for Corporate Average
Fuel Economy (CAFE) reports specified in 49 CFR part 537 (OMB control
number 2127-0019), add the additional burden for reporting changes
adopted in the October 15, 2012 final rule that recently came into
effect (see 77 FR 62623), and account for the change in burden as
proposed in this rule as well as for other CAFE reporting provisions
required by Congress and NHTSA. NHTSA is also changing the name of this
collection to more accurately represent the breadth of all CAFE
regulatory reporting. Although NHTSA seeks to add additional burden
hours to its CAFE report requirement in 49 CFR 537, the agency believes
there will be a reduction in burden due to the standardization of data
and the streamlined process. NHTSA is seeking public comment on this
collection.
In compliance with the PRA, this notice announces that the
information collection request (ICR) abstracted below has been
forwarded to OMB for review and comment. The ICR describes
[[Page 43478]]
the nature of the information collection and its expected burden.
Title: Corporate Average Fuel Economy.
Type of Request: Reinstatement and amendment of a previously
approved collection.
OMB Control Number: 2127-0019.
Form Numbers: NHTSA Form 1474 (CAFE Projections Reporting Template)
and NHTSA Form 1475 (CAFE Credit Template).
Requested Expiration Date of Approval: Three years from date of
approval.
Summary of the collection of information: As part of this
rulemaking, NHTSA is reinstating and modifying its previously-approved
collection for CAFE-related collections of information. NHTSA and EPA
have coordinated their compliance and reporting requirements in an
effort not to impose duplicative burden on regulated entities. This
information collection contains three different components: Burden
related NHTSA's CAFE reporting requirements, burden related to CAFE
compliance, but not via reporting requirements, and information
gathered by NHTSA to help inform CAFE analyses. All templates
referenced in this section will be available in the rulemaking docket
for comment.
1. CAFE Compliance Reports
NHTSA seeks to reinstate \948\ its collection related to the
reporting requirements in 49 U.S.C. 32907 ``Reports and tests of
manufacturers.'' In that section, manufacturers are statutorily
required to submit CAFE compliance reports to the Secretary of
Transportation.\949\ The reports must state if a manufacturer will
comply with its applicable fuel economy standard(s), what actions the
manufacturer intends to take to comply with the standard(s), and
include other information as required by NHTSA. Manufacturers are
required to submit two CAFE compliance reports--a pre-model year report
(PMY) and mid-model year (MMY) reporter--each year. In the event a
manufacturer needs to correct previously-submitted information, a
manufacturer may need to file additional reports.\950\
---------------------------------------------------------------------------
\948\ This collection expired on April 30, 2016.
\949\ 49 U.S.C. 32907 (delegated to the NHTSA Administrator at
49 CFR 1.95). Because of this delegation, for purposes of
discussion, statutory references to the Secretary of Transportation
in this section will discussed in terms of NHTSA or the NHTSA
administrator.
\950\ Specifically, a manufacturer shall submit a report
containing the information during the 30 days before the beginning
of each model year, and during the 30 days beginning the 180th day
of the model year. When a manufacturer decides that actions reported
are not sufficient to ensure compliance with that standard, the
manufacturer shall report additional actions it intends to take to
comply with the standard and include a statement about whether those
actions are sufficient to ensure compliance.
---------------------------------------------------------------------------
To implement this statute, NHTSA issued 49 CFR part 537,
``Automotive Fuel Economy Reports,'' which adds additional definition
to Sec. 32907. The first report, the PMY report must be submitted to
NHTSA before December 31 of the calendar year prior to the
corresponding model year and contain manufacturers' projected
information for that upcoming model year. The second report, the MMY
report must be submitted by July 31 of the given model year and contain
updated information from manufacturers based upon actual and projected
information known midway through the model year. Finally, the last
report, a supplementary report, is required to be submitted anytime a
manufacture needs to correct information previously submitted to NHTSA.
Compliance reports must include information on passenger and non-
passenger automobiles (trucks) describing the projected and actual fuel
economy standards, fuel economy performance values, production sales
volumes and information on vehicle design features (e.g., engine
displacement and transmission class) and other vehicle attribute
characteristics (e.g., track width, wheel base and other light truck
off-road features). Manufacturers submit confidential and non-
confidential versions of these reports to NHTSA. Confidential reports
differ by including estimated or actual production sales information,
which is withheld from public disclosure to protect each manufacturer's
competitive sales strategies. NHTSA uses the reports as the basis for
vehicle auditing and testing, which helps manufacturers correct
reporting errors prior to the end of the model year and facilitate
acceptance of their final CAFE report by the Environmental Protection
Agency (EPA). The reports also help the agency, as well as the
manufacturers who prepare them, anticipate potential compliance issues
as early as possible, and help manufacturers plan their compliance
strategies.
Further, NHTSA is modifying this collection to account for
additional information manufacturers are required to include in their
reports. In the 2017 and beyond final rule,\951\ NHTSA allowed for
manufacturers to gain additional fuel economy benefits by installing
certain technologies on their vehicles beginning with MY 2017.\952\
These technologies include air-conditioning systems with increased
efficiency, off-cycle technologies whose benefits are not adequately
captured on the Federal Test Procedure and/or the Highway Fuel Economy
Test,\953\ and hybrid electric technologies installed on full-size
pickup trucks. Prior to MY 2017, manufacturers were unable to earn a
fuel economy benefit for these technologies, so NHTSA's reporting
requirements did not include an opportunity to report them. Now,
manufacturers must provide information on these technologies in their
CAFE reports. NHTSA requires manufacturers to provide detailed
information on the model types using these technologies to gain fuel
economy benefits. These details are necessary to facilitate NHTSA's
technical analyses and to ensure the agency can perform random
enforcement audits when necessary.
---------------------------------------------------------------------------
\951\ 77 FR 62623 (Oct. 15, 2012).
\952\ These technologies were not included in the burden for
part 537 at the time as the additional reporting requirements would
not take effect until years later.
\953\ E.g., engine idle stop-start systems, active transmission
warmup systems, etc.
---------------------------------------------------------------------------
In addition to a list of all fuel consumption improvement
technologies utilized in their fleet, 49 CFR 537 requires manufacturers
to report the make, model type, compliance category, and production
volume of each vehicle equipped with each technology and the associated
fuel consumption improvement value (FCIV). NHTSA is proposing to add
the reporting and enforcement burden hours and cost for these new
incentives to this collection. Manufacturers can also petition the EPA
and NHTSA, in accordance with 40 CFR 86.1868-12 or 40 CFR 86.1869-12,
to gain additional credits based upon the improved performance of any
of the new incentivized technologies allowed for model year 2017. EPA
approves these petitions in collaboration with NHTSA and any
adjustments are taken into account for both programs. As a part the
agencies' coordination, NHTSA provides EPA with an evaluation of each
new technology to ensure its direct impact on fuel economy and an
assessment on the suitability of each technology for use in increasing
a manufacturer's fuel economy performance. Furthermore, at times, NHTSA
may independently request additional information from a manufacturer to
support its evaluations. This information along with any research
conclusions shared with EPA and NHTSA in the petitions is required to
be submitted in manufacturer's CAFE reports.
[[Page 43479]]
NHTSA is seeking to change the burden hours for its CAFE reporting
requirements in 49 CFR part 537. NHTSA plans to reduce the total amount
of time spent collecting the required reporting information by
standardizing the required data and streamlining the collection process
using a standardized reporting template. The standardized template will
be used by manufacturers to collect all the required CAFE information
under 49 CFR 537.7(b) and (c) and provides a format which ensures
accuracy, completeness and better alignment with the final data
provided to EPA.
2. Other CAFE Compliance Collections
NHTSA is proposing a new standardized template for manufacturers
buying CAFE credits and for manufacturers submitting credit
transactions in accordance with 49 CFR part 536. In 49 CFR part
536.5(d), NHTSA is required to assess compliance with fuel economy
standards each year, utilizing the certified and reported CAFE data
provided by the Environmental Protection Agency for enforcement of the
CAFE program pursuant to 49 U.S.C. 32904(e). Credit values are
calculated based on the CAFE data from the EPA. If a manufacturer's
vehicles in a particular compliance category performs better than its
required fuel economy standard, NHTSA adds credits to the
manufacturer's account for that compliance category. If a
manufacturer's vehicles in a particular compliance category performs
worse than the required fuel economy standard, NHTSA will add a credit
deficit to the manufacturer's account and will provide written
notification to the manufacturer concerning its failure to comply. The
manufacturer will be required to confirm the shortfall and must either:
Submit a plan indicating how it will allocate existing credits or earn,
transfer and/or acquire credits or pay the equivalent civil penalty.
The manufacturer must submit a plan or payment within 60 days of
receiving notification from NHTSA.
NHTSA is proposing for manufacturers to use the credit transaction
template any time a credit transaction request is sent to NHTSA. For
example, manufacturers that purchase credits and want to apply them to
their credit accounts will use the credit transaction template. The
template NHTSA is proposing is a simple spreadsheet that trading
parties fill out. When completed, parties will be able to click a
button on the spreadsheet to generate a joint transaction letter for
the parties to sign and submit to NHTSA, along with the spreadsheet.
NHTSA believes these changes will significantly reduce the burden on
manufacturers in managing their CAFE credit accounts.
Finally, NHTSA is accounting for the additional burden due to
existing CAFE program elements. In 49 CFR part 525, small volume
manufacturers submit petitions to NHTSA for exemption from an
applicable average fuel economy standard and to request to comply with
a less stringent alternative average fuel economy standard. In 49 CFR
part 534, manufacturers are required to submit information to NHTSA
when establishing a corporate controlled relationship with another
manufacturer. A controlled relationship exists between manufacturers
that control, are controlled by, or are under common control with, one
or more other manufacturers. Accordingly, manufacturers that have
entered into written contracts transferring rights and responsibilities
to other manufacturers in controlled relationships for CAFE purposes
are required to provide reports to NHTSA. There are additional
reporting requirements for manufacturers submitting carry back plans
and when manufacturers split apart from controlled relationships and
must designate how credits are to be allocated between the
parties.\954\ Manufacturers with credit deficits at the end of the
model year, can carry back future earned credits up to three model
years in advance of the deficit to resolve a current shortfall. The
carryback plan proving the existence of a manufacturers future earned
credits must be submitted and approved by NHTSA, pursuant to 49 U.S.C.
32903(b).
---------------------------------------------------------------------------
\954\ See 49 CFR part 536.
---------------------------------------------------------------------------
3. Analysis Fleet Composition
As discussed in Section II., in setting CAFE standards, NHTSA
creates an analysis fleet from which to model potential future economy
improvements. To compose this fleet, the agency uses a mixture of
compliance data and information from other sources to best replicate
the fleet from a recent model year. While refining the analysis fleet,
NHTSA occasionally asks manufacturers for information that is similar
to information submitted as part of EPA's final model year report
(e.g., final model year vehicle volumes). Periodically, NHTSA may ask
manufacturers for more detailed information than what is required for
compliance (e.g., what engines are shared across vehicle models).
Often, NHTSA requests this information from manufacturers after
manufacturers have submitted their final model year reports to EPA, but
before EPA processes and releases final model year reports.
Information like this, which is used to verify and supplement the
data used to create the analysis fleet, is tremendously valuable to
generating an accurate analysis fleet, and setting maximum feasible
standards. The more accurate the analysis fleet is, the more accurate
the modeling of what technologies could be applied will be. Therefore,
NHTSA is accounting for the burden on manufacturers to provide the
agency with this additional information. In almost all instances,
manufacturers already have the information NHTSA seeks, but it might
need to be reformatted or recompiled. Because of this, NHTSA believes
the burden to provide this information will often be minimal.
Affected Public: Respondents are manufacturers of engines and
vehicles within the North American Industry Classification System
(NAICS) and use the coding structure as defined by NAICS including
codes 33611, 336111, 336112, 33631, 33631, 33632, 336320, 33635, and
336350 for motor vehicle and parts manufacturing.
Respondent's obligation to respond: Regulated entities required to
respond to inquiries covered by this collection. 49 U.S.C. 32907. 49
CFR part 525, 534, 536, and 537.
Frequency of response: Variable, based on compliance obligation.
Please see PRA supporting documentation in the docket for more detailed
information.
Average burden time per response: Variable, based on compliance
obligation. Please see PRA supporting documentation in the docket for
more detailed information.
Number of respondents: 23.
4. Estimated Total Annual Burden Hours and Costs
[[Page 43480]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.305
O. Privacy Act
In accordance with 5 U.S.C. 553(c), the agencies solicit comments
from the public to better inform the rulemaking process. These comments
are posted, without edit, to www.regulations.gov, as described in DOT's
system of records notice, DOT/ALL-14 FDMS, accessible through
www.transportation.gov/privacy. In order to facilitate comment tracking
and response, we encourage commenters to provide their name, or the
name of their organization; however, submission of names is completely
optional.
List of Subjects
49 CFR Parts 523, 531, and 533
Fuel economy.
49 CFR Parts 536 and 537
Fuel economy, Reporting and recordkeeping requirements.
Regulatory Text
In consideration of the foregoing, under the authority of 49 U.S.C.
32901, 32902, and 32903, and delegation of authority at 49 CFR 1.95,
NHTSA proposes to amend 49 CFR Chapter V as follows:
PART 523--VEHICLE CLASSIFICATION
0
1. The authority citation for part 523 continues to read as follows:
Authority: 49 U.S.C 32901, delegation of authority at 49 CFR
1.95.
0
2. Amend Sec. 523.2 by revising the definitions of ``Curb weight'' and
``Full-size pickup truck'' to read as follows:
Sec. 523.2 Definitions.
* * * * *
Curb weight has the meaning given in 40 CFR 86.1803.
* * * * *
Full-size pickup truck means a light truck or medium duty passenger
vehicle that meets the requirements specified in 40 CFR 86.1803.
* * * * *
PART 531--PASSENGER AUTOMOBILE AVERAGE FUEL ECONOMY STANDARDS
0
3. The authority citation for part 531 continues to read as follows:
Authority: 49 U.S.C. 32902; delegation of authority at 49 CFR
1.95.
0
4. Amend Sec. 531.5 by revising Table III to paragraph (c), and
paragraph (d), deleting paragraph (e), and redesignating paragraph (f)
as paragraph (e) to read as follows:
Sec. 531.5 Fuel economy standards.
* * * * *
(c) * * *
BILLING CODE 4910-59-P
[[Page 43481]]
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[[Page 43482]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.307
[[Page 43483]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.308
(d) In addition to the requirements of paragraphs (b) and (c) of
this section, each manufacturer shall also meet the minimum fleet
standard for domestically manufactured passenger automobiles expressed
in Table IV:
[[Page 43484]]
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[[Page 43485]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.310
BILLING CODE 4910-59-C
* * * * *
0
5. Amend Sec. 531.6 by revising paragraphs (a) and (b) to read as
follows:
Sec. 531.6 Measurement and calculation procedures.
(a) The fleet average fuel economy performance of all passenger
automobiles that are manufactured by a manufacturer in a model year
shall be determined in accordance with procedures established by the
Administrator of the Environmental Protection Agency under 49 U.S.C.
32904 and set forth in 40 CFR part 600. For model years 2017 to 2026, a
manufacturer is eligible to increase the fuel economy performance of
passenger cars in accordance with procedures established by EPA set
forth in 40 CFR 600, Subpart F, including any adjustments to fuel
economy EPA allows, such as for fuel consumption improvements related
to air conditioning efficiency and off-cycle technologies.
(1) A manufacturer that seeks to increase its fleet average fuel
economy performance through the use of technologies that improve the
efficiency of air conditioning systems must follow the requirements in
40 CFR 86.1868-12. Fuel consumption improvement values resulting from
the use of those air conditioning systems must be determined in
accordance with 40 CFR 600.510-12(c)(3)(i).
(2) A manufacturer that seeks to increase its fleet average fuel
economy performance through the use of off-cycle technologies must
follow the requirements in 40 CFR 86.1869-12. A manufacturer is
eligible to gain fuel consumption improvements for predefined off-cycle
technologies in accordance with 40 CFR 86.1869-12(b) or for
technologies tested using EPA's 5-cycle methodology in accordance with
40 CFR 86.1869-12(c). The fuel consumption improvement is determined in
accordance with 40 CFR 600.510-12(c)(3)(ii).
(b) A manufacturer is eligible to increase its fuel economy
performance through use of an off-cycle technology requiring an
application request made to EPA in accordance with 40 CFR 86.1869-
12(d). The request must be approved by EPA in consultation with NHTSA.
To expedite NHTSA's consultation with EPA, a manufacturer shall
concurrently submit its application to NHTSA if the manufacturer is
seeking off-cycle fuel economy improvement values under the CAFE
program for those technologies. For off-cycle technologies that are
covered under 40 CFR 86.1869-12(d), NHTSA will consult with EPA
regarding NHTSA's evaluation of the specific off-cycle technology to
ensure its impact on fuel economy and the suitability of using the off-
cycle technology to adjust the fuel economy performance. NHTSA will
provide its views on the suitability of the technology for that purpose
to EPA. NHTSA's evaluation and review will consider:
(1) Whether the technology has a direct impact upon improving fuel
economy performance;
(2) Whether the technology is related to crash-avoidance
technologies, safety critical systems or systems affecting safety-
critical functions, or technologies designed for the purpose of
reducing the frequency of vehicle crashes;
(3) Information from any assessments conducted by EPA related to
the application, the technology and/or related technologies; and
(4) Any other relevant factors.
* * * * *
0
6. Add Sec. 531.7 to read as follows:
Sec. 531.7 Preemption.
(a) General. When an average fuel economy standard prescribed under
this chapter is in effect, a State or a political subdivision of a
State may not adopt or
[[Page 43486]]
enforce a law or regulation related to fuel economy standards or
average fuel economy standards for automobiles covered by an average
fuel economy standard under this chapter.
(b) Requirements Must Be Identical. When a requirement under
section 32908 of this title is in effect, a State or a political
subdivision of a State may adopt or enforce a law or regulation on
disclosure of fuel economy or fuel operating costs for an automobile
covered by section 32908 only if the law or regulation is identical to
that requirement.
(c) State and Political Subdivision Automobiles. A State or a
political subdivision of a State may prescribe requirements for fuel
economy for automobiles obtained for its own use.
0
7. Redesignate Appendix to Part 531--Example of Calculating Compliance
under Sec. 531.5(c) as Appendix A to Part 531--Example of Calculating
Compliance under Sec. 531.5(c) and amend newly redesignated Appendix A
by removing all all references to ``Appendix'' and adding in their
place, ``Appendix A.''
0
8. Add Appendix B to Part 531 to read as follows:
Appendix B to Part 531--Preemption
(a) Express Preemption:
(1) To the extent that any state law or regulation regulates or
prohibits tailpipe carbon dioxide emissions from automobiles, such a
law or regulation relates to average fuel economy standards within
the meaning of 49 U.S.C. 32919.
(A) Automobile fuel economy is directly and substantially
related to automobile tailpipe emissions of carbon dioxide;
(B) Carbon dioxide is the natural by-product of automobile fuel
consumption;
(C) The most significant and controlling factor in making the
measurements necessary to determine the compliance of automobiles
with the fuel economy standards in this Part is their rate of
tailpipe carbon dioxide emissions;
(D) Almost all technologically feasible reduction of tailpipe
emissions of carbon dioxide is achievable through improving fuel
economy, thereby reducing both the consumption of fuel and the
creation and emission of carbon dioxide;
(E) Accordingly, as a practical matter, regulating fuel economy
controls the amount of tailpipe emissions of carbon dioxide, and
regulating the tailpipe emissions of carbon dioxide controls fuel
economy.
(2) As a state law or regulation related to fuel economy
standards, any state law or regulation regulating or prohibiting
tailpipe carbon dioxide emissions from automobiles is expressly
preempted under 49 U.S.C. 32919.
(3) A state law or regulation having the direct effect of
regulating or prohibiting tailpipe carbon dioxide emissions or fuel
economy is a law or regulation related to fuel economy and expressly
preempted under 49 U.S.C. 32919.
(b) Implied Preemption:
(1) A state law or regulation regulating tailpipe carbon dioxide
emissions from automobiles, particularly a law or regulation that is
not attribute-based and does not separately regulate passenger cars
and light trucks, conflicts with:
(A) The fuel economy standards in this Part;
(B) The judgments made by the agency in establishing those
standards; and
(C) The achievement of the objectives of the statute (49 U.S.C.
Chapter 329) under which those standards were established, including
objectives relating to reducing fuel consumption in a manner and to
the extent consistent with manufacturer flexibility, consumer
choice, and automobile safety.
(2) Any state law or regulation regulating or prohibiting
tailpipe carbon dioxide emissions from automobiles is impliedly
preempted under 49 U.S.C. Chapter 329.
(3) A state law or regulation having the direct effect of
regulating or prohibiting tailpipe carbon dioxide emissions or fuel
economy is impliedly preempted under 49 U.S.C. Chapter 329.
PART 533--LIGHT TRUCK FUEL ECONOMY STANDARDS
0
9. The authority citation for part 533 continues to read as follows:
Authority: 49 U.S.C. 32902; delegation of authority at 49 CFR
1.95.
0
10. Amend Sec. 533.5 by revising Table VII to paragraph (a) to read as
follows and removing paragraph (k).
Sec. 533.5 Requirements.
(a) * * *
BILLING CODE 4910-59-P
[[Page 43487]]
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[[Page 43488]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.312
BILLING CODE 4910-59-C
* * * * *
0
11. Amend Sec. 533.6 by revising paragraphs (b) and (c) as follows:
Sec. 533.6 Measurement and calculation procedures.
* * * * *
(b) The fleet average fuel economy performance of all light trucks
that are manufactured by a manufacturer in a model year shall be
determined in accordance with procedures established by the
Administrator of the Environmental Protection Agency under 49 U.S.C.
32904 and set forth in 40 CFR part 600. For model years 2017 to 2026, a
manufacturer is eligible to increase the fuel economy performance of
light trucks in accordance with procedures established by EPA set forth
in 40 CFR part 600, subpart F, including any adjustments to fuel
economy EPA allows, such as for fuel consumption improvements related
to air conditioning efficiency, off-cycle technologies, and
hybridization and other performance-based technologies for full-size
pickup trucks that meet the requirements specified in 40 CFR 86.1803.
(1) A manufacturer that seeks to increase its fleet average fuel
economy performance through the use of technologies that improve the
efficiency of air conditioning systems must follow the requirements in
40 CFR 86.1868-12. Fuel consumption improvement values resulting from
the use of those air conditioning systems must be determined in
accordance with 40 CFR 600.510-12(c)(3)(i).
(2) A manufacturer that seeks to increase its fleet average fuel
economy performance through the use of off-cycle technologies must
follow the requirements in 40 CFR 86.1869-12. A manufacturer is
eligible to gain fuel consumption improvements for predefined off-cycle
technologies in accordance with 40 CFR 86.1869-12(b) or for
technologies tested using the EPA's 5-cycle methodology in accordance
with 40 CFR 86.1869-12(c). The fuel consumption improvement is
determined in accordance with 40 CFR 600.510-12(c)(3)(ii).
(3) The eligibility of a manufacturer to increase its fuel economy
using hybridized and other performance-based technologies for full-size
pickup trucks must follow 40 CFR 86.1870-12 and the fuel consumption
improvement of these full-size pickup truck technologies must be
determined in accordance with 40 CFR 600.510-12(c)(3)(iii).
(c) A manufacturer is eligible to increase its fuel economy
performance through use of an off-cycle technology requiring an
application request made to EPA in accordance with 40 CFR 86.1869-
12(d). The request must be approved by EPA in consultation with NHTSA.
To expedite NHTSA's consultation with EPA, a manufacturer shall
concurrently submit its application to NHTSA if the manufacturer is
seeking off-cycle fuel economy improvement values under the CAFE
program for those technologies. For off-cycle technologies that are
covered under 40 CFR 86.1869-12(d), NHTSA will consult with EPA
regarding NHTSA's evaluation of the specific off-cycle technology to
ensure its impact on fuel economy and the suitability of using the off-
cycle technology to adjust the fuel economy performance. NHTSA will
provide its views on the suitability of the technology for that purpose
to EPA. NHTSA's evaluation and review will consider:
(1) Whether the technology has a direct impact upon improving fuel
economy performance;
[[Page 43489]]
(2) Whether the technology is related to crash-avoidance
technologies, safety critical systems or systems affecting safety-
critical functions, or technologies designed for the purpose of
reducing the frequency of vehicle crashes;
(3) Information from any assessments conducted by EPA related to
the application, the technology and/or related technologies; and
(4) Any other relevant factors.
* * * * *
0
12. Add Sec. 533.7 to read as follows:
Sec. 533.7 Preemption.
(a) General. When an average fuel economy standard prescribed under
this chapter is in effect, a State or a political subdivision of a
State may not adopt or enforce a law or regulation related to fuel
economy standards or average fuel economy standards for automobiles
covered by an average fuel economy standard under this chapter.
(b) Requirements Must Be Identical. When a requirement under
section 32908 of this title is in effect, a State or a political
subdivision of a State may adopt or enforce a law or regulation on
disclosure of fuel economy or fuel operating costs for an automobile
covered by section 32908 only if the law or regulation is identical to
that requirement.
(c) State and Political Subdivision Automobiles.--A State or a
political subdivision of a State may prescribe requirements for fuel
economy for automobiles obtained for its own use.
0
13. Redesignate Appendix to Part 533--Example of Calculating Compliance
under Sec. 533.5(i) as Appendix A to Part 533--Example of Calculating
Compliance under Sec. 533.5(i) and amend newly redesignated Appendix A
by removing all references to ``Appendix'' and adding in their place,
``Appendix A''.
0
14. Add Appendix B to Part 533 to read as follows:
Appendix B to Part 533--Preemption
(a) Express Preemption:
(1) To the extent that any state law or regulation regulates or
prohibits tailpipe carbon dioxide emissions from automobiles, such a
law or regulation relates to average fuel economy standards within the
meaning of 49 U.S.C. 32919.
(A) Automobile fuel economy is directly and substantially related
to automobile tailpipe emissions of carbon dioxide;
(B) Carbon dioxide is the natural by-product of automobile fuel
consumption;
(C) The most significant and controlling factor in making the
measurements necessary to determine the compliance of automobiles with
the fuel economy standards in this Part is their rate of tailpipe
carbon dioxide emissions;
(D) Almost all technologically feasible reduction of tailpipe
emissions of carbon dioxide is achievable through improving fuel
economy, thereby reducing both the consumption of fuel and the creation
and emission of carbon dioxide;
(E) Accordingly, as a practical matter, regulating fuel economy
controls the amount of tailpipe emissions of carbon dioxide, and
regulating the tailpipe emissions of carbon dioxide controls fuel
economy.
(2) As a state law or regulation related to fuel economy standards,
any state law or regulation regulating or prohibiting tailpipe carbon
dioxide emissions from automobiles is expressly preempted under 49
U.S.C. 32919.
(3) A state law or regulation having the direct effect of
regulating or prohibiting tailpipe carbon dioxide emissions or fuel
economy is a law or regulation related to fuel economy and expressly
preempted under 49 U.S.C. 32919.
(b) Implied Preemption:
(1) A state law or regulation regulating tailpipe carbon dioxide
emissions from automobiles, particularly a law or regulation that is
not attribute-based and does not separately regulate passenger cars and
light trucks, conflicts with:
(A) The fuel economy standards in this Part;
(B) The judgments made by the agency in establishing those
standards; and
(C) The achievement of the objectives of the statute (49 U.S.C.
Chapter 329) under which those standards were established, including
objectives relating to reducing fuel consumption in a manner and to the
extent consistent with manufacturer flexibility, consumer choice, and
automobile safety.
(2) Any state law or regulation regulating or prohibiting tailpipe
carbon dioxide emissions from automobiles is impliedly preempted under
49 U.S.C. Chapter 329.
(3) A state law or regulation having the direct effect of
regulating or prohibiting tailpipe carbon dioxide emissions or fuel
economy is impliedly preempted under 49 U.S.C. Chapter 329.
PART 535--MEDIUM- AND HEAVY-DUTY VEHICLE FUEL EFFICIENCY PROGRAM
0
15. The authority citation for part 535 continues to read as follows:
Authority: 49 U.S.C. 32902 and 30101; delegation of authority
at 49 CFR 1.95.
0
16. Amend Sec. 535.6 by revising paragraph (a)(4)(ii) to read as
follows:
* * * * *
(a) * * *
(4) * * *
(ii) Calculate the equivalent fuel consumption test group results
as follows for spark-ignition vehicles and alternative fuel spark-
ignition vehicles. CO2 emissions test group result (grams
per mile)/8,887 grams per gallon of gasoline fuel) x (10\2\) = Fuel
consumption test group result (gallons per 100 mile).
* * * * *
0
16. Amend Sec. 535.6 by revising paragraphs (a)(4)(ii) and (d)(5)(ii)
to read as follows:
* * * * *
(a) * * *
(4) * * *
(ii) Calculate the equivalent fuel consumption test group results
as follows for spark-ignition vehicles and alternative fuel spark-
ignition vehicles. CO2 emissions test group result (grams
per mile)/8,877 grams per gallon of gasoline fuel) x (10-2)
= Fuel consumption test group result (gallons per 100 mile).
* * * * *
(d) * * *
(5) * * *
(ii) Calculate equivalent fuel consumption FCL values for spark-
ignition engines and alternative fuel spark-ignition engines.
CO2 FCL value (grams per hp-hr)/8,887 grams per gallon of
gasoline fuel) x (10-2) = Fuel consumption FCL value
(gallons per 100 hp-hr).
* * * * *
0
17. Amend Sec. 535.7 by revising the equations in paragraphs (b)(1),
(c)(1), (d)(1), (e)(2) and (f)(2)(iii)(E) to read as follows:
Sec. 535.7 Averaging, banking, and trading (ABT) credit program.
* * * * *
(b) * * *
(1) * * *
Total MY Fleet FCC (gallons) = (Std-Act) x (Volume) x (UL) x
(10-2)
Where:
Std = Fleet average fuel consumption standard (gal/100 mile).
Act = Fleet average actual fuel consumption value (gal/100 mile).
Volume = the total U.S.-directed production of vehicles in the
regulatory subcategory.
UL = the useful life for the regulatory subcategory. The useful life
value for heavy-pickup trucks and vans manufactured for model years
2013 through 2020 is equal to the 120,000 miles. The useful life for
model years 2021 and later is equal to 150,000 miles.
* * * * *
[[Page 43490]]
(c) * * *
(1) * * *
Vehicle Family FCC (gallons) = (Std-FEL) x (Payload) x (Volume) x (UL)
x (10-3)
Where:
Std = the standard for the respective vehicle family regulatory
subcategory (gal/1000 ton-mile).
FEL = family emissions limit for the vehicle family (gal/1000 ton-
mile).
Payload = the prescribed payload in tons for each regulatory
subcategory as shown in the following table:
[GRAPHIC] [TIFF OMITTED] TP24AU18.313
Volume = the number of U.S.-directed production volume of vehicles
in the corresponding vehicle family.
UL = the useful life for the regulatory subcategory (miles) as shown
in the following table:
[GRAPHIC] [TIFF OMITTED] TP24AU18.314
* * * * *
(d) * * *
(1) * * *
Engine Family FCC (gallons) = (Std-FCL) x (CF) x (Volume) x (UL) x
(10-2)
Where:
Std = the standard for the respective engine regulatory subcategory
(gal/100 hp-hr).
FCL = family certification level for the engine family (gal/100 hp-
hr).
CF = a transient cycle conversion factor in hp-hr/mile which is the
integrated total cycle horsepower-hour divided by the equivalent
mileage of the applicable test cycle. For engines subject to spark-
ignition heavy-duty standards, the equivalent mileage is 6.3 miles.
For engines subject to compression-ignition heavy-duty standards,
the equivalent mileage is 6.5 miles.
Volume = the number of engines in the corresponding engine family.
UL = the useful life of the given engine family (miles) as shown in
the following table:
[GRAPHIC] [TIFF OMITTED] TP24AU18.315
* * * * *
(e) * * *
(2) * * *
Vehicle Family FCC (gallons) = (Std - FEL) x (Payload) x (Volume) x
(UL) x (10-\3\)
Where:
Std = the standard for the respective vehicle family regulatory
subcategory (gal/1000 ton-mile).
FEL = family emissions limit for the vehicle family (gal/1000 ton-
mile).
Payload = 10 tons for short box vans and 19 tons for other trailers.
Volume = the number of U.S.-directed production volume of vehicles
in the corresponding vehicle family.
UL = the useful life for the regulatory subcategory. The useful life
value for heavy-duty trailers is equal to the 250,000 miles.
* * * * *
(f) * * *
(2) * * *
(iii) * * *
(E) * * *
[[Page 43491]]
Off-cycle FC credits = (CO2 Credit/CF) x Production x VLM
Where:
CO2 Credits = the credit value in grams per mile
determined in 40 CFR 86.1869-12(c)(3), (d)(1), (d)(2) or (d)(3).
CF = conversion factor, which for spark-ignition engines is 8,887
and for compression-ignition engines is 10,180.
Production = the total production volume for the applicable category
of vehicles.
VLM = vehicle lifetime miles, which for 2b-3 vehicles shall be
150,000 for the Phase 2 program.
The term (CO2 Credit/CF) should be rounded to the
nearest 0.0001.
* * * * *
PART 536--TRANSFER AND TRADING OF FUEL ECONOMY CREDITS
0
18. The authority citation for part 536 continues to read as follows:
Authority: 49 U.S.C. 32903; delegation of authority at 49 CFR
1.95.
0
19. Amend Sec. 536.4 by revising paragraph (c) to read as follows:
Sec. 536.4 Credits.
* * * * *
(c) Adjustment factor. When traded or transferred and used, fuel
economy credits are adjusted to ensure fuel oil savings is preserved.
For traded credits, the user (or buyer) must multiply the calculated
adjustment factor by the number of its shortfall credits it plans to
offset in order to determine the number of equivalent credits to
acquire from the earner (or seller). For transferred credits, the user
of credits must multiply the calculated adjustment factor by the number
of its shortfall credits it plans to offset in order to determine the
number of equivalent credits to transfer from the compliance category
holding the available credits. The adjustment factor is calculated
according to the following formula:
[GRAPHIC] [TIFF OMITTED] TP24AU18.316
Where:
A = Adjustment factor applied to traded and transferred credits when
they are applied to an existing credit shortfall. The quotient shall
be rounded to 4 decimal places;
* * * * *
0
20. Amend Sec. 536.5 by redesignating paragraphs (c)(1) and (c)(2) as
paragraphs (c)(2) and (c)(3), respectively, adding paragraph (c)(1),
and revising paragraph (d)(6) to read as follows:
Sec. 536.5 Trading infrastructure.
* * * * *
(c) * * *
(1) Entities trading credits must generate and submit trade
documents using the NHTSA Credit Template (OMB Control No. 2127-0019,
NHTSA Form 1475). Entities shall fill out the NHTSA Credit Template and
use it to generate a credit trade summary and credit trade
confirmation, the latter of which shall be signed by both trading
entities. The credit trade confirmation serves as an acknowledgement
that the parties have agreed to trade credits, and does not dictate
terms, conditions, or other business obligations. Managers legally
authorized to obligate the sale and purchase of the traded credits must
sign the trade confirmation. The completed credit trade summary and a
PDF copy of the signed trade confirmation must be submitted to NHTSA.
The NHTSA Credit Template is available for download at http://www.nhtsa.gov.
* * * * *
(d) * * *
(6) Credit allocation plans received from a manufacturer will be
reviewed and approved by NHTSA. Use the NHTSA Credit Template (OMB
Control No. 2127-0019, NHTSA Form 1475) to record the credit
transactions requested in the credit allocation plan. The template is a
fillable form that has an option for recording and calculating credit
transactions for credit allocation plans. The template calculates the
required adjustments to the credits. The credit allocation plan and the
completed transaction template must be submitted to NHTSA. NHTSA will
approve the credit allocation plan unless it finds that the proposed
credits are unavailable or that it is unlikely that the plan will
result in the manufacturer earning sufficient credits to offset the
subject credit shortfall. If the plan is approved, NHTSA will revise
the respective manufacturer's credit account accordingly. If the plan
is rejected, NHTSA will notify the respective manufacturer and request
a revised plan or payment of the appropriate fine.
* * * * *
PART 537--AUTOMOTIVE FUEL ECONOMY REPORTS
0
21. The authority citation for part 537 continues to read as follows:
Authority: 49 U.S.C. 32907, delegation of authority at 49 CFR
1.95.
0
24. Amend Sec. 537.5 by revising paragraph (d) and adding paragraph
(e) to read as follows:
Sec. 537.5 General requirements for reports.
* * * * *
(d) Beginning with MY 2019, each manufacturer shall generate
reports required by this part using the NHTSA CAFE Projections
Reporting Template (OMB Control No. 2127-0019, NHTSA Form 1474). The
template is a fillable form.
(1) Select the option to identify the report as a pre-model year
report, mid-model year report, or supplementary report as appropriate;
(2) Complete all required information for the manufacturer and for
all vehicles produced for the current model year required to comply
with CAFE standards. Identify the manufacturer submitting the report,
including the full name, title, and address of the official responsible
for preparing the report and a point of contact to answer questions
concerning the report.
(3) Use the template to generate confidential and non-confidential
reports for all the domestic and import passenger cars and light truck
fleet produced by the manufacturer for the current model year.
Manufacturers must submit a request for confidentiality in accordance
with 49 CFR 512 to withhold projected production sales volume estimates
from public disclosure. If the request is granted, NHTSA will withhold
the projected production sales volume estimates from public disclose
until all the vehicles produced by the manufacturer have been made
available for sale (usually one year after the current model year).
(4) Submit confidential reports and requests for confidentiality to
NHTSA on CD-ROM in accordance with Part 537.12. Email copies of non-
confidential
[[Page 43492]]
(i.e., redacted) reports to NHTSA's secure email address: [email protected].
Requests for confidentiality must be submitted in a PDF or MS Word
format. Submit 2 copies of the CD-ROM to: Administrator, National
Highway Traffic Administration, 1200 New Jersey Avenue SW, Washington,
DC 20590, and submit emailed reports electronically to the following
secure email address: [email protected];
(5) Confidentiality Requests.
(i) Manufacturers can withhold information on projected production
sales volumes under 5 U.S.C. 552(b)(4) and 15 U.S.C. 2005(d)(1). In
accordance, the manufacturer must:
(A) Show that the item is within the scope of sections 552(b)(4)
and 2005(d)(1);
(B) Show that disclosure of the item would result in significant
competitive damage;
(C) Specify the period during which the item must be withheld to
avoid that damage; and
(D) Show that earlier disclosure would result in that damage.
(ii) [Reserved]
(e) Each report required by this part must be based upon all
information and data available to the manufacturer 30 days before the
report is submitted to the Administrator.
0
23. Amend Sec. 537.6 by revising paragraphs (b) and (c) to read as
follows:
Sec. 537.6 General content of reports.
* * * * *
(b) Supplementary report. Except as provided in paragraph (c) of
this section, each supplementary report for each model year must
contain the information required by and Sec. 537.7(b) and (c) in
accordance with Sec. 537.8(b)(1), (2), (3), and (4) as appropriate.
(c) Exceptions. The pre-model year report, mid-model year report,
and supplementary report(s) submitted by an incomplete automobile
manufacturer for any model year are not required to contain the
information specified in Sec. 537.7(c)(4)(xv) through (xviii) and
(c)(5). The information provided by the incomplete automobile
manufacturer under Sec. 537.7(c) shall be according to base level
instead of model type or carline.
0
24. Amend Sec. 537.7 by revising paragraphs (a)(2) and (3) as follows:
Sec. 537.7 Pre-model year and mid-model year reports.
(a) * * *
(2) Provide a report with the information required by paragraph
(a)(1) of this section by each domestic and import passenger automobile
fleet, as specified in part 531 of this chapter, and by each the light
truck fleet, as specified in part 533 of this chapter, for the current
model year.
(3) Provide the information required by paragraph (a)(1) for pre-
and mid-model year reports using the NHTSA CAFE Projections Reporting
Template, OMB Control No. 2127-0019, NHTSA Form 1474. The required
reporting template can be downloaded from http://www.nhtsa.gov.
* * * * *
0
25. Amend Sec. 537.7 by revising paragraphs (b)(3), (b)(4), (b)(5),
(c)(1), (c)(2), (c)(3) and (c)(7)(i), (c)(7)(ii) and (c)(7)(iii) to
read as follows:
* * * * *
(b) * * *
(3) State the projected required fuel economy for the
manufacturer's passenger automobiles and light trucks determined in
accordance with 49 CFR 531.5(c) and 49 CFR 533.5 and based upon the
projected sales figures provided under paragraph (c)(2) of this
section. For each unique model type and footprint combination of the
manufacturer's automobiles, provide the information specified in
paragraph (b)(3)(i) and (ii) of this section and the CAFE Projections
Reporting Template, OMB Control No. 2127-0019, NHTSA Form 1474.
(i) In the case of passenger automobiles:
(A) Beginning model year 2013, base tire as defined in 49 CFR
523.2,
(B) Beginning model year 2013, front axle, rear axle and average
track width as defined in 49 CFR 523.2,
(C) Beginning model year 2013, wheelbase as defined in 49 CFR
523.2, and
(D) Beginning model year 2013, footprint as defined in 49 CFR
523.2.
(E) The fuel economy target value for each unique model type and
footprint entry listed in accordance with the equation provided in 49
CFR parts 531.
(4) State the projected final required fuel economy that the
manufacturer anticipates having if changes implemented during the model
year will cause the targets to be different from the target fuel
economy projected under paragraph (b)(3) of this section.
(5) State whether the manufacturer believes that the projections it
provides under paragraphs (b)(2) and (b)(4) of this section, or if it
does not provide an average or target under those paragraphs, the
projections it provides under paragraphs (b)(1) and (b)(3) of this
section, sufficiently represent the manufacturer's average and target
fuel economy for the current model year for purposes of the Act. In the
case of a manufacturer that believes that the projections are not
sufficiently representative for those purposes, state the specific
nature of any reason for the insufficiency and the specific additional
testing or derivation of fuel economy values by analytical methods
believed by the manufacturer necessary to eliminate the insufficiency
and any plans of the manufacturer to undertake that testing or
derivation voluntarily and submit the resulting data to the
Environmental Protection Agency under 40 CFR 600.509.
(c) * * *
(1) For each model type of the manufacturer's automobiles, provide
the information specified in paragraph (c)(2) of this section in the
NHTSA CAFE Projections Reporting Template (OMB Control No. 2127-0019,
NHTSA Form 1474) and list the model types in order of increasing
average inertia weight from top to bottom.
(2)(i) Combined fuel economy; and
(ii) Projected sales for the current model year and total sales of
all model types.
(3) For each vehicle configuration whose fuel economy was used to
calculate the fuel economy values for a model type under paragraph
(c)(2) of this section, provide the information specified in paragraph
(c)(4) of this section in the NHTSA CAFE Projections Reporting Template
(OMB Control No. 2127-0019, NHTSA Form 1474).
* * * * *
(7) * * *
(i) Provide a list of each air conditioning efficiency improvement
technology utilized in your fleet(s) of vehicles for each model year.
For each technology identify vehicles by make and model types that have
the technology, which compliance category those vehicles belong to and
the number of vehicles for each model equipped with the technology. For
each compliance category (domestic passenger car, import passenger car
and light truck) report the air conditioning fuel consumption
improvement value in gallons/mile in accordance with the equation
specified in 40 CFR 600.510-12(c)(3)(i).
(ii) Provide a list of off-cycle efficiency improvement
technologies utilized in your fleet(s) of vehicles for each model year
that is pending or approved by EPA. For each technology identify
vehicles by make and model types that have the technology, which
compliance category those vehicles belong to, the number of vehicles
for each model equipped with the technology, and the associated off-
cycle credits (grams/mile) available for each technology. For each
compliance
[[Page 43493]]
category (domestic passenger car, import passenger car and light truck)
calculate the fleet off-cycle fuel consumption improvement value in
gallons/mile in accordance with the equation specified in 40 CFR
600.510-12(c)(3)(ii).
(iii) Provide a list of full-size pick-up trucks in your fleet that
meet the mild and strong hybrid vehicle definitions. For each mild and
strong hybrid type, identify vehicles by make and model types that have
the technology, the number of vehicles produced for each model equipped
with the technology, the total number of full size pick-up trucks
produced with and without the technology, the calculated percentage of
hybrid vehicles relative to the total number of vehicles produced and
the associated full-size pickup truck credits (grams/mile) available
for each technology. For the light truck compliance category calculate
the fleet Pick-up Truck fuel consumption improvement value in gallons/
mile in accordance with the equation specified in 40 CFR 600.510-
12(c)(3)(iii).
* * * * *
0
26. Amend Sec. 537.8 by revising paragraphs (a)(3), paragraph
(b)(3)(i) and (ii), and paragraph (c)(1) and adding paragraphs (a)(4)
and (b)(4) to read as follows:
Sec. 537.8 Supplementary reports.
(a) * * *
(3) Each manufacturer whose pre- or mid-model year report omits any
of the information specified in Sec. 537.7(b) or (c) shall file a
supplementary report containing the information specified in paragraph
(b)(3) of this section.
(4) Each manufacturer whose pre- or mid-model year report omits any
of the information specified in Sec. 537.5(c) shall file a
supplementary report containing the information specified in paragraph
(b)(4) of this section.
(b) * * *
(3) * * *
(i) All of the information omitted from the pre- or mid-model year
report under Sec. 537.7(b) and (c); and
(ii) Such revisions of and additions to the information submitted
by the manufacturer in its pre-model year report regarding the
automobiles produced during the current model year as are necessary to
reflect the information provided under paragraph (b)(3)(i) of this
section.
(4) The supplementary report required by paragraph (a)(4) of this
section must contain:
(i) All information omitted from the pre-model year report under
Sec. 537.6(c)(2); and
(ii) Such revisions of and additions to the information submitted
by the manufacturer in its pre-model year report regarding the
automobiles produced during the current model year as are necessary to
reflect the information provided under paragraph (b)(4)(i) of this
section.
(c)(1) Each report required by paragraph (a)(1), (2), (3), or (4)
of this section must be submitted in accordance with Sec. 537.5(c) not
more than 45 days after the date on which the manufacturer determined,
or could have determined with reasonable diligence, that a report is
required under paragraph (a)(1), (2), (3), or (4) of this section.
* * * * *
Environmental Protection Agency
List of Subjects
40 CFR Part 85
Confidential business information, Imports, Labeling, Motor vehicle
pollution, Reporting and recordkeeping requirements, Research,
Warranties.
40 CFR Part 86
Administrative practice and procedure, Confidential business
information, Incorporation by reference, Labeling, Motor vehicle
pollution, Reporting and recordkeeping requirements.
For the reasons stated in the preamble, the Environmental
Protection Agency proposes to amend 40 CFR parts 85 and 86 as follows:
PART 85--CONTROL OF AIR POLLUTION FROM MOBILE SOURCES
0
27. The authority citation for part 85 continues to read as follows:
Authority: 42 U.S.C. 7401-7671q.
Subpart F--[Amended]
0
28. Amend Sec. 85.525 by revising paragraphs (b)(1)(iii) and
(b)(1)(iv) to read as follows:
Sec. 85.525 Applicable standards.
* * * * *
(b) * * *
(1) * * *
(iii) If the OEM complied with the nitrous oxide (N2O)
and methane (CH4) standards and provisions set forth in 40
CFR 86.1818-12(f)(1) or (3), and the fuel conversion CO2
measured value is lower than the in-use CO2 exhaust emission
standard, you also have the option through model year 2020 to convert
the difference between the in-use CO2 exhaust emission
standard and the fuel conversion CO2 measured value into GHG
equivalents of CH4 and/or N2O, using 298 g
CO2 to represent 1 g N2O and 25 g CO2
to represent 1 g CH4. You may then subtract the applicable
converted values from the fuel conversion measured values of
CH4 and/or N2O to demonstrate compliance with the
CH4 and/or N2O standards. This option may not be
used for model year 2021 or later.
(iv) Optionally, through model year 2020, compliance with
greenhouse gas emission requirements may be demonstrated by comparing
emissions from the vehicle prior to the fuel conversion to the
emissions after the fuel conversion. This comparison must be based on
FTP test results from the emission data vehicle (EDV) representing the
pre-conversion test group. The sum of CO2, CH4,
and N2O shall be calculated for pre- and post-conversion FTP
test results, where CH4 and N2O are weighted by
their global warming potentials of 25 and 298, respectively. The post-
conversion sum of these emissions must be lower than the pre-conversion
conversion greenhouse gas emission results. CO2 emissions
are calculated as specified in 40 CFR 600.113-12. If statements of
compliance are applicable and accepted in lieu of measuring
N2O, as permitted by EPA regulation, the comparison of the
greenhouse gas results also need not measure or include N2O
in the before and after emission comparisons. This option may not be
used for model year 2021 or later.
* * * * *
PART 86--CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES
AND ENGINES
0
29. The authority citation for part 86 continues to read as follows:
Authority: 42 U.S.C. 7401-7671q.
0
30. Amend Sec. 86.1818-12 as follows:
0
a. Revise paragraphs (c)(2)(i)(A) through (C);
0
b. Revise paragraphs (c)(3)(i)(A), (B) and (D);
0
c. Revise paragraph (f) introductory text; and paragraphs (f)(1)
through (3).
The revisions read as follows:
Sec. 86.1818-12 Greenhouse gas emission standards for light-duty
vehicles, light-duty trucks, and medium-duty passenger vehicles.
* * * * *
(c) * * *
(2) * * *
(i) * * *
(A) For passenger automobiles with a footprint of less than or
equal to 41 square feet, the gram/mile CO2 target value
shall be selected for the
[[Page 43494]]
appropriate model year from Table 1 to Paragraph (c)(2)(i)(A).
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP24AU18.317
(B) For passenger automobiles with a footprint of greater than 56
square feet, the gram/mile CO2 target value shall be
selected for the appropriate model year from Table 1 to Paragraph
(c)(2)(i)(B).
[[Page 43495]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.318
(C) For passenger automobiles with a footprint that is greater than
41 square feet and less than or equal to 56 square feet, the gram/mile
CO2 target value shall be calculated using the following
equation and rounded to the nearest 0.1 grams/mile, except that for any
vehicle footprint the maximum CO2 target value shall be the
value specified for the same model year in paragraph (c)(2)(i)(B) of
this section:
Target CO2 = [a x [fnof]] + b
Where:
[fnof] is the vehicle footprint, as defined in Sec. 86.1803; and
a and b are selected from Table 1 to Paragraph (c)(2)(i)(C):
[[Page 43496]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.319
* * * * *
(3) * * *
(i) * * *
(A) For light trucks with a footprint of less than or equal to 41
square feet, the gram/mile CO2 target value shall be
selected for the appropriate model year from Table 1 to Paragraph Table
1 to Paragraph (c)(3)(i)(A):
BILLING CODE 4910-59-C
[[Page 43497]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.320
(B) For light trucks with a footprint that is greater than 41
square feet and less than or equal to the maximum footprint value
specified in the table below for each model year, the gram/mile
CO2 target value shall be calculated using the following
equation and rounded to the nearest 0.1 grams/mile, except that for any
vehicle footprint the maximum CO2 target value shall be the
value specified for the same model year in paragraph (c)(3)(i)(D) of
this section:
Target CO2 = (a x [fnof]) + b
Where:
[fnof] is the footprint, as defined in Sec. 86.1803; and
a and b are selected from Table 1 to Paragraph Table 1 to Paragraph
(c)(3)(i)(B): For the appropriate model year:
[[Page 43498]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.321
* * * * *
(D) For light trucks with a footprint greater than the minimum
value specified in the table below for each model year, the gram/mile
CO2 target value shall be selected for the appropriate model
year from Table 1 to Paragraph Table 1 to Paragraph (c)(3)(i)(D):
[[Page 43499]]
[GRAPHIC] [TIFF OMITTED] TP24AU18.322
* * * * *
(f) Nitrous oxide (N2O) and methane (CH4) exhaust emission
standards for passenger automobiles and light trucks. Each
manufacturer's fleet of combined passenger automobile and light trucks
must comply with N2O and CH4 standards using
either the provisions of paragraph (f)(1), or, through model year 2020,
provisions of paragraphs (f)(2) or (3) of this section. Except with
prior EPA approval, a manufacturer may not use the provisions of both
paragraphs (f)(1) and (2) of this section in a model year. For example,
a manufacturer may not use the provisions of paragraph (f)(1) of this
section for their passenger automobile fleet and the provisions of
paragraph (f)(2) for their light truck fleet in the same model year.
The manufacturer may use the provisions of both paragraphs (f)(1) and
(through model year 2020) (3) of this section in a model year. For
example, a manufacturer may meet the N2O standard in
paragraph (f)(1)(i) of this section and an alternative CH4
standard determined under paragraph (f)(3) of this section. Vehicles
certified using the N2O data submittal waiver provisions of
Sec. 86.1829(b)(1)(iii)(G) are not required to be tested for
N2O under the in-use testing programs required by Sec.
86.1845 and Sec. 86.1846.
(1) Standards applicable to each test group. (i) Exhaust emissions
of nitrous oxide (N2O) shall not exceed 0.010 grams per mile
at full useful life, as measured according to the Federal Test
Procedure (FTP) described in subpart B of this part. Through model year
2020, manufacturers may optionally determine an alternative
N2O standard under paragraph (f)(3) of this section. This
option may not be used for model year 2021 or later. (ii) Exhaust
emissions of methane (CH4) shall not exceed 0.030 grams per
mile at full useful life, as measured according to the Federal Test
Procedure (FTP) described in subpart B of this part. Through model year
2020, manufacturers may optionally determine an alternative
CH4 standard under paragraph (f)(3) of this section. This
option may not be used for model year 2021 or later.
(2) Include N2O and CH4 in fleet averaging program. Through model
year 2020, manufacturers may elect to not meet the emission standards
in paragraph (f)(1) of this section. This option may not be used for
model year 2021 or later. Manufacturers making this election shall
include N2O and CH4 emissions in the
determination of their fleet average carbon-related exhaust emissions,
as calculated in 40 CFR part 600, subpart F. Manufacturers using this
option must include both N2O and CH4 full useful
life values in the fleet average calculations for passenger automobiles
and light trucks. Use of this option will account for N2O
and CH4 emissions within the carbon-related exhaust emission
value determined for each model type according to the provisions of 40
CFR part 600. This option requires the determination of full useful
life emission values for both the Federal Test Procedure and the
Highway Fuel Economy Test. Manufacturers selecting this option are not
required to demonstrate compliance with the standards in paragraph
(f)(1) of this section.
(3) Optional use of alternative N2O and/or CH4 standards. Through
model
[[Page 43500]]
year 2020, manufacturers may select an alternative standard applicable
to a test group, for either N2O or CH4, or both.
This option may not be used for model year 2021 or later. For example,
a manufacturer may choose to meet the N2O standard in
paragraph (f)(1)(i) of this section and an alternative CH4
standard in lieu of the standard in paragraph (f)(1)(ii) of this
section. The alternative standard for each pollutant must be greater
than the applicable exhaust emission standard specified in paragraph
(f)(1) of this section. Alternative N2O and CH4
standards apply to emissions measured according to the Federal Test
Procedure (FTP) described in Subpart B of this part for the full useful
life, and become the applicable certification and in-use emission
standard(s) for the test group. Manufacturers using an alternative
standard for N2O and/or CH4 must calculate
emission debits according to the provisions of paragraph (f)(4) of this
section for each test group/alternative standard combination. Debits
must be included in the calculation of total credits or debits
generated in a model year as required under Sec. 86.1865-12(k)(5). For
flexible fuel vehicles (or other vehicles certified for multiple fuels)
you must meet these alternative standards when tested on any applicable
test fuel type.
* * * * *
0
31. Revise Sec. 86.1867-12 to read as follows:
Sec. 86.1867-12 CO2 credits for reducing leakage of air conditioning
refrigerant.
Through model year 2020, manufacturers may generate credits
applicable to the CO2 fleet average program described in
Sec. 86.1865-12 by implementing specific air conditioning system
technologies designed to reduce air conditioning refrigerant leakage
over the useful life of their passenger automobiles and/or light
trucks. Manufacturers may not generate these credits for model year
2021 or later. Credits shall be calculated according to this section
for each air conditioning system that the manufacturer is using to
generate CO2 credits. Manufacturers may also generate early
air conditioning refrigerant leakage credits under this section for the
2009 through 2011 model years according to the provisions of Sec.
86.1871-12(b).
Issued on August 1, 2018, in Washington, DC, under authority
delegated in 49 CFR 1.95 and 501.5.
Heidi R. King,
Deputy Administrator, National Highway Traffic Safety Administration.
Andrew R. Wheeler,
Acting Administrator, Environmental Protection Agency.
[FR Doc. 2018-16820 Filed 8-23-18; 8:45 am]
BILLING CODE 4910-59-P