[Federal Register Volume 84, Number 123 (Wednesday, June 26, 2019)]
[Proposed Rules]
[Pages 30524-30569]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-12773]
[[Page 30523]]
Vol. 84
Wednesday,
No. 123
June 26, 2019
Part IV
Environmental Protection Agency
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40 CFR Parts 141 and 142
National Primary Drinking Water Regulations: Perchlorate; Proposed Rule
Federal Register / Vol. 84, No. 123 / Wednesday, June 26, 2019 /
Proposed Rules
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ENVIRONMENTAL PROTECTION AGENCY
40 CFR Parts 141 and 142
[EPA-HQ-OW-2018-0780; FRL-9994-68-OW]
RIN 2040-AF28
National Primary Drinking Water Regulations: Perchlorate
AGENCY: Environmental Protection Agency (EPA).
ACTION: Proposed rule, request for public comment.
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SUMMARY: The Environmental Protection Agency (EPA) is proposing a
drinking water regulation for perchlorate and a health-based Maximum
Contaminant Level Goal (MCLG) in accordance with the Safe Drinking
Water Act (SDWA). The EPA is proposing to set both the enforceable
Maximum Contaminant Level (MCL) for the perchlorate regulation and the
perchlorate MCLG at 0.056 mg/L (56 [micro]g/L). The EPA is proposing
requirements for water systems to conduct monitoring and reporting for
perchlorate and to provide information about perchlorate to their
consumers through public notification and consumer confidence reports.
This proposal includes requirements for primacy agencies that implement
the public water system supervision program under the SDWA. This
proposal also includes a list of treatment technologies that would
enable water systems to comply with the MCL, including affordable
compliance technologies for small systems serving 10,000 persons or
less.
DATES: Comments must be received on or before August 26, 2019. Under
the Paperwork Reduction Act (PRA), comments on the information
collection provisions are best assured of consideration if the Office
of Management and Budget (OMB) receives a copy of your comments on or
before July 26, 2019.
ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OW-
2018-0780, at https://www.regulations.gov. Follow the online
instructions for submitting comments. Once submitted, comments cannot
be edited or removed from Regulations.gov. The EPA may publish any
comment received to its public docket. Do not submit electronically any
information you consider to be Confidential Business Information (CBI)
or other information whose disclosure is restricted by statute.
Multimedia submissions (audio, video, etc.) must be accompanied by a
written comment. The written comment is considered the official comment
and should include discussion of all points you wish to make. The EPA
will generally not consider comments or comment contents located
outside of the primary submission (i.e., on the web, cloud, or other
file sharing system). For additional submission methods, the full EPA
public comment policy, information about CBI or multimedia submissions,
and general guidance on making effective comments, please visit http://www2.epa.gov/dockets/commenting-epa-dockets.
FOR FURTHER INFORMATION CONTACT: Samuel Hernandez, Office of Ground
Water and Drinking Water, Standards and Risk Management Division (Mail
Code 4607M), Environmental Protection Agency, 1200 Pennsylvania Avenue
NW, Washington, DC 20460; telephone number: (202) 564-1735; email
address: [email protected].
SUPPLEMENTARY INFORMATION: In addition to the proposed regulation, the
EPA is requesting comment on three alternatives: (1) Whether the MCL
and MCLG for perchlorate should be set at 0.018 mg/L (18 [micro]g/L),
(2) whether the MCL and MCLG for perchlorate should be set at 0.090 mg/
L (90 [micro]g/L), or (3) whether instead of issuing a national primary
drinking water regulation, the EPA should withdraw the Agency's
February 11, 2011, determination to regulate perchlorate in drinking
water based on new information that indicates that perchlorate does not
occur in public water systems with a frequency and at levels of public
health concern and there may not be a meaningful opportunity for health
risk reduction through a drinking water regulation. Under this last
alternative, the final action would be a withdrawal of the
determination to regulate and there would be no MCLG or national
primary drinking water regulation for perchlorate. This proposed rule
is organized as follows:
I. General Information
A. What is the EPA proposing?
B. Does this action apply to me?
II. Background
A. What is perchlorate?
B. Statutory Authority
C. Statutory Framework and Regulatory History
III. Assessment and Modeling of the Health Effects of Perchlorate
A. 2008 Preliminary Regulatory Determinations
B. 2009 Supplemental Request for Comment and 2011 Final
Regulatory Determination
C. Science Advisory Board Recommendations
D. Perchlorate Model Development and Peer Reviews
E. Sensitive Population for Deriving MCLG
F. BBDR Model Specification for the Sensitive Population
G. Epidemiological Literature
H. Identifying a Point of Departure for Developing the MCLG
I. Translate PODs to RfDs
J. Translate RfD Into an MCLG
IV. Maximum Contaminant Level Goal and Alternatives
V. Maximum Contaminant Level and Alternatives
VI. Occurrence
VII. Analytical Methods
VIII. Monitoring and Compliance Requirements
A. What are the proposed monitoring requirements?
B. Can States grant monitoring waivers?
C. How are system MCL violations determined?
D. When must systems complete initial monitoring?
E. Can systems use grandfathered data to satisfy the initial
monitoring requirements?
IX. Safe Drinking Water Act Right to Know Requirements
A. What are the Consumer Confidence Report requirements?
B. What are the public notification requirements?
X. Treatment Technologies
A. What are the best available technologies?
B. What are the small system compliance technologies?
XI. Rule Implementation and Enforcement
A. What are the requirements for primacy?
B. What are the State record keeping requirements?
C. What are the State reporting requirements?
XII. Health Risk Reduction Cost Analysis
A. Identifying Affected Entities
B. Method for Estimating Costs
C. Method for Estimating Benefits
D. Comparison of Costs and Benefits
XIII. Uncertainty Analysis
A. Uncertainty in the MCLG Derivation
B. Uncertainty in the Economic Analysis
XIV. Request for Comment on Proposed Rule
XV. Request for Comment on Potential Regulatory Determination
Withdrawal
XVI. Statutory and Executive Order Reviews
A. Executive Order 12866: Regulatory Planning and Review and
Executive Order 13563 Improving Regulation and Regulatory Review
B. Executive Order 13771: Reducing Regulations and Controlling
Regulatory Costs
C. Paperwork Reduction Act
D. Regulatory Flexibility Act (RFA)
E. Unfunded Mandates Reform Act
F. Executive Order 13132: Federalism
G. Executive Order 13175: Consultation and Coordination With
Indian Tribal Governments
H. Executive Order 13045: Protection of Children From
Environmental Health and Safety Risks
I. Executive Order 13211: Actions That Significantly Affect
Energy Supply, Distribution, or Use
J. National Technology Transfer and Advancement Act of 1995
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K. Executive Order 12898: Federal Actions To Address
Environmental Justice in Minority Populations and Low-Income
Populations
XVII. Consultations with the Science Advisory Board, National
Drinking Water Advisory Council, and the Secretary of Health and
Human Services
XVIII. References
I. General Information
A. What is the EPA proposing?
This action contains a proposal and three alternatives for public
comment. First, the EPA proposes to establish a Maximum Contaminant
Level Goal (MCLG) and National Primary Drinking Water Regulation
(NPDWR) for perchlorate in public water supplies. The EPA proposes an
MCLG of 56 [micro]g/L, and to regulate perchlorate in drinking water at
an enforceable maximum contaminant level (MCL) of 56 [micro]g/L.
The EPA is proposing an NPDWR for perchlorate in accordance with
its February 11, 2011, (76 FR 7762) determination to regulate
perchlorate under the SDWA. Based on the best available peer reviewed
science at that time, the EPA found that perchlorate met the SDWA's
three criteria for regulating a contaminant: (1) The contaminant may
have an adverse effect on the health of persons, (2) the contaminant is
known to occur or there is a substantial likelihood that the
contaminant will occur in public water systems (PWSs) with a frequency
and at levels of public health concern, and (3) in the sole judgment of
the Administrator, regulation of such contaminant presents a meaningful
opportunity for health risk reduction for persons served by PWSs.
Second, as explained in more detail below, the EPA is soliciting
comment on two alternative MCLG/MCL values of 18 [micro]g/L and 90
[micro]g/L respectively. Third, in light of new considerations that
have come to the EPA's attention since it issued its positive
regulatory determination in 2011, including information on lower levels
of occurrence of perchlorate than the EPA had previously believed to
exist and new analysis of the concentration that represents a level of
health concern, this action also discusses and requests comment on an
alternative action under which the EPA would withdraw its 2011
determination to regulate perchlorate. Under this alternative, there
would be no MCLG or NPDWR for perchlorate.
B. Does this action apply to me?
Entities that could potentially be affected include the following:
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Category Examples of potentially affected entities
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Public water systems......... Community water systems: Non-transient,
non-community water systems.
State and tribal agencies.... Agencies responsible for drinking water
regulatory development and enforcement.
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This table is not intended to be exhaustive, but rather provides a
guide for readers regarding entities that could be affected by this
action. To determine whether your facility or activities could be
affected by this action, you should carefully examine this proposed
rule. If you have questions regarding the applicability of this action
to a particular entity, consult the person listed in the FOR FURTHER
INFORMATION CONTACT section.
II. Background
A. What is perchlorate?
Perchlorate is a negatively charged inorganic ion that is comprised
of one chlorine atom bound to four oxygen atoms (ClO4-),
which is highly stable and mobile in the aqueous environment.
Perchlorate comes from both natural and manmade sources. It is formed
naturally via atmospheric processes and can be found within mineral
deposits in certain geographical areas. It is also produced in the
United States, and the most common compounds include ammonium
perchlorate and potassium perchlorate used primarily as oxidizers in
solid fuels to power rockets, missiles, and fireworks. For the general
population, most perchlorate exposure is through the ingestion of
contaminated food or drinking water.
B. Statutory Authority
Section 1412(b)(1)(A) of the SDWA requires the EPA to establish
NPDWRs for contaminants that may have an adverse effect on the health
of persons; that are known to occur or there is a substantial
likelihood that the contaminant will occur in public water systems with
a frequency and at levels of public health concern; and where in the
sole judgment of the Administrator, regulation of such contaminant
presents a meaningful opportunity for health risk reduction for persons
served by public water systems.
C. Statutory Framework and Regulatory History
Section 1412(b)(1)(B)(i) of the SDWA requires the EPA to publish
every five years a Contaminant Candidate List (CCL). The CCL is a list
of drinking water contaminants that are known or anticipated to occur
in public water systems and are not currently subject to the EPA
drinking water regulations. The EPA uses the CCL to identify priority
contaminants for regulatory decision-making and information collection.
Contaminants listed on the CCL may require future regulation under the
SDWA. The EPA included perchlorate on the first, second, and third CCLs
published in 1998, 2005, and 2009.
Once listed on the CCL, the Agency continues to collect data on CCL
contaminants to better understand their potential health effects and to
determine the levels at which they occur in drinking water. Section
1412(b)(1)(B)(ii) requires that, every five years, the EPA, after
public comment, issue a determination whether or not to regulate at
least five contaminants on the CCL. For any contaminant that the EPA
determines meets the criteria for regulation, under Section
1412(b)(1)(E), the EPA must issue a proposed national primary drinking
water regulation within two years and issue a final regulation 18
months after the proposal (which may be extended by 9 months).
As part of its responsibilities under the SDWA, the EPA implements
section 1445(a)(2), ``Monitoring Program for Unregulated
Contaminants.'' This section requires that once every five years, the
EPA issue a list of no more than 30 unregulated contaminants to be
monitored by public water system. This monitoring is implemented
through the Unregulated Contaminant Monitoring Rule (UCMR), which
collects data from community water systems (CWS) and non-transient,
non-community water systems (NTNCWS). The UCMR collects data from a
census of large water systems (serving more than 10,000 people) and
from a statistically representative sample of small water systems. On
September 17, 1999, the EPA published its first UCMR (64 FR 50556)
which required all large systems and a representative sample of small
systems to monitor for perchlorate and 25 other contaminants (USEPA,
1999, 2000b).
The EPA and other federal agencies asked the National Research
Council
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(NRC) to evaluate the health implications of perchlorate ingestion. The
NRC concluded that perchlorate exposure inhibits the transport of
iodide \1\ into the thyroid by a protein molecule knows as the sodium/
iodide symporter (NIS), which may lead to decreases in two hormones,
thyroxine (T3) and triiodothyronine (T4) and increases in thyroid-
stimulating hormone (TSH) (National Research Council (NRC), 2005b).
Additionally, the NRC concluded that the most sensitive population to
perchlorate exposure are ``the fetuses of pregnant women who might have
hypothyroidism or iodide deficiency'' (p. 178). The EPA established a
reference dose (RfD) consistent with the recommended National Research
Council RfD of 0.7 [micro]g/kg/day for perchlorate. The reference dose
is an estimate of a daily exposure to humans that is likely to be
without an appreciable risk of adverse effects. This RfD was based on a
study (Greer, Goodman, Pleus, & Greer, 2002) of perchlorate's
inhibition of radioactive iodine uptake in healthy adults and the
application of an uncertainty factor of 10 for intraspecies variability
(USEPA, 2005b).
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\1\ For the purposes of this FRN, ``iodine'' will be used to
refer to dietary intake before entering the body. Once in the body,
``iodide'' will be used to refer to the ionic form.
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In October 2008, the EPA published a preliminary regulatory
determination not to regulate perchlorate in drinking water and
requested public comment (73 FR 60262). In that preliminary
determination, the EPA tentatively concluded that perchlorate did not
occur with a frequency and at levels of public health concern and that
development of a regulation did not present a meaningful opportunity
for health risk reduction for persons served by public water systems.
The EPA derived and used a Health Reference Level (HRL) of 15 [mu]g/L
based on the RfD of 0.7 [micro]g/kg/day in making this conclusion
(USEPA, 2008a). Based primarily on the UCMR 1 occurrence data, the EPA
estimated that less than 1% of drinking water systems (serving
approximately 1 million people) had perchlorate levels above the HRL of
15 [micro]g/L. Based on this information the Agency determined that
perchlorate did not occur frequently at levels of health concern. The
EPA also determined that there was not a meaningful opportunity for a
NPDWR to reduce health risks.
In January 2009 the EPA published an interim health advisory for
perchlorate of 15 [micro]g/L, consistent with the HRL derivation for
perchlorate of 15 [micro]g/L described above. Health Advisories are
non-enforceable and non-regulatory and provide technical information to
state agencies and other public health officials on health effects,
analytical methodologies, and treatment technologies associated with
drinking water contamination. Health Advisories provide the public,
including the most sensitive populations, with a margin of protection
from a lifetime of exposure. For perchlorate, the health advisory was
developed for subchronic exposure (USEPA 2008d).
In August 2009, the EPA published a supplemental request for
comment with a new analysis that derived potential alternative HRLs for
14 life stages, including infants and children. The analysis used the
RfD of 0.7 [mu]g/kg/day and life stage-specific bodyweight and exposure
information (74 FR 41883; USEPA, 2009a). After careful consideration of
public comments on the October 2008 and August 2009 notices, on
February 11, 2011, the EPA published its determination to regulate
perchlorate (76 FR 7762; USEPA, 2011a). The Agency stated then that
when considering the alternative HRL benchmarks described in the 2009
notice, the likelihood of perchlorate to occur at levels of concern had
significantly increased in comparison to the levels described on the
2008 preliminary negative determination. The EPA concluded that as many
as 16 million people could potentially be exposed to perchlorate at
levels of concern, up from 1 million people originally described in the
2008 notice.
In its 2011 determination, the Agency found that perchlorate may
have an adverse effect on the health of persons, that it is known to
occur in public drinking water systems with a frequency and at levels
that present a public health concern, and in the judgment of the
Administrator, regulation of perchlorate presented a meaningful
opportunity for health risk reduction for persons served by public
water systems. As a result of the determination, and as required by
Section 1412(b)(1)(E), the EPA initiated the process to develop an MCLG
and NPDWR for perchlorate as described in this notice.
In September 2012, the U.S. Chamber of Commerce (the Chamber)
submitted to the EPA a Request for Correction under the Information
Quality Act regarding the EPA's regulatory determination. In the
request, the Chamber claimed that the UCMR 1 data did not comply with
data quality guidelines and were not representative of current
conditions. In response to this request, the EPA reassessed the data
and removed certain source water samples that could be paired with
appropriate follow-up samples located at the entry point to the
distribution system. The EPA also updated the UCMR 1 data for systems
in California and Massachusetts using state compliance data to reflect
current occurrence conditions after state regulatory limits for
perchlorate were implemented.
In response to a lawsuit brought to enforce the deadlines in
Section 1412(b)(1)(E), the U.S. District Court for the Southern
District of New York entered a consent decree, requiring the EPA to
propose an NPDWR with a proposed MCLG for perchlorate in drinking water
no later than October 31, 2018, and finalize an NPDWR and MCLG for
perchlorate in drinking water no later than December 19, 2019. The
deadline for the EPA to propose an NPDWR with a proposed MCLG for
perchlorate in drinking water was later extended to May 28, 2019. The
consent decree is available in the docket for today's proposed rule.
III. Assessment and Modeling of the Health Effects of Perchlorate
Perchlorate inhibits uptake of iodide into the thyroid gland by
competitively binding to the NIS (ATSDR, 2008; Greer et al., 2002; NRC,
2005; SAB 2013; Taylor et al., 2013). Iodide is necessary for the
synthesis of thyroid hormones and decreased iodide uptake into the
thyroid can adversely affect thyroid hormone production (SAB for the
U.S. EPA, 2013; Blount et al., 2006; Steinmaus et al., 2007, 2013,
2016, McMullen et al., 2017; Knight et al., 2018). These changes in
thyroid hormone levels in a pregnant woman may be linked to changes in
the neurodevelopment of her offspring (SAB for the U.S. EPA, 2013;
Korevaar et al., 2016; Fan and Wu, 2016; Wang et al., 2016; Alexander
et al., 2017; Thompson et al., 2018). In addition, alterations in
thyroid homeostasis may impact other body systems including the
reproductive (Alexander et al., 2017; Hou et al., 2016; Maraka et al.,
2016) and cardiovascular systems (Asvold et al., 2012; Sun et al.,
2017).
The mode of action of perchlorate toxicity has been proposed as
follows: exposure to perchlorate is known to inhibit the uptake of
iodide by the thyroid gland through the NIS (NRC, 2005; SAB for the
U.S. EPA, 2013). A sufficient inhibition of iodide uptake results in
iodide deficiency within the thyroid. Given that T3 and T4 require
iodide for production, a decrease in intra-thyroidal iodide can result
in decreased production of these hormones. This could in turn result in
increased TSH, the hormone that acts on
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the thyroid gland to stimulate iodide uptake to increase thyroid
hormone production (Blount, Pirkle, Osterloh, Valentin-Blasini, &
Caldwell, 2006; National Research Council (NRC), 2005; Steinmaus,
Miller, Cushing, Blount, & Smith, 2013; Steinmaus et al., 2016). For
populations with developing brains (e.g., fetuses, neonates, and
children), disruptions in homeostatic thyroid hormone function can
result in adverse neurodevelopmental effects (Alexander et al., 2017;
Glinoer & Delange, 2000; Glinoer & Rovet, 2009; SAB for the U.S. EPA,
2013). Specifically, decreased maternal thyroid hormone levels during
pregnancy, including in the hypothyroxinemic range,\2\ have been linked
to decrements in neurocognitive function in offspring (Alexander et
al., 2017; Thompson et al., 2018; Wang et al., 2016). There is also
limited evidence to suggest an association with other adverse
neurodevelopmental outcomes including ADHD, expressive language delay,
reduced school performance, autism, and delayed cognitive development
(Alexander et al., 2017; Ghassabian, Bongers-Schokking, Henrichs,
Jaddoe, & Visser, 2011; Gyllenberg et al., 2016; Henrichs et al., 2010;
Korevaar et al., 2016, Noten et al., 2015; Pop et al., 2003, 1999; SAB
for the U.S. EPA, 2013; van Mil et al., 2012).
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\2\ Maternal hypothyroxinemia is defined as TSH in the reference
range and fT4 in the lower percentiles. The SAB notes that
hypothyroxinemia has been defined by a ``variety of cutoffs . . .
ranging from fT4 below the 10th or 5th percentiles to below the
2.5th percentile'' (SAB, 2013, p.10) in the population.
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The difficulty in estimating the likelihood and magnitude of the
potential implications of perchlorate's mode of action on expressed
neurodevelopmental health effects in humans exposed to perchlorate
during development is the lack of robust epidemiological studies,
especially in sensitive populations. Therefore, based on the known mode
of action of perchlorate the Agency estimated potential health risks
using a novel approach suggested by the EPA's Science Advisory Board
(SAB for the U.S. EPA, 2013). The EPA's approach to estimating
perchlorate risks has evolved over time with improved research and
modeling capabilities. The following sections describe information
sources the EPA used in its assessment as well as the regulatory
process followed by the Agency in its decision making.
A. 2008 Preliminary Regulatory Determinations
In 2005, at the request of the EPA and other federal agencies, the
NRC evaluated the health implications of perchlorate ingestion. The NRC
concluded that perchlorate exposure could inhibit the transport of
iodide into the thyroid, leading to thyroid hormone deficiency (NRC,
2005). A significant inhibition of iodide uptake results in intra-
thyroid iodide deficiency, decreased synthesis of T3 and T4, and
increased TSH. The NRC also concluded that a prolonged decrease of
thyroid hormones is potentially more likely to have adverse effects in
sensitive populations (e.g., the fetuses of pregnant women who might
have hypothyroidism or iodide deficiency). Based on these findings, the
NRC recommended a reference dose of 0.7 [micro]g/kg/day.
Based on NRC's analysis, the EPA established a perchlorate
reference dose (RfD) of 0.7 [micro]g/kg/day in 2005 (USEPA, 2005). This
value was based on a no observed effect level (NOEL) of 7 [micro]g/kg/
day identified from a study (Greer, Goodman, Pleus, & Greer, 2002) of
perchlorate's inhibition of radioactive iodine uptake in healthy adults
and the application of an uncertainty factor of 10 for intraspecies
variability.
As discussed above, in 2008, the EPA derived an HRL of 15 [mu]g/L
using the RfD of 0.7 [mu]g/kg/day, a default bodyweight of 70 kg, a
default drinking water consumption rate of 2 L/day, and a perchlorate-
specific relative source contribution (RSC) of 62 percent that was
derived for a pregnant woman (USEPA, 2008a) (73 FR 60262). The RSC is
the percentage of the RfD remaining for drinking water after other
sources of exposure to perchlorate (i.e., food) have been considered.
The EPA's HRL was calculated to offer a margin of protection against
adverse health effects to the subpopulation identified by the NAS as
likely the most sensitive to the effects of perchlorate exposure,
fetuses.
B. 2009 Supplemental Request for Comment and 2011 Final Regulatory
Determination
The EPA received over 33,000 comments in response to its 2008
preliminary determination to not regulate perchlorate (USEPA, 2011a).
After reviewing the comments, the EPA developed alternative HRLs for
other sensitive populations in addition to fetuses of pregnant women.
The EPA developed alternative HRLs for 14 life stages including infants
and children. The EPA also evaluated the occurrence of perchlorate at
levels above these alternative HRLs using the UCMR 1 occurrence data.
The analysis used the RfD of 0.7 [mu]g/kg/day and life stage-
specific bodyweight and exposure information (i.e., drinking water
intake, RSC) for each of the 14 life stages evaluated. The resulting
HRLs ranged from 1 [mu]g/L to 47 [mu]g/L. In August 2009, the EPA
published a supplemental request for comment with the new analysis and
HRLs (74 FR 41883; USEPA, 2009a). After careful consideration of public
comments, on February 11, 2011, the EPA published its final
determination to regulate perchlorate (76 FR 7762; USEPA, 2011a).
C. Science Advisory Board Recommendations
As required by Section 1412(d) of the SDWA, as part of the NPDWR
development process, the EPA requested comments from the Science
Advisory Board (SAB) in 2012, seeking guidance on how best to consider
and interpret the life stage information, the epidemiologic and
biomonitoring data since the NRC report, physiologically-based
pharmacokinetic (PBPK) analyses, and the totality of perchlorate health
information to derive an MCLG for perchlorate. The SAB recommended the
following:
Derive a perchlorate MCLG that addresses sensitive life
stages through physiologically based pharmacokinetic/pharmacodynamic
(PBPK/PD) modeling based upon perchlorate's mode of action rather than
the default MCLG approach using the RfD and specific chemical exposure
parameters;
expand the modeling approach to account for thyroid
hormone perturbations and potential adverse neurodevelopmental outcomes
from perchlorate exposure;
utilize a mode-of-action framework for developing the MCLG
that links the steps in the proposed mechanism leading from perchlorate
exposure through iodide uptake inhibition--to thyroid hormone changes--
and finally to neurodevelopmental impacts; and
``Extend the [BBDR] model expeditiously to . . . provide a
key tool for linking early events with subsequent events as reported in
the scientific and clinical literature on iodide deficiency, changes in
thyroid hormone levels, and their relationship to neurodevelopmental
outcomes during sensitive early life stages'' (SAB for the U.S. EPA,
2013, p. 19).
This SAB-proposed framework would incorporate the previous endpoint
of iodide uptake inhibition that was the basis for the RfD as part of a
broader and more comprehensive framework that links perchlorate
exposure to adverse neurodevelopmental outcomes. It also focuses on the
smaller changes in thyroid hormones (specifically free T4 (fT4)) that
are associated with maternal hypothyroxinemia and subsequent
[[Page 30528]]
adverse neurodevelopmental health effects rather than the significant
changes in thyroid hormones (both fT4 and TSH) that are associated with
hypothyroidism.
D. Perchlorate Model Development and Peer Reviews
To address the SAB recommendations, the EPA revised an existing
PBPK/PD model that describes the dynamics of perchlorate, iodide, and
thyroid hormones in a woman during the third trimester of pregnancy
(Lumen, Mattie, & Fisher, 2013; USEPA, 2009b). The EPA also created its
own Biologically Based Dose Response (BBDR) models that included the
additional sensitive life stages identified by the SAB, i.e., breast-
and bottle-fed neonates and infants (SAB for the U.S. EPA, 2013, p.
19).
To determine whether the Agency had implemented the SAB
recommendations for modeling thyroid hormone changes, the EPA convened
an independent peer review panel to evaluate the BBDR models in January
2017 (External Peer Reviewers for USEPA, 2017). In addition to
estimating effects on breast fed infants, several reviewers recommended
that the EPA shift the primary focus of its analysis to modeling the
exposure implications to the fetus during early pregnancy. This was
based on the knowledge that fetuses lack a functioning thyroid gland
until approximately 16 gestational weeks and the substantial
epidemiological evidence linking early pregnancy low fT4 levels with
adverse neurodevelopmental outcomes (Endendijk et al., 2017, Korevaar
et al., 2016; Morreale de Escobar, Obreg[oacute]n, & Escobar del Rey,
2004, Pop et al., 1999; Pop et al., 2003). Specifically, the SAB
recommended that the EPA use specific sensitive populations to develop
the MCLG for perchlorate: ``the fetuses of hypothyroxinemic pregnant
women, and infants exposed to perchlorate through either water-based
formula preparations or the breast milk of lactating women'' (SAB for
the U.S. EPA, 2013, p. 19).
The EPA considered all recommendations from the 2017 peer review.
The previously developed BBDR model describing perchlorate's effects in
the third trimester (Lumen, Mattie, & Fisher, 2013; USEPA, 2009b) was
calibrated only for that phase of pregnancy, not for the first
trimester, and lacked a description of TSH signaling (feedback) that
becomes significant as individuals become hypothyroxinemic or
hypothyroid. In particular, this signaling was considered necessary to
accurately predict responses of women with very low iodine intake,
which was also part of the 2017 peer review recommendations. Therefore,
the Lumen et al., (2009b) model needed to be revised to address these
recommendations and the EPA implemented those changes needed to
increase the scientific rigor of the model and modeling results. These
modifications include:
Extending the model to early pregnancy;
Incorporating biological feedback control of hormone
production via TSH signaling, such that the model can describe lower
levels of iodide nutrition;
Calibrating the model and evaluating its behavior for
upper and lower percentiles of the population, as well as the
population median; and
Conducting an uncertainty analysis for key parameters.
The EPA convened a second independent peer review panel in January
2018 to evaluate these updates to the BBDR model. The EPA also
presented several approaches in the draft Proposed Approaches to Inform
the Derivation of a Maximum Contaminant Level Goal for Perchlorate in
Drinking Water (MCLG Approaches Report) to link the thyroid hormone
changes in a pregnant mother predicted by the BBDR model to
neurodevelopmental effects using evidence from the epidemiological
literature (External Peer Review for U.S. EPA, 2018). The 2018 peer
review identified a variety of strengths and limitations of the
modeling (to be discussed in more detail later in this notice). The
peer review panel was largely supportive of the efforts described in
the MCLG Approaches Report, as evidenced by the following from the peer
review final report:
Overall, the panel agreed that the EPA and its collaborators have
prepared a highly innovative state-of-the-science set of quantitative
tools to evaluate neurodevelopmental effects that could arise from
drinking water exposure to perchlorate. While there is always room for
improvement of the models, with limited additional work to address the
committee's comments [in the peer-reviewed report], the current models
are fit-for-purpose to determine an MCLG (External Peer Reviewers for
U.S. EPA, 2018, p. 2).
The EPA also presented an alternative, population-based approach
evaluating the shift in the proportion of the population that would
fall below a hypothyroxinemic cut point, given exposure to perchlorate
(Section 7 of the MCLG Approaches Report). This approach does not
directly connect the BBDR output to a neurodevelopmental endpoint.
However, for pregnant women in early pregnancy, this shift could be
related to avoiding an increase in the population of offspring's risk
of adverse neurodevelopmental impacts. The 2018 peer review identified
strengths associated with this approach, including
(1) the central premise, that hypothyroxinemia is associated with
adverse neurodevelopmental effects is supported by a large number of
studies, including categorical studies; (2) this approach encompasses a
variety of adverse neurodevelopmental outcomes, as indicated by these
studies, rather than focusing on one or a limited number of adverse
outcomes, as with the two-stage approach; and (3) this approach avoids
all of the uncertainties associated with determining a quantitative
relationship between a specific maternal fT4 level and the magnitude an
adverse neurodevelopmental effect. (External Peer Reviewers for U.S.
EPA, 2018, p. 7)
The peer reviewers expressed concern about hypothyroxinemia being a
precursor effect, rather than an adverse health outcome, which they
argued may create difficulties in explaining the basis for an MCLG
based on this approach to some audiences. However, the EPA has used
precursor effects as the basis for setting regulatory and non-
regulatory limits previously. The peer-review panel also expressed
concern that a standard definition of hypothyroxinemia has not yet been
established, as clinicians use varying fT4 thresholds to define their
own working definition of the condition. This also could lead to
difficulties communicating the population at risk for developing this
precursor effect as a result of perchlorate exposure.
Ultimately, the EPA chose to develop the MCLG using dose-response
functions from the epidemiological literature to estimate
neurodevelopmental impacts in the offspring of pregnant women exposed
to perchlorate. The EPA selected this proposed approach because it is
consistent with the SDWA's definition of an MCLG to avoid adverse
health effects and because it is most consistent with the SAB
recommendations. The EPA is requesting public comment in Section XIV on
the adequacies and uncertainties of the methodology to derive the MCLG
including the decision not to pursue this population-based approach for
setting the MCLG.
Based on the comments of the peer reviewers, the EPA's final
analysis informing the derivation of the MCLG and benefits of avoided
perchlorate exposure is based upon a 2-step
[[Page 30529]]
approach to modeling the neurodevelopmental effects on offspring of
pregnant women exposed to perchlorate in drinking water (see Figure 1).
In summary, because of the known mode of action, the lack of
epidemiological studies particularly in the sensitive populations and
the direction of the SAB to use a ``data-driven approach [which]
represents a more rigorous way to address differences in biology and
exposure between adults and sensitive life stages'' (p. 2, SAB 2013 for
U.S. EPA), the EPA uses a combination of the BBDR model that simulates
perchlorate potential impacts on maternal thyroid hormones during
pregnancy and the epidemiology literature that relates incremental
changes in maternal thyroid hormones to neurodevelopmental outcomes in
children. The following sections describe the approach in greater
detail, highlighting each step in which decisions and assumptions were
made.
[GRAPHIC] [TIFF OMITTED] TP26JN19.008
Note: Process figure does not imply the strength of scientific
evidence.
E. Sensitive Population for Deriving MCLG
SDWA 1412(b)(4)(A) requires MCLGs to be set at a concentration in
water ``at which no known or anticipated adverse effects on the health
of persons occur and which allows an adequate margin of safety.'' SDWA
1412(b)(3)(C)(V) further requires that the EPA ``consider the effects
of the contaminant on the general population and on groups within the
general population such as infants, children, pregnant women, the
elderly, individuals with a history of serious illness, or other
subpopulations that are identified as likely to be at greater risk of
adverse health effects due to exposure to contaminants in drinking
water than the general population.'' The EPA has interpreted these
requirements to establish MCLGs that avoid adverse effects within the
portions of the population that are at greater risk of adverse effects
from exposure to the contaminant. The EPA is proposing an MCLG that is
developed to protect the fetuses of a first trimester pregnant mother
with low-iodine intake levels (i.e., 75 [micro]g/kg/day), low fT4
levels (i.e., 10th percentile of an fT4 distribution for individuals
with 75 [micro]g/day iodine intake), and weak TSH feedback strength
(i.e., TSH feedback is reduced to be approximately 60 percent less
effective than for the median individual). The choice of this
population is consistent with discussion by the NRC (2005), and the SAB
(2013). The EPA believes that by protecting this population, the other
sensitive populations (i.e., breast- and bottle-fed infants) will also
be protected. This conclusion is based on the EPA's analysis of
predictions of the impact of perchlorate on fT4 levels from the
original EPA BBDR model (which was peer reviewed in January of 2017)
and an analysis of the literature on the connection between altered
thyroid hormones in these life stages, and neurodevelopmental outcomes.
The EPA's original BBDR model demonstrated that perchlorate had
minimal impact on the thyroid hormone levels for 30-, 60-, and 90-day
formula-fed infants, even at doses as high as 20 [micro]g/kg/day.
Specifically, the model demonstrated that ``the range of iodine levels
in formula is sufficient to almost entirely offset the effects of
perchlorate exposure at 30, 60 and 90 days'' (USEPA, 2017; p. 73). As a
result of these findings the EPA concluded that any MCLG based on the
fetus of the first trimester hypothyroxinemic pregnant mother would
also protect the formula-fed infant.
To determine if the same would be true for the breast-fed infant,
the EPA compared the predicted percent change in fT4 experienced at
given doses of perchlorate for both the breast-fed infant and the first
trimester pregnant mother at varying doses of iodine intake \3\ (50 to
100 [micro]g/day). Assuming 2 or 4 [micro]g/kg/day of perchlorate, the
first trimester hypothyroxinemic pregnant mother has a greater percent
change in fT4 compared to the 30 and 60 day breast-fed infant at all
maternal iodine intake levels evaluated, except for the 30 day breast-
fed infant of a mother consuming only 50 [micro]g/day iodine. However,
given that the original BBDR model did not have a TSH feedback loop,
T4, fT4, T3 and fT3 predictions for lactating mothers with less than 75
[micro]g/day iodine intake were considered highly uncertain because the
thyroid hormone levels had fallen into the hypothyroid range.
---------------------------------------------------------------------------
\3\ Given that the current version of the BBDR model contains a
TSH feedback loop and the infant models previously developed did not
contain this feedback loop, this comparison is done with the
feedback loop turned off.
---------------------------------------------------------------------------
The Agency found that there are reports in the scientific
literature suggesting that minor perturbations in thyroid hormone
levels in the first trimester mother may adversely impact her
offspring's neurodevelopment. Specifically, some studies show that
children exposed gestationally to maternal hypothyroxinemia (without
hypothyroidism) have a higher risk of reduced levels of global and
specific cognitive abilities, as well as increased rates of behavior
problems including greater dysregulation in early infancy and
attentional disorders in childhood (Kooistra, Crawford, van Baar,
Brouwers, & Pop, 2006; Man, Brown, & Serunian, 1991; Pop et al., 2003;
Pop et al., 1999). Notably these effects are correlated with both
degree (Henrichs et al., 2010; Pop et al., 1999) and duration (Pop et
al., 2003) of maternal hypothyroxinemia (SAB for the U.S. EPA, 2013, p.
10).
The EPA did not find analogous evidence linking minor perturbations
in thyroid hormones during infancy to adverse neurodevelopmental
outcomes in infants. This finding is consistent with conclusions by the
California Environmental Protection Agency (CalEPA) in their assessment
of a public health goal for perchlorate (California Environmental
Protection Agency, 2011, p. 90).
Specifically, two studies evaluated both the impact of maternal
hypothyroxinemia and infant fT4 levels on subsequent neurodevelopmental
outcomes. Costeira et al. (2011) found that children born to mothers
with low fT4 in the first trimester had increased odds of mild-to-
severe delays in
[[Page 30530]]
psychomotor development compared to children born to mothers with
normal fT4 levels. However, the authors found that neonatal thyroid
status (measured on day 3 after birth) did not influence development.
Additionally, Henrichs et al. (2010) found in their evaluation that
although maternal hypothyroxinemia was associated with language delay
and nonverbal cognitive delay, the neonatal thyroid status (thyroid
hormones measured in cord blood) did not explain the relationship
between maternal hypothyroxinemia, early pregnancy, and children's
cognitive impairment.
The SAB pointed to two lines of evidence supporting their
suggestion of the infant as a potentially sensitive population to
perchlorate: Preterm infants that experience transient hypothyroxinemia
of prematurity (THOP) and infants that experience congenital
hypothyroidism (SAB for the U.S. EPA, 2013). Thus, sufficient thyroid
hormone levels in infancy are necessary for the infant brain to develop
properly. However, the best evidence linking perturbations in thyroid
hormone levels to disrupted neurodevelopment for infants are in
individuals with significant thyroid deficiencies manifesting as
clinical conditions (e.g., THOP and congenital hypothyroidism). It is
unclear and unknown if minor perturbations in thyroid hormones in
infants, such as those that could be caused by environmental levels of
perchlorate, would result in adverse neurodevelopmental outcomes
similar to those seen in the literature for the offspring of first
trimester pregnant mothers with hypothyroxinemia. Given the lack of
evidence demonstrating minor perturbations in infant fT4 levels as
being associated with neurodevelopmental outcomes, the EPA has
concluded that it is appropriate to derive the perchlorate MCLG to
protect the first trimester fetus of a pregnant mother with low-iodine
intake. The EPA concludes that an MCLG calculated to offer a margin of
protection against adverse health effects to these fetuses targets the
most sensitive lifestage and will be protective of other potentially
sensitive life stages as well.
F. BBDR Model Specification for the Sensitive Population
The BBDR model used to develop the proposed MCLG has two main
components:
A pharmacokinetic model for perchlorate and iodide, which
describes chemical absorption, distribution, metabolism, and excretion
of perchlorate and iodide; and
A pharmacodynamic model, which describes the joint effect
of varying perchlorate and iodide blood concentrations on thyroidal
uptake of iodide and subsequent production of thyroid hormones,
including fT4.
The pharmacokinetic model component contains a physiological
description of a human mother and fetus during pregnancy (e.g., organ
volumes, blood flows) and chemical-specific information (e.g.,
partition coefficients, volume of distribution, rate constants for
transport, metabolism, and elimination) that enable a prediction of
perchlorate and iodide internal concentration at the critical target
(i.e., thyroidal sodium-iodide symporter of the mother) in association
with a particular exposure scenario (route of exposure, age, dose
level). This component of the model is similar to many other PBPK
models. Because perchlorate does not undergo metabolism in vivo
(Clewell et al., 2007), potential uncertainty from this factor of the
model is avoided since it does not need to be described.
The pharmacodynamic component of the model uses this internal
concentration to simulate how the chemical will act within a known
mechanism of action to perturb host systems and lead to a toxic effect.
Thus, the BBDR model estimates serum thyroid hormone levels in the
mother at specific gestational weeks, given specific levels of iodine
intake, the TSH feedback loop strength, and perchlorate doses. As noted
above, to be health protective the EPA chose to model a sensitive
individual (an adult woman with low iodine through the first trimester
of pregnancy) to derive an MCLG, thereby protecting both this target
sensitive population with an adequate margin of safety and those who
are less sensitive with an even larger margin of safety.
The BBDR model simulates perchlorate's impact on thyroid hormones
at each gestational week from conception to week 16. To derive the
MCLG, the EPA selected outputs for gestational week 13 to correspond
with the thyroid hormone data reported in Korevaar et al., (2016),
which is the basis for the Agency's quantitative relationship between
maternal thyroid hormone levels and neurodevelopmental impacts.
Individuals with low iodine intake have increased sensitivity to
perchlorate's impact on thyroid hormone levels because the functional
iodide reserve of the hypothalamic-pituitary-thyroid (HPT) system is
limited (Blount et al., 2006, Steinmaus et al., 2007; Leung, Pearce, &
Braverman, 2010). The EPA selected an iodine intake level of 75
[micro]g/day to simulate an individual with low-iodine intake. This
value represents an intake between the 15th and 20th percentile of the
women of child bearing age population distribution of estimated iodine
intake from the National Health and Nutrition Examination Survey
(NHANES). The EPA considered using a lower iodine intake level of 50
[micro]g/day, which represents approximately the 5th percentile of the
NHANES distribution. At 50 [micro]g/day of iodine intake, however, the
BBDR model predicts TSH levels that would be elevated to within the
clinically hypothyroid range before exposure to any perchlorate \4\
(TSH ranges between 4.51 and 5.41 milli-international units per liter
(mIU/L) at zero dose of perchlorate when evaluating gestational weeks
12 or 13). In contrast, at 75 [micro]g/day iodine, the BBDR modeled
concentrations of serum fT4 and TSH are significantly reduced from the
population median but are still within the euthyroid range. Thus, the
intake of 75 [micro]g/day is a better approximation of the sensitive
population--the offspring of pregnant women who have low fT4.
---------------------------------------------------------------------------
\4\ For the purposes of this analysis, the EPA evaluated the
American Thyroid Association's (ATA's) 2017 recommendations for
defining hypothyroidism (Alexander et al., 2017). Specifically the
ATA recommends ``in the pregnancy setting, maternal hypothyroidism
is defined as a TSH concentration elevated beyond the upper limit of
the pregnancy-specific reference range'' (Alexander et al., 2017, p.
332). ATA goes on to state, in the absence of population- and
trimester-specific reference ranges defined by a provider's
institute or laboratory, that the TSH reference ranges should be
obtained from similar patient populations. From their recommended
studies with trimester-specific data on a U.S. population, Lambert-
Meserlian et al. (2008) is the largest U.S.-based population with a
reference range upper bound of 3.37 mIU/L for the first trimester
(and 3.35 mIU/L for the second trimester). Therefore, these values
were used to compare to BBDR output TSH values in the first
trimester (or second trimester in cases of gestational weeks 15 and
16) to determine the presence of hypothyroidism.
---------------------------------------------------------------------------
TSH increases in response to decreases in T4 have been captured in
numerous studies that document the relationship between these hormones
(Blount et al., 2006; Steinmaus et al., 2013, 2016). The EPA designed
the BBDR model to depict this feedback regulation by adjusting a set of
three parameters: The number of sodium-iodide symporter sites, the T4
synthesis rate, and the T3 synthesis rate. The BBDR model allows for
variability in the strength of the TSH feedback by varying these
parameters with a variable called ``pTSH.'' For the MCLG analysis, the
EPA used a pTSH value of 0.398, which is the ratio of a median value
for TSH
[[Page 30531]]
from NHANES (non-pregnant women) to the 97.5 percentile value from
NHANES (non-pregnant women). This value represents an assumption that
sensitive individuals with high TSH and average fT4 levels exist, and
this is because the stimulus strength of TSH is proportionally weaker.
The EPA chose to use a low TSH feedback coefficient to ensure the MCLG
is protective of the sensitive population.
Example output from the BBDR model for gestational week 13 and a
low TSH feedback coefficient is presented in Table III-1.
Table III-1--Summary of BBDR Model Results for fT4 Levels: Pregnant Women at Gestational Week 13, Assuming Low
(75 [micro]g/day) Iodine Intake and with Muted TSH feedback strength \a\
----------------------------------------------------------------------------------------------------------------
Percentile fT4 (pmol/L) \b\ (% decrease from 0 dose)
Perchlorate dose ([mu]g/kg/day) ---------------------------------------------------------------------------
2.5th 5th 10th 50th
----------------------------------------------------------------------------------------------------------------
0................................... 5.57 6.09 6.70 8.84
1................................... 5.50 (-1.26%) 6.02 (-1.15%) 6.63 (-1.04%) 8.77 (-0.79%)
2................................... 5.43 (-2.45%) 5.96 (-2.24%) 6.56 (-2.04%) 8.71 (-1.54%)
3................................... 5.37 (-3.59%) 5.96 (-3.28%) 6.50 (-2.98%) 8.64 (-2.26%)
4................................... 5.31 (-4.68%) 5.83 (-4.28%) 6.44 (-3.89%) 8.58 (-2.95%)
5................................... 5.25 (-5.73%) 5.77 (-5.23%) 6.38 (-4.76%) 8.52 (-3.60%)
6................................... 5.19 (-6.73%) 5.72 (-6.14%) 6.33 (-5.59%) 8.47 (-4.23%)
7................................... 5.14 (-7.69%) 5.66 (-7.02%) 6.27 (-6.39%) 8.41 (-4.84%)
----------------------------------------------------------------------------------------------------------------
\a\ pTSH = 0.398; see USEPA, (2018b) for additional information on pTSH.
\b\ The 50th percentile is direct output from the BBDR model, and additional percentiles are estimated by
assuming a normal distribution with a SD of 1.67. All of the examined study data demonstrated a positive skew,
and overall the lognormal function demonstrated a better fit than a normal distribution. Despite this, the
available study data only accounted for variation due to gestation week and did not account for variation in
perchlorate and iodine intake in the measured populations. Because perchlorate and iodine can affect fT4
levels, and this relationship produced the estimated median BBDR values, the distribution around values
estimated by the model from perchlorate and iodine intake should account for a small reduction in variation
due to the effect of perchlorate and iodine intake. Additionally, as iodine has a demonstrated lognormal
distribution with strong right skew (e.g., Blount et al., 2007) and is predicted to have a stronger effect on
fT4 than perchlorate (see Section 3). The EPA assumed the error around predicted fT4 would likely be closer to
normal than lognormal after accounting for perchlorate and iodine intake.
When modeling changes in fT4, the baseline level of fT4 affects the
magnitude of changes seen as a result of perchlorate exposure.
Therefore, to predict the impact of perchlorate exposure on the
population distribution of fT4 for the identified sensitive population,
the EPA estimated a distribution for fT4 plasma concentrations around
the median modeled values based on fT4 data from studies that were used
to calibrate the BBDR model (C. Li et al., 2014; M[auml]nnist[ouml] et
al., 2011; Zhang et al., 2016). The EPA assumed the variation around
predicted fT4 concentrations for women with low fT4 of childbearing age
would likely be close to normal after accounting for perchlorate and
iodine intake, and thus estimated a combined standard deviation (SD)
using the distributional information from each of the studies (C. Li et
al., 2014; M[auml]nnist[ouml] et al., 2011; Zhang et al., 2016). The
EPA then used the estimated combined SD to predict a distribution of
fT4 around the median fT4 estimated by the BBDR model. To protect the
most sensitive population from adverse effects, the EPA chose to use
the 10th percentile from this distribution of baseline fT4 to conduct
its analyses to account for variability in thyroid hormones in the
population.\5\
---------------------------------------------------------------------------
\5\ For a discussion on the details of the BBDR model, including
uncertainties associated with the model the reader is directed to
section 3.5 of the MCLG Approaches Report.
---------------------------------------------------------------------------
G. Epidemiological Literature
The SAB recommended that the EPA integrate BBDR model results with
data on neurodevelopmental outcomes from epidemiological studies. There
is substantial epidemiological evidence that early pregnancy
hypothyroxinemia is a risk factor for a variety of adverse
neurodevelopmental outcomes, including those related to both cognition
and behavior (Costeira et al., 2011; Finken, van Eijsden, Loomans,
Vrijkotte, & Rotteveel, 2013; Ghassabian et al., 2014; Gyllenberg et
al., 2016; Henrichs et al., 2010; J[uacute]lvez et al., 2013; Kooistra,
Crawford, van Baar, Brouwers, & Pop, 2006; Korevaar et al., 2016; Y. Li
et al., 2010; Oostenbroek et al., 2017; P[auml]kkil[auml] et al., 2015;
Pop et al., 2003, 1999; Roman et al., 2013; van Mil et al., 2012).
These individual studies showing that maternal hypothyroxinemia is
associated with offspring neurodevelopment are also supported by three
meta-analyses (including one full systematic review), all of which
conclude maternal hypothyroxinemia is associated with increased risk of
cognitive delay, intellectual impairment, or lower scores on
performance tests when considering the entire body of evidence on this
topic (Fan & Wu, 2016; Thompson et al., 2018; Wang et al., 2016).
Additionally, the American Thyroid Association concludes that
``overall, available evidence appears to show an association between
hypothyroxinemia and cognitive development of the offspring''
(Alexander et al., 2017, p. 337).
The EPA did not conduct a full systematic review and weight of
evidence evaluation between maternal thyroid hormones and
neurodevelopmental outcomes given: (1) The body of scientific
literature regarding this association, and (2) the SAB recommendation
that the EPA ``consider available data on potential adverse health
effects (neurodevelopmental outcomes) due to thyroid hormone level
perturbations regardless of the cause of those perturbations'' (p. 25).
Instead, the EPA conducted a ``methodologic approach to reviewing the
literature'' to evaluate the body of literature on this topic. This
approach assisted in extrapolating the relationship modeled by the BBDR
model to neurodevelopmental outcomes by concentrating on studies that
allowed for evaluation of incremental changes in fT4 as they relate to
incremental changes in neurodevelopmental outcomes. More specifically,
the EPA only used studies that had sufficient data to show a
quantitative relationship between maternal fT4 and a neurodevelopmental
outcome. The EPA acknowledges that by not giving any weight to the
studies that did not show
[[Page 30532]]
a quantitative relationship between fT4 and neurodevelopmental
outcomes, the Agency may be overestimating the dose of perchlorate that
may be associated with adverse neurodevelopmental outcomes. This is a
health protective decision that adds to the margin of safety.
Ultimately, the EPA developed a dose-response function that
estimates incremental changes in a neurodevelopmental endpoint based on
a given change in thyroid hormone concentration (fT4), which could be
linked to a given dose of perchlorate using the BBDR model.
The specifics of this ``methodologic approach to reviewing the
literature'' follow. First, the EPA identified and screened the
available 71 epidemiological studies, which potentially pertained to
altered maternal thyroid hormone levels and offspring neurodevelopment
to identify candidates based on the following criteria:
Compatible with the sensitive life stages identified by
the NRC and SAB;
Continuous measure of thyroid hormone values (versus
categorical values);
Low risk of bias based on analysis using the National
Toxicology Program's Office of Health Assessment and Translation (OHAT)
Risk of Bias (ROB) tool score; and
Access to underlying data.
Second, using these screening steps, the EPA categorized all 71
studies into three groups. One group consisted of studies that were not
compatible \6\ with extending the BBDR model (40 studies). Another
group consisted of papers that were relevant to the pertinent life
stages but did not have data from which a dose-response analysis could
be conducted (15 studies). This includes studies that compared
differences between groups, for example studies of offspring of mothers
with hypothyroxinemia versus offspring of mothers without
hypothyroxinemia. Consequently, these studies may have provided insight
into the maternal thyroid hormone and offspring neurodevelopment
relationship but did not have enough information to develop a
continuous dose-response function. The last group of papers had data
that may inform a dose-response function (16 studies). This last group
of papers included publications that may have had categorical analyses
but also presented data that assessed fT4 as a continuous variable and
the outcome of interest. In most instances, the continuous fT4 variable
encompassed the full range for fT4 and not just the hypothyroxinemic
range. After excluding one paper due to a high risk of bias (Kastakina
et al., 2006) 15 papers remained that potentially had dose-response
data between a continuous measure of fT4 and various neurodevelopmental
outcomes describing cognition, behavior and other outcomes. The EPA
notes that by selecting the papers that potentially had dose response
data the Agency is deviating from the systematic weight of evidence
review approach to identify those studies that the SAB recommended we
examine to derive the MCLG.
---------------------------------------------------------------------------
\6\ For example, if the study evaluated the impact of only
neonatal thyroid hormones (i.e., at a potentially sensitive life
stage), it cannot be used because the BBDR model is specific to
early pregnancy. Further, if the study evaluates a population with
an existing disease (i.e., hypothyroidism) that may have a different
response to perchlorate compared to the euthyroid population, it was
not considered compatible with BBDR model results. Additionally, if
the study does not include information on T4 or fT4, it does not
assist in understanding the implications of the BBDR modeling
results. Another reason for exclusion at this stage include that the
study does not have a population with an exposure window (i.e., when
the thyroid hormone measurements are taken) that overlaps with the
outputs for the BBDR model. Specifically, the study should evaluate
thyroid hormone levels in pregnant mothers between conception and
gestational week 16. The neurodevelopmental outcomes could be
measured at any life stage.
---------------------------------------------------------------------------
Third, from these 15 papers five were selected for dose response
assessment--four related to cognition (Finken et al., 2013; Korevaar et
al., 2016; Pop et al., 2003, 1999) and one related to behavior
(Endendijk, Wijnen, Pop, & van Baar, 2017). The other ten papers were
excluded for a variety of reasons including updated analyses being
presented in a different paper for which dose-response analysis was
being conducted, lack of all the data needed to complete a dose-
response assessment (e.g., dose-response results were presented as
``per standard deviation of fT4'' but the standard deviation needed to
fully interpret the results for a continuous function was not presented
in the paper, statistical methods presented in the paper were
insufficient to allow for the derivation of a concentration response
function), or a lack of a relationship between maternal fT4 as a
continuous variable and the outcome of interest evaluated in the paper.
For example, Noten et al., (2015) found a relationship between maternal
hypothyroxinemia and offspring arithmetic test performance. However,
maternal fT4 as a continuous variable across the entire fT4 range was
not associated with arithmetic test performance. Given this null
finding, as well as the lack of published literature evaluating
maternal fT4 as a continuous variable and arithmetic test performance,
it would be difficult for the Agency to justify setting an MCLG based
on changes in this endpoint.
As laid out for the peer reviewers, for each study that met the
criteria identified above for dose-response modeling, a relationship
between maternal thyroid hormone levels (specifically fT4) and
offspring neurodevelopment was derived (see USEPA, 2018b). These
relationships were either presented in the original published paper or
derived by the EPA through either the digitization of figures or
through re-analysis of data provided by the study authors. The EPA used
the upper effect estimate (the upper bound of the 95th percent
confidence interval) from each study to assure consideration of the
populations likely to be at greater risk from the dose of perchlorate
associated with a given change in fT4.
Table III-2 provides a summary of the changes in fT4 predicted to
produce a 1, 2, and 3 percent decrease in any given neurodevelopmental
effect and corresponding perchlorate doses. The choice of 1, 2, and 3%
is based on the analyses for IQ, Mental Development Index (MDI), and
Psychomotor Development Index (PDI). Specifically, a 1%, 2%, or 3%
change from the standardized mean for each test (i.e., 100 points)
equates to a 1, 2, or 3 point change, respectively. The analyses for
anxiety/depression score and SD of reaction time are based on a 1%, 2%,
or 3% change from the study mean of each measure, which for anxiety/
depression is 0.01, 0.02, or 0.03 points, respectively, and for
reaction time is 2.7, 5.4, and 8.1 milliseconds (study mean SD of
reaction time = 270 ms), respectively (Endendijk et al., 2017; Finken
et al., 2013).
These results provide the potential impacts of perchlorate on
maternal fT4 (as predicted by the BBDR model) and subsequent
neurodevelopmental impacts (derived from the epidemiologic literature
\7\).
---------------------------------------------------------------------------
\7\ For a more complete description of all the studies evaluated
the reader is directed to Sections 5 and 6 of the MCLG Approaches
Report. For a discussion on the uncertainties related to the
approach the reader is directed specifically to section 6.5.
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[[Page 30533]]
[GRAPHIC] [TIFF OMITTED] TP26JN19.009
[[Page 30534]]
[GRAPHIC] [TIFF OMITTED] TP26JN19.010
H. Identifying a Point of Departure for Developing the MCLG
From the seven analyses presented in Table III-2 above, the EPA
chose to use its independent analysis of the Korevaar et al., (2016)
data (comprising of 3,600 useable mother/child data pairs) as the basis
for calculating the point of departure (POD) for the MCLG. There are
three reasons for this selection: (1) There is sufficient quantitative
data to derive a health impact function for the sensitive population of
interest; (2) the analysis adjusts for an appropriate set of
confounders, and (3) the neurodevelopmental endpoint--intelligence
quotient (IQ)--is more straightforward to interpret because there is
more national and cross-national data available (more on the selection
of this endpoint below). The other studies presented in Table III-2 do
not provide one or more of these features (USEPA, 2018b).
The five identified papers evaluated a variety of endpoints with
Korevaar et al., (2016) evaluating IQ, Pop, Kuijpens, et al., (1999)
and Pop, Brouwers, et al., (2003) using the Bayley Scale to evaluate
PDI and MDI, Finken, van Eijsden, Loomans, Vrijkotte, and Rotteveel
(2013) evaluating the SD of reaction time, and Endendijk, Wijnen, Pop,
and van Baar (2017) evaluating anxiety/depression scores using the
Child Behavioral Check List (CBCL). The SD of reaction time from Finken
et al., (2013) was not well-received by the peer reviewers (External
Peer Review for U.S. EPA, 2018) because it is difficult to ascertain
the true implications of a change in the SD of reaction time. The
Endendijk et al., (2017) study was identified after the peer review so
no feedback was given on the appropriateness of the endpoint; however,
the anxiety/depression raw score is not an intuitively interpretable
endpoint. Further, neither the Endendijk et al., (2017) nor the Finken
et al., (2013) analyses had functions for the sensitive life stage
(i.e., their analyses were based on the full range of fT4 levels and
did not concentrate on the impacts of low-end fT4 levels). For these
reasons, the Endendijk et al., (2017) and Finken et al., (2013) papers
were not selected for further evaluation.
The Korevaar et al., (2016) original and independent analyses are
preferable compared to the Pop, Kuijpens, et al., (1999) and Pop,
Brouwers, et al., (2003) studies because neither function derived from
the Pop et al., studies was adjusted for confounders. Additionally,
both Pop et al., papers have an N <50 compared to the Korevaar et al.,
analyses, which have an N of greater than 3,600.\8\
---------------------------------------------------------------------------
\8\ The original Korevaar et al. (2016) analysis included 3,839
mother/child pairs. The EPA reanalysis of the Korevaar et al. (2016)
data had a slightly lower N of 3,609 due to the exclusion of
subjects with imputed values for maternal fT4.
---------------------------------------------------------------------------
Although the original Korevaar et al., (2016) analysis was the most
rigorous analysis available in the literature to date, the Korevaar et
al., (2016) EPA reanalysis was chosen over the original analysis
because it included modifications to the analysis at the suggestion of
the peer review panel. The
[[Page 30535]]
revised analysis controls for a more parsimonious set of confounders
(e.g., previously included variables such as infant gender, maternal
parity, birthweight, mother's body mass index (BMI), and gestational
age at blood draw that are not related to both the exposure and the
outcome were excluded), thus decreasing the chances of overfitting the
estimation of the association between maternal fT4 and child IQ. The
EPA was prompted to revisit the original Korevaar et al., (2016) model
because of the feedback received during the peer review of the MCLG
Approaches Report. Specifically, a member of the peer-review panel
expressed the following suggestion:
Korevaar et al., [2016] controlled for instrumental variables (e.g.
gestational week at fT4 measurement) as well as variables that are
consequences of altered fT4 (e.g. maternal BMI), which may have biased
estimates. This study also assumed a log-linear relation between fT4
and the outcome but it is unclear whether the data fit this functional
form better than a linear form. Reanalysis of the data performed by EPA
should not include the variables noted above, which may have driven
measures of association towards the null, and should investigate the
most appropriate functional form to inform decisions about
transformation of fT4 values (External Peer Reviewers for U.S. EPA,
2018, pp. 61-62).
The EPA responded to this suggestion by developing a causal model
for the effect of maternal fT4 on child IQ to identify the minimum set
of confounding variables, testing the proper functional form of the
relationship between maternal fT4 and child IQ in the Korevaar et al.,
(2016) data, and making decisions about data quality and influential
data points in the analysis. That is, the EPA determined that there
were values of the independent variable of interest, fT4, in the
original analysis that were imputed using multiple imputations. This
could have impacted the effect estimate of the independent variable of
interest with data that were not directly measured. The EPA reanalysis
excludes these non-measured values. Subsequently, the EPA selected the
Korevaar et al., (2016) reanalysis as the most appropriate function
from which to assess the relationship between fT4 and IQ.\9\
---------------------------------------------------------------------------
\9\ A more complete description of the EPA independent analysis
of the Korevaar et al. (2016) data can be found in Section 6.3.2 of
the MCLG Approaches Report.
---------------------------------------------------------------------------
As indicated above, the EPA has utilized a health protective
approach to this analysis consistent with the SDWA definition of the
MCLG. The peer reviewers commented that this approach was fit-for-
purpose. In particular, the Agency assumed it could estimate risk
reductions based on evidence of a quantifiable relationship between
thyroid hormone changes and neurodevelopmental outcomes. The existence
of a quantifiable relationship between thyroid hormone changes and
neurodevelopmental outcomes has strong support from the literature on
the subject; however, not every study identified an association between
maternal fT4 and the specified outcome of interest, and the state of
the science on this relationship is constantly evolving. As explained
earlier, the results of the EPA's dose-response literature review
identified 31 studies that evaluated the association between maternal
thyroid hormone levels and offspring neurodevelopment, with
neurodevelopment defined using a variety of endpoints related to
cognition, behavior, and other outcomes such as autism. Among these
studies, only 16 were deemed to potentially possess information that
could inform a dose-response relationship. The other 15 only presented
data on categorical analyses assessing the impact of maternal
hypothyroxinemia on the neurodevelopmental outcomes of interest.
Therefore, because the data presented was only a comparison of two
groups, there was not information that could be used to inform a dose-
response function.
Of the 16 studies that potentially had data to inform a dose-
response function, 10 evaluated cognition using a variety of tests
including various IQ tests (three papers; Ghassabian et al., 2014;
Korevaar et al., 2016; Moleti et al., 2016), Bayley Scales of Infant
Development (two papers; Pop et al., 1999; Pop et al., 2003), and other
validated tests associated with child cognition such as expressive
language delay or test performance (five papers; Finken et al., 2013;
Henrichs et al., 2010; Kastakina et al., 2006; Noten et al., 2015; Oken
et al., 2009). Six of these papers found a statistically significant
relationship between maternal fT4, as a continuous variable, and
offspring cognitive outcome (Korevaar et al., 2016; Pop et al., 1999;
Pop et al., 2003; Finken et al., 2013; Henrichs et al., 2010, Kastakina
et al., 2006). However, there were studies where maternal fT4 as a
continuous variable was not significantly associated with the outcome
of interest. For example, in Ghassabian et al., (2014) the authors
found maternal hypothyroxinemia to be associated with an average of a
4.3-point reduction in IQ in their offspring compared to offspring of
non-hypothyroxinemic mothers. Nevertheless, when assessing the
relationship between the continuous measure of maternal fT4 as a
continuous variable (across the entire range of fT4 levels) and child
IQ, the authors did not find a significant relationship. Additionally,
Moleti et al., (2016) found the relationship between maternal fT4 and
child IQ to be consistently inversely associated with IQ scores, but
their assessment failed to reach statistical significance. This study
included fewer than 60 study participants and was considered by the
authors to be a pilot assessment.
In addition to the cognitive effects assessed and modeled, the EPA
identified four papers that assessed maternal fT4 status and behavioral
outcomes (Endendijk et al., 2017; Ghassabian et al., 2011; Modesto et
al., 2015; Oostenbroek et al., 2017), one paper that assessed maternal
fT4 status and autism (Roman et al., 2013) and one paper that evaluated
odds of a schizophrenia diagnosis as associated with maternal thyroid
hormone status (Gyllenberg et al., 2016). From this group of papers,
the majority of papers found an association either between maternal
hypothyroxinemia or maternal fT4 as a continuous variable and the
outcome of interest (Endendijk et al., 2017; Modesto et al., 2015;
Oostenbroek et al., 2017; Roman et al., 2013; Gyllenberg et al., 2016).
However, this was not always the case as exemplified by Ghassabian et
al., (2011) and Gyllenberg et al., (2016). Although Endendijk et al.,
(2017) found maternal fT4 to have a significant adverse impact on
anxiety/depression using the Child Behavioral Check List (CBCL),
Ghassabian et al., (2011) did not find any association between maternal
thyroid hormone status and offspring score on various components of the
CBCL. Additionally, Gyllenberg et al., (2016) found maternal
hypothyroxinemia during early to mid-gestation was associated with 70%
increased odds of schizophrenia diagnosis in offspring of
hypothyroxinemic mothers compared to the offspring of non-
hypothyroxinemic mothers. Gyllenberg et al., (2016) also found an
association with odds of schizophrenia diagnosis using conditional
logistic regression when assessing fT4 as a continuous variable across
the entire fT4 range (i.e., not just the hypothyroxinemic range);
however, this relationship was attenuated after controlling for
smoking.
Not every paper the EPA located in its literature review found a
statistically
[[Page 30536]]
significant association between maternal fT4 as a continuous variable
(i.e., the initially identified 16 studies identified as potentially
useful to inform a dose-response function) and the neurodevelopmental
outcome of interest. However, many studies located in the EPA
literature review, several meta-analyses (Fan & Wu, 2016; Thompson et
al., 2018 and Wang et al., 2016), the American Thyroid Association
(Alexander et al., 2017) and the U.S. EPA's SAB (2013) have concluded
there is a relationship between maternal hypothyroxinemia and various
neurodevelopmental outcomes. The relationship between maternal fT4
levels and neurodevelopmental outcomes appears strongest in the
hypothyroxinemic range, and when looking at the entire range of fT4 as
a continuous variable (as opposed to a categorical cut off), the
significant relationship between the two variables may dissipate.
Therefore, the EPA has concentrated on the neurodevelopmental impacts
of changes in fT4 in the lower range of fT4 from the Korevaar et al.,
(2016) data. In an attempt to minimize uncertainty, the EPA reanalyzed
the data collected by Korevaar et al., (2016) using a spline function
that estimates a coefficient specifically for the low range of the fT4
data.
There are a variety of neurodevelopmental endpoints used to examine
behavior and cognition in children (e.g., intelligence quotient (IQ),
motor skills, vocabulary and language development, stimulus
responsiveness, etc.). The EPA selected IQ decrements because this was
the endpoint evaluated in the Korevaar et al., (2016) study. The EPA
determined that the Korevaar study was the most rigorous analysis that
examined the relationship between decreased thyroid hormones and
neurodevelopmental effects. As such, in the derivation of the MCLG, IQ
is a surrogate for a suite of potential neurodevelopmental effects that
might occur to the offspring of hypothyroxinemic and iodine deficient
mothers.
There are several different tests that are widely used to measure
IQ in children, including the Stanford-Binet and the Wechsler
Intelligence Scale for Children (WISC) (Sternberg et al., 2001). Each
of these tests is intended to assess a child's global functioning and
uses a numerical IQ point scale (Beres et al., 2000). IQ scores are
standardized by age and sex group with a mean score of 100 points and a
standard deviation of 15 (Beres et al., 2000). Although the specific
tasks differ by test, all IQ tests contain a number of tasks to assess
diverse skills (Sternberg et al., 2001). For example, the WISC test
evaluates full-scale IQ using a combination of verbal and performance
scales (verbal IQ and performance IQ may also be assessed separately)
(Beres et al., 2000). The verbal scale includes tasks such as
arithmetic, vocabulary, and comprehension, while the performance scale
includes tasks such as picture completion, block design, and object
assembly (Beres et al., 2000). The WISC was standardized using a sample
of 2200 U.S. children aged 6 to 16 years old (Seashore et al., 1950).
It has been well validated and has demonstrated high reliability, with
a reliability coefficient of 0.96 observed across age groups (Beres et
al., 2000).
Associations have been found between IQ scores and both educational
achievement and attainment, though observed correlations vary widely.
In a review of the literature, Sternberg et al., (2001) suggest that IQ
scores explain approximately 25% of the variance in academic
achievement. Evidence also suggests that IQ is linked to career
outcomes and job performance, with observed correlations ranging from
approximately 0.2 to 0.6 (Sternberg et al., 2001). Research suggests
that children's rearing environment, including parental education,
while growing up may increase IQ scores in adolescence by several
points (e.g., Kendler et al., 2015).
IQ scores have been used to help diagnose disorders such as
intellectual disability and to identify children for placement into
specialized learning programs (Beres et al., 2000). For example, in the
Diagnostic and Statistical Manual of Mental Disorders, fifth edition
(DSM-V) IQ scores are used in an individual's comprehensive assessment
to determine intellectual disability, which pairs standardized testing
of intelligence with a clinical assessment of adaptive functioning.
Intellectual disability is considered for individuals with an IQ score
of about 70 or below (American Psychiatric Association, 2013).
The EPA uses a variety of science policy approaches to select
points of departure for developing regulatory values. For instance, in
noncancer risk assessment the EPA often uses a percentage change in
value. When assessing toxicological data, a 10 percent extra risk (for
discrete data), or a 1 standard deviation (i.e., 15 IQ points) change
from the mean (for continuous data) is often used (USEPA, 2012). A
smaller response to inform a POD has been applied when using
epidemiological literature because there is an inherently more direct
relationship between the study results and the exposure context and
health endpoint. Given the difficulty in identifying a response below
which no adverse impact occurs when considering a continuous outcome in
the human population, the EPA looked to its Benchmark Dose Guidance
(2012) for insight regarding a starting point. Specifically, ``[a] BMR
of 1% has typically been used for quantal human data from epidemiology
studies'' (p. 21, USEPA, 2012).
For the specific context of setting an MCLG for perchlorate, the
EPA made a policy decision to evaluate the level of perchlorate in
water associated with a 1 percent decrease, a 2 percent decrease, and a
3 percent decrease in the mean population IQ (i.e., 1, 2 and 3 IQ
points). The EPA selected IQ as a surrogate for neurodevelopmental
effects based upon its evaluation of the epidemiologic literature
describe above. The need to utilize the best available peer reviewed
data to inform scientific assumptions and policy choices to meet the
statutory requirements associated with developing an MCLG under the
SDWA highlights the challenges associated with regulating chemicals for
which potential effects are indirect, and scientific data do not
address all uncertainties. The Agency must make a policy decision
informed by science, consistent with statutory requirements even in
situations where the data do not provide clear choices. To develop the
proposed MCLG for perchlorate, the EPA made a policy decision to use a
2 IQ point decrement in the population-distribution of IQ for the
sensitive population. By selecting this approach, the EPA is not
establishing a precedent for future Agency actions on other
contaminants for which there is concern about potential thyroid
effects, either under the SDWA or other statutory frameworks.
Applying these response rates to the results from the reanalysis of
Korevaar et al., (2016), results in a POD dose of 3.1 [micro]g/kg/day
for a 1 point decrease in the sensitive population's IQ, a POD dose of
6.7 [micro]g/kg/day for a 2 point decrease in the sensitive
population's IQ, and a POD dose of 10.8 [micro]g/kg/day for a 3 point
decrease in the sensitive population's IQ. These PODs associated with a
1, 2, or 3 point decrease from the standardized mean IQ are calculated
for the most sensitive population. Specifically, the POD is designed to
provide an adequate margin of safety for the fetuses of mothers with
fT4 at the 10th percentile of a population with iodine intake of 75
[micro]g/day and a TSH feedback loop that is less than 60% as effective
as individuals with median
[[Page 30537]]
TSH feedback loop efficacy. That is, the analysis is designed to
protect the population of fetuses of mothers with suboptimal thyroid
functioning. For these reasons, and for the methodological reasons
described previously, the EPA believes that the selection of these
parameters and this point of departure assures no known or anticipated
adverse effects on the health of the most sensitive population and
allows for an adequate margin of safety.
I. Translate PODs to RfDs
When deriving an RfD the EPA evaluates whether to apply
uncertainty/variability factors to account for heterogeneity of effect
in the target population and data gaps (USEPA, 2002). As presented in A
Review of the RfD & RfC Processes (USEPA, 2002) the EPA considers the
following uncertainty factors: Inter-individual variability,
interspecies uncertainty, extrapolating from subchronic to chronic
exposure, extrapolating from a lowest-observed adverse effect level
(LOAEL) rather than from a no-observed-adverse-effect-level (NOAEL),
and an incomplete database. The factors are intended to account for:
(1) Variation in susceptibility among the members of the human
population (i.e., inter-individual or intraspecies variability); (2)
uncertainty in extrapolating animal data to humans (i.e., interspecies
uncertainty); (3) uncertainty in extrapolating from data obtained in a
study with less-than-lifetime exposure (i.e., extrapolating from
subchronic to chronic exposure); (4) uncertainty in extrapolating from
a LOAEL rather than from a NOAEL; and (5) uncertainty associated with
extrapolation when the database is incomplete. (U.S. EPA, 2011b) The
EPA has considered each of these factors in deriving an RfD to inform
an MCLG for perchlorate.
The EPA considered variation and uncertainty in the relationship
between exposure and response among the members of the human population
(i.e., uncertainty factor (UF) for within-human variability/inter-
individual variability, UFH). For this analysis a UF of 3 is
used. The approach taken to derive the RfD attempts to address
variability between the general population and the sensitive
population. Specifically, the EPA was able to modify the strength of
the TSH feedback loop and iodine intake levels in the BBDR model and
concentrate on the dose-response relationship between lower level (as
opposed to median level) fT4 and neurodevelopmental outcomes. However,
there is still uncertainty in the relationship between perchlorate
exposure and subsequent neurodevelopmental outcomes.\10\ There are very
few toxicokinetic calibration data available for the perchlorate to
thyroid hormone relationship described in the BBDR model. On the
toxicodynamic side of the BBDR model, aspects such as competitive
inhibition at the NIS, depletion of iodide stores under different
iodine intake levels and physiological states, and the ability of the
TSH feedback loop to compensate for perturbations in thyroid function
each have their own uncertain features. There are also uncertainties
linking maternal fT4 levels to offspring IQ. These uncertainties
include the population for which dose-response information is available
(i.e., no study is U.S. based), a lack of study information on the
iodine intake status for the population for which the dose-response
information is available, uncertainties around the methods used to
assess maternal fT4 measurement during pregnancy, and uncertainties
related to the true distribution of fT4 for a given iodine intake.
---------------------------------------------------------------------------
\10\ For a more complete discussion on the uncertainties in the
analysis the reader is directed to Sections 3.5 and 6.5 of the MCLG
Approaches Report.
---------------------------------------------------------------------------
Further, as discussed in section III.C. of this preamble the EPA
believes that protecting the fetus of a hypothyroxinemic woman will
protect other identified sensitive life stages. However, there is some
uncertainty due to the lack of information linking incremental changes
in infant thyroid hormone levels to adverse neuorodevelopmental
outcomes. In addition, this analysis is assuming that protecting a
first trimester fetus from alterations in maternal fT4 will protect the
fetus throughout pregnancy. This is based on epidemiologic evidence
that shows the relationship between first trimester maternal fT4 and
neurodevelopmental outcomes. This is potentially because before mid-
gestation, the mother is the only source of thyroid hormone for the
fetus (Morreale de Escobar et al., 2004). Therefore, when evaluating
maternal fT4 as associated with neurodevelopmental outcomes it is
critical to understand the first-trimester levels. Later in gestation,
when the fetal thyroid begins secreting thyroid hormones, maternal fT4
may no longer be a good surrogate for the thyroid hormone levels
available to the fetus. Given that the fetal thyroid has had little
time to develop, its iodine storage is much less than that of an adult,
hence there may be more sensitivity to short-term fluctuations in
iodine availability and uptake that may have little impact on maternal
levels. Therefore, there is some uncertainty about the impact
perchlorate may have on the fetal thyroid gland, and subsequent
neurodevelopmental impacts, in later trimesters of pregnancy. The
immature fetal HPT axis has very limited capacity to increase output of
thyroid hormones (Savin, Cveji[cacute], Nedi[cacute], &
Radosavljevi[cacute], 2003; van Den Hove, Beckers, Devlieger, De
Zegher, & De Nayer, 1999), so the fetal HPT may not be able to adjust
output in the face of reduced maternal fT4 supply and perchlorate
exposure. Therefore, as described above, the EPA selected an
intraspecies UF of 3 to account for the uncertainties in modeling the
impacts of perchlorate ingestion on the thyroid hormone levels for
pregnant mothers with low iodide intake, and the uncertainties in
predicting the neurodevelopmental effects of these thyroid hormone
changes on their children.
The EPA considered but did not derive a Data-Dependent
Extrapolation Factor (DDEF) for this analysis. As described above, the
UFs are applied based on the uncertainties in the perchlorate to
thyroid hormone and thyroid hormone to neurodevelopment
relationship.\11\ As noted above, the Agency has opted to apply a UF of
3 to the POD, which adds an adequate margin of safety to the MCLG
derivation. Section 4.4.5.3 (p. 4-42) of A Review of the RfD & RfC
Processes recommends reducing the intraspecies UF from a default of 10
``only if data are sufficiently representative of the exposure/dose-
response data for the most susceptible subpopulation(s)'' (p. xviii,
USEPA, 2002). The EPA selected a UF of 3 instead of the full 10 because
the modeled groups within the population that are identified as likely
to be at greater risk to perchlorate in drinking water (i.e., the fetus
of the iodide deficient pregnant mother) and has selected model
parameters to account for the most sensitive individuals in that group
(i.e., muted TSH feedback, low fT4 values, low-iodine intake).
---------------------------------------------------------------------------
\11\ As explained in U.S. EPA, 2014 ``UFs incorporate both
extrapolation components that address variability (heterogeneity
between species or within a population) and components that address
uncertainty (i.e., lack of knowledge) . . . whereas DDEFs focus on
variability'' (p. 7, US EPA, 2014).
---------------------------------------------------------------------------
Below we list the other uncertainty factors added and the
justification.
Uncertainty in extrapolating animal data to humans (i.e.,
interspecies uncertainty) (uncertainty factor, animal-to-human,
UFA). For this analysis an UF of 1 is used because this
factor is not applicable since animal studies were
[[Page 30538]]
not used to develop the BBDR model nor were they used to relate
alterations in maternal fT4 to IQ.
Uncertainty in extrapolating data obtained in a study with
less-than-lifetime exposure to lifetime exposure (i.e., extrapolating
from subchronic to chronic exposure, UFS). An uncertainty
factor of 1 is used. Extrapolating from subchronic to chronic exposures
did not occur as the BBDR model was designed to assess long-term
steady-state conditions in the non-pregnant woman and week-to-week
variation in pregnancy, rather than short-term (hour-to-hour or day-to-
day) fluctuations.
Uncertainty in extrapolating from a LOAEL rather than from
a NOAEL (uncertainty factor, LOAEL-to-NOAEL, UFL). A more
sophisticated BBDR modeling approach, coupled with extrapolation to
changes in IQ using linear regression, was used to determine a POD that
would not be expected to represent an adverse effect. Subsequently an
uncertainty factor of 1 is used. LOAELs and NOAELs were not identified
or used in this approach.
Uncertainty factor for database deficiency to address the
potential for deriving an inadequately protective RfD in the instance
where the available database provides an incomplete characterization of
the chemical's toxicity (database deficiency, UFD; USEPA,
2002). An uncertainty factor of 1 is used as ``[t]he mode of action of
perchlorate toxicity is well understood'' (SAB for the U.S. EPA, 2013,
p. 2).
The product of all the uncertainty factors
(UFH) is 3 (3 x 1 x 1 x 1 x 1).
Below we generate RfD's for each of the points of departure.
Using the POD of 6.7 [mu]g/kg/day based on a 2 percent decrease in
the population standardized mean IQ from the EPA's independent analysis
of the Korevaar et al., (2016) data, the EPA can derive a RfD by
incorporating the UFH, which results in the following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.011
Using an alternative POD of 3.1 [mu]g/kg/day based on a 1 percent
decrease in the population standardized mean IQ from the EPA's
independent analysis of the Korevaar et al., (2016) data, the EPA can
derive an RfD by incorporating the UFH. This results in the
following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.012
Using an alternative POD of 10.8 [mu]g/kg/day based on a 3 percent
decrease in the population standardized mean IQ from the EPA's
independent analysis of the Korevaar et al., (2016) data, the EPA can
derive an RfD by incorporating the UFH. This results in the
following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.013
J. Translate RfD Into an MCLG
To translate the RfD ([mu]g/kg/day) to a concentration in drinking
water ([mu]g/L), the EPA used the following equation:
[GRAPHIC] [TIFF OMITTED] TP26JN19.014
Where:
W = drinking water concentration of perchlorate in micrograms per
liter ([mu]g/L);
RfD = reference dose (1.03 [mu]g/kg/day for a 1 percent decrease in
IQ, 2.23 [mu]g/kg/day for a 2 percent decrease in IQ, or 3.6 [mu]g/
kg/day for a 3 percent decrease in IQ);
DWI = bodyweight-adjusted drinking water ingestion rate (L/kg/day);
and
RSCw = relative source contribution of drinking water to
overall perchlorate exposure.
To calculate the MCLGs, the EPA selected the 90th percentile body-
weight adjusted drinking water ingestion rate specific to women of
childbearing age (i.e., non-pregnant, non-lactating, 15-44 years of age
(0.032 L/kg/day). This decision is consistent with the analysis used in
deriving an RSC, which was performed using food consumption information
for a population of women of childbearing age from NHANES. The 90th
percentile is chosen to account for variability in drinking water
ingestion rates, but also adds another layer of health protection for
90% of women (Table III-3).
The EPA did not use water intake data for pregnant women because
the sample sizes were too small to be statistically stable. The use of
the drinking water intake for 15-44 year old women is consistent with
the analysis used in deriving an RSCw (described below),
which was performed using food consumption information for a population
of women of childbearing age from NHANES. The EPA acknowledges there is
a difference in the age range defining women of childbearing age used
to develop the drinking water ingestion rate and that used to develop
the RSC (20-44 years of age). The age range used to develop the
[[Page 30539]]
RSC was based on the range of ages used to define women of childbearing
age in developing the BBDR model. However, the EPA's Exposure Factors
Handbook (USEPA, 2011c) identifies drinking water ingestion rates for
women 15-44 years of age as corresponding to women of childbearing age.
The age range used for women of childbearing age in the BBDR model
fits within the age range used to develop the ingestion rates provided
in the Exposure Factors Handbook. Thus, the Agency believes the
difference in the age ranges will have minimal impact on the resulting
MCLG analysis.
Table III-3--Consumers-Only Estimated Direct and Indirect Community Water Ingestion Rates From Kahn and Stralka
(2008)
[L/kg/day]
----------------------------------------------------------------------------------------------------------------
90th 95th
Female population categories Sample size Mean Percentile Percentile
----------------------------------------------------------------------------------------------------------------
Pregnant........................................ 65 \a\ 0.014 \a\ 0.033 \a\ 0.043
Lactating....................................... 33 \a\ 0.026 \a\ 0.054 \a\ 0.055
Non-pregnant, non-lactating, 15 to 44 years of 2,028 0.015 0.032 0.038
age............................................
----------------------------------------------------------------------------------------------------------------
\a\ The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (FASEB/LSRO, 1995).
Individuals are exposed to perchlorate through ingestion of both
food and drinking water (ATSDR 2008, Huber et al., 2011). In
calculating the MCLGs, the EPA applies a relative source contribution
(RSC) to the RfD to account for the percentage of the RfD remaining for
drinking water after other sources of exposure to perchlorate have been
considered. Thus, the RSC for drinking water is based on the following
equation where ``Food'' is the perchlorate dose from food ingestion:
[GRAPHIC] [TIFF OMITTED] TP26JN19.015
To estimate the dose of perchlorate for women of childbearing age
coming from food, the EPA implemented a data integration methodology
that combined demographic variables, food consumption estimates, and
perchlorate contamination estimates in food from multiple sources
(USEPA, 2019c). These sources include:
The NHANES data available from the Centers for Disease
Control and Prevention's (CDC) National Center for Health Statistics
(NCHS) including the What We Eat in America (WWEIA) 24-hour food diary
data (CDC & NCHS, 2007, 2009, 2011); and
The Food and Drug Administration's (FDA's) Total Diet
Study (TDS) (U.S. Food and Drug Administration (FDA), 2015), which
analyzes contaminants in about 280 kinds of food and beverages commonly
consumed by the U.S. population.
The NHANES data provided individual food consumption profiles for
female participants age 20-44 (the women of childbearing age range used
for the BBDR model). The EPA matched TDS perchlorate concentrations
with each food consumed by a participant and calculated each
participant's daily perchlorate dose ([mu]g/kg/day) from food using the
participant's body weight. The EPA estimated each participant's
perchlorate dose using both mean and 95th percentile perchlorate
concentrations in food. The details of these assumptions are explained
on page 5-5 of the Technical Support Document: Deriving a Maximum
Contaminant Level Goal for Perchlorate in Drinking Water (USEPA 2019c).
Specifically, the EPA calculated both the mean and the 95th percentile
of the perchlorate levels in each food based on the 20 samples included
in the TDS data. In order to estimate the 95th percentile from the 20
samples, the EPA used the second-highest test result for each food to
represent the 95th percentile concentration. While simple, this method
avoids the need to assume a distributional shape for the samples, and
has been used in recent publications of TDS data for iodine (Carriquiry
et al., 2016). The aforementioned method for identifying the 95th
percentile concentration of perchlorate from food was selected over
other, more ``statistically based'' methods for estimating percentiles
as it avoids the need to assume a distributional shape for the samples.
The EPA determined that it was more reliable to assume the empirically
derived distribution as the basis for selecting the 95th percentile
(i.e., assuming the distribution was equal to the distribution of
samples collected in the TDS), as opposed to forcing a distributional
shape, such as normal or log-normal, onto the data that may not
necessarily be appropriate. With the chosen method, we can at least be
sure that the distributional shape is appropriate for the data at hand,
whereas by choosing the alternative that assumes a distributional
shape, in many instances we would not even be certain of that. The EPA
used these individual bodyweight-adjusted perchlorate doses from food
to calculate distributions of perchlorate dose from food for the
population of women age 20-44.
Table III-4 presents the mean and selected percentiles of the
distribution of perchlorate dose from food for women ages 20-44, for
both mean and 95th percentile perchlorate concentrations in food based
on the TDS. To calculate the RSC, the EPA selected the 90th percentile
dose of perchlorate from food, assuming a scenario where the food
contained the 95th percentile perchlorate concentration. This
corresponds to a perchlorate dose for food of 0.45 [mu]g/kg/day. The
EPA chose to use the 90th percentile bodyweight-adjusted perchlorate
consumption from food using the 95th percentile TDS results to estimate
the perchlorate RSC from drinking water. The EPA believes this is the
most appropriate value for perchlorate consumption from food to ensure
the protection of potentially highly exposed individuals. Given the
range of perchlorate concentrations in food, and that food is the only
other exposure source being considered in the RSC analysis, the EPA
believes it is sufficiently protective to estimate the MCLG for
drinking water using the 90th percentile bodyweight-adjusted
perchlorate consumption based on the 95th percentile perchlorate food
concentrations in TDS. This assures that highly exposed individuals
from this most sensitive population are considered in the evaluation of
whether perchlorate is found at levels of health concern.
[[Page 30540]]
Table III-4--Perchlorate Dose From Food ([mu]g/kg/day) in U.S. Women Ages 20-44 Using the Mean and 95th
Percentile TDS Results \1\
----------------------------------------------------------------------------------------------------------------
Perchlorate dose from food ([mu]g/kg/day)
---------------------------------------------
Level of bodyweight adjusted perchlorate consumption from Based on 95th
population distribution Based on mean percentile
concentrations of concentrations of
perchlorate in food perchlorate in food
----------------------------------------------------------------------------------------------------------------
Mean.............................................................. 0.09-0.12 0.23-0.24
50th Percentile................................................... 0.08-0.10 0.17-0.19
90th Percentile................................................... 0.18-0.21 0.45
99th Percentile................................................... 0.33-0.38 1.16-1.17
----------------------------------------------------------------------------------------------------------------
\1\ Ranges are due to various approaches for handling values level of detection. If no range is presented all
approaches resulted in the same value.
Bolded value represents the selected value.
The EPA used the drinking water intake and perchlorate dose from
food to calculate MCLGs for the three RfD values. Table III-5 shows the
RSC values for the three RfD values and the corresponding MCLGs
calculated using the EPA's standard equation.
[GRAPHIC] [TIFF OMITTED] TP26JN19.016
IV. Maximum Contaminant Level Goal and Alternatives
Section 1412(a)(3) of the SDWA requires the EPA to propose a
maximum contaminant level goal (MCLG) simultaneously with the NPDWR.
The MCLG is defined in Section 1412(b)(4)(A) as ``the level at which no
known or anticipated adverse effects on the health of persons occurs
and which allows an adequate margin of safety.'' The EPA is proposing
an MCLG of 56 [mu]g/L based on the rationale and methology described in
Section III above. The derivation of the proposed MCLG uses a point of
departure based upon a two percent decrease in IQ for offspring of
hypothyroxinemic women of child bearing age have with low iodine
intake. The EPA selected a 2 percent decrease in IQ for the proposed
[[Page 30541]]
perchlorate MCLG because this represents a small change in IQ, well
below one standard deviation for the subpopulation of interest.
As described in Section III, the EPA has selected model parameters
and other factors for the derivation of the MCLG that are health
protective, including the focus on the most sensitive life stage. The
EPA believes that the selection of the combination of protective
parameters and this point of departure assures no known or anticipated
adverse effects on the health of the most sensitive subpopulation and
allows for an adequate margin of safety. The EPA also acknowledges the
uncertainties in the derivation of the proposed (and alternative)
MCLGs. The EPA acknowledges in particular the challenge associated with
selecting the decrement of IQ that represents an adverse effect at the
population level and the uncertainties in predicting the dose of
perchlorate that may result in a particular IQ decrement given the
absence of robust human epidemiological data directly linking
perchlorate exposure to IQ decrements. The Agency seeks comment on the
alternative MCLG values of 18 [mu]g/L and 90 [mu]g/L, which the EPA
derived using the methodology described in Section III based on a one
percent and three percent decrease in IQ, respectively.
V. Maximum Contaminant Level and Alternatives
Under section 1412(b)(4)(B) of the SDWA, the EPA must establish a
maximum contaminant level (MCL) as close to the MCLG as is feasible.
The EPA evaluated available analytical methods to determine the lowest
concentration at which perchlorate can be measured and evaluated the
treatment technologies for perchlorate that have been examined under
field conditions (USEPA 2018a, 2019b). The EPA determined that setting
an MCL equal to the proposed MCLG of 56 [mu]g/L is feasible given that
the approved analytical method for perchlorate for UCMR 1 has a minimum
reporting level (MRL) of 4 [mu]g/L (USEPA 1999, 2000c) and that
available treatment technologies can treat to concentrations well below
56 [mu]g/L (USEPA, 2018c). Therefore, the EPA is proposing to set the
MCL for perchlorate at 56 [mu]g/L.
Because the EPA is taking comment on alternative MCLG values of 18
[mu]g/L and 90 [mu]g/L the Agency evaluated the feasibility of setting
an MCL at these levels. The EPA determined that the proposed MCL of 56
[mu]g/L is feasible, therefore a higher MCL alternative such as 90
[mu]g/L is also feasible. The EPA has concluded that analytical methods
are capable of measuring perchlorate at 18 [mu]g/L and that treatment
technologies have been demonstrated to achieve this level under field
conditions (USEPA 2018a, 2019b). Therefore, the EPA is requesting
comment on the feasibility of the proposed MCL of 56 [mu]g/L as well as
the feasibility of the alternative MCLs of 18 [mu]g/L and 90 [mu]g/L.
As the occurrence analysis in section VI demonstrates, there is
infrequent occurrence of perchlorate at 18 [mu]g/L, 56 [mu]g/L, or 90
[mu]g/L. Therefore, the EPA did not evaluate alternative MCL values
greater than the corresponding MCLG values. The purpose for evaluating
alternative MCL values is to determine whether there is an MCL at which
benefits justify the costs of setting an MCL. Given infrequent
occurrence, the majority of the costs associated with establishing an
NPDWR for perchlorate are for administrative and initial monitoring
activities (see section XI.B), which will not be significantly affected
by MCL values greater than corresponding MCLG values.
When proposing an MCL, the EPA must publish, and seek public
comment on, the health risk reduction and cost analyses (HRRCA) of each
alternative MCL considered (SDWA Section 1412(b)(3)(C)(i)), including:
The quantifiable and nonquantifiable health risk reduction benefits
attributable to MCL compliance; the quantifiable and nonquantifiable
health risk reduction benefits of reduced exposure to co-occurring
contaminants attributable to MCL compliance; the quantifiable and
nonquantifiable costs of MCL compliance; the incremental costs and
benefits of each alternative MCL; the effects of the contaminant on the
general population and sensitive subpopulations likely to be at greater
risk of exposure; any adverse health risks posed by compliance; and
other factors such as data quality and uncertainty. The EPA provides
this information in section XII in this preamble. The EPA must base its
action on the best available, peer-reviewed science and supporting
studies, taking into consideration the quality of the information and
the uncertainties in the benefit-cost analysis (SDWA Section
1412(b)(3)). The following sections, as well as the health effects
discussion in section III document the science and studies that the EPA
relied upon to develop estimates of benefits and costs and understand
the impact of uncertainty on the Agency's analysis.
VI. Occurrence
The UCMR 1 is the primary source of occurrence data the EPA relied
on to estimate the number of water systems (and associated population)
expected to be exposed at levels of perchlorate which could potentially
exceed the proposed and alternative MCL levels. Since UCMR 1 data was
first used to inform the Agency actions on the 2008 preliminary
regulatory determination and the 2011 final regulatory determination,
the Agency has modified its analysis of the UCMR 1 data set in response
to concerns raised by stakeholders regarding the data quality and to
represent current conditions at some States that have enacted
perchlorate regulations since the UCMR 1 data was collected. Despite
these updates, the EPA continues to rely on the UCMR 1 data because
they are the best available data collected in accordance with accepted
methods from a census of the large water systems (serving more than
10,000 people) and a statistically representative sample of small water
systems that provides the best available, national assessment of
perchlorate occurrence in drinking water.
In 1999, the EPA developed the first round of the UCMR program in
accordance with SDWA requirements to provide national occurrence
information on unregulated contaminants (USEPA, 1999, 2000b). The UCMR
1 required sampling from systems in all 50 States, the District of
Columbia, four U.S. territories, and tribal lands in five EPA Regions
including:
All 3,097 large (serving more than 10,000 people) CWSs and
NTNCWSs, which analyzed either four quarterly samples collected at 3-
month intervals (surface water sources), or two samples collected 5 to
7 months apart (ground water sources); and
a statistically representative selection of 800 small CWSs
and NTNCWSs, which analyzed either four quarterly samples collected at
3-month intervals (surface water sources) or two samples collected 5 to
7 months apart (ground water sources).
Water systems submitted UCMR 1 sampling results to the EPA from
2001 until 2005. Water systems were required to analyze samples for 26
contaminants including perchlorate. The EPA established a minimum
reporting level of 4 [mu]g/L for perchlorate in the UCMR.
The EPA conducted a data quality review of the UCMR 1 data
submitted by systems prior to analyzing the occurrence data for the
2011 perchlorate regulatory determination. The UCMR 1 dataset used by
the EPA included 34,331 samples with 637 measurements of perchlorate
above the minimum reporting level from 3,865 systems.
In September of 2012, the EPA received a ``Request for Correction''
[[Page 30542]]
letter from the United States Chamber of Commerce regarding information
and data (i.e., the occurrence of perchlorate in drinking water) used
by the EPA in its 2011 determination to regulate perchlorate. The U.S.
Chamber of Commerce letter stated that the EPA relied upon: (1) Data
that did not comply with data quality guidelines and (2) data that was
not representative of current conditions.
In response \12\ to the U.S. Chamber of Commerce, the EPA conducted
a detailed assessment of the source water sample detections and
determined that it was most appropriate to exclude the source water
sample detections from the UCMR 1 perchlorate data set when those
samples had appropriate follow-up entry point samples that were
included in the UCMR 1 perchlorate data set. In contrast, any source
water sample perchlorate detections for which no follow-up entry point
sampling was conducted by PWSs were retained in the UCMR 1 perchlorate
data set. As a result of the assessment, the EPA removed 199 source
water samples (97 detections) that could be paired with a second
follow-up sample located at the entry point to the distribution system.
Following this convention, the resulting UCMR 1 data set contains
34,132 perchlorate samples from 3,865 systems with a total of 540
detections from 149 PWSs.
---------------------------------------------------------------------------
\12\ See the EPA response letter at https://www.epa.gov/sites/production/files/2017-08/documents/12004-response_0.pdf.
---------------------------------------------------------------------------
Table VI-1 shows sample distribution by system size category and
measurement status. It also shows the number of entry points and
systems where perchlorate measurements were reported. The entry point
estimates differ from the system estimates because many water systems
have more than one entry point. For example, a ground water system with
two wells that has separate connections to the distribution system has
two entry points.
In response to the U.S. Chamber of Commerce request, the EPA has
also reassessed the UCMR 1 data in light of the adoption of regulatory
limits in two states. Massachusetts promulgated a drinking water
standard for perchlorate of 2 [mu]g/L in 2006 (MassDEP, 2006), and
California promulgated a drinking water standard of 6 [mu]g/L in 2007
(California Department of Public Health, 2007). Systems in these states
are now required to keep perchlorate levels in drinking water below
their state limits, which are lower than the proposed MCL and
alternative MCLs. Therefore, the UCMR 1 sampling results from systems
in these states do not reflect the current occurrence and exposure
conditions. For the purpose of estimating the costs and benefits of the
proposed rule, the EPA assumed that no additional monitoring and
treatment costs would be incurred by the systems in the States of
California and Massachusetts. Systems in California account for some of
the perchlorate measurements reported below. The notes in the tables
below indicate whether results include or exclude systems in California
and Massachusetts.
To update the occurrence data for systems sampled during UCMR 1
from the States of California and Massachusetts, the EPA identified all
systems and corresponding entry points which had reported perchlorate
detections in UCMR 1. Once the systems and entry points with detections
were appropriately identified, the EPA then used a combination of
available data from Consumer Confidence Reports (CCRs) and perchlorate
compliance monitoring data from California (https://sdwis.waterboards.ca.gov/PDWW/) and Massachusetts (https://www.mass.gov/service-details/public-water-supplier-document-search) to
match current compliance monitoring data (where available) to the
corresponding water systems and entry points sampled during UCMR 1.
Out of the 540 detections previously described the EPA updated data
for 321 detections (320 from California systems and 1 from a
Massachusetts system). The convention used by the EPA to accomplish the
substitution of data was to match entry points with compliance data for
active entry points based on most recently reported compliance
monitoring data, if more than one data point was reported for an entry
point, the assigned value is an average of the annual monitoring
results at the entry point. In cases were the EPA could not find
updated entry point data, then the original data from UCMR 1 for such
entry point was kept.
Table VI-1--UCMR 1 Data Summary Statistics
----------------------------------------------------------------------------------------------------------------
Small system Large system
Item sample census Sum
----------------------------------------------------------------------------------------------------------------
Total samples................................................... 3,295 30,837 34,132
Sample measurements >=4 [mu]g/L............................. 15 525 540
Sample measurements >18 [mu]g/L............................. 1 16 17
Sample measurements >56 [mu]g/L............................. 0 2 2
Sample measurements >90 [mu]g/L............................. 0 1 1
Total entry points.............................................. 1,454 13,482 14,936
Entry points at which measurements >=4 [mu]g/L.............. 8 328 336
Entry points at which measurements >18 [mu]g/L.............. 1 16 17
Entry points at which measurements >56 [mu]g/L.............. 0 2 2
Entry points at which measurements >90 [mu]g/L.............. 0 1 1
Total systems................................................... 797 3,068 3,865
Systems at which measurements >=4 [mu]g/L................... 8 141 149
Systems at which measurements >18 [mu]g/L................... 1 14 15
Systems at which measurements >56 [mu]g/L................... 0 2 2
Systems at which measurements >90 [mu]g/L................... 0 1 1
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b). The total row counts and counts of measurements >=4 [mu]g/L identify all instances where
perchlorate was detected at or above the minimum reporting level, including water systems in California and
Massachusetts, which account for 537 systems in total and 51 systems at which measurements >=4 [mu]g/L. The
instances where perchlorate measurements equal or exceed either 18 [mu]g/L, 56 [mu]g/L, or 90 [mu]g/L exclude
results from California and Massachusetts because water systems in these States must meet limits below 18
[mu]g/L. The small system counts reflect sample results that have not been extrapolated to small systems
nationwide.
[[Page 30543]]
Table VI-2 shows the service populations that correspond with the
occurrence summary in Table VI-1. The entry point population estimates
reflect the assumption that system population is uniformly distributed
across entry points; e.g., the entry point population for a system with
two entry points is one-half the total system population.
Table VI-2--UCMR1 Data Service Population Summary Statistics
----------------------------------------------------------------------------------------------------------------
Small system Large system
Item sample census Sum
----------------------------------------------------------------------------------------------------------------
Total entry point population.................................... 2,760,570 222,853,101 225,613,671
Population served by entry points at which measurements >=4 9,484 4,281,937 4,291,420
[micro]g/L.................................................
Population served by entry points at which measurements >18 2,155 618,406 620,560
[micro]g/L.................................................
Population served by entry points at which measurements >56 0 32,432 32,432
[micro]g/L.................................................
Population served by entry points at which measurements >90 0 25,972 25,972
[micro]g/L.................................................
Total system population......................................... 2,760,570 222,853,101 225,613,671
Population served by systems at which measurements >=4 13,483 16,159,082 16,172,565
[micro]g/L.................................................
Population served by systems at which measurements >18 4,309 696,871 701,180
[micro]g/L.................................................
Population served by systems at which measurements >56 0 64,733 64,733
[micro]g/L.................................................
Population served by systems at which measurements >90 0 25,972 25,972
[micro]g/L.................................................
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b). The populations for entry points/systems with measurements >=4 [micro]g/L identify all
instances where perchlorate was detected at or above the minimum reporting level, including water systems in
California and Massachusetts, which account for 39.6 million of the 225.6 million total population in UCMR 1,
and 1.9 million of the 4.3 million population served by entry points at which measurements >=4 [micro]g/L. The
instances where perchlorate measurements equal or exceed either 18 [micro]g/L, 56 [micro]g/L, or 90 [micro]g/L
exclude results from California and Massachusetts because water systems in these States must meet limits below
18 [micro]g/L. The small system counts reflect sample results that have not been extrapolated to small systems
nationwide.
As shown in the tables, 149 systems serving 16.2 million people had
measured levels of perchlorate greater than the minimum reporting
level. However, many of these systems have several entry points with no
measured levels of perchlorate greater than the minimum reporting
level; at the entry point level, the exposed population is
approximately 4.3 million people served by 336 entry points. Because
the uniform population distribution assumption may over or
underestimate the service population of any particular entry point, the
entry point estimates are uncertain. The system population estimates
serve as upper bounds on exposure.
The EPA used entry point maximum measurements to estimate potential
baseline occurrence and exposure at levels that exceed the proposed MCL
and alternative MCLs. The maximum measurements indicate perchlorate
levels that occurred in at least one quarterly sample among surface
water systems and at least one semi-annual sample among ground water
systems.
Table VI-3 through Table VI-5 show the occurrence and exposure
estimates based on the 56 [micro]g/L, 18 [micro]g/L MCL, and 90
[micro]g/L values, respectively. Each table provides estimates of the
entry points at which the maximum perchlorate concentrations exceed the
MCL value. The tables also report the system-level information for
these entry points.
Table VI-3--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 56 [micro]g/L
----------------------------------------------------------------------------------------------------------------
Affected entity Small systems Large systems Total systems
----------------------------------------------------------------------------------------------------------------
Entry points.................................................... 0 2 2
Population served............................................... 0 32,432 32,432
Water systems................................................... 0 2 2
Population served............................................... 0 64,733 64,733
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).
Table VI-4--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 18 [micro]g/L
----------------------------------------------------------------------------------------------------------------
Small systems
Affected entity \1\ Large systems Total systems
----------------------------------------------------------------------------------------------------------------
Entry points.................................................... 1 16 17
Population served............................................... 2,155 618,406 620,560
Water systems................................................... 1 14 15
Population served............................................... 4,309 696,871 701,180
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).
\1\ The values shown in the table are estimates based on the UCMR 1 data. The EPA also applied the statistical
sampling weights to the results to extrapolate results to national results. The entry point at which a
measurement exceeds 18 [micro]g/L is one of 20 in its sample stratum; no other sample in the stratum had a
measurement of perchlorate greater than the minimum reporting level. The entry point population of 2,155
represents 5.31% of the total population served by the six UCMR 1 systems in the stratum (40,574). Currently,
the stratum population of 774,780 accounts for 1.32% of the 58.7 million national population served by small
systems. Thus, the UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of small system customers (approximately
41,100) may be exposed to perchlorate greater than 18 [micro]g/L.
[[Page 30544]]
Table VI-5--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 90 [micro]g/L
----------------------------------------------------------------------------------------------------------------
Small systems
Affected entity \1\ Large systems Total systems
----------------------------------------------------------------------------------------------------------------
Entry points.................................................... 0 1 1
Population served............................................... 0 25,972 25,972
Water systems................................................... 0 1 1
Population served............................................... 0 25,972 25,972
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).
In summary, the perchlorate occurrence information suggests that at
an MCL of 56 [micro]g/L, two systems (0.004% of all water systems in
the U.S.) would exceed the regulatory threshold. One of these two
systems would exceed the alternative MCL of 90 [micro]g/L. In addition,
at an MCL of 18 [micro]g/L, there would be 15 systems (0.03% of all
water systems in the U.S.) that would exceed the regulatory threshold.
VII. Analytical Methods
The SDWA directs the EPA to set a contaminant's MCL as close to its
MCLG as is ``feasible'', the definition of which includes an evaluation
of the feasibility of performing chemical analysis of the contaminant
at standard drinking water laboratories. Specifically, the SDWA directs
the EPA to determine that it is economically and technologically
feasible to ascertain the level of the contaminant being regulated in
water in public water systems (Section 1401(1)(C)(i)). NPDWRs are also
to contain ``criteria and procedures to assure a supply of drinking
water which dependably complies with such [MCLs]; including accepted
methods for quality control and testing procedures to insure compliance
with such levels.'' (Section 1401(1)(D)).
To comply with these requirements, the EPA considers method
performance under relevant laboratory conditions, their likely
prevalence in certified drinking water laboratories, and the associated
analytical costs. The EPA has developed five analytical methods for the
identification and quantification of perchlorate in drinking water that
meet these criteria. The proposed EPA methods for perchlorate are:
314.0, 314.1, 314.2, 331.0, and 332.0. A detailed description of these
methods is presented in the Perchlorate Occurrence and Monitoring
Report (USEPA, 2019b).
The EPA Methods 314.0, 314.1, 314.2, 331.0, and 332.0 underwent the
EPA's analytical method development and validation processes. The
validation process includes a protocol for modifications to any
existing EPA-approved analytical methods and a protocol for new
determinative techniques. Both validation protocols are rigorous and
consider many technical aspects of analytical method performance,
including: Detection limits; instrument calibration; precision and
analyte recovery; analyte retention times; evaluation of blanks;
development of Quality Control acceptance criteria; analysis of field
samples; and other technical aspects of sample analysis and data
reporting. All of the proposed EPA analytical methods provide
performance data to demonstrate their capability to reliably and
consistently measure perchlorate in drinking water at the proposed and
alternate MCLs.
EPA Method 314.0, ``Determination of Perchlorate in Drinking Water
Using Ion Chromatography'' (Revision 1.0, USEPA, 1999a) has a method
detection limit (MDL) of 0.53 [micro]g/L. Single-laboratory mean
percent recovery in various aqueous matrices range from 86% to 113%
with Relative Standard Deviations (RSDs) of 1.0% to 12.8%. A minimum
reporting level (MRL) is not specified in the method; however, a range
of 3.0 to 5.0 [micro]g/L is cited as a benchmark range for quality
assurance/quality control (QA/QC) procedures. The MRL is to be
established as either a concentration that is greater than three times
the laboratory MDL or at a concentration that yields a response greater
than a signal to noise ratio of five. In either case, the MRL must not
be below the lowest instrument calibration standard (USEPA, 1999a).
Method 314.0 was widely adopted as the standard perchlorate method.
After the EPA published Method 314.0, the Agency adopted additional
method development goals for the analysis of perchlorate in drinking
water including: (1) Reducing MRL to less than 1 [micro]g/L through the
application of sample concentration techniques, microbore analytical
columns, and advanced detection systems (i.e., mass spectrometry), (2)
further increasing the tolerance for high ionic strength matrices, and
(3) enhancing measurement selectivity.
EPA Method 314.1, ``Determination of Perchlorate in Drinking Water
Using Inline Column Concentration/Matrix Elimination Ion Chromatography
with Suppressed Conductivity Detection'' (Revision 1.0, USEPA, 2005b)
documents the EPA single-laboratory Lowest Concentration Minimum
Reporting Levels (LCMRLs) of less than 0.2 [micro]g/L (DL = 0.03
[micro]g/L) using online sample pre-concentration. The method uses
matrix diversion to handle high ionic strength matrices (up to 1,000
mg/L TDS) and added confirmation analysis using a second analytical
column (USEPA, 2005b).
EPA Method 314.2, ``Determination of Perchlorate in Drinking Water
Using Two-Dimensional Ion Chromatography with Suppressed Conductivity
Detection'' (USEPA, 2008c) documents the EPA single-laboratory LCMRLs
of less than 0.1 [micro]g/L (DLs <0.02 [micro]g/L) using large volume
injection. The method uses 2-D chromatography to handle high ionic
strength matrices (up to 1,000 mg/L total dissolved solids [TDS]) and
eliminates the need for separate confirmation analysis (USEPA, 2008c).
EPA Method 331.0, ``Determination of Perchlorate in Drinking Water
by Liquid Chromatography Electrospray Ionization Mass Spectrometry''
(Revision 1.0, USEPA, 2005c) documents the EPA single-laboratory LCMRLs
of less than 0.1 [micro]g/L (DLs <0.01 [micro]g/L), applied multiple
analytical advancements to a liquid chromatography (LC) analysis
including a perchlorate selective LC column (AS-21), mass spectrometry
(MS) or MS/MS detection for selectivity and sensitivity, and a custom
labeled internal standard (Cl\18\O4-) (USEPA,
2005c).
EPA Method 332.0, ``Determination of Perchlorate in Drinking Water
by Ion Chromatography with Suppressed Conductivity and Electrospray
Ionization Mass Spectrometry'' (USEPA, Revision 1.0, 2005d) documents
the EPA single-laboratory LCMRL of 0.1 [micro]g/L (DL = 0.02 [micro]g/
L), applied multiple analytical advancements in an IC analysis
including suppressed conductivity IC, MS or MS/MS selectivity and
sensitivity, and a custom labeled internal standard
(Cl\18\O4) (USEPA, 2005d).
[[Page 30545]]
VIII. Monitoring and Compliance Requirements
A. What are the proposed monitoring requirements?
The EPA is proposing to require CWS and NTNCWSs to monitor for
perchlorate in accordance with the standardized monitoring framework
set out in 40 CFR 141 Subpart C (Standardized Monitoring Framework).
Public water systems must sample entry points to the distribution
system consistent with requirements in 40 CFR 141.23(a).
Under the Standardized Monitoring Framework, the monitoring
frequency for a public water system is dependent on previous monitoring
results and whether a monitoring waiver has been granted. The EPA is
proposing that consistent with the standardized monitoring framework
water systems would be initially required to monitor quarterly for
perchlorate. The EPA is also proposing that based upon the monitoring
results States would be able to reduce the monitoring frequency to
annually, once every three years or once every nine years if the State
concludes that the system is reliably and consistently below the MCL.
If a water system exceeds the perchlorate MCL, the system is in
violation and triggered into quarterly monitoring for that sampling
point in the next quarter after the violation occurred (40 CFR
141.23(c)(7)). The state may allow the system to return to the reduced
monitoring frequency when the state determines that the system is
reliably and consistently below the MCL. However, the state cannot make
a determination that the system is reliably and consistently below the
MCL until a minimum of 2 consecutive ground water or 4 consecutive
surface water samples below the MCL have been collected (40 CFR
141.23(c)(8)). All systems must comply with the sampling requirements,
unless a waiver has been granted in writing by the state (40 CFR
141.23(c)(6)).
B. Can states grant monitoring waivers?
Under this proposal, water systems may apply to the state, and
states may grant, a 9-year monitoring waiver for perchlorate if the
conditions described in 40 CFR 141.23(c)(3)-(6) are met. A state may
grant a waiver for surface water systems after three rounds of annual
monitoring with results less than the MCL and for groundwater systems
after conducting three rounds of monitoring with results less than the
MCL. One sample must be collected during the nine-year compliance cycle
that the waiver is effective, and the waiver must be renewed every nine
years.
C. How are system MCL violations determined?
Under this proposal, violations of the perchlorate MCL would be
determined in a manner consistent with 40 CFR 141.23(i)(3). Compliance
with the perchlorate MCL would be determined based on one sample if the
level is below the MCL. If the level of perchlorate exceeds the MCL at
any entry point in the initial sample, a confirmation sample is
required within two weeks of the system's receipt of notification of
the analytical result of the first sample, in accordance with
141.23(f)(1). Compliance shall be determined based on the average of
the initial and confirmation samples.
D. When must systems complete initial monitoring?
Pursuant to Section 1412(b)(10), this rule would be effective three
years after promulgation. To satisfy initial monitoring requirements,
CWS serving populations greater than 10,000 persons must collect 4
quarterly samples for perchlorate during the second compliance period
of the fourth compliance cycle (January 1, 2023- December 31, 2025) of
the Standardized Monitoring Framework. NTNCWS and CWSs serving 10,000
persons or less must collect 4 quarterly samples during the third
compliance period of the fourth compliance cycle (January 1, 2026-
December 31, 2028) of the Standardized Monitoring Framework.
E. Can systems use grandfathered data to satisfy the initial monitoring
requirements?
As proposed today, systems would be allowed to use grandfathered
perchlorate data collected after January 1, 2020, to satisfy the
initial monitoring requirements. To satisfy initial perchlorate
monitoring requirements, a system with appropriate historical
monitoring data for each entry point to the distribution system could
use the monitoring data from the compliance monitoring period between
January 1, 2020, and December 31, 2022, for CWSs serving greater than
10,000 persons and between January 1, 2023, and December 31, 2025, for
NTNCWs and for CWSs serving 10,000 or fewer persons.
IX. Safe Drinking Water Act Right to Know Requirements
A. What are the Consumer Confidence Report requirements?
A community water system must prepare and deliver to its customers
an annual Consumer Confidence Report (CCR) in accordance with
requirements in 40 CFR 141 Subpart O. A CCR provides customers with
information about their local drinking water quality as well as
information regarding the water system compliance with drinking water
regulations. Under this proposal CWSs would be required to report
perchlorate information in their CCR.
B. What are the public notification requirements?
All public water systems must give the public notice for all
violations of NPDWRs and for other situations. Under this proposal,
violations of the perchlorate MCL would be designated as Tier 1 and as
such, public water systems would be required to comply with 40 CFR
141.202. As described in Section III of this proposal, fetuses of first
trimester pregnant women with low iodine are the most sensitive
subpopulation, therefore, per 40 CFR 141.202(b)(1), notification of an
MCL violation should be provided as soon as practicable but no later
than 24 hours after the system learns of the violation under this
proposal.
X. Treatment Technologies
Systems that exceed the perchlorate MCL will need to adopt new
treatment or another strategy to reduce perchlorate to a level that
meets the MCL. When the EPA establishes an MCL for a drinking water
contaminant, Section 1412(b)(4)(E) of the SDWA requires that the Agency
``list the technology, treatment techniques, and other means which the
Administrator finds to be feasible for purposes of meeting [the MCL],''
which are referred to as best available technologies (BAT). These BATs
are used by states to establish conditions for source water variances
under Section 1415(a). Furthermore, Section 1412(b)(4)(E)(ii) requires
that the Agency identify small system compliance technologies (SSCT),
which are affordable treatment technologies, or other means that can
achieve compliance with the MCL (or treatment technique, where
applicable). The lack of an affordable SSCT for a contaminant triggers
certain additional procedures which can result in states issuing small
system variances under Section 1412(e) of the SDWA.
The Agency solicits public comment on the choice of available
treatment technologies discussed in this section.
A. What are the best available technologies?
The Agency identifies the best available technologies (BAT) as
those meeting the following criteria: (1) The capability of a high
removal efficiency;
[[Page 30546]]
(2) a history of full-scale operation; (3) general geographic
applicability; (4) reasonable cost based on large and metropolitan
water systems; (5) reasonable service life; (6) compatibility with
other water treatment processes; and (7) the ability to bring all of
the water in a system into compliance. The Agency is proposing the
following technologies as BAT for removal of perchlorate from drinking
water based its review of the treatment and cost literature (USEPA,
2018a):
Ion exchange;
biological treatment; and
centralized reverse osmosis.
There are also non-treatment options that might be used for
compliance in lieu of installing and operating treatment technologies.
These include blending existing water sources, replacing a perchlorate-
contaminated source of drinking water with a new source (e.g., a new
well), and purchasing compliant water from another system. Below are
brief descriptions of each proposed BAT.
Ion Exchange
Ion exchange is a physical and chemical separation process that can
achieve high perchlorate removal rates. Feed water passes through a
vessel containing a bed of resin made of synthetic beads or gel. As
feed water moves through the resin, an ionic contaminant such as
perchlorate exchanges for an ion (typically chloride) on the resin.
Demonstrated removal efficiencies for perchlorate are typically in the
high 90 percent range and can achieve concentrations less than 4
[micro]g/L in treated water (Drago & Leserman, 2011; Membrane
Technology, 2006; Siemens Water Technologies, 2009; The Interstate
Technology & Regulatory Council (ITRC) Team, 2008). The operation
continues until enough of the resin's available ion exchange sites have
ions from the feed water and the resin no longer effectively removes
the target contaminant, i.e., the contaminant ``breaks through'' the
treatment process. At this point, the resin must be disposed and
replaced or regenerated. The length of time until resin must be
replaced or regenerated is known as bed life and is a critical factor
in the cost effectiveness of ion exchange as a treatment technology.
One measurement of bed life is the volume of water that can be treated
before breakthrough--called bed volumes--the number of times the resin
bed can be filled before breakthrough. Several factors affect bed life,
including the presence of competing ions such as nitrate and the type
of resin used. Resin types tested for perchlorate removal include
strong-base polyacrylic, strong-base polystyrenic (including nitrate-
selective), weak-base polyacrylic, weak-base polystyrenic, and
perchlorate-selective. Based on studies of the effect of competing ions
on performance, perchlorate-selective resins can achieve bed lives
ranging from 105,000 to 170,000 bed volumes (Blute, Seidel, McGuire,
Qin, & Byerrum, 2006; Russell, Qin, Blute, McGuire, & Williams, 2008;
Wu & Blute, 2010).
Perchlorate-selective resin cannot be easily regenerated for reuse;
the exhausted resin must be disposed (i.e., operated on a `throw-away'
basis). This mode of operation, however, avoids the production of
liquid residuals in the form of spent regenerant. Therefore, in
combination with the long bed life, single-use perchlorate-selective
ion exchange can be a cost-effective treatment option in spite of the
need to dispose of the perchlorate-contaminated resin. Build-up of
arsenic or uranium on the resin may affect waste disposal options,
although studies of perchlorate-selective resins show that arsenic
concentrations remain below regulatory limits for hazardous waste
disposal and uranium concentrations generally remain below those that
require special handling as radioactive waste (Blute et al., 2006;
Russell et al., 2008; Wu & Blute, 2010). Ion exchange can increase the
corrosivity of treated water (Berlien, 2003; Betts, 1998; USEPA, 2005b)
because of the addition of chloride ions and/or removal of carbonates
and bicarbonates. Such instances can be addressed by adding or
adjusting corrosion control.
Biological Treatment
Biological treatment uses bacteria to reduce perchlorate to
chlorate, chlorite, chloride, and oxygen. Biological treatment can
destroy the perchlorate ion, eliminating the need for management of
perchlorate-bearing waste streams. Removal effectiveness exceeds 90
percent for bench-scale tests and full-scale treatment plant studies
(Kotlarz, Upadhyaya, Togna, & Raskin, 2016; Upadhyaya, Kotlarz, Togna,
& Raskin, 2015; U.S. Department of Defense (U.S. DoD), 2008, 2009; T.D.
Webster & Crowley, 2010, 2016; T.D. Webster & Litchfield, 2017).
Although biological treatment is a relatively new technology for
treatment of drinking water in the United States, the State of
California has identified biological treatment (along with ion
exchange) as one of two best available technologies for achieving
compliance with its standard for perchlorate in drinking water
(California Code of Regulations, Title 22, Chapter 15, Section
64447.2). The California BAT specifies a fluidized bed, although
studies suggest that a fixed bed is also effective. The first full-
scale fluidized bed facility using biological treatment of perchlorate
to supply municipal drinking water began operation in 2016 (T. D.
Webster & Crowley, 2016; T. D. Webster & Litchfield, 2017). Raw water
quality will affect process design, in particular, temperature affects
the rate of biomass growth; at temperatures below 10 degrees Celsius,
growth is inhibited and bioremediation becomes infeasible (Dugan,
2010b, 2010a; Dugan et al., 2009). This factor limits the feasibility
of biological treatment in areas that experience low water temperatures
during winter. In addition, bacteria in bioreactors require nutrients
to grow and effectively reduce perchlorate. Therefore, some source
waters may require supplemental addition of nutrients such as nitrogen
or phosphorus (Harding Engineering and Environmental Services (ESE),
2001; U.S. Department of Defense (U.S. DoD), 2008a, 2009).
Although the process does not produce perchlorate-contaminated
wastes, periodic removal of excess biomass, e.g., through backwash,
will be required. The backwash water is non-toxic and can be discharged
to a sanitary sewer (U.S. Department of Defense (U.S. DoD), 2008, 2009)
or recycled following clarification. Typically, post-treatment of
treated water also will be required because biological treatment
increases soluble microbial organic products, depletes oxygen, and can
add turbidity and sulfides (Dordelmann, 2009; Harding Engineering and
Environmental Services (ESE), 2001; U.S. Department of Defense (U.S.
DoD), 2008; T. D. Webster & Crowley, 2016; T. D. Webster & Litchfield,
2017). The treatment process, however, can result in removal of co-
occurring contaminants such as nitrate (Upadhyaya et al., 2015; Webster
and Crowley, 2010; Webster and Lichfield, 2017).
Reverse Osmosis
Reverse osmosis is a membrane filtration process that physically
removes perchlorate ions from drinking water. This process separates a
solute such as perchlorate ions from a solution by forcing the solvent
to flow through a membrane at a pressure greater than the normal
osmotic pressure. The membrane is semi-permeable, transporting
different molecular species at different rates. Water and low-molecular
weight solutes pass through the membrane and are removed as permeate,
or filtrate. Dissolved and suspended solids are rejected by the
membrane and are removed as
[[Page 30547]]
concentrate or reject. This technique does not destroy the perchlorate
ion and, therefore, creates a subsequent need for disposal or treatment
of perchlorate-contaminated waste (the concentrate).
Membranes may remove ions from feed water by a sieving action
(called steric exclusion), or by electrostatic repulsion of ions from
the charged membrane surface. Across multiple bench- and pilot-scale
studies, reverse osmosis membranes consistently achieve perchlorate
removal greater than 80 percent and up to 98 percent (Liang, Scott,
Palencia, & Bruno, 1998; Nam et al., 2005; Yoon, Amy, & Yoon, 2005;
Yoon, Yoon, Amy, & Her, 2005). While water quality affects process
design (e.g., recovery rate, cleaning frequency, and antiscalant
selection), it has relatively little effect on perchlorate removal
effectiveness of reverse osmosis membranes. Reverse osmosis generates a
relatively large concentrate stream, which will contain perchlorate as
well as other rejected dissolved solids, which will require disposal.
The large concentrate stream also means less treated water is available
for distribution (e.g., 70 to 85 percent of source water), which is a
disadvantage for systems with limited water supply. Because reverse
osmosis can increase the corrosivity of the treated water, it may
require post-treatment or blending with bypass water. Reverse osmosis
can, however, remove co-occurring contaminants including arsenic and
chromium-VI (Amy, Yoon, and Amy, 2005).
B. What are the small system compliance technologies?
The EPA is proposing the SSCT shown in Table X-1. The table shows
which of the BAT listed above are also affordable for each small system
size category listed in Section 1412(b)(4)(E)(ii) of the SDWA. The
Agency identified these technologies based on an analysis of treatment
effectiveness and affordability (USEPA, 2018a).
Table X-1--Proposed SSCT for Perchlorate Removal
----------------------------------------------------------------------------------------------------------------
System size (population Biological Point-of-use reverse
served) Ion exchange treatment Reverse osmosis osmosis
----------------------------------------------------------------------------------------------------------------
25-500........................ Yes.............. No.............. No.............. Yes.
501-3,300..................... Yes.............. Yes............. Yes............. Yes.
3,301-10,000.................. Yes.............. Yes............. Yes............. Not applicable.\a\
----------------------------------------------------------------------------------------------------------------
\a\ For perchlorate, the EPA has determined that implementing and maintaining this option for systems larger
than 3,300 people (greater than 1 MGD design flow) is likely to be impractical.
The SSCT listed in Table X-1 include a point-of-use (POU) version
of reverse osmosis in addition to the ion exchange, biological
treatment and reverse osmosis technologies described in the previous
section. This technology can be used by small systems to comply with
the proposed MCL and, therefore, meets the effectiveness requirement
for an SSCT. For perchlorate removal, NSF/ANSI Standard 58: Reverse
Osmosis Drinking Water Treatment Systems includes a protocol that
requires a reverse osmosis unit to be able to reduce perchlorate from a
challenge level of 130 [micro]g/L to a target level of 4 [micro]g/L
(NSF, 2004). Organizations (e.g., NSF International, Underwriters
Laboratories, Water Quality Association) provide third-party testing
and certification that POU devices meet drinking water treatment
standards. There are no perchlorate certification standards for other
types of POU devices such as those using ion exchange media.
The operating principle for POU reverse osmosis devices is the same
as centralized reverse osmosis: Steric exclusion and electrostatic
repulsion of ions from the charged membrane surface. In addition to a
reverse osmosis membrane for dissolved ion removal, POU reverse osmosis
devices often have a sediment pre-filter and a carbon filter in front
of the reverse osmosis membrane, a 3- to 5-gallon treated water storage
tank, and a carbon filter between the tank and the tap.
The EPA identified the SSCT using the affordability criteria
methodology it developed for drinking water rules (USEPA, 1998). The
analysis method is a comparison of estimated incremental household
costs for perchlorate treatment to an expenditure margin, which is the
difference between baseline household water costs and a threshold equal
to 2.5% of median household income. Table X-2 shows the expenditure
margins derived for the analysis. These margins show the cap on
affordable incremental annual expenditures.
Table X-2--Expenditure Margins for SSCT Affordability Analysis
----------------------------------------------------------------------------------------------------------------
Median
System size (population served) household Affordability Baseline water Expenditure
income \a\ threshold \b\ cost \c\ margin
(a) (b) = 2.5% x a (c) (d) = b-c
----------------------------------------------------------------------------------------------------------------
25-500........................................ $52,791 $1,320 $341 $979
501-3,300..................................... 51,093 1,277 395 883
3,301-10,000.................................. 55,975 1,399 412 987
----------------------------------------------------------------------------------------------------------------
Source: Best Available Technologies and Small System Compliance Technologies for Perchlorate in Drinking Water
(USEPA, 2018a).
\a\ MHI based on U.S. Census 2010 American Community Survey (ACS) 5-year estimates (U.S. Census Bureau, 2010)
stated in 2010 dollars, adjusted to 2017 dollars using the CPI (for all items) for areas under 50,000 persons
(Bureau of Labor Statistics (BLS), 2018b).
\b\ Affordability threshold equals 2.5 percent of MHI.
\c\ Household water costs derived from 2006 Community Water System Survey (USEPA, 2009c), based on residential
revenue per connection within each size category, adjusted to 2017 dollars based on the CPI (for all items)
for areas under 50,000 persons.
Table X-3 shows the estimates of per-household costs by treatment
technology and size category generated using the treatment cost method
described in section XII.B as well as Best Available Technologies and
Small
[[Page 30548]]
System Compliance Technologies for Perchlorate in Drinking Water
(USEPA, 2018a) and Technologies and Costs for Treating Perchlorate-
Contaminated Waters (USEPA, 2018c). Costs in bold font do not exceed
the corresponding expenditure margin and, therefore, meet the SSCT
affordability criterion. Therefore, the EPA has determined that there
are affordable small system compliance technologies available and the
Agency is not proposing any variance technologies.
Table X-3--Annual Incremental Cost Estimates for SSCT Affordability Analysis
----------------------------------------------------------------------------------------------------------------
System size (population Biological Point-of-use reverse
served) Ion exchange treatment Reverse osmosis osmosis
----------------------------------------------------------------------------------------------------------------
25-500........................ $378 to $610..... $2,146 to $3,709. $2,272 to $2,671 $265 to $271.
501-3,300..................... $98 to $148...... $324 to $566..... $561 to $688.... $250 to $251.
3,301-10,000.................. $104 to $153..... $211 to $315..... $431 to $493.... Not applicable.\a\
----------------------------------------------------------------------------------------------------------------
Source: Best Available Technologies and Small System Compliance Technologies for Perchlorate in Drinking Water
(USEPA, 2018a), which describes the different WBS model input assumptions that result in ranges of per-
household costs shown; bold font indicates cost estimates that do not exceed the corresponding expenditure
margin.
\a\ For perchlorate, the EPA has determined that implementing and maintaining a POU program for systems larger
than 3,300 people (greater than 1 MGD design flow) is likely to be impractical.
XI. Rule Implementation and Enforcement
A. What are the requirements for primacy?
This section describes the regulations and other procedures and
policies primacy entities must adopt, or have in place, to implement
the proposed perchlorate rule. States must continue to meet all other
conditions of primacy in 40 CFR part 142. Section 1413 of the SDWA
establishes requirements that primacy entities (States or Indian
Tribes) must meet to maintain primary enforcement responsibility
(primacy) for its public water systems. These include: (1) Adopting
drinking water regulations that are no less stringent than federal
NPDWRs in effect under sections 1412(a) and 1412(b) of the Act, (2)
Adopting and implementing adequate procedures for enforcement, (3)
Keeping records and making reports available on activities that the EPA
requires by regulation, (4) Issuing variances and exemptions (if
allowed by the State) under conditions no less stringent than allowed
by SDWA Sections 1415 and 1416, and (5) Adopting and being capable of
implementing an adequate plan for the provision of safe drinking water
under emergency situations.
40 CFR part 142 sets out the specific program implementation
requirements for States to obtain primacy for the Public Water Supply
Supervision Program, as authorized under section 1413 of the Act.
To implement the perchlorate rule, States would be required to
adopt revisions at least as stringent as the proposed provisions in 40
CFR 141.6 (Effective Dates); 40 CFR 141.23 (Inorganic chemical sampling
and analytical requirements); 40 CFR 141.51 (Maximum contaminant level
goals for inorganic contaminants); 40 CFR 141.60 (Effective Dates); 40
CFR 141.62 (Maximum contaminant levels for inorganic contaminants);
Appendix A to Subpart O ([Consumer Confidence Report] Regulated
contaminants); Appendix A to Subpart Q (NPDWR violations and other
situations requiring public notice); Appendix B to Subpart Q (Standard
health effects language for public notification); and 40 CFR 142.62
(Variances and exemptions from the maximum contaminant levels for
organic and inorganic contaminants). Under 40 CFR 142.12(b), all
primacy States/territories/tribes would be required to submit a revised
program to the EPA for approval within two years of promulgation of any
final perchlorate NPDWR or could request an extension of up to two
years in certain circumstances.
B. What are the State recordkeeping requirements?
The current regulations in 40 CFR 142.14 require States with
primary enforcement responsibility (i.e., primacy) to keep records of
analytical results to determine compliance, system inventories,
sanitary surveys, State approvals, vulnerability and waiver
determinations, monitoring requirements, monitoring frequency
decisions, enforcement actions, and the issuance of variances and
exemptions. The State record keeping requirements remain unchanged and
would apply to perchlorate as with any other regulated contaminant.
C. What are the State reporting requirements?
Currently, States must report to the EPA information under 40 CFR
142.15 regarding violations, variances and exemptions, enforcement
actions and general operations of State public water supply programs.
The State reporting requirements remain unchanged and would apply to
perchlorate as with any other regulated contaminant. However, the
perchlorate MCL could result in a greater frequency of reporting by
certain states. See discussion of Paperwork Reduction Act compliance in
Section XVI for more information.
XII. Health Risk Reduction Cost Analysis
Section 1412(b)(3)(C) of the 1996 Amendments to the SDWA requires
the EPA to prepare a Health Risk Reduction and Cost Analysis (HRRCA) in
support of any NPDWR that includes an MCL. This section addresses the
HRRCA requirements as indicated:
Quantifiable and non-quantifiable health risk reduction
benefits for which there is a factual basis in the rulemaking record to
conclude that such benefits are likely to occur as the result of
treatment to comply with each level (Sections XII.C and XII.D);
Quantifiable and non-quantifiable health risk reduction
benefits for which there is a factual basis in the rulemaking record to
conclude that such benefits are likely to occur from reductions in co-
occurring contaminants that may be attributed solely to compliance with
the MCL, excluding benefits resulting from compliance with other
proposed or promulgated regulations (Section XII.C);
Quantifiable and non-quantifiable costs for which there is
a factual basis in the rulemaking record to conclude that such costs
are likely to occur solely as a result of compliance with the MCL,
including monitoring, treatment, and other costs, and excluding costs
resulting from compliance with other proposed or promulgated
regulations (Section XII.B and XII.D);
The incremental costs and benefits associated with each
alternative MCL considered (Section XII.D);
The effects of the contaminant on the general population
and on groups within the general population, such as
[[Page 30549]]
infants, children, pregnant women, the elderly, individuals with a
history of serious illness, or other sensitive populations that are
identified as likely to be at greater risk of adverse health effects
due to exposure to contaminants in drinking water than the general
population (Section XII.C and Section III);
Any increased health risk that may occur as the result of
compliance, including risks associated with co-occurring contaminants
(Section XII.C); and
Other relevant factors, including the quality and extent
of the information, the uncertainties in the analysis, and factors with
respect to the degree and nature of the risk (Section XII.E).
A. Identifying Affected Entities
If the EPA issues a final NPDWR for perchlorate, it would affect
the following entities: CWSs and NTNCWSs that must meet the proposed
MCL and monitoring and reporting requirements; and primacy agencies
that must adopt and enforce the MCL as well as the monitoring and
reporting requirements. All of these entities would incur costs,
including administrative costs, monitoring and reporting costs, and--in
a limited number of cases--costs to reduce perchlorate levels in
drinking water to meet the proposed MCL using treatment or nontreatment
options. Section B below summarizes the method the EPA used to estimate
these costs.
The systems that reduce perchlorate concentrations will reduce
associated health risks. The EPA developed a method to estimate the
potential benefits of reduced perchlorate exposure among the service
populations of systems with elevated baseline perchlorate levels.
Section C below summarizes this method used to estimate these benefits.
Section D below provides the cost and benefit estimates. The EPA
prepared the Health Risk Reduction Cost Analysis of the Proposed
Perchlorate Rule (USEPA, 2019a), which is available in the docket for
the proposed rule. Section XIII summarizes and discusses key
uncertainties in the cost and benefit analyses.
B. Method for Estimating Costs
Some costs associated with an NPDWR are incurred by all CWS and
NTNCWS (e.g., monitoring and reporting) while others are only incurred
by systems with perchlorate levels exceeding the MCL. The EPA estimated
costs for CWS and NTNCWS to monitor and report perchlorate levels and
also estimated the costs for a subset of public water systems with
perchlorate levels greater than the proposed MCL to install and operate
treatment. The EPA assumed that affected water systems would adopt ion
exchange treatment because it is the most cost-effective treatment
option and easy to operate on a `throw-away' basis. If site-specific
nontreatment options are available and lower cost, then this assumption
might overstate costs. The EPA also estimated the costs for States and
other primacy agencies to assure systems implement the rule and to
report information to the EPA.
The EPA estimated initial costs for all CWS and NTNCWS operators to
read and understand the rule and provide training to their staff to
implement the proposed rule. The EPA also estimated the recurring costs
for all CWS and NTNCWS operators to conduct monitoring, report results,
and apply for waivers. For the purpose of these estimates, the EPA
assumed that both small and large systems would require the same amount
of time to read the rule, apply for a waiver, and collect a water
sample but that it would take large systems twice as long to provide
initial training to their staff. Table XII-1 summarizes the frequency
and labor hour assumptions for this analysis.
Table XII-1--Labor Hours for Drinking Water Systems Administrative and Monitoring Requirements
----------------------------------------------------------------------------------------------------------------
Small system Large system
Activity Frequency hours hours
----------------------------------------------------------------------------------------------------------------
Read the rule.............................. one time per system................ 4 4
Provide initial training................... one time per system................ 16 32
Apply to State for monitoring waiver....... once every 9 years per eligible 16 16
system.
Collect a single finished water sample \1\. per monitoring event............... 1 1
----------------------------------------------------------------------------------------------------------------
Source (USEPA, 2000a). The EPA's cost analysis reflects full MCL compliance and therefore the EPA did not
estimate Tier 1 notification costs.
\1\ The estimate is per sample. Therefore, a system conducting a year of quarterly monitoring at three entry
points incurs a total of 12 hours of labor to complete the task (3 entry points x 4 samples x 1 hour per
sample).
Systems will incur monitoring costs over the analysis period. The
EPA estimated monitoring frequency based on the proposed initial
monitoring requirements, the standard monitoring framework requirements
for inorganic contaminants, and the proposed implementation schedule.
The estimated number of monitoring samples over the analysis period
shown in Table XII-2 reflect the following phases:
1. Initial monitoring; four quarterly samples at every CWS and
NTNCWS entry point.
2. Preliminary regular monitoring before waiver application: Three
regular monitoring samples for every CWS and NTNCWS entry point
(collected annually at surface water system entry points and
triennially at ground water system entry points).
3. Long-term monitoring at either (a) regular monitoring frequency
for entry points at systems not granted waivers (60% of surface water
system and 10% of ground water systems), or (b) reduced monitoring
frequency for entry points at systems receiving waivers from primacy
agencies (40% of surface water systems and 90% of ground water
systems), which is one sample during every nine-year compliance
monitoring cycle.
Table XII-2--Estimates of Compliance Monitoring Samples by Phase and System Type, Size, and Source Water
----------------------------------------------------------------------------------------------------------------
Number of
Monitoring phase (sampling frequency) System type, size, and source water entry points Aggregate
\1\ samples \2\
----------------------------------------------------------------------------------------------------------------
1. Initial monitoring (4 quarterly samples All CWS and NTNCWS................. 92,656 370,624
in one year).
[[Page 30550]]
2. Preliminary regular monitoring (3 annual All CWS and NTNCWS................. 92,654 277,962
entry point samples for surface water
systems and 3 triennial entry point
samples for ground water systems).
3a. Long-term monitoring, no waiver (annual 60% of large surface water CWS..... 3,324 86,424
entry point samples). 60% of small surface water CWS and 6,064 139,472
all surface water NTNCWS.
3a. Long-term monitoring, no waiver 10% of large ground water CWS...... 680 4,080
(triennial entry point samples). 10% of small ground water CWS and 7,021 35,105
all ground water NTNCWS.
3b. Long-term monitoring, waiver (1 sample 40% of large surface water CWS..... 2,216 4,432
every 9 years). 40% of small surface water CWS and 4,043 8,086
all surface water NTNCWS.
3b. Long-term monitoring, waiver (1 sample 90% of large ground water CWS...... 6,117 12,234
every 9 years). 90% of small ground water CWS and 63,189 63,189
all ground water NTNCWS.
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
0780).
\1\ The EPA estimated a total of 92,656 entry points based on the total number of potentially affected systems
in SDWIS/FED and the average number of entry points per system in the UCMR 1 data by size category and source
water. The initial monitoring phase includes all entry points. The EPA assumed that the two entry points with
MCL exceedances at the proposed MCL of 56 [micro]g/L would continue to take quarterly samples for the duration
of the analysis period, for a total of 232 samples. Thus, they are excluded from the estimates for the
subsequent phases of regular and long-term monitoring. Primacy agencies may, however, allow monitoring to
return to a regular schedule if treatment process operation can reliably and consistently reduce perchlorate
below the MCL.
\2\ For Phase 3, the estimate of aggregate samples is the product of the number of entry points and the
frequency of sampling during the remaining years of the analysis period. For example, large surface water CWS
without a waiver conduct long-term annual monitoring for 26 years because they complete preliminary regular
monitoring in year 9. In contrast, large ground water CWS without a waiver begin long-term triennial
monitoring in year 16 because their preliminary regular monitoring phase lasts for 9 years (3 triennial
samples) instead of 3 years (3 annual samples). The estimates also reflect schedule differences by size
because large CWS begin monitoring schedules three years earlier than small CWS and all NTNCWS.
To estimate costs to CWSs and NTNCWSs associated with time spent on
compliance monitoring and other administrative costs, the EPA generally
uses the labor rate \13\ for full-time treatment plant operators in
CWSs from USEPA (2011c), which vary based on the size of the system.
The EPA calculated a weighted average fully loaded hourly wage rate for
water systems of $34.71.
---------------------------------------------------------------------------
\13\ Updated to 2017$ using the BLS Employment Cost Index for
Total Compensation for Private industry workers in Utilities.
---------------------------------------------------------------------------
Additionally, the EPA assumed that systems will incur an average
analytical cost of $64 per sample, which is the average cost per sample
obtained from multiple laboratories for perchlorate quantitation using
Method 314.0.
To estimate treatment cost, the EPA utilized the occurrence data
described in Section VI to estimate the number of system entry points
that exceed the proposed and alternative MCLs. The EPA estimated costs
that those water systems would incur to install and maintain treatment
using its work breakdown structure (WBS) cost estimating models. The
WBS models are spreadsheet-based engineering models for individual
treatment technologies, linked to a central database of component unit
costs. The WBS approach involves breaking a process down into discrete
components for the purpose of estimating costs and produce a
comprehensive assessment of the capital and operating requirements for
a treatment system.\14\ The EPA used the WBS models to generate total
capital and O&M cost estimates for each technology and nontreatment
option for up to 49 different system flow rates. The EPA generated
separate estimates that correspond to different water sources
(groundwater or surface water), three different cost levels (low, mid,
and high), and different technology-specific scenarios (e.g., 105,000
or 170,000 bed volumes for ion exchange). The EPA used the mid-cost
estimates for ion exchange to generate expected costs for all entry
points requiring perchlorate removal. This technology cost-effectively
removes perchlorate, but its ability to remove co-occurring
contaminants depends on influent characteristics and process design.
Therefore, the EPA did not assume that treatment might result in
ancillary quantifiable or non-quantifiable benefits of removing co-
occurring ions such as nitrate. Treatment costs include waste disposal
for spent resin, but do not include post-treatment costs for corrosion
control because blending rates at most entry points should not result
in much chloride addition or changes in corrosivity.
---------------------------------------------------------------------------
\14\ The document Technologies and Costs for Treating
Perchlorate-Contaminated Waters (USEPA, 2018c) contains more
complete discussion of the WBS models and the cost estimating
approach.
---------------------------------------------------------------------------
For purposes of estimating the costs and benefits, the EPA assumed
that CWSs and NTNCWSs in California and Massachusetts would not incur
additional cost or realize benefits because these States currently
regulate perchlorate at a more stringent level than the proposed MCL
and alternative MCL. For each entry point in the UCMR 1 dataset outside
of these two States, the EPA compared the maximum observed perchlorate
concentration to the MCL to identify those that have an exceedance of
the proposed MCL. The EPA assumed that these entry points would incur
costs for an additional confirmation sample and would need to implement
treatment to meet the MCL. For each entry point, the EPA estimated the
design flow and the average flow by service populations based on the
Agency's prior analysis of the relationships between these values
(USEPA, 2000b). The Agency assumed blending of treated water and
untreated water would be used to meet an average treatment target equal
to 80 percent of the MCL (for an MCL of 56 [micro]g/L the blending
target would be 45 [micro]g/L) given a 95 percent removal effectiveness
until perchlorate breakthrough. The Agency applied the capital cost and
O&M cost curves from the WBS models to the design and average flows
adjusted for
[[Page 30551]]
blending. When small systems in the UCMR 1 sample incurred treatment
costs, the EPA extrapolated the costs on a per capita basis to the
estimate of national population exposure derived using the small system
population sampling weights.
For the primacy agencies that will implement and enforce the rule
(including 49 States, one tribal nation and 5 territories), the EPA
estimated upfront costs incurred during the three years between rule
promulgation and the effective date to read and understand the rule,
adopt regulatory changes, and provide training to CWSs and NTNCWSs and
Agency staff. Primacy agencies will also have recurring costs to review
waiver applications and monitoring reports. Table XII-3 summarizes the
labor hour assumptions for these activities. The EPA requests comments
on these assumptions.
Table XII-3--Labor Hours for Primacy Agency Administrative Requirements
------------------------------------------------------------------------
Activity Frequency Hours
------------------------------------------------------------------------
Read and understand the rule, one time per Agency.... 416
adopt regulatory changes \1\.
Provide initial training and total per Agency....... 2,080
assistance to water systems
\2\.
Provide initial training to total per Agency....... 250
staff \2\.
Review waiver applications..... once every 9 years per 8
eligible system.
Review monitoring reports...... per monitoring event... 1
------------------------------------------------------------------------
Source (USEPA, 2000a).
\1\ The EPA assumed that two States that already regulate perchlorate in
drinking water would not incur the incremental burdens in this table
to regulate perchlorate under the proposed rule because they already
incur baseline costs for perchlorate regulation including monitoring
costs. The Agency assumed, however, that the two States would incur an
average of 40 hours to confirm that their existing requirements are at
least as protective as the proposed rule.
\2\ The EPA assumed that all training hours occur in a single year,
although the hours may actually occur over time. The total hour
estimates are average values across States.
State labor rates are based on the mean hourly wage rate from
Bureau of Labor Statistics (BLS) Standard Occupational Classification
code 19-2041 (State Government--Environmental Scientists and
Specialists, Including Health). Wages are loaded using a factor
calculated from the BLS Employer Costs for Employee Compensation report
(Bureau of Labor Statistics (BLS), 2016 Table 3), for a fully loaded
hourly wage rate for States of $50.67. The EPA requests comments on
these labor rate assumptions.
The proposed rule provides three years between the effective dates
and compliance dates for systems. For the purpose of estimating costs,
the EPA assumed that large CWSs would phase in administrative costs,
including initial monitoring, and upfront administrative costs
uniformly over the 3 years following the effective date (i.e., years 4
to 6 of the analysis period). Similarly, the EPA assumed that small
CWSs and NTNCSs will phase in these costs over the subsequent three-
year period (i.e., years 7 to 9 of the analysis period). The EPA
assumed that, within these periods, all systems would conduct initial
monitoring--one year of quarterly monitoring to determine whether
perchlorate concentrations are consistently and reliably below the
proposed MCL. Thereafter, systems with MCL exceedances would continue
to monitor quarterly, while systems below the MCL that obtain waivers
will monitor annually for three years (surface water systems) or
triennially for 9 years (ground water systems), then incur costs for a
waiver application. Thereafter, these systems will continue reduced
monitoring--once every nine years--under subsequent waivers. Systems
that are below the MCL without waivers will monitor once per year
(surface water systems) or once every three years (groundwater).
Consistent with USEPA (2008b), the EPA assumed that 90% of groundwater
and 40% of surface water systems that have all entry points below the
MCL would obtain waivers.
The EPA estimated the costs over a 35-year analysis period, which
includes a 3-year period prior to the effective date to allow for State
rule adoption activities, a 3-year period after the effective date to
allow initial monitoring among large CWSs, and a 3-year period after
that to allow initial monitoring for small CWSs and NTNCWSs. Evaluating
costs over 35 years covers a full life cycle of the capital investments
that large systems make in the 6th year; the WBS estimates of composite
useful life of the equipment and infrastructure investment is
approximately 30 years. The EPA assumed that treatment modifications
will be completed in the final year of the initial monitoring period
(i.e., year 6 of the analysis for large CWSs and year 9 for small CWSs
and NTNCWSs). The EPA calculated the present value of total costs in
each year of the analysis period and discounted to year 1 using both a
3% and 7% discount rate and annualized total present value of costs at
the same rates over 35 years to obtain a constant total annual cost
estimate to compare to total annual benefits.
Water systems typically recover costs through increased household
rates, resulting in increased costs at the household level.\15\ To
calculate the magnitude of the cost increase for systems that exceed
the proposed MCL or alternative MCL, the EPA first estimated the number
of households that may incur costs as a result of the rule based on the
population served by affected CWSs and NTNCWSs and the average
household size (U.S. Census Bureau, 2017b). The EPA divided the total
annual system-level costs by the number of households served by the
system.
---------------------------------------------------------------------------
\15\ For systems with monitoring costs only, household-level
costs will be negligible.
---------------------------------------------------------------------------
C. Method for Estimating Benefits
The EPA has taken an approach in evaluating the benefits for
perchlorate that is consistent with the SAB's recommendations for the
methodology to inform the MCLG for perchlorate. This approach involves
(a) using a BBDR model to estimate the impact of perchlorate on
maternal thyroid hormone levels during the first trimester of
pregnancy, and (b) using a dose-response function from the
epidemiological literature to model the relationship between altered
maternal thyroid hormone levels and offspring IQ. Currently available
science has limited this quantitative benefits assessment to the
relationship between perchlorate and IQ. Given that alterations in
thyroid hormones have been associated with other adverse outcomes,
including reproductive outcomes (Alexander et al., 2017; Hou et
[[Page 30552]]
al., 2016; Maraka et al., 2016) and effects on cardiovascular systems
(Asvold et al., 2012; Sun et al., 2017) there are likely non-quantified
benefits of risk reductions for other endpoints or reduced exposure to
co-occurring contaminants, which are addressed below. Uncertainties
regarding the quantifiable benefits are also addressed below.
The population impacted by the rule for which benefits can be
quantified is specific to live births from mothers who were served by a
CWS or NTNCWS with perchlorate concentrations above the potential MCLs.
To determine the nationwide population of children that will experience
a quantifiable benefit of avoided IQ decrements from reducing maternal
perchlorate exposure during pregnancy, the EPA first estimated the
total population being served by systems above the MCL based on data
from UCMR 1. The EPA then multiplied the total population served for
each affected CWS and NTNCWS by the proportion of women of childbearing
age (aged 15-44) in the US, which is 19.7 percent (U.S. Census Bureau,
2017a). The number of women of child-bearing age for each entry point
was then multiplied by the annual number of live births in the US, or
62 births per 1,000 women (6.2 percent) (Martin, Hamilton, & Osterman,
2017).
The EPA used a two-step dose-response model to estimate health
benefits of a reduction in perchlorate exposure as a result of
regulating perchlorate in drinking water not to exceed the proposed MCL
of 56 [mu]g/L and alternative MCLs of 18 [mu]g/L and 90 [mu]g/L. The
first step relates changes in perchlorate to changes in maternal free-
thyroxine (fT4) during the first trimester of pregnancy using the EPA's
BBDR model. Because the dose-response relationship between perchlorate
exposure and maternal fT4 is dependent on maternal iodine intake
status, this first-step analysis is repeated for several categories of
iodine intake. For the BBDR simulations, the EPA used the 90th
percentile ingestion rate to be consistent with the MCLG modeling
approach, which may overstate the exposure in the simulation.
The second step of the dose-response model subsequently relates the
predicted changes in maternal fT4 from the BBDR model to changes in
child IQ using the function estimated in the EPA independent analysis
of the Korevaar et al., (2016) study data. Ultimately, the changes in
IQ are estimated for each impacted iodine intake group, and all of the
impacted iodine intake groups' IQ decrements are averaged together
based on the proportion of individuals in each iodine intake category.
Table XII-4 shows the specific iodine intake groups and the proportion
of non-pregnant women of childbearing age that fall into each group.
Table XII-4--Proportion of Population Based on Maternal Iodine Intake
Status
------------------------------------------------------------------------
Proportion
of the
Iodine intake range ([mu]g/day) used for benefits analysis population
(%)
------------------------------------------------------------------------
0 to <55................................................... 7.14
55 to <60.................................................. 2.15
60 to <65.................................................. 1.06
65 to < 70................................................. 1.86
70 to <75.................................................. 1.31
75 to <80.................................................. 3.10
80 to <85.................................................. 2.62
85 to <90.................................................. 1.20
90 to <95.................................................. 1.83
95 to <100................................................. 2.94
100 to <125................................................ 13.56
125 to <150................................................ 9.08
150 to <170................................................ 10.31
170 to <300................................................ 24.47
>=300...................................................... 17.36
------------------------------------------------------------------------
Source: U.S. EPA (2019a).
These changes in child IQ are then monetized using the EPA's
estimate of the value of an IQ point. This estimate reflects the
discounted present value of lifetime income reductions attributable to
a 1-point reduction in IQ at birth. Therefore, the present value
depends on the discount rate. At a 3 percent discount rate, the
estimate is $18,686 per IQ point; at a 7 percent discount rate the
estimate is $3,631.
Other potential benefits not quantified or monetized include
additional avoided health effects which cannot currently be monetized,
improved public perception of water quality, as well as a possible
reduction of other co-occurring contaminants that target the thyroid,
such as nitrate, as a result of water treatment for removal of
perchlorate. For example, all of the treatment technologies evaluated
for this rule (ion exchange, biological treatment, and reverse osmosis)
can also remove co-occurring nitrate from drinking water. Section XIII
provides additional discussion of uncertainties in this analysis.
D. Comparison of Costs and Benefits
This section provides the estimates of costs and benefits that the
EPA derived using the methods described above. It includes estimates
for the proposed and alternative MCLs.
For the proposed MCL of 56 [mu]g/L, Table XII-5 summarizes the
total estimated cost of the proposed rule to water systems and primacy
agencies, and Table XII-6 summarizes the estimated per-household cost
for the system incurring treatment costs.\16\ Table XII-7 summarizes
the estimated benefits. In both instances, the estimates based on the
UCMR 1 sample are also national estimates because treatment costs occur
only at large systems; there are no small system treatment costs or
related benefits to extrapolate.
---------------------------------------------------------------------------
\16\ For all households served by all of the systems subject to
the monitoring costs as well as MCL compliance, the average annual
cost is less than $0.20.
Table XII-5--Summary of Total Annualized Costs at MCL of 56 [mu]g/L
[Millions; 2017$]
------------------------------------------------------------------------
Cost component 3% Discount 7% Discount
------------------------------------------------------------------------
Drinking Water Systems Treatment Costs.. $0.65 $0.70
Drinking Water Systems Monitoring and 5.93 6.38
Administration Costs\1\................
Drinking Water Systems Costs Subtotal... 6.58 7.07
State Administration Costs.............. 3.09 3.20
-------------------------------
Total Costs......................... 9.67 10.28
------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of
independent rounding.
[[Page 30553]]
\1\ Costs include monitoring for all CWS and NTNCWS. Some consecutive
systems that purchase 100% of their water from wholesale systems may
not be required to monitor for perchlorate provided States allow
integrated system agreements to include perchlorate among the
monitoring requirements that the wholesale system fulfills for the
consecutive system. The potential number of consecutive systems
excluded from perchlorate monitoring depends on system and State
decisions and, therefore, is unknown. Excluding monitoring costs for
approximately 8,400 consecutive systems that do not report a water
source facility (e.g., well or intake) in SDWIS/FED from the
monitoring cost analysis reduces annualized monitoring costs by $0.8
million.
Table XII-6--Summary of Household-Level Annual Costs for Systems
Treating to Comply with MCL at 56 [mu]g/L
[2017$]
------------------------------------------------------------------------
Cost range 3% Discount 7% Discount
------------------------------------------------------------------------
Minimum................................. $11 $14
Average................................. 40 47
Maximum................................. 69 80
------------------------------------------------------------------------
Source: (USEPA, 2019a).
Table XII-7--Summary of Total Annualized Benefits of Avoided Lost IQ Decrements at MCL of 56 [mu]g/L
[Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
Annual delta
Korevaar [beta] distribution IQ 3% Discount 7% Discount
----------------------------------------------------------------------------------------------------------------
Upper........................................................... 243 $3.57 $0.60
Central......................................................... 136 2.00 0.34
Lower........................................................... 30 0.44 0.07
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
For the alternative MCL of 18 [mu]g/L, Table XII-8 summarizes the
total cost of the proposed rule to water systems and primacy agencies,
and Table XII-9 summarizes the per-household cost for systems requiring
treatment, which vary across the systems. Table XII-10 summarizes the
quantified benefits. At this threshold, one entry point for one small
system in the UCMR 1 data had an exceedance. Therefore, the EPA
extrapolated the treatment costs and benefits from the UCMR 1 estimates
to national estimates based on sampling weights.
Table XII-8--Summary of Total Annualized Costs at MCL of 18 [mu]g/L
[Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
3% Discount 7% Discount 3% Discount 7% Discount
Cost component (UCMR 1) \1\ (UCMR 1) \1\ (national) \1\ (national) \1\
----------------------------------------------------------------------------------------------------------------
Drinking Water Systems Treatment Costs.......... $6.92 $7.29 $7.92 $8.37
Drinking Water Systems Monitoring and 5.94 6.38 5.94 6.38
Administration Costs...........................
Drinking Water Systems Costs Subtotal........... 12.85 13.67 13.86 14.75
State Administration Costs...................... 3.09 3.21 3.09 3.21
---------------------------------------------------------------
Total Costs................................. 15.95 16.88 16.95 17.96
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of independent rounding.
\1\ The EPA applied statistical sampling weights to the results to extrapolate small system results to national
results. The entry point at which a measurement exceeds 18 [mu]g/L is one of 20 in its sample stratum; no
other sample in the stratum had a measurement of perchlorate greater than the minimum reporting level. The
entry point population of 2,155 represents 5.31% of the total population served by the six UCMR 1 systems in
the stratum (40,574). Currently, the stratum population of 775,000 accounts for 1.32% of the 58.7 million
national population served by small systems. Thus, the UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of
small system customers (approximately 41,100) may be exposed to perchlorate greater than 18 [mu]g/L. The EPA
calculated per-capita costs for the system and extrapolated to national level based on this population
estimate.
\2\ Costs include monitoring for all CWS and NTNCWS. Under 40 CFR 141.29 some consecutive systems that purchase
100% of their water from wholesale systems may not be required to monitor for perchlorate provided primacy
agencies, with EPA concurrence, allow integrated system agreements to include perchlorate among the monitoring
requirements that the wholesale system fulfills for the consecutive system. The potential number of
consecutive systems excluded from perchlorate monitoring depends on system and primacy agency decisions and,
therefore, is unknown. Excluding monitoring costs for approximately 8,400 consecutive systems that do not
report a water source facility (e.g., well or intake) in SDWIS/FED from the monitoring cost analysis reduces
annualized monitoring costs by $0.8 million.
Table XII-9--Summary of Household-Level Annual Costs for Systems Treating To Comply With the MCL at 18 [micro]g/
L
[2017$]
----------------------------------------------------------------------------------------------------------------
3% Discount 7% Discount 3% Discount 7% Discount
Cost range (UCMR 1) \1\ (UCMR 1) \1\ (national) \1\ (national) \1\
----------------------------------------------------------------------------------------------------------------
Minimum......................................... $18 $24 $18 $24
Average......................................... 38 46 38 46
[[Page 30554]]
Max............................................. 72 84 72 84
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
\1\ National cost estimates include extrapolation for one small system entry point to national estimates based
on sampling weights. The per-household costs are the same for the sample and national extrapolations because
the small system cost extrapolation occurs on a per-capita basis.
Table XII-10--Total and Annualized Benefits of Avoided Lost IQ Decrements at 18 [micro]g/L
[Millions; 2017$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Annual delta IQ UCMR 1 National \1\
Korevaar [beta] distribution -----------------------------------------------------------------------------------------------
UCMR 1 National \1\ 3% Discount 7% Discount 3% Discount 7% Discount
--------------------------------------------------------------------------------------------------------------------------------------------------------
Upper................................................... 442 447 $6.50 $1.10 $6.56 $1.11
Central................................................. 248 251 3.65 0.62 3.68 0.62
Lower................................................... 54 55 0.80 0.13 0.80 0.14
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
\1\ The EPA applied statistical sampling weights to the results to extrapolate small system results to national results. The entry point at which a
measurement exceeds 18 [micro]g/L is one of 20 in its sample stratum; no other sample in the stratum had a measurement of perchlorate greater than the
minimum reporting level. The entry point population of 2,155 represents 5.31% of the total population served by the six UCMR 1 systems in the stratum
(40,574). Currently, the stratum population of 774,780 accounts for 1.32% of the 58.7 million national population served by small systems. Thus, the
UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of small system customers (approximately 41,100) may be exposed to perchlorate greater than 18
[micro]g/L. The EPA assumed that this population would incur benefits equivalent to the sampled entry point's population.
For the alternative MCL of 90 [micro]g/L, Table XII-11 summarizes
the total cost of the proposed rule to water systems and primacy
agencies, and Table XII-12 summarizes the per-household cost for
systems requiring treatment, which vary across the systems. Table XII-
13 summarizes the quantified benefits. At this threshold, no small
systems in the UCMR 1 data had an exceedance. Therefore, treatment
costs and benefits for the UCMR 1 data are the national estimates.
Table XII-11--Summary of Total Annualized Costs at MCL of 90 [micro]g/L
[Millions; 2017$]
------------------------------------------------------------------------
Cost component 3% discount 7% discount
------------------------------------------------------------------------
Drinking Water Systems Treatment Costs.. $0.49 $0.52
Drinking Water Systems Monitoring and 5.93 6.37
Administration Costs \1\...............
Drinking Water Systems Costs Subtotal... 6.42 6.89
State Administration Costs.............. 3.09 3.20
-------------------------------
Total Costs......................... 9.51 10.10
------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of
independent rounding.
\1\ Costs include monitoring for all CWS and NTNCWS. Some consecutive
systems that purchase 100% of their water from wholesale systems may
not be required to monitor for perchlorate provided States allow
integrated system agreements to include perchlorate among the
monitoring requirements that the wholesale system fulfills for the
consecutive system. The potential number of consecutive systems
excluded from perchlorate monitoring depends on system and State
decisions and, therefore, is unknown. Excluding monitoring costs for
approximately 8,400 consecutive systems that do not report a water
source facility (e.g., well or intake) in SDWIS/FED from the
monitoring cost analysis reduces annualized monitoring costs by $0.8
million.
Table XII-12--Summary of Household-Level Annual Costs for Systems
Treating To Comply With MCL at 90 [micro]g/L
[2017$]
------------------------------------------------------------------------
Cost range 3% Discount 7% Discount
------------------------------------------------------------------------
Minimum................................. $65 $76
Average................................. 65 76
Maximum................................. 65 76
------------------------------------------------------------------------
Source: (USEPA, 2019a). There is no variation in costs because treatment
costs occur at one entry point. The household costs are slight lower
compared to the maximum cost at 56 [micro]g/L because treatment costs
to meet an MCL of 90 [micro]g/L are lower than the costs to meet an
MCL of 56 [micro]g/L.
[[Page 30555]]
Table XII-13--Summary of Total Annualized Benefits of Avoided Lost IQ Decrements at MCL of 90 [micro]g/L
[Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
Annual delta
Korevaar [beta] distribution IQ 3% Discount 7% Discount
----------------------------------------------------------------------------------------------------------------
Upper........................................................... 222 $3.26 $0.55
Central......................................................... 124 1.83 0.31
Lower........................................................... 27 0.40 0.07
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
Table XII-14 provides a comparison of benefits and costs for three
MCL values. First, the table shows the total annual costs and total
annual benefits for each MCL. In all cases, the total costs are
substantially higher than the potential range of quantifiable benefits.
The table also shows the incremental impact on costs and benefits
between an MCL of 56 [micro]g/L and an MCL of 18 [micro]g/L and between
an MCL of 90 [micro]g/L and 56 [micro]g/L.
Section 1412(b)(4)(C) of the SDWA requires that when proposing a
national primary drinking water regulation, ``the Administrator shall
publish a determination as to whether the benefits of the maximum
contaminant level justify, or do not justify, the costs.'' The
infrequent occurrence of perchlorate at levels of health concern
imposes high monitoring and administrative cost burdens on public water
systems and the States. Based on a comparison of costs and benefits
estimated at the proposed MCL of 56 [micro]g/L using the best available
science and data, the EPA Administrator has determined based upon the
available information that the benefits of establishing an NPDWR for
perchlorate do not justify the associated costs.
Under these circumstances, Section 1412(b)(6)(A) of the SDWA
provides, with exceptions not relevant here, that ``the Administrator
may, after notice and opportunity for public comment promulgate a
maximum contaminant level for the contaminant that maximizes health
risk reduction benefits at a cost that is justified by the benefits.''
The EPA has evaluated the benefits and costs of alternative MCL values
of 18 [micro]g/L and 90 [micro]g/L. However, based upon the available
information the Administrator also finds that the benefits of an NPDWR
at the alternative MCL values would not justify the resulting rule
costs. The alternative MCLs would not increase net benefits, while
compliance costs associated mainly with nationwide CWS monitoring
requirements would remain relatively similar. Consistent with the
discretion afforded the Agency by SDWA Section 1412(b)(6)(A) to decide
whether or not to adjust an MCL to a level where the benefits justify
the costs, the EPA is however proposing, and may finalize, the MCL of
56 [micro]g/L notwithstanding the Agency's determination that benefits
would not justify the costs.
Table XII-14--Comparison of Annual Costs and Benefits by MCL
[Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
Cost 3% Benefit 3% Cost 7% Benefit 7%
MCL value discount discount discount discount
----------------------------------------------------------------------------------------------------------------
UCMR 1:
90 [micro]g/L.............................. $9.51 $0.40-$3.26 $10.10 $0.07-$0.55
56 [micro]g/L.............................. 9.67 0.44-3.57 10.28 0.07-0.60
18 [micro]g/L.............................. 15.95 0.80-6.50 16.88 0.13-1.10
Incremental (from 90 [micro]g/L to 56 [micro]g/ 0.16 0.04-0.31 0.18 0.0-0.05
L)............................................
Incremental (from 56 [micro]g/L to 18 [micro]g/ 6.28 0.36-2.93 6.60 0.06-0.50
L)............................................
----------------------------------------------------------------------------------------------------------------
National:
90 [micro]g/L.............................. 9.51 0.40-3.26 10.10 0.07-0.55
56 [micro]g/L \1\.......................... 9.67 0.44-3.57 10.28 0.07-0.60
18 [micro]g/L.............................. 16.95 0.80-6.56 17.96 0.14-1.11
Incremental (from 90 [micro]g/L to 56 [micro]g/ 0.16 0.04-0.31 0.18 0.0-0.05
L)............................................
Incremental (from 56 [micro]g/L to 18 [micro]g/ 7.28 0.36-2.99 7.69 0.07-0.51
L)............................................
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of independent rounding.
\1\ For the proposed MCL of 56 [micro]g/L and the alternative MCL of 90 [micro]g/L, the national estimates are
the same as the estimates based on UCMR 1 data because there were no small system sample results to
extrapolate to national small system estimates. At an MCL of 18 [micro]g/L, national estimates include
extrapolation for one small system entry point to national estimates based on sampling weights described
above.
XIII. Uncertainty Analysis
The EPA has presented an extensive discussion of the uncertainties
in the key analyses informing this proposal in the uncertainty section
of the MCLG Approaches Report and the uncertainties section of the
Economic Analysis document (USEPA, 2018b; USEPA, 2019a). A summarized
description of these uncertainties are presented below.
A. Uncertainty in the MCLG Derivation
Each input into the analysis to inform the MCLG is a decision point
associated with uncertainty. There is uncertainty in different aspects
of the BBDR model, ranging from structural and functional relationships
to specific parameter values for early pregnancy. There are very few
data available to calibrate the pharmacokinetic aspects of the model,
particularly at the life stage of interest. Also, the BBDR model does
not explicitly consider the effect of the presence of other goitrogens
(e.g., thiocyanate, nitrate) or effects of thyroid disease states.
Toxicodynamic aspects such as competitive inhibition at the NIS,
depletion of iodide stores under different iodine intake levels and
physiological states, and the ability of the TSH feedback loop to
compensate for perturbations in thyroid function
[[Page 30556]]
each have their own uncertain features. Additional uncertainty is
introduced by linking the BBDR model estimates of maternal fT4 to
altered neurodevelopment in offspring. None of the studies used to
evaluate potential adverse neurodevelopmental outcomes in offspring
born to hypothyroxinemic mothers was performed in the U.S. None of the
studies measured perchlorate exposure. Not all the studies measured
iodide levels in the study populations. The state of the science on the
relationship between maternal fT4 levels and offspring neurodevelopment
is constantly evolving. There are numerous indices used to assess
neurodevelopmental impacts and there is some uncertainty regarding the
selection of IQ as the critical endpoint for setting the MCLG.
A recently published paper evaluating the EPA's BBDR model and MCLG
Approaches, reiterated the uncertainties the Agency identified in its
analyses and questions the use of these quantitative tools for
perchlorate in a regulatory context (Clewell et al., 2019).
B. Uncertainty in the Economic Analysis
The EPA provides discussions regarding several sources of
uncertainty in the benefit and cost estimates in the Health Risk
Reduction and Cost Analysis (USEPA, 2019a). Table XIII-1 provides a
summary of sources of uncertainty and their potential effects on
estimated costs and benefits. The following discussion addresses
uncertainties specific to the benefits analysis.
Table XIII-1--Sources of Uncertainty in Economic Analysis
----------------------------------------------------------------------------------------------------------------
Description Potential effect \1\
----------------------------------------------------------------------------------------------------------------
Baseline Occurrence
----------------------------------------------------------------------------------------------------------------
UCMR 1 data are more than one decade old; actual occurrence could be lower (benefits and costs
(e.g., because of contaminant cleanup) or higher (e.g., because new will change in the same
systems use perchlorate-contaminated source water). direction).
UCMR 1 data include a sample of small systems; the Stage 1 results (entry - (benefits and costs will change
point maximums) indicate that no small systems would exceed 56 [micro]g/L in the same direction).
or 90 [micro]g/L and that one small system would exceed 18 [micro]g/L; it
is possible that there are additional small systems where the baseline
perchlorate is greater than the MCLs that are not captured in the national
extrapolation results.
The EPA assumed a uniform distribution of system population served across (benefits and costs
the entry points; the actual entry point service population could be will change in the same
greater than or less than the estimates. direction).
----------------------------------------------------------------------------------------------------------------
Benefits Analysis
----------------------------------------------------------------------------------------------------------------
The health risks and risk reductions are based on maximum recorded (benefits only).
concentration estimates and thus do not account for exposures to
concentrations greater than or less than this recorded maximum.
The EPA assumed that baseline fT4 is equal to the median, which likely - (benefits only).
underestimates disease benefits as the logarithmic relationship between
maternal fT4 and child IQ leads to larger relative changes in fT4, with
increasing levels of perchlorate and lower levels of baseline fT4.
The EPA assumed a median TSH feedback loop strength for the exposed (benefits only).
population does not incorporate the variability in the feedback mechanism
of the body's creation of TSH in response to decreasing fT4.
The EPA used a 90th percentile water intake rate to derive the MCLG and the + (benefits only).
dose-response equations for the benefits analysis. This approach results
in a protective MCLG value, but may overstate intake for the benefits
analysis \2\.
The IQ valuation uses estimates that the EPA derived using the same (benefits only).
approach as Salkever (1995). Results from other IQ valuation studies might
result in higher or lower benefit estimates.
The benefits analysis is based on a single health endpoint and the value of - (benefits only).
the endpoint is based solely on lost earnings.
----------------------------------------------------------------------------------------------------------------
Cost Analysis
----------------------------------------------------------------------------------------------------------------
The EPA assumed that systems requiring treatment would incorporate a safety + (benefits and costs will change
factor--treating to 80% of the proposed MCL or alternative MCL, which in the same direction).
increases costs and benefits.
The EPA assumed that all entry points requiring treatment would implement (costs only).
ion exchange, which may overestimate costs if non-treatment is an option
for one or more entry points or underestimate costs if site-specific
conditions result in higher costs at one or more entry points.
The EPA developed a monitoring schedule that assumed a uniform distribution (costs only).
of initial monitoring costs over three years; actual costs will vary.
The EPA assumed that long-term monitoring costs would occur in the last - (costs only).
year of the applicable three-year monitoring period or nine-year
monitoring cycle; systems may conduct monitoring in an earlier year of the
period or cycle.
The EPA assumed that 90% of ground water systems and 40% of surface water (costs only).
systems obtain perchlorate monitoring waivers; the actual percentages may
vary.
----------------------------------------------------------------------------------------------------------------
\1\ A ``-'' symbol indicates that benefits and/or costs will tend to be underestimated. A ``+'' symbol indicates
that benefits and/or costs will tend to be overestimated. A ``'' symbol indicates an unknown
direction of uncertainty, i.e., benefits and/or costs could be underestimated or overestimated.
\2\ The EPA did not include a perchlorate dietary dose in the benefits analysis, which would be unchanged
between baseline and proposed MCL scenarios if many areas do not irrigate with drinking water. For people who
obtain a significant portion of their fruit, vegetables, and milk from areas irrigated with the water from the
same sources as the drinking water, we would expect their exposure may drop with the reduction of perchlorate
in food products used locally. Because of this and the natural log form of the IQ response function, this
approach may slightly understate the avoided IQ decrement estimates.
The EPA acknowledges the uncertainty regarding the quantitative
health risk reduction. In particular, the Agency assumed it could
estimate risk reductions based on evidence of a quantifiable
relationship between thyroid hormone changes and neurodevelopmental
outcomes.
[[Page 30557]]
There are a number of potential benefits of reducing perchlorate in
drinking water that were not quantified as part of this analysis, which
may result in an underestimate of actual benefits. As described by the
SAB ``children exposed gestationally to maternal hypothyroxinemia
(without hypothyroidism) show reduced levels of global and specific
cognitive abilities, as well as increased rates of behavior problems
including greater dysregulation in early infancy and attentional
disorders in childhood (Man et al., 1991; Pop et al., 1999; Pop et al.,
2003; Kooistra et al., 2006)'' (p. 10, SAB for the U.S. EPA, 2013). The
EPA's literature review identified potential relationships between
maternal thyroid hormone alterations and the risk of schizophrenia,
ADHD, expressive language delay, reduced school performance and
increased odds of autism, among others, none of which are being
currently quantified in this assessment. Other potentially omitted
benefits include risks associated with effects of thyroid disorders in
adults, including cardiovascular disease risk; changes in thyroid
hormone levels and their relationship with total cholesterol, LDL
cholesterol, and triglycerides; as well as a possible relationship
between increases in TSH and risk of fatal coronary heart disease.
Treating for perchlorate in drinking water could also potentially
remove nitrate, which is a co-occurring contaminant and a goitrogen.
These additional potential health endpoints are not monetized in this
benefits analysis. The assumptions used to account for the previously
mentioned variability of the BBDR model inputs and uncertainty
surrounding the relationship between maternal fT4 and child IQ
discussed above may result in an overestimate of the monetized
benefits. Because IQ is a surrogate for broad range of potential
neurodevelopmental risks, it is unclear whether the analysis as a whole
over- or under-estimates the monetized benefits of a reduction of
perchlorate in drinking water.
XIV. Request for Comment on Proposed Rule
While all comments relevant to the national primary drinking water
regulation for perchlorate proposed today will be considered by the
EPA, comments on the following issues will be especially helpful to the
EPA in developing a final rule. The EPA specifically requests comment
on the following topics.
The adequacy and uncertainties of the BBDR model developed
by the EPA to predict thyroid hormone level changes caused by
perchlorate exposure to pregnant women with low iodide intake,
including the model and model parameters and assumptions (Section III
and Approaches Report).
The adequacy and uncertainties of the EPA's review and
application of the epidemiologic literature to quantify the
relationship between thyroid hormone changes in pregnant women and
neurodevelopmental effects including the assumptions, the selection of
the approach used, and the study used (Section III and Approaches
Report).
The adequacy and uncertainties of the methodology to
derive the MCLG including points of departure, assumptions, uncertainty
factor, and relative source contribution (Section III and Technical
Support Document: Deriving a Maximum Contaminant Level Goal for
Perchlorate in Drinking Water).
The proposed MCLG and MCL of 56 [micro]g/L as well as the
alternative MCLG and MCL values of 18 [micro]g/L and of 90 [micro]g/L.
The feasibility of the proposed MCL of 56 [micro]g/L as
well as the feasibility of the alternative MCLs of 18 [micro]g/L and 90
[micro]g/L.
The adequacy of the underlying assumptions and analysis of
occurrence (Section VI).
The costs and availability of Treatment Technologies
(Section X).
The adequacy of the underlying estimates, assumptions and
analysis used to estimate costs and describe unquantified costs
including the estimates of monitoring frequency, likelihood of systems
receiving a monitoring waiver, the administrative labor rate and the
operator labor rate. (Section XII and the Health Risk Reduction Cost
Analysis).
The adequacy of the underlying estimates, assumptions and
analysis used to estimate benefits and describe unquantified benefits
(Section XII and the Health Risk Reduction Cost Analysis).
Potential implementation challenges associated with the
proposed perchlorate regulation that the EPA should consider,
specifically for small systems.
The Administrator's finding in accordance with Section
1412(b)(4)(C) of the SDWA that the benefits of the proposed 56
[micro]g/L MCL for perchlorate do not justify the costs, and the
information that supports that determination as described in Section
XII of this notice.
The Administrator's proposal to, consistent with the
discretion afforded him by SDWA Section 1412(b)(6)(A), adopt an MCL of
56 [micro]g/L notwithstanding the Agency's SDWA Section 1412(b)(4)(C)
determination that the benefits of the MCL would not justify its costs.
The Agency's conclusion that no alternative MCL, including
the alternative MCL values of 18 [micro]g/L and 90 [micro]g/L discussed
above, would ``maximize health risk reduction benefits at a cost that
is justified by the benefits'' and the information and analytical
approaches used to arrive at that conclusion. The EPA is especially
interested in comments suggesting other approaches to deriving an MCL
for which the benefits justify the costs.
XV. Request for Comment on Potential Regulatory Determination
Withdrawal
The EPA is soliciting comments on withdrawing the 2011 Regulatory
Determination (see Section II-C, Regulatory History) based on several
factors. First, the findings, described in the occurrence section
(section VI) and in the updated health effects assessment (Section
III), suggest that perchlorate does not occur in public water systems
with a frequency and at levels of public health concern \17\ and
suggest that the regulation of perchlorate does not present a
meaningful opportunity for health risk reduction for persons served by
public water systems. The proposed regulation would require over sixty
thousand public water systems to monitor for perchlorate, but the
available data indicates that very few would find it at levels of
public health concern. Specifically, perchlorate occurrence information
suggests that at an MCL of 56 [micro]g/L only 2 systems (0.004% of all
water systems in the U.S.) would exceed the regulatory threshold. Even
at an MCL of 18 [micro]g/L, there would only be 15 systems (0.03% of
all water systems in the U.S.) that would exceed the regulatory
threshold. Only one system would exceed the alternative MCL of 90
[micro]g/L.
---------------------------------------------------------------------------
\17\ As shown in Section VI of this notice there is infrequent
occurrence of perchlorate at either 56 [micro]g/L, 18 [micro]g/L or
90 [micro]g/L, which are the possible levels expected to cause
adverse human health effects.
---------------------------------------------------------------------------
The EPA notes that in 2008, the EPA stated in its preliminary
regulatory determination that perchlorate did not occur with a
frequency and at levels of public health concern in public water
systems based upon the health effects and occurrence information
available at that time, which indicated that 0.8% of public water
system had perchlorate at levels exceeding the HRL of 15 [micro]g/L.
The EPA also stated that there was not a meaningful opportunity for a
NPDWR to reduce health risks based upon the estimates at that time that
0.9 million
[[Page 30558]]
people had perchlorate levels above the HRL.
The EPA further notes that the Agency has previously determined
CCL1 and CCL2 contaminants did not occur with frequency at levels of
public health concern when the percentage of water systems exceeding
the HRL were greater than the frequency of perchlorate occurrence level
at the proposed MCL (0.004% of all water systems in the U.S.). For
example, in 2003 the EPA determined that aldrin did not occur with a
frequency and at levels of public health concern based upon data that
showed 0.2% of water systems had aldrin at levels greater than the HRL.
The EPA also concluded that there was not a meaningful opportunity for
health risk reduction for persons served through a drinking water
regulation based on this occurrence data and the estimate that these
systems above the HRL served approximately 1 million people (USEPA,
2003). In 2008 the EPA determined that DCPA Mono- and Di-Acid
degradates did not occur with a frequency and at levels of public
health concern based on data that showed 0.03% of water systems
exceeded the HRL. The EPA also included that there was not a meaningful
opportunity for health risk reduction through a drinking water
regulation based on this occurrence data and the estimate that these
systems above the HRL served approximately 100,000 people (USEPA,
2008e).
SDWA Section 1412(b)(1)(A)(iii) states that the determination
regarding the meaningful opportunity is ``in the sole judgement of the
Administrator'' and therefore there may be other factors that
contribute to this determination for any given contaminant.
If, after consideration of public comment, the EPA withdraws the
perchlorate regulatory determination, there will be no NPDWR for
perchlorate, although the EPA can re-list perchlorate on the CCL and
proceed to regulation in the future if the occurrence or risk
information changes. As with other unregulated contaminants, the EPA
could address the limited instances of elevated levels of perchlorate
by working with the states or using its SDWA Section 1431 imminent and
substantial endangerment or Section 1412(b)(1)(f) health assessment
authorities, as appropriate. The EPA also requests comments on what
guidance it could provide the public if the regulatory determination
for perchlorate is withdrawn.
XVI. Statutory and Executive Order Reviews
A. Executive Order 12866: Regulatory Planning and Review and Executive
Order 13563: Improving Regulation and Regulatory Review
This action is a significant regulatory action since it raises
novel legal or policy issues. It was submitted to the Office of
Management and Budget (OMB) for review. Any changes made in response to
OMB recommendations have been documented in the docket.
The EPA evaluated the potential costs to States and utilities and
the potential benefits of the proposed rule. This analysis, Health Risk
Reduction Cost Analysis of the Proposed Perchlorate Rule (USEPA, 2019a)
is available in the docket and is summarized in section XI.
B. Executive Order 13771: Reducing Regulations and Controlling
Regulatory Costs
This action is expected to be an Executive Order 13771 regulatory
action. Details on the estimated costs of this proposed rule can be
found in the EPA's analysis of the potential costs and benefits
associated with this action.
C. Paperwork Reduction Act
The information collection requirements in this proposed rule have
been submitted for approval to the Office of Management and Budget
(OMB) under the Paperwork Reduction Act, 44 U.S.C. 3501 et seq. The
information collection requirements are not enforceable until OMB
approves them.
The monitoring information collected as a result of this rule will
allow the States and the EPA to evaluate compliance with the rule. For
the first 3-year period following rule promulgation, the major
information requirements concern primacy agency activities to implement
the rule including adopting the NPDWR into state regulations, providing
training to state and PWS employees, updating their monitoring data
systems, and reviewing system monitoring data and waiver requests.
Compliance actions for drinking water systems (including monitoring,
administration, and treatment costs) would not begin until after Year 3
due to the proposed effective date of this rule.
The estimate of annual average burden hours for the proposed rule
during the first three years following promulgation is 48,539 hours.
The annual average cost estimate is $7.4 million for labor. The burden
hours per response is 2,648 hours and the cost per response is
$134,159. The frequency of response (average responses per respondent)
is 1 for primacy agencies, annually (for upfront administrative
activities to implement the rule). The estimated number of likely
respondents is 55 over the three-year period (for an average of 18.3
each year).
Burden means the total time, effort, or financial resources
expended by persons to generate, maintain, retain, or disclose or
provide information to or for a federal agency. This includes the time
needed to review instructions; develop, acquire, install, and utilize
technology and systems for the purposes of collecting, validating, and
verifying information, processing and maintaining information, and
disclosing and providing information; adjust the existing ways to
comply with any previously applicable instructions and requirements;
train personnel to be able to respond to a collection of information;
search data sources; complete and review the collection of information;
and transmit or otherwise disclose the information.
An agency may not conduct or sponsor, and a person is not required
to respond to a collection of information unless it displays a
currently valid OMB control number. The OMB control numbers for the
EPA's regulations are listed in 40 CFR part 9.
Submit your comments on the Agency's need for this information, the
accuracy of the provided burden estimates, and any suggested methods
for minimizing respondent burden, including the use of automated
collection techniques, to the EPA at the public docket established for
this rule, which includes the ICR, Docket ID No. EPA-HQ-OW-2018-0780.
You may also send your ICR-related comments to OMB's Office of
Information and Regulatory Affairs via email to
[email protected], Attention: Desk Officer for the EPA. Since
OMB is required to make a decision concerning the ICR between 30 and 60
days after receipt, OMB must receive comments no later than [INSERT
DATE 30 DAYS AFTER DATE OF PUBLICATION IN THE FEDERAL REGISTER]. The
EPA will respond to any ICR-related comments in the final rule.
D. Regulatory Flexibility Act (RFA)
I certify that this action will not have a significant economic
impact on a substantial number of small entities under the RFA. The
Agency has determined that the proposed MCL of 56 [micro]g/L will not
result in annual costs that exceed one percent of revenue for small
systems affected by the proposed rule.
The small entities subject to the requirements of this action are
public
[[Page 30559]]
water systems serving 10,000 or fewer persons. This is the threshold
specified by Congress in the 1996 Amendments to the Safe Drinking Water
Act for small system flexibility provisions. In accordance with the RFA
requirements, the EPA proposed using this alternative definition in the
Federal Register, (63 FR 7620, February 13, 1998), requested public
comment, consulted with the Small Business Administration (SBA), and
expressed its intention to use the alternative definition for all
future drinking water regulations in the Consumer Confidence Reports
regulation (63 FR 44511, August 19, 1998). As stated in that final
rule, the alternative definition is applied to this proposed
regulation.
The proposed rule contains provisions that would affect 58,325 CWS
and NTNCWS serving 10,000 or fewer people. In order to meet the
proposed rule requirements, all of these systems will need to conduct
perchlorate monitoring. At the proposed MCL of 56 [micro]g/L, the UCMR
1 monitoring data indicate that no small systems would be required to
incur costs to reduce the levels of perchlorate in drinking water,
therefore, all small PWSs will incur monitoring costs only. Impacts on
small entities are described in more detail in Chapter 7 of the Health
Risk Reduction Cost Analysis of the Proposed Perchlorate Rule (USEPA,
2019a). Table XII-1 and Table XII-2 show the annual compliance costs of
the proposed rule on the small entities by system size for public and
private systems, respectively. Based on a comparison of annual costs
with annual revenue estimates, the EPA has determined that no small
systems will experience an impact of one percent or greater of average
annual revenues (USEPA 2019a).
Table XII-1--Annualized Monitoring and Administrative Costs as a Percentage of Average Annual Revenue for Small
Public CWSs by Size Category
----------------------------------------------------------------------------------------------------------------
Average
Size category annual 3% Discount 7% Discount
revenues \a\ \b\ \b\
----------------------------------------------------------------------------------------------------------------
Population served <100.......................................... $224,248 $88 (0.04%) $94 (0.04%)
Population served 101-500....................................... 197,315 88 (0.04%) 94 (0.05%)
Population served 501-3,300..................................... 202,382 88 (0.04%) 94 (0.05%)
Population served 3,301-10,000.................................. 1,092,187 88 (0.01%) 94 (0.01%)
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
0780).
\a\ Based on the CWSS (USEPA, 2009c Table 65) and updated to 2017$ based on the chained consumer price index for
fuels and utilities in U.S. city average, all urban consumers (BLS, 2018a). Revenues include all sources of
revenue including water revenue, non-water revenue, and municipal transfers to water systems.
\b\ Total annual monitoring and administrative costs for PWSs are approximately $6.6 million to $7.1 million
annually (Exhibit 5 5), with $5.1 million to $5.5 million accruing to small PWSs. Based on 58,325 small
systems, this yields an average annual per-system cost of $88 (3% discount rate) to $94 (7% discount rate).
Table XII-2--Annualized Monitoring and Administrative Costs as a Percentage of Average Annual Revenue for Small
Private CWSs by Size Category
----------------------------------------------------------------------------------------------------------------
Average
Size category annual 3% Discount 7% Discount
revenues \a\ \b\ \b\
----------------------------------------------------------------------------------------------------------------
Population served <100.......................................... $139,911 $88 (0.06%) $94 (0.07%)
Population served 101-500....................................... 351,974 88 (0.03%) 94 (0.03%)
Population served 501-3,300..................................... 254,706 88 (0.03%) 94 (0.03%)
Population served 3,301-10,000.................................. 951,692 88 (0.01%) 94 (0.01%)
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
0780)
\a\ Based on the CWSS (USEPA, 2009c Table 65) and updated to 2017$ based on the chained consumer price index for
fuels and utilities in U.S. city average, all urban consumers (BLS, 2018a). Revenues include all sources of
revenue including water revenue and non-water revenue.
\b\ Total annual monitoring and administrative costs for PWSs are approximately $6.6 million to $7.1 million
annually (Exhibit 5 5), with $5.1 million to $5.5 million accruing to small PWSs. Based on 58,325 small
systems, this yields an average annual per-system cost of $88 (3% discount rate) to $94 (7% discount rate).
E. Unfunded Mandates Reform Act
This action does not contain an unfunded mandate of $100 million or
more as described in UMRA, 2 U.S.C. 1531-1538. The action imposes
minimal enforceable duty on any state, local or tribal governments or
the private sector.
Based on the cost estimates detailed in Section XI, the EPA
determined that compliance costs in any given year would be below the
threshold set in UMRA, with maximum single-year costs of approximately
$10.2 million. The EPA has determined that this rule contains a federal
mandate that would not result in expenditures of $100 million or more
for State, local, and Tribal governments, in the aggregate, or the
private sector in any one year.
F. Executive Order 13132: Federalism
This action does not have federalism implications. It will not have
substantial direct effects of greater than $25 million 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. Annual costs are estimated to range from $9.6
million at a 3 percent discount rate to $10.2 million using a 7
percent, with $6.5 million to $7.0 million annually accruing to public
entities. The EPA has concluded that this proposed rule may be of
interest because it may impose direct compliance costs on State or
local governments, and the federal government will not provide the
funds necessary to pay those costs.
G. Executive Order 13175: Consultation and Coordination With Indian
Tribal Governments
The EPA has concluded that this proposed rule may have Tribal
implications, because it may impose direct compliance costs on Tribal
governments, and the federal government would not provide the
[[Page 30560]]
funds necessary to pay those costs. The EPA has identified 768 water
systems with 1,167 entry points under Native American ownership that
may be subject to the proposed rule. They would bear an estimated total
annualized cost of $74,100 at a 3 percent discount rate ($79,625 at 7
percent) to implement this rule as proposed, with all costs
attributable to monitoring and administrative costs. Estimated average
annualized cost per system ranges from $96 at a 3 percent discount rate
to $104 at a 7 percent discount rate.
Accordingly, the EPA provides the following Tribal summary impact
statement as required by section 5(b) of Executive Order 13175. The EPA
consulted with representatives of Tribal officials early in the process
of developing this proposed regulation to permit them to have
meaningful and timely input into its development. The EPA conducted
consultation with Indian Tribes which included a webinar with
interested tribes on February 28, 2012, to request input and provide
rulemaking information to interested parties. A meeting summary report
is available on the docket for public inspection (USEPA 2012a). The EPA
notes that 751 of the 768 Tribal systems identified by the Agency as
subject to the proposed rule are small systems that are expected to
incur only monitoring costs. Due to the health risks associated with
perchlorate, capital expenditures needed for compliance with the rule
would be eligible for federal funding sources, specifically the
Drinking Water State Revolving Fund. In the spirit of Executive Order
13175, and consistent with the EPA policy to promote communications
between the EPA and Tribal governments, the EPA specifically solicits
additional comment on this proposed rule from Tribal officials.
H. Executive Order 13045: Protection of Children From Environmental
Health and Safety Risks
This action is not subject to Executive Order 13045 because it is
not economically significant as defined in Executive Order 12866;
however, the environmental health risk addressed by this action may
have a disproportionate effect on children. Accordingly, the EPA
evaluated the environmental health or safety effects of perchlorate on
children. The results of this evaluation are contained in the Health
Effects Technical Support Document (USEPA 2018a) and described in
section III of this preamble. The EPA has evaluated the risk associated
with perchlorate in drinking water for the sensitive subpopulation--
offspring of pregnant women exposed to perchlorate during the first
trimester--and established a proposed MCLG that is protective of this
subpopulation as well as other children. The EPA also estimated the
health risk reduction of the proposed and alternative MCLs. This
analysis is described in the Health Risk Reduction and Cost Analysis
for the proposed rule (USEPA 2019a) and is summarized in section XI of
this preamble. Copies of the Health Effects Technical Support Document
and Economic Analysis and supporting information are available in the
public docket for today's proposal.
I. Executive Order 13211: Actions That Significantly Affect Energy
Supply, Distribution, or Use
This rule is not a ``significant energy action'' as defined in
Executive Order 13211, ``Actions Concerning Regulations That
Significantly Affect Energy Supply, Distribution, or Use'' (66 FR 28355
(May 22, 2001)) because it is not likely to have a significant adverse
effect on the supply, distribution, or use of energy. This
determination is based on the following analysis.
The first consideration is whether the proposed rule would
adversely affect the supply of energy. The proposed rule does not
regulate power generation, either directly or indirectly. The public
and private water systems that the proposed rule regulates do not
generate power. Further, the cost increases borne by customers of water
utilities as a result of the proposed rule are a low percentage of the
total cost of water, except for a few water systems that might install
treatment technologies and would likely spread that cost over their
customer base. In sum, the proposed rule does not regulate the supply
of energy, does not generally regulate the utilities that supply
energy, and is unlikely to affect significantly the customer base of
energy suppliers. Thus, the proposed rule would not translate into
adverse effects on the supply of energy.
The second consideration is whether the proposed rule would
adversely affect the distribution of energy. The proposed rule does not
regulate any aspect of energy distribution. The water systems that are
regulated by the proposed rule already have electrical service. At the
proposed MCL, one entry point at one system may require incremental
power to operate new treatment processes. The increase in peak
electricity demand at water utilities is negligible. Therefore, the EPA
estimates that the existing connections are adequate and that the
proposed rule has no discernable adverse effect on energy distribution.
The third consideration is whether the proposed rule would
adversely affect the use of energy. Because only one system is expected
to add treatment technologies that use electrical power, this potential
impact on sector demand or overall national demand for power is
negligible.
Based on its analysis of these considerations, the EPA has
concluded that proposed rule is not likely to have a significant
adverse effect on the supply, distribution, or use of energy.
J. National Technology Transfer and Advancement Act of 1995 and 1 CFR
Part 51
The proposed rule could involve voluntary consensus standards in
that it would require monitoring for Perchlorate. The EPA proposed five
analytical methods for the identification and quantification of
perchlorate in drinking water. The EPA methods 314.0, 314.1, 314.2,
331.0, and 332.0 incorporate quality control criteria which allow
accurate quantitation of perchlorate. Additional information about the
analytical methods is available in section VII of this notice. The EPA
has made, and will continue to make, these documents generally
available through www.regulations.gov and at the U.S. Environmental
Protection Agency Drinking Water Docket, William Jefferson Clinton West
Building, 1301 Constitution Ave. NW, Room 3334, Washington, DC 20460,
call (202) 566-2426.
The EPA's monitoring and sampling protocols generally include
voluntary consensus standards developed by agencies such as ASTM
International, Standard Methods and other such bodies wherever the EPA
deems these methodologies appropriate for compliance monitoring. The
EPA welcomes comments on this aspect of the proposed rulemaking and,
specifically, invites the public to identify potentially-applicable
voluntary consensus standards and to explain why such standards should
be used in this regulation. The Director of the Federal Register
approved the voluntary consensus standards incorporated by referenced
in Sec. 141.23 of the proposed regulatory text as of April 11, 2007.
K. Executive Order 12898: Federal Actions To Address Environmental
Justice in Minority Populations and Low-Income Populations
The EPA has determined that this proposed rule would not have
disproportionately high and adverse
[[Page 30561]]
human health or environmental effects on minority or low-income
populations because it would increase 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 public is invited to comment on this aspect of the proposed
rulemaking and, specifically, to recommend additional methods to
address Environmental Justice concerns from establishing a drinking
water rule for perchlorate in drinking water.
XVII. Consultations With the Science Advisory Board, National Drinking
Water Advisory Council, and the Secretary of Health and Human Services
In accordance with sections 1412(d) and 1412(e) of the Safe
Drinking Water Act (SDWA), the Agency consulted with the National
Drinking Water Advisory Council (NDWAC or the Council); the Secretary
of Health and Human Services; and with the EPA Science Advisory Board.
The Agency consulted with NDWAC during the Council's October 4-5, 2012
meeting. A summary of the NDWAC recommendations is available in the
National Drinking Water Advisory Council, Fall 2012 Meeting Summary
Report (NDWAC, 2012b) and the docket for this proposed rule. The EPA
carefully considered NDWAC recommendations during the development of a
proposed drinking water rule for perchlorate.
On May 29, 2012, the EPA sought guidance from the EPA Science
Advisory Board (SAB) on how best to consider and interpret life stage
information, epidemiological and biomonitoring data since the
publication of the National Research Council 2005 report, the Agency's
physiologically-based pharmacokinetic (PBPK) analyses, and the totality
of perchlorate health information to derive a Maximum Contaminant Level
Goal (MCLG) for perchlorate (USEPA, 2012; NRC, 2005). On May 29, 2013,
the EPA received significant input from SAB, summarized in the report,
SAB Advice on Approaches to Derive a Maximum Contaminant Level Goal for
Perchlorate (USEPA, 2013a).
On July 15, 2013, the EPA responded by stating that the Agency
would consider all the recommendations from the SAB, as it continued
working on the development of the rulemaking process for perchlorate
(USEPA 2013b). To address SAB recommendations, the EPA collaborated
with Food and Drug Administration (FDA) scientists to develop PBPK/
pharmacodynamic (PD), or biologically based dose-response (BBDR),
models that incorporate all available health related information on
perchlorate to predict changes in thyroid hormones in sensitive life
stages exposed to different dietary iodide and perchlorate levels
(USEPA 2017). As recommended by SAB, the EPA developed these models
based upon perchlorate's mode of action (i.e., iodide uptake inhibition
by the thyroid) (USEPA 2013a). Additional details are in section III.C.
of this notice and in the Health Effects of Perchlorate support
document located in the docket for this proposed rule.
In accordance with SAB recommendations, the EPA developed a two-
stage approach to integrate BBDR model results with data on
neurodevelopmental outcomes from epidemiological studies, this approach
allowed the Agency to link maternal thyroid hormones levels as a result
of low iodine intake and perchlorate exposure, to derive an MCLG that
directly addresses the most sensitive life stage (USEPA 2013a).
On March 25, 2019, the EPA consulted with the Department of Health
and Human Services (HHS). The EPA provided information to HHS officials
on the draft proposed perchlorate regulation and considered HHS input
as part of the interagency review described in section XVII.A.
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USEPA. (2002). A review of the reference dose and reference
concentration process.
USEPA (2003). Contaminant Candidate List Regulatory Determination
Support Document for Aldrin and Dieldrin. EPA-815-R-03-010. https://www.epa.gov/sites/production/files/2014-09/documents/support_cc1_aldrin-dieldrin_ccl_regdet.pdf.
USEPA. (2004). The Standardized Monitoring Framework: A Quick
Reference Guide. EPA-816-F-04-010.
USEPA. (2005a). Integrated Risk Information System (IRIS) Chemical
Assessment Summary: Perchlorate (ClO4-) and Perchlorate Salts. USEPA
National Center for Environmental Assessment.
USEPA. (2005b, May). Perchlorate Treatment Technology Update:
Federal Facilities Forum Issue Paper. Office of Solid Waste and
Emergency Response. EPA 542-R-05-015.
USEPA. (2008a). Drinking water: Preliminary regulatory determination
on perchlorate. Federal Register, 73 (198).
USEPA. (2008b, June). Draft Information Collection Request for the
Disinfectants/Disinfection Byproducts, Chemical, and Radionuclides
Rule.
USEPA. (2008c, November 12). National Ambient Air Quality Standards
for Lead. 73 FR 66964, p. 66964-67062. Retrieved from https://www.federalregister.gov/articles/2008/11/12/E8-25654/national-ambient-air-quality-standards-for-lead.
USEPA (2008d). Interim Drinking Water Health Advisory for
Perchlorate. Retrieved from: https://nepis.epa.gov/Exe/ZyPDF.cgi/P1004X7Q.PDF?Dockey=P1004X7Q.PDF.
USEPA. (2008e). Regulatory Determinations Support Document for
Selected Contaminants from the Second Drinking Water Contaminant
Candidate List (CCL 2). EPA-815-R-03-010. https://www.epa.gov/sites/production/files/2014-09/documents/chapter_4_dcpa_mono-_and_di-acid_degradates.pdf.
USEPA. (2009a). Drinking Water: Perchlorate Supplemental Request for
Comments.
USEPA. (2009b). Inhibition of the Sodium-Iodide Symporter By
Perchlorate: An Evaluation of Lifestage Sensitivity Using
Physiologically Based Pharmacokinetic (PBPK) Modeling (Final Report)
(EPA/600/R-08/106A). Washington, DC.
USEPA. (2009c, May). 2006 Community Water System Survey--Volume II:
Detailed Tables and Survey Methodology. Retrieved from https://www.epa.gov/dwstandardsregulations/community-water-system-survey.
USEPA. (2011a). Drinking Water: Regulatory Determination on
Perchlorate. Federal Register Notice. 76 FR No. 29. Pages 7762-7767.
(February 11, 2011) (to be codified at 40 CFR pt. 141). Retrieved
from https://www.federalregister.gov/articles/2011/02/11/2011-2603/drinking-water-regulatory-determination-on-perchlorate.
USEPA. (2011b). Exposure Factors Handbook 2011 Edition (Final
Report) (p. Chapter 8). Retrieved from https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=236252.
USEPA. (2011c). Labor Cost for National Drinking Water Rules.
USEPA. (2012). Benchmark dose technical guidance.
USEPA. (2012a). Perchlorate Tribal Stakeholder Meeting Summary.
February 28, 2012.
USEPA. (2017). Biologically Based Dose Response Models for the
Effect of Perchlorate on Thyroid Hormones in the Infant, Breast
Feeding Mother, Pregnant Mother, and Fetus: Model Development,
Revision, and Preliminary Dose-Response Analyses. (T.L. Paul
Schlosser and Santhini Ramasamy, Ed.). Peer Review Draft.
USEPA. (2017). Draft Report: Proposed Approaches to Inform the
Derivation of a Maximum Contaminant Level Goal for Perchlorate in
Drinking Water.
USEPA. (2018a). Best Available Technologies and Small System
Compliance Technologies for Perchlorate in Drinking Water. EPA 816-
R-19-006.
USEPA. (2018b). Proposed Approaches to Inform the Derivation of a
Maximum Contaminant Level Goal for Perchlorate in Drinking Water.
EPA 816-R-19-008.
USEPA. (2018c). Technologies and Costs for Treating Perchlorate-
Contaminated Waters. EPA 816-R-19-005.
USEPA. (2019a). Health Risk Reduction and Cost Analysis of the
Proposed Perchlorate National Primary Drinking Water Regulation. EPA
816-R-19-004.
USEPA. (2019b). Perchlorate Occurrence and Monitoring Report. EPA
816-R-19-003.
USEPA. (2019c). Technical Support Document: Deriving a Maximum
Contaminant Level Goal for Perchlorate in Drinking Water. EPA 816-R-
19-007.
van Den Hove, M.F., Beckers, C., Devlieger, H., De Zegher, F., & De
Nayer, P. (1999). Hormone synthesis and storage in the thyroid of
human preterm and term newborns: Effect of thyroxine treatment.
Biochimie, 81(5), 563-570.
van Mil, N.H., Steegers-Theunissen, R.P.M., Bongers-Schokking, J.J.,
El Marroun, H., Ghassabian, A., Hofman, A., . . . Tiemeier, H.
(2012). Maternal hypothryoxinemia during pregnancy and growth of the
fetal and infant head. Reproductive Sciences, 19(12), 1315-1322.
https://doi.org/10.1177/1933719112450338.
Wang, P., Gao, J., Zhao, S., Guo, Y., Wang, Z., & Qi, F. (2016).
Maternal thyroxine levels during pregnancy and outcomes of cognitive
development in children. Molecular Neurobiology, 53(4), 2241-2248.
https://doi.org/10.1007/s12035-015-9189-z.
Webster, T.D., & Crowley, T.J. (2010, November). Full-Scale
Implementation of a Biological Fluidized Bed Drinking Water
Treatment Plant for Nitrate and Perchlorate Treatment. Presented at
the 2010 Water Education Foundation Water Quality and Regulatory
Conference, Ontario, CA.
Webster, T.D., & Crowley, T.J. (2016, June). Biological treatment of
perchlorate in groundwater. Presented at the AWWA Annual Conference
and Exposition.
Webster, T.D., & Litchfield, M.H. (2017). Full-scale biological
treatment of nitrate and perchlorate for potable water production.
Journal AWWA, 109(5), 30-40.
Wu, X., & Blute, N.K. (2010, March). Perchlorate Removal Using
Single-Pass Ion Exchange Resin--Pilot Testing Purolite A532E at the
San Gabriel B6 Plant. Presented at the 2010 California-Nevada AWWA
Spring Conference, Hollywood, CA.
Yoon, J., Amy, G., & Yoon, Y. (2005). Transport of target anions,
chromate (Cr (VI)), arsenate (As (V)), and perchlorate (ClO4),
through RO, NF, and UF membranes. Water Science and Technology,
51(6-7), 327-334.
[[Page 30565]]
Yoon, J., Yoon, Y., Amy, G., & Her, N. (2005). Determination of
perchlorate rejection and associated inorganic fouling (scaling) for
reverse osmosis and nanofiltration membranes under various operating
conditions. Journal of Environmental Engineering, 726-733.
Zhang, X., Yao, B., Li, C., Mao, J., Wang, W., Xie, X., . . . Shan,
Z. (2016). Reference intervals of thyroid function during pregnancy:
self-sequential longitudinal study versus cross-sectional study.
Thyroid, 26(12), 1786-1793. https://doi.org/10.1089/thy.2016.0002.
List of Subjects
40 CFR Part 141
Chemicals, Incorporation by reference, Indians--lands,
Intergovernmental relations, Radiation protection, Reporting and
recordkeeping requirements, Water supply.
40 CFR Part 142
Administrative practice and procedure, Chemicals, Indians--lands,
Radiation protection, Reporting and recordkeeping requirements, Water
supply.
Dated: May 23, 2019.
Andrew R. Wheeler,
Administrator.
For the reasons stated in the preamble, the Environmental
Protection Agency proposes to amend 40 CFR parts 141 and 142 as
follows:
PART 141--NATIONAL PRIMARY DRINKING WATER REGULATIONS
0
1. The authority citation for part 141 continues to read as follows:
Authority: 42 U.S.C. 300f, 300g-1, 300g-2, 300g-3, 300g-4,
300g-5, 300g-6, 300j-4, 300j-9, and 300j-11.
0
2. Amend Sec. 141.6 by revising paragraph (a) and adding paragraph (l)
to read as follows:
Subpart A--General
Sec. 141.6 Effective dates.
(a) Except as provided in paragraphs (b) through (l) of this
section the regulations set forth in this part shall take effect on
June 24, 1977.
* * * * *
(l) The regulations contained in the revisions to Sec. Sec.
141.23(a)(4)(i), 141.23(a)(5), 141.23(c),141.23(f)(1), 141.23(i)(1)-
(2), 141.23(k)(1)-(3), 141.23(k)(3)(ii), 141.51(b), 141.60(b)(5),
141.62(b), 141.62(c), 141.62(e), Appendix A to Subpart O and Appendix A
and B to Subpart Q are effective for the purposes of compliance on
[DATE OF PUBLICATION OF FINAL RULE IN THE FEDERAL REGISTER].
0
3. Amend Sec. 141.23 by:
0
a. In paragraph (a)(4)(i) table:
0
i. Revising the table heading; and
0
ii. Adding an entry for ``Perchlorate'' in alphabetical order;
0
b. In paragraph (a)(5), after the text ``nickel,'' adding the text
``perchlorate,'';
0
c. In paragraph (c), after the text ``nickel,'' adding the text
``perchlorate,'';
0
d. Adding paragraph (c)(10);
0
e. In paragraph (f)(1), after the text ``nickel,'' adding the text
``perchlorate,'';
0
f. In paragraphs (i)(1) and (2), after the text ``nickel,'' adding the
text ``perchlorate,'';
0
g. Revising paragraph (i)(3);
0
h. In paragraph (k)(1):
0
i. Revising the introductory text; and
0
ii. In the table, adding the table designation, redesignating entries
21 through 26 as 22 through 27, and adding a new entry 21;
0
i. In paragraph (k)(2):
0
i. In the introductory paragraph, after the text ``nitrite,'' adding
the text ``perchlorate,''; and
0
ii. In the table, adding the table designation and adding, in
alphabetical order, an entry for ``Perchlorate'';
0
j. In paragraph (k)(3):
0
i. In the introductory paragraph, after the text ``nitrite'' adding the
text ``, perchlorate,''; and
0
ii. In paragraph (ii) table, adding the table designation, and adding
in alphabetical order, an entry for ``Perchlorate'';
The revisions and additions read as follows:
Subpart C--Monitoring and Analytical Requirements
Sec. 141.23 Inorganic chemical sampling and analytical requirements.
* * * * *
(a) * * *
(4) * * *
(i) * * *
Table 1 to Paragraph (a)(4)(i)-- Detection Limits for Inorganic Contaminants
[Composited samples]
----------------------------------------------------------------------------------------------------------------
Contaminant MCL (mg/l) Methodology Detection limit (mg/l)
----------------------------------------------------------------------------------------------------------------
* * * * * * *
Perchlorate.......................... 0.056 Ion Chromatography.......... 0.00053.
Inline Column Concentration/ 0.00003.
Matrix Elimination Ion
Chromatography with
Suppressed Conductivity
Detection.
Two-Dimensional Ion 0.000012-0.000018.
Chromatography with
Suppressed Conductivity
Detection.
Liquid Chromatography 0.000005 (Tandem Mass
Electrospray Ionization Spectrometry [MS/MS])
Mass Spectrometry. 0.000008 (Selected Ion
Monitoring [SIM]).
Ion Chromatography with 0.00002.
Suppressed Conductivity and
Electrospray Ionization
Mass Spectrometry.
* * * * * * *
----------------------------------------------------------------------------------------------------------------
* * * * *
(c) * * *
(10) Community water systems and non-transient non-community water
systems must conduct initial monitoring for perchlorate as follows:
(i) Community water systems serving greater than 10,000 persons
without acceptable historic data, as defined below, must collect four
consecutive quarterly samples at all sampling points between January 1,
2023 and December 31, 2025.
(ii) Community water systems serving 10,000 or fewer persons and
non-transient non-community water systems without acceptable historic
data, as defined below, must collect four consecutive quarterly samples
at all
[[Page 30566]]
sampling points between January 1, 2026 and December 31, 2028.
(iii) Grandfathering of data: States may allow historical
monitoring data collected at a sampling point to satisfy the initial
monitoring requirements for that sampling point, for the following
situations.
(A) To satisfy initial monitoring requirements, community water
systems serving greater than 10,000 persons having only one entry point
to the distribution system may use the monitoring data from the
compliance monitoring period between January 1, 2020 and December 31,
2022. Community water systems serving 10,000 or fewer persons and non-
transient non-community water systems having only one entry point to
the distribution system may use the monitoring data from the compliance
monitoring period between January 1, 2023 and December 31, 2025.
(B) To satisfy initial monitoring requirements, a system with
multiple entry points and having appropriate historical monitoring data
for each entry point to the distribution system may use the monitoring
data from the compliance monitoring period that began between January
1, 2020 and December 31, 2022, for community water systems serving
greater than 10,000 persons and between January 1, 2023 and December
31, 2025, for community water systems serving 10,000 or fewer persons
and for non-transient non-community water systems.
(C) To satisfy initial monitoring requirements, a system with
appropriate historical data for a representative point in the
distribution system may use the monitoring data from the compliance
monitoring period between January 1, 2020 and December 31, 2022, for
community water systems serving greater than 10,000 persons and between
January 1, 2023 and December 31, 2025, for community water systems
serving 10,000 or fewer persons and for non-transient non-community
water systems, provided that the State finds that the historical data
satisfactorily demonstrate that each entry point to the distribution
system is expected to be in compliance based upon the historical data
and reasonable assumptions about the variability of contaminant levels
between entry points. The State must make a written finding indicating
how the data conforms to these requirements.
(iv) The State may waive the final two quarters of initial
monitoring for perchlorate for a sampling point if the results of the
samples from the previous two quarters are below the detection limit.
* * * * *
(i) * * *
(3) Compliance with the maximum contaminant level for nitrate,
nitrite and perchlorate is determined based on one sample if the levels
of these contaminants are below the MCLs. If the level of perchlorate
exceeds the MCL in the initial sample, a confirmation sample is
required in accordance with paragraph (f)(1) of this section and
compliance shall be based on the average of the initial and
confirmation sample. If the levels of nitrate and/or nitrite exceed the
MCLs in the initial sample, a confirmation sample is required in
accordance with paragraph (f)(2) of this section and compliance shall
be based on the average of the initial and confirmation sample.
* * * * *
(k) * * *
(1) Analysis for the following contaminants shall be conducted in
accordance with the methods in the following table, or the alternative
methods listed in Appendix A to Subpart C of this part, or their
equivalent as determined by the EPA. Criteria for analyzing arsenic,
barium, beryllium, cadmium, calcium, chromium, copper, lead, nickel,
selenium, sodium, and thallium with digestion or directly without
digestion, and other analytical test procedures are contained in
Technical Notes on Drinking Water Methods, EPA-600/R-94-173, October
1994. This document is available from the National Service Center for
Environmental Publications (NSCEP), P.O. Box 42419, Cincinnati, OH
45242-0419 or http://www.epa.gov/nscep/.
Table 2 to Paragraph (k)(1)
--------------------------------------------------------------------------------------------------------------------------------------------------------
SM \4\
Contaminant Methodology \13\ EPA ASTM \3\ (18th, 19th SM \4\ SM Online Other
ed.) (20th ed.) \22\
--------------------------------------------------------------------------------------------------------------------------------------------------------
* * * * * * *
21. Perchlorate........................ Ion Chromatography............ \23\ 314.0
Inline Column Concentration/ \24\ 314.1
Matrix Elimination Ion
Chromatography with
Suppressed Conductivity
Detection.
Two-Dimensional Ion \25\ 314.2
Chromatography with
Suppressed Conductivity
Detection.
Liquid Chromatography \26\ 331.0
Electrospray Ionization Mass
Spectrometry.
Ion Chromatography with \27\ 332.0
Suppressed Conductivity and
Electrospray Ionization Mass
Spectrometry.
* * * * * * *
--------------------------------------------------------------------------------------------------------------------------------------------------------
\3\ Annual Book of ASTM Standards, ASTM International, 100 Barr Harbor Drive, West Conshohocken, PA 19428, http://www.astm.org.; Annual Book of ASTM
Standards 1994, Vols. 11.01 and 11.02; Annual Book of ASTM Standards 1996, Vols. 11.01 and 11.02; Annual Book of ASTM Standards 1999, Vols. 11.01 and
11.02; Annual Book of ASTM Standards 2003, Vols. 11.01 and 11.02.
\4\ Standard Methods for the Examination of Water and Wastewater, American Public Health Association, 800 I Street NW, Washington, DC 20001-3710;
Standard Methods for the Examination of Water and Wastewater, 18th edition (1992); Standard Methods for the Examination of Water and Wastewater, 19th
edition (1995); Standard Methods for the Examination of Water and Wastewater, 20th edition (1998).The following methods from this edition cannot be
used: 3111 B, 3111 D, 3113 B, and 3114 B.
[[Page 30567]]
\13\ Because MDLs reported in EPA Methods 200.7 and 200.9 were determined using a 2x preconcentration step during sample digestion, MDLs determined when
samples are analyzed by direct analysis (i.e., no sample digestion) will be higher. For direct analysis of cadmium and arsenic by Method 200.7, and
arsenic by Method 3120 B, sample preconcentration using pneumatic nebulization may be required to achieve lower detection limits. Preconcentration may
also be required for direct analysis of antimony, lead, and thallium by Method 200.9; antimony and lead by Method 3113 B; and lead by Method D3559-
90D, unless multiple in-furnace depositions are made.
* * * * * * *
\22\ Standard Methods Online, American Public Health Association, 800 I Street NW, Washington, DC 20001, available at http://www.standardmethods.org.
The year in which each method was approved by the Standard Methods Committee is designated by the last two digits in the method number. The methods
listed are the only online versions that may be used.
\23\ Determination of Perchlorate in Drinking Water Using Ion Chromatography (Revision 1.0, USEPA, 1999a).
\24\ Determination of Perchlorate in Drinking Water Using Inline Column Concentration/Matrix Elimination Ion Chromatography with Suppressed Conductivity
Detection (Revision 1.0, USEPA, 2005b).
\25\ Determination of Perchlorate in Drinking Water Using Two-Dimensional Ion Chromatography with Suppressed Conductivity Detection (USEPA, 2008c).
\26\ Determination of Perchlorate in Drinking Water by Liquid Chromatography Electrospray Ionization Mass Spectrometry'' (Revision 1.0, USEPA, 2005c).
\27\ Determination of Perchlorate in Drinking Water by Ion Chromatography with Suppressed Conductivity and Electrospray Ionization Mass Spectrometry''
(USEPA, Revision 1.0, 2005d).
The approved compliance methods for determining perchlorate in
drinking water listed in table 1 to paragraph (k) of this section, are
incorporated by reference. The Director of the Federal Register
approves this incorporation by reference in accordance with 5 U.S.C.
552(a) and 1 CFR part 51. Copies of the material incorporated by
reference in this paragraph (k) may be inspected at the U.S.
Environmental Protection Agency, EPA Headquarters Library, in the Water
Docket, at the EPA Docket Center (EPA/DC), EPA WJC West, Room 3334,
1301 Constitution Ave. NW, Washington, DC 20460. If you wish to obtain
this material from the EPA Docket Center, call (202) 566-2426. Copies
of this material also may be inspected at the National Archives and
Records Administration (NARA). For information on the availability of
this material at NARA, call (202) 741-6030, or go to www.archives.gov/federal-register/cfr/ibr-locations.html.
* * * * *
(2) * * *
Table 3 to Paragraph (k)(2)
----------------------------------------------------------------------------------------------------------------
Contaminant Preservative \1\ Container \2\ Time \3\
----------------------------------------------------------------------------------------------------------------
* * * * * * *
Perchlorate \7\...................... 4 [deg]C............... P or G................. 28 days.
* * * * * * *
----------------------------------------------------------------------------------------------------------------
\1\ For cyanide determinations samples must be adjusted with sodium hydroxide to pH 12 at the time off
collection. When chilling is indicated the sample must be shipped and stored at 4 [deg]C or less.
Acidification of nitrate or metals samples may be with a concentrated acid or a dilute (50% by volume)
solution of the applicable concentrated acid. Acidification of samples for metals analysis is encouraged and
allowed at the laboratory rather than at the time of sampling provided the shipping time and other
instructions in Section 8.3 of EPA Methods 200.7 or 200.8 or 200.9 are followed.
\2\ P = plastic, hard or soft; G = glass, hard or soft.
\3\ In all cases samples should be analyzed as soon after collection as possible. Follow additional (if any)
information on preservation, containers or holding times that is specified in method.
* * * * * * *
\7\ Sample collection for perchlorate shall be conducted following the requirements specified in the approved
methods in 141.23(k)(1) or the alternative methods listed in appendix A of subpart C of this part, or their
equivalent as determined by the EPA.
* * * * *
(3) * * *
(ii) * * *
Table 4 to Paragraph (k)(3)(ii)
------------------------------------------------------------------------
Acceptance
Contaminant limit
------------------------------------------------------------------------
* * * * *
Perchlorate............................................. 20% at
[gteqt]0.004
mg/L.
* * * * *
------------------------------------------------------------------------
* * * * *
0
4. In Sec. 141.51 amend paragraph (b) by adding a designation to the
table and by adding in alphabetical order, an entry for ``Perchlorate''
to read as follows:
Subpart F--Maximum Contaminant Level Goals and Maximum Residual
Disinfectant Level Goals
Sec. 141.51 Maximum contaminant level goals for inorganic
contaminants.
* * * * *
(b) * * *
Table 1 to Paragraph (b)
------------------------------------------------------------------------
Contaminant MCLG (mg/l)
------------------------------------------------------------------------
* * * * *
Perchlorate............................................. 0.056
* * * * *
------------------------------------------------------------------------
* * * * *
0
5. Amend Sec. 141.60 by adding paragraph (b)(5) to read as follows:
Subpart G--National Primary Drinking Water Regulations: Maximum
Contaminant Levels and Maximum Residual Disinfectant Levels
Sec. 141.60 Effective dates.
* * * * *
(b) * * *
(5) The effective date for Sec. 141.62(b)(17) is [DATE OF
PUBLICATION OF FINAL RULE IN THE FEDERAL REGISTER].
0
6. Amend Sec. 141.62 by:
0
a. In the table in paragraph (b), adding a designation to the table and
an entry for ``(17) Perchlorate'' at the end of the table;
0
b. In the table in paragraph (c), adding a designation to the table, an
entry for ``Perchlorate'' in alphabetical order, and an entry ``14 =
Biological Treatment'' under the undesignated heading entitled ``Key to
BATs; and
[[Page 30568]]
0
c. Adding paragraph (e).
The revisions and additions read as follows:
Sec. 141.62 Maximum contaminant levels for inorganic contaminants.
* * * * *
(b) * * *
Table 1 to Paragraph (b)
------------------------------------------------------------------------
Contaminant MCL (mg/l)
------------------------------------------------------------------------
* * * * *
(17) Perchlorate........................................ 0.056
------------------------------------------------------------------------
(c) * * *
Table 2 to Paragraph (c)--BAT for Inorganic Compounds Listed in Section
141.62(B)
------------------------------------------------------------------------
Chemical name BAT(s)
------------------------------------------------------------------------
* * * * *
Perchlorate............................................. 5, 7, 14.
* * * * *
------------------------------------------------------------------------
* * * * *
Key to BATs in Table
* * * * *
14 = Biological Treatment
* * * * *
(e) The Administrator, pursuant to section 1412 of the Act, hereby
identified in the following table the affordable technology, treatment
technique, or other means available to systems serving 10,000 persons
or fewer for achieving compliance with the maximum contaminant level
for perchlorate:
Table 3 to Paragraph (e)--Small System Compliance Technologies (SSCTS)
for Perchlorate
------------------------------------------------------------------------
Affordability for listed
Small system compliance technology small system categories
------------------------------------------------------------------------
Ion exchange.............................. All size categories.
Reverse osmosis (point of use)............ All size categories.
------------------------------------------------------------------------
0
7. Amend Appendix A to Subpart O of Part 141 table, under ``Inorganic
contaminants'', by adding an entry for ``Perchlorate'' in alphabetical
order to read as follows:
Subpart O--Consumer Confidence Reports
Appendix A to Subpart O of Part 141--Reguated Contaminants
--------------------------------------------------------------------------------------------------------------------------------------------------------
Traditional To convert
Contaminant (units) MCL in mg/ for CCR, MCL in CCR MCLG Major sources in drinking water Health effects
L multiply by units language
--------------------------------------------------------------------------------------------------------------------------------------------------------
* * * * * * *
Inorganic contaminants
Perchlorate................... 0.056 1000 56 56 Perchlorate is commonly used in solid rocket Offspring of
propellants, munitions, fireworks, airbag pregnant women and
initiators for vehicles, matches and signal infants who drink
flares. Perchlorate may occur naturally, water containing
particularly in arid regions such as the perchlorate in
southwestern United States and is found as a excess of the MCL
natural impurity in nitrate salts used to could experience
produce nitrate fertilizers, explosives and delays in their
other products. physical or mental
development.
* * * * * * *
--------------------------------------------------------------------------------------------------------------------------------------------------------
0
8. Amend Appendix A to Subpart Q of Part 141 table, under ``B.
Inorganic contaminants'', by adding an entry for ``Perchlorate'' in
alphabetical order to read as follows:
Subpart Q--Public Notification of Drinking Water Violations
* * * * *
Appendix A to Subpart Q of Part 141--NPDWR Violations and Other Situations Requiring Public Notice \1\
----------------------------------------------------------------------------------------------------------------
MCL/MRDL/TT violations \2\ Monitoring & testing procedure
---------------------------------------- violations
---------------------------------------
Contaminant Tier of public Tier of public
notice Citation notice Citation
required required
----------------------------------------------------------------------------------------------------------------
* * * * * * *
----------------------------------------------------------------------------------------------------------------
B. Inorganic Chemicals (IOCs)
----------------------------------------------------------------------------------------------------------------
* * * * * * *
14. Perchlorate................. 1 141.62(b)............. 3 141.23(a), (c),
141.23(f)(1).
[[Page 30569]]
* * * * * * *
----------------------------------------------------------------------------------------------------------------
\1\ Violations and other situations not listed in this table (e.g.,
failure to prepare Consumer Confidence Reports), do not require notice,
unless otherwise determined by the primacy agency. Primacy agencies
may, at their option, also require a more stringent public notice tier
(e.g., Tier 1 instead of Tier or Tier 2 instead of Tier 3) for specific
violations and situations listed in this Appendix, as authorized under
141.202(a) and 141.203(a).
\2\ MCL-Maximum contaminant level, MDRL-Maximum residual
disinfectant level, TT-treatment technique
* * * * *
0
9. Amend Appendix B to Subpart Q of Part 141 table, under ``C.
Inorganic contaminants'', by adding an entry for ``Perchlorate'' in
alphabetical order to read as follows:
Appendix B to Subpart Q of Part 141--Standard Health Effects Language for Public Notification
----------------------------------------------------------------------------------------------------------------
Standard health effects language for public
Contaminant MCLG \1\ mg/L MCL \2\ mg/L notification
----------------------------------------------------------------------------------------------------------------
* * * * * * *
----------------------------------------------------------------------------------------------------------------
C. Inorganic Chemicals (IOCs)
----------------------------------------------------------------------------------------------------------------
* * * * * * *
21. Perchlorate................ 0.056 0.056 Offspring of pregnant women and infants who
drink water containing perchlorate in excess
of the MCL could experience delays in their
physical or mental development.
* * * * * * *
----------------------------------------------------------------------------------------------------------------
\1\ MCLG--Maximum contaminant level goal.
\2\ MCL--Maximum contaminant level.
PART 142--NATIONAL PRIMARY DRINKING WATER REGULATIONS
IMPLEMENTATION
0
10. The authority citation for part 142 continues to read as follows:
Authority: 42 U.S.C. 300f, 300g-1, 300g-2, 300g-3, 300g-4,
300g-5, 300g-6, 300j-4, 300j-9, and 300j-11.
0
11. In Sec. 142.62 amend the table in paragraph (b) by adding a
designation to the table, an entry for ``Perchlorate'' in alphabetical
order; and an entry ``13 = Biological Treatment'' under the
undesignated heading entitled ``Key to BATs''.
Subpart G--Identification of Best Technology, Treatment Techniques
or Other Means Generally Available.
* * * * *
Sec. 142.62 Variances and exemptions from the maximum contaminant
levels for organic and inorganic chemicals.
* * * * *
(b) * * *
Table 1 to paragraph (b)--BAT for Inorganic Compounds Listed in Sec.
141.62(b)
------------------------------------------------------------------------
Chemical name BAT(s)
------------------------------------------------------------------------
* * * *
Perchlorate................................ 5, 7, 14
* * * *
------------------------------------------------------------------------
* * * * *
Key to BATs in Table
* * * * *
13 = Biological Treatment
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[FR Doc. 2019-12773 Filed 6-25-19; 8:45 am]
BILLING CODE 6560-50-P