[Federal Register Volume 73, Number 198 (Friday, October 10, 2008)]
[Pages 60262-60282]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: E8-24042]



 [EPA-HQ-OW-2008-0068; FRL-8727-6]
RIN 2040-ZA02

Drinking Water: Preliminary Regulatory Determination on 

AGENCY: Environmental Protection Agency (EPA).

ACTION: Notice.


SUMMARY: This action presents EPA's preliminary regulatory 
determination for perchlorate in accordance with the Safe Drinking 
Water Act (SDWA). The Agency has determined that a national primary 
drinking water regulation (NPDWR) for perchlorate would not present ``a 
meaningful opportunity for health risk reduction for persons served by 
public water systems.'' The SDWA requires EPA to make determinations 
every five years of whether to regulate at least five contaminants on 
the Contaminant Candidate List (CCL). EPA included perchlorate on the 
first and second CCLs that were published in the Federal Register on 
March 2, 1998 and February 24, 2005. Most recently, EPA presented final 
regulatory determinations regarding 11 contaminants on the second CCL 
in a notice published in the Federal Register on July 30, 2008. In 
today's action, EPA presents supporting rationale and requests public 
comment on its

[[Page 60263]]

preliminary regulatory determination for perchlorate. EPA will make a 
final regulatory determination for perchlorate after considering 
comments and information provided in the 30-day comment period 
following this notice. EPA plans to publish a health advisory for 
perchlorate at the time the Agency publishes its final regulatory 
determination to provide State and local public health officials with 
technical information that they may use in addressing local 

DATES: Comments must be received on or before November 10, 2008.

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OW-
2008-0068, by one of the following methods:
     www.regulations.gov: Follow the on-line instructions for 
submitting comments.
     Mail: Water Docket, Environmental Protection Agency, 
Mailcode: 2822T, 1200 Pennsylvania Ave., NW., Washington, DC 20460.
     Hand Delivery: Water Docket, EPA Docket Center (EPA/DC) 
EPA West, Room 3334, 1301 Constitution Ave., NW., Washington, DC. Such 
deliveries are only accepted during the Docket's normal hours of 
operation, and special arrangements should be made for deliveries of 
boxed information.
    Instructions: Direct your comments to Docket ID No. EPA-HQ-OW-2008-
0068. EPA's policy is that all comments received will be included in 
the public docket without change and may be made available online at 
www.regulations.gov, including any personal information provided, 
unless the comment includes information claimed to be Confidential 
Business Information (CBI) or other information whose disclosure is 
restricted by statute. Do not submit information that you consider to 
be CBI or otherwise protected through www.regulations.gov or e-mail. 
The www.regulations.gov Web site is an ``anonymous access'' system, 
which means EPA will not know your identity or contact information 
unless you provide it in the body of your comment. If you send an e-
mail comment directly to EPA without going through www.regulations.gov 
your e-mail address will be automatically captured and included as part 
of the comment that is placed in the public docket and made available 
on the Internet. If you submit an electronic comment, EPA recommends 
that you include your name and other contact information in the body of 
your comment and with any disk or CD-ROM you submit. If EPA cannot read 
your comment due to technical difficulties and cannot contact you for 
clarification, EPA may not be able to consider your comment. Electronic 
files should avoid the use of special characters, any form of 
encryption, and be free of any defects or viruses. For additional 
instructions on submitting comments, go to Unit I.B of the 
SUPPLEMENTARY INFORMATION section of this document.
    Docket: All documents in the docket are listed in the 
www.regulations.gov index. Although listed in the index, some 
information is not publicly available, e.g., CBI or other information 
whose disclosure is restricted by statute. Certain other material, such 
as copyrighted material, will be publicly available only in hard copy. 
Publicly available docket materials are available either electronically 
in www.regulations.gov or in hard copy at the Water Docket, EPA/DC, EPA 
West, Room 3334, 1301 Constitution Ave., NW., Washington, DC. The 
Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through 
Friday, excluding legal holidays. The telephone number for the Public 
Reading Room is (202) 566-1744, and the telephone number for the EPA 
Docket Center is (202) 566-2426.

FOR FURTHER INFORMATION CONTACT: Eric Burneson, Office of Ground Water 
and Drinking Water, Standards and Risk Management Division, at (202) 
564-5250 or e-mail [email protected]. For general information 
contact the EPA Safe Drinking Water Hotline at (800) 426-4791 or e-
mail: [email protected].

Abbreviations and Acronyms

a. i.--active ingredient
<--less than
<=--less than or equal to
>--greater than
>=--greater than or equal to
[mu]--microgram, one-millionth of a gram
[mu]g/g--micrograms per gram
[mu]g/kg--micrograms per kilogram
[mu]g/L--micrograms per liter
ATSDR--Agency for Toxic Substances and Disease Registry
AWWARF--American Water Works Association Research Foundation
BMD--bench mark dose
BMDL--bench mark dose level
BW--body weight for an adult, assumed to be 70 kilograms (kg)
CASRN--Chemical Abstract Services Registry Number
CBI--confidential business information
CCL--Contaminant Candidate List
CCL 1--EPA's First Contaminant Candidate List
CCL 2--EPA's Second Contaminant Candidate List
CDC--Centers for Disease Control and Prevention
CDPH---California Department of Public Health
CFR--Code of Federal Regulations
CMR--Chemical Monitoring Reform
CWS--community water system
DW--dry weight
DWEL--drinking water equivalent level
DWI--drinking water intake
EPA--United States Environmental Protection Agency
EPCRA--Emergency Planning and Community Right-to-Know Act
FDA--United States Food and Drug Administration
FQPA--Food Quality Protection Act
FR--Federal Register
FW--fresh weight
g/day--grams per day
HRL--health reference level
IOC--inorganic compound
IRIS--Integrated Risk Information System
LD50 --an estimate of a single dose that is expected to 
cause the death of 50 percent of the exposed animals; it is derived 
from experimental data.
LOAEL--lowest-observed-adverse-effect level
MA DEP--Massachusetts Department of Environmental Protection
MCL--maximum contaminant level
MCLG--maximum contaminant level goal
mg--milligram, one-thousandth of a gram
mg/kg--milligrams per kilogram body weight
mg/kg/day--milligrams per kilogram body weight per day
mg/L--milligrams per liter
mg/m\3\--milligrams per cubic meter
MRL--minimum or method reporting limit (depending on the study or 
survey cited)
N--number of samples
NAS--National Academy of Sciences
NCEH--National Center for Environmental Health (CDC)
NCFAP--National Center for Food and Agricultural Policy
NCI--National Cancer Institute
NCWS--non-community water system
ND--not detected (or non-detect)
NDWAC--National Drinking Water Advisory Council
NHANES--National Health and Nutrition Examination Survey (CDC)
NIS--sodium iodide symporter
NPDWR--national primary drinking water regulation
NPS--National Pesticide Survey
NQ--not quantifiable (or non-quantifiable)
NRC--National Research Council
NTP--National Toxicology Program
OA--oxanilic acid
OW--Office of Water
OPP--Office of Pesticide Programs
PBPK--physiologically based pharmacokinetic
PCR--polymerase chain reaction
PGWDB--pesticides in ground water data base
PWS--public water system
RAIU--radioactive iodide uptake
RED--Reregistration Eligibility Decision
RfC--reference concentration
RfD--reference dose
RSC--relative source contribution
SAB--Science Advisory Board
SDWA--Safe Drinking Water Act

[[Page 60264]]

SOC--synthetic organic compound
SVOC--semi-volatile organic compound
TDS--Total Diet Study (FDA)
TRI--Toxics Release Inventory
TSH--thyroid stimulating hormone
TT--treatment technique
UCMR 1--First Unregulated Contaminant Monitoring Regulation
UF--uncertainty factor
US--United States of America
USDA--United States Department of Agriculture
USGS--United States Geological Survey
UST--underground storage tanks
VOC--volatile organic compound
WHO--World Health Organization

Supplementary Information: 
I. General Information
    A. Does This Action Impose Any Requirements on My Public Water 
    B. What Should I Consider as I Prepare My Comments for EPA?
II. Purpose, Background and Summary of This Action
    A. What is the Purpose of This Action?
    B. Background on the CCL and Regulatory Determinations
    C. What Comments and Information Did EPA Receive Regarding 
Perchlorate in Response to the May 1, FR Notice?
    D. What is EPA's Preliminary Determination on Perchlorate and 
What Happens Next?
III. What Scientific Data and Analyses Did EPA Evaluate in Making a 
Preliminary Regulatory Determination for Perchlorate?
    A. Evaluation of Adverse Health Effects
    B. Evaluation of Perchlorate Occurrence in Drinking Water
    C. Evaluation of Perchlorate Exposure from Sources Other Than 
Drinking Water
IV. Preliminary Regulatory Determination on Perchlorate
    A. May Perchlorate Have an Adverse Effect on the Health of 
    B. Is Perchlorate Known to Occur or is There a Substantial 
Likelihood That Perchlorate Occurs at a Frequency and Level of 
Public Health Concern in Public Water Systems?
    C. Is There a Meaningful Opportunity for the Reduction of Health 
Risks From Perchlorate for Persons Served by Public Water Systems?
V. EPA's Next Steps
VI. References


I. General Information

A. Does This Action Impose Any Requirements on My Public Water System?

    Today's action seeks public comment on EPA's preliminary 
determination that a national primary drinking water regulation is not 
necessary for perchlorate, and thus imposes no requirements on public 
water systems. After review and consideration of public comment, EPA 
will issue a final regulatory determination.

B. What Should I Consider as I Prepare My Comments for EPA?

    You may find the following suggestions helpful for preparing your 
    1. Explain your views as clearly as possible.
    2. Describe any assumptions that you used.
    3. Provide any technical information and/or data you used that 
support your views.
    4. If you estimate potential burden or costs, explain how you 
arrived at your estimate.
    5. Provide specific examples to illustrate your concerns.
    6. Offer alternatives.
    7. Make sure to submit your comments by the comment period 
    8. To ensure proper receipt by EPA, identify the appropriate docket 
identification number in the subject line on the first page of your 
response. It would also be helpful if you provided the name, date, and 
Federal Register citation related to your comments.

II. Purpose, Background and Summary of This Action

    This section briefly summarizes the purpose of this action, the 
statutory requirements, previous activities related to the Contaminant 
Candidate List and regulatory determinations, and the approach used and 
outcome of this preliminary regulatory determination.

A. What is the Purpose of This Action?

    The purpose of today's action is to present EPA's preliminary 
regulatory determination on perchlorate, the process and the rationale 
used to make this determination, a brief summary of the supporting 
documentation, and a request for public comment.

B. Background on the CCL and Regulatory Determinations

    1. Statutory Requirements for CCL and Regulatory Determinations. 
The specific statutory requirements for the Contaminant Candidate List 
(CCL) and regulatory determinations can be found in section 1412(b)(1) 
of the Safe Drinking Water Act (SDWA). The CCL is a list of 
contaminants that are not subject to any proposed or promulgated 
national primary drinking water regulations (NPDWRs), are known or 
anticipated to occur in public water systems (PWSs), and may require 
regulation under the SDWA. The 1996 SDWA Amendments also direct EPA to 
determine, every five years, whether to regulate at least five 
contaminants from the CCL. The SDWA requires EPA to publish a Maximum 
Contaminant Level Goal\1\ (MCLG) and promulgate an NPDWR \2\ for a 
contaminant if the Administrator determines that:

    \1\ The MCLG is the ``maximum level of a contaminant in drinking 
water at which no known off anticipated adverse effect on the health 
of persons would occur, and which allows an adequate margin of 
safety. Maximum contaminant level goals are non-enforceable heath 
goals'' (CFR 141.2).
    \2\ An NPDWR is a legally enforceable standard that applies to 
public water systems. An NPDWR sets a legal limit (called a maximum 
contaminant level or MCL) or specifies a certain treatment technique 
(TT) for public water systems for a specific contaminant or group of 

    (a) The contaminant may have an adverse effect on the health of 
    (b) The contaminant is 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
    (c) 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.
    While carrying out the process to make a determination, the law 
requires EPA to take into consideration the effect contaminants have on 
subgroups that comprise a meaningful portion of the general population 
(such as infants, children, pregnant women, the elderly, individuals 
with a history of serious illness or other subpopulations) that are 
identifiable as being at greater risk of adverse health effects than 
the general population.
    If EPA makes a final determination that a national primary drinking 
water regulation is needed, the Agency has 24 months to publish a 
proposed MCLG and NPDWR. After the proposal, the Agency has 18 months 
to publish and promulgate a final MCLG and NPDWR (SDWA section 1412(b) 
(1) (E)).\3\

    \3\ The statute authorizes a nine month extension of this 
promulgation date.

    EPA published preliminary regulatory determinations for nine CCL 1 
contaminants on June 3, 2002, (67 FR 38222 (USEPA, 2002a)), and final 
regulatory determinations on July 18, 2003 (68 FR 42898 (USEPA, 
2003a)). EPA published preliminary regulatory determinations for eleven 
CCL 2 contaminants on May 1, 2007, (72 FR 24016 (USEPA, 2007)) and 
finalized these regulatory determinations on July 30, 2008 (73 FR 44251 
(USEPA, 2008c)). As part of its May 1, 2007, FR notice of preliminary 
regulatory determinations for 11 contaminants, EPA also presented 
information on several contaminants

[[Page 60265]]

from the second CCL for which the Agency was not yet making a 
preliminary regulatory determination, including perchlorate. 
Specifically, EPA indicated that additional information was needed to 
more fully characterize perchlorate exposure and determine whether it 
is appropriate to regulate perchlorate in drinking water (i.e., whether 
setting a national primary drinking water standard would provide a 
meaningful opportunity to reduce risk for people served by public water 
systems). The May 1, 2007, FR notice describes how the Agency was 
considering additional information including FDA food data and CDC 
human exposure data to determine whether to regulate perchlorate. (See 
the May 1, 2007, FR notice at 24038 for a discussion regarding the 
information that EPA had on perchlorate as well as the additional 
information that was needed before the Agency could make a preliminary 
regulatory determination for perchlorate).

C. What Comments and Information Did EPA Receive Regarding Perchlorate 
in Response to the May 1, FR Notice?

    Eight commenters on the Regulatory Determinations 2 Preliminary FR 
notice addressed perchlorate. EPA received comments that supported and 
comments that opposed regulating perchlorate. One of the commenters who 
encouraged regulation stated that perchlorate is known to occur in 
public water supplies in a number of States and ``while occurrence data 
does [sic] not suggest that perchlorate occurs at levels of public 
health concern in the vast majority of public drinking water supplies, 
and the population at risk appears to be small, that group does include 
a sensitive subpopulation (pregnant women and developing fetuses) of 
significant concern.'' Another commenter wrote ``the contamination of 
water supplies by perchlorate is on-going'' and ``perchlorate that has 
entered the soil and contaminated aquifers will likely lead to 
additional impacted sites.'' A commenter wrote that ``a number of 
States are moving to regulate perchlorate and a patchwork of different 
regulations will confuse the public and the regulated water 
    The commenters opposed to regulating perchlorate also cited the 
available information to support their recommendation. One commenter 
wrote that ``the extensive scientific record indicates that 
establishing a drinking water standard for perchlorate would not yield 
a meaningful opportunity to reduce risk to human health.'' Another 
commenter stated that perchlorate ``does not appear, at this stage, to 
be a nationwide problem.''
    Several commenters also addressed EPA's assessment that additional 
investigation is necessary to ascertain total human exposure before a 
preliminary regulatory determination could be made. Commenters wrote 
that the principal study on which EPA's Reference Dose (RfD) is based 
already accounts for background sources of perchlorate and therefore 
EPA should not adjust the RfD to account for other non-drinking-water 
    EPA has considered the perchlorate comments submitted in connection 
with the May 1, 2007, notice in the development of today's action. EPA 
will consider these and any further comments submitted in response to 
this notice before preparing a final regulatory determination for 

D. What is EPA's Preliminary Regulatory Determination on Perchlorate 
and What Happens Next?

    EPA is making a preliminary regulatory determination in this notice 
that a national primary drinking water rule is not necessary for 
perchlorate because a national primary drinking water regulation would 
not provide a meaningful opportunity to reduce health risk. EPA will 
make a final regulatory determination for perchlorate after considering 
comments and information provided in the 30-day comment period 
following this notice. One of the analyses that EPA considered for this 
preliminary determination is a physiologically-based pharmacokinetic 
(PBPK) model that predicts radioactive iodide uptake (RAIU) inhibition 
in the thyroid for various sub-populations and drinking water 
concentrations. The model, which is described in section IV.B.5, has 
already been published in peer-reviewed articles (Clewell et al., 2007 
and Merrill et al., 2005), but EPA subjected the model to intensive 
internal review prior to considering it for this regulatory 
determination and made several adjustments as a result. EPA believes it 
is appropriate to have these adjustments peer-reviewed. While the 
application of the model to non-adult subpopulations was part of the 
previously peer-reviewed articles, EPA will also ask the peer reviewers 
to comment on this issue to help EPA ensure that the model is 
appropriate for use in assessing health outcomes associated with 
perchlorate exposure for these populations. EPA intends to complete 
this review before publishing its final determination and will consider 
any comments from the reviewers. Additionally, EPA plans to publish a 
health advisory for perchlorate at the time the Agency publishes its 
final regulatory determination to provide State and local public health 
officials with information that they may use in addressing local 
    Additionally, at the same time that EPA publishes a health advisory 
for perchlorate, the Agency will withdraw its existing January 2006 
guidance regarding perchlorate and potential cleanup levels under the 
National Oil and Hazardous Substances Contingency Plan (National 
Contingency Plan, NCP) and will replace it with revised guidance. (See 
memorandum dated January 26, 2006, from Susan Parker Bodine to EPA 
Regional Administrators (US EPA, 2006).) Specifically, the January 2006 
guidance, in part, addresses the use of preliminary remediation goals 
(PRGs) for perchlorate contaminated water at National Priority List 
(NPL) sites. The January 2006 guidance recommends a PRG of 24.5 ppb, 
assuming that all exposure comes from ground water at the site. The 
recommended PRG is based on the assumption that all exposure comes from 
ground water, because at the time the January 2006 guidance was issued 
there was insufficient information available on the levels of 
perchlorate in food to calculate a national relative source 
contribution (RSC). In the absence of such national data on the levels 
of perchlorate found in foods, the approach outlined in the January 
2006 guidance was considered by the Agency to be the most 
scientifically defensible. In addition, because the recommended PRG 
generally is the starting point for determining appropriate site-
specific cleanup levels, the guidance also indicates that the cleanup 
level at any site should be evaluated on a case-by-case basis, and 
modified accordingly, based on site-specific information, including 
exposure to non-water sources, such as foods. EPA now has sufficient 
data to calculate a national RSC and has used this RSC to calculate a 
health reference level (HRL) for drinking water as part of the basis 
for today's preliminary determination. When EPA issues the final 
regulatory determination for perchlorate, the final HRL will be the 
basis for the health advisory value in the health advisory document the 
Agency expects to issue at that time. Thereafter, it may be appropriate 
to use the health advisory value as a ``to be considered'' (TBC) value 
in developing potential cleanup levels for perchlorate at Superfund 
sites. In addition, some State regulations may be applicable or 
relevant and appropriate requirements (ARARs)

[[Page 60266]]

when establishing cleanup levels for perchlorate at Superfund sites.

III. What Scientific Data and Analyses Did EPA Evaluate in Making a 
Preliminary Regulatory Determination for Perchlorate?

    This section summarizes the health effects, occurrence, and 
population exposure evaluation information EPA used to support the 
preliminary regulatory determination for perchlorate. EPA's conclusions 
with respect to these data are discussed in Section IV.

A. Evaluation of Precursor and Adverse Health Effects

    Section 1412(b)(1)(A)(i) of the SDWA requires EPA to determine 
whether a candidate contaminant may have an adverse effect on public 
health. EPA described the overall process the Agency used to evaluate 
health effects information in the May 1, 2007, Federal Register Notice 
(72 FR 24016 (USEPA, 2007)). This section presents specific information 
about the potential for precursor and adverse health effects from 
perchlorate, including a discussion of an extensive report completed by 
the National Academy of Sciences (NAS) on the issue and other research 
published after that report.
 1. NAS Review of Perchlorate Health Implications and EPA's Reference 
    In 2003, the National Research Council (NRC) of the NAS was asked 
to assess the current state of the science regarding potential adverse 
effects of disruption of thyroid function by perchlorate in humans and 
laboratory animals at various stages of life and, based on this review, 
to determine whether EPA's findings in its 2002 draft risk assessment 
were consistent with the current scientific evidence.
    In January 2005, the NRC published ``Health Implications of 
Perchlorate Ingestion,'' a review of the state of the science regarding 
potential adverse health effects of perchlorate exposure and mode-of-
action for perchlorate toxicity (NRC, 2005).
    Perchlorate can interfere with the normal functioning of the 
thyroid gland by competitively inhibiting the transport of iodide into 
the thyroid. Iodide is an important component of two thyroid hormones, 
T4 and T3, and the transfer of iodide from the blood into the thyroid 
is an essential step in the synthesis of these two hormones. Iodide 
transport into the thyroid is mediated by a protein molecule known as 
the sodium (Na+)-iodide (I-) symporter (NIS). NIS 
molecules bind iodide with very high affinity, but they also bind other 
ions that have a similar shape and electric charge, such as 
perchlorate. The binding of these other ions to the NIS inhibits iodide 
transport into the thyroid, which can result in intrathyroidal iodide 
deficiency and consequently decreased synthesis of T4 and T3. There is 
compensation for low-levels of iodide deficiency, however, such that 
the body maintains blood serum concentrations of thyroid hormones 
within narrow limits through feedback control mechanisms. The 
compensation for decreased thyroid hormone is accomplished by increased 
secretion of the thyroid stimulating hormone (TSH) from the pituitary 
gland triggered by the reduced hormone levels, which has among its 
effects the increased production of T4 and T3 (USEPA, 2005b). The 
thyroid's ability to compensate in this way is limited, though, such 
that sufficiently high levels of perchlorate exposure result in a 
reduction of T4 and T3 blood levels (after thyroid iodine stores are 
depleted). Sustained changes in thyroid hormone and TSH secretion can 
result in thyroid hypertrophy and hyperplasia (i.e., abnormal growth or 
enlargement of the thyroid) (USEPA, 2005b).
    Children born with congenital hypothyroidism may suffer from mild 
cognitive deficits despite hormone remediation (Rovet, 2002; Zoeller 
and Rovet, 2004), and subclinical hypothyroidism and reductions in T4 
(i.e., hypothyroxinemia) in pregnant women have been associated with 
neurodevelopmental delays and IQ deficits in their children (Pop et 
al., 1999, 2003; Haddow et al., 1999; Kooistra et al., 2006; Morreale 
de Escobar, 2000, 2004). Animal studies support these observations, and 
recent findings indicate that neurodevelopmental deficits are evident 
under conditions of hypothyroxinemia and occur in the absence of growth 
retardation (Auso et al., 2004; Gilbert and Sui, 2008; Sharlin et al., 
2008; Goldey et al., 1995).
    Results from studies of the effects of perchlorate exposure on 
hormone levels have been mixed. One recent study did not identify any 
effects of perchlorate on blood serum hormones (Amitai et al., 2007), 
while another study (Blount et al., 2006b) did identify such effects. 
The results of the Blount study are discussed further in Section 
    The data from epidemiological studies of the general population 
provide some information on possible effects of perchlorate exposure. 
Based upon analysis of the data available at the time NRC (2005) 
acknowledged that ecologic epidemiological data alone are not 
sufficient to demonstrate whether or not an association is causal, and 
that these studies can provide evidence bearing on possible 
associations. Noting the limitations of specific studies, the NRC 
(2005; chapter 3) committee concluded that the available 
epidemiological evidence is not consistent with a causal association 
between perchlorate and congenital hypothyroidism, changes in thyroid 
function in normal birthweight, full-term newborns, or hypothyroidism 
or other thyroid disorders in adults. The committee considered the 
evidence to be inadequate to determine whether or not there is a causal 
association between perchlorate exposure and adverse neurodevelopmental 
outcomes in children. The committee noted that no studies have 
investigated the relationship between perchlorate exposure and adverse 
outcomes among especially vulnerable groups, such as the offspring of 
mothers who had low dietary iodide intake, or low-birthweight or 
preterm infants (US EPA, 2005b).
    The NRC recommended data from the Greer et al. (2002) human 
clinical study as the basis for deriving a reference dose (RfD) for 
perchlorate (NRC, 2005). Greer et al., (2002) report the results of a 
study that measured thyroid iodide uptake, hormone levels, and urinary 
iodide excretion in a group of 37 healthy adults who were administered 
perchlorate doses orally over a period of 14 days. Dose levels ranged 
from 7 to 500 [mu]g/kg/day in the different experimental groups. The 
investigators found that the 24-hour inhibition of iodide intake ranged 
from 1.8 percent in the lowest dose group to 67.1 percent in the 
highest dose group. However, no significant differences were seen in 
measured blood serum thyroid hormone levels (T3, T4, total and free) in 
any dose group. The statistical no observed effect level (NOEL) for the 
perchlorate-induced inhibition of thyroid iodide uptake was determined 
to be 7 [mu]g/kg/day, corresponding to an iodide uptake inhibition of 
1.8 percent. Although the NRC committee concluded that hypothyroidism 
is the first adverse effect in the continuum of effects of perchlorate 
exposure, NRC recommended that ``the most health-protective and 
scientifically valid approach'' was to base the perchlorate RfD on the 
inhibition of iodide uptake by the thyroid (NRC, 2005). NRC concluded 
that iodide uptake inhibition, although not adverse, is the most 
appropriate precursor event in the continuum of possible effects of 
perchlorate exposure and would precede any adverse health effects of 
perchlorate exposure. The lowest dose

[[Page 60267]]

(7 [mu]g/kg/day) administered in the Greer et al., (2002) study was 
considered a NOEL (rather than a no-observed-adverse-effect level or 
NOAEL) because iodide uptake inhibition is not an adverse effect, but a 
biochemical precursor. The NRC further determined that, ``the very 
small decrease (1.8 percent) in thyroid radioiodide uptake in the 
lowest dose group was well within the variation of repeated 
measurements in normal subjects.'' A summary of the data considered and 
the NRC deliberations can be found in the NRC report (2005).
    The NRC recommended that EPA apply an intraspecies uncertainty 
factor of 10 to the NOEL to account for differences in sensitivity 
between the healthy adults in the Greer et al., (2002) study and the 
most sensitive population, fetuses of pregnant women who might have 
hypothyroidism or iodide deficiency. Because the fetus depends on an 
adequate supply of maternal thyroid hormone for its central nervous 
system development during the first trimester of pregnancy, iodide 
uptake inhibition from low-level perchlorate exposure has been 
identified as a concern in connection with increasing the risk of 
neurodevelopmental impairment in fetuses of high-risk mothers (NRC, 
2005). The NRC (2005) viewed the uncertainty factor of 10 as 
conservative and protective of health given that the point of departure 
(the NOEL) is based on a non-adverse effect (iodide uptake inhibition), 
which precedes the adverse effect in a continuum of possible effects of 
perchlorate exposure. The NRC panel concluded that no additional 
uncertainty factor was needed for the use of a less-than-chronic study, 
for deficiencies in the database, or for interspecies variability. 
EPA's Integrated Risk Information System (IRIS) adopted the NRC's 
recommendations resulting in an RfD of 0.7 [mu]g/kg/day, derived by 
applying a ten-fold total uncertainty factor to the NOEL of 7 [mu]g/kg/
day (USEPA, 2005b).
    The NRC emphasized that its recommendation ``differs from the 
traditional approach to deriving the RfD.'' The NRC recommended ``using 
a nonadverse effect rather than an adverse effect as the point of 
departure for the perchlorate risk asessement. Using a nonadverse 
effect that is upstream of the adverse effect is a more conservative, 
health-protective approach to the perchlorate risk assessment.'' The 
NRC also noted that the purpose of the 10-fold uncertainty factor is to 
protect sensitive subpopulations in the face of uncertainty regarding 
their relative sensitivity to perchlorate exposure. The NRC recognized 
that additional information on these relative sensitivities could be 
used to reduce this uncertainty factor in the future (NRC, 2005).\4\

    \4\ ``There can be variability in responses among humans. The 
intraspecies uncertainty factor accounts for that variability and is 
intended to protect populations more sensitive than the population 
tested. In the absence of data on the range of sensitivity among 
humans, a default uncertainty factor of 10 is typically applied. The 
factor could be set at 1 if data indicate that sensitive populations 
do not vary substantially from those tested.'' (NRC 2005, p 173)

2. Biomonitoring Studies
    After the NRC report was released, several papers were published 
that investigated whether biomonitoring data associated with the 
National Health and Nutrition Examination Survey (NHANES) could be used 
to discern if there was a relationship between perchlorate levels in 
the body and thyroid function. These papers also help to evaluate 
populations that might be considered to be more sensitive to 
perchlorate exposure.
    Blount et al., (2006b) published a study examining the relationship 
between urinary levels of perchlorate and blood serum levels of TSH and 
total T4 in 2,299 men and women (ages 12 years and older) who 
participated in CDC's 2001-2002 NHANES.\5\ Blount et al., (2006b) 
evaluated perchlorate along with a number of covariates known or likely 
to be associated with T4 or TSH levels to assess the relationship 
between perchlorate and these hormones, and the influence of other 
factors on this relationship. These covariates included gender, age, 
race/ethnicity, body mass index, serum albumin, serum cotinine (a 
marker of nicotine exposure), estimated total caloric intake, pregnancy 
status, post-menopausal status, premenarche status, serum C-reactive 
protein, hours fasting before sample collection, urinary thiocyanate, 
urinary nitrate, and use of selected medications. The study found that 
perchlorate was a statistically significant predictor of thyroid 
hormones in women, but not in men.

    \5\ While CDC researchers measured urinary perchlorate 
concentration for 2,820 NHANES participants, TSH and total T4 serum 
levels were only available for 2,299 of these participants.

    After finding evidence of gender differences, the researchers 
focused on further analyzing the NHANES data for the 1,111 women 
participants. They divided these 1,111 women into two categories, 
higher-iodide and lower-iodide urinary content, using a cut point of 
100 [mu]g/L of urinary iodide based on the median level the World 
Health Organization (WHO) considers indicative of sufficient iodide 
intake \6\ for a population. Hypothyroid women were excluded from the 
analysis. According to the study's authors, about 36 percent of women 
living in the United States have urinary iodide levels less than 100 
[mu]g/L (Caldwell et al., 2005). For women with urinary iodide levels 
less than 100 [mu]g/L, the study found that urinary perchlorate is 
associated with a decrease in (a negative predictor for) T4 levels and 
an increase in (a positive predictor for) TSH levels. For women with 
urinary iodide levels greater than or equal to 100 [mu]g/L, the 
researchers found that perchlorate is a significant positive predictor 
of TSH, but not a predictor of T4. The researchers state that 
perchlorate could be a surrogate for another unrecognized determinant 
of thyroid function.

    \6\ WHO notes that the prevalence of goiter begins to increase 
in populations with a median urinary iodide level below 100 [mu]g/L 
(WHO, 1994).

    Also, the study reports that while large doses of perchlorate are 
known to decrease thyroid function, this is the first time an 
association of decreased thyroid function has been observed at these 
low levels of perchlorate exposure. The clinical significance of the 
variations in T4/TSH levels, which were generally within normal limits, 
has not been determined. The researchers noted several limitations of 
the study (e.g., assumption that urinary perchlorate correlates with 
perchlorate levels in the stroma and tissue and measurement of total T4 
rather than free T4) and recommended that these findings be affirmed in 
at least one more large study focusing on women with low urine iodide 
levels. It is also not known whether the association between 
perchlorate and thyroid hormone levels is causal or mediated by some 
other correlate of both, although the relationship between urine 
perchlorate and total TSH and T4 levels persisted after statistical 
adjustments for some additional covariates known to predict thyroid 
hormone levels (e.g., total kilocalorie intake, estrogen use, and serum 
C-reactive protein levels). A planned follow-up study will include 
additional measures of thyroid health and function (e.g., TPO-
antibodies, free T4). An additional paper by Blount et al., (2006c), 
discussed further in Section III. C. 2. a., found that almost all 
participants in the NHANES survey, including the participants in this 
group, had urinary levels of perchlorate corresponding to estimated 
dose levels that are below the RfD of 0.7 [mu]g/kg/day.
    The Blount study suggested that perchlorate could be a surrogate 
for another unrecognized determinant of

[[Page 60268]]

thyroid function. There are other chemicals, including nitrate and 
thiocyanate, which can affect thyroid function. Steinmaus et al., 
(2007) further analyzed the data from NHANES 2001-2002 to assess the 
impact of smoking, cotinine and thiocyanate on the relationship between 
urinary perchlorate and blood serum T4 and TSH. Thiocyanate is a 
metabolite of cyanide found in tobacco smoke and is naturally occurring 
in some foods, including cabbage, broccoli, and cassava. Increased 
serum thiocyanate levels are associated with increasing levels of 
smoking. Thiocyanate affects the thyroid by the same mechanism as 
perchlorate (competitive inhibition of iodide uptake). Steinmaus et al. 
analyzed the data to determine whether smoking status (smoker or 
nonsmoker), serum thiocyanate, or serum cotinine were better predictors 
of T4 and TSH changes than perchlorate, or if the effects reflected the 
combined effects of perchlorate and thiocyanate
    Of female subjects 12 years of age and older in NHANES 2001-2002, 
1,203 subjects had data on blood serum T4, serum TSH, urinary 
perchlorate, iodine and creatinine. Subjects with extreme T4 or TSH (3 
individuals) or with a reported history of thyroid disease (91) were 
excluded from further analyses. Of the remaining women, 385 (35 
percent) had urinary iodine levels below 100 [mu]g/l. Steinmaus, et al. 
evaluated serum cotinine as an indicator of nicotine exposure, with 
levels greater than 10 ng/ml classified as high and levels less than 
0.015 ng/ml classified as low.
    The authors found no association between either perchlorate or T4 
and smoking, cotinine or thiocyanate in men or in women with urinary 
iodine levels greater than 100 [mu]g/l. In addition, they found no 
association between cotinine and T4 or TSH in women with iodine levels 
lower than 100 [mu]g/l. However, in women with urinary iodine levels 
lower than 100 [mu]g/l, an association between urinary perchlorate and 
decreased serum T4 was stronger in smokers than in non-smokers, and 
stronger in those with high urinary thiocyanate levels than in those 
with low urinary thiocyanate levels. Although noting that their 
findings need to be confirmed with further research, the authors 
concluded that for these low-iodine women the results suggest that at 
commonly-occurring perchlorate exposure levels, thiocyanate in tobacco 
smoke and perchlorate interact in affecting thyroid function, and that 
agents other than tobacco smoke might cause similar interactions 
(Steimaus et al., 2007).
    EPA also evaluated whether health information is available 
regarding children, pregnant women and lactating mothers. The NRC 
report discussed a number of epidemiological studies that looked at 
thyroid hormone levels in infants. A more recent study by Amitai et 
al., (2007) assessed T4 values in newborns in Israel whose mothers 
resided in areas where drinking water contained perchlorate at ``very 
high'' (340 [mu]g/L), ``high'' (12.94 [mu]g/L), or ``low'' (<3 [mu]g/L) 
perchlorate concentrations. The mean ( standard deviation) 
T4 value of the newborns in the very high, high, and low exposure 
groups was 13.8  3.8, 13.9  3.4, and 14.0 
 3.5 [mu]g/dL, respectively, showing no significant 
difference in T4 levels between the perchlorate exposure groups. This 
is consistent with the conclusions drawn by the NRC review of other 
epidemiological studies of newborns. The NRC (2005) also noted ``no 
epidemiologic studies are available on the association between 
perchlorate exposure and thyroid dysfunction among low-birthweight or 
preterm newborns, offspring of mothers who had iodide deficiency during 
gestation, or offspring of hypothyroid mothers.''
3. Physiologically-based Pharmacokinetic (PBPK) Models
    PBPK models represent an important class of dosimetry models that 
can be used to predict internal doses to target organs, as well as some 
effects of those doses (e.g., radioactive iodide uptake inhibition in 
the thyroid). To predict internal dose level, PBPK models use 
physiological, biochemical, and physicochemical data to construct 
mathematical representations of processes associated with the 
absorption, distribution, metabolism, and elimination of compounds. 
With the appropriate data, these models can be used to extrapolate 
across and within species and for different exposure scenarios, and to 
address various sources of uncertainty in health assessments, including 
uncertainty regarding the relative sensitivities of various 
    Clewell et al., (2007) developed multi-compartment PBPK models 
describing the absorption and distribution of perchlorate for the 
pregnant woman and fetus, the lactating woman and neonate, and the 
young child. This work built upon Merrill et al.'s, (2005) model for 
the average adult. Related research that served as the basis for the 
more recent PBPK modeling efforts was discussed by the NRC in their 
January 2005 report on perchlorate.
    The models estimated the levels of perchlorate absorbed through the 
gastrointestinal tract and its subsequent distribution within the body. 
Clewell et al., (2007) provided estimates of internal dose and 
resulting iodide uptake inhibition across all life stages, and for 
pregnant and lactating women. The paper reported iodide uptake 
inhibition levels for external doses of 1, 10, 100, and 1000 [mu]g/kg/
day. Results at the lower two doses indicated that the highest 
perchlorate blood concentrations in response to an external dose would 
occur in the fetus, followed by the lactating woman and the neonate. 
Predicted blood levels for all three groups (i.e., fetus, lactating 
women and neonates) were four- to five-fold higher than for non-
pregnant adults. Smaller relative differences were predicted at 
external doses of 100 and 1000 [mu]g/kg/day. The authors attributed 
this change to saturation of uptake mechanisms. The model predicted 
minimal effect of perchlorate on iodide uptake inhibition in all groups 
at the 1 [mu]g/kg/day external dose (about one and one half times the 
RfD), estimating 1.1 percent inhibition or less across all groups. 
Inhibition was predicted to be 10 percent or less in all groups at an 
external dose of 10 [mu]g/kg/day (about 14 times the RfD).
    The results of the model extrapolations were evaluated against data 
developed in two epidemiologic studies performed in Chile, one studying 
school children (Tellez et al., 2005) and another following women 
through pregnancy and lactation (Gibbs et al., 2004). The model 
predicted average blood serum concentrations of perchlorate in the 
women from the Gibbs et al., (2004) study which were nearly identical 
to their measured perchlorate blood serum concentrations. The blood 
serum perchlorate concentrations predicted from the Tellez et al., 
(2005) study were within the range of the measured concentrations, and 
the concentrations of perchlorate in breast milk predicted from the 
model were within two standard deviations of the measured 
concentrations. The authors concluded that the model predictions were 
consistent with empirical results and that the predicted extent of 
iodide inhibition in the most sensitive population (the fetus) is not 
significant at EPA's RfD of 0.7 [mu]g/kg-day.
    The NRC recommended that inhibition of iodide uptake by the 
thyroid, which is a precursor event and not an adverse effect, should 
be used as the basis for the perchlorate risk assessment (NRC, 2005). 
Consistent with this recommendation, iodide uptake inhibition was used 
by EPA as the critical effect in determining the reference dose (RfD) 
for perchlorate. Therefore, PBPK models of perchlorate and radioiodide, 
which were developed

[[Page 60269]]

to describe thyroidal radioactive iodide uptake (RAIU) inhibition by 
perchlorate for the average adult (Merrill et al., 2005), pregnant 
woman and fetus, lactating woman and neonate, and the young child 
(Clewell et al., 2007) were evaluated by EPA based on their ability to 
provide additional information surrounding this critical effect for 
potentially sensitive subgroups and reduce some of the uncertainty 
regarding the relative sensitivities of these subgroups.
    EPA evaluated the PBPK model code provided by the model authors and 
found minor errors in mathematical equations and computer code, as well 
as some inconsistencies between model code files. EPA made several 
changes to the code in order to harmonize the models and more 
adequately reflect the biology (see USEPA, 2008b) for more information.
    Model parameters describing urinary excretion of perchlorate and 
iodide were determined to be particularly important in the prediction 
of RAIU inhibition in all subgroups; therefore, a range of biologically 
plausible values available in the peer-reviewed literature was 
evaluated in depth using the PBPK models. Exposure rates were also 
determined to be critical for the estimation of RAIU inhibition by the 
models and were also further evaluated.
    Overall, detailed examination of Clewell et al., (2007) and Merrill 
et al., (2005) confirmed that the model structures were appropriate for 
predicting percent inhibition of RAIU by perchlorate in most 
lifestages. Unfortunately, the lack of biological information during 
early fetal development limits the applicability of the PBPK modeling 
of the fetus to a late gestational timeframe (i.e., near full term 
pregnancy, ~GW 40), so EPA did not make use of model predictions 
regarding early fetal RAIU inhibition. Although quantitative outputs of 
EPA's revised PBPK models differ somewhat from the published values, 
the EPA evaluation confirmed that, with modifications (as described in 
USEPA, 2008b), the Clewell et al., (2007) and Merrill et al., (2005) 
models provide an appropriate basis for calculating the lifestage 
differences in the degree of thyroidal RAIU inhibition at a given level 
of perchlorate exposure. The results of EPA's model application are 
discussed in Section IV.B.5.

B. Evaluation of Perchlorate Occurrence in Drinking Water

    The primary source of drinking water occurrence data used to 
support this preliminary regulatory determination is the data provided 
by public water systems in accordance with the first Unregulated 
Contaminant Monitoring Regulation (UCMR 1). The Agency also evaluated 
supplemental sources of occurrence information.
    1. The Unregulated Contaminant Monitoring Regulation. In 1999, EPA 
developed the UCMR program in coordination with the CCL and the 
National Drinking Water Contaminant Occurrence Database (NCOD) to 
provide national occurrence information on unregulated contaminants 
(September 17, 1999, 64 FR 50556 (USEPA, 1999b); March 2, 2000, 65 FR 
11372 (USEPA, 2000b); and January 11, 2001, 66 FR 2273 (USEPA, 2001b)).
    EPA designed the UCMR 1 data collection with three parts (or 
tiers). Occurrence data for perchlorate are from the first tier of UCMR 
(also known as UCMR 1 List 1 Assessment Monitoring). EPA required all 
large \7\ PWSs, plus a statistically representative national sample of 
800 small \8\ PWSs, to conduct Assessment Monitoring.\9\ Approximately 
one-third of the participating small systems were scheduled to monitor 
for these contaminants during each calendar year from 2001 through 
2003. Large systems could conduct one year of monitoring anytime during 
the 2001-2003 UCMR 1 period. EPA specified a quarterly monitoring 
schedule for 1,896 surface water systems and a twice-a-year, six-month 
interval monitoring schedule for 1,969 ground water systems. The 
objective of the UCMR 1 sampling approach for small systems was to 
collect contaminant occurrence data from a statistically selected, 
nationally representative sample of small systems. The small system 
sample was stratified and population-weighted, and included some other 
sampling adjustments, such as including at least 2 systems from each 
State. With contaminant monitoring data from all large PWSs and a 
statistical, nationally representative sample of small PWSs, the UCMR 1 
List 1 Assessment Monitoring program provides a contaminant occurrence 
data set suitable for national drinking water estimates.

    \7\ Systems serving more than 10,000 people.
    \8\ Systems serving 10,000 people or fewer.
    \9\ Large and small systems that purchase 100 percent of their 
water supply were not required to participate in the UCMR 1 
Assessment Monitoring or the UCMR 1 Screening Survey.

    EPA collected and analyzed drinking water occurrence data for 
perchlorate from 3,865 PWSs between 2001 and 2005 under the UCMR 1. EPA 
found that 160 (approximately 4.1 percent) of the 3,865 PWSs that 
sampled and reported had at least 1 analytical detection of perchlorate 
(in at least 1 sampling point) at levels greater than or equal to the 
method reporting limit (MRL) of 4 [mu]g/L. These 160 systems are 
located in 26 States and 2 territories. Of these 160 PWSs, 8 are small 
systems (serving 10,000 or fewer people) and 152 are large systems 
(serving more than 10,000 people). These 160 systems reported 637 
detections of perchlorate at levels greater than or equal to 4 [mu]g/L, 
which is approximately 11.3 percent of the 5,629 samples collected by 
these 160 systems and approximately 1.9 percent of the 34,331 samples 
collected by all 3,865 systems. The maximum reported concentration of 
perchlorate was 420 [mu]g/L, from a single surface water sample from a 
PWS in Puerto Rico. The average concentration of perchlorate for those 
samples with positive detections for perchlorate was 9.85 [mu]g/L and 
the median concentration was 6.40 [mu]g/L. A summary of the perchlorate 
occurrence statistics in UCMR 1 is shown in Table 1.

    \10\ Table 1 shows perchlorate detection sat levels greater than 
and equal to the MRL of 4 [mu]g/L.

                  Table 1--UCMR 1 Occurrence of Perchlorate at Concentrations >= 4 [mu]g/L \10\
                                                                Sampling     Sampling
            System size              Number of   Samples  w/     points     points  w/    Sampled    Systems  w/
                                      samples      detects       tested      detects      systems      detects
Small Systems.....................        3,295           15        1,454            8          797            8
Large Systems.....................       31,036          622       13,533          379        3,068          152
    Total Systems.................       34,331          637       14,987          387        3,865         160

[[Page 60270]]

1. For both large and small systems, at 3,865 systems with data, there were 34,331 samples taken at 14,987
  (entry) points resulting in 637 (1.86%) sample detects representing 387 (2.58%) of the entry/sample points in
  160 (4.14%) of the systems.
2. For 3,068 large systems with data, there were 31,036 samples taken at 13,533 entry points resulting in 622
  (2.00%) detections representing 379 (2.80%) entry/sample points in 152 (4.95%) of the systems.
3. For 797 small systems with data, there were 3,295 samples taken at 1,454 entry points, resulting in a total
  of 15 (0.455%) detections representing 8 (0.55%) entry/sample points at 8 (1%) of the systems.

    Table 2 presents EPA's estimates of the population served by water 
systems for which the highest reported perchlorate concentration was 
greater than various threshold concentrations ranging from 4 [mu]g/L 
(MRL) to 25 [mu]g/L. The fourth column of Table 2 presents a high end 
estimate of the population served drinking water above a threshold. 
This column presents the total population served by systems in which at 
least one sample was found to contain perchlorate above the threshold 
concentration. EPA considers this a high end estimate because it is 
based upon the assumption that the entire system population is served 
water from the entry point that had the highest reported perchlorate 
concentration. In fact, many water systems have multiple entry points 
into which treated water is pumped for distribution to their consumers. 
For the systems with multiple entry points, it is unlikely that the 
entire service population receives water from the one entry point with 
the highest single concentration. Therefore, EPA included a less 
conservative estimate of the population served water above a threshold 
in the fifth column in Table 2. EPA developed this estimate by assuming 
the population was equally distributed among all entry points. For 
example, if a system with 10 entry points serving 200,000 people had a 
sample from a single entry point with a concentration at or above a 
given threshold, EPA assumed that the entry point served one-tenth of 
the system population, and added 20,000 people to the total when 
estimating the population in the last column of Table 2. This approach 
may provide either an overestimate or an underestimate of the 
population served by the affected entry point. In contrast, in the 
example above, EPA added the entire system population of 200,000 to the 
more conservative population served estimate in column 4, which is 
likely an overestimate.

          Table 2--UCMR 1 Occurrence and Population Estimates for Perchlorate Above Various Thresholds
                                                                                         Population   for entry
                                                                                         served by    or sample
                                                               PWS entry or  sample      PWSs with      points
                                   PWSs with at  least 1      points  with at least 1    at least 1   having at
        Thresholds \a\           detection >  threshold of   detection >  threshold of  detection >    least 1
                                         interest                  interest \b\           threshold  detection >
                                                                                             of        threshold
                                                                                          interest        of
                                                                                            \c\        interest
4 [mu]g/L.....................  4.01%.....................  2.48%.....................   \e\ 16.6 M        5.1 M
                                (155 of 3,865)............  (371 of 14,987)...........
5 [mu]g/L.....................  3.16%.....................  1.88%.....................       14.6 M        4.0 M
                                (122 of 3,865)............  (281 of 14,987)...........
7 [mu]g/L.....................  2.12%.....................  1.14%.....................        7.2 M        2.2 M
                                (82 of 3,865).............  (171 of 14,987)...........
10 [mu]g/L....................  1.35%.....................  0.65%.....................        5.0 M        1.5 M
                                (52 of 3,865).............  (97 of 14,987)............
12 [mu]g/L....................  1.09%.....................  0.42%.....................        3.6 M        1.2 M
                                (42 of 3,865).............  (63 of 14,984)............
15 [mu]g/L....................  0.80%.....................  0.29%.....................        2.0 M        0.9 M
                                (31 of 3,865).............  (44 of 14,987)............
17 [mu]g/L....................  0.70%.....................  0.24%.....................        1.9 M        0.8 M
                                (27 of 3,865).............  (36 of 14,987)............
20 [mu]g/L....................  0.49%.....................  0.16%.....................        1.5 M        0.7 M
                                (19 of 3,865).............  (24 of 14,987)............
25 [mu]g/L....................  0.36%.....................  0.12%.....................        1.0 M       0.4 M
                                (14 of 3,865).............  (18 of 14,987)............
\a\ All occurrence measures in this table were conducted on a basis reflecting values greater than the listed
\b\ The entry/sample-point-level population served estimate is based on the system entry/sample points that had
  at least 1 analytical detection for perchlorate greater than the threshold of interest. The UCMR 1 small
  system survey was designed to be representative of the nation's small systems, not necessarily to be
  representative of small system entry points.
\c\ The system-level population served estimate is based on the systems that had at least 1 analytical detection
  for perchlorate greater than the threshold of interest.
\d\ Because the population served by each entry/sample point is not known, EPA assumed that the total population
  served by a particular system is equally distributed across all entry/sample points. To derive the entry/
  sample point-level population estimate, EPA summed the population values for the entry/sample points that had
  at least 1 analytical detection greater than the threshold of interest.
\e\ This value does not include the population associated with 5 systems serving 200,000 people that measured
  perchlorate at 4 [mu]g/L in at least one sample.

    2. Supplemental Occurrence Data. The Agency also evaluated drinking 
water monitoring data for perchlorate in California and Massachusetts. 
EPA considers these State data to be supplemental for purposes of this 
regulatory determination, because they are not nationally 
representative. EPA believes these State's monitoring results are 
generally consistent with the results collected by EPA under UCMR 1. 
The California Department of Public Health

[[Page 60271]]

(CDPH) last updated its perchlorate monitoring results on July 10, 2008 
(CDPH, 2008). The Massachusetts's Department of Environmental 
Protection (MA DEP) last updated its draft report on The Occurrence and 
Sources of Perchlorate in Massachusetts in April, 2006 (MA DEP, 2005).

C. Evaluation of Perchlorate Exposure From Sources Other Than Drinking 

    An important element of EPA's regulatory determination process is 
to consider the contaminant exposure that individuals are likely to 
receive from sources other than drinking water. An individual's total 
exposure to a contaminant is more relevant to his or her risk for 
adverse health effects than is exposure to the contaminant from 
drinking water alone.
    Because there are significant sources of perchlorate exposure other 
than through the drinking water route, EPA determined that data on 
exposure to perchlorate from these sources is critical to the 
evaluation of whether or not there is a meaningful opportunity for 
health risk reduction through a national primary drinking water rule 
for perchlorate. Dietary studies pose a particular challenge because 
there is great variety in the American diet and many foods must be 
analyzed to enable a comprehensive dietary exposure estimate. However, 
EPA believes that two recent studies provide a sound basis for 
evaluating total perchlorate exposure. These are the Food and Drug 
Administration (FDA) Total Diet Study and an analysis of NHANES/UCMR 
data conducted by EPA and CDC.
    FDA's Total Diet Study (TDS) combines nationwide sampling and 
analysis of hundreds of food items along with national surveys of food 
intake to develop comprehensive dietary exposure estimates for a 
variety of demographic groups in the U.S. CDC's NHANES data base 
measured perchlorate in the urine of a representative sample of 
Americans. EPA and CDC used data from the NHANES data base and UCMR 
monitoring to estimate perchlorate exposure from food and water 
together, and food alone, for different sub-populations. This section 
of the notice provides details on the results of these studies. Because 
the sources of exposure encompassed by each of these studies overlap, 
EPA has considered them both in making a regulatory determination in an 
effort to provide the most comprehensive basis for the preliminary 
    In this section, EPA also provides a brief review of other dietary 
and biomonitoring studies that, while not directly incorporated into 
our determination, tend to reinforce the results of the primary 
exposure studies.
    1. Food Studies. The FDA, the United States Department of 
Agriculture (USDA), and other researchers have studied perchlorate in 
foods. The most recent and most comprehensive information available on 
the occurrence of perchlorate in the diet has been published by FDA. 
This section describes two perchlorate studies released by FDA.--the 
Total Diet Study and FDA's Exploratory Survey Data on Perchlorate in 
    a. FDA Total Diet Study, 2005 and 2006. Since 1961, FDA has 
periodically conducted a broad-based food monitoring study known as the 
Total Diet Study (TDS). The purpose of the TDS is to measure substances 
in foods representative of the total diet of the U.S. population, and 
to make estimates of the average dietary intake of those substances for 
selected age-gender groups. A detailed history of the TDS can be found 
at the following Web site: http://www.cfsan.fda.gov/~comm/tds-toc.html.
    Murray et al., (2008) briefly describe the design of the current 
TDS. Dietary intakes of perchlorate were estimated by combining 
analytical results from the TDS with food consumption estimates 
developed specifically for estimating dietary exposure from TDS 
results. While the perchlorate data for TDS foods were collected in 
2005-2006, the food consumption data in the current TDS food list is 
based on results (Egan et al., 2007) from the USDA's 1994-96, 1998 
Continuing Survey of Food Intakes by Individuals (94-98 CSFII), which 
includes data for all age groups collected in 1994-96, and for children 
from birth through age 9 collected in 1998. Although over 6,000 
different foods and beverages were included in the food consumption 
surveys, these foods and beverages were collapsed into a set of 285 
representative foods and beverages by aggregating the foods according 
to the similarity of their primary ingredients and then selecting the 
specific food consumed in greatest quantity from each group as the 
representative TDS food for that group. The consumption amounts of all 
the foods in a group were aggregated and assigned to the representative 
food for that group. It is these 285 representative foods and beverages 
that are on the current TDS food list. This approach to estimating 
dietary intakes assumes that the analytical profiles (e.g., perchlorate 
concentrations) of the representative foods are similar to those of the 
larger group of foods from the original consumption survey to which 
they correspond. This approach provides a reasonable estimate of total 
dietary exposure to the analytes from all foods in the diet, not from 
the representative TDS foods alone. The sampled TDS foods are purchased 
at retail from grocery stores and fast-food restaurants. The foods are 
prepared table-ready prior to analyses, using distilled water when 
water is called for in the recipe. The analytical method developed and 
used by FDA to measure perchlorate in food samples has a nominal limit 
of detection (LOD) of 1.00 ppb and a limit of quantitation (LOQ) of 
3.00 ppb (Krynitsky et al., 2006).
    Murray et al., (2008) reports that FDA included perchlorate as an 
analyte in TDS baby foods in 2005 and in all other TDS foods in 2006. 
Iodine was analyzed in all TDS foods from five market baskets surveyed 
in late 2003 through 2004. Using these data collectively, FDA developed 
estimates of average dietary perchlorate and iodine intake for 14 age-
gender groups. To account for uncertainties associated with samples 
with no detectable concentrations of perchlorate or iodine (non-detects 
or NDs), FDA calculated a lower-bound and upper-bound for each estimate 
of average dietary exposure, assuming that NDs equal to zero and the 
LOD, respectively. Specifically, FDA multiplied these upper- and lower-
bound concentrations by the average daily consumption amount of the 
representative food for the given subpopulation group to provide a 
range of average intakes for each TDS food.
    Table 3 summarizes the FDA estimated upper- and lower-bound average 
dietary perchlorate intakes (from food) for 14 age-gender groups on a 
per kilogram of body weight per day basis to enable direct comparison 
to the perchlorate RfD. Murray et al., (2008) reports that average body 
weights for each population group were based on self-reported body 
weights from respondents in the 94-98 CSFII.

[[Page 60272]]

  Table 3--Lower- and Upper-Bound (ND = 0 and LOD) Perchlorate Intakes
                  From FDA's TDS Results for 2005-2006
                                            Average perchlorate intake
                                             from food  ([mu]g/kg/day)
            Population group             -------------------------------
                                            Lower-bound     Upper-bound
Infants--6-11 mo........................            0.26            0.29
Children--2 yr..........................            0.35            0.39
Children--6 yr..........................            0.25            0.28
Children--10 yr.........................            0.17            0.20
Teenage Girls--14-16 yr.................            0.09            0.11
Teenage Boys--14-16 yr..................            0.12            0.14
Women--25-30 yr.........................            0.09            0.11
Men--25-30 yr...........................            0.08            0.11
Women--40-45 yr.........................            0.09            0.11
Men--40-45 yr...........................            0.09            0.11
Women--60-65 yr.........................            0.09            0.10
Men--60-65 yr...........................            0.09            0.11
Women--70+ yr...........................            0.09            0.11
Men--70+ yr.............................            0.11            0.12

    Based on their analysis of TDS data, FDA reports that detectable 
levels of perchlorate were found in at least one sample in 74 percent 
(211 of 286) of TDS foods (Murray et al., 2008). The average estimated 
perchlorate intakes for the 14 age-gender groups range from 0.08 to 
0.39 [mu]g/kg/day, compared with the RfD of 0.7 [mu]g/kg/day. Though 
not shown here, Murray et al., (2008) reports that average estimated 
iodine intakes for the 14 age-gender groups range from 138 to 353 
[mu]g/person/day, and for all groups exceed the relevant U.S. dietary 
reference values used for assessing the nutritional status of 

    \11\ Murray et al., (2008) compared estimated average iodine 
intakes with U.S. Dietary Reference Intakes for iodine (NAS, 2000). 
The reference values cited by Murray et al., (2008) are as follows: 
130 [mu]g/person/day for infants, 65 [mu]g/person/day for children 
1-8 years, 73 [mu]g/person/day for children 9-13 years, and 95 
[mu]g/person/day for the remainder of population.

    The results of the TDS dietary intake assessment provide an 
estimate of the average dietary perchlorate intakes by specific age-
gender groups in the U.S. However, Murray et al. note that the current 
TDS design ``does not allow for estimates of intakes at the extremes 
(i.e., upper or lower percentiles of food consumption) or for 
population subgroups within the 14 age/sex groups that may have 
specific nutritional needs (e.g., the subgroups of pregnant and 
lactating women within the groups of women of child bearing age).'' 
Nevertheless, Murray et al. stated that: ``These TDS results increase 
substantially the available data for characterizing dietary exposure to 
perchlorate and provide a useful basis for beginning to evaluate 
overall perchlorate and iodine estimated dietary intakes in the U.S. 
    b. FDA Exploratory Survey Data on Perchlorate in Food, 2003-2005. 
Prior to including perchlorate in the TDS, FDA conducted exploratory 
surveys from October 2003 to September 2005 to determine the occurrence 
of perchlorate in a variety of foods. In May 2007, FDA provided an 
estimate of perchlorate exposure from these surveys (http://
www.cfsan.fda.gov/~dms/clo4ee.html). Using the data from these 
exploratory studies and food and beverage consumption values from 
USDA's 94-98 CSFII, FDA estimated mean perchlorate exposures of 0.053 
[mu]g/kg/day for all ages (2+ years), 0.17 [mu]g/kg/day for children 
(2-5 years), and 0.037 [mu]g/kg/day for females (15-45 years). There 
are uncertainties associated with the preliminary exposure assessment 
because the 27 foods and beverages selected represent only about 32 to 
42 percent of the total diet depending on the population group. 
Additionally, the overall goal of the sampling plan was to gather 
initial information on occurrence of perchlorate in foods from various 
locations with a high likelihood of perchlorate contamination. With the 
preceding caveats in mind, the results of these exploratory studies are 
generally consistent with the more complete results of the 2005-2006 
TDS. For the purpose of developing a national estimate of dietary 
perchlorate exposure, the results of FDA's exploratory studies are 
superseded by the results of the TDS.
    c. Other Published Food Studies.
    Since publication of EPA's May 2007 notice, Pearce et al., (2007) 
published an analysis of perchlorate concentrations in 17 brands of 
prepared ready to eat and concentrated liquid infant formula. 
Perchlorate concentrations in the 17 samples ranged from 0.22 to 4.1 
[mu]g/L, with a median concentration of 1.5 [mu]g/L. The researchers 
did not estimate the dose infants would consume at the concentrations 
observed in the study. FDA also included sampling and analysis of 
infant formula in their 2008 TDS analysis, discussed above.
    Studies, such as those published by Kirk et al., (2003, 2005) and 
Sanchez et al., (2005a, 2005b) have examined perchlorate in milk and 
produce. These studies and others were summarized in EPA's May 2007 
notice describing the status of EPA's evaluation of perchlorate (72 FR 
24016 (USEPA, 2007)).
    2. Biomonitoring Studies. Researchers have also begun to 
investigate perchlorate occurrence in humans by analyzing for 
perchlorate in urine and breast milk. For example, CDC has included 
perchlorate in its National Biomonitoring Program, which develops 
methods to measure environmental chemicals in humans. With this 
information, the CDC can obtain data on levels and trends of exposure 
to environmental chemicals in the U.S. population.
    a. Urinary Biomonitoring. In the largest study of its kind, Blount 
et al., (2006c) measured perchlorate in urine samples collected from a 
nationally representative sample of 2,820 U.S. residents as part of the 
2001-2002 NHANES. Blount et al., (2006c) detected perchlorate at 
concentrations greater than 0.05 [mu]g/L in all 2,820 urine samples 
tested, with a median concentration of 3.6 [mu]g/L and a 95th 
percentile of 14 [mu]g/L. Women of reproductive age (15-44 years) had a 
median urinary perchlorate

[[Page 60273]]

concentration of 2.9 [mu]g/L and a 95th percentile of 13 [mu]g/L. The 
demographic with the highest concentration of urinary perchlorate was 
children (6-11 years), who had a median urinary perchlorate 
concentration of 5.2 [mu]g/L. Blount et al., (2006c) estimated a total 
daily perchlorate dose for the NHANES participants aged 20 and older 
(for whom a creatinine correction method was available) and found a 
median dose of 0.066 [mu]g/kg/day (about one tenth of the RfD) and a 
95th percentile dose of 0.234 [mu]g/kg/day (about one third of the 
RfD). Eleven adults (0.7 percent) had estimated perchlorate exposure 
greater than perchlorate's RfD of 0.7 [mu]g/kg/day (the highest 
calculated exposure was 3.78 [mu]g/kg/day). Because of daily 
variability in diet and perchlorate exposure, and the short residence 
time of perchlorate in the body, these single sample measurements may 
overestimate long-term average exposure for individuals at the upper 
end of the distribution and may underestimate the long-term average 
exposure for individuals at the lower end of the distribution. Blount 
et al. did not estimate daily perchlorate dose for children and 
adolescents due to the limited validation of estimation methods for 
these age groups at that time (Blount et al., 2006c).
    In a recent unpublished, but peer reviewed, study, EPA and CDC 
investigators merged the data sets from NHANES and UCMR 1 to identify 
the NHANES participants from counties which had a perchlorate detection 
during the UCMR survey (USEPA, 2008a). The study assumes, based on 
previous analyses of perchlorate pharmacokinetics, that urine is the 
sole excretion pathway other than in lactating women. Since all NHANES 
participants' urine contained perchlorate, separating out those who had 
a higher potential for additional exposure via drinking water from 
those who had a lower potential for drinking water exposure left the 
remainder of participants whose exposure was expected to be primarily 
from food.
    The advantage of a urinary biomonitoring study is that it analyzes 
the perchlorate actually ingested in the diets of a large number of 
individuals rather than using estimators of perchlorate ingestion from 
a variety of foods for a diverse population. The methodology provides a 
novel opportunity to use public water system occurrence and human 
biomonitoring data to directly inform EPA's decision. The approach is 
reasonable for estimating perchlorate intake at various percentiles 
from food and to gain an understanding of the relative contribution 
from water. A limitation is in the use of NHANES's spot urine testing, 
and creatinine corrections for a population with diverse physiological 
characteristics, to calculate the daily perchlorate dose. The cross 
sectional study attempts to capture a representative exposure, but was 
limited by the need to match up drinking water occurrence data with 
biomonitoring data on a county-wide basis, even though county and 
public water system service area boundaries often do not coincide. 
There also may have been some temporal mismatch between the occurrence 
and biomonitoring data.
    As noted, the primary goal of the study was to derive the dose of 
perchlorate coming from food alone by eliminating possible sources of 
water contribution. Individuals' data were placed into one of three 
bins based on likelihood of perchlorate being in their tap water. The 
bins were further sorted by age and sex. Bin I was comprised of NHANES 
2001-2002 data for individuals residing in the same counties as public 
water systems that had at least one positive measurement of perchlorate 
during the sample period, as measured in UCMR 1. Therefore, this bin 
represented those who were more likely to be exposed to perchlorate in 
both food and water. For the most part, the average perchlorate level 
in urine for all age groups was the highest in this bin, and the 
creatinine-corrected average dose for all individuals in this group was 
0.101 [mu]g/kg/day, with a geometric mean of 0.080 [mu]g/kg/day.
    In contrast, Bin III was comprised of data for individuals 
considered less likely to have exposure to perchlorate via drinking 
water, as defined in one of three ways: (1) They resided in counties 
where there were no quantified detections of perchlorate in public 
drinking water systems sampled as part of UCMR (i.e., UCMR 1 results 
were below the minimum reporting limit of 4 [mu]g/L); or (2) they self-
reported that they had not consumed tap water in the previous 24 hours 
regardless of where they resided (i.e., they may have resided in a 
county with a positive UCMR finding, but did not drink tap water); or 
(3) again, not considering the UCMR status of the county, their 
response to NHANES indicated they used a reverse osmosis filter which 
may be effective for removing perchlorate. Bin III thus represents 
results of urinary perchlorate from individuals who were less likely to 
experience perchlorate exposure via tap water, and were thus more 
likely to have their perchlorate exposure caused solely by intake from 
food. The average creatinine-corrected perchlorate dose for these 
individuals was 0.090 [mu]g/kg/day, with a geometric mean of 0.062 
    Finally, Bin II included individuals residing in counties which had 
not been sampled in UCMR. As such, there is no information on potential 
perchlorate in their public drinking water. The average creatinine-
corrected perchlorate dose for these individuals was 0.072 [mu]g/kg/
day, with a geometric mean of 0.053 [mu]g/kg/day. The results for Bin 
II are somewhat anomalous, and may suggest either that drinking water 
concentrations are even lower in these non-monitored counties than in 
the Bin III counties or that food exposure for these counties was lower 
than for the counties in either Bin I or III. In any case, EPA's 
analysis to determine the RSC did not focus on Bin II, as discussed 
    A summary of selected results for individuals in Bins I and III is 
shown in Table 4. The estimates of daily perchlorate intake presented 
in Table 4 from the NHANES-UCMR analysis are somewhat higher than those 
of Blount et al., (2006). The Blount et al., (2006) estimates were 
limited to adults 20 years of age and older because application of the 
set of creatinine excretion equations used by Blount et al. to estimate 
perchlorate dose was limited to adults. Mage et al., (2007) provides an 
expanded set of equations that allows for estimating daily creatinine 
excretion rates for children, as well as for adults. Since children 
tend to have higher exposure on a per body weight basis than adults, it 
is not surprising that the estimates based on both adults and children 
are somewhat higher than the Blount estimates based on adults alone. 
The mean total exposure for people that are more likely to be exposed 
to perchlorate in food and water (Bin I) was calculated to be 0.101 
[mu]g/kg/day. The average exposure for people more likely to be exposed 
to perchlorate from food alone (Bin III) was 0.090 [mu]g/kg/day.

[[Page 60274]]

    Table 4--Estimated Daily Perchlorate Intakes ([mu]g/kg/day) for Two Bins Based on UCMR 1 Occurrence Data
                                                  Number of     Average     Geometric       50th         90th
              Group                    Bin*         people       (mean)        mean      percentile   percentile
Total............................            I           320        0.101        0.080        0.075        0.193
                                           III         2,063        0.090        0.062        0.058        0.167
Age: 6-11........................            I            52        0.152        0.132        0.131        0.237
                                           III           270        0.150        0.118        0.124        0.280
Age: 12-19.......................            I           100        0.109        0.078        0.070        0.286
                                           III           608        0.080        0.061        0.060        0.158
Age: 20 or more..................            I           168        0.091        0.074        0.071        0.186
                                           III         1,185        0.085        0.057        0.055        0.143
Females: 15-44...................            I            57        0.081        0.062        0.071        0.141
                                           III           505        0.093        0.055        0.052        0.143
Pregnant Females.................            I             8        0.097        0.086        0.060        0.121
                                           III            98        0.123        0.064        0.056       0.263
* Bin I was comprised of individuals residing in counties which had at least one positive measurement of
  perchlorate somewhere in the public drinking water supply. Bin III was comprised of individuals considered
  less likely to have exposure to perchlorate via drinking water based on a three-part test (see text).

    Using Bin III as the dose most closely representing only dietary 
perchlorate exposure, one can compare results from the FDA TDS, shown 
previously in Table 3. For example, for females 14-16, women 25-30, and 
women 40-45 years old, the FDA mean food dose was 0.09-0.1 [mu]g/kg/
day. In the EPA-CDC biomonitoring study of NHANES-UCMR, the mean food 
dose for women of child-bearing age (15-44 years old) was 0.093 [mu]g/
kg/day. The results from calculating likely food intakes (TDS study) 
and from urinalysis from actual intakes (NHANES/UCMR) are in close 
agreement where comparisons can be made.
    b. Breast Milk. A number of studies have investigated perchlorate 
in human breast milk. The most recent study included measurements from 
49 healthy Boston-area volunteers (10-250 days postpartum, median 48 
days; Pearce et al., 2007). Perchlorate was found in all samples, 
ranging from 1.3-411 [mu]g/L, with a median concentration of 9.1 [mu]g/
L and a mean concentration of 33 [mu]g/L. No correlation was found 
between perchlorate and iodine concentrations in breast milk. EPA notes 
that the Boston-area public water systems did not detect perchlorate in 
drinking water samples collected for the U.S. EPA's Unregulated 
Contaminant Monitoring Rule from 2001 to 2003, nor did Boston area 
systems detect perchlorate in samples collected in response to the 
Massachusetts DEP 2004 emergency regulations for perchlorate (see 
Section III.B of this notice).
    Kirk et al., (2005) analyzed 36 breast milk samples from 18 States 
(CA, CT, FL, GA, HI, MD, ME, MI, MO, NC, NE, NJ, NM, NY, TX, VA, WA, 
WV) and found perchlorate concentrations in all samples ranging from 
1.4 to 92.2 [mu]g/L, with a mean concentration of 10.5 [mu]g/L. Kirk et 
al., (2007) later did a smaller study involving 10 women, which 
included 6 samples on each of 3 days in a temporal study. Half the 
women were from Texas, but the others were from CO, FL, MO, NM, and NC. 
They found significant variation in all samples (n=147), with a range, 
mean, and median perchlorate concentration of 0.5-39.5 [mu]g/L, 5.8 
[mu]g/L, and 4.0 [mu]g/L, respectively.
    T[eacute]llez et al., (2005) reported maternal parameters for 
participants from a study conducted in Chile. Breast milk samples 
indicated that a significant amount of perchlorate leaves the body of 
the nursing mother through breast milk, in addition to urine. However, 
the breast milk perchlorate levels were highly variable and no 
significant correlations could be established between breast milk 
perchlorate and either urine perchlorate or breast milk iodide 
concentrations for the individuals evaluated in these Chilean cities 
(T[eacute]llez et al., 2005).
    Blount et al., (2007) also suggests breast milk as an excretion 
pathway and the NHANES-UCMR study authors observed a difference between 
the urinary perchlorate concentration of breast feeding women versus 
pregnant women with an overall mean concentration of 0.130 [mu]g/kg/day 
for 117 pregnant women compared to a concentration of 0.073 [mu]g/kg/
day for the 24 breast-feeding women (USEPA, 2008a).
    Dasgupta et al., (2008) analyzed breast milk samples and 24 hour 
urine samples from 13 lactating women from Texas for perchlorate and 
iodine. For breast milk, they found perchlorate concentrations ranging 
from 0.01 to 48 [mu]g/L, with a median concentration of 7.3 [mu]g/L and 
a mean concentration of 9.3 [mu]g/L (457 total samples). For iodine, 
concentrations ranged from 1 to 1,200 [mu]g/L, with a median 
concentration of 43 [mu]g/L and a mean concentration of 120 [mu]g/L 
(447 total samples). For urine they found perchlorate concentrations 
ranging from 0.6 to 80 [mu]g/L, with a median concentration of 3.2 
[mu]g/L and a mean concentration of 4.0 [mu]g/L (110 total samples). 
For iodine, concentrations ranged from 26 to 630 [mu]g/L, with a median 
concentration of 110 [mu]g/L and a mean concentration of 140 [mu]g/L 
(117 total samples)

IV. Preliminary Regulatory Determination for Perchlorate

    In making preliminary regulatory determinations, EPA uses the 
criteria mandated by the 1996 SDWA Amendments. EPA has found that 
perchlorate, at sufficiently high doses, may have an adverse effect on 
the health of persons, and that perchlorate is found in a small 
percentage of public water supply systems. However, EPA has determined 
that regulation of perchlorate in drinking water systems does not 
present a meaningful opportunity to reduce health risk for persons 
served by public water systems. This section describes how EPA has 
evaluated these three criteria in light of the data presented in 
Section III to make

[[Page 60275]]

a preliminary regulatory determination for perchlorate.

A. May Perchlorate Have an Adverse Effect on the Health of Persons?

    Yes. Perchlorate interacts with the sodium iodide symporter, 
reducing iodine uptake into the thyroid gland and, at sufficiently high 
doses, the amount of T4 produced and available for release into 
circulation. Sustained changes in thyroid hormone secretion can result 
in hypothyroidism. Thyroid hormones stimulate diverse metabolic 
activities in most tissues and individuals suffering from 
hypothyroidism experience a general slowing of metabolism of a number 
of organ systems. In adults, these effects are reversed once normal 
hormone levels are restored (NRC, 2005).
    In fetuses, infants, and young children, thyroid hormones are 
critical for normal growth and development. Irreversible changes, 
particularly in the brain, are associated with hormone insufficiencies 
during development in humans (Chan and Kilby, 2000 and Glinoer, 2007). 
Disruption of iodide uptake presents particular risks for fetuses and 
infants (Glinoer, 2007 and Delange, 2004). Because the fetus depends on 
an adequate supply of maternal thyroid hormone for its central nervous 
system development during the first trimester of pregnancy, iodide 
uptake inhibition from perchlorate exposure has been identified as a 
concern in connection with increasing the risk of neurodevelopmental 
impairment in fetuses of high-risk mothers (NRC, 2005). Poor iodide 
uptake and subsequent impairment of thyroid function in pregnant and 
lactating women have been linked to delayed development and decreased 
learning capability in infants and children with fetal and neonatal 
exposure (NRC, 2005)
    The NRC recommended basing the RfD on a precursor to an adverse 
effect rather than an adverse effect per se. The precursor event 
precedes a downstream adverse effect in the dose response continuum. In 
this case, NRC used prevention of iodide uptake inhibition, a precursor 
to adverse thyroid effects, to establish a level at which no adverse 
effects would be anticipated in exposed populations. This approach is 
consistent with the Agency's policy on the use of precursor events when 
appropriate in establishing the critical effect upon which an RfD is 
based (U.S. EPA, 2002c).
    Based on the information above, EPA finds that perchlorate, at 
sufficiently high doses, may have an adverse effect on the health of 

B. Is Perchlorate Known To Occur or Is There a Substantial Likelihood 
That Perchlorate Occurs at a Frequency and at a Level of Public Health 
Concern in Public Water Systems?

    No. EPA has found that perchlorate occurs infrequently at levels of 
health concern in public water systems. Specifically, EPA established a 
Health Reference Level (HRL) as the level of concern and evaluated the 
information on the occurrence of perchlorate in public water systems 
presented in Section III.B in relation to this HRL. The HRL is a 
benchmark against which EPA compares the concentrations of a 
contaminant found in public water systems to determine if it is at a 
level of public health concern. For past regulatory determinations for 
non-carcinogens, EPA has calculated an HRL using the Agency's reference 
dose (RfD) as follows:

HRL = [(RfD x BW)/DWI] x RSC


RfD = Reference Dose
BW = Body Weight for an adult assumed to be 70 kilograms (kg)
DWI = Drinking Water Intake for an adult, assumed to be 2 L/day
RSC = Relative Source Contribution, or the remaining portion of the 
reference dose available for drinking water after other sources of 
exposure have been considered (e.g., food, ambient air)

    In addition, EPA has used a RSC default value of 20 percent for 
screening purposes to estimate the HRL for past regulatory 
determinations because it has lacked adequate data to develop an 
empirical RSC. In the absence of such data, EPA has determined that it 
is appropriate to use a conservative value that is more likely to 
understate than to overstate the amount of contaminant that can be 
safely ingested through drinking water. For its two previous sets of 
regulatory determinations, EPA did not find contaminants at frequencies 
and levels of concern in comparison to the conservative screening-level 
HRL. Therefore, it was not necessary for the Agency to further evaluate 
the RSC in making regulatory determinations for these contaminants.
    However, the Agency believes that sufficient exposure data are 
available for perchlorate to enable EPA to estimate a better informed 
RSC and HRL that is more appropriate for fetuses of pregnant women (the 
most sensitive subpopulations identified by the NRC). These exposure 
data include the further analysis by EPA of the UCMR data and the CDC's 
NHANES biomonitoring data, as well as the FDA's Total Diet Study. The 
following sections describe EPA's analyses of each of these data 
sources to estimate RSCs and HRLs for this sensitive subpopulation.
    1. Total Diet Study for Estimation of an RSC. The results of FDA's 
recent evaluation of perchlorate under the TDS were presented in 
Section III.C.1 of this notice. The TDS estimates are representative of 
average, national, dietary perchlorate exposure, for the age-gender 
groups that were selected. EPA used FDA's dietary exposure estimates to 
calculate RSC values by subtracting the dietary estimates from the RfD 
(0.7 [mu]g/kg/day), dividing this difference by the RfD, and 
multiplying the result by 100 (to convert it to a percentage). Because 
EPA believes that dietary ingestion is the only significant pathway for 
non-drinking-water perchlorate exposure, the resulting RSCs represent 
the amount of perchlorate exposure (as a percentage of the RfD) that 
the average individual within a subgroup would have to ingest via 
drinking water in order to reach a level of total perchlorate exposure 
that equals the RfD. These RSCs, displayed as percentages, are 
presented in Table 5.

          Table 5--Relative Source Contributions Remaining for Water Based on TDS for Various Subgroups
                                                                       Total                       RSC remaining
                                                                    perchlorate      RfD that      for drinking
                        Population group                            intake from   remains ([mu]g/   water (as a
                                                                  food ([mu]g/kg/     kg/day)      percentage of
                                                                       day)                          the RfD)
Infants, 6-11 mo................................................       0.26-0.29       0.41-0.44           59-63
Children, 2 yr..................................................       0.35-0.39       0.31-0.35           44-50
Children, 6 yr..................................................       0.25-0.28       0.42-0.45           60-64
Children, 10 yr.................................................       0.17-0.20       0.50-0.53           71-76
Teenage Girls, 14-16 yr.........................................       0.09-0.11       0.59-0.61           84-87

[[Page 60276]]

Teenage Boys, 14-16 yr..........................................       0.12-0.14       0.56-0.58           80-83
Women, 25-30 yr.................................................       0.09-0.11       0.59-0.61           84-87
Men, 25-30 yr...................................................       0.08-0.11       0.69-0.62           84-89
Women, 40-45 yr.................................................       0.09-0.11       0.59-0.61           84-87
Men, 40-45 yr...................................................       0.09-0.11       0.59-0.61           84-87
Women, 60-65 yr.................................................       0.09-0.10       0.60-0.61           86-87
Men, 60-65 yr...................................................       0.09-0.11       0.59-0.61           84-87
Women, 70+ yr...................................................       0.09-0.11       0.59-0.61           84-87
Men, 70+ yr.....................................................       0.11-0.12       0.58-0.59           83-84

    The subpopulation that is the most sensitive to perchlorate 
exposure is the fetus of an iodine-deficient pregnant woman. The FDA 
TDS does not estimate the dietary intake of perchlorate specifically 
for pregnant women (nor can it specifically address iodine-deficient 
women); but it does present dietary estimates for three groups of women 
of childbearing age (Teenage girls 14-16, Women 25-30 and Women 40-45). 
The calculated RSCs range from 84 to 87 percent for women of 
childbearing age. Murray et al. (2008) suggested that perchlorate 
intake rates for pregnant and lactating women are ``likely to be 
somewhat higher than those of women of childbearing age as a whole.'' 
If this is true, an RSC derived based upon the TDS mean dietary intake 
for women of childbearing age may underestimate the relative source 
contribution from food for pregnant women.
    2. Urinary Data for Estimation of an RSC. As described in Section 
III.C.2 of this notice, EPA and CDC researchers analyzed NHANES urinary 
data in conjunction with UCMR occurrence data at the CDC's National 
Center for Environmental Health (NCEH) to evaluate exposure to 
perchlorate. These data were partitioned to provide an estimate of what 
portion of the overall exposure likely came from food alone. In this 
analysis, EPA and CDC researchers were able to characterize the 
distribution of actual perchlorate exposure as seen in their urine for 
pregnant women. This means that the analysis could determine not only 
the mean exposure, but also the exposure of highly exposed individuals. 
Results of this analysis, presented in Table 6, indicate that for 
pregnant women, exposure to perchlorate from food is 0.263 [mu]g/kg/day 
at the 90th percentile, representing nearly 38 percent of the RfD, and 
thus leaving an RSC for water of 62 percent.

             Table 6--Dose Remaining for Water, and Fraction of RfD (RSC) Based on NHANES-UCMR Analysis Calculations of Perchlorate in Food
                                            Mean food    RfD that                 Median      RfD that               percentile    RfD that
                  Group                       dose       remains     RSC as %    food dose    remains     RSC as %    food dose    remains     RSC as %
                                           ([mu]g/kg/   ([mu]g/kg/    of RfD    ([mu]g/kg/   ([mu]g/kg/    of RfD    ([mu]g/kg/   ([mu]g/kg/    of RfD
                                              day)         day)                    day)         day)                    day)         day)
Total population.........................       0.090        0.61           87       0.075        0.625          89       0.167        0.533          76
Ages 6-11................................       0.150        0.55           79       0.124        0.58           83       0.280        0.42           60
Ages 12-19...............................       0.080        0.62           89       0.060        0.64           91       0.158        0.542          77
Ages 20 +................................       0.085        0.615          88       0.055        0.645          92       0.143        0.557          80
Female 15-44.............................       0.093        0.607          87       0.052        0.65           93       0.143        0.557          80
Pregnant.................................       0.123        0.58           82       0.056        0.64           91       0.263        0.437          62

    3. HRL Derivation. EPA believes the NHANES-UCMR analysis is the 
best available information to characterize non-drinking water exposures 
to perchlorate for the most sensitive subpopulation. The FDA Total Diet 
Study provides a nationally representative estimate of the mean dietary 
exposure to perchlorate for 14 age and gender groups, including women 
of childbearing age. However, this study does not provide specific 
estimates for the most sensitive subpopulation, the iodine-deficient 
pregnant woman and her fetus. Also, this study estimates only mean 
exposures, so it does not account for the perchlorate exposure of 
highly exposed individuals. The NHANES-UCMR analysis provides a 
distribution of exposure (not just a mean) specific to almost 100 
pregnant women who are not likely to have been exposed to perchlorate 
from their drinking water, although it also does not separate out 
iodine-deficient pregnant women because of data limitations. Table 7 
presents the HRLs developed for the most sensitive subpopulation using 
the TDS data and the NHANES-UCMR data. EPA notes that the mean RSC for 
pregnant women estimated from the NHANES-UCMR data is very close to, 
but slightly lower than, the mean for women of childbearing age 
estimated from the TDS data. This shows close agreement between the two 
data sets and is consistent with the suggestion in Murray et al. that 
food exposures for pregnant women are likely to be somewhat higher than 
for women of childbearing age as a whole. (Note that higher food 
exposure equates to a lower RSC because a smaller fraction of the RfD 
is left to be allocated to drinking water.) While the means are 
available (and in close agreement) from both data sets, EPA believes it 
is more protective to estimate the HRL for drinking water by 
subtracting the 90th percentile exposure in food from the reference

[[Page 60277]]

dose to assure that the highly exposed individuals from this most 
sensitive subpopulation are considered in the evaluation of whether 
perchlorate is found at levels of health concern. The NHANES-UCMR data 
allow for the calculation of the 90th percentile food exposure, which 
results in an HRL of 15 [mu]g/L for the pregnant woman.

             Table 7--Health Reference Levels for Pregnant Women Using TDS Data and NHANES-UCMR Data
                                                  Drinking water    Source of RSC        RSC
         Subpopulation          Body weight \a\  consumption \a\      derivation      (percent)         HRL
Women of Childbearing Age.....  70 kg..........  2 liters.......  TDS mean (Table          84-87  21 [mu]g/L
Pregnant Women................  70 kg..........  2 liters.......  NHANES-UCMR mean            82  20 [mu]g/L
                                                                   (Table 6).
Pregnant Women................  70 kg..........  2 liters.......  NHANES-UCMR 90th            62  15 [mu]g/L
                                                                   (Table 6).
\a\ Default values used by EPA in the derivation of HRLs.

    4. Frequency of Exposure at Health Reference Level. The number of 
pregnant women potentially exposed to perchlorate in public drinking 
water above these HRLs can be estimated from the UCMR data. Using the 
data presented in Table 2, approximately 0.8 percent of the systems had 
one or more detections of perchlorate at or above 15 [mu]g/L, the HRL 
determined for pregnant women in this analysis. These systems serve a 
total of 2.0 million persons in their entire service area, of which 1.0 
million are females, and thus might become pregnant at some point 
during their lives. However, not all water system customers are living 
in households that are served water from the entry point(s) that tested 
positive. Table 2 also provides a more refined estimate of the 
potentially exposed population by factoring in an estimate of the 
portion of the system population served by each entry point (as 
described in Section III.B.1. of this notice). Using this second 
approach, which is likely to be more accurate, the number of people 
served by entry points which exceed the HRL is 0.9 million, of which 
0.45 million are females. EPA estimates that at any one time, 1.4 
percent of the population from Table 2 served by water systems (or 
entry points) that detected perchlorate at levels greater than 15 
[mu]g/L (Table 7) are pregnant women. This estimate is based on the 
number of live births (4,059,000, Ventura et al., 2004) as a percentage 
of the total U.S. population in 2000 (281,421,906, U.S. Census Bureau, 
2002). Therefore, a best estimate of about 16,000 pregnant women (with 
a high end estimate of 28,000) could be exposed at levels exceeding the 
HRL at any given time.
    Based on this analysis, EPA concludes that perchlorate occurs 
infrequently at levels of health concern in public water systems. There 
are a small percentage of public water systems (0.8 percent) where 
drinking water above the HRL, in combination with perchlorate from 
food, may result in exposures to pregnant women at levels that exceed 
the EPA reference dose for perchlorate. However, as explained in 
section IV.C, these exposures to perchlorate in drinking water at 
concentrations above the HRL do not rise to the level of a meaningful 
opportunity for public health risk reduction through a national primary 
drinking water regulation.
5. Consideration of Sensitive Subpopulations
    In making a regulatory determination, the SDWA requires EPA to take 
into consideration the effect of contaminants on subgroups that 
comprise a meaningful portion of the general population that are 
identifiable as being at greater risk of adverse health effects due to 
exposure to contaminants in drinking water than the general population.
    As noted above, in past regulatory determinations, EPA has 
calculated a screening level HRL based on drinking water consumption 
and body weight information for adults in general, combined with 
default assumptions about RSC, in the absence of robust empirical data. 
For this preliminary perchlorate determination, EPA has improved on 
this approach by using body weight, drinking water and food exposure 
data for pregnant women, in order to protect the most sensitive 
subpopulation identified by the NRC (i.e., the fetuses of these women). 
In addition, EPA has used 90th percentile rather than mean food 
exposure data to ensure that the HRL protects highly exposed pregnant 
women and their fetuses. However, infants, developing children, and 
people with iodine deficiency or thyroid disorders were also identified 
as sensitive subpopulations by the NRC. Because infants and children 
eat and drink more on a per body weight basis than adults, eating a 
normal diet and drinking water with 15 [mu]g/L of perchlorate may 
result in exposure that is greater than the reference dose in these 
groups. To address this concern, the potential effect of this intake on 
inhibition of iodide uptake in these subgroups (i.e., relative 
sensitivity) was evaluated using PBPK modeling, as discussed in Section 
III.A.3. Because the NRC (NRC, 2005) found that the inhibition of 
iodide uptake by the thyroid, which is a non-adverse precursor to any 
adverse effect, should be used as the basis for perchlorate risk 
assessment, evaluating iodide uptake inhibition is important for 
determining whether the HRL of 15 [mu]g/L (derived for pregnant women) 
is also an appropriate health reference level for the other sensitive 
subpopulations. Reducing some of the uncertainty regarding the relative 
sensitivities of these subpopulations will help to address the concerns 
that some groups may be exposed above the reference dose (calculated 
using group-specific body weight and intake information), particularly 
if PBPK modeling predicts that at the HRL, these groups do not 
experience precursor effects (RAIU inhibition) that exceed the no 
effect level from which the reference dose was derived.
    a. Published PBPK Models. The Clewell et al. (2007) and Merrill et 
al. (2005) PBPK models predict the distribution and elimination of 
perchlorate after it is ingested. The models also predict the level of 
RAIU inhibition that would result from different levels of perchlorate 
exposure for different subpopulations, including children and infants.
    Clewell et al. (2007) predicted that at a perchlorate dose of 0.001 
mg/kg/day (1 [mu]g/kg/day), approximately one and one half times the 
RfD, iodide uptake inhibition in the most sensitive populations, i.e., 
fetuses and infants, was no greater than 1.1 percent. This is below the 
level (1.8 percent) of inhibition at the NRC identified no-effect level 
(NOEL) in healthy adults and recommended as the point of departure for 
calculating the RfD, applying a 10-fold intraspecies uncertainty 
factor. The fact that for all subpopulations the predicted RAIU at a

[[Page 60278]]

level slightly above the RfD is still below the RAIU at the NOEL is 
consistent with the NRC's conclusion that the RfD would protect even 
the most sensitive sub-populations. However, because the Clewell model 
does not account for reduced urinary clearance that occurs in young 
infants, EPA modified the model as discussed in Section III.A.3 to 
address this and other limitations.
    b. Results of EPA's Application of the Published Models. EPA 
evaluated the published models (Clewell et al., 2007, and Merrill et 
al., 2005) and used them to further explore the relationship between 
water concentrations and iodide uptake inhibition in different 
subpopulations. As noted in Section III.A.3 and discussed in more 
detail in EPA's description of the model (USEPA, 2008b), EPA determined 
that it was appropriate to make several changes to the models' computer 
codes in order to harmonize them and more adequately reflect the 
biology. EPA considered in detail the data currently available for 
parameters determined to be particularly important to the models' 
predictions, and modified the model parameters describing exposure as 
well as urinary excretion of perchlorate and iodide. These 
modifications resulted in predicted RAIU inhibition rates that were up 
to 1.5 times the predicted inhibition rates in the earlier versions of 
the model. EPA believes its revisions have improved the predictive 
power of the model and has used its results as the basis for the 
following discussion.
    Consistent with both the unmodified Clewell model and the NRC's 
conclusions, EPA's analysis identified the near-term fetus (gestation 
week 40 fetus) as the most sensitive subgroup, with a percent RAIU 
inhibition that was 5-fold higher than the percent inhibition of the 
average adult at a dose equal to the point of departure (7 [mu]g/kg/
day). After correcting the model for reduced urinary clearance in 
infants, the same analysis shows that the predicted percent RAIU 
inhibition is approximately 1-to 2-fold higher for the breast-fed and 
bottle-fed infant (7-60 days) than for the average adult, and is 
slightly lower for the 1-2 year old child than for the average adult. 
While uncertainty remains regarding the model's predictions, EPA 
believes that it is a useful tool, in conjunction with appropriate 
exposure information, for evaluating the relative sensitivity of 
particular subpopulations (infants and children) that can inform our 
assessment of whether the HRL is an appropriate health reference level 
for all subpopulations (not just pregnant women).
    EPA thus applied the adjusted model to the HRL of 15 [mu]g/L to 
determine the predicted percent RAIU inhibition (Table 8). Iodide 
uptake inhibition levels for all other subpopulations, including 
infants and children, were estimated to be not greater than 2.0 percent 
at the 15 [mu]g/L drinking water concentration and not greater than 2.2 
percent when also considering perchlorate in food. The highest iodide 
update inhibition level (2.2 percent) was seen for the 7 day bottle fed 
infant; all other subpopulations, including the 60 day bottle fed 
infant as well as the 7 and 60 day breast fed infant had inhibition 
levels below 1.4 percent when also considering perchlorate in food. The 
2.2 percent inhibition level for 7-day old bottle fed infants is 
comparable to the 1.8 percent inhibition level that the NRC identified 
as a no effect level in healthy adults and recommended as the point of 
departure for calculating the RfD.\12\

    \12\ The model does not exactly match the average measured 
inhibition at each exposure concentration. At the point of departure 
(7 [mu]g/kg/day), the model predicts a value of 2.1 percent for 
adults, rather than the 1.8 percent from the Greer et al. (2002) 
study. Thus, the model slightly over-predicts the level of 
inhibition for this group at this exposure level, though this 
relationship may not hold true for other sub-groups and exposure 
levels. In any event, the difference between the average measured 
value of 1.8 percent and the model-predicted value of 2.1 percent is 
well within the statistical uncertainty in the data.

    Table 8 also shows the exposure to each subpopulation in [mu]g/kg 
of body weight. EPA notes that for some subgroups, the modeled exposure 
exceeds the RfD, though not for the most sensitive subgroup (i.e., 
pregnant women and their fetuses) from which the HRL was derived. EPA 
has used these exposure estimates as one input into the PBPK model to 
reduce the uncertainty associated with the relative sensitivities of 
other subgroups, particularly infants and children. EPA believes use of 
the model enhances its assessment beyond considering exposure alone by 
predicting the resulting iodide uptake inhibition that may result from 
that exposure. As noted above, the NRC concluded that the ``most health 
protective and scientifically valid approach'' was to base the point of 
departure for the RfD on the inhibition of iodide uptake by the thyroid 
(NRC, 2005), a non-adverse precursor effect. The predicted RAIU 
inhibition for all subgroups is comparable to or less than the RAIU at 
the NOEL selected by the NRC. Therefore EPA believes the HRL of 15 
[mu]g/L, derived for pregnant women, is also an appropriate health 
reference level for other sub-populations, against which to evaluate 
monitored levels of perchlorate occurrence in drinking water systems.

  Table 8--Predicted Percent Radioactive Iodide Uptake (RAIU) Inhibition and Corresponding Perchlorate Intake From Water at 15 [mu]g/L With and Without
                                                                       Food Intake
                                                                              90th     Perchlorate  Percent RAIU      TDS      intake from  Percent RAIU
                                                                           Percentile  intake from   inhibition    estimated     food and    inhibition
                                                             Body weight     water      only water    from only   perchlorate  water at 15    from food
                                                              (kg) \a\     intake (L/  at 15 [mu]g/  water at 15  intake from    [mu]g/L    and water at
                                                                            day) \b\   L ([mu]g/kg-    [mu]g/L    food ([mu]g/  ([mu]g/kg-   15 [mu]g/L
                                                                                           day)                   kg-day) \c\      day)
Average adult.............................................          70           2.24         0.48          0.15         0.10         0.58          0.18
Non-pregnant woman........................................          66           2.11         0.48          0.21         0.10         0.58          0.26
Pregnant woman:
    Mom--GW 13............................................          69           2.18         0.50          0.49         0.10         0.60          0.59
    Mom--GW 20............................................          71           2.34         0.50          0.49         0.10         0.60          0.59
    Mom--GW 40............................................          78           2.57         0.50          0.47         0.10         0.60          0.57
    Fetus--GW 40 \g\......................................           3.5  ...........  ...........          0.90  ...........  ...........          1.1
Breast-fed infant:
    Mom--7 d..............................................          74           2.96         0.60          0.18         0.10         0.70          0.21
    Infant--7 d...........................................           3.6     \d\ 0.52         1.36          1.1         \(d)\         1.59          1.3
    Mom--60 d.............................................          72           2.96         0.61          0.17         0.10         0.71          0.20
    Infant--60 d..........................................           5       \d\ 0.74         1.27          0.73        \(d)\         1.48          0.84

[[Page 60279]]

Bottle-fed infant:
    Infant--7 d...........................................           3.6     \e\ 0.84         3.53          2.0   1.42 [mu]g/         3.87          2.2
    Infant--60 d..........................................           5       \e\ 1.14         3.42          1.3   1.42 [mu]g/         3.74          1.4
    6-12 mo \f\...........................................           9.2         1.03         1.68          0.46        0.275         1.96          0.53
    1-2 yr \f\............................................          11.4         0.64         0.84          0.23        0.370         1.21          0.33 
\a\ Calculations for a 70 kg ``average'' adult are shown, while the body weight (BW) for the non-pregnant woman is from U.S. EPA 2004 (based on CSFII 94-
  96, 98) and BWs for the child are mean values from Kahn and Stralka (2008). BWs for pregnant and breast feeding moms, fetuses, bottle and breast fed
  infants are predicted weights (functions of age or gestation week) using growth equations from Gentry et al. (2002) as implemented in the PBPK models
  (Clewell et al. 2007; non-pregnant value is BW at day 0 of gestation).
\b\ Water intake levels for adults other than the lactating mother are based on normalized 90th percentile values for total water intake (direct and
  indirect) multiplied by the age- or gestation-week-dependent BW, as follows: 0.032 L/kg-day for average adult and non-pregnant woman; 0.033 L/kg-day
  for the pregnant woman. A fixed ingestion rate was used for the lactating mother because, while her BW is expected to drop during the weeks following
  the end of pregnancy, the demands of breast-feeding will be increasing. Values are from Kahn and Stralka (2008), except values for women are from U.S.
  EPA (2004).
\c\ The dietary values used correspond to the midpoint of the range of lower- and upper-bound average perchlorate levels for each subgroup, as
  identified from the FDA TDS in Murray et al. (2008), except for the bottle-fed infant. EPA used 1.42 [mu]g/L as the concentration of perchlorate in
  infant formula. This is based on an average of available FDA TDS data, with \1/2\ LOD included in the average for the samples in which perchlorate was
  not detected.
\d\ The breast-fed infants are assumed to have no direct exposure via food or water. The prediction for breast-fed infants in this table results from
  the dose from both food and water to the mother providing breast milk to the infant. Breast-fed infant ``water intake'' is the breast milk ingestion
  rate obtained by fitting an age-dependent function to the breast-milk ingestion data (L/kg-day) from Arcus-Arth et al. (2005). Urinary clearance rates
  for the lactating woman equal to that of the average adult were used, consistent with data presented in Delange (2004).
\e\ For the bottle-fed infant, normalized total water intake (direct and indirect, L/kg-day) was described as a smooth function of infant age fit to the
  results from Kahn and Stralka (2008), and multiplied by BW(age). For the 7-day-old infant, the data used to fit the function included the 90th
  percentile community water-consumers only intake (0.235 L/kg-day, N=40) for the <1 month old infant. For the 60-day-old infant, the 90th percentile
  community water-consumers only intake (0.228 L/kg-day, N=114) for the 1- to <3 months-old infant was used.
\f\ For the 6- to 12-month and 1- to 2-year-old children, EPA set the water ingestion based on published exposure tables and selected the age at which
  the model-predicted BW (from growth equations) matched the exposure-table mean. This approach resulted in model predictions for a 9.6-month-old child
  (to represent 6- to 12-month-old children) and a 1.3-year old (to represent 1- to 2-year-old children).
\g\ Due to data limitations, RAIU inhibition is calculated only for fetuses at GW 40.

c. Modeling Uncertainties
    EPA recognizes that there are uncertainties associated with this 
modeling, as there are for any modeling effort. For example, this 
analysis does not take into account within-group variability in 
pharmacokinetics, uncertainty in model parameters and predictions, or 
population differences in pharmacodynamics (PD) of receptor binding and 
upregulation. Also, the NRC identified fetuses of pregnant women that 
are hypothyroid or iodine deficient as the most sensitive 
subpopulation. The model predictions of RAIU inhibition in the various 
subgroups are average inhibition for typical, healthy individuals, not 
for hypothyroid or iodine deficient individuals. However, EPA did not 
rely on this analysis for determining the HRL. Rather, the HRL of 15 
[mu]g/L was calculated directly from the RfD to protect the most 
sensitive subpopulation, the fetuses of pregnant women, using high end 
exposure assumptions (e.g., estimated 90th percentile drinking water 
consumption and estimated 90th percentile perchlorate dietary (food) 
exposure). The PBPK modeling was used to provide information on the 
potential effects of exposure at the HRL for other subgroups, such as 
infants and children.
    In addition, the predicted inhibitions are averages for the 
subgroup as a whole, given the exposure assumptions used in the model. 
Thus, some members of a group would be expected to have RAIU inhibition 
greater than indicated in Table 8 for a particular perchlorate 
concentration, while others would have lesser inhibition. EPA was able 
to partially address this variability by using 90th percentile water 
consumption rates and mean body weights in the analysis to consider the 
highly exposed portions of the various subgroups. Most members of the 
subgroups would be expected to have exposures less than those indicated 
in Table 8.
    There is also some uncertainty regarding the water intake rates, 
particularly for infants. EPA described water intake by infants as a 
smooth function fit to the 90th percentile community water-consumers 
intake-rate data (intake per unit BW) of Kahn and Stralka (2008), which 
is then multiplied by the age-dependent BW to account for the changes 
occurring over the first weeks of life. This resulted in an estimated 
90th percentile water intake rate of 0.84 L/day for the 7-day bottle 
fed infant and used by EPA in PBPK model simulations. General 
information on water and formula intake for 7-day old infants is also 
available in guidelines for healthy growth and nutrition of the 
American Academy of Pediatrics (AAP, 2008). The values estimated using 
the guidelines from the AAP (0.126 L/kg-day assuming 80% is the percent 
water used in preparation of formula) for 7-day-old infants are close 
to the mean consumers-only intake rate for the 1-30 day-old infants 
from Kahn and Stralka (2008; 0.137 L/kg-day N=40).
    However, FDA has suggested an alternate approach, using the caloric 
intake requirement of a 7-day old infant as the basis for calculating 
consumption (FDA, 2008). This would likely yield a lower estimate of 
intake than the 0.84 L/day EPA has used in the model. If intake is 
lower, this would yield a lower prediction of RAIU inhibition, as can 
be seen from the value predicted for the 7-day old breast fed infant 
(1.4 percent). EPA plans to ask specifically for feedback on the 
consumption estimates

[[Page 60280]]

for 7-day old bottle-fed infants when the model revisions are peer 
    There is also uncertainty regarding the appropriate duration of 
exposure (i.e., days, weeks, months) to compare to the perchlorate RfD, 
which EPA defines as ``an estimate (with uncertainty spanning perhaps 
an order of magnitude) of a daily exposure to the human population 
(including sensitive subgroups) that is likely to be without an 
appreciable risk of deleterious effects during a lifetime.'' Reference 
values, like the RfD, are derived based on an assumption of continuous 
exposure throughout the duration specified, while intake levels may 
rapidly change day to day or during certain life stages. For 
comparability with the RfD, continuous perchlorate exposure was assumed 
in EPA's modeling analysis. Using perchlorate levels predicted for a 
continuous exposure (constant rate of introduction to the stomach), 
rather than incorporating changes in exposure and other input 
parameters over time (i.e., simulating the timing and quantity of 
specific ingestion events during the day), substantially reduced the 
effects of parameter uncertainty in the modeling. RAIU inhibition, on 
the other hand, is evaluated as the change in thyroid uptake of a pulse 
of iodide (radiolabeled, from an IV injection) at a time 24 hours after 
the pulse is administered. Thus, it represents the inhibition on a 
given day. This was true in the Greer study on which the RfD is based, 
and it is also true in the model. For all lifestages except the 
developing infant, the day-to-day variation in RAIU inhibition at the 
levels under consideration will have little or no effect. However, the 
effects of short-term inhibition in the infant (and fetus) may be of 
greater consequence than in the adult, although infants may also have 
less short-term variability in their diet and intake levels than 
adults. To address this concern, we present the results for the infant 
at both 7 days and 60 days after birth. The model predicts a fairly 
smooth variation in effect between these two ages.
d. Summary of Modeling Analysis
    In deciding whether to regulate perchlorate, EPA focused attention 
on the most sensitive subpopulation, a pregnant woman and her fetus. 
EPA calculated an HRL of 15 [mu]g/L for pregnant women using RSC 
information derived from an analysis of NHANES and UCMR data. EPA also 
conducted PBPK modeling to evaluate predicted biological outcomes 
associated with drinking water concentrations at the health reference 
level for different sensitive subpopulations. For pregnant women, EPA 
assumed a 90th percentile water ingestion rate of 0.033 L/kg-day, a 
food intake rate that represented the midpoint of the range of average 
perchlorate dietary exposures reported in Murray et al. (2008), and 
used the Clewell et al. (2007) PBPK model-fitted body weight. EPA 
believes that the model-fitted body weight provides a more realistic 
weight for the pregnant woman than EPA's 70 kg default assumption for 
adults. In addition, rather than using the default assumption of 2L/day 
water ingestion, EPA used a 90th percentile water ingestion rate 
normalized for body weight and based on data specifically for pregnant 
women (USEPA 2004b). Using these assumptions, the model predicted that 
the pregnant woman's dose of perchlorate would not exceed the reference 
dose if she consumed drinking water with a concentration of 15 [mu]g/L 
or less, which is consistent with the derivation of the HRL from the 
reference dose, based on average body weight, 90th percentile water 
consumption, and 90th percentile food exposure for pregnant women. The 
model further predicted that the percent inhibition in the fetus of a 
pregnant woman consuming drinking water with 15 [mu]g/L perchlorate (in 
combination with a normal diet) is 1.1 percent, below the 1.8 percent 
that the NRC determined to be a no-effect level in healthy adults. EPA 
evaluated other subpopulations to estimate iodide uptake inhibition and 
determined that 7-day old bottle-fed infants were predicted to have a 
2.2 percent inhibition level, after also accounting for food exposure, 
and all other subpopulations, including 60-day old bottle-fed infants, 
7 and 60 day old breast-fed infants, and children, were predicted to 
have levels of inhibition of 1.4 percent or less, after accounting for 
food. All of these levels are comparable to or below the 1.8 percent no 
effect inhibition level from the Greer study.
    Based on the health protective approach for deriving the RfD (i.e., 
use of a NOEL rather than a NOAEL as the point of departure), the 
conservative assumptions used in deriving the RSC and corresponding HRL 
(use of 90th percentile food exposure data specifically from pregnant 
women), and the PBPK modeling analysis of RAIU inhibition in 
potentially sensitive subpopulations, EPA believes drinking water with 
perchlorate concentrations at or below the HRL of 15 [mu]g/L is 
protective of all subpopulations. Based upon the HRL and the analysis 
of drinking water occurrence, EPA concludes that perchlorate does not 
occur at a frequency and level of health concern to warrant a national 
drinking water regulation.

C. Is There a Meaningful Opportunity for the Reduction of Health Risks 
From Perchlorate for Persons Served by Public Water Systems?

    The Agency does not believe that a national primary drinking water 
regulation for perchlorate presents a meaningful opportunity for health 
risk reduction for persons served by public water systems. EPA has 
found that perchlorate occurs infrequently above levels of health 
concern. Only 31 out of 3,865 systems (0.8 percent) detected 
perchlorate in drinking water above the HRL of 15 [mu]g/L. EPA's best 
estimate is that 0.9 million people (with an upper bound estimate of 2 
million people) may be consuming water containing perchlorate at levels 
that could exceed the HRL for perchlorate and the Agency estimates that 
fewer than 30,000 of them are pregnant women at any given time.
    EPA's RfD was derived by applying a 10 fold uncertainty factor to 
the dose corresponding to a non-statistically significant mean 1.8 
percent decline in RAIU in healthy adults following two weeks of daily 
exposure to perchlorate (Greer et al., 2002). Because iodide uptake 
inhibition is not an adverse effect but a precursor biochemical change, 
this point of departure (7 ug/kg/day) is a NOEL which provides for a 
more conservative and health-protective approach to perchlorate hazard 
assessment. After taking perchlorate in the diet into consideration, at 
the HRL of 15 [mu]g/L for perchlorate in drinking water, the models 
predicted that the percent RAIU inhibition in fetuses would be 1.1 
percent, while the inhibition in all other subgroups except the 7-day-
old bottle fed infant would be no greater than 1.4 percent. For the 7-
day-old bottle fed infant, the predicted inhibition is 2.2 percent. All 
of these values are comparable to or below the percent inhibition at 
the NOEL in the Greer study.
    Based on these analyses, EPA has determined that a national primary 
drinking water regulation for perchlorate would not present a 
meaningful opportunity for health risk reduction for persons served by 
public water systems.

V. EPA's Next Steps

    EPA requests comment on this preliminary determination that a 
national primary drinking water regulation for perchlorate would not 
present a meaningful opportunity for health risk reduction for persons 
served by public water systems. EPA also requests comment upon the 

[[Page 60281]]

data and supporting analyses for this determination. In past regulatory 
determinations, EPA has qualitatively but not quantitatively evaluated 
the health effects of exposure at the HRL on infants and children. 
Because the evaluation of the potential impacts of exposure at the HRL 
of 15 [mu]g/L on infants and children is a novel approach, EPA 
specifically requests comment on its use of the revised PBPK model to 
evaluate these potential impacts.
    EPA will respond to the public comments it receives on the 
preliminary determination and will review the comments from the peer 
review of its model application. After considering comments, EPA plans 
to issue a final regulatory determination for perchlorate by December 
2008. EPA also plans to publish a health advisory for perchlorate at 
the time of the final determination to provide information to Federal, 
Regional, State, and local public health officials regarding potential 
health risks from perchlorate-contaminated drinking water.

VI. References AAP, 2008:

AAP, 2008: American Academy of Pediatrics, Bright futures guidelines 
for health supervision of infants, children, and adolescents (2008) 
Amitai Y, Winston G, Sack J, Wasser J, Lewis M, Blount BC, Valentin-
Blasini L, Fisher N, Israeli A, and Leventhal A. (2007). Gestational 
exposure to high perchlorate concentrations in drinking water and 
neonatal thyroxine levels. Thyroid. 17(9): 843-850.
Arcus-Arth, A., G. Krowech, and L. Zeise. 2005. Breast milk and 
lipid intake distributions for assessing cumulative exposure and 
risk. Journal of Exposure Analysis and Environmental Epidemiology 
15(4): 357-365.
Auso E., R. Lavado-Autric, E. Cuevas, F.E. Del Rey, G, Morreale De 
Escobar, and P. Berbel. 2004. A moderate and transient deficiency of 
maternal thyroid function at the beginning of fetal 
neocorticogenesis alters neuronal migration. Endocrinology. 145: 
Blount, B.C., L. Valentin-Blasini, D.L. Ashley. 2006a. Assessing 
human exposure to perchlorate using biomonitoring. Journal of ASTM 
International. Vol. 3, No. 7. pp. 1-6.
Blount, B.C., J.L. Pirkle, J.D. Osterloh, L. Valentin-Blasini, and 
K.L. Caldwell. 2006b. Urinary perchlorate and thyroid hormone levels 
in adolescent and adult men and women living in the United States. 
Environmental Health Perspectives. Vol. 114, No. 12. pp. 1865-1871.
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    Dated: October 3, 2008.
Stephen L. Johnson,
 [FR Doc. E8-24042 Filed 10-9-08; 8:45 am]