[Federal Register Volume 73, Number 198 (Friday, October 10, 2008)]
[Notices]
[Pages 60262-60282]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: E8-24042]
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ENVIRONMENTAL PROTECTION AGENCY
[EPA-HQ-OW-2008-0068; FRL-8727-6]
RIN 2040-ZA02
Drinking Water: Preliminary Regulatory Determination on
Perchlorate
AGENCY: Environmental Protection Agency (EPA).
ACTION: Notice.
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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
contamination.
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
ChE--cholinesterase
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--gram
g/day--grams per day
HRL--health reference level
IOC--inorganic compound
IRIS--Integrated Risk Information System
kg--kilogram
L--liter
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
NOEL--no-observed-effect-level
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
T3--triiodothyronine
T4--thyroxine
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
System?
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
Persons?
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
SUPPLEMENTARY INFORMATION:
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
comments:
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
deadline.
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:
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\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
contaminants.
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(a) The contaminant may have an adverse effect on the health of
persons;
(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\
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\3\ The statute authorizes a nine month extension of this
promulgation date.
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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
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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
community.''
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
exposures.
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
perchlorate.
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
contamination.
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)
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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
Dose
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
III.A.2.
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\
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\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)
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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
subpopulations.
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
----------------------------------------------------------------------------------------------------------------
Notes:
[[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
estimate
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
\d\
----------------------------------------------------------------------------------------------------------------
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)............
----------------------------------------------------------------------------------------------------------------
Footnotes:
\a\ All occurrence measures in this table were conducted on a basis reflecting values greater than the listed
thresholds.
\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
Water
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
determination.
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
Food.
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
populations.\11\
---------------------------------------------------------------------------
\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.
population.''
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
[mu]g/kg/day.
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
below.
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
persons.
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
Where:
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
--------------------------------------------------------------------------------------------------------------------------------------------------------
90th
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
5).
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
percentile
(Table 6).
----------------------------------------------------------------------------------------------------------------
Footnotes:
\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
--------------------------------------------------------------------------------------------------------------------------------------------------------
Perchlorate
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
L
Infant--60 d.......................................... 5 \e\ 1.14 3.42 1.3 1.42 [mu]g/ 3.74 1.4
L
Child:
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
reviewed.
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
scientific
[[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)
http://brightfutures.aap.org/pdfs/Guidelines_PDF/6-Promoting_Healthy_Nutrition.pdf.
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:
4037-47.
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.
Blount, B.C., L. Valentin-Blasini, J.D. Osterloh, J.P. Mauldin, and
J.L. Pirkle. 2006c. Perchlorate Exposure of the U.S. Population,
2001-2002. Journal of Exposure Science and Environmental
Epidemiology. Advance online publication 18 October 2006. Available
on the Internet at: http://www.nature.com/jes/journal/vaop/ncurrent/pdf/7500535a.pdf.
Blount, B.C., L. Valentin-Blasini. 2006. Analysis of perchlorate,
thiocyanate, nitrate and iodide in human amniotic fluid using ion
chromatography and electrospray tandem mass spectrometry. Analytica
Chimica Acta. Vol. 567, No. 1. pp. 87-93.
CDPH. 2008. California Department of Public Health. ``Perchlorate in
California Drinking Water: Update and Overview.'' Available on the
Internet at: http://www.cdph.ca.gov/certlic/drinkingwater/Pages/Perchlorate.aspx. Updated July 8, 2008.
Caldwell K.L., Jones R., and Hollowell J.G. 2005. Urinary iodine
concentration: United States National Health and Nutrition
Examination Survey 2001-2002. Thyroid. Vol. 15, pp. 692-699.
Chan, S. and M.D. Kilby. 2000. Thyroid hormone and central nervous
system development. J Endocrinol 165(1): 1-8.
Clewell, R.A., E.A. Merrill, J.M. Gearhart, P.J. Robinson, T.R.
Sterner, D.R. Mattie, and H.J. Clewell, III. 2007. Perchlorate and
radiodide kinetics across life stages in the human: using PBPK
models to predict dosimetry and thyroid inhibition and sensitive
subpopulations based on developmental stage. Journal of Toxicology
and Environmental Health. Part A. 70:5 408-428.
Dasgupta, P.K., A.B. Kirk, J.V. Dyke, and S.I. Ohira. 2008. Intake
of Iodine and Perchlorate Excretion in Human Milk. Environ. Sci.
Technol. Advance online publication accessed September 18, 2008.
Delange, F. 2004. Optimal iodine during pregnancy, lactation and the
neonatal period. International Journal of Endocrinology and
Metabolism 3:1-12.
Egan, S.K., Bolger, P.M., and Carrington, C.D. 2007. Update of U.S.
FDA's Total Diet Study Food Lists and Diets. J Expo Sci Environ
Epidemiol. pp. 1-10. (As cited in Murray et al., 2007)
FDA, 2008: Food and Drug Administration. Volume of feeds for
infants. Memorandum from Benson M. Silverman, M.D., Staff Director,
Infant Formula/Medical Foods Staff, Center for Food Safety and
Applied Nutrition, to P. Michael Bolger.
Gibbs et al., 2004. J.P. Gibbs, L. Narayanan and D.R. Mattie, Crump
et al. Study among school children in Chile: subsequent urine and
serum perchlorate levels are consistent with perchlorate in water in
Taltal, J. Occup. Environ. Med 46 (2004) (6), pp. 516-517.
Gilbert, M.E. and L. Sui. 2008. Developmental exposure to
perchlorate alters synaptic transmission in hippocampus of the adult
rat. Environ Health Perspect 116: 752-60.
Glinoer, D. 2001. Potential consequences of maternal hypothyroidism
on the offspring: evidence and implications. Horm Res 55(3): 109-14.
Glinoer, D. 2007. Clinical and biological consequences of iodine
deficiency during pregnancy. Endocr Dev 10: 62-85.
Goldey, E.S., L.S. Kehn, G.L. Rehnberg, and K.M. Crofton. 1995.
Effects of developmental hypothyroidism on auditory and motor
function in the rat. Toxicology and Applied Pharmacology 135:67-76.
Greer, M.A., G. Goodman, R.C. Pleuss, and S.E. Greer. 2002. Health
effect assessment for environmental perchlorate contamination: the
dose response for inhibition of thyroidal radioiodide uptake in
humans. Environ Health Perspect Vol. 110. pp. 927-937.
Haddow, J.E., G.E. Palomaki, et al. 1999. Maternal thyroid
deficiency during pregnancy and subsequent neuropsychological
development of the child. New England Journal of Medicine 341(8):
549-55.
Kahn, H., and K. Stralka. 2008. Estimated daily average per capita
water ingestion by child and adult age categories based on USDA's
1994-96 and 1998 continuing survey of food intakes by individuals.
Journal of Exposure Analysis and Environmental Epidemiology
(accepted for publication).
Kirk, A.B., E.E. Smith, K. Tian, T.A. Anderson, and P.K. Dasgupta.
2003. Perchlorate in Milk. Environmental Science and Technology.
Vol. 37, No. 21. pp. 4979-4981.
Kirk, A.B., P.K. Martinelango, K. Tian, A. Dutta, E.E. Smith, and
P.K. Dasgupta. 2005. Perchlorate and iodide in dairy and breast
milk. Environmental Science and Technology. Vol. 39, No. 7. pp.
2011-2017.
Kirk, A.B., J.V. Dyke, C.F. Martin, and P.K. Dasgupta. 2007.
Temporal patterns in perchlorate, thiocyanate and iodide excretion
in human milk. Environ Health Perspect Online Vol. 115, No. 2. pp.
182-186.
Kooistra, L., S. Crawford, A.L. van Baar, E.P. Brouwers, and V.J.
Pop. 2006. Neonatal effects of maternal hypothyroxinemia during
early pregnancy. Pediatrics; 117; 161-167.
Krynitsky, A.J., R.A. Niemann, A.D. Williams, M.L. Hopper. 2006.
Streamlined sample preparation procedure for determination of
perchlorate anion in foods by ion chromatography-tandem mass
spectrometry. Analytica Chimica Acta Vol 567. pp. 94-99. (As cited
in Murray et al., 2007)
Mage, D.T., R.H. Allen, A. Kodali. 2007. Creatinine corrections for
estimating children's and adults' pesticide intake doses in
equilibrium with urinary pesticide and creatinine concentrations. J.
Expos Sci Enviro Epidem. 18, pp. 360-368.
Massachusetts Department of Environmental Protection (MA DEP). 2005.
The occurrence and sources of perchlorate in Massachusetts. Draft
Report. Available on the Internet at: http://www.mass.gov/dep/cleanup/sites/percsour.pdf. Updated April 2006.
[[Page 60282]]
Merrill, E.A., R.A. Clewell, P.J. Robinson, A.M. Jarabek, T.R.
Sterner, and J.W. Fisher. 2005. PBPK model for radioactive iodide
and perchlorate kinetics and perchlorate-induced inhibition of
iodide uptake in humans. Toxicological Sciences 83: 25-43.
Morreale de Escobar, G., M.J. Obregon, and F. Escobar del Rey. 2004.
Is neuropsychological development related to material hypothyroidism
or to maternal hypothyroxinemia? The Journal of Clinical
Endocrinology & Metabolism Vol. 85. No. 11.
Morreale de Escobar, G., M.J. Obregon, and F. Escobar del Rey. 2004.
Role of thyroid hormone during early brain development. European
Journal of Endocrinology 151: U25-U37.
Murray, C.W III, S.K. Egan, H. Kim, N. Beru, P.M. Bolger. 2008. U.S.
Food and Drug Administration's Total Diet Study: Dietary Intake of
Perchlorate and Iodine. Journal of Exposure Science and
Environmental Epidemiology, advance online publication, January 2,
2008.
National Research Council (NRC). 2005. Health Implications of
Perchlorate Ingestion. National Academies Press, Board on
Environmental Studies and Toxicology. January 2005. 276 p.
Pearce, E.N., A.M. Leung, B.C. Blount, H.R. Bazrafshan, X. He, S.
Pino, L. Valentin-Blasini, L.E. Braverman. 2007. Breast milk iodine
and perchlorate concentrations in lactating Boston-area women. J
Clin Endocrin Metab Vol. 92, No. 5, pp. 1673-1677.
Pop, V.J., J.L. Kuijpens, A.L. van Baar, G. Verkerk, M.M. van Son,
J.J. de Vijlder, T. Vulsma, W.M. Wiersinga. H.A. Drexhage, and H.L.
Vader. 1999. Low maternal free thyroxine concentrations during early
pregnancy are associated with impaired psychomotor development in
infancy. Clin Endocrinol (Oxf). Feb;50(2):149-55.
Pop, V.J., E.P. Brouwers, H.L. Vader, T. Vulsma, A.L. van Baar, and
J.J. de Vijlder JJ. 2003. Maternal hypothyroxinaemia during early
pregnancy and subsequent child development: A 3-year follow-up
study. Clin Endocrinol (Oxf). Sep;59(3):282-8.
Rovet, J.F., 2002. Congenital hypothyroidism: An analysis of
persisting deficits and associated factors. Child Neuropsychology
Vol. 8, No. 3. pp. 150-162.
Sanchez, C., Blount, B., L Valentin-Blasini, L., Krieger, R.
Perchlorate, thiocyanate, and nitrate in edible cole crops (Brassica
sp.) produced in the lower Colorado River region. Bull Environ
Contam Toxicol. 2007 Oct 26.
Sanchez, C.A., R.I Krieger, N. Khandaker, R.C. Moore, K.C. Holts,
and L.L. Neidel. 2005a. Accumulation and perchlorate exposure
potential of lettuce produced in the lower Colorado River region.
Journal of Agricultural and Food Chemistry Vol. 53. pp. 5479-5486.
Sanchez C.A., K.S. Crump, R.I. Krieger, N.R. Khandaker, and J.P.
Gibbs. 2005b. Perchlorate and nitrate in leafy vegetables of North
America. Environmental Science and Technology Vol. 39, No. 24, pp.
9391-9397.
Sharlin, D.S., D. Tighe, et al. 2008. The balance between
oligodendrocyte and astrocyte production in major white matter
tracts is linearly related to serum total thyroxine. Endocrinology
149(5): 2527-36.
Steinmaus, C., M.D. Miller, R. Howd. 2007. Impact of smoking and
thiocyanate on perchlorate and thyroid hormone associations in the
2001-2002 National Health and Nutrition Examination Survey. Environ
Health Perspect 115(9):1333-8.
T[eacute]llez, R.T., P.M. Chac[oacute]n, C.R. Abraca, B.C. Blount,
C.B. Van Landingham, K.S. Crump, and J.P. Gibbs. 2005. Chronic
environmental exposure to perchlorate through drinking water and
thyroid function during pregnancy and the neonatal period. Thyroid
Vol. 15, No. 9. pp. 963-975.
U.S. Census Bureau, 2002. U.S. Summary: 2000. U.S. Department of
Commerce, Economics and Statistics Administration, U.S. Census
Bureau. C2KPROF/00-US. July 2002.
USEPA. 1997a. Announcement of the Draft Drinking Water Contaminant
Candidate List; Notice. Federal Register. Vol. 62, No. 193. p.
52193, October 6, 1997.
USEPA. 1998a. Announcement of the Draft Drinking Water Contaminant
Candidate List; Notice. Federal Register. Vol. 63, No. 40. p. 10273,
March 2, 1998.
USEPA. 1999b. Revisions to the Unregulated Contaminant Monitoring
Regulation for Public Water Systems. Federal Register. Vol. 64, No.
180. p. 50556, September 17, 1999.
USEPA. 2000b. Unregulated Contaminant Monitoring Regulation for
Public Water Systems: Analytical Methods for Perchlorate and
Acetochlor; Announcement of Laboratory Approval and Performance
Testing (PT) Program for the Analysis of Perchlorate; Final Rule and
Proposed Rule. Federal Register. Vol. 65, No. 42. p. 11372, March 2,
2000.
USEPA. 2001b. Unregulated Contaminant Monitoring Regulation for
Public Water Systems; Analytical Methods for List 2 Contaminants;
Clarifications to the Unregulated Contaminant Monitoring Regulation.
Federal Register. Vol. 66, No. 8. p. 2273, January 11, 2001.
USEPA. 2002a. Announcement of Preliminary Regulatory Determinations
for Priority Contaminants on the Drinking Water Contaminant
Candidate List. Federal Register. Vol. 67, No. 106. p. 38222, June
3, 2002.
USEPA. 2002b. Perchlorate Environmental Contamination: Toxicological
Review and Risk Characterization. EPA/635/R-02/003. National Center
for Environmental Assessment, Office of Research and Development,
U.S. EPA.
USEPA. 2002c. A review of the reference dose and reference
concentration processes. Risk Assessment Forum, Washington, DC; EPA/
630/P-02/0002F. Available from: http://www.epa.gov/iris/backgr-d.htm.
USEPA. 2003a. Announcement of Regulatory Determinations for Priority
Contaminants on the Drinking Water Contaminant Candidate List.
Federal Register. Vol. 68, No. 138. p. 42897, July 18, 2003.
USEPA. 2004a. Drinking Water Contaminant Candidate List 2; Notice.
Federal Register. Vol. 69, No. 64. p. 17406, April 2, 2004.
USEPA. 2004b. Estimated Per Capita Water Ingestion and Body Weight
in the United States--An Update Based on Data Collected by the
United States Department of Agriculture's 1994-1996 and 1998
Continuing Survey of Food Intakes by Individuals. EPA-822-R-00-001.
Office of Science and Technology, Office of Water, U.S. EPA.
USEPA. 2005a. Notice--Drinking Water Contaminant Candidate List 2;
Final Notice. Federal Register. Vol. 70, No. 36. p. 9071, February
24, 2005.
USEPA. 2005b. ``Integrated Risk Information System (IRIS),
Perchlorate and Perchlorate Salts.'' February 2005. Available on the
Internet at: http://www.epa.gov/iris/subst/1007.htm. Accessed
February 2, 2005.
USEPA 2006. Assessment Guidance for Perchlorate. Memorandum from
Susan Bodine, Assistant Administrator of the Office of Solid Waste
and Emergency Response, to EPA Regional Administrators. Available on
the Internet at: http://www.epa.gov/fedfac/pdf/perchlorate_guidance.pdf. Accessed August 20, 2008
USEPA. 2007. Drinking Water: Regulatory Determinations Regarding
Contaminants on the Second Drinking Water Contaminant Candidate
List--Preliminary Determinations. Federal Register. 72 FR 24016. May
1, 2007.
USEPA, 2008a Evaluation of Perchlorate Exposure from Food and
Drinking Water: Results of NHANES Biomonitoring Data and UCMR 1
Occurrence Data Merge.
USEPA. 2008b. Inhibition of the Sodium-Iodide Symporter by
Perchlorate: Evaluation of Lifestage Sensitivity Using
Physiologically-Based Pharmacokinetic Modeling. {NOTE: Final title/
reference info for the document will be provided before
publication.{time}
USEPA. 2008c. Drinking Water: Regulatory Determinations Regarding
Contaminants on the Second Drinking Water Contaminant Candidate
List--Final Determinations. Federal Register. 73 FR 44251. July 30,
2008.
Ventura SJ, Abma JC, Mosher WD, Henshaw S. Estimated pregnancy rates
for the United States, 1990-2000: an update. National vital
statistics reports; vol 52 no 23. Hyattsville, Maryland: National
Center for Health Statistics. 2004.
Zoeller, R.T., and J. Rovet. 2004. Timing of thyroid hormone action
in the developing brain: clinical observations and experimental
findings. J Neuroendocrinology 16: 809-18.
Dated: October 3, 2008.
Stephen L. Johnson,
Administrator.
[FR Doc. E8-24042 Filed 10-9-08; 8:45 am]
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