United States
Environmental Protection
Agency
Interim Drinking Water
Health Advisory
For Perchlorate
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Interim Drinking Water Health Advisory
for Perchlorate
Prepared by:
Health and Ecological Criteria Division
Office of Science and Technology
Office of Water
U.S. Environmental Protection Agency
Washington, DC 20460
http://www.epa.gov/waterscience/
EPA 822-R-08-025
December 2008
in
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IV
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TABLE OF CONTENTS
ACKNOWLEDGMENTS VI
LIST OF ABBREVIATIONS VII
1.0 INTRODUCTION 1
2.0 GENERAL INFORMATION AND PROPERTIES 2
2.1 PHYSICAL AND CHEMICAL PROPERTIES 2
2.2 USES 3
3.0 OCCURRENCE AND EXPOSURE 3
3.1 Am 3
3.2 WATER 3
3.3 FOOD 4
3.4 BIOMONITORING STUDIES 8
3.5 SOIL 12
4.0 HEALTH EFFECTS DATA 12
4.1 HUMAN STUDIES AND MODELING 12
4.2 ANIMAL STUDIES 18
5.0 QUANTIFICATION OF TOXICOLOGICAL EFFECTS 19
5.1 REFERENCE DOSE DERIVATION 20
5.2 RELATIVE SOURCE CONTRIBUTION DERIVATION 22
5.3 SUBCHRONIC INTERIM HEALTH ADVISORY 25
5.4 SUBCHRONIC HEALTH ADVISORIES FOR OTHER SENSITIVE SUBPOPULATIONS 26
5.5 EVALUATION OF CARCINOGENIC POTENTIAL 34
6.0 OTHER CRITERIA, GUIDANCE, AND STANDARDS 34
7.0 ANALYTICAL METHODS 34
8.0 TREATMENT TECHNOLOGIES 35
9.0 REFERENCES 35
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ACKNOWLEDGMENTS
This document was prepared by Oak Ridge National Laboratory, Oak Ridge, Tennessee,
work assignment 2006-002-2, under the U.S. EPAIAG Number DW-89-92209701. The
Lead EPA Scientist is Elizabeth Doyle, Ph.D., Health and Ecological Criteria Division,
Office of Science and Technology, Office of Water, U. S. Environmental Protection
Agency.
VI
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LIST OF ABBREVIATIONS
ATSDR Agency for Toxic Substances and Disease Registry
BMD benchmark dose
BMDL benchmark dose level
BW body weight
CAS Chemical Abstracts Registry
CSF Cancer Slope Factor
CDC Centers for Disease Control and Prevention
CSF cancer slope factor
DWEL Drinking Water Equivalent Level
GD gestation day
HA Health Advisory
HSDB Hazardous Substance Data Bank
IRIS Integrated Risk Information System
kg kilogram
L liter
LOAEL lowest observed adverse effect level
MDL method detection limit
mg milligram
mg/kg milligram per kilogram of body weight
mg/L milligrams per liter (equivalent to parts per million [ppm])
jig microgram (one-millionth of a gram)
NHANES National Health and Nutrition Examination Survey
NOAEL no observed adverse effect level
NOEL no observed effect level
NRC National Research Council
OW Office of Water
PBPK Physiologically-Based Pharmacokinetic
ppb parts per billion
ppm parts per million
RAIU Radioactive Iodide Uptake
RfD reference dose
RSC relative source contribution
SIR standardized incidence ratio
SDWA Safe Drinking Water Act
T3 Triiodothyronine: thyroid hormone containing three iodine atoms
T4 Thyroxine: a biologically inactive prohormone containing four iodine atoms
that is activated to triiodothyronine by deiodinase. (also known as
tetraiodothyronine)
TSH Thyroid stimulating hormone (also known as thyrotropin)
UCMR Unregulated Contaminant Monitoring Regulation
UF uncertainty factor
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EPA U.S. Environmental Protection Agency
FDA U.S. Food and Drug Administration
USD A U. S. Department of Agriculture
Vlll
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1.0 INTRODUCTION
The Health Advisory (HA) Program, sponsored by the Office of Water (OW), provides
information on the environmental properties, health effects, analytical methodology, and
treatment technology for regulated and unregulated drinking water contaminants. HAs
establish non-regulatory concentrations of drinking water contaminants at which adverse
health effects are not anticipated to occur over specific exposure durations (one day, ten
days, a subchronic period, several years, and a lifetime). For perchlorate, EPA is
establishing an interim health advisory level for subchronic exposure. HAs serve as
informal technical guidance to assist Federal, State and local officials, and managers of
public or community water systems in protecting public health when emergency spills or
contamination situations occur. They are not legally enforceable Federal standards and are
subject to change as new information becomes available.
The Interim Drinking Water Health Advisory level (15 |ig/l) is based on the
recommendations of the National Research Council (NRC) of the National Academies as
reported in "Health Implications of Perchlorate Ingestion" (NRC, 2005). The NRC
recommended and EPA adopted a Reference Dose (RfD) of 0.7 jig/kg/day. The NRC
perchlorate committee took into consideration presentations at the committee's public
meetings, submitted public comments, and the comments made by technical experts on the
draft NRC perchlorate report. The NRC review followed two external draft toxicological
reviews of perchlorate prepared by EPA (1998, 2002) that were also subject to public
comment and independent external review. The NRC report can be accessed at
http://www.nap.edu/catalog.php?record_id=l 1202.
On October 10, 2008, the Agency issued a preliminary determination for perchlorate in
the Federal Register for public review and comment (USEPA, 2008a). The notice
described the Agency's preliminary decision that there is not a "meaningful opportunity
for health risk reduction" through a national drinking water regulation. Based on the
comments that it received, EPA believes that it would benefit once again from NRC input
regarding perchlorate, this time in the context of the application of the physiologically-
based pharmacokinetic (PBPK) modeling and assumptions regarding sensitive populations
in development of the interim HA level. Thus in 2009, EPA will engage the NRC to
provide additional advice.
The Agency is issuing this interim health advisory to assist state and local officials in
advance of a final regulatory determination. EPA expects to issue a final health advisory
concurrent with the final regulatory determination for perchlorate.
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2.0 GENERAL INFORMATION AND PROPERTIES
2.1 Physical and Chemical Properties
Perchlorate is an inorganic contaminant containing one chlorine atom bound to four
oxygen atoms in a tetrahedral configuration. As such, perchlorate (C1CV) is an anion that
forms salts with most cations. Commonly used perchlorate salts include ammonium
perchlorate and potassium perchlorate. Perchlorate is also used as sodium perchlorate,
aluminum perchlorate, hydrazine perchlorate, hydrogen perchlorate, hydroxylammonium
perchlorate, lithium perchlorate, magnesium perchlorate, nitronium perchlorate, and as
perchloric acid. Chemical Abstracts Service (CAS) registry numbers, as well as certain
physical and chemical properties for the most common forms of perchlorate are presented
in Table 2-1.
- cr
Perchl orate
Table 2-1. CAS Numbers and Physical/Chemical Properties of PerchloratePerchlorate
and Its Common Salts
CAS number
Molecular
Formula
Perchlorate
14797-73-0
C1O4
Ammonium
perchlorate
7790-98-9
NFLjClCU
Potassium
perchlorate
7778-74-7
KC1O4
Magnesium
perchlorate
10034-81-8
Mg(C104)2
Sodium
perchlorate
7601-89-0
NaClO4
Physical and Chemical Properties
Decomposition
Point
Melting Point
Molecular
Weight
Water
Solubility
99.45 g/mol :
439 °C2
11 7. 49 g/mol2
200 g/L @
25°C3
630°C7
525 °C4
138. 55 g/mol1
15g/L@25°C3
250 °C4
223.20
g/mol 4
99 g/lOOOg
@25°C5
480 °C4
122.4
g/mol :
209g/100
g@25°C6
1 Budavari, 1996,2 HSDB, 2004,3 Ashford, 1994, 4 Lide, 2000,s Weast, 1979,6 Gerhartz, 1985, 7Kubota, 2007
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2.2 Uses
While perchlorate has a wide variety of uses, it is primarily used in the form of
ammonium perchlorate as an oxidizer in solid fuels used in explosives, fireworks, road
flares, and rocket motors. Perchlorate can also be present as an ingredient or as an
impurity in road flares, lubricating oils, matches, aluminum refining, rubber
manufacturing, paint and enamel manufacturing, leather tanning, paper and pulp
processing (as an ingredient in bleaching powder), and as a dye mordant. Sodium
hypochlorite solutions used in water and wastewater treatment plants have also been
identified as a potential source of perchlorate contamination (US EPA, 2007).
3.0 OCCURRENCE AND EXPOSURE
Perchlorate occurs in the environment from its past and present use primarily in
rocket fuels, explosives, and fireworks. Perchlorate can also occur naturally in the
environment. For example, Chile possesses caliche ores rich in sodium nitrate (NaNOs),
which are also a natural source of perchlorate. These Chilean nitrate salts (saltpeter) have
been mined and refined to produce commercial fertilizers (US EPA, 2001). The US EPA
(2001) conducted a broad survey of fertilizers and other raw materials and found that all
products surveyed were devoid of perchlorate except for those known to contain or to be
derived from mined Chilean saltpeter.
3.1 Air
Perchlorate salts have very low vapor pressures and therefore are not expected to
volatilize to the air as fugitive emissions during their manufacture, processing, transport,
disposal, or use (ATSDR, 2005). However, persons may be exposed to perchlorate dust or
particles in an occupational setting, where the risk posed by that exposure would depend
on the particle size distribution (NRC, 2005).
3.2 Water
Perchlorate was sampled in drinking water supplies as part of the Unregulated
Contaminant Monitoring Regulation (UCMR) 1, List 1 Assessment Monitoring program.
Occurrence data for perchlorate was collected from 3,865 public water supplies between
2001 and 2005. Approximately 160 (4.1%) of these systems had at least 1 analytical
detection of perchlorate (in at least 1 entry/sampling point) at levels greater than or equal
to 4 |ig/L. These 160 systems are located in 26 states and 2 territories. Approximately
1.9% (or 637) of the 34,331 samples collected by all 3,865 public water supplies had
positive detections of perchlorate at levels greater than or equal to 4 |ig/L. The maximum
reported concentration of perchlorate, 420 |ig/L, was found in a single surface water
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sample from a public water supply in Puerto Rico. The average concentration of
perchlorate for those samples with positive detections for perchlorate was 9.85 jig/L and
the median concentration was 6.40 |ig/L.
There is limited information on the release of perchlorate to ambient water.
Perchlorate may be released to water from its manufacture, processing, or use. Perchlorate
may ultimately be released to surface water from the runoff or erosion of sand or soil
contaminated with the compound, while the percolation of water through contaminated
sand or soil could result in perchlorate contaminating groundwater (ATSDR, 2005).
Public water systems that have not previously monitored their drinking water for
perchlorate may want to review their source water assessments to determine if there are
any potential sources of perchlorate contamination within the contributing area of their
source.
3.3 Food
The U.S. Food and Drug Administration's (FDA) 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 US. In addition, the Centers for Disease Control and
Prevention's (CDC) National Health and Nutrition Examination Survey (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 results to estimate
perchlorate exposure from food and water together, and food alone, for different sub-
populations. This section provides details on the results of these studies.
3.3.1 Food Monitoring 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 TDS and FDA's Exploratory Survey Data on Perchlorate in Food.
3.3.1.1 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 US 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 the analytical results from the TDS with food
consumption estimates developed specifically for estimating dietary exposure from the
TDS results. While the perchlorate data for TDS foods were collected in 2005-2006, the
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food consumption data in the current IDS 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 intake 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, and not from the representative TDS foods alone.
The sampled TDS foods are purchased 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 etal, 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 also was analyzed in all
TDS foods from five market baskets surveyed in late 2003 through 2004. Using these data
collectively, FDA developed estimates of the 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 the average dietary exposure, assuming
that NDs equal zero and the LOD, respectively. Specifically, FDA multiplied these upper-
and lower-bound average 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 3-1 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. 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.
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Table 3-1. Lower- and Upper-bound (ND = 0 and LOD) Perchlorate Intakes
from FDA's TDS Results for 2005-2006.
Population Group
Infants
Children
Children
Children
Teenage Girls
Teenage Boys
Women
Men
Women
Men
Women
Men
Women
Men
6-11 mo
2yr
6 yr
10 yr
14-16 yr
14-16 yr
25-30 yr
25-30 yr
40-45 yr
40-45 yr
60-65 yr
60-65 yr
70+ yr
70+ yr
Average Perchlorate Intake from Food
(ug/kg/day)
Lower-bound
0.26
0.35
0.25
0.17
0.09
0.12
0.09
0.08
0.09
0.09
0.09
0.09
0.09
0.11
Upper-bound
0.29
0.39
0.28
0.20
0.11
0.14
0.11
0.11
0.11
0.11
0.10
0.11
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 a/., 2008). The average estimated perchlorate intakes for the 14 age-gender
groups range from 0.08 (for 25-30 year old men) to 0.39 (for children 2 years old)
|ig/kg/day, compared with the RfD of 0.7 |ig/kg/day. Though not shown here, Murray et
al. (2008) reports that the average estimated iodine intake for the 14 age-gender groups
range from 138 to 353 jig/person/day, and for all groups exceed the relevant US dietary
reference values used for assessing the nutritional status of populations.1
The results of the TDS dietary intake assessment provide an estimate of the average
dietary perchlorate intake by specific age-gender groups in the US. However, Murray et
al. note that the current TDS design "does not allow for estimates of intakes at the
1 Murray et al. (2008) compared estimated average iodine intake with US Dietary Reference Intakes for
iodine (NAS, 2000). The reference values cited by Murray et al. (2008) are as follows: 130 ug/person/day
for infants, 65 ug/person/day for children 1-8 years, 73 ug/person/day for children 9-13 years, and 95
ug/person/day for the remainder of population.
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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 etal. stated that: "These IDS 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 US population."
3.3.1.2 FDA Exploratory Survey Data on Perchlorate in Food, 2003-2005. Prior
to including perchlorate in the IDS, 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 jig/kg/day for all ages (2+ years), 0.17
|ig/kg/day for children (2-5 years), and 0.037 |ig/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, while the results of FDA's exploratory studies generally support the TDS
results, they are superseded by the results of the TDS, and as such they are not being used
in arriving at an interim HA.
3.3.1.3 Other Published Food Studies. Pearce etal. (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
Hg/L, with a median concentration of 1.5 |ig/L. The researchers did not estimate the
perchlorate dose to which infants would be exposed at the concentrations observed in the
study. FDA also included sampling and analysis of infant formula in their current 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.
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3.4 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, CDC can obtain data on the
levels and trends of exposure to environmental chemicals in the US population.
3.4.1 Urinary Biomonitoring. In the largest study of its kind, Blount etal. (2006c)
measured perchlorate in urine samples collected from a nationally representative sample of
2,820 US residents as part of the 2001-2002 NHANES. Blount et al. (2006c) detected
perchlorate at concentrations greater than 0.05 |ig/L in all 2,820 urine samples tested, with
a median concentration of 3.6 |ig/L and a 95th percentile of 14 |ig/L. Women of
reproductive age (15-44 years) had a median urinary perchlorate concentration of 2.9 |ig/L
and a 95th percentile of 13 |ig/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 |ig/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 jig/kg/day (about one tenth of the RfD)
and a 95th percentile dose of 0.234 jig/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
|ig/kg/day (the highest calculated exposure was 3.78 jig/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). Analyses on
pregnant and lactating women were limited because no information was available
regarding the trimester or stage of pregnancy for women reported as pregnant in the study,
and no specific information was available on the characteristics of lactating women.
EPA and CDC investigators merged the data sets from NHANES and UCMR 1 to
identify the NHANES participants from counties which had one or more perchlorate
detections during the UCMR survey (USEPA, 2008b). The study assumes, based on
previous analyses of perchlorate pharmacokinetics, that urine is the sole excretion pathway
of perchlorate from participants other than 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 as those participants whose exposure was
expected to be primarily from food.
The advantage of a urinary biomonitoring study is that it reflects the perchlorate
actually ingested in the diets of a large number of individuals rather than using estimators
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of perchlorate ingestion from a variety of foods for a diverse population. The analysis of
biomonitoring data also provides a novel opportunity to use public water system
occurrence and human biomonitoring data to compare perchlorate concentration in urine
from people in areas with perchlorate in their drinking water with perchlorate
concentration in urine from people in areas with no reported perchlorate in their drinking
water. The approach is reasonable for estimating perchlorate intake at various percentiles
from food and to gain an understanding of the relative contribution from drinking 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.
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
separated based on the likelihood of perchlorate being in their tap water. Groups 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.
This group 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 |ig/kg/day, with a geometric mean of 0.080 |ig/kg/day.
A second group was defined in one of three ways and was comprised of data for
individuals considered less likely to have exposure to perchlorate via drinking water and
thus, more likely to have their perchlorate exposure caused solely by intake from food: (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 |ig/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) not
considering the UCMR status of the county, their response to NHANES indicated they
used a reverse osmosis filter to filter their tap water, which would likely be effective for
removing perchlorate. The average creatinine-corrected perchlorate dose for these
individuals was 0.090 |ig/kg/day, with a geometric mean of 0.062 |ig/kg/day.
A summary of selected results for individuals in these two groups is shown in Table
3-2. The estimates of daily perchlorate intake presented in Table 3-2 from the NHANES-
UCMR analysis are somewhat higher than those of Blount et al. (2006a). The Blount et al.
(2006a) 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
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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 persons that
are more likely to be exposed to perchlorate in food and water was calculated to be 0.101
|ig/kg/day. The average exposure for persons more likely to be exposed to perchlorate
from food alone was 0.090 jig/kg/day.
Table 3-2. Estimated Daily Perchlorate Intakes (ug/kg/day) for Individuals
With and Without Exposure Through Drinking Water
Group
Total
Age: 6-11
Age: 12-19
Age: >20
Females:
15-44
Pregnant
Females
Perchlorate
Likely in
Water (+/-)
+
+
+
_
+
_
+
+
_
Number
of people
320
2063
52
270
100
608
168
1185
57
505
8
98
Average
(Mean)
0.101
0.090
0.152
0.150
0.109
0.080
0.091
0.085
0.081
0.093
0.097
0.123
Geometric
Mean
0.080
0.062
0.132
0.118
0.078
0.061
0.074
0.057
0.062
0.055
0.086
0.064
50th %ile
0.075
0.058
0.131
0.124
0.070
0.060
0.071
0.055
0.071
0.052
0.060
0.056
90th %tile
0.193
0.167
0.237
0.280
0.286
0.158
0.186
0.143
0.141
0.143
0.121
0.263
Comparison of exposure estimates for individuals more likely to be exposed only
through food to the FDA TDS, shown in Table 3-1, indicates good agreement at the mean.
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 |ig/kg/day, while 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 |ig/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.
3.4.2 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, etal., 2007). Perchlorate
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was found in all samples, ranging from 1.3-411 |ig/L, with a median concentration of 9.1
Hg/L and a mean concentration of 33 |ig/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 US EPA's
UCMR from 2001 to 2003, nor did Boston area systems detect perchlorate in samples
collected in response to the Massachusetts Department of Environmental Protection (DEP)
2004 emergency regulations for perchlorate.
Kirk etal. (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 |ig/L, with a mean concentration of
10.5 |ig/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 |ig/L, 5.8 |ig/L, and 4.0 |ig/L, respectively.
Tellez 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 concentrations and either urine
perchlorate concentrations or breast milk iodide concentrations for the individuals
evaluated in these Chilean cities (Tellez et al., 2005).
Blount et al. (2007) also suggested 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 |ig/kg/day for 117 pregnant women compared to a concentration of
0.073 |ig/kg/day for the 24 breast-feeding women (USEPA, 2008b).
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 |ig/L, with a median concentration of
7.3 |ig/L and a mean concentration of 9.3 |ig/L (457 total samples), while for iodine,
concentrations ranged from 1 to 1,200 |ig/L, with a median concentration of 43 |ig/L and a
mean concentration of 120 |ig/L (447 total samples). For urine they found perchlorate
concentrations ranging from 0.6 to 80 |ig/L, with a median concentration of 3.2 |ig/L and a
mean concentration of 4.0 |ig/L (110 total samples), while for iodine, concentrations
ranged from 26 to 630 |ig/L, with a median concentration of 110 |ig/L and a mean
concentration of 140 |ig/L (117 total samples).
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3.5 Soil
As discussed above (see section 3.0), perchlorate has been detected in fertilizers
derived from Chilean caliche (US EPA, 2001), and perchlorate-containing fertilizers could
result in contamination of soil as a direct result of their intended use (ATSDR, 2005).
Perchlorate has also been found in other geologic materials. Orris et al. (2003) measured
perchlorate at levels exceeding 1,000 parts per million (ppm or mg/kg) in several samples
of natural minerals, including potash ore from New Mexico and Saskatchewan (Canada),
playa crust from Bolivia, and hanksite from California.
4.0 HEALTH EFFECTS DATA
4.1 Human Studies and Modeling
4.1.1 Mode of Action. 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 the 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 RfD used in this assessment was developed by the 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. NRC (2005) noted that "Using a nonadverse effect
that is upstream of the adverse effect is a more conservative, health-protective approach to
the perchlorate risk assessment." This approach is consistent with the Agency's policy on
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the use of precursor events when appropriate in establishing the critical effect upon which
an RfD is based (U.S. EPA, 2002c).
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 a/., 1999, 2003; Haddow et a/., 1999; Kooistra et a/., 2006; Morreale de
Escobar et a/., 2004a, 2004b). 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 a/., 2004;
Gilbert and Sui, 2008; Sharlin etal, 2008; Goldey etal, 1995).
4.1.2 Epidemiology Data. The data from epidemiological studies of the general
population provide some information on possible effects of perchlorate exposure. Based
on an 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-birth weight, 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-birth weight or preterm infants (US EPA, 2005a).
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 etal., 2007), while another study (Blount etal., 2006b) did identify
such effects.
4.1.3 Biomonitoring Studies. After the NRC report was released, several papers
were published that investigated whether biomonitoring data associated with 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 etal. (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
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(ages 12 years and older) who participated in CDC's 2001-2002 NHANES2. 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 of 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.
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, those women with higher-iodide and lower-iodide urinary
content, using a cut point of 100 |ig/L of urinary iodide based on the median level the
World Health Organization (WHO) considers indicative of sufficient iodide intake3 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 |ig/L (Caldwell et al., 2005). For women with urinary iodide levels
less than 100 |ig/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 |ig/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 the thyroid function.
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-
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.
3 WHO notes that the prevalence of goiter begins to increase in populations with a median urinary iodide
level below 100 ug/L (WHO, 1994).
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antibodies, free T4). An additional paper by Blount et al. (2006c) 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
|ig/kg/day.
The Blount study suggested that perchlorate could be a surrogate for another
unrecognized determinant of thyroid function. There are other chemicals, including nitrate
and thiocyanate, which can affect the 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 jig /I. 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 perchlorate or T4 and smoking, cotinine
or thiocyanate in men or in women with urinary iodine levels greater than 100 |ig/l. In
addition, they found no association between cotinine and T4 or TSH in women with iodine
levels lower than 100 |ig/l. However, in women with urinary iodine levels lower than 100
|ig/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
agents other than tobacco smoke might cause similar interactions (Steinmaus 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 |ig/L),
"high" (12.94 |ig/L), or "low" (<3 |ig/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 |ig/dL, respectively, showing no significant
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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-birth weight or preterm
newborns, offspring of mothers who had iodide deficiency during gestation, or offspring of
hypothyroid mothers."
4.1.4 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 an 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 the 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 a/.'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 the 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 jig/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 times higher than for non-pregnant adults. Smaller relative differences were predicted
at external doses of 100 and 1000 jig/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 |ig/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 jig/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 etal.,
2005) and another following women through pregnancy and lactation (Gibbs et al., 2004).
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The model predicted average blood serum concentrations of perchlorate in 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 also 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
RfDofO.7 |ig/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 to describe thyroidal radioactive iodide uptake (RAIU) inhibition by perchlorate
for the average adult (Merrill et a/., 2005), pregnant woman and fetus, lactating woman
and neonate, and the young child (Clewell et a/., 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, 2008c) 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 life stages. 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,
2008c), the Clewell et al. (2007) and Merrill et al. (2005) models provide an appropriate
basis for calculating the life stage differences in the degree of thyroidal RAIU inhibition at
a given level of perchlorate exposure.
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4.1.5 Carcinogenicity. The NRC (2005) reviewed the available human data and
reached the following conclusion: "The epidemiologic evidence is insufficient to
determine whether there is a causal association between perchlorate exposure and thyroid
cancer. Only two studies related to this issue have been done, and both were ecologic. In
one study, the number of thyroid-cancer cases was too small to have a reasonable chance
of detecting an association if one existed (Li et a/., 2001). In the second, larger study
(Morgan and Cassady, 2002), mixed exposures were present (to perchlorate and TCE). In
neither study was it possible to adjust for potential confounding variables. The committee
notes, however, that on the basis of its understanding of the biology of human and rodent
thyroid tumors, it is unlikely that perchlorate poses a risk of thyroid cancer in humans."
4.2 Animal Studies
The NRC (2005) conducted a thorough review of the animal studies and reached the
following conclusions:
"The committee found that the animal studies of potential adverse effects of
perchlorate provided qualitative information, but the usefulness of the studies for
quantitatively estimating the risk of adverse effects in humans is small. The major
conclusions from the animal data are summarized below.
• Perchlorate has an antithyroid effect on rats at high doses (30 mg/kg of
ammonium perchlorate per day). That effect is characterized by decreases in
serum thyroid hormone and increases in serum TSH with morphologic changes in
the thyroid gland.
• The data are inadequate to determine whether or not a causal relationship exists
between perchlorate exposure of pregnant rats and neurodevelopmental
abnormalities in their pups, given the flaws in experimental design and methods
in the studies conducted to evaluate that end point.
• The data are inadequate to determine whether or not perchlorate exposure during
gestation and lactation in rats has effects on behavior, given the lack of sensitivity
of the tests conducted to evaluate that end point.
• Exposure to perchlorate can increase the incidence of thyroid tumors in rats when
the doses are high enough to decrease thyroid hormone production and increase
TSH secretion.
• The data favor rejection of a causal relationship between perchlorate exposure
and immunotoxicity.
• There are no data to suggest that perchlorate has effects that are not mediated
through inhibition of iodide transport in the thyroid gland.
• It is not possible to extrapolate data quantitatively from rodents to humans for
purposes of human health risk assessment. Most experimental studies in animals
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designed to characterize the effects of perchlorate exposure have been done in
rats. However, rats are much more sensitive to agents that disturb thyroid
function than are humans, so the relevance of rat studies in quantitative terms to
humans is limited."
5.0 QUANTIFICATION OF TOXICOLOGICAL EFFECTS
A subchronic HA covers a period of more than 30 days, but less than a year, and
considers the following exposure assumptions: a 70 kg adult consuming 2 Liters of water
per day. A relative source contribution (RSC) from water is also factored into the
subchronic HA calculation to account for contaminant exposures from other sources (air,
food, soil, etc.) of the contaminant.
The subchronic HA is calculated in a three-step process:
Step 1: Adopt a pre-existing Reference Dose (RfD) or calculate an RfD using
the following equation:
NOAEL or LOAEL or BMDL
RfD —
UF
Where:
NOAEL or = No- or Lowest-Observed-Adverse-Effect Level (in mg/kg
LOAEL bw/day).
BMDL = Lower confidence bound on the Bench Mark Dose (BMD).
The BMD and BMDL are obtained through modeling of the
dose-response relationship.
UF = Uncertainty factor established in accordance with EPA
guidelines.
The RfD is an estimate (with uncertainty spanning perhaps an order of magnitude) of
a daily human exposure to the human population (including sensitive subgroups) that is
likely to be without an appreciable risk of deleterious effects. It can be derived from a
NOAEL, LOAEL, or benchmark dose (BMD) with uncertainty factors generally applied to
reflect limitations in the data used. It is also sometimes derived from a NOEL, as is the
case for perchlorate, which provides a more health-protective value than using a NOAEL,
LOAEL or BMD.
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Step 2: From the RfD, calculate a Drinking Water Equivalent Level (DWEL).
The DWEL assumes that 100% of the exposure comes from drinking water.
DWEL =
DWI
Where:
RfD = Reference Dose (in mg/kg bw/day).
BW = Assumed body weight of an adult (70 kg).
DWI = Assumed human daily consumption for an adult (2 L/day)
Step 3: The subchronic HA is calculated by factoring in other sources of
exposure (such as air, food, soil) in addition to drinking water using the relative source
contribution (RSC) for the drinking water.
Subchronic HA = DWEL x RSC
Where:
DWEL = Drinking Water Equivalent Level (calculated from step 2)
RSC = Relative source contribution
Note. The procedure for establishing the RSC for perchlorate is below.
5.1 Reference Dose Derivation
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 jig/kg/day in
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 jig/kg/day, corresponding to 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
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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 NRC also stated "if that nonadverse
biochemical event is used to derive the RfD, chronic exposure will have no greater effect
than that resulting from short term exposure." The lowest dose (7 |ig/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 |ig/kg/day, derived by applying a ten-
fold total uncertainty factor to the NOEL of 7 |ig/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 perhlorate risk assessment. Using a
nonadverse effect that is upstream of the adverse effect is a more conservative, health-
protective approach to the perchlorate risk assessment." The NRC also noted that the
purpose of the 10-fold uncertainty factor is to protect sensitive subpopulations in the face
of uncertainty regarding their relative sensitivity to perchlorate exposure. The NRC
recognized that additional information on these relative sensitivities could be used to
reduce this uncertainty factor in the future (NRC, 2005).4
4 "There can be variability in responses among humans. The intraspecies uncertainty factor accounts for that
variability and is intended to protect populations more sensitive than the population tested. In the absence of
data on the range of sensitivity among humans, a default uncertainty factor of 10 is typically applied. The
factor could be set at 1 if data indicate that sensitive populations do not vary substantially from those
tested." (NRC, 2005, p 173)
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5.2 Relative Source Contribution Derivation
Sufficient exposure data are available for perchlorate to enable EPA to estimate a
data- derived RSC for fetuses of pregnant women (the most sensitive subpopulations
identified by the NRC). These exposure data include the analysis by EPA of the UCMR
data and CDC's NHANES biomonitoring data, as well as FDA's IDS. The following
sections describe EPA's analyses of each of these data sources to estimate RSCs and HA
level for sensitive subpopulations.
5.2.1. Total Diet Study for Estimation of an RSC. The results of FDA's recent
evaluation of perchlorate under the TDS were presented above. 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 |ig/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 5-1.
Table 5-1. Relative Source Contributions Remaining for Water Based on TDS
for Various Subgroups
Population Group
Infants, 6-11 mo
Children, 2 yr
Children, 6 yr
Children, lOyr
Teenage Girls, 14-16 yr
Teenage Boys, 14-16 yr
Women, 25-30 yr
Men, 25-30 yr
Women, 40-45 yr
Men, 40-45 yr
Total Perchlorate
Intake from Food
(|ig/kg/day)
0.26-0.29
0.35-0.39
0.25-0.28
0.17-0.20
0.09-0.11
0.12-0.14
0.09-0.11
0.08-0.11
0.09-0.11
0.09-0.11
RfD that
Remains
(|ig/kg/day)
0.41-0.44
0.31-0.35
0.42-0.45
0.50-0.53
0.59-0.61
0.56-0.58
0.59-0.61
0.69-0.62
0.59-0.61
0.59-0.61
RSC Remaining for
Drinking Water
(as%ageoftheRfD)
59%-63%
44%-50%
60%-64%
71%-76%
84%-87%
80%-83%
84%-87%
84%-89%
84%-87%
84%-87%
22
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Population Group
Women, 60-65 yr
Men, 60-65 yr
Women, 70+ yr
Men, 70+ yr
Total Perchlorate
Intake from Food
(Hg/kg/day)
0.09-0.10
0.09-0.11
0.09-0.11
0.11-0.12
RfDthat
Remains
(ng/kg/day)
0.60-0.61
0.59-0.61
0.59-0.61
0.58-0.59
RSC Remaining for
Drinking Water
(as%ageoftheRfD)
86%-87%
84%-87%
84%-87%
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 RSC from food for pregnant women.
5.2.2. Urinary Data for Estimation of an RSC. 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 5-2, indicate that for pregnant women, exposure to perchlorate from
food is 0.263 |ig/kg/day at the 90th percentile, representing nearly 38 percent of the RfD,
and thus leaving an RSC for water of 62 percent.
Table 5-2. Fraction of RfD (Relative Source Contribution) Based On NHANES-
UCMR Analysis Calculations of Perchlorate in Food
Group
Total
population
Ages 6-11
Ages 12-19
; ; RSC From
Mean Food i RfD that : Drinking
Dose ; Remains ; Water as
(jig/kg/day) : (jig/kg/day) I % of RfD
0.090
0.150
0.080
0.61
0.55
0.62
87
79
89
90th
Percentile
Food Dose
(jig/kg/day)
0.167
0.280
0.158
! RSC From
RfDthat \ Drinking
Remains : Water as %
(jig/kg/day) \ of RfD
0.533
0.42
76
60
0.542 \ 77
23
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Group
Ages 20 +
Female 15-
44
Pregnant
Mean Food
Dose
(Hg/kg/day)
0.085
0.093
0.123
RfDthat
Remains
(jig/kg/day)
0.615
0.607
0.58
RSC From
Drinking
Water as
%ofRfD
88
87
82
90th
Percentile
Food Dose
(Hg/kg/day)
0.143
0.143
0.263
RfDthat
Remains
(jig/kg/day)
0.557
0.557
0.437
RSC From
Drinking
Water as %
ofRfD
80
80
62
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 5-3
presents the potential RSC values 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.
(2008) 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 determine the interim HA level for drinking water by subtracting the
90th percentile exposure in food from the reference 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 interim HA
level of 15 |ig/L for the pregnant woman.
24
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Table 5-3. Potential Health Advisory Levels for Pregnant Women Using TDS
Data and NHANES-UCMR Data To Derive Relative Source Contribution
Sub
population
Women of
Childbearing
Age
Pregnant
Women
Pregnant
Women
Body
Weight a
70kg
70kg
70kg
Drinking Water
Consumption21
2 liters
2 liters
2 liters
Source of RSC
Derivation
TDS mean
(Table 5-1)
NHANES-UCMR
mean (Table 5-2)
NHANES-UCMR
90th percentile
(Table 5-2)
RSC From
Drinking
Water as
%RfD
84 - 87%
82%
62%
Potential
HA level
21|ig/L
20|ig/L
15|ig/L
Footnotes:
aDefault values used by EPA in the derivation of HA levels.
5.3 Subchronic Interim Health Advisory
Based upon the recommendations of the NRC (2005), the subchronic interim HA was
calculated for a pregnant woman as presented below:
Subchronic HA =
0.007 mg/kg/day x 70 kg x 0.6 2
10x2 L/day
= 0.0152 mg/L(roundedto0.015mg/Lorl5//g/L)
Where:
0.007 mg/kg/day
70kg
10
2L
0.62
NOEL (Greer etal., 2002)
Assumed body weight of an adult
Uncertainty factor
Assumed daily water consumption of an adult
Relative source contribution (Using urinary data from
the 2001-2002 National Health and Nutrition
Examination Survey (NHANES) combined with UCMR
occurrence data evaluating nationwide exposure to
perchlorate (using the 90th percentile of the
distribution), an RSC of 62% was calculated.)
25
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Note: The application of a 10-fold uncertainty factor accounts for variability in responses
among humans, and is intended to protect populations that are more sensitive than the
population tested. Because the critical study (Greer et a/., 2002) for perchlorate was based
on healthy adult men and women, an uncertainty factor of 10 is applied to protect the most
sensitive population, the fetuses of pregnant women who might have hypothyroidism or
iodide deficiency.
EPA developed the interim health advisory for the subchronic drinking water
exposure of the pregnant mother and her fetus. However, as noted by the NRC in their
recommendations, "chronic exposure will have no greater effect than that resulting from
short-term exposure. In fact, it may well have less effect because of the capacity of the
pituitary -thyroid system to compensate for iodide deficiency by increasing iodide
uptake."
5.4 Subchronic Health Advisories for Other Sensitive Subpopulations
Under the Safe Drinking Water Act, EPA must consider possible risk to sensitive
subpopulations. EPA developed its subchronic interim HA 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), and used the 90th
percentile rather than mean food exposure data to ensure that the interim HA protects
highly exposed pregnant women and their fetuses. However, infants, developing children,
and persons 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 |ig/L of
perchlorate may result in exposure that is greater than the reference dose in these sub-
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.
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 interim level of 15 |ig/L (derived for pregnant women) is also an
appropriate interim HA level for the other sensitive subpopulations. Reducing some of the
uncertainty regarding the relative sensitivities of these subpopulations will help 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 interim HA level, these groups do not experience precursor effects
(RAIU inhibition) that exceed the no effect level from which the reference dose was
derived.
5.4.1 Published PBPK Models. The Clewell etal. (2007) and Merrill etal. (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.
26
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Clewell etal. (2007) predicted that at a perchlorate dose of 0.001 mg/kg/day (1
Hg/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 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
above.
5.4.2 Results of EPA's Application of the Published Models. EPA evaluated the
published models (Clewell et a/., 2007, and Merrill et a/., 2005) and used them to further
explore the relationship between water concentrations and iodide uptake inhibition in
different subpopulations. 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 jig/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
interim HA is an appropriate level for all subpopulations (not just pregnant women).
EPA thus applied the adjusted model to the interim HA level of 15 |ig/L to
determine the predicted percent RAIU inhibition (Table 5-4). 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 |ig/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
27
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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.5
Table 5-4 also shows the exposure to each subpopulation in |ig/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
interim HA level 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 interim HA level of 15 |ig/L derived for pregnant women is also an
appropriate interim HA level for other sub-populations, against which to evaluate
monitored levels of perchlorate occurrence in drinking water systems.
5 The model does not exactly match the average measured inhibition at each exposure concentration. At
the point of departure (7 ug/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.
28
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Table 5-4. Predicted percent radioactive iodide uptake (RAIU) inhibition and corresponding perchlorate intake
from water at 15 |ig/L with and without food intake.
Average adult
Non-pregnant
woman
Pregnant
woman
Mom - GW 13
Mom - GW 20
Mom - GW 40
Fetus - GW 40g
Breast-fed
infant
Mom ~ 7 d
Infant - 7 d
Mom — 60 d
Infant - 60 d
Body
Weight
(kg)a
70
66
69
71
78
3.5
74
3.6
72
5
90th
Percentile
Water
Intake
(L/day)b
2.24
2.11
2.18
2.34
2.57
—
2.96
0.52d
2.96
0.74d
Perchlorate
Intake
from only
water at 15
ug/L
(jig/kg-day)
0.48
0.48
0.50
0.50
0.50
—
0.60
1.36
0.61
1.27
Percent
RAIU
Inhibition
from only
water at
15ug/L
0.15
0.21
0.49
0.49
0.47
0.90
0.18
1.1
0.17
0.73
TDS
estimated
perchlorate
intake from
food
(Hg/kg-day)c
0.10
0.10
0.10
0.10
0.10
—
0.10
a
0.10
d
Perchlorate
Intake from
food and
water at 15
Hg/L
(jig/kg-day)
0.58
0.58
0.60
0.60
0.60
—
0.70
1.59
0.71
1.48
Percent
RAIU
Inhibition
from food
and water at
15jig/L
0.18
0.26
0.59
0.59
0.57
1.1
0.21
1.3
0.20
0.84
29
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Bottle-fed
infant
Infant -- 7 d
Infant -- 60 d
Child
6-12 mof
l-2yrf
Body
Weight
(kg)a
3.6
5
9.2
11.4
90th
Percentile
Water
Intake
(L/day)b
0.84e
1.14e
1.03
0.64
Perchlorate
Intake
from only
water at 15
ug/L
(jig/kg-day)
3.53
3.42
1.68
0.84
Percent
RAIU
Inhibition
from only
water at
15ng/L
2.0
1.3
0.46
0.23
TDS
estimated
perchlorate
intake from
food
(jig/kg-day)c
1.42ng/L
1.42|ig/L
0.275
0.370
Perchlorate
Intake from
food and
water at 15
ug/L
(jig/kg-day)
3.87
3.74
1.96
1.21
Percent
RAIU
Inhibition
from food
and water at
15ng/L
2.2
1.4
0.53
0.33
Calculations for a 70 kg "average" adult are shown, while the body weight (BW) for the non-pregnant woman is from US
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 etal. (2002) as implemented in the PBPK models (Clewell etal. 2007; non-
pregnant value is BW at day 0 of gestation).
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).
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
|ig/L as the concentration of perchlorate in infant formula. This is based on an average of available FDA TDS data, with !/2
LOD included in the average for the samples in which perchlorate was not detected.
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
30
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(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).
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=l 14) for the 1- to <3 months-old infant was used.
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).
Due to data limitations, RAIU inhibition is calculated only for fetuses at GW 40.
31
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5.4.3 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 HA. Rather, the interim HA level of 15 |ig/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 interim HA level 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 5-4 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 5-4.
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).
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
32
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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 life stages 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.
5.4.4 Summary of Modeling Analysis. EPA focused attention on the most sensitive
subpopulation, a pregnant woman and her fetus. EPA calculated an interim HA level of 15 jig/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 interim HA 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 perchl orate would not exceed the reference dose if she consumed drinking
water with a concentration of 15 |ig/L or less, which is consistent with the derivation of the
interim HA level 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 |ig/L perchl orate (in combination with a normal diet) is 1.1 percent which is 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 interim HA level (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 that drinking water with perchlorate concentrations at or below the
interim HA level of 15 |ig/L is protective of all subpopulations.
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5.5 Evaluation of Carcinogenic Potential
The EPA currently requires that all new cancer risk assessments comply with the
Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005). The EPA (2005) describes
perchlorate's weight of evidence classification as "not likely to pose a risk of thyroid cancer in
humans, at least at doses below those necessary to alter thyroid hormone homeostasis, based on
the hormonally-mediated mode of action in rodent studies and species differences in thyroid
function. The epidemiological evidence is insufficient to determine whether or not there is a
causal association between exposure to perchlorate and thyroid cancer."
6.0 OTHER CRITERIA, GUIDANCE, AND STANDARDS
Two states have established regulatory standards for perchlorate in drinking water. In July
2006, Massachusetts promulgated a drinking water standard of 2 |ig/L for perchlorate (Mass
DEP, 2006), while California established an MCL of 6 |ig/L in October 2007 (CDPH, 2007).
The states used the same NOEL from the Greer et al. (2002) study as EPA, but different
methodologies for calculating RSC and addressing sensitive subpopulations. EPA believes that
its analysis is based on the best currently available science, data, and analyses, including some
analyses that were not available at the time these state standards were established, and that
drinking water with perchlorate concentrations at or below its interim HA level of 15 |ig/L is
protective of all subpopulations. The SDWA allows States to establish drinking water standards
that are more stringent than EPA's national standards, as well as for contaminants which EPA
has determined not to regulate. EPA supports such state action, especially in cases where there
are not enough public water systems above the interim HA level to warrant a national standard,
but where a few individual states may have a higher concentration of such systems.
7.0 ANALYTICAL METHODS
Perchlorate can be detected in drinking water by EPA methods 314.0, 314.1,314.2, 331.0
and 332.0. EPA method 314.0 was approved for the 2001 through 2003 monitoring of
perchlorate, required in the UCMR, and employs ion chromatography with conductivity
detection. The method detection limit (MDL) for method 314.0 is 0.53 |ig/L and the average
recovery is reported to range from 86 to 113 percent, depending on the matrix.
EPA Methods 314.1,314.2, 331.0, and 332.0 are newer methods that were published from
May 2005 through May 2008. Method 314.1 relies on ion chromatography with suppressed
conductivity detection, has an MDL of approximately 0.03 |ig/L and an average recovery
ranging from 75.9 to 108 percent, depending on the matrix and the type of analytical column
used. Method 314.2 uses two-dimensional ion chromatography followed by suppressed
conductivity detection. The MDL for perchlorate using this method is 0.012 to 0.018 |ig/L,
depending upon the volume of sample analyzed, and the average recovery of perchlorate ranges
from 92 to 110 percent, depending upon the matrix. Method 331.0 employs liquid
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chromatography with electrospray ionization mass spectrometry. The MDL for perchlorate
using this method is 0.008 |ig/L in selected ion monitoring mode (single stage mass
spectrometry) and 0.005 |ig/L in multiple reactions monitoring mode (tandem mass
spectrometry). The average recovery for perchlorate using Method 331.0 ranges from 95.1 to
105 percent, depending on the matrix. Method 332.0 employs ion chromatography with
electrospray ionization mass spectrometry detection. The MDL for perchlorate using this
method is 0.02 |ig/L and the average recovery ranges for 90 to 105 percent, depending on the
matrix.
8.0 TREATMENT TECHNOLOGIES
The physiochemical properties of perchlorate make its removal difficult by chemical
precipitation processes, such as conventional treatment. Researchers, however, have shown that
perchlorate can be effectively removed by using advanced treatment technologies, such as anion
exchange, modified granular activated carbon (GAC), reverse osmosis/nanofiltration membrane
filtration, chemical/electrochemical reduction (Gu and Coates, 2006) and biological reduction
(Logan et a/., 2004).
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