Document ID: EPA-HQ-OW-2018-0780-0001
Agency: epa
Document Type: Proposed Rule
Title: National Primary Drinking Water Regulations: Perchlorate
Posted Date: 2019-06-26T04:00Z

[Federal Register Volume 84, Number 123 (Wednesday, June 26, 2019)]
[Proposed Rules]
[Pages 30524-30569]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-12773]

[[Page 30523]]

Vol. 84

Wednesday,

No. 123

June 26, 2019

Part IV

Environmental Protection Agency

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40 CFR Parts 141 and 142

National Primary Drinking Water Regulations: Perchlorate; Proposed Rule

  Federal Register / Vol. 84, No. 123 / Wednesday, June 26, 2019 / 
Proposed Rules  

[[Page 30524]]

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ENVIRONMENTAL PROTECTION AGENCY

40 CFR Parts 141 and 142

[EPA-HQ-OW-2018-0780; FRL-9994-68-OW]
RIN 2040-AF28

National Primary Drinking Water Regulations: Perchlorate

AGENCY: Environmental Protection Agency (EPA).

ACTION: Proposed rule, request for public comment.

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SUMMARY: The Environmental Protection Agency (EPA) is proposing a 
drinking water regulation for perchlorate and a health-based Maximum 
Contaminant Level Goal (MCLG) in accordance with the Safe Drinking 
Water Act (SDWA). The EPA is proposing to set both the enforceable 
Maximum Contaminant Level (MCL) for the perchlorate regulation and the 
perchlorate MCLG at 0.056 mg/L (56 [micro]g/L). The EPA is proposing 
requirements for water systems to conduct monitoring and reporting for 
perchlorate and to provide information about perchlorate to their 
consumers through public notification and consumer confidence reports. 
This proposal includes requirements for primacy agencies that implement 
the public water system supervision program under the SDWA. This 
proposal also includes a list of treatment technologies that would 
enable water systems to comply with the MCL, including affordable 
compliance technologies for small systems serving 10,000 persons or 
less.

DATES: Comments must be received on or before August 26, 2019. Under 
the Paperwork Reduction Act (PRA), comments on the information 
collection provisions are best assured of consideration if the Office 
of Management and Budget (OMB) receives a copy of your comments on or 
before July 26, 2019.

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OW-
2018-0780, at https://www.regulations.gov. Follow the online 
instructions for submitting comments. Once submitted, comments cannot 
be edited or removed from Regulations.gov. The EPA may publish any 
comment received to its public docket. Do not submit electronically any 
information you consider to be Confidential Business Information (CBI) 
or other information whose disclosure is restricted by statute. 
Multimedia submissions (audio, video, etc.) must be accompanied by a 
written comment. The written comment is considered the official comment 
and should include discussion of all points you wish to make. The EPA 
will generally not consider comments or comment contents located 
outside of the primary submission (i.e., on the web, cloud, or other 
file sharing system). For additional submission methods, the full EPA 
public comment policy, information about CBI or multimedia submissions, 
and general guidance on making effective comments, please visit http://www2.epa.gov/dockets/commenting-epa-dockets.

FOR FURTHER INFORMATION CONTACT: Samuel Hernandez, Office of Ground 
Water and Drinking Water, Standards and Risk Management Division (Mail 
Code 4607M), Environmental Protection Agency, 1200 Pennsylvania Avenue 
NW, Washington, DC 20460; telephone number: (202) 564-1735; email 
address: hernandez.samuel@epa.gov.

SUPPLEMENTARY INFORMATION: In addition to the proposed regulation, the 
EPA is requesting comment on three alternatives: (1) Whether the MCL 
and MCLG for perchlorate should be set at 0.018 mg/L (18 [micro]g/L), 
(2) whether the MCL and MCLG for perchlorate should be set at 0.090 mg/
L (90 [micro]g/L), or (3) whether instead of issuing a national primary 
drinking water regulation, the EPA should withdraw the Agency's 
February 11, 2011, determination to regulate perchlorate in drinking 
water based on new information that indicates that perchlorate does not 
occur in public water systems with a frequency and at levels of public 
health concern and there may not be a meaningful opportunity for health 
risk reduction through a drinking water regulation. Under this last 
alternative, the final action would be a withdrawal of the 
determination to regulate and there would be no MCLG or national 
primary drinking water regulation for perchlorate. This proposed rule 
is organized as follows:

I. General Information
    A. What is the EPA proposing?
    B. Does this action apply to me?
II. Background
    A. What is perchlorate?
    B. Statutory Authority
    C. Statutory Framework and Regulatory History
III. Assessment and Modeling of the Health Effects of Perchlorate
    A. 2008 Preliminary Regulatory Determinations
    B. 2009 Supplemental Request for Comment and 2011 Final 
Regulatory Determination
    C. Science Advisory Board Recommendations
    D. Perchlorate Model Development and Peer Reviews
    E. Sensitive Population for Deriving MCLG
    F. BBDR Model Specification for the Sensitive Population
    G. Epidemiological Literature
    H. Identifying a Point of Departure for Developing the MCLG
    I. Translate PODs to RfDs
    J. Translate RfD Into an MCLG
IV. Maximum Contaminant Level Goal and Alternatives
V. Maximum Contaminant Level and Alternatives
VI. Occurrence
VII. Analytical Methods
VIII. Monitoring and Compliance Requirements
    A. What are the proposed monitoring requirements?
    B. Can States grant monitoring waivers?
    C. How are system MCL violations determined?
    D. When must systems complete initial monitoring?
    E. Can systems use grandfathered data to satisfy the initial 
monitoring requirements?
IX. Safe Drinking Water Act Right to Know Requirements
    A. What are the Consumer Confidence Report requirements?
    B. What are the public notification requirements?
X. Treatment Technologies
    A. What are the best available technologies?
    B. What are the small system compliance technologies?
XI. Rule Implementation and Enforcement
    A. What are the requirements for primacy?
    B. What are the State record keeping requirements?
    C. What are the State reporting requirements?
XII. Health Risk Reduction Cost Analysis
    A. Identifying Affected Entities
    B. Method for Estimating Costs
    C. Method for Estimating Benefits
    D. Comparison of Costs and Benefits
XIII. Uncertainty Analysis
    A. Uncertainty in the MCLG Derivation
    B. Uncertainty in the Economic Analysis
XIV. Request for Comment on Proposed Rule
XV. Request for Comment on Potential Regulatory Determination 
Withdrawal
XVI. Statutory and Executive Order Reviews
    A. Executive Order 12866: Regulatory Planning and Review and 
Executive Order 13563 Improving Regulation and Regulatory Review
    B. Executive Order 13771: Reducing Regulations and Controlling 
Regulatory Costs
    C. Paperwork Reduction Act
    D. Regulatory Flexibility Act (RFA)
    E. Unfunded Mandates Reform Act
    F. Executive Order 13132: Federalism
    G. Executive Order 13175: Consultation and Coordination With 
Indian Tribal Governments
    H. Executive Order 13045: Protection of Children From 
Environmental Health and Safety Risks
    I. Executive Order 13211: Actions That Significantly Affect 
Energy Supply, Distribution, or Use
    J. National Technology Transfer and Advancement Act of 1995

[[Page 30525]]

    K. Executive Order 12898: Federal Actions To Address 
Environmental Justice in Minority Populations and Low-Income 
Populations
XVII. Consultations with the Science Advisory Board, National 
Drinking Water Advisory Council, and the Secretary of Health and 
Human Services
XVIII. References

I. General Information

A. What is the EPA proposing?

    This action contains a proposal and three alternatives for public 
comment. First, the EPA proposes to establish a Maximum Contaminant 
Level Goal (MCLG) and National Primary Drinking Water Regulation 
(NPDWR) for perchlorate in public water supplies. The EPA proposes an 
MCLG of 56 [micro]g/L, and to regulate perchlorate in drinking water at 
an enforceable maximum contaminant level (MCL) of 56 [micro]g/L.
    The EPA is proposing an NPDWR for perchlorate in accordance with 
its February 11, 2011, (76 FR 7762) determination to regulate 
perchlorate under the SDWA. Based on the best available peer reviewed 
science at that time, the EPA found that perchlorate met the SDWA's 
three criteria for regulating a contaminant: (1) The contaminant may 
have an adverse effect on the health of persons, (2) the contaminant is 
known to occur or there is a substantial likelihood that the 
contaminant will occur in public water systems (PWSs) with a frequency 
and at levels of public health concern, and (3) in the sole judgment of 
the Administrator, regulation of such contaminant presents a meaningful 
opportunity for health risk reduction for persons served by PWSs.
    Second, as explained in more detail below, the EPA is soliciting 
comment on two alternative MCLG/MCL values of 18 [micro]g/L and 90 
[micro]g/L respectively. Third, in light of new considerations that 
have come to the EPA's attention since it issued its positive 
regulatory determination in 2011, including information on lower levels 
of occurrence of perchlorate than the EPA had previously believed to 
exist and new analysis of the concentration that represents a level of 
health concern, this action also discusses and requests comment on an 
alternative action under which the EPA would withdraw its 2011 
determination to regulate perchlorate. Under this alternative, there 
would be no MCLG or NPDWR for perchlorate.

B. Does this action apply to me?

    Entities that could potentially be affected include the following:

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           Category            Examples of potentially affected entities
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Public water systems.........  Community water systems: Non-transient,
                                non-community water systems.
State and tribal agencies....  Agencies responsible for drinking water
                                regulatory development and enforcement.
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    This table is not intended to be exhaustive, but rather provides a 
guide for readers regarding entities that could be affected by this 
action. To determine whether your facility or activities could be 
affected by this action, you should carefully examine this proposed 
rule. If you have questions regarding the applicability of this action 
to a particular entity, consult the person listed in the FOR FURTHER 
INFORMATION CONTACT section.

II. Background

A. What is perchlorate?

    Perchlorate is a negatively charged inorganic ion that is comprised 
of one chlorine atom bound to four oxygen atoms (ClO4-), 
which is highly stable and mobile in the aqueous environment. 
Perchlorate comes from both natural and manmade sources. It is formed 
naturally via atmospheric processes and can be found within mineral 
deposits in certain geographical areas. It is also produced in the 
United States, and the most common compounds include ammonium 
perchlorate and potassium perchlorate used primarily as oxidizers in 
solid fuels to power rockets, missiles, and fireworks. For the general 
population, most perchlorate exposure is through the ingestion of 
contaminated food or drinking water.

B. Statutory Authority

    Section 1412(b)(1)(A) of the SDWA requires the EPA to establish 
NPDWRs for contaminants that may have an adverse effect on the health 
of persons; that are known to occur or there is a substantial 
likelihood that the contaminant will occur in public water systems with 
a frequency and at levels of public health concern; and where in the 
sole judgment of the Administrator, regulation of such contaminant 
presents a meaningful opportunity for health risk reduction for persons 
served by public water systems.

C. Statutory Framework and Regulatory History

    Section 1412(b)(1)(B)(i) of the SDWA requires the EPA to publish 
every five years a Contaminant Candidate List (CCL). The CCL is a list 
of drinking water contaminants that are known or anticipated to occur 
in public water systems and are not currently subject to the EPA 
drinking water regulations. The EPA uses the CCL to identify priority 
contaminants for regulatory decision-making and information collection. 
Contaminants listed on the CCL may require future regulation under the 
SDWA. The EPA included perchlorate on the first, second, and third CCLs 
published in 1998, 2005, and 2009.
    Once listed on the CCL, the Agency continues to collect data on CCL 
contaminants to better understand their potential health effects and to 
determine the levels at which they occur in drinking water. Section 
1412(b)(1)(B)(ii) requires that, every five years, the EPA, after 
public comment, issue a determination whether or not to regulate at 
least five contaminants on the CCL. For any contaminant that the EPA 
determines meets the criteria for regulation, under Section 
1412(b)(1)(E), the EPA must issue a proposed national primary drinking 
water regulation within two years and issue a final regulation 18 
months after the proposal (which may be extended by 9 months).
    As part of its responsibilities under the SDWA, the EPA implements 
section 1445(a)(2), ``Monitoring Program for Unregulated 
Contaminants.'' This section requires that once every five years, the 
EPA issue a list of no more than 30 unregulated contaminants to be 
monitored by public water system. This monitoring is implemented 
through the Unregulated Contaminant Monitoring Rule (UCMR), which 
collects data from community water systems (CWS) and non-transient, 
non-community water systems (NTNCWS). The UCMR collects data from a 
census of large water systems (serving more than 10,000 people) and 
from a statistically representative sample of small water systems. On 
September 17, 1999, the EPA published its first UCMR (64 FR 50556) 
which required all large systems and a representative sample of small 
systems to monitor for perchlorate and 25 other contaminants (USEPA, 
1999, 2000b).
    The EPA and other federal agencies asked the National Research 
Council

[[Page 30526]]

(NRC) to evaluate the health implications of perchlorate ingestion. The 
NRC concluded that perchlorate exposure inhibits the transport of 
iodide \1\ into the thyroid by a protein molecule knows as the sodium/
iodide symporter (NIS), which may lead to decreases in two hormones, 
thyroxine (T3) and triiodothyronine (T4) and increases in thyroid-
stimulating hormone (TSH) (National Research Council (NRC), 2005b). 
Additionally, the NRC concluded that the most sensitive population to 
perchlorate exposure are ``the fetuses of pregnant women who might have 
hypothyroidism or iodide deficiency'' (p. 178). The EPA established a 
reference dose (RfD) consistent with the recommended National Research 
Council RfD of 0.7 [micro]g/kg/day for perchlorate. The reference dose 
is an estimate of a daily exposure to humans that is likely to be 
without an appreciable risk of adverse effects. This RfD was based on a 
study (Greer, Goodman, Pleus, & Greer, 2002) of perchlorate's 
inhibition of radioactive iodine uptake in healthy adults and the 
application of an uncertainty factor of 10 for intraspecies variability 
(USEPA, 2005b).
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    \1\ For the purposes of this FRN, ``iodine'' will be used to 
refer to dietary intake before entering the body. Once in the body, 
``iodide'' will be used to refer to the ionic form.
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    In October 2008, the EPA published a preliminary regulatory 
determination not to regulate perchlorate in drinking water and 
requested public comment (73 FR 60262). In that preliminary 
determination, the EPA tentatively concluded that perchlorate did not 
occur with a frequency and at levels of public health concern and that 
development of a regulation did not present a meaningful opportunity 
for health risk reduction for persons served by public water systems. 
The EPA derived and used a Health Reference Level (HRL) of 15 [mu]g/L 
based on the RfD of 0.7 [micro]g/kg/day in making this conclusion 
(USEPA, 2008a). Based primarily on the UCMR 1 occurrence data, the EPA 
estimated that less than 1% of drinking water systems (serving 
approximately 1 million people) had perchlorate levels above the HRL of 
15 [micro]g/L. Based on this information the Agency determined that 
perchlorate did not occur frequently at levels of health concern. The 
EPA also determined that there was not a meaningful opportunity for a 
NPDWR to reduce health risks.
    In January 2009 the EPA published an interim health advisory for 
perchlorate of 15 [micro]g/L, consistent with the HRL derivation for 
perchlorate of 15 [micro]g/L described above. Health Advisories are 
non-enforceable and non-regulatory and provide technical information to 
state agencies and other public health officials on health effects, 
analytical methodologies, and treatment technologies associated with 
drinking water contamination. Health Advisories provide the public, 
including the most sensitive populations, with a margin of protection 
from a lifetime of exposure. For perchlorate, the health advisory was 
developed for subchronic exposure (USEPA 2008d).
    In August 2009, the EPA published a supplemental request for 
comment with a new analysis that derived potential alternative HRLs for 
14 life stages, including infants and children. The analysis used the 
RfD of 0.7 [mu]g/kg/day and life stage-specific bodyweight and exposure 
information (74 FR 41883; USEPA, 2009a). After careful consideration of 
public comments on the October 2008 and August 2009 notices, on 
February 11, 2011, the EPA published its determination to regulate 
perchlorate (76 FR 7762; USEPA, 2011a). The Agency stated then that 
when considering the alternative HRL benchmarks described in the 2009 
notice, the likelihood of perchlorate to occur at levels of concern had 
significantly increased in comparison to the levels described on the 
2008 preliminary negative determination. The EPA concluded that as many 
as 16 million people could potentially be exposed to perchlorate at 
levels of concern, up from 1 million people originally described in the 
2008 notice.
    In its 2011 determination, the Agency found that perchlorate may 
have an adverse effect on the health of persons, that it is known to 
occur in public drinking water systems with a frequency and at levels 
that present a public health concern, and in the judgment of the 
Administrator, regulation of perchlorate presented a meaningful 
opportunity for health risk reduction for persons served by public 
water systems. As a result of the determination, and as required by 
Section 1412(b)(1)(E), the EPA initiated the process to develop an MCLG 
and NPDWR for perchlorate as described in this notice.
    In September 2012, the U.S. Chamber of Commerce (the Chamber) 
submitted to the EPA a Request for Correction under the Information 
Quality Act regarding the EPA's regulatory determination. In the 
request, the Chamber claimed that the UCMR 1 data did not comply with 
data quality guidelines and were not representative of current 
conditions. In response to this request, the EPA reassessed the data 
and removed certain source water samples that could be paired with 
appropriate follow-up samples located at the entry point to the 
distribution system. The EPA also updated the UCMR 1 data for systems 
in California and Massachusetts using state compliance data to reflect 
current occurrence conditions after state regulatory limits for 
perchlorate were implemented.
    In response to a lawsuit brought to enforce the deadlines in 
Section 1412(b)(1)(E), the U.S. District Court for the Southern 
District of New York entered a consent decree, requiring the EPA to 
propose an NPDWR with a proposed MCLG for perchlorate in drinking water 
no later than October 31, 2018, and finalize an NPDWR and MCLG for 
perchlorate in drinking water no later than December 19, 2019. The 
deadline for the EPA to propose an NPDWR with a proposed MCLG for 
perchlorate in drinking water was later extended to May 28, 2019. The 
consent decree is available in the docket for today's proposed rule.

III. Assessment and Modeling of the Health Effects of Perchlorate

    Perchlorate inhibits uptake of iodide into the thyroid gland by 
competitively binding to the NIS (ATSDR, 2008; Greer et al., 2002; NRC, 
2005; SAB 2013; Taylor et al., 2013). Iodide is necessary for the 
synthesis of thyroid hormones and decreased iodide uptake into the 
thyroid can adversely affect thyroid hormone production (SAB for the 
U.S. EPA, 2013; Blount et al., 2006; Steinmaus et al., 2007, 2013, 
2016, McMullen et al., 2017; Knight et al., 2018). These changes in 
thyroid hormone levels in a pregnant woman may be linked to changes in 
the neurodevelopment of her offspring (SAB for the U.S. EPA, 2013; 
Korevaar et al., 2016; Fan and Wu, 2016; Wang et al., 2016; Alexander 
et al., 2017; Thompson et al., 2018). In addition, alterations in 
thyroid homeostasis may impact other body systems including the 
reproductive (Alexander et al., 2017; Hou et al., 2016; Maraka et al., 
2016) and cardiovascular systems (Asvold et al., 2012; Sun et al., 
2017).
    The mode of action of perchlorate toxicity has been proposed as 
follows: exposure to perchlorate is known to inhibit the uptake of 
iodide by the thyroid gland through the NIS (NRC, 2005; SAB for the 
U.S. EPA, 2013). A sufficient inhibition of iodide uptake results in 
iodide deficiency within the thyroid. Given that T3 and T4 require 
iodide for production, a decrease in intra-thyroidal iodide can result 
in decreased production of these hormones. This could in turn result in 
increased TSH, the hormone that acts on

[[Page 30527]]

the thyroid gland to stimulate iodide uptake to increase thyroid 
hormone production (Blount, Pirkle, Osterloh, Valentin-Blasini, & 
Caldwell, 2006; National Research Council (NRC), 2005; Steinmaus, 
Miller, Cushing, Blount, & Smith, 2013; Steinmaus et al., 2016). For 
populations with developing brains (e.g., fetuses, neonates, and 
children), disruptions in homeostatic thyroid hormone function can 
result in adverse neurodevelopmental effects (Alexander et al., 2017; 
Glinoer & Delange, 2000; Glinoer & Rovet, 2009; SAB for the U.S. EPA, 
2013). Specifically, decreased maternal thyroid hormone levels during 
pregnancy, including in the hypothyroxinemic range,\2\ have been linked 
to decrements in neurocognitive function in offspring (Alexander et 
al., 2017; Thompson et al., 2018; Wang et al., 2016). There is also 
limited evidence to suggest an association with other adverse 
neurodevelopmental outcomes including ADHD, expressive language delay, 
reduced school performance, autism, and delayed cognitive development 
(Alexander et al., 2017; Ghassabian, Bongers-Schokking, Henrichs, 
Jaddoe, & Visser, 2011; Gyllenberg et al., 2016; Henrichs et al., 2010; 
Korevaar et al., 2016, Noten et al., 2015; Pop et al., 2003, 1999; SAB 
for the U.S. EPA, 2013; van Mil et al., 2012).
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    \2\ Maternal hypothyroxinemia is defined as TSH in the reference 
range and fT4 in the lower percentiles. The SAB notes that 
hypothyroxinemia has been defined by a ``variety of cutoffs . . . 
ranging from fT4 below the 10th or 5th percentiles to below the 
2.5th percentile'' (SAB, 2013, p.10) in the population.
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    The difficulty in estimating the likelihood and magnitude of the 
potential implications of perchlorate's mode of action on expressed 
neurodevelopmental health effects in humans exposed to perchlorate 
during development is the lack of robust epidemiological studies, 
especially in sensitive populations. Therefore, based on the known mode 
of action of perchlorate the Agency estimated potential health risks 
using a novel approach suggested by the EPA's Science Advisory Board 
(SAB for the U.S. EPA, 2013). The EPA's approach to estimating 
perchlorate risks has evolved over time with improved research and 
modeling capabilities. The following sections describe information 
sources the EPA used in its assessment as well as the regulatory 
process followed by the Agency in its decision making.

A. 2008 Preliminary Regulatory Determinations

    In 2005, at the request of the EPA and other federal agencies, the 
NRC evaluated the health implications of perchlorate ingestion. The NRC 
concluded that perchlorate exposure could inhibit the transport of 
iodide into the thyroid, leading to thyroid hormone deficiency (NRC, 
2005). A significant inhibition of iodide uptake results in intra-
thyroid iodide deficiency, decreased synthesis of T3 and T4, and 
increased TSH. The NRC also concluded that a prolonged decrease of 
thyroid hormones is potentially more likely to have adverse effects in 
sensitive populations (e.g., the fetuses of pregnant women who might 
have hypothyroidism or iodide deficiency). Based on these findings, the 
NRC recommended a reference dose of 0.7 [micro]g/kg/day.
    Based on NRC's analysis, the EPA established a perchlorate 
reference dose (RfD) of 0.7 [micro]g/kg/day in 2005 (USEPA, 2005). This 
value was based on a no observed effect level (NOEL) of 7 [micro]g/kg/
day identified from a study (Greer, Goodman, Pleus, & Greer, 2002) of 
perchlorate's inhibition of radioactive iodine uptake in healthy adults 
and the application of an uncertainty factor of 10 for intraspecies 
variability.
    As discussed above, in 2008, the EPA derived an HRL of 15 [mu]g/L 
using the RfD of 0.7 [mu]g/kg/day, a default bodyweight of 70 kg, a 
default drinking water consumption rate of 2 L/day, and a perchlorate-
specific relative source contribution (RSC) of 62 percent that was 
derived for a pregnant woman (USEPA, 2008a) (73 FR 60262). The RSC is 
the percentage of the RfD remaining for drinking water after other 
sources of exposure to perchlorate (i.e., food) have been considered. 
The EPA's HRL was calculated to offer a margin of protection against 
adverse health effects to the subpopulation identified by the NAS as 
likely the most sensitive to the effects of perchlorate exposure, 
fetuses.

B. 2009 Supplemental Request for Comment and 2011 Final Regulatory 
Determination

    The EPA received over 33,000 comments in response to its 2008 
preliminary determination to not regulate perchlorate (USEPA, 2011a). 
After reviewing the comments, the EPA developed alternative HRLs for 
other sensitive populations in addition to fetuses of pregnant women. 
The EPA developed alternative HRLs for 14 life stages including infants 
and children. The EPA also evaluated the occurrence of perchlorate at 
levels above these alternative HRLs using the UCMR 1 occurrence data.
    The analysis used the RfD of 0.7 [mu]g/kg/day and life stage-
specific bodyweight and exposure information (i.e., drinking water 
intake, RSC) for each of the 14 life stages evaluated. The resulting 
HRLs ranged from 1 [mu]g/L to 47 [mu]g/L. In August 2009, the EPA 
published a supplemental request for comment with the new analysis and 
HRLs (74 FR 41883; USEPA, 2009a). After careful consideration of public 
comments, on February 11, 2011, the EPA published its final 
determination to regulate perchlorate (76 FR 7762; USEPA, 2011a).

C. Science Advisory Board Recommendations

    As required by Section 1412(d) of the SDWA, as part of the NPDWR 
development process, the EPA requested comments from the Science 
Advisory Board (SAB) in 2012, seeking guidance on how best to consider 
and interpret the life stage information, the epidemiologic and 
biomonitoring data since the NRC report, physiologically-based 
pharmacokinetic (PBPK) analyses, and the totality of perchlorate health 
information to derive an MCLG for perchlorate. The SAB recommended the 
following:
     Derive a perchlorate MCLG that addresses sensitive life 
stages through physiologically based pharmacokinetic/pharmacodynamic 
(PBPK/PD) modeling based upon perchlorate's mode of action rather than 
the default MCLG approach using the RfD and specific chemical exposure 
parameters;
     expand the modeling approach to account for thyroid 
hormone perturbations and potential adverse neurodevelopmental outcomes 
from perchlorate exposure;
     utilize a mode-of-action framework for developing the MCLG 
that links the steps in the proposed mechanism leading from perchlorate 
exposure through iodide uptake inhibition--to thyroid hormone changes--
and finally to neurodevelopmental impacts; and
     ``Extend the [BBDR] model expeditiously to . . . provide a 
key tool for linking early events with subsequent events as reported in 
the scientific and clinical literature on iodide deficiency, changes in 
thyroid hormone levels, and their relationship to neurodevelopmental 
outcomes during sensitive early life stages'' (SAB for the U.S. EPA, 
2013, p. 19).
    This SAB-proposed framework would incorporate the previous endpoint 
of iodide uptake inhibition that was the basis for the RfD as part of a 
broader and more comprehensive framework that links perchlorate 
exposure to adverse neurodevelopmental outcomes. It also focuses on the 
smaller changes in thyroid hormones (specifically free T4 (fT4)) that 
are associated with maternal hypothyroxinemia and subsequent

[[Page 30528]]

adverse neurodevelopmental health effects rather than the significant 
changes in thyroid hormones (both fT4 and TSH) that are associated with 
hypothyroidism.

D. Perchlorate Model Development and Peer Reviews

    To address the SAB recommendations, the EPA revised an existing 
PBPK/PD model that describes the dynamics of perchlorate, iodide, and 
thyroid hormones in a woman during the third trimester of pregnancy 
(Lumen, Mattie, & Fisher, 2013; USEPA, 2009b). The EPA also created its 
own Biologically Based Dose Response (BBDR) models that included the 
additional sensitive life stages identified by the SAB, i.e., breast- 
and bottle-fed neonates and infants (SAB for the U.S. EPA, 2013, p. 
19).
    To determine whether the Agency had implemented the SAB 
recommendations for modeling thyroid hormone changes, the EPA convened 
an independent peer review panel to evaluate the BBDR models in January 
2017 (External Peer Reviewers for USEPA, 2017). In addition to 
estimating effects on breast fed infants, several reviewers recommended 
that the EPA shift the primary focus of its analysis to modeling the 
exposure implications to the fetus during early pregnancy. This was 
based on the knowledge that fetuses lack a functioning thyroid gland 
until approximately 16 gestational weeks and the substantial 
epidemiological evidence linking early pregnancy low fT4 levels with 
adverse neurodevelopmental outcomes (Endendijk et al., 2017, Korevaar 
et al., 2016; Morreale de Escobar, Obreg[oacute]n, & Escobar del Rey, 
2004, Pop et al., 1999; Pop et al., 2003). Specifically, the SAB 
recommended that the EPA use specific sensitive populations to develop 
the MCLG for perchlorate: ``the fetuses of hypothyroxinemic pregnant 
women, and infants exposed to perchlorate through either water-based 
formula preparations or the breast milk of lactating women'' (SAB for 
the U.S. EPA, 2013, p. 19).
    The EPA considered all recommendations from the 2017 peer review. 
The previously developed BBDR model describing perchlorate's effects in 
the third trimester (Lumen, Mattie, & Fisher, 2013; USEPA, 2009b) was 
calibrated only for that phase of pregnancy, not for the first 
trimester, and lacked a description of TSH signaling (feedback) that 
becomes significant as individuals become hypothyroxinemic or 
hypothyroid. In particular, this signaling was considered necessary to 
accurately predict responses of women with very low iodine intake, 
which was also part of the 2017 peer review recommendations. Therefore, 
the Lumen et al., (2009b) model needed to be revised to address these 
recommendations and the EPA implemented those changes needed to 
increase the scientific rigor of the model and modeling results. These 
modifications include:
     Extending the model to early pregnancy;
     Incorporating biological feedback control of hormone 
production via TSH signaling, such that the model can describe lower 
levels of iodide nutrition;
     Calibrating the model and evaluating its behavior for 
upper and lower percentiles of the population, as well as the 
population median; and
     Conducting an uncertainty analysis for key parameters.
    The EPA convened a second independent peer review panel in January 
2018 to evaluate these updates to the BBDR model. The EPA also 
presented several approaches in the draft Proposed Approaches to Inform 
the Derivation of a Maximum Contaminant Level Goal for Perchlorate in 
Drinking Water (MCLG Approaches Report) to link the thyroid hormone 
changes in a pregnant mother predicted by the BBDR model to 
neurodevelopmental effects using evidence from the epidemiological 
literature (External Peer Review for U.S. EPA, 2018). The 2018 peer 
review identified a variety of strengths and limitations of the 
modeling (to be discussed in more detail later in this notice). The 
peer review panel was largely supportive of the efforts described in 
the MCLG Approaches Report, as evidenced by the following from the peer 
review final report:
    Overall, the panel agreed that the EPA and its collaborators have 
prepared a highly innovative state-of-the-science set of quantitative 
tools to evaluate neurodevelopmental effects that could arise from 
drinking water exposure to perchlorate. While there is always room for 
improvement of the models, with limited additional work to address the 
committee's comments [in the peer-reviewed report], the current models 
are fit-for-purpose to determine an MCLG (External Peer Reviewers for 
U.S. EPA, 2018, p. 2).
    The EPA also presented an alternative, population-based approach 
evaluating the shift in the proportion of the population that would 
fall below a hypothyroxinemic cut point, given exposure to perchlorate 
(Section 7 of the MCLG Approaches Report). This approach does not 
directly connect the BBDR output to a neurodevelopmental endpoint. 
However, for pregnant women in early pregnancy, this shift could be 
related to avoiding an increase in the population of offspring's risk 
of adverse neurodevelopmental impacts. The 2018 peer review identified 
strengths associated with this approach, including
    (1) the central premise, that hypothyroxinemia is associated with 
adverse neurodevelopmental effects is supported by a large number of 
studies, including categorical studies; (2) this approach encompasses a 
variety of adverse neurodevelopmental outcomes, as indicated by these 
studies, rather than focusing on one or a limited number of adverse 
outcomes, as with the two-stage approach; and (3) this approach avoids 
all of the uncertainties associated with determining a quantitative 
relationship between a specific maternal fT4 level and the magnitude an 
adverse neurodevelopmental effect. (External Peer Reviewers for U.S. 
EPA, 2018, p. 7)
    The peer reviewers expressed concern about hypothyroxinemia being a 
precursor effect, rather than an adverse health outcome, which they 
argued may create difficulties in explaining the basis for an MCLG 
based on this approach to some audiences. However, the EPA has used 
precursor effects as the basis for setting regulatory and non-
regulatory limits previously. The peer-review panel also expressed 
concern that a standard definition of hypothyroxinemia has not yet been 
established, as clinicians use varying fT4 thresholds to define their 
own working definition of the condition. This also could lead to 
difficulties communicating the population at risk for developing this 
precursor effect as a result of perchlorate exposure.
    Ultimately, the EPA chose to develop the MCLG using dose-response 
functions from the epidemiological literature to estimate 
neurodevelopmental impacts in the offspring of pregnant women exposed 
to perchlorate. The EPA selected this proposed approach because it is 
consistent with the SDWA's definition of an MCLG to avoid adverse 
health effects and because it is most consistent with the SAB 
recommendations. The EPA is requesting public comment in Section XIV on 
the adequacies and uncertainties of the methodology to derive the MCLG 
including the decision not to pursue this population-based approach for 
setting the MCLG.
    Based on the comments of the peer reviewers, the EPA's final 
analysis informing the derivation of the MCLG and benefits of avoided 
perchlorate exposure is based upon a 2-step

[[Page 30529]]

approach to modeling the neurodevelopmental effects on offspring of 
pregnant women exposed to perchlorate in drinking water (see Figure 1). 
In summary, because of the known mode of action, the lack of 
epidemiological studies particularly in the sensitive populations and 
the direction of the SAB to use a ``data-driven approach [which] 
represents a more rigorous way to address differences in biology and 
exposure between adults and sensitive life stages'' (p. 2, SAB 2013 for 
U.S. EPA), the EPA uses a combination of the BBDR model that simulates 
perchlorate potential impacts on maternal thyroid hormones during 
pregnancy and the epidemiology literature that relates incremental 
changes in maternal thyroid hormones to neurodevelopmental outcomes in 
children. The following sections describe the approach in greater 
detail, highlighting each step in which decisions and assumptions were 
made.
[GRAPHIC] [TIFF OMITTED] TP26JN19.008

    Note: Process figure does not imply the strength of scientific 
evidence.

E. Sensitive Population for Deriving MCLG

    SDWA 1412(b)(4)(A) requires MCLGs to be set at a concentration in 
water ``at which no known or anticipated adverse effects on the health 
of persons occur and which allows an adequate margin of safety.'' SDWA 
1412(b)(3)(C)(V) further requires that the EPA ``consider the effects 
of the contaminant on the general population and on groups within the 
general population such as infants, children, pregnant women, the 
elderly, individuals with a history of serious illness, or other 
subpopulations that are identified as likely to be at greater risk of 
adverse health effects due to exposure to contaminants in drinking 
water than the general population.'' The EPA has interpreted these 
requirements to establish MCLGs that avoid adverse effects within the 
portions of the population that are at greater risk of adverse effects 
from exposure to the contaminant. The EPA is proposing an MCLG that is 
developed to protect the fetuses of a first trimester pregnant mother 
with low-iodine intake levels (i.e., 75 [micro]g/kg/day), low fT4 
levels (i.e., 10th percentile of an fT4 distribution for individuals 
with 75 [micro]g/day iodine intake), and weak TSH feedback strength 
(i.e., TSH feedback is reduced to be approximately 60 percent less 
effective than for the median individual). The choice of this 
population is consistent with discussion by the NRC (2005), and the SAB 
(2013). The EPA believes that by protecting this population, the other 
sensitive populations (i.e., breast- and bottle-fed infants) will also 
be protected. This conclusion is based on the EPA's analysis of 
predictions of the impact of perchlorate on fT4 levels from the 
original EPA BBDR model (which was peer reviewed in January of 2017) 
and an analysis of the literature on the connection between altered 
thyroid hormones in these life stages, and neurodevelopmental outcomes.
    The EPA's original BBDR model demonstrated that perchlorate had 
minimal impact on the thyroid hormone levels for 30-, 60-, and 90-day 
formula-fed infants, even at doses as high as 20 [micro]g/kg/day. 
Specifically, the model demonstrated that ``the range of iodine levels 
in formula is sufficient to almost entirely offset the effects of 
perchlorate exposure at 30, 60 and 90 days'' (USEPA, 2017; p. 73). As a 
result of these findings the EPA concluded that any MCLG based on the 
fetus of the first trimester hypothyroxinemic pregnant mother would 
also protect the formula-fed infant.
    To determine if the same would be true for the breast-fed infant, 
the EPA compared the predicted percent change in fT4 experienced at 
given doses of perchlorate for both the breast-fed infant and the first 
trimester pregnant mother at varying doses of iodine intake \3\ (50 to 
100 [micro]g/day). Assuming 2 or 4 [micro]g/kg/day of perchlorate, the 
first trimester hypothyroxinemic pregnant mother has a greater percent 
change in fT4 compared to the 30 and 60 day breast-fed infant at all 
maternal iodine intake levels evaluated, except for the 30 day breast-
fed infant of a mother consuming only 50 [micro]g/day iodine. However, 
given that the original BBDR model did not have a TSH feedback loop, 
T4, fT4, T3 and fT3 predictions for lactating mothers with less than 75 
[micro]g/day iodine intake were considered highly uncertain because the 
thyroid hormone levels had fallen into the hypothyroid range.
---------------------------------------------------------------------------

    \3\ Given that the current version of the BBDR model contains a 
TSH feedback loop and the infant models previously developed did not 
contain this feedback loop, this comparison is done with the 
feedback loop turned off.
---------------------------------------------------------------------------

    The Agency found that there are reports in the scientific 
literature suggesting that minor perturbations in thyroid hormone 
levels in the first trimester mother may adversely impact her 
offspring's neurodevelopment. Specifically, some studies show that 
children exposed gestationally to maternal hypothyroxinemia (without 
hypothyroidism) have a higher risk of reduced levels of global and 
specific cognitive abilities, as well as increased rates of behavior 
problems including greater dysregulation in early infancy and 
attentional disorders in childhood (Kooistra, Crawford, van Baar, 
Brouwers, & Pop, 2006; Man, Brown, & Serunian, 1991; Pop et al., 2003; 
Pop et al., 1999). Notably these effects are correlated with both 
degree (Henrichs et al., 2010; Pop et al., 1999) and duration (Pop et 
al., 2003) of maternal hypothyroxinemia (SAB for the U.S. EPA, 2013, p. 
10).
    The EPA did not find analogous evidence linking minor perturbations 
in thyroid hormones during infancy to adverse neurodevelopmental 
outcomes in infants. This finding is consistent with conclusions by the 
California Environmental Protection Agency (CalEPA) in their assessment 
of a public health goal for perchlorate (California Environmental 
Protection Agency, 2011, p. 90).
    Specifically, two studies evaluated both the impact of maternal 
hypothyroxinemia and infant fT4 levels on subsequent neurodevelopmental 
outcomes. Costeira et al. (2011) found that children born to mothers 
with low fT4 in the first trimester had increased odds of mild-to-
severe delays in

[[Page 30530]]

psychomotor development compared to children born to mothers with 
normal fT4 levels. However, the authors found that neonatal thyroid 
status (measured on day 3 after birth) did not influence development. 
Additionally, Henrichs et al. (2010) found in their evaluation that 
although maternal hypothyroxinemia was associated with language delay 
and nonverbal cognitive delay, the neonatal thyroid status (thyroid 
hormones measured in cord blood) did not explain the relationship 
between maternal hypothyroxinemia, early pregnancy, and children's 
cognitive impairment.
    The SAB pointed to two lines of evidence supporting their 
suggestion of the infant as a potentially sensitive population to 
perchlorate: Preterm infants that experience transient hypothyroxinemia 
of prematurity (THOP) and infants that experience congenital 
hypothyroidism (SAB for the U.S. EPA, 2013). Thus, sufficient thyroid 
hormone levels in infancy are necessary for the infant brain to develop 
properly. However, the best evidence linking perturbations in thyroid 
hormone levels to disrupted neurodevelopment for infants are in 
individuals with significant thyroid deficiencies manifesting as 
clinical conditions (e.g., THOP and congenital hypothyroidism). It is 
unclear and unknown if minor perturbations in thyroid hormones in 
infants, such as those that could be caused by environmental levels of 
perchlorate, would result in adverse neurodevelopmental outcomes 
similar to those seen in the literature for the offspring of first 
trimester pregnant mothers with hypothyroxinemia. Given the lack of 
evidence demonstrating minor perturbations in infant fT4 levels as 
being associated with neurodevelopmental outcomes, the EPA has 
concluded that it is appropriate to derive the perchlorate MCLG to 
protect the first trimester fetus of a pregnant mother with low-iodine 
intake. The EPA concludes that an MCLG calculated to offer a margin of 
protection against adverse health effects to these fetuses targets the 
most sensitive lifestage and will be protective of other potentially 
sensitive life stages as well.

F. BBDR Model Specification for the Sensitive Population

    The BBDR model used to develop the proposed MCLG has two main 
components:
     A pharmacokinetic model for perchlorate and iodide, which 
describes chemical absorption, distribution, metabolism, and excretion 
of perchlorate and iodide; and
     A pharmacodynamic model, which describes the joint effect 
of varying perchlorate and iodide blood concentrations on thyroidal 
uptake of iodide and subsequent production of thyroid hormones, 
including fT4.
    The pharmacokinetic model component contains a physiological 
description of a human mother and fetus during pregnancy (e.g., organ 
volumes, blood flows) and chemical-specific information (e.g., 
partition coefficients, volume of distribution, rate constants for 
transport, metabolism, and elimination) that enable a prediction of 
perchlorate and iodide internal concentration at the critical target 
(i.e., thyroidal sodium-iodide symporter of the mother) in association 
with a particular exposure scenario (route of exposure, age, dose 
level). This component of the model is similar to many other PBPK 
models. Because perchlorate does not undergo metabolism in vivo 
(Clewell et al., 2007), potential uncertainty from this factor of the 
model is avoided since it does not need to be described.
    The pharmacodynamic component of the model uses this internal 
concentration to simulate how the chemical will act within a known 
mechanism of action to perturb host systems and lead to a toxic effect.
    Thus, the BBDR model estimates serum thyroid hormone levels in the 
mother at specific gestational weeks, given specific levels of iodine 
intake, the TSH feedback loop strength, and perchlorate doses. As noted 
above, to be health protective the EPA chose to model a sensitive 
individual (an adult woman with low iodine through the first trimester 
of pregnancy) to derive an MCLG, thereby protecting both this target 
sensitive population with an adequate margin of safety and those who 
are less sensitive with an even larger margin of safety.
    The BBDR model simulates perchlorate's impact on thyroid hormones 
at each gestational week from conception to week 16. To derive the 
MCLG, the EPA selected outputs for gestational week 13 to correspond 
with the thyroid hormone data reported in Korevaar et al., (2016), 
which is the basis for the Agency's quantitative relationship between 
maternal thyroid hormone levels and neurodevelopmental impacts.
    Individuals with low iodine intake have increased sensitivity to 
perchlorate's impact on thyroid hormone levels because the functional 
iodide reserve of the hypothalamic-pituitary-thyroid (HPT) system is 
limited (Blount et al., 2006, Steinmaus et al., 2007; Leung, Pearce, & 
Braverman, 2010). The EPA selected an iodine intake level of 75 
[micro]g/day to simulate an individual with low-iodine intake. This 
value represents an intake between the 15th and 20th percentile of the 
women of child bearing age population distribution of estimated iodine 
intake from the National Health and Nutrition Examination Survey 
(NHANES). The EPA considered using a lower iodine intake level of 50 
[micro]g/day, which represents approximately the 5th percentile of the 
NHANES distribution. At 50 [micro]g/day of iodine intake, however, the 
BBDR model predicts TSH levels that would be elevated to within the 
clinically hypothyroid range before exposure to any perchlorate \4\ 
(TSH ranges between 4.51 and 5.41 milli-international units per liter 
(mIU/L) at zero dose of perchlorate when evaluating gestational weeks 
12 or 13). In contrast, at 75 [micro]g/day iodine, the BBDR modeled 
concentrations of serum fT4 and TSH are significantly reduced from the 
population median but are still within the euthyroid range. Thus, the 
intake of 75 [micro]g/day is a better approximation of the sensitive 
population--the offspring of pregnant women who have low fT4.
---------------------------------------------------------------------------

    \4\ For the purposes of this analysis, the EPA evaluated the 
American Thyroid Association's (ATA's) 2017 recommendations for 
defining hypothyroidism (Alexander et al., 2017). Specifically the 
ATA recommends ``in the pregnancy setting, maternal hypothyroidism 
is defined as a TSH concentration elevated beyond the upper limit of 
the pregnancy-specific reference range'' (Alexander et al., 2017, p. 
332). ATA goes on to state, in the absence of population- and 
trimester-specific reference ranges defined by a provider's 
institute or laboratory, that the TSH reference ranges should be 
obtained from similar patient populations. From their recommended 
studies with trimester-specific data on a U.S. population, Lambert-
Meserlian et al. (2008) is the largest U.S.-based population with a 
reference range upper bound of 3.37 mIU/L for the first trimester 
(and 3.35 mIU/L for the second trimester). Therefore, these values 
were used to compare to BBDR output TSH values in the first 
trimester (or second trimester in cases of gestational weeks 15 and 
16) to determine the presence of hypothyroidism.
---------------------------------------------------------------------------

    TSH increases in response to decreases in T4 have been captured in 
numerous studies that document the relationship between these hormones 
(Blount et al., 2006; Steinmaus et al., 2013, 2016). The EPA designed 
the BBDR model to depict this feedback regulation by adjusting a set of 
three parameters: The number of sodium-iodide symporter sites, the T4 
synthesis rate, and the T3 synthesis rate. The BBDR model allows for 
variability in the strength of the TSH feedback by varying these 
parameters with a variable called ``pTSH.'' For the MCLG analysis, the 
EPA used a pTSH value of 0.398, which is the ratio of a median value 
for TSH

[[Page 30531]]

from NHANES (non-pregnant women) to the 97.5 percentile value from 
NHANES (non-pregnant women). This value represents an assumption that 
sensitive individuals with high TSH and average fT4 levels exist, and 
this is because the stimulus strength of TSH is proportionally weaker. 
The EPA chose to use a low TSH feedback coefficient to ensure the MCLG 
is protective of the sensitive population.
    Example output from the BBDR model for gestational week 13 and a 
low TSH feedback coefficient is presented in Table III-1.

 Table III-1--Summary of BBDR Model Results for fT4 Levels: Pregnant Women at Gestational Week 13, Assuming Low
                    (75 [micro]g/day) Iodine Intake and with Muted TSH feedback strength \a\
----------------------------------------------------------------------------------------------------------------
                                                 Percentile fT4 (pmol/L) \b\ (% decrease from 0 dose)
  Perchlorate dose  ([mu]g/kg/day)   ---------------------------------------------------------------------------
                                            2.5th               5th                10th               50th
----------------------------------------------------------------------------------------------------------------
0...................................               5.57               6.09               6.70               8.84
1...................................      5.50 (-1.26%)      6.02 (-1.15%)      6.63 (-1.04%)      8.77 (-0.79%)
2...................................      5.43 (-2.45%)      5.96 (-2.24%)      6.56 (-2.04%)      8.71 (-1.54%)
3...................................      5.37 (-3.59%)      5.96 (-3.28%)      6.50 (-2.98%)      8.64 (-2.26%)
4...................................      5.31 (-4.68%)      5.83 (-4.28%)      6.44 (-3.89%)      8.58 (-2.95%)
5...................................      5.25 (-5.73%)      5.77 (-5.23%)      6.38 (-4.76%)      8.52 (-3.60%)
6...................................      5.19 (-6.73%)      5.72 (-6.14%)      6.33 (-5.59%)      8.47 (-4.23%)
7...................................      5.14 (-7.69%)      5.66 (-7.02%)      6.27 (-6.39%)      8.41 (-4.84%)
----------------------------------------------------------------------------------------------------------------
\a\ pTSH = 0.398; see USEPA, (2018b) for additional information on pTSH.
\b\ The 50th percentile is direct output from the BBDR model, and additional percentiles are estimated by
  assuming a normal distribution with a SD of 1.67. All of the examined study data demonstrated a positive skew,
  and overall the lognormal function demonstrated a better fit than a normal distribution. Despite this, the
  available study data only accounted for variation due to gestation week and did not account for variation in
  perchlorate and iodine intake in the measured populations. Because perchlorate and iodine can affect fT4
  levels, and this relationship produced the estimated median BBDR values, the distribution around values
  estimated by the model from perchlorate and iodine intake should account for a small reduction in variation
  due to the effect of perchlorate and iodine intake. Additionally, as iodine has a demonstrated lognormal
  distribution with strong right skew (e.g., Blount et al., 2007) and is predicted to have a stronger effect on
  fT4 than perchlorate (see Section 3). The EPA assumed the error around predicted fT4 would likely be closer to
  normal than lognormal after accounting for perchlorate and iodine intake.

    When modeling changes in fT4, the baseline level of fT4 affects the 
magnitude of changes seen as a result of perchlorate exposure. 
Therefore, to predict the impact of perchlorate exposure on the 
population distribution of fT4 for the identified sensitive population, 
the EPA estimated a distribution for fT4 plasma concentrations around 
the median modeled values based on fT4 data from studies that were used 
to calibrate the BBDR model (C. Li et al., 2014; M[auml]nnist[ouml] et 
al., 2011; Zhang et al., 2016). The EPA assumed the variation around 
predicted fT4 concentrations for women with low fT4 of childbearing age 
would likely be close to normal after accounting for perchlorate and 
iodine intake, and thus estimated a combined standard deviation (SD) 
using the distributional information from each of the studies (C. Li et 
al., 2014; M[auml]nnist[ouml] et al., 2011; Zhang et al., 2016). The 
EPA then used the estimated combined SD to predict a distribution of 
fT4 around the median fT4 estimated by the BBDR model. To protect the 
most sensitive population from adverse effects, the EPA chose to use 
the 10th percentile from this distribution of baseline fT4 to conduct 
its analyses to account for variability in thyroid hormones in the 
population.\5\
---------------------------------------------------------------------------

    \5\ For a discussion on the details of the BBDR model, including 
uncertainties associated with the model the reader is directed to 
section 3.5 of the MCLG Approaches Report.
---------------------------------------------------------------------------

G. Epidemiological Literature

    The SAB recommended that the EPA integrate BBDR model results with 
data on neurodevelopmental outcomes from epidemiological studies. There 
is substantial epidemiological evidence that early pregnancy 
hypothyroxinemia is a risk factor for a variety of adverse 
neurodevelopmental outcomes, including those related to both cognition 
and behavior (Costeira et al., 2011; Finken, van Eijsden, Loomans, 
Vrijkotte, & Rotteveel, 2013; Ghassabian et al., 2014; Gyllenberg et 
al., 2016; Henrichs et al., 2010; J[uacute]lvez et al., 2013; Kooistra, 
Crawford, van Baar, Brouwers, & Pop, 2006; Korevaar et al., 2016; Y. Li 
et al., 2010; Oostenbroek et al., 2017; P[auml]kkil[auml] et al., 2015; 
Pop et al., 2003, 1999; Roman et al., 2013; van Mil et al., 2012). 
These individual studies showing that maternal hypothyroxinemia is 
associated with offspring neurodevelopment are also supported by three 
meta-analyses (including one full systematic review), all of which 
conclude maternal hypothyroxinemia is associated with increased risk of 
cognitive delay, intellectual impairment, or lower scores on 
performance tests when considering the entire body of evidence on this 
topic (Fan & Wu, 2016; Thompson et al., 2018; Wang et al., 2016). 
Additionally, the American Thyroid Association concludes that 
``overall, available evidence appears to show an association between 
hypothyroxinemia and cognitive development of the offspring'' 
(Alexander et al., 2017, p. 337).
    The EPA did not conduct a full systematic review and weight of 
evidence evaluation between maternal thyroid hormones and 
neurodevelopmental outcomes given: (1) The body of scientific 
literature regarding this association, and (2) the SAB recommendation 
that the EPA ``consider available data on potential adverse health 
effects (neurodevelopmental outcomes) due to thyroid hormone level 
perturbations regardless of the cause of those perturbations'' (p. 25). 
Instead, the EPA conducted a ``methodologic approach to reviewing the 
literature'' to evaluate the body of literature on this topic. This 
approach assisted in extrapolating the relationship modeled by the BBDR 
model to neurodevelopmental outcomes by concentrating on studies that 
allowed for evaluation of incremental changes in fT4 as they relate to 
incremental changes in neurodevelopmental outcomes. More specifically, 
the EPA only used studies that had sufficient data to show a 
quantitative relationship between maternal fT4 and a neurodevelopmental 
outcome. The EPA acknowledges that by not giving any weight to the 
studies that did not show

[[Page 30532]]

a quantitative relationship between fT4 and neurodevelopmental 
outcomes, the Agency may be overestimating the dose of perchlorate that 
may be associated with adverse neurodevelopmental outcomes. This is a 
health protective decision that adds to the margin of safety.
    Ultimately, the EPA developed a dose-response function that 
estimates incremental changes in a neurodevelopmental endpoint based on 
a given change in thyroid hormone concentration (fT4), which could be 
linked to a given dose of perchlorate using the BBDR model.
    The specifics of this ``methodologic approach to reviewing the 
literature'' follow. First, the EPA identified and screened the 
available 71 epidemiological studies, which potentially pertained to 
altered maternal thyroid hormone levels and offspring neurodevelopment 
to identify candidates based on the following criteria:
     Compatible with the sensitive life stages identified by 
the NRC and SAB;
     Continuous measure of thyroid hormone values (versus 
categorical values);
     Low risk of bias based on analysis using the National 
Toxicology Program's Office of Health Assessment and Translation (OHAT) 
Risk of Bias (ROB) tool score; and
     Access to underlying data.
    Second, using these screening steps, the EPA categorized all 71 
studies into three groups. One group consisted of studies that were not 
compatible \6\ with extending the BBDR model (40 studies). Another 
group consisted of papers that were relevant to the pertinent life 
stages but did not have data from which a dose-response analysis could 
be conducted (15 studies). This includes studies that compared 
differences between groups, for example studies of offspring of mothers 
with hypothyroxinemia versus offspring of mothers without 
hypothyroxinemia. Consequently, these studies may have provided insight 
into the maternal thyroid hormone and offspring neurodevelopment 
relationship but did not have enough information to develop a 
continuous dose-response function. The last group of papers had data 
that may inform a dose-response function (16 studies). This last group 
of papers included publications that may have had categorical analyses 
but also presented data that assessed fT4 as a continuous variable and 
the outcome of interest. In most instances, the continuous fT4 variable 
encompassed the full range for fT4 and not just the hypothyroxinemic 
range. After excluding one paper due to a high risk of bias (Kastakina 
et al., 2006) 15 papers remained that potentially had dose-response 
data between a continuous measure of fT4 and various neurodevelopmental 
outcomes describing cognition, behavior and other outcomes. The EPA 
notes that by selecting the papers that potentially had dose response 
data the Agency is deviating from the systematic weight of evidence 
review approach to identify those studies that the SAB recommended we 
examine to derive the MCLG.
---------------------------------------------------------------------------

    \6\ For example, if the study evaluated the impact of only 
neonatal thyroid hormones (i.e., at a potentially sensitive life 
stage), it cannot be used because the BBDR model is specific to 
early pregnancy. Further, if the study evaluates a population with 
an existing disease (i.e., hypothyroidism) that may have a different 
response to perchlorate compared to the euthyroid population, it was 
not considered compatible with BBDR model results. Additionally, if 
the study does not include information on T4 or fT4, it does not 
assist in understanding the implications of the BBDR modeling 
results. Another reason for exclusion at this stage include that the 
study does not have a population with an exposure window (i.e., when 
the thyroid hormone measurements are taken) that overlaps with the 
outputs for the BBDR model. Specifically, the study should evaluate 
thyroid hormone levels in pregnant mothers between conception and 
gestational week 16. The neurodevelopmental outcomes could be 
measured at any life stage.
---------------------------------------------------------------------------

    Third, from these 15 papers five were selected for dose response 
assessment--four related to cognition (Finken et al., 2013; Korevaar et 
al., 2016; Pop et al., 2003, 1999) and one related to behavior 
(Endendijk, Wijnen, Pop, & van Baar, 2017). The other ten papers were 
excluded for a variety of reasons including updated analyses being 
presented in a different paper for which dose-response analysis was 
being conducted, lack of all the data needed to complete a dose-
response assessment (e.g., dose-response results were presented as 
``per standard deviation of fT4'' but the standard deviation needed to 
fully interpret the results for a continuous function was not presented 
in the paper, statistical methods presented in the paper were 
insufficient to allow for the derivation of a concentration response 
function), or a lack of a relationship between maternal fT4 as a 
continuous variable and the outcome of interest evaluated in the paper. 
For example, Noten et al., (2015) found a relationship between maternal 
hypothyroxinemia and offspring arithmetic test performance. However, 
maternal fT4 as a continuous variable across the entire fT4 range was 
not associated with arithmetic test performance. Given this null 
finding, as well as the lack of published literature evaluating 
maternal fT4 as a continuous variable and arithmetic test performance, 
it would be difficult for the Agency to justify setting an MCLG based 
on changes in this endpoint.
    As laid out for the peer reviewers, for each study that met the 
criteria identified above for dose-response modeling, a relationship 
between maternal thyroid hormone levels (specifically fT4) and 
offspring neurodevelopment was derived (see USEPA, 2018b). These 
relationships were either presented in the original published paper or 
derived by the EPA through either the digitization of figures or 
through re-analysis of data provided by the study authors. The EPA used 
the upper effect estimate (the upper bound of the 95th percent 
confidence interval) from each study to assure consideration of the 
populations likely to be at greater risk from the dose of perchlorate 
associated with a given change in fT4.
    Table III-2 provides a summary of the changes in fT4 predicted to 
produce a 1, 2, and 3 percent decrease in any given neurodevelopmental 
effect and corresponding perchlorate doses. The choice of 1, 2, and 3% 
is based on the analyses for IQ, Mental Development Index (MDI), and 
Psychomotor Development Index (PDI). Specifically, a 1%, 2%, or 3% 
change from the standardized mean for each test (i.e., 100 points) 
equates to a 1, 2, or 3 point change, respectively. The analyses for 
anxiety/depression score and SD of reaction time are based on a 1%, 2%, 
or 3% change from the study mean of each measure, which for anxiety/
depression is 0.01, 0.02, or 0.03 points, respectively, and for 
reaction time is 2.7, 5.4, and 8.1 milliseconds (study mean SD of 
reaction time = 270 ms), respectively (Endendijk et al., 2017; Finken 
et al., 2013).
    These results provide the potential impacts of perchlorate on 
maternal fT4 (as predicted by the BBDR model) and subsequent 
neurodevelopmental impacts (derived from the epidemiologic literature 
\7\).
---------------------------------------------------------------------------

    \7\ For a more complete description of all the studies evaluated 
the reader is directed to Sections 5 and 6 of the MCLG Approaches 
Report. For a discussion on the uncertainties related to the 
approach the reader is directed specifically to section 6.5.

---------------------------------------------------------------------------

[[Page 30533]]

[GRAPHIC] [TIFF OMITTED] TP26JN19.009

[[Page 30534]]

[GRAPHIC] [TIFF OMITTED] TP26JN19.010

H. Identifying a Point of Departure for Developing the MCLG

    From the seven analyses presented in Table III-2 above, the EPA 
chose to use its independent analysis of the Korevaar et al., (2016) 
data (comprising of 3,600 useable mother/child data pairs) as the basis 
for calculating the point of departure (POD) for the MCLG. There are 
three reasons for this selection: (1) There is sufficient quantitative 
data to derive a health impact function for the sensitive population of 
interest; (2) the analysis adjusts for an appropriate set of 
confounders, and (3) the neurodevelopmental endpoint--intelligence 
quotient (IQ)--is more straightforward to interpret because there is 
more national and cross-national data available (more on the selection 
of this endpoint below). The other studies presented in Table III-2 do 
not provide one or more of these features (USEPA, 2018b).
    The five identified papers evaluated a variety of endpoints with 
Korevaar et al., (2016) evaluating IQ, Pop, Kuijpens, et al., (1999) 
and Pop, Brouwers, et al., (2003) using the Bayley Scale to evaluate 
PDI and MDI, Finken, van Eijsden, Loomans, Vrijkotte, and Rotteveel 
(2013) evaluating the SD of reaction time, and Endendijk, Wijnen, Pop, 
and van Baar (2017) evaluating anxiety/depression scores using the 
Child Behavioral Check List (CBCL). The SD of reaction time from Finken 
et al., (2013) was not well-received by the peer reviewers (External 
Peer Review for U.S. EPA, 2018) because it is difficult to ascertain 
the true implications of a change in the SD of reaction time. The 
Endendijk et al., (2017) study was identified after the peer review so 
no feedback was given on the appropriateness of the endpoint; however, 
the anxiety/depression raw score is not an intuitively interpretable 
endpoint. Further, neither the Endendijk et al., (2017) nor the Finken 
et al., (2013) analyses had functions for the sensitive life stage 
(i.e., their analyses were based on the full range of fT4 levels and 
did not concentrate on the impacts of low-end fT4 levels). For these 
reasons, the Endendijk et al., (2017) and Finken et al., (2013) papers 
were not selected for further evaluation.
    The Korevaar et al., (2016) original and independent analyses are 
preferable compared to the Pop, Kuijpens, et al., (1999) and Pop, 
Brouwers, et al., (2003) studies because neither function derived from 
the Pop et al., studies was adjusted for confounders. Additionally, 
both Pop et al., papers have an N <50 compared to the Korevaar et al., 
analyses, which have an N of greater than 3,600.\8\
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    \8\ The original Korevaar et al. (2016) analysis included 3,839 
mother/child pairs. The EPA reanalysis of the Korevaar et al. (2016) 
data had a slightly lower N of 3,609 due to the exclusion of 
subjects with imputed values for maternal fT4.
---------------------------------------------------------------------------

    Although the original Korevaar et al., (2016) analysis was the most 
rigorous analysis available in the literature to date, the Korevaar et 
al., (2016) EPA reanalysis was chosen over the original analysis 
because it included modifications to the analysis at the suggestion of 
the peer review panel. The

[[Page 30535]]

revised analysis controls for a more parsimonious set of confounders 
(e.g., previously included variables such as infant gender, maternal 
parity, birthweight, mother's body mass index (BMI), and gestational 
age at blood draw that are not related to both the exposure and the 
outcome were excluded), thus decreasing the chances of overfitting the 
estimation of the association between maternal fT4 and child IQ. The 
EPA was prompted to revisit the original Korevaar et al., (2016) model 
because of the feedback received during the peer review of the MCLG 
Approaches Report. Specifically, a member of the peer-review panel 
expressed the following suggestion:
    Korevaar et al., [2016] controlled for instrumental variables (e.g. 
gestational week at fT4 measurement) as well as variables that are 
consequences of altered fT4 (e.g. maternal BMI), which may have biased 
estimates. This study also assumed a log-linear relation between fT4 
and the outcome but it is unclear whether the data fit this functional 
form better than a linear form. Reanalysis of the data performed by EPA 
should not include the variables noted above, which may have driven 
measures of association towards the null, and should investigate the 
most appropriate functional form to inform decisions about 
transformation of fT4 values (External Peer Reviewers for U.S. EPA, 
2018, pp. 61-62).
    The EPA responded to this suggestion by developing a causal model 
for the effect of maternal fT4 on child IQ to identify the minimum set 
of confounding variables, testing the proper functional form of the 
relationship between maternal fT4 and child IQ in the Korevaar et al., 
(2016) data, and making decisions about data quality and influential 
data points in the analysis. That is, the EPA determined that there 
were values of the independent variable of interest, fT4, in the 
original analysis that were imputed using multiple imputations. This 
could have impacted the effect estimate of the independent variable of 
interest with data that were not directly measured. The EPA reanalysis 
excludes these non-measured values. Subsequently, the EPA selected the 
Korevaar et al., (2016) reanalysis as the most appropriate function 
from which to assess the relationship between fT4 and IQ.\9\
---------------------------------------------------------------------------

    \9\ A more complete description of the EPA independent analysis 
of the Korevaar et al. (2016) data can be found in Section 6.3.2 of 
the MCLG Approaches Report.
---------------------------------------------------------------------------

    As indicated above, the EPA has utilized a health protective 
approach to this analysis consistent with the SDWA definition of the 
MCLG. The peer reviewers commented that this approach was fit-for-
purpose. In particular, the Agency assumed it could estimate risk 
reductions based on evidence of a quantifiable relationship between 
thyroid hormone changes and neurodevelopmental outcomes. The existence 
of a quantifiable relationship between thyroid hormone changes and 
neurodevelopmental outcomes has strong support from the literature on 
the subject; however, not every study identified an association between 
maternal fT4 and the specified outcome of interest, and the state of 
the science on this relationship is constantly evolving. As explained 
earlier, the results of the EPA's dose-response literature review 
identified 31 studies that evaluated the association between maternal 
thyroid hormone levels and offspring neurodevelopment, with 
neurodevelopment defined using a variety of endpoints related to 
cognition, behavior, and other outcomes such as autism. Among these 
studies, only 16 were deemed to potentially possess information that 
could inform a dose-response relationship. The other 15 only presented 
data on categorical analyses assessing the impact of maternal 
hypothyroxinemia on the neurodevelopmental outcomes of interest. 
Therefore, because the data presented was only a comparison of two 
groups, there was not information that could be used to inform a dose-
response function.
    Of the 16 studies that potentially had data to inform a dose-
response function, 10 evaluated cognition using a variety of tests 
including various IQ tests (three papers; Ghassabian et al., 2014; 
Korevaar et al., 2016; Moleti et al., 2016), Bayley Scales of Infant 
Development (two papers; Pop et al., 1999; Pop et al., 2003), and other 
validated tests associated with child cognition such as expressive 
language delay or test performance (five papers; Finken et al., 2013; 
Henrichs et al., 2010; Kastakina et al., 2006; Noten et al., 2015; Oken 
et al., 2009). Six of these papers found a statistically significant 
relationship between maternal fT4, as a continuous variable, and 
offspring cognitive outcome (Korevaar et al., 2016; Pop et al., 1999; 
Pop et al., 2003; Finken et al., 2013; Henrichs et al., 2010, Kastakina 
et al., 2006). However, there were studies where maternal fT4 as a 
continuous variable was not significantly associated with the outcome 
of interest. For example, in Ghassabian et al., (2014) the authors 
found maternal hypothyroxinemia to be associated with an average of a 
4.3-point reduction in IQ in their offspring compared to offspring of 
non-hypothyroxinemic mothers. Nevertheless, when assessing the 
relationship between the continuous measure of maternal fT4 as a 
continuous variable (across the entire range of fT4 levels) and child 
IQ, the authors did not find a significant relationship. Additionally, 
Moleti et al., (2016) found the relationship between maternal fT4 and 
child IQ to be consistently inversely associated with IQ scores, but 
their assessment failed to reach statistical significance. This study 
included fewer than 60 study participants and was considered by the 
authors to be a pilot assessment.
    In addition to the cognitive effects assessed and modeled, the EPA 
identified four papers that assessed maternal fT4 status and behavioral 
outcomes (Endendijk et al., 2017; Ghassabian et al., 2011; Modesto et 
al., 2015; Oostenbroek et al., 2017), one paper that assessed maternal 
fT4 status and autism (Roman et al., 2013) and one paper that evaluated 
odds of a schizophrenia diagnosis as associated with maternal thyroid 
hormone status (Gyllenberg et al., 2016). From this group of papers, 
the majority of papers found an association either between maternal 
hypothyroxinemia or maternal fT4 as a continuous variable and the 
outcome of interest (Endendijk et al., 2017; Modesto et al., 2015; 
Oostenbroek et al., 2017; Roman et al., 2013; Gyllenberg et al., 2016). 
However, this was not always the case as exemplified by Ghassabian et 
al., (2011) and Gyllenberg et al., (2016). Although Endendijk et al., 
(2017) found maternal fT4 to have a significant adverse impact on 
anxiety/depression using the Child Behavioral Check List (CBCL), 
Ghassabian et al., (2011) did not find any association between maternal 
thyroid hormone status and offspring score on various components of the 
CBCL. Additionally, Gyllenberg et al., (2016) found maternal 
hypothyroxinemia during early to mid-gestation was associated with 70% 
increased odds of schizophrenia diagnosis in offspring of 
hypothyroxinemic mothers compared to the offspring of non-
hypothyroxinemic mothers. Gyllenberg et al., (2016) also found an 
association with odds of schizophrenia diagnosis using conditional 
logistic regression when assessing fT4 as a continuous variable across 
the entire fT4 range (i.e., not just the hypothyroxinemic range); 
however, this relationship was attenuated after controlling for 
smoking.
    Not every paper the EPA located in its literature review found a 
statistically

[[Page 30536]]

significant association between maternal fT4 as a continuous variable 
(i.e., the initially identified 16 studies identified as potentially 
useful to inform a dose-response function) and the neurodevelopmental 
outcome of interest. However, many studies located in the EPA 
literature review, several meta-analyses (Fan & Wu, 2016; Thompson et 
al., 2018 and Wang et al., 2016), the American Thyroid Association 
(Alexander et al., 2017) and the U.S. EPA's SAB (2013) have concluded 
there is a relationship between maternal hypothyroxinemia and various 
neurodevelopmental outcomes. The relationship between maternal fT4 
levels and neurodevelopmental outcomes appears strongest in the 
hypothyroxinemic range, and when looking at the entire range of fT4 as 
a continuous variable (as opposed to a categorical cut off), the 
significant relationship between the two variables may dissipate. 
Therefore, the EPA has concentrated on the neurodevelopmental impacts 
of changes in fT4 in the lower range of fT4 from the Korevaar et al., 
(2016) data. In an attempt to minimize uncertainty, the EPA reanalyzed 
the data collected by Korevaar et al., (2016) using a spline function 
that estimates a coefficient specifically for the low range of the fT4 
data.
    There are a variety of neurodevelopmental endpoints used to examine 
behavior and cognition in children (e.g., intelligence quotient (IQ), 
motor skills, vocabulary and language development, stimulus 
responsiveness, etc.). The EPA selected IQ decrements because this was 
the endpoint evaluated in the Korevaar et al., (2016) study. The EPA 
determined that the Korevaar study was the most rigorous analysis that 
examined the relationship between decreased thyroid hormones and 
neurodevelopmental effects. As such, in the derivation of the MCLG, IQ 
is a surrogate for a suite of potential neurodevelopmental effects that 
might occur to the offspring of hypothyroxinemic and iodine deficient 
mothers.
    There are several different tests that are widely used to measure 
IQ in children, including the Stanford-Binet and the Wechsler 
Intelligence Scale for Children (WISC) (Sternberg et al., 2001). Each 
of these tests is intended to assess a child's global functioning and 
uses a numerical IQ point scale (Beres et al., 2000). IQ scores are 
standardized by age and sex group with a mean score of 100 points and a 
standard deviation of 15 (Beres et al., 2000). Although the specific 
tasks differ by test, all IQ tests contain a number of tasks to assess 
diverse skills (Sternberg et al., 2001). For example, the WISC test 
evaluates full-scale IQ using a combination of verbal and performance 
scales (verbal IQ and performance IQ may also be assessed separately) 
(Beres et al., 2000). The verbal scale includes tasks such as 
arithmetic, vocabulary, and comprehension, while the performance scale 
includes tasks such as picture completion, block design, and object 
assembly (Beres et al., 2000). The WISC was standardized using a sample 
of 2200 U.S. children aged 6 to 16 years old (Seashore et al., 1950). 
It has been well validated and has demonstrated high reliability, with 
a reliability coefficient of 0.96 observed across age groups (Beres et 
al., 2000).
    Associations have been found between IQ scores and both educational 
achievement and attainment, though observed correlations vary widely. 
In a review of the literature, Sternberg et al., (2001) suggest that IQ 
scores explain approximately 25% of the variance in academic 
achievement. Evidence also suggests that IQ is linked to career 
outcomes and job performance, with observed correlations ranging from 
approximately 0.2 to 0.6 (Sternberg et al., 2001). Research suggests 
that children's rearing environment, including parental education, 
while growing up may increase IQ scores in adolescence by several 
points (e.g., Kendler et al., 2015).
    IQ scores have been used to help diagnose disorders such as 
intellectual disability and to identify children for placement into 
specialized learning programs (Beres et al., 2000). For example, in the 
Diagnostic and Statistical Manual of Mental Disorders, fifth edition 
(DSM-V) IQ scores are used in an individual's comprehensive assessment 
to determine intellectual disability, which pairs standardized testing 
of intelligence with a clinical assessment of adaptive functioning. 
Intellectual disability is considered for individuals with an IQ score 
of about 70 or below (American Psychiatric Association, 2013).
    The EPA uses a variety of science policy approaches to select 
points of departure for developing regulatory values. For instance, in 
noncancer risk assessment the EPA often uses a percentage change in 
value. When assessing toxicological data, a 10 percent extra risk (for 
discrete data), or a 1 standard deviation (i.e., 15 IQ points) change 
from the mean (for continuous data) is often used (USEPA, 2012). A 
smaller response to inform a POD has been applied when using 
epidemiological literature because there is an inherently more direct 
relationship between the study results and the exposure context and 
health endpoint. Given the difficulty in identifying a response below 
which no adverse impact occurs when considering a continuous outcome in 
the human population, the EPA looked to its Benchmark Dose Guidance 
(2012) for insight regarding a starting point. Specifically, ``[a] BMR 
of 1% has typically been used for quantal human data from epidemiology 
studies'' (p. 21, USEPA, 2012).
    For the specific context of setting an MCLG for perchlorate, the 
EPA made a policy decision to evaluate the level of perchlorate in 
water associated with a 1 percent decrease, a 2 percent decrease, and a 
3 percent decrease in the mean population IQ (i.e., 1, 2 and 3 IQ 
points). The EPA selected IQ as a surrogate for neurodevelopmental 
effects based upon its evaluation of the epidemiologic literature 
describe above. The need to utilize the best available peer reviewed 
data to inform scientific assumptions and policy choices to meet the 
statutory requirements associated with developing an MCLG under the 
SDWA highlights the challenges associated with regulating chemicals for 
which potential effects are indirect, and scientific data do not 
address all uncertainties. The Agency must make a policy decision 
informed by science, consistent with statutory requirements even in 
situations where the data do not provide clear choices. To develop the 
proposed MCLG for perchlorate, the EPA made a policy decision to use a 
2 IQ point decrement in the population-distribution of IQ for the 
sensitive population. By selecting this approach, the EPA is not 
establishing a precedent for future Agency actions on other 
contaminants for which there is concern about potential thyroid 
effects, either under the SDWA or other statutory frameworks.
    Applying these response rates to the results from the reanalysis of 
Korevaar et al., (2016), results in a POD dose of 3.1 [micro]g/kg/day 
for a 1 point decrease in the sensitive population's IQ, a POD dose of 
6.7 [micro]g/kg/day for a 2 point decrease in the sensitive 
population's IQ, and a POD dose of 10.8 [micro]g/kg/day for a 3 point 
decrease in the sensitive population's IQ. These PODs associated with a 
1, 2, or 3 point decrease from the standardized mean IQ are calculated 
for the most sensitive population. Specifically, the POD is designed to 
provide an adequate margin of safety for the fetuses of mothers with 
fT4 at the 10th percentile of a population with iodine intake of 75 
[micro]g/day and a TSH feedback loop that is less than 60% as effective 
as individuals with median

[[Page 30537]]

TSH feedback loop efficacy. That is, the analysis is designed to 
protect the population of fetuses of mothers with suboptimal thyroid 
functioning. For these reasons, and for the methodological reasons 
described previously, the EPA believes that the selection of these 
parameters and this point of departure assures no known or anticipated 
adverse effects on the health of the most sensitive population and 
allows for an adequate margin of safety.

I. Translate PODs to RfDs

    When deriving an RfD the EPA evaluates whether to apply 
uncertainty/variability factors to account for heterogeneity of effect 
in the target population and data gaps (USEPA, 2002). As presented in A 
Review of the RfD & RfC Processes (USEPA, 2002) the EPA considers the 
following uncertainty factors: Inter-individual variability, 
interspecies uncertainty, extrapolating from subchronic to chronic 
exposure, extrapolating from a lowest-observed adverse effect level 
(LOAEL) rather than from a no-observed-adverse-effect-level (NOAEL), 
and an incomplete database. The factors are intended to account for: 
(1) Variation in susceptibility among the members of the human 
population (i.e., inter-individual or intraspecies variability); (2) 
uncertainty in extrapolating animal data to humans (i.e., interspecies 
uncertainty); (3) uncertainty in extrapolating from data obtained in a 
study with less-than-lifetime exposure (i.e., extrapolating from 
subchronic to chronic exposure); (4) uncertainty in extrapolating from 
a LOAEL rather than from a NOAEL; and (5) uncertainty associated with 
extrapolation when the database is incomplete. (U.S. EPA, 2011b) The 
EPA has considered each of these factors in deriving an RfD to inform 
an MCLG for perchlorate.
    The EPA considered variation and uncertainty in the relationship 
between exposure and response among the members of the human population 
(i.e., uncertainty factor (UF) for within-human variability/inter-
individual variability, UFH). For this analysis a UF of 3 is 
used. The approach taken to derive the RfD attempts to address 
variability between the general population and the sensitive 
population. Specifically, the EPA was able to modify the strength of 
the TSH feedback loop and iodine intake levels in the BBDR model and 
concentrate on the dose-response relationship between lower level (as 
opposed to median level) fT4 and neurodevelopmental outcomes. However, 
there is still uncertainty in the relationship between perchlorate 
exposure and subsequent neurodevelopmental outcomes.\10\ There are very 
few toxicokinetic calibration data available for the perchlorate to 
thyroid hormone relationship described in the BBDR model. On the 
toxicodynamic side of the BBDR model, aspects such as competitive 
inhibition at the NIS, depletion of iodide stores under different 
iodine intake levels and physiological states, and the ability of the 
TSH feedback loop to compensate for perturbations in thyroid function 
each have their own uncertain features. There are also uncertainties 
linking maternal fT4 levels to offspring IQ. These uncertainties 
include the population for which dose-response information is available 
(i.e., no study is U.S. based), a lack of study information on the 
iodine intake status for the population for which the dose-response 
information is available, uncertainties around the methods used to 
assess maternal fT4 measurement during pregnancy, and uncertainties 
related to the true distribution of fT4 for a given iodine intake.
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    \10\ For a more complete discussion on the uncertainties in the 
analysis the reader is directed to Sections 3.5 and 6.5 of the MCLG 
Approaches Report.
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    Further, as discussed in section III.C. of this preamble the EPA 
believes that protecting the fetus of a hypothyroxinemic woman will 
protect other identified sensitive life stages. However, there is some 
uncertainty due to the lack of information linking incremental changes 
in infant thyroid hormone levels to adverse neuorodevelopmental 
outcomes. In addition, this analysis is assuming that protecting a 
first trimester fetus from alterations in maternal fT4 will protect the 
fetus throughout pregnancy. This is based on epidemiologic evidence 
that shows the relationship between first trimester maternal fT4 and 
neurodevelopmental outcomes. This is potentially because before mid-
gestation, the mother is the only source of thyroid hormone for the 
fetus (Morreale de Escobar et al., 2004). Therefore, when evaluating 
maternal fT4 as associated with neurodevelopmental outcomes it is 
critical to understand the first-trimester levels. Later in gestation, 
when the fetal thyroid begins secreting thyroid hormones, maternal fT4 
may no longer be a good surrogate for the thyroid hormone levels 
available to the fetus. Given that the fetal thyroid has had little 
time to develop, its iodine storage is much less than that of an adult, 
hence there may be more sensitivity to short-term fluctuations in 
iodine availability and uptake that may have little impact on maternal 
levels. Therefore, there is some uncertainty about the impact 
perchlorate may have on the fetal thyroid gland, and subsequent 
neurodevelopmental impacts, in later trimesters of pregnancy. The 
immature fetal HPT axis has very limited capacity to increase output of 
thyroid hormones (Savin, Cveji[cacute], Nedi[cacute], & 
Radosavljevi[cacute], 2003; van Den Hove, Beckers, Devlieger, De 
Zegher, & De Nayer, 1999), so the fetal HPT may not be able to adjust 
output in the face of reduced maternal fT4 supply and perchlorate 
exposure. Therefore, as described above, the EPA selected an 
intraspecies UF of 3 to account for the uncertainties in modeling the 
impacts of perchlorate ingestion on the thyroid hormone levels for 
pregnant mothers with low iodide intake, and the uncertainties in 
predicting the neurodevelopmental effects of these thyroid hormone 
changes on their children.
    The EPA considered but did not derive a Data-Dependent 
Extrapolation Factor (DDEF) for this analysis. As described above, the 
UFs are applied based on the uncertainties in the perchlorate to 
thyroid hormone and thyroid hormone to neurodevelopment 
relationship.\11\ As noted above, the Agency has opted to apply a UF of 
3 to the POD, which adds an adequate margin of safety to the MCLG 
derivation. Section 4.4.5.3 (p. 4-42) of A Review of the RfD & RfC 
Processes recommends reducing the intraspecies UF from a default of 10 
``only if data are sufficiently representative of the exposure/dose-
response data for the most susceptible subpopulation(s)'' (p. xviii, 
USEPA, 2002). The EPA selected a UF of 3 instead of the full 10 because 
the modeled groups within the population that are identified as likely 
to be at greater risk to perchlorate in drinking water (i.e., the fetus 
of the iodide deficient pregnant mother) and has selected model 
parameters to account for the most sensitive individuals in that group 
(i.e., muted TSH feedback, low fT4 values, low-iodine intake).
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    \11\ As explained in U.S. EPA, 2014 ``UFs incorporate both 
extrapolation components that address variability (heterogeneity 
between species or within a population) and components that address 
uncertainty (i.e., lack of knowledge) . . . whereas DDEFs focus on 
variability'' (p. 7, US EPA, 2014).
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    Below we list the other uncertainty factors added and the 
justification.
     Uncertainty in extrapolating animal data to humans (i.e., 
interspecies uncertainty) (uncertainty factor, animal-to-human, 
UFA). For this analysis an UF of 1 is used because this 
factor is not applicable since animal studies were

[[Page 30538]]

not used to develop the BBDR model nor were they used to relate 
alterations in maternal fT4 to IQ.
     Uncertainty in extrapolating data obtained in a study with 
less-than-lifetime exposure to lifetime exposure (i.e., extrapolating 
from subchronic to chronic exposure, UFS). An uncertainty 
factor of 1 is used. Extrapolating from subchronic to chronic exposures 
did not occur as the BBDR model was designed to assess long-term 
steady-state conditions in the non-pregnant woman and week-to-week 
variation in pregnancy, rather than short-term (hour-to-hour or day-to-
day) fluctuations.
     Uncertainty in extrapolating from a LOAEL rather than from 
a NOAEL (uncertainty factor, LOAEL-to-NOAEL, UFL). A more 
sophisticated BBDR modeling approach, coupled with extrapolation to 
changes in IQ using linear regression, was used to determine a POD that 
would not be expected to represent an adverse effect. Subsequently an 
uncertainty factor of 1 is used. LOAELs and NOAELs were not identified 
or used in this approach.
     Uncertainty factor for database deficiency to address the 
potential for deriving an inadequately protective RfD in the instance 
where the available database provides an incomplete characterization of 
the chemical's toxicity (database deficiency, UFD; USEPA, 
2002). An uncertainty factor of 1 is used as ``[t]he mode of action of 
perchlorate toxicity is well understood'' (SAB for the U.S. EPA, 2013, 
p. 2).
     The product of all the uncertainty factors 
(UFH) is 3 (3 x 1 x 1 x 1 x 1).
    Below we generate RfD's for each of the points of departure.
    Using the POD of 6.7 [mu]g/kg/day based on a 2 percent decrease in 
the population standardized mean IQ from the EPA's independent analysis 
of the Korevaar et al., (2016) data, the EPA can derive a RfD by 
incorporating the UFH, which results in the following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.011

    Using an alternative POD of 3.1 [mu]g/kg/day based on a 1 percent 
decrease in the population standardized mean IQ from the EPA's 
independent analysis of the Korevaar et al., (2016) data, the EPA can 
derive an RfD by incorporating the UFH. This results in the 
following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.012

    Using an alternative POD of 10.8 [mu]g/kg/day based on a 3 percent 
decrease in the population standardized mean IQ from the EPA's 
independent analysis of the Korevaar et al., (2016) data, the EPA can 
derive an RfD by incorporating the UFH. This results in the 
following:
[GRAPHIC] [TIFF OMITTED] TP26JN19.013

J. Translate RfD Into an MCLG

    To translate the RfD ([mu]g/kg/day) to a concentration in drinking 
water ([mu]g/L), the EPA used the following equation:
[GRAPHIC] [TIFF OMITTED] TP26JN19.014

Where:

W = drinking water concentration of perchlorate in micrograms per 
liter ([mu]g/L);
RfD = reference dose (1.03 [mu]g/kg/day for a 1 percent decrease in 
IQ, 2.23 [mu]g/kg/day for a 2 percent decrease in IQ, or 3.6 [mu]g/
kg/day for a 3 percent decrease in IQ);
DWI = bodyweight-adjusted drinking water ingestion rate (L/kg/day); 
and
RSCw = relative source contribution of drinking water to 
overall perchlorate exposure.

    To calculate the MCLGs, the EPA selected the 90th percentile body-
weight adjusted drinking water ingestion rate specific to women of 
childbearing age (i.e., non-pregnant, non-lactating, 15-44 years of age 
(0.032 L/kg/day). This decision is consistent with the analysis used in 
deriving an RSC, which was performed using food consumption information 
for a population of women of childbearing age from NHANES. The 90th 
percentile is chosen to account for variability in drinking water 
ingestion rates, but also adds another layer of health protection for 
90% of women (Table III-3).
    The EPA did not use water intake data for pregnant women because 
the sample sizes were too small to be statistically stable. The use of 
the drinking water intake for 15-44 year old women is consistent with 
the analysis used in deriving an RSCw (described below), 
which was performed using food consumption information for a population 
of women of childbearing age from NHANES. The EPA acknowledges there is 
a difference in the age range defining women of childbearing age used 
to develop the drinking water ingestion rate and that used to develop 
the RSC (20-44 years of age). The age range used to develop the

[[Page 30539]]

RSC was based on the range of ages used to define women of childbearing 
age in developing the BBDR model. However, the EPA's Exposure Factors 
Handbook (USEPA, 2011c) identifies drinking water ingestion rates for 
women 15-44 years of age as corresponding to women of childbearing age.
    The age range used for women of childbearing age in the BBDR model 
fits within the age range used to develop the ingestion rates provided 
in the Exposure Factors Handbook. Thus, the Agency believes the 
difference in the age ranges will have minimal impact on the resulting 
MCLG analysis.

 Table III-3--Consumers-Only Estimated Direct and Indirect Community Water Ingestion Rates From Kahn and Stralka
                                                     (2008)
                                                   [L/kg/day]
----------------------------------------------------------------------------------------------------------------
                                                                                       90th            95th
          Female population categories              Sample size        Mean         Percentile      Percentile
----------------------------------------------------------------------------------------------------------------
Pregnant........................................              65       \a\ 0.014       \a\ 0.033       \a\ 0.043
Lactating.......................................              33       \a\ 0.026       \a\ 0.054       \a\ 0.055
Non-pregnant, non-lactating, 15 to 44 years of             2,028           0.015           0.032           0.038
 age............................................
----------------------------------------------------------------------------------------------------------------
\a\ The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
  described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (FASEB/LSRO, 1995).

    Individuals are exposed to perchlorate through ingestion of both 
food and drinking water (ATSDR 2008, Huber et al., 2011). In 
calculating the MCLGs, the EPA applies a relative source contribution 
(RSC) to the RfD to account for the percentage of the RfD remaining for 
drinking water after other sources of exposure to perchlorate have been 
considered. Thus, the RSC for drinking water is based on the following 
equation where ``Food'' is the perchlorate dose from food ingestion:
[GRAPHIC] [TIFF OMITTED] TP26JN19.015

    To estimate the dose of perchlorate for women of childbearing age 
coming from food, the EPA implemented a data integration methodology 
that combined demographic variables, food consumption estimates, and 
perchlorate contamination estimates in food from multiple sources 
(USEPA, 2019c). These sources include:
     The NHANES data available from the Centers for Disease 
Control and Prevention's (CDC) National Center for Health Statistics 
(NCHS) including the What We Eat in America (WWEIA) 24-hour food diary 
data (CDC & NCHS, 2007, 2009, 2011); and
     The Food and Drug Administration's (FDA's) Total Diet 
Study (TDS) (U.S. Food and Drug Administration (FDA), 2015), which 
analyzes contaminants in about 280 kinds of food and beverages commonly 
consumed by the U.S. population.
    The NHANES data provided individual food consumption profiles for 
female participants age 20-44 (the women of childbearing age range used 
for the BBDR model). The EPA matched TDS perchlorate concentrations 
with each food consumed by a participant and calculated each 
participant's daily perchlorate dose ([mu]g/kg/day) from food using the 
participant's body weight. The EPA estimated each participant's 
perchlorate dose using both mean and 95th percentile perchlorate 
concentrations in food. The details of these assumptions are explained 
on page 5-5 of the Technical Support Document: Deriving a Maximum 
Contaminant Level Goal for Perchlorate in Drinking Water (USEPA 2019c). 
Specifically, the EPA calculated both the mean and the 95th percentile 
of the perchlorate levels in each food based on the 20 samples included 
in the TDS data. In order to estimate the 95th percentile from the 20 
samples, the EPA used the second-highest test result for each food to 
represent the 95th percentile concentration. While simple, this method 
avoids the need to assume a distributional shape for the samples, and 
has been used in recent publications of TDS data for iodine (Carriquiry 
et al., 2016). The aforementioned method for identifying the 95th 
percentile concentration of perchlorate from food was selected over 
other, more ``statistically based'' methods for estimating percentiles 
as it avoids the need to assume a distributional shape for the samples. 
The EPA determined that it was more reliable to assume the empirically 
derived distribution as the basis for selecting the 95th percentile 
(i.e., assuming the distribution was equal to the distribution of 
samples collected in the TDS), as opposed to forcing a distributional 
shape, such as normal or log-normal, onto the data that may not 
necessarily be appropriate. With the chosen method, we can at least be 
sure that the distributional shape is appropriate for the data at hand, 
whereas by choosing the alternative that assumes a distributional 
shape, in many instances we would not even be certain of that. The EPA 
used these individual bodyweight-adjusted perchlorate doses from food 
to calculate distributions of perchlorate dose from food for the 
population of women age 20-44.
    Table III-4 presents the mean and selected percentiles of the 
distribution of perchlorate dose from food for women ages 20-44, for 
both mean and 95th percentile perchlorate concentrations in food based 
on the TDS. To calculate the RSC, the EPA selected the 90th percentile 
dose of perchlorate from food, assuming a scenario where the food 
contained the 95th percentile perchlorate concentration. This 
corresponds to a perchlorate dose for food of 0.45 [mu]g/kg/day. The 
EPA chose to use the 90th percentile bodyweight-adjusted perchlorate 
consumption from food using the 95th percentile TDS results to estimate 
the perchlorate RSC from drinking water. The EPA believes this is the 
most appropriate value for perchlorate consumption from food to ensure 
the protection of potentially highly exposed individuals. Given the 
range of perchlorate concentrations in food, and that food is the only 
other exposure source being considered in the RSC analysis, the EPA 
believes it is sufficiently protective to estimate the MCLG for 
drinking water using the 90th percentile bodyweight-adjusted 
perchlorate consumption based on the 95th percentile perchlorate food 
concentrations in TDS. This assures that highly exposed individuals 
from this most sensitive population are considered in the evaluation of 
whether perchlorate is found at levels of health concern.

[[Page 30540]]

     Table III-4--Perchlorate Dose From Food ([mu]g/kg/day) in U.S. Women Ages 20-44 Using the Mean and 95th
                                           Percentile TDS Results \1\
----------------------------------------------------------------------------------------------------------------
                                                                      Perchlorate dose from food ([mu]g/kg/day)
                                                                   ---------------------------------------------
     Level of bodyweight adjusted perchlorate consumption from                                 Based on 95th
                      population distribution                           Based on mean            percentile
                                                                      concentrations of      concentrations of
                                                                     perchlorate in food    perchlorate in food
----------------------------------------------------------------------------------------------------------------
Mean..............................................................              0.09-0.12              0.23-0.24
50th Percentile...................................................              0.08-0.10              0.17-0.19
90th Percentile...................................................              0.18-0.21                   0.45
99th Percentile...................................................              0.33-0.38              1.16-1.17
----------------------------------------------------------------------------------------------------------------
\1\ Ranges are due to various approaches for handling values level of detection. If no range is presented all
  approaches resulted in the same value.
Bolded value represents the selected value.

    The EPA used the drinking water intake and perchlorate dose from 
food to calculate MCLGs for the three RfD values. Table III-5 shows the 
RSC values for the three RfD values and the corresponding MCLGs 
calculated using the EPA's standard equation.
[GRAPHIC] [TIFF OMITTED] TP26JN19.016

IV. Maximum Contaminant Level Goal and Alternatives

    Section 1412(a)(3) of the SDWA requires the EPA to propose a 
maximum contaminant level goal (MCLG) simultaneously with the NPDWR. 
The MCLG is defined in Section 1412(b)(4)(A) as ``the level at which no 
known or anticipated adverse effects on the health of persons occurs 
and which allows an adequate margin of safety.'' The EPA is proposing 
an MCLG of 56 [mu]g/L based on the rationale and methology described in 
Section III above. The derivation of the proposed MCLG uses a point of 
departure based upon a two percent decrease in IQ for offspring of 
hypothyroxinemic women of child bearing age have with low iodine 
intake. The EPA selected a 2 percent decrease in IQ for the proposed

[[Page 30541]]

perchlorate MCLG because this represents a small change in IQ, well 
below one standard deviation for the subpopulation of interest.
    As described in Section III, the EPA has selected model parameters 
and other factors for the derivation of the MCLG that are health 
protective, including the focus on the most sensitive life stage. The 
EPA believes that the selection of the combination of protective 
parameters and this point of departure assures no known or anticipated 
adverse effects on the health of the most sensitive subpopulation and 
allows for an adequate margin of safety. The EPA also acknowledges the 
uncertainties in the derivation of the proposed (and alternative) 
MCLGs. The EPA acknowledges in particular the challenge associated with 
selecting the decrement of IQ that represents an adverse effect at the 
population level and the uncertainties in predicting the dose of 
perchlorate that may result in a particular IQ decrement given the 
absence of robust human epidemiological data directly linking 
perchlorate exposure to IQ decrements. The Agency seeks comment on the 
alternative MCLG values of 18 [mu]g/L and 90 [mu]g/L, which the EPA 
derived using the methodology described in Section III based on a one 
percent and three percent decrease in IQ, respectively.

V. Maximum Contaminant Level and Alternatives

    Under section 1412(b)(4)(B) of the SDWA, the EPA must establish a 
maximum contaminant level (MCL) as close to the MCLG as is feasible. 
The EPA evaluated available analytical methods to determine the lowest 
concentration at which perchlorate can be measured and evaluated the 
treatment technologies for perchlorate that have been examined under 
field conditions (USEPA 2018a, 2019b). The EPA determined that setting 
an MCL equal to the proposed MCLG of 56 [mu]g/L is feasible given that 
the approved analytical method for perchlorate for UCMR 1 has a minimum 
reporting level (MRL) of 4 [mu]g/L (USEPA 1999, 2000c) and that 
available treatment technologies can treat to concentrations well below 
56 [mu]g/L (USEPA, 2018c). Therefore, the EPA is proposing to set the 
MCL for perchlorate at 56 [mu]g/L.
    Because the EPA is taking comment on alternative MCLG values of 18 
[mu]g/L and 90 [mu]g/L the Agency evaluated the feasibility of setting 
an MCL at these levels. The EPA determined that the proposed MCL of 56 
[mu]g/L is feasible, therefore a higher MCL alternative such as 90 
[mu]g/L is also feasible. The EPA has concluded that analytical methods 
are capable of measuring perchlorate at 18 [mu]g/L and that treatment 
technologies have been demonstrated to achieve this level under field 
conditions (USEPA 2018a, 2019b). Therefore, the EPA is requesting 
comment on the feasibility of the proposed MCL of 56 [mu]g/L as well as 
the feasibility of the alternative MCLs of 18 [mu]g/L and 90 [mu]g/L.
    As the occurrence analysis in section VI demonstrates, there is 
infrequent occurrence of perchlorate at 18 [mu]g/L, 56 [mu]g/L, or 90 
[mu]g/L. Therefore, the EPA did not evaluate alternative MCL values 
greater than the corresponding MCLG values. The purpose for evaluating 
alternative MCL values is to determine whether there is an MCL at which 
benefits justify the costs of setting an MCL. Given infrequent 
occurrence, the majority of the costs associated with establishing an 
NPDWR for perchlorate are for administrative and initial monitoring 
activities (see section XI.B), which will not be significantly affected 
by MCL values greater than corresponding MCLG values.
    When proposing an MCL, the EPA must publish, and seek public 
comment on, the health risk reduction and cost analyses (HRRCA) of each 
alternative MCL considered (SDWA Section 1412(b)(3)(C)(i)), including: 
The quantifiable and nonquantifiable health risk reduction benefits 
attributable to MCL compliance; the quantifiable and nonquantifiable 
health risk reduction benefits of reduced exposure to co-occurring 
contaminants attributable to MCL compliance; the quantifiable and 
nonquantifiable costs of MCL compliance; the incremental costs and 
benefits of each alternative MCL; the effects of the contaminant on the 
general population and sensitive subpopulations likely to be at greater 
risk of exposure; any adverse health risks posed by compliance; and 
other factors such as data quality and uncertainty. The EPA provides 
this information in section XII in this preamble. The EPA must base its 
action on the best available, peer-reviewed science and supporting 
studies, taking into consideration the quality of the information and 
the uncertainties in the benefit-cost analysis (SDWA Section 
1412(b)(3)). The following sections, as well as the health effects 
discussion in section III document the science and studies that the EPA 
relied upon to develop estimates of benefits and costs and understand 
the impact of uncertainty on the Agency's analysis.

VI. Occurrence

    The UCMR 1 is the primary source of occurrence data the EPA relied 
on to estimate the number of water systems (and associated population) 
expected to be exposed at levels of perchlorate which could potentially 
exceed the proposed and alternative MCL levels. Since UCMR 1 data was 
first used to inform the Agency actions on the 2008 preliminary 
regulatory determination and the 2011 final regulatory determination, 
the Agency has modified its analysis of the UCMR 1 data set in response 
to concerns raised by stakeholders regarding the data quality and to 
represent current conditions at some States that have enacted 
perchlorate regulations since the UCMR 1 data was collected. Despite 
these updates, the EPA continues to rely on the UCMR 1 data because 
they are the best available data collected in accordance with accepted 
methods from a census of the large water systems (serving more than 
10,000 people) and a statistically representative sample of small water 
systems that provides the best available, national assessment of 
perchlorate occurrence in drinking water.
    In 1999, the EPA developed the first round of the UCMR program in 
accordance with SDWA requirements to provide national occurrence 
information on unregulated contaminants (USEPA, 1999, 2000b). The UCMR 
1 required sampling from systems in all 50 States, the District of 
Columbia, four U.S. territories, and tribal lands in five EPA Regions 
including:
     All 3,097 large (serving more than 10,000 people) CWSs and 
NTNCWSs, which analyzed either four quarterly samples collected at 3-
month intervals (surface water sources), or two samples collected 5 to 
7 months apart (ground water sources); and
     a statistically representative selection of 800 small CWSs 
and NTNCWSs, which analyzed either four quarterly samples collected at 
3-month intervals (surface water sources) or two samples collected 5 to 
7 months apart (ground water sources).
    Water systems submitted UCMR 1 sampling results to the EPA from 
2001 until 2005. Water systems were required to analyze samples for 26 
contaminants including perchlorate. The EPA established a minimum 
reporting level of 4 [mu]g/L for perchlorate in the UCMR.
    The EPA conducted a data quality review of the UCMR 1 data 
submitted by systems prior to analyzing the occurrence data for the 
2011 perchlorate regulatory determination. The UCMR 1 dataset used by 
the EPA included 34,331 samples with 637 measurements of perchlorate 
above the minimum reporting level from 3,865 systems.
    In September of 2012, the EPA received a ``Request for Correction''

[[Page 30542]]

letter from the United States Chamber of Commerce regarding information 
and data (i.e., the occurrence of perchlorate in drinking water) used 
by the EPA in its 2011 determination to regulate perchlorate. The U.S. 
Chamber of Commerce letter stated that the EPA relied upon: (1) Data 
that did not comply with data quality guidelines and (2) data that was 
not representative of current conditions.
    In response \12\ to the U.S. Chamber of Commerce, the EPA conducted 
a detailed assessment of the source water sample detections and 
determined that it was most appropriate to exclude the source water 
sample detections from the UCMR 1 perchlorate data set when those 
samples had appropriate follow-up entry point samples that were 
included in the UCMR 1 perchlorate data set. In contrast, any source 
water sample perchlorate detections for which no follow-up entry point 
sampling was conducted by PWSs were retained in the UCMR 1 perchlorate 
data set. As a result of the assessment, the EPA removed 199 source 
water samples (97 detections) that could be paired with a second 
follow-up sample located at the entry point to the distribution system. 
Following this convention, the resulting UCMR 1 data set contains 
34,132 perchlorate samples from 3,865 systems with a total of 540 
detections from 149 PWSs.
---------------------------------------------------------------------------

    \12\ See the EPA response letter at https://www.epa.gov/sites/production/files/2017-08/documents/12004-response_0.pdf.
---------------------------------------------------------------------------

    Table VI-1 shows sample distribution by system size category and 
measurement status. It also shows the number of entry points and 
systems where perchlorate measurements were reported. The entry point 
estimates differ from the system estimates because many water systems 
have more than one entry point. For example, a ground water system with 
two wells that has separate connections to the distribution system has 
two entry points.
    In response to the U.S. Chamber of Commerce request, the EPA has 
also reassessed the UCMR 1 data in light of the adoption of regulatory 
limits in two states. Massachusetts promulgated a drinking water 
standard for perchlorate of 2 [mu]g/L in 2006 (MassDEP, 2006), and 
California promulgated a drinking water standard of 6 [mu]g/L in 2007 
(California Department of Public Health, 2007). Systems in these states 
are now required to keep perchlorate levels in drinking water below 
their state limits, which are lower than the proposed MCL and 
alternative MCLs. Therefore, the UCMR 1 sampling results from systems 
in these states do not reflect the current occurrence and exposure 
conditions. For the purpose of estimating the costs and benefits of the 
proposed rule, the EPA assumed that no additional monitoring and 
treatment costs would be incurred by the systems in the States of 
California and Massachusetts. Systems in California account for some of 
the perchlorate measurements reported below. The notes in the tables 
below indicate whether results include or exclude systems in California 
and Massachusetts.
    To update the occurrence data for systems sampled during UCMR 1 
from the States of California and Massachusetts, the EPA identified all 
systems and corresponding entry points which had reported perchlorate 
detections in UCMR 1. Once the systems and entry points with detections 
were appropriately identified, the EPA then used a combination of 
available data from Consumer Confidence Reports (CCRs) and perchlorate 
compliance monitoring data from California (https://sdwis.waterboards.ca.gov/PDWW/) and Massachusetts (https://www.mass.gov/service-details/public-water-supplier-document-search) to 
match current compliance monitoring data (where available) to the 
corresponding water systems and entry points sampled during UCMR 1.
    Out of the 540 detections previously described the EPA updated data 
for 321 detections (320 from California systems and 1 from a 
Massachusetts system). The convention used by the EPA to accomplish the 
substitution of data was to match entry points with compliance data for 
active entry points based on most recently reported compliance 
monitoring data, if more than one data point was reported for an entry 
point, the assigned value is an average of the annual monitoring 
results at the entry point. In cases were the EPA could not find 
updated entry point data, then the original data from UCMR 1 for such 
entry point was kept.

                                   Table VI-1--UCMR 1 Data Summary Statistics
----------------------------------------------------------------------------------------------------------------
                                                                   Small system    Large system
                              Item                                    sample          census            Sum
----------------------------------------------------------------------------------------------------------------
Total samples...................................................           3,295          30,837          34,132
    Sample measurements >=4 [mu]g/L.............................              15             525             540
    Sample measurements >18 [mu]g/L.............................               1              16              17
    Sample measurements >56 [mu]g/L.............................               0               2               2
    Sample measurements >90 [mu]g/L.............................               0               1               1
Total entry points..............................................           1,454          13,482          14,936
    Entry points at which measurements >=4 [mu]g/L..............               8             328             336
    Entry points at which measurements >18 [mu]g/L..............               1              16              17
    Entry points at which measurements >56 [mu]g/L..............               0               2               2
    Entry points at which measurements >90 [mu]g/L..............               0               1               1
Total systems...................................................             797           3,068           3,865
    Systems at which measurements >=4 [mu]g/L...................               8             141             149
    Systems at which measurements >18 [mu]g/L...................               1              14              15
    Systems at which measurements >56 [mu]g/L...................               0               2               2
    Systems at which measurements >90 [mu]g/L...................               0               1               1
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b). The total row counts and counts of measurements >=4 [mu]g/L identify all instances where
  perchlorate was detected at or above the minimum reporting level, including water systems in California and
  Massachusetts, which account for 537 systems in total and 51 systems at which measurements >=4 [mu]g/L. The
  instances where perchlorate measurements equal or exceed either 18 [mu]g/L, 56 [mu]g/L, or 90 [mu]g/L exclude
  results from California and Massachusetts because water systems in these States must meet limits below 18
  [mu]g/L. The small system counts reflect sample results that have not been extrapolated to small systems
  nationwide.

[[Page 30543]]

    Table VI-2 shows the service populations that correspond with the 
occurrence summary in Table VI-1. The entry point population estimates 
reflect the assumption that system population is uniformly distributed 
across entry points; e.g., the entry point population for a system with 
two entry points is one-half the total system population.

                          Table VI-2--UCMR1 Data Service Population Summary Statistics
----------------------------------------------------------------------------------------------------------------
                                                                   Small system    Large system
                              Item                                    sample          census            Sum
----------------------------------------------------------------------------------------------------------------
Total entry point population....................................       2,760,570     222,853,101     225,613,671
    Population served by entry points at which measurements >=4            9,484       4,281,937       4,291,420
     [micro]g/L.................................................
    Population served by entry points at which measurements >18            2,155         618,406         620,560
     [micro]g/L.................................................
    Population served by entry points at which measurements >56                0          32,432          32,432
     [micro]g/L.................................................
    Population served by entry points at which measurements >90                0          25,972          25,972
     [micro]g/L.................................................
Total system population.........................................       2,760,570     222,853,101     225,613,671
    Population served by systems at which measurements >=4                13,483      16,159,082      16,172,565
     [micro]g/L.................................................
    Population served by systems at which measurements >18                 4,309         696,871         701,180
     [micro]g/L.................................................
    Population served by systems at which measurements >56                     0          64,733          64,733
     [micro]g/L.................................................
    Population served by systems at which measurements >90                     0          25,972          25,972
     [micro]g/L.................................................
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b). The populations for entry points/systems with measurements >=4 [micro]g/L identify all
  instances where perchlorate was detected at or above the minimum reporting level, including water systems in
  California and Massachusetts, which account for 39.6 million of the 225.6 million total population in UCMR 1,
  and 1.9 million of the 4.3 million population served by entry points at which measurements >=4 [micro]g/L. The
  instances where perchlorate measurements equal or exceed either 18 [micro]g/L, 56 [micro]g/L, or 90 [micro]g/L
  exclude results from California and Massachusetts because water systems in these States must meet limits below
  18 [micro]g/L. The small system counts reflect sample results that have not been extrapolated to small systems
  nationwide.

    As shown in the tables, 149 systems serving 16.2 million people had 
measured levels of perchlorate greater than the minimum reporting 
level. However, many of these systems have several entry points with no 
measured levels of perchlorate greater than the minimum reporting 
level; at the entry point level, the exposed population is 
approximately 4.3 million people served by 336 entry points. Because 
the uniform population distribution assumption may over or 
underestimate the service population of any particular entry point, the 
entry point estimates are uncertain. The system population estimates 
serve as upper bounds on exposure.
    The EPA used entry point maximum measurements to estimate potential 
baseline occurrence and exposure at levels that exceed the proposed MCL 
and alternative MCLs. The maximum measurements indicate perchlorate 
levels that occurred in at least one quarterly sample among surface 
water systems and at least one semi-annual sample among ground water 
systems.
    Table VI-3 through Table VI-5 show the occurrence and exposure 
estimates based on the 56 [micro]g/L, 18 [micro]g/L MCL, and 90 
[micro]g/L values, respectively. Each table provides estimates of the 
entry points at which the maximum perchlorate concentrations exceed the 
MCL value. The tables also report the system-level information for 
these entry points.

        Table VI-3--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 56 [micro]g/L
----------------------------------------------------------------------------------------------------------------
                         Affected entity                           Small systems   Large systems   Total systems
----------------------------------------------------------------------------------------------------------------
Entry points....................................................               0               2               2
Population served...............................................               0          32,432          32,432
Water systems...................................................               0               2               2
Population served...............................................               0          64,733          64,733
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).

        Table VI-4--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 18 [micro]g/L
----------------------------------------------------------------------------------------------------------------
                                                                  Small  systems
                         Affected entity                                \1\        Large systems   Total systems
----------------------------------------------------------------------------------------------------------------
Entry points....................................................               1              16              17
Population served...............................................           2,155         618,406         620,560
Water systems...................................................               1              14              15
Population served...............................................           4,309         696,871         701,180
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).
\1\ The values shown in the table are estimates based on the UCMR 1 data. The EPA also applied the statistical
  sampling weights to the results to extrapolate results to national results. The entry point at which a
  measurement exceeds 18 [micro]g/L is one of 20 in its sample stratum; no other sample in the stratum had a
  measurement of perchlorate greater than the minimum reporting level. The entry point population of 2,155
  represents 5.31% of the total population served by the six UCMR 1 systems in the stratum (40,574). Currently,
  the stratum population of 774,780 accounts for 1.32% of the 58.7 million national population served by small
  systems. Thus, the UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of small system customers (approximately
  41,100) may be exposed to perchlorate greater than 18 [micro]g/L.

[[Page 30544]]

        Table VI-5--Estimated Perchlorate Occurrence and Exposure: Entry Point Max Exceeds 90 [micro]g/L
----------------------------------------------------------------------------------------------------------------
                                                                   Small systems
                         Affected entity                                \1\        Large systems   Total systems
----------------------------------------------------------------------------------------------------------------
Entry points....................................................               0               1               1
Population served...............................................               0          25,972          25,972
Water systems...................................................               0               1               1
Population served...............................................               0          25,972          25,972
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019b).

    In summary, the perchlorate occurrence information suggests that at 
an MCL of 56 [micro]g/L, two systems (0.004% of all water systems in 
the U.S.) would exceed the regulatory threshold. One of these two 
systems would exceed the alternative MCL of 90 [micro]g/L. In addition, 
at an MCL of 18 [micro]g/L, there would be 15 systems (0.03% of all 
water systems in the U.S.) that would exceed the regulatory threshold.

VII. Analytical Methods

    The SDWA directs the EPA to set a contaminant's MCL as close to its 
MCLG as is ``feasible'', the definition of which includes an evaluation 
of the feasibility of performing chemical analysis of the contaminant 
at standard drinking water laboratories. Specifically, the SDWA directs 
the EPA to determine that it is economically and technologically 
feasible to ascertain the level of the contaminant being regulated in 
water in public water systems (Section 1401(1)(C)(i)). NPDWRs are also 
to contain ``criteria and procedures to assure a supply of drinking 
water which dependably complies with such [MCLs]; including accepted 
methods for quality control and testing procedures to insure compliance 
with such levels.'' (Section 1401(1)(D)).
    To comply with these requirements, the EPA considers method 
performance under relevant laboratory conditions, their likely 
prevalence in certified drinking water laboratories, and the associated 
analytical costs. The EPA has developed five analytical methods for the 
identification and quantification of perchlorate in drinking water that 
meet these criteria. The proposed EPA methods for perchlorate are: 
314.0, 314.1, 314.2, 331.0, and 332.0. A detailed description of these 
methods is presented in the Perchlorate Occurrence and Monitoring 
Report (USEPA, 2019b).
    The EPA Methods 314.0, 314.1, 314.2, 331.0, and 332.0 underwent the 
EPA's analytical method development and validation processes. The 
validation process includes a protocol for modifications to any 
existing EPA-approved analytical methods and a protocol for new 
determinative techniques. Both validation protocols are rigorous and 
consider many technical aspects of analytical method performance, 
including: Detection limits; instrument calibration; precision and 
analyte recovery; analyte retention times; evaluation of blanks; 
development of Quality Control acceptance criteria; analysis of field 
samples; and other technical aspects of sample analysis and data 
reporting. All of the proposed EPA analytical methods provide 
performance data to demonstrate their capability to reliably and 
consistently measure perchlorate in drinking water at the proposed and 
alternate MCLs.
    EPA Method 314.0, ``Determination of Perchlorate in Drinking Water 
Using Ion Chromatography'' (Revision 1.0, USEPA, 1999a) has a method 
detection limit (MDL) of 0.53 [micro]g/L. Single-laboratory mean 
percent recovery in various aqueous matrices range from 86% to 113% 
with Relative Standard Deviations (RSDs) of 1.0% to 12.8%. A minimum 
reporting level (MRL) is not specified in the method; however, a range 
of 3.0 to 5.0 [micro]g/L is cited as a benchmark range for quality 
assurance/quality control (QA/QC) procedures. The MRL is to be 
established as either a concentration that is greater than three times 
the laboratory MDL or at a concentration that yields a response greater 
than a signal to noise ratio of five. In either case, the MRL must not 
be below the lowest instrument calibration standard (USEPA, 1999a). 
Method 314.0 was widely adopted as the standard perchlorate method.
    After the EPA published Method 314.0, the Agency adopted additional 
method development goals for the analysis of perchlorate in drinking 
water including: (1) Reducing MRL to less than 1 [micro]g/L through the 
application of sample concentration techniques, microbore analytical 
columns, and advanced detection systems (i.e., mass spectrometry), (2) 
further increasing the tolerance for high ionic strength matrices, and 
(3) enhancing measurement selectivity.
    EPA Method 314.1, ``Determination of Perchlorate in Drinking Water 
Using Inline Column Concentration/Matrix Elimination Ion Chromatography 
with Suppressed Conductivity Detection'' (Revision 1.0, USEPA, 2005b) 
documents the EPA single-laboratory Lowest Concentration Minimum 
Reporting Levels (LCMRLs) of less than 0.2 [micro]g/L (DL = 0.03 
[micro]g/L) using online sample pre-concentration. The method uses 
matrix diversion to handle high ionic strength matrices (up to 1,000 
mg/L TDS) and added confirmation analysis using a second analytical 
column (USEPA, 2005b).
    EPA Method 314.2, ``Determination of Perchlorate in Drinking Water 
Using Two-Dimensional Ion Chromatography with Suppressed Conductivity 
Detection'' (USEPA, 2008c) documents the EPA single-laboratory LCMRLs 
of less than 0.1 [micro]g/L (DLs <0.02 [micro]g/L) using large volume 
injection. The method uses 2-D chromatography to handle high ionic 
strength matrices (up to 1,000 mg/L total dissolved solids [TDS]) and 
eliminates the need for separate confirmation analysis (USEPA, 2008c).
    EPA Method 331.0, ``Determination of Perchlorate in Drinking Water 
by Liquid Chromatography Electrospray Ionization Mass Spectrometry'' 
(Revision 1.0, USEPA, 2005c) documents the EPA single-laboratory LCMRLs 
of less than 0.1 [micro]g/L (DLs <0.01 [micro]g/L), applied multiple 
analytical advancements to a liquid chromatography (LC) analysis 
including a perchlorate selective LC column (AS-21), mass spectrometry 
(MS) or MS/MS detection for selectivity and sensitivity, and a custom 
labeled internal standard (Cl\18\O4-) (USEPA, 
2005c).
    EPA Method 332.0, ``Determination of Perchlorate in Drinking Water 
by Ion Chromatography with Suppressed Conductivity and Electrospray 
Ionization Mass Spectrometry'' (USEPA, Revision 1.0, 2005d) documents 
the EPA single-laboratory LCMRL of 0.1 [micro]g/L (DL = 0.02 [micro]g/
L), applied multiple analytical advancements in an IC analysis 
including suppressed conductivity IC, MS or MS/MS selectivity and 
sensitivity, and a custom labeled internal standard 
(Cl\18\O4) (USEPA, 2005d).

[[Page 30545]]

VIII. Monitoring and Compliance Requirements

A. What are the proposed monitoring requirements?

    The EPA is proposing to require CWS and NTNCWSs to monitor for 
perchlorate in accordance with the standardized monitoring framework 
set out in 40 CFR 141 Subpart C (Standardized Monitoring Framework). 
Public water systems must sample entry points to the distribution 
system consistent with requirements in 40 CFR 141.23(a).
    Under the Standardized Monitoring Framework, the monitoring 
frequency for a public water system is dependent on previous monitoring 
results and whether a monitoring waiver has been granted. The EPA is 
proposing that consistent with the standardized monitoring framework 
water systems would be initially required to monitor quarterly for 
perchlorate. The EPA is also proposing that based upon the monitoring 
results States would be able to reduce the monitoring frequency to 
annually, once every three years or once every nine years if the State 
concludes that the system is reliably and consistently below the MCL. 
If a water system exceeds the perchlorate MCL, the system is in 
violation and triggered into quarterly monitoring for that sampling 
point in the next quarter after the violation occurred (40 CFR 
141.23(c)(7)). The state may allow the system to return to the reduced 
monitoring frequency when the state determines that the system is 
reliably and consistently below the MCL. However, the state cannot make 
a determination that the system is reliably and consistently below the 
MCL until a minimum of 2 consecutive ground water or 4 consecutive 
surface water samples below the MCL have been collected (40 CFR 
141.23(c)(8)). All systems must comply with the sampling requirements, 
unless a waiver has been granted in writing by the state (40 CFR 
141.23(c)(6)).

B. Can states grant monitoring waivers?

    Under this proposal, water systems may apply to the state, and 
states may grant, a 9-year monitoring waiver for perchlorate if the 
conditions described in 40 CFR 141.23(c)(3)-(6) are met. A state may 
grant a waiver for surface water systems after three rounds of annual 
monitoring with results less than the MCL and for groundwater systems 
after conducting three rounds of monitoring with results less than the 
MCL. One sample must be collected during the nine-year compliance cycle 
that the waiver is effective, and the waiver must be renewed every nine 
years.

C. How are system MCL violations determined?

    Under this proposal, violations of the perchlorate MCL would be 
determined in a manner consistent with 40 CFR 141.23(i)(3). Compliance 
with the perchlorate MCL would be determined based on one sample if the 
level is below the MCL. If the level of perchlorate exceeds the MCL at 
any entry point in the initial sample, a confirmation sample is 
required within two weeks of the system's receipt of notification of 
the analytical result of the first sample, in accordance with 
141.23(f)(1). Compliance shall be determined based on the average of 
the initial and confirmation samples.

D. When must systems complete initial monitoring?

    Pursuant to Section 1412(b)(10), this rule would be effective three 
years after promulgation. To satisfy initial monitoring requirements, 
CWS serving populations greater than 10,000 persons must collect 4 
quarterly samples for perchlorate during the second compliance period 
of the fourth compliance cycle (January 1, 2023- December 31, 2025) of 
the Standardized Monitoring Framework. NTNCWS and CWSs serving 10,000 
persons or less must collect 4 quarterly samples during the third 
compliance period of the fourth compliance cycle (January 1, 2026-
December 31, 2028) of the Standardized Monitoring Framework.

E. Can systems use grandfathered data to satisfy the initial monitoring 
requirements?

    As proposed today, systems would be allowed to use grandfathered 
perchlorate data collected after January 1, 2020, to satisfy the 
initial monitoring requirements. To satisfy initial perchlorate 
monitoring requirements, a system with appropriate historical 
monitoring data for each entry point to the distribution system could 
use the monitoring data from the compliance monitoring period between 
January 1, 2020, and December 31, 2022, for CWSs serving greater than 
10,000 persons and between January 1, 2023, and December 31, 2025, for 
NTNCWs and for CWSs serving 10,000 or fewer persons.

IX. Safe Drinking Water Act Right to Know Requirements

A. What are the Consumer Confidence Report requirements?

    A community water system must prepare and deliver to its customers 
an annual Consumer Confidence Report (CCR) in accordance with 
requirements in 40 CFR 141 Subpart O. A CCR provides customers with 
information about their local drinking water quality as well as 
information regarding the water system compliance with drinking water 
regulations. Under this proposal CWSs would be required to report 
perchlorate information in their CCR.

B. What are the public notification requirements?

    All public water systems must give the public notice for all 
violations of NPDWRs and for other situations. Under this proposal, 
violations of the perchlorate MCL would be designated as Tier 1 and as 
such, public water systems would be required to comply with 40 CFR 
141.202. As described in Section III of this proposal, fetuses of first 
trimester pregnant women with low iodine are the most sensitive 
subpopulation, therefore, per 40 CFR 141.202(b)(1), notification of an 
MCL violation should be provided as soon as practicable but no later 
than 24 hours after the system learns of the violation under this 
proposal.

X. Treatment Technologies

    Systems that exceed the perchlorate MCL will need to adopt new 
treatment or another strategy to reduce perchlorate to a level that 
meets the MCL. When the EPA establishes an MCL for a drinking water 
contaminant, Section 1412(b)(4)(E) of the SDWA requires that the Agency 
``list the technology, treatment techniques, and other means which the 
Administrator finds to be feasible for purposes of meeting [the MCL],'' 
which are referred to as best available technologies (BAT). These BATs 
are used by states to establish conditions for source water variances 
under Section 1415(a). Furthermore, Section 1412(b)(4)(E)(ii) requires 
that the Agency identify small system compliance technologies (SSCT), 
which are affordable treatment technologies, or other means that can 
achieve compliance with the MCL (or treatment technique, where 
applicable). The lack of an affordable SSCT for a contaminant triggers 
certain additional procedures which can result in states issuing small 
system variances under Section 1412(e) of the SDWA.
    The Agency solicits public comment on the choice of available 
treatment technologies discussed in this section.

A. What are the best available technologies?

    The Agency identifies the best available technologies (BAT) as 
those meeting the following criteria: (1) The capability of a high 
removal efficiency;

[[Page 30546]]

(2) a history of full-scale operation; (3) general geographic 
applicability; (4) reasonable cost based on large and metropolitan 
water systems; (5) reasonable service life; (6) compatibility with 
other water treatment processes; and (7) the ability to bring all of 
the water in a system into compliance. The Agency is proposing the 
following technologies as BAT for removal of perchlorate from drinking 
water based its review of the treatment and cost literature (USEPA, 
2018a):
     Ion exchange;
     biological treatment; and
     centralized reverse osmosis.
    There are also non-treatment options that might be used for 
compliance in lieu of installing and operating treatment technologies. 
These include blending existing water sources, replacing a perchlorate-
contaminated source of drinking water with a new source (e.g., a new 
well), and purchasing compliant water from another system. Below are 
brief descriptions of each proposed BAT.
Ion Exchange
    Ion exchange is a physical and chemical separation process that can 
achieve high perchlorate removal rates. Feed water passes through a 
vessel containing a bed of resin made of synthetic beads or gel. As 
feed water moves through the resin, an ionic contaminant such as 
perchlorate exchanges for an ion (typically chloride) on the resin. 
Demonstrated removal efficiencies for perchlorate are typically in the 
high 90 percent range and can achieve concentrations less than 4 
[micro]g/L in treated water (Drago & Leserman, 2011; Membrane 
Technology, 2006; Siemens Water Technologies, 2009; The Interstate 
Technology & Regulatory Council (ITRC) Team, 2008). The operation 
continues until enough of the resin's available ion exchange sites have 
ions from the feed water and the resin no longer effectively removes 
the target contaminant, i.e., the contaminant ``breaks through'' the 
treatment process. At this point, the resin must be disposed and 
replaced or regenerated. The length of time until resin must be 
replaced or regenerated is known as bed life and is a critical factor 
in the cost effectiveness of ion exchange as a treatment technology. 
One measurement of bed life is the volume of water that can be treated 
before breakthrough--called bed volumes--the number of times the resin 
bed can be filled before breakthrough. Several factors affect bed life, 
including the presence of competing ions such as nitrate and the type 
of resin used. Resin types tested for perchlorate removal include 
strong-base polyacrylic, strong-base polystyrenic (including nitrate-
selective), weak-base polyacrylic, weak-base polystyrenic, and 
perchlorate-selective. Based on studies of the effect of competing ions 
on performance, perchlorate-selective resins can achieve bed lives 
ranging from 105,000 to 170,000 bed volumes (Blute, Seidel, McGuire, 
Qin, & Byerrum, 2006; Russell, Qin, Blute, McGuire, & Williams, 2008; 
Wu & Blute, 2010).
    Perchlorate-selective resin cannot be easily regenerated for reuse; 
the exhausted resin must be disposed (i.e., operated on a `throw-away' 
basis). This mode of operation, however, avoids the production of 
liquid residuals in the form of spent regenerant. Therefore, in 
combination with the long bed life, single-use perchlorate-selective 
ion exchange can be a cost-effective treatment option in spite of the 
need to dispose of the perchlorate-contaminated resin. Build-up of 
arsenic or uranium on the resin may affect waste disposal options, 
although studies of perchlorate-selective resins show that arsenic 
concentrations remain below regulatory limits for hazardous waste 
disposal and uranium concentrations generally remain below those that 
require special handling as radioactive waste (Blute et al., 2006; 
Russell et al., 2008; Wu & Blute, 2010). Ion exchange can increase the 
corrosivity of treated water (Berlien, 2003; Betts, 1998; USEPA, 2005b) 
because of the addition of chloride ions and/or removal of carbonates 
and bicarbonates. Such instances can be addressed by adding or 
adjusting corrosion control.
Biological Treatment
    Biological treatment uses bacteria to reduce perchlorate to 
chlorate, chlorite, chloride, and oxygen. Biological treatment can 
destroy the perchlorate ion, eliminating the need for management of 
perchlorate-bearing waste streams. Removal effectiveness exceeds 90 
percent for bench-scale tests and full-scale treatment plant studies 
(Kotlarz, Upadhyaya, Togna, & Raskin, 2016; Upadhyaya, Kotlarz, Togna, 
& Raskin, 2015; U.S. Department of Defense (U.S. DoD), 2008, 2009; T.D. 
Webster & Crowley, 2010, 2016; T.D. Webster & Litchfield, 2017). 
Although biological treatment is a relatively new technology for 
treatment of drinking water in the United States, the State of 
California has identified biological treatment (along with ion 
exchange) as one of two best available technologies for achieving 
compliance with its standard for perchlorate in drinking water 
(California Code of Regulations, Title 22, Chapter 15, Section 
64447.2). The California BAT specifies a fluidized bed, although 
studies suggest that a fixed bed is also effective. The first full-
scale fluidized bed facility using biological treatment of perchlorate 
to supply municipal drinking water began operation in 2016 (T. D. 
Webster & Crowley, 2016; T. D. Webster & Litchfield, 2017). Raw water 
quality will affect process design, in particular, temperature affects 
the rate of biomass growth; at temperatures below 10 degrees Celsius, 
growth is inhibited and bioremediation becomes infeasible (Dugan, 
2010b, 2010a; Dugan et al., 2009). This factor limits the feasibility 
of biological treatment in areas that experience low water temperatures 
during winter. In addition, bacteria in bioreactors require nutrients 
to grow and effectively reduce perchlorate. Therefore, some source 
waters may require supplemental addition of nutrients such as nitrogen 
or phosphorus (Harding Engineering and Environmental Services (ESE), 
2001; U.S. Department of Defense (U.S. DoD), 2008a, 2009).
    Although the process does not produce perchlorate-contaminated 
wastes, periodic removal of excess biomass, e.g., through backwash, 
will be required. The backwash water is non-toxic and can be discharged 
to a sanitary sewer (U.S. Department of Defense (U.S. DoD), 2008, 2009) 
or recycled following clarification. Typically, post-treatment of 
treated water also will be required because biological treatment 
increases soluble microbial organic products, depletes oxygen, and can 
add turbidity and sulfides (Dordelmann, 2009; Harding Engineering and 
Environmental Services (ESE), 2001; U.S. Department of Defense (U.S. 
DoD), 2008; T. D. Webster & Crowley, 2016; T. D. Webster & Litchfield, 
2017). The treatment process, however, can result in removal of co-
occurring contaminants such as nitrate (Upadhyaya et al., 2015; Webster 
and Crowley, 2010; Webster and Lichfield, 2017).
Reverse Osmosis
    Reverse osmosis is a membrane filtration process that physically 
removes perchlorate ions from drinking water. This process separates a 
solute such as perchlorate ions from a solution by forcing the solvent 
to flow through a membrane at a pressure greater than the normal 
osmotic pressure. The membrane is semi-permeable, transporting 
different molecular species at different rates. Water and low-molecular 
weight solutes pass through the membrane and are removed as permeate, 
or filtrate. Dissolved and suspended solids are rejected by the 
membrane and are removed as

[[Page 30547]]

concentrate or reject. This technique does not destroy the perchlorate 
ion and, therefore, creates a subsequent need for disposal or treatment 
of perchlorate-contaminated waste (the concentrate).
    Membranes may remove ions from feed water by a sieving action 
(called steric exclusion), or by electrostatic repulsion of ions from 
the charged membrane surface. Across multiple bench- and pilot-scale 
studies, reverse osmosis membranes consistently achieve perchlorate 
removal greater than 80 percent and up to 98 percent (Liang, Scott, 
Palencia, & Bruno, 1998; Nam et al., 2005; Yoon, Amy, & Yoon, 2005; 
Yoon, Yoon, Amy, & Her, 2005). While water quality affects process 
design (e.g., recovery rate, cleaning frequency, and antiscalant 
selection), it has relatively little effect on perchlorate removal 
effectiveness of reverse osmosis membranes. Reverse osmosis generates a 
relatively large concentrate stream, which will contain perchlorate as 
well as other rejected dissolved solids, which will require disposal. 
The large concentrate stream also means less treated water is available 
for distribution (e.g., 70 to 85 percent of source water), which is a 
disadvantage for systems with limited water supply. Because reverse 
osmosis can increase the corrosivity of the treated water, it may 
require post-treatment or blending with bypass water. Reverse osmosis 
can, however, remove co-occurring contaminants including arsenic and 
chromium-VI (Amy, Yoon, and Amy, 2005).

B. What are the small system compliance technologies?

    The EPA is proposing the SSCT shown in Table X-1. The table shows 
which of the BAT listed above are also affordable for each small system 
size category listed in Section 1412(b)(4)(E)(ii) of the SDWA. The 
Agency identified these technologies based on an analysis of treatment 
effectiveness and affordability (USEPA, 2018a).

                                Table X-1--Proposed SSCT for Perchlorate Removal
----------------------------------------------------------------------------------------------------------------
    System size (population                           Biological                          Point-of-use reverse
            served)                Ion exchange        treatment     Reverse  osmosis           osmosis
----------------------------------------------------------------------------------------------------------------
25-500........................  Yes..............  No..............  No..............  Yes.
501-3,300.....................  Yes..............  Yes.............  Yes.............  Yes.
3,301-10,000..................  Yes..............  Yes.............  Yes.............  Not applicable.\a\
----------------------------------------------------------------------------------------------------------------
\a\ For perchlorate, the EPA has determined that implementing and maintaining this option for systems larger
  than 3,300 people (greater than 1 MGD design flow) is likely to be impractical.

    The SSCT listed in Table X-1 include a point-of-use (POU) version 
of reverse osmosis in addition to the ion exchange, biological 
treatment and reverse osmosis technologies described in the previous 
section. This technology can be used by small systems to comply with 
the proposed MCL and, therefore, meets the effectiveness requirement 
for an SSCT. For perchlorate removal, NSF/ANSI Standard 58: Reverse 
Osmosis Drinking Water Treatment Systems includes a protocol that 
requires a reverse osmosis unit to be able to reduce perchlorate from a 
challenge level of 130 [micro]g/L to a target level of 4 [micro]g/L 
(NSF, 2004). Organizations (e.g., NSF International, Underwriters 
Laboratories, Water Quality Association) provide third-party testing 
and certification that POU devices meet drinking water treatment 
standards. There are no perchlorate certification standards for other 
types of POU devices such as those using ion exchange media.
    The operating principle for POU reverse osmosis devices is the same 
as centralized reverse osmosis: Steric exclusion and electrostatic 
repulsion of ions from the charged membrane surface. In addition to a 
reverse osmosis membrane for dissolved ion removal, POU reverse osmosis 
devices often have a sediment pre-filter and a carbon filter in front 
of the reverse osmosis membrane, a 3- to 5-gallon treated water storage 
tank, and a carbon filter between the tank and the tap.
    The EPA identified the SSCT using the affordability criteria 
methodology it developed for drinking water rules (USEPA, 1998). The 
analysis method is a comparison of estimated incremental household 
costs for perchlorate treatment to an expenditure margin, which is the 
difference between baseline household water costs and a threshold equal 
to 2.5% of median household income. Table X-2 shows the expenditure 
margins derived for the analysis. These margins show the cap on 
affordable incremental annual expenditures.

                         Table X-2--Expenditure Margins for SSCT Affordability Analysis
----------------------------------------------------------------------------------------------------------------
                                                    Median
        System size (population served)            household      Affordability   Baseline water    Expenditure
                                                  income \a\      threshold \b\      cost \c\         margin
                                                           (a)    (b) = 2.5% x a             (c)       (d) = b-c
----------------------------------------------------------------------------------------------------------------
25-500........................................         $52,791            $1,320            $341            $979
501-3,300.....................................          51,093             1,277             395             883
3,301-10,000..................................          55,975             1,399             412             987
----------------------------------------------------------------------------------------------------------------
Source: Best Available Technologies and Small System Compliance Technologies for Perchlorate in Drinking Water
  (USEPA, 2018a).
\a\ MHI based on U.S. Census 2010 American Community Survey (ACS) 5-year estimates (U.S. Census Bureau, 2010)
  stated in 2010 dollars, adjusted to 2017 dollars using the CPI (for all items) for areas under 50,000 persons
  (Bureau of Labor Statistics (BLS), 2018b).
\b\ Affordability threshold equals 2.5 percent of MHI.
\c\ Household water costs derived from 2006 Community Water System Survey (USEPA, 2009c), based on residential
  revenue per connection within each size category, adjusted to 2017 dollars based on the CPI (for all items)
  for areas under 50,000 persons.

    Table X-3 shows the estimates of per-household costs by treatment 
technology and size category generated using the treatment cost method 
described in section XII.B as well as Best Available Technologies and 
Small

[[Page 30548]]

System Compliance Technologies for Perchlorate in Drinking Water 
(USEPA, 2018a) and Technologies and Costs for Treating Perchlorate-
Contaminated Waters (USEPA, 2018c). Costs in bold font do not exceed 
the corresponding expenditure margin and, therefore, meet the SSCT 
affordability criterion. Therefore, the EPA has determined that there 
are affordable small system compliance technologies available and the 
Agency is not proposing any variance technologies.

                  Table X-3--Annual Incremental Cost Estimates for SSCT Affordability Analysis
----------------------------------------------------------------------------------------------------------------
    System size (population                            Biological                         Point-of-use  reverse
            served)                Ion exchange        treatment       Reverse osmosis           osmosis
----------------------------------------------------------------------------------------------------------------
25-500........................  $378 to $610.....  $2,146 to $3,709.  $2,272 to $2,671  $265 to $271.
501-3,300.....................  $98 to $148......  $324 to $566.....  $561 to $688....  $250 to $251.
3,301-10,000..................  $104 to $153.....  $211 to $315.....  $431 to $493....  Not applicable.\a\
----------------------------------------------------------------------------------------------------------------
Source: Best Available Technologies and Small System Compliance Technologies for Perchlorate in Drinking Water
  (USEPA, 2018a), which describes the different WBS model input assumptions that result in ranges of per-
  household costs shown; bold font indicates cost estimates that do not exceed the corresponding expenditure
  margin.
\a\ For perchlorate, the EPA has determined that implementing and maintaining a POU program for systems larger
  than 3,300 people (greater than 1 MGD design flow) is likely to be impractical.

XI. Rule Implementation and Enforcement

A. What are the requirements for primacy?

    This section describes the regulations and other procedures and 
policies primacy entities must adopt, or have in place, to implement 
the proposed perchlorate rule. States must continue to meet all other 
conditions of primacy in 40 CFR part 142. Section 1413 of the SDWA 
establishes requirements that primacy entities (States or Indian 
Tribes) must meet to maintain primary enforcement responsibility 
(primacy) for its public water systems. These include: (1) Adopting 
drinking water regulations that are no less stringent than federal 
NPDWRs in effect under sections 1412(a) and 1412(b) of the Act, (2) 
Adopting and implementing adequate procedures for enforcement, (3) 
Keeping records and making reports available on activities that the EPA 
requires by regulation, (4) Issuing variances and exemptions (if 
allowed by the State) under conditions no less stringent than allowed 
by SDWA Sections 1415 and 1416, and (5) Adopting and being capable of 
implementing an adequate plan for the provision of safe drinking water 
under emergency situations.
    40 CFR part 142 sets out the specific program implementation 
requirements for States to obtain primacy for the Public Water Supply 
Supervision Program, as authorized under section 1413 of the Act.
    To implement the perchlorate rule, States would be required to 
adopt revisions at least as stringent as the proposed provisions in 40 
CFR 141.6 (Effective Dates); 40 CFR 141.23 (Inorganic chemical sampling 
and analytical requirements); 40 CFR 141.51 (Maximum contaminant level 
goals for inorganic contaminants); 40 CFR 141.60 (Effective Dates); 40 
CFR 141.62 (Maximum contaminant levels for inorganic contaminants); 
Appendix A to Subpart O ([Consumer Confidence Report] Regulated 
contaminants); Appendix A to Subpart Q (NPDWR violations and other 
situations requiring public notice); Appendix B to Subpart Q (Standard 
health effects language for public notification); and 40 CFR 142.62 
(Variances and exemptions from the maximum contaminant levels for 
organic and inorganic contaminants). Under 40 CFR 142.12(b), all 
primacy States/territories/tribes would be required to submit a revised 
program to the EPA for approval within two years of promulgation of any 
final perchlorate NPDWR or could request an extension of up to two 
years in certain circumstances.

B. What are the State recordkeeping requirements?

    The current regulations in 40 CFR 142.14 require States with 
primary enforcement responsibility (i.e., primacy) to keep records of 
analytical results to determine compliance, system inventories, 
sanitary surveys, State approvals, vulnerability and waiver 
determinations, monitoring requirements, monitoring frequency 
decisions, enforcement actions, and the issuance of variances and 
exemptions. The State record keeping requirements remain unchanged and 
would apply to perchlorate as with any other regulated contaminant.

C. What are the State reporting requirements?

    Currently, States must report to the EPA information under 40 CFR 
142.15 regarding violations, variances and exemptions, enforcement 
actions and general operations of State public water supply programs. 
The State reporting requirements remain unchanged and would apply to 
perchlorate as with any other regulated contaminant. However, the 
perchlorate MCL could result in a greater frequency of reporting by 
certain states. See discussion of Paperwork Reduction Act compliance in 
Section XVI for more information.

XII. Health Risk Reduction Cost Analysis

    Section 1412(b)(3)(C) of the 1996 Amendments to the SDWA requires 
the EPA to prepare a Health Risk Reduction and Cost Analysis (HRRCA) in 
support of any NPDWR that includes an MCL. This section addresses the 
HRRCA requirements as indicated:
     Quantifiable and non-quantifiable health risk reduction 
benefits for which there is a factual basis in the rulemaking record to 
conclude that such benefits are likely to occur as the result of 
treatment to comply with each level (Sections XII.C and XII.D);
     Quantifiable and non-quantifiable health risk reduction 
benefits for which there is a factual basis in the rulemaking record to 
conclude that such benefits are likely to occur from reductions in co-
occurring contaminants that may be attributed solely to compliance with 
the MCL, excluding benefits resulting from compliance with other 
proposed or promulgated regulations (Section XII.C);
     Quantifiable and non-quantifiable costs for which there is 
a factual basis in the rulemaking record to conclude that such costs 
are likely to occur solely as a result of compliance with the MCL, 
including monitoring, treatment, and other costs, and excluding costs 
resulting from compliance with other proposed or promulgated 
regulations (Section XII.B and XII.D);
     The incremental costs and benefits associated with each 
alternative MCL considered (Section XII.D);
     The effects of the contaminant on the general population 
and on groups within the general population, such as

[[Page 30549]]

infants, children, pregnant women, the elderly, individuals with a 
history of serious illness, or other sensitive populations that are 
identified as likely to be at greater risk of adverse health effects 
due to exposure to contaminants in drinking water than the general 
population (Section XII.C and Section III);
     Any increased health risk that may occur as the result of 
compliance, including risks associated with co-occurring contaminants 
(Section XII.C); and
     Other relevant factors, including the quality and extent 
of the information, the uncertainties in the analysis, and factors with 
respect to the degree and nature of the risk (Section XII.E).

A. Identifying Affected Entities

    If the EPA issues a final NPDWR for perchlorate, it would affect 
the following entities: CWSs and NTNCWSs that must meet the proposed 
MCL and monitoring and reporting requirements; and primacy agencies 
that must adopt and enforce the MCL as well as the monitoring and 
reporting requirements. All of these entities would incur costs, 
including administrative costs, monitoring and reporting costs, and--in 
a limited number of cases--costs to reduce perchlorate levels in 
drinking water to meet the proposed MCL using treatment or nontreatment 
options. Section B below summarizes the method the EPA used to estimate 
these costs.
    The systems that reduce perchlorate concentrations will reduce 
associated health risks. The EPA developed a method to estimate the 
potential benefits of reduced perchlorate exposure among the service 
populations of systems with elevated baseline perchlorate levels. 
Section C below summarizes this method used to estimate these benefits.
    Section D below provides the cost and benefit estimates. The EPA 
prepared the Health Risk Reduction Cost Analysis of the Proposed 
Perchlorate Rule (USEPA, 2019a), which is available in the docket for 
the proposed rule. Section XIII summarizes and discusses key 
uncertainties in the cost and benefit analyses.

B. Method for Estimating Costs

    Some costs associated with an NPDWR are incurred by all CWS and 
NTNCWS (e.g., monitoring and reporting) while others are only incurred 
by systems with perchlorate levels exceeding the MCL. The EPA estimated 
costs for CWS and NTNCWS to monitor and report perchlorate levels and 
also estimated the costs for a subset of public water systems with 
perchlorate levels greater than the proposed MCL to install and operate 
treatment. The EPA assumed that affected water systems would adopt ion 
exchange treatment because it is the most cost-effective treatment 
option and easy to operate on a `throw-away' basis. If site-specific 
nontreatment options are available and lower cost, then this assumption 
might overstate costs. The EPA also estimated the costs for States and 
other primacy agencies to assure systems implement the rule and to 
report information to the EPA.
    The EPA estimated initial costs for all CWS and NTNCWS operators to 
read and understand the rule and provide training to their staff to 
implement the proposed rule. The EPA also estimated the recurring costs 
for all CWS and NTNCWS operators to conduct monitoring, report results, 
and apply for waivers. For the purpose of these estimates, the EPA 
assumed that both small and large systems would require the same amount 
of time to read the rule, apply for a waiver, and collect a water 
sample but that it would take large systems twice as long to provide 
initial training to their staff. Table XII-1 summarizes the frequency 
and labor hour assumptions for this analysis.

         Table XII-1--Labor Hours for Drinking Water Systems Administrative and Monitoring Requirements
----------------------------------------------------------------------------------------------------------------
                                                                                   Small  system   Large  system
                  Activity                                Frequency                    hours           hours
----------------------------------------------------------------------------------------------------------------
Read the rule..............................  one time per system................               4               4
Provide initial training...................  one time per system................              16              32
Apply to State for monitoring waiver.......  once every 9 years per eligible                  16              16
                                              system.
Collect a single finished water sample \1\.  per monitoring event...............               1               1
----------------------------------------------------------------------------------------------------------------
Source (USEPA, 2000a). The EPA's cost analysis reflects full MCL compliance and therefore the EPA did not
  estimate Tier 1 notification costs.
\1\ The estimate is per sample. Therefore, a system conducting a year of quarterly monitoring at three entry
  points incurs a total of 12 hours of labor to complete the task (3 entry points x 4 samples x 1 hour per
  sample).

    Systems will incur monitoring costs over the analysis period. The 
EPA estimated monitoring frequency based on the proposed initial 
monitoring requirements, the standard monitoring framework requirements 
for inorganic contaminants, and the proposed implementation schedule. 
The estimated number of monitoring samples over the analysis period 
shown in Table XII-2 reflect the following phases:
    1. Initial monitoring; four quarterly samples at every CWS and 
NTNCWS entry point.
    2. Preliminary regular monitoring before waiver application: Three 
regular monitoring samples for every CWS and NTNCWS entry point 
(collected annually at surface water system entry points and 
triennially at ground water system entry points).
    3. Long-term monitoring at either (a) regular monitoring frequency 
for entry points at systems not granted waivers (60% of surface water 
system and 10% of ground water systems), or (b) reduced monitoring 
frequency for entry points at systems receiving waivers from primacy 
agencies (40% of surface water systems and 90% of ground water 
systems), which is one sample during every nine-year compliance 
monitoring cycle.

    Table XII-2--Estimates of Compliance Monitoring Samples by Phase and System Type, Size, and Source Water
----------------------------------------------------------------------------------------------------------------
                                                                                     Number of
   Monitoring phase  (sampling frequency)    System type, size, and source water   entry points      Aggregate
                                                                                        \1\         samples \2\
----------------------------------------------------------------------------------------------------------------
1. Initial monitoring (4 quarterly samples   All CWS and NTNCWS.................          92,656         370,624
 in one year).

[[Page 30550]]

 
2. Preliminary regular monitoring (3 annual  All CWS and NTNCWS.................          92,654         277,962
 entry point samples for surface water
 systems and 3 triennial entry point
 samples for ground water systems).
3a. Long-term monitoring, no waiver (annual  60% of large surface water CWS.....           3,324          86,424
 entry point samples).                       60% of small surface water CWS and            6,064         139,472
                                              all surface water NTNCWS.
3a. Long-term monitoring, no waiver          10% of large ground water CWS......             680           4,080
 (triennial entry point samples).            10% of small ground water CWS and             7,021          35,105
                                              all ground water NTNCWS.
3b. Long-term monitoring, waiver (1 sample   40% of large surface water CWS.....           2,216           4,432
 every 9 years).                             40% of small surface water CWS and            4,043           8,086
                                              all surface water NTNCWS.
3b. Long-term monitoring, waiver (1 sample   90% of large ground water CWS......           6,117          12,234
 every 9 years).                             90% of small ground water CWS and            63,189          63,189
                                              all ground water NTNCWS.
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
  0780).
\1\ The EPA estimated a total of 92,656 entry points based on the total number of potentially affected systems
  in SDWIS/FED and the average number of entry points per system in the UCMR 1 data by size category and source
  water. The initial monitoring phase includes all entry points. The EPA assumed that the two entry points with
  MCL exceedances at the proposed MCL of 56 [micro]g/L would continue to take quarterly samples for the duration
  of the analysis period, for a total of 232 samples. Thus, they are excluded from the estimates for the
  subsequent phases of regular and long-term monitoring. Primacy agencies may, however, allow monitoring to
  return to a regular schedule if treatment process operation can reliably and consistently reduce perchlorate
  below the MCL.
\2\ For Phase 3, the estimate of aggregate samples is the product of the number of entry points and the
  frequency of sampling during the remaining years of the analysis period. For example, large surface water CWS
  without a waiver conduct long-term annual monitoring for 26 years because they complete preliminary regular
  monitoring in year 9. In contrast, large ground water CWS without a waiver begin long-term triennial
  monitoring in year 16 because their preliminary regular monitoring phase lasts for 9 years (3 triennial
  samples) instead of 3 years (3 annual samples). The estimates also reflect schedule differences by size
  because large CWS begin monitoring schedules three years earlier than small CWS and all NTNCWS.

    To estimate costs to CWSs and NTNCWSs associated with time spent on 
compliance monitoring and other administrative costs, the EPA generally 
uses the labor rate \13\ for full-time treatment plant operators in 
CWSs from USEPA (2011c), which vary based on the size of the system. 
The EPA calculated a weighted average fully loaded hourly wage rate for 
water systems of $34.71.
---------------------------------------------------------------------------

    \13\ Updated to 2017$ using the BLS Employment Cost Index for 
Total Compensation for Private industry workers in Utilities.
---------------------------------------------------------------------------

    Additionally, the EPA assumed that systems will incur an average 
analytical cost of $64 per sample, which is the average cost per sample 
obtained from multiple laboratories for perchlorate quantitation using 
Method 314.0.
    To estimate treatment cost, the EPA utilized the occurrence data 
described in Section VI to estimate the number of system entry points 
that exceed the proposed and alternative MCLs. The EPA estimated costs 
that those water systems would incur to install and maintain treatment 
using its work breakdown structure (WBS) cost estimating models. The 
WBS models are spreadsheet-based engineering models for individual 
treatment technologies, linked to a central database of component unit 
costs. The WBS approach involves breaking a process down into discrete 
components for the purpose of estimating costs and produce a 
comprehensive assessment of the capital and operating requirements for 
a treatment system.\14\ The EPA used the WBS models to generate total 
capital and O&M cost estimates for each technology and nontreatment 
option for up to 49 different system flow rates. The EPA generated 
separate estimates that correspond to different water sources 
(groundwater or surface water), three different cost levels (low, mid, 
and high), and different technology-specific scenarios (e.g., 105,000 
or 170,000 bed volumes for ion exchange). The EPA used the mid-cost 
estimates for ion exchange to generate expected costs for all entry 
points requiring perchlorate removal. This technology cost-effectively 
removes perchlorate, but its ability to remove co-occurring 
contaminants depends on influent characteristics and process design. 
Therefore, the EPA did not assume that treatment might result in 
ancillary quantifiable or non-quantifiable benefits of removing co-
occurring ions such as nitrate. Treatment costs include waste disposal 
for spent resin, but do not include post-treatment costs for corrosion 
control because blending rates at most entry points should not result 
in much chloride addition or changes in corrosivity.
---------------------------------------------------------------------------

    \14\ The document Technologies and Costs for Treating 
Perchlorate-Contaminated Waters (USEPA, 2018c) contains more 
complete discussion of the WBS models and the cost estimating 
approach.
---------------------------------------------------------------------------

    For purposes of estimating the costs and benefits, the EPA assumed 
that CWSs and NTNCWSs in California and Massachusetts would not incur 
additional cost or realize benefits because these States currently 
regulate perchlorate at a more stringent level than the proposed MCL 
and alternative MCL. For each entry point in the UCMR 1 dataset outside 
of these two States, the EPA compared the maximum observed perchlorate 
concentration to the MCL to identify those that have an exceedance of 
the proposed MCL. The EPA assumed that these entry points would incur 
costs for an additional confirmation sample and would need to implement 
treatment to meet the MCL. For each entry point, the EPA estimated the 
design flow and the average flow by service populations based on the 
Agency's prior analysis of the relationships between these values 
(USEPA, 2000b). The Agency assumed blending of treated water and 
untreated water would be used to meet an average treatment target equal 
to 80 percent of the MCL (for an MCL of 56 [micro]g/L the blending 
target would be 45 [micro]g/L) given a 95 percent removal effectiveness 
until perchlorate breakthrough. The Agency applied the capital cost and 
O&M cost curves from the WBS models to the design and average flows 
adjusted for

[[Page 30551]]

blending. When small systems in the UCMR 1 sample incurred treatment 
costs, the EPA extrapolated the costs on a per capita basis to the 
estimate of national population exposure derived using the small system 
population sampling weights.
    For the primacy agencies that will implement and enforce the rule 
(including 49 States, one tribal nation and 5 territories), the EPA 
estimated upfront costs incurred during the three years between rule 
promulgation and the effective date to read and understand the rule, 
adopt regulatory changes, and provide training to CWSs and NTNCWSs and 
Agency staff. Primacy agencies will also have recurring costs to review 
waiver applications and monitoring reports. Table XII-3 summarizes the 
labor hour assumptions for these activities. The EPA requests comments 
on these assumptions.

 Table XII-3--Labor Hours for Primacy Agency Administrative Requirements
------------------------------------------------------------------------
            Activity                    Frequency              Hours
------------------------------------------------------------------------
Read and understand the rule,    one time per Agency....             416
 adopt regulatory changes \1\.
Provide initial training and     total per Agency.......           2,080
 assistance to water systems
 \2\.
Provide initial training to      total per Agency.......             250
 staff \2\.
Review waiver applications.....  once every 9 years per                8
                                  eligible system.
Review monitoring reports......  per monitoring event...               1
------------------------------------------------------------------------
Source (USEPA, 2000a).
\1\ The EPA assumed that two States that already regulate perchlorate in
  drinking water would not incur the incremental burdens in this table
  to regulate perchlorate under the proposed rule because they already
  incur baseline costs for perchlorate regulation including monitoring
  costs. The Agency assumed, however, that the two States would incur an
  average of 40 hours to confirm that their existing requirements are at
  least as protective as the proposed rule.
\2\ The EPA assumed that all training hours occur in a single year,
  although the hours may actually occur over time. The total hour
  estimates are average values across States.

    State labor rates are based on the mean hourly wage rate from 
Bureau of Labor Statistics (BLS) Standard Occupational Classification 
code 19-2041 (State Government--Environmental Scientists and 
Specialists, Including Health). Wages are loaded using a factor 
calculated from the BLS Employer Costs for Employee Compensation report 
(Bureau of Labor Statistics (BLS), 2016 Table 3), for a fully loaded 
hourly wage rate for States of $50.67. The EPA requests comments on 
these labor rate assumptions.
    The proposed rule provides three years between the effective dates 
and compliance dates for systems. For the purpose of estimating costs, 
the EPA assumed that large CWSs would phase in administrative costs, 
including initial monitoring, and upfront administrative costs 
uniformly over the 3 years following the effective date (i.e., years 4 
to 6 of the analysis period). Similarly, the EPA assumed that small 
CWSs and NTNCSs will phase in these costs over the subsequent three-
year period (i.e., years 7 to 9 of the analysis period). The EPA 
assumed that, within these periods, all systems would conduct initial 
monitoring--one year of quarterly monitoring to determine whether 
perchlorate concentrations are consistently and reliably below the 
proposed MCL. Thereafter, systems with MCL exceedances would continue 
to monitor quarterly, while systems below the MCL that obtain waivers 
will monitor annually for three years (surface water systems) or 
triennially for 9 years (ground water systems), then incur costs for a 
waiver application. Thereafter, these systems will continue reduced 
monitoring--once every nine years--under subsequent waivers. Systems 
that are below the MCL without waivers will monitor once per year 
(surface water systems) or once every three years (groundwater). 
Consistent with USEPA (2008b), the EPA assumed that 90% of groundwater 
and 40% of surface water systems that have all entry points below the 
MCL would obtain waivers.
    The EPA estimated the costs over a 35-year analysis period, which 
includes a 3-year period prior to the effective date to allow for State 
rule adoption activities, a 3-year period after the effective date to 
allow initial monitoring among large CWSs, and a 3-year period after 
that to allow initial monitoring for small CWSs and NTNCWSs. Evaluating 
costs over 35 years covers a full life cycle of the capital investments 
that large systems make in the 6th year; the WBS estimates of composite 
useful life of the equipment and infrastructure investment is 
approximately 30 years. The EPA assumed that treatment modifications 
will be completed in the final year of the initial monitoring period 
(i.e., year 6 of the analysis for large CWSs and year 9 for small CWSs 
and NTNCWSs). The EPA calculated the present value of total costs in 
each year of the analysis period and discounted to year 1 using both a 
3% and 7% discount rate and annualized total present value of costs at 
the same rates over 35 years to obtain a constant total annual cost 
estimate to compare to total annual benefits.
    Water systems typically recover costs through increased household 
rates, resulting in increased costs at the household level.\15\ To 
calculate the magnitude of the cost increase for systems that exceed 
the proposed MCL or alternative MCL, the EPA first estimated the number 
of households that may incur costs as a result of the rule based on the 
population served by affected CWSs and NTNCWSs and the average 
household size (U.S. Census Bureau, 2017b). The EPA divided the total 
annual system-level costs by the number of households served by the 
system.
---------------------------------------------------------------------------

    \15\ For systems with monitoring costs only, household-level 
costs will be negligible.
---------------------------------------------------------------------------

C. Method for Estimating Benefits

    The EPA has taken an approach in evaluating the benefits for 
perchlorate that is consistent with the SAB's recommendations for the 
methodology to inform the MCLG for perchlorate. This approach involves 
(a) using a BBDR model to estimate the impact of perchlorate on 
maternal thyroid hormone levels during the first trimester of 
pregnancy, and (b) using a dose-response function from the 
epidemiological literature to model the relationship between altered 
maternal thyroid hormone levels and offspring IQ. Currently available 
science has limited this quantitative benefits assessment to the 
relationship between perchlorate and IQ. Given that alterations in 
thyroid hormones have been associated with other adverse outcomes, 
including reproductive outcomes (Alexander et al., 2017; Hou et

[[Page 30552]]

al., 2016; Maraka et al., 2016) and effects on cardiovascular systems 
(Asvold et al., 2012; Sun et al., 2017) there are likely non-quantified 
benefits of risk reductions for other endpoints or reduced exposure to 
co-occurring contaminants, which are addressed below. Uncertainties 
regarding the quantifiable benefits are also addressed below.
    The population impacted by the rule for which benefits can be 
quantified is specific to live births from mothers who were served by a 
CWS or NTNCWS with perchlorate concentrations above the potential MCLs. 
To determine the nationwide population of children that will experience 
a quantifiable benefit of avoided IQ decrements from reducing maternal 
perchlorate exposure during pregnancy, the EPA first estimated the 
total population being served by systems above the MCL based on data 
from UCMR 1. The EPA then multiplied the total population served for 
each affected CWS and NTNCWS by the proportion of women of childbearing 
age (aged 15-44) in the US, which is 19.7 percent (U.S. Census Bureau, 
2017a). The number of women of child-bearing age for each entry point 
was then multiplied by the annual number of live births in the US, or 
62 births per 1,000 women (6.2 percent) (Martin, Hamilton, & Osterman, 
2017).
    The EPA used a two-step dose-response model to estimate health 
benefits of a reduction in perchlorate exposure as a result of 
regulating perchlorate in drinking water not to exceed the proposed MCL 
of 56 [mu]g/L and alternative MCLs of 18 [mu]g/L and 90 [mu]g/L. The 
first step relates changes in perchlorate to changes in maternal free-
thyroxine (fT4) during the first trimester of pregnancy using the EPA's 
BBDR model. Because the dose-response relationship between perchlorate 
exposure and maternal fT4 is dependent on maternal iodine intake 
status, this first-step analysis is repeated for several categories of 
iodine intake. For the BBDR simulations, the EPA used the 90th 
percentile ingestion rate to be consistent with the MCLG modeling 
approach, which may overstate the exposure in the simulation.
    The second step of the dose-response model subsequently relates the 
predicted changes in maternal fT4 from the BBDR model to changes in 
child IQ using the function estimated in the EPA independent analysis 
of the Korevaar et al., (2016) study data. Ultimately, the changes in 
IQ are estimated for each impacted iodine intake group, and all of the 
impacted iodine intake groups' IQ decrements are averaged together 
based on the proportion of individuals in each iodine intake category. 
Table XII-4 shows the specific iodine intake groups and the proportion 
of non-pregnant women of childbearing age that fall into each group.

  Table XII-4--Proportion of Population Based on Maternal Iodine Intake
                                 Status
------------------------------------------------------------------------
                                                              Proportion
                                                                of the
 Iodine intake range ([mu]g/day) used for benefits analysis   population
                                                                 (%)
------------------------------------------------------------------------
0 to <55...................................................         7.14
55 to <60..................................................         2.15
60 to <65..................................................         1.06
65 to < 70.................................................         1.86
70 to <75..................................................         1.31
75 to <80..................................................         3.10
80 to <85..................................................         2.62
85 to <90..................................................         1.20
90 to <95..................................................         1.83
95 to <100.................................................         2.94
100 to <125................................................        13.56
125 to <150................................................         9.08
150 to <170................................................        10.31
170 to <300................................................        24.47
>=300......................................................        17.36
------------------------------------------------------------------------
Source: U.S. EPA (2019a).

    These changes in child IQ are then monetized using the EPA's 
estimate of the value of an IQ point. This estimate reflects the 
discounted present value of lifetime income reductions attributable to 
a 1-point reduction in IQ at birth. Therefore, the present value 
depends on the discount rate. At a 3 percent discount rate, the 
estimate is $18,686 per IQ point; at a 7 percent discount rate the 
estimate is $3,631.
    Other potential benefits not quantified or monetized include 
additional avoided health effects which cannot currently be monetized, 
improved public perception of water quality, as well as a possible 
reduction of other co-occurring contaminants that target the thyroid, 
such as nitrate, as a result of water treatment for removal of 
perchlorate. For example, all of the treatment technologies evaluated 
for this rule (ion exchange, biological treatment, and reverse osmosis) 
can also remove co-occurring nitrate from drinking water. Section XIII 
provides additional discussion of uncertainties in this analysis.

D. Comparison of Costs and Benefits

    This section provides the estimates of costs and benefits that the 
EPA derived using the methods described above. It includes estimates 
for the proposed and alternative MCLs.
    For the proposed MCL of 56 [mu]g/L, Table XII-5 summarizes the 
total estimated cost of the proposed rule to water systems and primacy 
agencies, and Table XII-6 summarizes the estimated per-household cost 
for the system incurring treatment costs.\16\ Table XII-7 summarizes 
the estimated benefits. In both instances, the estimates based on the 
UCMR 1 sample are also national estimates because treatment costs occur 
only at large systems; there are no small system treatment costs or 
related benefits to extrapolate.
---------------------------------------------------------------------------

    \16\ For all households served by all of the systems subject to 
the monitoring costs as well as MCL compliance, the average annual 
cost is less than $0.20.

   Table XII-5--Summary of Total Annualized Costs at MCL of 56 [mu]g/L
                            [Millions; 2017$]
------------------------------------------------------------------------
             Cost component                 3% Discount     7% Discount
------------------------------------------------------------------------
Drinking Water Systems Treatment Costs..           $0.65           $0.70
Drinking Water Systems Monitoring and               5.93            6.38
 Administration Costs\1\................
Drinking Water Systems Costs Subtotal...            6.58            7.07
State Administration Costs..............            3.09            3.20
                                         -------------------------------
    Total Costs.........................            9.67           10.28
------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of
  independent rounding.

[[Page 30553]]

 
\1\ Costs include monitoring for all CWS and NTNCWS. Some consecutive
  systems that purchase 100% of their water from wholesale systems may
  not be required to monitor for perchlorate provided States allow
  integrated system agreements to include perchlorate among the
  monitoring requirements that the wholesale system fulfills for the
  consecutive system. The potential number of consecutive systems
  excluded from perchlorate monitoring depends on system and State
  decisions and, therefore, is unknown. Excluding monitoring costs for
  approximately 8,400 consecutive systems that do not report a water
  source facility (e.g., well or intake) in SDWIS/FED from the
  monitoring cost analysis reduces annualized monitoring costs by $0.8
  million.

    Table XII-6--Summary of Household-Level Annual Costs for Systems
                Treating to Comply with MCL at 56 [mu]g/L
                                 [2017$]
------------------------------------------------------------------------
               Cost range                   3% Discount     7% Discount
------------------------------------------------------------------------
Minimum.................................             $11             $14
Average.................................              40              47
Maximum.................................              69              80
------------------------------------------------------------------------
Source: (USEPA, 2019a).

      Table XII-7--Summary of Total Annualized Benefits of Avoided Lost IQ Decrements at MCL of 56 [mu]g/L
                                                [Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
                                                                   Annual delta
                  Korevaar [beta] distribution                          IQ          3% Discount     7% Discount
----------------------------------------------------------------------------------------------------------------
Upper...........................................................             243           $3.57           $0.60
Central.........................................................             136            2.00            0.34
Lower...........................................................              30            0.44            0.07
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).

    For the alternative MCL of 18 [mu]g/L, Table XII-8 summarizes the 
total cost of the proposed rule to water systems and primacy agencies, 
and Table XII-9 summarizes the per-household cost for systems requiring 
treatment, which vary across the systems. Table XII-10 summarizes the 
quantified benefits. At this threshold, one entry point for one small 
system in the UCMR 1 data had an exceedance. Therefore, the EPA 
extrapolated the treatment costs and benefits from the UCMR 1 estimates 
to national estimates based on sampling weights.

                       Table XII-8--Summary of Total Annualized Costs at MCL of 18 [mu]g/L
                                                [Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
                                                    3% Discount     7% Discount     3% Discount     7% Discount
                 Cost component                    (UCMR 1) \1\    (UCMR 1) \1\   (national) \1\  (national) \1\
----------------------------------------------------------------------------------------------------------------
Drinking Water Systems Treatment Costs..........           $6.92           $7.29           $7.92           $8.37
Drinking Water Systems Monitoring and                       5.94            6.38            5.94            6.38
 Administration Costs...........................
Drinking Water Systems Costs Subtotal...........           12.85           13.67           13.86           14.75
State Administration Costs......................            3.09            3.21            3.09            3.21
                                                 ---------------------------------------------------------------
    Total Costs.................................           15.95           16.88           16.95           17.96
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of independent rounding.
\1\ The EPA applied statistical sampling weights to the results to extrapolate small system results to national
  results. The entry point at which a measurement exceeds 18 [mu]g/L is one of 20 in its sample stratum; no
  other sample in the stratum had a measurement of perchlorate greater than the minimum reporting level. The
  entry point population of 2,155 represents 5.31% of the total population served by the six UCMR 1 systems in
  the stratum (40,574). Currently, the stratum population of 775,000 accounts for 1.32% of the 58.7 million
  national population served by small systems. Thus, the UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of
  small system customers (approximately 41,100) may be exposed to perchlorate greater than 18 [mu]g/L. The EPA
  calculated per-capita costs for the system and extrapolated to national level based on this population
  estimate.
\2\ Costs include monitoring for all CWS and NTNCWS. Under 40 CFR 141.29 some consecutive systems that purchase
  100% of their water from wholesale systems may not be required to monitor for perchlorate provided primacy
  agencies, with EPA concurrence, allow integrated system agreements to include perchlorate among the monitoring
  requirements that the wholesale system fulfills for the consecutive system. The potential number of
  consecutive systems excluded from perchlorate monitoring depends on system and primacy agency decisions and,
  therefore, is unknown. Excluding monitoring costs for approximately 8,400 consecutive systems that do not
  report a water source facility (e.g., well or intake) in SDWIS/FED from the monitoring cost analysis reduces
  annualized monitoring costs by $0.8 million.

Table XII-9--Summary of Household-Level Annual Costs for Systems Treating To Comply With the MCL at 18 [micro]g/
                                                        L
                                                     [2017$]
----------------------------------------------------------------------------------------------------------------
                                                    3% Discount     7% Discount     3% Discount     7% Discount
                   Cost range                      (UCMR 1) \1\    (UCMR 1) \1\   (national) \1\  (national) \1\
----------------------------------------------------------------------------------------------------------------
Minimum.........................................             $18             $24             $18             $24
Average.........................................              38              46              38              46

[[Page 30554]]

 
Max.............................................              72              84              72              84
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
\1\ National cost estimates include extrapolation for one small system entry point to national estimates based
  on sampling weights. The per-household costs are the same for the sample and national extrapolations because
  the small system cost extrapolation occurs on a per-capita basis.

                               Table XII-10--Total and Annualized Benefits of Avoided Lost IQ Decrements at 18 [micro]g/L
                                                                    [Millions; 2017$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                  Annual delta IQ                     UCMR 1                       National \1\
              Korevaar [beta] distribution               -----------------------------------------------------------------------------------------------
                                                              UCMR 1       National \1\     3% Discount     7% Discount     3% Discount     7% Discount
--------------------------------------------------------------------------------------------------------------------------------------------------------
Upper...................................................             442             447           $6.50           $1.10           $6.56           $1.11
Central.................................................             248             251            3.65            0.62            3.68            0.62
Lower...................................................              54              55            0.80            0.13            0.80            0.14
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).
\1\ The EPA applied statistical sampling weights to the results to extrapolate small system results to national results. The entry point at which a
  measurement exceeds 18 [micro]g/L is one of 20 in its sample stratum; no other sample in the stratum had a measurement of perchlorate greater than the
  minimum reporting level. The entry point population of 2,155 represents 5.31% of the total population served by the six UCMR 1 systems in the stratum
  (40,574). Currently, the stratum population of 774,780 accounts for 1.32% of the 58.7 million national population served by small systems. Thus, the
  UCMR 1 results indicate that 0.07% (5.31% x 1.32%) of small system customers (approximately 41,100) may be exposed to perchlorate greater than 18
  [micro]g/L. The EPA assumed that this population would incur benefits equivalent to the sampled entry point's population.

    For the alternative MCL of 90 [micro]g/L, Table XII-11 summarizes 
the total cost of the proposed rule to water systems and primacy 
agencies, and Table XII-12 summarizes the per-household cost for 
systems requiring treatment, which vary across the systems. Table XII-
13 summarizes the quantified benefits. At this threshold, no small 
systems in the UCMR 1 data had an exceedance. Therefore, treatment 
costs and benefits for the UCMR 1 data are the national estimates.

 Table XII-11--Summary of Total Annualized Costs at MCL of 90 [micro]g/L
                            [Millions; 2017$]
------------------------------------------------------------------------
             Cost component                 3% discount     7% discount
------------------------------------------------------------------------
Drinking Water Systems Treatment Costs..           $0.49           $0.52
Drinking Water Systems Monitoring and               5.93            6.37
 Administration Costs \1\...............
Drinking Water Systems Costs Subtotal...            6.42            6.89
State Administration Costs..............            3.09            3.20
                                         -------------------------------
    Total Costs.........................            9.51           10.10
------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of
  independent rounding.
\1\ Costs include monitoring for all CWS and NTNCWS. Some consecutive
  systems that purchase 100% of their water from wholesale systems may
  not be required to monitor for perchlorate provided States allow
  integrated system agreements to include perchlorate among the
  monitoring requirements that the wholesale system fulfills for the
  consecutive system. The potential number of consecutive systems
  excluded from perchlorate monitoring depends on system and State
  decisions and, therefore, is unknown. Excluding monitoring costs for
  approximately 8,400 consecutive systems that do not report a water
  source facility (e.g., well or intake) in SDWIS/FED from the
  monitoring cost analysis reduces annualized monitoring costs by $0.8
  million.

    Table XII-12--Summary of Household-Level Annual Costs for Systems
              Treating To Comply With MCL at 90 [micro]g/L
                                 [2017$]
------------------------------------------------------------------------
               Cost range                   3% Discount     7% Discount
------------------------------------------------------------------------
Minimum.................................             $65             $76
Average.................................              65              76
Maximum.................................              65              76
------------------------------------------------------------------------
Source: (USEPA, 2019a). There is no variation in costs because treatment
  costs occur at one entry point. The household costs are slight lower
  compared to the maximum cost at 56 [micro]g/L because treatment costs
  to meet an MCL of 90 [micro]g/L are lower than the costs to meet an
  MCL of 56 [micro]g/L.

[[Page 30555]]

    Table XII-13--Summary of Total Annualized Benefits of Avoided Lost IQ Decrements at MCL of 90 [micro]g/L
                                                [Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
                                                                   Annual delta
                  Korevaar [beta] distribution                          IQ          3% Discount     7% Discount
----------------------------------------------------------------------------------------------------------------
Upper...........................................................             222           $3.26           $0.55
Central.........................................................             124            1.83            0.31
Lower...........................................................              27            0.40            0.07
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a).

    Table XII-14 provides a comparison of benefits and costs for three 
MCL values. First, the table shows the total annual costs and total 
annual benefits for each MCL. In all cases, the total costs are 
substantially higher than the potential range of quantifiable benefits. 
The table also shows the incremental impact on costs and benefits 
between an MCL of 56 [micro]g/L and an MCL of 18 [micro]g/L and between 
an MCL of 90 [micro]g/L and 56 [micro]g/L.
    Section 1412(b)(4)(C) of the SDWA requires that when proposing a 
national primary drinking water regulation, ``the Administrator shall 
publish a determination as to whether the benefits of the maximum 
contaminant level justify, or do not justify, the costs.'' The 
infrequent occurrence of perchlorate at levels of health concern 
imposes high monitoring and administrative cost burdens on public water 
systems and the States. Based on a comparison of costs and benefits 
estimated at the proposed MCL of 56 [micro]g/L using the best available 
science and data, the EPA Administrator has determined based upon the 
available information that the benefits of establishing an NPDWR for 
perchlorate do not justify the associated costs.
    Under these circumstances, Section 1412(b)(6)(A) of the SDWA 
provides, with exceptions not relevant here, that ``the Administrator 
may, after notice and opportunity for public comment promulgate a 
maximum contaminant level for the contaminant that maximizes health 
risk reduction benefits at a cost that is justified by the benefits.'' 
The EPA has evaluated the benefits and costs of alternative MCL values 
of 18 [micro]g/L and 90 [micro]g/L. However, based upon the available 
information the Administrator also finds that the benefits of an NPDWR 
at the alternative MCL values would not justify the resulting rule 
costs. The alternative MCLs would not increase net benefits, while 
compliance costs associated mainly with nationwide CWS monitoring 
requirements would remain relatively similar. Consistent with the 
discretion afforded the Agency by SDWA Section 1412(b)(6)(A) to decide 
whether or not to adjust an MCL to a level where the benefits justify 
the costs, the EPA is however proposing, and may finalize, the MCL of 
56 [micro]g/L notwithstanding the Agency's determination that benefits 
would not justify the costs.

                          Table XII-14--Comparison of Annual Costs and Benefits by MCL
                                                [Millions; 2017$]
----------------------------------------------------------------------------------------------------------------
                                                     Cost 3%        Benefit 3%        Cost 7%       Benefit 7%
                   MCL value                        discount         discount        discount        discount
----------------------------------------------------------------------------------------------------------------
UCMR 1:
    90 [micro]g/L..............................           $9.51     $0.40-$3.26           $10.10     $0.07-$0.55
    56 [micro]g/L..............................            9.67       0.44-3.57            10.28       0.07-0.60
    18 [micro]g/L..............................           15.95       0.80-6.50            16.88       0.13-1.10
Incremental (from 90 [micro]g/L to 56 [micro]g/            0.16       0.04-0.31             0.18        0.0-0.05
 L)............................................
Incremental (from 56 [micro]g/L to 18 [micro]g/            6.28       0.36-2.93             6.60       0.06-0.50
 L)............................................
----------------------------------------------------------------------------------------------------------------
National:
    90 [micro]g/L..............................            9.51       0.40-3.26            10.10       0.07-0.55
    56 [micro]g/L \1\..........................            9.67       0.44-3.57            10.28       0.07-0.60
    18 [micro]g/L..............................           16.95       0.80-6.56            17.96       0.14-1.11
Incremental (from 90 [micro]g/L to 56 [micro]g/            0.16       0.04-0.31             0.18        0.0-0.05
 L)............................................
Incremental (from 56 [micro]g/L to 18 [micro]g/            7.28       0.36-2.99             7.69       0.07-0.51
 L)............................................
----------------------------------------------------------------------------------------------------------------
Source: (USEPA, 2019a). Detail may not sum to total because of independent rounding.
\1\ For the proposed MCL of 56 [micro]g/L and the alternative MCL of 90 [micro]g/L, the national estimates are
  the same as the estimates based on UCMR 1 data because there were no small system sample results to
  extrapolate to national small system estimates. At an MCL of 18 [micro]g/L, national estimates include
  extrapolation for one small system entry point to national estimates based on sampling weights described
  above.

XIII. Uncertainty Analysis

    The EPA has presented an extensive discussion of the uncertainties 
in the key analyses informing this proposal in the uncertainty section 
of the MCLG Approaches Report and the uncertainties section of the 
Economic Analysis document (USEPA, 2018b; USEPA, 2019a). A summarized 
description of these uncertainties are presented below.

A. Uncertainty in the MCLG Derivation

    Each input into the analysis to inform the MCLG is a decision point 
associated with uncertainty. There is uncertainty in different aspects 
of the BBDR model, ranging from structural and functional relationships 
to specific parameter values for early pregnancy. There are very few 
data available to calibrate the pharmacokinetic aspects of the model, 
particularly at the life stage of interest. Also, the BBDR model does 
not explicitly consider the effect of the presence of other goitrogens 
(e.g., thiocyanate, nitrate) or effects of thyroid disease states. 
Toxicodynamic aspects such as competitive inhibition at the NIS, 
depletion of iodide stores under different iodine intake levels and 
physiological states, and the ability of the TSH feedback loop to 
compensate for perturbations in thyroid function

[[Page 30556]]

each have their own uncertain features. Additional uncertainty is 
introduced by linking the BBDR model estimates of maternal fT4 to 
altered neurodevelopment in offspring. None of the studies used to 
evaluate potential adverse neurodevelopmental outcomes in offspring 
born to hypothyroxinemic mothers was performed in the U.S. None of the 
studies measured perchlorate exposure. Not all the studies measured 
iodide levels in the study populations. The state of the science on the 
relationship between maternal fT4 levels and offspring neurodevelopment 
is constantly evolving. There are numerous indices used to assess 
neurodevelopmental impacts and there is some uncertainty regarding the 
selection of IQ as the critical endpoint for setting the MCLG.
    A recently published paper evaluating the EPA's BBDR model and MCLG 
Approaches, reiterated the uncertainties the Agency identified in its 
analyses and questions the use of these quantitative tools for 
perchlorate in a regulatory context (Clewell et al., 2019).

B. Uncertainty in the Economic Analysis

    The EPA provides discussions regarding several sources of 
uncertainty in the benefit and cost estimates in the Health Risk 
Reduction and Cost Analysis (USEPA, 2019a). Table XIII-1 provides a 
summary of sources of uncertainty and their potential effects on 
estimated costs and benefits. The following discussion addresses 
uncertainties specific to the benefits analysis.

                            Table XIII-1--Sources of Uncertainty in Economic Analysis
----------------------------------------------------------------------------------------------------------------
                                Description                                          Potential effect \1\
----------------------------------------------------------------------------------------------------------------
                                               Baseline Occurrence
----------------------------------------------------------------------------------------------------------------
UCMR 1 data are more than one decade old; actual occurrence could be lower    (benefits and costs
 (e.g., because of contaminant cleanup) or higher (e.g., because new          will change in the same
 systems use perchlorate-contaminated source water).                          direction).
UCMR 1 data include a sample of small systems; the Stage 1 results (entry    - (benefits and costs will change
 point maximums) indicate that no small systems would exceed 56 [micro]g/L    in the same direction).
 or 90 [micro]g/L and that one small system would exceed 18 [micro]g/L; it
 is possible that there are additional small systems where the baseline
 perchlorate is greater than the MCLs that are not captured in the national
 extrapolation results.
The EPA assumed a uniform distribution of system population served across     (benefits and costs
 the entry points; the actual entry point service population could be         will change in the same
 greater than or less than the estimates.                                     direction).
----------------------------------------------------------------------------------------------------------------
                                                Benefits Analysis
----------------------------------------------------------------------------------------------------------------
The health risks and risk reductions are based on maximum recorded            (benefits only).
 concentration estimates and thus do not account for exposures to
 concentrations greater than or less than this recorded maximum.
The EPA assumed that baseline fT4 is equal to the median, which likely       - (benefits only).
 underestimates disease benefits as the logarithmic relationship between
 maternal fT4 and child IQ leads to larger relative changes in fT4, with
 increasing levels of perchlorate and lower levels of baseline fT4.
The EPA assumed a median TSH feedback loop strength for the exposed           (benefits only).
 population does not incorporate the variability in the feedback mechanism
 of the body's creation of TSH in response to decreasing fT4.
The EPA used a 90th percentile water intake rate to derive the MCLG and the  + (benefits only).
 dose-response equations for the benefits analysis. This approach results
 in a protective MCLG value, but may overstate intake for the benefits
 analysis \2\.
The IQ valuation uses estimates that the EPA derived using the same           (benefits only).
 approach as Salkever (1995). Results from other IQ valuation studies might
 result in higher or lower benefit estimates.
The benefits analysis is based on a single health endpoint and the value of  - (benefits only).
 the endpoint is based solely on lost earnings.
----------------------------------------------------------------------------------------------------------------
                                                  Cost Analysis
----------------------------------------------------------------------------------------------------------------
The EPA assumed that systems requiring treatment would incorporate a safety  + (benefits and costs will change
 factor--treating to 80% of the proposed MCL or alternative MCL, which        in the same direction).
 increases costs and benefits.
The EPA assumed that all entry points requiring treatment would implement     (costs only).
 ion exchange, which may overestimate costs if non-treatment is an option
 for one or more entry points or underestimate costs if site-specific
 conditions result in higher costs at one or more entry points.
The EPA developed a monitoring schedule that assumed a uniform distribution   (costs only).
 of initial monitoring costs over three years; actual costs will vary.
The EPA assumed that long-term monitoring costs would occur in the last      - (costs only).
 year of the applicable three-year monitoring period or nine-year
 monitoring cycle; systems may conduct monitoring in an earlier year of the
 period or cycle.
The EPA assumed that 90% of ground water systems and 40% of surface water     (costs only).
 systems obtain perchlorate monitoring waivers; the actual percentages may
 vary.
----------------------------------------------------------------------------------------------------------------
\1\ A ``-'' symbol indicates that benefits and/or costs will tend to be underestimated. A ``+'' symbol indicates
  that benefits and/or costs will tend to be overestimated. A ``'' symbol indicates an unknown
  direction of uncertainty, i.e., benefits and/or costs could be underestimated or overestimated.
\2\ The EPA did not include a perchlorate dietary dose in the benefits analysis, which would be unchanged
  between baseline and proposed MCL scenarios if many areas do not irrigate with drinking water. For people who
  obtain a significant portion of their fruit, vegetables, and milk from areas irrigated with the water from the
  same sources as the drinking water, we would expect their exposure may drop with the reduction of perchlorate
  in food products used locally. Because of this and the natural log form of the IQ response function, this
  approach may slightly understate the avoided IQ decrement estimates.

    The EPA acknowledges the uncertainty regarding the quantitative 
health risk reduction. In particular, the Agency assumed it could 
estimate risk reductions based on evidence of a quantifiable 
relationship between thyroid hormone changes and neurodevelopmental 
outcomes.

[[Page 30557]]

    There are a number of potential benefits of reducing perchlorate in 
drinking water that were not quantified as part of this analysis, which 
may result in an underestimate of actual benefits. As described by the 
SAB ``children exposed gestationally to maternal hypothyroxinemia 
(without hypothyroidism) show reduced levels of global and specific 
cognitive abilities, as well as increased rates of behavior problems 
including greater dysregulation in early infancy and attentional 
disorders in childhood (Man et al., 1991; Pop et al., 1999; Pop et al., 
2003; Kooistra et al., 2006)'' (p. 10, SAB for the U.S. EPA, 2013). The 
EPA's literature review identified potential relationships between 
maternal thyroid hormone alterations and the risk of schizophrenia, 
ADHD, expressive language delay, reduced school performance and 
increased odds of autism, among others, none of which are being 
currently quantified in this assessment. Other potentially omitted 
benefits include risks associated with effects of thyroid disorders in 
adults, including cardiovascular disease risk; changes in thyroid 
hormone levels and their relationship with total cholesterol, LDL 
cholesterol, and triglycerides; as well as a possible relationship 
between increases in TSH and risk of fatal coronary heart disease. 
Treating for perchlorate in drinking water could also potentially 
remove nitrate, which is a co-occurring contaminant and a goitrogen. 
These additional potential health endpoints are not monetized in this 
benefits analysis. The assumptions used to account for the previously 
mentioned variability of the BBDR model inputs and uncertainty 
surrounding the relationship between maternal fT4 and child IQ 
discussed above may result in an overestimate of the monetized 
benefits. Because IQ is a surrogate for broad range of potential 
neurodevelopmental risks, it is unclear whether the analysis as a whole 
over- or under-estimates the monetized benefits of a reduction of 
perchlorate in drinking water.

XIV. Request for Comment on Proposed Rule

    While all comments relevant to the national primary drinking water 
regulation for perchlorate proposed today will be considered by the 
EPA, comments on the following issues will be especially helpful to the 
EPA in developing a final rule. The EPA specifically requests comment 
on the following topics.
     The adequacy and uncertainties of the BBDR model developed 
by the EPA to predict thyroid hormone level changes caused by 
perchlorate exposure to pregnant women with low iodide intake, 
including the model and model parameters and assumptions (Section III 
and Approaches Report).
     The adequacy and uncertainties of the EPA's review and 
application of the epidemiologic literature to quantify the 
relationship between thyroid hormone changes in pregnant women and 
neurodevelopmental effects including the assumptions, the selection of 
the approach used, and the study used (Section III and Approaches 
Report).
     The adequacy and uncertainties of the methodology to 
derive the MCLG including points of departure, assumptions, uncertainty 
factor, and relative source contribution (Section III and Technical 
Support Document: Deriving a Maximum Contaminant Level Goal for 
Perchlorate in Drinking Water).
     The proposed MCLG and MCL of 56 [micro]g/L as well as the 
alternative MCLG and MCL values of 18 [micro]g/L and of 90 [micro]g/L.
     The feasibility of the proposed MCL of 56 [micro]g/L as 
well as the feasibility of the alternative MCLs of 18 [micro]g/L and 90 
[micro]g/L.
     The adequacy of the underlying assumptions and analysis of 
occurrence (Section VI).
     The costs and availability of Treatment Technologies 
(Section X).
     The adequacy of the underlying estimates, assumptions and 
analysis used to estimate costs and describe unquantified costs 
including the estimates of monitoring frequency, likelihood of systems 
receiving a monitoring waiver, the administrative labor rate and the 
operator labor rate. (Section XII and the Health Risk Reduction Cost 
Analysis).
     The adequacy of the underlying estimates, assumptions and 
analysis used to estimate benefits and describe unquantified benefits 
(Section XII and the Health Risk Reduction Cost Analysis).
     Potential implementation challenges associated with the 
proposed perchlorate regulation that the EPA should consider, 
specifically for small systems.
     The Administrator's finding in accordance with Section 
1412(b)(4)(C) of the SDWA that the benefits of the proposed 56 
[micro]g/L MCL for perchlorate do not justify the costs, and the 
information that supports that determination as described in Section 
XII of this notice.
     The Administrator's proposal to, consistent with the 
discretion afforded him by SDWA Section 1412(b)(6)(A), adopt an MCL of 
56 [micro]g/L notwithstanding the Agency's SDWA Section 1412(b)(4)(C) 
determination that the benefits of the MCL would not justify its costs.
     The Agency's conclusion that no alternative MCL, including 
the alternative MCL values of 18 [micro]g/L and 90 [micro]g/L discussed 
above, would ``maximize health risk reduction benefits at a cost that 
is justified by the benefits'' and the information and analytical 
approaches used to arrive at that conclusion. The EPA is especially 
interested in comments suggesting other approaches to deriving an MCL 
for which the benefits justify the costs.

XV. Request for Comment on Potential Regulatory Determination 
Withdrawal

    The EPA is soliciting comments on withdrawing the 2011 Regulatory 
Determination (see Section II-C, Regulatory History) based on several 
factors. First, the findings, described in the occurrence section 
(section VI) and in the updated health effects assessment (Section 
III), suggest that perchlorate does not occur in public water systems 
with a frequency and at levels of public health concern \17\ and 
suggest that the regulation of perchlorate does not present a 
meaningful opportunity for health risk reduction for persons served by 
public water systems. The proposed regulation would require over sixty 
thousand public water systems to monitor for perchlorate, but the 
available data indicates that very few would find it at levels of 
public health concern. Specifically, perchlorate occurrence information 
suggests that at an MCL of 56 [micro]g/L only 2 systems (0.004% of all 
water systems in the U.S.) would exceed the regulatory threshold. Even 
at an MCL of 18 [micro]g/L, there would only be 15 systems (0.03% of 
all water systems in the U.S.) that would exceed the regulatory 
threshold. Only one system would exceed the alternative MCL of 90 
[micro]g/L.
---------------------------------------------------------------------------

    \17\ As shown in Section VI of this notice there is infrequent 
occurrence of perchlorate at either 56 [micro]g/L, 18 [micro]g/L or 
90 [micro]g/L, which are the possible levels expected to cause 
adverse human health effects.
---------------------------------------------------------------------------

    The EPA notes that in 2008, the EPA stated in its preliminary 
regulatory determination that perchlorate did not occur with a 
frequency and at levels of public health concern in public water 
systems based upon the health effects and occurrence information 
available at that time, which indicated that 0.8% of public water 
system had perchlorate at levels exceeding the HRL of 15 [micro]g/L. 
The EPA also stated that there was not a meaningful opportunity for a 
NPDWR to reduce health risks based upon the estimates at that time that 
0.9 million

[[Page 30558]]

people had perchlorate levels above the HRL.
    The EPA further notes that the Agency has previously determined 
CCL1 and CCL2 contaminants did not occur with frequency at levels of 
public health concern when the percentage of water systems exceeding 
the HRL were greater than the frequency of perchlorate occurrence level 
at the proposed MCL (0.004% of all water systems in the U.S.). For 
example, in 2003 the EPA determined that aldrin did not occur with a 
frequency and at levels of public health concern based upon data that 
showed 0.2% of water systems had aldrin at levels greater than the HRL. 
The EPA also concluded that there was not a meaningful opportunity for 
health risk reduction for persons served through a drinking water 
regulation based on this occurrence data and the estimate that these 
systems above the HRL served approximately 1 million people (USEPA, 
2003). In 2008 the EPA determined that DCPA Mono- and Di-Acid 
degradates did not occur with a frequency and at levels of public 
health concern based on data that showed 0.03% of water systems 
exceeded the HRL. The EPA also included that there was not a meaningful 
opportunity for health risk reduction through a drinking water 
regulation based on this occurrence data and the estimate that these 
systems above the HRL served approximately 100,000 people (USEPA, 
2008e).
    SDWA Section 1412(b)(1)(A)(iii) states that the determination 
regarding the meaningful opportunity is ``in the sole judgement of the 
Administrator'' and therefore there may be other factors that 
contribute to this determination for any given contaminant.
    If, after consideration of public comment, the EPA withdraws the 
perchlorate regulatory determination, there will be no NPDWR for 
perchlorate, although the EPA can re-list perchlorate on the CCL and 
proceed to regulation in the future if the occurrence or risk 
information changes. As with other unregulated contaminants, the EPA 
could address the limited instances of elevated levels of perchlorate 
by working with the states or using its SDWA Section 1431 imminent and 
substantial endangerment or Section 1412(b)(1)(f) health assessment 
authorities, as appropriate. The EPA also requests comments on what 
guidance it could provide the public if the regulatory determination 
for perchlorate is withdrawn.

XVI. Statutory and Executive Order Reviews

A. Executive Order 12866: Regulatory Planning and Review and Executive 
Order 13563: Improving Regulation and Regulatory Review

    This action is a significant regulatory action since it raises 
novel legal or policy issues. It was submitted to the Office of 
Management and Budget (OMB) for review. Any changes made in response to 
OMB recommendations have been documented in the docket.
    The EPA evaluated the potential costs to States and utilities and 
the potential benefits of the proposed rule. This analysis, Health Risk 
Reduction Cost Analysis of the Proposed Perchlorate Rule (USEPA, 2019a) 
is available in the docket and is summarized in section XI.

B. Executive Order 13771: Reducing Regulations and Controlling 
Regulatory Costs

    This action is expected to be an Executive Order 13771 regulatory 
action. Details on the estimated costs of this proposed rule can be 
found in the EPA's analysis of the potential costs and benefits 
associated with this action.

C. Paperwork Reduction Act

    The information collection requirements in this proposed rule have 
been submitted for approval to the Office of Management and Budget 
(OMB) under the Paperwork Reduction Act, 44 U.S.C. 3501 et seq. The 
information collection requirements are not enforceable until OMB 
approves them.
    The monitoring information collected as a result of this rule will 
allow the States and the EPA to evaluate compliance with the rule. For 
the first 3-year period following rule promulgation, the major 
information requirements concern primacy agency activities to implement 
the rule including adopting the NPDWR into state regulations, providing 
training to state and PWS employees, updating their monitoring data 
systems, and reviewing system monitoring data and waiver requests. 
Compliance actions for drinking water systems (including monitoring, 
administration, and treatment costs) would not begin until after Year 3 
due to the proposed effective date of this rule.
    The estimate of annual average burden hours for the proposed rule 
during the first three years following promulgation is 48,539 hours. 
The annual average cost estimate is $7.4 million for labor. The burden 
hours per response is 2,648 hours and the cost per response is 
$134,159. The frequency of response (average responses per respondent) 
is 1 for primacy agencies, annually (for upfront administrative 
activities to implement the rule). The estimated number of likely 
respondents is 55 over the three-year period (for an average of 18.3 
each year).
    Burden means the total time, effort, or financial resources 
expended by persons to generate, maintain, retain, or disclose or 
provide information to or for a federal agency. This includes the time 
needed to review instructions; develop, acquire, install, and utilize 
technology and systems for the purposes of collecting, validating, and 
verifying information, processing and maintaining information, and 
disclosing and providing information; adjust the existing ways to 
comply with any previously applicable instructions and requirements; 
train personnel to be able to respond to a collection of information; 
search data sources; complete and review the collection of information; 
and transmit or otherwise disclose the information.
    An agency may not conduct or sponsor, and a person is not required 
to respond to a collection of information unless it displays a 
currently valid OMB control number. The OMB control numbers for the 
EPA's regulations are listed in 40 CFR part 9.
    Submit your comments on the Agency's need for this information, the 
accuracy of the provided burden estimates, and any suggested methods 
for minimizing respondent burden, including the use of automated 
collection techniques, to the EPA at the public docket established for 
this rule, which includes the ICR, Docket ID No. EPA-HQ-OW-2018-0780. 
You may also send your ICR-related comments to OMB's Office of 
Information and Regulatory Affairs via email to 
OIRA_submission@omb.eop.gov, Attention: Desk Officer for the EPA. Since 
OMB is required to make a decision concerning the ICR between 30 and 60 
days after receipt, OMB must receive comments no later than [INSERT 
DATE 30 DAYS AFTER DATE OF PUBLICATION IN THE FEDERAL REGISTER]. The 
EPA will respond to any ICR-related comments in the final rule.

D. Regulatory Flexibility Act (RFA)

    I certify that this action will not have a significant economic 
impact on a substantial number of small entities under the RFA. The 
Agency has determined that the proposed MCL of 56 [micro]g/L will not 
result in annual costs that exceed one percent of revenue for small 
systems affected by the proposed rule.
    The small entities subject to the requirements of this action are 
public

[[Page 30559]]

water systems serving 10,000 or fewer persons. This is the threshold 
specified by Congress in the 1996 Amendments to the Safe Drinking Water 
Act for small system flexibility provisions. In accordance with the RFA 
requirements, the EPA proposed using this alternative definition in the 
Federal Register, (63 FR 7620, February 13, 1998), requested public 
comment, consulted with the Small Business Administration (SBA), and 
expressed its intention to use the alternative definition for all 
future drinking water regulations in the Consumer Confidence Reports 
regulation (63 FR 44511, August 19, 1998). As stated in that final 
rule, the alternative definition is applied to this proposed 
regulation.
    The proposed rule contains provisions that would affect 58,325 CWS 
and NTNCWS serving 10,000 or fewer people. In order to meet the 
proposed rule requirements, all of these systems will need to conduct 
perchlorate monitoring. At the proposed MCL of 56 [micro]g/L, the UCMR 
1 monitoring data indicate that no small systems would be required to 
incur costs to reduce the levels of perchlorate in drinking water, 
therefore, all small PWSs will incur monitoring costs only. Impacts on 
small entities are described in more detail in Chapter 7 of the Health 
Risk Reduction Cost Analysis of the Proposed Perchlorate Rule (USEPA, 
2019a). Table XII-1 and Table XII-2 show the annual compliance costs of 
the proposed rule on the small entities by system size for public and 
private systems, respectively. Based on a comparison of annual costs 
with annual revenue estimates, the EPA has determined that no small 
systems will experience an impact of one percent or greater of average 
annual revenues (USEPA 2019a).

 Table XII-1--Annualized Monitoring and Administrative Costs as a Percentage of Average Annual Revenue for Small
                                          Public CWSs by Size Category
----------------------------------------------------------------------------------------------------------------
                                                                      Average
                          Size category                               annual        3% Discount     7% Discount
                                                                   revenues \a\         \b\             \b\
----------------------------------------------------------------------------------------------------------------
Population served <100..........................................        $224,248     $88 (0.04%)     $94 (0.04%)
Population served 101-500.......................................         197,315      88 (0.04%)      94 (0.05%)
Population served 501-3,300.....................................         202,382      88 (0.04%)      94 (0.05%)
Population served 3,301-10,000..................................       1,092,187      88 (0.01%)      94 (0.01%)
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
  0780).
\a\ Based on the CWSS (USEPA, 2009c Table 65) and updated to 2017$ based on the chained consumer price index for
  fuels and utilities in U.S. city average, all urban consumers (BLS, 2018a). Revenues include all sources of
  revenue including water revenue, non-water revenue, and municipal transfers to water systems.
\b\ Total annual monitoring and administrative costs for PWSs are approximately $6.6 million to $7.1 million
  annually (Exhibit 5 5), with $5.1 million to $5.5 million accruing to small PWSs. Based on 58,325 small
  systems, this yields an average annual per-system cost of $88 (3% discount rate) to $94 (7% discount rate).

 Table XII-2--Annualized Monitoring and Administrative Costs as a Percentage of Average Annual Revenue for Small
                                          Private CWSs by Size Category
----------------------------------------------------------------------------------------------------------------
                                                                      Average
                          Size category                               annual        3% Discount     7% Discount
                                                                   revenues \a\         \b\             \b\
----------------------------------------------------------------------------------------------------------------
Population served <100..........................................        $139,911     $88 (0.06%)     $94 (0.07%)
Population served 101-500.......................................         351,974      88 (0.03%)      94 (0.03%)
Population served 501-3,300.....................................         254,706      88 (0.03%)      94 (0.03%)
Population served 3,301-10,000..................................         951,692      88 (0.01%)      94 (0.01%)
----------------------------------------------------------------------------------------------------------------
Source: Perchlorate Benefit-Cost Analysis Spreadsheet available in the proposed rule docket (EPA-HQ-OW-2018-
  0780)
\a\ Based on the CWSS (USEPA, 2009c Table 65) and updated to 2017$ based on the chained consumer price index for
  fuels and utilities in U.S. city average, all urban consumers (BLS, 2018a). Revenues include all sources of
  revenue including water revenue and non-water revenue.
\b\ Total annual monitoring and administrative costs for PWSs are approximately $6.6 million to $7.1 million
  annually (Exhibit 5 5), with $5.1 million to $5.5 million accruing to small PWSs. Based on 58,325 small
  systems, this yields an average annual per-system cost of $88 (3% discount rate) to $94 (7% discount rate).

E. Unfunded Mandates Reform Act

    This action does not contain an unfunded mandate of $100 million or 
more as described in UMRA, 2 U.S.C. 1531-1538. The action imposes 
minimal enforceable duty on any state, local or tribal governments or 
the private sector.
    Based on the cost estimates detailed in Section XI, the EPA 
determined that compliance costs in any given year would be below the 
threshold set in UMRA, with maximum single-year costs of approximately 
$10.2 million. The EPA has determined that this rule contains a federal 
mandate that would not result in expenditures of $100 million or more 
for State, local, and Tribal governments, in the aggregate, or the 
private sector in any one year.

F. Executive Order 13132: Federalism

    This action does not have federalism implications. It will not have 
substantial direct effects of greater than $25 million on the states, 
on the relationship between the national government and the states, or 
on the distribution of power and responsibilities among the various 
levels of government. Annual costs are estimated to range from $9.6 
million at a 3 percent discount rate to $10.2 million using a 7 
percent, with $6.5 million to $7.0 million annually accruing to public 
entities. The EPA has concluded that this proposed rule may be of 
interest because it may impose direct compliance costs on State or 
local governments, and the federal government will not provide the 
funds necessary to pay those costs.

G. Executive Order 13175: Consultation and Coordination With Indian 
Tribal Governments

    The EPA has concluded that this proposed rule may have Tribal 
implications, because it may impose direct compliance costs on Tribal 
governments, and the federal government would not provide the

[[Page 30560]]

funds necessary to pay those costs. The EPA has identified 768 water 
systems with 1,167 entry points under Native American ownership that 
may be subject to the proposed rule. They would bear an estimated total 
annualized cost of $74,100 at a 3 percent discount rate ($79,625 at 7 
percent) to implement this rule as proposed, with all costs 
attributable to monitoring and administrative costs. Estimated average 
annualized cost per system ranges from $96 at a 3 percent discount rate 
to $104 at a 7 percent discount rate.
    Accordingly, the EPA provides the following Tribal summary impact 
statement as required by section 5(b) of Executive Order 13175. The EPA 
consulted with representatives of Tribal officials early in the process 
of developing this proposed regulation to permit them to have 
meaningful and timely input into its development. The EPA conducted 
consultation with Indian Tribes which included a webinar with 
interested tribes on February 28, 2012, to request input and provide 
rulemaking information to interested parties. A meeting summary report 
is available on the docket for public inspection (USEPA 2012a). The EPA 
notes that 751 of the 768 Tribal systems identified by the Agency as 
subject to the proposed rule are small systems that are expected to 
incur only monitoring costs. Due to the health risks associated with 
perchlorate, capital expenditures needed for compliance with the rule 
would be eligible for federal funding sources, specifically the 
Drinking Water State Revolving Fund. In the spirit of Executive Order 
13175, and consistent with the EPA policy to promote communications 
between the EPA and Tribal governments, the EPA specifically solicits 
additional comment on this proposed rule from Tribal officials.

H. Executive Order 13045: Protection of Children From Environmental 
Health and Safety Risks

    This action is not subject to Executive Order 13045 because it is 
not economically significant as defined in Executive Order 12866; 
however, the environmental health risk addressed by this action may 
have a disproportionate effect on children. Accordingly, the EPA 
evaluated the environmental health or safety effects of perchlorate on 
children. The results of this evaluation are contained in the Health 
Effects Technical Support Document (USEPA 2018a) and described in 
section III of this preamble. The EPA has evaluated the risk associated 
with perchlorate in drinking water for the sensitive subpopulation--
offspring of pregnant women exposed to perchlorate during the first 
trimester--and established a proposed MCLG that is protective of this 
subpopulation as well as other children. The EPA also estimated the 
health risk reduction of the proposed and alternative MCLs. This 
analysis is described in the Health Risk Reduction and Cost Analysis 
for the proposed rule (USEPA 2019a) and is summarized in section XI of 
this preamble. Copies of the Health Effects Technical Support Document 
and Economic Analysis and supporting information are available in the 
public docket for today's proposal.

I. Executive Order 13211: Actions That Significantly Affect Energy 
Supply, Distribution, or Use

    This rule is not a ``significant energy action'' as defined in 
Executive Order 13211, ``Actions Concerning Regulations That 
Significantly Affect Energy Supply, Distribution, or Use'' (66 FR 28355 
(May 22, 2001)) because it is not likely to have a significant adverse 
effect on the supply, distribution, or use of energy. This 
determination is based on the following analysis.
    The first consideration is whether the proposed rule would 
adversely affect the supply of energy. The proposed rule does not 
regulate power generation, either directly or indirectly. The public 
and private water systems that the proposed rule regulates do not 
generate power. Further, the cost increases borne by customers of water 
utilities as a result of the proposed rule are a low percentage of the 
total cost of water, except for a few water systems that might install 
treatment technologies and would likely spread that cost over their 
customer base. In sum, the proposed rule does not regulate the supply 
of energy, does not generally regulate the utilities that supply 
energy, and is unlikely to affect significantly the customer base of 
energy suppliers. Thus, the proposed rule would not translate into 
adverse effects on the supply of energy.
    The second consideration is whether the proposed rule would 
adversely affect the distribution of energy. The proposed rule does not 
regulate any aspect of energy distribution. The water systems that are 
regulated by the proposed rule already have electrical service. At the 
proposed MCL, one entry point at one system may require incremental 
power to operate new treatment processes. The increase in peak 
electricity demand at water utilities is negligible. Therefore, the EPA 
estimates that the existing connections are adequate and that the 
proposed rule has no discernable adverse effect on energy distribution.
    The third consideration is whether the proposed rule would 
adversely affect the use of energy. Because only one system is expected 
to add treatment technologies that use electrical power, this potential 
impact on sector demand or overall national demand for power is 
negligible.
    Based on its analysis of these considerations, the EPA has 
concluded that proposed rule is not likely to have a significant 
adverse effect on the supply, distribution, or use of energy.

J. National Technology Transfer and Advancement Act of 1995 and 1 CFR 
Part 51

    The proposed rule could involve voluntary consensus standards in 
that it would require monitoring for Perchlorate. The EPA proposed five 
analytical methods for the identification and quantification of 
perchlorate in drinking water. The EPA methods 314.0, 314.1, 314.2, 
331.0, and 332.0 incorporate quality control criteria which allow 
accurate quantitation of perchlorate. Additional information about the 
analytical methods is available in section VII of this notice. The EPA 
has made, and will continue to make, these documents generally 
available through www.regulations.gov and at the U.S. Environmental 
Protection Agency Drinking Water Docket, William Jefferson Clinton West 
Building, 1301 Constitution Ave. NW, Room 3334, Washington, DC 20460, 
call (202) 566-2426.
    The EPA's monitoring and sampling protocols generally include 
voluntary consensus standards developed by agencies such as ASTM 
International, Standard Methods and other such bodies wherever the EPA 
deems these methodologies appropriate for compliance monitoring. The 
EPA welcomes comments on this aspect of the proposed rulemaking and, 
specifically, invites the public to identify potentially-applicable 
voluntary consensus standards and to explain why such standards should 
be used in this regulation. The Director of the Federal Register 
approved the voluntary consensus standards incorporated by referenced 
in Sec.  141.23 of the proposed regulatory text as of April 11, 2007.

K. Executive Order 12898: Federal Actions To Address Environmental 
Justice in Minority Populations and Low-Income Populations

    The EPA has determined that this proposed rule would not have 
disproportionately high and adverse

[[Page 30561]]

human health or environmental effects on minority or low-income 
populations because it would increase the level of environmental 
protection for all affected populations without having any 
disproportionately high and adverse human health or environmental 
effects on any population, including any minority or low-income 
population.
    The public is invited to comment on this aspect of the proposed 
rulemaking and, specifically, to recommend additional methods to 
address Environmental Justice concerns from establishing a drinking 
water rule for perchlorate in drinking water.

XVII. Consultations With the Science Advisory Board, National Drinking 
Water Advisory Council, and the Secretary of Health and Human Services

    In accordance with sections 1412(d) and 1412(e) of the Safe 
Drinking Water Act (SDWA), the Agency consulted with the National 
Drinking Water Advisory Council (NDWAC or the Council); the Secretary 
of Health and Human Services; and with the EPA Science Advisory Board. 
The Agency consulted with NDWAC during the Council's October 4-5, 2012 
meeting. A summary of the NDWAC recommendations is available in the 
National Drinking Water Advisory Council, Fall 2012 Meeting Summary 
Report (NDWAC, 2012b) and the docket for this proposed rule. The EPA 
carefully considered NDWAC recommendations during the development of a 
proposed drinking water rule for perchlorate.
    On May 29, 2012, the EPA sought guidance from the EPA Science 
Advisory Board (SAB) on how best to consider and interpret life stage 
information, epidemiological and biomonitoring data since the 
publication of the National Research Council 2005 report, the Agency's 
physiologically-based pharmacokinetic (PBPK) analyses, and the totality 
of perchlorate health information to derive a Maximum Contaminant Level 
Goal (MCLG) for perchlorate (USEPA, 2012; NRC, 2005). On May 29, 2013, 
the EPA received significant input from SAB, summarized in the report, 
SAB Advice on Approaches to Derive a Maximum Contaminant Level Goal for 
Perchlorate (USEPA, 2013a).
    On July 15, 2013, the EPA responded by stating that the Agency 
would consider all the recommendations from the SAB, as it continued 
working on the development of the rulemaking process for perchlorate 
(USEPA 2013b). To address SAB recommendations, the EPA collaborated 
with Food and Drug Administration (FDA) scientists to develop PBPK/
pharmacodynamic (PD), or biologically based dose-response (BBDR), 
models that incorporate all available health related information on 
perchlorate to predict changes in thyroid hormones in sensitive life 
stages exposed to different dietary iodide and perchlorate levels 
(USEPA 2017). As recommended by SAB, the EPA developed these models 
based upon perchlorate's mode of action (i.e., iodide uptake inhibition 
by the thyroid) (USEPA 2013a). Additional details are in section III.C. 
of this notice and in the Health Effects of Perchlorate support 
document located in the docket for this proposed rule.
    In accordance with SAB recommendations, the EPA developed a two-
stage approach to integrate BBDR model results with data on 
neurodevelopmental outcomes from epidemiological studies, this approach 
allowed the Agency to link maternal thyroid hormones levels as a result 
of low iodine intake and perchlorate exposure, to derive an MCLG that 
directly addresses the most sensitive life stage (USEPA 2013a).
    On March 25, 2019, the EPA consulted with the Department of Health 
and Human Services (HHS). The EPA provided information to HHS officials 
on the draft proposed perchlorate regulation and considered HHS input 
as part of the interagency review described in section XVII.A.

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Radosavljevi[cacute], R. (2003). Thyroid hormone synthesis and 
storage in the thyroid gland of human neonates. Journal of Pediatric 
Endocrinology and Metabolism, 16(4), 521-528.
Seashore, H., Wesman, A., & Doppelt, J. (1950). The standardization 
of the Wechsler intelligence scale for children. Journal of 
Consulting Psychology, 14(2), 99.
Siemens Water Technologies. (2009). Case Study: Municipality in the 
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Steinmaus, C., Miller, M.D., & Howd, R. (2007). Impact of smoking 
and thiocyanate on perchlorate and thyroid hormone associations in 
the 2001-2002 National Health and Nutrition Examination Survey. 
Environmental Health Perspectives, 1333-1338.
Steinmaus, C., Miller, M.D., Cushing, L., Blount, B.C., & Smith, 
A.H. (2013). Combined effects of perchlorate, thiocyanate, and 
iodine on thyroid function in the national health and nutrition 
examination survey 2007-8. Environmental Research, 123. https://doi.org/10.1016/j.envres.2013.01.005.
Steinmaus, C., Pearl, M., Kharrazi, M., Blount, B.C., Miller, M.D., 
Pearce, E.N., . . . Liaw, J. (2016). Thyroid hormones and moderate 
exposure to perchlorate during pregnancy in women in southern 
California. Environmental Health Perspectives, 124(6), 861-867. 
https://doi.org/10.1289/ehp.1409614.
Sternberg, R.J., Grigorenko, E.L., & Bundy, D.A. (2001). The 
predictive value of IQ. Merrill-Palmer Quarterly (1982-), 1-41.
Sun, J., Yao, L., Fang, Y., Chen, Y., et al. (2017). Relationship 
between Subclinical Thyroid Dysfunction and the Risk of 
Cardiovascular Outcomes: A Systematic Review and Meta-Analysis of 
Prospective Cohort Studies. Int J Endocrinol. 2017:8130796.
Taylor, P., Razvi, S., Pearce, S.H., & Dayan, C.M. (2013). Clinical 
review: A review of the clinical consequences of variation in 
thyroid function within the reference range. J Clin Endocrinol 
Metab, 98(9), 3562-3571. doi:10.1210/jc.2013-1315.
The Interstate Technology & Regulatory Council (ITRC) Team. (2008, 
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Perchlorate Contamination in Water and Soil. Retrieved from http://www.eosremediation.com/download/Perchlorate/ITRC%20PERC-2.pdf.
Thompson, W., Russell, G., Baragwanath, G., Matthews, J., Vaidya, 
B., & Thompson[hyphen]Coon, J. (2018). Maternal thyroid hormone 
insufficiency during pregnancy and risk of neurodevelopmental 
disorders in offspring: A systematic review and meta-analysis. 
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[[Page 30564]]

Upadhyaya, G., Kotlarz, N., Togna, P., & Raskin, L. (2015). 
Carbohydrate-Based Electron Donor for Biological Nitrate and 
Perchlorate Removal From Drinking Water. Journal--American Water 
Works Association, 107(12), E674-E684. https://doi.org/10.5942/jawwa.2015.107.0143.
U.S. Census Bureau. (2010). American Community Survey, 5-year 
Estimates (2006-2010).
U.S. Census Bureau. (2017a). Annual estimates of the resident 
population by single year of age and sex for the United States: 
April 1, 2010 to July 1, 2016.
U.S. Census Bureau. (2017b). Average Household Size of Occupied 
Housing Units by Tenure. American Community Survey 1-Year Estimates: 
Table B25010.
U.S. Department of Defense (U.S. DoD). (2008). Perchlorate Removal, 
Destruction, and Field Monitoring Demonstration (Drinking Water--
Pilot Scale) (ESTCP Cost and Performance Report (ER-0312)).
U.S. Department of Defense (U.S. DoD). (2009). Demonstration of a 
Full-Scale Fluidized Bed Bioreactor for the Treatment of Perchlorate 
at Low Concentrations in Groundwater (Environmental Security 
Technology Certification Program (ESTCP) Final Report (ER-0543)).
U.S. Food and Drug Administration (FDA). (2015). Total diet study--
study design. Retrieved from http://www.fda.gov/food/foodscienceresearch/totaldietstudy/ucm184232.htm#.
USEPA. (1991, February). Standardized Monitoring Framework.
USEPA. (1998). Variance Technology Findings for Contaminants 
Regulated Before 1996. EPA 815-R-98-003. September.
USEPA. (1999). Revisions to the Unregulated Contaminant Monitoring 
Regulation for Public Water Systems; Final Rule. 64 FR 80, p. 50556. 
September 17, 1999.
USEPA. (2000a). Arsenic in Drinking Water Economic Analysis. EPA 
815-R-00-026.
USEPA. (2000b). Geometries and Characteristics of Public Water 
Systems. EPA 815-R-00-024.
USEPA. (2000c). Unregulated Contaminant Monitoring Regulation 
Analytical Methods and Quality Control Manual. EPA 815-R-00-006.
USEPA (2000d). Methodology for Deriving Ambient Water Quality 
Criteria for the Protection of Human Health. EPA-822-B-00-004.
USEPA. (2002). A review of the reference dose and reference 
concentration process.
USEPA (2003). Contaminant Candidate List Regulatory Determination 
Support Document for Aldrin and Dieldrin. EPA-815-R-03-010. https://www.epa.gov/sites/production/files/2014-09/documents/support_cc1_aldrin-dieldrin_ccl_regdet.pdf.
USEPA. (2004). The Standardized Monitoring Framework: A Quick 
Reference Guide. EPA-816-F-04-010.
USEPA. (2005a). Integrated Risk Information System (IRIS) Chemical 
Assessment Summary: Perchlorate (ClO4-) and Perchlorate Salts. USEPA 
National Center for Environmental Assessment.
USEPA. (2005b, May). Perchlorate Treatment Technology Update: 
Federal Facilities Forum Issue Paper. Office of Solid Waste and 
Emergency Response. EPA 542-R-05-015.
USEPA. (2008a). Drinking water: Preliminary regulatory determination 
on perchlorate. Federal Register, 73 (198).
USEPA. (2008b, June). Draft Information Collection Request for the 
Disinfectants/Disinfection Byproducts, Chemical, and Radionuclides 
Rule.
USEPA. (2008c, November 12). National Ambient Air Quality Standards 
for Lead. 73 FR 66964, p. 66964-67062. Retrieved from https://www.federalregister.gov/articles/2008/11/12/E8-25654/national-ambient-air-quality-standards-for-lead.
USEPA (2008d). Interim Drinking Water Health Advisory for 
Perchlorate. Retrieved from: https://nepis.epa.gov/Exe/ZyPDF.cgi/P1004X7Q.PDF?Dockey=P1004X7Q.PDF.
USEPA. (2008e). Regulatory Determinations Support Document for 
Selected Contaminants from the Second Drinking Water Contaminant 
Candidate List (CCL 2). EPA-815-R-03-010. https://www.epa.gov/sites/production/files/2014-09/documents/chapter_4_dcpa_mono-_and_di-acid_degradates.pdf.
USEPA. (2009a). Drinking Water: Perchlorate Supplemental Request for 
Comments.
USEPA. (2009b). Inhibition of the Sodium-Iodide Symporter By 
Perchlorate: An Evaluation of Lifestage Sensitivity Using 
Physiologically Based Pharmacokinetic (PBPK) Modeling (Final Report) 
(EPA/600/R-08/106A). Washington, DC.
USEPA. (2009c, May). 2006 Community Water System Survey--Volume II: 
Detailed Tables and Survey Methodology. Retrieved from https://www.epa.gov/dwstandardsregulations/community-water-system-survey.
USEPA. (2011a). Drinking Water: Regulatory Determination on 
Perchlorate. Federal Register Notice. 76 FR No. 29. Pages 7762-7767. 
(February 11, 2011) (to be codified at 40 CFR pt. 141). Retrieved 
from https://www.federalregister.gov/articles/2011/02/11/2011-2603/drinking-water-regulatory-determination-on-perchlorate.
USEPA. (2011b). Exposure Factors Handbook 2011 Edition (Final 
Report) (p. Chapter 8). Retrieved from https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=236252.
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USEPA. (2012a). Perchlorate Tribal Stakeholder Meeting Summary. 
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Revision, and Preliminary Dose-Response Analyses. (T.L. Paul 
Schlosser and Santhini Ramasamy, Ed.). Peer Review Draft.
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Derivation of a Maximum Contaminant Level Goal for Perchlorate in 
Drinking Water.
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Implementation of a Biological Fluidized Bed Drinking Water 
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the 2010 Water Education Foundation Water Quality and Regulatory 
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Journal AWWA, 109(5), 30-40.
Wu, X., & Blute, N.K. (2010, March). Perchlorate Removal Using 
Single-Pass Ion Exchange Resin--Pilot Testing Purolite A532E at the 
San Gabriel B6 Plant. Presented at the 2010 California-Nevada AWWA 
Spring Conference, Hollywood, CA.
Yoon, J., Amy, G., & Yoon, Y. (2005). Transport of target anions, 
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through RO, NF, and UF membranes. Water Science and Technology, 
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[[Page 30565]]

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List of Subjects

40 CFR Part 141

    Chemicals, Incorporation by reference, Indians--lands, 
Intergovernmental relations, Radiation protection, Reporting and 
recordkeeping requirements, Water supply.

40 CFR Part 142

    Administrative practice and procedure, Chemicals, Indians--lands, 
Radiation protection, Reporting and recordkeeping requirements, Water 
supply.

    Dated: May 23, 2019.
Andrew R. Wheeler,
Administrator.

    For the reasons stated in the preamble, the Environmental 
Protection Agency proposes to amend 40 CFR parts 141 and 142 as 
follows:

PART 141--NATIONAL PRIMARY DRINKING WATER REGULATIONS

0
1. The authority citation for part 141 continues to read as follows:

    Authority:  42 U.S.C. 300f, 300g-1, 300g-2, 300g-3, 300g-4, 
300g-5, 300g-6, 300j-4, 300j-9, and 300j-11.

0
2. Amend Sec.  141.6 by revising paragraph (a) and adding paragraph (l) 
to read as follows:

Subpart A--General

Sec.  141.6   Effective dates.

    (a) Except as provided in paragraphs (b) through (l) of this 
section the regulations set forth in this part shall take effect on 
June 24, 1977.
* * * * *
    (l) The regulations contained in the revisions to Sec. Sec.  
141.23(a)(4)(i), 141.23(a)(5), 141.23(c),141.23(f)(1), 141.23(i)(1)-
(2), 141.23(k)(1)-(3), 141.23(k)(3)(ii), 141.51(b), 141.60(b)(5), 
141.62(b), 141.62(c), 141.62(e), Appendix A to Subpart O and Appendix A 
and B to Subpart Q are effective for the purposes of compliance on 
[DATE OF PUBLICATION OF FINAL RULE IN THE FEDERAL REGISTER].
0
3. Amend Sec.  141.23 by:
0
a. In paragraph (a)(4)(i) table:
0
i. Revising the table heading; and
0
ii. Adding an entry for ``Perchlorate'' in alphabetical order;
0
b. In paragraph (a)(5), after the text ``nickel,'' adding the text 
``perchlorate,'';
0
c. In paragraph (c), after the text ``nickel,'' adding the text 
``perchlorate,'';
0
d. Adding paragraph (c)(10);
0
e. In paragraph (f)(1), after the text ``nickel,'' adding the text 
``perchlorate,'';
0
f. In paragraphs (i)(1) and (2), after the text ``nickel,'' adding the 
text ``perchlorate,'';
0
g. Revising paragraph (i)(3);
0
h. In paragraph (k)(1):
0
i. Revising the introductory text; and
0
ii. In the table, adding the table designation, redesignating entries 
21 through 26 as 22 through 27, and adding a new entry 21;
0
i. In paragraph (k)(2):
0
i. In the introductory paragraph, after the text ``nitrite,'' adding 
the text ``perchlorate,''; and
0
ii. In the table, adding the table designation and adding, in 
alphabetical order, an entry for ``Perchlorate'';
0
j. In paragraph (k)(3):
0
i. In the introductory paragraph, after the text ``nitrite'' adding the 
text ``, perchlorate,''; and
0
ii. In paragraph (ii) table, adding the table designation, and adding 
in alphabetical order, an entry for ``Perchlorate'';
    The revisions and additions read as follows:

Subpart C--Monitoring and Analytical Requirements

Sec.  141.23   Inorganic chemical sampling and analytical requirements.

* * * * *
    (a) * * *
    (4) * * *
    (i) * * *

                  Table 1 to Paragraph (a)(4)(i)-- Detection Limits for Inorganic Contaminants
                                              [Composited samples]
----------------------------------------------------------------------------------------------------------------
             Contaminant                 MCL  (mg/l)            Methodology            Detection limit  (mg/l)
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
Perchlorate..........................           0.056  Ion Chromatography..........  0.00053.
                                                       Inline Column Concentration/  0.00003.
                                                        Matrix Elimination Ion
                                                        Chromatography with
                                                        Suppressed Conductivity
                                                        Detection.
                                                       Two-Dimensional Ion           0.000012-0.000018.
                                                        Chromatography with
                                                        Suppressed Conductivity
                                                        Detection.
                                                       Liquid Chromatography         0.000005 (Tandem Mass
                                                        Electrospray Ionization       Spectrometry [MS/MS])
                                                        Mass Spectrometry.            0.000008 (Selected Ion
                                                                                      Monitoring [SIM]).
                                                       Ion Chromatography with       0.00002.
                                                        Suppressed Conductivity and
                                                        Electrospray Ionization
                                                        Mass Spectrometry.
 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------

* * * * *
    (c) * * *
    (10) Community water systems and non-transient non-community water 
systems must conduct initial monitoring for perchlorate as follows:
    (i) Community water systems serving greater than 10,000 persons 
without acceptable historic data, as defined below, must collect four 
consecutive quarterly samples at all sampling points between January 1, 
2023 and December 31, 2025.
    (ii) Community water systems serving 10,000 or fewer persons and 
non-transient non-community water systems without acceptable historic 
data, as defined below, must collect four consecutive quarterly samples 
at all

[[Page 30566]]

sampling points between January 1, 2026 and December 31, 2028.
    (iii) Grandfathering of data: States may allow historical 
monitoring data collected at a sampling point to satisfy the initial 
monitoring requirements for that sampling point, for the following 
situations.
    (A) To satisfy initial monitoring requirements, community water 
systems serving greater than 10,000 persons having only one entry point 
to the distribution system may use the monitoring data from the 
compliance monitoring period between January 1, 2020 and December 31, 
2022. Community water systems serving 10,000 or fewer persons and non-
transient non-community water systems having only one entry point to 
the distribution system may use the monitoring data from the compliance 
monitoring period between January 1, 2023 and December 31, 2025.
    (B) To satisfy initial monitoring requirements, a system with 
multiple entry points and having appropriate historical monitoring data 
for each entry point to the distribution system may use the monitoring 
data from the compliance monitoring period that began between January 
1, 2020 and December 31, 2022, for community water systems serving 
greater than 10,000 persons and between January 1, 2023 and December 
31, 2025, for community water systems serving 10,000 or fewer persons 
and for non-transient non-community water systems.
    (C) To satisfy initial monitoring requirements, a system with 
appropriate historical data for a representative point in the 
distribution system may use the monitoring data from the compliance 
monitoring period between January 1, 2020 and December 31, 2022, for 
community water systems serving greater than 10,000 persons and between 
January 1, 2023 and December 31, 2025, for community water systems 
serving 10,000 or fewer persons and for non-transient non-community 
water systems, provided that the State finds that the historical data 
satisfactorily demonstrate that each entry point to the distribution 
system is expected to be in compliance based upon the historical data 
and reasonable assumptions about the variability of contaminant levels 
between entry points. The State must make a written finding indicating 
how the data conforms to these requirements.
    (iv) The State may waive the final two quarters of initial 
monitoring for perchlorate for a sampling point if the results of the 
samples from the previous two quarters are below the detection limit.
* * * * *
    (i) * * *
    (3) Compliance with the maximum contaminant level for nitrate, 
nitrite and perchlorate is determined based on one sample if the levels 
of these contaminants are below the MCLs. If the level of perchlorate 
exceeds the MCL in the initial sample, a confirmation sample is 
required in accordance with paragraph (f)(1) of this section and 
compliance shall be based on the average of the initial and 
confirmation sample. If the levels of nitrate and/or nitrite exceed the 
MCLs in the initial sample, a confirmation sample is required in 
accordance with paragraph (f)(2) of this section and compliance shall 
be based on the average of the initial and confirmation sample.
* * * * *
    (k) * * *
    (1) Analysis for the following contaminants shall be conducted in 
accordance with the methods in the following table, or the alternative 
methods listed in Appendix A to Subpart C of this part, or their 
equivalent as determined by the EPA. Criteria for analyzing arsenic, 
barium, beryllium, cadmium, calcium, chromium, copper, lead, nickel, 
selenium, sodium, and thallium with digestion or directly without 
digestion, and other analytical test procedures are contained in 
Technical Notes on Drinking Water Methods, EPA-600/R-94-173, October 
1994. This document is available from the National Service Center for 
Environmental Publications (NSCEP), P.O. Box 42419, Cincinnati, OH 
45242-0419 or http://www.epa.gov/nscep/.

                                                               Table 2 to Paragraph (k)(1)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                         SM \4\
              Contaminant                       Methodology \13\               EPA         ASTM \3\   (18th, 19th     SM \4\     SM Online      Other
                                                                                                          ed.)      (20th ed.)      \22\
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
                                                                      * * * * * * *
21. Perchlorate........................  Ion Chromatography............      \23\ 314.0
                                         Inline Column Concentration/        \24\ 314.1
                                          Matrix Elimination Ion
                                          Chromatography with
                                          Suppressed Conductivity
                                          Detection.
                                         Two-Dimensional Ion                 \25\ 314.2
                                          Chromatography with
                                          Suppressed Conductivity
                                          Detection.
                                         Liquid Chromatography               \26\ 331.0
                                          Electrospray Ionization Mass
                                          Spectrometry.
                                         Ion Chromatography with             \27\ 332.0
                                          Suppressed Conductivity and
                                          Electrospray Ionization Mass
                                          Spectrometry.
 
                                                                      * * * * * * *
--------------------------------------------------------------------------------------------------------------------------------------------------------
\3\ Annual Book of ASTM Standards, ASTM International, 100 Barr Harbor Drive, West Conshohocken, PA 19428, http://www.astm.org.; Annual Book of ASTM
  Standards 1994, Vols. 11.01 and 11.02; Annual Book of ASTM Standards 1996, Vols. 11.01 and 11.02; Annual Book of ASTM Standards 1999, Vols. 11.01 and
  11.02; Annual Book of ASTM Standards 2003, Vols. 11.01 and 11.02.
\4\ Standard Methods for the Examination of Water and Wastewater, American Public Health Association, 800 I Street NW, Washington, DC 20001-3710;
  Standard Methods for the Examination of Water and Wastewater, 18th edition (1992); Standard Methods for the Examination of Water and Wastewater, 19th
  edition (1995); Standard Methods for the Examination of Water and Wastewater, 20th edition (1998).The following methods from this edition cannot be
  used: 3111 B, 3111 D, 3113 B, and 3114 B.

[[Page 30567]]

 
\13\ Because MDLs reported in EPA Methods 200.7 and 200.9 were determined using a 2x preconcentration step during sample digestion, MDLs determined when
  samples are analyzed by direct analysis (i.e., no sample digestion) will be higher. For direct analysis of cadmium and arsenic by Method 200.7, and
  arsenic by Method 3120 B, sample preconcentration using pneumatic nebulization may be required to achieve lower detection limits. Preconcentration may
  also be required for direct analysis of antimony, lead, and thallium by Method 200.9; antimony and lead by Method 3113 B; and lead by Method D3559-
  90D, unless multiple in-furnace depositions are made.
* * * * * * *
\22\ Standard Methods Online, American Public Health Association, 800 I Street NW, Washington, DC 20001, available at http://www.standardmethods.org.
  The year in which each method was approved by the Standard Methods Committee is designated by the last two digits in the method number. The methods
  listed are the only online versions that may be used.
\23\ Determination of Perchlorate in Drinking Water Using Ion Chromatography (Revision 1.0, USEPA, 1999a).
\24\ Determination of Perchlorate in Drinking Water Using Inline Column Concentration/Matrix Elimination Ion Chromatography with Suppressed Conductivity
  Detection (Revision 1.0, USEPA, 2005b).
\25\ Determination of Perchlorate in Drinking Water Using Two-Dimensional Ion Chromatography with Suppressed Conductivity Detection (USEPA, 2008c).
\26\ Determination of Perchlorate in Drinking Water by Liquid Chromatography Electrospray Ionization Mass Spectrometry'' (Revision 1.0, USEPA, 2005c).
\27\ Determination of Perchlorate in Drinking Water by Ion Chromatography with Suppressed Conductivity and Electrospray Ionization Mass Spectrometry''
  (USEPA, Revision 1.0, 2005d).

    The approved compliance methods for determining perchlorate in 
drinking water listed in table 1 to paragraph (k) of this section, are 
incorporated by reference. The Director of the Federal Register 
approves this incorporation by reference in accordance with 5 U.S.C. 
552(a) and 1 CFR part 51. Copies of the material incorporated by 
reference in this paragraph (k) may be inspected at the U.S. 
Environmental Protection Agency, EPA Headquarters Library, in the Water 
Docket, at the EPA Docket Center (EPA/DC), EPA WJC West, Room 3334, 
1301 Constitution Ave. NW, Washington, DC 20460. If you wish to obtain 
this material from the EPA Docket Center, call (202) 566-2426. Copies 
of this material also may be inspected at the National Archives and 
Records Administration (NARA). For information on the availability of 
this material at NARA, call (202) 741-6030, or go to www.archives.gov/federal-register/cfr/ibr-locations.html.
* * * * *
    (2) * * *

                                           Table 3 to Paragraph (k)(2)
----------------------------------------------------------------------------------------------------------------
             Contaminant                   Preservative \1\          Container \2\               Time \3\
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
Perchlorate \7\......................  4 [deg]C...............  P or G.................  28 days.
 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------
\1\ For cyanide determinations samples must be adjusted with sodium hydroxide to pH 12 at the time off
  collection. When chilling is indicated the sample must be shipped and stored at 4 [deg]C or less.
  Acidification of nitrate or metals samples may be with a concentrated acid or a dilute (50% by volume)
  solution of the applicable concentrated acid. Acidification of samples for metals analysis is encouraged and
  allowed at the laboratory rather than at the time of sampling provided the shipping time and other
  instructions in Section 8.3 of EPA Methods 200.7 or 200.8 or 200.9 are followed.
\2\ P = plastic, hard or soft; G = glass, hard or soft.
\3\ In all cases samples should be analyzed as soon after collection as possible. Follow additional (if any)
  information on preservation, containers or holding times that is specified in method.
* * * * * * *
\7\ Sample collection for perchlorate shall be conducted following the requirements specified in the approved
  methods in 141.23(k)(1) or the alternative methods listed in appendix A of subpart C of this part, or their
  equivalent as determined by the EPA.

* * * * *
    (3) * * *
    (ii) * * *

                     Table 4 to Paragraph (k)(3)(ii)
------------------------------------------------------------------------
                                                            Acceptance
                       Contaminant                             limit
------------------------------------------------------------------------
 
                                * * * * *
Perchlorate.............................................          20% at
                                                            [gteqt]0.004
                                                                   mg/L.
 
                                * * * * *
------------------------------------------------------------------------

* * * * *
0
4. In Sec.  141.51 amend paragraph (b) by adding a designation to the 
table and by adding in alphabetical order, an entry for ``Perchlorate'' 
to read as follows:

Subpart F--Maximum Contaminant Level Goals and Maximum Residual 
Disinfectant Level Goals

Sec.  141.51   Maximum contaminant level goals for inorganic 
contaminants.

* * * * *
    (b) * * *

                        Table 1 to Paragraph (b)
------------------------------------------------------------------------
                       Contaminant                         MCLG  (mg/l)
------------------------------------------------------------------------
 
                                * * * * *
Perchlorate.............................................           0.056
 
                                * * * * *
------------------------------------------------------------------------

* * * * *
0
5. Amend Sec.  141.60 by adding paragraph (b)(5) to read as follows:

Subpart G--National Primary Drinking Water Regulations: Maximum 
Contaminant Levels and Maximum Residual Disinfectant Levels

Sec.  141.60   Effective dates.

* * * * *
    (b) * * *
    (5) The effective date for Sec.  141.62(b)(17) is [DATE OF 
PUBLICATION OF FINAL RULE IN THE FEDERAL REGISTER].
0
6. Amend Sec.  141.62 by:
0
a. In the table in paragraph (b), adding a designation to the table and 
an entry for ``(17) Perchlorate'' at the end of the table;
0
b. In the table in paragraph (c), adding a designation to the table, an 
entry for ``Perchlorate'' in alphabetical order, and an entry ``14 = 
Biological Treatment'' under the undesignated heading entitled ``Key to 
BATs; and

[[Page 30568]]

0
c. Adding paragraph (e).
    The revisions and additions read as follows:

Sec.  141.62   Maximum contaminant levels for inorganic contaminants.

* * * * *
    (b) * * *

                        Table 1 to Paragraph (b)
------------------------------------------------------------------------
                       Contaminant                          MCL  (mg/l)
------------------------------------------------------------------------
 
                                * * * * *
(17) Perchlorate........................................           0.056
------------------------------------------------------------------------

    (c) * * *

 Table 2 to Paragraph (c)--BAT for Inorganic Compounds Listed in Section
                                141.62(B)
------------------------------------------------------------------------
                      Chemical name                           BAT(s)
------------------------------------------------------------------------
 
                                * * * * *
Perchlorate.............................................       5, 7, 14.
 
                                * * * * *
------------------------------------------------------------------------

* * * * *

Key to BATs in Table

* * * * *
14 = Biological Treatment
* * * * *
    (e) The Administrator, pursuant to section 1412 of the Act, hereby 
identified in the following table the affordable technology, treatment 
technique, or other means available to systems serving 10,000 persons 
or fewer for achieving compliance with the maximum contaminant level 
for perchlorate:

 Table 3 to Paragraph (e)--Small System Compliance Technologies (SSCTS)
                             for Perchlorate
------------------------------------------------------------------------
                                              Affordability for listed
    Small system compliance technology         small system categories
------------------------------------------------------------------------
Ion exchange..............................  All size categories.
Reverse osmosis (point of use)............  All size categories.
------------------------------------------------------------------------

0
7. Amend Appendix A to Subpart O of Part 141 table, under ``Inorganic 
contaminants'', by adding an entry for ``Perchlorate'' in alphabetical 
order to read as follows:

Subpart O--Consumer Confidence Reports

                                               Appendix A to Subpart O of Part 141--Reguated Contaminants
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                Traditional   To convert
     Contaminant  (units)       MCL in  mg/    for CCR,   MCL in  CCR      MCLG             Major sources in drinking water            Health effects
                                     L       multiply by     units                                                                        language
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
                                                                      * * * * * * *
Inorganic contaminants
Perchlorate...................        0.056         1000           56           56  Perchlorate is commonly used in solid rocket    Offspring of
                                                                                     propellants, munitions, fireworks, airbag       pregnant women and
                                                                                     initiators for vehicles, matches and signal     infants who drink
                                                                                     flares. Perchlorate may occur naturally,        water containing
                                                                                     particularly in arid regions such as the        perchlorate in
                                                                                     southwestern United States and is found as a    excess of the MCL
                                                                                     natural impurity in nitrate salts used to       could experience
                                                                                     produce nitrate fertilizers, explosives and     delays in their
                                                                                     other products.                                 physical or mental
                                                                                                                                     development.
 
                                                                      * * * * * * *
--------------------------------------------------------------------------------------------------------------------------------------------------------

0
8. Amend Appendix A to Subpart Q of Part 141 table, under ``B. 
Inorganic contaminants'', by adding an entry for ``Perchlorate'' in 
alphabetical order to read as follows:

Subpart Q--Public Notification of Drinking Water Violations

* * * * *

     Appendix A to Subpart Q of Part 141--NPDWR Violations and Other Situations Requiring Public Notice \1\
----------------------------------------------------------------------------------------------------------------
                                        MCL/MRDL/TT violations \2\            Monitoring & testing  procedure
                                 ----------------------------------------               violations
                                                                         ---------------------------------------
           Contaminant            Tier of public                          Tier of public
                                      notice             Citation             notice             Citation
                                     required                                required
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------
                                          B. Inorganic Chemicals (IOCs)
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
14. Perchlorate.................               1  141.62(b).............               3  141.23(a), (c),
                                                                                           141.23(f)(1).
 

[[Page 30569]]

 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------

    \1\ Violations and other situations not listed in this table (e.g., 
failure to prepare Consumer Confidence Reports), do not require notice, 
unless otherwise determined by the primacy agency. Primacy agencies 
may, at their option, also require a more stringent public notice tier 
(e.g., Tier 1 instead of Tier or Tier 2 instead of Tier 3) for specific 
violations and situations listed in this Appendix, as authorized under 
141.202(a) and 141.203(a).
    \2\ MCL-Maximum contaminant level, MDRL-Maximum residual 
disinfectant level, TT-treatment technique
* * * * *
0
9. Amend Appendix B to Subpart Q of Part 141 table, under ``C. 
Inorganic contaminants'', by adding an entry for ``Perchlorate'' in 
alphabetical order to read as follows:

          Appendix B to Subpart Q of Part 141--Standard Health Effects Language for Public Notification
----------------------------------------------------------------------------------------------------------------
                                                                   Standard health effects language for public
          Contaminant            MCLG \1\  mg/L   MCL \2\  mg/L                    notification
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------
                                          C. Inorganic Chemicals (IOCs)
----------------------------------------------------------------------------------------------------------------
 
                                                  * * * * * * *
21. Perchlorate................           0.056           0.056  Offspring of pregnant women and infants who
                                                                  drink water containing perchlorate in excess
                                                                  of the MCL could experience delays in their
                                                                  physical or mental development.
 
                                                  * * * * * * *
----------------------------------------------------------------------------------------------------------------
\1\ MCLG--Maximum contaminant level goal.
\2\ MCL--Maximum contaminant level.

PART 142--NATIONAL PRIMARY DRINKING WATER REGULATIONS 
IMPLEMENTATION

0
10. The authority citation for part 142 continues to read as follows:

    Authority:  42 U.S.C. 300f, 300g-1, 300g-2, 300g-3, 300g-4, 
300g-5, 300g-6, 300j-4, 300j-9, and 300j-11.

0
11. In Sec.  142.62 amend the table in paragraph (b) by adding a 
designation to the table, an entry for ``Perchlorate'' in alphabetical 
order; and an entry ``13 = Biological Treatment'' under the 
undesignated heading entitled ``Key to BATs''.

Subpart G--Identification of Best Technology, Treatment Techniques 
or Other Means Generally Available.

* * * * *

Sec.  142.62   Variances and exemptions from the maximum contaminant 
levels for organic and inorganic chemicals.

* * * * *
    (b) * * *

  Table 1 to paragraph (b)--BAT for Inorganic Compounds Listed in Sec.
                                141.62(b)
------------------------------------------------------------------------
               Chemical name                            BAT(s)
------------------------------------------------------------------------
 
                                 * * * *
Perchlorate................................  5, 7, 14
 
                                 * * * *
------------------------------------------------------------------------

* * * * *

Key to BATs in Table

* * * * *
13 = Biological Treatment
* * * * *
[FR Doc. 2019-12773 Filed 6-25-19; 8:45 am]
 BILLING CODE 6560-50-P