National Emission Standards for Hazardous Air Pollutants: Coal- and Oil-Fired Electric Utility Steam Generating Units-Reconsideration of Supplemental Finding and Residual Risk and Technology Review, 2670-2704 [2019-00936]
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Federal Register / Vol. 84, No. 26 / Thursday, February 7, 2019 / Proposed Rules
ENVIRONMENTAL PROTECTION
AGENCY
40 CFR Part 63
[EPA–HQ–OAR–2018–0794; FRL–9988–93–
OAR]
RIN 2060–AT99
National Emission Standards for
Hazardous Air Pollutants: Coal- and
Oil-Fired Electric Utility Steam
Generating Units—Reconsideration of
Supplemental Finding and Residual
Risk and Technology Review
Environmental Protection
Agency (EPA).
ACTION: Proposed rule.
AGENCY:
The Environmental Protection
Agency (EPA) is proposing a revision to
its response to the U.S. Supreme Court
decision in Michigan v. EPA which held
that the EPA erred by not considering
cost in its determination that regulation
under section 112 of the Clean Air Act
(CAA) of hazardous air pollutant (HAP)
emissions from coal- and oil-fired
electric utility steam generating units
(EGUs) is appropriate and necessary.
After considering the cost of compliance
relative to the HAP benefits of
regulation, the EPA proposes to find
that it is not ‘‘appropriate and
necessary’’ to regulate HAP emissions
from coal- and oil-fired EGUs, thereby
reversing the Agency’s prior conclusion
under CAA section 112(n)(1)(A) and
correcting flaws in the Agency’s prior
response to Michigan v. EPA. We further
propose that finalizing this new
response to Michigan v. EPA will not
remove the Coal- and Oil-Fired EGU
source category from the CAA section
112(c) list of sources that must be
regulated under CAA section 112(d) and
will not affect the existing CAA section
112(d) emissions standards that regulate
HAP emissions from coal- and oil-fired
EGUs. We are soliciting comment,
however, on whether the EPA has the
authority or obligation to delist EGUs
from CAA section 112(c) and rescind (or
to rescind without delisting) the
National Emission Standards for
Hazardous Air Pollutants (NESHAP) for
Coal- and Oil-Fired EGUs, commonly
known as the Mercury and Air Toxics
Standards (MATS). The EPA is also
proposing the results of the residual risk
and technology review (RTR) of the
NESHAP that the Agency is required to
conduct in accordance with CAA
section 112. The results of the residual
risk analysis indicate that residual risks
due to emissions of air toxics from this
source category are acceptable and that
the current standards provide an ample
SUMMARY:
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margin of safety to protect public health.
No new developments in HAP emission
controls to achieve further cost-effective
emissions reductions were identified
under the technology review. Therefore,
based on the results of these analyses
and reviews, we are proposing that no
revisions to MATS are warranted.
Finally, the EPA is also taking comment
on establishing a subcategory for
emissions of acid gas HAP from existing
EGUs firing eastern bituminous coal
refuse.
DATES: Comments. Comments must be
received on or before April 8, 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 March 25, 2019.
Public Hearing. The EPA is planning
to hold at least one public hearing in
response to this proposed action.
Information about the hearing,
including location, date, and time, along
with instructions on how to register to
speak at the hearing, will be published
in a second Federal Register document.
ADDRESSES: Comments. Submit your
comments, identified by Docket ID No.
EPA–HQ–OAR–2018–0794, at https://
www.regulations.gov. Follow the online
instructions for submitting comments.
Once submitted, comments cannot be
edited or removed from Regulations.gov.
See SUPPLEMENTARY INFORMATION for
detail about how the EPA treats
submitted comments. Regulations.gov is
our preferred method of receiving
comments. However, the following
other submission methods are also
accepted:
• Email: a-and-r-docket@epa.gov.
Include Docket ID No. EPA–HQ–OAR–
2018–0794 in the subject line of the
message.
• Fax: (202) 566–9744. Attention
Docket ID No. EPA–HQ–OAR–2018–
0794.
• Mail: To ship or send mail via the
United States Postal Service, use the
following address: U.S. Environmental
Protection Agency, EPA Docket Center,
Docket ID No. EPA–HQ–OAR–2018–
0794, Mail Code 28221T, 1200
Pennsylvania Avenue NW, Washington,
DC 20460.
• Hand/Courier Delivery: Use the
following Docket Center address if you
are using express mail, commercial
delivery, hand delivery, or courier: EPA
Docket Center, EPA WJC West Building,
Room 3334, 1301 Constitution Avenue
NW, Washington, DC 20004. Delivery
verification signatures will be available
only during regular business hours.
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For
questions about this proposed action,
contact Mary Johnson, Sector Policies
and Programs Division (D243–01),
Office of Air Quality Planning and
Standards, U.S. Environmental
Protection Agency, Research Triangle
Park, North Carolina 27711; telephone
number: (919) 541–5025; fax number:
(919) 541–4991; and email address:
johnson.mary@epa.gov or Nick Hutson,
Sector Policies and Programs Division
(D243–01), Office of Air Quality
Planning and Standards, U.S.
Environmental Protection Agency,
Research Triangle Park, North Carolina
27711; telephone number: (919) 541–
2968; fax number: (919) 541–4991; and
email address: hutson.nick@epa.gov.
For specific information regarding the
risk modeling methodology, contact
Mark Morris, Health and Environmental
Impacts Division (C539–02), Office of
Air Quality Planning and Standards,
U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina
27711; telephone number: (919) 541–
5416; and email address: morris.mark@
epa.gov. For information about the
applicability of the NESHAP to a
particular entity, contact Sara Ayres,
Office of Enforcement and Compliance
Assurance, U.S. Environmental
Protection Agency, U.S. EPA Region 5
(E–19J), 77 West Jackson Boulevard,
Chicago, Illinois 60604; telephone
number: (312) 353–6266; and email
address: ayres.sara@epa.gov.
SUPPLEMENTARY INFORMATION:
Docket. The EPA has established a
docket for this rulemaking under Docket
ID No. EPA–HQ–OAR–2018–0794. All
documents in the docket are listed in
Regulations.gov. Although listed, some
information is not publicly available,
e.g., CBI (Confidential Business
Information) or other information whose
disclosure is restricted by statute.
Certain other material, such as
copyrighted material, is not placed on
the internet and will be publicly
available only in hard copy. Publicly
available docket materials are available
either electronically in Regulations.gov
or in hard copy at the EPA Docket
Center, Room 3334, EPA WJC West
Building, 1301 Constitution Avenue
NW, Washington, DC. The Public
Reading Room is open from 8:30 a.m. to
4:30 p.m., Monday through Friday,
excluding legal holidays. The telephone
number for the Public Reading Room is
(202) 566–1744, and the telephone
number for the EPA Docket Center is
(202) 566–1742.
Instructions. Direct your comments to
Docket ID No. EPA–HQ–OAR–2018–
0794. The EPA’s policy is that all
FOR FURTHER INFORMATION CONTACT:
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comments received will be included in
the public docket without change and
may be made available online at https://
www.regulations.gov, including any
personal information provided, unless
the comment includes information
claimed to be CBI or other information
whose disclosure is restricted by statute.
Do not submit information that you
consider to be CBI or otherwise
protected through https://
www.regulations.gov or email. This type
of information should be submitted by
mail as discussed below.
The EPA may publish any comment
received to its public docket.
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
https://www.epa.gov/dockets/
commenting-epa-dockets.
The https://www.regulations.gov
website allows you to submit your
comment anonymously, which means
the EPA will not know your identity or
contact information unless you provide
it in the body of your comment. If you
send an email comment directly to the
EPA without going through https://
www.regulations.gov, your email
address will be automatically captured
and included as part of the comment
that is placed in the public docket and
made available on the internet. If you
submit an electronic comment, the EPA
recommends that you include your
name and other contact information in
the body of your comment and with any
digital storage media you submit. If the
EPA cannot read your comment due to
technical difficulties and cannot contact
you for clarification, the EPA may not
be able to consider your comment.
Electronic files should not include
special characters or any form of
encryption and be free of any defects or
viruses. For additional information
about the EPA’s public docket, visit the
EPA Docket Center homepage at https://
www.epa.gov/dockets.
The EPA is soliciting comment on
numerous aspects of the proposed rule.
The EPA has indexed each comment
solicitation with an alpha-numeric
identifier (e.g., ‘‘C–1,’’ ‘‘C–2,’’ ’’C–3’’) to
provide a consistent framework for
effective and efficient provision of
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comments. Accordingly, the EPA asks
that commenters include the
corresponding identifier when
providing comments relevant to that
comment solicitation. The EPA asks that
commenters include the identifier in
either a heading, or within the text of
each comment (e.g., ‘‘In response to
solicitation of comment C–1, . . .’’) to
make clear which comment solicitation
is being addressed. The EPA emphasizes
that the Agency is not limiting comment
to these identified areas and encourages
provision of any other comments
relevant to this proposal.
Submitting CBI. Do not submit
information containing CBI to the EPA
through https://www.regulations.gov or
email. Clearly mark the part or all of the
information that you claim to be CBI.
For CBI information on any digital
storage media that you mail to the EPA,
mark the outside of the digital storage
media as CBI and then identify
electronically within the digital storage
media the specific information that is
claimed as CBI. In addition to one
complete version of the comments that
includes information claimed as CBI,
you must submit a copy of the
comments that does not contain the
information claimed as CBI directly to
the public docket through the
procedures outlined in Instructions
above. If you submit any digital storage
media that does not contain CBI, mark
the outside of the digital storage media
clearly that it does not contain CBI.
Information not marked as CBI will be
included in the public docket and the
EPA’s electronic public docket without
prior notice. Information marked as CBI
will not be disclosed except in
accordance with procedures set forth in
40 Code of Federal Regulations (CFR)
part 2. Send or deliver information
identified as CBI only to the following
address: OAQPS Document Control
Officer (C404–02), OAQPS, U.S.
Environmental Protection Agency,
Research Triangle Park, North Carolina
27711, Attention Docket ID No. EPA–
HQ–OAR–2018–0794.
Preamble Acronyms and
Abbreviations. We use multiple
acronyms and terms in this preamble.
While this list may not be exhaustive, to
ease the reading of this preamble and for
reference purposes, the EPA defines the
following terms and acronyms here:
AEGL acute exposure guideline level
AERMOD air dispersion model used by the
HEM–3 model
ATSDR Agency for Toxic Substances and
Disease Registry
CAA Clean Air Act
CalEPA California EPA
CAMR Clean Air Mercury Rule
CBI Confidential Business Information
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CEMS continuous emissions monitoring
systems
CFR Code of Federal Regulations
CPMS continuous parameter monitoring
system
ECMPS Emissions Collection and
Monitoring Plan System
EGU electric utility steam generating unit
EIA Energy Information Administration
EPA Environmental Protection Agency
EPRI Electric Power Research Institute
ERPG Emergency Response Planning
Guideline
fPM filterable particulate matter
HAP hazardous air pollutant(s)
HCl hydrochloric acid
HEM–3 Human Exposure Model, Version
1.1.0
HF hydrogen fluoride
Hg mercury
HI hazard index
HQ hazard quotient
ICR information collection request
IGCC integrated gasification combined
cycle
IRIS Integrated Risk Information System
km kilometer
lb/GWh pounds per gigawatt-hour
lb/MMBtu pounds per million British
thermal units
lb/MWh pounds per megawatt-hour
lb/TBtu pounds per trillion British thermal
units
MACT maximum achievable control
technology
MATS Mercury and Air Toxics Standards
mg/m3 milligrams per cubic meter
MIR maximum individual risk
MMBtu million British thermal units
MMBtu/hr million British thermal units per
hour
NAAQS National Ambient Air Quality
Standards
NAICS North American Industry
Classification System
NEEDS National Electric Energy Data
System
NEI National Emissions Inventory
NESHAP national emission standards for
hazardous air pollutants
NOX nitrogen oxides
NTTAA National Technology Transfer and
Advancement Act
OAQPS Office of Air Quality Planning and
Standards
OMB Office of Management and Budget
PB–HAP hazardous air pollutants known to
be persistent and bio-accumulative in the
environment
PDF Portable Document Format
PM particulate matter
PM2.5 fine particulate matter
POM polycyclic organic matter
PRA Paperwork Reduction Act
RDL representative detection level
REL reference exposure level
RFA Regulatory Flexibility Act
RfC reference concentration
RfD reference dose
RIA regulatory impact analysis
RTR residual risk and technology review
SAB Science Advisory Board
SO2 sulfur dioxide
TOSHI target organ-specific hazard index
tpy tons per year
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TRIM.FaTE Total Risk Integrated
Methodology.Fate, Transport, and
Ecological Exposure model
UARG Utility Air Regulatory Group
UF uncertainty factor
mg/m3 microgram per cubic meter
UMRA Unfunded Mandates Reform Act
URE unit risk estimate
USGS United States Geological Survey
Organization of this Document. The
information in this preamble is
organized as follows:
I. General Information
A. Does this action apply to me?
B. Where can I get a copy of this document
and other related information?
II. Appropriate and Necessary Finding
A. Overview
B. Background
C. The EPA’s Proposed Finding Under
CAA Section 112(n)(1)(A)
D. Effects of This Proposed Replacement of
the Supplemental Finding
III. Criteria for Delisting a Source Category
Under CAA Section 112(c)(9)
IV. Background on the RTR Action
A. What is the statutory authority for this
action?
B. What is this source category and how
does the current NESHAP regulate its
HAP emissions?
C. What data collection activities were
conducted to support this action?
D. What other relevant background
information and data are available?
V. RTR Analytical Procedures and DecisionMaking
A. How do we consider risk in our
decision-making?
B. How do we perform the technology
review?
C. How do we estimate post-MACT risk
posed by the source category?
VI. RTR Analytical Results and Proposed
Decisions
A. What are the results of the risk
assessment and analyses?
B. What are our proposed decisions
regarding risk acceptability, ample
margin of safety, and adverse
environmental effect?
C. What are the results and proposed
decisions based on our technology
review?
VII. Consideration of Separate Subcategory
and Acid Gas Standard for Existing EGUs
That Fire Eastern Bituminous Coal
Refuse
A. Background
B. Basis for Consideration of a Subcategory
C. Potential Subcategory Emission
Standards
VIII. Summary of Cost, Environmental, and
Economic Impacts
IX. Request for Comments
X. Submitting Data Corrections
XI. 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
Regulation and Controlling Regulatory
Costs
C. Paperwork Reduction Act (PRA)
D. Regulatory Flexibility Act (RFA)
E. Unfunded Mandates Reform Act
(UMRA)
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
Risks and Safety Risks
I. Executive Order 13211: Actions
Concerning Regulations That
Significantly Affect Energy Supply,
Distribution, or Use
J. National Technology Transfer and
Advancement Act (NTTAA)
K. Executive Order 12898: Federal Actions
to Address Environmental Justice in
Minority Populations and Low-Income
Populations
I. General Information
A. Does this action apply to me?
Table 1 of this preamble lists the
NESHAP and associated regulated
industrial source categories that are the
subject of this proposal. Table 1 is not
intended to be exhaustive, but rather
provides a guide for readers regarding
the entities that this proposed action is
likely to affect. The proposed standards,
once promulgated, will be directly
applicable to the affected sources.
Federal, state, local, and tribal
government entities that own and/or
operate EGUs subject to 40 CFR part 63,
subpart UUUUU would be affected by
this proposed action. The Coal- and OilFired EGU source category was added to
the list of categories of major and area
sources of HAP published under section
112(c) of the CAA on December 20, 2000
(65 FR 79825). CAA section 112(a)(8)
defines an electric utility steam
generating unit as: Any fossil fuel fired
combustion unit of more than 25
megawatts that serves a generator that
produces electricity for sale. A unit that
cogenerates steam and electricity and
supplies more than one-third of its
potential electric output capacity and
more than 25 megawatts electrical
output to any utility power distribution
system for sale is also considered an
EGU.
TABLE 1—NESHAP AND INDUSTRIAL SOURCE CATEGORIES AFFECTED BY THIS PROPOSED ACTION
NAICS code 1
Source category
NESHAP
Coal- and Oil-Fired EGUs ................................................
40 CFR part 63, subpart UUUUU ...................................
1 North
221112, 221122, 921150
American Industry Classification System.
II. Appropriate and Necessary Finding
B. Where can I get a copy of this
document and other related
information?
In addition to being available in the
docket, an electronic copy of this action
is available on the internet. Following
signature by the EPA Administrator, the
EPA will post a copy of this proposed
action at https://www.epa.gov/mats/
regulatory-actions-final-mercury-andair-toxics-standards-mats-power-plants.
Following publication in the Federal
Register, the EPA will post the Federal
Register version of the proposal and key
technical documents at this same
website. Information on the overall RTR
program is available at https://
www3.epa.gov/ttn/atw/rrisk/rtrpg.html.
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A. Overview
The EPA proposes this revised action
in response to the U.S. Supreme Court
decision in Michigan v. EPA, 135 S.Ct.
2699 (2015), which held that the EPA
erred by not considering cost in its
determination that regulation of HAP
emissions from coal- and oil-fired EGUs
is appropriate and necessary under CAA
section 112. In this action, after
considering the cost of compliance
relative to the HAP benefits of
regulation, the EPA proposes to find
that it is not ‘‘appropriate and
necessary’’ to regulate HAP emissions
from coal- and oil-fired EGUs, thereby
reversing the Agency’s conclusion
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under CAA section 112(n)(1)(A), first
made in 2000 and later affirmed in 2012
and 2016. This proposed response
corrects flaws in the EPA’s prior 2016
response to Michigan (82 FR 24420)
and, if finalized, would supplant that
2016 action. We also propose that
finalizing this action will not remove
the Coal- and Oil-Fired EGU source
category from the CAA section 112(c)(1)
list, nor will finalizing this action affect
the existing CAA section 112(d)
emissions standards promulgated in
2012 that regulate HAP emissions from
coal- and oil-fired EGUs, although this
action requests comment on that
proposed conclusion and whether the
EPA has the authority or obligation to
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delist the source category and rescind
the standards, or to rescind the
standards without delisting (Comment
C–1).
B. Background
In the 1990 Amendments to the CAA,
Congress substantially modified CAA
section 112, the provision of the CAA
addressing HAP. That provision
includes CAA section 112(b)(1), which
sets forth a list of 187 identified HAP,
and CAA sections 112(b)(2) and (3),
which give the EPA the authority to add
or remove pollutants from the list. CAA
section 112(a)(1) and (2) also specify the
two types of sources to be addressed:
Major sources and area sources. A major
source is any stationary source or group
of stationary sources at a single location
and under common control that emits or
has the potential to emit, considering
controls, 10 tons per year (tpy) or more
of any HAP or 25 tpy or more of any
combination of HAP. CAA section
112(a)(1). Any stationary source of HAP
that is not a major source is an area
source. CAA section 112(a)(2). All major
source categories, besides EGUs, were
required to be included on a published
list of sources subject to regulation
under CAA section 112, see CAA
sections 112(a)(1) and (c)(1), and area
sources ‘‘which the Administrator finds
presents a threat of adverse effects to
human health or the environment (by
such sources individually or in the
aggregate) warranting regulation under
this section’’ were also required to be
added to the list, see CAA section
112(c)(3). The EPA was to promulgate
emission standards under CAA section
112(d) for those source categories on the
list.
This general CAA section 112(c)
process of listing and regulation does
not apply to EGUs. Instead, Congress
enacted a special provision, CAA
section 112(n)(1)(A), which established
a separate process by which the EPA
was to determine whether to regulate
emissions of HAP from EGUs under
CAA section 112. CAA section
112(n)(1)(A) directs the EPA to conduct
a study to evaluate the hazards to public
health that are reasonably anticipated to
occur as a result of the HAP emissions
from EGUs, after the imposition of other
CAA provisions. The provision directs
that the EPA shall regulate EGUs under
CAA section 112 if the Administrator
determines, after considering the results
of the study, that such regulation is
‘‘appropriate and necessary.’’ CAA
section 112(n)(1)(A), therefore, sets a
unique process by which the
Administrator is to determine whether
to establish CAA section 112(d)
standards for EGUs. Moreover, the
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statute includes a separate definition of
‘‘EGU’’ which does not distinguish
between major and area sources. CAA
section 112(a)(8).
On December 20, 2000, the EPA
determined, pursuant to CAA section
112(n)(1)(A), that it was appropriate and
necessary to regulate coal- and oil-fired
EGUs under CAA section 112(d) and
added such units to the CAA section
112(c) List of Categories of Major and
Area Sources. 65 FR 79825 (2000
Finding). The EPA reversed that finding
in 2005, concluding that it was neither
appropriate nor necessary to regulate
EGUs under CAA section 112(n)(1)(A),
and stating that the effect of its reversal
of the appropriate and necessary finding
was removal of coal- and oil-fired EGUs
from the CAA section 112(c)(1) source
category list. 70 FR 15994 (March 29,
2005) (2005 Delisting Rule). The EPA
concurrently issued the Clean Air
Mercury Rule (CAMR), which regulated
mercury (Hg) from new and existing
coal-fired EGUs under CAA sections
111(b) and (d). The United States Court
of Appeals for the District of Columbia
(DC) Circuit (the Court) vacated the
EPA’s 2005 Delisting Rule in New Jersey
v. EPA, 517 F.3d 574 (D.C. Cir. 2008).
The Court ruled that the fact that the
EPA had reversed its prior appropriate
and necessary finding did not mean that
the Agency could remove the Coal- and
Oil-Fired EGU source category from the
CAA section 112(c)(1) list without going
through the generally applicable CAA
section 112(c)(9) delisting procedures.
Id. Instead, the Court held that the
Agency could only remove EGUs from
the CAA section 112(c)(1) list after
finding that the statutory criteria for
delisting set forth in CAA section
112(c)(9) had been met. Id. In addition,
the Court also vacated CAMR in light of
the EPA’s concession that it had no
authority to regulate Hg from EGUs
under CAA section 111 so long as EGUs
remained on the CAA section 112(c)(1)
source category list. 517 F.3d 574 (D.C.
Cir. 2008). (The Court did not address
the merits of CAMR under CAA section
111; its vacatur was based solely on its
holding that the delisting from CAA
section 112 was improper.)
On May 3, 2011, the EPA proposed to
reaffirm the 2000 appropriate and
necessary finding and proposed
NESHAP for coal- and oil-fired EGUs,
known as MATS. 76 FR 24976. The final
MATS rule was subsequently issued on
February 16, 2012. 77 FR 9304.
Industry, states, environmental
organizations, and public health
organizations challenged many aspects
of both the re-affirmed appropriate and
necessary finding and the final MATS
rule in the D.C. Circuit. The Court
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denied all challenges. White Stallion
Energy Center v. EPA, 748 F.3d 1222
(D.C. Cir. 2014). Some industry and
state petitioners sought further review of
the final MATS rule, and the U.S.
Supreme Court granted certiorari to
determine whether the EPA erred when
it concluded that it could properly make
the appropriate and necessary finding
under CAA section 112(n)(1)(A) without
consideration of cost. On June 29, 2015,
the Supreme Court ruled that the EPA
‘‘strayed far beyond [the] bounds’’ of
reasonable interpretation when it
determined cost was irrelevant to the
appropriate and necessary finding.
Michigan v. EPA, 135 S Ct. 2699, 2707
(2015). Specifically, the Supreme Court
held that cost was ‘‘an important aspect
of the problem’’ and that the Agency
was required to consider the cost of
regulation before deciding whether it
was appropriate and necessary to
impose that regulation on EGUs under
CAA section 112. Id. On remand from
the Supreme Court, the D.C. Circuit left
MATS in effect while the Agency
addressed the Michigan decision. Order,
White Stallion Energy Center v. EPA,
No. 12–1100 (D.C. Cir. Dec. 15, 2015)
(ECF No. 1588459).
On April 25, 2016, after public notice
and comment,1 the EPA finalized a
supplemental finding (2016
Supplemental Finding) concluding that
its consideration of cost did not change
its previous determination that
regulation of HAP emissions from coaland oil-fired EGUs is appropriate and
necessary. 82 FR 24420. In the 2016
Supplemental Finding, the EPA
considered costs under two alternative
approaches. Under the first approach,
the EPA evaluated compliance costs in
comparison to the industry’s historical
annual revenues and annual capital
expenditures, and examined impacts of
the rule on retail electricity prices. The
EPA concluded that because these costs
were within the range of historical
variability, the cost of MATS was
reasonable. The EPA also found that the
power sector could continue to perform
its primary function—the generation,
transmission, and distribution of
reliable electricity at reasonable cost—
after imposition of the MATS rule.
Based on the conclusion that the costs
of the rule were ‘‘reasonable’’ and
considering the benefits of reducing
HAP that had been identified in earlier
agency determinations, the Agency
affirmed the appropriate and necessary
finding under CAA section 112(n)(1)(A).
In the 2016 Supplemental Finding,
the EPA also presented a second,
alternative and independent, approach
1 80
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to considering cost. This approach
considered the results of the formal
cost-benefit analysis that the Agency
had previously performed for the
regulatory impact analysis (RIA) for the
final MATS rule.2 That RIA cost-benefit
analysis accounted for the monetized
and non-monetized benefits of MATS,
including HAP-related benefits that
could not be quantified or monetized, as
well as the monetized co-benefits of
reducing pollutants other than HAP.
The RIA analysis found that its
projection of these aggregated benefits
($37 to $90 billion each year) exceeded
the costs of compliance ($9.6 billion) by
three to nine times. The EPA, therefore,
concluded that the RIA’s cost-benefit
analysis also supported its affirmation
of the prior appropriate and necessary
finding under CAA section 112(n)(1)(A).
82 FR 24420.
A number of state and industry
groups petitioned for review of the 2016
Supplemental Finding in the D.C.
Circuit. Murray Energy Corp. v. EPA,
No. 16–1127 (D.C. Cir. filed April 25,
2016). In April 2017, given its interest
in reviewing the 2016 action, the EPA
moved the Court to continue oral
argument and hold the case in abeyance
in order to give the new Administration
an opportunity to undertake that review.
The Court granted the EPA’s request for
a continuance on April 27, 2017. Order,
Murray Energy Corp. v. EPA, No. 16–
1127 (D.C. Cir. April 27, 2017) (ECF No.
1672987).
C. The EPA’s Proposed Finding Under
CAA Section 112(n)(1)(A)
In this action, the EPA proposes to
conclude that the 2016 Supplemental
Finding was flawed and that, after
considering the cost of compliance
relative to the HAP benefits of MATS,
it is not appropriate and necessary to
regulate coal- and oil-fired EGUs under
section 112 of the CAA. CAA section
112(n)(1)(A) requires the EPA to
determine that both the appropriate and
the necessary prongs are met. Therefore,
if the EPA finds that either prong is not
satisfied, it cannot make an affirmative
appropriate and necessary finding. Cf.
70 FR 16000. The EPA’s reexamination
of its determination in this proposal
focuses on the first prong of that
analysis: Whether regulation is
‘‘appropriate,’’ after consideration of the
costs and benefits of such regulation.
The EPA has reexamined the cost
analyses presented in the 2016
2 U.S. EPA. 2011. Regulatory Impact Analysis for
the Final Mercury and Air Toxics Standards. EPA–
452/R–11–011. Available at https://www3.epa.gov/
ttn/ecas/docs/ria/utilities_ria_final-mats_201112.pdf. Docket ID No. EPA–HQ–OAR–2009–0234–
20131.
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Supplemental Finding and proposes to
determine that neither of the Finding’s
approaches to considering cost satisfies
the Agency’s obligation under CAA
section 112(n)(1)(A) as interpreted by
the Supreme Court in Michigan. Instead,
we use a different consideration of cost
for purposes of the appropriate and
necessary finding, one that we believe
aligns with the purpose of CAA section
112(n)(1)(A) as set forth in Michigan.3
We propose to directly compare the cost
of compliance with MATS with the
benefits specifically associated with
reducing emissions of HAP as the
primary inquiry in this finding, in order
to satisfy our duty to consider cost in
the context of CAA section 112(n)(1)(A).
The EPA also proposes that, because
a negative appropriate and necessary
finding cannot by itself remove a source
category from the CAA section 112(c)
list, see New Jersey, 517 F.3d at 582,
finalizing this finding will neither
remove the Coal- and Oil-Fired EGU
source category from the CAA section
112(c) list, nor will it alter or eliminate
the CAA section 112(d) emissions
standards imposed by MATS. The EPA
solicits public comment on all aspects
of this proposal, and retains the
discretion, as always, to make changes
3 Agencies have inherent authority to reconsider
past decisions and to revise, replace, or repeal a
decision to the extent permitted by law and
supported by a reasoned explanation. FCC v. Fox
Television Stations, Inc., 556 U.S. 502, 515 (2009);
Motor Vehicle Mfrs. Ass’n v. State Farm Mutual
Auto. Ins. Co., 463 U.S. 29, 42 (1983) (‘‘State
Farm’’). The EPA’s interpretations of the statutes it
administers are not ‘‘carved in stone,’’ but must be
evaluated ‘‘on a continuing basis,’’ for example, ‘‘in
response to . . . a change in administrations.’’ Nat’l
Cable & Telecomms. Ass’n v. Brand X internet
Servs., 545 U.S. 967, 981 (2005) (internal quotation
marks and citations omitted). An agency’s reasoning
can include a change in policy on the basis that
‘‘the agency believes it to be better,’’ even if a court
might disagree. White Stallion, 748 F.3d at 1235; see
also Nat’l Ass’n of Home Builders v. EPA, 682 F.3d
1032, 1038 & 1043 (D.C. Cir. 2012) (a revised
rulemaking based ‘‘on a reevaluation of which
policy would be better in light of the facts’’ is ‘‘well
within an agency’s discretion,’’ and ‘‘ ‘[a] change in
administration brought about by the people casting
their votes is a perfectly reasonable basis for an
executive agency’s reappraisal of the costs and
benefits of its programs and regulations’ ’’) (quoting
State Farm, 463 U.S. at 59 (Rehnquist, J., concurring
in part and dissenting in part)). The CAA
complements the EPA’s inherent authority to
reconsider prior rulemakings by providing the
Agency with broad authority to prescribe
regulations as necessary to carry out the
Administrator’s authorized functions under the
statute. 42 U.S.C. 7601(a). This broad discretion can
be limited by Congress, however. In New Jersey v.
EPA, the D.C. Circuit held that a reversal of the
appropriate and necessary finding would not have
the effect of removing Coal- and Oil-Fired EGUs
from the CAA section 112(c)(1) source category list
because Congress ‘‘unambiguously limit[ed] EPA’s
discretion’’ by fashioning a statutorily mandated
avenue for removing source categories from the list
in CAA section 112(c)(9). 517 F.3d 574, 582–83.
(D.C. Cir. 2008).
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in response to those comments prior to
finalizing this rule or to decide not to
finalize some or all aspects of this
proposal after considering public
comments.
1. The 2016 Supplemental Finding Was
an Improper Response to Michigan v.
EPA
a. The ‘‘Cost Reasonableness’’ Approach
Does Not Satisfy the Agency’s
Obligation Under CAA Section
112(n)(1)(A)
We propose to find that the Agency’s
2016 Supplemental Finding erred in its
consideration of cost. Specifically, we
find that what was described in the
2016 Supplemental Finding as the
preferred approach, or ‘‘cost
reasonableness test,’’ does not meet the
statute’s requirements to fully consider
costs, and was an unreasonable
interpretation of CAA section
112(n)(1)(A)’s mandate, as informed by
the Supreme Court’s opinion in
Michigan. In its 2016 Supplemental
Finding, the EPA developed a ‘‘cost
reasonableness test’’ based on D.C.
Circuit opinions that had evaluated the
Agency’s consideration of cost in the
context of setting new source
performance standards under section
111 of the CAA. See Legal
Memorandum Accompanying the
Proposed Supplemental Finding that it
is Appropriate and Necessary to
Regulate Hazardous Air Pollutants from
Coal- and Oil-Fired Electric Utility
Steam Generating Units (EGUs) (2015
Legal Memorandum). Because those
opinions interpreted CAA section 111 to
only prohibit the Agency from adopting
standards for new sources whose cost
would be ‘‘exorbitant,’’ Lignite Energy
Council v. EPA, 198 F.3d 930, 933 (D.C.
Cir. 1999), ‘‘excessive,’’ or
‘‘unreasonable,’’ Sierra Club v. Costle,
657 F.2d 298, 383 (D.C. Cir. 1981), we
concluded that we could consider cost
for CAA section 112(n)(1)(A) by
determining whether cost of compliance
was ‘‘reasonable’’—in other words,
whether the cost of regulation could be
absorbed by the power sector without
negatively affecting the industry’s
ability to continue performing its
primary function. That ‘‘cost
reasonableness test’’ compared
compliance costs of MATS relative to
historical annual revenues and annual
capital expenditures, and evaluated the
impacts of the rule on retail electricity
prices. Because we found that the costs
of compliance with the rule across the
entire utility sector were within
historical variability and would not shut
down the sector as a whole, the EPA
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concluded that the cost of compliance
with MATS was reasonable.
The Agency claimed that use of the
‘‘cost reasonableness test’’ for its CAA
section 112(n)(1)(A) appropriate and
necessary finding was supported by the
‘‘overall statutory objectives of section
112,’’ and stated that ‘‘cost was but one
factor among many’’ that the EPA must
consider. See Legal Memorandum at 20.
We also interpreted CAA section
112(n)(1)(A) and Michigan not to require
the EPA to assume that a consideration
of cost should predominate or take
primary significance to the
subordination of other considerations,
because of CAA section 112’s overall
concern with the nature of HAP
emissions and populations that might be
particularly sensitive to harms
associated with those emissions. Id.
In this notice, we are proposing to
find that the EPA did not comply with
its statutory duty to consider cost as part
of the appropriate and necessary finding
in the 2016 Supplemental Finding. The
2016 Supplemental Finding repeatedly
emphasized that the Michigan Court did
not hold that the CAA ‘‘unambiguously
required’’ the EPA to perform a formal
cost-benefit analysis to satisfy CAA
112(n)(1)(A). 135 S. Ct. at 2711. But, as
discussed below, the 2016
Supplemental Finding, among other
flaws, ignored observations about the
importance of the cost consideration to
the appropriate and necessary finding,
as provided by the Court in Michigan.
Contrary to the 2015 Legal
Memorandum’s suggestion that cost
should not ‘‘trump’’ or ‘‘predominate’’
other considerations, the Supreme Court
observed that ‘‘[a]gencies have long
treated cost as a centrally relevant factor
when deciding whether to regulate.’’ Id.
at 2707 (emphasis added). The Supreme
Court rejected arguments that the
general goals of CAA section 112 make
cost irrelevant to a CAA section
112(n)(1)(A) appropriate and necessary
finding. As such, the EPA must
meaningfully consider cost when
making this threshold finding. In
addition, the Supreme Court
emphasized that CAA section
112(n)(1)(A) reflects Congress’s intent
that the EPA treat EGUs differently from
other sources. Id. at 2710. The attempt
made in the 2016 Supplemental Finding
to ‘‘harmonize’’ CAA section
112(n)(1)(A) with the remainder of CAA
section 112 is, therefore, not consistent
with Congress’s intent and the Supreme
Court’s decision in Michigan v. EPA.
The 2016 Supplemental Finding’s
reliance on case law pertaining to CAA
section 111(b) new source rules was
similarly misguided. The methodologies
that courts have approved for
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considering costs of control
technologies for new sources that have
not yet been constructed are not
particularly informative in the context
of EPA’s deciding whether it is
appropriate to impose control
requirements on sources that are already
operating. Costs of control technologies
for new sources are borne as each source
is added to the fleet of existing sources
and are not imposed on the entire fleet
of existing sources within a period of a
few years, as is required under CAA
section 112. Moreover, the case law
cited by the 2015 Legal Memorandum is
distinguishable even without regard to
the fact that different statutory
provisions (CAA section 111 versus 112)
are at issue. For example, in Lignite
Council, the D.C. Circuit found that the
‘‘new standards will only modestly
increase the cost of producing electricity
in newly constructed boilers.’’ Lignite
Energy Council v. United States EPA,
198 F.3d at 933. Even in its flawed
conclusion that the cost of MATS was
‘‘reasonable,’’ the EPA did not go so far
as to say that the costs of that rule were
in any way ‘‘modest.’’
The primary, fatal flaw of the 2016
Supplemental Finding’s ‘‘preferred
approach’’ was its disregard for the
Michigan Court’s suggestion that, under
CAA section 112(n)(1)(A), the Agency
must meaningfully consider cost within
the context of a regulation’s benefits.
The decision contemplated that a proper
consideration of cost would be relative
to benefits. For example, the Court
questioned whether a regulation could
be considered ‘‘rational’’ where there
was a gross imbalance between costs
and benefits and stated that ‘‘[n]o
regulation is ‘‘appropriate’’ if it does
more harm than good.’’ Id. The Court
also made numerous references to a
direct comparison of the costs of MATS
with benefits from reducing emissions
of HAP. For instance, the Court pointed
out that ‘‘[t]he costs [of MATS] to power
plants were thus between 1,600 and
2,400 times as great as the quantifiable
benefits from reduced emissions of
hazardous air pollutants.’’ Id. at 2706.
Although the decision established no
bright-line rules, it suggested that CAA
section 112(n)(1)(A)’s requisite
consideration of cost would not be met
if the cost analysis did not ‘‘ensure costeffectiveness’’ or ‘‘prevent the
imposition of costs far in excess of
benefits.’’ Id. at 2710.
For these reasons, the 2016
Supplemental Finding’s ‘‘test’’ of
whether an industry can bear the cost of
regulation does not demonstrate that the
cost of MATS was ‘‘reasonable’’ under
the particular statutory context. More
importantly, the metrics ‘‘tested’’ by the
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2675
Agency in the 2016 Supplemental
Finding are irrelevant to the
determination of whether it is
‘‘appropriate and necessary’’ to impose
that regulation. Each cost metric the
Agency examined compared the cost of
MATS to other costs borne by the
industry, but never in its ‘‘preferred
approach’’ did the Agency make the
statutorily mandated assessment of
whether the benefits garnered by the
rule were worth it—i.e., a direct
comparison of costs and benefits.
Because the ‘‘cost reasonableness test’’
failed to consider cost in a meaningful
way relative to benefits, we, therefore,
conclude that approach did not
adequately address the Supreme Court’s
instruction that a reasonable regulation
requires an agency to fully consider ‘‘the
advantages and the disadvantages’’ of a
decision. See Michigan, 135 S. Ct. at
2707 (emphasis in original). Instead, we
propose to reconsider cost using a more
direct comparison of benefits and costs
to address the Supreme Court’s remand
of the appropriate and necessary
determination, as described below. As
noted below, final action on this
proposal would replace the 2016
Supplemental Finding.
b. The Cost-Benefit Approach in the
2016 Supplemental Finding’s
Alternative Approach Improperly
Considered Co-benefits From Non-HAP
Emissions Reductions
In the 2016 Supplemental Finding’s
alternative approach, the EPA
improperly made an independent
finding under CAA section 112(n)(1)(A)
that was based on a formal benefit-cost
analysis, which evaluates whether a
regulation will increase economic
efficiency, to find that it was
appropriate and necessary to regulate
EGUs under CAA section 112. See 81 FR
24425.4 The formal benefit-cost analysis
relied on information reported in the
RIA performed for the MATS rule. The
quantified benefits accounted for in the
formal benefit-cost analysis in the 2016
Supplemental Finding’s alternative
approach included both HAP and nonHAP air quality benefits. In this action,
we propose to find that the EPA’s equal
reliance on the particulate matter (PM)
air quality co-benefits projected to occur
as a result of the reductions in HAP was
flawed as the focus of CAA section
4 We use the term ‘‘formal benefit-cost analysis’’
to refer to an economic analysis that attempts to
quantify all significant consequences of an action in
monetary terms in order to determine whether an
action increases economic efficiency. Assuming
that all consequences can be monetized, actions
with positive net benefits (i.e., benefits exceed
costs) improve economic efficiency.
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112(n)(1)(A) is HAP emissions
reductions.
The EPA developed an RIA for the
2012 final MATS rule pursuant to
Executive Orders 12866 and 13563 and
other applicable statutes (e.g., the
Regulatory Flexibility Act and the
Unfunded Mandates Reform Act), as
informed by OMB guidance 5 and the
EPA’s Economic Guidelines.6 The
analyses the EPA conducted generated
an estimate of the quantifiable benefits
of HAP reductions under the rule of $4
to $6 million annually.7 The EPA also
analyzed the PM air quality co-benefits
of MATS and attributed these benefits to
the rule. The RIA included in its
analysis a consideration of the cobenefit reductions in the emissions of
pollutants other than the HAP regulated
by MATS, such as nitrogen oxides
(NOX) and sulfur dioxide (SO2), which
contribute to the formation of fine
particulate matter (PM2.5). Reductions of
these NOX and SO2 emissions result
from installing control technologies and
implementing the compliance strategies
necessary to reduce the HAP emissions
directly regulated by MATS. The EPA
projected that the co-benefits associated
with reducing these non-HAP pollutants
would be substantial. Indeed, these
projected co-benefits comprised the
overwhelming majority (approximately
99.9 percent) of the monetized benefits
of MATS reflected in the EPA’s RIA
($36 billion to $89 billion). By
comparison, compliance costs of the
final MATS rule were projected to be
$9.6 billion in 2015, and $8.6 billion
and $7.4 billion in 2020 and 2030,
respectively.8 These compliance costs
are an estimate of the increased
expenditures in capital, fuel, and other
inputs by the entire power sector to
comply with the EPA’s requirements,
while continuing to provide a given
level of electricity demand. In the 2016
Supplemental Finding’s alternative
approach, to satisfy the required
consideration of cost when determining
whether it is appropriate and necessary
to regulate under CAA section
5 U.S. OMB. 2003. Circular A–4 Guidance to
Federal Agencies on Preparation of Regulatory
Analysis. Available at https://www.whitehouse.gov/
sites/whitehouse.gov/files/omb/circulars/A4/a4.pdf.
6 U.S. EPA. 2014. Guidelines for Preparing
Economic Analyses. EPA–240–R–10–001. National
Center for Environmental Economics, Office of
Policy. Washington, DC. December. Available at
https://www.epa.gov/environmental-economics/
guidelines-preparing-economic-analyses. Docket ID
No. EPA–HQ–OAR–2009–0234–20503.
7 Like the MATS RIA, all benefits and costs in this
and subsequent sections are reported in 2007
dollars.
8 See Table 3–5 of the RIA: https://www3.epa.gov/
ttn/ecas/docs/ria/utilities_ria_final-mats_201112.pdf.
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112(n)(1)(A), the EPA compared these
monetized costs to the monetized
benefits, along with unquantified and
unmonetized effects, to conclude that
MATS would increase economic
efficiency and, therefore, reaffirmed its
earlier finding that it was appropriate
and necessary to regulate EGUs.
The EPA’s justification for its equal
reliance on the co-benefits of non-HAP
emissions when setting the MATS
standards in its CAA section
112(n)(1)(A) determination was flawed.
The Agency erred in concluding that the
statutory text of CAA section
112(n)(1)(A) and the legislative history
of CAA section 112 more generally
‘‘expressly support[ed]’’ the position
that it was reasonable to consider cobenefits, and give equal weight to those
co-benefits, in a CAA section
112(n)(1)(A) appropriate and necessary
finding. 81 FR 24439. The 2016
Supplemental Finding pointed to CAA
section 112(n)(1)(A)’s directive to
‘‘perform a study of the hazards to
public health reasonably anticipated to
occur as a result of emissions by electric
utility steam generating units of [HAP]
after imposition of the requirements of
[the CAA],’’ and noted that the
requirement to consider co-benefit
reduction of HAP resulting from other
CAA programs highlighted Congress’
understanding that programs targeted at
reducing non-HAP pollutants can and
do result in the reduction of HAP
emissions. Id. The finding also noted
that the Senate Report on CAA section
112(d)(2) recognized that maximum
achievable control technology (MACT)
standards would have the collateral
benefit of controlling criteria pollutants.
Id. However, these statements
acknowledging that reductions in HAP
can have the collateral benefit of
reducing non-HAP emissions and vice
versa, provides no support for the
proposition that any such co-benefits
should be the Agency’s primary
consideration when making a finding
under CAA section 112(n)(1)(A). Indeed,
it would be highly illogical for the
Agency to make a determination that
regulation under CAA section 112,
which is expressly designed to deal
with HAP, is justified principally on the
basis of the criteria pollutant impacts of
these regulations. That is, if the HAPrelated benefits are not at least
moderately commensurate with the cost
of HAP controls, then no amount of cobenefits can offset this imbalance for
purposes of a determination that it is
appropriate to regulate under CAA
section 112(n)(1)(A). Cf. Michigan, 135
S. Ct. at 2707 (‘‘One would not say that
it is even rational, never mind
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‘‘appropriate,’’ to impose billions of
dollars in economic costs in return for
a few dollars in health or environmental
benefits.’’).
The 2016 Supplemental Finding’s
benefit-cost approach also erred in
implying that the results of an economic
efficiency test, as informed by the
benefit-cost analysis presented in the
MATS RIA, should govern the cost
consideration assessment in CAA
section 112(n)(1)(A). A formal benefitcost analysis does not dictate how cost
should be considered under CAA
section 112(n)(1)(A), particularly where,
as noted above, the statutory provision
indicates Congress’ particular concern
about risks associated with HAP and the
benefits that would accrue from
reducing those risks. Although an
analysis of all benefits and costs in
accordance with generally recognized
benefit-cost analysis practices is
appropriate for informing the public
about the potential effects of any
regulatory action, as well as for
complying with the requirements of
Executive Order 12866, this does not
mean that equal consideration of all
benefits and costs, including cobenefits, is appropriate for the specific
statutory appropriate and necessary
finding called for under CAA section
112(n)(1)(A). Rather this finding is
necessarily governed by the particular
statutory language and context of this
provision, as discussed below.
In sum, the Agency did not provide
any meaningful support for its
conclusion that the statutory text and
legislative history support placing
consideration of co-benefits in a CAA
section 112(n)(1)(A) determination on
equal footing with the consideration of
HAP-specific benefits and, as explained
below, the statutory text strongly
supports the use of a different approach.
2. It Is Not Appropriate and Necessary
To Regulate EGUs Under CAA Section
112
In this action, the EPA proposes to
conclude that it is not appropriate and
necessary to regulate HAP from EGUs
under CAA section 112 because the
costs of such regulation grossly
outweigh the HAP benefits. The EPA is
taking comment on its proposal that
direct comparison of the rule’s costs and
benefits is a reasonable approach, if not
the only permissible approach, to
considering costs in response to
Michigan, and, further, that such a
comparison performed under CAA
section 112(n)(1)(A) should focus
primarily on benefits associated with
reduction of HAP (Comment C–2). A
proper consideration of costs based on
this approach demonstrates that the
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total cost of compliance with MATS
($7.4 to $9.6 billion annually) dwarfs
the monetized HAP benefits of the rule
($4 to $6 million annually). As
discussed further below, while there are
unquantified HAP benefits and
significant monetized PM co-benefits
associated with MATS, the
Administrator has concluded that the
identification of these benefits is not
sufficient, in light of the gross
imbalance of monetized costs and HAP
benefits, to support a finding that it is
appropriate and necessary to regulate
EGUs under CAA section 112.
The statutory text of CAA section
112(n)(1)(A) and the Michigan decision
both support focusing the ‘‘appropriate
and necessary’’ determination on HAPspecific benefits and costs. The study
referenced in CAA section 112(n)(1)(A)
specifically focuses on the hazards to
public health that will reasonably occur
as a result of HAP emissions, not
harmful emissions in general. According
to this section, ‘‘The Administrator shall
regulate electric utility steam generating
units under this section, if the
Administrator finds such regulation is
appropriate and necessary after
considering the results of the study
required by this subparagraph.’’ The
text, on its face, thus, suggests that
Congress wanted the Administrator’s
appropriate and necessary
determination to be focused on the
health hazards related to HAP emissions
and the potential benefits of avoiding
those hazards by reducing HAP
emissions. As noted in section II.C.1.b.
of this preamble, while the provision
acknowledges the existence of the
phenomenon of co-benefits by
referencing the potential for ancillary
reductions of HAP emissions by way of
CAA provisions targeted at other
pollutants, acknowledgement of that
fact does not address whether ancillary
reductions of criteria pollutants should
be part of the Administrator’s
determination under CAA section
112(n)(1)(A), which is undeniably
focused on hazards resulting from HAPspecific emissions. Indeed, the direction
to consider whether it is appropriate
and necessary to regulate HAP after
criteria pollutants have been addressed
by the CAA’s other requirements is, if
anything, support for the conclusion
that it is not proper to place much
weight on the co-benefits of further
criteria pollutant reductions as part of
the CAA section 112(n)(1)(A)
determination. Directing the EPA to
study HAP effects under CAA section
112 after other provisions of the CAA
had been implemented suggests that
Congress envisioned that the judgement
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about whether additional regulation was
appropriate and necessary should be
predicated primarily on an assessment
of HAP emissions from this source
category. Similarly, the general
recognition of the existence of collateral
benefits or controlling criteria pollutants
in CAA section 112’s legislative
history 9 does not shed any light on
whether such benefits should be given
equal consideration in a CAA section
112(n)(1)(A) determination. This is
particularly so where that legislative
history is unconnected to CAA section
112(n)(1)(A), a special provision written
by Congress to address the unique
circumstances facing EGUs. In fact, it
would not be reasonable to rely on such
legislative history in light of the
Supreme Court’s conclusion that the
Agency erred attempting to
‘‘harmonize’’ CAA section 112(n)(1)(A)
with the remainder of CAA section 112.
As the Court noted, ‘‘[t]his line of
reasoning overlooks the whole point of
having a separate provision about power
plants: Treating power plants different
from other stationary sources.’’
Michigan, 135 S. Ct. at 2710.
Finally, we note that this action
proposes to primarily consider the costs
of MATS in comparison with the HAP
benefits of the hazardous pollution
reductions from MATS. In keeping with
CAA section 112(n)(1)(A) and the
overall structure of the CAA, we think
it is appropriate not to give equal weight
to non-HAP co-benefits in this
comparison. Congress established a
rigorous system for setting standards of
acceptable levels of criteria air
pollutants and wrote a comprehensive
framework directing the implementation
of those standards in order to address
the health and environmental impacts
associated with those pollutants. See,
e.g., 42 U.S.C. 7409; 7410; 7501; 7502;
7505a; 7506; 7506a; 7507; 7509; 7509a;
7511; 7511a; 7511b; 7511c; 7511d;
7511e; 7511f; 7512; 7512a; 7513; 7513a;
7513b; 7514; and 7515. As noted above,
the vast majority of estimated monetized
benefits resulting from MATS are
associated with reductions in PM2.5
precursor emissions, principally NOX
and SO2. Both NOX and SO2 are criteria
pollutants and precursors to criteria
pollutants that are already addressed by
the cavalcade of statutory provisions
governing levels of these pollutants,
including the National Ambient Air
Quality Standards (NAAQS) provisions
that require the EPA to set standards for
9 See Legal Memorandum at 25 n.28 (citing A
Legislative History of the Clean Air Act
Amendments of 1990, Vol. 5, at 8512 (CAA
Amendments of 1989, at 172, Report of the
Committee on Environment and Public Works,
S.1630)).
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criteria pollutants requisite to protect
public health with an adequate margin
of safety, and by state, regional, and
national rulemakings establishing
control measures to meet those levels.
To the extent that additional reductions
of these criteria pollutants are necessary
to protect public health, regulation
explicitly targeted at these pollutants is
best reserved for the NAAQS program,
under which Congress provided the
EPA ample authority to regulate.
The total cost of compliance with
MATS ($7.4 to $9.6 billion annually) 10
vastly outweighs the monetized HAP
benefits of the rule ($4 to $6 million
annually).11 Even with the substantial
monetized PM co-benefits and the
significant unquantified HAP benefits
associated with MATS, the gross
disparity between monetized costs and
HAP benefits, which we believe to be
the primary focus of the Administrator’s
determination in CAA section
112(n)(1)(A), is too large to support an
affirmative appropriate and necessary
finding. As explained in the MATS RIA,
the only health benefit attributed to
reducing Hg emissions that the EPA
could quantify and monetize was IQ
loss in children born to a subset of
recreational fishers who consume fish
during pregnancy.12 The EPA also
identified benefits associated with
regulation of HAP from EGUs that could
not be quantified. These effects include
impacts of Hg on human health
(including neurologic, cardiovascular,
genotoxic, and immunotoxic effects), a
variety of adverse health effects
associated with exposure to certain nonHg HAP (including cancer, and chronic
and acute health disorders that
implicate multiple organ systems such
as the lungs and kidneys), and effects on
wildlife and ecosystems.13 14
The EPA acknowledges the
importance of these benefits and the
limitations on the Agency’s ability to
monetize HAP-specific benefits. The
10 See Table 3–5 on page 3–14 and Table 3–16 on
page 3–31 of the MATS RIA.
11 See Table ES–4 on page ES–6 of the MATS RIA.
12 U.S. EPA, 2011. Revised Technical Support
Document: National-Scale Assessment of Mercury
Risk to Populations with High Consumption of SelfCaught Freshwater Fish In Support of the
Appropriate and Necessary Finding for Coal- and
Oil-Fired Electric Generating Units. Office of Air
Quality Planning and Standards. November. EPA–
452/R–11–009. Docket ID No. EPA–HQ–OAR–
2009–0234–19913.
13 See Chapters 4 and 5 of the MATS RIA.
14 In addition, the MATS RIA attributed
unquantified health benefits to reductions in
emissions of nitrogen dioxide (NO2) and SO2.
However, as discussed above, these unquantified
criteria pollutant co-benefits are no longer relevant
given the different approach to considering such cobenefits that the EPA is now proposing to take. See
Chapter 5 of the MATS RIA.
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EPA agrees that such benefits are
relevant to any comparison of the
benefits and costs of a regulation.
Because unquantified benefits are, by
definition, not considered in monetary
terms, the Administrator must evaluate
the evidence of unquantified benefits
and determine the extent to which they
alter any conclusions based on the
comparison of monetized costs and
benefits. The MATS RIA accounts for all
the monetized and unquantified
benefits of the rule, and the EPA’s
proposed approach to the cost-benefit
analysis in the RIA does not discount
the existence or importance of the
unquantified benefits of reducing HAP
emissions.15 Instead, after fully
acknowledging the existence and
importance of such benefits, the EPA
proposes to conclude that substantial
and important unquantified benefits of
MATS are not sufficient to overcome the
significant difference between the
monetized benefits and costs of this
rule. As noted, the unquantified HAPrelated benefits of MATS involve only a
limited set of mercury and other HAPrelated morbidity effects in humans and
ecosystems. The EPA has provided an
updated comparison of costs and target
pollutant benefits in a memorandum to
the rulemaking docket.16 Table 1 of the
memorandum estimates that the net
target HAP benefits of the rule (HAP
benefits—costs) are negative. As noted
elsewhere in the notice, the actual costs
and benefits of the MATS rule may
differ from the EPA’s analysis. However,
as explained in the memorandum, given
that the CAA section 112(n)(1)(A)
finding is a threshold analysis that
Congress intended the Agency would
complete prior to regulation, the EPA
believes it is reasonable for purposes of
this reconsideration to rely on the
estimates projected prior to the rule’s
taking effect, i.e., the estimates of costs
and benefits calculated in the 2011 RIA.
In addition, even assuming that actual
15 Id. The Agency is not in this proposed
replacement to the 2016 Supplemental Finding
reopening the prior findings and risk assessments
made over the last two decades. The EPA also
explained in the MATS RIA that there are
significant obstacles to successfully quantifying and
monetizing the public health benefits from reducing
HAP emissions. These obstacles include gaps in
toxicological data, uncertainties in extrapolating
results from high-dose animal experiments to
estimate human effects at lower doses, limited
monitoring data, difficulties in tracking diseases
such as cancer that have long latency periods, and
insufficient economic research to support the
valuation of the health impacts often associated
with exposure to individual HAP.
16 Compliance Cost, HAP Benefits, and Ancillary
Co-Pollutant Benefits for ‘‘National Emission
Standards for Hazardous Air Pollutants: Coal-and
Oil-Fired Electric Utility Steam Generating Units—
Reconsideration of Supplemental Finding and
Residual Risk and Technology Review.’’
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costs and benefits differed from
projections made in 2011, given the
large difference between target HAP
benefits and estimated costs, the
outcome of the Agency’s proposed
finding here would likely stay the same.
For all of these reasons, and paying
particular heed to the statutory text and
purpose of CAA section 112(n)(1)(A) as
well as the Supreme Court’s direction in
Michigan, we propose to find that it is
not appropriate and necessary to
regulate coal- and oil-fired EGUs under
section 112 of the CAA.
D. Effects of This Proposed Replacement
of the Supplemental Finding
1. Effects of This Proposed Replacement
Final action on this proposed
replacement of the 2016 Supplemental
Finding will reverse the Agency’s
conclusion under CAA section
112(n)(1)(A), first made in 2000 and
later affirmed in 2012 and 2016, that it
is appropriate and necessary to regulate
HAP from EGUs. We propose to
conclude that finalizing this
replacement will not remove the Coaland Oil-Fired EGU source category from
the CAA section 112(c)(1) list, nor will
finalizing this revision otherwise affect
the existing CAA section 112(d)
emissions standards promulgated in
2012. Under D.C. Circuit case law, the
EPA’s determination that a source
category was listed in error does not by
itself remove a source category from the
CAA section 112(c)(1) list—even EGUs,
notwithstanding their special treatment
under CAA section 112(n). New Jersey v.
EPA, 517 F.3d 574 (D.C. Cir. 2008).
Instead, in order to remove a source
category from the CAA section 112(c)(1)
list, the EPA must determine that the
CAA section 112(c)(9) statutory criteria
for delisting have been met. Id. The EPA
requests comment on its interpretation
of New Jersey in the context of this
proposed finding (Comment C–3).
In 2005, the EPA reversed the
December 2000 Finding and concluded
that it was neither appropriate nor
necessary to regulate coal- and oil-fired
EGUs under CAA section 112 and
delisted such units from the CAA
section 112(c) source category list. 70
FR 15994. In that rule we stated, ‘‘EPA
reasonably interprets section
112(n)(1)(A) as providing it authority to
remove coal- and oil-fired units from the
section 112(c) list at any time that it
makes a negative appropriate and
necessary finding under the section.’’ 70
FR 16032 (2005 Delisting Rule). In the
2005 Delisting Rule, the EPA ‘‘identified
errors in the prior [2000] finding and
determined that the finding lacked
foundation.’’ Id. at 16033. Because we
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found that the 2000 Finding had been in
error at the time of listing, we
concluded that coal- and oil-fired EGUs
‘‘should never have been listed under
section 112(c) and therefore the criteria
of section 112(c)(9) do not apply’’ in
removing the source category from the
list. Id. In addition, we pointed out that
the inclusion of EGUs on the 112(c)(1)
list was not a ‘‘final agency action.’’ Id.
Therefore, we stated that we had
‘‘inherent authority under the CAA to
revise [the listing] at any time based on
either identified errors in the December
2000 finding or on new information that
bears upon that finding.’’ Id.
The D.C. Circuit rejected the EPA’s
interpretations and vacated the 2005
Delisting Rule, holding that the CAA
unambiguously requires the delisting
criteria in CAA section 112(c)(9) to have
been met before ‘‘any’’ source category
can be removed from the CAA section
112(c)(1) list. New Jersey, 517 F.3d at
582. It specified that, under the CAA’s
plain text and under step one of
Chevron, ‘‘the only way the EPA could
remove EGUs from the section 112(c)(1)
list’’ was to satisfy those criteria. Id.
(emphasis added). The Court expressly
rejected the EPA’s argument that,
‘‘[l]ogically, if EPA makes a
determination under section
112(n)(1)(A) that power plants should
not be regulated at all under section 112
. . . [then] this determination ipso facto
must result in removal of power plants
from the section 112(c) list.’’ Id.
(quoting the EPA’s brief). Instead, the
Court maintained that CAA section
112(n)(1) governed only how the
Administrator determines whether to
list EGUs, and that any and all attempts
to remove categories from the list were
under the exclusive purview of CAA
section 112(c)(9). See id. The Court
further held that the existence of CAA
section 112(c)(9) limited the normal
discretion an Agency would typically
have to reverse its position and undo
the administrative determination to list
EGUs as a source category. See Id. at
582–83.
In this action, we propose to reverse
the conclusions presented in the 2016
Supplemental Finding and to find that,
after consideration of the cost of
compliance with the CAA section
112(d) standards, it is not appropriate
and necessary to regulate HAP
emissions from EGUs under CAA
section 112. Consistent with New Jersey,
the EPA is proposing to find that this
reversal of the CAA section 112(n)(1)(A)
determination, if finalized, would not
have the effect of removing EGUs from
the CAA section 112(c)(1) source
category list. Because EGUs would
remain on the CAA section 112(c)(1)
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source category list, the CAA section
112(d) standards for that category, as
promulgated in the MATS rule, would
be unaffected by final action on this
proposal.
2. Alternative Interpretations of Effects
of This Proposed Replacement: Requests
for Comment
The EPA also solicits comment on
two alternative interpretations of the
impact of reversing the 2016
Supplemental Finding. Specifically, the
Agency solicits comment under two
separate theories on whether, contrary
to the interpretation discussed above,
the EPA would have authority to
rescind the MATS rule and delist EGUs
from CAA section 112 if, acting on
remand following the Supreme Court’s
opinion in Michigan, it were to finalize
its proposed conclusion that it is not
appropriate and necessary to regulate
HAP from coal- and oil-fired EGUs
(Comment C–4). The Agency also
solicits comment on whether, in light of
the fact that the CAA section
112(n)(1)(A) finding is a threshold
determination to setting the CAA
section 112(d) standards, we would be
obligated to rescind the rule if we were
to finalize our proposed finding that it
is not appropriate and necessary to
regulate HAP from these sources, even
if such a finding did not remove EGUs
from the list of covered sources under
CAA section 112(c) (Comment C–5).
In particular, we solicit comment on
whether the EPA could reasonably
conclude that the D.C. Circuit’s holding
in New Jersey v. EPA does not limit the
Agency’s authority to rescind the MATS
rule, under two alternative
interpretations (Comment C–6). Under
the first alternative interpretation, we
seek comment on whether New Jersey is
distinguishable because the facts here
are sufficiently different from those
considered by the Court reviewing the
2005 Delisting Rule at issue (Comment
C–7). In that case, the original 2000
Finding and CAA section 112(c)(1)
listing were in place, but because the
EPA had not yet promulgated CAA
section 112(d) standards, the finding
itself was not yet reviewable. CAA
section 112(e)(4); see also UARG v. EPA,
No. 01–1074, 2001 U.S. App. LEXIS
18436, 2001 WL 936363 (D.C. Cir. July
26, 2001). Here, the 2012 Finding was
challenged and reviewed by the
Supreme Court in Michigan v. EPA,
which found that the EPA’s
determination that it was appropriate
and necessary to regulate HAP from
EGUs was flawed. Because the Supreme
Court found that determination to be
flawed, the EPA necessarily retains the
discretion to reach a different
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conclusion from that reached in 2012
when we promulgated MATS. This
proposed reversal of the 2016
Supplemental Finding is a continuation
of the Agency’s response to the Supreme
Court’s remand, and New Jersey does
not limit the effect of an action made in
response to a Supreme Court decision
finding the original action flawed, nor
does it limit the Agency’s ability to
revise its response to a Supreme Court
decision. Therefore, the EPA would
have authority to rescind MATS and
remove EGUs from the list of source
categories regulation under CAA section
112 after finalizing this reversal of the
2016 Supplemental Finding.
Under the second alternative
interpretation, the EPA seeks comment
on whether, were the proposed reversal
to be finalized, EGUs would remain on
the CAA section 112(c) list of sources,
but the EPA would have the authority
to rescind the standards regulating those
source’s emissions under CAA section
112(d) in light of the fact that CAA
section 112(n)(1)(A) plainly establishes
that the Administrator must find
regulation under CAA section 112 is
appropriate and necessary as a
prerequisite to undertaking such
regulation (Comment C–8). New Jersey
v. EPA held that the EPA may not
remove a source category from the CAA
section 112(c) list without
demonstrating that the delisting analysis
under CAA section 112(c)(9) has been
satisfied, but the decision did not
address the question whether, in the
absence of a valid appropriate and
necessary finding, the EPA must
regulate EGUs for HAP.
Finally, although the alternative
interpretations described immediately
above both suggest the EPA would have
the discretionary authority to rescind
MATS (either with or without delisting),
the EPA solicits comment on whether,
under either alternative interpretation,
the Agency would instead be obligated
to rescind MATS once it finalized a
reversal of the 2016 Supplemental
Finding (Comment C–9).
We solicit comment on all aspects of
these alternative interpretations of the
impacts of replacing the 2016
Supplemental Finding and these
potential alternate readings of the
Court’s decision in New Jersey
(Comment C–10).
III. Criteria for Delisting a Source
Category Under CAA Section 112(c)(9)
As noted above, New Jersey held that
the EPA cannot remove a source
category from the CAA section 112(c)
source category list without addressing
the delisting criteria in CAA section
112(c)(9). CAA section 112(c)(9)(B)
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provides that ‘‘[t]he Administrator may
delete any source category’’ from the
CAA section 112(c) source category list
if the Agency determines that: (1) For
HAP that may cause cancer in humans,
‘‘no source in the category (or group of
sources in the case of area sources)
emits such hazardous air pollutants in
quantities which may cause a lifetime
risk of cancer greater than one in one
million to the individual in the
population who is most exposed to
emissions of such pollutants from the
source (or group of sources in the case
of area sources)’’; and (2) for HAP that
may result in human health effects other
than cancer or adverse environmental
effects, ‘‘a determination that emissions
from no source in the category or
subcategory concerned (or group of
sources in the case of area sources)
exceed a level which is adequate to
protect public health with an ample
margin of safety and no adverse
environmental effect will result from
emissions from any source.’’
In this action, the EPA is neither
conducting a delisting analysis under
CAA section 112(c)(9) for the Coal- and
Oil-Fired EGU source category, nor
soliciting comment on whether such an
analysis should be conducted, or on
what any such analysis would
demonstrate. Any such comments
would be outside the scope of this
action.
The Agency notes that the proposed
results of its risk review indicate that
with the MATS rule in place, the
estimated inhalation cancer risk to the
individual most exposed to actual
emissions from the source category is 9in-1 million. As noted above, the EPA
is not proposing a delisting analysis and
any such analysis would likely differ
from the analysis done for the CAA
section 112(f)(2) risk review in
important aspects.
In addition, on two previous
occasions, the EPA has examined the
statutory delisting criteria with respect
to EGUs and found that the criteria were
not met. We summarize without adding
to those findings below.
In 2011, in response to the EPA’s
request for comments on the proposed
MATS rule, the Utility Air Regulatory
Group (UARG) submitted a petition
pursuant to CAA section 112(c)(9)
requesting that coal-fired EGUs be
removed from the CAA section 112(c)
List of Categories of Major and Area
Sources.17 In its petition, UARG
17 Petition of the Utility Air Regulatory Group for
the De-Listing of Coal-Fired Electric Utility Steam
Generating Units as a Source Category Subject to
Section 112 of the Clean Air Act. Docket ID No.
EPA–HQ–OAR–2009–0234–17777.
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asserted that: (1) No coal-fired EGU or
group of coal-fired EGUs emit HAP in
amounts that will cause a lifetime
cancer risk greater than 1-in-1 million;
and (2) no coal-fired EGU or group of
coal-fired EGUs emit non-carcinogenic
HAP in amounts that will exceed a level
which is adequate to protect public
health with an ample margin of safety
or cause adverse environmental effects.
The EPA denied this petition on several
grounds.18 First, the EPA rejected
UARG’s request on the basis that, under
D.C. Circuit precedent, the Agency is
not permitted to delist a portion of a
source category that poses cancer
risks.19 Second, the EPA found that
UARG’s data and analyses identified a
maximum individual cancer risk of 4-in1 million, which exceeds the statutory
threshold in CAA section 112(c)(9)(B)(i)
of 1-in-1 million. Additionally, the EPA
found that UARG’s analysis did not
fully characterize noncancer human
health effects for the source category
and further, that UARG failed to show
that ‘‘no adverse environmental effects
will result from emissions from any
source’’ pursuant to CAA section
112(c)(9)(B)(ii). For all these reasons, the
EPA denied UARG’s petition to delist
coal-fired EGUs from the CAA section
112(c) source category list. UARG
challenged the EPA’s denial of its
delisting petition as arbitrary and
capricious, and the D.C. Circuit
dismissed UARG’s challenge on the
basis that the EPA had adequately
demonstrated that the CAA section
112(c)(9) delisting criteria were not met
by UARG’s analysis. White Stallion, 748
F.3d at 1248.
The EPA also independently
conducted an analysis which also
confirmed that the Coal- and Oil-Fired
EGU source category cannot be delisted
pursuant to CAA section 112(c)(9).20
The EPA analyzed non-Hg inhalation
risks from 16 EGU facility case studies,
18 77
FR 9365 (February 16, 2012).
petitioned the Agency to delist coalfired EGUs, which represent only a portion of the
listed source category. The EPA believed it was not
permitted to delist a portion of a source category,
where that source category poses cancer risks.
NRDC v. U.S. EPA, 489 F.3d 1364 (D.C. Cir. 2007).
Specifically, in NRDC, the D.C. Circuit held that the
Agency’s attempt to delist a ‘‘low-risk’’ subcategory
was ‘‘contrary to the plain language of the statute,’’
and that the statute only authorized the Agency to
remove source categories pursuant to CAA section
112(c)(9). Id. at 1373 (‘‘Because EPA’s interpretation
of Section 112(c)(9) as allowing it to exempt the
risk-based subcategory is contrary to the plain
language of the statute, the EPA’s interpretation
fails at Chevron step one.’’).
20 U.S. EPA, 2011. Supplement to the Non-Hg
Case Study Chronic Inhalation Risk Assessment in
Support of the Appropriate and Necessary Finding
for Coal- and Oil-Fired Electric Generating Units.
November. EPA–452/R–11–013. Docket ID No.
EPA–HQ–OAR–2009–0234–19912.
19 UARG
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including both coal- and oil-fired EGUs.
Of the 16 facilities analyzed, six had
cancer risks greater than 1-in-1 million,
exceeding the delisting criteria in CAA
section 112(c)(9)(B)(i). Because EGUs
failed to meet the first delisting
requirement, the Agency did not need to
determine whether the second delisting
requirement was satisfied.
IV. Background on the RTR Action
A. What is the statutory authority for
this action?
The statutory authority for this action
is provided by sections 112 and 301 of
the CAA, as amended (42 U.S.C. 7401 et
seq.). Section 112 of the CAA
establishes a two-stage regulatory
process to develop standards for
emissions of HAP from stationary
sources. Generally, the first stage
involves establishing technology-based
standards and the second stage involves
evaluating those standards that are
based on MACT to determine whether
additional standards are needed to
address any remaining risk associated
with HAP emissions. This second stage
is commonly referred to as the ‘‘residual
risk review.’’ In addition to the residual
risk review, the CAA also requires the
EPA to review standards set under CAA
section 112 every 8 years to determine
if there are ‘‘developments in practices,
processes, or control technologies’’ that
may be appropriate to incorporate into
the standards. This review is commonly
referred to as the ‘‘technology review.’’
When the two reviews are combined
into a single rulemaking, it is commonly
referred to as the ‘‘risk and technology
review.’’ The discussion that follows
identifies the most relevant statutory
sections and briefly explains the
contours of the methodology used to
implement these statutory requirements.
A more comprehensive discussion
appears in the document titled CAA
Section 112 Risk and Technology
Reviews: Statutory Authority and
Methodology in the docket for this
rulemaking.
In the first stage of the CAA section
112 standard setting process, the EPA
promulgates technology-based standards
under CAA section 112(d) for categories
of sources identified as emitting one or
more of the HAP listed in CAA section
112(b). Sources of HAP emissions are
either major sources or area sources, and
CAA section 112 establishes different
requirements for major source standards
and area source standards. ‘‘Major
sources’’ are those that emit or have the
potential to emit 10 tpy or more of a
single HAP or 25 tpy or more of any
combination of HAP. All other sources
are ‘‘area sources.’’ For major sources,
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CAA section 112(d)(2) provides that the
technology-based NESHAP must reflect
the maximum degree of emission
reductions of HAP achievable (after
considering cost, energy requirements,
and non-air quality health and
environmental impacts). These
standards are commonly referred to as
MACT standards. CAA section 112(d)(3)
also establishes a minimum control
level for MACT standards, known as the
MACT ‘‘floor.’’ The EPA must also
consider control options that are more
stringent than the floor. Standards more
stringent than the floor are commonly
referred to as beyond-the-floor
standards. In certain instances, as
provided in CAA section 112(h), the
EPA may set work practice standards
where it is not feasible to prescribe or
enforce a numerical emission standard.
For area sources, CAA section 112(d)(5)
gives the EPA discretion to set standards
based on generally available control
technologies or management practices
(GACT standards) in lieu of MACT
standards.
The second stage in standard-setting
focuses on identifying and addressing
any remaining (i.e., ‘‘residual’’) risk
according to CAA section 112(f). For
source categories subject to MACT
standards, section 112(f)(2) of the CAA
requires the EPA to determine whether
promulgation of additional standards is
needed to provide an ample margin of
safety to protect public health or to
prevent an adverse environmental
effect. Section 112(d)(5) of the CAA
provides that this residual risk review is
not required for categories of area
sources subject to GACT standards.
Section 112(f)(2)(B) of the CAA further
expressly preserves the EPA’s use of the
two-step approach for developing
standards to address any residual risk
and the Agency’s interpretation of
‘‘ample margin of safety’’ developed in
the National Emissions Standards for
Hazardous Air Pollutants: Benzene
Emissions from Maleic Anhydride
Plants, Ethylbenzene/Styrene Plants,
Benzene Storage Vessels, Benzene
Equipment Leaks, and Coke By-Product
Recovery Plants (Benzene NESHAP) (54
FR 38044, September 14, 1989). The
EPA notified Congress in the Risk
Report that the Agency intended to use
the Benzene NESHAP approach in
making CAA section 112(f) residual risk
determinations (EPA–453/R–99–001, p.
ES–11). The EPA subsequently adopted
this approach in its residual risk
determinations and the Court upheld
the EPA’s interpretation that CAA
section 112(f)(2) incorporates the
approach established in the Benzene
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NESHAP. See NRDC v. EPA, 529 F.3d
1077, 1083 (D.C. Cir. 2008).
The approach incorporated into the
CAA and used by the EPA to evaluate
residual risk and to develop standards
under CAA section 112(f)(2) is a twostep approach. In the first step, the EPA
determines whether risks are acceptable.
This determination ‘‘considers all health
information, including risk estimation
uncertainty, and includes a presumptive
limit on maximum individual lifetime
[cancer] risk (MIR) 21 of approximately 1
in 10 thousand.’’ 54 FR 38045,
September 14, 1989. If risks are
unacceptable, the EPA must determine
the emissions standards necessary to
reduce risk to an acceptable level
without considering costs. In the second
step of the approach, the EPA considers
whether the emissions standards
provide an ample margin of safety to
protect public health ‘‘in consideration
of all health information, including the
number of persons at risk levels higher
than approximately 1 in 1 million, as
well as other relevant factors, including
costs and economic impacts,
technological feasibility, and other
factors relevant to each particular
decision.’’ Id. The EPA must promulgate
emission standards necessary to provide
an ample margin of safety to protect
public health. After conducting the
ample margin of safety analysis, we
consider whether a more stringent
standard is necessary to prevent, taking
into consideration costs, energy, safety,
and other relevant factors, an adverse
environmental effect.
CAA section 112(d)(6) separately
requires the EPA to review standards
promulgated under CAA section 112
and revise them ‘‘as necessary (taking
into account developments in practices,
processes, and control technologies)’’ no
less often than every 8 years. In
conducting this review, which we call
the ‘‘technology review,’’ the EPA is not
required to recalculate the MACT floor.
Natural Resources Defense Council
(NRDC) v. EPA, 529 F.3d 1077, 1084
(D.C. Cir. 2008). Association of Battery
Recyclers, Inc. v. EPA, 716 F.3d 667
(D.C. Cir. 2013). The EPA may consider
cost in deciding whether to revise the
standards pursuant to CAA section
112(d)(6).
B. What is this source category and how
does the current NESHAP regulate its
HAP emissions?
The NESHAP for the Coal- and OilFired EGU source category (commonly
21 Although defined as ‘‘maximum individual
risk,’’ MIR refers only to cancer risk. MIR, one
metric for assessing cancer risk, is the estimated
risk if an individual were exposed to the maximum
level of a pollutant for a lifetime.
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18:43 Feb 06, 2019
Jkt 247001
referred to as MATS) were initially
promulgated on February 16, 2012 (77
FR 9304), under title 40 part 63, subpart
UUUUU. The MATS rule was amended
on April 19, 2012 (77 FR 23399), to
correct typographical errors and certain
preamble text that was inconsistent with
regulatory text; on April 24, 2013 (78 FR
24073), to update certain emission
limits and monitoring and testing
requirements applicable to new sources;
on November 19, 2014 (79 FR 68777), to
revise definitions for startup and
shutdown and to finalize work practice
standards and certain monitoring and
testing requirements applicable during
periods of startup and shutdown; and
on April 6, 2016 (81 FR 20172), to
correct conflicts between preamble and
regulatory text and to clarify regulatory
text. In addition, the electronic
reporting requirements of the rule were
amended on March 24, 2015 (80 FR
15510), to allow for the electronic
submission of Portable Document
Format (PDF) versions of certain reports
until April 16, 2017, while the EPA’s
Emissions Collection and Monitoring
Plan System (ECMPS) is revised to
accept all reporting that is required by
the rule, and on April 6, 2017 (82 FR
16736), and on July 2, 2018 (83 FR
30879), to extend the interim
submission of PDF versions of reports
through June 30, 2018, and July 1, 2020,
respectively.
The MATS rule applies to coal- and
oil-fired EGUs located at both major and
area sources of HAP emissions. The
sources subject to the MATS rule
include each individual or group of
coal- or oil-fired EGUs. An existing
affected source is the collection of coalor oil-fired EGUs in a subcategory
within a single contiguous area and
under common control. A new affected
source is each coal- or oil-fired EGU for
which construction or reconstruction
began after May 3, 2011. As previously
stated in section I of this preamble, an
electric utility steam generating unit is
a fossil fuel-fired combustion unit of
more than 25 megawatts (MW) that
serves a generator that produces
electricity for sale. A unit that
cogenerates steam and electricity and
supplies more than one-third of its
potential electric output capacity and
more than 25 MW electric output to any
utility power distribution system for
sale is also considered an electric utility
steam generating unit. The MATS rule
defines additional terms for determining
rule applicability, including, but not
limited to, definitions for ‘‘Coal-fired
electric utility steam generating unit,’’
‘‘Oil-fired electric utility steam
generating unit,’’ and ‘‘Fossil fuel-
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2681
fired.’’ Certain types of electric
generating units are not subject to 40
CFR part 63, subpart UUUUU: Any unit
designated as a major source stationary
combustion turbine subject to subpart
YYYY of part 63 and any unit
designated as an area source stationary
combustion turbine, other than an
integrated gasification combined cycle
(IGCC) unit; any EGU that is not a coalor oil-fired EGU and that meets the
definition of a natural gas-fired EGU in
40 CFR 63.10042; any EGU greater than
25 MW that has the capability of
combusting either coal or oil, but does
not meet the definition of a coal- or oilfired EGU because it did not fire
sufficient coal or oil to satisfy the
average annual heat input requirement
set forth in the definitions for coal-fired
and oil-fired EGUs in 40 CFR 63.10042;
and any electric steam generating unit
combusting solid waste (i.e., a solid
waste incineration unit) subject to
standards established under sections
129 and 111 of the CAA.
For coal-fired EGUs, the rule
established standards to limit emissions
of Hg, acid gas HAP, non-Hg HAP
metals (e.g., nickel, lead, chromium),
and organic HAP (e.g., formaldehyde,
dioxin/furan). Standards for
hydrochloric acid (HCl) serve as a
surrogate for the acid gas HAP, with an
alternate standard for SO2 that may be
used as a surrogate for acid gas HAP for
those coal-fired EGUs with flue gas
desulfurization (FGD) systems and SO2
continuous emissions monitoring
systems (CEMS) installed and
operational. Standards for filterable
particulate matter (fPM) serve as a
surrogate for the non-Hg HAP metals,
with standards for total non-Hg HAP
metals and individual non-Hg HAP
metals provided as alternative
equivalent standards. Work practice
standards limit formation and emission
of the organic HAP.
For oil-fired EGUs, the rule
establishes standards to limit emissions
of HCl and hydrogen fluoride (HF), total
HAP metals (e.g., Hg, nickel, lead), and
organic HAP (e.g., formaldehyde,
dioxin/furan). Standards for fPM serve
as a surrogate for total HAP metals, with
standards for total HAP metals and
individual HAP metals provided as
alternative equivalent standards. Work
practice standards limit formation and
emission of the organic HAP.
The MATS rule includes standards for
existing and new EGUs for seven
subcategories: Two for coal-fired EGUs,
one for IGCC EGUs, one for solid oilderived fuel-fired EGUs, and three for
liquid oil-fired EGUs. EGUs in six of the
subcategories are subject to numeric
emission limits for the pollutants
E:\FR\FM\07FEP2.SGM
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Federal Register / Vol. 84, No. 26 / Thursday, February 7, 2019 / Proposed Rules
described above except for organic HAP.
Organic HAP are regulated by a work
practice standard that requires periodic
combustion process tune-ups. EGUs in
the subcategory of limited-use liquid
oil-fired EGUs with an annual capacity
factor of less than 8 percent of its
maximum or nameplate heat input are
also subject to a work practice standard
consisting of periodic combustion
process tune-ups, but are not subject to
any numeric emission limits. Emission
limits for existing EGUs and new or
reconstructed EGUs are summarized in
Table 2 and Table 3, respectively.
TABLE 2—EMISSION LIMITS FOR EXISTING AFFECTED EGUS
Emission limit 1
Subcategory
Pollutant
1. Coal-fired unit not low rank virgin coal ..........
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
c. Hg .................................................................
a. fPM ...............................................................
2. Coal-fired unit low rank virgin coal .................
3. IGCC unit .......................................................
4. Liquid oil-fired unit—continental (excluding
limited-use liquid oil-fired subcategory units).
OR ....................................................................
Total HAP metals .............................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
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18:43 Feb 06, 2019
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3.0E–2 lb/MMBtu or 3.0E–1 lb/MWh.
OR
5.0E–5 lb/MMBtu or 5.0E–1 lb/GWh.
OR
8.0E–1 lb/TBtu or 8.0E–3 lb/GWh.
1.1 lb/TBtu or 2.0E–2 lb/GWh.
2.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
3.0E–1 lb/TBtu or 3.0E–3 lb/GWh.
2.8 lb/TBtu or 3.0E–2 lb/GWh.
8.0E–1 lb/TBtu or 8.0E–3 lb/GWh.
1.2 lb/TBtu or 2.0E–2 lb/GWh.
4.0 lb/TBtu or 5.0E–2 lb/GWh.
3.5 lb/TBtu or 4.0E–2 lb/GWh.
5.0 lb/TBtu or 6.0E–2 lb/GWh.
2.0E–3 lb/MMBtu or 2.0E–2 lb/MWh.
OR
2.0E–1 lb/MMBtu or 1.5 lb/MWh.
1.2 lb/TBtu or 1.3E–2 lb/GWh.
3.0E–2 lb/MMBtu or 3.0E–1 lb/MWh.
OR
5.0E–5 lb/MMBtu or 5.0E–1 lb/GWh.
OR
8.0E–1 lb/TBtu or 8.0E–3 lb/GWh.
1.1 lb/TBtu or 2.0E–2 lb/GWh.
2.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
3.0E–1 lb/TBtu or 3.0E–3 lb/GWh.
2.8 lb/TBtu or 3.0E–2 lb/GWh.
8.0E–1 lb/TBtu or 8.0E–3 lb/GWh.
1.2 lb/TBtu or 2.0E–2 lb/GWh.
4.0 lb/TBtu or 5.0E–2 lb/GWh.
3.5 lb/TBtu or 4.0E–2 lb/GWh.
5.0 lb/TBtu or 6.0E–2 lb/GWh.
2.0E–3 lb/MMBtu or 2.0E–2 lb/MWh.
OR
2.0E–1 lb/MMBtu or 1.5 lb/MWh.
4.0 lb/TBtu or 4.0E–2 lb/GWh.
4.0E–2 lb/MMBtu or 4.0E–1 lb/MWh.
OR
6.0E–5 lb/MMBtu or 5.0E–1 lb/GWh.
OR
1.4 lb/TBtu or 2.0E–2 lb/GWh.
1.5 lb/TBtu or 2.0E–2 lb/GWh.
1.0E–1 lb/TBtu or 1.0E–3 lb/GWh.
1.5E–1 lb/TBtu or 2.0E–3 lb/GWh.
2.9 lb/TBtu or 3.0E–2 lb/GWh.
1.2 lb/TBtu or 2.0E–2 lb/GWh.
1.9E+2 lb/MMBtu or 1.8 lb/MWh.
2.5 lb/TBtu or 3.0E–2 lb/GWh.
6.5 lb/TBtu or 7.0E–2 lb/GWh.
2.2E+1 lb/TBtu or 3.0E–1 lb/GWh.
5.0E–4 lb/MMBtu or 5.0E–3 lb/MWh.
2.5 lb/TBtu or 3.0E–2 lb/GWh.
3.0E–2 lb/MMBtu or 3.0E–1 lb/MWh.
OR
8.0E–4 lb/MMBtu or 8.0E–3 lb/MWh.
OR
1.3E+1 lb/TBtu or 2.0E–1 lb/GWh.
2.8 lb/TBtu or 3.0E–2 lb/GWh.
2.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
3.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
5.5 lb/TBtu or 6.0E–2 lb/GWh.
E:\FR\FM\07FEP2.SGM
07FEP2
Federal Register / Vol. 84, No. 26 / Thursday, February 7, 2019 / Proposed Rules
TABLE 2—EMISSION LIMITS FOR EXISTING AFFECTED EGUS—Continued
Subcategory
Emission limit 1
Pollutant
5. Liquid oil-fired unit—non-continental (excluding limited-use liquid oil-fired subcategory
units).
6. Solid oil-derived fuel-fired unit ........................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
Hg .............................................................
b. HCl ...............................................................
c. HF ................................................................
a. fPM ...............................................................
2.1E+1 lb/TBtu or 3.0E–1 lb/GWh.
8.1 lb/TBtu or 8.0E–2 lb/GWh.
2.2E+1 lb/TBtu or 3.0E–1 lb/GWh.
1.1E+2 lb/TBtu or 1.1 lb/GWh.
3.3 lb/TBtu or 4.0E–2 lb/GWh.
2.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
2.0E–3 lb/MMBtu or 1.0E–2 lb/MWh.
4.0E–4 lb/MMBtu or 4.0E–3 lb/MWh.
3.0E–2 lb/MMBtu or 3.0E–1 lb/MWh.
OR ....................................................................
Total HAP metals .............................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
Hg .............................................................
b. HCl ...............................................................
c. HF ................................................................
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
OR
6.0E–4 lb/MMBtu or 7.0E–3 lb/MWh.
OR
2.2 lb/TBtu or 2.0E–2 lb/GWh.
4.3 lb/TBtu or 8.0E–2 lb/GWh.
6.0E–1 lb/TBtu or 3.0E–3 lb/GWh.
3.0E–1 lb/TBtu or 3.0E–3 lb/GWh.
3.1E+1 lb/TBtu or 3.0E–1 lb/GWh.
1.1E+2 lb/TBtu or 1.4 lb/GWh.
4.9 lb/TBtu or 8.0E–2 lb/GWh.
2.0E+1 lb/TBtu or 3.0E–1 lb/GWh.
4.7E+2 lb/TBtu or 4.1 lb/GWh.
9.8 lb/TBtu or 2.0E–1 lb/GWh.
4.0E–2 lb/TBtu or 4.0E–4 lb/GWh.
2.0E–4 lb/MMBtu or 2.0E–3 lb/MWh.
6.0E–5 lb/MMBtu or 5.0E–4 lb/MWh.
8.0E–3 lb/MMBtu or 9.0E–2 lb/MWh.
OR
4.0E–5 lb/MMBtu or 6.0E–1 lb/GWh.
OR
8.0E–1 lb/TBtu or 7.0E–3 lb/GWh.
3.0E–1 lb/TBtu or 5.0E–3 lb/GWh.
6.0E–2 lb/TBtu or 5.0E–4 lb/GWh.
3.0E–1 lb/TBtu or 4.0E–3 lb/GWh.
8.0E–1 lb/TBtu or 2.0E–2 lb/GWh.
1.1 lb/TBtu or 2.0E–2 lb/GWh.
8.0E–1 lb/TBtu or 2.0E–2 lb/GWh.
2.3 lb/TBtu or 4.0E–2 lb/GWh.
9.0 lb/TBtu or 2.0E–1 lb/GWh.
1.2 lb/Tbtu 2.0E–2 lb/GWh.
5.0E–3 lb/MMBtu or 8.0E–2 lb/MWh.
OR
3.0E–1 lb/MMBtu or 2.0 lb/MWh.
2.0E–1 lb/TBtu or 2.0E–3 lb/GWh.
1 Units of emission limits:
lb/MMBtu = pounds pollutant per million British thermal units fuel input;
lb/TBtu = pounds pollutant per trillion British thermal units fuel input;
lb/MWh = pounds pollutant per megawatt-hour electric output (gross); and
lb/GWh = pounds pollutant per gigawatt-hour electric output (gross).
2 Alternate SO limit may be used if the EGU has some form of FGD system and SO CEMS installed.
2
2
TABLE 3—EMISSION LIMITS FOR NEW OR RECONSTRUCTED AFFECTED EGUS
Emission limit 1
Subcategory
Pollutant
1. Coal-fired unit not low rank virgin coal ..........
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
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18:43 Feb 06, 2019
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9.0E–2 lb/MWh.
OR
6.0E–2 lb/GWh.
OR
8.0E–3
3.0E–3
6.0E–4
4.0E–4
7.0E–3
2.0E–3
2.0E–2
4.0E–3
4.0E–2
E:\FR\FM\07FEP2.SGM
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
07FEP2
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Federal Register / Vol. 84, No. 26 / Thursday, February 7, 2019 / Proposed Rules
TABLE 3—EMISSION LIMITS FOR NEW OR RECONSTRUCTED AFFECTED EGUS—Continued
Subcategory
2. Coal-fired units low rank virgin coal ...............
3. IGCC unit .......................................................
4. Liquid oil-fired unit—continental (excluding
limited-use liquid oil-fired subcategory units).
5. Liquid oil-fired unit—non-continental (excluding limited-use liquid oil-fired subcategory
units).
VerDate Sep<11>2014
18:43 Feb 06, 2019
Emission limit 1
Pollutant
Jkt 247001
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
a. fPM ...............................................................
..........................................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
a. fPM ...............................................................
5.0E–2 lb/GWh.
1.0E–2 lb/MWh.
OR
1.0 lb/MWh.
3.0E–3 lb/GWh.
9.0E–2 lb/MWh.
OR
6.0E–2 lb/GWh.
OR
8.0E–3 lb/GWh.
3.0E–3 lb/GWh.
6.0E–4 lb/GWh.
4.0E–4 lb/GWh.
7.0E–3 lb/GWh.
2.0E–3 lb/GWh.
2.0E–2 lb/GWh.
4.0E–3 lb/GWh.
4.0E–2 lb/GWh.
5.0E–2 lb/GWh.
1.0E–2 lb/MWh.
OR
1.0 lb/MWh.
4.0E–2 lb/GWh.
7.0E–2 lb/MWh.3
9.0E–2 lb/MWh.4
OR
4.0E–1 lb/GWh.
OR
2.0E–2
2.0E–2
1.0E–3
2.0E–3
4.0E–2
4.0E–3
9.0E–3
2.0E–2
7.0E–2
3.0E–1
2.0E–3
OR
4.0E–1
3.0E–3
3.0E–1
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/MWh.
lb/MWh.
lb/GWh.
lb/MWh.
OR ....................................................................
Total HAP metals .............................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
Hg .............................................................
b. HCl ...............................................................
c. HF ................................................................
a. fPM ...............................................................
OR
2.0E–4 lb/MWh.
OR
OR ....................................................................
Total HAP metals .............................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
OR
7.0E–3 lb/MWh.
OR
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1.0E–2
3.0E–3
5.0E–4
2.0E–4
2.0E–2
3.0E–2
8.0E–3
2.0E–2
9.0E–2
2.0E–2
1.0E–4
4.0E–4
4.0E–4
2.0E–1
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/GWh.
lb/MWh.
lb/MWh.
lb/MWh.
8.0E–3 lb/GWh.
6.0E–2 lb/GWh.
E:\FR\FM\07FEP2.SGM
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Federal Register / Vol. 84, No. 26 / Thursday, February 7, 2019 / Proposed Rules
2685
TABLE 3—EMISSION LIMITS FOR NEW OR RECONSTRUCTED AFFECTED EGUS—Continued
Subcategory
Emission limit 1
Pollutant
6. Solid oil-derived fuel-fired unit ........................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
Hg .............................................................
b. HCl ...............................................................
c. HF ................................................................
a. fPM ...............................................................
OR ....................................................................
Total non-Hg HAP metals ................................
OR ....................................................................
Individual HAP metals:
Antimony, Sb ............................................
Arsenic, As ................................................
Beryllium, Be .............................................
Cadmium, Cd ............................................
Chromium, Cr ...........................................
Cobalt, Co .................................................
Lead, Pb ...................................................
Manganese, Mn ........................................
Nickel, Ni ...................................................
Selenium, Se ............................................
b. HCl ...............................................................
OR ....................................................................
SO2 2 ................................................................
c. Hg .................................................................
2.0E–3 lb/GWh.
2.0E–3 lb/GWh.
2.0E–2 lb/GWh.
3.0E–1 lb/GWh.
3.0E–2 lb/GWh.
1.0E–1 lb/GWh.
4.1 lb/GWh.
2.0E–2 lb/GWh.
4.0E–4 lb/GWh.
2.0E–3 lb/MWh.
5.0E–4 lb/MWh.
3.0E–2 lb/MWh.
OR
6.0E–1 lb/GWh.
OR
8.0E–3 lb/GWh.
3.0E–3 lb/GWh.
6.0E–4 lb/GWh.
7.0E–4 lb/GWh.
6.0E–3 lb/GWh.
2.0E–3 lb/GWh.
2.0E–2 lb/GWh.
7.0E–3 lb/GWh.
4.0E–2 lb/GWh.
6.0E–3 lb/GWh.
4.0E–4 lb/MWh.
OR
1.0 lb/MWh.
2.0E–3 lb/GWh.
1 Units of emission limits:
lb/MWh = pounds pollutant per megawatt-hour electric output (gross); and
lb/GWh = pounds pollutant per gigawatt-hour electric output (gross).
2 Alternate SO limit may be used if the EGU has some form of FGD system (or, in the case of IGCC EGUs, some other acid gas removal sys2
tem either upstream or downstream of the combined cycle block) and SO2 CEMS installed.
3 Duct burners on syngas; gross output.
4 Duct burners on natural gas; gross output.
C. What data collection activities were
conducted to support this action?
The EPA did not issue a new
information collection request (ICR) to
affected coal- and oil-fired EGUs to
obtain the data used to support this
action, but did use some information
from the 2010 ICR which collected data
during development of the MATS rule.
The data and data sources used to
conduct the residual risk assessment
and technology review for the Coal- and
Oil-Fired EGU source category are
described below in section IV.D of this
preamble.
D. What other relevant background
information and data are available?
The EPA used multiple sources of
information to support this proposed
action. A comprehensive list of facilities
and EGUs that are subject to the MATS
rule was compiled primarily using
publicly available information reported
to the EPA and information contained in
the Agency’s National Electric Energy
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Data System (NEEDS) database.22
Affected sources are required to use the
40 CFR part 75-based ECMPS 23 for
reporting emissions and related data
either directly for EGUs that use Hg,
HCl, HF, or SO2 CEMS or Hg sorbent
traps for compliance purposes or
indirectly as PDF files for EGUs that use
performance test results, PM continuous
parameter monitoring system (CPMS)
data, or PM CEMS for compliance
purposes. Directly submitted data are
maintained in ECMPS; indirectly
submitted data are maintained in
WebFIRE.24 The NEEDS database
contains generation unit information
used in the Agency’s power sector
modeling. Other sources used to refine
the facility list included an EPA
technical support document that
contained a list of potentially affected
22 See https://www.epa.gov/airmarkets/powersector-modeling-platform-v515.
23 See https://ampd.epa.gov/ampd/.
24 See https://cfpub.epa.gov/webfire; https://
www.epa.gov/electronic-reporting-air-emissions/
webfire.
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Sfmt 4702
EGUs in U.S. territories,25 the U.S.
Department of Energy’s Energy
Information Administration’s (EIA’s) list
of existing generators that reported for
2016 under Form EIA–860,26 and the
list of coal-fired EGUs included in a
June 2018 Electric Power Research
Institute (EPRI) technical report that
summarizes EPRI’s evaluation of HAP
emissions and their associated
inhalation health risks from coal-fired
power plants after implementation of
MATS.27 As of early 2018, we estimate
25 U.S. EPA, October 2014. Technical Support
Document for Calculating Carbon Pollution Goals
for Existing Power Plants in Territories and Areas
of Indian Country. Available at https://
archive.epa.gov/epa/sites/production/files/2014-10/
documents/20141028tsd-supplementalproposal.pdf.
26 See https://www.eia.gov/electricity/data/
eia860/.
27 EPRI. June 8, 2018. Hazardous Air Pollutants
(HAPs) Emission Estimates and Inhalation Human
Health Risk Assessment for U.S. Coal-Fired Electric
Generating Units: 2017 Base Year Post-MATS
Evaluation. Available at https://www.epri.com/#/
pages/product/3002013577/?lang=en. Note: There
is a companion June 22, 2018 EPRI technical report,
Multi-Pathway Human Health Risk Assessment for
Coal-Fired Power Plants, that describes EPRI’s
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that there are 713 existing coal- and oilfired EGUs located at 323 facilities that
are subject to 40 CFR part 63, subpart
UUUUU.
In developing the RTR emissions
dataset for the risk review, the primary
sources used to estimate annual HAP
emissions were the emissions data as
reported to the ECMPS and WebFIRE
databases by facilities with affected
EGUs. Emissions release point
parameters and locations for each EGU
were primarily based on information
reported to the ECMPS and generatorlevel specific information about existing
generators and their associated
environmental equipment that is
collected by the EIA under Form EIA–
860. The EPA sources of information
that were used to supplement the
ECMPS, WebFIRE, and EIA data include
emissions information collected through
the 2010 ICR during development of the
MATS rule and the 2014 National
Emissions Inventory (NEI) database. The
NEI is a database that contains
information about sources that emit
criteria air pollutants, their precursors,
and HAP. The database includes
estimates of annual air pollutant
emissions from point, nonpoint, and
mobile sources in the 50 states, the
District of Columbia, Puerto Rico, and
the Virgin Islands. The EPA collects this
information and releases an updated
version of the NEI database every 3
years. The NEI includes information
necessary for conducting risk modeling,
including annual HAP emissions
estimates from individual emission
points at facilities and the related
emissions release parameters. The June
2018 EPRI technical report was also
used as a source of supplemental
information.
In conducting the technology review,
the EPA examined information
submitted to the EPA’s ECMPS as well
as information that supports previous 40
CFR part 63, subpart UUUUU actions to
identify technologies currently being
used by affected EGUs and determine if
there have been developments in
practices, processes, or control
technologies. In addition to the ECMPS
data, we reviewed regulatory actions for
similar combustion sources and
conducted a review of literature
published by industry organizations,
technical journals, and government
organizations.
multi-pathway human health assessment of HAP
emissions from five coal-fired electric facilities
based on 2017 configurations (available at https://
www.epri.com/#/pages/product/3002013523/
?lang=en).
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V. RTR Analytical Procedures and
Decision-Making
on our policy under the Benzene
NESHAP where the EPA explained that:
In this section, we describe the
analyses performed to support the
proposed decisions for the RTR and
other issues addressed in this proposal.
[t]he policy chosen by the Administrator
permits consideration of multiple measures
of health risk. Not only can the MIR figure
be considered, but also incidence, the
presence of non-cancer health effects, and the
uncertainties of the risk estimates. In this
way, the effect on the most exposed
individuals can be reviewed as well as the
impact on the general public. These factors
can then be weighed in each individual case.
This approach complies with the Vinyl
Chloride mandate that the Administrator
ascertain an acceptable level of risk to the
public by employing his expertise to assess
available data. It also complies with the
Congressional intent behind the CAA, which
did not exclude the use of any particular
measure of public health risk from the the
EPA’s consideration with respect to CAA
section 112 regulations, and thereby
implicitly permits consideration of any and
all measures of health risk which the
Administrator, in his judgment, believes are
appropriate to determining what will ‘protect
the public health’.
A. How do we consider risk in our
decision-making?
As discussed in section IV.A of this
preamble and in the Benzene NESHAP,
in evaluating and developing standards
under CAA section 112(f)(2), we apply
a two-step approach to determine
whether or not risks are acceptable and
to determine if the standards provide an
ample margin of safety to protect public
health. As explained in the Benzene
NESHAP, ‘‘the first step judgment on
acceptability cannot be reduced to any
single factor’’ and, thus, ‘‘[t]he
Administrator believes that the
acceptability of risk under section 112 is
best judged on the basis of a broad set
of health risk measures and
information.’’ 54 FR 38046, September
14, 1989. Similarly, with regard to the
ample margin of safety determination,
‘‘the Agency again considers all of the
health risk and other health information
considered in the first step. Beyond that
information, additional factors relating
to the appropriate level of control will
also be considered, including cost and
economic impacts of controls,
technological feasibility, uncertainties,
and any other relevant factors.’’ Id.
The Benzene NESHAP approach
provides flexibility regarding factors the
EPA may consider in making
determinations and how the EPA may
weigh those factors for each source
category. The EPA conducts a risk
assessment that provides estimates of
the MIR posed by the HAP emissions
from each source in the source category,
the hazard index (HI) for chronic
exposures to HAP with the potential to
cause noncancer health effects, and the
hazard quotient (HQ) for acute
exposures to HAP with the potential to
cause noncancer health effects.28 The
assessment also provides estimates of
the distribution of cancer risk within the
exposed populations, cancer incidence,
and an evaluation of the potential for an
adverse environmental effect. The scope
of the EPA’s risk analysis is consistent
with the EPA’s response to comments
28 The MIR is defined as the cancer risk
associated with a lifetime of exposure at the highest
concentration of HAP where people are likely to
live. The HQ is the ratio of the potential exposure
to the HAP to the level at or below which no
adverse chronic noncancer effects are expected; the
HI is the sum of HQs for HAP that affect the same
target organ or organ system.
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See 54 FR 38057, September 14, 1989.
Thus, the level of the MIR is only one
factor to be weighed in determining
acceptability of risk. The Benzene
NESHAP explained that ‘‘an MIR of
approximately one in 10 thousand
should ordinarily be the upper end of
the range of acceptability. As risks
increase above this benchmark, they
become presumptively less acceptable
under CAA section 112, and would be
weighed with the other health risk
measures and information in making an
overall judgment on acceptability. Or,
the Agency may find, in a particular
case, that a risk that includes an MIR
less than the presumptively acceptable
level is unacceptable in the light of
other health risk factors.’’ Id. at 38045.
Similarly, with regard to the ample
margin of safety analysis, the EPA stated
in the Benzene NESHAP that: ‘‘EPA
believes the relative weight of the many
factors that can be considered in
selecting an ample margin of safety can
only be determined for each specific
source category. This occurs mainly
because technological and economic
factors (along with the health-related
factors) vary from source category to
source category.’’ Id. at 38061. We also
consider the uncertainties associated
with the various risk analyses, as
discussed earlier in this preamble, in
our determinations of acceptability and
ample margin of safety.
The EPA notes that it has not
considered certain health information to
date in making residual risk
determinations. At this time, we do not
attempt to quantify the HAP risk that
may be associated with emissions from
other facilities that do not include the
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source category under review, mobile
source emissions, natural source
emissions, persistent environmental
pollution, or atmospheric
transformation in the vicinity of the
sources in the category.
The EPA understands the potential
importance of considering an
individual’s total exposure to HAP in
addition to considering exposure to
HAP emissions from the source category
and facility. We recognize that such
consideration may be particularly
important when assessing noncancer
risk, where pollutant-specific exposure
health reference levels (e.g., reference
concentrations (RfCs)) are based on the
assumption that thresholds exist for
adverse health effects. For example, the
EPA recognizes that, although exposures
attributable to emissions from a source
category or facility alone may not
indicate the potential for increased risk
of adverse noncancer health effects in a
population, the exposures resulting
from emissions from the facility in
combination with emissions from all of
the other sources (e.g., other facilities) to
which an individual is exposed may be
sufficient to result in an increased risk
of adverse noncancer health effects. In
May 2010, the Science Advisory Board
(SAB) advised the EPA ‘‘that RTR
assessments will be most useful to
decision makers and communities if
results are presented in the broader
context of aggregate and cumulative
risks, including background
concentrations and contributions from
other sources in the area.’’ 29
In response to the SAB
recommendations, the EPA incorporates
cumulative risk analyses into its RTR
risk assessments, including those
reflected in this proposal. The Agency
(1) conducts facility-wide assessments,
which include source category emission
points, as well as other emission points
within the facilities; (2) combines
exposures from multiple sources in the
same category that could affect the same
individuals; and (3) for some persistent
and bioaccumulative pollutants,
analyzes the ingestion route of
exposure. In addition, the RTR risk
assessments consider aggregate cancer
risk from all carcinogens and aggregated
noncancer HQs for all noncarcinogens
affecting the same target organ or target
organ system.
Although we are interested in placing
source category and facility-wide HAP
risk in the context of total HAP risk
from all sources combined in the
29 Recommendations of the SAB RTR Panel are
provided in their report, which is available at
https://yosemite.epa.gov/sab/sabproduct.nsf/
4AB3966E263D943A8525771F00668381/$File/EPASAB-10-007-unsigned.pdf.
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vicinity of each source, we are
concerned about the uncertainties of
doing so. Estimates of total HAP risk
from emission sources other than those
that we have studied in depth during
this RTR review would have
significantly greater associated
uncertainties than the source category or
facility-wide estimates. Such aggregate
or cumulative assessments would
compound those uncertainties, making
the assessments too unreliable.
B. How do we perform the technology
review?
Our technology review focuses on the
identification and evaluation of
developments in practices, processes,
and control technologies that have
occurred since the MACT standards
were promulgated. Where we identify
such developments, we analyze their
technical feasibility, estimated costs,
energy implications, and non-air
environmental impacts. We also
consider the emission reductions
associated with applying each
development. This analysis informs our
decision of whether it is ‘‘necessary’’ to
revise the emissions standards. In
addition, we consider the
appropriateness of applying controls to
new sources versus retrofitting existing
sources. For this exercise, we consider
any of the following to be a
‘‘development’’:
• Any add-on control technology or other
equipment that was not identified and
considered during development of the
original MACT standards;
• Any improvements in add-on control
technology or other equipment (that were
identified and considered during
development of the original MACT
standards) that could result in additional
emissions reduction;
• Any work practice or operational
procedure that was not identified or
considered during development of the
original MACT standards;
• Any process change or pollution
prevention alternative that could be broadly
applied to the industry and that was not
identified or considered during development
of the original MACT standards; and
• Any significant changes in the cost
(including cost effectiveness) of applying
controls (including controls the EPA
considered during the development of the
original MACT standards).
In addition to reviewing the practices,
processes, and control technologies that
were considered at the time we
originally developed (or last updated)
the NESHAP, we review a variety of
data sources in our investigation of
potential practices, processes, or
controls to consider. See sections IV.C
and IV. D of this preamble for
information on the specific data sources
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2687
that were reviewed as part of the
technology review.
C. How do we estimate post-MACT risk
posed by the source category?
In this section, we provide a complete
description of the types of analyses that
we generally perform during the risk
assessment process. In some cases, we
do not perform a specific analysis
because it is not relevant. For example,
in the absence of emissions of HAP
known to be persistent and
bioaccumulative in the environment
(PB–HAP), we would not perform a
multipathway exposure assessment.
Where we do not perform an analysis,
we state that we do not and provide the
reason. While we present all of our risk
assessment methods, we only present
risk assessment results for the analyses
actually conducted (see section VI.B of
this preamble).
The EPA conducts a risk assessment
that provides estimates of the MIR for
cancer posed by the HAP emissions
from each source in the source category,
the HI for chronic exposures to HAP
with the potential to cause noncancer
health effects, and the HQ for acute
exposures to HAP with the potential to
cause noncancer health effects. The
assessment also provides estimates of
the distribution of cancer risk within the
exposed populations, cancer incidence,
and an evaluation of the potential for an
adverse environmental effect. The seven
sections that follow this paragraph
describe how we estimated emissions
and conducted the risk assessment. The
docket for this rulemaking contains the
following document which provides
more information on the risk assessment
inputs and models: Residual Risk
Assessment for the Coal- and Oil-Fired
EGU Source Category in Support of the
2019 Risk and Technology Review
Proposed Rule (risk document). The
methods used to assess risk (as
described in the seven primary steps
below) are consistent with those
described by the EPA in the document
reviewed by a panel of the EPA’s SAB
in 2009;30 and described in the SAB
review report issued in 2010. They are
also consistent with the key
recommendations contained in that
report.
30 U.S. EPA. June 2009. Risk and Technology
Review (RTR) Risk Assessment Methodologies: For
Review by the EPA’s Science Advisory Board with
Case Studies—MACT I Petroleum Refining Sources
and Portland Cement Manufacturing (EPA–452/R–
09–006). Available at https://www3.epa.gov/
airtoxics/rrisk/rtrpg.html.
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1. How did we estimate actual
emissions and identify the emissions
release characteristics?
Data for existing EGUs were used to
create the RTR emissions dataset for the
risk review as described in section IV.D
of this preamble. The RTR emissions
dataset includes information for 608
emission release points (i.e., stacks).
Because in some cases multiple EGUs
are routed to a single stack or a single
EGU is routed to two stacks, the number
of stacks is not the same as the number
of EGUs. The MATS rule regulates
emissions of HAP in four pollutant
categories: Hg, non-Hg metals, acid
gases, and organics. As described in
section IV.B of this preamble, EGUs in
six subcategories are subject to numeric
emission limits for specific HAP, or
surrogates for those HAP, in the three
pollutant categories of Hg, non-Hg
metals, and acid gases. EGUs are not
required to meet numeric emission
limits for organic HAP or to test and
report organic HAP emissions. During
the 2010 ICR effort of the original MATS
rulemaking process, most of the organic
HAP emissions data for EGUs were at or
below the detection levels of the
prescribed test methods, even when
long duration test runs (i.e.,
approximately 8 hours) were required.
In developing the RTR emissions
dataset, the EPA reviewed the available
organic HAP test results from the 2010
ICR. For each organic HAP tested, if 40
percent or more of the available test data
were above test method detection limits,
emissions estimates for that HAP were
included in the modeling file. Emissions
of the following HAP in each of the four
pollutant categories were estimated for
each emission release point and
included in the RTR emissions dataset:
• Hg: elemental gaseous Hg, gaseous
divalent Hg, particulate divalent Hg;
• Non-Hg metals: antimony, arsenic,
beryllium, cadmium, hexavalent chromium,
trivalent chromium, cobalt, lead, manganese,
nickel, selenium;
• Acid gases: HCl, HF; and
• Organics: formaldehyde, naphthalene, 2methylnaphthalene, phenanthrene, two
dioxin congeners, three furan congeners, and
seven polychlorinated biphenyls congeners.
As explained in section IV.D of this
preamble, emissions estimates for the
RTR emissions dataset were based
primarily on data submitted via the
EPA’s ECMPS by facilities with affected
EGUs. Calendar year 2017 data were
used where available because all
affected EGUs subject to numeric
emission limits would be required to
submit compliance data by then. Where
calendar year 2017 data were not
available, the most recent data available
were used. CEMS emissions data for Hg,
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HCl, and SO2 reported to the EPA’s
ECMPS were available as 2017 actual
annual values (i.e., pounds per year or
tpy).
Some emissions data for Hg, non-Hg
HAP metals, HCl, and fPM was
submitted to the EPA’s ECMPS, but
maintained in the WebFIRE database.
For those sources, the EPA extracted
data associated with operations in
summer 2017, when EGUs would be
expected to operate more frequently
given increased demand for electricity,
and used those summertime emissions
to estimate annual emissions of the
pollutants of interest. Specifically, test
averages from third quarter performance
stack tests (i.e., conducted between July
and September 2017) for any pollutant
and 30-day rolling average values as of
June 30, 2017, for PM CEMS and PM
CPMS were extracted and then
converted from pounds of pollutant per
million British thermal units or trillion
British thermal units (lb/MMBtu or lb/
TBtu) or pounds of pollutant per
megawatt-hour or gigawatt-hour (lb/
MWh or lb/GWh) to actual annual
emissions using 2017 total heat input
(MMBtu) or total gross load (MWh)
values, as appropriate. When ECMPSsubmitted data for HAP in the RTR
emissions dataset were not available,
actual annual emissions estimates were
based on data from the 2014 NEI and the
June 2018 EPRI technical report. Some
annual emissions estimates were also
generated using the ratio of non-Hg
metals to fPM and acid gases to SO2
from the 2010 ICR in conjunction with
more recent fPM or SO2 emissions data.
Emissions data from the 2010 ICR were
used to develop emission factors for the
non-Hg metals and acid gases included
in the RTR emissions dataset and to
develop ratios based on each of those
emission factors divided by average fPM
or SO2 values, respectively. Emissions
data for EGUs no longer operating were
excluded in the calculation of emission
factors or average fPM or SO2 values. In
addition, we included in each emission
factor and ratio calculation only the
2010 ICR data for EGUs where data for
both the non-Hg metal HAP (e.g.,
antimony) and fPM, or the acid gas HAP
(e.g., HCl) and SO2, were available.
Emission factors and emission factorbased ratios were developed for the
various combinations of fuel types and
emissions control device types. Actual
annual HAP-specific emissions for each
stack were then estimated by
multiplying each emission factor-based
ratio by the most recent fPM or SO2
annual emissions value (e.g., 2017
ECMPS or WebFIRE data or 2014 NEI
data). Because EGUs in the subcategory
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Sfmt 4702
of limited-use liquid oil-fired EGUs are
not subject to any numeric emission
limits, actual annual HAP-specific
emissions were estimated using 2014
NEI data or emission factor-based ratios
along with 2014 NEI data for PM and
SO2. Development of the emission
factors and emission factor-based ratios
is explained in the memorandum,
Emission Factor Development for RTR
Risk Modeling Dataset for Coal- and Oilfired EGUs, which is available in the
docket for this action.
The majority of the total (i.e., nonspeciated) Hg actual annual emissions
estimates were based on data
maintained in the EPA’s ECMPS for
CEMS data or sorbent traps or in
WebFIRE for performance stack tests
along with 2017 total heat input or total
gross load values, as appropriate. Where
such data were not available, total Hg
actual annual emissions were estimated
using the 2014 NEI or the June 2018
EPRI technical report. For a small
number of oil-fired EGUs, EPAdeveloped emission factors and
emission factor-based ratios were used
to estimate total Hg actual annual
emissions. Hg emissions were modeled
as three different species: elemental
gaseous Hg, gaseous divalent Hg, and
particulate divalent Hg. The EPA
utilized Hg speciation factors—
percentages based on fuel type and
installed emissions control equipment—
that were updated versions of those that
had been used in the development of
the MATS rule.31 Total Hg emissions
were then multiplied by the factors to
develop the speciated Hg actual annual
emissions estimates.
For the several EGUs that submitted
individual non-Hg HAP metals data to
the EPA, actual annual emissions were
estimated using the stack test values
maintained in WebFIRE and 2017 total
heat input or total gross load values, as
appropriate. The majority of the non-Hg
HAP metals actual annual emissions
estimates were based on emission
factor-based ratios for non-Hg HAP
metals and fPM annual emissions
values. Chromium emissions were
modeled as hexavalent chromium
(Cr(VI)) and trivalent chromium (Cr(III)).
Actual annual emissions of Cr(VI) and
Cr(III) were estimated by multiplying
total chromium emissions by the
31 See Attachment E of the Risk Modeling Dataset
Memo for the list of Hg speciation factors utilized
in compiling the RTR emissions dataset for the risk
review, available in the docket for this action. See
Appendix G of the Technical Support Document for
the Proposed Rule Emissions Inventories (available
in the rulemaking docket at EPA–HQ–OAR–2009–
0234–19908) for Hg speciation factors used in the
development of MATS.
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speciation factors for coal or oil, as
appropriate.
Actual annual emissions estimates for
HCl for EGUs that submitted data to the
EPA’s ECMPS were based on those
ECMPS CEMS data or WebFIRE
performance stack test data and 2017
total heat input or total gross load
values, as appropriate. Where acid gas
HAP data were not available in the
WebFIRE database, but SO2 data were
available in the ECMPS for requirements
other than those in the MATS rule (e.g.,
the acid rain rule), emission factorbased ratios for the acid gas HAP (i.e.,
HCl and HF) and SO2 annual emissions
values were used to estimate actual
annual HCl and HF emissions. In some
instances, actual annual HCl and HF
emissions were estimated based on
emission factor-based ratios and 2014
NEI data for SO2. In a small number of
other instances, actual annual HCl and
HF emissions were estimated using the
June 2018 EPRI technical report.
As previously explained, EGUs are
not required to meet numeric emission
limits for organic HAP or to test and
report organic HAP emissions. Actual
annual emissions for the 16 organic
HAP included in the RTR emissions
dataset are based on EPA-developed
representative detection level (RDL)
equivalent emissions values (lb/MMBtu)
based on fuel type. RDL equivalent
emissions values for 15 of the organic
HAP are based on the averages of betterperforming unit method detection levels
across many source categories. Because
we did not have an RDL analysis across
source categories for formaldehyde,
detection levels from the 2010 ICR data
were used to develop the RDL
equivalent emissions value for
formaldehyde. Actual annual emissions
of the 16 organic HAP were estimated
by multiplying the RDL equivalent
emissions values by 2017 total heat
input. Development of the RDL
equivalent emissions values is
explained in the memorandum,
Development of Representative
Detection Levels of Certain Organic HAP
Expressed as Pounds per Million British
Thermal Units of Fuel Input for RTR
Risk Modeling Dataset for Coal- and Oilfired EGUs, which is available in the
docket for this action.
Stack parameter values and locations
for each emissions release point
included in the RTR emissions dataset
were primarily based on information
reported to the ECMPS and generatorlevel specific information about existing
generators and their associated
environmental equipment that is
collected under Form EIA–860.
Specifically, the ECMPS was the
primary source for stack height,
diameter, and latitude/longitude
coordinates, and the EIA–860 database
was the primary source for stack
temperature, velocity, and flow rate.
Other sources of information that were
used to fill gaps in the site-specific
emissions release point data included
the 2014 NEI, parameters from similar
stacks at a specific facility, and default
parameter values based on MACT
source category 2014 NEI information.
2689
The RTR emissions dataset was
refined as necessary following a quality
assurance check of source locations,
emissions release characteristics, and
annual emissions estimates. Latitude
and longitude coordinates were checked
using Google Earth® to ensure that stack
locations were correct. Stack parameters
were checked to ensure that they were
within acceptable quality assurance
range check boundaries. Emissions
estimates were reviewed for
completeness and accuracy. Additional
details on the data and methods used to
develop ‘‘actual’’ emissions estimates
for the RTR emissions dataset are
provided in the memorandum,
Development of the RTR Risk Modeling
Dataset for the Coal- and Oil-Fired EGU
Source Category (Risk Modeling Dataset
Memo), included as Appendix 1 of the
risk document, which is available in the
docket for this action.
A comparison of the actual annual
HAP emissions in 2017 to the annual
HAP emissions prior to promulgation of
the MATS rule shows a 96-percent
reduction in total HAP emissions from
coal- and oil-fired EGUs. The actual
emissions from coal- and oil-fired EGUs
for 2017 and estimated emissions from
2010 are shown in Table 4. Estimates of
pre-MATS emissions of organic HAP
were not available. As discussed
previously in this section, the 2017
emissions of organic HAP are based on
RDL equivalent emissions values; the
actual 2017 emissions are likely lower
than the estimate of 3 tpy.
TABLE 4—HAP EMISSIONS FROM COAL- AND OIL-FIRED EGUS PRE- AND POST-MATS
2010
Emissions
(tons) 32
Pollutant
2017
Emissions
(tons)
Reduction
(%)
Hg ................................................................................................................................................
Acid Gases ..................................................................................................................................
Non-Hg Metals .............................................................................................................................
Organic HAP ................................................................................................................................
29
125,708
1,170
*
4
4,831
221
<3
86
96
81
*
Total ......................................................................................................................................
126,907
5,059
96
Note: The compliance date for the vast majority of affected EGUs was on or before April 16, 2016.
* Not available.
2. How did we estimate MACTallowable emissions?
The available emissions data in the
RTR emissions dataset include estimates
of the mass of HAP emitted during a
specified annual time period. These
‘‘actual’’ emission levels are often lower
32 Memorandum: Emissions Overview: Hazardous
Air Pollutants in Support of the Final Mercury and
Air Toxics Standard. EPA–454/R–11–014.
November 2011; Docket ID No. EPA–HQ–OAR–
2009–0234–19914.
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than the emission levels allowed under
the requirements of the current MACT
standards. The emissions allowed under
the MACT standards are referred to as
the ‘‘MACT-allowable’’ emissions. We
discussed the consideration of both
MACT-allowable and actual emissions
in the final Coke Oven Batteries RTR (70
FR 19998–19999, April 15, 2005) and in
the proposed and final Hazardous
Organic NESHAP RTR (71 FR 34428,
June 14, 2006, and 71 FR 76609,
December 21, 2006, respectively). In
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those actions, we noted that assessing
the risk at the MACT-allowable level is
inherently reasonable since that risk
reflects the maximum level facilities
could emit and still comply with
national emission standards. We also
explained that it is reasonable to
consider actual emissions, where such
data are available, in both steps of the
risk analysis, in accordance with the
Benzene NESHAP approach. (54 FR
38044, September 14, 1989.)
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MACT-allowable annual emissions of
Hg, non-Hg HAP metals, and acid gas
HAP were estimated using numeric
emission limits for existing sources in
the MATS rule along with 2017 total
heat input. For Hg, allowable annual
emissions of total Hg were estimated by
multiplying subcategory-specific Hg
emission limits by 2017 total heat input.
Allowable annual emissions of
elemental gaseous Hg, gaseous divalent
Hg, and particulate divalent Hg were
estimated by multiplying annual
emissions of total Hg by EPA-developed
Hg speciation factors which are based
on fuel type and emissions control
device type.
With regard to non-Hg HAP metals,
performance stack test data in almost all
instances was for fPM, a surrogate for
non-Hg HAP metals, and, as such,
allowable annual emissions were
estimated using the MATS rule’s fPM
emission limits. Specifically, allowable
annual emissions of the non-Hg HAP
metals were estimated by multiplying
subcategory-based fPM emission limits
by 2017 total heat input and by the
emission factor-based ratios for non-Hg
HAP metals that were calculated by the
EPA. Allowable annual emissions of
chromium as Cr(VI) and Cr(III) were
estimated by multiplying the total
chromium allowable emissions
estimates by the chromium speciation
factors for coal or oil, as appropriate.
For acid gas HAP, allowable annual
emissions of HCl and HF from oil-fired
EGUs were estimated by multiplying
subcategory-specific HCl and HF
emission limits by 2017 total heat input.
With regard to acid gas HAP for coalfired EGUs, some coal-fired sources
submitted data for HCl, a surrogate for
acid gas HAP, whereas other sources
submitted data for SO2, a surrogate for
acid gas HAP for certain coal-fired
EGUs. Allowable annual emissions of
HCl and HF from coal-fired EGUs were
estimated two different ways—one
based on the MATS rule’s HCl emission
limits and HF actual emissions adjusted
using an HCl emissions ratio and the
other based on the MATS rule’s SO2
emission limits and emission factorbased ratios—and the more conservative
estimate was used. In the first approach,
allowable annual emissions of HCl were
estimated by multiplying subcategoryspecific HCl emission limits by 2017
total heat input, and allowable annual
emissions of HF were estimated by
multiplying actual annual emissions of
HF by a ratio of HCl allowable annual
emissions to HCl actual annual
emissions. In the second approach,
allowable annual emissions of HCl and
HF were estimated by multiplying
subcategory-based SO2 emission limits
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by 2017 total heat input and by the
emission factor-based ratios for HCl and
HF that were calculated by the EPA.
Because there are no numeric
emission limits for organic HAP,
allowable annual emissions for the 16
organic HAP were assumed equal to the
actual annual emissions estimates for
the 16 organic HAP. The Risk Modeling
Dataset Memo, available in the docket
for this action, contains additional
information on the development of
estimated MACT-allowable emissions.
3. How do we conduct dispersion
modeling, determine inhalation
exposures, and estimate individual and
population inhalation risk?
Both long-term and short-term
inhalation exposure concentrations and
health risk from the source category
addressed in this proposal were
estimated using the Human Exposure
Model (HEM–3).33 The HEM–3 performs
three primary risk assessment activities:
(1) Conducting dispersion modeling to
estimate the concentrations of HAP in
ambient air, (2) estimating long-term
and short-term inhalation exposures to
individuals residing within 50
kilometers (km) of the modeled sources,
and (3) estimating individual and
population-level inhalation risk using
the exposure estimates and quantitative
dose-response information.
a. Dispersion Modeling
The air dispersion model AERMOD,
used by the HEM–3 model, is one of the
EPA’s preferred models for assessing air
pollutant concentrations from industrial
facilities.34 To perform the dispersion
modeling and to develop the
preliminary risk estimates, HEM–3
draws on three data libraries. The first
is a library of meteorological data,
which is used for dispersion
calculations. This library includes 1
year (2016) of hourly surface and upper
air observations from 824
meteorological stations, selected to
provide coverage of the United States
and Puerto Rico. A second library of
United States Census Bureau census
block35 internal point locations and
populations provides the basis of
human exposure calculations (U.S.
Census, 2010). In addition, for each
census block, the census library
includes the elevation and controlling
33 For more information about HEM–3, go to
https://www.epa.gov/fera/risk-assessment-andmodeling-human-exposure-model-hem.
34 U.S. EPA. Revision to the Guideline on Air
Quality Models: Adoption of a Preferred General
Purpose (Flat and Complex Terrain) Dispersion
Model and Other Revisions (70 FR 68218,
November 9, 2005).
35 A census block is the smallest geographic area
for which census statistics are tabulated.
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hill height, which are also used in
dispersion calculations. A third library
of pollutant-specific dose-response
values is used to estimate health risk.
These are discussed below.
b. Risk From Chronic Exposure to HAP
In developing the risk assessment for
chronic exposures, we use the estimated
annual average ambient air
concentrations of each HAP emitted by
each source in the source category. The
HAP air concentrations at each nearby
census block centroid located within 50
km of the facility are a surrogate for the
chronic inhalation exposure
concentration for all the people who
reside in that census block. A distance
of 50 km is consistent with both the
analysis supporting the 1989 Benzene
NESHAP (54 FR 38044, September 14,
1989) and the limitations of Gaussian
dispersion models, including AERMOD.
For each facility, we calculate the MIR
as the cancer risk associated with a
continuous lifetime (24 hours per day,
7 days per week, 52 weeks per year, 70
years) exposure to the maximum
concentration at the centroid of each
inhabited census block. We calculate
individual cancer risk by multiplying
the estimated lifetime exposure to the
ambient concentration of each HAP (in
micrograms per cubic meter (mg/m3)) by
its unit risk estimate (URE). The URE is
an upper-bound estimate of an
individual’s incremental risk of
contracting cancer over a lifetime of
exposure to a concentration of 1
microgram of the pollutant per cubic
meter of air. For residual risk
assessments, we generally use UREs
from the EPA’s Integrated Risk
Information System (IRIS). For
carcinogenic pollutants without IRIS
values, we look to other reputable
sources of cancer dose-response values,
often using California EPA (CalEPA)
UREs, where available. In cases where
new, scientifically credible doseresponse values have been developed in
a manner consistent with EPA
guidelines and have undergone a peer
review process similar to that used by
the EPA, we may use such doseresponse values in place of, or in
addition to, other values, if appropriate.
The pollutant-specific dose-response
values used to estimate health risk are
available at https://www.epa.gov/fera/
dose-response-assessment-assessinghealth-risks-associated-exposurehazardous-air-pollutants.To estimate
individual lifetime cancer risks
associated with exposure to HAP
emissions from each facility in the
source category, we sum the risks for
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each of the carcinogenic HAP 36 emitted
by the modeled facility. We estimate
cancer risk at every census block within
50 km of every facility in the source
category. The MIR is the highest
individual lifetime cancer risk estimated
for any of those census blocks. In
addition to calculating the MIR, we
estimate the distribution of individual
cancer risks for the source category by
summing the number of individuals
within 50 km of the sources whose
estimated risk falls within a specified
risk range. We also estimate annual
cancer incidence by multiplying the
estimated lifetime cancer risk at each
census block by the number of people
residing in that block, summing results
for all of the census blocks, and then
dividing this result by a 70-year
lifetime.
To assess the risk of noncancer health
effects from chronic exposure to HAP,
we calculate either an HQ or a target
organ-specific hazard index (TOSHI).
We calculate an HQ when a single
noncancer HAP is emitted. Where more
than one noncancer HAP is emitted, we
sum the HQ for each of the HAP that
affects a common target organ or target
organ system to obtain a TOSHI. The
HQ is the estimated exposure divided
by the chronic noncancer dose-response
value, which is a value selected from
one of several sources. The preferred
chronic noncancer dose-response value
is the EPA RfC, defined as ‘‘an estimate
(with uncertainty spanning perhaps an
order of magnitude) of a continuous
inhalation exposure to the human
population (including sensitive
subgroups) that is likely to be without
an appreciable risk of deleterious effects
during a lifetime’’ (https://
iaspub.epa.gov/sor_internet/registry/
termreg/searchandretrieve/glossaries
36 The EPA’s 2005 Guidelines for Carcinogen Risk
Assessment classifies carcinogens as: ‘‘carcinogenic
to humans,’’ ‘‘likely to be carcinogenic to humans,’’
and ‘‘suggestive evidence of carcinogenic
potential.’’ These classifications also coincide with
the terms ‘‘known carcinogen, probable carcinogen,
and possible carcinogen,’’ respectively, which are
the terms advocated in the EPA’s Guidelines for
Carcinogen Risk Assessment, published in 1986 (51
FR 33992, September 24, 1986). In August 2000, the
document, Supplemental Guidance for Conducting
Health Risk Assessment of Chemical Mixtures
(EPA/630/R–00/002), was published as a
supplement to the 1986 document. Copies of both
documents can be obtained from https://
cfpub.epa.gov/ncea/risk/recordisplay.
cfm?deid=20533&CFID=70315376&CFTOKEN=71
597944. Summing the risk of these individual
compounds to obtain the cumulative cancer risk is
an approach that was recommended by the EPA’s
SAB in their 2002 peer review of the EPA’s National
Air Toxics Assessment (NATA) titled NATA—
Evaluating the National-scale Air Toxics
Assessment 1996 Data—an SAB Advisory, available
at https://yosemite.epa.gov/sab/sabproduct.nsf/
214C6E915BB04E14852570CA007A682C/$File/
ecadv02001.pdf.
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andkeywordlists/search.do?details
=&vocabName=IRIS%20Glossary). In
cases where an RfC from the EPA’s IRIS
is not available or where the EPA
determines that using a value other than
the RfC is appropriate, the chronic
noncancer dose-response value can be a
value from the following prioritized
sources, which define their doseresponse values similarly to the EPA: (1)
The Agency for Toxic Substances and
Disease Registry (ATSDR) Minimum
Risk Level (https://www.atsdr.cdc.gov/
mrls/index.asp); (2) the CalEPA Chronic
Reference Exposure Level (REL) (https://
oehha.ca.gov/air/crnr/notice-adoptionair-toxics-hot-spots-program-guidancemanual-preparation-health-risk-0); or
(3), as noted above, a scientifically
credible dose-response value that has
been developed in a manner consistent
with EPA guidelines and has undergone
a peer review process similar to that
used by the EPA. The pollutant-specific
dose-response values used to estimate
health risks are available at https://
www.epa.gov/fera/dose-responseassessment-assessing-health-risksassociated-exposure-hazardous-airpollutants.
c. Risk From Acute Exposure to HAP
That May Cause Health Effects Other
Than Cancer
For each HAP for which appropriate
acute inhalation dose-response values
are available, the EPA also assesses the
potential health risks due to acute
exposure. For these assessments, the
EPA makes conservative assumptions
about emission rates, meteorology, and
exposure location. We use the peak
hourly emission rate,37 worst-case
dispersion conditions, and, in
accordance with our mandate under
section 112 of the CAA, the point of
highest off-site exposure to assess the
potential risk to the maximally exposed
individual.
To characterize the potential health
risks associated with estimated acute
inhalation exposures to a HAP, we
generally use multiple acute doseresponse values, including acute RELs,
acute exposure guideline levels
(AEGLs), and emergency response
planning guidelines (ERPG) for 1-hour
37 In the absence of hourly emission data, we
develop estimates of maximum hourly emission
rates by multiplying the average actual annual
emissions rates by a factor (either a categoryspecific factor or a default factor of 10) to account
for variability. This is documented in Residual Risk
Assessment for Coal- and Oil-Fired EGU Source
Category in Support of the 2019 Risk and
Technology Review Proposed Rule and in Appendix
5 of the report: Analysis of Data on Short-term
Emission Rates Relative to Long-term Emission
Rates. Both are available in the docket for this
rulemaking.
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2691
exposure durations, if available, to
calculate acute HQs. The acute HQ is
calculated by dividing the estimated
acute exposure by the acute doseresponse value. For each HAP for which
acute dose-response values are
available, the EPA calculates acute HQs.
An acute REL is defined as ‘‘the
concentration level at or below which
no adverse health effects are anticipated
for a specified exposure duration.’’ 38
Acute RELs are based on the most
sensitive, relevant, adverse health effect
reported in the peer-reviewed medical
and toxicological literature. They are
designed to protect the most sensitive
individuals, including children and the
elderly, in the population through the
inclusion of margins of safety. Because
margins of safety are incorporated to
address data gaps and uncertainties,
exceeding the REL does not
automatically indicate an adverse health
impact. AEGLs represent threshold
exposure limits for the general public
and are applicable to emergency
exposures ranging from 10 minutes to 8
hours.39 They are guideline levels for
‘‘once-in-a-lifetime, short-term
exposures to airborne concentrations of
acutely toxic, high-priority chemicals.’’
Id. at 21. The AEGL–1 is specifically
defined as ‘‘the airborne concentration
(expressed as ppm (parts per million) or
mg/m3 (milligrams per cubic meter)) of
a substance above which it is predicted
that the general population, including
susceptible individuals, could
experience notable discomfort,
irritation, or certain asymptomatic
nonsensory effects. However, the effects
are not disabling and are transient and
reversible upon cessation of exposure.’’
The document also notes that ‘‘Airborne
concentrations below AEGL–1 represent
exposure levels that can produce mild
and progressively increasing but
transient and nondisabling odor, taste,
and sensory irritation or certain
asymptomatic, nonsensory effects.’’ Id.
AEGL–2 are defined as ‘‘the airborne
38 CalEPA issues acute RELs as part of its Air
Toxics Hot Spots Program, and the 1-hour and 8hour values are documented in Air Toxics Hot
Spots Program Risk Assessment Guidelines, Part I,
The Determination of Acute Reference Exposure
Levels for Airborne Toxicants, which is available at
https://oehha.ca.gov/air/general-info/oehha-acute8-hour-and-chronic-reference-exposure-level-relsummary.
39 National Academy of Sciences, 2001. Standing
Operating Procedures for Developing Acute
Exposure Levels for Hazardous Chemicals, page 2.
Available at https://www.epa.gov/sites/production/
files/2015-09/documents/sop_final_standing_
operating_procedures_2001.pdf. Note that the
National Advisory Committee for Acute Exposure
Guideline Levels for Hazardous Substances ended
in October 2011, but the AEGL program continues
to operate at the EPA and works with the National
Academies to publish final AEGLs, (https://
www.epa.gov/aegl).
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concentration (expressed as parts per
million or milligrams per cubic meter)
of a substance above which it is
predicted that the general population,
including susceptible individuals, could
experience irreversible or other serious,
long-lasting adverse health effects or an
impaired ability to escape.’’ Id.
ERPGs are ‘‘developed for emergency
planning and are intended as healthbased guideline concentrations for
single exposures to chemicals.’’ 40 Id. at
1. The ERPG–1 is defined as ‘‘the
maximum airborne concentration below
which it is believed that nearly all
individuals could be exposed for up to
1 hour without experiencing other than
mild transient adverse health effects or
without perceiving a clearly defined,
objectionable odor.’’ Id. at 2. Similarly,
the ERPG–2 is defined as ‘‘the
maximum airborne concentration below
which it is believed that nearly all
individuals could be exposed for up to
one hour without experiencing or
developing irreversible or other serious
health effects or symptoms which could
impair an individual’s ability to take
protective action.’’ Id. at 1.
An acute REL for 1-hour exposure
durations is typically lower than its
corresponding AEGL–1 and ERPG–1.
Even though their definitions are
slightly different, AEGL–1s are often the
same as the corresponding ERPG–1s,
and AEGL–2s are often equal to ERPG–
2s. The maximum HQs from our acute
inhalation screening risk assessment
typically result when we use the acute
REL for a HAP. In cases where the
maximum acute HQ exceeds 1, we also
report the HQ based on the next highest
acute dose-response value (usually the
AEGL–1 and/or the ERPG–1).
For the Coal- and Oil-Fired EGU
source category, facility-level acute
factors (i.e., multipliers) developed by
the EPA were used to estimate acute
emissions and the potential health risks
due to acute exposure. First, 2017 total
heat input (MMBtu) and boiler
maximum rated heat input (MMBtu/hr)
data were used to calculate an acute
factor for EGUs where both values were
available. Next, facility-level acute
factors were calculated using a heat
input-weighted average based on 2017
heat input for each EGU located within
a facility fenceline. The facility-level
acute factor was used for each stack at
40 ERPGS Procedures and Responsibilities. March
2014. American Industrial Hygiene Association.
Available at https://www.aiha.org/get-involved/
AIHAGuidelineFoundation/
EmergencyResponsePlanningGuidelines/
Documents/ERPG%20Committee%20Standard%
20Operating%20Procedures%20%20%20March%202014%20Revision%20%28
Updated%2010-2-2014%29.pdf.
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the facility. For units at facilities that
did not have a facility-level factor (e.g.,
2017 total heat input and boiler
maximum rated heat input were not
available), a default facility-level value
of 6 was used. The default facility-level
value of 6 was developed by taking the
average of the calculated facility-level
factors. If the calculated facility-level
acute factor was greater than 10 (e.g., in
cases where the EGU had a low 2017
heat input relative to the maximum
rated heat input), the RTR program
default acute emission adjustment factor
of 10 was used. The default emission
adjustment factor of 10 reflects a Texas
study of short-term emissions
variability, which showed that most
peak emission events in a heavilyindustrialized four-county area (Harris,
Galveston, Chambers, and Brazoria
Counties, Texas) were less than twice
the annual average hourly emissions
rate. The highest peak emissions event
was 74 times the annual average hourly
emissions rate and the 99th percentile
ratio of peak hourly emissions rate to
the annual average hourly emissions
rate was 9.41 Considering this analysis,
to account for more than 99 percent of
the peak hourly emissions, a
conservative screening multiplication
factor of 10 is applied to the average
annual hourly emissions rate in the
EPA’s acute exposure screening
assessments as the default approach. In
this analysis, we inadvertently used
allowable emissions (rather than actual
emissions, which is our standard
practice) in conjunction with the facility
level acute factors in our screening
assessment of acute risk. Because the
results showed acute risks below a level
of concern even with acute emissions
being overstated due to the use of
allowable emissions, we did not correct
the analysis and consider it to clearly
support the conclusion that acute risks
are below a level of concern as shown
in Table 5 of this preamble. A further
discussion of the development of
facility-level acute factors and emissions
used to estimate acute exposure for the
risk modeling can be found in the Risk
Modeling Dataset Memo, available in
the docket for this rulemaking.
In our acute inhalation screening risk
assessment, acute impacts are deemed
negligible for HAP for which acute HQs
are less than or equal to 1 (even under
the conservative assumptions of the
41 Allen, et al., 2004. Variable Industrial VOC
Emissions and their impact on ozone formation in
the Houston Galveston Area. Texas Environmental
Research Consortium. Available at https://
www.researchgate.net/publication/237593060_
Variable_Industrial_VOC_Emissions_and_their_
Impact_on_Ozone_Formation_in_the_Houston_
Galveston_Area.
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screening assessment), and no further
analysis is performed for these HAP. In
cases where an acute HQ from the
screening step is greater than 1, we
consider additional site-specific data to
develop a more refined estimate of the
potential for acute exposures of concern.
4. How do we conduct the
multipathway exposure and risk
screening assessment?
The EPA conducts a tiered screening
assessment examining the potential for
significant human health risks due to
exposures via routes other than
inhalation (i.e., ingestion). We first
determine whether any sources in the
source category emit any PB–HAP, as
identified in the EPA’s Air Toxics Risk
Assessment Library (See Volume 1,
Appendix D, at https://www2.epa.gov/
fera/risk-assessment-and-modeling-airtoxics-risk-assessment-reference-library.
For the Coal- and Oil-Fired EGU
source category, we identified PB–HAP
emissions of lead compounds, arsenic
compounds, Hg compounds, cadmium
compounds, polycyclic organic matter
(POM), and dioxins, so we proceeded to
the next step of the evaluation. In this
step, we determine whether the facilityspecific emission rates of the emitted
PB–HAP are large enough to create the
potential for significant human health
risk through ingestion exposure under
reasonable worst-case conditions. To
facilitate this step, we use previously
developed screening threshold emission
rates for several PB–HAP that are based
on a hypothetical upper-end screening
exposure scenario developed for use in
conjunction with the EPA’s Total Risk
Integrated Methodology.Fate, Transport,
and Ecological Exposure (TRIM.FaTE)
model. The PB–HAP with screening
threshold emission rates are arsenic
compounds, cadmium compounds,
chlorinated dibenzodioxins and furans,
Hg compounds, and POM. Based on
EPA estimates of toxicity and
bioaccumulation potential, the
pollutants above represent a
conservative list for inclusion in
multipathway risk assessments for RTR
rules. (See Volume 1, Appendix D at
https://www.epa.gov/sites/production/
files/201308/documents/volume_1_
reflibrary.pdf). In this assessment, we
compare the facility-specific emission
rates of these PB–HAP to the screening
threshold emission rates for each PB–
HAP to assess the potential for
significant human health risks via the
ingestion pathway. We call this
application of the TRIM.FaTE model the
Tier 1 screening assessment. The ratio of
a facility’s actual emission rate to the
Tier 1 screening threshold emission rate
is a ‘‘screening value.’’
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We derive the Tier 1 screening
threshold emission rates for these PB–
HAP (other than lead compounds) to
correspond to a maximum excess
lifetime cancer risk of 1-in-1 million
(i.e., for arsenic compounds,
polychlorinated dibenzodioxins and
furans and POM) or, for HAP that cause
noncancer health effects (i.e., cadmium
compounds and Hg compounds), a
maximum HQ of 1. If the emission rate
of any one PB–HAP or combination of
carcinogenic PB–HAP in the Tier 1
screening assessment exceeds the Tier 1
screening threshold emission rate for
any facility (i.e., the screening value is
greater than 1), we conduct a second
screening assessment, which we call the
Tier 2 screening assessment.
In the Tier 2 screening assessment,
the location of each facility that exceeds
a Tier 1 screening threshold emission
rate is used to refine the assumptions
associated with the Tier 1 fisher and
farmer exposure scenarios at that
facility. A key assumption in the Tier 1
screening assessment is that a lake and/
or farm is located near the facility. As
part of the Tier 2 screening assessment,
we use a United States Geological
Survey (USGS) database to identify
actual waterbodies within 50 km of each
facility. We also examine the differences
between local meteorology near the
facility and the meteorology used in the
Tier 1 screening assessment. We then
adjust the previously-developed Tier 1
screening threshold emission rates for
each PB–HAP for each facility based on
an understanding of how exposure
concentrations estimated for the
screening scenario change with the use
of local meteorology and USGS
waterbody data. If the PB–HAP emission
rates for a facility exceed the Tier 2
screening threshold emission rates and
data are available, we may conduct a
Tier 3 screening assessment. If PB–HAP
emission rates do not exceed a Tier 2
screening value of 1, we consider those
PB–HAP emissions to pose risks below
a level of concern.
There are several analyses that can be
included in a Tier 3 screening
assessment, depending upon the extent
of refinement warranted, including
validating that the lakes are fishable,
considering plume-rise to estimate
emissions lost above the mixing layer,
and considering hourly effects of
meteorology and plume rise on
chemical fate and transport. If the Tier
3 screening assessment indicates that
risks above levels of concern cannot be
ruled out, the EPA may further refine
the screening assessment through a sitespecific assessment.
In evaluating the potential
multipathway risk from emissions of
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lead compounds, rather than developing
a screening threshold emission rate, we
compare maximum estimated chronic
inhalation exposure concentrations to
the level of the current NAAQS for
lead.42 Values below the level of the
primary (health-based) lead NAAQS are
considered to have a low potential for
multipathway risk.
For further information on the
multipathway assessment approach, see
the risk document, which is available in
the docket for this action.
5. How do we conduct the
environmental risk screening
assessment?
a. Adverse Environmental Effect,
Environmental HAP, and Ecological
Benchmarks
The EPA conducts a screening
assessment to examine the potential for
an adverse environmental effect as
required under section 112(f)(2)(A) of
the CAA. Section 112(a)(7) of the CAA
defines ‘‘adverse environmental effect’’
as ‘‘any significant and widespread
adverse effect, which may reasonably be
anticipated, to wildlife, aquatic life, or
other natural resources, including
adverse impacts on populations of
endangered or threatened species or
significant degradation of
environmental quality over broad
areas.’’
The EPA focuses on eight HAP, which
are referred to as ‘‘environmental HAP,’’
in its screening assessment: six PB–HAP
and two acid gases. The PB–HAP
included in the screening assessment
are arsenic compounds, cadmium
compounds, dioxins/furans, POM, Hg
(both inorganic Hg and methyl Hg), and
lead compounds. The acid gases
included in the screening assessment
are HCl and HF.
HAP that persist and bioaccumulate
are of particular environmental concern
because they accumulate in the soil,
sediment, and water. The acid gases,
HCl and HF, are included due to their
well-documented potential to cause
direct damage to terrestrial plants. In the
42 In doing so, the EPA notes that the legal
standard for a primary NAAQS—that a standard is
requisite to protect public health and provide an
adequate margin of safety (CAA section 109(b))—
differs from the CAA section 112(f) standard
(requiring, among other things, that the standard
provide an ‘‘ample margin of safety to protect
public health’’). However, the primary lead NAAQS
is a reasonable measure of determining risk
acceptability (i.e., the first step of the Benzene
NESHAP analysis) since it is designed to protect the
most susceptible group in the human population—
children, including children living near major lead
emitting sources. 73 FR 67002/3; 73 FR 67000/3; 73
FR 67005/1. In addition, applying the level of the
primary lead NAAQS at the risk acceptability step
is conservative, since that primary lead NAAQS
reflects an adequate margin of safety.
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environmental risk screening
assessment, we evaluate the following
four exposure media: terrestrial soils,
surface water bodies (includes watercolumn and benthic sediments), fish
consumed by wildlife, and air. Within
these four exposure media, we evaluate
nine ecological assessment endpoints,
which are defined by the ecological
entity and its attributes. For PB–HAP
(other than lead), both community-level
and population-level endpoints are
included. For acid gases, the ecological
assessment evaluated is terrestrial plant
communities.
An ecological benchmark represents a
concentration of HAP that has been
linked to a particular environmental
effect level. For each environmental
HAP, we identified the available
ecological benchmarks for each
assessment endpoint. We identified,
where possible, ecological benchmarks
at the following effect levels: probable
effect levels, lowest-observed-adverseeffect level, and no-observed-adverseeffect level. In cases where multiple
effect levels were available for a
particular PB–HAP and assessment
endpoint, we use all of the available
effect levels to help us to determine
whether ecological risks exist and, if so,
whether the risks could be considered
significant and widespread.
For further information on how the
environmental risk screening
assessment was conducted, including a
discussion of the risk metrics used, how
the environmental HAP were identified,
and how the ecological benchmarks
were selected, see Appendix 9 of the
risk document, which is available in the
docket for this action.
b. Environmental Risk Screening
Methodology
For the environmental risk screening
assessment, the EPA first determined
whether any facilities in the Coal- and
Oil-Fired EGU source category emitted
any of the environmental HAP. For the
Coal- and Oil-Fired EGU source
category, we identified emissions of
lead compounds, arsenic compounds,
Hg compounds, cadmium compounds,
POM, dioxins, HCl, and HF. Because
one or more of the environmental HAP
evaluated are emitted by at least one
facility in the source category, we
proceeded to the second step of the
evaluation.
c. PB–HAP Methodology
The environmental screening
assessment includes six PB–HAP,
arsenic compounds, cadmium
compounds, dioxins/furans, POM, Hg
(both inorganic Hg and methyl Hg), and
lead compounds. With the exception of
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lead, the environmental risk screening
assessment for PB–HAP consists of three
tiers. The first tier of the environmental
risk screening assessment uses the same
health-protective conceptual model that
is used for the Tier 1 human health
screening assessment. TRIM.FaTE
model simulations were used to backcalculate Tier 1 screening threshold
emission rates. The screening threshold
emission rates represent the emission
rate in tpy that results in media
concentrations at the facility that equal
the relevant ecological benchmark. To
assess emissions from each facility in
the category, the reported emission rate
for each PB–HAP was compared to the
Tier 1 screening threshold emission rate
for that PB–HAP for each assessment
endpoint and effect level. If emissions
from a facility do not exceed the Tier 1
screening threshold emission rate, the
facility ‘‘passes’’ the screening
assessment, and, therefore, is not
evaluated further under the screening
approach. If emissions from a facility
exceed the Tier 1 screening threshold
emission rate, we evaluate the facility
further in Tier 2.
In Tier 2 of the environmental
screening assessment, the screening
threshold emission rates are adjusted to
account for local meteorology and the
actual location of lakes in the vicinity of
facilities that did not pass the Tier 1
screening assessment. For soils, we
evaluate the average soil concentration
for all soil parcels within a 7.5-km
radius for each facility and PB–HAP.
For the water, sediment, and fish tissue
concentrations, the highest value for
each facility for each pollutant is used.
If emission concentrations from a
facility do not exceed the Tier 2
screening threshold emission rate, the
facility ‘‘passes’’ the screening
assessment and typically is not
evaluated further. If emissions from a
facility exceed the Tier 2 screening
threshold emission rate, we evaluate the
facility further in Tier 3.
As in the multipathway human health
risk assessment, in Tier 3 of the
environmental screening assessment, we
examine the suitability of the lakes
around the facilities to support life and
remove those that are not suitable (e.g.,
lakes that have been filled in or are
industrial ponds), adjust emissions for
plume-rise, and conduct hour-by-hour
time-series assessments. If these Tier 3
adjustments to the screening threshold
emission rates still indicate the
potential for an adverse environmental
effect (i.e., facility emission rate exceeds
the screening threshold emission rate),
we may elect to conduct a more refined
assessment using more site-specific
information. If, after additional
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refinement, the facility emission rate
still exceeds the screening threshold
emission rate, the facility may have the
potential to cause an adverse
environmental effect.
To evaluate the potential for an
adverse environmental effect from lead,
we compared the average modeled air
concentrations (from HEM–3) of lead
around each facility in the source
category to the level of the secondary
NAAQS for lead. The secondary lead
NAAQS is a reasonable means of
evaluating environmental risk because it
is set to provide substantial protection
against adverse welfare effects which
can include ‘‘effects on soils, water,
crops, vegetation, man-made materials,
animals, wildlife, weather, visibility and
climate, damage to and deterioration of
property, and hazards to transportation,
as well as effects on economic values
and on personal comfort and wellbeing.’’
d. Acid Gas Environmental Risk
Methodology
The environmental screening
assessment for acid gases evaluates the
potential phytotoxicity and reduced
productivity of plants due to chronic
exposure to HF and HCl. The
environmental risk screening
methodology for acid gases is a singletier screening assessment that compares
modeled ambient air concentrations
(from AERMOD) to the ecological
benchmarks for each acid gas. To
identify a potential adverse
environmental effect (as defined in
section 112(a)(7) of the CAA) from
emissions of HF and HCl, we evaluate
the following metrics: The size of the
modeled area around each facility that
exceeds the ecological benchmark for
each acid gas, in acres and km2; the
percentage of the modeled area around
each facility that exceeds the ecological
benchmark for each acid gas; and the
area-weighted average screening value
around each facility (calculated by
dividing the area-weighted average
concentration over the 50-km modeling
domain by the ecological benchmark for
each acid gas). For further information
on the environmental screening
assessment approach, see Appendix 9 of
the risk document, which is available in
the docket for this action.
6. How do we conduct facility-wide
assessments?
To put the source category risks in
context, we typically examine the risks
from the entire ‘‘facility,’’ where the
facility includes all HAP-emitting
operations within a contiguous area and
under common control. In other words,
we examine the HAP emissions not only
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from the source category emission
points of interest, but also emissions of
HAP from all other emission sources at
the facility for which we have data. For
this source category, we conducted the
facility-wide assessment using a dataset
compiled from the 2014 NEI. The source
category records of that NEI dataset
were removed, evaluated, and updated
as described in section IV.D of this
preamble: What other relevant
background information and data are
available? Once a quality assured source
category dataset was available, it was
placed back with the remaining records
from the NEI for that facility. The
facility-wide file was then used to
analyze risks due to the inhalation of
HAP that are emitted ‘‘facility-wide’’ for
the populations residing within 50 km
of each facility, consistent with the
methods used for the source category
analysis described above. For these
facility-wide risk analyses, the modeled
source category risks were compared to
the facility-wide risks to determine the
portion of the facility-wide risks that
could be attributed to the source
category addressed in this proposal. We
also specifically examined the facility
that was associated with the highest
estimate of risk and determined the
percentage of that risk attributable to the
source category of interest. The risk
document, available through the docket
for this action, provides the
methodology and results of the facilitywide analyses, including all facilitywide risks and the percentage of source
category contribution to facility-wide
risks.
7. How do we consider uncertainties in
risk assessment?
Uncertainty and the potential for bias
are inherent in all risk assessments,
including those performed for this
proposal. Although uncertainty exists,
we believe that our approach, which
used conservative tools and
assumptions, ensures that our decisions
are health and environmentally
protective. A brief discussion of the
uncertainties in the RTR emissions
dataset, dispersion modeling, inhalation
exposure estimates, and dose-response
relationships follows below. Also
included are those uncertainties specific
to our acute screening assessments,
multipathway screening assessments,
and our environmental risk screening
assessments. A more thorough
discussion of these uncertainties is
included in the risk document, which is
available in the docket for this action. If
a multipathway site-specific assessment
was performed for this source category,
a full discussion of the uncertainties
associated with that assessment can be
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found in Appendix 11 of that document,
Site-Specific Human Health
Multipathway Residual Risk Assessment
Report.
a. Uncertainties in the RTR Emissions
Dataset
Although the development of the RTR
emissions dataset involved quality
assurance/quality control processes, the
accuracy of emissions values will vary
depending on the source of the data, the
degree to which data are incomplete or
missing, the degree to which
assumptions made to complete the
datasets are accurate, errors in emission
estimates, and other factors. The
emission estimates considered in this
analysis generally are annual totals for
certain years, and they do not reflect
short-term fluctuations during the
course of a year or variations from year
to year. The estimates of peak hourly
emission rates for the acute effects
screening assessment were based on an
emission adjustment factor applied to
the average annual hourly emission
rates, which are intended to account for
emission fluctuations due to normal
facility operations.
b. Uncertainties in Dispersion Modeling
We recognize there is uncertainty in
ambient concentration estimates
associated with any model, including
the EPA’s recommended regulatory
dispersion model, AERMOD. In using a
model to estimate ambient pollutant
concentrations, the user chooses certain
options to apply. For RTR assessments,
we select some model options that have
the potential to overestimate ambient air
concentrations (e.g., not including
plume depletion or pollutant
transformation). We select other model
options that have the potential to
underestimate ambient impacts (e.g., not
including building downwash). Other
options that we select have the potential
to either under- or overestimate ambient
levels (e.g., meteorology and receptor
locations). On balance, considering the
directional nature of the uncertainties
commonly present in ambient
concentrations estimated by dispersion
models, the approach we apply in the
RTR assessments should yield unbiased
estimates of ambient HAP
concentrations. We also note that the
selection of meteorology dataset
location could have an impact on the
risk estimates. As we continue to update
and expand our library of
meteorological station data used in our
risk assessments, we expect to reduce
this variability.
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c. Uncertainties in Inhalation Exposure
Assessment
Although every effort is made to
identify all of the relevant facilities and
emission points, as well as to develop
accurate estimates of the annual
emission rates for all relevant HAP, the
uncertainties in our emission inventory
likely dominate the uncertainties in the
exposure assessment. Some
uncertainties in our exposure
assessment include human mobility,
using the centroid of each census block,
assuming lifetime exposure, and
assuming only outdoor exposures. For
most of these factors, there is neither an
underestimate nor overestimate when
looking at the maximum individual risk
or the incidence, but the shape of the
distribution of risks may be affected.
With respect to outdoor exposures,
actual exposures may not be as high if
people spend time indoors, especially
for very reactive pollutants or larger
particles. For all factors, we reduce
uncertainty when possible. For
example, with respect to census-block
centroids, we analyze large blocks using
aerial imagery and adjust locations of
the block centroids to better represent
the population in the blocks. We also
add additional receptor locations where
the population of a block is not well
represented by a single location.
d. Uncertainties in Dose-Response
Relationships
There are uncertainties inherent in
the development of the dose-response
values used in our risk assessments for
cancer effects from chronic exposures
and noncancer effects from both chronic
and acute exposures. Some
uncertainties are generally expressed
quantitatively, and others are generally
expressed in qualitative terms. We note,
as a preface to this discussion, a point
on dose-response uncertainty that is
stated in the EPA’s 2005 Guidelines for
Carcinogen Risk Assessment; namely,
that ‘‘the primary goal of EPA actions is
protection of human health;
accordingly, as an Agency policy, risk
assessment procedures, including
default options that are used in the
absence of scientific data to the
contrary, should be health protective’’
(the EPA’s 2005 Guidelines for
Carcinogen Risk Assessment, page 1–7).
This is the approach followed here as
summarized in the next paragraphs.
Cancer UREs used in our risk
assessments are those that have been
developed to generally provide an upper
bound estimate of risk.43 That is, they
43 IRIS glossary (https://ofmpub.epa.gov/sor_
internet/registry/termreg/searchandretrieve/
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2695
represent a ‘‘plausible upper limit to the
true value of a quantity’’ (although this
is usually not a true statistical
confidence limit). In some
circumstances, the true risk could be as
low as zero; however, in other
circumstances the risk could be
greater.44 Chronic noncancer RfC and
reference dose (RfD) values represent
chronic exposure levels that are
intended to be health-protective levels.
To derive dose-response values that are
intended to be ‘‘without appreciable
risk,’’ the methodology relies upon an
uncertainty factor (UF) approach,45
which considers uncertainty, variability,
and gaps in the available data. The UFs
are applied to derive dose-response
values that are intended to protect
against appreciable risk of deleterious
effects.
Many of the UFs used to account for
variability and uncertainty in the
development of acute dose-response
values are quite similar to those
developed for chronic durations.
Additional adjustments are often
applied to account for uncertainty in
extrapolation from observations at one
exposure duration (e.g., 4 hours) to
derive an acute dose-response value at
another exposure duration (e.g., 1 hour).
Not all acute dose-response values are
developed for the same purpose, and
care must be taken when interpreting
the results of an acute assessment of
human health effects relative to the
dose-response value or values being
exceeded. Where relevant to the
estimated exposures, the lack of acute
dose-response values at different levels
of severity should be factored into the
risk characterization as potential
uncertainties.
Uncertainty also exists in the
selection of ecological benchmarks for
the environmental risk screening
assessment. We established a hierarchy
of preferred benchmark sources to allow
selection of benchmarks for each
environmental HAP at each ecological
assessment endpoint. We searched for
benchmarks for three effect levels (i.e.,
no-effects level, threshold-effect level,
and probable effect level), but not all
combinations of ecological assessment/
environmental HAP had benchmarks for
glossariesandkeywordlists/search.do?
details=&glossaryName=IRIS%20Glossary).
44 An exception to this is the URE for benzene,
which is considered to cover a range of values, each
end of which is considered to be equally plausible,
and which is based on maximum likelihood
estimates.
45 See A Review of the Reference Dose and
Reference Concentration Processes, U.S. EPA,
December 2002, and Methods for Derivation of
Inhalation Reference Concentrations and
Application of Inhalation Dosimetry, U.S. EPA,
1994.
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all three effect levels. Where multiple
effect levels were available for a
particular HAP and assessment
endpoint, we used all of the available
effect levels to help us determine
whether risk exists and whether the risk
could be considered significant and
widespread.
Although we make every effort to
identify appropriate human health effect
dose-response values for all pollutants
emitted by the sources in this risk
assessment, some HAP emitted by this
source category are lacking doseresponse assessments. Accordingly,
these pollutants cannot be included in
the quantitative risk assessment, which
could result in quantitative estimates
understating HAP risk. To help to
alleviate this potential underestimate,
where we conclude similarity with a
HAP for which a dose-response value is
available, we use that value as a
surrogate for the assessment of the HAP
for which no value is available. To the
extent use of surrogates indicates
appreciable risk, we may identify a need
to increase priority for an IRIS
assessment for that substance. We
additionally note that, generally
speaking, HAP of greatest concern due
to environmental exposures and hazard
are those for which dose-response
assessments have been performed,
reducing the likelihood of understating
risk. Further, HAP not included in the
quantitative assessment are assessed
qualitatively and considered in the risk
characterization that informs the risk
management decisions, including
consideration of HAP reductions
achieved by various control options.
For a group of compounds that are
unspeciated (e.g., glycol ethers), we
conservatively use the most protective
dose-response value of an individual
compound in that group to estimate
risk. Similarly, for an individual
compound in a group (e.g., ethylene
glycol diethyl ether) that does not have
a specified dose-response value, we also
apply the most protective dose-response
value from the other compounds in the
group to estimate risk.
e. Uncertainties in Acute Inhalation
Screening Assessments
In addition to the uncertainties
highlighted above, there are several
factors specific to the acute exposure
assessment that the EPA conducts as
part of the risk review under section 112
of the CAA. The accuracy of an acute
inhalation exposure assessment
depends on the simultaneous
occurrence of independent factors that
may vary greatly, such as hourly
emissions rates, meteorology, and the
presence of humans at the location of
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the maximum concentration. In the
acute screening assessment that we
conduct under the RTR program, we
assume that peak emissions from the
source category and worst-case
meteorological conditions co-occur,
thus, resulting in maximum ambient
concentrations. These two events are
unlikely to occur at the same time,
making these assumptions conservative.
We then include the additional
assumption that a person is located at
this point during this same time period.
For this source category, these
assumptions would tend to be worstcase actual exposures, as it is unlikely
that a person would be located at the
point of maximum exposure during the
time when peak emissions and worstcase meteorological conditions occur
simultaneously.
f. Uncertainties in the Multipathway
and Environmental Risk Screening
Assessments
For each source category, we
generally rely on site-specific levels of
PB–HAP or environmental HAP
emissions to determine whether a
refined assessment of the impacts from
multipathway exposures is necessary or
whether it is necessary to perform an
environmental screening assessment.
This determination is based on the
results of a three-tiered screening
assessment that relies on the outputs
from models—TRIM.FaTE and
AERMOD—that estimate environmental
pollutant concentrations and human
exposures for five PB–HAP (dioxins,
POM, Hg, cadmium, and arsenic) and
two acid gases (HF and HCl). For lead,
we use AERMOD to determine ambient
air concentrations, which are then
compared to the secondary NAAQS
standard for lead. Two important types
of uncertainty associated with the use of
these models in RTR risk assessments
and inherent to any assessment that
relies on environmental modeling are
model uncertainty and input
uncertainty.46
Model uncertainty concerns whether
the model adequately represents the
actual processes (e.g., movement and
accumulation) that might occur in the
environment. For example, does the
model adequately describe the
movement of a pollutant through the
soil? This type of uncertainty is difficult
to quantify. However, based on feedback
received from previous EPA SAB
46 In the context of this discussion, the term
‘‘uncertainty’’ as it pertains to exposure and risk
encompasses both variability in the range of
expected inputs and screening results due to
existing spatial, temporal, and other factors, as well
as uncertainty in being able to accurately estimate
the true result.
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reviews and other reviews, we are
confident that the models used in the
screening assessments are appropriate
and state-of-the-art for the multipathway
and environmental screening risk
assessments conducted in support of
RTR.
Input uncertainty is concerned with
how accurately the models have been
configured and parameterized for the
assessment at hand. For Tier 1 of the
multipathway and environmental
screening assessments, we configured
the models to avoid underestimating
exposure and risk. This was
accomplished by selecting upper-end
values from nationally representative
datasets for the more influential
parameters in the environmental model,
including selection and spatial
configuration of the area of interest, lake
location and size, meteorology, surface
water, soil characteristics, and structure
of the aquatic food web. We also assume
an ingestion exposure scenario and
values for human exposure factors that
represent reasonable maximum
exposures.
In Tier 2 of the multipathway and
environmental screening assessments,
we refine the model inputs to account
for meteorological patterns in the
vicinity of the facility versus using
upper-end national values, and we
identify the actual location of lakes near
the facility rather than the default lake
location that we apply in Tier 1. By
refining the screening approach in Tier
2 to account for local geographical and
meteorological data, we decrease the
likelihood that concentrations in
environmental media are overestimated,
thereby increasing the usefulness of the
screening assessment. In Tier 3 of the
screening assessments, we refine the
model inputs again to account for hourby-hour plume rise and the height of the
mixing layer. We can also use those
hour-by-hour meteorological data in a
TRIM.FaTE run using the screening
configuration corresponding to the lake
location. These refinements produce a
more accurate estimate of chemical
concentrations in the media of interest,
thereby reducing the uncertainty with
those estimates. The assumptions and
the associated uncertainties regarding
the selected ingestion exposure scenario
are the same for all three tiers.
For the environmental screening
assessment for acid gases, we employ a
single-tiered approach. We use the
modeled air concentrations and
compare those with ecological
benchmarks.
For all tiers of the multipathway and
environmental screening assessments,
our approach to addressing model input
uncertainty is generally cautious. We
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choose model inputs from the upper
end of the range of possible values for
the influential parameters used in the
models, and we assume that the
exposed individual exhibits ingestion
behavior that would lead to a high total
exposure. This approach reduces the
likelihood of not identifying high risks
for adverse impacts.
Despite the uncertainties, when
individual pollutants or facilities do not
exceed screening threshold emission
rates (i.e., screen out), we are confident
that the potential for adverse
multipathway impacts on human health
is very low. On the other hand, when
individual pollutants or facilities do
exceed screening threshold emission
rates, it does not mean that impacts are
significant, only that we cannot rule out
that possibility and that a refined
assessment for the site might be
2697
not have appropriate multipathway
models that allow us to predict the
concentration of that pollutant. The EPA
acknowledges that other HAP beyond
these that we are evaluating may have
the potential to cause adverse effects
and, therefore, the EPA may evaluate
other relevant HAP in the future, as
modeling science and resources allow.
necessary to obtain a more accurate risk
characterization for the source category.
The EPA evaluates the following HAP
in the multipathway and/or
environmental risk screening
assessments, where applicable: Arsenic,
cadmium, dioxins/furans, lead, Hg (both
inorganic and methyl Hg), POM, HCl,
and HF. These HAP represent pollutants
that can cause adverse impacts either
through direct exposure to HAP in the
air or through exposure to HAP that are
deposited from the air onto soils and
surface waters and then through the
environment into the food web. These
HAP represent those HAP for which we
can conduct a meaningful multipathway
or environmental screening risk
assessment. For other HAP not included
in our screening assessments, the model
has not been parameterized such that it
can be used for that purpose. In some
cases, depending on the HAP, we may
VI. RTR Analytical Results and
Proposed Decisions
A. What are the results of the risk
assessment and analyses?
1. Inhalation Risk Assessment Results
Table 5 of this preamble provides a
summary of the results of the inhalation
risk assessment for the source category.
More detailed information on the risk
assessment can be found in the risk
document, available in the docket for
this action.
TABLE 5—COAL- AND OIL-FIRED EGU INHALATION RISK ASSESSMENT RESULTS
Maximum individual
cancer risk
(in 1 million) 2
Number of
facilities 1
322 .............
Based on . . .
Population at increased
risk of cancer
≥1-in-1 million
Based on . . .
Annual cancer
incidence
(cases per year)
Based on . . .
Maximum chronic
noncancer
TOSHI 3
Maximum screening
acute noncancer
HQ 4
Based on . . .
Actual
emissions
level 2
Allowable
emissions
level
Actual
emissions
level 2
Allowable
emissions
level
Actual
emissions
level 2
Allowable
emissions
level
Actual
emissions
level
Allowable
emissions
level
9
10
193,000
636,000
0.04
0.1
0.2
0.4
Based on actual
emissions level
HQREL = 0.09 (arsenic).
1
Number of facilities evaluated in the risk analysis.
Maximum individual excess lifetime cancer risk due to HAP emissions from the source category.
Maximum TOSHI. The target organ systems with the highest TOSHI for the source category are neurological and reproductive.
4 The maximum estimated acute exposure concentration was divided by available short-term threshold values to develop an array of HQ values. HQ values shown
use the lowest available acute threshold value, which in most cases is the REL. When an HQ exceeds 1, we also show the HQ using the next lowest available acute
dose-response value.
2
3
As shown in Table 5 of this preamble,
based on actual emissions, the estimated
cancer MIR is 9-in-1 million, and nickel
emissions from oil-fired EGUs are the
major contributor to the risk. The total
estimated cancer incidence from this
source category is 0.04 excess cancer
cases per year, or one excess case in
every 25 years. Approximately 193,000
people are estimated to have cancer
risks at or above 1-in-1 million from
HAP emitted from the facilities in this
source category. The estimated
maximum chronic noncancer TOSHI for
the source category is 0.2 (respiratory),
which is driven by emissions of nickel
and cobalt from oil-fired EGUs. No one
is exposed to TOSHI levels above 1.
Based on allowable emissions, the
estimated cancer MIR is 10-in-1 million,
and, as before, nickel emissions from
oil-fired EGUs are the major contributor
to the risk. The total estimated cancer
incidence from this source category is
0.1 excess cancer cases per year, or one
excess case in every 10 years.
Approximately 636,000 people are
estimated to have cancer risks at or
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above 1-in-1 million from HAP emitted
from the facilities in this source
category. The estimated maximum
chronic noncancer TOSHI for the source
category is 0.4 (respiratory), driven by
emissions of nickel and cobalt from oilfired EGUs. No one is exposed to TOSHI
levels above 1.
2. Acute Risk Results
Table 5 of this preamble provides the
worst-case acute HQ (based on the REL)
of 0.09, driven by actual emissions of
arsenic. There are no facilities that have
acute HQs (based on the REL or any
other reference values) greater than 1.
For more detailed acute risk results,
refer to the risk document.
3. Multipathway Risk Screening Results
Potential multipathway health risks
under a fisher and gardener scenario
were identified using a three-tier
screening assessment of the PB–HAP
emitted by facilities in this source
category, and a site-specific assessment
of Hg using TRIM.FaTE for one location.
Of the 322 MATS facilities modeled,
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307 facilities have reported emissions of
carcinogenic PB–HAP (arsenic, dioxins,
and POM) that exceed a Tier 1 cancer
screening value of 1, and 235 facilities
have reported emissions of noncarcinogenic PB–HAP (lead, Hg, and
cadmium) that exceed a Tier 1
noncancer screening value of 1. For
facilities that exceeded a Tier 1
multipathway screening value of 1, we
used additional facility site-specific
information to perform an assessment
through Tiers 2 and 3, as necessary, to
determine the maximum chronic cancer
and noncancer impacts for the source
category. For cancer, the highest Tier 2
screening value was 200. This screening
value was reduced to 50 after the plume
rise stage of Tier 3. Because this
screening value was much lower than
100-in-1 million, and because we expect
the actual risk to be lower than the
screening value (site-specific
assessments typically lower estimates
by an order of magnitude), we did not
perform further assessment for cancer.
For noncancer, the highest Tier 2
screening value was 30 (for Hg), with
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four facilities having screening values
greater than 20. These screening values
were reduced to 9 or lower after the
plume rise stage of Tier 3.
An exceedance of a screening value in
any of the tiers cannot be equated with
a risk value or an HQ (or HI). Rather, it
represents a high-end estimate of what
the risk or hazard may be. For example,
a screening value of 2 for a noncarcinogen can be interpreted to mean
that we are confident that the HQ would
be lower than 2. Similarly, a screening
value of 30 for a carcinogen means that
we are confident that the risk is lower
than 30-in-1 million. Our confidence
comes from the conservative, or healthprotective, assumptions encompassed in
the screening tiers: We choose inputs
from the upper end of the range of
possible values for the influential
parameters used in the screening tiers;
and we assume that the exposed
individual exhibits ingestion behavior
that would lead to a high total exposure.
In evaluating the potential for
multipathway effects from emissions of
lead, we compared modeled maximum
annual lead concentrations to the
secondary NAAQS for lead (0.15 mg/m3).
The modeled maximum annual lead
concentration is below the NAAQS for
lead, indicating a low potential for
multipathway impacts of concern due to
lead.
4. Multipathway Site-Specific
Assessment Results
Because the final stage of Tier 3 (timeseries) was unlikely to reduce the
highest Hg screening values to 1, we
conducted a site-specific multipathway
assessment of Hg emissions for this
source category. Analysis of the
facilities with the highest Tier 2 and
Tier 3 screening values helped identify
the location for the site-specific
assessment and the facilities to model
with TRIM.FaTE. We also considered
the effect multiple facilities within the
source category could have on common
lakes in the modeling domain. The
selection of the facilities for the sitespecific assessment also included
evaluating the number and location of
lakes impacted, watershed boundaries,
and land-use features around the target
lakes, (i.e., elevation changes,
topography, rivers).
The three facilities selected are
located near Underwood, North Dakota.
All three facilities had Tier 2 screening
values greater than or equal to 20. Two
of the facilities are near each other (16
km apart). The third facility is more
distant, about 20 to 30 km from the
other facilities, but it was included in
the analysis because it is within the 50km modeling domain of the other
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facilities and because it had an elevated
Tier 2 screening value. We expect that
the exposure scenarios we assessed for
these facilities are among the highest, if
not the highest, that might be
encountered for other facilities in this
source category. The refined sitespecific multipathway assessment, as in
the screening assessments, includes
some hypothetical elements, namely the
hypothetical human receptor (e.g., the
fisher scenario which did not screen out
in the screening assessments). It is
important to note that although the
multipathway assessment has been
conducted, no data exist to verify the
existence of the hypothetical human
receptor. The refined multipathway
assessment produced an HQ of 0.06 for
Hg for the three facilities assessed. This
risk assessment likely represents the
maximum hazard for Hg through fish
consumption for the source category
and, with an HQ less than 1, is below
the level of concern for exposure to
emissions from these sources.
5. Environmental Risk Screening Results
As described in section V.C of this
preamble, we conducted an
environmental risk screening
assessment for the Coal- and Oil-Fired
EGU source category for the following
pollutants: Arsenic, cadmium, dioxins/
furans, HCl, HF, lead, Hg (methyl Hg
and mercuric chloride), and POMs.
In the Tier 1 screening analysis for
PB–HAP (other than lead, which was
evaluated differently), POM emissions
had no exceedances of any of the
ecological benchmarks evaluated.
Arsenic and dioxins/furans emissions
had Tier 1 exceedances for surface soil
benchmarks. Cadmium and methyl Hg
emissions had Tier 1 exceedances for
surface soil and fish benchmarks.
Divalent Hg emissions had Tier 1
exceedances for sediment and surface
soil benchmarks.
A Tier 2 screening analysis was
performed for arsenic, cadmium,
dioxins/furans, divalent Hg, and methyl
Hg emissions. In the Tier 2 screening
analysis, arsenic, cadmium, and
dioxins/furans emissions had no
exceedances of any of the ecological
benchmarks evaluated. Divalent Hg
emissions from two facilities exceeded
the Tier 2 screen for a sediment
threshold level benchmark by a
maximum screening value of 2 at lake
#35731. Methyl Hg emissions from the
same two facilities exceeded the Tier 2
screen for a fish (avian/piscivores) noobserved-adverse-effect-level (NOAEL)
(merganser) benchmark by a maximum
screening value of 2 at the same lake
(lake #35731). A Tier 3 screening
assessment was performed to verify the
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existence of lake #35731. Lake #35731
was found to be located on-site and is
a man-made industrial pond, and,
therefore, was removed from the
assessment.
Methyl Hg emissions from two
facilities exceeded the Tier 2 screen for
a surface soil NOAEL for avian ground
insectivores (woodcock) benchmark by a
maximum screening value of 2. Other
surface soil benchmarks for methyl Hg,
such as the NOAEL for mammalian
insectivores and the threshold level for
the invertebrate community, were not
exceeded. Given the low Tier 2
maximum screening value of 2 for
methyl Hg, and the fact that only the
most protective benchmark was
exceeded, a Tier 3 environmental risk
screen was not conducted for methyl
Hg.
For lead, we did not estimate any
exceedances of the secondary lead
NAAQS. For HCl and HF, the average
modeled concentration around each
facility (i.e., the average concentration
of all off-site data points in the
modeling domain) did not exceed any
ecological benchmark. In addition, each
individual modeled concentration of
HCl and HF (i.e., each off-site data point
in the modeling domain) was below the
ecological benchmarks for all facilities.
Based on the results of the
environmental risk screening analysis,
we do not expect an adverse
environmental effect as a result of HAP
emissions from this source category.
6. Facility-Wide Risk Results
Based on facility-wide emissions, the
estimated cancer MIR is 9-in-1 million,
and nickel emissions from oil-fired
EGUs are the major contributor to the
risk. The total estimated cancer
incidence from this source category is
0.04 excess cancer cases per year, or one
excess case in every 25 years.
Approximately 203,000 people are
estimated to have cancer risks at or
above 1-in-1 million from HAP emitted
from the facilities in this source
category. The estimated maximum
chronic noncancer TOSHI for the source
category is 0.2 (respiratory), driven by
emissions of nickel and cobalt from oilfired EGUs. No one is exposed to TOSHI
levels above 1. These results are very
similar to those based on actual
emissions from the source category
because there is not significant
collocation of other sources with EGUs.
7. What demographic groups might
benefit from this regulation?
To examine the potential for any
environmental justice issues that might
be associated with the source category,
we performed a demographic analysis,
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which is an assessment of risk to
individual demographic groups of the
populations living within 5 km and
within 50 km of the facilities. In the
analysis, we evaluated the distribution
of HAP-related cancer and noncancer
risk from the Coal- and Oil-Fired EGU
source category across different
demographic groups within the
populations living near facilities.47
The results of the demographic
analysis are summarized in Table 6
below. These results, for various
demographic groups, are based on the
estimated risk from actual emissions
levels for the population living within
50 km of the facilities.
TABLE 6—COAL- AND OIL-FIRED EGU SOURCE CATEGORY DEMOGRAPHIC RISK ANALYSIS RESULTS
Population
with cancer
risk greater
than or equal
to 1-in-1
million
Total Population ...........................................................................................................................
Population
with HI greater
than 1
Nationwide
Source Category
317,746,049
193,000
0
White and Minority by Percent
White ............................................................................................................................................
Minority ........................................................................................................................................
62
38
1
* 99
0
0
Minority by Percent
African American .........................................................................................................................
Native American ..........................................................................................................................
Hispanic or Latino (includes white and nonwhite) .......................................................................
Other and Multiracial ...................................................................................................................
12
0.8
18
7
0
0
* 99
0
0
0
0
0
Income by Percent
Below Poverty Level ....................................................................................................................
Above Poverty Level ....................................................................................................................
14
86
40
60
0
0
Education by Percent
Over 25 and without a High School Diploma ..............................................................................
Over 25 and with a High School Diploma ...................................................................................
14
86
25
75
0
0
Linguistically Isolated by Percent
Linguistically Isolated ...................................................................................................................
6
* 67
0
* Note: All the people with a cancer risk greater than or equal to 1 in 1 million reside in Puerto Rico.
The results of the Coal- and Oil-Fired
EGU source category demographic
analysis indicate that emissions from
the source category expose
approximately 193,000 people to a
cancer risk at or above 1-in-1 million
and no people to a chronic noncancer
TOSHI greater than 1. There are only 4
facilities in the source category with
cancer risk at or above 1-in-1 million,
and all of them are located in Puerto
Rico. Consequently, all of the
percentages of the at-risk population in
each demographic group associated
with the Puerto Rican population are
much higher than their respective
nationwide percentages, and those not
associated with Puerto Rico are much
lower than their respective nationwide
percentages.
The methodology and the results of
the demographic analysis are presented
in a technical report, Risk and
Technology Review—Analysis of
Demographic Factors for Populations
Living Near Coal- and Oil-Fired EGUs,
available in the docket for this action.
47 Demographic groups included in the analysis
are: White, African American, Native American,
other races and multiracial, Hispanic or Latino,
children 17 years of age and under, adults 18 to 64
years of age, adults 65 years of age and over, adults
without a high school diploma, people living below
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B. What are our proposed decisions
regarding risk acceptability, ample
margin of safety, and adverse
environmental effect?
1. Risk Acceptability
As noted in section V.A of this
preamble, the EPA sets standards under
CAA section 112(f)(2) using ‘‘a two-step
standard-setting approach, with an
analytical first step to determine an
‘acceptable risk’ that considers all
health information, including risk
estimation uncertainty, and includes a
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presumptive limit on MIR of
approximately 1-in-10 thousand.’’ (54
FR 38045, September 14, 1989). In this
proposal, the EPA estimated risks based
on actual and allowable emissions from
coal- and oil-fired EGU sources, and we
considered these in determining
acceptability.
The estimated inhalation cancer risk
to the individual most exposed to actual
emissions from the source category is 9in-1 million. The estimated incidence of
cancer due to inhalation exposures is
0.04 excess cancer cases per year, or one
excess case every 25 years.
Approximately 190,000 people face an
increased cancer risk at or above 1-in1 million due to inhalation exposure to
HAP emissions from this source
category. The estimated maximum
chronic noncancer TOSHI from
the poverty level, people living two times the
poverty level, and linguistically isolated people.
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inhalation exposure for this source
category is 0.2. Based on allowable
emissions, the estimated inhalation
cancer risk to the individual most
exposed is 10-in-1 million, and the
estimated incidence of cancer due to
inhalation exposures is 0.1 excess
cancer cases per year, or one excess case
every 10 years. Approximately 640,000
people face an increased cancer risk at
or above 1-in-1 million due to
inhalation exposure to allowable HAP
emissions from this source category.
The maximum chronic noncancer
TOSHI from inhalation exposure is 0.4
based on allowable emissions. The
screening assessment of worst-case
acute inhalation impacts indicates that
no facilities have actual emissions that
result in an acute HQ greater than 1 for
any pollutant, with an estimated worstcase maximum acute HQ of 0.09 for
arsenic based on the 1-hour REL.
Potential multipathway human health
risks were estimated using a three-tier
screening assessment of the PB–HAP
emitted by facilities in this source
category. The only pollutants with
elevated screening values are arsenic
(cancer) and Hg (noncancer). The
highest Tier 3 cancer screening value is
50, mostly driven by arsenic. The
highest Tier 3 noncancer screening
value is 9, for Hg. We performed a sitespecific multipathway assessment
which indicates that the highest Hg HQ
expected from any facility in the source
category is much less than 1. In
evaluating the potential for
multipathway effects from emissions of
lead from the source category, we
compared modeled maximum annual
lead concentrations to the primary
NAAQS for lead (0.15 mg/m3). Results of
this analysis estimate that the NAAQS
for lead would not be exceeded at any
off-site locations.
In determining whether risks are
acceptable for this source category, the
EPA considered all available health
information and risk estimation
uncertainty as described above. The risk
results indicate that both the actual and
allowable inhalation cancer risks to the
individual most exposed are well below
100-in-1 million, which is the
presumptive limit of acceptability. Also,
the highest chronic noncancer TOSHI,
and the highest acute noncancer HQ, are
well below 1, indicating low likelihood
of adverse noncancer effects from
inhalation exposures. There are also low
risks associated with ingestion, with the
highest cancer risk being less than 50in-1 million based on a conservative
screening assessment, and the highest
noncancer hazard being less than 1
based on a site-specific multipathway
assessment.
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Considering all of the health risk
information and factors discussed
above, including the uncertainties
discussed in section V of this preamble,
the EPA proposes that the risks are
acceptable for this source category.
2. Ample Margin of Safety Analysis
As directed by CAA section 112(f)(2),
we conducted an analysis to determine
if the current emissions standards
provide an ample margin of safety to
protect public health. Under the ample
margin of safety analysis, the EPA
considers all health factors evaluated in
the risk assessment and evaluates the
cost and feasibility of available control
technologies and other measures
(including the controls, measures, and
costs reviewed under the technology
review) that could be applied to this
source category to further reduce the
risks (or potential risks) due to
emissions of HAP identified in our risk
assessment. In this analysis, we
considered the results of the technology
review, risk assessment, and other
aspects of our MACT rule review to
determine whether there are any costeffective controls or other measures that
would reduce emissions further to
provide an ample margin of safety with
respect to the risks associated with these
emissions.
Our risk analysis indicated the risks
from the source category are low for
both cancer and noncancer health
effects, and, therefore, any risk
reductions from further available
control options would result in minimal
health benefits. Moreover, as noted in
our discussion of the technology review
in section VI.C of this preamble, no
additional measures were identified for
reducing HAP emissions from affected
sources in the Coal- and Oil-Fired EGU
source category. Thus, we are proposing
that the current MATS requirements
provide an ample margin of safety to
protect public health.
3. Adverse Environmental Effects
Based on the results of our
environmental risk screening
assessment, we conclude that there is
not an adverse environmental effect
from the Coal- and Oil-Fired EGU
source category. We are proposing that
it is not necessary to set a more stringent
standard to prevent, taking into
consideration costs, energy, safety, and
other relevant factors, an adverse
environmental effect.
C. What are the results and proposed
decisions based on our technology
review?
As described in section V.B of this
preamble, our technology review
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focused on identifying developments in
practices, processes, and control
technologies that have occurred since
the MATS rule was promulgated.
Control technologies typically used to
minimize emissions of pollutants that
have numeric emission limits under the
MATS rule include electrostatic
precipitators and fabric filters for
control of PM and non-Hg HAP metals;
wet scrubbers and dry scrubbers for
control of acid gases (SO2, HCl, and HF);
and activated carbon injection for
control of Hg. The existing air pollution
control technologies that are currently
in use are well-established and provide
the capture efficiencies necessary for
compliance with the MATS emission
limits. Based on the effectiveness and
proven reliability of these control
technologies, and the relatively short
period of time since the promulgation of
the MATS rule, no developments in
practices, processes, or control
technologies, nor any new technologies
or practices were identified for the
control of non-Hg HAP metals, acid gas
HAP, or Hg. Organic HAP, including
emissions of dioxins and furans, are
regulated by a work practice standard
that requires periodic burner tune-ups
to ensure good combustion. This work
practice continues to be a practical
approach to ensuring that combustion
equipment is maintained and optimized
to run to reduce emissions of organic
HAP, and continues to be expected to be
more effective than establishing a
numeric standard that cannot reliably be
measured or monitored. Based on the
effectiveness and proven reliability of
the work practice standard, and the
relatively short amount of time since the
promulgation of the MATS rule, no
developments in work practices nor any
new work practices or operational
procedures have been identified for this
source category regarding the additional
control of organic HAP. Consequently,
we propose that no revisions to the
MATS rule are necessary pursuant to
CAA section 112(d)(6). Additional
details of our technology review can be
found in the memorandum, Technology
Review for the Coal- and Oil-fired EGU
Source Category, which is available in
the docket for this action.
VII. Consideration of Separate
Subcategory and Acid Gas Standard for
Existing EGUs That Fire Eastern
Bituminous Coal Refuse
The EPA is considering establishing a
subcategory for emissions of acid gas
HAP from existing EGUs firing eastern
bituminous coal refuse. In this action,
the EPA is soliciting comment on
whether establishment of such a
subcategory is needed (Comment C–11)
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and on the acid gas HAP emission
standards that would be established if
we create this subcategory (Comment C–
12).
A. Background
In the MATS rule proposal, the EPA
proposed a single acid gas emission
standard for all coal-fired power
plants—using HCl as a surrogate for all
acidic gas HAP. See 76 FR 24976, May
3, 2011. The EPA also proposed an
alternative emission standard for SO2 as
a surrogate for the acid gas HAP. SO2 is
also an acidic gas—though not a HAP—
and the controls used for SO2 emission
reduction are also effective for control of
the acid gas HAP. Further, most, if not
all, affected EGUs were already
measuring and reporting SO2 emissions
as a requirement of the Acid Rain
Program.
The Appalachian Region Independent
Power Producers Association
(ARIPPA) 48 submitted comments on the
MATS proposal arguing that the
characteristics of coal refuse made
achievement of the standard too costly
for its members and requested that the
EPA create a subcategory for facilities
burning coal refuse. The EPA
determined that there was no basis to
create such a subcategory and finalized
emission standards for both HCl and
SO2 that apply to all coal-fired EGUs.
See 77 FR 9304, February 16, 2012.
ARIPPA, along with other petitioners,
challenged the EPA’s determination in
the D.C. Circuit, and the Court upheld
the final rule. White Stallion, 748 F.3d
at 1249–50.
In addition to challenging the final
rule, ARIPPA also petitioned the
Agency for reconsideration, again
requesting a subcategory for the acid gas
standards for facilities combusting all
types of coal refuse. The EPA denied the
petition for reconsideration on grounds
that ARIPPA had adequate opportunity
to comment on the ability of coal refusecombusting facilities to comply with the
final standard. Furthermore, the EPA
determined that the ARIPPA petition
did not present any new information to
support a change in the previous
determination regarding the
appropriateness of a subcategory for the
acid gas HAP standard. ARIPPA
subsequently sought judicial review of
the denial of the petition for
reconsideration. ARIPPA v. EPA, No.
15–1180 (D.C. Cir.).49 In petitioner’s
briefs, ARIPPA claimed that the EPA
had misunderstood its reconsideration
petition and pointed to a distinction
between the control of acid gas
emissions from units burning anthracite
refuse and those burning bituminous
coal refuse. See Industry Pets. Br. at 35–
36, ARIPPA, No. 15–1180 (D.C. Cir. filed
Dec. 6, 2016). The EPA disagrees with
the assertion that the Agency
misunderstood the basis for ARIPPA’s
reconsideration petition as we could not
find a single statement in the
rulemaking record that clearly or even
vaguely requested a separate acid gas
HAP limit based on the distinction
between anthracite refuse and
bituminous coal refuse. Nonetheless, the
Agency recognizes that there are
differences in anthracite and
bituminous coal (and, thus, between
anthracite refuse and bituminous coal
refuse) and that those differences can
influence the acid gas HAP emissions
from EGUs firing those respective fuels.
Those differences may also impact the
unit’s ability to control those emissions.
B. Basis for Consideration of a
Subcategory
1. Differences Between Anthracite
Refuse and Eastern Bituminous Coal
Refuse
Anthracite (or ‘‘hard coal’’) is the
highest quality coal as it contains more
2701
carbon and fewer impurities—including
sulfur and chlorine—than lower ranks
of coal such as bituminous coal, subbituminous coal, and lignite. Anthracite
is rarely used in utility power plants,
but anthracite refuse is used by a small
number of EGUs located in
Pennsylvania. Bituminous coal is a
middle rank coal between
subbituminous coal and anthracite.
Bituminous coal typically has a high
heating value and is commonly used in
electricity generation in the United
States. Bituminous coal is mined in the
Appalachian region (northern Alabama
through Pennsylvania), the Interior
Region (primarily Illinois basin), and
the Western Region (a small amount of
bituminous coal mined primarily in
Colorado and Utah). The bituminous
coal in the Interior Region tends to have
the highest sulfur content, followed by
bituminous coals from the Appalachian
Region. Coals (of all types) mined in the
Western Region tend to have the lowest
sulfur and chlorine content—and the
highest content of free alkali (which can
act as a natural sorbent to neutralize
acid gases produced in the combustion
process). The EPA is aware of currently
operational coal-refuse EGUs that are
firing anthracite refuse (10 units),
subbituminous coal refuse (1 unit),
western bituminous coal refuse (1 unit),
and eastern bituminous coal refuse (12
units).
The existing eastern bituminous coal
refuse-fired EGUs that are currently in
operation are listed below in Table 7
(excluding Seward, as discussed later).
The table also lists the units’ net
summer capacity.
TABLE 7—EASTERN BITUMINOUS COAL REFUSE-FIRED EGUS IN CURRENT OPERATION *
ORIS Plant code
10143
10151
10151
10603
10641
10641
10743
10743
50974
50974
................
................
................
................
................
................
................
................
................
................
Plant
State
Colver Power Project ..............................................................................................................................
Grant Town Power Plant Unit 1A ...........................................................................................................
Grant Town Power Plant Unit 1B ...........................................................................................................
Ebensburg Power ....................................................................................................................................
Cambria Cogen Unit 1 ............................................................................................................................
Cambria Cogen Unit 2 ............................................................................................................................
Morgantown Energy Facility Unit 1 .........................................................................................................
Morgantown Energy Facility Unit 2 .........................................................................................................
Scrubgrass Generating Company LP Unit 1 ..........................................................................................
Scrubgrass Generating Company LP Unit 2 ..........................................................................................
PA
WV
WV
PA
PA
PA
WV
WV
PA
PA
Capacity
(MW)
110
40
40
50
44
44
25
25
42
42
* Excluding the Seward units (as explained later).
48 ARIPPA is a non-profit trade association
comprised of independent electric power
producers, environmental remediators, and service
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providers located in Pennsylvania and West
Virginia that use coal refuse as a primary fuel to
generate electricity.
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49 ARIPPA’s petition for review is currently being
held in abeyance. ARIPPA v. EPA, No. 15–1180,
Order, No. 1672985 (April 27, 2017).
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2. Control Technologies for Acid Gas
HAP
All coal refuse fuels are fired in
fluidized bed combustors (FBC) that use
limestone injection to minimize SO2
emissions and to increase heat transfer
efficiency. This limestone injection
technology may be adequate for EGUs
that are firing anthracite refuse,
subbituminous, and western bituminous
coal refuse to meet the MATS
alternative (surrogate) emission
standard for SO2 because, as previously
mentioned, the anthracite coals are
naturally much lower in impurities
(including sulfur and chlorine) and
western bituminous coals (and
subbituminous coals) have lower sulfur
and chlorine content and higher free
alkalinity. All anthracite coal refusefired and western bituminous coal
refuse-fired EGUs are currently emitting
SO2 at rates that are below the final
MATS emission standard for acid gas
HAP and the subbituminous coal refusefired EGU is currently emitting HCl at
a rate that is below the final MATS
emission standard for acid gas HAP.
Therefore, there is no need to consider
a subcategory that would include those
units. No anthracite coal refuse-fired or
western bituminous coal refuse-fired
EGUs are currently reporting HCl
emissions for compliance purposes;
they are all opting to, instead, report the
alternative standard for SO2.
However, ARIPPA has argued that, for
the eastern bituminous coal refuse-fired
EGUs, limestone injection alone is not
adequate to meet the final HCl or SO2
MATS emission standards. Operators
cannot simply continue to inject more
limestone to the combustor as that could
negatively affect the operation of the
combustor with limited impact on acid
gas emissions.50 For this reason,
bituminous coal refuse-fired EGUs are
required to install some sort of
downstream acid gas control technology
in order to meet the final acid gas MATS
standards. These downstream control
devices could include wet FGD
scrubbers, spray dryer absorbers (SDA),
or dry sorbent injection (DSI) systems.
Available information suggests that
wet FGD scrubbers and SDA systems
would be particularly expensive retrofit
control options for the small units that
are currently firing eastern bituminous
coal refuse. The cost effectiveness—i.e.,
the cost per incremental ton acid gas
HAP reduced—may be excessive and
50 ‘‘[I]ncreased limestone injection consistent
with current design and operational constraints
cannot further reduce HCl emissions . . . to levels
consistent with the Utility MACT limit.’’ See
ARIPPA Petition for Reconsideration, p. 5, See also
p. 10, Docket ID No. EPA–HQ–OAR–2009–0234–
20175.
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may be technically and practically
infeasible for these units. The EPA
solicits comment on whether these
controls are particularly costly for these
units to adopt (Comment C–13).
The eastern bituminous coal refusefired EGUs can also consider
installation of DSI technology, which is
a less costly control option. A DSI
system is used to inject powdered
alkaline sorbent (typically sodium- or
calcium-based sorbents) into the flue gas
stream. The alkaline sorbents neutralize
acidic gases and the resulting solids are
captured in a downstream PM control
device (e.g., a fabric filter). DSI has been
identified as a relatively low-cost
technology for control of acid gases.
Some commenters to the original MATS
proposal stated that DSI will not work
on units firing bituminous coals. Some
commenters stated that DSI is only
suitable for use on low-sulfur, lowchlorine western coals. In fact, in power
sector modeling using the Integrated
Planning Model (IPM) to support the
development of MATS, the EPA
restricted the availability of the DSI
option to only those units that use or
switch to relatively low-sulfur coal (up
to 2 lb/MMBtu SO2).51 Some eastern
bituminous coal refuse-fired EGUs have
tested DSI systems and have identified
the following problems that make the
technology infeasible. The use of
sodium-based sorbents negatively
impacts the usability, and, thus,
saleability, of the captured fly ash
which can be utilized in many useful
ways. One beneficial use includes using
fly ash in mine reclamation activities.
The increased sodium loading from the
injection of sodium-based sorbents can
increase the leachability and mobility of
metals from the fly ash.52 Therefore, the
saleability of the fly ash may be affected
by the use of DSI. When both calciumbased and sodium-based sorbents were
injected in testing, the emissions of Hg
increased considerably (well above the
final MATS emission standard for Hg).
This is due to the alkaline sorbents
scavenging free halides from the flue gas
stream—which effectively helps to
control acid gas emissions. However,
the free halides are also helpful in
oxidizing elemental Hg so that it can be
captured in a downstream PM control
device. All coal refuse-fired EGUs are
emitting at levels that are below the
final MATS standard for Hg (and also
with the standard for filterable PM). In
fact, FBC units—including those firing
coal refuse—are among the best
51 See
77 FR 9412.
ARIPPA comments on EPA’s Proposed
Supplemental Finding, available at Docket ID No.
EPA–HQ–OAR–2009–0234–20530.
52 See
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performers for Hg control.53 Therefore,
use of DSI technology for acid gas
control (if feasible), would likely also
require the installation of Hg-specific
control technology. The EPA is
soliciting comment on the technical
feasibility of installing DSI, dry FGD, or
other applicable control technologies at
these units and whether the installation
of acid gas HAP controls may create
technical infeasibilities in meeting other
MATS emission limits (Comment C–14).
Further, most of the existing eastern
bituminous coal refuse-fired EGUs are
small (most are less than 100 MW) and
may be constrained by space or other
configurational limitations. However,
there are two eastern bituminous coal
refuse-fired EGUs at the Seward
Generating Station in Pennsylvania that
the EPA would not consider for
inclusion in a potential subcategory.
The Seward units are the newest and, at
260 MW each, are by far the largest
EGUs that are firing coal refuse. The
Seward units were constructed with
installed downstream acid gas controls
that were part of the original design.
The Seward facility, therefore, did not
suffer from space and other
configurational limitations that can
affect other smaller existing eastern
bituminous coal refuse-fired EGUs that
are attempting to retrofit air pollution
controls. Further, the Seward units were
among the best performing units—with
respect to HCl emissions—when the
EPA developed the final MATS
emission standards. And, MATS
compliance reports submitted by the
Seward EGUs show that the units’ HCl
emissions are well below the final
MATS standard of 0.0020 lb/MMBtu.
The EPA has incomplete information
on the emissions controls that are
installed at the currently operating
eastern bituminous coal refuse-fired
EGUs (i.e., those identified earlier in
Table 7). The EPA solicits information
on installed controls at those units, the
types and amount of sorbents or
reagents (if any) that are used, and, if
present, the extent of the operation of
these emissions controls (Comment C–
15). The EPA also solicits comment on
the cost of retrofitting DSI, dry FGD, or
other applicable control technologies
such that eastern bituminous coal
refuse-fired EGUs are able to emit at or
below the MATS standard for HCl or
SO2 (Comment C–16). To better
understand the economic characteristics
of the eastern bituminous coal refusefired EGUs, the EPA additionally
solicits information on the operating
costs of these units, availability and cost
53 Ibid.
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of their fuel supplies, and any planned
retirements (Comment C–17).
C. Potential Subcategory Emission
Standards
As mentioned, the EPA is considering
establishing acid gas emission standards
for a subcategory of existing EGUs that
fire eastern bituminous coal refuse; and
we are soliciting comment on the need
for such a standard (Comment C–18).
The EPA has conducted an analysis to
determine what such a numerical
emission standard would be. The
analysis is summarized in a separate
memorandum available in the
rulemaking docket.54 The results of that
MACT floor analysis are shown below
in Table 8. After the EPA establishes the
MACT floor, it considers the costs and
non-air quality health and
environmental impacts and energy
requirements to determine whether a
more stringent, or ‘‘beyond-the-floor,’’
level of control should be established.
The average SO2 lb/MMBtu emission
rate was determined for each currently
operating eastern bituminous coal
refuse-fired EGU using monthly SO2
data available in the EPA’s ECMPS for
the period of January 2015 through June
2018. If the EPA were to establish a
beyond-the-floor SO2 emissions limit, it
would likely be in the range of 0.60—
0.70 lb/MMBtu; a limit that, on average,
the currently operating eastern
bituminous coal refuse-fired EGUs have
achieved based on their monthly
emissions data for January 2015 through
June 2018. Because no HCl emissions
data have been submitted for the
currently operating EGUs, and SO2 lb/
MWh emissions data are available for
only two of the EGUs, we could not use
this same beyond-the-floor methodology
to evaluate beyond-the-floor standards
for SO2 in lb/MWh or for HCl in either
lb/MMBtu or lb/MWh. We, therefore,
determined that the beyond-the-floor
standards for those pollutants should
reasonably be set based on the same
percentage reduction as the SO2 lb/
MMBtu described above (i.e., the 40percent reduction in the emissions rate
for SO2 between the MACT floor value
of 1.0 lb/MMBtu and the beyond-thefloor value of 0.60 lb/MMBtu). The
results of the MACT floor and the
beyond-the-floor analyses are shown
below in Table 8.
TABLE 8—MACT FLOOR RESULTS FOR POTENTIAL EASTERN BITUMINOUS COAL REFUSE-FIRED EGUS SUBCATEGORY
Parameter
HCl
SO2
Number in MACT floor
5
5
Subcategory
Existing Eastern Bituminous Coal Refuse-Fired
EGUs.
The EPA solicits comment on these
analyses and the methodology presented
in the accompanying memorandum
(Comment C–19).55 Additionally, the
EPA solicits comment on the
appropriate definition of an eastern
bituminous coal refuse-fired EGU
(Comment C–20). Specifically, the EPA
is seeking comment on the amount of
eastern bituminous coal refuse that an
EGU must fire to be an eastern
bituminous coal refuse-fired EGU (e.g.,
must the EGU fire 100 percent of the
fuel or should it be allowed to co-fire
some small amount of another fuel if
needed?) (Comment C–21). The EPA
also solicits comment on distinctions in
smaller FBC units as compared to larger
FBC units (e.g., those less than 150 MW
as compared to those greater than 150
MW in capacity) that fire eastern
bituminous coal refuse (Comment C–
22). The EPA further solicits comment
on potential effects of establishing an
acid gas HAP emission standard for a
subcategory of small EGUs burning
eastern bituminous coal refuse
(Comment C–23).
99% UPL of top 5 ..................................................
(i.e., MACT floor) ...................................................
Beyond-the-floor Standard ....................................
that are subject to the MATS rule. The
basis of our estimate of affected EGUs
and facilities are provided in the Risk
Modeling Dataset Memo, which is
available in the docket for this action.
Because the EPA is not proposing any
amendments to the MATS rule, there
would not be any cost, environmental,
or economic impacts as a result of this
proposed action.
IX. Request for Comments
VIII. Summary of Cost, Environmental,
and Economic Impacts
The EPA estimates that there are 713
existing EGUs located at 323 facilities
We solicit comments on this proposed
action. In addition to general comments
on this proposed action, we are also
interested in additional data that may
improve the risk assessments and other
analyses (Comment C–24). We are
specifically interested in receiving any
improvements to the data used in the
site-specific emissions profiles used for
risk modeling (Comment C–25). Such
data should include supporting
documentation in sufficient detail to
allow characterization of the quality and
representativeness of the data or
information. Section X of this preamble
provides more information on
submitting data. As described in section
VII of this preamble, we also solicit
comment on establishing a subcategory
and acid gas emission standards for
54 Memorandum titled NESHAP for Coal- and OilFired EGUs: MACT Floor Analysis and Beyond the
MACT Floor Analysis for Subcategory of Existing
Eastern Bituminous Coal Refuse-Fired EGUs Under
Consideration, available in Docket ID No. EPA–HQ–
OAR–2018–0794.
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0.060 lb/MMBtu
0.60 lb/MWh
0.040 lb/MMBtu
0.40 lb/MWh
1.0 lb/MMBtu
15 lb/MWh
0.6 lb/MMBtu
9 lb/MWh
existing eastern bituminous coal refusefired EGUs.
X. Submitting Data Corrections
The site-specific emissions profiles
used in the source category risk and
demographic analyses (including
instructions) are available for download
on the RTR website at https://
www3.epa.gov/ttn/atw/rrisk/rtrpg.html.
The data files include detailed
information for each HAP emissions
release point for the facilities in the
source category.
If you believe that the data are not
representative or are inaccurate, please
identify the data in question, provide
your reason for concern, and provide
any ‘‘improved’’ data that you have, if
available. When you submit data, we
request that you provide documentation
of the basis for the revised values to
support your suggested changes. To
submit comments on the data
downloaded from the RTR website,
complete the following steps:
1. Within this downloaded file, enter
suggested revisions to the data fields
appropriate for that information.
2. Fill in the commenter information
fields for each suggested revision (i.e.,
commenter name, commenter
organization, commenter email address,
55 Ibid.
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commenter phone number, and revision
comments).
3. Gather documentation for any
suggested emissions revisions (e.g.,
performance test reports, material
balance calculations).
4. Send the entire downloaded file
with suggested revisions in Microsoft®
Access format and all accompanying
documentation to Docket ID No. EPA–
HQ–OAR–2018–0794 (through the
method described in the ADDRESSES
section of this preamble).
5. If you are providing comments on
a single facility or multiple facilities,
you need only submit one file for all
facilities. The file should contain all
suggested changes for all sources at that
facility (or facilities). We request that all
data revision comments be submitted in
the form of updated Microsoft® Excel
files that are generated by the
Microsoft® Access file. These files are
provided on the RTR website at https://
www3.epa.gov/ttn/atw/rrisk/rtrpg.html.
XI. Statutory and Executive Order
Reviews
Additional information about these
statutes and Executive Orders can be
found at https://www.epa.gov/lawsregulations/laws-and-executive-orders.
PRA. OMB has previously approved the
information collection activities
contained in the existing regulations
and has assigned OMB control number
2060–0567. This action does not impose
an information collection burden
because the EPA is not proposing any
changes to the information collection
requirements.
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. This action will not
impose any requirements on small
entities. The EPA does not project any
potential costs or benefits associated
with this action.
E. Unfunded Mandates Reform Act
(UMRA)
This action does not contain an
unfunded mandate of $100 million or
more as described in UMRA, 2 U.S.C.
1531–1538, and does not significantly or
uniquely affect small governments. The
action imposes no enforceable duty on
any state, local, or tribal governments or
the private sector.
F. Executive Order 13132: Federalism
economically significant as defined in
Executive Order 12866, and because the
EPA does not believe the environmental
health or safety risks addressed by this
action present a disproportionate risk to
children. This action’s health and risk
assessments are contained in sections
V.A and C, and sections VI.A and B of
this preamble, and further documented
in the risk document, available in the
docket for this action.
I. Executive Order 13211: Actions
Concerning Regulations That
Significantly Affect Energy Supply,
Distribution, or Use
This action is not a ‘‘significant
energy action’’ because it is not likely to
have a significant adverse effect on the
supply, distribution, or use of energy.
This action is not anticipated to have
impacts on emissions, costs, or energy
supply decisions for the affected electric
utility industry.
J. National Technology Transfer and
Advancement Act (NTTAA)
This action does not involve technical
standards.
K. Executive Order 12898: Federal
Actions To Address Environmental
Justice in Minority Populations and
Low-Income Populations
A. Executive Order 12866: Regulatory
Planning and Review and Executive
Order 13563: Improving Regulation and
Regulatory Review
This action is a significant regulatory
action that was submitted to OMB for
review. Any changes made in response
to OMB recommendations have been
documented in the docket. The EPA
does not project any potential costs or
benefits associated with this action.
This action does not have federalism
implications. It will not have substantial
direct effects 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.
B. Executive Order 13771: Reducing
Regulation and Controlling Regulatory
Costs
This action is expected to be an
Executive Order 13771 regulatory
action. There are no quantified cost
estimates for this proposed rule because
this proposed rule is not expected to
result in any changes in costs.
This action does not have tribal
implications as specified in Executive
Order 13175. It would neither impose
substantial direct compliance costs on
tribal governments, nor preempt Tribal
law. Thus, Executive Order 13175 does
not apply to this action.
The EPA believes that this action does
not have disproportionately high and
adverse human health or environmental
effects on minority populations, lowincome populations, and/or indigenous
peoples, as specified in Executive Order
12898 (59 FR 7629, February 16, 1994).
The documentation for this decision is
contained in section VI.A of this
preamble and the technical report, Risk
and Technology Review—Analysis of
Demographic Factors for Populations
Living Near Coal- and Oil-Fired EGUs,
available in the docket for this action.
H. Executive Order 13045: Protection of
Children From Environmental Health
Risks and Safety Risks
Dated: December 27, 2018.
Andrew R. Wheeler,
Acting Administrator.
This action is not subject to Executive
Order 13045 because it is not
[FR Doc. 2019–00936 Filed 2–6–19; 8:45 am]
C. Paperwork Reduction Act (PRA)
This action does not impose any new
information collection burden under the
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G. Executive Order 13175: Consultation
and Coordination With Indian Tribal
Governments
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Agencies
[Federal Register Volume 84, Number 26 (Thursday, February 7, 2019)]
[Proposed Rules]
[Pages 2670-2704]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-00936]
[[Page 2669]]
Vol. 84
Thursday,
No. 26
February 7, 2019
Part II
Environmental Protection Agency
-----------------------------------------------------------------------
40 CFR Part 63
National Emission Standards for Hazardous Air Pollutants: Coal- and
Oil-Fired Electric Utility Steam Generating Units--Reconsideration of
Supplemental Finding and Residual Risk and Technology Review; Proposed
Rule
Federal Register / Vol. 84 , No. 26 / Thursday, February 7, 2019 /
Proposed Rules
[[Page 2670]]
-----------------------------------------------------------------------
ENVIRONMENTAL PROTECTION AGENCY
40 CFR Part 63
[EPA-HQ-OAR-2018-0794; FRL-9988-93-OAR]
RIN 2060-AT99
National Emission Standards for Hazardous Air Pollutants: Coal-
and Oil-Fired Electric Utility Steam Generating Units--Reconsideration
of Supplemental Finding and Residual Risk and Technology Review
AGENCY: Environmental Protection Agency (EPA).
ACTION: Proposed rule.
-----------------------------------------------------------------------
SUMMARY: The Environmental Protection Agency (EPA) is proposing a
revision to its response to the U.S. Supreme Court decision in Michigan
v. EPA which held that the EPA erred by not considering cost in its
determination that regulation under section 112 of the Clean Air Act
(CAA) of hazardous air pollutant (HAP) emissions from coal- and oil-
fired electric utility steam generating units (EGUs) is appropriate and
necessary. After considering the cost of compliance relative to the HAP
benefits of regulation, the EPA proposes to find that it is not
``appropriate and necessary'' to regulate HAP emissions from coal- and
oil-fired EGUs, thereby reversing the Agency's prior conclusion under
CAA section 112(n)(1)(A) and correcting flaws in the Agency's prior
response to Michigan v. EPA. We further propose that finalizing this
new response to Michigan v. EPA will not remove the Coal- and Oil-Fired
EGU source category from the CAA section 112(c) list of sources that
must be regulated under CAA section 112(d) and will not affect the
existing CAA section 112(d) emissions standards that regulate HAP
emissions from coal- and oil-fired EGUs. We are soliciting comment,
however, on whether the EPA has the authority or obligation to delist
EGUs from CAA section 112(c) and rescind (or to rescind without
delisting) the National Emission Standards for Hazardous Air Pollutants
(NESHAP) for Coal- and Oil-Fired EGUs, commonly known as the Mercury
and Air Toxics Standards (MATS). The EPA is also proposing the results
of the residual risk and technology review (RTR) of the NESHAP that the
Agency is required to conduct in accordance with CAA section 112. The
results of the residual risk analysis indicate that residual risks due
to emissions of air toxics from this source category are acceptable and
that the current standards provide an ample margin of safety to protect
public health. No new developments in HAP emission controls to achieve
further cost-effective emissions reductions were identified under the
technology review. Therefore, based on the results of these analyses
and reviews, we are proposing that no revisions to MATS are warranted.
Finally, the EPA is also taking comment on establishing a subcategory
for emissions of acid gas HAP from existing EGUs firing eastern
bituminous coal refuse.
DATES: Comments. Comments must be received on or before April 8, 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 March 25, 2019.
Public Hearing. The EPA is planning to hold at least one public
hearing in response to this proposed action. Information about the
hearing, including location, date, and time, along with instructions on
how to register to speak at the hearing, will be published in a second
Federal Register document.
ADDRESSES: Comments. Submit your comments, identified by Docket ID No.
EPA-HQ-OAR-2018-0794, at https://www.regulations.gov. Follow the online
instructions for submitting comments. Once submitted, comments cannot
be edited or removed from Regulations.gov. See SUPPLEMENTARY
INFORMATION for detail about how the EPA treats submitted comments.
Regulations.gov is our preferred method of receiving comments. However,
the following other submission methods are also accepted:
Email: a-and-r-docket@epa.gov. Include Docket ID No. EPA-
HQ-OAR-2018-0794 in the subject line of the message.
Fax: (202) 566-9744. Attention Docket ID No. EPA-HQ-OAR-
2018-0794.
Mail: To ship or send mail via the United States Postal
Service, use the following address: U.S. Environmental Protection
Agency, EPA Docket Center, Docket ID No. EPA-HQ-OAR-2018-0794, Mail
Code 28221T, 1200 Pennsylvania Avenue NW, Washington, DC 20460.
Hand/Courier Delivery: Use the following Docket Center
address if you are using express mail, commercial delivery, hand
delivery, or courier: EPA Docket Center, EPA WJC West Building, Room
3334, 1301 Constitution Avenue NW, Washington, DC 20004. Delivery
verification signatures will be available only during regular business
hours.
FOR FURTHER INFORMATION CONTACT: For questions about this proposed
action, contact Mary Johnson, Sector Policies and Programs Division
(D243-01), Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina
27711; telephone number: (919) 541-5025; fax number: (919) 541-4991;
and email address: johnson.mary@epa.gov or Nick Hutson, Sector Policies
and Programs Division (D243-01), Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina 27711; telephone number: (919) 541-2968; fax
number: (919) 541-4991; and email address: hutson.nick@epa.gov. For
specific information regarding the risk modeling methodology, contact
Mark Morris, Health and Environmental Impacts Division (C539-02),
Office of Air Quality Planning and Standards, U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina 27711;
telephone number: (919) 541-5416; and email address:
morris.mark@epa.gov. For information about the applicability of the
NESHAP to a particular entity, contact Sara Ayres, Office of
Enforcement and Compliance Assurance, U.S. Environmental Protection
Agency, U.S. EPA Region 5 (E-19J), 77 West Jackson Boulevard, Chicago,
Illinois 60604; telephone number: (312) 353-6266; and email address:
ayres.sara@epa.gov.
SUPPLEMENTARY INFORMATION:
Docket. The EPA has established a docket for this rulemaking under
Docket ID No. EPA-HQ-OAR-2018-0794. All documents in the docket are
listed in Regulations.gov. Although listed, some information is not
publicly available, e.g., CBI (Confidential Business Information) or
other information whose disclosure is restricted by statute. Certain
other material, such as copyrighted material, is not placed on the
internet and will be publicly available only in hard copy. Publicly
available docket materials are available either electronically in
Regulations.gov or in hard copy at the EPA Docket Center, Room 3334,
EPA WJC West Building, 1301 Constitution Avenue NW, Washington, DC. The
Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through
Friday, excluding legal holidays. The telephone number for the Public
Reading Room is (202) 566-1744, and the telephone number for the EPA
Docket Center is (202) 566-1742.
Instructions. Direct your comments to Docket ID No. EPA-HQ-OAR-
2018-0794. The EPA's policy is that all
[[Page 2671]]
comments received will be included in the public docket without change
and may be made available online at https://www.regulations.gov,
including any personal information provided, unless the comment
includes information claimed to be CBI or other information whose
disclosure is restricted by statute. Do not submit information that you
consider to be CBI or otherwise protected through https://www.regulations.gov or email. This type of information should be
submitted by mail as discussed below.
The EPA may publish any comment received to its public docket.
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 https://www.epa.gov/dockets/commenting-epa-dockets.
The https://www.regulations.gov website allows you to submit your
comment anonymously, which means the EPA will not know your identity or
contact information unless you provide it in the body of your comment.
If you send an email comment directly to the EPA without going through
https://www.regulations.gov, your email address will be automatically
captured and included as part of the comment that is placed in the
public docket and made available on the internet. If you submit an
electronic comment, the EPA recommends that you include your name and
other contact information in the body of your comment and with any
digital storage media you submit. If the EPA cannot read your comment
due to technical difficulties and cannot contact you for clarification,
the EPA may not be able to consider your comment. Electronic files
should not include special characters or any form of encryption and be
free of any defects or viruses. For additional information about the
EPA's public docket, visit the EPA Docket Center homepage at https://www.epa.gov/dockets.
The EPA is soliciting comment on numerous aspects of the proposed
rule. The EPA has indexed each comment solicitation with an alpha-
numeric identifier (e.g., ``C-1,'' ``C-2,'' ''C-3'') to provide a
consistent framework for effective and efficient provision of comments.
Accordingly, the EPA asks that commenters include the corresponding
identifier when providing comments relevant to that comment
solicitation. The EPA asks that commenters include the identifier in
either a heading, or within the text of each comment (e.g., ``In
response to solicitation of comment C-1, . . .'') to make clear which
comment solicitation is being addressed. The EPA emphasizes that the
Agency is not limiting comment to these identified areas and encourages
provision of any other comments relevant to this proposal.
Submitting CBI. Do not submit information containing CBI to the EPA
through https://www.regulations.gov or email. Clearly mark the part or
all of the information that you claim to be CBI. For CBI information on
any digital storage media that you mail to the EPA, mark the outside of
the digital storage media as CBI and then identify electronically
within the digital storage media the specific information that is
claimed as CBI. In addition to one complete version of the comments
that includes information claimed as CBI, you must submit a copy of the
comments that does not contain the information claimed as CBI directly
to the public docket through the procedures outlined in Instructions
above. If you submit any digital storage media that does not contain
CBI, mark the outside of the digital storage media clearly that it does
not contain CBI. Information not marked as CBI will be included in the
public docket and the EPA's electronic public docket without prior
notice. Information marked as CBI will not be disclosed except in
accordance with procedures set forth in 40 Code of Federal Regulations
(CFR) part 2. Send or deliver information identified as CBI only to the
following address: OAQPS Document Control Officer (C404-02), OAQPS,
U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina 27711, Attention Docket ID No. EPA-HQ-OAR-2018-0794.
Preamble Acronyms and Abbreviations. We use multiple acronyms and
terms in this preamble. While this list may not be exhaustive, to ease
the reading of this preamble and for reference purposes, the EPA
defines the following terms and acronyms here:
AEGL acute exposure guideline level
AERMOD air dispersion model used by the HEM-3 model
ATSDR Agency for Toxic Substances and Disease Registry
CAA Clean Air Act
CalEPA California EPA
CAMR Clean Air Mercury Rule
CBI Confidential Business Information
CEMS continuous emissions monitoring systems
CFR Code of Federal Regulations
CPMS continuous parameter monitoring system
ECMPS Emissions Collection and Monitoring Plan System
EGU electric utility steam generating unit
EIA Energy Information Administration
EPA Environmental Protection Agency
EPRI Electric Power Research Institute
ERPG Emergency Response Planning Guideline
fPM filterable particulate matter
HAP hazardous air pollutant(s)
HCl hydrochloric acid
HEM-3 Human Exposure Model, Version 1.1.0
HF hydrogen fluoride
Hg mercury
HI hazard index
HQ hazard quotient
ICR information collection request
IGCC integrated gasification combined cycle
IRIS Integrated Risk Information System
km kilometer
lb/GWh pounds per gigawatt-hour
lb/MMBtu pounds per million British thermal units
lb/MWh pounds per megawatt-hour
lb/TBtu pounds per trillion British thermal units
MACT maximum achievable control technology
MATS Mercury and Air Toxics Standards
mg/m\3\ milligrams per cubic meter
MIR maximum individual risk
MMBtu million British thermal units
MMBtu/hr million British thermal units per hour
NAAQS National Ambient Air Quality Standards
NAICS North American Industry Classification System
NEEDS National Electric Energy Data System
NEI National Emissions Inventory
NESHAP national emission standards for hazardous air pollutants
NOX nitrogen oxides
NTTAA National Technology Transfer and Advancement Act
OAQPS Office of Air Quality Planning and Standards
OMB Office of Management and Budget
PB-HAP hazardous air pollutants known to be persistent and bio-
accumulative in the environment
PDF Portable Document Format
PM particulate matter
PM2.5 fine particulate matter
POM polycyclic organic matter
PRA Paperwork Reduction Act
RDL representative detection level
REL reference exposure level
RFA Regulatory Flexibility Act
RfC reference concentration
RfD reference dose
RIA regulatory impact analysis
RTR residual risk and technology review
SAB Science Advisory Board
SO2 sulfur dioxide
TOSHI target organ-specific hazard index
tpy tons per year
[[Page 2672]]
TRIM.FaTE Total Risk Integrated Methodology.Fate, Transport, and
Ecological Exposure model
UARG Utility Air Regulatory Group
UF uncertainty factor
[micro]g/m\3\ microgram per cubic meter
UMRA Unfunded Mandates Reform Act
URE unit risk estimate
USGS United States Geological Survey
Organization of this Document. The information in this preamble is
organized as follows:
I. General Information
A. Does this action apply to me?
B. Where can I get a copy of this document and other related
information?
II. Appropriate and Necessary Finding
A. Overview
B. Background
C. The EPA's Proposed Finding Under CAA Section 112(n)(1)(A)
D. Effects of This Proposed Replacement of the Supplemental
Finding
III. Criteria for Delisting a Source Category Under CAA Section
112(c)(9)
IV. Background on the RTR Action
A. What is the statutory authority for this action?
B. What is this source category and how does the current NESHAP
regulate its HAP emissions?
C. What data collection activities were conducted to support
this action?
D. What other relevant background information and data are
available?
V. RTR Analytical Procedures and Decision-Making
A. How do we consider risk in our decision-making?
B. How do we perform the technology review?
C. How do we estimate post-MACT risk posed by the source
category?
VI. RTR Analytical Results and Proposed Decisions
A. What are the results of the risk assessment and analyses?
B. What are our proposed decisions regarding risk acceptability,
ample margin of safety, and adverse environmental effect?
C. What are the results and proposed decisions based on our
technology review?
VII. Consideration of Separate Subcategory and Acid Gas Standard for
Existing EGUs That Fire Eastern Bituminous Coal Refuse
A. Background
B. Basis for Consideration of a Subcategory
C. Potential Subcategory Emission Standards
VIII. Summary of Cost, Environmental, and Economic Impacts
IX. Request for Comments
X. Submitting Data Corrections
XI. 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 Regulation and Controlling
Regulatory Costs
C. Paperwork Reduction Act (PRA)
D. Regulatory Flexibility Act (RFA)
E. Unfunded Mandates Reform Act (UMRA)
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 Risks and Safety Risks
I. Executive Order 13211: Actions Concerning Regulations That
Significantly Affect Energy Supply, Distribution, or Use
J. National Technology Transfer and Advancement Act (NTTAA)
K. Executive Order 12898: Federal Actions to Address
Environmental Justice in Minority Populations and Low-Income
Populations
I. General Information
A. Does this action apply to me?
Table 1 of this preamble lists the NESHAP and associated regulated
industrial source categories that are the subject of this proposal.
Table 1 is not intended to be exhaustive, but rather provides a guide
for readers regarding the entities that this proposed action is likely
to affect. The proposed standards, once promulgated, will be directly
applicable to the affected sources. Federal, state, local, and tribal
government entities that own and/or operate EGUs subject to 40 CFR part
63, subpart UUUUU would be affected by this proposed action. The Coal-
and Oil-Fired EGU source category was added to the list of categories
of major and area sources of HAP published under section 112(c) of the
CAA on December 20, 2000 (65 FR 79825). CAA section 112(a)(8) defines
an electric utility steam generating unit as: Any fossil fuel fired
combustion unit of more than 25 megawatts that serves a generator that
produces electricity for sale. A unit that cogenerates steam and
electricity and supplies more than one-third of its potential electric
output capacity and more than 25 megawatts electrical output to any
utility power distribution system for sale is also considered an EGU.
Table 1--NESHAP and Industrial Source Categories Affected by This Proposed Action
----------------------------------------------------------------------------------------------------------------
Source category NESHAP NAICS code \1\
----------------------------------------------------------------------------------------------------------------
Coal- and Oil-Fired EGUs............. 40 CFR part 63, subpart UUUUU 221112, 221122, 921150
----------------------------------------------------------------------------------------------------------------
\1\ North American Industry Classification System.
B. Where can I get a copy of this document and other related
information?
In addition to being available in the docket, an electronic copy of
this action is available on the internet. Following signature by the
EPA Administrator, the EPA will post a copy of this proposed action at
https://www.epa.gov/mats/regulatory-actions-final-mercury-and-air-toxics-standards-mats-power-plants. Following publication in the
Federal Register, the EPA will post the Federal Register version of the
proposal and key technical documents at this same website. Information
on the overall RTR program is available at https://www3.epa.gov/ttn/atw/rrisk/rtrpg.html.
II. Appropriate and Necessary Finding
A. Overview
The EPA proposes this revised action in response to the U.S.
Supreme Court decision in Michigan v. EPA, 135 S.Ct. 2699 (2015), which
held that the EPA erred by not considering cost in its determination
that regulation of HAP emissions from coal- and oil-fired EGUs is
appropriate and necessary under CAA section 112. In this action, after
considering the cost of compliance relative to the HAP benefits of
regulation, the EPA proposes to find that it is not ``appropriate and
necessary'' to regulate HAP emissions from coal- and oil-fired EGUs,
thereby reversing the Agency's conclusion under CAA section
112(n)(1)(A), first made in 2000 and later affirmed in 2012 and 2016.
This proposed response corrects flaws in the EPA's prior 2016 response
to Michigan (82 FR 24420) and, if finalized, would supplant that 2016
action. We also propose that finalizing this action will not remove the
Coal- and Oil-Fired EGU source category from the CAA section 112(c)(1)
list, nor will finalizing this action affect the existing CAA section
112(d) emissions standards promulgated in 2012 that regulate HAP
emissions from coal- and oil-fired EGUs, although this action requests
comment on that proposed conclusion and whether the EPA has the
authority or obligation to
[[Page 2673]]
delist the source category and rescind the standards, or to rescind the
standards without delisting (Comment C-1).
B. Background
In the 1990 Amendments to the CAA, Congress substantially modified
CAA section 112, the provision of the CAA addressing HAP. That
provision includes CAA section 112(b)(1), which sets forth a list of
187 identified HAP, and CAA sections 112(b)(2) and (3), which give the
EPA the authority to add or remove pollutants from the list. CAA
section 112(a)(1) and (2) also specify the two types of sources to be
addressed: Major sources and area sources. A major source is any
stationary source or group of stationary sources at a single location
and under common control that emits or has the potential to emit,
considering controls, 10 tons per year (tpy) or more of any HAP or 25
tpy or more of any combination of HAP. CAA section 112(a)(1). Any
stationary source of HAP that is not a major source is an area source.
CAA section 112(a)(2). All major source categories, besides EGUs, were
required to be included on a published list of sources subject to
regulation under CAA section 112, see CAA sections 112(a)(1) and
(c)(1), and area sources ``which the Administrator finds presents a
threat of adverse effects to human health or the environment (by such
sources individually or in the aggregate) warranting regulation under
this section'' were also required to be added to the list, see CAA
section 112(c)(3). The EPA was to promulgate emission standards under
CAA section 112(d) for those source categories on the list.
This general CAA section 112(c) process of listing and regulation
does not apply to EGUs. Instead, Congress enacted a special provision,
CAA section 112(n)(1)(A), which established a separate process by which
the EPA was to determine whether to regulate emissions of HAP from EGUs
under CAA section 112. CAA section 112(n)(1)(A) directs the EPA to
conduct a study to evaluate the hazards to public health that are
reasonably anticipated to occur as a result of the HAP emissions from
EGUs, after the imposition of other CAA provisions. The provision
directs that the EPA shall regulate EGUs under CAA section 112 if the
Administrator determines, after considering the results of the study,
that such regulation is ``appropriate and necessary.'' CAA section
112(n)(1)(A), therefore, sets a unique process by which the
Administrator is to determine whether to establish CAA section 112(d)
standards for EGUs. Moreover, the statute includes a separate
definition of ``EGU'' which does not distinguish between major and area
sources. CAA section 112(a)(8).
On December 20, 2000, the EPA determined, pursuant to CAA section
112(n)(1)(A), that it was appropriate and necessary to regulate coal-
and oil-fired EGUs under CAA section 112(d) and added such units to the
CAA section 112(c) List of Categories of Major and Area Sources. 65 FR
79825 (2000 Finding). The EPA reversed that finding in 2005, concluding
that it was neither appropriate nor necessary to regulate EGUs under
CAA section 112(n)(1)(A), and stating that the effect of its reversal
of the appropriate and necessary finding was removal of coal- and oil-
fired EGUs from the CAA section 112(c)(1) source category list. 70 FR
15994 (March 29, 2005) (2005 Delisting Rule). The EPA concurrently
issued the Clean Air Mercury Rule (CAMR), which regulated mercury (Hg)
from new and existing coal-fired EGUs under CAA sections 111(b) and
(d). The United States Court of Appeals for the District of Columbia
(DC) Circuit (the Court) vacated the EPA's 2005 Delisting Rule in New
Jersey v. EPA, 517 F.3d 574 (D.C. Cir. 2008). The Court ruled that the
fact that the EPA had reversed its prior appropriate and necessary
finding did not mean that the Agency could remove the Coal- and Oil-
Fired EGU source category from the CAA section 112(c)(1) list without
going through the generally applicable CAA section 112(c)(9) delisting
procedures. Id. Instead, the Court held that the Agency could only
remove EGUs from the CAA section 112(c)(1) list after finding that the
statutory criteria for delisting set forth in CAA section 112(c)(9) had
been met. Id. In addition, the Court also vacated CAMR in light of the
EPA's concession that it had no authority to regulate Hg from EGUs
under CAA section 111 so long as EGUs remained on the CAA section
112(c)(1) source category list. 517 F.3d 574 (D.C. Cir. 2008). (The
Court did not address the merits of CAMR under CAA section 111; its
vacatur was based solely on its holding that the delisting from CAA
section 112 was improper.)
On May 3, 2011, the EPA proposed to reaffirm the 2000 appropriate
and necessary finding and proposed NESHAP for coal- and oil-fired EGUs,
known as MATS. 76 FR 24976. The final MATS rule was subsequently issued
on February 16, 2012. 77 FR 9304. Industry, states, environmental
organizations, and public health organizations challenged many aspects
of both the re-affirmed appropriate and necessary finding and the final
MATS rule in the D.C. Circuit. The Court denied all challenges. White
Stallion Energy Center v. EPA, 748 F.3d 1222 (D.C. Cir. 2014). Some
industry and state petitioners sought further review of the final MATS
rule, and the U.S. Supreme Court granted certiorari to determine
whether the EPA erred when it concluded that it could properly make the
appropriate and necessary finding under CAA section 112(n)(1)(A)
without consideration of cost. On June 29, 2015, the Supreme Court
ruled that the EPA ``strayed far beyond [the] bounds'' of reasonable
interpretation when it determined cost was irrelevant to the
appropriate and necessary finding. Michigan v. EPA, 135 S Ct. 2699,
2707 (2015). Specifically, the Supreme Court held that cost was ``an
important aspect of the problem'' and that the Agency was required to
consider the cost of regulation before deciding whether it was
appropriate and necessary to impose that regulation on EGUs under CAA
section 112. Id. On remand from the Supreme Court, the D.C. Circuit
left MATS in effect while the Agency addressed the Michigan decision.
Order, White Stallion Energy Center v. EPA, No. 12-1100 (D.C. Cir. Dec.
15, 2015) (ECF No. 1588459).
On April 25, 2016, after public notice and comment,\1\ the EPA
finalized a supplemental finding (2016 Supplemental Finding) concluding
that its consideration of cost did not change its previous
determination that regulation of HAP emissions from coal- and oil-fired
EGUs is appropriate and necessary. 82 FR 24420. In the 2016
Supplemental Finding, the EPA considered costs under two alternative
approaches. Under the first approach, the EPA evaluated compliance
costs in comparison to the industry's historical annual revenues and
annual capital expenditures, and examined impacts of the rule on retail
electricity prices. The EPA concluded that because these costs were
within the range of historical variability, the cost of MATS was
reasonable. The EPA also found that the power sector could continue to
perform its primary function--the generation, transmission, and
distribution of reliable electricity at reasonable cost--after
imposition of the MATS rule. Based on the conclusion that the costs of
the rule were ``reasonable'' and considering the benefits of reducing
HAP that had been identified in earlier agency determinations, the
Agency affirmed the appropriate and necessary finding under CAA section
112(n)(1)(A).
---------------------------------------------------------------------------
\1\ 80 FR 75025 (December 1, 2015).
---------------------------------------------------------------------------
In the 2016 Supplemental Finding, the EPA also presented a second,
alternative and independent, approach
[[Page 2674]]
to considering cost. This approach considered the results of the formal
cost-benefit analysis that the Agency had previously performed for the
regulatory impact analysis (RIA) for the final MATS rule.\2\ That RIA
cost-benefit analysis accounted for the monetized and non-monetized
benefits of MATS, including HAP-related benefits that could not be
quantified or monetized, as well as the monetized co-benefits of
reducing pollutants other than HAP. The RIA analysis found that its
projection of these aggregated benefits ($37 to $90 billion each year)
exceeded the costs of compliance ($9.6 billion) by three to nine times.
The EPA, therefore, concluded that the RIA's cost-benefit analysis also
supported its affirmation of the prior appropriate and necessary
finding under CAA section 112(n)(1)(A). 82 FR 24420.
---------------------------------------------------------------------------
\2\ U.S. EPA. 2011. Regulatory Impact Analysis for the Final
Mercury and Air Toxics Standards. EPA-452/R-11-011. Available at
https://www3.epa.gov/ttn/ecas/docs/ria/utilities_ria_final-mats_2011-12.pdf. Docket ID No. EPA-HQ-OAR-2009-0234-20131.
---------------------------------------------------------------------------
A number of state and industry groups petitioned for review of the
2016 Supplemental Finding in the D.C. Circuit. Murray Energy Corp. v.
EPA, No. 16-1127 (D.C. Cir. filed April 25, 2016). In April 2017, given
its interest in reviewing the 2016 action, the EPA moved the Court to
continue oral argument and hold the case in abeyance in order to give
the new Administration an opportunity to undertake that review. The
Court granted the EPA's request for a continuance on April 27, 2017.
Order, Murray Energy Corp. v. EPA, No. 16-1127 (D.C. Cir. April 27,
2017) (ECF No. 1672987).
C. The EPA's Proposed Finding Under CAA Section 112(n)(1)(A)
In this action, the EPA proposes to conclude that the 2016
Supplemental Finding was flawed and that, after considering the cost of
compliance relative to the HAP benefits of MATS, it is not appropriate
and necessary to regulate coal- and oil-fired EGUs under section 112 of
the CAA. CAA section 112(n)(1)(A) requires the EPA to determine that
both the appropriate and the necessary prongs are met. Therefore, if
the EPA finds that either prong is not satisfied, it cannot make an
affirmative appropriate and necessary finding. Cf. 70 FR 16000. The
EPA's reexamination of its determination in this proposal focuses on
the first prong of that analysis: Whether regulation is
``appropriate,'' after consideration of the costs and benefits of such
regulation. The EPA has reexamined the cost analyses presented in the
2016 Supplemental Finding and proposes to determine that neither of the
Finding's approaches to considering cost satisfies the Agency's
obligation under CAA section 112(n)(1)(A) as interpreted by the Supreme
Court in Michigan. Instead, we use a different consideration of cost
for purposes of the appropriate and necessary finding, one that we
believe aligns with the purpose of CAA section 112(n)(1)(A) as set
forth in Michigan.\3\ We propose to directly compare the cost of
compliance with MATS with the benefits specifically associated with
reducing emissions of HAP as the primary inquiry in this finding, in
order to satisfy our duty to consider cost in the context of CAA
section 112(n)(1)(A).
---------------------------------------------------------------------------
\3\ Agencies have inherent authority to reconsider past
decisions and to revise, replace, or repeal a decision to the extent
permitted by law and supported by a reasoned explanation. FCC v. Fox
Television Stations, Inc., 556 U.S. 502, 515 (2009); Motor Vehicle
Mfrs. Ass'n v. State Farm Mutual Auto. Ins. Co., 463 U.S. 29, 42
(1983) (``State Farm''). The EPA's interpretations of the statutes
it administers are not ``carved in stone,'' but must be evaluated
``on a continuing basis,'' for example, ``in response to . . . a
change in administrations.'' Nat'l Cable & Telecomms. Ass'n v. Brand
X internet Servs., 545 U.S. 967, 981 (2005) (internal quotation
marks and citations omitted). An agency's reasoning can include a
change in policy on the basis that ``the agency believes it to be
better,'' even if a court might disagree. White Stallion, 748 F.3d
at 1235; see also Nat'l Ass'n of Home Builders v. EPA, 682 F.3d
1032, 1038 & 1043 (D.C. Cir. 2012) (a revised rulemaking based ``on
a reevaluation of which policy would be better in light of the
facts'' is ``well within an agency's discretion,'' and `` `[a]
change in administration brought about by the people casting their
votes is a perfectly reasonable basis for an executive agency's
reappraisal of the costs and benefits of its programs and
regulations' '') (quoting State Farm, 463 U.S. at 59 (Rehnquist, J.,
concurring in part and dissenting in part)). The CAA complements the
EPA's inherent authority to reconsider prior rulemakings by
providing the Agency with broad authority to prescribe regulations
as necessary to carry out the Administrator's authorized functions
under the statute. 42 U.S.C. 7601(a). This broad discretion can be
limited by Congress, however. In New Jersey v. EPA, the D.C. Circuit
held that a reversal of the appropriate and necessary finding would
not have the effect of removing Coal- and Oil-Fired EGUs from the
CAA section 112(c)(1) source category list because Congress
``unambiguously limit[ed] EPA's discretion'' by fashioning a
statutorily mandated avenue for removing source categories from the
list in CAA section 112(c)(9). 517 F.3d 574, 582-83. (D.C. Cir.
2008).
---------------------------------------------------------------------------
The EPA also proposes that, because a negative appropriate and
necessary finding cannot by itself remove a source category from the
CAA section 112(c) list, see New Jersey, 517 F.3d at 582, finalizing
this finding will neither remove the Coal- and Oil-Fired EGU source
category from the CAA section 112(c) list, nor will it alter or
eliminate the CAA section 112(d) emissions standards imposed by MATS.
The EPA solicits public comment on all aspects of this proposal, and
retains the discretion, as always, to make changes in response to those
comments prior to finalizing this rule or to decide not to finalize
some or all aspects of this proposal after considering public comments.
1. The 2016 Supplemental Finding Was an Improper Response to Michigan
v. EPA
a. The ``Cost Reasonableness'' Approach Does Not Satisfy the Agency's
Obligation Under CAA Section 112(n)(1)(A)
We propose to find that the Agency's 2016 Supplemental Finding
erred in its consideration of cost. Specifically, we find that what was
described in the 2016 Supplemental Finding as the preferred approach,
or ``cost reasonableness test,'' does not meet the statute's
requirements to fully consider costs, and was an unreasonable
interpretation of CAA section 112(n)(1)(A)'s mandate, as informed by
the Supreme Court's opinion in Michigan. In its 2016 Supplemental
Finding, the EPA developed a ``cost reasonableness test'' based on D.C.
Circuit opinions that had evaluated the Agency's consideration of cost
in the context of setting new source performance standards under
section 111 of the CAA. See Legal Memorandum Accompanying the Proposed
Supplemental Finding that it is Appropriate and Necessary to Regulate
Hazardous Air Pollutants from Coal- and Oil-Fired Electric Utility
Steam Generating Units (EGUs) (2015 Legal Memorandum). Because those
opinions interpreted CAA section 111 to only prohibit the Agency from
adopting standards for new sources whose cost would be ``exorbitant,''
Lignite Energy Council v. EPA, 198 F.3d 930, 933 (D.C. Cir. 1999),
``excessive,'' or ``unreasonable,'' Sierra Club v. Costle, 657 F.2d
298, 383 (D.C. Cir. 1981), we concluded that we could consider cost for
CAA section 112(n)(1)(A) by determining whether cost of compliance was
``reasonable''--in other words, whether the cost of regulation could be
absorbed by the power sector without negatively affecting the
industry's ability to continue performing its primary function. That
``cost reasonableness test'' compared compliance costs of MATS relative
to historical annual revenues and annual capital expenditures, and
evaluated the impacts of the rule on retail electricity prices. Because
we found that the costs of compliance with the rule across the entire
utility sector were within historical variability and would not shut
down the sector as a whole, the EPA
[[Page 2675]]
concluded that the cost of compliance with MATS was reasonable.
The Agency claimed that use of the ``cost reasonableness test'' for
its CAA section 112(n)(1)(A) appropriate and necessary finding was
supported by the ``overall statutory objectives of section 112,'' and
stated that ``cost was but one factor among many'' that the EPA must
consider. See Legal Memorandum at 20. We also interpreted CAA section
112(n)(1)(A) and Michigan not to require the EPA to assume that a
consideration of cost should predominate or take primary significance
to the subordination of other considerations, because of CAA section
112's overall concern with the nature of HAP emissions and populations
that might be particularly sensitive to harms associated with those
emissions. Id.
In this notice, we are proposing to find that the EPA did not
comply with its statutory duty to consider cost as part of the
appropriate and necessary finding in the 2016 Supplemental Finding. The
2016 Supplemental Finding repeatedly emphasized that the Michigan Court
did not hold that the CAA ``unambiguously required'' the EPA to perform
a formal cost-benefit analysis to satisfy CAA 112(n)(1)(A). 135 S. Ct.
at 2711. But, as discussed below, the 2016 Supplemental Finding, among
other flaws, ignored observations about the importance of the cost
consideration to the appropriate and necessary finding, as provided by
the Court in Michigan.
Contrary to the 2015 Legal Memorandum's suggestion that cost should
not ``trump'' or ``predominate'' other considerations, the Supreme
Court observed that ``[a]gencies have long treated cost as a centrally
relevant factor when deciding whether to regulate.'' Id. at 2707
(emphasis added). The Supreme Court rejected arguments that the general
goals of CAA section 112 make cost irrelevant to a CAA section
112(n)(1)(A) appropriate and necessary finding. As such, the EPA must
meaningfully consider cost when making this threshold finding. In
addition, the Supreme Court emphasized that CAA section 112(n)(1)(A)
reflects Congress's intent that the EPA treat EGUs differently from
other sources. Id. at 2710. The attempt made in the 2016 Supplemental
Finding to ``harmonize'' CAA section 112(n)(1)(A) with the remainder of
CAA section 112 is, therefore, not consistent with Congress's intent
and the Supreme Court's decision in Michigan v. EPA.
The 2016 Supplemental Finding's reliance on case law pertaining to
CAA section 111(b) new source rules was similarly misguided. The
methodologies that courts have approved for considering costs of
control technologies for new sources that have not yet been constructed
are not particularly informative in the context of EPA's deciding
whether it is appropriate to impose control requirements on sources
that are already operating. Costs of control technologies for new
sources are borne as each source is added to the fleet of existing
sources and are not imposed on the entire fleet of existing sources
within a period of a few years, as is required under CAA section 112.
Moreover, the case law cited by the 2015 Legal Memorandum is
distinguishable even without regard to the fact that different
statutory provisions (CAA section 111 versus 112) are at issue. For
example, in Lignite Council, the D.C. Circuit found that the ``new
standards will only modestly increase the cost of producing electricity
in newly constructed boilers.'' Lignite Energy Council v. United States
EPA, 198 F.3d at 933. Even in its flawed conclusion that the cost of
MATS was ``reasonable,'' the EPA did not go so far as to say that the
costs of that rule were in any way ``modest.''
The primary, fatal flaw of the 2016 Supplemental Finding's
``preferred approach'' was its disregard for the Michigan Court's
suggestion that, under CAA section 112(n)(1)(A), the Agency must
meaningfully consider cost within the context of a regulation's
benefits. The decision contemplated that a proper consideration of cost
would be relative to benefits. For example, the Court questioned
whether a regulation could be considered ``rational'' where there was a
gross imbalance between costs and benefits and stated that ``[n]o
regulation is ``appropriate'' if it does more harm than good.'' Id. The
Court also made numerous references to a direct comparison of the costs
of MATS with benefits from reducing emissions of HAP. For instance, the
Court pointed out that ``[t]he costs [of MATS] to power plants were
thus between 1,600 and 2,400 times as great as the quantifiable
benefits from reduced emissions of hazardous air pollutants.'' Id. at
2706. Although the decision established no bright-line rules, it
suggested that CAA section 112(n)(1)(A)'s requisite consideration of
cost would not be met if the cost analysis did not ``ensure cost-
effectiveness'' or ``prevent the imposition of costs far in excess of
benefits.'' Id. at 2710.
For these reasons, the 2016 Supplemental Finding's ``test'' of
whether an industry can bear the cost of regulation does not
demonstrate that the cost of MATS was ``reasonable'' under the
particular statutory context. More importantly, the metrics ``tested''
by the Agency in the 2016 Supplemental Finding are irrelevant to the
determination of whether it is ``appropriate and necessary'' to impose
that regulation. Each cost metric the Agency examined compared the cost
of MATS to other costs borne by the industry, but never in its
``preferred approach'' did the Agency make the statutorily mandated
assessment of whether the benefits garnered by the rule were worth it--
i.e., a direct comparison of costs and benefits. Because the ``cost
reasonableness test'' failed to consider cost in a meaningful way
relative to benefits, we, therefore, conclude that approach did not
adequately address the Supreme Court's instruction that a reasonable
regulation requires an agency to fully consider ``the advantages and
the disadvantages'' of a decision. See Michigan, 135 S. Ct. at 2707
(emphasis in original). Instead, we propose to reconsider cost using a
more direct comparison of benefits and costs to address the Supreme
Court's remand of the appropriate and necessary determination, as
described below. As noted below, final action on this proposal would
replace the 2016 Supplemental Finding.
b. The Cost-Benefit Approach in the 2016 Supplemental Finding's
Alternative Approach Improperly Considered Co-benefits From Non-HAP
Emissions Reductions
In the 2016 Supplemental Finding's alternative approach, the EPA
improperly made an independent finding under CAA section 112(n)(1)(A)
that was based on a formal benefit-cost analysis, which evaluates
whether a regulation will increase economic efficiency, to find that it
was appropriate and necessary to regulate EGUs under CAA section 112.
See 81 FR 24425.\4\ The formal benefit-cost analysis relied on
information reported in the RIA performed for the MATS rule. The
quantified benefits accounted for in the formal benefit-cost analysis
in the 2016 Supplemental Finding's alternative approach included both
HAP and non-HAP air quality benefits. In this action, we propose to
find that the EPA's equal reliance on the particulate matter (PM) air
quality co-benefits projected to occur as a result of the reductions in
HAP was flawed as the focus of CAA section
[[Page 2676]]
112(n)(1)(A) is HAP emissions reductions.
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\4\ We use the term ``formal benefit-cost analysis'' to refer to
an economic analysis that attempts to quantify all significant
consequences of an action in monetary terms in order to determine
whether an action increases economic efficiency. Assuming that all
consequences can be monetized, actions with positive net benefits
(i.e., benefits exceed costs) improve economic efficiency.
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The EPA developed an RIA for the 2012 final MATS rule pursuant to
Executive Orders 12866 and 13563 and other applicable statutes (e.g.,
the Regulatory Flexibility Act and the Unfunded Mandates Reform Act),
as informed by OMB guidance \5\ and the EPA's Economic Guidelines.\6\
The analyses the EPA conducted generated an estimate of the
quantifiable benefits of HAP reductions under the rule of $4 to $6
million annually.\7\ The EPA also analyzed the PM air quality co-
benefits of MATS and attributed these benefits to the rule. The RIA
included in its analysis a consideration of the co-benefit reductions
in the emissions of pollutants other than the HAP regulated by MATS,
such as nitrogen oxides (NOX) and sulfur dioxide
(SO2), which contribute to the formation of fine particulate
matter (PM2.5). Reductions of these NOX and
SO2 emissions result from installing control technologies
and implementing the compliance strategies necessary to reduce the HAP
emissions directly regulated by MATS. The EPA projected that the co-
benefits associated with reducing these non-HAP pollutants would be
substantial. Indeed, these projected co-benefits comprised the
overwhelming majority (approximately 99.9 percent) of the monetized
benefits of MATS reflected in the EPA's RIA ($36 billion to $89
billion). By comparison, compliance costs of the final MATS rule were
projected to be $9.6 billion in 2015, and $8.6 billion and $7.4 billion
in 2020 and 2030, respectively.\8\ These compliance costs are an
estimate of the increased expenditures in capital, fuel, and other
inputs by the entire power sector to comply with the EPA's
requirements, while continuing to provide a given level of electricity
demand. In the 2016 Supplemental Finding's alternative approach, to
satisfy the required consideration of cost when determining whether it
is appropriate and necessary to regulate under CAA section
112(n)(1)(A), the EPA compared these monetized costs to the monetized
benefits, along with unquantified and unmonetized effects, to conclude
that MATS would increase economic efficiency and, therefore, reaffirmed
its earlier finding that it was appropriate and necessary to regulate
EGUs.
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\5\ U.S. OMB. 2003. Circular A-4 Guidance to Federal Agencies on
Preparation of Regulatory Analysis. Available at https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf.
\6\ U.S. EPA. 2014. Guidelines for Preparing Economic Analyses.
EPA-240-R-10-001. National Center for Environmental Economics,
Office of Policy. Washington, DC. December. Available at https://www.epa.gov/environmental-economics/guidelines-preparing-economic-analyses. Docket ID No. EPA-HQ-OAR-2009-0234-20503.
\7\ Like the MATS RIA, all benefits and costs in this and
subsequent sections are reported in 2007 dollars.
\8\ See Table 3-5 of the RIA: https://www3.epa.gov/ttn/ecas/docs/ria/utilities_ria_final-mats_2011-12.pdf.
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The EPA's justification for its equal reliance on the co-benefits
of non-HAP emissions when setting the MATS standards in its CAA section
112(n)(1)(A) determination was flawed. The Agency erred in concluding
that the statutory text of CAA section 112(n)(1)(A) and the legislative
history of CAA section 112 more generally ``expressly support[ed]'' the
position that it was reasonable to consider co-benefits, and give equal
weight to those co-benefits, in a CAA section 112(n)(1)(A) appropriate
and necessary finding. 81 FR 24439. The 2016 Supplemental Finding
pointed to CAA section 112(n)(1)(A)'s directive to ``perform a study of
the hazards to public health reasonably anticipated to occur as a
result of emissions by electric utility steam generating units of [HAP]
after imposition of the requirements of [the CAA],'' and noted that the
requirement to consider co-benefit reduction of HAP resulting from
other CAA programs highlighted Congress' understanding that programs
targeted at reducing non-HAP pollutants can and do result in the
reduction of HAP emissions. Id. The finding also noted that the Senate
Report on CAA section 112(d)(2) recognized that maximum achievable
control technology (MACT) standards would have the collateral benefit
of controlling criteria pollutants. Id. However, these statements
acknowledging that reductions in HAP can have the collateral benefit of
reducing non-HAP emissions and vice versa, provides no support for the
proposition that any such co-benefits should be the Agency's primary
consideration when making a finding under CAA section 112(n)(1)(A).
Indeed, it would be highly illogical for the Agency to make a
determination that regulation under CAA section 112, which is expressly
designed to deal with HAP, is justified principally on the basis of the
criteria pollutant impacts of these regulations. That is, if the HAP-
related benefits are not at least moderately commensurate with the cost
of HAP controls, then no amount of co-benefits can offset this
imbalance for purposes of a determination that it is appropriate to
regulate under CAA section 112(n)(1)(A). Cf. Michigan, 135 S. Ct. at
2707 (``One would not say that it is even rational, never mind
``appropriate,'' to impose billions of dollars in economic costs in
return for a few dollars in health or environmental benefits.'').
The 2016 Supplemental Finding's benefit-cost approach also erred in
implying that the results of an economic efficiency test, as informed
by the benefit-cost analysis presented in the MATS RIA, should govern
the cost consideration assessment in CAA section 112(n)(1)(A). A formal
benefit-cost analysis does not dictate how cost should be considered
under CAA section 112(n)(1)(A), particularly where, as noted above, the
statutory provision indicates Congress' particular concern about risks
associated with HAP and the benefits that would accrue from reducing
those risks. Although an analysis of all benefits and costs in
accordance with generally recognized benefit-cost analysis practices is
appropriate for informing the public about the potential effects of any
regulatory action, as well as for complying with the requirements of
Executive Order 12866, this does not mean that equal consideration of
all benefits and costs, including co-benefits, is appropriate for the
specific statutory appropriate and necessary finding called for under
CAA section 112(n)(1)(A). Rather this finding is necessarily governed
by the particular statutory language and context of this provision, as
discussed below.
In sum, the Agency did not provide any meaningful support for its
conclusion that the statutory text and legislative history support
placing consideration of co-benefits in a CAA section 112(n)(1)(A)
determination on equal footing with the consideration of HAP-specific
benefits and, as explained below, the statutory text strongly supports
the use of a different approach.
2. It Is Not Appropriate and Necessary To Regulate EGUs Under CAA
Section 112
In this action, the EPA proposes to conclude that it is not
appropriate and necessary to regulate HAP from EGUs under CAA section
112 because the costs of such regulation grossly outweigh the HAP
benefits. The EPA is taking comment on its proposal that direct
comparison of the rule's costs and benefits is a reasonable approach,
if not the only permissible approach, to considering costs in response
to Michigan, and, further, that such a comparison performed under CAA
section 112(n)(1)(A) should focus primarily on benefits associated with
reduction of HAP (Comment C-2). A proper consideration of costs based
on this approach demonstrates that the
[[Page 2677]]
total cost of compliance with MATS ($7.4 to $9.6 billion annually)
dwarfs the monetized HAP benefits of the rule ($4 to $6 million
annually). As discussed further below, while there are unquantified HAP
benefits and significant monetized PM co-benefits associated with MATS,
the Administrator has concluded that the identification of these
benefits is not sufficient, in light of the gross imbalance of
monetized costs and HAP benefits, to support a finding that it is
appropriate and necessary to regulate EGUs under CAA section 112.
The statutory text of CAA section 112(n)(1)(A) and the Michigan
decision both support focusing the ``appropriate and necessary''
determination on HAP-specific benefits and costs. The study referenced
in CAA section 112(n)(1)(A) specifically focuses on the hazards to
public health that will reasonably occur as a result of HAP emissions,
not harmful emissions in general. According to this section, ``The
Administrator shall regulate electric utility steam generating units
under this section, if the Administrator finds such regulation is
appropriate and necessary after considering the results of the study
required by this subparagraph.'' The text, on its face, thus, suggests
that Congress wanted the Administrator's appropriate and necessary
determination to be focused on the health hazards related to HAP
emissions and the potential benefits of avoiding those hazards by
reducing HAP emissions. As noted in section II.C.1.b. of this preamble,
while the provision acknowledges the existence of the phenomenon of co-
benefits by referencing the potential for ancillary reductions of HAP
emissions by way of CAA provisions targeted at other pollutants,
acknowledgement of that fact does not address whether ancillary
reductions of criteria pollutants should be part of the Administrator's
determination under CAA section 112(n)(1)(A), which is undeniably
focused on hazards resulting from HAP-specific emissions. Indeed, the
direction to consider whether it is appropriate and necessary to
regulate HAP after criteria pollutants have been addressed by the CAA's
other requirements is, if anything, support for the conclusion that it
is not proper to place much weight on the co-benefits of further
criteria pollutant reductions as part of the CAA section 112(n)(1)(A)
determination. Directing the EPA to study HAP effects under CAA section
112 after other provisions of the CAA had been implemented suggests
that Congress envisioned that the judgement about whether additional
regulation was appropriate and necessary should be predicated primarily
on an assessment of HAP emissions from this source category. Similarly,
the general recognition of the existence of collateral benefits or
controlling criteria pollutants in CAA section 112's legislative
history \9\ does not shed any light on whether such benefits should be
given equal consideration in a CAA section 112(n)(1)(A) determination.
This is particularly so where that legislative history is unconnected
to CAA section 112(n)(1)(A), a special provision written by Congress to
address the unique circumstances facing EGUs. In fact, it would not be
reasonable to rely on such legislative history in light of the Supreme
Court's conclusion that the Agency erred attempting to ``harmonize''
CAA section 112(n)(1)(A) with the remainder of CAA section 112. As the
Court noted, ``[t]his line of reasoning overlooks the whole point of
having a separate provision about power plants: Treating power plants
different from other stationary sources.'' Michigan, 135 S. Ct. at
2710.
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\9\ See Legal Memorandum at 25 n.28 (citing A Legislative
History of the Clean Air Act Amendments of 1990, Vol. 5, at 8512
(CAA Amendments of 1989, at 172, Report of the Committee on
Environment and Public Works, S.1630)).
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Finally, we note that this action proposes to primarily consider
the costs of MATS in comparison with the HAP benefits of the hazardous
pollution reductions from MATS. In keeping with CAA section
112(n)(1)(A) and the overall structure of the CAA, we think it is
appropriate not to give equal weight to non-HAP co-benefits in this
comparison. Congress established a rigorous system for setting
standards of acceptable levels of criteria air pollutants and wrote a
comprehensive framework directing the implementation of those standards
in order to address the health and environmental impacts associated
with those pollutants. See, e.g., 42 U.S.C. 7409; 7410; 7501; 7502;
7505a; 7506; 7506a; 7507; 7509; 7509a; 7511; 7511a; 7511b; 7511c;
7511d; 7511e; 7511f; 7512; 7512a; 7513; 7513a; 7513b; 7514; and 7515.
As noted above, the vast majority of estimated monetized benefits
resulting from MATS are associated with reductions in PM2.5
precursor emissions, principally NOX and SO2.
Both NOX and SO2 are criteria pollutants and
precursors to criteria pollutants that are already addressed by the
cavalcade of statutory provisions governing levels of these pollutants,
including the National Ambient Air Quality Standards (NAAQS) provisions
that require the EPA to set standards for criteria pollutants requisite
to protect public health with an adequate margin of safety, and by
state, regional, and national rulemakings establishing control measures
to meet those levels. To the extent that additional reductions of these
criteria pollutants are necessary to protect public health, regulation
explicitly targeted at these pollutants is best reserved for the NAAQS
program, under which Congress provided the EPA ample authority to
regulate.
The total cost of compliance with MATS ($7.4 to $9.6 billion
annually) \10\ vastly outweighs the monetized HAP benefits of the rule
($4 to $6 million annually).\11\ Even with the substantial monetized PM
co-benefits and the significant unquantified HAP benefits associated
with MATS, the gross disparity between monetized costs and HAP
benefits, which we believe to be the primary focus of the
Administrator's determination in CAA section 112(n)(1)(A), is too large
to support an affirmative appropriate and necessary finding. As
explained in the MATS RIA, the only health benefit attributed to
reducing Hg emissions that the EPA could quantify and monetize was IQ
loss in children born to a subset of recreational fishers who consume
fish during pregnancy.\12\ The EPA also identified benefits associated
with regulation of HAP from EGUs that could not be quantified. These
effects include impacts of Hg on human health (including neurologic,
cardiovascular, genotoxic, and immunotoxic effects), a variety of
adverse health effects associated with exposure to certain non-Hg HAP
(including cancer, and chronic and acute health disorders that
implicate multiple organ systems such as the lungs and kidneys), and
effects on wildlife and ecosystems.13 14
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\10\ See Table 3-5 on page 3-14 and Table 3-16 on page 3-31 of
the MATS RIA.
\11\ See Table ES-4 on page ES-6 of the MATS RIA.
\12\ U.S. EPA, 2011. Revised Technical Support Document:
National-Scale Assessment of Mercury Risk to Populations with High
Consumption of Self-Caught Freshwater Fish In Support of the
Appropriate and Necessary Finding for Coal- and Oil-Fired Electric
Generating Units. Office of Air Quality Planning and Standards.
November. EPA-452/R-11-009. Docket ID No. EPA-HQ-OAR-2009-0234-
19913.
\13\ See Chapters 4 and 5 of the MATS RIA.
\14\ In addition, the MATS RIA attributed unquantified health
benefits to reductions in emissions of nitrogen dioxide
(NO2) and SO2. However, as discussed above,
these unquantified criteria pollutant co-benefits are no longer
relevant given the different approach to considering such co-
benefits that the EPA is now proposing to take. See Chapter 5 of the
MATS RIA.
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The EPA acknowledges the importance of these benefits and the
limitations on the Agency's ability to monetize HAP-specific benefits.
The
[[Page 2678]]
EPA agrees that such benefits are relevant to any comparison of the
benefits and costs of a regulation. Because unquantified benefits are,
by definition, not considered in monetary terms, the Administrator must
evaluate the evidence of unquantified benefits and determine the extent
to which they alter any conclusions based on the comparison of
monetized costs and benefits. The MATS RIA accounts for all the
monetized and unquantified benefits of the rule, and the EPA's proposed
approach to the cost-benefit analysis in the RIA does not discount the
existence or importance of the unquantified benefits of reducing HAP
emissions.\15\ Instead, after fully acknowledging the existence and
importance of such benefits, the EPA proposes to conclude that
substantial and important unquantified benefits of MATS are not
sufficient to overcome the significant difference between the monetized
benefits and costs of this rule. As noted, the unquantified HAP-related
benefits of MATS involve only a limited set of mercury and other HAP-
related morbidity effects in humans and ecosystems. The EPA has
provided an updated comparison of costs and target pollutant benefits
in a memorandum to the rulemaking docket.\16\ Table 1 of the memorandum
estimates that the net target HAP benefits of the rule (HAP benefits--
costs) are negative. As noted elsewhere in the notice, the actual costs
and benefits of the MATS rule may differ from the EPA's analysis.
However, as explained in the memorandum, given that the CAA section
112(n)(1)(A) finding is a threshold analysis that Congress intended the
Agency would complete prior to regulation, the EPA believes it is
reasonable for purposes of this reconsideration to rely on the
estimates projected prior to the rule's taking effect, i.e., the
estimates of costs and benefits calculated in the 2011 RIA. In
addition, even assuming that actual costs and benefits differed from
projections made in 2011, given the large difference between target HAP
benefits and estimated costs, the outcome of the Agency's proposed
finding here would likely stay the same.
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\15\ Id. The Agency is not in this proposed replacement to the
2016 Supplemental Finding reopening the prior findings and risk
assessments made over the last two decades. The EPA also explained
in the MATS RIA that there are significant obstacles to successfully
quantifying and monetizing the public health benefits from reducing
HAP emissions. These obstacles include gaps in toxicological data,
uncertainties in extrapolating results from high-dose animal
experiments to estimate human effects at lower doses, limited
monitoring data, difficulties in tracking diseases such as cancer
that have long latency periods, and insufficient economic research
to support the valuation of the health impacts often associated with
exposure to individual HAP.
\16\ Compliance Cost, HAP Benefits, and Ancillary Co-Pollutant
Benefits for ``National Emission Standards for Hazardous Air
Pollutants: Coal-and Oil-Fired Electric Utility Steam Generating
Units--Reconsideration of Supplemental Finding and Residual Risk and
Technology Review.''
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For all of these reasons, and paying particular heed to the
statutory text and purpose of CAA section 112(n)(1)(A) as well as the
Supreme Court's direction in Michigan, we propose to find that it is
not appropriate and necessary to regulate coal- and oil-fired EGUs
under section 112 of the CAA.
D. Effects of This Proposed Replacement of the Supplemental Finding
1. Effects of This Proposed Replacement
Final action on this proposed replacement of the 2016 Supplemental
Finding will reverse the Agency's conclusion under CAA section
112(n)(1)(A), first made in 2000 and later affirmed in 2012 and 2016,
that it is appropriate and necessary to regulate HAP from EGUs. We
propose to conclude that finalizing this replacement will not remove
the Coal- and Oil-Fired EGU source category from the CAA section
112(c)(1) list, nor will finalizing this revision otherwise affect the
existing CAA section 112(d) emissions standards promulgated in 2012.
Under D.C. Circuit case law, the EPA's determination that a source
category was listed in error does not by itself remove a source
category from the CAA section 112(c)(1) list--even EGUs,
notwithstanding their special treatment under CAA section 112(n). New
Jersey v. EPA, 517 F.3d 574 (D.C. Cir. 2008). Instead, in order to
remove a source category from the CAA section 112(c)(1) list, the EPA
must determine that the CAA section 112(c)(9) statutory criteria for
delisting have been met. Id. The EPA requests comment on its
interpretation of New Jersey in the context of this proposed finding
(Comment C-3).
In 2005, the EPA reversed the December 2000 Finding and concluded
that it was neither appropriate nor necessary to regulate coal- and
oil-fired EGUs under CAA section 112 and delisted such units from the
CAA section 112(c) source category list. 70 FR 15994. In that rule we
stated, ``EPA reasonably interprets section 112(n)(1)(A) as providing
it authority to remove coal- and oil-fired units from the section
112(c) list at any time that it makes a negative appropriate and
necessary finding under the section.'' 70 FR 16032 (2005 Delisting
Rule). In the 2005 Delisting Rule, the EPA ``identified errors in the
prior [2000] finding and determined that the finding lacked
foundation.'' Id. at 16033. Because we found that the 2000 Finding had
been in error at the time of listing, we concluded that coal- and oil-
fired EGUs ``should never have been listed under section 112(c) and
therefore the criteria of section 112(c)(9) do not apply'' in removing
the source category from the list. Id. In addition, we pointed out that
the inclusion of EGUs on the 112(c)(1) list was not a ``final agency
action.'' Id. Therefore, we stated that we had ``inherent authority
under the CAA to revise [the listing] at any time based on either
identified errors in the December 2000 finding or on new information
that bears upon that finding.'' Id.
The D.C. Circuit rejected the EPA's interpretations and vacated the
2005 Delisting Rule, holding that the CAA unambiguously requires the
delisting criteria in CAA section 112(c)(9) to have been met before
``any'' source category can be removed from the CAA section 112(c)(1)
list. New Jersey, 517 F.3d at 582. It specified that, under the CAA's
plain text and under step one of Chevron, ``the only way the EPA could
remove EGUs from the section 112(c)(1) list'' was to satisfy those
criteria. Id. (emphasis added). The Court expressly rejected the EPA's
argument that, ``[l]ogically, if EPA makes a determination under
section 112(n)(1)(A) that power plants should not be regulated at all
under section 112 . . . [then] this determination ipso facto must
result in removal of power plants from the section 112(c) list.'' Id.
(quoting the EPA's brief). Instead, the Court maintained that CAA
section 112(n)(1) governed only how the Administrator determines
whether to list EGUs, and that any and all attempts to remove
categories from the list were under the exclusive purview of CAA
section 112(c)(9). See id. The Court further held that the existence of
CAA section 112(c)(9) limited the normal discretion an Agency would
typically have to reverse its position and undo the administrative
determination to list EGUs as a source category. See Id. at 582-83.
In this action, we propose to reverse the conclusions presented in
the 2016 Supplemental Finding and to find that, after consideration of
the cost of compliance with the CAA section 112(d) standards, it is not
appropriate and necessary to regulate HAP emissions from EGUs under CAA
section 112. Consistent with New Jersey, the EPA is proposing to find
that this reversal of the CAA section 112(n)(1)(A) determination, if
finalized, would not have the effect of removing EGUs from the CAA
section 112(c)(1) source category list. Because EGUs would remain on
the CAA section 112(c)(1)
[[Page 2679]]
source category list, the CAA section 112(d) standards for that
category, as promulgated in the MATS rule, would be unaffected by final
action on this proposal.
2. Alternative Interpretations of Effects of This Proposed Replacement:
Requests for Comment
The EPA also solicits comment on two alternative interpretations of
the impact of reversing the 2016 Supplemental Finding. Specifically,
the Agency solicits comment under two separate theories on whether,
contrary to the interpretation discussed above, the EPA would have
authority to rescind the MATS rule and delist EGUs from CAA section 112
if, acting on remand following the Supreme Court's opinion in Michigan,
it were to finalize its proposed conclusion that it is not appropriate
and necessary to regulate HAP from coal- and oil-fired EGUs (Comment C-
4). The Agency also solicits comment on whether, in light of the fact
that the CAA section 112(n)(1)(A) finding is a threshold determination
to setting the CAA section 112(d) standards, we would be obligated to
rescind the rule if we were to finalize our proposed finding that it is
not appropriate and necessary to regulate HAP from these sources, even
if such a finding did not remove EGUs from the list of covered sources
under CAA section 112(c) (Comment C-5).
In particular, we solicit comment on whether the EPA could
reasonably conclude that the D.C. Circuit's holding in New Jersey v.
EPA does not limit the Agency's authority to rescind the MATS rule,
under two alternative interpretations (Comment C-6). Under the first
alternative interpretation, we seek comment on whether New Jersey is
distinguishable because the facts here are sufficiently different from
those considered by the Court reviewing the 2005 Delisting Rule at
issue (Comment C-7). In that case, the original 2000 Finding and CAA
section 112(c)(1) listing were in place, but because the EPA had not
yet promulgated CAA section 112(d) standards, the finding itself was
not yet reviewable. CAA section 112(e)(4); see also UARG v. EPA, No.
01-1074, 2001 U.S. App. LEXIS 18436, 2001 WL 936363 (D.C. Cir. July 26,
2001). Here, the 2012 Finding was challenged and reviewed by the
Supreme Court in Michigan v. EPA, which found that the EPA's
determination that it was appropriate and necessary to regulate HAP
from EGUs was flawed. Because the Supreme Court found that
determination to be flawed, the EPA necessarily retains the discretion
to reach a different conclusion from that reached in 2012 when we
promulgated MATS. This proposed reversal of the 2016 Supplemental
Finding is a continuation of the Agency's response to the Supreme
Court's remand, and New Jersey does not limit the effect of an action
made in response to a Supreme Court decision finding the original
action flawed, nor does it limit the Agency's ability to revise its
response to a Supreme Court decision. Therefore, the EPA would have
authority to rescind MATS and remove EGUs from the list of source
categories regulation under CAA section 112 after finalizing this
reversal of the 2016 Supplemental Finding.
Under the second alternative interpretation, the EPA seeks comment
on whether, were the proposed reversal to be finalized, EGUs would
remain on the CAA section 112(c) list of sources, but the EPA would
have the authority to rescind the standards regulating those source's
emissions under CAA section 112(d) in light of the fact that CAA
section 112(n)(1)(A) plainly establishes that the Administrator must
find regulation under CAA section 112 is appropriate and necessary as a
prerequisite to undertaking such regulation (Comment C-8). New Jersey
v. EPA held that the EPA may not remove a source category from the CAA
section 112(c) list without demonstrating that the delisting analysis
under CAA section 112(c)(9) has been satisfied, but the decision did
not address the question whether, in the absence of a valid appropriate
and necessary finding, the EPA must regulate EGUs for HAP.
Finally, although the alternative interpretations described
immediately above both suggest the EPA would have the discretionary
authority to rescind MATS (either with or without delisting), the EPA
solicits comment on whether, under either alternative interpretation,
the Agency would instead be obligated to rescind MATS once it finalized
a reversal of the 2016 Supplemental Finding (Comment C-9).
We solicit comment on all aspects of these alternative
interpretations of the impacts of replacing the 2016 Supplemental
Finding and these potential alternate readings of the Court's decision
in New Jersey (Comment C-10).
III. Criteria for Delisting a Source Category Under CAA Section
112(c)(9)
As noted above, New Jersey held that the EPA cannot remove a source
category from the CAA section 112(c) source category list without
addressing the delisting criteria in CAA section 112(c)(9). CAA section
112(c)(9)(B) provides that ``[t]he Administrator may delete any source
category'' from the CAA section 112(c) source category list if the
Agency determines that: (1) For HAP that may cause cancer in humans,
``no source in the category (or group of sources in the case of area
sources) emits such hazardous air pollutants in quantities which may
cause a lifetime risk of cancer greater than one in one million to the
individual in the population who is most exposed to emissions of such
pollutants from the source (or group of sources in the case of area
sources)''; and (2) for HAP that may result in human health effects
other than cancer or adverse environmental effects, ``a determination
that emissions from no source in the category or subcategory concerned
(or group of sources in the case of area sources) exceed a level which
is adequate to protect public health with an ample margin of safety and
no adverse environmental effect will result from emissions from any
source.''
In this action, the EPA is neither conducting a delisting analysis
under CAA section 112(c)(9) for the Coal- and Oil-Fired EGU source
category, nor soliciting comment on whether such an analysis should be
conducted, or on what any such analysis would demonstrate. Any such
comments would be outside the scope of this action.
The Agency notes that the proposed results of its risk review
indicate that with the MATS rule in place, the estimated inhalation
cancer risk to the individual most exposed to actual emissions from the
source category is 9-in-1 million. As noted above, the EPA is not
proposing a delisting analysis and any such analysis would likely
differ from the analysis done for the CAA section 112(f)(2) risk review
in important aspects.
In addition, on two previous occasions, the EPA has examined the
statutory delisting criteria with respect to EGUs and found that the
criteria were not met. We summarize without adding to those findings
below.
In 2011, in response to the EPA's request for comments on the
proposed MATS rule, the Utility Air Regulatory Group (UARG) submitted a
petition pursuant to CAA section 112(c)(9) requesting that coal-fired
EGUs be removed from the CAA section 112(c) List of Categories of Major
and Area Sources.\17\ In its petition, UARG
[[Page 2680]]
asserted that: (1) No coal-fired EGU or group of coal-fired EGUs emit
HAP in amounts that will cause a lifetime cancer risk greater than 1-
in-1 million; and (2) no coal-fired EGU or group of coal-fired EGUs
emit non-carcinogenic HAP in amounts that will exceed a level which is
adequate to protect public health with an ample margin of safety or
cause adverse environmental effects. The EPA denied this petition on
several grounds.\18\ First, the EPA rejected UARG's request on the
basis that, under D.C. Circuit precedent, the Agency is not permitted
to delist a portion of a source category that poses cancer risks.\19\
Second, the EPA found that UARG's data and analyses identified a
maximum individual cancer risk of 4-in-1 million, which exceeds the
statutory threshold in CAA section 112(c)(9)(B)(i) of 1-in-1 million.
Additionally, the EPA found that UARG's analysis did not fully
characterize noncancer human health effects for the source category and
further, that UARG failed to show that ``no adverse environmental
effects will result from emissions from any source'' pursuant to CAA
section 112(c)(9)(B)(ii). For all these reasons, the EPA denied UARG's
petition to delist coal-fired EGUs from the CAA section 112(c) source
category list. UARG challenged the EPA's denial of its delisting
petition as arbitrary and capricious, and the D.C. Circuit dismissed
UARG's challenge on the basis that the EPA had adequately demonstrated
that the CAA section 112(c)(9) delisting criteria were not met by
UARG's analysis. White Stallion, 748 F.3d at 1248.
---------------------------------------------------------------------------
\17\ Petition of the Utility Air Regulatory Group for the De-
Listing of Coal-Fired Electric Utility Steam Generating Units as a
Source Category Subject to Section 112 of the Clean Air Act. Docket
ID No. EPA-HQ-OAR-2009-0234-17777.
\18\ 77 FR 9365 (February 16, 2012).
\19\ UARG petitioned the Agency to delist coal-fired EGUs, which
represent only a portion of the listed source category. The EPA
believed it was not permitted to delist a portion of a source
category, where that source category poses cancer risks. NRDC v.
U.S. EPA, 489 F.3d 1364 (D.C. Cir. 2007). Specifically, in NRDC, the
D.C. Circuit held that the Agency's attempt to delist a ``low-risk''
subcategory was ``contrary to the plain language of the statute,''
and that the statute only authorized the Agency to remove source
categories pursuant to CAA section 112(c)(9). Id. at 1373 (``Because
EPA's interpretation of Section 112(c)(9) as allowing it to exempt
the risk-based subcategory is contrary to the plain language of the
statute, the EPA's interpretation fails at Chevron step one.'').
---------------------------------------------------------------------------
The EPA also independently conducted an analysis which also
confirmed that the Coal- and Oil-Fired EGU source category cannot be
delisted pursuant to CAA section 112(c)(9).\20\ The EPA analyzed non-Hg
inhalation risks from 16 EGU facility case studies, including both
coal- and oil-fired EGUs. Of the 16 facilities analyzed, six had cancer
risks greater than 1-in-1 million, exceeding the delisting criteria in
CAA section 112(c)(9)(B)(i). Because EGUs failed to meet the first
delisting requirement, the Agency did not need to determine whether the
second delisting requirement was satisfied.
---------------------------------------------------------------------------
\20\ U.S. EPA, 2011. Supplement to the Non-Hg Case Study Chronic
Inhalation Risk Assessment in Support of the Appropriate and
Necessary Finding for Coal- and Oil-Fired Electric Generating Units.
November. EPA-452/R-11-013. Docket ID No. EPA-HQ-OAR-2009-0234-
19912.
---------------------------------------------------------------------------
IV. Background on the RTR Action
A. What is the statutory authority for this action?
The statutory authority for this action is provided by sections 112
and 301 of the CAA, as amended (42 U.S.C. 7401 et seq.). Section 112 of
the CAA establishes a two-stage regulatory process to develop standards
for emissions of HAP from stationary sources. Generally, the first
stage involves establishing technology-based standards and the second
stage involves evaluating those standards that are based on MACT to
determine whether additional standards are needed to address any
remaining risk associated with HAP emissions. This second stage is
commonly referred to as the ``residual risk review.'' In addition to
the residual risk review, the CAA also requires the EPA to review
standards set under CAA section 112 every 8 years to determine if there
are ``developments in practices, processes, or control technologies''
that may be appropriate to incorporate into the standards. This review
is commonly referred to as the ``technology review.'' When the two
reviews are combined into a single rulemaking, it is commonly referred
to as the ``risk and technology review.'' The discussion that follows
identifies the most relevant statutory sections and briefly explains
the contours of the methodology used to implement these statutory
requirements. A more comprehensive discussion appears in the document
titled CAA Section 112 Risk and Technology Reviews: Statutory Authority
and Methodology in the docket for this rulemaking.
In the first stage of the CAA section 112 standard setting process,
the EPA promulgates technology-based standards under CAA section 112(d)
for categories of sources identified as emitting one or more of the HAP
listed in CAA section 112(b). Sources of HAP emissions are either major
sources or area sources, and CAA section 112 establishes different
requirements for major source standards and area source standards.
``Major sources'' are those that emit or have the potential to emit 10
tpy or more of a single HAP or 25 tpy or more of any combination of
HAP. All other sources are ``area sources.'' For major sources, CAA
section 112(d)(2) provides that the technology-based NESHAP must
reflect the maximum degree of emission reductions of HAP achievable
(after considering cost, energy requirements, and non-air quality
health and environmental impacts). These standards are commonly
referred to as MACT standards. CAA section 112(d)(3) also establishes a
minimum control level for MACT standards, known as the MACT ``floor.''
The EPA must also consider control options that are more stringent than
the floor. Standards more stringent than the floor are commonly
referred to as beyond-the-floor standards. In certain instances, as
provided in CAA section 112(h), the EPA may set work practice standards
where it is not feasible to prescribe or enforce a numerical emission
standard. For area sources, CAA section 112(d)(5) gives the EPA
discretion to set standards based on generally available control
technologies or management practices (GACT standards) in lieu of MACT
standards.
The second stage in standard-setting focuses on identifying and
addressing any remaining (i.e., ``residual'') risk according to CAA
section 112(f). For source categories subject to MACT standards,
section 112(f)(2) of the CAA requires the EPA to determine whether
promulgation of additional standards is needed to provide an ample
margin of safety to protect public health or to prevent an adverse
environmental effect. Section 112(d)(5) of the CAA provides that this
residual risk review is not required for categories of area sources
subject to GACT standards. Section 112(f)(2)(B) of the CAA further
expressly preserves the EPA's use of the two-step approach for
developing standards to address any residual risk and the Agency's
interpretation of ``ample margin of safety'' developed in the National
Emissions Standards for Hazardous Air Pollutants: Benzene Emissions
from Maleic Anhydride Plants, Ethylbenzene/Styrene Plants, Benzene
Storage Vessels, Benzene Equipment Leaks, and Coke By-Product Recovery
Plants (Benzene NESHAP) (54 FR 38044, September 14, 1989). The EPA
notified Congress in the Risk Report that the Agency intended to use
the Benzene NESHAP approach in making CAA section 112(f) residual risk
determinations (EPA-453/R-99-001, p. ES-11). The EPA subsequently
adopted this approach in its residual risk determinations and the Court
upheld the EPA's interpretation that CAA section 112(f)(2) incorporates
the approach established in the Benzene
[[Page 2681]]
NESHAP. See NRDC v. EPA, 529 F.3d 1077, 1083 (D.C. Cir. 2008).
The approach incorporated into the CAA and used by the EPA to
evaluate residual risk and to develop standards under CAA section
112(f)(2) is a two-step approach. In the first step, the EPA determines
whether risks are acceptable. This determination ``considers all health
information, including risk estimation uncertainty, and includes a
presumptive limit on maximum individual lifetime [cancer] risk (MIR)
\21\ of approximately 1 in 10 thousand.'' 54 FR 38045, September 14,
1989. If risks are unacceptable, the EPA must determine the emissions
standards necessary to reduce risk to an acceptable level without
considering costs. In the second step of the approach, the EPA
considers whether the emissions standards provide an ample margin of
safety to protect public health ``in consideration of all health
information, including the number of persons at risk levels higher than
approximately 1 in 1 million, as well as other relevant factors,
including costs and economic impacts, technological feasibility, and
other factors relevant to each particular decision.'' Id. The EPA must
promulgate emission standards necessary to provide an ample margin of
safety to protect public health. After conducting the ample margin of
safety analysis, we consider whether a more stringent standard is
necessary to prevent, taking into consideration costs, energy, safety,
and other relevant factors, an adverse environmental effect.
---------------------------------------------------------------------------
\21\ Although defined as ``maximum individual risk,'' MIR refers
only to cancer risk. MIR, one metric for assessing cancer risk, is
the estimated risk if an individual were exposed to the maximum
level of a pollutant for a lifetime.
---------------------------------------------------------------------------
CAA section 112(d)(6) separately requires the EPA to review
standards promulgated under CAA section 112 and revise them ``as
necessary (taking into account developments in practices, processes,
and control technologies)'' no less often than every 8 years. In
conducting this review, which we call the ``technology review,'' the
EPA is not required to recalculate the MACT floor. Natural Resources
Defense Council (NRDC) v. EPA, 529 F.3d 1077, 1084 (D.C. Cir. 2008).
Association of Battery Recyclers, Inc. v. EPA, 716 F.3d 667 (D.C. Cir.
2013). The EPA may consider cost in deciding whether to revise the
standards pursuant to CAA section 112(d)(6).
B. What is this source category and how does the current NESHAP
regulate its HAP emissions?
The NESHAP for the Coal- and Oil-Fired EGU source category
(commonly referred to as MATS) were initially promulgated on February
16, 2012 (77 FR 9304), under title 40 part 63, subpart UUUUU. The MATS
rule was amended on April 19, 2012 (77 FR 23399), to correct
typographical errors and certain preamble text that was inconsistent
with regulatory text; on April 24, 2013 (78 FR 24073), to update
certain emission limits and monitoring and testing requirements
applicable to new sources; on November 19, 2014 (79 FR 68777), to
revise definitions for startup and shutdown and to finalize work
practice standards and certain monitoring and testing requirements
applicable during periods of startup and shutdown; and on April 6, 2016
(81 FR 20172), to correct conflicts between preamble and regulatory
text and to clarify regulatory text. In addition, the electronic
reporting requirements of the rule were amended on March 24, 2015 (80
FR 15510), to allow for the electronic submission of Portable Document
Format (PDF) versions of certain reports until April 16, 2017, while
the EPA's Emissions Collection and Monitoring Plan System (ECMPS) is
revised to accept all reporting that is required by the rule, and on
April 6, 2017 (82 FR 16736), and on July 2, 2018 (83 FR 30879), to
extend the interim submission of PDF versions of reports through June
30, 2018, and July 1, 2020, respectively.
The MATS rule applies to coal- and oil-fired EGUs located at both
major and area sources of HAP emissions. The sources subject to the
MATS rule include each individual or group of coal- or oil-fired EGUs.
An existing affected source is the collection of coal- or oil-fired
EGUs in a subcategory within a single contiguous area and under common
control. A new affected source is each coal- or oil-fired EGU for which
construction or reconstruction began after May 3, 2011. As previously
stated in section I of this preamble, an electric utility steam
generating unit is a fossil fuel-fired combustion unit of more than 25
megawatts (MW) that serves a generator that produces electricity for
sale. A unit that cogenerates steam and electricity and supplies more
than one-third of its potential electric output capacity and more than
25 MW electric output to any utility power distribution system for sale
is also considered an electric utility steam generating unit. The MATS
rule defines additional terms for determining rule applicability,
including, but not limited to, definitions for ``Coal-fired electric
utility steam generating unit,'' ``Oil-fired electric utility steam
generating unit,'' and ``Fossil fuel-fired.'' Certain types of electric
generating units are not subject to 40 CFR part 63, subpart UUUUU: Any
unit designated as a major source stationary combustion turbine subject
to subpart YYYY of part 63 and any unit designated as an area source
stationary combustion turbine, other than an integrated gasification
combined cycle (IGCC) unit; any EGU that is not a coal- or oil-fired
EGU and that meets the definition of a natural gas-fired EGU in 40 CFR
63.10042; any EGU greater than 25 MW that has the capability of
combusting either coal or oil, but does not meet the definition of a
coal- or oil-fired EGU because it did not fire sufficient coal or oil
to satisfy the average annual heat input requirement set forth in the
definitions for coal-fired and oil-fired EGUs in 40 CFR 63.10042; and
any electric steam generating unit combusting solid waste (i.e., a
solid waste incineration unit) subject to standards established under
sections 129 and 111 of the CAA.
For coal-fired EGUs, the rule established standards to limit
emissions of Hg, acid gas HAP, non-Hg HAP metals (e.g., nickel, lead,
chromium), and organic HAP (e.g., formaldehyde, dioxin/furan).
Standards for hydrochloric acid (HCl) serve as a surrogate for the acid
gas HAP, with an alternate standard for SO2 that may be used
as a surrogate for acid gas HAP for those coal-fired EGUs with flue gas
desulfurization (FGD) systems and SO2 continuous emissions
monitoring systems (CEMS) installed and operational. Standards for
filterable particulate matter (fPM) serve as a surrogate for the non-Hg
HAP metals, with standards for total non-Hg HAP metals and individual
non-Hg HAP metals provided as alternative equivalent standards. Work
practice standards limit formation and emission of the organic HAP.
For oil-fired EGUs, the rule establishes standards to limit
emissions of HCl and hydrogen fluoride (HF), total HAP metals (e.g.,
Hg, nickel, lead), and organic HAP (e.g., formaldehyde, dioxin/furan).
Standards for fPM serve as a surrogate for total HAP metals, with
standards for total HAP metals and individual HAP metals provided as
alternative equivalent standards. Work practice standards limit
formation and emission of the organic HAP.
The MATS rule includes standards for existing and new EGUs for
seven subcategories: Two for coal-fired EGUs, one for IGCC EGUs, one
for solid oil-derived fuel-fired EGUs, and three for liquid oil-fired
EGUs. EGUs in six of the subcategories are subject to numeric emission
limits for the pollutants
[[Page 2682]]
described above except for organic HAP. Organic HAP are regulated by a
work practice standard that requires periodic combustion process tune-
ups. EGUs in the subcategory of limited-use liquid oil-fired EGUs with
an annual capacity factor of less than 8 percent of its maximum or
nameplate heat input are also subject to a work practice standard
consisting of periodic combustion process tune-ups, but are not subject
to any numeric emission limits. Emission limits for existing EGUs and
new or reconstructed EGUs are summarized in Table 2 and Table 3,
respectively.
Table 2--Emission Limits for Existing Affected EGUs
------------------------------------------------------------------------
Subcategory Pollutant Emission limit \1\
------------------------------------------------------------------------
1. Coal-fired unit not low a. fPM.............. 3.0E-2 lb/MMBtu or
rank virgin coal. 3.0E-1 lb/MWh.
OR.................. OR
Total non-Hg HAP 5.0E-5 lb/MMBtu or
metals. 5.0E-1 lb/GWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 8.0E-1 lb/TBtu or
8.0E-3 lb/GWh.
Arsenic, As...... 1.1 lb/TBtu or 2.0E-
2 lb/GWh.
Beryllium, Be.... 2.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
Cadmium, Cd...... 3.0E-1 lb/TBtu or
3.0E-3 lb/GWh.
Chromium, Cr..... 2.8 lb/TBtu or 3.0E-
2 lb/GWh.
Cobalt, Co....... 8.0E-1 lb/TBtu or
8.0E-3 lb/GWh.
Lead, Pb......... 1.2 lb/TBtu or 2.0E-
2 lb/GWh.
Manganese, Mn.... 4.0 lb/TBtu or 5.0E-
2 lb/GWh.
Nickel, Ni....... 3.5 lb/TBtu or 4.0E-
2 lb/GWh.
Selenium, Se..... 5.0 lb/TBtu or 6.0E-
2 lb/GWh.
b. HCl.............. 2.0E-3 lb/MMBtu or
2.0E-2 lb/MWh.
OR.................. OR
SO2 \2\............. 2.0E-1 lb/MMBtu or
1.5 lb/MWh.
c. Hg............... 1.2 lb/TBtu or 1.3E-
2 lb/GWh.
2. Coal-fired unit low rank a. fPM.............. 3.0E-2 lb/MMBtu or
virgin coal. 3.0E-1 lb/MWh.
OR.................. OR
Total non-Hg HAP 5.0E-5 lb/MMBtu or
metals. 5.0E-1 lb/GWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 8.0E-1 lb/TBtu or
8.0E-3 lb/GWh.
Arsenic, As...... 1.1 lb/TBtu or 2.0E-
2 lb/GWh.
Beryllium, Be.... 2.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
Cadmium, Cd...... 3.0E-1 lb/TBtu or
3.0E-3 lb/GWh.
Chromium, Cr..... 2.8 lb/TBtu or 3.0E-
2 lb/GWh.
Cobalt, Co....... 8.0E-1 lb/TBtu or
8.0E-3 lb/GWh.
Lead, Pb......... 1.2 lb/TBtu or 2.0E-
2 lb/GWh.
Manganese, Mn.... 4.0 lb/TBtu or 5.0E-
2 lb/GWh.
Nickel, Ni....... 3.5 lb/TBtu or 4.0E-
2 lb/GWh.
Selenium, Se..... 5.0 lb/TBtu or 6.0E-
2 lb/GWh.
b. HCl.............. 2.0E-3 lb/MMBtu or
2.0E-2 lb/MWh.
OR.................. OR
SO2 \2\............. 2.0E-1 lb/MMBtu or
1.5 lb/MWh.
c. Hg............... 4.0 lb/TBtu or 4.0E-
2 lb/GWh.
3. IGCC unit................ a. fPM.............. 4.0E-2 lb/MMBtu or
4.0E-1 lb/MWh.
OR.................. OR
Total non-Hg HAP 6.0E-5 lb/MMBtu or
metals. 5.0E-1 lb/GWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 1.4 lb/TBtu or 2.0E-
2 lb/GWh.
Arsenic, As...... 1.5 lb/TBtu or 2.0E-
2 lb/GWh.
Beryllium, Be.... 1.0E-1 lb/TBtu or
1.0E-3 lb/GWh.
Cadmium, Cd...... 1.5E-1 lb/TBtu or
2.0E-3 lb/GWh.
Chromium, Cr..... 2.9 lb/TBtu or 3.0E-
2 lb/GWh.
Cobalt, Co....... 1.2 lb/TBtu or 2.0E-
2 lb/GWh.
Lead, Pb......... 1.9E+2 lb/MMBtu or
1.8 lb/MWh.
Manganese, Mn.... 2.5 lb/TBtu or 3.0E-
2 lb/GWh.
Nickel, Ni....... 6.5 lb/TBtu or 7.0E-
2 lb/GWh.
Selenium, Se..... 2.2E+1 lb/TBtu or
3.0E-1 lb/GWh.
b. HCl.............. 5.0E-4 lb/MMBtu or
5.0E-3 lb/MWh.
c. Hg............... 2.5 lb/TBtu or 3.0E-
2 lb/GWh.
4. Liquid oil-fired unit-- a. fPM.............. 3.0E-2 lb/MMBtu or
continental (excluding 3.0E-1 lb/MWh.
limited-use liquid oil-
fired subcategory units).
OR.................. OR
Total HAP metals.... 8.0E-4 lb/MMBtu or
8.0E-3 lb/MWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 1.3E+1 lb/TBtu or
2.0E-1 lb/GWh.
Arsenic, As...... 2.8 lb/TBtu or 3.0E-
2 lb/GWh.
Beryllium, Be.... 2.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
Cadmium, Cd...... 3.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
Chromium, Cr..... 5.5 lb/TBtu or 6.0E-
2 lb/GWh.
[[Page 2683]]
Cobalt, Co....... 2.1E+1 lb/TBtu or
3.0E-1 lb/GWh.
Lead, Pb......... 8.1 lb/TBtu or 8.0E-
2 lb/GWh.
Manganese, Mn.... 2.2E+1 lb/TBtu or
3.0E-1 lb/GWh.
Nickel, Ni....... 1.1E+2 lb/TBtu or
1.1 lb/GWh.
Selenium, Se..... 3.3 lb/TBtu or 4.0E-
2 lb/GWh.
Hg............... 2.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
b. HCl.............. 2.0E-3 lb/MMBtu or
1.0E-2 lb/MWh.
c. HF............... 4.0E-4 lb/MMBtu or
4.0E-3 lb/MWh.
5. Liquid oil-fired unit-- a. fPM.............. 3.0E-2 lb/MMBtu or
non-continental (excluding 3.0E-1 lb/MWh.
limited-use liquid oil-
fired subcategory units).
OR.................. OR
Total HAP metals.... 6.0E-4 lb/MMBtu or
7.0E-3 lb/MWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 2.2 lb/TBtu or 2.0E-
2 lb/GWh.
Arsenic, As...... 4.3 lb/TBtu or 8.0E-
2 lb/GWh.
Beryllium, Be.... 6.0E-1 lb/TBtu or
3.0E-3 lb/GWh.
Cadmium, Cd...... 3.0E-1 lb/TBtu or
3.0E-3 lb/GWh.
Chromium, Cr..... 3.1E+1 lb/TBtu or
3.0E-1 lb/GWh.
Cobalt, Co....... 1.1E+2 lb/TBtu or
1.4 lb/GWh.
Lead, Pb......... 4.9 lb/TBtu or 8.0E-
2 lb/GWh.
Manganese, Mn.... 2.0E+1 lb/TBtu or
3.0E-1 lb/GWh.
Nickel, Ni....... 4.7E+2 lb/TBtu or
4.1 lb/GWh.
Selenium, Se..... 9.8 lb/TBtu or 2.0E-
1 lb/GWh.
Hg............... 4.0E-2 lb/TBtu or
4.0E-4 lb/GWh.
b. HCl.............. 2.0E-4 lb/MMBtu or
2.0E-3 lb/MWh.
c. HF............... 6.0E-5 lb/MMBtu or
5.0E-4 lb/MWh.
6. Solid oil-derived fuel- a. fPM.............. 8.0E-3 lb/MMBtu or
fired unit. 9.0E-2 lb/MWh.
OR.................. OR
Total non-Hg HAP 4.0E-5 lb/MMBtu or
metals. 6.0E-1 lb/GWh.
OR.................. OR
Individual HAP
metals:
Antimony, Sb..... 8.0E-1 lb/TBtu or
7.0E-3 lb/GWh.
Arsenic, As...... 3.0E-1 lb/TBtu or
5.0E-3 lb/GWh.
Beryllium, Be.... 6.0E-2 lb/TBtu or
5.0E-4 lb/GWh.
Cadmium, Cd...... 3.0E-1 lb/TBtu or
4.0E-3 lb/GWh.
Chromium, Cr..... 8.0E-1 lb/TBtu or
2.0E-2 lb/GWh.
Cobalt, Co....... 1.1 lb/TBtu or 2.0E-
2 lb/GWh.
Lead, Pb......... 8.0E-1 lb/TBtu or
2.0E-2 lb/GWh.
Manganese, Mn.... 2.3 lb/TBtu or 4.0E-
2 lb/GWh.
Nickel, Ni....... 9.0 lb/TBtu or 2.0E-
1 lb/GWh.
Selenium, Se..... 1.2 lb/Tbtu 2.0E-2
lb/GWh.
b. HCl.............. 5.0E-3 lb/MMBtu or
8.0E-2 lb/MWh.
OR.................. OR
SO2 \2\............. 3.0E-1 lb/MMBtu or
2.0 lb/MWh.
c. Hg............... 2.0E-1 lb/TBtu or
2.0E-3 lb/GWh.
------------------------------------------------------------------------
\1\ Units of emission limits:
lb/MMBtu = pounds pollutant per million British thermal units fuel
input;
lb/TBtu = pounds pollutant per trillion British thermal units fuel
input;
lb/MWh = pounds pollutant per megawatt-hour electric output (gross); and
lb/GWh = pounds pollutant per gigawatt-hour electric output (gross).
\2\ Alternate SO2 limit may be used if the EGU has some form of FGD
system and SO2 CEMS installed.
Table 3--Emission Limits for New or Reconstructed Affected EGUs
------------------------------------------------------------------------
Subcategory Pollutant Emission limit \1\
------------------------------------------------------------------------
1. Coal-fired unit not low a. fPM.............. 9.0E-2 lb/MWh.
rank virgin coal.
OR.................. OR
Total non-Hg HAP 6.0E-2 lb/GWh.
metals.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 8.0E-3 lb/GWh.
Arsenic, As...... 3.0E-3 lb/GWh.
Beryllium, Be.... 6.0E-4 lb/GWh.
Cadmium, Cd...... 4.0E-4 lb/GWh.
Chromium, Cr..... 7.0E-3 lb/GWh.
Cobalt, Co....... 2.0E-3 lb/GWh.
Lead, Pb......... 2.0E-2 lb/GWh.
Manganese, Mn.... 4.0E-3 lb/GWh.
Nickel, Ni....... 4.0E-2 lb/GWh.
[[Page 2684]]
Selenium, Se..... 5.0E-2 lb/GWh.
b. HCl.............. 1.0E-2 lb/MWh.
OR.................. OR
SO2 \2\............. 1.0 lb/MWh.
c. Hg............... 3.0E-3 lb/GWh.
2. Coal-fired units low rank a. fPM.............. 9.0E-2 lb/MWh.
virgin coal.
OR.................. OR
Total non-Hg HAP 6.0E-2 lb/GWh.
metals.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 8.0E-3 lb/GWh.
Arsenic, As...... 3.0E-3 lb/GWh.
Beryllium, Be.... 6.0E-4 lb/GWh.
Cadmium, Cd...... 4.0E-4 lb/GWh.
Chromium, Cr..... 7.0E-3 lb/GWh.
Cobalt, Co....... 2.0E-3 lb/GWh.
Lead, Pb......... 2.0E-2 lb/GWh.
Manganese, Mn.... 4.0E-3 lb/GWh.
Nickel, Ni....... 4.0E-2 lb/GWh.
Selenium, Se..... 5.0E-2 lb/GWh.
b. HCl.............. 1.0E-2 lb/MWh.
OR.................. OR
SO2 \2\............. 1.0 lb/MWh.
c. Hg............... 4.0E-2 lb/GWh.
3. IGCC unit................ a. fPM.............. 7.0E-2 lb/MWh.\3\
.................... 9.0E-2 lb/MWh.\4\
OR.................. OR
Total non-Hg HAP 4.0E-1 lb/GWh.
metals.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 2.0E-2 lb/GWh.
Arsenic, As...... 2.0E-2 lb/GWh.
Beryllium, Be.... 1.0E-3 lb/GWh.
Cadmium, Cd...... 2.0E-3 lb/GWh.
Chromium, Cr..... 4.0E-2 lb/GWh.
Cobalt, Co....... 4.0E-3 lb/GWh.
Lead, Pb......... 9.0E-3 lb/GWh.
Manganese, Mn.... 2.0E-2 lb/GWh.
Nickel, Ni....... 7.0E-2 lb/GWh.
Selenium, Se..... 3.0E-1 lb/GWh.
b. HCl.............. 2.0E-3 lb/MWh.
OR.................. OR
SO2 \2\............. 4.0E-1 lb/MWh.
c. Hg............... 3.0E-3 lb/GWh.
4. Liquid oil-fired unit-- a. fPM.............. 3.0E-1 lb/MWh.
continental (excluding
limited-use liquid oil-
fired subcategory units).
OR.................. OR
Total HAP metals.... 2.0E-4 lb/MWh.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 1.0E-2 lb/GWh.
Arsenic, As...... 3.0E-3 lb/GWh.
Beryllium, Be.... 5.0E-4 lb/GWh.
Cadmium, Cd...... 2.0E-4 lb/GWh.
Chromium, Cr..... 2.0E-2 lb/GWh.
Cobalt, Co....... 3.0E-2 lb/GWh.
Lead, Pb......... 8.0E-3 lb/GWh.
Manganese, Mn.... 2.0E-2 lb/GWh.
Nickel, Ni....... 9.0E-2 lb/GWh.
Selenium, Se..... 2.0E-2 lb/GWh.
Hg............... 1.0E-4 lb/GWh.
b. HCl.............. 4.0E-4 lb/MWh.
c. HF............... 4.0E-4 lb/MWh.
5. Liquid oil-fired unit-- a. fPM.............. 2.0E-1 lb/MWh.
non-continental (excluding
limited-use liquid oil-
fired subcategory units).
OR.................. OR
Total HAP metals.... 7.0E-3 lb/MWh.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 8.0E-3 lb/GWh.
Arsenic, As...... 6.0E-2 lb/GWh.
[[Page 2685]]
Beryllium, Be.... 2.0E-3 lb/GWh.
Cadmium, Cd...... 2.0E-3 lb/GWh.
Chromium, Cr..... 2.0E-2 lb/GWh.
Cobalt, Co....... 3.0E-1 lb/GWh.
Lead, Pb......... 3.0E-2 lb/GWh.
Manganese, Mn.... 1.0E-1 lb/GWh.
Nickel, Ni....... 4.1 lb/GWh.
Selenium, Se..... 2.0E-2 lb/GWh.
Hg............... 4.0E-4 lb/GWh.
b. HCl.............. 2.0E-3 lb/MWh.
c. HF............... 5.0E-4 lb/MWh.
6. Solid oil-derived fuel- a. fPM.............. 3.0E-2 lb/MWh.
fired unit.
OR.................. OR
Total non-Hg HAP 6.0E-1 lb/GWh.
metals.
OR.................. OR
Individual HAP ....................
metals:
Antimony, Sb..... 8.0E-3 lb/GWh.
Arsenic, As...... 3.0E-3 lb/GWh.
Beryllium, Be.... 6.0E-4 lb/GWh.
Cadmium, Cd...... 7.0E-4 lb/GWh.
Chromium, Cr..... 6.0E-3 lb/GWh.
Cobalt, Co....... 2.0E-3 lb/GWh.
Lead, Pb......... 2.0E-2 lb/GWh.
Manganese, Mn.... 7.0E-3 lb/GWh.
Nickel, Ni....... 4.0E-2 lb/GWh.
Selenium, Se..... 6.0E-3 lb/GWh.
b. HCl.............. 4.0E-4 lb/MWh.
OR.................. OR
SO2 \2\............. 1.0 lb/MWh.
c. Hg............... 2.0E-3 lb/GWh.
------------------------------------------------------------------------
\1\ Units of emission limits:
lb/MWh = pounds pollutant per megawatt-hour electric output (gross); and
lb/GWh = pounds pollutant per gigawatt-hour electric output (gross).
\2\ Alternate SO2 limit may be used if the EGU has some form of FGD
system (or, in the case of IGCC EGUs, some other acid gas removal
system either upstream or downstream of the combined cycle block) and
SO2 CEMS installed.
\3\ Duct burners on syngas; gross output.
\4\ Duct burners on natural gas; gross output.
C. What data collection activities were conducted to support this
action?
The EPA did not issue a new information collection request (ICR) to
affected coal- and oil-fired EGUs to obtain the data used to support
this action, but did use some information from the 2010 ICR which
collected data during development of the MATS rule. The data and data
sources used to conduct the residual risk assessment and technology
review for the Coal- and Oil-Fired EGU source category are described
below in section IV.D of this preamble.
D. What other relevant background information and data are available?
The EPA used multiple sources of information to support this
proposed action. A comprehensive list of facilities and EGUs that are
subject to the MATS rule was compiled primarily using publicly
available information reported to the EPA and information contained in
the Agency's National Electric Energy Data System (NEEDS) database.\22\
Affected sources are required to use the 40 CFR part 75-based ECMPS
\23\ for reporting emissions and related data either directly for EGUs
that use Hg, HCl, HF, or SO2 CEMS or Hg sorbent traps for
compliance purposes or indirectly as PDF files for EGUs that use
performance test results, PM continuous parameter monitoring system
(CPMS) data, or PM CEMS for compliance purposes. Directly submitted
data are maintained in ECMPS; indirectly submitted data are maintained
in WebFIRE.\24\ The NEEDS database contains generation unit information
used in the Agency's power sector modeling. Other sources used to
refine the facility list included an EPA technical support document
that contained a list of potentially affected EGUs in U.S.
territories,\25\ the U.S. Department of Energy's Energy Information
Administration's (EIA's) list of existing generators that reported for
2016 under Form EIA-860,\26\ and the list of coal-fired EGUs included
in a June 2018 Electric Power Research Institute (EPRI) technical
report that summarizes EPRI's evaluation of HAP emissions and their
associated inhalation health risks from coal-fired power plants after
implementation of MATS.\27\ As of early 2018, we estimate
[[Page 2686]]
that there are 713 existing coal- and oil-fired EGUs located at 323
facilities that are subject to 40 CFR part 63, subpart UUUUU.
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\22\ See https://www.epa.gov/airmarkets/power-sector-modeling-platform-v515.
\23\ See https://ampd.epa.gov/ampd/.
\24\ See https://cfpub.epa.gov/webfire; https://www.epa.gov/electronic-reporting-air-emissions/webfire.
\25\ U.S. EPA, October 2014. Technical Support Document for
Calculating Carbon Pollution Goals for Existing Power Plants in
Territories and Areas of Indian Country. Available at https://archive.epa.gov/epa/sites/production/files/2014-10/documents/20141028tsd-supplemental-proposal.pdf.
\26\ See https://www.eia.gov/electricity/data/eia860/.
\27\ EPRI. June 8, 2018. Hazardous Air Pollutants (HAPs)
Emission Estimates and Inhalation Human Health Risk Assessment for
U.S. Coal-Fired Electric Generating Units: 2017 Base Year Post-MATS
Evaluation. Available at https://www.epri.com/#/pages/product/3002013577/?lang=en. Note: There is a companion June 22, 2018 EPRI
technical report, Multi-Pathway Human Health Risk Assessment for
Coal-Fired Power Plants, that describes EPRI's multi-pathway human
health assessment of HAP emissions from five coal-fired electric
facilities based on 2017 configurations (available at https://www.epri.com/#/pages/product/3002013523/?lang=en).
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In developing the RTR emissions dataset for the risk review, the
primary sources used to estimate annual HAP emissions were the
emissions data as reported to the ECMPS and WebFIRE databases by
facilities with affected EGUs. Emissions release point parameters and
locations for each EGU were primarily based on information reported to
the ECMPS and generator-level specific information about existing
generators and their associated environmental equipment that is
collected by the EIA under Form EIA-860. The EPA sources of information
that were used to supplement the ECMPS, WebFIRE, and EIA data include
emissions information collected through the 2010 ICR during development
of the MATS rule and the 2014 National Emissions Inventory (NEI)
database. The NEI is a database that contains information about sources
that emit criteria air pollutants, their precursors, and HAP. The
database includes estimates of annual air pollutant emissions from
point, nonpoint, and mobile sources in the 50 states, the District of
Columbia, Puerto Rico, and the Virgin Islands. The EPA collects this
information and releases an updated version of the NEI database every 3
years. The NEI includes information necessary for conducting risk
modeling, including annual HAP emissions estimates from individual
emission points at facilities and the related emissions release
parameters. The June 2018 EPRI technical report was also used as a
source of supplemental information.
In conducting the technology review, the EPA examined information
submitted to the EPA's ECMPS as well as information that supports
previous 40 CFR part 63, subpart UUUUU actions to identify technologies
currently being used by affected EGUs and determine if there have been
developments in practices, processes, or control technologies. In
addition to the ECMPS data, we reviewed regulatory actions for similar
combustion sources and conducted a review of literature published by
industry organizations, technical journals, and government
organizations.
V. RTR Analytical Procedures and Decision-Making
In this section, we describe the analyses performed to support the
proposed decisions for the RTR and other issues addressed in this
proposal.
A. How do we consider risk in our decision-making?
As discussed in section IV.A of this preamble and in the Benzene
NESHAP, in evaluating and developing standards under CAA section
112(f)(2), we apply a two-step approach to determine whether or not
risks are acceptable and to determine if the standards provide an ample
margin of safety to protect public health. As explained in the Benzene
NESHAP, ``the first step judgment on acceptability cannot be reduced to
any single factor'' and, thus, ``[t]he Administrator believes that the
acceptability of risk under section 112 is best judged on the basis of
a broad set of health risk measures and information.'' 54 FR 38046,
September 14, 1989. Similarly, with regard to the ample margin of
safety determination, ``the Agency again considers all of the health
risk and other health information considered in the first step. Beyond
that information, additional factors relating to the appropriate level
of control will also be considered, including cost and economic impacts
of controls, technological feasibility, uncertainties, and any other
relevant factors.'' Id.
The Benzene NESHAP approach provides flexibility regarding factors
the EPA may consider in making determinations and how the EPA may weigh
those factors for each source category. The EPA conducts a risk
assessment that provides estimates of the MIR posed by the HAP
emissions from each source in the source category, the hazard index
(HI) for chronic exposures to HAP with the potential to cause noncancer
health effects, and the hazard quotient (HQ) for acute exposures to HAP
with the potential to cause noncancer health effects.\28\ The
assessment also provides estimates of the distribution of cancer risk
within the exposed populations, cancer incidence, and an evaluation of
the potential for an adverse environmental effect. The scope of the
EPA's risk analysis is consistent with the EPA's response to comments
on our policy under the Benzene NESHAP where the EPA explained that:
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\28\ The MIR is defined as the cancer risk associated with a
lifetime of exposure at the highest concentration of HAP where
people are likely to live. The HQ is the ratio of the potential
exposure to the HAP to the level at or below which no adverse
chronic noncancer effects are expected; the HI is the sum of HQs for
HAP that affect the same target organ or organ system.
[t]he policy chosen by the Administrator permits consideration of
multiple measures of health risk. Not only can the MIR figure be
considered, but also incidence, the presence of non-cancer health
effects, and the uncertainties of the risk estimates. In this way,
the effect on the most exposed individuals can be reviewed as well
as the impact on the general public. These factors can then be
weighed in each individual case. This approach complies with the
Vinyl Chloride mandate that the Administrator ascertain an
acceptable level of risk to the public by employing his expertise to
assess available data. It also complies with the Congressional
intent behind the CAA, which did not exclude the use of any
particular measure of public health risk from the the EPA's
consideration with respect to CAA section 112 regulations, and
thereby implicitly permits consideration of any and all measures of
health risk which the Administrator, in his judgment, believes are
---------------------------------------------------------------------------
appropriate to determining what will `protect the public health'.
See 54 FR 38057, September 14, 1989. Thus, the level of the MIR is only
one factor to be weighed in determining acceptability of risk. The
Benzene NESHAP explained that ``an MIR of approximately one in 10
thousand should ordinarily be the upper end of the range of
acceptability. As risks increase above this benchmark, they become
presumptively less acceptable under CAA section 112, and would be
weighed with the other health risk measures and information in making
an overall judgment on acceptability. Or, the Agency may find, in a
particular case, that a risk that includes an MIR less than the
presumptively acceptable level is unacceptable in the light of other
health risk factors.'' Id. at 38045. Similarly, with regard to the
ample margin of safety analysis, the EPA stated in the Benzene NESHAP
that: ``EPA believes the relative weight of the many factors that can
be considered in selecting an ample margin of safety can only be
determined for each specific source category. This occurs mainly
because technological and economic factors (along with the health-
related factors) vary from source category to source category.'' Id. at
38061. We also consider the uncertainties associated with the various
risk analyses, as discussed earlier in this preamble, in our
determinations of acceptability and ample margin of safety.
The EPA notes that it has not considered certain health information
to date in making residual risk determinations. At this time, we do not
attempt to quantify the HAP risk that may be associated with emissions
from other facilities that do not include the
[[Page 2687]]
source category under review, mobile source emissions, natural source
emissions, persistent environmental pollution, or atmospheric
transformation in the vicinity of the sources in the category.
The EPA understands the potential importance of considering an
individual's total exposure to HAP in addition to considering exposure
to HAP emissions from the source category and facility. We recognize
that such consideration may be particularly important when assessing
noncancer risk, where pollutant-specific exposure health reference
levels (e.g., reference concentrations (RfCs)) are based on the
assumption that thresholds exist for adverse health effects. For
example, the EPA recognizes that, although exposures attributable to
emissions from a source category or facility alone may not indicate the
potential for increased risk of adverse noncancer health effects in a
population, the exposures resulting from emissions from the facility in
combination with emissions from all of the other sources (e.g., other
facilities) to which an individual is exposed may be sufficient to
result in an increased risk of adverse noncancer health effects. In May
2010, the Science Advisory Board (SAB) advised the EPA ``that RTR
assessments will be most useful to decision makers and communities if
results are presented in the broader context of aggregate and
cumulative risks, including background concentrations and contributions
from other sources in the area.'' \29\
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\29\ Recommendations of the SAB RTR Panel are provided in their
report, which is available at https://yosemite.epa.gov/sab/
sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA-SAB-10-
007-unsigned.pdf.
---------------------------------------------------------------------------
In response to the SAB recommendations, the EPA incorporates
cumulative risk analyses into its RTR risk assessments, including those
reflected in this proposal. The Agency (1) conducts facility-wide
assessments, which include source category emission points, as well as
other emission points within the facilities; (2) combines exposures
from multiple sources in the same category that could affect the same
individuals; and (3) for some persistent and bioaccumulative
pollutants, analyzes the ingestion route of exposure. In addition, the
RTR risk assessments consider aggregate cancer risk from all
carcinogens and aggregated noncancer HQs for all noncarcinogens
affecting the same target organ or target organ system.
Although we are interested in placing source category and facility-
wide HAP risk in the context of total HAP risk from all sources
combined in the vicinity of each source, we are concerned about the
uncertainties of doing so. Estimates of total HAP risk from emission
sources other than those that we have studied in depth during this RTR
review would have significantly greater associated uncertainties than
the source category or facility-wide estimates. Such aggregate or
cumulative assessments would compound those uncertainties, making the
assessments too unreliable.
B. How do we perform the technology review?
Our technology review focuses on the identification and evaluation
of developments in practices, processes, and control technologies that
have occurred since the MACT standards were promulgated. Where we
identify such developments, we analyze their technical feasibility,
estimated costs, energy implications, and non-air environmental
impacts. We also consider the emission reductions associated with
applying each development. This analysis informs our decision of
whether it is ``necessary'' to revise the emissions standards. In
addition, we consider the appropriateness of applying controls to new
sources versus retrofitting existing sources. For this exercise, we
consider any of the following to be a ``development'':
Any add-on control technology or other equipment that
was not identified and considered during development of the original
MACT standards;
Any improvements in add-on control technology or other
equipment (that were identified and considered during development of
the original MACT standards) that could result in additional
emissions reduction;
Any work practice or operational procedure that was not
identified or considered during development of the original MACT
standards;
Any process change or pollution prevention alternative
that could be broadly applied to the industry and that was not
identified or considered during development of the original MACT
standards; and
Any significant changes in the cost (including cost
effectiveness) of applying controls (including controls the EPA
considered during the development of the original MACT standards).
In addition to reviewing the practices, processes, and control
technologies that were considered at the time we originally developed
(or last updated) the NESHAP, we review a variety of data sources in
our investigation of potential practices, processes, or controls to
consider. See sections IV.C and IV. D of this preamble for information
on the specific data sources that were reviewed as part of the
technology review.
C. How do we estimate post-MACT risk posed by the source category?
In this section, we provide a complete description of the types of
analyses that we generally perform during the risk assessment process.
In some cases, we do not perform a specific analysis because it is not
relevant. For example, in the absence of emissions of HAP known to be
persistent and bioaccumulative in the environment (PB-HAP), we would
not perform a multipathway exposure assessment. Where we do not perform
an analysis, we state that we do not and provide the reason. While we
present all of our risk assessment methods, we only present risk
assessment results for the analyses actually conducted (see section
VI.B of this preamble).
The EPA conducts a risk assessment that provides estimates of the
MIR for cancer posed by the HAP emissions from each source in the
source category, the HI for chronic exposures to HAP with the potential
to cause noncancer health effects, and the HQ for acute exposures to
HAP with the potential to cause noncancer health effects. The
assessment also provides estimates of the distribution of cancer risk
within the exposed populations, cancer incidence, and an evaluation of
the potential for an adverse environmental effect. The seven sections
that follow this paragraph describe how we estimated emissions and
conducted the risk assessment. The docket for this rulemaking contains
the following document which provides more information on the risk
assessment inputs and models: Residual Risk Assessment for the Coal-
and Oil-Fired EGU Source Category in Support of the 2019 Risk and
Technology Review Proposed Rule (risk document). The methods used to
assess risk (as described in the seven primary steps below) are
consistent with those described by the EPA in the document reviewed by
a panel of the EPA's SAB in 2009;\30\ and described in the SAB review
report issued in 2010. They are also consistent with the key
recommendations contained in that report.
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\30\ U.S. EPA. June 2009. Risk and Technology Review (RTR) Risk
Assessment Methodologies: For Review by the EPA's Science Advisory
Board with Case Studies--MACT I Petroleum Refining Sources and
Portland Cement Manufacturing (EPA-452/R-09-006). Available at
https://www3.epa.gov/airtoxics/rrisk/rtrpg.html.
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[[Page 2688]]
1. How did we estimate actual emissions and identify the emissions
release characteristics?
Data for existing EGUs were used to create the RTR emissions
dataset for the risk review as described in section IV.D of this
preamble. The RTR emissions dataset includes information for 608
emission release points (i.e., stacks). Because in some cases multiple
EGUs are routed to a single stack or a single EGU is routed to two
stacks, the number of stacks is not the same as the number of EGUs. The
MATS rule regulates emissions of HAP in four pollutant categories: Hg,
non-Hg metals, acid gases, and organics. As described in section IV.B
of this preamble, EGUs in six subcategories are subject to numeric
emission limits for specific HAP, or surrogates for those HAP, in the
three pollutant categories of Hg, non-Hg metals, and acid gases. EGUs
are not required to meet numeric emission limits for organic HAP or to
test and report organic HAP emissions. During the 2010 ICR effort of
the original MATS rulemaking process, most of the organic HAP emissions
data for EGUs were at or below the detection levels of the prescribed
test methods, even when long duration test runs (i.e., approximately 8
hours) were required. In developing the RTR emissions dataset, the EPA
reviewed the available organic HAP test results from the 2010 ICR. For
each organic HAP tested, if 40 percent or more of the available test
data were above test method detection limits, emissions estimates for
that HAP were included in the modeling file. Emissions of the following
HAP in each of the four pollutant categories were estimated for each
emission release point and included in the RTR emissions dataset:
Hg: elemental gaseous Hg, gaseous divalent Hg,
particulate divalent Hg;
Non-Hg metals: antimony, arsenic, beryllium, cadmium,
hexavalent chromium, trivalent chromium, cobalt, lead, manganese,
nickel, selenium;
Acid gases: HCl, HF; and
Organics: formaldehyde, naphthalene, 2-
methylnaphthalene, phenanthrene, two dioxin congeners, three furan
congeners, and seven polychlorinated biphenyls congeners.
As explained in section IV.D of this preamble, emissions estimates
for the RTR emissions dataset were based primarily on data submitted
via the EPA's ECMPS by facilities with affected EGUs. Calendar year
2017 data were used where available because all affected EGUs subject
to numeric emission limits would be required to submit compliance data
by then. Where calendar year 2017 data were not available, the most
recent data available were used. CEMS emissions data for Hg, HCl, and
SO2 reported to the EPA's ECMPS were available as 2017
actual annual values (i.e., pounds per year or tpy).
Some emissions data for Hg, non-Hg HAP metals, HCl, and fPM was
submitted to the EPA's ECMPS, but maintained in the WebFIRE database.
For those sources, the EPA extracted data associated with operations in
summer 2017, when EGUs would be expected to operate more frequently
given increased demand for electricity, and used those summertime
emissions to estimate annual emissions of the pollutants of interest.
Specifically, test averages from third quarter performance stack tests
(i.e., conducted between July and September 2017) for any pollutant and
30-day rolling average values as of June 30, 2017, for PM CEMS and PM
CPMS were extracted and then converted from pounds of pollutant per
million British thermal units or trillion British thermal units (lb/
MMBtu or lb/TBtu) or pounds of pollutant per megawatt-hour or gigawatt-
hour (lb/MWh or lb/GWh) to actual annual emissions using 2017 total
heat input (MMBtu) or total gross load (MWh) values, as appropriate.
When ECMPS-submitted data for HAP in the RTR emissions dataset were not
available, actual annual emissions estimates were based on data from
the 2014 NEI and the June 2018 EPRI technical report. Some annual
emissions estimates were also generated using the ratio of non-Hg
metals to fPM and acid gases to SO2 from the 2010 ICR in
conjunction with more recent fPM or SO2 emissions data.
Emissions data from the 2010 ICR were used to develop emission factors
for the non-Hg metals and acid gases included in the RTR emissions
dataset and to develop ratios based on each of those emission factors
divided by average fPM or SO2 values, respectively.
Emissions data for EGUs no longer operating were excluded in the
calculation of emission factors or average fPM or SO2
values. In addition, we included in each emission factor and ratio
calculation only the 2010 ICR data for EGUs where data for both the
non-Hg metal HAP (e.g., antimony) and fPM, or the acid gas HAP (e.g.,
HCl) and SO2, were available. Emission factors and emission
factor-based ratios were developed for the various combinations of fuel
types and emissions control device types. Actual annual HAP-specific
emissions for each stack were then estimated by multiplying each
emission factor-based ratio by the most recent fPM or SO2
annual emissions value (e.g., 2017 ECMPS or WebFIRE data or 2014 NEI
data). Because EGUs in the subcategory of limited-use liquid oil-fired
EGUs are not subject to any numeric emission limits, actual annual HAP-
specific emissions were estimated using 2014 NEI data or emission
factor-based ratios along with 2014 NEI data for PM and SO2.
Development of the emission factors and emission factor-based ratios is
explained in the memorandum, Emission Factor Development for RTR Risk
Modeling Dataset for Coal- and Oil-fired EGUs, which is available in
the docket for this action.
The majority of the total (i.e., non-speciated) Hg actual annual
emissions estimates were based on data maintained in the EPA's ECMPS
for CEMS data or sorbent traps or in WebFIRE for performance stack
tests along with 2017 total heat input or total gross load values, as
appropriate. Where such data were not available, total Hg actual annual
emissions were estimated using the 2014 NEI or the June 2018 EPRI
technical report. For a small number of oil-fired EGUs, EPA-developed
emission factors and emission factor-based ratios were used to estimate
total Hg actual annual emissions. Hg emissions were modeled as three
different species: elemental gaseous Hg, gaseous divalent Hg, and
particulate divalent Hg. The EPA utilized Hg speciation factors--
percentages based on fuel type and installed emissions control
equipment--that were updated versions of those that had been used in
the development of the MATS rule.\31\ Total Hg emissions were then
multiplied by the factors to develop the speciated Hg actual annual
emissions estimates.
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\31\ See Attachment E of the Risk Modeling Dataset Memo for the
list of Hg speciation factors utilized in compiling the RTR
emissions dataset for the risk review, available in the docket for
this action. See Appendix G of the Technical Support Document for
the Proposed Rule Emissions Inventories (available in the rulemaking
docket at EPA-HQ-OAR-2009-0234-19908) for Hg speciation factors used
in the development of MATS.
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For the several EGUs that submitted individual non-Hg HAP metals
data to the EPA, actual annual emissions were estimated using the stack
test values maintained in WebFIRE and 2017 total heat input or total
gross load values, as appropriate. The majority of the non-Hg HAP
metals actual annual emissions estimates were based on emission factor-
based ratios for non-Hg HAP metals and fPM annual emissions values.
Chromium emissions were modeled as hexavalent chromium (Cr(VI)) and
trivalent chromium (Cr(III)). Actual annual emissions of Cr(VI) and
Cr(III) were estimated by multiplying total chromium emissions by the
[[Page 2689]]
speciation factors for coal or oil, as appropriate.
Actual annual emissions estimates for HCl for EGUs that submitted
data to the EPA's ECMPS were based on those ECMPS CEMS data or WebFIRE
performance stack test data and 2017 total heat input or total gross
load values, as appropriate. Where acid gas HAP data were not available
in the WebFIRE database, but SO2 data were available in the
ECMPS for requirements other than those in the MATS rule (e.g., the
acid rain rule), emission factor-based ratios for the acid gas HAP
(i.e., HCl and HF) and SO2 annual emissions values were used
to estimate actual annual HCl and HF emissions. In some instances,
actual annual HCl and HF emissions were estimated based on emission
factor-based ratios and 2014 NEI data for SO2. In a small
number of other instances, actual annual HCl and HF emissions were
estimated using the June 2018 EPRI technical report.
As previously explained, EGUs are not required to meet numeric
emission limits for organic HAP or to test and report organic HAP
emissions. Actual annual emissions for the 16 organic HAP included in
the RTR emissions dataset are based on EPA-developed representative
detection level (RDL) equivalent emissions values (lb/MMBtu) based on
fuel type. RDL equivalent emissions values for 15 of the organic HAP
are based on the averages of better-performing unit method detection
levels across many source categories. Because we did not have an RDL
analysis across source categories for formaldehyde, detection levels
from the 2010 ICR data were used to develop the RDL equivalent
emissions value for formaldehyde. Actual annual emissions of the 16
organic HAP were estimated by multiplying the RDL equivalent emissions
values by 2017 total heat input. Development of the RDL equivalent
emissions values is explained in the memorandum, Development of
Representative Detection Levels of Certain Organic HAP Expressed as
Pounds per Million British Thermal Units of Fuel Input for RTR Risk
Modeling Dataset for Coal- and Oil-fired EGUs, which is available in
the docket for this action.
Stack parameter values and locations for each emissions release
point included in the RTR emissions dataset were primarily based on
information reported to the ECMPS and generator-level specific
information about existing generators and their associated
environmental equipment that is collected under Form EIA-860.
Specifically, the ECMPS was the primary source for stack height,
diameter, and latitude/longitude coordinates, and the EIA-860 database
was the primary source for stack temperature, velocity, and flow rate.
Other sources of information that were used to fill gaps in the site-
specific emissions release point data included the 2014 NEI, parameters
from similar stacks at a specific facility, and default parameter
values based on MACT source category 2014 NEI information.
The RTR emissions dataset was refined as necessary following a
quality assurance check of source locations, emissions release
characteristics, and annual emissions estimates. Latitude and longitude
coordinates were checked using Google Earth[supreg] to ensure that
stack locations were correct. Stack parameters were checked to ensure
that they were within acceptable quality assurance range check
boundaries. Emissions estimates were reviewed for completeness and
accuracy. Additional details on the data and methods used to develop
``actual'' emissions estimates for the RTR emissions dataset are
provided in the memorandum, Development of the RTR Risk Modeling
Dataset for the Coal- and Oil-Fired EGU Source Category (Risk Modeling
Dataset Memo), included as Appendix 1 of the risk document, which is
available in the docket for this action.
A comparison of the actual annual HAP emissions in 2017 to the
annual HAP emissions prior to promulgation of the MATS rule shows a 96-
percent reduction in total HAP emissions from coal- and oil-fired EGUs.
The actual emissions from coal- and oil-fired EGUs for 2017 and
estimated emissions from 2010 are shown in Table 4. Estimates of pre-
MATS emissions of organic HAP were not available. As discussed
previously in this section, the 2017 emissions of organic HAP are based
on RDL equivalent emissions values; the actual 2017 emissions are
likely lower than the estimate of 3 tpy.
Table 4--HAP Emissions From Coal- and Oil-Fired EGUs Pre- and Post-MATS
----------------------------------------------------------------------------------------------------------------
2010 Emissions 2017 Emissions
Pollutant (tons) \32\ (tons) Reduction (%)
----------------------------------------------------------------------------------------------------------------
Hg.............................................................. 29 4 86
Acid Gases...................................................... 125,708 4,831 96
Non-Hg Metals................................................... 1,170 221 81
Organic HAP..................................................... * <3 *
-----------------------------------------------
Total....................................................... 126,907 5,059 96
----------------------------------------------------------------------------------------------------------------
Note: The compliance date for the vast majority of affected EGUs was on or before April 16, 2016.
* Not available.
2. How did we estimate MACT-allowable emissions?
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\32\ Memorandum: Emissions Overview: Hazardous Air Pollutants in
Support of the Final Mercury and Air Toxics Standard. EPA-454/R-11-
014. November 2011; Docket ID No. EPA-HQ-OAR-2009-0234-19914.
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The available emissions data in the RTR emissions dataset include
estimates of the mass of HAP emitted during a specified annual time
period. These ``actual'' emission levels are often lower than the
emission levels allowed under the requirements of the current MACT
standards. The emissions allowed under the MACT standards are referred
to as the ``MACT-allowable'' emissions. We discussed the consideration
of both MACT-allowable and actual emissions in the final Coke Oven
Batteries RTR (70 FR 19998-19999, April 15, 2005) and in the proposed
and final Hazardous Organic NESHAP RTR (71 FR 34428, June 14, 2006, and
71 FR 76609, December 21, 2006, respectively). In those actions, we
noted that assessing the risk at the MACT-allowable level is inherently
reasonable since that risk reflects the maximum level facilities could
emit and still comply with national emission standards. We also
explained that it is reasonable to consider actual emissions, where
such data are available, in both steps of the risk analysis, in
accordance with the Benzene NESHAP approach. (54 FR 38044, September
14, 1989.)
[[Page 2690]]
MACT-allowable annual emissions of Hg, non-Hg HAP metals, and acid
gas HAP were estimated using numeric emission limits for existing
sources in the MATS rule along with 2017 total heat input. For Hg,
allowable annual emissions of total Hg were estimated by multiplying
subcategory-specific Hg emission limits by 2017 total heat input.
Allowable annual emissions of elemental gaseous Hg, gaseous divalent
Hg, and particulate divalent Hg were estimated by multiplying annual
emissions of total Hg by EPA-developed Hg speciation factors which are
based on fuel type and emissions control device type.
With regard to non-Hg HAP metals, performance stack test data in
almost all instances was for fPM, a surrogate for non-Hg HAP metals,
and, as such, allowable annual emissions were estimated using the MATS
rule's fPM emission limits. Specifically, allowable annual emissions of
the non-Hg HAP metals were estimated by multiplying subcategory-based
fPM emission limits by 2017 total heat input and by the emission
factor-based ratios for non-Hg HAP metals that were calculated by the
EPA. Allowable annual emissions of chromium as Cr(VI) and Cr(III) were
estimated by multiplying the total chromium allowable emissions
estimates by the chromium speciation factors for coal or oil, as
appropriate.
For acid gas HAP, allowable annual emissions of HCl and HF from
oil-fired EGUs were estimated by multiplying subcategory-specific HCl
and HF emission limits by 2017 total heat input. With regard to acid
gas HAP for coal-fired EGUs, some coal-fired sources submitted data for
HCl, a surrogate for acid gas HAP, whereas other sources submitted data
for SO2, a surrogate for acid gas HAP for certain coal-fired
EGUs. Allowable annual emissions of HCl and HF from coal-fired EGUs
were estimated two different ways--one based on the MATS rule's HCl
emission limits and HF actual emissions adjusted using an HCl emissions
ratio and the other based on the MATS rule's SO2 emission
limits and emission factor-based ratios--and the more conservative
estimate was used. In the first approach, allowable annual emissions of
HCl were estimated by multiplying subcategory-specific HCl emission
limits by 2017 total heat input, and allowable annual emissions of HF
were estimated by multiplying actual annual emissions of HF by a ratio
of HCl allowable annual emissions to HCl actual annual emissions. In
the second approach, allowable annual emissions of HCl and HF were
estimated by multiplying subcategory-based SO2 emission
limits by 2017 total heat input and by the emission factor-based ratios
for HCl and HF that were calculated by the EPA.
Because there are no numeric emission limits for organic HAP,
allowable annual emissions for the 16 organic HAP were assumed equal to
the actual annual emissions estimates for the 16 organic HAP. The Risk
Modeling Dataset Memo, available in the docket for this action,
contains additional information on the development of estimated MACT-
allowable emissions.
3. How do we conduct dispersion modeling, determine inhalation
exposures, and estimate individual and population inhalation risk?
Both long-term and short-term inhalation exposure concentrations
and health risk from the source category addressed in this proposal
were estimated using the Human Exposure Model (HEM-3).\33\ The HEM-3
performs three primary risk assessment activities: (1) Conducting
dispersion modeling to estimate the concentrations of HAP in ambient
air, (2) estimating long-term and short-term inhalation exposures to
individuals residing within 50 kilometers (km) of the modeled sources,
and (3) estimating individual and population-level inhalation risk
using the exposure estimates and quantitative dose-response
information.
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\33\ For more information about HEM-3, go to https://www.epa.gov/fera/risk-assessment-and-modeling-human-exposure-model-hem.
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a. Dispersion Modeling
The air dispersion model AERMOD, used by the HEM-3 model, is one of
the EPA's preferred models for assessing air pollutant concentrations
from industrial facilities.\34\ To perform the dispersion modeling and
to develop the preliminary risk estimates, HEM-3 draws on three data
libraries. The first is a library of meteorological data, which is used
for dispersion calculations. This library includes 1 year (2016) of
hourly surface and upper air observations from 824 meteorological
stations, selected to provide coverage of the United States and Puerto
Rico. A second library of United States Census Bureau census block\35\
internal point locations and populations provides the basis of human
exposure calculations (U.S. Census, 2010). In addition, for each census
block, the census library includes the elevation and controlling hill
height, which are also used in dispersion calculations. A third library
of pollutant-specific dose-response values is used to estimate health
risk. These are discussed below.
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\34\ U.S. EPA. Revision to the Guideline on Air Quality Models:
Adoption of a Preferred General Purpose (Flat and Complex Terrain)
Dispersion Model and Other Revisions (70 FR 68218, November 9,
2005).
\35\ A census block is the smallest geographic area for which
census statistics are tabulated.
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b. Risk From Chronic Exposure to HAP
In developing the risk assessment for chronic exposures, we use the
estimated annual average ambient air concentrations of each HAP emitted
by each source in the source category. The HAP air concentrations at
each nearby census block centroid located within 50 km of the facility
are a surrogate for the chronic inhalation exposure concentration for
all the people who reside in that census block. A distance of 50 km is
consistent with both the analysis supporting the 1989 Benzene NESHAP
(54 FR 38044, September 14, 1989) and the limitations of Gaussian
dispersion models, including AERMOD.
For each facility, we calculate the MIR as the cancer risk
associated with a continuous lifetime (24 hours per day, 7 days per
week, 52 weeks per year, 70 years) exposure to the maximum
concentration at the centroid of each inhabited census block. We
calculate individual cancer risk by multiplying the estimated lifetime
exposure to the ambient concentration of each HAP (in micrograms per
cubic meter ([mu]g/m\3\)) by its unit risk estimate (URE). The URE is
an upper-bound estimate of an individual's incremental risk of
contracting cancer over a lifetime of exposure to a concentration of 1
microgram of the pollutant per cubic meter of air. For residual risk
assessments, we generally use UREs from the EPA's Integrated Risk
Information System (IRIS). For carcinogenic pollutants without IRIS
values, we look to other reputable sources of cancer dose-response
values, often using California EPA (CalEPA) UREs, where available. In
cases where new, scientifically credible dose-response values have been
developed in a manner consistent with EPA guidelines and have undergone
a peer review process similar to that used by the EPA, we may use such
dose-response values in place of, or in addition to, other values, if
appropriate. The pollutant-specific dose-response values used to
estimate health risk are available at https://www.epa.gov/fera/dose-response-assessment-assessing-health-risks-associated-exposure-hazardous-air-pollutants.To estimate individual lifetime cancer risks
associated with exposure to HAP emissions from each facility in the
source category, we sum the risks for
[[Page 2691]]
each of the carcinogenic HAP \36\ emitted by the modeled facility. We
estimate cancer risk at every census block within 50 km of every
facility in the source category. The MIR is the highest individual
lifetime cancer risk estimated for any of those census blocks. In
addition to calculating the MIR, we estimate the distribution of
individual cancer risks for the source category by summing the number
of individuals within 50 km of the sources whose estimated risk falls
within a specified risk range. We also estimate annual cancer incidence
by multiplying the estimated lifetime cancer risk at each census block
by the number of people residing in that block, summing results for all
of the census blocks, and then dividing this result by a 70-year
lifetime.
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\36\ The EPA's 2005 Guidelines for Carcinogen Risk Assessment
classifies carcinogens as: ``carcinogenic to humans,'' ``likely to
be carcinogenic to humans,'' and ``suggestive evidence of
carcinogenic potential.'' These classifications also coincide with
the terms ``known carcinogen, probable carcinogen, and possible
carcinogen,'' respectively, which are the terms advocated in the
EPA's Guidelines for Carcinogen Risk Assessment, published in 1986
(51 FR 33992, September 24, 1986). In August 2000, the document,
Supplemental Guidance for Conducting Health Risk Assessment of
Chemical Mixtures (EPA/630/R-00/002), was published as a supplement
to the 1986 document. Copies of both documents can be obtained from
https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=20533&CFID=70315376&CFTOKEN=71597944. Summing
the risk of these individual compounds to obtain the cumulative
cancer risk is an approach that was recommended by the EPA's SAB in
their 2002 peer review of the EPA's National Air Toxics Assessment
(NATA) titled NATA--Evaluating the National-scale Air Toxics
Assessment 1996 Data--an SAB Advisory, available at https://
yosemite.epa.gov/sab/sabproduct.nsf/
214C6E915BB04E14852570CA007A682C/$File/ecadv02001.pdf.
---------------------------------------------------------------------------
To assess the risk of noncancer health effects from chronic
exposure to HAP, we calculate either an HQ or a target organ-specific
hazard index (TOSHI). We calculate an HQ when a single noncancer HAP is
emitted. Where more than one noncancer HAP is emitted, we sum the HQ
for each of the HAP that affects a common target organ or target organ
system to obtain a TOSHI. The HQ is the estimated exposure divided by
the chronic noncancer dose-response value, which is a value selected
from one of several sources. The preferred chronic noncancer dose-
response value is the EPA RfC, defined as ``an estimate (with
uncertainty spanning perhaps an order of magnitude) of a continuous
inhalation exposure to the human population (including sensitive
subgroups) that is likely to be without an appreciable risk of
deleterious effects during a lifetime'' (https://iaspub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?details=&vocabName=IRIS%20Glossary). In cases where an RfC
from the EPA's IRIS is not available or where the EPA determines that
using a value other than the RfC is appropriate, the chronic noncancer
dose-response value can be a value from the following prioritized
sources, which define their dose-response values similarly to the EPA:
(1) The Agency for Toxic Substances and Disease Registry (ATSDR)
Minimum Risk Level (https://www.atsdr.cdc.gov/mrls/index.asp); (2) the
CalEPA Chronic Reference Exposure Level (REL) (https://oehha.ca.gov/air/crnr/notice-adoption-air-toxics-hot-spots-program-guidance-manual-preparation-health-risk-0); or (3), as noted above, a scientifically
credible dose-response value that has been developed in a manner
consistent with EPA guidelines and has undergone a peer review process
similar to that used by the EPA. The pollutant-specific dose-response
values used to estimate health risks are available at https://www.epa.gov/fera/dose-response-assessment-assessing-health-risks-associated-exposure-hazardous-air-pollutants.
c. Risk From Acute Exposure to HAP That May Cause Health Effects Other
Than Cancer
For each HAP for which appropriate acute inhalation dose-response
values are available, the EPA also assesses the potential health risks
due to acute exposure. For these assessments, the EPA makes
conservative assumptions about emission rates, meteorology, and
exposure location. We use the peak hourly emission rate,\37\ worst-case
dispersion conditions, and, in accordance with our mandate under
section 112 of the CAA, the point of highest off-site exposure to
assess the potential risk to the maximally exposed individual.
---------------------------------------------------------------------------
\37\ In the absence of hourly emission data, we develop
estimates of maximum hourly emission rates by multiplying the
average actual annual emissions rates by a factor (either a
category-specific factor or a default factor of 10) to account for
variability. This is documented in Residual Risk Assessment for
Coal- and Oil-Fired EGU Source Category in Support of the 2019 Risk
and Technology Review Proposed Rule and in Appendix 5 of the report:
Analysis of Data on Short-term Emission Rates Relative to Long-term
Emission Rates. Both are available in the docket for this
rulemaking.
---------------------------------------------------------------------------
To characterize the potential health risks associated with
estimated acute inhalation exposures to a HAP, we generally use
multiple acute dose-response values, including acute RELs, acute
exposure guideline levels (AEGLs), and emergency response planning
guidelines (ERPG) for 1-hour exposure durations, if available, to
calculate acute HQs. The acute HQ is calculated by dividing the
estimated acute exposure by the acute dose-response value. For each HAP
for which acute dose-response values are available, the EPA calculates
acute HQs.
An acute REL is defined as ``the concentration level at or below
which no adverse health effects are anticipated for a specified
exposure duration.'' \38\ Acute RELs are based on the most sensitive,
relevant, adverse health effect reported in the peer-reviewed medical
and toxicological literature. They are designed to protect the most
sensitive individuals, including children and the elderly, in the
population through the inclusion of margins of safety. Because margins
of safety are incorporated to address data gaps and uncertainties,
exceeding the REL does not automatically indicate an adverse health
impact. AEGLs represent threshold exposure limits for the general
public and are applicable to emergency exposures ranging from 10
minutes to 8 hours.\39\ They are guideline levels for ``once-in-a-
lifetime, short-term exposures to airborne concentrations of acutely
toxic, high-priority chemicals.'' Id. at 21. The AEGL-1 is specifically
defined as ``the airborne concentration (expressed as ppm (parts per
million) or mg/m\3\ (milligrams per cubic meter)) of a substance above
which it is predicted that the general population, including
susceptible individuals, could experience notable discomfort,
irritation, or certain asymptomatic nonsensory effects. However, the
effects are not disabling and are transient and reversible upon
cessation of exposure.'' The document also notes that ``Airborne
concentrations below AEGL-1 represent exposure levels that can produce
mild and progressively increasing but transient and nondisabling odor,
taste, and sensory irritation or certain asymptomatic, nonsensory
effects.'' Id. AEGL-2 are defined as ``the airborne
[[Page 2692]]
concentration (expressed as parts per million or milligrams per cubic
meter) of a substance above which it is predicted that the general
population, including susceptible individuals, could experience
irreversible or other serious, long-lasting adverse health effects or
an impaired ability to escape.'' Id.
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\38\ CalEPA issues acute RELs as part of its Air Toxics Hot
Spots Program, and the 1-hour and 8-hour values are documented in
Air Toxics Hot Spots Program Risk Assessment Guidelines, Part I, The
Determination of Acute Reference Exposure Levels for Airborne
Toxicants, which is available at https://oehha.ca.gov/air/general-info/oehha-acute-8-hour-and-chronic-reference-exposure-level-rel-summary.
\39\ National Academy of Sciences, 2001. Standing Operating
Procedures for Developing Acute Exposure Levels for Hazardous
Chemicals, page 2. Available at https://www.epa.gov/sites/production/files/2015-09/documents/sop_final_standing_operating_procedures_2001.pdf. Note that the
National Advisory Committee for Acute Exposure Guideline Levels for
Hazardous Substances ended in October 2011, but the AEGL program
continues to operate at the EPA and works with the National
Academies to publish final AEGLs, (https://www.epa.gov/aegl).
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ERPGs are ``developed for emergency planning and are intended as
health-based guideline concentrations for single exposures to
chemicals.'' \40\ Id. at 1. The ERPG-1 is defined as ``the maximum
airborne concentration below which it is believed that nearly all
individuals could be exposed for up to 1 hour without experiencing
other than mild transient adverse health effects or without perceiving
a clearly defined, objectionable odor.'' Id. at 2. Similarly, the ERPG-
2 is defined as ``the maximum airborne concentration below which it is
believed that nearly all individuals could be exposed for up to one
hour without experiencing or developing irreversible or other serious
health effects or symptoms which could impair an individual's ability
to take protective action.'' Id. at 1.
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\40\ ERPGS Procedures and Responsibilities. March 2014. American
Industrial Hygiene Association. Available at https://www.aiha.org/get-involved/AIHAGuidelineFoundation/EmergencyResponsePlanningGuidelines/Documents/ERPG%20Committee%20Standard%20Operating%20Procedures%20%20-%20March%202014%20Revision%20%28Updated%2010-2-2014%29.pdf.
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An acute REL for 1-hour exposure durations is typically lower than
its corresponding AEGL-1 and ERPG-1. Even though their definitions are
slightly different, AEGL-1s are often the same as the corresponding
ERPG-1s, and AEGL-2s are often equal to ERPG-2s. The maximum HQs from
our acute inhalation screening risk assessment typically result when we
use the acute REL for a HAP. In cases where the maximum acute HQ
exceeds 1, we also report the HQ based on the next highest acute dose-
response value (usually the AEGL-1 and/or the ERPG-1).
For the Coal- and Oil-Fired EGU source category, facility-level
acute factors (i.e., multipliers) developed by the EPA were used to
estimate acute emissions and the potential health risks due to acute
exposure. First, 2017 total heat input (MMBtu) and boiler maximum rated
heat input (MMBtu/hr) data were used to calculate an acute factor for
EGUs where both values were available. Next, facility-level acute
factors were calculated using a heat input-weighted average based on
2017 heat input for each EGU located within a facility fenceline. The
facility-level acute factor was used for each stack at the facility.
For units at facilities that did not have a facility-level factor
(e.g., 2017 total heat input and boiler maximum rated heat input were
not available), a default facility-level value of 6 was used. The
default facility-level value of 6 was developed by taking the average
of the calculated facility-level factors. If the calculated facility-
level acute factor was greater than 10 (e.g., in cases where the EGU
had a low 2017 heat input relative to the maximum rated heat input),
the RTR program default acute emission adjustment factor of 10 was
used. The default emission adjustment factor of 10 reflects a Texas
study of short-term emissions variability, which showed that most peak
emission events in a heavily-industrialized four-county area (Harris,
Galveston, Chambers, and Brazoria Counties, Texas) were less than twice
the annual average hourly emissions rate. The highest peak emissions
event was 74 times the annual average hourly emissions rate and the
99th percentile ratio of peak hourly emissions rate to the annual
average hourly emissions rate was 9.\41\ Considering this analysis, to
account for more than 99 percent of the peak hourly emissions, a
conservative screening multiplication factor of 10 is applied to the
average annual hourly emissions rate in the EPA's acute exposure
screening assessments as the default approach. In this analysis, we
inadvertently used allowable emissions (rather than actual emissions,
which is our standard practice) in conjunction with the facility level
acute factors in our screening assessment of acute risk. Because the
results showed acute risks below a level of concern even with acute
emissions being overstated due to the use of allowable emissions, we
did not correct the analysis and consider it to clearly support the
conclusion that acute risks are below a level of concern as shown in
Table 5 of this preamble. A further discussion of the development of
facility-level acute factors and emissions used to estimate acute
exposure for the risk modeling can be found in the Risk Modeling
Dataset Memo, available in the docket for this rulemaking.
---------------------------------------------------------------------------
\41\ Allen, et al., 2004. Variable Industrial VOC Emissions and
their impact on ozone formation in the Houston Galveston Area. Texas
Environmental Research Consortium. Available at https://www.researchgate.net/publication/237593060_Variable_Industrial_VOC_Emissions_and_their_Impact_on_Ozone_Formation_in_the_Houston_Galveston_Area.
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In our acute inhalation screening risk assessment, acute impacts
are deemed negligible for HAP for which acute HQs are less than or
equal to 1 (even under the conservative assumptions of the screening
assessment), and no further analysis is performed for these HAP. In
cases where an acute HQ from the screening step is greater than 1, we
consider additional site-specific data to develop a more refined
estimate of the potential for acute exposures of concern.
4. How do we conduct the multipathway exposure and risk screening
assessment?
The EPA conducts a tiered screening assessment examining the
potential for significant human health risks due to exposures via
routes other than inhalation (i.e., ingestion). We first determine
whether any sources in the source category emit any PB-HAP, as
identified in the EPA's Air Toxics Risk Assessment Library (See Volume
1, Appendix D, at https://www2.epa.gov/fera/risk-assessment-and-modeling-air-toxics-risk-assessment-reference-library.
For the Coal- and Oil-Fired EGU source category, we identified PB-
HAP emissions of lead compounds, arsenic compounds, Hg compounds,
cadmium compounds, polycyclic organic matter (POM), and dioxins, so we
proceeded to the next step of the evaluation. In this step, we
determine whether the facility-specific emission rates of the emitted
PB-HAP are large enough to create the potential for significant human
health risk through ingestion exposure under reasonable worst-case
conditions. To facilitate this step, we use previously developed
screening threshold emission rates for several PB-HAP that are based on
a hypothetical upper-end screening exposure scenario developed for use
in conjunction with the EPA's Total Risk Integrated Methodology.Fate,
Transport, and Ecological Exposure (TRIM.FaTE) model. The PB-HAP with
screening threshold emission rates are arsenic compounds, cadmium
compounds, chlorinated dibenzodioxins and furans, Hg compounds, and
POM. Based on EPA estimates of toxicity and bioaccumulation potential,
the pollutants above represent a conservative list for inclusion in
multipathway risk assessments for RTR rules. (See Volume 1, Appendix D
at https://www.epa.gov/sites/production/files/201308/documents/volume_1_reflibrary.pdf). In this assessment, we compare the facility-
specific emission rates of these PB-HAP to the screening threshold
emission rates for each PB-HAP to assess the potential for significant
human health risks via the ingestion pathway. We call this application
of the TRIM.FaTE model the Tier 1 screening assessment. The ratio of a
facility's actual emission rate to the Tier 1 screening threshold
emission rate is a ``screening value.''
[[Page 2693]]
We derive the Tier 1 screening threshold emission rates for these
PB-HAP (other than lead compounds) to correspond to a maximum excess
lifetime cancer risk of 1-in-1 million (i.e., for arsenic compounds,
polychlorinated dibenzodioxins and furans and POM) or, for HAP that
cause noncancer health effects (i.e., cadmium compounds and Hg
compounds), a maximum HQ of 1. If the emission rate of any one PB-HAP
or combination of carcinogenic PB-HAP in the Tier 1 screening
assessment exceeds the Tier 1 screening threshold emission rate for any
facility (i.e., the screening value is greater than 1), we conduct a
second screening assessment, which we call the Tier 2 screening
assessment.
In the Tier 2 screening assessment, the location of each facility
that exceeds a Tier 1 screening threshold emission rate is used to
refine the assumptions associated with the Tier 1 fisher and farmer
exposure scenarios at that facility. A key assumption in the Tier 1
screening assessment is that a lake and/or farm is located near the
facility. As part of the Tier 2 screening assessment, we use a United
States Geological Survey (USGS) database to identify actual waterbodies
within 50 km of each facility. We also examine the differences between
local meteorology near the facility and the meteorology used in the
Tier 1 screening assessment. We then adjust the previously-developed
Tier 1 screening threshold emission rates for each PB-HAP for each
facility based on an understanding of how exposure concentrations
estimated for the screening scenario change with the use of local
meteorology and USGS waterbody data. If the PB-HAP emission rates for a
facility exceed the Tier 2 screening threshold emission rates and data
are available, we may conduct a Tier 3 screening assessment. If PB-HAP
emission rates do not exceed a Tier 2 screening value of 1, we consider
those PB-HAP emissions to pose risks below a level of concern.
There are several analyses that can be included in a Tier 3
screening assessment, depending upon the extent of refinement
warranted, including validating that the lakes are fishable,
considering plume-rise to estimate emissions lost above the mixing
layer, and considering hourly effects of meteorology and plume rise on
chemical fate and transport. If the Tier 3 screening assessment
indicates that risks above levels of concern cannot be ruled out, the
EPA may further refine the screening assessment through a site-specific
assessment.
In evaluating the potential multipathway risk from emissions of
lead compounds, rather than developing a screening threshold emission
rate, we compare maximum estimated chronic inhalation exposure
concentrations to the level of the current NAAQS for lead.\42\ Values
below the level of the primary (health-based) lead NAAQS are considered
to have a low potential for multipathway risk.
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\42\ In doing so, the EPA notes that the legal standard for a
primary NAAQS--that a standard is requisite to protect public health
and provide an adequate margin of safety (CAA section 109(b))--
differs from the CAA section 112(f) standard (requiring, among other
things, that the standard provide an ``ample margin of safety to
protect public health''). However, the primary lead NAAQS is a
reasonable measure of determining risk acceptability (i.e., the
first step of the Benzene NESHAP analysis) since it is designed to
protect the most susceptible group in the human population--
children, including children living near major lead emitting
sources. 73 FR 67002/3; 73 FR 67000/3; 73 FR 67005/1. In addition,
applying the level of the primary lead NAAQS at the risk
acceptability step is conservative, since that primary lead NAAQS
reflects an adequate margin of safety.
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For further information on the multipathway assessment approach,
see the risk document, which is available in the docket for this
action.
5. How do we conduct the environmental risk screening assessment?
a. Adverse Environmental Effect, Environmental HAP, and Ecological
Benchmarks
The EPA conducts a screening assessment to examine the potential
for an adverse environmental effect as required under section
112(f)(2)(A) of the CAA. Section 112(a)(7) of the CAA defines ``adverse
environmental effect'' as ``any significant and widespread adverse
effect, which may reasonably be anticipated, to wildlife, aquatic life,
or other natural resources, including adverse impacts on populations of
endangered or threatened species or significant degradation of
environmental quality over broad areas.''
The EPA focuses on eight HAP, which are referred to as
``environmental HAP,'' in its screening assessment: six PB-HAP and two
acid gases. The PB-HAP included in the screening assessment are arsenic
compounds, cadmium compounds, dioxins/furans, POM, Hg (both inorganic
Hg and methyl Hg), and lead compounds. The acid gases included in the
screening assessment are HCl and HF.
HAP that persist and bioaccumulate are of particular environmental
concern because they accumulate in the soil, sediment, and water. The
acid gases, HCl and HF, are included due to their well-documented
potential to cause direct damage to terrestrial plants. In the
environmental risk screening assessment, we evaluate the following four
exposure media: terrestrial soils, surface water bodies (includes
water-column and benthic sediments), fish consumed by wildlife, and
air. Within these four exposure media, we evaluate nine ecological
assessment endpoints, which are defined by the ecological entity and
its attributes. For PB-HAP (other than lead), both community-level and
population-level endpoints are included. For acid gases, the ecological
assessment evaluated is terrestrial plant communities.
An ecological benchmark represents a concentration of HAP that has
been linked to a particular environmental effect level. For each
environmental HAP, we identified the available ecological benchmarks
for each assessment endpoint. We identified, where possible, ecological
benchmarks at the following effect levels: probable effect levels,
lowest-observed-adverse-effect level, and no-observed-adverse-effect
level. In cases where multiple effect levels were available for a
particular PB-HAP and assessment endpoint, we use all of the available
effect levels to help us to determine whether ecological risks exist
and, if so, whether the risks could be considered significant and
widespread.
For further information on how the environmental risk screening
assessment was conducted, including a discussion of the risk metrics
used, how the environmental HAP were identified, and how the ecological
benchmarks were selected, see Appendix 9 of the risk document, which is
available in the docket for this action.
b. Environmental Risk Screening Methodology
For the environmental risk screening assessment, the EPA first
determined whether any facilities in the Coal- and Oil-Fired EGU source
category emitted any of the environmental HAP. For the Coal- and Oil-
Fired EGU source category, we identified emissions of lead compounds,
arsenic compounds, Hg compounds, cadmium compounds, POM, dioxins, HCl,
and HF. Because one or more of the environmental HAP evaluated are
emitted by at least one facility in the source category, we proceeded
to the second step of the evaluation.
c. PB-HAP Methodology
The environmental screening assessment includes six PB-HAP, arsenic
compounds, cadmium compounds, dioxins/furans, POM, Hg (both inorganic
Hg and methyl Hg), and lead compounds. With the exception of
[[Page 2694]]
lead, the environmental risk screening assessment for PB-HAP consists
of three tiers. The first tier of the environmental risk screening
assessment uses the same health-protective conceptual model that is
used for the Tier 1 human health screening assessment. TRIM.FaTE model
simulations were used to back-calculate Tier 1 screening threshold
emission rates. The screening threshold emission rates represent the
emission rate in tpy that results in media concentrations at the
facility that equal the relevant ecological benchmark. To assess
emissions from each facility in the category, the reported emission
rate for each PB-HAP was compared to the Tier 1 screening threshold
emission rate for that PB-HAP for each assessment endpoint and effect
level. If emissions from a facility do not exceed the Tier 1 screening
threshold emission rate, the facility ``passes'' the screening
assessment, and, therefore, is not evaluated further under the
screening approach. If emissions from a facility exceed the Tier 1
screening threshold emission rate, we evaluate the facility further in
Tier 2.
In Tier 2 of the environmental screening assessment, the screening
threshold emission rates are adjusted to account for local meteorology
and the actual location of lakes in the vicinity of facilities that did
not pass the Tier 1 screening assessment. For soils, we evaluate the
average soil concentration for all soil parcels within a 7.5-km radius
for each facility and PB-HAP. For the water, sediment, and fish tissue
concentrations, the highest value for each facility for each pollutant
is used. If emission concentrations from a facility do not exceed the
Tier 2 screening threshold emission rate, the facility ``passes'' the
screening assessment and typically is not evaluated further. If
emissions from a facility exceed the Tier 2 screening threshold
emission rate, we evaluate the facility further in Tier 3.
As in the multipathway human health risk assessment, in Tier 3 of
the environmental screening assessment, we examine the suitability of
the lakes around the facilities to support life and remove those that
are not suitable (e.g., lakes that have been filled in or are
industrial ponds), adjust emissions for plume-rise, and conduct hour-
by-hour time-series assessments. If these Tier 3 adjustments to the
screening threshold emission rates still indicate the potential for an
adverse environmental effect (i.e., facility emission rate exceeds the
screening threshold emission rate), we may elect to conduct a more
refined assessment using more site-specific information. If, after
additional refinement, the facility emission rate still exceeds the
screening threshold emission rate, the facility may have the potential
to cause an adverse environmental effect.
To evaluate the potential for an adverse environmental effect from
lead, we compared the average modeled air concentrations (from HEM-3)
of lead around each facility in the source category to the level of the
secondary NAAQS for lead. The secondary lead NAAQS is a reasonable
means of evaluating environmental risk because it is set to provide
substantial protection against adverse welfare effects which can
include ``effects on soils, water, crops, vegetation, man-made
materials, animals, wildlife, weather, visibility and climate, damage
to and deterioration of property, and hazards to transportation, as
well as effects on economic values and on personal comfort and well-
being.''
d. Acid Gas Environmental Risk Methodology
The environmental screening assessment for acid gases evaluates the
potential phytotoxicity and reduced productivity of plants due to
chronic exposure to HF and HCl. The environmental risk screening
methodology for acid gases is a single-tier screening assessment that
compares modeled ambient air concentrations (from AERMOD) to the
ecological benchmarks for each acid gas. To identify a potential
adverse environmental effect (as defined in section 112(a)(7) of the
CAA) from emissions of HF and HCl, we evaluate the following metrics:
The size of the modeled area around each facility that exceeds the
ecological benchmark for each acid gas, in acres and km\2\; the
percentage of the modeled area around each facility that exceeds the
ecological benchmark for each acid gas; and the area-weighted average
screening value around each facility (calculated by dividing the area-
weighted average concentration over the 50-km modeling domain by the
ecological benchmark for each acid gas). For further information on the
environmental screening assessment approach, see Appendix 9 of the risk
document, which is available in the docket for this action.
6. How do we conduct facility-wide assessments?
To put the source category risks in context, we typically examine
the risks from the entire ``facility,'' where the facility includes all
HAP-emitting operations within a contiguous area and under common
control. In other words, we examine the HAP emissions not only from the
source category emission points of interest, but also emissions of HAP
from all other emission sources at the facility for which we have data.
For this source category, we conducted the facility-wide assessment
using a dataset compiled from the 2014 NEI. The source category records
of that NEI dataset were removed, evaluated, and updated as described
in section IV.D of this preamble: What other relevant background
information and data are available? Once a quality assured source
category dataset was available, it was placed back with the remaining
records from the NEI for that facility. The facility-wide file was then
used to analyze risks due to the inhalation of HAP that are emitted
``facility-wide'' for the populations residing within 50 km of each
facility, consistent with the methods used for the source category
analysis described above. For these facility-wide risk analyses, the
modeled source category risks were compared to the facility-wide risks
to determine the portion of the facility-wide risks that could be
attributed to the source category addressed in this proposal. We also
specifically examined the facility that was associated with the highest
estimate of risk and determined the percentage of that risk
attributable to the source category of interest. The risk document,
available through the docket for this action, provides the methodology
and results of the facility-wide analyses, including all facility-wide
risks and the percentage of source category contribution to facility-
wide risks.
7. How do we consider uncertainties in risk assessment?
Uncertainty and the potential for bias are inherent in all risk
assessments, including those performed for this proposal. Although
uncertainty exists, we believe that our approach, which used
conservative tools and assumptions, ensures that our decisions are
health and environmentally protective. A brief discussion of the
uncertainties in the RTR emissions dataset, dispersion modeling,
inhalation exposure estimates, and dose-response relationships follows
below. Also included are those uncertainties specific to our acute
screening assessments, multipathway screening assessments, and our
environmental risk screening assessments. A more thorough discussion of
these uncertainties is included in the risk document, which is
available in the docket for this action. If a multipathway site-
specific assessment was performed for this source category, a full
discussion of the uncertainties associated with that assessment can be
[[Page 2695]]
found in Appendix 11 of that document, Site-Specific Human Health
Multipathway Residual Risk Assessment Report.
a. Uncertainties in the RTR Emissions Dataset
Although the development of the RTR emissions dataset involved
quality assurance/quality control processes, the accuracy of emissions
values will vary depending on the source of the data, the degree to
which data are incomplete or missing, the degree to which assumptions
made to complete the datasets are accurate, errors in emission
estimates, and other factors. The emission estimates considered in this
analysis generally are annual totals for certain years, and they do not
reflect short-term fluctuations during the course of a year or
variations from year to year. The estimates of peak hourly emission
rates for the acute effects screening assessment were based on an
emission adjustment factor applied to the average annual hourly
emission rates, which are intended to account for emission fluctuations
due to normal facility operations.
b. Uncertainties in Dispersion Modeling
We recognize there is uncertainty in ambient concentration
estimates associated with any model, including the EPA's recommended
regulatory dispersion model, AERMOD. In using a model to estimate
ambient pollutant concentrations, the user chooses certain options to
apply. For RTR assessments, we select some model options that have the
potential to overestimate ambient air concentrations (e.g., not
including plume depletion or pollutant transformation). We select other
model options that have the potential to underestimate ambient impacts
(e.g., not including building downwash). Other options that we select
have the potential to either under- or overestimate ambient levels
(e.g., meteorology and receptor locations). On balance, considering the
directional nature of the uncertainties commonly present in ambient
concentrations estimated by dispersion models, the approach we apply in
the RTR assessments should yield unbiased estimates of ambient HAP
concentrations. We also note that the selection of meteorology dataset
location could have an impact on the risk estimates. As we continue to
update and expand our library of meteorological station data used in
our risk assessments, we expect to reduce this variability.
c. Uncertainties in Inhalation Exposure Assessment
Although every effort is made to identify all of the relevant
facilities and emission points, as well as to develop accurate
estimates of the annual emission rates for all relevant HAP, the
uncertainties in our emission inventory likely dominate the
uncertainties in the exposure assessment. Some uncertainties in our
exposure assessment include human mobility, using the centroid of each
census block, assuming lifetime exposure, and assuming only outdoor
exposures. For most of these factors, there is neither an underestimate
nor overestimate when looking at the maximum individual risk or the
incidence, but the shape of the distribution of risks may be affected.
With respect to outdoor exposures, actual exposures may not be as high
if people spend time indoors, especially for very reactive pollutants
or larger particles. For all factors, we reduce uncertainty when
possible. For example, with respect to census-block centroids, we
analyze large blocks using aerial imagery and adjust locations of the
block centroids to better represent the population in the blocks. We
also add additional receptor locations where the population of a block
is not well represented by a single location.
d. Uncertainties in Dose-Response Relationships
There are uncertainties inherent in the development of the dose-
response values used in our risk assessments for cancer effects from
chronic exposures and noncancer effects from both chronic and acute
exposures. Some uncertainties are generally expressed quantitatively,
and others are generally expressed in qualitative terms. We note, as a
preface to this discussion, a point on dose-response uncertainty that
is stated in the EPA's 2005 Guidelines for Carcinogen Risk Assessment;
namely, that ``the primary goal of EPA actions is protection of human
health; accordingly, as an Agency policy, risk assessment procedures,
including default options that are used in the absence of scientific
data to the contrary, should be health protective'' (the EPA's 2005
Guidelines for Carcinogen Risk Assessment, page 1-7). This is the
approach followed here as summarized in the next paragraphs.
Cancer UREs used in our risk assessments are those that have been
developed to generally provide an upper bound estimate of risk.\43\
That is, they represent a ``plausible upper limit to the true value of
a quantity'' (although this is usually not a true statistical
confidence limit). In some circumstances, the true risk could be as low
as zero; however, in other circumstances the risk could be greater.\44\
Chronic noncancer RfC and reference dose (RfD) values represent chronic
exposure levels that are intended to be health-protective levels. To
derive dose-response values that are intended to be ``without
appreciable risk,'' the methodology relies upon an uncertainty factor
(UF) approach,\45\ which considers uncertainty, variability, and gaps
in the available data. The UFs are applied to derive dose-response
values that are intended to protect against appreciable risk of
deleterious effects.
---------------------------------------------------------------------------
\43\ IRIS glossary (https://ofmpub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?details=&glossaryName=IRIS%20Glossary).
\44\ An exception to this is the URE for benzene, which is
considered to cover a range of values, each end of which is
considered to be equally plausible, and which is based on maximum
likelihood estimates.
\45\ See A Review of the Reference Dose and Reference
Concentration Processes, U.S. EPA, December 2002, and Methods for
Derivation of Inhalation Reference Concentrations and Application of
Inhalation Dosimetry, U.S. EPA, 1994.
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Many of the UFs used to account for variability and uncertainty in
the development of acute dose-response values are quite similar to
those developed for chronic durations. Additional adjustments are often
applied to account for uncertainty in extrapolation from observations
at one exposure duration (e.g., 4 hours) to derive an acute dose-
response value at another exposure duration (e.g., 1 hour). Not all
acute dose-response values are developed for the same purpose, and care
must be taken when interpreting the results of an acute assessment of
human health effects relative to the dose-response value or values
being exceeded. Where relevant to the estimated exposures, the lack of
acute dose-response values at different levels of severity should be
factored into the risk characterization as potential uncertainties.
Uncertainty also exists in the selection of ecological benchmarks
for the environmental risk screening assessment. We established a
hierarchy of preferred benchmark sources to allow selection of
benchmarks for each environmental HAP at each ecological assessment
endpoint. We searched for benchmarks for three effect levels (i.e., no-
effects level, threshold-effect level, and probable effect level), but
not all combinations of ecological assessment/environmental HAP had
benchmarks for
[[Page 2696]]
all three effect levels. Where multiple effect levels were available
for a particular HAP and assessment endpoint, we used all of the
available effect levels to help us determine whether risk exists and
whether the risk could be considered significant and widespread.
Although we make every effort to identify appropriate human health
effect dose-response values for all pollutants emitted by the sources
in this risk assessment, some HAP emitted by this source category are
lacking dose-response assessments. Accordingly, these pollutants cannot
be included in the quantitative risk assessment, which could result in
quantitative estimates understating HAP risk. To help to alleviate this
potential underestimate, where we conclude similarity with a HAP for
which a dose-response value is available, we use that value as a
surrogate for the assessment of the HAP for which no value is
available. To the extent use of surrogates indicates appreciable risk,
we may identify a need to increase priority for an IRIS assessment for
that substance. We additionally note that, generally speaking, HAP of
greatest concern due to environmental exposures and hazard are those
for which dose-response assessments have been performed, reducing the
likelihood of understating risk. Further, HAP not included in the
quantitative assessment are assessed qualitatively and considered in
the risk characterization that informs the risk management decisions,
including consideration of HAP reductions achieved by various control
options.
For a group of compounds that are unspeciated (e.g., glycol
ethers), we conservatively use the most protective dose-response value
of an individual compound in that group to estimate risk. Similarly,
for an individual compound in a group (e.g., ethylene glycol diethyl
ether) that does not have a specified dose-response value, we also
apply the most protective dose-response value from the other compounds
in the group to estimate risk.
e. Uncertainties in Acute Inhalation Screening Assessments
In addition to the uncertainties highlighted above, there are
several factors specific to the acute exposure assessment that the EPA
conducts as part of the risk review under section 112 of the CAA. The
accuracy of an acute inhalation exposure assessment depends on the
simultaneous occurrence of independent factors that may vary greatly,
such as hourly emissions rates, meteorology, and the presence of humans
at the location of the maximum concentration. In the acute screening
assessment that we conduct under the RTR program, we assume that peak
emissions from the source category and worst-case meteorological
conditions co-occur, thus, resulting in maximum ambient concentrations.
These two events are unlikely to occur at the same time, making these
assumptions conservative. We then include the additional assumption
that a person is located at this point during this same time period.
For this source category, these assumptions would tend to be worst-case
actual exposures, as it is unlikely that a person would be located at
the point of maximum exposure during the time when peak emissions and
worst-case meteorological conditions occur simultaneously.
f. Uncertainties in the Multipathway and Environmental Risk Screening
Assessments
For each source category, we generally rely on site-specific levels
of PB-HAP or environmental HAP emissions to determine whether a refined
assessment of the impacts from multipathway exposures is necessary or
whether it is necessary to perform an environmental screening
assessment. This determination is based on the results of a three-
tiered screening assessment that relies on the outputs from models--
TRIM.FaTE and AERMOD--that estimate environmental pollutant
concentrations and human exposures for five PB-HAP (dioxins, POM, Hg,
cadmium, and arsenic) and two acid gases (HF and HCl). For lead, we use
AERMOD to determine ambient air concentrations, which are then compared
to the secondary NAAQS standard for lead. Two important types of
uncertainty associated with the use of these models in RTR risk
assessments and inherent to any assessment that relies on environmental
modeling are model uncertainty and input uncertainty.\46\
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\46\ In the context of this discussion, the term ``uncertainty''
as it pertains to exposure and risk encompasses both variability in
the range of expected inputs and screening results due to existing
spatial, temporal, and other factors, as well as uncertainty in
being able to accurately estimate the true result.
---------------------------------------------------------------------------
Model uncertainty concerns whether the model adequately represents
the actual processes (e.g., movement and accumulation) that might occur
in the environment. For example, does the model adequately describe the
movement of a pollutant through the soil? This type of uncertainty is
difficult to quantify. However, based on feedback received from
previous EPA SAB reviews and other reviews, we are confident that the
models used in the screening assessments are appropriate and state-of-
the-art for the multipathway and environmental screening risk
assessments conducted in support of RTR.
Input uncertainty is concerned with how accurately the models have
been configured and parameterized for the assessment at hand. For Tier
1 of the multipathway and environmental screening assessments, we
configured the models to avoid underestimating exposure and risk. This
was accomplished by selecting upper-end values from nationally
representative datasets for the more influential parameters in the
environmental model, including selection and spatial configuration of
the area of interest, lake location and size, meteorology, surface
water, soil characteristics, and structure of the aquatic food web. We
also assume an ingestion exposure scenario and values for human
exposure factors that represent reasonable maximum exposures.
In Tier 2 of the multipathway and environmental screening
assessments, we refine the model inputs to account for meteorological
patterns in the vicinity of the facility versus using upper-end
national values, and we identify the actual location of lakes near the
facility rather than the default lake location that we apply in Tier 1.
By refining the screening approach in Tier 2 to account for local
geographical and meteorological data, we decrease the likelihood that
concentrations in environmental media are overestimated, thereby
increasing the usefulness of the screening assessment. In Tier 3 of the
screening assessments, we refine the model inputs again to account for
hour-by-hour plume rise and the height of the mixing layer. We can also
use those hour-by-hour meteorological data in a TRIM.FaTE run using the
screening configuration corresponding to the lake location. These
refinements produce a more accurate estimate of chemical concentrations
in the media of interest, thereby reducing the uncertainty with those
estimates. The assumptions and the associated uncertainties regarding
the selected ingestion exposure scenario are the same for all three
tiers.
For the environmental screening assessment for acid gases, we
employ a single-tiered approach. We use the modeled air concentrations
and compare those with ecological benchmarks.
For all tiers of the multipathway and environmental screening
assessments, our approach to addressing model input uncertainty is
generally cautious. We
[[Page 2697]]
choose model inputs from the upper end of the range of possible values
for the influential parameters used in the models, and we assume that
the exposed individual exhibits ingestion behavior that would lead to a
high total exposure. This approach reduces the likelihood of not
identifying high risks for adverse impacts.
Despite the uncertainties, when individual pollutants or facilities
do not exceed screening threshold emission rates (i.e., screen out), we
are confident that the potential for adverse multipathway impacts on
human health is very low. On the other hand, when individual pollutants
or facilities do exceed screening threshold emission rates, it does not
mean that impacts are significant, only that we cannot rule out that
possibility and that a refined assessment for the site might be
necessary to obtain a more accurate risk characterization for the
source category.
The EPA evaluates the following HAP in the multipathway and/or
environmental risk screening assessments, where applicable: Arsenic,
cadmium, dioxins/furans, lead, Hg (both inorganic and methyl Hg), POM,
HCl, and HF. These HAP represent pollutants that can cause adverse
impacts either through direct exposure to HAP in the air or through
exposure to HAP that are deposited from the air onto soils and surface
waters and then through the environment into the food web. These HAP
represent those HAP for which we can conduct a meaningful multipathway
or environmental screening risk assessment. For other HAP not included
in our screening assessments, the model has not been parameterized such
that it can be used for that purpose. In some cases, depending on the
HAP, we may not have appropriate multipathway models that allow us to
predict the concentration of that pollutant. The EPA acknowledges that
other HAP beyond these that we are evaluating may have the potential to
cause adverse effects and, therefore, the EPA may evaluate other
relevant HAP in the future, as modeling science and resources allow.
VI. RTR Analytical Results and Proposed Decisions
A. What are the results of the risk assessment and analyses?
1. Inhalation Risk Assessment Results
Table 5 of this preamble provides a summary of the results of the
inhalation risk assessment for the source category. More detailed
information on the risk assessment can be found in the risk document,
available in the docket for this action.
Table 5--Coal- and Oil-Fired EGU Inhalation Risk Assessment Results
--------------------------------------------------------------------------------------------------------------------------------------------------------
Maximum individual cancer Population at increased Annual cancer incidence Maximum chronic noncancer Maximum screening
risk (in 1 million) \2\ risk of cancer >=1-in-1 (cases per year) TOSHI \3\ acute noncancer HQ
---------------------------- million -------------------------------------------------------- \4\
Based on . . . ---------------------------- Based on . . . Based on . . . ---------------------
Number of ---------------------------- Based on . . . --------------------------------------------------------
facilities \1\ ----------------------------
Actual Allowable Actual Allowable Actual Allowable Actual Allowable Based on actual
emissions emissions emissions emissions emissions emissions emissions emissions emissions level
level \2\ level level \2\ level level \2\ level level level
--------------------------------------------------------------------------------------------------------------------------------------------------------
322............... 9 10 193,000 636,000 0.04 0.1 0.2 0.4 HQREL = 0.09
(arsenic).
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Number of facilities evaluated in the risk analysis.
\2\ Maximum individual excess lifetime cancer risk due to HAP emissions from the source category.
\3\ Maximum TOSHI. The target organ systems with the highest TOSHI for the source category are neurological and reproductive.
\4\ The maximum estimated acute exposure concentration was divided by available short-term threshold values to develop an array of HQ values. HQ values
shown use the lowest available acute threshold value, which in most cases is the REL. When an HQ exceeds 1, we also show the HQ using the next lowest
available acute dose-response value.
As shown in Table 5 of this preamble, based on actual emissions,
the estimated cancer MIR is 9-in-1 million, and nickel emissions from
oil-fired EGUs are the major contributor to the risk. The total
estimated cancer incidence from this source category is 0.04 excess
cancer cases per year, or one excess case in every 25 years.
Approximately 193,000 people are estimated to have cancer risks at or
above 1-in-1 million from HAP emitted from the facilities in this
source category. The estimated maximum chronic noncancer TOSHI for the
source category is 0.2 (respiratory), which is driven by emissions of
nickel and cobalt from oil-fired EGUs. No one is exposed to TOSHI
levels above 1.
Based on allowable emissions, the estimated cancer MIR is 10-in-1
million, and, as before, nickel emissions from oil-fired EGUs are the
major contributor to the risk. The total estimated cancer incidence
from this source category is 0.1 excess cancer cases per year, or one
excess case in every 10 years. Approximately 636,000 people are
estimated to have cancer risks at or above 1-in-1 million from HAP
emitted from the facilities in this source category. The estimated
maximum chronic noncancer TOSHI for the source category is 0.4
(respiratory), driven by emissions of nickel and cobalt from oil-fired
EGUs. No one is exposed to TOSHI levels above 1.
2. Acute Risk Results
Table 5 of this preamble provides the worst-case acute HQ (based on
the REL) of 0.09, driven by actual emissions of arsenic. There are no
facilities that have acute HQs (based on the REL or any other reference
values) greater than 1. For more detailed acute risk results, refer to
the risk document.
3. Multipathway Risk Screening Results
Potential multipathway health risks under a fisher and gardener
scenario were identified using a three-tier screening assessment of the
PB-HAP emitted by facilities in this source category, and a site-
specific assessment of Hg using TRIM.FaTE for one location. Of the 322
MATS facilities modeled, 307 facilities have reported emissions of
carcinogenic PB-HAP (arsenic, dioxins, and POM) that exceed a Tier 1
cancer screening value of 1, and 235 facilities have reported emissions
of non-carcinogenic PB-HAP (lead, Hg, and cadmium) that exceed a Tier 1
noncancer screening value of 1. For facilities that exceeded a Tier 1
multipathway screening value of 1, we used additional facility site-
specific information to perform an assessment through Tiers 2 and 3, as
necessary, to determine the maximum chronic cancer and noncancer
impacts for the source category. For cancer, the highest Tier 2
screening value was 200. This screening value was reduced to 50 after
the plume rise stage of Tier 3. Because this screening value was much
lower than 100-in-1 million, and because we expect the actual risk to
be lower than the screening value (site-specific assessments typically
lower estimates by an order of magnitude), we did not perform further
assessment for cancer. For noncancer, the highest Tier 2 screening
value was 30 (for Hg), with
[[Page 2698]]
four facilities having screening values greater than 20. These
screening values were reduced to 9 or lower after the plume rise stage
of Tier 3.
An exceedance of a screening value in any of the tiers cannot be
equated with a risk value or an HQ (or HI). Rather, it represents a
high-end estimate of what the risk or hazard may be. For example, a
screening value of 2 for a non-carcinogen can be interpreted to mean
that we are confident that the HQ would be lower than 2. Similarly, a
screening value of 30 for a carcinogen means that we are confident that
the risk is lower than 30-in-1 million. Our confidence comes from the
conservative, or health-protective, assumptions encompassed in the
screening tiers: We choose inputs from the upper end of the range of
possible values for the influential parameters used in the screening
tiers; and we assume that the exposed individual exhibits ingestion
behavior that would lead to a high total exposure.
In evaluating the potential for multipathway effects from emissions
of lead, we compared modeled maximum annual lead concentrations to the
secondary NAAQS for lead (0.15 [micro]g/m\3\). The modeled maximum
annual lead concentration is below the NAAQS for lead, indicating a low
potential for multipathway impacts of concern due to lead.
4. Multipathway Site-Specific Assessment Results
Because the final stage of Tier 3 (time-series) was unlikely to
reduce the highest Hg screening values to 1, we conducted a site-
specific multipathway assessment of Hg emissions for this source
category. Analysis of the facilities with the highest Tier 2 and Tier 3
screening values helped identify the location for the site-specific
assessment and the facilities to model with TRIM.FaTE. We also
considered the effect multiple facilities within the source category
could have on common lakes in the modeling domain. The selection of the
facilities for the site-specific assessment also included evaluating
the number and location of lakes impacted, watershed boundaries, and
land-use features around the target lakes, (i.e., elevation changes,
topography, rivers).
The three facilities selected are located near Underwood, North
Dakota. All three facilities had Tier 2 screening values greater than
or equal to 20. Two of the facilities are near each other (16 km
apart). The third facility is more distant, about 20 to 30 km from the
other facilities, but it was included in the analysis because it is
within the 50-km modeling domain of the other facilities and because it
had an elevated Tier 2 screening value. We expect that the exposure
scenarios we assessed for these facilities are among the highest, if
not the highest, that might be encountered for other facilities in this
source category. The refined site-specific multipathway assessment, as
in the screening assessments, includes some hypothetical elements,
namely the hypothetical human receptor (e.g., the fisher scenario which
did not screen out in the screening assessments). It is important to
note that although the multipathway assessment has been conducted, no
data exist to verify the existence of the hypothetical human receptor.
The refined multipathway assessment produced an HQ of 0.06 for Hg for
the three facilities assessed. This risk assessment likely represents
the maximum hazard for Hg through fish consumption for the source
category and, with an HQ less than 1, is below the level of concern for
exposure to emissions from these sources.
5. Environmental Risk Screening Results
As described in section V.C of this preamble, we conducted an
environmental risk screening assessment for the Coal- and Oil-Fired EGU
source category for the following pollutants: Arsenic, cadmium,
dioxins/furans, HCl, HF, lead, Hg (methyl Hg and mercuric chloride),
and POMs.
In the Tier 1 screening analysis for PB-HAP (other than lead, which
was evaluated differently), POM emissions had no exceedances of any of
the ecological benchmarks evaluated. Arsenic and dioxins/furans
emissions had Tier 1 exceedances for surface soil benchmarks. Cadmium
and methyl Hg emissions had Tier 1 exceedances for surface soil and
fish benchmarks. Divalent Hg emissions had Tier 1 exceedances for
sediment and surface soil benchmarks.
A Tier 2 screening analysis was performed for arsenic, cadmium,
dioxins/furans, divalent Hg, and methyl Hg emissions. In the Tier 2
screening analysis, arsenic, cadmium, and dioxins/furans emissions had
no exceedances of any of the ecological benchmarks evaluated. Divalent
Hg emissions from two facilities exceeded the Tier 2 screen for a
sediment threshold level benchmark by a maximum screening value of 2 at
lake #35731. Methyl Hg emissions from the same two facilities exceeded
the Tier 2 screen for a fish (avian/piscivores) no-observed-adverse-
effect-level (NOAEL) (merganser) benchmark by a maximum screening value
of 2 at the same lake (lake #35731). A Tier 3 screening assessment was
performed to verify the existence of lake #35731. Lake #35731 was found
to be located on-site and is a man-made industrial pond, and,
therefore, was removed from the assessment.
Methyl Hg emissions from two facilities exceeded the Tier 2 screen
for a surface soil NOAEL for avian ground insectivores (woodcock)
benchmark by a maximum screening value of 2. Other surface soil
benchmarks for methyl Hg, such as the NOAEL for mammalian insectivores
and the threshold level for the invertebrate community, were not
exceeded. Given the low Tier 2 maximum screening value of 2 for methyl
Hg, and the fact that only the most protective benchmark was exceeded,
a Tier 3 environmental risk screen was not conducted for methyl Hg.
For lead, we did not estimate any exceedances of the secondary lead
NAAQS. For HCl and HF, the average modeled concentration around each
facility (i.e., the average concentration of all off-site data points
in the modeling domain) did not exceed any ecological benchmark. In
addition, each individual modeled concentration of HCl and HF (i.e.,
each off-site data point in the modeling domain) was below the
ecological benchmarks for all facilities.
Based on the results of the environmental risk screening analysis,
we do not expect an adverse environmental effect as a result of HAP
emissions from this source category.
6. Facility-Wide Risk Results
Based on facility-wide emissions, the estimated cancer MIR is 9-in-
1 million, and nickel emissions from oil-fired EGUs are the major
contributor to the risk. The total estimated cancer incidence from this
source category is 0.04 excess cancer cases per year, or one excess
case in every 25 years. Approximately 203,000 people are estimated to
have cancer risks at or above 1-in-1 million from HAP emitted from the
facilities in this source category. The estimated maximum chronic
noncancer TOSHI for the source category is 0.2 (respiratory), driven by
emissions of nickel and cobalt from oil-fired EGUs. No one is exposed
to TOSHI levels above 1. These results are very similar to those based
on actual emissions from the source category because there is not
significant collocation of other sources with EGUs.
7. What demographic groups might benefit from this regulation?
To examine the potential for any environmental justice issues that
might be associated with the source category, we performed a
demographic analysis,
[[Page 2699]]
which is an assessment of risk to individual demographic groups of the
populations living within 5 km and within 50 km of the facilities. In
the analysis, we evaluated the distribution of HAP-related cancer and
noncancer risk from the Coal- and Oil-Fired EGU source category across
different demographic groups within the populations living near
facilities.\47\
---------------------------------------------------------------------------
\47\ Demographic groups included in the analysis are: White,
African American, Native American, other races and multiracial,
Hispanic or Latino, children 17 years of age and under, adults 18 to
64 years of age, adults 65 years of age and over, adults without a
high school diploma, people living below the poverty level, people
living two times the poverty level, and linguistically isolated
people.
---------------------------------------------------------------------------
The results of the demographic analysis are summarized in Table 6
below. These results, for various demographic groups, are based on the
estimated risk from actual emissions levels for the population living
within 50 km of the facilities.
Table 6--Coal- and Oil-Fired EGU Source Category Demographic Risk Analysis Results
----------------------------------------------------------------------------------------------------------------
Population
with cancer
risk greater Population
than or equal with HI
to 1-in-1 greater than 1
million
----------------------------------------------------------------------------------------------------------------
Nationwide Source Category
----------------------------------------------------------------------------------------------------------------
Total Population................................................ 317,746,049 193,000 0
----------------------------------------------------------------------------------------------------------------
White and Minority by Percent
----------------------------------------------------------------------------------------------------------------
White........................................................... 62 1 0
Minority........................................................ 38 * 99 0
----------------------------------------------------------------------------------------------------------------
Minority by Percent
----------------------------------------------------------------------------------------------------------------
African American................................................ 12 0 0
Native American................................................. 0.8 0 0
Hispanic or Latino (includes white and nonwhite)................ 18 * 99 0
Other and Multiracial........................................... 7 0 0
----------------------------------------------------------------------------------------------------------------
Income by Percent
----------------------------------------------------------------------------------------------------------------
Below Poverty Level............................................. 14 40 0
Above Poverty Level............................................. 86 60 0
----------------------------------------------------------------------------------------------------------------
Education by Percent
----------------------------------------------------------------------------------------------------------------
Over 25 and without a High School Diploma....................... 14 25 0
Over 25 and with a High School Diploma.......................... 86 75 0
----------------------------------------------------------------------------------------------------------------
Linguistically Isolated by Percent
----------------------------------------------------------------------------------------------------------------
Linguistically Isolated......................................... 6 * 67 0
----------------------------------------------------------------------------------------------------------------
* Note: All the people with a cancer risk greater than or equal to 1 in 1 million reside in Puerto Rico.
The results of the Coal- and Oil-Fired EGU source category
demographic analysis indicate that emissions from the source category
expose approximately 193,000 people to a cancer risk at or above 1-in-1
million and no people to a chronic noncancer TOSHI greater than 1.
There are only 4 facilities in the source category with cancer risk at
or above 1-in-1 million, and all of them are located in Puerto Rico.
Consequently, all of the percentages of the at-risk population in each
demographic group associated with the Puerto Rican population are much
higher than their respective nationwide percentages, and those not
associated with Puerto Rico are much lower than their respective
nationwide percentages.
The methodology and the results of the demographic analysis are
presented in a technical report, Risk and Technology Review--Analysis
of Demographic Factors for Populations Living Near Coal- and Oil-Fired
EGUs, available in the docket for this action.
B. What are our proposed decisions regarding risk acceptability, ample
margin of safety, and adverse environmental effect?
1. Risk Acceptability
As noted in section V.A of this preamble, the EPA sets standards
under CAA section 112(f)(2) using ``a two-step standard-setting
approach, with an analytical first step to determine an `acceptable
risk' that considers all health information, including risk estimation
uncertainty, and includes a presumptive limit on MIR of approximately
1-in-10 thousand.'' (54 FR 38045, September 14, 1989). In this
proposal, the EPA estimated risks based on actual and allowable
emissions from coal- and oil-fired EGU sources, and we considered these
in determining acceptability.
The estimated inhalation cancer risk to the individual most exposed
to actual emissions from the source category is 9-in-1 million. The
estimated incidence of cancer due to inhalation exposures is 0.04
excess cancer cases per year, or one excess case every 25 years.
Approximately 190,000 people face an increased cancer risk at or above
1-in-1 million due to inhalation exposure to HAP emissions from this
source category. The estimated maximum chronic noncancer TOSHI from
[[Page 2700]]
inhalation exposure for this source category is 0.2. Based on allowable
emissions, the estimated inhalation cancer risk to the individual most
exposed is 10-in-1 million, and the estimated incidence of cancer due
to inhalation exposures is 0.1 excess cancer cases per year, or one
excess case every 10 years. Approximately 640,000 people face an
increased cancer risk at or above 1-in-1 million due to inhalation
exposure to allowable HAP emissions from this source category. The
maximum chronic noncancer TOSHI from inhalation exposure is 0.4 based
on allowable emissions. The screening assessment of worst-case acute
inhalation impacts indicates that no facilities have actual emissions
that result in an acute HQ greater than 1 for any pollutant, with an
estimated worst-case maximum acute HQ of 0.09 for arsenic based on the
1-hour REL.
Potential multipathway human health risks were estimated using a
three-tier screening assessment of the PB-HAP emitted by facilities in
this source category. The only pollutants with elevated screening
values are arsenic (cancer) and Hg (noncancer). The highest Tier 3
cancer screening value is 50, mostly driven by arsenic. The highest
Tier 3 noncancer screening value is 9, for Hg. We performed a site-
specific multipathway assessment which indicates that the highest Hg HQ
expected from any facility in the source category is much less than 1.
In evaluating the potential for multipathway effects from emissions of
lead from the source category, we compared modeled maximum annual lead
concentrations to the primary NAAQS for lead (0.15 [mu]g/m\3\). Results
of this analysis estimate that the NAAQS for lead would not be exceeded
at any off-site locations.
In determining whether risks are acceptable for this source
category, the EPA considered all available health information and risk
estimation uncertainty as described above. The risk results indicate
that both the actual and allowable inhalation cancer risks to the
individual most exposed are well below 100-in-1 million, which is the
presumptive limit of acceptability. Also, the highest chronic noncancer
TOSHI, and the highest acute noncancer HQ, are well below 1, indicating
low likelihood of adverse noncancer effects from inhalation exposures.
There are also low risks associated with ingestion, with the highest
cancer risk being less than 50-in-1 million based on a conservative
screening assessment, and the highest noncancer hazard being less than
1 based on a site-specific multipathway assessment.
Considering all of the health risk information and factors
discussed above, including the uncertainties discussed in section V of
this preamble, the EPA proposes that the risks are acceptable for this
source category.
2. Ample Margin of Safety Analysis
As directed by CAA section 112(f)(2), we conducted an analysis to
determine if the current emissions standards provide an ample margin of
safety to protect public health. Under the ample margin of safety
analysis, the EPA considers all health factors evaluated in the risk
assessment and evaluates the cost and feasibility of available control
technologies and other measures (including the controls, measures, and
costs reviewed under the technology review) that could be applied to
this source category to further reduce the risks (or potential risks)
due to emissions of HAP identified in our risk assessment. In this
analysis, we considered the results of the technology review, risk
assessment, and other aspects of our MACT rule review to determine
whether there are any cost-effective controls or other measures that
would reduce emissions further to provide an ample margin of safety
with respect to the risks associated with these emissions.
Our risk analysis indicated the risks from the source category are
low for both cancer and noncancer health effects, and, therefore, any
risk reductions from further available control options would result in
minimal health benefits. Moreover, as noted in our discussion of the
technology review in section VI.C of this preamble, no additional
measures were identified for reducing HAP emissions from affected
sources in the Coal- and Oil-Fired EGU source category. Thus, we are
proposing that the current MATS requirements provide an ample margin of
safety to protect public health.
3. Adverse Environmental Effects
Based on the results of our environmental risk screening
assessment, we conclude that there is not an adverse environmental
effect from the Coal- and Oil-Fired EGU source category. We are
proposing that it is not necessary to set a more stringent standard to
prevent, taking into consideration costs, energy, safety, and other
relevant factors, an adverse environmental effect.
C. What are the results and proposed decisions based on our technology
review?
As described in section V.B of this preamble, our technology review
focused on identifying developments in practices, processes, and
control technologies that have occurred since the MATS rule was
promulgated. Control technologies typically used to minimize emissions
of pollutants that have numeric emission limits under the MATS rule
include electrostatic precipitators and fabric filters for control of
PM and non-Hg HAP metals; wet scrubbers and dry scrubbers for control
of acid gases (SO2, HCl, and HF); and activated carbon
injection for control of Hg. The existing air pollution control
technologies that are currently in use are well-established and provide
the capture efficiencies necessary for compliance with the MATS
emission limits. Based on the effectiveness and proven reliability of
these control technologies, and the relatively short period of time
since the promulgation of the MATS rule, no developments in practices,
processes, or control technologies, nor any new technologies or
practices were identified for the control of non-Hg HAP metals, acid
gas HAP, or Hg. Organic HAP, including emissions of dioxins and furans,
are regulated by a work practice standard that requires periodic burner
tune-ups to ensure good combustion. This work practice continues to be
a practical approach to ensuring that combustion equipment is
maintained and optimized to run to reduce emissions of organic HAP, and
continues to be expected to be more effective than establishing a
numeric standard that cannot reliably be measured or monitored. Based
on the effectiveness and proven reliability of the work practice
standard, and the relatively short amount of time since the
promulgation of the MATS rule, no developments in work practices nor
any new work practices or operational procedures have been identified
for this source category regarding the additional control of organic
HAP. Consequently, we propose that no revisions to the MATS rule are
necessary pursuant to CAA section 112(d)(6). Additional details of our
technology review can be found in the memorandum, Technology Review for
the Coal- and Oil-fired EGU Source Category, which is available in the
docket for this action.
VII. Consideration of Separate Subcategory and Acid Gas Standard for
Existing EGUs That Fire Eastern Bituminous Coal Refuse
The EPA is considering establishing a subcategory for emissions of
acid gas HAP from existing EGUs firing eastern bituminous coal refuse.
In this action, the EPA is soliciting comment on whether establishment
of such a subcategory is needed (Comment C-11)
[[Page 2701]]
and on the acid gas HAP emission standards that would be established if
we create this subcategory (Comment C-12).
A. Background
In the MATS rule proposal, the EPA proposed a single acid gas
emission standard for all coal-fired power plants--using HCl as a
surrogate for all acidic gas HAP. See 76 FR 24976, May 3, 2011. The EPA
also proposed an alternative emission standard for SO2 as a
surrogate for the acid gas HAP. SO2 is also an acidic gas--
though not a HAP--and the controls used for SO2 emission
reduction are also effective for control of the acid gas HAP. Further,
most, if not all, affected EGUs were already measuring and reporting
SO2 emissions as a requirement of the Acid Rain Program.
The Appalachian Region Independent Power Producers Association
(ARIPPA) \48\ submitted comments on the MATS proposal arguing that the
characteristics of coal refuse made achievement of the standard too
costly for its members and requested that the EPA create a subcategory
for facilities burning coal refuse. The EPA determined that there was
no basis to create such a subcategory and finalized emission standards
for both HCl and SO2 that apply to all coal-fired EGUs. See
77 FR 9304, February 16, 2012. ARIPPA, along with other petitioners,
challenged the EPA's determination in the D.C. Circuit, and the Court
upheld the final rule. White Stallion, 748 F.3d at 1249-50.
---------------------------------------------------------------------------
\48\ ARIPPA is a non-profit trade association comprised of
independent electric power producers, environmental remediators, and
service providers located in Pennsylvania and West Virginia that use
coal refuse as a primary fuel to generate electricity.
---------------------------------------------------------------------------
In addition to challenging the final rule, ARIPPA also petitioned
the Agency for reconsideration, again requesting a subcategory for the
acid gas standards for facilities combusting all types of coal refuse.
The EPA denied the petition for reconsideration on grounds that ARIPPA
had adequate opportunity to comment on the ability of coal refuse-
combusting facilities to comply with the final standard. Furthermore,
the EPA determined that the ARIPPA petition did not present any new
information to support a change in the previous determination regarding
the appropriateness of a subcategory for the acid gas HAP standard.
ARIPPA subsequently sought judicial review of the denial of the
petition for reconsideration. ARIPPA v. EPA, No. 15-1180 (D.C.
Cir.).\49\ In petitioner's briefs, ARIPPA claimed that the EPA had
misunderstood its reconsideration petition and pointed to a distinction
between the control of acid gas emissions from units burning anthracite
refuse and those burning bituminous coal refuse. See Industry Pets. Br.
at 35-36, ARIPPA, No. 15-1180 (D.C. Cir. filed Dec. 6, 2016). The EPA
disagrees with the assertion that the Agency misunderstood the basis
for ARIPPA's reconsideration petition as we could not find a single
statement in the rulemaking record that clearly or even vaguely
requested a separate acid gas HAP limit based on the distinction
between anthracite refuse and bituminous coal refuse. Nonetheless, the
Agency recognizes that there are differences in anthracite and
bituminous coal (and, thus, between anthracite refuse and bituminous
coal refuse) and that those differences can influence the acid gas HAP
emissions from EGUs firing those respective fuels. Those differences
may also impact the unit's ability to control those emissions.
---------------------------------------------------------------------------
\49\ ARIPPA's petition for review is currently being held in
abeyance. ARIPPA v. EPA, No. 15-1180, Order, No. 1672985 (April 27,
2017).
---------------------------------------------------------------------------
B. Basis for Consideration of a Subcategory
1. Differences Between Anthracite Refuse and Eastern Bituminous Coal
Refuse
Anthracite (or ``hard coal'') is the highest quality coal as it
contains more carbon and fewer impurities--including sulfur and
chlorine--than lower ranks of coal such as bituminous coal, sub-
bituminous coal, and lignite. Anthracite is rarely used in utility
power plants, but anthracite refuse is used by a small number of EGUs
located in Pennsylvania. Bituminous coal is a middle rank coal between
subbituminous coal and anthracite. Bituminous coal typically has a high
heating value and is commonly used in electricity generation in the
United States. Bituminous coal is mined in the Appalachian region
(northern Alabama through Pennsylvania), the Interior Region (primarily
Illinois basin), and the Western Region (a small amount of bituminous
coal mined primarily in Colorado and Utah). The bituminous coal in the
Interior Region tends to have the highest sulfur content, followed by
bituminous coals from the Appalachian Region. Coals (of all types)
mined in the Western Region tend to have the lowest sulfur and chlorine
content--and the highest content of free alkali (which can act as a
natural sorbent to neutralize acid gases produced in the combustion
process). The EPA is aware of currently operational coal-refuse EGUs
that are firing anthracite refuse (10 units), subbituminous coal refuse
(1 unit), western bituminous coal refuse (1 unit), and eastern
bituminous coal refuse (12 units).
The existing eastern bituminous coal refuse-fired EGUs that are
currently in operation are listed below in Table 7 (excluding Seward,
as discussed later). The table also lists the units' net summer
capacity.
Table 7--Eastern Bituminous Coal Refuse-Fired EGUs in Current Operation
*
------------------------------------------------------------------------
ORIS Plant code Plant State Capacity (MW)
------------------------------------------------------------------------
10143................. Colver Power Project.. PA 110
10151................. Grant Town Power Plant WV 40
Unit 1A.
10151................. Grant Town Power Plant WV 40
Unit 1B.
10603................. Ebensburg Power....... PA 50
10641................. Cambria Cogen Unit 1.. PA 44
10641................. Cambria Cogen Unit 2.. PA 44
10743................. Morgantown Energy WV 25
Facility Unit 1.
10743................. Morgantown Energy WV 25
Facility Unit 2.
50974................. Scrubgrass Generating PA 42
Company LP Unit 1.
50974................. Scrubgrass Generating PA 42
Company LP Unit 2.
------------------------------------------------------------------------
* Excluding the Seward units (as explained later).
[[Page 2702]]
2. Control Technologies for Acid Gas HAP
All coal refuse fuels are fired in fluidized bed combustors (FBC)
that use limestone injection to minimize SO2 emissions and
to increase heat transfer efficiency. This limestone injection
technology may be adequate for EGUs that are firing anthracite refuse,
subbituminous, and western bituminous coal refuse to meet the MATS
alternative (surrogate) emission standard for SO2 because,
as previously mentioned, the anthracite coals are naturally much lower
in impurities (including sulfur and chlorine) and western bituminous
coals (and subbituminous coals) have lower sulfur and chlorine content
and higher free alkalinity. All anthracite coal refuse-fired and
western bituminous coal refuse-fired EGUs are currently emitting
SO2 at rates that are below the final MATS emission standard
for acid gas HAP and the subbituminous coal refuse-fired EGU is
currently emitting HCl at a rate that is below the final MATS emission
standard for acid gas HAP. Therefore, there is no need to consider a
subcategory that would include those units. No anthracite coal refuse-
fired or western bituminous coal refuse-fired EGUs are currently
reporting HCl emissions for compliance purposes; they are all opting
to, instead, report the alternative standard for SO2.
However, ARIPPA has argued that, for the eastern bituminous coal
refuse-fired EGUs, limestone injection alone is not adequate to meet
the final HCl or SO2 MATS emission standards. Operators
cannot simply continue to inject more limestone to the combustor as
that could negatively affect the operation of the combustor with
limited impact on acid gas emissions.\50\ For this reason, bituminous
coal refuse-fired EGUs are required to install some sort of downstream
acid gas control technology in order to meet the final acid gas MATS
standards. These downstream control devices could include wet FGD
scrubbers, spray dryer absorbers (SDA), or dry sorbent injection (DSI)
systems.
---------------------------------------------------------------------------
\50\ ``[I]ncreased limestone injection consistent with current
design and operational constraints cannot further reduce HCl
emissions . . . to levels consistent with the Utility MACT limit.''
See ARIPPA Petition for Reconsideration, p. 5, See also p. 10,
Docket ID No. EPA-HQ-OAR-2009-0234-20175.
---------------------------------------------------------------------------
Available information suggests that wet FGD scrubbers and SDA
systems would be particularly expensive retrofit control options for
the small units that are currently firing eastern bituminous coal
refuse. The cost effectiveness--i.e., the cost per incremental ton acid
gas HAP reduced--may be excessive and may be technically and
practically infeasible for these units. The EPA solicits comment on
whether these controls are particularly costly for these units to adopt
(Comment C-13).
The eastern bituminous coal refuse-fired EGUs can also consider
installation of DSI technology, which is a less costly control option.
A DSI system is used to inject powdered alkaline sorbent (typically
sodium- or calcium-based sorbents) into the flue gas stream. The
alkaline sorbents neutralize acidic gases and the resulting solids are
captured in a downstream PM control device (e.g., a fabric filter). DSI
has been identified as a relatively low-cost technology for control of
acid gases. Some commenters to the original MATS proposal stated that
DSI will not work on units firing bituminous coals. Some commenters
stated that DSI is only suitable for use on low-sulfur, low-chlorine
western coals. In fact, in power sector modeling using the Integrated
Planning Model (IPM) to support the development of MATS, the EPA
restricted the availability of the DSI option to only those units that
use or switch to relatively low-sulfur coal (up to 2 lb/MMBtu
SO2).\51\ Some eastern bituminous coal refuse-fired EGUs
have tested DSI systems and have identified the following problems that
make the technology infeasible. The use of sodium-based sorbents
negatively impacts the usability, and, thus, saleability, of the
captured fly ash which can be utilized in many useful ways. One
beneficial use includes using fly ash in mine reclamation activities.
The increased sodium loading from the injection of sodium-based
sorbents can increase the leachability and mobility of metals from the
fly ash.\52\ Therefore, the saleability of the fly ash may be affected
by the use of DSI. When both calcium-based and sodium-based sorbents
were injected in testing, the emissions of Hg increased considerably
(well above the final MATS emission standard for Hg). This is due to
the alkaline sorbents scavenging free halides from the flue gas
stream--which effectively helps to control acid gas emissions. However,
the free halides are also helpful in oxidizing elemental Hg so that it
can be captured in a downstream PM control device. All coal refuse-
fired EGUs are emitting at levels that are below the final MATS
standard for Hg (and also with the standard for filterable PM). In
fact, FBC units--including those firing coal refuse--are among the best
performers for Hg control.\53\ Therefore, use of DSI technology for
acid gas control (if feasible), would likely also require the
installation of Hg-specific control technology. The EPA is soliciting
comment on the technical feasibility of installing DSI, dry FGD, or
other applicable control technologies at these units and whether the
installation of acid gas HAP controls may create technical
infeasibilities in meeting other MATS emission limits (Comment C-14).
---------------------------------------------------------------------------
\51\ See 77 FR 9412.
\52\ See ARIPPA comments on EPA's Proposed Supplemental Finding,
available at Docket ID No. EPA-HQ-OAR-2009-0234-20530.
\53\ Ibid.
---------------------------------------------------------------------------
Further, most of the existing eastern bituminous coal refuse-fired
EGUs are small (most are less than 100 MW) and may be constrained by
space or other configurational limitations. However, there are two
eastern bituminous coal refuse-fired EGUs at the Seward Generating
Station in Pennsylvania that the EPA would not consider for inclusion
in a potential subcategory. The Seward units are the newest and, at 260
MW each, are by far the largest EGUs that are firing coal refuse. The
Seward units were constructed with installed downstream acid gas
controls that were part of the original design. The Seward facility,
therefore, did not suffer from space and other configurational
limitations that can affect other smaller existing eastern bituminous
coal refuse-fired EGUs that are attempting to retrofit air pollution
controls. Further, the Seward units were among the best performing
units--with respect to HCl emissions--when the EPA developed the final
MATS emission standards. And, MATS compliance reports submitted by the
Seward EGUs show that the units' HCl emissions are well below the final
MATS standard of 0.0020 lb/MMBtu.
The EPA has incomplete information on the emissions controls that
are installed at the currently operating eastern bituminous coal
refuse-fired EGUs (i.e., those identified earlier in Table 7). The EPA
solicits information on installed controls at those units, the types
and amount of sorbents or reagents (if any) that are used, and, if
present, the extent of the operation of these emissions controls
(Comment C-15). The EPA also solicits comment on the cost of
retrofitting DSI, dry FGD, or other applicable control technologies
such that eastern bituminous coal refuse-fired EGUs are able to emit at
or below the MATS standard for HCl or SO2 (Comment C-16). To
better understand the economic characteristics of the eastern
bituminous coal refuse-fired EGUs, the EPA additionally solicits
information on the operating costs of these units, availability and
cost
[[Page 2703]]
of their fuel supplies, and any planned retirements (Comment C-17).
C. Potential Subcategory Emission Standards
As mentioned, the EPA is considering establishing acid gas emission
standards for a subcategory of existing EGUs that fire eastern
bituminous coal refuse; and we are soliciting comment on the need for
such a standard (Comment C-18). The EPA has conducted an analysis to
determine what such a numerical emission standard would be. The
analysis is summarized in a separate memorandum available in the
rulemaking docket.\54\ The results of that MACT floor analysis are
shown below in Table 8. After the EPA establishes the MACT floor, it
considers the costs and non-air quality health and environmental
impacts and energy requirements to determine whether a more stringent,
or ``beyond-the-floor,'' level of control should be established. The
average SO2 lb/MMBtu emission rate was determined for each
currently operating eastern bituminous coal refuse-fired EGU using
monthly SO2 data available in the EPA's ECMPS for the period
of January 2015 through June 2018. If the EPA were to establish a
beyond-the-floor SO2 emissions limit, it would likely be in
the range of 0.60--0.70 lb/MMBtu; a limit that, on average, the
currently operating eastern bituminous coal refuse-fired EGUs have
achieved based on their monthly emissions data for January 2015 through
June 2018. Because no HCl emissions data have been submitted for the
currently operating EGUs, and SO2 lb/MWh emissions data are
available for only two of the EGUs, we could not use this same beyond-
the-floor methodology to evaluate beyond-the-floor standards for
SO2 in lb/MWh or for HCl in either lb/MMBtu or lb/MWh. We,
therefore, determined that the beyond-the-floor standards for those
pollutants should reasonably be set based on the same percentage
reduction as the SO2 lb/MMBtu described above (i.e., the 40-
percent reduction in the emissions rate for SO2 between the
MACT floor value of 1.0 lb/MMBtu and the beyond-the-floor value of 0.60
lb/MMBtu). The results of the MACT floor and the beyond-the-floor
analyses are shown below in Table 8.
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\54\ Memorandum titled NESHAP for Coal- and Oil-Fired EGUs: MACT
Floor Analysis and Beyond the MACT Floor Analysis for Subcategory of
Existing Eastern Bituminous Coal Refuse-Fired EGUs Under
Consideration, available in Docket ID No. EPA-HQ-OAR-2018-0794.
Table 8--MACT Floor Results for Potential Eastern Bituminous Coal Refuse-Fired EGUs Subcategory
----------------------------------------------------------------------------------------------------------------
Parameter HCl SO2
Subcategory -------------------------------------------------------------------------------
Number in MACT floor 5 5
----------------------------------------------------------------------------------------------------------------
Existing Eastern Bituminous Coal 99% UPL of top 5........ 0.060 lb/MMBtu 1.0 lb/MMBtu
Refuse-Fired EGUs. (i.e., MACT floor)...... 0.60 lb/MWh 15 lb/MWh
Beyond-the-floor 0.040 lb/MMBtu 0.6 lb/MMBtu
Standard. 0.40 lb/MWh 9 lb/MWh
----------------------------------------------------------------------------------------------------------------
The EPA solicits comment on these analyses and the methodology
presented in the accompanying memorandum (Comment C-19).\55\
Additionally, the EPA solicits comment on the appropriate definition of
an eastern bituminous coal refuse-fired EGU (Comment C-20).
Specifically, the EPA is seeking comment on the amount of eastern
bituminous coal refuse that an EGU must fire to be an eastern
bituminous coal refuse-fired EGU (e.g., must the EGU fire 100 percent
of the fuel or should it be allowed to co-fire some small amount of
another fuel if needed?) (Comment C-21). The EPA also solicits comment
on distinctions in smaller FBC units as compared to larger FBC units
(e.g., those less than 150 MW as compared to those greater than 150 MW
in capacity) that fire eastern bituminous coal refuse (Comment C-22).
The EPA further solicits comment on potential effects of establishing
an acid gas HAP emission standard for a subcategory of small EGUs
burning eastern bituminous coal refuse (Comment C-23).
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\55\ Ibid.
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VIII. Summary of Cost, Environmental, and Economic Impacts
The EPA estimates that there are 713 existing EGUs located at 323
facilities that are subject to the MATS rule. The basis of our estimate
of affected EGUs and facilities are provided in the Risk Modeling
Dataset Memo, which is available in the docket for this action. Because
the EPA is not proposing any amendments to the MATS rule, there would
not be any cost, environmental, or economic impacts as a result of this
proposed action.
IX. Request for Comments
We solicit comments on this proposed action. In addition to general
comments on this proposed action, we are also interested in additional
data that may improve the risk assessments and other analyses (Comment
C-24). We are specifically interested in receiving any improvements to
the data used in the site-specific emissions profiles used for risk
modeling (Comment C-25). Such data should include supporting
documentation in sufficient detail to allow characterization of the
quality and representativeness of the data or information. Section X of
this preamble provides more information on submitting data. As
described in section VII of this preamble, we also solicit comment on
establishing a subcategory and acid gas emission standards for existing
eastern bituminous coal refuse-fired EGUs.
X. Submitting Data Corrections
The site-specific emissions profiles used in the source category
risk and demographic analyses (including instructions) are available
for download on the RTR website at https://www3.epa.gov/ttn/atw/rrisk/rtrpg.html. The data files include detailed information for each HAP
emissions release point for the facilities in the source category.
If you believe that the data are not representative or are
inaccurate, please identify the data in question, provide your reason
for concern, and provide any ``improved'' data that you have, if
available. When you submit data, we request that you provide
documentation of the basis for the revised values to support your
suggested changes. To submit comments on the data downloaded from the
RTR website, complete the following steps:
1. Within this downloaded file, enter suggested revisions to the
data fields appropriate for that information.
2. Fill in the commenter information fields for each suggested
revision (i.e., commenter name, commenter organization, commenter email
address,
[[Page 2704]]
commenter phone number, and revision comments).
3. Gather documentation for any suggested emissions revisions
(e.g., performance test reports, material balance calculations).
4. Send the entire downloaded file with suggested revisions in
Microsoft[supreg] Access format and all accompanying documentation to
Docket ID No. EPA-HQ-OAR-2018-0794 (through the method described in the
ADDRESSES section of this preamble).
5. If you are providing comments on a single facility or multiple
facilities, you need only submit one file for all facilities. The file
should contain all suggested changes for all sources at that facility
(or facilities). We request that all data revision comments be
submitted in the form of updated Microsoft[supreg] Excel files that are
generated by the Microsoft[supreg] Access file. These files are
provided on the RTR website at https://www3.epa.gov/ttn/atw/rrisk/rtrpg.html.
XI. Statutory and Executive Order Reviews
Additional information about these statutes and Executive Orders
can be found at https://www.epa.gov/laws-regulations/laws-and-executive-orders.
A. Executive Order 12866: Regulatory Planning and Review and Executive
Order 13563: Improving Regulation and Regulatory Review
This action is a significant regulatory action that was submitted
to OMB for review. Any changes made in response to OMB recommendations
have been documented in the docket. The EPA does not project any
potential costs or benefits associated with this action.
B. Executive Order 13771: Reducing Regulation and Controlling
Regulatory Costs
This action is expected to be an Executive Order 13771 regulatory
action. There are no quantified cost estimates for this proposed rule
because this proposed rule is not expected to result in any changes in
costs.
C. Paperwork Reduction Act (PRA)
This action does not impose any new information collection burden
under the PRA. OMB has previously approved the information collection
activities contained in the existing regulations and has assigned OMB
control number 2060-0567. This action does not impose an information
collection burden because the EPA is not proposing any changes to the
information collection requirements.
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. This
action will not impose any requirements on small entities. The EPA does
not project any potential costs or benefits associated with this
action.
E. Unfunded Mandates Reform Act (UMRA)
This action does not contain an unfunded mandate of $100 million or
more as described in UMRA, 2 U.S.C. 1531-1538, and does not
significantly or uniquely affect small governments. The action imposes
no enforceable duty on any state, local, or tribal governments or the
private sector.
F. Executive Order 13132: Federalism
This action does not have federalism implications. It will not have
substantial direct effects 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.
G. Executive Order 13175: Consultation and Coordination With Indian
Tribal Governments
This action does not have tribal implications as specified in
Executive Order 13175. It would neither impose substantial direct
compliance costs on tribal governments, nor preempt Tribal law. Thus,
Executive Order 13175 does not apply to this action.
H. Executive Order 13045: Protection of Children From Environmental
Health Risks and Safety Risks
This action is not subject to Executive Order 13045 because it is
not economically significant as defined in Executive Order 12866, and
because the EPA does not believe the environmental health or safety
risks addressed by this action present a disproportionate risk to
children. This action's health and risk assessments are contained in
sections V.A and C, and sections VI.A and B of this preamble, and
further documented in the risk document, available in the docket for
this action.
I. Executive Order 13211: Actions Concerning Regulations That
Significantly Affect Energy Supply, Distribution, or Use
This action is not a ``significant energy action'' because it is
not likely to have a significant adverse effect on the supply,
distribution, or use of energy. This action is not anticipated to have
impacts on emissions, costs, or energy supply decisions for the
affected electric utility industry.
J. National Technology Transfer and Advancement Act (NTTAA)
This action does not involve technical standards.
K. Executive Order 12898: Federal Actions To Address Environmental
Justice in Minority Populations and Low-Income Populations
The EPA believes that this action does not have disproportionately
high and adverse human health or environmental effects on minority
populations, low-income populations, and/or indigenous peoples, as
specified in Executive Order 12898 (59 FR 7629, February 16, 1994). The
documentation for this decision is contained in section VI.A of this
preamble and the technical report, Risk and Technology Review--Analysis
of Demographic Factors for Populations Living Near Coal- and Oil-Fired
EGUs, available in the docket for this action.
Dated: December 27, 2018.
Andrew R. Wheeler,
Acting Administrator.
[FR Doc. 2019-00936 Filed 2-6-19; 8:45 am]
BILLING CODE 6560-50-P