certain Texas EGUs as an alternative to BART.\126\ On June 29, 2020,
after completing rulemaking proceedings on reconsideration, the EPA
affirmed the Texas SO2 Trading program as a BART
alternative, with certain amendments as proposed in November 2019.\127\
This rulemaking, its rationale, and subsequent reconsideration and
affirmation in June 2020 are summarized in Section II.C and are not
repeated here.
---------------------------------------------------------------------------

    \126\ See 82 FR 48324 (October 17, 2017); In the same January
2017 and October 2017 notices, the EPA also proposed and finalized
action to rely on CSAPR participation as a NOX BART
alternative for Texas EGUs, see 82 FR at 946; 82 FR at 48361.
    \127\ 85 FR 49170 (Aug. 12, 2020).
---------------------------------------------------------------------------

3. The EPA's Denial of Petition for Reconsideration of the 2017
Affirmation of CSAPR As a BART Alternative
    On November 28, 2017, the Sierra Club and NPCA submitted a petition
for partial reconsideration (2017 petition) under CAA section
307(d)(7)(B) of our September 29, 2017 action withdrawing Texas from
the CSAPR trading programs for SO2 and annual NOX
and affirming that CSAPR participation continues to satisfy
requirements as a BART alternative (September 2017 Final Rule).\128\
The petitioners alleged that it was impracticable, and indeed
impossible, to comment on the relationship between the Texas
SO2 Trading Program and the CSAPR Better-Than-BART analysis
in the final rule because the EPA did not finalize the Texas
SO2 Trading Program until after the final rule was signed
and the EPA had assumed presumptive source-specific SO2 BART
controls in the rulemaking record for the final rule.\129\ The
petitioners also alleged it was impracticable to comment on other
aspects of the EPA's geographic emissions shifting analysis, which was
not presented until the final rule.\130\ The petitioners argued that
both sets of issues are of central relevance to the September 2017
Final Rule.
---------------------------------------------------------------------------

    \128\ The Sierra Club and National Parks Conservation
Association, Petition for Partial Reconsideration of Interstate
Transport of Fine Particulate Matter: Revision of Federal
Implementation Plan Requirements for Texas; Final Rule; 82 FR 45,481
(September 29, 2017); EPA-HQ-OAR-2016-0598; FRL-9968-46-OAR
(November 28, 2017).
    \129\ Id. at 8-9.
    \130\ Id. at 9.
---------------------------------------------------------------------------

    With respect to the BART requirements in Texas, the petitioners
argued that the final rule was ``impermissibly based upon a factual
predicate that no longer exists--namely, that sulfur dioxide emission
reductions associated with the installation of presumptive source-
specific BART would be install [sic] at Texas EGUs.'' \131\ The
petitioners went on to purportedly demonstrate, using the 2012
sensitivity analysis methodology developed by the EPA, that source-
specific BART in Texas would improve visibility in Class I areas in or
affected by Texas more than CSAPR or the Texas SO2 Trading
Program.\132\
---------------------------------------------------------------------------

    \131\ Id. at 10.
    \132\ Id. at 11-13.
---------------------------------------------------------------------------

    Concurrently with the affirmation of the Texas SO2
Trading Program on June 29, 2020, the EPA issued a denial of the 2017
petition (2020 Denial).\133\ In addition to addressing the other
objections raised in the 2017 petition,\134\

the EPA included an updated sensitivity analysis (2020 sensitivity
analysis) assessing whether CSAPR would remain a valid BART alternative
based on assumptions regarding emissions performance under the Texas
SO2 Trading Program rather than source-specific BART.\135\
The EPA used the same methodology it had used in its 2012 CSAPR Better-
Than-BART determination and applied an emissions assumption for the
Texas SO2 Trading Program used by Petitioners in their 2017
petition of 320,600 tons of SO2 per year. The EPA also used
an assumption that there would be a 22,300-ton increase in emissions in
a single State in the Group 2 trading program, Georgia.\136\ The EPA
presented the results of this analysis in Table 3 of the 2020 Denial,
and we asserted that for purposes of the ``prong 2'' portion of the
BART analysis, that CSAPR continued to perform equal to or better than
BART.\137\ Based on this analysis, the EPA reaffirmed the 2012 CSAPR
Better-Than-BART determination, albeit now on the assumption of the
Texas SO2 Trading Program operating in Texas rather than
CSAPR or presumptive source-specific BART.\138\
---------------------------------------------------------------------------

    \133\ 85 FR 40286 (July 6, 2020) (``2020 Denial''); See, e.g.,
Letter from U.S. EPA Administrator Andrew Wheeler to Joshua Smith,
Sierra Club, denying petition for reconsideration (June 29, 2020),
Docket ID EPA-HQ-OAR-2016-0598-0036. The EPA concurrently sent
identical letters to other petitioners. This letter, rather than the
Federal Register notice, is what we refer to when citing specific
pages in the ``2020 Denial.''
    \134\ In their 2020 petition for partial reconsideration
summarized below, Petitioners did not renew their objections as to
other aspects of the EPA's analysis in the 2020 Denial and therefore
these issues will not be summarized here. As to the issues not
raised in their 2020 petition, but addressed in denying their 2017
petition, the EPA is not reopening the bases for denial of these
objections set forth in its 2020 Denial letter. We note that in
their 2020 petition for partial reconsideration, Petitioners noted
that they ``continue to object'' to the EPA's use of ``presumptive''
BART limits in its CSAPR better than BART analysis. See 2020
Petition at 5 n.10. The EPA is not revisiting this issue here. The
EPA explained in its 2020 Denial why this objection did not meet
either prong of the CAA section 307(d)(7)(B) test for mandatory
reconsideration, including that petitioners could have, but did not,
comment on this issue in the original 2017 affirmation rulemaking
proceeding. See 2020 Denial at 19-20.
    \135\ 2020 Denial at 13-16.
    \136\ Id. at 14-15.
    \137\ Id. at 16.
    \138\ Note that neither in the 2020 Denial or in this present
proposal are we reopening our determination in the September 2017
Final Rule that withdrawal of Texas from the annual NOX
trading program would have caused sufficient changes in modeled
NOX emissions in a revised CSAPR scenario to materially
alter the visibility impacts comparison. See 82 FR 45492 n.82. As
detailed in the November 2016 proposal, projected annual
NOX emissions from Texas EGUs were only 2,600 tons higher
than the annual NOX emissions projected for the CSAPR +
BART-Elsewhere case, in which it was assumed that the EGUs were
subject to CSAPR requirements for both ozone-season and annual
NOX emissions. The EPA determined that this relatively
small increase in NOX emissions in the CSAPR + BART-
Elsewhere case would have been too small to cause any change in the
results of either prong of the two-pronged CSAPR-Better-Than-BART
test.
---------------------------------------------------------------------------

C. Summary of the 2020 Petition for Reconsideration and Associated
Litigation

    On August 28, 2020, the Sierra Club, NPCA, and Earthjustice
submitted a petition for partial reconsideration under CAA section
307(d)(7)(B) of the EPA's 2020 Denial of their November 2017 petition
for reconsideration (2020 petition).\139\ The petitioners alleged that
because the EPA presented the updated CSAPR Better-than-BART
sensitivity calculations for the first time in its 2020 Denial of the
2017 Petition (and thus they were not afforded an opportunity to
comment), and because that updated analysis is of central relevance to
the September 2017 Final Rule, the EPA must reconsider both actions
under CAA section 307(d)(7)(B). The petitioners alleged that, contrary
to the EPA's conclusions in its 2020 Denial, the updated CSAPR Better-
Than-BART analysis demonstrates that visibility improvement under CSAPR
is not equal to or greater than visibility improvement under source-
specific BART averaged over all 140 Class I areas, or the 60 eastern
Class I areas covered by CSAPR.\140\
---------------------------------------------------------------------------

    \139\ Petition for Partial Reconsideration of Denial of Petition
for Reconsideration and Petition for Reconsideration of the
Interstate Transport of Fine Particulate Matter: Revision of Federal
Implementation Plan Requirements for Texas (Aug. 28, 2020), Docket
ID EPA-HQ-OAR-2016-0598-0041.
    \140\ Id. at 9.
---------------------------------------------------------------------------

    Specifically, Petitioners note that had the EPA's results been
reformatted to display two decimal places instead of one, the average
visibility improvement for the CSAPR + BART-Elsewhere scenario would
have been less than that of the Nationwide BART scenario on two of the
four metrics used.\141\ Thus, Petitioners concluded that the EPA's 2020
sensitivity analysis proves that the visibility improvement in the
CSAPR + BART-Elsewhere scenario, with the adjustments made to Texas's
and Georgia's emissions, is not equal to or greater than the visibility
improvement in the Nationwide BART scenario. Moreover, Petitioners also
argue that it was impracticable for them to raise these issues
concerning the sensitivity analysis during the comment period for the
September 2017 Final Rule because the sensitivity calculations were
presented for the first time in the 2020 Denial.\142\ The Petitioners
claim that the data within the 2020 sensitivity analysis addresses an
issue of central relevance to the September 2017 Final Rule, i.e.,
whether CSAPR results in an overall improvement in visibility compared
to source-specific BART. Moreover, because Petitioners claim that the
EPA's sensitivity analysis showed that source-specific BART would
result in greater visibility improvement than CSAPR, they argue that
the EPA's continued reliance on CSAPR as a BART alternative is
arbitrary, capricious, and contrary to law.\143\
---------------------------------------------------------------------------

    \141\ Id. at 11.
    \142\ Id. at 12.
    \143\ Id. at 13.
---------------------------------------------------------------------------

    Sierra Club, NPCA, and Earthjustice also filed a petition for
judicial review of the 2020 Denial in the U.S. Court of Appeals for the
District of Columbia.\144\ On November 3, 2020, this challenge and the
Petitioners' preexisting challenge to the September 2017 final analysis
(No. 17-1253 (D.C. Cir.)) were consolidated. On January 13, 2021, the
court placed the petitions for review in abeyance pending further order
of the court, and the court directed the parties to file motions to
govern following the EPA's action on the 2020 petition.
---------------------------------------------------------------------------

    \144\ National Parks Conservation Association et al. v. EPA, No.
20-1341 (D.C. Cir. filed Sept. 4, 2020).
---------------------------------------------------------------------------

    The EPA is now proposing to deny the 2020 petition in this action.

D. Criteria for Granting a Mandatory Petition for Reconsideration

    Under section 307(d)(7)(B) of the Act, ``[o]nly an objection to a
rule or procedure which was raised with reasonable specificity during
the period for public comment . . . may be raised during judicial
review.'' \145\ However, ``[i]f a person raising an objection can
demonstrate . . . that it was impracticable to raise such objection
within such time or if the grounds for such objection arose after the
period for public comment . . . and if such objection is of central
relevance to the outcome of the rule, the Administrator shall convene a
proceeding for reconsideration of the rule.'' \146\ The EPA considers
an objection to be of ``central relevance'' to the outcome of a rule
``if it provides substantial support for the argument that the
regulation should be revised.'' \147\
---------------------------------------------------------------------------

    \145\ 42 U.S.C. 7607(d)(7)(B).
    \146\ Id.
    \147\ See Coal. For Responsible Regulation, Inc. v. EPA, 684
F.3d 102, 125 (D.C. Cir. 2012) (internal citation and quotation
omitted).
---------------------------------------------------------------------------

E. The EPA's Evaluation of the Petition for Reconsideration

    The EPA proposes to deny the 2020 petition because the objections
raised to the 2020 Denial are not ``centrally relevant'' under a
scenario in which the EPA finalizes the proposal to withdraw the
present BART-alternative intrastate trading FIP for Texas EGUs and
replaces those requirements with source-specific SO2 BART
requirements. Under this scenario, the findings made in the September
2017 Final Rule (i.e., the EPA's finding that CSAPR remains better than
BART) can be affirmed. The Agency acknowledges that the petitioners
raised legitimate questions in the 2020 petition concerning the 2020
sensitivity analysis and the conclusion that CSAPR remains better than
BART in a scenario in which the Texas SO2 Trading Program is
implemented. However, with this proposal and the return to source-
specific BART requirements in Texas, this issue is effectively
resolved. The 2020 petition can therefore be denied since the

objection raised is no longer centrally relevant.
    For purposes of the 2012 analytic demonstration that CSAPR provides
for greater reasonable progress than BART, the EPA treated Texas EGUs
as subject to CSAPR for SO2 and annual NOX (as
well as ozone-season NOX). In the September 2017 Final Rule,
the EPA recognized that the treatment of Texas EGUs in the 2012
analysis would have been different if those sources were not in the
CSAPR SO2 and annual NOX programs. To address
potential concerns about continuing to rely on CSAPR participation as a
BART alternative for EGUs in the remaining CSAPR States, the EPA
provided an analysis explicitly addressing the potential effect on the
2012 analytic demonstration if the treatment of Texas (and several
other States') EGUs had been consistent with the updated scope of CSAPR
coverage following the D.C. Circuit's remand of CSAPR in EME Homer
City. In particular, in its September 2017 Final Rule, the EPA assumed
that, as for all other non-CSAPR States, Texas EGUs would be subject to
presumptive, source-specific SO2 BART limits.
    As discussed below, if the EPA's proposal in this action to
implement source-specific BART requirements at certain EGUs in Texas is
finalized, the analytical basis for the EPA's September 2017
conclusions will be restored, and that analysis will continue to
support the conclusion that CSAPR participation would achieve greater
reasonable progress than BART, despite the change in the treatment of
Texas EGUs. Consequently, by virtue of this proposed action that
relates to Texas, the EPA is also able to propose to reaffirm the
continued validity of the CSAPR better-than-BART provision, 40 CFR
51.308(e)(4), which authorizes the use of CSAPR participation as a BART
alternative for BART-eligible EGUs for a given pollutant in States
whose EGUs continue to participate in a CSAPR trading program for that
pollutant. In the September 2017 Final Rule, the EPA evaluated whether
a revised CSAPR scenario reflecting the removal of Texas EGUs from the
CSAPR SO2 program (and other changes in CSAPR's geographic
scope) would continue to satisfy the two-pronged test under 40 CFR
51.308(e)(3). Regarding the changes in CSAPR requirements for Texas
EGUs, the EPA determined that the changes would have no adverse impact
on the 2012 analytic demonstration. Finalization of this proposal would
restore the analytical bases for the EPA's conclusions in the September
2017 Final Rule. We discuss that analysis in the following paragraphs
and explain how it would be restored if this action is finalized as
proposed.
    As the EPA concluded in the September 2017 Final Rule, Texas EGUs
are ineligible to rely on CSAPR as an SO2 BART alternative.
In this proposal, we are affirming this position and rejecting the
contrary arguments that the Agency previously put forward in support of
the Texas BART-alternative FIP, as explained above in Section IV. As
explained in the November 2016 proposal,\148\ if this information had
been available at the time of the 2012 CSAPR Better-than-BART
demonstration, the treatment of Texas EGUs in the baseline case and in
the Nationwide BART case would not have changed, but in the CSAPR +
BART-Elsewhere case, Texas EGUs would have been treated as subject to
source-specific SO2 BART instead of being treated as subject
to CSAPR SO2 requirements. In the case of Texas, the
projected SO2 emissions from affected EGUs in the modeled
Nationwide BART scenario (139,300 tons per year) are considerably lower
than the projected SO2 emissions from the affected EGUs in
the CSAPR + BART-Elsewhere scenario (266,600 tons per year as modeled,
and up to approximately 317,100 tons, as addressed in the 2012
sensitivity analysis).
---------------------------------------------------------------------------

    \148\ See 81 FR 78954 (Nov. 10, 2016).
---------------------------------------------------------------------------

    As modeled, treating Texas EGUs in the CSAPR + BART-Elsewhere
scenario as subject to source-specific SO2 BART instead of
CSAPR SO2 requirements would therefore have reduced
projected SO2 emissions by between 127,300 tons and
approximately 177,800 tons in this scenario, thereby improving
projected air quality in this scenario relative to projected air
quality in both the Nationwide BART scenario and the baseline
scenario.\149\ At the lower end of this range, a reduction in
SO2 emissions of 127,300 tons would represent a reduction of
over four percent of the total SO2 emissions from EGUs in
all modeled States in the CSAPR + BART-elsewhere scenario. The EPA has
previously observed that the visibility improvements from CSAPR
relative to BART are primarily attributable to the greater reductions
in SO2 emissions from CSAPR across the overall modeled
region in the CSAPR + BART-Elsewhere scenario relative to the
Nationwide BART scenario.
---------------------------------------------------------------------------

    \149\ As explained in greater detail in Section IV, while many
States participating in CSAPR were projected to have substantially
lower SO2 emissions under CSAPR as compared to
implementing BART requirements, this was not the case for Texas's
EGUs.
---------------------------------------------------------------------------

    With a return to source-specific SO2 BART requirements
at the relevant Texas EGUs, this analysis will continue to (or, once
again will) be valid. Further, we propose to find that the conclusions
reached in the September 2017 Final Rule regarding ``emissions
shifting'' from Texas back into the remaining CSAPR region would remain
valid if source-specific BART requirements are implemented at the
relevant Texas EGUs. The September 2017 Final Rule responded to a
comment regarding potential ``emissions shifting'' when Texas was
removed from the CSAPR SO2 trading program. For purposes of
the second prong, to account for the effect of potential emissions
shifting caused by the fact that Texas sources would no longer purchase
SO2 allowances from sources in other CSAPR Group 2 States,
the EPA assumed that SO2 emissions in Georgia could increase
by up to 22,300 tons, the quantity of allowances that Texas had been
projected to purchase from the other Group 2 States in the original
CSAPR scenario. However, as detailed above, the EPA showed in 2017 that
a potential shift of up to 22,300 SO2 tons to Georgia (or
other CSAPR States) would be dwarfed by the lower SO2 tons
emitted in Texas under a source-specific BART scenario (127,300 tons or
more). Therefore, the EPA proposes that the September 2017 Final Rule's
conclusion that CSAPR would continue to pass both prongs of the better-
than-BART test, even accounting for emissions shifting, remains valid
(or will once again be valid) if this proposal is finalized and source-
specific BART is implemented in Texas.
    In summary, the EPA proposes to affirm that if the information
regarding the proposed withdrawal of CSAPR FIP requirements for
SO2 for Texas EGUs had been available at the time of the
2012 CSAPR Better-than-BART analytic demonstration, the CSAPR + BART-
Elsewhere scenario would have reflected SO2 emissions from
Texas EGUs under presumptive source-specific BART. This would have been
127,300 or more tons per year lower than the emissions projections
under CSAPR and remains a valid assumption so long as the presumed
source-specific SO2 BART reductions are in fact required in
Texas. Under this assumption--which is, again, made possible by
withdrawing the current BART-alternative FIP and implementing source-
specific BART in Texas as outlined in this proposal--emissions would
not have changed in the Nationwide BART or baseline scenarios. Instead,
modeled visibility improvement in the CSAPR + BART-Elsewhere scenario
would have been

even larger relative to the other scenarios than what was modeled in
the 2012 analytic demonstration.
    Lower SO2 emissions in Texas (after implementation of
source-specific BART) would clearly lead to more visibility improvement
on the best and worst visibility days in the nearby Class I areas.
Since the ``original'' CSAPR + BART-Elsewhere scenario passed both
prongs of the better-than-BART test (compared to the Nationwide BART
scenario and the baseline scenario), a modified CSAPR + BART-Elsewhere
scenario without Texas in the CSAPR region would without question also
have passed both prongs of the better-than-BART test. The EPA therefore
further proposes that there is no need to do any new modeling or more
complicated sensitivity analysis to affirm the findings of the
September 2017 Final Rule. And for the same reason, there is no need to
do any additional modeling or analysis to support this finding under
the current Texas BART proposal in this action (i.e., to withdraw the
Texas SO2 Trading Program and replace the FIP with source-
specific BART for Texas EGUs), assuming this proposal is finalized.
    Therefore, the EPA proposes to deny the 2020 petition for partial
reconsideration and proposes to again affirm the use of CSAPR as a BART
alternative for all States whose EGUs continue to participate in the
CSAPR trading programs as to the relevant pollutants. Specifically, the
EPA proposes to conclude that, if the present proposal and the
restoration of the analytical premise for the findings of the September
2017 Final Rule are finalized, the objections that the 2020 petition
for partial reconsideration raised as to the analysis the EPA presented
in the 2020 Denial will be resolved and are therefore not of ``central
relevance'' to the September 2017 Final Rule. We are providing the
opportunity for, and invite, public comment on this proposed denial of
the petition for partial reconsideration.

VI. The EPA's Authority To Promulgate a FIP Addressing SO2
and PM BART

A. CAA Authority To Promulgate a FIP for SO2 BART

    Under section 110(c) of the CAA, whenever the EPA disapproves a
mandatory SIP submission in whole or in part, the EPA is required to
promulgate a FIP within 2 years unless we approve a SIP revision
correcting the deficiencies before promulgating a FIP. The term
``Federal implementation plan'' is defined in Section 302(y) of the CAA
in pertinent part as a plan promulgated by the Administrator to correct
an inadequacy in a SIP.
    Beginning in 2012, following the limited disapproval of the Texas
Regional Haze SIP, the EPA has had the authority and obligation to
promulgate a FIP to address BART for Texas EGUs for SO2. As
discussed in Section II, we exercised this FIP authority in October
2017 to promulgate a BART alternative (the Texas SO2 Trading
Program) to address the inadequacy of Texas's SIP as it pertained to
BART requirements for Texas EGUs for SO2. Because we are now
proposing that the basis for the Texas SO2 Trading Program
as a BART alternative rested on an erroneous interpretation of our BART
alternative regulations, and thus proposing to withdraw the program for
the reasons explained throughout Section IV, we have an obligation
under the CAA to promulgate a FIP in its place. We propose to exercise
this FIP authority through conducting a source-specific BART analysis
for those BART-eligible EGU sources participating in the Texas
SO2 Trading Program and, as appropriate, establish source-
specific BART emission limits and associated compliance requirements,
as identified in Sections VII and VIII of this action.

B. Error Correction and CAA Authority To Promulgate a FIP--PM BART

    The EPA proposes that its prior approval of a portion of Texas's
2009 Regional Haze SIP related to its finding that no EGUs were subject
to BART requirements for PM (PM BART) was in error under CAA section
110(k)(6). Section 110(k)(6) of the CAA provides the EPA with the
authority to make corrections to actions that are subsequently found to
be in error. Ass'n of Irritated Residents v. EPA, 790 F.3d 934, 948
(9th Cir. 2015) (explaining that 110(k)(6) is a ``broad provision''
enacted to provide the EPA with an avenue to correct errors). The EPA
proposes that its approval of the portion of Texas's Regional Haze SIP
addressing PM BART for EGUs was in error, as the approval was based on
the Texas SO2 Trading Program that was promulgated in error.
Under CAA section 110(k)(6), once the EPA determines that its previous
action approving a SIP revision was in error, the EPA may revise such
action as appropriate without requiring any further submission from the
State. To correct the error here, the EPA proposes to revise its
previous approval of the portion of Texas's 2009 Regional Haze SIP
addressing PM BART for EGUs and proposes to instead disapprove this
portion of Texas's SIP.
    In the 2009 Texas Regional Haze SIP, Texas conducted a screening
analysis of the visibility impacts from PM emissions in isolation and
determined that no EGUs were subject to BART for PM based on an
assumption that BART requirements for EGUs for both SO2 and
NOX were covered by participation in an earlier trading
program (CAIR). This decision was consistent with a 2006 EPA memorandum
titled ``Regional Haze Regulations and Guidelines for Best Available
Retrofit Technology (BART) Determinations''; however, that memorandum
stated that pollutant-specific screening is only appropriate in the
limited situation where a State is relying on a BART alternative, such
as a trading program, to address both NOX and SO2
BART.\150\
---------------------------------------------------------------------------

    \150\ Memorandum from Joseph Paisie to Kay Prince, ``Regional
Haze Regulations and Guidelines for Best Available Retrofit
Technology (BART) Determinations,'' July 19, 2006, available in the
docket for this action.
---------------------------------------------------------------------------

    In our 2017 Texas BART FIP, we created the Texas SO2
Trading Program as a BART alternative to satisfy SO2 BART
requirements for EGUs. As a result, the Texas BART FIP created a
scenario in which Texas EGUs were again subject to trading programs to
address both NOX and SO2 BART, and therefore, the
EPA approved the pollutant-specific screening for PM as performed by
Texas in its 2009 Regional Haze SIP submittal. Upon further
consideration, and as described in more detail above in Section IV, we
have determined that the Texas SO2 Trading Program as
promulgated in 2017, and affirmed in 2020, was based on an erroneous
interpretation of our BART alternative regulations. As such, it failed
to meet the requirements for a valid BART alternative and thus we are
proposing to withdraw the Texas SO2 Trading Program and to
satisfy SO2 BART requirements through conducting a source-
specific BART analysis. The basis for approval of Texas's SIP related
to the BART requirements for PM for EGUs rested on our creation of a
BART alternative for SO2, and we are proposing in this
action to determine that the Texas SO2 Trading Program is
not a valid BART alternative. Consistent with our proposal regarding
the Texas SO2 Trading Program, we are also proposing that
our approval of the portion of the 2009 Texas Regional Haze SIP related
to PM BART requirements for EGUs was in error.
    Accordingly, the EPA is proposing to correct its previous approval
of the Texas 2009 Regional Haze SIP submittal related to PM BART for
EGUs by proposing to disapprove Texas's pollutant-specific PM screening
analysis and determination that PM BART emission limits are not
required for any

Texas EGUs. The EPA is proposing this action through an error
correction under CAA section 110(k)(6). If the EPA finalizes this
disapproval, the EPA will have the authority and obligation under CAA
section 110(c)(1)(B), to promulgate a FIP within 2 years. As part of
this rulemaking, the EPA proposes to promulgate a FIP addressing PM
BART requirements and satisfying that FIP obligation. As discussed
further in Section VII and Section VIII, the EPA is proposing source-
specific PM BART requirements for those EGUs that we propose to find
subject to BART.

VII. BART Analysis for SO2 and PM

    As discussed in Section IV of this action, we are proposing to
withdraw the Texas SO2 Trading Program previously
established as an alternative to SO2 BART for Texas EGUs.
Thus, to satisfy SO2 BART requirements for Texas, we are
proposing to conduct a source-specific BART evaluation consistent with
the BART Guidelines for appropriate EGU sources. Specifically, we must
evaluate EGUs that were previously identified as BART-eligible, but for
which no subject-to-BART determinations were made because they were
included in the Texas SO2 Trading Program. Additionally,
because our approval of the portion of the Texas Regional Haze SIP
related to PM BART for EGUs was in error, we are now proposing an error
correction to disapprove that portion of the Texas SIP. We propose to
address the deficiency through a source-specific BART evaluation
consistent with the BART Guidelines for PM BART for the EGU sources
that were previously identified as BART-eligible, but for which no
subject-to-BART determinations were made because they were included in
the Texas SO2 Trading Program.

A. Identification of Sources Subject to BART

    In January 2016, we approved Texas's determination of which non-EGU
sources in the State are BART-eligible and the determination that none
of the State's BART-eligible non-EGU sources are subject to BART
because they are not reasonably anticipated to cause or contribute to
visibility impairment at any Class I areas.\151\ In our October 2017
Texas BART FIP,\152\ and subsequent affirmation in 2020, addressing
BART requirements for Texas EGUs, we noted that all BART-eligible EGUs
in Texas are either covered by a BART alternative or have screened out
of being subject to BART. Our October 2017 FIP lists the units covered
by the BART alternative for SO2 (i.e., the Texas
SO2 Trading Program) and identifies which of those units are
BART-eligible.\153\ For those BART-eligible EGUs that were not covered
by the Texas SO2 Trading Program, we finalized
determinations that those EGUs are not subject-to-BART for
NOX, SO2, and PM based on screening methods as
described in our 2017 proposed rule and BART Screening TSD.\154\
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    \151\ See 81 FR 296, 301 (Jan. 5, 2016).
    \152\ See 82 FR at 48328 (Oct. 17, 2017).
    \153\ 82 FR at 48329 (Oct.17, 2017).
    \154\ See 82 FR at 48328-29 (Oct.17, 2017). Table 2 in the
October 2017 notice lists the EGUs that we finalized as being BART-
eligible, but for which we determined were not be subject-to-BART
based on various screening analysis as more fully described in the
2017 proposal (82 FR at 918-21). We are not reopening that
determination in this action.
---------------------------------------------------------------------------

    Because we are now proposing to withdraw the Texas SO2
Trading Program, we must evaluate the EGU sources that were previously
identified as BART-eligible, but for which no subject-to-BART
determinations were made because they were included in the Texas
SO2 Trading Program. The sources included in the Texas
SO2 Trading Program are identified in Table 2.

                           Table 2--Sources Included in the Texas SO2 Trading Program
----------------------------------------------------------------------------------------------------------------
              Owner/operator                             Units                          BART-eligible
----------------------------------------------------------------------------------------------------------------
AEP......................................  Welsh Power Plant Unit 1........  Yes.
                                           Welsh Power Plant Unit 2........  Yes.
                                           Welsh Power Plant Unit 3........  No.
                                           H W Pirkey Power Plant Unit 1...  No.
                                           Wilkes Unit 1 [dagger]..........  Yes.
                                           Wilkes Unit 2 [dagger]..........  Yes.
                                           Wilkes Unit 3 [dagger]..........  Yes.
CPS Energy...............................  J. T. Deely Unit 1..............  Yes.
                                           J. T. Deely Unit 2..............  Yes.
                                           O. W. Sommers Unit 1 [dagger]...  Yes.
                                           O. W. Sommers Unit 2 [dagger]...  Yes.
LCRA.....................................  Fayette/Sam Seymour Unit 1......  Yes.
                                           Fayette/Sam Seymour Unit 2......  Yes.
Luminant.................................  Big Brown Unit 1................  Yes.
                                           Big Brown Unit 2................  Yes.
                                           Martin Lake Unit 1..............  Yes.
                                           Martin Lake Unit 2..............  Yes.
                                           Martin Lake Unit 3..............  Yes.
                                           Monticello Unit 1...............  Yes.
                                           Monticello Unit 2...............  Yes.
                                           Monticello Unit 3...............  Yes.
                                           Sandow Unit 4...................  No.
                                           Stryker ST2 [dagger]............  Yes.
                                           Graham Unit 2 [dagger]..........  Yes.
                                           Coleto Creek Unit 1.............  Yes.
NRG......................................  Limestone Unit 1................  No.
                                           Limestone Unit 2................  No.
                                           W. A. Parish Unit WAP4 [dagger].  Yes.
                                           W. A. Parish Unit WAP5..........  Yes.
                                           W. A. Parish Unit WAP6..........  Yes.
                                           W. A. Parish Unit WAP7..........  No.
Xcel.....................................  Tolk Station Unit 171B..........  No.
                                           Tolk Station Unit 172B..........  No.

                                           Harrington Unit 061B............  Yes.
                                           Harrington Unit 062B............  Yes.
                                           Harrington Unit 063B............  No.
El Paso Electric.........................  Newman Unit 2 [dagger]..........  Yes.
                                           Newman Unit 3 [dagger]..........  Yes.
                                           Newman Unit **4 [dagger]........  Yes.
                                           Newman Unit **5[dagger].........  Yes.
----------------------------------------------------------------------------------------------------------------
[dagger] Gas-fired or gas/fuel oil-fired units.

    Some of the BART-eligible sources that were included in the Texas
SO2 Trading Program have retired. Welsh Unit 2 retired in
2016 \155\ and Big Brown,\156\ Monticello,\157\ and the J.T. Deely
units retired at the end of 2018.\158\ These shutdowns are permanent
and enforceable because the CAA permits for these units have been
cancelled or the units have been withdrawn from the facilities' Title V
operating permits. These units may not return to operation without
going through CAA new source permitting and Title V operating
permitting requirements. Therefore, because the units are permanently
retired, it is not necessary to include these units in our screening
analysis to determine whether these sources are subject to BART.
---------------------------------------------------------------------------

    \155\ Welsh Unit 2 was retired on April 16, 2016, pursuant to a
Consent Decree (No. 4:10-cv-04017-RGK) and subsequently removed from
the Title V permit (permit no. O26). We have included the Consent
Decree, permitting notes, and new Title V permit showing that the
Unit is removed in the docket for this action.
    \156\ See letter dated March 27, 2018, from Kim Mireles of
Luminant to the TCEQ requesting to cancel certain air permits and
registrations for Big Brown available in the docket (EPA-R06-OAR-
2016-0611-0132) for this action.
    \157\ See letter dated February 8, 2018, from Kim Mireles of
Luminant to the TCEQ requesting to cancel certain air permits and
registrations for Monticello available in the docket (EPA-R06-OAR-
2016-0611-0130) for this action.
    \158\ See letter dated December 15, 2021, from Johnny Bowers,
Team Leader Air Permits Division at TCEQ to Danielle Frerich
regarding the cancellation of air quality permits for the J.T. Deely
units available in the docket for this action.
---------------------------------------------------------------------------

    To determine which of those remaining BART-eligible sources listed
in Table 2 are anticipated to cause or contribute to visibility
impairment in any Class I area (subject-to-BART),\159\ the BART
Guidelines state that CALPUFF or another appropriate model can be used
to predict the visibility impacts from a single source at a Class I
area. The BART source is the collection of BART-eligible emission units
at a facility. A detailed discussion of the subject-to-BART screening
analysis is provided in the 2023 BART Modeling TSD.\160\ We summarize
the methodology and results of this analysis here.
---------------------------------------------------------------------------

    \159\ See 40 CFR part 51, Appendix Y, III, How to Identify
Sources ``Subject to BART.''
    \160\ See our 2023 BART Modeling TSD in our docket.
---------------------------------------------------------------------------

1. Modeling Approach
    For States (or the EPA in the case of a FIP) using modeling to
determine the applicability of BART to single sources, the first step
in the BART Guidelines is to set a contribution threshold to assess
whether the impact of a single source (collectively the BART-eligible
units at a specific facility) is sufficient to cause or contribute to
visibility impairment at a Class I area. The BART Guidelines preamble
advises that, ``for purposes of determining which sources are subject
to BART, States should consider a 1.0 deciview (dv) change or more from
an individual source to `cause' visibility impairment, and a change of
0.5 dv to `contribute' to impairment.'' \161\ The BART Guidelines
further advise that ``States should have discretion to set an
appropriate threshold depending on the facts of the situation,'' but
``[a]s a general matter, any threshold that you use for determining
whether a source `contributes' to visibility impairment should not be
higher than 0.5 dv,'' and describe situations in which States may wish
to exercise their discretion to set lower thresholds, mainly in
situations in which a large number of BART-eligible sources within the
State and in proximity to a Class I area justify this approach.\162\ We
do not believe that the sources under consideration in this rule, most
of which are not in close proximity to a Class I area, merit the
consideration of a lower contribution threshold. Therefore, our
analysis employs a contribution threshold of 0.5 dv.
---------------------------------------------------------------------------

    \161\ 70 FR at 39118.
    \162\ 70 FR at 39118.
---------------------------------------------------------------------------

    In this action we conducted modeling using both CALPUFF \163\ and
CAMx.\164\ In the 2005 BART Guidelines, CALPUFF was in part chosen
because it is much less resource intensive with respect to required
computing power, run time, and development of model inputs than
chemical transport models such as CAMx. Additionally, CAMx tools for
assessing single source impacts were still undergoing development at
that time. CAMx tools have advanced since 2005, and while still
resource intensive, for this action we were able to conduct CAMx
modeling using TCEQ's modeling platform as a starting point for this
assessment. We discuss details of the CALPUFF and CAMx modeling systems
throughout this section and in the 2023 BART Modeling TSD.
---------------------------------------------------------------------------

    \163\ EPA used the version of CALPUFF approved previously for
regulatory modeling (CALPUFF version 5.8.5, level 15214) as
discussed on EPA's website (https://www.epa.gov/scram/air-quality-dispersion-modeling-alternative-models) and this CALPUFF version is
available for download from Exponent at https://www.src.com/.
    \164\ CAMx is available for download at https://www.camx.com/.
---------------------------------------------------------------------------

    As recommended in the BART Guidelines, we performed stand-alone,
source-specific CALPUFF modeling on several of the remaining BART-
eligible sources included in Table 2 to determine which of the BART-
eligible sources in Table 2 cause or contribute to visibility
impairment in nearby Class I areas. CALPUFF is a multi-species non-
steady-state puff dispersion model that simulates the effects of
pollution transport, dispersion, transformation, and removal of
emissions from modeled sources for transport distances beyond 50 km
using general background concentrations to represent air pollution
levels that the modeled sources emissions interact. Relevant guidance
\165\ States that the CALPUFF

model is generally applicable at distances from 50 km to at least 300
km downwind of a source. However, previous Regional Haze BART SIP
modeling conducted by consultants and the States extended beyond 300km
for numerous BART analyses.\166\ In fact, in evaluating the Texas 2009
Regional Haze SIP, the EPA, FLM representatives, and TCEQ agreed with
using CALPUFF for Texas sources for distances out to 614 km.\167\
Initially, CALPUFF results beyond 300 km were thought to be potentially
conservative (overestimate impacts); however subsequent analysis of
CALPUFF indicates that it can also underpredict impacts at ranges
greater than 300km.\168\ For this particular BART analysis, we chose to
evaluate CALPUFF results out to approximately 450 km due to these
potential uncertainties that seem to be larger at ranges greater than
450 km.\169\ All BART-eligible sources that we modeled with CALPUFF in
this action have at least one Class I area within the more typical
CALPUFF range of 300km (see Table 3 for distance to most impacted Class
I areas for each modeled source). This use of CALPUFF is consistent
with the EPA's recommendation in the 2005 BART Guidelines \170\ to
determine whether a source is subject to BART and in conducting the
BART analysis for those sources determined to be subject to BART.\171\
We also have CAMx modeling results for all coal-fired BART-eligible
sources and as such we have both CALPUFF and CAMx modeling results for
the coal-fired sources within 450 km of Class I area(s). For those
sources beyond 450 km, we only used CAMx modeling results as discussed
in more detail later in this section.
---------------------------------------------------------------------------

    \165\ Interagency Workgroup on Air Quality Modeling (IWAQM)
Phase 2 Summary Report and Recommendations for Modeling Long-Range
Transport and Impacts on Regional Visibility, EPA- 454/R-98-019,
IWAQM, 1998; ``Federal Land Managers' Air Quality Related Values
Workgroup (FLAG)'': Phase I Report, FLAG, USDI--National Park
Service, Air Resources Division, Denver, CO., 2000. https://www.nature.nps.gov/air/Pubs/pdf/flag/FlagFinal.pdf; Revisions to the
Guideline on Air Quality Models: Adoption of a Preferred Long Range
Transport Model and Other Resources, 72 FR 18440 (Apr. 15, 2003).
    \166\ Historically, the EPA has indicated that use of CALPUFF
was generally acceptable at 300 km and for larger emissions sources
with elevated stacks, such as coal-fired power plants, we and FLM
representatives have also allowed or supported the use of CALPUFF
results at larger distances, beyond 400 km in some cases. For
example, South Dakota used CALPUFF for Big Stone's BART
determination, including its impact on multiple Class I areas
further than 400 km away. See 76 FR 76646, 76654 (Dec. 8, 2011), 77
FR 24845 (Apr.26, 2012). Nebraska relied on CALPUFF modeling to
evaluate whether numerous power plants were subject to BART where
the ``Class I areas [were] located at distances of 300 to 600
kilometers or more from'' the sources. See Best Available Retrofit
Technology Dispersion Modeling Protocol for Selected Nebraska
Utilities, p. 3, EPA Docket ID No. EPA-R07-OAR-2012-0158-0008.
    \167\ In our 2014 proposed action and the 2016 final action on
the 2009 Texas Regional Haze SIP, we approved the use of CALPUFF to
screen BART-eligible non-EGU sources at distances of 400 to 614 km
for some sources. 79 FR 74818 (Dec. 16, 2014), 81 FR 296 (Jan. 5,
2016).
    \168\ ``Documentation of the Evaluation of CALPUFF and Other
Long Range Transport Models using Tracer Field Experiment Data''
(PDF)(247 pp, 8 MB, 05-01-2012, 454-R-12-003). Prepared for the U.S.
Environmental Protection Agency by the ENVIRON International
Corporation. (EPA Contract No: EP-D-07-102, Work Assignment No: 4-
06); ``Evaluation of Chemical Dispersion Models using Atmospheric
Plume Measurements from Field Experiments'' (PDF)(127 pp, 3 MB, 09-
01-2012). Prepared for the U.S. Environmental Protection Agency by
the ENVIRON International Corporation. (EPA Contract No: EP-D-07-
102, Work Assignment No: 4-06 and 5-08); and ``Comparison of Single-
Source Air Quality Assessment Techniques for Ozone,
PM2.5, other Criteria Pollutants and AQRVs'' (PDF)(143
pp, 19 MB, 09-01-2012). Prepared for the U.S. Environmental
Protection Agency by the ENVIRON International Corporation. (EPA
Contract No: EP-D-07-102, Work Assignment No: 4-06 and 5-08);
https://www.epa.gov/scram/air-modeling-reports-and-journal-articles.
See 2023 BART Modeling TSD for further discussion on this topic.
    \169\ We discuss the choice of using CALPUFF model results in
the 300-450 km range in more detail in the 2023 BART Modeling TSD.
    \170\ See 70 FR 39104, 39122-23 (July 6, 2005).
    \171\ 70 FR at 39122.
---------------------------------------------------------------------------

    Consistent with the BART Guidelines, for those sources modeled with
CALPUFF, we compared the 98th percentile (equivalent to the 8th highest
daily value in each year modeled) impact from the three modeled years
to the 0.5 dv screening threshold following the modeling protocol
described in the 2023 BART Modeling TSD.\172\ The BART Guidelines
recommend that States (or the EPA in the case of a FIP) use the 24-hour
average actual emission rate from the highest emitting day of the
meteorological period modeled, unless this rate reflects periods of
start-up, shutdown, or malfunction. Consistent with this
recommendation, in this action, we used the 24-hour average actual
emission rate from the highest emitting day during the baseline period.
---------------------------------------------------------------------------

    \172\ In the 2005 BART Guidelines the selection of the 98th
percentile value rather than the maximum value was made to address
concerns with CALPUFF's limitations that could result in the maximum
from CALPUFF modeling being overly conservative. We state that,
``Most important, the simplified chemistry in the model tends to
magnify the actual visibility effects of that source. Because of
these features and the uncertainties associated with the model, we
believe it is appropriate to use the 98th percentile--a more robust
approach that does not give undue weight to the extreme tail of the
distribution.'' 70 FR at 39121.
---------------------------------------------------------------------------

    For this proposed action, we conducted modeling using a baseline
period of emissions data of 2016-2020 and used meteorological data for
2016-2018 to evaluate source visibility impacts to Class I areas. Our
selection of this baseline period for subject-to-BART screening
modeling was made based on consideration of a number of factors. We
note that most BART screening analyses, including the BART screening in
the 2009 Texas Regional Haze SIP, were based on a 2000-2004 baseline
period, used 2001-2003 meteorological data, and used 2002 in the
baseline modeling to project 2018 visibility conditions for the first
planning period SIPs. Our 2017 proposed rule also used this
period.\173\
---------------------------------------------------------------------------

    \173\ See generally 82 FR 912 (January 4, 2017).
---------------------------------------------------------------------------

    We selected the 2016-2020 emissions baseline period for subject-to-
BART screening in this instance because recent actual emissions more
accurately reflect future anticipated emissions which is required in
evaluating controls. In addition, this emissions baseline period is
consistent with the 2016-2018 meteorological period modeled. In this
manner, the screening, visibility benefit analysis, cost analysis, and
consideration of existing controls are all based on consideration of
the same baseline meteorological time period, operating conditions, and
emissions. The 2000-2004 baseline period is no longer representative of
anticipated future emissions or current operations because more recent
regulatory actions, such as the MATS rule, and market pressures have
impacted how these units now operate. We also note that our previous
use of baseline emissions data from 2000-2004 reflected steady-state
operating conditions during periods of high-capacity utilization and
was appropriate for the screening nature of the analysis rather than
any specific federally enforceable limit in effect at that time. We
believe this same approach, updated for 2016-2020, continues to serve
the same function and provides a suitable estimate of emissions during
high utilization for each of these sources. Additionally, it also
allows the screening, visibility benefit analysis, cost analysis, and
consideration of existing controls to all be based on the same baseline
period for meteorological data, operating conditions, and emissions.
Using an appropriate, updated baseline is also the foundation for
evaluating control costs once a source is determined to be subject to
BART. The BART determination includes consideration of past practices,
existing controls, and anticipated future operation. The BART
Guidelines state that in evaluating the costs of controls as part of
the five-factor analysis for sources determined to be subject to BART,
baseline annual emissions utilized for control cost analyses should be
a realistic depiction of anticipated annual emissions for the source
and calculated based upon continuation of past practice \174\ in the
absence of enforceable limitations.
---------------------------------------------------------------------------

    \174\ Past practices can include a broad consideration of
operations, changes in market conditions, and unique situations that
can impact emissions.

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

    For both the CALPUFF and CAMx modeling, the maximum 24-hour
emission rate (lb/hr) for NOX and SO2 from the
2016-2020 baseline period for each source was identified through a
review of the daily emission data obtained from the EPA's Clean Air
Markets Program Data \175\ for each of the BART-eligible units included
in Table 2. Because daily emissions are not available for PM, we used
data from EPA's Air Markets Program Data and TCEQ's Central Registry EI
information to obtain PM10 and PM2.5 tpy emission
rates for each year (2016-2020) on a unit basis. We used the annual
average lb/MMBtu and the maximum daily heat input to calculate the
maximum daily PM10 and PM2.5 emissions rates that
were used in the subject to BART modeling and were also used in the
control cases. For the gas and gas/fuel oil facilities,\176\ we
utilized the heat input data from the EPA Clean Air Markets Division
(CAMD) coupled with the EPA's AP-42 emission factors to estimate
maximum PM10 and PM2.5 emissions. The 2023 BART
Modeling TSD includes additional discussion and source-specific
information used in the CALPUFF modeling for this portion of the
screening analysis.
---------------------------------------------------------------------------

    \175\ https://campd.epa.gov/. See ``2016-2020 CAMD Data
Evaluation.xlsx'' in the docket for this action.
    \176\ When we use the term ``gas,'' we mean ``pipeline natural
gas.''
---------------------------------------------------------------------------

    As previously discussed, while the BART Guidelines recommend the
use of CALPUFF to determine which sources are anticipated to contribute
to visibility impairment, the Guidelines also allow the use of another
``appropriate model'' to predict the visibility impacts from a single
source at a Class I area. Because some of these BART-eligible sources
(included in Table 2) are beyond the distance to Class I areas for
which CALPUFF modeling is typically used, we used photochemical grid
modeling (CAMx) to evaluate the visibility impacts of those sources. In
addition, we also used CAMx to evaluate the other BART-eligible coal-
fired EGUs with SO2 emissions located within the typical
CALPUFF modeling range. The CAMx modeling includes all of these
emission sources to provide a consistent approach to compare the
modeling results across all these sources. CAMx is a photochemical grid
model that is formulated to assess the long-range transport of
emissions from sources up to distances of several thousand miles
including emissions from sources outside the range that CALPUFF is
typically utilized. CAMx allows modeling of impacts from individual
sources and assessment of their impacts on Class I areas at distances
much greater than the limited CALPUFF model system and accounts for all
the other known emissions sources in the modeling domain that results
in varying background pollution levels temporally and spatially that
individual source emissions interact. Furthermore, CAMx is also more
suited than other possible modeling approaches for evaluating the
visibility impacts of SO2, NOX, VOC, and PM
emissions, as it has a more robust chemistry mechanism that is
continually updated as the scientific community of peers agree on
chemistry, physics, and structural upgrades. As such, CAMx provides a
scientifically defensible platform for the assessment of visibility
impacts over a wide range of source-to-receptor distances that has been
used by a number of States in development of their Regional Haze SIPs,
including Texas.
    Since CAMx modeling differs in several ways from CALPUFF modeling,
we are using different metrics to evaluate BART visibility impacts from
CAMx. For CAMx modeling, we utilize the maximum daily impact as the
primary metric for BART screening and assessment of visibility impacts
as compared to the use of the 98th percentile metric with CALPUFF. As
explained in the 2023 BART Modeling TSD, this approach recognizes
differences in the models and model inputs and their application in
determining whether the source is anticipated to cause or contribute to
visibility impairment. For example, one difference is that compared to
CALPUFF, CAMx utilizes a more robust chemistry mechanism, thus the
primary concern that drove the selection of the 98th percentile value
for CALPUFF based modeling are not applicable. Furthermore, because the
CAMx modeling uses a more limited meteorological data period (one year
of meteorology instead of three years used for CALPUFF modeling), and
CAMx modeling also uses only one receptor for the Class I area \177\
versus the many receptors covering the entire area of the Class I area
that are used in CALPUFF modeling, the maximum of the daily impacts at
a Class I area is appropriate for determining if a source is subject to
BART. The use of the maximum value from CAMx also comports with TCEQ's
use of the maximum value from CAMx modeling for BART screening that
TCEQ included in the 2009 Texas Regional Haze SIP.178 179
See the 2023 BART Modeling TSD for further discussion of the CALPUFF
and CAMx modeling systems, the metrics evaluated, and the limitations
and strengths of each modeling system.
---------------------------------------------------------------------------

    \177\ For CAMx, we used the location coordinates of the 13
IMPROVE monitors that represent the 15 Class I areas, as was done in
previous modeling. IMPROVE monitor GUMO1 represents both the
Guadalupe Mountains NP and the Carlsbad Caverns NP Class I areas,
and IMPROVE monitor WHPE1 represents both Wheeler Peak and Pecos
Wilderness Areas Class I areas. IMPROVE monitors are part of a
nationwide visibility monitoring network. The IMPROVE program
establishes current visibility and aerosol conditions in mandatory
Class I areas; identifies chemical species and emission sources
responsible for existing man-made visibility impairment; documents
long-term trends in visibility; and provides regional haze
monitoring representing all visibility-protected Federal Class I
areas, where practical.
    \178\ See 2009 Texas Regional Haze SIP Appendix 9-5, ``Screening
Analysis of Potential BART-Eligible Sources in Texas''; Revised
Draft Final Modeling Protocol Screening Analysis of Potentially
BART-Eligible Sources in Texas, Environ Sept. 27, 2006; and Guidance
for the Application of the CAMx Hybrid Photochemical Grid Model to
Assess Visibility Impacts of Texas BART Sources at Class I Areas,
Environ December 13, 2007 all available in the docket for this
action. The EPA, the Texas Commission on Environmental Quality
(TCEQ), and FLM representatives verbally approved the approach in
2006 and in email exchange with TCEQ representatives in February
2007 (see email from Erik Snyder (EPA) to Greg Nudd of TCEQ Feb. 13,
2007 and response email from Greg Nudd to Erik Snyder Feb. 15, 2007,
available in the docket for this action).
    \179\ We approved Texas's subject-to-BART analysis for non-EGU
sources which relied on this CAMx modeling in our January 5, 2016,
rulemaking (81 FR 296).
---------------------------------------------------------------------------

    For this proposed action, our CAMx modeling platform began with
TCEQ's 2016 Modeling Platform,\180\ namely TCEQ's 2016 emissions data,
2016 meteorological data, and other modeling files utilized in their
CAMx modeling for TCEQ's Second Planning Period Texas Regional Haze
SIP. We are using this updated modeling platform to reflect more recent
meteorology and emissions inventories and have identified it to be the
best available platform for modeling these sources in Texas.\181\ We
upgraded this modeling platform to the newest version of the CAMx
model, adjusted emissions for BART-eligible units, and utilized

different/new Particulate Matter Source Apportionment Technology (PSAT)
\182\ categories (individual EGU units and facilities) to track source
contributions for BART-eligible units. These adjustments are explained
in more detail in the 2023 BART Modeling TSD.
---------------------------------------------------------------------------

    \180\ For this action, we used TCEQ's 2016 modeling platform
from its Second Planning Period Regional Haze SIP revision. TCEQ
submitted this Second Planning Period Regional Haze SIP revision to
the EPA on July 20, 2021. The EPA has not reviewed this SIP nor
proposed action on this SIP, but we are utilizing the modeling
platform developed by TCEQ for this SIP to perform our modeling
analyses to determine whether a source is subject to BART and in
conducting the BART analysis for those sources determined to be
subject to BART. The EPA will evaluate the Second Planning Period
Regional Haze SIP submitted by TCEQ in a separate action. The SIP is
available at https://www.tceq.texas.gov/airquality/sip/bart/haze_sip.html and in the docket for this action.
    \181\ Consequently, a 2016-2018 period for CALPUFF modeling and
2016-2020 emissions would be consistent with this choice.
    \182\ CAMx includes an advanced mechanism that allows tracking
the contributions of individual sources and pollutants within the
grid model. For purposes of tracking particulate matter formation,
we employed the CAMx PSAT for the BART-eligible sources included in
the Texas SO2 Trading Program, including the three coal-
fired EGU sources that did not screen out with the CALPUFF modeling
(Harrington, Martin Lake, and Welsh).
---------------------------------------------------------------------------

    Using the BART Guidelines recommended maximum daily emissions and
post-processing approach, if the source (which is the aggregate of all
BART-eligible units at a specific facility) is shown to contribute less
than 0.5 dv to visibility impairment at all modeled Class I areas on
all modeled days, then it is said to be ``not subject to BART'' and may
be excluded from further steps in the BART process. The maximum modeled
impact for each source, taking into account the annual average natural
background conditions at the Class I areas, was compared to the 0.5 dv
contribution threshold. See the 2023 BART Modeling TSD for additional
details on the CAMx modeling.
2. Subject to BART Determinations Based on CALPUFF and CAMx Modeling
Results
    Table 3 shows the CALPUFF modeling results for the screening
analysis. The Graham, Newman, Stryker Creek, and Wilkes BART-eligible
units (all gas-fired or gas/fuel oil-fired BART-eligible units) that
were included in the Texas SO2 Trading Program can be
exempted from further analysis because they all have modeled maximum
98th percentile annual impacts at all Class I areas of less than the
0.5 dv threshold. When considering impacts modeled using CALPUFF, a
source is considered subject to BART if any of the three annual 98th
percentile values are 0.5 dv or greater. As Table 3 shows, the coal-
fired BART-eligible units at Martin Lake, Harrington, and Welsh did not
screen out based on the CALPUFF modeling and thus are considered to
cause or contribute to visibility impairment at Class I areas. See the
2023 BART Modeling TSD for this action for more details on the CALPUFF
modeling and the modeling results.

                                                        Table 3--CALPUFF BART Screening Analysis
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Maximum delta deciviews
          Plant name             Operator name     Boiler ID(s)    Most impacted class ------------------------------------------------ Less than 0.5 dv
                                                                    I area (distance)        2016            2017            2018
--------------------------------------------------------------------------------------------------------------------------------------------------------
Graham.......................  Luminant........  2..............  Wichita Mountains              0.297           0.203           0.423  Yes.
                                                                   (174 km).
Newman.......................  El Paso Electric  2, 3, **4, **5.  Guadalupe Mountain             0.342           0.368           0.354  Yes.
                                                                   (133 km).
Stryker Creek................  Luminant........  ST2............  Caney Creek (283 km)           0.054           0.059           0.064  Yes.
Wilkes Power Plant...........  AEP.............  1, 2, 3........  Caney Creek (174 km)           0.380           0.373           0.442  Yes.
Martin Lake..................  Luminant........  1,2,3..........  Caney Creek (238 km)            3.28            3.60            3.35  No.
Harrington...................  Xcel............  061B, 062B.....  Salt Creek (305 km).            0.49            0.59            0.54  No.
Harrington...................  Xcel............  061B, 062B.....  Wichita Mountains               0.54            0.45            0.58  No.
                                                                   (278 km).
Welsh........................  AEP.............  1..............  Caney Creek (161 km)             0.7            0.94            0.96  No.
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Table 4 summarizes the results of the CAMx screening analysis.
These results also establish the baseline impacts for further modeling
analyses of potential visibility benefits of controls. We note that all
six sources analyzed with CAMx PSAT modeling had impacts greater than
0.5 dv at one or more Class I areas. Table 4 also shows that the CAMx-
predicted visibility impacts range from 0.52 dv to 6.69 dv for these
six sources at individual Class I areas on their maximum impact day.
Additionally, Table 4 shows the number of days impacted over 0.5 dv and
1.0 dv at the maximum impacted Class I areas for each source. We note
that maximum impacts from Fayette \183\ are just above the 0.5 dv
threshold and only exceed the threshold on one day. However, because
the intent of the screening analysis is to be inclusive, we therefore
consider Fayette subject to BART. The relatively lower visibility
impacts and potential benefits from controls will be considered as part
of the five-factor analysis when determining the potential availability
of cost-effective emission reductions. With the exception of Fayette,
the BART-eligible sources modeled using CAMx had maximum impacts well
over the 0.5 dv threshold on multiple modeled days (ranging from 8 to
150 days).
---------------------------------------------------------------------------

    \183\ Fayette Power Project is also known as Sam Seymour. We
refer to it as Fayette throughout this document.

                                                  Table 4--CAMx BART Screening Source Analysis Summary
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Number of       Number of
       BART-eligible source                 Units           Most impacted class  Maximum delta-     Less than 0.5 dv?      modeled days    modeled days
                                                                  I area               dv                                  >=0.5 dv \1\    >=1.0 dv \1\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Coleto Creek......................  1....................  Caney Creek.........            1.55  No.....................              18               2
Fayette Power.....................  1 & 2................  Caney Creek.........            0.52  No.....................               1               0
Harrington........................  061B & 062B..........  White Mountain......            2.64  No.....................               8               3
Martin Lake.......................  1, 2, & 3............  Caney Creek.........            6.69  No.....................             150             101
W. A. Parish......................  WAP4, WAP5, & WAP6...  Wichita Mountains...            3.97  No.....................              35              12
Welsh.............................  1....................  Caney Creek.........            1.58  No.....................              27               6
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Number of days over 0.5 or 1.0 dv at the most impacted Class I area. See Table 12 for cumulative results at the 15 Class I areas analyzed.

    Based on the modeling analysis, the BART-eligible sources in Table
5 have been determined to cause or contribute to visibility impairment
at a nearby Class I area; therefore, we propose to find the six sources
are subject to BART. We must establish emission limits for visibility
impairing pollutants SO2 and PM through further evaluation
using the BART five factor analysis.\184\
---------------------------------------------------------------------------

    \184\ The NOX BART requirement for these EGU sources
is not addressed by source-specific limits in this proposal. The
EPA's determination that Texas' participation in CSAPR for ozone-
season NOX satisfies NOX BART for EGUs was
finalized in our October 17, 2017 final rule (82 FR 48324), thus
dispensing with the need for source-specific BART determinations and
requirements for NOX. We did not reopen that
determination in our August 2018 proposal, November 2019
supplemental proposal, or August 2020 final rule, and are not
reopening it in this proposal.

                Table 5--Sources That Are Subject-to-BART
------------------------------------------------------------------------
                 Facility                               Units
------------------------------------------------------------------------
Coleto Creek..............................  1.
Fayette Power.............................  1 & 2.
Harrington................................  061B & 062B.
Martin Lake...............................  1, 2 & 3.
W. A. Parish..............................  WAP4, WAP5 & WAP6.
Welsh.....................................  1.
------------------------------------------------------------------------

3. Subject to BART Determination for O.W. Sommers Units 1 and 2
    CPS Energy operates the Calaveras Power Station which is comprised
of O. W. Sommers Units 1 and 2, J. T. Deely Units 1 and 2,\185\ and J.
K. Spruce Units 1 and 2. In our 2017 Texas BART proposal, we identified
O. W. Sommers Units 1 and 2 and J. T. Deely Units 1 and 2 as BART-
eligible and conducted CAMx modeling to determine their visibility
impacts. Because J. T. Deely Units 1 and 2 subsequently ceased
operation and shut down, our analysis in this action is limited to the
two gas-fired units at O. W. Sommers. Given the retirement of the two
coal-fired units at J. T. Deely and the low SO2 emissions
from the O. W. Sommers gas-fired EGUs, rather than conducting new CAMx
modeling, we updated our analysis of O. W. Sommers Units 1 and 2
relying on the CAMx modeling from our 2017 Texas BART proposal (further
referred to as 2017 Proposal). In that analysis, we conducted CAMx
modeling using the combined maximum 24-hour emissions from both J. T.
Deely Units 1 and 2 and O. W. Sommers Units 1 and 2 to determine if the
aggregate BART-eligible source (all four BART-eligible units at
Calaveras Power Station) was subject to BART. The maximum modeled
impact from the Calaveras Power Station was 1.513 dv. As documented in
the BART Screening TSD and associated supporting documents for the 2017
BART FIP,\186\ the impacts of the two O. W. Sommers BART-eligible units
were previously estimated to have a maximum visibility impact of 0.286
dv at the Caney Creek Class I area, which is below the 0.5 dv
threshold.\187\
---------------------------------------------------------------------------

    \185\ Acosta, Sarah (January 3, 2019). ``CPS Energy closes coal-
fired Deely plant in operation since `70s to focus on cleaner energy
sources''. KSAT-TV. Retrieved January 4, 2019.
    \186\ ``Technical Support Document Our Strategy for Assessing
which Units are Subject to BART for the Texas Regional Haze BART
Federal Implementation Plan (BART Screening TSD), pdf page 72 and
Appendix E, available in the docket EPA-R06-OAR-2016-0611 (at EPA-
R06-OAR-2016-0611-0005).
    \187\ Id. pdf page 72 and Appendix E. CAMx Maximum Impact at
each Class Area; The O. W. Sommers BART-eligible units were modeled
individually, the sum (maximum dv impacts) of which is 0.286 dv.
Adding the maximum impacts of each unit results in a slight
overestimation of the visibility impacts, since we did not first
calculate total extinction and then dv, which is a natural
logarithmic function. Therefore 0.286 dv is conservative (higher
than if modeled).
---------------------------------------------------------------------------

    To bolster our current analysis, we also compared the modeled
SO2 and NOx emission rates from the O. W. Sommers
units with the recent maximum daily emissions from 2016-2020. Sulfate
and nitrate made up almost all of the extinction value on the maximum
impact day at Caney Creek Class I area, with approximately 89 percent
of the total extinction from nitrates and 9 percent from sulfates on
the maximum impact day due to emissions from O. W. Sommers. Because the
two O. W. Sommers BART-eligible units are located near each other and
have similar stack parameters, we used a linear adjustment comparing
emissions modeled previously to more recent emissions (2016-2020) to
provide an estimate of current visibility impact. While linear scaling
does not result in the same values as modeling, it is a reasonable
methodology to conservatively approximate the visibility impact from a
source.
    Table 6 compares the NOX and SO2 emission
rates modeled in the 2017 Proposal to the maximum daily emission rates
of NOX and SO2 from the 2016-2020
period.188 189 We did not compare PM10 or
PM2.5 as they were less than 3 percent of the total light
extinction on the maximum impact day. SO2 emissions from the
2016-2020 period were less than 3 percent of what was previously
modeled, and NOX emissions were 13.71 percent higher than
what was modeled for our 2017 Proposal for these two units.
Acknowledging that the reduction in SO2 emissions will
result in lower visibility impact, we choose to not adjust for the
lower SO2 emissions in an effort to be conservative in our
analysis. Scaling the 2017 visibility impact (0.286 dv at Caney Creek
Class I area) linearly to account for the 13.71 percent total increase
in NOX emissions, we estimate a maximum visibility impact of
0.325 dv at the Caney Creek Class I area, which is well below the 0.5
dv threshold. Based on this analysis, it is reasonable to conclude that
if emissions from the two O. W. Sommers BART-eligible units were
remodeled using recent emissions, it would result in a maximum
visibility impact less than 0.5 dv and would screen out of further
analysis. Therefore, the EPA proposes that O. W. Sommers Units 1 and 2
are not subject to BART.
---------------------------------------------------------------------------

    \188\ Id. Appendix A. Modeled parameters: Stack and emissions
for CAMx modeled sources for modeled emissions in 2017 proposal.
    \189\ https://campd.epa.gov/.

                           Table 6--O. W. Sommers BART-Eligible Units Emissions Modeled in 2017 vs. Recent 2016-2020 Emissions
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                         O. W. Sommers modeled in 2017 proposal (TPD)     O. W. Sommers max daily emissions 2016-2020
                                       ------------------------------------------------                      (TPD)                       2016-2020 Total
                                                                                ------------------------------------------------ as percentage of
                                            Unit 1          Unit 2           Total          Unit 1          Unit 2           Total      2017 modeled (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
SO2...................................            2.01           10.92           12.93           0.167           0.147            0.31              2.43
NOX...................................            5.96            8.04           14.00            9.32             6.6           15.92            113.71
--------------------------------------------------------------------------------------------------------------------------------------------------------

B. BART Five Factor Analysis

    The purpose of the BART analysis is to identify and evaluate the
best system of continuous emission reduction based on the BART
Guidelines.\190\ In determining BART, a State, or the EPA when
promulgating a FIP, must consider the five statutory factors in section
169A of the CAA: (1) The costs of compliance; (2) the energy and non-
air quality environmental impacts of compliance; (3) any existing
pollution control technology in use at the source; (4) the remaining
useful life of the source; and (5) the degree of improvement in
visibility which may reasonably be anticipated to result from the use
of such technology. See also 40 CFR 51.308(e)(1)(ii)(A). This is
commonly referred to as the ``BART five factor analysis.'' The BART
Guidelines break the analyses of these requirements into five steps:
\191\
---------------------------------------------------------------------------

    \190\ See July 6, 2005 BART Guidelines, 40 CFR part 51, Regional
Haze Regulations and Guidelines for Best Available Retrofit
Technology Determinations.
    \191\ 70 FR 39104, 39164 (July 6, 2005) [40 CFR part 51, App.
Y].
---------------------------------------------------------------------------

    STEP 1--Identify All Available Retrofit Control Technologies,
    STEP 2--Eliminate Technically Infeasible Options,
    STEP 3--Evaluate Control Effectiveness of Remaining Control
Technologies,
    STEP 4--Evaluate Impacts and Document the Results, and
    STEP 5--Evaluate Visibility Impacts.
    The following sections treat these steps individually for
SO2. We are combining these steps into one section in our
assessment of PM BART that follows the SO2 sections.
1. Step 1 and 2: Technically Feasible SO2 Retrofit Controls
    The BART Guidelines state that in identifying all available
retrofit control options,

    [Y]ou must identify the most stringent option and a reasonable
set of options for analysis that reflects a comprehensive list of
available technologies. It is not necessary to list all permutations
of available control levels that exist for a given technology--the
list is complete if it includes the maximum level of control each
technology is capable of achieving.\192\
---------------------------------------------------------------------------

    \192\ 70 FR at 39164, fn 12 [40 CFR part 51, App. Y].

    Adhering to this, we will identify a reasonable set of
SO2 control options, including those that cover the maximum
level of control each technology is capable of achieving. We will also
note whether any of these technologies are technically infeasible.
    The subject-to-BART units identified in Table 5 can be organized
into three broad categories, based on their fuel type and the potential
types of SO2 control options that could be available: (1)
coal-fired EGUs with no SO2 scrubber, (2) coal-fired EGUs
with existing SO2 scrubbers, and (3) gas-fired EGUs that do
not burn oil. This classification is represented in Table 7.

                             Table 7--Fuel/Control Types for Subject-to-BART Sources
----------------------------------------------------------------------------------------------------------------
                                                                            Coal (existing
              Facility                     Unit       Coal (no scrubber)       scrubber)              Gas
----------------------------------------------------------------------------------------------------------------
Coleto Creek (Dynegy)...............               1                  X
Fayette (LCRA)......................               1                                      X
Fayette (LCRA)......................               2                                      X
Harrington Station (Xcel)...........            061B                  X
Harrington Station (Xcel)...........            062B                  X
Martin Lake (Luminant)..............               1                                      X
Martin Lake (Luminant)..............               2                                      X
Martin Lake (Luminant)..............               3                                      X
W. A. Parish (NRG)..................            WAP4                                                          X
W. A. Parish (NRG)..................            WAP5                  X
W. A. Parish (NRG)..................            WAP6                  X
Welsh Power Plant (AEP).............               1                  X
----------------------------------------------------------------------------------------------------------------

    For the coal-fired EGUs without an existing scrubber, we have
identified four potential control technologies: (1) coal pretreatment,
(2) Dry Sorbent Injection (DSI), (3) dry Flue Gas Desulfurization
(FGD), and (4) wet FGD. For the coal-fired EGUs with existing
scrubbers, we will examine whether those scrubbers can be upgraded.
    Gas-fired EGUs that do not burn oil (W. A. Parish Unit WAP4) have
inherently very low SO2 emissions and there are no known
SO2 controls that can be evaluated.
a. Identification of Technically Feasible SO2 Retrofit
Control Technologies for Coal-Fired Units
    Available SO2 control technologies for coal-fired EGUs
consist of either pretreating the coal in order to improve its
qualities or by treating the flue gas through the installation of
either DSI or some type of scrubbing technology.
Coal Pretreatment
    Coal pretreatment, or coal upgrading, has the potential to reduce
emissions by reducing the amount of coal that must be burned in order
to result in the same heat input to the boiler. Coal pretreatment
broadly falls into two categories: coal washing and coal drying.
    Coal washing is often described as preparation (for particular
markets) or cleaning (by reducing the amount of mineral matter and/or
sulfur in the product coal).\193\ Washing operations are carried out
mainly on bituminous and anthracitic coals, as the characteristics of
subbituminous coals and lignite (brown coals) do not lend themselves to
separation of mineral matter by this means, except in a few cases.\194\
Coal is mechanically sized, then various washing techniques are
employed, depending on the particle size, type of coal, and the desired
level of preparation.\195\ Following the coal washing, the coal is
dewatered, and the waste streams are disposed.
---------------------------------------------------------------------------

    \193\ Couch, G. R., ``Coal Upgrading to Reduce CO2
emissions,'' CCC/67, October 2002, IEA Clean Coal Centre.
    \194\ Id.
    \195\ Various coal washing techniques are treated in detail in
Chapter 4 of Meeting Projected Coal Production Demands In The USA,
Upstream Issues, Challenges, and Strategies, The Virginia Center for
Coal and Energy Research, Virginia Polytechnic Institute and State
University, contracted for by the National Commission on Energy
Policy, 2008.
---------------------------------------------------------------------------

    Coal washing takes place offsite at large dedicated coal washing
facilities, typically located near where the coal is mined. Coal
washing carries with it a number of problems:
     Coal washing is not typically performed on the types of
coals used in

the power plants under consideration, Powder River Basin (PRB)
subbituminous and Texas lignites.
     Coal washing poses significant energy and non-air quality
considerations under section 51.308(e)(1)(ii)(A). For instance, it
results in the use of large quantities of water,\196\ and coal washing
slurries are typically stored in impoundments, which can, and have,
leaked.\197\
---------------------------------------------------------------------------

    \196\ ``Water requirements for coal washing are quite variable,
with estimates of roughly 20 to 40 gallons per ton of coal washed (1
to 2 gal per MMBtu) (Gleick, 1994; Lancet, 1993).'' Energy Demands
on Water Resources, Report to Congress on the Interdependency of
Energy and Water, U.S. Department of Energy, December 2006.
    \197\ Committee on Coal Waste Impoundments, Committee on Earth
Resources, Board on Earth Sciences and Resources, Division on Earth
and Life Studies; Coal Waste Impoundments, Risks, Responses, and
Alternatives; National Research Council; National Academy Press,
2002.
---------------------------------------------------------------------------

    Because of these issues, we do not consider coal washing as a part
of our reasonable set of options for analysis as BART SO2
control technology.
    In general, coal drying consists of reducing the moisture content
of lower rank coals, thereby improving the heating value of the coal
and so reducing the amount of coal that has to be combusted to achieve
the same power, thus improving the efficiency of the boiler. In the
process, certain pollutants are reduced as a result of (1) mechanical
separation of mineralized sulfur (e.g., iron pyrite) and rocks, and (2)
the unit burning less coal to make the same amount of power.
    Coal drying could be considered a potential BART control. Great
River Energy has developed a patented process which is being
successfully utilized at the Coal Creek facility in North Dakota and is
potentially available for installation at other facilities.\198\ This
process utilizes excess waste heat to run trains of moving fluidized
bed dryers. The process offers a number of co-benefits, such as general
savings due to lower coal usage (e.g., coal cost, ash disposal), less
power required to run mills and ID fans, and lower maintenance on coal
handling equipment air preheaters, etc. Coal Creek units also utilize
wet FGD to reduce SO2 emissions. Therefore, the observed
additional SO2 emission reductions are due to the
combination of a higher percentage of flue gas being scrubbed
(decreased bypass of the wet FGD) in combination with a decrease in
coal usage and any removal of sulfur in the drying process. We are not
aware of any other EGUs in the United States that utilize coal drying
for the purpose of reducing SO2 emissions. Therefore, we
believe coal drying has limited application at EGUs in the United
States.
---------------------------------------------------------------------------

    \198\ DryFining\TM\ is the company's name for the process. It is
described here: https://www.powermag.com/improve-plant-efficiency-and-reduce-co2-emissions-when-firing-high-moisture-coals/.
---------------------------------------------------------------------------

    Although coal drying may be a potential option for generally
improving boiler efficiency and obtaining some reduction in
SO2, its analysis presents a number of difficulties. For
instance, the degree of reduction in SO2 is dependent on
several factors. These include (1) the quality and quantity of the
waste heat available at the unit, (2) the type of coal being dried
(amount of bound sulfur, i.e., pyrites, moisture content), and (3) the
design of the boiler (e.g., limits to steam temperatures, which can
decrease due to the reduced flue gas flow through the convective pass
of the boiler). As a result of these issues, we do not further assess
coal drying as part of our reasonable set of options for BART analysis.
DSI
    DSI is not a stand-alone, add-on air pollution control system but a
modification to the combustion unit or ductwork. DSI is performed by
injecting a dry reagent into the hot flue gas, which chemically reacts
with SO2 and other gases to form a solid product that is
subsequently captured by the particulate control device. A blower
delivers the sorbent from its storage silos through piping directly to
the flue gas ducting via injection lances. In general, there are many
types of sorbent materials, but their efficacy is variable and
dependent on operating conditions. Trona is currently the most commonly
used sorbent for SO2 removal and is a naturally occurring
mineral primarily mined from the Green River Formation in Wyoming.
Trona can also be processed into sodium bicarbonate, which is more
reactive with SO2 than trona, but more expensive. Hydrated
lime is another potential sorbent that is more frequently used for acid
gas control.199 200
---------------------------------------------------------------------------

    \199\ See Documentation for the EPA's Power Sector Modeling
Platform v6 Using the Integrated Planning Model, dated September
2021, page 5-19. Documentation for v.6 downloaded from https://www.epa.gov/power-sector-modeling/documentation-epas-power-sector-modeling-platform-v6-summer-2021-reference.
    \200\ ``Dry Sorbent Injection of Sodium Sorbents,'' presented at
the LADCO Lake Michigan Air Directors Consortium, Emission Control
and Measurement Technology for Industrial Sources Workshop, March
24, 2010. A copy of the presentation is located in the docket at
EPA-R06-OAR-2016-0611-0043.
---------------------------------------------------------------------------

    There are many examples of DSI being used on coal-fired EGUs.
However, DSI may not be technically feasible at every coal-fired EGU.
For example, DSI technology is not a technically feasible control
option for boilers that burn fuels with sulfur content greater than 2
lb SO2/MMBtu.\201\ Although individual installations may
present technical difficulties or poor performance due to the
suboptimization of operational factors, we believe that DSI may be a
particularly appropriate SO2 control option for boilers that
burn low-sulfur coal or lignite, as such boilers typically do not need
SO2 controls with very high control efficiencies (i.e.,
greater than 95 percent) to achieve low emission rates. Because the
Texas coal-fired EGUs we are evaluating in this proposal burn low-
sulfur coal, we find that they are well suited for consideration of DSI
for SO2 control. Additionally, boilers that operate DSI and
burn low-sulfur coal require much less sorbent than boilers burning
high-sulfur coal to achieve similar control efficiencies. We also note
that DSI is a common control technology that has been widely installed
for compliance with the acid gas control requirements in the Mercury
and Air Toxics Standards (MATS).\202\ For these reasons, we find that
DSI is technically feasible and should be considered as a potential
BART control.
---------------------------------------------------------------------------

    \201\ IPM Model--Updates to Cost and Performance for APC
Technologies, Dry Sorbent Injection for SO2/HCl Control
Cost Development Methodology, Final April 2017, Project 13527-001,
Eastern Research Group, Inc., Prepared by Sargent & Lundy, page 3.
Documentation for v.6: Chapter 5: Emission Control Technologies,
Attachment 5-5: DSI Cost Methodology, downloaded from https://www.epa.gov/sites/default/files/2018-05/documents/attachment_5-5_dsi_cost_development_methodology.pdf.
    \202\ The MATS rule was finalized by the EPA in December 2011,
and compliance with the standard was required by 2015. The MATS rule
requires that plants greater than 25 megawatts meet the maximum
achievable control technology for mercury, hydrochloric acid, and
filterable particulate matter (note the MATS rule does not require
controls for SO2). See https://www.epa.gov/mats/regulatory-actions-final-mercury-and-air-toxics-standards-mats-power-plants.
---------------------------------------------------------------------------

SO2 Scrubbing Systems
    In contrast to DSI, SO2 scrubbing techniques utilize a
large, dedicated vessel in which the chemical reaction between the
sorbent (typically lime or limestone) and SO2 takes place
either completely or in large part. Also, in contrast to DSI systems,
SO2 scrubbers add water to the sorbent when introduced to
the flue gas. The two predominant types of SO2 scrubbing
employed at coal-fired EGUs are wet FGD and dry FGD. The U.S. Energy
Information Administration (EIA) reports \203\ the following types of
flue

gas desulfurization systems as being operational in the U.S. for 2020:
---------------------------------------------------------------------------

    \203\ See EIA-860 data available here: https://www.eia.gov/electricity/data/eia860/.

          Table 8--EIA Reported Desulfurization Systems in 2020
------------------------------------------------------------------------
                                                             Number of
                          Type                             installations
------------------------------------------------------------------------
Wet spray tower scrubber................................             288
Spray dryer absorber....................................             256
Circulating dry scrubber................................              41
Packed tower wet scrubber...............................               4
Venturi wet scrubber....................................              58
Jet bubbling reactor....................................              23
Tray tower wet scrubber.................................              63
Mechanically aided wet scrubber.........................               4
DSI.....................................................             149
Other...................................................              36
Unspecified.............................................               0
                                                         ---------------
  Total.................................................             922
------------------------------------------------------------------------

    Excluding the DSI installations,\204\ EIA lists 773 SO2
scrubber installations in operation in 2020. Of these, 288 are listed
as being spray type wet scrubbers, with an additional 63 listed as
being tray type wet scrubbers.\205\ An additional 256 are listed as
being spray dry absorber (SDA) scrubbers, which are a type of dry FGD.
Consequently, spray type or tray type wet scrubbers (wet FGD) account
for approximately 45 percent of all scrubber systems, and SDA accounts
for approximately 33 percent of all scrubber systems that were
operational in the U.S. in 2020.
---------------------------------------------------------------------------

    \204\ As discussed in this section, DSI is more commonly
installed for compliance with the acid gas control requirements for
MATS, not for meeting SO reduction requirements.
    \205\ Trays are often employed in spray type wet scrubbers and
EIA lists some of the wet spray tower systems as secondarily
including trays.
---------------------------------------------------------------------------

    We consider some of the other scrubber system types (e.g., venturi
and packed wet scrubber types) to be older, outdated technologies (that
are not existing controls or factor into considerations regarding
existing controls) and therefore will not be considered in our BART
analysis. Circulating dry scrubbers (CDS) is another type of dry
scrubbing system that can achieve high removal efficiencies but has
seen more limited use in the United States compared to SDA.\206\ Based
on available data, CDS systems have installed costs that are comparable
to SDA systems even though there are differences in design.\207\ CDS
systems may be capable of achieving a slightly higher control
efficiency than SDA, but based on 2019 data for coal-fired units at
power plants, the 12-month average emission rate for the top performing
50 percent FGD systems is 0.06 lb/MMBtu for SDA systems and 0.12 lb/
MMBtu for CDS systems.\208\
---------------------------------------------------------------------------

    \206\ See the EPA Air Pollution Control Cost Manual, Seventh
Edition (April 2021), Section 5, Chapter 1, page 1-44. The EPA Air
Pollution Control Cost Manual is available at https://www.epa.gov/economic-and-cost-analysis-air-pollution-regulations/cost-reports-and-guidance-air-pollution#cost%20manual. The EPA is currently in
the process of updating the Control Cost Manual and this update will
be the Seventh Edition. Although updates are not yet complete for
all sections the EPA intends to update in the Seventh Edition,
updated Section 5, Chapter 1, which is titled ``Wet and Dry
Scrubbers for Acid Gas Control,'' is now available and is part of
the Seventh Edition of the Control Cost Manual.
    \207\ See Control Cost Manual, Wet and Dry Scrubbers for Acid
Gas Control Response to Comment Document, pg 32. Available at
chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.epa.gov/sites/default/files/2021-05/documents/rtcdocument_wet_and_dry_scrubbers_controlcostmanual_7thedition.pdf
and in the docket for this action.
    \208\ The EPA Air Pollution Control Cost Manual (the Control
Cost Manual, or Manual), Seventh Edition (April 2021), Section 5,
Chapter 1 titled ``Wet and Dry Scrubbers for Acid Gas Control,''
page 1-12. The Control Cost Manual can be found at https://www.epa.gov/economic-and-cost-analysis-air-pollution-regulations/cost-reports-and-guidance-air-pollution#cost%20manual.
---------------------------------------------------------------------------

    The BART Guidelines explain that:
    A possible outcome of the BART procedures discussed in these
guidelines is the evaluation of multiple control technology
alternatives which result in essentially equivalent emissions. It is
not our intent to encourage evaluation of unnecessarily large numbers
of control alternatives for every emissions unit. Consequently, you
should use judgment in deciding on those alternatives for which you
will conduct the detailed impacts analysis (Step 4 below).\209\
---------------------------------------------------------------------------

    \209\ See 40 CFR part 51, Appendix Y--Guidelines For BART
Determinations Under the Regional Haze Rule, Section IV.D.2.
---------------------------------------------------------------------------

    We believe that evaluation of SDA and wet FGD covers a reasonable
range of control efficiencies offered by available SO2
scrubbing technologies and includes the most stringent control option
available.\210\ CDS will not be further considered as part of our
reasonable set of options for analysis for BART controls given the
similarity in cost and removal efficiencies with SDA. However, CDS
could potentially be considered as an alternative dry scrubber control
to SDA. We therefore solicit comment regarding costs and control
efficiency of CDS, including comments from the facilities we evaluated
for SO2 scrubbers on whether they have conducted analysis of
CDS, the level of SO2 control efficiency that could be
achieved with installation of CDS at the unit, and the estimated cost
of that control technology at the unit.
---------------------------------------------------------------------------

    \210\ The EPA Air Pollution Control Cost Manual (the Control
Cost Manual, or Manual), Seventh Edition (April 2021), Section 5,
Chapter 1 titled ``Wet and Dry Scrubbers for Acid Gas Control''
provides data summarizing the efficiency and SO2 emission
rates for SO2 scrubbers based on 2019 data for coal-fired
units at power plants. The 12-month average emission rate for the
top performing 50 percent FGD systems is 0.04 lb/MMBtu for limestone
wet FGD systems, 0.06 lb/MMBtu for SDA systems, and 0.12 lb/MMBtu
for CDS systems. (See page 1-12). The Control Cost Manual can be
found at https://www.epa.gov/economic-and-cost-analysis-air-pollution-regulations/cost-reports-and-guidance-air-pollution#cost%20manual.
---------------------------------------------------------------------------

    Wet FGD and SDA installations account for approximately 79 percent
of all scrubber installations in the U.S. and as such constitute a
reasonable set of SO2 scrubber control options. The vast
majority of the wet FGD and SDA installations utilize limestone and
lime, respectively as reagents. In addition, these technologies cover
the maximum level of SO2 control available. As described
above, these controls are in wide use and have been retrofitted to a
variety of boiler types and plant configurations. Based on typical SDA
performance, SDA scrubbers should not be applied to boilers that burn
fuels with more than 3 lb SO2/MMBtu.\211\ Typically, SDA
technology has been applied to boilers that burn fuels with less than 2
lb/MMBtu. The Texas coal-fired EGUs we are evaluating in our BART
analyses burn low sulfur coal and are suitable for evaluation of both
SDA and wet FGD. We see no technical infeasibility issues and believe
that limestone wet FGD and lime SDA should be considered as potential
BART controls for all unscrubbed coal-fired subject to BART units.
However, due to potential non-air quality concerns associated with
water availability, we limit our SO2 control analysis for
Harrington Units 061B and 062B to DSI and SDA. This is discussed in
more detail in Section VII.B.3.
---------------------------------------------------------------------------

    \211\ IPM Model--Updates to Cost and Performance for APC
Technologies, SDA FGD Cost Development Methodology, Final January
2017, Project 13527-001, Eastern Research Group, Inc., Prepared by
Sargent & Lundy, p. 2.
---------------------------------------------------------------------------

b. Identification of Technically Feasible SO2 Control
Technologies for Scrubber Upgrades
    In our 2016 Texas-Oklahoma FIP,\212\ we presented a great deal of
information on which we reached a conclusion that the existing
scrubbers for a number of facilities could be very cost-effectively
upgraded.\213\ While that action was stayed by the Fifth Circuit, the
basis for the stay was not related to that technical analysis. This
information remains valid and can be used to inform our BART analysis
in this proposal. Therefore, we have included this information in the
record for this proposal in Appendix A

of the 2023 BART FIP TSD in the docket.\214\ Appendix A also contains a
comprehensive survey we prepared as part of our 2016 Texas-Oklahoma FIP
of available literature concerning the kinds of upgrades that have been
performed by industry on scrubber systems similar to the ones installed
on the units included in this proposal. We then reviewed all
information we had at our disposal regarding the status of the existing
scrubbers for each unit, including any upgrades the facility may have
already installed. We finished by calculating the cost-effectiveness of
scrubber upgrades, using the facility's own information, obtained as a
result of our previous CAA section 114 collection efforts. The
companies that supplied this information have asserted a Confidential
Business Information (CBI) claim for much of it, as provided in 40 CFR
2.203(b). We therefore redacted any CBI information we utilized in our
analyses, or otherwise disguised it so that it cannot be traced back to
its specific source. Based on our review of this information, we find
that upgrades to the existing scrubbers should be considered as
potential BART controls for the three subject-to-BART units at the
Martin Lake facility.
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    \212\ 81 FR 296, 321 (Jan. 5, 2016).
    \213\ See information presented in Sections 6 and 7 of the 2016
Texas-Oklahoma FIP Cost TSD, Document No. EPA-R06-OAR-2014-0754-
0008, available at www.regulations.gov.
    \214\ See our 2023 BART FIP TSD, Appendix A, ``Wet FGD Scrubber
Upgrade Control Analysis as used in the Texas-Oklahoma FIP.''
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    The Fayette Units 1 and 2 are currently equipped with high
performing wet FGDs. Both units have demonstrated the ability to
maintain a SO2 30 Boiler Operating Day (BOD) average below
0.04 lb/MMBtu for years at a time.\215\ As we discuss in Section
VII.B.2.a, we state that retrofit wet FGDs should be evaluated at 98
percent control not to go below 0.04 lb/MMBtu. Because the Fayette
units are already performing at this level, we do not evaluate any
additional scrubber upgrades for these two units. Thus, our
SO2 BART analysis in this proposed rulemaking evaluates
scrubber upgrades as potential BART controls only for Martin Lake Units
1, 2, and 3.
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    \215\ See our 2023 BART FIP TSD for additional information and
graphs of this data.
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c. Identification of Technically Feasible SO2 Control
Technologies for Gas Fired Units
    Based on our subject to BART screening analysis, W. A. Parish Unit
WAP4 is the only gas-fired unit we determined to be subject to BART.
Because the BART screening analysis is done on a facility-wide basis,
Unit WAP4 is only subject to BART because it is collocated with two
BART-eligible coal-fired units. Gas-fired EGUs have inherently low
SO2 emissions \216\ and there are no known SO2
controls that can be evaluated. While we must assign SO2
BART determinations to the gas-fired unit, there are no practical add-
on controls to consider for setting a more stringent BART emission
limit. The Guidelines state that if the most stringent controls are
made federally enforceable for BART, then the otherwise required
analyses leading up to the BART determination can be skipped.\217\ As
there are no appropriate add-on controls and the status quo reflects
the most stringent control level, we are proposing that SO2
BART for W. A. Parish Unit WAP4 is to limit fuel to pipeline natural
gas, as defined at 40 CFR 72.2.\218\
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    \216\ AP 42, Fifth Edition, Volume 1, Chapter 1: External
Sources, Section 1.4, Natural Gas Combustion, available here:
https://www3.epa.gov/ttn/chief/ap42/ch01/final/c01s04.pdf.
    \217\ 70 FR at 39165 (``. . . you may skip the remaining
analyses in this section, including the visibility analysis . .
.'').
    \218\ As provided for in 40 CFR 72.2, pipeline natural gas
contains 0.5 grains or less of total sulfur per 100 standard cubic
feet. This is equivalent to an SO2 emission rate of
0.0006 lb/MMBtu.
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2. Step 3: Evaluation of Control Effectiveness
    In the following subsections, we evaluate the control levels each
technically feasible technology can achieve for the coal units. In so
doing, we consider the maximum level of control each technology is
capable of delivering based on a 30 BOD period. As the BART Guidelines
direct, ``[y]ou should consider a boiler operating day to be any 24-
hour period between 12:00 midnight and the following midnight during
which any fuel is combusted at any time at the steam generating unit.''
\219\ To calculate a 30-day rolling average based on BOD, the average
of the last 30 ``boiler operating days'' is used. In other words, days
are skipped when the unit is down, as for maintenance.
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    \219\ 70 FR 39103, 39172 (July 6, 2005), [40 CFR part 51, App.
Y].
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a. Evaluation of SO2 Control Effectiveness for Coal-Fired
Units Without an Existing Scrubber
Control Effectiveness of DSI
    DSI involves pneumatically injecting a sorbent either directly into
a coal-fired boiler or into ducting downstream of where the coal is
combusted. The sorbent interacts with various pollutants in the flue
gas, including SO2 and acid gases such as hydrochloric acid
(HCl), such that a fraction of these pollutants are removed from the
gas stream. After the appropriate chemical interactions between the
sorbent and the pollutants in the flue gas, the dry waste product of
the reaction is removed using a particulate control device, typically a
fabric filter baghouse or electrostatic precipitator (ESP). The
SO2 removal efficiency of DSI varies greatly but is highly
dependent on the following factors: the type of sorbent used; the
careful balancing of the stoichiometry of the molecules in the sorbent
(sodium in the case of trona or sodium bicarbonate, or calcium in the
case of hydrated lime) and SO2 molecules in the flue gas;
and the type of particulate capture device used in conjunction with the
sorbent injection. Removal efficiency can also be improved by
increasing the surface area of the sorbent to increase reactivity with
the SO2 gas. This can be achieved by crushing or ``milling''
the sorbent and also by applying heat. Both the application of heat and
milling the sorbent increase the efficiency of the DSI system, but also
increase the cost.\220\
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    \220\ IPM Model--Updates to Cost and Performance for APC
Technologies, Dry Sorbent Injection for SO2/HCl Control
Cost Development Methodology, Final April 2017, Project 13527-001,
Eastern Research Group, Inc., Prepared by Sargent & Lundy.
---------------------------------------------------------------------------

    The most common sodium-based sorbents used in DSI systems are trona
and sodium bicarbonate. Sodium bicarbonate is more effective in
removing SO2 emissions than trona,\221\ and therefore, less
sodium bicarbonate is needed for an equivalent amount of SO2
removal compared to trona. However, sodium bicarbonate is more
expensive than trona on a per ton basis. Hydrated lime is a calcium-
based sorbent that is also used in DSI systems. DSI using hydrated lime
typically achieves a lower SO2 removal efficiency compared
to DSI using trona. Aside from the lower SO2 removal
efficiency typically seen with hydrated lime, we also note that DSI
using hydrated lime as the sorbent may necessitate the use of a
baghouse rather than an ESP as the particulate capture device, which
would increase costs if a unit does not already have an existing
baghouse. Because trona is generally considered the most cost-effective
of the DSI sorbents for SO2 removal and considering the
limitations associated with hydrated lime for SO2 removal,
our DSI analysis is based on using milled trona as the sorbent.\222\
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    \221\ Sodium bicarbonate may be able to achieve even higher
SO2 removal efficiencies compared to trona. However, the
April 2017 IPM DSI documentation and associated 2019 Retrofit Cost
Analyzer (RCA) tool cost spreadsheet do not include information on
sodium bicarbonate costs and removal efficiencies.
    \222\ As discussed in the preceding paragraph, the removal
efficiency of trona can be improved by crushing or ``milling'' the
sorbent, which increases the reactivity with the SO2 gas.
The control efficiencies we evaluate for DSI and our cost analysis
is based on the use of milled trona.

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    In developing our BART analysis for DSI, we relied on the EPA's
April 2017 version of the Integrated Planning Model (IPM) DSI
documentation 223 224 and the 2019 version of the EPA's
Retrofit Cost Analyzer (RCA), which is an Excel-based tool that can be
used to estimate the cost of building and operating air pollution
controls and also employs version 6 of our IPM model.\225\ We expect
that by the time this proposal is published in the Federal Register, or
shortly thereafter, the EPA will have issued an updated version of the
IPM DSI documentation and an accompanying updated version of the RCA
tool for calculating the cost of DSI. The updated IPM DSI documentation
and updated RCA tool for DSI include a number of updates to the cost
algorithms and updated estimates for sorbent costs. Initial review of
the updated DSI documentation indicates the maximum potential
SO2 control efficiencies of DSI may be higher than indicated
in the April 2017 version of the IPM DSI documentation. The updated DSI
documentation and RCA tool also include updated cost algorithms
predicting the amount of sorbent required to achieve certain control
efficiencies that generally result in similar cost effectiveness values
($/ton) for DSI using milled trona compared to the cost algorithms used
in the April 2017 version of the IPM DSI documentation and the 2019
version of the RCA tool. This is the result of the updated efficiency
curves estimating lower sorbent use and updated higher costs for milled
trona. The updated RCA tool contains cost information for sodium
bicarbonate and the capability to estimate the cost of DSI using sodium
bicarbonate as the sorbent. In general, the cost-effectiveness values
for DSI using milled trona and sodium bicarbonate appear to be very
similar. Less sodium bicarbonate is needed than milled trona to achieve
a given control efficiency but the cost per ton of sodium bicarbonate
is higher compared to milled trona, thereby resulting in similar cost-
effectiveness values. However, the updated IPM DSI documentation
indicates that sodium bicarbonate may be able to achieve higher control
efficiencies compared to milled trona. We will include these documents
in the docket once they are finalized and made publicly available. As
these updated documents were not available at the time we developed our
cost analysis, we did not rely on this updated information in our DSI
cost analysis presented in this proposal. In general, the updated IPM
DSI documentation and updated RCA tool for DSI suggest that DSI could
potentially achieve higher SO2 control efficiencies at a
similar cost per SO2 tons removed. However, as described in
further detail below, absent site-specific information from the
facilities that we evaluated for DSI, we believe there is uncertainty
whether these units are capable of achieving the assumed maximum DSI
performance levels specified in either the April 2017 IPM DSI
documentation or the updated version of the IPM DSI documentation.
Similarly, we believe that our concern regarding the uncertainty in the
cost estimates for DSI at high SO2 removal levels would
still exist even if we were to rely on the updated versions of the IPM
DSI documentation and the RCA tool.\226\ However, as we discuss later
in this subsection, we solicit comment on the range and maximum control
efficiency that can be achieved with DSI at the evaluated units and
estimates of the range of associated costs. We are especially
interested in any site-specific analysis of DSI for the units we
evaluated, the level of SO2 control efficiency that could be
achieved with installation of DSI at these units, and the estimated
cost of that control technology at these units.
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    \223\ See Documentation for the EPA's Power Sector Modeling
Platform v6 Using the Integrated Planning Model, dated September
2021. Documentation for v.6 downloaded from https://www.epa.gov/power-sector-modeling/documentation-epas-power-sector-modeling-platform-v6-summer-2021-reference.
    \224\ IPM Model--Updates to Cost and Performance for APC
Technologies, Dry Sorbent Injection for SO2/HCl Control
Cost Development Methodology, Final April 2017, Project 13527-001,
Eastern Research Group, Inc., Prepared by Sargent &Lundy.
Documentation for v.6: Chapter 5: Emission Control Technologies,
Attachment 5-5: DSI Cost Methodology, downloaded from https://www.epa.gov/sites/default/files/2018-05/documents/attachment_5-5_dsi_cost_development_methodology.pdf.
    \225\ Retrofit Cost Analyzer, rev: 06-04-2019, downloaded from
https://www.epa.gov/power-sector-modeling/retrofit-cost-analyzer.
    \226\ We discuss these issues in more detail in Sections
VII.B.3.a and VIII.A.
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    According to the April 2017 IPM DSI documentation, the assumed
maximum DSI performance level using milled trona is 80 percent
SO2 removal for an Electrostatic Precipitator (ESP)
installation and 90 percent SO2 removal for a baghouse
installation.\227\ The BART Guidelines state the following regarding
selection of an emissions performance level or levels to evaluate in a
BART analysis for a control option with a wide range of emission
performance levels:
---------------------------------------------------------------------------

    \227\ IPM Model--Updates to Cost and Performance for APC
Technologies, Dry Sorbent Injection for SO2/HCl Control
Cost Development Methodology, Final April 2017, Project 13527-001,
Eastern Research Group, Inc., Prepared by Sargent & Lundy.
Documentation for v.6: Chapter 5: Emission Control Technologies,
Attachment 5-5: DSI Cost Methodology, downloaded from https://www.epa.gov/sites/default/files/2018-05/documents/attachment_5-5_dsi_cost_development_methodology.pdf.

    It is not our intent to require analysis of each possible level
of efficiency for a control technique as such an analysis would
result in a large number of options. It is important, however, that
in analyzing the technology you take into account the most stringent
emission control level that the technology is capable of achieving.
You should consider recent regulatory decisions and performance data
(e.g., manufacturer's data, engineering estimates and the experience
of other sources) when identifying an emissions performance level or
levels to evaluate.\228\
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    \228\ See 40 CFR Part 51, Appendix Y--Guidelines For BART
Determinations Under the Regional Haze Rule, Section IV.D.3.

    Adhering to this, we are evaluating each unit at its assumed
maximum achievable DSI performance level according to the April 2017
IPM DSI documentation. All the units we are evaluating for DSI controls
have existing baghouses with the exception of Harrington Unit 061B,
which has an ESP. For Coleto Creek Unit 1 and W. A. Parish Units WAP5
and WAP6, we are evaluating DSI at 90 percent SO2 removal.
For Welsh Unit 1 and Harrington Unit 062B, we are limiting the upper
DSI control to their equivalent SDA control efficiencies of 87 percent
and 89 percent, respectively. For Harrington Unit 061B, the only unit
with an existing ESP, we are evaluating DSI at 80 percent
SO2 removal.
    We recognize that there is some variation based on facility-
specific circumstances which could affect whether a given unit is
actually capable of achieving these assumed maximum performance levels.
There is typically a direct correlation with DSI between the targeted
SO2 removal efficiency and the amount of sorbent needed;
therefore, more sorbent is needed to reach higher SO2
removal efficiencies. However, the reaction between the sorbent and the
various pollutants in the flue gas results in a dry waste product that
must be removed using a particulate control device. As additional
sorbent is added to achieve higher SO2 removal efficiencies,
the increased dry waste product can impact the performance of the
particulate control device. For instance, DSI using trona and an ESP
for capture of the dry waste product typically can achieve 40-50
percent SO2 removal efficiency without an increase in
particulate emissions.\229\ At higher

SO2 removal efficiencies, however, depending on the
throughput capacity, an ESP may not be able to handle the increased dry
waste product. Similar issues exist where DSI is used with a fabric
filter for capture of the dry waste product. The increased dry waste
product produced in trying to achieve high SO2 removal
efficiencies would result in the more rapid formation of baghouse
filter cake, which is the mixture of fly ash and sorbent-SO2
reaction product. This would result in the need for more frequent
cleaning, more rapid filter bag wear, and more frequent replacement of
filter bags. The frequent need to clean and replace the filter bags may
become impractical and additional fabric filter compartments may need
to be added to handle the high loading that occurs at high
SO2 removal efficiencies. The exact SO2 removal
efficiency at which these secondary impacts would become significant is
typically site-specific. As we discuss in Section VII.B.3.a, these
secondary impacts associated with trying to achieve higher
SO2 removal efficiencies also lead to some uncertainty in
our cost estimates for DSI at high SO2 removal efficiencies.
---------------------------------------------------------------------------

    \229\ IPM Model--Updates to Cost and Performance for APC
Technologies, Dry Sorbent Injection for SO2/HCl Control
Cost Development Methodology, Final April 2017, Project 13527-001,
Eastern Research Group, Inc., Prepared by Sargent & Lundy.
Documentation for v.6: Chapter 5: Emission Control Technologies,
Attachment 5-5: DSI Cost Methodology, p. 3; downloaded from https://www.epa.gov/sites/default/files/2018-05/documents/attachment_5-5_dsi_cost_development_methodology.pdf.
---------------------------------------------------------------------------

    Site-specific information based on individual performance testing
is typically needed to be able to accurately determine the maximum DSI
SO2 removal efficiency for a particular unit. We do not have
this site-specific information and testing for the individual units
that we are evaluating for DSI. Instead, we analyzed publicly available
2017-2021 data for coal-fired EGUs with existing DSI systems and
estimated the monthly average SO2 removal efficiency of
existing DSI systems by utilizing the reported sulfur content and
tonnages of the fuels burned and reported to EIA \230\ and the
monitored SO2 outlet emissions reported to the EPA.\231\
Based on our analysis, we found that there is a large range of
SO2 removal efficiency at the coal-fired EGUs with existing
DSI for which there is publicly available data. However, unless there
is a specific regulatory requirement to meet a low SO2
emissions rate, DSI installations are often not optimized to achieve
the highest possible SO2 control efficiency. Of particular
interest for this BART analysis, there are existing coal-fired DSI
units that are consistently achieving high monthly average
SO2 removal efficiencies in the 70-90 percent range. We
discuss this analysis in further detail in our 2023 BART FIP TSD in the
docket. However, because we could only identify a few cases where units
are consistently achieving greater than 70 percent SO2
control efficiency and, most importantly, because we do not have the
site-specific information and individual performance testing needed to
accurately determine the maximum DSI SO2 removal efficiency
for a particular unit, we do not know whether the EGUs we are
evaluating in this proposal are capable of achieving the assumed
maximum DSI performance levels specified in the April 2017 IPM DSI
documentation or what level of control should be considered the maximum
achievable level for these units.
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    \230\ EIA Form 923. Available at https://www.eia.gov/electricity/data/eia923/.
    \231\ EPA Air Markets and Programs Data. Available at https://campd.epa.gov/.
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    Recognizing that DSI has a wide range of SO2 removal
efficiencies, that there is some variation based on facility-specific
circumstances which could affect whether a given unit is actually
capable of achieving the assumed maximum achievable control levels
outlined in the April 2017 IPM DSI documentation, and because we
believe it is useful to evaluate lesser levels of DSI control to
provide a range of costs, we will also evaluate these units at a DSI
SO2 control level that can likely be achieved by most coal-
fired units. DSI using trona and an ESP for particulate capture can
typically remove 40-50 percent of SO2 without affecting the
performance of the particulate control device.\232\ Therefore, we
believe 50 percent SO2 removal is a conservatively low DSI
control efficiency that any given coal-fired EGU is likely capable of
achieving without requiring high sorbent injection rates that may
negatively impact the particulate control. This approach is consistent
with the BART Guidelines, which state the following:
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    \232\ IPM Model--Updates to Cost and Performance for APC