Section 51.308(d)(1)(vi) because its RPGs for the Guadalupe Mountains
and Big Bend do not represent less visibility improvement than is
expected to result from the implementation of other requirements of the
CAA during this planning period.

C. Evaluation of Texas' Reasonable Progress Goals

    As required by Section 51.308(d)(1) of the Regional Haze Rule, the
TCEQ has established RPGs for its two Class I areas, Big Bend and the
Guadalupe Mountains. These RPGs must provide for an improvement in
visibility for the most impaired days over the period of the
implementation plan and ensure no degradation in visibility for the
least impaired days over the same planning period.
1. Establishment of the Reasonable Progress Goals
    The TCEQ states that its RPGs are derived from the CENRAP modeling
\187\ and reflect emission reductions programs already in place,
including CAIR and additional refinery SO2 reductions as a
result of our refinery consent decrees. The TCEQ states that these RPGs
assume that either CAIR will remain in place or will be replaced by a
comparable program to reduce visibility impairing pollution from
Electric Generating Units (EGUs) in Texas and in the eastern United
States. The following tables \188\ summarize the TCEQ RPGs:
---------------------------------------------------------------------------

    \187\ The TSD for CENRAP Emissions and Air Quality Modeling To
Support Regional Haze State Implementation is found in Appendix 8.1
of the Texas regional haze SIP.
    \188\ Reproduced from Tables 10-2 and 10-3 of the Texas regional
haze SIP.

                           Table 5--Texas Reasonable Progress Goals for 20% Worst Days
----------------------------------------------------------------------------------------------------------------
                                                                    Improvement                    Date natural
                                     Baseline     Projected 2018   projected by   Improvement by    visibility
          Class I area              conditions      visibility    2018 using RPG    2018 at URP     attained at
                                       (dv)         (RPG) (dv)         (dv)            (dv)          RPG rate
----------------------------------------------------------------------------------------------------------------
Big Bend........................           17.30            16.6             0.7             1.7            2155
Guadalupe Mountains.............           17.19            16.3             0.9             1.2            2081
----------------------------------------------------------------------------------------------------------------

                           Table 6--Texas Reasonable Progress Goals for 20% Best Days
----------------------------------------------------------------------------------------------------------------
                                                                     Baseline     Projected 2018
                          Class I area                              conditions      visibility    Improvement by
                                                                       (dv)         (RPG) (dv)       2018 (dv)
----------------------------------------------------------------------------------------------------------------
Big Bend........................................................             5.8             5.6             0.2
Guadalupe Mountains.............................................             5.9             5.7             0.2
----------------------------------------------------------------------------------------------------------------

    Based on the results of Texas' required reasonable progress four-
factor analysis (described in the following section), and the results
of the CENRAP modeling and additional information developed by CENRAP,
the TCEQ adopted the CENRAP modeled 2018 visibility conditions as the
RPGs for the Big Bend and Guadalupe Mountains Class I areas. The TCEQ
established a RPG of 16.6 dv for Big Bend and 16.3 dv for Guadalupe
Mountains for the 20% worst days for 2018. This represents a 0.7 dv and
0.9 dv improvement in visibility over the baseline conditions at Big
Bend and Guadalupe Mountains, respectively. Although Texas' RPGs do
provide for some improvement in visibility for the most impaired days
over the period of the SIP and ensure no degradation in visibility for
the least impaired days over the same period, we believe the overall
RPG goals that Texas established for its own Class I areas of Big Bend
and Guadalupe Mountains do not provide for reasonable progress based on
the four reasonable progress factors that a state is required to
consider in selecting a RPG under (d)(1)(i)(A). For the reasons
discussed below, we propose to find that the RPGs identified for the
Texas Class I areas are not reasonable. We address our proposed finding
regarding whether the Texas regional haze SIP satisfies the
requirements under Section 51.308(d)(1) to set RPGs below.
2. Texas' Reasonable Progress Four Factor Analysis
    In establishing a RPG for a Class I area located within a state,
Texas is required by CAA Section 169A(g)(1) and Section
51.308(d)(1)(i)(A) to ``[c]onsider the costs of compliance, the time
necessary for compliance, the energy and non-air quality environmental
impacts of compliance, and the remaining useful life of any potentially
affected sources, and include a demonstration showing how these factors
were taken into consideration in selecting the goal.'' This requirement
is often referred to as the reasonable progress ``four factor
analysis.'' In addition to this explicit statutory and regulatory
requirement, the Regional Haze Rule also establishes an analytical
requirement to ensure that Texas carefully consider the suite of
emission reduction measures necessary to attain the URP. Under Section
51.308(d)(1)(iii), the Regional Haze Rule provides that we will
consider both Texas' consideration of the four factors in Section
51.308(d)(1)(i)(A) and its analysis of the URP ``[i]n determining
whether the State's goal for visibility improvement provides for
reasonable progress.'' As explained in the preamble to the Regional
Haze Rule, the URP analysis was adopted to ensure that states use a
common analytical framework and to provide an informed and equitable
decision making process to ensure a transparent process that would,
among other things, guarantee that the public would be provided with
the information necessary to understand the emission reductions needed,
the costs of such measures, and other factors associated with
improvements in visibility.\189\ The preamble to the Regional Haze Rule
\190\ also states that the URP does not establish a ``safe harbor'' for
the state in setting its progress goals:
---------------------------------------------------------------------------

    \189\ 64 FR 35733 (July 1, 1999).
    \190\ 64 FR 35732 (July 1, 1999).

    If the State determines that the amount of progress identified
through the [URP] analysis is reasonable based upon the statutory
factors, the State should identify this amount of progress as its
reasonable progress goal for the first long-term strategy, unless it
determines that additional progress beyond this amount is also
reasonable. If the State determines that additional progress is
reasonable based on the statutory factors, the State should adopt
that amount of progress as its goal for the first long-term
---------------------------------------------------------------------------
strategy.

    In establishing its RPGs for 2018 for the 20% worst days, the TCEQ
relied on the improvements in visibility that are anticipated to result
from federal, state, and local control programs. Based on the emission
reductions from these measures, CENRAP modeled the projected visibility
conditions anticipated at each Class I area in 2018 and the TCEQ used
these results to establish its RPGs. The TCEQ states it developed its
RPGs after considering the regulatory factors required under Section
51.308(d)(1)(i)(A), discussed above. The TCEQ focused its control
strategy analysis on point source emissions of SO2 and
NOX, as the sources of these pollutants are the main
anthropogenic pollutants that affect visibility at Class I areas in
Texas. It examined visibility impairment at the Texas Class I areas and
Class I areas in nearby states. The TCEQ stated that source
apportionment modeling results, summarized in Chapter 11 of the Texas
regional haze SIP, demonstrate that NOX and SO2
are the main anthropogenic pollutants that affect visibility at the
Class I areas in Texas and Class I areas in surrounding states. Source
apportionment modeling also indicated that sulfur emissions that impact
visibility are dominated by point sources, while impacts from
NOX emissions are more evenly distributed between area,
mobile and point sources. The following table \191\ summarizes the
source category contributions from the 2002 base case CENRAP source
apportionment modeling for the five Class I areas whose visibility is
most impacted by Texas emissions. In evaluating the emission inventory
projections, Texas concluded that for SO2, point sources are
responsible for over 90% of the projected 2018 statewide emissions, and
for NOX, point sources comprise over 45% of the projected
statewide emissions. The TCEQ noted that NOX emissions are
more evenly distributed among point, mobile, and area sources, and that
states have very limited authority to reduce mobile source emissions
and are already addressing road and non-road mobile emissions. The TCEQ
noted the largest category of area source NOX is upstream
oil and gas production, and it is taking all steps it has determined
are reasonable at this time to control these sources as part of the
Dallas-Fort Worth ozone SIP and is investing $4,000,000 in a grant
program to assist with the retrofitting of gas-fired, rich burn
compressor engines. The TCEQ also noted uncertainty in upstream oil and
gas emission estimates. Therefore, the TCEQ reasoned that since point
sources

are the single largest pollution category for SO2 and
NOX, it should concentrate its RPG strategy on analyzing
controls for point sources.
---------------------------------------------------------------------------

    \191\ Reproduced from Table 3 in Appendix 10-1 of the Texas
regional haze SIP.

                      Table 7--Percentage Source Category Contributions to SO4 and NO3 at the Five Class I Areas Texas Most Impacts
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                             Big Bend                                   Guadalupe Mountains
                                                         -----------------------------------------------------------------------------------------------
                                                               Point          Mobile           Area            Point          Mobile           Area
--------------------------------------------------------------------------------------------------------------------------------------------------------
SO4.....................................................            67.1             2.8             6.9            75.6             3.5             8.5
NO3.....................................................            26.6            28.6            14.3            29.2            36.5            13.9
--------------------------------------------------------------------------------------------------------------------------------------------------------

--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                              Wichita Mountains                    Salt Creek                     White Mountain
                                                      --------------------------------------------------------------------------------------------------
                                                         Point      Mobile      Area      Point      Mobile      Area      Point      Mobile      Area
--------------------------------------------------------------------------------------------------------------------------------------------------------
SO4..................................................       78.2        3.7        9.2       73.8        3.9        8.1       75.2        4.1        8.1
NO3..................................................       28.1       44.7       13.4       35.8       29.9       17.1       27.9       40.3       12.0
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Having narrowed the scope of the control analysis to point sources
of NOX and SO2, the TCEQ developed a list of
potential controls and costs associated with those controls to inform
their four factor analysis. It used the control strategy analysis
developed by CENRAP as the starting point for its analysis. CENRAP
contracted with Alpine Geophysics to conduct an evaluation of possible
additional point-source add-on controls for sources in CENRAP states.
The Alpine Geophysics evaluation relied on AirControlNET,\192\ a
database tool we released in 2006 to enable cost-benefit analyses of
potential emissions control measures and strategies. Alpine Geophysics
prepared cost estimates for potential add-on controls for
NOX and SO2 reductions in 2005 dollars for point
sources in CENRAP states. The Iowa Department of Natural Resources and
Kansas Department of Health and Environment staff developed Area-of-
Influence (AOI) data for each Class I area in every CENRAP member
state, as well as distance calculations for each source to each Class I
area for inclusion in the Alpine Geophysics analysis. Available
SO2 and NOX control strategies in the
AirControlNET dataset were applied to EGU and non-EGU sources to
develop a master list of available incremental control strategies for
the CENRAP states.\193\ The TCEQ reviewed this information for Texas
sources and made changes based on additional information and past
experience. The TCEQ also added some additional sources from source-
types not included in the CENRAP AirControlNET dataset. This work
resulted in a list of potential add-on controls for reducing
SO2 and NOX at Texas point sources, an estimate
of the costs associated with each control, and identification of the
AOIs for each Class I area.
---------------------------------------------------------------------------

    \192\ Additional information and a copy of the AirControl NET
software can be found at: http://www.epa.gov/ttn/ecas/AirControlNET.htm
    \193\ Lists of NOX and SO2 controls
meeting cost thresholds ranging from $1,500/ton to $10,000/ton
developed by Alpine Geophysics are available in the docket to this
action (See spreadsheets titled ``nox_cost_ton_--2_'' and
``so2_cost_ton'')
---------------------------------------------------------------------------

    The TCEQ states its analysis focused on moderate cost controls for
sources it believed were likely to contribute to visibility impairment
at Class I areas. In an effort to further narrow the list of potential
controls, the TCEQ followed the screening process summarized below and
as detailed in Section 10-1.3 of Appendix 10-1 of the Texas regional
haze SIP:
     Identified controls at sources with potential control
strategy costs greater than $2,700 per ton SO2 or
NOX were initially screened out.
     Remaining sources were reduced by eliminating the ones the
TCEQ believed were so far away from any of the ten Class I areas, that
any reduction in their emissions would likely not have a perceptible
impact on visibility.
     Remaining sources were further reduced by eliminating the
ones for which a ratio of the estimated projected 2018 base annual
emissions (tons) of SO2 or NOX to distance
(kilometers), to any Class I area, did not exceed five.
     Any source with predicted 2018 emissions less than 100
tons per year was excluded.
    Separate from the above described screening process, the TCEQ also
excluded additional NOX controls on cement kilns from
consideration, as it concluded it had already required all the measures
it had determined reasonable to control NOX emissions from
these sources in the latest Dallas-Fort Worth ozone SIP revision. The
TCEQ reasoned, based on a study performed for the Dallas-Fort Worth
ozone SIP revision,\194\ that a 35 to 50% NOX control range
was the most appropriate control level to address ozone formation. The
TCEQ developed a source cap that required a reduction of approximately
9.69 tons per day (tpd) of NOX emissions from the cement
kilns in Ellis County starting March 2009.
---------------------------------------------------------------------------

    \194\ Assessment of NOX Emission Reduction Strategies
for Cement Kilns--Ellis County Final Report, TCEQ Contract No. 582-
04-65589, Work Order No.05-06, Prepared by: ERG, Inc., 10200
Alliance Road, Suite 190, Cincinnati, Ohio 45242-4716. Available at:
http://www.tceq.state.tx.us/assets/public/implementation/air/sip/agreements/BSA/CEMENT_FINAL_REPORT_70514_final.pdf
---------------------------------------------------------------------------

    The types of controls considered by the CENRAP study, based on
industrial categories, are listed below:
SO2 Control at 24 Facilities From 15 Sites
 Natural Gas Transmission--Flue Gas Desulfurization (FGD)
 Crude Petroleum--Sulfur recovery and/or tail gas treatment
 Inorganic chemical plants--coal washing and Spray Dryer
Absorber (SDA) on boilers, increase efficiency of sulfuric acid plants
 Electric Generating Units (EGU)--coal washing and FGD wet
scrubbing
 Carbon black--FGD
NOX Control for 24 Facilities at 15 Sites
     Natural Gas Transmission--Low NOX Burners
(LNB), Selective Catalytic Reduction (SCR) + LNB
     EGU--LNB with Close Coupled Over-Fired Air (LNC1), and
with both LNC1 and Separated Over-Fired Air (LNC3)
     Flat Glass--LNB, SCR
     Paper Mills SNCR and Oxygen Trim (OT) with water injection
     Chemical Plant Boiler--SCR

    The total cost of controls and the resulting emission reductions
were calculated by summing up the

individual costs of those identified controls located within the AOI of
Big Bend or the Guadalupe Mountains. The TCEQ also performed this
calculation for eight additional Class I areas in other states impacted
by Texas' emissions: Breton Island, Caney Creek, Carlsbad Caverns, Salt
Creek, Upper Buffalo, Wheeler Peak, White Mountain, and the Wichita
Mountains. The annualized costs \195\ that would result from the
imposition of the above controls within each Class I area's AOI are
shown below.
---------------------------------------------------------------------------

    \195\ Annualized costs are the total yearly costs, typically the
sum of the yearly capital cost (amortized over the life of the
control) and the yearly operational cost. In this instance, the TCEQ
relied upon our AirControlNET model which for these types of
controls typically assumed a 30 year control life.

       Table 8--Annualized Cost of Controls for Each Class I Area
         [Controls at facilities within each class I area's AOI]
------------------------------------------------------------------------
           Class I area                    NOX                SO2
------------------------------------------------------------------------
Big Bend..........................        $24,100,000       $215,900,000
Breton Island.....................         27,000,000        231,000,000
Caney Creek.......................         28,600,000        245,900,000
Carlsbad Caverns..................         24,100,000        255,500,000
Guadalupe Mountains...............         33,800,000        254,900,000
Salt Creek........................         27,000,000        251,900,000
Upper Buffalo.....................         24,100,000        233,800,000
Wheeler Peak......................         22,700,000        229,500,000
White Mountains...................         23,000,000        244,500,000
Wichita Mountains.................         28,100,000        269,500,000
------------------------------------------------------------------------

    Many of these controls are in more than one AOI. The TCEQ reviewed
the total cost of all state-wide point source controls identified by
the process described above, as follows for 13 facilities with
SO2 controls and 15 facilities with NOX controls.

         Table 9--Total Estimated Cost of Texas Control Set 196
------------------------------------------------------------------------
             Pollutant               Reduction  (tpy)    Estimated cost
------------------------------------------------------------------------
Sulfur Dioxide (SO2)..............            155,873       $270,800,000
Nitrogen Oxides (NOX).............             27,132         53,500,000
                                   -------------------------------------
    Total Costs...................  .................       $324,300,000
------------------------------------------------------------------------

    The 196 TCEQ used the results of the 2018 CENRAP state-wide
photochemical grid modeling analyses (that includes the 2018 modeling
and a CENRAP control case modeling scenario) to estimate the visibility
benefit that would result in 2018 from controlling those sources in
Texas identified by it following the process described above. CENRAP
developed a modeling scenario to estimate the effectiveness of a
specific suite of controls on facilities in the CENRAP states. CENRAP
based its control sensitivity analysis on a maximum estimated cost of
$5,000 per ton of emissions of NOX or SO2 reduced
estimated in the Alpine Geophysics report and evaluated only those
point sources predicted to emit 100 tons or more of SO2 or
NOX in the year 2018.\197\ Similar to the Texas analysis,
CENRAP further refined the sources for analysis, considering controls
only for those sources with emissions of NOX or
SO2 greater than or equal to five tons per year per
kilometer of distance to the nearest Class I area. This distance-
weighing criterion limited the sensitivity evaluation to sources with
the greatest likely influence on visibility. The CENRAP control
sensitivity modeling run included emission reductions beyond CAIR and
BART in the CENRAP states at all point sources where the cost-
effectiveness and Q/D \198\ criteria discussed above were met, and
projected the resulting visibility conditions in 2018 at the CENRAP
Class I areas. This modeling was developed as a starting point for
discussion and development of refined analyses as needed.\199\
---------------------------------------------------------------------------

    \196\ Reproduced from Table 4 in Appendix 10-1 of the Texas
regional haze SIP.
    \197\ See Section 2.14 of the Technical Support Document for
CENRAP Emissions and Air Quality Modeling to Support Regional Haze
State Implementation Plans, September 12, 2007.
    \198\ Q/D is the ratio of annual emissions over distance to a
Class I area.
    \199\ ``The results of the modeling were not intended to be
prescriptive; instead, they were intended to be a starting point for
control discussions that would require much greater refinement.''
CENRAP TSD, page 2-37.
---------------------------------------------------------------------------

    The TCEQ used the CENRAP control sensitivity analysis and the
CENRAP 2018 visibility projection modeling as the starting point for
estimating the visibility benefit of implementing only the controls
identified by it above for Texas point sources. The TCEQ used the
results of this modeling analysis and the source apportionment modeling
results to determine an ``effectiveness ratio'' for NOX and
SO2 reductions, which it states provides an estimate of
improvement in visibility for every ton of NOX and
SO2 reduced in order to produce ``an order of magnitude
estimate of the likely visibility improvements resulting from the point
source.'' See Appendix 10-2 and 10-4 of the Texas regional haze SIP and
our TX TSD for additional information on the methodology Texas used to
develop this estimate.
    The TCEQ summarizes the estimated visibility improvement that would
result in 2018 from the imposition of all the above controls as follows
\200\:
---------------------------------------------------------------------------

    \200\ Table 5 in Appendix 10-1 of the Texas Regional Haze SIP.

   Table 10--TCEQ Projected Visibility Improvement to Selected Class I
             Areas From the Imposition of Potential Controls
------------------------------------------------------------------------
                                                           Visibility
                     Class I area                      improvement  (dv)
------------------------------------------------------------------------
Big Bend.............................................               0.16
Breton Island........................................               0.05
Caney Creek..........................................               0.33
Carlsbad Caverns.....................................               0.22
Guadalupe Mountains..................................               0.22
Salt Creek...........................................               0.18
Upper Buffalo........................................               0.16
Wheeler Peak.........................................               0.04
White Mountains......................................               0.24
Wichita Mountains....................................               0.36
------------------------------------------------------------------------

    After identification of potential controls for multiple sources,
estimation of aggregate costs associated with those controls and
estimation of the overall visibility improvement anticipated from
implementation of those controls as described above, the TCEQ then
weighed the four statutory factors in determining the reasonableness of
additional controls and selecting the RPGs for Big Bend and Guadalupe
Mountains. In general, the cost of compliance was the key factor
considered by the TCEQ. It determined that the time necessary for
compliance was not a critical factor for the determination of
applicable additional controls for Texas sources. It stated that to the
extent energy impacts are quantifiable for a particular control, they
were included in its cost estimates. However, it stated that
``including [energy and non-air quality environmental] impacts on a
source-by-source basis would have added further weight against finding
that the potential additional controls were reasonable to apply.''
\201\ The TCEQ also stated that for the purposes of initial analysis,
no limited remaining useful life was assumed. The TCEQ describes the
cost of compliance as a factor used to determine whether compliance
costs for sources are reasonable compared to the emission reductions
and visibility improvement they will achieve. The TCEQ weighed the four
reasonable progress factors as follows:
---------------------------------------------------------------------------

    \201\ Page 10-8 of the Texas Regional Haze SIP.
---------------------------------------------------------------------------

a. Cost of Compliance
    The TCEQ concluded that at a total estimated cost of over $300
million and (in its view) no perceptible visibility benefit, it was not
reasonable to implement additional controls. All units in Texas that
met the emissions over distance threshold were assessed. The TCEQ
states it adopted its $2,700 cost threshold to limit the proposed
controls group to cost-effective measures. Annualized cost values, and
emission reductions based on proposed efficiencies listed in
AirControlNET, were used. Modifications for Texas included the
consideration of flue gas desulfurization for carbon black units.
b. Time Necessary for Compliance
    The TCEQ determined that the time necessary for compliance was not
a critical factor for the determination of applicable additional
controls for its sources. It noted that in our CAIR regulatory impact
statement, we estimated that approximately 30 months is required to
design, build, and install SO2 scrubbing technology for a
single EGU boiler. The TCEQ stated that the total time for a single
facility to comply with one of the NOX caps would be about
five years. It estimated that completion by 2018 would still be
anticipated. For mobile sources, MOBILE and NONROAD model runs were
completed for the 2018 emissions inventory. These model runs
incorporated the degree of fleet and expected engine replacement prior
to 2018. The completion of other proposed controls were anticipated by
2018.
c. Energy and Non-Air Quality Environmental Impacts of Compliance
    The TCEQ stated that to the extent energy impacts are quantifiable
for a particular control, they were included in its cost estimates.
However, it stated that ``including [energy and non-air quality
environmental] impacts on a source-by-source basis would have added
further weight against finding that the potential additional controls
were reasonable to apply. Source-by-source review of the non-air
quality impacts of the potential controls would possibly have led to a
different determination about the unreasonableness of the set of
potential additional controls.'' \202\ The TCEQ noted that scrubbers,
SCR systems, and Selective Non-Catalytic Reduction (SNCR) systems
installed under the EGU control strategies would require electricity to
operate fans and other ancillary equipment. However, it noted that
estimates were given that the electricity and steam required by
controls installed to meet SO2 and NOX emission
caps would be less than 1% of the total electricity and steam
production of EGUs. TCEQ noted that Scrubbers, coal washing, and spray
dryers would require additional safeguards for fuel handling and waste
handling systems to avoid additional non-air environmental impacts such
as increased effluents in waste water discharges and storm water
runoff. The TCEQ expected that solid waste disposal and wastewater
treatment costs would be less than five percent of the total operating
costs of pollution control equipment. It noted that these factors would
have to be considered specific to individual sources.
---------------------------------------------------------------------------

    \202\ Texas Regional Haze SIP, page 10-8.
---------------------------------------------------------------------------

d. Remaining Useful life
    The TCEQ noted that CENRAP considered the remaining useful life in
modeling for mobile sources that assumes reduced emissions per vehicle
mile traveled due to the turnover of the on-road mobile source fleet.
It noted that for sources with a relatively short remaining useful
life, this consideration would have weighed more heavily against a
determination that controlling those sources would have been
reasonable. The TCEQ believed that this factor was not critical for its
sector analyses for the 2018 timeline and did not assume any limited
useful equipment life. Only units that were scheduled for shutdown
under enforceable decrees were eliminated from the 2018 inventory and
further analysis.
e. TCEQ Noted Uncertainty in Visibility Projections Due to CAIR
    The TCEQ noted that the majority of the emission reductions
underlying the predicted visibility improvements in 2018 resulting from
controls already in effect or scheduled to become effective will result
from the CAIR program in particular. The CAIR program allows interstate
trading of allowances, and does not put specific emission limits on
specific sources. Further, it notes that because emission allowances
can be purchased by EGUs, visibility improvement may be less or more
that that predicted by the CENRAP's modeling. CENRAP used our
Integrated Planning Model (IPM) to predict the emission reductions
expected from CAIR in 2018. The TCEQ assumed that any replacement for
CAIR will include interstate trading of emissions allowances. The TCEQ
presents a comparison \203\ of its baseline 2002 SO2
emissions, the CAIR budget for EGUs in 2015 and the IPM predicted
SO2 emissions for the 2018 planning year:
---------------------------------------------------------------------------

    \203\ Reproduced from Table 10-7 in the Texas Regional Haze SIP.

  Table 11--Comparison of Texas 2002 Baseline SO2 Emissions, 2015 CAIR
            EGUs Budget and 2018 IPM Predicted SO2 Emissions
------------------------------------------------------------------------
                                                             Texas SO2
                      SO2 emissions                          emissions
                                                               (tpy)
------------------------------------------------------------------------
Current (2002 base case)................................         550,000
EPA's CAIR budget for Texas EGUs for 2015...............         225,000
IPM projection CENRAP modeled for 2018..................         350,000
------------------------------------------------------------------------

    The TCEQ notes that the IPM model analysis used by CENRAP predicts
that by 2018 EGUs in Texas will purchase approximately 125,000 tpy of
emissions allowances from out of state. This represents more than 50%
of Texas' total CAIR SO2 budget. The TCEQ states that it
requested that key EGUs in Texas review and comment on the predictions
of the IPM model. However, no EGU made an enforceable commitment to any
particular pollution control strategy and preferred to retain the
flexibility offered by the CAIR program.
f. The TCEQ Reasonable Progress Conclusion
    The TCEQ's assessment of reasonable progress rested primarily on
its calculation of the total cost of the controls it analyzed versus
the visibility benefits at the ten Class I areas it analyzed. It
concluded, ``At a total estimated cost exceeding $300 million and no
perceptible visibility benefit, Texas has determined that it is not
reasonable to implement additional controls at this time.'' \204\
---------------------------------------------------------------------------

    \204\ Texas Regional Haze SIP, page 10-7.
---------------------------------------------------------------------------

    Section 51.308(d)(1)(iii) requires that in determining whether the
state's goal for visibility improvement provides for reasonable
progress towards natural visibility conditions, the Administrator will
evaluate the demonstrations developed by the state pursuant to Sections
51.308(d)(1)(i) and (d)(1)(ii). We perform that evaluation beginning in
the next section.
3. Our Analysis of Texas' Reasonable Progress Four Factor Analysis
    We agree with the TCEQ's decision to focus the analysis of the four
statutory factors on point sources, as the CENRAP modeling results and
the TCEQ's analysis in Chapter 11 and appendix 10-1 of the Texas
regional haze SIP indicate that the predominant anthropogenic
pollutants that affects the state's ability to meet the URP goals in
2018 on the worst 20% days at the Texas Class I areas are largely due
to sulfate and nitrate, primarily from point sources. We agree with the
TCEQ's assessment that the cost of compliance is the dominant factor,
and its incorporation of the other factors into the cost, where
applicable. We note, however, that because the TCEQ did not evaluate
controls on a source-by-source basis, source-specific factors related
to the evaluation of the reasonable progress four factor analysis could
not be considered. We also agree with the TCEQ's decision to consider
visibility benefits in weighing the factors and to assist in its
consideration of the cost of compliance. While visibility is not an
explicitly listed factor to consider when determining whether
additional controls are reasonable, the purpose of the four-factor
analysis is to determine what degree of progress toward natural
visibility conditions is reasonable. Therefore, we believe it is
appropriate to consider the projected visibility benefit of the
controls when determining if cost-effective controls are warranted to
make reasonable progress. However, the TCEQ did not discriminate
between and analyze controls on those source(s) with the highest
potential visibility benefit at each Class I area. We disagree with the
set of potential controls identified by the TCEQ and how it analyzed
and weighed the four reasonable progress factors in a number of key
areas.
a. The TCEQ's Cost-Effectiveness Threshold Approach
    The TCEQ eliminated controls with an estimated cost-efficiency
greater than $2,700/ton from any further analysis, regardless of their
potential visibility benefits. Given the large number of sources and
their large geographic distribution, some consideration of location and
emissions data is needed before controls should have been eliminated
from further analysis. The TCEQ supports its selection of this value
with reference to ``EPA estimated cost of implementing CAIR was up to
$2,700/ton.'' However, although we demonstrated that CAIR was
acceptable in lieu of BART, CAIR was not designed as a reasonable
progress strategy. A state should look beyond BART for additional
reductions when developing its long-term strategy to achieve reasonable
progress at its Class I areas.\205\ As a result of the application of
this $2,700/ton threshold, potentially cost-effective controls were not
evaluated at sources that may result in meaningful visibility benefits
at Guadalupe Mountains or Big Bend. For example, potential
SO2 controls for the Tolk Station were estimated in the
Alpine Geophysics analysis to cost an average of approximately $3,100/
ton and result in nearly 20,000 tpy reduced across the two units.
Applying the $2,700/ton threshold, the TCEQ did not consider potential
controls on any EGUs in West Texas to improve visibility at the two
Class I areas located in West Texas despite the potential visibility
benefits from controlling these large point sources. Sensitivity
analysis performed by CENRAP suggests to us that a threshold in the
range of $4,000/ton to $5,000/ton would be reasonable for purposes of
identifying potential cost-effective controls for further
analysis.\206\
---------------------------------------------------------------------------

    \205\ Per Section 51.308(e)(5), ``After a State has met the
requirements for BART or implemented emissions trading program or
other alternative measure that achieves more reasonable progress
than the installation and operation of BART, BART-eligible sources
will be subject to the requirements of paragraph (d) of this section
in the same manner as other sources.''
    \206\ See ``Sensitivity Run Specifications for CENRAP
Consultation,'' available in the docket for this action.
---------------------------------------------------------------------------

b. The TCEQ's Weighing of the Four Factors for Individual Sources
    The TCEQ constructed a large potential control set consisting of a
mix of large and small sources, located at various distances from Class
I areas, with a large geographical distribution. Because of the
variation in size, type, and location of these sources, the potential
to impact visibility and potential benefit from controls at a given
Class I area can vary greatly between the identified sources. This
potential control set identified by the TCEQ included controls on some
sources that would likely result in significant visibility benefits,
but also included controls on many sources with much less anticipated
visibility benefits. Because it only estimated the visibility benefit
of all the controls together, the TCEQ was not able to assess the
potential benefit of controlling individual sources with significant,
and potentially cost-effective, visibility benefits. Also, we believe
that individual benefits were masked by the inclusion of those controls
with little visibility benefit that only served to increase the total
cost figures. For example, the TCEQ identified SO2 controls
at Big Brown to be approximately $1,500/ton, significantly less than
its $2,700/ton threshold. These controls were estimated to achieve
greater than 40,000 tpy SO2 emission reductions. Despite
this evidence in the record of an identified cost-effective control
that results in large emission reductions, and source apportionment
modeling identifying large impacts from

EGU sources in northeast Texas, the TCEQ did not separately evaluate
the visibility benefit from the implementation of this control, or
appropriately weigh the four reasonable progress factors in determining
the reasonableness of this individual control.
    Because individual sources were not considered by the TCEQ, we
found it is necessary to conduct an additional analysis to determine
whether this approach materially affected the outcome of the TCEQ
analysis. As we demonstrate in detail in our FIP TSD, by analyzing
sources individually, we believe we have identified a small number of
sources that are responsible for much of Texas' collective visibility
impact on the Texas' Class I areas, which if controlled, would provide
for visibility benefit at Texas' Class I areas. That modeling is
summarized below.
    Our preliminary modeling study identified those facilities with the
largest impacts on the Texas Class I areas on the 20% worst days in
2018.\207\ This modeling includes the same projections the TCEQ used to
account for predicted reductions due to CAIR. The projected impacts
\208\ in 2018 from the top ten facilities in Texas that impact
visibility at Big Bend and the Guadalupe Mountains are summarized in
Tables 12 and 13 below (see our FIP TSD for more details). Texas point
sources combined are projected in 2018 to contribute approximately 8%
(3.56 Mm-\1\) to the total visibility impairment at Big
Bend, and 9% (3.84 Mm-\1\) to the total visibility
impairment at Guadalupe Mountains. These results below show that some
facilities can have large impacts on certain days and significant
impacts on the 20% worst days, even including facilities like Big Brown
which is more than 700 km from Big Bend and more than 800 km from the
Guadalupe Mountains. We note that Texas decided to invite states to
consult using the CENRAP Particulate Matter Source Apportionment
Technology (PSAT) results and included states with > 0.5 inverse
megameter impact (from all sources in the state) on one of Texas' Class
I areas.\209\ These results also suggest that controlling a small
number of sources will result in visibility benefits at both Class I
areas, and that rather than evaluating controls at all facilities
identified by Texas combined, a subset of those facilities (and some
additional facilities not identified) may be reasonable.
---------------------------------------------------------------------------

    \207\ As discussed later in this TSD, this study also looked at
impacts from Texas sources on Class I areas in other States.
    \208\ We occasionally present visibility in extinction, rather
than deciviews (dv). Light extinction, in units of inverse
megameters (Mm-\1\), is the amount of light lost as it
travels over one million meters. The haze index, in units of
deciviews (dv), is calculated directly from the total light
extinction, bext, as follows: HI = 10 ln(bext/10). Extinction is an
appropriate measure for the visibility impairment contribution from
individual sources because it avoids the sensitivity of the
logarithmic transformation for calculating deciviews to the overall
level of visibility impairment including the impacts of other
sources.
    \209\ See Appendix 4-1: Summary of Consultation Calls.

    Table 12--2018 Phase 1 EPA Source Apportionment Modeling Results, top ten Facilities in Texas That Impact
                                             Visibility at Big Bend
----------------------------------------------------------------------------------------------------------------
                                                                                % Contribution
                                                                  Extinction (Mm-    to total     Max extinction
                 Rank                         Facility name        1) 20% worst     visibility      during 20%
                                                                       days       impairment 20%    worst days
                                                                                worst days
----------------------------------------------------------------------------------------------------------------
1.....................................  SOMMERS DEELY S.........           0.276            0.57           1.193
2.....................................  COLETO CREEK PL.........           0.216            0.44           0.937
3.....................................  BIG BROWN...............           0.212            0.44           0.923
4.....................................  RELIANT ENERGY *........           0.103            0.21           0.441
5.....................................  LIGNITE-FIRED P **......           0.101            0.21           0.428
6.....................................  MONTICELLO STM..........           0.096            0.20           0.413
7.....................................  W A PARISH STAT.........           0.090            0.18           0.385
8.....................................  BIG SPRING CARB.........           0.084            0.17           0.356
9.....................................  SANDOW STEAM EL.........           0.080            0.16           0.342
10....................................  MARTIN LAKE ELE.........           0.080            0.16           0.342
----------------------------------------------------------------------------------------------------------------
* This is the Limestone facility.
** This is the San Miguel facility.

    Table 13--2018 Phase 1 EPA Source Apportionment Modeling Results, top ten Facilities in Texas That Impact
                                        Visibility at Guadalupe Mountains
----------------------------------------------------------------------------------------------------------------
                                                                                % Contribution
                                                                  Extinction (Mm-    to total     Max extinction
                 Rank                         Facility name        1) 20% worst     visibility      during 20%
                                                                       days       impairment 20%    worst days
                                                                                worst days
----------------------------------------------------------------------------------------------------------------
1.....................................  TOLK STATION............           0.302            0.65           1.004
2.....................................  BIG BROWN...............           0.235            0.50           0.809
3.....................................  BIG SPRING CARB.........           0.226            0.48           0.775
4.....................................  SOMMERS DEELY S.........           0.208            0.44           0.688
5.....................................  HARRINGTON STAT.........           0.184            0.39           0.606
6.....................................  MONTICELLO STM..........           0.114            0.24           0.391
7.....................................  WAHA PLANT..............           0.113            0.24           0.387
8.....................................  RELIANT ENERGY *........           0.111            0.24           0.372
9.....................................  MARTIN LAKE ELE.........           0.104            0.22           0.351
10....................................  COLETO CREEK PL.........           0.066            0.14           0.227
----------------------------------------------------------------------------------------------------------------
* This is the Limestone facility.

c. The TCEQ's Cost of Compliance Analysis Assumed Future CAIR
Reductions as a Baseline
    We based our determination that CAIR was better than BART in part
on a finding that CAIR resulted in an overall improvement in visibility
determined by comparing the average differences over all affected Class
I areas. We noted at the time that BART is one component of a long-term
strategy to make reasonable progress, but it is not the only component.
\210\ Thus, when assessing reasonable progress, a state should look
beyond BART for additional reductions when determining what long-term
strategy will achieve reasonable progress at its Class I areas. A
critical decision point in performing cost analysis for potential
controls is the determination of an emission baseline. As we state
above, the TCEQ projected that Texas EGUs would purchase approximately
125,000 tpy of emissions allowances from out of state. The TCEQ relied
on the IPM predictions as discussed above to estimate 2018 emission
levels for EGUs. The TCEQ also notes that there is uncertainty in the
size and distribution in emissions in the future projections.
Nevertheless, the TCEQ utilized this future projection of 2018
emissions as the starting point for its estimation of emission
reductions and the associated costs of additional controls.
---------------------------------------------------------------------------

    \210\ 70 FR 39137 (July 6, 2005).
---------------------------------------------------------------------------

    For example, Big Brown Unit 1's SO2 emissions in 2002
were 34,448 tpy. The IPM predictions that were incorporated into the
2018 emission level assume that a roughly 1/3 reduction in these
emissions will occur in response to CAIR by switching to a coal with a
lower sulfur content, resulting in a 2018 SO2 emission level
of 23,142 tpy. The TCEQ's cost-effectiveness calculation for post-
combustion controls on Big Brown Unit 1 was based on reducing that
projected 2018 SO2 emission level of 23,142 tpy by 90%,
resulting in a reduction of 20,828 tpy. This results in a cost of
$32,766,310/yr, or a cost-effectiveness calculation of $1,573/ton.
However, the installation of a scrubber would allow Big Brown
flexibility in fuel choice thus allowing the unit to continue to burn
the higher average sulfur fuel it currently burns, instead of moving to
the low sulfur coal predicted by IPM.
    Big Brown Unit 1 SO2 emissions in 2012 were 32,100 tons.
The issue of scrubber efficiency aside, a reduction of 90% from these
actual emission levels would result in an SO2 reduction in
the range of 29,000 to 31,000 tpy. While the numerator ($) in the cost-
effectiveness metric of $/ton will increase slightly beyond what was
estimated by Alpine Geophysics due to an increased sulfur loading to
the scrubber, the denominator (tons) would increase by roughly 50%,
thus improving (lowering) the overall cost-effectiveness of controlling
Big Brown Unit 1 significantly.\211\ Estimates for scrubbers at
Monticello are similarly impacted by the cost-methodology used by Texas
in estimating cost-effectiveness on a cost-per-ton basis.
---------------------------------------------------------------------------

    \211\ See our cost-effectiveness calculations for retrofitting
Big Brown and other Texas EGU with scrubbers in section VII.F.
---------------------------------------------------------------------------

    We believe that in performing its control analysis, the TCEQ should
have given greater consideration to the flexibility in the CAIR trading
program and the resulting uncertainty in the projected emissions. In
other words, the TCEQ could have recognized that implementation of
reasonable controls under the Regional Haze Rule would likely not be in
addition to anticipated reductions due to CAIR predicted by IPM, but
would replace or complement any controls predicted by IPM.
d. The TCEQ's Assumptions of SO2 Control Efficiency of
Scrubbers
    We note that the control efficiency of scrubbers evaluated by
CENRAP and Texas, based on the data from AirControlNET, was assumed to
be 90%. As we discuss in detail in our FIP TSD, we establish that
SO2 scrubbers are capable of achieving emission reductions
of at least 95% for dry scrubbers and 98% for wet scrubbers. These
additional reductions would further reduce the price on a $/ton basis
and increase the visibility benefit anticipated due to controls.
e. The TCEQ's Evaluation of Potential Visibility Improvements
    In considering whether compliance costs for sources were
reasonable, the TCEQ compared those costs to the emission reductions
and visibility improvement those sources would achieve. While
visibility is not an explicitly listed factor to consider when
determining whether additional controls are reasonable, the purpose of
the four-factor analysis is to determine what degree of progress toward
natural visibility conditions is reasonable. Therefore, we consider it
appropriate to consider the projected visibility benefit of the
controls when determining if the controls are needed to make reasonable
progress. We discuss this in more detail in our FIP TSD.
    In evaluating and dismissing the estimated visibility benefit from
the control set identified by the TCEQ, the TCEQ states that the
estimated benefit is not perceptible (less than 1 dv) and that it is
less than 0.5 dv, the threshold used under BART requirements used to
determine if a facility contributes to visibility impairment. The 0.5
dv BART threshold referred to applies to the maximum anticipated
visibility impact on a single day due to the short-term maximum actual
baseline emissions from a single facility, compared to clean background
conditions. The reasonable progress analysis presented by the TCEQ
contemplates the visibility benefit anticipated for an average tpy
emission reduction (as opposed to the impact from the total short-term
maximum emissions from the sources) averaged across the 20% worst days,
which would be anticipated to be significantly lower. See our FIP TSD
for a detailed discussion of the different metrics and modeling
typically used for BART and reasonable progress analyses. Furthermore,
in a situation where the installation of BART may not result in a
perceptible improvement in visibility, the visibility benefit may still
be significant, as explained by the Regional Haze Rule: \212\
---------------------------------------------------------------------------

    \212\ 70 FR 39130 (July 6, 2005)

    Even though the visibility improvement from an individual source
may not be perceptible, it should still be considered in setting
BART because the contribution to haze may be significant relative to
other source contributions in the Class I area. Thus, we disagree
that the degree of improvement should be contingent upon
---------------------------------------------------------------------------
perceptibility.

    As we stated in our Oklahoma final decision: \213\
---------------------------------------------------------------------------

    \213\ 76 FR 81739 (Dec. 28, 2011).

    Given that sources are subject to BART based on a contribution
threshold of no greater than 0.5 deciviews, it would be inconsistent
to automatically rule out additional controls where the improvement
in visibility may be less than 1.0 deciview or even 0.5 deciviews. A
perceptible visibility improvement is not a requirement of the BART
determination because visibility improvements that are not
---------------------------------------------------------------------------
perceptible may still be determined to be significant.

f. The TCEQ's ``Order of Magnitude Estimate'' for Visibility
Improvement
    The TCEQ produced an ``order of- magnitude estimate'' of the
visibility improvements resulting from the level of aggregate emission
reductions that would result from its point source control strategy
using PSAT results and effectiveness ratios. This methodology assumes
that all emission reductions within a PSAT region have the same

effectiveness in reducing visibility impairment. The estimated
effectiveness factor applied equally to all emission reductions located
in the East Texas source region, including Sommers Deely Spruce (440 km
from Big Bend and 680 km from Guadalupe Mountains) and Monticello (850
km from Big Bend and 920 km from Guadalupe Mountains). Given the large
difference in distances between these two facilities and the Class I
areas, it is reasonable to expect that the effectiveness of emission
reductions could vary greatly between the two. We propose to find that
the TCEQ's analysis is insufficient to determine the visibility benefit
of controlling the source or subset of sources with the most effective
controls for improving visibility conditions at a Class I area or a
number of Class I areas and that the potential visibility benefits from
controlling these sources may be significant. Our own source
apportionment modeling has confirmed that individual sources within the
CENRAP modeling PSAT regions had significantly different impacts,
leading us to believe that TCEQ's reliance on an aggregate analysis
materially affected its conclusion that existing and scheduled controls
would achieve reasonable progress.\214\
---------------------------------------------------------------------------

    \214\ See the FIP TSD.
---------------------------------------------------------------------------

g. Upgrades to Existing Controls
    The CENRAP analysis and the additional analysis performed by the
TCEQ did not consider the reasonableness of control upgrades or
increased utilization of existing controls. We note that the
AirControlNET database does not include general information for the
cost and effectiveness of scrubber upgrades as the cost and reductions
from these potential upgrades are typically very specific to the
existing equipment and site-specific conditions. Many Texas EGU's are
equipped with older vintage scrubbers and/or have scrubber bypasses
that divert a portion of the exhaust gas around the control equipment.
In some cases, excess scrubbing capacity is simply not being utilized.
Texas includes many of these sources with controls in the maps showing
area of influence and ``high priority'' sources for other state's Class
I areas, as well as in the table of sources within the Class I areas
AOI, in their correspondence with other states (see Appendix 4.3 of the
TX regional haze SIP). However, Texas did not provide any analysis of
the four factors on these partially controlled sources or include these
sources in a Q/D analysis to identify those sources with the largest
potential to impact visibility due to emissions and distance. There are
a number of EGUs with existing controls with 2018 projected emissions
large enough to have a Q/D many times greater than threshold (Q/D > 5)
used by Texas. Furthermore, even with these existing controls, some of
these EGUs are among the largest SO2 sources in the state.
For example, the Martin Lake facility has a Q/D for Guadalupe Mountains
(958 km away) greater than 37 using the projected 2018 SO2
emissions.\215\ The 2018 projected emissions includes predicted
emission reductions due to CAIR at many of these controlled facilities,
suggesting some increase in control efficiency and/or burning fuels
with a lower average sulfur content is already included in the 2018
projections. Absent any additional analysis, however, it is not
possible to determine whether additional reductions beyond those
included in the 2018 emission inventory for these facilities are cost-
effective, result in visibility benefits at the Class I areas and are
reasonable. For example, emissions at Martin Lake unit 1 in the CENRAP
emission inventory are projected to decrease from 24,832 tpy in 2002 to
11,351 tpy in 2018. As we discuss in our FIP TSD, based on coal data
submitted to the U.S. Energy Information Administration, upgrading the
existing scrubber to 95% control efficiency would result in an
approximate emission reduction of an additional 7,000 tpy beyond those
reductions projected to occur due to CAIR. Scrubber upgrades across all
three Martin Lake units could result in emission reductions of
approximately 21,000 tpy beyond the level of control assumed in the
2018 projections. Given the size of these sources, the size of the
impact from Texas emissions, and the source apportionment data
indicating the large impact from SO2 emissions from EGUs, we
believe it was unreasonable for Texas to not perform any analysis on
these sources or request additional information from the facilities
concerning potential upgrades. As documented in our FIP TSD, scrubber
upgrades are often very cost-effective on a cost per ton basis. Our
analysis in the FIP TSD demonstrates that many of these older
SO2 scrubbers can be cost-effectively upgraded. The
importance of this omission becomes clear from our analysis that shows
that for a cost-effectiveness of approximately $600/ton or less, over
100,000 tpy of SO2 emission reductions can be achieved from
a small number of scrubber upgrades, resulting in cost-effective
visibility benefits at Texas Class I areas and Class I areas in other
states. Thus, we propose to find that this omission by TCEQ materially
affected the outcome of its four-factor analysis. See our FIP TSD for a
detailed discussion of the visibility benefits anticipated from
scrubber upgrades.
---------------------------------------------------------------------------

    \215\ We note that recent actual emissions at the facility are
roughly twice as large as the 2018 projected value. Based on 2002
emissions, the Q/D for Guadalupe Mountains for SO2
emissions is approximately 69.
---------------------------------------------------------------------------

h. Our Conclusion Regarding the TCEQ's Analysis of the Four Reasonable
Progress Factors
    For the reasons described above, we propose to disapprove Texas'
analysis of the reasonable progress factors under Section
51.308(d)(1)(i)(A).
4. Texas' Assertion That its Progress Goals Are Reasonable
    Section 51.308(d)(1)(ii) provides that for the period of the SIP,
if Texas establishes a RPG that provides for a slower rate of
improvement in visibility than the rate that would be needed to attain
natural conditions by 2064, it must demonstrate based on the factors in
Section 51.308(d)(1)(i)(A) that the rate of progress for the SIP to
attain natural conditions by 2064 is not reasonable; and that the
progress goal it adopted is reasonable. As part of its SIP assessment,
Texas must provide to the public for review the number of years it
would take to attain natural conditions if visibility improvement
continues at the rate of progress it selected as reasonable. In
determining whether the Texas' goals for visibility improvement provide
for reasonable progress towards natural visibility conditions, the
Administrator will evaluate the demonstrations developed by it pursuant
to Section 51.308(d)(1)(i) and (d)(1)(ii).
a. The TCEQ's Evaluation
    Texas' RPGs for the 20% worst days establish a slower rate of
progress than the URP for Big Bend and the Guadalupe Mountains. The
TCEQ calculated that under the rate of progress selected as reasonable,
natural visibility conditions (as calculated by Texas) would not be
attained at Big Bend until 2155 and at the Guadalupe Mountains until
2081. In Appendix 10-3 of its regional haze SIP, the TCEQ includes
calculations based on our default natural conditions, estimating
attainment of natural visibility conditions at the Big Bend in 2215 and
Guadalupe Mountains in 2167.
    The TCEQ believes the RPGs it established for Big Bend and the
Guadalupe Mountains on the 20% worst

days are reasonable, and that it is not reasonable to achieve the glide
path in 2018. In support of this conclusion, it included a discussion
of the pollutant contributions and the sources of visibility impairment
at these Class I areas (see Section 10.6. and Chapter 11 of the Texas
Regional Haze SIP and Table 14 below). In considering the four
reasonable progress factors under 40 CFR 51.308(d)(i)(A), as discussed
in Section V.C.2, above, the TCEQ also took other factors into
consideration in determining that it is not reasonable to achieve the
glide paths in 2018 and that the RPGs adopted by the state are
reasonable. The TCEQ indicated that the ability to meet the URP or make
additional progress towards reaching natural visibility conditions is
impeded primarily by the following: the significant contribution of
emissions from Mexico and other international sources; the uncertainty
in the effect of CAIR; and the poor cost-effectiveness of additional
reasonable point source controls.
    The TCEQ noted that the CENRAP PSAT analysis indicates that 52% of
the impairment at Big Bend and 25% of the impairment at Guadalupe
Mountains is from Mexico and further south. Substantial reductions in
emissions from outside the United States are needed to meet the goal of
natural visibility at the Texas Class I areas. As discussed elsewhere
in this notice, the TCEQ considered the URP and the emission reductions
necessary to meet the URP in establishing the RPG.

 Table 14--CENRAP's PSAT Contribution to Visibility in the Texas Class I
                       Areas on the Worst 20% Days
------------------------------------------------------------------------
                                                             Guadalupe
          Contribution by area             Big Bend  (%)  Mountains  (%)
------------------------------------------------------------------------
Texas...................................            24.8            34.8
Mexico..................................            26.7            16.5
Boundary Conditions.....................            25.7             8.7
Other U.S...............................            11.9            18.9
Miscellaneous...........................             5.8             9.6
Neighboring States......................             5.1            11.5
------------------------------------------------------------------------

    In addition, with respect to reductions at Texas sources, the TCEQ
noted a wide range of measures and programs in place in Texas that
result in emission reductions that often go beyond federal
requirements. Chapter 11 and Appendices 11-2 (Federal and Texas
Programs Related to On-Road and Non-Road Mobile Sources) and 11-3
(Major Point Source NOX Rules and Reductions Promulgated in
Texas Since 2000) detail additional rules and programs that minimize
emissions that can cause or contribute to local and regional visibility
impairment. In Section 10.2 of the Texas regional haze SIP, the TCEQ
identifies the following programs:
     Opacity limits on grandfathered facilities;
     Best Available Control Technology (BACT) requirements that
typically go beyond EPA's New Source Performance Standards (NSPS) for
new and modified sources;
     Extensive NOX emission limits on existing and
new sources including major, minor and area sources including some on a
statewide basis;
     Texas Emission Reduction Program (TERP), which provides
financial incentives to accelerate the implementation of new, cleaner
diesel engine technologies in on-road and non-road applications; and
     Air Check Texas Repair and Replacement Assistance Program,
which provides financial incentives for scrapping older gasoline-
powered on-road vehicles.
    The TCEQ noted that the established RPGs reflect emission reduction
programs already in place, including CAIR, additional refinery
SO2 reductions as a result of refinery consent decrees,
Texas ozone SIP revisions, and the Texas Clean Air Act. It noted that
the majority of the emission reductions underlying the predicted
visibility improvements are from the CAIR program or its eventual
replacement. The TCEQ assumes that any replacement for CAIR will
include interstate trading of emissions allowances and therefore there
is uncertainty regarding how visibility will be improved at individual
Class I areas. The TCEQ states that because emission allowances can be
purchased by EGUs relatively close to the Texas Class I areas from EGUs
far from the Texas Class I areas, the visibility improvement, may not
be as great as predicted by the CENRAP's modeling. Conversely, nearby
EGUs may elect to control beyond their emission caps and sell emission
allowances out of state, resulting in reduced emissions closer to the
Texas Class I areas.
    The TCEQ concluded that ``given the significant impact from
international emissions, the uncertainty in the impact of CAIR, and the
poor cost-effectiveness of additional, reasonable point source
controls, the TCEQ has determined that additional controls for regional
haze are not appropriate at this time.'' \216\
---------------------------------------------------------------------------

    \216\ Section 10.7 of the Texas Regional Haze SIP.
---------------------------------------------------------------------------

b. Our Evaluation
    We agree that there is uncertainty regarding the size and location
of reductions at Texas EGUs due to implementation of CAIR/CSAPR. While
reductions at certain facilities within Texas would result in
improvements in visibility conditions at the Texas Class I areas or
Class I areas in other states, similar reductions at other facilities
may have no impact on visibility conditions at the Class I area.
Furthermore, reductions that are seasonal in nature due to decreased
operation during the fall and/or winter reduce annual emissions,
contribute towards CAIR/CSAPR compliance, but will not lead to improved
visibility during the 20% worst days, which typically occur during the
summer months. For example, in recent years the Monticello units have
been shut down for several non-summer months, which has resulted in
reduced annual emissions, while having no impact on summer time
emissions or visibility impacts during the summer months. The CENRAP
source apportionment results include the projected reductions due to
CAIR compliance and show that even after these reductions, impacts from
Texas points sources remain the most significant portion of the total
visibility impairment with available controls at Big Bend and
Guadalupe. Analysis of recent emissions from Texas EGUs shows that in
many cases current emission levels are above those predicted in the
2018 CENRAP modeling. In fact, in the case of Martin Lake, current
annual emissions are roughly twice those included in the 2018 modeling,
and we are not aware of

any upcoming controls or changes in operation to suggest that future
actual emissions will decrease to those predicted levels.
    We also agree with the TCEQ's conclusion that it is not reasonable
to meet the URP for the Texas Class I areas for this planning period.
We agree with the TCEQ that emissions and transport from Mexico and
other international sources will limit the rate of progress achievable
on the 20% worst days and that efforts to meet the goal of natural
visibility by 2064 would require further emission reductions not only
within Texas, but also large emission reductions from international
sources.
    We also note the more recent IMPROVE monitored data at the Big Bend
and Guadalupe Mountains indicate that more progress than anticipated by
the CENRAP modeling has occurred.\217\ The most recent five-year (2009-
2013) average conditions for the 20% worst days is 16.3 dv at Big Bend
and 15.3 dv at Guadalupe Mountains. This is below the level anticipated
in the CENRAP projection for 2018 of 16.6 dv for Big Bend and 16.3 dv
for Guadalupe Mountains. We believe that this observed improvement from
the baseline conditions is the result of meteorological conditions,
reduction in the impacts from SO2 emissions, and a reduction
in the impacts from coarse material. More recent emission inventory
data shows reductions in emissions in most states beyond what was
projected in the 2018 modeling, including large reductions in emissions
from the Eastern United States. Emissions from non-EGU Texas point
sources are lower than have been projected in the modeling. We note
that additional reductions are still needed to meet or exceed the URP
goals for 2018 as calculated by us in Section VII.M below. As discussed
above, emission reductions at some of the sources that impact
visibility the most are still above the emission level projected in the
model and we believe that cost-effective controls are likely available
at these sources.
---------------------------------------------------------------------------

    \217\ Available at: http://vista.cira.colostate.edu/tss/
---------------------------------------------------------------------------

    However, for the reasons we have discussed above, although we agree
with the TCEQ that a rate of improvement necessary to attain natural
visibility conditions by 2064 is not reasonable, we do not believe that
the rate of improvement the TECQ has selected is reasonable, because we
disagree with its four factor analysis and the analysis of emission
measures needed to meet the URP. Therefore we propose to disapprove the
TCEQ's RPGs for Big Bend and the Guadalupe Mountains under Section
51.308(d)(1)(ii). In so doing, we rely on the specific directive in
Section 51.308(d)(1)(iii): ``In determining whether the State's goal
for visibility improvement provides for reasonable progress towards
natural visibility conditions, the Administrator will evaluate the
demonstrations developed by the State pursuant to paragraphs (d)(1)(i)
and (d)(1)(ii) of this section.'' We also propose to disapprove the
Texas' RPGs for the 20% best days. We propose to find that visibility
on these days will be better than Texas projects, given additional
controls in our proposed FIP.
5. Reasonable Progress Consultation
    Pursuant to Section 51.308(d)(1)(iv), Texas consulted with other
states which may reasonably be anticipated to cause or contribute to
visibility impairment at its two Class I areas. In any situation in
which Texas cannot agree with another such state or group of states
that a goal provides for reasonable progress, Texas must describe in
its submittal the actions taken to resolve the disagreement. In
reviewing Texas' SIP submittal, the Administrator will take this
information into account in determining whether Texas' goal for
visibility improvement provides for reasonable progress towards natural
visibility conditions.
    The TCEQ held three conference calls in July, 2007 to which
Arkansas, Kansas, Louisiana, New Mexico, and Oklahoma were invited. The
TCEQ used CENRAP generated products, such as regional photochemical
modeling results and visibility projections, and source apportionment
modeling to assist in identifying neighboring states' contributions to
the visibility impairment at its Class I areas. Specifically, the TCEQ
used the results from the CENRAP particulate matter source
apportionment technology (PSAT) modeling to determine that New Mexico,
Oklahoma, Kansas, and Louisiana contribute to visibility impairment at
the Texas Class I areas. The TCEQ invited those states with a > 0.5
inverse megameter impact on one of its Class I areas to its
consultations. Other participants that attended one or more of the
calls included CENRAP, us, and the federal land managers. The TCEQ
invited tribes in all of the CENRAP states to the consultation calls,
but no tribes participated in the consultation on Big Bend and
Guadalupe Mountains. These calls are summarized in Appendix 4-1 of the
Texas regional haze SIP.
    The first consultation call primarily addressed technical papers
that discussed the natural conditions, the impacts of dust storms in
Big Bend and the Guadalupe Mountains, our IPM emission projections, and
the URP and RPGs for the Texas Class I areas. The second and third
consultation calls consisted of discussions between the states and
federal land managers regarding the dust storm technical papers. The
TCEQ presented the URPs for its Class I areas, discussed controls that
are in place in Texas, and its decision that no additional controls
would be included in its regional haze SIP. The federal land managers
suggested that the TCEQ revise the Prevention of Significant
Deterioration (PSD) permit process to include FLM notification
provisions. Texas committed to further consultations with the federal
land managers to address their concerns about the Texas PSD program.
    The TCEQ discussed the CENRAP PSAT modeling results with the
attendees. It noted that the BRAVO study indicated that for
SO4, which has the largest visibility impact of all
pollutants at Big Bend, approximately \1/3\ comes from Mexico, \1/3\
from Texas, and \1/3\ from the Midwest and South beyond Texas. It noted
that these results are somewhat inconsistent with CENRAP PSAT modeling
results, which indicate that slightly more than half of the visibility
impairment at Big Bend comes from Mexico and other areas outside the
U.S.
    New Mexico and the federal land managers discussed that despite the
Guadalupe Mountains in Texas and Carlsbad Caverns in New Mexico sharing
the same monitor, these Class I areas appeared to have significantly
different calculated natural visibility values, individually prepared
by the two states.\218\ The federal land managers and we both expressed
a desire to review the TCEQ's natural visibility calculation.
---------------------------------------------------------------------------

    \218\ Note that we discuss the difference between the natural
visibility value calculated by New Mexico for Carlsbad Caverns and
that calculated by Texas for the Guadalupe Mountains elsewhere in
our proposal.
---------------------------------------------------------------------------

    The TCEQ concluded its consultations by noting that other states'
visibility impacts on Big Bend and the Guadalupe Mountains are
relatively small. Texas sources are responsible for 25% and 35% of the
visibility impairment at Big Bend and the Guadalupe Mountains,
respectively. Neighboring states combined contribute only 5% of the
visibility impairment at Big Bend and 11.5% at the Guadalupe Mountains.
As a result of these

consultations, the TCEQ did not request any additional reductions from
other states.
    Citing the source apportionment results and results of the BRAVO
study, in Section 11.3 of the Texas regional haze SIP, Texas requests
in its SIP that we initiate and pursue federal efforts to reduce
impacts from international transport. Due to large contributions from
international sources, the TCEQ concludes it will be impossible to
reach natural conditions without significant reductions in Mexico and
other countries, in parallel with reductions within Texas and the rest
of the United States. The TCEQ notes that Class I areas in other states
will also benefit from reductions in emissions from international
sources. We acknowledge that emissions from Mexico significantly impact
the visibility at Big Bend and the Guadalupe Mountains. As we state in
the Regional Haze Rule,\219\ ``the EPA does not expect States to
restrict emissions from domestic sources to offset the impacts of
international transport of pollution. We believe that States should
evaluate the impacts of current and projected emissions from
international sources in their regional haze programs, particularly in
cases where it has already been well documented that such sources are
important.''
---------------------------------------------------------------------------

    \219\ 64 FR 35736 (July 1, 1999).
---------------------------------------------------------------------------

    We reviewed the CENRAP PSAT data for the Texas Class I areas
referred to during the consultation calls, as well as the technical
papers discussed during those calls and the summary of the calls in
Appendix 4-1 of Texas' SIP submittal. Approximately half of the 2002
visibility impairment at Big Bend is due to Mexico and other
international sources captured in the modeled boundary conditions, one
quarter of the impairment is due to Texas sources and the remaining
quarter is due to all the remaining sources combined, with the largest
contributions in this group from the Eastern United States (2.5%) and
Louisiana (2.8%). Examining only contributions due to point sources in
2002, Texas point sources contribute 10% of the total visibility
impairment at Big Bend and Mexico point sources contribute 16.9%. The
largest impact from a nearby state is Louisiana at a little more than
2% contribution. All other nearby states contribute less than 1% to the
total visibility impairment at Big Bend. The source apportionment
results for 2018 projections at Big Bend show similar levels of
contribution with a slight decrease in Texas and Eastern United States
contributions. Mexico and other international sources contribute
approximately one quarter of the visibility impairment and Texas
contributes about one third of the visibility impairment at the
Guadalupe Mountains in 2002. The next largest contributing source
regions are New Mexico (7.3%, 4.7% from natural sources), Kansas
(3.3%), the Eastern United States (3.2%), Western United States (3.0%),
and Oklahoma (2.5%). Examining only contributions due to point sources
in 2002, Texas point sources contribute 8.7% of the total visibility
impairment and Mexico point sources contribute 6.8%. The largest impact
from a nearby state is New Mexico at a little more than 1%
contribution. All other nearby states contribute less than 1% to the
total visibility impairment at Guadalupe Mountains. The source
apportionment results for 2018 projections at Guadalupe Mountains show
similar levels of contribution with a slight decrease in eastern United
States contributions. PSAT results show an overwhelming contribution
from international sources and Texas sources and the technical papers
shared by Texas suggest that dust storms significantly impact a number
of the worst 20% days at these Class I areas.
    We find that the TCEQ appropriately identified those states with
the largest impacts on Texas Class I areas and invited them for
consultation. We agree with Texas' determination that was not
reasonable to request additional controls from other states at this
time. Given the small contributions from individual nearby states,
especially when only considering anthropogenic sources that can be
easily controlled in comparison with the size of impacts from Texas
sources and international sources, we find that it was reasonable for
the TCEQ to have focused the analysis of additional controls on sources
within Texas. We propose to find that Texas has satisfied the
requirement under Section 51.308(d)(1)(iv) to consult with other states
which may reasonably be anticipated to cause or contribute to
visibility impairment at its two Class I areas.

D. Evaluation of Texas' BART Determinations

    As part of its strategy to address BART, the TCEQ adopted a BART
rule on January 10, 2007, as 30 TAC Chapter 116, Subchapter M.\220\
This rule identifies potentially affected sources as those belonging to
one of 26 BART source industry categories; having a Potential to Emit
(PTE) of 250 tpy or more of any visibility impairing pollutant; and not
operating prior to August 7, 1962, and being in existence on August 7,
1977. It uses a value of 0.5 dv as the visibility contribution
threshold. It also incorporates the BART model plant and de minimis
exemption criteria discussed below, and exempts EGUs that participate
in CAIR from undergoing a BART review for NOX and
SO2. It specifies that all non-exempt sources must undergo a
BART review, according to the BART Guidelines. Lastly, it provides that
BART controls must be installed and operational within 5 years
following our approval of this SIP. We have reviewed the Texas BART
rule and propose to approve it, with the exception of Texas' reliance
on CAIR to meet BART, as discussed in more detail in Section V.D.3.
---------------------------------------------------------------------------

    \220\ The Texas BART Rule is present in Appendix 9-2 of the
Texas regional haze SIP.
---------------------------------------------------------------------------

    Texas exercised its option under Section 51.308(e)(4) (as it read
at that time) that participation in CAIR is equivalent to BART. This
exempted EGUs impacted by CAIR from a BART analysis for SO2
and NOX. As a result, the TCEQ did not evaluate BART-
eligible EGUs that are included in CAIR for SO2 and
NOX. This EGU BART exemption does not extend to particulate
matter. As explained further in Section V.D.3, we earlier issued a
limited disapproval of Texas' regional haze SIP based on its reliance
on CAIR. We are now proposing a FIP to replace reliance on CAIR with
reliance on the trading programs of CSAPR as an alternative to BART for
SO2 and NOX emissions from EGUs in the regional
haze plan for Texas.
    As discussed in more detail in our BART Rule,\221\ the BART
evaluation process consists of three components: (1) An identification
of all the BART-eligible sources, (2) an assessment of whether those
BART-eligible sources are in fact subject to BART and (3) a
determination of any BART controls. The TCEQ addressed these steps as
follows:
---------------------------------------------------------------------------

    \221\ 70 FR 39104 (July 6, 2005).
---------------------------------------------------------------------------

1. Identification of BART-Eligible Sources
    The first step of a BART evaluation is to identify all the BART-
eligible sources within the state's boundaries. The TCEQ identified the
BART-eligible sources in Texas by utilizing the three eligibility
criteria in the BART Guidelines \222\ and our regulations (Section
51.301): (1) One or more emission units at the facility fit within one
of the 26 categories listed in the BART Guidelines; (2) the emission
unit(s) began operation on or after August 6, 1962, and was in
existence on

August 6, 1977; and (3) potential emissions of any visibility-impairing
pollutant from subject units are 250 tons or more per year.
---------------------------------------------------------------------------

    \222\ 70 FR 39158-39161 (July 6, 2005).
---------------------------------------------------------------------------

    The TCEQ did not have a comprehensive database of potential
emissions from facilities, so it used annual emissions reporting with
some adjustments. The TCEQ's State of Texas Air Reporting System
(STARS) database was used to determine which sources were potentially
BART-eligible. In addition to NOX and SO2, the
TCEQ also screened its database for sources of Volatile Organics (VOC)
and coarse particulate matter (PM10) greater than 200 tpy.
The TCEQ used PM10 as a conservative value for direct
PM2.5. However, because this database does not contain all
information necessary to determine BART eligibility, the TCEQ also
surveyed companies regarding their potential to emit and construction
dates in order to complete the BART eligibility determination. In order
to reduce the number of companies requiring clarification, the TCEQ
chose to adopt a model plant analysis approach based on our model
plants \223\ in order to eliminate smaller sources of NOX
and SO2 sources from being surveyed and potentially subject
to BART. Regarding the use of the model plant approach, the BART
Guidelines state:\224\
---------------------------------------------------------------------------

    \223\ 70 FR 39162 (July 6, 2005).
    \224\ 70 FR 39163 (July 6, 2005).

    Based on our analyses, we believe that a State that has
established 0.5 deciviews as a contribution threshold could
reasonably exempt from the BART review process sources that emit
less than 500 tons per year of NOX or SO2 (or
combined NOX and SO2), as long as these
sources are located more than 50 kilometers from any Class I area;
and sources that emit less than 1000 tons per year of NOX
or SO2 (or combined NOX and SO2)
---------------------------------------------------------------------------
that are located more than 100 kilometers from any Class I area.

    Since the STARS database includes reported actual emissions instead
of potential to emit, the TCEQ added some conservatism to the inclusion
of sources. The TCEQ modified its model plant approach and reduced the
emission threshold to 375 tpy for sources greater than 50 km and 750
tpy for sources greater than 100 km to capture sources that might not
have been above the BART Guideline's emissions threshold, based only on
their 2002 emissions levels.
    As a result of the BART eligibility screening analysis, 254 sites/
facilities (approximately 12% of the 2,165 facilities in the Texas 2002
emissions inventory) were identified as being potentially BART-eligible
based on their county's minimum distance to Class I areas and their
actual emissions. The TCEQ then sent surveys to these sites to request
additional information in identifying construction or reconstruction
dates and whether the potential to emit of potential BART eligible
equipment exceeded the BART eligibility threshold of 250 tpy. As a
result of the BART eligibility survey, the TCEQ determined that the
following sites \225\ numbered 1 through 120 were BART-eligible. During
TCEQ's review of BART eligible sources another 6 facilities were
identified as potentially BART eligible (numbered 121-126):
---------------------------------------------------------------------------

    \225\ Reproduced from Table 9-2 of the Texas regional haze SIP
with additional sources later identified added.

                    Table 15--Potential BART-Eligible Sources Based on Results of TCEQ Survey
----------------------------------------------------------------------------------------------------------------
          No.                    Account                  Source                  Regulated entity          SIC
----------------------------------------------------------------------------------------------------------------
1......................  AC0017B                 Abitibi Consolidated      RN100220110                      2621
                                                  Corp.
2......................  TG0044C                 AEP Texas...............  RN101531226                      4911
3......................  CD0013K                 AEP Texas Central         RN102560687                      4911
                                                  Company.
4......................  NE0024E                 AEP Texas Central         RN100642040                      4911
                                                  Company.
5......................  NE0026A                 AEP Texas Central         RN100552181                      4911
                                                  Company.
6......................  JI0030K                 AEP Texas North Company.  RN100215557                      4911
7......................  CB0003M                 Alcoa Alumina &           RN100242577                      2819
                                                  Chemicals.
8......................  MM0001T                 Alcoa Inc...............  RN100221472                      3334
9......................  HT0011Q                 Alon USA Lp.............  RN100250869                      2911
10.....................  ED0034O                 Ash Grove (Formerly       RN100225978                      3241
                                                  North Texas Cement).
11.....................  HG0558G                 Atofina Chemicals Inc...  RN100209444                      2869
12.....................  BL0021O                 BASF Corporation........  RN100218049                      2869
13.....................  GB0001R                 BP Amoco Chemical         RN102536307                      2869
                                                  Company.
14.....................  GB0004L                 BP Products North         RN102535077                      2911
                                                  America In Texas.
15.....................  GH0003Q                 Cabot Corporation.......  RN100221761                      2895
16.....................  BG0045E                 Capitol Cement Div        RN100211507                      3241
                                                  Capitol.
17.....................  GH0004O                 Celanese Chemical.......  RN101996395                      2869
18.....................  MH0009H                 Celanese Limited........  RN100258060                      2869
19.....................  ED0011D                 Chaparral Steel           RN100216472                      3312
                                                  Midlothian.
20.....................  BJ0001T                 Chemical Lime Ltd.......  RN100219856                      3274
21.....................  HG0310V                 Chevron Phillips          RN103919817                      2869
                                                  Chemical.
22.....................  BL0758C                 Chevron Phillips          RN100825249                      2869
                                                  Chemical.
23.....................  HW0013C                 Chevron Phillips          RN102320850                      2869
                                                  Chemical Co.
24.....................  NE0027V                 Citgo Refining &          RN102555166                      2911
                                                  Chemicals.
25.....................  BG0057U                 City Public Service.....  RN100217975                      4911
26.....................  BG0186I                 City Public Service.....  RN100217835                      4911
27.....................  HW0018P                 Conoco Phillips           RN102495884                      2911
                                                  (Formerly Phillips 66).
28.....................  CR0020C                 Copano Processing LP....  RN101271419                      1321
29.....................  AB0012W                 DCP (Formerly Duke        RN100218684                      1321
                                                  Energy Field Services).
30.....................  HW0008S                 Degussa Engineered        RN100209659                      2895
                                                  Carbons.
31.....................  HGA005E                 DOW.....................  RN104150123                      2869
32.....................  HG0126Q                 DOW.....................  RN100227016                      2869
33.....................  CI0022A                 Dynegy Midstream          RN100222900                      1321
                                                  Services.
34.....................  HH0042M                 Eastman Chemical Company  RN100219815                      2869
35.....................  HG0218K                 E.I. Dupont de Nemours &  RN100225085                      2869
                                                  Co.
36.....................  OC0007J                 E.I. Dupont de Nemours &  RN100542711                      2869
                                                  Co.
37.....................  EE0029T                 El Paso Electric Co.....  RN100211309                      4911

38.....................  TH0004D                 Electric Utility Dept...  RN100219872                      4911
39.....................  CG0012C                 Enbridge Pipelines......  RN102166964                      1321
40.....................  MQ0009F                 Entergy Gulf States Inc.  RN100226877                      4911
41.....................  OC0013O                 Entergy Gulf States Inc.  RN102513041                      4911
42.....................  BL0113I                 Equistar................  RN100218601                      2869
43.....................  BL0268B                 Equistar Chemicals LP...  RN100237668                      2821
44.....................  HG0033B                 Equistar Chemicals LP...  RN100542281                      2869
45.....................  HG0228H                 Exxon Chemical Co.......  RN102212925                      2869
46.....................  JE0065M                 Exxon Mobil Chemical Co.  RN100211903                      2821
47.....................  HG0229F                 ExxonMobil Chemical Co..  RN102574803                      2869
48.....................  HG0232Q                 ExxonMobil Corp.........  RN102579307                      2911
49.....................  JE0067I                 ExxonMobil Oil Corp.....  RN102450756                      2911
50.....................  NE0120H                 Flint Hills Resources...  RN102534138                      2911
51.....................  NE0122D                 Flint Hills Resources LP  RN100235266                      2911
52.....................  JE0052V                 Huntsman Corporation....  RN100219252                      2869
53.....................  JE0135Q                 Huntsman Petrochemical    RN100217389                      2869
                                                  Corp.
54.....................  EB0057B                 Huntsman Polymers.......  RN101867554                      2869
55.....................  BL0002S                 INEOS Olefins & Polymers  RN100238708                      2869
56.....................  CG0010G                 International Paper Co..  RN100543115                      2621
57.....................  OCA002B                 Invista.................  RN104392626                      2869
58.....................  VC0008Q                 Invista (Formerly Du      RN102663671                      2869
                                                  Pont De Nemours).
59.....................  WE0005G                 Laredo Power............  RN100213909                      4911
60.....................  MB0123F                 Lehigh Cement Company...  RN100218254                      3241
61.....................  NE0025C                 Lon C Hill Power........  RN100215979                      4911
62.....................  BC0015L                 Lower Colorado River      RN102038486                      4911
                                                  Authority.
63.....................  FC0018G                 Lower Colorado River      RN100226844                      4911
                                                  Authority.
64.....................  HG1575W                 Lyondell Chemical.......  RN100633650                      2869
65.....................  HG0048L                 Lyondell Citgo Refining.  RN100218130                      2911
66.....................  GB0055R                 Marathon Ashland          RN100210608                      2911
                                                  Petroleum.
67.....................  HH0019H                 NORIT Americas Inc......  RN102609724                      2819
68.....................  GB0037T                 NRG Texas (Formerly       RN101062826                      4911
                                                  Texas Genco LP).
69.....................  ED0051O                 Owens Corning...........  RN100223585                      3296
70.....................  HG1451S                 Oxyvinyls LP............  RN102518065                      2821
71.....................  HG0175D                 Pasadena Refining.......  RN100716661                      2911
72.....................  JE0042B                 Premcor Refining Group..  RN102584026                      2911
73.....................  MC0002H                 Regency Tilden Gas        RN100216621                      2819
                                                  (Formerly Enbridge).
74.....................  HG0697O                 Rhodia Inc..............  RN100220581                      2819
75.....................  HG0632T                 Rohm & Haas Texas.......  RN100223205                      2869
76.....................  HG0659W                 Shell Oil Co............  RN100211879                      2911
77.....................  HW0017R                 Sid Richardson Carbon...  RN100222413                      2895
78.....................  HT0027B                 Sid Richardson Carbon Co  RN100226026                      2895
79.....................  BL0038U                 Solutia Inc.............  RN100238682                      2869
80.....................  TF0012D                 Southwestern Electric     RN100213370                      4911
                                                  Power.
81.....................  GJ0043K                 Southwestern Electric     RN102156916                      4911
                                                  Power.
82.....................  ME0006A                 Southwestern Electric     RN100542596                      4911
                                                  Power.
83.....................  PG0040T                 Southwestern Public       RN100224641                      4911
                                                  Service.
84.....................  PG0041R                 Southwestern Public       RN100224849                      4911
                                                  Service.
85.....................  LN0081B                 Southwestern Public       RN100224765                      4911
                                                  Service.
86.....................  JE0091L                 Sun Marine Terminal.....  RN100214626                      4226
87.....................  WN0042V                 Targa...................  RN102552387                      1311
88.....................  CY0019H                 Targa (Formerly Dynegy    RN102551785                      1311
                                                  Midstream).
89.....................  OC0019C                 Temple-Inland...........  RN100214428                      2621
90.....................  CI0012D                 Texas Genco LP..........  RN100825371                      4911
91.....................  FG0020V                 Texas Genco LP..........  RN100888312                      4911
92.....................  HK0014M                 Texas Lehigh Cement Co..  RN102597846                      3241
93.....................  HG0562P                 Texas Petrochemicals LP.  RN100219526                      2869
94.....................  BL0082R                 The Dow Chemical Co.....  RN100225945                      2869
95.....................  JE0039N                 The Goodyear Tire And     RN102561925                      2822
                                                  Rubber Co.
96.....................  NE0022I                 Ticona Polymers Inc.....  RN101625721                      2869
97.....................  JE0005H                 Total Petrochemicals....  RN102457520                      2911
98.....................  ED0066B                 TXI Operations LP.......  RN100217199                      3241
99.....................  FI0020W                 TXU Big Brown Company LP  RN101198059                      4911
100....................  DB0251U                 TXU Electric Company....  RN101559854                      4911
101....................  FB0025U                 TXU Generation Company    RN102285855                      4911
                                                  LP.
102....................  HQ0012T                 TXU Generation Company    RN100664812                      4911
                                                  LP.
103....................  MB0116C                 TXU Generation Company    RN102566494                      4911
                                                  LP.
104....................  MM0023J                 TXU Generation Company    RN102147881                      4911
                                                  LP.
105....................  MO0014L                 TXU Generation Company    RN102285848                      4911
                                                  LP.
106....................  RL0020K                 TXU Generation Company    RN102583093                      4911
                                                  LP.
107....................  TA0352I                 TXU Generation Company    RN100693308                      4911
                                                  LP.
108....................  WC0028Q                 TXU Generation Company    RN102183969                      4911
                                                  LP.
109....................  YB0017V                 TXU Generation Company    RN102563426                      4911
                                                  LP.

110....................  TF0013B                 TXU Generation Company    RN102285921                      4911
                                                  LP.
111....................  GB0076J                 Union Carbide Corp......  RN100219351                      2869
112....................  CB0028T                 Union Carbide             RN102181526                      2869
                                                  Corporation.
113....................  HR0018T                 Valence Midstream Ltd...  RN100213685                      1321
114....................  GB0073P                 Valero Refining Co Texas  RN100238385                      2911
115....................  NE0043A                 Valero Refining Company.  RN100211663                      2911
116....................  MR0008T                 Valero McKee............  RN100210517                      2911
117....................  WH0014S                 Vetrotex Wichita Falls    RN100218601                      3229
                                                  Plant.
118....................  VC0003D                 Victoria Power..........  RN100214980                      4911
119....................  JB0016M                 Vintage Petroleum Inc...  RN100214592                      1311
120....................  JC0003K                 Westvaco................  RN102157609                      2631
121 \226\..............  JE0343H                 BMC Holdings Inc........  .............................  ......
122....................  AG0024G                 Pueblo Midstream Gas      .............................  ......
                                                  Corp.
123....................  GBA007G                 INEOS...................  .............................  ......
124....................  HG0130C                 Valero Refining Texas LP  .............................  ......
125....................  JH0025O                 Johns Manville            .............................  ......
                                                  International.
126....................  PE0024Q                 Regency Gas Services....  .............................  ......
----------------------------------------------------------------------------------------------------------------

    We have reviewed the TCEQ's development of their list of BART-
eligible facilities (ultimately 126 sources) and we propose to conclude
that the TCEQ has adequately identified all sources that are BART
eligible in the state.
---------------------------------------------------------------------------

    \226\ Numbers 121-130 were not included in TCEQ's initial list
of 120 sources potentially subject to BART but were added during
their review and development of the SIP.
---------------------------------------------------------------------------

2. Identification of Sources Subject to BART
    The second step of the BART evaluation is to identify those BART-
eligible sources that may reasonably be anticipated to cause or
contribute to visibility impairment at any Class I area, i.e. those
sources that are subject to BART. The BART Guidelines allow states to
consider exempting some BART-eligible sources from further BART review
because they may not reasonably be anticipated to cause or contribute
to any visibility impairment in a Class I area. Sources that are not
exempted by the state are required to conduct a full BART analysis and
the state then makes a determination of what is BART for each of these
subject to BART sources.
a. Modeling Methodology
    Consistent with the BART Guidelines, the TCEQ chose to evaluate
sources and determine if they were exempt from being subject to BART.
When exempting sources from BART because they do not cause or
contribute to visibility impairment in a Class I area, the BART
Guidelines suggest three sub-options for determining that certain
sources are not subject to BART: \227\
---------------------------------------------------------------------------

    \227\ 70 FR 39162-3 (July 6, 2005).
---------------------------------------------------------------------------

     The use of model plants to exempt sources with common
characteristics.
     A cumulative modeling analysis to show that groups of
sources are not subject to BART.
     An individual source attribution approach.
    The TCEQ utilized all of these options to determine which sources
were subject to BART. These BART exemption exercises are explained
below. The BART Guidelines direct states to address SO2,
NOX and direct PM (including both PM10 and
PM2.5) emissions as visibility-impairing pollutants, and
states must exercise their ``best judgment to determine whether VOC or
ammonia emissions from a source are likely to have an impact on
visibility in an area.'' \228\ Ammonia (NH3) emissions in
Texas are primarily due to area sources, such as livestock and
fertilizer application.\229\ Because these are not point sources, they
are not subject to BART. CENRAP modeling demonstrated that VOCs from
anthropogenic sources are not significant visibility-impairing
pollutants at the Guadalupe Mountains and Big Bend. The TCEQ further
investigated VOC and direct PM impacts with the photochemical modeling
as discussed below. We have reviewed this information and propose to
agree with the TCEQ's decision to address only SO2,
NOX and PM as visibility impairing pollutants because VOC
emissions from anthropogenic sources are not significant visibility-
impairing pollutants at Class I areas in Texas and surrounding states
and NH3 emissions in Texas are primarily due to area
sources.
---------------------------------------------------------------------------

    \228\ 70 FR 39162 (July 6, 2005).
    \229\ See Tables 7-1 and 7-3 of the Texas regional haze SIP.
Area sources comprise approximately 94% of the total 2002 ammonia
emissions, and approximately 93% of the total projected 2018 ammonia
emissions.
---------------------------------------------------------------------------

    The BART Guidelines provide that states may choose to use the
CALPUFF \230\ modeling system, or another appropriate model, to predict
the visibility impacts from a single source on a Class I area and to
therefore determine whether an individual source is anticipated to
cause or contribute to impairment of visibility in Class I areas, i.e.,
``is subject to BART.'' The Guidelines state that we believe CALPUFF is
the best regulatory modeling application currently available for
predicting a single source's contribution to visibility
impairment.\231\ The TCEQ consulted with us and FLM representatives and
used both the Comprehensive Air Quality Model with extensions (CAMx)
\232\ and CALPUFF modeling systems to determine whether individual
sources in Texas were subject to or exempt from BART.
---------------------------------------------------------------------------

    \230\ Note that our reference to CALPUFF encompasses the entire
CALPUFF modeling system, which includes the CALMET, CALPUFF, and
CALPOST models and other pre and post processors. The different
versions of CALPUFF have corresponding versions of CALMET, CALPOST,
etc. which may not be compatible with previous versions (e.g., the
output from a newer version of CALMET may not be compatible with an
older version of CALPUFF). The different versions of the CALPUFF
modeling system are available from the model developer at http://www.src.com/verio/download/download.htm.
    \231\ 70 FR 39162 (July 6, 2005).
    \232\ CAMx model code and user's guide can be found at http://www.camx.com/download/default.aspx.Model code used in our analysis
is available with the modeling files.
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    The BART Guidelines also recommend that states develop a modeling
protocol for making individual source attributions, and suggest that
states may choose to consult with us and their regional planning
organization to address any

issues prior to modeling. The CENRAP states, including Texas, developed
the ``CENRAP BART Modeling Guidelines.'' \233\ Stakeholders, including
EPA, FLM representatives, industrial sources, trade groups, and other
interested parties, actively participated in the development and review
of the CENRAP protocol. CENRAP provided readily available modeling data
bases for use by states to conduct their analyses. We note that the
original CALPUFF meteorological databases generated by CENRAP did not
include observations as our guidance recommends,\234\ therefore sources
were evaluated using the 1st High values instead of the 8th High
values. The use of the 1st High modeling values was agreed to by us,
representatives of the Federal Land Managers, and CENRAP stakeholders.
We propose to find the chosen model and the general modeling
methodology for the initial CALPUFF based screening modeling with
CENRAP meteorological data acceptable. We further discuss both refined
analyses using CALPUFF and CAMx modeling systems below.
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    \233\ CENRAP BART Modeling Guidelines, T. W. Tesche, D. E.
McNally, and G. J. Schewe (Alpine Geophysics LLC), December 15,
2005, available at http://www.deq.state.ok.us/aqdnew/RulesAndPlanning/Regional_Haze/SIP/Appendices/index.htm.
    \234\ 40 CFR part 51, Appendix W: Guideline on Air Quality
Models Parts 8.3(d) and <IP_ADDRESS>(d).
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b. Contribution Threshold
    For states using modeling to determine the applicability of BART to
single sources, the BART Guidelines note that the first step is to set
a contribution threshold to assess whether the impact of a single
source is sufficient to cause or contribute to visibility impairment at
a Class I area. The BART Guidelines state that, ``[a] single source
that is responsible for a 1.0 dv change or more should be considered to
`cause' visibility impairment.'' \235\ The BART Guidelines also state
that ``the appropriate threshold for determining whether a source
contributes to visibility impairment' may reasonably differ across
States,'' 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.'' Further, in setting a contribution
threshold, states should ``consider the number of emissions sources
affecting the Class I areas at issue and the magnitude of the
individual sources' impacts. The Guidelines affirm that states are free
to use a lower threshold if they conclude that the location of a large
number of BART-eligible sources in proximity of a Class I area
justifies this approach. Texas adopted a contribution threshold of 0.5
dv for determining which sources are subject to BART. For BART eligible
EGUs that were originally covered by CAIR for NO2 and
SO2, TCEQ used this threshold for PM impacts. For CALPUFF
modeling that used the non-guideline CENRAP meteorological data and
CAMx modeling we agreed to use the 1st High or maximum impact for
evaluation with the threshold value. For the refined CALPUFF modeling
that used meteorological data that did meet our guidelines we agreed
with the use of the 98th percentile value. We agree with Texas'
selection of this threshold value.
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    \235\ 70 FR 39104, 39161 (July 6, 2005).
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    The TCEQ first performed cumulative modeling analyses using the
CAMx model. TCEQ's CAMx modeling utilized the existing CENRAP
photochemical modeling databases and CAMx modeling tools of Particulate
Source Apportionment Tagging (PSAT) with Plume-in-Grid (PiG) treatment
to assess contribution of groups of sources initially and later
individual sources. As a result of this modeling, several BART-eligible
sources were eliminated from further consideration due to their
insignificant impacts on visibility at Class I areas. The remaining
sources were required to perform source-specific screening modeling
analyses using either the CALPUFF or the CAMx model setup developed by
the TCEQ. TCEQ also utilized model plant approaches to screen out some
sources. BART-eligible sources that were not eliminated due to any of
the modeling analyses were then given the option of either reducing
their emissions from their BART-eligible units using an enforceable
mechanism, such as a permit, or performing a BART analysis. The
following sections describe this process.
c. Cumulative Modeling Using CAMx PSAT
    Due to the large number of sources the TCEQ initially conducted a
cumulative modeling analysis to eliminate groups of sources from being
subject to BART, as described in its CAMx modeling protocol and its
CAMx modeling report.\236\ In addition to the cumulative CAMx modeling,
the TCEQ developed its model plants based on the CAMx modeling
results.\237\ CAMx also gave a more sophisticated way to evaluate VOC
emissions from BART sources and determine if they needed to be
evaluated further. The TCEQ also used the CAMx modeling and source
grouping to assess the BART sources' direct PM emissions impacts. It
relied on CAIR coverage for NOX and SO2 emissions
from EGUs subject to CAIR, so it only assessed impacts of VOCs and
direct PM from these sources.
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    \236\ Screening Analysis of Potentially BART-Eligible Sources in
Texas, and Final Report, Screening Analysis of Potential BART-
Eligible Sources in Texas, located in Appendices 9-4 and 9-5 of the
Texas Regional Haze SIP, respectively.
    \237\ See the CAMx modeling report, Addendum I, BART Exemption
Screening Analysis, and Addendum II, BART Exemption Screening
Analysis, located in Appendices 9-5 and 9-6 of the Texas Regional
Haze SIP.
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    The TCEQ's CAMx modeling determined that visibility impacts at
Class I areas due to all VOC emissions from BART eligible sources was
well below the 0.5 dv threshold. The TCEQ CAMx modeling screened direct
PM emissions from 37 EGUs using groupings and some individual source
analyses. Of these, 35 of the 37 sources screened out from BART for
direct PM emissions with the two remaining sources being from Account
TF0012D--SWEPCO Welsh and Account TF0013B--TXU Monticello. The TCEQ
also evaluated VOC emissions from non-EGU sources and screened out all
but one non-EGU facility, the exception being Account CG0010G--
International Paper facility. We have reviewed the TCEQ's analysis as
further discussed in our BART TSD, and we propose to concur with the
TCEQ's screening out of all BART sources from further screening or BART
evaluation for VOC and direct PM emissions except for the International
Paper, Monticello and Welsh accounts that were further evaluated for
screening to be discussed later.
    The TCEQ also developed a Texas model plant for PM based on the
previously discussed PM modeling for evaluation of two additional
sources that were not in the original CAMx grouping modeling for PM. As
further discussed in our BART TSD and the TCEQ's regional haze SIP, two
accounts were screened out from being subject to BART. They were
Account CI0012D--Texas Genco LP and Account HW004D--Agrium. We have
reviewed this analysis and propose to concur with TCEQ's analysis and
conclusion to screen out these two facilities from being subject to
BART for their potential PM impacts.
    For SO2 and NOX BART screening, the TCEQ
screened out many sources that were BART eligible and determined that
they were eliminated from being subject to BART using either the
cumulative CAMx modeling analyses or the Texas model plants approach
based on sources in the CAMx groupings that screened out or using our
model plants.

The 94 non-EGU sources were broken into groups of sources (initially 5-
10 sources per group approximately). Further analysis used the same
sources and broke them into smaller groups for further evaluation and
screening. From this second round of CAMx source grouping, the TCEQ
developed model plants from the sources in the groups that screened
out. The TCEQ's model plant analyses is further discussed in our BART
TSD and the Texas regional haze SIP submittal.
    If the technical analysis indicated a source was screened out, the
TCEQ requested each source to certify that they agreed with the
modeling analyses and data inputs (emissions, stack parameters, etc.).
BART-eligible sources that were not eliminated from being subject to
BART using these methods were required to conduct their own screening
modeling analysis using either CALPUFF or CAMx modeling on an
individual basis, using protocols developed by the TCEQ. As part of
this analysis, the TCEQ also utilized our model plants and more
facility specific information to screen out some facilities. Using
these three techniques (CAMx grouping modeling, Texas model plants, and
our model plants), the TCEQ screened out 72 facilities that were BART
eligible based on their NOX and/or SO2 emissions
from being determined as subject to BART and a full five factor
analysis. Table 17 below summarizes all the BART-eligible sources that
were eliminated and how each source was eliminated. For sources
eliminated from being subject to BART using the cumulative CAMx
modeling analyses, CAMx based model plants and our model plants it is
indicated in the column titled ``Cum. Model CAMx''. For full details
see our BART TSD. We have reviewed the evaluation of facilities in
TCEQ's cumulative/grouping CAMx modeling analyses, the TCEQ's Texas
Model Plants analyses, and the TCEQ's analyses using our Model Plants;
and we propose to concur with the screening out from a full BART
analysis of the 72 facilities indicated in Table 17 under the column
titled ``Cum. Model CAMx'' based on estimated/modeled impacts from
NOX and SO2 from each facility.
    Many of the facilities not screened out by the TCEQ were further
evaluated with individual facility impact modeling using either CALPUFF
or CAMx. We discuss the TCEQ's individual facility analysis in the
following sections.
d. Individual Source Apportionment Modeling Using CALPUFF
    As previously discussed CENRAP developed a CALPUFF modeling
protocol and the meteorological modeling files (CALMET files) for
conducting individual facility impact analysis from NOX and
SO2 emissions. The CENRAP CALMET data set did not include
observations, so CALPUFF modeling that used the CENRAP CALMET data had
to use the 1st High value from the modeling instead of the 8th High.
TCEQ contacted the sources that did not previously screen out and gave
them the option to do additional analysis with CALPUFF and/or CAMx.
Facilities submitted individual source modeling protocols for their
facilities and submitted them to TCEQ, us, and FLM representatives for
review and comment. For the CALPUFF modeling, some sources used the
CENRAP CALMET data and the 1st High metric for evaluation against the
screening level of 0.5 del-dv (delta, or change in deciviews) and other
sources developed CALMET with inclusion of meteorological observations
data and used the 8th High modeling value instead. The TCEQ received
and reviewed the additional individual source attribution modeling
using the CALPUFF model.\238\ The 29 BART-eligible sources that were
eliminated from being subject to BART based on CALPUFF modeling results
are listed in the column labeled ``CALPUFF'' in Table 17, below.
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    \238\ The TCEQ CALPUFF modeling protocol, Best Available
Retrofit Technology (BART) Modeling Protocol to Determine Sources
Subject to BART in the State of Texas, and a summary report for each
modeling demonstration are included in Appendix 9-8 of the Texas
regional haze SIP.
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    We have reviewed the modeling reports and files provided for these
29 modeling efforts. Seventeen facilities screened out using the CENRAP
No-Observation data set and followed the approved CENRAP protocol,
including model setup/flags, post processing procedures, and accepted
versions of the CALPUFF modeling suite at the time. Twelve facilities
screened out using the refined CALMET data set using the CENSARA MM5
data and incorporating land and upper air meteorological data. From the
discussion on PM screening above, there were three facilities that did
not screen out (International Paper, TXU--Monticello, and AEP Welsh)
which were evaluated in these model runs and these facilities were 3 of
the 29 screened out here. We have reviewed the TCEQ's individual source
apportionment CALPUFF modeling analysis, and we propose to concur with
TCEQ's conclusion to screen these 29 sources from being subject to
BART.
e. Individual Source Apportionment Modeling Using CAMx
    Some facilities desired to do a single source analysis with CAMx.
To standardize the modeling and evaluation, TCEQ developed ``The CAMx