Technical Support Document (TSD)
for the Proposed Revised CSAPR Update for the 2008 Ozone NAAQS
Docket ID No. EPA-HQ-OAR-2020-0272
Ozone Transport Policy Analysis
Proposed Rule TSD
U.S. Environmental Protection Agency
Office of Air and Radiation
October 2020
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The analysis presented in this document supports the EPA's proposed Revised Cross-
State Air Pollution Rule Update for the 2008 Ozone NAAQS (Revised CSAPR Update). This
TSD includes analysis to help quantify upwind state emissions that significantly contribute to
nonattainment or interfere with maintenance of the 2008 ozone NAAQS in downwind states and
quantification of emission budgets (i.e., limits on emissions). The analysis is described in
Sections VII and VIII of the preamble to the rule. This TSD also broadly describes how the EPA
used historical data and the Integrated Planning Model (IPM) to inform air quality modeling,
budget setting, and policy analysis aspects of this rule. This TSD is organized as follows:
A. Background on EPA's Analysis to Quantify Emissions that Significantly Contribute to
Nonattainment or Interfere with Maintenance of the 2008 Ozone NAAQS
B. Using Engineering Analytics and Integrated Planning Model (IPM) to Assess Air Quality
Modeling, EGU NOx Mitigation Strategies, and Policy Impacts
C. Calculating Budgets from Historical Data and IPM Analysis
1. Calculating 2021-2025 engineering baseline for NOx (from adjusted historical data)
2. Estimating impacts of combustion and post combustion controls on state emission budgets
3. Estimating emission reduction potential from generation shifting
4. Variability limits and RIA scenarios
D. Analysis of Air Quality Responses to Emission Changes Using an Ozone Air Quality
Assessment Tool (AQAT)
1. Introduction: development of the ozone AQAT
2. Details on the construction of the ozone AQAT
3. Description of analytical results
4. Comparison between the air quality assessment tool estimates
E. Observations on Cost and Air Quality Factors for 2024
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A. Background on EPA's Analysis to Quantify Emissions that Significantly Contribute to
Nonattainment or Interfere with Maintenance of the 2008 Ozone NAAQS
In the preamble, EPA describes the 4-Step Good Neighbor Framework that it is applying
to identify upwind states' emissions that significantly contribute to nonattainment or interfere
with maintenance with respect to the 2008 ozone National Ambient Air Quality Standard
(NAAQS) in other states and to implement appropriate emission reductions. This framework was
used in the original CSAPR rulemaking to address interstate transport with respect to the 1997
ozone NAAQS and the 1997 and 2006 PM2.5 NAAQS and was also used in the 2016 CSAPR
Update to address interstate transport with respect to the 2008 ozone NAAQS.
The first step of the Good Neighbor Framework uses air quality analysis to identify
nonattainment and maintenance receptors for the 2008 ozone NAAQS. The second step of the
framework uses further air quality analysis to identify upwind states whose ozone pollution
contributions to these monitoring sites meet or exceed a specified threshold and therefore merit
further analysis. See section VI of the preamble for details on applying these steps with respect
to interstate emissions transport for the 2008 ozone NAAQS.
The third step in the Good Neighbor Framework quantifies upwind state emissions that
significantly contribute to nonattainment or interfere with maintenance of the 2008 ozone
NAAQS at the downwind receptors, and identifies the electricity generating unit (EGU) NOx
emission budgets and/or non-EGU emissions reduction for each state that represent the reduction
of these emissions levels. See section VII of the preamble with respect to interstate emissions
transport for the 2008 ozone NAAQS. Finally, the fourth step of the Good Neighbor Framework
implements the emission budgets in each state through the CSAPR NOx ozone season allowance
trading program or other enforceable mechanism. See section VIII of the preamble for details on
proposed implementation for this rule.
This TSD primarily addresses step three of the Good Neighbor Framework related to
EGU emissions as well as to the effects on air quality of both EGU and non-EGU emissions
reductions. In order to establish EGU NOx emissions budgets for each linked upwind state, EPA
first identifies various possible uniform levels of NOx control stringency based on available
EGU NOx control strategies and represented by cost thresholds.1 The EGU emission reductions
pertaining to each level of control stringency are derived using historical data and EPA's
integrated planning model (IPM) for the power sector as described in sections B and C of this
TSD. The adjusted historical data and the model data are combined in order to quantify a series
of potential EGU NOx emission budgets for each linked upwind state at each level of uniform
NOx control stringency. A similar assessment for one scenario was done for non-EGUs. Next,
EPA uses the ozone Air Quality Assessment Tool (AQAT) to estimate the air quality impacts of
the upwind state emissions reductions on downwind ozone pollution levels for each of the
assessed cost threshold levels. Specifically, EPA looks at the magnitude of air quality
improvement at each receptor at each level of control, it examines whether receptors change
status (shifting from either nonattainment to maintenance, or from maintenance to attainment),
and looks at the individual contributions of each state to each of its receptors. See section D in
this TSD for discussion of the development and use of the ozone AQAT.
Finally, the EPA uses this air quality information within the multi-factor test, along with
NOx reduction potential and cost, to select a particular level of uniform NOx control stringency
1 See the EGU NOx Mitigation Strategies Proposed Rule TSD
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that addresses each state's significant contribution to nonattainment and interference with
maintenance (see Section VII of the preamble for additional information).
In this TSD, EPA assesses the EGU NOx mitigation potential for all states in the
contiguous U.S. EPA assessed the air quality impacts for all monitors in the contiguous U.S.
from emission reductions. In applying the multi-factor test for purposes of identifying the
appropriate level of control, the EPA evaluated NOx reductions and air quality improvements at
the four receptors from the two home states and the 12 upwind states that were linked to
downwind receptors in step two of the 4-Step Good Neighbor Framework. The 12 upwind
linked states are listed in Table A-l below.
Table A-l. Upwind States Evaluated in the Multi-factor Test
Ozone Season NOx
Illinois
New Jersey
Indiana
New York
Kentucky
Ohio
Louisiana
Pennsylvania
Maryland
Virginia
Michigan
West Virginia
B. Using the Engineering Analytics Tool and the Integrated Planning Model (IPM) to
Assess Air Quality Modeling, EGU NOx Mitigation Strategies, and Policy Impacts
Similar to the final CSAPR Update, EPA relied on adjusted historical data (engineering
analytics) and its power sector modeling platform using IPM as part of the process to quantify
significant contribution at step three within the 4-Step Good Neighbor Framework. Historical
data were adjusted through the engineering analytics tool and used along with IPM to analyze the
ozone season NOx emission reductions available from EGUs at various uniform levels of NOx
control stringency, represented by cost per ton, in each upwind state. Finally, IPM was used to
evaluate compliance with the rule and the rule's regulatory control alternatives (i.e., compliance
with the emission budgets, with a more stringent alternative, and with a less stringent
alternative). EPA also used its engineering analytics tool and IPM projections to perform air
quality assessment for steps 1 and 2.
The engineering analytics tool uses the latest emissions and operating data reported under
40 CFR part 75 by covered units (which were 2019 ozone-season data at the time of this
analysis). It is a tool that builds estimates of future unit-level and state-level emissions based on
exogenous changes to historical heat input and emissions data reflecting fleet changes known to
occur subsequent to the last year of available data. See Section C. Calculating Budgets from
Historical Data and IPM Analysis for a detailed description of the engineering analytics tool.
IPM is a multiregional, dynamic, deterministic linear programming model of the U.S.
electric power sector that EPA uses to analyze cost and emissions impacts of environmental
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policies.2 All IPM cases for this rule included representation of the Title IV SO2 cap and trade
program; the NOx SIP Call; the CSAPR and CSAPR Update regional cap and trade programs;
consent decrees and settlements; and state and federal rules as listed in the IPM documentation
referenced above.
Application of the 4-Step Good Neighbor Framework requires robust data collection,
IPM modeling and engineering analytics is time consuming. Rather than freezing all IPM data
sets at the outset of EPA's analysis for the proposed rule, the EPA allowed for ongoing
improvement of the relied-upon EGU data. As a result, each step of EPA's analysis for the
proposed rule is informed by the best available data at the time the analysis was conducted.
In the power sector modeling done for this rule, the EPA needed to quantify emissions for
three different analytic purposes. The first purpose was to provide future base case EGU
emissions for input to air quality modeling to identify nonattainment and maintenance receptors
and quantify interstate contribution to inform steps 1 and 2 of the 4-Step Good Neighbor
Framework. This base case incorporated the most important fleet changes and retrofits identified
through comments up to Fall of 2019 using the National Electricity Energy Data System
(NEEDS) EGU inventory, January 8, 2020 version. The version of the NEEDS file reflects EGU
fleet updates through November 2019.3
The second purpose was to construct an illustrative base case and control case to study
the potential cost and reduction potential of different uniform technology scenarios. This set of
cases is referred to as the "Illustrative Cases." These illustrative cases are primarily cost
threshold runs that EPA performed where the agency would first adjust the base case to reflect
the relevant control technologies being considered and would then perform a sensitivity where a
dollar per ton price constraint (e.g., $1,600 per ton) was applied to that adjusted base case to
estimate the additional reductions to be expected from generation shifting at a dollar per ton level
commensurate with the technology cost.
The third purpose was to estimate system impacts of the proposed rule and confirm the
impact of implementing the state emissions budgets in a region-wide trading program. This set of
cases is referred to as the "Final Cases." For the Final Cases, the EPA applied the state emission
budgets and corresponding state and regional caps to the same base case used in the illustrative
cases. EPA also performed a "less stringent" and "more stringent" control scenario policy case
using lower and higher state emission budgets respectively. The "Final Cases" were used to
inform the cost and benefits of this rulemaking, as described in the Regulatory Impact Analysis,
or RIA, for this rule.
Table B-l below summarizes the various IPM runs conducted and Appendix C provides
further details on each of these scenarios.
2 See "Documentation for EPA's Power Sector Modeling Platform v6 using January 2020 Reference Case".
Available at https://www.epa.gov/airmarkets/epas-power-sector-modeling-platform-v6-using-ipm-january-2020-
reference-case.
3 https://www.epa.gov/airmarkets/national-electric-energy-data-system-needs-v6
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Table B-l. Summary of Sets of Scenarios.
Air Quality Modeling
Base Case
Illustrative Cases
Final Cases
Scenarios Run
Base Case (IPM)
Base Case (IPM)
Base Case (Engineering
Analytics)
Uniform Control/Cost
Threshold (IPM and
Engineering Analytics)
Policy Cases (IPM)
What Analysis Each
Set of Runs Informs
Base Case air quality
modeling to identify
nonattainment and
maintenance receptors
and estimate upwind
contributions (steps 1
and 2)
Development of a set of
state emission budgets
for each cost threshold
(step 3)
RIA analysis to
gauge system impacts
when budgets are
implemented through
a trading program
(step 4)
EGU Updates
Captured in Each Set
of Runs
Updates as of
November 2019
Updates as of lune 30,
2020
Updates as of lune
30,2020
For the "Illustrative Case" IPM runs, the EPA modeled the emissions that would occur
within each state in a Base Case. The EPA then designed a series of IPM runs that imposed
increasing cost thresholds representing uniform levels of NOx controls and tabulated those
projected emissions for each state at each cost level. The EPA has referred to these runs as "Cost
Threshold Runs" and these tabulations, when combined with adjusted historical data, as "cost
curves."4 The cost curves report the remaining emissions at each cost threshold after the state
has made emission reductions that are available up to the particular cost threshold analyzed.
In each Cost Threshold run, the EPA applied the applicable ozone-season cost level to all
fossil-fuel-fired EGUs with a capacity greater than 25 MW in all states, though only the
estimates for the four receptors, the two "home states", and the 12 linked states affect the results
in Step 3. As described in the EGU NOx Mitigation Strategies TSD, because of the time required
to build advanced pollution controls, the model was prevented from building any new post-
4 These projected state level emissions and heat input for each "cost threshold" run are presented in several formats.
The IPM analysis outputs available in the docket contain a "state emissions" file for each analysis. The file contains
two worksheets. The first is titled "all units" and shows aggregate emissions for all units in the state. The second is
titled "all fossil > 25MW" and shows emissions for a subset of these units that have a capacity greater than 25 MW.
The 2021 emissions and heat input in the "all fossil > 25 MW" worksheet is used to derive the generation shifting
component of the state emission budgets for each upwind state at the cost thresholds.
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combustion controls, such as SCR or SNCR, before 2025, in response to the cost thresholds.5
Similarly, the model was not enabled to build incremental new units in that time frame. In
response to the ozone-season NOx cost, the modeling allows turning on idled existing SCR and
SNCR, optimization of existing SCR, shifting generation to lower-NOx emitting EGUs, and
adding or upgrading NOx combustion controls (such as state-of-the-art low NOx burners (LNB))
in 2021/2022.
In these scenarios, EPA imposed cost thresholds of $500, $1,600, $3,900, $5,800, $9,600
per ton of ozone season NOx. See Preamble Section VII for a discussion of how the cost
thresholds were determined. Table B-2 below summarizes the reduction measures that are
broadly available at various cost thresholds.
Table B-2. Reduction strategies available to EGUs at each cost threshold.
Cost Threshold ($ per
ton Ozone-Season NOx)
Reduction Options
$500
-Generation shifting
$1,600
-Above option; and
-Retrofitting state-of-the-art combustion controls;
-Optimizing idled SCRs (to 0.08 lb/MMBtu);
-Optimizing operating SCRs (to 0.08 lb/MMBtu);
$3,900
-Above options; and
-Optimizing SNCRs
$5,800
-Above options; and
-Installing SNCR on certain coal units lacking post-
combustion retrofit
$9,600
-Same as $3,900/ton options; and
-Installing SCR on certain coal units lacking SCR post-
combustion controls
For both Engineering analytics and IPM:
At $500/ton:
o Engineering Analytics - no change.
o IPM - cost of $500 per ton applied to base case for EGUs > 25 MW.
At $l,600/ton:
o Engineering Analytics - If 2019 adjusted baseline rate was greater than 0.08
lb/MMBtu for SCR controlled units, that rate and corresponding emissions were
adjusted down to 0.08 lb/MMBtu starting in 2021; for units with LNB upgrade
potential and an adjusted historical rate greater than 0.1549 lb/MMBtu, their rates
were adjusted downwards to 0.1549 lb/MMBtu (for dry bottom wall-fired boilers)
or 0.1390 lb/MMBtu (for tangentially fired boilers) starting in 2022.
5 IPM results do include certain newly built post-combustion NOx control retrofits in base case modeling, cost
curve runs, and remedy runs. These pre-2020 retrofits do not reflect any controls installed in response to the rule,
but instead represent those that are already announced and/or under construction and expected to be online by 2021,
or controls that were projected to be built in the base case in response to existing consent decree or state rule
requirements.
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o IPM - cost of $1,600 per ton applied for EGUs > 25 MW; Units with existing
SCRs have their emission rates lowered to the lower of their mode 4 NOx rate in
NEEDS and the "widely achievable" optimized emissions rate of 0.08
lbs/MMBtu. 6
At $3,900/ton:
o Engineering Analytics - Same as $l,600/ton; additionally, units with SNCRs
were given their mode 2 NOx rates if they were not already operating at that level
or better in 2019.
o IPM - Same as $l,600/ton; additionally, units with idled SNCRs were identified
as units equipped with SNCR and mode 2 NOx rates in NEEDS greater than 0.30
lbs/MMBtu. These units were given NOx rates 25% lower to reflect SNCR
operation. In most cases the unit was already operating below 0.30 lb/MMBtu, in
which case it was given its mode 2 rate reflecting SNCR operation. Cost of
$3,900 per ton applied for EGUs > 25 MW.
At $5,800/ton:
o Engineering Analytics - Same as $3,900/ton; additionally, coal units greater than
100 MW and lacking a post-combustion control were given a 25% reduction to
adjusted historical baseline emissions starting in 2024 to reflect SNCR
installation.7
o IPM - Same as $3,900/ton; additionally, coal units greater than 100 MW and
lacking a post combustion control were given a 25% reduction from their mode 2
rate reflecting SNCR installation, starting in model run year 2025.8 Cost of
$5,800 per ton applied for EGUs > 25 MW.
At $9,600/ton:
o Engineering Analytics - Same as $3,900/ton; additionally, coal units greater than
100 MW and lacking a SCR were given an emission rate equal to the greater of a
reduction of 90% or 0.07 lb/MMBtu reflecting SCR installation starting in 2024.
o IPM - Same as $3,900/ton; additionally, coal units greater than 100 MW and
lacking SCR were assigned a mode four emission rate of 0.07 lb/MMBtu
reflecting SCR installation starting in model run year 2025. Cost of $9,600 per ton
applied for EGUs > 25 MW.
As described in preamble section VII, the EPA limited its assessment of generation
shifting to reflect shifting only to other EGUs within the same state as a proxy for generation
6 The mode 4 NOx rate, as described in Chapter 3 of the Documentation for EPA Base Case v.6 Using Integrated
Planning Model, represents post-combustion controls operating and state-of-the-art combustion controls, where
applicable. For units determined to be operating their SCR, the rate is typically equal to the unit's rate reported in
previous year ETS data. For units not operating their SCRs, the mode 4 rate is calculated as described in Attachment
3-1 of the Documentation for EPA Base Case v.6 Using Integrated Planning Model available at
https://www.epa.gov/airmarkets/ipm-v6-power-system-operation-assumptions-attachment-3-l-nox-rate-
development-epa.
7 As described in preamble section VII. C, EPA does not believe these controls to be available on a regional scale
until 2025. However, the EPA shows their impact from 2024 onwards in its engineering analysis. For its IPM
analysis, there is no model run year for 2024, so 2025 is the first year for which they can be assumed.
8 EPA's Power Sector Model v.6 using IPM does not have a 2024 model run year.
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shifting that could occur for the 2021 ozone season. EPA did this by limiting state generation in
each Cost Threshold run to not go below the level in its respective Base Case. EPA also limited
the potential for any new build in response to the price signal in the near term as it was interested
in capturing generation shifting among the existing fleet.
Section C.l-3 of this TSD describes how state emissions budgets were calculated using a
combination of historical data and data from the IPM cost threshold cases. Once these budgets
were calculated, EPA used the budgets for covered states to conduct IPM Final Cases to
investigate the impact of compliance with the budgets calculated from the $500, $1,600, $9,600
per ton cases. These cases reflect a less stringent scenario, the proposed scenario, and a more
stringent scenario. Specifically, the budgets informed by the Illustrative $1,600 per ton Cost
Threshold case were used for the proposed policy scenario, and the budgets informed by the
Illustrative $500 and $9,600 per ton cost threshold cases informed the less and more stringent
scenarios. These scenarios were used to inform the RIA.
To model these scenarios in IPM, EPA used the calculated state emissions budget and
assurance levels (121% of the state emission budget) to set state and regional ozone-season NOx
emissions limits. Additionally, EPA assumed a starting bank of allowances equal to 21% of the
sum of the 12 states' budgets. States could individually emit up to their assurance levels in each
run year, and collectively could not have emissions exceeding the sum of their regional budget
and banked allowances in each run year. In the proposed scenario and the more stringent
scenario, units with existing operating SCRs were assumed to operate them at the lower of their
mode 4 NOx rate in NEEDS and the "widely achievable" emissions rate of 0.08 lb/MMBtu, as
EPA determined this was a cost-effective mitigation strategy. Additionally, for these same two
scenarios, coal units were assumed to upgrade to state-of-the-art combustion controls if they did
not already have them. In the more stringent scenario, coal units greater than 100 MW without an
SCR were assumed to retrofit with a new SCR and achieve an emission rate of 0.07 lb/MMBtu.
While the EPA conservatively limited generation shifting in developing the budgets, through use
of state-level generation constraints, the EPA believes that generation shifting may occur broadly
among states as a compliance mechanism and so removed that constraint for the IPM Final Cases
reflecting program implementation.
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C. Calculating Budgets from Historical Data and IPM Analysis
As described in Section VIII.B of the preamble, similar to CSAPR Update, the EPA
determined it was appropriate to calculate budgets by combining historical emissions and heat
input data with projections from IPM to derive state emission budgets. Section VIII.B notes there
are three primary steps in this process: 1) EPA determines a future year baseline using historical
data, 2) EPA adjusts that baseline to reflect the combustion and post-combustion control
mitigation measures deemed cost-effective at a given cost threshold, and 3) EPA factors in
emission reduction potential from generation shifting at a cost threshold commensurate with that
mitigation technology's control operation cost. Similar to CSAPR Update, in this proposal the
EPA calculated state budgets with the following formula:
2021 State OS NOx Budget =
2021 State OS Baseline Heat Input *[2021 State OS NOx Emissions Rate
(2021 IPM Base Case OS NOx Emissions Rate 2021 IPM Cost Threshold OS NOx Emissions
Rate)]9
The first two variables in the equation are derived from historical data and are the primary
determinants of states' emissions budgets. They are described in the first two sections below.
The last two variables are identified through IPM analysis and described in section C.3 below.10
In section C.4, EPA discusses variability limits and RIA scenarios.
1. Calculating 2021-2025 Engineering Baseline for NOx (from adjusted historical data)
The underlying data and calculations described below can be found in the workbook titled
(Appendix A - State Emission Budget Calculations and Engineering Analytics). They are also
available in the docket and on the EPA website.
EPA starts with 2019 reported, seasonal, historical NOx emissions and heat input data for each
unit.11 This reflects the latest owner/operator reported data available at the time of EPA analysis.
The NOx emissions data for units that report data to EPA under the Acid Rain Program (ARP),
the Cross-State Air Pollution Rule (CSAPR) and CSAPR Update Rule are aggregated to the
summer/ozone season period (May-September). Because the unit-level NOx emissions for the
summer/ozone-season period are relevant to determining ozone-season emissions budgets, those
files are shown in the "unit 2021" through "unit 2025" sheets in the "Appendix A: State
Emission Budget Calculations and Engineering Analytics" file accompanying this document.12
In that file, unit-level details such as facility name, unit ID, unit type, capacity, etc. are shown in
columns A through H of the "unit 2021" through "unit 2025" worksheets. Reported historical
data for these units such as historical emissions, heat input, generation, etc. are shown in
9 The year in the formula changes for each year of budget calculation.
10 Given the proximity of the first implementation year to the analytics for this rulemaking and its promulgation,
EPA determined the use of this budget setting approach provided the most precision and expediency for this
rulemaking.
11 "Seasonal" refers to the ozone-season program months of May through September.
12 The EPA notes that historical unit-level ozone season EGU NOx emission rates are publicly available and quality
assured data. The data are monitored using continuous emissions monitors (CEMs) or other monitoring approaches
available to qualifying units under 40 CFR part 75 and are reported to the EPA directly by power sector sources.
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columns I through L. The 2019 historical emissions value in column I. The assumed future year
baseline emissions estimate (e.g., 2021-2025) is shown in column U, and reflects either the same
emissions level as that observed in 2019, or a modification of that value based on changes
expected to the operational or pollution control status of that unit.13 These modifications are
made due to:
a. Retirements - Emissions from units with upcoming confirmed retirement dates prior
to that designated year are adjusted to zero. Retirement dates are identified through a
combination of sources including EIA Form 860, utility-announced retirements,
stakeholder feedback provided to EPA, and the National Electricity Energy Data
System (NEEDS) June 2020 file. The impact of retirements on emissions is shown in
column M. The retiring units are flaggec
in column N.
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
0 MMBtu x .2 lb/MMBtu = 0 ton
b. Coal to Gas Conversion - Emissions from coal units with scheduled conversions to
natural gas fuel use by the designated future year are adjusted to reflect reduced
emission rates associated with natural gas. To reflect a given unit's conversion to gas,
that unit's future emission rates for NOx are assumed to be half of its 2019 coal-fired
emission rates while utilization levels are assumed to remain the same.14 Therefore,
the future year estimated emissions for these converting units are expected to be half
of 2019 levels for NOx. Units expected to convert to gas are flagged using EIA Form
860, NEEDS June 2020, and stakeholder feedback. The impact of coal to gas
conversion for the future year is shown in column Q, flagged in column R. The
example below pertains to NOx emission estimates.
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .1 lb/MMBtu = .5 ton
c. Retrofits - Emissions from units with scheduled SCR or SNCR retrofits are adjusted
to reflect the emission rates expected with new SCR installation (0.075 lb/MMBtu of
NOx) and new SNCR (a 25% decrease in emission rate) and are assumed to operate
at the same 2019 utilization levels.15 These emission rates were multiplied by the
affected unit's 2019 heat input to estimate the future year emission level. The impact
of post-combustion control retrofits on future year emissions assumptions is shown in
column S, flagged in column T.
For SNCR:
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .15 lb/MMBtu = .75 ton
For SCR:
13 Based on data and changes known as of 6/30/2020.
14 This is consistent with NOx rate change used in IPM. See "Documentation for EPA Base Case v.5.13 Using the
Integrated Planning Model.", table 5-21.
15 Ibid.
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2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 Ib/MMBtu = 1 ton
10,000 MMBtu x .075 Ib/MMBtu = .375 ton
d. Other - EPA also made several unit-specific adjustments to 2019 emission levels to
reflect forthcoming emission or emission rate requirements specified in consent
decrees, BART requirements, and/or other revised permit limits. The impacts for
future year emission assumptions are shown in column U, flagged in column V.
e. New Units - Emissions for new units are identified in the "New units" worksheet.
They reflect under-construction and/or permitted units greater than 25 MW that are
expected to be in commercial operation by the designated future year. These assumed
emission values for new units are reflected in column F and the online years are in
column H. To obtain these emissions, EPA identified all new fossil-fired EGUs
coming online after 2019 according to EIA Form 860 and in NEEDSv.6 June 2020.
EPA then identified the heat rate and capacity values for these units using EIA Form
860, NEEDSv.6 June 2020 and stakeholder-provided data. Next, EPA identified the
2019 average seasonal capacity factor for similar units that came online between
2015-2019. EPA used these seasonal capacity factors (e.g., 65% for NGCC), the
unit's capacity, the unit's heat rate, and the unit's estimated NOx rate to estimate
future year emissions (capacity x capacity factor x number of hours in ozone season
x heat rate * NOx emission rate = NOx emissions).
2019
Future Year (e.g., 2021)
Unit x
0 MMBtu x .0 Ib/MMBtu = 0 ton
100 MW * .65 *(153x24) *8000 Btu/KWh *.01
Ib/MMBtu = 9 tons
After completing these steps, EPA has unit-level and state-level future year baselines that
originate from the most recently reported data (2019) and incorporate known EGU fleet changes.
The state-level file reflects a summation of the unit-level values and provides the state-level heat
input value used as the first variable in the emissions budget formula below. It also provides the
starting value for the second variable (i.e., showing the future year baseline emission rate) before
any mitigation technologies (i.e., higher $ per ton levels) beyond the baseline are incorporated.16
.2021 State OS-N£bJBmlgyt -^
<|021 State OS Baseline HeatJnpJ.it <^021 State 05 NOx Emissions~Ra£^
(2u2i IPM daseCase OS NOx Emissions naze 202IIPM Cost Threshold OS NOx Emissions
Rate)]
2. Estimating impacts of combustion and post combustion controls on state emission budgets
16 While less relevant to emission budgets setting, EPA also created a future year baseline for 1) NOx and SO2
emission from EGUs not currently covered under existing EPA programs that require emissions monitoring and
reporting under 40 CFR part 75, and for other pollutants for all grid connected EGUs (e.g., PM2 5, P.M10, CO).
These data points were used in some of the air quality analysis and in some of the system impacts estimates for the
RIA. The EPA also evaluates whether the assumed aggregate heat input changes given retirements and new builds
are consistent with trends observed historically in the fleet and with new planned units identified in EIA Form 860.
This evaluation is in the appendix to this document.
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Next, EPA evaluates the impact of the different combustion and post-combustion controls and
establishes the impact on the state OS NOx Emission rate to complete the second variable in the
equation above. Similar to the methodology above, EPA continued to adjust the historical data to
reflect a future year with specific uniform control assumptions. However, these adjustments
were to capture changes incremental to the baseline reflecting different uniform control
measures. EPA applied these adjustments for analytical purposes to all states, but only the 12
linked states' adjustments are relevant for emission budgets proposed in this rule. Each of these
adjustments is shown incrementally for the relevant mitigation technology in the "unit 2021"
through "unit 2025" worksheets.
a. SCR optimization ($1,600 per ton)- Emissions from units with existing SCRs, but that
operated at an emission rate greater than 0.08 lb/MMBtu in 2019, were adjusted
downwards to reflect expected emissions when the SCR is operated to achieve a 0.08
lb/MMBtu emission rate. The 0.08 lb/MMBtu emission rate was identified as the
emission rate that reflected the fleet-average optimization assumption for SCR controlled
units that were not currently optimizing their controls. The optimized emission rate is
multiplied by baseline heat input levels to arrive at the future year emissions estimate.
The impact on future year emission assumptions is shown in column W and flagged in
column X of the "unit 2021" through "unit 2025" worksheets. EPA notes this assumption
only applies to ozone-season NOx as that is the season in which the proposed Revised
CSAPR Update Rule would likely incentivize such operation.
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .08 lb/MMBtu = .4 ton
b. State-of-the- art combustion controls ($1,600per ton) - Emissions from units that were
operating in 2019 without state-of-the-art combustion controls were adjusted downwards
to reflect assumed installation of, or upgrade to, these controls and their expected
emission rate impact. EPA assumed a future year emission rate of 0.1549 lbs/MMBtu for
units with dry bottom wall-fired boilers expected to install/upgrade combustion controls,
and 0.1390 lbs/MMBtu for tangentially fired units expected to install/upgrade
combustion controls. These emission rates were multiplied by each unit's future year
baseline heat input to estimate its future emission level. Details of EPA's assessment of
state-of-the-art NOx combustion controls and corresponding emission rates are provided
in the EGU NOx Mitigation Strategies Proposed Rule TSD. The impact of state-of-the-
art combustion controls on future year emission assumptions is shown in column Y and
flagged in column Z of the "unit 2021" through "unit 2025" worksheets. Note - these
assumptions apply to both winter and ozone season emissions adjustments as the controls
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x ,139lb/MMBtu = 7 ton
c. SNCR optimization ($3,900 per ton)- Emissions from units with existing SNCRs, but that
operated at an emission rate greater than the SNCR optimization rate, were adjusted
downwards to reflect expected emissions when the SNCR is optimized. This emission
rate was identified specific to each unit based on historical data and is described in the
NOx Mitigation Strategy TSD. The optimized emission rate is multiplied by future year
13
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baseline heat input levels to arrive at the future year emissions estimate. For the units
affected by this adjustment, the impact on future year emission assumptions is shown in
column AA and flagged in column AB of the "unit 2021" through "unit 2025"
worksheets. Note, this assumption only applies to ozone-season NOx as that is the season
in which the proposed Revised CSAPR Update Rule would likely incentivize such
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .15 lb/MMBtu = .75 ton
d. SNCR retrofit ($5,800per ton) - Emissions from coal units greater than 100 MW without
post-combustion controls were adjusted downwards to reflect expected emissions if an
SNCR were to be retrofitted on the unit. The emission rate was identified as 75% of the
unit's baseline emission rate level (i.e., reflecting a 25% reduction from the technology).
The adjusted emission rate is multiplied by future year baseline heat input levels to arrive
at the future year emissions estimate for that technology. For the units affected by this
adjustment, the impact on future year emission assumptions is shown in column AC and
flagged in column AD of the "unit 2021" through "unit 2025" worksheets. Note, this
assumption only applies to ozone-season NOx as that is the season in which the proposed
Revised CSAPR Update Rule would likely incentivize such installation and operation.
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .15 lb/MMBtu = .75 ton
e. SCR retrofit ($9,600 per ton)- Emissions from coal units greater than 100 MW without
SCR controls were adjusted downwards to reflect expected emissions if an SCR were to
be retrofitted on the unit. The emission rate was identified as 10% of the unit's baseline
emission rate or 0.07 lb/MMBtu (i.e., a 90% reduction with an emission rate floor of 0.07
lb/MMBtu).17 The adjusted emission rate is multiplied by future year baseline heat input
levels to arrive at the future year emissions estimate for that technology. For the units
affected by this adjustment, the impact on future year emission assumptions is shown in
column AE and flagged in column AF of the "unit 2021" through "unit 2025"
worksheets. Note, this assumption only applies to ozone-season NOx as that is the period
in which the proposed Revised CSAPR Update Rule would likely incentivize such
2019
Future Year (e.g., 2021)
Unit x
10,000 MMBtu x .2 lb/MMBtu = 1 ton
10,000 MMBtu x .07lb/MMBtu = .35 ton
These adjustments for each uniform control technology (reflected by a $ per ton marginal cost)
resulted in adjusted OS NOx emissions, heat input, and emission rates at the unit-level. When
summed up to the state level, these changes resulted in the State OS NOx Emission Rate listed
second in the formula below. EPA notes, this emission rate for any given uniform control level
times the baseline heat input would provide the state emissions budget without generation
17 This is a conservative estimate based on the floor rates for new SCRs in the IPM documentation, ranging from
0.05 to 0.07 lbs/mmBtu, depending on coal type. See "Documentation for EPA Base Case v.5.13 Using the
Integrated Planning Model," table 5-5.
14
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shifting. These pre-generation shifting emission budget levels at the state-level are visible in the
worksheets titled "State 2021" through "State 2025" in the Appendix A: Budget Emission Budget
Calculations and Engineering Analytics workbook accompanying this document.
State 2021 OS NOx Budget =
2021 State OS Baseline Heat Input H2Q21 State OS NOx Emissions Rc
(2021 IPM Base Case OS NOx Emissions Rate 2021 IPM Cost Threshold OS NOx Emissions
Rate)]
3. Estimating Emission Reduction Potential from Generation Shifting
The last two variables in the equation relate to emission reductions from generation shifting.
Here, as in the CSAPR Update, EPA uses the Integrated Planning Model (IPM) to capture the
change in emission rate in a state's fossil-fuel fired power fleet when. While holding everything
else equal, EPA applies a given $ per ton marginal cost constraint. EPA relies on IPM for this
analysis as generation shifting occurs on a cost continuum and is a function of least-cost dispatch
under different constraints. To derive this value, EPA first prepares an adjusted base case that
reflects all the combustion or post-combustion mitigation measures discussed above for a given
cost threshold. These adjusted base cases are specific to the uniform mitigation scenario. For
instance, for the $1,600 per ton scenario EPA adjusts its base case to reflect the optimization of
SCRs and combustion control upgrades by adjusting the emission rates to the levels discussed
above for relevant units not already achieving that level. EPA then executes an IPM run with
these new exogenous assumptions and observes the state-level emission rate for fossil-fuel fired
units greater than 25 MW. This is the third variable in the emissions budget formula.
Next, EPA performs a sensitivity for these adjusted base case runs where it applies the same set
of assumptions in variable three, but layers on a commensurate marginal cost price signal (e.g.,
$1,600 per ton). In addition to the mitigation measures assumed, the entire fossil-fuel fired EGU
fleet greater than 25 MW in the state is subjected to a cost-per-ton price associated with that
technology. The model solves for least-cost dispatch given this additional marginal cost
constraints for seasonal ozone emissions. EPA observes the state-level emission rate for fossil-
fuel fired units greater than 25 MW. This data point becomes the fourth variable in the state-
emissions budget formula. The difference between the third and fourth variables reflects the
change in emission rate due solely to generation shifting at a given $ per ton level.
State 2021 OS NOx Budget =
2021 State OS Baseline Heat Input *[2021 State OS NOx Emissions Rate
-(2t>21 IPM Base case OS NOx Emissions Rate 2021 IPM Cost Threshold UIj NOx Limssiou
Rate)]1N ________
This difference in the state-level emission rate between the two IPM cases is shown in columns
N through Q in the worksheet titled "State 2021", columns L through N for worksheets titled
"State 2022 " and "State 2023", columns P through T for "State 2024" and "State 2025". These
values are in the Appendix A: State Emission Budget Calculations and Engineering Analytics
workbook accompanying this document.
18 The year in the formula changes for each year of budget calculation.
15
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Once EPA calculated the change in emissions rate between the IPM adjusted base case
and each cost threshold case, the EPA then subtracted this change in emissions rate from the
state OS NOx emission rate without generation shifting (the second variable in the formula).
This yielded state-level, historically-anchored, emission rates reflecting NOx reduction potential
for a given uniform control measure.
Finally, the EPA multiplied these rates by each state's adjusted heat input (historical heat
input adjusted for retirements and new builds identified in variable one of the formula) to yield
emission budgets for each cost threshold. The state budgets for the different cost thresholds are
displayed in Table C-l through C-5. EPA notes that budgets are calculated for all states for the
purpose of AQAT analysis, as explained in section D of this TSD, even if the state is not covered
by the proposed Revised CSAPR Update Rule.
In addition to being shown below, the state-level emission budgets are calculated in the
far right-hand side columns of each "State" worksheet for each $ per ton technology available
that year. These budgets reflect an application of the formula described above to the data in the
spreadsheet. The underlying formulas are imbedded in each cell and reference the appropriate
data point previously listed in the spreadsheet. These state-emission budgets reflect the inclusion
of generation shifting. The difference between these proposed state-emission budgets shown in
the far right columns titled "state emissions budgets with generation shifting" columns and the
"state emission budgets without generation shifting" columns reflect the additional reduction due
to generation shifting at a given cost threshold.
Generation shifting accounts for a small amount of emissions reductions relative to the
combustion and post combustion control mitigation measures (see Table C-10). In its cost
threshold modeling, EPA limited generation levels in a state to its base case level so that states
would not achieve emission reductions by importing more generation from out-of-state EGUs
and reducing in-state generation (e.g., emissions leakage). This assumption ensures that the
generation shifting-based reductions are, and can be achieved, within a state. EPA also only
assumes generation shifting from the projected baseline fleet, it does not incorporate generation
shifting from any assumed incremental new build capacity that could be incentivized by a price
level. Finally, in EPA's budget setting process it only includes generation shifting at $ per ton
levels that encourage the optimization of existing or newly installed controls considered at that
cost level. Capturing reduction potential from generation shifting in the state's emission budgets
is meant to preserve the incentive for combustion and post combustion controls to operate.
Factoring generation shifting into the state emissions budgets helps promote an allowance price
commensurate with these levels. In this rule, generation shifting is intended to be a mitigation
measure supportive to those combustion and post-combustion control measures, not incremental
to it. Therefore, EPA designed its IPM analysis and utilized the results for emission budget
purposes in a manner that did not allow for, or include, emission reductions from projected
model new builds or retirements that occurred in response to a $ per ton price signal.19 Instead,
EPA examined generation shifting that was expected to occur among the baseline fleet at cost
19 EPA also relied on the modeled emission rate change in the IPM 2021 results for each year of the budget
calculation to avoid capturing generation shifting attributable to model-projected new builds in later years that are
not yet under construction.
16
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threshold levels commensurate with post-combustion control operation (i.e., $1,600 per ton or
$3,900 per ton) at fossil fuel-fired units greater than 25 MW for 2021.20
20 As explained in preamble Section VII.B. 1, EPA does not believe regional post-combustion control installation
(represented by higher cost thresholds of $5800/ton and $9600/ton) is possible prior to 2025, and thus not relevant
for consideration in this action as there are no non-attainment or maintenance receptors in 2025 after reductions
available at $1600/ton are implemented. However, for illustrative purposes, EPA assessed reductions at these levels
as well. For the higher cost thresholds of $5,800/ton and $9,600/ton pertaining to the later years of analysis (2024
and 2025), EPA used the generation shifting emission rate delta consistent with the cost of operating those controls
(e.g., $3900/ton) to ensure that all controls (existing and new) would have an incentive to operate if installed. EPA
also performed a feasibility check on its generation shifting assumptions to assess whether such generation shifting
would still be likely once those assumed controls were installed. If the state's assumed emission rate reductions
from generation shifting were greater than 10% of the IPM baseline, and its adjusted historical baseline for that year
was less than 90% of the IPM baseline, then no additional reductions were assumed from generation shifting at
higher cost thresholds of $5,800 and $9,600 in EPA's 2024 analysis. While this last assessment was done for all
states, only Utah and Arizona (states which are not covered in this rulemaking) were affected.
17
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Table C-l. 2021 Emissions for States at Different Uniform Control Scenarios (Reflected by $ per
ton)
OS NOx (tons)
2021
Baseline
$500/ton
0.08 SCR
Optimization
($1,600/ton)
0.08 SCR
Optimization +
SOA ($1,600/ton)
0.08 SCR
Optimization +
SOA + SNCR
Optimization
($3,900/ton)
Alabama
7,786
7,785
7,786
7,610
7,610
Arizona
5,389
5,100
4,616
4,167
2,168
Arkansas
8,731
8,655
8,708
8,330
7,936
California
1,298
1,297
1,062
1,062
1,062
Colorado
7,484
7,487
7,471
7,448
7,149
Connecticut
344
316
307
307
305
Delaware
223
223
206
206
197
Florida
15,011
15,002
13,979
13,979
13,614
Fort Mojave
53
53
53
53
53
Georgia
7,833
7,833
7,808
7,808
7,773
Idaho
204
204
204
204
204
Illinois
9,688
9,667
9,444
9,444
9,086
Indiana
15,856
15,677
12,500
12,468
12,035
Iowa
8,567
8,447
7,714
7,626
7,041
Kansas
6,057
6,053
5,384
5,384
5,233
Kentucky
15,588
15,606
14,384
11,936
11,826
Louisiana
15,488
15,442
15,402
14,871
14,233
Maine
67
67
67
67
67
Maryland
1,565
1,565
1,522
1,498
1,340
Massachusetts
332
329
329
329
319
Michigan
13,893
13,120
12,727
11,767
11,542
Minnesota
5,961
5,836
5,450
5,450
4,766
Mississippi
8,032
8,029
8,027
7,213
6,960
Missouri
12,445
12,385
11,358
11,358
11,025
Montana
3,553
3,553
3,553
3,553
3,553
Navajo
1,319
1,319
1,319
1,319
1,319
Nebraska
8,078
8,013
8,037
7,251
7,155
Nevada
2,434
1,833
1,456
1,456
1,415
New Hampshire
386
386
299
299
299
New Jersey
1,346
1,346
1,253
1,253
1,257
New Mexico
4,656
4,624
4,502
4,502
3,854
New York
3,187
3,182
3,137
3,137
3,038
North Carolina
15,869
15,772
11,188
11,188
8,479
North Dakota
11,885
11,829
11,774
11,774
10,544
Ohio
15,832
15,490
9,605
9,605
9,482
Oklahoma
8,964
8,878
8,717
8,717
8,498
Oregon
350
350
350
350
350
Pennsylvania
11,570
11,487
8,076
8,076
7,791
Rhode Island
233
233
233
233
233
South Carolina
4,979
4,979
3,839
3,839
3,831
South Dakota
586
579
577
577
579
Tennessee
4,547
4,549
4,367
4,367
4,280
Texas
44,729
43,803
42,312
41,995
39,838
Utah
6,729
4,862
4,837
4,837
2,979
Ute
2,144
2,144
2,144
2,144
2,144
Vermont
51
51
51
51
51
Virginia
4,592
4,588
4,544
4,072
3,929
Washington
1,609
1,609
1,609
1,609
1,603
18
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West Virginia
15,165
15,017
13,686
12,813
12,446
Wisconsin
5,171
5,041
4,875
4,875
4,842
Wyoming
11,480
11,480
11,366
9,684
8,298
12 Linked States
Total
123,770
122,187
106,280
100,940
98,005
"Note - For 2021 EPA shows $1,600 ton with and without LNB upgrade; given it is proposing to not require budgets reflecting LNB
controls until 2022.
Table C-2. 2022 Emissions for States at Different Uniform Control Scenarios (Reflected by $ per
ton)
OS NOx (tons)
2022 Baseline
$500/ton
0.08 SCR Optimization
+ SOA ($1,600/ton)
0.08 SCR Optimization
+ SOA + SNCR
Optimization
($3,900/ton)
Alabama
7,786
7,785
7,610
7,610
Arizona
5,389
5,100
4,167
2,168
Arkansas
8,731
8,655
8,330
7,936
California
1,290
1,290
1,054
1,054
Colorado
7,484
7,487
7,448
7,149
Connecticut
341
313
304
302
Delaware
220
220
203
194
Florida
15,011
15,002
13,979
13,614
Fort Mojave
53
53
53
53
Georgia
7,833
7,833
7,808
7,773
Idaho
204
204
204
204
Illinois
9,652
9,632
9,415
9,057
Indiana
15,383
15,206
11,998
11,570
Iowa
8,567
8,447
7,626
7,041
Kansas
6,057
6,053
5,384
5,233
Kentucky
15,588
15,606
11,936
11,826
Louisiana
15,488
15,442
14,871
14,233
Maine
67
67
67
67
Maryland
1,565
1,565
1,498
1,340
Massachusetts
332
329
329
319
Michigan
13,893
13,120
11,767
11,542
Minnesota
5,883
5,759
5,373
4,688
Mississippi
8,032
8,029
7,213
6,960
Missouri
12,445
12,385
11,358
11,025
Montana
3,249
3,249
3,249
3,249
Navajo
1,319
1,319
1,319
1,319
Nebraska
8,078
8,013
7,251
7,155
Nevada
2,434
1,833
1,456
1,415
New Hampshire
386
386
299
299
New Jersey
1,346
1,346
1,253
1,257
New Mexico
4,656
4,624
4,502
3,854
New York
3,187
3,182
3,137
3,038
North Carolina
15,869
15,772
11,188
8,479
North Dakota
11,885
11,829
11,774
10,544
Ohio
15,917
15,560
9,676
9,548
Oklahoma
8,964
8,878
8,717
8,498
Oregon
350
350
350
350
Pennsylvania
11,570
11,487
8,076
7,791
Rhode Island
233
233
233
233
South Carolina
4,979
4,979
3,839
3,831
19
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South Dakota
586
579
577
579
Tennessee
4,547
4,549
4,367
4,280
Texas
44,729
43,803
41,995
39,838
Utah
6,729
4,862
4,837
2,979
Ute
2,144
2,144
2,144
2,144
Vermont
51
51
51
51
Virginia
4,175
4,172
3,656
3,514
Washington
1,609
1,609
1,609
1,603
West Virginia
15,165
15,017
12,813
12,446
Wisconsin
5,171
5,041
4,875
4,842
Wyoming
10,918
10,918
9,296
7,910
12 Linked States Total
122,929
121,335
100,096
97,162
Table C-3. 2023 Emissions for States at Different Uniform Control Scenarios (Reflected by $ per
ton).
OS NOx (tons)
2023 Baseline
$500/ton
0.08 SCR Optimization
+ SOA ($1,600/ton)
0.08 SCR Optimization
+ SOA + SNCR
Optimization
($3,900/ton)
Alabama
7,786
7,785
7,610
7610
Arizona
5,389
5,100
4,167
2168
Arkansas
8,731
8,655
8,330
7936
California
1,290
1,290
1,054
1054
Colorado
6,996
6,999
6,961
6675
Connecticut
341
313
304
302
Delaware
220
220
203
194
Florida
14,221
14,212
13,272
12915
Fort Mojave
53
53
53
53
Georgia
7,833
7,833
7,808
7773
Idaho
204
204
204
204
Illinois
8,599
8,579
8,397
8054
Indiana
15,383
15,206
11,998
11570
Iowa
8,176
8,061
7,266
6706
Kansas
6,057
6,053
5,384
5233
Kentucky
15,588
15,606
11,936
11826
Louisiana
15,488
15,442
14,871
14233
Maine
67
67
67
67
Maryland
1,565
1,565
1,498
1340
Massachusetts
316
313
313
303
Michigan
11,056
10,313
9,803
9586
Minnesota
4,650
4,543
4,201
3612
Mississippi
8,032
8,029
7,213
6960
Missouri
12,165
12,106
11,079
10750
Montana
3,249
3,249
3,249
3249
Navajo
1,319
1,319
1,319
1319
Nebraska
8,078
8,013
7,251
7155
Nevada
2,320
1,730
1,361
1320
New Hampshire
386
386
299
299
New Jersey
1,346
1,346
1,253
1257
New Mexico
4,580
4,548
4,428
3790
New York
3,187
3,182
3,137
3038
North Carolina
15,869
15,772
11,188
8479
20
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North Dakota
9,166
9,128
9,091
8046
Ohio
15,917
15,560
9,676
9548
Oklahoma
8,964
8,878
8,717
8498
Oregon
350
350
350
350
Pennsylvania
11,570
11,487
8,076
7791
Rhode Island
233
233
233
233
South Carolina
4,979
4,979
3,839
3831
South Dakota
586
579
577
579
Tennessee
4,547
4,549
4,367
4280
Texas
44,539
43,614
41,807
39653
Utah
6,729
4,862
4,837
2979
Ute
2,144
2,144
2,144
2144
Vermont
51
51
51
51
Virginia
4,175
4,172
3,656
3514
Washington
1,609
1,609
1,609
1603
West Virginia
13,407
13,272
11,810
11447
Wisconsin
4,912
4,785
4,622
4590
Wyoming
10,337
10,337
8,954
7568
12 Linked States Total
117,281
115,730
96,111
93,204
Table C-4. 2024 Emissions for States at Different Uniform Control Scenarios (Reflected by $ per
OS NOx (tons)
0.08 SCR
0.08 SCR
2024
0.08 SCR
Optimization
+ SOA
0.08 SCR
Optimization +
SOA + SNCR
Optimization
Optimization +
SOA + SNCR
Optimization +
SNCR Retrofit
Optimization +
SOA + SNCR
Optimization +
SCR Retrofit
Baseline
$500/ton
($1,600/ton)
($3,900/ton)
($5,800/ton)
($9,600/ton)
Alabama
7,786
7,785
7,610
7,610
7,610
7,515
Arizona
5,389
5,100
4,167
2,168
2,168
2,168
Arkansas
8,731
8,655
8,330
7,936
6,359
4,661
California
1,290
1,290
1,054
1,054
1,054
1,054
Colorado
6,284
6,287
6,249
5,962
5,327
3,967
Connecticut
341
313
304
302
302
302
Delaware
220
220
203
194
194
194
Florida
14,133
14,124
13,184
12,827
12,475
11,782
Fort Mojave
53
53
53
53
53
53
Georgia
7,833
7,833
7,808
7,773
7,773
7,773
Idaho
204
204
204
204
204
204
Illinois
8,599
8,579
8,397
8,054
7,490
7,142
Indiana
12,755
12,603
9,447
9,090
8,782
8,264
Iowa
8,176
8,061
7,266
6,706
5,719
3,335
Kansas
6,057
6,053
5,384
5,233
4,815
3,658
Kentucky
15,588
15,606
11,936
11,826
10,501
8,852
Louisiana
15,488
15,442
14,871
14,233
13,994
12,636
Maine
67
67
67
67
67
67
Maryland
1,565
1,565
1,498
1,340
1,340
1,239
Massachusetts
316
313
313
303
303
303
Michigan
10,841
10,116
9,614
9,402
8,541
7,315
Minnesota
4,650
4,543
4,201
3,612
3,050
2,596
Mississippi
8,032
8,029
7,213
6,960
6,677
6,398
Missouri
12,165
12,106
11,079
10,750
10,750
9,306
Montana
3,249
3,249
3,249
3,249
2,445
1,544
Navajo
1,319
1,319
1,319
1,319
1,319
1,319
21
-------
Nebraska
7,371
7,307
6,909
6,814
5,627
4,060
Nevada
2,320
1,730
1,361
1,320
978
229
New Hampshire
386
386
299
299
299
299
New Jersey
1,346
1,346
1,253
1,257
1,257
1,257
New Mexico
4,580
4,548
4,428
3,790
3,790
1,816
New York
3,169
3,163
3,119
3,020
3,020
3,020
North Carolina
15,869
15,772
11,188
8,479
8,479
5,189
North Dakota
9,166
9,128
9,091
8,046
7,237
2,250
Ohio
15,917
15,560
9,676
9,548
9,548
9,126
Oklahoma
8,964
8,878
8,717
8,498
7,820
7,251
Oregon
350
350
350
350
350
350
Pennsylvania
11,570
11,487
8,076
7,791
7,648
7,578
Rhode Island
233
233
233
233
233
233
South Carolina
4,979
4,979
3,839
3,831
3,831
3,831
South Dakota
586
579
577
579
579
579
Tennessee
4,547
4,549
4,367
4,280
4,280
4,280
Texas
44,539
43,614
41,807
39,653
36,007
29,946
Utah
6,729
4,862
4,837
2,979
2,979
2,979
Ute
2,144
2,144
2,144
2,144
1,608
573
Vermont
51
51
51
51
51
51
Virginia
3,912
3,908
3,395
3,254
3,254
3,022
Washington
1,609
1,609
1,609
1,603
1,603
761
West Virginia
13,407
13,272
11,810
11,447
11,447
9,569
Wisconsin
4,383
4,261
4,104
4,073
4,073
4,073
Wyoming
10,337
10,337
8,954
7,568
6,603
3,972
12 Linked States
Total
114,157
112,647
93,092
90,262
86,822
79,020
Table C-5. 2025 Emissions for States at Different Uniform Control Scenarios (Reflected by $ per
ton).
OS NOx (tons)
2025
Baseline
$500/ton
0.08 SCR
Optimization +
SOA
($1600/ton)
0.08 SCR
Optimization +
SOA + SNCR
Optimization
($3,900/ton)
0.08 SCR
Optimization +
SOA + SNCR
Optimization +
SNCR Retrofit
($5,800/ton)
0.08 SCR
Optimization +
SOA + SNCR
Optimization +
SCR Retrofit
($9,600/ton)
Alabama
7,786
7,785
7,610
7,610
7,610
7,515
Arizona
5,389
5,100
4,167
2,168
2,168
2,168
Arkansas
8,731
8,655
8,330
7,936
6,359
4,661
California
1,290
1,290
1,054
1,054
1,054
1,054
Colorado
6,284
6,287
6,249
5,962
5,327
3,967
Connecticut
341
313
304
302
302
302
Delaware
220
220
203
194
194
194
Florida
13,566
13,557
12,618
12,263
11,911
11,218
Fort Mojave
53
53
53
53
53
53
Georgia
7,833
7,833
7,808
7,773
7,773
7,773
Idaho
204
204
204
204
204
204
Illinois
8,478
8,459
8,277
7,938
7,374
7,025
Indiana
12,755
12,603
9,447
9,090
8,782
8,264
Iowa
8,176
8,061
7,266
6,706
5,719
3,335
Kansas
6,057
6,053
5,384
5,233
4,815
3,658
Kentucky
15,588
15,606
11,936
11,826
10,501
8,852
Louisiana
15,488
15,442
14,871
14,233
13,994
12,636
Maine
67
67
67
67
67
67
Maryland
1,565
1,565
1,498
1,340
1,340
1,239
22
-------
Massachusetts
316
313
313
303
303
303
Michigan
10,841
10,116
9,614
9,402
8,541
7,315
Minnesota
4,650
4,543
4,201
3,612
3,050
2,596
Mississippi
8,032
8,029
7,213
6,960
6,677
6,398
Missouri
12,165
12,106
11,079
10,750
10,750
9,306
Montana
3,249
3,249
3,249
3,249
2,445
1,544
Navajo
1,319
1,319
1,319
1,319
1,319
1,319
Nebraska
7,347
7,283
6,885
6,791
5,603
4,036
Nevada
2,320
1,730
1,361
1,320
978
229
New Hampshire
386
386
299
299
299
299
New Jersey
1,346
1,346
1,253
1,257
1,257
1,257
New Mexico
4,580
4,548
4,428
3,790
3,790
1,816
New York
3,169
3,163
3,119
3,020
3,020
3,020
North Carolina
15,451
15,355
10,780
8,121
8,121
5,109
North Dakota
9,166
9,128
9,091
8,046
7,237
2,250
Ohio
15,917
15,560
9,676
9,548
9,548
9,126
Oklahoma
8,964
8,878
8,717
8,498
7,820
7,251
Oregon
350
350
350
350
350
350
Pennsylvania
11,570
11,487
8,076
7,791
7,648
7,578
Rhode Island
233
233
233
233
233
233
South Carolina
4,979
4,979
3,839
3,831
3,831
3,831
South Dakota
586
579
577
579
579
579
Tennessee
3,953
3,954
3,907
3,826
3,826
3,826
Texas
44,398
43,475
41,670
39,518
35,872
29,811
Utah
6,729
4,862
4,837
2,979
2,979
2,979
Ute
2,144
2,144
2,144
2,144
1,608
573
Vermont
51
51
51
51
51
51
Virginia
3,912
3,908
3,395
3,254
3,254
3,022
Washington
1,609
1,609
1,609
1,603
1,603
761
West Virginia
13,407
13,272
11,810
11,447
11,447
9,569
Wisconsin
4,383
4,261
4,104
4,073
4,073
4,073
Wyoming
10,337
10,337
8,954
7,568
6,603
3,972
12 Linked States Total
114,036
112,527
92,972
90,146
86,706
78,903
As noted in Section VII of the Preamble, EPA identified $1,600 per ton as the point for
determining significant contribution from EGUs under the Step 3 multifactor test. Section VIII
explains that EPA applied this cost threshold to each year through 2024 to arrive at a budget
estimate for that year. Those state-level emissions budgets for the 12 states along with the
corresponding percent reduction relative to 2019 and the state's baseline emissions for that year
are shown below in Tables C-6 through C-10.21
Table C-6 - OS NOx, 2021 Emissions Budget, and % Reduction
2016 OS
NOx
2019 OS
NOx
Baseline
2021 OS
NOx
2021
Budget
%
Reduction
from 2019
% Reduction
from 2021
Baseline
Illinois
14,553
11,871
9,688
9,444
20%
3%
Indiana
34,636
16,594
15,856
12,500
25%
21%
Kentucky
25,403
19,117
15,588
14,384
25%
8%
Louisiana
19,615
15,365
15,488
15,402
0%
1%
21 An expanded table providing state emission budgets for these 12 linked states and a potential emission budget for
additional Group 1 or Group 2 state wishing to switch to the Group 3 program is provided in Appendix G
23
-------
Maryland
4,471
1,662
1,565
1,522
8%
3%
Michigan
17,632
14,055
13,893
12,727
9%
8%
New Jersey
2,463
1,346
1,346
1,253
1%
7%
New York
6,534
3,224
3,187
3,137
3%
2%
Ohio
24,205
16,390
15,832
9,605
41%
39%
Pennsylvania
31,896
12,093
11,570
8,076
33%
30%
Virginia
9,833
4,668
4,592
4,544
3%
1%
West Virginia
21,178
15,615
15,165
13,686
12%
10%
Total
212,418
132,000
123,770
106,280
19%
14.1%
Table C-7. OS NOx, 2022 Emissions Budget, and % Reduction
2016
2019
Baseline
%
% Reduction
OS
OS
2022 OS
2022
Reduction
from 2022
NOx
NOx
NOx
Budget
from 2019
Baseline
Illinois
14,553
11,871
9,652
9,415
21%
2%
Indiana
34,636
16,594
15,383
11,998
28%
22%
Kentucky
25,403
19,117
15,588
11,936
38%
23%
Louisiana
19,615
15,365
15,488
14,871
3%
4%
Maryland
4,471
1,662
1,565
1,498
10%
4%
Michigan
17,632
14,055
13,893
11,767
16%
15%
New Jersey
2,463
1,346
1,346
1,253
7%
7%
New York
6,534
3,224
3,187
3,137
3%
2%
Ohio
24,205
16,390
15,917
9,676
41%
39%
Pennsylvania
31,896
12,093
11,570
8,076
33%
30%
Virginia
9,833
4,668
4,175
3,656
22%
12%
West Virginia
21,178
15,615
15,165
12,813
18%
16%
Total
212,418
132,000
122,929
100,096
24%
18.6%
Table C-8. OS NOx, 2023 Emissions Budget, and
% Reduction
2016
2019
Baseline
%
% Reduction
OS
OS
2023 OS
2023
Reduction
from 2023
NOx
NOx
NOx
Budget
from 2019
Baseline
Illinois
14,553
11,871
8,599
8,397
29%
2%
Indiana
34,636
16,594
15,383
11,998
28%
22%
Kentucky
25,403
19,117
15,588
11,936
38%
23%
Louisiana
19,615
15,365
15,488
14,871
3%
4%
Maryland
4,471
1,662
1,565
1,498
10%
4%
Michigan
17,632
14,055
11,056
9,803
30%
11%
New Jersey
2,463
1,346
1,346
1,253
7%
7%
New York
6,534
3,224
3,187
3,137
3%
2%
Ohio
24,205
16,390
15,917
9,676
41%
39%
24
-------
Pennsylvania
31,896
12,093
11,570
8,076
33%
30%
Virginia
9,833
4,668
4,175
3,656
22%
12%
West Virginia
21,178
15,615
13,407
11,810
24%
12%
Total
212,418
132,000
117,280
96,111
27%
18.1%
Table C-9. OS NOx, 2024 Onward: Emissions Budget, anc
% Reduction
2016
OS
NOx
2019
OS
NOx
Baseline
2024 OS
NOx
2024
Budget
%
Reduction
from 2019
% Reduction
from 2024
Baseline
Illinois
14,553
11,871
8,599
8,397
29%
2%
Indiana
34,636
16,594
12,755
9,447
43%
26%
Kentucky
25,403
19,117
15,588
11,936
38%
23%
Louisiana
19,615
15,365
15,488
14,871
3%
4%
Maryland
4,471
1,662
1,565
1,498
10%
4%
Michigan
17,632
14,055
10,841
9,614
32%
11%
New Jersey
2,463
1,346
1,346
1,253
7%
7%
New York
6,534
3,224
3,169
3,119
3%
2%
Ohio
24,205
16,390
15,917
9,676
41%
39%
Pennsylvania
31,896
12,093
11,570
8,076
33%
30%
Virginia
9,833
4,668
3,912
3,395
27%
13%
West Virginia
21,178
15,615
13,407
11,810
24%
12%
Total
212,418
132,000
114,156
93,092
29%
18.5%
Table C-10. Emission Reduction Attributable to Generation Shifting (for 12 linked states).
Baseline
OS NOx
Budget
Without
Gen
Shifting
Budget
With
Gen.
Shifting
% Reduction from
Generation Shifting as a
Percentage of Baseline
2021
123,770
108,745
106,280
2%
2022
122,929
102,571
100,096
2%
2023
117,280
98,529
96,111
2%
2024
114,156
95,437
93,092
2%
4. Variability Limits and RIA Scenarios
Once EPA determined state-emission budgets, EPA calculated the variability limits and
assurance levels for each state based on the calculated emission budgets. Each state's variability
limit is 21% of its budget, and its assurance level is the sum of its budget and variability limit (or
121% of its budget). The variability limits and assurance levels are further described and shown
in section VIII of the preamble for the proposed Revised CSAPR Update and shown in Table
Appendix G-l.
25
-------
As explained in the preamble, the EPA is proposing EGU NOx ozone season emission
budgets reflecting the uniform cost threshold of $1,600 per ton to eliminate significant
contribution to nonattainment and interference with maintenance.
For the RIA analysis, EPA used the budgets informed by the $1,600 per ton cost
threshold scenario. Additionally, the RIA includes analysis of the less stringent policy option,
using the budgets from a $500 per ton cost threshold case, and a more stringent policy
alternative, using 2025 budgets from the $9,600 per ton cost threshold case reflecting SCR
retrofits at coal units greater than 100 MW lacking such controls.
The IPM runs performed for this analysis are listed in Appendix C of this TSD. Table
Appendix C-l lists the name of each IPM run next to a description of the run. The output files of
these model runs can be found in the rulemaking docket. Detailed budget calculations for all
cost per ton cases can be found in Appendix A - State Emission Budget Calculations and
Engineering Analytics.
26
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D. Analysis of Air Quality Responses to Emission Changes Using an Ozone Air Quality
Assessment Tool (AQAT)
EPA has defined each linked upwind state's significant contribution to nonattainment and
interference with maintenance of downwind air quality using a multi-factor test (described in the
preamble at section VII in step three of the 4-Step Good Neighbor Framework) which is based
on cost, emissions, and air quality factors. A key quantitative input for determining the amount
of each state's emission reduction obligation is the predicted downwind ambient air quality
impacts of upwind EGU emission reductions under the budgets at various levels of NOx
emission control and under a scenario of potential upwind non-EGU emissions reductions. See
section C of this TSD for information regarding EGUs and see preamble section VII for
information about non-EGUs. The emission reductions from the various cost thresholds can
potentially result in air quality improvements such that individual receptors drop below the level
of the NAAQS based on the cumulative air quality improvement from the upwind states, or
potentially decrease each upwind state's contributions such that they possibly drop below the 1%
linkage threshold (used in step two of the Good Neighbor Framework to identify the states for
further analysis).
Air quality modeling would be the optimal way to examine these questions at each cost
threshold level from EGUs and non-EGUs. However, due to time and resource limitations EPA
was unable to use full air quality modeling for all but a few emissions scenarios. Therefore, in
order to estimate the air quality impacts for the various levels of emission reductions and to
ensure that each step of its analysis is informed by the evolving emissions data, EPA used a
simplified air quality assessment tool (AQAT).22 The simplified tool allows the Agency to
analyze many more NOx emission budget levels than would otherwise be possible. EPA
recognizes that AQAT is not the equivalent of photochemical air quality modeling. However,
AQAT is directly informed by air quality modeling data. Further, AQAT has evolved through
iterative development under the original CSAPR and the CSAPR Update. One such evolution is
its calibration of the change in air quality based on air quality modeling of a particular emission
reduction scenario. EPA examined various cost threshold scenarios for the year 2024 using two
different calibration factors as a mechanism to estimate the range of results.
The inputs and outputs of the tool can be found in the "Ozone AQAT Proposal.xlsx"
excel workbook.
The remainder of section D of this document will:
Present an introduction and overview of the ozone AQAT;
Describe the construction of the ozone AQAT; and
Provide the results of the NOx emission cost threshold analyses.
1. Introduction: Development of the ozone AQAT
The ozone AQAT was developed for use in the rule's step three air quality analysis as
part of the multi-factor test. Specifically, the AQAT was designed to evaluate air quality
22 EPA used CAMx to model several base cases (i.e., one of 2016, one of 2023, and one of 2028). The EPA
calculated air quality contributions for each state for both the 2023 and 2028 cases. EPA did not explicitly model
2021.
27
-------
changes in response to emissions changes in order to quantify necessary emission reductions
under the good neighbor provision and to evaluate potential budgets for over-control as to either
the 1% threshold or the downwind receptor status. EPA described and used a similar tool in the
original CSAPR to evaluate good neighbor obligations with respect to the fine particulate matter
(PM2.5) NAAQS and in the CSAPR Update to evaluate good neighbor obligations with respect to
ozone. For the CSAPR Update, EPA refined both the construction and application of the
assessment tool for use in estimating changes in ozone concentrations in response to changes in
NOx emissions. We followed the methodology developed in the CSAPR Update rulemaking
where we calibrate the response of a pollutant using two CAMx simulations at different emission
levels.23'24
A critical factor in the assessment tool is the establishment of a relationship between
ozone season NOx emission reductions and reductions in ozone. Within AQAT, we assume that
the reduction of a ton of emissions of NOx from the upwind state results in a particular level of
improvement in air quality downwind.25 For the purposes of developing and using an
assessment tool to compare the air quality impacts of NOx emission reductions under various
emission cost threshold emission levels, we determine the relationship between changes in
emissions and changes in ozone contributions on a receptor-by-receptor basis. Specifically, EPA
assumed that, within the range of total NOx emissions being considered (as defined by the cost
threshold emission levels), a change in ozone season NOx emissions leads to a proportional
change in downwind ozone contributions.26 This proportional relationship was then modified
using calibration factors created using the 2023 base case contribution air quality modeling and
either the 2016 base case (for cases between 2016 and 2023) or the 2028 base case (for cases
from 2023 to 2028) to account for the majority of the nonlinearity between emissions and ozone
concentrations. For example, for a particular receptor in 2022, we could assume that a 20%
decrease in the upwind state's emissions leads to a 20% decrease in its downwind ozone
contribution in the "uncalibrated" ozone AQAT, while following the application of the
23 In CSAPR, we estimated changes in sulfate using changes in SO2 emissions.
24 In this rule, as was the case for the CSAPR Update, we used CAMx to calibrate the assessment tool's predicted
change in ozone concentrations to changes in NOx emissions. This calibration is receptor-specific and is based on
the changes in NOx emissions and resulting ozone concentrations between the 2023 base case and either the 2016
base case or the 2028 base case. One of these two calibration points (either 2016 or 2028) was used to create site-
specific calibration factors so that the response of ozone concentrations to upwind NOx emission changes would
more closely align with ozone estimates from CAMx. For time periods before 2023, we used the 2016 calibration
point, for 2023 and later, we used the 2028 calibration point.
25 This downwind air quality improvement is assumed to be indifferent to the source sector or the location of the
particular emission source within the state where the ton was reduced. For example, reducing one ton of NOx
emissions from the power sector is assumed to have the same downwind ozone reduction as reducing one ton of
NOx emissions from the mobile source sector.
26The relationship between NOx emissions and ozone concentrations is known to be non-linear when examined over
large ranges of NOx emissions (e.g., J.H. Seinfeld and S.N. Pandis, Atmospheric Chemistry and Physics From Air
Pollution to Climate Change, 2nd Edition, John Wiley and Sons, 2006, Hoboken, NJ, pp 236-237). However, for
smaller ranges of NOx and VOC emissions, while meteorological conditions are held constant, the relationship may
be reasonably linear. The nonlinearities are evident over tens of ppb of ozone changes with tens of percent changes
in the overall emission inventories. For most states examined here, under the various control scenarios, most
changes in the emission inventory are on the order of a few percent and most air quality changes are on the order of
a fraction of a ppb. In this assessment tool, we are assuming a linear relationship between NOx emissions and ozone
concentrations calibrated between two CAMx simulations. A significant portion of the nonlinearity is accounted for
by using the calibration factor and having the air quality estimates occur at levels of emissions between the 2023
base case and the other base case used in the calibration (which were both modeled in CAMx).
28
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calibration factor (based on the change to 2016) it may only decrease by 10% decrease in
"calibrated" AQAT (where the calibration factor is 0.5). Typically, the calibration factors were
substantially less than one, often on the order of 0.3 (thus, a 10% decrease in emissions would
result in a 3% decrease in ozone concentration). The creation of the calibration factors is
described in detail in section D.2.c (1) of this TSD.
In summary, because the tool is only being used over a range for which a calibration
factor has been developed, and because other options such as using CAMx to model all scenarios
is cost and time-prohibitive, EPA used ozone AQAT to estimate the downwind ozone reductions
due to upwind NOx emission reductions for the air quality input to the multi-factor test for this
rule. Other options, such as directly scaling the results (i.e., an "uncalibrated ozone AQAT")
will likely greatly overestimate the air quality impacts of emission reductions.
Section D.2, below, is a technical explanation of the construction of the ozone AQAT.
Readers who prefer to access the results of the analysis using the ozone AQAT are directed to
section D.3.
2. Details on the construction of the ozone AQAT
(a) Overview of the ozone AQAT
This section describes the step-by-step development process for the ozone AQAT. All
the input and output data can be found in the Excel worksheets described in Appendix B. In the
ozone AQAT, EPA links state-by-state NOx emission reductions (derived from the non-EGU
assessment and/or the IPM EGU modeling combined with the EGU engineering assessment)
with CAMx modeled ozone contributions in order to predict ozone concentrations at different
levels of emission levels at monitoring sites. The reduction in ozone contributions at each cost
threshold level and the resulting air quality improvement at monitoring sites with projected
nonattainment and/or maintenance problems were then considered in a multi-factor test for
identifying the level of emissions reductions that define significant contribution to nonattainment
and interference with maintenance.
In applying AQAT to analyze air quality improvements at a given receptor for the cost
threshold scenarios, emissions were reduced in only those upwind states that were "linked" to
that receptor in step 2 of the Good Neighbor Framework (i.e., those states that contributed an air
quality impact at or above 1 percent of the NAAQS). Emissions were also reduced in the state
that contained that receptor (regardless of the level of that state's contribution) at a level of
control stringency consistent with the budget level applied in upwind states.
Specifically, the key estimates from the ozone AQAT for each receptor are:
The ozone contribution as a function of emissions at each cost threshold level, for
each upwind state that is contributing above the 1 percent air quality threshold and the
state containing the receptor.
The ozone contribution under base case NOx emissions in the various years, for each
upwind state that is not above the 1 percent air quality threshold for that receptor.
29
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The non-anthropogenic (i.e., background, boundary, biogenic, and wildfire) ozone
concentrations. These are assumed to be constant and equal to the contributions from
the 2023 base case source apportionment modeling.
The results of the ozone AQAT analysis for each emission cost threshold level for EGUs and
non-EGUs can be found in section D.3 of this document.
(b) Data used to construct the ozone AQAT for this rule
Several air quality modeling and emissions inventory sources were used to construct the
calibrated ozone AQAT for this rule. Using the calibration factors, EPA modulated the 2023
CAMx ozone season contributions for each upwind state to each downwind receptor. These
modulations were enough to adjust the concentrations to represent a different year (i.e., 2021).
In all cases, the starting point was the 2023 base case CAMx run with contributions. For each
scenario, EPA multiplied each state's percent change in emissions relative to the 2023 base case
ozone season NOx emission inventories from all source sectors used in the source apportionment
CAMx air quality modeling (this includes all anthropogenic sources and excludes biogenic
sources and wildfires) by the receptor-specific calibration factor and the state's base case
contribution. Note that the 2023 scenario in CAMx used IPM emission estimates. The base case
emission inventories for the 2023 base case and the 2016 and 2028 base cases are discussed in
the Air Quality Modeling TSD. The ozone season NOx EGU and non-EGU emissions for each
emission scenario including the base case as modeled in AQAT are described in section C of this
TSD.
As described in the Air Quality Modeling TSD, the air quality contributions and
emissions were modeled for all states in the contiguous United States and the District of
Columbia. Thus, in the ozone AQAT, any emission differences between the 2023 air quality
modeling base case and the scenario would result in changes in air quality contributions and
ozone concentrations at the downwind monitors.
(c) Detailed outline of the process for constructing and utilizing the ozone AQAT
The ozone AQAT was created and used in a multi-step process. First, a calibrated ozone
AQAT was created using the contributions and emission inventory from the 2023 base case air
quality modeling as well as the 2016 base case (for all scenarios with years greater than or equal
to 2023, the calibrated AQAT used the design values and emission inventory from the 2028 base
case). For each emissions cost threshold scenario evaluated, for each state, EPA identified the
percent change in anthropogenic NOx emissions relative to the 2023 base case and multiplied
this by the receptor-specific calibration factor as well as by the state- and receptor-specific
contribution. This resulted in a state- and receptor-specific "change in contribution" relative to
the 2023 base case. Each state's change in contribution value was then added to (or subtracted
from) its 2023 base case contribution and the results summed for all states for each receptor. To
this total of each state's contribution to each receptor, the receptor-specific base case
contributions from the other source-categories were added (modified if necessary in the same
way if necessary to adjust to a different year), resulting in an estimated design value for each
30
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receptor.27 The calibrated ozone AQAT was used to project the ozone concentrations for each
NOx emission budget level on a receptor-by-receptor basis for every monitor throughout the
domain.
In order to facilitate understanding of the calibration process, EPA describes below a
demonstrative example: monitor number 090019003 in Fairfield County, Connecticut, with a
2023 base case projected ozone average design value of 76.9 parts per billion (ppb) and
maximum design value of 77.2 ppb.
(1) Create the calibration factors
The process for creating the calibration factors remains unchanged from the method used
in the CSAPR Update. To create the calibration factors, EPA used emissions, contributions, and
design values from the 2023 CAMx run that used IPM for emissions, and the emissions and
design values from either the 2016 or 2028 CAMx base cases. All changes in emissions and air
quality are relative to the proposed 2023 CAMx base case.
First, EPA used ozone season state-level 2023 base case total NOx emissions from all
source sectors. This emissions data is divided into multiple source sectors for the purposes of air
quality modeling: airports, beis, cmv_clc2_12, cmv_c3_12, nonpt, nonroad, np oilgas, onroad,
pt oilgas, ptagfire, ptegu, ptfire, ptnonipm, rail, rwc (see the Preparation of Emissions
Inventories for 2016vl North American Emissions Modeling Platform TSD for additional details
on the emissions inventories used in the CAMx air quality modeling). The anthropogenic state-
level total NOx emissions used in the air quality contribution modeling are the sum of emissions
from all these source sectors except (beis, ptagfire, and ptfire). Next, EPA summed the ozone
season total anthropogenic NOx emissions across all relevant source sectors for both the 2016
and 2028 base cases. EPA calculated the ratio of the emissions for each of these two base cases
to the total emissions for the 2023 base case for each state modeled in CAMx. More information
on the emissions inventories can be found in the preamble to the proposed rule. The total
emissions data and resulting ratios can be found in Table D-l and in the ozone AQAT worksheet
"calib_emiss".
For each monitor, the "uncalibrated" change in concentration was found by multiplying
each state's 2023 base case ozone air quality contribution by the difference in the state's ratio of
emissions. The difference in the ratio of emissions was calculated as the difference in total
ozone season anthropogenic NOx emissions between the either the 2016 base case (or the 2028
base case) and the 2023 base case scenario divided by the 2023 base case emission. Thus, when
the 2016 or 2028 base case had smaller emissions than the 2023 base case, the net result was a
negative number. Each state's fractional change in emissions was multiplied by its 2023 base
case contribution to get a state- specific change in contribution (Table D-l). For each monitor,
the change in concentrations was summed across all states. The result was the total
"uncalibrated" change in concentration.
27 Details on procedures for calculating average and maximum design values can be found in the Air Quality
Modeling TSD.
31
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Table D-l. The 2023,2016, and 2028 Base Cases Total Anthropogenic NOx Emissions with 2023 Ozone
Contributions (ppb) and Uncalibrated Contributions for 2016 and 2023 for the Westport Monitor Number
090019003 in Fairfield County, Connecticut.
Fraction of 2016
Fraction of 2028
Uncalibrated
Uncalibrated
2023 Base
2016 Base
2028 Base
Base Case
Base Case
2023 Base
Change in
Change in
Uncalibrated
Uncalibrated
State
Case NOx
Case NOx
Case NOx
Emissions to 2023
Emissions to
Case Ozone
AQ
AQ
Contribution
Contribution
Emissions
Emissions
Emissions
Base Case
Emissions
2023 Base Case
Emissions
Contributions
Contribution
for 2016
Contribution
for 2028
2016
2028
AL
67,839
101,168
60,574
0.491
-0.107
0.113
0.056
-0.012
0.169
0.101
AZ
45,043
70,225
37,041
0.559
-0.178
0.016
0.009
-0.003
0.025
0.013
AR
46,552
68,756
40,093
0.477
-0.139
0.176
0.084
-0.024
0.259
0.151
CA
145,157
212,134
133,619
0.461
-0.079
0.035
0.016
-0.003
0.051
0.032
CO
61,473
86,684
55,852
0.410
-0.091
0.065
0.027
-0.006
0.091
0.059
CT
12,724
18,874
11,227
0.483
-0.118
2.682
1.296
-0.316
3.979
2.367
DE
6,985
10,193
6,274
0.459
-0.102
0.425
0.195
-0.043
0.620
0.382
DC
1,610
2,338
1,348
0.453
-0.163
0.041
0.019
-0.007
0.060
0.035
FL
114,045
186,866
99,721
0.639
-0.126
0.075
0.048
-0.009
0.123
0.065
GA
73,702
115,451
65,044
0.566
-0.117
0.165
0.093
-0.019
0.258
0.146
ID
19,924
29,416
16,389
0.476
-0.177
0.028
0.013
-0.005
0.041
0.023
IL
103,625
143,831
93,027
0.388
-0.102
0.798
0.310
-0.082
1.107
0.716
IN
82,323
129,702
73,428
0.576
-0.108
1.239
0.713
-0.134
1.952
1.105
IA
48,818
67,053
41,876
0.374
-0.142
0.169
0.063
-0.024
0.232
0.145
KS
69,568
91,022
61,361
0.308
-0.118
0.129
0.040
-0.015
0.168
0.114
KY
51,946
88,409
45,953
0.702
-0.115
0.854
0.599
-0.098
1.453
0.755
LA
105,245
138,804
98,692
0.319
-0.062
0.266
0.085
-0.017
0.351
0.250
ME
13,132
19,133
11,619
0.457
-0.115
0.007
0.003
-0.001
0.010
0.006
MD
27,785
43,974
24,694
0.583
-0.111
1.181
0.688
-0.131
1.869
1.050
MA
33,006
45,621
29,957
0.382
-0.092
0.079
0.030
-0.007
0.110
0.072
MI
87,686
118,418
81,141
0.350
-0.075
1.678
0.588
-0.125
2.266
1.553
MN
63,293
89,970
53,343
0.421
-0.157
0.188
0.079
-0.030
0.267
0.159
MS
33,963
56,364
30,491
0.660
-0.102
0.101
0.067
-0.010
0.168
0.091
MO
74,595
116,616
63,863
0.563
-0.144
0.356
0.200
-0.051
0.556
0.305
MT
28,901
40,605
24,884
0.405
-0.139
0.075
0.030
-0.010
0.105
0.064
NE
43,475
59,121
37,771
0.360
-0.131
0.076
0.028
-0.010
0.104
0.066
NV
19,070
30,601
15,844
0.605
-0.169
0.012
0.007
-0.002
0.020
0.010
NH
7,763
11,753
6,806
0.514
-0.123
0.018
0.009
-0.002
0.028
0.016
NJ
37,738
58,456
33,624
0.549
-0.109
8.446
4.637
-0.921
13.083
7.525
NM
53,165
70,102
47,356
0.319
-0.109
0.038
0.012
-0.004
0.051
0.034
NY
77,766
106,248
69,004
0.366
-0.113
14.141
5.179
-1.593
19.320
12.547
NC
76,448
101,378
64,646
0.326
-0.154
0.548
0.179
-0.085
0.727
0.464
ND
46,471
58,914
41,774
0.268
-0.101
0.080
0.021
-0.008
0.101
0.071
OH
98,579
141,543
87,637
0.436
-0.111
2.506
1.092
-0.278
3.598
2.228
OK
101,105
120,286
92,941
0.190
-0.081
0.195
0.037
-0.016
0.233
0.180
OR
31,443
46,235
26,228
0.470
-0.166
0.028
0.013
-0.005
0.041
0.023
PA
112,449
160,648
100,275
0.429
-0.108
6.723
2.882
-0.728
9.604
5.995
RI
4,742
6,994
4,106
0.475
-0.134
0.010
0.005
-0.001
0.015
0.009
SC
46,385
67,218
40,781
0.449
-0.121
0.177
0.079
-0.021
0.256
0.155
SD
13,753
21,784
10,688
0.584
-0.223
0.047
0.028
-0.011
0.075
0.037
TN
57,191
89,762
50,022
0.569
-0.125
0.318
0.181
-0.040
0.499
0.278
TX
314,342
418,972
288,147
0.333
-0.083
0.582
0.194
-0.049
0.776
0.534
UT
35,868
53,661
31,932
0.496
-0.110
0.033
0.016
-0.004
0.049
0.029
VT
4,047
6,078
3,340
0.502
-0.175
0.014
0.007
-0.002
0.021
0.011
VA
57,856
93,453
51,398
0.615
-0.112
1.273
0.783
-0.142
2.057
1.131
WA
58,962
89,605
49,093
0.520
-0.167
0.055
0.028
-0.009
0.083
0.046
wv
53,854
61,692
52,047
0.146
-0.034
1.459
0.212
-0.049
1.671
1.410
WI
48,283
75,140
41,731
0.556
-0.136
0.229
0.127
-0.031
0.357
0.198
WY
41,098
53,908
36,966
0.312
-0.101
0.078
0.024
-0.008
0.103
0.070
TRIBAL
5,858
17,759
5,875
2.032
0.003
0.004
0.009
0.000
0.013
0.004
CAN MEX
0
0
2.52895
0
0
2.52895
2.52895
OFFSHORE
0
0
0.67413
0
0
0.67413
0.67413
FIRE
0
0
0.34482
0
0
0.34482
0.34482
ICBC
0
0
20.63261
0
0
20.63261
20.63261
BIOG
0
0
4.68736
0
0
4.68736
4.68736
32
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Next, the estimate of the monitor specific ozone responses under the 2016 or 2028 base
cases was used to calibrate the ozone AQAT to CAMx and to derive the calibration factors. One
factor was created using the 2016 base and is applied to all scenarios from 2016 to 2023, the
other factor was created using the 2028 base and is applied to all scenarios from 2023 to 2028.
First, the changes in ozone predicted by the ozone AQAT and CAMx for the average design
values were calculated for each monitor for the 2016 or 2028 base case relative to the 2023 base
case concentrations. The change in ozone predicted by CAMx was then divided by the change in
ozone predicted by the uncalibrated AQAT, resulting in a monitor-specific calibration factor (see
Table D-2 for an example calculation using the 2016 and 2028 base cases). The calculation of
these monitor-specific calibration factors provided EPA with the ability to align the ozone
response predicted by the ozone AQAT to the ozone response predicted by CAMx.
The ozone AQAT and CAMx concentration differences can be found in the "Ozone
AQATProposal.xlsx" excel workbook in columns BK and BL, respectively, on worksheets
"calib_2016" and "calib_2028". The resulting calibration factors can be found in column BM of
the aforementioned excel worksheets. The calibration factor, multiplied by the fractional change
in emissions (relative to the 2023) base and multiplied by the 2023 base air quality contribution,
results in the fractional change in air quality contribution for any alternative scenario.
Table D-2. Design Values in the 2023 Base Case and the 2016 and 2028 Base Cases and
Estimated Change in Design Value Relative to the 2023 Base Case from CAMx and
Uncalibrated AQAT for the Westport Monitor Number 090019003 in Fairfield County,
Connecticut.
2023 Base
Case
Concentration
(PPb)
2016 Base
Case
Concentration
(PPb)
2028 Base
Case
Concentration
(PPb)
Change in
Concentration
from 2016 to
2023
(PPb)
Change in
Concentration
from 2028 to
2023
(PPb)
CAMx
76.90
82.70
74.30
5.80
-2.60
Uncalibrated AQAT
76.90
98.04
71.70
21.14
-5.20
Calibration Factor -
Change in
Concentration from
CAMx Divided by
Change in
Concentration from the
Uncalibrated AQAT
0.2743
0.4998
(2) Create a calibrated version of the ozone AQAT for emission budget analysis for the proposed
rule
Next, EPA used 2023 base case emissions and 2023 base case air quality ozone
contributions from the air quality modeling along with either the 2016-based or 2028-based
calibration factors to create a "calibrated" AQAT specific to the year being assessed. EPA
examined the changes in the 2023 air quality contributions from changes in emissions relative to
33
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the 2023 base case emissions (while using the calibration factor). This calibrated AQAT was
then used to estimate the change in predicted ozone due to NOx emission reductions under each
emission cost threshold level evaluated for EGUs and non-EGUs in each year.
First, as described in section VII of the preamble and above in section C of this TSD for
EGUs, EPA identified various cost threshold levels of emissions based on projected changes in
emissions rates and adjusted historical data. For each state, for each year, the total anthropogenic
NOx emissions (excluding the EGU emissions) are presented in Table D-3. These "straight line"
emissions inventories were created by linearly interpolating the emissions for all anthropogenic
source sectors except EGUs between 2023 and 2016 (or between 2023 and 2028).
The EGU point inventory is composed of emissions from units that report emissions to
EPA's Clean Air Markets Division (CAMD) under 40 CFR Part 75 (most emissions from these
sources are measured by continuous emission monitoring systems (CEMS)) and units that are
typically included in EPA's power sector modeling using the Integrated Planning Model (IPM)
but that do not report to CAMD and typically lack CEMS (i.e., the nonCEM units). Within the
air quality modeling platform, different approaches are taken depending on whether an emissions
inventory for EGUs is created using an IPM-based emission estimates or an engineering analysis
based platform. The nonCEM components for various air quality model platforms are shown in
Table D-4. For each year, based on the available air quality modeling runs available (in 2016,
2023, and 2028) an engineering-based nonCEM point EGU component was created (Table D-5).
For the years from 2016 through 2023, this was a straight line linear interpolation of the 2016
and 2023 nonCEM component from the engineering based air quality runs. For years 2023
through 2028, we used 2023 nonCEM values held constant for all years. The component of the
EGU point inventory from CAMD reporting units (labelled "CEMs") was developed using
engineering analysis (see section C for details). For each year, we show EGU emissions for
units with CEMs as a function of cost threshold level (see Tables C-l through C-5 for the years
2021 through 2025, respectively). These levels include:
Engineering Baseline,
$500/ton,
Optimize SCR,
Optimize SCR + State of the Art Combustion Controls (SOA CC),
Optimize SNCR+ SCR + SOA CC ,
New SNCR + Optimize SNCR+ SCR + SOA CC
New SCR + Optimize SNCR+ SCR + SOA CC.
In the construction of AQAT, for each scenario, we assembled an emission inventory
from all anthropogenic sources for each state. In other words, we combine the year-specific
anthropogenic emissions from Table D-3, with the relevant EGU nonCEM component from D-5,
and one of the EGU CEM estimates from Tables C-l through C-5.
Finally, these emission totals are compared to the 2023 case that was modeled with
CAMx. For each emission cost threshold level in each analysis year, EPA calculated the ratio of
the emission differences from the scenario and the 2023 air quality modeling base case to the
total NOx emissions for the 2023 air quality modeling base case used in the air quality modeling
for each state (see Tables D-6 through D-10). For each year, we also created a complete
"straight line" emissions inventory including a linear interpolation of the EGU inventory from
the air quality modeling between 2023 and 2016 and between 2023 and 2028. Similarly, in
Table D-l 1, we examined the emission reduction for non-EGUs in tranche 1 for glass and
34
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cement controls below $2,000 per ton, and then estimated the ratio of the emission difference
relative to the 2023 air quality modeling base case.
For each cost threshold level analyzed, on a receptor-by-receptor basis, the emissions
change for each upwind state is associated with one of two emission levels (either the
engineering base case emission level for that year or the particular cost threshold level)
depending on whether the upwind state is "linked" to that receptor or if the receptor is located
within the state. States that are contributing above the air quality threshold (i.e., greater than or
equal to 1 percent of the NAAQS) to the monitor, as well as the state containing the monitor,
make NOx emission reductions available at the particular cost threshold level for that year. The
emissions for all other states are adjusted to the engineering base case level for that year.
For the $l,600/ton control case at various years, all states that were linked to any receptor
in 2021 were simultaneously adjusted to the emission levels in the control case, regardless of
whether the state was "linked." This scenario examines the emission results when budgets have
been applied to the geography. For each monitor, the predicted change in contribution of ozone
from each state is calculated by multiplying the state-specific 2023 base case ozone contributions
from the air quality modeling by the calibration factor as well as by the ratio of the change in
emissions (Tables D-l through D-10, for either the emission cost threshold level or the
engineering base case emission level depending on whether the state is linked).28 This calibrated
change in ozone is then added to the ozone contribution from the 2023 base case air quality
modeling. The result is the state and receptor specific "calibrated" total ozone contribution after
implementation of the emission at a particular cost threshold level.
For each monitor, these state-level "calibrated" contributions are then summed to
estimate total ozone contribution from the states to a particular receptor in the CAMx modeling
domain. Finally, "other" modeled ozone contributions ("CAN MEX", "OFFSHORE",
"USCANMEX FIRE", "ICBC", and "BIOG") are added from the 2023 base case air quality
modeling to the state contributions to account for other sources of ozone affecting the modeling
domain. The total ozone from all the states and "other" contributions equals the average design
values estimated in the assessment tool. The maximum design values were estimated by
multiplying the estimated average design values by the ratio of the modeled 2023 base case
maximum to average design values.
Generally, as the emission cost threshold stringency increased, the estimated average and
maximum design values at each receptor decreased. In the assessment tool, the estimated value
of the average design value was used to estimate whether the location will be out of attainment,
while the estimated maximum design value was used to estimate whether the location will have
problems maintaining the NAAQS. The area was noted as having a nonattainment or
maintenance issue if either estimated air quality level was greater than or equal to 76 ppb.
28 The change in concentration can be positive or negative, depending on whether the state's total anthropogenic
ozone season NOx emissions for the scenario are larger or smaller than the 2023 air quality modeling base case
emission level.
35
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Table D-3. Ozone Season Anthropogenic NOx Emissions (Tons) without EGUs for Each
State.
State
2021
2022
2023
2024
2025
2026
Alabama
69,987
66,163
62,338
60,603
58,868
57,134
Arizona
45,793
42,719
39,644
38,220
36,796
35,371
Arkansas
42,259
39,586
36,914
35,793
34,672
33,551
California
161,697
152,246
142,795
140,823
138,852
136,880
Colorado
59,562
56,774
53,986
52,934
51,881
50,829
Connecticut
12,579
11,683
10,787
10,496
10,205
9,914
Delaware
7,443
7,053
6,664
6,514
6,365
6,216
District of Columbia
1,817
1,713
1,609
1,556
1,504
1,452
Florida
113,717
105,687
97,657
94,900
92,143
89,385
Georgia
77,170
71,638
66,107
64,178
62,248
60,319
Idaho
22,332
21,039
19,745
19,039
18,333
17,627
Illinois
103,427
98,260
93,094
90,938
88,782
86,626
Indiana
73,016
68,763
64,511
62,670
60,829
58,988
Iowa
42,556
39,903
37,250
35,915
34,580
33,246
Kansas
67,361
64,151
60,941
59,345
57,749
56,153
Kentucky
49,241
46,459
43,676
42,486
41,296
40,106
Louisiana
101,112
98,267
95,423
94,142
92,862
91,582
Maine
13,285
12,535
11,786
11,486
11,186
10,886
Maryland
28,862
26,913
24,963
24,334
23,705
23,076
Massachusetts
33,806
32,138
30,469
29,869
29,269
28,669
Michigan
81,760
77,760
73,761
72,229
70,696
69,163
Minnesota
62,574
58,958
55,342
53,789
52,236
50,683
Mississippi
35,723
33,389
31,055
30,299
29,543
28,787
Missouri
68,437
63,937
59,436
57,302
55,169
53,035
Montana
27,412
26,140
24,868
24,079
23,290
22,501
Nebraska
38,582
36,322
34,063
32,847
31,631
30,414
Nevada
21,229
19,836
18,443
17,822
17,202
16,581
New Hampshire
8,429
7,948
7,466
7,280
7,093
6,906
New Jersey
41,044
38,117
35,189
34,314
33,439
32,564
New Mexico
52,452
50,678
48,905
47,794
46,684
45,573
New York
78,610
74,563
70,517
68,874
67,231
65,587
North Carolina
68,043
63,994
59,944
58,207
56,469
54,732
North Dakota
37,522
36,370
35,218
34,332
33,446
32,561
Ohio
90,701
85,504
80,307
78,080
75,853
73,626
Oklahoma
96,329
94,061
91,794
89,825
87,856
85,887
Oregon
34,601
32,676
30,751
29,716
28,681
27,646
Pennsylvania
106,545
102,733
98,920
96,913
94,906
92,899
Rhode Island
5,095
4,739
4,384
4,258
4,133
4,007
South Carolina
45,792
42,877
39,963
38,799
37,636
36,472
South Dakota
15,556
14,414
13,273
12,653
12,032
11,412
Tennessee
61,367
57,590
53,813
52,363
50,913
49,462
Texas
297,010
283,927
270,845
265,662
260,480
255,297
Utah
33,095
31,333
29,572
28,803
28,034
27,266
Vermont
4,583
4,311
4,038
3,897
3,756
3,614
Virginia
61,278
57,313
53,347
51,893
50,439
48,985
Washington
65,990
62,147
58,305
56,338
54,371
52,404
West Virginia
37,555
37,047
36,540
36,056
35,573
35,089
Wisconsin
50,430
47,071
43,713
42,447
41,182
39,917
Wyoming
34,845
34,165
33,486
33,011
32,536
32,061
Tribal Data
2,742
2,743
2,744
2,754
2,764
2,773
36
-------
Table D-4. EGU Point Source NOx Emissions (Tons) from Units without CEMs from AQ
Modeling Inventory.
State
2016 Eng EGU
2023 IPM
EGU
nonCEMs
2023 Eng EGU
2028 IPM EGU
nonCEMs
nonCEMs
nonCEMs
Alabama
482
473
200
450
Arizona
367
1,012
377
1,117
Arkansas
141
526
87
528
California
1,972
1,674
1,968
444
Colorado
334
604
277
998
Connecticut
1,272
1,759
1,362
1,788
Delaware
80
131
80
142
District of Columbia
0
0
0
0
Florida
6,189
8,376
6,466
8,569
Georgia
1,580
838
1,640
856
Idaho
528
164
413
161
Illinois
55
1,070
49
1,128
Indiana
611
1,165
722
1,115
Iowa
635
797
618
880
Kansas
109
1,001
93
653
Kentucky
1
366
1
561
Louisiana
3,885
1,943
3,908
1,964
Maine
1,972
1,280
1,908
1,275
Maryland
901
1,930
924
1,983
Massachusetts
2,363
2,044
2,349
2,046
Michigan
1,367
3,825
1,367
3,939
Minnesota
1,740
1,556
1,502
1,522
Mississippi
1,726
959
1,341
952
Missouri
471
331
456
349
Montana
933
3
933
3
Nebraska
665
750
664
748
Nevada
155
268
155
253
New Hampshire
374
215
374
206
New Jersey
1,083
1,844
1,022
1,955
New Mexico
98
72
98
88
New York
1,996
5,068
2,094
5,142
North Carolina
740
1,559
862
1,827
North Dakota
156
116
14
121
Ohio
722
1,881
981
1,961
Oklahoma
1
753
277
695
Oregon
712
515
712
515
Pennsylvania
2,187
5,945
2,543
5,573
Rhode Island
35
313
35
308
South Carolina
604
647
698
834
South Dakota
30
23
30
24
Tennessee
7
510
116
508
Texas
1,996
5,101
2,026
4,623
Utah
561
109
48
91
Vermont
61
9
0
9
Virginia
2,995
2,772
2,996
2,962
Washington
1,536
565
1,503
550
West Virginia
1
0
1
0
Wisconsin
61
612
92
617
Wyoming
11
0
0
0
Tribal Data
50
455
71
3,080
37
-------
Table D-5. EGU Point Source NOx Emissions (Tons) from Units without CEMs Adjusted
by Year.
State
2021
2022
2023
2024
2025
2026
Alabama
280
240
200
200
200
200
Arizona
374
376
377
377
377
377
Arkansas
102
95
87
87
87
87
California
1,969
1,969
1,968
1,968
1,968
1,968
Colorado
294
286
277
277
277
277
Connecticut
1,337
1,349
1,362
1,362
1,362
1,362
Delaware
80
80
80
80
80
80
District of Columbia
0
0
0
0
0
0
Florida
6,387
6,426
6,466
6,466
6,466
6,466
Georgia
1,623
1,631
1,640
1,640
1,640
1,640
Idaho
446
429
413
413
413
413
Illinois
50
50
49
49
49
49
Indiana
690
706
722
722
722
722
Iowa
623
621
618
618
618
618
Kansas
98
95
93
93
93
93
Kentucky
1
1
1
1
1
1
Louisiana
3,902
3,905
3,908
3,908
3,908
3,908
Maine
1,926
1,917
1,908
1,908
1,908
1,908
Maryland
918
921
924
924
924
924
Massachusetts
2,353
2,351
2,349
2,349
2,349
2,349
Michigan
1,367
1,367
1,367
1,367
1,367
1,367
Minnesota
1,570
1,536
1,502
1,502
1,502
1,502
Mississippi
1,451
1,396
1,341
1,341
1,341
1,341
Missouri
460
458
456
456
456
456
Montana
933
933
933
933
933
933
Nebraska
664
664
664
664
664
664
Nevada
155
155
155
155
155
155
New Hampshire
374
374
374
374
374
374
New Jersey
1,039
1,031
1,022
1,022
1,022
1,022
New Mexico
98
98
98
98
98
98
New York
2,066
2,080
2,094
2,094
2,094
2,094
North Carolina
827
845
862
862
862
862
North Dakota
54
34
14
14
14
14
Ohio
907
944
981
981
981
981
Oklahoma
198
237
277
277
277
277
Oregon
712
712
712
712
712
712
Pennsylvania
2,441
2,492
2,543
2,543
2,543
2,543
Rhode Island
35
35
35
35
35
35
South Carolina
671
684
698
698
698
698
South Dakota
30
30
30
30
30
30
Tennessee
85
100
116
116
116
116
Texas
2,017
2,021
2,026
2,026
2,026
2,026
Utah
195
122
48
48
48
48
Vermont
18
9
0
0
0
0
Virginia
2,996
2,996
2,996
2,996
2,996
2,996
Washington
1,513
1,508
1,503
1,503
1,503
1,503
West Virginia
1
1
1
1
1
1
Wisconsin
83
88
92
92
92
92
Wyoming
3
2
0
0
0
0
Tribal Data
65
68
71
71
71
71
38
-------
Table D-6. 2021 Fractional Difference in Emissions Relative to 2023 Air Quality Modeling
Base Case for Each State.
State
Eng Baseline
$500/ton
Optimize
SCR
Optimize
SCR + SOA
CC
Optimize
SNCR+ SCR
+ SOA CC
New SNCR +
Optimize
SNCR+ SCR
+ SOA CC
New SCR +
Optimize
SNCR+ SCR
+ SOA CC
Straight Line
Interpolation
Alabama
0.151
0.151
0.151
0.148
0.148
0.148
0.147
0.140
Arizona
0.145
0.138
0.127
0.117
0.073
0.073
0.073
0.160
Arkansas
0.098
0.096
0.097
0.089
0.080
0.047
0.010
0.136
California
0.136
0.136
0.135
0.135
0.135
0.135
0.135
0.132
Colorado
0.095
0.095
0.095
0.095
0.090
0.077
0.046
0.117
Connecticut
0.121
0.119
0.118
0.118
0.118
0.118
0.118
0.138
Delaware
0.109
0.109
0.107
0.107
0.105
0.105
0.105
0.131
District of
Columbia
0.129
0.129
0.129
0.129
0.129
0.129
0.129
0.129
Florida
0.185
0.185
0.176
0.176
0.173
0.169
0.163
0.182
Georgia
0.175
0.175
0.175
0.175
0.175
0.175
0.175
0.162
Idaho
0.153
0.153
0.153
0.153
0.153
0.153
0.153
0.136
Illinois
0.092
0.092
0.090
0.090
0.086
0.081
0.077
0.111
Indiana
0.088
0.086
0.047
0.047
0.042
0.033
0.017
0.164
Iowa
0.060
0.058
0.043
0.041
0.029
0.009
-0.040
0.107
Kansas
0.057
0.057
0.047
0.047
0.045
0.039
0.022
0.088
Kentucky
0.248
0.248
0.225
0.178
0.176
0.150
0.118
0.201
Louisiana
0.145
0.145
0.144
0.139
0.133
0.131
0.118
0.091
Maine
0.163
0.163
0.163
0.163
0.163
0.163
0.163
0.131
Maryland
0.128
0.128
0.127
0.126
0.120
0.120
0.116
0.166
Massachusetts
0.106
0.105
0.105
0.105
0.105
0.105
0.105
0.109
Michigan
0.106
0.098
0.093
0.082
0.080
0.070
0.056
0.100
Minnesota
0.108
0.106
0.100
0.100
0.089
0.080
0.073
0.120
Mississippi
0.331
0.331
0.331
0.307
0.299
0.291
0.283
0.188
Missouri
0.090
0.090
0.076
0.076
0.071
0.071
0.052
0.161
Montana
0.104
0.104
0.104
0.104
0.104
0.076
0.045
0.116
Nebraska
0.089
0.087
0.088
0.070
0.067
0.039
-0.001
0.103
Nevada
0.249
0.217
0.198
0.198
0.196
0.178
0.138
0.173
New Hampshire
0.184
0.184
0.173
0.173
0.173
0.173
0.173
0.147
New Jersey
0.151
0.151
0.148
0.148
0.148
0.148
0.148
0.157
New Mexico
0.076
0.075
0.073
0.073
0.061
0.061
0.024
0.091
New York
0.078
0.078
0.078
0.078
0.076
0.076
0.076
0.105
North Carolina
0.108
0.107
0.047
0.047
0.012
0.012
-0.031
0.093
North Dakota
0.064
0.063
0.062
0.062
0.035
0.006
-0.112
0.077
Ohio
0.090
0.086
0.027
0.027
0.025
0.025
0.021
0.125
Oklahoma
0.043
0.043
0.041
0.041
0.039
0.032
0.026
0.054
Oregon
0.134
0.134
0.134
0.134
0.134
0.134
0.134
0.134
Pennsylvania
0.072
0.071
0.041
0.041
0.038
0.037
0.037
0.122
Rhode Island
0.131
0.131
0.131
0.131
0.131
0.131
0.131
0.136
South Carolina
0.109
0.109
0.084
0.084
0.084
0.084
0.084
0.128
South Dakota
0.176
0.175
0.175
0.175
0.175
0.175
0.175
0.167
Tennessee
0.154
0.154
0.151
0.151
0.149
0.149
0.149
0.163
Texas
0.094
0.091
0.086
0.085
0.078
0.066
0.047
0.095
Utah
0.116
0.064
0.063
0.063
0.011
0.011
0.011
0.142
Vermont
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.143
Virginia
0.190
0.190
0.189
0.181
0.179
0.179
0.175
0.176
Washington
0.172
0.172
0.172
0.172
0.172
0.172
0.158
0.148
West Virginia
-0.021
-0.024
-0.049
-0.065
-0.072
-0.072
-0.106
0.042
Wisconsin
0.153
0.151
0.147
0.147
0.146
0.146
0.145
0.159
Wyoming
0.127
0.127
0.124
0.084
0.050
0.026
-0.038
0.089
Tribal Data
0.079
0.079
0.079
0.079
0.079
-0.012
-0.189
0.580
39
-------
Table D-7. 2022 Fractional Difference in Emissions Relative to 2023 Air Quality Modeling
Base Case for Each State.
State
Eng Baseline
$500/ton
Optimize
SCR
Optimize
SCR + SOA
CC
Optimize
SNCR+ SCR
+ SOA CC
New SNCR +
Optimize
SNCR+ SCR
+ SOA CC
New SCR +
Optimize
SNCR+ SCR
+ SOA CC
Straight Line
Interpolation
Alabama
0.094
0.094
0.094
0.091
0.091
0.091
0.090
0.070
Arizona
0.076
0.070
0.059
0.049
0.005
0.005
0.005
0.080
Arkansas
0.040
0.038
0.039
0.031
0.023
-0.011
-0.047
0.068
California
0.071
0.071
0.070
0.070
0.070
0.070
0.070
0.066
Colorado
0.050
0.050
0.050
0.049
0.045
0.031
0.000
0.059
Connecticut
0.051
0.049
0.048
0.048
0.048
0.048
0.048
0.069
Delaware
0.053
0.053
0.050
0.050
0.049
0.049
0.049
0.066
District of
Columbia
0.064
0.064
0.064
0.064
0.064
0.064
0.064
0.065
Florida
0.115
0.115
0.106
0.106
0.102
0.099
0.093
0.091
Georgia
0.100
0.100
0.100
0.100
0.100
0.100
0.100
0.081
Idaho
0.088
0.088
0.088
0.088
0.088
0.088
0.088
0.068
Illinois
0.042
0.042
0.040
0.040
0.036
0.031
0.027
0.055
Indiana
0.031
0.029
-0.010
-0.010
-0.016
-0.023
-0.036
0.082
Iowa
0.006
0.003
-0.012
-0.014
-0.026
-0.046
-0.095
0.053
Kansas
0.011
0.011
0.001
0.001
-0.001
-0.007
-0.024
0.044
Kentucky
0.194
0.195
0.171
0.124
0.122
0.097
0.065
0.100
Louisiana
0.118
0.118
0.117
0.112
0.106
0.104
0.091
0.046
Maine
0.106
0.106
0.106
0.106
0.106
0.106
0.106
0.065
Maryland
0.058
0.058
0.057
0.056
0.050
0.050
0.046
0.083
Massachusetts
0.055
0.055
0.055
0.055
0.055
0.055
0.055
0.055
Michigan
0.061
0.052
0.048
0.037
0.034
0.024
0.010
0.050
Minnesota
0.049
0.047
0.041
0.041
0.030
0.021
0.014
0.060
Mississippi
0.261
0.261
0.261
0.237
0.229
0.221
0.213
0.094
Missouri
0.030
0.029
0.016
0.016
0.011
0.011
-0.008
0.080
Montana
0.049
0.049
0.049
0.049
0.049
0.021
-0.010
0.058
Nebraska
0.037
0.035
0.036
0.018
0.015
-0.013
-0.053
0.051
Nevada
0.176
0.144
0.125
0.125
0.122
0.105
0.065
0.086
New Hampshire
0.122
0.122
0.111
0.111
0.111
0.111
0.111
0.073
New Jersey
0.073
0.073
0.071
0.071
0.071
0.071
0.071
0.078
New Mexico
0.043
0.042
0.040
0.040
0.028
0.028
-0.010
0.046
New York
0.027
0.026
0.026
0.026
0.025
0.025
0.025
0.052
North Carolina
0.056
0.054
-0.006
-0.006
-0.041
-0.041
-0.084
0.047
North Dakota
0.039
0.038
0.037
0.037
0.010
-0.019
-0.137
0.038
Ohio
0.038
0.035
-0.025
-0.025
-0.026
-0.026
-0.030
0.062
Oklahoma
0.021
0.020
0.019
0.019
0.017
0.010
0.004
0.027
Oregon
0.073
0.073
0.073
0.073
0.073
0.073
0.073
0.067
Pennsylvania
0.039
0.038
0.008
0.008
0.005
0.004
0.003
0.061
Rhode Island
0.056
0.056
0.056
0.056
0.056
0.056
0.056
0.068
South Carolina
0.046
0.046
0.022
0.022
0.022
0.022
0.022
0.064
South Dakota
0.093
0.092
0.092
0.092
0.092
0.092
0.092
0.083
Tennessee
0.088
0.088
0.085
0.085
0.084
0.084
0.084
0.081
Texas
0.052
0.049
0.044
0.043
0.036
0.025
0.006
0.048
Utah
0.065
0.013
0.012
0.012
-0.040
-0.040
-0.040
0.071
Vermont
0.080
0.080
0.080
0.080
0.080
0.080
0.080
0.072
Virginia
0.115
0.115
0.114
0.106
0.103
0.103
0.099
0.088
Washington
0.107
0.107
0.107
0.107
0.107
0.107
0.093
0.074
West Virginia
-0.030
-0.033
-0.058
-0.074
-0.081
-0.081
-0.116
0.021
Wisconsin
0.084
0.081
0.078
0.078
0.077
0.077
0.075
0.079
Wyoming
0.097
0.097
0.094
0.058
0.024
0.000
-0.064
0.045
Tribal Data
0.080
0.080
0.080
0.080
0.080
-0.011
-0.188
0.290
40
-------
Table D-8. 2023 Fractional Difference in Emissions Relative to 2023 Air Quality Modeling
Base Case for Each State.
State
Eng Baseline
$500/ton
Optimize
SCR
Optimize
SCR + SOA
CC
Optimize
SNCR+ SCR
+ SOA CC
New SNCR +
Optimize
SNCR+ SCR
+ SOA CC
New SCR +
Optimize
SNCR+ SCR
+ SOA CC
Straight Line
Interpolation
Alabama
0.037
0.037
0.037
0.034
0.034
0.034
0.033
0.000
Arizona
0.008
0.002
-0.009
-0.019
-0.063
-0.063
-0.063
0.000
Arkansas
-0.018
-0.019
-0.018
-0.026
-0.035
-0.069
-0.105
0.000
California
0.006
0.006
0.005
0.005
0.005
0.005
0.005
0.000
Colorado
-0.003
-0.003
-0.004
-0.004
-0.009
-0.022
-0.053
0.000
Connecticut
-0.018
-0.020
-0.021
-0.021
-0.021
-0.021
-0.021
0.000
Delaware
-0.003
-0.003
-0.005
-0.005
-0.007
-0.007
-0.007
0.000
District of
Columbia
-0.001
-0.001
-0.001
-0.001
-0.001
-0.001
-0.001
0.000
Florida
0.038
0.038
0.029
0.029
0.026
0.023
0.017
0.000
Georgia
0.025
0.025
0.025
0.025
0.025
0.025
0.025
0.000
Idaho
0.022
0.022
0.022
0.022
0.022
0.022
0.022
0.000
Illinois
-0.018
-0.018
-0.020
-0.020
-0.023
-0.029
-0.032
0.000
Indiana
-0.021
-0.023
-0.061
-0.062
-0.067
-0.074
-0.088
0.000
Iowa
-0.057
-0.059
-0.074
-0.075
-0.087
-0.107
-0.156
0.000
Kansas
-0.036
-0.036
-0.045
-0.045
-0.047
-0.053
-0.070
0.000
Kentucky
0.141
0.141
0.118
0.071
0.068
0.043
0.011
0.000
Louisiana
0.091
0.091
0.090
0.085
0.079
0.077
0.064
0.000
Maine
0.048
0.048
0.048
0.048
0.048
0.048
0.048
0.000
Maryland
-0.012
-0.012
-0.014
-0.014
-0.020
-0.020
-0.024
0.000
Massachusetts
0.004
0.004
0.004
0.004
0.003
0.003
0.003
0.000
Michigan
-0.017
-0.026
-0.030
-0.031
-0.034
-0.044
-0.058
0.000
Minnesota
-0.028
-0.030
-0.036
-0.036
-0.045
-0.054
-0.061
0.000
Mississippi
0.190
0.190
0.190
0.166
0.159
0.150
0.142
0.000
Missouri
-0.034
-0.035
-0.049
-0.049
-0.053
-0.053
-0.072
0.000
Montana
0.005
0.005
0.005
0.005
0.005
-0.023
-0.054
0.000
Nebraska
-0.015
-0.017
-0.016
-0.034
-0.037
-0.065
-0.105
0.000
Nevada
0.097
0.066
0.047
0.047
0.044
0.027
-0.013
0.000
New Hampshire
0.060
0.060
0.049
0.049
0.049
0.049
0.049
0.000
New Jersey
-0.005
-0.005
-0.007
-0.007
-0.007
-0.007
-0.007
0.000
New Mexico
0.008
0.007
0.005
0.005
-0.007
-0.007
-0.044
0.000
New York
-0.025
-0.025
-0.026
-0.026
-0.027
-0.027
-0.027
0.000
North Carolina
0.003
0.002
-0.058
-0.058
-0.094
-0.094
-0.137
0.000
North Dakota
-0.045
-0.045
-0.046
-0.046
-0.069
-0.086
-0.193
0.000
Ohio
-0.014
-0.018
-0.077
-0.077
-0.079
-0.079
-0.083
0.000
Oklahoma
-0.001
-0.002
-0.003
-0.003
-0.005
-0.012
-0.018
0.000
Oregon
0.012
0.012
0.012
0.012
0.012
0.012
0.012
0.000
Pennsylvania
0.005
0.004
-0.026
-0.026
-0.028
-0.030
-0.030
0.000
Rhode Island
-0.019
-0.019
-0.019
-0.019
-0.019
-0.019
-0.019
0.000
South Carolina
-0.016
-0.016
-0.041
-0.041
-0.041
-0.041
-0.041
0.000
South Dakota
0.010
0.009
0.009
0.009
0.009
0.009
0.009
0.000
Tennessee
0.022
0.022
0.019
0.019
0.018
0.018
0.018
0.000
Texas
0.010
0.007
0.002
0.001
-0.006
-0.017
-0.037
0.000
Utah
0.013
-0.039
-0.039
-0.039
-0.091
-0.091
-0.091
0.000
Vermont
0.011
0.011
0.011
0.011
0.011
0.011
0.011
0.000
Virginia
0.046
0.046
0.045
0.037
0.035
0.035
0.031
0.000
Washington
0.042
0.042
0.042
0.042
0.042
0.042
0.027
0.000
West Virginia
-0.073
-0.075
-0.086
-0.102
-0.109
-0.109
-0.144
0.000
Wisconsin
0.009
0.006
0.003
0.003
0.002
0.002
0.002
0.000
Wyoming
0.066
0.066
0.064
0.033
-0.001
-0.025
-0.089
0.000
Tribal Data
0.081
0.081
0.081
0.081
0.081
-0.011
-0.187
0.000
41
-------
Table D-9. 2024 Fractional Difference in Emissions Relative to 2023 Air Quality Modeling
Base Case for Each State.
State
Eng Baseline
$500/ton
Optimize
SCR
Optimize
SCR + SOA
CC
Optimize
SNCR+ SCR
+ SOA CC
New SNCR +
Optimize
SNCR+ SCR
+ SOA CC
New SCR +
Optimize
SNCR+ SCR
+ SOA CC
Straight Line
Interpolation
Alabama
0.011
0.011
0.011
0.008
0.008
0.008
0.007
-0.021
Arizona
-0.023
-0.030
-0.041
-0.051
-0.095
-0.095
-0.095
-0.036
Arkansas
-0.042
-0.043
-0.042
-0.050
-0.059
-0.093
-0.129
-0.028
California
-0.007
-0.007
-0.009
-0.009
-0.009
-0.009
-0.009
-0.016
Colorado
-0.032
-0.032
-0.032
-0.033
-0.037
-0.048
-0.070
-0.018
Connecticut
-0.041
-0.043
-0.044
-0.044
-0.044
-0.044
-0.044
-0.024
Delaware
-0.024
-0.024
-0.027
-0.027
-0.028
-0.028
-0.028
-0.020
District of
Columbia
-0.033
-0.033
-0.033
-0.033
-0.033
-0.033
-0.033
-0.033
Florida
0.013
0.013
0.004
0.004
0.001
-0.002
-0.008
-0.025
Georgia
-0.001
-0.001
-0.001
-0.001
-0.002
-0.002
-0.002
-0.023
Idaho
-0.013
-0.013
-0.013
-0.013
-0.013
-0.013
-0.013
-0.035
Illinois
-0.039
-0.039
-0.041
-0.041
-0.044
-0.050
-0.053
-0.020
Indiana
-0.075
-0.077
-0.115
-0.115
-0.120
-0.123
-0.130
-0.022
Iowa
-0.084
-0.087
-0.101
-0.103
-0.114
-0.134
-0.183
-0.028
Kansas
-0.059
-0.059
-0.068
-0.068
-0.070
-0.076
-0.093
-0.024
Kentucky
0.118
0.118
0.095
0.048
0.046
0.020
-0.012
-0.023
Louisiana
0.079
0.078
0.078
0.073
0.067
0.065
0.052
-0.012
Maine
0.025
0.025
0.025
0.025
0.025
0.025
0.025
-0.023
Maryland
-0.035
-0.035
-0.036
-0.037
-0.043
-0.043
-0.046
-0.022
Massachusetts
-0.014
-0.014
-0.014
-0.014
-0.015
-0.015
-0.015
-0.018
Michigan
-0.037
-0.045
-0.050
-0.051
-0.053
-0.063
-0.077
-0.015
Minnesota
-0.053
-0.055
-0.060
-0.060
-0.069
-0.078
-0.085
-0.031
Mississippi
0.168
0.168
0.168
0.144
0.137
0.128
0.120
-0.020
Missouri
-0.063
-0.063
-0.077
-0.077
-0.082
-0.082
-0.101
-0.029
Montana
-0.022
-0.022
-0.022
-0.022
-0.022
-0.050
-0.081
-0.028
Nebraska
-0.060
-0.061
-0.061
-0.070
-0.072
-0.100
-0.136
-0.026
Nevada
0.064
0.033
0.014
0.014
0.012
-0.006
-0.045
-0.034
New Hampshire
0.036
0.036
0.025
0.025
0.025
0.025
0.025
-0.025
New Jersey
-0.028
-0.028
-0.030
-0.030
-0.030
-0.030
-0.030
-0.022
New Mexico
-0.013
-0.014
-0.016
-0.016
-0.028
-0.028
-0.065
-0.022
New York
-0.047
-0.047
-0.047
-0.047
-0.049
-0.049
-0.049
-0.023
North Carolina
-0.020
-0.021
-0.081
-0.081
-0.116
-0.116
-0.159
-0.031
North Dakota
-0.064
-0.064
-0.065
-0.065
-0.088
-0.105
-0.213
-0.020
Ohio
-0.037
-0.040
-0.100
-0.100
-0.101
-0.101
-0.105
-0.022
Oklahoma
-0.020
-0.021
-0.023
-0.023
-0.025
-0.031
-0.037
-0.016
Oregon
-0.021
-0.021
-0.021
-0.021
-0.021
-0.021
-0.021
-0.033
Pennsylvania
-0.013
-0.013
-0.044
-0.044
-0.046
-0.048
-0.048
-0.022
Rhode Island
-0.045
-0.045
-0.045
-0.045
-0.045
-0.045
-0.045
-0.027
South Carolina
-0.041
-0.041
-0.066
-0.066
-0.066
-0.066
-0.066
-0.024
South Dakota
-0.035
-0.036
-0.036
-0.036
-0.036
-0.036
-0.036
-0.045
Tennessee
-0.003
-0.003
-0.006
-0.006
-0.008
-0.008
-0.008
-0.025
Texas
-0.007
-0.010
-0.014
-0.015
-0.022
-0.034
-0.053
-0.017
Utah
-0.008
-0.060
-0.061
-0.061
-0.113
-0.113
-0.113
-0.022
Vermont
-0.024
-0.024
-0.024
-0.024
-0.024
-0.024
-0.024
-0.035
Virginia
0.016
0.016
0.016
0.007
0.005
0.005
0.001
-0.022
Washington
0.008
0.008
0.008
0.008
0.008
0.008
-0.006
-0.033
West Virginia
-0.082
-0.084
-0.095
-0.111
-0.118
-0.118
-0.153
-0.007
Wisconsin
-0.028
-0.031
-0.034
-0.034
-0.035
-0.035
-0.035
-0.027
Wyoming
0.055
0.055
0.052
0.021
-0.013
-0.036
-0.100
-0.020
Tribal Data
0.082
0.082
0.082
0.082
0.082
-0.009
-0.186
0.001
42
-------
Table D-10. 2025 Fractional Difference in Emissions Relative to 2023 Air Quality
Modeling Base Case for Each State. i
State
Eng Baseline
$500/ton
Optimize
SCR
Optimize
SCR + SOA
CC
Optimize
SNCR+ SCR
+ SOA CC
New SNCR +
Optimize
SNCR+ SCR
+ SOA CC
New SCR +
Optimize
SNCR+ SCR
+ SOA CC
Straight Line
Interpolation
Alabama
-0.015
-0.015
-0.015
-0.017
-0.017
-0.017
-0.019
-0.043
Arizona
-0.055
-0.062
-0.072
-0.082
-0.127
-0.127
-0.127
-0.071
Arkansas
-0.066
-0.067
-0.066
-0.074
-0.083
-0.117
-0.153
-0.055
California
-0.021
-0.021
-0.023
-0.023
-0.023
-0.023
-0.023
-0.032
Colorado
-0.049
-0.049
-0.050
-0.050
-0.055
-0.065
-0.087
-0.037
Connecticut
-0.064
-0.066
-0.067
-0.067
-0.067
-0.067
-0.067
-0.047
Delaware
-0.046
-0.046
-0.048
-0.048
-0.049
-0.049
-0.049
-0.041
District of
Columbia
-0.066
-0.066
-0.066
-0.066
-0.066
-0.066
-0.066
-0.065
Florida
-0.016
-0.016
-0.025
-0.025
-0.028
-0.031
-0.037
-0.050
Georgia
-0.027
-0.027
-0.027
-0.027
-0.028
-0.028
-0.028
-0.047
Idaho
-0.049
-0.049
-0.049
-0.049
-0.049
-0.049
-0.049
-0.071
Illinois
-0.061
-0.061
-0.063
-0.063
-0.066
-0.072
-0.075
-0.041
Indiana
-0.097
-0.099
-0.137
-0.138
-0.142
-0.146
-0.152
-0.043
Iowa
-0.111
-0.114
-0.129
-0.130
-0.142
-0.162
-0.211
-0.057
Kansas
-0.081
-0.082
-0.091
-0.091
-0.093
-0.099
-0.116
-0.047
Kentucky
0.095
0.095
0.072
0.025
0.023
-0.003
-0.035
-0.046
Louisiana
0.067
0.066
0.066
0.061
0.055
0.052
0.040
-0.025
Maine
0.002
0.002
0.002
0.002
0.002
0.002
0.002
-0.046
Maryland
-0.057
-0.057
-0.059
-0.060
-0.065
-0.065
-0.069
-0.044
Massachusetts
-0.033
-0.033
-0.033
-0.033
-0.033
-0.033
-0.033
-0.037
Michigan
-0.055
-0.063
-0.067
-0.069
-0.071
-0.081
-0.095
-0.030
Minnesota
-0.077
-0.079
-0.085
-0.085
-0.094
-0.103
-0.110
-0.063
Mississippi
0.146
0.146
0.146
0.122
0.114
0.106
0.098
-0.041
Missouri
-0.091
-0.092
-0.106
-0.106
-0.110
-0.110
-0.130
-0.058
Montana
-0.049
-0.049
-0.049
-0.049
-0.049
-0.077
-0.108
-0.056
Nebraska
-0.088
-0.090
-0.089
-0.099
-0.101
-0.128
-0.164
-0.052
Nevada
0.032
0.001
-0.019
-0.019
-0.021
-0.039
-0.078
-0.068
New Hampshire
0.012
0.012
0.000
0.000
0.000
0.000
0.000
-0.049
New Jersey
-0.051
-0.051
-0.054
-0.054
-0.054
-0.054
-0.054
-0.044
New Mexico
-0.034
-0.035
-0.037
-0.037
-0.049
-0.049
-0.086
-0.044
New York
-0.068
-0.068
-0.068
-0.068
-0.070
-0.070
-0.070
-0.045
North Carolina
-0.048
-0.049
-0.109
-0.109
-0.144
-0.144
-0.183
-0.062
North Dakota
-0.083
-0.084
-0.084
-0.084
-0.107
-0.124
-0.232
-0.040
Ohio
-0.059
-0.063
-0.122
-0.122
-0.124
-0.124
-0.128
-0.044
Oklahoma
-0.040
-0.040
-0.042
-0.042
-0.044
-0.051
-0.057
-0.032
Oregon
-0.054
-0.054
-0.054
-0.054
-0.054
-0.054
-0.054
-0.066
Pennsylvania
-0.031
-0.031
-0.062
-0.062
-0.064
-0.065
-0.066
-0.043
Rhode Island
-0.072
-0.072
-0.072
-0.072
-0.072
-0.072
-0.072
-0.054
South Carolina
-0.066
-0.066
-0.091
-0.091
-0.091
-0.091
-0.091
-0.048
South Dakota
-0.080
-0.081
-0.081
-0.081
-0.081
-0.081
-0.081
-0.089
Tennessee
-0.039
-0.039
-0.039
-0.039
-0.041
-0.041
-0.041
-0.050
Texas
-0.024
-0.027
-0.031
-0.032
-0.039
-0.051
-0.070
-0.033
Utah
-0.029
-0.081
-0.082
-0.082
-0.134
-0.134
-0.134
-0.044
Vermont
-0.059
-0.059
-0.059
-0.059
-0.059
-0.059
-0.059
-0.070
Virginia
-0.009
-0.009
-0.010
-0.018
-0.020
-0.020
-0.024
-0.045
Washington
-0.025
-0.025
-0.025
-0.025
-0.025
-0.025
-0.039
-0.067
West Virginia
-0.091
-0.093
-0.104
-0.120
-0.127
-0.127
-0.162
-0.013
Wisconsin
-0.054
-0.057
-0.060
-0.060
-0.061
-0.061
-0.061
-0.054
Wyoming
0.043
0.043
0.040
0.010
-0.024
-0.048
-0.112
-0.040
Tribal Data
0.084
0.084
0.084
0.084
0.084
-0.007
-0.184
0.001
43
-------
Table D-ll. 2023 Ozone Season Anthropogenic NOx Emissions Reductions (Tons) for non-
EGUs and Fractional Difference in Emissions for the non-EGU Scenario Relative to the
State
Non-EGU
glass and
cement,
refined
analysis,
others
unchanged,
below
$2,000/ton
(Tons)
Fractional
Difference
EGU
$l,600/ton
+non-EGU
tranche 1
glass &
cement
analyzed
Alabama
-
0.034
Arizona
-
-0.019
Arkansas
-
-0.026
California
-
0.005
Colorado
-
-0.004
Connecticut
-
-0.021
Delaware
-
-0.005
District of
Columbia
-
-0.001
Florida
-
0.029
Georgia
-
0.025
Idaho
-
0.022
Illinois
464
-0.025
Indiana
666
-0.070
Iowa
-
-0.075
Kansas
-
-0.045
Kentucky
-
0.071
Louisiana
-
0.085
Maine
-
0.048
Maryland
62
-0.017
Massachusetts
-
0.004
Michigan
-
-0.031
Minnesota
-
-0.036
Mississippi
-
0.166
Missouri
-
-0.049
Montana
-
0.005
Nebraska
-
-0.034
Nevada
-
0.047
New Hampshire
-
0.049
New Jersey
-
-0.007
New Mexico
-
0.005
New York
238
-0.029
North Carolina
-
-0.058
North Dakota
-
-0.046
Ohio
-
-0.077
Oklahoma
-
-0.003
Oregon
-
0.012
Pennsylvania
-
-0.026
Rhode Island
-
-0.019
South Carolina
-
-0.041
South Dakota
-
0.009
Tennessee
-
0.019
Texas
-
0.001
Utah
-
-0.039
Vermont
-
0.011
Virginia
138
0.035
Washington
-
0.042
West Virginia
-
-0.102
Wisconsin
-
0.003
Wyoming
-
0.033
44
-------
Tribal Data - 0.081
45
-------
3. Description of the analytic results.
For each year 2021-2025, EPA used the ozone AQAT to estimate improvements in
downwind air quality at base case levels, at $1,600 per ton emission budget levels, and at higher
$ per ton emission budget levels. At each cost threshold level, using AQAT, EPA examined
whether the average and maximum design values for each of the receptors. EPA evaluated the
degree of change in ppb and whether it decreased average or maximum values to below 76 ppb
(at which point their nonattainment and maintenance issues, respectively, would be considered
resolved). EPA also examined each state's air quality contributions at each emission budget
level, assessing whether a state maintained at least one linkage (i.e., greater than 1% (.75 ppb) to
a receptor that was estimated to remain in nonattainment and/or maintenance. EPA examined
the engineering base case, $l,600/ton, $3,900/ton, $5,800/ton, and $9,600/ton. EPA also created
"straight line" estimates comparable to those used at Steps 1 and 2. The preamble explains at
section VII.D how EPA considered the results of the air quality analyses described in this TSD to
determine the appropriate emission levels for eliminating significant contribution to
nonattainment and interference with maintenance.
For each year, the average and maximum design values (in ppb) estimated using the
assessment tool for each identified receptor for each cost threshold level have been rounded to
hundredths of a ppb and can be found in Tables D-12 through D-21. There are four monitors,
three in Connecticut and one in Texas. Scenarios that are not viable, for technical or policy
reasons, have been blacked out in these tables.
In 2021, we observe that the Stratford monitor 090013007 in Fairfield County,
Connecticut, switches to maintenance at the $l,600/ton level (where SCRs are optimized). In
other words, its average design value drops below 76 ppb (Table D-12), while its maximum
design value stays above 76 ppb (Table D-13). The Madison monitor 090099002 in New Haven
County, Connecticut, has both its average and maximum design values below 76 at all cost
levels, including in the Engineering Base. It was estimated to have a maintenance issue in the
2021 Base Case interpolated from the air quality modeling and used at Steps 1 and 2 (with its
maximum design value higher than 76 ppb).
In 2024, there is only one receptor remaining (the Westport monitor 090019003 in
Fairfield County, Connecticut). This receptor switches from nonattainment to maintenance at
$l,600/ton (Tables D-18 and D-19).
EPA also assessed changes in air quality for the non-EGU scenarios for 2023, 2024, and
2025. In these cases, we included EGU emission reductions at the $l,600/ton cost threshold
level. The results are shown in Table D-22.
In the assessment of air quality using the calibrated assessment tool, we are able to
estimate the change in the air quality contributions of each upwind state to each receptor (see the
description of the state and receptor-specific contributions in section D.2.c.(2)) in order to
determine whether any state's contribution is below the 1 percent threshold used in step 2 of the
4-Step Good Neighbor Framework to identify "linked" upwind states. For this over-control
assessment, we compared each state's adjusted ozone concentration against the 1% air quality
threshold at each of the cost threshold levels up to $9,600/ton at each remaining receptor, using
AQAT. To see static air quality contributions and design value estimates for the four receptors
46
-------
of interest for each of the years for each of the cost levels, see the individual worksheets labeled:
$9600; $5800; $3900; $1600 w CC & non-EGU; $1600 w CC; $1600 wo CC; $500;
straightline_base; and eng_base. For interactive worksheets, refer to the "scenario_202X"
worksheets after setting the desired scenario in the "summaryDVs" worksheet. Then, adjust
cells J27 and J28 to match the desired scenario of interest. The numbering for the various
scenarios is shown in Table D-23. For a cost threshold run, cell J27 would be a value of 1
through 7, while cell J28 should be fixed with a value of 1. For all linked states, in the cost
threshold analysis, we did not see any instances where a state's contributions dropped below 1%
of the NAAQS for all its linkages to remaining downwind receptors. That is, if a state was
linked to a receptor in 2021 in the base case, and that receptor remained either nonattainment or
maintenance in other years or at other cost thresholds, the state remained linked with a
contribution greater than or equal to 1% of the NAAQS. This is not a surprising result because,
for a linkage to be resolved by emission reductions of just a few percent, the original base
contribution would need to be within a few percent of the threshold. As a hypothetical example,
if the state is making a 6% emission reduction in its overall anthropogenic ozone season NOx
emissions, and the calibration factor was 0.5, its original base case maximum contribution to a
remaining unresolved nonattainment and/or maintenance receptor would need to be just under
1.03% of the NAAQS or 0.77 ppb, to drop below the 0.75 ppb linkage threshold.
Lastly, once the EGU budgets for the rule were established (based on the results of the
multi-factor test), it was possible to estimate air quality concentrations in the "control scenario"
at each downwind receptor for each year using the ozone AQAT (Table D-24). Here, we apply a
scenario where all states (regardless of whether they are linked to a particular receptor or to a
different receptor in the geography) have the same cost threshold applied as do the "linked"
states. We observe very little effect of this on air quality at the receptor and in no case are the
changes large enough to shift the status of a receptor from either nonattainment to maintenance
or from maintenance to attainment. This is not surprising because the contributions to each
receptor from these non-linked states are already below the 1% threshold.
47
-------
Table D-12. 2021 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Assessment Tool Average Ozone Design Values (ppb).
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Straight
line
Engineering
Baseline
$500/to
n
Optimi
ze SCR
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR+
SCR +
SOA
CC
90013007
CT
Fairfield
74.3
76.50
76.10
76.09
75.92
75.88
75.86
m
¦
90019003
CT
Fairfield
76.9
78.56
78.26
78.24
78.11
78.08
78.06
m
¦
90099002
CT
New Haven
71.7
73.98
73.56
73.55
73.36
73.32
73.29
m
¦
482010024
TX
Harris
74.0
75.51
75.61
75.57
75.51
75.49
75.39
M
¦
Table D-13. 2021 Maximum Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors.
Monitor
Identification
Number
90013007
90019003
90099002
482010024
State
CT
CT
CT
TX
County
Fairfield
Fairfield
New Haven
Harris
CAMx
2023 Base
Case (ppb)
Straight
line
75.2
77.43
77.2
78.86
73.8
76.15
75.6
77.15
Assessment Tool Maximum Ozone Design Values (ppb).
Engineering
Baseline
77.02
78.56
75.72
77.25
$500/to
n
77.01
78.55
75.70
77.21
Optimi
ze SCR
76.83
78.41
75.51
77.14
Optimi
ze SCR
+ SOA
CC
76.80
78.39
75.47
77.12
Optimi
ze
SNCR+
SCR +
SOA
CC
K3
76.78
78.37
75.44
77.02
I I
Table D-14. 2022 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Assessment Tool Average Ozone Design Values (ppb).
Straight
line
Engineering
Baseline
$500/to
n
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR+
SCR +
SOA
CC
90013007
CT
Fairfield
74.3
75.40
75.14
75.12
74.92
74.90
90019003
CT
Fairfield
76.9
77.73
77.53
77.52
77.36
77.34
90099002
CT
New Haven
71.7
72.84
72.57
72.55
72.33
72.30
482010024
TX
Harris
74.0
74.76
74.98
74.94
¦
74.85
74.75
tl
I I
Table D-15. 2022 Maximum Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
| Assessment Tool Maximum Ozone Design Values (ppb). |
Straight
line
Engineering
Baseline
$500/to
n
T
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR
+ SCR
+ SOA
CC
90013007
CT
Fairfield
75.2
76.31
76.05
76.03
75.83
75.81
90019003
CT
Fairfield
77.2
78.03
77.84
77.83
77.66
77.64
m
¦
90099002
CT
New Haven
73.8
74.98
74.69
74.68
¦
74.44
74.41
m
¦
482010024
TX
Harris
75.6
76.37
76.60
76.56
¦
76.47
76.37
M
¦
48
-------
Table D-16. 2023 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Assessment Tool Average Ozone Design Values (ppb).
Straight
line
Engineering
Baseline
$500/to
n
T
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR+
SCR +
SOA
CC
90013007
CT
Fairfield
74.3
74.30
74.08
74.06
73.79
73.76
90019003
CT
Fairfield
76.9
76.90
76.69
76.67
76.39
76.36
90099002
CT
New Haven
71.7
71.70
71.46
71.43
¦
71.14
71.09
482010024
TX
Harris
74.0
74.00
74.55
74.49
¦
74.35
74.18
I I
Table D-17. 2023 Maximum Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
| Assessment Tool Maximum Ozone Design Values (ppb). |
Straigh
t line
Engineering
Baseline
$500/t
on
T
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR
+ SCR
+ SOA
CC
90013007
CT
Fairfield
75.2
75.20
74.98
74.96
74.68
74.65
m
¦
90019003
CT
Fairfield
77.2
77.20
76.99
76.97
76.69
76.65
m
¦
90099002
CT
New Haven
73.8
73.80
73.55
73.52
¦
73.22
73.18
m
¦
482010024
TX
Harris
75.6
75.60
76.17
76.10
¦
75.95
75.78
M
¦
Table D-18. 2024 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
Assessment Tool Average Ozone Design Values (ppb).
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Straight
line
Engineering
Baseline
$500/t
on
T
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR
+ SCR
+ SOA
CC
New
SNCR +
Optimiz
e
SNCR+
SCR +
SOA
CC
New SCR
+
Optimize
SNCR+
SCR +
SOACC
90013007
CT
Fairfield
74.3
73.76
73.53
73.51
¦
73.24
73.21
73.19
73.12
90019003
CT
Fairfield
76.9
76.38
76.16
76.14
¦
75.86
75.82
75.79
75.73
90099002
CT
New Haven
71.7
71.14
70.88
70.85
¦
70.56
70.52
70.49
70.41
482010024
TX
Harris
74.0
73.58
74.14
74.07
¦
73.93
73.76
73.51
73.05
Table D-19. 2024 Maximum Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors.
Assessment Tool Maximum Ozone Design Values
(ppb).
Engineering
Baseline
$500/t
on
x
Optimi
ze SCR
Optimi
ze
New
SNCR +
New SCR
+
Monitor
CAMx
¦
+ SOA
SNCR
Optimiz
Optimize
Identification
State
County
2023 Base
Straigh
CC
+ SCR
e
SNCR+
Number
Case (ppb)
t line
+ SOA
CC
SNCR+
SCR +
SOA
CC
SCR +
SOACC
90013007
CT
Fairfield
75.2
74.65
74.42
74.40
¦
74.13
74.09
74.07
74.01
90019003
CT
Fairfield
77.2
76.68
76.45
76.43
¦
76.15
76.12
76.09
76.02
90099002
CT
New Haven
73.8
73.22
72.96
72.93
¦
72.63
72.58
72.55
72.47
49
-------
482010024 | TX | Harris | 75.6 | 75.17 | 75.74 | 75.67 | 75.53 | 75.36 | 75.09 | 74.63~|
Table D-20. 2025 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors.
Assessment Tool Average Ozone Design Values (ppb).
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Straight
line
Engineering
Baseline
$500/t
on
T
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR
+ SCR
+ SOA
CC
New
SNCR +
Optimiz
e
SNCR+
SCR +
SOA
CC
New SCR
+
Optimize
SNCR+
SCR +
SOACC
90013007
CT
Fairfield
74.3
73.22
73.00
72.98
¦
72.71
72.68
72.66
72.60
90019003
CT
Fairfield
76.9
75.86
75.65
75.63
¦
75.35
75.31
75.28
75.22
90099002
CT
New Haven
71.7
70.58
70.33
70.31
¦
70.01
69.97
69.94
69.86
482010024
TX
Harris
74.0
73.16
73.71
73.64
¦
73.50
73.34
73.08
72.62
Table D-21. 2025 Maximum Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors.
Assessment Tool Maximum Ozone Design Values
(ppb).
Engineerin
g Baseline
$500/t
on
T
Optimi
ze SCR
Optimi
ze
New
SNCR +
New SCR
+
Monitor
Identification
State
County
CAMx
2023 Base
Straigh
¦
+ SOA
CC
SNCR
+ SCR
Optimiz
e
Optimize
SNCR+
Number
Case (ppb)
t line
+ SOA
CC
SNCR+
SCR +
SOA
CC
SCR +
SOACC
90013007
CT
Fairfield
75.2
74.11
73.89
73.87
¦
73.60
73.56
73.54
73.47
90019003
CT
Fairfield
77.2
76.16
75.94
75.92
¦
75.64
75.61
75.58
75.51
90099002
CT
New Haven
73.8
72.65
72.39
72.37
¦
72.06
72.02
71.99
71.90
482010024
TX
Harris
75.6
74.74
75.30
75.24
¦
75.09
74.92
74.66
74.19
Table D-22. Average and Maximum Ozone DVs (ppb) for non-EGU NOx Emissions Level*
for Each Year Assessed.
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case Avg
DV (ppb)
Average Design Value (ppb)
Maximum Design Value (ppb)
2023
2024
2025
2023
2024
2025
90013007
CT
Fairfield
74.3
73.76
73.21
72.69
74.65
74.10
73.57
90019003
CT
Fairfield
76.9
76.36
75.83
75.32
76.66
76.12
75.61
90099002
CT
New Haven
71.7
71.10
70.53
69.98
73.18
72.59
72.03
482010024
TX
Harris
74.0
74.35
73.93
73.50
75.95
75.53
75.09
*non-EGU AQAT air quality estimates include EGU emission reductions at the $l,600/ton level.
Table D-23. Description of the Various Scenarios Modeled in AQAT.
Scenari
0
Cost
Threshol
d Level
Short
Descriptio
n
Description
1
$0
Eng base
202X Engineering Baseline +engineering nonCEMs
2
$500
$500
202X Engineering Baseline +engineering nonCEMs +$500/ton reductions (either replacement of
base or 2021 $l,600/ton (SOA CC+SCR optimization)).
3
$1,600
$1,600 w/o
CC
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu
50
-------
4
$1,600
$1,600 w
cc
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu + SOA
combustion controls
5
$3,900
$3,900
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu + SOA
combustion controls + SNCRs optimized
6
$5,800
$5,800
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu + SOA
combustion controls + SNCRs optimized + new SNCRs
7
$9,600
$9,600
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu + SOA
combustion controls + SNCRs optimized + new SCRs
8
NA
Straightline
base
202X Straight line emissions interpolation (an approximation of that used for Steps 1 and 2).
9
NA
ne^Analyzed...number oftons ofnon-EGU glass and cement, refined analysis.
10
$1,600 up
to $2,000
$1,600 w
CC & non-
EGU
202X Engineering Baseline +engineering nonCEMs + SCRs optimized at 0.08 lb/MMBtu + SOA
combustion controls + non-EGU glass and cement, refined analysis, others unchanged, below
$2,000 per ton.
Table D-24. Average and Maximum Ozone DVs (ppb) for the $1,600 Per Ton "Control
Scenario" for each Year Assessed.
Monitor
Identification
Number
State
County
CAMx
2023
Base
Case
(PPb)
Average Design Value (ppb)
Maximum Design Value (ppb)
2021
2022
2023
2024
2025
2021
2022
2023
2024
2025
90013007
CT
Fairfield
74.3
75.88
74.92
73.79
73.24
72.71
76.80
75.83
74.68
74.13
73.59
90019003
CT
Fairfield
76.9
78.08
77.36
76.39
75.85
75.34
78.38
77.66
76.69
76.15
75.64
90099002
CT
New Haven
71.7
73.32
72.32
71.13
70.56
70.01
75.47
74.44
73.22
72.62
72.06
482010024
TX
Harris
74.0
75.49
74.85
74.34
73.93
73.50
77.12
76.47
75.95
75.53
75.09
4. Comparison between the air quality assessment tool estimates
As described earlier, AQAT was calibrated using CAMx data from either 2016 or 2028.
Thus, it was possible to evaluate the estimates from the tool for a comparable scenario. The
average design values from AQAT for 2024 for the various scenarios are shown using the 2016-
based calibration factor (Table D-25), as well as the differences between the values in Tables D-
18 and D-25. The differences are shown in Table D-26. The AQAT values and the differences
in the table have been rounded to a hundredth of a ppb. For this set of scenarios, the differences
are moderate, with a maximum value of 0.53 ppb.
There can be a small offset between the estimates (based on the impacts of the two
different calibration factors). Within a set of estimates, the differences are likely to be
comparable. That is, comparing two different scenarios in Table D-18 with the same two
scenarios in Table D-25, produces similar changes in air quality. For example, the difference
between the engineering base and the $1,600 per ton level where SCR is optimized and
combustion controls are installed results in a difference of 0.30 ppb when the 2028 calibration
factor is applied and 0.28 ppb when the 2016 calibration factor is applied. The results of this
demonstrate that, considering the time and resource constraints faced by the EPA, the AQAT
provides reasonable estimates of air quality concentrations for each receptor, can provide
reasonable inputs for the multi-factor assessment, and can serve as a method to test for linkages
dropping below the threshold.
51
-------
Table D-25. 2024 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors Using the Calibration Factor
Assessment Tool Average Ozone Design Values (ppb).
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Straight
line
Engineering
Baseline
$500/to
n
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR+
SCR +
SOA
CC
New
SNCR +
Optimiz
e
SNCR+
SCR +
SOACC
New SCR
+
Optimize
SNCR+
SCR +
SOACC
90013007
CT
Fairfield
74.3
73.92
73.76
73.74
¦
73.55
73.53
73.51
73.47
90019003
CT
Fairfield
76.9
76.61
76.49
76.48
¦
76.33
76.31
76.29
76.26
90099002
CT
New Haven
71.7
71.30
71.12
71.10
¦
70.89
70.86
70.84
70.79
482010024
TX
Harris
74.0
73.74
74.08
74.04
¦
73.96
73.86
73.70
73.42
Table D-26. 2024 Average Ozone DVs (ppb) for NOx Emissions Cost Threshold Levels
($/ton) Assessed Using the Ozone AQAT for All Receptors.
Assessment Tool Average Ozone Design Values (ppb).
Monitor
Identification
Number
State
County
CAMx
2023 Base
Case (ppb)
Straight
line
Engineering
Baseline
$500/to
n
Optimi
ze SCR
+ SOA
CC
Optimi
ze
SNCR+
SCR +
SOA
CC
New
SNCR +
Optimiz
e
SNCR+
SCR +
SOACC
New SCR
+
Optimize
SNCR+
SCR +
SOACC
90013007
CT
Fairfield
74.3
0.16
0.22
0.23
¦
0.31
0.32
0.33
0.34
90019003
CT
Fairfield
76.9
0.23
0.34
0.34
¦
0.47
0.49
0.50
0.53
90099002
CT
New Haven
71.7
0.16
0.24
0.25
¦
0.33
0.35
0.35
0.38
482010024
TX
Harris
74.0
0.16
-0.05
-0.03
¦
0.03
0.09
0.19
0.37
E. Observations on Cost and Air Quality Factors in 2024
Section VII of the preamble discusses the cost and air quality factors in the multifactor
test and reaches the conclusions about the requisite level of emissions control for each year. The
higher cost thresholds of $5,800 per ton and $9,600 per ton associated with post-combustion
control installation were not considered in the 2021 multi-factor test as they pertain to
technologies not possible to install at a regional scale until 2025. However, for illustrative
purposes, EPA examined their reduction potential and air quality impact of these controls
starting in 2024. As described in sections C and D of this TSD, EPA quantified emissions from
upwind states at various levels of uniform NOx control stringency, each represented by uniform
control technology and corresponding NOx reduction and then evaluated the potential air quality
consequences of these potential reductions.
EPA combines costs, EGU NOx reductions, and corresponding improvements in
downwind ozone concentrations for different control levels in its multi-factor test. EPA
examines whether any receptor shifts from nonattainment to maintenance or from maintenance to
attainment. In 2024, the last receptor (Westport) in Fairfield Connecticut shifts from
nonattainment to maintenance at $1,600 per ton. This receptor is minimally above the 75.9
threshold in 2024 and is fully resolved by 2025. No additional changes are observed at higher
cost threshold levels in 2024 or 2025. EPA analysis also results in a "knee-in-the-curve" graph
(see preamble section VII for details about this figure for 2021). Figure E-l below illustrates the
52
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air quality improvement for the mitigation technologies up to $9,600 per ton for EGUs for 2024.
In Figure E-l, the 2024 "knee" is also at a point where emission budgets reflect a control
stringency with an estimated marginal cost of $1,600 per ton. The more stringent emission
budget levels (e.g., emission budgets reflecting mitigation technologies that cost $3,900 per ton
or greater) yield fewer additional emission reductions and fewer air quality improvements
relative to the increase in control costs. For the reasons described in section VII of the preamble,
the $1,600 per ton cost threshold is a reasonable stopping level for 2021 and 2022. Although
EPA evaluated the potential reductions from post combustion controls, that technology did not
qualify as an option for future years as EPA explains those controls are not possible on a regional
scale until 2025, and EPA expects no remaining air quality problems for the 2008 ozone NAAQS
standard in that year at the $1,600 per ton level.
Figure E-l. EGU Ozone Season NOX Reduction Potential in 11 Linked States and
Corresponding Total Reductions in Downwind Ozone Concentration at the Westport
Fairfield Connecticut Receptor for each Cost Threshold Level Evaluated in 2024.
0.5 | r 35,000
Cost per Ton
53
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Appendix A: State Emission Budget Calculations and Engineering
Analytics
See Excel workbook titled "State Emission Budget Calculations and Engineering Analytics" on
EPA's website and in the docket for this rulemaking
54
-------
Appendix B: Description of Excel Spreadsheet Data Files Used in
the AQAT
55
-------
EPA placed the OzoneAQATProposal.xlsx Excel workbook file in the Revised
CSAPR Update docket that contains all the emission and CAMx air quality modeling inputs and
resulting air quality estimates from the AQAT. The following bullets describe the contents of
various worksheets within the AQAT workbook:
State-level emissions
"2021 CAMD emiss" through "2026 CAMD emiss" contain EGU emissions
measurements and estimates for each state. Various columns contain the 2016 and 2019
OS measured emissions, CSAPR Update Budgets, and then emissions for the engineering
base along with each of the cost thresholds.
"2016fhl" contains state and source-sector specific ozone-season NOx emission totals
for the 2016 base case modeled in CAMx.
"2023fhl" contains state and source-sector specific ozone-season NOx emission totals for
the 2023 base case with EGU estimates from IPM modeled in CAMx.
"2023fhl_eng" contains state and source-sector specific ozone-season NOx emission
totals for the 2023 base case with EGU estimates from engineering analysis that could be
used in CAMx.
"2028fhl" contains state and source-sector specific ozone-season NOx emission totals for
the 2028 base case with EGU estimates from IPM modeled in CAMx.
"AQMEGUemiss" has a breakdown of the point EGU emission inventory used in the
air quality modeling, for the units with CEMs and those that don't (nonCEMs).
"calib emiss" has the total anthropogenic emissions by state for each of the base cases
modeled in CAMx. This worksheet also contains the fraction change for each of these
scenarios relative to the 2023fhl base case modeled in CAMx.
"2021_emiss_total", "2022_emiss_total", "2023_emiss_total", "2024_emiss_total",
"2025_emiss_total", "2026_emiss_total" each of these worksheets reconstructs total
anthropogenic emissions for the year, with various EGU emission inventories for
different cost threshold (including the engineering base case). The total anthropogenic
emissions can be found for each state in columns AX through BF. These totals are then
compared to the 2023fhl emission level to make a fractional change in emissions in
columns BH through BQ. Non-EGU emissions change and fractional change (inclusive
of EGU changes at $l,600/ton) are found in columns BP and BQ, respectively
Air quality modeling design values and contributions from CAMx
"DVs_2023fhl Contribs_raw" contains average and maximum design values as well as
state by state contributions for the 2023fhl base case modeled in CAMx.
"2023_contribs" contains average and maximum design values as well as state by state
contributions for the 2023fhl base case modeled in CAMx.
"DVs_2028fhl Contribs_raw" contains average and maximum design values as well as
state by state contributions for the 2028fhl base case modeled in CAMx.
"2028_contribs_2023receptors" contains average and maximum design values as well as
state by state contributions for the 2028fhl base case modeled in CAMx. The receptors
listed are the same receptors in the 2023fhl CAMx modeling.
"2028fhl DVs" contains average and maximum design values for each receptor in 2028
with EGU estimates from IPM.
56
-------
Calibration factor creation and assessment
"calib_2016" includes the calculation of the calibration factor based on the 2023
contributions, and percent change of 2016 emissions relative to 2023 emissions. The
calibration factor can be found in column BM. "calib_2028" includes the calculation of
the calibration factor based on the 2023 contributions, and percent change of 2028
emissions relative to 2023 emissions. The calibration factor can be found in column BM.
"calib comp" includes a summary of the three calibration factors (one based on 2016, one
based on 2023 with engineering EGU emissions, and the last one based on 2028).
Air quality estimates
"Summary DVs" contains the average and maximum design value estimates (rounded to
two decimal places) for receptors that were nonattainment or maintenance in the 2021
base case interpolation modeling. Values for each year (2021 through 2015), for each
cost threshold are shown. Grey filled cells are not considered viable scenarios. Each
scenario has the cost threshold shown for that run the linked and unlinked states.
Adjustment to cells J27 and J28will result in interactive adjustment for the other
worksheets and will adjust the average design values in column J and maximum design
values in column X.
"scenario_2021" through "scenario_2025" contains the average and maximum design
value estimates (as well as the individual state's air quality contributions) for a particular
scenario identified in cells G2 and G3. The fractional emission changes for each of the
linked and unlinked states are shown in rows 2 and 3.
"straightline_2021" through "straightline_2026" contains the average and maximum
design value estimates (as well as the individual state's air quality contributions) for the
emissions scenario that is a linear interpolation of the emissions between the 2016 base
case and the 2023fhl base case (or between the 2023fhl base case and 2028fhl base
case).
"control_2021" through "contol_2025" contains the average and maximum design value
estimates (as well as the individual state's air quality contributions) for a particular
scenario identified in cells G2 and G3. States that are "linked" to any receptor in the
geography are assigned the values in row 2 while nonlinked states are assigned the values
in row 3.
"scenario_2024 alt calibration" contains the average and maximum design value
estimates (as well as the individual state's air quality contributions) for a particular
scenario identified in cells G2 and G3. The fractional emission changes for each of the
linked and unlinked states are shown in rows 2 and 3. This uses the calibration factor
based on the 2016 air quality modeling, rather than the calibration factor based on the
2028 air quality modeling.
The individual cost level worksheets labeled: "$9600"; "$5800"; "$3900"; "$1600 w CC
& non-EGU"; "$1600 w CC"; "$1600 wo CC"; "$500"; "straightline_base"; and
"eng base" contain static air quality contributions and design value estimates for the four
receptors of interest for each of the years.
57
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Appendix C: IPM Runs Used in Transport Rule Significant
Contribution Analysis
58
-------
Table C-l lists IPM runs used in analysis for this rule. The IPM runs can be found in the
docket for this rulemaking under the IPM file name listed in square brackets in the table below.
Table Appendix C-l. IPM Runs Used in Transport Rule Significant Contribution Analysis
Run Name
[IPM File Namel
Description
Air Quality Modeling Base Case
EPA617BC75L
Model run used for the air quality modeling base case at steps 1
and 2, which includes the national Title IV S02 cap-and-trade
program; NOx SIP Call; the Cross-State Air Pollution trading
programs, and settlements and state rules. It also includes key
fleet updates regarding new units, retired units, and control
retrofits that were known by Fall of 2019.
Illustrative Base Case
EPA617_CURR_ 1 g
Model run used as the base case for the Illustrative Analysis of
cost threshold analyses. Based on the air quality modeling base
case, but with projected retirements and retrofits in 2021 limited.
Illustrative Base Case with optimization
technology + LNB upgrade
EPA617_CURR_5d
Imposes state-level generation constraints starting in 2021 for
fossil-fuel fired units greater than 25 MW that is equal to
Illustrative Base Case levels. Also assumes optimization of
existing post-combustion controls and upgrade of combustion
controls if mode 3
-------
Illustrative $9,600 per ton Cost Threshold
EPA617_CURR_7d
Same as Illustrative Base Case with optimization technology,
LNB, + SCR retrofit, but with $9,600/OS NOx ton OS ton price
signal applied in the ozone-season.
Illustrative $500 per ton Cost Threshold
EPA617_CURR_1 Od
Same as Illustrative Base Case, but with $500/OS NOx ton OS
ton price signal applied in the ozone-season.
Illustrative More Stringent Policy Case
EPA617CURR13
Same as Illustrative Base Case, but with ozone season emissions
budgets with variability limits applied for the 12 states reflecting
$1600 per OS NOx ton through 2023 and $9600 per OS NOx ton
for 2025 model run year, along with a regional cap equal to the
sum of the 12 states' budgets for each year.
Illustrative LessStringent Policy Case
EPA617CURR12
Same as Illustrative Base Case, but with ozone season emissions
budgets with variability limits applied for the 12 states reflecting
$500 per OS NOx ton starting in 2021, along with a regional cap
equal to the sum of the 12 states' budgets for each year.
Proposed Policy Scenario
EPA617CURR14
Same as Illustrative Base Case, but with ozone season emissions
budgets with variability limits applied for the 12 states reflecting
$1600 per OS NOx ton starting in 2021, along with a regional
cap equal to the sum of the 12 states' budgets for each year.
60
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Appendix D: Ozone-Season NOx Emissions Limits for IPM Modeling
Table Appendix D-l. State and Regional Caps for IPM Final Case Analysis for the Proposed Rule
Policy Case
Less Stringent Case
($500/ton)
More Stringent Case
($9,600/ton)
Assurance Level (121% of
Budget)
Assurance Level (121% of
Budget)
Assurance Level (121% of
Budget)
2021
2023
2025
2021
2023
2025
2021
2023
2025
Illinois
11,428
10,161
10,161
11,697
10,381
10,381
11,428
10,161
8,642
Indiana
15,125
14,518
11,430
18,969
18,399
15,250
15,125
14,518
10,000
Kentucky
17,405
14,443
14,443
18,883
18,883
18,883
17,405
14,443
10,712
Louisiana
18,636
17,994
17,994
18,685
18,685
18,685
18,636
17,994
15,289
Maryland
1,842
1,812
1,812
1,894
1,894
1,894
1,842
1,812
1,499
Michigan
15,399
11,862
11,633
15,875
12,479
12,240
15,399
11,862
8,851
New Jersey
1,517
1,517
1,517
1,629
1,629
1,629
1,517
1,517
1,521
New York
3,796
3,796
3,774
3,850
3,850
3,828
3,796
3,796
3,654
Ohio
11,622
11,708
11,708
18,743
18,828
18,828
11,622
11,708
11,042
Pennsylvania
9,771
9,771
9,771
13,899
13,899
13,899
9,771
9,771
9,169
Virginia
5,498
4,424
4,108
5,552
5,048
4,729
5,498
4,424
3,656
West Virginia
16,560
14,290
14,290
18,170
16,059
16,059
16,560
14,290
11,578
Region Cap (Budget
Total)
106,280
96,112
93,092
122,187
115,729
112,648
106,280
96,112
79,019
61
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Appendix E: Generation Shifting Analysis
Table Appendix E-l. Tons of EGU NOx Reduction Potential from Shifting Generation Compared to Adjusted Historical
Emissions.
2021
2022
2023
2024
Baseline
(tons)
Reductions
from
generation
shifting at
$1600 per
ton (tons)
Reductions
from
generation
shifting
(%)
Baseline
(tons)
Reductions
from
generation
shifting at
$1600 per
ton (tons)
Reductions
from
generation
shifting
(%)
Baseline
(tons)
Reductions
from
generation
shifting at
$1600 per
ton (tons)
Reductions
from
generation
shifting
(%)
Baseline
(tons)
Reductions
from
generation
shifting at
$1600 per
ton (tons)
Reductions
from
generation
shifting
(%)
Illinois
9,688
53
1%
9,652
53
1%
8,599
50
1%
8,599
50
i%
Indiana
15,856
317
2%
15,383
314
2%
15,383
314
2%
12,755
269
2%
Kentucky
15,588
(11)
0%
15,588
(11)
0%
15,588
(11)
0%
15,588
(11)
0%
Louisiana
15,488
86
1%
15,488
86
1%
15,488
86
1%
15,488
86
1%
Maryland
1,565
1
0%
1,565
1
0%
1,565
1
0%
1,565
1
0%
Michigan
13,893
1,166
8%
13,893
1,166
8%
11,056
1,121
10%
10,841
1,096
10%
New Jersey
1,346
(1)
0%
1,346
(1)
0%
1,346
(1)
0%
1,346
(1)
0%
New York
3,187
50
2%
3,187
50
2%
3,187
50
2%
3,169
50
2%
Ohio
15,832
315
2%
15,917
328
2%
15,917
328
2%
15,917
328
2%
Pennsylvania
11,570
338
3%
11,570
338
3%
11,570
338
3%
11,570
338
3%
Virginia
4,592
46
1%
4,175
45
1%
4,175
45
1%
3,912
44
1%
West
Virginia
15,165
105
1%
15,165
105
1%
13,407
95
1%
13,407
95
1%
Total
123,770
2,465
2%
122,929
2,474
2%
117,280
2,416
2%
114,156
2,345
2%
62
-------
63
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Appendix F: Feasibility Assessment for Engineering Analytics Baseline
Similar to CSAPR Update Final Action, EPA analyzed and confirmed that the assumed fleet operations in its emissions and budget
estimates were compatible with future load requirements by verifying that new units in addition to the existing fleet would provide
enough generation, assuming technology-specific capacity factors, to replace the retiring generation expected to occur in years 2021
through 2024. EPA assessed generation adequacy specific to the 12 states covered under this action. Moreover, EPA uses these
observations to determine whether any assumed replacement generation from existing units is necessary to offset the announced
retirements and continue to satisfy electricity load. Alternatively, EPA looked at whether the combination of new units (both fossil
and non-fossil) provide sufficient new generation to replace retiring generation. In this case, EPA found that the new unit generation
from fossil and renewable generation would exceed the generation from retiring units, suggesting that no replacement generation from
existed units is needed. Moreover, EPA found the change in generation from the covered fossil units to be within the observed
historical trend.
EPA first identified the collective heat input and generation from the 12 states covered in this action and compared it to
historical trends for these same states. This illustrated that the assumed heat input and generation from fleet turnover was
consistent with recent historical trends (see tables Appendix F-l and Appendix F-2 below).
EPA then identified the 2020 Energy Information Administration's Annual Energy Outlook (EIA AEO) growth projections
from 2019 through 2024 electricity demand levels ( 0.8%) from its reference case, and estimated future year generation
matching this sector growth rate.29
Next, EPA identified the amount of generation in its baseline factoring in retirements and new fossil units. EPA compared this
value to 2019 reported levels and the trend in fossil generation from 2016 to 2019 to verify that EPA's assumed baseline was
well within the assumed trend for fossil generation in the 12 states. For example, generation from covered fossil sources in
these 12 states has dropped at an average rate greater than 2% per year between 2016 and 2019 (410 TWh to 384 Twh).
However, EPA's baseline generation from covered fossil sources for the 12 states assumes that the average rate of decline is
less than 1% per year (384 TWh to 379 TWh) which is well within the observed historical trend.(See Table Appendix F-2).
29 Department of Energy, Annual Energy Outlook 2020. Available at https://www.eia. gov/outlooks/aeo/data/browser/#/?id=8-
AE02020&cases=ref2020&sourcekey=0
64
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EPA then identified new RE capacity under construction, testing, or in site prep by 2021. For years beyond 2021, EPA also
identified new capacity that was planned but with regulatory approvals pending for years 2022 and beyond (as this capacity is
unlikely to have yet started construction).30
EPA calculated and added the RE generation values to the fossil baseline to estimate future year generation in the state (see
Table Appendix F-3). EPA used a capacity factor of 42.7% for wind, 21.6% for solar, and 65% for NGCC%.
Using these technology-specific capacity factors based on past performance and IPM documentation, EPA anticipated over 20
TWh from new generation already under construction or being planned. This combined with the baseline exceeds the expected
generation load for the 12 states.
Not only is the baseline generation within the recent historical fossil generation trend (See Table Appendix F-2) on its own, but
the the potential new generation (over 20 TWh) when added to the baseline values is significantly greater than historical fossil
generation for the 12 states with assumed annual growth of .8%. This suggests that available capacity would serve load
requirements.
Table Appendix F-l: Heat Input Change Due to Fleet Turnover (Historical and Future)
Reported Heat Input from Covered
Fossil Units (TBtu)
Assumed Heat Input from Covered Fossil
(TBtu)
2016
2017
2018
2019
2021
2022
2023
2024
Illinois
383.4
333.2
379.3
311.7
273.2
272.5
257.3
257.3
Indiana
415.6
379.1
432.3
356.5
356.5
352.3
352.3
302.3
Kentucky
360.2
319.1
351.3
313.8
286.9
286.9
286.9
286.9
Louisiana
331.8
302.0
312.2
317.4
339.9
339.9
339.9
339.9
Maryland
108.7
76.9
95.7
83.0
82.5
82.5
82.5
82.5
Michigan
331.5
317.0
344.4
316.1
315.0
315.0
302.8
296.0
New Jersey
178.7
145.1
150.8
144.9
144.9
144.9
144.9
144.9
New York
269.7
199.7
228.6
195.6
214.2
214.2
214.2
214.1
Ohio
429.0
401.0
392.2
391.2
376.2
392.0
392.0
392.0
30 Department of Energy, EIAForm 860, Generator Form 3-1. 2019 Early Release. Available at https://www.eia.gov/electricity/data/eia860/
65
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Pennsylvania
515.8
473.1
460.1
485.2
505.5
505.5
505.5
505.5
Virginia
259.9
228.2
241.0
237.9
237.5
234.5
234.5
225.5
West Virginia
323.1
324.0
303.6
287.9
285.3
285.3
260.0
260.0
Total
3,907.4
3,498.3
3,691.5
3,441.0
3,417.6
3,425.5
3,372.8
3,306.8
Table Appendix F-2: Generation Change Due to Fleet Turnover (Historical and Future)
Reported Generation from
Covered Fossil Units (TWh)
Assumed Generation from Covered
Fossil (TWh)
State
2016
2017
2018
2019
2021
2022
2023
2024
Illinois
38.6
33.9
38.7
32.7
28.9
28.8
27.2
27.2
Indiana
42.7
39.4
45.8
38.8
38.8
38.4
38.4
33.8
Kentucky
37.1
33.8
37.2
33.6
31.0
31.0
31.0
31.0
Louisiana
36.0
33.1
34.6
36.1
39.7
39.7
39.7
39.7
Maryland
11.0
7.9
10.4
9.5
9.4
9.4
9.4
9.4
Michigan
31.8
30.8
34.0
31.7
31.6
31.6
32.1
31.4
New Jersey
20.5
17.2
18.2
18.0
18.0
18.0
18.0
18.0
New York
30.0
22.5
25.6
22.5
25.5
25.5
25.5
25.5
Ohio
47.9
45.1
45.5
45.8
44.4
46.9
46.9
46.9
Pennsylvania
53.6
49.7
49.8
56.7
61.1
61.1
61.1
61.1
Virginia
27.8
25.5
27.1
28.9
28.9
28.9
28.9
28.0
West Virginia
33.9
33.8
31.8
29.9
29.9
29.9
27.2
27.2
Total
410.9
372.9
398.7
384.1
387.1
389.2
385.4
379.2
Table Appendix F-3: Assumed Baseline OS Generation and Expected New Build Generation (TWh)
2019
2020
2021
2022
2023
2024
2019 Generation Levels with .8% growth
384.1
387.2
390.3
393.4
396.5
399.7
Assumed Baseline Fossil Generation with
Known Fossil Retirement and Fossil New Build*
384.1
387.1
389.2
385.4
379.2
New Build (Non-Fossil)
4.6
7.2
7.2
7.2
Total
391.7
396.4
392.6
386.4
Total (including planned NGCC new build)***
412.4
408.6
402.4
66
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includes "committed" new fossil that is under
construction
**Likely understates new RE as it may not show up in EIA 860 far in advance due to shorter
installation time. Note, this assumes no new RE in 2023 and beyond.
***lncludes new fossil that is planned for 2022 or later, but with approval
pending
67
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Appendix G: State Emission Budgets and Variability Limits
Table Appendix G-l: State Emission Budgets and Variability Limits (tons)
2021
2022
2023
2024
State
Emission
Budgets
Variability
Limit
Emission
Budgets
Variability
Limit
Emission
Budgets
Variability
Limit
Emission
Budgets
Variability
Limit
Alabama
7,786
1,635
7,610
1,598
7,610
1,598
7,610
1,598
Arkansas
8,708
1,829
8,330
1,749
8,330
1,749
8,330
1,749
Georgia
7,808
1,640
7,808
1,640
7,808
1,640
7,808
1,640
Illinois
9,444
1,983
9,415
1,977
8,397
1,763
8,397
1,763
Indiana
12,500
2,625
11,998
2,520
11,998
2,520
9,447
1,984
Iowa
7,714
1,620
7,626
1,601
7,266
1,526
7,266
1,526
Kansas
5,384
1,131
5,384
1,131
5,384
1,131
5,384
1,131
Kentucky
14,384
3,021
11,936
2,507
11,936
2,507
11,936
2,507
Louisiana
15,402
3,234
14,871
3,123
14,871
3,123
14,871
3,123
Maryland
1,522
320
1,498
315
1,498
315
1,498
315
Michigan
12,727
2,673
11,767
2,471
9,803
2,059
9,614
2,019
Mississippi
6,315
1,326
6,315
1,326
6,315
1,326
6,315
1,326
Missouri
11,358
2,385
11,358
2,385
11,079
2,327
11,079
2,327
New Jersey
1,253
263
1,253
263
1,253
263
1,253
263
New York
3,137
659
3,137
659
3,137
659
3,119
655
Ohio
9,605
2,017
9,676
2,032
9,676
2,032
9,676
2,032
Oklahoma
8,717
1,831
8,717
1,831
8,717
1,831
8,717
1,831
Pennsylvania
8,076
1,696
8,076
1,696
8,076
1,696
8,076
1,696
Tennessee
4,367
917
4,367
917
4,367
917
4,367
917
Texas
42,312
8,886
41,995
8,819
41,807
8,779
41,807
8,779
Virginia
4,544
954
3,656
768
3,656
768
3,395
713
West
Virginia
13,686
2,874
12,813
2,691
11,810
2,480
11,810
2,480
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Wisconsin
4,875
1,024
4,875
1,024
4,622
971
4,104
862
Note - State budgets would be limited to not exceed their CSAPR Update budget level. This would only impact Mississippi as they
would continue to have an emissions budget of 6,315 tons if they were to participate in the Group 3 ozone-season NOx program.
69
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