EPA-457/R-07-001
April 2007
Technical Support Document for the Prevention of
Significant Deterioration and Nonattainment Area New
Source Review: Emissions Increase Test for Electric
Generating Units
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Policy Division
New Source Review Group
Research Triangle Park, North Carolina
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SB.
Technical Support Document for Prevention of
Significant Deterioration And Nonattainment Area New
Source Review: Emissions Increase Test for Electric
Generating Units
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Table of Contents
List of Figures i
List of Tables ii
Chapter 1. Overview 1-1
Chapter 2. The Integrated Planning Model (IPM) 2-1
Chapter 3. NSR Availability Scenarios-SO2 andNOx 3-1
3.1 NSR Availability Scenarios 3-1
3.2 SO2 andNOx Control Device Installation 3-4
3.3 SO2 andNOx National Emissions • 3-5
3.4 SO2 and NOX Local Emissions Impact 3-6
3.5 SO2 and NOX Impact on Air Quality .....3-16
Chapter 4. NSR Availability Scenarios- PM2.5, VOC, and CO 4-1
4.1 NSR Availability Scenario 4-1
4.2 PM2.5, VOC, and CO Control Device Installation 4-1
4.3 PM2.5, VOC, and CO National Emissions 4-2
4.4 PM2.5, VOC, and CO Local Emissions Impact 4-3
4.5 PM2.5, VOC, and CO Air Quality 4-13
Chapter 5. NSR Efficiency Scenarios- SO2 and NOX 5-1
5.1 NSR Efficiency Scenario 5-1
5.2 SO2 and NOX Control Device Installation 5-4
5.3 SO2 and NOX National Emissions 5-5
5.4 SO2 andNOx Local Emissions Impact 5-6
5.5 SO2 and NOX Air Quality Impact.... 5-14
Chapter 6. NSR Efficiency Scenarios- PM2.5, VOC, and CO 6-18
6.1 NSR Efficiency Scenario 6-18
6.2 PM2.5, VOC, and CO Control Device Installation 6-18
6.3 PM2.5, VOC, and CO National Emissions 6-19
6.4 PM2.5, VOC, and CO Local Emissions Impact 6-21
6.5 PM2.5, VOC, and CO Air Quality 6-28
Appendix A Net Change in 2020 EGU SO2 and NOX Emissions Under NSR Availability
and Efficiency Compared to Total State SO2 andNOx Emissions A-l
Appendix B Net EGU CO Emissions Change in Counties that are Nonattainment for CO
NAAQS B-l
List of Figures
Figure 3.1 2020 County-level SO2 Emissions Changes With a 4% Increase in EGU
Availability 3-17
Figure 3.2 2020 County-level NOX Emissions Changes With a 4% Increase in EGU
Availability 3-18
Figure 4.1 2020 PM2.s County-level .Emissions Changes With a 4% Increase in EGU
Availability 4-16
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Figure 4.2 2020 County-level VOC Emissions Changes With a 4% Increase in EGU
Availability 4-17
Figure 4.3 2020 County-level CO Emissions Changes With a 4% Increase in EGU
Availability 4-18
Figure 5.1 The Value of Efficiency 5-2
Figure 5.2 2020 County-level SOa Emissions Changes with Efficiency Increase 5-16
Figure 5.3 2020 County-level NOX Emissions Changes with Efficiency Increase 5-17
Figure 6.1 2020 County Level PMi.s Emissions Changes - Efficiency Scenario 6-31
Figure 6.2 2020 County Level VOC Emissions Changes - Efficiency Scenario 6-32
Figure 6.3 2020 County Level CO Emissions Changes - Efficiency Scenario 6-33
f
List of Tables
Table 3.1 2020 National EGUs With Emission Controls Under NSR Availability
Scenarios 3-4
Table 3.2 National EGU Emissions Under NSR Availability Scenarios Compared to
CAIR/CAMR/CAVR 2020 (tpy) 3-5
Table 3.3 Changes in County-level SO2 Emissions NSR Availability (4%) Scenario
Compared to CAIR/CAMR/CAVR 2020 3-8
Table 3.4 Changes in County-level NOX Emissions NSR Availability (4%) Scenario
Compared to CAIR/CAMR/CAVR 2020 3-9
Table 3.5 Largest County-level Decreases and Increases Under NSR Availability (4%)
Scenario (tpy) 3-12
Table 4.1 EGU Emissions As Percent of 2020 National Emissions (tpy) 4-2
Table 4.2 National EGU Emissions Under NSR Availability Scenario Compared to
CAIR/CAMR/CAVR 2020 (tpy) 4-3
Table 4.3 Changes in County-level PM2.s Emissions NSR Availability (4%) Scenario 4-4
Table 4.4 Changes in County-level VOC Emissions NSR Availability (4%) Scenario.4-4
Table 4.5 Changes in County-level CO Emissions NSR Availability (4%) Scenario.... 4-5
Table 4.6 Largest County-level Decreases and Increases of Primary PM2.5 Under NSR
Availability (4%) Scenario (tpy) 4-9
Table 4.7 Largest County-level Decreases and Increases of VOC Under NSR
Availability (4%) Scenario (tpy) 4-10
Table 4.8 Largest County-level Decreases and Increases of CO Under NSR Availability
(4%) Scenario (tpy) 4-11
Table 5.1 2020 National EGUs with Emission Controls Under NSR Efficiency 5-5
Table 5.2 National EGU Emissions Under NSR Efficiency Scenario Compared to
CAIR/CAMR/CAVR 2020 (tpy) 5-6
Table 5.3 Changes in County-level SO2 Emissions NSR Efficiency Scenario Compared
to CAIR/CAMR/CAVR 2020 5-7
Table 5.4 Changes in County-level NOX Emissions NSR Efficiency Scenario Compared
to CAIR/CAMR/CAVR 2020 5-7
Table 5.5 Largest County-level Decreases and Increases of SO2 and NOX Under NSR
Efficiency Scenario (tpy) 5-10
Table 6.1 EGU Emissions As Percent of 2020 National Emissions (tpy) 6-19
ii
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Table 6.2 National EGU Emissions Under NSR Efficiency Scenario Compared to
CAIR/CAMR/CAVR 2020 (tpy) 6-20
Table 6.3 Changes in County-level PM2.5 Emissions NSR Efficiency Scenario 6-21
Table 6.4 Changes in County-level VOC Emissions NSR Efficiency Scenario 6-22
Table 6.5 Changes in County-level CO Emissions NSR Efficiency Scenario 6-22
Table 6.6 Largest County-level Decreases and Increases of Primary PM2.5 Under NSR
Efficiency 6-25
Table 6.7 Largest County-level VOC Decreases and Increases Under NSR Efficiency
Scenario 6-26
Table 6.8 Largest County-level CO Decreases and Increases Under NSR Efficiency
Scenario 6-27
in
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Chapter 1.
Overview
This Technical Support Document contains information and analyses supporting
the proposed rule Prevention of Significant Deterioration, Nonattainment New Source
Review, and New Source Performance Standards: Electric Generating Units (70 FR
61081). Our supplemental proposal contains additional regulatory and policy
background for the proposed rule, as well as the specific regulatory language. This TSD
contains specific information about three separate analyses conducted in support of the
proposed regulatory approach, as included in the proposal and the supplemental proposal.
Our analyses rely on the Integrated Planning Model (IPM), which we describe in
Chapter 2. Chapters 3 and 4 contain the results of our first analysis, that of the effect of
changing from an annual to an hourly emissions increase test, under which a source may
operate more hours annually. We call this analysis the NSR Availability Scenario.
Chapter 3 examines the Availability Scenarios as they relate to SO2 and NOX emissions.
Chapter 4 examines the Availability Scenarios as they relate to PIVb.s, VOC, and CO
emissions.
Chapter 5 contains our second analysis, which we call the NSR Efficiency
Analysis. This analysis assumes an increase in efficiency. Aside from independent
factors such as climate and economy, efficiency is a primary determinant of the hours of
operation of a given EGU. Neither the current annual emissions increase test nor any of
the proposed EGU emission increase test alternatives directly measure an EGU's
efficiency. However, the output-based alternatives (Alternatives 2, 4, and 6 in the
proposal), which are expressed in a Ib/KWh-hour format that measures mass emissions
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1-Overview
per unit of electricity, are closely related to an EGU's efficiency. Thus, an output-based
test encourages efficient units, which has well-recognized benefits. We anticipate that
the output-based alternatives in particular, and the other alternatives to a lesser extent,
could have the effect of encouraging EGUs to increase their efficiency. As none^of the
emission increase tests would directly measure the effect of increased efficiency on
emissions, we examined the effect of increasing efficiency in a separate analysis.
Chapter 5 includes the result of the Efficiency Analysis as it relates to SC>2 and NOX;
Chapter 6 includes the results of the Efficiency Analysis as it relates to PM2.5, VOC, and
CO.
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Chapter 2.
The Integrated Planning Model (IPM)
We use the IPM to analyze the projected impact of environmental policies on the
electric power sector in the 48 contiguous States and the District of Columbia. The IPM
is a multi-regional, dynamic, deterministic linear programming model of the entire
electric power sector. It provides forecasts of least-cost capacity expansion, electricity
dispatch, and emission control strategies for meeting energy demand and environmental,
transmission, dispatch, and reliability constraints. We have used the IPM extensively to
evaluate the cost and emissions impacts of proposed policies to limit emissions of sulfur
dioxide (802) and nitrogen oxides (NOX) from the electric power sector. The IPM was a
key analytical tool in developing the Clean Air Interstate Regulation (CAIR; see 70 FR
25162). However, the IPM capabilities and results are not limited to projections for
CAIR States. It includes data for and projects emissions and controls for the electric
sector in the contiguous United States.
Each IPM model run is based on emissions controls on existing units, State
regulations, cost and performance of generating technologies, 862 and NOX heat rates,
natural gas supply and prices, and electricity demand growth assumptions. This input is
updated on a regular basis. We used the IPM to project EGU SC^ and NOX controls,
emissions, and air quality in 2020 considering projected emission controls under the
Clean Air Interstate Rule, Clean Air Mercury Rule, and Clean Air Visibility Rule. For
convenience, we refer to this projection as the CAIR/CAMR/CAVR 2020 Base Case
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2-IPM
Scenario or, more simply, the Base Case Scenario. The IPM model used for this scenario
isIPMv.2.1.9.1
The IPM v 2.1.9 is based on 2,053 model plants, which represent 13,819 EGUs,
including 1,242 coal-fired EGUs.2 This represents all existing EGUs in the contiguous
United States as of 2004, as well as new units that are already planned or committed, and
new units that are projected to come online by 2007. The underlying data for these plants
is contained in the National Electric Energy Data System (NEEDS), which contains
geographic location, fuel use, emissions control, and other data on each existing EGU.
NEEDS data for existing EGUs comes from a number of sources, including information
submitted to EPA under the Title IV Acid Rain Program and the NOX Budget Program, as
well as information submitted to the Department of Energy's Energy Information
Agency, on Forms EIA 860 and 767. That is, the underlying data for each existing EGU
in the IPM v.2.1.9 is information from an actual EGU in operation as of 2004 that has
been submitted to the EPA or the DOE.
The IPM v.2.1.9 model also accounts for growth in the EGU sector that is
projected to occur through new builds, including both planned-committed units and
potential units. Planned-committed EGUs are those that are likely to come online,
because ground has been broken, financing obtained, or other demonstrable factors
indicate a high probability that the EGU will come online. Planned-committed units in
1 Complete documentation for IPM, including the Base Case Scenario, is available at
http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html. See also Docket Item
EPA-HQ-OAR-2005-0163, DCN 01.
2 See the NEEDS 2004 documentation for IPM v.2.1.9 in Exhibit 4-6, which can be
found at http://www.epa.gov/airmarkets/progsregs/epa-ipm/past-modeling.html. See
also Docket Item EPA-HQ-OAR-2005-0163, DCN 02.
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2-IPM
IPM v.2.1.9 were based on two information sources: RDI NewGen database (RDI)
distributed by Platts (www.platts.com) and the inventory of planned-committed units
assembled by DOE, Energy Information Administration, for their Annual Energy
Outlook. Potential EGUs are those units that may be built at a future date in response to
electricity demand. In IPM v.2.1.9, potential new units are modeled as additional
capacity and generation that may come online in each model region.
IPM v.2.1.9 also accounts for emission limitations due to State regulations and
enforcement actions. It includes State regulations that limit SO2 and NOX emissions from
EGUs. These are included Appendix 3-2 of the IPM documentation, available at
http://www.epa.gov/airmarkets/epa-ipm/.3 The IPM v.2.1.9 includes NSR settlement
requirements for the following six utility companies: SIGECO, PSEG Fossil, TECO, We
Energies (WEPCO), VEPCO and Santee Cooper. The settlements are included as they
existed on March 19, 2004. A summary of the settlement agreements is included in
Appendix 3-3 of the IPM documentation and is available at
http://www.epa.gov/airmarkets/epa-ipm/.4
In the IPM, EPA does not attempt to model unit-specific decisions to make
equipment change or upgrades to non-environmental related equipment that could affect
efficiency, availability or cost to operate the unit (and thus the amount of generation).
Modeling such decisions would require either obtaining or making assumptions about the
condition of equipment at units and would greatly increase model size, limiting its
applicability in policy analysis. Specifically, IPM does not project that any particular
3 See also Docket Item EPA-HQ-OAR-2005-0163, DCN 03.
4 See also Docket Item EPA-HQ-OAR-2005-0163, DCN 03.
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2-IPM
existing EGU will make physical or operational changes that increase its efficiency,
generation, or emissions. Therefore, IPM does not predict which particular EGUs will be
subject to the major NSR applicability requirements. However, as discussed below, EPA
has specially designed inputs to IPM that provide useful information directly related to
major NSR applicability requirements. As we discuss below, these inputs are in the form
of constraints to the IPM model rather than changes on a unit-by-unit basis.
Reliability is a critical element of power plant operation. Reliability is generally
defined as whether an EGU is able to operate over sustained periods at the level of output
required by the utility. One measure of reliability is availability, the percentage of total
time in a given period that an EGU is available to generate electricity. An EGU is
available if it is capable of providing service, regardless of the capacity level that can be
provided. Availability is generally measured using the number of hours that an EGU
operates annually. For example, if an EGU operated 8,760 hours in a particular year, it
was 100 percent available. Each year, EGUs are not available for some number of hours
due to planned outages, maintenance outages, and forced outages.
IPM v.2.1.9 uses information from the North American Electric Reliability
Council (NERC)'s Generator Availability Data System (GADS) to determine the annual
availability for EGUs. The GADS database includes operating histories—some dating
back to the early 1960's—for more than 6,500 EGUs. These units represent more than
75 percent of the installed generating capacity in the United States and Canada. Each
utility provides reports, detailing its units' operation and performance. The reports
include types and causes of outages and deratings, unit capacity ratings, energy
production, fuel use, and design information. GADS provides a standard set of
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2- IPM
definitions for determining how to classify an outage on a unit, including planned
outages, maintenance outages, and forced outages. The GADS data are reported and
summarized annually. A planned outage is the removal of a unit from service to perform
work on specific components that is scheduled well in advance and has a predetermined
start date and duration (for example, annual overhaul, inspections, testing). Turbine and
boiler overhauls or inspections, testing, and nuclear refueling are typical planned outages;
A maintenance outage is the removal of a unit from service to perform work on
specific components that can be deferred beyond the end of the next weekend, but
requires the unit be removed from service before the next planned outage. Typically,
maintenance outages may occur any time during the year, have flexible start dates, and
may or may not have predetermined durations: For example, a maintenance outage
would occur if an EGU experiences a sudden increase in fan vibration. The vibration is
not severe enough to remove the unit from service immediately, but does require that the
unit be removed from service soon to check the problem and make repairs.
A forced outage is an unplanned component failure or other breakdown that
requires the unit be removed from service immediately, that is, within 6 hours, or before
the end of the next weekend. A common cause of forced outages is boiler tube failure.
Each EGU must report the number of hours due to planned outages, maintenance
outages, and forced outages to NERC annually. NERC summarized the data for all coal-
fired EGUs over the period from 2000 - 2004 in its Annual Unit Performance Statistics
Report.5 For the years 2001 - 2004, the average annual planned outage hours for all
5 The report is available at http://www.nerc.com/~gads/ and in the Docket as Item EPA-
HQ-OAR-2005-0163, DCN 04.
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2-IPM
EGUs was 572.09 (about 23 days), the average annual maintenance outage hours for all
EGUs was 156.27 (about 6 days), and the average annual forced outage hours for all
coal-fired EGUs was 348.75 (about 14 days). The total annual unavailable hours were
1,087.57, which is 15.1 percent of the total annual hours of 8,760. Based on this data, the
IPM v.2.1.9 assumed coal-fired EGUs were 85 percent available. As just noted, of the
1,087.57 total unavailable hours, 348.75 were forced outage hours, which means that
coal-fired EGUs were unavailable due to forced outages approximately 4 percent of the
hours in a year for the years 2000 - 2004.
We recently released a graphic presentation of electric power sector results under
CAIR/CAMR/CAVR. Entitled "Contributions of CAIR/CAMR/CAVR to NAAQS
Attainment: Focus on Control Technologies and Emission Reductions in the Electric
Power Sector," it is available at http://www.epa.gov/airmarkets/cair/analyses.html.6
As this presentation shows, under the CAIR/CAMR/CAVR 2020 Base Case Scenario,
local SC>2 and NOX emissions generally decrease, average SOa and NOX emission rates
decrease, and national SOa and NOX emissions decrease. As this document also shows,
half of the coal-fired generation is expected to have scrubbers and either SCR or SNCR
by 2020. These effects occur throughout the contiguous 48 States, not just in the CAIR
States.
6 Also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 05.
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Chapters.
NSR Availability Scenarios- SO2 and NOX
3.1 NSR Availability Scenarios
We developed two IPM scenarios, which we call the CAIR/CAMR/CAVR NSR
Availability Scenarios, or, more simply, the NSR Availability Scenarios, to examine how
changes to major NSR applicability under the proposed regulations could, by allowing
sources to make repairs or improvements that increase hours of operation, affect
emissions and control technology installation. These IPM scenarios are based on the
CAIR/CAMR/CAVR 2020 Scenario, which employs the IPM v.2.1.9 model that we
describe in Chapter 2 of this document, including information for the electric sector in the
contiguous United States. Chapter 2 also contains specific information on the
assumptions about EGU assumptions in the IPM v.2.1.9.
The parameters in the IPM model are based on availability for 6,500 EGUs over
the 5-year period from 2000 - 2004. In the NSR Availability scenarios, however, we
changed the parameters in IPM v.2.1.9 consistent with the way EGUs might operate
under the more flexible regulations that we are proposing. That is, we assumed that some
owner/operators might make changes that increase the hours of operation of some EGUs.
It is unlikely that an owner/operator would be able to make changes that reduce the hours
that an EGU is unavailable due to a planned outage or a maintenance outage. However,
EGUs would be able to make changes that increase their hours of operation as a result of
a reduction in the number and length of forced outages. Specifically, with more
flexibility concerning the number of hours EGUs operate annually, EGU owner/operators
may replace broken-down equipment in an effort to reduce the number of forced outages.
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3- NSR Availability- SO2 and NOX
Such actions would increase the safety, reliability, and efficiency of EGUs, consistent
with one of our primary policy goals for our proposed regulations.
Therefore, in the NSR Availability Scenario, we assumed that coal-fired EGUs
would be able to make changes that affect forced outage hours in two, alternative, ways:
(1) coal-fired EGUs would reduce their forced outage hours by half (2 percent increase in
availability); and (2) coal-fired EGUs would have no forced outage hours (4 percent
increase in availability). Therefore, in the first model run, we increased the coal-fired
availability by 2 percent, from 85 percent to 87 percent annually. In the second NSR
EGU run, we increased coal-fired availability by 4 percent, to 89 percent annually. We
believe it is unlikely that an EGU would be able to make repairs that completely
eliminate forced outage hours. However, we wanted a robust examination of changes
that could impact emissions and air quality.7 We therefore made the very conservative
assumption to increase to EGU availability by 2 percent and 4 percent over the actual
historical hours of operation for 6,500 EGUs over the years 2000 - 2004. All other
information in the NSR Availability Scenarios is the same as that in IPM v.2.1.9 used for
the CAIR/CAMR/CAVR Scenario.
The NERC GADS calculates the average availability for an EGU by taking the
actual total number of unavailable hours in a given year for all EGUs and dividing it
evenly among the total number of EGUs. Based on the GADS data, the IPM assumes an
upper bound of 85 percent availability for coal-fired EGUs. In GADS data for the years
7 While we believe it is most likely that an EGU would increase its hours of operation
under today's proposed regulations due to reducing the number of hours that the EGU is
unavailable due to forced outage hours, the analysis is applicable to increases in hours of
operation for other reasons.
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3- NSR Availability- SO2 and NOX
2000 - 2004, some EGUs actually had more than 85 percent availability and some
actually had less. The particular EGUs that had greater than 85 percent availability and
less than 85 percent varied from year to year. Similarly, by eliminating forced outages,
some EGUs could increase their availability by more than 2-4 percent and some EGUs
could increase their availability by less than 2-4 percent. Likewise, the particular EGUs
that were able to reduce their forced outage hours would also vary from year to year. For
modeling purposes, it thus makes more sense to assume an average availability than to
determine unit-by-unit availabilities for each and every EGU in a given year.
Our approach based on average availability is also consistent with actual
historical operations at particular EGUs and plantsites, which are most directly related to
local emissions and air quality. Variation in actual annual hours of operation at a given
EGU and at given plantsites do occur under current major NSR applicability. It is not
uncommon for actual hours of operation for a particular EGU to vary by 348 hours
(4 percent availability) or more from year to year. It is also not uncommon for the
variation in actual hours of operation to occur among EGUs at a particular plantsite by
4 percent or more from year to year. For example, in one year Unit A might run
7,800 hours and Unit B might run 7,400 hours. In the next year Unit B might run
7,800 hours and Unit A 7,400 hours. This pattern further supports an approach based on
average availability for estimating local emissions. Changes in average availability,
rather than the absolute availability of any given EGU, thus is appropriate for analyzing
the impact of proposed changes to major NSR applicability.
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3- NSR Availability- SO2 and NO,
3.2 SO2 and NOX Control Device Installation
As Table 3.1 shows, the NSR Availability Scenarios project retrofitting of more
control devices than under the CAIR/CAMR/CAVR 2020 Scenario.8 This result occurs
whether hours of operation increase by 2 percent or by 4 percent. Significantly, under the
4 percent scenario, more Gigawatts (GW) of electric capacity are controlled than under
the 2 percent scenario. For example, under NSR Availability 4%, there is 3.63 more GW
of national EGU capacity with flue gas desulruization (FGD, also known as scrubbers)
than under CAIR/CAMR/CAVR 2020. These results are consistent with what IPM
generally projects, as noted above; that is, the more hours an EGU operates, the more
likely it is to install controls.9 We thus conclude that the more hours an EGU operates,
the more likely it is to install controls, regardless of whether the major NSR applicability
test is on an hourly basis or an annual basis.
Table 3.1 2020 National EGUs With Emission Controls Under NSR
Availability Scenarios
FGD
SCR
EGUs with Additional Controls
Compared to 2004 Base Case
NSR Availability
2%
1 09.62 GW
73.47 GW
NSR Availability
4%
111.53 GW
73.92 GW
EGUs with Additional Controls
Compared to CAIR/CAMR/CAVR
2020
NSR Availability
2%
1.71 GW
0.62 GW
NSR Availability
4%
3.63 GW
1 .07 GW
8 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 06. (System Summary
Report for NSR Availability)
9 See our report, "Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus
on Control Technologies and Emission Reductions in the Electric Power Sector," on
pages 39 and 43. The report is available at http://www.epa.gov/air/cair/charts.html.
The report is also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 05.
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3- NSR Availability- SO2 and NO*
3.3 SO2 and NOX National Emissions
As Table 3.2 shows, the NSR Availability Scenarios project essentially no
changes in 862 or NOX emissions nationally by 2020 as compared to emissions under the
CAIR/CAMR/CAVR 2020 Scenario.10 This result is consistent with the fact that under
the NSR Availability Scenarios, the amount of controls increases, compared to
CAIR/CAMR/CAVR 2020, and we find that these associated emissions decreases offset
the emissions increases associated with the reduced forced outages and higher production
levels.
Table 3.2 National EGU Emissions Under NSR Availability Scenarios Compared
to CAIR/CAMR/CAVR 2020 (tpy)
SO2
NOX
CAIR/CAMR/CAVR
4,277,000
1,989,000
NSR 4%
4,271,000
2,016,000
NSR 2%
4,261,000
2,003,000
Change-NSR
4%
-6,000
<1 % decrease
28,000
1 % increase
Change-NSR
2%
-16,000
<1 % decrease
14,000
1 % increase
As noted above, the NSR Availability Scenarios examine emissions changes
based on very conservative estimates developed using actual historical hours of operation
for 6,500 EGUs over the years 2000 - 2004. We conclude that to any extent that EGU
hours of operation increase under a maximum hourly test, as opposed to the current
10 CAIR/CAMR/CAVR SO2 and NQX emissions available as Docket Item EPA-HQ-
OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05].
NSR SO2 and NOX Availability Emissions available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 14. [EPA 219b_NSR_OAQPS_ 5_Pech_2020_07-05-06 (to EPA)]
National totals for CAIR/CAMR/CAVR and NSR Availability include new units (IPM
new units and planned-committed units).
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3- NSR Availability- SO2 and NO,
average annual 5-year baseline test, such increased hours of operation would not increase
national EGU SCh emissions. The increased efficiency would have very little effect on
national EGU NOX emissions, with approximately one percent increase nationally. This
conclusion as to emissions in the contiguous 48 States supports extending the proposed
rules nationwide, instead of limiting them to the States in the CAIR region.
3.4 SO2 and NOX Local Emissions Impact
We used the IPM runs - the CAIR/CAMR/CAVR 2020 and the NSR Availability
and Efficiency Scenarios - to project future emissions. The IPM is based on data from
actual EGUs that are aggregated into model plants and that, after the IPM is run and
results are recorded, can be disaggregated back to the actual EGUs. As a result, county-
level emissions can be calculated. As we discuss in detail in Section 2, for both the
CAIR/CAMR/CAVR 2020 and the NSR Availability Scenarios, the underlying data for
each existing EGU is information from actual operations as of 2004. The information
for each EGU is the same in both IPM scenarios, with the exception of the assumptions
regarding higher availability for the NSR Scenario that we describe in Section 3.1, such
as might occur under the proposed revisions to the major NSR emissions increase test.
Of course, the other inputs into IPM were the same for both runs, and are independent of
any major NSR applicability test. These include power system operation, financial, fuel,
the ability of each owner/operator to have complete knowledge of the marketplace, and
other assumptions. We describe these assumptions and uncertainties in detail in the
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3- NSR Availability- SO2 and NOX
documentation for the IPM.11 The emission projections from the IPM Scenarios, based
on these assumptions and methodologies, are illustrative of likely variation in effects at
the local level under alternative scenarios rather than definitive projections of the
emissions from individual (specific) EGUs or plants.
Based on our experience with cap-and-trade programs and our modeling using IPM,
the IPM results suggest the following general considerations about the impact of the
proposed NSR emissions increase tests on local emissions.
The proposed revised NSR emissions increase test would likely result in a somewhat
different pattern of local emissions, with some counties experiencing decreases and
some experiencing increases. A substantial majority of counties experience little or
no change in emissions.
In those counties where emission decreases are projected, they often occur because
EGUs are projected to install controls under the NSR Availability Scenario, but not
under the CAIR/CAM/CAVR Scenario. This effect occurs because as EGUs increase
their hours of operation, it becomes cost effective to install controls. This result is
consistent with our earlier observations.12 In other cases, decreases occur because
more cost effective generation displaces less cost effective generation, and the less
cost effective EGUs retire. This effect occurs even though the more cost effective
EGUs increased their hours of operation. In both these situations where hours of
operation increase, these EGUs would be unlikely to trigger major NSR under any of
the alternative scenarios.
Where emission increases do occur, they are generally small and sparsely distributed
such that there is very little effect on local air quality. Furthermore, the increases are
within the variability that actually occurred, as measured using CEMS, at individual
EGUS over the period 2003-2004 under the current NSR emissions increase test.
To examine the effect of the maximum hourly test on local air quality, we
compared 2020 county-level EGU 862 and NOX emissions under the
11 Complete documentation for IPM, including the Base Case Scenario, is available at
http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html. See also Docket Item
EPA-HQ-OAR-2005-1063, DCN 03.
12 These results are consistent with what IPM generally projects, as noted above; that is,
the more hours an EGU operates, the more likely it is to install controls. See Footnote 9.
3-7
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3- NSR Availability- SO2 and NOX
CAIR/CAMR/CAVR 2020 and NSR Availability (4%) Scenario.13 Tables 3.3 and 3.4
show these comparisons.14
Table 3.3 Changes in County-level SO2 Emissions NSR Availability (4%)
Scenario Compared to CAIR/CAMR/CAVR 2020
Changes in SO2 Emissions
Total number of counties with decreases
Decreases between 20,000 and 36,941 tpy
Decreases between 3,000 and 20,000 tpy
Decreases between 1 ,000 and 3,000 tpy
Decreases between 40 and 1 000 tpy
Decreases up to 39 tpy
No change in EGU emissions
Increases up to 39 tpy
Increases between 40 and 1000 tpy
Increases between 1 ,000 and 3,000 tpy
Increases between 3,000 and 6,801 tpy
Total number of counties with increases
Number of Counties
65
2
13
12
31
7
780
30
255
47
6
338
13 CAIR/CAMR/CAVR SO2 and NOX emissions available as Docket Item EPA-HQ-
OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05].
NSR SO2 and NOX Availability Emissions available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 14. [EPA 219b_NSR_OAQPS_ 5_Pech_2020_07-05-06 (to EPA)]
14 Emission increases of at least 0.5 tpy. Does not include emissions due to new EGUs
(IPM new units and IPM planned-committed units). New units (IPM new units and
planned-committed units) were not included in CAIR/CAMR/CAVR 2020 and NSR
Availability county-level emission totals because they had not been assigned to a county.
New EGUs would not be subject to proposed rule. New EGUs would be subject to major
NSR, including control technology review for installation of BACT/LAER.
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3- NSR Availability- SO2 and NOX
Table 3.4 Changes in County-level NOX Emissions NSR Availability (4%)
Scenario Compared to CAIR/CAMR/CAVR 2020
Changes in NOX Emissions
Total number of counties with decreases
Decreases between 3,000 and 10,720 tpy
Decreases between 1 ,000 and 3,000 tpy
Decreases between 40 and 1000 tpy
Decreases up to 39 tpy
No change in EGU emissions
Increases up to 39 tpy
Increases between 40 and 1000 tpy
Increases between 1 ,000 and 3,000 tpy
Increases between 3,000 and 3,172 tpy
Total number of counties with increases
Number of Counties
238
2
9
61
166
540
126
269
9
1
405
As Tables 3.3 and 3.4 show, the proposed revised NSR applicability tests would, under
the very conservative assumptions described above, result in a somewhat different pattern
of local emissions, with some counties experiencing reductions, some experiencing
increases, and some remaining the same. This pattern is consistent with the fact that most
coal-fired EGUs are in the CAIR region and therefore subject to regulations
implementing the CAIR cap. According to the DOE's Energy Information Agency, for
the years 2003 - 2004, approximately 80 percent of the coal steam electric generation and
75 percent of all electric generation occurred in CAIR States.15 Furthermore, EGUs are
subject to national SC>2 caps under the Acid Rain Program.
15 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 08. (2000 - 2004 Electric
Generation)
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3- NSR Availability- SO2 and NOX
For these reasons, an increase in emissions in one area results in a decrease
elsewhere. This dynamic occurs regardless of the major NSR applicability test for
existing EGUs. Nonetheless, the NSR Availability Scenario demonstrates that this
pattern continues to occur when increased availability is assumed, such as we assume for
present purposes would occur under the proposed maximum hourly tests.
In counties with an 862 emissions increase of at least 40 tons per year (tpy),
emission increases ranged from 43 to 6,801 tpy. The degree of county-level emission
decreases was higher than that of the increases, ranging from 10 to 36,941 tpy. This
pattern also occurred with NOX emissions. As Table 3.4 shows, in counties with a NOX
emissions increase of at least 40 tpy, emission increases ranged from 41 to 3,172 tpy.
The degree of county-level emission decreases was higher than that of the NOX increases,
ranging from 1 to 10,720 tpy. The increases and decreases occurred in CAIR and non-
CAIR States.
To gain a further perspective on the projected county-level SC>2 and NOX increases
under the NSR Availability (4%) Scenario, we compared them to recorded actual annual
EGU SC>2 and NOX emissions in 2003 - 2004.16 We examined actual annual emissions
from CEMS data transmitted to the Agency on these EGUs. In 2004, 2 EGUs had
emissions increases greater than 3,721 tpy NOX as compared to 2003. In 2004, 15 EGUs
had emissions increases greater than 6,801 tpy SC>2 as compared to 2003. Thus, the
highest county-level projected emissions increases for SC>2 and NOX under the NSR
Availability (4%) Scenario are less than the emissions increases that actually occurred,
16 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 15. (2003 - 2004 Emission
Changes)
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3- NSR Availability- SO2 and NO*
measured using CEMS, at individual EGUs over the period of 2003 - 2004. As this
perspective shows, the local emissions increases that the IPM results indicate could
theoretically occur from the proposed emissions increase test are not large. They are also
within the variability that occurred under the current emissions increase test between the
years 2003 - 2004. Furthermore, under the current actual-to-projected-actual emissions
increase test, ECU owner/operators can select any 24-month baseline period within the 5-
year period immediately preceding the beginning of actual construction of the project.
Owner operators can select a baseline period of higher annual emissions under the
existing emissions increase test to avoid triggering major NSR applicability. The
emission increases observed under the NSR Availability Scenario are within the range of
the recorded actual annual emissions. Thus, we believe it unlikely that the emission
increases under the NSR Availability Scenario would lead to a different applicability
result under the proposed hourly tests compared to the existing annual emissions increase
test.
We next examined the reasons for the largest increases and decreases in county-
level emissions under the NSR Availability (4%) Scenario. As we discussed in detail in
Section III. B., the difference in the assumptions in the NSR Availability Scenario as
compared to the CAIR/CAMR/CAVR 2020 Scenario is the hours of operation.
Therefore, the changes in county level emissions are a direct function of our IPM
assumptions concerning the hours of operation. We did not assume that any existing
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3- NSR Availability- SO2 and NOX
EGU would increase its capacity in the NSR Availability Scenario. Table 3.5 shows the
counties with the largest decreases and increases in 862 and NOX emissions.17
Table 3.5 Largest County-level Decreases and Increases Under NSR Availability
(4%) Scenario (tpy)
5 counties with largest decrease in SO2 emissions under the NSR Availability
Scenario
State
GA
AL
TN
MN
TX
County
Monroe
Jackson
Sumner
Itasca
Titus
Decrease
-36,941
-27,572
-17,282
-10,759
-10,552
Variations in unit-level data that would explain
the decrease
Unit installs SCR and FGD in 4% run, no control
in CAIR/CAMR/CAVR 2020
Widow Creek Units 1-6 are retired in the 4% run
Units are partially retrofitted in BART, fully
retrofitted in 4%
FGD goes on unit 3 in the 4% run
Welsh unit 1 gets FGD in 4% run
5 counties with largest decrease in NOX emissions under NSR Scenario
State
GA
OH
OH
PA
Wl
County
Monroe
Lucas
Montgomery
Clearfield
Buffalo
Decrease
-10,720
-3,038
-2,722
-1,782
-1,770
Variations in unit-level data that would explain
the increase
Scherer units get SCR and FGD retrofits in the 4%
run
Bay Shore units 2,3 get SCR and FGD retrofits in
the 4% run
Hutchings units 1-6 retire
Shawville unit 1 retires
Alma units 4 & 5 retire
17 Analysis of largest county-level emission changes available as Docket Item EPA-HQ-
OAR-2005-0163, DCN 15. CAIR/CAMR/CAVR SO2 and NOX emissions available as
Docket Item EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan
(to EPA)07-11-05]. NSR Availability SO2 and NOX Emissions available as Docket Item
EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_NSR_OAQPS_5_Pech_2020_07-05-
06 (to EPA)] Does not include emissions due to new EGUs (IPM new units and IPM
planned-committed units).
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3- NSR Availability- SO2 and NOX
Table 3.6 Largest County-level Decreases and Increases Under NSR Availability
(4%) Scenario (tpy)
5 counties with largest increase in SO2 emissions under the NSR Availability
Scenario
State
GA
Ml
Ml
GA
KY
County
Bartow
Monroe
St. Clair
Heard
Jefferson
Increase
6,801
5,065
4,011
3,720
3,401
Variations in unit-level data that would explain
the increase
No change in controls, total fuel use increases
No change in controls, total fuel use increases
No change in controls, total fuel use increases
No change in controls, total fuel use increases
No change in controls, total fuel use increases
5 counties with largest increase in NOX emissions under the NSR Availability
Scenario
State
NM
MT
ND
AZ
Wl
County
San Juan
Rosebud
Mercer
Coconino
Grant
Increase
3,172
1,543
1,445
1,379
1,306
Variations in unit-level data that would explain
the increase
No change in controls, total fuel use increases
No change in controls, total fuel use increases
No change in controls, total fuel use increases
No change in controls, total fuel use increases
SCR on Nelson plant in CAIR/CAMR/CAVR 2020,
no SCR under NSR 4%; decrease in utilization in
NSR 4% compared to CAIR/CAMR/CAVR 2020.
For most counties in Table 3.5 where 862 and NOX emission decreases are
projected (Monroe, Georgia; Sumner, Tennessee; Itasca, Minnesota; Titus, Texas; and
Lucas, Ohio), the decreases occur because EGUs are projected to install controls under
the NSR Availability (4%) Scenario but are not projected to install controls under
CAIR/CAMR/CAVR. This effect occurs because as these EGUs increase their hours of
operation, they reach a break-even point where it becomes cost effective to install
controls rather than to buy allowances. For other counties in Table 3.5 (Jackson County,
Alabama; Montgomery County, Ohio; Clearfield County, Pennsylvania), decreases occur
because EGUs are projected to retire under the NSR Availability (4%) Scenario but are
not projected to be retired under CAIR/CAMR/CAVR 2020. This effect occurs because
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3- NSR Availability- SO2 and NO,
more cost effective generation from EGUs that increased their availability under the NSR
Availability Scenario displaces less cost effective generation from other EGUs, which
then retire.
As Table 3.5 shows, county-level 862 and NOX increases are small and sparsely
distributed. The increases are small even in the counties where the highest SC>2 and NOX
increases are projected. In most of the counties in Table 3.5, the emission increases are
due to increased fuel use by the EGUs within those counties, consistent with increased
hours of operation. The exception is Grant County, Wisconsin, where SCR for the
Nelson plant is projected under CAIR/CAMR/CAVR 2020, but not under the NSR
Availability (4%) Scenario. In this instance, the projected increases at the Nelson plant
occur because under the CAIR/CAMR/CAVR 2020 IPM, it is modeled as putting on
controls. In the NSR Availability run, however, the Nelson plant decreases its utilization
compared to CAIR/CAMR/CAVR 2020, and as a result it does not install the projected
SCR controls. This result occurs because Nelson is less efficient compared to other
EGUs. If this particular EGU (or any other EGU) were to increase its efficiency and
utilization, it is likely that it would put on controls, consistent with our finding that the
more hours an EGU operates, the likelier it is to install controls.
To gain further perspective on the magnitude of the 862 and NOX emissions
changes under the NSR Availability Scenario, we compared them to total 862 and NOX
emissions at the State level. Specifically, we compared the net change in statewide EGU
SO2 and NOX emissions under the NSR Availability Scenario to the total State SCh and
NOX emissions under CAIR/CAMR/CAVR 2020. As Appendix A shows, in States
where SC>2 emissions increase under the NSR Availability Scenario as compared to
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3- NSR Availability- SO2 and NOX
CAIR/CAMR/CAVR 2020, the net emissions increase is at most 3 percent of the total
SO2 emissions in the State. As Appendix A shows, in States where NOX emissions
increase under the NSR Availability Scenario as compared to CAIR/CAMR/CAVR 2020,
the net emissions increase ranges is at most 2 percent of the total NOX emissions in the
State. Thus where SC-2 and NOX emissions increase under the NSR Availability Scenario,
they are small in comparison to total 862 and NOX emissions at the State level.
As we discussed in Section 3.1, our approach is based on average availability,
assuming a constraint of 89 percent availability. Due to the variation in EGU hours of
operation from year to year, for modeling purposes it makes sense to assume an average
availability rather than to determine unit-by-unit availabilities for each and every EGU in
a given year. We therefore believe the NSR Availability Scenario provides a very
conservative estimate of the emissions increases that would theoretically occur under our
proposed regulations.
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3- NSR Availability- SO2 and NOX
3.5 SO2 and NOX Impact on Air Quality
As we discussed above, projected emissions changes under proposed revised NSR
applicability tests would result in a somewhat different pattern of local emissions, with
some counties experiencing reductions, some experiencing increases, and some
remaining the same. As we also noted, the degree and pattern of these emission changes
is consistent with those under CAIR/CAMR/CAVR 2020. Moreover, the emission
changes under the NSR Availability Scenario are projected using very conservative
assumptions, as described above. Figures 3.1 and 3.2 compare projected county-level
SO2 and NOx emissions under NSR Availability 4% to those projected under
CAIR/CAMR/CAVR 2020.18
18CAIR/CAMR/CAVR SO2 and NOX emissions available as Docket Item EPA-HQ-OAR-
2005-0163. DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA) 07-11-05]. NSR
Availability SO2 and NOX Emissions available as Docket Item EPA-HQ-OAR-2005-
0163, DCN 14. [EPA 219b_NSR_OAQPS_5_Pech_2020_07-05-06 (to EPA)]
3-16
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Counties with NOx Changes (TPY)
HI -10.720 - -3000
B| -3,000--1.000
| | -1,000--40
I | -40- 40
| : M | 40 - 1 ,QDO
H 1,000- 3.172
| | Counties with No NOx Changes
Figure 3.1 2020 County-level SO2 Emissions Changes With a 4% Increase in ECU
Availability
3-17
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Counties with SO2 Changes (TPY)
H -33.841 - -20,000
|H -20.000 - -3.000
•M -3,000- -1.000
I I-1.000--40
I |-40-40
I 140-1.000
HI 1.000-3.000
H| 3,000 -8.901
I I Counties w«h No SO2 Changes
Figure 3.2 2020 County-level NOX Emissions Changes With a 4% Increase in ECU
Availability
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3- NSR Availability- SO2 and NOX
As Figures 3.1 and 3.2 show, projected increases in SOa and NOX emissions due
to increased hours of operation at EGUs under the NSR Availability (4%) Scenario are
small in magnitude and sparse across the continental U.S. Therefore, we would expect
these increases to cause minimal local ambient effect, both directly on 862 and NOX
emissions and as precursors to formation of PlVb.s (862 and NOX emissions) and ozone
(NOX emissions). Because many counties experience decreases in emissions, we would
further expect any local ambient effects from increased emissions to be somewhat
diminished because of the emissions decreases elsewhere that yield regionwide
improvements in air quality, including SC>2, NOX, PM2.5, and ozone. We expect similar
outcomes with respect to the NSR Availability (2%) Scenario where the emissions
changes are smaller and exhibit a pattern of increases and decreases that is similar to that
of the NSR Availability (4%) Scenario.
Based on the spatial distribution of 862 and NOX emissions changes as shown in
Figures 3.1 and 3.2, we expect patterns of air quality changes respectively under the NSR
Availability (4%) Scenario to be consistent with projections under CAIR/CAMR/CAVR
in 2020. We thus believe that the local air quality under today's proposed regulations
would be commensurate with that under the CMAQ modeling
3-19
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3- NSR Availability- SO2 and NOX
based on CAIR/CAMR/CAVR 2020 Scenario emissions projections. 19
19 As part of the CAIR/CAMR/CAVR analyses, we examined the air quality impact of
EGU SC>2 and NOX emissions on SCh, NOX, PIVh.s (for which 863 and NOX emissions are
precursors), and 8-hour ozone concentrations (for which NOX is a precursor).
Specifically, we modeled the change in annual average concentrations of SOa and NOX
under CAIR/CAMR/CAVR 2020 and compared these results to the base case emissions
in 2001 using the CMAQ model. We also modeled the change in annual average
concentrations of PM2.5 under CAIR/CAMR/CAVR 2020 and compared these results to
the base case emissions in 2001 using the CMAQ model. The CMAQ modeling was
conducted as part of EPA's multipollutant legislative assessment and the results are
available at http://www.epa.gov/airmarkets/progsregs/cair/multi.html. Multipollutant
Regulatory Analysis: The Clean Air Interstate Rule, The Clean Air Mercury Rule, and
the Clean Air Visibility Rule (EPA promulgated rules, 2005). The specific technical
support document on air quality modeling for CAIR/CAMR/CAVR, Technical Support
Document for Air Quality Modeling Technique, is available at
http://www.epa.gov/airmarkets/progsregs/cair/multi.html by clicking on the
Technical Support Document - Air Quality Modeling Technique used for Multi-Pollutant
Analysis link. It is also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 09.
Finally, we modeled the annual average concentrations of 8-hour ozone under
CAIR/CAMR/CAVR 2020 and compared these results to the average ambient
concentrations for 1999 - 2003.) This information by county is contained in a
spreadsheet file available on our website. The information on 8-hour ozone
concentrations is available at
http://www.epa.gov/airmarkets/progsregs/cair/multi.html
(Air quality Modeling Results Excel File, Impact on Ozone concentrations, by county.)
It is also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 16.
3-20
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Chapter 4.
NSR Availability Scenarios- PM2.5, VOC, and CO
4.1 NSR Availability Scenario
We used the NSR Availability Scenarios that we describe in Chapter 3 to examine
the PM2.5, VOC, and CO emissions and air quality impacts of the proposed hourly
emissions increase test. This chapter provides the results of our analyses.
4.2 PM2.s, VOC, and CO Control Device Installation
As we discuss in the PM2.5 NAAQS RIA, our NEEDS indicates that as of 2004,
84 percent of all coal- fired EGUS have an electrostatic precipitator (ESP) in operation,
about 14 percent of EGUs have a fabric filter, and roughly 2 percent have wet
scrubbers.20 Gas-fired turbines are clean burning and Best Available Control Technology
(BACT) or the Lowest Achievable Emission Rate (LAER) for these EGUs is no control.
BACT/LAER for VOC and CO is good combustion control. Furthermore, ECU
owner/operators have natural incentives to reduce VOC emissions. VOCs are products of
incomplete combustion. These compounds are discharged into the atmosphere when fuel
remains unburned or is burned only partially during the combustion process. Fuel is a
significant portion of total costs for EGUs, particularly for older EGUs where capital
costs are paid off. EGU owner/operators have in fact improved combustion practices to
increase combustion efficiency, thereby limiting unbumed fuel. Cost effective operation
20 See Regulatory Impact Analysis for PMb.s rule at pg 3-34. Available at
http://www.epa.gov/ttn/ecas/ria.html and as Docket Item EPA-HQ-OAR-2005-0163,
DCN 10.
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4- NSR Availability- PM2.5, VOC, and CO
is especially desirable in areas where a cap and trade program increases the cost of
operation by creating a cost to pollute, as is the case in the CAIR region where most
ozone and PM2.s nonattainment areas are located.
4.3 PM2.5, VOC, and CO National Emissions
As Table 4.1 shows, EGUs contribute a small percentage of national PM2.5, CO,
and VOC emissions.
21
Table 4.1 EGU Emissions As Percent of 2020 National Emissions (tpy)
PM25
VOC
CO
EGU
533,000
45,000
718,000
National
6,206,000
12,414,000
82,852,000
EGU as % National
8.6%
0.4%
0.9%
As Table 4.2 shows, the NSR Availability Scenarios project essentially no
changes in PM2.5, VOC, or CO emissions nationally by 2020 as compared to emissions
under the CAIR/CAMR/CAVR Scenario.22
21 CO emissions information from Clear Air Interstate Rule Emissions Inventory
Technical Support Document, available at
http://www.epa.gov/interstateairquality/pdfs/finaltech01.pdf. CO emissions rounded
to nearest thousand ton level. Also available as Docket Item EPA-HQ-OAR-2005-0163,
DCN 11. PM2.5 and VOC emissions information from PM2.5NAAQS RIA, available at
http://www.epa.gov/ttn/ecas/ria.html. Also available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 10.
22 Emissions information Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 17.
[NSR Availability PM2.5) VOC, and CO] National totals for CAIR/CAMR/CAVR and
NSR Availability include new units (IPM new units and planned-committed units).
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4- NSR Availability- PM2.5, VOC, and CO
Table 4.2 National EGU Emissions Under NSR Availability Scenario
Compared to CAIR/CAMR/CAVR 2020 (tpy)
PM25
VOC
CO
CAIR/CAMR/CAVR
526,642
45,020
716,184
NSR 4%
524,245
45,391
711,254
Change-NSR 4%
(2,397)
371
(4,930)
As described in Chapter 3, the NSR Availability Scenarios examine emissions
changes based on very conservative estimates developed using actual historical hours of
operation for 6,500 EGUs over the years 2000 - 2004. We conclude that to any extent
that EGU hours of operation increase under a maximum hourly test as opposed to the
current average annual 5-year baseline test, such increased hours of operation would not
increase national EGU PM2.5 and CO emissions, and would have very little effect on
VOC emissions. This conclusion as to emissions in the contiguous 48 States supports
extending the proposed rules nationwide, instead of limiting them to the States in the
CAIR region.
4.4 PM2.5, VOC, and CO Local Emissions Impact
To examine the effect of the maximum hourly test on local air quality, we
compared 2020 county-level EGU PM2.5, VOC, and CO emissions under the
CAIR/CAMR/CAVR 2020 and NSR Availability (4%) Scenario.23
23 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability
PM2.5, VOC, and CO]
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4- NSR Availability- PM2.5, VOC, and CO
Tables 4.3 through 4.5 show these comparisons.
24
Table 4.3 Changes in County-level PM2.5 Emissions NSR Availability (4%)
Scenario
Changes in PM2.s Emissions
Total # of counties with decreases in ECU emissions
# of counties with decreases in ECU emissions between -1 ,001 and -
2,074 tpy
# of counties with decreases in ECU emissions between -40 and -
1,000 tpy
# of counties with decreases in ECU emissions between -1 and -39 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 39 tpy
# of counties with increases in EGU emissions between 40 and
536 tpy
Total # of counties with increases in EGU emissions
Counties
133
1
27
105
437
250
134
384
Table 4.4 Changes in County-level VOC Emissions NSR Availability (4%)
Scenario
Changes in VOC Emissions
Total # of counties with decreases in EGU emissions
# of counties with decreases in EGU emissions between -40 and -
87 tpy
# of counties with decreases in EGU emissions between -1 and -39 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 22 tpy
Total # of counties with increases in EGU emissions
Counties
89
2
87
569
296
296
24 Emission increases of at least 0.5 tpy. Does not include emissions due to new EGUs
(IPM new units and IPM planned-committed units). New units (IPM new units and
planned-committed units) were not included in CAIR/CAMR/CAVR 2020 and NSR For
the reasons we discuss in Section 3.4, the modeling results are illustrative of likely
variations in effects at the local level under alternative scenarios rather than definitive
projections of the emissions from individual (specific) EGUs or plants.
Availability county-level emission totals because they had not been assigned to a county.
New EGUs would not be subject to proposed rule. New EGUs would be subject to major
NSR, including control technology review for installation of BACT/LAER.
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4- NSR Availability- PM2.5> VOC, and CO
Table 4.5 Changes in County-level CO Emissions NSR Availability (4%)
Scenario
Changes in CO Emissions
Total # of counties with decreases in ECU emissions
# of counties with decreases in ECU emissions between -40 and -
735 tpy
# of counties with decreases in EGU emissions between -1 and -39 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 39 tpy
# of counties with increases in EGU emissions between 40 and
755 tpy
Total # of counties with increases in EGU emissions
Counties
240
55
185
334
247
133
380
As Tables 4.3 through 4.5 show, the proposed revised NSR applicability tests
would, under the very conservative assumptions described in Chapter 3, result in a
somewhat different pattern of local emissions, with some counties experiencing
reductions, some experiencing increases, and some remaining the same. That is, this
pattern occurs when increased availability is assumed, such as we assume for present
purposes would occur under the proposed maximum hourly tests. The increases and
decreases in county-level EGU PMi.s, VOC, and CO emissions are small and sparsely
distributed.
As Table 4.3 shows, the highest county-level PMb.s emissions increase was
536 tpy. As Table 4.4 shows, county-level VOC emissions increases ranged from 1 to
22 tpy. As Table 4.5 shows, the highest county-level CO emissions increase was 755 tpy.
The increases and decreases occurred in CAIR and non-CAIR States.
To gain a further perspective on the projected county-level PM2.5, VOC, and CO
increases under the NSR Availability (4%) Scenario, we compared them to actual annual
EGU PM2.5, VOC, and CO emissions in 2003 - 2004. We calculated the actual annual
PM2.5, VOC, and CO emissions for each EGU using the actual heat input (MMBtu)
4-5
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4- NSR Availability- PM2.5, VOC, and CO
CEMS data and an emission factor.25 Based on this analysis, we believe it unlikely that
the emission increases under the NSR Availability Scenario would lead to a different
applicability result under the proposed hourly tests compared to the existing annual
emissions increase test.
In 2004, one EGU had an emissions increase of 3,845 tpy PM2.5 and 56 EGUs had
emission increases of greater than 536 tpy as compared to 2003. Thus, the highest
county-level projected emissions increases for Plvb.s under the NSR Availability (4%)
Scenario are significantly less than the emissions increases that actually occurred, based
on measured data, at individual EGUs over the period of 2003 - 2004. The emission
decreases observed under the NSR Availability Scenario are within the range of the
actual annual emissions based on recorded data. Furthermore, under the current actual-to-
projected-actual emissions increase test, EGU owner/operators can select any 24-month
baseline period within the 5-year period immediately preceding the beginning of actual
construction of the project. Owner operators can select a baseline period of higher annual
emissions under the existing emissions increase test to avoid triggering major NSR
applicability.
In 2004, actual VOC emission changes compared to 2003 ranged from a 38 tpy
decrease to 53 tpy increase. Thus, the greatest county-level projected emissions
decreases for VOC under the NSR Availability (4%) Scenario are less than the emissions
decreases that actually occurred, based on measured data, at individual EGUs over the
period of 2003 - 2004. The highest county-level projected emission increases in the NSR
25 Analysis and emission factors used available as Docket Item EPA-HQ-OAR-2005-
0163, DCN 15. [2003-2004 PM2.5, VOC, and CO Emissions]
4-6
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4- NSR Availability- PM2.5, VOC, and CO
Availability Scenarios are 19, 19, 20, 22, and 23. In 2004, the five highest emission
increases at individual EGUs as compared to 2003 were 27, 29, 31, 35, and 53. Thus, the
highest VOC emission increases under the NSR Availability (4%) Scenario are less than
the emissions increases that actually occurred, based on measured data, at individual
EGUs over the period of 2003 - 2004.
In 2004, actual CO emission changes compared to 2003 ranged from a 580 tpy
decrease to a 623 tpy increase. Thus, the highest county-level projected emissions
increases for CO under the NSR Availability (4%) Scenario are less and the greatest
county-level projected CO emission decreases are greater, than the emissions increases
and decreases that actually occurred, based on measured data, at individual EGUs over
the period of 2003-2004.
As this analysis shows, the local PlV^.s, VOC, and CO emissions increases that the
IPM results indicate could theoretically occur from this action are not large. They are
also within the variability that occurred under the current emissions increase test between
the years 2003 - 2004. Therefore, we believe it is unlikely that the emission increases
under the NSR Availability Scenario would lead to a different applicability result under
the proposed hourly tests compared to the existing annual emissions increase test.
' We next examined the reasons for the largest decreases and increases in county-
level emissions under the NSR Availability (4%) Scenario. As we discussed in detail in
Section III. B., the difference in the assumptions in the NSR Availability Scenario as
compared to the CAIR/CAMR/CAVR 2020 Scenario is the hours of operation.
Therefore, the changes in county level emissions are a direct function of our IPM
4-7
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4- NSR Availability- PM2.5, VOC, and CO
assumptions concerning the hours of operation. We did not assume that any existing
EGU would increase its capacity in the NSR Availability Scenario.
Tables 4.6 through 4.8 show the counties with the largest decreases and increases
in EGU PM2.5, VOC, and CO emissions.26
26 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability
PM2.5, VOC, and CO] Emission increases of at least 0.5 tpy. Does not include emissions
due to new EGUs (IPM new units and IPM planned-committed units).
4-8
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4- NSR Availability- PM2.5, VOC, and CO
Table 4.6 Largest County-level Decreases and Increases of Primary PM2.s Under NSR Availability (4%) Scenario (tpy
5 counties with largest decrease in Primary PM2.s emissions under the NSR Availability Scenario
State
Alabama
Pennsylvania
Ohio
Ohio
Pennsylvania
County
Jackson
Lawrence
Montgomery
Pickaway
Snyder
County-level Emissions
NSR
Availability
(4%)
1,384
208
2
1
0
CAIR/CAMR/CAVR
2020
3,457
914
670
649 •
614
Decrease
-2,073
-706
-668
-648
-614
Variations in unit-level data that would
explain the decrease
6 of 8 Widows Creek units retire
New Castle units 3 and 4 retire
Hutchings units 1-6 retire
Picway retires
Sunbury retires
5 counties with largest increase in Primary PM2.s emissions under the NSR Availability Scenario
State
Minnesota
Missouri
Oklahoma
New Mexico
Texas
County
Sherburne
New Madrid
Mayes
San Juan
Titus
County-level Emissions
NSR
Availability
(4%)
11,897
10,899
8,230
7,969
3,414
CAIR/CAMR/CAVR
2020
11,361
10,408
7,863
7,609
3,175
Increase
536
491
367
360
239
Variations in unit-level data that would
explain the increase
Heat input and emissions increased at
Sherburne Go's 3 units
Heat input increased at New Madrid's 2 units
Heat input increased
Heat input increased
Heat input increased
4-9
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4- NSR Availability- PM2.s, VOC, and CO
Table 4.7 Largest County-level Decreases and Increases of VOC Under NSR Availability (4%) Scenario (tpy)
5 counties with largest decrease in VOC emissions under the NSR Availability Scenario
State
Georgia
Alabama
Nevada
Ohio
Texas
County
Monroe
Jackson
Clark
Montgomery
Rusk
County-level Emissions
NSR
Availability
(4%)
346
99
271
1
489
CAIR/CAMR/CAVR
2020
433
167
299
27
515
Decrease
-87
-68
-28
-26
-26
Variations in unit-level data that would
explain the decrease
Heat input decreased at all 4 Scherer Units
6 of 8 Widows Creek units retired
Heat input decrease
Hutchings units 1-6 retire
Heat input decrease
5 counties with largest increase in VOC emissions under the NSR Availability Scenario
State
New Mexico
North Dakota
Kentucky
New York
Massachusetts
County
San Juan
Mercer
Muhlenberg
Oswego
Barnstable
County-level Emissions
NSR
Availability
(4%)
496
501
442
49
38
CAIR/CAMR/CAVR
2020
473
479
422
30
19
Increase
23"
22
20
19
19
Variations in unit-level data that would
explain the increase
Heat input increased for all units
Heat input increased for all units
Heat input increased
Heat input increased
Heat input increased
27 The EGU VOC emissions for San Juan County, New Mexico under CAIR/CAMR/CAVR 2020 are projected to be 473.4
tons and under NSR Availability 2020 are projected to be 495.7 tons, shown in Table 4.7 as 473 and 496 tons due to rounding.
The actual increase is 22.3 tons.
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4- NSR Availability- PM2.5, VOC, and CO
Table 4.8 Largest County-level Decreases and Increases of CO Under NSR Availability (4%) Scenario (tpy)
5 counties with largest decrease in CO emissions under the NSR Availability Scenario
State
Georgia
California
Alabama
Massachusetts
Alabama
County
Monroe
Los
Angeles
Morgan
Essex
Jackson
County-level Emissions
NSR
Availability
(4%)
2,913
7,050
754
256
825
CAIR/CAMR/CAVR
2020
3,648
7,765
1,418
915
1,394
Decrease
-735
-715
-664
-659
-569
Variations in unit-level data that would
explain the decrease
Emissions decreased at Scherer's 4 units an
other units
Emissions decreased for El Segundo's unit ,
Haynes1 3 units, and Scattergood's 2 units
Heat input decreased
Heat input decreased
Heat input decreased
5 counties with largest increase in CO emissions under the NSR Availability Scenario
State
New York
Massachusetts
Texas
Oklahoma
Florida
County
Oswego
Barnstable
Robertson
Le Flore
Duval
County-level Emissions
NSR
Availability
(4%)
1,916
1,483
13,166
9,804
9,017
CAIR/CAMR/CAVR
2020
1,161
757
12,572
9,362
8,608
Increase
755
726
594
442
409
Variations in unit-level data that would
explain the increase
Sithe Independence 6 units' emissions incre?
Heat input increased
Heat input increased
Heat input increased at AES Shady Point's
2 units
Heat input increased
4-11
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4- NSR Availability- PM2.5, VOC, and CO
For some counties in Tables 4.6 though 4.8 where PM2.5, CO, and VOC emission
decreases are projected, the decreases occur because heat input and emissions decreased
at existing units. This effect occurs because more cost effective generation from EGUs
that increased their availability under the NSR Availability Scenario displaces less cost
effective generation from other EGUs. The less efficient EGUs then decrease their
usage, reflected by decreased heat input and emissions. In Jackson Co., Alabama,
decreases occur because EGUs are projected to retire under the NSR Availability (4%)
Scenario but are not projected to be retired under CAIR/CAMR/CAVR 2020. This effect
also occurs because more cost effective generation from EGUs that increased their
availability under the NSR Availability Scenario displaces less cost effective generation
from other EGUs, which then retire. In other counties, PM2.5, VOC, and CO emission
decreases occur because less new generation was projected for that county under the NSR
Availability Scenario as opposed to under CAIR/CAMR/CAVR.
As noted previously, county-level increases are small and sparsely distributed. As
Tables 4.6 through 4.8 show, the PM2.5, VOC, and CO increases are small even in the
'counties where the highest increases are projected. In many of the counties shown here,
the emission increases are due to increased fuel use by the EGUs within those counties,
consistent with increased hours of operation. In other counties, emission increases occur
where more new generation was projected for that county under the NSR Availability
Scenario as opposed to under CAIR/CAMR/CAVR. Increased generation due to new
EGUs would be subject to major NSR review and would not be affected by the proposed
emissions increase test.
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4- NSR Availability- PM2.5, VOC, and CO
4.5 PM25, VOC, and CO Air Quality
As Figures 4.1 through 4.3 show,28 projected PMb.s, VOC, and CO emissions
changes under the proposed revised NSR applicability tests would result in a somewhat
different pattern of local emissions, with some counties experiencing reductions, some
experiencing increases, and some remaining the same compared to emissions changes
under CAIR/CAMR/CAVR 2020. As Figures 4.1 through 4.3 show, projected increases
in EGU PM2.5, VOC, and CO emissions due to increased hours of operation at EGUs
under the NSR Availability (4%) Scenario are small in magnitude and sparse across the
continental U.S. Therefore, we would expect these increases to cause minimal changes in
local ambient effect in comparison to that observed under CAIR/CAMR/CAVR for PM2.5
and ozone (for which VOC is a precursor). Because many counties experience decreases
in emissions, we would further expect any local ambient effects from increased emissions
to be somewhat diminished because the emissions decreases elsewhere yield regionwide
improvements in air quality.
Furthermore, as noted in Table 4.1, EGU VOC emissions are less than one
percent of national VOC emissions. Also national VOC emissions and national EGU
VOC emissions are declining. According to our latest analysis, 2020 national VOC
emissions are projected to be 5,219,000 tons less than 2001 national VOC emissions;
28 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability
PM2.5, VOC, and CO]
4-13
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4- NSR Availability- PM2.5, VOC, and CO
2020 national EGU VOC emissions are projected to be 8,000 tons less than 2001 national
ECU VOC emissions.29
For these reasons, EGUs do not contribute significantly to national or local VOC
emissions. Furthermore, EGU owner/operators have natural incentives to reduce VOC
emissions. VOCs are products of incomplete combustion. These compounds are
discharged into the atmosphere when fuel remains unburned or is burned only partially
during the combustion process. Fuel is a significant portion of total costs for EGUs,
particularly for older EGUs, where capital costs are paid off. EGU owner/operators have
in fact improved combustion practices to increase combustion efficiency, thereby limiting
unburned fuel. Cost effective operation is especially desirable in areas where a cap and
trade program increases the cost of operation by creating a cost to pollute, as is the case
in the CAIR region where most ozone nonattainment areas are located.
We have not modeled national or regional air quality improvements in CO
concentrations. As noted in Table 4.1, however, EGU CO emissions are less than one
percent of national CO emissions. According to our latest analysis, 2020 national CO
emissions are projected to be 19,892,017 tons less than 2001 national CO emissions.30
Local CO emissions are generally a function of traffic congestion from mobile sources.
For these reasons, EGUs do not contribute significantly to national or local CO
emissions. Furthermore, as with VOCs, EGU owner/operators have natural incentives to
reduce CO emissions, as fuel costs are a significant portion of total costs for EGUs.
29 See the PM2.5NAAQS RIA at 1-9. Also available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 10.
30 See the Clean Air Interstate Rule Emissions Inventory Technical Support Document at
pgs 7 and 38. Also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 11.
4-14
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4-NSR Availability-PM2.s, VOC, and CO
There currently are only five CO nonattainment areas: El Paso, Texas; Las
Vegas, NV; Los Angeles South Coast Air Basin, CA; Missoula, MT; and Reno, NV. For
these five local areas, we computed the net emissions change in the EGU CO emissions
between CAIR/CAMR/CAVR 2020 and NSR Availability. Appendix B of this document
includes this analysis. As Appendix B shows, in most of these counties IPM projects no
change or a decrease in emissions in the NSR Availability Scenario compared to
CAIR/CAMR/CAVR 2020. No emissions increase of greater than 40 tpy PM2.5 is
projected for any local area in the NSR Availability Scenario compared to
CAIR/CAMR/CAVR 2020. The projected increases in CO emissions due to increased
hours of operation at EGUs under the NSR Availability (4%) Scenario thus are small in
magnitude and sparse across the continental U.S. We would expect these increases to
cause minimal local ambient effect on CO. Therefore, based on the small increases and
sparse distribution of CO emissions compared to CAIR/CAMR/CAVR 2020, and the
small contribution of EGU emissions to national and local CO levels, we project no
notable local impact on air quality from EGU CO emissions from NSR Availability 4%.
4-15
-------
4- NSR Availability- PM2.s, VOC, and CO
Counties with PM, i Changes
^|-2074--1000
rj -999- -40
| j-39-40
iyg 41 - 536
-;-.;I Counties with No PM; - Changes
Figure 4.1 2020 PM2.s County-level Emissions Changes With a 4% Increase in EGU Availability
4-16
-------
4- NSR Availability- PM2.5, VOC, and CO
« •
Counties with VOC Changes
-39 - 22
! Counties with No VOC Changes
Figure 4.2 2020 County-level VOC Emissions Changes With a 4% Increase in ECU Availability
4-17
-------
4- NSR Availability- PM2.5, VOC, and CO
Counties with CO Changes
[IJ-735--40
^-39-40
41-755
I Counties with No CO Changes
Figure 4.3 2020 County-level CO Emissions Changes With a 4% Increase in ECU Availability
4-18
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Chapter 5.
NSR Efficiency Scenarios- SO2 and NOX
5.1 NSR Efficiency Scenario
We designed another IPM model run to evaluate whether efficiency
improvements that sources may make as a result of today's proposed regulations would
lead to local emissions increases and adverse effects on ambient air quality. We call this
run the NSR Efficiency Scenario.
Heat rates describe the efficiency of a unit—that is, the amount of electricity
generated per fuel input. In EPA's NEEDS, used to populate the IPM, heat rates are
expressed as Btus per KWh.31 Heat rates for coal steam EGUs in the IPM model 2.1.9,
used in the NSR Efficiency Scenario, range from 8,300 to 14,500 Btu/KWh. Heat rates
are often converted to an efficiency percent. (1 KWh =3,412 Btu) Utility boiler thermal
efficiencies generally range from approximately 31 to 38 percent. The more efficient an
EGU, the less fuel it uses and the less it emits for a given period of operation. For
example, a 50 MW combustion turbine that operates 500 hours a year, for 25,000 MWh
per year at an emission rate of 75 ppmvd NOX, would emit 46 tons of NOX per year at
25 percent efficiency, 41 tons of NOX per year at 28 percent efficiency, 37 tons of NOX
per year at 31 percent efficiency, or 34 tons of NOX per year at 34 percent efficiency.
1 IPM v.2.1.9 Documentation can be viewed and downloaded at
www.epa.gov/airmarkets/epa-ipm. It is also available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 01 and EPA-HQ-OAR-2005-0163, DCN 03. For more information on
heat rates used in the IPM modeling, see Chapter 3 of the IPM documentation on the
website above. It is also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 3.
5-1
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5- NSR Efficiency Scenarios- SO2 and NOX
The Value of Efficiency
Two 500 MW Generators
Both generate 4 MM MWh/yr
12,407 Tons NO,/ye
6.2 Ib NO/MWh
0,236 Tons NO^ye
5.1 IbNO/M "
40% Efficiency
Figure 5.1 The Value of Efficiency
The more efficient an EGU is, the less fuel it has to bum to generate the same
amount of electricity. Since fuel costs are typically the biggest operating expense for an
EGU, this will generally translate to lower-cost electricity. The lower the cost to generate
electricity from a given EGU, the more likely it is to be dispatched and to operate more
hours. Aside from independent factors such as climate and economy, efficiency is a
primary determinant of the hours of operation of a given EGU. Neither the current
annual emissions increase test nor any of the proposed EGU emission increase test
alternatives directly measure an EGU's efficiency. However, the output-based
alternatives (Alternatives 2, 4, 6, and 8), which are expressed in a Ib/KWh format that
measures mass emissions per unit of electricity, are closely related to an EGU's
efficiency. Thus, an output-based test encourages efficient units, which has well-
recognized benefits. We anticipate that the output-based alternatives in particular, and
5-2
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5- NSR Efficiency Scenarios- SO2 and NOX
the other alternatives to a lesser extent, could have the effect of encouraging EGUs to
increase their efficiency. For these reasons, we focused on efficiency to examine whether
the hourly test could result in emissions increases as compared to the annual emissions
increase test. Of all coal-fired EGUs nationally, we identified the least efficient
35 percent. These EGUs all have heat rates of 11,000 Btu/KWh or higher. We also
identified a reasonable amount of efficiency increase. Based on a review of the literature,
the extent to which heat rates can be improved at existing plants is estimated to be at best
3 to 5 percent. This is because heat rate is primarily dependent on unit design, and the
design of a plant cannot be changed once built.32 We therefore assumed a 4 percent
efficiency increase in our NSR IPM run. We also constrained the IPM model such that
there was no option for any EGU to increase capacity, heat rate, or availability. Thus,
under the NSR Efficiency Scenario, there was no increase in the existing operating and
physical capacity of each coal steam EGU, as measured in MMBtu/hr.33 Because it is
unlikely that 35 percent of all coal-fired EGUs would increase their efficiency, and
because a 4 percent efficiency increase is on the outer bounds of possible efficiency
increases, our analysis provides a very conservative approach based on a worst-case
scenario that may overestimate emission increases at individual units.
32 Review of Potential Efficiency Improvements at Coal-Fired Power Plants, available in
Docket as item . See also Demonstration of EPRI Heat-Rate Improvement Guidelines,
available in Docket as item EPA-HQ-OAR-2005-0163, DCN 19.
33 We believe it is unlikely that an EGU would increase its efficiency without also
increasing its operating and physical capacity. Nonetheless, we designed the IPM
Scenario to assess the impact of efficiency increases on actual emissions. This analysis
was only possible through constraining the model such that no increases in operating and
physical capacity are allowed.
5-3
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5- NSR Efficiency Scenarios- SO2 and NO,
We did not assume efficiency increases in combustion turbines in the NSR EGU
Efficiency Scenario analysis. Combustion turbines are generally used as peaking units
and therefore provide only a small percentage of net generation. In 2004, as measured
from actual recorded fuel use (MMBtu) submitted to EPA for all EGUs subject to the
Acid Rain Program, combustion turbines accounted for approximately 2.5 percent of total
heat input, and coal steam EGUs accounted for approximately 85.7 percent of total heat
input.34
We ran the IPM with this scenario (4 percent efficiency increase for 371 coal-
fired EGU, no increase in physical and operating existing capacity) and compared the
results to the CAIR/CAVR/CAMR IPM model. We found approximately the same
results from the NSR Efficiency Scenario as from the NSR Availability Scenarios.
5.2 SO2 and NOX Control Device Installation
As Table 5.1 shows, the NSR Efficiency Scenario projects retrofitting of more
control devices than under the CAIR/CAMR/CAVR 2020.35 These results are consistent
with what IPM generally projects. The more efficient an EGU is, the more cost effective
it is to operate. The more cost effective it is to operate, the more hours it will operate.
The more hours it operates, the more likely it is to install controls.36 We thus conclude
34 Based on actual data submitted to EPA by EGUs subject to the Acid Rain Program.
Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 20. (ARPunitlevel2004)
35 Information from system summary report for the NSR Efficiency IPM Run. Available
as Docket Item EPA-HQ-OAR-2005-0163, DCN 13. (System Summary Report for NSR
Efficiency)
36 See our report, "Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus
on Control Technologies and Emission Reductions in the Electric Power Sector," on
pages 39 and 43. The report is available at
http://www.epa.gov/air/interstateairquality/charts.html. It is also available as Docket
Item EPA-HQ-OAR-2005-0163, DCN 05.
5-4
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5- NSR Efficiency Scenarios- SO2 and NOX
that the more efficiently an EGU operates, the more likely it is to install controls,
regardless of whether the major NSR applicability test is on an hourly basis or an annual
basis.
Table 5.1 2020 National EGUs with Emission Controls Under NSR
Efficiency
FGD
SCR
EGUs with Additional Controls
Compared to 2004 Controls Case
109GW
74 GW
EGUs with Additional Controls
Compared to CAIR/CAMR/CAVR
2020
1.5GW
1.0 GW
5.3 SO2 and NOX National Emissions
As Table 5.2 shows, the NSR Efficiency Scenarios project reductions in 862 and
NOX emissions nationally by 2020 as compared to emissions under the Base Case
Scenario.37 This result is consistent with the fact that under the NSR Efficiency Scenario,
the amount of controls increases, compared to the Base Case.
37 CAIR/CAMR/CAVR SO2 and NOX emissions available as Docket Item EPA-HQ-
OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05].
NSR Efficiency SO2 and NOX Emissions Available as Docket Item EPA-HQ-OAR-2005-
0163, DCN 07. [EPA 219b_NSR_OAQPS_ 2a_Pechan_2020_(to EPA) 4-27-06]
National totals for CAIR/CAMR/CAVR and NSR Efficiency include new units (IPM
new units and planned-committed units).
5-5
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5- NSR Efficiency Scenarios- SO2 and NOX
Table 5.2 National EGU Emissions Under NSR Efficiency Scenario Compared
to CAIR/CAMR/CAVR 2020 (tpy)
SO2
NOx
Total Emissions
Under
CAIR/CAMR/CAVR
4,277,000
1,989,000
Total Emissions Under
NSR Efficiency
4,265,000
1,984,000
Emissions Change Under
NSR Efficiency Compared to
CAIR/CAMR/CAVR
-12,000
-5,000
As noted above, the NSR Efficiency Scenarios examine emissions changes based on very
conservative estimates of technically feasible improvements in efficiency. We conclude that to
any extent that EGU efficiency increases under a maximum hourly test, as opposed to the current
average annual 5-year baseline test, such increased efficiency would not increase national EGU
SOa and NOX emissions. This conclusion as to emissions in the contiguous 48 States supports
extending the proposed rules nationwide, instead of limiting them to the States in the CAIR
region.
5.4 SO2 and NOX Local Emissions Impact
To examine the effect of the maximum hourly test on local air quality, we compared 2020
county-level EGU SO2 and NOX emissions under the CAIR/CAMR/CAVR 2020 and NSR
Efficiency Scenario.38 Tables 5.3 and 5.4 show these comparisons.39
38 CAIR/CAMR/CAVR SO2 and NOX emissions available as Docket Item EPA-HQ-OAR-2005-
0163, DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05]. NSR Efficiency SO2
and NOX Emissions Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 07. [EPA
219b_NSR_OAQPS_2a_Pechan_2020_(to EPA) 4-27-06]
39 Emission increases of at least 0.5 tpy. Does not include emissions due to new EGUs
(IPM new units and IPM planned-committed units). New units (IPM new units and planned-
committed units) were not included in CAIR/CAMR/CAVR 2020 and NSR Efficiency county-
level emission totals because they had not been assigned to a county.
5-6
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5- NSR Efficiency Scenarios- SO2 and NO*
Table 5.3 Changes in County-level SO2 Emissions NSR Efficiency Scenario
Compared to CAIR/CAMR/CAVR 2020
Emissions Change
Total # of counties with decreases in EGU Emissions
# of counties with EGU emissions decreases between 3,000 and 17,384 tpy
# of counties with EGU emissions decreases between 1 ,000 and 3,000 tpy
# of counties with EGU emissions decreases between 40 and 1 ,000 tpy
# of counties with EGU emissions decreases up to 39 tpy
# of counties with no change in EGU emissions
# of counties with EGU emissions increases up to 39 tpy
# of counties with EGU emissions increases between 40 and 1 ,000 tpy
# of counties with EGU emissions increases between 1 ,000 and 3,000 tpy
# of counties with EGU emissions increases between 3,000 and 34,276 tpy
Total # of counties with increases in EGU Emissions
Number
of
Counties
142
5
13
110
14
976
12
40
9
4
65
Table 5.4 Changes in County-level NOX Emissions NSR Efficiency Scenario
Compared to CAIR/CAMR/CAVR 2020
Emissions Change
Total # of counties with decreases in EGU Emissions
# of counties with EGU emissions decreases between 1,000 and 2,297 tpy
# of counties with EGU emissions decreases between 40 and 1 ,000 tpy
# of counties with EGU emissions decreases up to 39 tpy
# of counties with no change in EGU emissions
# of counties with EGU emissions increases up to 39 tpy
# of counties with EGU emissions increases between 40 and 1 ,000 tpy
# of counties with EGU emissions increases between 1,000 and 3,098 tpy
Total # of counties with increases in EGU Emissions
Number
of
Counties
285
3
109
173
802
61
30
5
96
New EGUs would not be subject to proposed rule. New EGUs would be subject to
major NSR, including control technology review for installation of BACT/LAER. For the
reasons we discuss in Section 3.4, the modeling results are illustrative of likely variation in
effects at the local level under alternative scenarios rather than definitive projections of the
emissions from individual (specific) EGUs or plants.
5-7
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5- NSR Efficiency Scenarios- SO2 and NOX
As we discuss in Section 5.1, it is unlikely that 35 percent of all coal-fired EGUs would increase
their efficiency, and because a 4 percent efficiency increase is on the outer bounds of possible
efficiency increases, our analysis provides a very conservative approach based on a worst-case
scenario that may overestimate emission increases at individual units. As Tables 5.3 and 5.4
show, the proposed revised NSR applicability tests would, under our very conservative
assumptions, result in a somewhat different pattern of local emissions, with some counties
experiencing reductions, some experiencing increases, and some remaining the same. This
pattern is consistent with the fact that most coal-fired EGUs are in the CAIR region and therefore
subject to regulations implementing the CAIR cap. According to the DOE's Energy Information
Agency, for the years 2003 - 2004, approximately 80 percent of the coal steam electric
generation and 75 percent of all electric generation occurred in CAIR States.40 Furthermore,
EGUs are subject to national 862 caps under the Acid Rain Program.
For these reasons, as under the NSR EGU Availability Scenarios, an increase in
emissions will also result in a decrease in emissions elsewhere. As noted elsewhere, the
presence of a regionwide cap under CAIR results in the same phenomenon within the CAIR
region. That is, an increase in emissions in one area results in a decrease elsewhere. This
dynamic occurs regardless of the major NSR applicability test for existing EGUs. Nonetheless,
the NSR Efficiency Scenario demonstrates that this pattern continues to occur when increased
efficiency is assumed, such as we assume for present purposes would occur under the proposed
40 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 08. (2000-2004 Electric
Generation)
5-8
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5- NSR Efficiency Scenarios- SO2 and NO*
maximum hourly tests.
To gain a further perspective on the projected county-level SCh and NOX increases under
the NSR Efficiency Scenario, we compared them to recorded actual annual EGU 862 and NOX
emissions in 2003 - 2004.41 We examined actual annual emissions from CEMS data transmitted
to the Agency on these EGUs. In 2004, six EGUs had emissions increases greater than 3,098 tpy
NOX as compared to 2003. In 2004, ten EGUs had emissions increases greater than 8,035 tpy
862 as compared to 2003. Thus, with the exception of Humphreys County, TN, the highest
county-level projected emissions increases for SC^ and NOX under the NSR Efficiency Scenario
are less than the emissions increases that actually occurred, measured using CEMS, at individual
EGUs over the period of 2003 - 2004. As this perspective shows, the local emissions increases
that the IPM results indicate could theoretically occur from this action are not large. Concerning
the 34,275 tpy 862 projected increase in Humphreys County, as shown in Table 5.5, these plants
have not really increased emissions as compared to historical operation, and they certainly have
not increased emissions because they have made changes that avoid major NSR. Rather, the
increase is due to plants operating differently under two model runs with different assumptions.
We next examined the reasons for the largest increases and decreases in county-level emissions
under the NSR Efficiency Scenario. Table 5.5 shows the counties with the greatest 862 and NO
increases and decreases.42
41 Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 15. (2003-2004 Emission Changes)
42 CAIR/CAMR/CAVR SO2 and NOx emissions available as Docket Item EPA-HQ-OAR-2005-0163,
DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05]. NSR Efficiency SO2 and NOx
Emissions Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 07. [EPA 219b_NSR_OAQPS_
2a_Pechan_2020_(to EPA) 4-27-06] Does not include emissions due to new EGUs (IPM new units and
IPM planned-committed units).
5-9
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5- NSR Efficiency Scenarios- SO2 and NO*
Table 5.5 Largest County-level Decreases and Increases of SO2 and NOX Under NSR Efficiency Scenario (tpy)
5 counties with largest decrease in SO2 emissions under the NSR Efficiency Scenario
State
TN
MN
SC
OH
PA
County
Sumner
Itasca
Berkeley
Lucas
Clear-field
County-level Emissions
NSR
Efficiency
2,157
14,938
17,493
3,785
2,494
CAIR/CAMR/CAVR
2020
19,541
26,403
23,486
8,070
6,736
Decrease
17,384
11,465
5,993
4,285
4,242
Variations in unit-level data that would
explain the decrease
Units 1-4 partially retrofit in CAIR/CAMR/C^
fully retrofit in NSR Efficiency
FGD goes on Clay Boswell unit 3 in NSR
Efficiency run
FGD goes on Jeffries unit 3 in NSR run
FGD goes on Bayshore units 2 & 3 in NSR
Efficiency run
Shawville unit 1 retires under NSR Efficienc
Run
5 counties with largest decrease in NOX emissions under the NSR Efficiency Scenario
State
OH
PA
OH
MO
Ml
County
Lucas
Clearfield
Clermont
Greene
Ottawa
County-level Emissions
NSR
Efficiency
1,907
1,149
6,898
6,296
22,453
CAIR/CAMR/CAVR
2020
4,204
2,997
8,035
7,264
23,271
Decrease
2,297
1,848
1,137
968
818
Variations in unit-level data that would
explain the increase
Bayshore 2 & 3 put on SCR and FGD undei
Efficiency
Shawville unit 1 retires under NSR Efficienc
Beckjord unit 3 installs SCR and FGD undei
NSR Efficiency
Southwest 1 installs a SNCR under NSR
Efficiency
Campbell units decrease fuel use in NSR
Efficiency
5-10
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5- NSR Efficiency Scenarios- SO2 and NOX
Table 5.5 Largest County-level Decreases and Increases of SO2 and NOX Under NSR Efficiency Scenario (tpy)
5 counties with largest increase in SO2 emissions under the NSR Efficiency Scenario
State
TN
PA
OH
PA
GA
County
Humphreys
Berks
Coshocton
Snyder
Coweta
County-level Emissions
NSR
Efficiency
48,773
8,035
17,980
7,824
7,811
CAIR/CAMR/CAVR
2020
14,498
0
12,045
4,274
5,479
Increase
34,275
8,035
5,935
3,550
2,332
Variations in unit-level data that would
explain the increase
Johnsonville Units 1-8 retire under
CAIR/CAMR/CAVR
Titus units 1-3 retire under CAIR/CAMR/CA
Conesville units 1 & 2 retire under
CAIR/CAMR/CAVR
Sunbury units 1-3 retire under
CAIR/CAMR/CAVR
Yates units 2 & 3 Increase total fuel use unc
NSR Efficiency Run
5 counties with largest increase in NOX emissions under the NSR Efficiency Scenario
State
OH
PA
TN
PA
Wl
County
Coshocton
Berks
Humphreys
Snyder
Grant
County-level Emissions
NSR
Efficiency
6,889
2,409
2,926
3,131
3,753
CAIR/CAMR/CAVR
2020
3,791
130
870
1,167
2,220
Increase
3,098
2,279
2,056
1,964
1,533
Variations in unit-level data that would
explain the increase
Conesville units 1 & 2 retire under
CAIR/CAMR/CAVR
Coal units retire in CAIR/CAMR/CAVR, but
under NSR Efficiency
Johnsonville Units 1-8 retire under
CAIR/CAMR/CAVR
Sunbury units retire under CAIR/CAMR/CA^
but not under NSR Efficiency
Units put on SCR in CAIR/CAMR/CAVR, bu
under NSR Efficiency
5-11
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5- NSR Efficiency Scenarios- SO2 and NO*
For most counties in Table 5.5 where SC>2 and NOX emission decreases are projected
(Sumner, TN; Itasca, MN; Berkeley, SC; Lucas, Ohio; Clermont, OH; and Greene, MO ), the
decreases occur because EGUs are projected to install controls under the NSR Efficiency
Scenario but are not projected to install controls under CAIR/CAMR/CAVR . This effect occurs
because as these EGUs increase their hours of operation, they reach a break-even point where it
becomes cost effective to install controls rather than to buy allowances. In Clearfield, PA, SO2
decreases occur because EGUs are projected to retire under the NSR Efficiency Scenario but are
not projected to be retired under CAIR/CAMR/CAVR 2020. This effect occurs because more
cost effective generation from EGUs that increased their efficiency under the NSR Efficiency
Scenario displaces less cost effective generation from other EGUs, which then retire. In
Clermont, OH, NOX decreases occur because Beckjord installs SCR and FGD in NSR Efficiency,
but not under CAIR/CAMR/CAVR 2020. The IPM projects that this unit would not install SCR
under the CAIR/CAMR/CAVR Scenario because its utilization is not as high in comparison to
its utilization under the NSR Efficiency Scenario. This result is consistent with what IPM
generally projects—the more hours an EGU operates, the more likely it is to install controls.
As Table 5.5 shows, the highest SO2 and NOX increases are projected for the following
counties: Berks, Pennsylvania; Coshocton, Ohio; Humphreys, TN; Snyder, Pennsylvania;
Coweta, Georgia; and Grant, Wisconsin. As under the NSR Availability Scenario, even these
emission increases are generally small. In most of these counties, emission increases are due to
units projected to retire under the CAIR/CAMR/CAVR 2020 IPM, but not to retire under the
NSR Efficiency Scenario. Comparing the NSR run to the Base Case, it appears that emissions in
these counties have increased. However, these plants have not really increased emissions as
5-12
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5- NSR Efficiency Scenarios- SO2 and NOX
compared to historical operation, and they certainly have not increased emissions because they
have made changes that avoid major NSR. Rather, the increase is due to plants operating
differently under two model runs with different assumptions. This is true of the largest SC>2
emissions increase (34,275 tpy) projected in Humphreys County, Tennessee. We also note that
862 emissions in nearby Sumner County decrease by 17,384 tpy.
Likewise, in Grant County, Wisconsin, emission increases are projected to occur where
SCR for the Nelson plant is projected under CAIR/CAMR/CAVR 2020, but not under the NSR
Efficiency Scenario. The IPM projects that this unit would not install SCR under the NSR
Efficiency Scenario because it decreases utilization in comparison to its utilization under
CAIR/CAMR/CAVR Scenario. This is because other more efficient units have increased their
utilization. If the Nelson unit were to increase its utilization, it would then be a good candidate
to install SCR.
To gain further perspective on the magnitude of the 862 and NOX emissions changes
under the NSR Efficiency Scenario, we compared them to total 862 and NOX emissions at the
State level. Specifically, we compared the net change in statewide EGU SC>2 and NOX emissions
under the NSR Efficiency Scenario to the total State 862 and NOX emissions under
CAIR/CAMR/CAVR 2020. As Appendix A shows, in States where SCh emissions increase
under the NSR Efficiency Scenario as compared to CAIR/CAMR/CAVR 2020, the net emissions
increase ranges is at most 6 percent of the total SC>2 emissions in the State. As Appendix A also
shows, in States where NOX emissions increase under the NSR Availability Scenario as
compared to CAIR/CAMR/CAVR 2020, the net emissions increase ranges is at most 2 percent
of the total NOX emissions in the State. Thus where SC>2 and NOX emissions increase under the
5-13
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5- NSR Efficiency Scenarios- SO2 and NOX
NSR Efficiency Scenario, they are small in comparison to total SC>2 and NOX emissions at the
State level.
5.5 SO2 and NOX Air Quality Impact
As we discussed above, projected emissions changes under proposed revised NSR
applicability tests would result in a somewhat different pattern of local emissions, with some
counties experiencing reductions, some experiencing increases, and some remaining the same.
As we also noted, the degree and pattern of these changes is consistent with those under
CAIR/CAMR/CAVR 2020. Moreover, the emission changes under the NSR Efficiency Scenario
are projected assuming very conservative assumptions, as described above.
Figures 5.2 and 5.3 compare projected county-level 862 and NOX emissions under the
NSR Efficiency Scenario to those projected under CAIR/CAMR/CAVR 2020.43 Projected
increases in emissions of these pollutants due to increased efficiency at EGUs under the NSR
Efficiency Scenario are generally small in magnitude and sparse across the continental U.S.
Therefore, we would expect these increases to cause minimal local ambient effect, both directly
on SC>2 and NOX emissions and as precursors to formation of PM2.5 (SC>2 and NOX emissions) and
ozone (NOX emissions). Because many counties experience decreases in emissions, we would
further expect any local ambient effects from increased emissions to be somewhat diminished
43 CAIR/CAMR/CAVR emissions available as Docket Item EPA-HQ-OAR-2005-0163, DCN
09. CAIR/CAMR/CAVR SO2 and NOX emissions available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan (to EPA)07-11-05]. NSR Efficiency
SO2 and NOX Emissions Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 07. [EPA
219b_NSR_OAQPS_ 2a_Pechan_2020_(to EPA) 4-27-06]
5-14
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5- NSR Efficiency Scenarios- SO2 and NOX
because of the emissions decreases elsewhere that yield regionwide improvements in air quality,
including 862, NOX, PM2.5, and ozone.
Based on the spatial distribution of 862 and NOX emissions changes as shown in
Figures 5.1 and 5.2, we expect patterns of air quality changes respectively under the NSR
Efficiency Scenario to be consistent with projections under CAIR/CAMR/CAVR in 2020. We
thus believe that the local air quality under today's proposed regulations would be commensurate
with that under the CMAQ modeling based on CAIR/CAMR/CAVR 2020 Scenario emissions
projections.44
44 As we discussed in Section 2.5, our projections of 2020 air quality under CAIR/CAMR/CAVR
are on our website and in the docket for this rulemaking.
5-15
-------
5- NSR Efficiency Scenarios- SO2 and NOX
Counties with SO2 Changes
Hi -17384- -3000
^H -2999 - -1000
[ •-. | -999 - -40
j ! -39 - 40
1 -100°
1001 -3000
3001 - 34275
Counties with No SO2 Changes
Figure 5.2 2020 County-level SO2 Emissions Changes with Efficiency Increase
5-16
-------
5- NSR Efficiency Scenarios- SO2 and NOX
Counties with NOx Changes (TPY)
Hi -2297- -1000
i -999--40
! -39 - 40
41 -1000
| 1001 -3098
i Countes with No NOx Changes
Figure 5.3 2020 County-level NOX Emissions Changes with Efficiency Increase
5-17
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6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
Chapter 6.
NSR Efficiency Scenarios- PM2.s, VOC, and CO
6.1 NSR Efficiency Scenario
We used the NSR Efficiency Scenarios that we describe in Chapter 5.1 to examine the
PM2.5, VOC, and CO emissions and air quality impacts of the proposed hourly emissions
increase test. This chapter provides the results of our analyses.
6.2 PM2.5, VOC, and CO Control Device Installation
As we discussion the PM2.5NAAQS RIA, our NEEDS indicates that as of 2004,
84 percent of all coal-fired EGUS have an ESP in operation, about 14 percent of EGUs have a
fabric filter, and roughly 2 percent have wet PM2.5, scrubbers.45 Gas-fired turbines are clean
burning and BACT/LAER for these EGUs is no control. BACT/LAER for VOC and CO is good
combustion control. Furthermore, EGU owner/operators have natural incentives to reduce VOC
emissions. VOCs are products of incomplete combustion. These compounds are discharged into
the atmosphere when fuel remains unburned or is burned only partially during the combustion
process. Fuel is a significant portion of total costs for EGUs, particularly for older EGUs where
capital costs are paid off. EGU owner/operators have in fact improved combustion practices to
increase combustion efficiency, thereby limiting unburned fuel. Cost effective operation is
especially desirable in areas where a cap and trade program increases the cost of operation by
45 See Regulatory Impact Analysis for PM2.5 rule at pg 3-34. Available at
http://www.epa.gov/ttn/ecas/ria.html and as Docket Item EPA-HQ-OAR-2005-0163, DCN 10.
6-18
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6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
creating a cost to pollute, as is the case in the CAIR region where most ozone and PM2.5
nonattainment areas are located.
6.3 PM2.s, VOC, and CO National Emissions
As Table 6.1 shows, EGUs are a small percentage of national PMi.s, CO, and VOC
emissions.
46
Table 6.1 EGU Emissions As Percent of 2020 National Emissions (tpy)
PM2.5
VOC
CO
EGU
533,000^
45,000
717,889
National
6,206,000
12,414,000
82,851,643
EGU as % National
8.6%
0.4%
0.9%
As Table 6.2 shows, the NSR Efficiency Scenarios project essentially no changes in
PM2.5, VOC, or CO emissions nationally by 2020 as compared to emissions under the
CAIR/CAMR/CAVR Scenario.
47
46 CO emissions information from Clear Air Interstate Rule Emissions Inventory Technical
Support Document, available at http://www.epa.gov/air/interstateairquality/technical.html.
Also available as Docket Item EPA-HQ-OAR-2005-0163, DCN 11. PM2.5 and VOC emissions
information from PIVb.s NAAQS RIA, available at http://www.epa.gov/ttn/ecas/ria.html. Also
available as Docket Item EPA-HQ-OAR-2005-0163, DCN 10.
47 Emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 18. [NSR
Efficiency PM2.5, VOC, and CO.] National totals for CAIR/CAMR/CAVR and NSR Efficiency
include new units (IPM new units and planned-committed units).
6-19
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6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
Table 6.2 National EGU Emissions Under NSR Efficiency Scenario
Compared to CAIR/CAMR/CAVR 2020 (tpy)
PM25
VOC
CO
CAIR/CAMR/CAVR
526,642
45,019
716,184
NSR Efficiency
529,647
44,835
711,314
Change-NSR
Efficiency
3,005
-184
-4,870
As described in Chapter 5, the NSR Efficiency Scenarios examine emissions changes
based on very conservative estimates of technically feasible improvements in efficiency. We
conclude that to any extent that EGU hours of operation increase under a maximum hourly test,
as opposed to the current average annual 5-year baseline test, such increased hours of operation
would not increase national EGU PM2.5, VOC, and CO emissions. The increased efficiency
would have very little effect on national PM2.5 emissions, with less than half of a percent
increase nationally. This conclusion as to emissions in the contiguous 48 States supports
extending the proposed rules nationwide, instead of limiting them to the States in the CAIR
region.
6-20
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6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
6.4 PM2.5, VOC, and CO Local Emissions Impact
To examine the effect of the maximum hourly test on local air quality, we compared 2020
county-level EGU PM2.5, VOC, and CO emissions under the CAIR/CAMR/CAVR 2020 and
NSR Efficiency Scenario.48 Tables 6.3 through 6.5 show these comparisons. 49
Table 6.3 Changes in County-level PM2.s Emissions NSR Efficiency Scenario
Changes in PM2.s Emissions
Total # of counties with decreases in EGU emissions
# of counties with decreases in EGU emissions between -40 and -
599 tpy
# of counties with decreases in EGU emissions between -1 and -39 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 39 tpy
# of counties with increases in EGU emissions between 40 and
1 ,000 tpy
# of counties with increases in EGU emissions between 1,001 and
3,672 tpy
Total # of counties with increases in EGU emissions
Counties
187
33
154
713
31
22
2
55
48 Emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 18. [NSR
Efficiency PMb.s, VOC, and CO.] Emission increases of at least 0.5 tpy. Does not include
e'missions due to new EGUs (IPM new units and IPM planned-committed units). New units
(IPM new units and planned-committed units) were not included in CAIR/CAMR/CAVR 2020
and NSR Efficiency county-level emission totals because they had not been assigned to a county.
New EGUs would not be subject to proposed rule. New EGUs would be subject to major NSR,
including control technology review for installation of BACT/LAER.
49 For the reasons we discuss in Section 3.4, the modeling results are illustrative of likely
variation in effects at the local level under alternative scenarios rather than definitive projections
of the emissions from individual (specific) EGUs or plants.
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6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
Table 6.4 Changes in County-level VOC Emissions NSR Efficiency Scenario
Changes in VOC Emissions
Total # of counties with decreases in EGU emissions
# of counties with decreases in EGU emissions between -1 and -20 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 39 tpy
# of counties with increases in EGU emissions between 40 and 88 tpy
Total # of counties with increases in EGU emissions
Counties
131
131
792
31
1
32
Table 6.5 Changes in County-level CO Emissions NSR Efficiency Scenario
Changes in CO Emissions
Total # of counties with decreases in EGU emissions
# of counties with decreases in EGU emissions between -40 and -659
Tpy
# of counties with decreases in EGU emissions between -1 and -39 tpy
# of counties with no change in EGU emissions
# of counties with increases in EGU emissions between 1 and 39 tpy
# of counties with increases in EGU emissions between 40 and 7
31 tov
Total # of counties with increases in EGU emissions
Counties
269
39
230
591
83
12
95
As Tables 6.3 through 6.5 show, the proposed revised NSR applicability tests would,
under the very conservative assumptions described in Chapter 5, result in a somewhat different
pattern of local emissions, with some counties experiencing reductions, some experiencing
increases, and some remaining the same. That is, this pattern occurs when increased efficiency is
assumed, such as we assume for present purposes would occur under the proposed maximum
hourly test. The increases and decreases in county-level EGU PM2.5, VOC, and CO emissions
are small and sparsely distributed.
6-22
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6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
As Table 6.3 shows, the highest county level PM2.5, emission increase was 3,672 tpy.
VOC emission increases ranged from 28 to 88 tpy. The highest county level CO emissions
increase was-731 tpy. The increases and decreases occurred in CAIR and non-CAIR States.
To gain a further perspective on the projected county-level PMi.s, VOC, and CO
increases under the NSR Efficiency Scenario, we compared them to actual annual EGU PMa.s,,
VOC, and CO emissions in 2003 - 2004. As we discussed in Chapter 4, we calculated the actual
annual PM2.5, VOC, and CO emissions for each EGU using the actual heat input (MMBtu)
CEMS data and an emission factor.50 In 2004, PM2.5, emissions changes ranged from a 2,080 tpy
decrease to a 3,845 tpy increase as compared to 2003. Thus, the highest county-level projected
emissions increases and decreases for PM2.5, under the NSR Efficiency Scenario are within the
range of the emissions changes that actually occurred.
In 2004, actual VOC emission changes compared to 2003 ranged from a 38 tpy decrease
to 53 tpy increase. Thus, the greatest county-level projected emissions increases and decreases
for VOC under the NSR Efficiency Scenario are commensurate with the emissions increases and
decreases that actually occurred, based on measured data, at individual EGUs over the period of
2003 - 2004.
In 2004, actual CO emission changes compared to 2003 ranged from a 580 tpy decrease
to a 623 tpy increase. Thus, the highest county-level projected emissions increases and the
greatest projected county-level decreases for CO under NSR Efficiency are commensurate with
50 Analysis and emission factors used available as Docket Item EPA-HQ-OAR-2005-0163, DCN
15. [2003-2004 PM2.5, VOC, and CO Emissions]
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6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
the emissions increases and decreases that actually occurred, based on measured data, at
individual EGUs over the period of 2003 - 2004.
As this analysis shows, the local emissions increases that the IPM results indicate could
theoretically occur from the proposed emissions increase test are not large. They are also within
the variability that occurred under the current emissions increase test between the years 2003 -
2004. Furthermore, under the current actual-to-projected-actual emissions increase test, EGU
owner/operators can select any 24-month baseline period within the 5-year period immediately
preceding the beginning of actual construction of the project. Owner operators can select a
baseline period of higher annual emissions under the existing emissions increase test to avoid
triggering major NSR applicability. The emission increases observed under the NSR Efficiency
Scenario are within the range of the recorded actual annual emissions. Thus, we believe it
unlikely that the emission increases under the NSR Efficiency Scenario would lead to a different
applicability result under the proposed hourly tests compared to the existing annual emissions
increase test.
We next examined the reasons for the largest decreases and increases in county-level
emissions under the NSR Efficiency Scenario. Tables 6.6 through 6.8 show the counties with the
largest decreases and increases in EGU PM2.5,, VOC, and CO emissions.51
51 Emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 18. [NSR
Efficiency PM2.5, VOC, and CO.] Does not include emissions due to new EGUs (IPM new units
and IPM planned-committed units).
6-24
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6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
Table 6.6 Largest County-level Decreases and Increases of Primary PM2.s Under
NSR Efficiency
Change in unit-level data for the five counties where Primary PM2.s emissions
decrease most
State
Pennsylvania
South Carolina
Missouri
Ohio
Indiana
County
Clearfield
Berkeley
St. Louis
Clermont
Floyd
Emissions
Change
(tpy)
-599
-471
-233
-200
-167
Reason for Variations in Unit-level Data
Shawville Unit 1 retires under NSR
Efficiency
FGD goes on Jeffries Unit 3 in NSR
Efficiency
Fuel use decreases under NSR Efficiency
Beckjord Unit 3 installs SCR and FGD
under NSR Efficiency
Fuel use decreases under NSR Efficiency
Change in unit-level data for the five counties where Primary PM2.s emissions
increase most
State
Tennessee
Ohio
Pennsylvania
Pennsylvania
New York
County
Humphreys
Coshocton
Berks
Snyder
Monroe
Emissions
Change
(tpy)
3,672
1,508
958
514
407
Reason for Variations in Unit-level Data
Johnsonville units 1-8 retire in
CAIR/CAMR/
CAVR
Conesville Units 1-2 retire in
CAIR/CAMR/CAVR
Titus Units 1-2 retire in CAIR/CAMR/CAVR
Sunbury units retire in CAIR/CAMR/CAVR
Fuel use increases under NSR Efficiency
6-25
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6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
Table 6.7 Largest County-level VOC Decreases and Increases Under NSR Efficiency
Scenario
Change in unit-level data for the five counties where VOC emissions decrease
State
Texas
Massachusetts
Kansas
Pennsylvania
North Dakota
County
Rusk
Essex
Pottawatomie
Clearfield
Mercer
Emissions
Change
(tpy)
-20
-17
-12
-10
-10
Reason for Variations in Unit-level Data
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Shawville Unit 1 retires under NSR Efficiency
Fuel use decreases under NSR Efficiency
Change in unit-level data for the five counties where VOC emissions increase most
State
Tennessee
Ohio
Pennsylvania
Massachusetts
Alabama
County
Humphreys
Coshocton
Berks
Barnstable
Morgan
Emissions
Change
(tpy)
88
28
19
16
15
Reason for Variations in Unit-level Data
Johnsonville units 1-8 retire in
CAIR/CAMR/CAVR
Conesville Units 1-2 retire in
CAIR/CAMR/CAVR
Titus Units 1-2 retire in CAIR/CAMR/CAVR
Fuel use increases under NSR Efficiency
Fuel use increases under NSR Efficiency
6-26
-------
6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
Table 6.8 Largest County-level CO Decreases and Increases Under NSR Efficiency
Scenario
Change in unit-level data for the five counties where CO emissions decrease most
State
Massachusetts
Texas
Texas
Mississippi
Mississippi
County
Essex
Robertson
Newton
Benton
Lowndes
Emissions
Change
(tpy)
-659
-503
-352
-259
-230
Reason for Variations in Unit-level
Data
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Fuel use decreases under NSR Efficiency
Change in unit-level data for the five counties where CO emissions increase most
State
Tennessee
Massachusetts
Alabama
Iowa
Pennsylvania
County
Humphreys
Barnstable
Morgan
Muscatine
Berks
Emissions
Change
(tpy)
731
614
580
209
152
Reason for Variations in Unit-level
Data
Johnsonville units 1-8 retire in
CAIR/CAMR/CAVR
Fuel use increases under NSR Efficiency
Fuel use increases under NSR Efficiency
Fuel use increases under NSR Efficiency
Titus Units 1-2 retire in
CAIR/CAMR/CAVR
For some counties in Tables 6.6 though 6.8 where PM2.5, CO, and VOC emission
decreases are projected, the decreases occur because heat input and emissions decreased at
existing units. This effect occurs because more cost effective generation from EGUs that
increased their efficiency under the NSR Efficiency Scenario displaces less cost effective
generation from other EGUs, which then are operated less. In Clearfield and Snyder Counties,
Pennsylvania, decreases occur because EGUs are projected to retire under the NSR Efficiency
Scenario, but are not projected to be retired under CAIR/CAMR/CAVR 2020. This effect occurs
because more cost effective generation from EGUs that increased their efficiency under the NSR
Efficiency Scenario displaces less cost effective generation from other EGUs, which then retire.
6-27
-------
6- NSR Efficiency Scenarios- PM2.s, VOC, and CO
As noted previously, county-level increases are small and sparsely distributed. As
Tables 6.6 through 6.8 show, the PM2.5, VOC, and CO increases are small even in the counties
where the highest increases are projected. In most of the counties shown here, the emission
increases are due to increased fuel use by the EGUs within those counties, consistent with
increased utilization for more efficient units. In Humphreys County, Tennessee, emission
increases are due to units projected to retire under the CAIR/CAMR/CAVR 2020 IPM, but not to
retire under the NSR Efficiency Scenario. Comparing the NSR run to the Base Case, it appears
that emissions in these counties have increased. However, these EGUs have not really increased
emissions as compared to historical operation, and they certainly have not increased emissions
because they have made changes that avoid major NSR. Rather, the increase is due to plants
operating differently under two model runs with different assumptions.
6.5 PM2.5, VOC, and CO Air Quality
As Figures 6.1 through 6.3 show,52 projected PM2.5, VOC, and CO emissions changes
under the proposed revised NSR applicability tests would result in a somewhat different pattern
of local emissions, with some counties experiencing reductions, some experiencing increases,
and some remaining the same compared to emissions changes under CAIR/CAMR/CAVR 2020.
As Figures 6.1 through 6.3 also show, projected increases in EGU PM2.s, VOC, and CO
emissions due to increased efficiency at EGUs under the NSR Efficiency Scenario are small in
magnitude and sparse across the continental U.S. Therefore, we would expect these increases to
52 Emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 18. [NSR
Efficiency PM2.5, VOC, and CO.]
6-28
-------
6- NSR Efficiency Scenarios- PMz.s, VOC, and CO
cause minimal changes in local ambient effect in comparison to that observed under
CAIR/CAMR/CAVR for PM2.5 and ozone (for which VOC is a precursor). Because many
counties experience decreases in emissions, we would further expect any local ambient effects
from increased emissions to be somewhat diminished because of the emissions decreases
elsewhere that yield regionwide improvements in air quality.
Furthermore, as noted in Table 4.1, EGU VOC emissions are less than one percent of
national VOC emissions. Also national VOC emissions and national EGU VOC emissions are
declining. For these reasons, EGUs do not contribute significantly to national or local VOC
emissions. Moreover, as we also discussed in Section 4.1, EGU owner/operators have natural
incentives to reduce VOC emissions.
The Agency has not conducted regional modeling for CO. Nonetheless, due to the small
magnitude and sparse distribution of CO increases, we would expect these increases to cause
minimal changes in local ambient effect in comparison to current air quality. As noted in
Table 4.1, EGU CO emissions are less than one percent of national CO emissions. As we also
note, local CO emissions are generally a function of traffic congestion from mobile sources. For
these reasons, EGUs do not contribute significantly to national or local CO emissions.
Furthermore, as with VOCs, EGU owner/operators have natural incentives to reduce CO
emissions.
There currently are only five CO nonattainment areas: El Paso, Texas; Las Vegas, NV;
Los Angeles South Coast Air Basin, CA; Missoula, MT; and Reno, NV. For these five local
areas, we computed the net emissions change in the EGU CO emissions between
CAIR/CAMR/CAVR 2020 and NSR Availability. Appendix B of this document includes this
6-29
-------
6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
analysis. As Appendix B shows, in all of these counties, IPM projects no change or a decrease in
emissions in the NSR Efficiency Scenario compared to CAIR/CAMR/CAVR 2020. We would
expect these changes to cause minimal local ambient effect on CO. Therefore, based on lack of
emission increases compared to CAIR/CAMR/CAVR 2020, and the small contribution of EGU
emissions to national and local CO levels, we project no notable local impact on air quality from
EGU CO emissions from the NSR Efficiency Scenario.
6-30
-------
6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
Counties with PMi .t Changes (TPY)
m .gge. .40
| 1-38-40
| | 41 - 10CO
|H 1001 - 3672
I | Countes wish No PMt » Changes
Figure 6.1 2020 County Level PM2.s Emissions Changes - Efficiency Scenario
6-31
-------
6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
Counties with VOC Changes (TPY)
| 1-20-40
•I ~i -;s
| | Counues «i* No VOC Changes
Figure 6.2 2020 County Level VOC Emissions Changes - Efficiency Scenario
6-32
-------
6- NSR Efficiency Scenarios- PM2.5, VOC, and CO
Counties with CO Changes (TRY)
Hi -058--40
I 1-39-40
|^| 41 -731
I I CounSes mi* No CO Changes
Figure 6.3 2020 County Level CO Emissions Changes - Efficiency Scenario
6-33
-------
Appendices
-------
Appendix A
Net Change in 2020 ECU SO2 and NOX Emissions Under NSR Availability and
Efficiency Compared to Total State SOz and NOX Emissions
-------
Appendix A
Appendix A-1. Net Change in 2020 NSR EGU State SO2 Emissions Compared to
Total State SO2 Emissions
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of
Columbia
•Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan.
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
Net Change in
EGU SO2
Emissions
NSR Efficiency
(TRY)
-1,822
0
316
'0
-6
-492
0
-101
0
-55
6,516
0
0
-531
-1,488
-1,230
-1,631
-3,759
0
0
0
163
-4,601
-11,670
285
-2,605
-1,835
-711
-829
0
-293
0
2,058
Net Change in
EGU SO2
Emissions NSR
Availability
(TRY)
-20,740
0
1,856
1,077
239
2,713
184
1,307
0
8,780
-24,179
0
0
11,881
10,404
5,893
2,763
10,965
2,929
325
1,112
641
17,313
-8,724
2,123
8,749
-1,505
1,735
-3,507
0
119
2,497
-1,762
Statewide SO2
Emissions
CAIR/CAMR/CAVR
2020 (TRY)
404,008
21,260
106,516
160,747
92,092
78,121
23,036
103,137
8,992
350,121
303,711
59,337
33,119
606,029
544,567
281,328
90,953
345,501
496,455
68,154
132,385
138,055
544,906
130,026
134,670
445,291
57,540
61,335
33,831
29,980
103,058
181,326
314,928
Efficiency
Change
as%
Total
0%
0%
-2%
0%
0%
-1%
-8%
0%
-3%
0%
2%
0%
0%
-2%
-1%
-3%
-2%
-3%
0%
-3%
-2%
-2%
-1%
-9%
0%
-1%
-3%
-1%
-2%
-12%
0%
0%
0%
Availability
Change as
% Total
-5%
0%
0%
1%
0%
3%
-7%
1%
-3%
3%
-8%
0%
0%
0%
2%
0%
3%
2%
1%
-2%
-1%
-2%
3%
-7%
2%
2%
-3%
3%
-10%
-12%
0%
1%
-1%
A-1
-------
Appendix A
Appendix A-1. Net Change in 2020 NSR EGU State SO2 Emissions Compared to
Total State SO2 Emissions
State
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Net Change in
EGU SO2
Emissions
NSR Efficiency
(TRY)
1,575
-2,177
626
-115
0
9,791
0
-7,632
0
16,582
-2,872
-206
0
9
0
-941
-1,152
-110
Net Change in
EGUSO2
Emissions NSR
Availability
(TRY)
2,391
2,884
-12,045
2,108
474
-8,017
0
1,902
163
-18,791
-7,409
1,775
0
421
578
4,081
339
-6,576
Statewide SO2
Emissions
CAIR/CAMR/CAVR
2020 (TRY)
215,595
214,795
437,903
92,440
58,030
364,935
10,153
173,698
27,631
266,366
618,508
62,308
11,606
187,486
77,584
200,548
290,184
116,317
Efficiency
Change
as%
Total
-1%
-1%
0%
0%
0%
3%
-4%
-7%
0%
6%
-2%
0%
-6%
-2%
0%
-1%
-1%
0%
Availability
Change as
% Total
-1%
1%
-3%
2%
1%
-2%
-4%
-1%
1%
-7%
-3%
3%
-6%
-2%
1%
1%
-1%
-6%
Availability from EPA219b_NSR_OAQPS_5_Pec_2020_(To EPA) 07-05-06.xls. Available as Docket Item EPA-
HQ-OAR-2005-0163, DCN 14.
Efficiency from EPA219b_NSR_OAQPS_2a_Pech_2020 (to EPA) 4-27-06.xls. Available as Docket Item.
Efficiency SO2 and NOX Emissions Available as Docket Item EPA-HQ-OAR-2005-0163, DCN 07.
Statewide emissions data from EPA Analyses on Multipollutant Legislation. Available as Docket Item EPA-HQ-
OAR-2005-0163, DCN 09.
A-2
-------
Appendix A
Appendix A-2. Net Change in 2020 NSR ECU State NOX Emissions Compared to
Total State NOX Emissions
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of
Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Net Change in
ECU NOX
Emissions
NSR Efficiency
(TRY)
857
0
-72
-86
-49
-669
-5
-144
0
51
1,644
0
0
176
-1 ,074
-415
-942
-328
-233
0
0
-78
-1,362
-119
-214
-1,746
-142
-596
-432
0
-149
-8
278
80
-977
Net Change in
ECU NOX
Emissions NSR
Availability
(TPY)
-53
0
2,834
1,321
-87
2,491
246
479
0
1,706
-9,581
0
0
1,923
1,485
476
1,815
2,286
1,199
41
72
670
3,883
1,664
264
1,567
1,745
1,957
-882
34
60
3,421
1,382
1,824
1,784
Statewide NOX
Emissions
CAIR/CAMR/CAVR
2020 (TRY)
278,013
86,419
277,013
220,397
775,856
204,480
77,563
44,155
9,977
413,481
346,886
64,149
115,895
451,611
372,156
. 197,735
232,808
308,910
688,070
60,407
164,694
171,707
443,323
269,632
232,760
286,013
129,714
147,473
86,789
39,228
197,531
264,963
421,630
257,614
107,842
Efficiency
Change
as%
Total
-1%
0%
-1%
0%
-1%
0%
-2%
0%
-2%
-2%
-1%
0%
0%
0%
-1%
-1%
-1%
0%
0%
-1%
-1%
-1%
-1%
0%
0%
-1%
0%
0%
-2%
-2%
0%
0%
-1%
-2%
-1%
Availability
Change as
% Total
-1%
0%
0%
0%
-1%
1%
-2%
1%
-2%
-1%
-4%
0%
0%
0%
0%
-1%
1%
1%
0%
-1%
-1%
0%
0%
1%
0%
1%
1%
1%
-2%
-2%
0%
1%
-1%
-1%
2%
A-3
-------
Appendix A
Appendix A-2. Net Change in 2020 NSR EGU State NOX Emissions Compared to
Total State NOX Emissions
State
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Net Change in
EGU NOX
Emissions
NSR Efficiency
(TRY)
-228
-387
0
2,842
0
-513
-8
1,893
-2,025
-111
0
61
0>
91
1,143
-425
Net Change in
EGUNOX
Emissions NSR
Availability
(TRY)
-5,988
2,291
379
-2,925
0
1,114
57
560
860
2,519
0
454
639
1,806
1,010
2,508
Statewide NOX
Emissions
CAIR/CAMR/CAVR
2020 (TRY)
439,737
275,407
144,461
485,111
23,814
175,163
41,845
251,093
1,163,006
157,523
19,740
339,589
184,239
168,983
216,712
210,178
Efficiency
Change
as%
Total
0%
-1%
0%
0%
0%
-3%
0%
1%
-2%
0%
-1%
-1%
-1%
0%
-1%
0%
Availability
Change as
% Total
-2%
0%
0%
-1%
0%
-2%
0%
0%
-1%
2%
-1%
-1%
0%
1%
-1%
1%
Availability from
2005-0163, DCN
EPA219b_NSR_OAQPS_5_Pec_2020JTo EPA) 07-05-06.xls. Available as Docket Item EPA-HQ-OAR-
14.
Efficiency from EPA219b_NSR_OAQPS_2a_Pech_2020 (to EPA) 4-27-06.xls. Available as Docket Item EPA-HQ-OAR-
2005-0163, DCN 07.
Statewide emissions data from EPA Multipollutant Analyses. Available as Docket Item EPA-HQ-OAR-2005-0163,
DCN 09.
A-4
-------
Appendix B
Net EGU CO Emissions Change in Counties that are Nonattainment for CO
NAAQS
-------
Appendix B
Appendix B. Net EGU CO Emissions Change in Counties that are Nonattainment for CO
State
CA
NV
NV
MT
TX
Class 1
Name(s)
Los Angeles
South Coast
Air Basin
Reno
Las Vegas
Missoula
El Paso
Counties
Los Angeles
Orange
Riverside
San Bernardino
Washoe
Clark
Missoula
El Paso
CAIR7CAMR7CAVR CO
Emissions 2020 (tpy)
7,765
43
12
540
-
4,691
-
3
NSRCO
Availability
(tpy)
7,050
43
12
553
.
4,493
-
0
Net CO Emissions
Change (NSR
Availability Minus
CAIR/CAMR/CAVR 2020)
-715
0
0
13
-
-198
-
-3
NSRCO
Efficiency
(tpy)
7,764
43
12
540
.
4,619
-
3
Net CO
Change (Is
IV
CAIR/CAM
CAIR/CAMR/CAVR data and availability emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability PM2.5, VOC,
and CO.]
Efficiency emissions information available as Docket Item EPA-HQ-OAR-2005-0163, DCN 18. [NSR Efficiency PM2.5, VOC, and CO.]
-------
United States
Environmental Protection
Agency
Office of Air Quality Planning and
Standards
Air Quality Policy Division
New Source Review Group
Research Triangle Park, NC
Publication No. EPA-
457/R-07-001
January 2007
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