On a state-by-state basis, all retail electricity prices vary considerably. In 2014, the national average retail electricity price (all sectors) was 10.44 cents/KWh, with a range from 7.13 cents (Washington) to 33.43 (Hawaii).

     Average national retail electricity prices increased between 2000 and 2014 by 15.5 percent in real terms (2011$). The amount of increase differed for the three major end use categories (residential, commercial and industrial). National average industrial prices increased the most (15.3 percent), and commercial prices increased the least (8.9 percent). The real year prices for 2000 through 2014 are shown in Figure 2-5.

Figure 2-5.	Real National Average Electricity Prices for Three Major End-Use Categories
Source: EIA Monthly Energy Review, Table 9.8
	Most of these electricity price increases occurred between 2002 and 2008; since 2008 nominal electricity prices have been relatively stable while overall inflation continued to increase. The increase in nominal electricity prices for the major end use categories, as well as increases in the GDP price and CPI-U indices for comparison, are shown in Figure 2-6.

Figure 2-6.	Relative Increases in Nominal National Average Electricity Prices for Major End-Use Categories, With Inflation Indices
	For a longer term perspective, Figure 2-7 shows real (2011$) electricity prices for the three major customer categories since 1960,  and Figure 2-8 shows the relative change in real electricity prices relative to the prices since 1960. As can be seen in the figures, the price for industrial customers has always been lower than for either residential or commercial customers, but the industrial price has been more volatile. While the industrial real price of electricity in 2014 was relatively unchanged from 1960, residential and commercial real prices are 22 percent and 28 percent lower respectively than in 1960.

Figure 2-7.	Real National Average Electricity Prices for Three Major End-Use Categories (including taxes), 1960-2014 (2011$)
Source: EIA Monthly Energy Review , May 2016, Table 9.8

Figure 2-8.	Relative Change in Real National Average Electricity Prices (2011$) for Three Major End-Use Categories
Source: EIA Monthly Energy Review, May 2016, Table 9.8

2.3.2	Prices of Fossil Fuels Used for Generating Electricity
      Another important factor in the changes in electricity prices are the changes in delivered fuel prices for the three major fossil fuels used in electricity generation; coal, natural gas and oil. Relative to real prices in 2000, the national average real price (in 2011$) of coal delivered to EGUs in 2014 had increased by 49 percent, while the real price of natural gas decreased by 12 percent. The real price of delivered oil increased by 109 percent, but with oil declining as an EGU fuel (in 2014 oil generated only 1 percent of electricity) the doubling of delivered oil prices had little overall impact in the electricity market. The combined real delivered price of all fossil fuels in 2014 increased by 44 percent over 2000 prices. Figure 2-9 shows the relative changes in real price of all 3 fossil fuels between 2000 and 2014.

Figure 2-9.	Relative Real Prices of Fossil Fuels for Electricity Generation; Change in National Average Real Price per MMBtu Delivered to EGU
Source: Monthly Energy Review, May 2016, Table 9.9

2.3.3	Changes in Electricity Intensity of the U.S. Economy from 2000 to 2014
An important aspect of the changes in electricity generation (i.e., electricity demand) between 2000 and 2014 is that while total net generation increased by 8 percent over that period, the demand growth for generation was lower than both the population growth (13 percent) and real GDP growth (27 percent). Figure 2-10 shows the growth of electricity generation, population and real GDP during this period.

Figure 2-10.	Relative Growth of Electricity Generation, Population and Real GDP Since 2000
Sources: Generation: U.S. EIA Monthly Energy Review, May 2016. Table 7.2a Electricity Net Generation: Total (All Sectors). Population: U.S. Census. Real GDP: 2016 Economic Report of the President, Table B-3.

	Because demand for electricity generation grew more slowly than both the population and GDP, the relative electric intensity of the U.S. economy improved (i.e., less electricity used per person and per real dollar of output) during 2000 to 2014. On a per capita basis, real GDP per capita grew by 12 percent between 2000 and 2014. At the same time electricity generation per capita decreased by 4 percent. The combined effect of these two changes improved the overall electricity efficiency of the U.S. market economy. Electricity generation per dollar of real GDP decreased 15 percent. These relative changes are shown in Figure 2-11. Figures 2-10 and 2-11 clearly show the effects of the 2007  -  2009 recession on both GDP and electricity generation, as well as the effects of the subsequent economic recovery.

Figure 2-11.	Relative Change of Real GDP, Population and Electricity Generation Intensity Since 2000
Sources: Generation: U.S. EIA Monthly Energy Review, May 2016. Table 7.2a Electricity Net Generation: Total (All Sectors). Population: U.S. Census. Real GDP: 2016 Economic Report of the President, Table B-3.

2.4	Deregulation and Restructuring
The process of restructuring and deregulation of wholesale and retail electricity markets has changed the structure of the electric power industry. In addition to reorganizing asset management between companies, restructuring sought a functional unbundling of the generation, transmission, distribution, and ancillary services the power sector has historically provided, with the aim of enhancing competition in the generation segment of the industry.
Beginning in the 1970s, government policy shifted against traditional regulatory approaches and in favor of deregulation for many important industries, including transportation (notably commercial airlines), communications, and energy, which were all thought to be natural monopolies (prior to 1970) that warranted governmental control of pricing. However, deregulation efforts in the power sector were most active during the 1990s. Some of the primary drivers for deregulation of electric power included the desire for more efficient investment choices, the economic incentive to provide least-cost electric rates through market competition, reduced costs of combustion turbine technology that opened the door for more companies to sell power with smaller investments, and complexity of monitoring utilities' cost of service and establishing cost-based rates for various customer classes. Deregulation and market restructuring in the power sector involved the divestiture of generation from utilities, the formation of organized wholesale spot energy markets with economic mechanisms for the rationing of scarce transmission resources during periods of peak demand, the introduction of retail choice programs, and the establishment of new forms of market oversight and coordination.
The pace of restructuring in the electric power industry slowed significantly in response to market volatility in California and financial turmoil associated with bankruptcy filings of key energy companies. By the end of 2001, restructuring had either been delayed or suspended in eight states that previously enacted legislation or issued regulatory orders for its implementation (shown as "Suspended" in Figure 2-12). Eighteen other states that had seriously explored the possibility of deregulation in 2000 reported no legislative or regulatory activity in 2001 (EIA, 2003) ("Not Active" in Figure 2-13). Currently, there are 15 states plus the District of Columbia where price deregulation of generation (restructuring) has occurred ("Active" in Figure 2-13). Power sector restructuring is more or less at a standstill; by 2010 there were no active proposals under review by the Federal Energy Regulatory Commission (FERC) for actions aimed at wider restructuring, and no additional states have begun retail deregulation activity since that time.

Figure 2-12.	Status of State Electricity Industry Restructuring Activities
Source:	EIA 2010. "Status of Electricity Restructuring by State." Available online at: <http://www.eia.gov/cneaf/electricity/page/restructuring/restructure_elect.html>.

	One major effect of the restructuring and deregulation of the power sector was a significant change in type of ownership of electricity generating units in the states that deregulated prices. Throughout most of the 20th century electricity was supplied by vertically integrated regulated utilities. The traditional integrated utilities provided generation, transmission and distribution in their designated areas, and prices were set by cost of service regulations set by state government agencies (e.g., Public Utility Commissions). Deregulation and restructuring resulted in unbundling of the vertical integration structure. Transmission and distribution continued to operate as monopolies with cost of service regulation, while generation shifted to a mix of ownership affiliates of traditional utility ownership and some generation owned and operated by competitive companies known as Independent Power Producers (IPPs). The resulting generating sector differed by state or region, as the power sector adapted to the restructuring and deregulation requirements in each state.
	By the year 2000, the major impacts of adapting to changes brought about by deregulation and restructuring during the 1990s were nearing completion. In 2000, traditional utilities owned 77 percent of U.S. generating capacity (MW) while IPPs owned 23 of U.S. generating capacity, respectively. The mix of electricity generated (MWh) was more heavily weighted towards the utilities, with a distribution in 2000 of 83 percent, and 17 percent for IPPs.
	Since 2000, IPPs have expanded faster than traditional utilities, substantially increasing their share by 2014 of both capacity (59 percent utility, 41 percent IPPs) and generation (60 percent utility, 40 percent IPP).
	The mix of capacity and generation for each of the ownership types is shown in Figures 2-13 (capacity) and 2-14 (generation). The capacity and generation data for commercial and industrial owners are not shown on these figures due to the small magnitude of those ownership

types. A portion of the shift of capacity and generation is due to sales and transfers of generation assets from traditional utilities to IPPs, rather than strictly the result of newly built units.

 Figures 2-13 & 2-14.	 Capacity and Generation Mix by Ownership Type, 2000 & 2014

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CHAPTER 3:  EMISSIONS AND AIR QUALITY MODELING IMPACTS
Overview
	This Chapter describes the methods for estimating emissions and air quality for the 2017 baseline and 2017 illustrative final CSAPR Update emissions budgets described in Chapter 4. In Section 3.1, we describe the air quality modeling platform, in Section 3.2 we describe the development of emissions inventories used in the air quality modeling, and in Section 3.3 we describe the methods for processing the air quality modeling outputs to create inputs for estimating benefits. The 2017 baseline and illustrative control case air quality model predictions were used to calculate "benefit per ton" factors of reduced nitrogen oxides (NOX) on both ozone and fine particulate matter (PM2.5) concentrations.[,] These factors were then used to estimate the benefits of the regulatory control alternatives, as described in Chapter 5. Details on the air quality modeling are provided in the Air Quality Modeling Technical Support Document, which can be found in the docket for this rule.
3.1	Air Quality Modeling Platform
      We use the emissions inputs described in Section 3.2 for national scale applications of the Comprehensive Air Quality Model with Extensions (CAMx) modeling system to estimate ozone and PM2.5 air quality in the contiguous U.S.  CAMx is a three-dimensional grid-based Eulerian photochemical model designed to estimate ozone and PM2.5 concentrations over seasonal and annual time periods.  Because it accounts for spatial and temporal variations as well as differences in the reactivity of emissions, CAMx is useful for evaluating the impacts of the rule on ozone and PM2.5 concentrations.
      For this analysis we used CAMx to simulate air quality for every hour of every day of the year.  These model applications require a variety of input files that contain information pertaining to the modeling domain and simulation period.  In addition to the CAMx model, our modeling system includes (1) emissions for a 2011 base year and 2017 emissions for the baseline and the final CSAPR Update emissions budgets, (2) meteorological data inputs for the year 2011, and (3) estimates of intercontinental transport (i.e., boundary concentrations) from a global photochemical model.  Using these data, CAMx generates hourly predictions of ozone and PM2.5 component species concentrations.  The model predictions for the 2011 base year, the baseline in 2017, and the final CSAPR Update emissions budgets were combined with ambient air quality observations to calculate seasonal mean ozone air quality metrics and annual mean PM2.5 for the baseline in 2017 and the final CSAPR Update emissions budgets, which were then used as input for the benefits analysis.
3.1.1	Simulation Periods
For use in this benefits analysis, the simulation period modeled by CAMx included separate full-year application for each of the three emissions scenarios (i.e., 2011 base year, 2017 baseline and 2017 final CSAPR Update emissions budgets).
3.1.2	Air Quality Modeling Domain
      Figure 3-1 shows the geographic extent of the modeling domain that was used for air quality modeling in this analysis. The domain covers the 48 contiguous states, along with the southern portions of Canada and the northern portions of Mexico. This modeling domain contains 25 vertical layers with a top at about 17,550 meters, or 50 millibars (mb), and horizontal grid resolution of 12 km x 12 km. The model simulations produce hourly air quality concentrations for each 12 km[2] grid cell across the modeling domain.

Figure 3-1.	National air quality modeling domain.
3.1.3	Air Quality Model Inputs
	CAMx requires a variety of input files that contain information pertaining to the modeling domain and simulation period.  These include gridded, hourly emissions estimates and meteorological data, and initial and boundary conditions.  Separate emissions inventories were prepared for the 2011 base year, the 2017 baseline, and final CSAPR Update emissions budgets.  All other inputs were specified for the 2011 base year model application and remained unchanged for each future-year modeling scenario.
      CAMx requires detailed emissions inventories containing temporally allocated emissions for each grid-cell in the modeling domain for each species being simulated, as described in Section 3.2.  The meteorological data model inputs for the 2011 base year were derived from running Version 3.4 of the Weather Research Forecasting Model (WRF). The meteorological outputs from WRF include hourly-varying horizontal wind components (i.e., speed and direction), temperature, moisture, vertical diffusion rates, and rainfall rates for each grid cell in each vertical layer. The CAMx lateral boundary and initial species concentrations are provided by a three-dimensional global atmospheric chemistry and transport model (GEOS-Chem).  The lateral boundary species concentrations varied with height and time (every 3 hours).
3.2	Development of Emissions Inventories
3.2.1	2011 Base Year Emissions
The 2011 emissions inventories are primarily based on the 2011 National Emissions Inventory, version 2 (2011NEIv2) for point sources, nonpoint sources, commercial marine vessels (CMV), nonroad mobile sources and fires, although the inventories used for modeling often have temporal resolution additional to what is available in the NEI. The onroad mobile source emissions are similar to those in the 2011NEIv2, but were generated using the official release 2014a version of the Motor Vehicle Emissions Simulator (MOVES2014a) (http://www3.epa.gov/otaq/models/moves/), while the 2011NEIv2 emissions were generated using MOVES2014. Biogenic emissions and emissions inventories for Canada and Mexico are also included in the air quality modeling. The meteorological data used to develop and temporally allocate emissions were consistent with the 2011 data used for the air quality modeling.
The emissions inventories and modeling thereof incorporate comments received on the Notice of Data Availability (NODA) published in the Federal Register on August 4, 2015 (80 FR 46271), and from comments on the earlier notices for the 2011 and 2018 emissions modeling platforms: the Notice of Availability of the Environmental Protection Agency's 2011 Emissions Modeling Platform issued November 27, 2013 (78 FR 70935) and the Notice of Availability of the Environmental Protection Agency's 2018 Emissions Modeling Platform issued January 14, 2014 (79 FR 2437), respectively.  The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system (Houyoux et al., 2000) version 37 was used to prepare the emissions inventories for CAMx.  Details regarding the development of the emission inventories and emissions modeling for the 2011 base year and the 2017 baseline are documented in the Technical Support Document Preparation of Emissions Inventories for the Version 6.3, 2011 Emissions Modeling Platform (EPA, 2016) and can be found in the docket for the CSAPR Update.
3.2.2	2017 Baseline Emissions
The emission inventories for the 2017 future baseline have been developed using projection methods that are specific to emission source type. Future emissions are projected from the 2011 base year either by running models to estimate future year emissions from specific types of emission sources (e.g., EGUs, and onroad and nonroad mobile sources), or for other types of sources by adjusting the base year emissions according to the best estimate of changes expected to occur in the intervening years (e.g., non-EGU point and nonpoint sources).  The same emissions are used in the base and future years for biogenic, fire, and offshore oil platform sources. For the remaining sectors, rules and specific legal obligations that go into effect in the intervening years, along with changes in activity for the sector, are considered when possible. The modeled 2017 baseline emission inventories represent predicted emissions that account for Federal and State measures promulgated or under reconsideration by February, 2016. With the exception of speciation profiles for mobile sources and temporal profiles for EGUs, the same ancillary data files are used to prepare the future year emissions inventories for air quality modeling as were used to prepare the 2011 base year inventories. Details on the included measures are provided the emissions modeling TSD (EPA, 2016) and in Chapter 4 .
The 2017 baseline inventory for EGUs represents demand growth, fuel resource availability, generating technology cost and performance, and other economic factors affecting power sector behavior. The EGU emissions for the air quality modeling were developed using the IPM version 5.15 base case. The IPM base case reflects the expected emissions accounting for the effects of environmental rules and regulations, consent decrees and settlements, plant closures, units built, control devices installed, and forecast unit construction through the calendar year 2017. Significant federal and state measures that area accounted for in the baseline EGU emissions in 2017 are discussed in Chapter 4.
The 2018 emissions output from IPM were adjusted to reflect 2017 emissions levels as described in "Calculating 2017 NOx Emissions" (see http://www2.epa.gov/airmarkets/calculating-2017-nox-emissions).  Temporal allocation was used to process the seasonal emissions outputs from IPM to hourly emissions.  To the extent possible, this temporal allocation process preserved the emissions patterns from the base year (2011), while keeping the maximum emissions below those that occurred in the period 2011-2014.
  Projections for most stationary emissions sources other than EGUs (i.e., non-EGUs) were developed by using the EPA Control Strategy Tool (CoST) to create post-controls future year inventories. CoST is described at http://www3.epa.gov/ttnecas1/cost.htm. The 2017 baseline non-EGU stationary source emissions inventory includes all enforceable national rules and programs, including the Reciprocating Internal Combustion Engines (RICE) and cement manufacturing National Emissions Standards for Hazardous Air Pollutants (NESHAPs) and Boiler Maximum Achievable Control Technology (MACT) reconsideration reductions. Projection factors and percent reductions for non-EGU point sources reflect comments received by EPA in response to 80 FR 46271, along with emissions reductions due to national and local rules, control programs, plant closures, consent decrees and settlements. Ancillary reductions to criteria air pollutant (CAP) emissions from stationary engines as a result of the Reciprocating Internal Combustion Engines (RICE) National Emission Standard for Hazardous Air Pollutants (NESHAP) are included.  Reductions due to the New Source Performance Standards (NSPS) volatile organic compound (VOC) controls for oil and gas sources, and the NSPS controls for process heaters, internal combustion engines, and natural gas turbines are also included.
Regional projection factors for point and nonpoint oil and gas emissions were developed using Annual Energy Outlook (AEO) 2014 (U.S. EIA, 2014) projections from year 2011 to year 2018. Projected emissions for corn ethanol, cellulosic ethanol and biodiesel plants, refineries and upstream impacts represent the Energy Independence and Security Act (EISA) renewable fuel standards mandate in the Renewable Fuel Standards Program (RFS2).  Airport-specific terminal area forecast (TAF) data were used for aircraft to account for projected changes in landing/takeoff activity.
Projection factors for livestock are based on expected changes in animal population from 2005 Department of Agriculture data, updated according to EPA experts in July 2012; fertilizer application ammonia (NH3) emissions projections include upstream impacts representing EISA. Area fugitive dust projection factors for categories related to livestock estimates are based on expected changes in animal population and upstream impacts from EISA. Fugitive dust for paved and unpaved roads take growth in VMT and population into account. Residential Wood Combustion (RWC) projection factors reflect assumed growth of wood burning appliances based on sales data, equipment replacement rates and change outs. These changes include growth in lower-emitting stoves and a reduction in higher emitting stoves. Impacts from the NSPS for wood burning devices are also included.
Projection factors for the remaining nonpoint sources such as stationary source fuel combustion, industrial processes, solvent utilization, and waste disposal, reflect comments received on the projection of these sources as a result of rulemakings and outreach to states on emission inventories, and they also include emission reductions due to control programs.  Future year portable fuel container (PFC) inventories reflect the impact of the final Mobile Source Air Toxics (MSAT2) rule along with state comments received in response to 80 FR 46271.
The MOVES2014a-based 2017 onroad emissions account for changes in activity data and the impact of on-the-books national rules including: the Tier 3 Vehicle Emission and Fuel Standards Program, the Light-Duty Vehicle Tier 2 Rule, the Heavy Duty Diesel Rule, the Mobile Source Air Toxics Rule, the Renewable Fuel Standard (RFS2), the Light Duty Green House Gas/Corporate Average Fuel Efficiency (CAFE) standards for 2012-2016, the Heavy-Duty Vehicle Greenhouse Gas Rule, the 2017 and the Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards; Final Rule (LD GHG). The 2017 onroad emissions also include state rules related to the adoption of low emission vehicle (LEV) standards, inspection and maintenance programs, Stage II refueling controls, and local fuel restrictions. For California, the baseline emissions were provided by the California Air Resources Board and include most this state's on-the-books regulations, such as those for idling of heavy-duty vehicles, chip reflash, public fleets, track trucks, drayage trucks, and heavy duty trucks and buses (CARB, 2016).
The nonroad mobile source emissions for 2017, including those for railroads and commercial marine vessel emissions, also include all national control programs. These control programs include the Clean Air Nonroad Diesel Rule  -  Tier 4, the Nonroad Spark Ignition rules, and the Locomotive-Marine Engine rule.   For ocean-going vessels (Class 3 marine), the emissions data reflect the 2005 voluntary Vessel Speed Reduction (VSR) within 20 nautical miles, the 2007 and 2008 auxiliary engine rules, the 40 nautical mile VSR program, the 2009 Low Sulfur Fuel regulation, the 2009-2018 cold ironing regulation, the use of 1% sulfur fuel in the Emissions Control Area (ECA) zone, the 2012-2015 Tier 2 NOx controls, the 2016 0.1% sulfur fuel regulation in ECA zone, and the 2016 International Marine Organization (IMO) Tier 3 NOx controls. Non-U.S. and U.S. category 3 commercial marine emissions were projected to 2017 using consistent methods that incorporated controls based on ECA and IMO global NOx and sulfur dioxide (SO2) controls. For California, the 2017 emissions for these categories reflect the state's Off-Road Construction Rule for "In-Use Diesel", cargo handling equipment rules in place as of 2011 (see http://www.arb.ca.gov/ports/cargo/cargo.htm), and state rules through 2011 related to Transportation Refrigeration Units, the Spark-Ignition Marine Engine and Boat Regulations adopted on July 24, 2008 for pleasure craft, and the 2007 and 2010 regulations to reduce emissions from commercial harbor craft.
The modeled 2011 emission case uses 2010 Canada emissions data, which is the latest year for which Environment Canada had provided data at the time the modeling was performed. Although no accompanying future-year projected baseline inventories were provided in a form suitable for this analysis, for the 2017 emissions, known shutdowns to Canadian coal EGU units in Ontario were incorporated. In addition, onroad and nonroad mobile source emissions were scaled to represent average changes in U.S. emissions due to the similarities between U.S. and Canadian mobile source regulations. For Mexico, emissions compiled from the Inventario Nacional de Emisiones de Mexico, 2008 were used for 2011, as that was the latest complete inventory available.  For the 2017 baseline, projected emissions for the year 2018 based on the 2008 inventory were used (ERG, 2014). Table 3-1 shows the modeled national 2011 and 2017 NOX and VOC emissions by sector. Additional details on the base year and projected inventories and on the emissions by state are given in the emissions modeling TSD (US EPA, 2016).
Table 3-1.		2011 Base Year and 2017 Baseline NOx and VOC Emissions by Sector (thousand tons)
                                    Sector
                                   2011 NOx
                                   2017 NOx
                                   2011 VOC
                                   2017 VOC
                                   EGU-point
                                     2,100
                                     1,300
                                      38
                                      36
                                 NonEGU-point
                                     1,200
                                     1,200
                                      800
                                      800
                               Point oil and gas
                                      510
                                      440
                                      160
                                      170
                                     Fires
                                      380
                                      380
                                     4,800
                                     4,800
                             Nonpoint oil and gas
                                      660
                                      730
                                     2,500
                                     2,900
                          Residential wood combustion
                                      34
                                      36
                                      440
                                      440
                                Other nonpoint
                                      720
                                      730
                                     3,700
                                     3,500
                                    Nonroad
                                     1,600
                                     1,100
                                     2,000
                                     1,400
                                    Onroad
                                     5,600
                                     3,000
                                     2,700
                                     1,500
                        Commercial marine vessels (CMV)
                                      410
                                      360
                                      13
                                      13
                                  Locomotive
                                      790
                                      680
                                      41
                                      28
                                   Biogenics
                                      910
                                      910
                                    42,800
                                    42,800
                                     TOTAL
                                    15,000
                                    10,900
                                    59,900
                                    58,400

3.2.3	2017 Illustrative Emissions Case for the Final CSAPR Update Emissions Budgets
The EPA's approach to developing IPM v5.15-based emissions for the final CSAPR Update emissions budgets is methodologically consistent with the EPA's approach to establishing the final EGU NOX ozone-season emissions budgets to reduce interstate ozone transport for the 2008 ozone NAAQS. These illustrative EGU NOX ozone-season emissions budgets and their associated assurance levels, along with corresponding emission changes for other pollutants as predicted by IPM, were modeled in IPM v5.15 to create the illustrative final emissions case.  As noted in Chapter 4, section 4.3.1, although IPM v5.15 was used for modeling EGU emission for the baseline and the illustrative final emissions case, there were additional updates to EGU emissions that were included in the IPM run for the CSAPR Update illustrative final emissions case that were not included in the baseline. See Chapter 4, Table 4-4 for the illustrative final emissions.
The emissions for the illustrative final emissions case were processed for air quality modeling in the same way as the 2017 baseline. The only difference in the emissions inventories were the EGU emissions.  The hourly temporal allocation for the illustrative final emissions case inventories preserved the patterns from the 2017 baseline to the extent possible by maintaining consistent unit-specific and regional, where appropriate, profiles in both cases. Thus, the same hourly temporal patterns in the baseline are reflected in this final emissions case, including any adjustments made to constrain the hourly 2017 emissions below the maximum levels during the 2011-2014 period.
3.2.4	Effect of Emissions Reductions on Downwind Receptors
      As described in Sections V and VI of the preamble, and in the Ozone Transport Policy Analysis Final Rule TSD, and summarized here, EPA evaluated the effect of the CSAPR Update on nonattainment and maintenance receptors with respect to interstate transport for the 2008 ozone NAAQS. The 2008 ozone standard is 75 parts per billion (ppb), annual fourth-highest daily maximum 8 hour concentration, averaged over 3 years. As described in Section V of the preamble, the nonattainment and maintenance receptors with respect to interstate transport for the 2008 ozone NAAQS in 2017 were identified using air quality modeling for 2011 and 2017 combined with measured design values for a base period encompassing 2009-2013.   There are 19 receptors in 9 states identified as non-attainment and/or maintenance monitors for this CSAPR Update. Six of these monitors are non-attainment monitors and 13 are maintenance monitors. The average of the average design values of all 19 receptors is 75.9 ppb in 2017. The average of the maximum design values of all 19 receptors is 78.1 ppb in 2017.
      As described in the Ozone Transport Policy Analysis Final Rule TSD, these design values were identified using an updated version of the EGU base case, the same one that was used to establish emission budgets for the final CSAPR Update. Like the base case used to estimate the costs and benefits of the CSAPR Update, this base case accounts for the Pennsylvania NOx RACT final rule promulgated in April 2016. However, the 2017 EGU emission levels in this base case also account for recent historical information about emissions, which grounds the 2017 emission projections in historic data for the purpose of setting emission budgets. To evaluate the effect of the CSAPR Update on the 19 nonattainment and/or maintenance receptors, we assume that the affected source emissions under the CSAPR Update equals the EGU NOX ozone season emission budgets. That is, that the difference in the affected source emission levels from the updated base case and the final EGU NOX ozone season emission budgets was used to estimate the change in average and maximum design values at the 19 receptors reported in this section of the RIA.
      The ozone Air Quality Assessment Tool (AQAT) was used to estimate the impact of the upwind states' EGU NOX reductions on downwind ozone pollution concentrations. Specifically, AQAT was used to forecast both the average and maximum design values at the 19 receptors. The AQAT was developed specifically for use in the CSAPR Update rule. This tool uses air quality modeling outputs to calibrate the predicted change in ozone concentrations to reflect changes in NOX emissions. See the Ozone Transport Policy Analysis Final Rule TSD for the air quality estimates and for details on the construction of the AQAT.   The effect of the CSAPR Update on the 19 nonattainment and/or maintenance receptors is an average reduction in the average and maximum ozone design values of 0.28 ppb and 0.29 ppb in 2017, respectively. The emission reductions are expected to reduce the average and maximum design values below the level of the NAAQS at three of the 19 receptors, therefore resolving their nonattainment and maintenance issues, while bringing the other 16 receptors closer to attainment and maintenance. Results for each of the 19 receptors are described in the Ozone Transport Policy Analysis Final Rule TSD.
3.3	Post-Processing of Air Quality Modeling for Benefits Calculations
3.3.1	Converting CAMx Ozone Outputs to Benefits Inputs
	The CAMx model generates predictions of hourly ozone concentrations for every grid cell.  Future-year estimates of ozone for each of three health benefits metrics for ozone were calculated using model predictions. The modeled change in ozone between the 2011 base year and the 2017 future baseline and illustrative control case were used to create relative reduction factors (RRFs) which were then applied to 2011 ambient ozone concentrations, as described below.  The health benefits metrics for ozone are May through September seasonal average 8-hour daily maximum ozone concentrations. 	The procedures for determining the ozone RRFs for these metrics are similar to those described in EPA guidance for modeling attainment of the ozone standard (EPA, 2014).  This guidance recommends that model predictions be used in a relative sense to estimate changes expected to occur in ozone concentrations for a future year emissions case.  The RRFs and future year ozone concentrations were calculated using EPA's software Modeled Attainment Test Software (MATS) (Abt, 2014).  EPA used MATS to estimate the ozone impacts of the emissions reductions in the 2017 illustrative control case.
	For the purposes of projecting future ozone concentrations for input to the benefits calculations, we applied MATS using the base year 2011 modeling results and the results from the 2017 baseline and 2017 illustrative control case scenarios.  In our application of MATS for ozone we used the ozone monitoring data centered about 2011 (2010-2012 ozone data) from the Aerometric Information Retrieval System (AIRS) as the set of base-year measured concentrations. The ambient ozone data and modeled ozone outputs were combined using the MATS "eVNA" spatial fusion technique to generate gridded sets of spatial fields (interpolated ozone metrics for each modeled 12km grid cell in the modeling domain) for each of the three ozone metrics for the 2011 base year period.  The ratio of the seasonal average model-predicted future case ozone concentrations to the corresponding seasonal average model-predicted 2011 concentrations in each grid cell (RRF's) was calculated and then multiplied by the gridded interpolated ozone concentrations for each metric to produce gridded ozone concentrations for the 2017 baseline and 2017 illustrative control case. The resulting gridded files for the 2017 baseline and illustrative control cases were then input to the Benefits Mapping and Analysis Program  -  Community Edition (BenMAP-CE) (version 1.1) (Abt, 2012) to calculate benefit per ton factors for each metric. Information on the calculation of the benefit per ton factors is provided in Chapter 5.
3.3.2	Converting CAMx PM2.5 Outputs to Benefits Inputs
  The CAMx model (ENVIRON, 2014) generates predictions of hourly PM2.5 species concentrations for every grid cell.  The species include a primary fraction and several secondary PM2.5 species (e.g., sulfates, nitrates, and organics).  PM2.5 is calculated as the sum of the primary and the secondary formed particles.  Future-year estimates of PM2.5 were calculated using RRFs applied to 2010-2012 ambient PM2.5 and PM2.5 species concentrations, as described below.
	The procedures for determining the RRFs are similar to those in EPA guidance for modeling the PM2.5 NAAQS (EPA, 2014).  This guidance recommends that model predictions be used in a relative sense to estimate changes expected to occur in each PM2.5 species.  The modeled attainment test procedure for calculating future year PM2.5 values is described in the modeling guidance and is codified in EPA's MATS.  EPA used this procedure to estimate the ambient impacts of the emissions reductions in the 2017 illustrative control case.  For the purposes of projecting future PM2.5 concentrations for input to the benefits calculations, we applied the modeled attainment test procedure using the base year 2011 modeling results and the results from the 2017 baseline and 2017 illustrative control case.  In our application of MATS for PM2.5 we used the PM2.5 monitoring data and speciated monitoring data centered about 2011 (2010-2012) from the state PM2.5 Federal Reference Method (FRM) network, the Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) network as the set of base-year measured concentrations. The ambient PM2.5 and species data and modeled PM2.5 and species outputs were combined using the MATS "eVNA" spatial fusion technique to generate gridded sets of spatial fields (interpolated annual average PM2.5 and species concentrations for each modeled 12km grid cell in the modeling domain) for the 2011 base year period.  The ratio of the quarterly average model-predicted future case PM2.5 species concentrations to the corresponding quarterly average model-predicted 2011 species concentrations in each grid cell (RRF's) were calculated and then multiplied by the gridded interpolated PM2.5 species concentrations to produce gridded PM2.5 species concentrations for the 2017 baseline and 2017 illustrative control case. Output files from this process include both quarterly and annual mean PM2.5 mass concentrations and PM2.5 species concentrations which are then processed to produce BenMAP input files containing annual mean PM2.5 mass concentrations for the 2017 baseline and for the 2017 illustrative control case.  These data files were then input to BenMAP to calculate PM2.5 benefit per ton factors. Information on the calculation of the benefit per ton factors is provided in Chapter 5.
3.4	Limitations
	The air quality modeling for this analysis relied upon state-of-the-science tools, methods, and data. Still, there are uncertainties associated with the projected baseline and illustrative control case ozone concentrations that stem from limitations and uncertainties in the individual components of the modeling process. These include (1) limitations in the emissions inventories for specific source categories in terms of representing base year emissions and the methodologies and economic assumptions associated with projecting emissions to a future year, (2) uncertainties in the construct of the photochemical model that may affect the characterization of physical properties and chemical reactions, (3) uncertainties in other model inputs such as meteorology and international transport, and (4) uncertainties in the measured ozone concentrations that are used as the basis for projecting future concentrations at individual locations and the spatial fields used for benefits calculations. It is not clear that the net effect of the limitations and uncertainties in the modeling process bias the analysis in either direction. Rather, they should be viewed as considerations in interpreting the results.
3.5	References
Abt Associates, 2012. "BenMAP User's Manual Appendices," prepared for U.S. Research Triangle Park, NC: U. S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Available at: <http://www.epa.gov/air/benmap/models/BenMAPAppendicesOct2012.pdf>. Accessed June 6, 2015.
Abt Associates, 2014. User's Guide: Modeled Attainment Test Software. http://www3.epa.gov/scram001/modelingapps_mats.htm.
California Air Resources Board, 2016.  EMFAC2014 v1.0.7 technical documentation.  Available at http://www.arb.ca.gov/msei/downloads/emfac2014/emfac2014-vol3-technical-documentation-052015.pdf.
ENVIRON, 2014. User's Guide Comprehensive Air Quality Model with Extensions version 6.11, www.camx.com. ENVIRON International Corporation, Novato, CA.
ERG, 2014. Develop Mexico Future Year Emissions Final Report. Available at ftp://ftp.epa.gov/EmisInventory/2011v6/v2platform/2011emissions/Mexico_Emissions_WA%204-09_final_report_121814.pdf.
Houyoux, M.R., Vukovich, J.M., Coats, C.J., Wheeler, N.J.M., Kasibhatla, P.S. (2000), Emissions inventory development and processing for the Seasonal Model for Regional Air Quality (SMRAQ) project, Journal of Geophysical Research  -  Atmospheres, 105(D7), 9079-9090.
U.S. Energy Information Administration, 2014. Annual Energy Outlook, 2014 (http://www.eia.gov/forecasts/archive/aeo14/).
 U.S. Environmental Protection Agency, 2014. Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze, Research Triangle Park, NC. (http://www3.epa.gov/ttn/scram/guidance/guide/Draft_O3-PM-RH_Modeling_Guidance-2014.pdf)
U.S. Environmental Protection Agency, 2016. Preparation of Emissions Inventories for the Version 6.3, 2011 Emissions Modeling Platform, Research Triangle Park, NC. Available from the 2011v6.3 platform section of https://www.epa.gov/air-emissions-modeling/2011-version-6-air-emissions-modeling-platforms.

CHAPTER 4:  COST, EMISSIONS, AND ENERGY IMPACTS
Overview
      This chapter reports the compliance costs, emissions, and energy analyses performed for the final CSAPR Update. The EPA used the Integrated Planning Model (IPM), developed by ICF International, to conduct most of the analysis discussed in this chapter.
As explained in detail below, this chapter presents analysis of three regulatory control alternatives. These regulatory control alternatives include assumptions about the possible actions that electric generating units (EGUs) may pursue to reduce their nitrogen oxides (NOX) emissions in order to comply with the EGU NOX ozone season emission budgets in the 22-state region.
 The chapter is organized as follows: following a summary of the regulatory control alternatives analyzed and a summary of the EPA's methodology, we present estimates of compliance costs, as well as estimated impacts on emissions, generation, capacity, fuel use, fuel price, and retail electricity price.  Additional impacts are presented in subsequent chapters.
4.1	Regulatory Control Alternatives
      The primary purpose of the CSAPR Update is to address interstate air quality impacts with respect to the 2008 ozone National Ambient Air Quality Standards (NAAQS). The EPA originally published CSAPR on August 8, 2011, to address interstate transport of ozone pollution under the 1997 ozone NAAQS. The CSAPR Update will reduce ozone season (May 1 through September 30) NOX emissions in 22 eastern states that can be transported downwind as NOX or, after transformation in the atmosphere, as ozone, and can negatively affect air quality and public health in downwind areas. For these 22 eastern states, the EPA is issuing Federal Implementation Plans (FIPs) that generally provide updated CSAPR NOX ozone season emission budgets for EGUs.  These emission budgets represent the remaining EGU emissions after reducing those amounts of each state's emissions that significantly contribute to downwind nonattainment or interfere with maintenance of the 2008 ozone NAAQS in downwind states, as required under Clean Air Act (CAA) section 110(a)(2)(D)(i)(I). The CSAPR Update FIPs also require affected EGUs to participate in the CSAPR NOX ozone season allowance trading program subject to these emission budgets starting with the 2017 ozone season. The allowance trading program is the remedy in the FIPs that achieves the ozone season NOX emission reductions required by the rule. The allowance trading program essentially converts the EGU NOX emission budget for each of the 22 states into a limited number of NOX allowances that, on a tonnage basis, equal the state's ozone season NOX emission budget. EGUs covered by the FIPs are able to trade NOX ozone season allowances among EGUs within their state and across state boundaries, with emissions and the use of allowances subject to certain limits.
      This RIA evaluates the benefits, costs and certain impacts of compliance with three regulatory control alternatives. The CSAPR Update EGU NOX ozone season emission budgets that the EPA is finalizing were developed using uniform control stringency represented by $1,400 per ton (2011$), whereas the more and less stringent alternatives were developed using uniform control stringency represented by $3,400 per ton and $800 per ton (2011$), respectively. The EPA assesses compliance with these sets of emission budgets through implementation of the CSAPR NOX ozone season allowance trading program. Aside from the difference in emission budgets, other key regulatory features of the allowance trading program, such as the ability to bank allowances for future use, are the same across all the three different sets of NOX emission budgets analyzed. This chapter describes the EPA's analysis of the CSAPR Update and more and less stringent alternatives. As described below, the emission budgets evaluated for the CSAPR Update regulatory control alternatives in this RIA are illustrative because they differ somewhat from the budgets finalized in this rule.
4.1.2	Regulatory Control Alternatives Analyzed
In accordance with Executive Orders 12866 and 13563, the guidelines of OMB Circular A-4, and EPA's Guidelines for Preparing Economic Analyses, this RIA analyzes the benefits and costs associated with complying with the CSAPR Update.  The final CSAPR Update emission budgets  in this RIA represents  illustrative EGU NOX ozone season emission budgets for each state that were developed using uniform control stringency represented by $1,400 per ton (2011$).
      Additionally, OMB Circular A-4 requires analysis of at least one potential alternative standard level that is more stringent than the finalized standard and one that is less stringent than the finalized standard. In response to this requirement, this RIA analyzes the final CSAPR Update emission budgets as well as a more and a less stringent alternative to the CSAPR Update. The more and less stringent alternatives differ from the CSAPR Update in that they set different EGU NOX ozone season emission budgets for the affected EGUs. The less-stringent scenario uses emission budgets that were developed using uniform control stringency represented by $800 per ton (2011$).  The more-stringent scenario uses emission budgets that were developed using uniform control stringency represented by $3,400 per ton (2011$). These sets of emissions budgets are analogous to those that the EPA explicitly took comment on in the CSAPR Update proposal. We continue to analyze these scenarios alongside the finalized approach to evaluate how economic and environmental information that has been updated since proposal affected these non-finalized options.  See section VI of the preamble for further details of these emission budgets.
All three scenarios are illustrative in nature, and the budgets included in the "CSAPR Update" scenario differ slightly from the budgets finalized in this rule. That is because subsequent to completion of the analysis of these three scenarios, the EPA made minor updates to budgets as well as to the modeling platform.  The EPA finds that the three illustrative regulatory control alternatives presented in this RIA variously provide a reasonable approximation of the impacts of the final rule, as well as an evaluation of the relative impacts of two regulatory alternatives.  This finding is supported by an analysis of the costs and impacts (but not the benefits) of the final CSAPR Update emission budgets, as estimated using the updated modeling platform. This analysis is provided in Appendix 4A.
      Table 4-1 reports the illustrative EGU NOX ozone season emission budgets that are evaluated in this RIA. As described above, starting in 2017, emissions from affected EGUs across this entire region cannot exceed the sum of emission budgets but for the ability to use banked allowances from previous years for compliance. Furthermore, emissions from affected EGUs in a particular state are subject to the CSAPR assurance provisions, which require additional allowance surrender penalties (a total of 3 allowances per-ton of emissions) on emissions that exceed a state's CSAPR NOX ozone season assurance level, or 121 percent of the emission budget. The CSAPR NOX ozone season allowance trading program is described in further detail in Section VII of the preamble.
Table 4-1	Illustrative NOX Ozone Season Emission Budgets (Tons) Evaluated in this RIA

                                           CSAPR Update (Not Finalized Budgets)
                                                     More Stringent Alternative
                                                     Less Stringent Alternative
Alabama
                                                                         12,599
                                                                         11,406
                                                                         13,548
Arkansas
                                                                          9,211
                                                                          9,041
                                                                         12,060
Delaware
                                                                            497
                                                                            494
                                                                            497
Illinois
                                                                         14,588
                                                                         14,464
                                                                         14,632
Indiana
                                                                         21,527
                                                                         19,804
                                                                         26,419
Iowa
                                                                         11,272
                                                                         11,065
                                                                         11,477
Kansas
                                                                          7,782
                                                                          7,730
                                                                          7,785
Kentucky
                                                                         19,675
                                                                         19,475
                                                                         23,030
Louisiana
                                                                         18,636
                                                                         18,470
                                                                         19,087
Maryland
                                                                          3,457
                                                                          2,838
                                                                          3,795
Michigan
                                                                         16,483
                                                                         15,222
                                                                         18,630
Mississippi
                                                                          6,315
                                                                          6,191
                                                                          6,350
Missouri
                                                                         15,085
                                                                         14,604
                                                                         16,628
New Jersey
                                                                          2,057
                                                                          2,061
                                                                          2,063
New York
                                                                          5,050
                                                                          4,928
                                                                          5,129
Ohio
                                                                         18,763
                                                                         18,599
                                                                         22,372
Oklahoma
                                                                         11,742
                                                                          9,254
                                                                         13,871
Pennsylvania
                                                                         19,554
                                                                         19,479
                                                                         29,875
Tennessee
                                                                          9,115
                                                                          9,115
                                                                          9,115
Texas
                                                                         51,931
                                                                         50,022
                                                                         54,544
Virginia
                                                                          9,224
                                                                          8,758
                                                                          9,263
West Virginia
                                                                         18,152
                                                                         17,706
                                                                         25,730
Wisconsin
                                                                          7,862
                                                                          7,791
                                                                          7,922
TOTAL
                                                                        310,577
                                                                        298,515
                                                                        353,821

      Note that EGUs have flexibility in determining how they will comply with the allowance trading program. As discussed below, the way that they comply may differ from the methods forecast in the modeling for this RIA.
      See section 4.3 for further discussion of the modeling approach used in the analysis presented below.
4.2	Power Sector Modeling Framework
      IPM is a state-of-the-art, peer-reviewed, dynamic linear programming model that can be used to project power sector behavior under future business-as-usual conditions, and to examine prospective air pollution control policies throughout the contiguous United States for the entire electric power system. EPA used IPM to project likely future electricity market conditions with and without the CSAPR Update.
      IPM is a multi-regional, dynamic, deterministic linear programming model of the contiguous U.S. electric power sector. It provides estimates of least cost capacity expansion, electricity dispatch, and emissions control strategies while meeting energy demand and environmental, transmission, dispatch, and reliability constraints. The EPA has used IPM for over two decades to better understand power sector behavior under future business-as-usual conditions and to evaluate the economic and emission impacts of prospective environmental policies. The model is designed to reflect electricity markets as accurately as possible. The EPA uses the best available information from utilities, industry experts, gas and coal market experts, financial institutions, and government statistics as the basis for the detailed power sector modeling in IPM. The model documentation provides additional information on the assumptions discussed here as well as all other model assumptions and inputs.
      The model incorporates a detailed representation of the fossil-fuel supply system that is used to estimate equilibrium fuel prices. The model includes an endogenous representation of the North American natural gas supply system through a natural gas module that reflects a partial supply and demand equilibrium of the North American gas market, accounting for varying levels of potential power sector and non-power sector gas demand and corresponding gas production and price levels. This module consists of 118 supply, demand, and storage nodes and 15 liquefied natural gas re-gasification facility locations that are tied together by a series of linkages (i.e., pipelines) that represent the North American natural gas transmission and distribution network.
      IPM also endogenously models the partial equilibrium of coal supply and EGU coal demand levels throughout the contiguous U.S., taking into account assumed non-power sector demand and imports/exports. IPM reflects 36 coal supply regions, 14 coal grades, and the coal transport network, which consists of over four thousand linkages representing rail, barge, and truck and conveyer linkages. The coal supply curves in IPM were developed during a thorough bottom-up, mine-by-mine approach that depicts the coal choices and associated supply costs that power plants would face if selecting that coal over the modeling time horizon. The IPM documentation outlines the methods and data used to quantify the economically recoverable coal reserves, characterize their cost, and build the 36 coal regions' supply curves.
      To estimate the annualized costs of additional capital investments in the power sector, the EPA uses a conventional and widely accepted approach that applies a capital recovery factor (CRF) multiplier to capital investments and adds that to the annual incremental operating expenses. The CRF is derived from estimates of the power sector's cost of capital (i.e., private discount rate), the amount of insurance coverage required, local property taxes, and the life of capital. It is important to note that there is no single CRF factor applied in the model; rather, the CRF varies across technologies, book life of the capital investments, and regions in the model in order to better simulate power sector decision-making.
      The EPA has used IPM extensively over the past two decades to analyze options for reducing power sector emissions. Previously, the model has been used to estimate the costs, emission changes, and power sector impacts for the Clean Air Interstate Rule (U.S. EPA, 2005), the original Cross-State Air Pollution Rule  (U.S. EPA, 2011), the Mercury and Air Toxics Standards (MATS) (U.S. EPA, 2011a), the Clean Power Plan (CPP) for Existing Power Plants (U.S. EPA, 2015), and the Carbon Pollution Standards for New Power Plants (U.S. EPA, 2015a). The EPA has also used IPM to estimate the air pollution reductions and power sector impacts of water and waste regulations affecting EGUs, including Cooling Water Intakes (316(b)) Rule (U.S. EPA, 2014), Disposal of Coal Combustion Residuals from Electric Utilities (CCR) (U.S. EPA, 2015b) and Steam Electric Effluent Limitation Guidelines (ELG) (U.S. EPA, 2015c).
The model and the EPA's input assumptions undergo periodic formal peer review. The rulemaking process also provides opportunity for expert review and comment by a variety of stakeholders, including owners and operators of capacity in the electricity sector that is represented by the model, public interest groups, and other developers of U.S. electricity sector models. The feedback that the Agency receives provides a highly-detailed review of key input assumptions, model representation, and modeling results. IPM has received extensive review by energy and environmental modeling experts in a variety of contexts. For example, in the late 1990s, the Science Advisory Board reviewed IPM as part of the CAA Amendments Section 812 prospective studies that are periodically conducted. The model has also undergone considerable interagency scrutiny when it was used to conduct over a dozen legislative analyses (performed at Congressional request) over the past decade. The Agency has also used the model in a number of comparative modeling exercises sponsored by Stanford University's Energy Modeling Forum over the past 15 years. IPM has also been employed by states (e.g., for RGGI, the Western Regional Air Partnership, Ozone Transport Assessment Group), other Federal and state agencies, environmental groups, and industry.
4.3	EPA's Power Sector Modeling of the Base Case and Three Regulatory Control Alternatives
      The IPM "base case" for any regulatory impact analysis is a business-as-usual scenario that represents expected behavior in the electricity sector under market and regulatory conditions in the absence of the rule. As such, an IPM base case represents an element of the 2017 and 2020 baseline for this RIA. The EPA frequently updates the IPM base case to reflect the latest available electricity demand forecasts from the U.S. Energy Information Agency (EIA) as well as expected costs and availability of new and existing generating resources, fuels, emission control technologies, and regulatory requirements.
4.3.1	EPA's IPM Base Case v.5.15
      EPA's IPM modeling platform used to analyze this rule (v.5.15) is similar to the version used to analyze the CSAPR Update proposal, and incorporates minor updates made primarily in response to comments received on an August 4, 2015 Notice of Data Availability and the proposed rule.
      As with the CSAPR Update proposal, the IPM v.5.15 modeling platform incorporates federal and most state laws and regulations whose provisions were either in effect or enacted and clearly delineated by February 1, 2016.  The base case includes the Final Mercury and Air Toxics Standards (MATS), and two non-air federal rules affecting EGUs: Cooling Water Intakes (316(b)) Rule (U.S. EPA, 2014), and Combustion Residuals from Electric Utilities (CCR) (U.S. EPA, 2015b). Additionally, all new capacity projected by the model is compliant with Clean Air Act 111(b) standards, including the final standards of performance for GHG emissions from new sources.  As described in section IV.B of the preamble, the Clean Power Plan (CPP) is not included in this analysis.
 Unlike the base case used in the analysis of the proposed rule, which was conducted prior to the D.C. Circuit's issuance of EME Homer City II, the base case for the final rule accounts for compliance with the original CSAPR by including as constraints all original CSAPR emission budgets with the exception of remanded Phase 2 NOX ozone season emission budgets for 11 states and  Phase 2 NOX ozone season emission budgets for four additional states that were finalized in the original CSAPR supplemental rule. For more information, see section V of the preamble.
Additionally, after the IPM modeling for the final rule was underway, Pennsylvania published a new RACT rule that would require EGU NOX reductions starting on January 1, 2017. The EPA was unable to explicitly include this final state rule in the IPM base case for the final CSAPR Update. However, the EPA recognizes that the implementation of this final state rule will precede the first control period for the final CSAPR Update. The agency believes that it is reasonable to remove the impacts of the Pennsylvania RACT rule from the estimated impacts of the CSAPR Update to appropriately reflect the emission reductions, costs, and benefits attributable to the CSAPR Update.  Therefore, the EPA evaluated the EGU emission reductions expected to result from Pennsylvania's RACT rule exogenously and isolated these impacts from the EPA's assessment of emission reductions, benefits, and costs estimated for the CSAPR Update and the more and less stringent alternatives. For more information, see the Ozone Transport Policy Analysis TSD.
      Other updates to the v.5.15 base case used in this final rule include largely unit-level specifications (e.g., pollution control configurations and emissions rates), and planned power plant construction and closures that the EPA was aware of by February 1, 2016. In Maryland, emission rates of units were updated to reflect compliance with the state's RACT rule.  Additionally, given the lead times for new coal-fired and combined cycle plants, EPA did not allow the model to build additional capacity of those types in 2018 beyond announced new builds. Similarly, EPA did not allow new renewable generation to be built before 2018, nor did EPA did not allow the model to retire any units beyond announced retirements before 2020. Finally, NOX-specific pollution control retrofits were limited to retrofits that occurred in the base case. For a detailed account of all updates made to the v.5.15 modeling platform, see the IPM v.5.15 Supplemental Documentation for the Final Cross State Air Pollution Update Rule, available in the docket..
      EPA also updated the National Electric Energy Data System (NEEDS), based largely on public comment received in response to an August 4, 2015 Notice of Data Availability and the proposed rule. This database contains the unit-level data that is used to construct the "model" plants that represent existing and planned-committed units in EPA modeling applications of IPM. NEEDS includes detailed information on each individual EGU, including geographic, operating, air emissions, and other data on every generating unit in the contiguous U.S.
While the EPA used IPM Base Case v.5.15 throughout the development and analysis of the final CSAPR Update, minor updates were made to this modeling platform over the course of the final rule development.  Subsequent to the initial base case projections that provided power sector emissions data used for air quality modeling, the EPA made minor updates to the modeling platform, which focus primarily on electricity generating unit-level input assumptions regarding NOX rates. The EPA believes that these updates, while relatively minor in the context of national emission projections, improve the model's ability to reflect the electric power system in relation to the CSAPR Update, and enable the EPA to provide the best projections possible to evaluate this rule.  For more information, see IPM v.5.15 Supplemental Documentation for the Final Cross State Air Pollution Rule Update.
The analysis of cost and impacts presented in this chapter is based on a single IPM base case, and represents incremental impacts projected solely as a result of compliance with the illustrative emission budgets  presented in Table 4-1 above.  Note that further analysis, which includes additional updates, is presented in Appendix 4A.
4.3.2.	Methodology for Evaluating the Regulatory Control Alternatives
To estimate the costs, benefits, and economic and energy market impacts of the CSAPR Update, the EPA conducted quantitative analysis of the three regulatory control alternatives: the illustrative final CSAPR Update emission budgets and more and less stringent alternatives. Details about these regulatory control alternatives, including state-specific EGU NOX ozone-season emissions budgets for each alternative as analyzed in this RIA, are provided above in section 4.1.
Before undertaking power sector analysis to evaluate compliance with the regulatory control alternatives, the EPA first considered available EGU NOX mitigation strategies that could be implemented for the first compliance period (i.e., the 2017 ozone season). The EPA considered all widely-used EGU NOX control strategies: optimizing NOX removal by existing, operational selective catalytic reduction (SCRs) and turning on and optimizing existing idled SCRs; turning on existing idled SNCRs; installation of (or upgrading to) state-of-the-art NOX combustion controls; shifting generation to units with lower NOX emission rates; and installing new SCRs and SNCRs. Similarly, as proposed, EPA determined that the power sector could implement all of these NOX mitigation strategies, except installation of new SCRs or SNCRs, for the 2017 ozone-season. For more details on these assessments, including the assessment of EGU NOX mitigation costs and feasibility, please refer to the Final EGU NOX Mitigation Strategies TSD, in the docket for this rule.
These mitigation strategies are primarily captured within the model.  However, due to limitations on model size, IPM v.5.15 does not have the ability to determine, within the model, whether or not to operate existing EGU post-combustion NOX controls (i.e., SCR or SNCR) in response to a regulatory emission requirement. Whether or not an existing post-combustion NOx control at a particular EGU is operating in a model scenario is determined by the model user. In order to evaluate compliance with the regulatory control alternatives, the EPA determined, outside the model, whether or not operation of existing controls that are idle in the base case would be reasonably expected for compliance with each of the evaluated regulatory control alternatives. After imposing the requirement to operate these controls, IPM estimated the associated NOX reductions and impacts associated with each regulatory alternative.
The EGU NOX mitigation strategies that are assumed to operate or are available to reduce NOX in order to comply with each of the regulatory control alternatives are shown in Table 4-2; more information about the estimated costs of these controls can be found in the EGU NOX Mitigation Strategies TSD.
Table 4-2.	NOX Mitigation Strategies Implemented for Compliance with the Regulatory Control Alternatives
                        Regulatory Control Alternative
NOX Controls Implemented
Less Stringent Alternative
 Fully operating existing SCRs to achieve 0.081 lb/MMBtu NOX emission rate (costs estimated outside IPM)
 Shift generation to minimize costs (costs estimated within IPM)
CSAPR Update
      (All controls above)
     Turn on idled SCRs (costs estimated within IPM)
     Install or upgrade combustion controls (costs estimated outside IPM)
More Stringent Alternative
      (All controls above)
     Turn on idled SNCRs ( costs estimated within IPM)

      In addition to the limitation on ozone season NOX emissions required by the EGU emissions budgets for the 22 states, there are four important features of the allowance trading program represented in the model that may influence the level and location of NOX emissions from affected EGUs. They are: the ability of affected EGUs to buy and sell NOX ozone season allowances from one another for compliance purposes; the ability of affected EGUs to bank NOX ozone season allowances for future use; the effect of limits on the total ozone season NOX emissions from affected EGUs in each state required by the assurance provisions; and the treatment of banked 2015 and 2016 vintage NOX ozone season allowances issued under the original CSAPR to address interstate ozone transport for the 1997 ozone NAAQS. Each of these features of the ozone season allowance trading program is described below.
      Affected EGUs are expected to choose the least-cost method of complying with the requirements of the allowance trading program, and the distribution of ozone season NOX emissions across affected EGUs is generally governed by this cost-minimizing behavior in the analysis. The total ozone season NOX emissions from affected EGUs in this analysis are limited to the amount allowed by the sum of the NOX budgets across the 22 states. Furthermore, allowances may be banked for future use. The number of banked allowances is influenced by the determination, outside the model, whether or not existing controls that are idle in the base case are turned on and by if it is less costly to abate ozone season NOX emissions in a current ozone season than to abate emissions in a later ozone season. Affected EGUs are expected to bank NOX ozone season allowances in the 2017 ozone season for use in the later ozone season. Based on observation, the EPA believes that this is a reasonable illustrative compliance path for EGUs, which may wish to bank allowances for future use under economic reasons or non-economic reasons such as being prepared for future variability in power sector operations.
      While there are no explicit limits on the exchange of allowances between affected EGUs and on the banking of 2017 and future vintage NOX ozone season allowances, the assurance provisions limit the amount of seasonal NOX emissions by affected EGUs in each of the 22 states. The assurance level limits affected EGU emissions over an ozone season to the state's NOX ozone season emission budget plus an increment equal to 21 percent of each state's emissions budget. This increment is called the variability limit. See section VII.E.4 of the preamble for a discussion of the purpose of the assurance provision and further detail about how the variability limits and assurance levels are determined. If a state exceeds its assurance level in a given year, sources within that state are assessed a total of 3-to-1 allowance surrender on the excess tons. Section VII.E.4 of the preamble also explains how the EPA then determines which EGUs are subject to this surrender requirement. In the modeling, the assurance provisions are represented by a limit on the total ozone season NOX emissions that may be emitted by affected EGUs in each state, and thus the modeling does not permit affected EGUs to emit beyond the assurance levels and thus incur penalties.
      As described in section VII.C.2 of the preamble, the rule allows 2015 and 2016 vintage NOX ozone season allowances (that had been issued under CSAPR to address interstate ozone transport for the 1997 ozone NAAQS) to be used for compliance with this rule, following a one-time conversion that reduces the overall quantity of banked allowances from that time period.  Based on EPA's expectation of the size of the NOX allowance bank after the one-time conversion carried out pursuant to the terms of this final rule, the treatment of these banked allowances is represented in the modeling as an additional 65,221 tons of NOX allowances, the equivalent of one year of the variability limit associated with the illustrative emission budgets, that may be used by affected EGUs during the 2017 ozone season or in later ozone seasons.
4.3.3	Methodology for Estimating Compliance Costs
This section describes EPA's approach to quantify estimated compliance costs associated with the three regulatory control alternatives.  These compliance costs include estimates projected directly by the model as well as calculations performed outside of the model that use IPM model inputs and methods.  The model projections capture the costs associated with three of the NOX mitigation strategies: turning on idled SCRs, turning on idled SNCRs, and shifting generation to lower-NOX emitting EGUs. The costs of increasing the use and optimizing the performance of existing and operating SCRs, and for installing or upgrading NOX combustion controls, were estimated outside of the model. The costs for these two NOX mitigation strategies are calculated based on IPM emissions projections and utilize the same NOX control cost equations used in IPM. Therefore, this estimate is consistent with modeled projections and provides the best available quantification of the costs of these NOX mitigation strategies.
The following steps summarize the EPA's methodology for estimating the component of compliance costs that are calculated outside of the model for the CSAPR Update scenario:
 In the model projections, identify all model plants in the 22-state region that can adopt the following NOX mitigation strategies:
 Fully operating existing SCRs
 Installing or upgrading NOX combustion controls
 Estimate the total NOX reductions that are attributable to each of these strategies:
 Fully operating existing SCRs (SCRs operating in base case): 24,100 tons
 Fully operating existing SCRs (SCRs not operating in base case): 4,500 tons
 Installing or upgrading NOX combustion controls: 9,700 tons
 Estimate the average cost associated with each of these strategies:
 Fully operating existing SCRs (SCRs operating in base case): $670/ton
 Fully operating existing SCRs (SCRs not operating in base case): $1,000/ton
 Installing or upgrading NOX combustion controls: $1,200/ton
 Multiply (2) by (3) to estimate the total cost associate with each of these strategies.
Table 4-3 summarizes the results of this methodology for the illustrative CSAPR Update scenario in 2017.
Table 4-3.	Summary of Methodology for Calculating Compliance Costs Estimated Outside of IPM for CSAPR Update, 2017 (2011$)
NOX Mitigation Strategy
                                                     NOX Ozone Season Emissions
                                                                         (Tons)
                                                           Average Cost ($/ton)
                                                                     Total Cost
                                                                          ($MM)
Maximizing the use of existing SCRs (operating in Base Case)
                                                                         24,100
                                                                            670
                                                                             16
Maximizing the use of existing SCRs (not operating in Base Case)
                                                                          4,500
                                                                          1,000
                                                                            4.5
Installing/upgrading NOX combustion controls
                                                                          9,700
                                                                          1,200
                                                                             12

The total costs of compliance with the regulatory control alternatives are estimated as the sum of the costs that are modeled within IPM and the costs that are calculated outside the model.
4.4	Estimated Impacts of the Regulatory Control Alternatives
4.4.1	Emission Reduction Assessment
As discussed in Chapter 3, the EPA determined that NOX emissions in 22 eastern states affect the ability of downwind states to attain and maintain the 2008 ozone NAAQS. For these 22 eastern states, the EPA is issuing Federal Implementation Plans (FIPs) that generally update the existing CSAPR NOX ozone-season emission budgets for EGUs and implement these budgets via the CSAPR NOX ozone-season allowance trading program.
The NOX emissions reductions are presented in this RIA for two time periods: 2017 (the principal year of interest for the CSAPR update) and 2020. As with proposal RIA, the 2017 emissions estimates are based on IPM projections for 2018, and reflect exogenous adjustments to account for known differences between 2017 and 2018 (e.g., planned closures, coal-to-gas conversions, and planned SCR retrofits).  For more information on these and other adjustments, see Policy Analysis TSD.
Table 4-4 presents the estimated reduction in power sector NOX emissions resulting from compliance with the evaluated regulatory control alternatives (i.e., emissions budgets) in the 22-state region, as well as the impact on states not in the region. The emission reductions follow an expected pattern: the less stringent alternative produces substantially smaller emission reductions than EPA's final emissions budgets, and the more stringent alternative results in slightly more NOX reductions.
Table 4-4.	EGU Ozone Season NOX Emissions and Emission Changes (thousand tons) for the Base Case and the Regulatory Control Alternatives
                               Ozone Season NOX
                                (thousand tons)
                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                     2017
Region
                                                                          369.5
                                                                          308.3
                                                                          342.7
                                                                          303.2
                                                                          -61.2
                                                                          -26.8
                                                                          -66.3

Non-Region
                                                                          205.4
                                                                          205.3
                                                                          205.4
                                                                          205.5
                                                                           -0.1
                                                                            0.0
                                                                            0.2

Total
                                                                          574.8
                                                                          513.5
                                                                          548.1
                                                                          508.8
                                                                          -61.3
                                                                          -26.8
                                                                          -66.1
                                     2020
Region
                                                                          374.6
                                                                          302.8
                                                                          347.7
                                                                          297.8
                                                                          -71.8
                                                                          -26.9
                                                                          -76.8

Non-Region
                                                                          181.6
                                                                          181.5
                                                                          181.6
                                                                          181.8
                                                                           -0.1
                                                                            0.0
                                                                            0.2

Total
                                                                          556.2
                                                                          484.3
                                                                          529.3
                                                                          479.6
                                                                          -71.9
                                                                          -26.9
                                                                          -76.6

      The results of EPA's IPM analysis show that, with respect to compliance with the illustrative  EGU NOX emission budgets, maximizing the use of existing operating SCRs  provides the largest  amount of ozone season NOX emission reductions 42 percent), and turning on idled SCRs produces an additional 32 percent of the total ozone season NOX reductions. Combustion controls (16 percent) and generation shifting (10 percent) make up the remainder of the ozone season NOX reductions. In the more stringent alternative, compliance by turning on idle existing SNCRs makes up 1 percent of the total reductions and generation shifting increases to 16 percent, while the shares attributed to the other four mitigation measures are similar to, if slightly smaller than, the shares for compliance with the finalized EGU NOX emissions budgets. In the less stringent alternative, compliance by maximizing the use of existing operating SCRs provides 85% of the total reductions, with the remainder attributable to generation shifting.
      In addition to the ozone season NOX reductions, there will also be reductions of other air emissions emitted by EGUs burning fossil fuels (i.e., co-pollutants). These other emissions include the annual total changes in emissions of NOx, SO2 and CO2. The small SO2 emissions increase is attributable primarily to a few model plants, for which the model projected a slightly different 2016 MATS control strategy in the base case than with the CSAPR Update, resulting in a small change in SO2 emissions.  Since the MATS rule is currently effective, the EPA believes that the MATS control strategies at these plants are currently in place, and not likely to change as a result of the CSAPR Update.  Therefore, the EPA does not view the projected SO2 increase as a meaningful impact of the policy.  The co-pollutant emission reductions are presented in Table 4-5.

Table 4-5.	EGU Annual Emissions and Emissions Changes for NOX, SO2 and CO2 for the Regulatory Control Alternatives
                                  Annual NOX
                                (thousand tons)
                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                     2017
Region
                                                                          806.6
                                                                          732.2
                                                                          779.7
                                                                          727.3
                                                                          -74.5
                                                                          -26.9
                                                                          -79.3

Non-Region
                                                                          439.1
                                                                          439.0
                                                                          439.1
                                                                          439.2
                                                                            0.0
                                                                            0.0
                                                                            0.1

Total
                                                                        1,245.7
                                                                        1,171.2
                                                                        1,218.8
                                                                        1,166.5
                                                                          -74.5
                                                                          -26.9
                                                                          -79.2
                                     2020
Region
                                                                          820.2
                                                                          735.5
                                                                          793.2
                                                                          730.6
                                                                          -84.7
                                                                          -27.0
                                                                          -89.5

Non-Region
                                                                          415.3
                                                                          415.3
                                                                          415.3
                                                                          415.4
                                                                            0.0
                                                                            0.0
                                                                            0.1

Total
                                                                        1,235.5
                                                                        1,150.7
                                                                        1,208.5
                                                                        1,146.0
                                                                          -84.8
                                                                          -27.0
                                                                          -89.4

                                  Annual SO2
                                (thousand tons)
                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                     2017
Region
                                                                          914.8
                                                                          918.9
                                                                          915.9
                                                                          922.1
                                                                            4.1
                                                                            1.1
                                                                            7.3

Non-Region
                                                                          324.1
                                                                          322.1
                                                                          323.7
                                                                          321.7
                                                                           -2.0
                                                                           -0.4
                                                                           -2.4

Total
                                                                        1,238.9
                                                                        1,241.0
                                                                        1,239.6
                                                                        1,243.8
                                                                            2.2
                                                                            0.7
                                                                            5.0
                                     2020
Region
                                                                          914.8
                                                                          918.9
                                                                          915.9
                                                                          922.1
                                                                            4.1
                                                                            1.1
                                                                            7.3

Non-Region
                                                                          324.1
                                                                          322.1
                                                                          323.7
                                                                          321.7
                                                                           -2.0
                                                                           -0.4
                                                                           -2.4

Total
                                                                        1,238.9
                                                                        1,241.0
                                                                        1,239.6
                                                                        1,243.8
                                                                            2.2
                                                                            0.7
                                                                            5.0

                                  Annual CO2
                              (MM metric tonnes)
                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                     2017
Region
                                                                        1,237.2
                                                                        1,235.5
                                                                        1,235.8
                                                                        1,234.9
                                                                           -1.7
                                                                           -1.4
                                                                           -2.3

Non-Region
                                                                          653.5
                                                                          653.6
                                                                          653.6
                                                                          653.7
                                                                            0.1
                                                                            0.1
                                                                            0.3

Total
                                                                        1,890.7
                                                                        1,889.1
                                                                        1,889.4
                                                                        1,888.6
                                                                           -1.6
                                                                           -1.3
                                                                           -2.0
                                     2020
Region
                                                                        1,237.2
                                                                        1,235.5
                                                                        1,235.8
                                                                        1,234.9
                                                                           -1.7
                                                                           -1.4
                                                                           -2.3

Non-Region
                                                                          653.5
                                                                          653.6
                                                                          653.6
                                                                          653.7
                                                                            0.1
                                                                            0.1
                                                                            0.3

Total
                                                                        1,890.7
                                                                        1,889.1
                                                                        1,889.4
                                                                        1,888.6
                                                                           -1.6
                                                                           -1.3
                                                                           -2.0

4.4.2	Compliance Cost Assessment
The estimates of the changes in the cost of supplying electricity for the regulatory control alternatives are presented in Table 4-6. The costs associated with compliance with monitoring, recordkeeping, and reports requirements are not included within the estimates in this table and can be found in preamble section X.B.
Table 4-6.	Compliance Cost Estimates (millions of 2011$) for the Regulatory  Control Alternatives

                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
2017-2020 (Annualized)
                                                                           68.4
                                                                            8.0
                                                                           82.0
2017 (Annual)
                                                                           0.01
                                                                          -55.7
                                                                           -0.4
2020 (Annual)
                                                                          136.9
                                                                           77.1
                                                                          164.6
"2017-2020 (Annualized)" reflects total estimated annual compliance costs levelized over the period 2017 through 2020, discounted using a 4.77 discount rate. "2017 (Annual)" and "2020 (Annual)" reflect point estimates in each of those years.

There are several notable aspects of the results presented in Table 4-6. The most notable result in Table 4-6 is that the estimated annual compliance costs for the less and more stringent alternatives are negative (i.e., a cost reduction) in 2017, although these regulatory control alternatives reduce annual NOX emissions by approximately 27,000 and 79,000 tons respectively as shown in Table 4-5. While seemingly counterintuitive, estimating negative compliance costs in a single year is possible given the assumption of perfect foresight.  IPM's objective function is to minimize the discounted net present value (NPV) of a stream of annual total cost of generation over a multi-decadal time period. For example, with the assumption of perfect foresight it is possible that on a national basis within the model the least-cost compliance strategy may be to delay a new investment which was projected to occur sooner in the base case. Such a delay could result in a lowering of annual cost in an early time period and increase it in later time periods.
In addition to evaluating annual compliance cost impacts, the EPA believes that a full understanding of these three regulatory control alternatives benefits from an evaluation of annualized costs over the 2017-2020 time frame.  EPA limits its analysis to this timeframe considering that on October 1, 2015, the EPA strengthened the ground-level ozone NAAQS to 70 ppb. The EPA is mindful of the need to address ozone transport for the 2015 ozone NAAQS. Given the statutory implementation timeline of good neighbor requirements with respect to the 2015 ozone NAAQS, the EPA anticipates that further actions to reduce interstate emission transport related to ozone pollution could take place in the near future.  Therefore, it is appropriate to evaluate the costs of the regulatory control alternatives over the 2017-2020 timeframe.  Starting with the estimated annual cost time series, it is possible to estimate the net present value of that stream, and then estimate a levelized annual cost associated with compliance with each regulatory control alternative. For this analysis we first calculated the NPV of the stream of costs from 2017 through 2020 using a 4.77 percent discount rate.  EPA typically uses a 3 and a 7 percent discount rate to discount future year social benefits and social costs in regulatory impact analyses (USEPA, 2010). In this cost annualization we use a 4.77 percent discount rate, which is consistent with the rate used in IPM's objective function for minimizing the NPV of the stream of total costs of electricity generation.
After calculating the NPV of the cost streams, the same 4.77 percent discount rate and 2017-2020 time period is used to calculate the levelized annual (i.e., annualized) cost estimates shown in Table 4-6.
Additionally, note that the 2017-2020 equivalent annualized compliance cost estimates have the expected relationship to each other; the annualized costs are lowest for the less stringent alternatives, and highest for the more stringent alternative.
4.4.3	Impacts on Fuel Use, Prices and Generation Mix
While the CSAPR Update is expected to result in significant NOX emissions reductions, it is estimated to result in relatively modest impacts to the power sector. While these impacts are relatively small in percentage terms, consideration of these potential impacts is an important component of assessing the relative impact of the regulatory control alternatives. In this section we discuss the estimated changes in fuel use, fuel prices, generation by fuel type, capacity by fuel type, and retail electricity prices.
Tables 4-7 and 4-8 present the percentage changes in national coal and natural gas usage by EGUs in 2017 These fuel use estimates reflect a modest shift to natural gas from coal. The projected impacts in 2020 are similarly very small.
Table 4-7.	2017 Projected Power Sector Coal Use for the Base Case and the Regulatory Control Alternatives

                                 Million Tons
                         Percent Change from Base Case

                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
Appalachia
                                                                            118
                                                                            117
                                                                            118
                                                                            117
                                                                          -0.2%
                                                                          -0.1%
                                                                          -0.4%
Imports
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                            N/A
                                                                            N/A
                                                                            N/A
Interior
                                                                            227
                                                                            227
                                                                            227
                                                                            227
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Waste Coal
                                                                              6
                                                                              6
                                                                              6
                                                                              6
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
West
                                                                            352
                                                                            351
                                                                            351
                                                                            350
                                                                          -0.4%
                                                                          -0.4%
                                                                          -0.5%
Total
                                                                            703
                                                                            701
                                                                            701
                                                                            700
                                                                          -0.2%
                                                                          -0.2%
                                                                          -0.3%

Table 4-8. 2017 Projected Power Sector Natural Gas Use for the Base Case and the Regulatory Control Alternatives
                              Trillion Cubic Feet
                         Percent Change from Base Case
                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                            8.8
                                                                            8.8
                                                                            8.8
                                                                            8.8
                                                                           0.2%
                                                                           0.1%
                                                                           0.3%

     Tables 4-9 and 4-10 present the projected coal and natural gas prices in 2017, as well as the percent change from the base case projected as a result of the regulatory control alternatives.  These minor impacts in 2017 are consistent with the small changes in fuel use summarized above.  The projected impacts in 2020 are similarly very small.
Table 4-9. 2017 Projected Minemouth and Power Sector Delivered Coal Price for the Base Case and the Regulatory Control Alternatives

                                    $/MMBtu
                         Percent Change from Base Case

                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
Minemouth
                                                                           1.51
                                                                           1.51
                                                                           1.51
                                                                           1.51
                                                                          -0.1%
                                                                          -0.2%
                                                                          -0.3%
Delivered
                                                                           2.31
                                                                           2.31
                                                                           2.31
                                                                           2.31
                                                                          -0.1%
                                                                          -0.2%
                                                                          -0.2%

Table 4-10. 2017 Projected Henry Hub and Power Sector Delivered Natural Gas Price for the Base Case and the Regulatory Control Alternatives

                                    $/MMBtu
                         Percent Change from Base Case

                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
Henry Hub
                                                                           4.33
                                                                           4.33
                                                                           4.33
                                                                           4.33
                                                                           0.0%
                                                                           0.0%
                                                                           0.1%
Delivered
                                                                           4.52
                                                                           4.52
                                                                           4.52
                                                                           4.53
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%

Table 4-11 presents the projected percentage changes in the amount of electricity generation in 2017 by fuel type.  Consistent with the fuel use projections and emissions trends above, the EPA projects very small overall shift from coal to gas.  The projected impact in 2020 is similarly very small.
Table 4-11. 2017 Projected Generation by Fuel Type for the Base Case and the Regulatory Control Alternatives

                               Generation (MWh)
                         Percent Change from Base Case

                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
Coal
                                                                          1,388
                                                                          1,386
                                                                          1,387
                                                                          1,385
                                                                          -0.2%
                                                                          -0.1%
                                                                          -0.2%
Natural Gas
                                                                          1,195
                                                                          1,198
                                                                          1,197
                                                                          1,199
                                                                           0.2%
                                                                           0.1%
                                                                           0.3%
Nuclear
                                                                            787
                                                                            787
                                                                            787
                                                                            787
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Hydro
                                                                            281
                                                                            281
                                                                            281
                                                                            281
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Non-Hydro RE
                                                                            421
                                                                            421
                                                                            421
                                                                            421
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Oil\Gas Steam
                                                                             50
                                                                             50
                                                                             50
                                                                             50
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Other
                                                                              8
                                                                              8
                                                                              8
                                                                              8
                                                                           0.9%
                                                                          -1.2%
                                                                           0.4%
Total
                                                                          4,131
                                                                          4,131
                                                                          4,131
                                                                          4,131
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Note: In this table, "Non-Hydro RE" includes biomass, geothermal, landfill gas, solar, and wind
Table 4-12 presents the projected percentage changes in the amount of generating capacity in 2020 by primary fuel type.  As explained above, none of the regulatory control alternatives are expected to have a net impact on overall capacity by primary fuel type in 2017, and the model was specified accordingly.
Table 4-12. 2020 Projected Capacity by Fuel Type for the Base Case and the Regulatory Control Alternatives

                                 Capacity (GW)
                         Percent Change from Base Case

                                                                      Base Case
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
                                                                   CSAPR Update
                                                     Less-Stringent Alternative
                                                     More-Stringent Alternative
Coal
                                                                            209
                                                                            209
                                                                            209
                                                                            209
                                                                          -0.3%
                                                                          -0.2%
                                                                          -0.3%
Natural Gas
                                                                            391
                                                                            391
                                                                            391
                                                                            391
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Nuclear
                                                                            101
                                                                            101
                                                                            101
                                                                            102
                                                                           0.3%
                                                                           0.1%
                                                                           0.3%
Hydro
                                                                            107
                                                                            107
                                                                            107
                                                                            107
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Non-Hydro RE
                                                                            138
                                                                            138
                                                                            138
                                                                            138
                                                                           0.0%
                                                                           0.0%
                                                                           0.0%
Oil\Gas Steam
                                                                             83