Additionally, most states have implemented Renewable Portfolio Standards (RPS), or Renewable Electricity Standards (RES).  These programs are designed to increase the renewable share of a state's total electricity generation.  Currently 30 states and the District of Columbia have enforceable RPS or other mandatory renewable capacity policies, and 7 states have voluntary goals.  These programs vary widely in structure, enforcement, and scope.
2.8.2 	Federal Policies
In April 2007, the Supreme Court concluded that GHGs met the CAA definition of an air pollutant, giving the EPA the authority to regulate GHGs under the CAA contingent upon an agency determination that GHG emissions from new motor vehicles cause or contribute to air pollution that may reasonably be anticipated to endanger public health or welfare. This decision to regulate GHG emissions for motor vehicles set the stage for the determination of whether other sources of GHG emissions, including stationary sources, would need to be regulated as well.
In response to the FY2008 Consolidated Appropriations Act (H.R. 2764; Public Law 110 - 161), the EPA issued the Mandatory Reporting of Greenhouse Gases Rule (74 FR 5620) which required reporting of GHG data and other relevant information from fossil fuel suppliers and industrial gas suppliers, direct greenhouse gas emitters, and manufacturers of heavy-duty and off-road vehicles and engines. The purpose of the rule was to collect accurate and timely GHG data to inform future policy decisions. As such, it did not require that sources control greenhouse gases, but sources above certain threshold levels must monitor and report emissions.
In August 2007, the EPA issued a prevention of significant deterioration (PSD) permit to Deseret Power Electric Cooperative, authorizing it to construct a new waste-coal-fired EGU near its existing Bonanza Power Plant, in Bonanza, Utah. The permit did not include emissions control requirements for CO2. The EPA acknowledged the Supreme Court decision, but found that decision alone did not require PSD permits to include limits on CO2 emissions. Sierra Club challenged the Deseret permit. In November 2008, the Environmental Appeals Board (EAB) remanded the permit to the EPA to reconsider "whether or not to impose a CO2 BACT (best available control technology) limit in light of the `subject to regulation' definition under the CAA." The remand was based in part on EAB's finding that there was not an established EPA interpretation of the regulatory phrase "subject to regulation."
In December 2008, the Administrator issued a memo indicating that the PSD Permitting Program would apply to pollutants that are subject to either a provision in the CAA or a regulation adopted by the EPA under the CAA that requires actual control of emissions of that pollutant. The memo further explained that pollutants for which the EPA regulations only require monitoring or reporting, such as the provisions for CO2 in the Acid Rain Program, are not subject to PSD permitting. Fifteen organizations petitioned the EPA for reconsideration, prompting the agency to issue a revised finding in March 2009. After reviewing comments, the EPA affirmed the position that PSD permitting is not triggered for a pollutant such as GHGs until a final nationwide rule requires actual control of emissions of the pollutant. For GHGs, this meant January 2011 when the first national rule limiting GHG emissions for cars and light trucks was scheduled to take effect. Therefore, a permit issued after January 2, 2011, would have to address GHG emissions.
The Administrator signed two distinct findings in December 2009 regarding greenhouse gases under section 202(a) of the Clean Air Act. The endangerment finding indicated that current and projected concentrations of the six key well-mixed greenhouse gases  -- CO2, CH4, N2O, hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and SF6  --  in the atmosphere threaten the public health and welfare of current and future generations. These greenhouse gases have long lifetimes and, as a result, become homogeneously distributed through the lower level of the Earth's atmosphere (IPCC, 2001). This differentiates them from other greenhouse gases that are not homogeneously distributed in the atmosphere. The cause and contribute finding indicated that the combined emissions of these well-mixed greenhouse gases from new motor vehicles and new motor vehicle engines contribute to the greenhouse gas pollution which threatens public health and welfare. Both findings were published in the Federal Register on December 15, 2009 (Docket ID EPA-HQ-OAR-2009-0171). These findings did not themselves impose any requirements on any industry or other entities, but allowed the EPA to regulate greenhouse gases under the CAA (see preamble section II.E for regulatory background). This action was a prerequisite to implementing the EPA's proposed greenhouse gas emission standards for light-duty vehicles, which was finalized in January 2010. Once a pollutant is regulated under the CAA, it is subject to permitting requirements under the PSD and Title V programs.  The 2009 Endangerment Finding and a denial of reconsideration were challenged in a lawsuit; on June 26, 2012, the DC Circuit Court upheld the Endangerment Finding and the Reconsideration Denial, ruling that the Finding was neither arbitrary nor capricious, was consistent with Massachusetts v. EPA, and was adequately supported by the administrative record. The Court found that the EPA had based its decision on "substantial scientific evidence," noted that the EPA's reliance on assessments was consistent with the methods decision-makers often use to make a science-based judgment, and stated that "EPA's interpretation of the governing CAA provisions is unambiguously correct."
In May 2010, the EPA issued the final Tailoring Rule which set thresholds for GHG emissions that define when permits under the New Source Review and Title V Operating Permit programs are required for new and existing industrial facilities. Facilities responsible for nearly 70 percent of the national GHG emissions from stationary sources, including EGUs, were subject to permitting requirements under the rule.  This rule was upheld by the D.C. Circuit in 2012.
The EPA entered into a proposed settlement agreement in December 2010 to issue rules that will address greenhouse gas emissions from fossil fuel-fired power plants. On March 27, 2012, EPA proposed NSPS for CO2 emissions from new source natural gas, coal, and other solid fossil-fired EGUs.  After consideration of information provided in more than 2.7 million comments on the March 27, 2012 proposal, as well as consideration of continuing changes in the electricity sector, the EPA determined that revisions in its initially proposed approach were warranted.  EPA replaced that prior proposal with a new proposal for NSPS for CO2 emissions from EGUs on September 20, 2013; this action finalizes that rulemaking.  Existing source standards are not addressed in this action. Details of the settlement agreement can be found on the EPA website.
2.9 	Revenues and Expenses
Due to lower retail electricity sales, total utility operating revenues declined in 2012 to $271 billion from a peak of almost $300 billion in 2008. Despite revenues not returning to 2008 levels in 2012, operating expenses were appreciably lower and as a result, net income also rose in comparison to 2008 (see Table 2-9). Recent economic events have put downward pressure on electricity demand, thus dampening electricity prices and consumption (utility revenues), but have also reduced the price and cost of fossil fuels and other expenses. In 2012 electricity generation was 1.28 percent below the generation in 2011, and has declined in 4 of the past 5 years.
Table 2-9 shows that investor-owned utilities (IOUs) earned income of about 13.0 percent compared to total revenues in 2012. The 2012 return on revenue was the third highest year for the period 2002 to 2012 (average: 11.9 percent range: 10.6 percent to 13.32 percent).

Table 2-9. 	Revenue and Expense Statistics for Major U.S. Investor-Owned Electric Utilities for 2010 (nominal $millions)

2002

2008

2012
Utility Operating Revenues
                                    219,609
                                    298,962
                                    270,912
Electric Utility
                                    200,360
                                    266,124
                                    249,166
Other Utility
                                    19,250
                                    32,838
                                    21,745
Utility Operating Expenses
                                    189,062
                                    267,263
                                    235,694
Electric Utility
                                    171,604
                                    236,572
                                    220,722
      Operation
                                    116,660
                                    175,887
                                    152,379
         Production
                                    90,715
                                    140,974
                                    111,714
            Cost of Fuel
                                    24,149
                                    47,337
                                    38,998
            Purchased Power
                                    58,810
                                    84,724
                                    54,570
            Other
                                     7,776
                                     8,937
                                    18,146
      Transmission
                                     3,560
                                     6,950
                                     7,183
      Distribution
                                     3,117
                                     3,997
                                     4,181
      Customer Accounts
                                     4,168
                                     5,286
                                     5,086
      Customer Service
                                     1,820
                                     3,567
                                     5,640
      Sales
                                      264
                                      225
                                      221
      Admin. and
      General
                                    13,018
                                    14,718
                                    18,353
      Maintenance
                                    10,861
                                    14,192
                                    15,489
      Depreciation
                                    16,199
                                    19,049
                                    23,677
      Taxes and Other
                                    26,716
                                    26,202
                                    29,177
       Other Utility
                                    17,457
                                    30,692
                                    14,972
Net Utility Operating Income
                                    30,548
                                    31,699
                                    35,218
Source: Table 8.3, EIA Electric Power Annual, 2012
Note: This data does not include information for public utilities, nor for Independent Power Producers (IPPs).
2.10 	Natural Gas Market
The natural gas market in the United States has historically experienced significant price volatility from year to year, between seasons within a year, can undergo major price swings during short-lived weather events (such as cold snaps leading to short-run spikes in heating demand), and has seen a dramatic shift since 2008 due increased production from shale formations . Over the last decade, the annual average nominal price of gas delivered to the power sector peaked in 2008 at $9.02/mmBtu  and has since fallen dramatically to a low of $3.42/mmBtu in 2012. During that time, the daily price of natural gas reached as high as $18.48/mmBtu and as low as $2.03.  Adjusting for inflation using the GDP implicit price deflator, in $2011 the annual average price of natural gas delivered to the power sector ranged peaked at $9.38/mmBtu in 2008 and have fallen dramatically to a low of $3.36 in 2012.  The annual natural gas prices in both nominal and real (2011$) terms are in Figure 2-21. A comparison of the trends in the real price of natural gas with the real price of delivered coal and oil are shown in Figure 2-22. Figure 16 shows that while the real price of coal and oil increased from 2002 to 2012 (+54 percent and +203 percent respectively), the real price of natural gas declined by 22 percent in the same period. Most of the decline in real natural gas prices occurred between 2008 (the peak price year) and 2012, during which real gas prices declined by 64 percent while coal and oil prices both increased by 9 percent.  The sharp decline in natural gas prices from 2008 to 2012 was primarily caused by the rapid increase in natural gas production from shale formations.

Figure 2-21.	Nominal and Real (2011$) Prices of Natural Gas Delivered to the Power Sector ($/mmBtu)
Source: http://www.eia.gov/totalenergy/data/monthly/#prices. Downloaded 2/15/2015.

Figure 2-22.	 Relative Change in Real (2011$) Prices of Fossil Fuels Delivered to the Power Sector ($/mmBtu)
Source: http://www.eia.gov/totalenergy/data/monthly/#prices. Downloaded 2/15/2015.

Current and projected natural gas prices are considerably lower than the prices observed over the past decade, largely due to advances in hydraulic fracturing and horizontal drilling techniques that have opened up new shale gas resources and substantially increased the supply of economically recoverable natural gas. According to AEO 2012 (EIA 2012):
      Shale gas refers to natural gas that is trapped within shale formations. Shales are fine-grained sedimentary rocks that can be rich sources of petroleum and natural gas. Over the past decade, the combination of horizontal drilling and hydraulic fracturing has allowed access to large volumes of shale gas that were previously uneconomical to produce. The production of natural gas from shale formations has rejuvenated the natural gas industry in the United States.
The U.S. Energy Information Administration's Annual Energy Outlook 2014 estimates that the United States possessed 2,266 trillion cubic feet (Tcf) of technically recoverable dry natural gas resources as of January 1, 2012. Proven reserves make up 15 percent of the technically recoverable total estimate, with the remaining 85 percent from unproven reserves. Natural gas from proven and unproven shale resources accounts for 611 Tcf of this resource estimate.
Many shale formations, especially the Marcellus, are so large that only small portions of the entire formations have been intensively production-tested. Furthermore, estimates from the Marcellus and other emerging fields with few wells already drilled are likely to shift significantly over time as new geological and production information becomes available. Consequently, the estimate of technically recoverable resources is highly uncertain, and is regularly updated as more information is gained through drilling and production.
At the 2012 rate of U.S. consumption (about 25.6 Tcf per year), 2,266 Tcf of natural gas is enough to supply nearly 90 years of use. The AEO 2014 estimate of  the shale gas resource base is modestly higher than the AEO 2012 estimate (2,214 Tcf) shale gas production estimates, driven by lower drilling costs and continued drilling in shale plays with high concentrations of natural gas liquids and crude oil, which have a higher value in energy equivalent terms than dry natural gas.
EIA's projections of natural gas conditions did not change substantially in AEO 2014 from either the AEO 2012 or 2013, and EIA is still forecasting abundant reserves consistent with the above findings.  Recent historical data reported to EIA is also consistent with these trends, with 2014 being the highest year on record for domestic natural gas production.
2.11 	References
Advanced Resources International. Improving Domestic Energy Security and Lowering CO2 Emissions with "Next Generation" CO2-Enhanced Oil Recovery (CO2-EOR). 2011. Available online at: http://www.netl.doe.gov/research/energy-analysis/publications/details?pub=df02ffba-6b4b-4721-a7b4-04a505a19185. Han, Weon S., McPherson, B J., Lichtner, P C., and Wang, F P. Evaluation of CO2 trapping mechanisms at the SACROC northern platform, Permian basin, Texas, site of 35 years of CO2 injection. American Journal of Science 310. (2010): 282-324.Interagency Task Force on Carbon Capture and Storage. Report of the Interagency Task Force on Carbon Capture and Storage. August 2010. Available online at: http://www.epa.gov/climatechange/downloads/CCS-Task-Force-Report-2010.pdf.
Intergovernmental Panel on Climate Change. Climate Change 2001: The Scientific Basis. 2001. Available online at: http://www.grida.no/publications/other/ipcc_tar/?src=/climate/ipcc_tar/wg1/218.htm.
International Energy Agency (IEA). Tracking Clean Energy Progress 2013. Input to the Clean Energy Ministerial. 2013. Available online at: http://www.iea.org/etp/tracking/.
Koottungal, Leena. 2014 Worldwide EOR Survey, Oil & Gas Journal, Volume 112, Issue 4, April 7, 2014 (corrected tables appear in Volume 112, Issue 5, May 5, 2014).
National Energy Technology Laboratory (NETL). Reducing CO2 Emissions by Improving the Efficiency of Existing Coal-fired Power Plant Fleet. July 2008. Available online at: http://www.netl.doe.gov/energy-analyses/pubs/CFPP%20Efficiency-FINAL.pdf.
National Energy Technology Laboratory (NETL). The United States 2012 Carbon Utilization and Storage Atlas, Fourth Edition. 2012. Available online at: http://www.netl.doe.gov/technologies/carbon_seq/refshelf/atlasIV/.
National Energy Technology Laboratory (NETL). Energy Analyses: Cost and Performance Baselines for Fossil Energy Plants. 2013. Available online at: http://www.netl.doe.gov/energy-analyses/baseline_studies.html.
Pacific Northwest National Laboratory (PNNL). An Assessment of the Commercial Availability of Carbon Dioxide Capture and Storage Technologies as of June 2009. June 2009. Available online at: http://www.pnl.gov/science/pdf/PNNL-18520_Status_of_CCS_062009.pdf.
U.S. Energy Information Administration (U.S. EIA). Carbon Dioxide Emissions from the Generation of Electric Power in the United States. July 2000. Available online at: ftp://ftp.eia.doe.gov/environment/co2emiss00.pdf.
U.S. Energy Information Administration (U.S. EIA). Electric Power Annual 2003. 2003. Available online at: http://www.eia.gov/electricity/annual/archive/03482003.pdf.
U.S. Energy Information Administration (U.S. EIA). Electric Power Annual 2009. 2009. Available online at: http://www.eia.gov/electricity/annual/archive/03482009.pdf.
U.S. Energy Information Administration (U.S. EIA). Electric Power Annual 2011. 2013. Available online at: http://www.eia.gov/electricity/annual/.
U.S. Energy Information Administration (U.S. EIA). "Status of Electricity Restructuring by State." 2010a. Available online at: http://www.eia.gov/cneaf/electricity/page/restructuring/restructure_elect.html.
U.S. Energy Information Administration (U.S. EIA). AEO 2010 Retrospective Review. 2010b. Available online at: http://www.eia.gov/forecasts/aeo/retrospective/.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2010. 2010c. Available online at: http://www.eia.gov/oiaf/archive/aeo10/index.html.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Review 2010. 2010d. Available online at: http://www.eia.gov/totalenergy/data/annual/pdf/aer.pdf.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2011. 2011. Available online at: http://www.eia.gov/forecasts/archive/aeo11/.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2012 (Early Release). 2012. Available online at: http://www.eia.gov/forecasts/aeo/.
U.S. Energy Information Administration (U.S. EIA). Today in Energy: Most states have Renewable Portfolio Standards.  2012a. Available online at: http://www.eia.gov/todayinenergy/detail.cfm?id=4850.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2013. 2013. Available online at: http://www.eia.gov/forecasts/aeo/.
U.S. Energy Information Administration (U.S. EIA). Monthly Energy Review, April  2015. 2015. Available online at: http://www.eia.gov/totalenergy/data/monthly/.
U.S. Environmental Protection Agency (U.S. EPA). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 - 2011. April 2013. Available online at: http://www.epa.gov/climatechange/Downloads/ghgemissions/US-GHG-Inventory-2013-Main-Text.pdf.
U.S. Geological Survey (USGS) Carbon Dioxide Storage Resources Assessment Team. National assessment of geologic carbon dioxide storage resources  -  Results: U.S. Geological Survey Circular 1386. Available online at: http://pubs.usgs.gov/circ/1386/.
 Chapter 3
Benefits of Reducing Greenhouse gas emissions and Other Pollutants
 This rule is designed to set emission limits for carbon dioxide (CO2), thereby limiting potential increases in future emissions and CO2 concentrations. This will reduce the risk of some adverse effects of climate change. As discussed in Chapter 5, the U.S. Environmental Protection Agency (EPA) does not anticipate any notable CO2 emission changes resulting from the rule. Rather, by clarifying that in the future new coal-fired power plants will be required to meet a particular performance standard, this rulemaking reduces uncertainty and may enhance the prospects for the deployment of carbon capture and storage (CCS).
This chapter summarizes the adverse effects on public health and public welfare detailed in the 2009 Endangerment Finding. The major assessments by the U.S. Global Change Research Program (USGCRP), the Intergovernmental Panel on Climate Change (IPCC), and the National Research Council (NRC) served as the primary scientific basis for these effects. A discussion of climate science findings from newer assessments can be found in the Preamble. This chapter also provides a general discussion about how the climate-related and human health benefits of emissions reductions are estimated.  These valuation approaches are used in Chapter 5 to assess the relative differences in emissions between newly built electric generating technologies.
3.1	Overview of Climate Change Impacts from GHG Emissions
Through the implementation of CAA regulations, the EPA addresses the negative externalities caused by air pollution. In 2009, the EPA Administrator found that elevated concentrations of greenhouse gases in the atmosphere may reasonably be anticipated both to endanger public health and to endanger public welfare. It is these adverse impacts that make it necessary for the EPA to regulate GHGs from EGU sources. The preamble summarizes the public health and public welfare impacts that were detailed in the 2009 Endangerment Finding. For health, these include the increased likelihood of heat waves, negative impacts on air quality, more intense hurricanes, more frequent and intense storms and heavy precipitation, and impacts on infectious and waterborne diseases. For welfare, these include reduced water supplies in some regions, increased water pollution, increased occurrences of floods and droughts, rising sea levels and damage to coastal infrastructure, increased peak electricity demand, changes in ecosystems, and impacts on indigenous communities.
The preamble also summarizes new scientific assessments and recent climatic observations. Major scientific assessments released since the 2009 Endangerment Finding have improved scientific understanding of the climate, and provide even more evidence that GHG emissions endanger public health and welfare for current and future generations. The National Climate Assessment (NCA3), in particular, assessed the impacts of climate change on human health in the United States, finding that, Americans will be impacted by "increased extreme weather events, wildfire, decreased air quality, threats to mental health, and illnesses transmitted by food, water, and disease-carriers such as mosquitoes and ticks." These assessments also detail the risks to vulnerable groups such as children, the elderly and low income households. Furthermore, the assessments present an improved understanding of the impacts of climate change on public welfare, higher projections of future sea level rise than had been previously estimated, a better understanding of how the warmth in the next century may reach levels that would be unprecedented relative to the preceding millions of years of history, and new assessments of the impacts of climate change on permafrost and ocean acidification. The impacts of GHG emissions will be realized worldwide, independent upon their location of origin, and impacts outside of the United States will produce consequences relevant to the United States.
3.2	Social Cost of Carbon
The social cost of carbon (SC-CO2) is a metric that estimates the monetary value of impacts associated with marginal changes in CO2 emissions in a given year. It includes a wide range of anticipated climate impacts, such as net changes in agricultural productivity and human health, property damage from increased flood risk, and changes in energy system costs, such as reduced costs for heating and increased costs for air conditioning. It is typically used to assess the avoided damages as a result of regulatory actions (i.e., benefits of rulemakings that lead to an incremental reduction in cumulative global CO2 emissions). This section discusses the development of the SC-CO2 estimates and the Chapter 5 analysis applies the SC-CO2 estimates to illustrate the value to society of the difference in CO2 emissions among different generation technologies.
The SC-CO2 estimates used in this analysis were developed over many years, using the best science available, and with input from the public.  Specifically, an interagency working group (IWG) that included the EPA and other executive branch agencies and offices used three integrated assessment models (IAMs) to develop the SC-CO2 estimates and recommended four global values for use in regulatory analyses. The SC-CO2 estimates were first released in February 2010 and updated in 2013 using new versions of each IAM.  These estimates were published in the 2013 Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 (2013 SC-CO2 TSD) and henceforth we refer to them as the "SC-CO2 estimates."
The SC-CO2 estimates were developed using an ensemble of the three most widely cited integrated assessment models in the economics literature with the ability to estimate the SC-CO2. A key objective of the IWG was to draw from the insights of the three models while respecting the different approaches to linking GHG emissions and monetized damages taken by modelers in the published literature. After conducting an extensive literature review, the interagency group selected three sets of input parameters (climate sensitivity, socioeconomic and emissions trajectories, and discount rates) to use consistently in each model. All other model features were left unchanged, relying on the model developers' best estimates and judgments, as informed by the literature. Specifically, a common probability distribution for the equilibrium climate sensitivity parameter, which informs the strength of climate's response to atmospheric GHG concentrations, was used across all three models. In addition, a common range of scenarios for the socioeconomic parameters and emissions forecasts were used in all three models. Finally, the marginal damage estimates from the three models were estimated using a consistent range of discount rates, 2.5, 3.0, and 5.0 percent. See the 2010 SC-CO2 TSD for a complete discussion of the methods used to develop the estimates and the key uncertainties, and the 2013 SC-CO2 TSD for the updated estimates.
The SC-CO2 estimates represent global measures because of the distinctive nature of the climate change, which is highly unusual in at least three respects. First, emissions of most GHGs contribute to damages around the world independent of the country in which they are emitted. The SC-CO2 must therefore incorporate the full (global) damages caused by GHG emissions to address the global nature of the problem. Second, the U.S. operates in a global and highly interconnected economy, such that impacts on the other side of the world can affect our economy.  Damages from climate change in other countries can affect U.S. companies and citizens, and conflict exacerbated by climate change can require military expenditures by the U.S. This means that the true costs of climate change to the U.S. are larger than the direct impacts that simply occur within the U.S. Third, climate change represents a classic public goods problem, but one that the United States cannot solve alone. A global estimate of the SC-CO2 is therefore the economically appropriate reference point for collective actions to reduce climate change.
With the release of the 2010 SC-CO2 estimates the IWG noted that there remained a number of limitations to the analysis and committed to updating the estimates as the science and economic understanding of climate change and its impacts on society improves over time.  In particular, a goal was set to revisit the SC-CO2 estimates "within two years or at such time as substantially updated models become available." Subsequent to the release of the 2010 TSD, all three of the models used in the development of the SC-CO2 estimates were updated by their (academic) developers, in part, to reflect more recent information on the potential impacts of climate change. Therefore, in 2013 the IWG released an update to the SC-CO2 estimates that maintained the same methodology underpinning the previous estimates, but applied the most current versions of the three IAMs. The 2013 process did not revisit the 2010 interagency modeling decisions (e.g., with regard to the discount rate, reference case socioeconomic and emission scenarios or equilibrium climate sensitivity). Rather, improvements in the way damages are modeled are confined to those that have been incorporated into the latest versions of the models by the developers themselves and used in peer-reviewed publications.
The model updates reflected in the 2013 SC-CO2 estimates include: an explicit representation of sea level rise damages in the DICE and PAGE models; updated adaptation assumptions, revisions to ensure damages are constrained by GDP, updated regional scaling of damages, and a revised treatment of potentially abrupt shifts in climate damages in the PAGE model; an updated carbon cycle in the DICE model; and updated damage functions for sea level rise impacts, the agricultural sector, and reduced space heating requirements, as well as changes to the transient response of temperature to the buildup of GHG concentrations and the inclusion of indirect effects of methane emissions in the FUND model. The 2013 SC-CO2 TSD provides additional detail on the specific model improvements and the updated estimates. When attempting to assess the incremental economic impacts of CO2 emissions, the analyst faces a number of serious challenges. A report from the National Academies of Science (NRC, 2009) points out that any assessment will suffer from uncertainty, speculation, and lack of information about (1) future emissions of greenhouse gases, (2) the effects of past and future emissions on the climate system, (3) the impact of changes in climate on the physical and biological environment, and (4) the translation of these environmental impacts into economic damages.  As a result, any effort to quantify and monetize the harms associated with climate change will raise serious questions of science, economics, and ethics and should be viewed as provisional.
The 2010 SC-CO2 TSD noted a number of limitations to the SC-CO2 analysis, including the incomplete way in which the integrated assessment models capture catastrophic and non-catastrophic impacts, their incomplete treatment of adaptation and technological change, uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk aversion. Current integrated assessment models do not assign value to all of the important physical, ecological, and economic impacts of climate change recognized in the climate change literature due to a lack of precise information on the nature of damages and because the science incorporated into these models understandably lags behind the most recent research. The limited amount of research linking climate impacts to economic damages makes the modeling exercise even more difficult. These individual limitations do not all work in the same direction in terms of their influence on the SC-CO2 estimates, though taken together they suggest that the SC-CO2 estimates are likely conservative. In particular, the IPCC Fourth Assessment Report (2007), which was the most current IPCC assessment available at the time of the IWG's 2009-2010 review, concluded that "It is very likely that [SC-CO2 estimates] underestimate the damage costs because they cannot include many non-quantifiable impacts." Since then, the peer-reviewed literature has continued to support this conclusion. For example, the IPCC Fifth Assessment report observed that SCC estimates continue to omit various impacts that would likely increase damages. The 95th percentile estimate was included in the recommended range for regulatory impact analysis to address these concerns.
Nonetheless, these estimates and the discussion of their limitations represent the best available information about the social benefits of CO2 reductions to inform benefit-cost analysis. The new versions of the models used to estimate the values presented below offer some improvements in these areas, although further work remains warranted.
Accordingly, the EPA and other agencies continue to engage in research on modeling and valuation of climate impacts with the goal to improve these estimates. The EPA and other federal agencies have considered the extensive public comments on ways to improve SC-CO2 estimation received via the notice and comment periods that were part of numerous rulemakings.  In addition, OMB's Office of Information and Regulatory Affairs sought public comment on the approach used to develop the SC-CO2 estimates. The comment period ended on February 26, 2014, and OMB is reviewing the comments received.
The four SC-CO2 estimates, updated in 2013, are as follows: $14, $47, $70, and $140 per metric ton of CO2 emissions in the year 2022 (2011$).  The first three values are based on the average SC-CO2 from the three IAMs, at discount rates of 5, 3, and 2.5 percent, respectively. SC-CO2 estimates for several discount rates are included because the literature shows that the SC-CO2 is quite sensitive to assumptions about the discount rate, and because no consensus exists on the appropriate rate to use in an intergenerational context (where costs and benefits are incurred by different generations). The fourth value is the 95th percentile of the SC-CO2 from all three models at a 3 percent discount rate. It is included to represent higher-than-expected impacts from temperature change further out in the tails of the SC-CO2 distribution (representing less likely, but potentially catastrophic, outcomes).
Table 3-1 presents the updated global SC-CO2 estimates for the years 2015 to 2050. In order to calculate the dollar value for emission reductions, the SC-CO2 estimate for each emissions year would be applied to changes in CO2 emissions for that year, and then discounted back to the analysis year using the same discount rate used to estimate the SC-CO2.  The SC-CO2 increases over time because future emissions are expected to produce larger incremental damages as physical and economic systems become more stressed in response to greater climate change. Note that the interagency group estimated the growth rate of the SC-CO2 directly using the three integrated assessment models rather than assuming a constant annual growth rate. This helps to ensure that the estimates are internally consistent with other modeling assumptions.
Table 3-1.	Global Social Cost of CO2, 2015-2050[a] (in 2011$)

                                     Year
                          Discount Rate and Statistic

                                  5% Average
                                  3% Average
                                 2.5% Average
                                      3%
                               95[th] percentile
                                     2015
                                      $12
                                      $39
                                      $61
                                     $120
                                     2020
                                      $13
                                      $46
                                      $68
                                     $140
                                     2022
                                      $14
                                      $47
                                      $70
                                     $140
                                     2025
                                      $15
                                      $50
                                      $74
                                     $150
                                     2030
                                      $17
                                      $55
                                      $80
                                     $170
                                     2035
                                      $20
                                      $60
                                      $85
                                     $190
                                     2040
                                      $22
                                      $65
                                      $92
                                     $200
                                     2045
                                      $26
                                      $70
                                      $98
                                     $220
                                     2050
                                      $28
                                      $76
                                     $100
                                     $230
[a] The SC-CO2 values vary depending on the year of CO2 emissions and are defined in real terms. These SC-CO2 values are stated in $/metric ton. Unrounded numbers from the 2013 SC-CO2 TSD were adjusted to 2011$ and used in the illustrative analysis in Chapter 5.

3.3	Health Co-Benefits of SO2 and NOx Reductions
The EPA anticipates that this rule will result in negligible emission changes by 2022. However, if CO2 emissions are reduced from new EGUs under this rule, then emissions of other pollutants from the power sector would also likely be reduced. For example, reducing CO2 emissions through the adoption of CCS from coal-fired boilers may also yield sulfur dioxide (SO2) and nitrogen oxide (NOX) emission reductions, which in turn would yield health benefits (we refer to these additional benefits as "co-benefits").
SO2 is a precursor for fine particulate matter formation, which is particulate matter 2.5 micrometers in diameter and smaller (PM2.5), while NOX is a precursor for PM2.5 and ground-level ozone formation. As such, reductions of SO2 and NOX would in turn lower overall ambient concentrations of PM2.5 and ozone. Reducing exposure to PM2.5 and ozone is associated with human health benefits including avoided mortality and morbidity. Researchers have associated PM2.5 and ozone exposure with adverse health effects in numerous toxicological, clinical, and epidemiological studies (U.S. EPA, 2009; U.S. EPA, 2013a). Health effects associated with exposure to PM2.5 include premature mortality for adults and infants, cardiovascular morbidity such as heart attacks and hospital admissions, and respiratory morbidity such as asthma attacks, bronchitis, hospital and emergency room visits, work loss days, restricted activity days, and respiratory symptoms. Health effects associated with exposure to ozone include premature mortality and respiratory morbidity such as hospital admissions, emergency room visits, and school loss days. In addition to human health co-benefits associated with PM2.5 and ozone exposure, reducing SO2 and NOX emissions under this rule would result in reduced health impacts from direct exposure to these pollutants.
Reducing SO2 and NOX emissions would also result in other human welfare (non-health) improvements including improvements in ecosystem services. SO2 and NOX emissions can adversely impact vegetation and ecosystems through acidic deposition and nutrient enrichment, and can affect certain manmade materials, visibility, and climate (U.S. EPA, 2009; U.S. EPA, 2008).
The avoided incidences of health effects and monetized value of health or non-health improvements that result from SO2 and NOx emissions reductions depend on the location of those reductions. For a full discussion of the human health, ecosystem and other benefits of reducing SO2 and NOX emissions from power sector sources, please refer to the Regulatory Impact Analysis for the Final Carbon Pollution Guidelines for Existing Power Plants (U.S. EPA, 2015).
The EPA anticipates that this rule will result in negligible emission changes by 2022. As a result we did not perform a full health co-benefit impact assessment for a specific modeled compliance scenario. In Chapter 5, EPA presents results for several illustrative analyses that show the potential impacts of the rule if certain key assumptions were to change.  When assessing the co-benefits of differences in emissions from different generation technologies in Chapter 5, the EPA does not assert a specific location for the illustrative new unit. Instead, the EPA relied on a national-average benefit per-ton (BPT) method to estimate PM2.5-related health impacts of SO2 and NOX emissions. The BPT approach provides an estimate of the total monetized human health benefits (the sum of premature mortality and morbidity) of reducing one ton of PM2.5 precursor (i.e., NOX and SO2) from the sector. To develop the BPT estimates used in this analysis the EPA utilized detailed air quality modeling of the entire power sector SO2 and NOX emissions along with the BenMAP model to estimate the benefits of air quality improvements using projected 2020 population, baseline incidence rates, and economic factors.
The SO2- and NOX-related BPT estimates utilized in this analysis are derived from the Technical Support Document (TSD) on estimating the BPT of reducing PM2.5 and its precursors (U.S. EPA, 2013b). These BPT values are estimated in a methodologically consistent manner with those reported in Fann et al. (2012). They differ from those reported in Fann et al. (2012) as they reflect the health impact studies and population data updated in the benefits analysis of the final PM NAAQS RIA (U.S. EPA, 2012). The recalculation of the Fann et al. (2012) BPT values based on the updated data from the PM NAAQS RIA (U.S. EPA, 2012) is described in the TSD (U.S. EPA, 2013b). The BPT values are for the entire electricity sector and are not differentiated by fuel or generator type.
The methods used for this analysis are consistent with those used to estimate the health co-benefits from secondary PM2.5 formation for the Regulatory Impact Analysis for the Final Carbon Pollution Guidelines for Existing Power Plants (U.S. EPA, 2015).  One notable difference between the BPT values used in the two analyses is that this analysis utilizes national-average BPT estimates because EPA does not assert a specific location for the illustrative new unit, whereas the BPT estimates used in the RIA for the final existing source guidelines differ by region. Chapter 5 discusses how the analysis may be affected when considering regional differences in the damages associated with these pollutants.
Despite our attempts to quantify and monetize as many of the co-benefits of reducing emissions from electricity generating sources as possible, not all known health and non-health co-benefits from reducing SO2 and NOx are accounted for in this assessment. For more information about unquantified health and non-health co-benefits of SO2 and NOx please refer to tables 5-2 and 6-2 of the PM NAAQS RIA (U.S. EPA, 2012), respectively. Furthermore, the analysis that follows does not account for known differences in other air and water pollutants between the different generating technologies, including, for example, ozone and directly-emitted PM and ozone.  The reason and implications for limiting our consideration of co-benefits to pollutants that cause secondary PM2.5 is discussed in Chapter 5.
As we do not conjecture a specific location for the new units being compared, this RIA is unable to include the type of detailed uncertainty assessment found in the PM NAAQS RIA (U.S. EPA, 2012). However, the results of the uncertainty analyses presented in the PM NAAQS RIA can provide some information regarding the uncertainty inherent in the benefits results presented in this analysis. In addition to the uncertainties described in the PM NAAQS RIA, the use of BPT estimates come with additional uncertainty. Specifically, these national-average BPT estimates reflect a specific geographic distribution of SO2 and NOX reductions resulting in a specific reduction in PM2.5 exposure and may not fully reflect local or regional variability in population density, meteorology, exposure, baseline health incidence rates, timing of emissions, or other factors that might lead to an over-estimate or under-estimate of the actual benefits associated with PM2.5 precursors in a specific location. These estimates are illustrative as the EPA does not assert a specific location for the illustrative electricity generation technologies and is therefore unable to specifically determine the population that would be affected by their emissions. Therefore, the benefits for any specific unit can be different than the estimates shown here.
Notwithstanding these limitations, reducing one thousand tons of annual SO2 from U.S. power sector sources has been estimated to yield between 4 and 9 incidences of premature mortality avoided and monetized PM2.5-related health benefits (including these incidences of premature mortality avoided) between $38 million and $85 million in 2020 (2011$) using a 3% discount rate or between $34 million and $76 million (2011$) using a 7% discount rate. Additionally, reducing one thousand tons of annual NOX from U.S. EGUs has been estimated to yield up to 1 incidence of premature mortality avoided and monetized PM2.5-related health benefits (including these incidences of premature mortality avoided) of between $5.5 million and $12 million in 2020 (2011$) using a 3% discount rate or between $5.0 million and $11 million (2011$) using a 7% discount rate. For each pollutant, the range of estimated benefits for each discount rate is due to the EPA's use of two alternative primary estimates of PM2.5-related mortality impacts: a lower primary estimate based on Krewski et al. (2009) and a higher primary estimate based on Lepeule et al. (2012). The benefit per ton values are reported in Table 3-2.
Table 3-2.	Monetized Health Benefits Per Ton of PM2.5 Precursor Reductions in 2020[a] (in 2011$)

                                PM2.5 Precursor

                                      SO2
                                      NOX
3% Discount Rate

   Krewski et al. (2009)
                                   $38,000
                                    $5,500
   Lepeule et al. (2012)
                                    $85,000
                                    $12,000
7% Discount Rate

   Krewski et al. (2009)
                                    $34,000
                                    $5,000
   Lepeule et al. (2012)
                                    $76,000
                                    $11,000
[a] These estimates are from U.S. EPA, 2013a (electricity generating units) and are adjusted to 2011$ using the Gross Domestic Product implicit price deflator reported by the Department of Commerce.
3.4	References
40 CFR Chapter I [EPA - HQ - OAR - 2009 - 0171; FRL - 9091 - 8] RIN 2060 - ZA14, "Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act," Federal Register / Vol. 74, No. 239 / Tuesday, December 15, 2009 / Rules and Regulations.
Fann, N., K.R. Baker, C.M. Fulcher. 2012. Characterizing the PM2.5-related health benefits of emission reductions for 17 industrial, area and mobile emission sectors across the U.S. Environment International, Volume 49, 15 November 2012, Pages 141-151, ISSN 0160- 4120, http://dx.doi.org/10.1016/j.envint.2012.08.017.
Interagency Working Group (IWG) on Social Cost of Carbon (SC-CO2). 2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. Docket ID EPA-HQ-OAR-2009-0472-114577. Participation by Council of Economic Advisers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury. <http://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf> Accessed March 31, 2015.
Interagency Working Group (IWG) on Social Cost of Carbon (SC-CO2). 2013. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. Docket ID EPA-HQ-OAR-2013-0495. Participation by Council of Economic Advisers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Domestic Policy Council, Environmental Protection Agency, National Economic Council, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury. <http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/technical-update-social-cost-of-carbon-for-regulator-impact-analysis.pdf> Accessed March 31, 2015.
Intergovernmental Panel on Climate Change (IPCC). 2007. Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (AR4) [Core Writing Team, Pachauri, R.K and Reisinger, A. (eds.)]. IPCC, Geneva, Switzerland, 104 pp. <http://www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_synthesis_report.htm>. Accessed March 30, 2015.
Krewski, D., R.T. Burnett, M.S. Goldbert, K. Hoover, J. Siemiatycki, M. Jerrett, M. Abrahamowicz, and W.H. White. 2009. "Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality." Special Report to the Health Effects Institute. Cambridge, MA. July.
Lepeule, J., F. Laden, D. Dockery, and J. Schwartz. 2012. "Chronic Exposure to Fine Particles and Mortality: An Extended Follow-Up of the Harvard Six Cities Study from 1974 to 2009." Environ Health Perspect. In press. Available at: http://dx.doi.org/10.1289/ehp.1104660.
Medina-Ramon, M. and J. Schwartz, 2007: Temperature, temperature extremes, and mortality: a study of acclimatization and effect modification in 50 U.S. cities.  Occupational and Environmental Medicine, 64(12), 827-833.
National Research Council (NRC). 2009. Hidden Cost of Energy: Unpriced Consequences of Energy Production and Use. National Academies Press. Washington, DC.
U.S. Environmental Protection Agency (U.S. EPA). 2008. Integrated Science Assessment for Oxides of Nitrogen and Sulfur  - Ecological Criteria National (Final Report). National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-08/139. December. Available on the Internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485.
U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for Environmental Assessment  -  RTP Division. December. Available on the Internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546.
U.S. Environmental Protection Agency (U.S. EPA). 2011. Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards. Office of Air Quality Planning and Standards, Research Triangle Park, NC. December. Available on the Internet at http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf.
U.S. Environmental Protection Agency (U.S. EPA). 2012. Regulatory Impact Analysis (RIA) for the Final Revisions to the National Ambient Air Quality Standards for Particulate Matter. Office of Air Quality Planning and Standards, Research Triangle Park, NC. December. Available on the Internet at http://www.epa.gov/ttn/ecas/regdata/RIAs/finalria.pdf.
U.S. Environmental Protection Agency (U.S. EPA). 2013a. Integrated Science Assessment for Ozone and Related Photochemical Oxidants. EPA/600/R-10/076F. Research Triangle Park, NC: U.S. EPA. February. Available on the Internet at http://oaspub.epa.gov/eims/eimscomm.getfile?p_download_id=511347.
U.S. Environmental Protection Agency (U.S. EPA). 2013b. Technical Support Document Estimating the Benefit per Ton of Reducing PM2.5 Precursors from 17 Sectors. Office of Air Quality Planning and Standards, Research Triangle Park, NC. January. Available on the Internet at http://www2.epa.gov/sites/production/files/2014-10/documents/sourceapportionmentbpttsd.pdf
U.S. Environmental Protection Agency (U.S. EPA). 2015. Regulatory Impact Analysis for the Final Carbon Pollution Guidelines for Existing Power Plants. [UPDATE LOCATION WHEN AVAILABLE]
U.S. Global Change Research Program (USGCRP). Global Climate Change Impacts in the United States.  Thomas R. Karl, Jerry M. Melillo, and Thomas C. Peterson, (eds.). Cambridge University Press, 2009.
 Chapter 4
Costs, Economic, and Energy Impacts
4.1	Synopsis
This chapter reports the central compliance cost, economic, and energy impact analyses performed for the proposed EGU New Source GHG Standards. The EPA analyzed and assessed a wide range of potential scenarios and outcomes, using a detailed power sector model, other government projections for the power sector, and additional economic assessments and analyses to determine the potential impacts of this action.
The primary finding of this assessment is that in the absence of this proposed rule, all projected unplanned capacity additions affected by this proposal during the analysis period would already be compliant with the rule's requirements (e.g., natural gas combined cycle units, low capacity factor natural gas combustion turbines, and small amounts of coal-fired units with CCS supported by Federal and State funding). The analysis period is defined as through 2022 to reflect that CAA Section 111(b) requires that the NSPS be reviewed every eight years.  The EPA's conclusion was based on:
      * EIA power sector modeling projections,
      * EPA power sector modeling projections,
      * Electric utility integrated resource planning (IRP) documents,
      * Projected new EGUs reported by industry to EIA.
The EPA's finding of no new conventional coal-fired capacity is robust beyond the analysis period (past 2030 in both EIA and EPA baseline modeling projections) and across a wide range of alternative potential market, technical, and regulatory scenarios that influence power sector investment decisions.  As a result, the EGU New Source GHG Standards are not expected to change GHG emissions for newly constructed EGUs, and are anticipated to yield no monetized benefits and impose negligible costs, economic impacts, or energy impacts on the electricity sector or society.  While the EPA does not project any new coal-fired EGUs without CCS to be built in the absence of this rule, this chapter presents an analysis of the project-level costs of building new coal-fired capacity with and without CCS to demonstrate that a requirement of partial CCS would not preclude new coal construction.  An additional illustrative analysis, presented at the end of this chapter, shows that even in the unlikely event that new, noncompliant EGU capacity would be built in the absence of this rule the proposed EGU New Source GHG Standards would provide net social benefits under a range of assumptions.
4.2	Requirements of the Final GHG EGU NSPS
      In this action, the EPA is finalizing standards of performance for two basic categories of new units that have not commenced construction by January 8, 2014: (i) fossil fuel-fired electric utility steam generating units (boilers and IGCC units), including new units and existing units that undergo a major modification or reconstruction; and (ii) natural gas-fired stationary combustion turbines that generate electricity for sale and meet certain size and operational criteria.

      The EPA is finalizing standards of performance for affected sources within the following two categories: (1) all fossil fuel-fired steam generating units (steam generating units, boilers and IGCC units), and (2) all natural gas-fired stationary combustion turbines, regardless of the size of the stationary turbine unit. All affected new fossil fuel-fired EGUs would be required to meet an output-based emission rate of a specific mass of CO2 per MWh of electricity generated energy output on a gross basis.

      New fossil fuel-fired steam generating units (boilers and IGCC units) would be required to meet an emission standard of 1,400 lb CO2/MWh of gross energy output. This is a less stringent standard than the proposed limitation (1,100 lb CO2/MWh) in the 2013 proposed rule. Existing fossil fuel-fires steam generating units that 	are making modifications that will result in an increase of more than 10% of that unit's historic CO2/MWh emission rate, or are being reconstructed, will be required to meet an emission standard determined by the size of the heat input of the unit. Such modified units with a heat input greater than 2,000 MMBtu/hour will have an emission limit of 1,800 lb CO2/MWh of gross energy output. Modified units with a heat input rate less than or equal to 2,000 MMBtu/hour will have an emission limit of 2,000 lb CO2/MWh of gross energy output.

      Newly constructed, modified or reconstructed natural gas-fired stationary combustion turbines will be required to meet a standard of 1,000 lb CO2/MWh of gross energy output (or 1,080 lb CO2/MWh of net energy output). This emission limit applies to all affected natural gas-fired stationary combustion units regardless of size. The natural gas combustion turbine standard, however, will only apply to units that will exceed a sales threshold on the amount of electricity generated that is sold to the electric grid. The purpose of the sales threshold criterion is to permit gas-fired combustion turbines that will operate as a combined heat and power (CHP) unit and only sell a small portion of the gross electricity generated to the grid to not have to meet the same emission standard as a combustion turbine unit designed primarily to generate electricity to be sold to the grid.

       Please refer to the preamble for additional detail concerning affected sources and standards of performance.
4.3	Power Sector Modeling Framework
4.3.1	Modeling Overview
Over the last decade, the EPA has conducted extensive analyses of regulatory actions impacting the power sector.  These efforts support the Agency's understanding of key policy variables and provide the framework for how the Agency estimates the costs and benefits associated with its actions that impact the power sector.  Current forecasts for the utilization of new and existing generating capacity are a key input into evaluating the impact of this rule.  Given excess capacity within the existing fleet and relatively low forecasts of electricity demand growth, there is limited new capacity - of any type - expected to be constructed over the next decade.  A small number of new coal-fired power plants have been completed and brought online in recent years; however, the EPA does not expect the construction of any new non-compliant coal-fired capacity through the analysis period. The EPA also does not expect any new non-compliant natural gas-fired stationary combustion turbines meeting the applicability criteria to be built. This conclusion is based in part on the Agency's own power sector modeling utilizing IPM as well as EIA's Annual Energy Outlook 2014 (AEO 2014) projections.
IPM, developed by ICF International, Inc, 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 examine prospective air pollution control policies throughout the United States for the entire electric power system. The EPA used IPM to project likely future electricity market conditions with and without this rule.  In addition to using IPM, the EPA has closely examined the AEO 2014 from the EIA.
To produce the AEO, EIA employs the National Energy Modeling System (NEMS), an energy-economy modeling system of the United States.  According to EIA:
"NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics."
The Electricity Market Module of NEMS produces projections of power sector behavior that minimize the cost of meeting electricity demand subject to the sector's inherent constraints, including the availability of existing generation capacity, transmission capacity and cost, cost of utility and nonutility technologies, expected load shapes, fuel markets, regulations, and other factors. EIA's AEO projections independently support the EPA's conclusions in that it projects no new generation capacity being constructed through the analysis period that would not already meet the level of the standard even in the absence of the standard.  Both sets of modeling results are presented in Section 4.4.
4.3.2	The Integrated Planning Model
IPM is a multi-regional, dynamic, deterministic linear programming model of the U.S. electric power sector. It provides forecasts of least cost capacity expansion, electricity dispatch, and emission 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 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.[,]
Although the Agency typically focuses on broad system effects when assessing the economic impacts of a particular policy, the EPA's application of IPM includes a detailed and sophisticated regional representation of key power sector variables and its organization.  When considering which new units are most cost effective to build and operate, the model considers the relative economics of various technologies based on a wide spectrum of current and future considerations, including capital costs, operation and maintenance costs, fuel costs, utility sector regulations, and emission profiles.  The capital costs for new units account for regional differences in labor, material, and construction costs. These regional cost differentiation factors are based on assumptions used in the EIA's AEO.
As part of IPM's assessment of the relative economic value of building a new power plant, the model incorporates a detailed representation of the fossil-fuel supply system that is used to forecast equilibrium fuel prices, a key component of new power plant economics.  The model includes an endogenous representation of the North American natural gas supply system through a natural gas module that reflects full supply/demand equilibrium of the North American gas market.  This module consists of 118 supply, demand, and storage nodes, 15 liquefied natural gas regasification facility locations and 3 LNG export 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 coal supply and demand system throughout the continental U.S., and reflects non-power sector demand and imports/exports.  IPM reflects 36 coal supply regions, 465 coal supply curves for each of 9 years, 14 coal sulfur grades, and the coal transport network, which consists of 4,947 linkages representing the costs of transporting coal via rail, barge, and truck and conveyer linkages connecting 41 regions with 575 individual coal-fired generating stations.  The coal supply curves and the transport network costs used in IPM are publicly available, were developed during a thorough bottom-up, mine-by-mine approach that depicts the coal choices and associated supply costs that power plants will face 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 84 coal supply curves.  The coal supply curves were developed in consultation with Wood Mackenzie, one of the leading energy consulting firms and specialists in coal supply.  These curves have been independently reviewed by industry experts and have been made available for public review on several occasions over the past two years during other rulemaking processes.
The EPA has used IPM extensively over the past two decades to analyze options for reducing power sector emissions. Recently, the model has been used to forecast the costs, emission changes, and power sector impacts for the Clean Air Interstate Rule (CAIR), Cross-State Air Pollution Rule (CSAPR), and the Mercury and Air Toxics Standards (MATS).
The model undergoes periodic formal peer review, which includes separate expert panels for both the model itself and the EPA's key modeling input assumptions. The rulemaking process also provides opportunity for expert review and comment by stakeholders, including owners and operators of the electricity sector that is represented by the model, public interest groups, and other developers of U.S. electricity sector models.  EPA is required to respond to significant comments submitted regarding the inputs used in IPM, its structure, and application.  The feedback that the Agency receives provides a detailed check for 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, from the mid-1990s through 2011 the Science Advisory Board reviewed IPM as part of the CAA Amendments Section 812 studies of the Clean Air Act costs and benefits that are periodically conducted.  The model has also undergone considerable interagency scrutiny when it has been used to conduct over one dozen legislative analyses (performed at Congress' request) over the past decade.  In addition, Regional Planning Organizations throughout the U.S. have extensively examined IPM as a key element in the state implementation plan (SIP) process for achieving the National Ambient Air Quality Standards.  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, all of whom subject the model to their own review procedures. States have also used the model extensively to inform issues related to ozone in the northeastern U.S.  This groundbreaking work set the stage for the NOx SIP call, which has helped reduce summer NOx emissions and the formation of ozone in densely populated areas in the northeast.
4.4	Analyses of Future Generating Capacity
4.4.1	Base Case Power Sector Modeling Projections
EPA conducted analysis and modeling in support of the April 2012 EGU GHG New Source Standards proposal, and concluded that new unplanned noncompliant base load power plants are not expected to be economic both during, and well beyond, the analysis period. The EPA conducted an analysis of the economic impacts by modeling a base case scenario of future electricity market conditions. The EPA's IPM modeling for the 2012 proposal utilized the IPM v. 4.10 base case, and relied on the AEO 2010 for the electric demand forecast for the U.S. and employed a set of the EPA's assumptions regarding fuel supplies, the performance and cost of electric generation technologies, pollution controls, and numerous other parameters.
After considering public comments received on the 2012 proposal, the EPA issued a new proposal for carbon emissions from new power plants in September, 2013. The EPA's IPM modeling of the 2013 111(b) proposal relied on the AEO 2013 electric demand forecast, and was analyzed using the IPM v. 5.13 base case.
For the analysis of the final 111(b) rule, the EPA used the IPM v. 5.14 base case, which relied on the electric demand forecast in AEO 2014. The v. 5.14 base case updated v. 5.13 unit level specifications (including control configurations) based on comments received and environmental regulations.  The base case accounts for the effects of the finalized MATS and CSAPR rules, New Source Review settlements and state rules through 2014 impacting sulfur dioxide (SO2), NOx, directly emitted particulate matter and CO2, and final actions the EPA has taken to implement the Regional Haze Rule. The EPA's IPM base case also includes two federal non-air rules effecting EGUs: the Cooling Water Intakes (316(b)) Rule and the Disposal of Coal Combustion Residuals from Electric Utilities Rule (CCR).
The EPA's IPM base case forecast finds that new generation capacity is expected to be compliant with the standards, even in the absence of this rule. Some new coal-fired units with federally-supported carbon capture and storage (CCS) are forecast to be constructed, though these units are expected to be compliant with their standards under this rule. New capacity is forecast to be predominately stationary combustion turbines and renewables. New simple-cycle combustion turbines (CTs) constructed in the EPA's IPM base case are assumed to operate at an emissions rate above the standard. Mirroring real world behavior, relatively low levels of CT generation are projected in the base case. In the base case new CTs are forecast to operate, on average in each domestic model region, at capacity factors well below the applicability requirements of this rule.  In the base case the maximum average capacity factor for individual new CTs is 14% or less across all domestic regions and all simulation years.  The emission rate of new natural gas combined cycle (NGCC) units in the EPA's IPM base case emit below the emissions rate standard of this final rule by assumption. However, a modeled emissions rate for new NGCC units below the standard is consistent with the detailed emissions rate analysis described in the preamble for this rule, which carefully considered emissions rate data on newly constructed NGCC units and GHG limitations in recently issued construction permits for NGCC facilities.
The EIA projections that are reflected in AEO 2014 are summarized in the following tables alongside the EPA base case projections.  New coal-fired capacity through 2030 in the AEO 2014 reference case is entirely CCS-equipped and would be in compliance with this proposal (300 MW).  The projected CCS-equipped capacity is assumed to occur in response to existing Federal, State, and local incentives for the technology. According to the AEO 2014  -  which represents existing policies and regulations influencing the power sector - the vast majority of new, unplanned generating capacity is forecast to be either natural gas-fired or renewable.  The economics favoring new natural gas combined cycle (NGCC) additions instead of coal-fired additions are robust under a range of sensitivity cases examined in the AEO 2013 and AEO 2014.  Sensitivity cases that EIA conducted in those AEOs separately examine higher economic growth, lower coal prices, no risk premium for greenhouse gas emissions liability from conventional coal, and lower oil and natural gas resources also forecast zero unplanned additions of coal-fired capacity without CCS in the analysis period.  This has been a consistent finding in the AEO, which led EIA to conclude that "the low capital expense, technical maturity, and dispatchability of natural gas generation are likely to dominate investment decisions under current policies and projected prices."

Table 4-1.	Reference Case Unplanned Cumulative Capacity Additions (GW)

                                      EPA
                            AEO 2014 Reference Case
                                 Capacity Type
                                     2020
                                     2020
                                     2025
                                     2030
Conventional Coal
                                       0
                                       0
                                       0
                                       0
Coal with CCS
                                      0.3
                                      0.3
                                      0.3
                                      0.3
Natural Gas CC
                                      6.9
                                      9.8
                                     28.8
                                     95.7
Natural Gas CT
                                      2.6
                                     14.1
                                     34.5
                                     49.2
Nuclear
                                       0
                                       0
                                       0
                                       0
Renewables
                                     15.9
                                     17.4
                                     19.3
                                     22.5
Distributed Generation
                                       0
                                      1.6
                                      3.3
                                      4.6
Total
                                     25.8
                                     43.2
                                     86.3
                                     141.4
Notes: The sum of the table values in each column may not match the total figure due to rounding. EPA capacity data is net nameplate capacity, AEO capacity data is net summer generating capacity.
Source: EPA 2020 projection from IPM v. 5.14 base case; EIA 2020-2030 projection from EIA Annual Energy Outlook 2014, Table A9.

The capacity projections of EIA and the EPA represent a continuation of current trends, where natural gas-fired capacity has been the technology of choice for base load and intermediate load power generation over the last few years (see Figure 4-1), due in large part to its significant levelized cost of electricity (LCOE) advantage over coal-fired generating technologies.  A greater discussion of the relative LCOE of different generating technologies is provided beginning in Section 4.4.

Figure 4-1.	Historical U.S. Power Plant Capacity Additions, by Technology, 1940-2011

Source: Form EIA-860 (2011)
Note: Renewables include hydro, geothermal, biomass solar, and wind energy technologies.
In addition to new builds, increased electricity demand is expected to be partially fulfilled by increased utilization of existing generating capacity.  Generation projections are the result of least-cost economic modeling both in IPM and AEO 2014, and reflect the most cost-effective dispatch and investment decisions modeled, given a variety of variables and constraints.  Even without the deployment of new conventional coal-fired capacity, U.S. electricity demand will continue to be met by a diverse mix of electricity generation sources with coal projected to continue to provide the largest share of electricity (36% of total 2020 generation in AEO 2014 and 37% in the EPA's projections), as displayed in Table 4-2.

Table 4-2.	2012 U.S. Electricity Net Generation and Projections for 2020, 2025, and 2030 (Billion kWh)

                                  Historical
                                      EPA
                            AEO 2014 Reference Case

                                     2012
                                     2020
                                     2020
                                     2025
                                     2030
Coal
                                     1,512
                                     1,534
                                     1,646
                                     1,689
                                     1,692
Oil
                                      23
                                      47
                                      18
                                      19
                                      19
Natural Gas
                                     1,228
                                     1,156
                                     1,286
                                     1,410
                                     1,552
Nuclear
                                      769
                                      815
                                      779
                                      711
                                      782
Hydroelectric
                                      274
                                      282
                                      288
                                      291
                                      294
Wind
                                      142
                                      251
                                      218
                                      218
                                      219
Other Renewables
                                      48
                                      121
                                      102
                                      133
                                      154
Other
                                      71
                                      -7
                                      65
                                      151
                                      103
Total
                                     4,067
                                     4,199
                                     4,402
                                     4,622
                                     4,815
Source: Historical data from Form EIA-860, 2012.  EPA 2020 projection from IPM 5.14 base case; EIA 2020-2030 projection from EIA Annual Energy Outlook 2014, Tables A8 and A16
Notes: The sum of the table values in each column may not match the total figure due to rounding.  "Other Renewables" include biomass, geothermal, waste and solar electric generation capacity.  "Other" includes pumped storage (net loss, non-biogenic waste, batteries, hydrogen, and other misc. generation and storage technologies. Negative value reflects net energy loss from pumped storage.
It has been previously noted that since the time of the original 2012 proposed new source rule, projections for key market variables are now even less favorable to the development of coal-fired capacity.  State and regional regulations have necessarily evolved since the AEO 2010 and the EPA's modeling projections for the 2012 proposal, most notably regulations of GHG emissions from the power sector and state renewable portfolio standards (RPS):
         * State regulations addressing CO2 emissions  -  Several states have adopted measures to address emissions of CO2 from the power sector.  These approaches include flexible market-based programs like California's Assembly Bill 32 and the RGGI in the Northeast, and specific GHG performance standards for new power plants in California, Oregon, New York, and Washington.
         * State Renewable Portfolio Standards (RPS)  -  According to EIA, 30 states and the District of Columbia have an enforceable RPS, or similar laws.  There are eight other States that have voluntary goals.  These measures, in conjunction with Federal financial incentives, are key drivers of the significant growth in new renewable energy seen over the past few years and expected over the next decade.
         * State and Utility IRPs  -  IRPs, which are usually adopted by utilities in response to state requirements, allow regulators and utilities to consider a broader array of measures to meet future electric demand most cost effectively.  IRPs also help electric planners to consider key strategic and policy goals like electric reliability, environmental impacts, and the economic efficiency of power sector investments. In general, these plans confirm the expectation that utilities anticipate that any new sources of generation will be from renewables, in response to state and federal regulations and incentives, and natural gas prices.  Furthermore, these plans reflect an expectation of relatively low demand growth due, in part, to policies and regulations to reduce the electricity consumption such as energy efficiency regulations and policies, evolution of the Smart Grid, and demand response measures.
4.4.2	Alternative Scenarios from AEO 2014
In addition to EPA's own analysis, EPA reviewed EIA's recent forecasts of new capacity in the electricity sector for the AEO 2014, which uses the National Energy Market System (NEMS) model. The AEO 2014 reference case forecasts no new coal that would not comply with the final new source standards. Furthermore, the reference case projects a capacity factor for CTs of less than 20% in all regions and in all years.  Furthermore, power sector modeling by EIA projects no new coal-fired capacity in the analysis period have been demonstrated to be robust under a range of alternative assumptions that influence the industry's decisions to build new power plants.  For example, EIA typically supplements the AEO with scenarios that explore key market, technical, and regulatory issues.  Of the 31 scenarios contained in the AEO 2014, none project new coal-fired capacity in the analysis period, including the four scenarios that may be considered most favorable to the development of coal-fired capacity displayed in Table 4-3.

Table 4-3.	AEO 2014 Reference and Alternative Scenario Forecasts of Unplanned Cumulative Capacity Additions by 2020, GW
                                 Capacity Type
                                   Reference
                                  High Growth
                                 Low Coal Cost
                          Low Gas & Oil Resource
                                No GHG Concern
Conventional Coal
                                       0
                                       0
                                       0
                                       0
                                       0
Coal with CCS
                                      0.3
                                      0.3
                                      0.3
                                      0.3
                                      0.3
Natural Gas
                                     23.9
                                     34.4
                                     19.8
                                     16.3
                                     22.7
Nuclear
                                       0
                                       0
                                      0.0
                                      2.5
                                      0.0
Non-Hydro Renewables
                                     17.4
                                     19.7
                                     17.6
                                     23.7
                                     17.5
Other
                                      1.6
                                      2.0
                                      1.5
                                      0.8
                                      1.6
Total
                                     43.2
                                     56.5
                                     39.3
                                     43.6
                                     42.1

4.4.3	Power Sector Fuel Price Dynamics and Trends
As mature technologies, the cost and performance characteristics of conventional coal-fired capacity and NGCC are projected by EPA to be relatively stable over time in comparison to emerging generation technologies.  Therefore, expectations of future fuel prices play a key role in determining the overall cost competitiveness of conventional coal-fired units versus NGCC units.
Current and projected natural gas prices are considerably lower than observed prices over the past decade.  This is largely due to advances in hydraulic fracturing and horizontal drilling techniques that have opened up new shale gas resources and substantially increased the supply of economically recoverable natural gas. According to EIA:
      Shale gas refers to natural gas that is trapped within shale formations. Shales are fine-grained sedimentary rocks that can be rich sources of petroleum and natural gas. Over the past decade, the combination of horizontal drilling and hydraulic fracturing has allowed access to large volumes of shale gas that were previously uneconomical to produce. The production of natural gas from shale formations has rejuvenated the natural gas industry in the United States.
      Of the natural gas consumed in the United States in 2011, about 95% was produced domestically; thus, the supply of natural gas is not as dependent on foreign producers as is the supply of crude oil, and the delivery system is less subject to interruption. The availability of large quantities of shale gas should enable the United States to consume a predominantly domestic supply of gas for many years and produce more natural gas than it consumes.
The AEO 2014 projects U.S. natural gas production will increase by 13.3 trillion cubic feet (Tcf), a 55% increase (from 24.3 Tcf in 2014 to 37.5 Tcf in 2040). Over 75% of this forecasted increase in domestic natural gas production is due the projected doubling of shale gas production, which is forecast to increase by 10.2 TCF (from 9.6 TCF in 2014 to 19.8 TCF in 2040).
 Recent historical data reported to EIA is also consistent with these trends, with 2014 being the highest year on record for domestic natural gas production. Gas production in 2014 was 6.3% above production in 2013, which is the largest annual growth rate since 1984.  The average real (2011$) delivered natural gas price delivered to the power sector was $4.39 per MMBtu in 2014, an increase from $4.25/MMBtu in 2013.
Increases in the natural gas resource base have led to fundamental changes in the outlook for natural gas.  While sources may disagree on the absolute level of increases from shale resources, there is general agreement that recoverable natural gas resources will be substantially higher for the foreseeable future than previously anticipated, exerting downward pressure on natural gas prices.[,]  Modeling by the EPA and EIA incorporates the impact of these additional resources on the forecasts of the price of natural gas used by electric generating units.  The increases in the natural gas resource base are reflected not only in current natural gas prices and projections (e.g., AEO 2014), but also in current capacity planning by utilities and electricity producers across the country.  The North American Electric Reliability Corporation's (NERC) Long Term Reliability Assessment, which is based on utility plans for new capacity over a 10-year period, reinforces this consensus by stating that "gas-fired generation [is] the primary choice for new capacity."
EPA's and EIA's modeling frameworks are designed to reflect the longer term, fundamentals-based perspective that electric utilities and developers employ in evaluating capital investments, while utilizing scenario testing to account for broader fuel market uncertainties.  Short-term fuel price volatility is not the most relevant factor in this context because new power plants have asset lives measured in decades, not in months or years, and new capacity investment decisions are based on long-run expected prices, not month-to-month, or even year-to year, variations in fuel prices.  Shorter-term prices will affect how units are dispatched, but these potential dispatch impacts are considered with other factors over a longer time horizon and factored into the choice of which type of plant to build.  In contrast, the uncertainty surrounding long-term fuel prices will exert significantly greater influence on the technology selected for new capacity additions. In a modeling context with perfect foresight, this longer term uncertainty may be evaluated by the scenario testing presented throughout this analysis.
In addition to major changes in the gas supply outlook, there have been notable changes in the coal supply outlook.  Coal costs have generally increased over the past few years due primarily to increased production costs.  These costs have increased as the most accessible and economically viable mines are depleted, requiring movement into coal reserves that are more costly to mine.  The basic trends in coal supply are not expected to change for the foreseeable future.
      Taken together, current and expected natural gas and coal market trends are contributing to a fundamental shift in the economic conditions for new power plant development that utilities and developers have recognized and responded to in planning.
4.4.4	Power Sector Fuel Projections
  To examine the potential impacts of uncertainty inherent in natural gas and coal markets, the EIA used scenario analysis to generate the 2020 fuel price projections in Table 4-4.

Table 4-4.	National Delivered 2020 Fuel Prices by AEO 2014 Scenario (2011$/MMBtu)
                                   Scenario
                                  Natural Gas
                                     Coal
Reference
                                     4.99
                                     2.57
High Growth
                                     5.28
                                     2.59
Low Growth
                                     4.97
                                     2.55
High Coal Cost
                                     5.13
                                     2.90
Low Coal Cost
                                     4.88
                                     2.27
High Gas/Oil Resource
                                     4.30
                                     2.45
Low Gas/Oil Resource
                                     5.63
                                     2.63

	However, given that power plants are long-lived assets, capacity planning decisions are necessarily undertaken with a forward view of expected market and regulatory conditions.  In producing the AEO 2014, EIA capacity expansion projections are informed by a lifecycle cost analysis over a 30-year period in which the expectations of future prices are consistent with the projections realized in the model (i.e. the model executes decisions with perfect foresight of future market, technical, and regulatory conditions).  Therefore, the fuel prices that inform capacity expansion decisions in 2020 is not only the prices that year, but the entire future fuel price stream.  For example, Figure 4-2 displays EIA's natural gas price projections for the Reference Case and several key scenarios through 2040.

Figure 4-2.	National Real Price of Natural Gas Delivered to EGUs for Select AEO 2014 Scenarios (2011$/MMBtu)
      Note: The AEO gas price forecasts go through 2040. The AEO forecasted prices are interpolated to 2040 by applying the average annual rate of price increase from 2035 to 2040 in each AEO scenario to all subsequent years from 2041 through 2049.

	 Natural gas prices are expected to increase after 2020 in all scenarios; however, rising natural gas prices through 2040  -  including in EIA's low gas/oil resource scenario - are still not sufficient to support new, non-compliant coal-fired generation in the analysis period (i.e., through 2022), demonstrating that natural gas prices at currently low levels are not required to persist for NGCC to maintain its economic advantage over coal-fired technologies.
While the uniformity of EIA scenarios in projecting no new non-compliant coal-fired capacity through the analysis period is compelling, the scenario projections cannot fully illustrate the extent of the economic advantage that NGCC maintains over conventional coal  -  only that the advantage remains intact across a broad range of market and technical scenarios.  To identify potential market conditions that could fully erode the private cost advantages of NGCC over coal-fired technologies during the analysis period, the following section adopts a static, engineering cost analysis.
4.5	Levelized Cost of Electricity Analysis
New capacity projections from the EPA and EIA reviewed in the previous section indicate that the NSPS is not projected to require changes in the design or construction of new EGUs from what would be expected in the absence of the rule.  Thus, under both the baseline projections and alternative scenarios analyzed in AEO 2014, the proposed EGU New Source GHG Standards are not projected to result in any emission reductions, monetized benefits, or costs.
To further examine the robustness of these conclusions the EPA conducted additional analysis using the levelized cost of electricity (LCOE) for different types of new generation technologies.  The LCOE is a widely used metric that represents the cost, in dollars per output, of building and operating a generating facility over the entirety of its economic life.  Evaluating competitiveness on the basis of the LCOE is particularly useful in establishing cost comparisons between generation types with similar operating characteristics but with different cost and financial characteristics.  The typical cost components associated with the LCOE include capital, fixed operating and maintenance (FOM), variable operating and maintenance (VOM), and fuel.
4.5.1	Overview of the Concept of Levelized Cost of Electricity
The levelized capital and FOM costs may be calculated by taking the annualized capital and FOM (expressed in $/kW-yr) costs and spreading the expense over the annual generation of the facility using the expected average annual capacity factor (the percent of full load at which a unit would produce its actual annual generation if it operated for 8760 hours). The annualized capital cost (expressed in $/kw-yr) is the product of the $/kW capital cost and the capital recovery factor (CRF).  A CRF may be calculated using the project's interest rate (i) and book life (n).
The VOM cost, which is already expressed in terms of cost per unit output, may be presented with or without the fuel expense.  The fuel expense is typically the largest component of VOM costs (non-fuel components to VOM include start-up fuel, consumables, inspections, etc.) and for certain capacity types  -  such as NGCC  -  fuel expense may represent the majority of the LCOE.
Because levelized costs consider the entire lifecycle of the facility, fuel expenses are represented by the levelized fuel price which captures the forecast of annual delivered fuel prices over the economic life of the facility at a given discount rate.  Levelizing fuel prices recognizes the necessity to consider the trajectory of fuel costs over the facility's entire economic life.
It should be noted that there are other important considerations beyond the LCOE that impact power plant investment decisions.  New power plant developers must consider the particular demand characteristics in any particular region, the existing mix of generators, operational flexibility of different types of generation, prevailing and expected electricity prices, other potential revenue opportunities (e.g., the capacity value of a particular unit, where certain power markets have mechanisms to compensate units for availability to maintain reliability, sale of co-products, etc.), and the varying financial risks associated with different generation technologies.  Broader system-wide power sector modeling  -  such as the analyses conducted by the EPA and EIA  -  is able to more effectively capture some of these considerations.
4.5.2	Cost and Performance of Technologies
The NGCC and coal-fired generation technology cost and performance assumptions that form the basis for the LCOE analysis in this chapter are from the DOE's National Energy Technology Laboratory (NETL).  NETL cost and performance characteristics were selected for coal-fired technologies because the NETL estimates were unique in the detail of their cost and performance estimates for a range of CO2 capture levels for both new super critical pulverized coal (SCPC) and integrated gasification combined cycle (IGCC) facilities.[,] The CO2 capture sensitivity analysis included an evaluation of the cost, performance, and environmental profile of these facilities under different configurations that were tailored to achieve a specific level of carbon capture.  The EPA selected NETL cost and performance characteristics for NGCC to ensure that the cost comparisons between NGCC and coal-fired technologies  -  the primary comparison made in this chapter  -  was based on a single, internally consistent framework.  For technologies where NETL cost and performance estimates were not available or sufficiently recent  -  such as for nuclear and simple cycle CT  -  EPA adopted EIA's AEO 2014 estimates of the LCOE.
To represent a new SCPC facility, NETL assumed a new boiler with a combination of low-NOx burners with overfire air and a selective catalytic reduction system for NOx control. The plant was assumed to have a fabric filter and a wet limestone flue gas desulfurization scrubber for particulate matter and SO2 control, respectively. For configurations including CCS, the plant was assumed to have a sodium hydroxide polishing scrubber to ensure that the flue gas entering the CO2 capture system has a SO2 concentration of 10 ppmv or less. The SCPC with CCS plant configurations were assumed to be equipped with Fluor's Econamine FG Plus[SM] process for post-combustion CO2 capture via temperature swing absorption with a monoethanolamine (MEA) solution as the chemical solvent.
Specific to the partial capture configurations for SCPC, the NETL study identified two options. The first option identified was to process the entire flue gas stream through the MEA capture system, but at reduced solvent circulation rates. The second option was to maintain the same high solvent circulation rate and stripping steam requirement as would be used for full capture, but only treat a portion of the total flue gas stream. The NETL report determined that this "slip stream" approach was the most economical because a reduction in flue gas flow rate will: (1) decrease the quantity of energy consumed by flue gas blowers; (2) reduce the size of the CO2 absorption columns; and (3) trim the cooling water requirement of the direct contact cooling system. The "slip stream" approach  -  which leads to lower capital and operating costs  -  was therefore adopted by the EPA for cost and performance estimates under partial capture.
For a new IGCC EGU, the NETL study evaluated a number of IGCC plant configurations. EPA adopted the configurations presented as the most viable  -  from both an economic and technological perspective  -  for the no capture, partial capture and full capture cases. The no CO2 capture case employed an IGCC that used the two-stage acid gas (Selexol(TM)) process for acid gas control (i.e., hydrogen sulfide and CO2) but no water-gas shift reactor. The 25 percent CO2 capture case utilized the same two-stage Selexol(TM) unit to maximize CO2 capture from the unshifted syngas.  To achieve higher CO2 capture levels  -  including full capture - the IGCC was assumed to be configured with a two-stage water-gas shift reaction with bypass and the two-stage acid gas (Selexol(TM)) scrubbing system.  In summary, the technology cost and performance characteristics utilized by the EPA in developing the LCOE estimates discussed in this chapter and Chapter 5 are listed below in Table 4-5.
Table 4-5.	Technology Cost and Performance Specifications (2011$)
                                 Capacity Type
                      Total Overnight Capital Cost ($/kw)
                 Fixed Operations & Maintenance ($/kw-yr)
                 Variable Operations & Maintenance ($/MWh)
                         Levelized Fuel Cost ($/MMBtu)
                         Net Plant HHV Efficiency (%)
NGCC
                                      891
                                     31.4
                                      1.8
                                     6.07
                                     51.1
SCPC
                                     2,452
                                     83.0
                                      7.7
                                     2.80
                                     39.3
SCPC w/ Partial CCS
(1,400 lbs/MWh gross)
                                     2,876
                                     94.9
                                      8.9
                                     2.80
                                     36.9
IGCC
                                     2,969
                                     81.8
                                      9.3
                                     2.80
                                     39.0
IGCC w/ Partial CCS
(1,400 lbs/MWh gross)
                                     3,419
                                     112.5
                                      9.4
                                     2.80
                                     38.8
Notes: The coal assumed is a bituminous coal with a sulfur content of 2.8% (dry) at a real (2011$) price of $2.80/MMBtu, consistent with AEO 2014 Reference Case forecast levelized delivered coal (all types) price.  The natural gas price is the EIA AEO 2014 forecast levelized real (2011$) delivered gas price from EIA's AEO 2014 Reference Case.  NETL (2013) explains that there are a range of future potential costs that are up to 15% below, or 30% above their central estimate, consistent with a "feasibility study" level of design engineering applied to the various cases in this study. The value of the studies lie not in the absolute accuracy of the individual case results but in the fact that all cases were evaluated under the same set of technical and economic assumptions. This consistency of approach allows meaningful comparisons among the cases evaluated.

4.5.3	Levelized Cost of Electricity of New Generation Technologies
To support and provide context for the sectoral modeling results presented above, this section presents two LCOE comparisons:
      1. NGCC to Uncontrolled Coal  -  to demonstrate the cost advantages of NGCC across a range of natural gas prices and regional market conditions.
      2. NGCC to CT  -  to demonstrate the low likelihood of a new combustion turbine being built with the expectation of meeting the applicability criteria based on utilization and thus being covered by this proposal.
The illustrative unit cost and performance characteristics used in this section assume representative costs associated with spatially dependent components, such as connecting to existing fuel delivery infrastructure and the transmission grid. In practice units may experience higher or lower costs for these components depending on where they are located.  It should be noted that the LCOE comparisons presented in this section only represent the cost to the generator and do not reflect the additional social costs that are associated with emissions of greenhouse gases or other air pollutants.  A broader consideration of the health and welfare impacts of emissions from these technologies is considered in Chapter 5.
 It is also important to note that both the EIA and EPA apply a climate uncertainty adder (CUA) - represented by a three percent increase to the weighted average cost of capital  -  to new, conventional coal-fired capacity types.  EIA developed the CUA to address differences in how investments in new capacity are evaluated in power sector models as compared to resource planning exercises commonly conducted by the industry.  While baseline power sector modeling scenarios may not specify potential future GHG regulatory requirements, investors in the industry typically incorporate some expectation of a future cost to limit CO2 emissions in resource planning evaluations that influence investment decisions.   Therefore, the CUA reflects the additional risk typically assigned by project developers and utilities to GHG-intensive projects in a context of climate uncertainty.  When comparing ex-ante private investment costs, the EPA believes the inclusion of the CUA in LCOE estimates is consistent with the industry's current planning and evaluation framework for future projects (demonstrable through IRPs and public utility commission orders) and is therefore necessary to adopt in evaluating potential investment behavior in light of the cost competitiveness of alternative generating technologies.
In defining the CUA, EIA states that "the adjustment should not be seen as an increase in the actual cost of financing, but rather as representing the implicit hurdle being added to GHG-intensive projects to account for the possibility they may eventually have to purchase allowances or invest in other GHG emission-reducing projects that offset their emissions." Therefore, the EPA recognizes the application of the CUA is context dependent  -  as a part of the planning process it is appropriately applied in an evaluative sense to prospective projects, and then removed once a project transitions from planning to execution.  While omitting the CUA is inconsistent with an analysis considering how project characteristics and market conditions would lead a developer or utility to select a certain project, as is the purpose of this section, for transparency the LCOE estimates for uncontrolled coal-fired projects are presented both with and without the CUA.  All LCOE estimates of coal-fired facilities with CCS (partial or full) are presented without the CUA, to represent the reduced CO2 liability associated with such technologies.
4.5.4	Levelized Cost of Electricity of NGCC and Uncontrolled Coal
The EPA's base LCOE estimates for NGCC, SCPC, and IGCC are displayed in Figure 4-3 by cost component (capital, FOM, VOM, TS&M and fuel) and assume a construction date of 2020. Although the EPA believes that this cost data is broadly representative of the economics between new coal and new natural gas facilities, this analysis assumes representative new units and does not reflect the full array of new generating sources that could potentially be built.  To the extent that other types of new units that would be affected by this rule are built, they may exhibit different costs than those presented here.  For example, new conventional coal facilities of a size smaller than what is assumed in the base estimate would tend to exhibit a relatively higher LCOE, while some technologies could potentially display a lower LCOE if  -  all else equal - fuel could be obtained at a lower price than that assumed in this analysis (such as may be the case for petroleum coke or waste coal facilities).  These potential differences do not fundamentally change the analysis presented in this chapter.
On a levelized cost basis, NGCC is significantly cheaper than all of the uncontrolled coal-fired options.  In addition to the disparity in LCOE totals, the cost composition exhibits fundamental differences between natural gas- and coal-fired facilities, with NGCC dominated by fuel expense and the levelized cost of coal-fired technologies driven by capital expense.  Consequently, this section will explore the impact of changes in natural gas price and the capital costs of coal-fired facilities to better quantify the magnitude of the relative cost advantage NGCC exhibits over coal-fired alternatives.

Figure 4-3.	Illustrative Wholesale Levelized Cost of Electricity of Alternative New Generation Technologies by Cost Component
      Notes:
      (1) The coal assumed is a bituminous coal with a sulfur content of 2.8% (dry) and a real delivered price of $2.80/MMBtu. $2.80/MMBtu is the levelized real (2011$) delivered average coal price from the AEO 2014 reference case for all coals during the 20 year forecast period 2020-2039. The $2.80/MMBtu coal price is assumed for all years; therefore, the price serves as both the 2020 fuel cost as well as the levelized fuel cost over any future period of time.
      (2) The levelized delivered price of natural gas is $6.07/MMBtu (2011$).This price is the levelized real (2011$) delivered gas price from the AEO 2014 reference during the 20 year forecast period 2020-2039.
      (3) A 3% climate uncertainty adder (CUA) is added to the SCPC without any CCS control. The CUA is not added to the SCPC with partial control, nor to the two IGCC alternatives.
      (4) The cost of CO2 transport, storage and monitoring (TS&M) is included as part of LCOE for the two alternatives capturing CO2.
      (5) The gross CO2 emission rates for these illustrative new generation technologies are: NGCC = 778 lbs/MMBtu; SCPC (no CCS) = 1,677 lbs/MMBtu; SCPC with CCS on 22% of emission stream = 1,400 lbs/MMBtu; IGCC (no CCS) = 1,434 lbs/MMBtu; IGCC with CCS on 2.8% of emission stream = 1,400 lbs/MMBtu.
      (6) A capacity factor of 85 percent is assumed across all technologies.
      (7) For comparison, EIA estimates levelized costs under AEO 2013 assumptions for SCPC and IGCC are $99/MWh and $122/MWh, respectively, including a 3% CUA and excluding transmission investment costs. The levelized costs presented above are based on NETL assumptions and will necessarily differ from AEO 2014 levelized costs for a variety of reasons, including cost and performance characteristics, financial assumptions, and fuel input prices.
The figure below presents the LCOE of an NGCC facility at three levelized natural gas price levels.  For reference, the base LCOE estimates for SCPC and IGCC (with no CO2 control) are included as well.

Figure 4-4.	Illustrative Wholesale Levelized Cost of Electricity of Alternative New Generation Technologies Across Select Natural Gas Prices

It is only when natural gas prices exceed $10/MMBtu on a levelized basis (in 2011$) that new coal-fired generation without CCS approaches parity with NGCC in terms of the LCOE (none of the EPA sensitivities or AEO 2014 scenarios described in this chapter project national average natural gas prices near that level).   To achieve a $10/MMBtu levelized price in 2020 would require a significantly more pessimistic natural gas outlook than what is contained in AEO's low natural gas resource scenario.  To illustrate, Table 4-6 report the levelized natural gas prices (initial year of 2020) for both a 20-year period (to accommodate the end of EIA's modeling projections in 2040) and 30-year period (calculated by continuing the projected level of price increases through 2050).

Table 4-6.	Levelized Natural Gas Prices by Select AEO 2014 Scenario (2011$/MMBtu)
                                   Scenario
                            20-Year AEO Projection
                                  (2020-2039)
                         30-Year AEO-Based Projection
                                  (2020-2049)
Reference
                                     6.07
                                     6.53
High Growth
                                     6.32
                                     6.96
Low Growth
                                     5.78
                                     6.20
High Coal Cost
                                     6.19
                                     6.69
Low Coal Cost
                                     6.03
                                     6.47
High Gas/Oil Resource
                                     4.80
                                     4.85
Low Gas/Oil Resource
                                     7.70
                                     8.45
            Note: Discount rate of 5%, consistent with IPM assumptions.  The 30-year natural gas price is calculated by applying the average annual rate of price increase from 2035 to 2040 in all subsequent years from 2041 through 2049.
One potential price path that would achieve a $10/MMBtu on a 20-year levelized basis in 2020 is a natural gas price path 30% higher than EIA's low resource scenario in all years; see Figure 4-5 below.  This illustrative price path to achieve a $10/MMBtu levelized price would result in a $11.02/MMBtu annual real price in 2030 and a $13.81/MMBtu real price in 2040.

Figure 4-5.	Projected Real National Delivered Natural Gas Price for Select AEO 2014 Scenarios and Illustrative Path for > $10/MMBtu Levelized Cost

It is important to note that the LCOE calculations are based on assumptions regarding the average national cost of generation at new facilities.  It is known that there is significant spatial variation in the costs of new generation due to design differences, labor productivity and wage differences, and delivered fuel prices, among other potential factors.
For example, EIA utilizes capital cost scalars to capture regional differences in labor, material and construction costs.  The minimum and maximum capital cost scalars across all regions in AEO 2014 for SCPC, IGCC, and NGCC build options are presented below in Table 4-7:
Table 4-7.	AEO 2014 Regional Capital Cost Scalars by Capacity Type
                                 Capacity Type
                          Minimum Capital Cost Scalar
                          Maximum Capital Cost Scalar
SCPC
                                     0.885
                                     1.152
IGCC
                                     0.908
                                     1.136
NGCC
                                     0.893
                                     1.205
	Applying the regional capital cost scalars displayed above to the base LCOE estimates developed earlier in this section produces only a small change in the relative competitiveness of the technologies as seen in Table 4-8.
Table 4-8.	LCOE Estimates with Minimum and Maximum AEO 2014 Regional Capital Cost Scalars (2011$/MWh)
                                 Capacity Type
                                  Reference
                                     LCOE
                          Minimum Capital Cost Scalar
                          Maximum Capital Cost Scalar
SCPC (no CCS, with CUA)
                                      91
                                      81
                                      105
IGCC (no CCS, without CUA)
                                      96
                                      87
                                      109
NGCC
                                      59
                                      53
                                      71
	The LCOE of SCPC in the lowest capital cost region still results in an LCOE that is 13% higher than an NGCC located in the most expensive capital cost region.  The IGCC LCOE is 22% above NGCC in the most expensive region.
The other primary driver in determining the regional impact on competitiveness of new build options is delivered fuel prices.  As part of the AEO, EIA releases electric power projections  -  including fuel prices  -  for each of the 22 Electricity Market Module (EMM) regions.  The two regions with the highest projected 2020 natural gas prices in the AEO 2014 are the Western Electricity Coordinating Council/Southwest (`Southwest') and the Florida Reliability Coordinating Council (FRCC).  The 20-year levelized natural gas and coal price forecasts (2020-2039) in the AEO 2014 reference case are displayed in Figure 4-6 for both regions.

Figure 4-6.	Levelized Regional Fuel Price from AEO 2014 Reference Case, 2020-2039 			(2011$/MMBtu)
While the FRCC region experiences the highest overall natural gas prices, the Southwest region realizes a greater $/MMBtu differential between coal and natural gas prices under the AEO projections; the impact on the LCOE of the SCPC, IGCC, and NGCC technologies without CCS is reported in Table 4-9 for both sets of fuel prices, as well as the national average for comparison.
Table 4-9.	LCOE Estimates For Minimum and Maximum AEO 2014 Regional Capital Cost 			Scalars (2011$/MWh)
                                 Capacity Type
                         National Average Fuel Prices
                               FRCC Fuel Prices
                             Southwest Fuel Prices
SCPC (w/ 3% CUA)
                                      91
                                      98
                                      88
IGCC (No CUA)
                                      96
                                      104
                                      93
NGCC
                                      59
                                      87
                                      70
Due to the greater fuel price differential, the more favorable region for the development of coal-fired facilities from an LCOE perspective is the Southwest, where the regional fuel prices reduce the LCOE advantage of NGCC to $28/MWh over SCPC (compared with a $32 advantage with national fuel prices) and $23/MWh over IGCC (compared with a $37 advantage with national fuel prices.
In conclusion, even the most favorable combination of regional variability in capital costs and delivered fuel prices represented by EIA are insufficient to support new, unplanned, conventional coal-fired capacity in the analysis period.

4.5.7	Levelized Cost of Simple Cycle Combustion Turbine and Natural Gas Combined Cycle
Simple Cycle Combustion Turbines (CTs) fulfill a fundamentally different function in power sector operations than that of NGCC and fossil-fired steam facilities.  CTs are designed to start quickly in order to meet demand for electricity during peak operating periods and are generally less expensive to build (on a capital cost basis) but are also less fuel efficient than combined cycle technology, (which employs heat recovery systems).  Due to lower fuel efficiencies, CTs produce a significantly higher cost of electricity (cost per kWh) at higher capacity factors and consequently are typically utilized at levels below the applicability requirements for sources affected by the EGU New Source GHG Standards.  Specifically, the final emission standards do not apply to stationary combustion turbines subject to a federally enforceable permit condition limiting annual electric sales to the specific design efficiency of the combustion turbine multiplied by the unit's potential electric output or less. New CTs are expected to most often be built to ensure reserve margins are met during peak periods (typically in the summer), and in some instances be able to generate additional revenues by selling capacity into power markets.  Thus, in practice, EPA expects that potential CT units would not meet the applicability requirements finalized in this rule and would therefore, not be subject to the standards of performance.
To illustrate the economic incentives of utilizing combustion turbines in an intermediate and base load mode of operation, Figure 4-7 presents the LCOE estimates for a new CT, Advanced CT and NGCC at increasing capacity factors.  The estimates utilize the AEO 2014 Reference Case levelized natural gas price for 2020.

Figure 4-7.	Levelized Cost of Electricity Across a Range of Capacity Factors, CT and NGCC 			(2011$/MWh at $6.07/MMBtu Levelized Natural Gas Price)
	In the LCOE figure above, utilizing a CT for generation is less expensive than an NGCC unit only at capacity factors of less than 20%.  If expected utilization is greater than 20%, it can reasonably be expected that a utility or developer would seek to deploy NGCC over CT for a host of economic, environmental, and technical reasons.  Furthermore, the design net efficiencies for currently available potentially impacted aeroderivative simple cycle combustion turbines range from approximately 32 percent for smaller designs to 39 percent for the largest intercooled designs. The efficiencies of industrial frame units range from 30 percent for smaller designs to 36 percent for the largest units. The EPA therefore does not expect new CT units to be constructed, which would meet the applicability requirements.
4.8	Macroeconomic and Employment Impacts
These final EGU New Source GHG Standards are not anticipated to change GHG emissions for newly constructed electric generating units, and are anticipated to impose negligible costs or monetized benefits.  EPA typically impacts on employment or labor markets associated with rules based on the estimated compliance costs and other energy impacts, which serve as an input to such analyses.  However, since the EPA does not forecast a change in behavior relative to the baseline in response to this rule, there are no notable macroeconomic or employment impacts expected as a result of this rule.
4.9	References
Dixit, Avinash and Pindyck, Robert. Investment Under Uncertainty. 1994. Princeton University Press.
Fann, N., K.R. Baker, C.M. Fulcher. 2012. Characterizing the PM2.5-related health benefits of emission reductions for 17 industrial, area and mobile emission sectors across the U.S. Environment International, Volume 49, 15 November 2012, Pages 141-151, ISSN 0160-4120, http://dx.doi.org/10.1016/j.envint.2012.08.017.
Joskow, P.L. 2010. Comparing the Cost of Intermittent and Dispatchable Electricity Generating Technologies. MIT Center for Energy and Environmental Policy Research Working Paper 10-013.
P.L. Joskow. 2011. Comparing the Costs of Intermittent and Dispatchable Electricity Generating Technologies. American Economic Review. vol. 101:238-41.
Krewski, D., R.T. Burnett, M.S. Goldbert, K. Hoover, J. Siemiatycki, M. Jerrett, M. Abrahamowicz, and W.H. White. 2009. "Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and Mortality." Special Report to the Health Effects Institute. Cambridge, MA. July.
Lepeule, J., F. Laden, D. Dockery, and J. Schwartz. 2012. "Chronic Exposure to Fine Particles and Mortality: An Extended Follow-Up of the Harvard Six Cities Study from 1974 to 2009." Environ Health Perspect. In press. Available at: http://dx.doi.org/10.1289/ehp.1104660.
Malik, N.S. 2010, November 1. NextEra CEO sees clean energy standards replacing recent climate proposals [Radio transcript]. Dow Jones News [Online]. Available: Dow Jones Interactive Directory: Publications Library.
Mufson, S. 2011, January 2. Coal's burnout. The Washington Post. Retrieved from
      http://www.washingtonpost.com/newssearch.

Muller, N.Z., R. Mendelsohn, and W. Nordhaus. 2011. Environmental Accounting for Pollution in the United States Economy. American Economic Review. 101:1649-1675.
National Energy Technology Laboratory (NETL). Cost and Performance of PC and IGCC Plants for a Range of Carbon Dioxide Capture. Revised Sept. 16, 2013. Available online at: http://www.netl.doe.gov/energy-analyses/pubs/Gerdes-08022011.pdf.
Rosenberg, M. 2011, September/October. "The Reign of Cheap Gas." EnergyBiz Magazine. Retrieved from http://www.energybiz.com/magazine/article/234577/reign-cheap-gas.
Tong, S. 2010, November 1. Placing Bets on Clean Energy. [Radio transcript]. American Public Media: Marketplace [Online]. Available: Marketplace Programs on Demand.
National Petroleum Council. 2011. Prudent Development: Realizing the Potential of North America's Abundant Natural Gas and Oil Resources. Available online at: http://www.npc.org/reports/rd.html.
National Research of Council (NRC). 2009. Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use. National Academies Press: Washington, D.C.
Trigeorgis, Lenos. Real Options: Managerial Flexibility and Strategy in Resource Allocation. 1996. The MIT Press.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2010. 2010. Available online at: http://www.eia.gov/oiaf/archive/aeo10/index.html.
U.S. Energy Information Administration (U.S. EIA). Annual Energy Outlook 2013. 2013. Available online at: http://www.eia.gov/forecasts/aeo/.
U.S. Environmental Protection Agency (U.S. EPA). 2008. Integrated Science Assessment for Oxides of Nitrogen and Sulfur  - Ecological Criteria National (Final Report). National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-08/139. December. Available on the Internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485.
U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for Environmental Assessment  -  RTP Division. December. Available on the Internet at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546.