21,771
                                    ARIZONA
                                      143
                                    1,290
                                   ARKANSAS
                                     6,812
                                    70,184
                                  CALIFORNIA
                                    37,357
                                   463,665
                                   COLORADO
                                    41,458
                                   393,734
                                  CONNECTICUT
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                   DELAWARE
                                      44
                                      44
                             DISTRICT OF COLUMBIA
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                    FLORIDA
                                    113,251
                                   611,793
                                    GEORGIA
                                    160,210
                                   175,322
                                    HAWAII
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                     IDAHO
                                      44
                                     430
                                   ILLINOIS
                                    11,045
                                   128,772
                                    INDIANA
                                    35,296
                                    75,189
                                     IOWA
                                      11
                                      55
                                    KANSAS
                                    11,993
                                    95,173
                                   KENTUCKY
                                     3,219
                                    8,433
                                   LOUISIANA
                                    186,842
                                  2,319,238
                                     MAINE
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                   MARYLAND
                                     2,050
                                    2,127
                                 MASSACHUSETTS
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
(Continued on next page)

Table 2-8. 	Total CO2 Storage Resource (DOE-NETL), cont.

                                 Million Tons*
                                     State
                                 Low Estimate
                                 High Estimate
                                   MICHIGAN
                                    20,999
                                    52,040
                                   MINNESOTA
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                  MISSISSIPPI
                                    159,846
                                  1,306,270
                                   MISSOURI
                                      11
                                     187
                                    MONTANA
                                    93,233
                                  1,006,100
                                   NEBRASKA
                                    26,202
                                   124,826
                                    NEVADA
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                 NEW HAMPSHIRE
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                  NEW JERSEY
                                       0
                                     0
                                  NEW MEXICO
                                    47,135
                                   395,828
                                   NEW YORK
                                     5,115
                                    5,115
                                NORTH CAROLINA
                                     1,477
                                    20,271
                                 NORTH DAKOTA
                                    73,954
                                   162,569
                             Offshore Federal Only
                                    539,956
                                  7,098,976
                                     OHIO
                                    14,837
                                    14,837
                                   OKLAHOMA
                                    62,777
                                   269,570
                                    OREGON
                                     7,507
                                   103,286
                                 PENNSYLVANIA
                                    24,361
                                    24,361
                                 RHODE ISLAND
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                SOUTH CAROLINA
                                    33,180
                                    37,677
                                 SOUTH DAKOTA
                                     9,656
                                    26,489
                                   TENNESSEE
                                      474
                                    4,255
                                     TEXAS
                                    489,205
                                  4,772,925
                                     UTAH
                                    28,076
                                   265,558
                                    VERMONT
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                   VIRGINIA
                                      485
                                    3,208
                                  WASHINGTON
                                    40,367
                                   547,550
                                 WEST VIRGINIA
                                    18,353
                                    18,353
                                   WISCONSIN
                           not assessed by DOE-NETL
                           not assessed by DOE-NETL
                                    WYOMING
                                    80,127
                                   754,917
                                  U.S. Total
                                   2,531,653
                                  22,147,811

* States with a "zero" value represent estimates of minimal CO2 storage resource. States that have not yet been assessed by DOE-NETL have been identified.

2.7.2 	Availability of Geologic Sequestration in Deep Saline Formations
DOE and the United States Geological Survey (USGS) have independently conducted preliminary analyses of the availability and potential CO2 sequestration capacity of deep saline formations in the United States. DOE estimates are compiled by the DOE's NATCARB system using volumetric models and published in a Carbon Utilization and Storage Atlas. DOE estimates that areas of the United States with appropriate geology have a sequestration potential of at least 2,200 billion tons of CO2 in deep saline formations. According to DOE, at least 39 states have geologic characteristics that are amenable to deep saline GS in either onshore or offshore locations. In 2013, the USGS completed its evaluation of the technically accessible GS resources for CO2 in U.S. onshore areas and state waters using probabilistic assessment. The USGS estimates a mean of 3,300 billion tons of subsurface CO2 sequestration potential, including saline and oil and gas reservoirs, across the basins studied in the United States. As shown in Figure 2-21, there are 39 states for which onshore and offshore deep saline formation storage capacity has been identified.
2.7.3	Availability of CO2 Storage via Enhanced Oil Recovery
Although the regulatory impact analysis for this rule relies on GS in deep saline formations, the EPA also recognizes the potential for securely sequestering CO2 via EOR. EOR has been successfully used at numerous production fields throughout the United States to increase oil recovery. The oil industry in the United States has over 40 years of experience with EOR. An oil industry study in 2014 identified more than 125 EOR projects in 98 fields in the United States. More than half of the projects evaluated in the study have been in operation for more than 10 years, and many have been in operation for more than 30 years. This experience provides a strong foundation for demonstrating successful CO2 injection and monitoring technologies, which are needed for safe and secure GS that can be used for deployment of CCS across geographically diverse areas.
Currently, 12 states have active EOR operations and most have developed an extensive CO2 infrastructure, including pipelines, to support the continued operation and growth of EOR. An additional 18 states are within 100 kilometers (62 miles) of current EOR operations (see Figure 2-21).  The vast majority of EOR is conducted in oil reservoirs in the Permian Basin, which extends through southwest Texas and southeast New Mexico. States where EOR is currently used include Alabama, Colorado, Louisiana, Michigan, Mississippi, New Mexico, Oklahoma, Texas, Utah, and Wyoming.
At the project level, the volume of CO2 already injected for EOR and the duration of operations are of similar magnitude to the duration and volume of CO2 expected to be captured from fossil fuel-fired EGUs. The volume of CO2 used in EOR operations can be large  (e.g., 55 million tons of CO2 were stored in the SACROC unit in the Permian Basin over 35 years), and operations at a single oil field may last for decades, injecting into multiple parts of the field.  According to data reported to the EPA's Greenhouse Gas Reporting Program (GHGRP), approximately 66 million tons of CO2 were supplied to EOR in the United States in 2013. Approximately 70 percent of this total CO2 supplied was produced from natural (geologic) CO2 sources, and approximately 30 percent was captured from anthropogenic sources.
A DOE-sponsored study has analyzed the geographic availability of applying EOR in 11 major oil producing regions of the United States and found that there is an opportunity to significantly increase the application of EOR to areas outside of current operations.  DOE-sponsored geologic and engineering analyses show that expanding EOR operations into areas additional to the capacity already identified and applying new methods and techniques over the next 20 years could utilize 20 billion tons of anthropogenic CO2 and increase total oil production by 67 billion barrels. The availability of anthropogenic CO2 in areas outside of current sources could drive new EOR projects by making more CO2 locally available.
2.8	State Policies on GHG and Clean Energy Regulation in the Power Sector
Several states have also established emission performance standards or other measures to limit emissions of GHGs from new EGUs that are comparable to or more stringent than this rulemaking.
In 2003, then-Governor George Pataki sent a letter to his counterparts in the Northeast and Mid-Atlantic inviting them to participate in the development of a regional cap-and-trade program addressing power plant CO2 emissions.  This program, known as the Regional Greenhouse Gas Initiative (RGGI), began in 2009 and sets a regional CO2 cap for participating states.  The currently participating states include: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont.  The cap covers CO2 emissions from all fossil-fired EGUs greater than 25 MW in participating states, and limits total emissions to 91 million tons in 2014. The 2014 emissions cap is a 51 percent reduction below the initial cap in 2009 to 2011 of 188 million tons.  This emissions budget is reduced 2.5 percent annually from 2015 to 2020. RGGI CO2 allowances are sold in a quarterly auction. RGGI conducted their 27[th] quarterly allowance auction in March, 2015 the market clearing price was $5.41 per ton of CO2 for current allowances, which was a record high price (the February '15 price of $5.21 was the previous record).  A total of allowances for 15.3 million tons were sold in the March 2015 auction, well below the record of 38.7 million tons sold in June 2013 for $3.21 per ton.
In September 2006, California Governor Schwarzenegger signed into law Senate Bill 1368. The law limits long-term investments in base load generation by the state's utilities to power plants that meet an emissions performance standard jointly established by the California Energy Commission and the California Public Utilities Commission. The Energy Commission has designed regulations that establish a standard for new and existing base load generation owned by, or under long-term contract to publicly owned utilities, of 1,100 lb CO2/MWh -net.
In 2006, Governor Schwarzenegger also signed into law Assembly Bill 32, the Global Warming Solutions Act of 2006.  This act includes a multi-sector GHG cap-and-trade program which covers approximately 85 percent of the state GHG emissions.  EGUs are included in phase I of the program, which began in 2013.  Phase II begins in 2020 and includes upstream sources.  The cap is based on a 2 percent reduction from total 2012 expected emissions, and declines 2 percent annually through 2014, then 3 percent each year until 2020.  The AB32 cap and trade program began functioning in 2011, and functioning market is now operating on the NYMEX futures commodity market. The final 2014 market price for carbon allowances was $11.23/ton of carbon. On April 17, 2015 the 2015 allowance futures price was $11.48/ton, and the spot price was $11.30/ton.
In May 2007, Washington Governor Gregoire signed Substitute Senate Bill 6001, "Base load Electric Generation Performance" which established statewide GHG emissions reduction goals, and imposed an emission standard that applies to any base load electric generation that commenced operation after June 1, 2008 and is located in Washington, whether or not that generation serves load located within the state. Base load generation facilities must initially comply with an emission limit of 1,100 lb CO2/MWh-net. In 2013 the State of Washington revised the emission limit to 970 lb CO2/MWh-net based on a survey of available NGCC generation units commercially available in the United States.
In 1997, Oregon required a new base load gas fired power plants to meet a CO2 emission standard that was 17 percent below the most efficient NGCC unit operating in the United States.  In 2000 Oregon established that the effective 17 percent below most efficient was 675 lb CO2/MWh-net  In July 2009, Oregon Governor Kulongoski signed Senate Bill 101, which mandated that facilities generating base load electricity, whether gas- or coal-fired, must have emissions equal to or less than 1,100 lb CO2/MWh-net regardless of fuel type, and prohibited utilities from entering into long-term purchase agreements for base load electricity with out-of-state facilities that do not meet that standard. Natural gas- and petroleum distillate-fired facilities that are primarily used to serve peak demand or to integrate energy from renewable resources are specifically exempted from the performance standard.
In August 2011, New York Governor Cuomo signed the Power NY Act of 2011. Implementing regulations established CO2 emission standards for new and modified electric generators greater than 25 MW.  The standards vary based on the type of facility: base load facilities must meet a CO2 standard of 925 lb/MWh-net or 120 lb/MMBtu, and peaking facilities must meet a CO2 standard of 1,450 lb/MWh-net or 160 lb/MMBtu.
Several other states have enacted CO2 regulations affecting EGUs that do not set emission limits, but set other regulatory requirements limiting CO2 emissions from EGUs.  For example, Montana enacted a law in 2007 requiring the Public Service Commission to limit approvals of new equity interests in or leases of a facility used to generate coal-based electricity to facilities that capture and sequester at least half of their CO2 emissions.  Minnesota enacted the Next Generation Energy Act in 2007 requiring increases in power sector greenhouse gas emissions from any new large coal energy facilities built in Minnesota or the import of electricity from such a facility located out of state to be offset by equivalent emission reductions.  New Mexico enacted legislation in 2007 authorizing tax credits and cost recovery incentives for qualifying coal-fired facilities. To qualify, plants must capture and store emissions so that they emit less than 1,100 lb CO2/MWh, among other requirements.
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 29 states, the District of Columbia and Guam have enforceable RPS or other mandatory renewable capacity policies, and 8 states, Puerto Rico and Guam have voluntary goals.  These programs vary widely in structure, enforcement, and scope.
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 four of the past five 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 2002, 2008 and 2012 (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: These data do not include information for public utilities, nor for IPPs.
2.10 	Natural Gas Market
The natural gas market in the United States has historically experienced significant price volatility from year to year and between seasons, 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 to 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/MMBtu.  Adjusting for inflation using the GDP implicit price deflator, in 2011 dollars the annual average price of natural gas delivered to the power sector peaked at $9.38/MMBtu in 2008 and has fallen to a low of $3.36/MMBtu in 2012.  The annual natural gas prices in both nominal and real (2011$) terms are shown in Figure 2-22. A comparison of the trends in the real price of natural gas with the real prices of delivered coal and oil is shown in Figure 2-23. Figure 2-23 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 in the same period.  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 2-22.	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 2-23.	 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 the U.S. Energy Information Administration's Annual Energy Outlook 2012 (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 EIA's AEO 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, there is some uncertainty in estimate of technically recoverable resources, and it 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) of shale gas production, 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 continues to forecast  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. Clean Energy States Alliance (CESA). The State of State Renewable Portfolio Standards. June 2013. Available online at http://www.cesa.org/assets/2013-Files/RPS/State-of-State-RPSs-Report-Final-June-2013.pdfHan, 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.Independent Monitor's Prudency Evaluation Report for the Kemper County IGCC Project. April 15, 2014. Available online at: http://www.psc.state.ms.us/InsiteConnect/InSiteView.aspx?model=INSITE_CONNECT&queue=CTS_ARCHIVEQ&docid=328417.
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 atmospheric CO2 concentrations. This will reduce the risk of adverse effects of climate change. As discussed in Chapter 4, the U.S. Environmental Protection Agency (EPA) anticipates negligible CO2 emission changes resulting from the rule relative to baseline conditions, due to market baseline market conditions. The final standards provide the benefit of regulatory certainty that any new coal-fired power plant must limit its CO2 emissions to a level reflecting the performance of a highly efficient super critical pulverized coal (SCPC) unit utilizing post-combustion partial carbon capture and storage (CCS).  As explained in preamble section V.P.1.b, there are documented instances of project developers abandoning projects using CCS due to this lack of regulatory certainty.  In addition, the history of regulatory actions has shown that emission standards that are based on the performance  of advanced control equipment lead to increased use of that control equipment, and that the absence of a requirement stifles technology development. (See preamble section V.P.1.b.)
This chapter summarizes the adverse effects on public health and public welfare from the emissions of CO2, which is a well-mixed greenhouse gas. This form of air pollution was determined by the EPA in the 2009 Endangerment Finding to endanger public health and welfare. 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 bases for the Endangerment Finding. 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 quantify and monetize the relative differences in emissions between electric generating technologies that may be constructed in the future.
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.  The preamble to the final rule 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 further improved scientific understanding of climate change, and provide even more evidence that GHG emissions endanger public health and welfare for current and future generations. The Third 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." The IPCC reported similar conclusions in its Fifth Assessment Report, finding that it is likely that adverse health impacts related to heat exposure are already being exacerbated by climate change and that, if unabated, climate change will lead to a greater risk of morbidity and mortality due to more intense heat waves, undernutrition, and increased prevalence of food- and water-borne illnesses. 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, improved projections of future warming over the next century, higher projections of future sea level rise than had been previously estimated due in part to improved understanding of the Antarctic and Greenland ice sheets, more detailed description of U.S. impacts based on the National Climate Assessment, improved understanding of changes in rainfall and droughts, 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 analyses in Chapter 5 apply 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 these analyses were developed over many years, using the best science available, and with multiple opportunities for input from the public, which is discussed further below.  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. As noted in the Government Accountability Office's 2014 review, this interagency working group (1) used consensus-based decision-making, (2) relied on existing academic literature and modeling, and (3) took steps to disclose limitations and incorporate new information by considering public comments and revising the estimates as updated research became available.
The SC-CO2 estimates were first released in February 2010 and updated in 2013 using new versions of each IAM.  As discussed further below, the IWG published two minor corrections to the SC-CO2 estimates in July 2015. These estimates are published in the Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 ("current 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 current SC-CO2 TSD for the latest 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.  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 because each country's reductions benefit everyone else and no country can be excluded from enjoying the benefits of other countries' reductions, even if it provides no reductions itself. In this situation, the only way to achieve an economically efficient level of emissions reductions is for countries to cooperate in providing mutually beneficial reductions beyond the level that would be justified only by their own domestic benefits. In reference to the public good nature of mitigation and its role in foreign relations, thirteen prominent academics noted that these "are compelling reasons to focus on a global [SC-CO2]" in a recent article on the SC-CO2 (Pizer et al., 2014). In addition, as noted in OMB's Response to Comments on the SC-CO2, there is no bright line between domestic and global damages. Adverse impacts on other countries can have spillover effects on the United States, particularly in the areas of national security, international trade, public health and humanitarian concerns.

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 SC-CO2 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.
The EPA and other agencies have continued to consider feedback on the SC-CO2 estimates from stakeholders through a range of channels, including public comments on this rulemaking and others that use the SC-CO2 in supporting analyses and through regular interactions with stakeholders and research analysts implementing the SC-CO2 methodology used by the interagency working group. The SC-CO2 comments received on this rulemaking covered a wide range of topics including the technical details of the modeling conducted to develop the SC-CO2 estimates, the aggregation and presentation of the SC-CO2 estimates, and the process by which the SC-CO2 estimates were derived. The EPA Response to Comments document provides a summary and response to the SC-CO2 comments submitted to this rulemaking.
Many of the comments the EPA received in this proceeding mirrored those that OMB received in response to a separate request for public comment on the approach used to develop the estimates and the EPA has carefully considered those comments and responses here.   After careful evaluation of the full range of comments submitted to OMB, the IWG continued to recommend the use of these SC-CO2 estimates in regulatory impact analysis. The IWG remains committed to ensuring that the SC-CO2 estimates continue to reflect the best available scientific and economic information on climate change.  In light of this commitment, the IWG announced plans to obtain expert independent advice from the National Academies of Sciences, Engineering, and Medicine. The Academies process will be informed by the public comments received and focus on the technical merits and challenges of potential approaches to improving the SC-CO2 estimates in future updates.
 OMB also has published a revised TSD that informed our analysis here.  The revision to the TSD is limited to two minor technical corrections to the current estimates. One technical correction addressed an inadvertent omission of climate change damages in the last year of analysis (2300) in one model and the second addressed a minor indexing error in another model. On average the revised recommended SC-CO2 estimates are one dollar less than the mean SC-CO2 estimates reported in the November 2013 revision to the May 2013 TSD. The change in the estimates associated with the 95th percentile estimates when using a 3 percent discount rate is slightly larger, as those estimates are heavily influenced by the results from the model that was affected by the indexing error.
The EPA has examined the minor technical corrections in the revised TSD and the public comments -- including those submitted to OMB's separate SC-CO2 comment process -- here as part of its consideration of whether and how to use SC-CO2 estimates in this proceeding.  Based on this examination, the EPA concurs with the consensus-based interagency working group, of which it is an active member, and finds that it is reasonable, and scientifically appropriate, to use the current SC-CO2 estimates for purposes of analysis here.
The four SC-CO2 estimates the EPA is selecting to use in its analysis here are as follows: $13, $41, $62, and $120 per short ton of CO2 emissions in the year 2022 (2011$).  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 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.	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
                                      $11
                                      $35
                                      $54
                                     $100
                                     2020
                                      $12
                                      $41
                                      $60
                                     $120
                                     2022
                                      $13
                                      $41
                                      $62
                                     $120
                                     2025
                                      $13
                                      $44
                                      $65
                                     $130
                                     2030
                                      $15
                                      $48
                                      $70
                                     $150
                                     2035
                                      $17
                                      $53
                                      $75
                                     $160
                                     2040
                                      $20
                                      $58
                                      $81
                                     $180
                                     2045
                                      $22
                                      $62
                                      $86
                                     $190
                                     2050
                                      $25
                                      $66
                                      $90
                                     $200
[a] These SC-CO2 values are stated in $/short ton and rounded to two significant figures. Unrounded estimates from the current TSD have been converted from $/metric ton to $/short ton using conversion factor 0.90718474 for consistency with this rulemaking and adjusted to 2011$ using the GDP Implicit Price Deflator (1.0613744). This calculation does not change the underlying methodology nor does it change the meaning of the SC-CO2 estimates. For both metric and imperial denominated SC-CO2 estimates, the values vary depending on the year of CO2 emissions and are defined in real terms. The unrounded 2011$ estimates are used in the Chapter 5 illustrative analysis.  The SC-CO2 estimates shown in this table have been rounded to two significant digits.

3.3	Health Co-Benefits of SO2 and NOx Reductions
The EPA anticipates that this rule will result in negligible emission changes over the baseline 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 by coal-fired boilers may also yield sulfur dioxide (SO2) and 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. For example, ambient concentrations of SO2 are associated with respiratory symptoms in children, emergency department visits, and hospitalizations for respiratory conditions.
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).
As described in Chapter 4, the EPA anticipates that this rule will result in no emission changes by 2022. As a result we did not need to perform a full health co-benefit impact assessment for a specific modeled compliance scenario. In Chapter 5, the EPA presents results for several illustrative plant-level analyses that show the potential impacts of the rule if certain key assumptions were to change substantially.  When assessing the co-benefits of differences in emissions from different generation technologies in Chapter 5, the EPA does not assume 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 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 the 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.
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 or directly-emitted PM.  The implications for limiting our consideration of co-benefits to pollutants that cause secondary PM2.5 is discussed in Chapter 5.
As we do not assume a specific location for the new units being compared, this RIA is unable to include the type of detailed uncertainty assessment found in the RIA for the National Ambient Air Quality Standards for Particulate Matter (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 assume 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 four and nine 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 percent discount rate or between $34 million and $76 million (2011$) using a 7 percent discount rate. Additionally, reducing one thousand tons of annual NOX from U.S. EGUs has been estimated to yield up to one 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 percent discount rate or between $5.0 million and $11 million (2011$) using a 7 percent 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, Revised July 2015. 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/inforeg/scc-tsd-final-july-2015.pdf > Accessed July 2, 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.
Intergovernmental Panel on Climate Change (IPCC). 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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.
National Research Council (NRC). 2013. Climate and Social Stress: Implications for Security Analysis. The National Academies Press. Washington, DC.
Pizer, W., M. Adler, J. Aldy, D. Anthoff, M. Cropper, K. Gillingham, M. Greenstone, B. Murray, R. Newell, R. Richels, A. Rowell, S. Waldhoff, J. Wiener. 2014. "Using and improving the social cost of carbon." Science, Vol. 346, No. 6214, 12/05/14, pp 1189-1190.
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.
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 of the New Source Standards
4.1	Synopsis
This chapter reports the compliance cost, economic, and energy impact analyses performed for the final EGU New Source GHG Standards. The U.S. Environmental Protection Agency (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 baseline, all projected unplanned capacity additions affected by these standards 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 carbon capture and storage (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, and
      * Projected new EGUs reported by industry to the U.S. Energy Information Administration (EIA).
The EPA's forecast of no new non-compliant coal-fired capacity remains 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 due to economic conditions.  An additional illustrative analysis, presented in Chapter 5, shows that even in the unlikely event that new, non-compliant EGU capacity would be built, the final EGU New Source GHG Standards would provide net 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) and (ii) natural gas-fired stationary combustion turbines that generate electricity for sale and meet certain applicability criteria.

      The EPA is finalizing standards of performance for affected EGUs within the following two categories: (1) all fossil fuel-fired steam generating units (steam generating units, boilers and integrated gasification combined cycle (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 carbon dioxide (CO2) per megawatt-hour (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.

      Newly constructed natural gas-fired stationary combustion turbines will be required to meet a standard of 1,000 lb CO2/MWh of gross energy output (or 1,030 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 only sell a small portion of the gross electricity generated to the grid ("non-base load units") to not have to meet the same emission standard as a combustion turbine unit designed primarily to generate base and intermediate electricity to be sold to the grid.

       Please refer to the preamble for additional detail concerning affected EGUs 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 the Integrated Planning Model (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 modeling results from a number of alternative baseline scenarios in 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 corroborate the EPA's conclusions in that the forecast no new generation capacity being constructed through the analysis period that would not already meet the final new source standards.  Both the IPM and AEO 2014 NEMS 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 were developed based on data and assumptions used in the EIA's AEO 2013.
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 three 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 nine 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, and 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.  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. 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), the Mercury and Air Toxics Standards (MATS), and the proposed GHG emission guidelines for existing source EGUs.  Recently IPM has also been used to estimate the air pollution reductions and power sector impacts of water and waste regulations affecting EGUs, including Cooling Water Intakes (316(b)) Rule, Disposal of Coal Combustion Residuals from Electric Utilities (CCR) and Steam Electric Effluent Limitation Guidelines (ELG).
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.  The 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 Clean Air Act (CAA) Amendments Section 812 studies of the CAA 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 state partnerships (e.g., the Regional Greenhouse Gas Initiative (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 nitrogen oxide (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
The "base case" for this analysis is a business-as-usual scenario that would be expected under market and regulatory conditions in the absence of this rule. As such, the IPM base case represents the baseline for this regulatory impact analysis. The EPA frequently updates the IPM base case to reflect the latest available electricity demand forecasts, as well as expected costs and availability of new and existing generating resources, fuels, and emissions control technologies.
The EPA conducted analysis and modeling in support of the April 2012 EGU GHG New Source Standards proposal, and concluded that new unplanned non-compliant base load power plants are not expected to be built through the analysis period (2020 for the original proposal) and beyond (77 FR 22392, April 13, 2012). 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. For the 2012 proposal, the EPA also conducted three additional base case sensitivity analyses using IPM.
After considering public comments received on the 2012 proposal, the EPA issued a new proposal for carbon emissions from new power plants (79 FR 1430, January 8, 2014). The EPA's IPM modeling of the 2013 proposal relied on the AEO 2013 electric demand forecast, and was analyzed using the IPM v. 5.13 base case. The EPA also conducted three additional base case sensitivity analyses using IPM.
For the analysis of the final 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 EGU compliance plans in response to 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).
Table 4-1 reports the unplanned capacity additions forecast by the IPM base case. Unplanned capacity additions are those that the model forecasts to be built in response to forecast economic conditions, such as fuel prices and demand growth. The EPA's IPM base case forecast finds that EGUs are projected to adopt technology for new steam and combustion turbine generation capacity that would be compliant with the standards, even in the absence of this rule. Only some new coal-fired units with carbon capture and storage (CCS) technology, which are receiving partial federal financial support, are included in the baseline modeling. Furthermore, 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. However, 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 percent or less across all domestic regions and all simulation years.  The emissions rate of new natural gas combined cycle (NGCC) units in the EPA's IPM base case is below the emissions rate standard of this final rule, although this is by assumption. However, assuming an emissions rate for new NGCC units that is below the emissions rate standard is consistent with the detailed emissions rate analysis described in the preamble for this rule. That analysis carefully considered emissions rate data on newly constructed NGCC units and GHG limitations in recently issued construction permits for NGCC facilities and found that these facilities operated below the standard or were permitted to operate below the standard.
The EIA projections that are reflected in AEO 2014 reference case are summarized in the following tables alongside the EPA base case projections.  According to the EIA, the AEO 2014 reference case "projection is a business-as-usual trend estimate, given known technology and technological and demographic trends." It represents existing policies and regulations influencing the power sector.  As shown in Table 4-1, new coal-fired capacity through 2030 is projected to be entirely CCS-equipped and would be in compliance with these standards (300 MW) in the AEO 2014 reference case.  The projected CCS-equipped capacity is assumed to occur in response to existing federal, state, and local incentives for the technology. The AEO 2014 reference case forecasts that the vast majority of new, unplanned generating capacity will be either natural gas-fired or renewable.  The reference case projects a capacity factor for simple cycle combustion turbines of less than 20 percent in all regions and in all years, and therefore these units are projected to operate below the applicability limit for this final rule.  As in the IPM-based analysis, the emission rate for new NGCC units in the AEO 2014 reference case is assumed to be below the applicable standard in this final rule.
As described in detail in 4.4.2, 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 2014.  Sensitivity cases that EIA conducted in the AEO 2014, as well as the AEO 2013, 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. None of these sensitivity cases forecast unplanned additions of coal-fired capacity without CCS in the analysis period.  This has been a consistent finding in the AEO, which led the Department of Energy (DOE) 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.	Unplanned Cumulative Capacity Additions (GW)

                                 EPA Base Case
                            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
                                       -
                                      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, 1891-2013
Source: Form EIA-860 (2013)
Notes: Figure reflects all capacity brought online from 1891  -  2013, including 77 GW subsequently retired. Total capacity shown: 1,126 GW, including 12 GW built pre-1940.   Other Renewables include: hydro, biomass, solar, landfill gases, solid waste combustion and geothermal. Other includes: petroleum & distillates, petroleum coke, propane, other gases and waste heat not otherwise included.
 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 percent of total 2020 generation in AEO 2014 and 37 percent 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 Base Case
                            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 miscellaneous generation and storage technologies. Negative value reflects net energy loss from pumped storage.
It has been previously noted that the current projections for key market variables, such as natural gas prices, and state and regional regulations are now even less favorable to the development of non-compliant coal-fired capacity than at the time of the 2012 proposal.  State and regional regulations have changed since the 2012 proposal, as noted in Section 2.8, 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  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)  -  There are now 29 states, the District of Columbia and Puerto Rico that have an enforceable RPS, or similar laws.  Eight other States, the Virgin Islands and Guam 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. Only 12 states do not currently have an enforceable RPS.
         * 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 any new sources of generation will be from sources that meet the standards set in this regulation.  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
As described in the previous section, in addition to the EPA's own analysis, the EPA reviewed EIA's recent forecasts of new capacity in the electricity sector for the AEO 2014. The AEO 2014 reference case forecasts no new non-compliant capacity would be built. Power sector modeling by EIA also projects that their conclusion of there being no new coal-fired capacity built in the analysis period is 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 used by the EPA for this RIA, 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 Case 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
 Note: The AEO 2014 scenario definitions are: High Economic Growth increases annual real GDP growth by 2.8 percent per year through 2040 (reference case GDP growth is 2.4 percent per year); Low Coal Cost assumes 2.4 percent greater regional coal mining productivity growth than in the reference case, and lower wages, equipment, and declining transportation costs for the coal industry than in the reference case, falling to 25 percent below the reference case by 2040; Low Oil and Gas Resource reduces the ultimate estimated recovery of shale gas, tight gas, and tight oil by 50 percent; No GHG Concern removes the perceived risk of incurring costs under a future GHG policy from market investment decisions.
4.4.3	Power Sector Fuel Price Dynamics and Trends
Expectations about what new fossil-fired generation would serve future demand have changed over the past decade from generating sources that use coal to those, primarily combined cycle systems, which use natural gas. As mature technologies, the cost and performance characteristics of conventional coal-fired capacity and NGCC are projected by the EPA to be relatively stable over time.  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 percent 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 percent increase (from 24.3 Tcf in 2014 to 37.5 Tcf in 2040). Over 75 percent of this forecast 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 percent above production in 2013, which is the largest annual growth rate since 1984.  The average real (2011$) natural gas price delivered to the power sector was $4.39/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."
The 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 analyzing alternative scenarios 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 comparisons of alternative scenarios presented throughout this chapter.
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 recent 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. The relative prices of available fuels partially drive power sector investment decisions. Even under scenarios where the spread between the unit price of gas and coal is highest, no construction of new non-compliant generating capacity is projected in 2020, as shown in Table 4-3.

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
	Note: AEO 2014 scenario definitions: High Economic Growth assumes real GDP growth is 2.8 percent peryear from 2012 to 2040 (base case assumes 2.4 percent); Low Economic Growth assumes real GDP growth is 1.9 percent per year High Coal Cost assumes lower regional productivity growth rates and higher wages, equipment, and transportation costs for the coal industry; Low Coal Cost assumes greater regional productivity growth rates and lower wages, equipment, and transportation costs for the coal industry; High Oil and Gas Resource expands the ultimate estimated recovery of shale gas, tight gas, and tight oil by 100 percent; Low Oil and Gas Resource reduces the ultimate estimated recovery of shale gas, tight gas, and tight oil by 50 percent.
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 are 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 2050.

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 2050 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 through 2022 in these scenarios. This demonstrates that natural gas prices do not have to continue at currently low levels 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 cost advantages of NGCC over coal-fired technologies during the analysis period, the unit-level engineering cost analysis in section 5.4 compares these technologies. That analysis builds on the unit-level cost comparisons presented in the following sections of this chapter.
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 final EGU New Source GHG Standards are projected to result in negligible emission reductions, quantified 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), transportation, storage and monitoring (TS&M) and fuel.  (See preamble section V. H. 5.)
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 8,760 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 and book life.
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
This section reports the LCOE of individual technologies that are affected EGUs of this final rule. These are compared in the following sections. The NGCC and coal-fired generation technology cost and performance assumptions that form the basis for the LCOE analysis in this RIA 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.[,] In particular, the NETL costs released in 2015 include vendor quotes for new technology deployed. The use of NETL cost and performance characteristics also allows for comparisons to be made across generating technologies using a single, internally consistent framework. 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.  For simple cycle CTs, NETL cost and performance estimates were not available or sufficiently recent so the 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 parts per million or less. The SCPC unit treating a slip stream with partial post-combustion CCS were assumed to be equipped with the CO2 removal system designed by Shell Cansolv, the system currently in full-scale commercial use at the Boundary Dam facility.  Estimated costs for the system reflect the latest vendor quotations.
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 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 would: (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. 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$)
                                 Capacity Type
                             Capital Cost ($/MWh)
                  Fixed Operations & Maintenance ($/MWh)
                 Variable Operations & Maintenance ($/MWh)
                                   TS&M
                                    ($/MWh)
                          Levelized Fuel Cost ($/MWh)
                         Net Plant HHV Efficiency (%)
NGCC
                                      13
                                       4
                                      1.8
                                       -
                                      42
                                     50.2
SCPC
                                      39
                                      10
                                       9
                                       -
                                      25
                                     40.7
SCPC w/ Partial CCS
(1,400 lb/MWh gross)
                                      51
                                      11
                                      10
                                       1
                                      26
                                     39.2
SCPC Co-Firing Natural Gas (1,400 lb/MWh gross)
                                      39
                                      10
                                       9
                                       -
                                      34
                                     40.3
IGCC
                                      54
                                      14
                                       9
                                       -
                                      26
                                     39.0
IGCC Co-Firing Natural Gas (1,400 lb/MWh)
                                      54
                                      14
                                       9
                                       -
                                      28
                                     39.0
Notes: Cost from NETL 2015. The coal assumed is a bituminous coal with a sulfur content of 2.8 percent (dry) at a real (2011$) price of $2.94/MMBtu, consistent with NETL 2015.  The analysis uses a natural gas price of $6.19. NETL uses a high-risk financial structure resulting in a capital charge factor (CCF) of 0.124 to evaluate the costs of all cases with CO2 capture (non-capture case uses a conventional financial structure with a CCF of 0.116).
NETL (2015) explains that there are a range of future potential costs that are up to 15 percent below, or 30 percent 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 non-compliant 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 these standards.
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 (i.e., non-health benefits) impacts of emissions from these technologies is considered in Chapter 5.
 It is also important to note that both the EIA and the 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 inconsistencies between power sector modeling absent GHG regulation and the widespread use of a cost of CO2 emissions in power sector resource planning. 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 planning cost typically assigned by project developers and utilities to GHG-intensive projects in a context of climate uncertainty.  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 pertinent when evaluating 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 to evaluating 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 cost estimates based on the 2015 NETL analysis for non-compliant coal-fired projects are presented in the following analysis both with and without the CUA.  All LCOE estimates of coal-fired facilities with CCS 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 Non-compliant Coal