Having calculated estimates of jobs per million dollars of energy efficiency expenditure, we use EPA's illustrative energy efficiency investment levels of the first-year costs expected for states to attain a target of 1 percent growth in demand-side efficiency improvements (see Chapter 3.6 of this RIA for more information). If some states were to target rates of energy efficiency savings greater than one percent, they may see increased energy efficiency employment impacts, relative to the one percent growth assumed in this analysis. The first year cost of saved energy accounts for both the costs to the utilities that are funding the demand-side energy efficiency programs (known as the program costs), and the additional cost to the end-user purchasing a more energy efficient technology (known as the participant costs). Total costs were divided evenly, 50 percent each, between program costs and participant costs. First-year costs are not annualized; they are the projected expenditures on demand-side energy efficiency activities in that year. As shown in the Greenhouse Gas Abatement Measures TSD, Table 5-29, first-year costs for a 1 percent growth target in energy efficiency activities are projected to be $18.1 billion (2011 $) in 2020. Multiplying this dollar expenditure by the jobs per dollar estimates results in projected employment impacts for demand-side energy efficiency activities ranging from 37,570 to 59,700 jobs in 2020 depending on the jobs per million dollars estimate used: low or high. Employment impacts for demand-side energy efficiency activities range from 52,590 to 83,590 jobs in 2025, and from 52,440 to 83,360 jobs in 2030. These estimates are shown in Table 6-6 below.

Table 6-6.	Estimated Demand-Side Energy Efficiency Employment Impacts: Target 1 percent Growth in Energy Efficiency
Source
                                    Factor
Employment impact (jobs)*

                                     2020
                                     2025
                                     2030
EPA low estimate, using BLS and Census data, and power sector modeling projections
                                     2.07
                                    37,570
                                    52,590
                                    52,440
EPA high estimate, using BLS and Census data, and power sector modeling projections
                                     3.29
                                    59,700
                                    83,590
                                    83,360
*Since these figures represent number of employees (full- or part-time) they should not be added to the full-time equivalent job-years reported in Table 6-5. Energy efficiency costs are from 1 percent growth target projections for the continental U.S. (excludes Alaska, Hawaii, and U.S. Territories): $18.1 billion (2011 $) in 2020. First-year energy efficiency costs are the same for rate-based and mass-based scenarios. See chapter 3 of this RIA and Greenhouse Gas Abatement Measures TSD, Table 5-29, for more information.
      Although this approach has the advantage of using a range of estimates, derived from U.S. government data, on energy efficiency employment per million dollars in industry shipments, this approach is limited by its focus on manufacturing sectors and direction of bias (overestimation or underestimation) cannot be determined at this time.
Our estimates of 2.07 to 3.29 demand-side energy efficiency jobs per million dollars of 2011 expenditure fit with other estimates in the literature, focused on government data sources, and are on the smaller end of the range. Figure 6.6 shows the range of estimates, including EPA low (2.07) and EPA high (3.29). The 2010 Department of Commerce report estimates overall employment per million dollar values, ranging from 4.65 to 4.85 (Department of Commerce 2010a). The report also contains some case studies, and for those focused on energy efficiency, the Department of Commerce estimates 6.21 jobs per million dollars in green buildings activities and 7.53 jobs per million dollars for energy efficiency appliances. Lawrence Berkeley National Lab (Goldman et al. 2010) reports a wide range of estimates: from 2.5 jobs per million dollars for energy service companies (ESCOs), to 8.9 jobs per million dollars for low income weatherization activities. The Pacific Northwest National Labs report (Anderson et al. 2014), in surveying the literature, estimates 8 jobs per million dollars of consumer electricity bill savings and 11 jobs per million dollars of initial energy efficiency investments.

Figure 6.4. Demand-Side Energy Efficiency Employment: Jobs per One Million Dollars (2011$)
There is more uncertainty involved in this approach than the standard bottom-up engineering analysis used to estimate electricity generation and fuel production employment impacts of this rulemaking. For those, the EPA was able to identify a limited set of activities (e.g., constructing a new NGCC power plant), and study associated labor requirements. Demand-side energy efficiency improvements, in contrast, encompass a wide array of activities (subsidies for efficient appliances, "smart meters," etc.). In addition, there is considerable uncertainty regarding which activities a state will choose. Thus, the validity of the jobs per dollar approach used here relies on the assumption that states will use a mix of activities similar to the 2011 composition of energy efficiency sectors identified by BLS.
In addition, the EPA does not have access to bottom-up information regarding labor requirements for these activities. Use of a constant job per dollar fraction is at best a crude approximation of these labor requirements. The EPA has identified several other limitations of this approach, outlined below.
      Job Reclassification. Job numbers in this chapter represent gross changes in the affected sector. As such they may over-estimate impacts to the extent that jobs created displace workers employed elsewhere in the economy. For demand-side efficiency activities this potential over-statement is may be higher than in other sectors. If states encourage consumers to purchase ENERGY STAR appliances, for example, currently employed workers in factories and retail outlets may simply be given a different task. This approach, however, would count these workers as jobs created.
      Imports. The job per dollar fraction used in the employment projection is calculated based on jobs per dollar of revenue for domestic firms only. To the extent that spending on demand-side energy efficiency activities goes toward the purchase of imported goods this projection will overstate the U.S. employment impact of those expenditures.
      Fixed Coefficient. Implicit in this approach is the assumption that employment impacts can be projected decades into the future on the basis of a single calculation from 2011 data. The labor intensity of demand-side energy efficiency will likely change with technological innovation in the sector. In addition, even absent technological change, labor intensity of expenditures will likely change over time as states alter their portfolio of efficiency activities (e.g., by moving to higher cost activities after exhausting opportunities for low cost efficiency gains).

      Non-additional Activities. Here we assume that all activities financed by demand-side energy efficiency expenditures are additional to what would have been undertaken in the absence of these programs. If utilities finance some actions customers would have undertaken in the absence of these programs (e.g., if a customer receives a rebate for an energy efficient appliance that would have been purchased without the rebate), these numbers would overestimate employment impacts of the proposed guidelines.

6.6	Conclusion
This chapter presents qualitative and quantitative discussions of potential employment impacts of the final guidelines for electricity generation, fuel production, and demand-side energy efficiency sectors. The qualitative discussion identifies challenges associated with estimating net employment effects and discusses anticipated impacts related to the rule. It includes an in-depth discussion of economic theory underlying analysis of employment impacts. The employment impacts for regulated firms can be decomposed into output and substitution effects, both of which may be positive or negative. Consequently, economic theory alone cannot predict the direction or magnitude of a regulation's employment impact. It is possible to combine theory with empirical studies specific to the regulated firms and other relevant sectors if data and methods of sufficient detail and quality are available. Finally, economic theory suggests that environmental regulations may have positive impacts on labor supply and productivity as well.
We examine the peer-reviewed economics literature analyzing various aspects of labor demand, relying on the above theoretical framework. Determining the direction of employment effects in regulated industries is challenging because of the complexity of the output and substitution effects. Complying with a new or more stringent regulation may require additional inputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms (and firms in other relevant industries) in their production processes. The available literature illustrates some of the difficulties for empirical estimation: for example, there is a paucity of publicly data on plant-level employment, thus most studies must rely on confidential plant-level employment data from the U.S. Census Bureau, typically combined with pollution abatement expenditure data, that are too dated to be reliably informative, or other measures of the stringency of regulation. In addition, the most commonly used empirical methods can only estimate the gross effects of regulation on employment (i.e. the impact of that more stringent regulation has on employment relative to less stringent or no regulation), not the net effects. Empirical analysis at the industry level requires estimates of product demand elasticity; production factor substitutability; supply elasticity of production factors; and the share of total costs contributed by wages, by industry, and perhaps even by facility Econometric studies of environmental rules converge on the finding that employment effects, whether positive or negative, have been small in regulated sectors.
The illustrative quantitative analysis in this chapter projects a subset of potential employment impacts in the electricity generation, fuel production, and demand-side energy efficiency sectors. States have the responsibility and flexibility to implement policies and practices for compliance with Final EGU GHG Existing Source Guidelines. As such, given the wide range of approaches that may be used, quantifying the associated employment impacts is difficult. EPA's employment analysis includes projected employment impacts associated with these guidelines for the electric power industry, coal and natural gas production, and demand-side energy efficiency activities. These projections are derived, in part, from a detailed model of the electricity production sector used for this regulatory analysis, and U.S. government data on employment and labor productivity. In the electricity, coal, and natural gas sectors, the EPA estimates that these guidelines could have an employment impact of roughly [X] job-years in 20XX for the rate-based scenario and [X] job-years for the mass-based scenario of that same year (see Tables 6-4 and 6-5).
Employment impacts from demand-side energy efficiency activities are based on historic data on jobs supported per million dollars of expenditure on energy efficiency. Demand-side energy efficiency employment impacts would approximately range from 37,570 to 59,700 jobs in 2020, 52,590 to 83,590 jobs in 2025, and from 52,440 to 83,360 jobs in 2030 for the rate-based approach and a 1 percent growth target for energy efficiency expenditures (see Table 6-6).
The IPM-generated job-year numbers for the electricity, coal and natural gas sectors should not be added to the demand-side efficiency job impacts, since the former are reported in full-time equivalent jobs, whereas the latter do not distinguish between full- and part-time employment. Finally, note again that this is an illustrative analysis, and CAA section 111(d) allows each state to determine the appropriate combination of, and the extent of its reliance on, measures for its state plan, by way of meeting its state-specific goal. Given the flexibilities afforded states in complying with the emission guidelines, the impacts reported in this chapter are illustrative of actions states may take.
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Appendix 6A: Estimating Supply Side Employment impacts
This appendix presents the methods used to estimate the supply-side employment impacts of the Final Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electric Utility Generating Units (herein referred to as "final emission guidelines" or the "Clean Power Plan Final Rule"). The focus of the employment analysis is limited to the direct changes in the amount of labor needed in the power, fuels and generating equipment sectors directly influenced by the illustrative plan approaches analyzed for the final emission guidelines. It does not include the ripple effects of these impacts on the broader economy (i.e., the "multiplier" effect), nor does it include the wider economy-wide effects of the changes to the energy markets, such as changes in electricity prices.
The methods used to estimate the supply-side employments are based on methods previously developed for the Mercury and Air Toxics Standards (MATS) Regulatory Impact Analysis (RIA). The methods used in this analysis to estimate the recurring labor impacts (e.g., labor associated with operating and maintaining generating units, as well as labor needed to mine coal and natural gas) are the same as was used in MATS (with updated data where available).
The labor analysis in the MATS RIA was primarily concerned with the labor needs of retrofitting pollution control equipment. The analysis for the Clean Power Plan Final Rule, however, involves the quantity and timing of the labor needs of building new renewable and natural gas, as well as making heat rate improvements (HRI) at existing coal fired EGUs. These construction-related compliance activities in the Clean Power Plan Final Rule required developing additional appropriate analytical methods that were not needed for the MATS analysis. The newly developed analytical methods for the construction-related activities are similar in structure and overall approach to the methods used in MATS, but required additional data and engineering information not needed in the MATS RIA.
6A.1	General Approach
The analytical approach used in this analysis is a bottom-up engineering method combining the EPA's cost analysis of the final emission guidelines with data on labor productivity, engineering estimates of the amount and types of labor needed to manufacture, construct, and operate different types of generating units, and prevailing wage rates for skilled and general labor categories. The approach involved using utility power sector projections and various energy market implications under the final emission guidelines from modeling conducted with the EPA Base Case version 5.15, using the Integrated Planning Model (IPM(R)), along with data from secondary sources, to estimate the first order employment impacts for 2020, 2025, and 2030.
Throughout the supply-side labor analysis the engineering approach projects labor changes measured as the change in each analysis year in job-years employed in the power generation and directly related sectors (e.g., equipment manufacturing, fuel supply and generating efficiency services). Job-years are not individual jobs, nor are they necessarily permanent nor full time jobs. Job-years the amount of work performed by one full time equivalent (FTE) employee in one year. For example, 20 job-years in 2020 may represent 20 full-time jobs or 40 half-time jobs in that year, or any combination of full- and part-time workers such that total 20 FTEs.
6A.1.1	Employment Effects Included In the Analysis
      The estimates of the employment impacts (both positive and negative) are divided into five categories:
   * additional employment to make HRI at existing coal fired EGUs;
   * additional construction-related employment to manufacture and install additional new generating capacity (renewables, and natural gas combined cycle or combustion turbine units) when needed as part of early compliance actions;
   * lost construction-related employment opportunities due to reductions in the total amount of new generating capacity needed to be built in the later years because of reduced overall demand for electricity because of demand-side energy efficiency activities;
   * lost operating and maintenance employment opportunities due to increased retirements of coal and small oil/gas units;
   * changes (both positive and negative) in coal mining and natural gas extraction employment due to the aggregate net changes in fuel demands arising from all the activities occurring due to compliance with the final emission guidelines.
Some of the changes are one-time labor effects which are associated with the building (or avoiding building) new generating capacity and installing HRI. This type of employment effects involves project-specific labor that is used for 2 to 4 years to complete a specific construction and installation type of project. There are other labor effects, however, which continue year after year. For example, bringing new generating capacity online creates an ongoing need for labor to operate and maintain the new generating capacity throughout the expected service life of the unit. New generating capacity also creates a need for additional employment to provide the fuel annually to run the new capacity. There are also continuing effects from the lost operations and maintenance (O&M) and fuel sector labor opportunities from decisions to retire existing capacity, as well as similar lost labor opportunities from decisions to reduce a portion of the amount of additional capacity needed in the base case.
6A.2	Employment Changes due to Heat Rate Improvements
The employment changes due to HRI were estimated based on the incremental MW capacity estimated to implement such improvements by 2020 as indicated by the analysis conducted by EPA. The heat rate improvement job impacts were assumed to have all occurred by 2020 and thus this study assumes there will be no HRI related jobs after 2020 (i.e., no permanent O&M related jobs due to HRI for 2025 or 2030). EPA modeled the heat rate improvements exogenously in IPM using the assumption that all "relevant" units can improve their heat rate by 6 percent at a capital cost of $100/kW. This study assumes that these investments will occur over a four-year period culminating in 2020. Hence, the per-year cost of heat rate was calculated to be $25/kW, and this cost was used in the next step.
This cost was then allocated to four categories based on the estimates provided by Andover Technology Partners (ATP), which were adapted from proxy projects involving installation of combustion control retrofits, such as those installed under the Best Available Retrofit Technology (BART) submissions from coal-fired power plants located in Wyoming and Arizona. For more details, refer to the Staudt (2014) report. These proxies were chosen to ensure that the types of activities involved and their associated costs would be representative of those investments EPA expects power plants to undertake for efficiency upgrades.
Information on cost for these proxies were then extrapolated to approximate the labor requirements for four broad categories of labor  -  boilermakers and general construction, engineering and management support labor, labor required to produce the equipment in upstream sectors, and labor required to supply the materials (assumed to be primarily steel) in upstream sectors. More details about these estimates are provided in the Staudt (2014) report.
Based on the cost allocated in each categories and output per worker figures for respective industries in 2020, the employment gains for heat rate improvement were estimated for 2020 using the assumptions summarized in Table 6A-1 below. Output per workers in future years were adjusted to account for growth in labor productivity, based on historical evidence of productivity growth rates for the relevant sectors.
Table 6A-1.	Labor Productivity Growth Rate due to Heat Rate Improvement

                                 Share of the
                              Total Capital Cost
                             Output/Worker (2020)
                              Labor Productivity
                                  Growth Rate
Boilermaker and Gen. Const.
                                      40%
                                    $78,500
                                      0%
Management/Engineering
                                      20%
                                   $141,000
                                     1.3%
Equipment
                                      30%
                                   $458,000
                                     3.2%
Materials
                                      10%
                                   $424,000
                                     -1.2%

For these output per worker figures, a power sector construction industry (NAICS 237130) was used for general construction and boilermakers, Engineering Services (NAICS 54133) was used for the engineering and management component, Machinery Manufacturing (NAICS 333) was used for the equipment sector, and steel manufacturing (NAICS 33121) was used for materials. Use of machinery manufacturing for equipment and steel for materials was based on an analysis of the types of materials and equipment needed for these projects, and what EPA determined to be the most appropriate industry sectors for those. For more details, refer to the Staudt (2014) report.
6A.2.1	Employment Changes Due to Building (or Avoiding) New Generation Capacity
Employment changes due to new generation units were based on the incremental changes in capacity (MW), capital costs ($MM), and fixed operations and maintenance (FOM) costs ($MM) between the policy scenario and the base case in a given year.
New capacities were aggregated by generation type into the following categories:
 Combined Cycle,
 Combustion Turbine, and
 Renewables (which includes biomass, geothermal, landfill gas, onshore wind, and solar).
For each category, the analysis estimated the impacts due to both the construction and operating labor requirements for corresponding capacity changes. The construction labor was estimated using information on the capital costs, while the operating labor was estimated using the FOM costs.
Because IPM outputs provide annualized capital costs ($MM), EPA first converted the annualized capital costs to changes in the total capital investment using the corresponding capital charge rates. These total capital investments were then converted to annual capital investments using assumptions about the estimated duration of the construction phase, in order to estimate the annual impacts on construction phase labor. Duration estimates were based on assumptions for construction lengths used in EPA's IPM modeling. Specific assumptions used for different generating technologies are shown in Table 6A-2 below.
Table 6A-2.	Capital Charge Rate and Duration Assumptions
New Investment Technology
      Capital Charge Rate
      Duration (Years)
Advanced Combined Cycle
                                     10.3%
                                       3
Advanced Combustion Turbine
                                     10.6%
                                       2
Renewables

Biomass
                                     9.5%
                                       3
Wind (Onshore)
                                     10.9%
                                       3
Landfill Gas
                                     10.9%
                                       3
Solar
                                     10.9%
                                       3
Geothermal
                                     10.9%
                                       3

Annual capital costs for each generation type were then broken down into four categories: equipment, material (which is assumed to be primarily steel), installation labor, and support labor in engineering and management. The percentage breakdowns shown in Table 6A-3 were estimated using information provided by Staudt (2014), based primarily on published budgets for new unit assembled in a study for the National Energy Technology Laboratory (NETL). For more details, refer to the Staudt (2014) report. Annual capital costs for each generation type provided by the IPM output were allocated according to this breakdown.
Table 6A-3.	Expenditure Breakdown due to New Generating Capacity

                                   Equipment
                                   Material
                                     Labor
                              Eng. and Const. Mgt
Renewables
                                      54%
                                      6%
                                      31%
                                      9%
Combined Cycle
                                      65%
                                      10%
                                      18%
                                      7%
Combustion Turbine
                                      65%
                                      10%
                                      18%
                                      7%

The short-term construction labor of the new generation units were based on output ($ per worker) figures for the respective sectors. The total direct workers per $1 million of output for the baseline year 2007 were forecasted to the years under analysis using the relevant labor productivity growth rate. Table 6A-4 shows the figures for each of the five productivities: general power plant construction; engineering and management; material use; equipment use; and plant operators. The resulting values were multiplied by the capital costs to get the job impact.
Table 6A-4.	Labor Productivity due to New Generating Capacity

                              Labor Productivity
                                 Growth Rate
                                  Workers per
                               Million $ (2007)
General Power Plant Construction
                                     0.0%
                                      5.7
Engineering and Management
                                     1.3%
                                      5.2
Material Use (Steel)
                                     -1.2%
                                      2.0
Equipment Use (Machinery)
                                     3.2%
                                      3.3
Plant Operators
                                     2.8%
                                     10.8

General installation labor, assumed to be mostly related to the general power plant construction phase, was matched with the power industry specific construction sector. Engineering/management was matched to the engineering services sector to determine their respective output per worker. For materials, EPA assumed steel to be the proxy and used the steel manufacturing sector for this productivity. Equipment was assumed to primarily come from machinery manufacturing sector (such as turbines, engines and fans).
The net labor impact for construction labor for a given year was adjusted to account for changes in capacity that has already taken place in the prior IPM run year. Because IPM reports cumulative changes for new generating capacity for any given run year, this adjustment ensured that the short-term construction phase job impacts in any given run year does not reflect the cumulative effects of prior construction changes for the given policy scenario. The estimated amount of the change in construction-related labor in a single IPM run year (e.g., 2025) represents the average labor impact that occurs in all years between that IPM run year and the previous run year (i.e., the labor estimates derived from the 2025 IPM run year are the average annual labor impacts in 2021 through 2025). The construction labor results for 2020 represent the average labor impacts in 2017 through 2020.
The plant operating employment estimates used a simpler methodology as the one described above. The operating employment estimates use the IPM estimated change in FOM costs for the IPM run year. Because the FOM costs are inherently estimates for a single year, the operating employment estimates are for a single year only. While there are obviously operating employment effects occurring in every year throughout the entire IPM estimation period (2017-2030), the labor analysis only estimates the single year labor impacts in the IPM run years: 2020, 2025 and 2030. The total direct workers for $1 million and labor productivity growth rate provided for plant operators in Table 6A-4 were used to estimate the employment impact.
6A.2.2	Employment Changes due to Coal and Oil/Gas Retirements
Employment changes due to plant retirements were calculated using the IPM projected changes in retirement capacities for coal and oil/gas units for the relevant year and the estimated changes in total FOM costs due to those retiring units. Thus, the basic assumption in this analysis was that increased retirements (over the base case) will lead to reduced FOM expenditures at those plants which were assumed to lead to direct job losses for plant workers.
In order to estimate the total FOM changes due to retirements, EPA first estimated the average FOM costs ($/kW) for existing coal-fired and oil/gas-fired units in the base case, as shown in Table 6A-5 below. It was assumed that the average FOM cost of existing units in the base case can be used as a proxy for the lost economic output due to fossil retirements. Thus, changes in the FOM costs for these retiring units were derived by taking the product of the incremental change in capacity and the average FOM costs. These values were converted to lost employment using data from the Economic Census and BLS on the output/worker estimates for the utility sector.
Table 6A-5.	Average FOM Cost Assumptions

                                     2020
                                     2025
                                     2030
Coal
                                      65
                                      68
                                      69
Oil and Gas
                                      21
                                      22
                                      22

Note that the retirement related employment losses are assumed to include losses directly affecting the utility sector, and do not include losses in upstream sectors that supply other inputs to the EGU sector (except fuel related job losses, which are estimated separately and discussed in the next section).
6A.2.3	Employment Changes due to Coal and Oil/Gas Retirements
Two types of employment impacts due to projected fuel use changes were estimated in this section. First, employment losses due to either reductions or shifts in coal demand were estimated using an approach similar to EPA's coal employment analyses under Title IV of the Clean Air Act Amendments. Using this approach, changes in coal demand (in short tons) for various coal supplying regions were taken from EPA's base and policy case runs for the proposed EGU GHG NSPS. These changes were converted to job-years using U.S. Energy information Administration (EIA) data on regional coal mining productivity (in short tons per employee hour), using 2008 labor productivity estimates.[,]
Specifically, the incremental changes to coal demand were calculated based on the coal supply regions in IPM -- Appalachia, Interior, and West and Waste Coal (which was estimated using U.S. total productivity). Worker productivity values used for estimating coal related job impacts are shown in Table 6A-6 below.
Table 6A-6.	Labor Productivity due to New Generating Capacity

                              Labor Productivity
Coal (Short tons/ employee hour)

Appalachia
                                     2.91
Interior
                                     4.81
West
                                     19.91
Waste
                                     5.96
Natural Gas (MMBtu/ employee hour)
                                      126
Pipeline Construction (Workers per $Million)
                                      5.1

For natural gas demand, labor productivity per unit of natural gas was unavailable, unlike coal labor productivities used above. Most secondary data sources (such as Census and EIA) provide estimates for the combined oil and gas extraction sector. This section thus used an adjusted labor productivity estimate for the combined oil and gas sector that accounts for the relative contributions of oil and natural gas in the total sector output (in terms of the value of energy output in MMBtu). This estimate of labor productivity was then used with the incremental natural gas demand for the respective IPM runs to estimate the job-years for the specific year (converting the TCF of gas used projected by IPM into MMBtu using the appropriate conversion factors). In addition, the pipeline construction costs were estimated using endogenously determined gas market model parameters in IPM used by EPA for the MATS rule (using assumptions for EPA's Base Case v4.10). This analysis assumed that the need for additional pipeline would be proportionate to those projected for the MATS rule and were hence extrapolated from those estimates. The job-years associated with the pipeline construction were included in the natural gas employment estimates.

Chapter 7: Statutory and Executive Order Analysis
7.1	Executive Order 12866: Regulatory Planning and Review, and Executive Order 13563: Improving Regulation and Regulatory Review
This final action is an economically significant regulatory action that was submitted to the OMB for review. Any changes made in response to OMB recommendations have been documented in the docket. The EPA prepared an analysis of the potential costs and benefits associated with this action.
Consistent with Executive Order 12866 and Executive Order 13563, the EPA estimated the costs and benefits for illustrative plan approaches of implementing the guidelines. The final rule establishes: 1) carbon dioxide (CO2) emission performance rates for two source categories of existing fossil fuel-fired EGUs, fossil fuel-fired electric utility steam generating units and stationary combustion turbines, and 2) guidelines for the development, submittal and implementation of state plans that implement the CO2 emission performance rates. Actions taken to comply with the guidelines will also reduce the emissions of directly-emitted PM2.5, SO2 and NOX. The benefits associated with these PM2.5, SO2 and NOX reductions are referred to as co-benefits, as these reductions are not the primary objective of this rule.
The EPA has used the social cost of carbon estimates presented in the Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 (May 2013, Revised June 2015) ("current TSD") to analyze CO2 climate impacts of this rulemaking. We refer to these estimates, which were developed by the U.S. government, as "SC-CO2 estimates." The SC-CO2 is an estimate of the monetary value of impacts associated with a marginal change in CO2 emissions in a given year. The four SC-CO2 estimates are associated with different discount rates (model average at 2.5 percent discount rate, 3 percent, and 5 percent; 95[th] percentile at 3 percent), and each increases over time. In this summary, the EPA provides the estimate of climate benefits associated with the SC-CO2 value deemed to be central in the current TSD: the model average at 3 percent discount rate.
The EPA estimates that, in 2020, the final guidelines will yield monetized climate benefits (in 2011$) of approximately $[X] billion (3 percent model average). The air pollution health co-benefits in 2020 are estimated to be $[X] billion to $[X] billion (2011$) for a 3 percent discount rate and $[X] billion to $[X] billion (2011$) for a 7 percent discount rate. The annual, illustrative plan costs estimated by IPM and inclusive of demand-side energy efficiency program and participant costs and MRR costs, are approximately $[X] billion (2011$) in 2020. The quantified net benefits (the difference between monetized benefits and costs) in 2020 are estimated to range from $[X] billion to $[X] billion (2011$) using a 3 percent discount rate (model average).
The EPA estimates that, in 2025, the final guidelines will yield monetized climate benefits (in 2011$) of approximately $[X] billion (3 percent model average). The air pollution health co-benefits in 2025 are estimated to be $[X] billion to $[X] billion (2011$) for a 3 percent discount rate and $[X] billion to $[X] billion (2011$) for a 7 percent discount rate. The annual, illustrative state plan costs estimated by IPM and inclusive of demand side energy efficiency program and participant costs and MRR costs, are approximately $[X] billion (2011$) in 2025. The quantified net benefits (the difference between monetized benefits and costs) in 2025 are estimated to range from $[X] billion to $[X] billion (2011$) using a 3 percent discount rate (model average).
The EPA estimates that, in 2030, the final guidelines will yield monetized climate benefits (in 2011$) of approximately $[X] billion (3 percent model average). The air pollution health co-benefits in 2030 are estimated to be $[X] billion to $[X] billion (2011$) for a 3 percent discount rate and $[X] billion to $[X] billion (2011$) for a 7 percent discount rate. The annual, illustrative state plan costs estimated by IPM and inclusive of demand side energy efficiency program and participant costs and MRR costs, are approximately $[X] billion (2011$) in 2030. The quantified net benefits (the difference between monetized benefits and costs) in 2030 are estimated to range from $[X] billion to $[X] billion (2011$) using a 3 percent discount rate (model average).
There are additional important benefits that the EPA could not monetize. Due to current data and modeling limitations, our estimates of the benefits from reducing CO2 emissions do not include important impacts like ocean acidification or potential tipping points in natural or managed ecosystems. Unquantified benefits also include climate benefits from reducing emissions of non-CO2 greenhouse gases (e.g., nitrous oxide and methane) and co-benefits from reducing direct exposure to SO2, NOx and hazardous air pollutants (e.g., mercury and hydrogen chloride), as well as from reducing ecosystem effects and visibility impairment. Based upon the foregoing discussion, it remains clear that the benefits of this proposal are substantial, and far exceed the costs. Additional benefit, cost and net benefit estimates are provided in Chapter 8 of this report.
7.2	Paperwork Reduction Act (PRA)
The information collection requirements in this rule have been submitted for approval to OMB under the PRA. The Information Collection Request (ICR) document prepared by the EPA has been assigned the EPA ICR number 2503.02. You can find a copy of the ICR in the docket for this rule, and it is briefly summarized here. The information collection requirements are not enforceable until OMB approves them.
This rule does not directly impose specific requirements on EGUs located in states, U.S. territories or areas of Indian country. The rule also does not impose specific requirements on tribal governments that have affected EGUs located in their area of Indian country. For areas of Indian country, the rule establishes CO2 emission performance goals that could be addressed through either tribal or federal plans. A tribe would have the opportunity under the Tribal Authority Rule (TAR), but not the obligation, to apply to the EPA for Treatment as State (TAS) for purposes of a CAA section 111(d) plan and, if approved by the EPA, to establish a CAA section 111(d) plan for its area of Indian country. To date, no tribe has requested or obtained TAS eligibility for purposes of a CAA section 111(d) plan. For areas of Indian country with affected EGUs where a tribe has not applied for TAS and submitted any needed plan, if the EPA determines that a CAA section 111(d) plan is necessary or appropriate, the EPA would have the responsibility to establish the plans. Because tribes are not required to implement section 111(d) plans and because no tribe has yet sought TAS eligibility for this purpose, this action is not anticipated to impose any information collection burden on tribal governments over the 3-year period covered by this ICR.
This rule does impose specific requirements on state and U.S. territory governments with affected EGUs. The information collection requirements are based on the recordkeeping and reporting burden associated with developing, implementing, and enforcing a plan to limit CO2 emissions from existing sources in the utility power sector. These recordkeeping and reporting requirements are specifically authorized by CAA section 114 (42 U.S.C. 7414). All information submitted to the EPA pursuant to the recordkeeping and reporting requirements for which a claim of confidentiality is made is safeguarded according to agency policies set forth in 40 CFR part 2, subpart B.
The annual burden for this collection of information for the states (averaged over the first 3 years following promulgation) is estimated to be a range of 529,000 to 859,000 hours at a total annual labor cost of $37.4 to $60.8 million. The lower bound estimate reflects the assumption that some states already have energy efficiency and renewable energy programs in place. The higher bound estimate reflects the overly-conservative assumption that no states have energy efficiency and renewable energy programs in place.
The annual burden for this collection of information for the two affected U.S. territories, i.e., Puerto Rico and Guam, (averaged over the first 3 years following promulgation of this action) is estimated to be 23,700 to 38,200 hours at a total annual labor cost of $1.68 to $2.71 million.
The total annual burden for the federal government associated with the state collection of information (averaged over the first 3 years following promulgation) is estimated to be 54,901 hours at a total annual labor cost of $3.04 million. The total annual burden for the federal government associated with the territorial collection of information (averaged over the first 3 years following promulgation) is estimated to be 2,600 hours at a total annual labor cost of $145,000. Burden is defined at 5 CFR 1320.3(b).
An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB control number. The OMB control numbers for the EPA's regulations in 40 CFR are listed in 40 CFR part 9. When OMB approves this ICR, the agency will announce that approval in the Federal Register and publish a technical amendment to 40 CFR part 9 to display the OMB control number for the approved information collection activities contained in this final rule.
7.3	Regulatory Flexibility Act (RFA)
The EPA certifies that this action will not have a significant economic impact on a substantial number of small entities under the RFA. This action will not impose any requirements on small entities. Specifically, emission guidelines established under CAA section 111(d) do not impose any requirements on regulated entities and, thus, will not have a significant economic impact upon a substantial number of small entities. After emission guidelines are promulgated, states and U.S. territories establish emission standards on existing sources, and it is those requirements that could potentially impact small entities.
Our analysis here is consistent with the analysis of the analogous situation arising when the EPA establishes NAAQS, which do not impose any requirements on regulated entities. As here, any impact of a NAAQS on small entities would only arise when states take subsequent action to maintain and/or achieve the NAAQS through their state implementation plans. See American Trucking Assoc. v. EPA, 175 F.3d 1029, 1043-45 (D.C. Cir. 1999) (NAAQS do not have significant impacts upon small entities because NAAQS themselves impose no regulations upon small entities).
Nevertheless, the EPA is aware that there is substantial interest in the rule among small entities and, as detailed in section III.A of the preamble to the proposed carbon pollution emission guidelines for existing EGUs (79 FR 34845-34847; June 18, 2014) and in section II.D of the preamble to the proposed carbon pollution emission guidelines for existing EGUs in Indian Country and U.S. Territories (79 FR 65489; November 4, 2014), has conducted an unprecedented amount of stakeholder outreach. As part of that outreach, agency officials participated in many meetings with individual utilities and electric utility associations, as well as industry leaders and trade association representatives from various industries. While formulating the provisions of the rule, the EPA considered the input provided over the course of the stakeholder outreach as well as the input provided in the many public comments.
7.4	Unfunded Mandates Reform Act (UMRA)
This action does not contain an unfunded mandate of $100 million or more as described in UMRA, 2 U.S.C. 1531 - 1538, and does not significantly or uniquely affect small governments. The emission guidelines do not impose any direct compliance requirements on EGUs located in states, U.S. territories or areas of Indian country. As explained in section XII.B above, the rule also does not impose specific requirements on tribal governments that have affected EGUs located in their area of Indian country. The rule does impose specific requirements on state and U.S. territory governments that have affected EGUs. Specifically, states and U.S. territories are required to develop plans to implement the guidelines under CAA section 111(d) for affected EGUs. The burden for states and U.S. territories to develop CAA section 111(d) plans in the 3-year period following promulgation of the rule was estimated and is listed in section XII.B above, but this burden is estimated to be below $100 million in any one year. Thus, this rule is not subject to the requirements of section 202 or section 205 of the UMRA.
This rule is also not subject to the requirements of section 203 of UMRA because it contains no regulatory requirements that might significantly or uniquely affect small governments. Specifically, the state and U.S. territory governments to which rule requirements apply are not considered small governments.
In light of the interest among governmental entities, the EPA conducted outreach with national organizations representing state and local elected officials and U.S. territory and tribal governmental entities while formulating the provisions of this rule. Sections III.A and XI.F of the preamble to the proposed carbon pollution emission guidelines for existing EGUs (79 FR 34845-34847; June 18, 2014) and sections II.D and VI.F of the preamble to the proposed carbon pollution emission guidelines for existing EGUs in areas of Indian Country and U.S. Territories (79 FR 65489; November 4, 2014) describes the extensive stakeholder outreach the EPA has conducted on setting emission guidelines for existing EGUs. The EPA considered the input provided over the course of the stakeholder outreach as well as the input provided in the many public comments when developing the provisions of these emission guidelines.
7.5	Executive Order 13132: Federalism
The EPA has concluded that this action may have federalism implications, pursuant to agency policy for implementing the Order, because it imposes substantial direct compliance costs on state or local governments, and the federal government will not provide the funds necessary to pay those costs. As discussed in the Supporting Statement found in the docket for this rulemaking, the development of state plans will entail many hours of staff time to develop and coordinate programs for compliance with the rule, as well as time to work with state legislatures as appropriate, to develop a plan submittal. Consistent with this determination, the EPA provides the following federalism summary impact statement.
The EPA consulted with state and local officials early in the process of developing the proposed action to permit them to have meaningful and timely input into its development. As described in the Federalism discussion in the preamble to the proposed standards of performance for GHG emissions from new EGUs (79 FR 1501; January 8, 2014), the EPA consulted with state and local officials in the process of developing the proposed standards for newly constructed EGUs. This outreach addressed planned actions for new, reconstructed, modified and existing sources. The EPA invited the following 10 national organizations representing state and local elected officials to a meeting on April 12, 2011, in Washington DC: (1) National Governors Association; (2) National Conference of State Legislatures, (3) Council of State Governments, (4) National League of Cities, (5) U.S. Conference of Mayors, (6) National Association of Counties, (7) International City/County Management Association, (8) National Association of Towns and Townships, (9) County Executives of America, and (10) Environmental Council of States. The National Association of Clean Air Agencies also participated. On February 26, 2014, the EPA re-engaged with those governmental entities to provide a pre-proposal update on the emission guidelines for existing EGUs and emission standards for modified and reconstructed EGUs. In addition, as described in section III.A of the preamble to the proposed carbon pollution emission guidelines for existing EGUs (79 FR 34845-34847; June 18, 2014), extensive stakeholder outreach conducted by the EPA allowed state leaders, including governors, state attorneys general, environmental commissioners, energy officers, public utility commissioners, and air directors, opportunities to engage with EPA officials and provide input regarding reducing carbon pollution from power plants.
In the spirit of Executive Order 13132, and consistent with the EPA's policy to promote communications between the EPA and state and local governments, the EPA specifically solicited comment on the proposed action from state and local officials. The EPA received comments from over 400 entities representing state and local governments.
Several themes emerged from state and local government comments. Commenters raised concerns with the building blocks that comprise the best system of emission reduction (BSER), including the stringency of the building blocks, and the timing of achieving interim CO2 levels. They also identified the potential for electric system reliability issues and stranded assets due to the proposed timeframe for plan submittals and CO2 emission reductions. In addition, states commented on state plan development and implementation topics, including state plan approaches, early actions, trading programs, interstate crediting for RE, and EPA guidance and outreach.
Commenters identified overarching concerns regarding the stringency of the CO2 goals and the timeframe for achieving reductions that encompassed the building blocks, the BSER, and associated timing for achievement of interim CO2 levels. State commenters, in particular, identified changes to the stringency of the building blocks, concerns with the timeframe over which reductions must be achieved, and concerns with the approaches and measures used for the BSER. For the final rule, in response to stakeholder comments, the EPA has made refinements to the building blocks, the period of time over which measures are deployed, and the stringency of emission limitations that those measures can achieve in a practical and reasonable cost way. The final BSER reflects those refinements.
To many commenters, the proposal's 2020 compliance date, together with the stringency of the interim CO2 goal, bore significant reliability implications. In this final rule, the agency is addressing those concerns via adjustments to the compliance timeframe (an 8-year interim period that begins in 2022) and to the approach for meeting interim CO2 emission performance rates (a glide path separated into three steps, 2022-2024, 2025-2027, and 2028-2029). These adjustments provide more time for planning, consultation and decision making in the formulation of state plans and in EGUs' choices of compliance strategies. The final rule also retains flexibilities presented in the proposal and offers additional opportunities, including opportunities for trading within and between states, and other multi-state plan approaches that will further support electric system reliability. The EPA is also requiring states to consult with relevant ISOs/RTOs and/or planning/reliability authorities during plan development, and to document recommendations in their plans  -  and is providing the time for states to do so. Even with this foundation of flexibility in place, these final guidelines further provide states with the option of proposing amendments to approved plans in the event that unanticipated and significant reliability challenges arise.
Commenters provided compelling information indicating that it will take longer than the agency initially anticipated to adjust investments and achieve interim CO2 reductions. Recognizing this, as well as the urgent need for actions to reduce GHG emissions, the EPA is requiring states to frame an initial plan by August 31, 2016, and is allowing states two additional years to submit a final plan, if justified (to be submitted by August 31, 2018).
States commented on state plan development and implementation topics that included state plan approaches, early actions being taken into account, trading programs being allowed, interstate crediting for RE being allowed, and guidance and outreach being provided by the EPA. For the state plan approaches, commenters expressed concerns with the proposed "portfolio approach" for state plans, including concerns with enforceability of requirements, and identified a "state commitment approach" with backstop measures as an option for state plans. In this final rule, in response to stakeholder comments on the portfolio approach and alternative approaches, the EPA is finalizing a "state measures" approach that includes a requirement for the inclusion of backstop measures.
State commenters also expressed interest in the EPA ensuring that early actions to reduce CO2 are rewarded. In this final rule, states with currently existing programs and policies, and states that put in place new programs and policies early, will be better positioned to achieve the CO2 goals. Measures that a state takes prior to 2022, or programs already in place by 2022, that result in CO2 emission reductions during the 2022-2029 period will contribute toward meeting both the interim and final CO2 emission performance rates. Thus, states with currently existing programs and policies, and states that put in place new programs and policies early, will be better positioned to achieve the goals. RE generating capacity and demand-side EE measures that are installed after 2012 will be eligible for use in adjusting a CO2 emission performance rate.
Many state commenters supported the use of mass-based and rate-based emission trading programs in state plans, including interstate emission trading programs. The EPA also received a number of comments from states and stakeholders about the value of EPA support in developing and/or administering tracking systems to support state administration of rate-based and mass-based emission trading programs. In this final rule, states may use trading or averaging approaches and technologies or strategies that are not explicitly mentioned in any of the three building blocks as part of their overall plans, as long as they achieve the required emission reductions from affected fossil-fuel-fired EUGs. In addition, in response to concerns from states and power companies that the need for up-front interstate cooperation in developing multi-state plans could inhibit the development of interstate programs that could lower cost, the final rule provides additional options to allow individual EGUs to use creditable out-of-state reductions to achieve required CO2 reductions, without the need for up-front interstate agreements. The EPA is committed to working with states to provide support for tracking of emissions and allowances or credits, to help implement multi-state trading or averaging approaches.
In their comments, many states identified the need for the EPA to provide guidance, including guidance on RE and EE emission measurement and verification (EM&V), and to maintain regular contact/forums with states throughout the implementation process. To provide state and local governments and other stakeholders with an understanding of the rule requirements, and to provide efficiencies where possible and reduce the cost and administrative burden, the EPA will continue outreach throughout the plan development and submittal process. Outreach will include opportunities for states to participate in briefings, teleconferences, and meetings about the final rule. The EPA's 10 regional offices will continue to be the entry point for states, tribes and territories to ask technical and policy questions. The agency will host (or partner with appropriate groups to co-host) a number of webinars about various components of the final rule during the first two months after the final rule is issued. The EPA will use information from this outreach process to inform the training and other tools that will be of most use to the states, tribes, and territories that are implementing the final rule. The EPA expects to issue guidance on specific topics, including evaluation, measurement and verification (EM&V) for RE and demand-side EE, state-community engagement, and resources and financial assistance for RE and demand-side EE. As guidance documents, tools, templates and other resources become available, the EPA, in consultation with the U.S. Department of Energy and other federal agencies, will continue to make these resources available via a dedicated website.
A list of the state and local government commenters has been provided to OMB and has been placed in the docket for this rulemaking. In addition, the detailed response to comments from these entities is contained in the EPA's response to comments document on this final rulemaking, which has also been placed in the docket for this rulemaking.
As required by section 8(a) of Executive Order 13132, the EPA included a certification from its Federalism Official stating that the EPA had met the Executive Order's requirements in a meaningful and timely manner when it sent the draft of this final action to OMB for review pursuant to Executive Order 12866. A copy of the certification is included in the public version of the official record for this final action.
7.6	Executive Order 13175: Consultation and Coordination with Indian Tribal Governments
This action has tribal implications. However, it will neither impose substantial direct costs on federally recognized tribal governments, nor preempt tribal law. Tribes are not required to develop or adopt CAA programs, but they may apply to the EPA for treatment in a manner similar to states (TAS) and, if approved, do so. As a result, tribes are not required to develop plans to implement the guidelines under CAA section 111(d) for affected EGUs in their areas of Indian country. To the extent that a tribal government seeks and attains TAS status for that purpose, these emission guidelines would require that planning requirements be met and emission management implementation plans be executed by the tribes. The EPA notes that this rule does not directly impose specific requirements on affected EGUs, including those located in areas of Indian country, but provides guidance to any tribe approved by the EPA to address CO2 emissions from EGUs subject to section 111(d) of the CAA. The EPA also notes that none of the affected EGUs are owned or operated by tribal governments.
As described in sections III.A and XI.F of the preamble to the proposed carbon pollution emission guidelines for existing EGUs (79 FR 34845-34847; June 18, 2014) and sections II.D and VI.F of the preamble to the proposed carbon pollution emission guidelines for existing EGUs in Indian Country and U.S. Territories (79 FR 65489; November 4, 2014), the rule was developed after extensive and vigorous outreach to tribal governments. These tribes expressed varied points of view. Some tribes raised concerns about the impacts of the regulations on EGUs located in their areas of Indian country and the subsequent impact on jobs and revenue for their tribes. Other tribes expressed concern about the impact the regulations would have on the cost of water covered under treaty to their communities as a result of increased costs to the EGU that provide energy to transport the water to the tribes. Other tribes raised concerns about the impacts of climate change on their communities, resources, ways of life and hunting and treaty rights. The tribes were also interested in the scope of the guidelines being considered by the agency (e.g., over what time period, relationship to state and multi-state plans) and how tribes will participate in these planning activities.
The EPA consulted with tribal officials under the EPA Policy on Consultation and Coordination with Indian Tribes early in the process of developing this action to permit them to have meaningful and timely input into its development. A summary of that consultation follows.
Prior to issuing the supplemental proposal on November 4, 2014, the EPA consulted with tribes as follows. The EPA held a consultation with the Ute Tribe, the Crow Nation, and the Mandan, Hidatsa, Arikara (MHA) Nation on July 18, 2014. On August 22, 2014, the EPA held a consultation with the Fort Mojave Tribe. On September 15, 2014, the EPA held a consultation with the Navajo Nation. The Navajo Nation sent a letter to the EPA on September 18, 2014, summarizing the information presented at the consultation and the Navajo Nation's position on the supplemental proposal. One issue raised by tribal officials was the potential impacts of the June 18, 2014 proposal and the supplemental proposal on tribes with budgets that are dependent on revenue from coal mines and power plants, as well as employment at the mines and power plants. The tribes noted the high unemployment rates and lack of access to basic services on their lands. Tribal officials also asked whether the rules will have any impact on a tribe's ability to seek TAS. Tribal officials also expressed interest in agency actions with regard to facilitating power plant compliance with regulatory requirements. The Navajo Nation made the following recommendations in their letter of September 18, 2014: the Navajo Nation supports a mass-based CO2 emission standard based on the highest historical CO2 emissions since 1996; the Navajo Nation requests that the EPA grant the Navajo Nation carbon credits and that the Navajo Nation retains ownership and control of such credits; building block 2 is not appropriate for the Navajo Nation because there are no NGCC plants located on the Navajo Nation; building block 3 is not appropriate for the Navajo Nation because the Navajo people already receive virtually all of their electricity from carbon-free sources (mostly hydroelectric power) and their use of electricity is negligible compared to the generation at the power plants; building block 4 is not appropriate for the Navajo Nation because of the inadequate access to electricity, and the goal should allow for an increase in energy consumption on the Navajo Nation; the supplemental proposal should consider the useful life of the power plants located on the Navajo Nation; and the supplemental proposal should clarify that RE projects located within the Navajo Nation that provide electricity outside the Navajo Nation should be counted toward meeting the relevant state's RE goals under the Clean Power Plan.
After issuing the supplemental proposal, the EPA held additional consultation with tribes. On November 18, 2014, the EPA held consultations with the following tribes: Fort McDowell Yavapai Nation, Fort Mojave Tribe, Hopi Tribe, Navajo Nation, and Ak-Chin Indian Community. A consultation with the Ute Indian Tribe of the Uintah and Ouray Reservation was held on December 16, 2014 and with the Gila River Indian Community on January 15, 2015. The Navajo Nation reiterated the concerns raised during the previous consultation. Several tribes also again indicated that they wanted to ensure they would be included in the development of any tribal or federal plans for areas of Indian country. The Fort Mojave Tribe and the Navajo Nation expressed concern with using data from 2012 as the basis for the goal for their areas of Indian country; in their view, that year was not representative for the affected EGU. On April 28, 2015, the EPA held an additional consultation with the Navajo Nation. The issues raised by the Navajo Nation during the consultation included whether the EPA has the authority to set less stringent standards on a case-by-case basis, and a suggested "parity glide path" that would account and adjust for the very low electricity usage by the Navajo Nation and promote Navajo Nation economic growth and demand.
As required by section 7(a), the EPA's Tribal Consultation Official has certified that the requirements of the executive order have been met in a meaningful and timely manner. A copy of the certification is included in the docket for this action.
7.7	Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks
This action is subject to Executive Order 13045 (62 FR 19885, April 23, 1997) because it is an economically significant regulatory action as defined by Executive Order 12866, and the EPA believes that the environmental health or safety risk addressed by this action has a disproportionate effect on children. Accordingly, the agency has evaluated the environmental health and welfare effects of climate change on children.
CO2 is a potent greenhouse gas that contributes to climate change and is emitted in significant quantities by fossil fuel-fired power plants. The EPA believes that the CO2 emission reductions resulting from implementation of these final guidelines, as well as substantial ozone and PM2.5 emission reductions as a co-benefit, will further improve children's health.
The assessment literature cited in the EPA's 2009 Endangerment Finding concluded that certain populations and lifestages, including children, the elderly, and the poor, are most vulnerable to climate-related health effects. The assessment literature since 2009 strengthens these conclusions by providing more detailed findings regarding these groups' vulnerabilities and the projected impacts they may experience.
These assessments describe how children's unique physiological and developmental factors contribute to making them particularly vulnerable to climate change. Impacts to children are expected from heat waves, air pollution, infectious and waterborne illnesses, and mental health effects resulting from extreme weather events. In addition, children are among those especially susceptible to most allergic diseases, as well as health effects associated with heat waves, storms, and floods. Additional health concerns may arise in low income households, especially those with children, if climate change reduces food availability and increases prices, leading to food insecurity within households.
7.8	Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use
This action, which is a significant regulatory action under EO 12866, is likely to have a significant effect on the supply, distribution, or use of energy. The EPA has prepared a Statement of Energy Effects for this action as follows. We estimate a [X] to [X] percent change in retail electricity prices on average across the contiguous U.S. in [20XX], and a [X] to [X] percent reduction in coal-fired electricity generation as a result of this rule. The EPA projects that utility power sector delivered natural gas prices will increase/decrease by about [X] to [X] percent in [20XX]. For more information on the estimated energy effects, please refer to the economic impact analysis for this proposal. The analysis is presented in more detail in Chapter 3 of this RIA.
7.9	National Technology Transfer and Advancement Act
This rulemaking does not involve technical standards.
7.10	Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations
Executive Order 12898 (59 FR 7629; February 16, 1994) establishes federal executive policy on environmental justice. Its main provision directs federal agencies, to the greatest extent practicable and permitted by law, to make environmental justice part of their mission by identifying and addressing, as appropriate, disproportionately high and adverse human health or environmental effects of their programs, policies and activities on minority populations and low-income populations in the U.S. The EPA defines environmental justice as the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies. The EPA has this goal for all communities and persons across this Nation. It will be achieved when everyone enjoys the same degree of protection from environmental and health hazards and equal access to the decision-making process to have a healthy environment in which to live, learn, and work.
Leading up to this rulemaking the EPA summarized the public health and welfare effects of GHG emissions in its 2009 Endangerment Finding. See, section VIII.A of the preamble where the EPA summarizes the public health and welfare impacts from GHG emissions that were detailed in the 2009 Endangerment Finding under CAA section 202(a)(1). As part of the Endangerment Finding, the Administrator considered climate change risks to minority populations and low-income populations, finding that certain parts of the population may be especially vulnerable based on their characteristics or circumstances. Populations that were found to be particularly vulnerable to climate change risks include the poor, the elderly, the very young, those already in poor health, the disabled, those living alone, and/or indigenous populations dependent on one or a few resources. See sections XII.F and XII.G, above, where the EPA discusses Consultation and Coordination with Tribal Governments and Protection of Children. The Administrator placed weight on the fact that certain groups, including children, the elderly, and the poor, are most vulnerable to climate-related health effects.
The record for the 2009 Endangerment Finding summarizes the strong scientific evidence in the major assessment reports by the U.S. Global Change Research Program (USGCRP), the Intergovernmental Panel on Climate Change (IPCC), and the National Research Council (NRC) of the National Academies that the potential impacts of climate change raise environmental justice issues. These reports concluded that poor communities can be especially vulnerable to climate change impacts because they tend to have more limited adaptive capacities and are more dependent on climate-sensitive resources such as local water and food supplies. In addition, Native American tribal communities possess unique vulnerabilities to climate change, particularly those impacted by degradation of natural and cultural resources within established reservation boundaries and threats to traditional subsistence lifestyles. Tribal communities whose health, economic well-being, and cultural traditions that depend upon the natural environment will likely be affected by the degradation of ecosystem goods and services associated with climate change. The 2009 Endangerment Finding record also specifically noted that Southwest native cultures are especially vulnerable to water quality and availability impacts. Native Alaskan communities are already experiencing disruptive impacts, including coastal erosion and shifts in the range or abundance of wild species crucial to their livelihoods and well-being.
The most recent assessments continue to strengthen scientific understanding of climate change risks to minority populations and low-income populations in the United States. The new assessment literature provides more detailed findings regarding these populations' vulnerabilities and projected impacts they may experience. In addition, the most recent assessment reports provide new information on how some communities of color may be uniquely vulnerable to climate change health impacts in the United States. These reports find that certain climate change related impacts -- including heat waves, degraded air quality, and extreme weather events -- have disproportionate effects on low-income populations and some communities of color, raising environmental justice concerns. Existing health disparities and other inequities in these communities increase their vulnerability to the health effects of climate change. In addition, assessment reports also find that climate change poses particular threats to health, well-being, and ways of life of indigenous peoples in the United States.
As the scientific literature presented above and as the 2009 Endangerment Finding illustrates, low income populations and some communities of color are especially vulnerable to the health and other adverse impacts of climate change. The EPA believes that communities will benefit from this final rulemaking because this action directly addresses the impacts of climate change by limiting GHG emissions through the establishment of CO2 emission guidelines for existing affected fossil fuel-fired EGUs.
In addition to reducing CO2 emissions, the guidelines finalized in this rulemaking would reduce other emissions from affected EGUs that reduce generation due to higher adoption of energy efficiency and renewable energy. These emission reductions will include SO2 and NOx, which form ambient PM2.5 and ozone in the atmosphere, and hazardous air pollutants (HAP), such as mercury and hydrochloric acid. In the final rule revising the annual PM2.5 NAAQS, the EPA identified low-income populations as being a vulnerable population for experiencing adverse health effects related to PM exposures. Low-income populations have been generally found to have a higher prevalence of pre-existing diseases, limited access to medical treatment, and increased nutritional deficiencies, which can increase this population's risk to PM-related and ozone-related effects. Therefore, in areas where this rulemaking reduces exposure to PM2.5, ozone, and methylmercury, low-income populations will also benefit from such emissions reductions. The RIA for this rulemaking, included in the docket for this rulemaking, provides additional information regarding the health and ecosystem effects associated with these emission reductions.
Additionally, as outlined in the community considerations section IX of the preamble, the EPA has put a number of conditions in place to help ensure that this action will not have potential disproportionately high and adverse human health or environmental effects on all communities (low income, communities of color, indigenous populations). As described in the community considerations section of the preamble, the EPA also conducted a proximity analysis, which is available in the docket of this rulemaking.
7.11	Congressional Review Act (CRA)
This final action is subject to the CRA, and the EPA will submit a rule report to each House of the Congress and to the Comptroller General of the United States. This action is a "major rule" as defined by 5 U.S.C. 804(2).

Chapter 8: Comparison of Benefits and Costs
8.1	Comparison of Benefits and Costs
The benefits, costs, and net benefits of the illustrative plan scenarios are presented in this chapter of the Regulatory Impact Analysis (RIA) for the Final Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electric Utility Generating Units. As discussed in Chapter 1, the EPA is establishing carbon dioxide (CO2) emission performance rates for two source categories of existing fossil fuel-fired EGUs, fossil fuel-fired electric utility steam generating units and stationary combustion turbines. Given the flexibilities afforded states in complying with the emission guidelines, the benefits, cost and economic impacts reported in this RIA are not definitive estimates, but are instead illustrative of plan approaches states may take.
The EPA has used the social cost of carbon estimates presented in the Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 (May 2013, Revised June 2015) ("current SC-CO2 TSD") to analyze CO2 climate impacts of this rulemaking. We refer to these estimates, which were developed by the U.S. government, as "SC-CO2 estimates." The SC-CO2 is an estimate of the monetary value of impacts associated with a marginal change in CO2 emissions in a given year. The four SC-CO2 estimates are associated with different discount rates (model average at 2.5 percent discount rate, 3 percent, and 5 percent; 95[th] percentile at 3 percent), and each increases over time. In this comparison of benefits and costs, the EPA provides the estimate of climate benefits associated with the SC-CO2 value deemed to be central in the current SC-CO2 TSD (the model average at 3% discount rate). In addition to reducing CO2 emissions, implementing these final emission guidelines is expected to reduce emissions of SO2 and NOX, which are precursors to formation of ambient PM2.5, as well as directly emitted fine particles. Therefore, reducing these emissions would also reduce human exposure to ambient PM2.5 and ozone precursors, and the associated PM2.5 and ozone related health effects. Tables 8-1 and 8-2 provide a summary of the climate benefits, air quality co-benefits, and costs for the illustrative rate-based and mass-based plan scenarios.
The EPA could not monetize important categories of impacts. Due to current data and modeling limitations, our estimates of the benefits from reducing CO2 emissions do not include important impacts like ocean acidification or potential tipping points in natural or managed ecosystems. Unquantified impacts also include those associated with changes in emissions of other pollutants that affect the climate, such as methane. In addition, the analysis does not quantify co-benefits from reducing exposure to SO2, NOx, and hazardous air pollutants (e.g., mercury and hydrogen chloride), as well as ecosystem effects and visibility impairment.
Based upon the foregoing discussion, it remains clear that this final rule's combined climate benefits and human health co-benefits associated with the reduction in other air pollutants substantially outweigh the illustrative plan scenario costs.

Table 8-1.	Monetized Benefits, Costs, and Net Benefits Under the Rate-based Illustrative Plan Approach (billions of 2011$)[a]

                              Rate-Based Scenario

                                     2020
                                     2025
                                     2030
Climate Benefits [b]

                               5% discount rate
                                    $0.80
                                     $3.1
                                     $6.4
                               3% discount rate
                                     $2.8
                                     $10
                                     $20
                              2.5% discount rate
                                     $4.1
                                     $15
                                     $29
                      95th percentile at 3% discount rate
                                     $8.2
                                     $31
                                     $61

                     Air Quality Co-benefits Discount Rate

                                      3%
                                      7%
                                      3%
                                      7%
                                      3%
                                      7%
Air Quality Health Co-benefits [c]
                                 $0.7 to $1.8
                                 $0.6 to $1.7
                                  $7.4 to $18
                                  $6.7 to $16
                                  $14 to $34
                                  $13 to $31
Compliance Costs [d]
                                     $2.4
                                     $1.16
                                     $8.4
Net Benefits [e]
                                 $1.1 to $2.2
                                 $1.0 to $2.1
                                  $17 to $27
                                  $16 to $25
                                  $26 to $46
                                  $25 to $43
Non-Monetized Benefits
                        Non-monetized climate benefits

                 Reductions in exposure to ambient NO2 and SO2

                       Reductions in mercury deposition

Ecosystem benefits associated with reductions in emissions of NOX, SO2, PM, and mercury

                            Visibility improvement

[a] All are rounded to two significant figures, so figures may not sum.
[b] The climate benefit estimate in this summary table reflects global impacts from CO2 emission changes and does not account for changes in non-CO2 GHG emissions. Also, different discount rates are applied to SC-CO2 than to the other estimates because CO2 emissions are long-lived and subsequent damages occur over many years. The benefit estimates in this table are based on the average SC-CO2 estimated for a 3% discount rate, however we emphasize the importance and value of considering the full range of SC-CO2 values. As shown in the RIA, climate benefits are also estimated using the other three SC-CO2 estimates (model average at 2.5 percent discount rate, 3 percent, and 5 percent; 95[th] percentile at 3 percent). The SC-CO2 estimates are year-specific and increase over time.
[c] The air quality health co-benefits reflect reduced exposure to PM2.5 and ozone associated with emission reductions of directly emitted PM2.5, SO2 and NOX. The range reflects the use of concentration-response functions from different epidemiology studies. The reduction in premature fatalities each year accounts for over 98 percent of total monetized co-benefits from PM2.5 and ozone. These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality because the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type.
d Total costs are approximated by the illustrative plan scenario costs estimated using the Integrated Planning Model for the proposed guidelines and a discount rate of approximately 5 percent. This estimate includes monitoring, recordkeeping, and reporting costs and demand side energy efficiency program and participant costs.
[e] The estimates of net benefits in this summary table are calculated using the global SC-CO2 at a 3 percent discount rate (model average). The RIA includes combined climate and health estimates based on additional discount rates.
[f] Estimates in the table are presented for three analytical years with air quality co-benefits calculated using two discount rates. The estimates of co-benefits are annual estimates in each of the analytical years, reflecting discounting of mortality benefits over the cessation lag between changes in PM2.5 concentrations and changes in risks of premature death (see RIA Chapter 4 for more details), and discounting of morbidity benefits due to the multiple years of costs associated with some illnesses. The estimates are not the present value of the benefits of the rule over the full compliance period.
Table 8-2.	Monetized Benefits, Costs, and Net Benefits Under the Mass-based Illustrative Plan Approach Scenario (billions of 2011$) [a]

                              Mass-Based Scenario

                                     2020
                                     2025
                                     2030
Climate Benefits [b]

                               5% discount rate
                                     $[X]
                                     $[X]
                                     $[X]
                               3% discount rate
                                     $[X]
                                     $[X]
                                     $[X]
                              2.5% discount rate
                                     $[X]
                                     $[X]
                                     $[X]
                      95th percentile at 3% discount rate
                                     $[X]
                                     $[X]
                                     $[X]

                     Air Quality Co-benefits Discount Rate

                                      3%
                                      7%
                                      3%
                                      7%
                                      3%
                                      7%
Air Quality Health Co-benefits [c]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
Costs [d]
                                     $[X]
                                     $[X]
                                     $[X]
Net Benefits [e]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
                                 $[X] to $[X]
Non-Monetized Benefits
                        Non-monetized climate benefits

                 Reductions in exposure to ambient NO2 and SO2

                       Reductions in mercury deposition

Ecosystem benefits associated with reductions in emissions of NOX, SO2, PM, and mercury

                            Visibility improvement

[a] All are rounded to two significant figures, so figures may not sum.
[b] The climate benefit estimate in this summary table reflects global impacts from CO2 emission changes and does not account for changes in non-CO2 GHG emissions. Also, different discount rates are applied to SC-CO2 than to the other estimates because CO2 emissions are long-lived and subsequent damages occur over many years. The benefit estimates in this table are based on the average SC-CO2 estimated for a 3% discount rate, however we emphasize the importance and value of considering the full range of SC-CO2 values. As shown in the RIA, climate benefits are also estimated using the other three SC-CO2 estimates (model average at 2.5 percent discount rate, 3 percent, and 5 percent; 95[th] percentile at 3 percent). The SC-CO2 estimates are year-specific and increase over time.
[c] The air quality health co-benefits reflect reduced exposure to PM2.5 and ozone associated with emission reductions of directly emitted PM2.5, SO2 and NOX. The range reflects the use of concentration-response functions from different epidemiology studies. The reduction in premature fatalities each year accounts for over 98 percent of total monetized co-benefits from PM2.5 and ozone. These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality because the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type.
[d] Total costs are approximated by the illustrative plan scenario costs estimated using the Integrated Planning Model for the proposed guidelines and a discount rate of approximately 5 percent. This estimate includes monitoring, recordkeeping, and reporting costs and demand side energy efficiency program and participant costs.
[e] The estimates of net benefits in this summary table are calculated using the global SC-CO2 at a 3 percent discount rate (model average). The RIA includes combined climate and health estimates based on additional discount rates.
[f] Estimates in the table are presented for three analytical years with air quality co-benefits calculated using two discount rates.  The estimates of co-benefits are annual estimates in each of the analytical years, reflecting discounting of mortality benefits over the cessation lag between changes in PM2.5 concentrations and changes in risks of premature death (see RIA Chapter 4 for more details), and discounting of morbidity benefits due to the multiple years of costs associated with some illnesses.  The estimates are not the present value of the benefits of the rule over the full compliance period.
8.2	Uncertainty Analysis
The Office of Management and Budget's circular Regulatory Analysis (Circular A-4) provides guidance on the preparation of regulatory analyses required under E.O. 12866, and requires an uncertainty analysis for rules with annual benefits or costs of $1 billion or more. This final rulemaking surpasses that threshold for both benefits and costs. Throughout the RIA, we considered a number of sources of uncertainty, both quantitatively and qualitatively, on benefits and costs. We summarize three key elements of our analysis of uncertainty here:
   * Evaluating uncertainty in the illustrative plan approaches that states will implement, which influences both costs and benefits.
   * Assess uncertainty in the methods used to calculate the health co-benefits associated with the reduction in PM2.5 and ozone and the use of a benefits-per-ton approach in estimating these co-benefits.
   * Characterizing uncertainty in monetizing climate-related benefits.
Some of these elements are evaluated using probabilistic techniques, whereas for others the underlying likelihoods of certain outcomes are unknown and we use scenario analysis to evaluate their potential effect on the benefits and costs of this rulemaking.
8.2.1	Uncertainty in Costs and Illustrative Plan Approaches
The calculation of the state goals is based on an evaluation of methods for reducing the carbon emissions intensity of electricity generation that may be achieved at reasonable cost. Our best estimates of the costs of these methods of intensity reduction are reported within the cost analysis of this rule and are included in the cost modeling in the RIA.
A significant source of uncertainty under this regulation is the ultimate approach states will take to comply with the guidelines, which will affect both the costs and benefits of this rule. For this reason we modeled two potential illustrative plan scenarios for each regulatory option: the rate-based illustrative plan scenario and the mass-based illustrative plan scenario. The cost...
The reductions of CO2 and other pollutants from fossil fuel combustion....
However, from this analysis we see that the net benefits of the two scenarios, given consistent assumptions,
8.2.2	Uncertainty Associated with Estimating the Social Cost of Carbon
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 (IAM) 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. Currently 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. 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) concluded that "It is very likely that [SC-CO2 estimates] underestimate the damage costs because they cannot include many non-quantifiable impacts" and the IPCC Fifth Assessment report observed that SC-CO2 estimates continue to omit various impacts that would likely increase damages. The 95[th] percentile estimate was included in the recommended range for regulatory impact analysis, in part, to address these concerns.
The modeling underlying the development of the SC-CO2 estimates addressed uncertainty in several ways. An ensemble of three IAMs were used to generate the SC-CO2 estimates to capture differences in model structures that, in part, reflect uncertainty in the scientific literature about these relationships. Parametric uncertainty was explicitly addressed in each IAM, though to differing degrees, through Monte Carlo simulations in which explicit probability distributions for key parameters were specified, including the equilibrium climate sensitivity, which represents the long-run responsiveness of the climate to increasing GHG concentrations. Furthermore, the analysis considered five different socioeconomic and emissions forecasts to capture the sensitivity of the SC-CO2 estimates to key exogenous projections used in the modeling. Finally, the results were calculated for three discount rates, which were selected, in part, to reflect uncertainty about how interest rates may change over time and the possibility that climate damages are positively correlated with uncertain future economic activity. This analysis produced 45 different distributions of the SC-CO2 estimates for each emissions year. To produce a range of plausible estimates that are manageable in regulatory analysis but still reflects the uncertainty in the results four point estimates were recommended. The use of this range of point estimates in this rulemaking helps to reflect the uncertainty in the SC-CO2 estimates. Chapter 4 of this RIA provides a comprehensive discussion about the methodology and application of the SC-CO2; see both the 2010 TSD and current SC-CO2 TSD for a full description.
In addition, OMB's Office of Information and Regulatory Affairs received comments regarding uncertainty and the SC-CO2 estimates in response to a separate request for public comment on the approach used to develop the estimates. Commenters discussed the analyses and presentation of uncertainty in the TSD as well as the implications of uncertainty for use of the SC-CO2 estimates in regulatory impact analysis. In their response, the interagency working group (IWG) acknowledged uncertainty in the SC-CO2 estimates but disagreed with commenters that suggested the uncertainty undermines use of the SC-CO2 estimates in regulatory impact analysis. The IWG went on to note that the uncertainty in the SC-CO2 estimates is fully acknowledged and comprehensively discussed in the TSDs and supporting academic literature, and that while all regulatory impact analysis involves uncertainty, these analyses can provide useful information to decision makers and the public. See the IWG Response to Comments for the complete response.
8.2.3	Uncertainty Associated with PM2.5 and Ozone Health Co-Benefits Assessment
Our estimate of the total monetized co-benefits is based on EPA's interpretation of the best available scientific literature and methods and supported by the SAB-HES and the National Academies of Science (NRC, 2002). Below are key assumptions underlying the estimates for PM2.5-related premature mortality, which accounts for 98 percent of the monetized PM2.5 health co-benefits:
          We assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM2.5 varies considerably in composition across sources, but the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type. The PM ISA concluded that "many constituents of PM2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific outcomes" (U.S. EPA, 2009).
          We assume that the health impact function for fine particles is log-linear without a threshold in this analysis. Thus, the estimates include health co-benefits from reducing fine particles in areas with varied concentrations of PM2.5, including both areas that do not meet the fine particle standard and those areas that are in attainment, down to the lowest modeled concentrations.
          We assume that there is a "cessation" lag between the change in PM exposures and the total realization of changes in mortality effects. Specifically, we assume that some of the incidences of premature mortality related to PM - 2.5 exposures occur in a distributed fashion over the 20 years following exposure based on the advice of the SAB-HES (U.S. EPA-SAB, 2004), which affects the valuation of mortality co-benefits at different discount rates. EPA quantitatively assessed uncertainty in the air quality health co-benefits, including probabilistic approaches.
In addition, EPA provides the 95[th] percentile confidence interval for avoided PM-related premature deaths and the associated economic valuation using two key epidemiology studies. EPA provides the PM-related results using alternate concentration-response relationship provided by an expert elicitation and alternate ozone-related results using concentration-response relationships provided by alternate epidemiology studies. In addition, we include an assessment of the distribution of population exposure in the modeling underlying the benefit-per-ton estimates. For further discussion and characterization of those uncertainties influencing the benefit assessment, see Chapter 4 of this RIA.
As noted and described in Chapter 4 of this RIA, we use a benefit-per-ton approach to quantify health co-benefits. All benefit-per-ton have inherent limitations, including that the estimates reflect the geographic distribution of the modeled sector emissions, which may not match the emission reductions anticipated by the final emission guidelines, and they may not reflect local variability in population density, meteorology, exposure, baseline health incidence rates, or other local factors for any specific location. In addition, these estimates reflect the regional average benefit-per-ton for each ambient PM2.5 precursor emitted from EGUs, which assumes a linear atmospheric response to emission reductions. The regional benefit-per-ton estimates, although less subject to these types of uncertainties than national estimates, still should be interpreted with caution. Even though we assume that all fine particles have equivalent health effects, the benefit-per-ton estimates vary between precursors depending on the location and magnitude of their impact on PM2.5 levels, which drive population exposure.
8.3	References
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 IPCC. Available at <http://www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_synthesis_report.htm>. Accessed June 6, 2015.
National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations. National Academies Press. Washington, DC.
U.S. Environmental Protection Agency -- Science Advisory Board (U.S. EPA-SAB). 2004. Advisory Council on Clean Air Compliance Analysis Response to Agency Request on Cessation Lag. EPA-COUNCIL-LTR-05-001. December. Available at <http://yosemite.epa.gov/sab/sabproduct.nsf/0/39F44B098DB49F3C85257170005293E0/$File/council_ltr_05_001.pdf>. Accessed June 4, 2015.
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, Research Triangle Park, NC. Available at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. Accessed June 4, 2015.

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United States
Environmental Protection Agency
                 Office of Air Quality Planning and Standards
                   Health and Environmental Impacts Division
                          Research Triangle Park, NC
                                                                Publication No.
                                                               EPA-452/R-15-003
                                                                      July 2015