On the other hand, while the scale of environmental regulation often is not sufficient to influence government spending and investment demand, the Leontief structure for intermediate goods and its assumption of fixed investment and government spending may make the Multimarket Model less responsive to regulatory shocks.   Given the competing sources of bias, the ultimate direction of the bias with regards to economic impacts and social costs is difficult to ascertain a priori.

 8.1.2	Economic Impact Analysis Results
Market-Level Results
Market-level impacts include price and quantity adjustments including the changes in international trade (Table 8-1).For the final Transport Rule, , the Agency's economic model suggests the average national price increase for energy is 0.16%.  Higher energy costs result in subsequent manufacturing sector price increases nationwide of 0.01% or less.  Imports also slightly rise because of higher U.S. prices. The one exception is transportation services; since sectors using transportation services are producing less, the demand for transportation services declines.  The size of the transportation services demand shift outweighs any supply side cost increases that place upward pressure on service prices (e.g. higher electricity and refined petroleum prices).  As a result, the average transportation services price falls.
 Social Cost Estimates of Transport Rule
In the short run, the Agency's partial equilibrium multi-market model suggests that industries are able to pass on $0.7 billion (2007$) of the Transport Rule's costs to U.S. households in the form of higher prices (Table 8-2). Existing U.S. industries' surplus falls by $0.2 billion and the net U.S. loss in aggregate, is $0.9 billion (2007$).  This is slightly higher than the annualized nationwide compliance cost estimate of the final rule as shown in Chapter 7 of the RIA because it excludes gains to other countries discussed below.

Table 8-1.	Short-Term Market-Level Changes (in percent) within the U.S. Economy in 2014
                                Industry Sector
                                  U.S. Prices
                                U.S. Production
                                    Imports
                               U.S. Consumption
                                    Exports
Energy
                                                                        -0.163%
                                                                        -0.031%
0.009%

                                                                        -0.016%
                                                                        -0.031%
    Coal
                                    -0.017
                                    -0.047
                                    -0.048
                                    -0.052
                                     0.003
    Crude Oil Extraction
                                     0.004
                                    -0.053
                                     0.027
                                   −0.003
                                     0.000
    Electric generation
                                     0.770
                                    -0.059
                                     0.000
                                    -0.059
                                    -0.137
    Natural Gas
                                     0.004
                                    -0.033
                                     0.057
                                    -0.018
                                    -0.002
    Refined Petroleum
                                     0.002
                                    -0.002
                                     0.003
                                    -0.001
                                    -0.0002
Nonmanufacturing
                                                                        0.0004
                                                                         -0.002
                                                                          0.001
                                                                        -0.0016
                                                                         -0.001
Manufacturing

Food, beverages, and textiles
                                                                          0.004
                                                                         -0.005
                                                                          0.006
                                                                         -0.003
                                                                         -0.003
Lumber, paper, and printing
                                                                          0.008
                                                                         -0.005
                                                                          0.009
                                                                         -0.003
                                                                         -0.006
Chemicals
                                                                          0.002
                                                                         -0.006
                                                                          0.003
                                                                         -0.003
                                                                         -0.002
Plastics and Rubber
                                                                          0.005
                                                                         -0.006
                                                                          0.008
                                                                       −0.003
                                                                         -0.005
Nonmetallic Minerals
                                                                          0.009
                                                                       −0.006
                                                                          0.011
                                                                         -0.003
                                                                         -0.009
Primary Metals
                                                                          0.007
                                                                       −0.007
                                                                          0.007
                                                                         -0.004
                                                                       −0.007
Fabricated Metals
                                                                          0.006
                                                                         -0.002
                                                                          0.007
                                                                       −0.002
                                                                         -0.003
Machinery and Equipment
                                                                         0.0007
                                                                         -0.002
                                                                         0.0005
                                                                         -0.002
                                                                        -0.0008
Electronic Equipment
                                                                         0.0007
                                                                         -0.002
                                                                         0.0007
                                                                         -0.002
                                                                         -0.001
Transportation Equipment
                                                                         0.0008
          -0.003
                                                                          0.001
                                                                         -0.002
                                                                         -0.001
Other
                                                                          0.002
                                                                         -0.007
                                                                          0.004
                                                                         -0.003
                                                                         -0.003
Wholesale and Retail Trade
                                                                          0.001
                                                                       −0.002
                                                                          0.001
                                                                         -0.002
                                                                         -0.002
Transportation Services
                                                                         -0.003
                                                                       −0.003
                                                                       −0.003
                                                                         -0.003
                                                                          0.003
Other Services
                                                                          0.001
                                                                       −0.002
                                                                         0.0007
                                                                         -0.002
                                                                         -0.001
Note:  Approximated using the IPM cost analysis. For example, with the $0.8 billion increase in costs for the electric power sector, IPM projects a 0.77 percent increase in the retail price of electricity in 2015.  All other energy market-level changes are determined within the multimarket model.  Appendix B provides additional details.
As U.S. prices rise, other countries are affected through international trade relationships. The price of goods produced in the United States increase, domestic exports decline, and domestic production is replaced to a certain degree by imports; the model estimates a net gain of about $0.04 billion for other countries. The net change in total surplus is lower than the annualized nationwide compliance cost estimate of the final rule as shown in Chapter 7 of the RIA. Our estimate of social costs for the rule incorporates the net change in total surplus, and this estimate is $0.81 billion (2007 dollars) as shown in Table 8-2, or nearly identical to the compliance costs.  Compliance costs based on the pre-policy output levels would be overstated if we do not consider the new lower levels of consumption as a result of higher market prices.

Table 8-2.	Distribution of Social Costs (billions, 2007$): 2015
  Change in U.S. consumer surplus

−$0.68
  Change in U.S. producer surplus

−$0.17
Net Change in U.S. Surplus

−$0.85
  Net change in rest of world surplus

$0.04
Net change in Total Surplus

−0.81$

The surplus losses are concentrated in the electric generation sector (percent) and other services (percent).  Other services include information, finance and insurance, real estate, professional services, management, administrative services, education, health care, arts, accommodations, and public services.  Although electricity costs represent a small share of total service industry production costs, the service sectors represent a significant economic sector within the U.S. economy and use a large amount of electricity.  The transition or short-term evaluation using a partial equilibrium model does not allow for resources to be allocated according to price changes.  So the results of the model do not capture any distortions in the economy that may results as the price of electricity changes.  If the distortions are significant, the "true" social cost would be higher than the compliance cost and the results of this partial equilibrium model.
 8.1.3	Alternative Approach to Estimating Social Cost
In the Transport Rule proposed last summer, EPA used a different model to estimate the social cost of the regulatory approach than applied in this RIA.  That model, EPA's Economic Model for Policy Analysis (EMPAX), is a computable general equilibrium model (CGE) which dynamically cascades the cost of a regulation through the entire economy.  However, since that rule was proposed, an updated version of EMPAX was used to estimate the social cost of the Clean Air Act in a new EPA report entitled "The Benefits and Costs of the Clean Air Act from 1990 to 2020. This report is available at http://www.epa.gov/air/sect812/feb11/fullreport.pdf.
This updated version of EMPAX added in the benefit-side effects (incorporating labor-force and health care expenditures) which significantly changed the social cost estimate from the previous edition.  In December 2010, EPA's Science Advisory Board (SAB) found that  "The inclusion of benefit-side effects (reductions in mortality, morbidity, and health-care expenditures) in a computable general equilibrium (CGE) model represents a significant step forward in benefit-cost analysis." http://yosemite.epa.gov/sab/sabproduct.nsf/1E6218DE3BFF682E852577FB005D46F1/$File/EPA-COUNCIL-11-001-unsigned.pdf.  A description of the changes to the model and implications are covered in detail in chapter 8 of the section 812 report.  EPA has determined that it needs to update the EMPAX model version used for RIAs to add this benefit-side effect prior to use in any additional regulatory analysis.  In addition, the total nationwide annual compliance costs of the Transport Rule are now much lower than estimated for the proposal, and now are low enough so that EMPAX may not be as appropriate a model to use to for social costs and other economic impact estimation for this final rule.  With the benefit-side effects updates now in the process of being incorporated into the model in response to SAB's guidance, and the relatively low nationwide annual compliance cost incurred by the electric power sector for this final rule as mentioned earlier in this RIA,  EPA will not use EMPAX for this final RIA. Once those benefits are accounted for in the social cost estimate from EMPAX, they will not be included in the reported estimate of total benefits to avoid double-counting.

8.2	Employment Impacts for the Transport Rule
In addition to addressing the costs and benefits of the Transport Rule, EPA has estimated the impacts of this rulemaking on labor demand, and the results are presented in this section. While a standalone analysis of employment impacts is not included in a standard cost-benefit analysis, such an analysis is of particular concern in the current economic climate. Executive Order 13563, states, "Our regulatory system must protect public health, welfare, safety, and our environment while promoting economic growth, innovation, competitiveness, and job creation" (emphasis added).  Therefore, we have provided this analysis to inform the discussion of labor demand and job impacts.  We provide an estimate of the employment impacts on the regulated industry over time.  We also provide the short-term employment impacts (increase in labor demand) associated with the construction of needed pollution control equipment.
We have not quantified the rule's effects on all labor in other sectors not regulated by this rule, or the effects induced by changes in workers' incomes.  What follows is an overview of the various ways that environmental regulation can affect employment, followed by a discussion of the estimated impacts of this rule.  EPA continues to explore the relevant theoretical and empirical literature and seeks public comment in order to ensure that such estimates are as accurate, useful and informative as possible.
From an economic perspective, labor is an input into producing goods and services; if regulation requires that more labor be used to produce a given amount of output, that additional labor is reflected in an increase in the cost of production.  Moreover, when the economy is at full employment, we would not expect an environmental regulation to have an impact on overall employment since labor is being shifted from one sector to another. On the other hand, in periods of high unemployment, an increase in labor demand due to regulation may result in a net increase in overall employment. With significant numbers of workers unemployed, the opportunity costs associated with displacing jobs in other sectors are likely to be much smaller.
To provide a partial picture of the employment consequences of this rule, EPA takes two approaches.  First, the analysis uses the results of Morgenstern, Pizer, and Shih (2002) to estimate the effects of the regulation on the regulated industry, the electric power industry in this case.  This approach has been used by EPA in recent Regulatory Impact Analyses.  (See, for example, the Regulatory Impact Analysis for the recently finalized Industrial Boilers and Commercial and Institutional Solid Waste (CISWI) rulemakings, promulgated on February 21, 2011).  Second, EPA uses projections from IPM to estimate the short-term employment effects resulting from construction and resource requirements as a result of the additional demand for pollution control equipment.  Historically, EPA has only reported employment impacts on a few regulations.  Section 8.3 discusses the estimates of the employment consequences in the electricity sector, using the Morgenstern, et al. approach.  Section 8.4 estimates the employment effects in the environmental protection sector, using the second approach.

8.3	Employment Impacts primarily on the regulated industry: Morgenstern, Pizer, and Shih (2002)
EPA examined possible employment effects within the electric utility sector using a peer-reviewed, published study that explores historical relationships between industrial employment and environmental regulations (Morgenstern, Pizer, and Shih, 2002).  The fundamental insight of Morgenstern, et al. is that environmental regulations can be understood as requiring regulated firms to add a new output (environmental quality) to their product mixes. Although legally compelled to satisfy this new demand, regulated firms have to finance this additional production with the proceeds of sales of their other (market) products. Satisfying this new demand requires additional inputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms in their production processes.
Thus, Morgenstern et al. decompose the overall effect of a regulation on employment into the following three subcomponents:
         The "Demand Effect": higher production costs raise market prices, reducing consumption (and production), thereby reducing demand for labor within the regulated industry [;]
         The "Cost Effect": As production costs increase, plants use more of all inputs, including labor, to maintain a given level of output.  For example, in order to reduce pollutant emissions while holding output levels constant, regulated firms may require additional labor;
         The "Factor-Shift Effect": Regulated firms' production technologies may be more or less labor intensive after complying with a regulation (i.e., more/less labor is required per dollar of output).
         Decomposing the overall employment impact of environmental regulation into three subcomponents clarifies the conceptual relationship between environmental regulation and employment in regulated sectors, and permitted Morgenstern, et al. to provide an empirical estimate of the net impact. For present purposes, the net effect is of particular interest, and is the focus of our analysis.
Using plant-level Census information between the years 1979 and 1991, Morgenstern et al. estimate the size of each effect for four polluting and regulated industries (petroleum, plastic material, pulp and paper, and steel). On average across the four industries, each additional $1 million ($1987) spending on pollution abatement results in a (statistically insignificant) net increase of 1.55 (+/- 2.24) jobs. As a result, the authors conclude that increases in pollution abatement expenditures do not necessarily cause economically significant employment changes. The conclusion is similar to Berman and Bui (2001) who found that increased air quality regulation in Los Angeles did not cause in large employment changes.
Since the Morgenstern, et al. parameter estimates are expressed in jobs per million ($1987) of environmental compliance expenditures, their study offers a transparent and simple way to transfer estimates for other employment analysis. For each of the three job effects outlined above, EPA used the Morgenstern et al. four industry average parameters and standard errors along with the estimated private compliance costs to provide a range of electricity sector employment effects associated with the Transport Rule.
By applying these estimates to pollution abatement costs for the final rule for the electric power sector, we estimated each effect. The results are
         Demand effect:  −to + jobs in the directly affected sector with a central estimate of −;
         Cost effect:  + to + jobs in the directly affected sector with a central estimate of +; and
         Factor-shift effect:  + to + jobs in the directly affected sector with a central estimate of +.
         EPA estimates the net employment effect to range from -  to + jobs in the directly affected sector with a central estimate of +. ,
These estimates are shown in Table 8-3.
Table 8-3.	Employment Impacts Using Peer-Reviewed Study

                   Estimates using Morgenstern et al. (2002)

                                 Demand Effect
                                  Cost Effect
                              Factor Shift Effect

                                  Net Effect
Change in Full-Time Jobs per Million Dollars of Environmental Expenditure[a]
                                    −3.56
                                     2.42
                                     2.68
                                     1.55
Standard Error
                                     2.03
                                     0.83
                                     1.35

                                     2.24
EPA estimate for Transport Rule[b]
                                +200 to -3,000
                                 +400 to 2,000
                                  0 to +2,000
                                -1,000 to 3,000
[a] Expressed in 1987 dollars. See footnote 8 for inflation adjustment factor used in the analysis.
[b] According to the 2007 Economic Census, the electric power generation, transmission and distribution sector (NAICS 2211) had approximately 510,000 paid employees.  Both the midpoint and range for each effect are reported in the last row of the table.
All ranges for these job changes are based on the 95[th] percentile of results.  EPA recognizes there may be other employment effects which are not considered in the Morgenstern et al. study. For example, employment in environmental protection industries may increase as firms purchase more pollution control equipment and services to meet the rule's requirements. EPA does provide such an estimate of employment change later in this section in a separate analysis. On the other hand, industries that use electricity will face higher electricity prices as the result of the transport rule, reduce output, and demand less labor. We do not currently have sufficient information to quantify these as potential employment gains or losses.
8.3.1	Limitations
Although the Morgenstern et al. paper provides information about the potential job effects of environmental protection programs, there are several caveats associated with using those estimates to analyze the final rule. First, the Morgenstern et al. estimates presented in Table 8-3 and used in EPA's analysis represent the weighted average parameter estimates for a set of manufacturing industries (pulp and paper, plastics, petroleum, and steel). Morgenstern, et al. present those industries' estimates separately, and they range from -1.13 jobs per $1 million (in 1987 dollars) of environmental expenditures for pulp and paper, to +6.90 jobs for plastics.  Only two of the total jobs estimates are statistically significantly different from zero, and the overall weighted average used here, 1.55 jobs per $1 million, is not statistically significant.  Moreover, here we are applying the estimate to the electricity generating industry.
Second, relying on Morgenstern et al. implicitly assumes that estimates derived from 1979 - 1991 data are still applicable.  Third, the methodology used in Morgenstern et al. assumes that regulations affect plants in proportion to their total costs. In other words, each additional dollar of regulatory burden affects a plant by an amount equal to that plant's total costs relative to the aggregate industry costs. By transferring the estimates, EPA assumes a similar distribution of regulatory costs by plant size and that the regulatory burden does not disproportionately fall on smaller or larger plants.
8.4	Employment Impacts of the Transport Rule - Environmental Protection Sector Approach, by 2014
The Transport Rule will require additional pollution control equipment and services in order to reduce emissions from the power sector and address nonattainment and the transport of air emissions cross state borders.  Historically, new categories of employment have been created in the process of implementing regulations to make our air safer to breathe.  When a regulation is promulgated, the first response of industry is to order pollution control equipment and services in order to comply with the regulation when it becomes effective.  Revenue and employment in the environmental technology industry have grown steadily between 2000 and 2008, reaching an industry total of approximately $300 billion in revenues and 1.7 million employees in 2008.  While these revenues and employment figures represent gains for the environmental technologies industry, they are costs to the regulated industries required to install the equipment.  Moreover, it is not clear the 1.7 million employees in 2008 represent anything other than workers diverted from other productive employment as opposed to new additional employment.
Regulated firms hire workers to design and construct pollution control equipment.  Once the equipment is installed, regulated firms hire workers to operate and maintain the pollution control equipment  -  much like they hire workers to produce more output.  A study by Resources for the Future examined how regulated industries respond to regulation.  They found that on average, employment goes up in regulated firms.  Of course, these firms may also reassign existing employees to do these activities.
Environmental regulations support employment in many basic industries. In addition to the increase in employment in the environmental protection industry (increased orders for pollution control equipment), environmental regulations also support employment in industries that provide intermediate goods to the environmental protection industry.  For example, $1 billion in capital expenditures to reduce air pollution involves the purchase of abatement equipment. The equipment manufacturers, in turn, order steel, tanks, vessels, blowers, pumps, and chemicals to manufacture and install the equipment.
A study (2008) by Bezdek, Wendling, and DiPernab found that "investments in environmental protection industries create jobs and displace jobs, but the net effect on employment is positive."
The focus of this part of the employment analysis is on short-term jobs related to the compliance actions of the affected entities and includes estimates of the employment impacts due to the increased demand for pollution control equipment.   Results indicate that the Transport Rule has the potential to result in a net increase of labor in these industries, driven by the increased demand for new pollution controls.  Overall, the preliminary results of the environmental protection sector approach indicate that the Transport Rule could support an increase of about 2,230 job-years by 2014.
8.4.1	Overall Approach and Methodology for Environmental Protection Sector Approach
EPA commissioned ICF International to provide estimates for the Environmental Protection Sector, and the analysis utilizes a bottom-up engineering based methodology combined with macroeconomic data on industrial output and productivity, to estimate employment impacts.  It relies on projections from the IPM model and projections for new pollution control equipment and related costs, along with data from the Bureau of Labor Statistics and other sources.  The approach also relies upon prior EPA studies on similar issues, and in particular uses data and information from an extensive resource study conducted in 2002, which was updated in the Spring of 2011 and reflects more recent information.  The approach involves using IPM projected results from the Transport Rule analysis for the set of pollution control technologies expected to be installed to comply with the rule, along with data from secondary sources, to estimate the job impacts using this approach.  This includes the labor needed to design, manufacture and install the needed pollution control equipment over the years leading up to compliance in 2014.
For construction labor, the labor needs are derived from the 2002 EPA resource analysis for installing various retrofits (FGD  -  Flue Gas Desulfurization scrubbers, SCR- selective catalytic reduction, and DSI -  dry sorbent injection) and are further classified into different labor categories, such as boilermakers, engineers and a catch-all "other installation labor."  For the inputs needed (e.g., steel), the 2002 resource study was used to determine the steel demand for each MW of additional pollution control and combined with labor productivity data from the Economic Census and BLS for relevant industries.
More detail on methodology, assumptions, and data sources can be found in Appendix D of this RIA - "Employment Estimates of Direct Labor in Response to the Transport Rule in 2014."
Projections from IPM were used to estimate the incremental retrofit capacities projected in response to the final rule.  These additional pollution controls are shown in Table 8-4 below, and reflect the added pollution controls needed to meet the requirements of the rule.  Additional information on the power sector impacts can be found in Chapter 7 of the RIA.
Table 8-4.	Increased Pollution Control Demand due to the Transport Rule, by 2014 (GW)
Retrofit Type
                     Existing Controls Induced to Operate
                             Newly Built Controls
FGD
                                      25
                                       6
SCR
                                       5
                                       0
DSI
                                       0
                                       3

8.4.2	Summary of Employment Estimates from Environmental Protection Sector Approach
Table 8-5 presents additional detail on the estimated employment impacts using the environmental protection sector approach resulting from the Transport Rule.  Results for the Environmental Protection Sector Approach indicate the Transport Rule could support or create roughly 2,230 one-time job-years of increased demand for direct labor, driven by the need to design and build the pollution control equipment.

Table 8-5.	Employment Effects Using the Environmental Protection Sector Approach for the Transport Rule by 2014 (in Job-Years)
                                  Employment
                            Incremental Employment
One-Time Employment Changes for Construction

  1.	Boilermakers
890
  2.	Engineers
440
  3.	General Construction
880
  4.	Steel Manufacturing
20

 8.4.3	Other Employment Impacts of the Transport Rule
We expect ongoing employment impacts on regulated and non-regulated entities for a variety of reasons.  These include labor changes in the regulated entities resulting from shifts in demand for fuels, increased demand for materials to operate pollution control equipment, changes in employment resulting from coal retirements, and changes in other industries due to changes in the price of electricity and natural gas.  We provide preliminary estimates of some of these effects below.  The most notable of the ones we are unable to estimate are the impacts on employment as a result of the increase in electricity and other energy prices in the economy.  Because of this inability to estimate all the important employment impacts, EPA neither sums the impacts that the Agency is able to estimate for the ongoing non-regulated group or make any inferences of whether there is a net gain or loss of employment for the non-regulated group. These other ongoing employment impacts are found in Table 8-6, and these employment impacts are not included in the Agency estimate of employment impacts for this Transport Rule for the reasons mentioned in this paragraph.
Table 8-6.	Employment Impacts for Entities Not Regulated by the Transport Rule
Employment  Changes for Ongoing  Annual Operation

  Employment  Changes from Changes to Demand in Materials

      1.	Limestone (FGD)
2,440
      2.	Ammonia (SCR)
30
      3.	Catalyst (SCR)
20
      4.	Sodium Bicarbonate (DSI)
160
      Sub-Total:
2,650

  Employment  Changes for Ongoing Annual Retrofit Operation
2,320
Employment Annual Changes due to Coal Capacity Retirements
(2,710)
Annual Employment Changes due to Changes in Fuel Use
(990)
  Coal
--------------------------------------------------------------------------------
         (2,030)
  Natural Gas
810
  New Natural Gas Pipeline
230
8.5	Summary
The three approaches use different analytical techniques and are applied to different industries during different time periods, and they use different units of analysis.  These estimates should not be summed because of the different metrics, length and methods of analysis as mentioned in Section 8.4.  The Morgenstern estimates are used for the ongoing employment impacts for the regulated entities (the electric power sector).  The short term estimates for employment needed to design, construct, and install the pollution control equipment in the period leading up to the compliance date are also provided.  Finally some of the other types of employment impacts that will be ongoing are estimated as well but are not included in the employment impacts estimated for the final Transport Rule.
Table 8-7 shows the employment impacts of the final Transport Rule as estimated by the environmental protection sector approach and by the Morgenstern approach.
Table 8-7.	Estimated Employment Impact Table

Annual (reoccurring)
One time (construction during compliance period)
Environmental Protection Sector approach*
Not Applicable
2,230
Net Effect on Electric Utility Sector Employment from Morgenstern et al. approach***
**+700
- 1,000 to +3,000****
Not Applicable
*These one-time impacts on employment are estimated in terms of job-years.
**This estimate is not statistically different from zero.
***These annual or recurring employment impacts are estimated in terms of production workers as defined by the US Census Bureau's Annual Survey of Manufacturers (ASM).
**** 95% confidence interval

8.6	References
Berman, E., and L. T. M. Bui. 2001. "Environmental Regulation and Labor Demand: Evidence from the South Coast Air Basin." Journal of Public Economics 79(2):265-295.
Bezdek, R. H., Wendling, R. M., and DiPerna, P. 2008. "Environmental Protection, the Economy, and Jobs: National and Regional Analyses." Journal of Environmental Management 86(1):63-79.
Greenstone, M. 2002. "The Impacts of Environmental Regulations on Industrial Activity: Evidence from the 1970 and 1977 Clean Air Act Amendments and the Census of Manufactures. Journal of Political Economy 110(6):1175-1219.
Henderson, J. V. 1996. "Effects of Air Quality Regulation." American Economic Review 86(4):789-813.
Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 2002. "Jobs versus the Environment: An Industry-Level Perspective." Journal of Environmental Economics and Management 43(3):412-436.
US Environmental Protection Agency (EPA).  "Impacts of the Acid Rain Program on Coal Industry Employment."  EPA 430-R-01-002, (2001).
US Environmental Protection Agency.  Engineering and Economic Factors Affecting the Installation of Control Technologies for Multipollutant Strategies, EPA-600/R-02/073 (2002).
US Energy Information Administration (EIA), Annual Energy Review 2009.  "Coal Mining Productivity By State and Mine Type."
US Census Bureau, 2007 and 2002 Economic Census. "Manufacturing and Mining: Detailed Statistics by Ind for the US, Utiltiities: Summary Statistics for the US."
US Bureau of Labor Statistics, United States Department of Labor. "Industry Labor Productivity and Cost Data Tables, Annual Percent Changes." (2010).

Chapter 9
         Statutory and executive order analyses

	This chapter presents discussion and analyses relating to relevant Executive Orders and statutory requirements relevant for the Transport Rule.  We discuss potential impacts to affected small entities as required by the Regulatory Flexibility Act (RFA), as amended by the Small Business Regulatory Enforcement Fairness Act (SBREFA).  We also describe the analysis conducted to meet the requirements of the Unfunded Mandates Reform Act of 1995 (UMRA) that assess the impact of the Transport Rule for state, local and Tribal governments and the private sector.  Analyses conducted to comply with the Paperwork Reduction Act (PRA) are also discussed.  In addition, we address the requirements of Executive Order (EO) 13045:  Protection of Children from Environmental Health and Safety Risks; EO 13175:  Consultation and Coordination with Indian Tribal Governments; and EO 12898:  Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations.  The Discussion of Executive Order 13211:  Actions that Significantly Affect Energy Supply, Distribution or Use is provided in Chapter 7 of this RIA.

9.1	Small Entity Impacts
		The Regulatory Flexibility Act (5 U.S.C. 601 et seq.), as amended by the Small Business Regulatory Enforcement Fairness Act (Public Law No. 104-121), provides that whenever an agency is required to publish a general notice of proposed rulemaking, it must prepare and make available an initial regulatory flexibility analysis, unless it certifies that the proposed rule, if promulgated, will not have a significant economic impact on a substantial number of small entities (5 U.S.C.  605[b]).  Small entities include small businesses, small organizations, and small governmental jurisdictions.
For the purposes of assessing the impacts of the Transport Rule on small entities, a small entity is defined as:
      (1)	A small business according to the Small Business Administration size standards by the North American Industry Classification System (NAICS) category of the owning entity.  The range of small business size standards for electric utilities is 4 billion kilowatt-hours of production or less;
      (2)	a small government jurisdiction that is a government of a city, county, town, district, or special district with a population of less than 50,000; and
      (3)	a small organization that is any not-for-profit enterprise that is independently owned and operated and is not dominant in its field.
      Table 9-1 lists entities potentially affected by this final rule with the applicable NAICS code.

         Table 9-1.  Potentially Regulated Categories and Entities[a]-

                                   Category

                                 NAICS Code[b]

                  Examples of Potentially Regulated Entities

Industry

                                    221112

Fossil fuel-fired electric utility steam generating units.

Federal Government

                                   221112[c]

Fossil fuel-fired electric utility steam generating units owned by the federal government.

State/Local/
Tribal Government

                                   221112[c]

Fossil fuel-fired electric utility steam generating units owned by municipalities.

                                    921150

Fossil fuel-fired electric utility steam generating units in Indian Country.

[a]Include NAICS categories for source categories that own and operate electric generating units only.
[b]North American Industry Classification System.
[c]Federal, state, or local government-owned and operated establishments are classified according to the activity in which they are engaged.

      EPA examined the potential economic impacts to small entities associated with this rulemaking based on assumptions of how the affected entities will implement control measures to meet their NOx and SO2 budgets.  This analysis does not examine potential indirect economic impacts associated with the Transport Rule, such as employment effects in industries providing fuel and pollution control equipment, or the potential effects of electricity price increases on industries and households.

9.1.1	Identification of Small Entities
		EPA used Velocity Suite's Ventyx data as a basis for identifying plant ownership and compiling the list of potentially affected small entities, in conjunction with IPM outputs.  The Ventyx data set contains detailed ownership and corporate affiliation information.  For plants burning fossil fuel as the primary fuel, plant-level boiler and generator capacity, heat input, generation, and emissions data were aggregated by owner and then parent company.  Entities with more than 4 billion kWh of annual electricity generation were removed from the list, as were municipal-owned entities serving a population greater than 50,000.  For cooperatives, investor-owned utilities, and subdivisions that generate less than 4 billion kWh of electricity annually but may be part of a large entity, additional research on power sales, operating revenues, and other business activities was performed to make a final determination regarding size.  Because the rule does not affect units with a generating capacity of less than 25 MW, small entities that do not own at least one generating unit with a capacity greater than or equal to 25 MW were dropped from the data set.  According to EPA's analysis, about 390 small entities were exempted by this provision.  Finally, small entities for which IPM does not project generation in 2014 in the base case were omitted from the analysis because they are not projected to be operating and thus will not face the costs of compliance with the Transport Rule.  After omitting entities for the reasons above, EPA identified a total of 108 potentially affected small entities, out of a possible 610.  The number of potentially affected small entities by ownership type is listed in Table 9-2.

9.1.2	Overview of Analysis and Results
		This section presents the methodology and results for estimating the impact on the Transport Rule to small entities in 2014 based on the following endpoints:
         * annual economic impacts of the Transport Rule on small entities and
         * ratio of small entity impacts to revenues from electricity generation.
<IP_ADDRESS>	Methodology for Estimating Impacts of the Transport Rule on Small Entities
		An entity can comply with the Transport Rule through some combination of the following: installing retrofit technologies, purchasing allowances, switching to a cleaner fuel, or reducing emissions through a reduction in generation or improved efficiency.  Additionally, units with more allowances than needed can sell these allowances in the market.  The chosen compliance strategy will be primarily a function of the unit's marginal control costs and its position relative to the marginal control costs of other units.
      To attempt to account for each potential control strategy, EPA estimates compliance costs as follows:
	CCompliance = Δ COperating+Retrofit + Δ CFuel + Δ CAllowances + Δ CTransaction + Δ R
where C represents a component of cost as labeled, and Δ R represents the value of foregone electricity generation, calculated as the difference in revenues between the base case and the Transport Rule.
      In reality, compliance choices and market conditions can combine such that an entity may actually experience a savings in any of the individual components of cost.  Under the Transport Rule, some units will forgo some level of electricity generation (and thus revenues) to comply and this impact will be lessened on these entities by the projected increase in electricity prices under the Transport Rule. On the other hand, those maintaining or increasing generation levels will see an increase in electricity revenues and as a result, lower net compliance costs. If entities are able to increase revenue more than an increase in fuel cost and other operating costs, ultimately they will have negative net compliance costs (or savings).  Elsewhere, units burning high or medium sulfur coal might decide to pay relatively more for low-sulfur coal under the Transport Rule and sell allowances on the market, in the hopes of negating some or all of their compliance costs.  Overall, small entities are not projected to install relatively costly emissions control retrofits, but may choose to do so in some instances.  Because this analysis evaluates the total costs along each of the compliance strategies laid out above for each entity, it inevitably captures savings or gains such as those described.  As a result, what we describe as cost is really more of a measure of the net economic impact of the rule on small entities.
      For this analysis, EPA used IPM-parsed outputs to estimate costs based on the parameters above, at the unit level.  These impacts were then summed for each small entity, adjusting for ownership share.  Net impact estimates were based on the following:  operating and retrofit costs, sale or purchase of allowances, and the change in fuel costs or electricity generation revenues under the Transport Rule relative to the base case.  These individual components of compliance cost were estimated as follows:
      (1) Operating and retrofit costs:  Using the IPM-parsed output for the base case and the Transport Rule, EPA identified units that install control technology under the Transport Rule and the technology installed.  The equations for calculating retrofit costs were adopted from EPA's version of IPM.  The model calculates the capital cost (in $/MW); the fixed operation and maintenance (O&M) cost (in $/MW-year); the variable O&M cost (in $/MWh); and the total annualized retrofit cost for units projected to install FGD, DSI, SCR, or SNCR.
      (2) Sale or purchase of allowances:  EPA estimated the value of initial SO2 and NOx annual and NOx ozone season allowance holdings.  For both SO2 and NOx, the state emission budgets were assumed to be apportioned to units based on their share of the state's historic heat input (but not exceeding the unit's maximum historic emissions). Using 2006-2010 data, the three highest, non- zero annual heat input values within the 5 year period are selected and averaged for each unit.  EPA calculated each unit's SO2 and NOx annual and NOx ozone season allowance allocations as the ratio of that unit's historic heat input to the sum of all units' historic heat input in the applicable state, times the final state budget for existing units.  Thus each unit's allocation is the unit's proportional share of the state budget, based on historic heat input.  See Allowance Allocations in the Existing and New Units under the Transport Rule Federal Implementation Plans TSD.
      To estimate the value of allowances holdings, allocated allowances were subtracted from projected emissions, and the difference was then multiplied by the allowance prices projected by IPM for 2014.  Units were assumed to purchase or sell allowances to exactly cover their projected emissions under the Transport Rule.
      (3) Fuel costs:  Fuel costs were estimated by multiplying fuel input (MMBtu) by region and fuel-type-adjusted fuel prices ($/MMBtu) from IPM.  The change in fuel expenditures under the Transport Rule was then estimated by taking the difference in fuel costs between the Transport Rule and the base case.
      (4)  Value of electricity generated:  EPA estimated electricity generation by first estimating unit capacity factor and maximum fuel capacity.  Unit capacity factor is estimated by dividing fuel input (MMBtu) by maximum fuel capacity (MMBtu).  The maximum fuel capacity was estimated by multiplying capacity (MW) * 8,760 operating hours * heat rate (MMBtu/MWh).  The value of electricity generated is then estimated by multiplying capacity (MW) * capacity factor * 8,760 * regional-adjusted retail electricity price ($/MWh), for all entities except those categorized as "Private" in Ventyx.  For private entities, EPA used wholesale electricity price instead retail electricity price because most of the private entities are independent power producers (IPP). IPPs sell their electricity to wholesale purchasers and do not own transmission facilities and thus their revenue was estimated with wholesale electricity prices.
      As discussed later in this analysis, 70 percent of small entities projected to incur positive costs under the Transport Rule do not have to operate in a competitive market environment and thus should be able to pass compliance costs on to consumers.  We defined cost of service regions as regions with a deregulation percentage of less than 20 percent. The deregulation percentage is defined for this analysis as a percentage estimating the degree of competition in electricity market, as provided by EIA.  The lower this percentage means that there are more areas with cost of service market characteristics. We have used the estimates published in AEO 2010.
      To somewhat account for this cost pass-through, we incorporated the projected regional-adjusted retail electricity price calculated under the Transport Rule in our estimation of generation revenue under the Transport Rule.
      (5) Administrative costs:  Because most affected units are already monitored as a result of other regulatory requirements, EPA considered the primary administrative cost to be transaction costs related to purchasing or selling allowances.  EPA assumed that transaction costs were equal to 1.5 percent of the total absolute value of a unit's allowances.  This assumption is based on market research by ICF International.

<IP_ADDRESS>	Results
		The potential impacts of the Transport Rule on small entities are summarized in Table 9-2.  All costs are presented in $2007.  EPA estimated the annualized net compliance cost to small entities to be approximately $38 million in 2014.  As the table below indicates, net compliance costs for some ownership groups are actually negative, implying the group as a whole is estimated to have cost savings under the Transport Rule.  The fact that these groups have net savings does not mean that each small entity in that group would benefit from the Transport Rule.  In most cases, the net savings are driven by a few entities that are able to increase their electricity revenues by increasing generation and taking advantage of higher electricity prices.

 Table 9-2.  Projected Impact of the Transport Rule on Small Entities in 2014

                              EGU Ownership Type

                    Number of Potentially Affected Entities
                  Total Net Compliance Cost ($2007 millions)

 Number of Small Entities with Compliance Costs >1% of Generation Revenues

 Number of Small Entities with Compliance Costs >3% of Generation Revenues
Cooperative
                                      25
                                     $52.9
                                       7
                                       5
Investor-Owned Utility
                                       9
                                     -$9.9
                                       0
                                       0
Municipal
                                      51
                                     $3.0
                                      15
                                       5
Subdivision
                                       5
                                     -$2.1
                                       0
                                       0
Private
                                      18
                                     -$5.7
                                       2
                                       1
Total
                                      108
                                     $38.1
                                      24
                                      11
Note:	The total number of potentially affected entities in this table excludes around 390 entities that have been dropped because they will not be affected by the Transport Rule, because they only own units less than 25 MW.. Also, the total number of entities with costs greater than 1 percent or 3 percent of revenues includes only entities experiencing positive costs.  A negative cost value implies that the group of entities experiences a net savings under the Transport Rule.  Definitions of types of entities are the following: Cooperative = User-owned utility company; Investor-Owned Utility = Utility owned by stockholders; Municipal = Publicly owned utility; Subdivision = County, municipality, hospital district or school district that receives electric service from an entity; Private = Privately owned electric companies not openly traded on stock markets
Source:	IPM analysis
      EPA assessed the economic and financial impacts of the rule using the ratio of compliance costs to the value of revenues from electricity generation, focusing in particular on entities for which this measure is greater than 1 percent.  Although this metric is commonly used in EPA impact analyses, it makes the most sense when as a general matter an analysis is looking at small businesses that operate in competitive environments.  However, small businesses in the electric power industry often operate in a price-regulated environment where they are able to recover expenses through rate increases.  Given this, EPA considers the 1 percent measure in this case a crude measure of the price increases these small entities will be asking of rate commissions or making at publicly owned companies.
      EPA assessed the potential impact of this action on small entities and found that there are about 660 potentially affected small units (i.e., greater than 25 MW and generating less than 4MM MWh) out of 3,625 existing units greater than 25 MW in the TR region.  The majority of these EGUs are owned by entities that do not meet the small entity definition.  The remaining 271 of 660 EGUs are owned by 108 potentially affected small entities and are likely to be affected by today's rule. Of the 108 small entities considered in this analysis, 24 entities may experience compliance costs greater than 1 percent of generation revenues in 2014.  Entities that experience negative net costs under the Transport Rule are excluded from these totals.  These results do not fully account for the reality that about 70 percent of these entities operate in cost of service markets and thus should be able to recover all of their costs of complying with the Transport Rule.  In EPA's modeling, most of the cost impacts for these small entities and their associated units are driven by lower electricity generation relative to the base case.  Specifically, two units reduce their generation by significant amounts, driving the bulk of the costs for all small entities.  Excluding these two units, another driver of small entity impacts for sub-divisions and private small entities is higher fuel costs, which the affected units would be expected to use irrespective of whether they had to comply with this rule. Increased fuel costs are often passed through to rate-payers as common practice in many areas of the U.S. due to fuel adder arrangements instituted by state public utility commissions. Finally, EPA's decision to exclude units smaller than 25 MW has already significantly reduced the burden on potentially small entities by nearly 390.  Hence, EPA has concluded that there is no significant economic impact on a substantial number of small entities (No SISNOSE) for this rule.  The number of entities with compliance costs exceeding 3 percent of generation revenues is also included in Table 9-2.
      The distribution across entities of economic impacts as a share of base case revenue is summarized in Table 9-3.  Although the distributions of economic impacts on each ownership type are in general fairly tight, there are a few outliers for which the percentage of economic impacts as a share of revenue is either very low or very high relative to the capacity-weighted average.  In the cases where entities are projected to experience negative net impacts that are a high percentage of revenues, these entities have units that are able to increase generation with the Transport Rule or sell excess allowances, thus increasing revenues.  In the cases where entities are projected to experience positive net impacts that are a high percentage of revenues, these entities do not find it economic to retrofit and are unable to switch to a lower sulfur coal. Thus, another reason for entities incurring impacts is that they are expected to reduce their generation under the Transport Rule which reduces revenues collected from electricity sales and inflates net costs.

Table 9-3.  Summary of Distribution of Economic Impacts of the Transport Rule on Small Entities in 2014
                              EGU Ownership Type
   Capacity-Weighted Average Economic Impacts as a % of Generation Revenues
                                      Min
                                      Max
Cooperative
                                     -0.1%
                                    -13.1%
                                     47.8%
Investor-owned utility
                                      -2%
                                    -13.6%
                                     -0.4%
Municipal
                                     -0.7%
                                    -78.1%
                                     26.0%
Subdivision
                                     -0.4%
                                    -13.2%
                                     6.7%
Private
                                      -3%
                                     -2.0%
                                     0.2%
All
                                     -1.0%
                                    -78.1%
                                     47.8%

Source:  IPM analysis

      The separate components of annualized costs to small entities under the Transport Rule are summarized in Table 9-4.  The most significant components of incremental cost to these entities under the Transport Rule are due to lower electricity revenues as some EGUs reduce their generation under the policy case in IPM.  This effect is most prominent for Cooperatives in particular, as two coal units reduce a significant portion of their generation.  As discussed above, excluding these two units from the sample, leads to an overall cost savings for the rest of the Co-ops.  Allowances purchases also account for a portion of the total costs to small entities.  All ownership types, with the exception of municipals, are net purchasers of allowances. Additionally, fuel costs and operating costs appear to decrease for cooperatives, but this is mostly due to one large unit significantly cutting its generation, thus translating to lower variable costs for the whole group.  Across all other ownership types, with the exception of municipals, electricity revenues actually increase. This is due largely to the projected increase in electricity prices under the Transport Rule.
Table 9-4.  Incremental Annualized Costs under the Transport Rule Summarized by Ownership Group and Cost Category in 2014 ($2007 millions)
                              EGU Ownership Type
                           Retrofit + Operating Cost
                          Net Purchase of Allowances
                                   Fuel Cost
                           Lost Electricity Revenue
                              Administrative Cost
Cooperative
                                    -$11.3
                                     $4.9
                                    -$50.7
                                    -$109.8
                                     $0.2
Investor-Owned Utility
                                     $0.2
                                     $1.0
                                     -$0.6
                                     $10.6
                                     $0.0
Municipal
                                     $4.1
                                     -$3.4
                                     -$0.8
                                     -$3.0
                                     $0.1
Subdivision
                                     $0.2
                                     $0.6
                                     $3.1
                                     $6.0
                                     $0.0
Private
                                     $0.3
                                     $3.2
                                     $7.2
                                     $16.5
                                     $0.1
TOTAL
                                     -$6.5
                                     $6.3
                                    -$41.8
                                    -$79.6
                                     $0.5
Source:  IPM analysis.
      Furthermore, 601 MW of total small entity capacity, or about 1 percent of total small entity capacity in the Transport Rule region, is projected to be uneconomic to maintain under the Transport Rule relative to the base case.  To put these numbers in context, of all affected capacity under the Transport Rule, about 4.8 GW (1.6 percent) of coal-fired capacity is projected to be uneconomic to maintain relative to the base case.  This comparison suggests that small entities should not be disproportionately affected by the Transport Rule.  In practice, units projected to be uneconomic to maintain may be mothballed, retired, or kept in service to ensure transmission reliability in certain parts of the grid.  Our IPM modeling is unable to distinguish between these potential outcomes.

9.1.3	Summary of Small Entity Impacts
		EPA examined the potential economic impacts to small entities associated with this rulemaking based on assumptions of how the affected states will implement control measures to meet their emissions.  To summarize, of the 108 small entities potentially affected, and the 610 small entities in the Transport Rule region that are included in EPA's modeling, 25 may experience compliance costs in excess of 1 percent of revenues in 2014, based on assumptions of how the affected states implement control measures to meet their emissions budgets as set forth in this rulemaking.  Potentially affected small entities experiencing compliance costs in excess of 1 percent of revenues have some potential for significant impact resulting from implementation of the Transport Rule.  However, as noted above, it is EPA's position that because very few of the affected entities currently operate in a competitive market environment, they should generally be able to pass the costs of complying with the Transport Rule on to rate-payers.  Furthermore, the decision to include only units greater than 25 MW in size exempts around 390 potentially small entities that would otherwise be affected by the Transport Rule.

9.2	Unfunded Mandates Reform Act (UMRA) Analysis
		Title II of the UMRA of 1995 (Public Law 104-4)(UMRA) establishes requirements for federal agencies to assess the effects of their regulatory actions on state, local, and Tribal governments and the private sector.  Under Section 202 of the UMRA, 2 U.S.C. 1532, EPA generally must prepare a written statement, including a cost-benefit analysis, for any proposed or final rule that includes any Federal mandate that may result in the expenditure by State, local, and Tribal governments, in the aggregate, or by the private sector, of $100,000,000 or more ... in any one year.  A Federal mandate is defined under Section 421(6), 2 U.S.C. 658(6), to include a Federal intergovernmental mandate and a Federal private sector mandate.  A Federal intergovernmental mandate, in turn, is defined to include a regulation that would impose an enforceable duty upon State, Local, or Tribal governments, Section 421(5)(A)(i), 2 U.S.C. 658(5)(A)(i), except for, among other things, a duty that is a condition of Federal assistance, Section 421(5)(A)(i)(I).  A Federal private sector mandate includes a regulation that would impose an enforceable duty upon the private sector, with certain exceptions, Section 421(7)(A), 2 U.S.C. 658(7)(A).
      Before promulgating an EPA rule for which a written statement is needed under Section 202 of the UMRA, Section 205, 2 U.S.C. 1535, of the UMRA generally requires EPA to identify and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost-effective, or least burdensome alternative that achieves the objectives of the rule. EPA included descriptions of three remedy options that it considered when developing its proposed rule: (1) the proposed remedy of State Budgets/Limited Trading, (2) State Budgets/Intrastate Trading, and (3) Direct Controls. Moreover, section 205 allows EPA to adopt an alternative other than the least costly, most cost-effective or least burdensome alternative if the Administrator publishes with the final rule an explanation why that alternative was not adopted.
      Furthermore, as EPA stated in the proposal and final rule, EPA is not directly establishing any regulatory requirements that may significantly or uniquely affect small governments, including Tribal governments.  Thus, under the Transport Rule, EPA is not obligated to develop under Section 203 of the UMRA a small government agency plan.
      EPA analyzed the economic impacts of the Transport Rule on government entities and this section presents the results of that analysis.  The analysis does not examine potential indirect economic impacts associated with the Transport Rule, such as employment effects in industries providing fuel and pollution control equipment, or the potential effects of electricity price increases on industries and households. Analyses of employment effects and the potential effects of electricity price increases on industries can be found in Chapter 8 of this RIA.

9.2.1	Identification of Government-Owned Entities
	-	Using Ventyx data, EPA identified state- and municipality-owned utilities and subdivisions in the Transport Rule region.  EPA then used IPM-parsed output to associate these plants with individual generating units.  Entities that did not own at least one unit with a generating capacity of greater than 25 MW were omitted from the analysis because of their exemption from the rule.  This exempts 354 entities owned by state or local governments.  Additionally, government-owned entities for which IPM does not project generation in 2014 under the base case or the Transport Rule were exempted from this analysis, because they are not projected to be operating and thus will not face the costs of compliance with the Transport Rule. Eleven additional entities were dropped from the analysis for this reason.  EPA identified 98 state or municipality-owned utilities that are potentially affected by the Transport Rule, out of a possible 463. These results are summarized in Table 9-5.
9.2.2	Overview of Analysis and Results
		After identifying potentially affected government entities, EPA estimated the impact of the Transport Rule in 2014 based on the following:
         * total impacts of compliance on government entities and
         * ratio of government entity impacts to revenues from electricity generation.
The financial burden to owners of EGUs under the Transport Rule is composed of compliance and administrative costs.  This section outlines the compliance and administrative costs for the 98 potentially affected government-owned units in the Transport Rule region.
<IP_ADDRESS>	Methodology for Estimating Impacts of the Transport Rule on Government Entities
		The primary burden on state and municipal governments that operate utilities under the Transport Rule is the cost of installing control technology on units to meet SO2 and NOx emission limits or the cost of purchasing allowances.  However, an entity can comply with the Transport Rule through any combination of the following:  installing retrofit technologies, purchasing allowances, switching to a cleaner fuel, or reducing emissions through a reduction in generation.  Additionally, units with more allowances than needed can sell these allowances on the market.  The chosen compliance strategy will be primarily a function of the unit's marginal control costs and its position relative to the marginal control costs of other units.
      To attempt to account for each potential control strategy, EPA estimates compliance costs as follows:
	CCompliance = Δ COperating+Retrofit + Δ CFuel + Δ CAllowances + Δ CTransaction + Δ R
where C represents a component of cost as labeled, and Δ R represents the retail value of foregone electricity generation.
      In reality, compliance choices and market conditions can combine such that an entity may actually experience a savings in any of the individual components of cost.  Under the Transport Rule, for example, some units will forgo some level of electricity generation (and thus revenues) to comply.   The impact of forgone generation revenues will be lessened by the projected increase in electricity prices under the Transport Rule; while those not reducing generation levels will see an increase in electricity revenues. Because this analysis evaluates the total costs along each of the four compliance strategies laid out above for each entity, it inevitably captures savings or gains such as those described.  As a result, what we describe as cost is really more of a measure of the net economic impact of the rule on small entities.
      In this analysis, EPA used unit-level IPM-parsed outputs for the base case and the Transport Rule to estimate compliance costs based on the parameters above. These costs were then aggregated for each small government entity, adjusting for ownership share.  Compliance cost estimates were based on the following:  operating and retrofit costs, sale or purchase of allowances, and the change in fuel costs or electricity generation revenues under the Transport Rule relative to the base case.  These components of compliance cost were estimated as follows:
      (1) Retrofit and operating costs:  Using the IPM-parsed output for the base case and the Transport Rule, EPA identified units that install control technology under the Transport Rule and the technology installed.  The equations for calculating retrofit costs for SCR, SNCR, and FGD were adopted from EPA's version of IPM (version 4.10).  The model calculates the capital cost (in $/MW), the fixed O&M cost (in $/MW-year), the variable O&M cost (in $/MWh).
      (2) Sale or purchase of allowances:  EPA estimated the value of initial SO2 and NOx annual and NOx ozone season allowance holdings.  For both SO2 and NOx, the state emission budgets were assumed to be apportioned to units based on their share of the state's historic heat input (but not exceeding the unit's maximum historic emissions). Using 2006-2010 data, the three highest, non- zero annual heat input values within the 5 year period are selected and averaged for each unit.  EPA calculated each unit's SO2 and NOx annual and NOx ozone season allowance allocations as the ratio of that unit's historic heat input to the sum of all units' historic heat input in the applicable state, times the final state budget for existing units.  Thus each unit's allocation is the unit's proportional share of the state budget, based on historic heat input.  See Allowance Allocations in the Transport Rule Federal Implementation Plans TSD.
      To estimate the value of allowances holdings, allocated allowances were subtracted from projected emissions, and the difference was then multiplied by the allowance price projected by IPM.  Units were assumed to purchase or sell allowances to exactly cover their projected emissions under the Transport Rule.
      (3) Fuel costs:  Fuel costs were estimated by multiplying fuel input (MMBtu) by region and fuel type-adjusted fuel prices ($/MMBtu) from IPM.  The change in fuel expenditures under the Transport Rule was then estimated by taking the difference in fuel costs between the Transport Rule and the base case.
      (4) Value of electricity generated:  EPA estimated electricity generation by first estimating the unit capacity factor and maximum fuel capacity.  The unit capacity factor is estimated by dividing fuel input (MMBtu) by maximum fuel capacity (MMBtu).  The maximum fuel capacity was estimated by multiplying capacity (MW) * 8,760 operating hours * heat rate (MMBtu/MWh).  The value of electricity generated was then estimated by multiplying capacity (MW) * capacity factor * 8,760 * regional-adjusted retail electricity price ($/MWh).
      (5) Administrative costs:  Because most affected units are already monitored as a result of other regulatory requirements, EPA considered the primary administrative cost to be transaction costs related to purchasing or selling allowances.  EPA assumed that transaction costs were equal to 1.5 percent of the total absolute value of a unit's allowances.  This assumption is based on market research by ICF International.
<IP_ADDRESS>	Results
      	A summary of economic impacts on government-owned entities is presented in Table 9-5.  According to EPA's analysis, the total net economic impact on each category of government-owned entity (state- and municipality-owned utilities and subdivisions) is expected to be about $26 million in 2014.

Table 9-5.  Summary of Potential Impacts on Government Entities under the Transport Rule in 2014
                              EGU Ownership Type
                         Potentially Affected Entities
                  Projected Annualized Costs ($2007 millions)
Number of Government Entities with Compliance Costs >1% of Generation Revenues
Number of Government Entities with Compliance Costs >3% of Generation Revenues
Municipal
                                      86
                                     $15.5
                                      25
                                      12
State
                                       6
                                     $0.9
                                       0
                                       0
Subdivision
                                       6
                                     $9.5
                                       1
                                       0
Total
                                      98
                                     $25.9
                                      26
                                      12
Note:	The total number of potentially affected entities in this table excludes the 365 entities that have been dropped because they will not be affected by the Transport Rule, either because they only own units less than 25 MW (354 entities) or because they would not operate in either the base or the policy cases (the remaining 11 entities).  Also, the total number of entities with costs greater than 1 percent or 3 percent of revenues includes only entities experiencing positive costs.
Source:	IPM analysis
      As was done for the small entities analysis, EPA further assessed the economic and financial impacts of the rule using the ratio of compliance costs to the value of revenues from electricity generation in the base case, also focusing specifically on entities for which this measure is greater than 1 percent.  EPA projects that 26 government entities will have compliance costs greater than 1 percent of revenues from electricity generation in 2014.  As was true with the small entity analysis, one main driver of cost increases for these government entities appear to be revenue losses due to lower electricity generation relative to the base case.  As will be discussed below in more detail, while government entities do face higher costs under the Transport Rule than under the base case, these cost increases are actually lower than what EPA estimated under the proposed rule.  Revenues from electricity generation for these entities, however, go down more than what EPA estimated under the proposed Transport Rule, leading to a net cost increase for these entities. Entities that are projected to experience negative compliance costs under the Transport Rule are not included in those totals.  This approach is more indicative of a significant impact when an analysis is looking at entities operating in a competitive market environment.  Government-owned entities do not operate in a competitive market environment and therefore will be able to recover expenses under the Transport Rule through rate increases.  Given this, EPA considers the 1 percent measure in this case a crude measure of the extent to which rate increases will be made at publicly owned companies.
      The distribution across entities of economic impacts as a share of base case revenue is summarized in Table 9-6.  Although the distributions of economic impacts on each ownership type are in general fairly tight, there are a few outliers for which the percentage of economic impacts as a share of revenue is either very low or very high relative to the capacity-weighted average.    This is especially true for municipality-owned entities where the maximum economic impact as a share of base case revenues is approximately 35 percent.  Thus, a few municipality-owned entities experience economic impacts that are significantly higher than the capacity-weighted average for this group.  Another reason for entities incurring impacts is that they are expected to reduce their generation under the Transport Rule which reduces revenues collected from electricity sales and inflates net costs. In the cases where entities are projected to experience negative net impacts that are a high percentage of revenues, these entities have units that are able to increase generation with the Transport Rule or sell excess allowances, thus increasing revenues.
Table 9-6.  Distribution of Economic Impacts on Government Entities under the Transport Rule in 2014
                              EGU Ownership Type
   Capacity-Weighted Average Economic Impacts as a % of Generation Revenues
                                      Min
                                      Max
Municipal
                                    -0.00%
                                    -78.1%
                                     34.5%
State
                                     0.02%
                                     -2.6%
                                     0.6%
Sub-division
                                     0.65%
                                     -2.0%
                                     1.3%
All
                                    -0.04%
                                    -78.1%
                                     34.5%
Source:  IPM analysis

      The separate components of annualized incremental cost under the Transport Rule to each group of government entities are summarized in Table 9-7.  While all groups experience higher costs in general, there is a wide variation in these increases across groups.  Municipal entities have the highest retrofit and operating costs as they dominate the universe of affected government entities. Municipal and state entities are net sellers of allowances, which lessens the net impact of the rule for these entities. Sub-divisions are net purchasers of allowances, though the higher electricity revenues for them negate those cost increases as a group.  Both sub-divisions and state-owned entities benefit from higher electricity revenues, but they also incur higher fuel costs as they increase their electricity generation.  In aggregate, cost increases across the three groups are about $29 million relative to the base case (compared to about $135 million projected in the proposal).  As a group, these entities also gain about $3 million in higher electricity revenues (compared to $150 million increased revenues projected in the proposal), resulting in a net increase of about $26 million in impacts under the final rule.

      Table 9-7.  Incremental Annualized Costs under the Transport Rule Summarized by Ownership Group and Cost Category ($2007 millions) in 2014
                              EGU Ownership Type
                          Retrofit +  Operating Cost
                          Net Purchase of Allowances
                                   Fuel Cost
                         Increased Electricity Revenue
                              Administrative Cost
Municipal
                                    $28. 8
                                     -$6.9
                                    -$21.6
                                    -$14.4
                                     $0.8
State
                                     $3.6
                                     -$2.8
                                     $7.6
                                     $7.7
                                     $0.1
Subdivision
                                     $0.2
                                     $4.6
                                     $14.5
                                     $9.9
                                     $0.1
Source: ICF International analysis based on IPM analysis
      IPM modeling of the Transport Rule projects that approximately 76 MW (4 units) of municipality-owned capacity would be uneconomic to maintain under the Transport Rule, beyond what is projected in the base case.  This represents about 0.4 percent of all subdivision, state, and municipality capacity in the Transport Rule region.  For comparison, overall affected capacity under the Transport Rule, about 4.2 GW, or 1.6 percent of all coal-fired capacity is projected to be uneconomic to maintain relative to the base case.  This comparison suggests that government entities should not face a disproportionate burden under the Transport Rule.  In practice, units projected to be uneconomic to maintain may be "mothballed," retired, or kept in service to ensure transmission reliability in certain parts of the grid.  Our IPM modeling is unable to distinguish between these potential outcomes.
9.2.3	Summary of Government Entity Impacts
		EPA examined the potential economic impacts on state and municipality-owned entities associated with this rulemaking based on assumptions of how the affected states will implement control measures to meet their emissions.  According to EPA's analysis, the total net economic impact on government-owned entities is expected to be about $26 million in 2014. Of the 98 government entities considered in this analysis and the 463 government entities in the Transport Rule region that are included in EPA's modeling, 26 may experience compliance costs in excess of 1 percent of revenues in 2014, based on our assumptions of how the affected states implement control measures to meet their emissions budgets as set forth in this rulemaking.
	Government entities projected to experience compliance costs in excess of 1 percent of revenues have some potential for significant impact resulting from implementation of the Transport Rule.  However, as noted above, it is EPA's position that because these government entities can pass on their costs of compliance to rate-payers, they will not be significantly affected.  Furthermore, the decision to include only units greater than 25 MW in size exempts 354 government entities that would otherwise be potentially affected by the Transport Rule.

9.3	Paperwork Reduction Act
		In compliance with the Paperwork Reduction Act (44 U.S.C. 3501 et seq.), EPA has submitted a proposed Information Collection Request (ICR) (EPA ICR number 2391.02) to the Office of Management and Budget (OMB) for review and approval.  The ICR describes the nature of the information collection and its estimated burden and cost associated with the final rule, including estimates of the anticipated monitoring, reporting, and record-keeping burden and associated costs for states, local governments, and sources.  In cases where information is already collected by a related program, the ICR takes into account only the additional burden.  This situation arises in states that are also subject to requirements of the Consolidated Emissions Reporting Rule (EPA ICR number 0916.10; OMB control number 2060-0088) or for sources that are subject to the Acid Rain Program (EPA ICR number 1633.13; OMB control number 2060-0258), NOx SIP Call (EPA ICR number 1857.03; OMB control number 2060-0445), or CAIR (EPA ICR number 2152.04; OMB control number 2060-0570) requirements.
      The record-keeping and reporting burden to sources resulting from states choosing to participate in a regional cap-and-trade program is approximately $26 million annually.  The total number of burden hours associated with the record-keeping and reporting burden to Transport Rule-affected sources, states, and EPA for states choosing to participate in a regional cap-and-trade program is approximately 185,000 hours annually.  These estimates include the annualized cost of installing and operating appropriate SO2 and NOx emissions monitoring equipment to measure and report the total emissions of these pollutants from affected EGUs (serving generators greater than 25 megawatts capacity).  The burden to state and local air agencies includes any necessary SIP revisions, performance of monitoring certification, and fulfilling of audit responsibilities.
      EPA received no adverse comment on the ICR submitted for the proposed Transport Rule (EPA ICR number 2391.01).  More information on the ICR analysis is included in the Transport Rule docket.
9.4    Protection of Children from Environmental Health and Safety Risks
Executive Order 13045 (62 FR 19885, April 23, 1997) applies to any rule that:  (1) is determined to be "economically significant" as defined under EO 12866, and (2) concerns an environmental health or safety risk that EPA has reason to believe may have a disproportionate effect on children.  If the regulatory action meets both criteria, the Agency must evaluate the environmental health or safety effects of this planned rule on children, and explain why this planned regulation is preferable to other potentially effective and reasonably feasible alternatives considered by the Agency.
This rule is not subject to EO 13045 because it does not involve decisions on environmental health or safety risks that may disproportionately affect children. The EPA believes that the emission reductions from the strategies in this final rule will further improve air quality and will further improve children's health.
9.5	Executive Order 13132, Federalism
Under EO 13132, EPA may not issue an action that has federalism implications, that imposes substantial direct compliance costs, and that is not required by statute, unless the Federal government provides the funds necessary to pay the direct compliance costs incurred by State and local governments, or EPA consults with State and local officials early in the process of developing the proposed action.
EPA has concluded that this action does not have federalism implications.   It will not impose substantial direct effects on State or local governments, or on the relationship between the Federal government and the States, or on the distribution of power and responsibilities among the various levels of government, as specified in EO 13132.  Thus, Executive Order 13132 does not apply to the final rule.
In the spirit of EO 13132, and consistent with EPA policy to promote communications between EPA and State and local governments, EPA did provide information to State and local officials.  EPA sent a letter to the ten Representative National Organizations to draw their attention to the Transport Rule Notice of Data Availability (NODA) on allowance allocations and other related matters and to invite their comments. Following that letter in early 2011, EPA participated in informational calls with the Environmental Councils of the States (ECOS) and the National Governors Association to provide information about the NODA directly to State and local officials.  There were no new concerns raised during these informational calls.
9.6	Executive Order 13175, Consultation and Coordination with Indian Tribal Governments
Subject to EO 13175 (65 FR 67249, November 9, 2000) EPA may not issue a regulation that has Tribal implications, that imposes substantial direct compliance costs, and that is not required by statute, unless the Federal government provides the funds necessary to pay the direct compliance costs incurred by Tribal governments, or EPA consults with Tribal officials early in the process of developing the proposed regulation and develops a Tribal summary impact statement.  EO 13175 requires EPA to develop an accountable process to ensure "meaningful and timely input by tribal officials in the development of regulatory policies that have tribal implications."
EPA has concluded that this action may have Tribal implications.  However, it will neither impose substantial direct compliance costs on Tribal governments, nor preempt Tribal law.  EPA consulted with tribal officials during the process of finalizing this regulation to permit them to have meaningful and timely input into its development.
EPA received comments on the proposed rule that the Agency did not properly conduct consultation during the proposal phase of the rulemaking.  In response to these comments, EPA sent a letter to all federally-recognized tribes in the country offering consultation.  In addition, several comments also noted that the Agency did not adequately consider opportunities for tribes to enter into any of the trading programs and, in particular, did not consider sovereignty issues when addressing how to distribute allowances to potential new units in Indian country.  On January 7, 2011, EPA issued a NODA requesting comment on allocations for new units in Indian country, among other topics.  The Agency held a formal consultation call with three tribes on January 21, 2011.  A follow up call was held on Feb. 4, 2011 with 11 tribes.   EPA considered the additional input from these consultation and information calls, in conjunction with the public comments, in the development of the final rule.  Accordingly, EPA created an Indian country new unit set-aside to specifically address tribes's concerns regarding the protection of tribal sovereignty in the distribution of allowances for new units in Indian country.
As required by section 7(a) of the Executive Order, EPA's Tribal Consulation 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.

9.7    Environmental Justice
            Executive Order (EO) 12898 (59 FR 7629 (Feb. 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 United States.

9.7.1. Consideration of Environmental Justice Issues in the Rule Development Process
      During development of this final Transport Rule, EPA considered its impacts on low-income, minority, and tribal communities in several ways. EPA's assessment included a) the structure of the rule and responses to comments received on the proposed rule on issues specific to these communities;  b) expected SO2 and NOX emission reductions; c) expected PM2.5 and ozone air quality improvements; d) expected health benefits, including asthma and other health effects of particular concern for environmental justice communities; and e) a quantitative assessment of the expected socioeconomic distribution of a key health benefit (reduction in premature mortality).   This last analysis, the distributional analysis, estimated the PM2.5 mortality risks according to race, income, and educational attainment before and after implementation of the Transport Rule.  A description of these analyses and the conclusions reached can be found in section XII. J of the preamble for this final Transport Rule.
      Briefly, all of these analyses indicate large health and environmental benefits for susceptible and vulnerable populations as a result of implementing this Transport Rule.  The final rule will provide significant health and environmental benefits to numerous low-income, minority, and tribal individuals in both rural areas and inner cities in the region affected by this rule. This includes, among others, people with asthma, people with heart disease, and people living in ozone or fine particle (PM2.5) nonattainment areas.
      The distributional analysis indicates that the populations with the largest improvement (i.e. largest decline) in PM2.5 mortality risk as a result of the Transport Rule in 2014 (compared to the base case in 2014) are people living in the highest-risk counties. Among these counties, the largest improvements are for people with less than high school or high school education. These reductions in risk within the highest-risk counties, as well as the reductions in risk within the other 95 percent of counties, are distributed among populations of different races fairly evenly. Therefore, there is no indication that people of particular race receive a greater benefit (or smaller benefit) than others. None of the analyses, including the distributional analysis, showed evidence of adverse effects for any socioeconomic group.
      These analyses are based on the same data and modeling tools used for the other analyses of this Transport Rule.  A detailed description of the underlying data and analytical techniques used can be found in Chapter 3 of this RIA (emissions), Chapter 4 (air quality), and Chapter 5 (benefits). The analysis of the human health benefits of the rule, including the socioeconomic distribution of mortality benefits among different populations, is described in Appendix A of this RIA.
9.7.2. Meaningful Public Participation
      During the comment period for the proposed rule, EPA reached out specifically to environmental justice communities and organizations to notify them of the opportunity to provide comments on this rule and to solicit their comments on both the proposed rule and upcoming actions. EPA held public hearings on this rule and received an extensive number of comments in writing.  EPA has responded to these comments as part of this final rulemaking.

CHAPTER 10
COMPARISON OF BENEFITS AND COSTS

10.1	Comparison of Benefits and Costs
      As shown in Chapter 8, the estimated social costs to implement the final Transport Rule, as described in this document, are approximately $0.81 billion in 2014 (2007 dollars).   As shown in Chapter 5, the estimated benefits from implementation of the final Transport Rule are approximately $120 to 280 billion + $110 to 250 billion + B in 2014 (2007 dollars, based on a discount rate of 3 percent and 7 percent, respectively and rounded to three significant figures) EPA can thus calculate the net benefits of the final rule by subtracting the estimated social costs from the estimated benefits in 2014.   The annual net benefits of the final Transport rule are approximately $120 to 280 + B billion using a 3 percent discount rate or $110 to 250 + B billion using a 7 percent discount rate.  (B represents the sum of all unquantified benefits and disbenefits of the regulation.)  Therefore, EPA expects that implementation of this rule, based solely on economic efficiency criteria, will provide society with a significant net gain in social welfare, notwithstanding the expansive set of health and environmental effects we were unable to quantify.  Further quantification of directly emitted PM2.5-, mercury-, acidification-, and eutrophication-related impacts would increase the estimated net benefits of the rule.  Table 10-1 presents a summary of the benefits, costs, and net benefits of the final rule.
      As explained in Chapter 5, EPA presents two types of probabilistic approaches to characterize uncertainty in the benefit estimates for the Transport Rule.  The first approach generates a distribution of benefits based on the classical statistical error expressed in the underlying health and economic valuation studies used in the benefits modeling framework.  The second approach uses the results from a pilot expert elicitation project designed to characterize key aspects of uncertainty in the ambient PM2.5/mortality relationship, and augments the uncertainties in the mortality estimate with the statistical error reported for other endpoints in the benefit analysis.

      EPA also analyzed the costs and benefits of two alternative scenarios that impose relatively more stringent and relatively less stringent SO2 budgets in Group 1 states, compared to the final Transport Rule, beginning in 2014, in accordance with Circular A-4 Guidance (OMB, 2003). These scenarios are illustrative of the cost and benefit impacts of varying program stringency.  They are designed to show the effects of more stringent and less stringent SO2 reduction requirements in a regulatory structure that is otherwise the same as the remedy.
      Both of the alternative scenarios represent a limited interstate trading program to achieve emission reductions, as in the final Transport rule remedy.    Both alternative scenarios impose the same NOx and SO2 emission reduction requirements in 2012 as imposed by the final Transport Rule. The options vary in stringency for the SO2 budgets in Group 1 states that exist in the final rule's remedy, which are modeled on emission reductions in 2014 available for those states up to a marginal cost of $2,300 per ton.  Beginning in 2014, the less stringent alternative scenario imposes higher SO2 budgets in Group 1 states based on modeled emissions from the $1,600 per ton cost threshold analysis described in preamble section VI.B.  The more stringent alternative scenario reflects 2014 reduction requirements based on modeled emissions at the $10,000 per ton cost threshold.
      Air quality modeling was not conducted for these two alternatives. EPA applied a benefit- per-ton approach appropriate for deriving PM-related benefits for these alternative scenarios from the full benefit estimation methodology conducted for the final Transport Rule's remedy, as described in Chapter 5.  The alternative scenarios' social costs are estimated using the Multimarket Model while using the private compliance costs are projected using IPM.  Table 10-2 presents the emissions forecast for SO2 and NOx in 2014 under the Transport Rule and the more or less stringent scenarios.  Table 10-3 presents the estimated social costs and health benefits, including net social benefit, of the two alternative scenarios alongside corresponding estimates for the final Transport Rule remedy.
Table 10-1.  Summary of Annual Benefits, Costs, and Net Benefits of the Final Transport Rule in 2014[a] (billions of 2007 dollars)

                                  Description

                               Preferred Remedy

Social costs[b]

   3 percent discount rate
                                     $0.81

   7 percent discount rate
                                     $0.81

Social benefits[c,d,e]
   3 percent discount rate
   7 percent discount rate

                               $120 to $280 + B
                               $110 to $250 + B

  Health-related benefits:
   3 percent discount rate
   7 percent discount rate

                               $110 to $270 + B
                               $100 to $250 + B

  Visibility benefits
                                     $4.1

Net benefits (benefits-costs)[e,f]
   3 percent discount rate
   7 percent discount rate

                                 $120 to $280
                                 $110 to $250
[a]	  Estimated rounded to two significant figures.
[b]	Note that costs are the annualized total social costs of reducing pollutants including NOx and SO2 for the EGU source category in the final Transport Rule region in 2014.  Social costs are estimated using the MultiMarket model, the model employed by EPA in this RIA to estimate economic impacts to industries outside the electric power sector. This model does not estimate indirect impacts associated with a regulation such as this one.   More information on the social costs can be found in Chapter 8 and Appendix B of this RIA.
[c]	Total benefits are comprised primarily of monetized PM-related health benefits.  The reduction in premature fatalities each year accounts for over 90 percent of total monetized benefits.  Benefits in this table are nationwide (with the exception of ozone and visibility) and are associated with NOx and SO2 reductions.  Ozone benefits represent benefits nationwide.  Visibility benefits represent benefits in Class I areas in the southeast, southwest and California. The estimate of social benefits also includes CO2-related benefits calculated using the social cost of carbon, discussed further in Chapter 5.
[d]	Not all possible benefits or disbenefits are quantified and monetized in this analysis.  B is the sum of all unquantified benefits and disbenefits.  Potential benefit categories that have not been quantified and monetized are listed in Table 1-4.
[e]	Valuation assumes discounting over the SAB-recommended 20-year segmented lag structure.  Results reflect the use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for preparing economic analyses (EPA, 2010; OMB, 2003).
[f]	Net benefits are rounded to three significant figures.  Columnar totals may not sum due to rounding.

Table 10-2. Projected 2014 National Emissions of SO2 and NOX with the Base Case (No Further Controls) and with Transport Rule (Million Tons) and for More and Less Stringent Scenarios.
                                   Pollutant
                                   Base Case
                                Selected Remedy
                            Less Stringent Scenario
                            More Stringent Scenario
SO2 (Annual)
7.2
3.4
3.5
2.4
NOX (Annual)
2.1
1.9
1.8
1.8
NOX (Ozone Season)
0.9
0.8
0.8
0.8

Table 10-3.  Summary of PM Annual Health Benefits, Costs, and Net Benefits of Versions of the Selected Remedy Option in 2014[a] (billions of 2007 dollars)
                                  Description
                                Selected Remedy
                            Less Stringent Scenario
                            More Stringent Scenario

Social costs[b]

   3 percent discount rate
                                     $0.81
                                     $0.43
                                     $3.6

   7 percent discount rate
                                     $0.81
                                     $0.43
                                     $3.6
Health PM benefits[c,d]

   3 percent discount rate
   7 percent discount rate
                               $110 to $270 + B
                               $100 to $250 + B
                                $98 to $240 + B
                                $89 to $220 + B
                               $130 to $320 + B
                               $120 to $290 + B
Net benefits (benefits-costs)[e,f]

   3 percent discount rate
   7 percent discount rate
                               $110 to $270 + B
                               $100 to $250 + B
                                $98 to $240 + B
                                $88 to $220 + B
                               $130 to $320 + B
                               $120 to $290 + B
 [a]Estimates rounded to two significant figures.
[b]	Note that costs are the annualized total social costs of reducing pollutants including NOx and SO2 for the EGU source category in the final Transport Rule region in 2014.  Social costs are estimated using the MultiMarket model, the model employed by EPA in this RIA to estimate economic impacts to industries outside the electric power sector. This model does not estimate indirect impacts associated with a regulation such as this one. More information on the social costs can be found in Chapter 8 and Appendix B of this RIA.
[c]	Due to methodological limitations, the health benefits of these remedy options include PM2.5  - related benefits but omit visibility, ozone, and CO2-related benefits. We present the PM2.5  - related benefits of the preferred remedy, omitting these other important benefits, so that readers may compare directly the benefits of the preferred and alternate remedies.   Total benefits are comprised primarily of the value of PM-related avoided premature mortalities.  The reduction in these premature mortalities in each year account for over 90 percent of total PM2.5-related monetized benefits.  Benefits in this table are nationwide and are associated with NOx and SO2 reductions. To ensure that the benefits of the selected remedy and the more and less stringent scenarios are directly comparable, we exclude the visibility-related benefits of the selected remedy from this table; these visibility-related benefits are approximately $ 4.1 billion (2007$).
[d]	Not all possible benefits or disbenefits are quantified and monetized in this analysis.  B is the sum of all unquantified benefits and disbenefits.  Potential benefit categories that have not been quantified and monetized are listed in Table 1-5.
[e]	Valuation assumes discounting over the SAB-recommended 20-year segmented lag structure.  Results reflect the use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for preparing economic analyses (EPA, 2010; OMB, 2003).
[f]	Net benefits are rounded to three significant figures.  Columnar totals may not sum due to rounding.
*	 The 2014 compliance costs (incremental to the base case) for the selected remedy, less stringent scenario, and more stringent scenario are approximately $0.8, $0.4 and $3.6 billion in 2007 dollars.

10.2	References
Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery.  2006. Reduction in Fine Particulate Air Pollution and Mortality.  American Journal of Respiratory and Critical Care Medicine 173:667-672.

	Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston.  2002.  "Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution."  Journal of the American Medical Association 287:1132-1141.
U.S. Environmental Protection Agency (EPA).  December 2010.  Guidelines for Preparing Economic Analyses.  EPA 240-R-10-001.
U.S. Office of Management and Budget (OMB).  2003.  Circular A-4 Guidance to Federal Agencies on Preparation of Regulatory Analysis.
Woodruff, T.J., J. Grillo, and K.C. Schoendorf.  1997.  "The Relationship Between Selected Causes of Postneonatal Infant Mortality and Particulate Infant Mortality and Particulate Air Pollution in the United States."  Environmental Health Perspectives 105(6):608-612.

--------------------------------------------------------------------------------
                        Appendix A
--------------------------------------------------------------------------------

--------------------------------------------------------------------------------
Distribution of the PM2.5-Related Benefits Among Vulnerable and Susceptible Populations

Characterizing the distribution of health impacts across the population
This analysis aims to answer two principal questions regarding the distribution of PM2.5-related benefits resulting from the implementation of the final Transport Rule:
   1. What is the baseline distribution of PM2.5-related mortality risk according to the race, income and education of the population?
   2. How does the Transport Rule change the distribution of risk among populations of different races -- particularly among those populations at greatest risk in the baseline?
In this analysis we find that the level of PM2.5 mortality risk is not distributed equally throughout the U.S., or among populations of different levels of educational attainment -- though the level of mortality risk appears to be shared fairly equally among populations of different races. We find that the Transport Rule provides air quality improvements, and lowers PM2.5-related mortality risk, fairly equally among minority populations and greatly reduces PM2.5 mortality risk among those populations at greatest risk in the baseline.

    Methodology

As a first step, we estimate the level of PM2.5-related mortality risk in each county in the continental U.S. based on 2005 air quality levels, which provides a baseline against which projected changes in PM2.5 risk attributable to the Transport rule may be compared. This portion of the analysis follows an approach described elsewhere (Fann et al. 2011a, Fann et al. 2011b), wherein modeled 2005 PM2.5 levels are used to calculate the proportion of all-cause mortality risk attributable to total PM2.5 levels in each county in the Continental U.S. Within each county we estimate the level of all-cause PM2.5 mortality risks for adult populations as well as the level of PM2.5 mortality risk according to the race, income and educational attainment of the population.

Our approach to calculating PM2.5 mortality risk is generally consistent with the primary analysis with the two exceptions: the PM mortality risk coefficients used to quantify impacts and the baseline mortality rates used to calculate mortality impacts (a detailed discussion of how both the mortality risk coefficients and baseline incidence rates are used to estimate the incidence of PM2.5-related deaths may be found in the benefits chapter). We substitute risk estimates drawn from the Krewski et al. (2009) extended analysis of the ACS cohort. In particular, we applied the all-cause mortality risk estimate random effects Cox model that controls for 44 individual and 7 ecological covariates, using average exposure levels for 1999-2000 over 116 U.S. cities (Krewski et al. 2009) (RR=1.06, 95% confidence intervals 1.04 -- 1.08 per 10ug/m[3] increase in PM2.5. This mean relative risk estimate is identical to the Pope et al. (2002) risk estimate applied for the primary analysis (thought the standard error around the mean RR estimate is slightly different).

Within both this and other analyses of the ACS cohort (see: Krewski et al. 2000), educational attainment has been found to be inversely related to the risk of all-cause mortality. That is, populations with lower levels of education (in particular, < grade 12) are more vulnerable to PM2.5-related mortality. Krewski and colleagues note that "...the level of education attainment may likely indicate the effects of complex and multifactorial socioeconomic processes on mortality...", factors that we would like to account for in this EJ assessment. When estimating PM mortality impacts among populations according to level of education, we applied PM2.5 mortality risk coefficients modified by educational attainment: less than grade 12 (RR = 1.082, 95% confidence intervals 1.024 -- 1.144 per 10 ug/m[3] change), grade 12 (RR = 1.072, 95% confidence intervals 1.020 -- 1.127 per 10 ug/m[3] change), and greater than grade 12 (RR = 1.055, 95% confidence intervals 1.018 -- 1.094 per 10 ug/m[3] change). The Pope et al. (2002) study does not provide education-stratified RR estimates. The principal reason we applied risk estimates from the Krewski study was to ensure that the risk coefficients used to estimate all-cause mortality risk and education-modified mortality risk were drawn from a consistent modeling framework.

The other key difference between this distributional analysis and the primary analysis relates to the baseline mortality rates. As described in the benefits chapter, we calculate PM-related mortality risk relative to baseline mortality rates in each county. Traditionally we have applied county-level age- and sex-stratified rates when calculating these impacts (Abt, 2008). For the calculation of PM impacts by race, we incorporated race-specific (stratified by White/Black/Asian/Native American) baseline mortality rates. This approach improves our ability to characterize the relationship between race and susceptibility to PM2.5-related mortality.

The result of this analysis is a distribution of PM2.5 mortality risk estimates by county, stratified by each of the three population variables (race, income and educational attainment). We next identified the counties at or above the median and upper 95[th] percentile of the PM2.5 mortality risk distribution. We selected this percentile cut-off to capture the very highest levels of PM2.5 mortality risk. The second step of the analysis was to repeat the sequence above by estimating PM2.5 mortality risk in 2014 prior to, and after, the implementation of the Transport Rule. We also report the per-person PM2.5 exposure for each of the three scenarios (2005, 2014, 2014 post-Transport Rule) by populations of different race.

	Results

The level of PM2.5 exposure and mortality risk among all populations declines significantly between 2005, 2014 prior to, and then after, the implementation of the Transport Rule (Table 1, Figures 1 -- 3). In each figure we outline in yellow those counties at or above the 2005 median risk level. The number of counties at or above this level falls significantly between 2005 and the implementation of the 2014 Transport Rule, suggesting that the combination of this rule as well as others being implemented between 2005 and 2014 greatly reduce the level of PM mortality risk among adult populations.

We next stratify the PM mortality risk according to race, income and educational attainment. For these analyses we estimated the change in PM mortality risk between 2005 and 2014 among populations living in those counties at the upper 95[th] percentile of the mortality risk in the 2005 baseline; we then compared the change in risk among these populations living in high-risk counties with populations living in all other counties. Figures 4 -- 6 summarize these results. Tables 2-4 enumerate the data used to construct these figures.

In Figure 4, we plot the level of PM mortality risk among populations of different races according to whether those populations live in counties identified as "greater risk" counties or "all other counties." As described above, we define "greater risk" counties as those at or above the 95[th] percentile of PM2.5 mortality risk in 2005, and "all other counties" as those with PM2.5 mortality risk below this level. The results of this analysis suggest that the PM2.5 mortality risk among these populations at "greater risk" falls significantly between 2005, 2014 and the implementation of the 2014 Transport Rule. Upon implementing the 2014 Transport Rule, the estimated PM2.5 mortality risk among these populations is roughly equal to the level of PM2.5 mortality risk experienced by those populations in "all other counties" in 2005. These results also suggest that all populations, irrespective of race, are receiving a reduction in PM2.5 mortality risk; limits to data resolution prevent us from delineating the PM mortality risk according to population race with confidence.

In Figure 5, we illustrate the change in the level of PM2.5 mortality risk among populations living in those counties that meet two criteria: (1) the county is at the upper 95[th] percentile of mortality risk in 2005; (2) the county is at the upper 95[th] percentile in terms of the number of individuals living below the poverty line. We also estimate the change in PM2.5 risk among all other counties.  The analysis indicates that people living in the highest risk and poorest counties will experience a larger improvement in PM2.5 mortality risk than those living in lower risk counties containing a smaller number of individuals living below the poverty line..

In Figure 6, we summarize the change in PM2.5 mortality risk among populations who have attained three alternate levels of education -- less than highschool, highschool and greater than highschool. As described above, we apply education-stratified PM2.5 mortality risk coefficients for this analysis. These results indicate that populations with less than a highschool education are at higher risk of PM2.5 mortality in 2005, irrespective of whether these populations live in "greater risk" counties, according to the definition described above. Between 2005 and the 2014 Transport Rule, all populations see their mortality risk fall, regardless of educational attainment.

Figure 1: Distribution of PM2.5 mortality risk in 2005

Figure 2: Distribution of PM2.5 mortality risk in 2014 (prior to the implementation of the Transport Rule)

Figure 3: Distribution of PM2.5 mortality risk in 2014 (after the implementation of the Transport Rule)

Table 1: Per-person level of annual mean PM2.5 exposure (ug/m[3]/person) between 2005 and the 2014 Transport Rule

Year
                                     Race

                                     Asian
                                     Black
                                Native American
                                     White
2005
                                     11.5
                                     12.1
                                       9
                                     10.7
2014 (pre-Transport Rule)
                                      9.4
                                      9.6
                                      7.7
                                      8.7
2014 (post-Transport Rule
                                      8.9
                                      8.5
                                      7.1
                                      7.8

Figure 4: Change in the percentage of PM2.5-attributable deaths by race between 2005 and the implementation of the 2014 Transport Rule

Table 2: Numerical values used for Figure 4 above

Year
                                     Race

                                     Asian
                                     Black
                                Native American
                                     White
Among populations at greater risk

   2005
                                     7.9%
                                     7.8%
                                     7.9%
                                     8.0%
   2014 (pre-Transport Rule)
                                     6.2%
                                     5.9%
                                     6.1%
                                     6.2%
   2014 (post-Transport Rule
                                     5.1%
                                      5%
                                     5.1%
                                     5.2%
Among all other populations

   2005
                                     4.9%
                                     5.0%
                                     4.5%
                                     5.2%
   2014 (pre-Transport Rule)
                                     4.2%
                                     4.2%
                                     4.2%
                                     4.2%
   2014 (post-Transport Rule
                                     3.5%
                                     3.6%
                                     3.4%
                                     3.8%

Figure 5: Change in the percentage of PM2.5-attributable deaths among populations by poverty level between 2005 and the implementation of the 2014 Transport Rule

Table 3: Numerical values used for Figure 5 above

Year
                                     Race

                                     Asian
                                     Black
                                Native American
                                     White
Among populations living in counties with the largest number of individuals living below the poverty line

   2005
                                     7.9%
                                     7.8%
                                     7.9%
                                      8%
   2014 (pre-Transport Rule)
                                     6.1%
                                     6.1%
                                     6.2%
                                     6.3%
   2014 (post-Transport Rule
                                     5.3%
                                     5.3%
                                     5.4%
                                     5.4%
Among all other populations

   2005
                                     4.9%
                                      5%
                                     4.6%
                                     5.3%
   2014 (pre-Transport Rule)
                                     4.1%
                                     4.2%
                                     3.9%
                                     4.4%
   2014 (post-Transport Rule
                                     3.5%
                                     3.6%
                                     3.4%
                                     3.8%

Figure 6: Change in the percentage of PM2.5-attributable deaths among populations by educational attainment between 2005 and the implementation of the 2014 Transport Rule

Table 4: Numerical values used for Figure 6 above

Year
                                     Race

                                 < Grade 12
                                  = Grade 12
                                 > Grade 12
Among populations at greater risk

   2005
                                     11.0%
                                     9.1%
                                     7.5%
   2014 (pre-Transport Rule)
                                     8.4%
                                     7.4%
                                     5.8%
   2014 (post-Transport Rule
                                     7.1%
                                     6.3%
                                     4.9%
Among all other populations

   2005
                                     7.2%
                                     6.4%
                                     4.9%
   2014 (pre-Transport Rule)
                                      6%
                                     5.3%
                                     4.1%
   2014 (post-Transport Rule
                                     5.2%
                                     4.6%
                                     3.6%

References

Fann N, Roman HR, Fulcher CF, Gentile M, Wesson K, Hubbell BJ, Levy JI. Maximizing Health Benefits and Minimizing Inequality: Incorporating Local Scale Data in the Design and Evaluation of Air Quality Policies. Risk Analysis; 2011a. In Press.

Fann N, Lamson A, Wesson K, Risley D, Anenberg SC, Hubbell BJ. Estimating the National Public Health Burden Associated with Exposure to Ambient PM2.5 and Ozone. Risk Analysis; 2011b. In Press.