Estuaries in the eastern United States are an important source of food production, in particular fish and shellfish production.  The estuaries are capable of supporting large stocks of resident commercial species, and they serve as the breeding grounds and interim habitat for several migratory species.  To provide an indication of the magnitude of provisioning services associated with coastal fisheries, from 2005 to 2007, the average value of total catch was $1.5 billion per year.  It is not known, however, what percentage of this value is directly attributable to or dependent upon the estuaries in these states.
In addition to affecting provisioning services through commercial fish harvests, eutrophication in estuaries may also affect the demand for seafood.  For example, a well-publicized toxic pfiesteria bloom in the Maryland Eastern Shore in 1997, which involved thousands of dead and lesioned fish, led to an estimated $56 million (in 2007 dollars) in lost seafood sales for 360 seafood firms in Maryland in the months following the outbreak (Lipton, 1999).
Estuaries in the United States also provide an important and substantial variety of cultural ecosystem services, including water-based recreational and aesthetic services.  The water quality in the estuary directly affects the quality of these experiences. For example, there were 26 million days of saltwater fishing coastal states from North Carolina to Massachusetts in 2006 (FWA and Census, 2007).  Assuming an average consumer surplus value for a fishing day at $36 (in 2007 dollars) in the Northeast and $87 in the Southeast (Kaval and Loomis, 2003), the aggregate value was approximately $1.3 billion (in 2007 dollars).  In addition, almost 6 million adults participated in motorboating in coastal states from North Carolina to Massachusetts, for a total of nearly 63 million days annually during 1999 - 2000 (Leeworthy and Wiley, 2001).  Using a national daily value estimate of $32 (in 2007 dollars) for motorboating (Kaval and Loomis (2003), the aggregate value of these coastal motorboating outings was $2 billion per year.   Almost 7 million participated in birdwatching for 175 million days per year, and more than 3 million participated in visits to non-beach coastal waterside areas.
Estuaries and marshes have the potential to support a wide range of regulating services, including climate, biological, and water regulation; pollution detoxification; erosion prevention; and protection against natural hazards from declines in SAV (MEA, 2005).  SAV can help reduce wave energy levels and thus protect shorelines against excessive erosion, which increases the risks of episodic flooding and associated damages to near-shore properties or public infrastructure or even contribute to shoreline retreat.
<IP_ADDRESS> Terrestrial Enrichment

      Terrestrial enrichment occurs when terrestrial ecosystems receive N loadings in excess of natural background levels, either through atmospheric deposition or direct application.  Evidence presented in the Integrated Science Assessment (U.S. EPA, 2008f) supports a causal relationship between atmospheric N deposition and biogeochemical cycling and fluxes of N and carbon in terrestrial systems.  Furthermore, evidence summarized in the report supports a causal link between atmospheric N deposition and changes in the types and number of species and biodiversity in terrestrial systems.  Nitrogen enrichment occurs over a long time period; as a result, it may take as much as 50 years or more to see changes in ecosystem conditions and indicators.  This long time scale also affects the timing of the ecosystem service changes. The ISA for NOx/SOx  -  Ecological Criteria concluded that the evidence is sufficient to infer a causal relationship between nitrogen deposition and the alteration of species richness, species composition, and biodiversity in terrestrial ecosystems (U.S. EPA, 2008f).
One of the main provisioning services potentially affected by N deposition is grazing opportunities offered by grasslands for livestock production in the Central U.S.  Although N deposition on these grasslands can offer supplementary nutritive value and promote overall grass production, there are concerns that fertilization may favor invasive grasses and shift the species composition away from native grasses. This process may ultimately reduce the productivity of grasslands for livestock production.  Losses due to invasive grasses can be significant; for example, based on a bioeconomic model of cattle grazing in the upper Great Plains, Leitch, Leistritz, and Bangsund (1996) and Leistritz, Bangsund, and Hodur (2004) estimated $130 million in losses due to a leafy spurge infestation in the Dakotas, Montana, and Wyoming.  However, the contribution of N deposition to these losses is still uncertain.
Terrestrial nutrient enrichment also affects cultural and regulating services. For example, in California, Coastal Sage Scrub (CSS) habitat concerns focus on a decline in CSS and an increase in nonnative grasses and other species, impacts on the viability of threatened and endangered species associated with CSS, and an increase in fire frequency. Changes in Mixed Conifer Forest (MCF) include changes in habitat suitability and increased tree mortality, increased fire intensity, and a change in the forest's nutrient cycling that may affect surface water quality through nitrate leaching (U.S. EPA, 2008f). CSS and MCF are an integral part of the California landscape, and together the ranges of these habitats include the densely populated and valuable coastline and the mountain areas.  Numerous threatened and endangered species at both the state and federal levels reside in CSS and MCF. The value that California residents and the U.S. population as a whole place on CSS and MCF habitats is reflected in the various federal, state, and local government measures that have been put in place to protect these habitats, including the Endangered Species Act, conservation planning programs, and private and local land trusts. CSS and MCF habitat are showcased in many popular recreation areas in California, including several national parks and monuments. In addition, millions of  individuals are involved in fishing, hunting, and wildlife viewing in California every year (DOI, 2007). The quality of these trips depends in part on the health of the ecosystems and their ability to support the diversity of plants and animals found in important habitats found in CSS or MCF ecosystems and the parks associated with those ecosystems. Based on analyses in the NOx SOx REA average values of the total benefits in 2006 from fishing, hunting, and wildlife viewing away from home in California were approximately $950 million, $170 million, and $3.6 billion, respectively (U.S.EPA, 2009c). In addition, data from California State Parks (2003) indicate that in 2002, 69% of adult residents participated in trail hiking for an average of 24 days per year. The aggregate annual benefit for California residents from trail hiking in 2007 was $11 billion (U.S.EPA, 2009c). It is not currently possible to quantify the loss in value of services due to nitrogen deposition as those losses are already reflected in the estimates of the contemporaneous total value of these recreational activities. Restoration of services through decreases in nitrogen deposition would likely increase the total value of recreational services.
Fire regulation is also an important regulating service that could be affected by nutrient enrichment of the CSS and MCF ecosystems by encouraging growth of more flammable grasses, increasing fuel loads, and altering the fire cycle. Over the 5-year period from 2004 to 2008, Southern California experienced, on average, over 4,000 fires per year burning, on average, over 400,000 acres per year (National Association of State Foresters [NASF], 2009). It is not possible at this time to quantify the contribution of nitrogen deposition, among many other factors, to increased fire risk.

5.5.6 Benefits of Reducing Ozone Effects on Vegetation and Ecosystems

Ozone causes discernible injury to a wide array of vegetation (U.S. EPA, 2006a; Fox and Mickler, 1996).   Sensitivity to ozone is highly variable across plant species, with over 65 plant species identified as "ozone-sensitive", many of which occur in state and national parks and forests. In terms of forest productivity and ecosystem diversity, ozone may be the pollutant with the greatest potential for regional-scale forest impacts (U.S. EPA, 2006a).  Studies have demonstrated repeatedly that ozone concentrations commonly observed in polluted areas can have substantial impacts on plant function (De Steiguer et al., 1990; Pye, 1988).
      When ozone is present in the air, it can enter the leaves of plants, where it can cause significant cellular damage.  Like carbon dioxide (CO2) and other gaseous substances, ozone enters plant tissues primarily through the stomata in leaves in a process called "uptake" (Winner and Atkinson, 1986).  Once sufficient levels of ozone (a highly reactive substance), or its reaction products, reaches the interior of plant cells, it can inhibit or damage essential cellular components and functions, including enzyme activities, lipids, and cellular membranes, disrupting the plant's osmotic (i.e., water) balance and energy utilization patterns (U.S. EPA, 2006a; Tingey and Taylor, 1982).  With fewer resources available, the plant reallocates existing resources away from root growth and storage, above ground growth or yield, and reproductive processes, toward leaf repair and maintenance, leading to reduced growth and/or reproduction.  Studies have shown that plants stressed in these ways may exhibit a general loss of vigor, which can lead to secondary impacts that modify plants' responses to other environmental factors.  Specifically, plants may become more sensitive to other air pollutants, or more susceptible to disease, pest infestation, harsh weather (e.g., drought, frost) and other environmental stresses, which can all produce a loss in plant vigor in ozone-sensitive species that over time may lead to premature plant death.  Furthermore, there is evidence that ozone can interfere with the formation of mycorrhiza, essential symbiotic fungi associated with the roots of most terrestrial plants, by reducing the amount of carbon available for transfer from the host to the symbiont (U.S. EPA, 2006a).
      This ozone damage may or may not be accompanied by visible injury on leaves, and likewise, visible foliar injury may or may not be a symptom of the other types of plant damage described above.  Foliar injury is usually the first visible sign of injury to plants from ozone exposure and indicates impaired physiological processes in the leaves (Grulke, 2003).  When visible injury is present, it is commonly manifested as chlorotic or necrotic spots, and/or increased leaf senescence (accelerated leaf aging).  Because ozone damage can consist of visible injury to leaves, it can also reduce the aesthetic value of ornamental vegetation and trees in urban landscapes, and negatively affects scenic vistas in protected natural areas.
	Ozone can produce both acute and chronic injury in sensitive species depending on the concentration level and the duration of the exposure.  Ozone effects also tend to accumulate over the growing season of the plant, so that even lower concentrations experienced for a longer duration have the potential to create chronic stress on sensitive vegetation.  Not all plants, however, are equally sensitive to ozone.  Much of the variation in sensitivity between individual plants or whole species is related to the plant's ability to regulate the extent of gas exchange via leaf stomata (e.g., avoidance of ozone uptake through closure of stomata) (U.S. EPA, 2006a; Winner, 1994).  After injuries have occurred, plants may be capable of repairing the damage to a limited extent (U.S. EPA, 2006a).  Because of the differing sensitivities among plants to ozone, ozone pollution can also exert a selective pressure that leads to changes in plant community composition.  Given the range of plant sensitivities and the fact that numerous other environmental factors modify plant uptake and response to ozone, it is not possible to identify threshold values above which ozone is consistently toxic for all plants.
	Because plants are at the base of the food web in many ecosystems, changes to the plant community can affect associated organisms and ecosystems (including the suitability of habitats that support threatened or endangered species and below ground organisms living in the root zone).  Ozone impacts at the community and ecosystem level vary widely depending upon numerous factors, including concentration and temporal variation of tropospheric ozone, species composition, soil properties and climatic factors (U.S. EPA, 2006a).  In most instances, responses to chronic or recurrent exposure in forested ecosystems are subtle and not observable for many years.  These injuries can cause stand-level forest decline in sensitive ecosystems (U.S. EPA, 2006a, McBride et al., 1985; Miller et al., 1982).  It is not yet possible to predict ecosystem responses to ozone with much certainty; however, considerable knowledge of potential ecosystem responses has been acquired through long-term observations in highly damaged forests in the United States (U.S EPA, 2006a).
<IP_ADDRESS> Ozone Effects on Forests
      Air pollution can affect the environment and affect eco - logical systems, leading to changes in the ecological com - munity and influencing the diversity, health, and vigor of individual species (U.S. EPA, 2006a).  Ozone has been shown in numerous studies to have a strong effect on the health of many plants, including a variety of commercial and ecologically impor - tant forest tree species throughout the United States (U.S. EPA, 2007b).
      In the U.S., this data comes from the U.S. Department of Agriculture (USDA) Forest Service Forest Inventory and Analysis (FIA) program.  As part of its Phase 3 program, formerly known as Forest Health Monitoring, FIA examines ozone injury to ozone-sensitive plant species at ground moni - toring sites in forestland across the country (excluding woodlots and urban trees).  FIA looks for damage on the foliage of ozone-sensitive forest plant species at each site that meets certain minimum criteria.  Because ozone injury is cumulative over the course of the growing season, examinations are conducted in July and August, when ozone injury is typically highest.
      Monitoring of ozone injury to plants by the USDA Forest Service has expanded over the last 15 years from monitoring sites in 10 states in 1994 to nearly 1,000 monitoring sites in 41 states in 2002.  Since 2002, the monitoring program has further expanded to 1,130 monitoring sites in 45 states.  Figure 5-13 shows the results of this monitoring program for the year 2002 broken down by U.S. EPA Regions.  Figure 5-14 identifies the counties that were included in Figure 5-13, and provides the county-level data regarding the presence or absence of ozone-related injury.  As shown in Figure 5-14 large geographic areas of EPA Regions 6, 8, and 10 were not included in the assessment. Ozone damage to forest plants is classified using a subjective five-category biosite index based on expert opinion, but designed to be equivalent from site to site.  Ranges of biosite values translate to no injury, low or moderate foliar injury (visible foliar injury to highly sensi - tive or moderately sensitive plants, respectively), and high or severe foliar injury, which would be expected to result in tree-level or ecosystem-level responses, respectively (U.S. EPA, 2006a; Coulston, 2004).  The highest percentages of observed high and severe foliar injury, which are most likely to be associated with tree or ecosystem-level responses, are primarily found in the Mid-Atlantic and Southeast regions.  While the assessment showed considerable regional variation in ozone injury, this assessment targeted different ozone-sensitive species in different parts of the country with varying ozone sensitivity, which contributes to the apparent regional differences.  It is important to note that ozone can have other, more significant impacts on forest plants (e.g. reduced  biomass growth in trees) prior to showing signs of visible foliar injury (U.S. EPA, 2006a).

Figure 5-13: Visible Foliar Injury to Forest Plants from Ozone in U.S. by EPA Regions, [a, b][, c]

                 		[c] Degree of Injury: These categories reflect a subjective index based on expert opinion.  Ozone can have other, more significant impacts on forest plants (e.g. reduced biomass growth in trees) prior to showing signs of visible foliar injury.

	Figure 5-14. Presence and Absence of Visible Foliar Injury, as measured by U.S. Forest Service, 2002 (U.S. EPA, 2007)

Assessing the impact of ground-level ozone on forests in the eastern United States involves understanding the risks to sensitive tree species from ambient ozone concentrations and accounting for the prevalence of those species within the forest.  As a way to quantify the risks to particular plants from ground-level ozone, scientists have developed ozone-exposure/tree-response functions by exposing tree seedlings to different ozone levels and measuring reductions in growth as "biomass loss."  Typically, seedlings are used because they are easy to manipulate and measure their growth loss from ozone pollution.  The mechanisms of susceptibility to ozone within the leaves of seedlings and mature trees are identical, and the decreases predicted using the seedlings should be related to the decrease in overall plant fitness for mature trees, but the magnitude of the effect may be higher or lower depending on the tree species (Chappelka and Samuelson, 1998).  In areas where certain ozone-sensitive species dominate the forest community, the biomass loss from ozone can be sig - nificant.  Experts have identified 2% annual biomass loss as a level of concern, which would cause long term ecological harm as the short-term negative effects on seedlings compound to affect long-term forest health (Heck and Cowling, 1997).
      Some of the common tree species in the United States that are sensitive to ozone are black cherry (Prunus serotina), tulip-poplar (Liriodendron tulipifera), and eastern white pine (Pinus strobus).  Ozone-exposure/tree-response functions have been developed for each of these tree species, as well as for aspen (Populus tremuliodes), and ponderosa pine (Pinus ponderosa) (U.S. EPA, 2007b).  Other common tree species, such as oak (Quercus spp.) and hickory (Carya spp.), are not as sensitive to ozone.  Consequently, with knowledge of the distribution of sensitive species and the level of ozone at particular locations, it is possible to estimate a "biomass loss" for each species across their range.  As shown in Figure 5-15, current ambient levels of ozone are associated with significant biomass loss across large geographic areas (U.S. EPA, 2009b).  However, this information is unavailable for this final rule.
      To estimate the biomass loss for forest ecosystems across the eastern Unit - ed States, the biomass loss for each of the seven tree spe - cies was calculated using the three-month, 12-hour W126 exposure metric at each location, along with each tree's individual C-R functions.  The W126 exposure metric was calculated using monitored ozone data from CASTNET and AQS sites, and a three-year average was used to mitigate the effect of variations in meteorological and soil moisture conditions.  The biomass loss estimate for each species was then multiplied by its prevalence in the forest community using the U.S. Department of Agriculture (USDA) Forest Service IV index of tree abundance calculated from Forest Inventory and Analysis (FIA) measurements (Prasad, 2003).  Sources of uncertainty include the ozone-exposure/plant-response functions, the tree abundance index, and other factors (e.g., soil moisture).  Although these factors were not considered, they can affect ozone damage (Chappelka, 1998).

Figure 5-15:  Estimated Black Cherry, Yellow Poplar, Sugar Maple, Eastern White Pine, Virginia Pine, Red Maple, and Quaking Aspen Biomass Loss due to Current Ozone Exposure, 2006-2008 (U.S. EPA, 2009b)

      Ozone damage to the plants including the trees and understory in a forest can affect the ability of the forest to sustain suitable habitat for associated species particularly threatened and endangered species that have existence value  -  a nonuse ecosystem service - for the public.  Similarly, damage to trees and the loss of biomass can affect the forest's provisioning services in the form of timber for various commercial uses.  In addition, ozone can cause discoloration of leaves and more rapid senescence (early shedding of leaves), which could negatively affect fall-color tourism because the fall foliage would be less available or less attractive.  Beyond the aesthetic damage to fall color vistas, forests provide the public with many other recreational and educational services that may be affected by reduced forest health including hiking, wildlife viewing (including bird watching), camping, picnicking, and hunting.  Another potential effect of biomass loss in forests is the subsequent loss of climate regulation service in the form of reduced ability to sequester carbon (Felzer et al., 2005).

<IP_ADDRESS> Ozone Effects on Crops and Urban Ornamentals

      Laboratory and field experiments have also shown reductions in yields for agronomic crops exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g., cotton and wheat).  Damage to crops from ozone exposures includes yield losses (i.e., in terms of weight, number, or size of the plant part that is harvested), as well as changes in crop quality (i.e., physical appearance, chemical composition, or the ability to withstand storage) (U.S. EPA, 2007b).  The most extensive field experiments, conducted under the National Crop Loss Assessment Network (NCLAN) examined 15 species and numerous cultivars.  The NCLAN results show that "several economically important crop species are sensitive to ozone levels typical of those found in the United States" (U.S. EPA, 2006a).  In addition, economic studies have shown reduced economic benefits as a result of predicted reductions in crop yields, directly affecting the amount and quality of the provisioning service provided by these crops, associated with observed ozone levels (Kopp et al., 1985; Adams et al., 1986; Adams et al., 1989).  In addition, visible foliar injury by itself can reduce the market value of certain leafy crops (such as spinach, lettuce). According to the Ozone Staff Paper, there has been no evidence that crops are becoming more tolerant of ozone (U.S. EPA, 2007b).  Using the Agriculture Simulation Model (AGSIM) (Taylor, 1994) to calculate the agricultural benefits of reductions in ozone exposure, U.S. EPA estimated that attaining a W126 standard of 13 ppm-hr would produce monetized benefits of approximately $400 million to $620 million in 2006 (inflated to 2006 dollars) (U.S. EPA, 2007b).
      Urban ornamental plants are an additional vegetation category likely to experience some degree of negative effects associated with exposure to ambient ozone levels.  Several ornamental species have been listed as sensitive to ozone (Abt Associates, 1995).Because ozone causes visible foliar injury, the aesthetic value of ornamentals (such as petunia, geranium, and poinsettia) in urban landscapes would be reduced (U.S. EPA, 2007b).  Sensitive ornamental species would require more frequent replacement and/or increased maintenance (fertilizer or pesticide application) to maintain the desired appearance because of exposure to ambient ozone (U.S. EPA, 2007b).  In addition, many businesses rely on healthy-looking vegetation for their livelihoods (e.g., horticulturalists, landscapers, Christmas tree growers, farmers of leafy crops, etc.) and a variety of ornamental species have been listed as sensitive to ozone (Abt Associates, 1995).  The ornamental landscaping industry is  multi-billion industry that affected both private property owners/tenants and by governmental units responsible for public areas (Abt Associates, 1995).   Preliminary data from the 2007 Economic Census indicate that the landscaping services industry, which is primarily engaged in providing landscape care and maintenance services and installing trees, shrubs, plants, lawns, or gardens, was valued at $53 billion (U.S. Census Bureau, 2010).  Therefore, urban ornamentals represent a potentially large unquantified benefit category.  This aesthetic damage may affect the enjoyment of urban parks by the public and homeowners' enjoyment of their landscaping and gardening activities.  In addition, homeowners may experience a reduction in home value or a home may linger on the market longer due to decreased aesthetic appeal.  In the absence of adequate exposure-response functions and economic damage functions for the potential range of effects relevant to these types of vegetation, we cannot conduct a quantitative analysis to estimate these effects.

5.5.7 Unquantified SO2 and NO2 -Related Human Health Benefits
      Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment for Sulfur Dioxide concluded that there is a causal relationship between respiratory health effects and short-term exposure to SO2 (U.S. EPA, 2008).  The immediate effect of SO2 on the respiratory system in humans is bronchoconstriction.  Asthmatics are more sensitive to the effects of SO2 likely resulting from preexisting inflammation associated with this disease.  A clear concentration-response relationship has been demonstrated in laboratory studies following exposures to SO2 at concentrations between 20 and 100 ppb, both in terms of increasing severity of effect and percentage of asthmatics adversely affected. Based on our review of this information, we identified four short-term morbidity endpoints that the SO2 ISA identified as a "causal relationship": asthma exacerbation, respiratory-related emergency department visits, and respiratory-related hospitalizations.  The differing evidence and associated strength of the evidence for these different effects is described in detail in the SO2 ISA.  The SO2 ISA also concluded that the relationship between short-term SO2 exposure and premature mortality was "suggestive of a causal relationship" because it is difficult to attribute the mortality risk effects to SO2 alone.  Although the SO2 ISA stated that studies are generally consistent in reporting a relationship between SO2 exposure and mortality, there was a lack of robustness of the observed associations to adjustment for pollutants.  We did not quantify these benefits due to time constraints.
      Epidemiological researchers have associated NO2 exposure with adverse health effects in numerous toxicological, clinical and epidemiological studies, as described in the Integrated Science Assessment for Oxides of Nitrogen - Health Criteria (Final Report) (U.S. EPA, 2008c).  The NO2 ISA provides a comprehensive review of the current evidence of health and environmental effects of NO2.  The NO2 ISA concluded that the evidence "is sufficient to infer a likely causal relationship between short-term NO2 exposure and adverse effects on the respiratory system" (ISA, section <IP_ADDRESS>).  These epidemiologic and experimental studies encompass a number of endpoints including [Emergency Department (ED)] visits and hospitalizations, respiratory symptoms, airway hyperresponsiveness, airway inflammation, and lung function.  Effect estimates from epidemiologic studies conducted in the United States and Canada generally indicate a 2-20% increase in risks for ED visits and hospital admissions and higher risks for respiratory symptoms (ISA, section 5.4).  The NO2 ISA concluded that the relationship between short-term NO2 exposure and premature mortality was "suggestive but not sufficient to infer a causal relationship" because it is difficult to attribute the mortality risk effects to NO2 alone.  Although the NO2 ISA stated that studies consistently reported a relationship between NO2 exposure and mortality, the effect was generally smaller than that for other pollutants such as PM.  We did not quantify these benefits due to time constraints.

5.6 Social Cost of Carbon and Greenhouse Gas Benefits

      EPA has assigned a dollar value to reductions in carbon dioxide (CO2) emissions using recent estimates of the "social cost of carbon" (SCC).  The SCC is an estimate of the monetized damages associated with an incremental increase in carbon emissions in a given year.  It is intended to include (but is not limited to) changes in net agricultural productivity, human health, property damages from increased flood risk, and the value of ecosystem services due to climate change.  The SCC estimates used in this analysis were developed through an interagency process that included EPA and other executive branch entities, and concluded in February 2010.  EPA first used these SCC estimates in the benefits analysis for the final joint EPA/DOT Rulemaking to establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards; see the rule's preamble for discussion about application of SCC (75 FR 25324; 5/7/10).  The SCC Technical Support Document (SCC TSD) provides a complete discussion of the methods used to develop these SCC estimates.
      The interagency group selected four SCC values for use in regulatory analyses, which we have applied in this analysis: $5, $21, $35, and $65 per metric ton of CO2 emissions in 2010, in 2007 dollars.  The first three values are based on the average SCC from three integrated assessment models, at discount rates of 2.5, 3, and 5 percent, respectively.  SCCs at several discount rates are included because the literature shows that the SCC is quite sensitive to assumptions about the discount rate, and because no consensus exists on the appropriate rate to use in an intergenerational context. The fourth value is the 95th percentile of the SCC from all three models at a 3 percent discount rate.  It is included to represent higher-than-expected impacts from temperature change further out in the tails of the SCC distribution. Low probability, high impact events are incorporated into all of the SCC values through explicit consideration of their effects in two of the three models as well as the use of a probability density function for equilibrium climate sensitivity.  Treating climate sensitivity probabilistically results in more high temperature outcomes, which in turn lead to higher projections of damages.
      The SCC increases over time because future emissions are expected to produce larger incremental damages as physical and economic systems become more stressed in response to greater climatic change.  Note that the interagency group estimated the growth rate of the SCC directly using the three integrated assessment models rather than assuming a constant annual growth rate. This helps to ensure that the estimates are internally consistent with other modeling assumptions.   The SCC estimates for the analysis years of 2014, in 2007 dollars are provided in Table 5-15.
      When attempting to assess the incremental economic impacts of carbon dioxide emissions, the analyst faces a number of serious challenges.  A recent report from the National Academies of Science (NRC 2009) points out that any assessment will suffer from uncertainty, speculation, and lack of information about (1) future emissions of greenhouse gases, (2) the effects of past and future emissions on the climate system, (3) the impact of changes in climate on the physical and biological environment, and (4) the translation of these environmental impacts into economic damages.  As a result, any effort to quantify and monetize the harms associated with climate change will raise serious questions of science, economics, and ethics and should be viewed as provisional.
      The interagency group noted a number of limitations to the SCC analysis, including the incomplete way in which the integrated assessment models capture catastrophic and non-catastrophic impacts, their incomplete treatment of adaptation and technological change, uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk aversion.  The limited amount of research linking climate impacts to economic damages makes the interagency modeling exercise even more difficult.  The interagency group hopes that over time researchers and modelers will work to fill these gaps and that the SCC estimates used for regulatory analysis by the Federal government will continue to evolve with improvements in modeling. Additional details on these limitations are discussed in the SCC TSD.
      In light of these limitations, the interagency group has committed to updating the current estimates as the science and economic understanding of climate change and its impacts on society improves over time.  Specifically, the interagency group has set a preliminary goal of revisiting the SCC values within two years or at such time as substantially updated models become available, and to continue to support research in this area.
      Applying the global SCC estimates to the estimated reductions in CO2 emissions for the range of policy scenarios, we estimate the dollar value of the climate related benefits captured by the models for each analysis year.  For internal consistency, the annual benefits are discounted back to NPV terms using the same discount rate as each SCC estimate (i.e. 5%, 3%, and 2.5%) rather than 3% and 7%. These estimates are provided in Table 5-16.

Table 5-15.  Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2014 (in 2007$)[a]
Discount Rate and Statistic
                                 SCC estimate
5%     Average
                                                                           $5.5
3%     Average
                                                                          $23.4
2.5%  Average
                                                                          $37.7
3%     95%ile
                                                                          $71.2
[a] The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts.

Table 5-16.  Monetized SCC-Derived Benefits of CO2 Emissions Reductions in 2014 (in millions of 2007$)[a]
Discount Rate and Statistic
                                            SCC-derived benefits
Tons of CO2 reduced (millions)
                                                                             25

5%     Average
                                                                           $140
3%     Average
                                                                           $590
2.5%  Average
                                                                           $950
3%     95%ile
                                                                         $1,800
[a] The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts.

5.7 Benefits Results
	Applying the impact and valuation functions described previously in this chapter to the estimated changes in ozone and PM yields estimates of the changes in physical damages (e.g., premature mortalities, cases, admissions, and change in light extinction) and the associated monetary values for those changes.  Estimates of physical health impacts among those states in either the ozone or PM2.5 trading region, or outside the trading region, are presented in Table 5-17.  Monetized values for both health and welfare endpoints within the trading region are presented in Table 5-18, along with total aggregate monetized benefits. All of the monetary benefits are in constant-year 2007 dollars. The PM2.5-related benefits of the more and less stringent scenarios were within about 15% of the selected remedy. The results of that analysis may be found in the cost-benefit comparison chapter (Chapter 10 of this RIA). Table 5-17: Estimated Reduction in Incidence of Adverse Health Effects of the Selected remedy (95% confidence intervals)[A]
Health Effect
                            Within transport region
                            Beyond transport region
                                     Total
PM-Related endpoints

Premature Mortality

Pope et al. (2002) (age >30)
                                    13,000
                               (5,200 -- 21,000)
                                      33
                                   (5 -- 60)
                                    13,000
                               (5,200 -- 21,000)

Laden et al. (2006) (age >25)
                                    34,000
                               (18,000 -- 49,000)
                                      84
                                  (31 -- 140)
                                    34,000
                               (18,000 -- 49,000)

Infant (< 1 year)
                                      59
                                  (-47 -- 160)
                                     0.15
                                 (-0.2 -- 0.5)
                                      59
                                  (-47 -- 160)
Chronic Bronchitis
                                     8,700
                               (1,600 -- 16,000)
                                      23
                                   (-5 -- 50)
                                     8,700
                               (1,600 -- 16,000)
Non-fatal heart attacks (age > 18)
                                    15,000
                               (5,600 -- 24,000)
                                      40
                                   (7 -- 72)
                                    15,000
                               (5,600 -- 24,000)
Hospital admissions -- respiratory
(all ages)
                                     2,700
                                (1,300 -- 4,000)
                                       5
                                    (2 -- 9)
                                     2,700
                                (1,300 -- 4,000)
Hospital admissions -- cardiovascular (age > 18)
                                     5,700
                                (4,200 -- 6,600)
                                      15
                                   (10 -- 19)
                                     5,800
                                (4,200 -- 6,600)
Emergency room visits for asthma
(age < 18)
                                     9,800
                               (5,800 -- 14,000)
                                      21
                                   (7 -- 36)
                                     9,800
                               (5,800 -- 14,000)
Acute bronchitis
(age 8-12)
                                    19,000
                                (-630 -- 37,000)
                                      50
                                  (-29 -- 130)
                                    19,000
                                (-660 -- 37,000)
Lower respiratory symptoms (age 7-14)
                                    240,000
                              (120,000 -- 360,000)
                                      630
                                 (130 -- 1,100)
                                    240,000
                              (120,000 -- 360,000)
Upper respiratory symptoms
(asthmatics age 9-18)
                                    180,000
                              (57,000 -- 310,000)
                                      480
                                  (-25 -- 980)
                                    180,000
                              (57,000 -- 310,000)
Asthma exacerbation
(asthmatics 6-18)
                                    400,000
                             (45,000 -- 1,100,000)
                                     1,100
                                (-250 -- 2,900)
                                    400,000
                             (45,000 -- 1,100,000)
Lost work days
(ages 18-65)
                                   1,700,000
                            (1,500,000 -- 1,900,000)
                                     4,300
                                (3,500 -- 5,200)
                                   1,700,000
                            (1,500,000 -- 1,900,000)
Minor restricted-activity days
(ages 18-65)
                                  10,000,000
                           (8,400,000 -- 11,000,000)
                                    26,000
                               (20,000 -- 32,000)
                                  10,000,000
                           (8,400,000 -- 12,000,000)
--------------------------------------------------------------------------------

--------------------------------------------------------------------------------

Ozone-related endpoints
Premature mortality

                               Multi-city  and NMMAPS
Bell et al. (2004) (all ages)
                                      27
                                   (11 -- 42)
                                      0.1
                                 (0.01 -- 0.3)
                                      27
                                   (11 -- 42)

Schwartz et al. (2005)
(all ages)
                                      41
                                   (17 -- 64)
                                      0.2
                                  (0.1 -- 0.4)
                                      41
                                   (17 -- 65)

Huang et al. (2005)
(all ages)
                                      37
                                   (17 -- 57)
                                      0.2
                                  (0.1 -- 0.4)
                                      37
                                   (17 -- 57)
                                 Meta-analyses
Ito et al. (2005) (all ages)
                                      120
                                  (78 -- 160)
                                      0.6
                                  (0.3 -- 0.9)
                                      120
                                  (79 -- 160)

Bell et al. (2005) (all ages)
                                      87
                                  (48 -- 130)
                                      0.5
                                  (0.2 -- 0.8)
                                      87
                                  (48 -- 130)

Levy et al. (2005) (all ages)
                                      120
                                  (89 -- 150)
                                      0.7
                                  (0.4 -- 0.9)
                                      120
                                  (90 -- 160)
Hospital admissions -- respiratory causes (ages > 65)
                                      160
                                  (21 -- 280)
                                      1.2
                                  (0.1 -- 2.3)
                                      160
                                  (21 -- 290)
Hospital admissions -- respiratory causes (ages <2)
                                      83
                                  (43 -- 120)
                                      0.5
                                  (0.2 -- 0.8)
                                      84
                                  (43 -- 120)
Emergency room visits for asthma (all ages)
                                      86
                                  (-2 -- 260)
                                      0.4
                                 (-0.2 -- 1.4)
                                      86
                                  (-2 -- 260)
Minor restricted-activity days (ages 18-65)
                                    160,000
                              (80,000 -- 240,000)
                                      910
                                 (240 -- 1,600)
                                    160,000
                              (80,000 -- 240,000)
School absence days
                                    51,000
                               (22,000 -- 73,000)
                                      290
                                  (59 -- 490)
                                    51,000
                               (22,000 -- 74,000)
[A] Estimates rounded to two significant figures; column values will not sum to total value.
[B] The negative estimates for certain endpoints are the result of the weak statistical power of the study used to calculate these health impacts and do not suggest that increases in air pollution exposure result in decreased health impacts.

Table 5-18: Estimated Economic Value of Health and Welfare Benefits (95% confidence intervals, billions of 2007$)[A]

                                 Health Effect
                                   Pollutant
                            Within transport region
                          Beyond transport region[B]
                                     Total
Premature Mortality (Pope et al. 2002 PM mortality and Bell et al. 2004 ozone mortality estimates)

	3% discount rate
                                PM2.5 & O3
                                     $100
                                 ($8.3 -- $320)
                                     $0.3
                                ($0.01 -- $0.9)
                                     $100
                                 ($8.3 -- $320)

7% discount rate
                                PM2.5 & O3
                                      $94
                                 ($7.5 -- $280)
                                     $0.2
                                ($0.01 -- $0.8)
                                      $94
                                 ($7.5 -- $290)
Premature Mortality (Laden et al. 2006 PM mortality and Levy et al. 2005 ozone mortality estimates)

	3% discount rate
                                PM2.5 & O3
                                     $270
                                 ($23 -- $770)
                                     $0.7
                                 ($0.05 -- $2)
                                     $270
                                 ($23 -- $770)

7% discount rate
                                PM2.5 & O3
                                     $240
                                 ($21 -- $700)
                                     $0.6
                                ($0.05 -- $1.8)
                                     $240
                                 ($21 -- $700)
Chronic Bronchitis
                                     PM2.5
                                     $4.2
                                 ($0.2 -- $19)
                                     $0.01
                               ($-0.003--$0.06)
                                     $4.2
                                 ($0.2 -- $19)
Non-fatal heart attacks

	3% discount rate
                                     PM2.5
                                     $1.7
                                 ($0.3 -- $4.2)
                                    $0.004
                               ($0.003 -- $0.01)
                                     $1.7
                                 ($0.3 -- $4.2)

7% discount rate
                                     PM2.5
                                     $1.3
                                 ($0.3 -- $3.1)
                                    $0.004
                               ($0.002 -- $0.001)
                                     $1.3
                                 ($0.3 -- $3.1)
Hospital admissions -- respiratory
                                PM2.5 & O3
                                     $0.04
                                ($0.02 -- $0.06)
                                      ---
                                     $0.04
                                ($0.02 -- $0.06)
Hospital admissions -- cardiovascular
                                     PM2.5
                                     $0.09
                                ($0.01 -- $0.2)
                                      ---
                                     $0.09
                                ($0.01 -- $0.2)
Emergency room visits for asthma
                                PM2.5 & O3
                                    $0.003
                               ($0.002 -- $0.006)
                                      ---
                                    $0.003
                               ($0.002 -- $0.006)
Acute bronchitis
                                     PM2.5
                                    $0.008
                            (<$-0.01 -- $0.02)[c]
                                      ---
                                    $0.008
                            (<$-0.01 -- $0.02)[c]
Lower respiratory symptoms
                                     PM2.5
                                    $0.004
                               ($0.002 -- $0.009)
                                      ---
                                    $0.004
                               ($0.002 -- $0.009)
Upper respiratory symptoms
                                     PM2.5
                                    $0.005
                             (<$0.01 -- $0.014)
                                      ---
                                    $0.005
                             (<$0.01 -- $0.014)
Asthma exacerbation
                                     PM2.5
                                     $0.02
                               ($0.002 -- $0.08)
                                      ---
                                     $0.02
                               ($0.002 -- $0.08)
Lost work days
                                     PM2.5
                                     $0.2
                                ($0.17 -- $0.24)
                                      ---
                                     $0.2
                                ($0.17 -- $0.24)
School loss days
                                      O3
                                     $0.01
                               ($0.004 -- $0.013)
                                      ---
                                     $0.01
                               ($0.004 -- $0.013)
Minor restricted-activity days
                                PM2.5 & O3
                                     $0.7
                                  ($0.3 -- $1)
                                      ---
                                     $0.7
                                  ($0.3 -- $1)
Recreational visibility,  Class I areas
                                     PM2.5

                                     $4.1
Social cost of carbon (3% discount rate, 2014 value)
                                      CO2

                                     $0.6

Monetized total Benefits
(Pope et al. 2002 PM2.5 mortality  and Bell et al. 2004 ozone mortality estimates)

3% discount rate
                                   PM2.5, O3
                                     $110
                                 ($8.8 -- $340)
                                     $0.28
                                ($0.01 -- $0.9)
                                     $120
                                 ($14 -- $350)

7% discount rate
                                  PM2.5, O3
                                     $100
                                  ($8 -- $310)
                                     $0.25
                                ($0.01 -- $0.85)
                                     $110
                                 ($13 -- $320)
Monetized total Benefits
(Laden et al. 2006 PM2.5 mortality  and Levy et al. 2005 ozone mortality estimates)

3% discount rate
                                   PM2.5, O3
                                     $270
                                 ($24 -- $800)
                                     $0.7
                                ($0.05 -- $2.1)
                                     $280
                                 ($29 -- $810)

7% discount rate
                                  PM2.5, O3
                                     $250
                                 ($22 -- $720)
                                     $0.6
                                ($0.04 -- $1.9)
                                     $250
                                 ($26 -- $730)
[A] Estimates rounded to two significant figures.
B Monetary value of endpoints marked with dashes are < $100,000. States included in transport region may be found in chapter 2.
C The negative estimates for certain endpoints are the result of the weak statistical power of the study used to calculate these health impacts and do not suggest that increases in air pollution exposure result in decreased health impacts.

	Not all known PM- and ozone-related health and welfare effects could be quantified or monetized.  The monetized value of these unquantified effects is represented by adding an unknown "B" to the aggregate total.  The estimate of total monetized health benefits is thus equal to the subset of monetized PM- and ozone-related health and welfare benefits plus B, the sum of the nonmonetized health and welfare benefits; this B represents both uncertainty and a bias in this analysis, as it reflects those benefits categories that we are unable quantify in this analysis.
	Total monetized benefits are dominated by benefits of mortality risk reductions.  The primary analysis projects that the preferred remedy will result in between 13,000 and 34,000 PM2.5 and ozone-related avoided premature deaths annually in 2014. Our estimate of total monetized benefits in 2014 for the selected remedy is between $120 billion and $280 billion using a 3 percent discount rate and between $110 billion and $250 using a 7 percent discount rate.  Health benefits account for between 97 and 99 percent of total benefits depending on the PM2.5 and ozone mortality estimates used, in part because we are unable to quantify most of the non-health benefits.  The monetized benefit associated with reductions in the risk of premature mortality, which accounts for between $100 and $270 billion in 2014, depending again on the PM and ozone mortality risk estimates used, is between 93 and 97 percent of total monetized health benefits.  The next largest benefit is for reductions in chronic illness (CB and nonfatal heart attacks), although this value is more than an order of magnitude lower than for premature mortality.  Hospital admissions for respiratory and cardiovascular causes, visibility, MRADs, work loss days, school absence days, and worker productivity account for the majority of the remaining benefits.  The remaining categories each account for a small percentage of total benefit; however, they represent a large number of avoided incidences affecting many individuals.  A comparison of the incidence table to the monetary benefits table reveals that there is not always a close correspondence between the number of incidences avoided for a given endpoint and the monetary value associated with that endpoint.  For example, there are almost 100 times more work loss days than premature mortalities, yet work loss days account for only a very small fraction of total monetized benefits.  This reflects the fact that many of the less severe health effects, while more common, are valued at a lower level than the more severe health effects.  Also, some effects, such as hospital admissions, are valued using a proxy measure of WTP.  As such, the true value of these effects may be higher than that reported in Table 5-18.
Figures 5-15 and 5-16 illustrates the geographic distribution of avoided PM2.5 and ozone-related mortalities estimated to result from the selected remedy. Figure 5-17 plots the cumulative distribution of the percentage of deaths due to PM2.5 and ozone in 2014, prior to and after the implementation of the Transport Rule remedy. As illustrated in this figure, once implemented the Transport Rule is estimated to reduce by a substantial fraction the percentage of total deaths due to PM2.5 and ozone.  While not quantified in this RIA, we expect the Transport Rule to produce important public health benefits for populations living in Canada. Approximately 90% of the Canadian population lives within 100 miles of the U.S. border, suggesting that some of the air quality improvements projected in areas near the U.S.-Canada border would be enjoyed by Canadian populations as well. A recent analysis (Chestnut and Mills, 2005) of the U.S. Acid Rain Program estimates annual benefits of the program in 2010 to both Canada and the United States at $122 billion and costs for that year at $3 billion (2000$) -- a 40-to-1 benefit/cost ratio. These quantified benefits in the United States and Canada are the result of improved air quality prolonging lives, reducing heart attacks and other cardiovascular and respiratory problems, and improving visibility. The complete report is available in volume 77, issue 3, of the Journal of Environmental Management.
These figures show that while there are very large health benefits throughout most of the East, there could be several areas where a very small disbenefit could result if further governmental actions do not occur to address them in the future. There are several upcoming planned federal actions that could lead to further large reductions throughout the US of ambient levels of fine particles and ozone.  Additionally, state actions to address regional haze in the near future and the existing NAAQS for fine particles and ozone could address these situations.  There are also other state actions, such as the recent Colorado Clean Air  -  Clean Jobs Act of April 2010 that is likely to convert much of the Front Range coal-fired generation in Colorado to natural gas in the near future.

Figure 5-15: Estimated reduction in excess PM2.5-related premature mortalities estimated to occur in each county in 2014 as a result of the selected remedy.

Figure 5-16: Estimated reduction in excess ozone-related premature mortalities estimated to occur in each county in 2014 as a result of the selected remedy

Figure 5-17: Cumulative percentage of the reduction in all-cause mortality attributable to reductions in PM2.5 and Ozone resulting from the selected remedy by county in 2014[A]

[A]Bell et al. 2005 ozone mortality estimate and Pope et al. 2002 PM2.5 mortality estimates.

Figure 5-18 summarizes an array of PM2.5-related monetized benefits estimates based on alternative epidemiology and expert-derived PM-mortality estimate as well as the sum of ozone-related benefits using the Bell et al. (2004) mortality estimate.
      Based on our review of the current body of scientific literature, EPA estimated PM-related mortality without applying an assumed concentration threshold. EPA's Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was recently reviewed by EPA's Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b), concluded that the scientific literature consistently finds that a no-threshold log-linear model most adequately portrays the PM-mortality concentration-response relationship while recognizing potential uncertainty about the exact shape of the concentration-response function. Consistent with this finding, we have conformed the threshold sensitivity analysis to the current state of the PM science improved upon our previous approach for estimating the sensitivity of the benefits estimates to the presence of an assumed threshold by incorporating a new "Lowest Measured Level" (LML) assessment.
      This approach summarizes the distribution of avoided PM mortality impacts according to the baseline (i.e. pre-Transport Rule) PM2.5 levels experienced by the population receiving the PM2.5 mortality benefit (Figure 5-19). We identify on this figure the lowest air quality levels measured in each of the two primary epidemiological studies EPA uses to quantify PM-related mortality. This information allows readers to determine the portion of PM-related mortality benefits occurring above or below the LML of each study; in general, our confidence in the estimated PM mortality decreases as we consider air quality levels further below the LML in the two epidemiological studies. While the LML analysis provides some insight into the level of uncertainty in the estimated PM mortality benefits, EPA does not view the LML as a threshold and continues to quantify PM-related mortality impacts using a full range of modeled air quality concentrations.
      The very large proportion of the avoided PM-related impacts we estimate in this analysis occur among populations exposed at or above the LML of each study (Figures 5-19) increasing our confidence in the PM mortality analysis. Approximately 69% of the avoided impacts occur at or above an annual mean PM2.5 level of 10 ug/m[3] (the LML of the Laden et al. 2006 study); about 96% occur at or above an annual mean PM2.5 level of 7.5 ug/m3 (the LML of the Pope et al. 2002 study). As we model mortality impacts among populations exposed to levels of PM2.5 that are successively lower than the LML of each study our confidence in the results diminishes. However, the analysis above confirms that the great majority of the impacts occur at or above each study's LML.
      As an example, when considering mortality impacts among populations living in areas with an annual mean PM level of 8 ug/m3, we would place greater confidence in estimates drawn from the Pope et al. 2002 study, as this air quality level is above the LML of this study. Conversely, we would place equal confidence when estimating mortality impacts among populations living in locations where the annual mean PM levels are above 10 ug/m3 because this value is at or above the LML of each study.
      Finally, Figure 5-20 illustrates the percentage of population exposed to different levels of annual mean PM2.5 levels in the baseline and after the implementation of the Transport Rule in 2014. The Transport Rule reduces overall PM2.5 levels substantially, particularly among highly exposed populations located within the states covered by the rule. Locations of the U.S. where annual mean PM levels are below the lowest measured level of the Pope study--western states in particular--are generally unaffected by the rule. However, for populations in the far western portion of the Transport Rule region, where annual mean PM2.5 concentrations are below 7.5 ug /m3, there are benefits of the rule, although the relative magnitude of those benefits compared to benefits in the majority of the areas covered by the Transport Rule is small.  In these areas there is lower confidence in the magnitude of the benefits associated with reductions in long-term PM2.5.  However, in these same areas, there may be additional benefits associated with short term elevated levels of PM, and there is relatively greater confidence in those benefits.   In addition, we note that prior to the implementation of the Transport Rule, 85% of the population live in areas where PM2.5 levels are projected to be above the lowest measured levels of the Pope study. Taken together, this information increases our confidence in the estimated mortality reductions for this rule.
      While the LML of each study is important to consider when characterizing and interpreting the overall level PM-related benefits, as discussed earlier in this chapter, EPA believes that both cohort-based mortality estimates are suitable for use in air pollution health impact analyses. When estimating PM mortality impacts using risk coefficients drawn from the Laden et al. analysis of the Harvard Six Cities and the Pope et al. analysis of the American Cancer Society cohorts there are innumerable other attributes that may affect the size of the reported risk estimates -- including differences in population demographics, the size of the cohort, activity patterns and particle composition among others. The LML assessment presented here provides a limited representation of one key difference between the two studies.

Figure 5-18: Estimated PM2.5- related premature mortalities avoided according to epidemiology or expert-derived PM mortality risk estimate[A]

[A] Column total equals sum of PM2.5-related mortality and morbidity benefits and ozone-related morbidity and mortality benefits using the Bell et al. (2004) mortality estimate.

Figure 5-19: Distribution of PM2.5-related mortality impacts by baseline PM2.5 levels, PM2.5 epidemiology study and lowest measured level (LML) of each study

Figure 5-20: Cumulative percentage of adult population at annual mean PM2.5 levels (pre- and post-2014 Transport Rule)

5.8 Discussion
This analysis demonstrates the significant health and welfare benefits of the Transport Rule. We estimate that by 2014 the rule will have reduced the number of PM2.5 and ozone-related premature mortalities by between 13,000 and 34,000, produce substantial non-mortality benefits and significantly improve visibility in Class 1 areas. This rule promises to yield significant welfare impacts as well, though the quantification of those endpoints in this RIA is incomplete.  These significant health and welfare benefits suggest the important role that pollution from the EGU sector plays in the public health impacts of air pollution.
Inherent in any complex RIA such as this one are multiple sources of uncertainty. Some of these we characterized through our quantification of statistical error in the concentration response relationships and our use of the expert elicitation-derived PM mortality functions. Others, including the projection of atmospheric conditions and source-level emissions, the projection of baseline morbidity rates, incomes and technological development are unquantified. When evaluated within the context of these uncertainties, the health impact and monetized benefits estimates in this RIA can provide useful information regarding the public health impacts attributable to EGUs.

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CHAPTER 6
ELECTRIC POWER SECTOR PROFILE

      This chapter discusses important aspects of the power sector that relate to the Transport Rule, including the types of power-sector sources affected by the Transport Rule, and provides background on the power sector and electric generating units (EGUs).  In addition, this chapter provides some historical background on EPA regulation of and future projections for the power sector.

6.1	Power Sector Overview
	The production and delivery of electricity to customers consists of three distinct segments: generation, transmission, and distribution.
6.1.1	Generation
	Electricity generation is the first process in the delivery of electricity to consumers.  Most of the existing capacity for generating electricity involves creating heat to rotate turbines which, in turn, create electricity.  The power sector consists of over 17,000 generating units, comprising fossil-fuel-fired units, nuclear units, and hydroelectric and other renewable sources dispersed throughout the country (see Table 6-1).

Table 6-1.  Existing Electricity Generating Capacity by Energy Source, 2009
Energy Source
                             Number of Generators
                       Generator Nameplate Capacity (MW)
                      Generator Net Summer Capacity (MW)
Coal
                                     1,436
                                    338,723
                                    314,294
Petroleum