## From: Culligan, Kevin [mailto:Culligan.Kevin@epa.gov] Sent: Monday, May 26, 2014 4:37 PM To: Higgins, Cortney Cc: Wayland, Robertj Subject: FW: EGU GHG Existing Source RIA Chapter 4

For tomorrow's 10:00 benefits discussion.

<< E.O. 12866 Chapter_4_Existing_EGU_Benefits_5.26.14.docx >>

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4-1 

## CHAPTER 4: ESTIMATED CLIMATE BENEFITS AND HUMAN HEALTH CO-BENEFITS

4.1 Introduction
Implementing the proposed Emission Guidelines for Greenhouse Gas (GHG) Emissions from Existing Stationary Sources: Electric Utility Generating Units (EGUs) (hereafter, EGU GHG Existing Source Guidelines) is expected to reduce emissions of carbon dioxide (CO 2 

### ) and have ancillary human health benefits (i.e., co-benefits) associated with lower ambient concentrations of criteria air pollutants. This chapter describes the methods used to estimate the
monetized climate benefits and the monetized ai r pollution health co-benefits associated with reducing exposure to ambient fine particulate matter (PM 2.5 

### ) and ozone by reducing emissions of precursor pollutants (i.e., sulfur dioxide (SO 2 

### ), nitrogen dioxide (NO 2 

### ), and directly emitted
PM 2.5 

### ). Data, resource, and methodological limitations prevent EPA from monetizing the benefits from several important co-benefit cate gories, including reducing direct exposure to SO 2 

### , NO 2 

### , and hazardous air pollutants (HAP), as well as ecosystem effects and visibility impairment. We qualitatively discuss these unquant ified benefits in this chapter.

This chapter provides estimates of the moneti zed climate benefits and air pollution health
co-benefits associated with emission reductions for two options with two illustrative compliance scenarios across several analysis years and discount rates. The estimated benefits associated with these emission reductions are beyond those achieved by previous EPA rulemakings, including the Mercury and Air Toxics Standards (MATS).

4.2 Estimated Climate Benefits from CO 2 

### The primary goal of the proposed guidelines is to reduce emissions of CO 2 

### . In this section, we provide an overview of the public health and public welfare effects associated with climate change. We also provide information regarding the economic valuation of CO 2 

### using the Social Cost of Carbon (SCC), a metric that estimates the monetary value of impacts associated with marginal changes in CO 2 

### emissions in a given year. Table 4-1 summarizes the quantified and unquantified climate benefits in this analysis.

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4-2 Table 4-1. Climate Effects Benefits Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information Improved Environment Reduced climate effects Global climate impacts from CO 2 —  SCC TSD Climate impacts from ozone and black carbon (directly emitted PM) — — Ozone ISA, PM ISA * Other climate impacts (e.g., other GHGs such as methane, aerosols, other impacts) — — IPCC *

* We assess these co-benefits qualitatively because we do not have sufficient confidence in available data or methods.


### 4.2.1 Public Health Effects from Climate Change
Climate change threatens public health in a number of ways: direct temperature effects, the effect of higher atmospheric CO 2 

### concentrations on characteristics of air quality, changes in vector-borne diseases, and changes in the severity and frequency of extreme weather events. This section summarizes the 2009 Endangerment Findi ng’s conclusions for each of these effects in

turn. 1



### Heat is already the leading cause of weather-re lated deaths in the United States, and heat
waves are associated with marked short-term incr eases in mortality and morbidity. It has already been observed that unusually hot days and heat waves are becoming more frequent, and that unusually cold days are becoming less frequent. In the future, severe heat waves are projected to further intensify in magnitude a nd duration over the portions of the United States where these events have already been observed. If this observed warming trend continues as projected, it is expected that heat-related mortality and morbid ity will increase. Different segments of the population are sensitive for different reasons, with older adults, the chronically sick, the very young, city-dwellers, and those taking medications that disrupt thermoregulation being the most sensitive to hot temperatures. Other groups that ha ve also been found to be sensitive to hot temperatures are the mentally ill, those lack ing access to air conditioning, those working or playing outdoors, and socially isolated persons . With continued warming over time, these

1 For more information on the impacts of climate change see the 2009 Endangerment Finding . “Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act,” 74 Fed. Reg. 66,496 (Dec. 15, 2009). http://www.epa.gov/climatechange/endangerment/ Comment [A1]: OMB comment: As noted separately, we want to discuss the language section and make sure we have consistent and agreed upon language, similar to what we’ve done with the PM benefits language.
EPA Response: EPA is happy to discuss further. Please note that we have updated the parallel section in the preamble to include, for example, a brief discussion of peer-reviewed assessments published after the 2009 Endangerment Finding. We anticipate carrying these edits to the relevant section of RIA Section 4.2.1 (benefits chapter)

Comment [A2]: OMB Comment: Citation?
EPA Response: Please see paragraph above, which states that the entire section summarizes the 2009 Endangerment Finding.

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4-3 adverse effects would be expected to increase as serious heat events become more frequent, prolonged, and extreme.

Conversely, increases in temperature are also expected to lead to some reduction in the risk of death, related to extreme cold. Evidence suggests that the net impact of changes in heat and cold mortality is likely to be adverse. The latest report from At the time of the Finding, the U.S. Global Change Research Program (USGCRP, 2009) reference ds a study which by MedinaRamon and Schwartz (2007) that analyzed daily mortality and weather data in 50 U.S. cities from 1989 to 2000. This report found that, on average, cold snaps in the United States increased death rates by 1.6 percent, while heat waves triggered a 5.7 percent increase in death rates. While a single study is not conclusive, this study finds that increases in heat-related mortality, due to global warming in the United States, are likely to be greater than decreases in cold-related mortality found that reductions in deaths related to the projected decline in extreme cold events were not expected to compensate for the project ed increase in heat-related deaths: the most recent report (USGRP, 2014) has further confirmed that conclusion . The tendency for mortality
rates to increase in winter occurs for reasons which are not strongly correlated with cold temperatures, such as influenza. Analyses of the effects of warmer winters on mortality must consider these relationships to avoid overestimating the effects of temperature increases during
that season.

Climate change is expected to increase regional ozone pollution, relative to ozone levels in the absence of climate change. Increased levels of ozone are associated with risks of respiratory illnesses and premature death. In addition to human health effects, tropospheric ozone has significant adverse effects on crop yields, pasture a nd forest growth, and the composition of plant and animal species populations, pasture and fore st growth, and the composition of plant and animal species populations.

Peer reviewed modeling studies discussed in EPA’s Interim Assessment (U.S. EPA, 2009a) show that climate change is likely to cause increases in summertime ozone concentrations over substantial regions of the country, especially on the highest ozone days and in the largest metropolitan areas with the worst ozone problems. This effect was not uniform across the country, with some areas projected to have little change or slight decreases, though the decreases

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4-4 are expected to be less pronounced and occur in less populous regions than the increases. The key metric for regulating U.S. air quality is the maximum daily 8-hour average ozone concentration. For those regions where modeli ng projected climate-induced increases, the increase in 2050 was in the range of 2 to 8 ppb, averaged over the summer season. The increases were substantially greater than 2 to 8 ppb during the peak pollution episodes that tend to occur over a number of days each summer.

In addition to direct temperature health effects and climate change induced air quality effects, there is also the potential for increased mortality rates, injuries, infectious diseases, and
stress-related disorders re sulting from more frequent extreme weather events.

Climate change is expected to lead to an increase in the frequency of heavy precipitation events, which would be associated with increas ed risk of deaths and injuries, as well as infectious, respiratory and skin diseases. Floods are low-probability, high-impact events that can overwhelm physical infrastructure, human resilience, and social organization. Floods can result in health impacts such as deaths, injuries, inf ectious diseases, toxic contamination, and mental health problems.

Climate change is expected to lead to increases tropical cyclone intensity (hurricanes and tropical storms). Increases in tropical cyclone in tensity are linked to increases in the risk of deaths, injuries, waterborne and food borne diseas es, as well as post-traumatic stress disorders. Storm surge is the leading cause of death in coas tal storms, and the risk of death by drowning due to surge is expected to increase with rising sea levels and increased storm intensity as the result of climate change. Projected increases in flooding due to increased intensity of cyclonic events is also expected to lead to adverse public health impacts as noted above.

According to the assessment literature, under changing climate and environmentalconditions there will also likely be an increase in the spread of serial episodes of food and waterborne pathogens among susceptible populations, depending on the pathogens’ survival, persistence, habitat range and transmission. Food borne diseases show some relationship with temperature. The range of some zoonotic disease carriers, such as the Lyme disease-carrying tick, may increase with temperature.

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4-5 Increases in atmospheric CO 2 

### concentrations directly as well as changes in the climate are expected to stimulate plants to increase photosynthesis, biomass, water use efficiency, and reproductive effort resulting in greater growth and distribution of weeds, grasses, and trees. Such increases could lead to greater production, di stribution, dispersion, and allergenicity of aeroallergens. These changes in aeroallergens and subsequent human exposures could affect the prevalence and severity of allergy symptoms. Howe ver, the scientific literature does not provide definitive data or conclusions on how climate change might impact aeroallergens and subsequently the prevalence of allergenic illnesse s in the U.S. The IPCC concluded that pollens are likely to increase with elevated temperature and CO 2 

### (IPCC, 2007).

4.2.2 Public Welfare Effects from Climate Change
As with public health, there are multiple pathways in which the greenhouse gas air pollution and resultant climate change affect climate-sensitive economic sectors and environmental media. These sectors include agriculture; forestry; water resources; sea level rise in coastal areas; energy, infrastructure, and se ttlements; and ecosystems and wildlife. Impacts from climate change will also occur outside of the United States. This section summarizes the 2009 Endangerment Finding’s conclu sions for each of these effects. 2



### As noted above, elevated CO 2 

### concentrations and modest temperature increases may stimulate plants to increase photosynthesis, bi omass, water use efficiency, and reproductive effort. These impacts and the potential for longer growing seasons may result in increased agricultural productivity. But, the same effects may also enhance pest and weed growth. Further temperature increases, possible changes to precipitation patterns and variability, and any increases in ground-level ozone induced by higher temperatures are expected to reduce agricultural productivity. A USGCRP report (2009) concluded that while for some crops such as grain and oilseed crops there may be, on net, a beneficial effect over the next couple decades, as temperature rises, these crops will begin to experience failure, especially if climate variability increases and precipitation lessens or becomes more variable. Changes in the intensity and frequency of extreme weather events, such as droughts and heavy storms, have the potential to

2 “Endangerment and Cause or Contribute Findings for Gr eenhouse Gases Under Section 202(a) of the Clean Air Act,” 74 Fed. Reg. 66,496 (Dec. 15, 2009) (“Endangerment Finding”).

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4-6 negatively impact U.S. agriculture. Changes in pr ecipitation patterns, in addition to increasing temperatures and longer growing seasons, can also change the demand for irrigation requirements and could potentially increase irrigation demand.

With respect to livestock, higher temperatur es will very likely reduce livestock production during the summer season in some areas, but these losses will very likely be partially offset by warmer temperatures during the winter season. The impact on livestock productivity due to increased variability in weather patterns, will likely be far greater than the effects associated with an absolute change in average climatic conditions.

For the forestry sector, the effects are similar to the agriculture sector. There is the potential for beneficial effects due to elevated concentrations of carbon dioxide, modest temperature increases, and nitrogen deposition, but there is also the potential for adverse effects from higher temperature increases, changing precipitation patterns, increased populations and spread of insects and disease, and the potential for more frequent and severe extreme weather events. According to the science assessment reports upon which the Administrator relied for the 2009 Endangerment Finding, climate change ha s very likely increased the size and number of wildfires, insect outbreaks, and increased tree mort ality in the Interior West, the Southwest, and Alaska, and will continue to do so.

If existing trends in precipitation continue, it is expected that forest productivity will likely decrease in the Interior West, Southwest, eastern portions of the Southeast and Alaska. Forest productivity will likely increase in the northeastern United States, Lake States, and in western portions of the Southeast. An increase in forecast drought events, as a result of climate change, is also likely to reduce forest productivity where such events occur.

The connection of water resources to climate change is very important, given the increasing demand for adequate water supplies and services for agricultural, municipal, energy, and industrial uses, coupled with existing strain s on this scarce resource in many parts of the country. According to the assessment literature , climate change has already altered, and will likely continue to alter the water cycle, affecting where, when, and how much water is available for all uses. With higher temperatures, the water-holding capacity of the atmosphere and

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4-7 evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts.

Climate change is and will continue to cause the shrinking of the snowpack, induced by increasing temperatures. In the western United St ates, there is already well-documented evidence of a shrinking snowpack due to climate warming. Earlier meltings, with increased runoff in the winter and early spring, increase flood concerns and also result in substantially decreased summer flows. This pattern of reduced snowpack and changes to the flow patterns pose serious risks to major population regions, such as California, which rely on snowmelt-dominated watersheds for their water supply. Increased precipitation is expected to increase total water flow in some eastern areas leading to increased flood risk and potential water pollution. Despite the increased average flow, increased variability may still enable periods of drought.

Climate change will likely further constrain ov er-allocated water resources in some regions of the United States, increasing competition among agricultural, municipal, industrial, and ecological uses. Increased incidence of extrem e weather and floods may also overwhelm or damage water treatment and management systems, resulting in water quality problems.

According to the assessment literature, sea level is rising along much of the U.S. coast and the rate of change will very likely increase in the future, exacerbating the impacts of progressive inundation, storm-surge flooding, and shoreline erosion. A large percentage of the U.S. population lives in these coastal areas. The most vulnerable areas are the Atlantic and Gulf Coasts, the Pacific Islands, and parts of Alaska . Cities such as New Orleans, Miami, and New York are particularly at risk, and could have diffi culty coping with the sea level rise projected by the end of the century under a higher emissions scenario. Population growth and the rising value of infrastructure increases the vulnerability of coastal areas to climate variability and future climate change. Adverse impacts on islands present concerns for Hawaii and the U.S. territories.
Reductions in Arctic sea ice increases extreme coastal erosion in Alaska, due to the increased exposure of the coastline to strong wave action. In the Great Lakes, where sea level rise is not a concern, both extremely high and low water levels, resulting from changes to the hydrological cycle, have been damaging and disr uptive to shoreline communities.

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4-8 Coastal wetland loss is being observed in the United States where these ecosystems are squeezed between natural and artificial landward boundaries and rising sea levels. Up to 21 percent of the remaining coastal wetlands in the U. S. mid-Atlantic region are potentially at risk of inundation between 2000 and 2100. Stress will increase on coastal habitats through the interaction of climate change with developm ent and pollution relate d to development.

Although increases in mean sea level over the 21 st 

### century and beyond are projected to inundate unprotected, low-lying areas, the most devastating impacts are likely to be associated with storm surge. In combination, expected rates of sea level rise, projected storm intensity, wave height, and storm surge all suggest more severe coastal flooding and erosion hazards. Higher sea level provides an elevated base from which storm surges occur and diminishes the rate at which low-lying areas drain, increasing the risk of flooding from rainstorms. In New York City and Long Island, flooding from a combination of sea level rise and storm surge could be several meters deep. Projections suggest that the recurrence period of a 100-year flood event in this area might be reduced to 4–60 years by the 2080s. Additionally, some major urban centers in the U.S., such as areas of New Orleans are si tuated in low-lying flood plains, presenting increased risk from storm surges.

With respect to infrastructure, climate change vulnerabilities of industry, settlement, and society are more related to changes in the intens ity and frequency of extreme weather events than gradual changes in temperature. Extreme weather events could threaten U.S. energy infrastructure (transmission and distribution), tr ansportation infrastructure (roads, bridges, airports and seaports), water infrastructure, and other built aspects of human settlements. Moreover, soil subsidence caused by the melting of pe rmafrost in the Arctic region is a risk to gas and oil pipelines, electrical transmiss ion towers, roads, and water systems.

Within settlements experiencing climate change stressors, certain parts of the population may be especially vulnerable based on their circumstances. These include the poor, the elderly, the very young, those already in poor health, the disabled, those living alone, and/or indigenous populations dependent on one or a few resources. In Alaska, indigenous communities are likely to experience disruptive impacts, including shifts in the range or abundance of wild species crucial to their livelihoods and well-being.

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4-9 Climate change is exerting major influences on natural environments and biodiversity, and these influences are generally expected to grow with increased warming. Observed changes in the life cycles of plants and animals include shifts in habitat ranges, timing of migration patterns, and changes in reproductive timing and behavior.

The underlying assessment literature finds with high confidence that substantial changes in the structure and functioning of terrestrial ecosystems are very likely to occur with global warming greater than 2 to 3 °C above pre-industrial levels, with predominantly negative consequences for biodiversity and the provisioning of ecosystem goods and services. With global average temperature changes above 2 °C, many terrestrial, freshwater, and marine species (particularly endemic species), are at far greater risk of extinction than in the geological past. Climate change and ocean acidification will likely impair a wide range of planktonic and other
marine calcifiers such as corals. Even without oc ean acidification effects, increases in sea surface temperature of about 1 to 3 °C are projected to result in more frequent coral bleaching events and widespread coral mortality. In the Arctic, wildlife faces great challenges from the effects of climatic warming, as projected reductions in s ea ice will drastically shrink marine habitat for polar bears, ice-inhabiting s eals, and other animals.

Some common forest types are projected to expand, others are projected to contract, and others, such as spruce-fir, are likely to disappear from the contiguous United States. Changes in plant species composition in resp onse to climate change can incr ease ecosystem vulnerability to other disturbances, including wildfires and biologi cal invasion. Disturbances such as wildfires and insect outbreaks are increasing in the United States and are likely to intensify with warmer winters, drier soils and longer growing seasons in the future. The areal extent of drought-limited ecosystems is projected to increase 11 percent per °C warming in the United States. In California, temperature increases greater than 2 °C may lead to conversion of shrubland into desert and grassland ecosystems and evergreen conifer forests into mixed deciduous forests. Greater intensity of extreme events may alter disturbance regimes in coastal ecosystems leading to changes in diversity and ecosystem functionin g. Species inhabiting salt marshes, mangroves, and coral reefs are likely to be particularly vulnerable to these effects.

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4-10 According to the USGCRP report of June 2009 and other sources, climate change impacts in certain regions of the world may exacerbate problems that raise humanitarian, trade, and national security issues for the United States. 3 

### The IPCC (2007) identifies the most vulnerable regions of the world as:

1. Africa, especially the sub-Saharan region, because of current low adaptive capacity as

well as climate change

2. Small islands due to high exposure of population and infrastructure to risk of sea-level rise and increased storm surge

3. Asian mega-deltas due to large populations and high exposure to sea level rise, storm surge, and river flooding

4. The Arctic because of the effects of high rates of projected warming on natural systems Climate change has been described as a potent ial threat multiplier wi th regard to national security issues. While some of these internationa l risks do not readily le nd themselves to precise analyses or future projections, given the unavoidable global nature of the climate change problem it is appropriate and prudent to consider how impacts in other world regions may present risks to the U.S. population.

4.2.3 Climate Change Impacts in New Assessments
A number of major peer-reviewed scientific assessments have been released since the administrative record concerning the Endang erment Finding closed following the EPA’s 2010 Reconsideration Denial. These assessments include the IPCC’s 2012 “Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation” (SREX) and 2013-14 Fifth Assessment Report (A R5), the USGCRP’s 2014 “Climate Change Impacts in the United States” (Climate Change Impacts), and the NRC’s 2010 “Ocean Acidification: A National Strategy to Meet the Challenges of a Changing Ocean” (Ocean Acidification), 2011 “Report on Climate Stabiliza tion Targets: Emissions, Concentrations, and

3 ‘‘In an increasingly interdependent world, U.S. vulnerability to climate change is linked to the fates of other nations. For example, conflicts or mass migrations of people resulting from food scarcity and other resource limits, health impacts or environmental stresses in other parts of the world could threaten U.S. national security.’’ (Karl et al., 2009). Formatted: 03 Second-Level Subheading BOLD Comment [A3]: EPA Response: This section was added in response to comments on the Preamble requesting more discussion of recent assessments. EPA would be happy to discuss this addition.
Note that we continue to rely most heavily on the Endangerment Finding itself, as it is well-vetted and Court-tested and is a key part of the justification for the regulation of GHGs, and as the conclusions of the Finding have generally been confirmed by subsequent assessments.

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4-11 Impacts over Decades to Millennia” (Climate Stab ilization Targets), 20 11 ““National Security Implications for U.S. Naval Forces” (Nationa l Security Implications), 2011 “Understanding Earth’s Deep Past: Lessons for Our Climate Futu re” (Understanding Earth’s Deep Past), 2012 “Sea Level Rise for the Coasts of California, Oregon, and Washington: Past, Present, and Future”, 2012 “Climate and Social Stress: Implications for Security Analysis” (Climate and Social Stress), and 2013 “Abrupt Impacts of Cl imate Change” (Abrupt Impacts) assessments.

The EPA has reviewed these assessments and finds that in general, the improved understanding of the climate system they pres ent strengthens the case that GHGs endanger public health and welfare.

The IPCC report and three of the new NRC assessments provide estimates of projected global sea level rise that are larger than, and in some cases more than twice as large as, the rise estimated in a 2007 IPCC assessment of between 0.18 and 0.59 meters by the end of the century, relative to 1990. (It should be noted that in 2007, the IPCC stated that including poorly understood ice sheet processes could lead to an increase in the projections.) While these NRC and IPCC assessments continue to recognize and characterize the uncertainty inherent in accounting for ice sheet processes, these revised estimates strongly support and strengthen the existing finding that GHGs are reasonably anticipated to endanger public health and welfare. Other key findings of the recent assessments are described briefly below.

According to the IPCC in the SREX, “A changing climate leads to changes in the frequency, intensity, spatial ex tent, duration, and timing of extreme weather and climate events, and can result in unprecedented extreme weather and climate events. ” The SREX documents observational evidence of changes in some weather and climate extremes that have occurred globally since 1950. The assessment also provides evidence regarding the cause of some of these changes to elevated concentrations of GHGs, including warming of extreme daily temperatures, intensified extreme precipitation events, and increases in extreme coastal high water levels due to rising sea level. The SREX projects further in creases in some extreme weather and climate events during the 21st century. Combined with increasing vulnerability and exposure of populations and assets, changes in extreme weather and climate events have consequences for

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4-12 disaster risk, with particular impacts on the wa ter, agriculture and food security and health

sectors.

In the Climate Stabilization Targ ets assessment, the NRC states:

Emissions of carbon dioxide from the burning of fossil fuels have ushered in a new epoch where human activities will largely determine the evolution of Earth’s climate. Because carbon dioxide in the atmosphere is long lived, it can effectively lock Earth and future generations into a range of impacts, some of which could become very severe.

The assessment concludes that carbon dioxide emissions will alter the atmosphere’s composition and therefore the climate for thousands of years; and attempts to quantify the results of stabilizing GHG concentrations at different le vels. The report also projects the occurrence of several specific climate change impacts, finding warming could lead to increases in heavy rainfall and decreases in crop yields and Arctic sea ice extent, along with other significant changes in precipitation and stream flow. For an increase in global average temperature of 1 to 2 oC above pre-industrial levels, the assessment fo und that the area burnt by wildfires in western North America will likely more than double and coral bleaching and erosion will increase due both to warming and ocean acidification. An increase of 3 oC will lead to a sea level rise of 0.5 to 1 meter by 2100. With an increase of 4 oC, the average summer in the United States would be as warm as the warmest summers of the past century. The assessment notes that although many important aspects of climate change are difficult to quantify, the risk of adverse impacts is likely to increase with increasing temperature, and the risk of surprises can be expected to increase with the duration and magnitude of the warming.

The NRC assessment on Sea Level Rise projects a gl obal sea level rise of 0.5 to 1.4 meters by 2100, which is sufficient to lead to rising re lative sea level even in the northern states. Another assessment considers potential impacts of sea level rise and suggests that “the Department of the Navy should expect roughly 0.4 to 2 meters global average sea-level rise by 2100. This assessment also recommends preparing for increased needs for humanitarian aid; responding to the effects of climate change in geopolitical hotspots, including possible mass

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4-13 migrations; and addressing changing security needs in the Arctic as sea ice retreats. A third NRC assessment found that it would be “prudent for secur ity analysts to expect climate surprises in the coming decade . . . and for them to become progressively more serious and more frequent thereafter[.]”

Another NRC assessment finds that “the magn itude and rate of the present greenhouse gas increase place the climate system in what could be one of the most severe increases in radiative forcing of the global climate system in Earth history.” This assessment finds that CO2 concentrations by the end of the century, wit hout a reduction in emissions, are projected to increase to levels that Earth has not experienced for more than 30 million years.

Similarly, an NRC assessment on ocean acidification finds that “[t]he chemistry of the ocean is changing at an unprecedented rate and magnitude due to anthropogenic carbon dioxide emissions; the rate of change exceeds any known to have occurred for at least the past hundreds of thousands of y ears.” The assessment notes that th e full range of consequences is still unknown, but the risks “threaten coral reefs, fi sheries, protected species, and other natural resources of value to society.”

The most recent assessments to be releas ed were the IPCC AR5 assessments between September 2013 and April 2014, the NRC Abrupt Impacts assessment in December of 2013, and the USGCRP Climate Impacts assessment in May of 2014. The NRC Abrupt Impacts report examines the potential for tipping points, thresholds beyond which major and rapid changes occur in the Earth’s climate system or other systems impacted by the climate. The Abrupt Impacts report did find less cause for concern than some previous assessments regarding some abrupt events within the next century such as disruption of the Atlantic Meridional Overturning Circulation (AMOC) and sudden releases of high-latitude methane from hydrates and permafrost , but found that the potential for ab rupt changes in ecosystems, weather and climate extremes, and groundwater supplies critical for ag riculture now seem more likely, severe, and imminent. The assessment found that some abrupt changes were already underway (Arctic sea ice retreat and increases in extinction risk due to the speed of climate change), but cautioned that even abrupt changes such as the AMOC disruption that are not expected in this century can have severe impacts when they happen.

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4-14 The IPCC AR5 assessments also generally co nfirm and strengthen previous findings. For example, confidence in attributing recent warm ing to human causes has increased: the IPCC stated that it is extremely likely (>95% conf idence) that human influences have been the dominant cause of recent warming. Moreover, the IPCC found that the last 30 years were likely (>66% confidence) the warmest 30 year period in the Northern Hemisphere of the past 1400 years, that the rate of ice loss of worldwide glaciers and the Greenland and Antarctic ice sheets has likely increased, that there is medium confidence that the recent summer sea ice retreat in the Arctic is larger than has been in 1450 years, and that concentrations of carbon dioxide and several other of the major greenhouse gases are higher than they have been in at least 800,000 years. Climate-change induced impacts have be en observed in changing precipitation patterns, melting snow and ice, species migration, ne gative impacts on crops, increased heat and decreased cold mortality, and altered ranges for water-borne illnesses and disease vectors. Additional risks from future changes include deat h, injury, and disrupted livelihoods in coastal zones and regions vulnerable to inland flooding, food insecurity linked to warming, drought, and flooding, especially for poor populations, reduced access to drinking and irrigation water for those with minimal capital in semi-arid regi ons, and decreased biodiversity in marine ecosystems, especially in the Arctic and tropics, with implications for coastal livelihoods. The
IPCC determined that continued emissions of greenhouse gases will cause future warming and changes in all components of the climate system, and that limiting climate change will require substantial and sustained reductions of greenhouse gases.

Finally, the recently released USGCRP “Climate Change Impacts” assessment emphasizes that climate change is already happening now and it is happening in the United States. The
assessment documents the increases in some extreme weather and climate events in recent decades, the damage and disruption to infrastru cture and agriculture, and projects continued increase and more severe changes across a wide range of peoples, sectors, and ecosystems.

The EPA plans to continue relying heavily on the major assessments by the USGCRP, the IPCC,
and the NRC to summarize the state of climate science and to inform EPA actions related to climate change. Assessments from these bodies represent the current state of knowledge, comprehensively cover and synthesize thousands of individual studies to obtain the majority Formatted: Indent: First line: 0"

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4-15 conclusions from the body of scientific literature and undergo a rigorous and exacting standard of review by the peer expert community and U.S. government.

4.2. 43 Social Cost of Carbon
We estimate the global social benefits of CO 2 

### emission reductions expected from the proposed guidelines using the federal government’s SCC estimates presented in the 2013 Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 (2013 SCC TSD)

. 4 

### We refer to these estimates, which were developed by the U.S. government, as “SCC estimates.” The SCC is a metric that estimates the monetary value of impacts associated with marginal changes in CO 2 

### emissions in a given year. It includes a wide range of anticip ated climate impacts, such as net changes in agricultural productivity and human health, property damage from increased flood risk, and changes in energy system costs, such as reduced costs for heating and increased costs for air conditioning. It is typically used to assess the a voided damages as a result of regulatory actions (i.e., benefits of rulemakings that have an incremental impact on cumulative global CO 2 

### emissions).

The federal SCC estimates of SCC used in this analysis were developed over many years, using the best science available, and with input from the public. The EPA and other federal agencies have considered the extensive public comments on ways to improve SCC estimation received via the notice and comment period that was part of numerous rulemakings since 2006. In addition, OMB’s Office of Information and Regulatory Affairs recently sought public

4 Docket ID EPA-HQ-OAR-2013-0495, Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executi ve Order 12866, Interagency Working Group on Social Cost of Carbon , with participation by Council of Economic Advisers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, De partment of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury (May 2013, Revised November 2013). Available at: http://www.whitehouse.gov/sites/default/files/omb/asse ts/inforeg/technical-update-social-cost-of-carbon-forregulator-impact-analysis.pdf.The federal government c oncluded that a global measure of the benefits from reducing U.S. GHG emissions should be the standard pract ice when conducting regulatory impact analysis in support of federal rule makings. See Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executi ve Order 12866, Interagency Working Group on Social Cost of Carbon (2013) and Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12 866, Interagency Working Group on Social Cost of Carbon (2010). Formatted: Font: Italic

Comment [A4]: OMB comment: Vis a vis footnote 59 See edits to exec summary – referring to this is the “federal government” rather than the TSD by name, in the way you’d refer to any E.O. guidance (e.g., A-4) is awkward.
EPA Response: As noted in edits to the Executive Summary, EPA has deleted labels of “federal gov’t” and replaced with a complete definition referencing the TSD.

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4-16 comment on the approach used to develop the SCC estimates. The comment period ended on February 26, 2014, and OMB is reviewing the comments received.

An interagency process that included the EP A and other executive branch entities used three integrated assessment models (IAMs) to develop SCC estimates and selected four global values for use in regulatory analyses. The SCC estimates were first released in February 2010 and updated in 2013 using new versions of each IAM. 5



### The SCC estimates represent global measures because of the distinctive nature of the climate change problem. The climate change problem is highly unusual in at least two respects. First, emissions of most GHGs contribute to damages around the world even when they are emitted in the United States. The SCC must therefore incorporate the full (global) damages caused by GHG emissions in order to address the global nature of the problem. Second, climate change presents a problem that the United States along cannot solve. The US now operates in a global, highly interconnected economy such that impacts on the other side of the world now affect our economy. Climate damages in other co untries can affect U.S. companies. Climateexacerbated conflict can require military expenditures by the U.S. All of this means that the true cost of climate change to U.S. is much larger than impacts that simply occur in the U.S. Climate change presents a problem that the United States alone cannot solve. A global number is the economically appropriate reference point for collective actions to reduce climate change.

A key objective in the development of the SCC estimates was to enable a consistent exploration of three integrated assessment models (DICE, FUND, and PAGE) 6 

### while respecting the different approaches to quantifying damages taken by the key modelers in the field. The

5 Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: Social Cost of Carbon for

Regulatory Impact Analysis Under Executive Order 1286 6, Interagency Working Group on Social Cost of Carbon , with participation by Council of Economic Advise rs, Council on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, a nd Department of Treasury (February 2010). Available at: http://www.whitehouse.gov/sites/defaul t/files/omb/inforeg/for-agencies/Socia l-Cost-of-Carbon-for-RIA.pdf. See previous citation for 2013 SCC TSD.

6 The full models names are as follows: Dynamic Integrated Climate and Economy (DICE); Climate Framework for Uncertainty, Negotiation, and Distribution (FUND); and Policy Analysis of the Greenhouse Gas Effect (PAGE).

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4-17 selection of the three input parameters (equilibri um climate sensitivity, reference socioeconomic scenarios, discount rate) was based on an extensive review of the literature. Specifically, a probability distribution for climate sensitivity was specified as an input into all three models. In addition, the interagency group used a range of scenarios for the socio-economic parameters and a range of values for the discount rate. All other model features were left unchanged, relying on the model developers’ best estimates and judgments. In DICE, these parameters are handled deterministically and represented by fixed consta nts; in PAGE, most parameters are represented by probability distributions. FUND was also run in a mode in which parameters were treated probabilistically. The use of three models and thes e input parameters allowed for exploration of important uncertainties in the way climate damages are estimated, equilibrium climate sensitivity, reference socioeconomic and emission tr ajectories, and discount rate. As stated in the 2010 SCC TSD, however, key uncertainties remain as the existing models are imperfect and incomplete.The federal government first released the estimates in February 2010 and updated them in 2013 using new versions of each IAM. See tT he 2010 SCC Technical Support Document (SCC TSD ) for provides a complete discussion of the methods used to develop the estimates and the key uncertainties , and the 2013 SCC TSD for presents and discusses the updated estimates. 7,8



### Notably, the 2013 process did not revisit the 2010 interagency modeling decisions (e.g., with regard to the discount rate, reference case socioeconomic and emission scenarios or equilibrium climate sensitivity). Rather, improv ements in the way damages are modeled are confined to those that have been incorporated into the latest versions of the models by the

7 Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon, with participation by Council of Economic Advi sers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, a nd Department of Treasury (February 2010). Available at: http://www.whitehouse.gov/sites/default/files/omb/in foreg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf

8 Docket ID EPA-HQ-OAR-2013-0495, Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon, with participation by Council of Economic Advisers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, De partment of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury (May 2013, Revised November 2013). Available at: http://www.whitehouse.gov/sites/default/files/omb/asse ts/inforeg/technical-update-social-cost-of-carbon-forregulator-impact-analysis.pdf.

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4-18 developers themselves and used in peer-reviewed publications. The model updates that are relevant to the SCC estimates include: an explicit representation of sea level rise damages in the Dynamic Integrated Climate and Economy ( DICE ) and Policy Analysis of the Greenhouse Effect ( PAGE ) models; updated adaptation assumptions, revisions to ensure damages are constrained by GDP, updated regional scaling of damages, and a revised treatment of potentially abrupt shifts in climate damages in the PAGE model; an updated carbon cycle in the DICE model; and updated damage functions for sea level rise imp acts, the agricultural sector, and reduced space heating requirements, as well as changes to the transient response of temperature to the buildup
of GHG concentrations and the inclusion of i ndirect effects of methane emissions in the Climate Framework for Uncertainty, Negotiation, and Distribution ( FUND ) model. The 2013 SCC TSD provides complete details.

When attempting to assess the incremental economic impacts of carbon dioxide emissions, the analyst faces a number of serious challenge s. A report from the National Academies of Science (NRC, 2009) points out that any assessme nt will suffer from uncertainty, speculation, and lack of information about (1) future emissi ons 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. 9 

### As a result, any effort to quantify and monetize the harms associated with climate change will raise serious questions of science, economics, and ethics and should be viewed as provisional.

The 2010 SCC TSD noted a number of limitations to the SCC analysis, including theincomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatme nt of adaptation and technological change, uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk aversion. Current integrated assessment models do not assign value to all of the important physical, ecological, and economic impacts of clim ate change recognized in the climate change literature due to a lack of precise information on the nature of damages and because the science

9 National Research Council (2009). Hidden Costs of Ener gy: Unpriced Consequences of Energy Production and Use. National Academies Press. See docket ID EPA-HQ-OAR-2009-0472-11486. Comment [A5]: OMB comment: See comments in exec summary re: needing to add language re: uncertainty/limitations. We can point you to the passages in the 2010 TSD that we think should be added here.
EPA response: Yes, please let us know which text you are thinking of in particular. Also, we did not see comments about uncertainty/limitations in the RIA executive summary related to SCC. We responded to comments requesting info about public comments, global versus domestic, the 3 input assumptions, and nomenclature. We also updated this chapter with information about uncertainty. Please let us know if we missed something.

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4-19 incorporated into these models understandably lags behind the most recent research. The limited amount of research linking climate impacts to economic damages makes the modeling exercise
even more difficult. These individua l limitations do not all work in the same direction in terms of their influence on the SCC estimates, though taken together they suggest that the SCC estimates are likely conservative. In particular, the IPCC Fourth Assessment Report (2007) concluded that “It is very likely that [SCC estimates] underestimate the damage costs because they cannot include many non-quantifiable impacts.”

Nonetheless, these estimates and the discussi on of their limitations represent the best
available information about the social benefits of CO 2 

### reductions to inform benefit-cost analysis.
The new versions of the models used to esti mate the values presen ted below offer some improvements in these areas, although further work remains warranted. Accordingly, the EPA and other agencies continue to engage in research on modeling and valuation of climate impacts with the goal to improve these estimates. Additional details are provided in the SCC TSDs.

The four SCC estimates, updated in 2013, are as follows: $13, $46, $68, and $137 per
metric ton of CO 2 

### emissions in the year 2020 (2011$). 10 

### The first three values are based on the average SCC from the three IAMs, at discount rates of 5, 3, and 2.5 percent, respectively. SCC
estimates for 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 (where costs and benefits are incurred by different generations). The fourth value is the 95 th 

### 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 (representing less likely, but potentially catastrophic, outcomes).

Table 4-2 presents the updated global SCC estimates for the years 2015 to 2050. In order to calculate the dollar value for emission reductions, the SCC estimate for each emissions year would be applied to changes in CO 2 

### emissions for that year, and then discounted back to the

10 The 2010 and 2013 TSDs present SCC in 2007$. The estimates were adjusted to 2011$ using GDP Implicit Price Deflator, http://www.gpo.gov/fdsys/pkg/ECONI-2013-02/pdf/ECONI-2013-02-Pg3.pdf

.

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4-20 analysis year using the same discount rate used to estimate the SCC. 11 

### 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 climate 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. Tables 4-3 through 4-5 report the incremental climate benefits estimated in three analysis years (2020, 2025, and 2030) for the two illustrative compliance scenarios (i.e., state and regional) for two options evaluated.

Table 4-2. Global Social Cost of CO 2 

### , 2015-2050 (in 2011$)*

Year Discount Rate and Statistic 5% Average 3% Average 2.5% Average 3% (95th percentile) 2015 $12 $39 $61 $116 2020 $13 $46 $68 $137 2025 $15 $50 $74 $153 2030 $17 $55 $80 $170 2035 $20 $60 $85 $187 2040 $22 $65 $92 $204 2045 $26 $70 $98 $220 2050 $28 $76 $104 $235 * The SCC values vary depending on the year of CO 2 emissions and are defined in real terms, i.e., adjusted for

inflation using the GDP implicit price deflator. Th ese SCC values are stated in $/metric ton.



### Table 4-3. Estimated Global Climate Benefits of CO 2 

### Reductions for Proposed EGU GHG Existing Source Guidelines in 2020 (billions of 2011$)*

Discount Rate and Statistic Option 1 – state Option 1 – regional Option 2 – state Option 2 - regional Million metric tonnes of CO 2 reduced 383 371 295 283 5% (average) $4.9 $4.7 $3.8 $3.6 3% (average) $18 $17 $14 $13 2.5% (average) $26 $25 $20 $19 3% (95 th percentile) $52 $51 $40 $39 * The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts.

11 This analysis co nsidered the climate impacts of only CO 2 emission change. As discussed below, the climate impacts of other pollutants were not calculated for the proposed guidelines. Furthermore, the U.S. Interagency Working Group on the Social Cost of Carbon has so far only considered estimates for the social cost of CO 2 . While CO 2 is the dominant GHG emitted by the sector, we reco gnize the representative facilities within these comparisons may also have different emission rates for ot her climate forcers that will serve a minor role in determining the overall social cost of generation.

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4-21 Table 4-4. Estimated Global Climate Benefits of CO 2 

### Reductions for Proposed EGU GHG Existing Source Guidelines in 2025 (billions of 2011$)*

Discount Rate and Statistic Option 1 – state Option 1 - regional Option 2 – state Option 2 - regional Million metric tonnes of CO 2 reduced 506 501 376 368 5% (average) $7.6 $7.5 $5.6 $5.5 3% (average) $25 $25 $19 $18 2.5% (average) $37 $37 $28 $27 3% (95 th percentile) $77 $76 $57 $56 * The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts.



### Table 4-5. Estimated Global Climate Benefits of CO 2 

### Reductions for Proposed EGU GHG Existing Source Guidelines in 2030 (billions of 2011$)*

Discount Rate and Statistic Option 1 – state Option 1 - regional Option 2 – state Option 2 - regional Million metric tonnes of CO 2 reduced 555 545 373 353 5% (average) $9.5 $9.3 $6.4 $6.0 3% (average) $31 $30 $21 $20 2.5% (average) $44 $44 $30 $28 3% (95 th percentile) $94 $92 $63 $60 * The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts. 

### It is important to note that the climate benef its presented above are associated with changes
in CO 2 

### emissions only. Implementing these guide lines, however, will have an impact on the emissions of other pollutants that w ouldill affect the climate. Both predicting reductions in emissions and estimating tT he climate impacts of these other pollutants, however, can is be complex . The climate impacts of these other pollutants, and have not been calculated for the proposed guidelines. 12



### The se other emissionpollutant s potentially reduced as a result of these guidelines include other greenhouse gases (such as methane), aerosol s and aerosol precursors such as black carbon, organic carbon, sulfur dioxide and nitrogen oxides, and ozone precursors such as nitrogen oxides and volatile organic carbon compounds. Changes in em issions of these pollutants (both increases and decreases) can could be a direct ly result from of changes in electricity generation, upstream fossil fuel extraction and transport, and/or downstream secondary market impacts. Reductions in black carbon or ozone precursors are projected to would lead to further cooling, but reductions in

12 The federal government’s SCC estimates are designed to a ssess the climate benefits associated with changes in CO 2 emissions only. Comment [A6]: OMB Edit : “Both predicting reductions in emissions and estimating climate impacts of these pollutants, however, is complex, and have not been calculated for the proposed guidelines.
EPA response : Edited to retain accuracy; as discussed below, some of the upstream emissions changes were estimated.

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4-22 the other aerosol species and precursors are projected to would lead to warming. Therefore, changes in non-CO 2 

### pollutants could potentially augment or offset the climate benefits calculated here. These pollutants can act in different ways and on different timescales than carbon dioxide. For example, aerosols reflect (and in the case of black carbon, absorb) incoming radiation, whereas greenhouse gases absorb outgoing infrared radiation. In addition, tT hese aerosols are thought to can also affect climate indirectly by altering properties of clouds. Black carbon can also deposit on snow and ice, darkening these surfaces and accelerating melting. In terms of lifetime, while carbon dioxide emissions can increase concentrations in the atmosphere for hundreds or thousands of years, many of these other pollutants are short lived and remain in the atmosphere for short periods of time ranging from days to weeks and can therefore exhibit large spatial and temporal variability.

While the EPA has not quantified the climate impacts of these other pollutants for the proposed guidelines, the Agency has analyzed the potential changes in upstream methane emissions from the natural gas and coal production sectors that may result from the compliance scenarios examined in this RIA in the appendix to Chapter 3. The EPA assessed whether the net change in upstream methane emissions from natural gas and coal production is likely to be positive or negative and also assessed the pote ntial magnitude of changes relative to CO 2 

### emissions reductions anticipated at pow er plants. This assessment included CO 2 

### emissions from the flaring of methane, but did not evaluate potential changes in other combustion-related CO 2 

### emissions, such as emissions associated with dr illing, mining, processing, and transportation in the natural gas and coal production sectors. This analysis found that the net upstream CH 4 

### emissions from natural gas systems and coal mines and CO 2 

### emissions from flaring of methane will likely decrease under the proposed guidelines. Furthermore, the analysis suggests that the changes in upstream methane emissions are small relative to the changes in direct emissions from power plants.

4.3 Estimated Human Health Co-Benefits

In addition to CO 2 

### , implementing these proposed guidelines is expected to reduce
emissions of SO 2 

### and NO X 

### , which are precursors to formation of ambient PM 2.5 

### , as well as Comment [A7]: OMB Edit: change “and accelerating” to “which may accelerate.”
EPA Response : EPA’s climate science experts view this edit as an unnecessary caveat because darkening a snow surface accelerates melting.

Comment [A8]: OMB edit: is projected to reduce...” EPA response: We did not accept this edit because we believe the current wording is more accurate.

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4-23 directly emitted fine particles. 13 

### Therefore, reducing these emissions would also reduce human exposure to ambient PM 2.5 

### and the incidence of PM 2.5 

### -related health effects. In addition, in the presence of sunlight, NO X 

### and VOCs can undergo a chemical reaction in the atmosphere to form

ozone. Depending on localized con centrations of volatile or ganic compounds (VOCs), rR educing
NO X 

### emissions would also reduce human exposure to ozone and the incidence of ozone-related health effects. Although we do not have sufficient data to quantify these impacts in this analysis, reducing emissions of SO 2 

### and NOx would also reduce ambient exposure to SO 2 

### and NO 2 

### , respectively. In this section, we provide an overview of the monetized PM 2.5 

### and ozone-related co-benefits estimated for the proposed guidelines. The estimated co-benefits associated with these emission reductions are beyond those achieved by previous EPA rulemakings, including MATS. A full description of the underlying data, studies, and assumptions is provided in the PM NAAQS RIA (U.S. EPA, 2012a) and Ozone NAAQS RIA (U.S. EPA, 2008b, 2010d).

There are several important considerations in assessing the air pollution-related health cobenefits for a climate-focused rulemaking. Firs t, these estimated health co-benefits do not account for any climate-related air quality chan ges (e.g., increased ambient ozone associated with higher temperatures) but rather changes in precursor emissions affected by this rulemaking.Excluding climate-related air quality changes may underestimate ozone-related health cobenefits. It is unclear how PM 2.5 

### -related health co-benefits would be impacted by excluding climate-related air quality changes since the scie nce is unclear as to how climate change may
affect PM 2.5 

### exposure. Second, the estimated health co-benefits also do not consider temperature
modification of PM 2.5 

### and ozone risks (Roberts 2004; Ren 2006a, 2006b, 2008a, 2008b). Third, the estimated climate benefits reported in this RIA reflect global benefits, while the estimated health co-benefits are calculated for the contiguous U.S. only. Excluding temperature modification of air pollution risks and internati onal air pollution-related h ealth benefits implies that the quantified health co-benefit s likely lead to underestimation.

13 We estimate the health co-benefits associated with emission reductions of two categories of directly emitted particles: elemental carbon plus organic carbon (EC+OC) and crustal. Crustal emissions are composed of compounds associated with minerals and metals from the earth’s surface, including carbonates, silicates, iron, phosphates, copper, and zinc. Often, crustal material represen ts particles not classified as one of the other species (e.g., organic carbon, elemental carbon, nitrate, sulfate, chloride, etc.). Comment [A9]: OMB edit: Depending on local levels of VOCs, reducing NOx emissions tends to reduce human exposure to ozone, which is associated with ozone-related health effects. EPA response: We did not accept the edits to the second half of the sentence because we believe the current wording to be more accurate. Also, it is parallel to the preceding statement regarding the incidence of PM-related health effects.

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4-24 Implementing these guidelines may lead to reductions in ambient PM 2.5 

### concentrations below the National Ambient Air Quality Standard s (NAAQS) for PM and ozone in some areas and assist other areas with attaining thes e NAAQS. Because the NAAQS RIAs (U.S. EPA, 2012a, 2008b, 2010d) also calculated PM and ozone benefits, there are important differences worth noting in the design and analytical obj ectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a re vised air quality standard nationwide based on an array of emission reduction strategies for di fferent sources including known and unknown controls, incremental to implementation of existing regulations and controls needed to attain the current standards. In short, NAAQS RIAs hypothesize, but do not predict, the reduction strategies that States may c hoose to enact when implementi ng a revised NAAQS. The setting of a NAAQS does not directly result in costs or benefits, and as such, EPA’s NAAQS RIAs are merely illustrative and the estimated costs and benef its are not intended to be added to the costs and benefits of other regulations that result in specific costs of control and emission reductions. However, it is possible that some costs and bene fits estimated in this RIA may account for the same air quality improvements as estim ated in the illustrative NAAQS RIAs.

Similar to NAAQS RIAs, the emission reduc tion scenarios estimated for the proposed guidelines are also illustrative. In contrast to NAAQS RIAs, all of the emission reductions for the illustrative compliance scenarios would occur in one well-characterized sector (i.e., the EGU sector). In general, EPA is more confident in the magnitude and location of the emission reductions for implementation rules, which typically require specific emission reductions in a specific sector. As such, emission reductions achieved under promulgated implementation rules will ultimately be reflected in the baseline of future NAAQS analyses, which would reduce the
incremental costs and benefits associated with attaining revised future NAAQS. EPA does not re-issue illustrative RIAs outside of the rulemaking process that retroactively update the baseline to account for implementation rules promulgated after an RIA was completed. For more information on the relationship between illustrativ e analyses, such as for the NAAQS and this proposal, and implementation rules, please see Section 1.3 of the PM NAAQS RIA (U.S. EPA, 2012a).

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4-25 4.3.1 Health Impact Assessment for PM 2.5 

### and Ozone

The Integrated Science Assessment for Particulate Matter (PM ISA) (U.S. EPA, 2009b)
identified the human health effects associated with ambient PM 2.5 

### exposure, which include premature morality and a variety of morbidity effects associated with acute and chronic exposures. Similarly, the Integrated Science Assessment for Ozone and Related Photochemical
Oxidants (Ozone ISA) (U.S. EPA, 2013b) identified the human health effects associated with ambient ozone exposure, which include premature morality and a variety of morbidity effects associated with acute and chronic exposures. Tabl e 4-6 identifies the quantified and unquantified co-benefit categories captured in EPA’s health co-benefits estimates for reduced exposure to
ambient PM 2.5 

### and ozone. Although the table below does not list unquantified health effects such

as those associated with exposure to SO 2 

### , NO 2 

### , and mercury nor welfare effects such as acidification and nutrient enrichment, these effects are described in detail in Chapters 5 and 6 of the PM NAAQS RIA (U.S. EPA, 2012a) and summarized later in this chapter. It is important to emphasize that the list of unquan tified benefit categories is not e xhaustive, nor is quantification of each effect complete.

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4-26 Table 4-6. Human Health Effects of Ambient PM 2.5 

### and Ozone

Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information Improved Human Health Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30)   PM ISA

Infant mortality (age <1)   PM ISA

Reduced incidence of morbidity from exposure to PM 2.5 Non-fatal heart attacks (age > 18)   PM ISA Hospital admissions—respiratory (all ages)   PM ISA Hospital admissions—cardiovascular (age >20)   PM ISA Emergency room visits for asthma (all ages)   PM ISA Acute bronchitis (age 8-12)   PM ISA Lower respiratory symptoms (age 7-14)   PM ISA Upper respiratory symptoms (asthmatics age 9-11)   PM ISA Asthma exacerbation (asthmatics age 6-18)   PM ISA Lost work days (age 18-65)   PM ISA Minor restricted-activity days (age 18-65)   PM ISA Chronic Bronchitis (age >26) — — PM ISA Emergency room visits for cardiovascular effects (all ages) — — PM ISA 1
Strokes and cerebrovascular disease (age 50-79) — — PM ISA 1 Other cardiovascular effects (e.g., other ages) — — PM ISA 2 Other respiratory effects (e.g., pulmonary function, non-asthma ER visits, non-bronchitis chronic diseases, other ages and populations) — — PM ISA 2

Reproductive and developmental effects (e.g., low birth weight, pre-term births, etc) — — PM ISA 2,3
Cancer, mutagenicity, a nd genotoxicity effects — — PM ISA 2,3
Reduced incidence of mortality from exposure to ozone Premature mortality based on short-term study estimates (all ages)   Ozone ISA Premature mortality based on long-term study estimates (age 30–99) — — Ozone ISA 1

Reduced incidence of morbidity from exposure to ozone Hospital admissions—respiratory causes (age > 65)   Ozone ISA Hospital admissions—respiratory causes (age <2)   Ozone ISA Emergency department visits for asthma (all ages)   Ozone ISA Minor restricted-activity days (age 18–65)   Ozone ISA School absence days (age 5–17)   Ozone ISA Decreased outdoor worker productivity (age 18–65) — — Ozone ISA 1 Other respiratory effects (e.g., premature aging of lungs) — — Ozone ISA 2

Cardiovascular and ne rvous system effects — — Ozone ISA 2 Reproductive and developmental effects — — Ozone ISA 2,3

1 We assess these co-benefits qualitatively due to data a nd resource limitations for this analysis, but we have quantified them in sensitivity analyses for other analyses.

2 We assess these co-benefits qualitatively because we do not have sufficient confidence in available data or methods.

3 We assess these co-benefits qualitatively because current evidence is only suggest ive of causality or there are other significant concerns over the strength of the association.

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4-27 We follow a “damage-function” approach in calculating benefits, which estimates changes in individual health endpoints (specific effects that can be associated with changes in air quality) and assigns values to those changes assuming i ndependence of the values for those individual endpoints. Because EPA rarely has the time or resources to perform new research to measure directly, either health outcomes or their values for regulatory analyses, our estimates are based on the best available methods of benefits transfer, which is the science and art of adapting primary research from similar contexts to estima te benefits for the environmental quality change under analysis. We use a “benefit-per-ton” approach to estimate the PM 2.5 

### and ozone co-benefits in this RIA. This section describes the underlying basis for the health and economic valuation estimates, and the subsequent section provides an overview of the benefit-per-ton estimates,
which are described in detail in the appendix to this chapter.

The health impact assessment (HIA) quantifie s the changes in the incidence of adverse health impacts resulting from changes in human exposure to PM 2.5 

### and ozone. We use the environmental Benefits Mapping and Analysis Program (BenMAP) (version 4.0.66) to systematize health impact analyses by applying a database of key input parameters, including population projections, health impact functions, and valuation functions (Abt Associates, 2012). For this assessment, the HIA is limited to those health effects that are directly linked to ambient
PM 2.5 

### and ozone concentrations. There may be other indirect health impacts associated with reducing emissions, such as occupational health exposures. Epidemiological studies generally provide estimates of the relative risks of a partic ular health effect for a given increment of air pollution (often per 10 μg/m 3 

### for PM 2.5 

### or ppb for ozone). These relative risks can be used to develop risk coefficients that relate a unit reduction in PM 2.5 

### to changes in the incidence of a health effect. We refer the reader to the PM NAAQS RIA (U.S. EPA, 2012a) and Ozone NAAQS RIA (U.S. EPA, 2008b, 2010d) for more information regarding the epidemiology studies and risk coefficients applied in this analysis, and we briefly elaborate on adult premature mortality below. The size of the mortality eff ect estimates from epidemiological studies, the serious nature of the effect itself, and the high monetary value ascribed to prolonging life make mortality risk reduction the most significant h ealth endpoint quantified in this analysis.

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4-28 Considering a substantial body of published scie ntific literature and reflecting thousands of epidemiology, toxicology, and clinical studies, the PM ISA documents the association between
elevated PM 2.5 

### concentrations and adverse health effects, including increased premature mortality (U.S. EPA, 2009b). The PM ISA, which was twice reviewed by the Clean Air Scientific Advisory Committee of EPA’s Science Advisory Board (SAB-CASAC) (U.S. EPA-SAB, 2009b, 2009c), concluded that there is a causal relationship between mortality and both long-term and short-term exposure to PM 2.5 

### based on the entire body of scientific evidence. The PM ISA also
concluded that the scientific literature consiste ntly 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. In addition to adult mortality discussed in more detail below, we use effect coefficients from Woodruff et al. (1997) to estimate PM-related infant mortality.

For adult PM-related mortality, we use the effect coefficients from the most recent epidemiology studies examining two large population cohorts: the American Cancer Society cohort (Krewski et al., 2009) and the Harvard Six Cities cohort (Lepeule et al., 2012). The PM ISA (U.S. EPA, 2009b) concluded that the ACS and Six Cities cohorts provide the strongest evidence of the association between long-term PM 2.5 

### exposure and premature mortality with support from a number of additional cohort st udies. The SAB’s Health Effects Subcommittee (SAB-HES) also supported using these two cohorts for analyses of the benefits of PM reductions (U.S. EPA-SAB, 2010a). As both the ACS and Six Cities cohort studies have inherent strengths and weaknesses, we present PM 2.5 

### co-benefits estimates using relative risk estimates from both these cohorts (Krewski et al ., 2009; Lepeule et al., 2012).

As a characterization of uncertainty regarding the adult PM 2.5 

### -mortality relationship, EPA graphically presents the PM 2.5 

### co-benefits derived from EPA’s expert elicitation study (Roman et al., 2008; IEc, 2006). The primary goal of the 2006 study was to elicit from a sample of health experts probabilistic distributions describing uncertainty in estimates of the reduction in mortality among the adult U.S. population resulting from reductions in ambient annual average
PM 2.5 

### concentrations. In that study, twelve experts provided independent opinions regarding the 4.3.1.1 Mortality Concentration-Response Functions for PM 2.5 Formatted: Style 04 Third-Level Subheading BOLD + After: 12 pt1, Space After: 0 pt

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4-29 PM 2.5 

### -mortality concentration-response function. Because the experts relied upon the ACS and Six Cities cohort studies to inform their concentration-response functions, the benefits estimates derived from the expert responses generally fall between results derived from these studies (see Figure 4-1). We do not combine the expert results in order to preserve the breadth and diversity of opinion on the expert panel. This presentation of the expert-derived results is generally consistent with SAB advice (U.S. EPA-SAB, 2008), which recommended that the EPA emphasize that “scientific differences existed only with respect to the magnitude of the effect of
PM 2.5 

### on mortality, not whether such an effect existed” and that the expert elicitation “supports
the conclusion that the benefits of PM 2.5 

### control are very likely to be substantial”. Although it is possible that newer scientific literature could revi se the experts’ quantitative responses if elicited again, we believe that these general conclusions are unlikely to change.

4.3.1.2 Mortality Concentrati on-Response Functions for Ozone
In 2008, the National Academies of Science (NRC, 2008) issued a series ofrecommendations to the EPA regarding the quantification and valuation of ozone-related shortterm mortality. Chief among these was that “...short-term exposure to ambient ozone is likely to contribute to premature deaths” and the commit tee recommended that “ozone-related mortality be included in future estimates of the health benefits of reducing ozone exposures...” The NAS also recommended that “...the greatest emphasis be placed on the multicity and NMMAPS [National Morbidity, Mortality, and Air Pollution Study] studies without exclusion of the metaanalyses” (NRC, 2008). In view of the findings of the National Academies panel, we estimate the co-benefits of avoiding short-term ozone mort ality using the Bell et al. (2004) NMMAPS analysis, the Schwartz (2005) multi-city study, the Huang et al. (2005) multi-city study as well as effect estimates from the three meta-analyses (Bel l et al. (2005), Levy et al. (2005), and Ito et al. (2005)). These studies are consistent with the studies used in the Ozone NAAQS RIA (U.S. EPA, 2008b, 2010d). 14 

### For simplicity, we report the ozone mortality estimates in this RIA as a range from Bell et al. (2004) to Levy et al. (2005) to represent the lowest and the highest co-

14 Since EPA received NAS advice, EPA published the Oz one ISA (U.S. EPA, 2013b) and the second draft Ozone Health Risk and Exposure Assessment (U.S. EPA, 2014a). Th erefore, the ozone mortality studies applied in this analysis, while current at the time of the previous Ozone NAAQS RIAs, do not reflect the most updated literature available. The selection of ozone mortality studies used to estimate benefits in RIAs will be revisited in the forthcoming RIA accompanying the on-going review of the Ozone NAAQS.

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4-30 benefits estimates based on these six ozone mortality studies. In addition, we graphically present
estimated co-benefits derived from all six studies mentioned above as a characterization of uncertainty regarding the ozone -mortality relationship in Figure 4-1.

4.3.2 Economic Valuation for Health Co-benefits
After quantifying the change in adverse health impacts, we estimate the economic value of these avoided impacts. Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects by a small amount for a large population. Therefore, the appropriate economic measure is willingness to pay (WTP) for changes in risk of a health effect. For some health effects, such as hospital admissions, WTP estimates are generally not available, so we use the cost of treating or mitigating th e effect. These cost-of-illness (COI) estimates generally (although not necessarily in every case) understate the true value of reductions in risk of a health effect. They tend to reflect the di rect expenditures related to treatment but not the value of avoided pain and suffering from the health effect. The unit values applied in this analysis are provided in Table 5-9 of the PM NAAQS RIA for each health endpoint (U.S. EPA, 2012a).

Avoided premature deaths account for 98 percent of monetized PM-related co-benefits and over 90 percent of monetized ozone-related co-benefits. The economics literature concerning the appropriate method for valuing re ductions in premature mortality risk is still developing. The adoption of a value for the projected reduction in th e risk of premature mortality is the subject of continuing discussion within the economics and public policy analysis community. Following
the advice of the SAB’s Environmental Econom ics Advisory Committee (SAB-EEAC), the EPA currently uses the value of statistical life (VSL ) approach in calculating estimates of mortality benefits, because we believe this calculation provi des the most reasonable single estimate of an individual’s willingness to trade off money for reductions in mortality risk (U.S. EPA-SAB, 2000). The VSL approach is a summary measure for the value of small changes in mortality risk experienced by a large number of people.

EPA continues work to update its guidance on valuing mortality risk reductions, and the Agency consulted several times with the SAB-EE AC on this issue. Until updated guidance is available, the Agency determined that a single, peer-reviewed estimate applied consistently, best

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4-31 reflects the SAB-EEAC advice it has received. Therefore, EPA has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparing Economic Analyses (U.S. EPA, 2000) 15 

### while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates derived from 26 labor market and contingent valuation studies published between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$). 16 

### We then adjust this VSL to account for the currency year and to account for income growth from 1990 to the analysis year. Specifically, the VSLs applied in this analysis in 2011$ after adjusting for income gr owth are $9.9 million for 2020 and $10.1 million
for 2025 and 2030. 17



### The Agency is committed to using scientifically sound, appropriately reviewed evidence invaluing mortality risk reductions and has made significant progress in responding to the SABEEAC’s specific recommendations. In the process, the Agency has identified a number of important issues to be considered in updating its mortality risk valuation estimates. These are detailed in a white paper, “Valuing Mortality Risk Reductions in Environmental Policy” (U.S. EPA, 2010c), which recently underwent review by the SAB-EEAC. A meeting with the SAB on this paper was held on March 14, 2011 and formal recommendations were transmitted on July 29, 2011 (U.S. EPA-SAB, 2011). EPA is taking SAB’s recommendations under advisement.

In valuing PM 2.5 

### -related premature mortality, we disc ount the value of premature mortality occurring in future years using rates of 3 percent and 7 percent (OMB, 2003). We assume that there is a “cessation” lag between changes in PM exposures and the total realization of changes in health effects. Although the structure of the lag is uncertain, the EPA follows the advice of the SAB-HES to assume a segmented lag structure characterized by 30 percent of mortality reductions in the first year, 50 percent over years 2 to 5, and 20 percent over the years 6 to 20
after the reduction in PM 2.5 

### (U.S. EPA-SAB, 2004c). Changes in the cessation lag assumptions

15 In the updated Guidelines for Preparing Economic Analyses (U.S. EPA, 2010e), EPA re tained the VSL endorsed by the SAB with the understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future.

16 In 1990$, this base VSL is $4.8 million.

17 Income growth projections are only currently available in BenMAP through 2024, so both the 2025 and 2030 estimates use income growth only through 2024 and are therefore likely underestimates.

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4-32 do not change the total number of estimated deaths but rather the timing of those deaths. Because short-term ozone-related premature mortality occurs within the analysis year, the estimated
ozone-related co-benefits are id entical for all discount rates.

4.3.3 Benefit-per-ton Estimates for PM 2.5 

### We used a “benefit-per-ton” approach to estimate the PM 2.5 

### co-benefits in this RIA. EPA has applied this approach in several previous RIAs (e.g., U.S. EPA, 2011b, 2011c, 2012b). These benefit-per-ton estimates provide the total monetized human health co-benefits (the sum of premature mortality and premature morbidity), of reducing one ton of PM 2.5 

### (or PM 2.5 

### precursor such as NO X 

### or SO 2 

### ) from a specified source. Specifically, in this analysis, we multiplied the estimates for the EGU sector by the corresponding emission reductions based on regional (i.e., East, West, and California) benefit-per-ton estimates.

The method used to calculate the regional bene fit-per-ton estimates is a slight modification of the national benefit-per-ton estimates described in the TSD: Estimating the Benefit per Ton of Reducing PM 2.5 

### Precursors from 17 Sectors (U.S. EPA, 2013a). The national estimates were derived using the approach published in Fann et al. (2012), but they have since been updated to reflect the epidemiology studies and Census population data first applied in the final PM NAAQS RIA (U.S. EPA, 2012a). The approach in Fann et al. (2012) is similar to the work previously published by Fann et al. (2009), but the newer study includes improvements that provide more refined estimates of PM 2.5 

### -related health benefits for emissions reductions in the various sectors. Specifically, the air quality modelin g data reflect industrial sectors that are more narrowly defined. In addition, the updated air quality modeling data reflects more recent emissions data (2005 rather than 2001) and has higher spatial resolution (12km rather than 36 km grid cells). 18 

### For this rulemaking, to generate the regi onal benefit-per-ton estimates we simply aggregated the EGU impacts in BenMAP to the region (i.e., East, West, and California) rather than aggregating to the nation as was done in Fann et al. (2012). We then divided the regional

18 Although the modeling underlying the benefit-per-ton es timates does not reflect emission reductions anticipated from MATS, the EGU contribution to ambient PM 2.5 and ozone on a per-ton basis would be similar. (Fann, Fulcher, and Baker, 2013) Because th e emission reductions in this RIA are calculated from an IPM base case that includes MATS (see Chapter 3), there is no do uble-counting concern with the resulting co-benefits estimates.

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4-33 benefits by the regional emissions rather than the national emissions. The appendix to this chapter provides additional detail regarding these calculations.

As noted below in the characterization of un certainty, all benefit-per-ton estimates have inherent limitations. Specifically, all benefit-per-ton estimates reflect the geographic distribution of the modeled sector emissions, which may not match the emission reductions anticipated by the proposed guidelines, and they may not refl ect local variability in population density, meteorology, exposure, baseline health incidence rates, or other local factors for any specific location. In addition, these estimates reflect the regional average benefit-per-ton for each ambient
PM 2.5 

### precursor emitted from EGUs, which assumes a linear atmospheric re sponse to emission reductions. The regional benefit-per-ton estimates, although less subject to these types of uncertainties than national estimates, still should be interpreted with caution. Even though we assume that all fine particles have equivalent health effects, the benefit-per-ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 

### levels, which drive population exposure.

4.3.4 Benefit-per-ton Estimates for Ozone

Similar to PM 2.5 

### , we used a “benefit-per-ton” approach in this RIA to estimate the ozone co-benefits, which represent the total monetized human health co-benefits (the sum of premature mortality and premature morbidity) of reducing one ton of NOx (an ozone precursor). Also
consistent with the PM 2.5 

### estimates, we generated regional benefit-per-ton estimates for ozone for the EGU sector using the air quality modeling data described in Fann et al. (2012) and using the updated Census population data first applied in the final PM NAAQS RIA (U.S. EPA, 2012a). In
contrast to the PM 2.5 

### estimates, the ozone estimates are not based on changes to annual emissions. Instead, the regional estimates (i.e., East, West, and California) correspond to NO X 

### emissions from U.S. EGUs during the ozone-season (May to September). Because we estimateozone health impacts from May to September only, this approach underestimates ozone cobenefits in areas with a longer ozone season such as southern California and Texas. These
estimates assume that EGU-attributable ozone formation at the regional-level is due to NOx
alone. Because EGUs emit little VOC relative to NO X 

### emissions, it is unlikely that VOCs emitted by EGUs would contribute substantially to regional ozone formation. All benefit-per-ton

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4-34 estimates have inherent limitations and should be interpreted with cau tion. We provide more detailed information regarding the generation of th ese estimates in the appendix to this chapter.

4.3.5 Estimated Health Co-Benefits Results
Tables 4-7 through 4-9 provide the national and regional benefit-per-ton estimates for 2020, 2025, and 2030. Tables 4-10 through 4-12 provide the emission reductions estimated to occur in three analysis years (2020, 2025, and 2030) for two illustrative compliance scenarios (i.e., state and regional) for two options by region (i.e., East, West, and California). 19 

### Tables 4-13 through 4-15 summarize the national monetized PM and ozone-related health co-benefits estimated to occur in three analysis years (2020, 2025, and 2030) for the options by precursor pollutant using discount rates of 3 percent and 7 percent. Tables 4-16 through 4-18 provide
national summaries of the reductions in health incidences estimated for the options associated with these pollution reductions in 2020, 2025, and 2030. Figure 4-1 provides a visual representation of the range of estimated PM 2.5 

### and ozone-related co-benefits using concentrationresponse functions from different studies and expert opinion for the options evaluated in 2020 as an illustrative analysis year. Figures 4-2 and 4-3 provide a breakdown of the monetized health co-benefits for each of the options evaluated in 2020 as an illustrative analysis year by precursor pollutant and region, respectively.

19 See Chapter 3 of this RIA for more information regardin g the expected emission reductions used to calculate the

health co-benefits in this chapter. Chapter 3 also provides more information regarding the illustrative compliance scenarios.

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4-35 Table 4-7. Summary of National and Regional Benefit-per-ton Estimates for EGUs in 2020 (2011$)*

Pollutant Discount Rate National Regional East West California

SO 2 3% $38,000 to $86, 000 $40,000 to $90 ,000 $7,800 to $18,000 $160,0 00 to $320,000 7% $34,000 to $77, 000 $36,000 to $82 ,000 $7,100 to $16,000 $140,0 00 to $320,000 Directly emitted PM 2.5 (EC+OC) 3% $140,000 to $320,000 $140,000 to $320,0 00 $56,000 to $130,000 $ 280,000 to $570,000 7% $130,000 to $290,000 $130,000 to $280,0 00 $50,000 to $110,000 $ 250,000 to $570,000 Directly emitted PM 2.5 (crustal) 3% $18,000 to $40, 000 $18,000 to $41 ,000 $11,000 to $25,000 $110,000 to $220,000 7% $16,000 to $36,000 $16,000 to $37,000 $10,000 to $23,000 $95,000 to $220,000

NO X (as PM 2.5 ) 3% $5,600 to $13,000 $6,700 to $15,000 $1,200 to $2,600 $17,000 to $34,000 7% $5,000 to $11,000 $6,000 to $14,000 $1,000 to $2,400 $15,000 to $34,000 NO X (as Ozone) N/A $3,800 to $16,000 $4,600 to $19,000 $930 to $4,000 $7,400 to $31,000 * The range of estimates reflects the range of epidem iology studies for avoided premature mortality for PM 2.5 and

ozone. All estimates are rounded to two significant figur es. The monetized co-benefits do not include reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairment. All fine particles are assumed to have equivalent health effects, but the be nefit per ton estimates vary depending on the location and magnitude of their impact on PM 2.5 concentrations, which drive population exposure. The monetized co-benefits incorporate the conversion from precursor emissions to ambient fine particles and ozone. Benefit-per-ton estimates for ozone are based on ozone season NO X emissions. Ozone co-benefits occu r in analysis year, so they are the same for all discount rates. Confidence intervals ar e unavailable for this analysis because of the benefitper-ton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 percent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012).



### Table 4-8. Summary of National and Regional Benefit-per-Ton Estimates for EGUs in 2025 (2011$)*

Pollutant Discount Rate National Regional East West California

SO 2 3% $41,000 to $93, 000 $44,000 to $98 ,000 $8,800 to $20,000 $180,0 00 to $410,000 7% $37,000 to $84, 000 $39,000 to $89 ,000 $8,000 to $18,000 $160,0 00 to $370,000 Directly emitted PM 2.5 (EC+OC) 3% $150,000 to $350,000 $150,000 to $340,0 00 $64,000 to $140,000 $ 320,000 to $720,000 7% $140,000 to $310,000 $140,000 to $310,0 00 $58,000 to $130,000 $ 290,000 to $650,000 Directly emitted PM 2.5 (crustal) 3% $17,000 to $39,000 $18,000 to $40,000 $12,000 to $27,000 $43,000 to $96,000 7% $15,000 to $35,000 $16,000 to $36,000 $11,000 to $24,000 $38,000 to $87,000

NO X (as PM 2.5 ) 3% $6,000 to $14,000 $7,200 to $16,000 $1,300 to $2,900 $19,000 to $42,000 7% $5,400 to $12,000 $6,500 to $15,000 $1,200 to $2,600 $17,000 to $38,000 NO X (as Ozone) N/A $4,900 to $21,000 $5,900 to $25,000 $1,200 to $5,400 $9,900 to $42,000 * The range of estimates reflects the range of epidem iology studies for avoided premature mortality for PM 2.5 and

ozone. All estimates are rounded to two significant figur es. The monetized co-benefits do not include reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairment. All fine particles are assumed to have equivalent health effects, but the be nefit per ton estimates vary depending on the location and magnitude of their impact on PM 2.5 concentrations, which drive population exposure. The monetized co-benefits incorporate the conversion from precursor emissions to ambient fine particles and ozone. Benefit-per-ton estimates for ozone are based on ozone season NO X emissions. Ozone co-benefits occu r in analysis year, so they are the same for all discount rates. Confidence intervals ar e unavailable for this analysis because of the benefitper-ton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 percent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012).

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4-36 Table 4-9. Summary of National and Regional Benefit-per-Ton Estimates for EGUs in 2030 (2011$)*

Pollutant Discount Rate National Regional East West California

SO 2 3% $44,000 to $100,000 $47,0 00 to $110,000 $9,800 to $2 2,000 $200,000 to $450,000 7% $40,000 to $90, 000 $42,000 to $95 ,000 $8,800 to $20,000 $180,0 00 to $410,000 Directly emitted PM 2.5 (EC+OC) 3% $170,000 to $370,000 $160,000 to $370,0 00 $71,000 to $160,000 $ 360,000 to $800,000 7% $150,000 to $340,000 $150,000 to $330,0 00 $64,000 to $150,000 $ 320,000 to $730,000 Directly emitted PM 2.5 (crustal) 3% $18,000 to $42,000 $19,000 to $43,000 $13,000 to $30,000 $47,000 to $110,000 7% $17,000 to $38,000 $17,000 to $38,000 $12,000 to $27,000 $43,000 to $96,000

NO X (as PM 2.5 ) 3% $6,400 to $14,000 $7,600 to $17,000 $1,400 to $3,200 $21,000 to $42,000 7% $5,800 to $13,000 $6,900 to $16,000 $1,300 to $2,900 $19,000 to $47,000 NO X (as Ozone) N/A $5,300 to $23,000 $6,300 to $27,000 $1,400 to $6,000 $11,000 to $47,000 * The range of estimates reflects the range of epidem iology studies for avoided premature mortality for PM 2.5 and

ozone. All estimates are rounded to two significant figur es. The monetized co-benefits do not include reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairment. All fine particles are assumed to have equivalent health effects, but the be nefit per ton estimates vary depending on the location and magnitude of their impact on PM 2.5 concentrations, which drive population exposure. The monetized co-benefits incorporate the conversion from precursor emissions to ambient fine particles and ozone. Benefit-per-ton estimates for ozone are based on ozone season NO X emissions. Ozone co-benefits occu r in analysis year, so they are the same for all discount rates. Confidence intervals ar e unavailable for this analysis because of the benefitper-ton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 percent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012).

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4-37 Table 4-10. Emission Reductions of Criteria Pollutants for the Proposed EGU GHG Existing Source Guidelines in 2020 (thousands of short tons) * Region SO 2 All-year NOx Ozone-Season NOx Directly emitted PM 2.5 (EC+OC) * Directly emitted PM 2.5 (crustal) * Option 1 - State

East 311 315 135 5 41 West 25 51 22 <1 4 California 0<1 1 1 N/A N/A National Total 335 367 157 6 45 Option 1 - Regional

East 279 305 130 5 41 West 10 32 13 0 3 California 2 8 3 N/A N/A National Total 292 345 146 6 44 Option 2 - State East 247 240 101 4 35 West 20 40 18 <1 3 California 0<1 1 1 N/A N/A National Total 267 281 119 5 38 Option 2 - Regional East 234 235 97 4 33 West 8 25 11 <1 2 California 2 8 3 N/A N/A National Total 244 268 111 5 36 *Emissions of directly emitted particles not yet available. *A ll emissions shown in the table are rounded, so regional emission reductions may appear to not sum to national total. Formatted Table

Formatted Table

Formatted: Font: 10 pt

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4-38 Table 4-11. Emission Reductions of Criteria Pollutants for the Proposed EGU GHG Existing Source Guidelines in 2025 (thousands of short tons) * Region SO 2 All-year NOx Ozone-Season NOx Directly emitted PM 2.5 (EC+OC) * Directly emitted PM 2.5 (crustal) * Option 1 - State

East 395 378 164 6 44 West 30 53 23 1 6 California 1 5 2 N/A N/A National Total 425 436 190 6 49 Option 1 - Regional

East 376 372 160 5 42 West 16 34 15 1 4 California 3 16 5 N/A N/A National Total 395 421 180 6 46 Option 2 - State

East 301 271 114 4 34 West 25 42 20 <1 4 California 1 4 2 N/A N/A National Total 327 317 136 5 38 Option 2 - Regional

East 281 270 113 4 32 West 13 24 11 <1 3 California 3 14 5 N/A N/A National Total 297 309 129 4 34 *Emissions of directly emitted particles not yet available. *A ll emissions shown in the table are rounded, so regional emission reductions may appear to not sum to national total.

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4-39 Table 4-12. Emission Reductions of Criteria Pollutants for the Proposed EGU GHG Existing Source Guidelines in 2030 (thousands of short tons) * Region SO 2 All-year NOx Ozone-Season NOx Directly emitted PM 2.5 (EC+OC)* Directly emitted PM 2.5 (crustal)* Option 1 - State

East 441 376 163 5 39 West 30 52 24 1 5 California 0<1 0<1 0<1 N/A N/A National Total 471 428 187 6 44 Option 1 - Regional

East 406 366 158 5 39 West 16 33 15 <1 4 California 2 7 3 N/A N/A National Total 424 407 176 5 42 Option 2 - State

East 299 238 104 4 31 West 22 36 16 <1 3 California 0<1 0<1 0 N/A N/A National Total 321 274 120 4 34 Option 2 - Regional

East 275 227 98 4 29 West 11 20 9 <1 2 California 1 4 3 N/A N/A National Total 287 252 110 4 31 *Emissions of directly emitted particles not yet available. *A ll emissions shown in the table are rounded, so regional emission reductions may appear to not sum to national total. Formatted: Font: 10 pt
Formatted: Normal

Formatted: Normal

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4-40 Table 4-13. Summary of Estimated Monetized Health Co-Benefits for the Proposed EGU GHG Existing Source Guidelines in 2020 (millions of 2011$) * Pollutant 3% Discount Rate 7% Discount Rate Option 1 - State

SO 2 $13,000 to $29,000 $11,000 to $26,000 Directly emitted PM 2.5 (EC+OC) $760 to $1,700 $690 to $1,600 Directly emitted PM 2.5 (crustal) $790 to $1,800 $710 to $1,600 NOx (as PM 2.5 ) $2,200 to $4,900 $2,000 to $4,400 NOx (as Ozone) $640 to $2,700 $640 to $2,700 Total $17,000$15,000 to $40,000$36,000 $15,000$14,000 to $36,000$33,000 Option 1 - Regional

SO 2 $12,000 to $26,000 $11,000 to $24,000 Directly emitted PM 2.5 (EC+OC) $750 to $1,700 $670 to $1,500 Directly emitted PM 2.5 (crustal) $770 to $1,700 $690 to $1,600 NOx (as PM 2.5 ) $2,200 to $5,000 $2,000 to $4,500 NOx (as Ozone) $630 to $2,700 $630 to $2,700 Total $16,000$15,000 to $37,000$34,000 $15,000$13,000 to $34,000$31,000 Option 2 - State

SO 2 $10,000 to $23,000 $9,100 to $21,000 Directly emitted PM 2.5 (EC+OC) $640 to $1,500 $580 to $1,300 Directly emitted PM 2.5 (crustal) $660 to $1,500 $600 to $1,400 NOx (as PM 2.5 ) $1,700 to $3,800 $1,500 to $3,400 NOx (as Ozone) $480 to $2,100 $480 to $2,100 Total $14,000$12,000 to $32,000$29,000 $12,000$11,000 to $29,000$26,000 Option 2 - Regional

SO 2 $9,800 to $22,000 $8,900 to $20,000 Directly emitted PM 2.5 (EC+OC) $610 to $1,400 $550 to $1,200 Directly emitted PM 2.5 (crustal) $630 to $1,400 $570 to $1,300 NOx (as PM 2.5 ) $1,700 to $3,900 $1,600 to $3,500 NOx (as Ozone) $470 to $2,000 $470 to $2,000 Total $13,000$12,000 to $31,000$28,000 $12,000$11,000 to $28,000$25,000 * All estimates are rounded to two significant figures so numbers may not sum down columns. The estimated monetized co-benefits do not include climate benefits or reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairme nt. All fine particles are assumed to have equivalent health effects, but the benefit-per-ton estimates vary depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The moneti zed co-benefits incorporate the conv ersion from precursor emissions to ambient fine particles and ozone. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in analysis year, so they are the same for all discount rates. Confidence intervals are unavailable for this analysis because of the benefit-perton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 per cent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012). Emissions of directly emitted particles not yet available.

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4-41 Table 4-14. Summary of Estimated Monetized Health Co-Benefits for the Proposed EGU GHG Existing Source Guidelines in 2025 (millions of 2011$) * Pollutant 3% Discount Rate 7% Discount Rate Option 1 - State

SO 2 $18,000 to $40,000 $16,000 to $36,000 Directly emitted PM 2.5 (EC+OC) $900 to $2,000 $810 to $1,800 Directly emitted PM 2.5 (crustal) $830 to $1,900 $750 to $1,700 NOx (as PM 2.5 ) $2,900 to $6,500 $2,600 to $5,800 NOx (as Ozone) $1,000 to $4,400 $1,000 to $4,400
Total $23,000$22,0 00 to $54,000$51,000 $21,000$20,000 to $49,000$46,000 Option 1 - Regional

SO 2 $17,000 to $38,000 $15,000 to $35,000 Directly emitted PM 2.5 (EC+OC) $850 to $1,900 $760 to $1,700 Directly emitted PM 2.5 (crustal) $780 to $1,800 $700 to $1,600 NOx (as PM 2.5 ) $3,000 to $6,800 $2,700 to $6,100 NOx (as Ozone) $1,000 to $4,300 $1,000 to $4,300
Total $23,000$21,0 00 to $53,000$50,000 $21,000$19,000 to $48,000$45,000 Option 2 - State

SO 2 $14,000 to $30,000 $12,000 to $27,000 Directly emitted PM 2.5 (EC+OC) $690 to $1,600 $630 to $1,400 Directly emitted PM 2.5 (crustal) $640 to $1,400 $580 to $1,300 NOx (as PM 2.5 ) $2,100 to $4,700 $1,900 to $4,200 NOx (as Ozone) $720 to $3,100 $720 to $3,100
Total $18,000$16,0 00 to $41,000$38,000 $16,000$15,000 to $37,000$35,000 Option 2 - Regional

SO 2 $13,000 to $29,000 $12,000 to $26,000 Directly emitted PM 2.5 (EC+OC) $640 to $1,400 $580 to $1,300 Directly emitted PM 2.5 (crustal) $590 to $1,300 $530 to $1,200 NOx (as PM 2.5 ) $2,200 to $5,000 $2,000 to $4,500 NOx (as Ozone) $730 to $3,100 $730 to $3,100
Total $17,000$16,0 00 to $40,000$37,000 $16,000$14,000 to $36,000$34,000 * All estimates are rounded to two significant figures so numbers may not sum down columns. The estimated monetized co-benefits do not include climate benefits or reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairme nt. All fine particles are assumed to have equivalent health effects, but the benefit-per-ton estimates vary depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The moneti zed co-benefits incorporate the conv ersion from precursor emissions to ambient fine particles and ozone. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in analysis year, so they are the same for all discount rates. Confidence intervals are unavailable for this analysis because of the benefit-perton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 per cent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012). Emissions of directly emitted particles not yet available.

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4-42 Table 4-15. Summary of Estimated Monetized Health Co-Benefits for the Proposed EGU GHG Existing Source Guidelines in 2030 (millions of 2011$) * Pollutant 3% Discount Rate 7% Discount Rate Option 1 - State

SO 2 $21,000 to $47,000 $19,000 to $43,000 Directly emitted PM 2.5 (EC+OC) $870 to $2,000 $780 to $1,800 Directly emitted PM 2.5 (crustal) $800 to $1,800 $720 to $1,600 NOx (as PM 2.5 ) $2,900 to $6,600 $2,600 to $6,000 NOx (as Ozone) $1,100 to $4,600 $1,100 to $4,600
Total $27,000$25,0 00 to $62,000$58,000 $24,000$23,000 to $57,000$53,000 Option 1 - Regional

SO 2 $20,000 to $44,000 $18,000 to $40,000 Directly emitted PM 2.5 (EC+OC) $840 to $1,900 $760 to $1,700 Directly emitted PM 2.5 (crustal) $770 to $1,700 $700 to $1,600 NOx (as PM 2.5 ) $3,000 to $6,700 $2,700 to $6,100 NOx (as Ozone) $1,100 to $4,500 $1,100 to $4,500
Total $25,000$24,0 00 to $59,000$55,000 $23,000$21,000 to $54,000$50,000 Option 2 - State

SO 2 $14,000 to $32,000 $13,000 to $29,000 Directly emitted PM 2.5 (EC+OC) $680 to $1,500 $610 to $1,400 Directly emitted PM 2.5 (crustal) $620 to $1,400 $560 to $1,300 NOx (as PM 2.5 ) $1,900 to $4,200 $1,700 to $3,800 NOx (as Ozone) $680 to $2,900 $680 to $2,900
Total $18,000$17,0 00 to $42,000$39,000 $16,000$15,000 to $38,000$36,000 Option 2 - Regional

SO 2 $13,000 to $30,000 $12,000 to $27,000 Directly emitted PM 2.5 (EC+OC) $630 to $1,400 $570 to $1,300 Directly emitted PM 2.5 (crustal) $580 to $1,300 $520 to $1,200 NOx (as PM 2.5 ) $1,800 to $4,200 $1,700 to $3,800 NOx (as Ozone) $660 to $2,800 $660 to $2,800
Total $17,000$16,0 00 to $40,000$37,000 $15,000$14,000 to $36,000$34,000 * All estimates are rounded to two significant figures so numbers may not sum down columns. The estimated monetized co-benefits do not include climate benefits or reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairme nt. All fine particles are assumed to have equivalent health effects, but the benefit-per-ton estimates vary depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The moneti zed co-benefits incorporate the conv ersion from precursor emissions to ambient fine particles and ozone. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in analysis year, so they are the same for all discount rates. Confidence intervals are unavailable for this analysis because of the benefit-perton methodology. In general, the 95 th percentile confidence interval for monetized PM 2.5 benefits ranges from approximately -90 percent to +180 per cent of the central estimates based on Krewski et al. (2009) and Lepeule et al. (2012). Emissions of directly emitted particles not yet available.

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4-43 Table 4-16. Summary of Avoided Health Incidences from PM 2.5 

### -Related and OzoneRelated Co-benefits for Proposed EGU GHG Existing Source Guidelines in 2020* Option 1 - state Option 1 - regional Option 2 - state Option 2 - regional PM 2.5 -related Health Incidences Avoided Premature Mortality Krewski et al. (2009) (adult) 1,8001,600 1,7001,50 0 1,4001,300 1,4001,30 0 Lepeule et al. (2012) (adult) 4,1003,700 3,8003,40 0 3,2002,900 3,2002,90 0 Woodruff et al. (1997) (infant) 44 43 33 33 Avoided Morbidity Emergency department visits for asthma (all ages) 950860 890800 760680 740670 Acute bronchitis (age 8–12) 2,6002,400 2,5002,20 0 2,1001,900 2,0001,80 0 Lower respiratory symptoms (age 7–14) 33,00030,00 0 31,00028, 000 27,00024,00 0 26,00024, 000 Upper respiratory symptoms (asthmatics age 9–11) 48,00044,00 0 45,00041, 000 38,00035,00 0 38,00034, 000 Minor restricted-activity days (age 18–65) 1,300,0001, 200,000 1,200,000 1,100,000 1,000,00094 0,000 1,000,000 930,000 Lost work days (age 18–65) 220,000200, 000 210,00019 0,000 180,000160, 000 170,00016 0,000 Asthma exacerbation (age 6–18) 100,00098,0 00 95,00091, 000 82,00078,00 0 80,00076, 000 Hospital admissions—respiratory (all ages) 530480 490450 420380 410370 Hospital admissions—cardiovascular (age > 18) 650590 610550 520470 500460 Non-Fatal Heart Attacks (age >18)

Peters et al. (2001) 2,1001,900 1,9001,70 0 1,6001,500 1,6001,40 0 Pooled estimate of 4 studies 220200 210190 180160 170160 Ozone-Related Health Incidences Avoided Premature Mortality Bell et al. (2004) (all ages) 36 35 27 27 Levy et al. (2005) (all ages) 170 160 120 120 Avoided Morbidity Hospital admissions—respiratory causes (ages > 65) 220 210 160 160 Hospital admissions—respiratory causes (ages < 2) 100 98 76 74 Emergency room visits for asthma (all ages) 120 110 89 87 Minor restricted-activity days (ages 18-65) 210,000 210,000 160,000 160,000 School absence days 72,00072,00 0 71,00071, 000 55,000 54,000 * All estimates are rounded to whole numbers with two significant figures. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates for all precursor s. Co-benefits for ozone are based on ozone season NOx emissions. Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology. In general, the 95 th percentile confidence interval for the health im pact function alone ranges from approximately ±30 percent for mortality incidence based on Krewski et al. (2009) and ±46 per cent based on Lepeule et al. (2012). Formatted Table

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-44 Table 4-17. Summary of Avoided Health Incidences from PM 2.5 

### -Related and OzoneRelated Co-benefits for Proposed EGU GHG Existing Source Guidelines in 2025* Option 1 - state Option 1 - regional Option 2 - state Option 2 - regional PM 2.5 -related Health Incidences Avoided Premature Mortality Krewski et al. (2009) (adult) 2,4003,200 2,3002,10 0 1,8002,50 0 1,8001,600
Lepeule et al. (2012) (adult) 5,4007,200 5,3004,80 0 4,1005,50 0 4,0003,700 Woodruff et al. (1997) (infant) 56 54 45 43 Avoided Morbidity Emergency department visits for asthma (all ages) 1,2001,600 1,2001,10 0 9301,200 900830
Acute bronchitis (age 8–12) 3,4004,800 3,3003,10 0 2,6003,70 0 2,5002,300
Lower respiratory symptoms (age 7–14) 43,00061,0 00 43,00039, 000 33,00047, 000 32,00030,000
Upper respiratory symptoms (asthmatics age 9–11) 63,00088,0 00 62,00057, 000 48,00068, 000 46,00043,000
Minor restricted-activity days (age 18–65) 1,700,0002, 400,000 1,600,000 1,500,000 1,300,000 1,800,000 1,200,0001,10 0,000 Lost work days (age 18–65) 280,000400 ,000 280,00026 0,000 210,00031 0,000 210,000190,00 0 Asthma exacerbation (age 6–18) 130,000200 ,000 130,00013 0,000 100,00016 0,000 100,00096,000 Hospital admissions—respiratory (all ages) 730920 710660 560710 540490 Hospital admissions—cardiovascular (age > 18) 8901,100 870800 680850 650600 Non-Fatal Heart Attacks (age >18)

Peters et al. (2001) 2,8003,600 2,7002,50 0 2,1002,80 0 2,1001,900
Pooled estimate of 4 studies 310390 300280 230300 220210 Ozone-Related Health Incidences Avoided Premature Mortality Bell et al. (2004) (all ages) 93 92 65 66 Levy et al. (2005) (all ages) 420 420 300 300 Avoided Morbidity Hospital admissions—respiratory causes (ages > 65) 600 600 430 430 Hospital admissions—respiratory causes (ages < 2) 250 240 180 180 Emergency room visits for asthma (all ages) 290 290 210 210 Minor restricted-activity days (ages 18-65) 520,000 520,000 370,000 370,000 School absence days 180,000 180,000 130,000 130,000 * All estimates are rounded to whole numbers with two significant figures. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates for all precursor s. Co-benefits for ozone are based on ozone season NOx emissions. In general, the 95 th percentile confidence interval for the he alth impact function alone ranges from approximately ±30 percen t for mortality incidence based on Krewski et al. (2009) and ±46 pe rcent based on Lepeule et al. (2012). Formatted Table

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4-45 Table 4-18. Summary of Avoided Health Incidences from PM 2.5 

### -Related and OzoneRelated Co-Benefits for Proposed EGU GHG Existing Source Guidelines in 2030* Option 1 - state Option 1 - regional Option 2 - state Option 2 - regional PM 2.5 -related Health Incidences Avoided Premature Mortality Krewski et al. (2009) (adult) 2,7002,600 2,6002,40 0 1,9001,70 0 1,8001,600
Lepeule et al. (2012) (adult) 6,2005,800 5,9005,40 0 4,2003,90 0 4,0003,600 Woodruff et al. (1997) (infant) 55 54 33 43 Avoided Morbidity Emergency department visits for asthma (all ages) 1,4001,300 1,3001,20 0 930850 900800
Acute bronchitis (age 8–12) 3,7003,500 3,5003,30 0 2,5002,30 0 2,5002,200
Lower respiratory symptoms (age 7–14) 48,00045,00 0 45,00042, 000 33,00030, 000 32,00028,0 00 Upper respiratory symptoms (asthmatics age 9–11) 69,00064,00 0 66,00061, 000 47,00043, 000 46,00041,0 00 Minor restricted-activity days (age 18–65) 1,800,0001, 700,000 1,700,000 1,600,000 1,200,000 1,100,000 1,200,0001, 100,000 Lost work days (age 18–65) 310,000290, 000 290,00027 0,000 210,00019 0,000 210,000180 ,000 Asthma exacerbation (age 6–18) 150,000150, 000 140,00014 0,000 100,00099 ,000 100,00093, 000 Hospital admissions—respiratory (all ages) 870810 820760 590540 540510 Hospital admissions—cardiovascular (age > 18) 1,000970 980910 710650 650610 Non-Fatal Heart Attacks (age >18)

Peters et al. (2001) 3,3003,100 3,1002,90 0 2,2002,10 0 2,1001,900
Pooled estimate of 4 studies 360330 340320 240220 220210 Ozone-Related Health Incidences Avoided Premature Mortality Bell et al. (2004) (all ages) 97 96 62 60 Levy et al. (2005) (all ages) 440 430 280 270 Avoided Morbidity Hospital admissions—respiratory causes (ages > 65) 670 660 430 410 Hospital admissions—respiratory causes (ages < 2) 250 240 160 150 Emergency room visits for asthma (all ages) 290 290 190 180 Minor restricted-activity days (ages 18-65) 510,000 510,000 330,000 320,000 School absence days 180,000 180,000 120,000 110,000 * All estimates are rounded to whole numbers with two significant figures. Co-benefits for PM 2.5 precursors are based on regional benefit-per-ton estimates for all precursor s. Co-benefits for ozone are based on ozone season NOx emissions. In general, the 95 th percentile confidence interval for the he alth impact function alone ranges from approximately ±30 percen t for mortality incidence based on Krewski et al. (2009) and ±46 pe rcent based on Lepeule et al. (2012). Formatted Table

Formatted Table

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4-46 PM 2.5 

### Ozone

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-47 Figure 4-1. Monetized Health Co-benefits for each Option (Regional Compliance) of the Proposed EGU GHG Existing Source Guidelines in 2020 *

*The PM 2.5 graphs show the estimated PM 2.5 co-benefits at disc oo unt rates of 3% and 7% using effect coefficients derived from the Krewski et al. (2009) study and the Lepe ule et al. (2012) study, as well as 12 effect coefficients derived from EPA’s expert elicitation on PM mortality (Roman et al., 2008). The results shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration-response functions provided in those studies. The ozone graphs show the estimated ozone co-benefits derived from six ozone mortality studies (i.e., Bell et al. (2004), Schwartz (2005), Huang et al. (2005), Bell et al. (2005), Levy et al. (2005), and Ito et al. (2005). Ozone co-benefits o ccur in the analysis year, so they are the same for all discount rates. These estimates do not include climate benefits. The monetized co-benefits do not include climate benefits or reduced health effects from direct exposure to NO 2 , SO 2 , ecosystem effects, or visibility impairment. Results would be similar if the state compliance scenario was shown.

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-48 SO2 73% Directly emitted PM2.5 (EC+OC) 4%

Directly emitted PM2.5 (Crustal)

5%

NOx (as PM2.5)

14% NOx (as Ozone)

4% 

# Option 1 ‐ Regional

SO2 70% Directly emitted PM2.5 (EC+OC) 5%

Directly emitted PM2.5 (Crustal)

5%

NOx (as PM2.5)

13% NOx (as Ozone)

7% 

# Option 1 ‐ Regional Low Health Co

‐ benefits High Health Co

‐ benefits

Low Health Co

‐ benefits High Health Co

‐ benefits

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4-49 SO2 74% Directly emitted PM2.5 (EC+OC)

5% Directly emitted PM2.5 (Crustal)

5%
NOx (as PM2.5)

13%
NOx (as Ozone)

3% 

## Option 2 ‐ Regional

SO2 72% Directly emitted PM2.5 (EC+OC) 4%

Directly emitted PM2.5 (Crustal)

5%
NOx (as PM2.5)

13% NOx (as Ozone)

6% 

## Option 2 ‐ Regional

SO2 81% Directly emitted PM2.5 (EC+OC)

0% Directly emitted PM2.5 (Crustal) 0%

NOx (as PM2.5)

15%

NOx (as Ozone)

4% 

## Option 1 ‐ Regional

SO2 77% Directly emitted PM2.5 (EC+OC)

0%
Directly emitted PM2.5 (Crustal)

0% NOx (as PM2.5)

15%

NOx (as Ozone)

8% 

## Option 1 ‐ Regional

SO2 82% Directly emitted PM2.5 (EC+OC)

0% Directly emitted PM2.5 (Crustal) 0%

NOx (as PM2.5)

14% NOx (as Ozone)

4% 

## Option 2 ‐ Regional

SO2 79% Directly emitted PM2.5 (EC+OC)

0%
Directly emitted PM2.5 (Crustal)

0% NOx (as PM2.5)

14% NOx (as Ozone)

7% 

## Option 2 ‐ Regional Formatted: 10 Caption Figure, Centered, Space After: 6 pt, Keep with next

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-50 Figure 4-2. Breakdown of Monetized Health Co-benefits by Precursor Pollutant at a 3% Discount Rate for each Option (Regional Compliance) for Proposed EGU GHG Existing Source Guidelines in 2020* * “Low Health Co-benefits” refers to the combined health co-benefits estimated using the Bell et al. (2004) mortality study for ozone with the Krew ski et al. (2009) mortality study for PM 2.5 . “High Health Co-benefits” refers to the combined health co-b enefits estimated using the Levy et al. (2005) mortality study for ozone with the Lepeule et al. (2012) mortality study for PM 2.5 . Emission reductions of directly emitted particles are not yet available. Results would be similar if the state compliance scenario was shown.

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4-51 East 95.6% West 1.1%

California

3.3% 

## Option 1 ‐ Regional

East 95.5% West 1.2%

California

3.3% 

## Option 1 ‐ Regional

East 95.5% West 0.9%

California

3.6% 

## Option 1 ‐ Regional

East 95.5% West 0.9%

California

3.6% 

## Option 1 ‐ Regional Low Health Co

‐ benefits High Health Co

‐ benefits

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-52 Figure 4-3. Breakdown of Monetized Health Co-Benefits by Region at a 3% Discount Rate for each Option (Regional compliance) for Proposed EGU GHG Existing Source Guidelines in 2020* * “Low Health Co-benefits” refers to the combined health co-benefits estimated using the Bell et al. (2004) mortality study for ozone with the Krewsk i et al. (2009) mortality study for PM 2.5 . “High Health Co-benefits” refers to the combined health co-b enefits estimated using the Levy et al. (2005) mortality study for ozone with the Lepeule et al. (2012) mortality study for PM 2.5 . Results would be similar if the state compliance scenario was shown. 

### 4.3.6 Characterization of Uncertainty in the Estimated Health Co-benefits
In any complex analysis using estimated parameters and inputs from numerous models, there are likely to be many sources of uncertainty. This analysis is no exception. This analysis includes many data sources as inputs, includi ng emission inventories, air quality data from models (with their associated parameters an d inputs), population data, population estimates, health effect estimates from epidemiology studies, economic data for monetizing co-benefits, and assumptions regarding the future state of th e world (i.e., regulations, technology, and human East 95.1% West 1.1%

California

3.8% 

## Option 2 ‐ Regional

East 95.0% West 1.1%

California

3.9% 

## Option 2 ‐ Regional

East 94.9% West 0.8%

California

4.2% 

## Option 2 ‐ Regional

East 94.8% West 0.9%

California

4.3% 

## Option 2 ‐ Regional

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-53 behavior). Each of these inputs may be uncertain and would affect the estimate of co-benefits. When the uncertainties from each stage of the analysis are compounded, even small uncertainties can have large effects on the total quantified benef its. Therefore, the estimates of co-benefits in each analysis year should be viewed as representative of the general magnitude of co-benefits of the illustrative compliance scenarios, rather than the actual co-benefits anticipated from implementing the proposed guidelines.

This RIA does not include the type of detailed uncertainty assessment found in the PM NAAQS RIA (U.S. EPA, 2012a) or the Ozone NA AQS RIA (U.S. EPA, 2008b) because we lack the necessary air quality modeling input and/or monitoring data to run the benefits model. However, the results of the quantitative and qualita tive uncertainty analyses presented in the PM NAAQS RIA and Ozone NAAQS RIAs can provide some information regarding the uncertainty inherent in the estimated co-benefits results pres ented in this analysis. For example, sensitivity analyses conducted for the PM NAAQS RIA indicat e that alternate cessation lag assumptions could change the estimated PM 2.5 

### -related mortality co-benefits discounted at 3 percent by between 10 percent and –27 percent and that alternate income growth adjustments could change
the PM 2.5 

### -related mortality co-benefit s by between 33 percent and

− 14 percent. Although we generally do not calculate confidence in tervals for benefit-per-ton estimates and they can provide an incomplete picture about the overall uncertainty in the benefits estimates 

### , the PM NAAQS RIA can provide an indication of the random sampling error in the health impact and economic valuation functions using Monte Carlo methods. 

### In general, the 95 th 

### percentile confidence interval
for monetized PM 2.5 

### benefits ranges from approximately -90 percent to +180 percent of the
central estimates based on Krewski et al. (2009) and Lepeule et al. (2012). The 95 th 

### percentile confidence interval for the health impact function alone ranges from approximately ±30 percent for mortality incidence based on Krewski et al. (2009) and ±46 percent based on Lepeule et al. (2012).



### Unlike RIAs for which EPA conducts air quality modeling, we do not have information on the specific location of the air quality changes associated with the proposed guidelines. As such,
it is not feasible to estimate th e proportion of co-benefits occurring in different locations, such as designated nonattainment areas. Instead, we applied benefit-per-ton estimates, which reflect specific geographic patterns of emissions reduc tions and specific air quality and benefits modeling assumptions. For example, these esti mates may not reflect local variability in

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-54 population density, meteorology, exposure, baseline health incidence rates, or other local factors that might lead to an over-estimate or under-estimate of the actual co-benefits of controlling PM and ozone precursors. Use of these benefit-per-ton values to estimate co-benefits may lead to higher or lower benefit estimates than if co-benefits were calculated based on direct air quality modeling. Great care should be taken in applying these estimates to emission reductions occurring in any specific location, as these are all based on broad emission reduction scenarios and therefore represent average benefits-per-ton over the entire region. The benefit-per-ton for emission reductions in specific locations may be very different than the estimates presented here. To the extent that the geographic distributio n of the emissions reductions achieved by implementing the proposed guidelines is different than the emissions in the sector modeling, the co-benefits may be underestimated or overestimated. For more information regarding the limitations of benefit-per-ton estimates derived from the sector modeling, see the TSD describing the calculation of the national benefit-per-ton estimates (U.S. EPA, 2013a) and Fann et al. (2012). In addition, the appendix to this chapter provides additional uncertainty information regarding the benefit-per-ton estimates applied in this RIA, including an evaluation of the
similarities and differences in th e spatial distribution of EGU emissions in the sector modeling and the IPM base case discussed in Chapter 3 of this RIA.

Our estimate of the total monetized co-benefits is based on EPA’s interpretation of the best available scientific literature and methods and supported by the SAB-HES and the National Academies of Science (NRC, 2002). Below are key assumptions underlying the estimates for
PM 2.5 

### -related premature mortality, which accounts for 98 percent of the monetized PM 2.5 

### health
co-benefits.

1. We assume that all fine particles, rega rdless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 

### varies considerably in composition across sources, but the scientific evidence is not yet sufficient to allow differ entiation of effect es timates by particle type. The PM ISA concluded that “many constituents of PM 2.5 

### can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific outcomes” (U.S. EPA, 2009b).

2. We assume that the health impact function for fine particles is log-linear without a threshold in this analysis. Thus, the estimates include health co-benefits from

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4-55 reducing fine particles in areas with varied concentrations of PM 2.5 

### , including both areas that do not meet the fine particle standard and those areas that are in attainment, down to the lowest modeled concentrations.

3. We assume that there is a “cessation” lag between the change in PM exposures and the total realization of changes in mortality effects. Specifically, we assume that some of the incidences of premature mortality related to PM 2.5 

### exposures occur in a distributed fashion over the 20 years following exposure based on the advice of theSAB-HES (U.S. EPA-SAB, 2004c), which affects the valuation of mortality cobenefits at different discount rates.
In general, we are more confident in the magnitude of the risks we estimate from simulated
PM 2.5 

### concentrations that coincide with the bulk of the observed PM concentrations in the epidemiological studies that are used to estimate the benefits. Likewise, we are less confident in
the risk we estimate from simulated PM 2.5 

### concentrations that fall be low the bulk of the observed data in these studies. Concentration benchmark analyses (e.g., lowest measured level [LML], one standard deviation below the mean of the air quality data in the study, etc.) allow readers to determine the portion of population exposed to annual mean PM 2.5 

### levels at or above different concentrations, which provides some insight into the level of uncertainty in the estimated PM 2.5 

### mortality benefits. In this analysis, we apply two concentration benchmark approaches (LML and one standard deviation below the mean) that have been incorporated into recent RIAs and EPA’s Policy Assessment for Particulate Matter (U.S. EPA, 2011d). There are uncertainties inherent in identifying any particular point at which our confidence in reported associations becomes appreciably less, and the scientific evidence provides no clear dividing line. However, the EPA
does not view these concentration benchmarks as a concentration threshold below which we would not quantify health co-benefits of air quality improvements. 20 

### Rather, the co-benefits estimates reported in this RIA are the best estimates because they reflect the full range of air quality concentrations associated with the emission reduction strategies. The PM ISA concluded that the scientific evidence collectively is suffic ient to conclude that the relationship between long-term PM 2.5 

### exposures and mortality is causal and that overall the studies support the use of a no-threshold log-linear model to estimate PM-rel ated long-term mortality (U.S. EPA, 2009b).

20 For a summary of the scientific review statements regarding the lack of a threshold in the PM 2.5 -mortality

relationship, see the TSD entitled Summary of Expert Opinions on the Existence of a Threshold in the Concentration-Response Function for PM 2.5 -related Mortality (U.S. EPA, 2010b).

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4-56 For this analysis, policy-specific air quality data is not available. For this RIA, we are unable to estimate the percentage of premature mo rtality associated with the emission reductions
at each PM 2.5 

### concentration. However, we believe that it is still important to characterize the distribution of exposure to baseline concentrations. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 

### level in the baseline of the source apportionment modeling used to calculate the benefit-per-ton estimates for this sector. 21 

### It is important to note that baseline exposure is on ly one parameter in the health impact function, along with baseline incidence rates population and change in air quality. In other words, the percentage of the population exposed to air pollution below the LML is not the same as the percentage of the population experiencing health impacts as a result of a specific emission reduction policy. The most important aspect, wh ich we are unable to quantify without rulespecific air quality modeling, is the shift in ex posure anticipated by im plementing the proposed guidelines. Therefore, caution is warranted when interpreting the LML assessment in this RIA because these results are not consistent with results from RIAs that had air quality modeling.

Table 4-19 provides the percentage of the population exposed above and below two concentration benchmarks (i.e., LML and one standard deviation below the mean) in the modeled baseline for the sector modeling. Figure 4-4 shows a bar chart of the percentage of the population exposed to various air quality levels in the baseline, and Figure 4-5 shows a cumulative distribution function of the same data. Both figures identify the LML for each of the major cohort studies.

21 As noted above, the modeling used to generate the be nefit-per-ton estimates does not reflect emission reductions

anticipated from MATS rule. Therefore, the baseline PM 2.5 concentrations in the LML assessment are higher than would be expected if MATS was reflected.

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4-57 Table 4-19. Population Exposure in the Baseline Modeling Above and Below Various Concentrations Benchmarks in the Underlying Epidemiology Studies *

Epidemiology Study Below 1 Standard Deviation. Below AQ Mean At or Above 1 Standard Deviation Below AQ Mean Below LML At or Above LML
Krewski et al. (2009) 89% 11% 7% 93% Lepeule et al. (2012) N/A N/A 23% 67%

* One standard deviation below the mean is equivalent to the middle of the range between the 10 th and 25 th

percentile. For Krewski, the LML is 5.8 μg/m 3 and one standard deviation below the mean is 11.0 μg/m 3 . For Lepeule et al., the LML is 8 μg/m 3 and we do not have the data for one st andard deviation below the mean. It is important to emphasize that although we have lower levels of confidence in levels below the LML for each study, the scientific evidence does not support the existence of a level below which health effects from exposure to PM 2.5 do not occur.



### Figure 4-4 . Percentage of Adult Population (age 30+) by Annual Mean PM 2.5 

### Exposure in the Baseline Sector Modeling Among the populations exposed to PM 2.5 in the baseline: 93% are exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study 67% are exposed to PM 2.5 levels at or above the LML of the Lepeule et al. (2012) study 0% 5% 10% 15% 20% 25%

<1 1

‐ 2 2

‐ 3 3

‐ 4 4

‐ 5 5

‐ 6 6

‐ 7 7

‐ 8 8

‐ 9 9

‐ 10 10

‐ 11 11

‐ 12 12

‐ 13 13

‐ 14 14

‐ 15 15

‐ 16 16

‐ 17 17

‐ 18 18

‐ 19 19

‐ 20PercentageofPopulationExposed

Baseline Annual Mean PM 2.5 Level (μg/m 3 ) LML of Lepeule et al. (2012) study LML of Krewski et al. (2009) study

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4-58 Figure 4-5 . Cumulative Distribution of Adult Population (age 30+) by Annual Mean PM 2.5 

### Exposure in the Baseline Sector Modeling

4.4 Combined Climate Benefits and Health Co-benefits Estimates
In this analysis, we were able to monetize the estimated co-benefits associated with the
decreased emissions of CO 2 

### and reduced exposure to PM 2.5 

### and ozone, but we were unable to monetize the co-benefits associated with reducing exposure to mercury, hydrogen chloride, carbon monoxide, SO 2 

### , and NO 2 

### , as well as ecosystem effects and visibility impairment. Specifically, we estimated the combined climate benefits at discount rates of 5 percent, 3 percent, 2.5 percent, and 3 percent (95 th 

### percentile) (as estimated by the interagency working group), and health co-benefits at discount rates of 3 percent and 7 percent (as recommended by
EPA’s Guidelines for Preparing Economic Analyses (U.S. EPA, 2010e) and OMB’s Circular A4 [OMB, 2003]).

Different discount rates are applied to SCC than to the health co-benefit estimates
because CO 2 

### emissions are long-lived and subsequent damages occur over many years.

Among the populations exposed to PM 2.5 in the baseline: 93% are exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study 67% are exposed to PM 2.5 levels at or above the LML of the Lepeule et al. (2012) study 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Cumulativepercentageofpopulationexposed

Baseline Annual Mean PM 2.5 Level (μg/ m 3 ) LML of Krewski et al. (2009) study LML of Lepeule et al. (2012) study

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4-59 Moreover, several rates are applied to SCC beca use the literature shows that it is sensitive to assumptions about discount rate and because no consensus exists on the appropriate rate to use in an intergenerational context. The SCC interagency group centered its attention on the 3 percent discount rate but emphasized the importance of considering all four SCC estimates. 22 

### The EPA has evaluated the range of potential impacts by co mbining all SCC values w ith health co-benefits values at the 3 percent and 7 percent discount rates. To be consistent with concepts of intergenerational discounting, values for health benefits, which occur within a generation, would only be combined with SCC values using a lower discount rate (e.g., the 7 percent health benefit estimates would be combined with 5 percent or lower SCC values, but the 3 percent health benefit would not be combined with the 5 percent SCC value). While the 5 percent SCC and 3 percent health benefit estimate falls within the range of values we analyze, this individual estimate should not be used independently in an analysis, as it represents a combination of discount rates that is unlikely to occur. Combin ing the 3 percent SCC values with the 3 percent
health benefit values assumes that there is no difference in discount rates between intragenerational and inte rgenerational impacts.

Tables 4-20 through 4-22 provide the combined climate and health benefits for each option evaluated for 2020, 2025, and 2030. Figure 4-6 shows the breakdown of the monetized benefits by pollutant for each option evaluated in 2020 as an illustrative analysis year using a 3 percent discount rate.

22 See the 2010 SCC TSD. Docket ID EPA-HQ-OAR-2009-0472-114577 or

http://www.whitehouse.gov/sites/default/files/omb/in foreg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf for details.

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4-60 Table 4-20. Combined Climate Benefits and Health Co-Benefits for Proposed EGU GHG Existing Source Guidelines in 2020 (billions of 2011$)*

SCC Discount Rate Climate Benefits Only Climate Benefits and plus Health Co-Benefits (Discount Rate Applied to Health Co-Benefits)

3% 7% Option 1 - state 383 million metric tonnes CO 2 5% $4.9 $22$20 toto $45$41 $20$19 toto $41$38 3% $18 $35$33 toto $57$54 $33$32 toto $54$50 2.5% $26 $43$42 toto $66$62 $42$40 toto $62$59 3% (95 th percentile) $52 $69$68 toto $92$89 $68$66 toto $88$85 Option 1 - regional 371 million metric tonnes CO 2 5% $4.7 $21$19 toto $42$39 $19$18 toto $39$36 3% $17 $33$32 toto $54$51 $32$30 toto $51$48 2.5% $25 $41$40 toto $63$59 $40$38 toto $59$56 3% (95 th percentile) $51 $67$65 toto $88$85 $65$64 toto $85$81 Option 2 - state 295 million metric tonnes CO 2 5% $3.8 $17$16 toto $35$32 $16$15 toto $32$30 3% $14 $27$26 toto $45$42 $26$25 toto $42$40 2.5% $20 $34$32 toto $52$49 $32$31 toto $49$46 3% (95 th percentile) $40 $54$53 toto $72$69 $53$51 toto $69$66 Option 2 - regional 283 million metric tonnes CO 2 5% $3.6 $17$16 toto $34$32 $16$15 toto $32$29 3% $13 $26$25 toto $44$41 $25$24 toto $41$38 2.5% $19 $33$31 toto $50$47 $31$30 toto $47$45 3% (95 th percentile) $39 $52$51 toto $70$67 $51$50 toto $67$64 *All estimates are rounded to two significant figures. Climate benefits are based on reductions in CO 2 emissions. Co-benefits are based on regional benefit-per-ton estimat es. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in an alysis year, so they are the same fo r all discount rates. The health cobenefits reflect the sum of the PM 2.5 and ozone co-benefits and reflect the ra nge based on adult mortality functions (e.g., from Krewski et al. (2009) with Bell et al. (2004) to Lepeule et al. (2012) with Levy et al. (2005)). The monetized health co-benefits do not include redu ced health effects from direct exposure to NO 2 , SO 2 , and HAP; ecosystem effects; or visibility impairment. Emission reductions of directly emit ted particles are not yet available.

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4-61 Table 4-21. Combined Climate Benefits and Health Co-Benefits for Proposed EGU GHG Existing Source Guidelines in 2025 (billions of 2011$)*

SCC Discount Rate Climate Benefits Only Climate Benefits and plus Health Co-Benefits (Discount Rate Applied to Health Co-Benefits)

3% 7% Option 1 - state 506 million metric tonnes CO 2 5% $7.6 $31$29 toto $62$58 $29$27 toto $57$54 3% $25 $49$47 toto $80$76 $46$45 toto $75$71 2.5% $37 $61$59 toto $92$88 $58$57 toto $87$83 3% (95 th percentile) $77 $100$99 toto $130$130 $98$97 toto $130$120 Option 1 - regional 501 million metric tonnes CO 2 5% $7.5 $30$29 toto $61$57 $28$27 toto $56$53 3% $25 $48$46 toto $78$75 $46$44 toto $74$70 2.5% $37 $60$58 toto $90$86 $57$56 toto $85$82 3% (95 th percentile) $76 $99$98 toto $130$130 $97$96 toto $120$120 Option 2 - state 376 million metric tonnes CO 2 5% $5.6 $23$22 toto $47$44 $22$20 toto $43$40 3% $19 $36$35 toto $60$57 $35$34 toto $56$54 2.5% $28 $45$44 toto $69$66 $44$42 toto $65$62 3% (95 th percentile) $57 $75$74 toto $98$95 $73$72 toto $95$92 Option 2 - regional 368 million metric tonnes CO 2 5% $5.5 $23$21 toto $46$43 $21$20 toto $42$39 3% $18 $36$34 toto $59$56 $34$33 toto $55$52 2.5% $27 $44$43 toto $67$64 $43$42 toto $64$61 3% (95 th percentile) $56 $73$72 toto $96$93 $72$71 toto $93$90 *All estimates are rounded to two significant figures. Climate benefits are based on reductions in CO 2 emissions. Co-benefits are based on regional benefit-per-ton estimat es. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in an alysis year, so they are the same for all discount rates. The health cobenefits reflect the sum of the PM 2.5 and ozone co-benefits and reflect the ra nge based on adult mortality functions (e.g., from Krewski et al. (2009) with Bell et al. (2004) to Lepeule et al. (2012) with Levy et al. (2005)). It is important to note that the monetized health co-benefits do not include reduced health effects from direct exposure to NO 2 , SO 2 , and HAP; ecosystem effects; or visibility impairment. Emission reductions of directly emitted particles are not yet available.

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4-62 Table 4-22. Combined Climate Benefits and Health Co-Benefits for Proposed EGU GHG Existing Source Guidelines in 2030 (billions of 2011$)*

SCC Discount Rate Climate Benefits Only Climate Benefits and plus Health Co-Benefits (Discount Rate Applied to Health Co-Benefits)

3% 7% Option 1 - state 555 million metric tonnes CO 2 5% $9.5 $36$34 toto $72$68 $34$32 toto $66$63 3% $31 $57$56 toto $93$89 $55$53 toto $87$84 2.5% $44 $71$69 toto $110$100 $69$67 toto $100$98 3% (95 th percentile) $94 $120$120 toto $160$150 $120$120 toto $150$150 Option 1 - regional 545 million metric tonnes CO 2 5% $9.3 $35$32 toto $68$62 $32$30 toto $63$57 3% $30 $55$53 toto $89$83 $53$51 toto $84$78 2.5% $44 $69$67 toto $100$97 $66$65 toto $97$92 3% (95 th percentile) $92 $120$120 toto $150$150 $120$110 toto $150$140 Option 2 - state 373 million metric tonnes CO 2 5% $6.4 $24$33 toto $48$65 $23$31 toto $44$60 3% $21 $39$54 toto $63$86 $37$52 toto $59$81 2.5% $30 $48$67 toto $72$99 $46$65 toto $68$94 3% (95 th percentile) $63 $81$120 toto $110$150 $80$110 toto $100$140 Option 2 - regional 353 million metric tonnes CO 2 5% $6.0 $23$22 toto $46$43 $21$20 toto $42$40 3% $20 $37$35 toto $59$56 $35$34 toto $56$53 2.5% $28 $45$44 toto $68$65 $44$43 toto $64$62 3% (95 th percentile) $60 $77$76 toto $100$97 $75$74 toto $96$93 *All estimates are rounded to two significant figures. Climate benefits are based on reductions in CO 2 emissions. Co-benefits are based on regional benefit-per-ton estimat es. Co-benefits for ozone are based on ozone season NOx emissions. Ozone co-benefits occur in an alysis year, so they are the same fo r all discount rates. The health cobenefits reflect the sum of the PM 2.5 and ozone co-benefits and reflect the ra nge based on adult mortality functions (e.g., from Krewski et al. (2009) with Bell et al. (2004) to Lepeule et al. (2012) with Levy et al. (2005)). It is important to note that the monetized health co-benefits do not include reduced health effects from direct exposure to NO 2 , SO 2 , and HAP; ecosystem effects; or visibility impairment. Emission reductions of directly emitted particles are not yet available.

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4-63 CO2 54% SO2 37% Directly emitted PM2.5 (EC+OC) 0%

Directly emitted PM2.5 (Crustal) 0%

NOx (as PM2.5)

7% NOx (as Ozone) 2% 

## Option 1 ‐ Regional

CO2 33% SO2 52% Directly emitted PM2.5 (EC+OC) 0%

Directly emitted PM2.5 (Crustal) 0% NOx (as PM2.5) 10%

NOx (as Ozone) 5% 

## Option 1 ‐ Regional

CO2 52% SO2 35% Directly emitted PM2.5 (EC+OC) 2%

Directly emitted PM2.5 (Crustal) 2%

NOx (as PM2.5)

7% NOx (as Ozone) 2% 

## Option 1 ‐ Regional

CO2 31% SO2 49% Directly emitted PM2.5 (EC+OC) 3%

Directly emitted PM2.5 (Crustal) 3%

NOx (as PM2.5)

9% NOx (as Ozone) 5% 

## Option 1 ‐ Regional Low Health Co

‐ benefits High Health Co

‐ benefits

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4-64 Figure 4-6. Breakdown of Combined Monetized Climate and Health Co-benefits of Proposed EGU GHG Existing Source Guidelines in 2020 by Option (Regional Compliance) and Pollutant (3% discount rate)* * “Low Health Co-benefits” refers to the combined health co-benefits estimated using the Bell et al. (2004) mortality study for ozone with the Krew ski et al. (2009) mortality study for PM 2.5 . “High Health Co-benefits” refers to the combined health co-b enefits estimated using the Levy et al. (2005) mortality study for ozone with the Lepeule et al. (2012) mortality study for PM 2.5 . Results would be similar if the state compliance scenario was shown. 

### 4.5 Unquantified Co-benefits
The monetized co-benefits estimated in this RIA only reflect a subset of co-benefits
attributable to the health effect reductions associ ated with ambient fine particles and ozone. Data, time, and resource limitations prevented EPA from quantifying the impacts to, or monetizing the co-benefits from several important benefit cate gories, including co-benefits associated with exposure to several HAP (including mercury and hydrogen chloride) SO 2 

### and NO 2 

### , as well as CO2 50% SO2 37% Directly emitted PM2.5 (EC+OC) 2%

Directly emitted PM2.5 (Crustal) 2%

NOx (as PM2.5)

7% NOx (as Ozone) 2% 

## Option 2 ‐ Regional

CO2 30% SO2 50% Directly emitted PM2.5 (EC+OC) 3%

Directly emitted PM2.5 (Crustal) 3%

NOx (as PM2.5)

9% NOx (as Ozone) 5% 

## Option 2 ‐ Regional

CO2 52% SO2 39% Directly emitted PM2.5 (EC+OC) 0%

Directly emitted PM2.5 (Crustal) 0%

NOx (as PM2.5)

7% NOx (as Ozone) 2% 

## Option 2 ‐ Regional

CO2 32% SO2 54% Directly emitted PM2.5 (EC+OC) 0%

Directly emitted PM2.5 (Crustal) 0% NOx (as PM2.5)

9%

NOx (as Ozone) 5% 

## Option 2 ‐ Regional

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4-65 ecosystem effects, and visibility impairment due to the absence of air quality modeling data for these pollutants in this analysis. This does not imply that there are no co-benefits associated with these emission reductions. In this section, we provide a qualitative description of these benefits,
which are listed in Table 4-23.

Table 4-23. Unquantified Health and Welfare Co-benefits Categories

Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information Improved Human Health

Reduced incidence of morbidity from exposure to NO 2 Asthma hospital admissions (all ages) — — NO 2 ISA 1 Chronic lung disease hospital admissions (age > 65) — — NO 2 ISA 1
Respiratory emergency department visits (all ages) — — NO 2 ISA 1 Asthma exacerbation (asthmatics age 4–18) — — NO 2 ISA 1 Acute respiratory symptoms (age 7–14) — — NO 2 ISA 1 Premature mortality — — NO 2 ISA 1,2,3 Other respiratory effects (e.g., airway hyperresponsiveness and inflammation, lung function, other ages and populations) — — NO 2 ISA 2,3

Reduced incidence of morbidity from exposure to SO 2 Respiratory hospital admissions (age > 65) — — SO 2 ISA 1 Asthma emergency department visits (all ages) — — SO 2 ISA 1 Asthma exacerbation (asthmatics age 4–12) — — SO 2 ISA 1 Acute respiratory symptoms (age 7–14) — — SO 2 ISA 1 Premature mortality — — SO 2 ISA 1,2,3 Other respiratory effects (e.g., airway hyperresponsiveness and inflammation, lung function, other ages and populations) — — SO 2 ISA 1,2

Reduced incidence of morbidity from exposure to CO Cardiovascular effects — — CO ISA 1,2 Respiratory effects — — CO ISA 1,2,3 Central nervous system effects — — CO ISA 1,2,3 Premature mortality — — CO ISA 1,2,3 Reduced incidence of morbidity from exposure to methylmercury Neurologic effects—IQ loss — — IRIS; NRC, 2000 1

Other neurologic effects (e.g., developmental delays, memory, behavior) — — IRIS; NRC, 2000 2

Cardiovascular effects — — IRIS; NRC, 2000 2,3
Genotoxic, immunologic, a nd other toxic effects — — IRIS; NRC, 2000 2,3 Reduced incidence of morbidity from exposure to HAP Effects associated with exposure to hydrogen chloride — — ATSDR, IRIS 1,2

Improved Environment Table 4-12. Continued Reduced visibility impairment Visibility in Class 1 areas — — PM ISA 1 Visibility in residential areas — — PM ISA 1

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4-66 Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information
Reduced effects on materials Household soiling — — PM ISA 1,2 Materials damage (e.g., corrosion, increased wear) — — PM ISA 2 Reduced effects from PM deposition (metals and organics) Effects on Individual organisms and ecosystems — — PM ISA 2

Reduced vegetation and ecosystem effects from exposure to ozone Visible foliar injury on vegetation — — Ozone ISA 1 Reduced vegetation growth and reproduction — — Ozone ISA 1 Yield and quality of commercial forest products and crops — — Ozone ISA 1
Damage to urban ornamental plants — — Ozone ISA 2 Carbon sequestration in terrestrial ecosystems — — Ozone ISA 1 Recreational demand associated with forest aesthetics — — Ozone ISA 2

Other non-use effects Ozone ISA 2 Ecosystem functions (e.g., water cycling, biogeochemical cycles, net primary productivity, leaf-gas exchange, community composition) — — Ozone ISA 2

Reduced effects from acid deposition Recreational fishing — — NO x SO x ISA 1 Tree mortality and decline — — NO x SO x ISA 2 Commercial fishing and forestry effects — — NO x SO x ISA 2 Recreational demand in terrestrial and aquatic ecosystems — — NO x SO x ISA 2

Other non-use effects NO x SO x ISA 2 Ecosystem functions (e.g., biogeochemical cycles) — — NO x SO x ISA 2

Reduced effects from nutrient enrichment Species composition and biodiversity in terrestrial and estuarine ecosystems — — NO x SO x ISA 2
Coastal eutrophication — — NO x SO x ISA 2 Recreational demand in te rrestrial and estuarine ecosystems — — NO x SO x ISA 2

Other non-use effects NO x SO x ISA 2 Ecosystem functions (e.g., biogeochemical cycles, fire regulation) — — NO x SO x ISA 2 Reduced vegetation effects from ambient exposure to SO 2 and NO x Injury to vegetation from SO 2 exposure — — NO x SO x ISA 2

Injury to vegetation from NO x exposure — — NO x SO x ISA 2

Reduced ecosystem effects from exposure to methylmercury Effects on fish, birds, and mammals (e.g., reproductive effects) — — Mercury Study RTC 2
Commercial, subsistence and recreational fishing — — Mercury Study RTC 1

1 We assess these co-benefits qualitatively due to data and resource limitations for this RIA. 2 We assess these co-benefits qualitatively because we do not have sufficient confidence in available data or

methods. 3 We assess these co-benefits qualitatively because current evidence is only suggest ive of causality or there are other significant concerns over the strength of the association.


### 4.5.1 HAP Co-benefits
Due to methodology and resource limitations, we were unable to estimate the co-benefits associated with reducing emissions of the hazard ous air pollutants in this analysis. EPA’s SAB-

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4-67 HES concluded that “the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air pollut ants (HAPs) are daunting...due to a lack of exposure-response functions, uncertainties in emissions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods” (U.S. EPA-SAB, 2008). In 2009, EPA convened a workshop to address the inherent co mplexities, limitations, and
uncertainties in current methods to quantify the benefits of reducing HAP. Recommendations from this workshop included identifying research priorities, focusing on susceptible and vulnerable populations, and improving dose-res ponse relationships (Gwinn et al., 2011).

Chapter 4 of the MATS RIA (U.S. EPA, 2011b) describes the health effects associated with HAP emitted by EGUs. Below we describe th e health effects associated with the two HAP for which we were able to quantify emission reductions for the proposed guidelines: mercury and hydrogen chloride. Using the IPM modeling described in Chapter 3 of this RIA, wW e estimate that the illustrative compliance scenarios for the proposed guidelines would reduce mercury emissions by up to 2.1 tons and hydrogen chloride by up to 590 tons by 2030. These HAP emission reductions are beyond those achieved by MATS.

4.5.1.1 Mercury
Mercury in the environment is transforme d into a more toxic form, methylmercury (MeHg). Because Hg is a persistent pollutant, Me Hg accumulates in the food chain, especially the tissue of fish. When people consume these fish, they consume MeHg. In 2000, the NAS Study was issued which provides a thorough review of the effects of MeHg on human health (NRC, 2000). 23 

### Many of the peer-reviewed articles cited in this section are publications originally cited in the Mercury Study. 24 

### In addition, EPA has conducted literature searches to obtain other related and more recent publications to complement the material summarized by the
NRC in 2000.

23 National Research Council (NRC). 2000 . Toxicological Effects of Methylmercury . Washington, DC: National

Academies Press.

24 U.S. Environmental Protection Agency (U.S. EPA). 1997. Mercury Study Report to Congress , EPA–HQ–OAR–

2009–0234–3054. December. Available on the In ternet at <http://www.epa.gov/hg/report.htm>. Comment [A10]: OMB comment: Can EPA better explain how these numbers were derived? We’d also like to discuss whether the same tons of NOx are being modeled in the indirect PM and ozone sections.
EPA response: We clarified the origin of the HAP emission reductions in the text. In response to the second question, the source apportionment modeling captures the atmospheric transformation from NOx emissions into ambient PM2.5 and ozone. Because NOx forms both ambient PM2.5 and ozone, there is no double counting of benefits. We have conservatively limited the NOx emissions to thedefined ozone season for estimating ozone cobenefits, and we use the all-year NOx emissions to estimate PM co-benefits.

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4-68 In its review of the literature, the NAS foun d neurodevelopmental effects to be the most sensitive and best documented endp oints and appropriate for establishing a reference dose (RfD) (NRC, 2000); in particular NAS supported the use of results from neurobehavioral or neuropsychological tests. The NAS report noted th at studies in animals reported sensory effects as well as effects on brain development and memory functions and support the conclusions based on epidemiology studies. The NAS noted that their recommended endpoints for an RfD are associated with the ability of children to learn and to succeed in school. They concluded the following: “The population at highest risk is the children of women who consumed large amounts of fish and seafood during pregnancy. The committee concludes that the risk to that population is likely to be sufficient to result in an increase in the number of children who have to struggle to keep up in school.”

The NAS summarized data on cardiovascular effects available up to 2000. Based on these and other studies, the NRC concluded that “Although the data base is not as extensive for cardiovascular effects as it is for other end poin ts (i.e., neurologic effects), the cardiovascular system appears to be a target for MeHg toxicity in humans and animals.” The NRC also stated
that “additional studies are needed to better charac terize the effect of meth ylmercury exposure on blood pressure and cardiovascular function at various stages of life.”

Additional cardiovascular studies have been published since 2000. EPA did not develop a quantitative dose-response assessment for car diovascular effects associated with MeHg exposures, as there is no consensus among scientists on the dose-response functions for these effects. In addition, there is inconsistency among available studies as to the association between MeHg exposure and various cardiovascular system effects. The pharmacokinetics of some of the exposure measures (such as toenail Hg levels) are not well understood. The studies have not yet received the review and scrutiny of the more well-established neurotoxicity data base.

The Mercury Study noted that MeHg is not a potent mutagen but is capable of causing chromosomal damage in a number of experimental systems. The NAS concluded that evidence that human exposure to MeHg caused genetic damage is inconclusive; they note that some earlier studies showing chromosomal damage in lymphocytes may not have controlled sufficiently for potential confounders. One study of adults living in the Tapajós River region in Brazil (Amorim

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-69 et al., 2000) reported a direct relationship betw een MeHg concentration in hair and DNA damage in lymphocytes, as well as effects on chromosomes. 25 

### Long-term MeHg exposures in this population were believed to occur through consumption of fish, suggesting that genotoxic effects (largely chromosomal aberrations) may result fr om dietary, and chronic MeHg exposures similar to and above those seen in the Faroes and Seychelles populations.

Although exposure to some forms of Hg can result in a decrease in immune activity or an autoimmune response (ATSDR, 1999), evidence for immunotoxic effects of MeHg is limited (NRC, 2000) 26



### . Based on limited human and animal data, MeHg is classified as a “possible” human carcinogen by the International Agency for Research on Cancer (IARC, 1994) 27 

### and in IRIS (U.S. EPA, 2002). 28 

### The existing evidence supporting the possibility of carcinogenic effects in humans from low-dose chronic exposures is te nuous. Multiple human epidemiological studies have found no significant association between Hg exposure and overall cancer incidence, although a few studies have shown an association between Hg exposure and specific types of cancer incidence (e.g., acute leukemia and liver cancer) (NRC, 2000).

There is also some evidence of reproductive and renal toxicity in humans from MeHg exposure. However, overall, human data regarding reproductive, renal, and hematological toxicity from MeHg are very limited and are based on either studies of the two high-dose poisoning episodes in Iraq and Japan or animal data, rather than epidemiological studies of chronic exposures at the levels of interest in this analysis.

25 Amorim, M.I.M., D. Mergler, M.O. Bahia, H. Dubeau, D. Miranda, J. Lebel, R.R. Burbano, and M. Lucotte.

2000. Cytogenetic damage related to low levels of met hyl mercury contamination in the Brazilian Amazon. An. Acad. Bras. Ciênc. 72(4): 497-507.

26 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological Profile for Mercury. U.S.

Department of Health and Human Services, Public Health Service, Atlanta, GA.

27 International Agency for Research on Cancer (IARC). 1994. IARC Monographs on the Evaluation of

Carcinogenic Risks to Humans and their Supplements: Beryllium, Cadmium, Mercury, and Exposures in the Glass Manufacturing Industry. Vol. 58. Jalili, H.A., and A.H. Abbasi. 1961. Poisoning by ethyl mercury toluene sulphonanilide. Br. J. Indust. Med. 18(Oct.):303-308 (as cited in NRC, 2000).

28 U.S. Environmental Protection Agency (EPA). 2002. Integrated Risk Information System (IRIS) on

Methylmercury. National Center for Environmental Assessm ent. Office of Research and Development. Available at http://www.epa.gov/iris/subst/0073.htm

.

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4-70 4.5.1.2 Hydrogen Chloride
Hydrogen chloride (HCl) is a corrosive ga s that can cause irritation of the mucous membranes of the nose, throat, and respiratory tract. Brief exposure to 35 ppm causes throat irritation, and levels of 50 to 100 ppm are barely tolerable for 1 hour. 29 

### The greatest impact is on the upper respiratory tract; exposure to high conc entrations can rapidly lead to swelling and spasm of the throat and suffocation. Most seri ously exposed persons have immediate onset of rapid breathing, blue coloring of the skin, and narrowing of the bronchioles. Exposure to HCl can lead to Reactive Airways Dysfunction Syndrome (R ADS), a chemically, or irritant-induced type of asthma. Children may be more vulnerable to corrosive agents than adults because of the relatively smaller diameter of their airways. Children may also be more vulnerable to gas exposure because of increased minute ventilation per kg and failure to evacuate an area promptly when exposed. Hydrogen chloride has not been classified for carcinogenic effects. 30



### 4.5.2 Additional NO 2 

### Health Co-Benefits
In addition to being a precursor to PM 2.5 

### and ozone, NOx emissions are also associated with a variety of adverse health effects associated with direct exposure. Unfortunately, we were
unable to estimate the health co-benefits associated with reduced NO 2 

### exposure in this analysis. Therefore, this analysis only quantified and monetized the PM 2.5 

### and ozone co-benefits
associated with the reductions in NO 2 

### emissions.

Following a comprehensive review of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment for Ox ides of Nitrogen —Health Criteria (NOx ISA) (U.S. EPA, 2008c) concluded that there is a likely causal relationship between respiratory health effects and short-term exposure to NO 2 

### . The NOx ISA concluded that the evidence “is sufficient to infer a likely causal relationship between short-term NO 2 

### exposure and adverse effects on the respiratory system.” These epidemiologic and experimental studies encompass a number of endpoints including emergency department visi ts and hospitalizations, respiratory symptoms,

29 Agency for Toxic Substances and Disease Registry (A TSDR). Medical Management Guidelines for Hydrogen

Chloride. Atlanta, GA: U.S. Department of Health and Human Services. Available at http://www.atsdr.cdc.gov/mmg/mmg.asp?id=758&tid=147#bookmark02

. 30 U.S. Environmental Protection Agency (U.S. EPA). 1995. “Integrated Risk Information System File of Hydrogen

Chloride.” Washington, DC: Research and Development, National Center for Environmental Assessment. This material is available at http://www.epa.gov/iris/subst/0396.htm

.

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-71 airway hyperresponsiveness, airway inflammation, and lung function. The NOx ISA also concluded that the relationship between short-term NO 2 

### exposure and premature mortality was “suggestive but not sufficient to infer a causal rela tionship,” because it is difficult to attribute the mortality risk effects to NO 2 

### alone. Although the NOx ISA stat ed that studies consistently reported a relationship between NO 2 

### exposure and mortality, the effect was generally smaller than that for other pollutants such as PM.

4.5.3 Additional SO 2 

### Health Co-Benefits
In addition to being a precursor to PM 2.5 

### , SO 2 

### emissions are also associated with a variety of adverse health effects associated with direct exposure. Unfortunately, we were unable to
estimate the health co-benefits associated with reduced SO 2 

### in this analysis because we do not have air quality modeling data available. Therefore, this analysis only quantifies and monetizes
the PM 2.5 

### co-benefits associated with the reductions in SO 2 

### emissions.

Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment for Oxides of Sulfur —Health Criteria (SO 2 

### ISA) concluded that there is a causal relationship between respiratory health effects and short-term exposure to SO 2 

### (U.S. EPA, 2008a). The immediate effect of SO 2 

### on the respiratory system in
humans is bronchoconstriction. Asthmatics are more sensitive to the effects of SO 2 

### likely resulting from preexisting inflammation associat ed with this disease. A clear concentrationresponse relationship has been demonstrated in laboratory studies following exposures to SO 2 

### 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 SO 2 

### ISA identified as a “causal relationship”: asthma exacerbation, respiratory-related emergency department visits, and respiratory-related hospitalizations. The diffe ring evidence and associated strength of the
evidence for these different effects is described in detail in the SO 2 

### ISA. The SO 2 

### ISA also concluded that the relationship between short-term SO 2 

### exposure and premature mortality was “suggestive of a causal relationship” because it is di fficult to attribute the mortality risk effects to
SO 2 

### alone. Although the SO 2 

### ISA stated that studies are generally consistent in reporting a relationship between SO 2 

### exposure and mortality, there was a lack of robustness of the observed

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-72 associations to adjustment for pollutants. We did not quantify these co-benefits due to data
constraints.

4.5.4 Additional NO 2 

### and SO 2 

### Welfare Co-Benefits

As described in the Integrated Science Assessment for Oxides of Nitrogen and Sulfur — Ecological Criteria (NOx ISA) (U.S. EPA, 2008d), SO 2 

### and NOx emissions also contribute to a variety of adverse welfare effects, including acidi c deposition, visibility impairment, and nutrient enrichment. Deposition of nitrogen causes acidification, which can cause a loss of biodiversity of fishes, zooplankton, and macro invertebrates in aquatic ecosystems, as well as a decline in sensitive tree species, such as red spruce (Picea rubens) and sugar maple (Acer saccharum) in terrestrial ecosystems. In the northeastern U.S., the surface waters affected by acidification are a
source of food for some recreational and subsistence fishermen and for other consumers and support several cultural services, including aesth etic and educational services and recreational fishing. Biological effects of acidification in terrestrial ecosystems are generally linked to aluminum toxicity, which can cause reduced root growth, whic h restricts the ability of the plant to take up water and nutrients. These direct effects can, in turn, increase the sensitivity of these plants to stresses, such as droughts, cold temp eratures, insect pests, and disease leading to increased mortality of canopy trees. Terrestrial ac idification affects several important ecological services, including declines in habitat for threat ened and endangered species (cultural), declines in forest aesthetics (cultural), declines in forest productivity (provisioning), and increases in
forest soil erosion and reductions in water rete ntion (cultural and regulating). (U.S. EPA, 2008d)

Deposition of nitrogen is also associated with aquatic and terrestrial nutrient enrichment. In estuarine waters, excess nutrient enrichment can lead to eutrophication. Eutrophication of estuaries can disrupt an important source of food production, particular ly fish and shellfish production, and a variety of cultural ecosystem services, including water-based recreational and
aesthetic services. Terrestrial nutrient enrichment is associated with changes in the types and number of species and biodiversity in terrestrial systems. Excessive nitrogen deposition upsets the balance between native and nonnative plants, changing the ability of an area to support biodiversity. When the composition of species changes, then fire frequency and intensity can also change, as nonnative grasses fuel more fre quent and more intense wildfires. (U.S. EPA, 2008d)

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4-73 4.5.5 Ozone Welfare Co-Benefits
Exposure to ozone has been associated with a wide array of vegetation and ecosystem effects in the published literature (U.S. EPA, 201 3b). Sensitivity to ozone is highly variable across species, with over 65 plan sp ecies identified as “ozone-sensitive”, many of which occur in state and national parks and forests. These effects include those that damage or impair the intended use of the plant or ecosystem. Such effects are considered adverse to the public welfare and can include reduced growth and/or biomass pro duction in sensitive pl ant species, including forest trees, reduced crop yields, visible foliar injury, reduced plant vigor (e.g., increased susceptibility to harsh weather, disease, ins ect pest infestation, and competition), species composition shift, and changes in ecosystems and associated ecosystem services.

4.5.6 Carbon Monoxide Co-Benefits
CO in ambient air is formed primarily by the incomplete combustion of carbon-containing fuels and photochemical reactions in the atmosphere. The amount of CO emitted from these reactions, relative to carbon dioxide (CO 2 

### ), is sensitive to conditions in the combustion zone, such as fuel oxygen content, burn temperature, or mixing time. Upon inhalation, CO diffuses through the respiratory system to the blood, which can cause hypoxia (reduced oxygen availability). Carbon monoxide can elicit a broad range of effects in multiple tissues and organ systems that are dependent upon concentration and duration of exposure. The Integrated Science Assessment for Carbon Monoxide (U.S. EPA, 2010a) concluded that short-term exposure to CO is “likely to have a causal relationship” with cardi ovascular morbidity, particularly in individuals with coronary heart disease. Epidemiologic st udies associate short-term CO exposure with increased risk of emergency department visits and hospital admissions. Coronary heart disease includes those who have angina pectoris (cardiac chest pain), as well as those who have experienced a heart attack. Other subpopulations potentially at risk include individuals with diseases such as chronic obstructive pulmona ry disease (COPD), anemia, or diabetes, and individuals in very early or late life stages, such as older adults or the developing young. The evidence is suggestive of a causal relationship between short-term exposure to CO and respiratory morbidity and mortality. The evidence is also suggestive of a causal relationship for birth outcomes and developmental effects follow ing long-term exposure to CO, and for central nervous system effects linked to short- and long-term exposure to CO.

### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

4-74 4.5.7 Visibility Impairment Co-Benefits
Reducing secondary formation of PM 2.5 

### would improve levels visibility in the U.S. because suspended particles and gases degrade visibility by scattering and absorbing light (U.S. EPA, 2009b). Fine particles with significant light-extin ction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil (Sisler, 1996). Visibility has direct significance to people’s enjoyment of daily activities and their overall sense of wellbeing. Good visibility increases the quality of life where individuals live and work, and where they engage in recreational activities. Particulate sulfate is the dominant source of regional haze in the eastern U.S. and particulate nitrate is an important contributor to light extinction in California and the upper Midwestern U.S., particularly during winter (U.S. EPA, 2009b). Previous analyses (U.S. EPA, 2011a) show that visibility co-benefits can be a significant welfare benefit category. Without air quality modeling, we are unable to estimate visibility related benefits, and we are also unable to determine whether the emission reductions associated with the proposed guidelines would be likely to have a significant im pact on visibility in urban areas or Class I

areas.

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4-75 4.6 References
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4-77 National Research Council. 2010. Advancing the Science of Climate Change . National Academies Press. Washington, DC.

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4-78 U.S. Environmental Protection Agency (U.S. EPA). 1995. Regulatory Impact Analysis for the Petroleum Refinery NESHAP. Revised Draft for Promulgation . Office of Air Quality Planning and Standards, Research Triangle Park, N.C. Available on the Internet at <http://www.regmarkets.org/admin/authorpdfs/page.php?id=705>. U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economic Analyses. EPA 240-R-00-003. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. September. Available at: <http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/cover.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2006. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final) . EPA/600/R-05/004aF-cF. Washington, DC: U.S. EPA. February. Available at: <http://cfpub.epa.gov/ncea/CFM/recordisplay.cfm?deid=149923>. U.S. Environmental Protection Agency (U.S. EPA). 2008a. Integrated Science Assessment for Sulfur Oxides—Health Criteria (Final Report) . National Center for Environmental Assessment, Research Triangle Park, NC. September. Available at: <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=198843>. U.S. Environmental Protection Agency (U.S. EPA). 2008b. Final Ozone NAAQS Regulatory Impact Analysis . EPA-452/R-08-003. Office of Air Qual ity Planning and Standards Health and Environmental Impacts Division, Air Benefit and Cost Group Research Triangle Park, NC. March. Available at: <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=194645>. U.S. Environmental Protection Agency (U.S. EPA). 2008c. Integrated Science Assessment for Oxides of Nitrogen - Health Criteria (Final Report). National Center for Environmental Assessment, Research Triangle Park, NC. July. Available at: <http://www.epa.gov/ttnecas1/regdata/RIAs/6-ozoneriachapter6.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2008d. Integrated Science Assessment for Oxides of Nitrogen and Sulfur–Ecological Criteria National (Final Report ). National Center for Environmental Assessment, Research Tria ngle Park, NC. EPA/600/R-08/139. December. Available at: <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485>. U.S. Environmental Protection Agency (U.S. EPA). 2009a. Assessment of the Impacts of GlobalChange on Regional U.S. Air Quality: A Synthesis of Climate Change Impacts on GroundLevel Ozone. An Interim Report of the U.S. EPA Global Change Research Program. U.S. Environmental Protection Agency, Washingt on, DC, EPA/600/R–07/094. Available at: <http://ofmpub.epa.gov/eims/eimsco mm.getfile?p_download_id=491176>.

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4-79 U.S. Environmental Protection Agency (U.S. EPA). 2009b. Integrated Science Assessment for Particulate Matter (Final Report) . EPA-600-R-08-139F. National Center for Environmental Assessment – RTP Division. December. Available at: <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. U.S. Environmental Protection Agency (U.S. EPA). 2010a. Integrated Science Assessment for Carbon Monoxide. National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-09/019F. January. Available at: <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686>. U.S. Environmental Protection Agency (U.S. EPA). 2010b. Technical Support Document: Summary of Expert Opinions on the Existence of a Threshold in the Concentration-Response Function for PM 2.5 

### -related Mortality. Research Triangle Park, NC. June. Available at: <http://www.epa.gov/ttn/ecas/regda ta/Benefits/thresholdstsd.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2010c. Valuing Mortality Risk Reductions for Environmental Policy: A Wh ite Paper: SAB Review Draft . National Center for Environmental Economics December. Available at: <http://yosemite.epa.gov/ee/epa/eerm.nsf/ vwAN/EE-0563-1.pdf/$file/EE-0563-1.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2010d. Section 3: Re

‐ analysis of the Benefits of Attaining Alternative Ozone Standards to Incorporate Current Methods . Available at: <http://www.epa.gov/ttnecas1/regdata/RIAs/s3 -supplemental_analysis-updated_benefits11- 5.09.pdf >. U.S. Environmental Protection Agency (U.S. EPA). 2010e. Guidelines for Preparing Economic Analyses . EPA 240-R-10-001. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. December. Available at: <http://yosemite.epa.gov/ee/epa/eerm.nsf/v wAN/EE-0568-50.pdf/$file/EE-0568- 50.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2011a. The Benefits and Costs of the Clean Air Act from 1990 to 2020 . Office of Air and Radiation, Washington, DC. March. Available at: <http://www.epa.gov/cleanairactbenefits/feb11/fullreport_rev_a.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2011b. Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards. EPA-452/R-11-011. December. Available at: <http://www.epa.gov/ttn/ecas/regda ta/RIAs/matsriafinal.pdf>.

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4-80 U.S. Environmental Protection Agency (U.S. EPA). 2011c. Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants for Industrial, Commercial, and Institutional Boilers and Process Heaters. February. Available at: <http://www.epa.gov/ttnecas1/regdata/RIAs/boilersriafinal110221_psg.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2011d. Policy Assessment for the Review of the Particulate Matter National Ambient Air Quality Standards . EPA-452/D-11-003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. April. Available at: <http://www.epa .gov/ttn/naaqs/standards/pm/data/20110419pmpafinal.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2012a. Regulatory Impact Analysis for the Final Revisions to the National Ambient Ai r Quality Standards for Particulate Matter . EPA452/R-12-003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. December. Available at: <http://www.epa.gov/pm/2012/finalria.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2012b. Regulatory Impact Analysis: Petroleum Refineries New Source Performance Standards Ja. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. June. Available at: <http://www.epa.gov/ttnecas1/regdata/RIAs/ refineries_nsps_ja_final_ria.pdf>. U.S. Environmental Protection Agency (U.S. EPA). 2013a. Technical Support Document: Estimating the Benefit per ton of Reducing PM 2.5 

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### ***E.O. 12866 Review – Draft – Do Not Cite, Quote or Release During Review***

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