7. Uncertainties Associated With Aggregation of Monetized Benefits S Health benefits estimates are limited to the available effect estimates. Thus, unquantified or unmonetized benefits are not included. 10 12 10.4 Phase One Analysis: Modeled Air Quality Change and Health Effects Resulting from a Portion of Emission Reductions at Boiler and Process Heaters Sources In phase one of the benefit analysis, we are able to link approximately 50 percent of the emission reductions from this regulation to specific locations of boilers/ process heaters. This allows us to evaluate the change in air quality around these sources and the resulting effect on the health of the surrounding population. The analysis performed for the emission reductions evaluated in phase one can be thought of as having three parts, including:

1. Calculation of the impact that our standards will have on the nationwide inventories for PM and SO 2 emissions;

2. Air quality modeling to determine the changes in ambient concentrations of PM that will result from the changes in nationwide inventories of directly emitted PM and precursor pollutants; and 3. A benefits analysis to determine the changes in human health, both in terms of physical effects and monetary value, that result from the changes in ambient concentrations of PM.

Steps 1 and 2 are discussed in previous chapters of this RIA. For step 3, we follow the same general methodology used in the benefits analysis of the HDD rulemaking, as well as the proposed NRD rule and the IAQR. EPA also relies heavily on the advice of its independent Science Advisory Board ( SAB) in determining the health and welfare effects considered in the benefits analysis and in establishing the most scientifically valid measurement and valuation techniques.

Figure 10 1 illustrates the steps necessary to link the emission reductions included in the phase one analysis with economic measures of benefits. The first two steps involve the specification and implementation of the regulation. First, the specific regulatory options for reducing air pollution from industrial boilers/ process heaters are established. In this chapter, we evaluate the benefits of two regulatory options: the MACT floor and an above the floor option. Next, we determine the changes in boiler and process heater control technology that can be used to meet the level of emissions reductions specified by the regulatory options ( see Chapter 2). The changes in pollutant emissions resulting from the required changes in control technology at boilers/ process heaters are then calculated, along with predictions of emissions for other industrial sectors in the baseline. The predicted emissions reductions described in Chapter 3 are then used as inputs to air quality models that predict ambient concentrations of pollutants over time and space. These concentrations depend on climatic conditions and complex chemical interactions. 10 13 Figure 10 1. Steps in Phase One of the Benefits Analysis for the Industrial Boilers/ Process Heaters NESHAP NESHAP Regulatory Options

Apply Control Technology to Affected Sources

Estimate Expected Reductions in SO 2 and PM Emissions

Model Changes in Ambient Concentrations of PM 2.5 and PM 10

Estimate Expected Changes in Human Health Outcomes

Estimate Monetary Value of Changes in Human Health Outcomes

Account for Income Growth and Calculate Total Benefits 17Details of the calculation of the income adjustment factors are provided in the IAQR RIA ( U. S. EPA, 2003b).

10 14 Changes in ambient concentrations will lead to new levels of environmental quality in the U. S., reflected both in human health and in non health welfare effects. For this analysis, however, we do not evaluate and monetize changes in non health welfare effects, such as visibility and agricultural yields. To generate estimated health outcomes, projected changes in ambient PM concentrations were input to a benefits model, known as the Criteria Air Pollutant Modeling System ( CAPMS), a customized GIS based program. CAPMS assigns pollutant concentrations to population grid cells for input into concentration response functions. CAPMS uses census block population data and changes in pollutant concentrations to estimate changes in health outcomes for each grid cell. For purposes of this analysis, we assume a constant proportion of baseline incidence of the various health effects to the future incidence of health effects.

Our analysis also accounts for expected growth in real income over time. Economic theory argues that WTP for most goods ( such as environmental protection) will increase if real incomes increase. The economics literature suggests that the severity of a health effect is a primary determinant of the strength of the relationship between changes in real income and WTP ( Alberini, 1997; Miller, 2000; Viscusi, 1993). As such, we use different factors to adjust the WTP for minor health effects, severe and chronic health effects, and premature mortality. Adjustment factors used to account for projected growth in real income from 1990 to 2005 are 1.03 for minor health effects, 1.09 for severe and chronic health effects, and 1.08 for premature mortality17.

It should be noted that since proposal of the Industrial Boilers and Process Heaters NESHAP, the benefit methodology utilized by EPA has been updated to reflect the current science in air quality modeling and benefits modeling. Due to time and resource constraints, EPA was unable to complete a full reassessment of the benefits analysis from proposal. However, EPA has carefully considered the differences in methodology from proposal. Based on the IAQR benefit analysis document, we determined that the NESHAP's analysis from proposal does not include additional benefit endpoints ( i. e., infant mortality, heart attacks, and asthma exacerbation), which would increase the total benefit estimate from proposal. The IAQR also uses a newer study of premature mortality due to PM, which would increase the benefit estimate from proposal. The VSL estimate for premature mortality has been lowered slightly from $ 6 million to $ 5.5 million in the IAQR, which would decrease the benefit estimate from proposal. Finally, an updated air quality model ( i. e., REMSAD) would also increase our total benefit estimate in this analysis. Although the overall impact on total benefits is not determinable without a full reassessement of benefits, it is unlikely that our comparison of benefits to costs would reveal a substantially different conclusion ( e. g., we still expect benefits to exceed costs by a substantial amount).

Based on the structure of analysis presented above, Section 10.4.1 provides a description of how we quantify and value changes in individual health effects. Then, in Section 10.4.2 we present quantified estimates of the reductions in health effects resulting from phase one of the benefit analysis. 10 15 10.4.1 Quantifying Individual Health Effect Endpoints We use the term " endpoints" to refer to specific effects that can be associated with changes in air quality. To estimate these endpoints, EPA combines changes in ambient air quality levels with epidemiological evidence about population health response to pollution exposure. The most significant monetized benefits of reducing ambient concentrations of PM are attributable to reductions in human health risks. EPA's Criteria Document for PM lists numerous health effects known to be linked to ambient concentrations of the pollutant ( US EPA, 1996a). The previous chapter described some of these effects. This section describes methods used to quantify and monetize changes in the expected number of incidences of various health effects. For further detail on the methodology used to assess human health benefits such as those included in phase one of this analysis, refer to the HDD RIA and TSD, and the IAQR benefit analysis.

The specific PM endpoints that are evaluated in this analysis include:

° Premature mortality ° Bronchitis  chronic and acute ° Hospital admissions  respiratory and cardiovascular ° Emergency room visits for asthma ° Asthma attacks ° Lower and upper respiratory illness ° Minor restricted activity days ° Work loss days As is discussed previously, this analysis relies on concentration response ( C R) functions estimated in published epidemiological studies relating health effects to ambient air quality. The specific studies from which C R functions are drawn are included in Table 10 4. Because we rely on methodology used in prior benefit analyses, a complete discussion of the C R functions used for this analysis and information about each endpoint are contained in the IAQR RIA .

While a broad range of serious health effects have been associated with exposure to elevated PM levels ( described more fully in the EPA's PM Criteria Document ( US EPA, 1996a), we include only a subset of health effects in this quantified benefit analysis. Health effects are excluded from this analysis for four reasons: ( i) the possibility of double counting ( such as hospital admissions for specific respiratory diseases); ( ii) uncertainties in applying effect relationships based on clinical studies to the affected population; ( iii) a lack of an established C R relationship; or ( iv) lack of resources to estimate some endpoints.

Using the C R functions derived from the studies cited in this table, we apply that same C R relationship to all locations in the U. S. Although the C R relationship may in fact vary somewhat from one location to another ( for example, due to differences in population susceptibilities or differences in the composition of PM), location specific C R functions are generally not available. A single function applied everywhere may result in overestimates of incidence changes in some locations and underestimates in other locations, but these locationspecific biases will, to some extent, cancel each other out when the total incidence change is calculated. It is not possible to know the extent or direction of the bias in the total incidence change based on the general application of a single C R function everywhere.

Recently, the Health Effects Institute ( HEI) reported findings by investigators at Johns Hopkins University and others that have raised concerns about aspects of the statistical 10 16 methodology used in a number of recent time series studies of short term exposures to air pollution and health effects ( Greenbaum, 2002a). Some of the concentration response functions used in this benefits analysis were derived from such short term studies. The estimates derived from the long term mortality studies, which account for a major share of the benefits in theanalysis, are not affected. As discussed in HEI materials provided to sponsors and to the Clean Air Scientific Advisory Committee ( Greenbaum, 2002a, 2002b), these investigators found problems in the default " convergence criteria" used in Generalized Additive Models ( GAM) and a separate issue first identified by Canadian investigators about the potential to underestimate standard errors in the same statistical package. 1 These and other investigators have begun to reanalyze the results of several important time series studies with alternative approaches that address these issues and have found a downward revision of some results. For example, the mortality risk estimates for short term exposure to PM 10 from NMMAPS were overestimated ( the C R function based on the NMMAPS results used in this benefits analysis uses the revised NMMAPS results). 2 However, both the relative magnitude and the direction of bias introduced by the convergence issue is case specific. In most cases, the concentration response relationship may be overestimated; in other cases, it may be underestimated. The preliminary renalyses of the mortality and morbidity components of NMMAPS suggest that analyses reporting the lowest relative risks appear to be affected more greatly by this error than studies reporting higher relative risks ( Dominici et al., 2002; Schwartz and Zanobetti, 2002).

Our examination of the original studies used in this analysis finds that the health endpoints that are potentially affected by the GAM issues include: reduced hospital admissions and reduced lower respiratory symptoms; reduced lower respiratory symptoms; and reduced premature mortality due to short term PM 10 exposures and reduced premature mortality due to short term PM 2.5 exposures. While resolution of these issues is likely to take some time, the preliminary results from ongoing reanalyses of some of the studies used in our analyses ( Dominici et al, 2002; Schwartz and Zanobetti, 2002; Schwartz, personal communication 2002) suggest a more modest effect of the S plus error than reported for the NMMAPS PM 10 mortality study. While we wait for further clarification from the scientific community, we have chosen not to remove these results from the Industrial Boilers and Process Heaters NESHAP benefits estimates, nor have we elected to apply any interim adjustment factor based on the preliminary reanalyses. EPA will continue to monitor the progress of this concern, and make appropriate adjustments as further information is made available.

<IP_ADDRESS> Concentration Response Functions for Premature Mortality Both long and short term exposures to ambient levels of air pollution have been associated with increased risk of premature mortality. The size of the mortality risk estimates from these epidemiological studies, the serious nature of the effect itself, and the high monetary value ascribed to prolonging life make mortality risk reduction the most important health endpoint quantified in this analysis. Because of the importance of this endpoint and the considerable uncertainty among economists and policymakers as to the appropriate way to value reductions in mortality risks, this section discusses some of the issues surrounding the estimation of premature mortality. For additional discussion on mortality and issues related to estimating risk for other health effects categories, we refer readers to the discussions presented in the IAQR.

Epidemiological analyses have consistently linked air pollution, especially PM, with excess mortality. Although a number of uncertainties remain to be addressed by continued research ( NRC, 1998), a substantial body of published scientific literature documents the correlation between elevated PM concentrations and increased mortality rates. Community 10 17 epidemiological studies that have used both short term and long term exposures and response have been used to estimate PM/ mortality relationships. Short term studies use a time series approach to relate short term ( often day to day) changes in PM concentrations and changes in daily mortality rates up to several days after a period of elevated PM concentrations. Long term studies examine the potential relationship between community level PM exposures over multiple years and community level annual mortality rates. 10 18 Table 10 4. PM related Health Outcomes and Studies Included in the Analysis Health Outcome Pollutant Applied Population Source of Effect Estimate Source of Baseline Incidence Premature Mortality All cause premature mortality from long term exposure PM2.5 > 29 years Krewski et al., 2000 U. S. Centers for Disease Control, 1999 Chronic Illness Chronic Bronchitis ( pooled estimate) PM2.5 PM10 > 26 years > 29 years Abbey et al., 1995 Schwartz et al., 1993 Abbey et al., 1993 Abbey et al., 1993 Adams and Marano, 1995 Hospital Admissions COPD PM10 > 64 years Samet et al., 2000 Graves and Gillum, 1997 Pneumonia PM10 > 64 years Samet et al., 2000 Graves and Gillum, 1997 Asthma PM2.5 < 65 years Sheppard et al., 1999 Graves and Gillum, 1997 Total Cardiovascular PM10 > 64 years Samet et al., 2000 Graves and Gillum, 1997 Asthma Related ER Visits PM10 All ages Schwartz et al., 1993 Smith et al., 1997 Graves and Gillum, 1997 Other Effects Asthma Attacks PM10 Asthmatics, all ages Whittemore and Korn, 1980 Krupnick, 1988 Adams and Marano, 1995 Acute Bronchitis PM2.5 Children, 8 12 years Dockery et al., 1996 Adams and Marano, 1995 Upper Respiratory Symptoms PM10 Asthmatic children, 9 11 Pope et al., 1991 Pope et al., 1991 Lower Respiratory Symptoms PM2.5 Children, 7 14 years Schwartz et al., 1994 Schwartz et al., 1994 Work Loss Days PM2.5 Adults, 18 65 years Ostro, 1987 Adams and Marano, 1995 Minor Restricted Activity Days ( minus asthma attacks) PM2.5 Adults, 18 65 years Ostro and Rothschild., 1989 Ostro and Rothschild, 1989 Researchers have found statistically significant associations between PM and premature mortality using both types of studies. In general, the risk estimates based on the long term exposure studies are larger than those derived from short term studies. Cohort analyses are better able to capture the full public health impact of exposure to air pollution over time ( Kunzli, 2001; NRC, 2002). This section discusses some of the issues surrounding the estimation of premature mortality. 18The EPA recognizes that the ACS cohort also is not completely representative of the demographic mix in the general population. The ACS cohort is almost entirely white, and has higher income and education levels relative to the general population. The EPA's approach to this problem is to match populations based on the potential for demographic characteristics to modify the effect of air pollution on mortality risk. Thus, for the various ACS based models, we are careful to apply the effect estimate only to ages matching those in the original studies, because age has a potentially large modifying impact on the effect estimate, especially when younger individuals are excluded from the study population. For the Lipfert analysis, the applied population should be limited to that matching the sample used in the analysis. This sample was all male, veterans, and diagnosed hypertensive. There are also a number of differences between the composition of the sample and the general population, including a higher percentage of African Americans ( 35 percent), and a much higher percentage of smokers ( 81 percent former smokers, 57 percent current smokers) than the general population ( 12 percent African American, 24 percent current smokers). These composition differences cannot be controlled for, but should be recognized as adding to the potential extrapolation bias. The EPA recognizes the difficulty in controlling for composition of income and education levels. However, in or out criterion such as age, veteran status, hypertension, race and sex are all controllable by applying filters to the population data. The EPA has traditionally only controlled for age, because the ACS study used only age as a screen.

10 19 Over a dozen studies have found significant associations between various measures of long term exposure to PM and elevated rates of annual mortality, beginning with Lave and Seskin ( 1977). Most of the published studies found positive ( but not always statistically significant) associations with available PM indices such as total suspended particles ( TSP). Particles of different fine particles components ( i. e., sulfates), and fine particles, as well as exploration of alternative model specifications sometimes found inconsistencies ( e. g., Lipfert, [ 1989]). These early " cross sectional" studies ( e. g., Lave and Seskin [ 1977]; Ozkaynak and Thurston [ 1987]) were criticized for a number of methodological limitations, particularly for inadequate control at the individual level for variables that are potentially important in causing mortality, such as wealth, smoking, and diet. More recently, several long term studies have been published that use improved approaches and appear to be consistent with the earlier body of literature. These new " prospective cohort" studies reflect a significant improvement over the earlier work because they include individual level information with respect to health status and residence. The most extensive study and analyses has been based on data from two prospective cohort groups, often referred to as the Harvard " Six City Study" ( Dockery et al., 1993) and the " American Cancer Society or ACS study" ( Pope et al., 1995); these studies have found consistent relationships between fine particle indicators and premature mortality across multiple locations in the United States. A third major data set comes from the California based 7th Day Adventist Study ( e. g., Abbey et al, 1999), which reported associations between long term PM exposure and mortality in men. Results from this cohort, however, have been inconsistent and the air quality results are not geographically representative of most of the United States. More recently, a cohort of adult male veterans diagnosed with hypertension has been examined ( Lipfert et al., 2000). The characteristics of this group differ from the cohorts in the ACS, Six Cities, and 7th Day Adventist studies with respect to income, race, health status, and smoking status. Unlike previous long term analyses, this study found some associations between mortality and ozone but found inconsistent results for PM indicators. Because of the selective nature of the population in the veteran's cohort, which may have resulted in estimates of relative risk that are biased relative to a relative risk for the general population, we have chosen not to include any effect estimates from the Lipfert et al. ( 2000) study in our benefits assessment. 18 Given their consistent results and broad geographic coverage, the Six City and ACS data have been particularly important in benefits analyses. The credibility of these two studies is 10 20 further enhanced by the fact that they were subject to extensive reexamination and reanalysis by an independent team of scientific experts commissioned by HEI ( Krewski et al., 2000). The final results of the reanalysis were then independently peer reviewed by a Special Panel of the HEI Health Review Committee. The results of these reanalyses confirmed and expanded those of the original investigators. This intensive independent reanalysis effort was occasioned both by the importance of the original findings as well as concerns that the underlying individual health effects information has never been made publicly available.

The HEI re examination lends credibility to the original studies and highlights sensitivities concerning the relative impact of various pollutants, the potential role of education in mediating the association between pollution and mortality, and the influence of spatial correlation modeling. Further confirmation and extension of the overall findings using more recent air quality and a longer follow up period for the ACS cohort was recently published in the Journal of the American Medical Association ( Pope et al., 2002).

In developing and improving the methods for estimating and valuing the potential reductions in mortality risk over the years, the EPA has consulted with the SAB HES. That panel recommended use of long term prospective cohort studies in estimating mortality risk reduction ( EPA SAB COUNCIL ADV 99 005, 1999). This recommendation has been confirmed by a recent report from the National Research Council, which stated that " it is essential to use the cohort studies in benefits analysis to capture all important effects from air pollution exposure" ( NAS, 2002, p. 108). More specifically, the SAB recommended emphasis on the ACS study because it includes a much larger sample size and longer exposure interval and covers more locations ( e. g., 50 cities compared to the Six Cities Study) than other studies of its kind. As explained in the regulatory impact analysis for the Heavy Duty Engine/ Diesel Fuel rule ( EPA, 2000a), more recent EPA benefits analyses have relied on an improved specification of the ACS cohort data that was developed in the HEI reanalysis ( Krewski et al., 2000). The latest reanalysis of the ACS cohort data ( Pope et al., 2002), provides additional refinements to the analysis of PMrelated mortality by ( a) extending the follow up period for the ACS study subjects to 16 years, which triples the size of the mortality data set; ( b) substantially increasing exposure data, including consideration for cohort exposure to PM2.5 following implementation of PM2.5 standard in 1999; ( c) controlling for a variety of personal risk factors including occupational exposure and diet; and ( d) using advanced statistical methods to evaluate specific issues that can adversely affect risk estimates including the possibility of spatial autocorrelation of survival times in communities located near each other. Because of these refinements, the SAB HES recommends using the Pope et al. ( 2002) study as the basis for the primary mortality estimate for adults and suggests that alternate estimates of mortality generated using other cohort and time series studies could be included as part of the sensitivity analysis ( SAB HES, 2003). However, as is discussed above EPA did not reassess the benefit analysis presented at proposal of this rule to account for the new data of the Pope et al. ( 2002) study.

This analysis also accounts for a lag between reductions in PM 2.5 concentrations and reductions in mortality incidence. It is currently unknown whether there is a time lag ( a delay between changes in PM exposures and changes in mortality rates) in the long term PM2.5/ premature mortality relationship. The existence of such a lag is important for the valuation of premature mortality incidences because economic theory suggests that benefits occurring in the future should be discounted. Although there is no specific scientific evidence of the existence or structure of a PM effects lag, current scientific literature on adverse health effects, such as those associated with PM ( e. g., smoking related disease) and the difference in the effect size between chronic exposure studies and daily mortality studies suggest that all incidences of premature mortality reduction associated with a given incremental change in PM exposure probably would not occur in the same year as the exposure reduction. This same smoking related 19http:// www. biostat. jhsph. edu/ biostat/ research/ update. main. htm 20Both the single day and distributed lag models are likely to be affected to the same degree by the S Plus convergence issue. As such, the ratio of the coefficients from the models should not be affected as much by any changes in the coefficient 10 21 literature implies that lags of up to a few years are plausible. Adopting the lag structure endorsed by the SAB ( EPA SAB COUNCIL ADV 00 001, 1999), we assume a five year lag structure, with 25 percent of premature deaths occurring in the first year ( in 2005), another 25 percent in the second year, and 16.7 percent in each of the remaining three years. The mortality incidences across the 5 year period is then discounted back to our year of analysis, 2005.

For reductions in direct emissions of PM 10, we use a different C R function, based on the studies of mortality and shorter term exposures to PM. Long term studies of the relationship between chronic exposure and mortality have not found significant associations with coarse particles or total PM 10. As discussed earlier in this chapter, concerns have recently been raised about aspects of the statistical methodology used in a number of recent time series studies of short term exposures to air pollution and health effects. Due to the " S Plus" issue identified by the Health Effects Institute, we use as the basis for the our primary estimate the revised relative risk from the NMMAPS study, reported on the website of the Johns Hopkins School of Public Health19. Similar to the PM 2.5 lag adjustment discussed above, we also include an adjustment for PM 10 to account for recent evidence that daily mortality is associated with particle levels from a number of previous days. We use the overall pooled NMMAPS estimate of a 0.224 percent increase in mortality for a 10 µ g/ m3 increase in PM 10 as the starting point in developing our C R function. In a recent analysis, Schwartz ( 2000) found that elevated levels of PM 10 on a given day can elevate mortality on a number of following days. This type of multi day model is often referred to as a " distributed lag" model because it assumes that mortality following a PM event will be distributed over a number of days following or " lagging" the PM event5. Because the NMMAPS study reflects much broader geographic coverage ( 90 cities) than the Schwartz study ( 10 cities), and the Schwartz study has not been reanalyzed to account for the " S Plus" issue, we choose to apply an adjustment based on the Schwartz study to the NMMAPS study to reflect the effect of a distributed lag model.

The distributed lag adjustment factor is constructed as the ratio of the estimated coefficient from the unconstrained distributed lag model to the estimated coefficient from the single lag model reported in Schwartz ( 2000) 20. The unconstrained distributed lag model coefficient estimate is 0.0012818 and the single lag model coefficient estimate is 0.0006479. The ratio of these estimates is 1.9784. This adjustment factor is then multiplied by the revised estimated coefficients from the NMMAPS study. The NMMAPS coefficient corresponding to the 0.224 percent increase in mortality risk is 0.000224. The adjusted NMMAPS coefficent is then 0.000224* 1.9784 = 0.000444.

10.4.2 Valuing Individual Health Effect Endpoints The appropriate economic value of a change in a health effect depends on whether the health effect is viewed ex ante ( before the effect has occurred) or ex post ( after the effect has occurred). Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health affects by a fairly small amount for a large population. The appropriate economic measure is therefore ex ante WTP for changes in risk. However, epidemiological studies generally provide estimates of the relative risks of a particular health effect avoided due to a reduction in air 10 22 pollution. A convenient way to use this data in a consistent framework is to convert probabilities to units of avoided statistical incidences. This measure is calculated by dividing individual WTP for a risk reduction by the related observed change in risk. For example, suppose a measure is able to reduce the risk of premature mortality from 2 in 10,000 to 1 in 10,000 ( a reduction of 1 in 10,000). If individual WTP for this risk reduction is $ 100, then the WTP for an avoided statistical premature mortality amounts to $ 1 million ($ 100/ 0.0001 change in risk). Using this approach, the size of the affected population is automatically taken into account by the number of incidences predicted by epidemiological studies applied to the relevant population. The same type of calculation can produce values for statistical incidences of other health endpoints.

For some health effects, such as hospital admissions, WTP estimates are generally not available. In these cases, we use the cost of treating or mitigating the effect as a primary estimate. For example, for the valuation of hospital admissions we use the avoided medical costs as an estimate of the value of avoiding the health effects causing the admission. These costs of illness ( COI) estimates generally understate the true value of reductions in risk of a health effect. They tend to reflect the direct expenditures related to treatment but not the value of avoided pain and suffering from the health effect. In the NRD rule RIA and TSD, and the IAQR, we describe how the changes in health effects should be valued and indicate the value functions selected to provide monetized estimates of the value of changes in health effects. Table 10 5 below summarizes the value estimates per health effect that we used in this analysis. Note that the unit values for hospital admissions are the weighted averages of the ICD 9 code specific values for the group of ICD 9 codes included in the hospital admission categories.

Table 10 5. Unit Values Used for Economic Valuation of Health Endpoints Health or Welfare Endpoint Estimated Value Per Incidence ( 1999$) Central Estimate Derivation of Estimates Premature Mortality ( longterm exposure) ) $ 6 million per statistical life Value is the mean of value of statistical life estimates from 26 studies ( 5 contingent valuation and 21 labor market studies) reviewed for the Section 812 Costs and Benefits of the Clean Air Act, 1990 2010 ( US EPA, 1999).

Chronic Bronchitis $ 331,000 Value is the mean of a generated distribution of WTP to avoid a case of pollution related CB. WTP to avoid a case of pollution related CB is derived by adjusting WTP ( as described in Viscusi et al., 1991) to avoid a severe case of CB for the difference in severity and taking into account the elasticity of WTP with respect to severity of CB.

Hospital Admissions Chronic Obstructive Pulmonary Disease ( COPD) ( ICD codes 490 492, 494 496) $ 12,378 The COI estimates are based on ICD 9 code level information ( e. g., average hospital care costs, average length of hospital stay, and weighted share of total COPD category illnesses) reported in Elixhauser ( 1993).

Pneumonia ( ICD codes 480 487) $ 14,693 The COI estimates are based on ICD 9 code level information ( e. g., average hospital care costs, average length of hospital stay, and weighted share of total pneumonia category illnesses) reported in Elixhauser ( 1993). Table 10 5. Unit Values Used for Economic Valuation of Health Endpoints Health or Welfare Endpoint Estimated Value Per Incidence ( 1999$) Central Estimate Derivation of Estimates 10 23 Asthma admissions $ 6,634 The COI estimates are based on ICD 9 code level information ( e. g., average hospital care costs, average length of hospital stay, and weighted share of total asthma category illnesses) reported in Elixhauser ( 1993).

All Cardiovascular ( ICD codes 390 429) $ 18,387 The COI estimates are based on ICD 9 code level information ( e. g., average hospital care costs, average length of hospital stay, and weighted share of total cardiovascular illnesses) reported in Elixhauser ( 1993).

Emergency room visits for asthma $ 299 COI estimate based on data reported by Smith, et al. ( 1997). Table 10 5. Unit Values Used for Economic Valuation of Health Endpoints Health or Welfare Endpoint Estimated Value Per Incidence ( 1999$) Central Estimate Derivation of Estimates 10 24 Respiratory Ailments Not Requiring Hospitalization Upper Respiratory Symptoms ( URS) $ 24 Combinations of the 3 symptoms for which WTP estimates are available that closely match those listed by Pope, et al. result in 7 different " symptom clusters," each describing a " type" of URS. A dollar value was derived for each type of URS, using mid range estimates of WTP ( IEc, 1994) to avoid each symptom in the cluster and assuming additivity of WTPs. The dollar value for URS is the average of the dollar values for the 7 different types of URS.

Lower Respiratory Symptoms ( LRS) $ 15 Combinations of the 4 symptoms for which WTP estimates are available that closely match those listed by Schwartz, et al. result in 11 different " symptom clusters," each describing a " type" of LRS. A dollar value was derived for each type of LRS, using mid range estimates of WTP ( IEc, 1994) to avoid each symptom in the cluster and assuming additivity of WTPs. The dollar value for LRS is the average of the dollar values for the 11 different types of LRS.

Acute Bronchitis $ 57 Average of low and high values recommended for use in Section 812 analysis ( Neumann, et al. 1994)

Restricted Activity and Work Loss Days Work Loss Days ( WLDs) Variable Regionally adjusted median weekly wage for 1990 divided by 5 ( adjusted to 1999$) ( US Bureau of the Census, 1992).

Minor Restricted Activity Days ( MRADs) $ 48 Median WTP estimate to avoid one MRAD from Tolley, et al. ( 1986) . 21The choice of a discount rate, and its associated conceptual basis, is a topic of ongoing discussion within the federal government. The EPA adopted a 3 percent discount rate for its primary estimate in this case to reflect reliance on a " social rate of time preference" discounting concept. We have also calculated benefits and costs using a 7 percent rate consistent with an " opportunity cost of capital" concept to reflect the time value of resources directed to meet regulatory requirements. In this case, the benefit and cost estimates were not significantly affected by the choice of discount rate. Further discussion of this topic appears in the EPA's Guidelines for Preparing Economic Analyses ( in press).

10 25 Adjustments for Growth in Real Income Our analysis also accounts for expected growth in real income over time. Economic theory argues that WTP for most goods ( such as environmental protection) will increase if real incomes increase. The economics literature suggests that the severity of a health effect is a primary determinant of the strength of the relationship between changes in real income and WTP ( Alberini, 1997; Miller, 2000; Viscusi, 1993). As such, we use different factors to adjust the WTP for minor health effects, severe and chronic health effects, and premature mortality. Adjustment factors used to account for projected growth in real income from 1990 to 2005 are 1.03 for minor health effects, 1.09 for severe and chronic health effects, and 1.08 for premature mortality.

<IP_ADDRESS> Valuation of Reductions in Premature Mortality Risk We estimate the monetary benefit of reducing premature mortality risk using the " value of statistical lives saved" ( VSL) approach, which is a summary measure for the value of small changes in mortality risk experienced by a large number of people. The VSL approach applies information from several published value of life studies to determine a reasonable benefit of preventing premature mortality. The mean value of avoiding one statistical death is estimated to be $ 6 million in 1999 dollars. This represents an intermediate value from a range of estimates that appear in the economics literature, and it is a value the EPA has used in rulemaking support analyses and in the Section 812 Reports to Congress. This estimate is the mean of a distribution fitted to the estimates from 26 value of life studies identified in the Section 812 reports as " applicable to policy analysis." The approach and set of selected studies mirrors that of Viscusi ( 1992) ( with the addition of two studies), and uses the same criteria as Viscusi in his review of value of life studies. The $ 6 million estimate is consistent with Viscusi's conclusion ( updated to 1999$) that " most of the reasonable estimates of the value of life are clustered in the $ 3.7 to $ 8.6 million range." Five of the 26 studies are contingent valuation ( CV) studies, which directly solicit WTP information from subjects; the rest are wage risk studies, which base WTP estimates on estimates of the additional compensation demanded in the labor market for riskier jobs, controlling for other job and employee characteristics such as education and experience.

As indicated in the previous section on quantification of premature mortality benefits, we assume for this analysis that some of the incidences of premature mortality related to PM exposures occur in a distributed fashion over the five years following exposure. To take this into account in the valuation of reductions in premature mortality, we apply an annual three percent discount rate to the value of premature mortality occurring in future years21.

The economics literature concerning the appropriate method for valuing reductions in premature mortality risk is still developing. The adoption of a value for the projected reduction in the risk of premature mortality is the subject of continuing discussion within the economic and public policy analysis community. Regardless of the theoretical economic considerations, the EPA prefers not to draw distinctions in the monetary value assigned to the lives saved even if they differ in age, health status, socioeconomic status, gender, or other characteristic of the adult population. 10 26 Following the advice of the EEAC of the SAB, the EPA currently uses the VSL approach in calculating the primary estimate of mortality benefits, because we believe this calculation provides the most reasonable single estimate of an individual's willingness to trade off money for reductions in mortality risk ( EPA SAB EEAC 00 013). Although there are several differences between the labor market studies we use to derive a VSL estimate and the particulate matter air pollution context addressed here, those differences in the affected populations and the nature of the risks imply both upward and downward adjustments. In the absence of a comprehensive and balanced set of adjustment factors, the EPA believes it is reasonable to continue to use the $ 6 million value while acknowledging the significant limitations and uncertainties in the available literature.

Some economists emphasize that the value of a statistical life is not a single number relevant for all situations. Indeed, the VSL estimate of $ 6 million ( 1999 dollars) is itself the central tendency of a number of estimates of the VSL for some rather narrowly defined populations. When there are significant differences between the population affected by a particular health risk and the populations used in the labor market studies, as is the case here, some economists prefer to adjust the VSL estimate to reflect those differences.

There is general agreement that the value to an individual of a reduction in mortality risk can vary based on several factors, including the age of the individual, the type of risk, the level of control the individual has over the risk, the individual's attitudes towards risk, and the health status of the individual. While the empirical basis for adjusting the $ 6 million VSL for many of these factors does not yet exist, a thorough discussion of these factors is contained in the benefits TSD for the nonroad diesel rulemaking ( Abt Associates, 2003). The EPA recognizes the need for investigation by the scientific community to develop additional empirical support for adjustments to VSL for the factors mentioned above.

The SAB EEAC advised in their recent report that the EPA " continue to use a wage riskbased VSL as its primary estimate, including appropriate sensitivity analyses to reflect the uncertainty of these estimates," and that " the only risk characteristic for which adjustments to the VSL can be made is the timing of the risk"( EPA SAB EEAC 00 013). In developing our primary estimate of the benefits of premature mortality reductions, we have followed this advice and discounted over the lag period between exposure and premature mortality.

Uncertainties Specific to Premature Mortality Valuation. The economic benefits associated with premature mortality are the largest category of monetized benefits of the NESHAP. In addition, in prior analyses, the EPA has identified valuation of mortality benefits as the largest contributor to the range of uncertainty in monetized benefits ( see EPA [ 1999]). Because of the uncertainty in estimates of the value of premature mortality avoidance, it is important to adequately characterize and understand the various types of economic approaches available for mortality valuation. Such an assessment also requires an understanding of how alternative valuation approaches reflect that some individuals may be more susceptible to air pollution induced mortality or reflect differences in the nature of the risk presented by air pollution relative to the risks studied in the relevant economics literature.

The health science literature on air pollution indicates that several human characteristics affect the degree to which mortality risk affects an individual. For example, some age groups appear to be more susceptible to air pollution than others ( e. g., the elderly and children). Health status prior to exposure also affects susceptibility. An ideal benefits estimate of mortality risk reduction would reflect these human characteristics, in addition to an individual's WTP to improve one's own chances of survival plus WTP to improve other individuals' survival rates. The ideal measure would also take into account the specific nature of the risk reduction 10 27 commodity that is provided to individuals, as well as the context in which risk is reduced. To measure this value, it is important to assess how reductions in air pollution reduce the risk of dying from the time that reductions take effect onward, and how individuals value these changes. Each individual's survival curve, or the probability of surviving beyond a given age, should shift as a result of an environmental quality improvement. For example, changing the current probability of survival for an individual also shifts future probabilities of that individual's survival. This probability shift will differ across individuals because survival curves depend on such characteristics as age, health state, and the current age to which the individual is likely to survive.

Although a survival curve approach provides a theoretically preferred method for valuing the benefits of reduced risk of premature mortality associated with reducing air pollution, the approach requires a great deal of data to implement. The economic valuation literature does not yet include good estimates of the value of this risk reduction commodity. As a result, in this study we value avoided premature mortality risk using the VSL approach.

Other uncertainties specific to premature mortality valuation include the following:

Across study variation: There is considerable uncertainty as to whether the available literature on VSL provides adequate estimates of the VSL saved by air pollution reduction. Although there is considerable variation in the analytical designs and data used in the existing literature, the majority of the studies involve the value of risks to a middle aged working population. Most of the studies examine differences in wages of risky occupations, using a wage hedonic approach. Certain characteristics of both the population affected and the mortality risk facing that population are believed to affect the average WTP to reduce the risk. The appropriateness of a distribution of WTP based on the current VSL literature for valuing the mortality related benefits of reductions in air pollution concentrations therefore depends not only on the quality of the studies ( i. e., how well they measure what they are trying to measure), but also on the extent to which the risks being valued are similar and the extent to which the subjects in the studies are similar to the population affected by changes in pollution concentrations.

Level of risk reduction: The transferability of estimates of the VSL from the wagerisk studies to the context of the Interstate Air Quality Rulemaking analysis rests on the assumption that, within a reasonable range, WTP for reductions in mortality risk is linear in risk reduction. For example, suppose a study estimates that the average WTP for a reduction in mortality risk of 1/ 100,000 is $ 50, but that the actual mortality risk reduction resulting from a given pollutant reduction is 1/ 10,000. If WTP for reductions in mortality risk is linear in risk reduction, then a WTP of $ 50 for a reduction of 1/ 100,000 implies a WTP of $ 500 for a risk reduction of 1/ 10,000 ( which is 10 times the risk reduction valued in the study). Under the assumption of linearity, the estimate of the VSL does not depend on the particular amount of risk reduction being valued. This assumption has been shown to be reasonable provided the change in the risk being valued is within the range of risks evaluated in the underlying studies ( Rowlatt et al., 1998).

Voluntariness of risks evaluated: Although job related mortality risks may differ in several ways from air pollution related mortality risks, the most important difference may be that job related risks are incurred voluntarily, or generally assumed to be, whereas air pollution related risks are incurred involuntarily. Some evidence suggests that people will pay more to reduce involuntarily incurred risks than risks incurred voluntarily. If this is the case, WTP estimates based on wage risk studies may 10 28 understate WTP to reduce involuntarily incurred air pollution related mortality risks.

Sudden versus protracted death: A final important difference related to the nature of the risk may be that some workplace mortality risks tend to involve sudden, catastrophic events, whereas air pollution related risks tend to involve longer periods of disease and suffering prior to death. Some evidence suggests that WTP to avoid a risk of a protracted death involving prolonged suffering and loss of dignity and personal control is greater than the WTP to avoid a risk ( of identical magnitude) of sudden death. To the extent that the mortality risks addressed in this assessment are associated with longer periods of illness or greater pain and suffering than are the risks addressed in the valuation literature, the WTP measurements employed in the present analysis would reflect a downward bias.

Self selection and skill in avoiding risk. Recent research ( Shogren et al., 2002) suggests that VSL estimates based on hedonic wage studies may overstate the average value of a risk reduction. This is based on the fact that the risk wage tradeoff revealed in hedonic studies reflects the preferences of the marginal worker ( i. e., that worker who demands the highest compensation for his risk reduction). This worker must have either higher risk, lower risk tolerance, or both. However, the risk estimate used in hedonic studies is generally based on average risk, so the VSL may be upwardly biased because the wage differential and risk measures do not match.

<IP_ADDRESS> Valuation of Reductions in Chronic Bronchitis The best available estimate of WTP to avoid a case of chronic bronchitis ( CB) comes from Viscusi, et al. ( 1991). The Viscusi, et al. study, however, describes a severe case of CB to the survey respondents. We therefore employ an estimate of WTP to avoid a pollution related case of CB, based on adjusting the Viscusi, et al. ( 1991) estimate of the WTP to avoid a severe case. This is done to account for the likelihood that an average case of pollution related CB is not as severe. The adjustment is made by applying the elasticity of WTP with respect to severity reported in the Krupnick and Cropper ( 1992) study. Details of this adjustment procedure can be found in the IAQR and its supporting documentation, and in the most recent Section 812 study ( EPA 1999).

We use the mean of a distribution of WTP estimates as the central tendency estimate of WTP to avoid a pollution related case of CB in this analysis. The distribution incorporates uncertainty from three sources: ( 1) the WTP to avoid a case of severe CB, as described by Viscusi, et al.; ( 2) the severity level of an average pollution related case of CB ( relative to that of the case described by Viscusi, et al.); and ( 3) the elasticity of WTP with respect to severity of the illness. Based on assumptions about the distributions of each of these three uncertain components, we derive a distribution of WTP to avoid a pollution related case of CB by statistical uncertainty analysis techniques. The expected value ( i. e., mean) of this distribution, which is about $ 331,000 ( 1999$), is taken as the central tendency estimate of WTP to avoid a PM related case of CB.

10.4.3 Results of Phase One Analysis: Benefits Resulting from a Portion of Emission Reductions at a Subset of Boiler and Process Heater Sources 10 29 Applying the C R and valuation functions described above to the estimated changes in PM from phase one of our analysis yields estimates of the number of avoided incidences ( i. e. premature mortalities, cases, admissions, etc.) and the associated monetary values for those avoided incidences. In Table 10 6, we provide the results for the MACT floor option resulting from the phase one analysis. Tables 10 7 present the results for the above the MACT floor option resulting from the phase one analysis. To obtain a total benefit estimate, we aggregate dollar benefits associated with each of the health effects examined, such as hospital admissions, assuming that none of the included health and welfare effects overlap. All of the monetary benefits are in constant 1999 dollars.

As we have discussed, not all known PM related health and welfare effects could be quantified or monetized. These unmonetized benefits are indicated in Tables 10 6 and 10 7 by place holders, labeled B 1 and B 2. In addition, unmonetized benefits associated with HAP reductions are indicated by the placeholder B 3. Unquantified reduce incidences of physical effects are indicated by U 1 and U 2. The estimate of total monetized health benefits is thus equal to the subset of monetized PM related health benefits plus B H, the sum of the unmonetized health benefits. 10 30 Table 10 6. Phase One Analysis: Estimate of Annual Benefits Associated with Approximately 50% of the Emission Reductions from the Industrial Boilers/ Process Heaters NESHAP ( MACT Floor Regulatory Option in 2005) Using Air Quality Modeling & the CAPMS Benefit ModelA, B Endpoint Avoided IncidenceC ( cases/ year) Monetary BenefitsD ( millions 1999$, adjusted for growth in real income)

Premature mortalityE, F ( long term exposure, adults 30 and over)  Using a 3% discount rate 1,170 $ 7,325  Using a 7% discount rate 1,170 $ 6,880 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,340 $ 845 Hospital Admissions   Pneumonia ( adults, over 64) 500 $ 5 Hospital Admissions   COPD ( adults, 64 and over) 420 $ 5 Hospital Admissions   Asthma ( 65 and younger) 120 $ 1 Hospital Admissions   Cardiovascular ( adults, over 64) 1,230 $ 25 Emergency Room Visits for Asthma ( 65 and younger) 930 <$ 1 Asthma Attacks ( asthmatics, all ages) 79,020 B1 Acute bronchitis ( children, 8 12) 2,430 <$ 1 Lower respiratory symptoms ( children, 7 14) 26,470 <$ 1 Upper respiratory symptoms ( asthmatic children, 9 11) 89,480 $ 5 Work loss days ( adults, 18 65) 205,400 $ 20 Minor restricted activity days ( adults, age 18 65) 1,011,200 $ 50 Other PM related health effectsG U1 B2 HAP health effectsG U2 B3 Total Monetized Health Related BenefitsF  Using a 3% discount rate   $ 8,280+ BH  Using a 7% discount rate   $ 7,835+ BH AThe results presented in this table are based on those SO 2 and PM emission reductions identified for specific sources included in the Inventory Database. This includes approximately 50% of all emission reductions estimated by the rule. The location of all other emission reductions ( i. e. noninventory reductions) cannot be determined specifically and hence cannot be modeled in an air quality model. See Section 10.5 and Appendix D for benefit estimation of non inventory emission reductions. B The results presented in this table reflect the outcome of the combination of PM and SO 2 model runs. See Appendix D for a presentation of results for each pollutant independently. C Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. E Note that the estimated value for PM related premature mortality assumes the 5 year distributed lag structure described in detail in the Regulatory Impact Analysis of Heavy Duty Engine/ Diesel Fuel rule. F Monetized benefits are presented using two different discount rates. Results calculated using 3 percent discount rate are recommended by EPA's Guidelines for Preparing Economic Analyses ( U. S. EPA, 2000a). Results calculated using 7 percent discount rate are recommended by OMB Circular A 94 ( OMB, 1992). G A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 17. 10 31 Thus, the estimate of total monetized benefits for phase one of the Industrial Boilers/ Process Heaters NESHAP benefit analysis associated with the MACT floor is approximately $ 8 billion + B H ( using either a 3% or 7% discount rate). The benefits of phase one in combination with the phase two estimate of benefits will serve as the basis for our estimate of the total benefits of the regulation. For the Above the MACT floor option of this NESHAP, Table 10 7 indicates that the estimate of total monetized benefits for phase one of the analysis is approximately $ 10 billion + B H using a 3% discount rate ( or approximately $ 9.5 billion using a 7% discount rate). 10 32 Table 10 7. Phase One Analysis: Estimate of Annual Benefits Associated with Approximately 50% of the Emission Reductions from the Industrial Boilers/ Process Heaters NESHAP ( Above the MACT Floor Regulatory Option in 2005) Using Air Quality Modeling & the CAPMS Benefit ModelA, B Endpoint Avoided IncidenceC ( cases/ year) Monetary BenefitsD ( millions 1999$, adjusted for growth in real income)

Premature mortalityE, F ( long term exposure, adults, 30 and over)  Using a 3% discount rate 1,390 $ 8,740  Using a 7% discount rate 1,390 $ 8,210 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,860 $ 1,030 Hospital Admissions   Pneumonia ( adults, over 64) 610 $ 10 Hospital Admissions   COPD ( adults, 64 and over) 500 $ 5 Hospital Admissions   Asthma ( 65 and younger) 140 $ 1 Hospital Admissions   Cardiovascular ( adults, over 64) 1,480 $ 25 Emergency Room Visits for Asthma ( 65 and younger) 1,140 <$ 1 Asthma Attacks ( asthmatics, all ages) 97,060 B1 Acute bronchitis ( children, 8 12) 2,870 <$ 1 Lower respiratory symptoms ( children, 7 14) 31,290 <$ 1 Upper respiratory symptoms ( asthmatic children, 9 11) 110,370 $ 5 Work loss days ( adults, 18 65) 243,870 $ 25 Minor restricted activity days ( adults, age 18 65) 1,196,500 $ 60 Other PM related health effectsF U1 B2 HAP health effectsG U2 B3 Total Monetized Health Related BenefitsF  Using a 3% discount rate   $ 9,905+ BH  Using a 7% discount rate   $ 9,375+ BH AThe results presented in this table are based on those SO 2 and PM emission reductions identified for specific sources included in the Inventory Database. This includes approximately 50% of all emission reductions estimated by the rule. The location of all other emission reductions ( i. e. noninventory reductions) cannot be determined specifically and hence cannot be modeled in an air quality model. See Section 10.5 and Appendix D for benefit estimation of non inventory emission reductions. B The results presented in this table reflect the outcome of the combination of PM and SO 2 model runs. See Appendix D for a presentation of results for each pollutant independently. C Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. E Note that the estimated value for PM related premature mortality assumes the 5 year distributed lag structure described in detail in the Regulatory Impact Analysis of Heavy Duty Engine/ Diesel Fuel rule. E Monetized benefits are presented using two different discount rates. Results calculated using 3 percent discount rate are recommended by EPA's Guidelines for Preparing Economic Analyses ( U. S. EPA, 2000a). Results calculated using 7 percent discount rate are recommended by OMB Circular A 94 ( OMB, 1992). F A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 17. 10 33 Transfer Value

Benefits Emission Reductions 10.5 Phase Two Analysis: Benefit Transfer Valuation of Remaining Emission Reductions As is mentioned previously, only a portion of the expected emission reductions of the rule can be mapped to specific locations and hence modeled to determine the change in air quality ( e. g., change in ambient PM concentrations). For approximately 50% of the PM reductions and approximately 30% of the SO 2 reductions, the lack of location specific data prevents us from utilizing the S R Matrix to determine air quality changes and the CAPMS model to estimate total benefits. We can assume, however, that these reductions are achieved uniformly throughout the country because the location of boilers/ process heaters in the U. S. is spread fairly evenly across all states. To estimate benefits for these reductions, we use the results of the air quality and benefit analysis provided in phase one to infer the average benefit value per ton of emission reduction for each pollutant  PM and SO 2. The benefit transfer values for PM and SO 2 are then applied to all remaining emission reductions to approximate total benefits of phase two of this analysis.

Before determining the benefit value to transfer to these reductions, one consideration must first be made. The total benefits that result from the air quality analysis of phase one is due to the combination of both direct PM reductions and SO 2 reductions that transform into secondary PM. Without knowledge of the percent of the total benefits in phase one that can be attributed to direct PM versus the percent of phase one benefits attributed to SO 2, we cannot accurately assign the monetized benefits to the tons reduced of each pollutant. To correctly apportion the total benefit value from phase one to the respective PM and SO 2 reductions, we performed two additional S R Matrix model runs of the reductions valued in phase one; one evaluation of the benefits of the PM reductions alone ( holding SO 2 unchanged), and one run of the benefits of the SO 2 reductions alone ( holding PM reductions unchanged). This allows us to determine the appropriate benefit transfer value for each individual pollutant. Because the combined effect of reducing both PM and SO 2 simultaneously at one location would result in a larger change in the concentration of PM, it can be expected that the air quality analyses of each pollutant alone will result in lower changes in concentrations and hence lower calculated benefits. The air quality and benefit assessment of the individual pollutants are again performed for each regulatory option: the MACT floor, and the above the MACT floor option. The detailed results of the additional air quality and benefit model runs are reported in Appendix D.

These data, along with the set of C R and valuation functions contained in CAPMS, constitute the input set for the benefits transfer value function. The benefits transfer function for each pollutant is specified as:

The numerator in the transfer value formula is total monetary benefits, which is determined by applying the same economic valuation functions specified in Table 10 5 to changes in incidences of human health endpoints resulting from the air quality modeling of each pollutant separately. In Appendix D, we show the calculated benefit transfer value of the total monetized benefits of PM alone and SO 2 alone and also for each individual endpoint included in this analysis.

A similar calculation is also done for the number of incidences associated with each endpoint. From the air quality assessments of PM and SO 2 alone, we divide total incidences of an endpoint by the total emission reductions included in the air quality scenario. Therefore, we determine a measure of the number of incidences of each health effect that can result from a ton 10 34 of pollutant reductions ( for example, 0.10 fewer asthma cases per ton reduced). This allows us to transfer the incidence per ton reduced to the remaining set of emission reductions of the phase two analysis.

Note that for both dollar and incidence per ton estimates, we assume that each ton of pollutant has the same impact, so that subnational applications are inappropriate as the national application requires assuming populations are uniformly distributed throughout the U. S.

Once all transfer values are determined for each endpoint and total benefits, we apply them to the set of phase two emission reductions. Finally, we combine our phase two estimates of benefits with the phase one calculated benefits to provide an estimate of total benefits for each endpoint and determine the total monetized benefits associated with the rule.

Sections 10.5.1 and 10.5.2 provide further detail on the transfer values obtained for SO 2 and PM in this analysis.

10.5.1 SO 2 Benefits Transfer Values Using the results of the air quality analysis of SO 2 reductions alone ( holding PM unchanged) from phase one, we can extract information on the total number of incidences and total benefit value of each endpoint to estimate the SO 2 benefit transfer values. As an example of the calculation consider the following: the total SO 2 emission reductions applied in the S R matrix analysis for phase one of this analysis are 82,542 tons. Under the MACT floor, the analysis yields approximately 240 fewer premature deaths at a total value of $ 1.5 billion ( see Appendix D for details). Therefore, the benefit transfer value to apply to SO 2 emission reductions in the phase two analysis associated with the mortality endpoint would on average be $ 18,385 per ton reduced. This procedure is repeated for each endpoint and for the total benefits estimate associated with SO 2 reductions alone. Further, based on these results it can be estimated that SO 2 reductions from the MACT floor on average result in 0.003 fewer incidences of mortality per ton reduced ( 240 incidences/ 82,542 tons).

The following tables present the incidence and benefits data necessary to calculate the benefits transfer values for SO 2. Table 10 8 present the benefit transfer values for the MACT floor option, while Table 10 9 presents benefit transfer values associated with the Above the MACT floor option. The benefits transfer values for SO 2 emission reductions are reported in 1999 dollars. Differences in benefit/ ton estimates between the MACT floor option and the above the floor option may be due to differences in the location of emission reductions and other factors. In particular, while PM reductions from process heaters are not expected to accrue at the MACT floor level of control, approximately 18,300 tons are estimate for the above the floor option. The Inventory Database provides information on the location of the majority of process heaters and thus we can apply a large percentage of these reductions directly into the air quality and benefit analysis. In addition, the process heaters affected by this proposal are largely found at large facilities located near large cities, thus the changes in air quality are applied to the populated areas around the cities. 10 35 Table 10 8. SO2 Benefit Transfer Values Based on Data From Phase One Analysis MACT Floor Regulatory OptionA Endpoint Avoided IncidenceB ( cases/ year) Incidence Per Ton ReducedC Monetary BenefitsD ( millions 1999$, adjusted for growth in real income) Total Benefit Per Ton ReducedC ($/ ton)

Premature mortalityE ( long term exposure, adults 30 and over)  Using a 3% discount rate 240 0.0029 $ 1,520 $ 18,385  Using a 7% discount rate 240 0.0029 $ 1,425 $ 17,270 Chronic bronchitis ( adults, 26 and over, WTP valuation) 320 0.0039 $ 115 $ 1,400 Hospital Admissions   Pneumonia ( adults, over 64) 60 0.0008 $ 1 $ 10 Hospital Admissions   COPD ( adults, 64 and over) 50 0.0006 $ 1 $ 5 Hospital Admissions   Asthma ( 65 and younger) 20 0.0003 <$ 1 <$ 5 Hospital Admissions   Cardiovascular ( adults, over 64) 150 0.0018 $ 5 $ 30 Emergency Room Visits for Asthma ( 65 and younger) 130 0.0016 <$ 1 <$ 1 Asthma Attacks ( asthmatics, all ages) 11,120 0.1347 B 1 B 1 Acute bronchitis ( children, 8 12) 490 0.0059 <$ 1 <$ 1 Lower respiratory symptoms ( children, 7 14) 5,330 0.0645 <$ 1 $ 1 Upper respiratory symptoms ( asthmatic children, 9 11) 12,980 0.1572 <$ 1 $ 5 Work loss days ( adults, 18 65) 42,611 0.5162 $ 5 $ 55 Minor restricted activity days ( adults, age 18 65) 214,592 2.5998 $ 10 $ 130 Other PM related health effectsF U 1  B 2 B 2 HAP related health effectsF U 2  B 3 B 3 Total Benefits of SO2 Related ReductionsE  Using a 3% discount rate     $ 1,650 $ 20,030+ B H  Using a 7% discount rate C  $ 1,560 $ 18,910+ B H A Results of the phase one benefit analysis of SO 2 emission reductions are presented in Appendix D, and replicated in columns 2 and 4 of this table. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Total SO 2 emission reductions included in the phase one analysis and applied to derive the benefit transfer values of this table are 82,542 tons. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. E Monetized benefits are presented using two different discount rates. Results calculated using 3 percent discount rate are recommended by EPA's Guidelines for Preparing Economic Analyses ( U. S. EPA, 2000a). Results calculated using 7 percent discount rate are recommended by OMB Circular A 94 ( OMB, 1992).

Table 10 9. SO2 Benefit Transfer Values Based on Data From Phase One Analysis Above the MACT Floor Regulatory OptionA 10 36 Endpoint Avoided IncidenceB ( cases/ year) Incidence Per Ton ReducedC Monetary BenefitsD ( millions 1999$, adjusted for growth in real income) Total Benefit Per Ton ReducedC ($/ ton)

Premature mortality ( long term exposure, adults, 30 and over)  Using a 3% discount rate 310 0.0032 $ 1,935 $ 20,305  Using a 7% discount rate 310 0.0032 $ 1,820 $ 19,070 Chronic bronchitis ( adults, 26 and over, WTP valuation) 400 0.0042 $ 145 $ 1,500 Hospital Admissions   Pneumonia ( adults, over 64) 70 0.0007 $ 1 $ 10 Hospital Admissions   COPD ( adults, 64 and over) 60 0.0006 $ 1 $ 10 Hospital Admissions   Asthma ( 65 and younger) 30 0.0003 <$ 1 <$ 5 Hospital Admissions   Cardiovascular ( adults, over 64) 170 0.0018 $ 5 $ 35 Emergency Room Visits for Asthma ( 65 and younger) 150 0.0015 <$ 1 <$ 1 Asthma Attacks ( asthmatics, all ages) 12,250 0.1284 B 1 B 1 Acute bronchitis ( children, 8 12) 660 0.0069 <$ 1 <$ 1 Lower respiratory symptoms ( children, 7 14) 7,170 0.0752 <$ 1 $ 1 Upper respiratory symptoms ( asthmatic children, 9 11) 14,160 0.1485 <$ 1 $ 5 Work loss days ( adults, 18 65) 54,980 0.5765 $ 5 $ 60 Minor restricted activity days ( adults, age 18 65) 279,760 2.9337 $ 15 $ 145 Other PM related health effects U 1  B 2 B 2 HAP related health effects U 2  B 3 B 3 Total Benefits of SO2 Related Reductions  Using a 3% discount rate C  $ 2,105 $ 22,070+ B H  Using a 7% discount rate     $ 1,990 $ 20,840+ B H A Results of the phase one benefit analysis of SO 2 emission reductions are presented in Appendix D, and replicated in columns 2 and 4 of this table. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Total SO 2 emission reductions included in the phase one analysis and applied to derive the benefit transfer values of this table are 95,361 tons. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. 10.5.2 PM Benefits Transfer Values The transfer values for PM are developed using the same basic approach as for the SO2 reductions. However, the PM benefits analysis conducted for this RIA includes health benefits associated with reductions in both PM 2.5 and PM 10. Therefore, the benefit transfer values for endpoints associated with PM 2.5 alone will be established using an estimate of the portion of total PM reductions that are likely to be PM 2.5. Likewise the benefit endpoints associated with PM 10 alone require an estimate of PM 10 emission reductions to derive the benefit transfer value for such endpoints. Fortunately, the S R Matrix model has a component that can approximate PM 2.5 emissions from a total change in PM. Based on this approximation, of the 265,155 tons of PM 10 emission reductions included in the air quality analysis of the MACT floor from phase one, 22 Reductions in PM2.5 are derived as a function of the estimated PM10 reductions. The S R matrix model contains coefficients that relate reductions in both directly emitted PM10 and directly emitted PM2.5. At the time the S R matrix was being developed in the early 1990s, a nationwide inventory of directly emitted PM2.5 emissions was not available, so the author developed a method for crudely estimating PM2.5 emissions from PM10 emissions. The air quality changes predicted by the model for direct PM2.5 were then developed from these crude emissions estimates. A full discussion of the derivation of PM2.5 estimates is provided in E. H. Pechan ( 1994 and 1996), and Latimer and Associates( 1996). The PM Calculator Tool can also be found on the Internet at www. epa. gov/ chief/ software/ pmcalc/ index. html.

10 37 approximately 75,095 tons are PM 2.5.22 The endpoints associated with PM 2.5 are long term mortality, minor restricted activity days ( MRAD), and acute respiratory symptoms. All other endpoints are associated with PM 10 reductions. For the MACT floor option, Tables 10 9 present the total incidence and benefits data for each endpoint from the phase one analysis , and the calculated the benefits transfer values for PM that are to be applied for the phase two analysis. Table 10 10 present similar data for the above the MACT floor regulatory option. 10 38 Table 10 10. PM Benefit Transfer Values Based on Data From Phase One Analysis MACT Floor Regulatory OptionA Endpoint Avoided IncidenceB ( cases/ year) Incidence Per Ton ReducedC Monetary BenefitsD ( millions 1999$, adjusted for growth in real income) Total Benefit Per Ton ReducedC ($/ ton)

Premature mortality ( long term, adults, 30 and over)  Using a 3% discount rate 900 0.01202 $ 5,675 $ 75,595  Using a 7% discount rate 900 0.01202 $ 5,330 $ 71,005 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,360 0.0089 $ 850 $ 3,195 Hospital Admissions   Pneumonia ( adults, over 64) 510 0.0019 $ 10 $ 30 Hospital Admissions   COPD ( adults, 64 and over) 420 0.0016 $ 5 $ 20 Hospital Admissions   Asthma ( 65 and younger) 90 0.0012 $ 1 $ 10 Hospital Admissions   Cardiovascular ( adults, over 64) 1,230 0.0046 $ 25 $ 85 Emergency Room Visits for Asthma ( 65 and younger) 950 0.0036 <$ 1 $ 1 Asthma Attacks ( asthmatics, all ages) 80,700 0.3043 B 1 B 1 Acute bronchitis ( children, 8 12) 1,870 0.0248 <$ 1 $ 1 Lower respiratory symptoms ( children, 7 14) 20,370 0.2712 <$ 1 $ 5 Upper respiratory symptoms ( asthmatic children, 9 11) 91,620 0.3455 $ 5 $ 10 Work loss days ( adults, 18 65) 158,560 2.1115 $ 20 $ 225 Minor restricted activity days ( adults, age 18 65) 760,870 10.132 $ 40 $ 500 Other PM related health effects U 1  B 2 B 2 HAP related health effects U 2  B 3 B 3 Total Benefits of PM Related Reductions  Using a 3% discount rate)     $ 6,620 $ 88,120+ B H  Using a 7% discount rate     $ 6,275 $ 83,530+ B H A Results of the phase one benefit analysis of PM emission reductions are presented in Appendix D, and replicated in columns 2 and 4 of this table. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Total PM 10 and PM 2.5 emission reductions included in the phase one analysis and applied to derive the benefit transfer values of this table are 265,155 tons and 75,095 tons, respectively. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. 10 39 Table 10 11. PM Benefit Transfer Values Based on Data From Phase One Analysis Above the MACT Floor Regulatory OptionA Endpoint Avoided IncidenceB ( cases/ year) Incidence Per Ton ReducedC Monetary BenefitsD ( millions 1999$, adjusted for growth in real income) Total Benefit Per Ton ReducedC Premature mortality ( long term exposure, adults, 30 and over)  Using a 3% discount rate 1,090 0.0115 $ 6,835 $ 72,290  Using a 7% discount rate 1,090 0.0115 $ 6,420 $ 67,900 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,680 0.0085 $ 965 $ 3,070 Hospital Admissions   Pneumonia ( adults, over 64) 570 0.0018 $ 10 $ 30 Hospital Admissions   COPD ( adults, 64 and over) 470 0.0015 $ 5 $ 20 Hospital Admissions   Asthma ( 65 and younger) 110 0.0012 $ 1 $ 10 Hospital Admissions   Cardiovascular ( adults, over 64) 1,390 0.0044 $ 25 $ 80 Emergency Room Visits for Asthma ( 65 and younger) 1,070 0.0034 <$ 1 $ 1 Asthma Attacks ( asthmatics, all ages) 90,940 0.2897 B 1 B 1 Acute bronchitis ( children, 8 12) 2,230 0.0236 <$ 1 $ 1 Lower respiratory symptoms ( children, 7 14) 24,330 0.2572 <$ 1 $ 5 Upper respiratory symptoms ( asthmatic children, 9 11) 103,400 0.3294 $ 5 $ 10 Work loss days ( adults, 18 65) 190,370 2.0131 $ 20 $ 215 Minor restricted activity days ( adults, age 18 65) 918,650 9.7144 $ 45 $ 485 Other PM related health effects U 1  B 2 B 2 HAP related health effects U 2  B 3 B 3 Total Benefits of PM Related Reductions  Using a 3% discount rate C  $ 7,910 $ 83,645+ B H  Using a 7% discount rate     $ 7,495 $ 79,255+ B H A Results of the phase one benefit analysis of PM emission reductions are presented in Appendix D, and replicated in columns 2 and 4 of this table. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Total PM 10 and PM 2.5 emission reductions included in the phase one analysis and applied to derive the benefit transfer values of this table are 313,947 tons and 94,565 tons, respectively. D Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. 10 40 10.5.3 Application of Benefits Transfer Values to Phase Two Emission Reductions Emission reductions included in phase two of our benefit analysis are summarized in Table 10 2. These reductions will be applied to the benefit transfer values developed in the previous section. These emission reductions are derived by simply subtracting the emission reductions including in the phase one analysis from the total emission reductions anticipated from this NESHAP.

Thus, in the final step of the phase two analysis, the transfer values calculated in section 10.5.3 are multiplied by the emission reductions associated with the phase two analysis. Appendix D provides tables showing the benefit estimation for each pollutant ( PM and SO 2) separately. In the tables below, we combine the total SO 2 benefits of phase two with the total PM benefits of phase two from Appendix D to provide a summary of total benefits associated with phase two of this analysis for each regulatory option analyzed. 10 41 Table 10 12. Phase Two Analysis: Annual Health Benefits Associated with Non Inventory Emission Reductions of the Industrial Boilers/ Process Heaters NESHAP  MACT Floor Regulatory Option in 2005, Using Benefit Transfer ValuesA Endpoint Avoided IncidenceB ( cases/ year) Monetary BenefitsC ( millions 1999$, adjusted for growth in real income)

Premature mortalityD ( long term exposure, adults, 30 and over)  Using a 3% discount rate 1,100 $ 6,920  Using a 7% discount rate 1,110 $ 6,495 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,760 $ 990 Hospital Admissions   Pneumonia ( adults, over 64) 590 $ 10 Hospital Admissions   COPD ( adults, 64 and over) 490 $ 5 Hospital Admissions   Asthma ( 65 and younger) 110 $ 1 Hospital Admissions   Cardiovascular ( adults, over 64) 1,430 $ 25 Emergency Room Visits for Asthma ( 65 and younger) 1,110 <$ 1 Asthma Attacks ( asthmatics, all ages) 94,470 B 1 Acute bronchitis ( children, 8 12) 2,270 <$ 1 Lower respiratory symptoms ( children, 7 14) 24,770 <$ 1 Upper respiratory symptoms ( asthmatic children, 10 11) 107,380 <$ 5 Work loss days ( adults, 18 65) 193,270 $ 20 Minor restricted activity days ( adults, age 18 65) 931,140 $ 45 Other PM related health effectsE U 1 B 2 HAP related health effectsE U 2 B 3 Total Monetized Health Related Benefits  Using a 3% discount rate   $ 8,020+ BH  Using a 7% discount rate   $ 7,600+ BH A The results presented in this table reflect the outcome of the combination of PM and SO 2 benefit estimates from the application of benefit transfer values applied in the phase two analysis. See Appendix D for a presentation of results for each pollutant independently. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. D Note that the estimated value for PM related premature mortality assumes the 5 year distributed lag structure described in detail in the Regulatory Impact Analysis of Heavy Duty Engine/ Diesel Fuel rule. E A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 16. 10 42 Table 10 13. Phase Two Analysis: Annual Health Benefits Associated with Non Inventory Emission Reductions of the Industrial Boilers/ Process Heaters NESHAP  Above the MACT Floor Regulatory Option in 2005, Using Benefit Transfer ValuesA Endpoint Avoided IncidenceB ( cases/ year) Monetary BenefitsC ( millions 1999$, adjusted for growth in real income)

Premature mortalityD ( long term exposure, adults, 30 and over)  Using a 3% discount rate 1,020 $ 6,400  Using a 7% discount rate 1,020 $ 6,010 Chronic bronchitis ( adults, 26 and over, WTP valuation) 2,350 $ 850 Hospital Admissions   Pneumonia ( adults, over 64) 500 $ 10 Hospital Admissions   COPD ( adults, 64 and over) 410 $ 5 Hospital Admissions   Asthma ( 65 and younger) 100 $ 1 Hospital Admissions   Cardiovascular ( adults, over 64) 1,200 $ 20 Emergency Room Visits for Asthma ( 65 and younger) 930 <$ 1 Asthma Attacks ( asthmatics, all ages) 79,260 B 1 Acute bronchitis ( children, 8 12) 2,100 <$ 1 Lower respiratory symptoms ( children, 7 14) 22,890 <$ 1 Upper respiratory symptoms ( asthmatic children, 10 11) 90,220 <$ 5 Work loss days ( adults, 18 65) 178,650 $ 20 Minor restricted activity days ( adults, age 18 65) 868,360 $ 45 Other PM related health effectsE U 1 B 2 HAP related health effectsE U 2 B 3 Total Monetized Health Related Benefits  Using a 3% discount rate   $ 7,350+ BH  Using a 7% discount rate   $ 6,960+ BH A The results presented in this table reflect the outcome of the combination of PM and SO 2 benefit estimates from the application of benefit transfer values applied in the phase two analysis. See Appendix D for a presentation of results for each pollutant independently. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. D Note that the estimated value for PM related premature mortality assumes the 5 year distributed lag structure described in detail in the Regulatory Impact Analysis of Heavy Duty Engine/ Diesel Fuel rule. E A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 16. 10 43 10.6 Total Benefits of the Industrial Boilers/ Process Heaters NESHAP Given the estimates of benefits from phases one and two of this analysis, this section combines those results to present the estimate of total benefits of the NESHAP. To obtain this estimate, we aggregate dollar benefits associated with each of the effects examined, such as hospital admissions, into a total benefits estimate assuming that none of the included health and welfare effects overlap. The benefits associated with the health and welfare effects is the sum of the separate effects estimates. Total monetized benefits associated with the MACT floor regulatory option of the Industrial Boilers/ Process Heaters NESHAP are listed in Table 10 14, along with a breakdown of benefits by endpoint. Table 10 15 provides total annual benefits of the above the MACT floor option.

Again, note that the value of endpoints known to be affected by PM that we are not able to monetize are assigned a placeholder value ( e. g., B 1, B 2, etc.). Unquantified physical effects are indicated by a U. The estimate of total benefits is thus the sum of the monetized benefits and a constant, B, equal to the sum of the unmonetized benefits, B 1+ B 2+...+ B n.

A comparison of the incidence column to the monetary benefits column reveals that there is not always a close correspondence between the number of incidences avoided for a given endpoint and the monetary value associated with that endpoint. For example, under the MACT floor option there are over 75 times more asthma attacks than premature mortalities, yet these asthma attacks account for only a very small fraction of total monetized benefits. This reflects the fact that many of the less severe health effects, while more common, are valued at a lower level than the more severe health effects. Also, some effects, such as asthma attacks, are valued using a proxy measure of WTP. As such the true value of these effects may be higher than that reported in Table 10 14 and Table 10 15.

The estimate of total monetized benefits for the MACT floor is $ 16.3 billion when using a 3 percent discount rate ( or $ 15.4 billion when using a 7 percent discount rate). Of this total, $ 14.2 billion ( or $ 13.4 billion) are the benefits of reduced premature mortality risk from PM exposure. Total monetized benefits are dominated by the benefits of reduced mortality risk, accounting for 87 percent of total monetized benefits, followed by chronic bronchitis totaling $ 1.8 billion, which represents 11 percent of the total. Following chronic bronchitis, minor restricted activity days ( MRADs) is the next largest quantified benefit category totaling $ 100 million, and it also presents the category with the largest number of incidences at 1,942,340 per year. MRADs in combination with lost work days and avoided hospital admissions from cardiovascular related illness account for $ 140 million of total benefits. For the asthma related endpoints, we note that the MACT floor will result in approximately 173,000 fewer asthma attacks, more than 2,000 fewer visits to the emergency room of hospitals for asthma, and 200 fewer hospital admissions for asthma related effects.

Total annual benefits of the above the MACT floor regulatory option are $ 17.2 billion under when using a 3 percent discount rate ( or $ 16.3 billion when using a 7 percent discount rate). Similar to the MACT floor results, the mortality endpoint accounts for the majority of benefits at $ 15.1 billion ( or $ 14.2 billion), followed by chronic bronchitis at $ 1.9 billion. MRADs account for $ 100 million in benefits and 2,064,854 fewer incidences. The monetized benefits of MRADs combined with lost work days and cardiovascular related hospital admissions account for $ 180 million of benefits. For the asthma related endpoints, we note that the above the MACT floor option will result in approximately 82,000 fewer asthma attacks, more than 2,000 fewer visits to the emergency room of hospitals for asthma, and about 240 fewer hospital admissions for asthma related effects. 10 44 10 45 Table 10 14. Total Annual Benefits of the Industrial Boilers/ Process Heaters NESHAP A MACT Floor Regulatory Option Endpoint Avoided IncidenceB ( cases/ year) Monetary BenefitsC ( millions 1999$, adjusted for growth in real income)

Premature mortalityD ( long term exposure, adults, 30 and over)  Using a 3% discount rate 2,270 $ 14,240  Using a 7% discount rate 2,270 $ 13,375 Chronic bronchitis ( adults, 26 and over, WTP valuation) 5,100 $ 1,835 Hospital Admissions   Pneumonia ( adults, over 64) 1,100 $ 15 Hospital Admissions   COPD ( adults, 64 and over) 900 $ 10 Hospital Admissions   Asthma ( 65 and younger) 230 <$ 5 Hospital Admissions   Cardiovascular ( adults, over 64) 2,660 $ 50 Emergency Room Visits for Asthma ( 65 and younger) 2,040 <$ 1 Asthma Attacks ( asthmatics, all ages) 173,490 B1 Acute bronchitis ( children, 8 12) 4,700 <$ 1 Lower respiratory symptoms ( children, 7 14) 51,240 $ 1 Upper respiratory symptoms ( asthmatic children, 10 11) 196,860 $ 5 Work loss days ( adults, 18 65) 398,670 $ 40 Minor restricted activity days ( adults, age 18 65) 1,942,340 $ 100 Other PM related health effectsE U1 B2 HAP related health effectsE U2 B3 Total Monetized Health Related BenefitsF  Using a 3% discount rate C $ 16,300+ B H  Using a 7% discount rate C $ 15,430+ B H A The results presented in this table include all emission reductions including those identified for specific sources included in the Inventory Database included in the Phase One analysis and the remaining reductions not included in the Inventory Database included in the Phase Two analysis B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. D The estimated value for PM related premature mortality assumes a 5 year distributed lag structure and discounted at a 3% rate, which is described in the IAQR benefit anlaysis. E A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 16. 10 46 Table 10 15. Total Annual Benefits of the Industrial Boilers/ Process Heaters NESHAP A Above the MACT Floor Regulatory Option Endpoint Avoided IncidenceB ( cases/ year) Monetary BenefitsC ( millions 1999$, adjusted for growth in real income)

Premature mortalityD ( long term exposure, adults, 30 and over)  Using a 3% discount rate 2,410 $ 15,135  Using a 7% discount rate 2,410 $ 14,220 Chronic bronchitis ( adults, 26 and over, WTP valuation) 5,220 $ 1,875 Hospital Admissions   Pneumonia ( adults, over 64) 1,110 $ 15 Hospital Admissions   COPD ( adults, 64 and over) 910 $ 10 Hospital Admissions   Asthma ( 65 and younger) 240 <$ 5 Hospital Admissions   Cardiovascular ( adults, over 64) 2,680 $ 50 Emergency Room Visits for Asthma ( 65 and younger) 2,080 <$ 1 Asthma Attacks ( asthmatics, all ages) 82,130 B 1 Acute bronchitis ( children, 8 12) 4,970 <$ 1 Lower respiratory symptoms ( children, 7 14) 54,190 $ 1 Upper respiratory symptoms ( asthmatic children, 10 11) 200,590 $ 5 Work loss days ( adults, 18 65) 275,710 $ 30 Minor restricted activity days ( adults, age 18 65) 2,064,850 $ 100 Other PM related health effectsE U 1 B 2 HAP related health effectsE U 2 B 3 Total Monetized Health Related Benefits  Using a 3% discount rate   $ 17,230+ BH  Using a 7% discount rate   $ 16,310+ BH A The results presented in this table include all emission reductions including those identified for specific sources included in the Inventory Database and the remaining reductions not included in the Inventory Database. B Incidences are rounded to the nearest 10 and may not add due to rounding. Incidences of unquantified endpoints are indicated with a U. C Dollar values are rounded to the nearest 5 million and may not add due to rounding. The value of unquantified endpoints are indicated with a B. D The estimated value for PM related premature mortality assumes a 5 year distributed lag structure and discounted at a 3% rate, which is described in the IAQR benefit anlaysis. E A detailed listing of unquantified PM and HAP related health effects is provided in Table 10 16. 10 47 10.7 Limitations of the Analysis 10.7.1 Uncertainties and Assumptions Significant uncertainties and potential biases are inherent in any benefits analysis based on benefits transfer techniques. This analysis uses two forms of benefit transfer, ( 1) the transfer of dose response functions and valuation estimates from published articles, and ( 2) the transfer of value per ton reduced from the monetized estimate in the phase one analysis. The degree of uncertainty and bias depends on how divergent the reality of the policy situation is from the state of the world assumed in the benefits transfer approaches.

For this analysis, several key assumptions may lead to over or underestimation of benefits. Table 10 8 lists these assumptions, and where possible indicate the expected direction of the bias. This is by no means an exhaustive list, but captures what we have identified as key assumptions. In addition to these uncertainties and biases, there are uncertainties and biases embedded in the original benefits analyses from which the transfer values were generated. Some of these potential biases and assumptions are discussed in the preceding sections. For a full discussion of these uncertainties, see the RIA for the Heavy Duty Engine/ Diesel Fuel rule, as well as the Section 812 report to congress on the Benefits and Costs of the Clean Air Act 1999 to 2010. 10 48 Table 10 16. Significant Uncertainties and Biases Associated with the Industrial Boilers/ Process Heaters Benefit Analysis Assumption Direction of BiasA Omission of HAP effects, and PM effects associated with visibility and materials damage benefit categories Downward Estimated emission reductions accurately reflect conditions in 2005 Unknown Future meteorology well represented by modeled meteorology Unknown Benefits from source studies do not include all benefits and disbenefits Unknown Population, demographics, exposures, and air quality included in phase one analysis is representative for the transfer to the phase two analysis Unknown Linear extrapolation of future populations Unknown Accuracy of S R Matrix representativeness of secondary PM formation chemistry Unknown A A downward bias is an indicator that total benefits are underestimated. An upward bias is an indicator that total benefits are overestimated. In several cases, the direction of the bias is unknown and can potential be an underestimate or an overestimate of total benefits.

10.7.2 Unquantified Effects In addition to the monetized benefits presented in the above tables, it is important to recognize that many benefit categories associated with HAP, SO 2, and PM reductions are not quantified or monetized for this analysis. With respect to the benefits of reducing exposure to HAPs, EPA has developed a rudimentary risk analysis focusing only on cancer risks. As discussed above, this analysis suggests that the rule would reduce cancer incidence by roughly tens of cases per year if it were implemented at all affected boiler and process heater facilities. Placing a value on these impacts would increase the economic benefits of the rule. This analysis carries significant assumptions, uncertainties, and limitations. EPA is working with the SAB to develop better methods for analyzing the cancer and non cancer benefits of HAP reductions. EPA will include a monetized estimate of the benefits of reducing HAP emissions with the analysis for the final rule if it is able to develop better methods before promulgation of this rule. Other potentially important unquantified benefit categories are listed in Table 10 17. For a more complete discussion of unquantified benefits and disbenefits, see the RIA for the Heavy Duty Engine/ Diesel Fuel rule. 10 49 Table 10 17. Unquantified Benefit Categories Unquantified Benefit Categories Associated with HAPs Unquantified Benefit Categories Associated with PM Health Categories Airway responsiveness Pulmonary inflammation Increased susceptibility to respiratory infection Acute inflammation and respiratory cell damage Chronic respiratory damage/ Premature aging of lungs Emergency room visits for asthma Changes in pulmonary function Morphological changes Altered host defense mechanisms Other chronic respiratory disease Emergency room visits for asthma Emergency room visits for nonasthma respiratory and cardiovascular causes Lower and upper respiratory symptoms Acute bronchitis Shortness of breath Increased school absence rates Welfare Categories Ecosystem and vegetation effects Damage to urban ornamentals ( e. g., grass, flowers, shrubs, and trees in urban areas) Commercial field crops Fruit and vegetable crops Reduced yields of tree seedlings, commercial and non commercial forests Damage to ecosystems Materials damage Materials damage Damage to ecosystems ( e. g., acid sulfate deposition) Nitrates in drinking water Visibility in recreational and residential areas 10 50 10.8 Benefit Cost Comparison This Regulatory Impact Analysis ( RIA) provides cost, economic impact, and benefit estimates that are potentially useful for evaluating regulatory alternatives for the industrial boilers and process heaters rule. Benefit cost analysis provides a systematic framework for assessing and comparing such alternatives. According to economic theory, the efficient alternative maximizes net benefits to society ( i. e., social benefits minus social costs). However, there are practical limitations for the comparison of benefits to costs in this analysis. In particular, the inability to quantify the primary HAP related benefits of the rule, as well as the inability to quantify the disbenefits of increased electricity generation related emissions introduces biases into our estimate of benefits that make comparison with costs less meaningful. Executive Order 12866 clearly indicates that unquantifiable or nonmonetizable categories of both costs and benefits should not be ignored. There are many important unquantified and unmonetized costs and benefits associated with reductions in PM 10 and PM 2.5 emissions, including many health and welfare effects. Potential PM benefit categories that have not been quantified and monetized are listed in Table 10 18 of this chapter. It is also important to recall that this analysis is only of the monetizable benefits associated with PM 10 and PM 2.5 reductions. The rule is designed to reduce HAP emissions. By achieving these HAP reductions, the rule reduces the risks associated with exposures to those chemicals, including the risk of fatal cancers. It is likely the monetized benefit estimates presented in this chapter are expected to underestimate total benefits of the rule.

In addition to categories that cannot be included in the calculated net benefits, there are also practical limitations for the comparison of benefits to costs in this analysis, which have been discussed throughout this chapter. Several specific limitations deserve to be mentioned again here:

The state of atmospheric modeling is not sufficiently advanced to provide a workable " one atmosphere" model capable of characterizing ground level pollutant exposure for all pollutants of interest ( e. g., ozone, particulate matter, carbon monoxide, nitrogen deposition, etc). Therefore, the EPA must employ several different pollutant models to characterize the effects of alternative policies on relevant pollutants. Also, not all atmospheric models have been widely validated against actual ambient data. In particular, since a broad scale monitoring network is in the early stages of development for fine particulate matter ( PM 2.5), atmospheric models designed to capture the effects of alternative policies on PM 2.5 are not fully validated. Additionally, significant shortcomings exist in the data that are available to perform these analyses. While containing identifiable shortcomings and uncertainties, EPA believes the models and assumptions used in the analysis are reasonable based on the available data and evidence.

Qualitative and more detailed discussions of the above and other uncertainties and limitations are included in detail in earlier sections. In particular, the fact that only half of the sources expected to be affected by this rule are actually covered in these analysis contributes to the uncertainty of the benefits estimates ( as well those of the costs and economic impacts, as well). Data limitations prevent an overall quantitative estimate of the uncertainty associated with final estimates. Nevertheless, the reader should keep all of these uncertainties and limitations in mind when reviewing and interpreting the results.

° The PM benefit estimates do not include the monetary value of several known PMrelated welfare effects, including recreational and residential visibility, household soiling, and materials damage. 10 51 Nonetheless, if one is mindful of these limitations, the relative magnitude of the benefitcost comparison presented here can be useful information. Thus, this section summarizes the benefit and cost estimates that are potentially useful for evaluating the efficiency of the Industrial Boilers and Process Heaters rule.

The estimated social cost of implementing the NESHAP at the MACT floor is approximately $ 837 million ( 1999$) in third year after issuance of this rule. The monetized benefits of the MACT floor are $ 16.3 billion when using a 3 percent discount rate ( or approximately $ 15.4 billion when using a 7 percent discount rate). Keeping in mind that no primary HAP related benefits are quantified, comparison with costs indicates that our estimate of monetized benefits of ancillary PM 10 and SO 2 reductions alone exceed the compliance costs by nearly a factor of 20.

For the above the floor option ( also called " Option 1A" in this RIA), the estimated social cost is $ 1.9 billion ( 1999$) in third year after issuance of this rule. The monetized benefits of the above the floor option are $ 17.2 billion when using a 3 percent discount rate ( or approximately $ 16.3 billion when using a 7 percent discount rate). Thus, our estimate of benefits of the above the floor option exceed the costs by a factor of 8.

It is also useful to consider the incremental costs and benefits of moving from the MACT floor to the above the floor option. The incremental net benefits of going to the above the floor option from the NESHAP ( the MACT floor alternative) is $ 160 million ( using a 3 percent discount rate). Hence, the final rule can be considered a more efficient alternative to society than the above the floor option from the standpoint of maximizing net benefits. Note that while monetized benefits of PM 10 and SO 2 reductions are large in this instance, they account for only a portion of the benefits of this rule. Notable omissions include all benefits of HAPs and VOC reductions, including reduced cancer incidences, central nervous system and cardiovascular system effects, and ozone related benefits. It is also important to note that not all benefits of PM 10 reductions have been monetized. Categories which have contributed significantly to monetized benefits in past analyses ( see the Heavy Duty Engine/ Diesel Fuel RIA) include recreational and residential visibility and household soiling. Table 10 17 lists known unquantified benefits associated with PM and HAP reductions. Table 10 18 summarizes the costs, benefits, and net benefits for the rule and the above the floor option, and shows a comparison of the two options.

We did not attempt to estimate welfare benefits associated with PM reductions for this rule because of the difficulty in developing acceptable benefit transfer values for these effects. The SAB has recently reviewed existing studies valuing improvements in residential visibility and reductions in household soiling and advised that these studies do not provide an adequate basis for valuing these effects in cost benefit analyses ( EPA SAB COUNCIL ADV 00 002, 1999; EPA SAB Council ADV 003, 1998). Reliable methods do exist for valuing visibility improvements in Federal Class I areas, however, the benefits transfer method outlined above does not allow for predictions of changes in visibility at specific Class I areas. These predictions are necessary to estimate Class I area visibility benefits. As such we have left this potentially important endpoint unquantified for this analysis. Given the proximity of some sources to national parks in the Northwest ( Mt. Ranier, Olympic, and Crater Lake), Northern Rockies ( Glacier), and Maine ( Acadia), these omitted benefits may be significant.

As we characterize the comparison of benefits to costs, it should be recognized that the Agency believes its risk based approach to regulating HCl and Mn emissions from industrial boilers will reduce the cost impact of this final MACT standard while still achieving substantial reduction in HCl and Mn exposure by affected populations. In offering this approach, the 10 52 Agency recognizes that there may be foregone benefits associated in excess of the resulting reduction in costs. As is discussed in earlier in the RIA, the Agency is not able to quantify the benefits of HAP reductions. However, the reduction in HCl and Mn benefits are not anticipated to be substantial based on the description of potential effects described in Chapter 9 of this RIA. The acid gas scrubbers installed by industrial boilers not only reduce HCl emissions but also sulfur dioxide ( SO 2) emissions simultaneously. Reduction of SO 2 emissions can provide large monetized benefits since it is a precursor of fine particulate matter ( PM 2.5), a pollutant associated with a high degree of premature mortality in exposed populations. The fabric filters installed by industrial boilers not only reduce Mn emissions but also PM emissions simultaneously. Reduction of directly emitted coarse particulate matter ( PM 10) emissions can also provide large monetized benefits as well. While there may be foregone benefits in excess of the cost reduction, it should be recognized that the estimated monetized benefits from implementation of the final rule including this risk based approach are still much larger than the costs ($ 14.5 billion versus $ 690 million, or greater by a factor of 21). In addition, it should be recognized that the reductions not achieved due to industrial boilers taking advantage of the risk based approach could be obtained in a more efficient manner through other regulatory programs to reduce PM. More information on comparing the benefits of this rule to its costs can be found earlier in this RIA chapter.

The Agency recognizes that many States will want to reduce SO 2 and PM emissions from current levels in order to meet requirements associated with the proposed Interstate Air Quality Rule ( IAQR) and PM National Ambient Air Quality Standards ( NAAQS). It may be necessary for States to require reductions of SO 2 in higher amounts than can be obtained from the venturi scrubbers or PM reductions from fabric filters that would be required to meet this final MACT standard. The Agency understands that it would be difficult for States to justify requiring industrial boilers to dismantle scrubbers and fabric filters installed to comply with the MACT standard in order to install more expensive ones that meet potentially more stringent SO 2 and PM control requirements associated with implementation of the IAQR and PM NAAQS. The Agency will work carefully with States to help them minimize the potential " stranded investment" by industrial boiler owners in venturi scrubbers that may result as State agencies develop SIPs to meet the IAQR and PM NAAQS. 10 53 Table 10 18. Annual Net Benefits of the Industrial Boilers and Process Heaters NESHAP in 2005 MACT Floor ( Million 1999$) Above the MACT Floor ( Million 1999$)

Social CostsB $ 837 $ 1,923 Social BenefitsB, C, D:

HAP related health and welfare benefits Not monetized Not monetized PM related welfare benefits Not monetized Not monetized SO2 and PM related health benefits:

 Using 3% Discount Rate  Using 7% Discount Rate $ 16,300 + B $ 15,430 + B $ 17,230 + B $ 16,310 + B Net Benefits ( Benefits  Costs) C, D:

 Using 3% Discount Rate  Using 7% Discount Rate $ 15,465 $ 14,595 $ 15,305 + B $ 14,385 + B A All costs and benefits are rounded to the nearest $ 5 million. Thus, figures presented in this table may not exactly equal benefit and cost numbers presented in earlier sections of the chapter. B Note that costs are the total costs of reducing all pollutants, including HAPs as well as SO 2 and PM 10. Benefits in this table are associated only with PM and SO 2 reductions. C Not all possible benefits or disbenefits are quantified and monetized in this analysis. Potential benefit categories that have not been quantified and monetized are listed in Table 8 13. B is the sum of all unquantified benefits and disbenefits. D Monetized benefits are presented using two different discount rates. Results calculated using 3 percent discount rate are recommended by EPA's Guidelines for Preparing Economic Analyses ( U. S. EPA, 2000a). Results calculated using 7 percent discount rate are recommended by OMB Circular A 94 ( OMB, 1992). 10 54 References:

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Whittemore, A. S. and E. L. Korn. 1980. Asthma and Air Pollution in the Los Angeles Area. American Journal of Public Health. 70: 687 696. A 58 APPENDIX A: ECONOMIC MODEL OF MARKETS AFFECTED BY THE BOILERS AND PROCESS HEATERS MACT The primary purpose of the EIA for the final rule is to describe and quantify the economic impacts associated with the rule. The Agency used a basic framework that is consistent with economic theory and the analyses performed for other rules to develop estimates of these impacts. This approach employs standard microeconomic concepts to model behavioral responses expected to occur with regulation. This appendix describes the spreadsheet model in more detail and discusses how the Agency

collected the baseline data set from the Annual Energy Outlook 2002 ( DOE, EIA, 2002), U. S. Census Bureau ( U. S. Department of Commerce, 2001), and U. S. Department of Agriculture ( USDA, 2002).

characterized market supply and demand for each market and specified links between the energy and agricultural, manufacturing, mining, and commercial markets.

introduced a policy " shock" into the model by using control cost induced shifts in the supply functions, and

used a solution algorithm to determine a new with regulation equilibrium for each market.

A. 1 Baseline Data Set EPA collected the following data to characterize the baseline year, 2005:

Energy Market Data   The Department of Energy's Supplemental Tables to the Annual Energy Outlook 2002 report forecasts of price, quantity, and fuel intensities used to calibrate the model.

Agriculture, Mining, Manufacturing, Commercial Sectors   EPA obtained shipment data from the 1997 Economic Census and 1997 Agriculture Census. We then used annual growth rates reported by the Bureau of Economic Analysis ( BEA, 1997) to estimate baseline shipment data for 2005. The Agency selected units for output such that the price in each market equals one. We computed energy demand using fuel intensity data reported in the AEO 2002.

Supply and Demand Elasticities   The supply and demand elasticity values used in the market model are reported in Table 5 2 of this report. Given the uncertainties regarding these parameters, EPA also conducted several sensitivity analyses and report these results in Appendix B. A. 2 Multi Market Model The model includes four energy markets ( coal, electricity, natural gas, and petroleum) and 24 goods and service markets. The following sections describe model equations the Agency developed to characterize these markets and estimate welfare changes resulting from the rule.

A. 1.1 Supply Side Modeling EPA estimated the change in quantity supplied as follows: A 1   qS

q 0 S

S

  p

c

n  j  1   j  p j p 0 ( A. 1)

  PS  q 1

(   p

c

n  j  1   j  p j)

0.5

  q

(   p

c

n  j  1   j  p j) ( A. 2)

Q Dj  n  i  1 q Dji , ( A. 3)

  q D j  q 0 D j

  D j

  p j p j0 ( A. 4)

BTU ji1  BTU ji q i0

FSW

q i1 ( A. 5) where is the baseline quantity, is the domestic supply elasticity, the term q S 0

S   p

c

n  j  1   j  p j is the change in the producer's net price, and p 0 is the baseline price. The change in net price is composed of the change in baseline price resulting from the regulation, the direct shift in the supply function resulting from compliance costs, and the indirect shift in the supply function resulting from changes in input prices in energy market ( j). The fuel share is allowed to vary using a fuel switching rule relying on cross price elasticities of demand between energy sources.

A. 1.1.2 Producer Welfare Measurement EPA approximated the change in producer surplus with the following equation: Increased control costs, higher energy input costs, and output declines have a negative effect on domestic producer surplus. However, these losses are mitigated to some degree as a result of higher market prices. A. 1.2 Energy Demand Side Modeling Market demand in the energy markets is expressed as the sum of the energy, residential, agriculture, manufacturing, mining, commercial, and transportation sectors:

where j indexes the energy market and i indexes the consuming sector. The change in residential quantity demanded of energy market j can be approximated as follows:

where is baseline consumption,  Dj is the residential demand elasticity and (  p) is the change in the q Dj 0 market price. In contrast, energy demand from energy, agricultural, manufacturing, mining, commercial, and transportation sectors is modeled as a derived demand resulting from the production and consumption choices in these industries. Energy demand responds to changes in sector output and fuel switching that occurs in response to changes in relative energy prices. For each of these sectors, energy demand is expressed as follows:

where BTU is demand for energy market j from sector i, q is sector i's output, and FSW is a factor generated by the fuel switching algorithm. The subscripts 0 and 1 represent baseline and with regulation A 2   q D i  q 0 D i

  D i

  p i p i0 ( A. 6)

  CS

q 1

  p  0.5

  q

  p ( A. 7) conditions, respectively. A. 1.3 Agriculture, Manufacturing, Mining, Commercial, and Transportation Demand Side Modeling The change in quantity demanded in these markets can be approximated as follows:

where is baseline output,  D is the demand elasticity of the respective market ( i) and (  p i) is the q Di 0 change in the market price. The change in consumer surplus in markets is approximated as follows: As shown, higher market prices and reduced consumption lead to welfare losses for consumers.

A. 2 With Regulation Market Equilibrium Determination Market adjustments can be conceptualized as an interactive feedback process. Supply segments face increased production costs as a result of the rule and are willing to supply smaller quantities at the baseline price. This reduction in market supply leads to an increase in the market price that all producers and consumers face, which leads to further responses by producers and consumers and thus new market prices. The new with regulation equilibrium is the result of a series of iterations in which price is adjusted and producers and consumers respond, until a set of stable market prices arises where total market supply equals market demand ( i. e., Qs = Q D) in each market. Market price adjustment takes place based on a price revision rule that adjusts price upward ( downward) by a given percentage in response to excess demand ( excess supply). The algorithm for determining with regulation equilibria can be summarized by seven recursive steps: 1. Impose the control costs on affected supply segments, thereby affecting their supply decisions.

2. Recalculate the market supply in each market. Excess demand currently exists.

3. Determine the new prices via a price revision rule.

4. Recalculate market supply with new prices, accounting for fuel switching choices associated with new energy prices.

5. Compute market demand in each market.