6-1 

Chapter 6: Incremental Benefits of Attaining Alternative Ozone Standards Relative to the 

Current 8-hour Standard (0.08 ppm) 

Synopsis 

Based on projected emissions and air quality modeling, in 2020, 28 counties in the U.S. with 

ozone monitors are anticipated to fail to meet an alternative ozone standard of 0.075 ppm for the 

4th highest maximum 8-hour ozone concentration. This number falls to 11 for an ozone standard 

of 0.079 ppm, and increases to 89 for a standard of 0.070 ppm, and increases to 231 for an 

alternative standard of 0.065 ppm (see Figure 3.4 in Chapter 3). We estimated the health benefits 

of attaining these alternative ozone standards across the nation using the EPA Environmental 

Benefits Modeling and Analysis Program (BenMAP) using a two-stage analysis. 

In the first stage, we estimated the benefits associated with improving modeled air quality using 

known control technologies. These control strategies were sufficient to bring some, but not all, 

areas into attainment with the alternative standards. Thus, for some areas, the benefits computed 

during this first stage only represented partial attainment. In the second stage, we estimated the 

benefits of fully attaining the standards in all areas by using a “rollback” method. This method 

reduced ozone concentrations at nonattaining monitors to a level that would just meet the 

standards. To estimate the benefits for the 0.075 ppm and 0.079 standards, we deviated from this 

two-stage approach. Instead, we used an interpolation technique (please see Appendix 6a for 

more details on this technique). Benefits for the South Coast and San Joaquin areas of California 

(which are not expected to reach attainment of the current standard until after 2020) are 

estimated separately and can be found in Appendix 7b.1

 For all alternative standards, we used 

health impact functions based on published epidemiological studies and valuation functions 

derived from the economics literature to calculate the monetary value of the adverse health 

outcomes potentially avoided due to these reductions in ambient ozone levels.2 Key health 

endpoints included premature mortality, hospital and emergency room visits, school absences, 

and minor restricted activity days. 

There is considerable uncertainty in the magnitude of the association between ozone and 

premature mortality. This analysis presents four independent estimates of this association based 

upon different functions reported in the scientific literature. We also note that this range of 

estimates do not fully capture the uncertainties within each study. Recognizing that additional 

research is necessary to clarify the underlying mechanisms causing these effects, we also 

consider the possibility that the observed associations between ozone and mortality may not be 

causal in nature. Using the National Morbidity, Mortality and Air Pollution Study (NMMAPS), 

which was used as the primary basis for the risk analysis presented in our Staff Paper and 

reviewed by Clean Air Science Advisory Committee (CASAC), we estimated 250 avoided 

premature deaths annually in 2020 from reducing ozone levels to meet a standard of 0.070 ppm. 

When added to the other projected benefits from reduced ozone, including 3,000 hospital and 

 

1

 All subsequent estimates of full attainment ozone benefits and PM2.5 co-benefits found in this 

chapter exclude these two areas of California. 2

 Health impact functions measure the change in a health endpoint of interest, such as hospital 

admissions, for a given change in ambient ozone or PM concentration 
6-2 

emergency room admissions, 640,000 school absences, and over 1.7 million minor restricted 

activity days, we estimated a total ozone-related benefit of $2.2 billion/yr (2006$). Using three 

studies that synthesize data across a large number of individual studies, we estimate between 810 

and 1,100 avoided premature deaths annually in 2020 from reducing ozone to 0.070 ppm, 

leading to total monetized ozone-related benefits of between $6.5 and $9 billion/yr. 

Alternatively, if there is no causal relationship between ozone and mortality, avoided premature 

deaths associated with reduced ozone exposure would be zero and total monetized ozone-related 

morbidity benefits would be $230 million/yr. 

For the selected standard of 0.075 ppm, using the NMMAPS ozone mortality study resulted in 71 

premature deaths avoided and total monetized benefits of $620 million/yr, incremental to 

attainment of the 0.08 ppm standard. Using the three synthesis studies, estimated premature 

deaths avoided for the less stringent standard are between 230 and 320 with total monetized 

ozone benefits between $1.9 and $2.6 billion/yr. Alternatively, if there is no causal relationship 

between ozone and mortality, avoided premature deaths associated with reduced ozone exposure 

would be zero and total monetized ozone-related morbidity benefits would be $73 million/yr. 

For a less stringent standard of 0.079 ppm, using the NMMAPS ozone mortality study resulted in 

24 premature deaths avoided and total monetized benefits of $220 million/yr, incremental to 

attainment of the 0.08 ppm standard. Using the three synthesis studies, estimated premature 

deaths avoided for the less stringent standard are between 80 and 110, with total monetized 

ozone benefits between $640 and $890 million/yr. Alternatively, if there is no causal relationship 

between ozone and mortality, avoided premature deaths associated with reduced ozone exposure 

would be zero and total monetized ozone-related morbidity benefits would be $28 million/yr. 

For a more stringent standard of 0.065 ppm, using the NMMAPS ozone mortality study resulted 

in 450 premature deaths avoided and total monetized benefits of $3.9 billion/yr, incremental to 

attainment of the 0.08 ppm standard. Using the three synthesis studies, estimated premature 

deaths avoided for the more stringent standard are between 1,500 and 2,100, with total 

monetized ozone benefits between $12 and $16 billion/yr. Alternatively, if there is no causal 

relationship between ozone and mortality, avoided premature deaths associated with reduced 

ozone exposure would be zero and total monetized ozone-related morbidity benefits would be 

$420 million/yr. 

These estimates reflect EPA’s interim approach to characterizing the benefits of reducing 

premature mortality associated with ozone exposure. EPA has requested advice from the 

National Academy of Sciences on how best to quantify uncertainty in the relationship between 

ozone exposure and premature mortality in the context of quantifying benefits associated with 

alternative ozone control strategies. We expect to receive this advice later this spring. 

The monetary benefits of visibility improvements from PM2.5 reductions associated with from the 

0.070 modeled attainment strategy in selected federal Class I Areas in 2020 is $160 million/yr. 

In addition to the direct benefits from reducing ozone, attainment of the standards would likely 

result in additional health and welfare benefits because reducing the ozone precursors NOx and 

VOC will also reduce PM2.5. Using both modeled and extrapolated reductions in these precursor 

emissions, we estimated PM-related co-benefits for the four alternative standards. For each 
6-3 

alternative standard, we provide a range of estimated benefits based on several different PM 

mortality effect estimates. These effect estimates were derived from two different sources: the 

published epidemiology literature and an expert elicitation study conducted by EPA in 2006. 

For the 2020 attainment of the 0.075 ppm alternative, incremental to attainment of the 0.08 ppm 

standard, we estimate total ozone and PM2.5-related co-benefits to be between $3.6 and $16 

billion/yr; this range encompasses the expert functions and the ozone mortality functions as well 

as the possibility that there is no causal relationship between ozone and mortality. 

For the 2020 attainment of the 0.079 ppm alternative, incremental to attainment of the 0.08 ppm 

standard, we estimate total ozone and PM2.5-related co-benefits to be between $2 and $11 

billion/yr; this range encompasses the expert functions and the ozone mortality functions as well 

as the possibility that there is no causal relationship between ozone and mortality. 

For the 2020 attainment of the 0.070 ppm alternative, incremental to attainment of the 0.08 ppm 

standard, we estimate total ozone and PM2.5-related co-benefits to be between $6.5 and $27 

billion/yr (3% and 7% discount rates, 2006$); this range encompasses the expert functions and 

the ozone mortality functions as well as the possibility that there is no causal relationship 

between ozone and mortality. 

For the 2020 attainment of the 0.065 ppm alternative, incremental to attainment of the 0.08 ppm 

standard, we estimate total ozone and PM2.5-related co-benefits of between $11 and $42 

billion/yr; this range encompasses the expert functions and the ozone mortality functions as well 

as the possibility that there is no causal relationship between ozone and mortality. 

6.1 Background 

The purpose of this analysis is to assess the human health benefits of attaining the selected 8-

hour ozone standard of 0.075 ppm as well as alternative standards, including 0.079 ppm, 0.070 

ppm, and 0.065 ppm, incremental to attainment of the current 8-hour ozone standard of 0.08 

ppm.3

 We applied a damage function approach similar to those used in several recent U.S. EPA 

regulatory impact analyses, including those for the 2006 Particulate Matter (PM) NAAQS (U.S. 

EPA, 2006) and the Clean Air Interstate Rule (U.S. EPA, 2005). This approach estimates 

changes in individual health and welfare endpoints (specific effects that can be associated with 

changes in air quality) and assigns values to those changes assuming independence of the 

individual values. We calculated total benefits simply by summing the values for all nonoverlapping health and welfare endpoints. This analysis largely builds on both the analytical 

approach used in the 2006 PM NAAQS RIA and the analysis of ozone health impacts reported in 

Hubbell et al. (2005) and the Clean Air Interstate Rule RIA (2005). For a more detailed 

discussion of the principles of benefits analysis used here, please see those documents, as well as 

the EPA Guidelines for Economic Analysis (2000).4,5,6 

 

3

 This is effectively 0.084 ppm due to current rounding conventions. When calculating benefits in 

this chapter we followed the rounding convention and rounded to 0.084 ppm. 4

 U.S. EPA. 2006. Regulatory Impact Analysis, 2006 National Ambient Air Quality Standards 

for Particle Pollution, Chapter 5. Available at http://www.epa.gov/ttn/ecas/ria.html. 
6-4 

We applied a two-stage approach to estimate the benefits of fully attaining each alternative 

standard. In the first stage, we estimated the benefits associated with improving modeled air 

quality using known and available control technologies. These control strategies were sufficient 

to bring some, but not all, areas into attainment with the various alternative standards. Thus, for 

some areas, the benefits computed during this first stage only represented partial attainment (see 

Chapter 3 for details on these control technologies and the results of the air quality modeling). In 

the second stage, we estimated the benefits of fully attaining the standards in all areas by using a 

“rollback” method. This method reduced ozone concentrations at residually nonattaining 

monitors to a level that would just meet the standards (see Appendix 6a for details on this 

methodology). We tested the sensitivity of our results to different assumptions, including the 

choice of health effect estimates from epidemiological studies and economic valuation 

parameters for those health effects. A quantitative assessment of non-health benefits (e.g., 

benefits from reduced ozone-related crop damage) was beyond the scope of this analysis due to 

data and resource limitations. 

For this assessment, we estimated the benefits of reducing ozone and PM concentrations by 

applying illustrative control strategies on ozone precursor emissions to attain alternative ozone 

NAAQS. With the exception of ozone-related premature mortality, we used methods consistent 

with previous PM and ozone benefits assessments. Specifically, we used the same approach to 

analyze PM co-benefits as the 2006 PM NAAQS RIA (U.S. EPA, 2006). In addition, we used a 

nearly identical approach to analyze the ozone benefits as the 2007 Ozone RIA (U.S. EPA, 

2007). 

All estimates of ozone benefits and PM2.5 co-benefits in this chapter are incremental to a baseline 

of national full attainment with 0.08 ppm.7

 This baseline incorporates emission reductions 

projected to be achieved through an array of federal rules such as the Clean Air Interstate and 

Non-Road Diesel Rules, as well as ozone and PM2.5 state implementation plans. Moreover, the 

PM2.5 co-benefits are incremental to an assumption of full attainment of the 2006 PM2.5 NAAQS. 

See Chapter 3 for a complete discussion of the baseline. The PM co-benefits presented in this 

chapter are incremental to the PM benefits estimated in the 2006 PM NAAQS RIA and reflect 

the PM benefits from NOx reductions associated with each ozone control strategy. 

Furthermore, none of the estimates of incidence or monetary benefits provided in this chapter 

include South Coast and San Joaquin Valley Air Basins. Attainment dates will be determined in 

the future through the SIP process based on criteria in the CAA, future air quality data, and 

future rulemakings and are not knowable at this time. For analytical simplicity, and in keeping 

 5

 Hubbell, B., A. Hallberg, D.R. McCubbin, and E. Post. 2005. Health-Related Benefits of 

Attaining the 8-Hr Ozone Standard. Environmental Health Perspectives 113:73–82. 

U.S. EPA. 2000. Guidelines for Preparing Economic Analyses. 

http://yosemite1.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/Guidelines.pdf 6

 U.S. EPA. 2000. Guidelines for Preparing Economic Analyses. 

http://yosemite1.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/Guidelines.pdf 7

 The PM2.5 benefits presented below reflect the NOx emission reductions from the ozone control 

strategy. Reductions from Ocean-Going Vessels burning residual diesel fuel were included both 

East and West in the baseline PM co-benefits, but not included in the ozone baseline for the 

west. See chapter 3 for more details of this rule and its application. 
6-5 

with the proposal analysis, we have chosen to use an analysis year of 2020 and generally assume 

attainment in that year. The exception is the San Joaquin and South Coast California areas where 

SIP submittals for the current standard show that they would have current standard attainment 

dates later than 2020. For these two areas in California, we are assuming a new standard 

attainment date of 2030. Estimates of the costs and benefits of attaining the 0.075 ppm standard 

and the alternate air quality standards for these two areas in 2030 not included in the primary 

benefit analysis and are provided in Appendix 7b. 

For purposes of this analysis, we assume attainment by 2020 for all areas except San Joaquin 

Valley and South Coast air basins in California. The state has submitted plans to EPA for 

implementing the current ozone standard which propose that these two areas of California meet 

that standard by 2024. We have assumed for analytical purposes that the San Joaquin Valley and 

South Coast air basin would attain a new standard in 2030. There are many uncertainties 

associated with the year 2030 analysis. Between 2020 and 2030 several federal air quality rules 

are likely to further reduce emissions of NOx and VOC, such as, but not limited to National rules 

for Diesel Locomotives, Diesel Marine Vessels, and Small Nonroad Gasoline Engines. These 

emission reductions should lower ambient levels of ozone in California between 2020 and 2030. 

Complete emissions inventories as well as air quality modeling were not available for this year 

2030 analysis. Due to these limitations, it is not possible to adequately model 2030 air quality 

changes that are required to develop robust controls strategies with associated costs and benefits. 

In order to provide a rough approximation of the costs and benefits of attaining 0.075 ppm and 

the alternate standards in San Joaquin and South Coast air basins, we have relied on the available 

data. Available data includes emission inventories, which do not include any changes in 

stationary source emissions beyond 2020, and 2020 supplemental air quality modeling. This 

data was used to develop extrapolated costs and benefits of 2030 attainment. These results 

indicate that benefits would be between $0.13 billion and $2.0 billion for the selected ozone 

standard of 0.075 ppm in 2030. To view the complete analysis for the San Joaquin Valley and 

South Coast air basins, see Appendix 7b.3 

The remainder of this chapter describes the data and methods used in this analysis, along with 

the results. Appendix 6a of this RIA provides additional details of the analysis. Section 6.2 

discusses the probabilistic framework for the benefits analysis and how key uncertainties are 

addressed in the analysis. Section 6.3 discusses the literature on ozone- and PM-related health 

effects and describes the specific set of health impact functions we used in the benefits analysis. 

Section 6.4 describes the economic values selected to estimate the dollar value of ozone- and 

PM- related health impacts. Finally, Section 6.5 presents the results and implications of the 

analysis. 

6.2 Characterizing Uncertainty: Moving Toward a Probabilistic Framework for 

Benefits Assessment 

The National Research Council (NRC) (2002) highlighted the need for EPA to conduct rigorous 

quantitative analysis of uncertainty in its benefits estimates and to present these estimates to 

decision makers in ways that foster an appropriate appreciation of their inherent uncertainty. In 

response to these comments, EPA’s Office of Air and Radiation (OAR) is developing a 

comprehensive strategy for characterizing the aggregate impact of uncertainty in key modeling 
6-6 

elements on both health incidence and benefits estimates. Components of that strategy include 

emissions modeling, air quality modeling, health effects incidence estimation, and valuation. 

Two aspects of OAR’s strategy have been used in several recent RIAs and are also employed in 

this analysis.8,9,10 First, we used Monte Carlo methods for estimating characterizing random 

sampling error associated with the concentration response functions from epidemiological 

studies and economic valuation functions. Monte Carlo simulation uses random sampling from 

distributions of parameters to characterize the effects of uncertainty on output variables, such as 

incidence of premature mortality. Specifically, we used Monte Carlo methods to generate 

confidence intervals around the estimated health impact and dollar benefits. The reported 

standard errors in the epidemiological studies determined the distributions for individual effect 

estimates. Table 6.4 describes the distributions for unit values. 

Second, because characterization of random statistical error omits important sources of 

uncertainty (e.g., in the functional form of the model—e.g., whether or not a threshold may exist) 

we used a recently completed expert elicitation of the concentration response function describing 

the relationship between premature mortality and ambient PM2.5 concentration.11 Use of the 

expert elicitation and incorporation of the standard errors approaches provide insights into the 

likelihood of different outcomes and about the state of knowledge regarding the benefits 

estimates. Both approaches have different strengths and weaknesses, which are fully described in 

Chapter 5 of the PM NAAQS RIA. 

In benefit analyses of air pollution regulations conducted to date, the estimated impact of 

reductions in premature mortality has accounted for 85% to 95% of total benefits. Therefore, it is 

particularly important to attempt to characterize the uncertainties associated with reductions in 

premature mortality. The health impact functions used to estimate avoided premature deaths 

associated with reductions in ozone have associated standard errors that represent the statistical 

errors around the effect estimates in the underlying epidemiological studies.12 In our results, we 

report credible intervals based on these standard errors, reflecting the uncertainty in the estimated 

change in incidence of avoided premature deaths. We also provide multiple estimates, to reflect 

model uncertainty between alternative study designs. In addition, we characterize the uncertainty 

introduced by the inability of existing empirical studies to discern whether the relationship 

 

8

 U.S. Environmental Protection Agency, 2004a. Final Regulatory Analysis: Control of 

Emissions from Nonroad Diesel Engines. EPA420-R-04-007. Prepared by Office of Air and 

Radiation. Available at http://www.epa.gov/nonroad-diesel/2004fr/420r04007.pdf 9

 U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis for the Clean Air 

Interstate Rule. EPA 452/-03-001. Prepared by Office of Air and Radiation. Available at: 

http://www.epa.gov/interstateairquality/tsd0175.pdf 10 U.S. Environmental Protection Agency, 2006. Regulatory Impact Analysis for the PM 

NAAQS. EPA Prepared by Office of Air and Radiation. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf 11 Expert elicitation is a formal, highly structured and well documented process whereby expert 

judgments, usually of multiple experts, are obtained (Ayyb, 2002). 

12 Health impact functions measure the change in a health endpoint of interest, such as hospital 

admissions, for a given change in ambient ozone or PM concentration. 
6-7 

between ozone and pre-mature mortality is causal by providing an effect estimate preconditioned 

on an assumption that the effect estimate for pre-mature mortality from ozone is zero. 

For premature mortality associated with exposure to PM, we follow the same approach used in 

the RIA for 2006 PM NAAQS (U.S. EPA, 2006), presenting several empirical estimates of 

premature deaths avoided, and a set of twelve estimates based on results of the expert elicitation 

study.13 Even these multiple characterizations, including confidence intervals, omit the 

contribution to overall uncertainty of uncertainty in air quality changes, baseline incidence rates, 

populations exposed and transferability of the effect estimate to diverse locations. Furthermore, 

the approach presented here does not yet include methods for addressing correlation between 

input parameters and the identification of reasonable upper and lower bounds for input 

distributions characterizing uncertainty in additional model elements. As a result, the reported 

confidence intervals and range of estimates give an incomplete picture about the overall 

uncertainty in the estimates. This information should be interpreted within the context of the 

larger uncertainty surrounding the entire analysis. 

6.3 Health Impact Functions 

Health impact functions measure the change in a health endpoint of interest, such as hospital 

admissions, for a given change in ambient ozone or PM concentration. Health impact functions 

are derived from primary epidemiology studies, meta-analyses of multiple epidemiology studies, 

or expert elicitations. A standard health impact function has four components: 1) an effect 

estimate from a particular study; 2) a baseline incidence rate for the health effect (obtained from 

either the epidemiology study or a source of public health statistics such as the Centers for 

Disease Control); 3) the size of the potentially affected population; and 4) the estimated change 

in the relevant ozone or PM summary measures. 

A typical health impact function might look like: 

( 1) = 0 ⋅ − ⋅ x

y y eβ Δ Δ

where y0 is the baseline incidence (the product of the baseline incidence rate times the potentially 

affected population), β is the effect estimate, and Δx is the estimated change in the summary 

ozone measure. There are other functional forms, but the basic elements remain the same. 

Chapter 3 described the ozone and PM air quality inputs to the health impact functions. The 

following subsections describe the sources for each of the other elements: size of potentially 

affected populations; effect estimates; and baseline incidence rates. 

 

13 Industrial Economics, Inc. 2006. Expanded Expert Judgment Assessment of the ConcentrationResponse Relationship Between PM2.5 Exposure and Mortality. Prepared for EPA Office of Air 

Quality Planning and Standards, September. Available at: 

http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_report.pdf 
6-8 

6.3.1 Potentially Affected Populations 

The starting point for estimating the size of potentially affected populations is the 2000 U.S. 

Census block level dataset (Geolytics 2002). Benefits Modeling and Analysis Program 

(BenMAP) incorporates 250 age/gender/race categories to match specific populations potentially 

affected by ozone and other air pollutants. The software constructs specific populations matching 

the populations in each epidemiological study by accessing the appropriate age-specific 

populations from the overall population database. BenMAP projects populations to 2020 using 

growth factors based on economic projections (Woods and Poole Inc. 2001). 

6.3.2 Effect Estimate Sources 

The most significant monetized benefits of reducing ambient concentrations of ozone and PM 

are attributable to reductions in human health risks. EPA’s Ozone and PM Criteria Documents 

outline numerous health effects known or suspected to be linked to exposure to ambient ozone 

and PM (US EPA, 2006; US EPA, 2005; Anderson et al., 2004). EPA recently evaluated the PM 

literature for use in the benefits analysis for the 2006 PM NAAQS RIA. Because we use the 

same literature for the PM co-benefits analysis in this RIA, we do not provide a detailed 

discussion of individual effect estimates for PM in this section. Instead, we refer the reader to the 

2006 PM NAAQS RIA for details.14 

More than one thousand new ozone health and welfare studies have been published since EPA 

issued the 8-hour ozone standard in 1997. Many of these studies investigated the impact of ozone 

exposure on health effects such as changes in lung structure and biochemistry; lung 

inflammation; asthma exacerbation and causation; respiratory illness-related school absence; 

hospital and emergency room visits for asthma and other respiratory causes; and premature 

death. 

We were not able to separately quantify all of the PM and ozone health effects that have been 

reported in the ozone and PM criteria documents in this analysis for four reasons: (1) the 

possibility of double counting (such as hospital admissions for specific respiratory diseases); 

(2) uncertainties in applying effect relationships that are based on clinical studies to the 

potentially affected population; (3) the lack of an established concentration-response 

relationship; or (4) the inability to appropriately value the effect (for example, changes in forced 

expiratory volume) in economic terms. Table 6.1 lists the human health and welfare effects of 

pollutants affected by the alternative standards. Table 6.2 lists the health endpoints included in 

this analysis. 

In order to select appropriate epidemiological studies to use for our effect estimates, we applied 

several criteria to determine the set of studies that is likely to provide the best estimates of effects 

in the U.S. To account for the potential effects of different health care systems or underlying 

health status of populations, we gave preference to U.S. studies over non-U.S. studies. In 

addition, due to the potential for confounding by co-pollutants, we gave preference to effect 

 

14 U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis for the PM 

NAAQS. EPA Prepared by Office of Air and Radiation. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf pp. 5-29. 
6-9 

estimates from models that included both ozone and PM over effect estimates from singlepollutant models.15,16

A number of endpoints that are not health-related may also contribute significant monetized 

benefits. Potential welfare benefits associated with ozone exposure include increased outdoor 

worker productivity; increased yields for commercial and non-commercial crops; increased 

commercial forest productivity; reduced damage to urban ornamental plants; increased 

recreational demand for undamaged forest aesthetics; and reduced damage to ecosystem 

functions (U.S. EPA 1999, 2006). Although we estimate the value of increased outdoor worker 

productivity, estimation of other welfare effects is beyond the scope of this analysis. 

 

15 U.S. Science Advisory Board. 2004. Advisory Plans for Health Effects Analysis in the 

Analytical Plan for EPA’s Second Prospective Analysis –Benefits and Costs of the Clean Air 

Act, 1990—2020. EPA-SAB-COUNCIL-ADV-04-004. 

16 National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed 

Air Pollution Regulations. Washington, DC: The National Academies Press. 
6-10 

Table 6.1: Human Health and Welfare Effects of Ozone and PM2.5 

Pollutant/Effect 

Quantified and Monetized in Base 

Estimatesa Unquantified Effectsh

—Changes in: 

PM/Healthb Premature mortality based on both cohort 

study estimates and on expert elicitationc,d

Bronchitis: chronic and acute 

Hospital admissions: respiratory and 

cardiovascular 

Emergency room visits for asthma 

Nonfatal heart attacks (myocardial infarction) 

Lower and upper respiratory illness 

Minor restricted-activity days 

Work loss days 

Asthma exacerbations (asthmatic population) 

Respiratory symptoms (asthmatic population) 

Infant mortality 

Subchronic bronchitis cases 

Low birth weight 

Pulmonary function 

Chronic respiratory diseases other than 

chronic bronchitis 

Non-asthma respiratory emergency room 

visits 

UVb exposure (+/-)e

PM/Welfare Visibility in Southeastern, southwestern and 

California Class I areas 

Visibility in northeastern and Midwestern 

Class I areas 

Household soiling 

Visibility in residential and non-Class I 

areas 

UVb exposure (+/-)e

Ozone/Healthf Premature mortality: short-term exposures 

Hospital admissions: respiratory 

Emergency room visits for asthma 

Minor restricted-activity days 

School loss days 

Asthma attacks 

Acute respiratory symptoms 

Cardiovascular emergency room visits 

Chronic respiratory damage 

Premature aging of the lungs 

Non-asthma respiratory emergency room 

visits 

UVb exposure (+/-)e

Ozone/Welfare Decreased outdoor worker productivity 

Yields for commercial crops 

Yields for commercial forests and 

noncommercial crops 

Damage to urban ornamental plants 

Recreational demand from damaged forest 

aesthetics 

Ecosystem functions 

UVb exposure (+/-)e

a

 Primary quantified and monetized effects are those included when determining the primary estimate of total monetized benefits 

of the alternative standards. b

 In addition to primary economic endpoints, there are a number of biological responses that have been associated with PM health

effects including morphological changes and altered host defense mechanisms. The public health impact of these biological 

responses may be partly represented by our quantified endpoints. c

 Cohort estimates are designed to examine the effects of long-term exposures to ambient pollution, but relative risk estimates 

may also incorporate some effects due to shorter term exposures (see Kunzli, 2001 for a discussion of this issue). d

 While some of the effects of short-term exposure are likely to be captured by the cohort estimates, there may be additional 

premature mortality from short-term PM exposure not captured in the cohort estimates included in the primary analysis. e

 May result in benefits or disbenefits. Appendix 6d includes a sensitivity analysis that partially quantifies this endpoint. This 

analysis was performed for the purposes of this RIA only. f

 In addition to primary economic endpoints, there are a number of biological responses that have been associated with ozone 

health including increased airway responsiveness to stimuli, inflammation in the lung, acute inflammation and respiratory cell 

damage, and increased susceptibility to respiratory infection. The public health impact of these biological responses may be 

partly represented by our quantified endpoints. g

 The categorization of unquantified toxic health and welfare effects is not exhaustive. h

 Health endpoints in the unquantified benefits column include both a) those for which there is not consensus on causality and b) 

those for which causality has been determined but empirical data are not available to allow calculation of benefits. 
6-11 

Table 6.2: Ozone and PM Related Health Endpoints Basis for the Concentration-Response 

Function Associated with that Endpoint, and Sub-Populations for which They Were 

Computed 

Endpoint Pollutant Study Study Population 

Premature Mortality 

Premature 

mortality—daily 

time series, nonaccidental 

O3 (8-hour max) 

O3 (8-hour max) 

O3 (8-hour max) 

O3 (8-hour max) 

Bell et al (2004) (NMMAPS study) 

Meta-analyses: 

Bell et al (2005) 

Ito et al (2005) 

Levy et al (2005) 

All ages 

Premature 

mortality—cohort 

study, all-cause 

PM2.5 (annual 

avg) 

Pope et al. (2002) 

Laden et al. (2006) 

>29 years 

>25 years 

Premature 

mortality, total 

exposures 

PM2.5 (annual 

avg) 

Expert Elicitation (IEc, 2006) >24 years 

Premature 

mortality—allcause 

PM2.5 (annual 

avg) 

Woodruff et al. (1997) Infant (<1 year) 

Chronic Illness 

Chronic bronchitis PM2.5 (annual 

avg) 

Abbey et al. (1995) >26 years 

Nonfatal heart 

attacks 

PM2.5 (24-hour 

avg) 

Peters et al. (2001) Adults (>18 years) 

Hospital Admissions 

Pooled estimate: 

Schwartz (1995)—ICD 460–519 (all resp) 

Schwartz (1994a; 1994b)—ICD 480–486 

(pneumonia) 

Moolgavkar et al. (1997)—ICD 480–487 

(pneumonia) 

Schwartz (1994b)—ICD 491–492, 494–496 

(COPD) 

Moolgavkar et al. (1997)—ICD 490–496 

(COPD) 

>64 years 

O3 (24-hour avg) 

Burnett et al. (2001) <2 years 

PM2.5 (24-hour 

avg) 

Pooled estimate: 

Moolgavkar (2003)—ICD 490–496 (COPD) 

Ito (2003)—ICD 490–496 (COPD) 

>64 years 

PM2.5 (24-hour 

avg) 

Moolgavkar (2000)—ICD 490–496 (COPD) 20–64 years 

PM2.5 (24-hour 

avg) 

Ito (2003)—ICD 480–486 (pneumonia) >64 years 

Respiratory 

PM2.5 (24-hour 

avg) 

Sheppard (2003)—ICD 493 (asthma) <65 years 

PM2.5 (24-hour 

avg) 

Pooled estimate: 

Moolgavkar (2003)—ICD 390–429 (all 

cardiovascular) 

Ito (2003)—ICD 410–414, 427–428 (ischemic 

heart disease, dysrhythmia, heart failure) 

Cardiovascular >64 years 

PM2.5 (24-hour 

avg) 

Moolgavkar (2000)—ICD 390–429 (all 

cardiovascular) 

20–64 years 

Asthma-related 

ER visits 

O3 (8-hour max) Pooled estimate: 

Jaffe et al (2003) 5–34 years 
6-12 

Endpoint Pollutant Study Study Population 

Peel et al (2005) 

Wilson et al (2005) 

All ages 

All ages 

Asthma-related 

ER visits (con’t) 

PM2.5 (24-hour 

avg) 

Norris et al. (1999) 0–18 years 

Other Health Endpoints 

Acute bronchitis PM2.5 (annual 

avg) 

Dockery et al. (1996) 8–12 years 

Upper respiratory 

symptoms 

PM10 (24-hour 

avg) 

Pope et al. (1991) Asthmatics, 9–11 

years 

Lower respiratory 

symptoms 

PM2.5 (24-hour 

avg) 

Schwartz and Neas (2000) 7–14 years 

Asthma 

exacerbations 

PM2.5 (24-hour 

avg) 

Pooled estimate: 

Ostro et al. (2001) (cough, wheeze and 

shortness of breath) 

Vedal et al. (1998) (cough) 

6–18 yearsa

Work loss days PM2.5 (24-hour 

avg) 

Ostro (1987) 18–65 years 

School absence 

days O3 (8-hour avg) 

O3 (1-hour max) 

Pooled estimate: 

Gilliland et al. (2001) 

Chen et al. (2000) 

5–17 yearsb

Minor Restricted O3 (24-hour avg) Ostro and Rothschild (1989) 18–65 years 

Activity Days 

(MRADs) 

PM2.5 (24-hour 

avg) 

Ostro and Rothschild (1989) 18–65 years 

a

 The original study populations were 8 to 13 for the Ostro et al. (2001) study and 6 to 13 for the Vedal et 

al. (1998) study. Based on advice from the Science Advisory Board Health Effects Subcommittee 

(SAB-HES), we extended the applied population to 6 to 18, reflecting the common biological basis for 

the effect in children in the broader age group. See: U.S. Science Advisory Board. 2004. Advisory 

Plans for Health Effects Analysis in the Analytical Plan for EPA’s Second Prospective Analysis –

Benefits and Costs of the Clean Air Act, 1990—2020. EPA-SAB-COUNCIL-ADV-04-004. See also 

National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air 

Pollution Regulations. Washington, DC: The National Academies Press. 

b

 Gilliland et al. (2001) studied children aged 9 and 10. Chen et al. (2000) studied children 6 to 11. Based 

on recent advice from the National Research Council and the EPA SAB-HES, we have calculated 

reductions in school absences for all school-aged children based on the biological similarity between 

children aged 5 to 17.
6-13 

6.3.2.1 Premature Mortality Effects Estimates

While particulate matter is the criteria pollutant most clearly associated with premature 

mortality, recent research suggests that short-term repeated ozone exposure also likely 

contributes to premature death. The 2006 Ozone Criteria Document states, “Consistent with 

observed ozone-related increases in respiratory- and cardiovascular-related morbidity, several 

newer multi-city studies, single-city studies, and several meta-analyses of these studies have 

provided relatively strong epidemiologic evidence for associations between short-term ozone 

exposure and all-cause mortality, even after adjustment for the influence of season and PM” 

(EPA, 2006: E-17). The epidemiologic data are also supported by recent experimental data from 

both animal and human studies, which provide evidence suggestive of plausible pathways by 

which risk of respiratory or cardiovascular morbidity and mortality could be increased by 

ambient ozone. With respect to short-term exposure, the Ozone Criteria Document concludes, 

“This overall body of evidence is highly suggestive that ozone directly or indirectly contributes 

to non-accidental and cardiopulmonary-related mortality, but additional research is needed to 

more fully establish underlying mechanisms by which such effects occur” (pg. E-18). 

With respect to the time-series studies, the conclusion regarding the relationship between shortterm exposure and premature mortality is based, in part, upon recent city-specific time-series 

studies such as the Schwartz (2004) analysis in Houston and the Huang et al. (2004) analysis in 

Los Angeles.17 This conclusion is also based on recent meta-analyses by Bell et al. (2005), Ito et 

al. (2005), and Levy et al. (2005), and a new analysis of the National Morbidity, Mortality, and 

Air Pollution Study (NMMAPS) data set by Bell et al. (2004), which specifically sought to 

disentangle the roles of ozone, PM, weather-related variables, and seasonality. The 2006 Criteria 

Document states that “the results from these meta-analyses, as well as several single- and 

multiple-city studies, indicate that co-pollutants generally do not appear to substantially 

confound the association between ozone and mortality” (p. 7-103). However, CASAC raised 

questions about the implications of these time-series results in a policy context. Specifically, 

CASAC emphasized that “...while the time-series study design is a powerful tool to detect very 

small effects that could not be detected using other designs, it is also a blunt tool” (Henderson, 

2006: 3). They point to findings (e.g., Stieb et al., 2002, 2003) that indicated associations 

between premature mortality and all of the criteria pollutants, indicating that “findings of timeseries studies do not seem to allow us to confidently attribute observed effects to individual 

pollutants” (id.). They note that “not only is the interpretation of these associations complicated 

by the fact that the day-to-day variation in concentrations of these pollutants is, to a varying 

degree, determined by meteorology, the pollutants are often part of a large and highly correlated 

mix of pollutants, only a very few of which are measured” (id.). Even with these uncertainties, 

the CASAC Ozone Panel, in its review of EPA’s Staff Paper, found “...premature total nonaccidental and cardiorespiratory mortality for inclusion in the quantitative risk assessment to be 

appropriate.” 

 

17 For an exhaustive review of the city-specific time-series studies considered in the ozone staff 

paper, see: U.S. Environmental Protection Agency, 2007. Review of the National Ambient Air 

Quality Standards for Ozone: Policy Assessment of Scientific and Technical Information. 

Prepared by the Office of Air and Radiation. Available at 

http://www.epa.gov/ttn/naaqs/standards/ozone/data/2007_01_ozone_staff_paper.pdf. pp. 5-36. 
6-14 

Consistent with the methodology used in the ozone risk assessment found in the Characterization 

of Health Risks found in the Review of the National Ambient Air Quality Standards for Ozone: 

Policy Assessment of Scientific and Technical Information, we included ozone mortality in the 

primary health effects analysis, with the recognition that the exact magnitude of the effects 

estimate is subject to continuing uncertainty. We used estimates from the Bell et al. (2004) 

NMMAPS analysis, as well as effect estimates from the three meta-analyses. In addition, we 

include the possibility that there is not a causal association between ozone and mortality, i.e., that 

the effect estimate for premature mortality could be zero. EPA expects to receive advice from the 

National Academy of Sciences on how best to quantify uncertainty in the relationship between 

ozone exposure and premature mortality in the context of quantifying benefits associated with 

alternative ozone control strategies later this spring. 

We estimate the change in mortality incidence and estimated credible interval18 resulting from 

application of the effect estimate from each study and present them separately to reflect 

differences in the study designs and assumptions about causality. However, it is important to 

note that this procedure only captures the uncertainty in the underlying epidemiological work, 

and does not capture other sources of uncertainty, such as uncertainty in the estimation of 

changes in air pollution exposure (Levy et al., 2000). 

Ozone Exposure Metric. Both the NMMAPS analysis and the individual time series studies 

upon which the meta analyses were based use the 24-hour average or 1-hour maximum ozone 

levels as exposure metrics. The 24-hour average is not the most relevant ozone exposure metric 

to characterize population-level exposure. Given that the majority of the people tend to be 

outdoors during the daylight hours and concentrations are highest during the daylight hours, the 

24-hour average metric is not appropriate. Moreover, the 1-hour maximum metric uses an 

exposure window different than that that used for the current ozone NAAQS. Together, this 

means that the most biologically relevant metric, and the one used in the ozone NAAQS since 

1997 is the 8-hour maximum standard. Thus, although our analysis at proposal calculated impact 

functions based on either the 24 hour average or 1-hour maximum ozone levels originally 

reported in the epidemiogical studies, for the final rule analysis, we have converted ozone 

mortality health impact functions that use a 24-hour average or 1-hour maximum ozone metric to 

maximum 8-hour average ozone concentration using standard conversion functions. 

This practice is consistent both with the available exposure modeling and with the form of the 

current ozone standard. This conversion also does not affect the relative magnitude of the health 

impact function. An equivalent change in the 24-hour average, 1-hour maximum and 8-hour 

maximum will provide the same overall change in incidence of a health effect. The conversion 

ratios are based on observed relationships between the 24-hour average and 8-hour maximum 

ozone values. For example, in the Bell et al., 2004 analysis of ozone-related premature mortality, 

the authors found that the relationship between the 24-hour average, the 8-hour maximum, and 

the 1-hour maximum was 2:1.5:1, so that the derived health impact effect estimate based on the 

1-hour maximum should be half that of the effect estimate based on the 24-hour values (and the 

8-hour maximum three-quarters of the 24-hour effect estimate). 

 

18 A credible interval is a posterior probability interval used in Bayesian statistics, which is 

similar to a confidence interval used in frequentist statistics. 
6-15 

In EPA’s risk analysis for the ozone NAAQS rule, mortality risks were estimated for 8 urban 

areas based on application of city-specific effect estimates derived from single city studies and 

from the Bell et al (2004) and Huang et al (2005) multi-city studies. These effect estimates were 

based on 24-hour average daily ozone concentrations. While it may have been preferable to use 

shorter averaging times, conversions from daily averages to shorter averaging times was not 

appropriate due to the lack of city-specific conversion factors. In our benefits analysis for the 

ozone NAAQS, we applied national effect estimates based on the pooled multi-city results 

reported in Bell et al (2004) and the three meta-analysis studies. Bell et al (2004), Bell et al 

(2005), Levy et al (2005), and Ito et al (2005) all provide national conversion ratios between 

daily average and 8-hour and 1-hour maxima, based on national data. However, these 

conversions were not specific to the ozone “warm” season which was the period used in the 

health risk assessment. As such we were able to convert the national C-R function parameters 

from daily average to 8-hour average, albeit with the introduction of additional uncertainty due 

to the use of effect estimates based on a mixture of warm season and all year data in the 

epidemiological studies. Given the heterogeneity in ratios of daily average to 8-hour and 1-hour 

maxima that exists between cities, it would be inappropriate to use national conversion ratios to 

adjust C-R functions for individual cities. 

6.3.2.2 Respiratory Hospital Admissions Effect Estimates

Detailed hospital admission and discharge records provide data for an extensive body of 

literature examining the relationship between hospital admissions and air pollution. This is 

especially true for the portion of the population aged 65 and older, because of the availability of 

detailed Medicare records. In addition, there is one study (Burnett et al., 2001) providing an 

effect estimate for respiratory hospital admissions in children under two. 

Because the number of hospital admission studies we considered is so large, we used results 

from a number of studies to pool some hospital admission endpoints. Pooling is the process by 

which multiple study results may be combined in order to produce better estimates of the effect 

estimate, or β. For a complete discussion of the pooling process, see Abt (2005).19 To estimate 

total respiratory hospital admissions associated with changes in ambient ozone concentrations for 

adults over 65, we first estimated the change in hospital admissions for each of the different 

effects categories that each study provided for each city. These cities included Minneapolis, 

Detroit, Tacoma and New Haven. To estimate total respiratory hospital admissions for Detroit, 

we added the pneumonia and COPD estimates, based on the effect estimates in the Schwartz 

study (1994b). Similarly, we summed the estimated hospital admissions based on the effect 

estimates the Moolgavkar study reported for Minneapolis (Moolgavkar et al., 1997). To estimate 

total respiratory hospital admissions for Minneapolis using the Schwartz study (1994a), we 

simply estimated pneumonia hospital admissions based on the effect estimate. Making this 

assumption that pneumonia admissions represent the total impact of ozone on hospital 

admissions in this city will give some weight to the possibility that there is no relationship 

between ozone and COPD, reflecting the equivocal evidence represented by the different studies. 

We then used a fixed-effects pooling procedure to combine the two total respiratory hospital 

admission estimates for Minneapolis. Finally, we used random effects pooling to combine the 

 

19 Abt Associates, Incorporated. Environmental Benefits Mapping and Analysis Program, 

Technical Appendices. May 2005. pp. I-3 
6-16 

results for Minneapolis and Detroit with results from studies in Tacoma and New Haven from 

Schwartz (1995). As noted above, this pooling approach incorporates both the precision of the 

individual effect estimates and between-study variability characterizing differences across study 

locations. 

6.3.2.3 Asthma-Related Emergency Room Visits Effect Estimates

We used three studies as the source of the concentration-response functions we used to estimate 

the effects of ozone exposure on asthma-related emergency room (ER) visits: Peel et al. (2005); 

Wilson et al. (2005); and Jaffe et al. (2003). We estimated the change in ER visits using the 

effect estimate(s) from each study and then pooled the results using the random effects pooling 

technique (see Abt, 2005). The study by Jaffe et al. (2003) examined the relationship between 

ER visits and air pollution for populations aged five to 34 in the Ohio cities of Cleveland, 

Columbus and Cincinnati from 1991 through 1996. In single-pollutant Poisson regression 

models, ozone was linked to asthma visits. We use the pooled estimate across all three cities as 

reported in the study. The Peel et al. study (2005) estimated asthma-related ER visits for all ages 

in Atlanta, using air quality data from 1993 to 2000. Using Poisson generalized estimating 

equations, the authors found a marginal association between the maximum daily 8-hour average 

ozone level and ER visits for asthma over a 3-day moving average (lags of 0, 1, and 2 days) in a 

single pollutant model. Wilson et al. (2005) examined the relationship between ER visits for 

respiratory illnesses and asthma and air pollution for all people residing in Portland, Maine from 

1998–2000 and Manchester, New Hampshire from 1996–2000. For all models used in the 

analysis, the authors restricted the ozone data incorporated into the model to the months ozone 

levels are usually measured, the spring-summer months (April through September). Using the 

generalized additive model, Wilson et al. (2005) found a significant association between the 

maximum daily 8-hour average ozone level and ER visits for asthma in Portland, but found no 

significant association for Manchester. Similar to the approach used to generate effect estimates 

for hospital admissions, we used random effects pooling to combine the results across the 

individual study estimates for ER visits for asthma. The Peel et al. (2005) and Wilson et al. 

(2005) Manchester estimates were not significant at the 95 percent level, and thus, the 

confidence interval for the pooled incidence estimate based on these studies includes negative 

values. This is an artifact of the statistical power of the studies, and the negative values in the 

tails of the estimated effect distributions do not represent improvements in health as ozone 

concentrations are increased. Instead, these should be viewed as a measure of uncertainty due to 

limitations in the statistical power of the study. We included both hospital admissions and ER 

visits as separate endpoints associated with ozone exposure because our estimates of hospital 

admission costs do not include the costs of ER visits and most asthma ER visits do not result in a 

hospital admission. 

6.3.2.4 Minor Restricted Activity Days Effects Estimate

Minor restricted activity days (MRADs) occur when individuals reduce most usual daily 

activities and replace them with less-strenuous activities or rest, but do not miss work or school. 

We estimated the effect of ozone exposure on MRADs using a concentration-response function 

derived from Ostro and Rothschild (1989). These researchers estimated the impact of ozone and 

PM2.5 on MRAD incidence in a national sample of the adult working population (ages 18 to 65) 

living in metropolitan areas. We developed separate coefficients for each year of the Ostro and 
6-17 

Rothschild analysis (1976–1981), which we then combined for use in EPA’s analysis. The effect 

estimate used in the impact function is a weighted average of the coefficients in Ostro and 

Rothschild (1989, Table 4), using the inverse of the variance as the weight. 

6.3.2.5 School Absences Effect Estimate

Children may be absent from school due to respiratory or other acute diseases caused, or 

aggravated by, exposure to air pollution. Several studies have found a significant association 

between ozone levels and school absence rates. We use two studies (Gilliland et al., 2001; Chen 

et al., 2000) to estimate changes in school absences resulting from changes in ozone levels. The 

Gilliland et al. study estimated the incidence of new periods of absence, while the Chen et al. 

study examined daily absence rates. We converted the Gilliland et al. estimate to days of absence 

by multiplying the absence periods by the average duration of an absence. We estimated 1.6 days 

as the average duration of a school absence, the result of dividing the average daily school 

absence rate from Chen et al. (2000) and Ransom and Pope (1992) by the episodic absence 

duration from Gilliland et al. (2001). Thus, each Gilliland et al. period of absence is converted 

into 1.6 absence days. 

Following recent advice from the National Research Council (2002), we calculated reductions in 

school absences for the full population of school age children, ages five to 17. This is consistent 

with recent peer-reviewed literature on estimating the impact of ozone exposure on school 

absences (Hall et al. 2003). We estimated the change in school absences using both Chen et al. 

(2000) and Gilliland et al. (2001) and then, similar to hospital admissions and ER visits, pooled 

the results using the random effects pooling procedure. 

6.3.2.6 Outdoor Worker Productivity

To monetize benefits associated with increased worker productivity resulting from improved 

ozone air quality, we used information reported in Crocker and Horst (1981). Crocker and Horst 

examined the impacts of ozone exposure on the productivity of outdoor citrus workers. The 

study measured productivity impacts. Worker productivity is measuring the value of the loss in 

productivity for a worker who is at work on a particular day, but due to ozone, cannot work as 

hard. It only applies to outdoor workers, like fruit and vegetable pickers, or construction workers. 

Here, productivity impacts are measured as the change in income associated with a change in 

ozone exposure, given as the elasticity of income with respect to ozone concentration. The 

reported elasticity translates a ten percent reduction in ozone to a 1.4 percent increase in income. 

Given the national median daily income for outdoor workers engaged in strenuous activity 

reported by the U.S. Census Bureau (2002), $68 per day (2000$), a ten percent reduction in 

ozone yields about $0.97 in increased daily wages. We adjust the national median daily income 

estimate to reflect regional variations in income using a factor based on the ratio of county 

median household income to national median household income. No information was available 

for quantifying the uncertainty associated with the central valuation estimate. Therefore, no 

uncertainty analysis was conducted for this endpoint. 
6-18 

6.3.2.7 Visibility Benefits

Changes in the level of ambient PM2.5 caused by the reduction in emissions associated with the 

alternative standards will change the level of visibility throughout the United States. Increases in 

PM concentrations cause increases in light extinction, a measure of how much the components of 

the atmosphere absorb light. This chapter contains an estimate of the monetized benefits of 

improved visibility associated with the simulated emission control strategy to attain the 0.070 

ppm ozone standard. The methodology we followed to estimate changes in visibility benefits is 

consistent with the PM2.5 RIA (EPA, 2006), which is described on page 5-60 of that document. 

6.3.2.8 Other Unquantified Effects

Direct Ozone Effects on Vegetation. The Ozone Criteria Document notes that “current ambient 

concentrations in many areas of the country are sufficient to impair growth of numerous common 

and economically valuable plant and tree species” (U.S. EPA, 2006, page 9-1). Changes in 

ground-level ozone resulting from the implementation of alternative ozone standards may affect 

crop and forest yields throughout the affected area. Recent scientific studies have also found that 

at sufficient concentrations ozone negatively affects the quality or nutritive value of some 

sensitive crops (U.S. EPA, 2006, page 9-16). 

Well-developed techniques exist to provide monetary estimates of these benefits to agricultural 

producers and to consumers. These techniques use models of planting decisions, yield response 

functions, and the supply of and demand for agricultural products. The resulting welfare 

measures are based on predicted changes in market prices and production costs. Models also 

exist to measure benefits to silvicultural producers and consumers. There is considerable 

uncertainty, however, in such estimates, including the fact that the extensive management of 

agricultural crops may mitigate the potential O3-related effects. For this reason, the estimates of 

economic crop loss developed using the updated AGSIM model were not relied on for this 

analysis of alternative O3 standards. In addition, these models have not been adapted for use in 

analyzing ozone-related forest impacts. Again, because there commercial activities are highly 

managed the potential benefits of alternative O3 standards are uncertain. Because of these 

uncertainties and resource limitations, we are unable to provide benefits estimates for the 

commercial production of agricultural and silvaculture commodities. 

An additional welfare benefit of reducing ambient ozone concentrations is the economic value of 

reduced aesthetic injury to forests. There is sufficient scientific information available to reliably 

establish that ambient ozone causes visible injury to foliage and impair the growth of some 

sensitive plant species (U.S. EPA, 2006, page 9-19). However, present analytic tools and 

resources preclude us from quantifying the benefits of improved forest aesthetics. 

Urban ornamentals (floriculture and nursery crops) are an additional vegetation category that 

may experience negative effects from exposure to ambient ozone and may affect large economic 

sectors. However, the absence of adequate exposure-response functions and economic damage 

functions for the potential range of effects relevant to these types of vegetation precludes us from 

quantifying these direct economic benefits. The farm production value of ornamental crops was 

estimated at over $14 billion in 2003 (USDA, 2004). This is therefore a potentially important 

welfare effects category, but information and valuation methods are not available to allow for 
6-19 

plausible estimates of the percentage of these expenditures that may be related to impacts 

associated with ozone exposure. 

Nitrogen Deposition. Deposition to Estuarine and Coastal Waters. Excess nutrient loads, 

especially of nitrogen, cause a variety of adverse consequences to the health of estuarine and 

coastal waters. These effects include toxic and/or noxious algal blooms such as brown and red 

tides, low (hypoxic) or zero (anoxic) concentrations of dissolved oxygen in bottom waters, the 

loss of submerged aquatic vegetation due to the light-filtering effect of thick algal mats, and 

fundamental shifts in phytoplankton community structure (Bricker et al., 1999). A recent study 

found that for the period 1990–2002, atmospheric deposition accounted for 17 percent of nitrate 

loadings in the Gulf of Mexico, where severe hypoxic zones have been existed over the last two 

decades (Booth and Campbell, 2007).20

Reductions in atmospheric deposition of NOx are expected to reduce the adverse impacts 

associated with nitrogen deposition to estuarine and coastal waters. However, direct functions 

relating changes in nitrogen loadings to changes in estuarine benefits are not available. The 

preferred WTP-based measure of benefits depends on the availability of these functions and on 

estimates of the value of environmental responses. Because neither appropriate functions nor 

sufficient information to estimate the marginal value of changes in water quality exist at present, 

calculation of a WTP measure is not possible. 

Deposition to Agricultural and Forested Land. Implementation strategies for alternative 

standards that reduce NOX emissions will also reduce nitrogen deposition on agricultural land 

and forests. There is some evidence that nitrogen deposition may have positive effects on 

agricultural output through passive fertilization. Holding all other factors constant, farmers’ use 

of purchased fertilizers or manure may increase as deposited nitrogen is reduced. Estimates of 

the potential value of this possible increase in the use of purchased fertilizers are not available, 

but it is likely that the overall value is very small relative to other health and welfare effects. The 

share of nitrogen requirements provided by this deposition is small, and the marginal cost of 

providing this nitrogen from alternative sources is quite low. In some areas, agricultural lands 

suffer from nitrogen over-saturation due to an abundance of on-farm nitrogen production, 

primarily from animal manure. In these areas, reductions in atmospheric deposition of nitrogen 

from PM represent additional agricultural benefits.

Information on the effects of changes in passive nitrogen deposition on forests and other 

terrestrial ecosystems is very limited. The multiplicity of factors affecting forests, including other 

potential stressors such as ozone, and limiting factors such as moisture and other nutrients, 

confound assessments of marginal changes in any one stressor or nutrient in forest ecosystems. 

However, reductions in deposition of nitrogen could have negative effects on forest and 

vegetation growth in ecosystems where nitrogen is a limiting factor (US EPA, 1993). Moreover, 

 

20 Booth, M.S., and C. Campbell. 2007. Spring Nitrate Flux in the Mississippi River Basin: A 

Landscape Model with Conservation Applications. Environ. Sci. Technol.; 2007; ASAP Web 

Release Date: 20-Jun-2007; (Article) DOI: 10.1021/es070179e 
6-20 

any positive effect that nitrogen deposition has on forest productivity would enhance the level of 

carbon dioxide sequestration as well.21,22,23 

On the other hand, there is evidence that forest ecosystems in some areas of the United States 

(such as the western U.S.) are nitrogen saturated (US EPA, 1993). Once saturation is reached, 

adverse effects of additional nitrogen begin to occur such as soil acidification, which can lead to 

leaching of nutrients needed for plant growth and mobilization of harmful elements such as 

aluminum. Increased soil acidification is also linked to higher amounts of acidic runoff to 

streams and lakes and leaching of harmful elements into aquatic ecosystems. 

Ultraviolet Radiation. Atmospheric ozone absorbs a harmful band of ultraviolet radiation from 

the sun called UV-B, thus providing a protective shield to the Earth’s surface. The majority of 

this protection occurs in the stratosphere where 90% of atmospheric ozone is located. The 

remaining 10% of the Earth’s ozone is present at ground level (referred to as tropospheric ozone) 

(NAS, 1991; NASA). Only a portion of the tropospheric fraction of UV-B shielding is from 

anthropogenic sources (e.g., power plants, byproducts of combustion). The portion of ground 

level ozone associated with anthropogenic sources varies by locality and over time. Even so, it is 

reasonable to assume that reductions in ground level ozone would lead to increases in the same 

health effects linked to in UV-B exposures. These effects include fatal and nonfatal melanoma 

and non-melanoma skin cancers and cataracts. The values of $15,000 per case for non-fatal 

melanoma skin cancer, $5,000 per case for non-fatal non-melanoma skin cancer, and $15,000 per 

case of cataracts have been used in analyses of stratospheric ozone depletion (U.S. EPA, 1999). 

Fatal cancers are valued using the standard VSL estimate, which for 2020 is $6.6 million 

(2006$). UV-B has also been linked to ecological effects including damage to crops and forest. 

For a more complete listing of quantified and unquantified UV-B radiation effects, see Table G-4 

and G-7 in the Benefits and Costs of the Clean Air Act, 1990–2010 (U.S. EPA, 1999). UV-B 

related health effects are also discussed in the context of stratospheric ozone in a 2006 report by 

ICF Consulting, prepared for the U.S. EPA. 

There are many factors that influence UV-B radiation penetration to the earth’s surface, 

including latitude, altitude, cloud cover, surface albedo, PM concentration and composition, and 

gas phase pollution. Of these, only latitude and altitude can be defined with small uncertainty in 

any effort to assess the changes in UV-B flux that may be attributable to any changes in 

tropospheric ozone as a result of any revision to the Ozone NAAQS. Such an assessment of UVB related health effects would also need to take into account human habits, such as outdoor 

activities (including age- and occupation-related exposure patterns), dress and skin care to 

adequately estimate UV-B exposure levels. However, little is known about the impact of these 

factors on individual exposure to UV-B. 

 

21 Peter M. Vitousek et. al., “Human Alteration of the Global Nitrogen Cycle: Causes and 

Consequences” Issues in Ecology No. 1 (Spring) 1997. 22 Knute J. Nadelhoffer et. al., “Nitrogen deposition makes a minor contribution to carbon 

sequestration in temperate forests” Nature 398, 145-148 (11 March 1999). 23 Martin Köchy and Scott D. Wilson, “Nitrogen deposition and forest expansion in the northern 

Great Plains Journal of Ecology Journal of Ecology 89 (5), 807–817. 
6-21 

Moreover, detailed information does not exist regarding other factors that are relevant to 

assessing changes in disease incidence, including: type (e.g., peak or cumulative) and time 

period (e.g., childhood, lifetime, current) of exposures related to various adverse health outcomes 

(e.g., damage to the skin, including skin cancer; damage to the eye, such as cataracts; and 

immune system suppression); wavelength dependency of biological responses; and 

interindividual variability in UV-B resistance to such health outcomes. Beyond these wellrecognized adverse health effects associated with various wavelengths of UV radiation, the 

Criteria Document (Section 10.2.3.6) also discusses protective effects of UV-B radiation. Recent 

reports indicate the necessity of UV-B in producing vitamin D, and that vitamin D deficiency can 

cause metabolic bone disease among children and adults, and may also increase the risk of many 

common chronic diseases (e.g., type I diabetes and rheumatoid arthritis) as well as the risk of 

various types of cancers. Thus, the Criteria Document concludes that any assessment that 

attempts to quantify the consequences of increased UV-B exposure on humans due to reduced 

ground-level O3 must include consideration of both negative and positive effects. However, as 

with other impacts of UVB on human health, this beneficial effect of UVB radiation has not 

previously been studied in sufficient detail. EPA has conducted a screening level analysis of the 

effects of reduced ozone concentrations on UVB exposures. This analysis is based on the air 

quality modeling conducted for the proposed Ozone NAAQS RIA, and is described in Appendix 

6d to the this RIA. The screening analysis has been peer-reviewed and a summary of the peerreview comments and responses are provided with the report. 

Climate Implications of Tropospheric Ozone. Although climate and air quality are generally 

treated as separate issues, they are closely coupled through atmospheric processes. Ozone, itself, 

is a major greenhouse gas and climate directly influences ambient concentrations of ozone. 

The concentration of tropospheric ozone has increased substantially since the pre-industrial era 

and has contributed to warming. Tropospheric ozone is (after carbon dioxide and methane) the 

third most important contributor to greenhouse gas warming. The National Academy of Sciences 

recently stated24 that regulations targeting ozone precursors would have combined benefits for 

public health and climate. As noted in the OAQPS Staff Paper, the overall body of scientific 

evidence suggests that high concentrations of ozone on a regional scale could have a discernible 

influence on climate. However, the Staff Paper concludes that insufficient information is 

available at this time to quantitatively inform the secondary NAAQS process with regard to this 

aspect of the ozone-climate interaction 

 

24 National Academy of Sciences, “Radiative Forcing of Climate Change: Expanding the 

Concept and Addressing Uncertainties,” October 2005. 
6-22 

Climate change can affect tropospheric ozone by modifying emissions of precursors, chemistry, 

transport and removal.25 Climate change affects the sources of ozone precursors through physical 

response (lightning), biological response (soils, vegetation, and biomass burning) and human 

response (energy generation, land use, and agriculture). Increases in regional ozone pollution are 

expected due to higher temperatures and weaker circulation. Simulations with global climate 

models for the 21st century indicate a decrease in the lifetime of tropospheric ozone due to 

increasing water vapor, which could decrease global background ozone concentrations. 

The Intergovernmental Panel on Climate Change (IPCC) recently released a report26 that 

projects, with “virtual certainty,” declining air quality in cities due to warmer and fewer cold 

days and nights and/or warmer/more frequent hot days and nights over most land areas. The 

report states that projected climate change-related exposures are likely to affect the health status 

of millions of people, in part, due to higher concentrations of ground level ozone related to 

climate change. 

The IPCC also reports27 that the current generation of tropospheric ozone models is generally 

successful in describing the principal features of the present-day global ozone distribution. 

However, there is much less confidence in the ability to reproduce the changes in ozone 

associated with perturbations of emissions or climate. There are major discrepancies with 

observed long-term trends in ozone concentrations over the 20th century, including after 1970 

when the reliability of observed ozone trends is high. Resolving these discrepancies is needed to 

establish confidence in the models. 

The EPA is currently leading a research effort with the goal of identifying changes in regional 

US air quality that may occur in a future (2050) climate, focusing on fine particles and ozone. 

The research builds first on an assessment of changes in US air quality due to climate change, 

which includes direct meteorological impacts on atmospheric chemistry and transport and the 

effect of temperature changes on air pollution emissions. Further research will result in an 

assessment that adds the emission impacts from technology, land use, demographic changes, and 

air quality regulations to construct plausible scenarios of US air quality 50 years into the future. 

As noted in the Staff Paper, results from these efforts are expected to be available for 

consideration in the next review of the ozone NAAQS. 

 

25Denman, K.L., G. Brasseur, A. Chidthaisong, P. Ciais, P.M. Cox, R.E. Dickinson, D. 

Hauglustaine, C. Heinze, E. Holland, D. Jacob, U. Lohmann, S Ramachandran, P.L. da Silva 

Dias, S.C. Wofsy and X. Zhang, 2007: Couplings Between Changes in the Climate System and 

Biogeochemistry. In: Climate Change 2007: The Physical Science Basis. Contribution of 

Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate 

Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and 

H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, 

NY, USA. 

26 IPCC, Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability, 

Summary for Policymakers. 

27 Denman, et al, 2007: Couplings Between Changes in the Climate System and 

Biogeochemistry. In: Climate Change 2007: The Physical Science Basis. 
6-23 

6.3.3 Baseline Incidence Rates 

Epidemiological studies of the association between pollution levels and adverse health effects 

generally provide a direct estimate of the relationship of air quality changes to the relative risk of 

a health effect, rather than estimating the absolute number of avoided cases. For example, a 

typical result might be that a 10 ppb decrease in daily ozone levels might, in turn, decrease 

hospital admissions by 3 percent. The baseline incidence of the health effect is necessary to 

convert this relative change into a number of cases. A baseline incidence rate is the estimate of 

the number of cases of the health effect per year in the assessment location, as it corresponds to 

baseline pollutant levels in that location. To derive the total baseline incidence per year, this rate 

must be multiplied by the corresponding population number. For example, if the baseline 

incidence rate is the number of cases per year per million people, that number must be multiplied 

by the millions of people in the total population. 

Table 6.3 summarizes the sources of baseline incidence rates and provides average incidence 

rates for the endpoints included in the analysis. For both baseline incidence and prevalence data, 

we used age-specific rates where available. We applied concentration-response functions to 

individual age groups and then summed over the relevant age range to provide an estimate of 

total population benefits. In most cases, we used a single national incidence rate, due to a lack of 

more spatially disaggregated data. Whenever possible, the national rates used are national 

averages, because these data are most applicable to a national assessment of benefits. For some 

studies, however, the only available incidence information comes from the studies themselves; in 

these cases, incidence in the study population is assumed to represent typical incidence at the 

national level. Regional incidence rates are available for hospital admissions, and county-level 

data are available for premature mortality. We have projected mortality rates such that future 

mortality rates are consistent with our projections of population growth (Abt Associates, 2005). 

6.4 Economic Values for Health Outcomes 

Reductions in ambient concentrations of air pollution generally lower the risk of future adverse 

health effects for a large population. Therefore, the appropriate economic measure is willingnessto-pay (WTP) for changes in risk of a health effect rather than WTP for a health effect that would 

occur with certainty (Freeman, 1993). Epidemiological studies generally provide estimates of the 

relative risks of a particular health effect that is avoided because of a reduction in air pollution. 

We converted those to units of avoided statistical incidence for ease of presentation. We 

calculated the value of avoided statistical incidences by dividing individual WTP for a risk 

reduction by the related observed change in risk. For example, suppose a pollution-reduction 

regulation 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 death is $1 million ($100/0.0001 change in risk). 
6-24 

Table 6.3: National Average Baseline Incidence Rates 

Rate per 100 people per yeard by Age Group 

Endpoint Source Notes <18 

18–

24 

25–

34 

35–

44 

45–

54 

55–

64 65+ 

Mortality CDC Compressed 

Mortality File, accessed 

through CDC Wonder 

(1996–1998) 

nonaccidental 0.025 0.022 0.057 0.150 0.383 1.006 4.937 

Respiratory 

Hospital 

Admissions 

1999 NHDS public use 

data filesb

incidence 0.043 0.084 0.206 0.678 1.926 4.389 11.629 

Asthma ER 

visits 

2000 NHAMCS public 

use data filesc

; 1999 

NHDS public use data 

filesb

incidence 1.011 1.087 0.751 0.438 0.352 0.425 0.232 

Minor 

Restricted 

Activity Days 

(MRADs) 

Ostro and Rothschild 

(1989, p. 243) 

incidence — 780 780 780 780 780 — 

School Loss 

Days 

National Center for 

Education Statistics 

(1996) and 1996 HIS 

(Adams et al., 1999, 

Table 47); estimate of 

180 school days per year 

all-cause 990.0 — — — — — — 

 

Endpoint Source Notes

Rate per 100 People 

per Year

Ostro et al. 

(2001) 

Incidence (and prevalence) 

among asthmatic AfricanAmerican children 

Daily wheeze 

Daily cough 

Daily dyspnea 

0.076 (0.173) 

0.067 (0.145) 

0.037 (0.074) 

Asthma 

Exacerbations 

Vedal et al. 

(1998) 

Incidence (and prevalence) 

among asthmatic children 

Daily wheeze 

Daily cough 

Daily dyspnea 

0.038 

0.086 

0.045 a

 The following abbreviations are used to describe the national surveys conducted by the National Center 

for Health Statistics: HIS refers to the National Health Interview Survey; NHDS—National Hospital 

Discharge Survey; NHAMCS—National Hospital Ambulatory Medical Care Survey. 

b

 See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHDS/

c

 See ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHAMCS/ 

d

 All of the rates reported here are population-weighted incidence rates per 100 people per year. 

Additional details on the incidence and prevalence rates, as well as the sources for these rates are 

available upon request. 
6-25 

WTP estimates generally are not available for some health effects, such as hospital admissions. 

In these cases, we used the cost of treating or mitigating the effect as a primary estimate. These 

cost-of-illness (COI) estimates generally understate the true value of reducing the risk of a health 

effect, because they reflect the direct expenditures related to treatment, but not the value of 

avoided pain and suffering (Harrington and Portney, 1987; Berger, 1987). We provide unit 

values for health endpoints (along with information on the distribution of the unit value) in 

Table 6.4. All values are in constant year 2006 dollars, adjusted for growth in real income out to 

2020 using projections provided by Standard and Poor’s. Economic theory argues that WTP for 

most goods (such as environmental protection) will increase if real income increases. Many of 

the valuation studies used in this analysis were conducted in the late 1980s and early 1990s. 

Because real income has grown since the studies were conducted, people’s willingness to pay for 

reductions in the risk of premature death and disease likely has grown as well. We did not adjust 

cost of illness-based values because they are based on current costs. Similarly, we did not adjust 

the value of school absences, because that value is based on current wage rates. Table 6.4 

presents the values for individual endpoints adjusted to year 2020 income levels. The discussion 

below provides additional details on ozone related endpoints. For details on valuation estimates 

for PM related endpoints, see the 2006 PM NAAQS RIA. 

6.4.1 Mortality Valuation 

To estimate the monetary benefit of reducing the risk of premature death, we used the “value of 

statistical lives” saved (VSL) approach, which is a summary measure for the value of small 

changes in mortality risk for a large number of people. The VSL approach applies information 

from several published value-of-life studies to determine a reasonable monetary value of 

preventing premature mortality. The mean value of avoiding one statistical death is estimated to 

be roughly $6.6 million at 1990 income levels (2006$), and $7.9 million (2006$) at 2020 income 

levels. This represents an intermediate value from a variety of estimates in the economics 

literature (see the 2006 PM NAAQS RIA for more details on the calculation of VSL). 

6.4.2 Hospital Admissions Valuation 

In the absence of estimates of societal WTP to avoid hospital visits/admissions for specific 

illnesses, estimates of total cost of illness (total medical costs plus the value of lost productivity) 

typically are used as conservative, or lower bound, estimates. These estimates are biased 

downward, because they do not include the willingness-to-pay value of avoiding pain and 

suffering. 

The International Classification of Diseases (ICD-9, 1979) code-specific COI estimates used in 

this analysis consist of estimated hospital charges and the estimated opportunity cost of time 

spent in the hospital (based on the average length of a hospital stay for the illness). We based all 

estimates of hospital charges and length of stays on statistics provided by the Agency for 

Healthcare Research and Quality (AHRQ 2000). We estimated the opportunity cost of a day 

spent in the hospital as the value of the lost daily wage, regardless of whether the hospitalized 

individual is in the workforce. To estimate the lost daily wage, we divided the 1990 median 

weekly wage by five and inflated the result to year 2000$ using the CPI-U “all items.” The 

resulting estimate is $109.35. The total cost-of-illness estimate for an ICD code-specific hospital 

stay lasting n days, then, was the mean hospital charge plus $109 multiplied by n. 
6-26 

Table 6.4: Unit Values for Economic Valuation of Health Endpoints (2006$) 

Central Estimate of Value 

Per Statistical Incidence 

Health Endpoint 

1990 Income 

Level 

2020 Income 

Level Derivation of Distributions of Estimates 

Premature Mortality (Value of a Statistical Life) 

$6,600,000 $7,900,000 Point estimate is the mean of a normal distribution with a 95% confidence in

$10 million. Confidence interval is based on two meta-analyses of the wage-million represents the lower end of the interquartile range from the Mrozek aanalysis and $10 million represents the upper end of the interquartile range fAldy (2003) meta-analysis. The mean of the distribution is consistent with ththird meta-analysis (Kochi et al 2006). The VSL represents the value of a smrisk aggregated over the affected population. 

Chronic Bronchitis (CB) 

$410,000 $500,000 The WTP to avoid a case of pollution-related CB is calculated as WTP WTP 

x 

= 

the severity of an average CB case, WTP13 is the WTP for a severe case of C

parameter relating WTP to severity, based on the regression results reported Cropper (1992). The distribution of WTP for an average severity-level case oMonte Carlo methods, drawing from each of three distributions: (1) WTP to CB is assigned a 1/9 probability of being each of the first nine deciles of the responses in Viscusi et al. (1991); (2) the severity of a pollution-related case case described in the Viscusi study) is assumed to have a triangular distributlikely value at severity level 6.5 and endpoints at 1.0 and 12.0; and (3) the coof WTP with respect to severity is normally distributed with mean = 0.18 an0.0669 (from Krupnick and Cropper [1992]). This process and the rationale fdescribed in detail in the Costs and Benefits of the Clean Air Act, 1990 to 20

Nonfatal Myocardial Infarction (heart attack)  3% discount rate

 Age 0–24  Age 25–44  Age 45–54  Age 55–65  Age 66 and over  7% discount rate Age 0–24  Age 25–44  Age 45–54  Age 55–65  Age 66 and over 

$79,685 $88,975 $93,897 

$167,532 

$79,685 $77,769 $87,126 $91,559 

$157,477 

$77,769 

$79,685 $88,975 $93,897 

$167,532 

$79,685 $77,769 $87,126 $91,559 

$157,477 

$77,769 

No distributional information available. Age-specific cost-of-illness values rdirect medical costs over a 5-year period following a nonfatal MI. Lost earnion Cropper and Krupnick (1990). Direct medical costs are based on simple afrom Russell et al. (1998) and Wittels et al. (1990). Lost earnings: Cropper and Krupnick (1990). Present discounted value of 5 years of lost earage of onset: at 3% at 7%  25–44 $8,774 $7,855  45–54 $12,932 $11,578  55–65 $74,746 $66,920 Direct medical expenses: An average of: 

1. Wittels et al. (1990) ($102,658—no discounting) 2. Russell et al. (1998), 5-year period ($22,331 at 3% discount rate; $21,1
6-27 

Central Estimate of Value 

Per Statistical Incidence 

Health Endpoint 

1990 Income 

Level 

2020 Income 

Level Derivation of Distributions of Estimates 

Hospital Admissions 

Chronic Obstructive Pulmonary Disease (COPD) 

$16,606 $16,606

No distributional information available. The COI estimates (lost earnings plu

are based on ICD-9 code-level information (e.g., average hospital care costs, 

hospital stay, and weighted share of total COPD category illnesses) reported Healthcare Research and Quality (2000) (www.ahrq.gov). 

Asthma Admissions $8,900 $8,900

No distributional information available. The COI estimates (lost earnings plu

are based on ICD-9 code-level information (e.g., average hospital care costs, 

hospital stay, and weighted share of total asthma category illnesses) reported Healthcare Research and Quality (2000) (www.ahrq.gov). 

All Cardiovascular 

$24,668 $24,668

No distributional information available. The COI estimates (lost earnings plu

are based on ICD-9 code-level information (e.g., average hospital care costs, 

hospital stay, and weighted share of total cardiovascular category illnesses) rHealthcare Research and Quality (2000) (www.ahrq.gov). 

All respiratory (ages 65+) $24,622 $24,622

No distributions available. The COI point estimates (lost earnings plus direct based on ICD-9 code level information (e.g., average hospital care costs, avestay, and weighted share of total COPD category illnesses) reported in AgenResearch and Quality, 2000 (www.ahrq.gov). 

All respiratory (ages 0–2) $10,385 $10,385

No distributions available. The COI point estimates (lost earnings plus direct based on ICD-9 code level information (e.g., average hospital care costs, avestay, and weighted share of total COPD category illnesses) reported in AgenResearch and Quality, 2000 (www.ahrq.gov). 

Emergency Room Visits for Asthma $384 $384

No distributional information available. Simple average of two unit COI valu

(1) $311.55, from Smith et al. (1997) and (2) $260.67, from Stanford et al. (1999). 

Respiratory Ailments Not Requiring Hospitalization 

Upper Respiratory Symptoms (URS) 

$30 $30 Combinations of the three symptoms for which WTP estimates are available 

those listed by Pope et al. result in seven different “symptom clusters,” each URS. A dollar value was derived for each type of URS, using mid-range esti1994) to avoid each symptom in the cluster and assuming additivity of WTPinformation surrounding the frequency with which each of the seven types oURS symptom complex, we assumed a uniform distribution between $9.2 an
6-28 

Central Estimate of Value 

Per Statistical Incidence 

Health Endpoint 

1990 Income 

Level 

2020 Income 

Level Derivation of Distributions of Estimates 

Lower Respiratory Symptoms (LRS) 

$19 $21

Combinations of the four symptoms for which WTP estimates are available tlisted by Schwartz et al. result in 11 different “symptom clusters,” each descA dollar value was derived for each type of LRS, using mid-range estimates avoid each symptom in the cluster and assuming additivity of WTPs. The dothe average of the dollar values for the 11 different types of LRS. In the absesurrounding the frequency with which each of the 11 types of LRS occurs wcomplex, we assumed a uniform distribution between $6.9 and $24.46. 

Asthma Exacerbations 

$50 $54

Asthma exacerbations are valued at $45 per incidence, based on the mean of 

estimates for the four severity definitions of a “bad asthma day,” described in (1986). This study surveyed asthmatics to estimate WTP for avoidance of a “defined by the subjects. For purposes of valuation, an asthma exacerbation is equivalent to a day in which asthma is moderate or worse as reported in the R(1986) study. The value is assumed have a uniform distribution between $15

Acute Bronchitis 

$429 $453

Assumes a 6-day episode, with the distribution of the daily value specified aand high values based on those recommended for related respiratory symptom(1994). The low daily estimate of $10 is the sum of the mid-range values rec(1994) for two symptoms believed to be associated with acute bronchitis: cotightness. The high daily estimate was taken to be twice the value of a minor activity day, or $110. 

Work Loss Days (WLDs) 

Variable 

(U.S. median 

= $130) 

 No distribution available. Point estimate is based on county-specific median 

by 50 (assuming 2 weeks of vacation) and then by 5—to get median daily wCensus, compiled by Geolytics, Inc. 

Minor Restricted Activity Days (MRADs) 

$61 $64 Median WTP estimate to avoid one MRAD from Tolley et al. (1986). Distrib

triangular with a minimum of $22 and a maximum of $83, with a most likely based on assumption that value should exceed WTP for a single mild symptofor a single symptom—for eye irritation—is $16.00) and be less than that for distribution acknowledges that the actual value is likely to be closer to the po

extreme. 

School Absence Days 

$89 $89 No distribution available 
6-29 

6.4.3 Asthma-Related Emergency Room Visits Valuation 

To value asthma emergency room visits, we used a simple average of two estimates from the 

health economics literature. The first estimate comes from Smith et al. (1997), who reported 

approximately 1.2 million asthma-related emergency room visits in 1987, at a total cost of 

$186.5 million (1987$). The average cost per visit that year was $155; in 2000$, that cost was 

$311.55 (using the CPI-U for medical care to adjust to 2000$). The second estimate comes from 

Stanford et al. (1999), who reported the cost of an average asthma-related emergency room visit 

at $260.67, based on 1996–1997 data. A simple average of the two estimates yields a (rounded) 

unit value of $286. 

6.4.4 Minor Restricted Activity Days Valuation 

No studies are reported to have estimated WTP to avoid a minor restricted activity day. 

However, one of EPA’s contractors, IEc (1993) has derived an estimate of willingness to pay to 

avoid a minor respiratory restricted activity day, using estimates from Tolley et al. (1986) of 

WTP for avoiding a combination of coughing, throat congestion and sinusitis. The IEc estimate 

of WTP to avoid a minor respiratory restricted activity day is $38.37 (1990$), or about $52 

($2000). 

Although Ostro and Rothschild (1989) statistically linked ozone and minor restricted activity 

days, it is likely that most MRADs associated with ozone exposure are, in fact, minor respiratory

restricted activity days. For the purpose of valuing this health endpoint, we used the estimate of 

mean WTP to avoid a minor respiratory restricted activity day. 

6.4.5 School Absences 

To value a school absence, we: (1) estimated the probability that if a school child stays home 

from school, a parent will have to stay home from work to care for the child; and (2) valued the 

lost productivity at the parent’s wage. To do this, we estimated the number of families with 

school-age children in which both parents work, and we valued a school-loss day as the 

probability that such a day also would result in a work-loss day. We calculated this value by 

multiplying the proportion of households with school-age children by a measure of lost wages. 

We used this method in the absence of a preferable WTP method. However, this approach 

suffers from several uncertainties. First, it omits willingness to pay to avoid the symptoms/illness 

that resulted in the school absence; second, it effectively gives zero value to school absences that 

do not result in work-loss days; and third, it uses conservative assumptions about the wages of 

the parent staying home with the child. Finally, this method assumes that parents are unable to 

work from home. If this is not a valid assumption, then there would be no lost wages. 

For this valuation approach, we assumed that in a household with two working parents, the 

female parent will stay home with a sick child. From the Statistical Abstract of the United States 

(U.S. Census Bureau, 2001), we obtained: (1) the numbers of single, married and “other” 

(widowed, divorced or separated) working women with children; and (2) the rates of 

participation in the workforce of single, married and “other” women with children. From these 

two sets of statistics, we calculated a weighted average participation rate of 72.85 percent. 
6-30 

Our estimate of daily lost wage (wages lost if a mother must stay at home with a sick child) is 

based on the year 2000 median weekly wage among women ages 25 and older (U.S. Census 

Bureau, 2001). This median weekly wage is $551. Dividing by five gives an estimated median 

daily wage of $103. To estimate the expected lost wages on a day when a mother has to stay 

home with a school-age child, we first estimated the probability that the mother is in the 

workforce then multiplied that estimate by the daily wage she would lose by missing a workday: 

72.85 percent times $103, for a total loss of $75. This valuation approach is similar to that used 

by Hall et al. (2003). 

6.5 Results and Implications 

6.5.1 Ozone Benefit Estimates 

Figure 6.1 summarizes the valuation of ozone benefits. Tables 6.6 through 6.21 summarize the 

reduction in incidence for ozone- and PM-related health endpoints for each of the alternative 

ozone standards evaluated. Tables 6.22 through 6.37 summarize the ozone-related economic 

benefits for each of the alternative standards.28 Note that incidence and valuation estimates for 

each standard alternative are presented in separate tables In addition to the mean incidence 

estimates, we have included 5th and 95th percentile estimates when available, based on the Monte 

Carlo simulations described above. In the tables for the 0.065 ppm and 0.070 ppm alternative 

standards, the change in ozone-related incidence from attaining the alternative standards is 

presented for both the partial attainment scenario and the full attainment scenario (i.e., sum of the 

change in incidence associated with achieving the partial attainment increment plus the residual 

attainment increment). As described in Appendix 6a, to calculate the additional change in ozone 

concentrations to get from partial attainment to full attainment, we rolled back the ozone monitor 

data so that the 4th highest daily maximum 8-hour average just met the level required to attain the 

alternative standard. This approach will likely understate the benefits that would occur due to 

implementation of actual controls to reduce ozone precursor emissions because controls 

implemented to reduce ozone concentrations at the highest monitor would likely result in some 

reductions in ozone concentrations at attaining monitors down-wind (i.e., the controls would lead 

to concentrations below the standard in down-wind locations); estimating benefits that occur at 

these downwind monitors as a result of air quality improvements below the standard would be 

appropriate because ozone is a non-threshold pollutant. Therefore, air quality improvements and 

resulting health benefits from full attainment would be more widespread than we have estimated 

in our rollback analyses. The incidence and valuation results for attainment of the 0.075 ppm and 

0.079 ppm alternatives are derived through an interpolation technique described in Appendix 6a. 

As such, these estimates are presented as full attainment only. 

We model all ozone-related premature mortality and morbidity to occur in the same year as the 

change in exposure rather than assuming a ‘lag’ in the change in health state, as we do for PM. 

Therefore, we do not discount ozone estimates. 

 

28 Note that the valuation estimates for ozone benefits are not discounted due to the fact that there 

is no lag between changes in exposure and premature mortality, as is calculated for PM2.5

benefits. 
6-31 

 Figure 6.1: Valuation of Ozone Morbidity and Mortality Benefits Results by Standard 

Alternative*

* This figure reflects full attainment in all locations of the U.S. except two areas of California. These two 

areas, which have high levels of ozone, are not planning to meet the current standard until after 2020. 

The estimates in the figure do not reflect benefits for the San Joaquin and South Coast Air Basins. 

6.5.2 PM2.5 Co-Benefit Estimation Methodology 

Figure 6.2 summarizes the valuation of PM benefits at a 3% and 7% discounted rate, 

respectively. A series of tables below present the PM2.5 co-benefits associated with full 

attainment of the 0.065 ppm, 0.070 ppm, 0.075 ppm and 0.079 ppm alternatives. To derive 

estimates of incidence and valuation for the PM2.5 related co-benefits of full attainment of each 

ozone standard alternative, we applied a scaling technique described below. To estimate total 

valuation estimates, we applied benefit per-ton metrics; this procedure is detailed further below. 

Valuation estimates of the PM2.5-related full attainment benefits are presented at a 3% discount 

rate and at a 7% discount rate. All PM2.5 co-benefit estimates are incremental to the 2006 PM 

NAAQS RIA. 
6-32 

Figure 6.2: Valuation of PM Co-Benefits by Standard Alternative at 3% and 7%* 

* This figure reflects full attainment in all locations of the U.S. except two areas of California. These 

two areas, which have high levels of ozone, are not planning to meet the current standard until after 

2020. The estimates in the figure do not reflect benefits for the San Joaquin and South Coast Air 

Basins. 
6-33 

Estimating PM2.5 Co-Benefits Resulting from Full Attainment of the Selected Standard and Each 

Standard Alternative 

The modeled PM2.5 air quality scenario reflects the PM2.5 changes associated with partially 

attaining 0.070 ppm incremental to a partial attainment of 0.08 ppm; due to analytical limitations 

it was not possible to model a full-attainment PM2.5 scenario for the selected standard or each 

standard alternative. Thus, using this projected air quality change to estimate PM2.5 co-benefits 

would under or overstate the benefits of attaining each standard alternative; this is due in part to 

the fact that the model run projects the air quality changes from NOx reductions needed to attain 

a baseline of 0.08 ppm. Of greater analytical value would be an estimate of the PM2.5 co-benefits 

associated with fully attaining 0.070 ppm incremental to full attainment of the 0.08 ppm 

standard. 

To generate such an estimate, we calculated a new PM2.5 baseline that established the PM2.5 air 

quality associated with full attainment of 0.08 ppm. To create such a baseline, EPA utilized 

benefit PM2.5 per-ton estimates. These PM2.5 benefit per-ton estimates provide the total 

monetized human health benefits (the sum of premature mortality and premature morbidity) of 

reducing one ton of PM2.5 from a specified source. EPA has used a similar technique in previous 

Regulatory Impact Analyses.29 These estimates are based on the sum of the valuation of the Pope 

(2002) estimates of mortality (3% discount rate, 2006$) and valuation of the morbidity 

incidence. Readers interested in reviewing the complete methodology for creating the benefit 

per-ton estimates used in this analysis can consult the Technical Support Document 

accompanying this RIA. 

Estimating the PM2.5 benefits that represented the full attainment of both 0.070 ppm incremental 

to full attainment of 0.08 ppm entailed the following four steps:

1. Estimate the number of tons of NOx necessary to attain a baseline of 0.08 ppm. Chapter 4 

described the method used to estimate the extrapolated NOx emissions reductions 

necessary to attain a baseline of 0.08 ppm full attainment. 

2. Calculate the benefits of attaining 0.08 ppm incremental to partial attainment of 0.08 

ppm. To estimate the benefits of fully attaining 0.08 ppm incremental to partial 

attainment of 0.08 ppm, the relevant benefit per ton is simply multiplied by the total 

number of extrapolated NOx tons abated. Note that this calculation step allows us to net 

out the benefits of attaining the current standard, so that all subsequent benefits are 

incremental to the full attainment of 0.080 ppm.

3. Calculate the benefits of partially attaining 0.070 ppm incremental to full attainment of 

0.08 ppm. Subtract the benefits of fully attaining 0.080 ppm incremental to the partial 

 

29 Final Regulatory Impact Analysis: Industrial Boilers and Process Heaters. Prepared by Office 

of Air and Radiation. Available: http://www.epa.gov/ttn/ecas/regdata/EIAs/chapter10.pdf 

[accessed 18 May 2007]. 
6-34 

attainment of 0.08 ppm to create a new estimate of incremental 0.070 ppm partial 

attainment.

4. Calculate the PM2.5 benefits of fully attaining 0.070 ppm. Multiplying the estimate of the 

extrapolated NOx tons necessary to attain 0.070 ppm fully (Table 5.3) produces an 

estimate of the incremental benefits of fully attaining 0.070 ppm incremental to partial 

attainment of 0.070 ppm. By adding this incremental benefit estimate to the benefits 

generated in step 3, we derived a total benefit estimate of attaining 0.070 ppm 

incremental to 0.08 ppm. 

5. Repeat step 4 to estimate the benefits of 0.075 ppm, 0.079 ppm and 0.065 ppm. Step 4 

may be repeated by substituting the NOx tons necessary to attain the selected alternative 

of 0.075 ppm and the remaining alternatives of 0.079 ppm and 0.065 ppm to produce an 

estimate of total PM2.5 co-benefits. 

The process for estimating the PM2.5 co-benefits of fully attaining 0.065 ppm, 0.075 ppm, and 

0.079 ppm is identical to the steps above, with the following exception; in step four we 

substituted the number of extrapolated tons necessary to attain 0.065 ppm, 0.075 ppm, and 0.079 

ppm respectively. Table 7-5 below provides the inputs to the calculation steps described above. 

In the example below, we calculate total benefits using the Pope et al. (2002) mortality estimate. 

However, in subsequent tables we present benefits using Laden et al. (2006) as well as the twelve 

expert functions described previously in this document. Note that while our benefit per ton 

estimates are associated with broad source categories (in this case, NOx emitting Electrical 

Generating Units, Other NOx emitting point sources and NOx emitting Mobile sources) the 

extrapolated tons were not. For this reason we simply assumed that the total number of 

extrapolated NOx tons were evenly distributed between these three source types. 

The PM2.5 benefits of attaining 0.065 ppm, 0.075 ppm and 0.079 ppm incremental to partial 

attainment of 0.070 ppm are $7.5 billion, $0.6 billion and -$1 billion respectively. Simulated 

attainment of the 0.79 ppm alternative required fewer emission reductions than were modeled in 

the emissions control strategy to simulate attainment with 0.070 ppm. For this reason, we “netted 

out” the benefits of the incremental NOx emission reductions that were present in the 0.070 ppm 

control case but not necessary to attain 0.079 ppm. 

The benefit per-ton estimates produce estimates of total valuation but not incidence. To estimate 

total incidence, we applied a simple scaling factor. To estimate PM2.5-related incidence 

associated with the attainment of each ozone alternative, we calculated a separate scaling factor 

as follows: (1) we calculated the ratio of the full attainment PM2.5 valuation estimate (calculated 

using the benefit per ton metrics described below) to the partial attainment to the partial 

attainment PM2.5 valuation estimate; (2) multiply this scaling ratio against each of the PM2.5

partial attainment mortality and morbidity endpoints to generate a scaled estimate of mortality 

and morbidity. While there are clearly substantial uncertainties inherent in this technique, it does 

produce useful screening-level estimates of PM2.5-related incidence.

The total PM2.5 benefits of attaining 0.065 ppm, 0.075 ppm and 0.079 ppm are $11 billion, $3.6 

billion and $2 billion respectively. The full attainment PM2.5 benefits do not include confidence 

intervals. Because this full attainment estimate was derived by summing the modeled PM2.5
6-35 

benefits and the benefits derived using the benefit per-ton metrics—and these benefit per ton 

metrics do not include confidence intervals—the resulting sum of total PM2.5 benefits do not 

include confidence intervals. 

Table 6.5: Estimated PM2.5 Co-Benefits Associated with Full Attainment of 0.070 ppm 

Incremental to 0.08 ppma

Calculation 

Extrapolated NOx 

Tons 

Benefit per Ton 

Estimate 

Valuation of PM2.5

Benefits 

(Billions 2006$)b

Benefits of attaining 0.08 ppm partially and 

0.070 ppm partially (i.e. the benefits of the 

modeled scenario): 

— — $3.4 

NOx EGU: 37,400 $3,200 

NOx Point: 37,400 $3,000 

Benefits of attaining 0.08 ppm from a 

baseline of 0.08 ppm partial attainment: 

NOx Mobile: 37,400 $4,800 

$0.4 

Benefits of attaining 0.070 ppm partially, 

incremental to attainment of 0.08 ppm — — $3 

NOx EGU: 310,000 $3,200 

NOx Point: 310,000 $3,000 

NOx Mobile: 310,000 $4,800 

Benefits of attaining 0.070 ppm in 2020 

incremental to partial attainment of 0.070 

ppm 

VOC: 310,000 $430 

$3.5 

Benefits of attaining 0.070 ppm incremental 

to attainment of 0.08 ppm 

 $6.5 

a Numbers have been rounded to two significant figures and therefore summation may not match table 

estimates. PM2.5 benefit estimates do not include confidence intervals because they are derived using 

benefit per-ton estimates. 

b All estimates derived using the Pope et al. (2002) mortality estimate at a 3% and 7% discount rate, in 

2006$. This table reflects full attainment in all locations of the U.S. except two areas of California. 

These two areas, which have high levels of ozone, are not planning to meet the current standard until 

after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air 

Basins. 

Estimated reductions in ozone mortality incidence provided in Tables 6.6, 6.10, 6.14, and 6.18 

represent the number of premature deaths potentially avoided due to reductions in ozone 

exposure in 2020 using warm season functions from the recent ozone-mortality NMMAPS 

analysis of 95 U.S. communities (Bell et al., 2004) and three meta-analyses of the available 

published literature on ozone-mortality effects (Bell et al., 2005; Ito et al., 2005; Levy et al., 

2005). These same tables also include the possibility that there is not a causal association 

between ozone and mortality, i.e., that the estimate for premature mortality avoided could be 

zero. Model uncertainty, including whether or not the relationship is assumed to be causal, is a 

key source of uncertainty. Although multiple estimates are presented in these tables, no attempt 

was made to quantify the likelihood of a causal relationship between short-term ozone exposure 

and increased mortality or to weigh the results of the various models. 

The estimate of central tendency for premature mortality is expressed as the arithmetic mean, 

with the assumption of a normal distribution, and represents the central estimate of the number of 

premature deaths avoided in association with the alternative standards based on each study. 
6-36 

Statistical uncertainty associated with the model estimate for each study is characterized by the 

95% credible interval30 around the mean estimate (i.e., 2.5th and 97.5th percent interval). Of the 

four available studies, the NMMAPS study by Bell et al. (2004) is considered to be the most 

representative for evaluating potential mortality-related benefits associated with the alternative 

standards due to its extensive coverage (examination of 95 large communities across the United 

States over an extended period of time, from 1987 to 2000) and its specific focus on the ozonemortality relationship. Annual estimates of lives saved from this study are lower than those from 

the three meta-analyses, possibly due to more stringent adjustment for meteorological factors (Ito 

et al., 2005; Ostro et al., 2006), publication bias in the meta-analyses (Bell et al., 2005; Ito et al., 

2005) or other factors. Clearly, the ozone-mortality reduction estimates are conditional on a 

causal relationship. 

The Ozone Criteria Document (U.S. EPA, 2006) and Staff Paper (U.S. EPA, 2007) concluded 

that the overall body of evidence is highly suggestive that (short-term exposure to) ozone directly 

or indirectly contributes to non-accidental cardiopulmonary-related mortality. However, various 

sources of uncertainty remain, including the possibility that there is no causal relationship 

between ozone and mortality (i.e., zero effect). For instance, because results of time-series 

studies implicate all of the criteria air pollutants, and those who would be expected to be 

potentially more susceptible to ozone exposure are likely to have lower exposure to ozone due to 

the amount of time that they spend indoors, CASAC31 stated that it seems unlikely that the 

observed associations between short-term ozone concentrations and daily mortality are due 

solely to ozone itself (i.e., ozone may be serving as a marker for other agents that are 

contributing to the short-term exposure effects on mortality). Even so, CASAC concluded that 

the evidence was strong enough to support a quantitative risk assessment of the relationship 

between short-term exposure to ozone and premature mortality as part of the Staff Paper. EPA 

has asked the National Academy of Sciences32 for their advice on how best to quantify the 

uncertainty about the relationship between ambient ozone exposure and premature mortality 

within the context of quantifying projected benefits of alternative control strategies. We expect to 

receive this advice later this spring. 

Using the NMMAPS study that was used as the basis for the risk analysis presented in our Staff 

Paper, we estimate 71 avoided premature deaths annually in 2020 from reducing ozone levels to 

meet the selected standard of 0.075 ppm, which, when added to the other projected ozone related 

benefits, leads to an estimated total benefit of $620 million/yr. Using three studies that synthesize 

data across a large number of individual studies, we estimate between 230 and 320, with total 

monetized ozone benefits to be between $1.9 and $2.6 billion/yr. Alternatively, if there is no 

causal relationship between ozone and mortality, avoided premature deaths would be zero. For a 

 

30 A credible interval is a posterior probability interval used in Bayesian statistics, which is 

similar to a confidence interval used in frequentist statistics. 31 Clean Air Scientific Advisory Committee’s Peer Review of the Agency’s 2nd Draft Ozone 

Staff Paper, October 24, 2006. EPA-CASAC-07-001. Available at http://www.epa.gov/sab/pdf/casac07-001.pdf 32 National Academy of Sciences (2007) Project Scope. Estimating Mortality Risk Reduction 

Benefits from Decreasing Tropospheric Ozone Exposure. Division on Earth and Life Studies, 

Board on Environmental Studies and Toxicology. Available at 

http://www8.nationalacademies.org/cp/projectview.aspx?key=48768 
6-37 

standard of 0.079 ppm, using the NMMAPS ozone mortality study, we estimate 24 premature 

deaths avoided and total monetized benefits of $220 million/yr. Using the three synthesis studies, 

we estimate premature deaths avoided for the less stringent standard to be between 80 and 110, 

with total monetized ozone benefits to be between $640 and $890 million/yr. For a standard of 

0.070 ppm, using the NMMAPS ozone mortality study, we estimate 250 premature deaths 

avoided and total monetized benefits of $2.2 billion/yr. Using the three synthesis studies, we 

estimate premature deaths avoided for the less stringent standard to be between 810 and 1,100 

avoided premature deaths annually in 2020, leading to total monetized benefits of between $6.5 

and $9 billion/yr. For a standard of 0.065 ppm, using the NMMAPS ozone mortality study, we 

estimated to result in 450 premature deaths avoided and total monetized benefits of $3.9 

billion/yr. Using the three synthesis studies, estimated premature deaths avoided for the more 

stringent standard are between 1,500 and 2,100, with total monetized ozone benefits between $12 

and $16 billion/yr. Including premature mortality in our estimates had the largest impact on the 

overall magnitude of benefits: Premature mortality benefits account for more than 95 percent of 

the total benefits we can monetize. We note that these estimates reflect EPA’s interim approach 

to characterizing the benefits of reducing premature mortality associated with ozone exposure. 

As mentioned above, EPA has requested advice from the NAS on this issue. 

6.5.3 Estimate of Full Attainment Benefits 

Tables 6.38 through 6.41 below summarize the estimates of full attainment and PM2.5 co-benefit 

estimate for each standard alternative. The presentation of ozone benefits and PM2.5 co-benefits 

for each standard alternative is broken into two tables. The first table presents the national ozone 

benefits and PM2.5 co-benefits. Tables 6.42 through 6.49 summarize the combined ozone and 

PM2.5 co-benefits. 
6-38 

Table 7-6: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual Reductions in the 

Incidence of Premature Mortality Associated with Ozone Exposure in 2020 (Incremental 

to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals in 

Parentheses) B, C, D, E

Model or AssumptionA Reference National Modeled Partial 

Attainment 

National Rolled-Back Full 

Attainment 

120 450 NMMAPS Bell et al. 2004 (43--210) (170--730) 

400 1500 Bell et al. 2005 (200--610) (760--2,200) 

550 2000 Ito et al. 2005 (340--760) (1,300--2,700) 

560 2100 

Meta-Analysis 

Levy et al. 2005 (390--730) (1,500--2,600) 

Assumption that association is not causal 0 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-39 

Table 7-7: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual Reductions in the 

Incidence of Morbidity Associated with Ozone Exposure (Incremental to Current Ozone 

Standard, 95% Confidence Intervals in Parentheses)A,B

 

Morbidity Endpoint 

National Modeled Partial 

Attainment 

National Rolled Back Full 

Attainment 

700 2,700 Hospital Admissions (ages 0-1) (310--1,100) (1,300--4,000) 

420 3,200 Hospital Admissions (ages 65-99) (-190--1,100) (74--6,200) 

Emergency Department Visits, 550 1900 

Asthma-RelatedC (-57--1,500) (-130--5,500) 

300,000 1,100,000 School Absences (77,000--560,000) (320,000--1,800,000) 

 810,000 2,900,000 Minor Restricted Activity Days (350,000--1,300,000) (1,300,000--4,400,000) 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

C

 The negative 5th percentile incidence estimates for this health endpoint are a result of the weak statistical power 

of the study and should not be inferred to indicate that decreased ozone exposure may cause an increase in 

asthma-related emergency department visits.
6-40 

Table 7-8: Illustrative 0.065 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of PM Premature Mortality associated with PM co-benefitC 

 

Mortality Endpoint National 2020 Benefits 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA 1,000 

Harvard Six-City StudyB 2,300 

Woodruff et al 1997 (infant mortality) 2.9 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A 4,000 

Expert B 3,100 

Expert C 3,100 

Expert D 2,100 

Expert E 5,000 

Expert F 2,800 

Expert G 1,800 

Expert H 2,300 

Expert I 3,000 

Expert J 2,400 

Expert K 490 

Expert L 2,100 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-41 

Table 7-9: Illustrative 0.065 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of Morbidity Associated with PM Co-benefitA, B

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) 970 

Nonfatal myocardial infarction (age >17) 940 

Hospital admissions--respiratory (all ages) 660,000 

Hospital admissions-- cardiovascular (age >17) 17,000 

Emergency room visits for asthma (age <19) 13,000 

Acute bronchitis (age 8-12) 110,000 

Lower respiratory symptoms (age 7-14) 2,600 

Upper respiratory symptoms (asthmatic children age 9-18) 16,000 

Asthma exacerbation (asthmatic children age 6-18) 270 

Work loss days (age 18-65) 550 

Minor restricted activity days (age 18-65) 2,300 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. 

Estimates do not include confidence intervals because they were derived through a scaling technique 

described above. This table reflects full attainment in all locations of the U.S. except two areas of California. 

These two areas, which have high levels of ozone, are not planning to meet the current standard until after 

2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

B Morbidity Impact Functions Derived from Epidemiology Literature 
6-42 

Table 7-10: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual Reductions in 

the Incidence of Premature Mortality Associated with Ozone Exposure in 2020 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses) B, C, D, E

 

Model or AssumptionA

 Reference National Modeled Partial 

Attainment 

National Rolled Back Full 

Attainment 

120 250 NMMAPS Bell et al. 2004 (43--210) (92--410) 

400 810 Bell et al. 2005 (200--610) (410--1,200) 

550 1100 Ito et al. 2005 (340--760) (690--1,500) 

560 1100 

Meta-Analysis 

Levy et al. 2005 (390--730) (800--1,500) 

Assumption that association is not causal 0 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-43 

Table 7-11: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual Reductions in 

the Incidence of Morbidity Associated with Ozone Exposure (Incremental to Current 

Ozone Standard, 95% Confidence Intervals in Parentheses)A,B

 

Morbidity Endpoint 

National Modeled Partial 

Attainment 

National Rolled Back Full 

Attainment 

700 1,500 Hospital Admissions (ages 0-1) (310--1,100) (720--2,400) 

420 1,400 Hospital Admissions (ages 65-99) (-190--1,100) (-110--3,000) 

Emergency Department Visits, 550 1000 

Asthma-RelatedC (-57--1,500) (-82--3,000) 

300,000 640,000 School Absences (77,000--560,000) (180,000--1,000,000) 

 810,000 1,700,000 Minor Restricted Activity Days (350,000--1,300,000) (740,000--2,600,000) 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

C

 The negative 5th percentile incidence estimates for this health endpoint are a result of the weak statistical power 

of the study and should not be inferred to indicate that decreased ozone exposure may cause an increase in 

asthma-related emergency department visits.
6-44 

Table 7-12: Illustrative 0.070 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of PM Premature Mortality associated with PM co-benefitC 

 

Mortality Endpoint National 2020 Benefits 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA 650 

Harvard Six-City StudyB 1,500 

Woodruff et al 1997 (infant mortality) 1.9 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A 2,600 

Expert B 2,000 

Expert C 2,000 

Expert D 1,400 

Expert E 3,200 

Expert F 1,800 

Expert G 1,100 

Expert H 1,500 

Expert I 1,900 

Expert J 1,600 

Expert K 310 

Expert L 1,400 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-45 

Table 7-13: Illustrative 0.070 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of Morbidity Associated with PM Co-benefitA, B

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) 630 

Nonfatal myocardial infarction (age >17) 610 

Hospital admissions--respiratory (all ages) 430,000 

Hospital admissions-- cardiovascular (age >17) 11,000 

Emergency room visits for asthma (age <19) 8,100 

Acute bronchitis (age 8-12) 72,000 

Lower respiratory symptoms (age 7-14) 1,700 

Upper respiratory symptoms (asthmatic children age 9-18) 10,000 

Asthma exacerbation (asthmatic children age 6-18) 180 

Work loss days (age 18-65) 350 

Minor restricted activity days (age 18-65) 1,500 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. 

Estimates do not include confidence intervals because they were derived through a scaling technique 

described above. This table reflects full attainment in all locations of the U.S. except two areas of California. 

These two areas, which have high levels of ozone, are not planning to meet the current standard until after 

2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

B Morbidity Impact Functions Derived from Epidemiology Literature 
6-46 

 

Table 7-14: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual Reductions in 

the Incidence of Premature Mortality Associated with Ozone Exposure in 2020 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses) B, C, D, E

 

Model or AssumptionA

 Reference National Full Attainment 

71 NMMAPS Bell et al. 2004 (27--110) 

230 Bell et al. 2005 (120--340) 

310 Ito et al. 2005 (200--430) 

320 

Meta-Analysis 

Levy et al. 2005 (230--420) 

Assumption that association is not causal 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-47 

Table 7-15: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual Reductions in 

the Incidence of Morbidity Associated with Ozone Exposure (Incremental to Current 

Ozone Standard, 95% Confidence Intervals in Parentheses)A,B

 

Morbidity Endpoint National Full Attainment 

480 Hospital Admissions (ages 0-1) (230--730) 

470 Hospital Admissions (ages 65-99) (-5.1--930) 

Emergency Department Visits, 280 

Asthma-RelatedC (-18--830) 

200,000 School Absences (58,000--320,000) 

500,000 Minor Restricted Activity Days (230,000--760,000) 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

C

 The negative 5th percentile incidence estimates for this health endpoint are a result of the weak statistical power 

of the study and should not be inferred to indicate that decreased ozone exposure may cause an increase in 

asthma-related emergency department visits.
6-48 

Table 7-16: Illustrative 0.075 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of PM Premature Mortality associated with PM co-benefitC 

 

Mortality Endpoint National 2020 Benefits 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA 390 

Harvard Six-City StudyB 880 

Woodruff et al 1997 (infant mortality) 1.1 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A 1,600 

Expert B 1,200 

Expert C 1,200 

Expert D 820 

Expert E 2,000 

Expert F 1,100 

Expert G 690 

Expert H 880 

Expert I 1,200 

Expert J 950 

Expert K 190 

Expert L 820 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-49 

Table 7-17: Illustrative 0.075 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of Morbidity Associated with PM Co-benefitA, B

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) 380 

Nonfatal myocardial infarction (age >17) 370 

Hospital admissions--respiratory (all ages) 260,000 

Hospital admissions-- cardiovascular (age >17) 6,700 

Emergency room visits for asthma (age <19) 4,900 

Acute bronchitis (age 8-12) 43,000 

Lower respiratory symptoms (age 7-14) 1,000 

Upper respiratory symptoms (asthmatic children age 9-18) 6,100 

Asthma exacerbation (asthmatic children age 6-18) 110 

Work loss days (age 18-65) 210 

Minor restricted activity days (age 18-65) 890 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

B Morbidity Impact Functions Derived from Epidemiology Literature 
6-50 

Table 7-18: Illustrative Strategy to Attain 0.079 ppm: Estimated Annual Reductions in 

the Incidence of Premature Mortality Associated with Ozone Exposure in 2020 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses) B, C, D, E

 

Model or AssumptionA

 Reference National Full Attainment 

24 NMMAPS Bell et al. 2004 (10--39) 

80 Bell et al. 2005 (42--120) 

110 Ito et al. 2005 (69--150) 

110 

Meta-Analysis 

Levy et al. 2005 (80--140) 

Assumption that association is not causal 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-51 

Table 7-19: Illustrative Strategy to Attain 0.079 ppm: Estimated Annual Reductions in 

the Incidence of Morbidity Associated with Ozone Exposure (Incremental to Current 

Ozone Standard, 95% Confidence Intervals in Parentheses)A,B

 

Morbidity Endpoint National Full Attainment 

190 Hospital Admissions (ages 0-1) (9.0--350) 

190 Hospital Admissions (ages 65-99) (90--280) 

Emergency Department Visits, 87 

Asthma-RelatedC (-5.2--250) 

72,000 School Absences (21,000--110,000) 

180,000 Minor Restricted Activity Days (83,000--270,000) 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

B

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

C

 The negative 5th percentile incidence estimates for this health endpoint are a result of the weak statistical power 

of the study and should not be inferred to indicate that decreased ozone exposure may cause an increase in 

asthma-related emergency department visits.
6-52 

Table 7-20: Illustrative 0.079 ppm Full Attainment Scenario: Estimated Annual 

Reductions in the Incidence of PM Premature Mortality associated with PM co-benefitC 

 

Mortality Endpoint National 2020 Benefits 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA 250 

Harvard Six-City StudyB 560 

Woodruff et al 1997 (infant mortality) 0.71 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A 1,000 

Expert B 760 

Expert C 750 

Expert D 530 

Expert E 1,200 

Expert F 690 

Expert G 440 

Expert H 560 

Expert I 750 

Expert J 600 

Expert K 120 

Expert L 530 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-53 

Table 7-21: Illustrative 0.079 ppm Full Attainment Scenario: 

Estimated Annual Reductions in the Incidence of Morbidity Associated 

with PM Co-benefitA, B, C

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) 240 

Nonfatal myocardial infarction (age >17) 230 

Hospital admissions--respiratory (all ages) 160,000 

Hospital admissions-- cardiovascular (age >17) 4,200 

Emergency room visits for asthma (age <19) 3,100 

Acute bronchitis (age 8-12) 28,000 

Lower respiratory symptoms (age 7-14) 640 

Upper respiratory symptoms (asthmatic children age 9-18) 3,900 

Asthma exacerbation (asthmatic children age 6-18) 67 

Work loss days (age 18-65) 140 

Minor restricted activity days (age 18-65) 570 

 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM 

NAAQS RIA. Estimates do not include confidence intervals because they were derived 

through a scaling technique described above. 

B Morbidity Impact Functions Derived from Epidemiology Literature 

C

 This table reflects full attainment in all locations of the U.S. except two areas of 

California. These two areas, which have high levels of ozone, are not planning to meet the 

current standard until after 2020. The estimates in the table do not reflect benefits for the 

San Joaquin and South Coast Air Basins. 
6-54 

Table 7-22: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence 

Intervals in Parentheses, Millions of 2006$)B,C,D,E

 

Model or 

AssumptionA Reference National Modeled Partial Attainment National Rolled Back Full Attainment 

 $960 $3,500 NMMAPS Bell et al. 

2004 ($140--$2,200) ($510--$7,800) 

Bell et al. $3,100 $11,000 

2005 ($490--6,600) ($1,800--24,000) 

 $4,200 $15,000 Ito et al. 2005 (730--$8,600) (2,700--$31,000) 

 $4,400 $16,000 

Meta-Analysis 

Levy et al. 

2005 ($770--$8,500) ($2,800--$31,000) 

Assumption that association is not 

causal 0 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see 

text in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible 

interval around the mean estimates of the annual number of lives saved are based on an assumption of a 

normal distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a 

confidence interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two 

areas, which have high levels of ozone, are not planning to meet the current standard until after 2020. The 

estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-55 

Table 7-23: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incremental to 

Current Ozone Standard, 95% Confidence Intervals in Parentheses, Millions of 2006$) A,B

 

Morbidity Endpoint 

National Modeled Partial 

Attainment 

National Rolled Back Full 

Attainment 

$6.9 $26 Hospital Admissions (ages 0-1) ($3.4--10) ($14.0--39) 

Hospital Admissions (ages 65- $9.9 $74 

99)C (-$3.3--$24) ($8.40--$140) 

Emergency Department Visits, $0.20 $0.69 

Asthma-RelatedC ($0.0--$0.56) ($0.0--$2.0) 

$27 $99 School Absences ($8.4--$48) ($34--$150) 

 $48 $170 Minor Restricted Activity Days ($18--$89) ($67--$310) 

Worker Productivity $6.8 $49 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. This table reflects full attainment in all locations of the U.S. except two areas 

of California. These two areas, which have high levels of ozone, are not planning to meet the current standard 

until after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

C

 The negative 5th percentile incidence estimates for this health endpoint are a result of the weak statistical power 

of the study and should not be inferred to indicate that decreased ozone exposure may cause an increase in 

asthma-related emergency department visits.
6-56 

Table 7-24: Illustrative 0.065 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of PM Premature Mortality associated with PM 

co-benefit (Millions of 2006$)C 

Mortality Endpoint 

National 2020 Benefits 

(3% discount rate) 

National 2020 Benefits 

(7% discount rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA $9,700 $8,800 

Harvard Six-City StudyB $22,000 $20,000 

Woodruff et al 1997 (infant mortality) $20 $16 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $33,000 $30,000 

Expert B $25,000 $23,000 

Expert C $25,000 $22,000 

Expert D $17,000 $16,000 

Expert E $41,000 $37,000 

Expert F $23,000 $20,000 

Expert G $15,000 $13,000 

Expert H $19,000 $17,000 

Expert I $25,000 $22,000 

Expert J $20,000 $18,000 

Expert K $4,300 $3,900 

Expert L $18,000 $16,000 

 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-57 

Table 7-25: Illustrative 0.065 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of Morbidity Associated with PM Co-benefit 

(Millions of 2006$)A, B, C

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) $480 

Nonfatal myocardial infarction (age >17) 

3% discount rate $250 

7% discount rate $240 

Hospital admissions--respiratory (all ages) $5.8 

Hospital admissions-- cardiovascular (age >17) $15 

Emergency room visits for asthma (age <19) $0.35 

Acute bronchitis (age 8-12) $1.3 

Lower respiratory symptoms (age 7-14) $0.33 

Upper respiratory symptoms (asthmatic children age 9-18) $0.39 

Asthma exacerbation (asthmatic children age 6-18) $0.84 

Work loss days (age 18-65) $14 

Minor restricted activity days (age 18-65) $19 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. 

Estimates do not include confidence intervals because they were derived through a scaling technique described 

above. 

B Morbidity Impact Functions Derived from Epidemiology Literature 

C

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-58 

Table 7-26: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses, Millions of 2006$)B,C,D,E

 

Model or 

AssumptionA Reference National Modeled Partial Attainment National Rolled Back Full Attainment 

 $960 $1,900 NMMAPS Bell et al. 

2004 ($140--$2,200) ($280--$4,300) 

Bell et al. $3,100 $6,200 

2005 ($490--6,600) ($1,000--13,000) 

 $4,200 $8,500 Ito et al. 2005 (730--$8,600) (1,500--$17,000) 

 $4,400 $8,800 

Meta-Analysis 

Levy et al. 

2005 ($770--$8,500) ($1,600--$17,000) 

Assumption that association is not 

causal 0 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-59 

Table 7-27: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incremental to 

Current Ozone Standard, 95% Confidence Intervals in Parentheses, Millions of 2006$) A,B

 

Morbidity Endpoint 

National Modeled Partial 

Attainment 

National Rolled Back Full 

Attainment 

$6.9 $15 Hospital Admissions (ages 0-1) ($3.4--10) ($7.8--23) 

$9.9 $34 Hospital Admissions (ages 65-99) (-$3.3--$24) ($0.59--$67) 

Emergency Department Visits, $0.20 $0.37 

Asthma-Related ($0.0--$0.56) ($0.0--$1.1) 

$27 $57 School Absences ($8.4--$48) ($19--$88) 

 $48 $98 Minor Restricted Activity Days ($18--$89) ($38--$180) 

Worker Productivity $6.8 $27 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. This table reflects full attainment in all locations of the U.S. except two areas 

of California. These two areas, which have high levels of ozone, are not planning to meet the current standard 

until after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-60 

Table 7-28: Illustrative 0.070 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of PM Premature Mortality associated with PM 

co-benefit (Millions of 2006$)C 

Mortality Endpoint 

National 2020 Benefits 

(3% discount rate) 

National 2020 Benefits (7% 

discount rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA $6,000 $5,400 

Harvard Six-City StudyB $13,000 $12,000 

Woodruff et al 1997 (infant mortality) $13 $11 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $21,000 $19,000 

Expert B $16,000 $15,000 

Expert C $16,000 $15,000 

Expert D $11,000 $10,000 

Expert E $27,000 $24,000 

Expert F $15,000 $13,000 

Expert G $9,500 $8,600 

Expert H $12,000 $11,000 

Expert I $16,000 $14,000 

Expert J $13,000 $12,000 

Expert K $2,700 $2,500 

Expert L $12,000 $10,000 

 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. This 

table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the 

table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-61 

Table 7-298: Illustrative 0.070 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of Morbidity Associated with PM Co-benefit 

(Millions of 2006$)A, B, C

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) $310 

Nonfatal myocardial infarction (age >17) 

3% discount rate $160 

7% discount rate $160 

Hospital admissions--respiratory (all ages) $3.7 

Hospital admissions-- cardiovascular (age >17) $9.8 

Emergency room visits for asthma (age <19) $0.22 

Acute bronchitis (age 8-12) $0.85 

Lower respiratory symptoms (age 7-14) $ 0.22 

Upper respiratory symptoms (asthmatic children age 9-18) $0.25 

Asthma exacerbation (asthmatic children age 6-18) $0.54 

Work loss days (age 18-65) $8.9 

Minor restricted activity days (age 18-65) $12 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. 

B Morbidity Impact Functions Derived from Epidemiology Literature 

C

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-62 

Table 7-30: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses, Millions of 2006$)B,C,D,E

 

Model or 

AssumptionA Reference National Full Attainment 

$550 NMMAPS Bell et al. 2004 ($81--$1,200) 

 $1,800 Bell et al. 2005 ($290--3,800) 

 $2,400 Ito et al. 2005 (420--$4,900) 

 $2,500 

Meta-Analysis 

Levy et al. 

2005 ($450--$4,900) 

Assumption that association is not 

causal 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-63 

Table 7-31: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incremental to 

Current Ozone Standard, 95% Confidence Intervals in Parentheses, Millions of 2006$) A,B

 

Morbidity Endpoint National Full Attainment 

$4.8 Hospital Admissions (ages 0-1) ($2.5--$7.1) 

$11 Hospital Admissions (ages 65-99) ($0.89--21) 

Emergency Department Visits, $0.10 

Asthma-Related ($0.00--$0.3) 

$18 School Absences ($6.1--$27) 

$29 Minor Restricted Activity Days ($12--$54) 

Worker Productivity $10 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-64 

Table 7-32: Illustrative 0.075 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of PM Premature Mortality associated with PM 

co-benefit (Millions of 2006$)C 

Mortality Endpoint 

National 2020 Benefits 

(3% discount rate) 

National 2020 Benefits (7% 

discount rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA $3,300 $3,000 

Harvard Six-City StudyB $7,400 $6,600 

Woodruff et al 1997 (infant mortality) $8 $6 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $13,000 $12,000 

Expert B $9,900 $8,900 

Expert C $9,800 $8,900 

Expert D $6,900 $6,200 

Expert E $16,000 $15,000 

Expert F $9,000 $8,100 

Expert G $5,800 $5,200 

Expert H $7,300 $6,600 

Expert I $9,700 $8,800 

Expert J $7,900 $7,100 

Expert K $1,600 $1,500 

Expert L $6,900 $6,200 

 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical and 

totals will not sum across columns. All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include 

confidence intervals because they were derived through a scaling technique described above. This table reflects 

full attainment in all locations of the U.S. except two areas of California. These two areas, which have high levels 

of ozone, are not planning to meet the current standard until after 2020. The estimates in the table do not reflect 

benefits for the San Joaquin and South Coast Air Basins. 
6-65 

Table 7-33: Illustrative 0.075 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of Morbidity Associated with PM Co-benefit 

(Millions of 2006$)A, B, C

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) $180 

Nonfatal myocardial infarction (age >17) 

3% discount rate $97 

7% discount rate $94 

Hospital admissions--respiratory (all ages) $2.3 

Hospital admissions-- cardiovascular (age >17) $5.9 

Emergency room visits for asthma (age <19) $0.13 

Acute bronchitis (age 8-12) $0.51 

Lower respiratory symptoms (age 7-14) $0.13 

Upper respiratory symptoms (asthmatic children age 9-18) $0.15 

Asthma exacerbation (asthmatic children age 6-18) $0.33 

Work loss days (age 18-65) $5.3 

Minor restricted activity days (age 18-65) $7.2 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. 

Estimates do not include confidence intervals because they were derived through a scaling technique described 

above. 

B Morbidity Impact Functions Derived from Epidemiology Literature 

C

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates 

in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-66 

Table 7-34: Illustrative Strategy to Attain 0.079 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure 

(Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals 

in Parentheses, Millions of 2006$)B,C,D,E

 

Model or 

AssumptionA Reference National Full Attainment 

$190 NMMAPS Bell et al. 2004 ($28--$420) 

 $620 Bell et al. 2005 ($100--1,300) 

 $830 Ito et al. 2005 (140--$1,700) 

 $860 

Meta-Analysis 

Levy et al. 

2005 ($160--$1,700) 

Assumption that association is not 

causal 0 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 With the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval 

around the mean estimates of the annual number of lives saved are based on an assumption of a normal 

distribution. 

C

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. 

D All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

E

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-67 

Table 7-35: Illustrative Strategy to Attain 0.079 ppm: Estimated Annual Valuation of 

Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incremental to 

Current Ozone Standard, 95% Confidence Intervals in Parentheses, Millions of 2006$) A,B

 

Morbidity Endpoint National Full Attainment 

$4.4 Hospital Admissions (ages 0-1) ($0.60--$7.9) 

$1.9 Hospital Admissions (ages 65-99) ($0.98--2.7) 

Emergency Department Visits, $0.03 

Asthma-Related ($0.00--$0.09) 

$6.4 School Absences ($2.2--$9.5) 

$11 Minor Restricted Activity Days ($4.2--$19) 

Worker Productivity $4.7 

 

A All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. 

B This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-68 

Table 7-36: Illustrative 0.079 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of PM Premature Mortality associated with PM 

co-benefit (Millions of 2006$)C 

Mortality Endpoint 

National 2020 Benefits 

(3% discount rate) 

National 2020 Benefits (7% 

discount rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyA $1,800 $1,600 

Harvard Six-City StudyB $4,100 $3,700 

Woodruff et al 1997 (infant mortality) $5.0 $4.0 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $8,400 $7,600 

Expert B $6,400 $5,700 

Expert C $6,400 $5,700 

Expert D $4,400 $4,000 

Expert E $11,000 $9,500 

Expert F $5,800 $5,200 

Expert G $3,700 $3,400 

Expert H $4,700 $4,300 

Expert I $6,300 $5,700 

Expert J $5,100 $4,600 

Expert K $1,000 $910 

Expert L $4,400 $3,900 

 

A The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

B

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

C All estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. All 

estimates incremental to 2006 PM NAAQS RIA. Estimates do not include confidence intervals because they were 

derived through a scaling technique described above. This table reflects full attainment in all locations of the U.S. 

except two areas of California. These two areas, which have high levels of ozone, are not planning to meet the 

current standard until after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South 

Coast Air Basins. 
6-69 

Table 7-37: Illustrative 0.079 ppm Full Attainment Scenario: Estimated Annual 

Valuation of Reductions in the Incidence of Morbidity Associated with PM Co-benefit 

(Millions of 2006$)A, B, C

 

Morbidity Endpoint National 2020 Benefits 

Chronic Bronchitis (age >25 and over) $120 

Nonfatal myocardial infarction (age >17) 

3% discount rate $62 

7% discount rate $60 

Hospital admissions--respiratory (all ages) $1.4 

Hospital admissions-- cardiovascular (age >17) $3.8 

Emergency room visits for asthma (age <19) $0.086 

Acute bronchitis (age 8-12) $0.33 

Lower respiratory symptoms (age 7-14) $0.083 

Upper respiratory symptoms (asthmatic children age 9-18) $0.10 

Asthma exacerbation (asthmatic children age 6-18) $0.21 

Work loss days (age 18-65) $3.4 

Minor restricted activity days (age 18-65) $4.6 

A All estimates rounded to two significant figures. All estimates incremental to 2006 PM NAAQS RIA. Estimates 

do not include confidence intervals because they were derived through a scaling technique described above. 

B Morbidity Impact Functions Derived from Epidemiology Literature 

C

 This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-70 

Table 7-38: Estimate of Annual Ozone and PM2.5 Combined Morbidity and Mortality 

(Millions of 2006$) for the 0.065 ppm Full Attainment 

 

Ozone Mortality and Morbidity Benefits of Attaining 0.065 ppm Total 

NMMAPS Bell (2004) $3,900 

Bell (2005) $12,000 

Meta-Analysis Ito (2005) $16,000 

Levy (2005) $16,000 

No Causality $420 

 

PM2.5 Mortality and Morbidity Benefits of Attaining 0.065 ppm 

Total (3% 

Discount Rate) 

Total (7% 

Discount Rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyC $11,000 $9,600 

Harvard Six-City StudyD $23,000 $20,000 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $34,000 $31,000 

Expert B $26,000 $24,000 

Expert C $26,000 $23,000 

Expert D $18,000 $17,000 

Expert E $42,000 $38,000 

Expert F $24,000 $21,000 

Expert G $15,000 $14,000 

Expert H $19,000 $18,000 

Expert I $25,000 $23,000 

Expert J $21,000 $19,000 

Expert K $5,100 $4,700 

Expert L $19,000 $17,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. Credible intervals for ozone estimates and confidence intervals for PM2.5

estimates not provided because the valuation estimates were derived through a scaling technique (see above) that 

precluded us from generating such estimates. 

C

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

D Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

E

 All estimates incremental to 2006 PM NAAQS RIA. Estimates derived using benefit per ton estimates 

discounted at 3% and 7%. This table reflects full attainment in all locations of the U.S. except two areas of 

California. These two areas, which have high levels of ozone, are not planning to meet the current standard until 

after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-71 

Table 7-39: Estimate of Annual Ozone and PM2.5 Combined Morbidity and Mortality 

(Millions of 2006$) for the 0.070 ppm Full Attainment 

 

Ozone Mortality and Morbidity Benefits of Attaining 0.070 ppm Total 

NMMAPS Bell (2004) $2,200 

Bell (2005) $6,500 

Meta-Analysis Ito (2005) $8,800 

Levy (2005) $9,000 

No Causality $230 

 

PM2.5 Mortality and Morbidity Benefits of Attaining 0.070 ppm 

Total (3% 

Discount Rate) 

Total (7% 

Discount Rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyC $6,500 $5,900 

Harvard Six-City StudyD $14,000 $13,000 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $22,000 $20,000 

Expert B $17,000 $15,000 

Expert C $17,000 $15,000 

Expert D $12,000 $11,000 

Expert E $27,000 $24,000 

Expert F $15,000 $14,000 

Expert G $10,000 $9,100 

Expert H $13,000 $11,000 

Expert I $17,000 $15,000 

Expert J $13,000 $12,000 

Expert K $3,200 $3,000 

Expert L $12,000 $11,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. Credible intervals for ozone estimates and confidence intervals for PM2.5

estimates not provided because the valuation estimates were derived through a scaling technique (see above) that 

precluded us from generating such estimates. 

C

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

D Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

E

 All estimates incremental to 2006 PM NAAQS RIA. Estimates derived using benefit per ton estimates 

discounted at 3% and 7%. This table reflects full attainment in all locations of the U.S. except two areas of 

California. These two areas, which have high levels of ozone, are not planning to meet the current standard until 

after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-72 

Table 7-40: Estimate of Annual Ozone and PM2.5 Combined Morbidity and Mortality 

(Millions of 2006$) for the 0.075 ppm Full Attainment 

 

Ozone Mortality and Morbidity Benefits of Attaining 0.075 ppm Total 

NMMAPS Bell (2004) $620 

Bell (2005) $1,900 

Meta-Analysis Ito (2005) $2,500 

Levy (2005) $2,600 

No Causality $73 

 

PM2.5 Mortality and Morbidity Benefits of Attaining 0.075 ppm 

Total (3% 

Discount Rate) 

Total (7% 

Discount Rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyC $3,600 $3,300 

Harvard Six-City StudyD $7,700 $7,000 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $13,000 $12,000 

Expert B $10,000 $9,200 

Expert C $10,000 $9,200 

Expert D $7,200 $6,500 

Expert E $16,000 $15,000 

Expert F $9,300 $8,400 

Expert G $6,100 $5,500 

Expert H $7,600 $6,900 

Expert I $10,000 $9,100 

Expert J $8,200 $7,400 

Expert K $1,900 $1,800 

Expert L $7,200 $6,500 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. Credible intervals for ozone estimates and confidence intervals for PM2.5

estimates not provided because the valuation estimates were derived through a scaling technique (see above) that 

precluded us from generating such estimates. 

C

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

D Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

E

 All estimates incremental to 2006 PM NAAQS RIA. Estimates derived using benefit per ton estimates 

discounted at 3% and 7%. This table reflects full attainment in all locations of the U.S. except two areas of 

California. These two areas, which have high levels of ozone, are not planning to meet the current standard until 

after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-73 

Table 7-41: Estimate of Annual Ozone and PM2.5 Combined Morbidity and Mortality 

(Millions of 2006$) for the 0.079 ppm Full Attainment 

 

Ozone Mortality and Morbidity Benefits of Attaining 0.079 ppm Total 

NMMAPS Bell (2004) $220 

Bell (2005) $640 

Meta-Analysis Ito (2005) $860 

Levy (2005) $890 

No Causality $28 

 

PM2.5 Mortality and Morbidity Benefits of Attaining 0.079 ppm 

Total (3% 

Discount Rate) 

Total (7% 

Discount Rate) 

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyC $2,000 $1,800 

Harvard Six-City StudyD $4,300 $3,900 

Mortality Impact Functions Derived from Expert Elicitation 

Expert A $8,600 $7,800 

Expert B $6,600 $5,900 

Expert C $6,600 $5,900 

Expert D $4,600 $4,200 

Expert E $11,000 $9,700 

Expert F $6,000 $5,400 

Expert G $3,900 $3,600 

Expert H $4,900 $4,500 

Expert I $6,500 $5,900 

Expert J $5,300 $4,800 

Expert K $1,200 $1,100 

Expert L $4,600 $4,100 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text 

in section 6.3.2.1). 

B

 A credible interval is a posterior probability interval used in Bayesian statistics, which is similar to a confidence 

interval used in frequentist statistics. Credible intervals for ozone estimates and confidence intervals for PM2.5

estimates not provided because the valuation estimates were derived through a scaling technique (see above) that 

precluded us from generating such estimates. 

C

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs. 

D Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for 

advice on the appropriate method for incorporating what has previously been a sensitivity estimate. 

E

 All estimates incremental to 2006 PM NAAQS RIA. Estimates derived using benefit per ton estimates 

discounted at 3% and 7%. This table reflects full attainment in all locations of the U.S. except two areas of 

California. These two areas, which have high levels of ozone, are not planning to meet the current standard until 

after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-74 

Table 7-42: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

3% Discount Rate) for the 0.065 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $14,000 $22,000 $26,000 $27,000 $11,000 

Harvard Six-City StudyC

 $26,000 $34,000 $38,000 $39,000 $23,000 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $34,000 $38,000 $46,000 $50,000 $50,000 

Expert B $26,000 $30,000 $38,000 $42,000 $42,000 

Expert C $26,000 $30,000 $38,000 $42,000 $42,000 

Expert D $19,000 $22,000 $30,000 $34,000 $35,000 

Expert E $42,000 $46,000 $54,000 $58,000 $58,000 

Expert F $24,000 $27,000 $35,000 $39,000 $40,000 

Expert G $16,000 $19,000 $27,000 $31,000 $32,000 

Expert H $20,000 $23,000 $31,000 $35,000 $36,000 

Expert I $26,000 $29,000 $37,000 $41,000 $42,000 

Expert J $21,000 $25,000 $33,000 $37,000 $37,000 

Expert K $5,500 $9,000 $17,000 $21,000 $21,000 

Expert L $19,000 $23,000 $30,000 $35,000 $35,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-75 

Table 7-43: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

7% Discount Rate) for the 0.065 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $13,000 $21,000 $25,000 $26,000 $10,000 

Harvard Six-City StudyC

 $24,000 $32,000 $36,000 $37,000 $21,000 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $34,000 $42,000 $46,000 $47,000 $31,000 

Expert B $27,000 $35,000 $39,000 $40,000 $24,000 

Expert C $27,000 $35,000 $39,000 $40,000 $24,000 

Expert D $20,000 $28,000 $32,000 $33,000 $17,000 

Expert E $42,000 $50,000 $54,000 $54,000 $38,000 

Expert F $25,000 $33,000 $37,000 $38,000 $22,000 

Expert G $18,000 $26,000 $30,000 $30,000 $14,000 

Expert H $21,000 $29,000 $33,000 $34,000 $18,000 

Expert I $27,000 $35,000 $39,000 $39,000 $23,000 

Expert J $23,000 $31,000 $35,000 $35,000 $19,000 

Expert K $8,600 $16,000 $21,000 $21,000 $5,100 

Expert L $21,000 $29,000 $33,000 $33,000 $17,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-76 

Table 7-44: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

3% Discount Rate) for the 0.070 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $8,700 $13,000 $15,000 $16,000 $6,700 

Harvard Six-City StudyC

 $16,000 $20,000 $23,000 $23,000 $14,000 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $24,000 $28,000 $31,000 $31,000 $22,000 

Expert B $19,000 $23,000 $26,000 $26,000 $17,000 

Expert C $19,000 $23,000 $25,000 $26,000 $17,000 

Expert D $14,000 $18,000 $21,000 $21,000 $12,000 

Expert E $29,000 $34,000 $36,000 $36,000 $27,000 

Expert F $17,000 $22,000 $24,000 $24,000 $15,000 

Expert G $12,000 $16,000 $19,000 $19,000 $10,000 

Expert H $15,000 $19,000 $21,000 $22,000 $13,000 

Expert I $19,000 $23,000 $25,000 $26,000 $17,000 

Expert J $16,000 $20,000 $22,000 $22,000 $14,000 

Expert K $5,400 $9,700 $12,000 $12,000 $3,500 

Expert L $14,000 $19,000 $21,000 $21,000 $12,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-77 

Table 7-45: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

7% Discount Rate) for the 0.070 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $8,100 $12,000 $15,000 $15,000 $6,100 

Harvard Six-City StudyC

 $15,000 $19,000 $21,000 $22,000 $13,000 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $22,000 $26,000 $29,000 $29,000 $20,000 

Expert B $17,000 $22,000 $24,000 $24,000 $15,000 

Expert C $17,000 $22,000 $24,000 $24,000 $15,000 

Expert D $13,000 $17,000 $19,000 $20,000 $11,000 

Expert E $27,000 $31,000 $33,000 $33,000 $25,000 

Expert F $16,000 $20,000 $23,000 $23,000 $14,000 

Expert G $11,000 $16,000 $18,000 $18,000 $9,300 

Expert H $14,000 $18,000 $20,000 $20,000 $12,000 

Expert I $17,000 $21,000 $24,000 $24,000 $15,000 

Expert J $14,000 $19,000 $21,000 $21,000 $12,000 

Expert K $5,100 $9,500 $12,000 $12,000 $3,200 

Expert L $13,000 $17,000 $20,000 $20,000 $11,000 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-78 

Table 7-46: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

3% Discount Rate) for the 0.075 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $4,200 $5,500 $6,100 $6,200 $3,700 

Harvard Six-City StudyC

 $8,300 $9,500 $10,000 $10,000 $7,800 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $14,000 $15,000 $16,000 $16,000 $13,000 

Expert B $11,000 $12,000 $13,000 $13,000 $10,000 

Expert C $11,000 $12,000 $13,000 $13,000 $10,000 

Expert D $7,800 $9,000 $9,700 $9,800 $7,300 

Expert E $17,000 $18,000 $19,000 $19,000 $17,000 

Expert F $9,900 $11,000 $12,000 $12,000 $9,300 

Expert G $6,700 $7,900 $8,600 $8,700 $6,100 

Expert H $8,300 $9,500 $10,000 $10,000 $7,700 

Expert I $11,000 $12,000 $13,000 $13,000 $10,000 

Expert J $8,800 $10,000 $11,000 $11,000 $8,300 

Expert K $2,600 $3,800 $4,400 $4,500 $2,000 

Expert L $7,800 $9,000 $9,700 $9,800 $7,300 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-79 

Table 7-47: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

7% Discount Rate) for the 0.075 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $3,900 $5,100 $5,800 $5,900 $3,400 

Harvard Six-City StudyC

 $7,600 $8,800 $9,500 $9,500 $7,000 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $13,000 $14,000 $15,000 $15,000 $12,000 

Expert B $9,800 $11,000 $12,000 $12,000 $9,300 

Expert C $9,800 $11,000 $12,000 $12,000 $9,200 

Expert D $7,100 $8,400 $9,000 $9,100 $6,600 

Expert E $16,000 $17,000 $17,000 $17,000 $15,000 

Expert F $9,000 $10,000 $11,000 $11,000 $8,500 

Expert G $6,100 $7,400 $8,000 $8,100 $5,600 

Expert H $7,500 $8,800 $9,400 $9,500 $7,000 

Expert I $9,700 $11,000 $12,000 $12,000 $9,100 

Expert J $8,000 $9,300 $9,900 $10,000 $7,500 

Expert K $2,400 $3,600 $4,300 $4,300 $1,800 

Expert L $7,100 $8,400 $9,000 $9,100 $6,600 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-80 

Table 7-48: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

3% Discount Rate) for the 0.079 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $2,200 $2,700 $2,900 $2,900 $2,100 

Harvard Six-City StudyC

 $4,500 $4,900 $5,200 $5,200 $4,300 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $8,900 $9,300 $9,500 $9,500 $8,700 

Expert B $6,800 $7,200 $7,400 $7,400 $6,600 

Expert C $6,800 $7,200 $7,400 $7,500 $6,600 

Expert D $4,900 $5,300 $5,500 $5,500 $4,700 

Expert E $11,000 $11,000 $12,000 $12,000 $11,000 

Expert F $6,200 $6,700 $6,900 $6,900 $6,000 

Expert G $4,100 $4,600 $4,800 $4,800 $4,000 

Expert H $5,200 $5,600 $5,800 $5,800 $5,000 

Expert I $6,700 $7,200 $7,400 $7,400 $6,500 

Expert J $5,500 $5,900 $6,200 $6,200 $5,300 

Expert K $1,400 $1,900 $2,100 $2,100 $1,200 

Expert L $4,800 $5,200 $5,400 $5,400 $4,600 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate in 

recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which 

have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in the table 

do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-81 

Table 7-49: Combined Estimate of Annual Ozone and PM2.5 Benefits (Millions of $2006, 

7% Discount Rate) for the 0.079 ppm Alternative Standard 

Alternative Standard and Model or AssumptionA

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Derived from Epidemiology Literature 

ACS StudyB $2,100 $2,500 $2,700 $2,700 $1,900 

Harvard Six-City StudyC

 $4,100 $4,500 $4,800 $4,800 $3,900 

Mortality Impact Functions Derived from Expert Elicitation

Expert A $8,000 $8,400 $8,700 $8,700 $7,800 

Expert B $6,100 $6,600 $6,800 $6,800 $5,900 

Expert C $6,200 $6,600 $6,800 $6,800 $6,000 

Expert D $4,400 $4,800 $5,100 $5,100 $4,200 

Expert E $9,900 $10,000 $11,000 $11,000 $9,700 

Expert F $5,600 $6,100 $6,300 $6,300 $5,500 

Expert G $3,800 $4,200 $4,400 $4,400 $3,600 

Expert H $4,700 $5,100 $5,300 $5,400 $4,500 

Expert I $6,100 $6,500 $6,700 $6,800 $5,900 

Expert J $5,000 $5,400 $5,700 $5,700 $4,800 

Expert K $1,300 $1,800 $2,000 $2,000 $1,100 

Expert L $4,300 $4,800 $5,000 $5,000 $4,100 

 

A Does not represent equal weighting among models or between assumption of causality vs. no causality (see text in 

section 6.3.2.1). 

B

 The estimate is based on the concentration-response (C-R) function developed from the study of the American 

Cancer Society cohort reported in Pope et al (2002), which has previously been reported as the primary estimate 

in recent RIAs 

C

 Based on Laden et al (2006) reporting of the extended Six-cities study; to be reviewed by the EPA-SAB for advice 

on the appropriate method for incorporating what has previously been a sensitivity estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals for PM2.5 estimates not provided due to 

the fact that the valuation estimates were derived through a scaling technique (see above) that precluded us from 

generating such estimates. Estimates derived using a combination of modeling data and benefit per ton estimates. 

This table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, 

which have high levels of ozone, are not planning to meet the current standard until after 2020. The estimates in 

the table do not reflect benefits for the San Joaquin and South Coast Air Basins. 
6-82 

Figure 6.3: Ozone and PM2.5 Benefits by Standard Alternative (3% and 7% Discount 

Rates) 

Figure 7.3 graphically shows the breakdown between ozone and PM morbidity and mortality 

monetized benefits for one example combination with PM benefits discounted at 3% and 7%, 

respectively. This example combination of Bell 2004 and Pope have been used in previous 

RIAs and Risk Assessments. 
6-83 

Figure 6.4: Example Combined Ozone and PM2.5 Monetized Benefits Estimates by 

Standard Alternative (3% and 7% Discount Rates)* 

Figure 7.4 graphically shows four combinations of ozone and PM benefits estimates. These 

intermediate combinations represent reference points: 

• Bell 2004 is the epidemiological study that underlies the ozone NAAQS risk assessment and Pope 

is the PM mortality function that was in several EPA RIAs, and 

• Bell 2005 is one of three ozone meta-analyses and Laden is a more recent PM epidemiological 

study that was used as an alternative in the PM NAAQS RIA 
6-84 

Figure 6.5 and Figure 6.6 show the complete range of combinations of ozone and PM mortality 

functions at 3 and 7 percent, respectively. These graphs display all possible combinations of 

benefits, utilizing the five different ozone functions and the fourteen different PM functions, for 

each standard alternative. Each of the 70 bars represents an independent and equally probably 

point estimate of benefits under a certain combination of ozone and PM functions. Thus it is not 

possible to infer the likelihood of any single benefit estimate. 

Figure 6.5:* 

079

075

070 

0 065

10000

20000

30000

40000

50000

60000

Millions of 2006$

Ozone and PM Total Benefits including all combinations of mortality 

estimates 

(3% Discount Rate)

No Causality & Expert K

Bell 2004 & Pope

Bell 2005 & Laden

Levy & Expert E

* These figures reflect full attainment in all locations of the U.S. except two areas of California. 

These two areas, which have high levels of ozone, are not planning to meet the current 

standard until after 2020. The estimates in the table do not reflect benefits for the San Joaquin 

and South Coast Air Basins. No causality, Bell, and Levy represent ozone estimates. Expert 

K, Pope, Laden, and Expert E represent PM estimates. 
6-85 

Figure 6.6*: 

079

075 

070 

065

0

10000

20000

30000

40000

50000

60000

Millions of 2006$

Ozone and PM Total Benefits including all combinations of mortality 

estimates

 (7% Discount Rate)

No Causality & Expert K

Bell 2004 & Pope

Bell 2005 & Laden

Levy & Expert E

* These figures reflect full attainment in all locations of the U.S. except two areas of California. 

These two areas, which have high levels of ozone, are not planning to meet the current 

standard until after 2020. The estimates in the table do not reflect benefits for the San Joaquin 

and South Coast Air Basins. No causality, Bell, and Levy represent ozone estimates. Expert K, 

Pope, Laden, and Expert E represent PM estimates. 
6-86 

6.5.4 Estimates of Visibility Benefits 

Table 7-50 below summarizes the regional distribution of visibility benefits in Class I areas in 

2020. Note that these estimates represent the monetized visibility benefits associated with the 

modeled ozone emission control strategy, and do not reflect the visibility benefits of fully 

attaining the 0.075 ppm selected alternative. For this reason, they are not added to the human 

health-based benefits estimates. The methodology we followed to generate these estimates may 

be found in the PM2.5 RIA (EPA, 2006) 

Table 7-50: Monetary Benefits Associated with Visibility Improvements from the 

0.070 Simulated Ozone Attainment Strategy in Selected Federal Class I Areas in 

2020 (in millions of 2006$)A

 

California Southwest Southeast Total 

$5 $95 $56 $160 

 

A All estimates are rounded to 2 significant digits. All rounding occurs after final summing of unrounded 

estimates. As such, totals will not sum across columns. 

6.5.5 Discussion of Results and Uncertainties 

The results of this analysis suggest there will be significant additional health and welfare benefits 

arising from reducing emissions from a variety of sources in and around projected nonattaining 

counties in 2020. While 2020 is the expected date that states would need to demonstrate 

attainment with the revised standard, it is expected that benefits (and costs) will begin occurring 

much earlier, as states begin implementing control measures to show reasonable progress 

towards attainment. Using the full range of benefits (including the results of the expert 

elicitation), we estimate that total ozone benefits and PM2.5 co-benefits would be between $2.0 

and $19 billion annually for the 0.075 ppm selected alternative when the emissions reductions 

from implementing the new standard are fully realized. The magnitude of these estimated 

benefits provide additional evidence of the important role that implementation of the standards 

plays in reducing the health risks associated with exceeding the standard. 

There are several important factors to consider when evaluating the relative benefits of the 

attainment strategies for each of the alternative ozone standards: 

1. California (outside of San Joaquin Valley and South Coast) accounts for a substantial 

share of the total benefits for each of the evaluated standards. Benefits are most 

uncertain for California due to the unique challenge of modeling attainment with the 

standards in this state. These challenges include high levels of ozone, difficulties in 

modeling the impacts of emissions controls on air quality, and the very large proportion 

of California benefits that were derived through extrapolation. On the one hand, these 

California benefits are likely to understate the actual benefits of attainment strategies, 

because we applied an estimation approach that reduced concentrations only at the 

specific violating monitors and not surrounding monitors that did not violate the 
6-87 

standards. The magnitude of this underestimate is unknown. On the other hand, it is 

possible that new technologies might not meet the specifications, development timelines, 

or cost estimates provided in this analysis, thereby increasing the uncertainty in when and 

if such benefits would be truly achieved. 

2. The extrapolation and interpolation techniques used to estimate the full attainment 

benefits of the selected and three alternate standards contributed some uncertainty to the 

analysis. The great majority of benefits estimated for the 0.065 ppm standard alternative 

were derived through extrapolation. As noted previously in this chapter, these benefits are 

likely to be more uncertain than the modeled benefits. The 0.075 ppm and 0.079 ppm 

benefits were derived by interpolating the full attainment benefits of the 0.070 ppm 

alternative (a process which is described in Appendix 6a). This approach may under- or 

over-estimate benefits if the actual geographic distribution of air quality changes is 

different than that assumed in the interpolation. 

3. There are a variety of uncertainties associated with the health impact functions used in 

this modeling effort. These include: within study variability, which is the precision with 

which a given study estimates the relationship between air quality changes and health 

effects; across study variation, which refers to the fact that different published studies of 

the same pollutant/health effect relationship typically do not report identical findings and 

in some instances the differences are substantial; the application of C-R functions 

nationwide, which does not account for any relationship between region and health effect, 

to the extent that such a relationship exists; extrapolation of impact functions across 

population, in which we assumed that certain health impact functions applied to age 

ranges broader than that considered in the original epidemiological study; and, finally, 

there are various uncertainties in the C-R function, including causality, the correlation 

among multiple pollutants, the shape of the C-R function and the relative toxicity of PM 

component species, and the lag between exposure and the onset of the health effect. 

4. There are a variety of uncertainties associated with the economic valuation of the health 

endpoints estimated in this analysis. Uncertainties specific to the valuation of premature 

mortality include across study variation; the assumption that WTP for mortality risk 

reduction is linear; assuming that voluntary and involuntary mortality risk will be valued 

equally; assuming that premature mortality from air pollution risk, which tend to involve 

longer periods of time, will be valued the same as short catastrophic events; the 

possibility for self-selection in avoiding risk, which may bias WTP estimates upward. 

5. This analysis includes estimates of PM2.5 co-benefits that were derived through benefit 

per-ton estimates. These benefit per-ton estimates represent regional averages. As such, 

they do not reflect any local variability in the incremental PM2.5 benefits per ton of NOx 

abated. As discussed in the PM2.5 NAAQS RIA (Table 5.5), there are a variety of 

uncertainties associated with these PM benefits. 

6. PM2.5 co-benefits represent a substantial proportion of total benefits. For the 0.075 ppm 

selected standard, we estimate co-benefits from PM to be between 42% and 99% of total 

benefits, depending on the PM2.5 and ozone mortality functions used. When calculating 

PM2.5 co-benefits we assume that states will pursue an ozone strategy that reduces NOx 
6-88 

emissions. As such, these estimates are strongly influenced by the assumption that all PM 

components are equally toxic. We also acknowledge that when implementing any new 

standard, states may elect to pursue a different ozone strategy, which would in turn affect 

the level of PM2.5 co-benefits. 

7. Projecting key variables introduces uncertainty. Inherent in any analysis of future 

regulatory programs are uncertainties in projecting atmospheric conditions and sourcelevel emissions, as well as population, health baselines, incomes, technology, and other 

factors. In addition, data limitations prevent an overall quantitative estimate of the 

uncertainty associated with estimates of total economic benefits. If one is mindful of 

these limitations, the magnitude of the benefits estimates presented here can be useful 

information in expanding the understanding of the public health impacts of reducing 

ozone precursor emissions. 

8. This analysis omits certain unquantified effects due to lack of data, time and resources. 

These unquantified endpoints include the direct effects of ozone on vegetation, the 

deposition of nitrogen to estuarine and coastal waters and agricultural and forested land, 

and the changes in the level of exposure to ultraviolet radiation from ground level ozone. 

EPA will continue to evaluate new methods and models and select those most appropriate 

for estimating the health benefits of reductions in air pollution. It is important to continue 

improving benefits transfer methods in terms of transferring economic values and 

transferring estimated impact functions. The development of both better models of 

current health outcomes and new models for additional health effects such as asthma, 

high blood pressure, and adverse birth outcomes (such as low birth weight) will be 

essential to future improvements in the accuracy and reliability of benefits analyses (Guo 

et al., 1999; Ibald-Mulli et al., 2001). Enhanced collaboration between air quality 

modelers, epidemiologists, toxicologists, and economists should result in a more tightly 

integrated analytical framework for measuring health benefits of air pollution policies. 

Readers interested in a more extensive discussion of the sources of uncertainty in human 

health benefits analyses should consult the PM NAAQS RIA. 

6.5.6 Summary of Total Benefits 

Table 6.51 presents the total number of estimated ozone and PM2.5-related premature mortalities 

and morbidities avoided nationwide in 2020. Ranges within the mortality section reflect 

variability in the studies upon which the estimates associated with premature mortality were 

derived. The lower end of the range reflects the Expert K derived mortality functions, and the 

upper end of the range reflects the Expert E derived mortality functions. Figure 6.7 graphically 

presents the total number of estimated ozone and PM2.5-related premature mortalities avoided in 

2020 by standard. Tables 6.52 through 6.56 show the overall ozone, PM, and combined results 

with regional breakdowns. 
6-89 

Table 6.51: Summary of Total Number of Annual Ozone and PM2.5 -Related Premature Mortalities and Prem

2020A

Combined Estimate of Mortality

 Combined Range of Ozone Benefits and PM2.5 Co-benefits by 

Model or Assumption 0.079 ppm 0.075 ppm 0.070 ppm 

NMAPS Bell (2004) 140 to 1,300 260 to 2,000 560 to  Bell (2005) 200 to 1,300 420 to 2,200 1,100 to Meta-analysis Ito 230 to 1,400 500 to 2,300 1,400 to  Levy 230 to 1,400 510 to 2,300 1,400 to No Causality 120 to 1,200 190 to 2,000 310 to 

Combined Estimate of Morbidity Combined Ozone Benefits and PM2.5 Co-benefits by Stan

Acute Myocardial InfarctionB 570 890 1,500 

Upper Respiratory SymptomsB 3,100 4,900 8,100 Lower Respiratory SymptomsB 4,200 6,700 11,000 Chronic BronchitisB 240 380 630 Acute BronchitisB 640 1,000 1,700 Asthma ExacerbationB 3,900 6,100 10,000 Work Loss DaysB 28,000 43,000 72,000 School Loss DaysC 72,000 200,000 640,000 Hospital and ER Visits 890 1,900 5,100 Minor Restricted Activity Days 340,000 750,000 2,100,000 A Does not reflect estimates for the San Joaquin and South Coast Air Basins B PM-related benefits only C Ozone-related benefits only D Includes ozone benefits, and PM2.5 co-benefits. Range was developed by adding the estimate from the ozone premature morta

lower and upper ends of the range of the PM2.5 premature mortality functions characterized in the expert elicitation. 
6-90 

Figure 6.7: Total Annual Ozone and PM2.5-Related Premature Mortalities Avoided in 2020 by Stand
6-91 

Table 6.52: Regional Breakdown of Annual Ozone Benefit Results by Health Endpoint in 2020 (thous

Endpoint Group Author Year 079 Valuation 079 Incidence 075 Valuation 075 Incidence 070 Valuation 070 Incidence 065 Val

Hospital Admissions, Respiratory (0-1) 470 $ 47 2,200 $ 220 8,800 $ 880 

$ 

Hospital Admissions, Respiratory (65+) 1,300 $ 54 5,200 $ 220 20,000 $ 870 

$ 

Emergency Room Visits, Respiratory 13 $ 35 68 $ 190 290 $ 770 

$ 

School Loss Days 1,700 $ 19,000 8,500 $ 95,000 35,000 $ 390,000 

$ 

Worker Productivity 430 $ 370,000 2,100 $ 1,800,000 8,700 $ 7,500,000 

$ 

Acute Respiratory Symptoms 2,800 $ 47,000 15,000 $ 250,000 61,000 $ 1,000,000 1

$ 

Mortality Bell et al. 2004 50,000 $ 7 290,000 $ 38 1,300,000 $ 170 2,4

$ 

Mortality Bell et al. 2005 160,000 $ 21 940,000 $ 120 4,100,000 $ 530 7,6

$ 

Mortality Ito et al. 220,000 $ 29 1,300,000 $ 170 5,600,000 $ 730 10,0

$ 

Mortality Levy et al. 230,000 $ 30 1,300,000 $ 170 5,800,000 $ 750 11,0

$ 

Hospital Admissions, Respiratory (0-1) 10 $ 1.0 18 $ 1.8 820 $ 83 

$ 

Emergency Room Visits, Respiratory 0.14 $ 0.39 0.27 $ 0.74 9.4 $ 26 

$ 

School Loss Days 33 $ 370 60 $ 670 2,600 $ 29,000 

$ 

Worker Productivity 6.3 $ 5,500 11 $ 9,900 360 $ 310,000 

$ 

Acute Respiratory Symptoms 61 $ 1,000 110 $ 1,800 4,500 $ 76,000 

$ 

Hospital Admissions, Respiratory (65+) 30 $ 1.3 58 $ 2.5 (39) $ (1.6) 

$ 

Mortality Bell et al. 2004 1,500 $ 0.20 2,700 $ 0.35 69,000 $ 9.0 2

$ 

Mortality Bell et al. 2005 5,100 $ 0.65 8,900 $ 1.2 230,000 $ 30 6

$ 

Mortality Ito et al. 6,800 $ 0.88 12,000 $ 1.6 310,000 $ 40 9

$ 

Mortality Levy et al. 7,100 $ 0.92 13,000 $ 1.6 320,000 $ 42 9

$ 

Hospital Admissions, Respiratory (0-1) 1,400 $ 140 2,600 $ 260 5,800 $ 580 

$ 

Emergency Room Visits, Respiratory 19 $ 51 36 $ 97 79 $ 220 

$ 

School Loss Days 4,700 $ 53,000 9,000 $ 100,000 20,000 $ 220,000 

$ 

Worker Productivity 4,300 $ 3,800,000 8,000 $ 7,100,000 18,000 $ 16,000,000 

$ 

Acute Respiratory Symptoms 7,800 $ 130,000 15,000 $ 250,000 33,000 $ 550,000 

$ 

Hospital Admissions, Respiratory (65+) 3,100 $ 130 5,800 $ 240 13,000 $ 560 

$ 

Mortality Bell et al. 2004 140,000 $ 18 260,000 $ 33 580,000 $ 75 9

$ 

Mortality Bell et al. 2005 450,000 $ 58 840,000 $ 110 1,900,000 $ 250 3,1

$ 

Mortality Ito et al. 610,000 $ 78 1,100,000 $ 150 2,600,000 $ 330 4,2

$ 

Mortality Levy et al. 630,000 $ 81 1,200,000 $ 150 2,700,000 $ 340 4,3

$ 

Hospital Admissions, Respiratory (0-1) 1,900 $ 190 4,800 $ 480 15,000 $ 1,500 

$ 

Hospital Admissions, Respiratory (65+) 4,400 $ 190 11,000 $ 470 34,000 $ 1,400 

$ 

Emergency Room Visits, Respiratory 32 $ 87 100 $ 280 370 $ 1,000 

$ 

School Loss Days 6,400 $ 72,000 18,000 $ 200,000 57,000 $ 640,000 

$ 

Worker Productivity 4,700 $ 4,200,000 10,000 $ 9,000,000 27,000 $ 23,000,000 

$ 

Acute Respiratory Symptoms 11,000 $ 180,000 29,000 $ 500,000 98,000 $ 1,700,000 1

$ 

Mortality Bell et al. 2004 190,000 $ 24 550,000 $ 71 1,900,000 $ 250 3,5

$ 

Mortality Bell et al. 2005 620,000 $ 80 1,800,000 $ 230 6,200,000 $ 810 11,0

$ 

Mortality Ito et al. 830,000 $ 110 2,400,000 $ 310 8,500,000 $ 1,100 15,0

$ 

Mortality Levy et al. 860,000 $ 110 2,500,000 $ 320 8,800,000 $ 1,100 16,0

$ 

National Total East Rest of West California

* National Total does not reflect benefits for the South Coast and San Joaquin Air Basins. Confidence intervals not available for PM estima

two significant figures. Valuation results for mortality and nonfatal myocardial infarctions are shown at a 3% discount rate. Does not incl
6-92 

Table 6.53: Regional Breakdown of Annual PM Benefit Results by Health Endpoint in 2020 

(thousands of 2006$) at 3%* 

Endpoint Group Author 079 Valuation 079 

Incidence 075 Valuation 075 Incidence 070 Valuation 070 Incidence 065 Valuation 065 Incidence

Chronic Bronchitis 31,000 $ 64 91,000 $ 190 190,000 $ 390 300,000 $ 620 

Emergency Room Visits, Respiratory 23 $ 62 66 $ 180 140 $ 380 220 $ 600 

Acute Respiratory Symptoms 1,200 $ 43,000 3,600 $ 130,000 7,500 $ 260,000 12,000 $ 420,000 

Upper+Lower Respiratory Symptoms 47 $ 1,900 140 $ 5,700 290 $ 12,000 460 $ 19,000 

Work Loss Days 910 $ 7,300 2,600 $ 21,000 5,500 $ 45,000 8,800 $ 71,000 

Acute Bronchitis 87 $ 170 250 $ 490 530 $ 1,000 840 $ 1,600 

Asthma Exacerbation 55 $ 1,000 160 $ 3,000 340 $ 6,300 530 $ 10,000 

Hospital Admissions 1,400 $ 54 4,000 $ 160 8,400 $ 330 13,000 $ 520 

Non-fatal myocardial infarction 16,000 $ 150 48,000 $ 440 100,000 $ 920 160,000 $ 1,500 

Infant Mortality Woodruff 1,300 $ 0.19 3,900 $ 0.55 8,100 $ 1.20 13,000 $ 1.80 

Mortality Pope 480,000 $ 66 1,600,000 $ 190 3,700,000 $ 400 6,200,000 $ 640 

Mortality Laden 1,100,000 $ 150 3,600,000 $ 430 8,300,000 $ 900 14,000,000 $ 1,400 

Mortality Expert E 2,800,000 $ 330 8,000,000 $ 960 16,000,000 $ 2,000 26,000,000 $ 3,200 

Mortality Expert K 270,000 $ 32 800,000 $ 93 1,700,000 $ 190 2,700,000 $ 310 

Chronic Bronchitis 740 $ 1.5 740 $ 1.5 10,000 $ 21 27,000 $ 55 

Emergency Room Visits, Respiratory 0.54 $ 1.5 0.54 $ 1.5 7.4 $ 20 20 $ 53 

Acute Respiratory Symptoms 29 $ 1,000 29 $ 1,000 400 $ 14,000 1,100 $ 37,000 

Upper+Lower Respiratory Symptoms 1.1 $ 46 1.1 $ 46 15 $ 630 40 $ 1,700 

Work Loss Days 21 $ 170 21 $ 170 290 $ 2,400 780 $ 6,300 

Acute Bronchitis 2.0 $ 4.0 2.0 $ 4.0 28 $ 55 74 $ 140 

Asthma Exacerbation 1.3 $ 24 1.3 $ 24 18 $ 330 47 $ 890 

Hospital Admissions 32 $ 1.3 32 $ 1.3 450 $ 17 1,200 $ 46 

Non-fatal myocardial infarction 390 $ 3.5 390 $ 3.5 5,300 $ 49 14,000 $ 130 

Infant Mortality Woodruff 31 $ 0.00 31 $ 0.00 430 $ 0.06 1,100 $ 0.16 

Mortality Pope 11,000 $ 1.5 13,000 $ 1.5 200,000 $ 21 550,000 $ 56 

Mortality Laden 26,000 $ 3.5 29,000 $ 3.5 440,000 $ 48 1,200,000 $ 130 

Mortality Expert E 66,000 $ 7.8 65,000 $ 7.8 880,000 $ 110 2,300,000 $ 280 

Mortality Expert K 6,300 $ 0.8 6,500 $ 0.8 90,000 $ 10 240,000 $ 27 

Chronic Bronchitis 86,000 $ 180 93,000 $ 190 110,000 $ 220 150,000 $ 300 

Emergency Room Visits, Respiratory 63 $ 170 68 $ 180 78 $ 210 110 $ 290 

Acute Respiratory Symptoms 3,400 $ 120,000 3,600 $ 130,000 4,200 $ 150,000 5,800 $ 200,000 

Upper+Lower Respiratory Symptoms 130 $ 5,300 140 $ 5,800 160 $ 6,700 220 $ 9,200 

Work Loss Days 2,500 $ 20,000 2,700 $ 22,000 3,100 $ 25,000 4,300 $ 35,000 

Acute Bronchitis 240 $ 460 260 $ 500 300 $ 580 410 $ 800 

Asthma Exacerbation 150 $ 2,800 160 $ 3,100 190 $ 3,500 260 $ 4,900 

Hospital Admissions 3,800 $ 150 4,100 $ 160 4,700 $ 180 6,500 $ 250 

Non-fatal myocardial infarction 45,000 $ 410 49,000 $ 450 56,000 $ 510 77,000 $ 710 

Infant Mortality Woodruff 3,600 $ 0.52 3,900 $ 0.56 4,500 $ 0.65 6,200 $ 0.89 

Mortality Pope 1,300,000 $ 180 1,700,000 $ 200 2,100,000 $ 220 3,000,000 $ 310 

Mortality Laden 3,000,000 $ 410 3,700,000 $ 440 4,700,000 $ 510 6,700,000 $ 700 

Mortality Expert E 7,600,000 $ 910 8,100,000 $ 980 9,200,000 $ 1,100 13,000,000 $ 1,600 

Mortality Expert K 740,000 $ 88 810,000 $ 95 950,000 $ 110 1,300,000 $ 150 

Chronic Bronchitis 120,000 $ 240 180,000 $ 380 310,000 $ 630 480,000 $ 970 

Emergency Room Visits, Respiratory 86 $ 230 130 $ 370 220 $ 610 350 $ 940 

Acute Respiratory Symptoms 4,600 $ 160,000 7,200 $ 260,000 12,000 $ 430,000 19,000 $ 660,000 

Upper+Lower Respiratory Symptoms 180 $ 7,300 280 $ 12,000 460 $ 19,000 720 $ 30,000 

Work Loss Days 3,400 $ 28,000 5,300 $ 43,000 8,900 $ 72,000 14,000 $ 110,000 

Acute Bronchitis 330 $ 640 510 $ 1,000 850 $ 1,700 1,300 $ 2,600 

Asthma Exacerbation 210 $ 3,900 330 $ 6,100 540 $ 10,000 840 $ 16,000 

Hospital Admissions 5,200 $ 200 8,100 $ 320 14,000 $ 530 21,000 $ 820 

Non-fatal myocardial infarction 62,000 $ 570 97,000 $ 890 160,000 $ 1,500 250,000 $ 2,300 

Infant Mortality Woodruff 5,000 $ 0.71 7,800 $ 1.10 13,000 $ 1.90 20,000 $ 2.90 

Mortality Pope 1,800,000 $ 250 3,300,000 $ 390 6,000,000 $ 650 9,700,000 $ 1,000 

Mortality Laden 4,100,000 $ 560 7,400,000 $ 880 13,000,000 $ 1,500 22,000,000 $ 2,300 

Mortality Expert E 11,000,000 $ 1,200 16,000,000 $ 2,000 27,000,000 $ 3,200 41,000,000 $ 5,000 

Mortality Expert K 1,000,000 $ 120 1,600,000 $ 190 2,700,000 $ 310 4,300,000 $ 490 

National Total East Rest of West California

* National Total does not reflect benefits for the South Coast and San Joaquin Air Basins. Confidence intervals not available 

for PM estimates. All estimates rounded to two significant figures. Valuation results for mortality and nonfatal myocardial 

infarctions are shown at a 3% discount rate. PM incidence and other PM morbidity incidence and valuation estimates are 

identical to Table 6.54 because these are not discounted. Does not include visibility benefits. 
6-93 

Table 6.54: Regional Breakdown of Annual PM Benefit Results by Health Endpoint in 2020 

(thousands of 2006$) at 7%* 

Endpoint Group Author 079 Valuation 079 

Incidence 075 Valuation 075 

Incidence 070 Valuation 070 

Incidence 065 Valuation 065 

Incidence

Chronic Bronchitis 31,000 $ 64 91,000 $ 190 190,000 $ 390 300,000 $ 620 

Emergency Room Visits, Respiratory 23 $ 62 66 $ 180 140 $ 380 220 $ 600 

Acute Respiratory Symptoms 1,200 $ 43,000 3,600 $ 130,000 7,500 $ 260,000 12,000 $ 420,000 

Upper+Lower Respiratory Symptoms 47 $ 1,900 140 $ 5,700 290 $ 12,000 460 $ 19,000 

Work Loss Days 910 $ 7,300 2,600 $ 21,000 5,500 $ 45,000 8,800 $ 71,000 

Acute Bronchitis 87 $ 170 250 $ 490 530 $ 1,000 840 $ 1,600 

Asthma Exacerbation 55 $ 1,000 160 $ 3,000 340 $ 6,300 530 $ 10,000 

Hospital Admissions 1,400 $ 54 4,000 $ 160 8,400 $ 330 13,000 $ 520 

Non-fatal myocardial infarction 16,000 $ 150 46,000 $ 440 97,000 $ 920 150,000 $ 1,500 

Infant Mortality Woodruff 1,100 $ 0.17 3,100 $ 0.50 6,500 $ 1.00 10,000 $ 1.60 

Mortality Pope 440,000 $ 66 1,500,000 $ 190 3,300,000 $ 400 5,600,000 $ 640 

Mortality Laden 980,000 $ 150 3,300,000 $ 430 7,500,000 $ 900 12,000,000 $ 1,400 

Mortality Expert E 2,500,000 $ 330 7,200,000 $ 960 15,000,000 $ 2,000 23,000,000 $ 3,200 

Mortality Expert K 240,000 $ 32 720,000 $ 93 1,500,000 $ 190 2,500,000 $ 310 

Chronic Bronchitis 740 $ 1.5 740 $ 1.5 10,000 $ 21 27,000 $ 55 

Emergency Room Visits, Respiratory 0.54 $ 1.5 0.54 $ 1.5 7.4 $ 20 20 $ 53 

Acute Respiratory Symptoms 29 $ 1,000 29 $ 1,000 400 $ 14,000 1,100 $ 37,000 

Upper+Lower Respiratory Symptoms 1.1 $ 46 1.1 $ 46 15 $ 630 40 $ 1,700 

Work Loss Days 21 $ 170 21 $ 170 290 $ 2,400 780 $ 6,300 

Acute Bronchitis 2.0 $ 4.0 2.0 $ 4.0 28 $ 55 74 $ 140 

Asthma Exacerbation 1.3 $ 24 1.3 $ 24 18 $ 330 47 $ 890 

Hospital Admissions 32 $ 1.3 32 $ 1.3 450 $ 17 1,200 $ 46 

Non-fatal myocardial infarction 370 $ 3.5 370 $ 3.5 5,100 $ 49 14,000 $ 130 

Infant Mortality Woodruff 25 $ 0.00 25 $ 0.00 350 $ 0.06 920 $ 0.15 

Mortality Pope 10,000 $ 1.5 12,000 $ 1.5 180,000 $ 21 490,000 $ 56 

Mortality Laden 23,000 $ 3.5 27,000 $ 3.5 400,000 $ 48 1,100,000 $ 130 

Mortality Expert E 59,000 $ 7.8 58,000 $ 7.8 790,000 $ 110 2,100,000 $ 280 

Mortality Expert K 5,700 $ 0.8 5,800 $ 0.8 81,000 $ 10 220,000 $ 27 

Chronic Bronchitis 86,000 $ 180 93,000 $ 190 110,000 $ 220 150,000 $ 300 

Emergency Room Visits, Respiratory 63 $ 170 68 $ 180 78 $ 210 110 $ 290 

Acute Respiratory Symptoms 3,400 $ 120,000 3,600 $ 130,000 4,200 $ 150,000 5,800 $ 200,000 

Upper+Lower Respiratory Symptoms 130 $ 5,300 140 $ 5,800 160 $ 6,700 220 $ 9,200 

Work Loss Days 2,500 $ 20,000 2,700 $ 22,000 3,100 $ 25,000 4,300 $ 35,000 

Acute Bronchitis 240 $ 460 260 $ 500 300 $ 580 410 $ 800 

Asthma Exacerbation 150 $ 2,800 160 $ 3,100 190 $ 3,500 260 $ 4,900 

Hospital Admissions 3,800 $ 150 4,100 $ 160 4,700 $ 180 6,500 $ 250 

Non-fatal myocardial infarction 44,000 $ 410 47,000 $ 450 54,000 $ 510 75,000 $ 710 

Infant Mortality Woodruff 2,900 $ 0.47 3,200 $ 0.51 3,700 $ 0.58 5,100 $ 0.80 

Mortality Pope 1,200,000 $ 180 1,500,000 $ 200 1,900,000 $ 220 2,700,000 $ 310 

Mortality Laden 2,700,000 $ 410 3,300,000 $ 440 4,200,000 $ 510 6,000,000 $ 700 

Mortality Expert E 6,900,000 $ 910 7,300,000 $ 980 8,300,000 $ 1,100 11,000,000 $ 1,600 

Mortality Expert K 670,000 $ 88 740,000 $ 95 860,000 $ 110 1,200,000 $ 150 

Chronic Bronchitis 120,000 $ 240 180,000 $ 380 310,000 $ 630 480,000 $ 970 

Emergency Room Visits, Respiratory 86 $ 230 130 $ 370 220 $ 610 350 $ 940 

Acute Respiratory Symptoms 4,600 $ 160,000 7,200 $ 260,000 12,000 $ 430,000 19,000 $ 660,000 

Upper+Lower Respiratory Symptoms 180 $ 7,300 280 $ 12,000 460 $ 19,000 720 $ 30,000 

Work Loss Days 3,400 $ 28,000 5,300 $ 43,000 8,900 $ 72,000 14,000 $ 110,000 

Acute Bronchitis 330 $ 640 510 $ 1,000 850 $ 1,700 1,300 $ 2,600 

Asthma Exacerbation 210 $ 3,900 330 $ 6,100 540 $ 10,000 840 $ 16,000 

Hospital Admissions 5,200 $ 200 8,100 $ 320 14,000 $ 530 21,000 $ 820 

Non-fatal myocardial infarction 60,000 $ 570 94,000 $ 890 160,000 $ 1,500 240,000 $ 2,300 

Infant Mortality Woodruff 4,000 $ 0.64 6,300 $ 1.00 11,000 $ 1.70 16,000 $ 2.60 

Mortality Pope 1,600,000 $ 250 3,000,000 $ 390 5,400,000 $ 650 8,800,000 $ 1,000 

Mortality Laden 3,700,000 $ 560 6,600,000 $ 880 12,000,000 $ 1,500 20,000,000 $ 2,300 

Mortality Expert E 9,500,000 $ 1,200 15,000,000 $ 2,000 24,000,000 $ 3,200 37,000,000 $ 5,000 

Mortality Expert K 910,000 $ 120 1,500,000 $ 190 2,500,000 $ 310 3,900,000 $ 490 

National Total East Rest of West California

* National Total does not reflect benefits for the South Coast and San Joaquin Air Basins. Confidence intervals not available 

for PM estimates. All estimates rounded to two significant figures. Valuation results for mortality and nonfatal myocardial 

infarctions are shown at a 7% discount rate. PM incidence and other PM morbidity incidence and valuation estimates are 

identical to Table 6.53 because these are not discounted. Does not include visibility benefits. 
6-94 

Table 6.55: Regional Breakdown of Annual Ozone and PM Benefit Results by Health 

Endpoint in 2020 (3% discount rate, thousands of 2006$)* 

Endpoint Group Author Year 079 

Valuation 

075 

Valuation 

070 

Valuation 

065 

Valuation 

Ozone Morbidity (non-causal) $6,600 $33,000 $130,000 $250,000 

Ozone Mortality Bell 2004 $50,000 $290,000 $1,300,000 $2,400,000 

Ozone Mortality Bell 2005 $160,000 $940,000 $4,100,000 $7,600,000 

Ozone Mortality Ito 2005 $220,000 $1,300,000 $5,600,000 $10,000,000 

Ozone Mortality Levy 2005 $230,000 $1,300,000 $5,800,000 $11,000,000 

PM Infant Mortality Woodruff $1,300 $3,900 $8,100 $13,000 

PM Morbidity $51,000 $150,000 $310,000 $500,000 

PM Mortality Pope $480,000 $1,600,000 $3,700,000 $6,200,000 

PM Mortality Laden $1,100,000 $3,600,000 $8,300,000 $14,000,000 

PM Mortality Expert E $2,800,000 $8,000,000 $16,000,000 $26,000,000 

East 

PM Mortality Expert K $270,000 $800,000 $1,700,000 $2,700,000 

Ozone Morbidity (non-causal) $140 $260 $8,200 $24,000 

Ozone Mortality Bell 2004 $1,500 $2,700 $69,000 $200,000 

Ozone Mortality Bell 2005 $5,100 $8,900 $230,000 $670,000 

Ozone Mortality Ito 2005 $6,800 $12,000 $310,000 $900,000 

Ozone Mortality Levy 2005 $7,100 $13,000 $320,000 $950,000 

PM Infant Mortality Woodruff $31 $31 $430 $1,100 

PM Morbidity $1,200 $1,200 $17,000 $44,000 

PM Mortality Pope $11,000 $13,000 $200,000 $550,000 

PM Mortality Laden $26,000 $29,000 $440,000 $1,200,000 

PM Mortality Expert E $66,000 $65,000 $880,000 $2,300,000 

Rest of West 

PM Mortality Expert K $6,300 $6,500 $90,000 $240,000 

Ozone Morbidity (non-causal) $21,000 $40,000 $90,000 $140,000 

Ozone Mortality Bell 2004 $140,000 $260,000 $580,000 $940,000 

Ozone Mortality Bell 2005 $450,000 $840,000 $1,900,000 $3,100,000 

Ozone Mortality Ito 2005 $610,000 $1,100,000 $2,600,000 $4,200,000 

Ozone Mortality Levy 2005 $630,000 $1,200,000 $2,700,000 $4,300,000 

PM Infant Mortality Woodruff $3,600 $3,900 $4,500 $6,200 

PM Morbidity $140,000 $150,000 $180,000 $240,000 

PM Mortality Pope $1,300,000 $1,700,000 $2,100,000 $3,000,000 

PM Mortality Laden $3,000,000 $3,700,000 $4,700,000 $6,700,000 

PM Mortality Expert E $7,600,000 $8,100,000 $9,200,000 $13,000,000 

California 

PM Mortality Expert K $740,000 $810,000 $950,000 $1,300,000 

Ozone Morbidity (non-causal) $28,000 $73,000 $230,000 $420,000 

Ozone Mortality Bell 2004 $190,000 $550,000 $1,900,000 $3,500,000 

Ozone Mortality Bell 2005 $620,000 $1,800,000 $6,200,000 $11,000,000 

Ozone Mortality Ito 2005 $830,000 $2,400,000 $8,500,000 $15,000,000 

Ozone Mortality Levy 2005 $860,000 $2,500,000 $8,800,000 $16,000,000 

PM Infant Mortality Woodruff $5,000 $7,800 $13,000 $20,000 

PM Morbidity $190,000 $300,000 $500,000 $780,000 

PM Mortality Pope $1,800,000 $3,300,000 $6,000,000 $9,700,000 

PM Mortality Laden $4,100,000 $7,400,000 $13,000,000 $22,000,000 

PM Mortality Expert E $11,000,000 $16,000,000 $27,000,000 $41,000,000 

National Total 

PM Mortality Expert K $1,000,000 $1,600,000 $2,700,000 $4,300,000 

* Totals do not reflect benefits for the South Coast and San Joaquin Air Basins. Confidence intervals not 

available for PM estimates. All estimates rounded to two significant figures. Valuation results for mortality and 

nonfatal myocardial infarctions are shown at a 3% discount rate. Does not include visibility benefits. 
6-95 

Table 6.56: Regional Breakdown of Annual Ozone and PM Benefit Results by Health 

Endpoint in 2020 (7% discount rate, thousands of 2006$)* 

Endpoint Group Author Year 079 

Valuation 

075 

Valuation 

070 

Valuation 

065 

Valuation 

Ozone Morbidity (non-causal) $6,600 $33,000 $130,000 $250,000 

Ozone Mortality Bell 2004 $50,000 $290,000 $1,300,000 $2,400,000 

Ozone Mortality Bell 2005 $160,000 $940,000 $4,100,000 $7,600,000 

Ozone Mortality Ito 2005 $220,000 $1,300,000 $5,600,000 $10,000,000 

Ozone Mortality Levy 2005 $230,000 $1,300,000 $5,800,000 $11,000,000 

PM Infant Mortality Woodruff $1,100 $3,100 $6,500 $10,000 

PM Morbidity $51,000 $150,000 $310,000 $490,000 

PM Mortality Pope $440,000 $1,500,000 $3,300,000 $5,600,000 

PM Mortality Laden $980,000 $3,300,000 $7,500,000 $12,000,000 

PM Mortality Expert E $2,500,000 $7,200,000 $15,000,000 $23,000,000 

East 

PM Mortality Expert K $240,000 $720,000 $1,500,000 $2,500,000 

Ozone Morbidity (non-causal) $140 $260 $8,200 $24,000 

Ozone Mortality Bell 2004 $1,500 $2,700 $69,000 $200,000 

Ozone Mortality Bell 2005 $5,100 $8,900 $230,000 $670,000 

Ozone Mortality Ito 2005 $6,800 $12,000 $310,000 $900,000 

Ozone Mortality Levy 2005 $7,100 $13,000 $320,000 $950,000 

PM Infant Mortality Woodruff $25 $25 $350 $920 

PM Morbidity $1,200 $1,200 $16,000 $44,000 

PM Mortality Pope $10,000 $12,000 $180,000 $490,000 

PM Mortality Laden $23,000 $27,000 $400,000 $1,100,000 

PM Mortality Expert E $59,000 $58,000 $790,000 $2,100,000 

Rest of West 

PM Mortality Expert K $5,700 $5,800 $81,000 $220,000 

Ozone Morbidity (noncausal) $21,000 $40,000 $90,000 $140,000 

Ozone Mortality Bell 2004 $140,000 $260,000 $580,000 $940,000 

Ozone Mortality Bell 2005 $450,000 $840,000 $1,900,000 $3,100,000 

Ozone Mortality Ito 2005 $610,000 $1,100,000 $2,600,000 $4,200,000 

Ozone Mortality Levy 2005 $630,000 $1,200,000 $2,700,000 $4,300,000 

PM Infant Mortality Woodruff $2,900 $3,200 $3,700 $5,100 

PM Morbidity $140,000 $150,000 $180,000 $240,000 

PM Mortality Pope $1,200,000 $1,500,000 $1,900,000 $2,700,000 

PM Mortality Laden $2,700,000 $3,300,000 $4,200,000 $6,000,000 

PM Mortality Expert E $6,900,000 $7,300,000 $8,300,000 $11,000,000 

California 

PM Mortality Expert K $670,000 $740,000 $860,000 $1,200,000 

Ozone Morbidity (non-causal) $28,000 $73,000 $230,000 $420,000 

Ozone Mortality Bell 2004 $190,000 $550,000 $1,900,000 $3,500,000 

Ozone Mortality Bell 2005 $620,000 $1,800,000 $6,200,000 $11,000,000 

Ozone Mortality Ito 2005 $830,000 $2,400,000 $8,500,000 $15,000,000 

Ozone Mortality Levy 2005 $860,000 $2,500,000 $8,800,000 $16,000,000 

PM Infant Mortality Woodruff $4,000 $6,300 $11,000 $16,000 

PM Morbidity $190,000 $300,000 $500,000 $780,000 

PM Mortality Pope $1,600,000 $3,000,000 $5,400,000 $8,800,000 

PM Mortality Laden $3,700,000 $6,600,000 $12,000,000 $20,000,000 

PM Mortality Expert E $9,500,000 $15,000,000 $24,000,000 $37,000,000 

National Total 

PM Mortality Expert K $910,000 $1,500,000 $2,500,000 $3,900,000 

* Totals do not reflect benefits for the South Coast and San Joaquin Air Basins. Confidence intervals not 

available for PM estimates. All estimates rounded to two significant figures. Valuation results for mortality and 

nonfatal myocardial infarctions are shown at a 7% discount rate. Does not include visibility benefits. 
6-96 

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