### 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 mo deling, in 2020, 28 counties in the U.S. with ozone monitors are anticipated to fail to meet an alternative ozone sta ndard of 0.075 ppm for the
4 th 

### highest maximum 8-hour ozone c oncentration. This number falls to 11 for an ozone standard of 0.079 ppm, and increases to 89 for a standa rd 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 a ssociated with improving mo deled air quality using known control technologies. These c ontrol strategies were sufficient to bring some, but not all, areas into attainment with the alternative standa rds. Thus, for some areas, the benefits computed during this first stage only repres ented partial attainment. In the second stage, we estimated the benefits of fully attaining th e standards in all areas by usi ng a “rollback” method. This method reduced ozone concentrations at nonattaining mon itors to a level that would just meet the standards. To estimate the bene fits for the 0.075 ppm and 0.079 standa rds, we deviated from this two-stage approach. Instead, we used an inter polation technique (pleas e see Appendix 6a for more details on this technique). Benefits for th e 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 ep idemiological studies and valuation functions derived from the economics literature to calculate the monetary value of the adverse health outcomes potentially avoided due to thes e reductions in ambient ozone levels. 2 

### Key health endpoints included premature mort ality, hospital and emergency r oom visits, school absences, and minor restricted activity days.

There is considerable uncertainty in the ma gnitude of the association between ozone and premature mortality. This analysis presents four independent estim ates of this association based upon different functions reported in the scientific literature. We al so note that this range of estimates do not fully capture the uncertainti es within each study. Recognizing that additional research is necessary to clarify the underlyi ng mechanisms causing these effects, we also consider the possibility that th e observed associations between ozone and mortality may not be causal in nature. Using the National Morbid ity, Mortality and Air Pollution Study (NMMAPS), which was used as the primary basis for the ri sk analysis presented in our Staff Paper and reviewed by Clean Air Science Advisory Co mmittee (CASAC), we estimated 250 avoided premature deaths annually in 2020 from reducing oz one 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 PM 2.5 

### co-benefits found in this chapter exclude these tw o areas of California.

2 

### Health impact functions measure the change in a health endpoint of in terest, such as hospital admissions, for a given change in am bient 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-relate d benefit of $2.2 billion/yr (2006$). Using three studies that synthesize data acro ss a large number of individual st udies, 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 w ould 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. A lternatively, if there is no causal relationship between ozone and mortality, avoided premature d eaths 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, usi ng 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. Alte rnatively, if there is no causal relationship between ozone and mortality, avoided premature d eaths 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, us ing the NMMAPS ozone mortality study resulted in 450 premature deaths avoided and total moneti zed 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 st andard are between 1,500 and 2,100, with total monetized ozone benefits between $12 and $16 bill ion/yr. Alternatively, if there is no causal relationship between ozone and mortality, avoide d 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 e xposure. EPA has requested advice from the National Academy of Sciences on how best to qu antify uncertainty in the relationship between ozone exposure and premature mortality in the c ontext of quantifying bene fits associated with alternative ozone control strate gies. We expect to receive th is advice later this spring.

The monetary benefits of visibility improvements from PM 2.5 

### reductions associated with from the 0.070 modeled attainment strategy in selected fe deral Class I Areas in 2020 is $160 million/yr.

In addition to the direct benefits from reduci ng ozone, attainment of th e standards would likely result in additional health and welfare benefits because reducing the ozone precursors NOx and VOC will also reduce PM 2.5 

### . Using both modeled and extrapolat ed 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 alternativ e, incremental to atta inment of the 0.08 ppm standard, we estimate total ozone and PM 2.5 

### -related co-benefits to be between $3.6 and $16 billion/yr; this range encompasses the expert f unctions 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 alternativ e, incremental to atta inment of the 0.08 ppm standard, we estimate total ozone and PM 2.5 

### -related co-benefits to be between $2 and $11 billion/yr; this range encompasses the expert f unctions 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 alternativ e, incremental to atta inment of the 0.08 ppm standard, we estimate total ozone and PM 2.5 

### -related co-benefits to be between $6.5 and $27 billion/yr (3% and 7% discount rates, 2006$); this range encompa sses 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 alternativ e, incremental to atta inment of the 0.08 ppm standard, we estimate total ozone and PM 2.5 

### -related co-benefits of between $11 and $42 billion/yr; this range encompasses the expert f unctions 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 a ttaining 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 simila r to those used in several recent U.S. EPA regulatory impact analyses, incl uding 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 bene fits 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 Cl ean Air Interstate Rule RIA (2005). For a more detailed discussion of the principles of be nefits 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 ro unding conventions. When calculating benefits in this chapter we followe d 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 th e benefits of fully a ttaining each alternative standard. In the first stage, we estimated the benefits associated with improving modeled air quality using known and available control technologies. These cont rol strategies were sufficient to bring some, but not all, areas into attainment with the various alterna tive standards. Thus, for some areas, the benefits computed during this firs t stage only represented pa rtial attainment (see Chapter 3 for details on these cont rol technologies and the results of the air quality modeling). In the second stage, we estimated the benefits of fu lly attaining the standard s in all areas by using a “rollback” method. This method reduced ozone concentrations at residually nonattaining monitors to a level that woul d just meet the standards (see Appendix 6a for details on this methodology). We tested the sensitivity of our re sults to different assu mptions, including the choice of health effect estimates from ep idemiological studies and economic valuation parameters for those health effects. A quant itative 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 pr ecursor emissions to attain alternative ozone NAAQS. With the exception of ozon e-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 th e 2006 PM NAAQS RIA (U.S. EPA, 2006). In addition, we used a nearly identical approach to analyze the oz one benefits as the 2007 Ozone RIA (U.S. EPA, 2007).

All estimates of ozone benefits and PM 2.5 

### co-benefits in this chapter are incremental to a baseline of national full atta inment with 0.08 ppm. 7 

### This baseline incorpor ates emission reductions projected to be achieved through an array of fede ral rules such as the Clean Air Interstate and Non-Road Diesel Rules, as well as ozone and PM 2.5 

### state implementation plans. Moreover, the
PM 2.5 

### co-benefits are incremental to an a ssumption of full attainment of the 2006 PM 2.5 

### NAAQS. See Chapter 3 for a complete discussion of the ba seline. 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 asso ciated 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 Ba sins. Attainment dates will be determined in the future through the SIP process based on criter ia 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. E nvironmental Health Perspectives 113:73–82. U.S. EPA. 2000. Guidelines for Preparing Economic Analyses. http://yosemite1.epa.gov/ee/epa/eed.nsf/webpa ges/Guidelines.html/$file/Guidelines.pdf

6 

### U.S. EPA. 2000. Guidelines for Preparing Economic Analyses. http://yosemite1.epa.gov/ee/epa/eed.nsf/webpa ges/Guidelines.html/$file/Guidelines.pdf

7 

### The PM 2.5 

### benefits presented below reflect the NOx emission reductions from the ozone control strategy. Reductions from Ocean-Going Vessels bur ning 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 Sa n 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 attain ing the 0.075 ppm standard and the alternate air quality sta ndards for these two areas in 2030 not included in the primary benefit analysis and ar e provided in Appendix 7b.

For purposes of this analysis, we assume a ttainment by 2020 for all areas except San Joaquin Valley and South Coast air basins in Californi a. The state has submitted plans to EPA for implementing the current ozone standard which pr opose that these two area s of California meet that standard by 2024. We have assumed for analyt ical purposes that the San Joaquin Valley and South Coast air basin would attain a new st andard in 2030. There are many uncertainties associated with the year 2030 analysis. Between 2020 and 2030 several fede ral air quality rules are likely to further reduce emi ssions 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 leve ls 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 devel op robust controls strate gies with associated costs and benefits. In order to provide a rough approximation of th e costs and benefits of attaining 0.075 ppm and the alternate standards in San Joaquin and South Co ast air basins, we have relied on the available data. Available data includes emission invent ories, which do not in clude 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 comp lete 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 th e analysis. Section 6.2 discusses the probabilistic framework for the be nefits analysis and how key uncertainties are addressed in the analysis. Secti on 6.3 discusses the li terature on ozone- and PM-related health effects and describes the specific set of health imp act 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) high lighted the need for EPA to conduct rigorous quantitative analysis of uncertain ty in its benefits estimates and to present these estimates to decision makers in ways that foster an appropria te 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 aggr egate 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 incide nce 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 concentra tion response functions from epidemiological studies and economic valuation functions. Mont e Carlo simulation uses random sampling from distributions of parameters to characterize the e ffects of uncertainty on out put variables, such as incidence of premature mortality. Specifically, we used Monte Carlo methods to generate confidence intervals around the estimated heal th impact and dollar benefits. The reported standard errors in the epidemiological studies de termined the distributions for individual effect estimates. Table 6.4 describes the distributions for unit values.

Second, because characterization of random stat istical error omits important sources of uncertainty (e.g., in the functional form of the m odel—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 PM 2.5 

### concentration. 11 

### Use of the expert elicitation and incorporati on of the standard errors appro aches provide insights into the likelihood of different outcomes and about the state of knowledge regarding the benefits estimates. Both approaches have different streng ths and weaknesses, which are fully described in Chapter 5 of the PM NAAQS RIA.

In benefit analyses of air po llution regulations conducted to da te, the estimated impact of reductions in premature mortality has accounted for 85% to 95% of to tal 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 altern ative study designs. In addition, we characterize the uncertainty introduced by the inability of existing empirical studies to discern wh ether the relationship

8 

### U.S. Environmental Protection Agency, 2004a . Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines. EP A420-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. Re gulatory 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/inters tateairquality/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/Chap ter%205--Benefits.pdf

11 

### Expert elicitation is a formal, highly struct ured 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 in terest, such as hospital admissions, for a given change in ambient ozone or PM concentration.

### 6-7 between ozone and pre-mature mortality is caus al 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), pr esenting several empi rical estimates of premature deaths avoided, and a set of twelve es timates 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, ba seline incidence rates, populations exposed and transferabi lity of the effect estimate to diverse locations. Furthermore, the approach presented here does not yet incl ude methods for addressing correlation between input parameters and the identification of reasonable upper and lo wer bounds for input distributions characterizing uncertainty in additional model elements. As a result, the reported confidence intervals and range of estimates gi ve an incomplete picture about the overall uncertainty in the estimates. This information s hould be interpreted with in 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 inte rest, 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 th e 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 

### e y y Δ β 

### Δ

where y 0 

### is the baseline incidence (the product of the baseline incide nce rate times the potentially affected population), β is the effect estimate, and Δ 

### x is the estimated change in the summary ozone measure. There are other functional form s, 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 e ach of the other elements: size of potentially affected populations; effect estimat es; and baseline incidence rates.

13 

### Industrial Economics, Inc. 2006. Expanded Expert Judgment Assessment of the ConcentrationResponse Relationship Between PM 2.5 

### Exposure and Mortality. Pr epared for EPA Office of Air Quality Planning and Standards, September. Available at: http://www.epa.gov/ttn/ecas/regda ta/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 categori es to match specific populations potentially affected by ozone and other air pollutants. The software constructs specific populations matching the populations in each epid emiological study by accessing the appropriate age-specific populations from the overall population database . BenMAP projects populations to 2020 using growth factors based on economic project ions (Woods and Poole Inc. 2001).

6.3.2 Effect Estimate Sources

The most significant monetized benefits of redu cing 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 suspecte d 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 relationsh ips that are based on clinical studies to the potentially affected population; (3) the lack of an estab lished 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 altern ative standards. Table 6.2 lists the health endpoints included in this analysis.

In order to select appropriate epidemiological st udies to use for our effect estimates, we applied several criteria to determine the set of studies that is likely to provide the be st 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/Chap ter%205--Benefits.pdf 

### pp. 5-29.

### 6-9 estimates from models that included both ozon e and PM over effect estimates from singlepollutant models. 15 , 16



### A number of endpoints that are not health-rela ted may also contribute significant monetized benefits. Potential welfare bene fits associated with ozone ex posure include increased outdoor worker productivity; increased yields for co mmercial and non-commercial crops; increased commercial forest productivity; reduced damage to urban ornamental plants; increased recreational demand for undamaged forest aes thetics; and reduced damage to ecosystem functions (U.S. EPA 1999, 2006). Although we estim ate the value of increased outdoor worker productivity, estimation of other welfare eff ects 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 PM 2.5

Pollutant/Effect Quantified and Monetized in Base Estimates a Unquantified Effects h —Changes in:
PM/Health b Premature mortality based on both cohort study estimates and on expert elicitation c,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 (a sthmatic 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/Health f 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 ou tdoor 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 an d altered host defense mech anisms. 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-te rm exposures to ambient pollution, but relative risk estimates

may also incorporate some effects due to shorter term e xposures (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 e xposure not captured in the cohort estima tes included in the primary analysis.

e May result in benefits or disbenefits. Appendix 6d includes a sensitivity analysis that partia lly quantifies this endpoint. Th is

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 responsiv eness to stimuli, inflammation in the lung , acute inflammation and respiratory cell damage, and increased susceptibility to resp iratory infection. The public health imp act of these biological responses may be partly represented by our quantified endpoints.

g The categorization of unquantified toxic hea lth and welfare effects is not exhaustive.

h Health endpoints in the unquantified benef its column include both a) those for whic h there is not consensus on causality and b ) those for which causality has been determ ined but empirical data are not availa ble to allow calculation of benefits.

### 6-11 Table 6.2: Ozone and PM Related Health Endpo ints 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—dailytime 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 PM 2.5 (annual avg) Pope et al. (2002) Laden et al. (2006) >29 years >25 years

Premature mortality, total

exposures PM 2.5 (annual avg) Expert Elicitation (IEc, 2006) >24 years

Prematuremortality—allcause PM 2.5 (annual avg) Woodruff et al. (1997) Infant (<1 year)

Chronic Illness

Chronic bronchitis PM 2.5 (annual avg) Abbey et al. (1995) >26 years

Nonfatal heart attacks PM 2.5 (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
PM 2.5 (24-hour avg) Pooled estimate: Moolgavkar (2003)—ICD 490–496 (COPD) Ito (2003)—ICD 490–496 (COPD) >64 years

PM 2.5 (24-hour avg) Moolgavkar (2000)—ICD 490–496 (COPD) 20–64 years

PM 2.5 (24-hour avg) Ito (2003)—ICD 480–486 (pneumonia) >64 years Respiratory

PM 2.5 (24-hour avg) Sheppard (2003)—ICD 493 (asthma) <65 years

PM 2.5 (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) >64 years Cardiovascular

PM 2.5 (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) PM 2.5 (24-hour avg) Norris et al. (1999) 0–18 years

Other Health Endpoints

Acute bronchitis PM 2.5 (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 PM 2.5 (24-hour avg) Schwartz and Neas (2000) 7–14 years

Asthma exacerbations PM 2.5 (24-hour avg) Pooled estimate: Ostro et al. (2001) (cough, wheeze and shortness of breath) Vedal et al. (1998) (cough) 6–18 years a

Work loss days PM 2.5 (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 years b

O3 (24-hour avg) Ostro and Rothschild (1989) 18–65 years Minor Restricted Activity Days (MRADs) PM 2.5 (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. S ee: 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 Counc il and the EPA SAB-HES, we have calculated reductions in school absences for all school-aged child ren 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 polluta nt most clearly associ ated with premature mortality, recent research suggests that shor t-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 ad justment for the influence of season and PM” (EPA, 2006: E-17). The epidemiologic data are al so 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 ex posure, the Ozone Criteria Document concludes, “This overall body of evidence is highly suggestiv e 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 c onclusion regarding the re lationship 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 Hu ang 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 an alysis 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-pollutant s generally do not appear to substantially confound the association between ozone and mo rtality” (p. 7-103). However, CASAC raised questions about the implications of these time-s eries results in a policy context. Specifically, CASAC emphasized that “...while the time-series stu dy design is a powerful tool to detect very small effects that could not be detected using ot her 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 criter ia 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 con centrations of these poll utants 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 mo rtality for inclusion in the quant itative risk assessment to be appropriate.”

17 

### For an exhaustive review of th e city-specific time-series studies considered in the ozone staff paper, see: U.S. Environmental Protection Ag ency, 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 oz one 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 Info rmation, we included ozone mortality in the primary health effects analysis, with the recogn ition 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 fro m 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 qu antify uncertainty in the relationship between ozone exposure and premature mortality in the c ontext of quantifying bene fits associated with alternative ozone control stra tegies later this spring.

We estimate the change in mortality in cidence and estimated credible interval 18 

### resulting from application of the effect estim ate 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 unce rtainty in the underlying epidemiological work, and does not capture other sources of uncertain ty, such as uncertainty in the estimation of changes in air pollution ex posure (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 concentrat ions are highest during the daylight hours, the 24-hour average metric is not appropriate. Mo reover, 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 metr ic, and the one used in the ozone NAAQS since 1997 is the 8-hour maximum standard. Thus, althoug h our analysis at propos al calculated impact functions based on either the 24 hour average or 1-hour maxi mum ozone levels originally reported in the epidemiogical studies, for the fi nal 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 concentrati on using standard conversion functions.

This practice is consistent both with the availa ble 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 th e 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., 20 04 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 deri ved health impact effect estimate based on the 1-hour maximum should be half that of the eff ect 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 ru le, mortality risks were estimated for 8 urban areas based on application of c ity-specific effect estimates deri ved 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 estim ates based on the pooled multi-city results reported in Bell et al (2004) a nd 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 conversio n ratios between daily average and 8-hour and 1-hour maxima , based on national data. However, these conversions were not specific to the ozone “w arm” 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 wi th the introduction of additional uncertainty due to the use of effect estimates based on a mixt ure 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 inap propriate 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 reco rds provide data for an extensive body of literature examining the relationship between ho spital 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 (B urnett et al., 2001) providing an effect estimate for respiratory hospit al admissions in children under two.

Because the number of hospital ad mission 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 th e pooling process, see Abt (2005). 19 

### To estimate total respiratory hospital admissions associated w ith 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 fo r each city. These citie s included Minneapolis, Detroit, Tacoma and New Haven. To estimate total respiratory hospital admissions for Detroit, we added the pneumonia and COPD estimates, base d on the effect estimates in the Schwartz study (1994b). Similarly, we summed the estim ated hospital admissions based on the effect estimates the Moolgavkar study reported for Mi nneapolis (Moolgavkar et al., 1997). To estimate total respiratory hospital admi ssions for Minneapolis using th e Schwartz study (1994a), we simply estimated pneumonia hospital admissions based on the effect estimate. Making this assumption that pneumonia admissions represen t 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 a pproach incorporates both the precision of the individual effect estimates and between-study variability characterizi ng differences across study locations.

6.3.2.3 Asthma-Related Emergency Room Visits Effect Estimates

We used three studies as the source of the con centration-response functions we used to estimate the effects of ozone exposure on asthma-related emergency room (E R) 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 19 96. In single-pollutant Poisson regression models, ozone was linked to asthma visits. We us e 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 associat ion between the maximum daily 8-hour average ozone level and ER visits for asthma over a 3-da y moving average (lags of 0, 1, and 2 days) in a single pollutant model. Wilson et al. (2005) exam ined 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 in corporated into the model to the months ozone levels are usually measured, the spring-summe r months (April through September). Using the generalized additive model, Wilson et al. (2 005) 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 eff ects pooling to combine the results across the individual study estimates for ER visits for as thma. The Peel et al. (2005) and Wilson et al. (2005) Manchester estimates were not signific ant at the 95 percent level, and thus, the confidence interval for the pooled incidence es timate based on these studies includes negative values. This is an artifact of the statistical pow er 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 visi ts 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 activ ities 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
PM 2.5 

### on MRAD incidence in a national sample of the adult working population (ages 18 to 65) living in metropolitan areas. We developed separa te 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 weight ed 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 re spiratory or other acute diseases caused, or aggravated by, exposure to air pollution. Seve ral studies have found a significant association between ozone levels and school absence rates. We use two studies (Gill iland et al., 2001; Chen et al., 2000) to estimate changes in school abse nces 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 th e 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. (20 01). Thus, each Gilliland et al. pe riod of absence is converted into 1.6 absence days.

Following recent advice from the National Resear ch 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 estim ating the impact of ozone exposure on school absences (Hall et al. 2003). We estimated the ch ange 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 (1 981). Crocker and Horst examined the impacts of ozone exposure on the productivity of outdoor citrus workers. The study measured productivity impacts. Worker pr oductivity is measuring the value of the loss in productivity for a worker who is at work on a pa rticular day, but due to ozone, cannot work as hard. It only applies to outdoor workers, like fr uit and vegetable pickers, or construction workers. Here, productivity impacts are measured as the ch ange in income associated with a change in ozone exposure, given as the elasticity of inco me with respect to ozone concentration. The reported elasticity translates a ten percent reducti on 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 h ousehold income. No information was available for quantifying the uncertainty associated with the central valuation estimate. Therefore, no uncertainty analysis was c onducted for this endpoint.

### 6-18 6.3.2.7 Visibility Benefits

Changes in the level of ambient PM 2.5 

### caused by the reduction in em issions associated with the alternative standards will chan ge the level of visibility throughout the United States. Increases in PM concentrations cause increases in light extin ction, a measure of how much the components of the atmosphere absorb light. This chapter contai ns an estimate of the monetized benefits of improved visibility associated with the simulate d emission control strategy to attain the 0.070 ppm ozone standard. The methodology we followed to estimate changes in vi sibility benefits is consistent with the PM 2.5 

### RIA (EPA, 2006), which is describe d 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 plan t and tree species” (U.S. EPA, 2006, page 9-1). Changes in ground-level ozone resulting from the implementa tion of alternative ozone standards may affect crop and forest yields throughout the affected area. Recent scientif ic studies have also found that at sufficient concentrations ozone negatively a ffects the quality or nutritive value of some sensitive crops (U.S. EPA, 2006, page 9-16).

Well-developed techniques exist to provide moneta ry estimates of these benefits to agricultural producers and to consumers. Thes e techniques use models of pl anting decisions, yield response functions, and the supply of and demand for ag ricultural products. The resulting welfare measures are based on predicted changes in mark et prices and production costs. Models also exist to measure benefits to silvicultural producers and consumers. There is considerable uncertainty, however, in such estimates, includi ng the fact that the extensive management of agricultural crops may mitigate the potential O3-relate d effects. For this reason, the estimates of economic crop loss developed using the update d AGSIM model were not relied on for this analysis of alternative O3 standa rds. 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 ar e 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 suffi cient 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 be nefits 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 ex posure-response functions and economic damage functions for the potential range of effects relevant to these types of vegeta tion precludes us from quantifying these direct economic benefits. The farm production value of ornamental crops was estimated at over $14 billion in 2003 (USDA, 20 04). This is therefore a potentially important welfare effects category, but information and va luation 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 advers e consequences to the health of estuarine and coastal waters. These effects incl ude toxic and/or noxious algal blooms such as brown and red tides, low (hypoxic) or zero (anoxic) concentr ations of dissolved oxyge n in bottom waters, the loss of submerged aquatic vegetation due to the li ght-filtering effect of thick algal mats, and fundamental shifts in phytopla nkton community structure (Brick er 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 h ypoxic zones have been ex isted over the last two decades (Booth and Campbell, 2007). 20



### Reductions in atmospheric deposition of NOx ar e expected to reduce the adverse impacts associated with nitrogen deposition to estuarine and coastal waters. However, direct functions relating changes in nitrogen loadings to change s 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 valu e of changes in water quality exist at present, calculation of a WTP meas ure is not possible.

Deposition to Agricultural and Forested Land. Implementation strategies for alternative standards that reduce NO X 

### 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 manur e may increase as deposited nitr ogen is reduced. Estimates of the potential value of this possible increase in th e use of purchased fertilizers are not available, but it is likely that the overall value is very sma ll 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-sat uration due to an abundance of on-farm nitrogen production, primarily from animal manure. In these areas, re ductions 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 f actors such as moisture and other nutrients, confound assessments of marginal changes in an y one stressor or nutrient in forest ecosystems. However, reductions in deposition of nitrog en 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 Ni trate Flux in the Mississippi River Basin: A Landscape Model with Conservation Applicatio ns. 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 satura ted (US EPA, 1993). On ce saturation is reached, adverse effects of additional nitrogen begin to occu r 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 sh ield to the Earth’s su rface. 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 trop ospheric fraction of UV- B shielding is from anthropogenic sources (e.g., power plants, bypr oducts of combustion). The portion of ground level ozone associated with anthropogenic source s 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. Th ese 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 depl etion (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 u nquantified UV-B radiation effects, see Table G-4 and G-7 in the Benefits and Costs of the Cl ean 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 ra diation penetration to the earth’s surface, including latitude, altitude, cloud cover, surf ace 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 ta ke 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 Alterati on of the Global Nitrogen Cycle: Causes and Consequences” Issues in Ecology No. 1 (Spring) 1997.

22 

### Knute J. Nadelhoffer et. al., “Nitrogen de position 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 de position and forest ex pansion 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 expo sures 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 de pendency of biological responses; and interindividual variability in UV-B resistance to such health outcomes. Beyond these wellrecognized adverse health effects associated w ith 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 produci ng vitamin D, and that vitamin D deficiency can cause metabolic bone disease among children and ad ults, and may also incr ease 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 incr eased UV-B exposure on humans due to reduced ground-level O3 must include consideration of bot h negative and positive effects. However, as with other impacts of UVB on hu man health, this beneficial e ffect 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 Oz one 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 atmo spheric processes. Ozone, itself, is a major greenhouse gas and climate directly influences ambient concentrations of ozone.

The concentration of tropospheric ozone has incr eased substantially since the pre-industrial era and has contributed to warming. Tropospheric oz one is (after carbon dioxide and methane) the third most important contributor to greenhouse gas warming. The National Academy of Sciences recently stated 24 

### that regulations targeti ng 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 Pape r 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), biologica l response (soils, vegetation, and biomass burning) and human response (energy generation, land use, and agricu lture). Increases in regi onal 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 decrea se global background ozone concentrations.

The Intergovernmental Panel on Climate Ch ange (IPCC) recently released a report 26 

### 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 a ffect the health status of millions of people, in part, due to higher concentrations of ground level ozone related to climate change.

The IPCC also reports 27 

### that the current generation of trop ospheric ozone models is generally successful in describing the principal features of the present-day global ozone distribution. However, there is much less confidence in th e ability to reproduce the changes in ozone associated with perturbations of emissions or climate. There are major discrepancies with observed long-term trends in oz one concentrations over the 20 th 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 construc t plausible scenarios of US air qua lity 50 years into the future. As noted in the Staff Paper, results from th ese efforts are expected to be available for consideration in the next review of the ozone NAAQS.

25 

### Denman, 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 Inte rgovernmental 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 Pr ess, Cambridge, United Kingdom and New York, NY, USA.

26 

### IPCC, Climate Change 2007: Climate Cha nge 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 betw een pollution levels and adverse health effects generally provide a direct es timate of the relationship of air quality changes to the relative risk of a health effect, rather than es timating 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 in cidence of the health effect is necessary to convert this relative change into a number of cases. A baseline in cidence rate is the estimate of the number of cases of the health effect per year in the assessme nt 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 popul ation 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 provi des 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 pr ovide 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 in formation comes from the studies themselves; in these cases, incidence in the study population is assumed to represent ty pical incidence at the national level. Regional incidence rates are av ailable for hospital admissions, and county-level data are available for premature mortality. We ha ve projected mortality ra tes such that future mortality rates are consistent wi th our projections of populatio n 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 h ealth effect that would occur with certainty (Freeman, 1993). Epidemiologi cal studies generally pr ovide estimates of the relative risks of a particul ar health effect that is avoided be cause of a reduction in air pollution. We converted those to units of avoided statis tical incidence for ease of presentation. We calculated the value of avoided statistical inci dences by dividing indivi dual WTP for a risk reduction by the related observ ed change in risk. For example, suppose a pollution-reduction regulation is able to re duce 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 th is 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 year d 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 files b incidence 0.043 0.084 0.206 0.678 1.926 4.389 11.629

Asthma ER visits 2000 NHAMCS public use data files c ; 1999 NHDS public use data files b 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 th e national surveys conducted by the National Center

for Health Statistics: HIS refers to the Nationa l 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-we ighted 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 expenditu res related to treatment , but not the value of avoided pain and suffering (Harrington and Po rtney, 1987; Berger, 1987). We provide unit values for health endpoints (along with inform ation on the distribution of the unit value) in Table 6.4. All values are in constant year 2006 doll ars, 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) w ill increase if real income increases. Many of the valuation studies used in this analysis we re 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 dis ease likely has grown as well. We did not adjust cost of illness-based values because they are base d on current costs. Similarly, we did not adjust the value of school absences, because that va lue is based on current wage rates. Table 6.4 presents the values for individua l endpoints adjusted to year 2 020 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 ri sk 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 VS L 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 NAA QS 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 wi llingness-to-pay value of avoiding pain and suffering.

The International Classificatio n of Diseases (ICD-9, 1979) code-specific COI estimates used in this analysis consist of estim ated hospital charges and the es timated opportunity cost of time spent in the hospital (based on th e average length of a hospital stay for the illness). We based all estimates of hospital charges and length of stay s 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 $109 multiplied by n.6-26Table 6.4: Unit Values for EconomicValuation of Health Endpoints (2006$)Central Estimate of ValuePer Statistical IncidenceHealth Endpoint1990 IncomeLevel2020 IncomeLevel Derivation of Distributions of EstimatesPremature Mortality(Value of a StatisticalLife)$6,600,000 $7,900,000 Point estimate is the mean of a normaldistribution with a 95% confidence interval between $1 and$10 million. Confidence interval is based on twometa-analyses of the wage-risk VSL literature: $1million represents the lower end of the interquartile range from the Mrozek and Taylor (2002) metaanalysis and $10 million represents the upper endof the interquartile range from the Viscusi andAldy (2003) meta-analysis. The mean of the distribution is consistent with the mean estimate from athird meta-analysis (Kochi et al 2006). The VSL represents the value of a small change in mortalityrisk aggregated over the affected population.Chronic Bronchitis(CB)$410,000 $500,000 The WTP to avoid a case of pollution-related CB is calculated asWTP WTP exx=− −1313**( )

β, where x isthe severity of an averageCB case, WTP13 is the WTP for a severe case of CB, andis theparameter relating WTP to severity, based on the regression results reported in Krupnick andCropper (1992). The distribution of WTP for an average severity-level case of CB was generated byMonte Carlo methods, drawing from each of threedistributions: (1) WTP to avoid a severe case ofCB is assigned a 1/9 probability of being each of the first nine deciles of the distribution of WTPresponses in Viscusi et al. (1991); (2) the severityof a pollution-related case of CB (relative to thecase described in the Viscusi study) is assumed to have a triangular distribution, with the mostlikely value at severity level 6.5 and endpoints at 1.0 and 12.0; and (3) the constant in the elasticityof WTP with respect to severity is normally distributed with mean = 0.18 and standard deviation =0.0669 (from Krupnick and Cropper [1992]). This process and the rationale for choosing it isdescribed in detail in the Costs and Benefits of the Clean Air Act, 1990 to 2010 (EPA, 1999).Nonfatal MyocardialInfarction (heartattack)3% discount rateAge 0–24Age 25–44Age 45–54Age 55–65Age 66 and over7% discount rateAge 0–24Age 25–44Age 45–54Age 55–65Age 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$77,769No distributional information available. Age-specific cost-of-illness values reflect lost earnings anddirect medical costs over a 5-year period following a nonfatal MI. Lost earnings estimates are basedon Cropper and Krupnick (1990). Direct medical costs are based on simple average of estimatesfrom Russell et al. (1998) and Wittels et al. (1990).Lost earnings:Cropper and Krupnick (1990). Present discounted value of 5 years of lost earnings:age of onset: at 3% at 7%25–44 $8,774 $7,85545–54 $12,932 $11,57855–65 $74,746 $66,920Direct 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; $21,113 at 7% discount rate)6-27Central Estimate of ValuePer Statistical IncidenceHealth Endpoint1990 IncomeLevel2020 IncomeLevel Derivation of Distributions of EstimatesHospital AdmissionsChronicObstructivePulmonary Disease(COPD)$16,606$16,606No distributional information available. The COI estimates (lost earnings plusdirect medical costs)are based on ICD-9 code-level information (e.g.,average hospital care costs, average length ofhospital stay, and weighted share of total COPDcategory illnesses) reported in Agency forHealthcare Research and Quality (2000) (www.ahrq.gov).AsthmaAdmissions$8,900$8,900No distributional information available. The COI estimates (lost earnings plusdirect medical costs)are based on ICD-9 code-level information (e.g.,average hospital care costs, average length ofhospital stay, and weighted share of total asthmacategory illnesses) reported in Agency forHealthcare Research and Quality (2000) (www.ahrq.gov).All Cardiovascular$24,668$24,668No distributional information available. The COI estimates (lost earnings plusdirect medical costs)are based on ICD-9 code-level information (e.g.,average hospital care costs, average length ofhospital stay, and weighted share of total cardiovascular category illnesses) reported in Agency forHealthcare Research and Quality (2000) (www.ahrq.gov).All respiratory(ages 65+)$24,622$24,622No distributions available. The COI point estimates (lost earnings plus direct medical costs) arebased on ICD-9 code level information (e.g., average hospital care costs, average length of hospitalstay, and weighted share of total COPD category illnesses) reported in Agency for HealthcareResearch and Quality, 2000 (www.ahrq.gov).All respiratory(ages 0–2)$10,385$10,385No distributions available. The COI point estimates (lost earnings plus direct medical costs) arebased on ICD-9 code level information (e.g., average hospital care costs, average length of hospitalstay, and weighted share of total COPD category illnesses) reported in Agency for HealthcareResearch and Quality, 2000 (www.ahrq.gov).Emergency RoomVisits for Asthma$384$384No distributional information available.Simple average of two unit COI values:(1) $311.55, from Smith et al. (1997) and(2) $260.67, from Stanford et al. (1999).Respiratory Ailments NotRequiring HospitalizationUpper RespiratorySymptoms (URS)$30 $30 Combinations of the three symptoms for which WTP estimates are available that closely matchthose listed by Pope et al. result in seven different “symptom clusters,” each describing a “type” ofURS. A dollar value was derived for each type ofURS, using mid-range estimates of WTP (IEc,1994) to avoid each symptom inthe cluster and assuming additivityof WTPs. In the absence ofinformation surrounding the frequency with which each of the seven types of URS occurs within theURS symptom complex, we assumed a uniform distribution between $9.2 and $43.1.6-28Central Estimate of ValuePer Statistical IncidenceHealth Endpoint1990 IncomeLevel2020 IncomeLevel Derivation of Distributions of EstimatesLower RespiratorySymptoms (LRS)$19$21Combinations of the four symptoms for which WTP estimates are available that closely match thoselisted by Schwartz et al. result in 11 different “symptom clusters,” each describing a “type” of LRS.A dollar value was derived for each type of LRS, using mid-range estimates of WTP (IEc, 1994) toavoid each symptom in the cluster and assuming additivity of WTPs. The dollar value for LRS isthe average of the dollar values for the 11 different types of LRS. In the absence of informationsurrounding the frequency with which each of the 11 types of LRSoccurs within the LRS symptomcomplex, we assumed a uniform distribution between $6.9 and $24.46.AsthmaExacerbations$50$54Asthma exacerbations are valued at $45 per incidence, based on the mean of average WTPestimates for the four severity definitions of a “bad asthma day,” described in Rowe and Chestnut(1986). This study surveyed asthmatics to estimate WTP for avoidance of a “bad asthma day,” asdefined by the subjects. For purposes of valuation, an asthma exacerbation is assumed to beequivalent to a day in which asthma is moderate or worse as reported in the Rowe and Chestnut(1986) study. The value is assumed have a uniform distribution between $15.6 and $70.8.Acute Bronchitis$429$453Assumes a 6-day episode, with the distribution ofthe daily value specifiedas uniform with the lowand high values based on those recommended for related respiratory symptoms in Neumann et al.(1994). The low daily estimate of $10 is the sum of the mid-range values recommended by IEc(1994) for two symptoms believed to be associated with acute bronchitis: coughing and chesttightness. The high daily estimate was taken to betwice the value of a minor respiratory restrictedactivity day, or $110.Work Loss Days(WLDs)Variable(U.S. median= $130)No distribution available. Point estimate is based on county-specific median annual wages dividedby 50 (assuming 2 weeks of vacation) and then by 5—to get median daily wage. U.S. Year 2000Census, compiled by Geolytics, Inc.Minor RestrictedActivity Days(MRADs)$61 $64 Median WTP estimate to avoid one MRAD from Tolley et al. (1986). Distribution is assumed to betriangular with a minimum of $22 and a maximum of $83, with a most likely value of $52. Range isbased on assumption that value should exceed WTP for a single mild symptom (the highest estimatefor a single symptom—for eye irritation—is $16.00)and be less than that for a WLD. The triangulardistribution acknowledges that the actual value is likely to be closer to the point estimate than eitherextreme.School AbsenceDays$89 $89 No distribution available

### 6-29 6.4.3 Asthma-Related Emerge ncy 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 emergenc y room visits in 1987, at a total cost of $186.5 million (1987$). The average cost per visi t that year was $155; in 2000$, that cost was $311.55 (using the CPI-U for medical care to ad just to 2000$). The s econd 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 av erage 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 WT P to avoid a minor restricted activity day. However, one of EPA’s contractor s, IEc (1993) has derived an es timate of willingness to pay to avoid a minor respiratory restricted activity day, using esti mates from Tolley et al. (1986) of WTP for avoiding a combination of coughing, thro at 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) statistic ally linked ozone and mi nor 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 th e 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 sc hool-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 scho ol-age children by a measure of lost wages.

We used this method in the absence of a pr eferable 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 e ffectively 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 assume s 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. Fr om 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 $55 1. Dividing by five gives an estimated median daily wage of $103. To estimate the expected lo st wages on a day when a mother has to stay home with a school-age child, we first estimate d 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 be nefits. 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 thro ugh 6.37 summarize the ozone-related economic benefits for each of th e alternative standards. 28 

### Note that incidence and valuation estimates for each standard alternative are presented in separa te tables In addition to the mean incidence estimates, we have included 5 th 

### and 95 th 

### percentile estimates when available, based on the Monte Carlo simulations described above. In the tabl es for the 0.065 ppm and 0.070 ppm alternative standards, the change in ozone-related inciden ce from attaining the alternative standards is presented for both the partial attain ment scenario and the full attainme nt scenario (i.e., sum of the change in incidence associated w ith 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 4 th 

### highest daily maximum 8-hour average just met the level required to attain the alternative standard. This approach will likely u nderstate 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 m onitors down-wind (i.e., the controls would lead to concentrations below the standard in down-wi nd locations); estimating benefits that occur at these downwind monitors as a result of air quali ty improvements below the standard would be appropriate because ozone is a non-threshold poll utant. 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 valua tion results for attainment of the 0.075 ppm and 0.079 ppm alternatives are derived through an inte rpolation technique desc ribed in Appendix 6a. As such, these estimates are presented as full attainment only.

We model all ozone-related premature mortality a nd 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 benef its are not discounted due to the fact that there is no lag between changes in exposure and pr emature mortality, as is calculated for PM 2.5 

### benefits.

### 6-31 Figure 6.1: Valuation of Ozone Morbidity an d 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 pla nning 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 PM 2.5 

### 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 PM 2.5 

### 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 PM 2.5 

### related co-benefits of full attainment of each ozone standard alternative, we applied a scali ng technique described be low. To estimate total valuation estimates, we applied benefit per-ton metr ics; this procedure is detailed further below. Valuation estimates of the PM 2.5 

### -related full attainment benefits are presented at a 3% discount rate and at a 7% discount rate. All PM 2.5 

### 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 locati ons 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 be nefits for the San Joaquin and South Coast Air Basins.

### 6-33 Estimating PM 2.5 

### Co-Benefits Resulting from Full Attainment of the Selected Standard and Each Standard Alternative

The modeled PM 2.5 

### air quality scenario reflects the PM 2.5 

### changes associated with partially attaining 0.070 ppm incremental to a partial attain ment of 0.08 ppm; due to analytical limitations it was not possible to model a full-attainment PM 2.5 

### scenario for the selected standard or each standard alternative. Thus, using this pr ojected air quality change to estimate PM 2.5 

### co-benefits would under or overstate the benefits of attaining each standard alternative; th is is due in part to the fact that the model run projects the air qualit y changes from NOx reductions needed to attain a baseline of 0.08 ppm. Of greater analyt ical value would be an estimate of the PM 2.5 

### co-benefits associated with fully attaining 0.070 ppm in cremental to full attainment of the 0.08 ppm standard.

To generate such an estimate, we calculated a new PM 2.5 

### baseline that established the PM 2.5 

### air quality associated with full attainment of 0.08 ppm. To create such a baseline, EPA utilized benefit PM 2.5 

### per-ton estimates. These PM 2.5 

### benefit per-ton estimates provide the total monetized human health benefits (the sum of premature mortality and premature morbidity) of reducing one ton of PM 2.5 

### from a specified source. EPA has used a similar technique in previous Regulatory Impact Analyses. 29 

### These estimates are based on the su m of the valuation of the Pope (2002) estimates of mortality (3% discount ra te, 2006$) and valuation of the morbidity incidence. Readers inte rested in reviewing the complete methodology for creating the benefit per-ton estimates used in this analysis can consult the Techni cal Support Document accompanying this RIA.

Estimating the PM 2.5 

### benefits that represented the full at tainment 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 nece ssary 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 atta ining 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 benef it 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 stan dard, so that all subs equent 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/regdat a/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 PM 2.5 

### benefits of fully attaining 0.070 ppm . Multiplying the estimate of the extrapolated NOx tons necessa ry to attain 0.070 ppm fully (Table 5.3) produces an estimate of the incremental be nefits of fully attaining 0. 070 ppm incremental to partial attainment of 0.070 ppm. By adding this in cremental benefit estimate to the benefits generated in step 3, we derived a tota l benefit estimate of attaining 0.070 ppm incremental to 0.08 ppm.

5. Repeat step 4 to estimate the bene fits of 0.075 ppm, 0.079 ppm and 0.065 ppm . Step 4 may be repeated by substituting the NOx tons n ecessary to attain the selected alternative of 0.075 ppm and the remaining alternativ es of 0.079 ppm and 0.065 ppm to produce an estimate of total PM 2.5 

### co-benefits.

The process for estimating the PM 2.5 

### co-benefits of fully atta ining 0.065 ppm, 0.075 ppm, and 0.079 ppm is identical to the st eps above, with the following exception; in step four we substituted the number of extrapolated tons neces sary to attain 0.065 ppm, 0.075 ppm, and 0.079 ppm respectively. Table 7-5 below provides the in puts to the calculati on 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 cate gories (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 dist ributed between these three source types.

The PM 2.5 

### 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 attainme nt 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 PM 2.5 

### -related incidence associated with the attainment of each ozone alte rnative, we calculated a separate scaling factor as follows: (1) we calculated the ratio of the full attainment PM 2.5 

### valuation estimate (calculated using the benefit per ton metrics described below) to the partial attainment to the partial attainment PM 2.5 

### valuation estimate; (2) multiply this scaling ratio against each of the PM 2.5 

### partial attainment mortality and morbidity endpoi nts to generate a scaled estimate of mortality and morbidity. While there are clearly substantial un certainties inherent in this technique, it does produce useful screening-level estimates of PM 2.5 

### -related incidence.

The total PM 2.5 

### benefits of attaining 0.065 ppm, 0.07 5 ppm and 0.079 ppm are $11 billion, $3.6 billion and $2 billion respectively. The full attainment PM 2.5 

### benefits do not include confidence intervals. Because this full attainment estimate was derived by summing the modeled PM 2.5

### 6-35 benefits and the benefits deri ved using the benefit per-ton me trics—and these benefit per ton metrics do not include confidence intervals—the resulting sum of total PM 2.5 

### benefits do not include confidence intervals.

Table 6.5: Estimated PM 2.5 

### Co-Benefits Associated with Full Attainment of 0.070 ppm Incremental to 0.08 ppm a

Calculation Extrapolated NOx
Tons Benefit per Ton Estimate Valuation of PM 2.5 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. PM 2.5 

### benefit estimates do not include confiden ce intervals because they are derived using benefit per-ton estimates.

b 

### All estimates derived using the Pope et al. (2002) mo rtality estimate at a 3% and 7% discount rate, in

2006$. This table reflects full attainment in all lo cations 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 incidenc e provided in Tables 6.6, 6.10, 6.14, and 6.18 represent the number of premature deaths pote ntially avoided due to reductions in ozone exposure in 2020 using warm season functi ons 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 (B ell et al., 2005; Ito et al., 2005; Levy et al., 2005). These same tables also include the possib ility that there is not a causal association between ozone and mortality, i.e., that the esti mate for premature mortality avoided could be zero. Model uncertainty, including whether or not th e relationship is assumed to be causal, is a key source of uncertainty. Although multiple estimat es 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 mo rtality is expressed as the arithmetic mean, with the assumption of a normal distribution, and re presents 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 mode l estimate for each study is characterized by the 95% credible interval 30 

### around the mean estimate (i.e., 2.5th and 97.5th percent in terval). Of the four available studies, the NMMAPS study by Bell et al. (2004) is considered to be the most representative for evaluating potential mortality-rel ated benefits associated with the alternative standards due to its extensive coverage (exami nation 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 stri ngent adjustment for meteorological factors (Ito et al., 2005; Ostro et al., 2006), publication bias in the meta-analy ses (Bell et al., 2005; Ito et al., 2005) or other factors. Clearly, the ozone-mor tality reduction estimat es 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 car diopulmonary-related mortality. However, various sources of uncertainty remain, including the po ssibility 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 crit eria 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, CASAC 31 

### 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 se rving 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 premat ure mortality as part of the Staff Paper. EPA has asked the National Academy of Sciences 32 

### for their advice on how best to quantify the uncertainty about the relationship between ambi ent ozone exposure and premature mortality within the context of quantifying projected benefits of alternative control st rategies. 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 re ducing 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 studie s, 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 Ea rth and Life Studies, Board on Environmental Studies and Toxicology. Available at http://www8.nationalacademies.o rg/cp/projectview.aspx?key=48768

### 6-37 standard of 0.079 ppm, using the NMMAPS oz one 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 be tween $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 b illion/yr. Using the three synthesis studies, we estimate premature deaths avoided for the less st ringent standard to be between 810 and 1,100 avoided premature deaths annually in 2020, leadin g to total monetized be nefits 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 moneti zed benefits of $3.9 billion/yr. Using the three synthesis studies, es timated 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 premat ure 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 PM 2.5 

### co-benefit estimate for each standard alternative. The presentation of ozone benefits and PM 2.5 

### co-benefits for each standard alternative is broken into two ta bles. The first table presents the national ozone benefits and PM 2.5 

### co-benefits. Tables 6.42 through 6.49 summarize the combined ozone and
PM 2.5 

### co-benefits.

### 6-38 Table 7-6: Illustrative Stra tegy to Attain 0.065 ppm: Estima ted Annual Reductions in the Incidence of Premature Mortality Associat ed with Ozone Exposure in 2020 (Incremental to Current Ozone Standard, Arithmetic Mean, 95% Confidence Intervals in Parentheses) B, C, D, E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Stra tegy to Attain 0.065 ppm: Estima ted Annual Reductions in the Incidence of Morbidity Associated with Oz one Exposure (Incrementa l 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)
550 1900 Emergency Department Visits, Asthma-Related C (-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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 5 th percentile incidence estimates for this health en dpoint 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 Prematu re Mortality associated with PM co-benefit C

Mortality Endpoint National 2020 Benefits Mortality Impact Functions Deri ved from Epidemiology Literature ACS Study A 1,000 Harvard Six-City Study B 2,300 Woodruff et al 1997 (infant mortality) 2.9 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 A ttainment Scenario: Estimated Annual

Reductions in the Incidence of Morbid ity Associated with PM Co-benefit A, 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 a ll locations of the U.S. except two areas of California. These two areas, which have high levels of ozone, ar e 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 Atta in 0.070 ppm: Estimated Annual Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure in 2020 (Incremental to Current Ozone Standard, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses) B, C, D, E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Atta in 0.070 ppm: Estimated Annual Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incre mental 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)
550 1000 Emergency Department Visits, Asthma-Related C (-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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 5 th percentile incidence estimates for this health en dpoint 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 A ttainment Scenario: Estimated Annual Reductions in the Incidence of PM Prematu re Mortality associated with PM co-benefit C

Mortality Endpoint National 2020 Benefits Mortality Impact Functions Deri ved from Epidemiology Literature ACS Study A 650 Harvard Six-City Study B 1,500 Woodruff et al 1997 (infant mortality) 1.9 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 A ttainment Scenario: Estimated Annual

Reductions in the Incidence of Morbid ity Associated with PM Co-benefit A, 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 a ll locations of the U.S. except two areas of California. These two areas, which have high levels of ozone, ar e 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, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses) B, C, D, E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Atta in 0.075 ppm: Estimated Annual Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incre mental 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)
280 Emergency Department Visits, Asthma-Related C (-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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 5 th percentile incidence estimates for this health en dpoint 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 A ttainment Scenario: Estimated Annual Reductions in the Incidence of PM Prematu re Mortality associated with PM co-benefit C

Mortality Endpoint National 2020 Benefits Mortality Impact Functions Deri ved from Epidemiology Literature ACS Study A 390 Harvard Six-City Study B 880 Woodruff et al 1997 (infant mortality) 1.1 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 A ttainment Scenario: Estimated Annual

Reductions in the Incidence of Morbid ity Associated with PM Co-benefit A, 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 signifi cant figures. All estimates incrementa l 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 Atta in 0.079 ppm: Estimated Annual Reductions in the Incidence of Premature Mortality Associated with Ozone Exposure in 2020 (Incremental to Current Ozone Standard, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses) B, C, D, E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Atta in 0.079 ppm: Estimated Annual Reductions in the Incidence of Morbidity Associated with Ozone Exposure (Incre mental 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)
87 Emergency Department Visits, Asthma-Related C (-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 m eet 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 5 th percentile incidence estimates for this health en dpoint 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 A ttainment Scenario: Estimated Annual Reductions in the Incidence of PM Prematu re Mortality associated with PM co-benefit C

Mortality Endpoint National 2020 Benefits Mortality Impact Functions Deri ved from Epidemiology Literature ACS Study A 250 Harvard Six-City Study B 560 Woodruff et al 1997 (infant mortality) 0.71 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 In cidence of Morbidity Associated with PM Co-benefit A, 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 figu res. All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include confid ence 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 Standa rd, Arithmetic Mean, 95% Confidence Intervals in Parentheses, Millions of 2006$) B,C,D,E

Model or Assumption A Reference National Modeled Partial Attainment National Rolled Back Full Attainment $960 $3,500 NMMAPS Bell et al.
2004 ($140--$2,200) ($510--$7,800) $3,100 $11,000 Bell et al.

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 causa lity 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 numb er 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 planni ng 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 Inter vals 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) $9.9 $74 Hospital Admissions (ages 65- 99) C (-$3.3--$24) ($8.40--$140) $0.20 $0.69 Emergency Department Visits, Asthma-Related C ($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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 5 th percentile incidence estimates for this health en dpoint 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 A ttainment 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 Deri ved from Epidemiology Literature ACS Study A $9,700 $8,800 Harvard Six-City Study B $22,000 $20,000 Woodruff et al 1997 (infant mortality) $20 $16 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 A ttainment 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 m eet 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 Mo rtality Associated with Ozone Exposure (Incremental to Current Ozone Standard, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses, Millions of 2006$) B,C,D,E

Model or Assumption A Reference National Modeled Partial Attainment National Rolled Back Full Attainment $960 $1,900 NMMAPS Bell et al.
2004 ($140--$2,200) ($280--$4,300) $3,100 $6,200 Bell et al.

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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Inter vals 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) $0.20 $0.37 Emergency Department Visits, 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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 A ttainment 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 Deri ved from Epidemiology Literature ACS Study A $6,000 $5,400 Harvard Six-City Study B $13,000 $12,000 Woodruff et al 1997 (infant mortality) $13 $11 Mortality Impact Functions Deri ved 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 previous ly 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 signifi cant figures. All estimates incrementa l 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 A ttainment 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 signifi cant figures. All estimates incrementa l 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 m eet 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 Mo rtality Associated with Ozone Exposure (Incremental to Current Ozone Standard, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses, Millions of 2006$) B,C,D,E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Inter vals 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) $0.10 Emergency Department Visits, 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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 A ttainment 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 Deri ved from Epidemiology Literature ACS Study A $3,300 $3,000 Harvard Six-City Study B $7,400 $6,600 Woodruff et al 1997 (infant mortality) $8 $6 Mortality Impact Functions Deri ved 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 previous ly 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. A ll 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 ar eas 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 A ttainment 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 Mo rtality Associated with Ozone Exposure (Incremental to Current Ozone Standard, Ar ithmetic Mean, 95% Confidence Intervals in Parentheses, Millions of 2006$) B,C,D,E

Model or Assumption A 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 be tween assumption of causality vs. no causality (see text in section 6.3.2.1).

B With the exception of the assumption of no causal relatio nship, the arithmetic mean and 95% credible interval around the mean estimates of the an nual 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 m eet 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 Inter vals 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) $0.03 Emergency Department Visits, 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 th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 A ttainment 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 Deri ved from Epidemiology Literature ACS Study A $1,800 $1,600 Harvard Six-City Study B $4,100 $3,700 Woodruff et al 1997 (infant mortality) $5.0 $4.0 Mortality Impact Functions Deri ved 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 previous ly 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 tabl e do not reflect benefits for the San Joaquin and South Coast Air Basins.

### 6-69 Table 7-37: Illustrative 0.079 ppm Full A ttainment 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 signifi cant figures. All estimates incrementa l 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 m eet 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 PM 2.5 

### 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 Ito (2005) $16,000 Meta-Analysis Levy (2005) $16,000 No Causality $420

PM 2.5 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 Study C $11,000 $9,600 Harvard Six-City Study D $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 be tween 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 PM 2.5 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 previous ly 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 attainme nt 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 PM 2.5 

### 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 Ito (2005) $8,800 Meta-Analysis Levy (2005) $9,000 No Causality $230

PM 2.5 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 Study C $6,500 $5,900 Harvard Six-City Study D $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 be tween 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 PM 2.5 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 previous ly 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 attainme nt 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 PM 2.5 

### 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 Ito (2005) $2,500 Meta-Analysis Levy (2005) $2,600 No Causality $73

PM 2.5 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 Study C $3,600 $3,300 Harvard Six-City Study D $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 be tween 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 PM 2.5 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 previous ly 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 attainme nt 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 PM 2.5 

### 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 Ito (2005) $860 Meta-Analysis Levy (2005) $890 No Causality $28

PM 2.5 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 Study C $2,000 $1,800 Harvard Six-City Study D $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 be tween 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 PM 2.5 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 previous ly 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 attainme nt 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 3% Discount Rate) for the 0.065 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $14,000 $22,000 $26,000 $27,000 $11,000

Harvard Six-City Study C $26,000 $34,000 $38,000 $39,000 $23,000 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 7% Discount Rate) for the 0.065 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $13,000 $21,000 $25,000 $26,000 $10,000

Harvard Six-City Study C $24,000 $32,000 $36,000 $37,000 $21,000 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 3% Discount Rate) for the 0.070 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $8,700 $13,000 $15,000 $16,000 $6,700

Harvard Six-City Study C $16,000 $20,000 $23,000 $23,000 $14,000 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 7% Discount Rate) for the 0.070 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $8,100 $12,000 $15,000 $15,000 $6,100

Harvard Six-City Study C $15,000 $19,000 $21,000 $22,000 $13,000 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 3% Discount Rate) for the 0.075 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $4,200 $5,500 $6,100 $6,200 $3,700

Harvard Six-City Study C $8,300 $9,500 $10,000 $10,000 $7,800 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 7% Discount Rate) for the 0.075 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $3,900 $5,100 $5,800 $5,900 $3,400

Harvard Six-City Study C $7,600 $8,800 $9,500 $9,500 $7,000 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 3% Discount Rate) for the 0.079 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $2,200 $2,700 $2,900 $2,900 $2,100

Harvard Six-City Study C $4,500 $4,900 $5,200 $5,200 $4,300 Mortality Impact Functions Deri ved 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 betw een 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of the U.S. except two areas of Calif ornia. 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 Estima te of Annual Ozone and PM 2.5 

### Benefits (Millions of $2006, 7% Discount Rate) for the 0.079 ppm Alternative Standard

Alternative Standard and Model or Assumption A

Bell (2004) Bell (2005) Ito (2005) Levy (2005) No Causality

Mortality Impact Functions Deri ved from Epidemiology Literature

ACS Study B $2,100 $2,500 $2,700 $2,700 $1,900

Harvard Six-City Study C $4,100 $4,500 $4,800 $4,800 $3,900 Mortality Impact Functions Deri ved 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 betw een 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 previous ly 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 PM 2.5 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 combin ation of modeling data and benefit per ton estimates. This table reflects full attainment in all locations of th e U.S. except two areas of California. These two areas, which have high levels of ozone, are not planning to m eet 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 PM 2.5 

### Benefits by Standard Alt ernative (3% and 7% Discount Rates)



### Figure 7.3 graphically shows the breakdown be tween 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 PM 2.5 

### 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 alte rnative 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. Thes e graphs display all po ssible combinations of benefits, utilizing the five different ozone functio ns 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 combin ation of ozone and PM functions. Thus it is not possible to infer the likelihood of any single benefit estimate.

Figure 6.5:*

079 0 7 5 070 065 0 10000 20000 30000 40000 50000 60000Millions of2006$ 

### Ozone and PM Total Benefits including all combinations of mortality
estimates (3% Discount Rate)

N

o C

au

s a l i t y &

E

xp

e r t K

B el

l 2 0 0 4

&

P

o p e

B el

l 2 0 0 5

&

L ad

en

L ev

y &

E

xp

er t E



### * These figures reflect full attainment in all loca tions 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 ta ble do not reflect benef its 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*:

0 7 9 075 070 0 6 5 0 10000 20000 30000 40000 50000 60000Millions of 2006$ 

### Ozone and PM Total Benefits including all combinations of mortality
estimates (7% Discount Rate)

N

o C

au

s a l i t y &

E

x p e r t K

B e l l 2 0 0 4

&

P

o p e

B e l l 2 0 0 5

&

L a d e n

L e v y &

E

x p er t E



### * These figures reflect full attainment in all loca tions 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 re flect 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 distribu tion of visibility benefits in Class I areas in 2020. Note that these estimates represent the mone tized 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. Fo r 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 PM 2.5 

### 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 emission s from a variety of sources in and around projected nonattaining counties in 2020. While 2020 is the expected date that states woul d 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 PM 2.5 

### 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 impo rtant role that implementation of the standards plays in reducing the health risks as sociated with exceeding the standard.

There are several important factor s to consider when evaluating the relative benefits of the attainment strategies for each of the alternative oz one standards:

1. California (outside of San Joaquin Valley an d 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 in clude 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 extrapolat ion. 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 surround ing monitors that did not violate the

### 6-87 standards. The magnitude of this underest imate 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 so me uncertainty to the analysis. The great majority of benefits estimated for the 0.065 ppm standard alternative were derived through extrapolation. As noted pr eviously in this chapter, these benefits are likely to be more uncertain than the mo deled benefits. The 0.075 ppm and 0.079 ppm benefits were derived by in terpolating 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 geogra phic 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 variab ility, which is the precision with which a given study estimates the relationshi p between air quality changes and health effects; across study variation, which refers to the fact that differe nt published studies of the same pollutant/health effect relationship typically do not report identical findings and in some instances the differences are subs tantial; the applicati on of C-R functions nationwide, which does not account for any rela tionship between region and health effect, to the extent that such a relationship exis ts; extrapolation of im pact 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, includ ing 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 exposu re 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 th e 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 PM 2.5 

### co-benefits that were derived through benefit per-ton estimates . These benefit per-ton estimates re present regional averages. As such, they do not reflect any local va riability in the incremental PM 2.5 

### benefits per ton of NOx abated. As discussed in the PM 2.5 

### NAAQS RIA (Table 5.5), there are a variety of uncertainties associated with these PM benefits.

6. PM 2.5 

### 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 PM 2.5 

### and ozone mortality functions used. When calculating
PM 2.5 

### 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 PM 2.5 

### 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 p opulation, health baselines, incomes, technology, and other factors. In addition, data limitations prev ent an overall quantitative estimate of the uncertainty associated with estimates of to tal 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 di rect effects of ozone on vegetation, the deposition of nitrogen to estuarine and coas tal 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 a nd models and select th ose 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 imp act functions. The developmen t of both better models of current health outcomes and new models for additional health effects such as asthma, high blood pressure, and adverse birth outc omes (such as low birth weight) will be essential to future improvements in the accur acy and reliability of benefits analyses (Guo et al., 1999; Ibald-Mulli et al., 2001). Enhanced collaboration between air quality modelers, epidemiologists, toxicologists, an d economists should result in a more tightly integrated analytical framework for measuring health benefits of air pollution policies. Readers interested in a more extensive discu ssion of the sources of uncertainty in human health benefits analyses shoul d consult the PM NAAQS RIA.

6.5.6 Summary of Total Benefits

Table 6.51 presents the total number of estimated ozone and PM 2.5 

### -related premature mortalities and morbidities avoided nationwide in 2020. Ra nges within the mortality section reflect variability in the studies upon which the estimat es associated with premature mortality were derived. The lower end of the range reflects th e Expert K derived mortality functions, and the upper end of the range reflects the Expert E deri ved mortality functions. Figure 6.7 graphically presents the total number of estimated ozone and PM 2.5 

### -related premature mort alities avoided in 2020 by standard. Tables 6.52 through 6.56 s how the overall ozone, PM, and combined results with regional breakdowns.6-89Table 6.51: Summary of Total Number of Annual Ozone and PM2.5-Related Premature Mortalities and Premature Morbidity Avoided in2020ACombined Estimate of MortalityCombined Range of Ozone Benefits and PM2.5Co-benefits by Standard AlternativeDModel or Assumption0.079 ppm 0.075 ppm 0.070 ppm 0.65 ppmNMAPS Bell (2004) 140 to 1,300 260 to 2,000 560 to 3,500 940 to 5,500Bell (2005) 200 to 1,300 420 to 2,200 1,100 to 4,100 2,000 to 6,500Meta-analysis Ito 230 to 1,400 500 to 2,300 1,400 to 4,300 2,500 to 7,000Levy 230 to 1,400 510 to 2,300 1,400 to 4,400 2,500 to 7,100No Causality 120 to 1,200 190 to 2,000 310 to 3,200 490 to 5,000Combined Estimate of MorbidityCombined Ozone Benefits and PM2.5Co-benefits by Standard AlternativeAcute Myocardial InfarctionB570 890 1,500 2,300Upper Respiratory SymptomsB3,100 4,900 8,100 13,000Lower Respiratory SymptomsB4,200 6,700 11,000 17,000Chronic BronchitisB240 380 630 970Acute BronchitisB640 1,000 1,700 2,600Asthma ExacerbationB3,900 6,100 10,000 16,000Work Loss DaysB28,000 43,000 72,000 110,000School Loss DaysC72,000 200,000 640,000 1,100,000Hospital and ER Visits 890 1,900 5,100 9,400Minor Restricted Activity Days 340,000 750,000 2,100,000 3,500,000ADoes not reflect estimates for the San Joaquin and South Coast Air BasinsBPM-related benefits onlyCOzone-related benefits onlyDIncludes ozone benefits, and PM2.5co-benefits. Range was developed by adding the estimatefrom the ozone premature mortality function to both thelower and upper ends of the range of the PM2.5premature mortality functions characterized in the expert elicitation.6-90Figure 6.7: Total Annual Ozone and PM2.5-Related Premature Mortalities Avoided in 2020 by Standard Alternative6-91Table 6.52: Regional Breakdown of Annual Ozone BenefitResults by Health Endpoint in 2020 (thousands of 2006$)*Endpoint Group Author Year079Valuation079Incidence075 Valuation075Incidence070 Valuation070Incidence065 Valuation065IncidenceHospital Admissions, Respiratory (0-1) 470$ 472,200$ 2208,800$ 88015,000$ 1,500Hospital Admissions, Respiratory (65+) 1,300$ 545,200$ 22020,000$ 87050,000$ 2,100Emergency Room Visits, Respiratory 13$ 3568$ 190290$ 770530$ 1,400School Loss Days 1,700$ 19,0008,500$ 95,00035,000$ 390,00061,000$ 690,000Worker Productivity 430$ 370,0002,100$ 1,800,0008,700$ 7,500,00016,000$ 14,000,000Acute Respiratory Symptoms 2,800$ 47,00015,000$ 250,00061,000$ 1,000,000110,000$ 1,800,000Mortality Bell et al. 2004 50,000$ 7290,000$ 381,300,000$ 1702,400,000$ 300Mortality Bell et al. 2005 160,000$ 21940,000$ 1204,100,000$ 5307,600,000$ 980Mortality Ito et al. 220,000$ 291,300,000$ 1705,600,000$ 73010,000,000$ 1,300Mortality Levy et al. 230,000$ 301,300,000$ 1705,800,000$ 75011,000,000$ 1,400Hospital Admissions, Respiratory (0-1) 10$ 1.018$ 1.8820$ 832,000$ 200Emergency Room Visits, Respiratory 0.14$ 0.390.27$ 0.749.4$ 2627$ 74School Loss Days 33$ 37060$ 6702,600$ 29,0006,500$ 72,000Worker Productivity 6.3$ 5,50011$ 9,900360$ 310,0001,900$ 1,600,000Acute Respiratory Symptoms 61$ 1,000110$ 1,8004,500$ 76,00011,000$ 180,000Hospital Admissions, Respiratory (65+) 30$ 1.358$ 2.5(39)$ (1.6)3,200$ 140Mortality Bell et al. 2004 1,500$ 0.202,700$ 0.3569,000$ 9.0200,000$ 26Mortality Bell et al. 2005 5,100$ 0.658,900$ 1.2230,000$ 30670,000$ 87Mortality Ito et al. 6,800$ 0.8812,000$ 1.6310,000$ 40900,000$ 120Mortality Levy et al. 7,100$ 0.9213,000$ 1.6320,000$ 42950,000$ 120Hospital Admissions, Respiratory (0-1) 1,400$ 1402,600$ 2605,800$ 5809,100$ 910Emergency Room Visits, Respiratory 19$ 5136$ 9779$ 220130$ 340School Loss Days 4,700$ 53,0009,000$ 100,00020,000$ 220,00031,000$ 350,000Worker Productivity 4,300$ 3,800,0008,000$ 7,100,00018,000$ 16,000,00031,000$ 26,000,000Acute Respiratory Symptoms 7,800$ 130,00015,000$ 250,00033,000$ 550,00052,000$ 880,000Hospital Admissions, Respiratory (65+) 3,100$ 1305,800$ 24013,000$ 56022,000$ 910Mortality Bell et al. 2004 140,000$ 18260,000$ 33580,000$ 75940,000$ 120Mortality Bell et al. 2005 450,000$ 58840,000$ 1101,900,000$ 2503,100,000$ 400Mortality Ito et al. 610,000$ 781,100,000$ 1502,600,000$ 3304,200,000$ 540Mortality Levy et al. 630,000$ 811,200,000$ 1502,700,000$ 3404,300,000$ 560Hospital Admissions, Respiratory (0-1) 1,900$ 1904,800$ 48015,000$ 1,50026,000$ 2,700Hospital Admissions, Respiratory (65+) 4,400$ 19011,000$ 47034,000$ 1,40074,000$ 3,200Emergency Room Visits, Respiratory 32$ 87100$ 280370$ 1,000690$ 1,900School Loss Days 6,400$ 72,00018,000$ 200,00057,000$ 640,00099,000$ 1,100,000Worker Productivity 4,700$ 4,200,00010,000$ 9,000,00027,000$ 23,000,00049,000$ 42,000,000Acute Respiratory Symptoms 11,000$ 180,00029,000$ 500,00098,000$ 1,700,000170,000$ 2,900,000Mortality Bell et al. 2004 190,000$ 24550,000$ 711,900,000$ 2503,500,000$ 450Mortality Bell et al. 2005 620,000$ 801,800,000$ 2306,200,000$ 81011,000,000$ 1,500Mortality Ito et al. 830,000$ 1102,400,000$ 3108,500,000$ 1,10015,000,000$ 2,000Mortality Levy et al. 860,000$ 1102,500,000$ 3208,800,000$ 1,10016,000,000$ 2,100

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 totwo significant figures. Valuation results for mortality and nonfatal myocardial infarctions are shown at a 3% discount rate. Does not include visibility benefits.

### 6-92 Table 6.53: Regional Breakdown of Annual PM Be nefit Results by Heal th 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 $ 490National TotalEastRest of WestCalifornia

* 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 fi gures. Valuation results for mort ality 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 Be nefit Results by Heal th 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 $ 490National TotalEastRest of WestCalifornia

* 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 fi gures. Valuation results for mort ality 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 Oz one 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 $26,000,000East

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 $2,300,000Rest 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 $13,000,000California

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 $41,000,000National 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 Oz one 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 $23,000,000East

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 $2,100,000Rest of West

PM Mortality Expert K $5,700 $5,800 $81,000 $220,000Ozone 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 $11,000,000California

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 $37,000,000National 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.

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