Document ID: EPA-HQ-OAR-2007-0225-0033
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2007-08-02T04:00Z

Chapter 6.  Incremental Benefits of Attaining Alternative Ozone
Standards Relative to the Current 8-hour Standard (0.08 ppm) 

Synopsis

Based on projected emissions and air quality modeling, in 2020, 203
counties in the U.S. with ozone monitors are estimated to fail to meet
an alternative ozone standard of 0.070 ppm for the 4th highest maximum
8-hour ozone concentration.   This number falls to 82 for an alternative
standard of 0.075 ppm, and further to xxx for an ozone standard of 0.079
ppm and increases to 360 for an alternative standard of 0.065 ppm.  We
estimated the health benefits of attaining these alternative ozone
standards across the U.S. using the EPA Environmental Benefits Modeling
and Analysis Program (BenMAP).  We performed a two-stage analysis.  

In the first stage we estimated the benefits associated with changes in
modeled air quality following application of control technologies known
to be currently available.  These control strategies were sufficient to
bring some, but not all, areas into attainment with the various standard
levels.  Thus, the benefits computed during this first stage were for
partial attainment in some areas.  In the second stage, we estimated the
benefits of fully attaining the standards in all areas by using a
“rollback” methodology to reduce ozone concentrations at residually
nonattaining monitors to a level that would just meet the standards.  We
deviated from this two-stage approach when analyzing the 0.075 ppm
standard alternative, where we applied an interpolation technique that
is detailed further in this chapter. To calculate the monetary value of
the adverse health outcomes potentially avoided due to these reductions
in ambient ozone levels, we used health impact functions based on
published epidemiological studies, and valuation functions derived from
the economics literature.  Key health endpoints analyzed included
premature mortality, hospital and emergency room visits, school
absences, and minor restricted activity days.

There is considerable uncertainty in the magnitude of the association
between ozone and premature mortality. This analysis presents four
alternative estimates for the association based upon different functions
reported in the scientific literature..  We also note that there are
uncertainties within each study that are not fully captured by this
range of estimates.  Recognizing that additional research is needed to
more fully establish underlying mechanisms by which such effects occur,
we also consider the possibility that the observed associations between
ozone and mortality may not be causal in nature.  Using the National
Morbidity, Mortality and Air Pollution Study (NMMAPS) that was used as
the primary basis for the risk analysis presented in our Staff Paper and
reviewed by Clean Air Science Advisory Committee (CASAC), we estimated
280 avoided premature deaths annually in 2020 from reducing ozone levels
to meet a standard of 0.070 ppm, which, when added to the other
projected benefits from reduced ozone, including  5,600 hospital and
emergency room admissions, 780,000 school absences, and over 2,100,000
minor restricted activity days, leads to an estimated total
ozone-related benefit of $2 billion/yr (1999$).  Using three studies
that synthesize data across a large number of individual studies, we
estimate between 1,100 and 1,400 avoided premature deaths annually in
2020 from reducing ozone to 0.070 ppm, leading to total monetized
ozone-related benefits of between $7.4 and $9.1 billion/yr. 
Alternatively, if there is no causal relationship between ozone and
mortality, avoided premature deaths associated with reduced ozone
exposure would be zero and total monetized ozone-related morbidity
benefits would be $190 million/yr.  

For a less stringent standard of 0.075 ppm, using the NMMAPS ozone
mortality study resulted in 200 premature deaths avoided and total
monetized benefits of $1.6 billion/yr.  Using the three synthesis
studies, estimated premature deaths avoided for the less stringent
standard are between 880 and 1,100, with total monetized ozone benefits
between $5.9 and $7.3 billion/yr. Alternatively, if there is no causal
relationship between ozone and mortality, avoided premature deaths
associated with reduced ozone exposure would be zero and total monetized
ozone-related morbidity benefits would be $150 million/yr.  

For a more stringent standard of 0.065 ppm, using the NMMAPS ozone
mortality study resulted in 530 premature deaths avoided and total
monetized benefits of $3.7 billion/yr.  Using the three synthesis
studies, estimated premature deaths avoided for the more stringent
standard are between 2,100 and 2,400, with total monetized ozone
benefits between $14 and $16 billion/yr.  Alternatively, if there is no
causal relationship between ozone and mortality, avoided premature
deaths associated with reduced ozone exposure would be zero and total
monetized ozone-related morbidity benefits would be $330 million/yr.
These estimates reflect EPA's interim approach to characterizing the
benefits of reducing premature mortality associated with ozone exposure.
  EPA has requested advice from the National Academy of Sciences on how
best to quantify uncertainty in the relationship between ozone exposure
and premature mortality in the context of quantifying benefits
associated with alternative ozone control strategies. 

In addition to the direct benefits from reduced ozone concentrations,
attainment of the standards would likely result in health and welfare
benefits from the reduction of PM2.5 that would occur as ozone precursor
emissions (NOx and VOC) are reduced.  Using both modeled and
extrapolated reductions in these precursor emissions, we estimated
PM-related co-benefits for the three alternative standards.  For each
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 partial attainment of the 0.070 ppm standard, we estimated PM
co-benefits including between 220 and 2,200 premature deaths avoided,
with total monetized PM co-benefits of between $1.3 and $13 billion/yr
(3% discount rate, 1999$).  For the 2020 attainment of the 0.070 ppm
alternative, incremental to attainment of the 0.08 ppm standard, we
estimate total ozone and PM2.5-related co-benefits to be between $2.3B
and $31B; this range encompasses the expert functions and the ozone
mortality functions as well as the possibility that there is no causal
relationship between ozone and mortality. For the 2020 attainment of the
0.065 ppm alternative, incremental to attainment of the 0.08 ppm
standard, we estimate total benefits of between $4.3B and $56B; this
range encompasses the expert functions and the ozone mortality functions
as well as the possibility that there is no causal relationship between
ozone and mortality. For the 2020 attainment of the 0.075 ppm
alternative, incremental to attainment of the 0.08 ppm standard, we
estimate total ozone and PM2.5-related co-benefits to be between $1.2 B
and $19 B; this range encompasses the expert functions and the ozone
mortality functions as well as the possibility that there is no causal
relationship between ozone and mortality.

 6.1.  	Background

Our purpose for this analysis is to assess the human health benefits of
attaining alternative 8-hour ozone standards, including 0.075 ppm, 0.070
ppm, and 0.065 ppm, incremental to attainment of the current 8-hour
ozone standard of 0.08 ppm. We applied a damage function approach
similar to those used in several recent U.S. EPA regulatory impact
analyses, including those for the 2006 Particulate Matter (PM) NAAQS
(U.S. EPA, 2006) and the Clean Air Interstate Rule (U.S. EPA, 2005). 
This approach estimates changes in individual health and welfare
endpoints (specific effects that can be associated with changes in air
quality) and assigns values to those changes assuming independence of
the individual values.  Total benefits are calculated simply as the sum
of the values for all non-overlapping health and welfare endpoints. This
analysis largely builds off of both the analytical approach used in the
2006 PM NAAQS RIA and the analysis of ozone health impacts reported in
Hubbell et al. (2005) and the Clean Air Interstate Rule RIA (2005).  For
a more detailed discussion of the principles of benefits analysis used
here, we refer the reader to those documents, as well as to the EPA
Guidelines for Economic Analysis.,,  

We applied a two-stage approach to estimate the benefits of fully
attaining each alternative standard.  In the first stage, we estimated
the benefits associated with changes in modeled air quality following
application of control technologies known to be currently available. 
These control strategies were sufficient to bring some, but not all,
areas into attainment with the various standard levels.  Thus, the
benefits computed during this first stage were for partial attainment in
some areas (see Chapter 3 for details on these control technologies and
the results of the air quality modeling).  In the second stage, we
estimated the benefits of fully attaining the standards in all areas by
using a “rollback” methodology to reduce ozone concentrations at
residually nonattaining monitors to a level that would just meet the
standards (see Appendix 6 for details on this methodology).   We
conducted analyses to examine the sensitivity of our results to a number
of different assumptions about the choice of health effects and effect
estimates from published epidemiological studies, as well as parameters
that affect the economic valuation of health effects.  A quantitative
assessment of non-health benefits, e.g. benefits from reduced
ozone-related crop damage, was outside of the scope of this analysis due
to data and resource limitations.

For this assessment, we estimated benefits of changes in ozone and PM
co-benefits resulting from application of illustrative control
strategies on ozone precursor emissions to attain alternative ozone
NAAQS.  With the exception of ozone-related premature mortality, we use
methods consistent with previous PM and ozone benefits assessments. 
Specifically, the analysis of PM co-benefits uses an approach identical
to that used in the 2006 PM NAAQS RIA (U.S. EPA, 2006).  The ozone
benefits analysis for non-mortality endpoints uses an approach nearly
identical to that for the Clean Air Interstate Rule RIA (U.S. EPA,
2005). 

All ozone and PM2.5 co-benefits estimates in this chapter are
incremental to a baseline of national full attainment with 0.08 ppm.
This baseline incorporates emission reductions projected to be achieved
as a result of an array of federal rules such as the Clean Air
Interstate and Non-Road Diesel Rule, as well as ozone and PM2.5 state
implementation plans. Moreover, the PM2.5 co-benefits are incremental to
an assumption of full attainment of the 2006 PM2.5 NAAQS. A complete
discussion of the baseline may be found in Chapter 3. The PM co-benefits
presented in this chapter are incremental to the PM benefits estimated
in the 2006 PM NAAQS RIA and reflect the PM benefits from NOx reductions
associated with each ozone control strategy.

The remainder of this chapter describes the data and methods used in
this analysis, along with the results.  Additional details of the
analysis are provided in Appendix 6 of this RIA.  Section 6.2 discusses
the probabilistic framework for the benefits analysis and how key
uncertainties are addressed in the analysis.  Section 6.3 discusses the
literature on ozone- and PM-related health effects and describes the
specific set of health impact functions we used in the benefits
analysis.  Section 6.4 describes the economic values selected to
estimate the dollar value of ozone- and PM- related health impacts. 
Finally, Section 6.5 presents the results and implications of the
analysis.  

6.2.  	Characterizing Uncertainty: Moving Toward a Probabilistic
Framework for Benefits Assessment

The National Research Council (NRC) (2002) highlighted the need for EPA
to conduct rigorous quantitative analysis of uncertainty in its benefits
estimates and to present these estimates to decision makers in ways that
foster an appropriate appreciation of their inherent uncertainty.  In
response to these comments, EPA’s Office of Air and Radiation (OAR) is
developing a comprehensive strategy for characterizing the aggregate
impact of uncertainty in key modeling elements on both health incidence
and benefits estimates. Components of that process include emissions
modeling, air quality modeling, health effects incidence estimation, and
valuation. 

Two aspects of OAR’s approach that have been used in several recent
RIAs are employed here.,, First, we use Monte Carlo methods for
estimating characterizing random sampling error associated with the
concentration response functions from epidemiological studies and
economic valuation functions. Monte Carlo simulation uses random
sampling from distributions of parameters to characterize the effects of
uncertainty on output variables, such as incidence of premature
mortality. Specifically, we used Monte Carlo methods to generate
confidence intervals around the estimated health impact and dollar
benefits.    Distributions for individual effect estimates are based on
the reported standard errors in the epidemiological studies. 
Distributions for unit values are described in Table 6-4.

Second, we use a recently completed expert elicitation of the
concentration response function describing the relationship between
premature mortality and ambient PM2.5 concentration. We note that
incorporating only the uncertainty from random sampling error omits
important sources of uncertainty (e.g., in the functional form of the
model—e..g., whether or not a threshold may exist). Use of the expert
elicitation and incorporation of the standard errors approaches provide
insights into the likelihood of different outcomes and about the state
of knowledge regarding the benefits estimates. Both approaches have
different strengths and weaknesses, which are full described in Chapter
5 of the PM NAAQS RIA. 

In benefit analyses of air pollution regulations conducted to date, the
estimated impact of reductions in premature mortality has accounted for
85% to 95% of total benefits.  Therefore, in characterizing the
uncertainty related to the estimates of total benefits it is
particularly important to attempt to characterize the uncertainties
associated with this endpoint.  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. 
In our results, we report credible intervals based on these standard
errors, reflecting the uncertainty in the estimated change in incidence
of avoided premature deaths.  We also provide multiple estimates, to
reflect model uncertainty between alternative study designs.  In
addition, we characterize the uncertainty introduced by the inability of
existing empirical studies to discern whether the relationship between
ozone and pre-mature mortality is causal by providing an effect estimate
preconditioned on an assumption that the effect estimate for pre-mature
mortality from ozone is zero.  

For premature mortality associated with exposure to PM, we follow the
same approach used in the RIA for 2006 PM NAAQS (U.S. EPA, 2006),
presenting several empirical estimates of premature deaths avoided, and
a set of twelve estimates based on results of the expert elicitation
study.  Even these multiple characterizations, including confidence
intervals, omit the contribution to overall uncertainty of uncertainty
in air quality changes, baseline incidence rates, populations exposed
and transferability of the effect estimate to diverse locations. 
Furthermore, the approach presented here does not yet include methods
for addressing correlation between input parameters and the
identification of reasonable upper and lower bounds for input
distributions characterizing uncertainty in additional model elements.
As a result, the reported confidence intervals and range of estimates
give an incomplete picture about the overall uncertainty in the
estimates.  This information should be interpreted within the context of
the larger uncertainty surrounding the entire analysis. 

6.3.  	Health Impact Functions

Health impact functions measure the change in a health endpoint of
interest, such as hospital admissions, for a given change in ambient
ozone or PM concentration.  Health impact functions are derived from
primary epidemiology studies, meta-analyses of multiple epidemiology
studies, or expert elicitations.  A standard health impact function has
four components: 1) an effect estimate from a particular study; 2) a
baseline incidence rate for the health effect (obtained from either the
epidemiology study or a source of public health statistics such as the
Centers for Disease Control); 3) the size of the potentially affected
population; and 4) the estimated change in the relevant ozone or PM
summary measures.

A typical health impact function might look like:  

where y0 is the baseline incidence (the product of the baseline
incidence rate times the potentially affected population),  is the
effect estimate, and x is the estimated change in the summary ozone
measure.  There are other functional forms, but the basic elements
remain the same.  Chapter 3 described the ozone and PM air quality
inputs to the health impact functions.  The following subsections
describe the sources for each of the other elements:  size of
potentially affected populations; effect estimates; and baseline
incidence rates.

6.3.1  Potentially Affected Populations

The starting point for estimating the size of potentially affected
populations is the 2000 U.S. Census block level dataset (Geolytics
2002).  Benefits Modeling and Analysis Program (BenMAP) incorporates 250
age/gender/race categories to match specific populations potentially
affected by ozone and other air pollutants.  The software constructs
specific populations matching the populations in each epidemiological
study by accessing the appropriate age-specific populations from the
overall population database.  BenMAP projects populations to 2020 using
growth factors based on economic projections (Woods and Poole Inc.
2001). 

6.3.2  Effect Estimate Sources

The most significant benefits of reducing ambient concentrations of
ozone and PM are attributable to reductions in human health risks. 
EPA’s Ozone and PM Criteria Documents and the World Health
Organization’s 2003 and 2004 reports outline numerous health effects
known or suspected to be linked to exposure to ambient ozone and PM (US
EPA, 2006; US EPA, 2005; WHO, 2003; 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. 

More than one thousand new ozone health and welfare studies have been
published since EPA issued the 8-hour ozone standard in 1997.  Many of
these studies investigated the impact of ozone exposure on health
effects such as: changes in lung structure and biochemistry; lung
inflammation; asthma exacerbation and causation; respiratory
illness-related school absence; hospital and emergency room visits for
asthma and other respiratory causes; and premature death.  

We were not able to separately quantify all of the PM and ozone health
effects that have been reported in the ozone and PM criteria documents
in this analysis for four reasons: (1) the possibility of double
counting (such as hospital admissions for specific respiratory
diseases); (2) uncertainties in applying effect relationships that are
based on clinical studies to the potentially affected population; (3)
the lack of an established concentration-response relationship; or 4)
the inability to appropriately value the effect (for example, changes in
forced expiratory volume) in economic terms.  Table 6-1 lists the human
health and welfare effects of pollutants affected by the alternate
standards. Table 6-2 lists the health endpoints included in this
analysis.Table 6-1 Human Health and Welfare Effects of Pollutants
Affected by the Alternate Standards  TC \l2 " 

Pollutant/Effect	Quantified and Monetized in Base Estimatesa
Unquantified Effects - Changes in:

PM/Healthb	Premature mortality based on both cohort study estimates and
on expert elicitationc,d

Bronchitis:  chronic and acute

Hospital admissions:  respiratory and cardiovascular

Emergency room visits for asthma

Nonfatal heart attacks (myocardial infarction)

Lower and upper respiratory illness

Minor restricted-activity days

Work loss days 

Asthma exacerbations (asthmatic population)

Respiratory symptoms (asthmatic population)

Infant mortality	Subchronic bronchitis cases

Low birth weight

Pulmonary function

Chronic respiratory diseases other than chronic bronchitis

Nonasthma respiratory emergency room visits

UVb exposure (+/-)e

PM/Welfare

Visibility in Southeastern Class I areas

Visibility in northeastern and Midwestern Class I areas

Household soiling

Visibility in western U.S. Class I areas

Visibility in residential and non-Class I areas

UVb exposure (+/-)e

Ozone/Healthf	Premature mortality: short-term exposures

Hospital admissions:  respiratory 

Emergency room visits for asthma

Minor restricted-activity days

School loss days

Asthma attacks

Acute respiratory symptoms

	Cardiovascular emergency room visits

Chronic respiratory damage

Premature aging of the lungs

Nonasthma respiratory emergency room visits

UVb exposure (+/-)e

Ozone/Welfare

Decreased outdoor worker productivity 

Yields for commercial crops

Yields for commercial forests and noncommercial crops

Damage to urban ornamental plants

Recreational demand from damaged forest aesthetics

Ecosystem functions

UVb exposure (+/-)e

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

b In addition to primary economic endpoints, there are a number of
biological responses that have been associated with PM health effects
including morphological changes and altered host defense mechanisms. 
The public health impact of these biological responses may be partly
represented by our quantified endpoints.

c Cohort estimates are designed to examine the effects of long term
exposures to ambient pollution, but relative risk estimates may also
incorporate some effects due to shorter term exposures (see Kunzli, 2001
for a discussion of this issue).

d While some of the effects of short-term exposure are likely to be
captured by the cohort estimates, there may be additional premature
mortality from short-term PM exposure not captured in the cohort
estimates included in the primary analysis.

e May result in benefits or disbenefits.  

f In addition to primary economic endpoints, there are a number of
biological responses that have been associated with ozone health
including increased airway responsiveness to stimuli, inflammation in
the lung, acute inflammation and respiratory cell damage, and increased
susceptibility to respiratory infection.  The public health impact of
these biological responses may be partly represented by our quantified
endpoints.

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

  SEQ CHAPTER \h \r 1 Table 6-2.  Ozone and PM Related Health Endpoints
basis for the concentration-response function associated with that
endpoint, and sub-populations for which they were computed.

Endpoint	Pollutant	Study	Study Population

Premature Mortality

Premature mortality – daily time series, non-accidental	O3 (24-hour
avg)

O3 (24-hour avg)

O3 (1-hour max)

O3 (1-hour max)	Bell et al (2004) (NMMAPS study)

Meta-analyses:

Bell et al (2005)

Ito et al (2005)

Levy et al (2005)	All ages

Premature mortality —cohort study, all-cause	PM2.5 (annual avg)	Pope
et al. (2002  XE "Pope et al. (2002"  )

Laden et al. (2006)	>29 years

>25 years

Premature mortality, total exposures	PM2.5 (annual avg)	Expert
Elicitation (IEc, 2006  XE "IEc, 2006"  )	>24 years

Premature mortality — all-cause	PM2.5 (annual avg)	Woodruff et al.
(1997  XE "Woodruff et al. (1997"  )	Infant (<1 year)

Chronic Illness

Chronic bronchitis	PM2.5 (annual avg)	Abbey et al. (1995  XE "Abbey et
al. (1995"  )	>26 years

Nonfatal heart attacks	PM2.5 (24-hour avg)	Peters et al. (2001  XE
"Peters et al. (2001"  )	Adults (>18 years)

Hospital Admissions 

Respiratory	

O3 (24-hour avg)	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

Burnett et al. (2001)	<2 years

	PM2.5 (24-hour avg)	Pooled estimate:

Moolgavkar (2003  XE "Moolgavkar (2003"  )—ICD 490-496 (COPD)

Ito (2003  XE "Ito (2003"  )—ICD 490-496 (COPD)	>64 years

	PM2.5 (24-hour avg)	Moolgavkar (2000  XE "Moolgavkar (2000"  )—ICD
490-496 (COPD)	20–64 years

	PM2.5 (24-hour avg)	Ito (2003  XE "Ito (2003"  )—ICD 480-486
(pneumonia)	>64 years

	PM2.5 (24-hour avg)	Sheppard (2003  XE "Sheppard (2003"  )—ICD 493
(asthma)	<65 years

Cardiovascular	PM2.5 (24-hour avg)	Pooled estimate:

Moolgavkar (2003  XE "Moolgavkar (2003"  )—ICD 390-429 (all
cardiovascular)

Ito (2003  XE "Ito (2003"  )—ICD 410-414, 427-428 (ischemic heart
disease, dysrhythmia, heart failure)	>64 years

	PM2.5 (24-hour avg)	Moolgavkar (2000  XE "Moolgavkar (2000"  )—ICD
390-429 (all cardiovascular)	20–64 years

Asthma-related ER visits	O3 (8-hour max)	Pooled estimate:

Jaffe et al (2003)

Peel et al (2005)

Wilson et al (2005)	

5–34 years

All ages

All ages

Asthma-related ER visits (con’t)	PM2.5 (24-hour avg)	Norris et al.
(1999  XE "Norris et al. (1999"  )	0–18 years

Other Health Endpoints

Acute bronchitis	PM2.5 (annual avg)	Dockery et al. (1996  XE "Dockery et
al. (1996"  )	8–12 years

Upper respiratory symptoms	PM10 (24-hour avg)	Pope et al. (1991  XE
"Pope et al. (1991"  )	Asthmatics, 9–11 years

Lower respiratory symptoms	PM2.5 (24-hour avg)	Schwartz and Neas (2000 
XE "Schwartz and Neas (2000"  )	7–14 years

Asthma exacerbations	PM2.5 (24-hour avg)	Pooled estimate:

Ostro et al. (2001  XE "Ostro et al. (2001"  ) (cough, wheeze and
shortness of breath)

Vedal et al. (1998  XE "Vedal et al. (1998"  ) (cough)	6–18 yearsa

Work loss days	PM2.5 (24-hour avg)	Ostro (1987  XE "Ostro (1987"  )
18–65 years

School absence days	

O3 (8-hour avg)

O3 (1-hour max)	Pooled estimate:

Gilliland et al. (2001)

Chen et al. (2000)	

5–17 yearsb

Minor Restricted Activity Days (MRADs)	O3 (24-hour avg)	Ostro and
Rothschild (1989  XE "Ostro and Rothschild (1989"  )	18–65 years

	PM2.5 (24-hour avg)	Ostro and Rothschild (1989  XE "Ostro and
Rothschild (1989"  )	18–65 years

a   The original study populations were 8 to 13 for the Ostro et al.
(2001  XE "Ostro et al. (2001"  ) study and 6 to 13 for the Vedal et al.
(1998  XE "Vedal et al. (1998"  ) study.  Based on advice from the
Science Advisory Board Health Effects Subcommittee (SAB-HES), we
extended the applied population to 6 to 18, reflecting the common
biological basis for the effect in children in the broader age group.
See: U.S. Science Advisory Board. 2004.  Advisory Plans for Health
Effects Analysis in the Analytical Plan for EPA’s Second Prospective
Analysis –Benefits and Costs of the Clean Air Act, 1990—2020.
EPA-SAB-COUNCIL-ADV-04-004. See also National Research Council (NRC). 
2002.  Estimating the Public Health Benefits of Proposed Air Pollution
Regulations.  Washington, DC:  The National Academies Press.

b   Gilliland et al. (2001) studied children aged 9 and 10.  Chen et al.
(2000) studied children 6 to 11.  Based on recent advice from the
National Research Council and the EPA SAB-HES, we have calculated
reductions in school absences for all school-aged children based on the
biological similarity between children aged 5 to 17.

In selecting epidemiological studies as sources of effect estimates, we
applied several criteria to develop a set of studies that is likely to
provide the best estimates of impacts in the U.S.  To account for the
potential impacts of different health care systems or underlying health
status of populations, we give preference to U.S. studies over non-U.S.
studies.  In addition, due to the potential for confounding by
co-pollutants, we give preference to effect estimates from models
including both ozone and PM over effect estimates from single-pollutant
models.,

A number of endpoints that are not health-related also may significantly
contribute to monetized benefits.  Potential welfare benefits associated
with ozone exposure include: increased outdoor worker productivity;
increased yields for commercial and non-commercial crops; increased
commercial forest productivity; reduced damage to urban ornamental
plants; increased recreational demand for undamaged forest aesthetics;
and reduced damage to ecosystem functions (U.S. EPA 1999, 2006).  While
we include estimates of the value of increased outdoor worker
productivity, estimation of other welfare impacts is beyond the scope of
this analysis.  

6.3.2.1 Premature Mortality Effects Estimates

While particulate matter is the criteria pollutant most clearly
associated with premature mortality, recent research suggests that
short-term repeated ozone exposure likely contributes to premature
death.  The 2006 Ozone Criteria Document states:  “Consistent with
observed ozone-related increases in respiratory- and
cardiovascular-related morbidity, several newer multi-city studies,
single-city studies, and several meta-analyses of these studies have
provided relatively strong epidemiologic evidence for associations
between short-term ozone exposure and all-cause mortality, even after
adjustment for the influence of season and PM” (EPA, 2006: E-17).  The
epidemiologic data are also supported by newly available experimental
data from both animal and human studies which provide evidence
suggestive of plausible pathways by which risk of respiratory or
cardiovascular morbidity and mortality could be increased by ambient
ozone.  With respect to short-term exposure, the ozone Criteria Document
concludes:  “This overall body of evidence is highly suggestive that
ozone directly or indirectly contributes to non-accidental and
cardiopulmonary-related mortality, but additional research is needed to
more fully establish underlying mechanisms by which such effects
occur” (pg. E-18).	 

With respect to the time-series studies, the conclusion regarding the
relationship between short-term exposure and premature mortality is
based, in part, upon recent city-specific time-series studies such as
the Schwartz (2004) analysis in Houston and the Huang et al. (2004)
analysis in Los Angeles. This conclusion is also based on recent
meta-analyses by Bell et al. (2005), Ito et al. (2005), and Levy et al.
(2005), and a new analysis of the National Morbidity, Mortality, and Air
Pollution Study (NMMAPS) data set by Bell et al. (2004), which
specifically sought to disentangle the roles of ozone, PM,
weather-related variables, and seasonality.  The 2006 Criteria Document
states that “the results from these meta-analyses, as well as several
single- and multiple-city studies, indicate that co-pollutants generally
do not appear to substantially confound the association between ozone
and mortality” (p. 7-103).  However, CASAC raised questions about the
implications of these time-series results in a policy context. 
Specifically, CASAC emphasized that “…while the time-series study
design is a powerful tool to detect very small effects that could not be
detected using other designs, it is also a blunt tool” (Henderson,
2006: 3).  They point to findings (e.g., Stieb et al., 2002, 2003) that
indicated associations between premature mortality and all of the
criteria pollutants, indicating that “findings of time-series studies
do not seem to allow us to confidently attribute observed effects to
individual pollutants” (id.).  They note that “not only is the
interpretation of these associations complicated by the fact that the
day-to-day variation in concentrations of these pollutants is, to a
varying degree, determined by meteorology, the pollutants are often part
of a large and highly correlated mix of pollutants, only a very few of
which are measured” (id.).  Even with these uncertainties, the CASAC
Ozone Panel, in its review of EPA’s Staff Paper, found “…premature
total non-accidental and cardiorespiratory mortality for inclusion in
the quantitative risk assessment to be appropriate.”

Consistent with the methodology used in the ozone risk assessment found
in the Characterization of Health Risks found in the Review of the
National Ambient Air Quality Standards for Ozone: Policy Assessment of
Scientific and Technical Information, we included ozone mortality in the
primary health effects analysis, with the recognition that the exact
magnitude of the effects estimate is subject to continuing uncertainty. 
We used effect estimates from the Bell et al. (2004) NMMAPS analysis, as
well as effect estimates from the three meta-analyses.  In addition, we
include the possibility that there is not a causal association between
ozone and mortality, i.e., that the effect estimate for premature
mortality could be zero.  	

We estimate the change in mortality incidence and estimated credible
interval resulting from application of the effect estimate from each
study and present them separately to reflect differences in the study
designs and assumptions about causality.   However, it is important to
note that this procedure only captures the uncertainty in the underlying
epidemiological work, and does not capture other sources of uncertainty,
such as uncertainty in the estimation of changes in air pollution
exposure (Levy et al., 2000).

6.3.2.2 Respiratory Hospital Admissions Effect Estimates

Detailed hospital admission and discharge records provide data for an
extensive body of literature examining the relationship between hospital
admissions and air pollution. This is especially true for the portion of
the population aged 65 and older, because of the availability of
detailed Medicare records.  In addition, there is one study (Burnett et
al., 2001) providing an effect estimate for respiratory hospital
admissions in children under two.

Because the number of hospital admission studies we considered is so
large, we used results from a number of studies to pool some hospital
admission endpoints.  Pooling is the process by which multiple study
results may be combined in order to produce better estimates of the
effect estimate, or β. For a complete discussion of the pooling
process, see Abt (2005). To estimate total respiratory hospital
admissions associated with changes in ambient ozone concentrations for
adults over 65, we first estimated the change in hospital admissions for
each of the different effects categories that each study provided for
each city. These cities included Minneapolis, Detroit, Tacoma and New
Haven.  To estimate total respiratory hospital admissions for Detroit,
we added the pneumonia and COPD estimates, based on the effect estimates
in the Schwartz study (1994b).  Similarly, we summed the estimated
hospital admissions based on the effect estimates the Moolgavkar study
reported for Minneapolis (Moolgavkar et al., 1997).  To estimate total
respiratory hospital admissions for Minneapolis using the Schwartz study
(1994a), we simply estimated pneumonia hospital admissions based on the
effect estimate.  Making this assumption that pneumonia admissions
represent the total impact of ozone on hospital admissions in this city
will give some weight to the possibility that there is no relationship
between ozone and COPD, reflecting the equivocal evidence represented by
the different studies.  We then used a fixed-effects pooling procedure
to combine the two total respiratory hospital admission estimates for
Minneapolis.  Finally, we used random effects pooling to combine the
results for Minneapolis and Detroit with results from studies in Tacoma
and New Haven from Schwartz (1995).  As noted above, this pooling
approach incorporates both the precision of the individual effect
estimates and between-study variability characterizing differences
across study locations.

6.3.2.3 Asthma-Related Emergency Room Visits Effect Estimates

We used three studies as the source of the concentration-response
functions we used to estimate the effects of ozone exposure on
asthma-related emergency room (ER) visits:  Peel et al. (2005); Wilson
et al. (2005); and Jaffe et al. (2003).  We estimated the change in ER
visits using the effect estimate(s) from each study and then pooled the
results using the random effects pooling technique (see Abt, 2005).  The
study by Jaffe et al. (2003) examined the relationship between ER visits
and air pollution for populations aged five to 34 in the Ohio cities of
Cleveland, Columbus and Cincinnati from 1991 through 1996.  In
single-pollutant Poisson regression models, ozone was linked to asthma
visits.  We use the pooled estimate across all three cities as reported
in the study.  The Peel et al. study (2005) estimated asthma-related ER
visits for all ages in Atlanta, using air quality data from 1993 to
2000.  Using Poisson generalized estimating equations, the authors found
a marginal association between the maximum daily 8-hour average ozone
level and ER visits for asthma over a 3-day moving average (lags of 0,
1, and 2 days) in a single pollutant model.  Wilson et al. (2005)
examined the relationship between ER visits for respiratory illnesses
and asthma and air pollution for all people residing in Portland, Maine
from 1998-2000 and Manchester, New Hampshire from 1996-2000.  For all
models used in the analysis, the authors restricted the ozone data
incorporated into the model to the months ozone levels are usually
measured, the spring-summer months (April through September).  Using the
generalized additive model, Wilson et al. (2005) found a significant
association between the maximum daily 8-hour average ozone level and ER
visits for asthma in Portland, but found no significant association for
Manchester.   Similar to the approach used to generate effect estimates
for hospital admissions, we used random effects pooling to combine the
results across the individual study estimates for ER visits for asthma. 
The Peel et al. (2005) and Wilson et al. (2005) Manchester estimates
were not significant at the 95 percent level, and thus, the confidence
interval for the pooled incidence estimate based on these studies
includes negative values.  This is an artifact of the statistical power
of the studies, and the negative values in the tails of the estimated
effect distributions do not represent improvements in health as ozone
concentrations are increased.  Instead these should be viewed as a
measure of uncertainty due to limitations in the statistical power of
the study.  Note that we included both hospital admissions and ER visits
as separate endpoints associated with ozone exposure, because our
estimates of hospital admission costs do not include the costs of ER
visits, and because most asthma ER visits do not result in a hospital
admission. 

6.3.2.4 Minor Restricted Activity Days Effects Estimate

Minor restricted activity days (MRADs) occur when individuals reduce
most usual daily activities and replace them with less-strenuous
activities or rest, but do not miss work or school.  We estimated the
effect of ozone exposure on MRADs using a concentration-response
function derived from Ostro and Rothschild (1989).   These researchers
estimated the impact of ozone and PM2.5 on MRAD incidence in a national
sample of the adult working population (ages 18 to 65) living in
metropolitan areas.  We developed separate coefficients for each year of
the Ostro and Rothschild analysis (1976-1981), which we then combined
for use in EPA’s analysis.  The effect estimate used in the impact
function is a weighted average of the coefficients in Ostro and
Rothschild (1989, Table 4), using the inverse of the variance as the
weight.

6.3.2.5 School Absences Effect Estimate

Children may be absent from school due to respiratory or other acute
diseases caused, or aggravated by, exposure to air pollution.  Several
studies have found a significant association between ozone levels and
school absence rates.  We use two studies (Gilliland et al., 2001; Chen
et al., 2000) to estimate changes in school absences resulting from
changes in ozone levels.  The Gilliland et al. study estimated the
incidence of new periods of absence, while the Chen et al. study
examined daily absence rates.  We converted the Gilliland et al.
estimate to days of absence by multiplying the absence periods by the
average duration of an absence.  We estimated 1.6 days as the average
duration of a school absence, the result of dividing the average daily
school absence rate from Chen et al. (2000) and Ransom and Pope (1992)
by the episodic absence duration from Gilliland et al. (2001).  Thus,
each Gilliland et al. period of absence is converted into 1.6 absence
days.

Following recent advice from the National Research Council (2002), we
calculated reductions in school absences for the full population of
school age children, ages five to 17.  This is consistent with recent
peer-reviewed literature on estimating the impact of ozone exposure on
school absences (Hall et al. 2003).  We estimated the change in school
absences using both Chen et al. (2000) and Gilliland et al. (2001) and
then, similar to hospital admissions and ER visits, pooled the results
using the random effects pooling procedure.

6.3.2.6 Worker Productivity

To monetize benefits associated with increased worker productivity
resulting from improved

ozone air quality, we used information reported in Crocker and Horst
(1981). Crocker and Horst examined the impacts of ozone exposure on the
productivity of outdoor citrus workers. The study measured productivity
impacts. Worker productivity is measuring the value of the loss in
productivity for a worker who is at work on a particular day, but due to
ozone, cannot work as hard.  It only applies to outdoor workers, like
fruit and vegetable pickers, or construction workers. Here, productivity
impacts are measured as the change in income associated with a change in
ozone exposure, given as the elasticity of income with respect to ozone
concentration. The reported elasticity translates a ten percent
reduction in ozone to a 1.4 percent increase in income. Given the
national median daily income for outdoor workers engaged in strenuous
activity reported by the U.S. Census Bureau (2002), $68 per day (2000$),
a ten percent reduction in ozone yields about $0.97 in increased daily
wages. We adjust the national median daily income estimate to reflect
regional variations in income using a factor based on the ratio of
county median household income to national median household income. No
information was available for quantifying the uncertainty associated
with the central valuation estimate. Therefore, no uncertainty analysis
was conducted for this endpoint.

6.3.2.7 Visibility Benefits

Changes in the level of ambient PM2.5 caused by the reduction in
emissions associated with the proposed standards will change the level
of visibility throughout the United States.  Increases in PM
concentrations cause increases in light extinction, a measure of how
much the components of the atmosphere absorb light. Due to time
limitations, this benefits assessment does not consider the value of
improvements in visibility associated with simulated attainment of
alternate ozone standards. We anticipate that the benefits assessment
supporting the promulgated ozone standard will consider this important
benefits category.

Other Unquantified Effects

Direct Ozone Effects on Vegetation

The Ozone Criteria Document notes that “current ambient concentrations
in many areas of the country are sufficient to impair growth of numerous
common and economically valuable plant and tree species.” ( xe "U.S.
EPA, 1996a" U.S. EPA, 2006, page 9-1).  Changes in ground-level ozone
resulting from the implementation of alternative ozone standards are
expected to affect crop and forest yields throughout the affected area. 
Recent scientific studies have also found the ozone negatively impacts
the quality or nutritive value of crops (U.S. EPA, 2006, page 9-16).

Well-developed techniques exist to provide monetary estimates of these
benefits to agricultural producers and to consumers.  These techniques
use models of planting decisions, yield response functions, and the
supply of and demand for agricultural products.  The resulting welfare
measures are based on predicted changes in market prices and production
costs.  Models also exist to measure benefits to silvicultural producers
and consumers.  However, these models have not been adapted for use in
analyzing ozone-related forest impacts.  Because of resource
limitations, we are unable to provide agricultural or benefits estimates
for the proposed rule.

An additional welfare benefit expected to accrue as a result of
reductions in ambient ozone concentrations in the United States is the
economic value the public receives from reduced aesthetic injury to
forests.  There is sufficient scientific information available to
reliably establish that ambient ozone levels cause 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 EPA from quantifying the benefits of improved forest
aesthetics.

Urban ornamentals (floriculture and nursery crops) represent an
additional vegetation category likely to experience some degree of
negative effects associated with exposure to ambient ozone levels and
likely to affect large economic sectors.  In the absence of adequate
exposure-response functions and economic damage functions for the
potential range of effects relevant to these types of vegetation, no
direct quantitative economic benefits analysis has been conducted.  The
farm production value of ornamental crops was estimated at over $14
billion in 2003 (USDA, 2004).  This is therefore a potentially important
welfare effects category.  However, information and valuation methods
are not available to allow for plausible estimates of the percentage of
these expenditures that may be related to impacts associated with ozone
exposure.

Nitrogen Deposition  

Deposition to Estuarine and Coastal Waters	  

Excess nutrient loads, especially of nitrogen, cause a variety of
adverse consequences to the health of estuarine and coastal waters. 
These effects include toxic and/or noxious algal blooms such as brown
and red tides, low (hypoxic) or zero (anoxic) concentrations of
dissolved oxygen in bottom waters, the loss of submerged aquatic
vegetation due to the light-filtering effect of thick algal mats, and
fundamental shifts in phytoplankton community structure  xe "Bricker et
al., 1999" (Bricker et al., 1999).  A recent study found that for the
period 1990-2002, atmospheric deposition accounted for 17 percent of
nitrate loadings in the Gulf of Mexico, where severe hypoxic zones have
been existed over the last two decades (Booth and Campbell, 2007).

Reductions in atmospheric deposition of NOx are expected to reduce the
adverse impacts associated with nitrogen deposition to estuarine and
coastal waters.  However, direct functions relating changes in nitrogen
loadings to changes in estuarine benefits are not available.  The
preferred WTP-based measure of benefits depends on the availability of
these functions and on estimates of the value of environmental
responses.  Because neither appropriate functions nor sufficient
information to estimate the marginal value of changes in water quality
exist at present, calculation of a WTP measure is not possible.  

Deposition to Agricultural and Forested Land

Implementation strategies for alternative standards which reduce NOX
emissions, will also reduce nitrogen deposition on agricultural land and
forests.  There is some evidence that nitrogen deposition may have
positive effects on agricultural output through passive fertilization. 
Holding all other factors constant, farmers’ use of purchased
fertilizers or manure may increase as deposited nitrogen is reduced. 
Estimates of the potential value of this possible increase in the use of
purchased fertilizers are not available, but it is likely that the
overall value is very small relative to other health and welfare
effects.  The share of nitrogen requirements provided by this deposition
is small, and the marginal cost of providing this nitrogen from
alternative sources is quite low.  In some areas, agricultural lands
suffer from nitrogen over-saturation due to an abundance of on-farm
nitrogen production, primarily from animal manure.  In these areas,
reductions in atmospheric deposition of nitrogen from PM represent
additional agricultural benefits.

Information on the effects of changes in passive nitrogen deposition on
forests and other terrestrial ecosystems is very limited. The
multiplicity of factors affecting forests, including other potential
stressors such as ozone, and limiting factors such as moisture and other
nutrients, confound assessments of marginal changes in any one stressor
or nutrient in forest ecosystems.  However, reductions in deposition of
nitrogen could have negative effects on forest and vegetation growth in
ecosystems where nitrogen is a limiting factor (US EPA, 1993).

On the other hand, there is evidence that forest ecosystems in some
areas of the United States (such as the western U.S.) are nitrogen
saturated (US EPA, 1993).  Once saturation is reached, adverse effects
of additional nitrogen begin to occur such as soil acidification which
can lead to leaching of nutrients needed for plant growth and
mobilization of harmful elements such as aluminum.  Increased soil
acidification is also linked to higher amounts of acidic runoff to
streams and lakes and leaching of harmful elements into aquatic
ecosystems. 

Ultraviolet Radiation

Another category of potential effects that may change in response to
ozone reduction strategies results from the shielding provided by ozone
against the harmful effects of ultraviolet radiation (UV-B) derived from
the sun.  UV-B exposure has been linked to a number of health effects,
including fatal and nonfatal melanoma and non-melanoma skin cancers and
cataracts.   The values of $15,000 per case for non-fatal melanoma skin
cancer, $5,000 per case for non-fatal non-melanoma skin cancer, and
$15,000 per case of cataracts have been used in analyses of
stratospheric ozone depletion (U.S. EPA, 1999).  Fatal cancers are
valued using the standard VSL estimate, which for 2020 is $6.6 million
(1999$). UV-B has also been linked to ecological effects including
damage to crops and forests.  For a more complete listing, see Table G-4
in the Benefits and Costs of the Clean Air Act, 1990-2010 (U.S. EPA,
1999).  UV-B related health effects are also discussed in the context of
stratospheric ozone in a 2006 report by ICF Consulting, prepared for the
U.S. EPA.  The great majority of UV-b shielding results from naturally
occurring ozone in the stratosphere, but the 10 percent of total
“column” ozone present in the troposphere also contributes (NAS,
1991). A variable portion of this tropospheric fraction of UV-B
shielding is derived from ground level or “smog” ozone related to
anthropogenic air pollution. Therefore, strategies that reduce ground
level ozone will, in some small measure, increase exposure to UV-B from
the sun. 

There are many factors that influence UV-B radiation penetration to the
earth’s surface, including latitude, altitude, cloud cover, surface
albedo, PM concentration and composition, and gas phase pollution. Of
these, only latitude and altitude can be defined with small uncertainty
in any effort to assess the changes in UV-B flux that may be
attributable to any changes in tropospheric O3 as a result of any
revision to the O3 NAAQS. Such an assessment of UV-B related health
effects would also need to take into account human habits, such as
outdoor activities (including age- and occupation-related exposure
patterns), dress and skin care to adequately estimate UV-B exposure
levels.

However, little is known about the impact of these factors on individual
exposure to UVB.

Moreover, detailed information does not exist regarding other factors
that are relevant to assessing changes in disease incidence, including:
type (e.g., peak or cumulative) and time period (e.g., childhood,
lifetime, current) of exposures related to various adverse health
outcomes (e.g., damage to the skin, including skin cancer; damage to the
eye, such as cataracts; and immune system suppression); wavelength
dependency of biological responses; and interindividual variability in
UV-B resistance to such health outcomes. Beyond these well recognized
adverse health effects associated with various wavelengths of UV
radiation, the Criteria Document (section 10.2.3.6) also discusses
protective effects of UV-B radiation. Recent reports indicate the
necessity of UV-B in producing vitamin D, and that vitamin D deficiency
can cause metabolic bone disease among children and adults, and may also
increase the risk of many common chronic diseases (e.g., type I diabetes
and rheumatoid arthritis) as well as the risk of various types of
cancers. Thus, the Criteria Document concludes that any assessment that
attempts to quantify the consequences of increased UV-B exposure on
humans due to reduced ground-level O3 must include consideration of both
negative and positive effects. However, as with other impacts of UV-B on
human health, this beneficial effect of UV-B radiation has not been
studied in sufficient detail to allow for a credible health benefits or
risk assessment. In conclusion, the effect of changes in surface-level
O3 concentrations on UV-induced health outcomes cannot yet be critically
assessed within reasonable uncertainty (Criteria Document, p. 10-36).

In conclusion, the effect of changes in tropospheric O3 concentrations
on UV-B induced health outcomes cannot yet be critically assessed within
reasonable uncertainty. However, not accounting for the effects of
increased UV-B exposures likely lends a small upward bias to the net
monetized benefits presented in this analysis.

6.3.2.8.4 Climate Implications of Tropospheric Ozone

Although climate and air quality are generally treated as separate
issues, they are closely coupled through atmospheric processes.   Ozone,
itself, is a major greenhouse gas and climate directly influences
ambient concentrations of ozone.

The concentration of tropospheric ozone has increased substantially
since the pre-industrial era and has contributed to warming. 
Tropospheric ozone is (after CO2 and CH4) the third most important
contributor to greenhouse gas warming.  The National Academy of Sciences
recently stated that regulations targeting ozone precursors would have
combined benefits for public health and climate.  As noted in the OAQPS
Staff Paper, the overall body of scientific evidence suggests that high
concentrations of ozone on a regional scale could have a discernible
influence on climate. However, the Staff Paper concludes that
insufficient information is available at this time to quantitatively
inform the secondary NAAQS process with regard to this aspect of the
ozone-climate interaction.  

Climate change can affect tropospheric ozone by modifying emissions of
precursors, chemistry, transport and removal. Climate change affects the
sources of ozone precursors through physical response (lightning),
biological response (soils, vegetation, and biomass burning) and human
response (energy generation, land use, and agriculture).  Increases in
regional ozone pollution are expected due to higher temperatures and
weaker circulation.  Simulations with global climate models for the 21st
century indicate a decrease in the lifetime of tropospheric ozone due to
increasing water vapor which could decrease global background ozone
concentrations.

The Intergovernmental Panel on Climate Change (IPCC) recently released a
report which projects, with “virtual certainty,” declining air
quality in cities due to warmer and fewer cold days and nights and/or
warmer/more frequent hot days and nights over most land areas.  The
report states that projected climate change-related exposures are likely
to affect the health status of millions of people, in part, due to
higher concentrations of ground level ozone related to climate change.

The IPCC also reports that the current generation of tropospheric ozone
models is generally successful in describing the principal features of
the present-day global ozone distribution.  However, there is much less
confidence in the ability to reproduce the changes in ozone associated
with perturbations of emissions or climate. There are major
discrepancies with observed long-term trends in ozone concentrations
over the 20th century, including after 1970 when the reliability of
observed ozone trends is high. Resolving these discrepancies is needed
to establish confidence in the models.

The EPA is currently leading a research effort with the goal of
identifying changes in regional US air quality that may occur in a
future (2050) climate, focusing on fine particles and ozone. The
research builds first on an assessment of changes in US air quality due
to climate change, which includes direct meteorological impacts on
atmospheric chemistry and transport and the effect of temperature
changes on air pollution emissions. Further research will result in an
assessment that adds the emission impacts from technology, land use,
demographic changes, and air quality regulations to construct plausible
scenarios of US air quality 50 years into the future.  As noted in the
Staff Paper, results from these efforts are expected to be available for
consideration in the next review of the ozone NAAQS.  

6.3.3  Baseline Incidence Rates

Epidemiological studies of the association between pollution levels and
adverse health effects generally provide a direct estimate of the
relationship of air quality changes to the relative risk of a health
effect, rather than estimating the absolute number of avoided cases. 
For example, a typical result might be that a 100 ppb decrease in daily
ozone levels might, in turn, decrease hospital admissions by 3 percent. 
The baseline incidence of the health effect is necessary to convert this
relative change into a number of cases.  A baseline incidence rate is
the estimate of the number of cases of the health effect per year in the
assessment location, as it corresponds to baseline pollutant levels in
that location.  To derive the total baseline incidence per year, this
rate must be multiplied by the corresponding population number.  For
example, if the baseline incidence rate is the number of cases per year
per 100,000 people, that number must be multiplied by the number of
100,000s in the population.

Table 6-3 summarizes the sources of baseline incidence rates and
provides average incidence rates for the endpoints included in the
analysis.  For both baseline incidence and prevalence data, we used
age-specific rates where available.  We applied concentration-response
functions to individual age groups and then summed over the relevant age
range to provide an estimate of total population benefits.  In most
cases, we used a single national incidence rate, due to a lack of more
spatially disaggregated data.  Whenever possible, the national rates
used are national averages, because these data are most applicable to a
national assessment of benefits.  For some studies, however, the only
available incidence information comes from the studies themselves; in
these cases, incidence in the study population is assumed to represent
typical incidence at the national level.  Regional incidence rates are
available for hospital admissions, and county-level data are available
for premature mortality.  We have projected mortality rates such that
future mortality rates are consistent with our projections of population
growth (Abt Associates, 2005  XE "Abt Associates, 2005"  ).

Table 6-3.  National Average Baseline Incidence Rates

Endpoint	Source	Notes	Rate per 100 people per year D by Age Group

	<18	18-24	25-34	35-44	45-54	55-64	65+

Mortality	CDC Compressed Mortality File, accessed through CDC Wonder
(1996-1998)	non-accidental	0.025	0.022	0.057	0.150	0.383	1.006	4.937

Respiratory Hospital Admissions. 	1999 NHDS public use data filesB
incidence	0.043	0.084	0.206	0.678	1.926	4.389	11.629

Asthma ER visits	2000 NHAMCS public use data filesC; 1999 NHDS public
use data filesB	incidence	1.011	1.087	0.751	0.438	0.352	0.425	0.232

Minor Restricted Activity Days (MRADs)	Ostro and Rothschild  
MACROBUTTON endnote+.cit (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	–	–	–	–	–	–

A The following abbreviations are used to describe the national surveys
conducted by the National Center for Health Statistics: HIS refers to
the National Health Interview Survey; NHDS - National Hospital Discharge
Survey; NHAMCS - National Hospital Ambulatory Medical Care Survey.

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

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

D All of the rates reported here are population-weighted incidence rates
per 100 people per year.  Additional details on the incidence and
prevalence rates, as well as the sources for these rates are available
upon request. Table 6-3 National Average Baseline Incidence Rates
(continued)

Endpoint	Source	Notes	Rate per 100 people per year 4 

Asthma Exacerbations	Ostro et al. (2001)	Incidence (and prevalence)
among asthmatic African-American children	Daily wheeze

Daily cough

Daily dyspnea	0.076 (0.173)

0.067 (0.145)

0.037 (0.074)

	Vedal et al. (1998)	Incidence (and prevalence) among asthmatic children
Daily wheeze

Daily cough

Daily dyspnea	0.038

0.086

0.045

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 willingness-to-pay (WTP)
for changes in risk of a health effect rather than WTP for a health
effect that would occur with certainty (Freeman, 1993).  Epidemiological
studies generally provide estimates of the relative risks of a
particular health effect that is avoided because of a reduction in air
pollution. We converted those to units of avoided statistical incidence
for ease of presentation. We calculated the value of avoided statistical
incidences by dividing individual WTP for a risk reduction by the
related observed change in risk.  For example, suppose a
pollution-reduction regulation is able to reduce the risk of premature
mortality from 2 in 10,000 to 1 in 10,000 (a reduction of 1 in 10,000).
If individual WTP for this risk reduction is $100, then the WTP for an
avoided statistical premature death is $1 million ($100/0.0001 change in
risk).

WTP estimates generally are not available for some health effects, such
as hospital admissions.  In these cases, we used the cost of treating or
mitigating the effect as a primary estimate.  These cost-of-illness
(COI) estimates generally understate the true value of reducing the risk
of a health effect, because they reflect the direct expenditures related
to treatment, but not the value of avoided pain and suffering
(Harrington and Portney, 1987; Berger, 1987).  We provide unit values
for health endpoints (along with information on the distribution of the
unit value) in Table 6-4.  All values are in constant year 2000 dollars,
adjusted for growth in real income out to 2020 using projections
provided by Standard and Poor’s. Economic theory argues that WTP for
most goods (such as environmental protection) will increase if real
income increases.  Many of the valuation studies used in this analysis
were conducted in the late 1980s and early 1990s.  Because real income
has grown since the studies were conducted, people’s willingness to
pay for reductions in the risk of premature death and disease likely has
grown as well.  We did not adjust cost of illness-based values because
they are based on current costs.  Similarly, we did not adjust the value
of school absences, because that value is based on current wage rates. 
Table 6.4 presents the values for individual endpoints adjusted to year
2020 income levels.  The discussion below provides additional details on
ozone related endpoints.  For details on valuation estimates for PM
related endpoints, see the 2006 PM NAAQS RIA. 	

6.4.1 Mortality Valuation

To estimate the monetary benefit of reducing the risk of premature
death, we used the “value of statistical lives” saved (VSL)
approach, which is a summary measure for the value of small changes in
mortality risk for a large number of people.  The VSL approach applies
information from several published value-of-life studies to determine a
reasonable monetary value of preventing premature mortality.  The mean
value of avoiding one statistical death is estimated to be roughly $5.5
million at 1990 income levels (2000 $), and $6.6 million at 2020 income
levels.  This represents an intermediate value from a variety of
estimates in the economics literature (see the 2006 PM NAAQS RIA for
more details on the calculation of VSL). 

6.4.2 Hospital Admissions Valuation

In the absence of estimates of societal WTP to avoid hospital
visits/admissions for specific illnesses, estimates of total cost of
illness (total medical costs plus the value of lost productivity)
typically are used as conservative, or lower bound, estimates. These
estimates are biased downward, because they do not include the
willingness-to-pay value of avoiding pain and suffering.  

n.  

6.4.3 Asthma-Related Emergency Room Visits Valuation

To value asthma emergency room visits, we used a simple average of two
estimates from the health economics literature.  The first estimate
comes from Smith et al. (1997), who reported approximately 1.2 million
asthma-related emergency room visits in 1987, at a total cost of $186.5
million (1987$).  The average cost per visit that year was $155; in
2000$, that cost was $311.55 (using the CPI-U for medical care to adjust
to 2000$).  The second estimate comes from Stanford et al. (1999), who
reported the cost of an average asthma-related emergency room visit at
$260.67, based on 1996-1997 data.  A simple average of the two estimates
yields a (rounded) unit value of $286.

6.4.4 Minor Restricted Activity Days Valuation 

No studies are reported to have estimated WTP to avoid a minor
restricted activity day.  However, one of EPA’s contractors, IEc
(1993) has derived an estimate of willingness to pay to avoid a minor
respiratory restricted activity day, using estimates from Tolley et al.
(1986) of WTP for avoiding a combination of coughing, throat congestion
and sinusitis.  The IEc estimate of WTP to avoid a minor respiratory
restricted activity day is $38.37 (1990$), or about $52 ($2000).

Although Ostro and Rothschild (1989) statistically linked ozone and
minor restricted activity days, it is likely that most MRADs associated
with ozone exposure are, in fact, minor respiratory restricted activity
days. For the purpose of valuing this health endpoint, we used the
estimate of mean WTP to avoid a minor respiratory restricted activity
day.

6.4.5 School Absences

To value a school absence, we:  (1) estimated the probability that if a
school child stays home from school, a parent will have to stay home
from work to care for the child; and (2) valued the lost productivity at
the parent’s wage.  To do this, we estimated the number of families
with school-age children in which both parents work, and we valued a
school-loss day as the probability that such a day also would result in
a work-loss day. We calculated this value by multiplying the proportion
of households with school-age children by a measure of lost wages.

We used this method in the absence of a preferable WTP method. However,
this approach suffers from several uncertainties. First, it omits
willingness to pay to avoid the symptoms/illness that resulted in the
school absence; second, it effectively gives zero value to school
absences that do not result in work-loss days; and third, it uses
conservative assumptions about the wages of the parent staying home with
the child. Finally, this method assumes that parents are unable to work
from home. If this is not a valid assumption, then there would be no
lost wages. 

For this valuation approach, we assumed that in a household with two
working parents, the female parent will stay home with a sick child. 
From the Statistical Abstract of the United States (U.S. Census Bureau,
2001), we obtained:  (1) the numbers of single, married and “other”
(widowed, divorced or separated) working women with children; and (2)
the rates of participation in the workforce of single, married and
“other” women with children.  From these two sets of statistics, we
calculated a weighted average participation rate of 72.85 percent.

Our estimate of daily lost wage (wages lost if a mother must stay at
home with a sick child) is based on the year 2000 median weekly wage
among women ages 25 and older (U.S. Census Bureau, 2001). This median
weekly wage is $551. Dividing by five gives an estimated median daily
wage of $103. To estimate the expected lost wages on a day when a mother
has to stay home with a school-age child, we first estimated the
probability that the mother is in the workforce then multiplied that
estimate by the daily wage she would lose by missing a work day: 72.85
percent times $103, for a total loss of $75.   This valuation approach
is similar to that used by Hall et al. (2003).

Table 6-4.  Unit Values for Economic Valuation of Health Endpoints
(1999$)

Health Endpoint	Central Estimate of Value Per Statistical Incidence

1990 Income Level	2020 Income Level	Derivation of Distributions of
Estimates

Premature Mortality (Value of a Statistical Life)	$5,500,000	$6,600,000
Point estimate is the mean of a normal distribution with a 95%
confidence interval between $1 and $10 million.  Confidence interval is
based on two meta-analyses of the wage-risk VSL literature:  $1 million
represents the lower end of the interquartile range from the Mrozek and
Taylor (2002  XE "Mrozek and Taylor (2002"  ) meta-analysis and $10
million represents the upper end of the interquartile range from the
Viscusi and Aldy (2003  XE "Viscusi and Aldy (2003"  ) meta-analysis. 
The mean of the distribution is consistent with the mean estimate from a
third meta-analysis (Kochi et al 2006). The VSL represents the value of
a small change in mortality risk aggregated over the affected
population.

Chronic Bronchitis (CB)	$340,000	$420,000	The WTP to avoid a case of
pollution-related CB is calculated as 

 is the WTP for a severe case of CB, and  is the parameter relating
WTP to severity, based on the regression results reported in   XE
"Krupnick and Cropper, 1992"  Krupnick and Cropper (1992).  The
distribution of WTP for an average severity-level case of CB was
generated by Monte Carlo methods, drawing from each of three
distributions:  (1) WTP to avoid a severe case of CB is assigned a 1/9
probability of being each of the first nine deciles of the distribution
of WTP responses in   XE "Viscusi et al., 1991"  Viscusi et al. (1991);
(2) the severity of a pollution-related case of CB (relative to the case
described in the Viscusi study) is assumed to have a triangular
distribution, with the most likely value at severity level 6.5 and
endpoints at 1.0 and 12.0; and (3) the constant in the elasticity of WTP
with respect to severity is normally distributed with mean = 0.18 and
standard deviation = 0.0669 (from   XE "Krupnick and Cropper, 1992" 
Krupnick and Cropper [1992]).  This process and the rationale for
choosing it is described in detail in the Costs and Benefits of the
Clean Air Act, 1990 to 2010 (  XE "U.S. EPA, 1999"  EPA, 1999). 

(continued)

Table 6-4:  Unit Values Used for Economic Valuation of Health Endpoints
(1999$) (continued)

Health Endpoint	Central Estimate of Value Per Statistical Incidence

1990 Income Level	2020 Income Level	Derivation of Distributions of
Estimates

Nonfatal Myocardial Infarction (heart attack)

	3% discount rate

	Age 0–24

	Age 25–44

	Age 45–54

	Age 55–65

	Age 66 and over

	7% discount rate

	Age 0–24

	Age 25–44

	Age 45–54

	Age 55–65

	Age 66 and over	

$66,902

$74,676

$78,834

$140,649

$66,902

$65,293

$73,149

$76,871

$132,214

$65,293	

$66,902

$74,676

$78,834

$140,649

$66,902

$65,293

$73,149

$76,871

$132,214

$65,293	No distributional information available.  Age-specific
cost-of-illness values reflect lost earnings and direct medical costs
over a 5-year period following a nonfatal MI.  Lost earnings estimates
are based on Cropper and Krupnick (1990  XE "Cropper and Krupnick (1990"
 ).  Direct medical costs are based on simple average of estimates from
Russell et al. (1998  XE "Russell et al. (1998"  ) and Wittels et al.
(1990  XE "Wittels et al. (1990"  ).

Lost earnings:

Cropper and Krupnick (1990  XE "Cropper and Krupnick (1990"  ).  Present
discounted value of 5 years of lost earnings:

age of onset:	at 3%	at 7%

25-44	$8,774	$7,855

45-54	$12,932	$11,578

55-65	$74,746	$66,920

Direct medical expenses:  An average of:

1.	Wittels et al. (1990  XE "Wittels et al. (1990"  ) ($102,658—no
discounting)

2.	Russell et al. (1998  XE "Russell et al. (1998"  ), 5-year period
($22,331 at 3% discount rate; $21,113 at 7% discount rate)

Hospital Admissions

Chronic Obstructive Pulmonary Disease (COPD)

	$12,378	$12,378	No distributional information available. The COI
estimates (lost earnings plus direct medical costs) are based on ICD-9
code-level information (e.g., average hospital care costs, average
length of hospital stay, and weighted share of total COPD category
illnesses) reported in Agency for Healthcare Research and Quality (2000 
XE "Agency for Healthcare Research and Quality (2000"  ) (www.ahrq.gov).

Asthma Admissions	$6,634	$6,634	No distributional information available.
The COI estimates (lost earnings plus direct medical costs) are based on
ICD-9 code-level information (e.g., average hospital care costs, average
length of hospital stay, and weighted share of total asthma category
illnesses) reported in Agency for Healthcare Research and Quality (2000)
(www.ahrq.gov). 

All Cardiovascular

	$18,387	$18,387	No distributional information available. The COI
estimates (lost earnings plus direct medical costs) are based on ICD-9
code-level information (e.g., average hospital care costs, average
length of hospital stay, and weighted share of total cardiovascular
category illnesses) reported in Agency for Healthcare Research and
Quality (2000) (www.ahrq.gov). 

All respiratory (ages 65+)	$18,353	$18,353	No distributions available.
The COI point estimates (lost earnings plus direct medical costs) are
based on ICD-9 code level information (e.g., average hospital care
costs, average length of hospital stay, and weighted share of total COPD
category illnesses) reported in Agency for Healthcare Research and
Quality, 2000 (www.ahrq.gov).

Table 6-4:  Unit Values Used for Economic Valuation of Health Endpoints
(1999$) (continued)

Health Endpoint	Central Estimate of Value Per Statistical Incidence

1990 Income Level	2020 Income Level	Derivation of Distributions of
Estimates

All respiratory (ages 0-2)	$7,741   	$7,741   	No distributions
available. The COI point estimates (lost earnings plus direct medical
costs) are based on ICD-9 code level information (e.g., average hospital
care costs, average length of hospital stay, and weighted share of total
COPD category illnesses) reported in Agency for Healthcare Research and
Quality, 2000 (www.ahrq.gov).

Emergency Room Visits for Asthma	$286	$286	No distributional information
available.  Simple average of two unit COI values:

(1) $311.55, from Smith et al. (1997  XE "Smith et al. (1997"  ) and

(2) $260.67, from Stanford et al. (1999  XE "Stanford et al. (1999"  ).

Respiratory Ailments Not Requiring Hospitalization

Upper Respiratory Symptoms (URS)	$25	$27	Combinations of the three
symptoms for which WTP estimates are available that closely match those
listed by Pope et al. result in seven different “symptom clusters,”
each describing a “type” of URS.  A dollar value was derived for
each type of URS, using mid-range estimates of WTP (IEc, 1994) to avoid
each symptom in the cluster and assuming additivity of WTPs.  In the
absence of information surrounding the frequency with which each of the
seven types of URS occurs within the URS symptom complex, we assumed a
uniform distribution between $9.2 and $43.1.

Lower Respiratory Symptoms (LRS)	$16	$18	Combinations of the four
symptoms for which WTP estimates are available that closely match those
listed by Schwartz et al. result in 11 different “symptom clusters,”
each describing a “type” of LRS.  A dollar value was derived for
each type of LRS, using mid-range estimates of WTP (IEc, 1994) to avoid
each symptom in the cluster and assuming additivity of WTPs.  The dollar
value for LRS is the average of the dollar values for the 11 different
types of LRS.  In the absence of information surrounding the frequency
with which each of the 11 types of LRS occurs within the LRS symptom
complex, we assumed a uniform distribution between $6.9 and $24.46.

Asthma Exacerbations	$42	$45	Asthma exacerbations are valued at $45 per
incidence, based on the mean of average WTP estimates for the four
severity definitions of a “bad asthma day,” described in   XE "Rowe
and Chestnut (1986"  Rowe and Chestnut (1986).  This study surveyed
asthmatics to estimate WTP for avoidance of a “bad asthma day,” as
defined by the subjects.  For purposes of valuation, an asthma
exacerbation is assumed to be equivalent to a day in which asthma is
moderate or worse as reported in the   XE "Rowe and Chestnut (1986" 
Rowe and Chestnut (1986) study.  The value is assumed have a uniform
distribution between $15.6 and $70.8.

(continued)

Table 6-4:  Unit Values Used for Economic Valuation of Health Endpoints
(1999$) (continued)

Health Endpoint	Central Estimate of Value Per Statistical Incidence

1990 Income Level	2020 Income Level	Derivation of Distributions of
Estimates

Acute Bronchitis	$360	$380	Assumes a 6-day episode, with the
distribution of the daily value specified as uniform with the low and
high values based on those recommended for related respiratory symptoms
in   XE "Neumann et al. (1994"  Neumann et al. (1994).  The low daily
estimate of $10 is the sum of the mid-range values recommended by   XE
"IEc, 1994"  IEc   MACROBUTTON endnote+.cit (1994)  for two symptoms
believed to be associated with acute bronchitis:  coughing and chest
tightness.  The high daily estimate was taken to be twice the value of a
minor respiratory restricted-activity day, or $110.  

Work Loss Days (WLDs)	Variable (U.S. median=$110)

No distribution available.  Point estimate is based on county-specific
median annual wages divided by 50 (assuming 2 weeks of vacation) and
then by 5—to get median daily wage. U.S. Year 2000 Census, compiled by
Geolytics, Inc.

Minor Restricted Activity Days (MRADs)	$51	$54	Median WTP estimate to
avoid one MRAD from Tolley et al. (1986).  Distribution is assumed to be
triangular with a minimum of $22 and a maximum of $83, with a most
likely value of $52.  Range is based on assumption that value should
exceed WTP for a single mild symptom (the highest estimate for a single
symptom—for eye irritation—is $16.00) and be less than that for a
WLD.  The triangular distribution acknowledges that the actual value is
likely to be closer to the point estimate than either extreme.

School Absence Days	$75	$75	No distribution available

6.5  	Results and Implications

Tables 6-5 through 6-22 summarize the reduction in incidence for ozone-
and PM-related health endpoints for each of the alternative ozone
standards evaluated.  Tables 6-23 through 6-34 summarize the
ozone-related economic benefits for each of the alternative standards.
Note that incidence and valuation estimates for each standard
alternative are broken into two sets of tables.  The first set of tables
summarizes incidence and valuation for simulated national attainment
with the standard alternative in the East and areas outside of
California, and “glidepath” attainment in California. The second set
of tables present incidence and valuation estimates for California
post-2020, to account for the additional emission reductions projected
to occur as a result of full implementation of a series of mobile source
rules.  In addition to the mean incidence estimates, we have included
5th and 95th percentile estimates, except where noted, based on the
Monte Carlo simulations described above.  In the tables presenting the
0.065 ppm and 0.070 ppm estimates, the total change in ozone-related
incidence from fully attaining the alternative standards is broken out
into the change in incidence associated with the modeled partial
attainment scenario and the sum of the change in incidence associated
with achieving the partial attainment increment plus the residual
attainment increment.  As described in Appendix 6, to calculate the
change in ozone concentrations to reach full attainment, we rolled back
the ozone monitor data so that the 4th highest daily maximum 8-hour
average just met the level required to attain the alternative standard. 
This approach will likely understate the benefits that would occur due
to implementation of actual controls to reduce ozone precursor emissions
because controls implemented to reduce ozone concentrations at the
highest monitor would likely result in some reductions in ozone
concentrations at attaining monitors down-wind (i.e. the controls would
lead to concentrations below the standard in down-wind locations). 
Therefore, air quality improvements and resulting health benefits from
full attainment would be more widespread than we have estimated in our
rollback analyses. The incidence and valuation results for attainment of
the 0.075 ppm alternative are derived through an interpolation technique
described in Appendix 6. As such, these estimates are presented as full
attainment only.

In addition to disaggregating ozone benefits between modeled and
rollback for the 0.070 ppm standard alternative, we also provide
disaggregation by region, with separate benefits estimates for the
Eastern U.S., California, and the Western U.S. outside of California.
The estimates of ozone-related mortality and morbidity for California
are broken into glidepath and full attainment.  Certain California
projected non-attainment counties are required to meet an ozone target
above the actual standard  (that is, a “glidepath”) by 2020 due to
the severity of non-attainment. The estimates in this column reflect the
benefits of meeting this target.  

6.5.1 Glidepath incidence and valuation estimates for 0.065 ppm and
0.075 ppm alternatives

This analysis includes an assessment of the benefits of reaching the
glidepath targets for each of the standard alternatives in 2020 in
California. Due to time and resource limitations, we were able to
perform a full scale benefits analysis of the California glidepath
targets for the 0.070 ppm alternative only. Thus, we derived the
glidepath benefits estimates for the 0.075 ppm and 0.065 ppm
alternatives by applying a scaling factor. This scaling factor
represents the ratio of the California 0.070 ppm glidepath full
attainment benefits to the California 0.070 ppm full attainment
benefits. This process entailed the following steps: (1) calculate the
ratio of the California 0.070 ppm glidepath target benefits to the
California 0.070 ppm full attainment benefits for each incidence and
valuation estimate; (2) multiply this ratio by the California full
attainment 0.075 ppm and 0.065 ppm incidence and valuation estimate to
derive glidepath estimates. Because these results are scaled, it was not
possible to generate confidence intervals. 

While clearly the 2020 glidepath targets for the current and alternative
standards vary among the standard alternatives, the relative air quality
increment between the glidepath base and control cases in California is
nearly identical among the standard alternatives. As such, we believe
this scaling approach is a valid technique to develop screening-level
estimates of 0.065 ppm and 0.075 ppm California glidepath benefits.

6.5.2 PM2.5 co-benefit estimates

As discussed further below, tables 6-9, 6-10, 6-15, 6-17, 6-21 and 6-22
present the PM2.5 co-benefits associated with full attainment of the
0.065 ppm, 0.070 ppm and 0.075 ppm alternatives. To derive estimates of
incidence and valuation for the PM2.5 related co-benefits of full
attainment of each ozone standard alternative, we applied two different
scaling techniques. To estimate total valuation estimates, we applied
benefit per-ton metrics; this procedure is detailed further below. Note
that the valuation estimates of the PM2.5-related full attainment
benefits are presented at a 3% discount rate; due to time and resource
limitations it was not possible to calculate these benefits at a 7%
discount rate. Had we performed this calculation, we estimate that
PM2.5-related full attainment co-benefits would be approximately 15%
lower. All PM2.5 co-benefit estimates are incremental to the 2006 PM
NAAQS RIA.

To estimate total incidence estimates, we applied a simple scaling
factor. To estimate PM2.5-related incidence associated with the
attainment of each ozone alternative, we calculated a separate scaling
factor as follows: (1) we calculated the ratio of the full attainment
PM2.5 valuation estimate (calculated using the benefit per ton metrics
described above) to the partial attainment to the partial attainment
PM2.5 valuation estimate; (2) multiply this scaling ratio against each
of the PM2.5 partial attainment mortality and morbidity endpoints to
generate a scaled estimate of mortality and morbidity. While there are
clearly substantial uncertainties inherent in this technique, it does
produce useful screening-level estimates of PM2.5-related incidence

Table 6-5: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual
Reductions in the Incidence of Premature Mortality Associated with Ozone
Exposure in 2020 (Incremental to Current Ozone Standard)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	National 2020 Benefits

Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	GlidepathE

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	  Bell et al. 2004	130 

(45--220)	480 

(160—790)	0.23 

(0.08--0.37)	43 

(15-72)	

8.5	530

Meta-Analysis	  Bell et al. 2005	540 

(260--820)	1,900 

(930—2,900)	0.86 

(0.42—1.3)	180 

(86—270)	

34

	2,100

	  Levy et al. 2005	780 

(540--1,000)	2,100 

(1,500—2,800)	31 

(22--41)	190 

(130—250)	32

	2,400

	  Ito et al. 2005	590 

(360--820)	2,100 

(1,300—2,900)	1 

(0.6--1.4)	190 

(120—270)	37

	2,300

Assumption that association

is not causal	0	0	0	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

D All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

E This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.



A The negative 5th percentile incidence estimates for this health
endpoint are a result of the weak statistical power of the study and
should not be inferred to indicate that decreased ozone exposure may
cause an increase in asthma-related emergency department visits. 

B All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-6: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual
Reductions in the Incidence of Premature Morbidity Associated with Ozone
Exposure (Incremental to Current Ozone Standard, 95% Confidence
Intervals in Parentheses)

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	National 2020 Benefits

	Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentC

	Hospital Admissions 

(ages 0-1)	960 

(410--1,500)	2,700 

(1,200—4,300)	53 

(23--83)	330 

(150—520)	48

	3,100

Hospital Admissions 

(ages 65-99)	1,100 

(52—2,800)	3,900

 (180—9,800)	3.8 

(0.17--9.4)	320 

(16—790)	57

	4,300

Emergency Department Visits, Asthma-RelatedA	830 

(-230--2,500)	2,500 

(-680—7,700)	21 

(-5.8--66)	130 

(-35—400)	19

	2,600

School Absences	410,000 

(100,000--1,000,000)	1,200,000 

(290,000—3,000,000)	20,000 

(4,900--53,000)	120,000 

(30,000—310,000)	19,000

	1,300,000

Minor Restricted Activity Days	1,100,000 

(460,000--1,800,000)	3,200,000 

(1,300,000—5,000,000)	49,000 

(20,000--78,000)	310,000 

(130,000—490,000)	50,000

	3,500,000

Table 6-7: Illustrative Strategy to Attain 0.065 ppm in California:
Estimated Annual Reductions in the Incidence of Premature Mortality
Associated with Ozone Exposure 

(Incremental to Current Ozone Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	8.5	95	100

Meta-Analysis	  Bell et al. 2005	34	390	420

	  Levy et al. 2005	32	420	450

	  Ito et al. 2005	37	420	450

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across
columnsTable 6-8: Illustrative Strategy to Attain 0.065 ppm in
California: Estimated Annual Reductions in the Incidence of Premature
Morbidity Associated with Ozone Exposure (Incremental to Current Ozone
Standard, 95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	48	830	880

Hospital Admissions 

(ages 65-99)	57	620	670

Emergency Department Visits, Asthma-RelatedA	19	290	310

School Absences	19,000	320,000	340,000

Minor Restricted Activity Days	50,000	780,000	830,000

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

D All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Expert L	3,100	58 	310	370 



Table 6-10: Illustrative 0.065 ppm Full Attainment Scenario: Estimated
Annual Reductions in the Incidence of Premature Morbidity Associated
with PM Co-benefit (95th percentile confidence intervals provided in
parentheses)

	National + 2020 California Glidepath Benefits	California

Glidepath	Incremental Post-2020 Benefits	Total

Morbidity Impact Functions Derived from Epidemiology Literature

	Chronic Bronchitis (age >25 and over)	1,400	26 	140	170

Nonfatal myocardial infarction (age >17)	870 	73	390	460 

Hospital admissions--respiratory (all ages)	31,000 	590 	3,200	3,800 

Hospital admissions-- cardiovascular 

(age >17)	59,000 	1,100 	5,900	7,100 

Emergency room visits for asthma 

(age <19)	1,900 	35	190	220 

Acute bronchitis (age 8-12)	3,700 	69 	370	440 

Lower respiratory symptoms (age 7-14)	30,000 	580 	3,100	3,600 

Upper respiratory symptoms (asthmatic children age 9-18)	22,000 	420 
2,200	2,700 

Asthma exacerbation (asthmatic children age 6--18)	28,000 	520 	2,800
3,300 

Work loss days (age 18-65)	190,000 	3,600 	19,000	23,000 

Minor restricted activity days (age 18-65)	1,100,000 	22,000 	120,000
140,000 

 	 	 	 

A All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.Table 6-11: Illustrative Strategy to Attain
0.070 ppm: Estimated Annual Reductions in the Incidence of Premature
Mortality Associated with Ozone Exposure (Incremental to Current Ozone
Standard)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Attainment

Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentD

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	Bell et al. 2004	130 

(45--220)	260 

(88--440)	0.23 

(0.08--0.37)	11 

(3.8--19)	5.5 

(1.8--9.1)	280

(93—470)

Meta-Analysis	Bell et al. 2005	540 

(260--820)	1,100 

(510—1,600)	0.86 

(0.42--1.3)	47 

(23--71)	22 

(11--34)	1,100

(540—1,700)

	Levy et al. 2005	780 

(540--1,000)	1,300 

(900—1,700)	31 

(22--41)	73 

(50--95)	21 

(14--27)	1,400

(960—1,800)

	Ito et al. 2005	590 

(360--820)	1,200 

(700--1,600)	1 

(0.6--1.4)	50 

(30--70)	24 

(15--34)	1,200

(740—1,700)

Assumption that association is not causal

0	0	0	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

D 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 5-12: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual
Reductions in the Incidence of Premature Morbidity Associated with Ozone
Exposure (Incremental to Current Ozone Standard, 95% Confidence
Intervals in Parentheses)

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	2020 National Benefits

	Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentB

	Hospital Admissions 

(ages 0-1)	960 

(410--1,500)	1,700 

(720--2,600)	53 

(23--83)	130 

(55--200)	33 

(14--51)	1,800

(790—2,900)

Hospital Admissions 

(ages 65-99)	1,100 

(52—2,800)	2,100 

(100--5,400)	3.8 

(0.17--9.4)	86 

(4.2--210)	37 

(1.8--92)	2,300

(110—5,700)

Emergency Department Visits, Asthma-RelatedA	830 

(-230--2,500)	1,500 

(-400--4,300)	21 

(-5.8--66)	50 

(-13--150)	13 

(-3.5--37)	1,500

(-420—4,500)

School Absences	410,000 

(100,000--1,000,000)	720,000 

(170,000--1,800,000)	20,000 

(4,900--53,000)	47,000 

(11,000--120,000)	13,000 

(3,100--33,000)	780,000

(190,000—1,900,000)

Minor Restricted Activity Days	1,100,000 

(460,000--1,800,000)	1,900,000 

(790,000--3,000,000)	49,000 

(20,000--78,000)	120,000 

(49,000--190,000)	34,000 

(14,000--53,000)	2,100,000

(850,000—3,300,000)

A The negative 5th percentile incidence estimates for this health
endpoint are a result of the weak statistical power of the study and
should not be inferred to indicate that decreased ozone exposure may
cause an increase in asthma-related emergency department visits. 

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across
columns.

Table 6-13: Illustrative Strategy to Attain 0.070 ppm in California:
Estimated Annual Reductions in the Incidence of Premature Mortality
Associated with Ozone Exposure (Incremental to Current Ozone Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	5.5 

(1.8--9.1)	56	62

Meta-Analysis	  Bell et al. 2005	22 

(11--34)	230	250

	  Levy et al. 2005	21 

(14--27)	250	280

	  Ito et al. 2005	24 

(15--34)	250	270

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-14: Illustrative Strategy to Attain 0.070 ppm in California:
Estimated Annual Reductions in the Incidence of Premature Morbidity
Associated with Ozone Exposure (Incremental to Current Ozone Standard,
95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	33 

(14--51)	520	560

Hospital Admissions 

(ages 65-99)	37 

(1.8--92)	370	400

Emergency Department Visits, Asthma-RelatedA	13 

(-3.5--37)	180	190

School Absences	13,000 

(3,100--33,000)	200,000	210,000

Minor Restricted Activity Days	34,000 

(14,000--53,000)	480,000	520,000

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

Table 6-16: Illustrative 0.075 ppm Full Attainment Scenario: Estimated
Annual Reductions in the Incidence of Morbidity Associated with PM
Co-benefit (95th percentile confidence intervals provided in
parentheses)

	National + 2020 California Glidepath Benefits	California

Glidepath	Incremental Post-2020 Benefits	Total

Morbidity Impact Functions Derived from Epidemiology Literature

	Chronic Bronchitis (age >25 and over)	740	10	100	110

Nonfatal myocardial infarction (age >17)	2,100	29	290	320

Hospital admissions--respiratory (all ages)	17,000	240	2,300	2,600

Hospital admissions-- cardiovascular 

(age >17)	31,000	450	4,400	4,800

Emergency room visits for asthma 

(age <19)	990	14	140	150

Acute bronchitis (age 8-12)	1,900	28	270	300

Lower respiratory symptoms (age 7-14)	16,000	230	2,300	2,500

Upper respiratory symptoms (asthmatic children age 9-18)	12,000	168
1,700	1,800

Asthma exacerbation (asthmatic children age 6--18)	15,000	210	2,100
2,300

Work loss days (age 18-65)	100,000	1,500	14,000	16,000

Minor restricted activity days (age 18-65)	610,000	8,600	85,000	93,000

 	 	 	 

A All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.Table 6-17: Illustrative Strategy to Attain
0.075 ppm: Estimated Annual Reductions in the Incidence of Premature 

Mortality Ozone Exposures (Incremental to Current Ozone Standard)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Benefits

Glidepath AttainmentE

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	  Bell et al. 2004	190	8.9	0	200

Meta-Analysis	  Bell et al. 2005	840	40	0	880

	  Levy et al. 2005	1,100	65	0	1,100

	  Ito et al. 2005	920	43	0	960

Assumption that association

is not causal	0	0	0

0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals not provided due to the fact
that the incidence estimates were derived through an interpolation
technique (see Appendix 6) that precluded us from generating such
estimates.   

D All estimates rounded to two significant figures. As such, totals will
not sum across columns

E This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

A Confidence intervals not provided due to the fact that the incidence
estimates were derived through an interpolation technique (see Appendix
6) that precluded us from generating such estimates.

Table 6-18: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual
Reductions in the Incidence of Premature Morbidity Associated with Ozone
Exposure (Incremental to Current Ozone Standard)A

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	2020 National Benefits

	Glidepath AttainmentC

	Hospital Admissions (ages 0-1)	1,300	110	0	1,400

Hospital Admissions (ages 65-99)	1,700	76	0	1,800

Emergency Department Visits, Asthma-Related	1,200	44	0	1,200

School Absences	570,000	42,000	0	610,000

Minor Restricted Activity Days	1,500,000	110,000	0	1,600,000

B All estimates rounded to two significant figures. As such, totals will
not sum across columns

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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-19: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Reductions in the Incidence of Premature Mortality
Associated with Ozone Exposure (Incremental to Current Ozone Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	0	35	35

Meta-Analysis	  Bell et al. 2005	0	140	140

	  Levy et al. 2005	0	150	150

	  Ito et al. 2005	0	160	160

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-20: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Reductions in the Incidence of Premature Morbidity
Associated with Ozone Exposure (Incremental to Current Ozone Standard,
95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	0	320	320

Hospital Admissions 

(ages 65-99)	0	230	230

Emergency Department Visits, Asthma-RelatedA	0	110	110

School Absences	0	120,000	120,000

Minor Restricted Activity Days	0	290,000	290,000

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

D All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-22: Illustrative 0.075 ppm Full Attainment Scenario: Estimated
Annual Reductions in the Incidence of Premature Morbidity Associated
with PM Co-benefit (95th percentile confidence intervals provided in
parentheses)

	National + 2020 California Glidepath Benefits	California

Glidepath	Incremental Post-2020 Benefits	Total

Morbidity Impact Functions Derived from Epidemiology Literature

	Chronic Bronchitis (age >25 and over)	380	0	28	28

Nonfatal myocardial infarction (age >17)	1,100	0	80	80

Hospital admissions--respiratory (all ages)	8,600	0	640	640

Hospital admissions-- cardiovascular 

(age >17)	16,000	0	1,200	1,200

Emergency room visits for asthma 

(age <19)	510	0	38	38

Acute bronchitis (age 8-12)	1,000	0	75	75

Lower respiratory symptoms (age 7-14)	8,300	0	630	630

Upper respiratory symptoms (asthmatic children age 9-18)	6,100	0	460	460

Asthma exacerbation (asthmatic children age 6--18)	7,600	0	570	570

Work loss days (age 18-65)	53,000

	0	4,000

	4,000

Minor restricted activity days (age 18-65)	310,000	0	23,000	23,000

 	 	 	 

A All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.Table 6-23: Illustrative Strategy to Attain
0.065 ppm: Estimated Annual Valuation of Reductions in the Incidence of
Premature Mortality Associated with Ozone Exposure (Incremental to
Current Ozone Standard, Millions of 1999$)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Benefits

Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentE

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	  Bell et al. 2004	$850

($120—$1,900)	$3,100 

($430--$6,800)	$1.4

($0.2--$3.2)	$280 

($39--$620)	$54	$3,400

Meta-Analysis	  Bell et al. 2005	$3,500

($550--$7,500)	$12,000 

($2,000--$26,000)	$5.5

($0.9--$12)	$1,100 

($180--$2,400)	$220	$14,000

	  Levy et al. 2005	$5,000

($890--$9,600)	$14,000 

($2,400--$26,000)	$200

($36--$390)	$1,200 

($220--$2,400)	$200	$15,000

	  Ito et al. 2005	$3,800

($650--$7,500)	$13,000 

($2,300--$27,000)	$6.3

($1.1--$13)	$1,200

 ($210--$2,400)	$240	$15,000

Assumption that association

is not causal	0	0	0	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

D All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

E This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-24: Illustrative Strategy to Attain 0.065 ppm: Estimated Annual
Reductions in the Incidence of Premature Morbidity Associated with Ozone
Exposure (Incremental to Current Ozone Standard, 95% Confidence
Intervals in Parentheses, 

Millions of 1999$)

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	2020 National Benefits

	Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentB

	Hospital Admissions 

(ages 0-1)	$7.1

($3.1--$11)	$20 

($8.8--$32)	$0.39

($0.17--$0.62)	$2.5 

($1.1--$3.9)	$0.4	$23

Hospital Admissions 

(ages 65-99)	$19

($0.9--$49)	$68 

($3.2--$170)	$0.67

($0.003—

$0. 2)	$5.6 

($0.28--$14)	$1	$75

Emergency Department Visits, Asthma-Related	$0.23

($-0.06--$0.67)	$0.7 

($-0.2--$2)	--	$0.04 

($-0.009--$0.1)	--	$0.7

School Absences	$30

($7.2-$72)	$87 

($21--$210)	$1.5

($0.35--$3.8)	$8.9 

($2.1--$22)	$1.4	$97

Worker Productivity	$15	$38	$0.38	$3.9	$2.9	$45

Minor Restricted Activity Days	$27

($1.2--$63)	$79 

($3.4--$180)	$1.2

($0.05--$2.8)	$7.6 

($0.3--$18)	$1.3	$87

A All estimates rounded to two significant figures. As such, totals will
not sum across columns

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-25: Illustrative Strategy to Attain 0.065 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Mortality Associated with Ozone Exposure (Incremental to Current Ozone
Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	$54	$610	$660

Meta-Analysis	  Bell et al. 2005	$220	$2,500	$2,700

	  Levy et al. 2005	$200	$2,600	$2,900

	  Ito et al. 2005	$240	$2,700	$2,900

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, totals will
not sum across columns

Table 6-26: Illustrative Strategy to Attain 0.065 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Morbidity Associated with Ozone Exposure (Incremental to Current Ozone
Standard, 95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	$0.4	$6.2	$6.6

Hospital Admissions 

(ages 65-99)	$1	$11	$12

Emergency Department Visits, Asthma-RelatedA	--	$0.8	$0.9

School Absences	$1.4	$23	$25

Worker Productivity	$2.9	$26	$29

Minor Restricted Activity Days	$1.3	$19	$21

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

D All estimates rounded to two significant figures. As such, totals will
not sum across columns



Table 6-27: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual
Valuation of Reductions in the Incidence of Premature Mortality
Associated with Ozone Exposure (Incremental to Current Ozone Standard,
Millions of 1999$)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Benefits

Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentD

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	Bell et al. 2004	$850

($120—$1,900)	$1,700

($240--$3,800)	$1.4

($0.2--$3.2)	$73

($10--$160)	$35

($5--$78)	$1,800

($250--$4,000)

Meta-Analysis	Bell et al. 2005	$3,500

($550--$7,500)	$6,800

($1,100--$14,000)	$5.5

($0.9--$12)	$300

($48--$630)	$140

($23--$300)	$7,200

($1,200--$15,000)

	Levy et al. 2005	$5,000

($890--$9,600)	$8,300

($1,500--$16,000)	$200

($36--$390)	$470

($83--$900)	$130

($24--$260)	$8,900

($1,600--$17,000)

	Ito et al. 2005	$3,800

($1,300--$9,300)	$7,400

($1,300--$15,000)	$6.3

($1.1--$13)	$320

($56--$640)	$150

($27--$310)	$7,900

($1,400--$16,000)

Assumption that association is not causal

0	0	0	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

D 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-28: Illustrative Strategy to Attain 0.070 ppm: Estimated Annual
Valuation of Reductions in the Incidence of Premature Morbidity
Associated with Ozone Exposure (Incremental to Current Ozone Standard,
95% Confidence Intervals in Parentheses, Millions of 1999$)

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	2020 National Benefits

	Modeled Partial Attainment	Full Attainment	Modeled Partial Attainment
Full Attainment	Glidepath AttainmentA

	Hospital Admissions 

(ages 0-1)	$7.1

($3.1--$11)	$12

($5.3--$19)	$0.39

($0.17--$0.62)	$1

($0.41--$1.5)	$0.24

($0.11--$0.38)	$14

($5.9--$21)

Hospital Admissions 

(ages 65-99)	$19

($0.9--$49)	$38

($1.8--$95)	$0.67

($0.003—

$0. 2)	$1.5

($0.074--$3.8)	$0.65

($0.32--$1.6)	$40

($1.9--$100)

Emergency Department Visits, Asthma-Related	$0.23

($-0.06--$0.67)	$0.4

($-0.1--$1.2)	--	--	--	$0.5

(-$0.1--$1.2)

School Absences	$30

($7.2-$72)	$52

($13--$130)	$1.5

($0.35--$3.8)	$3.4

($0.8--$8.4)	$0.93

($0.2--$2.4)	$56

($14--$140)

Worker Productivity	$15	$22	$0.38	$1.4	$1.9	$26

Minor Restricted Activity Days	$27

($1.2--$63)	$47

($2--$110)	$1.2

($0.05--$2.8)	$2.9

($0.13--$6.8)	$0.83

($0.036--$1.9)	$51

($2.2--$120)

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-29: Illustrative Strategy to Attain 0.070 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Mortality Associated with Ozone Exposure (Incremental to Current Ozone
Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	$35

($5--$78)	$360	$390

Meta-Analysis	  Bell et al. 2005	$140

($23--$300)	$1,500	$1,600

	  Levy et al. 2005	$130

($24--$260)	$1,600	$1,800

	  Ito et al. 2005	$150

($27--$310)	$1,600	$1,700

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-30: Illustrative Strategy to Attain 0.070 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Morbidity Associated with Ozone Exposure (Incremental to Current Ozone
Standard, 95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	$0.24

($0.11--$0.38)	$3.9	$4.2

Hospital Admissions 

(ages 65-99)	$0.65

($0.32--$1.6)	$6.5	$7.2

Emergency Department Visits, Asthma-RelatedA	--	$0.05	$0.05

School Absences	$0.93

($0.2--$2.4)	$15	$15

Worker Productivity	$1.9	$16	$17

Minor Restricted Activity Days	$0.83

($0.036--$1.9)	$12	$13

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

D All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns

Table 6-31: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual
Monetary Value of Reductions in the Incidence of Premature Morbidity
Associated with Exposure to Ozone (Millions of 1999$, Incremental to
Current Standard)A

Morbidity Endpoint	Eastern U.S.	Western U.S. Excluding California
California	2020 National Benefits

	Glidepath AttainmentC

	Hospital Admissions (ages 0-1)	$9.9	$0.9	0	$11

Hospital Admissions (ages 65-99)	$31	$1.4	0	$32

Emergency Department Visits, Asthma-Related	$0.3	$0.013	0	$0.3

School Absences	$41	$3	0	$44

Worker Productivity	$20	$1.3	0	$21

Minor Restricted Activity Days	$38	$2.6	0	$40

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number    of lives saved are based on an assumption of a
normal distribution. Confidence intervals not provided due to the fact
that the incidence estimates were derived through an interpolation
technique that precluded us from generating such estimates.

C 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 not provided due to the fact
that the incidence estimates were derived through an interpolation
technique (see Appendix 6) that precluded us from generating such
estimates.   

D All estimates rounded to two significant figures. As such, totals will
not sum across columns

E This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

A Confidence intervals not provided due to the fact that the incidence
estimates were derived through an interpolation technique (see Appendix
6) that 

Table 6-32: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual
Monetary Value of Reductions in the Incidence of Mortality  Associated
with Exposure to Ozone (Millions of 1999$, Incremental to Current
Standard)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Benefits

Glidepath AttainmentE

	Arithmetic MeanB 

(95% Credible Intervals)C

NMMAPS	  Bell et al. 2004	$1,400	$66	0	$1,400

Meta-Analysis	  Bell et al. 2005	$5,400	$270	0	$5,700

	  Levy et al. 2005	$6,700	$430	0	$7,100

	  Ito et al. 2005	$5,900	$290	0	$6,200

Assumption that association

is not causal	0	0	0	0

precluded us from generating such estimates.   

B All estimates rounded to two significant figures. As such, totals will
not sum across columns

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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-33: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Mortality Associated with Ozone Exposure (Incremental to Current Ozone
Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	0	$220	$220

Meta-Analysis	  Bell et al. 2005	0	$910	$910

	  Levy et al. 2005	0	$990	$990

	  Ito et al. 2005	0	$990	$990

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment. 

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, totals will
not sum across columns

Table 6-34: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Morbidity Associated with Ozone Exposure (Incremental to Current Ozone
Standard, 95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions 

(ages 0-1)	0	$2.4	$2.4

Hospital Admissions 

(ages 65-99)	0	$4	$4

Emergency Department Visits, Asthma-RelatedA	0	$0.03	$0.03

School Absences	0	$8.7	$8.7

Worker Productivity	0	$9	$9

Minor Restricted Activity Days	0	$7.3	$7.3

A 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 reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described below.

D All estimates rounded to two significant figures. As such, totals will
not sum across columns

Estimated reductions in ozone mortality incidence provided in Tables
6-5, 6-7, 6-11, 6-13, 6-17 and 6-19 represent the number of premature
deaths potentially avoided due to reductions in ozone exposure in 2020
using warm season functions from the recent ozone-mortality NMMAPS
analysis of 95 U.S. communities (Bell et al., 2004) and three
meta-analyses of the available published literature on ozone-mortality
effects (Bell et al., 2005; Ito et al., 2005; Levy et al., 2005).  These
same tables also include the possibility that there is not a causal
association between ozone and mortality, i.e., that the estimate for
premature mortality avoided could be zero. As noted above, for each
standard alternative we break out estimates between 2020 national
glidepath and California post-2020. Model uncertainty, including whether
or not the relationship is assumed to be causal, is a key source of
uncertainty.  Although multiple estimates are presented in these tables,
no attempt was made to quantify the likelihood of a causal relationship
between short-term ozone exposure and increased mortality or to weigh
the results of the various models.  

The estimate of central tendency for premature mortality is expressed as
the arithmetic mean, with the assumption of a normal distribution, and
represents the central estimate of the number of premature deaths
avoided in association with the proposed standard based on each study. 
Statistical uncertainty associated with the model estimate for each
study is characterized by the 95% credible interval around the mean
estimate (i.e., 2.5th and 97.5th percent interval).  Of the four
available studies, the NMMAPS study by Bell et al. (2004) is considered
to be the most representative for evaluating potential mortality-related
benefits associated with the proposed standard due to its extensive
coverage (examination of 95 large communities across the United States
over an extended period of time, from 1987 to 2000) and its specific
focus on the ozone-mortality relationship.  Annual estimates of lives
saved from this study are lower than those from the three meta-analyses,
possibly due to more stringent adjustment for meteorological factors
(Ito et al., 2005; Ostro et al., 2006), publication bias in the
meta-analyses (Bell et al., 2005; Ito et al., 2005) or other factors. 
Clearly, the ozone-mortality reduction estimates are conditional on a
causal relationship.  

The Ozone Criteria Document (U.S. EPA, 2006) and Staff Paper (U.S. EPA,
2007) concluded that the overall body of evidence is highly suggestive
that (short-term exposure to) ozone directly or indirectly contributes
to non-accidental cardiopulmonary-related mortality.  However, various
sources of uncertainty remain, including the possibility that there is
no causal relationship between ozone and mortality (i.e., zero effect). 
For instance, because results of time-series studies implicate all of
the criteria air pollutants, and those who would be expected to be
potentially more susceptible to ozone exposure are likely to have lower
exposure to ozone due to the amount of time that they spend indoors,
CASAC stated that it seems unlikely that the observed associations
between short-term ozone concentrations and daily mortality are due
solely to ozone itself (i.e., ozone may be serving as a marker for other
agents that are contributing to the short-term exposure effects on
mortality).  Even so, CASAC concluded that the evidence was strong
enough to support a quantitative risk assessment of the relationship
between short-term exposure to ozone and premature mortality as part of
the Staff Paper.  EPA has asked the National Academy of Sciences for
their advice on how best to quantify the uncertainty about the
relationship between ambient ozone exposure and premature mortality
within the context of quantifying projected benefits of alternative
control strategies.

Using the NMMAPS study that was used as the basis for the risk analysis
presented in our Staff Paper, we estimate 280 avoided premature deaths
annually in 2020 from reducing ozone levels to meet a proposed standard
of 0.070 ppm, which, when added to the other projected ozone related
benefits, leads to an estimated total benefit of $1.8 billion/yr. Using
three studies that synthesize data across a large number of individual
studies, we estimate between 1,100 and 1,400 avoided premature deaths
annually in 2020, leading to total monetized benefits of between $7.2
and $8.9 billion/yr. Alternatively, if there is no causal relationship
between ozone and mortality, avoided premature deaths would be zero. 
For a proposed standard of 0.075 ppm, using the NMMAPS ozone mortality
study, we estimate 200 premature deaths avoided and total monetized
benefits of $1.4 billion/yr.  Using the three synthesis studies, we
estimate premature deaths avoided for the less stringent standard to be
between 880 and 1,100, with total monetized ozone benefits to be between
$5.7 and $7.1 billion/yr.  Because EPA is taking comment on alternatives
as low as 0.065 ppm, we show that a more stringent standard of 0.065
ppm, using the NMMAPS ozone mortality study is estimated to result in
530 premature deaths avoided and total monetized benefits of $3.4
billion/yr.  Using the three synthesis studies, estimated premature
deaths avoided for the more stringent standard are between 2,100 and
2,400, with total monetized ozone benefits between $14 and $15
billion/yr.  Including premature mortality in our estimates had the
largest impact on the overall magnitude of benefits:  Premature
mortality benefits account for more than 95 percent of the total
benefits we can monetize.  We note that these estimates reflect EPA's
interim approach to characterizing the benefits of reducing premature
mortality associated with ozone exposure.   EPA has requested advice
from the NAS on how best to quantify uncertainty in the relationship
between ozone exposure and premature mortality in the context of
quantifying benefits associated with alternative ozone control
strategies.

6.5.3 PM2.5 Co-Benefits Resulting from Attainment of 0.070 ppm
incremental to 0.08 ppm

The summary of PM2.5 related co-benefits in the tables above represent
the benefits of partially attaining 0.070 ppm incremental to a partial
attainment of 0.08 ppm. Thus, these estimates overstate the benefits of
0.070 ppm partial attainment relative to the actual incremental benefits
of this scenario; this is due to the fact that the benefits estimates in
these tables include the benefits of NOx reductions that would be
required to attain a baseline of 0.08 ppm. Of greater analytical value
would be an estimate of the PM2.5 co-benefits associated with fully
attaining 0.070 ppm incremental to full attainment of the 0.08 ppm
standard.  

To generate such an estimate, we calculated a new PM2.5 baseline that
established the PM2.5 air quality associated with full attainment of
0.08 ppm. To create such a baseline, EPA utilized benefit PM2.5 per-ton
estimates. These PM2.5 benefit per-ton estimates provide the total
monetized human health benefits (the sum of premature mortality and
premature morbidity) of reducing one ton of PM2.5 from a specified
source. EPA has used a similar technique in previous Regulatory Impact
Analyses. These estimates are based on the sum of the valuation of the
Pope (2002) estimates of mortality (3% discount rate, 1999$) and
valuation of the morbidity incidence. Readers interested in reviewing
the complete methodology for creating the benefit per-ton estimates used
in this analysis can consult the Technical Support Document accompanying
this RIA.

Estimating the PM2.5 benefits that represented the full attainment of
both 0.070 ppm incremental to full attainment of 0.08 ppm entailed the
following four steps:

Estimate the number of tons of NOx necessary to attain a baseline of
0.08 ppm. Chapter 3 described the method used to estimate the
extrapolated NOx emissions reductions necessary to attain a baseline of
0.08 ppm full attainment. 

Calculate the benefits of attaining 0.08 ppm. To estimate the benefits
of fully attaining 0.080 ppm incremental to partial attainment of 0.080
ppm, the relevant benefit per ton is simply multiplied by the total
number of extrapolated NOx tons abated. 

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 attainment of 0.080 ppm to create a
new estimate of incremental 0.070 ppm partial attainment.

Calculate the PM2.5 benefits of fully attaining 0.070 ppm. Multiplying
the estimate of the extrapolated NOx tons necessary to attain 0.070 ppm
fully (found in chapter 3) produces an estimate of the incremental
benefits of fully attaining 0.070 ppm incremental to partial attainment
of 0.070 ppm. By adding this incremental benefit estimate to the
benefits generated in step 3, we derived a total benefit estimate of
attaining 0.070 ppm incremental to 0.08 ppm.

The process for estimating the PM2.5 co-benefits of fully attaining
0.065 ppm and 0.075 ppm is identical to the steps above, with the
following exception; in step four we substituted the number of
extrapolated tons necessary to attain 0.065 ppm and 0.075 ppm,
respectively.  Table 5-21 below provides the inputs to the calculation
steps described above. In the example below we calculate total benefits
using the Pope et al. (2002) mortality estimate. However, in subsequent
tables we present benefits using Laden et al. (2006) as well as the
twelve expert functions described previously in this document. Note that
while our benefit per ton estimates are associated with broad source
categories (in this case, NOx Electrical Generating Units, Other NOx
point sources and Mobile NOx sources) the extrapolated tons were not.
For this reason we simply assumed that the total number of extrapolated
NOx tons were evenly distributed between these three source types.

Table 6-35: Estimated PM2.5 Co-Benefits Associated with Full Attainment
of 0.070 ppm incremental to 0.08 ppma

Calculation	Extrapolated NOx Tons	Benefit per ton estimate	Valuation of
PM2.5 Benefits

(Billions 1999$)

	Benefits of attaining 0.08 ppm partially and 0.070 ppm partially:b	---
---	$3.2B

	Benefits of attaining 0.08 ppm from a baseline of 0.08 ppm partial
attainment:	NOx EGU: 151,000	$3,400	$1.7B

	NOx Point: 151,000	$3,100

NOx Mobile: 151,000	$5,000

Benefits of attaining 0.070 ppm partially, incremental to attainment of
0.08 ppm	---	---	            = $3.2B - $1.7B

                                      =$1.5 B

	Benefits of attaining 0.070 ppm incremental to partial attainment of
0.070 ppm	NOx EGU: 420,000	$3,400	$4.8B

	NOx Point: 420,000	$3,100

NOx Mobile: 420,000	$5,000

Benefits of attaining 0.070 ppm incremetnal to attainment of 0.08 ppm

	           =$1.5B + 4.8B

                                      =$6.3B

	a Numbers have been rounded to two significant figures and therefore
summation may not match table estimates. PM2.5 benefit estimates do not
include confidence intervals because they are derived using benefit
per-ton estimates.

b From table 5-16 above

The procedure for calculating the PM2.5 benefits resulting from full
attainment of 0.075 ppm and 0.065 ppm is identical to this example, with
the exception of step 4; the PM2.5 benefits of attaining 0.065 ppm and
0.075 ppm incremental to partial attainment of 0.070 ppm are $9.7B and
$1.4B respectively. Thus, the total PM2.5 benefits of attaining 0.065
ppm and 0.075 ppm are $11B and $3B, respectively. The full attainment
PM2.5 benefits do not include confidence intervals. Because this full
attainment estimate was derived by summing the modeled PM2.5 benefits
and the benefits derived using the benefit per-ton metrics—and these
benefit per ton metrics do not include confidence intervals—the
resulting sum of total PM2.5 benefits do not include confidence
intervals.

6.5.4 Estimate of Full Attainment Benefits 

Tables 6-36 through 6-41 below summarize the estimates of full
attainment and 2020 California glidepath attainment ozone benefits and
PM2.5 co-benefit estimate for each standard alternative. The
presentation of ozone benefits and PM2.5 co-benefits for each standard
alternative is broken into two tables. The first table presents the
national glidepath ozone benefits and PM2.5 co-benefits. The second
table presents California-only glidepath and post-2020 ozone benefits
and PM2.5 co-benefits. Tables 6-42 through 6-51 summarize the combined
ozone and PM2.5 co-benefits. The presentation of combined ozone and
PM2.5 co-benefit tables is broken into four components for each standard
alternative. The first table presents national glidepath benefits. The
second table presents the California-only glidepath benefits. The third
table presents the incremental benefits that accrue in California from
full attainment of the alternative standard after 2020. The last table
presents total California benefits—the sum of glidepath benefits and
post-2020 benefits.Table 6-36: Estimate of Total Annual Ozone and PM2.5
Benefits (95% Confidence Intervals, Millions of $1999) for the 0.065 ppm
Standard Alternative: National Glidepath Attainment 

Ozone Mortality and Morbidity Benefits of Attaining 0.065 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

NMMAPS 	Bell (2004)	$3,700

Meta-Analysis	Bell (2005)	$14,000

	Ito (2005)	$15,000

	Levy (2005)	$16,000

No Causality	$330

PM2.5 Mortality and Morbidity Benefits of Attaining 0.065 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyC	$10,000

Harvard Six-City StudyD	$22,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$33,000

Expert B	$25,000

Expert C	$25,000

Expert D	$17,000

Expert E	$41,000

Expert F	$23,000

Expert G	$14,000

Expert H	$18,000

Expert I	$24,000

Expert J	$20,000

Expert K	$3,900

Expert L	$18,000

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 

Table 6-37: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Standard
Alternative: California Attainment 

Ozone Mortality and Morbidity Benefits of Attaining 0.065 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	$61	 $690 	$750

Meta-Analysis	Bell (2005)	$230	 $2,600 	$2,800

	Ito (2005)	$210	 $2,800 	$3,000

	Levy (2005)	$240	 $2,700 	$3,000

No Causality	$6.8	$93	$100 

PM2.5 Mortality and Morbidity Benefits of Attaining 0.065 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	$190	$1,000	$1,200

Harvard Six-City StudyD	$410	$2,200	$2,600

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$620	$3,300	$3,900

Expert B	$470	$2,500	$3,000

Expert C	$470	$2,500	$3,000

Expert D	$330	$1,700	$2,100

Expert E	$770	$4,100	$4,900

Expert F	$430	$2,300	$2,700

Expert G	$270	$1,500	$1,700

Expert H	$350	$1,800	$2,200

Expert I	$460	$2,500	$2,900

Expert J	$370	$2,000	$2,400

Expert K	$75	$400	$470

Expert L	$340	$1,800	$2,100

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 

Table 6-38: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Standard
Alternative: National Glidepath Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.070 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

(95% Credible Intervals)C

NMMAPS	Bell (2004)	$2,000

($300--$4,400)

Meta-Analysis	Bell (2005)	$7,400

($1,200--$16,000)

	Ito (2005)	$8,000

($1,400--$16,000)

	Levy (2005)	$9,100

($1,600--$18,000)

No Causality	$190

($49--$400)

PM2.5 Mortality and Morbidity Benefits of Attaining 0.070 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyD	$5,400

Harvard Six-City StudyE	$12,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$17,000

Expert B	$13,000

Expert C	$13,000

Expert D	$9,200

Expert E	$22,000

Expert F	$12,000

Expert G	$7,700

Expert H	$9,800

Expert I	$13,000

Expert J	$11,000

Expert K	$2,100

Expert L	$9,500

 A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number  of lives saved are based on an assumption of a normal
distribution. Confidence intervals not available for PM2.5 valuation
estimates due to the fact that they were derived through a scaling
technique (see above) that precluded us from generating such estimates.

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 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

E 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. 

F All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 

Table 6-39: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Standard
Alternative: California Attainment 

Ozone Mortality and Morbidity Benefits of Attaining 0.070 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	$40

($7.2--$86)	$410	$450

Meta-Analysis	Bell (2005)	$150

($25--$310)	$1,500	$1,700

	Ito (2005)	$160

($29--$320)	$1,600	$1,800

	Levy (2005)	$140

($26--$270)	$1,700	$1,800

No Causality	$4.5

($2.3--$8.2)	$57	$61

PM2.5 Mortality and Morbidity Benefits of Attaining 0.070 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	$77	$750	$830

Harvard Six-City StudyD	$160	$1,600	$1,800

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$250	$2,400	$2,700

Expert B	$190	$1,900	$2,000

Expert C	$190	$1,800	$2,000

Expert D	$130	$1,300	$1,400

Expert E	$310	$3,000	$3,300

Expert F	$170	$1,700	$1,800

Expert G	$110	$1,100	$1,200

Expert H	$140	$1,400	$1,500

Expert I	$190	$1,800	$2,000

Expert J	$150	$1,500	$1,600

Expert K	$30	$290	$320

Expert L	$140	$1,300	$1,500

 A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 



Table 6-40: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Standard
Alternative: National Glidepath Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.075 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

NMMAPS	Bell (2004)	$1,600

Meta-Analysis	Bell (2005)	$5,900

	Ito (2005)	$6,400

	Levy (2005)	$7,300

No Causality	$150

PM2.5 Mortality and Morbidity Benefits of Attaining 0.075 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyC	$2,800

Harvard Six-City StudyD	$6,300

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$9,000

Expert B	$6,900

Expert C	$6,800

Expert D	$4,700

Expert E	$11,000

Expert F	$6,200

Expert G	$4,000

Expert H	$5,000

Expert I	$6,700

Expert J	$5,400

Expert K	$1,100

Expert L	$4,900

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean estimates of the annual number of lives saved are based
on an assumption of a normal distribution. Credible intervals for ozone
estimates and confidence intervals for PM2.5 estimates not provided due
to the fact that the valuation estimates were derived through a scaling
technique (see above) that precluded us from generating such estimates..

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

F All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 

Table 6-41: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Standard
Alternative: California Attainment 

Ozone Mortality and Morbidity Benefits of Attaining 0.075 ppm 

Standard Alternative and 

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	0	$260	$260

Meta-Analysis	Bell (2005)	0	$940	$940

	Ito (2005)	0	$1,000	$1,000

	Levy (2005)	0	$1,000	$1,000

No Causality	0	$33	$33

PM2.5 Mortality and Morbidity Benefits of Attaining 0.075 ppm 

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	0	$210	$210

Harvard Six-City StudyD	0	$450	$450

Mortality Impact Functions Derived from Expert Elicitation

Expert A	0	$670	$670

Expert B	0	$510	$510

Expert C	0	$510	$510

Expert D	0	$350	$350

Expert E	0	$840	$840

Expert F	0	$460	$460

Expert G	0	$300	$300

Expert H	0	$380	$380

Expert I	0	$500	$500

Expert J	0	$410	$410

Expert K	0	$81	$81

Expert L	0	$370	$370

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower. 

Table 6-42: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$14,000	$24,000	$25,000	$26,000	$10,000

Harvard Six-City StudyC	$26,000	$36,000	$37,000	$38,000	$22,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$36,000	$47,000	$48,000	$48,000	$33,000

Expert B	$29,000	$39,000	$40,000	$40,000	$25,000

Expert C	$28,000	$39,000	$40,000	$40,000	$25,000

Expert D	$21,000	$31,000	$32,000	$33,000	$18,000

Expert E	$45,000	$55,000	$56,000	$56,000	$41,000

Expert F	$26,000	$36,000	$38,000	$38,000	$23,000

Expert G	$18,000	$28,000	$30,000	$30,000	$15,000

Expert H	$22,000	$32,000	$34,000	$34,000	$19,000

Expert I	$28,000	$38,000	$40,000	$40,000	$25,000

Expert J	$23,000	$34,000	$35,000	$35,000	$20,000

Expert K	$7,700	$18,000	$19,000	$19,000	$4,300

Expert L	$22,000	$33,000	$30,000	$33,000	$18,000

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-43: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: California Glidepath Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$250	$420	$400	$430	$200

Harvard Six-City StudyC	$470	$640	$620	$650	$420

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$680	$850	$830	$860	$630

Expert B	$530	$700	$690	$710	$480

Expert C	$530	$690	$680	$710	$470

Expert D	$390	$550	$540	$570	$330

Expert E	$830	$1,000	$980	$1,000	$780

Expert F	$490	$650	$640	$670	$430

Expert G	$330	$500	$490	$510	$280

Expert H	$410	$570	$560	$590	$350

Expert I	$520	$690	$670	$700	$470

Expert J	$430	$600	$590	$610	$3800

Expert K	$140	$300	$290	$320	$82

Expert L	$400	$570	$550	$580	$350

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-44: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: Incremental Benefits of California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,700	$3,500	$3,700	$3,700	$1,100

Harvard Six-City StudyC	$2,800	$4,700	$4,900	$4,900	$2,300

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$3,900	$5,800	$6,000	$6,000	$3,400

Expert B	$3,200	$5,000	$5,200	$5,200	$2,600

Expert C	$3,100	$5,000	$5,200	$5,200	$2,600

Expert D	$2,400	$4,200	$4,500	$4,400	$1,800

Expert E	$4,800	$6,600	$6,800	$6,800	$4,200

Expert F	$2,900	$4,800	$5,000	$4,900	$2,400

Expert G	$2,100	$3,900	$4,200	$4,100	$1,500

Expert H	$2,500	$4,300	$4,600	$4,500	$1,900

Expert I	$3,100	$4,900	$5,200	$5,100	$2,500

Expert J	$2,600	$4,500	$4,700	$4,700	$2,100

Expert K	$1,000	$2,900	$3,100	$3,100	$480

Expert L	$2,400	$4,300	$4,500	$4,500	$1,900

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-45: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: Total California Benefits of Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,900	$3,900	$4,100	$4,100	$1,300

Harvard Six-City StudyC	$3,300	$5,300	$5,500	$5,500	$2,700

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$4,600	$6,600	$6,800	$6,800	$4,000

Expert B	$3,7000	$5,700	$5,900	$5,900	$3,100

Expert C	$3,600	$5,700	$5,900	$5,900	$3,100

Expert D	$2,800	$4,800	$5,000	$5,000	$2,200

Expert E	$5,600	$7,600	$7,800	$7,800	$5,000

Expert F	$3,400	$5,400	$5,600	$5,600	$2,800

Expert G	$2,400	$4,400	$4,700	$4,600	$1,800

Expert H	$2,900	$4,900	$5,100	$5,100	$2,300

Expert I	$3,600	$5,600	$5,800	$5,800	$3,000

Expert J	$3,100	$5,100	$5,300	$5,300	$2,500

Expert K	$1,200	$3,200	$3,400	$3,400	$570

Expert L	$2,800	$4,900	$5,100	$5,100	$2,200

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-46: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$7,400	$13,000	$13,000	$14,000	$5,600

Harvard Six-City StudyC	$14,000	$19,000	$20,000	$21,000	$12,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$19,000	$25,000	$25,000	$27,000	$18,000

Expert B	$15,000	$21,000	$21,000	$22,000	$14,000

Expert C	$15,000	$21,000	$21,000	$22,000	$13,000

Expert D	$11,000	$17,000	$17,000	$18,000	$9,300

Expert E	$24,000	$29,000	$30,000	$31,000	$22,000

Expert F	$14,000	$19,000	$20,000	$21,000	$12,000

Expert G	$9,700	$15,000	$16,000	$17,000	$7,900

Expert H	$12,000	$17,000	$18,000	$19,000	$9,900

Expert I	$15,000	$20,000	$21,000	$22,000	$13,000

Expert J	$13,000	$18,000	$19,000	$20,000	$11,000

Expert K	$4,100	$9,500	$10,000	$11,000	$2,300

Expert L	$12,000	$17,000	$18,000	$19,000	$9,700

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-47: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: California Glidepath Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$120	$220	$240	$210	$81

Harvard Six-City StudyC	$200	$310	$320	$300	$170

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$290	$390	$410	$390	$250

Expert B	$230	$340	$350	$330	$190

Expert C	$230	$330	$350	$320	$190

Expert D	$170	$280	$290	$270	$140

Expert E	$350	$460	$470	$450	$310

Expert F	$210	$320	$330	$310	$180

Expert G	$150	$260	$270	$250	$110

Expert H	$180	$290	$300	$280	$140

Expert I	$220	$330	$340	$320	$190

Expert J	$190	$300	$310	$290	$150

Expert K	$69	$180	$190	$170	$34

Expert L	$180	$280	$290	$270	$140

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-48: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: Incremental Benefits of California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,100	$2,200	$2,400	$2,400	$800

Harvard Six-City StudyC	$2,000	$3,100	$3,200	$3,300	$1,700

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$2,800	$3,900	$4,000	$4,100	$2,500

Expert B	$2,200	$3,400	$3,500	$3,500	$1,900

Expert C	$2,200	$3,300	$3,400	$3,500	$1,900

Expert D	$1,700	$2,800	$2,900	$2,900	$1,300

Expert E	$3,400	$4,500	$4,600	$4,700	$3,100

Expert F	$2,100	$3,200	$3,300	$3,300	$1,700

Expert G	$1,500	$2,600	$2,700	$2,700	$1,100

Expert H	$1,800	$2,900	$3,000	$3,000	$1,400

Expert I	$2,200	$3,300	$3,400	$3,500	$1,900

Expert J	$1,900	$3,000	$3,100	$3,100	$1,500

Expert K	$680	$1,800	$1,900	$1,900	$350

Expert L	$1,700	$2,800	$2,900	$3,000	$1,400

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 



Table 6-49: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,300	$2,500	$2,600	$2,600	$890

Harvard Six-City StudyC	$2,200	$3,400	$3,500	$3,600	$1,800

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$3,100	$4,300	$4,400	$4,500	$2,700

Expert B	$2,500	$3,700	$3,800	$3,800	$2,100

Expert C	$2,500	$3,700	$3,800	$3,800	$2,100

Expert D	$1,800	$3,000	$3,200	$3,200	$1,500

Expert E	$3,800	$5,000	$5,100	$5,100	$3,400

Expert F	$2,300	$3,500	$3,600	$3,600	$1,900

Expert G	$1,600	$2,800	$2,900	$3,000	$1,200

Expert H	$1,900	$3,100	$3,300	$3,300	$1,600

Expert I	$2,400	$3,600	$3,800	$3,800	$2,100

Expert J	$2,000	$3,300	$3,400	$3,400	$1,700

Expert K	$7500	$2,000	$2,100	$2,100	$380

Expert L	$1,900	$3,100	$3,200	$3,300	$1,500

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates.  Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-50: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$4,400	$8,700	$9,300	$10,000	$2,900

Harvard Six-City StudyC	$7,900	$12,000	$13,000	$14,000	$6,500

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$11,000	$15,000	$15,000	$16,000	$9,100

Expert B	$8,400	$13,000	$13,000	$14,000	$7,000

Expert C	$8,400	$13,000	$13,000	$14,000	$6,900

Expert D	$6,300	$11,000	$11,000	$12,000	$4,900

Expert E	$13,000	$17,000	$18,000	$19,000	$11,000

Expert F	$7,800	$12,000	$13,000	$14,000	$6,300

Expert G	$5,500	$9,900	$10,000	$11,000	$4,100

Expert H	$6,600	$11,000	$12,000	$12,000	$5,200

Expert I	$8,300	$13,000	$13,000	$14,000	$6,800

Expert J	$7,000	$11,000	$12,000	$13,000	$5,600

Expert K	$2,800	$7,100	$7,600	$8,500	$1,200

Expert L	$6,500	$11,000	$11,000	$12,000	$5,100

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

 B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate. 

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

Table 6-51: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Alternative
Standard: California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

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

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$470	$1,200	$1,200	$1,200	$240

Harvard Six-City StudyC	$700	$1,400	$1,500	$1,500	$480

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$930	$1,600	$1,700	$1,700	$710

Expert B	$770	$1,500	$1,500	$1,500	$550

Expert C	$760	$1,500	$1,500	$1,500	$540

Expert D	$610	$1,300	$1,400	$1,400	$390

Expert E	$1,100	$1,800	$1,900	$1,900	$870

Expert F	$720	$1,400	$1,500	$1,500	$500

Expert G	$550	$1,200	$1,300	$1,300	$330

Expert H	$630	$1,300	$1,400	$1,400	$410

Expert I	$760	$1,500	$1,500	$1,500	$540

Expert J	$660	$1,400	$1,400	$1,400	$440

Expert K	$340	$1,000	$1,100	$1,100	$120

Expert L	$620	$1,300	$1,400	$1,400	$400

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower. 

6.5.5 Discussion of Results and Uncertainties

This analysis has estimated the health and welfare benefits of
reductions in ambient concentrations of ozone and particulate matter
resulting from a set of illustrative control strategies to reduce
emissions of ozone.  The results suggest there will be significant
additional health and welfare benefits arising from reducing emissions
from a variety of sources in and around projected nonattaining counties
in 2020.  While 2020 is the expected date that states would need to
demonstrate attainment with the revised standard, it is expected that
benefits (and costs) will begin occurring much earlier, as states begin
implementing control measures to show reasonable progress towards
attainment. Using the full range of benefits (including the results of
the expert elicitation), we estimate that total ozone and PM2.5 benefits
would be between and $2.7B and $37B annually for the 0.070 ppm
alternative when the emissions reductions from implementing the new
standard is fully realized provides additional evidence of the important
role that implementation of the standards plays in reducing the health
risks associated with exceeding the standard.

There are several important factors to consider when evaluating the
relative benefits of the attainment strategies for each of the
alternative ozone standards.  

California accounts for a substantial share of the total benefits for
each of the evaluated standards.  Benefits are most uncertain for
California given the unique challenge of modeling attainment with the
standards due to the high levels of ozone, difficulties of modeling the
impacts of emissions controls on air quality, and the very large
proportion of California benefits that were derived through
extrapolation are very large relative to other areas of the U.S. for
each standard alternative. On the one hand, these California benefits
are likely to understate the actual benefits of attainment strategies,
because we applied an estimation approach that reduced concentrations
only at the specific violating monitors and not surrounding monitors
that did not violate the standards.  The magnitude of this underestimate
is unknown. On the other hand, it is possible that new technologies
might not meet the specifications, development timelines, or cost
estimates provided in this analysis, thereby increasing the uncertainty
in when and if such benefits would be truly achieved.

There are substantial uncertainties associated with the estimated
benefits of the 0.065 ppm and 0.075 ppm alternatives, which were derived
through extrapolation and interpolation, respectively. The great
majority of benefits estimated for the 0.065 ppm standard alternative
were derived through extrapolation. As noted above, these benefits are
likely to be more uncertain than the modeled benefits. The 0.075 ppm
benefits were derived through an interpolation technique (described in
Appendix 6) which scaled-down the benefits of the 0.070 ppm benefits
analysis. A key assumption in this approach is that the control strategy
to attain 0.075 ppm would share the same characteristics of the 0.070
ppm strategy—namely, regional emission controls on electrical
generating units and emission controls applied to counties within 200km
of projected non-attainment monitors. To the extent that states utilized
fewer regional emission controls, total benefits for the 0.075 ppm
strategy may be smaller. 

There are a variety of uncertainties associated with the health impact
functions used in this modeling effort. These include: within study
variability, which is the precision with which a given study estimates
the relationship between air quality changes and health effects; across
study variation, which refers to the fact that different published
studies of the same pollutant/health effect relationship typically do
not report identical findings and in some instances the differences are
substantial.; the application of C-R functions nationwide, which does
not account for any relationship between region and health effect, to
the extent that such a relationship exists; extrapolation of impact
functions across population, in which we assumed that certain health
impact functions applied to age ranges broader than that considered in
the original epidemiological study; and, finally, there are various
uncertainties in the C-R function, including causality, the correlation
among multiple pollutants, the shape of the C-R function and the
relative toxicity of PM component species, and the lag between exposure
and the onset of the health effect. 

There are a variety of uncertainties associated with the economic
valuation of the health endpoints estimated in this analysis.
Uncertainties specific to the valuation of premature mortality include
across study variation; the assumption that WTP for mortality risk
reduction is linear; assuming that voluntary and involuntary mortality
risk will be valued equally; assuming that premature mortality from air
pollution risk, which tend to involve longer periods of time, will be
valued the same as short catastrophic events; the possibility for
self-selection in avoiding risk, which may bias WTP estimates upward. 

This analysis includes estimates of PM2.5 co-benefits that were derived
through benefit per-ton estimates derived from the Pope et. al (2002)
mortality estimate. These benefit per-ton estimates represent regional
averages. As such, they do not reflect any local variability in the
incremental PM2.5 benefits per ton of NOx abated. As discussed in the PM
NAAQS RIA (Table 5.5), there are a large number of uncertainties
associated with these PM benefits.

For the 0.070 ppm alternative, we estimate co-benefits from PM to be
between 20% and 99% of total benefits, depending on the PM2.5 and ozone
mortality functions used. In our calculation of PM2.5 co-benefits we
assume that states will pursue an ozone strategy that reduces NOx
emissions. As such, these estimates are strongly influenced by the
assumption that all PM components are equally toxic. We also acknowledge
that when implementing any new standard, states may elect to pursue a
different ozone strategy, which would in turn affect the level of PM2.5
co-benefits. 

Inherent in any analysis of future regulatory programs are uncertainties
in projecting atmospheric conditions and source-level emissions, as well
as population, health baselines, incomes, technology, and other factors.
 In addition, data limitations prevent an overall quantitative estimate
of the uncertainty associated with estimates of total economic benefits.
 If one is mindful of these limitations, the magnitude of the benefits
estimates presented here can be useful information in expanding the
understanding of the public health impacts of reducing ozone precursor
emissions.

There are certain unquantified effects not considered in this benefits
analysis due to lack of data, time and resources. These unquantified
endpoints include the direct effects of of ozone on vegetation, the
deposition of nitrogen to estuarine and coastal waters and agricultural
and forested land, and the changes in the level of exposure to
ultraviolet radiation from ground level ozone. 

EPA will continue to evaluate new methods and models and select those
most appropriate for estimating the health benefits of reductions in air
pollution.  It is important to continue improving benefits transfer
methods in terms of transferring economic values and transferring
estimated impact functions.  The development of both better models of
current health outcomes and new models for additional health effects
such as asthma, high blood pressure, and adverse birth outcomes (such as
low birth weight) will be essential to future improvements in the
accuracy and reliability of benefits analyses (Guo et al., 1999  XE "Guo
et al., 1999"  ; Ibald-Mulli et al., 2001  XE "Ibald-Mulli et al., 2001"
 ).  Enhanced collaboration between air quality modelers,
epidemiologists, toxicologists, and economists should result in a more
tightly integrated analytical framework for measuring health benefits of
air pollution policies. Readers interested in a more extensive
discussion of the sources of uncertainty in human health benefits
analyses should consult the PM NAAQS RIA.

6.5.6 Summary of Total Benefits

Tables 6-52 presents the total number of estimated ozone and
PM2.5-related premature mortalities and morbidities avoided nationwide
in 2020. Table 6-53 presents these estimates for California, post 2020.

Table 6-52: Summary of Total Number of Annual Ozone and PM2.5-Related
Premature Mortalities and Premature Morbidity Avoided: 

2020 National Benefits

Combined Estimate of Mortality

Standard Alternative and 

Model or AssumptionA	Combined Range of Ozone Benefits and

 PM2.5 Co-Benefits

0.075 ppm 	0.070 ppm	0.065 ppm

NMMAPS 	Bell (2004)	390 to 2,100	650 to 4,000	1,200 to 7,600

Meta-Analysis	Bell (2005)	1,100 to 2,800	1,500 to 4,900	2,800 to 9,200

	Ito (2005)	1,200 to 2,900	1,600 to 5,000	9,400 to 3,100

	Levy (2005)	1,300 to 3,000	1,800 to 5,100	9,400 to 3,000

No Causality	190 to 1,900	370 to 4,000	690 to 7,000

	Combined Estimate of Morbidity

	Acute Myocardial Infarction	1,100	2,100	3,900

Hospital and ER Visits	30,000	55,000	100,000

Chronic Bronchitis	380	740	1,400

Acute Bronchitis	1,000	1,900	3,700

Asthma Exacerbation	7,600	15,000	28,000

Lower Respiratory Symptoms	8,300	16,000	30,000

Upper Respiratory Symptoms	6,100	12,000	22,000

School Loss Days	610,000	780,000	1,300,000

Work Loss Days	53,000	100,000	190,000

Minor Restricted Activity Days	2,000,000	2,700,000	4,700,000

	

Table 6-53: Summary of Total Number of Annual Ozone and PM2.5-Related
Premature Mortalities and Premature Morbidity Avoided: California Post
2020 Attainment

Combined Estimate of Mortality

Standard Alternative and 

Model or AssumptionA	Combined Range of Ozone Benefits and

 PM2.5 Co-Benefits

0.075 ppm 	0.070 ppm	0.065 ppm

NMMAPS 	Bell (2004)	49 to 180	120 to 640	190 to 950

Meta-Analysis	Bell (2005)	160 to 290	310 to 830	500 to 1,300

	Ito (2005)	170 to 300	320 to 850	540 to 1,300

	Levy (2005)	170 to 300	330 to 850	530 to 1,300

No Causality	14 to 150	56 to 580	82 to 840

	Combined Estimate of Morbidity

	Acute Myocardial Infarction	80	320	460

Hospital and ER Visits	2,600	8,700	13,000

Chronic Bronchitis	28	110	170

Acute Bronchitis	75	300	440

Asthma Exacerbation	570	2,300	3,300

Lower Respiratory Symptoms	630	2,500	3,600

Upper Respiratory Symptoms	460	1,800	2,700

School Loss Days	120,000	210,000	340,000

Work Loss Days	3,900	16,000	23,000

Minor Restricted Activity Days	320,000	610,000	970,000

	

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 Health impact functions measure the change in a health endpoint of
interest, such as hospital admissions, for a given change in ambient
ozone or PM concentration

 This is effectively 0.084 ppm due to current rounding conventions. When
calculating benefits in this chapter we followed the rounding convention
and rounded to 0.084 ppm.

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Guidelines.pdf" 
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uidelines.pdf 

 The one exception relates to the use of updated health impact functions
for emergency department visits. These new functions are detailed
further in this chapter.

 The PM2.5 benefits presented below reflect the NOx emission reductions
from the ozone control strategy. Reductions from Ocean-Going Vessels
burning residual diesel fuel were included both East and West in the
baseline PM co-benefits, but not included in the ozone baseline for the
west.  See chapter 3 for more details of this rule and its application.

 U.S. Environmental Protection Agency, 2004a.  Final Regulatory
Analysis: Control of Emissions from Nonroad Diesel Engines. 
EPA420-R-04-007.  Prepared by Office of Air and Radiation.  Available at
  HYPERLINK "http://www.epa.gov/nonroad-diesel/2004fr/420r04007.pdf" 
http://www.epa.gov/nonroad-diesel/2004fr/420r04007.pdf  

 U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis
for the Clean Air Interstate Rule. EPA 452/-03-001.  Prepared by Office
of Air and Radiation.  Available at:   HYPERLINK
http://www.epa.gov/interstateairquality/tsd0175.pdf
http://www.epa.gov/interstateairquality/tsd0175.pdf 

 U.S. Environmental Protection Agency, 2006. Regulatory Impact Analysis
for the PM NAAQS. EPA  Prepared by Office of Air and Radiation. 
Available at:   HYPERLINK
"http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf" 
http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf  

 Expert elicitation is a formal, highly structured and well documented
process whereby expert judgments, usually of multiple experts, are
obtained (Ayyb, 2002). 

 Health impact functions measure the change in a health endpoint of
interest, such as hospital admissions, for a given change in ambient
ozone or PM concentration. 

 Industrial Economics, Inc.  2006.  Expanded Expert Judgment Assessment
of the Concentration-Response Relationship Between PM2.5 Exposure and
Mortality.  Prepared for EPA Office of Air Quality Planning and
Standards, September.  Available at:    HYPERLINK
"http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_report.pdf" 
http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_report.pdf  

 U.S. Environmental Protection Agency, 2005. Regulatory Impact Analysis
for the PM NAAQS. EPA  Prepared by Office of Air and Radiation. 
Available at:   HYPERLINK
"http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf" 
http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf  pp.
5-29.

 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. 

 National Research Council (NRC).  2002.  Estimating the Public Health
Benefits of Proposed Air Pollution Regulations.  Washington, DC:  The
National Academies Press.

 For an exhaustive review of the city-specific time-series studies
considered in the ozone staff paper, see: U.S. Environmental Protection
Agency, 2007. Review of the National Ambient Air Quality Standards for
Ozone: Policy Assessment of Scientific and Technical Information.
Prepared by the Office of Air and Radiation. Available at
http://www.epa.gov/ttn/naaqs/standards/ozone/data/2007_01_ozone_staff_pa
per.pdf. pp. 5-36.

 A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

 Abt Associates, Incorporated. Environmental Benefits Mapping and
Analysis Program, Technical Appendices. May 2005. pp. I-3

 Booth, M.S., and C. Campbell.  2007.  Spring Nitrate Flux in the
Mississippi River Basin: A Landscape Model with Conservation
Applications.  Environ. Sci. Technol.; 2007; ASAP Web Release Date:
20-Jun-2007; (Article) DOI: 10.1021/es070179e

 U.S. Environmental Protection Agency.  1999.  The Benefits and Costs of
the Clean Air Act, 1990-2010.  Prepared for U.S. Congress by U.S. EPA,
Office of Air and Radiation/Office of Policy Analysis and Review,
Washington, DC, November; EPA report no. EPA-410-R-99-001.

  Ibid.

  ICF Consulting.  2006.  Human Health Benefits of Stratospheric Ozone
Protection. Peer Reviewed Report  Prepared for: Global Programs
Division, Office of Air and Radiation, U.S. Environmental Protection
Agency.  April 24, 2006.

 National Academy of Sciences, “Radiative Forcing of Climate Change:
Expanding the Concept and Addressing Uncertainties,” October 2005.

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 Intergovernmental Panel on Climate Change [Solomon, S., D.
Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L.
Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA.

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

Summary for Policymakers

 Denman, et al, 2007: Couplings Between Changes in the Climate System
and Biogeochemistry. In: Climate Change 2007: The Physical Science
Basis. 

 Note that the valuation estimates for ozone benefits are not
discounted. Because these are short term benefits that occur the same
year in which the alternate standard is met, discounting is not
necessary.

 A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

 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   HYPERLINK "http://www.epa.gov/sab/pdf/casac-07-001.pdf" 
http://www.epa.gov/sab/pdf/casac-07-001.pdf  

 National Academy of Sciences (2007) Project Scope.  Estimating
Mortality Risk Reduction Benefits from Decreasing Tropospheric Ozone
Exposure.  Division on Earth and Life Studies, Board on Environmental
Studies and Toxicology.  Available at   HYPERLINK
"http://www8.nationalacademies.org/cp/projectview.aspx?key=48768" 
http://www8.nationalacademies.org/cp/projectview.aspx?key=48768  

 Final Regulatory Impact Analysis: Industrial Boilers and Process
Heaters. Prepared by Office of Air and Radiation. Available:
http://www.epa.gov/ttn/ecas/regdata/EIAs/chapter10.pdf [accessed 18 May
2007].

 U.S. Environmental Protection Agency, 2006. Regulatory Impact Analysis
for the PM NAAQS. EPA  Prepared by Office of Air and Radiation. 
Available at:   HYPERLINK
"http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf" 
http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf 

6- PAGE   2 

6- PAGE   1 

A The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

B Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

C All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.

A The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

B Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

C All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.

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A The estimate is based on the concentration-response (C-R) function
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B Based on Laden et al (2006) reporting of the extended Six-cities
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C All estimates rounded to two significant figures. As such, confidence
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All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.