United States EPA Science Advisory EPA-SAB-COUNCIL-ADV-04-002
Environmental Board Staff Office (1400A) March 2004
Protection Agency Washington DC www.epa.gov/sab
Advisory on 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
Advisory by the Health Effects
Subcommittee of the Advisory Council
on Clean Air Compliance Analysis
-------
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
OFFICE OF THE ADMINISTRATOR
February 25, 2004 scenes ADVISORY BOARD
EPA-SAB-COUNCEL-ADV-4-002
The Honorable Michael O. Leavitt
Administrator
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Subject: Advisory on 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
Dear Administrator Leavitt:
The Advisory Council on Clean Air Compliance Analysis (Council) met on December
19,2003 to discuss and approve this Advisory provided by its Health Effects Subcommittee on
the Agency's plans for health effects analyses in the upcoming Second Prospective Analysis of
the costs and benefits of the Clean Air Act. The Health Effects Subcommittee (HES) developed
the Advisory after meeting in a public session, August 27-29,2003 to consider in detail charge
questions from the Agency related to a wide range of health effects to be addressed in the Second
Prospective Analysis and after holding several public teleconferences on the topic.
The Council and the HES are guided in this Advisory by the Agency's charge from
Congress in 812 of the Clean Air Act Amendments of 1990 that the mandated analyses be
"comprehensive" and "that the Administrator shall consider all of the economic, public health,
and environmental benefits of efforts to comply, hi any case where numerical values are
assigned to such benefits, a default assumption of zero value shall not be assigned to such
benefits unless supported by specific data."
The Council and the HES provide this advice to assist the Agency in fully characterizing
the science related to health effects related to the Clean Air Act. We point out that now, as in the
Recycled/Recyclable
Printed on pap« lhai contain*
* toast 7S* racydwi Gb*
-------
past, major categories of effects will be left unqualified such as cardiovascular morbidity from
long-term exposure, ecological effects and most air toxics health effects, because of the
limitations of existing scientific methods and data. We appreciate the efforts made by EPA's
Project Team to expand benefit categories to be captured in the Second Prospective Analysis in
their exhaustive review of a wealth of new scientific literature and their efforts to characterize
the uncertainties associated with that new literature.
The HES and the Council generally support EPA's Analytic Plan. There are two issues,
however, which we believe deserve more careful attention. One is the Agency's exploration of
the use of formal expert judgment as a means for characterizing uncertainty analysis about
mortality from Particulate Matter (PM) exposure. We applaud the Agency's interest in exploring
the use of formal expert judgment as a tool for improving uncertainty analysis and believe that
the proposed pilot study has great potential to yield important insights. The pilot is well
designed to inform subsequent and more comprehensive expert elicitation projects, but relies on
the opinions of a relatively small group of experts. It may provide preliminary information about
the general magnitude of the mortality effects, and may yield a sense of both the uncertainty
inherent in these estimates and the factors largely responsible for such uncertainty. However,
until the pilot study methods and results have been subjected to peer review, it may be unwise for
the Agency to rely directly on these preliminary results in key policy decisions.
The second issue is the omission of infant mortality effects and exacerbation of asthma
from the base case analysis in the study. We strongly recommend that the Agency redesign the
analysis to include these effects in their base case.
We strongly advise that the Agency should continue to use prospective cohort studies as
the basis for analysis of mortality effects of PM in the base case for the study. We propose that
the Second Prospective Analysis present the base case with associated uncertainties (preferably
confidence intervals of 10%-90%), plus a set of sensitivity analyses, rather than the base case
and a single "alternative analysis." The Council and the HES advise that the single "alternative
analysis" to the base case described in the Agency's Draft Analytical Plan does not represent to
us, as scientific and technical experts, the comprehensive scientific analysis of health benefits
that we understand the Clean Air Act to require. We advise that the Agency aim for a
quantitative base case that includes best estimates for all health effects for which there is
reasonable quantitative evidence with careful avoidance of potential double counting. This
should be supplemented with an acknowledgement of the likely benefits that cannot be
adequately quantified at this time. If alternative estimates are presented, they should be balanced
to reflect the possibilities that the base case may either understate or overstate actual health
benefits.
We also support EPA's plans for meta-analyses for ozone mortality and the Agency's
plans to consider adding it to base case analysis, subsequent to review of the results of those
analyses.
-------
We appreciate the opportunity to review the Analytical Plan and to provide you with
advice on the analysis of health effects. The HES would be pleased to expand on any of the
findings described in this report and we look forward to your response.
Sincerely,
CQJr
Dr. Bart Ostro, Chair Dr. Trudy Ann Cameron, Chair
Health Effects Subcommittee Advisory Council on Clean Air
Compliance Analysis
-------
NOTICE
This report has been written as part of the activities of the EPA Advisory Council on Clean Air
Compliance Analysis (Council), a public advisory group providing extramural scientific
information and advice to the Administrator and other officials of the Environmental Protection
Agency. The Council is structured to provide balanced, expert assessment of scientific matters
related to problems facing the Agency. This report has not been reviewed for approval by the
Agency and, hence, the contents of this report do not necessarily represent the views and policies
of the Environmental Protection Agency, nor of other agencies in the Executive Branch of the
Federal government, nor does mention of trade names of commercial products constitute a
recommendation for use. Reports of the Council are posted on the EPA website at
http://www.epa.gov/sab.
-------
U.S. Environmental Protection Agency
Advisory Council on Clean Air Compliance Analysis
Health Effects Subcommittee
CHAIR
Dr. Bart Ostro, California Office of Environmental Health Hazard Assessment (OEHHA),
Oakland, CA
MEMBERS
Mr. John Fintan Hurley, Institute of Occupational Medicine (IOM), Edinburgh, Scotland
Dr. Patrick Kinney, Columbia University, New York, NY
Dr. Michael Kleinman, University of California, Irvine, CA
Dr. Nino Kuenzli, University of Southern California, Los Angeles, CA
Dr. Morton Lippmann, New York University School of Medicine, Tuxedo, NY
Dr. Rebecca Parkin, The George Washington University, Washington, DC
SCIENCE ADVISORY BOARD STAFF
Dr. Angela Nugent, Designated Federal Officer
-------
U.S. Environmental Protection Agency
Advisory Council on Clean Air Compliance Analysis (Council)
Special Council Panel for the Review of the Third 812 Analysis
CHAIR
Dr. Trudy Cameron, University of Oregon, Eugene, OR
COUNCIL MEMBERS
Dr. David T. Allen, University of Texas, Austin, TX
Ms. Lauraine Chestnut, Stratus Consulting Inc., Boulder, CO
Dr. Lawrence Goulder, Stanford University, Stanford, CA
Dr. James Hammitt, Harvard University, Boston, MA
Dr. F. Reed Johnson, Research Triangle Institute, Research Triangle Park, NC
Dr. Charles Kofstad, University of California, Santa Barbara, CA
Dr. Lester B. Lave, Carnegie Mellon University, Pittsburgh, PA
Dr. Virginia McConnell, Resources for the Future, Washington, DC
Dr. Bart Ostro, California Office of Environmental Health Hazard Assessment (OEHHA),
Oakland, CA
Dr. V. Kerry Smith, North Carolina State University, Raleigh, NC
OTHER PANEL MEMBERS
Dr. John Evans;- Harvard University, Portsmouth, NH
Dr. Dale Hattis, Clark University, Worcester, MA
Dr. D. Warner North, NorthWorks Inc., Belmont, CA
Dr. Thomas S. Wallsten, University of Maryland, College Park, MD
SCIENCE ADVISORY BOARD STAFF
Dr. Angela Nugent, Designated Federal Officer
iii
-------
TABLE OF CONTENTS
1. EXECUTIVE SUMMARY 1
2. INTRODUCTION 3
2.1. BACKGROUND ON THIS ADVISORY 3
2.2. CHARGE QUESTIONS RELATED TO HEALTH EFFECTS 4
3. RESPONSES TO CHARGE QUESTIONS 5
3.1. AGENCY CHARGE QUESTION 11: PLANS FOR ESTIMATING, EVALUATING, AND REPORTING CHANGES IN
HEALTH EFFECT OUTCOMES BETWEEN SCENARIOS 5
3.1.1. Ozone effects and issue of covariation with Paniculate Matter (PM) 5
3.1.2. Source-Specific Concentration-Response (C-R) Functions 5
3.1.3. Extrapolation to Other Age Groups •. 6
3.1.4. Exposure Assessment (Use of Grids) 7
3.1.5. Infant effects 8
3.1.6. Asthma 9
3.1.7. Effects of 'the SONOCO Suite 10
3.2. AGENCY CHARGE QUESTION 12: ENDPOINTS FOR PARTICIPATE MATTER AND OZONE 11
3.2.1. New and Revised Endpoints for Paniculate Matter. 12
3.2.2. New and Revised Ozone Endpoints 13
3.3. AGENCY CHARGE QUESTION 13: BASELINE DATA 13
3.4. AGENCY CHARGE QUESTION 14: SCIENTIFIC MERITS OF ALTERNATIVE METHODS TO EXPERT ELICITATION
FOR ESTIMATING THE INCIDENCES OF PM-RELATED PREMATURE MORTALITY 17
3.5. AGENCY CHARGE QUESTION 15: ALTERNATIVE ANALYSIS FOR PM CONTROL 20
3.6. AGENCY CHARGE QUESTION 16: CESSATION LAG 22
3.7. AGENCY CHARGE QUESTION 17: ALTERNATIVES TO THE BASE ESTIMATE 25
3.8. AGENCY CHARGE QUESTION 29: PLANS FOR EXPERT ELICITATION PILOT FOR PREMATURE MORTALITY.
29
3.9. AGENCY CHARGE QUESTION 30: PLANS FOR ESTIMATING INDEPENDENT EFFECTS OF OZONE
MORTALITY 34
3.10. AGENCY CHARGE QUESTION 32: EVALUATING DATA QUALITY AND PLANS FOR PUBLICATION OF
INTERMEDIATE DATA PRODUCTS 35
3.11. AGENCY CHARGE QUESTION 33: PLANS FOR AGGREGATION AND PRESENTATION OF ANALYTICAL
RESULTS FROM THE HEALTH ANALYSIS 36
3.12. AGENCY CHARGE QUESTION 34: PLANS FOR STRATOSPHERIC OZONE ANALYSIS 38
3.13. AGENCY CHARGE QUESTION 35:" PLANS FOR AN AIR Toxic CASE STUDY 38
REFERENCES 41
APPENDIX A: LIST OF CHARGE QUESTIONS PROVIDED TO THE HES 47
APPENDIX B: BIOSKETCHES OF HES MEMBERS AND MEMBERS OF THE COUNCIL AND
COUNCIL SPECIAL PANEL FOR THE REVIEW OF THE THIRD 812 ANALYSIS WHO ASSISTED
WITH DEVELOPMENT OF THIS HES ADVISORY 53
IV
-------
1. EXECUTIVE SUMMARY
In this Advisory, the Health Effects Subcommittee (HES) of the Advisory Council on
Clean Air Compliance Analysis provides detailed advice related to a wide range of health effects
to be addressed in the Second Prospective Analysis. The overall purpose of the Advisory is to
assist the Agency in fully characterizing the science associated with health effects related to the
Clean Air Act.
The HES generally supports EPA's Analytic Plan. There are two major issues, however,
which it singled out for more careful attention. One is the Agency's exploration of the use of
formal expert judgment as a means for characterizing uncertainty in the effects of PM exposure
on human mortality. The second is the omission of two important effects, infant mortality and
exacerbation of asthma, from the base case analysis in the study.
t
The HES supports the Agency's interest in exploring the use of formal expert judgment
as a too! for improving uncertainty analysis and believes that the proposed pilot study has great
potential to yield important insights. It notes, however that although the pilot is well designed to
inform subsequent and more comprehensive expert elicitation projects, it relies on the opinions
of a relatively small group of experts. It may provide preliminary information about the general
magnitude of the mortality effects from PM exposure, and may yield a sense of both the
uncertainty inherent in these estimates and the factors largely responsible for such uncertainty.
However, until the pilot study methods and results have been subjected to peer-review, it may be
unwise for the Agency to rely directly on these preliminary results in key policy decisions.
In regard to the omission of infant mortality and asthma exacerbation, the HES advises
that the Agency redesign the analysis to include these effects in the base case.
In regard to the base case for the study, the HES recommends that the Agency continue to
use prospective cohort studies as the basis for analysis of mortality effects of PM. The HES
advises that the Second Prospective Analysis present the base case with associated uncertainties
(preferably confidence intervals of 90% and 10%), plus a set of sensitivity analyses, rather than
the base case and a single "alternative analysis."
In addition to these major points, the HES provides advice on many detailed charge
questions. This summary identifies that advice briefly. The HES advises the Agency on the use
of alternative data or methods for characterizing: ozone effects; covariation with particulate
matter (PM); source-specific concentration-response (C-R) functions; extrapolation to other age
groups; exposure assessment (use of grids); infant effects; asthma effects; and the effects of
sulfur dioxide (S02), nitrogen dioxide (NO2), carbon monoxide (CO) (the SONOCO Suite).
The HES generally indicates support for the Agency's incorporation of several new and
revised endpoints for PM, and suggests some modifications to the Agency's approach. The HES
commends the EPA for its efforts to identify appropriate databases to update and strengthen
population characteristics and health outcome rates. It identifies, however, some remaining
1
-------
issues concerning data sources and the uses of the data that need to be considered in further
detail before the plan is implemented.
In regard to several questions related to the scientific merits of alternative methods for
estimating the incidences of PM-related premature mortality, the Subcommittee agrees with
EPA's current proposal to use prospective cohort-based estimates in the base case. Different
cohort studies and, within each study, various concentration-response (C-R) functions are
available, using different causes of death, exposure windows, subgroups, and models. The HES
recommends that the base case rely on the Pope et al. (2002) study and that EPA use total
mortality concentration-response functions (CFRs), rather than separate cause-specific CFRs, to
calculate total PM mortality cases.
The HES also provides advice on how to address the question of cessation lag, which is
the time lag between reductions in concentrations of air pollutants and manifestation of health
benefits in the population. The HES notes that for long-term PM effects, empirical evidence is
lacking to estimate the lags. Given this problem, the HES recommends that the Agency consider
developing models for each cause of death category expected to make up PM mortality, since the
lag structure most likely differs for different PM-associated disease processes. Although specific
causes of death would not be specifically calculated in the base case, the literature provides
enough information to guide estimates of the likely proportion of PM mortality by disease type
(Pope et al., 2002,2004).
The Subcommittee endorses EPA's plans to sponsor three new meta-analyses of ozone
mortality impacts to help characterize the independent health effects of ozone. It provides advice
concerning how to address issues raised regarding aggregation and presentation of analytical
results from the planned health analysis.
The HES concludes that the Agency's proposed revised approach to determining costs
and benefits of controls to limit stratospheric ozone reductions by anthropogenic chemicals is
sound and addresses the issue comprehensively. The HES also notes that the Agency's basic
conception of the air i-oxics case study is reasonable, given that the chemical chosen, benzene, is
data rich. Several suggestions for strengthening the approach are also provided. Finally, the
HES makes several recommendations for the Agency to consider regarding the proposal to use a
five-year cessation lag for benzene-induced leukemia.
-------
2. INTRODUCTION
2.1. Background on this Advisory.
The purpose of this Advisory is to provide commentary and guidance on EPA plans for
developing the health effects analysis described in the July 8, 2003 review document, Benefits
and Costs of the Clean Air Act 1990-2020: Revised Analytical Plan for EPA's Second
Prospective Analysis (Analytical Plan).
The Health Effects Subcommittee (HES) of the Advisory Council on Clean Air
Compliance Analysis (Council) held a public meeting on August 27-29, 2003 to receive briefings
and discuss the charge questions provided by the Agency related to health effects analysis for the
Analytical Plan. In addition to the Chair of the HES, who represents the HES on the Council,
one additional member of the Council, Ms. Lauraine Chestnut, participated in this meeting. Four
other members of the Council's Special Council Panel for the Review of the Third 812 Analysis,1
who were added to the Council especially to address issues associated with analysis of
uncertainty and statistical and subjective probability, joined the meeting either in person, by
teleconference or by providing written comments for consideration during the Subcommittee
meeting. In their discussions, members focused on issues related to the Agency's plan to
develop health effects estimates. The charge questions are discussed in Section 2.2. and listed in
Appendix A.
During the meeting in August, the Chair of the HES, Dr. Bart Ostro, provided
information that he was considering serving as one of the five experts to be elicited by the
Agency for a pilot study of premature mortality from exposure to particulate matter. That pilot is
the subject of Charge Question 29. After the meeting, Dr. Ostro indeed decided to serve as one
of the experts and also agreed to recuse himself from HES and Council deliberations on this
question. Dr. Nino Kuenzli from the HES was appointed by the SAB Staff Office as the HES
chair for discussions of this question.
The HES held an additional public teleconference on October 30,2003 and thisn the
Council held a public teleconference meeting on December 19,2003 to discuss and formalize the
advice to the EPA Administrator on this topic.
1 Dr. John Evans, Senior Lecturer on Environmental Science, Harvard University; Dr. Dale
Hattis, Research Professor, Center for Technology, Environment, and Development, George
Perkins Marsh Institute, Clark University; Dr. D. Warner North, President, North Works Inc.; Dr.
Thomas S. Wallsten, Professor, Department of Psychology, University of Maryland.
3
-------
2.2. Charge Questions Related to Health Effects.
In its review of the analytical plan, the Council and its subcommittees are guided by the
Council mandate, as identified in the Clean Air Act (CAA) Amendments of 1990:
a) Are the input data used for each component of the analysis sufficiently valid and
reliable for the intended analytical purpose?
b) Are the models, and the methodologies they employ, used for each component of
the analysis sufficiently valid and reliable for the intended analytical purpose?
c) If the answer to either of the two questions above is negative, what specific
alternative assumptions, data or methodologies does the Council recommend the
Agency consider using for the second prospective analysis?
In addition to this mandate, the Council received thirty-seven charge questions related to
the draft analytical plan. Among those thirty-seven charge questions provided to the Council,
fourteen charge questions related to health effects, uncertainty analysis of health effects, plans
related to data quality and intermediate data products, results aggregation and reporting,
uncertainty, stratospheric ozone analysis, and an air toxics case study. These Charge Questions
are excerpted from the list of revised charge questions provided by the Agency on July 8,2003
and listed in Appendix A to this Report. The charge questions listed there and addressed in this
report by the HES retain the numbering scheme provided by the Agency in July.
Specifically, subsection (g) of CAA Section 312 (as amended by Section 812 of the
amendments) states: "(g) The Council shall — (1) review the data to be used for any analysis
required under this section and make recommendations to the Administrator on the use of such
data, (2) review the methodology used to analyze such data and make recommendations to the
Administrator on the use of such methodology; and (3) prior to issuance of a report required
under subsection (d) or (e), review the findings of such report, and make recommendations to the
Administrator concerning the validity and utility of such findings."
4
-------
3. RESPONSES TO CHARGE QUESTIONS
3.1. Agency Charge Question 11; Plans for estimating, evaluating, and reporting
changes in health effect outcomes between scenarios.
Charge Question 11. Does the Council support the plans described in chapter 6 for estimating,
evaluating, and reporting changes in health effect outcomes between scenarios? If there are
particular elements of these plans which the Council does not support, are there alternative data
or methods the Council recommends?
HES Response: The HES provides here comments not specifically addressed in other formal
charge questions posed by the Agency.
3.1.1. Ozone effects and issue of covariation with Paniculate Matter (PM).
The underlying consideration here is whether ozone effects can be added to those based
on C-R functions for PM without double counting. In the case of short-term exposure endpoints,
the risks of doing so to any substantial extent are small because PM and ozone concentrations
tend to be the least correlated of the criteria pollutants. For some endpoints, it will be possible to
estimate risk ratios from two-pollutant (ozone and PM) models, where the estimate for each is
adjusted for the other. This is one technique, albeit with some remaining possibility for
misattribution, to minimize the possibility of double counting. However, since the co-variation
of PM and ozone is often low, this is not a requirement. Several studies now suggest that daily
exposure to ozone is associated with both daily mortality and morbidity, such as hospital
admissions. Some of these findings have been demonstrated in season-specific analysis (Samet
et al., 2000), which could then be used in the Section 812 Analysis. The HES urges caution,
however, in basing estimates on C-R functions derived solely from studies conducted in the
northeastern U.S. and southeastern Canada, where ozone and sulfates tend to be highly
correlated. To the extent that pollution-specific evidence is drawn from data where the
correlations between the pollutants are low, HES suggests that ozone-specific estimates be
included in the aggregate estimates.
In the case of long-term exposures and mortality, EPA has correctly decided not to
attribute any mortality effects to long-term exposure to ozone given the lack of any evidence
supporting an independent effect. The Pope et al., 2002 follow-up study found no association
between mortality and long-term average ambient ozone concentration.
3.1.2. Source-Specific Concentration-Response fC-R) Functions.
Regarding the term "C-R functions," the Subcommittee notes that Chapter 6 (e.g. pages
6-1 and 6-2) uses the term C-R functions interchangeably for: 1) the concentration-response
function epidemiologic studies used to quantify the association and 2) the "impact function" or
"attributable case function." This latter function not only uses the epidemiology-based C-R
function, but also the pollution level, the population size, and the baseline frequency of the
-------
outcome as input. The Subcommittee advises not to use one term for both, as this creates
confusion in discussions of various aspects, including uncertainties (e.g., a subsequent "impact
function" faces more uncertainties than the constituent C-R function).
There are only a few source-specific C-R functions currently available for species of PM
and the Agency does not propose to use them in the Section 812 Analysis. For example, Laden
et al. (2000), using source apportionment in the Boston area concluded that traffic-related
pollutants and coal combustion-related particles were significantly related to short-term
mortality, while soil-derived particles were not, with traffic-related particles having the largest
effect. Hoek et a!. (2000) concluded that annual mortality was significantly related to proximity
to heavily traveled roadways, particularly for those with high volumes of truck traffic. However,
for the application of these studies to the 812 Analysis, one would also need the exposure
distribution data for these source-specific surrogates for the U.S., which are not readily available.
Thus, it is still appropriate to make calculations based on PM2.5 or PM10, rather than source-
specific PM. It is important, however, to describe what the most important sources are for PM.
Specifically, it would be of interest to provide estimates of the contributions of various sources to
the ambient PM, including both primary and secondary processes. The health impact of a
specific source may be larger or smaller than its relative contribution to the ambient PM
concentration, as toxicities may be source dependent. This should also be discussed in the
Agency's analysis.
The issue of a special role for traffic-related air pollution is complicated by the strong
spatial gradient of primary pollutants from traffic sources. Studies around California freeways
indicated that ultrafine particle numbers can vary by an order of magnitude within 100 meters,
carbon monoxide and nitrogen oxides by somewhat smaller ratios, while PM2.5 mass, which is
dominated by regional background, shows little variation with proximity to traffic (Zhu et al.,
2002). Furthermore, regional ambient ozone is greatly reduced near the freeway due to its
scavenging by nitric oxide. These spatial variations are important for some health effects.
Recent animal inhalation studies conducted at varying distances from a freeway show effects for
close-in animals not seen for animals exposed at greater distances (Lippmann et al., 2003).
These studies complement the observations of human populations in relation to roadway
proximity (Hoek et al., 2002, Laden et al., 2000, Venn et al., 2001).
The cost-benefit analyses for 812 cannot quantitatively address this issue of traffic-
related pollution effects because its grid-based exposure estimates are based on much larger
spatial elements. The available database remains inadequate for the disaggregation of
concentration-response relationships by pollutant source category. However, the HES
recommends that the Second Prospective 812 Analysis consider conducting some sensitivity
analysis that incorporates the limited information on relative toxicities.
3.1.3. Extrapolation to Other Age Groups.
For mortality associated with long-term pollution exposure, extrapolation of the C-R
relations to adult age groups younger than those studied in the epidemiologic reports would be
unnecessary. For long-term exposure related endpoints, the baseline frequency increases rapidly
6
-------
with age and the public health impact for adult ages below about 30 can be expected to be too
small to significantly affect the totals obtained from the listed C-R functions. An exception to
this would be made if the Harvard six-city cohort (Dockery et al., 1993) were used in a
sensitivity analysis, since this cohort included participants who were age 25 and above.
For health effects other than mortality, EPA should strongly consider broadening the age
ranges beyond those included in the original studies that established the risk coefficients. In
general, the age ranges studied were limited more by population access or study design
considerations than by real restrictions on effects to the age group studied. Therefore, the age
range should be expanded where there is some reasonable physiological basis for expecting that
the effects occur among a wider range of ages (e.g., applying C-R functions to all children rather
than just the ages of school children in the original study).
3.1.4. Exposure Assessment (Use of Grids).
The exposure assessment approach utilizes the best available data and models. However,
uncertainties remain large in this area - and the magnitude of these uncertainties will require
careful characterization in the Second Prospective Analysis. Important uncertainties arise in the
translation of modeling results to population-relevant concentration estimates. In the case of
ozone, the procedure involves modeling three multi-day episodes for the eastern U.S. and two
multi-day episodes in the western U.S. Each episode is approximately of duration of one to two
weeks. These brief modeling results are then extrapolated to the entire ozone season by
reference to observed data available from AIRS. The result is a grid of 12x12 km hourly (ozone)
concentration estimates that cover this continental U.S. EPA should work towards extending the
modeling so that it covers longer, more representative periods, with less reliance on temporal
extrapolation. In addition, there is a need to estimate uncertainties associated with this
extrapolation.
Block-level data from the 2000 U.S. Census are used to develop population estimates
corresponding to the grid resolution of each air quality model (e.g. 12x12 km for ozone). Health
impacts are then estimated by applying epidemiologically derived C-R functions to the
concentration, population, and baseline outcome rates for each grid. There is some question
about the impacts of using these grid average concentration estimates as inputs to C-R functions
which were derived from epidemiology studies in which a different sort of exposure measure is
used (i.e., the concentrations at one or several population-oriented monitors across a
metropolitan area). There may not be a problem since both the pre- and post-control scenarios
use the same (potentially biased) configuration. However, this should be discussed and verified.
Center-city monitors may over-estimate some population exposures in epidemiology studies
whereas the gridded concentrations provide a broader, area-wide exposure estimate. The
Subcommittee suggests that EPA do a sensitivity analysis in which the health assessment is
repeated using the mean of the estimated concentrations for the grids in which monitors are
located in a selected urban area, for example. This could be compared to the standard
assessment results to see how big the differences are.
-------
The Subcommittee also wishes to emphasize the need for efforts to improve exposure
modeling and health assessment for people living near roadways and other local sources. A
growing literature has emphasized the importance of roadway proximity as a risk factor for both
elevated exposures and adverse health outcomes (Zhu et al., 2002; Brunekreef et al., 1997; Hoek
et al., 2000).
3.1.5. Infant effects.
The Subcommittee proposes that EPA include effects of air pollution on infant mortality
rates in the base estimates. In recent years, several international studies addressed the
association of ambient air pollution and death during the first year of life. The outcome has also
been included in the 2002 World Health Organization Global Burden of Disease study on
ambient air (Ezzati et al., 2002). The WHO report relied on several time-series studies that relate
daily exposures to PM to mortality for children under age five. The findings of effects of
ambient air pollutants on respiratory inflammation in children support the evidence of effects on .
infants where respiratory infections are a major cause of infant deaths. The evidence for air
pollutants to promote respiratory infections in infants has recently been corroborated (Belanger
et al., 2003). A further argument to include infant mortality is the availability of effect estimates
from a large U.S. cohort study conducted by Woodruff et al. (1997). It is based on ~4 million
infants born 1989-91 in 86 metropolitan areas. Exposure was defined as the mean outdoor PMIO
levels for the first two months of life. Woodruff et al. controlled for some individual risk factors
for infant mortality (i.e., maternal education, maternal ethnicity, parental marital status, maternal
smoking during pregnancy) and other potential confounders (i.e., infants' month and year of
birth, average temperature during first 2 months of life). They found that postneonatal mortality
from all causes (excluding violent death) increased by 4% (95% confidence interval [CI] 2-7%)
for every 10 ug/m3 PMIO. Sudden infant death syndrome (SIDS) and respiratory disease deaths
in infants with normal birth weight increased by 12% (95% CI 7-17%) and 20% (95% CI 6-36%)
for every 10ug/m3 PMIO, respectively.
The Subcommittee also notes a re-analysis of Lipfert (2000) that partly confirmed
associations (for PMIO only). He used all U.S. infants born in 1990. However, exposure
assignment was a larger non-systematic source of error in this study, as the annual 1990 mean
was assigned to each infant, thus including pre- and post-mortem air quality data. The HES
therefore recommends using the available cohort and cross-sectional studies (Woodruff et a!.,
1997, Chay and Greenstone, 2001) and the time-series studies to derive quantitative estimates of
infant mortality.
Unfortunately, it is difficult to estimate the lost years of life associated with these deaths.
In the most extreme case, each air pollution-related infant death loses the total years of life (life
expectancy at birth). In the other extreme, one may hypothesize that all these infants were
susceptible for death at a young age no matter what levels of air pollution they would experience
in the first weeks of life (harvesting only). In the latter case, air pollution would be considered of
limited public health relevance for this outcome. So far, no infant mortality study has formally
addressed the issue of harvesting. Therefore, the number of life-years lost among infants is not
known. This range of uncertainty needs to be addressed as part of the uncertainty analysis.
8
-------
The Subcommittee also notes that the reference to Kaiser et al. (2001) in the Analytic
Plan is misleading. Kaiser et al. is not a study that investigates the association of air pollution
with infant mortality. It is, however, a published abstract of an impact assessment that estimated
the air-pollution-related burden of infant mortality. The assessment used the Woodruff et al.
study as input information.
3.1.6. Asthma,
The Subcommittee proposes that EPA include asthma exacerbations for children and
adults in the base case. The evidence for adverse effects of ambient air pollution, particularly PM
and ozone, among asthmatics is sufficient to include it in the benefits analyses. On the other
hand, the association of new onset of asthma (incidence of doctor's diagnosed asthma) is
currently less clear and probably a more complex issue of interacting environmental and genetic
factors. Thus, the Subcommittee suggests not including new onset of asthma in the base case
assessment at this time. The Subcommittee advises the Agency not to use the term "chronic
asthma." Asthma is, by definition, a chronic obstructive disease with the level of obstruction
being a function of exposure to various triggers, including air pollution. "New onset of asthma;"
"incidence of physician-diagnosed asthma;" "prevalence of doctor's diagnosed asthma," etc., are
more appropriate terms.
The Subcommittee acknowledges that dealing with asthma exacerbations is a challenge
in the context of benefits assessment for the 812 Analysis. The definition of an asthma
exacerbation varies across studies, and is partly determined by study design. Panel studies are
able to monitor daily onset of symptoms or medication use, whereas cross-sectional or cohort
studies usually ask about the occurrence or frequency of symptoms during the past year.
Although ali these approaches are useful avenues for epidemiological investigation, the
methodological differences among studies make it difficult to apply their results for benefits
assessments.
The difficulties are not primarily related to the choices of C-R functions but rather to the
definition and the respective derivation of an appropriate background frequency of asthma
attacks, and the assignment of a monetary value. The latter may depend on the severity of an
exacerbation. Neither asthma nor exacerbations are consistently defined in air pollution studies.
Nevertheless, the Subcommittee recommends that the Agency include asthma exacerbation in the
base case and rely on panel studies to derive a C-R function. In the selection of a C-R function
for asthma, the Subcommittee recommends selection of studies that have comparable design as
well as similar baseline frequencies for both asthma prevalence and exacerbation rates. Among
such a set of studies, C-R functions and background rates of exacerbations may be estimated
(with distributions) for use in the 812 Analysis. The distributions of these parameters may be
part of the uncertainty assessment. In the absence of population-based background frequency
data, EPA may consider the use of frequency information provided in the studies used to derive
the C-R function. Given the internal consistency of these studies, this choice may be more
appropriate, thereby limiting uncertainties. The selection of studies used for the derivation of C-
R functions and background frequencies may include more recent publications from western
9
-------
European studies, if those studies appear in the peer-reviewed literature. This may lead to a
larger number of studies with comparable designs and, thus, more consistent results.
The determination of the age range for the quantification of asthma attacks or symptoms
may be less restrictive than for other outcomes. The HES recommends in particular that the
Agency consider extrapolating results to a wider age range than the original asthma studies in
children. Studies in children usually restrict age ranges based on logistic rather than
pathophysiologic reasons. The Committee considers it unlikely that exacerbations of symptoms
observed in children age 11, for example, would not be observed among somewhat older or
younger children. Thus, for the quantification of symptoms in children it is recommended to
apply CR-functions to all children age 6 to 18. The exclusion of younger children is based on
the uncertainty in the definition of asthma in early life, the exacerbation thereof, and the related
CR-function for air pollution.
One may assume that, among asthmatics, a day with an exacerbation would likely also be
a day of restricted activity. Thus, the estimate of days with asthma exacerbation could be
subtracted from days with restricted activity to avoid double counting. Clearly, however, the
monetary valuation of these two outcomes may be different.
In the absence of independent response functions for PM and ozone, the Subcommittee
recommends the Agency use only one pollutant as a surrogate for the whole effect, although this
may underestimate the overall effect on asthmatics. This recommendation is in contrast to the
recommendation the HES makes for hospital admissions, where effects from both particles and
ozone should be estimated. This recommendation relating to asthma reflects the fact that there
are many more single- and multi-pollutant studies available for hospital admissions than there
are comparable studies on asthma attacks. This may, however, change in the future as more
multi-pollutant studies on asthma exacerbations are published or cities with low correlations
between ozone and PM are examined. This.recommendation is based on the concern that
potential double counting be avoided and should not be interpreted as implying that only one of
these pollutants contributes to asthma exacerbations.
The 812 report should mention that the social costs of the effect of pollution on those
with asthma are most likely underestimated since the epidemiological studies do not incorporate
the treatment and averting behavior asthmatics may engage in to mitigate the adverse effects of
air pollution.
3.1.7. Effects of the SONOCO Suite.
As outlined in Exhibit 6-1 in the Analytical Plan, a few selected endpoints for Sulfur
Dioxide (SO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO) (the SONOCO Suite) will be
quantified and monetized, and a few have been selected for sensitivity analyses. The HES
concurs with the use of the C-R functions as used in the First Prospective Study as the best
available estimates since little, if any, new work has been reported and also concurs with the plan
to update these functions as new information becomes available during the 812 process. In
supporting the quantification of some endpoints in relation, to the SONOCO gases, the HES is
10
-------
not taking a view on causality or biological plausibility of these specific pollutants. Rather, the
Subcommittee is assuming that, where they are used, C-R functions for these pollutants are
quantifying adverse effects of some aspects of the pollution mixture which are not already taken
into account via C-R functions in PM or ozone. Where C-R functions are used for each of the
three gases, e.g., for respiratory hospital admissions, the HES asks that the possibility of double
counting be considered and discussed whenever the analysis involves aggregating across all
pollutants that have been quantified.
The HES advises that the Agency provide an expanded discussion of the following points
concerning the Analysis. With regard to SO2, the HES notes that Pope et al. (2002) show
mortality associations for sulfur oxides, albeit there are also associations between SO2 and non-
cardiopulmonary deaths as well. The HES advises that the Agency discuss the pros and cons of
possible inclusion of sulfur dioxide and mortality from longer-term exposure. With regard to
nitrogen dioxide, European short-term effect studies suggest an interaction with PM (i.e., PM
effects are increased in the presence of NOa, and NCh is significantly associated with increased
respiratory infections). It is not clear whether these will be included in the analysis. Interaction
between pollutants is not discussed (i.e., ozone and N02 have more than additive effects in some
toxicological studies). Finally, with regard to CO, the Subcommittee asks the Agency to
consider and discuss whether non-asthma ER visits for respiratory or cardiovascular causes
should be moved to the base case analysis.
3.2. Agency Charge Question 12: Endpoints for Particulate Matter and Ozone.
Charge Question 12. EPA seeks advice from the Council regarding the technical and scientific
merits of incorporating several new or revised endpoint treatments in the current analysis. These
health effect endpoints include:
a. Premature mortality from paniculate matter in adults 30 and over, PM (Krewski
et ah, 2000);
b. A PM premature mortality supplemental-calculation for adults 30 and over using
the Pope 2002 ACS follow-up study with regional controls;
c. Hospital admissions for all cardiovascular causes in adults 20-64, PM
(Moolgavkar et a!., 2000);
d. ER visits for asthma in children 0-18, PM (Norris et al., 1999);
e. Non-fatal heart attacks, adults over 30, PM (Peters et al., 2001);
f. School loss days, Ozone (Gilliland et al., 2001; Chen et al., 2000);
g. Hospital admissions for all respiratory causes in children under 2, Ozone (Burnett
etal., 2001); and
11
-------
h. Revised sources for concentration-response functions for hospital admission for
pneumonia, COPD, and total cardiovascular: Samet et al., 2000 (a.PM10 study),
to Lippmann et al., 2000 and Moolgavkar, 2000 (PM2.5 studies).
HES Response: The HES comments regarding new endpoints used for paniculate matter
and ozone appear immediately below in separate sections
3.2.1. New and Revised Endpoints for Particulate Matter.
The HES generally supports the incorporation of the new and revised endpoints as
indicated in charge question 12. However, some modifications are suggested, specifically:
a. The Pope et al. (2002) results should be used for the base estimate of premature
mortality, rather than the Krewski et al. (2000). As indicated below, the Pope et
al. data set adds nine years of data to the follow-up period, and additional
exposure data. Some of the authors are the same as in the original Dockery et al.
(1993) study and the Krewski et al. (2000) study, so they benefit from the insight
gained by the Krewski reanalysis. In addition, the HES recommends using the
risk estimates resulting from using all the years of exposure data, since this may
serve to reduce measurement error. Sensitivity analysis for this endpoint could
use other estimates (Pope et al., 2002; Krewski et al., 2000; and/or the results of
Dockery et al., 1993). Whichever is used, the choice should be explained in the
Agency's assessment.
b. Estimates for hospital admissions studies (c and h) should utilize the large number
of studies relating PM10 to both respiratory and cardiovascular admissions rather
than simply rely on the Moolgavkar et al. (2000) and the Lippmann et al. (2000)
studies of PM2.5. Estimates should be based on a meta-analysis of these studies
conducted in multiple cites throughout the U.S. Such a meta-analysis would
represent a broader range of conditions, co-pollutants, and climates than does
reliance on any single study. In addition, the studies using PM10 incorporate the
potential effects of coarse, as well as fine, particles. In the case of analysis related
specifically to PM2.5, the use of the above PM2.5-based studies is recommended
if their impact is appreciably different from the results obtained by using the
PMlO-specific studies, adjusted for PM2.5.
c. As discussed above in Charge Question 11, several other endpoints should be
added to the base case analysis including: 1) asthma exacerbations and PM; and
2) infant mortality and PM so that the base case will be more reflective of the
comprehensive scientific analysis of health benefits that the Clean Air Act
requires. In addition, as indicated above, the HES recommends that the age
categories for the applied effects be increased when it is reasonable.
The Subcommittee also notes that EPA has five criteria to select C-R functions (page 6-
10, top). The HES requests EPA to provide more explanation of how criterion 5 (biological
12
-------
plausibility) was applied. The Analytical Plan did not contain sufficient information to allow the
HES to assess use of this criterion.
3.2.2. New and Revised Ozone Endpoints.
The Subcommittee concurs with EPA's two new endpoints related to ozone exposure.
Gilliland et al. (2001) demonstrated acute associations between ozone and increased illness-
related school absences among children enrolled in the California Children's Health Study. The
study methods were thorough in terms of population characterization, exposure assessment and
outcome assessment. One additional study (Burnett et al., 2001), supports an increase in
respiratory hospital admissions for children under 2 years of age in relation to short-term ozone
exposures.
3.3. Agency Charge Question 13: Baseline Data.
Agency Charge Question 13: EPA seeks advice from the Council regarding the merits of
applying updated data for baseline health effect incidences, prevalence rates, and other
population characteristics as described in chapter 6. These updated incidence/prevalence data
include:
a. Updated county-level mortality rates (all-cause, non-accidental, cardiopulmonary,
lung cancer, COPD) from 1994-1996 to 1996-1998 using the CDC Wonder
Database;
b. Updated hospitalization rates from 1994 to 1999 and switched from national rates
to regional rates using 1999 National Hospital Discharge Survey results;
c. Developed regional emergency room visit rates using results of the 2000 National
Hospital Ambulatory Medical Care Survey;
d. -Updated prevalence of asthma and chronic bronchitis to 1999 using results of the
National Health Interview Survey (NHIS), as reported by the American Lung
Association (ALA), (2002);
e. Developed non-fatal heart attack incidence rates based on National Hospital
Discharge Survey results;
f. Updated the national acute bronchitis incidence rate using NHIS data as reported
in ALA (2002), Table 11;
g. Updated the work loss days rate using the 1996 NHIS data, as reported in Adams
etal. (1999), Table 41;
13
-------
h. Developed school absence rates using data from the National Center for
Education Statistics and the 1996 NHIS, as reported in Adams, et al. (1999),
Table 46.
i. Developed baseline incidence rates for respiratory symptoms in asthmatics, based
on epidemiological studies (Ostro et al., 2001; Vedal et al., 1998; Yu et al.; 2000;
McConnell et al., 1999; Pope et al., 1991).
HES Response: Overall, the Subcommittee commends the EPA for its efforts to identify
appropriate databases to update and strengthen population characteristics and health outcome
rates. There are some problems, however, that remain with the data sources and the use of the
data that need to be considered in further detail before the plan is implemented. The HES
highlights the major issues in comments here.
Fundamentally, baseline incidence rates are multipliers in the estimation of some health
effects and therefore have a direct influence on the estimation of effects and potential benefits.
In the first prospective analysis, preference was given to baseline incidence data at the county
level, followed by national-level data. If those were not available, baseline incidence data for the
study population were used to derive the impact functions. The primary data sources were the
1990 U.S. Vital Statistics and the 1997 National Hospital Discharge Survey (NHDS) of the
Centers for Disease Control and Prevention. For the second prospective analysis, the baseline
incidences will be adapted to match the specific populations studied and additional sources of
information at the regional level are included for hospitalization rates and emergency room
visits. These additions can be of some help in improving the accuracy of benefits calculations by
location.
The Subcommittee also notes that mortality and morbidity rates may change over time
for at least two different reasons: either because of changes in underlying age-specific disease
rates or because of changes hi the age structure of the population. Therefore, there is a need for
the Agency to carefully consider the potential impacts of changing age structure on mortality and
morbidity estimates. On page 6-15 -of the Analytical Plan, paragraph 1, line 6, the Agency states,
"baseline incidence rates. ..may decline slightly over time" without stating clearly which factors
are involved in making this assumptions.
The HES notes that there are several factors to consider, in addition to age, that can alter
incidence rates over time and recommends that EPA discuss these factors. For example,
demographic changes such as increasing proportions of minorities, and economic factors may
lead to decreasing health care access that may also increase baseline rates.
Although EPA states, "we will not attempt to estimate changes in baseline incidence
rates," perhaps an analysis of rate trends retrospectively to 1990 or earlier could be useful in
ascertaining how such changes contribute to overall uncertainty. EPA should evaluate whether
there may be useful contrasts, between the incidence rates used in the first analysis and the
updated incidence rates that could shed some light on this issue.
14
-------
While many of the data sources selected for the second prospective analysis are
appropriate, some may need to be considered more thoroughly to appreciate their specific
limitations before use in the cost-benefit analysis. The following themes emerged from the HES
review of these data sources and exemplify the types of issues that need to be evaluated as EPA
develops its analytic plans:
a. The number of persons or health events included in some of the national surveys
may not be very large, particularly at the county level, as described in portions of
the draft analytical plan. For example, EPA's plan to work with more than one
year of the CDC Wonder data will help address this problem for many outcomes,
but "missing" data will probably remain for several of the outcomes. This
situation raises a question as to whether the use of particular health events may
introduce a high level of uncertainty into the analysis. At the present time, the
plan does not recognize this problem, discuss what level of "missing" data would
be judged as unacceptable, or explain what alternative outcome categories or data
sources would be used. The Subcommittee advises the Agency to distinguish
between: a) the spatial resolution at which the analysis is conducted, and b) the
spatial resolution at which results will be reported and conclusions will be drawn.
It is likely that results for small areas will be (much) less reliable than for bigger
ones, because often the small area input data will be average values from wider
geographical regions, applied to all small subareas of that region.
b. Selecting specific diagnostic codes within broad health outcome categories, as
planned, is expected to provide health outcome estimates that can be more closely
linked to the results of epidemiological studies. However, if in the efforts to
achieve a match, the outcome specification is too narrow (e.g., "acute bronchitis"
instead of "all respiratory conditions"), small numbers will seriously reduce the
reliability of the analysis. Therefore, careful consideration of the diagnostic codes
to use (with the related tradeoffs in uncertainty) will be an important step in
constructing the baseline data sets.
c. Additionally, there is concern that reliance on poorly defined diagnostic
categories wil! result in estimates with a high degree of error. Examples of such
categories or diagnoses include acute and chronic bronchitis, asthma
exacerbation, school absence, etc. In these cases, the national data set definitions
should be compared to the definitions used in epidemiological studies and a
determination made as to whether the national sources will provide comparable
outcome data. If the definitional differences are large, it may be more prudent to
use the epidemiological studies to construct baseline rates, depending in part on
the size of the baseline epidemiological studies and the representativeness of their
populations.
d. The design of the national databases relies on complex sampling schemes that
may or may not include sizable populations at risk for air pollution-related health
effects. For example, the NHDS and the National Hospital Ambulatory Medical
15
-------
Care Survey (NHAMCS) use sampling designs that exclude specific types of
hospitals and, as a result, exclude potentially sizable segments of the U.S.
population (e.g., military and institutionalized persons). These groups may be at
increased risk for important adverse outcomes of interest (e.g., heart attacks,
chronic bronchitis, cancers, etc.), which would then be undercounted by relying
solely on the identified national data sets. Omitting these groups would bias the
prevalence downwards and result in lower effect estimates. For outcomes where
the exclusions may result in significant underestimates, careful consideration
should be given to identifying additional data sources (e.g., databases for
institutionalized persons, or the health care databases of the U.S. Department of
Defense and/or Veterans Affairs) for otherwise excluded populations.
Additionally, the HES recommends that EPA seek expert consultation from the
National Center for Health Statistics (NCHS) for in-depth information about the
design of the selected databases and the limitations that need to be considered
when applying the data for EPA's estimation purposes.3
e. The use of 1999 data from the NHIS may present problems in the analysis.
Despite the advantages of having supplemental data on asthma outcomes, the
1999 survey relies on an unusually small sample size. This important limitation
will probably result in "missing" data especially for county-level purposes.
Whether the sample is so small that it will result in unreliable rates and thereby
prevent the use of this year of data, or whether its use only for specific analyses
may be appropriate, needs to be determined. If this year of data turns out to be
unacceptable, the use of a more recent year with a larger sample size is
recommended. The data may be sufficient for national or statewide conclusions,
but not for small-area conclusions. The Subcommittee asks EPA to consider the
extent to which the analysis will be reported and interpreted at finer geographical
resolution.
f. The methods planned to construct the work loss and school absence rates are not
clear i&the documentation reviewed by the HES. For example, it is not clear.
which health condition(s) on the cited Tables 41 and 46 will be used or what level
of relative standard errors will be judged as acceptable for estimation purposes.
Additionally, which National Center for Education Statistics (U.S. Dept. of
Education) data will be used in combination with which NHIS data is not clear.
g. The epidemiological studies listed for developing the pediatric asthma symptom
rates as a group provide good evidence. However, these studies depend on self-
reported outcome data with little or no assessment of the reliability of the data;
EPA should explore this issue with the authors. EPA is encouraged to contact the
authors to obtain their judgments and any evidence or analyses on the reliability
of the self-reported outcome data in their studies. Authors sometimes collect data
for variables known to relate well to variables that are more subjective. When
3 The Center's experts can be reached through www.cdc.gov/nchs/ or 301-458-4636.
16
-------
there are stable relationships between such variables, their correlation can be used
to assess the reliability of the more subjective data. It would be useful to
determine whether the authors have data that were or could be used to assess
reliability; if not, then their best judgments of the self-reported data's reliability
should be obtained.
The HES also noted that all of these papers studied populations living in the western
United States. This observation raised the question as to whether the air pollution mix and/or the
characteristics of the populations studied need to be evaluated to determine how relevant the
results are for the entire U.S. population. Application of these epidemiological data to the entire
country may introduce additional uncertainty.
3.4. Agency Charge Question 14: Scientific merits of alternative methods to expert
elicitation for estimating the incidences of PM-related premature mortality.
Charge Question 14. EPA plans to initiate an expert elicitation process to develop a
probability-based method for estimating changes in incidence of PM-related premature mortality.
Plans for this expert elicitation are described in chapter 9 of this blueprint, and a separate charge
question below requests advice from the Council pertaining to the merits of the design of this
expert elicitation. EPA recognizes, however, the possibility that this expert elicitation process
may not be fully successful and/or may not be completed in time to support the current 812
analysis. Therefore, in order to facilitate effective planning and execution of the early analytical
steps that provide inputs to the concentration-response calculations, EPA seeks advice from the
Council regarding the scientific merits of alternative methods for estimating the incidences of
PM-related premature mortality, including advice pertaining to the most scientifically defensible
choices for the following specific factors:
a. Use of cohort mortality studies, daily mortality studies, or some combination of
the two types of studies;
b. Selection of specific studies for estimating long-term and/or short-term mortality
effects;
c. Methods for addressing -either quantitatively or qualitatively- uncertain factors
associated with the relevant concentration-response function(s), including
1. Shape of the PM mortality C-R function (e.g., existence of a threshold),
2. PM causality,
3. PM component relative toxicity, and
4. PM mortality effect cessation lag structure
5. Cause of death and underlying health conditions for individuals dying
prematurely due to chronic and/or short-term exposures to particulate
matter
17
-------
6. The use of ambient measures of exposure for estimating chronic health
effects, given recent research reviewed in the NAS (2002) report that
questions the implications of using ambient measures in cohort studies
HES Response: The Subcommittee notes that there is some overlap between this Charge
Question and Charge Questions 16,17 and 29. HES recommendations regarding C-R functions
for PM also affect recommendations on expert elicitation and alternatives to expert elicitation.
Those recommendations will be discussed in response to Charge Question 29. The response to
Charge Question 16 will address the cessation lag issue and the response to Charge Question 17
will address the question of alternative estimates.
The Subcommittee agrees with EPA's current proposal to use cohort-based estimates in
the base case. Different cohort studies and, within each study, various C-R functions are
available, using different causes of death, exposure windows, subgroups, and models. The HES
concludes that the base case should use the Pope et al. (2002) study, which relies on a larger
number of deaths and longer follow-up of the American Cancer Society (ACS) cohort than does
Pope et al. (1995) or its HEI reanalysis (Krewski et al, 2000). In addition, this analysis profited
from the extensive experience and review process of Krewski et al. (2000), two of whose key
authors (Krewski, Burnett) are also co-authors of Pope et al. (2002). The HES proposes that
EPA use total mortality estimates. The cause-specific estimates can be used to communicate the
relative contribution of the main air pollution related causes of death. The HES, however,
recommends that EPA not primarily use cause-specific estimates, given the larger uncertainties
in these estimates. The estimates originate from a smaller number of cases with potential errors
in coding of causes of death.
In the Analytical Plan, EPA makes good arguments for the use of the ACS cohort for the
base case. However, the HES recommends modification in the way ACS and the Harvard 6-
Cities Studies are compared (e.g., in Appendix D). ACS has some inherent deficiencies, in
particular the imprecise exposure data, and the non-representative (albeit very large) population.
Thus, ACS is not necessarily "the better study," but, at this point in time, is a prudent choice for
the base case estimates in the Second Prospective Analysis. The Harvard Six-Cities C-R
functions are valid estimates on a more representative, although geographically selected,
population, and its updated analysis has not yet been published. The Six Cities estimates may be
used in a sensitivity analysis to demonstrate that with different but also plausible selection
criteria for C-R functions, benefits may be considerably larger than suggested by the ACS study.
The not-yet-published updated estimates of the expanded Harvard follow-up will be particularly
useful for this purpose if and when they are accepted for publication in a peer-reviewed journal.
The Subcommittee had several discussions about the use of time-series based mortality
functions. In line with published work on this issue, the HES would like to emphasize the
importance of understanding and communicating the fundamental differences in the outcome of
these studies as compared to cohort studies.
To estimate the full range of the contribution of air pollution to all processes that
ultimately contribute to shortening in life expectancy one needs to follow large cohorts over
18
-------
many years to measure the association of the exposure experience with the person-time in the
population. ACS is an example of this approach. Although ACS published the data in the "case
domain" (body counts), the underlying model uses person-year information (or survival time).
Time series studies, on the other hand, estimate specifically the number of premature
deaths affected by the exposure conditions shortly before death. The approach counts deaths
rather than person-time, thus, it does not provide direct information about the lost time of life
among these deaths. The Subcommittee therefore reminds the Agency that any assumption
about the amount of time lost among these acute effect cases is a matter of judgment. The only
information that can be derived from the time-series literature is the evidence that the lost time
appears to be very short (harvesting) for only a small fraction of the deaths.
Although cohort studies can be considered to measure the full range of person-time lost
due to all kinds of effects of air pollution, this assumption is only theoretically true. Due to
methodological Jimitations, the currently available cohort studies may most likely miss part of
the time lost or the attributable cases (Kunzli, Medina et al., 2001; Martuzzi, 2001). Because of
the limited amount of exposure data, these studies are unlikely to capture the mortality effects of
specific short-term exposure patterns or the long-term mortality consequences of exposures in
early lifetime (unless the intra-city exposures in early life are highly correlated with those
exposures measured primarily during middle age). The studies of early lifetime exposure
suggest impaired lung function growth and accelerated decline in areas with higher pollution and
strongly support the notion of chronic effects. Lung function is one of the strongest long-term
predictors of life expectancy. Therefore, the findings on reduced lung function in children and
adults are consistent with the shorter life expectancies as observed in the cohort studies.
The studies of long-term exposure may also fail to fully capture those deaths that lose
only a short time period. The times-series approach has the advantage of capturing all deaths
associated with short-term changes, regardless of the amount of lifetime lost. Thus, it is
conceivable that the total air pollution-related death toll may be the sum of the cases derived
from cohort studies plus some unknown fraction of those cases derived from time-series
estimates. The overlap in these two quantities is not known. In addition,.if there is non-
differential exposure misclassification, it would likely lead to an underestimation of the effects.
In the'base case, the HES proposes that EPA assume full overlap, i.e., to ignore the additional
short-term cases in the benefit analysis. This interpretation of the literature captures the full
effect for which there is substantial quantitative evidence but avoids making assumptions that
might substantially overstate or double count the effects. In the sensitivity analysis or the expert
elicitation, other probabilities of the overlap could be considered. However, the HES also
suggests that mortality estimates based on the time-series studies alone be presented to inform
the public of the implications of these studies. The advantage of these cases is that they reflect
the portion of the problem that is expected to be resolved 'immediately1 with improved air
quality, whereas the uncertainty around lag time to full benefits is much larger for the chronic
effect cases. Time-series studies with distributed lag models take this possibility into account
and, thus, provide the C-R functions of choice to characterize the full range of short-term effects.
These short-term estimates may utilize recent evidence of stronger effects from cumulative
19
-------
exposure, but should not be added to or substituted for the effects developed from the cohort
studies.
The Subcommittee agrees that the whole range of uncertainties, such as the questions of
causality, shape of C-R functions and thresholds, relative toxicity, years of life lost, cessation lag
structure, cause of death, biologic pathways, or susceptibilities may be viewed differently for
acute effects versus long-term effects.
For the studies of long-term exposure, the HES notes that Krewski et al. (2000) have
conducted the most careful work on this issue. They report that the associations between PM2.5
and both all-cause and cardiopulmonary mortality were near linear within the.relevant ranges,
with no apparent threshold. Graphical analyses of these studies (Dockery et al., 1993, Figure 3
and Krewski et al., 2000, page 162) also suggest a continuum of effects down to lower levels.
Therefore, it is reasonable for EPA to assume a no threshold model down to, at least, the low end
of the concentrations reported in the studies.
Regarding the question of component relative toxicity, the evidence at this time
supporting differential toxicities based on particle chemistry is provided by a few studies of
short-term exposure (e.g., Laden et al., 2000). Currently, there is little evidence from the long-
term exposure studies to suggest differential toxicity. Therefore, it is appropriate at this time for
EPA to assume equal toxicity across particle components and it is reasonable to explore
alternative possible implications of differential particle component potency in supplementary
sensitivity analyses.
3.5. Agency Charge Question 15; Alternative Analysis for PM Control.
Charge Question 15. EPA estimates of benefit from particulate control may
underestimate the impact of nonfatal cardiopulmonary events on premature mortality and life
expectancy. For the base analyses, which rely on cohort evidence, the limited follow-up periods
for the cohorts may not fully capture the impacts of nonfatal cardiovascular events on premature
mortality later in life. For the alternative analyses -including cost-effectiveness analyses-which
rely more on acute studies and life-expectancy loss, the years of life are estimated only for fatal
events. Yet nonfatal events such as myocardial infarction reduce a person's life expectancy by a
substantial percentage.
a. Do you agree that EPA, in the 812 analyses, should adjust benefit estimates to
account for the mortality effects of non-fatal cardiovascular and respiratory
events?
b. What medical studies and mathematical models of disease might be useful to
review or use if EPA moves in this direction?
c. When the nonfatal events are valued in economic terms, should EPA assume that
the published unit values for morbidity already account for the life-expectancy
20
-------
loss or should an explicit effort be made to monetize the resulting longevity
losses?
HES Response: In regard to Question 15.a., a reasonable presumption to make is that the
cohort mortality studies capture the full effect of PM on mortality and it would not be
appropriate to add additional mortality effects that might be associated with quantified PM
morbidity effects such as nonfatal heart attack or chronic bronchitis. As noted above (see
response to Charge Question 14), some effects may be omitted in the cohort results. These
omissions might be for those individuals with very short life expectancy (very short-term shift in
timing of death), or those associated with very long-term or distant past exposures (beyond the
time frame of the cohort or due to increased measurement error from cohort member migration).
If short-term exposure mortality studies were to be used as the basis of mortality
estimates and if the cohort study estimates were being ignored, then it would be appropriate to
add mortality effects of PM-induced chronic illnesses. However, in response to Charge Question
14 above, the HES has strongly advised against ignoring the cohort study estimates.
The HES also discussed Quality Adjusted Life Year (QALY) estimates for cohort study-
based mortality. The question is how the morbidity period that precedes death might be
considered. The cohort study results do not tell us to what extent PM causes the ongoing disease
that ultimately leads to death versus aggravating an already existing disease, but the HES sees
from the morbidity studies that PM is a risk factor for onset of new chronic disease, at least for
chronic bronchitis. Models of disease, as discussed for question 15.b., might be helpful in
determining how to consider this. For some (uncertain) share of the deaths, PM is likely causing
the disease as well as the death.
In regard to question 15.b., the HES notes: a) that this is a conditional question (what
medical studies and mathematical models of disease might be useful to review or use, if EPA
moves in this direction), and b) that, with use of the cohort studies, it is not necessary to move in
this direction. Nevertheless, it is useful to consider the issue. The ideal basis for such estimates
would be fully validated quantitative causal models of chronic cardiovascular and respiratory
diseases, including contributions of air pollutants to both the chronic underlying disease
processes, and acute events that precipitate clinical manifestations such as myocardial infarctions
and arrhythmias associated with "sudden death." This ideal is not yet close to being realized.
However, some data and models can contribute to the construction of reasonable preliminary
assessments.
Some models can take the form of analogies with the prevention of fatal and nonfatal
cardiovascular events by other types of interventions—for example pharmacological
interventions such as cholesterol-lowering drugs. Long-term double-blind intervention studies
done for testing the efficacy and safety of these agents are the most secure basis for determining
health improvements that are causally related to specific risk-factor-related interventions,
although in some cases the length of follow-up may not be sufficient to provide ideal full-
lifetime evaluations.
21
-------
Longer follow-up is almost certainly possible by the use of long-term prospective
epidemiological observations of the relationships between specific cardiovascular risk factors
(e.g., fibrinogen levels, low FEVl levels, low heart rate variability) and both total mortality and
nonfatal cardiovascular and respiratory disease events. Such analogies may be considered
promising as each of these three biomarkers has both associations with ambient airborne particle
levels (Ackerman-Liebrich et al., 1997; Schwartz, 2001; Xu et al., 1991; Chestnut et al., 1991;
Pope et al., 1999; Gold et al., 2000) and significant independently predictive associations with
cardiovascular mortality (Knuiman et al.; 1999; James et al., 1999; Ryan et al., 1999; Lange et
al., 1990; Folsom et al.; 1997; Danesh et al., 1998; Huikuri et al., 1998; Tsuji et al., 1994; and
Klieger et al., 1987). To do these calculations, the long-term prospective cardiovascular
epidemiology observations would be used to construct life table models to indicate the long-term
changes in both non-fatal and fatal cardiovascular and respiratory events associated with specific
amounts of change in each biomarker across the range of age groups studied. From these
analogies, the amount of life shortening falling outside the follow-up limits of the air pollution
cohort studies could be estimated, as well as effects from birth provided that migration is not too
great, and the pollution ranking of cities has not changed considerably over time.
In the Global Burden of Disease report (Ezzati et al., 2002), WHO utilized other
techniques for estimating effects of chronic exposure prior to mortality. Therefore, HES also
recommends that these methods be investigated.
In regard to question 15.c., (Do unit values for morbidity reflect life expectancy loss?),
this will be further addressed by the Council, but in general, it depends on how the value
estimate was derived. Cost-of-illness estimates include life expectancy losses (which are valued
based on lost earnings/productivity) only if they are explicitly added. The values EPA is
currently using for hospital admissions and for non-fatal heart attack do not include anything for
life expectancy losses. Values for chronic bronchitis are based on a stated preference
(willingness to pay) study (Viscusi et al., 1991). Lifetime symptoms of chronic bronchitis were
described to respondents but nothing was mentioned about any potential reduced life expectancy.
Regarding the second part of Charge Question 15.c. (Should an explicit effort be made to
monetize the resulting longevity losses?), actual longevity losses from chronic disease will be
picked up by the cohort studies. If, as the HES advises, the cohort study estimates of mortality
are always included, then it would probably lead to double counting to incorporate the longevity
losses also in the valuation of chronic disease.
3.6. Agency Charge Question 16; Cessation Lag.
Charge Question 16. In recent EPA rulemakings, EPA's "base estimate" of benefit from
PM control has been based on cohort epidemiological studies that characterize the chronic
effects of pollution exposure on premature death as well as capturing a fraction of acute
premature mortality effects. If these chronic effects occur only after repeated, long-term
exposures, there could be a substantial latency period and associated cessation lag. As such, a
proper benefits analysis must consider any time delay between reductions in exposure and
reductions in mortality rates. For the acute effects, such as those considered in EPA's alternative
22
-------
benefit analyses, the delays between elevated exposure and death are short (less than two
months), and thus time-preference adjustments are not necessary.
a. In the previous 812 analysis and in recent rulemakings, EPA assumed a weighted
5-year time course of benefits in which 25% of the PM-related mortality benefits
were assumed to occur in the first and second year, and 16.7% were assumed to
occur in each of the remaining 3 years. Although this procedure was endorsed by
SAB, the recent NAS report (2002) found "little justification" for a 5-year time
course and recommended that a range of assumptions be made with associated
probabilities for their plausibility. Do you agree with the NAS report that EPA
should no longer use the deterministic, 5-year time course?
b. One alternative EPA is considering is to use a range of lag structures from 0 to
20-30 years, with the latter mentioned by NAS in reference to the Nyberg et al.
PM lung cancer study, with 10 or 15 years selected as the mid-point value until
more definitive information becomes available. If this simple approach is used,
should it be applied to the entire mortality association characterized in the cohort
studies, or only to the difference between the larger mortality effect characterized
in the cohort studies and the somewhat smaller effect found in the time series
studies of acute exposure? Should judgmental probabilities be applied to different
lags, as suggested by NAS?
c. Another option under consideration is to construct a 3-parameter Weibull
probability distribution for the population mean duration of the PM mortality
cessation lag. The Weibull distribution is commonly used to represent
probabilities based on expert judgment, with the 3-parameter version allowing the
shaping of the probability density function to match expected low, most likely,
and expected high values. EPA is still considering appropriate values for the low,
most likely, and expected high values -and therefore for the Weibull shape and
location parameters- and EPA is interested in any advice the Council wishes to
provide pertaining to the merits of this approach and/or reasonable values for the
probability distribution.
HES Response: Given the purpose of the 812 Studies (to estimate a future situation), the
cessation lag is a very important issue. As noted by EPA, for short-term effects (including time-
series based observations of mortality) this is not a problem, and there is even published
evidence that these short-term effects closely follow changes in the pollution, thus, benefits are
'immediate' (on the annual aggregate level). For long-term effects, the HES notes that empirical
evidence is lacking to inform the choice of the lag distribution directly and agrees with the NAS
report that there is little empirical justification for the 5-year cessation lag structure used in the
previous analyses. This is because the cohort mortality studies reported to-date have lacked data
on the long-term time-course of exposures for each cohort member; such data, if available, might
enable testing hypotheses regarding alternative exposure lag structures, if sufficient statistical
power was available. However, the HES'notes the importance of developing some estimates of
the cessation lag rather than assuming there is no lag and urges the Agency begin to move from
23
-------
the relatively arbitrary assumptions of the 5-year lag structure to an approach based on some
plausible models of the disease processes involved. Lacking direct information from the cohort
studies themselves, new insights regarding the shape of the cessation lag can only come from
improved understanding of the mechanism of the exposure-response relationship. Information
that may prove valuable in this regard could include results from clinical, experimental animal,
and in-vitro studies, and analogies with the health effects of other long-term inhalation
exposures, such as cigarette smoking. The clinical intervention literature (e.g., cardiovascular
trials) or smoking cessation data may be useful.
The HES recommends that the Agency consider developing models for each cause of
death category expected to make up PM mortality, since the lag structure most likely differs for
different PM-associated disease processes. Although specific causes of death would not be
specifically calculated in the base case, the literature provides enough information to guide
estimates of the likely proportion of PM mortality by disease type (Pope et al., 2002, 2004). As a
general rule, one may assume that the longer the air-pollution-sustained disease process is, the
longer the delay. This may be true whether pollution is an initiator or a promoter. For example,
if inhalation of carcinogens from ambient air contributes to the incidence of lung cancer, the
pathophysiologic process between exposure and death may take many years (for the average
case) and the benefit of a reduction in carcinogenic constituents in PM between the year 2000
and the year 2010 may lead to a reduction in lung cancer rates only after many years. For effects
of long-term PM exposures on pulmonary disease (e.g., COPD), a useful model may be the
change in the natural history of lung function with exposure to air pollution. Several studies
show effects of long-term PM exposures on decreased lung function (e.g., Gauderman et al.,
2002)). By analogy with cigarette smoking, this may put people on steeper trajectories of lung
function decline, which is a known risk factor for premature mortality. This might imply
distributed lags extending over a substantial fraction of a lifetime. On the other extreme, some
cardiovascular deaths captured in the cohort studies may be due to air pollution during the last
months to years prior to death whereas the underlying susceptibility to a cardiovascular death
may be due to non-air pollution causes (e.g., diabetes). Lifetime lost, captured in the cohort, may
still be rather long (see comments in response to Charge Question 17). Clean air policies would
bring a rather immediate benefit for such kind of cases. For example, Lightwood and Glantz
(1997) conducted a meta-analysis of studies to determine how excess risks of myoc'ardial
infarction and stroke in smokers decline after quitting. They reported that risks would be
reduced after roughly 1.5 years. Finally, to the extent that cohort results capture a portion of the
acute time-series mortality effects of PM, there may be an even shorter lag.
EPA staff has presented several alternative lag structures, including the use of a flexible
Weibull distribution spanning up to 25 years. It would be useful to utilize a distribution that
could incorporate time lag to benefits based on different patterns of exposure-response consistent
with models developed of the various response mechanisms. For example, acute effects may be
reduced within the first 6 months of an exposure change, medium-term effects may be reduced
within 2 to 5 years, and long-term effects may be reduced after 15 to 25 years. Thus, the HES
supports either the use of a Weibull distribution or a simpler distributional form made up of
several segments to cover the response mechanisms outlined above, given our lack of knowledge
on the specific form of the distributions. An important question to be resolved is what the
24
-------
relative magnitudes of these segments should be, and how many of the acute effects are assumed
to be included in the cohort effect estimate. The Subcommittee suggests that a smoother might
be applied to the lag function to smooth the discontinuities. Given the current lack of direct data
upon which to specify the lag function, the HES recommends that this question be considered for
inclusion in future expert elicitation efforts and/or sensitivity analyses. As noted, time lag to
benefits may depend on the cause of death and the underlying morbidity processes that
ultimately lead to premature death.
3.7. Agency Charge Question 17; Alternatives to the Base Estimate.
Charge Question 17. In support of Clear Skies and several recent rule makings, the
Agency has presented an Alternative Estimate of benefits as well as the Base Estimate. EPA
developed the Alternative Estimate as an interim approach until the Agency completes a formal
probabilistic analysis of benefits. NAS (2002) reinforced the need for a probabilistic analysis.
The Alternative Estimate is not intended as a substitute method and needs to be considered in
conjunction with the Base Estimate. Presentation of Base and Alternative estimates in the 812
Report may not be necessary if the probability analysis planned for the 812 Report is successful.
While the Base Estimate assumes that acute and chronic mortality effects are causally related to
pollution exposure, the Alternative Estimate assumes only acute effects occur or that any chronic
effects are smaller than assumed in the Base Estimate. The Council's advice is sought on the
following matters:
a. It has been noted by some particle scientists that the size of estimates based on
time series studies that incorporate a distributed lag model, accounting for effects
of 30 to 60 days after elevated exposure, may be similar in size to some
interpretations of the results from the cohort studies. Does the Council agree that
it is a reasonable alternative to use an estimate of the concentration-response
function consistent with this view? If the Council agrees with the assumption, can
it suggest an improved approach for use in an Alternative Estimate? The agency
also seeks advice on appropriate bounds for a sensitivity analysis of the mortality
estimate to be-used in support of the Alternative Estimate.
b. An assumption that a specific proportion of the PM-related premature mortality
incidences are incurred by people with pre-existing Chronic Obstructive
Pulmonary Disease (COPD) and that these incidences are associated with a loss of
six months of life, regardless of age at death. If these values are not valid, what
values would be more appropriate? Do you recommend a sensitivity analysis of 1
to 14 years (with the latter based on standard life tables), as included in the draft
regulatory impact analysis of the proposed Nonroad diesel rule?
c. An assumption that the non-COPD incidences of PM-re!ated premature mortality
are associated with a loss of five years of life, regardless of age at death. If these
values are not valid, what values would be more appropriate? Do you recommend
a sensitivity analysis of 1 to 14 years (with the latter based on standard life
25
-------
tables), as included in the draft regulatory impact analysis of the proposed
Nonroad diesel rule?
d. Additional quantified and/or monetized effects are those presented as sensitivity
analyses to the primary estimates or in addition to the primary estimates, but not
included in the primary estimate of total monetized benefits. While no causal
mechanism has been identified for chronic asthma and ozone exposure, there is
suggestive epidemiological evidence.
1. Two studies suggest a statistical association between ozone and new onset
asthma for two specific groups: children who spend a lot of time
exercising outdoors and non-smoking men. We seek SAB comment on our
approach to quantifying new onset asthma in the sensitivity analyses.
2. Premature mortality associated with ozone is not currently separately
included in the primary analysis because the epidemiological evidence is
not consistent. We seek SAB comment on our approach to quantifying
ozone mortality in the sensitivity analyses.
3. Does the Council agree that there is enough data to support a separate set
of health impacts assessment for asthmatics? If so, does the approach
proposed by the Agency address the uncertainty in the literature?
HES Response: In regard to question 17.a., the HES recommends that the alternative
estimate, as presented in recent EPA analyses, not be included in the Section 812 Analysis for
several reasons. First, it gives a zero probability to the mortality effects of long-term exposure
and in doing so, seriously underestimates the effects of air pollution. Second, there is little logic
to providing an alternative low estimate without providing an accompanying alternative high
estimate. The HES recommends that until a more comprehensive probabilistic uncertainty
analysis is feasible, the Agency continue to base high and low estimates on statistical error
around the existing C-R functions, including that using Pope et al., 2002 for premature mortality.
The HES agrees with use of the cohort mortality studies for the base case estimate because this
study design is capable of capturing effects of long-term PM exposure that the time-series study
design simply cannot-capture. In the view of the HES, the selection process that EPA. has used to
develop the base case health estimates for PM provides an estimate based on sound scientific
evidence of effects. Although there is considerable uncertainty in the estimate for many reasons,
it is not a worst-case estimate and it may be either higher or lower than the true effects.
Therefore, the HES does not agree that the use of the time-series mortality studies, adjusted for a
distributed lag, is an acceptable single alternative estimate to the base case estimate.
In regard to questions 17.b. and c., which concern estimates of life-years lost, the
Subcommittee agrees that the interpretation of mortality risk results is enhanced if estimates of
lost life-years can be made.
As mentioned previously, time-series studies do not provide direct estimates of the time
lost, although Burnett et al. (2003) have indicated that under certain restrictive assumptions,
some conclusions can be drawn from these studies. Therefore, time lost estimates among these
acute cases remain to a large extent a matter of judgment. The time lost may depend on the
26
-------
cause of death and the age at death. For example, whereas the acute terminal effects of air
pollution on patients with lung cancer may make only a small change on life expectancy, a
myocardial infarction in a 60 year old may lead to many years of life lost. The HES notes that in
the non-road diesel rule benefits assessment, life-years lost is calculated for short-term exposure
mortality. Causes of death are separated into COPD and non-COPD and in both cases, it is
assumed that all the affected individuals had serious pre-existing and life shortening chronic
illness. This is a strong assumption (that everyone who dies from short-term PM exposure has
severe pre-existing disease). Although it may be defensible for the short-term exposure mortality
(but even there it is probably too strong), this assumption should not be applied to the mortality
estimates based on cohort studies.
For calculating life-years lost for the cohort studies, the Subcommittee recommends
contacting researchers using the ACS and the 6-ctties data to see if they might have life-years
lost estimates available based on their data. If not, in the short-term the Agency may reasonably
stay with a calculation based on standard life tables. This assumes that in the absence of the PM
exposure life expectancy would have been the same as the average for others of the same age and
gender (which includes an average number of people with chronic disease). Some support for
this assumption comes from the evidence presented in the ACS reanalysis showing that the
mortality risk is no greater for those with pre-existing illness at the time of enrollment in the
study (Krewski et al, 2000).
The Subcommittee recommends that EPA use a life table approach such as the ones
described by Miller and Hurley (2003). This paper applies estimates of relative risk to a given
underlying population-at-risk and its associated age-specific death rates. The life table can be
applied in either a "static" or "dynamic" process. The "static", approach takes the risk ratios from
the cohort studies (i.e., the percentage change per unit PM2.5) and applies this to the baseline
death rate to give "extra" deaths per year. Depending on the cause of death, it then estimates life
years lost per death. This approach ignores how different death rates in any one-year alter the
population-at-risk in future years. Treating years as independent, it provides estimates of "extra
deaths" or 'lives saved" each year.
The "dynamic" approach uses life-table methods to follow over time the impact on the
population-at-risk of higher (lower) age-specific death rates. The consequent changes to the
population-at-risk affect mortality estimates. These estimates are most naturally expressed in
terms of earlier (later) deaths, i.e., in terms of changes in life expectancy or life-years lost. The
observability of "extra death" has recently been questioned by Rab! (2003). The argument
strongly depends on the assumptions of the underlying diseases processes. As mentioned by
Rabl, "extra death" can be "observed" for chronic disease processes such as cancer. Lung cancer
is part of the cohort mortality estimates. The Subcommittee agrees that the "cancer model" can
be generalized to other long-term chronic disease processes of relevance in the air pollution
domain. Thus, results can be expressed in terms of "extra" deaths or "saved" lives in various
time-periods.
Whether to use the static or dynamic approach depends on: a) correctness; b) workability;
and c) whether the differences matter. On (a), the dynamic approach is more comprehensive,
27
-------
more correct, and pushes for greater transparency of assumptions. On (b), the static approach is
easier to implement. However, the technical implementation issues of the life table approach are
not difficult in principle and have been solved in practice. They need not be a deterrent to
implementation. On (c), the two approaches give the same results for year I. They diverge
increasingly with time. This divergence, and its impact on mortality estimates, is positively
associated with the size of the differences in hazard rates. The importance of the differences in
mortality impacts is negatively associated with the discount rate used. The Subcommittee
recommends that: a) whichever approach is used as primary, the other is used in a sensitivity
analysis, and the results compared; b) if differences are non-trivial, then the dynamic (life-table)
approach be taken as best (Miller and Hurley 2003).
If the Agency adopts the approach discussed in response to Charge Question 16 of
modeling the exposure-response processes to estimate the range of cessation lags, a similar
approach could be used to estimate life-years saved. Just as likely ranges of cessation lags may
be estimated by looking at what is known about different causes of death and how PM may be
contributing to the disease processes and attempting to build some models/ranges of that process,
ranges of life-years lost could be similarly estimated. Whether the Agency uses a static or
dynamic life table, the assumption made in the life tables approach is that the average remaining
disease-specific life expectancy for the people whose deaths are predicated on air pollution
exposure is the same as the average remaining life expectancy for all individuals (i.e., where
deaths are both related and non-related to air pollution) of the same age and gender. This may
result in an overestimate of life-years saved due to PM reductions if the disease profile of the
subgroup impacted by air pollution is different from the profile of the full group (i.e., if the air
pollution-impacted people with previous cardiovascular disease are more frail than people who
die from cardiovascular disease, in general). It would be reasonable to assume, consistent with
the cessation lag estimates, that some share of the deaths are among people with lower than
average life expectancy. The Agency could use available information on causes of death and
likely disease processes to propose a set of reasonable assumptions for both cessation lags and
life-years saved that are consistent with one another. For example, some share of the COPD
deaths associated with PM exposure consists of individuals who developed COPD because of
long-term PM exposure. In this instance the cessation lag may be many years and the life-years
lost is consistent with standard life tables. In another category, there may be heart attack deaths
associated with PM exposure that include individuals who had already existing coronary heart
disease. In mis-case the cessation lag may be quite short and the life-years saved, although
substantial, may be less than the standard life tables calculation because of the pre-existing
disease. In yet another category, there may be PM-related deaths due to pneumonia in
individuals with rates of pre-existing disease comparable to the general population. If in the
absence of PM exposure a full recovery would have been made, then the cessation lag is quite
short and the life-years saved is consistent with the standard life tables.
The HES acknowledges, however, that uncertainties remain, given that no study has
formally analyzed the years of life lost and the dependence of years of life lost on causes of
death, pre-existing diseases, and the underlying distributions of other susceptibilities. Even
though a considerable amount of judgment would be involved, an approach that uses available
information to estimate the shares of PM-associated deaths in each of several categories may
28
-------
provide a more defensible set of assumptions for estimating both cessation lags and life-years
saved than more arbitrary assumptions.
In regard to question 17.d.i., which concerns methods for quantifying new onset asthma,
the Subcommittee agrees that, so far, there are only two studies suggesting an effect of ozone on
new onset (incidence) of asthma. Findings suggest some complex interactions of exposure and
time-activity patterns outdoor, and the asthma literature indicates that onset of asthma depends
on a variety of interacting factors, which may in addition change with age. Other air pollution
studies are not conclusive on the issue. Thus, the HES recommends that EPA leave onset of
asthma out of the base case quantitative estimates. The issue may be discussed qualitatively and
should be reconsidered if new information becomes available. The exclusion of this outcome
may lead to some underestimation of the overall benefits.
Question 17.d.ii concerning ozone mortality is discussed later under Charge Question 30.
In regard to question 17-d.iii, concerning a separate asthma analysis, there is some appeal to
looking at a subgroup that may have greater sensitivity to pollution exposure than the general
population and those with asthma are a reasonable group to choose. However, with the
recommendation that asthma exacerbation be added back into the primary set of C-R functions,
the need for this is reduced.
3.8. Agency Charge Question 29: Plans for Expert Elicitation Pilot for Premature
Mortality.
Charge Question 29. Does the Council support the plans described in chapter 9 for the
expert elicitation pilot project to develop a probability-based PM2.5 C-R function for premature
mortality, including in particular the elicitation process design? If the Council does not support
the expert elicitation pilot project, or any particular aspect of its design, are there alternative
approaches the Council recommends for estimating PM-related mortality benefits for this
analysis, including in particular a probabilistic distribution for the C-R function to reflect
uncertainty in the overall C-R function and/or its components?
HES Response: The HES supports the use of expert judgment as a means of
systematically characterizing the state of knowledge about the likely health impacts of changes
in PM2.5 concentrations. We fully endorse the view espoused by the recent National Research
Council Committee on Estimating the Health Benefits of Air Pollution Regulations that the
question is not whether expert judgment will be used, but how it will be used (National Research
Council, 2002).
Expert judgments have long been important to risk assessment and management
processes, because of the many uncertainties that need to be addressed. There are various
approaches for incorporating expert judgment into risk assessment. These vary in many ways -
including whether judgments are explicit or implicit, whether they are formally or informally
elicited, whether (and the degree to which) they seek quantitative answers, and whether they seek
consensus or not. It is well recognized that no single approach will suit all decision processes
and that more formal approaches (which may be resource intensive) must be reserved for dealing
29
-------
with issues characterized by large uncertainty and substantial consequences of errors in decision-
making. The HES agrees with die Agency that the PM C-R mortality function is a good
candidate for formal elicitation of expert judgment. While there have been several reviews of the
use of formal expert judgment, little attention has been given to their potential application in
support of environmental risk assessment (Wright and Ayton, 1994 and Walker, et al., 2001).
This pilot study presents a unique opportunity to thoughtfully examine the benefits and costs of
this approach in such settings.
In any application of formally elicited expert judgment, the major issues in the design of
the study are:
a. definition of the question(s) to be elicited;
b. specification of the pool of relevant expertise and choice of an approach for
identification and selection of experts;
c. determining which materials to include in a briefing book;
d. deciding whether to hold a workshop (at which the evidence can be reviewed; the
procedures for eliciting expert judgment can be introduced; the protocol can be
presented, discussed and revised; and at which the potential problems in eliciting
judgments can be reviewed);
developing a protocol for eliciting judgments and determining:
1. whether an aggregate question or a set of disaggregated questions will be
used; and if a disaggregated approach is used,
i. determining how to structure the questions, and
ii. developing a method for dealing with correlated answers;
what approaches will be used to encourage experts to fully consider the
range of evidence, including contradictory evidence;
- whether elicitation aids (such as probability wheels) will be used; -
f. determining whether efforts will be made to check the internal consistency of the
judgments; and
g. deciding whether and how judgments will be combined, and if so, what
information will be used in combining judgments (e.g., performance on
calibration questions, peer or self ratings).
e.
2.
3.
The HES review of the Agency's plans for the expert elicitation pilot project to develop a
C-R function for PM related premature mortality has been particularly difficult because the
materials available for review have been modified several times during the period of review.
The original Analytic Plan was received in May and then in June (just days before the first
scheduled Council and HES meeting) much of the key material relevant to the pilot study was
withdrawn.
30
-------
The initial HES evaluation of the plans was based a review of the brief Oust over two-
page) description of the Agency's plans available at the time of the 27-29 August HES meeting.
These materials indicated that the Agency and its contractors were aware of the general literature
in the field, and suggested that they were following generally accepted practice, but left the
Subcommittee with many unanswered questions. These were described in a set of comments
prepared by the HES after its 27-29 August public meeting and were provided to the Agency in
draft form in a letter dated 21 October 2003. The HES concerns include the issues that follow.
Perhaps the most important question had to do with clear definition of the goal of the
pilot project. Was it intended primarily to allow the Agency to gain experience with the
formulation and conduct of expert judgment exercises? Or was it intended to provide
information useful for near-term policy analyses, such as the off-road diesel rule? The HES
pointed out that our evaluation of the pilot study was heavily dependent on its intended purpose.
Second, HES members were concerned about the scope of the question to be addressed
by the pilot expert judgment. Was the exercise intended to produce a concentration-response
function for PM2.5 mass (without regard to source), or was it intended to address differential
relative toxicity? Was the concentration-response function intended to represent the response
averaged across the United States (without regard to background levels of PM2.5 and other
pollutants), or was it intended to be applied to specific regions of the United States (allowing for
background levels of PM2.5 and co-pollutants)? Were the results intended to be applied more
broadly (e.g., outside of the United States)? Again, the HES indicated that advice about the
utility of the approach taken and the results obtained would depend on knowing the answers to
these questions.
Third, the HES desired clearer information about the criteria that would be used in the
selection of individual experts. The EPA had indicated that it was considering relying on experts
selected from two recent National Academy of Science panels that had dealt extensively with
airborne particulate matter and the HES agreed that this had certain merits, especially for the
pilot study. However, the HES did not have adequate information to understand how the Agency
intended to deal with the question of the disciplinary mix of experts involved in the study. The
HES emphasized the need to use experts familiar with the elicited issues and to balance the
group to ensure that experts from all key disciplines (epidemiology, toxicology, basic biology,
clinical medicine) are well represented. There was also some concern that attributes of the group
other than discipline might need to be balanced as well. While recognizing that in the pilot
project the number of experts must be limited, the HES urged the Agency to broaden the expert
pool used in support of the final elicitations.
Fourth, the HES wondered why the Agency had decided to use a single composite (or
aggregate) question - e.g., "What reduction in mortality would be expected from a 1 ug/m3
reduction in PM2.5 across the entire United States?"- rather than a set of disaggregated
questions. This was in part because we worried that some analysts using the results might be
frustrated if they could not understand the reasoning used by the experts to develop their
characterizations of the state of knowledge. Many experts in the field argue that the quantitative
31
-------
answers are less important than the insights produced. In this spirit, the HES recommended that
the Agency collect narrative descriptions-of the rationale used by each expert and that these be
presented along with the quantitative characterizations of uncertainty given by the experts.
Further, the HES encouraged the Agency to rely on a disaggregated approach, especially with
regard to short-term exposure and long-term exposure effects.
Fifth, on the basis of the limited materials available, the HES could not determine
whether the experts would be engaged in the development of the elicitation protocol, briefing
book and other materials. The HES noted that one of the most important determinants of the
success of past exercises has been whether the experts involved had confidence in the process
and argued that development of the briefing book and the elicitation protocol should involve an
iterative process with extensive interaction between the experts and the elicitation team.
Sixth, the HES observed that the materials that had been provided were not clear about
how the individual expert judgments would be aggregated. The HES advised the EPA to present
the entire collection of individual judgments; to carefully examine the collection of individual
judgments noting the extent of agreement or disagreement; to thoughtfully assess the reasons for
any disagreement; and to consider formal combinations of judgments only after such deliberation
and with full awareness of the context for this analysis (see Morgan and Henrion, 1990, pages
164 to 168). If the individual judgments are to be aggregated, the HES urged the EPA to present
both simple (equal weight) aggregations and more complex (calibration weighted) versions of
the results, and stressed that users of the information must be made aware of the entire spectrum
of results.
Seventh, the original materials suggested that experts might be asked how to weight the
results from time-series and cohort studies. The HES strongly disagreed with this approach;
noted that cohort and time-series studies measure two different effects; and argued that they
should be viewed as complementary sources of evidence, rather than as alternate sources of
evidence. The HES urged the Agency to elicit both.
- After the Agency provided the SAB Staff Office with the elicitation protocol for the pilot
project to provide to the HES in late October, the HES discussed these issues at a public
teleconference on 30 October 2003. The lead discussants relayed these views to the Council for
further discussion at a public meeting on 5-6 November 2003. At that meeting, the Agency
briefed the Council more completely on the approaches that it used in the selection and
elicitation of experts. However, by the time the HES and Council received these materials, the
pilot project was well underway, the final elicitation protocol was complete, and many (if not all)
of the expert elicitations had been conducted.
These materials provide answers to many of our original questions. For example, the
elicitation protocol makes it quite clear that the Agency intends to use the results of the pilot
project in the development of Regulatory Impact Assessments (RIAs) for specific proposed
regulations (such as the non-road diesel rule and the PM transport rule). The protocol states that
the elicitation will focus on determining the PM C-R function for specific changes in PM mass
concentrations, and also indicates that auxiliary questions will be asked about the potential
32
-------
impact of PM composition. The Agency indicates that the five experts who participated in the
elicitation, Jonathon Samet, Mark Utell, Bart Ostro, Roger McClellan and Scott Zeger, were
selected on the basis of a process in which ten leading authors of PM mortality papers were
asked to rank the members of the two relevant NAS panels. The protocol now includes several
questions, which ask experts to carefully outline the rationale underlying their stated judgments.
The protocol clearly states that individual judgments (without specific attribution) and pooled
results (using equal weights) will be provided as study results. The protocol asks experts to
separately consider time-series and cohort evidence.
The HES is encouraged by these responses, but has a few residual concerns, including:
a. Whether the Agency believes that the small pool of experts that could be studied
in the pilot was adequate to reflect the legitimate spectrum of beliefs among
experts from the several key disciplines. The HES recognizes that in order to
make the pilot tractable it was necessary to limit participation, and is aware of the
many factors which must be balanced in the selections of expert panels (Hawkins
and Graham, 1988), but is concerned about whether the judgments of such a
limited group can reasonably be interpreted as representing a fair and balanced
view of the current state of knowledge. The Subcommittee also advises EPA to
consider the problem of potential multiple and repeated elicitations of a small
pool of experts and how to use the most appropriate methods for a high quality
elicitation process overall.
b. Whether the elicitation procedures ensured that experts would give adequate
attention to contradictory evidence. While procedures may have been in place to
cause experts to fully consider countervailing evidence and theory, neither the
protocol nor the Agency briefing adequately described these.
c. Whether the approach used to deal with the relationships between evidence from
time-series and cohort studies was fully adequate. While the HES believes that
the approach reflected in the elicitation protocol is far- superior to the Agency's -
original plan to ask the experts to weight the two approaches, the HES believes
that further attention to the framing of the "short-term" and "long-term" effects of
particulate matter may be appropriate. There is some concern among the HES
that the definitions of "short-term" and "long-term" may have been somewhat
ambiguous. Further, the HES believes that careful discussion of this framing
during the review of the pilot project might lead to improvements in the design of
subsequent expert elicitation studies.
d. Whether the decision to omit the workshop may have limited the ability of the
experts to participate in the design of the protocol and thereby may have
influenced their confidence in the process.
e. Whether the decision to ask the experts to use frequencies and probabilities in
several different ways - e.g., response rates, subjective probabilities, percent
33
-------
reductions in response rates ~ may have resulted in some confusion. The use of a
single probability scale may be considered instead of the current variety of scales
ranging from yes/no to (more informative) probability statements.
f. Whether there might have been benefits to using widely available tools, such as
probability wheels, in the elicitations. Two advantages of the approach used
previously by Whitfield and Wallsten (1989) are that by relying on probability
wheels response confusion is minimized and by asking each question in several
different ways one may easily check for and assure consistency of responses.
However, in view of the fact that the pilot project is well-underway, the experts have
already been selected, and many (if not all) of the interviews have been conducted, the HES sees
little potential benefit in providing detailed suggestions about the design or conduct of the pilot
study.
Instead, the HES focuses our comments on the review and interpretation of results from
the pilot study. Specifically:
a. the HES recommends that the Agency conduct a thoughtful and comprehensive
peer-review of the pilot study;
b. the HES recommends that the Agency view the results of the pilot study
somewhat tentatively until the review is complete; and
c. the HES urges the Agency to apply a common sense standard to the results - i.e.,
do the experts involved "stand behind" the results? Do they believe that the
process has faithfully captured their beliefs about the mortality effects of PM?
In summary, the HES generally supports the use of expert judgment to inform policy
analysis; commends the EPA for moving in this direction; understands their hesitancy to move
too quickly; supports the pilot study; questions whether it is advantageous to use the results of
the pilot study in support of a major regulatory initiative; seeks much more detailed information
about the approach used; advises that the pilot study be reviewed, in particular the process and
interpretation of the pilot study results; and urges the EPA to invest adequate resources, time,
and managerial attention to further development of this approach so that it can be used to inform
this Second Prospective Analysis of the Clean Air Act.
3.9. Agency Charge Question 30; Plans for Estimating Independent Effects of Ozone
Mortality.
Charge Question 30. EPA plans to develop estimates of an independent mortality effect
associated with ozone, as described in chapter 9. Does the Council support the use of the most
recent literature on the relationship between short-term ozone exposure and daily death rates,
specifically that portion of the literature describing models that control for potential confounding
by PM2 5? Does the Council agree with the use of that literature as the basis for deriving
34
-------
quantified estimates of an independent mortality impact associated with ozone, especially in
scenarios where short-term PM2.5 mortality estimates are used as the basis for quantifying PM
mortality related benefits? Does the Council support the plans described in chapter 9 for the
pilot project to use this literature to develop estimates of the ozone related premature mortality
C-R function using the three alternative meta-analytic approaches? If the Council does not
support this pilot project, or any particular aspect of its design, are there alternative approaches
to quantifying ozone-related premature mortality that the Council recommends?
HES Response: Acute ozone effects pose an important yet complex issue that needs to
be addressed as EPA moves forward with benefits analyses. A large and growing literature
exists on ozone mortality associations with and without control of PM covariates. However, the
interpretation of these results is made complicated by several issues, including possible
confounding by PM, effect modification by season and interactions with temperature and other
weather factors. Thus, the effects are hard to ignore, but their interpretation remains
problematic, raising questions as to how best to incorporate these effects into the benefits
analysis. The Subcommittee endorses EPA's plans to sponsor three new meta-analyses of ozone
impacts. This will yield information on the consistency of the effects of ozone and to what
extent they are independent of PM. While the HES agrees with EPA that PM2.5 is the most
important co-pollutant to be concerned about, the meta-analyses should not necessarily be
limited to only those ozone studies that have PM2.5 data. Other studies may also be informative,
including those using PM10, estimated PM2.5, and/or optical measures of paniculate blackness.
The Subcommittee looks forward to reviewing the results of these meta-analyses.
3.10. Agency Charge Question 32: Evaluating Data Quality and Plans for Publication of
Intermediate Data Products.
Agency Charge Question 32. Does the Council support the plans described in chapter 10
for evaluating the quality of data inputs and analytical outputs associated with this study,
including the planned publication of intermediate data products and comparison of intermediate
and final results with other data or estimates? If the Council does not support these plans, are
there alternative approaches, intermediate data products, data or model comparisons, or other
data quality criteria the Council recommends? Please consider EPA's Information Quality
Guidelines in this regard.
HES Response: The Subcommittee enthusiastically supports EPA's plan to make
available through EPA's web site the intermediate information and data products produced in the
course of the 812 analysis. The BENMAP system demonstrated to the Subcommittee appears to
be an invaluable tool for both generation and facilitation of a widespread understanding of the
analysis and its results. In particular, it will enhance understanding of the assumptions used in
constructing the aggregates of results, and the consequences of alternative aggregation
approaches and assumptions.
It might be of interest to assess the degree of "surprise"—where possible compare the
extent of each change with the prior belief about the uncertainty in the estimate. Historically,
even in fields with well-established procedures for estimating uncertainties (such as
35
-------
measurements of elementary particle masses by physicists), it is found that traditional statistical
procedures for estimating standard errors, etc., systematically understate actual uncertainties as
later calculated by comparing improved measurements with older measurements and previously
estimated uncertainties (for examples see the references provided below). This is because
traditional statistical uncertainty estimation approaches tend to be based solely on random
sampling-error uncertainties in the data, neglecting what frequently turns out to be appreciable
systematic or calibration errors (Shlyakhter 1992,1994a and 1994b). Developing fair estimates
of uncertainties for the CAAA benefit and cost projections will require analysts to have inputs
that can be interpreted in terms of both types of uncertainty. Systematic evaluation of the extent
and reasons for changes in successive sets of emissions estimates will be a start toward providing
invaluable inputs to the overall uncertainty analysis.
The HES also suggests that there is some value in having clearly stated data quality
objectives (DQOs) and a specific comprehensive data quality assurance (QA) protocol. These
objectives should be derived from the context of the 812 Analysis and should guide the design
and presentation of the intermediate data products to best serve the needs of specific audiences
for the data. Discussion among the group identified two broad types of users whose differing
needs should be kept in mind: a) policy and staff advisors whose main goal may be to understand
the basis of the 812 analysis and its conclusions, and b) analysts who wish to conduct
independent evaluations based on data used by the Agency. With the needs of these two groups
in mind, the disclosure and ready availability of the intermediate data products, presented on the
website and otherwise in context along with a summary of the DQOs, should greatly enhance the
value of the 812 analysis for both public and private sector decision-makers.
3.11. Agency Charge Question 33: Plans for aggregation and presentation of analytical
results from the Health Analysis.
Charge Question 33: Does the Council support the plans described in Chapter 11 for the
aggregation and presentation of analytical results from this study? If the Council does not
support these plans, are there alternative approaches, aggregation methods, results presentation
techniques, or other tools the Council recommends?
HES Response: For the first prospective study, EPA compared costs to benefits for the
years 2000 and-2010. The Agency also aggregated the net present value of costs and benefits for
the 1990 through 2010 period. The approach was to use a linear interpolation between the years
1990 and 2000 and a second linear interpolation between 2000 and 2010. The linear
interpolation was used because air quality modeling was only carried out for the years 2000 and
2010.
The modeling results for the first study supported estimates of annual and cumulative
costs for Titles I through V and annual estimates for Title VI. The benefits were not
disaggregated by Title nor, with some minor exceptions, were they disaggregated by geographic
area, although spatially disaggregated data were presented in the report appendices.
36
-------
a. Alternative approaches: The formal probability analysis method will eventually
be used to provide better estimates of uncertainty and estimations of mode!
sensitivity to modeled factors. This may be superior to assessing uncertainty by
comparing results obtained using different analytical methodologies.
b. Aggregation methods: There are only a few C-R functions for source-specific
health effects and therefore limited information for sector-specific PM health
benefits or for apportioning health benefits among sources or sectors other than as
a function of source-specific contributions to ambient PM mass. With the
exception of particle size considerations, the toxicity of all PM is treated as
equivalent regardless of its origin. There is limited evidence (i.e., Laden et. al.,
2000) to suggest some differential toxicity of PM, at least regarding mortality and
daily PM exposures. If the data are available on source-specific changes in PM,
EPA should consider conducting a limited sensitivity analysis utilizing some of
this evidence,
1. Sectoral Disaggregation - The plan for generating sector-specific benefit
results involves independent scenarios that selectively omit emissions
reductions for a single sector (i.e., holding emissions at pre-CAAA levels)
while bringing all other sectors to their post-CAAA levels. The Air
Quality Modeling Subcommittee has evaluated the issues of emissions
estimates and transport. The HES assumes the estimates will include data
to compute exposures to both fine and coarse mode particles. The Agency
can use these exposures in conjunction with appropriate C-R functions to
estimate health benefits by sector.
2. Spatial Disaggregation - The cost and benefit modeling for spatial
disaggregation will be presented in the Appendix. There are limitations in
ability to predict population growth patterns on a spatial level over several
years accurately. Also on a regional level, areas that incur pollutant
abatement costs may be different from areas that receive health benefits.
Spatially disaggregated health benefits can be estimated but because of the
mismatch with costs, it may be difficult to interpret the disaggregated net
benefits.
3. Pollutant Endpoint Disaggregation - In cases where endpoint-pollutant
combinations can be identified that can be associated with a specific
benefit, disaggregated benefits can be presented. Detailed statistical
analyses to identify pollutant interactions have been used in apportioning
air pollution contributions among sources. It may be possible to use such
source-receptor methods for disaggregating health effects among pollutant
combinations.
37
-------
3.12. Agency Charge Question 34: Plans for Stratospheric Ozone Analysis.
Charge Question 34. Does the Council support the plans describe in Appendix E for
updating the estimated costs and benefits of Title VI programs? If the Council does not support
these plans, are there alternative data, models, or methods the Council recommends?
HES Response: The proposed revised approach to determining costs and benefits of
controls to limit stratospheric ozone reductions by anthropogenic chemicals is sound, and
addresses the issue comprehensively. Recent advances in knowledge and models make it
possible to address the issue with somewhat greater confidence, while still recognizing that great
uncertainties remain concerning both scientific and economic assumptions and constraints when
dealing with a time frame extending to 2075. Overall, the Subcommittee concludes that the
plans make quite reasonable assumptions and choices.
The Subcommittee suggests that the text be revised to provide more information on two
points: a) the basis for the effects coefficient for cataract formation, and b) the basis for the
effects coefficient for basa! cell carcinoma and malignant melanoma. The Subcommittee also
suggests the following specific comments to strengthen Appendix E: a) on page E-4, the
judgment that unqualified ecological benefits are minimal compared to the benefits estimated
by the AHEF model could be correct, but needs to be better justified, and b) on page E-6, replace
"ozone depletion" with the term "ODS control." Additionally, the text needs to clarify the
source of the cataract data to be used (in the public meeting, EPA staff said it was the National
Eye Institute database) and any sample size or other issues with the data that would raise
concerns about its use for this analysis. Although the state of the science is not well developed,
the levels of uncertainty in both the cancer and cataract data need to be described and their
potential impacts on the cost-benefit analysis discussed. Mention of the limitations and/or lack
of data from animal models relevant to specific human outcomes (e.g., basal cell carcinoma,
malignant melanoma.) would strengthen this section.
/
3.13. Agency Charge Question 35; Plans for an Air Toxic Case Study.
Charge Question 35. Does the Council support the plans described in Appendix E for
the benzene case study, including the planned specific data, models, and methods, and the ways
in which these elements have been integrated? If the Council does not support these plans, are
there alternative data, models, or methods the Council recommends?
HES Response: The Subcommittee notes that the basic conception of the case study is
reasonable, given that the chemical chosen is data rich, and therefore not a typical air toxic.
Several suggestions for strengthening the approach follow. The plan for deriving the C-R
function mentions only an analysis of a relatively small (only nine leukemia cases) and older
epidemiology study (Crump et al., 1994). The current plan neglects much newer and more
extensive leukemia and supporting chromosome breakage, and other genetic biomarker exposure
response data collected by U.S. researchers among large numbers of Chinese workers with a
broad range of exposures (Hayes et al., 2000,1997; Rothman et a!., 1995,1996a, 1996b, 1997).
The exposure estimates used in these studies have been criticized (Wong, 1999), however,
38
-------
further work with the authors of the study seems likely to be able to produce dose response
information that is at least equal to, and likely superior to, that which is the basis of the older
benzene cancer potency estimates. One particularly important implication of the newer
information is that in contrast to the suggestion of an upward turning curve from the older higher
dose data, the newer data seem to indicate a convex dose response shape (linear at low doses,
with some flattening at higher dose rates). This finding is consistent with high dose saturation of
the generation of some genetically active activated intermediate metabolite, most likely a
metabolite produced by a specific P450 enzyme (Rothman et al., 1997).
The HES also suggests that EPA consider and reviews other well-conducted studies,
especially where these have been conducted at exposure levels closer to what the general public
may experience (e.g. Rushton and Romaniuk, 1997 and Schnatter et al., 1996). Uncertainty
assessment should include consideration of extrapolation from high-exposure studies of adult
(usually male) workers, to the lower exposures and more diverse population of the public.
In regard to the data, the 1990 data, measured by Texas Natural Resource Conservation
Commission, will be used as the base case (pre-CAAA). The 1999 NTI could be used as a
surrogate for the 2000 (post-CAAA) data. The Agency, might, however, find it more consistent
to project the data to 2000. The HES considered the four options identified by the Agency for
incorporating CAAA impacts. Option 2 takes into account MACT expectations as well as
impact of the Houston Ozone State Implementation Plan (SIP) provisions, but Option 3, which
uses existing EPA databases, might be easier to implement.
The plan to limit the case study to the Houston area makes sense for this first cut. If the
benefits turn out to be non-negligible, a broader application of the case study might be
warranted. Extension to Portland and/or Philadelphia should depend on the Houston outcome.
Agency Charge Question 36. A cessation lag for benzene-induced leukemia is difficult
to estimate and model precisely due to data limitations, and EPA plans to incorporate a five-year
cessation lag as an approximation based on available data on the latency period of leukemia and
on the exposure lags used in risk models for the Pliofilm cohort (Crump, 1994 and Silver et al.,
2002). Does the SAB support adoption of this assumed cessation lag? If the Council does not
support the assumed five-year cessation lag, are there alternative lag structures or approaches the
Council recommends?
HES Response: The simple lag interpretation of 5 years mentioned in the blueprint does
not seem to utilize all the material in the original Crump (1994) paper-in particular, an equation
(utilizing the parameter K) that Crump uses to weight exposures that occurred at different times
relative to the appearance of the leukemias. Some finite minimum lag is likely to be justified by
the growth rate of tumors from initial single cells to the point at which there are enough cells to
be clinically detectable as a cancer. This issue needs to be revisited in the light of a more recent
analysis of data from the original U.S. cohort (Silver et al., 2002) as well as observations of the
distributions of excess tumors in studies of radiation-induced leukemias. If available, data from
the NCI-Chinese studies (cited above) should also be analyzed for differences in the timing of
exposures and the timing of the appearance of tumors.
39
-------
40
-------
REFERENCES
Ackermann-Liebrich, U, Leuenberger P, Schwartz J, Schindler C, Monn C et al. (1997).
Lung Function and Long Term Exposure to Air Pollutants in Switzerland.
American Journal of Respiratory and Critical Care Medicine 155,122-129.
Belanger, K., Beckett, W.( Triche, E., Bracken, M.B., Holford, T et al. (2003).
Symptoms of wheeze and persistent cough in the first year of life: associations
with indoor allergens, air contaminants, and maternal history of asthma.
American Journal of Epidemiology 158:195-202.
Brunekreef, B., Janssen N.A., de Hartog, J., Harssema, H., Knape. M., et al. (1997). Air
Pollution from Truck Traffic and Lung Function in Children Living Near
Motorways. Epidemiology 8: 298-303.
Burnett, R.T., Smith-Doiron, M., Stieb, D., Raizenne, M.E., Brook, J.R. et al. (2001).
Association between ozone and hospitalization for acute respiratory diseases in
children less than 2 years of age. American Journal of Epidemiology 153: 444-
452.
Chay, K.Y., Greenstone, M. (2001). The impact of air pollution on infant mortality:
Evidence from geographic variation in pollution shocks induced by a recession.
Berkeley, CA: University of California, Berkeley, Department of Economics.
Available: http://elsa.berkelev.edu/users/kenchay/].
Chestnut, L.G., Schwartz, J, Savitz, D, Burchfiel, C.M. (1991). Pulmonary Function and
Ambient Particulate Matter Epidemiological Evidence from NHANES I.
Archives of Environmental Health 46:13 5-144.
Clancy, L., P. Goodman, et al. (2002). Effect of air'-poHution control on death rates in
Dublin, Ireland: an intervention study. Lancet 360(9341): L210-4.
Cooke, R.M. (1991). Experts in Uncertainty: Opinion and Subjective Probability in
Science. Oxford University Press, New York.
Crump, K..S. (1994). Risk of benzene-induced leukemia: A sensitivity analysis of the
pliofilm cohort with additional follow-up and new exposure estimates. Journal of
Toxicology and Environmental Health 42: 219-242.
Danesh, J., Collins, R. Appleby, P., Peto, R. (1998). Association of Fibrinogen, C-
reactive Protein, Albumin, or Leukocyte Count with Coronary Heart Disease.
Journal of the American Medical Association 279(18): 1477-82.
Dockery, D.W., Pope, C.A. Ill, Xu, X., Spengler, J.D., Ware, J.H., Fay, M.E .et ai. 1993.
An association between air pollution and mortality in six U.S. cities. New
England Journal of Medicine 329:1753-9.
Dominici, F., A. McDermott, et al. (2003). Airborne paniculate matter and mortality:
timescale effects in four US cities. American Journal of Epidemiology 157(12):
1055-65.
Ezzati M., Lopez, A.D., Rodgers A., et al. (2002). Selected major risk factors and global
and regional burden of disease. Lancet 360: 1347-60.
Folsom, A.R., Wu, K.K., Rosamond, W.D., Sharrett, A.R., and Chambless, L.E. (1997).
Prospective study of hemostatic factors and incidence of coronary heart disease.
The Atherosclerosis Risk in Communities (ARIC) study. Circulation 96: 1102-
08.
41
-------
Gauderman, W.J., Gilliland, G.F., Vora, H., Avol, E., Stram, D., McConnell, R. et ai.
(2002). Association between air pollution and lung function growth in southern
California children: results from a second cohort. American Journal of
Respiratory and Critical Care Medicine. 166(1): 76-84.
Gilliland, F.D., Berhane, K., Rappaport, E.B., Thomas, D.C., Avol, E., Gauderman, W.J.,
London, S.J., Margolis, H.G., McConnell, R., Islam, K.T., Peters, J.M. (2001).
The effects of ambient air pollution on school absenteeism due to respiratory
illnesses. Epidemiology 12:43-54
Gold, D.R., Litonjua, A. Schwartz, J., Lovett, E., Larson, A. et al. (2000). Ambient
Pollution and Heart Rate Variability. Circulation 101:1267-73.
Hattis, D. and Burmaster, D.E. (1994). Assessment of Variability and Uncertainty
Distributions for Practical Risk Analyses. Risk Analysis 14:713-730.
Hattis, D., Russ, A., Goble, R., Banati, P., and Chu, M. (2001). Human Interindividual
Variability in Susceptibility to Airborne Particles. Risk Analysis 21(4): 585-599.
Hawkins N.C. and Graham J.D. (1988). Expert scientific judgment and cancer risk
assessment: a pilot study of pharmacokinetic data. Risk Analysis 8:615-625.
Hayes, R.B., Yin, S., Rothman, N., Dosemeci, M., Li, G., Travis, L.T., Smith, M.T., et al.
(2000). Benzene and lymphohematopoietic malignancies in China. Journal of
Toxicology and Environmental Health A. 61:419-432.
Hayes, R.B., Yin, S.N., Dosemeci, M., Li, G.L., Wacholder, S. et al. (1997). Benzene
and the dose-related incidence of hematologic neoplasms in China. Journal of.
National. Cancer Institute 89:1065-1071.
Hoek, G., Brunekreef, B., Verhoeff, A., van Wijnen, J., Fischer, P. (2000). Daily
mortality and air pollution in The Netherlands. Journal of Air and Waste
Management Association 50(8): 1380-9.
Hoek, G., Brunekreef, B., Fischer, P., van Wijnen, J. 2001. The association between air
pollution and heart failure, arrhythmia, embolism, thrombosis, and other
cardiovascular causes of death in a time series study. Epidemiology 12(3): 355-7.
Hoek, G., Brunekreef, B., Goldbohm, S., Fischer, P., van den Brandt, P.A. (2002).
Association between mortality and indicators of traffic-related air pollution in the
Netherlands: a eohort study. Lancet 360(9341): 1203-9.
Huikuri, H.V., Makikallio T.H., Airaksinen K.E., Seppanen T., Puukka P., et al. (1998).
Power-Law Relationship of Heart Rate Variability as a Predictor of Mortality in
the Elderly. Circulation 97, 2031-2036.
Kleiger, R.E., Miller, J.P., Bigger, J.T., Moss, A.J., and the Multicenter Post-Infarction
Research Group. (1987). Decreased heart rate variability and its association with
increased mortality after acute myocardial infarction. American Journal of
Cardiology 59:256-262.
Kaiser R., Kunzli N., Schwartz J. (2001). The impact of PM10 on infant mortality in 8
US cities. American Journal of Respiratory and Critical Care Medicine. 163(5):
A881.
Krewski, D, Burnett, R., Goldberg, M.S., Koover, K., Siemiatycki, J., Jerrett, M. et al.
(2000). Reanalysis of the Harvard Six Cities Study and the American Cancer
Society Study of Particulate Air Pollution and Mortality. Health Effects Institute
(A special report of the Institute's Particle Epidemiology Reanalysis Project).
42
-------
Kunzli, N., S. Medina, et al. (2001). Assessment of deaths attributable to air pollution:
should we use risk estimates based on time series or on cohort studies? American
Journal of Epidemiology 153(11): 1050-5.
James, A.L., Knuiman, M.W., Divitini, M.L., Musk, A. W, Ryan, G., Bartholomew, H.C.
(1999). Associations Between White Blood Cell Count, Lung Function,
Respiratory Illness and Mortality: the Busselton Health Study. European
Respiratory Journal 13:1115-1119.
Knuiman, M. W., James, A. L, Divitini, M. L., Ryan, G., Bartholomew, H. C., Musk, A.
W. (1999). Lung Function, Respiratory Symptoms, and Mortality: Results from
the Busselton Health Study. Annals of Epidemiology 9:297-306.
Laden, F., L. M. Neas, et al. (2000). Association of fine particulate matter from different
sources with daily mortality in six U.S. cities. Environmental Health Perspectives
108(10): 941-7.
Lange, P., Nyboe, J., Appleyard, M., Jensen, G., Schnohr, P. (1990) Spirometric
Findings and Mortality in Never-Smokers. Journal of Clinical Epidemiology
43:867-873.
Lightwood, J.M. and Glantz, S.A. (1997) Short-term economic and health benefits of
smoking cessation. Myocardial infarction and stroke. Circulation 96: 1089-96.
Lippmann, M., Frampton, M., Schwartz, J., Dockery, D., Schlesinger, R.B., Koutrakis,
P., Froines, J., et al. (2003). The U.S. Environmental Protection Agency
particulate matter health effects research centers program: A midcourse report of
status, progress, and plans. Environmental Health Perspectives 111:1074-1092.
Lippmann, M., Ito, K., Nadas, A., Burnett, R.T. (2000). Association of particulate
matter components with daily mortality and morbidity in urban populations,
Health Effects Institute 95:5-72, discussion 73-82.
Lipfert, F. W., Zhang, J., Wyzga, R.E. (2000). Infant mortality and air pollution: A
comprehensive analysis of U.S. data for 1990. Journal of Air and Waste
Management Association 50:1350-1366.
Martuzzi, M. (2001). Re: "Assessment of deaths attributable to air pollution: should we
use risk estimates based on time series or on cohort studies?" American Journal of
Epidemiology 154(10): 974-5.
Miller, B.G., Hurley, J.F. (2003). Life table methods for quantitative impact assessments
in chronic mortality. Journal of Epidemiology and Community Health 57(3): 200-
6.
Moolgavkar, S.H. (2000). Air Pollution and Hospital Admissions for Diseases of the
Circulatory System in Three U.S. Metropolitan Areas. Journal of Air and Waste
Management Association 50:1199-206.
Morgan, M.G., Henrion, M. (1990). Uncertainty: A Guide to Dealing with Uncertainty
in Quantitative Risk and Policy Analysis. Cambridge University Press,
Cambridge, UK.
National Research Council. (2002). Estimating the Public Health Benefits of Proposed
Air Pollution Regulations. National Academy Press, Washington, DC.
Nyberg, F., Gustavsson, P. et al. (2000). Urban air pollution and lung cancer in
Stockholm. Epidemiology 11(5): 487-95.
43
-------
Pope, C. A. III. (1996). Paniculate pollution and health: a review of the Utah valley
experience. Journal of Exposure Analysis and Environmental Epidemiology 6(1):
23-34.
Pope, C.A. Ill, Burnett, R.T., Thurston, G.D., Thun, M.J., Calle, E.E., Krewski, D.,
Godleski M.D. (2004). Cardiovascular mortality and long-term exposure to
particulate air pollution. Circulation 109:71-77.
Pope, C.A. HI, Burnett, R.T., Thun, M.J, Calle, E.E., Krewski, D., Ito, K., Thurston, G.D.
(2002). Lung cancer, cardiopulmonary mortality, and long-term exposure to fine
particulate air pollution. Journal of the American Medical Association 287:1132-
1141.
Pope, C.A. Ill, Thun, M.J., Namboodiri, M.M., Dockery, D.W., Evans, J.S., Speizer,
F.E. et al. (1995). Particulate air pollution as a predictor of mortality in a
prospective study of U.S. adults. American Journal of Respiratory and Critical
Care Medicine 151:669-74.
Pope, C.A., Verrier, R.L., Lovett, E.G., Larson, A.C., Raizenne, M.E., Kanner, R.E.,
Schwartz, J., Villegas, G.M., Gold, D.R., Dockery, D.W. (1999). Heart rate
variability associated with particulate air pollution. American Heart Journal
138(5): 890-9.
Rabl A. (2003). Interpretation of air pollution mortality: number of deaths or years of
life lost? Journal of Air and Waste Management Association 53:41-50.
Rothman, N., Haas, R., Hayes, R.B., Li, G.L., Wiemels, J., Campleman, S., Quintana, P.
J. E., Xi, L. J., Dosemeci, M., Titenko-Holland, N. et a!., 1995. Benzene induces
gene-duplicating but not gene-inactivating mutations at the glycophorin A locus
in exposed humans. Proceedings of the National Academy of Sciences 92:4069-
4073.
Rothman, N., Smith, M., Hayes, R.B., Li, G.L., Irons, R.D., Dosemeci, M., Haas, R. et al.
(1996). An epidemic logical study of early biologic effects of benzene in Chinese
workers. Environmental Health Perspectives 104 (Suppl. 6): 1365-1370.
Rothman, N., Li, G.L., Dosemeci, M., Bechtold, W.E., Marti, G.E., Wang, Y.2. et al.
(1996). Hematotoxicity among Chinese workers heavily exposed to benzene.
American Journal of Industrial Medicine 29: 236-246.
Rothman, N., Smith, M.T., Hayes, R.B., Traver, R.D., Hoener, B., Campleman, S., Li,
G.L. et al. (1997). Benzene poisoning, a risk factor for hematological
malignancy, is associated with the NQ01 609CT mutation for rapid fractional
excretion of chlorzoxazone. Cancer Research 57: 2839-2842.
Rushton, L., Romaniuk, H. (1997). A case-control study to investigate the risk of
leukemia associated with exposure to benzene in petroleum marketing and
distribution workers in the United Kingdom. Occupational and Environmental
Medicine 54: 152-166 (Abstract on
http://oem.bmjjournals.eom/cgi/content/abstract/54/3/152).
Ryan, G. et al. (1999). Decline in Lung Function and Mortality: The Busselton Health
Study. Journal of Epidemiology and Community Health 53:230-234.
Samet. J.M., Zeger, S.L., Dominici, F., Curriero, F., Coursac, L, Dockery, D.W. et al.
2000. The National Morbidity, Mortality, and Air Pollution Study. Part II:
44
-------
Morbidity and mortality from air pollution in the United States. Health Effects
Institute (94 Pt 2): 5-70; discussion 71-9.
Schnatter, AR et al. (1996). Lymphohaematopoietic malignancies and quantitative
estimates of exposure to benzene in Canadian petroleum distribution workers.
Occupational and Environmental Medicine 53:773-781. Abstract on
http://oem.bmjjournals.com/cgi/content/abstract/53/ll/773
Schwartz, J. (2001). Air Pollution and Blood Markers of Cardiovascular Risk.
Environmental Health PerspectiveslQ9, supplement 3: 405-9.
Shlyakhter, A.I.,Kammen, D.M. (1992). Sea-Level Rise or Fall? Nature 253:25.
Shlyakhter, A.I. (1994a). An Improved Framework for Uncertainty Analysis:
Accounting for Unsuspected Errors. Risk Analysis 14:441-447.
Shlyakhter, A.I. (1994b). Uncertainty Estimates in Scientific Models: Lessons from
Trends in Physical Measurements, Population and Energy Projections. In
Uncertainty Modeling and Analysis: Theory and Application, B. M. Ayyub and
M. M. Gupta, Eds., Elseiver Science, B. V., 477-496.
Silver, S.R., Rinsky, R.A., Cooper, S.P., Hornung, R.W., and Lai, D. (2002). Effect of
follow-up time on risk estimates: A longitudinal examination of the relative risks
of leukemia and multiple myeloma in a rubber hydrochloride cohort. American
Journal of Industrial Medicine 42: 481-489.
Smith, M.T., Zhang, L., Wang, Y., Hayes, R.B., Li, G., Wiemels, J., Dosemeci, M., et al.
(1998). Increased translocations and aneusomy in chromosome 8 and 21 among
workers exposed to benzene. Cancer Research 58:2176-2181.
Sorlie, P., W. Kannel, et al. (1989). Mortality associated with respiratory function and
symptoms in advanced age; The Framinghatn Study. American Review of
Respiratory Diseases 140:379-84.
Tsuji, H., Venditti, F.J., Manders, E.S., Evans, J.C., Larson, M.G., Feldman, C.L. et al.
(1994). Reduced Heart Rate Variability and Mortality Risk in an Elderly Cohort:
The Framingham Heart Study. Circulation 90:878-83.
Venn, A.J., Lewis, S.A., Cooper, M., Hubbard, R., Britton, J. (2001). Living near a main
road and the risk of wheezing illness in children. American Journal of
Respiratory and Critical Care Medicine 164(12): 2177-80.
Walker KJD, Evans JS, and Macintosh D. (2001). Use of expert judgment in exposure
assessment. Part I. Characterization of personal exposure to benzene. Risk
Analysis 11:308-322.
Whitfield R.G., Wallsten, T.S. (1989). A risk assessment for selected lead-induced
health effects: an example of a general methodology. Risk Analysis 9:197-207.
Wong, O. (1999). A critique of the exposure assessment in the epidemiologic study of
benzene-exposed workers in China conducted by the Chinese Academy of
Preventive Medicine and the U. S. National Cancer Institute. Regulatory
Toxicology and Pharmacology 30: 259-267.
Woodruff, T.J., Grillo, J., Schoendorf, K.C. 1997. The relationship between selected
causes of postneonatal infant mortality and particulate air pollution in the United
States. Environmental Health Perspectives 105:608-612.
Wright GW and Ayton P. (eds.) (1994). Subjective Probability. John Wiley and Sons.
New York, NY.
45
-------
Xu. X., Dockery D. W., Wang, L. (1991). Effects of Air Pollution on Adult Pulmonary
Function. Archives of Environmental Health 46(4), 198-206.
Zhu, Y., Hinds, W.C., Kirn, S., Sioutas, C. (2002). Concentration and size distribution
of ultrafme particles near a major highway. Journal of Air and Waste
Management Association 52:1032-1042.
46
-------
APPENDIX A: LIST OF CHARGE QUESTIONS PROVIDED TO
THEHES
Listed below are the charge questions addressed by the Health Effects Subcommittee of
the Advisory Council in Clean Air Compliance Analysis in this report. Charge Questions
Appear as provided by the Agency.
Charge Question 11. Does the Council support the plans described in chapter 6 for estimating,
evaluating, and reporting changes in health effect outcomes between scenarios? If there are
particular elements of these plans which the Council does not support, are there alternative data
or methods the Council recommends?
Charge Question 12. EPA seeks advice from the Council regarding the technical and scientific
merits of incorporating several new or revised endpoint treatments in the current analysis. These
health effect endpoints include:
a. Premature mortality from paniculate matter in adults 30 and over, PM (Krewski et ai.,
2000);
b. A PM premature mortality supplemental calculation for adults 30 and over using the
Pope 2002 ACS follow-up study with regional controls;
c. Hospital admissions for ail cardiovascular causes in adults 20^64, PM (Moolgavkar et al.,
2000);
d. ER visits for asthma in children 0-18, PM (Morris et al., 1999);
e. Non-fatal heart attacks, adults over 30, PM (Peters et al., 2001);
f. School loss days, Ozone (Gilliland et al., 2001; Chen et al., 2000);
g. Hospital admissions for all respiratory causes in children under 2, Ozone (Burnett et al.,
2001); and,
h. Revised sources for concentration-response functions for hospital admission for
pneumonia, COPD, and total cardiovascular: Samet et al., 2000 (a PM10 study), to Lippmann et
al., 2000 and Moolgavkar, 2000 (PM2.5 studies).
*•».
Charge Question 13. EPA seeks advice from the Council regarding the merits of applying
updated data for baseline health effect incidences, prevalence rates, and other population
characteristics as described in chapter 6. These updated incidence/prevalence data include:
a. Updated county-level mortality rates (all-cause, non-accidental, cardiopulmonary, lung
cancer, COPD) from 1994-1996 to 1996-1998 using the CDC Wonder Database;
b. Updated hospitalization rates from 1994 to 1999 and switched from national rates to
regional rates using 1999 National Hospital Discharge Survey results;
c. Developed regional emergency room visit rates using results of the 2000 National
Hospital Ambulatory Medical Care Survey;
d. Updated prevalence of asthma and chronic bronchitis to 1999 using results of the
National Health Interview Survey (HIS), as reported by the American Lung Association (ALA),
2002;
47
-------
e. Developed non-fatal heart attack incidence rates based on National Hospital Discharge
Survey results;
f. Updated the national acute bronchitis incidence rate using HIS data as reported in ALA,
2002, Table 11;
g. Updated the work loss days rate using the 1996 HIS data, as reported in Adams, et al.
1999, Table 41;
h. Developed school absence rates using data from the National Center for Education
Statistics and the 1996 HIS, as reported in Adams, et al., 1999, Table 46.
1. Developed baseline incidence rates for respiratory symptoms in asthmatics, based on
epidemiological studies (Ostro et al. 2001; Vedal et al. 1998; Yu et al; 2000; McConnell et al.,
1999; Pope et al., 1991).
Charge Question 14. EPA plans to initiate an expert elicitation process to develop a probability-
based method for estimating changes in incidence of PM-related premature mortality. Plans for
this expert elicitation are described in chapter 9 of this blueprint, and a separate charge question
below requests advice from the Council pertaining to the merits of the design of this expert
elicitation. EPA recognizes, however, the possibility that this expert elicitation process may not
be fully successful and/or may not be completed in time to support the current 812 analysis.
Therefore, in order to facilitate effective planning and execution of the early analytical steps
which provide inputs to the concentration-response calculations, EPA seeks advice from the
Council regarding the scientific merits of alternative methods for estimating the incidences of
PM-related premature mortality, including advice pertaining to the most scientifically defensible
choices for the following specific factors:
a. Use of cohort mortality studies, daily mortality studies, or some combination of the two
types of studies
b. Selection of specific studies for estimating long-term and/or short-term mortality effects
c. Methods for addressing -either quantitatively or qualitatively- uncertain factors
associated with the relevant concentration-response function(s), including
i. Shape of the PM mortality C-R function (e.g., existence of a threshold),
ii. PM causality,
iii. PM component relative toxicity, and
iv. PM mortality effect cessation lag structure
v. Cause of death and underlying health conditions for individuals dying
prematurely due to chronic and/or short term exposures to particulate matter
vi. The use of ambient measures of exposure for estimating chronic health effects,
given recent research reviewed in the NAS (2002) report that questions the implications
of using ambient measures in cohort studies
Charge Question 15. EPA estimates of benefit from particulate control may underestimate the
impact of nonfatal cardiopulmonary events on premature mortality and life expectancy. For the
base analyses, which rely on cohort evidence, the limited follow-up periods for the cohorts may
not fully capture the impacts of nonfatal cardiovascular events on premature mortality later in
life. For the alternative analyses -including cost-effectiveness analyses- which rely more on
acute studies and life-expectancy loss, the years of life are estimated only for fatal events. Yet
48
-------
nonfatal events such as myocardial infarction reduce a person's life expectancy by a substantial
percentage.
a. Do you agree that EPA, in the 812 analyses, should adjust benefit estimates to account
for the mortality effects of non-fatal cardiovascular and respiratory events?
b. What medical studies and mathematical models of disease might be useful to review or
use if EPA moves in this direction?
c. When the nonfatal events are valued in economic terms, should EPA assume that the
published unit values for morbidity already account for the life-expectancy loss or should an
explicit effort be made to monetize the resulting longevity losses?
Charge Question 16. In recent EPA rulemakings, EPA's "base estimate" of benefit from PM
control has been based on cohort epidemiological studies that characterize the chronic effects of
pollution exposure on premature death as well as capturing a fraction of acute premature
mortality effects. If these chronic effects occur only after repeated, long-term exposures, there
could be a substantial latency period and associated cessation lag. As such, a proper benefits
analysis must consider any time delay between reductions in exposure and reductions in
mortality rates. For the acute effects, such as those considered in EPA's alternative benefit
analyses, the delays between elevated exposure and death are short (less than two months), and
thus time-preference adjustments are not necessary.
a. In the previous 812 analysis and in recent rulemakings, EPA assumed a weighted 5-year
time course of benefits in which 25% of the PM-related mortality benefits were assumed to occur
in the first and second year, and 16.7% were assumed to occur in each of the remaining 3 years.
Although this procedure was endorsed by SAB, the recent NAS report (2002) found "little
justification" for a 5-year time course and recommended that a range of assumptions be made
with associated probabilities for their plausibility. Do you agree with the NAS report that EPA
should no longer use the deterministic, 5-year time course?
b. One alternative EPA is considering is to use a range of lag structures from 0 to 20-30
years, with the latter mentioned by NAS in reference to the Nyberg et al PM lung cancer study,
with 10 or 15 years selected as the mid-point value until more definitive information becomes
available. If this simple approach is used, should it be applied to the entire mortality association
characterized in the cohort studies, or only to the difference between the larger mortality effect
characterized in the cohort studies and the somewhat smaller effect found in the time series
studies of acute exposure? Should judgmental probabilities be applied to different lags, as
suggested by NAS?
c. Another option under consideration is to construct a 3-parameter Weibull probability
distribution for the population mean duration of the PM mortality cessation lag. The Weibull
distribution is commonly used to represent probabilities based on expert judgment, with the 3-
parameter version allowing the shaping of the probability density function to match expected
low, most likely, and expected high values. EPA is still considering appropriate values for the
low, most likely, and expected high values -and therefore for the Weibull shape and location
parameters- and EPA is interested in any advice the Council wishes to provide pertaining to the
merits of this approach and/or reasonable values for the probability distribution.
Charge Question 17. In support of Clear Skies and several recent rule makings the Agency has
presented an Alternative Estimate of benefits as well as the Base Estimate. EPA developed the
49
-------
Alternative Estimate as an interim approach until the Agency completes a formal probabilistic
analysis of benefits. NAS (2002) reinforced the need for a probabilistic analysis. The Alternative
Estimate is not intended as a substitute method and needs to be considered in conjunction with
the Base Estimate. Presentation of Base and Alternative estimates in the 812 Report may not be
necessary if the probability analysis planned for the 812 Report is successful. While the Base
Estimate assumes that acute and chronic mortality effects are causally related to pollution
exposure, the Alternative Estimate assumes only acute effects occur or that any chronic effects
are smaller in size than assumed in the Base Estimate. The Council's advice is sought on the
following matters:
a. It has been noted by some particle scientists that the size of estimates based on time series
studies that Incorporate a distributed lag model, accounting for effects of 30 to 60 days after
elevated exposure, may be similar in size to some interpretations of the results from the cohort
studies. Does the Council agree that it is a reasonable alternative to use an estimate of the
concentration-response function consistent with this view? If the Council agrees with the
assumption, can it suggest an improved approach for use in an Alternative Estimate? The agency
also seeks advice on appropriate bounds for a sensitivity analysis of the mortality estimate to be
used in support of the Alternative Estimate.
b. An assumption that a specific proportion of the PM-related premature mortality
incidences are incurred by people with pre-existing Chronic Obstructive Pulmonary Disease
(COPD) and that these incidences are associated with a loss of six months of life, regardless of
age at death. If these values are not valid, what values would be more appropriate? Do you
recommend a sensitivity analysis of 1 to 14 years (with the latter based on standard life tables),
as included in the draft regulatory impact analysis of the proposed Nonroad diesel rule?
c. An assumption that the non-COPD incidences of PM-related premature mortality are
associated with a loss of five years of life, regardless of age at death. If these values are not valid,
what values would be more appropriate? Do you recommend a sensitivity analysis of 1 to 14
years (with the latter based on standard life tables), as included in the draft regulatory impact
analysis of the proposed Nonroad diesel rule?
d. Additional quantified and/or monetized effects are those presented as sensitivity analyses
to the primary estimates or in addition to the primary estimates, but not included in the primary
estimate of total monetized benefits. While no causal mechanism has been identified for chronic
asthma and ozone exposure, there is suggestive epidemiologica! evidence.
i. Two studies suggest a statistical association between ozone and new onset asthma
for two'specific groups: children who spend a lot of time exercising outdoors and non-
smoking men. We seek SAB comment on our approach to quantifying new onset asthma
in the sensitivity analyses.
ii. Premature mortality associated with ozone is not currently separately included in
the primary analysis because the epidemiological evidence is not consistent. We seek
SAB comment on our approach to quantifying ozone mortality in the sensitivity analyses.
iii. Does the Council agree that there is enough data to support a separate set of
health impacts assessment for asthmatics? If so, does the approach proposed by the
Agency address the uncertainty in the literature?
Charge Question 29. Does the Council support the plans described in chapter 9 for the expert
elicitation pilot project to develop a probability-based PM2.5 C-R function for premature '
50
-------
mortality, including in particular the elicitation process design? If the Council does not support
the expert elicitation pilot project, or any particular aspect of its design, are there alternative
approaches the Council recommends for estimating PM-related mortality benefits for this
analysis, including in particular a probabilistic distribution for the C-R function to reflect
uncertainty in the overall C-R function and/or its components?
Charge Question 30. EPA plans to develop estimates of an independent mortality effect
associated with ozone, as described in chapter 9. Does the Council support the use of the most
recent literature on the relationship between short-term ozone exposure and daily death rates,
specifically that portion of the literature describing models which control for potential
confounding by PM2.5? Does the Council agree with the use of that literature as the basis for
deriving quantified estimates of an independent mortality impact associated with ozone,
especially in scenarios where short-term PM2.5 mortality estimates are used as the basis for
quantifying PM mortality related benefits? Does the Council support the plans described in
chapter 9 for the pilot project to use this literature to develop estimates of the ozone related
premature mortality C-R function using the three alternative meta-analytic approaches? If the
Council does not support this pilot project, or any particular aspect of its design, are there
alternative approaches to quantifying ozone-related premature mortality which the Council
recommends?
Charge Question 32. Does the Council support the plans described in chapter 10 for evaluating
the quality of data inputs and analytical outputs associated with this study, including the planned
publication of intermediate data products and comparison of intermediate and final results with
other data or estimates? If the Council does not support these plans, are there alternative
approaches, intermediate data products, data or model comparisons, or other data quality criteria
the Council recommends? Please consider EPA's Information Quality Guidelines in this regard.
Charge Question 33. Does the Council support the plans described in Chapter 11 for the
aggregation and presentation of analytical results from this study? If the Council does not
support these plans, are there alternative approaches, aggregation methods, results presentation
techniques, or other tools the Council recommends?
Charge Question 34. Does the Council support the plans describe in Appendix D for updating
the estimated costs and benefits of Title VI programs? If the Council does not support these
plans, are there alternative data, models, or methods the Council recommends?
Charge Question 35. Does the Council support the plans described in Appendix E for the
benzene case study, including the planned specific data, models, and methods, and the ways in
which these elements have been integrated? If the Council does not support these plans, are there
alternative data, models, or methods the Council recommends?
Charge Question 36. A cessation lag for benzene-induced leukemia is difficult to estimate and
model precisely due to data limitations, and EPA plans to incorporate a five-year cessation lag as
an approximation based on available data on the latency period of leukemia and on the exposure
lags used in risk models for the Pliofilm cohort (Crump, 1994 and Silver et ah, 2002). Does the
51
-------
SAB support adoption of this assumed cessation lag? If the Council does not support the
assumed five-year cessation lag, are there alternative lag structures or approaches the Council
recommends?
52
-------
APPENDIX B: BIOSKETCHES OF HES MEMBERS AND
MEMBERS OF THE COUNCIL AND COUNCIL SPECIAL PANEL
FOR THE REVIEW OF THE THIRD 812 ANALYSIS WHO
ASSISTED WITH DEVELOPMENT OF THIS HES ADVISORY
Dr. John Evans
Dr. Evans is Senior Lecturer in Environmental Science at Harvard School of Public
Health, where he serves as co-director of the Program in Environmental Science and Risk
Management. He holds a B.S.E. (Industrial Engineering) and a M.S. (Water Resources
Management) from the University of Michigan and earned his S.M. and Sc.D. in Environmental
Health Sciences at Harvard. Dr. Evans has worked in the field of risk analysis for over twenty
years and has emphasized the importance of characterizing uncertainty in estimates of health
risks in his research. He has experience in uncertainty analysis and has conducted several studies
using formally elicited expert judgment to describe uncertainty in environmental health risks. His
recent work has examined the role of decision and value of information analysis in setting
priorities for environmental research. Dr. Evans has been a member of the Society for Risk
Analysis since it was founded; has served as the Chair of the New England Chapter, and as both
a member of the Editorial Board of the SRA's journal Risk Analysis and as an area editor of Risk
Analysis. He was a member of the NAS Committee on Estimating the Health Benefits of Air
Pollution Regulations and also served on the EPA Science Advisory Board (Drinking Water
Committee). Dr. Evans' current research funding comes largely (over 90%) from the
Government of Kuwait. In the past his work has been funded by a number of sources, including
the US EPA Office for Research and Development, the Mexican Government (through
subcontracts with MIT), several corporations and individuals (through contracts with and/or gifts
to the Harvard Center for Risk Analysis), Health Canada, and the US Nuclear Regulatory
Commission.
Ms. Lauraine G. Chestnut
Ms. Lauraine G. Chestnut, Managing Economist at Stratus Consulting Inc., is an
economist who specializes in the quantification and monetary valuation of human health and
environmental effects associated with air pollutants. She has 20 years of experience with Stratus
Consulting and its predecessors working for clients including the U.S. Environmental Protection
Agency, California Air Resources Board, Environment Canada, World Bank, and Asian
Development Bank, quantifying the damages of air pollution, including human health effects,
visibility aesthetics, materials damages, and crop damage. She has conducted original economic
and survey research to estimate the value to the public of protecting human health and visibility
aesthetics from the effects of air pollution. She has developed quantification models to estimate
the health benefits of reductions in air pollutants that have been used to assess the benefits of
provisions of the Clean Air Act in the U.S., proposed Canadian air quality standards, air quality
standards in Bangkok, and elsewhere. Ms. Chestnut has published articles related to this work in
Land Economics, Environmental Research, Journal of the Air and Waste Management
Association, and Journal of Policy Analysis and Management, and as chapters in the following
53
-------
titled books: Valuing Cultural Heritage, Air Pollution and Health, and Air Pollution's Toll on
Forests and Crops. Ms. Chestnut managed an epidemiology and economic study of the health
effects of particulate air pollution in Bangkok, working closely with the Thai Pollution Control
Department, the School of Public Health at Chulalongkorn University, and the World Bank. Ms.
Chestnut co-authored publications on the Bangkok studies in the Journal of the Air and Waste
Management Association, Environmental Health Perspectives, American Journal of Agricultural
Economics, Journal of Exposure Analysis and Environmental Epidemiology. Ms. Chestnut
received a B.A. in economics from Earlham College, Richmond, Indiana, in 1975, and an M.A.
in economics from the University of Colorado, Boulder, in 1981. She is a member of the
Association of Environmental and Resource Economists and of the Air and Waste Management
Association.
Dr. Dale Hartis
Dr. Dale Hattis is Research Professor with the Center for Technology Environment and
Development (CENTED) of the George Perkins Marsh Institute at Clark University. For the past
twenty-seven years he has been engaged in the development and application of methodology to
assess the health ecological and economic impacts of regulatory actions. His work has focused
on the development of methodology to incorporate interindividual variability data and
quantitative mechanistic information into risk assessments for both cancer and non-cancer
endpoints. Specific studies have included quantitative risk assessments for hearing disability in
relation to noise exposure renal effects of cadmium reproductive effects of
ethoxyethanolneurological effects of methyl mercury and acrylamide and chronic lung function
impairment from coal dust four pharmacokinetic-based risk assessments for carcinogens (for
perchloroethylene ethylene oxide butadiene and diesel particulates) an analysis of uncertainties
in pharmacokmetic modeling for perchloroethylene and an analysis of differences among species
in processes related to carcinogenesis. He has recently been appointed as a member of the
Environmental Health Committee of the EPA Science Advisory Board and for several years he
has served as a member of the Food Quality Protection Act Science Review Board. Currently he
is also serving as a member of the National Research Council Committee on Estimating the
Health-Risk-Reduction Benefits of Proposed Air Pollution Regulations. The primary source of
his recent cooperative agreement support is the U.S. Environmental Protection Agency and
specifically the Office of Research and Development's National Center for Environmental
Assessment. This research includes: (1) Age related differences in susceptibility to
carcinogenesis; towards a quantitative analysis of empirical data. Instrument number (Term:
April 2002-Sept 2003); (2) Methods for evaluating human interindividual variability regarding
susceptibility to particulates (Term Sept 98~September 2002); and (3) also funding from the
State of Connecticut to work on Child/Adult differences in pharmacokinetic parameters, as a
subcontractor as part of a cooperative agreement. He has been a councilor and is a Fellow of the
Society for Risk Analysis and serves on the editorial board of its journal Risk Analysis. He holds
a Ph.D. in Genetics from Stanford University and a B.A. in biochemistry from the University of
California at Berkeley.
Mr. Fintan Hurley
54
-------
Mr. Fintan Hurley is currently Research Director at the Institute of Occupational
Medicine (IOM) - an independent non-profit organization carrying out research and consulting
in occupational and environmental health, exposure and risk assessment - in Edinburgh,
Scotland, UK. Dr. Hurley graduated 1st Honours B.A. in Mathematics, Statistics and Economics
at the National University of Ireland (NUI) in Cork in 1970; MA (NUI) Mathematics and
Statistics in 1971; post-graduate research in Bayesian methods at University of Edinburgh. His
main research activities have been (i) epidemiological studies of the health effects of long-term
occupational exposures to dusts, pesticides and (ii) since the early 1990s, on estimating the
public health impacts and associated costs of outdoor air pollution, overall and from particular
sources (electricity generation and transport...). His research experience has been multi-
disciplinary, working closely with physicians, lexicologist, exposure specialists, ergonomists,
economists, psychologists, mathematical modelers as well as other statisticians. Since 1996 he
has been a member of the Committee on the Medical Effects of Air Pollutants (COMEAP) of the
UK Department of Health and was from 1998-2002 a member of the Expert Panel on Air Quality
Standards (EPAQS) of the UK Department of Environment (then, DEFRA).
Dr. Patrick Kinney
Dr. Kinney is Associate Professor of Clinical Public Health in Environmental Health
Sciences, Sc.D. Environmental Health Sciences/Air Pollution Control and Physiology at the
Harvard University School of Public Health. His areas of research include Air pollution
epidemiology, exposure assessment, exposure modeling, risk assessment. He is the Author of
EPA ozone and PM criteria documents - epidemiology sections; member of NAS panel on
Health Benefits Analysis.
Dr. Michael Kleinman
Dr. Michael T. Kleinman is a Professor of Community and Environmental Medicine at
the University of California, Irvine. He has a Ph.D. in Environmental Health Sciences from New
York University and a M.S. in Chemistry (Biochemical Toxicology) from the Polytechnic
Institute of Brooklyn. He also holds a B.S. in Chemistry from Brooklyn College, City University
of New York. Dr. Kleinman has extensive experience in studies of the effects of airborne
contaminants on health. His current research activities include inhalation studies with laboratory
animals and human volunteers to test hypotheses related to defining causal relationships between
health effects and components of ultrafine, fine and coarse pollutant particles. A key component
in these studies, which include both laboratory based and epidemiological panel research
programs, is the assessment of exposure and the relationship of exposure to dose. Dr. Kleinman
also has had extensive experience in determinations of atmospheric transport of chemical
contaminants. Dr. Kleinman has previously served as a consultant to the HEES. He currently is a
member of the executive committee of the Southern California Particle Center and Supersite
which is a multi-institutional consortium based at UCLA and which is supported by USEPA and
the California Air Resources Board. He is currently the Chair of the Air Quality Advisory
Committee for the state of California. This committee reviews the scientific basis of air quality
regulations promulgated by the California EPA. Dr. Kleinman is a member of a National
Academy of Sciences Committee to evaluate the preparation of the US Navy to operate in
55
-------
Chemical, Biological and Radiological Warfare situations. He was also the co-Chair of a
National Academy of Sciences Committee to evaluate current capabilities related to Protection of
Deployed Forces Against Chemical and Biological Weapons. He is the past chair of the
Environmental Division of the Air and Waste Management Association and is a member of the
executive committee of the University of California Toxic Substance Teaching and Research
Program.
Dr. Nino Kiinzli
Dr. Nino Kunzli, MD PhD, former Assistant Professor (P.O.) at the Institute for Social
and Preventive Medicine (ISPM) at the University of Basel (Switzerland), is Associate Professor
at University of Southern California Keck School of Medicine (Department of Preventive
Medicine; Environmental Health Science Division), Los Angeles. As an environmental
epidemiologist, his main areas of focus are exposure to and health effects of ambient air
pollution and the public health impact of these effects. He is a co-investigator and member of
research teams such as the Swiss Study on Air Pollution and Lung Diseases in Adults
(SAPALDIA; Swiss National Science Foundation), the European Community Respiratory Health
Survey II (European Community Research Programs), where he leads the Air Pollution Central
Unit, the European Population Exposure Distribution Assessment Study (EXPOLIS), and the UC
Berkeley Ozone Study (Prof. Ira Tager; NIH grant). At USC he collaborates with the repeated
cohort Children Health Study on air pollution and health in 12 South Coast Basin communities
(NIH). He serves on national and international expert committees and as reviewers of the major
journals in this field. With the Trinational European Air Pollution Impact Assessment project,
published in Lancet, he intensified particularly a debate about the interpretation of air pollution
epidemiology and its application to risk assessment. The concepts published in the American
Journal of Epidemiology have been subject of several committees such as from WHO, leading to
methodological guidelines and further work by many others. He was a member of the U.S.
National Academy of Sciences NRC Committee on Estimating the Health-Risk-Reduction
Benefits of Proposed Air Pollution Regulations which also addressed the issue of how to
interpret effect estimates from different study designs.
w -
Dr. Morton Lippmann
Current'professional affiliations and positions held by Dr. Lippman include: Professor,
NYU School of Medicine, Area(s) of expertise, and research activities and interests: Human
environmental exposure assessment and associated health effects, respiratory tract dosimetry,
aerosol science and technology, risk assessment. Leadership positions in national associations or
professional publications or other significant distinctions: Past Chair of: EPA SAB CASAC SAB
Exposure Comm. NIOSH Board of Scientific Counselors Amer. Conf. of Governmental
Industrial Hygienists, Past President: International Society of Exposure Analysis, Educational
background, especially advanced degrees, including when and from which institutions these
were granted: B.Ch.E. (1954) - The Cooper Union S.M. (1955) - Harvard Univ. Ph.D. (1967) -
New York Univ.
56
-------
Dr. Warner North
Dr. D. Warner North is president and principal scientist of North Works, Inc., a consulting
firm in Behnont, California, and consulting professor in the Department of Management Science
and Engineering at Stanford University. Over the past thirty years Dr. North has carried out
applications of decision analysis, risk analysis, and cost-benefit analysis for electric utilities in
the US and Mexico, for the petroleum and chemical industries, and for US government agencies
with responsibility for energy and environmental protection. He has served as a member and
consultant to the Science Advisory Board of the US Environmental Protection Agency since
1978, and as a presidentially appointed member of the US Nuclear Waste Technical Review
Board (1989-1994). Dr. North is a co-author of many reports dealing with environmental risk for
the National Research Council of the National Academy of Sciences, including "Risk
Assessment in the Federal Government: Managing the Process" (1983), "Improving Risk
Communication" (1989),"Science and Judgment in Risk Assessment" (1994), and
"Understanding Risk: Informing Decisions in a Democratic Society" (1996). Dr. North was a
member of the Board on Radioactive Waste Management of the National Research Council from
1995 until 1999. He was the chair for the steering and advisory committees for the International
Workshop on the Disposition of High-Level Radioactive Waste, held November 4-5,1999, and
leading to the National Research Council report, "Disposition of High-Level Waste and Spent
Nuclear Fuel: The Continuing Societal and Technical Challenges," published in June 2001. Dr.
North is a past president (1991-92) of the international Society for Risk Analysis, a recipient of
the Frank P. Ramsey Medal from the Decision Analysis Society in 1997 for lifetime
contributions to the field of decision analysis, and the 1999 recipient of the Outstanding Risk
Practitioner Award from the Society for Risk Analysis. Dr. North received his Ph.D. in
operations research from Stanford University and his B.S. in physics from Yale University.
Dr. Bart Ostro
Bart Ostro, Ph.D., is currently the Chief of the Air Pollution Epidemiology Unit, Office
of Environmental Health Hazard Assessment, and California Environmental Protection Agency.
His primarily responsibilities are to formulate the Agency's recommendations for state ambient
air quality standards and to investigate the potential health effects of criteria air pollutants. His
previous research on mortality and morbidity effects of air pollution, has contributed to the
determination of federal and state air pollution standards for ozone and particulate matter. Dr.
Ostro was also a co-author of the EPA regulatory impact analysis that was a basis for the federal
ban of lead in gasoline. Dr. Ostro has served as a consultant with several federal and
international institutions including the World Health Organization and the World Bank, and with
several foreign governments including Mexico, Indonesia, Italy, the European Union, Thailand,
and Chile. He currently serves on the National Academy of Sciences' Committee on Estimating
the Health Risk Reduction Benefits of Proposed Air Pollution Regulations, and is on the
Scientific Oversight Committee for ATHENA (Air Pollution Health Effects in Europe and North
America) for the Health Effects Institute. Dr. Ostro received a Ph.D. in Economics from Brown
University and a Certification in Environmental Epidemiology from the State of California. He
has published over 60 articles on air pollution epidemiology and environmental economics in
peer reviewed journals. His current research interests involve conducting epidemiological studies
57
-------
on the mortality and morbidity effects of criteria air pollutants, examining the health effects of
traffic, and quantifying the health benefits and associated uncertainties related to air pollution
control.
, Dr. Rebecca Parkin
Dr. Rebecca T. Parkin is an Associate Professor in the Department of Environmental and
Occupational Health with a joint appointment in the Department of Epidemiology and
Biostatistics in the School of Public Health and Health Services at The George Washington
University. She is also the Scientific Director of the Center for Risk Science and Public Health
at the University. Previously Dr. Parkin was director of Scientific, Professional and Section
Affairs at the American Public Health Association; the assistant commissioner of the Division of
Occupational and Environmental Health at the New Jersey Department of Health; and an
environmental epidemiologist at the Centers for Disease Control. Her areas of expertise include
environmental epidemiology, public health policy, vaccine risk/benefit communication, and
environmental health risk assessment and communication. She has been a member of the
National Research Council's (NRC's) Water Science and Technology Board; and has served on
numerous committees of the NRC, the Institute of Medicine, Environmental Protection Agency,
Health and Human Services, and Agency for Toxic Substances and Disease Registry.
Throughout her career, she has served as a site visitor for the Council on Education for Public
Health, and as a peer reviewer for several professional journals focused on environmental health.
Recently, she has coauthored a book on the CCL microbiai pathogens and related risk
assessment issues. Dr. Parkin received her A.B. in sociology from Cornell University; M.P.H. in
environmental health and Ph.D. in epidemiology from Yale University; and Certificate in
Science, Technology, and Policy from Princeton University. She has been honored by Yale
University as a Distinguished Alumna for her extensive public service.
Dr. Thomas Wallsten
Dr. Thomas S. Wallsten is a professor in the Department of Psychology and in the
Program in-Cognitive Science and Neuroscience. He received his Ph.D. from the .University of
Pennsylvania in 1969, did a postdoctoral fellowship at the University of Michigan in 1970, and
then joined the faculty at the University of North Carolina, Chapel Hill. He was professor of
psychology and director of the Cognitive Science program when he left UNC-CH in 2000. Over
the past years he was a visiting professor or visiting scholar at the University of Chicago, Duke
University, Haifa University in Israel, and University of Oldenburg in Germany. He is a
mathematical and cognitive psychologist with expertise in subjective probability, judgment,
choice, decision behavior, and related areas of decision science and cognitive psychology. His
current research focuses on subjective probability encoding and representation, communication
of opinion, and human information processing under uncertainty. This research has been
supported over the past 30 years primarily by grants from the National Science Foundation
(NSF), with occasional additional support from other agencies. Current grants are from NSF and
the Air Force Office of Scientific Research. Among his advisory roles, he was editor of the
Journal of Mathematical Psychology from 1990-1994, associate editor of Psychometrika from
1984-1988, associate editor of the Journal of Experimental Psychology: Learning, Memory, and
58
-------
Cognition from 2000-2003, and on numerous editorial boards. He served in various advisory
roles for NSF: During 1995-1997 on the grant review panel for Methodology, Measurement, and
Statistics Program in the Division of Social, Behavioral, and Economic Research; in 2000 as a
member of the Committee of Visitors for Social, Behavioral, and Economic Sciences
Directorate; in 2003 as a member of the Committee of Visitors for the Behavioral and Cognitive
Sciences Directorate; in 1998 on an ad hoc NSF_EPA grant review panel. In 2002,he was a grant
review panel member for the Cognition and Student Learning Program of the Department of
Education Office of Educational Research and Improvement.
59
------- |