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Estimating Mortality Risk Reduction and Economic 

Benefits from Controlling Ozone Air Pollution 

Committee on Estimating Mortality Risk Reduction 

Benefits from Decreasing Tropospheric Ozone 

Exposure, National Research Council 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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Committee on Estimating Mortality Risk Reduction Benefits from 

Decreasing Tropospheric Ozone Exposure 

Board on Environmental Studies and Toxicology 

Division on Earth and Life Studies
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v 

COMMITTEE ON ESTIMATING MORTALITY RISK REDUCTION BENEFITS 

FROM DECREASING TROPOSPHERIC OZONE EXPOSURE

Members 

JOHN C. BAILAR III (Chair), University of Chicago, IL

RICHARD T. BURNETT, Health Canada, Ottawa, ON, Canada

LAURAINE G. CHESTNUT, Stratus Consulting Inc., Boulder, CO

W. MICHAEL FOSTER, Duke University Medical Center, Durham, NC 

A. MYRICK FREEMAN, III, Bowdoin College, Brunswick, ME 

MONTSERRAT FUENTES, North Carolina State University, Raleigh, NC

DANIEL S. GREENBAUM, Health Effects Institute, Boston, MA

ALAN KRUPNICK, Resources for the Future, Washington, DC

NINO KÜNZLI, Center for Research in Environmental Epidemiology at 

Municipal Institute of Medical Research, Barcelona, Spain

KENT E. PINKERTON, University of California, Davis, CA

ARMISTEAD G. RUSSELL, Georgia Institute of Technology, Atlanta, GA

HELEN SUH, Harvard School of Public Health, Boston, MA 

EVELYN O. TALBOTT, University of Pittsburgh Graduate School of Public 

Health, PA 

Staff 

RAYMOND A. WASSEL, Project Director 

NORMAN GROSSBLATT, Senior Editor 

MIRSADA KARALIC-LONCAREVIC, Manager, Technical Information Center

JOHN BROWN, Program Associate 

RADIAH ROSE, Senior Editorial Assistant 

Sponsor 

U.S. ENVIRONMENTAL PROTECTION AGENCY
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

http://www.nap.edu/catalog/12198.html

vi 

BOARD ON ENVIRONMENTAL STUDIES AND TOXICOLOGY1

Members 

JONATHAN M. SAMET (Chair), Johns Hopkins University, Baltimore, MD 

RAMON ALVAREZ, Environmental Defense Fund, Austin, TX 

JOHN M. BALBUS, Environmental Defense Fund, Washington, DC 

DALLAS BURTRAW, Resources for the Future, Washington, DC 

JAMES S. BUS, Dow Chemical Company, Midland, MI 

RUTH DEFRIES, University of Maryland, College Park 

COSTEL D. DENSON, University of Delaware, Newark 

E. DONALD ELLIOTT, Willkie Farr & Gallagher LLP, Washington, DC 

MARY R. ENGLISH, University of Tennessee, Knoxville

J. PAUL GILMAN, Covanta Energy Corporation, Fairfield, NJ 

SHERRI W. GOODMAN, Center for Naval Analyses, Alexandria, VA 

JUDITH A. GRAHAM (Retired), Pittsboro, NC 

WILLIAM P. HORN, Birch, Horton, Bittner and Cherot, Washington, DC 

WILLIAM M. LEWIS, JR., University of Colorado, Boulder

JUDITH L. MEYER, University of Georgia, Athens 

DENNIS D. MURPHY, University of Nevada, Reno

PATRICK Y. O’BRIEN, ChevronTexaco Energy Technology Company, 

Richmond, CA 

DOROTHY E. PATTON (Retired), U.S. Environmental Protection Agency, 

Chicago, IL 

DANNY D. REIBLE, University of Texas, Austin 

JOSEPH V. RODRICKS, ENVIRON International Corporation, Arlington, VA 

ARMISTEAD G. RUSSELL, Georgia Institute of Technology, Atlanta 

ROBERT F. SAWYER, University of California, Berkeley 

KIMBERLY M. THOMPSON, Massachusetts Institute of Technology, Cambridge 

MONICA G. TURNER, University of Wisconsin, Madison 

MARK J. UTELL, University of Rochester Medical Center, Rochester, NY 

CHRIS G. WHIPPLE, ENVIRON International Corporation, Emeryville, CA 

LAUREN ZEISE, California Environmental Protection Agency, Oakland 

Senior Staff 

JAMES J. REISA, Director 

DAVID J. POLICANSKY, Scholar 

RAYMOND A. WASSEL, Senior Program Officer for Environmental Studies 

EILEEN N. ABT, Senior Program Officer for Risk Analysis 

SUSAN N.J. MARTEL, Senior Program Officer for Toxicology 

KULBIR BAKSHI, Senior Program Officer 

ELLEN K. MANTUS, Senior Program Officer 

RUTH E. CROSSGROVE, Senior Editor 

 1

This study was planned, overseen, and supported by the Board on Environmental 

Studies and Toxicology. 
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

http://www.nap.edu/catalog/12198.html

vii 

OTHER REPORTS OF THE

BOARD ON ENVIRONMENTAL STUDIES AND TOXICOLOGY

Respiratory Disease Research at NIOSH (2008) 

Evaluating Research Efficiency in the U.S. Environmental Protection Agency 

(2008) 

Hydrology, Ecology, and Fishes of the Klamath River Basin (2008) 

Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk 

Assessment (2007) 

Models in Environmental Regulatory Decision Making (2007) 

Toxicity Testing in the Twenty-first Century: A Vision and a Strategy (2007) 

Sediment Dredging at Superfund Megasites: Assessing the Effectiveness (2007) 

Environmental Impacts of Wind-Energy Projects (2007) 

Scientific Review of the Proposed Risk Assessment Bulletin from the Office of 

Management and Budget (2007) 

Assessing the Human Health Risks of Trichloroethylene: Key Scientific Issues 

(2006) 

New Source Review for Stationary Sources of Air Pollution (2006) 

Human Biomonitoring for Environmental Chemicals (2006) 

Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment (2006) 

Fluoride in Drinking Water: A Scientific Review of EPA’s Standards (2006) 

State and Federal Standards for Mobile-Source Emissions (2006) 

Superfund and Mining Megasites—Lessons from the Coeur d’Alene River Basin (2005) 

Health Implications of Perchlorate Ingestion (2005) 

Air Quality Management in the United States (2004) 

Endangered and Threatened Species of the Platte River (2004) 

Atlantic Salmon in Maine (2004) 

Endangered and Threatened Fishes in the Klamath River Basin (2004) 

Cumulative Environmental Effects of Alaska North Slope Oil and Gas Development (2003) 

Estimating the Public Health Benefits of Proposed Air Pollution Regulations 

(2002) 

Biosolids Applied to Land: Advancing Standards and Practices (2002) 

The Airliner Cabin Environment and Health of Passengers and Crew (2002) 

Arsenic in Drinking Water: 2001 Update (2001) 

Evaluating Vehicle Emissions Inspection and Maintenance Programs (2001) 

Compensating for Wetland Losses Under the Clean Water Act (2001) 

A Risk-Management Strategy for PCB-Contaminated Sediments (2001) 

Acute Exposure Guideline Levels for Selected Airborne Chemicals (five volumes, 2000-2007) 

Toxicological Effects of Methylmercury (2000) 

Strengthening Science at the U.S. Environmental Protection Agency (2000) 

Scientific Frontiers in Developmental Toxicology and Risk Assessment (2000) 

Ecological Indicators for the Nation (2000) 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

http://www.nap.edu/catalog/12198.html

viii 

Waste Incineration and Public Health (2000) 

Hormonally Active Agents in the Environment (1999) 

Research Priorities for Airborne Particulate Matter (four volumes, 1998-2004) 

The National Research Council’s Committee on Toxicology: The First 50 

Years (1997) 

Carcinogens and Anticarcinogens in the Human Diet (1996) 

Upstream: Salmon and Society in the Pacific Northwest (1996) 

Science and the Endangered Species Act (1995) 

Wetlands: Characteristics and Boundaries (1995) 

Biologic Markers (five volumes, 1989-1995) 

Review of EPA’s Environmental Monitoring and Assessment Program (three 

volumes, 1994-1995) 

Science and Judgment in Risk Assessment (1994) 

Pesticides in the Diets of Infants and Children (1993) 

Dolphins and the Tuna Industry (1992) 

Science and the National Parks (1992) 

Human Exposure Assessment for Airborne Pollutants (1991) 

Rethinking the Ozone Problem in Urban and Regional Air Pollution (1991) 

Decline of the Sea Turtles (1990) 

Copies of these reports may be ordered from the National Academies Press 

(800) 624-6242 or (202) 334-3313 

www.nap.edu 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

http://www.nap.edu/catalog/12198.html

ix

Preface 

The U.S. Environmental Protection Agency (EPA) asked for an 

independent study by the National Research Council to evaluate the scientific 

and technical bases of approaches used by EPA for estimating ozone-mortality 

reduction and associated benefits of health-based standards over time. In 

response, the National Research Council established the Committee on Mortality 

Risk Reduction Benefits from Decreasing Tropospheric Ozone Exposure. 

Biographic information on the committee members is presented in Appendix A. 

In the course of preparing this report, the committee met four times. At 

three of the meetings—which were held in Irvine, CA; Washington, DC; and 

Woods Hole, MA—officials of EPA and academic researchers were invited to 

meet with the committee and present their views and results of their work. 

Interested members of the public at large were also given an opportunity to 

speak on those occasions. The fourth meeting was held in closed session so that 

the committee could complete drafting its report. Subsequently, the committee 

held three teleconferences to complete its deliberations. 

As this report was being written, EPA was in the process of reviewing the 

existing National Ambient Air Quality Standards (NAAQS) for ozone. The primary (health-based) ozone NAAQS was set at 0.08 parts ppm for the annual 

fourth-highest daily maximum 8-h average concentration, averaged over 3 years. 

The committee’s statement of task (see Chapter 1) and its deliberations were not 

dependent on EPA’s decisions provided in its final rule on March 12, 2008 

which lowered the level of the 8-h standard to 0.075 ppm. 

The committee received oral and written presentations from John Balmes, 

University of California, San Francisco; Michelle Bell, Yale University; Kiros 

Berhane, University of Southern California; J.R. DeShazo, University of 

California, Los Angeles; James Hammitt, Harvard University; Bryan Hubbell, 

EPA; Al McGartland, EPA; Joel Schwartz, Harvard University; Anne Smith, 

CRA International; Deborah Shprentz, consultant to the American Lung 

Association; and Ira Tager, University of California, Berkeley. 

Nathalie Simon, of EPA, provided the committee with information from 

EPA and the published scientific literature. 

This report has been reviewed in draft form by persons chosen for their 

diverse perspectives and technical expertise in accordance with procedures 
Copyright © National Academy of Sciences. All rights reserved.

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x Preface 

approved by the National Research Council’s Report Review Committee. The 

purpose of the independent review is to provide candid and critical comments 

that will assist the institution in making its published report as sound as possible 

and to ensure that the report meets institutional standards of objectivity, 

evidence, and responsiveness to the study charge. The review comments and 

draft manuscript remain confidential to protect the integrity of the deliberative 

process. We thank the following for their review of this report: Francesca 

Dominici, Johns Hopkins University; Mark Frampton, University of Rochester; 

John Graham, Frederick S. Pardee RAND Graduate School; Jane Hall, 

California State University; James Hammitt, Harvard University; Fintan Hurley, 

Institute of Occupational Medicine (in the United Kingdom); Jonathan Levy, 

Harvard University; Thomas Lumley, University of Washington; Frederick 

Lurmann, Sonoma Technology, Inc.; Jennifer Peel, Colorado State University; 

Richard Smith, University of North Carolina; Ira Tager, University of 

California, Berkeley; and Sverre Vedal, University of Washington. 

Although the reviewers listed above have provided many constructive 

comments and suggestions, they were not asked to endorse the conclusions or 

recommendations, nor did they see the final draft of the report before its release. 

The review of the report was overseen by Gilbert Omenn, University of 

Michigan Medical School, and Edwin Clark, II, Earth Policy Institute. 

Appointed by the National Research Council, they were responsible for making 

certain that an independent examination of the report was carried out in 

accordance with institutional procedures and that all review comments were 

carefully considered. Responsibility for the final content of the report rests 

entirely with the author committee and the institution. We thank the report 

review monitor and coordinator. 

We also thank Bailus Walker, Jr. for his constructive service on the 

committee; he resigned from the committee for personal reasons. 

The committee’s work for this report was assisted by staff of the National 

Research Council’s Board on Environmental Studies and Toxicology (BEST). 

We thank Raymond Wassel, project director, and James Reisa, director of 

BEST. Technical information was provided by Mirsada Karalic-Loncarevic. 

Invaluable logistical support was provided by John Brown. Other staff members 

who contributed to this effort are Radiah Rose (senior editorial assistant) and 

Heidi Murray-Smith (research associate). The report was edited by Norman 

Grossblatt. 

John C. Bailar III, Chair

Committee on Mortality Risk Reduction 

Benefits from Decreasing Tropospheric 

Ozone Exposure 
Copyright © National Academy of Sciences. All rights reserved.

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xi

Contents 

SUMMARY ...................................................................................................................... 3 

1 INTRODUCTION ............................................................................................... 17 

 Charge to the Committee, 18 

2 OVERVIEW OF AMBIENT-OZONE STANDARDS DEVELOPMENT 

AND BENEFITS ASSESSMENT ....................................................................... 23 

 Introduction, 23 

 Setting National Ambient Air Quality Standards for Ozone, 23 

 Implementing the NAAQS, 29 

 The Scientific Basis of Primary NAAQS for Ozone, 30 

Regulatory Benefits Assessment for Setting and Implementing National 

 Ambient Air Quality Standards, 33 

Environmental Protection Agency’s Approach to Estimating Ozone Mortality 

 Impacts and Valuing Mortality Risk Reduction, 41 

 Overview of Other Approaches, 44 

 The Major Questions, 47 

 

3 AMBIENT OZONE AND RELATED POLLUTANTS.................................... 48

 Ozone Formation and Transport, 48 

 Ozone Measurement, 53 

 Sources of Ozone Precursors and Ozone Control, 55 

 Related Pollutants, 56 

 Ozone Control, 63 

 Ozone Dynamics and Monitoring: Implications for Health Studies, 66 

 Ozone-Exposure Modeling, 70 

 Summary, 72 

4 CONTRIBUTIONS OF RELEVANT HEALTH STUDIES TO THE 

ESTIMATION OF REDUCTIONS IN PREMATURE MORTALITY .......... 75

Introduction, 75 

 Biologic Plausibility, 76 

 Ozone-Mortality Studies, 78 

 Susceptibility, 96 

 Other Factors That Affect Interpretation of Ozone Mortality Effects, 102 
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xii Contents 

Use of Epidemiologic Information in Ozone-Related Risk and Benefits 

 Assessment, 117 

 Conclusions and Recommendations, 121 

5 ECONOMIC VALUATION OF REDUCTION IN MORTALITY RISK 

ASSOCIATED WITH AMBIENT OZONE .................................................... 128

Introduction, 128 

 Conceptual Underpinnings of Valuation of Mortality Risk, 129 

 Empirical Methods of Valuing Mortality-Risk Reductions, 134 

Environmental Protection Agency’s Current Approach to Valuing Mortality- 

 Risk Reductions, 139 

 Empirical Evidence on Valuation of Mortality-Risk Reductions, 144 

 Findings and Recommendations, 155 

 Recommendations for Future Research, 158 

6 OVERALL CONCLUSIONS AND RECOMMENDATIONS ....................... 160

Ozone Mortality Effect, 160 

Interpretation of Results of Health Studies, 161 

Health-Based Information for Benefits Assessments, 169 

Valuation, 172 

Research Recommendations, 176 

Regulatory Impact Analyses Involving Ozone Mortality, 179 

REFERENCES ............................................................................................................ 182

ABBREVIATIONS ...................................................................................................... 204

APPENDIX A: BIOGRAPHICAL INFORMATION ON THE COMMITTEE 

ON ESTIMATING MORTALITY RISK REDUCTION 

BENEFITS FROM DECREASING TROPOSPHERIC OZONE 

EXPOSURE....................................................................................... 206 

APPENDIX B: ENVIRONMENTAL PROTECTION AGENCY’S REGULATORY 

IMPACT ANALYSIS FOR THE FINAL OZONE NATIONAL 

AMBIENT AIR QUALITY STANDARD....................................... 211 

BOXES, FIGURES, AND TABLES 

BOXES 

1-1 Statement of Task, 19 

2-1 The Estimation of the “Policy Relevant Background,” 27 

2-2 Definition of Value of a Statistical Life in Relation to Willingness to Pay, and a 

Numerical Example, 36 

2-3 Definition of Value of a Statistical Life Year in Relation to Value of a Statistical 

Life, and Numerical Examples, 37 

3-1 Policy Relevant Background, 54 

4-1 Definitions of Time-Series Analysis and Meta-Analysis, 80 
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Contents xiii 

FIGURES 

1-1 Methods used by EPA to assess the effects of NAAQS and control strategies 

developed to implement the standards, 22 

2-1 Counties violating 1997 primary 8-h NAAQS for ozone and other photochemical 

oxidants, 26 

2-2 Counties with monitors readings that would violate alternate 8-h ozone standards 

of 0.070 and 0.075 ppm proposed by EPA in June 2007 (on basis of 2003-2005 

monitoring data), 28 

3-1 Source and chemical links between ozone and PM formation, 49 

3-2 Ozone isopleth diagrams showing the nonlinear response of ozone to emissions 

of VOCs and NOx and how they can vary from a city center to a downwind 

location, 51 

3-3 Ozone concentrations in Atlanta in 2006: (a) diurnal variation of ozone on July 22; 

(b) daily maximum, 51 

3-4 Simulated ozone concentration and sensitivity of ozone to Atlanta-area NOx and 

VOC emissions for downtown Atlanta and a suburban location downwind, 52 

3-5 Anthropogenic sources of 2002 ozone-precursor emissions of VOCs and NOx, 56 

3-6 Left, ozone and PM2.5 nonattainment areas in the eastern United States in 2006. 

Right, implementation of CAIR and other controls is expected to bring future 

ozone concentrations in many areas in the eastern United States into attainment of 

the previous 0.08-ppm ozone NAAQS, 57 

3-7 Composition of PM2.5 in representative urban and rural locations. Urban sites are 

Toronto, ON, Canada; Washington, DC; Atlanta, GA; Mexico City, Mexico; Los 

Angeles, CA; and Fresno, CA, 63 

3-8 Calculated daily sensitivities of maximum 8-h averaged ozone in Atlanta, Chicago, 

Houston, Los Angeles, and New York regionwide changes in NOx emissions and 

corresponding simulated concentrations, 65 

3-9 Activity patterns by time of day. Adapted from U.S. National Human Activity 

Pattern Survey, 69 

4-1 Percentage increase in ozone-associated mortality in meta-analyses and time-series 

studies, 90 

TABLES 

2-1 History of Primary NAAQS for Ozone and Other Photochemical Oxidants, 25 

3-1a Day-to-Day Correlation Between Air Pollutants in Boston, MA, by Season 

(Summer Nonshaded, Winter Shaded), 1999-2004, 58 

3-1b Day-to-Day Correlation Between Air Pollutants in St. Louis, MO, by Season 

(Nonwinter Clear, Winter Shaded), April 2001-September 2002, 58 

3-1c Day-to-Day Correlation Between Air Pollutants in Los Angeles, CA, by Season 

(Nonwinter Clear, Winter Shaded), June 2002-December 2003, 59 

3-2 Pollutant Correlations at Jefferson Street SEARCH Site, Atlanta, GA, 

1999-2006, 61 

3-3 Simulated Sensitivity of Annual Average Ozone to NOx and Sensitivity of FourthHighest 8-h Average Ozone to NOx, 65 

4-1 Summaries of Recent Studies of Acute Effects of Ozone on Mortality, 82 
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xiv Contents 

4-2 Summaries of Recent Time Series Studies of Acute Effects of Ozone on 

Mortality, 84 

4-3 Summary of Meta-analyses, 86 

B-1 (EPA 2008b, Table 7-14) Illustrative Strategy to Attain 0.075 ppm: Estimated 

Annual Reductions in the Incidence of Premature Mortality Associated with Ozone 

Exposure in 2020 (Incremental to Current Ozone Standard, Arithmetic Mean, 95% 

Confidence Intervals in Parentheses, 212 
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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3

Summary 

Increased concentrations of ozone in the lower atmosphere are formed 

from pollutants emitted by such human activities as the combustion of fossil 

fuels. Natural sources of emissions, such as vegetation, also contribute to ozone 

formation. Because human exposure to ozone in the lower atmosphere at the 

increased concentrations that result from precursor emissions can cause respiratory problems and other health effects, ozone is one of the six criteria pollutants 

regulated by the U.S. Environmental Protection Agency (EPA) under the Clean 

Air Act.1

 

Studies published since 1990 have yielded mixed evidence of a relationship between short-term exposure to ozone and premature death. According to 

analyses of evidence published in recent years, the risk of death in the population increases slightly but consistently as exposure to ozone increases. However, 

at the same time, interpretation of this evidence by EPA and scientists outside 

the agency has been complicated by ozone’s occurrence in mixtures with other 

pollutants that have similar effects and by uncertainties including those which 

result from using outdoor-ozone measurements to estimate exposures of people 

who spend most of their time indoors. 

The Clean Air Act requires EPA to review periodically the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants.2

 Each time 

NAAQS are reviewed, the EPA administrator must weigh the most recent evidence and current uncertainties and make a public-health policy judgment about 

whether the existing standards are adequate to protect the public health with an 

adequate margin of safety or should be lowered or raised. 

 1

Most ozone in the lower atmosphere is formed by a complex series of photochemical 

reactions in the presence of sunlight involving nitrogen oxides and volatile organic compounds. Ozone is used here to refer to the broad array of photochemical oxidants in ambient air, of which ozone is the primary component. 2

As this report was being prepared, EPA was reviewing the NAAQS for ozone. EPA’s 

final decision on the ozone NAAQS based on its review was announced in March 2008. 
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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4 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

After the NAAQS are determined, EPA must address any mitigation 

measures needed to reduce emissions. When deciding on mitigation actions expected to cost more than $100 million per year, EPA, like other federal agencies, 

is required to carry out a cost-benefit analysis of alternative regulatory strategies, such as those to attain the ozone NAAQS. However, EPA is not allowed to 

consider monetary costs when setting NAAQS. 

To assess the benefits portion of its cost-benefit analysis of the ozone 

NAAQS, EPA uses results of epidemiologic studies to estimate the number of 

premature deaths avoided by the expected reduction in ozone concentration for 

the population at risk (that is, the number of deaths postponed to some future 

year and generally with a different cause of death). It then assigns a monetary 

value to the avoided deaths by using a concept known as the value of a statistical 

life. That value is derived from studies of adults (mostly of working age) who 

indicate or reveal, through choices in the labor market or in other ways, the 

amount that they would be willing to pay to change their risk of death in a given 

period by a small amount. EPA applies the same value to all premature deaths 

avoided regardless of the age or health status of the population experiencing the 

potential change in risk of death. However, the willingness to pay for a reduction in the risk of death hypothetically depends on the characteristics (for example, life expectancy or health status) of the individuals affected or on the nature 

of the risk (for example, accident vs illness). 

In light of recent evidence on the relationship of ozone to mortality and 

questions about its implications for benefit analysis, EPA asked the National 

Research Council to establish a committee of experts to evaluate independently 

the contributions of recent epidemiologic studies to understanding the size of the 

ozone-mortality effect in the context of benefit analysis. The committee was also 

asked to assess methods for estimating how much a reduction in short-term exposure to ozone would reduce premature deaths, to assess methods for estimating associated increases in life expectancy, and to assess methods for estimating 

the monetary value of the reduced risk of premature death and increased life 

expectancy in the context of health-benefits analysis. The charge to this National 

Research Council committee focused on benefit analysis; it did not include considering how evidence is used to set the ozone NAAQS.3

 

OVERALL CONCLUSIONS AND RECOMMENDATIONS 

The committee concludes from its review of the health-based evidence 

that short-term exposure to ambient ozone is likely to contribute to premature deaths. Despite some continuing questions about the interpretation of the 

evidence, the committee concluded that the evidence is strong enough to be used 

in the estimation of the expected mortality-reduction benefits of a decrease in 

exposure to ozone. Human chamber and toxicologic studies have yielded strong 

 3

A full statement of the committee’s charge is presented in Box 1-1 of Chapter 1. 
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Summary 5 

evidence indicating that short-term exposure to ozone can exacerbate lung conditions, causing illness and hospitalization, and can potentially lead to death. 

The available evidence on ozone exposure and exacerbation of heart conditions, 

which is less abundant, points to another concern. Epidemiologic studies have 

also found that exposure to ozone is associated with adverse lung and heart effects. 

Recommendation: The committee recommends that ozone-related 

mortality be included in future estimates of the health benefits of reducing ozone exposure. The committee further recommends that the 

greatest emphasis be placed on estimates from new systematic multicity analyses that use national databases of air pollution and mortality, such as in the National Morbidity, Mortality, and Air Pollution 

Study, without excluding consideration of meta-analyses of previously 

published studies. Emphasis should also be placed on risk estimation 

based on analyzing data on multiple days so that delayed acute effects 

estimates can be included. The health-benefits estimates should be accompanied by a broad array of analyses of uncertainty but should 

give little or no weight to the assumption that there is no causal association between estimated reductions in premature mortality and reduced ozone exposure. 

Because older persons appear to be at higher risk of health-related effects 

from ozone pollution, it is appropriate to consider whether the willingness to pay 

for mortality risk reductions should and could reflect the number of years of life 

by which life would be extended by reductions in ozone. The committee concludes that the evidence is insufficient to support a specific adjustment of 

the aggregate willingness to pay for reduction in annual mortality risk on 

the basis of differences in remaining life expectancy. 

Recommendation: Although there are many concerns about the accuracy of a willingness-to-pay (WTP) value and the corresponding value 

of a statistical life (VSL) that does not vary with population or risk 

characteristics, the committee recommends the use of a constant WTP 

and corresponding VSL as the most scientifically supportable approach to monetary valuation of ozone-related mortality risk given 

the information available in the epidemiologic and economics literature. 

INTERPRETATION OF RESULTS OF HEALTH STUDIES 

The associations between ozone exposure and premature mortality in the 

recent health studies appear robust, but several factors create considerable uncertainty about them. Those factors can affect estimates of risk of ozone-related 
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6 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

mortality in various ways. In some cases, the factors would cause an underestimation of risk; in other cases, an overestimation. On balance, the committee 

considers the evidence from the studies to be strong enough for use in deriving 

risk estimates, but the various factors and their potential effects on the estimates 

should be fully acknowledged. 

Short-Term Exposure to Ambient Ozone 

Time-series epidemiologic studies of short-term effects of ozone typically 

characterize human exposure by using ambient concentrations measured at fixed 

outdoor monitoring sites. Exposure is characterized by applying an averaging 

period to the daily ambient monitoring data. Changes in the average values are 

then linked with changes in mortality. When averaged over 24 h, ambient concentrations are weakly associated with corresponding personal ozone exposure, 

although the association is stronger in the summer than in winter. For shorter 

averaging periods, such as the afternoon (when both personal outdoor activity 

and ozone concentration can be at their highest), results from one study suggest 

that hourly or daily peak ambient ozone concentration may be an appropriate 

proxy for corresponding hourly or peak personal exposure. Whether observations from that study are relevant for people at risk for ozone-related death warrants further examination. 

The choice of averaging period to characterize short-term ozone exposure 

in linking ambient ozone concentration with mortality risk can have a large effect on estimates of benefits of emission-control programs. For example, under 

some conditions, efforts to lower emissions of oxides of nitrogen could reduce 

the daily peak ozone concentration but raise daily average concentrations (see 

Chapter 3). Thus, a cost-benefit analysis of an emission-control program that 

examines mortality and daily average concentrations of ozone could appear to 

have a negative effect, whereas an analysis that examines mortality and daily 

peak concentrations could appear to show a benefit. It is not known which averaging period reflects personal exposure more accurately or is more closely related to mortality risk. 

Recommendation: Future studies of the effects of short-term ozone 

exposure should determine whether and how much daily peak exposures, such as 1-h or 8-h exposures, and longer-term average exposures, such as over 24 h, are associated with ozone-related mortality. 

Benefits assessors at EPA and elsewhere should use the results to 

identify the appropriate exposure averaging periods so that they can 

estimate how efforts to attain the ozone NAAQS will affect ozone exposure and health. Regulators should take into account the possibility 

that the effects of ozone-control strategies averaged over 24 h may be 

quite different from those averaged over shorter periods. 
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Summary 7 

Potential Confounding by Other Pollutants 

Studies have not been sufficient to control fully for potential confounding 

by or ozone interaction with constituents of airborne particulate matter that has a 

diameter equal to or less than 2.5 μm (PM2.5). Such constituents include sulfates, 

acids, elemental and organic carbon, and metals. The potential for confounding 

of ozone health effects by PM2.5 constituents differs by region and season. For 

example, in the eastern United States, confounding is most likely in the summer 

months, when ozone and PM2.5 are strongly correlated in many locations. In the 

winter, the potential for confounding is likely to be less. It will be difficult to 

address such confounding with currently available data, however, because data 

on PM2.5 components at many sites have only recently begun to be routinely 

collected and because winter ozone concentrations (see next section) are often 

not measured. 

Recommendation: Epidemiologic research on associations between air 

pollution and health outcomes should investigate regional and seasonal associations between ambient (outdoor) concentrations and human exposures to ozone and PM2.5. It should also investigate how data 

on pollutants can be used to control for confounding and correlations 

between the various pollutant measures. When possible, researchers 

should address those issues by focusing on groups of people who are 

sensitive to ozone and by using data on the chemical and physical 

components and size distribution of ambient particles. 

Recommendation: EPA and the scientific community should account 

for seasonal and geographic variability in the relationship between 

ozone and its potential confounders and should increasingly include 

the growing database on PM2.5 constituents in analyses of confounding 

of ozone associations. The most relevant particle-component data 

should be collected frequently enough to improve understanding of 

the potential for confounding. 

Ozone-Mortality Relationships During Winter Months 

There is a lack of observed association between ozone and mortality during periods when ozone is low, such as winter. Reasons for the lack of association are not well understood in part because of the decrease in monitoring during 

those periods. Better understanding of ozone-mortality relationships in the winter is important for full exploration of effects at low concentrations. Although 

ambient ozone is one of the best-characterized pollutants in the United States, 

ozone monitors are usually operated only during the so-called ozone season—

the warmer period of the year, which varies from city to city. 
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8 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Recommendation: EPA and states should extend operation of ozone 

monitoring into winter and report the results. The winter program 

should be sufficient to allow researchers to examine seasonal differences in risk, how these seasonal differences vary spatially between 

communities with warmer and cooler winters, and ozone-mortality relationships at lower ozone concentrations. Ozone is a regional pollutant, so winter measurements need not be collected at all the summer 

locations; but if measurements are collected in winter, they should be 

collected with the same frequency as summer measurements. 

Frailty and Ozone Mortality 

Benefits assessors seek information on whether the mortality risk associated with acute ozone exposure is attributable to short-term displacement (in this 

case, advancement) of deaths that would have occurred in a few days or more 

without acute ozone exposure. If it is so attributable, they can focus their efforts 

on estimating the value that frail people would place on reducing their ozonemortality risk. 

On the basis of available evidence, the committee concludes that 

deaths related to exposure to ozone are not restricted to people who are at 

high risk of death within a few days. For example, a recent study of data collected from several U.S. cities reports that short-term ozone exposure is likely to 

contribute to shortening life and not only among people who are near death. 

However, because the evidence comes from only one study, it warrants confirmation by other studies. 

Recommendation: EPA and the scientific community should conduct 

additional studies to investigate whether and how much ozone-related 

mortality is restricted to people who are already at high risk of death 

within a few days and how much ozone-related mortality occurs in 

people who are not already at risk of death in a few days. The studies 

should include use of various methods, for example, focus on investigating subjects who have diseases, such as diabetes or heart disease, 

that are known to be associated with air-pollution-related mortality 

risk. 

Susceptibility 

Preliminary results indicate that the effect of acute ozone exposure on 

mortality is likely to be larger than average in persons with pre-existing 

disease, especially lung and heart diseases. The list of factors that plausibly 

modify effects is rather long and still insufficiently investigated (see Chapter 4). Although susceptibility factors are important, the distribution of ozonemortality-effect estimates among the categories of susceptibility is not ade-
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Summary 9 

quately known. Consequently, the overall (population-weighted average) mortality effect in the total population is the only currently available basis of risk 

assessments; this approach is a source of an unknown amount of uncertainty in 

calculating the overall benefit of an ozone reduction in reducing mortality risk. 

Recommendation: EPA and the scientific community should identify 

personal characteristics that are important in understanding ozonemortality relationships. They should develop a distribution of ozonemortality effect estimates among the categories of susceptibility; this 

will enable benefits assessment to include quantitative details of the 

heterogeneity of effects in the total population. 

Presence or Absence of a Threshold for Ozone-Related Mortality 

The association between short-term variations in ambient ozone concentrations and fluctuations in mortality rates is usually characterized as linear. Because the association is based on epidemiologic studies that can only approximate exposure on the basis of ambient monitoring data, the assumption of 

linearity should be viewed with caution. At low ozone concentrations, the question arises whether the association is linear or more accurately characterized as 

having a “threshold”—a concentration of ozone below which exposure poses no 

risk of death. Individuals have their own susceptibility, which is characterized 

by a unique exposure-response association; this association may include a 

unique threshold value that can vary with susceptibility of the individual at any 

given moment and with the averaging period used to assess exposure. 

On the basis of its review of the evidence, the committee concludes 

that the association between short-term changes in ozone concentrations 

and mortality is generally linear throughout most of the concentration 

range, although uncertainties make it difficult to determine whether there 

is a threshold for the association at the lower end of the range. If there is a 

threshold, it is likely to be below the current NAAQS. 

Recommendation: EPA and the scientific community should explore 

further how personal thresholds may vary and the extent to which 

one’s threshold depends on one’s frailty at any given moment. Because it is not clear whether there is an association between ozone and 

mortality in the cooler months, warmer months should be examined 

separately. The research should involve panel studies of individuals 

considered to be susceptible to premature death from ozone exposure, 

such as those with impaired lung or heart function. A sensitivity 

analysis is needed to assess how different thresholds in exposureresponse relationships may affect ozone-mortality risk estimates that 

are based on results of epidemiologic studies. 
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10 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Accounting for a Lag in Mortality Response to Ozone 

Deaths related to short-term ozone exposure may not occur until several 

days after the exposure or may be associated with multiple short-term exposures. 

Many studies of short-term effects investigate a change in death rates for only 

one or a few days, but distributed-lag models can be used to look further ahead 

to capture delayed mortality, often referred to as a subacute response. Distributed-lag analyses appear to capture the overall effects of ozone better than 

do single-day models, but there have been relatively few such analyses. 

Recommendation: EPA and the scientific community should develop 

appropriate databases and conduct distributed-lag analyses in future 

epidemiologic investigations to improve understanding of the statistical distribution of time between an increase in the ambient ozone concentration and the occurrence of deaths. 

Chronic Exposures 

EPA benefits assessments have not included estimates of mortality risk 

due to long-term (chronic) exposure to ozone, because evidence does not directly demonstrate a causal relationship when the period between exposure and 

death is longer than a few days. However, the observed associations between 

ozone exposure and decreased small-airway lung function during childhood and 

adolescence suggest that ozone-related mortality is at least partially attributable 

to exposures that last more than a few days. The general association between 

poor lung function and shortened life expectancy is strong and well established, 

so evidence of an effect of ozone exposure on lung function increases the plausibility of mortality from chronic exposure. The weak current evidence from 

cohort studies of an association of premature mortality with chronic exposure to ozone suggests that risks may be larger than those observed in acute 

effects studies alone.

The standard approach to investigating effects of cumulative ozone exposure on life expectancy is the cohort study, in which large numbers of subjects 

are followed for several years. After taking into account all other factors that are 

likely to affect mortality, cohort studies can test the null hypothesis that mortality is the same among populations that have different ozone-exposure histories. 

However, none of the cohort studies available was designed to investigate 

chronic effects of ozone, and differences in ozone exposure among subjects in 

each study tended to be rather small. If further confirmed, the weak current 

evidence from cohort studies of an association of premature mortality with 

longer-term exposure would support the notion that effects seen in timeseries studies reflect only a portion of the total effect. 
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Summary 11 

Recommendation: EPA, the National Institutes of Health, and the scientific community should encourage additional studies of the association between long-term ozone exposure and mortality. They should 

also encourage development of models of long-term ozone exposures 

that can account for variations in exposure at the individual level and 

between and within cities. As new cohort evidence of effects of chronic 

exposures becomes available, EPA should consider including it in its 

benefits assessments. 

Effect of Ozone Exposure on Life Expectancy 

Effects of long-term cumulated exposure are, by design, not addressed in 

short-term time-series studies. Distributed-lag models integrate the distribution 

of the time between exposure and death, but they focus on a short window (several days to weeks) after exposure. It is appropriate to use time-series results 

to estimate changes in life expectancy due to acute exposures by using cohort life-table methods if it is assumed that all members of the population at 

risk for death from ozone exposure have the same life expectancy as others 

in the same age and sex cohort (see Chapter 4). However, the committee 

finds that that assumption is questionable because people at greatest risk 

for death from short-term ozone exposure are likely to be those who have 

pre-existing diseases and thus life expectancy lower than average for their 

age. 

Recommendation: Additional studies are needed to assess the extent 

to which differences in susceptibility in a general population affect the 

variability associated with mortality risk estimates. To the extent that 

data are not available, models and assumptions can be used for sensitivity analysis to assess how risk estimates might vary with susceptibility. 

Characterizing Mortality Risk by Using Studies of Acute 

and Chronic Exposure 

Ozone-mortality risk is often expressed as the expected number of deaths 

attributable to ozone air pollution or lives saved by reducing ozone pollution by 

some amount. However, reductions in ozone exposure are expected to increase 

life expectancy and decrease age-adjusted annual death rates (for example, 

number of deaths per 100,000 of population). Thus, the number of older people 

would increase, the absolute number of deaths at higher ages would increase, 

and the annual number of deaths would return to normal in future years, although they would occur at higher ages and probably with different causes. Alternative approaches to the expression of ozone-mortality effects, such as death 

rates, will have similar results if one is concerned only with short-term effects of 
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12 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

pollution changes. However, when one includes subacute and chronic effects 

estimates on mortality, the discrepancies between the results of the different 

approaches increase, and the conceptual flaws of the “attributable-cases” model 

become more pronounced. 

Recommendation: EPA should evaluate alternative approaches for 

expressing ozone-mortality risk associations and consider the implications of using them in benefits assessments. EPA should consider placing greater emphasis on reporting changes in age-specific death rates 

in the relevant population and develop models for consistent calculation of changes in life expectancy and changes in numbers of deaths at 

all ages. 

VALUATION 

Willingness-to-Pay Estimates 

Estimates of the value of a statistical life (VSL) are derived from estimates 

of an individual’s willingness to pay (WTP) for changing his or her mortality 

risk by a small amount in a given period (usually annual) (see Chapter 2). The 

objective of an economic-benefits assessment is to develop an aggregate estimate of the welfare gain for everyone who benefits from a policy or program 

that is intended to reduce risk. Both economic theory and available empirical 

evidence are inconclusive about how people’s WTP values vary with two important individual characteristics: age, as a proxy for remaining life expectancy, and 

health status. The evidence is also inconclusive about how WTP varies with 

cause of death, but there is greater clarity that reducing the risks of latent mortality response should be valued less than reducing risks of immediate death. The 

committee concludes that the empirical evidence is insufficient to support a 

specific quantitative adjustment of WTP estimates to account for differences in remaining life expectancy, but it does not reject the general concept 

that such adjustments may be appropriate. It is plausible that people with 

shorter remaining life expectancy would be willing to devote less of their resources to reducing their mortality risk than those with longer remaining life 

expectancy. In contrast, if the condition causing the shortened life expectancy 

can be treated and improved and an acceptable quality of life can be preserved 

or restored, people may put a high value on extending life, even if they have 

other health impairments or are quite elderly. 

Recommendation: Researchers should continue to explore how WTP 

for reduction in mortality risk may vary with individual characteristics (such as age and health status), type of risk (such as accident vs 

illness), and time between changes in air quality and changes in risk. 
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Summary 13 

Efforts to obtain better information about the preferences of the older 

population regarding reductions in mortality risk will probably entail 

greater use of surveys in which subjects respond to hypothetical situations. 

Value of a Statistical Life, Individual Characteristics, and Risk Contexts 

To estimate VSL, EPA mostly uses WTP values that are based on a context (for example, traffic accidents or workplace accidents) and a population that 

differ from the context and population relevant to the pollution-related risks that 

EPA is assessing. Two general approaches are available for measuring WTP for 

changes in mortality risk. The revealed-preference approach analyzes actual 

human behavior from which WTP for mortality-risk reductions may be estimated, for example, a wage-risk study of people’s decisions on tradeoff between 

income and job-related mortality risk. The stated-preference approach surveys 

subjects’ responses to hypothetical situations designed to reveal their WTP. 

EPA’s use of average WTP values in different risk contexts and for different population characteristics introduces considerable uncertainty about 

how these factors affect estimates of benefits. However, the current literature is inconclusive about how and how much the WTP values may vary 

with those factors. Although it is difficult to say how much the WTP values 

may differ, it is apparent that wage-risk studies cannot focus on the population and the risk context for ozone mortality. 

Recommendation: EPA should ensure that estimates of average WTP 

selected from the literature reflect results of both revealed-preference 

studies and stated-preference studies. EPA should consider the 

strengths and weaknesses of each study approach and consider how 

closely the available studies match the policy context in population at 

risk and type of risk. EPA should give less weight to wage-risk studies 

in selecting estimates of the WTP than in the past. 

The Value of a Statistical Life Year 

Given that the committee recommends the development of models for estimating life years saved (in addition to estimating changes in annual death rates 

and reductions in premature deaths), is it feasible to assign a monetary value 

directly to changes in life expectancy? Some analysts have converted VSL estimates into monetary values per statistical life year (VSLY) (see Chapter 2). Just 

as for VSL, there is a choice between using a constant or non-constant VLSY. 

Because a calculation of life years saved takes into account the remaining life 

expectancy of those whose deaths may have been prevented in a given period, 

use of a constant VSLY assumes that WTP values for mortality-risk reductions 
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14 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

are consistently declining with increasing age. Available empirical evidence 

does not support that assumption, so it does not support the use of a constant VSLY for benefits assessment. However, the economics literature does 

not reject the use of a non-constant VSLY (or a non-constant VSL). There 

is likely to be good reason to use non-constant values if there were sufficient 

empirical evidence of how WTP for mortality risk reduction varies with 

differences in remaining life expectancy and other factors. However, the 

committee concludes that current evidence is not sufficient to assign a nonconstant VSLY or non-constant VSL. 

Recommendation: Unless future research produces empirical support 

for the assumptions that underlie a constant VSLY, EPA should not 

attempt to make valuation adjustments for changes in remaining life 

expectancy by estimating life years saved and applying a constant 

VSLY. More research is needed on appropriate ways to measure the 

values that people attach to changes in life expectancy. 

Sensitivity Analyses 

Use of the average VSL obtained from the literature may overestimate the 

WTP to reduce ozone-related risk of premature death. That is because the population of older people appears to have greater mortality risk associated with 

ozone. Because older people have average remaining life expectancy that is substantially less than that of the whole population, the WTP to reduce the risk of 

death in the older population might be less than the WTP of the population as a 

whole. However, the effect of shorter life expectancy on older people’s WTP 

may be offset to some extent by a higher WTP for a reduction in risk because of 

their poorer health status or their higher baseline risk compared with those of the 

general population. Results in the empirical literature are not consistent, but several studies suggest that WTP to reduce mortality risk is constant or declines 

slightly with age. That implies that a proportional adjustment of the VSL 

for remaining life expectancy (that is, using a constant VSLY) would result 

in using too low a value of WTP for reducing ozone-related mortality. 

Recommendation: Given the uncertainty in the accuracy of available 

estimates of the VSL for ozone-related mortality, EPA should conduct 

sensitivity analyses that use a range of estimates or assumptions to see 

how the overall conclusions of the cost-benefit comparison might 

change. The selection of alternative assumptions for the sensitivity 

analyses could be based on either theory or evidence. However, when 

there is less confidence in the alternative assumptions used in sensitivity analyses, their results should not be given equal weight in the presentation of results. 
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Summary 15 

Recommendations for Future Research on Valuation 

There is a fundamental need to understand better how age and remaining 

life expectancy affect WTP for reductions in mortality risk or increased life expectancy. An important next step is to ask that researchers report total age effects (WTP by age cohort) in addition to effects of age alone on WTP for a small 

reduction in mortality risk in a given period. Given the correlation of age with 

some of the other factors, there may be less uncertainty in the estimates of a total 

age effect. However, age-related income differences, sex differences, health 

differences, and the like would then be embedded in the estimates of WTP, and 

it might not be appropriate to use different VSLs that have these effects embedded. 

Several recent economic studies have attempted to assess the effects of 

age and other factors on valuation. However, the efforts have been hampered by 

the lack of availability of the datasets produced for the published studies. EPA 

should urge researchers whom it funds for WTP studies to make their datasets 

available for future meta-analyses in addition to providing their published results. 

EPA and the scientific community should explore and develop methods 

for characterizing and valuing changes in mortality risk that reflect the full life 

cycle. Studies to date have focused on WTP for annual changes in mortality risk, 

but the risk change of interest in most pollution-control assessments is more 

comprehensively described as a shift in survival probabilities across a large part 

of the human life span. 

Environmental-benefits assessments rely primarily on estimates of WTP 

for reductions in risks of accidental death to estimate values for reducing risks of 

illness-related deaths. It is unknown how risk context (such as illness vs a workrelated accident) affects a valuation estimate. EPA and the scientific community 

should seek to learn more about how mortality-risk characteristics affect the 

valuation of reducing risks. 

FUTURE REGULATORY-IMPACT ANALYSES 

INVOLVING OZONE MORTALITY 

Because short-term exposure to ambient ozone is likely to contribute to 

premature deaths, future regulatory-impact analyses (RIAs) concerning ozonecontrol measures should include the benefits of reduced mortality risk. As in 

EPA’s RIA for the recently finalized ozone NAAQS, emphasis should be on 

using estimates from new systematic multicity analyses that used national databases of air pollution and mortality, such as in the National Morbidity, Mortality, and Air Pollution Study, without excluding consideration of meta-analysis of 

previously published studies. Future RIAs should give little or no weight to the 

assumption that there is no causal association between estimated reductions in 
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16 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

premature mortality and reduced ozone exposure. Health-benefits estimates 

should be accompanied by a broad array of analyses of uncertainty. 

Distributed-lag models over several days appear better than single-day 

models at capturing the acute and subacute mortality effects of ozone exposure 

and should be part of future benefits assessments to the extent that they are supported in the literature. 

Future RIAs should incorporate research results on the mortality effects of 

chronic ozone exposure and research that addresses key uncertainties related to 

potential confounding factors, exposure measures, and susceptibility as appropriate. 

Despite many concerns about the accuracy of any specific WTP value and 

a corresponding VSL that does not vary with population or risk characteristics, 

the committee recommends a single VSL as the most scientifically supportable 

approach at present for monetary valuation of ozone-related mortality. Before 

making a substantial change in its approach for valuation of mortality-risk reductions, EPA should have fairly conclusive empirical evidence to support the 

change. It is the committee’s judgment that the available evidence is not now 

sufficient to support such a change, but sensitivity analyses should explore alternative approaches and further research should be conducted to answer the questions raised about the validity of EPA’s current approach. Benefits-assessment 

methods may need to be revised as new information emerges on characteristics 

of populations susceptible to an ozone-mortality risk and on variations in WTP 

for mortality-risk reductions (or increases in life expectancy) based on different 

population characteristics. 

EPA should consider placing greater emphasis on reporting changes in 

age-specific death rates and changes in life expectancy in the relevant populations than on reporting estimates of lives saved or premature deaths avoided. 

In this report, the committee has identified major gaps in knowledge about 

methods for assessing benefits of ozone-related mortality risk reduction and has 

recommended research strategies to close those gaps. The committee recognizes 

that many of the recommended research activities are complex and will be difficult to undertake, and that sufficient resources may not be available to undertake 

them all in the near term. Therefore, EPA and other agencies that might carry 

out the recommended research will need to set priorities and develop a strategy 

for addressing the various information needs. 
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17

1 

Introduction

The Clean Air Act requires the U.S. Environmental Protection Agency 

(EPA) to issue and review periodically the National Ambient Air Quality Standards (NAAQS) for each of six criteria pollutants. One of those pollutants is 

ozone in the lower atmosphere.1

 Although ozone was originally viewed as an 

urban pollutant (associated largely with such locations as Los Angeles), it is 

now recognized that ozone formation and transport over much larger areas result 

in increased exposures to humans nationwide (e.g., NRC 1991). International 

transport of ozone exacerbates the problem (Jacob et al. 1999). 

Efforts to mitigate ambient ozone involve controlling precursor emissions 

(nitrogen oxides [NOx] and volatile organic compounds [VOCs]) from a wide 

range of stationary sources (such as factories, electricity-generating facilities, 

and gasoline stations) and mobile sources. Although EPA is not allowed to consider costs and benefits when setting NAAQS, economic analyses are carried out 

for the proposed and final NAAQS to estimate costs and benefits expected to 

result from the standards. And federal agencies deciding on (generally national) 

actions expected to cost more than $100 million per year are required to carry 

out a cost-benefit analysis of alternative regulatory strategies and to assess the 

distribution of their impacts in different segments of society. 

In past assessments of the benefits of regulations to mitigate ozone, EPA 

has addressed the relationship between ozone exposure and respiratory disorders. 

EPA’s reviews since the Regulatory Impact Analysis for the 1997 NAAQS 

(EPA 1997a) have included the results of epidemiologic studies that link ambient ozone concentrations with premature deaths in sensitivity analyses, but EPA 

has not included these mortality results in their primary estimates of the benefits 

 1

In this report ozone is used to refer to the broad array of photochemical oxidants present in ambient air. 
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18 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

of reductions in ambient ozone concentrations because of uncertainty about the 

appropriate interpretation of these results. 

Studies published since 1990 have yielded evidence in support of a relationship between short-term exposure and premature death. They include cityspecific time-series studies, many of which have been included in recent metaanalyses (Bell et al. 2004, 2005; Ito et al. 2005; Levy et al. 2005). However, 

interpretation of the evidence is complicated by ozone’s occurrence in mixtures 

of other pollutants whose concentrations fluctuate in a similar manner and can 

be influenced by short-term meteorologic changes. It is important to understand 

whether it is ozone or a copollutant that is causing health effects, because steps 

to control the wrong agent will be both expensive and ineffective. Interpretation 

of the health studies results is also complicated by uncertainties that result from 

relying on ozone measurements from outdoor monitoring sites to estimate exposures of people who spend most of their time indoors. 

If changes in risks of premature mortality are attributed to changes in ambient ozone concentrations in regulatory benefits assessments, EPA also needs 

an estimate of the monetary value of such changes in mortality risk. In previous 

sensitivity analyses of mortality risk reduction benefits from ozone reductions, 

EPA used the same value of statistical life (VSL) as that used for analysis of 

other mortality risks, such as those associated with particulate matter with a diameter less than or equal to 2.5 microns (PM2.5). Available VSL estimates are 

drawn largely from studies of working-age adults with average remaining life 

expectancies. There are many questions about the applicability of these estimates to mortality risks associated with ozone, which may fall disproportionately to an older population with shorter remaining life expectancy and more 

frail health status. 

CHARGE TO THE COMMITTEE 

In light of the recent evidence on ozone mortality risk and questions about 

its implications for benefit analysis, EPA asked the National Research Council 

for scientific advice on how the ozone-mortality research findings could be used 

in the context of health-benefit analyses associated with regulatory assessments. 

In response, the National Research Council established the Committee on 

Mortality Risk Reduction Benefits from Decreasing Tropospheric Ozone 

Exposure (see Appendix A). 

The Statement of Task to the committee (see Box 1-1) includes evaluation 

of the scientific and technical bases of approaches used by EPA for estimating 

reductions in mortality risk and associated benefits of health-based ozone standards over time. The committee was to assess methods for estimating reductions 

in premature death due to diminished short-term exposure to ozone, increases in 

life expectancy, economic valuation of the increased life expectancy, and associated uncertainties and their general implications for decision-making. The 
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Introduction 19 

BOX 1-1 Statement of Task 

An NRC committee will evaluate the scientific and technical bases of 

approaches used by EPA for estimating ozone mortality risk reduction and 

associated benefits of health-based standards over time. It will assess 

methods for estimating reductions in premature mortality due to diminished 

short-term exposure to ozone, increases in life expectancy, economic 

valuation of the increased life expectancy, and associated uncertainties 

and their general implications for decision making. In addition, the committee will recommend approaches for characterizing and communicating 

each of those aspects in regulatory health benefit analyses. 

Specifically, the committee’s evaluation will include consideration of 

the following aspects: 

The committee will take into account the relevant reports of past 

NRC and IOM committees, as well as risk assessment for particulate matter (PM) carried out by the EPA. 

(1) Relative contributions of recent studies (especially those published since 2003) for characterizing the size of the ozone-mortality effect 

in the context of benefits analysis. 

(2) Potential implications of methods used in the recent studies on 

reported benefits estimates (e.g., selection of data considered in the studies, selection of mortality effect estimates from within the considered data, 

control for effect moderators [such as temporal trends], treatment of potential publication bias, or other factors). Include consideration of the likely 

direction and magnitude of any influences that may result from choice of 

methods. 

(3) Available data and methods to account for the relative roles of 

potential confounders, such as copollutants, and the influence they have 

on estimates of ozone mortality effects. 

(4) The most appropriate exposure metrics for use in developing a 

concentration-response function designed to quantify the number of premature mortalities associated with specific regulatory options. How does 

the choice of exposure metrics affect benefits estimation? Include consideration of dose estimation, particularly for sensitive groups.

(5) Adequacy of a basis for estimating the likely impact on life expectancy from reductions in short-term daily exposures to ozone. If there is an 

adequate basis, provide specific recommendations, if possible, on approaches for how EPA should quantitatively express the magnitude and 

associated uncertainties of this impact. 

(6) Strengths and weaknesses of the data, methods, and assumptions employed by EPA for sensitivity analyses in the context of an ozonemortality effect relationship. 

(7) Quantitative approaches for estimating the degree of uncertainty 

in premature mortality estimates associated with reductions in ambient 

(Continued) 
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20 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

BOX 1-1 Continued 

ozone concentrations. Aspects to be considered will include both parameter and model uncertainty in the concentration-response function, differences within and between the epidemiologic and toxicologic data bases, 

reliance on surrogates of personal exposure, identification of sensitive 

populations, and other factors. Identify methods of presenting the quantitative uncertainty estimates. 

(8) Scientific approaches for assigning economic values to reductions in mortality risk when the reduction in risk results in changes in lifeexpectancy of varying lengths. If there is an adequate basis for quantifying 

those changes, consider: 

(a) How the current understanding of premature mortality associated 

with short-term ozone exposure informs the most appropriate scientific approach to economic valuation of benefits. Consider methods to 

account for baseline health status, baseline and the magnitude of the 

change in life-expectancy, differences across various sectors of the 

population, uncertainty, and other relevant factors. 

(b) Applicability of the economics literature on mortality risk valuation 

and the associated methodologies developed for economic valuation 

of premature mortality reductions in the context of the health effects 

of ozone. 

(c) Issues that are specific to ozone and those which may be more 

broadly applicable to benefits assessments for other risk reduction 

strategies. 

(9) Major gaps in knowledge about ozone-mortality benefits analysis 

and the most promising research strategies to close those gaps. Identify 

any additional data, analyses, or research needed to separate the relative 

contributions of ozone and other gaseous or particulate components of the 

air pollution mix to the total short term premature mortality effect documented in the literature. 

In assessing the methods for estimating ozone mortality risk, the 

committee will not develop its own estimate of such risk. In assessing the 

methods for economic valuation of reductions in mortality risk, the committee will not itself judge the appropriateness of values assigned to a life 

saved or life years added. 

Sponsor: U.S. Environmental Protection Agency.

committee was asked in the Statement of Task to consider the relative contributions of recent studies (especially those published since 2003) to characterization 

of the size of the ozone-mortality effect in the context of benefit analysis. The 
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Introduction 21 

recent studies include Bell et al. (2004); Bell et al. (2005); Ito et al. (2005); and 

Levy et al. (2005). The committee was also to consider the potential implications of the methods (such as criteria for selection of data) used in the recent 

studies. 

The committee was asked specifically not to develop its own estimate of 

ozone mortality risk or to judge the appropriateness of values assigned to a life 

saved or life years added by decreases in ozone exposure. Because the committee was asked to focus on human mortality risk reduction and associated benefits, 

it considered changes in human morbidity as an end point only to the extent that 

they illuminate issues related to mortality. The committee was not asked to assess changes in other effects of ozone (referred to as secondary effects), such as 

effects on agricultural crops and forests that would result from changes in ozone 

concentrations. 

In carrying out its charge, the committee considered presentations made 

during its public sessions and relevant scientific and technical documents prepared by EPA and other organizations. The committee sought to benefit from 

and build on the work of other advisory groups. For example, the National Research Council report titled Estimating the Public Health Benefits of Proposed 

Air Pollution Regulations evaluated methods used by EPA to estimate health 

benefits, primarily the analysis of mortality associated with exposure to airborne 

particulate matter (NRC 2002). The Institute of Medicine report Valuing Health 

for Regulatory Cost-effectiveness Analysis (IOM 2006) addressed analytic and 

policy issues, including the use of cost-effectiveness analysis to estimate healthrelated effects of regulatory actions. EPA’s Science Advisory Board (SAB) has 

completed several reviews of ozone mortality in EPA’s benefit-analysis framework. An SAB developed an advisory report on mortality risk valuation and 

how the valuation may be affected by differences in life expectancy (EPA SAB 

2007). The journal Review of Environmental Economics and Policy published an 

issue containing a series of articles on mortality risk and valuation (Review of 

Environmental Economics and Policy 2007, Vol. 1[2]). The report of a conference on Critical Considerations in Evaluating Scientific Evidence of Health Effects of Ambient Ozone summarized scientific issues the conference participants 

viewed as central for decisions to be made in setting the ozone NAAQS (Brauer 

et al. 2007). The committee also considered a EPA staff paper that summarized 

staff recommendations on the ozone NAAQS to the EPA administrator (EPA 

2007a) and EPA’s regulatory impact analysis to accompany the agency’s recent 

proposal for revising the NAAQS for ozone (EPA 2007b). 

Figure 1-1 presents a sequence of analytic methods used by EPA to assess 

mortality risk reduction and associated health benefits expected to result from 

setting and implementing ozone NAAQS (see Chapter 2). Estimation of the potential health effects of actions taken to improve air quality, and the economic 

value of those effects, requires estimation of the likely changes in emissions, 

ambient ozone concentrations, population exposures, and health risk and then 

the economic valuation of the change in risk. Figure 1-1 shows which components of the committee’s Statement of Task correspond to specific steps in the 
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22 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

sequence of analytic methods. It also indicates which chapters of this report 

cover specific topics. Chapter 6 integrates the committee’s overall conclusions 

and recommendations concerning ozone exposure, mortality risk, and benefit assessment. 

FIGURE 1-1 Methods used by EPA to assess the effects of NAAQS and control strategies developed to implement the standards. The left portion of the figure indicates the 

chapters of this report that deal with each method. Numbers in brackets correspond to 

relevant portions of the committee’s statement of task, shown in Box 1-1. NOTE: The 

committee was not asked to and did not consider the cost aspects of benefit-cost analysis 

and cost-effectiveness analysis. Abbreviations: ∆ = change; NAAQS = National Ambient 

Air Quality Standard. 
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23

2 

Overview of Ambient-Ozone Standards 

Development and Benefits Assessment 

INTRODUCTION 

Ozone has been the subject of extensive research, standard-setting, and 

air-pollution control activities for over 3 decades in the United States and in 

other countries. This chapter provides background on the committee’s consideration of the implications of recent findings of associations of ambient ozone 

concentrations with mortality, including the setting of national ambient air quality standards, the process of implementing the standards, the scientific basis of 

standard-setting, the use of health studies to quantify expected health effects of 

changes in air quality, the concepts underlying economic valuation of such 

health effects, and experience in the United States and elsewhere in applying 

these concepts to estimate benefits of ozone reduction. 

SETTING NATIONAL AMBIENT AIR QUALITY 

STANDARDS FOR OZONE

Beginning in 1970, the U.S. Clean Air Act (CAA) directed the 

Environmental Protection Agency (EPA) to consider the best available science 

bearing on exposure to and effects of several ambient air pollutants that are 

emitted by a wide array of sources and to set National Ambient Air Quality 

Standards (NAAQS) for pollutants to which the public was widely exposed. 

Under the CAA, NAAQS are to be set and reconsidered every 5 y, and the 

administrator of EPA is to consider setting primary NAAQS to protect the 

public health and secondary NAAQS to protect the public welfare (for example, 

buildings, materials, and ecosystems). In setting the primary NAAQS, the 

administrator is to consider all available science, historically compiled in a so-
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24 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

called criteria document1

 prepared by EPA scientists and consultants, and to set 

standards at levels that are “requisite to protect the public health with an 

adequate margin of safety.” The act does not include costs of implementation in 

the criteria for setting the NAAQS, and EPA—with consistent support from the 

courts—has interpreted that to mean that it may not consider costs in NAAQS 

decisions (American Trucking Associations, Inc. v. U.S. EPA, D.C. Cir 97-1440 

and 97-144). 

In essence, that has meant that each time a NAAQS is reviewed, the administrator must weigh the most recent evidence and continuing uncertainties 

and make a “public-health policy judgment” about whether the newest evidence 

provides enough certainty about the likelihood and public-health significance of 

effects above, at, and below the current standard to warrant a determination that 

the current standard is adequate to protect the public health with an adequate 

margin of safety or should be lowered or raised. 

Once that determination is made for a particular pollutant or class of pollutants, EPA is expected to make decisions about four aspects of the standards: 

• The indicator (the pollutant to be monitored and assessed for attainment). 

• The level of the standard. 

• The averaging time (for example, 1 h, 8 h, 1 d, or 1 y). 

• The statistical form of the standard (for example, whether the standard 

will not be met if it is exceeded more than 1% of the time, on the third-highest 

day each year, or other similar measure). 

Since the inception of NAAQS, EPA has determined that photochemicaloxidant air pollution, formed when specific chemicals in the air react with light 

and heat, is of sufficient public-health concern to merit establishment of a 

primary NAAQS. In implementing that determination, EPA has since 1979 

identified ozone, a prominent member of the class of photochemical oxidants 

(such as nitrogen dioxide), as an indicator for setting the NAAQS and tracking 

whether areas of the country are in attainment of the standards. Over the last 38 

y, as scientific understanding of ozone health effects has evolved, EPA has 

reviewed and updated, as needed, the primary NAAQS for ozone and other 

photochemical oxidants in 1971, 1979, 1993, and 1997 (see Table 2-1). As 

illustrated in Figure 2-1, under the 1997 NAAQS, ozone nonattainment has 

occurred largely in heavily populated areas east of the Mississippi River, 

 1

In December 2006, EPA indicated that after the current ozone NAAQS review process, it would no longer use the historical terminology of criteria document to summarize 

the science and staff paper to summarize staff risk assessment and recommendations to 

the administrator. The criteria document would be replaced by an integrated science assessment and the staff paper would be replaced by an advanced notice of proposed rulemaking (EPA 2007c). 
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TABLE 2-1 History of Primary NAAQS for Ozone and Other Photochemical OxidantsaYear Indicator Level Averaging Time Form Scientific Rationale 1971 Total photochemical 

oxidants 

0.08 ppm 1 h Not to be exceeded 

more than 1 h/y 

Principal study cited for final found increased asthma-attack frequency when hourly average reached 125μg/m3 (0.10 ppm); 

final standard included margin of safety below most likely threshold suggested by this study (Bachmann 2007) 

1979 Ozone 0.12 ppm 1 h More than 1 d/y with 

maximal hourly average above 0.12 ppm 

Move to ozone-specific effects; three clinical studies found reduction in pulmonary function or symptoms as having lowest effect level in humans at 0.15-0.3 ppm with evidence of lower effect levels in animals (Bachmann 2007) 

1993 Ozone Determination that no change was necessary 1997 Ozone 0.08 ppm 8 h Annual 4th-highest 

daily maximal 8-h average concentration, averaged over 3 y 

Many new studies over a decade found effects at concentrations below 1979 standard with increased importance of 6-8-h exposures; key studies found lung-function decrements, respiratory symptoms, increased sensitivity to irritants, indicators of pulmonary inflammation increasing 

across range of 0.08, 0.1, and 0.12 pm for 6- to 8-h exposures with subjects engaged in intermittent exercise; numerous epidemiologic studies found increased hospital admissions and emergency-room visits for respiratory causes attributed primarily to ozone; proposal highlighted risk assessment for children (nine-city) and for New York City hospital admissions. (Bachmann 2007) 

2008 Ozone 0.075 ppm 8 h Annual 4th-highest 

daily maximal 8-h average concentration, averaged over 3 y 

Strengthened clinical database showing effects at 0.080 ppm; 

limited data on potential effects on some subgroups at 0.060 ppm (6- to 8-h exposure) (Adams 2002, 2003, 2006); substantially increased epidemiologic evidence on morbidity effects (EPA 2008a). Also see Box 2-1. 

aThis table focuses on the primary rather than secondary NAAQS. 

25
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FIGURE 2-1 Counties violating 1997 primary 8-h NAAQS for ozone and other photochemical oxidants. Source: EPA 2007d. 

26 
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Ambient-Ozone Standards Development and Benefits Assessment 27 

BOX 2-1 The Estimation of the “Policy Relevant Background” 

One step in the process of setting the NAAQS which was not a focus 

of this report is to assess the amount of risk reduction expected to result 

from its implementation, an involved and often ambiguous process. It is 

unlikely that lowering a standard will lead to no ozone concentrations occurring that are greater than the set level without ozone concentrations 

below the level of the standard also being affected. Likewise, raising the 

level of the standard would not lead quickly to ozone concentrations increasing up to the standard at all locations. In order to conduct its risk assessment, EPA assesses how ozone at all concentrations will respond to 

the change in the standard. However, during the NAAQS process the specific rules and controls that will be implemented in response to a change 

are not known, so neither is it known how a change in the standard will 

impact air quality. There are a large number of possible paths towards 

cleaner air and attaining a standard, and as discussed later, their impacts 

on ozone concentrations at different times of the day and different periods 

of the year can differ substantially, even if all of the paths suggest that they 

will lead to attainment. The question is how can EPA assess the health and 

welfare implications of a revised NAAQS without better knowing the likely 

air quality response. 

EPA deals with this ambiguity by prescribing a “Policy Relevant 

Background” (PRB), and then rolls back current levels towards this background level in such a way that the standard would now be met. In so doing, all levels above the PRB are reduced (see EPA [2006a, 2007a] for a 

more complete description of the definition, calculation and use of PRB). 

EPA further goes on to define the PRB as the level that the pollutant concentration would be in the absence of anthropogenic emissions from the 

US, Mexico and Canada. In the 2006 Ozone Criteria Document, a global 

chemical model was used to calculate spatially and temporally varying 

PRBs (EPA 2006a). Removing emissions from Canada and Mexico has 

been criticized for, among other reasons, providing an unrealistically low 

estimate for PRB (Brauer et al. 2007). 

Defining a PRB is unnecessary for establishing a level above which 

ozone is harmful to human health or for estimating changes due to a specific regulatory action, nor is it needed for quantifying human health responses to short-term ozone levels or monetizing risk changes in response 

to ozone changes, which are the primary foci of this study. Thus, this 

Committee did not explore this issue in detail, though the report discusses 

aspects of PRB in Chapter 3. 

throughout California, and in major cities in Texas, Arizona, and Colorado. 

Figure 2-2 shows counties with monitor readings that would violate alternate 8-h 

ozone standards of 0.070 and 0.075 ppm proposed by EPA in June 2007. 
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FIGURE 2-2 Counties with monitors readings that would violate alternate 8-h ozone standards of 0.070 and 0.075 ppm proposed by EPA in 

June 2007 (on basis of 2003-2005 monitoring data). Source: EPA 2007e.

28 
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Ambient-Ozone Standards Development and Benefits Assessment 29 

On March 12, 2008, EPA issued revisions to the ozone primary and secondary NAAQS (EPA 2008a). The level of the primary 8-h standard was lowered to 0.075 ppm and the secondary standard was set to be the same as the revised primary standard. 

IMPLEMENTING THE NAAQS 

Once a NAAQS is set, EPA and the states and tribes pursue three basic 

paths to ensure that the standards are met throughout the country: 

• First, EPA establishes reference methods for measuring the indicator 

pollutant, and states and tribes implement monitoring programs to determine 

whether areas in their jurisdictions are in or out of attainment of the NAAQS. 

Under the 1997 ozone NAAQS, about 391 counties or parts of counties with a 

total population of over 36 million are in nonattainment of the standards (Figure 

2-1). 

• Second, once EPA determines that any area is not in attainment of the 

NAAQS, the state that contains the area must develop a state implementation 

plan (SIP) that includes the actions it will take to reduce emissions and bring the 

area into attainment. States that are in attainment must consider actions that will 

ensure that they maintain that status. If a state fails in those efforts, EPA has the 

authority to implement its own plan; this has rarely occurred.

• Third, to the extent that Congress has authorized EPA to take national 

or regional action to address emissions that lead to nonattainment, EPA proposes 

and implements regulations to do so (for example, national motor-vehicle and 

fuel standards).

Beyond those regulatory actions, EPA works with states, tribes, and local 

authorities to implement an air-quality index system, which assesses the likelihood that air quality in a given area on a given day will be near or above the 

standard. The likelihood of poor air quality in turn sets off broad-based publicinformation efforts to alert residents, especially such sensitive populations as the 

elderly or asthmatic, to restrict activity that might increase exposure. 

In the case of ozone, regulatory actions at state and federal levels have 

taken many forms and have resulted in controls on emissions of volatile organic 

compounds and nitrogen oxides—the two primary precursors of ozone and other 

photochemical oxidants—from fuels, on-road and nonroad engines, electricpower facilities, manufacturing facilities, consumer products (such as paints), 

and many other sources. A National Research Council analysis of those efforts 

in 2004 found that although many actions have been taken at federal, regional, 

and state levels, the vast majority of reductions have come through national and 

regional multistate actions, rather than individual state actions. An exception is 

California, which has had the most aggressive air-quality programs in the nation 

(NRC 2004a). 
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30 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

THE SCIENTIFIC BASIS OF PRIMARY NAAQS FOR OZONE

For over 50 y, detailed scientific investigations have examined nearly 

every aspect of ozone and other photochemical oxidants, and this robust body of 

research has served as the basis of each succeeding NAAQS determination by 

EPA. The research has taken several forms: 

• Atmospheric chemistry to understand the sources of ozone precursors 

and the formation of ozone and other photochemical oxidants. 

• Exposure research to characterize pollutant concentrations and human 

activity patterns that lead to contact with the pollutants over specific periods. 

Toxicologic research in vitro test systems (such as various human cells and 

other biologic media) and in vivo experiments (involving a wide array of animal 

species and animal models of human disease). 

• Epidemiologic research, including panel, cohort, and broader population studies of the acute or chronic effects of ozone exposure on morbidity and 

mortality in children and adults. 

• Controlled human exposure (or “clinical”) studies of varied healthy 

and compromised adult volunteers exposed to ozone or ozone combined with 

other gases. 

Research findings have contributed to the understanding necessary to establish a NAAQS. In particular, the human studies—epidemiologic and clinical 

studies—have contributed several key pieces of standard-setting information, 

including information on the effects of real-world exposure of human beings to 

contaminants, the smallest exposure that can be demonstrated to have effects in 

humans, and the degree to which effects are found in sensitive populations. 

Recent Scientific Conclusions About Risks Posed by Ozone Exposure 

Overall, extensive toxicologic, epidemiologic, and clinical research on the 

effects of exposure to ozone has yielded strong evidence of effects on respiratory end points at or near current regulatory levels, and in a variety of populations. However, clinical studies have shown substantial variability in individual 

responses; even sensitive populations, such as asthmatics, exhibit a range of 

responses and nonresponse (EPA 2006a). Although an extensive literature—in 

toxicology, epidemiology, and controlled human exposure studies—has reported 

consistent evidence of such effects, there are still uncertainties in our understanding, for example: 

• Uncertainty about the relationship between outdoor ozone concentrations and personal exposure, especially of persons who spend most of their time 

indoors or use air conditioning during periods of peak ozone concentrations. 
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Ambient-Ozone Standards Development and Benefits Assessment 31 

• Uncertainty about the degree to which epidemiologic studies can identify the effects of individual pollutants, such as ozone, that are present in mixtures of pollutants in the ambient air. 

• Uncertainty about the degree to which current study designs and datasets enable understanding of risks resulting from exposures at very low pollutant 

concentrations and whether there is any threshold for effects. 

• Uncertainty, despite high-quality studies of long-term effects on lung 

growth in children (CalEPA 2006), about long-term exposure to ozone as a risk 

factor for chronic illness and premature death. 

On the basis of the available evidence, EPA in its most recent criteria 

document (EPA 2006a, p. 8-77) concluded that “the overall evidence supports a 

causal relationship between acute ambient ozone exposures and increased respiratory morbidity outcomes resulting in increased ED (emergency-department) 

visits and respiratory hospitalizations during the warm season.” EPA’s most 

recent staff paper (EPA 2007a, pp. 5-92 and 5-93), summarizing staff recommendations on the NAAQS for the administrator) further concludes that there is 

clear and convincing evidence of causality for lung function decrements in 

healthy children under moderate exertion for 8-hr average ozone exposures. We 

also judge that there is strong evidence for a causal relationship between respiratory symptoms in asthmatic children and ozone exposures and between hospital 

admissions for respiratory causes and ambient ozone exposures. There is greater 

uncertainty and somewhat less confidence about the relationship between ozone 

and non-accidental and cardiorespiratory mortality, although the Criteria Document’s overall evaluation is that it is highly suggestive that this relationship exists. The strengths and weaknesses of the recent literature on mortality and 

ozone are explored in greater detail in Chapter 4. 

Recent reviews of the evidence by the World Health Organization in its 

establishment of world air-quality guidelines (WHO 2006) and by the California 

Air Resources Board in its establishment of state air-quality standards (CalEPA 

2007) have reached similar conclusions although the latter reviews have given 

somewhat greater causal weight to the associations with premature mortality. 

Evolution of the Science of the Health Effects of Ozone 

and Particulate Matter 

A broad and deep literature on the health effects of exposure to ozone has 

developed over the last 35 y and has resulted in a series of actions to set and 

revise the NAAQS and to reduce emissions of precursors. Similarly, over the 

last 15 y, much scientific and regulatory activity has been generated by intense 

interest in the effects of exposure to particulate matter (PM), especially PM with 

a diameter equal to or less than 2.5 μm (PM2.5) (EPA 2007f). There are useful 

parallels and differences between the literature on ozone and that on PM2.5, and 
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32 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

they have to some extent resulted in different approaches to the estimation of 

benefits of reducing exposure and in differences in actions taken. 

In general terms, the ozone literature developed first out of observations of 

populations exposed outdoors (for example, panel studies of summer campers) 

and then from what has become a large set of controlled human exposure (clinical) studies. More recently, and to some extent in parallel with the PM literature, 

ozone research has moved into the realm of broader population epidemiology 

with a growing number of hospitalization studies and other time-series studies 

starting in the 1990s. Cohort studies have not been designed to look specifically 

at ozone and premature mortality, and testing for the statistical significance of 

ozone-mortality relationships was not feasible due to insufficient variation in 

estimated long-term exposure to ozone (see Chapter 4). However several studies, 

especially the Southern California Children’s study, have examined longer-term 

morbidity effects (Tager et al. 2005; CalEPA 2006). Most cohort studies of PM 

have examined potential effects of ozone both as a confounder and for its independent effects, although few have found statistically significant evidence of 

such effects (see Chapter 4 for a review of the studies). One regulatory result of 

the relative absence of data on longer-term effects has been a focus on setting 

only a short-term NAAQS for ozone: a 1-h standard, which after nearly 30 y 

was replaced by an 8-h standard in 1997. 

The PM2.5 literature expanded rapidly after findings in the early 1990s of 

the associations of PM with morbidity and mortality in single-city time-series 

studies followed by the publication of results of two major cohort studies—the 

Harvard Six Cities Study (Dockery et al. 1993) and an American Cancer Society 

(ACS) study (Pope et al. 1995)—that showed much larger associations with 

longer-term residence in areas with high concentrations of PM2.5. Those results 

motivated the first major revision of the PM NAAQS in a decade in 1997 with 

the development of both shorter-term (24-h) and longer-term (annual) standards 

and a host of aggressive new regulatory actions for vehicles, power plants, and 

other sources. The controversy over those standards resulted in the launching of 

a major multidisciplinary research program (over $50 million/y for nearly a decade), which has provided substantial additional information on exposure, toxicology, and epidemiology and involved the first use of clinical studies in this 

context (NRC 2004b). In turn, the new information led to many specific control 

actions related to such sources as diesel engines (EPA 2007g) and electricpower plants (EPA 2007h) and, in September 2006, an EPA decision to tighten 

the daily PM standard (but not the annual standard). Those actions were justified 

largely by cost-benefit analyses based on the substantial potential mortality 

benefits estimated from the ACS study and later reanalyses and extended analyses (Krewski et al. 2000; Pope et al. 2002, 2004). 

The focus on PM science and regulation over the last decade has had several ramifications for ozone. The understandably enhanced policy attention to 

PM resulted in substantially increased funding for and scientific attention to PM 

research, to some extent at the expense of research on ozone and other pollutants 

(except as they might be confounders of PM effects). The substantial estimated 
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Ambient-Ozone Standards Development and Benefits Assessment 33 

mortality benefits of reducing PM have resulted in estimates of health benefits 

of reducing PM that are much larger than those estimated for reducing ozone 

and other pollutants; one consequence has been in substantial political support 

for revisions in regulations that address PM. In the last several years, partly because of the increased attention to mortality, there have been increased efforts 

on the part of regulators and scientists to understand better whether mortality 

effects may be attributed to exposure to ozone and, if so, to incorporate them 

into future standard-setting and benefits assessment. Those considerations 

caused EPA to fund of studies of the short-term mortality effects of ozone that 

are a primary focus of the present committee’s review. 

REGULATORY BENEFITS ASSESSMENT FOR SETTING AND 

IMPLEMENTING NATIONAL AMBIENT AIR QUALITY STANDARDS 

Quantitative assessment of the potential health benefits of actions planned 

to improve air quality has become a central component of regulatory impact 

analysis in the United States and other countries. As described in Figure 1-1 (see 

Chapter 1), the process involves estimation of the likely changes in population 

exposure to pollutants and the resulting changes in health risk as well as the 

economic valuation of the changes in health risk. 

Use of Health Studies for Regulatory Benefits Assessments 

There is a fundamental difference between information needed for regulatory benefits assessment and information needed to set a protective health standard. Selection of a primary (health-based) standard focuses on the lowest ambient concentration that poses a risk of adverse health effects in the most sensitive 

population. Assessing benefits requires information for estimating all the reductions in health risks in the entire population that is expected to experience a reduction in ambient concentrations. 

The information needs for a comprehensive benefits assessment have led 

EPA to rely almost entirely on epidemiologic studies to support quantification of 

health effects of PM and ozone, whereas clinical and toxicologic studies are 

often important for standard-setting. Epidemiologic studies link health outcomes 

measured in the general population or in specific cohorts to differences in ambient pollution concentrations at different times or in different locations. Widespread monitoring has made large-scale epidemiologic studies of the criteria 

pollutants feasible in the United States and many other countries. The real world 

thus becomes the laboratory, and subjects are studied in their normal environments. That has three important advantages for benefits assessment: 

• Estimates of changes in rates of health outcomes in the population as a 

result of changes in ambient pollutant concentrations can be directly estimated 
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34 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

without the extrapolations required when clinical or toxicologic study results are 

used for such purposes. 

• Epidemiologic studies generally include serious health effects, such as 

death, chronic disease, and hospitalization that cannot be tested in clinical studies. 

• Epidemiologic studies can be designed to measure the effects of longterm exposures to air pollutants, which are difficult to assess in clinical studies. 

• At the same time, important limitations of epidemiology studies also exist, and these contribute to some of the key uncertainties in the benefits assessments for PM and ozone that EPA conducts for NAAQS and other rulemakings. 

• Epidemiologic studies can demonstrate statistical associations, but 

alone they cannot prove causation. A number of factors make such casual determinations difficult, including potential confounding factors such as weather, 

other pollutants, and socioeconomic status; and uncertainties in assessing actual 

personal exposure. These factors can and have been included in analyses, but 

there is always a chance that their effects have not been adequately defined and 

removed. 

• It is difficult to isolate the independent health effects of individual pollutants that occur in mixtures in ambient air. That is a concern for ozone and 

PM2.5, especially in the warm-weather months in the eastern United States. 

Those strengths and weaknesses of the epidemiologic literature, especially 

in the case of the ozone-mortality studies that are the subject of this report, are 

described in further detail in Chapter 4. 

Concepts of Economic Valuation of Mortality Risk Reduction 

for Regulatory Benefits Assessment 

A charge to the present committee is to address the quantification and 

economic valuation of mortality-risk reductions in the context of cost-benefit 

analysis. Cost-benefit analysis is the comparison of a monetary measure of the 

welfare gain for those who benefit from a policy or program with a monetary 

measure of the welfare loss for those who are harmed (that is, who incur costs) 

by the policy or program. Those who benefit and those who are harmed may be 

the same or different members of the population. For example, if a regulation 

causes higher electricity prices by reducing power-plant emissions, many of the 

people who pay higher prices will also experience a reduction in health risks 

because air quality is improved. However, the additional costs and the value of 

the health-risk reduction will not necessarily be the same for everyone affected. 

In general, cost-benefit analysis focuses on aggregate costs and benefits, and a 

program is considered to have a net benefit to society if total benefits exceed 

total costs. If an assessment of how costs and benefits are distributed is done, it 

is a separate assessment. 
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As noted above, cost-benefit analysis is intended to measure how those affected by a policy value the costs that they incur or the benefits that they receive. 

The appropriate monetary measure of a benefit is the maximal expenditure (or 

income reduction) that one would be willing to make to obtain the benefit if 

such a transaction were feasible. That is called the willingness to pay (WTP) for 

the benefit. The WTP in this context is a metric for the opportunity-cost value of 

the benefit because it is a measure of the alternative consumption opportunities 

that a person is willing to forgo to obtain the benefit. 

WTP measures are based on studies of people’s own preferences, including their preferences regarding tradeoffs between reducing risks to their own 

lives and other uses of their available resources. WTP values are not independent of the valuation context or of a person’s circumstances, so a WTP value for a 

given benefit may vary among contexts and among people. For example, a WTP 

value is a function of a person’s available income and wealth. That is inherent in 

the measure: it is a measure of the resources that a person is willing to exchange 

for a given benefit, and it will therefore be a function of the total resources 

available to that person. What that means for policy analysis is that WTP estimates should be drawn from studies of populations that have relevant characteristics similar to those of the population affected by the policy. 

The cost-benefit analysis of a program that provides reductions in mortality risks typically focuses on the values of a risk reduction to all the affected 

persons summed to obtain the total benefit of the risk reduction. Questions are 

sometimes raised about whether values that people hold for others’ risk reductions should be added to obtain the total value of a program to society. JonesLee (1991) presented a theoretical analysis that clarified that issue and illustrated the importance of unambiguously defining whose risk is being reduced in 

an empirical WTP estimation study. His analysis demonstrated under what conditions WTP for other people’s mortality-risk changes should be added to the 

value of one’s own risk reduction to obtain an optimal allocation of resources to 

health and safety efforts. His analysis showed that if people’s altruism toward 

others is general regarding the others’ enjoyment and satisfaction, there is no 

need to add WTP values for others’ mortality risk reductions to WTP for people’s own mortality risk reduction in a cost-benefit analysis. It is only in the case 

of what Jones-Lee calls “paternalistic altruism” that an argument could be made 

for adding WTP values that a person has for another’s mortality risk reduction in 

a cost-benefit analysis. What he means by paternalistic altruism is when a person values the other person’s consumption or behavior for its own sake regardless of the other person’s enjoyment, such as when a parent is happy that the 

child eats the spinach even if the child is miserable doing it.

Estimates of the value of a statistical life (VSL) are often used in costbenefit analyses of programs that are expected to reduce mortality risk in a 

population. VSL estimates are derived from estimates of a person’s WTP for 

changing his or her mortality risk in a given period by a small amount (see Box 

2-2). Although the VSL estimate is applied in an assessment by estimating the 
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36 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

BOX 2-2 Definition of Value of a Statistical Life in Relation to Willingness 

to Pay, and a Numerical Example 

The value of a statistical life (VSL) is an artificial construct that gives 

a defined group of identical people’s aggregate willingness to pay for a 

reduction in the risk of death that would result on the average in one less 

death for the group. 

Numerical example of VSL: Assume that each person in a group of 

100,000 is willing to pay $50 in higher annual energy costs to reduce his or 

her own annual risk of dying from 5 per 100,000 to 4 per 100,000. There 

will be one less death in this group if the policy is undertaken. But we cannot know which of the 99,996 survivors would have died without the policy. 

The group has an aggregate annual willingness to pay of $5 million ($50 x 

100,000) and one death was avoided. Thus, the value of this statistical life 

is $5 million. 

number of lives saved and multiplying by the VSL, it is numerically equal to the 

sum of the estimates of WTP values for small changes in risk to each exposed 

person. In the example in Box 2-2, the WTP value is not correctly interpreted as 

a $5 million value for the single life saved (which is not identified) but rather a 

$50 value to each of the 100,000 people who experience a reduction of 1 in 

100,000 in mortality risk. It is not known whose premature death is avoided, so 

the concept of VSL is inherently ex ante in that it is based on values of changes 

in risk rather than values of identified lives. 

The VSL is a computational tool to assist in scaling WTP estimates for 

valuing different magnitudes of risk change. Its use in this way is based on an 

implicit assumption that WTP to reduce risk is the same per unit of change in 

risk regardless of the cause or context of the risk. 

There are many unanswered questions about how the VSL might vary in 

different contexts and in populations with different characteristics. One important and controversial question is whether WTP for mortality-risk reduction is 

expected to be proportional to remaining life expectancy. If it is, it may be more 

appropriate to use a monetary value of a statistical life year (VSLY) (see Box 2-

3) or to adjust the VSL to reflect preferences of people at different ages rather 

than use the same VSL in all cost-benefit analyses. Evidence regarding that 

question and other factors concerning the estimation of the VSL are discussed in 

Chapter 5. 

The choice between using a VSL or a VSLY to calculate mortality-risk reduction benefits is also related to whether mortality-risk reductions are expressed as reductions in lives saved or as reductions in life years saved. A calculation of lives saved is a measure of the number of people in a population who 

would have died in a given period but whose deaths are postponed because of 
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BOX 2-3 Definition of Value of a Statistical Life Year in Relation to Value of 

a Statistical Life, and Numerical Examples 

The value of a statistical life year (VSLY) is another artificial construct, which gives a group of identical people’s aggregate willingness to 

pay to extend the life of one person in the group by 1 y. In theory, the 

VSLY could be estimated directly; in practice, it is usually derived from an 

estimate of the value of a statistical life (VSL). 

Numerical examples of VSLY: In the simplest case of a zero discount rate and a constant VSLY, the VSLY is the VSL divided by the number of life years saved by the reduction in risk (calculated from the remaining life expectancy of the people at risk). Thus, using the numerical 

example for the VSL from Box 2-2, if the average remaining life expectancy 

for the group with the VSL of $5,000,000 is 40 y, the VSLY equals 

$125,000 ($5,000,000 divided by 40). In practice, the values for future 

years are presumed to be discounted at some rate of time preference such 

that years further in the future are given less weight in current decisionmaking than years close to the present. For a discount rate of 5%, for example, a VSL of $5,000,000 implies a larger VSLY of about $291,000 if the 

VSLY is assumed to be the same for every remaining year. In this example, the VSL is interpreted as a present value of a stream of equal annual 

values over a 40-y period discounted at an annual rate of 5%. It is not required that the VSLY be a constant value for every year, although it is often 

assumed when a VSLY is calculated from a VSL. 

the reduction in pollution exposure. A calculation of life years saved takes into 

account the remaining life expectancy of those whose deaths were prevented in a 

given period. For example, if the reduction in pollution exposure is such that 10 

70-y-old people who would otherwise have died next year do not die then and if 

their average remaining life expectancy is 15 y, 10 lives and a total of 150 lifeyears are saved. Of course, the specific people whose deaths are prevented cannot be identified, and remaining life expectancy of any specific person is not 

known, but estimates can be made by using pollution-related risk estimates for 

age groups and using life tables that give average remaining life expectancies of 

people of different ages. This is discussed further in Chapter 4. 

Proponents of using life years saved, rather than lives saved, as the unit of 

measure for mortality-risk reduction in cost-benefit analyses of environmental 

regulations have several arguments, including these: 

• A measure of life years is intuitively appealing because lives are never 

“saved,” rather, survival curves are shifted (that is, life expectancy is increased). 

• Life years saved are commonly used in medical-care decision-making 

and health-care policy analysis. 
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38 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

• An intervention or program that provides a person a larger life expectancy increase is intuitively preferable to one that provides a smaller life expectancy increase. 

The relative merits of the alternative methods for measuring and valuing 

mortality-risk changes are discussed in more detail in Chapters 4 and 5. 

Role of Cost-Benefit Analysis2

As noted above, the use of economic analysis—of the costs and monetary 

benefits of an action—is not allowed in the setting of the NAAQS, but such 

analysis is conducted in three important arenas. The first is a set of retrospective 

and prospective analyses of the costs and benefits of the CAA; these analyses 

are required by Section 812 of the 1990 amendments to the act. Two have been 

conducted: the first looked backward for the period 1970-1990, and the second 

looked forward for the period 1990-2010 (EPA 1997b, 1999a, 2003a). 

The other two uses of economic analysis are in response to a series of 

presidential directives, begun in the Ford administration and most recently codified in Executive Order 12866 during the Clinton era (with later interpretation 

by the George W, Bush administration’s Office of Management and Budget, for 

example, in the recent Executive Order 13422). Executive Order 12866 mandates a regulatory-impact analysis (RIA) of the costs and benefits of any federal 

agency action expected to have a “significant economic impact” (that is, an economic impact expected to exceed $100 million). For the air-quality management 

process, that has two facets: 

• First, an RIA is prepared for both a proposed and a final setting of each 

NAAQS. Although the law and recent court decisions (American Trucking Associations, Inc. v. U.S. EPA, D.C. Cir 97-1440 and 97-144) do not allow the 

results of this analysis to be used in setting the NAAQS, the RIA does provide 

public information about quantifiable costs and benefits of the proposal and inform public debate. 

• Second, and perhaps more important, an RIA is prepared for every major EPA rule designed to reduce emissions of NAAQS pollutants or their precursors from mobile, stationary, and other sources. Although the RIA does not have 

a statutory role in EPA’s setting of the standard, the CAA provisions that authorize actions to meet a standard normally do include cost among the criteria to be 

considered, so the cost and benefit analyses conducted in an RIA often are important in determining which actions to reduce emissions may be most effective 

in improving health at the lowest cost. Furthermore, Sunstein (2002) has argued 

 2

The discussion in this section contains text that is excerpted or summarized from a 

document by L. Robinson (2007). The discussion is also informed by another document 

by L. Robinson (2004). 
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Ambient-Ozone Standards Development and Benefits Assessment 39 

that a series of judicial decisions has created a default requirement that, “Unless 

Congress has clearly said otherwise, agencies will be permitted to take costs into 

account...and expected to balance costs against benefits in issuing regulations.” 

(Sunstein 2002, p. 31) 

The U.S. Office of Management and Budget (OMB) gives guidance for 

conducting RIAs—most recently in 2003 (OMB 2003). EPA has guidance for 

conducting the analyses that is more specific to the issues related to environmental regulation (EPA 2000a). OMB notes (OMB 2003, p. 2) that the motivation for the analyses is “to (1) learn if the benefits of an action are likely to justify the costs or (2) discover which of various possible alternatives would be 

most cost-effective.” 

OMB’s guidance acknowledges that there are instances when important 

beneficial effects or costs of a regulation cannot be quantified or monetized. In 

such instances, OMB recommends a “threshold” or “break-even” analysis to 

evaluate the significance of nonquantified beneficial effects or costs. For instance, such an analysis would examine what the value of the nonquantified 

beneficial effects would have to be for the net benefits to be positive. For example, assume that a pollution-reduction program costs $10 million and has two 

benefits: benefits to the commercial forest industry that can be quantified and 

benefits to forest ecosystems that cannot be quantified. If the benefit to the 

commercial forest industry is estimated at $7 million, the benefit to forest ecosystems would have to be worth more than $3 million for the total benefits to 

exceed the costs. 

EPA’s guidance (EPA 2000a) provides more detail on what is to be included in quantified costs and benefits, how these are defined for cost-benefit 

analysis, and specific approaches that are used in the literature to quantify the 

types of costs and benefits that are typically affected by environmental regulations. 

Both guidance documents include the following general recommendations: 

• Conduct a comprehensive cost-benefit analysis for each regulatory alternative being assessed. This includes quantification and monetization of all 

costs and benefits, including those that might be considered ancillary (i.e., supplementary). When important costs or benefits cannot be quantified, a qualitative description of these costs or benefits should be included, as well as an assessment based on professional judgment of how important such costs and 

benefits might be. 

• The methods used and assumptions made should be presented in a 

transparent way to the reader, so that the policy maker can understand the process by which the results were obtained. 

• Uncertainty in the results should be communicated in a quantitative way, 

if possible, using techniques such as probability distributions, confidence intervals, or high, low bounds. The effects of key assumptions on the results should 
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40 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

also be presented, such as with sensitivity analyses that replace key assumptions 

with other plausible assumptions and demonstrate the effect on the results. 

• In all cases, the cost-benefit analyses are intended to support decision 

making, not determine the decision. In some cases there are other statutory goals 

besides efficiency that are overriding. There are also other considerations such 

as the distribution of costs and benefits to various groups or sectors of society 

that should be taken into account. 

Both of the guidance documents refer readers to standard texts on costbenefit analysis and summarize the standard concepts that underlie this type of 

analysis. They note that the goal is to quantify both costs and benefits in terms 

of “opportunity cost.” For benefits, this means a measure of what those who 

benefit would be willing to forgo to obtain the specified benefit. This is the definition of WTP, which is essentially a monetary measure of how much better off 

the benefiting population perceives themselves to be, assuming they have full 

information about what the benefits are. A fundamental point here is that the 

monetary measure of the value of the benefit is to be based on the value placed 

on the benefit by the group or sector receiving. It is not the value held by the 

policy maker or the experts. This is also why WTP estimates for changes in 

health are preferred to cost of illness estimates that reflect only medical costs 

and productivity losses. 

EPA’s Science Advisory Board, especially the Environmental Economics 

Advisory Committee, provides reviews and recommendations on drafts of 

EPA’s guidance document for conducting RIAs, and provides specific advice on 

cost-benefit analysis. In addition, the Advisory Council on Clean Air Compliance Analysis was established under Section 812 of the 1990 Clean Air Act 

Amendments to provide advice on the cost-benefit analysis of the Clean Air Act 

that was mandated by Section 812. The Council has provided detailed advice on 

cost-benefit analysis for air pollution related assessments, and EPA has considered this advice in its RIAs as well as in the assessment of the costs and benefits 

of the Clean Air Act. 

In Circular A-4, OMB (2003) discusses the quantification and economic 

valuation of mortality risk reductions. OMB does not require the use of any specific measure of effectiveness, such as lives saved or life-years saved, but encourages agencies to report results using multiple metrics that may provide different insights and perspectives. 

The OMB notes that [VSL and VSLY] are subject to continued research 

and debate and indicates that agencies should describe the limitations of 

their chosen approach. The Circular reports that the range of VSL estimates found in the literature is generally between $1 million and $10 million; as a result, regulatory agencies generally use values from within this 

range. 
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In addition, Circular A-4 discusses options for adjusting VSL estimates to 

reflect differences between the scenarios addressed in the research literature and the specific regulatory scenarios being assessed...It includes cautions on the application of age adjustments [for VSLs] and suggests the 

use of larger VSLY estimates for older individuals [if VSLY measures are 

used].... 

In some of its regulatory assessments [in 2003 and earlier], the EPA presented sensitivity analyses [using different VSL estimates for different age 

groups] based on research suggesting that older individuals are willing to 

pay less for life-saving interventions than younger adults (e.g., Jones-Lee 

1989; Jones-Lee et al. 1993). 

In response, the OMB issued a memorandum advising agencies against 

adjusting the VSL for age (Graham 2003). This memorandum suggested 

that more recent research (ultimately published in Alberini et al. 2004a) 

did not fully support the VSL age adjustment found in earlier studies. It 

indicated that, when VSLY estimates are used instead of VSL, the yearly 

values are likely to be higher for senior citizens because “seniors face larger overall health risks from all causes and because they have accumulated 

savings and liquid assets to expend on protection of their health and 

safety” (Graham 2003, p. 2)... 

However, the guidance in this OMB memorandum, which was eventually 

incorporated into Circular A-4, does not necessarily eliminate the use of 

different values for younger versus older individuals. When VSLY estimates are applied, the total value of a risk reduction is equal to the product 

of the VSLY estimate and the discounted number of life-years saved. 

Unless the VSLY estimates for older individuals are large enough to compensate for the smaller number of life-years remaining, the use of VSLY 

estimates will result in lower values for older individuals (Robinson 2007, 

p. 286-287). 

ENVIRONMENTAL PROTECTION AGENCY’S APPROACH TO 

ESTIMATING OZONE MORTALITY IMPACTS AND VALUING 

MORTALITY RISK REDUCTION3

Several examples show how EPA’s benefits assessments include quantified and monetized ozone health benefits. All of these have included several 

morbidity endpoints in the primary estimates. Ozone mortality has been quantified as a sensitivity analysis based on available daily time series estimates of the 

 3 The discussion in this section contains text that is excerpted or summarized from a 

document by L. Robinson (2007). The discussion is also informed by another document 

by L. Robinson (2004). 
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42 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

effect of ozone on mortality risk and using the VSL that has been used by EPA 

for PM mortality. 

These have included the 

• 1997 NAAQS RIA (EPA 1997a) 

• Costs and Benefits of the CAA (EPA 1997b; prospective 1999a) 

• Tier 2 Motor Vehicle Emission Standards RIA (1999b) 

• Clean Air Interstate Rule (CAIR) RIA (EPA 2005a) and 

• Proposed Small Engines Emission Rule (EPA 2007i). 

EPA has prepared a RIA to accompany their proposal for revising the 

NAAQS for ozone (EPA 2007b). In that analysis, EPA has included calculations 

of reductions in mortality associated with reductions in ozone concentrations 

using alternative approaches and has presented all the results side-by-side. One 

calculation was based on the results of a multi-city study by Bell et al. (2004). 

This study provided the basis for the “primary” estimates of mortality reductions 

in EPA’s earlier risk assessment. A second set of calculations was based on the 

three meta-analyses of ozone related mortality studies. These results gave mortality reduction estimates about 4 to 5 times larger than the estimates based on 

Bell et al. (2004), and that were relatively close to one another. The third calculation excluded any mortality associated with ozone and counted only the morbidity health outcomes. In addition to the health benefits of reductions in ozone, 

EPA calculated the health benefits of PM2.5 reductions that would result from 

control strategies expected to be used to meet the ozone standards, which would 

reduce precursors that cause formation of both ozone and PM2.5. 

EPA’s current primary approach for economic valuation of mortality risk 

reductions is a variation on their long-standing approach of using the same VSL 

for all annual mortality reductions. Starting with the RIA for the Clean Air Interstate Rule (EPA, 2005a), EPA has been using a central VSL that is a midpoint 

between results obtained in two meta-analyses of the wage-risk literature (described in Chapter 5). This is a VSL of $5.5 million in 1999 dollars and at 1990 

income levels. When adjusted to expected income levels in 2006, this is about 

$6.3 (still in 1999 dollars). This VSL reflects the Agency’s estimates of the individuals’ willingness to pay (WTP) for small reductions in the risk of premature death for the population at large. EPA’s current selection of VSL from the 

literature is similar to, but somewhat lower than the mean VSL EPA used earlier 

that was based on a review of a number of both revealed preference and stated 

preference studies (EPA 2000a). 

In their primary benefits estimates, EPA applies the VSL to all lives saved 

regardless of the age or health status of the population experiencing the change 

in mortality risk and regardless of the cause of the mortality risk change. Although there is some expectation that willingness to pay for mortality risk reductions may vary with the characteristics of the population affected or with the 

context of the risk change, EPA has concluded that there is insufficient empiri-
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Ambient-Ozone Standards Development and Benefits Assessment 43 

cal information available upon which to base adjustments for these factors at this 

time. EPA’s SAB (2007) has agreed with this conclusion regarding the state of 

the currently available literature. Following advice from the SAB, EPA adjusts 

its base VSL estimates for expected future real income growth and for any expected time lags between change in long-term pollution exposures and mortality 

risk reductions (often referred to as cessation lags). EPA included several different sensitivity analyses of the effects of age adjustments (adjusting VSL and/or 

applying VSLY estimates) in several of its reports prior to the development of 

OMB’s Circular A-4, which cautions against making age adjustments to the 

VSL (Robinson 2007). These sensitivity analyses were included, for example, in 

the retrospective and prospective assessments of the costs and benefits of the 

Clean Air Act (EPA 1997b, 1999a) and in the RIAs for the heavy-duty diesel 

rule (EPA 2000b) and the Clear Skies legislation proposal (EPA 2003b, 2006b). 

“For example, for the heavy-duty diesel rule (EPA 2000c), the EPA used 

VSL age adjustments based on Jones-Lee (1989) and Jones-Lee et al. 

(1993) in sensitivity analysis, which reduced its primary benefits estimate 

by 10 or 40 percent, depending on the adjustment factor applied. In a sensitivity analysis for regulations addressing emissions from large spark ignition engines (EPA 2002), the agency used a more complicated approach 

that reflected initial results from the work of Alberini et al. (2004) as well 

as the adjustment factor from Jones-Lee (1989)” (Robinson 2007, pp. 290-

291). 

In this case, EPA derived different estimates of VSLY for younger and 

older age groups from selected VSL estimates. The result was a higher VSLY 

for the older age group. They applied these VSLY estimates of life-years saved 

for each age group. The net effect was a lower value for risk reduction for the 

older age group because the smaller remaining life expectancy more than offset 

the higher VSLY. 

As part of the process of updating their Guidelines for economic analysis, 

EPA asked SAB to consider again the question of whether monetary values for 

mortality risk reduction in cost-benefit analyses should be adjusted for differences in the life expectancy of those at risk. The SAB (2007) concluded that 

economic theory provides indeterminate results about how remaining life expectancy may affect a person’s WTP for mortality risk reduction and that this question must be addressed empirically. They further concluded that results in the 

empirical literature are also insufficient at this time to provide a basis for making quantitative adjustments to VSL according to the age or remaining life expectancy of the population at risk. In addition, they concluded that the empirical 

literature provides no support for the assumption implicit in the use of a constant 

VSLY that WTP for mortality risk reduction is proportional to remaining life 

expectancy. They recommended continued use of a constant VSL, with encouragement to EPA to fund more research to address the questions of how VSL 

varies with age and other population and risk characteristics. 
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44 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

OVERVIEW OF OTHER APPROACHES 

Other Federal Agencies 

Other federal agencies do not deal with ozone mortality in their regulatory 

analyses, but they often deal with other kinds of mortality risk. 

Other agencies promulgate fewer economically significant rules that require valuing the risk of premature mortality. Between October 2003 and 

September 2005, four agencies (in addition to the EPA) prepared final 

rules with quantified health and safety benefits that were reviewed by the 

OMB (OMB 2005, 2006). These agencies included the Food and Drug 

Administration (FDA) and the Centers for Medicare and Medicaid Services (CMS) in the Department of Health and Human Services (HHS), as 

well as the National Highway Traffic Safety Administration (NHTSA) and 

the Federal Motor Carrier Safety Administration (FMCSA) in the Department of Transportation (DOT). An earlier review, covering the period between January 2000 and June 2004, reported similar patterns in agency 

promulgation of major health and safety rules (Robinson 2004)” (Robinson 2007, p. 293). 

Agencies of the Department of Health and Human Services (Food and Drug 

Administration and Centers for Medicare & Medicaid Services) 

The FDA does not provide formal internal guidance for economic analysis, 

but it applies a similar approach across many of its rules. For premature 

mortality, the agency often uses a VSL estimate of $5million, without 

specifying a dollar year, and occasionally provides alternative estimates 

using higher or lower values [see, for example, 68 Fed. Reg. 41434 [2003], 

69 Fed. Reg. 9120 [2004]; 70 Fed. Reg. 33997 [2005]]. This estimate is 

roughly in the middle of the $1 million to $10 million range cited in Circular A-4 (OMB 2003). The FDA rarely adjusts its VSL estimates for scenario differences, although it has addressed cessation lag (e.g., in its transfat rule, FDA 2003), and added the cost of cancer treatment ($25,000) and 

an adjustment for psychological factors ($5,000) to the VSL for a rule on 

X-rays [(70 Fed. Reg. 33997 [2005]]. Thus, while its base VSL estimates 

are similar to those used by the EPA, the values ultimately applied by the 

FDA may be quite different because of the income growth and other adjustments made by the EPA. A few FDA analyses have presented alternative estimates of the value of mortality risk reductions using VSLY as well 

as VSL estimates [e.g., 68 Fed. Reg. 41434 [2003]] (Robinson 2007, p. 

293). 
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Ambient-Ozone Standards Development and Benefits Assessment 45 

FDA sometimes uses VSLY estimates to quantify monetary values for 

changes in morbidity following the methods developed by Mauskopf and French 

(1991); these estimates are derived from VSL estimates in the literature assuming constant VSLY for remaining (discounted) life expectancy. 

Another HHS agency, CMS, develops few economically significant rules 

with health and safety impacts; most of its programs involve transfers (e.g., 

from taxpayers to Medicare and Medicaid recipients) and hence are not 

subject to the OMB requirements for regulatory analysis. In its immunization rule (70 Fed. Reg. 58835 [2005]), CMS applies the same VSL estimate as FDA ($5 million), noting that it is roughly the mid-point of the 

range of values suggested by OMB (Robinson 2007, p. 294). 

Agencies of Department of Transportation (National Highway Traffic 

Safety Administration and Federal Motor Carrier Safety Administration) 

Both the NHTSA and the FMCSA rely on the DOT guidance for their 

base VSL estimates. In contrast to EPA and the HHS agencies, the DOT agencies primarily address injury-related accidental deaths rather than deaths from 

illness. 

The DOT currently recommends the use of a $3.0 million VSL—noting 

that this value is imprecise and should be used as “a guide for thoughtful 

decision-making” (DOT 2002, p. 1). Its approach is based largely on the 

results of Miller (1990), with adjustments for inflation and newer studies. 

Miller’s 1990 estimates vary from those used by the EPA because he applies different criteria to determine which studies to include, and adjusts 

the results to address certain limitations of the studies. The DOT indicates 

that it continues to review the literature and consider whether changes to 

this value are needed (DOT 2002) (Robinson 2007, p. 294). 

California 

The state of California conducted a benefits assessment during the process 

of making their latest revisions to the state ambient ozone standard in 2004. 

They selected central, low and high estimates of the percentage change in mortality association with daily fluctuations in ambient ozone concentrations, based 

on available daily time-series studies. The entire selected range was above zero, 

implying a 100 percent probability of a nonzero effect of ozone on mortality. 

Their results were not used to help set the standard, but to assess what the health 

benefits to the California public would be if the alternative ambient standards 

were met compared to current concentrations. In a subsequent publication, Ostro 

et al. (2006) included a monetary valuation for the ozone-related mortality cases, 

using EPA’s selected estimate of the VSL. 
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46 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Canada 

The Canadian government has also used benefits assessments to determine 

the quantity and economic valuation of health effects associated with air pollution in Canada and for programs to reduce air pollution. Judek et al. (2005) estimated the effects of all air pollutants on mortality rates in Canada, including 

estimates of the effects of ozone on mortality. The concentration-response function for ozone was drawn from a daily time-series study of 12 Canadian cities 

(Burnett et al. 2004), using a multi-pollutant model the authors estimated for 

Health Canada (not reported in the published paper) (Personal communication 

with D. Stieb, August 8, 2007). The concentration response function for ozone 

mortality used was about 0.084% (standard error of 0.014%) change in mortality 

per ppb change in daily high-hour ozone. For monetary valuation of air pollution 

related mortality, Health Canada has been using a range of VSL estimates based 

on the WTP literature in Canada and the United States. These VSL estimates 

have been adjusted downward somewhat based on results from a relatively early 

stated preference study (Jones-Lee et al. 1985) that showed a lower WTP for 

mortality risk reduction for older subjects. VSL estimates from the working age 

population were thus adjusted downward to reflect the age distribution of nonaccidental causes of mortality that are associated with air pollution. Health Canada is currently planning to update their procedures for selecting values for mortality risk reductions. 

Europe 

There have been several efforts in Europe to estimate both the mortality 

impacts of exposure to ozone, and to value those impacts. These have included 

the ongoing work of the European Union’s ExternE program, as well as the July 

2007 Clean Air Strategy of the United Kingdom (DEFRA 2007). While the general approach for estimating impacts and benefits is very similar to that followed 

in the United States (as described in Figure 1-1 in Chapter 1), there are three 

areas where these efforts have differed from normal EPA practice to date: 

• First, these analyses have fairly unambiguously accepted from the epidemiologic literature that there are robust associations of mortality with ozone 

exposure and thus have used European time-series studies of these effects to 

estimate health impacts of current exposure, and the potential reduction in those 

impacts from regulatory actions. 

• Second, these analyses have generally included an analysis of life-years 

lost, in the case of the UK including estimates of both life years and numbers of 

deaths (DEFRA 2007), while in the case of ExternE, rejecting the estimation of 

numbers of deaths and relying solely on life years lost (Bickel and Friedrich 

2005). 
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• Third, the economic valuation estimates used in this ExternE analysis 

are from recent stated preference studies conducted in France, Italy, and United 

Kingdom (Alberini et al., 2006b). Their selected central estimate of EUR 50,000 

per life year was derived from the median WTP value for the 5 in 1,000 mortality risk change over 10 years (median VSL was about EUR1.1 million). The 

ExternE authors converted this 10-year mortality risk change to its equivalent in 

increased life expectancy for each age/gender cohort and calculated the VSLY 

implicit in the WTP responses. 

THE MAJOR QUESTIONS 

As this overview has suggested, there is a broad and deep literature documenting a range of health effects from exposure to ozone, and this has had an 

important role in the setting and implementation of NAAQS for ozone for over 

35 years. In considering whether and how the recent studies of ozone and mortality should be incorporated in estimating benefits going forward, the Committee focused on two primary areas of questions: 

• The Robustness of the Ozone Mortality Studies. The estimation from 

epidemiologic evidence of health impacts, and the economic value of those impacts, requires confidence, as noted above, that ozone exposures can adequately 

be separated from other exposures in the epidemiology studies and that the epidemiology has adequately controlled for possible confounding factors. Although 

a number of others in Europe and California have made the judgment that these 

studies are adequate, the Committee was charged to make an independent determination on these questions. These questions are addressed in detail by the 

Committee in Chapters 3 and 4.

• The Appropriate Methods for Estimating the Value of Potential Ozone 

Mortality Benefits. If the epidemiology studies provide adequate evidence for 

the estimation of mortality impacts, there are important questions about the appropriate methods for estimating the value of such impacts that are described 

initially above, and are addressed in detail in Chapter 5. 
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48

3 

Ambient Ozone and Related Pollutants

Ozone is a naturally occurring compound that is found in the troposphere 

(the layer of the atmosphere next to Earth’s surface) and, at greater concentrations, in the stratosphere (the layer about 10-50 km above the surface). In the 

stratosphere, ozone absorbs and thus reduces the amount of potentially harmful 

ultraviolet (UV) radiation. Ozone in the troposphere also absorbs UV radiation 

and plays a role in the degradation of toxic compounds. More important, however, tropospheric ozone is responsible for various deleterious effects on humans 

and other organisms that are exacerbated by increased ambient ozone concentrations. Preindustrial tropospheric background ozone concentrations were about 

10 ppb, but they have increased to about 30-40 ppb (e.g., Volz and Kley 1988; 

NRC 1991; Finnlayson-Pitts and Pitts 2000) because of emissions and atmospheric chemistry, as discussed below. In and around urban areas in the United 

States, ambient ozone concentrations rise much further, to about 160 ppb in 

Houston and 180 ppb in Los Angeles. Although such concentrations may seem 

extreme, they are substantially reduced from the concentrations of more than 

400 ppb experienced in the 1970s (e.g., NRC 1991). 

OZONE FORMATION AND TRANSPORT 

We must understand the formation and transport of tropospheric ozone if 

we are to be able to interpret health-benefits assessments of ozone and conduct 

new ones, inasmuch as the interpretation of epidemiologic analyses must consider ozone’s spatial and temporal patterns and their relationships with human 

exposure. Processes that affect ozone dynamics also affect other pollutants, such 

as components of particulate matter, and lead to what can be strong correlations 

between pollutant concentrations. This effect hinders our ability to determine the 

health effects of single pollutants that are present in a mixture. That is critical 

because a study may falsely implicate a pollutant that is not responsible for most 

of the health effects found, and strategies designed to reduce that pollutant may 
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Ambient Ozone and Related Pollutants 49 

be ineffective in reducing the pollutants that are responsible for the health effects. An important question is whether that is the case in the approach to ozone 

and airborne particulate matter (PM), of which the latter seems to have greater 

health effects (see Chapter 2). 

Most ozone in the troposphere is not directly emitted to the atmosphere 

(although there are minor sources of such ozone, including some indoor air 

cleaners) (e.g., NRC 1991). Rather, it is formed from a complex series of photochemical reactions of the primary precursors: nitrogen oxides (NOx where [NOx] 

indicates the sum of [NO] and [NO2]), volatile organic compounds (VOCs), and 

to a smaller extent other pollutants, such as carbon monoxide (CO) (Figure 3-1) 

(e.g., NRC 1991). The specific reactions that form most of the tropospheric 

ozone are the photolysis of NO2 followed by the combination of the released 

oxygen atom with the abundant oxygen molecules (O2): 

NO2 + sunlight Æ NO + O [3-1] 

O + O2 Æ O3 [3-2] 

SO 2 H2SO4

NH 3

OH

O3, H2 2 O , O 2

H2O

Organic 

Compounds

RO 2

Secondary Organic

Particles

OH

O3

Organic Particles

Inorganic

Nitrates

NO3

N2O5

HNO3

3

NO 2

Ozone

hν

OH

O3

O3

NO

h

Volatile 

Compounds

Semivolatile

Compounds

Semivolatile and 

Gaseous

Compounds 

NH 4 NO3

(NH 4)2 SO4

Chemical Deposition

SO 2 H2SO4

NH 3

OH

O3, H2 2 O , O 2

H2O

Organic 

Compounds

RO 2

Secondary Organic

Particles

OH

O3

Organic Particles

Inorganic

Nitrates

NO3

N2O5

HNO3

3

NO 2

Ozone

hν

OH

O3

O3

NO

h

Volatile 

Compounds

Semivolatile

Compounds

Semivolatile and 

Gaseous

Compounds 

NH 4 NO3

(NH 4)2 SO4

Chemical Deposition

FIGURE 3-1 Source and chemical links between ozone and PM formation. Major precursors are shown in boxes with thick sides. Secondary particle components are shown in 

boxes with thin solid sides. Mobile sources (cars, trucks, and off-road vehicles) and 

plants are major sources of VOCs, and mobile sources and electricity-generating units are 

dominant sources of NOx, but myriad smaller sources also contribute. Trace species, such 

as OH, are crucial to the formation of ozone, sulfate, nitrate, and organic-carbon particulate matter. Ozone also leads to the oxidation of SO2 and NO2. Biologic activity and fertilizer use dominate ammonia (NH3) emissions. Source: Modified from NARSTO 2004. 

Reprinted with permission; copyright 2004, Cambridge University Press. 
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50 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

VOCs enter the picture by their reactions with the hydroxyl radical (OH) 

and other oxidants, which lead to the formation of NO2 from NO, shown in a 

highly simplified form as 

VOC + OH Æ RO2 [3-3] 

RO2 + NO Æ NO2 + OPs [3-4] 

In Reactions 3-3 and 3-4, RO2 is an oxygenated radical (there are many such 

species in the atmosphere), and OPs are oxygenated organic products, including 

aldehydes, ketones, acids, and condensable species that lead to secondary organic aerosol (SOA) formation. Although a small fraction of ground-level ozone 

is transported from the stratosphere, the reactions shown above (summarizing 

hundreds of reactions and species) are responsible for most ambient ozone, particularly on high-ozone days in urban areas (Fiore et al. 2003). Thus, ozone airquality management strategies concentrate on reducing emissions of the ozone 

precursors. However, the nonlinearity of the relationship between ozone and its 

precursors (Figure 3-2) complicates decisions about which precursors should be 

controlled and to what degree. 

Because reactions that form ozone are driven by sunlight, ambient ozone 

concentrations exhibit both diurnal variation (they are typically highest during 

the afternoon, as seen in Figure 3-3a) and marked seasonal variation (they are 

highest in summer, as seen in Figure 3-3b). Ambient concentrations are highest 

during hot, sunny summer episodes characterized by low ventilation (a result of 

low winds and low vertical mixing). Diurnal variability is enhanced, particularly 

in urban areas, by reactions between ozone and fresh emissions of NO (such as 

that from automobiles): 

NO + O3 Æ NO2 + O2 [3-5] 

(An additional, more complex set of reactions leads to local reductions in ozone 

in response to increased NOx emissions.) The impact of this Reaction 3-5 is particularly marked after the sun sets and during the day in areas with high NOx 

(Figure 3-2); it forces ozone concentrations down, even below background concentrations. NO-associated decreases tend to occur relatively close to the NO 

sources. Indeed, increased NOx emissions can lead to local ozone reductions (for 

example, near major roads and near the stack in power-plant plumes), whereas 

ozone formation downwind is enhanced (Figure 3-4) (see also Ryerson et al. 

2001). The relationship between VOC emissions and ozone concentrations is 

somewhat simpler, with higher emissions typically leading to higher ambient 

ozone concentrations, particularly in urban areas. 

The long effective atmospheric lifetime of ozone, measured in weeks 

(IPCC 2001), leads to substantial regional and intercontinental transport, and 

increased global NOx emissions result in steadily increasing background ozone 

concentrations (e.g., Finnlayson-Pitts and Pitts 2000). That is in stark contrast 
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Ambient Ozone and Related Pollutants 51 

FIGURE 3-2 Ozone isopleth diagrams showing the nonlinear response of ozone to emissions of VOCs and NOx and how they can vary from a city center to a downwind location. 

Source: Adapted from Dodge 1977. 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 5 10 15 20 25 30

Hour

Ozone (ppm)

0

0.04

0.08

0.12

0.16

0 60 120 180 240 300 360

Day of Year

Maximum Ozone (ppm)

Maximum Ozone

(a) (b)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 5 10 15 20 25 30

Hour

Ozone (ppm)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 5 10 15 20 25 30

Hour

Ozone (ppm)

0

0.04

0.08

0.12

0.16

0 60 120 180 240 300 360

Day of Year

Maximum Ozone (ppm)

Maximum Ozone

0

0.04

0.08

0.12

0.16

0 60 120 180 240 300 360

Day of Year

Maximum Ozone (ppm)

Maximum Ozone

(a) (b)

FIGURE 3-3 Ozone concentrations in Atlanta in 2006: (a) diurnal variation of ozone on 

July 22; (b) daily maximum. 

with the initial view that ozone was an urban air pollutant that affected primarily 

the larger cities, such as Los Angeles (NRC 1991), and that it could be substantially mitigated by reducing VOCs. As pollution transport from high-NOxemitting areas, such as the Ohio River Valley, to downwind areas and cities became recognized as an important contributor to regional ozone, control efforts 

were redirected to reduce NOx. Now industrialization of developing nations and 

recognition of the stability of ozone and its increased concentrations over the 

oceans have led to a global view of the problem. Global background concentrations are increasing, they are higher over the continents, and they are yet higher 
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52 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

over and downwind of cities. As the ozone NAAQS is tightened, the regional 

concentrations approach the desired concentrations, providing very little room 

for the bump of ozone from individual cities. 

Downtown Atlanta

-0.040

-0.020

0.000

0.020

0.040

0.060

0.080

0.100

0:00

2:00

4:00

6:00

8:00

10:00

12:00

14:00

16:00

18:00

20:00

22:00

Local Time

Ozone Concentrations & 

Source Contributions (ppm)

S(2) cross

S(2) VOC

S(2) NOX

S(1) VOC

S(1) NOX

Ozone Conc.

Suburban Atlanta (Cherokee Co.)

-0.040

-0.020

0.000

0.020

0.040

0.060

0.080

0.100

0:00

2:00

4:00

6:00

8:00

10:00

12:00

14:00

16:00

18:00

20:00

22:00

Local Time

Ozone Concentrations &

Source Contributions (ppm)

S(2) cross

S(2) VOC

S(2) NOX

S(1) VOC

S(1) NOX

Ozone Conc.

FIGURE 3-4 Simulated ozone concentration and sensitivity of ozone to Atlanta-area 

NOx and VOC emissions for downtown Atlanta and a suburban location downwind. Bars 

in each graph illustrate how much local emissions change ozone concentrations in downtown and suburban Atlanta. Combined red and tan bars show how emissions of NOx in 

the Atlanta area affect ozone. If bars are above zero (positive sensitivity), Atlanta NOx

emissions increase ozone in locations shown at that time. If bars are negative, such NOx

emissions lead to decreases in ozone at that location and time. Locally, increased NOx

emissions lead to decrease in ozone (negative sensitivity) through much of day downtown 

but generally increase ozone downwind in suburban area. VOC emissions increase ozone 

during daytime downtown (for example, green portion of bars) but have less effect at 

night and downwind. Gap between ozone concentration and sum of sensitivities shows 

magnitude of ozone transported from outside area. Reducing local NOx emissions can 

decrease ozone peak but actually lead to an increase in 24-h average ozone on such a 

high-ozone day. On lower-ozone days, decreasing local NOx emissions can increase 

ozone through more of day. Source: Cohan et al. 2005. Reprinted with permission; copyright 2005, American Chemical Society.
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Ambient Ozone and Related Pollutants 53 

The amount of regional transport relative to local ozone production and 

the amount of NOx emissions relative to VOC emissions lead to differences in 

the dynamics of ozone formation between cities (and in responses to control, as 

discussed below). Where VOC emissions are abundant (or NOx emissions are 

low) and ozone concentrations are more homogeneous, ozone goes down relatively little at night, and weekend concentrations are similar to those in the rest 

of the week. That is particularly true in rural areas. In a place like Los Angeles, 

where ozone is largely produced locally and there are relatively high local NOx

emissions, ozone has a distinct diurnal trend, reaching a maximum in the afternoon and dropping toward zero in the evening and during the night. Ozone can 

increase on the weekend as NOx emissions decline (for example, because of 

decreases in traffic and construction). That is the “weekend-weekday ozone” 

effect (e.g., Chow 2003 and references therein). 

Despite the continuing rise in NOx emissions worldwide and increases in 

vehicle miles driven and electricity production from fossil-fuel combustion in 

the United States, ambient ozone concentrations in cities in the United States 

and other developed countries have generally decreased. The reductions have 

occurred as the result of decreases in VOC emissions, which tend to have a local 

effect on reducing ozone, and NOx controls, which lead to a more regional reduction. In many cities, particularly in the eastern United States, ozone originates primarily from distant VOC and NOx sources; it is formed as prevailing 

winds transport pollutants into the cities. Local VOC and NOx emissions cause 

more ozone to be added (e.g., NRC 1991, 2004a and references therein), and this 

leads to regionally high ozone concentrations with a noticeable increase in and 

downwind of cities (Figure 3-4; also see Box 3-1). 

OZONE MEASUREMENT 

In the United States, ozone concentrations are typically reported as a 

“mixing ratio,” the ratio of the number of molecules of ozone to the number of 

all molecules in the same volume of air. For example, the typical unit used for 

regulatory purposes is parts per million, although scientific studies often use 

parts per billion. The prior NAAQS was an average of 0.08 ppm over 8 h, which, 

with rounding, was effectively 84 ppb, whereas the current NAAQS is 0.075 

ppm. Other nations often use units of mass per volume, such as micrograms per 

cubic meter.1

 

Ground-level ambient ozone has for many decades been one of the most 

well-characterized pollutants in the United States, especially in more populated 

areas where multiple monitors are used. For example, the Los Angeles Basin has 

over 30 ozone monitors. Ozone is also measured in rural locations and in na- 

 1

Ozone at 1 ppb is about 2 μg m-3 (within about 2% at standard temperature and pressure). 
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54 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

BOX 3-1 Policy Relevant Background

EPA defines the policy relevant background (PRB) as the level that a 

pollutant concentration would be in the absence of anthropogenic emissions from the United States, Mexico, and Canada (see Chapter 2). However, because of intercontinental transport of ozone and its precursor 

emissions, it is not feasible to directly measure the amount of ambient 

ozone attributable only to PRB sources. Therefore, modeling is the only 

viable approach to estimating a PRB. Observations in very remote places 

can be used to assess how well a model simulates chemistry and transport 

in clean regions. In the 2006 Criteria Document, EPA used results from the 

GEOS-Chem global air quality model (Fiore et al. 2003), with U.S., Canadian and Mexican anthropogenic emissions removed, to provide temporally 

and spatially varying PRB ozone levels (EPA 2006a). As applied, GEOSChem used a spatial resolution of 2o

 latitude by 2.5o longitude (about 200 

km x 275 km). Criticisms of this approach include the model’s coarse spatial resolution and reliance on the assumption that Canadian and Mexican 

emissions would be potentially removed by U.S. policies (e.g., Brauer et al. 

2007). Further, some analyses of observations at remote sites suggest that 

the calculated PRBs are low (Lefohn 2006; Brauer et al. 2007), noting that 

the model may underestimate the impact of some natural processes. 

Although the approach used by EPA in calculating the PRB was reasonable given the information available at the time, there is a need to address the criticisms levied in order to provide a better foundation for a similar exercise in the future. The inclusion of Canadian and Mexican 

emissions removal in the process is a policy decision, and the influence of 

that choice is uncertain. GEOS-Chem’s coarse resolution is of some concern, because the effect of using a model with a coarse resolution is uncertain, though given the lack of local emissions substantial concentration 

gradients are not expected. Although comparison of simulated ozone levels at a remote site to those observed did not show significant bias (Fiore 

et al. 2003, Hudman et al. 2004), demonstrating that the simulated distributions of observed ozone agree with observations at a variety of remote 

sites would strengthen the foundation of the modeling approach(es) chosen for future implementation. In regards to how to scale ozone levels between current levels and those meeting various proposed NAAQS, an assessment of how ozone will respond to the alternate path(s) of emissions 

removal would be of interest (e.g., compare removing 50% of the NOx, 

versus 50% of the VOC versus 50% of both). Such information can be 

used in the uncertainty assessments conducted as part of the NAAQS review process.

tional parks, for example, as part of the IMPROVE network (Sisler and Malm 

2000). In many locations, however, ozone monitors are operated only during the 

ozone season, which varies from place to place. During the ozone season, monitors provide nearly continuous measurement, although levels are typically re-
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Ambient Ozone and Related Pollutants 55 

ported hourly. Thus, information on ozone, both spatial and temporal, is relatively complete in contrast with information on other pollutants. The wealth of 

information on ozone can be contrasted with that on airborne fine PM with an 

aerodynamic diameter less than 2.5 μm (PM2.5), which has been widely monitored for less than a decade and of which many of the measurements are for 24-h 

periods as opposed to hourly in the case of ozone. 

Chemiluminescent monitors or UV absorption monitors are typically used 

for routine ozone measurements. A recent Environmental Protection Agency 

(EPA) analysis found that when averaged over 8 h monitor precision is better 

than 3%, which is why the ozone design value (for an emission-control program) determined from an area’s monitoring data is within about 1.3 ppb (about 

3 μg m-3) (EPA 2007a). For regulatory purposes, data are rounded to the last 

figure in the level of the standard; thus, the previous standard of 0.08 ppm has 

led to an effective standard of 0.084 ppm (EPA 2007a). In other words, a measured value of 0.084 ppm would be rounded down to meet the 0.08 standard. This 

improved measurement accuracy has prompted EPA and its Clean Air Science 

Advisory Committee to recommend making the revised ozone NAAQS more 

precise, that is, adding an extra digit to the level of the standard. In March 2008, 

EPA set the level of the standard at 0.075 ppm (EPA 2008a). 

SOURCES OF OZONE PRECURSORS AND OZONE CONTROL 

There are myriad major outdoor sources of VOCs, including vegetation, 

solvent use, and mobile sources (Figure 3-5). Ambient sources of NOx include 

fuel combustion (for example, in cars, trucks, construction equipment, factories, 

and power plants) and to a lesser extent biogenic activity (Figure 3-5). The distribution of sources and the other factors that contribute to ozone cause the highest ozone concentrations to be in or just downwind of larger cities, particularly 

cities that are sunny during summer, such as Los Angeles, Houston, cities in the 

Northeast Corridor, and Atlanta. However, smaller cities can experience ozone 

concentrations above the previous NAAQS of 0.08 ppm; with the promulgation 

of a tighter ozone standard, even more areas are expected to be out of attainment 

of the NAAQS for ozone (see Figures 2-1 and 2-2 in Chapter 2). 

Early ozone-control programs concentrated on VOC-emission reductions 

because they were thought to be cost-effective, decreased concentrations of 

many additional air toxicants, and, unlike control of NOx, were unlikely to raise 

ozone concentrations. However, as the regional nature of the ozone problem 

became apparent, the focus shifted to NOx-emission controls, which had a 

greater influence on regional ozone concentrations. For example, the recent 

Clean Air Interstate Rule (CAIR) (EPA 2007h), which is designed to reduce 

ozone and PM2.5, focuses on reducing NOx and SO2 from electricity-generating 

units and other large sources in 28 eastern states and the District of Columbia. 
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56 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

VOCa

NOx

FIGURE 3-5 Anthropogenic sources of 2002 ozone-precursor emissions of VOCs and 

NOx. Biogenic sources are not included but dominate nationwide VOC emissions. 

Source: EPA 2003c, Figures 2-19 and 2-36. 

Automobile standards, which originally limited VOC and CO emissions, now 

include limits on NOx and PM emissions. If the imposition of CAIR, tighter 

automobile and truck emission standards, and other controls are effective to the 

extent expected by EPA, they will lower ozone substantially in the near future 

(Figure 3-6). Those controls would reduce NOx by about 42% and anthropogenic VOCs by 28% by 2020 (Woo et al. 2006). Given that those steps are not 

likely to bring all areas into attainment, state improvement plans will need to 

include further controls. 

RELATED POLLUTANTS 

In assessments of the mortality risks associated with ozone exposure, it is 

important to consider how emission sources, meteorology, and the chemistry of 

ozone formation affect the formation of other pollutants of concern, including 

components of particulate matter (for example, the sulfate fraction of PM2.5) and 

other gases, such as aldehydes, and acids (Figure 3-1). The sharing of many of 
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FIGURE 3-6 Left, ozone and PM2.5 nonattainment areas in the eastern United States in 2006. Right, implementation of CAIR and other controls is expected to bring future ozone concentrations in many areas in the eastern United States into attainment of the previous 0.08-ppm ozone 

NAAQS. Source: EPA 2005c. 

57
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58 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

the sources and the intertwining of chemical and meteorologic processing lead 

to strong correlations between ambient ozone concentrations and concentrations 

of the other pollutants, such as sulfate and particulate organic carbon in summer 

(see Tables 3-1a, b, c and Table 3-2). The strong linkages and the fact that the 

other pollutants may have health effects are captured in a regulatory context in 

TABLE 3-1a Day-to-Day Correlation Between Air Pollutants in Boston, MA, 

by Season (Summer Nonshaded, Winter Shaded), 1999-2004a

 O3 PM2.5 SO4

2- BC PN NO2 CO SO2

O3 1.00 0.55b 0.59b -0.06 -0.34b 0.10 -0.03 0.01 

PM2.5 -0.62b 1.00 0.74b 0.43b -0.37b 0.27b 0.36b 0.11 

SO4

2- -0.43b 0.78b

 1.00 0.34b -0.31b 0.25b 0.14 0.13 

BC -0.60b 0.67b 0.64b

 1.00 0.11 0.55b 0.39b 0.17 

PN -0.13 -0.04 0.10 0.10 1.00 0.25b

 0.03 0.22b

NO2 -0.56b 0.60b 0.57b 0.64b 0.33b

 1.00 0.54b 0.32b

CO -0.58b 0.50b 0.48b 0.72b 0.23b 0.59b

 1.00 0.33b

SO2 -0.42b 0.64b 0.50b 0.47b 0.32b 0.63b 0.60b

 1.00 

a

Pearson correlation coefficients. Summer defined as May-August, winter as NovemberFebruary. BC = black carbon. PN = particle number. b

indicates p-value < 0.0001. 

TABLE 3-1b Day-to-Day Correlation Between Air Pollutants in St. Louis, MO, 

by Season (Nonwinter Clear, Winter Shaded), April 2001-September 2002a

 O3 PM2.5 SO4

2- NO3- BC OC NO2 CO SO2

O3 1.00 0.39b 0.37b -0.54b 0.02 0.30b -0.10c -0.21b 0.06 

PM2.5 -0.29 c 1.00 0.72b 0.06 0.50b 0.60b 0.23b 0.24b -0.03 

SO4

2- -- -- 1.00 -- 0.47b

 0.69b 0.18c 0.22c 0.02 

NO3- -- -- -- 1.00 0.07 -0.06 0.28b

 0.32b -0.01 

BC -0.39b 0.61b -- -- 1.00 0.77b

 0.69b 0.52b 0.03 

OC -0.20 0.68b -- -- 0.92b

 1.00 0.47b 0.42b 0.17c

NO2 -0.23 c 0.53b -- -- 0.70b 0.70b

 1.00 0.49b 0.16c

CO -0.35b 0.53b -- -- 0.86b 0.79b 0.53b

 1.00 0.05 

SO2 -0.02 0.30b -- -- 0.29c 0.27c 0.35b 0.25c

 1.00 

a

Pearson correlation coefficients. Winter defined as November-March, nonwinter as 

April-October. Data from St. Louis Supersite. PM2.5 measured with beta-attenuation 

gauge monitor. BC = black carbon. OC = organic carbon. Sulfate and nitrate data not 

available during winter 2001-2002. Sample sizes for pairwise comparisons generally 

above 70 in winter and from about 110 to 390 in nonwinter (except 53 for SO4

2- and OC 

comparisons in nonwinter). b

indicates p-value < 0.0001. cindicates p-value < 0.05. 
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TABLE 3-1c Day-to-Day Correlation Between Air Pollutants in Los Angeles, 

CA, by Season (Nonwinter Clear, Winter Shaded), June 2002-December 2003a

 O3 PM2.5 SO4

2- NO3- EC OC NO2 SO2

O3 1.00 0.08 0.32c -0.08 -0.56b -0.32 -0.38b -0.07 

PM2.5 -0.32b 1.00 0.87b 0.78b 0.33c 0.49b 0.46b -0.04 

SO4

2- -0.08 0.79 b 1.00 0.68b

 -0.01 0.17 -0.05 0.09 

NO3- -0.27 0.97 b 0.82b

 1.00 0.33c 0.44c 0.31c -0.02 

EC -0.80b 0.65 c 0.21 0.52c

 1.00 0.87b 0.86b 0.28c

OC -0.60c 0.82 b 0.40c 0.69b 0.84b

 1.00 0.89b 0.31c

NO2 -0.64b 0.65 b 0.41c 0.64c 0.87b 0.90b

 1.00 0.21b

SO2 -0.30b 0.28 c 0.25 0.27 0.51c 0.41c 0.55b

 1.00 

a

Pearson correlation coefficients. Winter defined as November-February, nonwinter as 

March-October. Data from EPA Speciation Network. EC, elemental carbon. OC, organic 

carbon. In winter, sample sizes for pairwise comparisons with particles 27 or 28 and for 

comparisons between gases, about 180; in summer, samples sizes for comparisons with 

particles above 60 and for comparisons between gases, 370. bindicates p-value < 0.0001. c

indicates p-value < 0.05. 

that the NAAQS is for ozone and other photochemical oxidants; ozone is used 

as an indicator of the presence of the wide array of photochemical oxidants present in ambient air. (Other photochemical oxidants include a wide variety of 

both organic and inorganic species, such as nitrogen dioxide, organic and inorganic acids [sulfuric, nitric, formic, etc.], organic and inorganic peroxides, other 

reactive oxygen species such as quinones, and many more. [see also Figure 3-1 

for chemical linkages].) Similarly, epidemiologic studies of ozone-health associations tacitly include the potential exposure to co-occurring pollutants unless 

they control for such additional exposure. However, the complete suite of other 

pollutants has never been monitored sufficiently to be included in such studies. 

Many of the photochemical oxidants that would be expected to covary with 

ozone are hardly, if ever, monitored. 

Correlations between ozone and other pollutants, both measured and unmeasured, have led to an awareness of the possible confounding of ozone-health 

effects analyses. As shown on Tables 3-1a-c, correlations between ambient 

ozone and other pollutants, such as PM, vary substantially by geographic location, season, and pollutant. For example, associations between ambient ozone 

and PM2.5 differ substantially in the Western and Eastern United States, between 

summer and winter, and for different PM components. Also, correlations among 

ambient ozone and other pollutants have been shown to vary by averaging period. These results suggest that the potential for confounding of ozone-health 

effects also varies by these factors, as discussed in Chapter 4. Strong correla- 
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60 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

tions between ambient ozone and its co-pollutants further suggest that it may be 

difficult to separate the effects of ambient ozone from its co-pollutants in epidemiologic studies based on using ambient concentrations as an estimate of exposure. 

Of ozone’s copollutants, ambient PM2.5 has been of particular concern 

with regard to confounding because of its observed effects on health and the 

often strong, seasonally varying correlations between ambient concentrations of 

ozone and PM2.5 (Tables 3-1 and 3-2). PM2.5 is a mixture of many compounds 

that originate from a variety of primary emission sources and reactions in the 

atmosphere. Not only do the formation and fate of specific compounds vary 

temporally and spatially but health assessments suggest that the components 

have different health effects (e.g., Laden et al. 2000; Peel et al. 2005; Thurston 

et al. 2005; Sarnat et al. 2008). 

Strong summer correlations between ozone and PM2.5 may be attributed to 

similar formation processes. For example, in New York and other eastern U.S. 

states (Figure 3-6), PM2.5 in summer consists largely of sulfate, which originates 

primarily from the oxidation of emitted SO2 by the hydroxyl radical (Figure 3-1, 

Reaction 3-6), the same molecule that leads to oxidation of VOCs: 

SO2 + OH Æ . . . Æ H2SO4 Æ sulfate aerosol. [3-6] 

In winter, particulate nitrate formation from emitted NOx can be important. It, 

too, is oxidized by the hydroxyl radical: 

NO2 + OH Æ HNO3 Æ . . . Æ nitrate aerosol. [3-7] 

In addition, some organic products (OPs) formed in Reaction 3-4 can lead to 

SOA production and thus also contribute to PM2.5 concentrations. In contrast, 

ozone concentrations can be depressed in areas with high NO and NO2 (such as 

areas close to highways). That also means that ozone concentrations can be 

lower in areas that have pollutants coming from substantial NOx sources. For 

example, high concentrations of ultrafine particles (less than 100 nm in diameter) are found near freeways, which also have higher concentrations of CO and 

NOx (Zhu et al. 2002; Sardar et al. 2004). However, ozone and PM2.5 can correlate positively away from the source, for example, because of similar formation 

routes and precursor emission sources of ozone and sulfate (Figure 3-1). 

The relation between ambient ozone and PM2.5 can differ substantially between winter and summer, especially in areas with low winter sulfate, such as 

the eastern United States (Tables 3-1a,b,c). As a result of lower sulfate formation, primary PM2.5 sources—such as motor vehicles, wind-blown dust, and 

combustion—contribute a larger fraction of ambient PM2.5. Furthermore, secondary nitrates increase in winter because of a decrease in competition for ammonia (NH3) by sulfate and because of the decrease in temperature, both of which 
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TABLE 3-2 Pollutant Correlations at Jefferson Street SEARCH Site, Atlanta, GA, 1999-2006a 24-h O3 1-h max O3 8-h max O3

24-h O3

(O3 season) 

1-h max O3 

(O3 season) 

8-h max O3

(O3 season) 

PM2.5 0.31 0.52 0.47 0.60 0.74 0.73 SO4 0.56 0.65 0.63 0.55 0.61 0.61 

Organic carbon PM (OC) 0.02 0.24 0.19 0.55 0.70 0.70 24-h O3 1.00 0.87 0.91 1.00 0.80 0.87 

1-h max O3 0.87 1.00 0.98 0.80 1.00 0.97 

8-h max O3 0.91 0.98 1.00 0.87 0.97 1.00 24-h O3 (O3 season) 1.00 0.80 0.87 1.00 0.80 0.87 

24-h NO -0.31 -0.06 -0.11 -0.07 0.25 0.23 24 h average NO2 -0.13 0.12 0.07 0.16 0.45 0.42 

24-h average PM10 0.31 0.53 0.49 0.55 0.74 0.73 

aThis SEARCH site (Hansen et al. 2006) is the only location that has such a long record of daily speciated PM2.5, PM10, NOx, and 

O3 for such an analysis. 

61
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62 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

increase the stability of ammonium nitrate. At the same time, the decrease in 

solar radiation leads to lower hydroxyl-radical concentrations and reduced VOC 

oxidation and thus to lower NO conversion to NO2. The primary NO emissions 

then scavenge ozone. Thus, on days when primary PM and NO are poorly dispersed, concentrations of both increase, and the increased NO lowers ozone (often to well below background concentrations). Ambient concentrations of ozone 

and PM2.5 may not correlate or may even correlate negatively in winter (Tables 

3-1a,b,c). The seasonal variability in the ambient ozone-PM2.5 association suggests that the potential for confounding of ozone health effects by PM2.5 also 

differs by season, with confounding most likely when they correlate strongly in 

summer (see also Bell et al. 2007). 

The potential for confounding of ambient-ozone health effects by ambient 

PM2.5 also probably depends on particle composition, which varies with location 

and season (Figure 3-7). As shown above, ambient ozone concentrations tend to 

correlate strongly and positively with ambient sulfate but not with ambient traffic-related elemental carbon, where a negative correlation is often found. Since 

studies have suggested that PM2.5 health impacts may differ by component, these 

results indicate that confounding by specific PM2.5 components, including sulfate, elemental carbon, metals, and secondary organics, should also be examined. 

It will be difficult to address such confounding with currently available data, 

however, because data on the PM2.5 component have only recently been collected routinely in many sites. EPA’s Speciation Trends Network (STN) for 

monitoring PM2.5 components started in 2000, and individual monitors came on 

line at different times. Most monitors measure a standard set of characteristics, 

including PM2.5 mass and various components (Peterson et al. 2000; Flanagan et 

al 2006). In the near future, new speciated measurements may provide the 

needed data, but, unlike ozone data, such data are now generally available only 

once every 3 or 6 d. To understand how short-term variation in PM2.5 components might confound ozone-mortality associations, more frequent measurements may be needed. One other approach to avoiding the confounding by PM2.5

is to consider the spatial distribution of the two pollutants, although they have 

similar spatial distributions (Figure 3-4b), which are tied to their similarities in 

sources, transport, and chemistry. Confounding of epidemiologic studies of 

ozone-mediated mortality and other health effects by PM2.5, especially by such 

specific components of PM2.5 as sulfate, presents formidable challenges to the 

interpretation of both time-series and spatial distributions. A further challenge to 

epidemiologic studies is that there are hundreds of gaseous and particle-bound 

ozone-related pollutants, including peroxides, other reactive oxygen species, and 

oxidized organics—most of which are not routinely monitored. The correlations 

between ozone and PM, as well as the lack of characterization of the variety of 

ambient pollutants that may also contribute to adverse health outcomes, presents 

a challenge to epidemiologic studies of PM effects and to studies of ozone effects because of the potential for confounding by many of the pollutants in the 

atmospheric mixture. 
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Ambient Ozone and Related Pollutants 63 

FIGURE 3-7 Composition of PM2.5 in representative urban and rural locations. Urban 

sites are Toronto, ON, Canada; Washington, DC; Atlanta, GA; Mexico City, Mexico; Los 

Angeles, CA; and Fresno, CA. Averaging periods and average PM2.5 mass are indicated. 

All sites have at least 1 y of sampling except Mexico City, for which average was determined for 14 d in 1 mo. More recent short-term measurements from December 1995 and 

January 1996 at Fresno and Kern Wildlife Refuge in California show lower PM2.5 mass 

concentrations than displayed here but similar composition. Colorado Plateau data are 

averages of IMPROVE sites in Bryce Canyon, Canyonlands, Grand Canyon, Petrified 

Forest, Mesa Verde, and Zion National Parks. Source: NARSTO 2003. Reprinted with 

permission; copyright 2005, Cambridge University Press. 

OZONE CONTROL 

EPA uses morbidity and mortality risk estimates to assess the benefits of 

its pollutant-control programs and thus the benefits of reductions in specific 

emissions from specific sources. That approach has a subtle but profound effect 

on the metric chosen to link ambient ozone concentrations with mortality risk. 

Various studies (e.g., Bell et al. 2005; Levy et al. 2005) have considered different metrics to characterize short-term ozone exposure, including the 24-h aver-
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64 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

age, the 8-h maximum (similar to the NAAQS), and the 1-h maximum (similar 

to the prior NAAQS). In meta-analyses of studies of the relationships between 

ozone and mortality (e.g., Bell et al. 2005), ozone concentrations were linearly 

scaled to the same metric to allow comparisons across studies; for example, a 

24-h ozone average was used by Bell et al. (2005). Scaling of the 1-h maximum, 

the 24-h average, and the 8-h maximum ambient ozone concentrations is reasonable given their typically strong correlations for a given location, but it is not 

generalizable to ozone-control strategies in that the 24-h average and 1-h and 8-

h maximum ambient ozone concentrations will respond differently to specific 

control strategies (Table 3-3) (Liao et al. 2008). For example, although measures 

to reduce ground-level NOx emissions in a city, such as that from cars, may result in lower daily maximum ambient ozone concentrations on sunny stagnant 

days (for example, see Figure 3-8) (Cohan et al. 2005) in or downwind of such 

cities as Atlanta, Houston, and New York (Sillman et al. 1990; NRC 1991), the 

measures can also result in higher 24-h averages because of the higher nighttime 

ozone concentrations due to reduced ozone scavenging at night (as discussed 

above). Furthermore, on days that are cloudy or otherwise less conducive to 

ozone formation, NOx-reduction measures can result in both higher peak and 

higher average ozone; that is, the sensitivities of ozone to NOx controls are negative (Figure 3-8). Thus, strategies aimed at meeting the NAAQS (based on reducing the fourth-highest 8-h maximum) can lead to increases in average ozone 

level concentrations (Table 3-3). 

This issue is directly related to assessments of the characteristics of ozone 

exposure that lead to death and other end points of concern. As shown in Table 

3-2 and noted in various studies (e.g., Bell et al. 2004), various ozone metrics 

for data collected in a specific location tend to be highly correlated, so it may 

seem unimportant to distinguish between them; given the degree of correlation, 

it may be difficult for an epidemiologic study to do so. However, the choice of 

metric can be influential in determining benefits of control programs. For example, a program that lowers NOx emissions could reduce peak ozone concentrations but raise average concentrations. A cost-benefit analysis based on mortality and average ozone could appear to show a negative benefit although the 

association with peak summertime concentrations appears to be positive. As 

discussed later, it is unknown which is more accurate, so evaluating the benefits 

of urban NOx reduction is uncertain in both magnitude and sign. Complicating 

the process is that the association might depend on the metric of exposure, that 

is, whether the response is taken to have a threshold or not. In the recent 

NAAQS review process, EPA assumed a linear nonthreshold response (EPA 

2007a). 

Control programs for ozone will affect other pollutant concentrations because ozone precursors are also responsible for formation of other species; pollutants have many sources in common. The effects of these ozone-control programs on other species will vary in space and time and, as discussed above for 

ozone, can even change direction, depending on conditions. In general, reduc- 
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Ambient Ozone and Related Pollutants 65 

TABLE 3-3 Simulated Sensitivity of Annual Average Ozone to NOx and 

Sensitivity of Fourth-Highest 8-h Average Ozone to NOx

a

 

 Atlanta Chicago Houston 

Los 

Angeles New York 

2001 annual average 

ozone -0.06 -0.11 -0.05 -0.07 -0.11 

2001 fourth-highest 8-h 

average ozone 

0.42 0.26 0.28 0.05 -0.29 

a

Negative sensitivity means that ozone will go up if NOx emissions are reduced. Sensitivities provided are local (for example, in given conditions, how ozone will respond to 

emission changes) and are given as parts per billion per 1% change in domainwide NOx

emissions. As shown, annual average ozone goes up in each location, although fourthhighest 8-h averages typically are reduced. Source: Adapted from Liao et al. 2008. Reprinted with permission; copyright 2008, American Chemical Society. 

Atlanta (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

SMDAO3, NOx (ppb)

Atlanta (2050)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

 Atlanta (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Chicago (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

SMDAO3, NOx (ppb)

Chicago (2050)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Chicago (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Houston (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

SMDAO3, NOx (ppb)

Houston (2050)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Houston (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Los Angeles (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

SMDAO3, NOx (ppb)

Los Angeles (2050)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

Los Angeles (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

New York (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

MDA8hr O3 (ppb)

SMDAO3, NOx 

(ppb)

New York (2050)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

MDA8hr O3 (ppb)

New York (2001)

-1.0

-0.5

0.0

0.5

1.0

0 50 100 150

MDA8h O3 (ppb)

FIGURE 3-8 Calculated daily sensitivities of maximum 8-h averaged ozone in Atlanta, 

Chicago, Houston, Los Angeles, and New York regionwide changes in NOx emissions 

and corresponding simulated concentrations. Shown are responses both at the city center 

and at the location of the regional maximum for 2001, and for the city-center case in 

2050 in response to a 51% reduction in NOx emissions. Results shown are for change in 

ozone in parts per billion per 1% change in domainwide NOx emissions. Although highest 

8-h ozone average may decrease with NOx controls, lower peak daily concentrations can 

increase. Ozone formations at the location of the regional maximums tend to be more 

NOx-limited. Source: Liao et al. 2008. Reprinted with permission; copyright 2008, 

American Chemical Society. 
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66 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

tions in NOx will directly reduce nitrate formation (e.g., Russell and Cass 1986; 

Boylan et al. 2006), and there is evidence that they will slightly increase sulfate. 

For example, Liao et al. (2007b) found that the effect of a 1% reduction in NOx

emissions would be a 0.2-ppb reduction in average fourth-highest 8-h maximum 

ozone, a 0.01-μg/m3

 reduction in average annual nitrate aerosol, and a slight 

increase in average annual sulfate, with some areas experiencing small increases 

and others seeing decreases. Reductions in anthropogenic VOC emissions would 

reduce SOA formation, although the relationship between anthropogenic and 

biogenic VOC emissions and SOA formation is uncertain, and it would depend 

on which VOC species were being controlled (e.g., Robinson et al. 2007). Some 

organic compounds (such as benzene) are toxicants or (as in the case of formaldehyde) result in formation of toxicants in the atmosphere. Effects on toxic 

compounds will depend on the type of control and the source. For example, reducing automobile VOC emissions will probably reduce benzene, and changing 

paint solvents will affect the concentrations of other compounds. VOC controls 

will lead to minor changes in sulfate and nitrate concentrations (Napelenok et al. 

2007). 

Much less is known about how ozone-related controls will affect concentrations of reactive oxygen species (ROS), in large part because of the general 

lack of specific knowledge about ROS. The chemistry of oxidant species and the 

presence of their precursors suggest that reductions in VOC emissions would 

lead to reductions in organic ROS. If the ROS is associated with metals, the effect of ozone-related controls is less obvious, because the dominant precursor 

sources are less common and the chemistry not as well explored. 

Some PM-related controls (such as NOx controls, as discussed above) will 

affect ozone concentrations and (as in the case of control of fly ash) could reduce metal-associated ROS. SO2 reductions will have a minor effect on ozone 

concentrations (Napelenok et al. 2007), and the direction of the response is uncertain (Dickerson et al. 1997; Jacobson 1998). 

OZONE DYNAMICS AND MONITORING: 

IMPLICATIONS FOR HEALTH STUDIES 

Time-series studies of ozone typically assess health effects in terms of 

ambient concentrations measured over time at a central monitoring site or at 

several sites in the study area. The use of ambient concentrations to estimate 

exposures is a source of considerable uncertainty in understanding ozonemediated mortality with respect to both how well they indicate ozone exposures 

over time and space and how well ozone effects can be separated from effects of 

other pollutants or weather conditions. The relation of ambient concentrations to 

ozone exposures of a study population depends on several factors, including the 

spatial distribution of ambient ozone and the typical activity patterns and homeventilation patterns of the study community. Spatial variability in ambient ozone 

concentrations is generally less important in that concentrations of ambient 
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Ambient Ozone and Related Pollutants 67 

ozone and other secondary pollutants tend to be relatively homogeneous (e.g., 

Wade et al. 2006) over large areas. Over greater distances, ambient ozone concentrations do vary, being sometimes higher in suburban and rural areas than in 

urban areas (Liu et al. 1993; Waldman et al. 1990) and higher away from roads 

than near roads. Transport of ozone and its precursors can also lead to a gradient 

in concentrations in an area. 

Such causes of spatial variability in ozone concentrations in a community 

increase exposure error in time-series studies based on ambient concentrations, 

because this spatial variability can vary over time. The increased error may result in biased risk estimates (Wakefield and Shaddick 2006). Nevertheless, spatial variability in ozone concentrations is generally a minor concern in timeseries epidemiologic studies because other factors, such as indoor concentrations 

and activity patterns, usually introduce larger errors in estimates of ozone exposure over time. Indoor ozone generally originates outdoors; indoor sources—

such as photocopiers, laser printers, and some air cleaners—are not present in 

most homes. Indoor residential ozone concentrations are thus determined 

primarily by outdoor concentrations and by factors that affect the ability of 

ozone to penetrate into and persist in the home, including removal by reaction 

on surfaces, air exchange between indoors and outdoors, air filtration, and 

reactions between ozone and other indoor pollutants. 

Under normal conditions, the half-life of ozone indoors is only 7-10 min 

(Weschler 2000). For averaging periods of 24 h, the short half-life results in 

generally low indoor concentrations (and often below the sampling method limit 

of detection).2

 These low concentrations reflect high rates of ozone removal by 

surface reactions. Indoor ozone concentrations are typically 10-50% of outdoor 

concentrations (Weschler 2006). Even at their lows, 24-h indoor ozone concentrations exhibit some diurnal and seasonal variation that reflects the outdoor 

variation. Indoor ozone concentrations tend to be higher in summer than in winter, when they are generally at or below the limit of detection of some measurement methods in personal exposure studies (Liu et al. 1993; 1997; Avol et al. 

1998; Sarnat et al. 2006). For example, in a Southern California study of 126 

homes (February-December 1994), mean 24-h indoor ozone concentrations (13 

± 12 ppb) were lower than corresponding outdoor concentrations (37 ± 19 ppb) 

(Liu et al. 1997). Indoor:outdoor ratios were greater during the summer pollution period. Higher summer ratios indicate the importance of home ventilation, 

especially in homes that do not have air conditioning or tight sealing. In non-airconditioned and other well-ventilated homes, 24-h indoor concentrations can be 

a larger fraction of corresponding outdoor concentrations (Liu et al. 1993; Gold 

et al. 1996; Sarnat et al. 2006; Weschler 2006). 

Similarly, in shorter averaging periods, indoor residential ozone concentrations can be a larger fraction of those outdoors when windows are opened. In 

 2

With the exception of periods when indoor concentrations of nitric oxide (NO) are 

elevated, indoor ozone concentrations are normally not below the limit of detection of 

UV photometric methods (Weschler and Shields 1994). 
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68 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

a study by Zhang and Lioy (1994), for example, indoor ozone concentrations in 

six New Jersey homes measured during the high-ozone afternoon hours (2:30-

7:30 pm) were found to track outdoor concentrations, with a mean ratio of 5-h 

indoor to outdoor ozone concentrations of 0.22 (+ 0.09) to 0.62 (+ 0.11). The 

indoor:outdoor ratios were highest (0.59 + 0.16) when windows were open and 

gas stoves were off. For homes with air conditioning and homes with closed 

windows and no air conditioning the indoor:outdoor ratios over the 5-h highozone periods remained relatively low, 0.28 (+ 0.12) and 0.26 (+ 0.12), respectively. Use of a gas stove lowered indoor:outdoor ratios further for all ventilation conditions. 

The low indoor ozone concentrations explain why 24-h personal ozone 

exposures are low: people spend on the average 87% of their time indoors 

(Klepeis et al. 2001). The average amount of time people spend outside during 

their day varies little across the United States (Klepeis et al. 2001). Therefore, 

daily averaged ozone concentrations to which people are exposed (averaged 

over the time spent indoors and outdoors) are generally low relative to outdoor 

concentrations averaged over the same period regardless of geographic location, 

with measured personal ozone concentrations generally below the limit of detection of some measurement methods. Like 24-h outdoor and indoor concentrations, 24-h personal ozone exposures are higher in summer than in winter, although summertime concentrations to which individuals are exposed (averaged 

over 24-h) are still a relatively small fraction of corresponding 24-h outdoor 

values (Liu et al. 1993, 1997; Sarnat et al. 2000; Sarnat et al. 2006). For example, 

in a Steubenville, OH, cohort of older adults which was conducted over a seven 

month period, the mean 24-h personal:ambient ratio of ozone concentration, 

0.24, was substantially lower than that of any of the other measured pollutants 

(PM2.5, EC, sulfate, NO2, and SO2). 

It is important to note that over periods of less than a day, such as 1 h, personal ozone exposures can be relatively high; Hourly personal exposure concentrations were shown in a scripted-exposure study to be comparable with corresponding outdoor concentrations when the trained technician spent the time 

outdoors (Chang et al. 2000). Based on these findings, it is possible that hourly 

and peak ambient ozone concentrations are appropriate surrogates for personal 

ozone exposure concentration, especially in summer and during peak afternoon 

high ozone hours, which account for much of the individual outdoor time (Figure 3-9). Further study should examine whether this is in fact the case, especially for individuals who are susceptible to ozone exposures. 

Hourly personal exposures in the scripted-exposure study were also 

strongly associated with hourly outdoor concentrations when the trained technician was outdoors (Chang et al. 2000). In contrast, when the technician spent the 

hour indoors or in transit, associations between hourly personal exposures and 

ambient concentrations were not significant. Similarly, over 24 h, the vast majority of which is spent indoors, many studies suggest that personal ozone exposure concentrations are not strongly associated with corresponding ambient con- 
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FIGURE 3-9 Activity patterns by time of day. Adapted from U.S. National Human Activity Pattern Survey. Source: Klepeis et al. 2001. Reprinted with permission; copyright 

2001, Journal of Exposure Science and Environmental Epidemiology. 

centrations regardless of whether individuals are followed over time or at one 

point in time, with consistently low slopes and R2

 values for regressions of personal ozone on ambient concentration (Brauer et al. 1989; Liu et al. 1993, 1997; 

Linaker et al. 2000; Patterson and Eatough 2000; Sarnat et al. 2000; Sarnat et al. 

2006). It is important to note that these low R2

 values may be due in part to the 

low measured personal exposures, which were often below the limit of detection 

of the measurement methods used in those studies. Despite this, the low R2

 values do suggest that estimates from time-series studies may be biased toward the 

null hypothesis. 

More recent studies suggest that the associations are substantially weaker 

than those for PM2.5 and sulfate (Sarnat et al. 2000; Sarnat et al. 2006) and 

stronger in summer than in winter. The seasonal variability probably reflects 

increased home ventilation in the hotter summer months. Consistently with that, 

the slope of the regression between 24-h ambient ozone concentrations and corresponding personal exposures in Steubenville, OH, was 100% higher for elderly people spending time in well-ventilated indoor environments (slope, 0.18 ±

0.03; t value, 7.34) than for other people (slope, 0.08 ± 0.04; t value, 1.89). As 

supported by Levy et al. (2005), those findings suggest that ventilation (and thus 

season) is an important modifier of ozone-mortality risk estimates, and further 

provide potential explanations for observed seasonal or between study variability in other studies. 
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70 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Even in well-ventilated conditions, however, the slope of the ozone association is small, and this suggests that only minor changes in ozone exposure 

occur in response to moderate changes in outdoor concentration. Together, low 

personal exposure concentrations and weak personal-ambient concentration relationships suggest that 24-h ambient ozone concentrations are poor proxies for 

personal exposure. For shorter averaging periods, results of the one scriptedexposure study suggest that hourly or peak ambient ozone concentrations may 

be appropriate proxies for corresponding hourly or peak personal exposures. 

Additional short-term personal-ozone exposure studies are needed, given 

ozone’s large contribution to uncertainty in ozone-mortality risk estimates; however, these studies will require the development of new measurement methods 

that have sufficient sensitivity to measure these likely low, short-term exposures. 

The relatively poor correlation of ambient ozone concentration with personal exposure—combined with the strong associations among ambient ozone 

concentration, ambient PM2.5 concentration, and temperature—raises concerns 

about whether ozone mortality attributed to ozone is due instead to these or 

other correlated factors. Evidence from a series of 24-h multipollutant exposure 

panel studies performed generally over two seasons at locations—including Baltimore, MD (Sarnat et al. 2001), Steubenville, OH (Sarnat et al. 2005), and Boston, MA (Rojas-Bracho et al. 2004)—indicates that potential confounding by 

correlated pollutants and weather is an important source of uncertainty in ozonemortality risk estimates. Results from longitudinal analyses have consistently 

shown, for example, that 24-h ambient ozone concentrations are substantially 

weaker proxies for corresponding exposures than PM2.5. In addition, studies 

have shown 24-h ambient ozone concentrations to be important proxies for personal PM2.5 exposures over time. Associations between 24-h ambient ozone 

concentrations and personal PM2.5 exposures tended to be stronger in Boston and 

Steubenville than in Baltimore, possibly because of better home ventilation in 

the two cities. It is consistent with that idea that for all cities 24-h ambient ozone 

was a stronger proxy for personal PM2.5 exposures for individuals followed in 

summer than winter and for people spending most of their time in wellventilated than in poorly ventilated environments. Because exposure studies of 

confounding have been based on 24-h values and for individuals living within 

the eastern United States, the generalizability of these results to exposures 

measured over shorter periods and to other populations is not known. 

OZONE-EXPOSURE MODELING 

One method for linking personal ozone exposure to ambient ozone concentration, and thus linking ambient ozone to health end points, is to model exposure in ways that account for individual behavior and individual ozone exposure concentrations. Such simulation models are valuable for estimating airpollution exposures in the absence of direct measurement. They can provide a 

framework for extending risk analyses across large geographic domains, even at 
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the national level. They can also be used to help to estimate the effect of ambient 

pollutant reductions on personal exposure, as is done in developing the ozone 

criteria document. Such analysis has been used in advising the EPA administrator on proposing standards (e.g., EPA 2007a). 

Exposure-simulation models can be used in epidemiologic models to study 

the association between human exposure to ozone and mortality or morbidity 

instead of relying on a monitored ozone value and providing a potentially more 

accurate representation of individual ozone exposure. Such human-exposure 

models could be powerful tools for drawing inferences about the health risks 

associated with exposure to tropospheric ozone. That approach was taken in the 

recent EPA ozone staff paper as part of the policy assessment (EPA 2007a). 

Uncertainty in such models should be characterized and quantified properly before they are used for ozone-mortality risk assessment for regulatory purposes. 

The ozone-exposure model developed by EPA to estimate human population exposure to the criteria and other toxic pollutants is called Air Pollutants 

Exposure (APEX). APEX is a probabilistic model designed to account for the 

numerous sources of variability that affect people’s exposures. APEX simulates 

the movement of people through time and space and estimates their exposure to 

a given pollutant in indoor, outdoor, and vehicular microenvironments. Daily 

activity patterns for individuals in a study area, one of the inputs to APEX, are 

estimated from detailed time-location-activity diaries that are compiled in the 

Consolidated Human Activity Database (CHAD) (McCurdy et al. 2000; EPA 

2003d). The diaries contain information regarding age, sex, race, employment 

status, occupation, day of week, daily maximum hourly average temperature, 

each location during the day, and start time, duration, and type of activity performed. APEX estimates the concentration in the microenvironment associated 

with each event in an individual’s activity pattern and sums the event-specific 

exposures within each hour to obtain a continuous series of hourly exposures 

spanning the period of interest. Activity-specific simulated breathing rates of 

individuals are used in APEX to characterize intake during each period. The 

breathing, or ventilation, rates are derived from energy-expenditure estimates for 

each activity included in CHAD and are adjusted for age-specific and sexspecific physiologic characteristics associated with each simulated individual. 

Ozone concentrations in each microenvironment are estimated with massbalance or transfer factors, and the user specifies prior probability distributions 

for the parameters to be used in the model; the prior distributions are used to 

model the uncertainties and variabilities in the parameters. 

APEX combines the estimated time series of exposure concentrations that 

a simulated individual experiences during the modeled period with the estimated 

time spent in each of the microenvironments visited according to the activity 

diary. The hourly average exposures of each simulated individual are timeweighted averages of the within-hour exposures. APEX then statistically summarizes and tabulates the 1-h, 8-h, and 24-h individual exposures, and then provides a distribution of ozone exposure for the population in a given census as 
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72 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

characterized by the simulated individuals. The estimated exposure is a linear 

function of the ambient ozone concentrations. 

Although there is the potential to use those exposure simulation models 

for future analyses, APEX has not yet been used to characterize ozone exposure 

in epidemiologic models for national ozone mortality analysis. Therefore, it has 

not been given more extensive consideration in this report. 

The parameter uncertainty in APEX is represented by prior distributions 

assigned to most of the parameters in the model. The prior distributions given to 

the model parameters are based on regional studies; to extend the prior distributions to the national level, more exposure studies should be conducted. There 

also is uncertainty in the formulation of the model and in the inputs. The different sources of error and uncertainties in APEX result from variability that is not 

modeled or is modeled incorrectly; from erroneous or uncertain inputs; from 

errors in coding; from simplifications of physical, chemical, and biologic processes to form the conceptual models; and from flaws in the conceptual model. In 

particular, the uncertainty in the estimation of ambient air quality will be propagated by APEX. The APEX output may also be very sensitive to the prior distributions used in the microenvironmental models. APEX relies heavily on the 

assumption that exposure to ozone is a linear function of ambient concentration, 

and this assumption needs more justification. 

CHAD may be the best available source of human-activity data for use in 

exposure modeling, but issues regarding how well CHAD diaries represent the 

simulated populations remain. CHAD contains 20,000 people that are used to 

represent several million over long periods, the diary data are relatively old 

(some data were generated in the 1980s), and there are diary structure differences (real-time data collection vs data collection by recall); each of these characteristics may lead to errors. The human diaries used by the model might be too 

limited to characterize and represent the simulated populations. EPA has conducted some validation studies of APEX (EPA 2007k). The committee agrees 

that the APEX approach is a useful way to assess population exposure, but remaining uncertainties require further study to estimate their magnitude and, to 

the extent possible, reduce them. 

SUMMARY 

Interpretation of studies relating measurements of ambient ozone to health 

end points is made difficult by the dynamics of ozone and associated pollutants, 

particularly how temporal and spatial variations affect individual human exposure. (Other questions about the existing evidence are addressed in Chapter 4.) 

Correlations between ozone and PM2.5 vary spatially, seasonally, and with PM2.5

components, all of which can confound the interpretation of epidemiologic 

analyses. Furthermore, exposure studies which typically relied on passive ozone 

monitors found that ambient ozone concentrations are not highly correlated with 

concentrations indoors, where people spend most of their lives, or with observed 
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Ambient Ozone and Related Pollutants 73 

personal exposures. Indoor ozone concentrations exhibit some diurnal and seasonal variations that reflect the outdoor variations. Correlations with ambient 

concentrations may be artificially low given that measured 24-h personal exposures concentrations and indoor concentrations were often below the method 

limit of detection. One way to improve characterization of indoor ozone exposure is to use continuous ozone monitors, which have greater sensitivity than 

passive ozone monitors. At the population level, characterization of ozone exposures can be improved using exposure modeling, although additional uncertainties are involved in model application. Accounting for those complexities presents a formidable obstacle in interpreting results of epidemiologic studies of 

ozone and health. 

Finding: Potential confounding of ozone-mortality studies by PM presents 

a challenge, particularly in considering seasonal and component effects. Some 

species are much more (or less) correlated with ozone when specific seasons are 

considered (for example, summer, when ozone is high) than over an annual cycle. Considering only PM mass would not account for effects of specific PM 

components. 

Recommendation: Both exposure and epidemiologic researchers should 

investigate seasonal and regional associations between ambient concentrations 

and exposures to ozone and PM2.5, (and its components), how they affect control 

of confounding, and correlations between the various pollutant concentrations. 

When possible, researchers should address those issues by focusing on groups of 

individuals who are sensitive to ozone exposures and by using data on the 

chemical and physical components and size distribution of PM2.5. 

EPA and the scientific community should increasingly include the growing Speciated Trends Network (STN) database in future analyses of potential 

confounding of the ozone associations. EPA should work with the scientific 

community to ensure that the STN collects data frequently enough on the particle components most relevant to the potential for confounding. 

Finding: Personal exposure, considering time spent outdoors and indoors 

on a 24-h basis, is poorly correlated with monitored ambient ozone concentrations, with low slopes of the regression of personal exposure on ambient ozone 

levels. However, findings on exposure in the afternoon, when both outdoor activity and ozone concentrations can peak, suggest that exposures to higher ozone 

concentrations are better captured by ambient monitoring. Control programs 

based on reducing peak afternoon ozone concentrations on days when they are 

greater than the standard can result in an increase in the 24-h concentrations on 

days that are conducive to ozone formation and can also increase afternoon concentrations on days less conducive to ozone formation. 

Recommendation: Future studies should determine whether and how 

much daily peak exposures, such as 1h or 8h exposures, and longer-term average 

exposures, such as over 24h, are associated with ozone-related mortality so as to 

guide control decisions for protecting public health. Benefits assessors at EPA 

and elsewhere should use the results to identify the appropriate exposure metrics 
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74 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

to estimate how efforts to attain the ozone NAAQS will affect ozone exposure 

and health. 

The committee notes that EPA has apparently not considered the use of 

two or more averaging times jointly. Does adding metric C to a model that already contains metric A, or metrics A and B, improve the fit of the model? Such 

analyses should be fairly easy to conduct and might show that 1-hour, 8-hour, or 

24-hour averaging times are roughly equivalent and that any one of these can 

substitute for the others. Conversely, one might find that one or two of these 

metrics add little when the third is already in the model. Or, it is possible that 

some combination of two or three of these is a better measure for analysis than 

any one alone. Measurement error is likely to blur the actual contributions of 

each metric and the relationships among them, but that is not relevant when the 

goal is to find the best empirical fit to the data. 

Regulators need to consider that control strategies may affect 24-h average 

concentrations quite differently from how they affect shorter-term exposures and 

that peak short-term concentrations on lower-ozone days will respond differently, and often in the opposite direction, from the same measure of ozone on a 

high-ozone day. 

Finding: Human-exposure simulation models, such as APEX, present an 

approach to estimating ozone exposure different from reliance solely on observations. However, such models introduce their own uncertainties, and they need 

to be further evaluated and their uncertainties characterized. 

Recommendation: EPA should conduct more detailed evaluations of 

APEX and other models used to improve characterization of ozone exposure at 

the population level by taking human activity into account. Detailed evaluation 

will require further human-exposure studies, which will need improved instrumentation and approaches for monitoring personal exposures. The extent to 

which the human diaries represent the population under study, as used by APEX, 

warrants further explication, and more extensive and more up-to-date diary data 

should be collected, in particular for children and minority groups. Those data, 

when tied to data on pollution concentrations and ozone-alert days, can be used 

to assess the type and degree of changes in behavior to avoid ozone exposure. 

The cost of such changes in behavior associated with increased pollution currently is not addressed in RIAs prepared by EPA. 

Finding: Epidemiologic studies of ozone health effects are limited, in part, 

by the reduced availability of ozone data in winter. 

Recommendation: EPA and states should extend operation of ozone 

monitoring into winter and report the measurements. The size of the winter program should be sufficient to enhance researchers’ ability to examine (1) seasonal 

differences in risk, (2) how these seasonal risk differences vary spatially between communities with warmer and cooler winters, and (3) ozone-mortality 

relationships at lower ozone concentrations. In recognition that ozone is a regional pollutant, winter measurements need not be collected in all the summer 

locations but, when they are collected, should be collected at the frequency of 

summer measurements. 
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75

4 

Contributions of Relevant Health 

Studies to the Estimation of Reductions 

in Premature Mortality 

INTRODUCTION 

This chapter reviews evidence of ozone-mediated effects on mortality. It 

builds on the wealth of toxicologic and epidemiologic evidence showing the 

deleterious effects of ozone on an array of health effects, including oxidative 

damage to DNA, inflammation, oxidative stress, heart-rate variability, decrease 

in lung function, such respiratory conditions as bronchitis and wheezing, increase in medication use, and exacerbation of respiratory diseases leading to 

emergency-room visits and hospitalization. Those effects have consistently been 

found in toxicologic and epidemiologic studies, independently of study design 

and location, and therefore constitute compelling and well-accepted evidence 

that ozone adversely affects health. 

In contrast, until its regulatory impacts assessment (RIA) for the proposed 

ozone national ambient air quality standards (NAAQS) released in 2007, the 

Environmental Protection Agency (EPA) had not included mortality results in it 

primary estimates of the benefits of reductions in acute exposure to ambient 

ozone, because of uncertainty about the appropriate interpretation of those results. Previously, EPA had included epidemiologic studies that link ambient 

ozone concentrations with premature deaths in sensitivity analyses. The shift is 

attributable to consistent findings from multicity time-series studies and metaanalyses conducted over the past few years that suggested a modest but highly 

significant increase in mortality associated with relatively short-term exposure 

to ambient ozone. 

This chapter reviews evidence of ozone-related death with regard to its 

biologic plausibility and reviews findings from the multicity time-series studies 

and meta-analyses. It also assesses evidence of the existence of susceptible 

groups and discusses how such factors as personal and population average-
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76 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

exposure error, epidemiologic designs and methods of analysis, measures of the 

effects of ozone exposure on death, and uncertainty contribute to our ability to 

estimate ozone-related mortality risk and to apply the estimates to risk and benefits analysis. 

BIOLOGIC PLAUSIBILITY 

The mechanisms by which ozone can damage health and possibly lead to 

mortality remain a subject of considerable clinical interest. Toxicologic studies 

have attempted to identify the mechanisms by using a variety of techniques, 

from ultrastructural, biochemical, and cytologic analyses to in vivo measurement of airflow mechanics. The techniques generally examine the effects of controlled ozone exposures of less than 8 h and, to a smaller extent, exposures of 

several days to increased ambient concentrations. 

The findings of a number of toxicologic studies provide insights to suggest 

the potential for a number of events by which ozone exposure could lead to increased mortality, including lung inflammation leading to local pulmonary compromise (Devlin et al. 1991; Holz et al. 1999; Koren et al. 1991; Ratto et al. 

2006; Bosson et al. 2007), worsening of pre-existing cardiopulmonary disease, 

systemic release of mediators that affect adverse cardiovascular events 

(Hollingsworth et al. 2007), effects on the autonomic nervous system that could 

contribute to increased airway responsiveness (Chen et al. 2003) or reduced 

heart rate variability, and an increase in factors that lead to vascular changes 

(Chuang et al. 2007). Definitive proof of such occurrences leading to mortality 

are not found in the current scientific literature, however, there is ample evidence ozone can induce mechanisms through a sequence of events to trigger 

oxidative stress or inflammation pathways, which can contribute to release of 

pulmonary or systemic mediators. The events may further result in the exacerbation of a pre-existing respiratory or cardiovascular condition. Chen et al. (2004) 

found increased sensitivity to aeroallergens in a subgroup of asthmatics following exposure to 200 ppb ozone. There exists the biological plausibility that for a 

few individuals with pre-existing cardiopulmonary or chronic respiratory disease, such oxidative or inflammatory events could also cause death, via the onset 

of an asthmatic attack (Selgrade et al. 2008), myocardial infarction, or vascular 

event. Inflammatory events have been shown to occur for 20-30 h after inhalation of ozone even at ambient concentrations in the range of 0.08-0.10 ppm 

(Ratto et al. 2006; Chuang et al. 2007). There is less information on the airway 

inflammatory response to ozone at low concentrations, such as at or below 0.08 

ppm. 

The oxidative stress and inflammation cascade is initiated by an ozonemediated airway and lung tissue response (Chuang et al. 2007). Ozone can initiate the cascade immediately after inhalation when it comes in contact with 

epithelial lining fluids and cellular membranes, most often at nasal epithelial 

surfaces and at the junction of the bronchioles and the alveolar region (centriaci-
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Study Contributions to the Estimation of Reduced Premature Mortality 77 

nar region). At the air-liquid interfaces, ozone can interact with unsaturated fatty 

acids to form lipid ozonation products, which in turn can activate lipases that 

lead to production and release of cell-signal transduction molecules and proinflammatory mediators. With oxygen species and reactive oxygen metabolites 

generated by exposure, those products of ozone exposure may lead to oxidative 

stress and the upregulation of transcription factors, such as NF-κB and proinflammatory genes. Correspondingly, antioxidant enzymes (such as glutathione 

enzymes, superoxide dismutase, and catalase) and nonenzymatic factors (such as 

ascorbic acid and α-tocopherol) that react with ozone directly have been shown 

to attenuate oxidant damage to airway lipid membranes. 

Biochemical evidence of ozone-mediated inflammation is provided by 

animal and human studies that show increases in downstream activation products of the innate immune system, including fibronectin, elastase, plasminogen 

activator, tissue factor, factor VIII, C3a fragment of complement, prostaglandins, interleukin-1 (IL-1), tumor-necrosis factor a, IL-6, IL-8, and granulocyte 

macrophage colony-stimulating factor (GM-CSF) in alveolar lavage fluid 

(Koren et al. 1989; Aris et al. 1993; Devlin et al. 1994). Inflammatory effects of 

ozone occur in people who are healthy and in people who have increased vulnerability because of host (genetic) factors or pre-existing cardiopulmonary disease, such as asthma. For example, ozone exposure at 100 ppb for 2 h leads to 

an acute neutrophilic inflammation of the airway in allergic asthmatic subjects 

(Depuydt et al. 2002). In addition, pre-exposure of these subjects (atopic asthmatics) to ozone potentiates the late-phase eosinophilic response to the allergen. 

The acute lung response to ambient ozone has many clinical features in common 

with asthma, and ozone exposure also leads to increase in proinflammatory cytokines (Koren et al.1989), cellular inflammation in airway tissues, and bronchial hyperresponsiveness (Foster et al. 2000). Perhaps as a result, exposure to 

ambient ozone can exacerbate pre-existing allergic asthma (White et al. 1994). 

Cultured human epithelial cells (HBECs) from asthmatic and nonasthmatic subjects exposed for 6 h to ozone at 100 ppb had increases in inflammationassociated mediators IL-8, GM-CSF, and intercellular adhesion molecule 1 

(Bayram et al. 2001). HBECs from asthmatic but not nonasthmatic people also 

showed increased expression of the chemotactic cytokine CCL5. Increased expression of CCL5 suggests that ozone exposure may increase eosinophilic inflammation, exacerbate asthmatic symptoms, and lead to pathologic changes in 

the epithelium (Bayram et al. 2001). Support for that suggestion is provided by 

studies that show human asthmatic subjects to have increased eosinophilic inflammation of the lower airways after prolonged acute exposure to ozone at 160 

ppb. Epithelial cytokine expression of IL-5, GM-CSF, and IL-8 has also been 

found to be higher in asthmatic subjects after laboratory exposure to ozone for 2 

h at 200 ppb (Bosson et al. 2003). 

Numerous laboratory chamber studies have validated the reproducible nature of the inflammatory lung response (Devlin et al. 1991; Koren et al. 1991; 

Holz et al. 1999). That finding has been supported by additional studies in humans using therapeutic ablation of inflammatory effects, which have also helped 
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78 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

uncover essential mechanisms of injury. Although inhalation of the corticosteroid budesonide was not found to limit ozone-induced airway inflammation in 

healthy subjects, budesonide reduced neutrophilic infiltration in patients with 

mild asthma as evidenced by changes in the inflammatory cellularity of induced 

sputum (Nightingale et al. 2000; Vagaggini et al. 2001). Inhaled and oral corticosteroids have also been found to ablate ozone-induced neutrophilic inflammation in selected healthy subjects who were characterized as neutrophilic ozoneresponsive (Holz et al. 2005). In mildly asthmatic subjects, pretreatment and 

posttreatment with apocynin aerosol, an inhibitor of the nictotinamide adenine 

dinucleotide phosphate (NADPH) oxidase complex present in membranes of 

inflammatory cells (eosinophils and neutrophils) and a source of reactive oxygen 

species, prevented ozone-induced airway hyperresponsiveness to methacholine 

(Peters et al. 2001). 

There has been relatively little research done on cardiovascular effects of 

ozone as compared with the amount done on pulmonary effects. Gong et al. 

(1998) used an ozone chamber study to monitored cardio-vascular effects in 

humans. In response to exposures to 300 ppb ozone, no major acute cardiovascular changes were found to be induced in either hypertensive or control subjects. It was noted, however, that ozone can increase myocardial work and impair pulmonary gas exchange. 

Together, those findings constitute supporting evidence that ozone exposure induces a cascade of events that increase oxidative stress and inflammation. 

As observed in numerous cohort and toxicologic studies, it is plausible that increased oxidative stress and inflammation can influence cardiac risk and ultimately mortality through increased autonomic dysregulation, vascular dysfunction, atherosclerosis, and arrhythmogenesis (Ridker et al. 1998, 2000; Pradhan et 

al. 2001, 2002). Those downstream effects may be most pronounced in people 

who have pre-existing diseases, in that ozone exposure may worsen a disturbed 

respiratory, vascular, or cardiac system, making them more vulnerable to 

ozone’s adverse effects. 

The adverse effects can occur after intermittent exposure to ozone, which 

is a typical pattern of exposure to this pollutant. Although the effects of ozone 

may accumulate over a lifetime, it is well established that gaps in ozone exposure lead to a decrease in innate resistance to its adverse effects. With the onset 

of each ozone-exposure episode, the injury process will be repeated, initiating 

once again the biologic events listed above. Such a cellular response to ozone 

means that each exposure event poses a renewed risk of a cascade of activities 

that could decrease resiliency and possibly enhance vulnerability, resulting in 

premature death. 

OZONE-MORTALITY STUDIES 

Given the evidence from toxicologic studies, it is biologically plausible 

that ozone exposures are also related to death in human populations. From a 
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Study Contributions to the Estimation of Reduced Premature Mortality 79 

biologic and epidemiologic perspective, there are two main ways in which air 

pollutants, such as ozone, may affect mortality: as a consequence of acute effects that cause death in the near term and as a consequence of chronic pathophysiologic changes that ultimately lead to death. The two may well overlap and 

be interrelated, but the distinction is useful because it is relevant to the interpretation and quantification of risks. 

Acute Studies 

Acute effects of ozone are those observed within a few hours or days of a 

rather short exposure. In those cases, exposure is typically defined as the maximum concentration on a given day, the mean across the 8 consecutive hours 

with the highest concentrations, or the 24-h average concentration. Under this 

acute-effect model, if death occurs, it is a consequence of the exposure. An acute 

exposure may also trigger a condition of poor health or frailty that can lead to 

death within a few days or weeks if intervention is not successful; in this delayed case, death may be considered a subacute effect of an acute (short-term) 

exposure. 

Time-series analysis is by far the most common approach to investigate 

the acute and subacute effects of ozone on mortality (see Box 4-1). The most 

systematic and comprehensive time-series analyses were two multicity studies 

(Bell et al. 2004; Ito et al. 2005) and three meta-analyses (Bell et al. 2005; Ito et 

al. 2005; Levy et al. 2005) solicited and commissioned by EPA.1

 The three research teams conducting the meta-analyses were provided with the same databases from EPA but conducted the analyses separately and did not communicate 

with each other about their methods or findings until the studies were completed. Those studies examined ozone-mediated mortality while addressing previously unresolved issues related to confounding, exposure variability, and 

model specifications. Although the studies used different approaches, their major results were similar: each found a statistically significant relationship between ozone exposure and premature mortality that appears robust after controlling for exposure to particulate matter with a diameter of 10 μm or less (PM10). 

The similar estimates from these three meta-analyses suggest not only an indication of stable estimates in the literature, but also indicate that the meta-analytic 

approach is generally insensitive to analytical decisions, which provides support 

for the meta-analytical methods. Together, their results were cited by EPA as 

constituting strong evidence of a link between short-term exposure at concentrations below the NAAQS and premature mortality. However, many questions 

remain, specifically regarding the size and significance of the ozone-mortality 

effect and the implications of the findings for ozone benefits analysis. Study 

 1

The study by Ito et al. (2005) included both a meta-analysis and a time-series analysis; results from the time-series analysis were intended to help to explain issues identified 

in the meta-analysis. 
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80 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

BOX 4-1 Definitions of Time-Series Analysis and Meta-Analysis

Time-series analysis describes and models the behavior of observations that are occurring sequentially and is analysis of the temporal relation 

between ozone and mortality data at different times. Moreover, time series 

analysis in air pollution studies is typically an approach in which daily mortality or morbidity counts are expressed as a function of covariates, including at least one indicator of air pollution in regression models, which can 

control for confounding effects of seasonality, long term trend and weather. 

The multicity time-series model has several advantages over multicity 

meta-analyses. Instead of having to rely on the different analytic approaches and assumptions used by researchers of completed studies, the 

multi-city time-series model provides the ability to use an identical model 

structure, exposure lags, control for confounders, and statistical criteria for 

data from all cities. Furthermore, the time-series model can include factors 

that explain differences in effect estimates among the cities, such as region, housing characteristics, and measurement method. 

Meta-analysis is a statistical technique used to aggregate, summarize, and review previous quantitative research. Through meta-analysis, a 

wide variety of questions can be investigated, assuming that a representative body of primary research exists. Selected parts of the reported results 

of primary studies (effect sizes or other characteristics) are analyzed as 

other data are: descriptively and then inferentially to test hypotheses. The 

appeal of meta-analysis is that it in effect combines research on a topic 

into one large study with many subjects. The danger is that in aggregating 

a large set of studies, the construct definitions can become imprecise and 

the results difficult to interpret fully (Neill 2006). Moreover, a major issue 

with meta-analysis is publication bias, which refers to the greater likelihood 

that studies with statistically significant positive results will be published as 

compared with studies reporting negative results. Thus, estimates from 

pooled meta-analysis may overestimate the association between ozone 

and mortality. 

Like multicity time-series analyses, meta-analyses use a multilevel 

model to examine pollution-effect associations. City specific estimates 

(level 2) are obtained from time series data, (level 1) for each city with a 

generalized linear model analysis. These are then pooled into a national 

average estimate using a Bayesian hierarchical model in which stages of 

the hierarchy have assumed normal distributions.

descriptions, findings, limitations, and remaining issues related to the five comprehensive analyses are presented below. 

Multicity Time-Series Studies 

Two multicity time-series studies of ozone and mortality were conducted. 

Bell et al. (2004) used the National Morbidity, Mortality, and Air Pollution 
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Study Contributions to the Estimation of Reduced Premature Mortality 81 

Study (NMMAPS) database to conduct a large time-series analysis with data 

from 95 U.S. cities over the period 1987-2000. Ito et al. 2005 conducted a timeseries study with data from seven U.S. metropolitan areas over the period 1985-

1995. 

Bell et al. (2004). As shown in Table 4-1, Bell et al. used data and methods developed for the NMMAPS study to estimate a national average relative 

rate of mortality (noninjury mortality and cardiovascular and respiratory mortality) associated with short-term average ambient ozone concentrations in 1987-

2000 in 95 large U.S. urban communities made up of almost 40% of the U.S. 

population. The 95 areas were chosen on the basis of availability of daily ozone 

data from EPA’s Aerometric Information Retrieval Service (now known as the 

Air Quality System database). Descriptive statistics on each community are provided at (iHAPSS 2005). For ozone, the 24-h average, maximum 8-h, and 

maximum hourly concentrations were calculated for each day. In several locations, ozone was measured only during the peak ozone season, April-October. A 

two-stage statistical model was used to estimate a national average association 

between short-term ambient ozone concentrations and mortality risks, accounting for weather, seasonality, long-term trends, and PM10. In the first stage, distributed-lag overdispersed Poisson regression models were used for estimating 

community-specific relative rates of mortality associated with exposure to ozone 

in the week prior to death. In the second stage, the community-specific relative 

rates were combined to generate a national average estimate of the association 

between ozone and mortality that accounts for within-community and acrosscommunity variability. 

Analyses were performed with multiple ozone-concentration metrics (1-h 

maximum, 8-h maximum, and 24-h average), which were highly correlated with 

each other; variations were most likely due to weather and sources of ozone. 

Temperature was modeled as a natural cubic spline (a type of mathematical 

function) of a day’s temperature and the average of the three previous days’ 

temperatures. Analyses were based on single-day lags and constrained and unconstrained distributed-lag models for all 95 communities, for all communities 

in warm months (April-October), and for the 55 communities on which yearly 

ozone data were available. The sensitivity of model results to choice of model, 

temperature, age (all ages and less than 65, 65-74, and over 75 years), and PM10

was also assessed. The sensitivity analysis with PM10 was limited to days for 

which PM10 and ozone data were available (1 in 6 days). 

Results showed that average short-term changes in ozone are significantly 

associated with premature mortality and that the statistical association is robust 

to adjustments for PM10, weather (temperature), and seasonality. It should be 

noted that robustness for PM10 may have been hindered by lack of daily monitoring data. Ozone-mediated risks were greater for cardiovascular and respiratory mortality than for total mortality, and effects were larger at lag 0 d than lag 

1 or 2 d. Bell et al. examined the 95 communities using a constrained distributed-lag model and found a statistically significant 0.52% (95% posterior 
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TABLE 4-1 Summaries of Recent Studies of Acute Effects of Ozone on Mortality Author Source 

Design/ Number of Studies or Cities Period 

Exposure Metrics 

Health Outcomes 

Risk (95% Confidence Interval) per 10 ppb 

Noninjury mortality 

0.52% (0.27-0.77%) 

Bell, McDermott, Zeger, Samet, and Dominici al. 

JAMA 2004; 292(19): 2372-2378 

Time-series study of 95 U.S. large urban areas 

1987-2000 Cumulative 

exposure of previous week Cardiovascular 

and respiratory mortality 

0.64% (0.31-0.98%) 

Meta-analysis of 43 studies (international) 

1990-2003 24-h average 0.8% 

(0.55 -1.0%) 

Ito, Leon, and Lippmann 

Epidemiology 2005;16(4): 446-457 

Time-series analysis of 7 U.S. cities 

1985-1995 0- and 1-d lag, 

24-h average 

Nonaccidental mortality 

0.52-1.0%a

1-h maximum 0.41% 

(0.32-0.52%) 

1-h maximum: summer; 

0.84% (0.57-1.09%) 

Levy, Chemerynski, and Sarnat 

Epidemiology 2005;16(4): 458-468 

Meta-regression of 28 time-series studies (international) 

Pre-October 2003 

1-h maximum: winter 

All-causes mortality 

-0.04% (-0.34 to 0.28%) 

Bell, Dominici, and Samet 

Epidemiology 2005;16(4): 436-445 

Meta-analysis of 39 time-series studies 

1990-June 2004 0-, 1-, and 2-d lag 

or 2-d average of lags (0, 1, and 2 d) 

Total mortality 0.87% 

(0.55-1.18%) 

aRange of risk estimates without confidence intervals.

82 
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Study Contributions to the Estimation of Reduced Premature Mortality 83 

interval: 0.27%-0.77%) increase in non-accidental mortality for a 10 ppb increase in the previous week’s daily average ozone concentration. The increase in 

cardiovascular and respiratory mortality was somewhat higher at 0.64% (95% 

PI, 0.31%-0.98%). Interestingly, Bell et al. found a lower increase in total mortality of 0.39% (95% posterior interval: 0.13%-0.65%) in those communities 

during the ozone high season (April through October). Results were similar for 

the unconstrained models. 

The mortality effect of a single day of ozone exposure appeared to be distributed over several days. The study further suggested that ozone-mortality effects can be calculated separately from PM-mortality effects because ozone risk 

estimates were robust to adjustment for PM10. Bell et al. (2007) also reported the 

95 Bayesian city-specific estimates of risk and the standard deviation of these 

city-specific estimates. The standard deviation for the constrained distributed lag 

model was 0.64%. Thus 95% of the true city-specific risk effects lie in the interval -0.73% to 1.77%. Bell at al. (2007) further investigated whether PM is a 

confounder of ozone and mortality using data for 98 U.S. urban communities 

from 1987 to 2000. They concluded that neither PM10 nor PM2.5 is a likely confounder of observed ozone and mortality relationships. They recommended that 

further investigation is needed of potential confounding of the short-term effects 

of ozone on mortality by PM chemical composition. As part of a larger study of 

ozone and mortality, Ito et al. (2005) conducted a time-series analysis with data 

from seven U.S. cities (Chicago, Detroit, Houston, Minneapolis-St Paul, New 

York City, Philadelphia, and St Louis) for the period 1985-1994 (Table 4-2). 

Those cities were chosen because of the availability of data on daily (or nearly 

daily) PM10, which went back to 1985 in most cities, and their relatively large 

populations. It was necessary to obtain daily rather than every-6th-day samples 

(the usual sampling frequency for most U.S. cities) of PM to obtain reasonable 

statistical power (Ito, personal communication, 12/04/07). In each of the cities, 

ambient ozone was measured year-round, and daily PM10 data were available for 

all cities except New York. PM2.5 data were available for selected years for 

Philadelphia (1992-1995) and St. Louis (1985-1989). Ito et al. (2005) used the 

data specifically to examine the sensitivity of ozone-mortality risk estimates to 

several factors, including season, alternative weather models and adjustments 

(of which four were examined), and confounding by PM. Results of the sensitivity analyses were intended to supplement a corresponding meta-analysis.

To characterize the ozone-PM relationships across seasons, the authors 

computed the mean ozone concentration for each quintile of PM in summer and 

winter. To examine the sensitivity of ozone-mortality risk estimates to alternative weather-model specifications and temporal adjustments, they used a Poisson 

generalized linear model that adjusted for temporal trends, day of week, and 

weather effects. The average of 0- to 1-d lagged 24-h average ozone concentration was included. A smoothing function of days using natural splines was included to adjust for seasonal cycles and other temporal trends, and various 

weather models from the literature were investigated. 
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84 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

TABLE 4-2 Summaries of Recent Time Series Studies of Acute Effects of 

Ozone on Mortality 

Authors Bell, McDermott, Zeger, 

Samet, and Dominici. 

Ito, Leon, and Lippmann 

Study design (methods) Time-series study Time-series study 

Type of model(s) Hierarchic (mixed-effects), 

distributed Lag 

Poisson generalized linear 

model 

Numbers of studies or cities 95 U.S. large urban areas 7 U.S. large urban areas 

Study periods 1987-2000 1985-1995 

Exposure level County level Metropolitan areas 

Exposure metric 24-h average 

1. Maximum 8-h average 

2. Maximum hourly 

concentration 

24-h average 

Time of study 1. April-October 

2. Whole year 

Whole year 

Health outcomes 1. Non-injury-related 

mortality 

2. Cardiovascular and 

respiratory mortality 

Total nonaccidental 

mortality 

Lag time days in days 0, 1, 2, 3, up to a week 

Adjustment for temperature Yes Yes 

Adjustment for humidity No No 

Adjustment for season Yes Yes 

Consideration of age strata Yes Yes 

Adjustment for PM10 Yes Yes 

Adjustment for PM2.5 Yes Yes 

Adjustment for other 

pollutants 

No No 

RESULTS 

Non-injury-related 

mortality (per 10-ppb 

change)

 1-h maximum 

 8-h maximum 

 24-h average 

0.39% (95% posterior 

interval, 0.13-0.65%) with 

up to a week lag (AprilOctober) 

1.0% (0 .55-1.40%) with 0-, 

1-d lag.(year-round) 

Cardiovascular and 

respiratory mortality 

(per 10-ppb change) 

 1-h maximum 

 8-h maximum 

 24-h average 

0.64% (0.31-0.98%) with 

up to a week lag 
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Study Contributions to the Estimation of Reduced Premature Mortality 85 

Results from the multicity analysis show short-term associations between 

ozone and mortality with substantial heterogeneity across cities. Pooled analysis 

for the six cities with corresponding daily PM data resulted in an all-year, 

ozone-only mortality effect estimate of 2.0% (1.1-2.9%) for the quintile model 

and 1.0% (0.0-2.0%) for the model that used four smoothing terms per 20-ppb 

increase in the average of 0- and 1-d lag 24-h ozone. When stratified by season, 

the excess risk estimates were higher in summer than in the whole year and in 

cold seasons, when the estimates were low or null. The potential confounding 

between ozone and PM did not substantially affect ozone risk estimates. 

Results further showed that the use of different weather models could account for a twofold difference in overall effects estimates (0.24-0.49%) in analyses that included yearly data, with the quintile temperature model producing the 

largest estimate and the model that used four smoothing terms producing the 

smallest. Regardless of the adjustment for weather and for PM10, PM2.5, and season, however, large city-to-city variation in ozone-associated mortality risk estimates persisted. The heterogeneity was thought to be due to corresponding 

heterogeneity in factors known to vary with city, such as air-conditioning use, 

study population, ozone, and other photochemical oxidants. 

The relationship between ozone and PM10 was characterized by a positive 

slope in summer and a negative, shallower slope in winter. The relationships 

between temperature and ozone were generally J-shaped. Smoothing for temporal trend did not generally alter the risk estimates. 

In addition to the largely U.S.-based multicity studies (Bell et al. 2004 and 

Ito et al. 2005), Gryparis et al. (2004) collected data on daily ozone concentration, daily number of deaths, confounders, and potential effect modifiers for 23 

European cities for at least three years since 1990. Effect estimates were obtained for each city with city-specific models and were then combined using 

second stage regression models. No significant effects were noted during the 

cold half of the year but for the warm season, an increase in the one hour ozone 

concentration by 10 ug/m3

 was associated with a 0.33% increase in total daily 

number of deaths. When considering the number of cardiovascular deaths, there 

was a 0.45% increase. When considering respiratory deaths, there was a 1.13% 

increase. The corresponding figures for 8-h ozone levels were similar. 

Meta-analyses 

Three meta-analyses were carried out to obtain a summary or composite 

estimate of ozone-associated mortality risks while explaining observed heterogeneity in risk estimates. The meta-analyses used different statistical techniques 

and datasets to aggregate results of multiple time-series studies of changes in 

ozone and mortality (Tables 4-1, 4-2, and 4-3). Ito et al. (2005) considered 43 

time-series studies in the U.S. and abroad that were conducted in 1990-2003. 

Levy et al. (2005) considered 48 risk estimates from 28 time-series studies 
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TABLE 4-3 Summary of Meta-analysesReference 

Number of Studies (or Cities) Areaa

Study Period 

Season of Study 

Exposure Metric Lag (d) 

Adjustment for Other Pollutants Mortality 

% Change in Daily Mortality per 10 ppb change in ozone (95% CI) 

Levy et al. 2005 

46 Inter 1973-1999 All 1-h maximum 

(4:3:2 1,8,24 conversion) 

0-2 NA All causes 0.41 

(0.31-0.51) 

27 N. Am All 1-h maximum 0-2 NA All causes 0.41 

(0.29-0.53) 

31 Inter All 1-h maximum 0 NA All causes 0.51 

(0.37-0.66) 

15 Inter All 1-h maximum 1-2 NA All causes 0.25 

(0.18-0.31) 

14 Inter Summer 1-h maximum 0-2 NA All causes 0.84 

(0.57-1.10) 

 10 Inter Winter 1-h maximum 0-2 NA All causes -0.04 

(-0.33 to 0.27) 

 23 

23 

Inter Inter 

 All 

All 

1-h maximum 1-h maximum 

0-2 0-2 

NA All causes 0.55 

(0.37-0.72) 0.31 (0.20-0.45) 

86 
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24-h average All causes, 

non-accidental 

0.80 (0.6-1.0) 

Ito et al. 2005 

43 Inter 1990-2003 Year round

Maximum 1-h average 

Up to 3 NA 

All causes, non-accidental 

0.39 (0.26-0.51) 

24-h average PM10 All causes, 

non-accidental 

0.75 (0.4-1.1) 

 15 Am 1983-1999 Year round

Maximum 1-h average 

 All causes, 

non-accidental 

N/A 

All causes, non-accidental 

0.87 (0.55-1.18) 

Cardiovascular 1.11 

(0.68-1.53) 

24-h average 

Respiratory 0.47 

(0.51-1.47) 

Maximum 8-h average 

NA 

Bell et al. 2005 

39 Various 

Maximum 1-h average 

 PM10

PM2.5

NA 

aInter = International; Am = America. 

87
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88 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

with study data from 1973 to 1999, excluding publications from NMMAPS. The 

meta-analysis conducted by Bell et al. (2005) used 144 effect estimates from 39 

time-series studies published from 1990 to June 2004, also excluding studies 

based on NMMAPS. Each of the meta-analyses examined statistical concerns 

(confounding, collinearity, and possible interaction effects) related to modeling 

of a dependent response variable. 

Ito et al. (2005). Ito et al. conducted a meta-analysis of single-city studies 

that investigated the short-term association between ozone and nonaccidental 

mortality (at all ages or over the age of 65 y). From each study, a “preselected” 

exposure lag (up to 3 d for consistency) was used in the meta-analyses to avoid 

selecting the most statistically significant lag and artificially biasing the estimate 

upward. Ozone-related changes in mortality risk were summarized by season. 

The authors conducted analyses to examine the sensitivity of the results to using 

different number of nonparametric smoothing terms in the generalized additive 

model. 

The combined random-effects estimate from the 43 studies included in the 

meta-analysis was 1.6% (95% CI, 1.1-2.0%) excess mortality per 20-ppb increase in 24-h average ozone (roughly 0.80% excess mortality per 10-ppb increase). There was large heterogeneity in ozone-mortality risk estimates across 

studies that was potentially related to city-specific factors, such as mean temperature, or model specifications. Correspondingly, seasonal differences in 

ozone-mortality estimates were found. For the 10 studies that reported ozone 

risk by season, the ozone risk estimates were typically larger in summer than in 

winter, with random-effects estimates of 2.2% (95% CI, 0.8-3.6%) and 3.5% 

(95% CI, 2.1-4.9%) per 20-ppb increase in 24-h average ozone for all year and 

the warmer season, respectively. Although adjustment for PM10 had little effect 

on the ozone-mortality association for the whole year, the study showed potential confounding of ozone effects by PM10 in the warm season. That seasonspecific confounding by PM10 or temperature might explain the reported observed negative ozone-mortality associations. 

Levy et al. (2005). Levy et al. applied an empiric Bayes metaregression to 

estimate the health effects of ozone on all-causes mortality and to assess predictors of between-study variability. Their meta-analysis included 48 city-specific 

relative-risk estimates from 28 studies conducted in North America and Europe 

and published before October 2003. In the metaregression, a hierarchic linear 

model with known level-1 variances was applied, and exposures were assessed 

with the 1-h maximum ambient ozone concentration. The meta-analysis found a 

significant overall 0.41% (95% CI, 0.32-0.52%) increase in daily mortality per 

10-ppb increase in 1-h maximum ozone concentrations; results in North American and European cities were similar. Results from the metaregression also 

demonstrated seasonal heterogeneity in ozone health effects, with a significant 

0.84% (95% CI, 0.57-1.09%) increase per 10-ppb increase in 1-h maximum 

ozone in summer and a nonsignificant -0.04% (95% CI, -0.34 to 0.28%) decrease in winter for the same increase in maximum ozone. Furthermore, results 

with the metaregression model suggested that between-study variability in 
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Study Contributions to the Estimation of Reduced Premature Mortality 89 

ozone-related mortality could be partially explained by between-study differences in exposure lag times, air-conditioning prevalence, and ozone and other 

air-pollutant relationships, with effect estimates greatest for same-day exposures, studies conducted in cities with low air-conditioning prevalence, and a 

positive association between ozone and NO2. In addition, studies using 8-h 

maximum ozone concentrations to estimate exposures had slightly lower estimates than studies using 1-h maximum or 24-h averages. 

Bell et al. (2005). Bell et al. combined 144 effect estimates (38 from the 

U.S. and 106 from outside the U.S.) from 39 time-series studies to generate a 

pooled estimate of how ozone affects mortality. Included in the meta-analysis 

were peer-reviewed time-series studies that were in English, were published and 

indexed from 1990 to June 21, 2004, provided numerical estimates and 95% 

confidence intervals or t-values of the ozone-mortality relationship (total, cardiovascular, or respiratory mortality), and were not based on NMMAPS. The 

authors combined information across locations and estimated the pooled effect 

by using a two-stage Bayesian hierarchic model. Pooled estimates were generated on the basis of exposure lags, age groups, cause-specific mortality, concentration metrics, study location (U.S. or elsewhere), and potential confounding by 

PM. Pooled estimates from the time-series studies not based on NMMAPS were 

compared with pooled estimates from NMMAPS studies. 

The meta-analysis showed that overall a 10-ppb increase in ozone in the 

few preceding days (lags of 0, 1, or 2 d or a 2-d average of lags of 0 and 1 d or 

lags of 1 and 2 d) was associated with a 0.87% (95% posterior interval, 0.55-

1.18%) increase in total mortality. The ozone-associated risk for cardiovasculardisease mortality was larger, 1.11% (95% PI, 0.68-1.53%); and that for respiratory mortality was lower and insignificant, 0.47% (95% PI, -0.51 to 1.47%). 

Findings were similar for U.S. and non-U.S. cities. The statistical association 

was robust to the type of adjustment made for PM, weather, and seasonality. 

When PM10 or PM2.5 was included in the model, for example, effect estimates 

for ozone-mediated total mortality were similar, albeit insignificant, at 0.97% 

(95% PI, 0.03-1.98%). 

Pooled estimates were similar for the meta-analysis and NMMAPS results. 

Both studies showed larger effects for cardiovascular mortality (meta-analysis) 

and cardiovascular and respiratory mortality (for NMMAPS) than for total mortality, larger effects for exposures at lag 0 d than lag 1 or 2 d, and lack of confounding by PM. However, the estimated pooled effects from the meta-analysis 

were higher than those from NMMAPS, and the difference was attributed to 

possible publication bias (see below). The authors therefore recommend caution 

in the use of single-city studies, whether individual or pooled. 

Summary of Multicity Time-Series Studies and Meta-analyses 

Each of the multicity time-series studies and meta-analyses found strong 

evidence of a statistically significant association between short-term ozone ex-
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90 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

posure and mortality, and overall effect estimates were generally similar (Figure 

4-1). Effect estimates, however, were higher for the meta-analyses, and this suggested the influence of publication bias on the ozone mortality effect estimates. 

The publication bias was attributed to the fact that meta-analyses relied solely on 

published studies, which are more likely to contain statistically significant findings of an ozone-mortality association. As a result, the pooled meta-analysis 

estimates may overstate the true ozone-mortality relationship. Moreover, inasmuch as the meta-analyses are based on individual study results rather than uniform analysis of the “raw” data from each city, it is possible that meta-analyses 

preferentially included the most significant results (obtained with different 

ozone exposure matrices and statistical models), and this, too, would result in 

higher effect estimates. % Increase in Mortality per 10 ppb Daily O3

-0.5

0.5

1.0

1.5

0.0

Thurston & Ito (01)

Levy et al. (01)

Stieb et al. (02)

Anderson et al. (04)

Bell et al. (05a)Levy et al. (05)Ito et al. (05)

Bell et al. (04)Bell et al. (06)

Gryparis et al. (04)

Schwartz (05)

L01

L0

1

L0

6

U.S.

U.S.

U.S.

Europe

U.S.

Europe

-0.5

0.5

1.0

1.5

0.0

L01

L0

1

L0

6

L01

L0

1

L0

6

U.S.

U.S.

U.S.

Europe

U.S.

Europe

% Increase in Mortality per 10 ppb Daily O3

-0.5

0.5

1.0

1.5

0.0

Thurston & Ito (01)

Levy et al. (01)

Stieb et al. (02)

Anderson et al. (04)

Bell et al. (05a)Levy et al. (05)Ito et al. (05)

Bell et al. (04)Bell et al. (06)

Gryparis et al. (04)

Schwartz (05)

L01

L0

1

L0

6

L01

L0

1

L0

6

U.S.

U.S.

U.S.

Europe

U.S.

Europe

-0.5

0.5

1.0

1.5

0.0

L01

L0

1

L0

6

L01

L0

1

L0

6

U.S.

U.S.

U.S.

Europe

U.S.

Europe

FIGURE 4-1 Percentage increase in ozone-associated mortality in meta-analyses and 

time-series studies. Results from all meta-analyses (first seven bars from left), multicity 

time-series (next three bars), and case-crossover study (last bar on right). “L06” refers to 

exposures estimated with distributed-lag models of week-long ambient ozone concentrations, “L01” to exposures estimated with average of same-day and previous-day ambient 

concentrations. Results presented in the papers were converted to the percent increase in 

mortality risk per 10 ppb increase in daily ozone levels. If both summer and yearly results 

were presented, yearly results were used. Several studies presented results as the 1-hour 

or 8-h daily maxima. To convert to the 24-hour ozone, conversion factors as noted in the 

studies were used when such values were provided. Otherwise, 1.73 was used for the 

ratio of the 1-h max to the 24-h average and 1.53 was used for the ratio of the 8-h max to 

the 24-h average, based on analysis of ozone levels at 78 U.S. cities. For studies that presented results based on μgm/m3

, the increment of ozone was converted to ppb based on 

1.96 μgm/m3

 = 1 ppb. Source: Adapted from Bell (2007) presentation to committee. Reprinted with permission from author; copyright 2007. 
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Study Contributions to the Estimation of Reduced Premature Mortality 91 

Each of the investigations found heterogeneity of risk across cities or 

counties, particularly with regard to the time-series analyses. A recent paper by 

Bell and Dominici (2008) investigated whether this heterogeneity could be explained by community specific characteristics using NMMAPS. These included 

race, income, education, urbanization, transportation use, particulate matter and 

ozone concentrations, the number of ozone monitors, weather and the use of air 

conditioning. National relative rate did not vary greatly after adjusting for community specific variables (0.46% to 0.54% increase in mortality per 10 ppb increase in the previous week’s ozone). Between-city heterogeneity in effect estimates (which is assessed in meta-analyses by using between-study variability) 

was attributed to several factors, consistently including seasonality and exposure 

lag periods. Effect estimates were generally higher in summer than in whole 

year and winter, irrespective of analysis or model choice, although Bell et al. 

(2004) found higher effects for all-year analyses compared to warm season 

analyses. Furthermore, ozone mortality effects were greater after same-day than 

after previous-day exposures in Levy et al. (2005) and Bell et al. (2004, 2005) 

and after exposures averaged over the week preceding death than after a single 

day in Bell et al. (2004). Those results suggest that ozone’s mortality effects are 

largest on the day or days immediately preceding death but cannot be explained 

fully by these exposures as they accumulate over the week. Another important 

explanatory factor was air-conditioning prevalence: effect estimates were lower 

in cities that had higher air-conditioning prevalence (Levy et al. 2005; Bell and 

Dominici 2008). 

Ozone mortality effects were generally not confounded by temperature or 

PM when year-round data were examined. However, the potential for confounding by PM was shown to vary by season: confounding was shown in summer but 

not winter by Ito et al. (2005). The seasonal confounding pattern is consistent 

with the seasonal pattern in ambient-ozone and ambient-PM associations in 

many U.S. cities. Moreover, an additional limitation of the multi-city studies is 

that they were not able to evaluate any co-pollutants for confounding other than 

PM10 and PM2.5. 

Although temperature was not shown to explain the ozone-mortality associations completely, the associations were found to be sensitive to adjustments 

for the mathematical form of temperature in models. As found by Ito et al. 

(2005), the use of more aggressive temperature-smoothing models resulted by 

itself in a 50% smaller effect estimate than other, simpler weather models. The 

effect of temperature adjustment was offered as an explanation for the observed 

doubling of the effect estimate found in the Ito et al. (2005) meta-analysis compared with Bell (2004) NMMAPS, which used four smoothing terms to adjust 

for temperature and dew point. Given those potentially large effects and the fact 

that the appropriate or best method to adjust for temperature is not known, risk 

estimates should consider uncertainties introduced by different model choices to 

account for weather. Also, care must be taken not to select the lag time with the 

largest risk estimate so as not to bias the estimate upwards. 
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92 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Chronic Studies 

Long-term effects of ozone on mortality are considered to be the result of 

cumulative effects on chronic pathologic conditions caused by repeated exposure to ozone, that is, not the consequence of exposure that occurred yesterday 

or recently but the cumulated result of conditions that develop over longer periods. These chronic conditions may lead to subclinical or clinical effects and ultimately to death. In such deaths, very recent exposure is not relevant; what matters is the long-term history of exposure that increases frailty and thus shortens 

life expectancy because of related chronic conditions. 

The standard approach to investigate such effects is the cohort study, in 

which large numbers of subjects are followed for several years. Ideally, the cumulated long-term exposure of each subject to ambient ozone is estimated. The 

cohort study accumulates time to death. If there is no effect of ozone on mortality, subjects with high long-term or lifetime exposure to ozone will have the 

same life expectancy as subjects with low ozone exposure. That is, mortality 

rates, after all other factors that might affect mortality are taken into account, are 

expected to be the same among populations that have different ozone exposure 

histories. Cohort studies use variation in ambient air-pollution concentrations 

over space to create contrasts in personal exposure, whereas time-series studies 

use variation in time. 

Chronic Ozone Exposure and Life Expectancy

Several air-pollution cohort studies have been published in North America 

and Europe. The mortality cohort studies have focused on ambient particulate 

matter or markers of local traffic to characterize exposure of the cohorts. In contrast, the assessment of the association between life expectancy and ambient 

ozone has been addressed to a much lesser extent. None of the cohort studies 

available at this time were designed to investigate chronic effects of ozone, and 

contrasts in estimated long-term exposure were rather limited. Results of the few 

cohort studies with ozone data available and that did report associations between 

long-term mean concentrations of ozone and death rates were not consistent. 

The American Cancer Society study (ACS)—the largest cohort study of 

all—and the Harvard Six City study initially found a nonsignificant negative 

association of ozone with mortality on the basis of ozone recorded year-round 

(Dockery et al. 1993; Pope et al. 1995). The Health Effects Institute (HEI) reanalysis based on cohort followup from 1982 to 1989, however, reported a significant association of the third-quarter (July-September) average daily 1-h 

maximum ozone concentration for 1980 only and % increase in cardiopulmonary mortality of 1.026 (1.003-1.051) per 10 ppb increase in ozone (Krewski et 

al. 2000). The extended analysis of the ACS cohort from 1982 to 1998 (Pope et 

al. 2002) observed increased mortality from cardiopulmonary diseases with the 

1982-1998 third-quarter average of the daily 1-h maximum ozone concentration 
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of 1.011 % increase in mortality (0.998-1.026) per 10 ppb change in ozone. A 

positive but not statistically significant relative risk was observed between ozone 

and cardiovascular events on the basis of hospital records and deaths in the subset of 28,402 women followed for an average of 6 y in the Women’s Health Initiative Observational Study (Miller et al. 2007). A negative but not statistically 

significant association with ozone risk was observed after adjustment for several 

copollutants, including PM2.5. The 15-y followup of the Adventist Health on 

Smog (AHSMOG) population showed that lung cancer was significantly associated with ozone in men (Abbey et al. 1999). For other causes of death, associations were positive but did not reach statistical significance. Those few cohort 

studies have not demonstrated a clear positive association between long-term 

average ozone concentrations and cardiopulmonary mortality after controlling 

for PM2.5 

A persistent problem in the analyses of long-term associations between 

ambient ozone and health is the characterization of exposure. Factors such as 

correlations with copollutants, the far lower concentrations of ozone indoors 

than outdoors, the relevance of ventilation rates, and the influence of timeactivity patterns—hamper characterization of the effects of long-term exposure 

to ozone. Those factors are likely sources of nonsystematic errors that are expected to lead to an underestimation of effects. 

Long-Term Effects of Ozone on Lung Function 

A relevant although indirect approach to evaluation of the evidence of 

long-term effects of pollution on life expectancy studies the effects of pollution 

on the development of lung function. Measures of lung function, such as forced 

vital capacity (FVC, the vital capacity expired during a forced spirometric test) 

or the forced expiratory volume (such as FEV1, the volume expired during the 

first second of a spirometry test), are strong predictors of life expectancy and 

correlate in particular with various chronic inflammatory cardiorespiratory diseases and related deaths. Associations between long-term exposure to ambient 

ozone and the development of lung function throughout life can provide useful 

complementary evidence about the role of ozone as a risk factor for shorter life 

expectancy. Lung function increases during childhood and adolescence and 

steadily declines with age after a few years of a plateau phase in early adulthood. Reduction in growth or accelerated decline can result in clinically relevant 

impairment of lung function which in turn strongly correlates with premature 

death. 

As in the case of mortality studies, PM-related investigations of lung function are more abundant and extensive than those dealing with ozone. However, 

some studies were either designed to or did report associations between ambient 

ozone and lung function in children. Recent relevant examples are the Southern 

California Children’s Health Study (CHS) (Gaudermann et al. 2004), the University of California, Berkeley (UCB) ozone studies (Künzli et al. 1997; Tager 
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94 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

et al. 2005), the Yale college-student study (Galizia and Kinney 1999), and a 

cohort study in Mexico City (Rojas-Martinez et al. 2007). Both lung function 

and growth correlated with ambient pollution in those investigations, but the 

specific contribution of ozone was less clearly established. 

Interpretation of findings of effects of chronic ozone exposure on mortality is complicated by an unexplained inconsistency reported in the CHS, the 

largest study, with 8 y of annual followup already published. At the beginning of 

the cohort study, elementary-school children’s lung function correlated with the 

long-term mean of the 1-h maximum ozone across 12 communities (Peters et al. 

1999). Associations were particularly pronounced with respect to small-airway 

function. That would be expected in that tissue dose of inhaled ozone is known 

to be highest in the small airways (Hu et al. 1994; Kabel et al. 1994), but the 

findings were significant only in girls and in boys who spent more time outdoors. During the cohort followup, however, lung-function growth rate showed 

significant associations with a set of urban pollutants, although findings for 

ozone were not significant and were inconsistent among age groups and measures of function (Gauderman et al. 2000, 2002, 2004). Growth rates in smallairway function were inversely (although not significantly) associated with 

ozone in the youngest cohort (Gauderman et al. 2002) but not in the 8-y followup from the age of 10y to 18 y (Gauderman et al. 2004). The comparisons 

were based on community-level assignment of exposure to ozone, that is, spatial 

differences in ozone concentrations within communities and among homes were 

not available. As emphasized by the same research group, indoor:outdoor ratios 

of ozone among houses in some of the CHS communities are very heterogeneous (Avol et al. 1998), and strong negative correlations between (measured) 

ozone and NO2 along busy roads have been reported (McConnell et al. 2006). In 

contrast to PM, indoor levels of ozone are far lower then outdoors, and the use 

of outdoor monitors to characterize ozone exposure has been shown to be far 

more challenging than in case of PM. In the main analyses of the CHS, ambient 

ozone has been measured only at the central monitor, so the negative correlations may be a serious problem in light of the association observed in the CHS 

between proximity to traffic and lung-function development (Gauderman et al. 

2007). Compared to other pollutants, the cross-community contrasts in ozone 

concentrations was smaller and the same study found rather strong effects related to organic and inorganic acids. The formation of the latter is closely tied to 

ozone photochemistry. Moreover, Gauderman et al. (2004) also showed that the 

community (mainly Long Beach) with the lowest ozone concentrations ranked 

highest for elemental carbon, which correlated strongly with lung-function 

growth. Control of such strong negative correlations between pollutants is challenging in a 12-community design and highlights the inherent difficulties faced 

in all chronic-effects studies in the assessment of personal exposure to ambient 

ozone. As discussed elsewhere in this report, one may need an individual-level 

rather than community-level characterization of exposure to ozone. 

Several cohort studies—including those with UCB students (Künzli et al. 

1997; Tager et al. 2005) and Yale freshmen (Galizia and Kinney 1999) men-
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Study Contributions to the Estimation of Reduced Premature Mortality 95 

tioned above—assigned individual ozone exposures for each study subject. Results of the studies suggest adverse long-term effects of ozone on lung function, 

which were robust in multipollutant models and among studies. The finding of 

the first UCB pilot study (Künzli et al. 1997), for example, was fully confirmed 

in a second investigation (Tager et al. 2005) with a larger sample that showed 

lifetime home outdoor ozone exposures significantly associated with smallairway function. The studies were cross-sectional, so their findings can be compared only with the cross-sectional (partly positive) findings of the CHS mentioned above (Peters et al. 1999). 

Correspondingly, a recent followup study of a Mexican cohort of children 

(Rojas-Martinez et al. 2007) reported significant associations of ozone with lung 

growth, and adjustment for copollutants did not remove these associations. Each 

child lived within 2 km of a monitoring station. The stations were placed at the 

schools and so captured the ambient conditions during school hours and in particular exposure during times spent outdoors at school. The study was based on 

36 clusters of children who shared schools and residential neighborhoods and 

thus had similar exposures (Rojas-Martinez et al. 2007). 

Ihorst et al. (2004) repeated lung-function measurements twice a year for 

3.5 y in 2,153 schoolchildren in 15 towns in Germany and Austria. They concluded that ozone may be related to seasonal changes in functional growth. No 

effects were detectable if the measurements were integrated over the entire 3.5 y 

of followup. The latter finding may be due to partial reversal of acute seasonal 

ozone-mediated effects on lung capacity, as described in chamber studies, but it 

is also of note that contrasts in the long-term concentrations of ozone were 

rather small among the towns. 

Effects of ozone on adult lung function have been poorly investigated in 

epidemiologic studies. Recent studies had insufficient ranges of ambient ozone 

concentrations or did not use ambient ozone data at all. In a study conducted 

more then 20 y ago in the Los Angeles area, both lung function and its decline 

correlated with oxidant pollutants (Detels et al. 1987; Tashkin et al. 1994). 

However, although the findings were suggestive, firm conclusions could not be 

drawn, given that the comparison relied on only three Southern California communities; it was impossible to disentangle effects of various components of the 

pollution or of community-specific confounders from those expected to be due 

to ozone. 

According to animal studies, adverse effects of long-term exposure to 

ozone on pulmonary function are biologically plausible. As discussed previously, chronic ozone exposure results in the formation of fewer airways, hyperplasia of bronchial epithelium, increased mucous cells, and shifts in airway 

smooth-muscle orientation and abundance, all of which increase airway hyperreactivity in monkeys. Lung-function decreases are both a direct result of those 

effects and a secondary result of the increase in insults that the lungs will experience because of increased susceptibility to infection and exacerbation of 

respiratory problems later in life. 
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96 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

It should be noted that an indirect argument for plausibility in this context 

leaves open the possibility for impaired lung function being only a marker of 

poor health rather than a definite step in the biologic pathway of chronic effects 

of ozone. Another possibility is that ozone could affect mortality without any 

effects on lung function. However, chronic subclinical systemic inflammation 

due to ozone may well contribute to damages in the lung or the vascular system 

of the lung, resulting in lower lung function, which is a typical feature of many 

chronic inflammatory diseases. Thus, the indirect argument for coherence linking chronic effects on lung function with long-term effects on life expectancy 

has some appeal despite not being stringent proof. Unfortunately, as discussed 

below, neither chronic effects on lung function nor on mortality are as well and 

consistently established in ozone studies as they are for urban air pollution 

marked with ambient particulate matter due the lack of studies designed for the 

purpose to understand chronic effects of ozone. 

Summary of Chronic Effects

Some inconsistencies remain to be clarified in the epidemiologic findings 

regarding ozone’s effects on lung function during childhood and adolescence, 

but the observed associations between ozone and small-airway function should 

not be downplayed. Ozone tissue dose is highest in the small airways, so the 

findings are in line with expected ozone-related pathophysiologic conditions that 

result in reduced lung function. The evidence of an effect of long-term exposure 

to ozone on lung-function growth increases the plausibility of an effect of the 

same exposure on mortality. The association between poor lung function and 

reduced life expectancy is strong and well established. 

SUSCEPTIBILITY 

It is well accepted that susceptibility to adverse effects of environmental 

exposures depend on endogenous factors (such as sex, age, and genes) and exogenous factors (such as diet, physical activity, and time spent outdoors). Such 

co-determinants of a person’s response to ozone would lead to either attenuation 

or amplification of the effects. Exposure to increased concentrations of ozone 

has been shown to be associated with adverse health effects in some seemingly 

healthy individuals, as well as in individuals who are members of susceptible 

groups, including asthmatics (Romieu et al. 1997; Bernstein et al. 2004; Finkelstein and Johnston 2004; Maynard 2004; Wilson et al. 2004; McCunney 2005; 

Trasande and Thurston 2005). Studies have estimated that about 30 to 50% of 

the population may experience measurable adverse effects after short-term exposure to ozone at concentrations such as about 100 to 200 ppb (McDonnell 

1991; Corradi et al. 2002; Arjomandi et al. 2005). Observations of different responses suggest that individual host factors, are likely to be important determinants of adverse health effects associated with ozone exposure (Kleeberger 
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Study Contributions to the Estimation of Reduced Premature Mortality 97 

1995; Drazen and Beier 1997; Arjomandi et al. 2005; Kleeberger 2005; McCunney 2005). 

Although susceptibility varies among people, questions remain about the 

factors that make people more or less susceptible. Answers to those questions 

would be helpful in the evaluation of risks. 

As summarized below, it is recognized that host factors regulate the biologic and physiologic responses to ambient ozone in rodents (Kleeberger et al. 

1997; Savov et al. 2004) and humans (Weinmann et al. 1995; Balmes et al. 

1996). Studies have focused mainly on acute rather then chronic effects of 

ozone, but modifiers of acute effects may to some extent be markers of susceptibility to chronic effects, given that some chronic pathologic conditions may be 

the cumulated results of repeated acute effects. The following discussion of factors in the susceptibility to acute effects of ozone may therefore be of broader 

relevance. 

Age 

Whether age modifies the effect of ozone has not been extensively investigated. Studies that have addressed the issue have suggested lower relative risks 

in the young. Because of the much higher baseline risk of death in the elderly, 

the absolute contribution of ozone may be substantially larger in them. The 

NMMAPS analyses of Bell et al. (2004) reported larger effects in people 65-74 

y old (0.7% change per 10-ppb increase in the previous week’s ozone concentration) than in younger and older people (about 0.5%). Medina-Ramon and 

Schwartz (in press) reported that individuals greater than 65 y old presented an 

additional increase in mortality as compared to younger individuals. Normal 

growth during adolescence and aging of the adult lung are suggested as host 

factors that moderate the functional changes induced by ozone exposure. A 

normal physiologic aspect of growth and aging is a predictable increase followed by a decline in lung function. In laboratory-based studies designed to 

evaluate age as an important variable in response to ozone exposure, two investigations (Drechsler-Parks et al. 1987; Reisenauer et al. 1988) demonstrated a 

reduced acute functional response (such as FEV1) to ozone in subjects over 40 y 

old. However, the decline in the functional response with age does not necessarily imply that effects of ozone on mortality would follow the same pattern, inasmuch as different pathophysiologic pathways may play a role. The negative 

correlation between functional response to ozone exposure and age may be in 

part attributable to the beneficial role of the mucous lining of the conducting 

airways in lung defense against irritant gases (Emmons and Foster 1991). 

It is important to note that early exposure to ozone may have effects over 

the life span of a person. Recent studies have demonstrated ozone’s substantial 

impact on a variety of respiratory conditions in children, including the genesis of 

asthma in young people (McConnell et al. 2002), which may have later effects 

on health and pollution-mediated responses. Furthermore, the response to ozone 
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98 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

in children is clearly different from that in adults. Children spend more time 

outdoors, where ozone concentrations are highest, and have higher levels of activity, which contribute to greater ventilatory rates relative to body mass than 

observed in adults; these factors logically are associated with greater ozone 

doses in children than in adults. Those conditions, coupled with the fact that 

children have an immature immune system and are in the process of developing 

the capacity to metabolize a wide variety of xenobiotic compounds, accentuate 

their susceptibility to environmental injury. 

Studies conducted in nonhuman primate neonates (rhesus monkeys) have 

demonstrated that early exposure to ozone is associated with a substantial reduction in airway formation and morphogenesis that results in the formation of 

fewer airways, hyperplasia of bronchial epithelium, increased mucous cells, and 

shifts in airway smooth-muscle orientation and abundance, all of which increase 

airway hyperreactivity (Joad et al. 2006; Fanucchi et al. 2006). Other alterations 

in postnatal lung development include interrupted differentiation of airway 

basement membranes, modified airway epithelial nerve-fiber distribution, and 

reorganization of the airway vascular and immune systems (Kajekar et al. 2007; 

Plopper et al. 2007). Such alterations in early life can have lasting consequences, 

such as increased susceptibility to infection, respiratory compromise, and exacerbation of insults to the lungs later in life. 

Sex and Ethnic Background 

Epidemiologic studies of the acute effects of ozone on mortality have not 

paid much attention to sex or ethnicity as modifiers of effects. Medina-Ramon 

and Schwartz (in press) report that blacks are more susceptible to ozone associated mortality than non-blacks, and females are more susceptible than men. The 

laboratory-based studies mentioned above (Drechsler-Parks et al. 1987; 

Reisenauer et al. 1988) have demonstrated not only a reduced functional response (such as FEV1) to ozone in the elderly but a larger response in female 

subjects than in males. In both studies, the effective ozone exposure dose (the 

product of concentration, duration of exposure, and minute ventilation) inhaled 

by the female subjects was lower than that inhaled by the males. It seems that 

older, even postmenopausal women are selectively more responsive to ozone 

exposure than age-matched men: the reasons for the difference remain unknown, 

but there may be interactions between hormonal factors and mortality. That has 

not been specifically investigated. 

In laboratory-based studies (Seal et al. 1993) designed specifically to 

evaluate ozone-mediated responses by race and sex, the pattern of response was 

not significantly different among four sex-race groups (male and female, white, 

and black). Changes in FEV1, airway resistance, and cough in response to ozone 

at various concentrations (1, 120, 180, 240, 300, and 400 ppb) were compared; a 

significant decrease in FEV1 was observed after exposure to ozone at each concentration. When the FEV1 responses were collapsed across all ozone concentra-
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tions and subjected to multiple comparison analysis, it was found that black men 

and black women had significantly larger decrements in FEV1 than white men 

and that black men had significantly larger decrements than white women. The 

interrelation between acute functional response and acute risk of death was not 

established. 

Pre-existing Diseases 

For biologic reasons, it is plausible that pre-existing morbidity can modify 

the effects of exposure to ozone.2

 For example, a subject in the critical phase of 

a bout of pneumonia will have lower capacity to deal with additional exogenous 

stressors than will a healthy person. However, formal tests of interactions of 

ozone exposure with pre-existing conditions are not much published yet for 

ozone effects on mortality. Bell et al. 2004 observed similar effects for total 

mortality and death from cardiorespiratory causes. Medina-Ramon and Schwartz 

(in press) reported that among a range of chronic diseases considered to modify 

the mortality effect of ozone exposure, only atrial fibrillations showed significantly stronger associations with ozone. The additional percent increase in mortality risk per 10 ppb change in ozone was 1.66% (0.03, 3.32). Diabetes, stroke 

and other conditions did not modify the association. Although effects were also 

1.35% larger per 10 ppb change in ozone among those with asthma listed as the 

second cause of death, this modification was not statistically significant (-0.31, 

3.03). 

The preliminary findings of mortality studies are supported by ozone studies that used outcomes other than death, such as those reporting an increase in 

asthma hospitalizations during days with high ozone concentrations. Subjects 

with respiratory diseases (such as asthma) and those prone to cardiovascular 

death (such as those with atherosclerotic plaque) may be considered “susceptible.” 

Genetic Susceptibility

Functional differences in the genes that play a role in the pathogenesis of 

the adverse effects of ozone are the primary candidates for gene-ozone interactions. Several studies, summarized next, confirm that concept. The issue has not 

been addressed with respect to acute effects of ozone on mortality. 

Results from both animal and human studies support a role of genetic susceptibility in modulating ozone-induced lung inflammation and other pathologic 

effects and suggest important roles for genes associated with both oxidative 

stress and innate immunity (reviewed in Backus-Hazzard et al. 2004). In humans, genes associated with oxidative stress, redox balance, and innate immu-

 2

The concept of pre-existing diseases or frailty does not imply that susceptible people 

are necessarily very ill and destined to die soon. 
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100 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

nity have been examined for associations between genetic polymorphisms, oxidant exposure, and adverse respiratory outcomes. Several of those studied are 

related to oxidative stress and redox balance, for example, glutathione Stransferase M1 (GSTM1), glutathione S-transferase P1 (GSTP1), nicotinamide 

adenosine dinucleotide (phosphate) reduced: quinone oxidoreductase (NQO1), 

glutathione peroxidase-1 (GPX1), glutathione reductase (GR), and superoxide 

dismutase-2 (SOD2). 

The GSTM1 null and NQO1 wild-type (NQO1wt) variants have shown interesting results. In studies in Italy, Bergamaschi et al. (2001) reported small 

decrements in both FEV1 (about 3%) and peak expiratory flow (PEF) (about 

9%) in 24 healthy subjects with GSTM1 null and NQO1wt genotypes after a 2-h 

outdoor bike ride when ambient ozone was over 0.080 ppm. Functional changes 

were associated with small increases in serum CC16 (interpreted as reflecting an 

increase in epithelial permeability). In a later laboratory-exposure study using 

similar ozone concentrations, Corradi et al. (2002) reported increased exhaledbreath condensate (EBC) 8-isoprostane, leukotriene B4 (LT-B4), and thiobarbituric acid-reacting substances (TBARs) in 22 healthy nonsmoking subjects in 

the same genetic groups (GSTM1 null and NQO1wt) after 2 h of intermittent 

exercise. 

With respect to responses to ozone in the presence of both airway disease 

and genetic factors, Romieu and colleagues have observed asthmatic children 

exposed to high ambient ozone concentrations in Mexico City (Romieu et al. 

2002, 2004; David et al. 2003). In about 150 asthmatic children, both decrements in forced expiratory flow rate at 25-50% lung volume (FEF25-75) (5.2% 

decrease per 0.05-ppm increase in ozone concentration) (Romieu et al. 2004) 

and increased breathing difficulties (8% increase per 0.020-ppm increase in the 

ozone 1-h daily maximum averaged over 7 d) were found in GSTM1 null asthmatics; similar deficits in lung function growth were reported earlier by 

Gilliland et al. (2002) for asthmatic children who were homozygous for the 

GSTP1val 105 allele. In a case-control study of 218 case-parent triads, David et 

al. (2003) observed that among GSTM1 null children with high ozone exposure 

in Mexico City the children who were NQO1ser187ser homozygotes appeared 

to be protected from the development of asthma compared with 

NQO1pro187pro homozygotes. The finding of an interaction of ozone effects 

with those genes supports the notion that oxidative stress is a relevant pathway 

of action. 

Socioeconomic Status and Other Factors

Socioeconomic status (SES) may be a marker of a variety of factors that 

modify the effects of ozone. Modification of effects by SES has been investigated in the case of urban PM pollution rather than ozone. There is a high correlation between SES—including diet and the intake of antioxidants, physical activity, time spent outdoors, strenuous work-related outdoor work, the use of air 
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Study Contributions to the Estimation of Reduced Premature Mortality 101 

conditioning, stress, and exposure to environmental copollutants—and various 

health-relevant (both adverse and protective) effects (O’Neil et al. 2003). 

The intervention study of Romieu et al. (2004) supplied antioxidants during a “treatment” period. The intervention period resulted in lower effects of 

ozone on lung function than in periods of supplementation with placebo. The 

protective effect of antioxidants was particularly strong in those genetically deficient in the ability to oppose oxidative stress (Romieu et al. 2008). 

Relevance of Susceptibility to the Interpretation of Mortality Studies

The fact that occurrence or degree of adverse effects of ozone depends on 

other host factors has important ramifications in the interpretation of epidemiologic findings. It is relevant for risk assessors and policy-makers. The few studies summarized above lead to the preliminary conclusion that the effects of 

ozone on acute death rates are likely to be larger in those with pre-existing 

pathologic conditions and the list of plausible candidates modifying effects is 

rather long, although poorly investigated at this point in time (see above). Although the role of genes has not been investigated for mortality, they undoubtedly play an important role as modifiers of various pathways involved in premature mortality. Interactions among combinations of all those factors have not 

been investigated. Although some susceptibility factors may explain heterogeneity in effects only within populations, other marker of susceptibility may very 

across cities, thus partly explain heterogeneity in ozone effects observed between cities such as, for example, the use of air conditioning (Zanobetti and 

Schwartz 2008). Medina-Ramon and Schwartz (in press) reported that susceptibility factors had a larger effect in cities with lower ozone concentrations. For 

instance, the additional increase in ozone-related mortality for the elderly was 

1.48% (0.81, 2.15) in a city with a mean ozone concentration of 42 ppb versus 

0.45% (-0.27, 1.19) in a city with a level of 51 ppb. 

One can infer that the occurrence of effects depends on subjects’ susceptibility profile, which consists of a wide range and combination of single factors. 

“Susceptibility” is most likely not a dichotomous trait but a dynamic characteristic that follows a wide distribution in the population, from no to high susceptibility. Given the involvement of various complex mechanisms, susceptibility may 

be outcome-specific or pathway-specific. The level of susceptibility of any subject at any time may depend on the joint distribution of various exogenous and 

endogenous determinants of susceptibility (and their interactions) and may 

change over time. Another view of or consequence of the variation in susceptibility is that the dose (or the ambient concentrations) necessary to trigger an 

event (death in this case) and the time between exposure and event must follow 

some distribution among people. 

The observable association between ozone and mortality thus reflects the 

weighted average of all true (unobservable) individual concentration-response 

functions. The latter cannot be established, but the risk of dying because of a 10-
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102 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

ppb increase in ozone concentrations is likely to be substantially larger among 

the most susceptible population. 

We emphasize that the concept of “frailty” discussed later in this chapter 

in the section on short-term mortality displacement can be seen as a complementary way of describing aspects of “susceptibility.” Very short displacement of 

death (or “harvesting”) may reflect the most extreme tail in the continuum of 

losing just a few days of life due to ozone exposure versus the loss of months or 

years at the other end of the distribution. Those carrying the worst combination 

of susceptibility factors at any point in time may be viewed as the faction in the 

population with the highest frailty and the shortest remaining life expectancy. 

While “heavily diseased” people may belong to the “frailty pool,” “high 

susceptibility” or “high frailty” may as well be a clinically silent condition of an 

apparently “healthy” subject. For example, substantial evidence supports the 

notion that pollutants such as urban particulate matter or diesel exhaust activate 

an array of partly interrelated mechanisms that are all involved in triggering 

myocardial infarction (MI) and arrhythmia (Brook et al. 2004; Mills et al 2007). 

Subjects prone to suffer an MI or arrhythmia would belong to the pool of “frail” 

(or susceptible) subjects, but many of those who suffer lethal or nonlethal MI or 

arrhythmia would not be considered “heavily diseased” until the occurrence of 

the first event (the MI or arrhythmia), because often the underlying pathologic 

condition, such as atherosclerosis, is silent. Thus, being susceptible does not 

mean being severely ill. It is also likely that frailty varies in any person because 

although acute illness (such as pneumonia) might put a person in the pool of 

those susceptible to death from ozone exposure, if the person survives and recovers the frailty would be decreased. 

Although susceptibility factors certainly matter, the distribution of the 

ozone-mortality effect estimates across the categories of susceptibility is not 

known; that is, the quantitative details of the heterogeneity of effects are not 

readily available. Therefore, the overall (population-weighted average) effect in 

the total population is the only currently scientifically supportable entity to use 

in risk assessment. Its use is appropriate, even though the population-weighted 

mean effect may not be a valid estimate for any specific sub-population, because 

the ‘true’ effect may be much larger among the susceptible individuals but much 

smaller or zero among the less susceptible. To determine the change in risk associated with changes in ambient ozone concentrations for a specific location, 

the estimated posterior distribution of the city-specific ozone-mortality risks 

should be reported, including the mean and standard deviation of the distribution, and the Bayesian shrunk city-specific risks. 

OTHER FACTORS THAT AFFECT INTERPRETATION OF 

OZONE MORTALITY EFFECTS 

Errors in Exposure Estimates

The use of daily, 1-h maximum, or 8-h maximum ambient concentrations 
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to estimate exposure in ozone-mortality studies clearly results in error. Results 

of exposure studies suggest that the error is large, with consistently weak (and 

often insignificant) associations found between 24-h ambient ozone concentrations and corresponding personal exposures and with personal exposure concentrations at or below the measurement limit of detection. As discussed in Chapter 

3, those weak associations (based on the results of exposure studies relying 

mainly on passive ozone monitors) are attributed primarily to people’s spending 

most of their time indoors, where ozone concentrations tend to be low and uncorrelated with outdoor concentrations. For ozone-mortality studies, which are 

time-series and case-crossover in design, the use of 24-h ambient concentrations 

to estimate exposures will result in reduced power to examine associations between ozone exposure and mortality (Carroll et al. 1995; Zeger et al. 2000) and 

can lead to bias in estimates of ozone mortality effects (Zeger et al. 2000). 

The magnitude of exposure errors probably depends on several factors, including season, home ventilation characteristics, and exposure averaging time. 

Ozone’s mortality effects, for example, were shown to be greater in the warm 

season than in winter or the entire year (Ito et al. 2005; Levy et al. 2005). 

Greater ozone effects in the warm months are consistent with people’s spending 

more time outdoors and tending to live in homes that have better ventilation in 

the warm months. As evidenced by results of exposure studies, both those factors should lead to stronger 24-h ambient-personal associations, and thus lower 

exposure error, in the warm seasons, through increased contributions of ambient 

ozone to personal exposures and through greater infiltration of ozone from outdoor to indoor environments, respectively. Those factors may also result in effective doses that vary by season, for example, because of differential physicalactivity patterns and breathing rates, which would result in seasonal differences 

in exposure error. The seasonal differences may be mitigated by behavior patterns that are modified by air-quality alerts, which lead people to spend more 

time indoors on high-ozone days. The effect of behavior during ozone airquality alerts warrants further examination, as discussed in Chapter 3. 

The importance of season and ventilation has been further shown by Levy 

et al. (2005), who provided preliminary evidence of decreasing city-specific 

ozone mortality effects with increasing prevalence of central air conditioning, 

presumably because of weaker personal-ambient ozone associations and thus 

greater exposure error in homes with air-conditioning use. Further support is 

provided by Ito et al. (2005), who found mean city-specific temperature to be 

negatively associated with corresponding city-specific ozone-mortality risk estimates, possibly because of the influence of air-conditioning prevalence in the 

cities. Those findings suggest that error due to the use of 24-h ambient concentrations as the exposure metric is greater in winter than in summer, and this offers a potential explanation of the lower ozone mortality effects in cold seasons 

than in warm seasons. 

Even in the warm months in non-air-conditioned homes, when exposure 

errors are lower, it probably remains a concern for health studies and their interpretation. As discussed in Chapter 3, when 24-h ambient concentrations are sig-
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104 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

nificantly related to 24-h personal ozone exposures, the slope of their association 

remains small and substantially lower than those found for PM2.5 and sulfate 

(Sarnat et al. 2000; Sarnat et al. 2006). The low slopes may raise questions about 

biologic plausibility. Taken at face value, they suggest that some minute change 

in the true (unknown) 24-h mean exposure to ozone of only 1 ppb or a few parts 

per billion could cause death. That appears hard to accept, but other interpretations of the studies may lead to less paradoxical conclusions. 

Given the observed consistency in ozone-mortality findings and the low 

24-h personal-ambient ozone associations, it is possible that 24-h ambient ozone 

concentrations are representative not to 24-h personal ozone exposures, but to 

some correlated toxic agent or agents. These correlated toxic agent(s) could include photochemical pollutant mixtures, ozone byproducts, or ozone exposure of 

shorter or longer duration. For exposures of shorter duration, for example it is 

well established that 24-h ambient concentrations are strongly correlated with 1-

h and 8-h maximum ambient concentrations. 

Although it has not been much studied, it is also possible that maximum 

ambient ozone concentrations averaged over 1-h or 8-h are better proxies (with 

respect to both strength and magnitude of association) of corresponding 1-h and 

8-h ozone exposures than 24-h ambient concentrations and exposures. In a 

scripted-exposure study using a trained technician, for example, 1-h ambient 

concentrations were strong proxies of corresponding personal exposures when 

the technician spent the hour outdoors. During the time outdoors, 1-h ambient 

ozone concentrations explained most of the variability in personal exposures and 

were about equal to personal exposures (Chang et al. 2000). 

The generalizability of those study findings to at-risk populations, such as 

the elderly, after their typical activities is not known and warrants future study. 

People are outdoors primarily when maximum 1-h and 8-h ozone concentrations 

occur in the afternoon, so it is possible that ozone-mortality studies are reflecting maximum ozone exposures averaged over 1 h or 8 h rather than the daily 

ambient ozone concentration. Given the high correlation between these ambient 

short-term concentrations and the 24-h mean associations, use of the 24-h concentrations in time-series studies may serve as an equally good proxy for peak 

exposures. If so, the differences in the true (unknown) day-to-day peak exposure 

may indeed be far more than 1 ppb or a few parts per billion and reach some 20-

40 ppb. Such an interpretation would resolve the apparent paradox of a few parts 

per billion causing death. 

Confounding

Co-linearity among ambient pollutants raises concerns about possible confounding of ozone mortality effects by correlated co-pollutants, such as PM2.5 

(and its components), NO2, and SO2. This concern centers upon the possibility 

that ambient effects associated with ozone concentrations may represent not 

only consequences of ozone but also of correlated pollutants not included in the 
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health effects model. This possibility is critical to address, as our understanding 

of confounding is central to our ability to ascertain the effects of ozone on mortality and any benefits that will result from ozone control. Of the possible confounders, ambient PM2.5 its components, and weather have raised the most concerns about confounding. This concern results from several factors, including 

the strong correlation of ambient ozone with temperature and ambient PM2.5 as 

well as between mortality and both temperature and ambient PM2.5. For PM2.5, 

concerns over confounding also arise from the relatively weak association between personal and ambient ozone, especially in relation to the much stronger 

association between personal and ambient PM2.5. As noted in Chapter 3, relations between ambient ozone, temperature and ambient PM2.5 vary substantially 

by season and geographical location, suggesting that the potential impact of confounding must also be considered by season and location. Also, as noted in 

Chapter 3, the association between ozone and PM2.5 components is less well 

understood, in particular as to how this association varies by location, season, 

and component and how it differs for ambient concentrations and actual personal exposures. 

Even with these seasonal and geographical considerations, controlling for 

confounding in ozone mortality studies is a considerable challenge. To date, 

ozone mortality studies generally have addressed confounding by weather (generally temperature and/or dew point) using a variety of approaches, including 

those based on indicator variables, linear terms, V-shaped linear terms, and nonlinear smooth terms. The ability of these approaches to control for confounding 

and their corresponding impact on ozone mortality risk estimates have been 

shown to differ. In a reanalysis of data from seven cities, for example, Ito et al. 

(2005) examined the impact of control for weather using four approaches (quintile indicator variables, V-shaped linear terms, and two combinations of nonlinear smooth terms) and showed that overall ozone mortality risk estimates differed by as much as 100% when different approaches were used to control for 

weather. Models using indicator variables had the highest risk estimates, while 

models with four non-linear terms had the lowest estimates. Further, the model 

with the four non-linear terms had the best statistical fit but also the greatest 

concurvity with ozone, suggesting that ozone and temperature effects from these 

models are the most difficult to separate. Consistent with these findings, Levy et 

al. (2005) (using a meta-analytic approach) found that studies with non-linear 

temperature terms had higher ozone mortality effect estimates than studies using 

linear terms, although results were limited by the fact that only a small fraction 

of the examined studies used linear terms. Despite non-linear terms having the 

lowest effect estimates, Levy et al. (2005) and Ito et al. (2005) are consistent in 

that the ozone risk was influenced by the manner in which temperature was 

modeled. Implications of these findings to other ozone mortality studies are not 

known. At a minimum, the observed large impact of model choices on ozone 

mortality risk estimates suggests that control for weather is an important source 

of uncertainty in ozone mortality risk estimates. 
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106 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

To address uncertainties based on model choices, Schwartz (2004) examined ozone mortality effects in 14 cities using a case-crossover approach, which 

controlled for temperature mainly by matching control days with the temperature on the day of death. Using this approach, Schwartz showed a significant 

overall effect of ambient ozone on mortality that was greater in warm as compared to cold seasons, with these effects relatively unchanged when control days 

were matched on temperature. Similar effects when control days were matched 

or unmatched on temperature suggest that observed ozone mortality effects are 

not due to confounding by weather. However, these findings need to be replicated in additional studies. Further research examining the potential for confounding by weather and the impact of methods used to control for this confounding are clearly needed. 

For PM2.5, ozone mortality studies have addressed concerns about confounding focusing on PM2.5 as mainly as a whole (and not its components). The 

potential for confounding has been examined using multiple pollutant models, 

showing for example that yearly ozone mortality estimates are robust to adjustment for ambient particles and suggesting that confounding of ozone mortality 

effects by ambient particles is not substantial (Bell et al. 2007). Interpretation of 

the findings from these multi-pollutant models, however, is complex. For example, the use of two-stage regressions (as was used in the ozone meta-analyses) to 

examine confounding by correlated pollutants have raised statistical concerns 

about the potential for misleading results (Marcus and Kegler 2001). Further, 

measurement error can differ substantially by pollutant, raising further issues 

regarding interpretability of findings. Franklin and Schwartz (2008) found a 

0.89% (95% CI: 0.45%, 1.33%) increase in non-accidental mortality with a 10 

ppb increase in same-day 24-h summertime ozone across the 18 communities. 

After adjustment for PM2.5 mass or nitrate this estimate decreased slightly but 

when adjusted for particle sulfate, the estimate was substantially reduced to 

0.58% (95% CI: -0.33%, 1.49%). The authors concluded that the association 

between ozone and mortality is confounded by particle sulfate, suggesting that 

some PM components could be responsible for part of the observed ozone mortality effect. 

Interpretation of multi-pollutant results is further complicated by the 

strong correlations among the ambient pollutants, which make their associations 

with health effects difficult to separate. For multi-pollutant analyses based on 

yearly rather than seasonal data, this separation is particularly difficult, given the 

seasonal variability in ambient pollution relationships (see Chapter 3). Further, 

correlations with ambient ozone in the eastern U.S. generally are strongly positive in the summer but weak or negative in the winter. Evidence from Ito et al. 

(2005), which examined associations for seven cities located primarily in the 

eastern U.S., suggests that this seasonal variability in ambient pollutant correlations is important, as ozone mortality estimates for the warm and cold seasons 

were lower and were more similar by season when measured ambient fine particles were included in the season-specific models. Since the relation between 

ambient ozone and ambient PM2.5 differ substantially by season and location, the 
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observed similar warm and cold season associations suggest observed ozone 

mortality effects in the eastern U.S. were not due to confounding by ambient 

particles. The observed seasonal differences demonstrates the importance and 

need for season-specific analyses to examine potential confounding of ozone 

mortality effects by PM2.5 and other pollutants. These types of analyses should 

be repeated for other regions of the United States. 

The implications of findings based on multipollutant ambient concentrations for actual exposures and their impact on ozone mortality estimates is not 

clear. When ambient ozone and PM2.5 concentrations are included in the same 

model, they are assumed to be proxies of their own exposures. However, results 

from exposure studies suggest that this assumption may not be valid in some 

geographic areas, as 24-h ambient ozone concentrations in the eastern U.S. have 

been shown to be better measures of exposures to PM2.5 than to ozone (Sarnat et 

al. 2001), while 24-h ambient PM2.5 concentrations have been related to personal 

exposures to ozone in addition to PM2.5. These findings from the U.S. East Coast 

may suggest that ambient ozone and ambient PM2.5 are serving as proxies for the 

same pollutant or pollutant mixtures, although results are somewhat limited by 

the fact that 24-h personal ozone exposures measured in these studies are often 

near or below the method limit of detection. Despite this, 24-h personal ozone 

exposures have been shown to be poorly correlated with corresponding personal 

PM2.5 exposures, suggesting that if ozone mortality studies were to include more 

direct measures of ozone and PM2.5 exposures, issues related to confounding of 

ozone mortality effects by PM2.5 may be better resolved—at least for the assessment of daily exposure periods. For shorter exposure averaging periods, 

confounding of ozone mortality effects by PM2.5 may still be possible, as 1-h 

personal ozone and PM2.5 exposures were strongly correlated in one study when 

the technician was outdoors and away from roads (Chang et al. 2000). Whether 

exposure study results from the East Coast and for PM2.5 can be generalized to 

other locations and to specific PM2.5 components, respectively, is of yet unknown. 

Air-Pollutant Mixtures 

Results of toxicologic studies provide conflicting evidence on whether the 

mortality risks posed by ozone differ in the presence of other air-pollutant exposures. Follinsbee and coauthors (1981) have shown in young healthy subjects 

that exposure to a gas-phase mixture of ozone and NO2 induced about the same 

degree of pulmonary-function decrease and breathing-pattern changes as were 

observed previously in a separate dataset on subjects exposed to ozone alone 

(Follinsbee et al. 1977). 

In contrast, a mixture of ozone and NO2 was found to elicit greater pulmonary-function decrements in both older (about 50-75 y old) and younger subjects 

than ozone alone (Drechsler-Parks et al. 1987, 1989). Older subjects were less 

responsive than younger subjects, but both cohorts exhibited a fairly broad range 
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108 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

of pulmonary-function changes. Exposure to the mixture, but not exposure to the 

individual pollutants, led to decreases in the older subjects in stroke volume, 

heart rate, and cardiac output during exercise periods of the exposure. That observation suggests not only that exercise performance may be limited by exposure to the pollutant gases as a mixture but that it may put people with preexisting cardiovascular disease at increased risk of exacerbation of their disease. 

Cardiac-function was not studied in the younger cohort. Healthy adults (56-85 y 

old) showed significantly smaller exercise-induced cardiac output with exposure 

to the combination of nitrogen dioxide (NO2) + ozone than with exposure to 

ozone or filtered air alone (Drechsler-Parks 1995). Also, as discussed earlier in 

this chapter, Levy et al. (2005) found the estimates of ozone-mortality effects 

estimates were higher where there was a positive correlation between ozone and 

NO2. 

Controlled exposure to mixtures has also been evaluated in susceptible 

populations. For example, exposure of mild atopic asthmatics for 3 h to ozone at 

200 ppb, NO2 at 400 ppb, or a combination of the two pollutants significantly 

increased sensitivity to inhaled allergen compared with exposure to air, without 

additive effects. Restudy of the same subjects for 6 h at half the concentrations 

did not have significant effects. The results suggest that the pollutant-induced 

changes in sensitivity to allergen in mild allergic asthmatics may depend on a 

threshold concentration of gas-phase pollutants rather than on the total amount 

of pollutants inhaled (Jenkins et al. 1999). 

Gas-phase copollutants can exert their own direct effects on the respiratory 

tract; however, they may also influence the deposition fraction of solid-phase air 

pollutants—that is, fine and coarse particles—and localize and intensify injury 

to epithelial tissues. For example, ozone-induced airway obstruction has been 

shown to develop differentially even in healthy subjects (in a current database 

on 140 subjects exposed to ozone in controlled chamber studies), and as many as 

one-third of the subjects have a significant degree of airflow obstruction during 

and immediately after short periods of exposure to a concentration similar to an 

ambient concentration of ozone. Ozone-induced airflow obstruction has been 

shown to increase bronchial deposition of respirable particles (PM2.5) in the 

lower respiratory tract (Foster et al. 1993). The pulmonary inflammation and 

increased epithelial permeability that follow ozone exposure may also lead to 

increased transepithelial transport of deposited particles, which may increase the 

risk of PM-related systemic effects. 

Just as ozone can have direct effects on airway epithelial tissues, PM2.5

exposure is known to induce systemic inflammation and proinflammatory cytokine production that may result from free-radical activity of components in PM. 

Controlled chamber studies have also been evaluated with 2-h exposures to concentrated ambient fine particles (at about 150 μg/m3

) in combination with ozone 

at 120 ppb. In healthy subjects, those exposures induced an immediate alteration 

in vascular function as indexed by brachial arterial vasoconstriction (Brook et al. 

2002). That suggestive study has shown that acute exposure to fine-particle and 
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ozone mixtures at concentrations often found in the urban environment can lead 

to acute peripheral arterial constriction. 

Thresholds 

To summarize the association between daily variations in ambient ozone 

concentration and daily fluctuations in deaths, a linear model is used in which it 

is assumed that the change in mortality risk is constant across levels of pollution. 

It is unlikely that the association between exposure and response at the individual level follows that simple mathematical formulation. People have their own 

susceptibility, which is characterized by a unique exposure-response association. 

The association may be further characterized by a unique “threshold” value, an 

ozone exposure concentration below which there is no risk of death. Each person’s threshold value will also vary over time, depending on the frailty of the 

person at any given moment, and thresholds may depend on the averaging period used to assess exposure. 

The time-series design, however, relates individual exposure not to individual risk but to the average of personal exposures among the at-risk population 

on any given day. Thus, the appropriate concentration-response function for the 

time-series studies is based on an aggregation of individual exposure-response 

curves. Aggregation of a large number of complex functions can yield smoother 

and more nearly linear curves at the population level, so we would expect the 

shape of the concentration-response function based on time-series studies to 

have a form that is relatively simple. 

The shape of the concentration-response function for ozone and mortality 

has been examined in detail (Bell et al. 2006). The association between a 2-d 

moving average of daily average ozone concentrations in 98 U.S. communities 

based on time-series data from 1987-2000 was examined. Bell et al. restricted 

their analysis to all nonaccidental causes of death and the entire year of observation. Three methods were considered to examine the shape of the concentrationresponse function: restricting ozone concentrations below specified values, postulating a threshold function with no risk below the threshold and a linear association above it, and a natural spline formulation of association. A positive association between ambient daily average ozone concentrations and mortality was 

observed down to 15 ppb for the restriction and spline approaches, and the 

threshold model could not show any substantial improvement in statistical fit 

down to concentrations of 5 ppb, the lowest value examined. We note that positive and statistically significant (p < 0.05) associations were observed down to 

25 ppb using the restriction approach. The risks based on 24-h mean ozone concentrations below either 20ppb or 15ppb were positive, but did not reach formal 

statistical significance. Threshold values based on 8-h running daily maxima 

would be somewhat higher. 

Those results suggest a near-linear association between ambient concentration of 24-h mean ozone and daily mortality count in the United States. Mis-
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110 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

classifying exposure (by using an average of ambient fixed-site monitoring data 

to estimate population average personal exposure) makes it more difficult to 

distinguish between linear and threshold models (Cakmak et al. 1999). Estimates 

of the concentration-response curve based on epidemiologic studies with imprecisely measured exposure should therefore be viewed with caution. A sensitivity 

analysis of the shape of the curve may be required to capture the uncertainties in 

this procedure more fully. Moreover, approaches based on 24-h averaging may 

cloud thresholds related to actual exposures which may be better represented 

with shorter averaging times, such as by using an 8-h maximum or daily 1-h 

maximum. 

The analysis of Bell et al. (2006) examined data from the entire year. 

However, it is not clear whether there is an association between ozone and mortality in the cooler months (Levy et al. 2005). The warmer months should therefore be examined separately. There is likely to be less exposure error during that 

time because people tend to spend more time outdoors or with their windows 

open. However, the magnitude and nature of the error could depend on location. 

Furthermore, confounding by other pollutants, particularly PM2.5 in the warmer 

season (Levy et al. 2005), may alter the shape of the concentration-response 

curve. 

Future approaches to further examining concentration-response relationships should consider using alternative algorithms for computing nationally averaged effects, using regional nonlinear or threshold estimates, and repeating all 

analyses using 8-h and 1-h maxima, instead of 24-h ozone data. 

On the basis of its review of the evidence, the committee concluded that 

the association between ozone concentration and mortality is generally linear 

throughout most of the concentration range although a number of uncertainties 

make it difficult to know whether there is a threshold for the association at the 

lower end of the range. If there is a threshold, it is probably at a concentration 

below the current ambient air quality standards. 

Short-Term Mortality Displacement

Investigations of acute effects of pollution assess the association between 

the daily number of events and ambient air quality during the period shortly before death. By the design of the studies, the time of life lost or the “prematurity” 

of the deaths is not directly observable. In the absence of knowledge about the 

amount of time lost because of these acute effects, one may hypothesize that air 

pollutants were able to trigger death only among a pool of very frail people, 

namely, those already in very bad health. Assuming that the remaining life expectancy among those frail subjects was short even in the absence of pollution, 

the effect of air pollution would consist of only a minor shift of the time of 

death, that is, a short “advancement” of death. The concept that air pollution 

affects mortality only in frail people already near death is referred to as short-
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Study Contributions to the Estimation of Reduced Premature Mortality 111 

term mortality displacement.3

 A period with increased mortality would be counterbalanced by a period with lower then expected mortality because deaths 

among the pool of susceptible people have already occurred (the “premature 

deaths” have been displaced by a few days). It has not been defined how “short” 

the advancement of death must be to qualify as short-term displacement, but the 

committee assumes that this concept implies losing a few days rather then weeks 

or months. 

The issue of short-term mortality displacement is important in the judgment of the public-health relevance and quantification of the public-health impact of the acute effects of air pollution if one is willing to weight the deaths of 

people destined to die within a very short time differently from the deaths of 

people who would have a longer life expectancy if there had been no exposure 

to ozone. 

The significance of effects will be determined by the size of the frail pool 

and the extent of displacement among the pool (Fung 2007). Air pollutants may 

affect the pool in various ways. The size of the pool, the rates at which people 

join or leave the pool, and the causes of their joining or leaving all affect the 

dynamics in mortality patterns. Ozone could increase the death rate outside the 

risk pool, increase the recruitment rate into the pool, or delay the recovery rate 

outside the pool. The net acute impact would depend on the relative size of each 

effect, so the temporal pattern of increased deaths after exposure might be complex. If ozone affects only the death rate outside the risk pool, one would expect 

to see fewer people die after an ozone episode because the risk pool is smaller. If 

instead ozone increases recruitment or delays recovery, the risk pool may 

enlarge, and the number of deaths in the period after the episode would be larger 

rather than smaller. Rabl (2006) has emphasized that the main effects in the 

mortality-displacement hypothesis are in essence unobservable because observed death rates are the net result of all the changes that affect the dynamics of 

the pool of frail subjects. He has shown that the increase in rates due to premature displacement and the decrease in deaths after the depletion of the susceptible pool cannot be observed or disentangled. 

Short-term mortality displacement has been investigated (with ambient 

PM as the marker of daily pollution) in several ways with a variety of statistical 

methods, including assessment of the displacement with generalized additive 

models (Zanobetti 2000), decomposition of the time series into time components 

(Zeger et al. 1999; Schwartz 2000), Gaussian-state space models (Murray and 

Nelson 2000), frequency-domain log-linear regressions (Kelsall et al. 1999), and 

time-scaled Fourier analyses (Dominici et al. 2003; Fung et al. 2005). Questions 

remain about the methods and assessment of mortality displacement, and the 

time lost because of acute effects of ambient PM cannot be quantified, but the 

 3

The term harvesting is sometimes used instead of short-term mortality displacement

to refer to the concept that air pollution leads to the death of people who are highly susceptible and near death (and die a few days earlier than they would have without airpollution exposure) rather than death of people who are not otherwise near death. 
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112 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

main conclusion from all the work is that the observed acute effects cannot be 

explained only by short-term displacement of death. 

Apart from those findings, one should emphasize that the idea that all 

acute effects of ozone can be explained by short-term mortality displacement 

involves a biologically implausible dichotomization of the distribution in the 

time between some adverse acute exposure and death. Instead, the time between 

exposure and death and the time lost are expected to follow some distributions 

that depend on the pattern of susceptibility factors or the frailty of the population. For example, survival time after an MI follows a wider distribution. Some 

MIs are immediately lethal, but survivors experience a wide distribution of increased risk of death as compared to those who have not suffered an MI, and 

risks are particularly increased at the onset of an MI but also in the early phase 

of recovery. Thus, if air pollution triggers MIs, the natural distribution of time to 

death after an MI should most likely be mirrored in MI-related deaths due to air 

pollution in that the severity of an MI and its survival pattern depend less on the 

trigger than on the underlying pathology, such as location or degree of atherosclerosis. 

A similar case that demonstrates the inherent limitation of the hypothesis 

of short-term mortality displacement can be made for the frail pool of patients 

with chronic obstructive pulmonary disease (COPD). Air pollution may trigger 

acute exacerbations due to, for example, the interference of particles with defense mechanisms in the lung, but whether and when decompensation and death 

occur depend on various host and exogenous factors, including type and time of 

access to health care, that affect the distribution of probability of and time to 

death. During an exacerbation of COPD due to, for example, a pneumonia, the 

patient may be particularly frail during the critical phase of the pneumonia (typically at the end of the first week) and have a transient inability to deal with the 

additional stress of increased ozone exposure. That may lead to death; but in the 

absence of the additional hazard posed by ozone, the patient might have survived and lived for as long as an “average” COPD patient of the same age. This 

example underscores that frailty is not necessarily a stable condition but may 

change substantially over short periods in a given subject. Some of the acute 

effects of ozone (see earlier discussion in this chapter), in fact, contribute to 

moving subjects to a higher level of frailty. 

In contrast, the terminal phase of lung cancer may serve as an example in 

favor of air pollution’s being in the role of short-term mortality displacement. 

As shown by Goldberg et al. (2001) in patients with lung cancer, death rates 

correlate with ambient concentrations of urban air pollution. However, lung cancer continues to be by and large an incurable disease with short survival time 

after diagnosis. Thus, the role of acute exposure to air pollution in the terminal 

phase of this disease may be considered less relevant despite some additional 

displacement of lung-cancer death due to air pollution. 

The above examples and discussion explain well the observation made in 

the literature on short-term mortality displacement by PM that risk estimates 

may increase if the statistical models take extended lag periods into account. 
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Study Contributions to the Estimation of Reduced Premature Mortality 113 

The observations after the classical London smog further support the concept of 

distributions of events with long tails of subacute effects on mortality rates. The 

latter remained above expected values for several months after the extreme 

smog episode without observable evidence of short-term mortality displacement. 

One published study (Zanobetti and Schwartz 2008) addresses this important issue related to the acute effects of ozone. It investigated the effects of 

short-term ozone exposure on mortality in summer by using distributed-lag 

models. With that seasonal restriction, it was not possible to assess the longer 

tail of the effects beyond 21 d. As in the case of PM, the study does not support 

the notion that only short-term mortality displacement occurs. However, in contrast with the evidence from PM studies, these preliminary results suggest that 

death rates normalize within about 1 wk, that is, faster than in the case of PM. 

Accordingly, the effect estimates (or odds ratios) of distributed-lag models were 

not much larger than those of the acute 1- to 2-d model. As mentioned, the details of the interrelated effects of the size of the frail pool and changes in size 

due to persons becoming frail or recovering and leaving it cannot be disentangled in these approaches. The apparent difference between results of the PM 

distributed-lag models and those in the ozone studies is difficult to interpret. The 

20-d distributed-lag effect of ozone on mortality was at most some 60% larger 

than the immediate lag-0 effect—a substantially smaller difference than that 

reported for PM. There is a need for further investigations of short-term mortality displacement and the distribution of lagged subacute effects of ozone, but 

one can conclude, on the basis of the preliminary analyses and on conceptual 

grounds, that acute effects of ozone based on the published meta-analytic slopes 

underestimate to some degree the total acute and subacute effects. The underestimation may be smaller than in case of PM. 

It is also of note that the preliminary findings regarding the probable pattern of acute and subacute effects of ozone on mortality do not provide further 

information about the occurrence or size of chronic effects. 

On the basis of the above background from the PM literature, the biologic 

concepts of acute effects, and the preliminary results from Zanobetti and 

Schwartz (2008), one can conclude the following: 

• Short-term displacement of death is a likely explanation for the subgroup in the upper tail of the susceptibility of the frailty distribution. The size of 

the fraction explained by short-term displacement is not known. 

• Short-term mortality displacement is not a plausible explanation of all 

effects. In fact, the short-term-displacement-only hypothesis conflicts with the 

notion that underlying mechanism, frailty, severity of outcomes, and time between exposure and event all follow some distributions in populations. Although 

the amount of life time lost is not observed in acute-effects studies, the upper tail 

of the distribution of time lost may be months or years. 

The distributed-lag effect estimates from time-series studies may be used 

to estimate the population average lifetime lost because of acute and subacute 
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114 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

effects of ozone if one assumes a common hazard or probability of instantaneous 

death in all members of the population of any given age. More likely, though, 

hazard rates follow a wide distribution, thus the assumption reflects a simplification. That “population mean” approach, however, does not reflect the distribution of the amount of time lost because of the deaths that occur as a consequence 

of increased ozone concentrations or the distribution of pre-existing frailty 

among those affected. These issues highlight the difficulties in translating the 

time-series findings into an estimate of life time lost. Sensitivity analysis should 

be conducted on the number of degrees of freedom used to analyze the time 

trend in models with distributed lags because the risk estimates for the longer 

lagging times can be influenced by how temporal trends in mortality effects are 

modeled. 

Uncertainty and Variability in Ozone-Mortality Analysis4

One of the major barriers to the broad acceptance of recent EPA healthbenefits analysis is the large amount of inherent uncertainty. How the agency 

deals with that uncertainty is therefore critical for acceptance. 

Assessment of uncertainty is not the same as assessment of variability. 

Uncertainty is a consequence of imperfection in knowledge or data and can (in 

theory) always be reduced by getting better data. Variability is an inherent property of an exposed population and cannot be changed by getting better data. A 

fair and balanced characterization of uncertainty in risk estimation is important 

because most risk estimation is not highly precise and many people are tempted 

to over interpret the resulting values. EPA (1997c) recognizes that wellperformed uncertainty analysis helps decision-makers and the public to place 

risk estimates in the proper perspective and facilitates informed decisionmaking. The need for uncertainty analysis is also recognized in other countries 

as evidenced by the European Commission report (Bickel and Friedrich 2005) 

that emphasizes the importance of proper communication of uncertainties to 

ensure that users understand the limitations of analyses and their results. 

Other reports discuss the issue of uncertainty in risk assessment and benefits estimation (NAE 1972; NRC 1975, 1982, 1983, 1994, 1996, 2002, 2007a; 

PCCRARM 1997). All those reports found that proper and adequate characterization of uncertainty is essential. Almost all expressed concern that most risk 

assessments and health-benefits analyses tend to underestimate uncertainties and 

leave decision-makers with unwarranted confidence in the risk estimates provided. To address that concern, the reports recommended the use of formal approaches to characterize uncertainty, such as Bayesian analysis or Monte Carlo 

analysis (Gilks et al. 1996). Less consistent were opinions about characterization 

 4

This section concerns the uncertainty and variability in the analysis of mortality associated with ozone exposure. The potential uncertainty in the monetary valuation of mortality risk associated with ozone is considered in Chapter 5. 
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of model uncertainty: some reports discussed and recommended the use of expert judgment, and others recommended that such scientific uncertainty be thoroughly described but not quantified. Efforts to characterize model uncertainty, 

however, are critical, as evidenced by the most recent report (NRC 2007b), 

which states that model uncertainty in particular tends to be understated or ignored. That report states that modelers often assume that their models are correct 

and base estimates of the models’ parameter values on single studies; because a 

model may be incorrect or incomplete, the uncertainties that they produce may 

be significant. 

Sources of Uncertainty

There are many sources of uncertainty in mortality-risk assessment related 

to ozone exposure, including random sampling error in a random sample of data, 

measurement error (systematic error or random error), data nonrepresentativeness, surrogate data, lack of relevant data, problem and scenario specification, 

and model uncertainty. Of those, only sampling error is captured in ordinary 

statistical measurers of uncertainty (p-values and confidence bounds), so total 

uncertainty is necessarily greater and perhaps much greater than can be directly 

measured. 

Several methods exist to reduce uncertainty, including iteration of modelbuilding and input distributions, in combination with sensitivity analysis, which 

can help to focus resources on the most important model inputs and components. 

The uncertainty sources that probably have the greatest influence in ozonemortality analysis are the epidemiologic models. Much of this uncertainty results from unavoidable and expected variability, from estimation of concentration-response functions with epidemiologic studies, from possible lagged effects, and from baseline statistical variation. Baseline statistical variation, which 

tends to be inherent in data, could be reduced in some cases with control measures and in others with better models. To deal with model uncertainty, it is possible to compare alternative models but not combine them, weight predictions of 

alternative models (for example, with probability trees), or use metamodels that 

degenerate into alternative models. Uncertainty is also associated with ozone 

concentrations and with the reliability of ambient ozone-monitoring data to indicate ozone exposure. 

As stated above, the formal approaches to uncertainty analysis in mortality 

models include Bayesian analysis and Monte Carlo analysis. The use of expert 

judgment, which could be considered an empiric Bayesian approach, provides 

another framework for uncertainty analysis. EPA used expert elicitation in the 

2006 final regulatory impact analysis for the PM NAAQS (EPA 2006). However, the best way to use expert judgment remains to be determined. A key step 

in moving forward would be to agree on conditions under which expert judgment is an acceptable input, even for rule-making situations. The World Health 

Organization (WHO 2000) has developed guidelines to identify a set of proc-
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116 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

esses and general approaches to assess available epidemiologic information in a 

clear, consistent, and explicit manner. In particular, it recommended the use of 

expert assessment according to an explicit protocol, defined in advance. The 

essential components of the protocol are: specification of the question to be addressed, justification of the expertise represented, and specification of the methods to be used. Before EPA makes a decision about the use of expert judgment 

in the context of the impact of ozone on mortality and for benefit analysis, further evaluation is needed to assess the relevance and usefulness of the recent 

expert elicitation results for PM. In particular, in view of the time and cost associated with an expert-judgment procedure, the agency needs to understand 

whether, in the case of PM, the expert elicitation in the presence of other sensitivity analysis added substantial value or could have been replaced with a published formal or “qualitative” meta-analysis. 

EPA could also consider other options for incorporating expert judgment 

into its probabilistic uncertainty analysis. The agency possesses considerable 

internal expertise, which should be used as fully as possible. If it continues to 

use expert elicitation for uncertainty analysis, it should consult outside experts 

as needed, individually or in panels. The experts and the rationales and empirical 

bases of their judgments should be made known. 

It is important to distinguish between uncertainty due to projecting the future and uncertainty inherent in estimating mortality on the basis of information 

on the magnitude of ozone exposure, which varies across space and time and 

among individuals. 

Thus, a good characterization of temporal and spatial correlation is also 

needed. Sensitivity analysis and model diagnostics would help to determine the 

appropriateness of the spatial and temporal characterization of the dependence 

structure (and other assumptions) incorporated in the models under consideration. 

The ability to quantify and propagate uncertainty throughout the analysis 

is still in development. However, uncertainty analysis has developed further and 

faster than our ability to use it in decision-making. A National Research Council 

report (2007a) recommends that more attention be paid to questions of how to 

use uncertainty analysis to set action levels and make regulatory decisions. Effective communication of uncertainty requires a high level of interaction with 

the relevant decision-makers to ensure that they have the necessary information 

about the nature and sources of uncertainty and its consequences. 

Uncertainty in Air-Quality Numeric Models

Air-quality numeric models, such as the Community Multiscale Air Quality (CMAQ) model, are potentially valuable tools that can extend the ozonemortality analysis to places and times on which the desired data are not available. Air-quality models, which are based on the dynamics and mechanics of 

atmospheric processes, typically provide information on larger regions than data 
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from observational networks. Errors and biases in these deterministic models are 

still inevitable because physical processes are simplified or neglected and because of the mathematical approximations used in assigning parameter values 

and inaccurate inputs. As a result of their own uncertainties, the models will add 

more uncertainty to the ozone-mortality risk-assessment estimates if they are 

used to characterize ozone exposures in future studies. 

Evaluation of these models and their uncertainties can help to quantify and 

characterize the magnitude of errors in the models. Although a full Bayesian 

analysis that incorporates all sources of information may be desirable in principle, it will be necessary in practice to make strategic choices about which 

sources of uncertainty justify such treatment and which sources are handled better through less formal means, such as consideration of how model outputs 

might change as some of the inputs vary through ranges of plausible values. 

A National Research Council report (NRC 2007b) describes in more detail 

different sources of uncertainty in air-quality numeric models and addresses the 

question of how to judge whether these models and their results are adequate for 

supporting regulatory decision-making. Effective communication of the different sources of uncertainty in the models requires a high level of interaction with 

the relevant decision-makers to ensure that they have the necessary information 

about the nature and sources of uncertainty and its consequences. Thus, if such 

models are used to assist in mortality risk assessment, uncertainty analysis and 

extensive discussion between analysts and decision-makers are needed. 

USE OF EPIDEMIOLOGIC INFORMATION IN OZONE-RELATED 

RISK AND BENEFITS ASSESSMENT 

Because death is inevitable, the question relevant to policy-makers, risk 

assessors, and the public is whether people who live in areas more highly exposed to air pollution experience death at an earlier age than people who live in 

communities that are less exposed. The effect of pollution on death may be 

quantified in terms of number of deaths in a given period or life months (or 

years) lost. 

Number of Deaths

The “acute-effect studies” directly estimate the change in daily death rates 

due to short-term exposure (or a short pulse of exposure). Most models investigate the change in death rates for only one or a few days, whereas distributedlag models look further ahead to capture delayed acute effects, often referred to 

as subacute effects. The expansions are useful in understanding the statistical 

distribution of time between an exposure pulse and the time pattern of occurrence of death. On a population level, it is extremely unlikely that all ozonerelated deaths occur either immediately or within 1-2 d of exposure. A more 

plausible model assumes that susceptibility to death (or frailty) and the success 
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118 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

of intervention strategies follow a distribution wherein some people die immediately or within 1-2 d and others first suffer acute health ailments (such as an MI 

or pneumonia) and their deaths follow a period of unsuccessful treatment or as a 

result of the decompensation of defense mechanisms. The most complete assessment of the association between acute exposure and death originates in distributed-lag models that integrate the distribution of the time between exposure 

and death. However, both the usual time-series model and the distributed-lag 

models focus on a short window of exposure. Effects of long-term cumulated 

exposure are, by design, ignored in such models. 

In contrast, cohort studies focus on the associations between some metric 

of long-term exposure and death rates (as in the ACS study and the Harvard Six 

Cities Study). As a consequence, the increases in death rates associated with 

pollution may reflect the total effect of pollution on death, including life time 

lost because of acute or subacute effects and because of chronic conditions. For 

example, if pollution increases systemic inflammation, it may contribute to remodeling of airways and to obstruction or contribute to the development of 

atherosclerosis, and these chronic ailments increase the risk of premature death 

independently of any acute effects of pollution. One may argue that the current 

way of reconstructing long-term exposure in cohort studies is insensitive to 

short-term peaks and changes in exposure and that cohort studies may therefore 

miss some acute effects. Although cohort studies are likely to capture a large 

fraction of the effects of pollution on death—including most acute, chronic, and 

combined effects—some fraction of the immediate acute effects may not be contained in the effect signal, so the total effect of ozone might be larger than that 

observed in cohort studies. 

Years of Life Lost 

If one assumes that baseline probability of death or hazard is common to 

all members of the population at any given age, one can treat estimates of pollution-related risk based on time-series mortality studies in a manner similar to 

estimates obtained from cohort studies (Miller and Armstrong 2001; Burnett et 

al. 2003; Rabl 2006). That is, the risk estimates from time-series studies can be 

used to estimate the life years lost because of acute effects of pollution in the 

same way that risk estimates from cohort studies are used to derive the time lost 

because of the chronic, if not total, effects of pollution. However, there is probably a wide distribution of likelihood of death in any population on any given 

day. Current ambient ozone concentrations probably will not increase risk to a 

point at which death is likely for most of the population, and only people in a 

frail state (for example, having a chronic disease) would clearly be at risk of 

death from ozone exposure. 

It is assumed that large portions of the population are at risk of death because of longer-term exposure to air pollution, so it is more reasonable to apply 

a common baseline hazard function within the cohort design. Relative risks from 
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the cohort studies are then combined with common baseline hazard functions, in 

the form of life tables, for selected populations to estimate the amount of life 

lost because of exposure to air pollution (Coyle et al. 2003; Miller and Hurley 

2003). The same life-table calculations can be used to estimate the number of 

people who will die over a fixed period because of changes in air pollution exposure. 

If the hazard and risk distributions in the population are not independent, 

estimates of excess deaths and life years lost in the entire population because of 

changes in ozone exposure based on time-series studies will not equal the average of estimates across all risk groups.5

 The size of the difference is not known 

but could be estimated if risks for susceptible groups are obtained (Goldberg et 

al. 2005). 

Translation to Risk and Benefits Assessment

Acute and chronic effects of urban air pollution, such as PM, on mortality 

have been well established. Risks based on cohort studies are some 10 times 

larger than those based on acute-effects studies that investigated only the influence of yesterday’s concentrations of PM2.5 on today’s death rates and some 3-5 

times larger than the total acute effects, including death, distributed over several 

weeks. 

More recent risk assessments provided separate estimates of acute effects 

that occur within a few days of exposure and total effects. Such separation may 

be useful, given that the time between pollution abatement and health benefits 

may follow a distribution, with acute effects being reduced more quickly than 

effects due to chronic conditions (Röösli et al. 2005). 

Ozone-mortality risk assessment faces major challenges. As summarized 

above, evidence of long-term effects of ozone on mortality (or survival time) is 

presently weak, so the derivation of a relative risk to describe the association 

between ozone exposure and death is more difficult than in the case of PM. The 

translation of the results into number of attributable deaths is possible but leaves 

us with two main challenges. First, the assessment of acute effects would be 

incomplete if based solely on the usual time-series studies, given that subacute 

(delayed) effects are not captured with these studies; only one study has published estimates for distributed-lag models. Second, in the absence of abundant 

quantifiable evidence of chronic effects of ozone on mortality, total life time lost 

because of both acute and chronic effects cannot be estimated. The current evidence from cohort studies, although it is weak, supports the notion that the estimates of the risk of death due to ozone may be largely underestimated if based 

 5

In this context, the distribution of hazards among the population is the likelihood of 

death at any age; the distribution of risk is the association between ozone and death at any 

age. 
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120 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

solely on the main time-series studies that were at the center of EPA’s request 

for this report. 

While the current lack of a sufficient number of ozone cohort studies precludes a respective assessment, lessons learned from PM would suggest that 

estimations based on time-series study alone are far smaller than the overall 

long-term cumulated effects. 

The question of how to translate epidemiologic information into risk and 

benefit assessment is the subject of debates. Many risk assessments derive, as 

one intermediate step, the number of deaths attributable to air pollution on an 

annual basis. That approach has several limitations that are of concern particularly for chronic effects but conceptually also apply to acute effects, as is the 

case for the acute effects of ozone on death. Although it is true that pollution 

increases the mortality risk and thus the number of deaths, one has to emphasize 

that death is inevitable and that improvement in air quality only postpones death 

and does not prevent it. The concept of “attributable cases” is often interpreted 

as the corollary of “preventable cases,” which in the matter of death is certainly 

wrong. 

Another problem faced with “attributable death” originates in the fact that 

changes in death rates in any population lead to changes in the age structure of 

the population. That is, a reduction in air pollution will lead to longer life expectancy and increase the number of elderly people. Age-adjusted death rates are 

expected to decrease under cleaner conditions, but the absolute number of deaths 

will steadily increase as the population ages. As a consequence, the “attributable 

deaths” (or benefits) will not be the same throughout the years after an improvement in air quality. Instead, there will be a complex interplay between the 

distribution of acute vs chronic causes of premature death in which reduction in 

death rates caused by chronic exposures will take longer to materialize than reduction in death rates from acute effects and longer than the changes in the 

population age structure due to the removal or reduction of a risk factor. 

The net result of those dynamics is a continual adjustment of the expected 

annual change in the number of deaths attributable to a change in pollution. As 

shown by Miller and Hurley (2006), although the benefit (in absolute number of 

deaths) may steadily increase during a few years, it will later decrease for a couple of years and ultimately reach a time when the absolute number of deaths (per 

year) is larger than it was in the more polluted condition. Therefore, expression 

of benefits due to reduction in mortality rates can ultimately not be correctly 

expressed as a stable annual number of deaths prevented. 

For all those reasons, risk assessors omit the expression of “attributable 

cases of death” but prefer to derive years of life lost (YLL) due to some policy 

change. Although the derivation of YLL is based on the same input information—the risk changes derived from epidemiologic studies—the use of YLL is 

more appealing because one can derive the total YLL for the entire remaining 

life time of any cohort, whether dynamic or static, and express benefits in terms 

of annual YLL (Brunekreef et al. 2007). However, even though it may be more 

appealing to express mortality-risk change in YLL, the concept may be more 
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Study Contributions to the Estimation of Reduced Premature Mortality 121 

problematic for valuation purposes than that of “attributable deaths” (see Chapter 5). 

Another potential approach to the translation of epidemiologic information 

into risk and benefit assessment is to stop short of calculating annual numbers of 

deaths prevented and simply report the change in the annual mortality rate expected as a result of the change in ozone. Rabl (2006) shows the mathematical 

relationships between the change in mortality rate, the annual reduction in number of deaths, and the years of life saved. For an acute mortality effect as a result 

of short-term (daily) pollution-exposure changes and a stable population (in 

which births equal deaths), he shows that a permanent reduction in pollution 

temporarily reduces the number of deaths over some period because people who 

would have died from pollution live longer. Eventually, however, they die from 

something else, so the annual number of deaths returns to its previous level. 

However, there is a permanent increase in life expectancy, a larger population, 

and thus a permanently lower mortality rate. The valuation implications of this 

are discussed in Chapter 5. 

CONCLUSIONS AND RECOMMENDATIONS 

Overall Conclusions and Recommendations 

Human chamber and toxicologic studies have yielded strong evidence indicating that short-term exposure to ozone can exacerbate lung conditions, causing illness and hospitalization, and potentially lead to death. Although it is less 

abundant, the available evidence on ozone exposure and exacerbation of heart 

conditions points to another area of concern. Panel and epidemiologic studies 

have also found that exposure to ozone (as an indicator of a broad mix of photochemical oxidants) has those effects. The committee found that the four recent 

time-series analyses and meta-analyses of the relationship between exposure to 

ozone (and other photochemical oxidants) and premature mortality add to the 

evidence by providing robust statistical evidence of an association. 

Overall Conclusions 

On the basis of the broader available evidence and the additional insights 

obtained from its review of the new time-series studies, the committee concludes 

that short-term exposure to ambient ozone and the larger photochemical-oxidant 

mixture is likely to contribute to premature deaths. Although it is rarely possible 

to exclude the possibility of zero effect in such analyses, the committee concludes that an absence of any effect is highly unlikely. Despite some continuing 

questions about the evidence, the committee concludes that it is strong enough 

to be used in the estimation of the expected benefits of reductions in population 

mortality risk that would result from reducing exposure to ozone and/or the photochemical-oxidant mixture. 
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122 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Overall Recommendation 

The committee recommends that ozone-related mortality, estimated on the 

basis of the results of the recent time-series analyses, be included in future estimates of health benefits of reducing exposure to ambient ozone. The committee 

further recommends that the greatest emphasis be placed on estimates based on 

systematic new multicity analyses using national databases of air pollution and 

mortality, such as was done in the National Morbidity, Mortality, and Air Pollution Study database, without excluding consideration of meta-analyses of previously published studies. Emphasis should also be placed on risk estimates obtained from analyzing data on multiple days so as to include delayed acute 

effects. Such health-benefits estimates should be accompanied by a broad array 

of analyses of uncertainty, while at the same time understanding that a zero 

value is highly unlikely. 

Strengths and Limitations of the Evidence 

In reaching its overall conclusions and recommendation, the committee 

identified a number of strengths and limitations of the evidence. 

On the basis of available evidence, the committee believes that deaths related to exposure to ozone (and other photochemical oxidants) are not likely to 

be restricted to people who are at very high risk of death within a few days. The 

evidence is provided by the recent analysis of time series in several U.S. cities 

that focused specifically on a mortality-displacement pattern in the time course 

of exposure and death (Zanobetti and Schwartz 2008). In that analysis, it was 

clear that short-term mortality displacement (or ‘harvesting’) could not fully 

explain the observed increase in death. The estimates steadily decreased with 

increasing lags, reaching the level of no effect approximately seven days after 

exposure but without reaching negative associations at any of these days as one 

would expected if all events were explained by short-term displacement among 

the pool of extremely sick and frail people. As discussed by Rabl (2006), if pollution affects both the extremely frail and others, the portion related to displacement cannot be quantified as one can only observe the net difference between short-term harvesting and all other acute effects. The pattern observed in 

Zanobetti and Schwartz (2008) indicates that at no lag until the disappearance of 

any effect (day 7) was the portion explained by mortality displacement larger 

than the rest. This evidence, albeit from only one study provides evidence that 

ozone-mortality effects are associated not just with those already near to death. 

In contrast with the PM literature, very few data are available from the use 

of distributed-lag models. Those available suggest that in the case of either 

ozone or PM, effect estimates steadily increase with increasing time of the investigated effects. Specifically, subacute (longer-term) effects that combine effects of several days or weeks of exposure are larger than immediate short-term 

effects, whereas estimates of effects from cohort studies are the largest. How-
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ever, the increase in estimates is far larger for PM than for ozone. That may be a 

consequence of attenuation due to large errors in characterizing exposure to 

ozone, or it may reflect a more dominant role of acute pathologic conditions 

related to ozone exposure whereas the role of chronic pathologic conditions is 

more important in the effects of PM. As these interpretations rely on very few 

studies, further confirmation is warranted. 

In addition to the specific analyses in the time-series studies, there is only 

very weak, evidence from cohort studies of an association of premature mortality with longer-term exposure. Thus, the committee could not conclude at this 

time that exposure to long term ozone concentrations is related to mortality. 

Although the associations in the recent time-series studies appear sufficiently robust to provide a basis for estimating benefits, several factors need to 

be considered in interpretation: 

• The committee found that short-term ozone exposure is likely to contribute to premature mortality in addition to the risks posed by weather and PM, 

but studies have not been sufficient to control fully for potential confounding by 

or interactions with condensed-phase constituents of airborne PM, such as sulfates, acids, carbon, and other elements. 

• Controlling for such confounding is further complicated by the data 

from personal-exposure studies, which have found low correlations of monitored 

ambient ozone with personal ozone exposure. 

Detailed Conclusions and Recommendations 

In addition to its conclusions about the strengths and limitations of the 

new time-series evidence, the committee identified several kinds of additional 

needed research. 

Conclusion: On the basis of available evidence, the committee believes 

that deaths related to exposure to ozone (and other photochemical oxidants) are 

not likely to be restricted to those in people who are at very high risk of death 

within a few days. Because the evidence is based on results from only one study, 

it warrants confirmation by other studies. 

Recommendation: EPA and the scientific community should conduct additional studies to investigate short-term mortality displacement and include the 

use of alternative methods. An example of such methods is investigation of people who have diseases, such as diabetes and heart disease, which are known to 

induce high mortality risk associated with air pollution. 

Conclusion: If further confirmed, the weak current evidence from cohort 

studies of an association of premature mortality with longer-term exposure 

would tend to support the assumption that not all the effects seen in time-series 

studies are due to short-term mortality displacement. 
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124 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Recommendation: The committee recommends that EPA, the National 

Institutes of Health (NIH), and the scientific community conduct further work 

with cohort studies to examine the association between long-term ozone exposure and mortality. The use of very large cohorts with long followup periods 

may be required because the long-term ozone-exposure mortality risk appears to 

be much smaller than that posed by fine PM. This may require pooling information from several cohorts to obtain sufficient statistical power. Long-term ozoneexposure models also need to be further developed to distinguish between variations in exposure not only on the between-cities and within-cities scales but at 

the individual level. 

Recommendation: To the extent that new cohort evidence is strengthened, EPA should consider including estimates based on that evidence in its 

benefits assessments. 

Conclusion: Epidemiologic studies have found that ozone-mediated risks 

were greater for cardiovascular mortality than for total mortality. However, there 

have been only a few toxicologic or human research studies directly evaluating 

cardiovascular effects of ozone exposure. 

Recommendation: EPA, NIH, and the scientific community should conduct further studies on the cardiovascular effects of ozone exposure, both in human and animal models. Studies should be designed to identify genetic susceptibility factors. 

Conclusion: Although the committee found that short-term ozone exposure is likely to contribute to premature mortality, the optimal way to quantify 

the effect is unavailable. The method that EPA uses now is appropriate only in 

very restricted situations that are not likely to be realistic. 

Recommendation: EPA should study emerging concepts and evaluate 

their use and implications in benefits assessments, including relationships between changes in mortality rates, annual deaths prevented, and years of life 

saved. The alternative approaches for expressing ozone mortality effects will 

lead to rather similar results if one is supposed to express only the most immediate (acute) effects of pollution. However, with the integration of subacute effects 

estimates and in particular in the case of use of long-term chronic-effect estimates, the discrepancies between the approaches increase, and the conceptual 

flaws of the “attributable-cases” model become more pronounced. 

Conclusion: Expected differences in susceptibility causes substantial uncertainty in estimating mortality risks on the basis of results of epidemiologic 

studies of total populations because of the lack of independence between pollution-related risk and baseline hazard. 

Recommendation: EPA and NIH should encourage more studies on potentially susceptible population groups, and EPA should explore the effects of 

uncertainty on risk assessments. To the extent that data are not available, models 

and assumptions can be used for sensitivity analysis. 
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Study Contributions to the Estimation of Reduced Premature Mortality 125 

Conclusion: Although the recent time-series studies have, to the extent 

possible, included analyses of alternative ozone metrics (such as 1-h maximum 

and 8-h maximum), it is important to further examine the relationship between 

those averaging times and to identify additional ozone metrics based on person 

exposures. That is important both to examine dose-response relationships, test 

potential confounding more effectively and to inform future regulatory choices 

among actions that might have differential effects on peak and multi-hour averages. 

Recommendation: EPA and the scientific community should design and 

conduct studies that use the full array of potential ozone metrics, including those 

that estimate population personal exposures. 

Conclusion: Control for confounding has not sufficiently accounted for 

geographic and seasonal variability in the relationship between ozone and is 

possible confounders. Further, data on PM speciation have not been sufficient to 

include in analyses of potential confounding; however such data are increasingly 

available from the Speciation Trends Network. 

Recommendation: EPA and the scientific community should account for 

seasonal and geographic variability in the relation between ozone and its confounders and should increasingly include the growing STN database in all future 

analyses of potential confounding of the ozone associations. To this end, EPA 

(through its PM Centers program), the Health Effects Institute (through its National Particle Component Toxicity Initiative [or NPACT]), and others (such as 

the Electric Power Research Institute) are supporting major new efforts in both 

time series and cohort epidemiology, to address this need. Further EPA should 

work with the scientific community to ensure that STN collects data frequently 

enough on the particle components most relevant to the potential for confounding. 

Conclusion: On the basis of its review of the evidence, the committee 

concludes that the association between short-term ozone changes in ozone concentrations and mortality is generally linear throughout most of the concentration range, although uncertainties make it difficult to determine whether there is 

a threshold for the association for the association at the lower end of the range. 

If there is a threshold, it is probably at a concentration below the current ambient 

air quality standards. 

Recommendation: EPA and the scientific community should further explore how individual thresholds may vary and the extent to which thresholds 

depend on the frailty of the individual at any given moment. The research should 

involve panel studies of individuals considered to be susceptible to premature 

death from ozone exposure, such as those with impaired lung function. 

Because it is not clear whether there is an association between ozone and 

mortality in the cooler months, warmer months should be examined separately. 

A sensitivity analysis should be conducted on concentration-response relation-
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126 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

ships to capture more fully the uncertainties contributed by reliance on average 

fixed-site monitoring data to estimate population-average personal exposure. 

Conclusion: There is a lack of an observed association between ozone and 

mortality during the periods when exposure to ozone is expected to be low, and 

the ability to understand the lack is inhibited in part by the fact that monitoring 

is more limited during the winter periods. Better understanding of ozonemortality relationships during winter is important for full exploration of (1) seasonal differences in risk, (2) how these seasonal risk differences vary spatially 

between communities with warmer and cooler winters, and (3) ozone-mortality 

relationships at lower ozone concentrations. 

Recommendation: EPA and the states should extend operation of ozone 

monitoring into winter and report the measurements. 

Conclusion: As has been the case with PM, ozone analyses conducted 

with distributed-lag models over several days appear to capture overall effects 

better, but there have been relatively few of them. 

Recommendation: EPA and the scientific community should seek out 

appropriate databases and conduct distributed-lag analyses as part of future epidemiologic investigations to understand the statistical distribution of time between an “exposure pulse” and the time pattern of occurrence of death. 

Conclusion: Uncertainty in the epidemiologic models is likely to introduce substantial uncertainty into ozone-mortality analyses. 

Recommendations: The committee identified several approaches to addressing the uncertainty: 

• Results of the models should be presented with discussion of their reliability and of the estimated uncertainty about which model (if any) is reasonably correct. 

• EPA should consider Bayesian approaches, including additional expert 

elicitation once the recent experience with PM has been evaluated, to uncertainty analysis. 

• As EPA develops computational models and input distributions, it 

should intermittently conduct sensitivity analyses to focus resources on the most 

important inputs and parts of the models. 

• EPA should distinguish between data-derived estimates of some components (such as the concentration-response function) and expert opinions about 

other components that are lacking in scientific data to achieve a better understanding of how existing data and expert judgment combine to produce estimates and of where new data would be most valuable. 

• Time-series studies and meta-analyses should conduct additional sensitivity calculations, in particular to examine sensitivity of results to the structure 

of the cessation lag and sensitivity of the premature-mortality estimate to the 
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Study Contributions to the Estimation of Reduced Premature Mortality 127 

presence of a potential threshold concentration of ozone below which mortality 

effects are not observable. EPA should present multiple results from each study 

and characterize the different sources of error in the studies in a final uncertainty 

estimation on their benefits analysis. 

• Air-quality numeric models (such as CMAQ) should be considered for 

use in ozone epidemiologic studies to extend the spatial scale of available data. 

However, the uncertainty associated with the models needs to be carefully considered before inferences are drawn from the simulation models for mortality 

risk assessment. 
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128

5 

Economic Valuation of Reduction in Mortality 

Risk Associated with Ambient Ozone 

INTRODUCTION 

This chapter examines the conceptual and empirical literature on the economic valuation of reductions in mortality risks generally and specifically in the 

context of the epidemiologic literature on the linkage between ozone and mortality risks discussed in Chapter 4. 

As described in Chapter 2, the U.S. Environmental Protection Agency 

(EPA) follows standard practice in cost-benefit analyses by using estimates of 

willingness to pay (WTP) to calculate the economic value of reducing mortality 

risks. EPA’s current approach for estimating the benefits of reducing mortality 

risk has several steps. First, it estimates the reduction in individuals’ annual 

mortality risk stemming from the expected change in ozone concentration. Next, 

it calculates the annual number of deaths avoided (that is, postponed to some 

future year) by the postulated reduction in ozone concentrations to which the 

population at risk would be exposed. A central estimate of the distribution of 

economic values of the avoided deaths is then calculated by using a central 

value of a statistical life (VSL) drawn from the available WTP literature related 

to changes in annual mortality risk. Uncertainties in the estimates of mortality 

effects and valuation are then accounted for with reference to the confidence 

intervals around the estimates. 

One important and controversial issue related to valuation is whether the 

effects of reducing mortality risk should be measured in terms of lives saved 

(deaths postponed) or years of life extension (increased remaining life expectancy). If it is the latter, then it may be more appropriate to use a monetary value 

per statistical life year (VSLY) or to adjust the VSL to reflect the preferences of 

people of different ages rather than to use the same VSL in all cost-benefit 

analyses. (see Chapter 2 for definitions and examples of VSL and VSLY.) EPA 

has included various sensitivity analyses (alternative calculations) to explore the 
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Economic Valuation of Reduction in Mortality Risk 129 

implications of alternative approaches in several of its cost-benefit analyses for 

air-pollution regulations. However, the agency has been using the same VSL 

estimates regardless of remaining life expectancy in its primary analyses. The 

Office of Management and Budget (OMB) has urged caution in adjusting VSL 

on the basis of age because of uncertainties in the literature (Graham 2003) but 

encourages sensitivity analyses with alternative measures of changes in mortality and its monetary valuation. This chapter examines the theoretical and empirical evidence regarding the relationship between age and WTP for mortality-risk 

reductions in later sections. 

As noted in Chapter 4, another related question is whether those most affected by ozone are already in such poor health that their remaining life expectancy is low despite a reduction in ozone exposure. If decreases in short-term 

ozone concentrations merely decrease “harvesting” those who are already frail 

and near death, the economic benefit of reducing their exposure to air pollution 

may be relatively small and should be reflected in a much lower VSL or VSLY 

than that estimated for relatively healthy people. In addition, perhaps we should 

be considering the preferences of those at high risk (generally, those in poor 

health) regarding reduction in their mortality risk. 

This chapter takes up the question of whether the VSL or the VSLY is 

more appropriate for EPA to use in valuing reductions in mortality risk associated with reduced exposure to ozone. It also considers what economic theory 

and the empirical literature say about how WTP for reductions in mortality risk 

varies with the age of the person at risk, the size of the risk change, the health 

status of those at risk (existing chronic illness vs average health and effects on 

quality of remaining life), income, and other socioeconomic variables to improve approaches for assigning values to reductions in risk.

CONCEPTUAL UNDERPINNINGS OF VALUATION 

OF MORTALITY RISK 

As introduced in Chapter 2, cost-benefit analysis for a regulatory decision 

is intended to help answer the question of whether some proposed policy will 

result in more welfare for the affected people—that is, whether the expected 

benefits of the regulation are worth the expected costs. The standard approach to 

cost-benefit analysis is to quantify both costs and benefits in terms of “opportunity cost.” For benefits, that means a measure of what those who benefit would 

be willing to forgo to obtain the specified benefit. This is the basic concept of 

WTP, which is taken to be a measure of how much better off the members of the 

benefiting population perceive themselves to be, assuming that the members of 

the population have full information about the benefits.1

 

 1

There is some debate in the literature on the foundations of welfare economics as the 

whether WTP is an appropriate measure of the welfare changes of individuals. For a recent overview of this debate, see Adler and Posner (2006), especially Chapter 2. WTP as 
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130 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

In the early days of cost-benefit analysis for public programs, the predominant approach to determining the monetary value of programs that reduced 

mortality risks was the human-capital approach. That approach focused on the 

financial loss when a person dies prematurely, as measured by lost lifetime earnings (see, for example, Dublin and Lotka 1930). It is conceptually similar to the 

cost-of-illness approach, which measures lost earnings and medical costs due to 

illness and premature death. Later, several economists (for example, Schelling 

1968 and Mishan 1971) discussed why those indicators of the financial burden 

of disease and premature death do not measure the monetary value of the full 

effect of disease and premature death on the welfare of the population and are 

therefore insufficient for a full cost-benefit analysis of public policies aimed at 

reducing morbidity or mortality. They noted that those financial measures ascribe no value to the lives of homemakers or retired persons, and they argued 

that a more appropriate way to value a program that reduces mortality risk is to 

determine what the reduction in risk is worth to the people who benefit. Thus, 

WTP is a more appropriate measure of the change in welfare in cost-benefit 

analysis because it reflects not just the financial effect but the value that people 

place on the effect on quality of life and longevity. 

WTP specifically measures the ex ante value of reduction in risk that public-health and public-safety programs may provide. It is not known specifically 

whose death will be prevented, only that the probability of death in a group of 

people will be reduced. Generally, WTP is expected to exceed the cost of illness, 

but costs paid by third parties (such as insurance-paid medical costs) will generally not be included in an individual’s WTP and should in some cases be added 

to individuals’ WTP to determine total value. There is substantial evidence that 

WTP for reductions in mortality risk typically exceed by a substantial amount 

the expected value of lost earnings (e.g., Viscusi 1993). 

Some authors have argued that the appropriate measure of WTP for risk 

reduction is not the values expressed by the people actually affected by the policy, but the values of people who do not know their actual position in society 

(age, income, wealth, health status, etc.) but are acting behind a “veil of ignorance” or as “impartial spectators” (see, for example, Pratt and Zeckhauser 

1996; Sunstein 2002; Hammitt 2007, p. 237). There is an extensive literature in 

welfare economics based on these ideas as first developed by Harsanyi (1955) 

and Rawls (1971). But with one significant exception, this literature has focused 

on the principles of distributive justice and fairness and not on the valuation 

 

a welfare measure is criticized as being dependent on the existing distribution of income 

and wealth and on existing preferences of individuals, which may be influenced by such 

things as addictive behaviors. The standard approach in cost-benefit analysis is to acknowledge these difficulties in principle but to base empirical measures of value on WTP 

whenever possible. In fact, the OMB Circular A-4 is explicit in calling for monetary 

measures based on WTP (OMB 2003). 
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Economic Valuation of Reduction in Mortality Risk 131 

of specific goods received by individuals. The exception is the paper by Pratt 

and Zeckhauser (1996). We see this literature as offering an interesting thought 

experiment for considering ethical issues regarding distributive justice and 

valuation. But it does not offer practical methods and techniques for the development of criteria of distributive justice or for the empirical estimation of values. All of the practical methods for estimating values are necessarily based on 

the preferences of individuals who know their positions in society, and these 

values are based on expressions of WTP for changes in risk. 

A possible surrogate for the “veil of ignorance” or “impartial observer” 

perspective is the “public preference” or “social value” approach to determining 

benefits. This approach involves asking people to express their WTP for policies 

that would reduce the risk of premature mortality for specified groups of individuals with certain characteristics, for example, age. Some studies have shown 

that people have different preferences concerning policies delivering health improvements or risk reductions to different social groups (Cropper et al. 1994; 

Dolan et al. 2005). But such studies are not based on the “veil of ignorance” 

approach, because it is not possible to show that people could in fact ignore their 

own position in society relative to those whose risk changes they were being 

asked about. For either approach, the conceptual questions regarding appropriate 

aggregation of such values for a specific policy assessment have not been resolved (see below). 

Basing the values used in economic analysis on the preferences of the affected individuals is a fundamental tenet in welfare economics. Thus, the monetary measure of the benefit of a reduction in mortality risk is based on the value 

placed on the benefit by the individuals receiving it. It is not the value held by 

the policy-maker or the experts. The standard approach for cost-benefit analyses 

is thus to measure the benefits of a mortality-risk reduction on the basis of the 

value to each individual of his or her own reduction in risk and then to sum these 

values across all affected individuals. 

An important conceptual question is whether, if individuals are altruistic 

toward others, especially family and friends, altruistic feelings should be included in the valuation of reductions in mortality risk by adding WTP values 

that people have for others’ risk reductions. As was discussed in Chapter 2, economic analysis (e.g., Jones-Lee 1991) shows that if the altruism involves a general regard for the well-being of others, that is, is non-paternalistic in nature, 

summing WTP over all affected individuals would leave the sign of net social 

benefits unchanged since the altruists’ benefits would be offset by the altruists’ 

recognition of the costs of the policy to others. Summation is appropriate only if 

the altruism is paternalistic in nature. Because we have no evidence to indicate 

the extent of paternalistic altruism regarding risk reductions, we consider that 

the approach of using individuals’ WTP only for their own mortality-risk reduction is appropriate. 
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132 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

According to this approach, maximum WTP for mortality-risk reduction is 

defined as the amount of money that would make the person indifferent between 

choosing to spend the money to decrease his or her own mortality risk and forgoing the decrease in risk and keeping the money to spend on other things. Expressions for a person’s WTP can be derived from models of the choices made 

by utility-maximizing people (see Chapter 10 of Freeman [2003] for an overview). The models are simplified representations to describe economic behavior 

and to predict the choices that a utility-maximizing person would make. They 

provide a formal definition of WTP and provide a basis for analyzing the factors 

that determine a person’s WTP and how it may vary. For example, the model 

can help to analyze the question of whether VSL varies with age, income, and 

other socioeconomic characteristics of individuals. 

The life-cycle consumption model (see Shepard and Zeckhauser 1982; 

Cropper and Sussman 1990) is the most comprehensive economic model that is 

available for analyzing how WTP for small changes in mortality risk is expected 

to be related to a person’s age and other factors. In the model, persons, acting as 

individuals, are assumed to try to maximize their expected “utility from consumption” over their lifetimes, given constraints involving their initial wealth, 

their annual income, the cost of consumption, and a subjective rate of time preference. Utility from consumption is the satisfaction or enjoyment obtained from 

any activity that involves an expenditure of money or time. The subjective rate 

of time preference is the rate at which a person discounts future utility relative to 

current utility. Empirical evidence and common sense suggest that the value to a 

person today of future consumption is something less then the value of current 

consumption, and the difference between the two is the discount factor (which 

implies a subjective rate of time preference). 

The model postulates that a person makes economic choices on the basis 

of his or her expectations about future utility from future consumption and about 

future income, all discounted to a present value at the person’s rate of time preference. People are also assumed to include in their choices their expectations 

about their future survival probability. The model incorporates constraints that 

people have because of initial wealth and income over time, and it takes opportunities for borrowing, bequests, and lending into account. 

In a simple model, an expression of a person’s maximum WTP for a small 

reduction in mortality risk can be derived to illuminate the factors expected to 

influence the magnitude of and variation in WTP. The expression is the product 

of the reciprocal of the probability of surviving the current period, the present 

discounted value of the expected utility from consumption conditional on surviving the period, and the reciprocal of the marginal utility of consumption conditional on survival (used to convert utility into monetary terms). Marginal utility of consumption is the additional satisfaction or enjoyment obtained from a 

small increment of consumption. 
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Economic Valuation of Reduction in Mortality Risk 133 

To examine the effect of age on WTP for a reduction in the current risk of 

death, we ask how age would affect each of those terms.2

 As people age, their 

probability of surviving the current period generally falls. Thus, their WTP to 

reduce their mortality risk in the current period is expected to increase because 

as the probability of death in the current period rises, a person is likely to be 

willing to forgo more current consumption to increase the chances of surviving 

to the next period to continue enjoying the fruits of his or her resources. That 

may be offset, or at least limited, by a desire to leave some bequest for one’s 

children and others. However, aging not only increases current risk, it decreases 

life expectancy conditional on surviving the current period, and this is expected 

to decrease WTP. This effect could easily offset the first effect on WTP. 

How the present value of expected utility of consumption—the second 

term of the equation—changes with age is ambiguous. If per-period consumption and its utility were constant over time, the present value of expected utility 

of consumption would be proportional to discounted remaining life expectancy. 

With rare exceptions, mortality rates rise with age. Thus, the decrease in remaining life expectancy with increasing age motivates the hypothesis that WTP for 

mortality-risk reduction should fall with age. However, if there are constraints 

on borrowing against future income, per-period consumption is likely to rise in 

the earlier years of the life cycle. If, for example, a person cannot be a net borrower but can lend at the riskless rate of interest, his or her consumption is likely 

to be constrained by limited income at the beginning of life due to lower earning 

potential. That will cause the present value of the utility of consumption and 

hence the WTP for mortality-risk reduction to increase up to some point and 

then to decline (Shepard and Zeckhauser 1982); a plot of WTP against age 

would have an inverted U-shape. 

The combined effect of all those factors is that the impact of age on WTP 

for mortality-risk reduction is ambiguous on the basis of theoretical analysis 

alone. It requires empirical evidence to determine whether the combined effect 

of these factors is that WTP increases, decreases, or remains the same over all or 

part of a lifetime. 

Similar arguments can be made about health status. Health status may affect life expectancy, pleasure in consumption, or both. If life expectancy is reduced because of illness, the first term in the expression of WTP should be positive; with smaller chances of surviving the current period, the person should be 

willing to pay more to reduce mortality risk. As with age, the effect of health on 

the other factors that determine WTP is ambiguous. Chronic illness, for example, could reduce the quality of life and cause a person to derive less enjoyment 

from consumption. 

In summary, the effects of age and health status on WTP are ambiguous. 

Under reasonable assumptions the discounted expected utility of consumption 

 2

See Hammitt (2007) for further discussion of the points raised in the remainder of 

this section. 
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134 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

increases with future health and life expectancy (and so decreases with age). The 

ambiguity arises because the expected marginal utility of consumption is also 

likely to increase with future health and life expectancy. Since VSL is the ratio 

of the discounted expected utility of consumption to the expected marginal utility of consumption, and since both terms move in the same direction, the effect 

on the ratio is indeterminate. Thus, the combined effect of lower likelihood of 

survival and shorter remaining life expectancy on WTP to reduce mortality risk 

is ambiguous. 

So far, we have described only the effects of a current change in risk of 

death on WTP (or VSL). Also potentially relevant to valuing the effect of ozone 

on mortality risk is the WTP (or VSL) associated with a future change in risk of 

death. A lag between a change in exposure and a change in risk is often referred 

to as a latency in the risk. To address it, the life-cycle model can be further manipulated (see Alberini et al. 2006a) to show that the WTP for risk reduction in 

some future period is likely to be lower than the WTP for risk reduction in the 

current period for two reasons. First, there is a probability that the person will 

not survive to the age when the risk reduction is to be realized. And second, if 

the rate of time preference is positive, the prospect of future consumption has 

less current utility than present consumption. However, if WTP for some risk 

reduction increases with age faster than the discount rate, the current WTP for a 

future risk reduction would be larger than for a current risk reduction (Hammitt 

and Liu 2004). 

The models can provide insights into other key factors that affect WTP. 

WTP for a given risk reduction should be larger than WTP for a smaller risk 

reduction. However, the VSL is arithmetically the WTP divided by the risk reduction, so that simple relationship is not enough to predict whether the VSL 

will be lower (or higher) for a smaller risk reduction. The theoretical literature 

(Hammitt and Graham 1999) suggests that for small changes in mortality risk, 

WTP will move roughly in proportion to the size of the risk change, leaving the 

VSL roughly constant over different risk changes. However, empirical studies 

(see Hammitt and Graham [1999] for a summary and Alberini et al. [2004] for a 

more recent example) often find that the VSL is larger for smaller risk changes. 

The expected effect of greater income or greater wealth on WTP (and 

therefore the VSL) is unambiguous. Higher income (or greater wealth) is expected to increase WTP for a given risk reduction. No life-cycle models in the 

literature distinguish effects on WTP on the basis of sex, race, marital status, 

number of children, or other variables that one might hypothesize could affect 

WTP. However, the empirical literature has looked at some of those issues (see 

below). 

EMPIRICAL METHODS OF VALUING 

MORTALITY-RISK REDUCTIONS 

WTP is typically measured by analyzing the prices paid for goods and ser-
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Economic Valuation of Reduction in Mortality Risk 135 

vices. The maximum price that a person is willing to pay for a good or service is 

a measure of how much the person values the good or service. Prices for reducing or preventing mortality risks cannot be directly observed, because, for the 

most part, reduction or prevention of mortality risks is not directly purchased in 

the marketplace. However, there are instances in which the monetary tradeoffs 

that people are willing to make between income and mortality risks can be observed or measured, for example, higher wages for riskier jobs or higher prices 

for safer products. 

There are two general economic approaches to measuring WTP for nonmarket goods, such as changes in mortality risks. The first is to analyze actual 

situations in which WTP for changes in mortality risks may be indirectly revealed; this category of estimation approaches, which is based on behavior, is 

called revealed preference. The second is to have subjects respond to a hypothetical situation that is designed to have them reveal their WTP; this category, 

which is based on responses to survey questions, is called stated preference.3

Revealed-Preference Methods 

An example of revealed-preference methods is a wage-risk study in which 

wage premiums for risks of death on the job are estimated. This approach analyzes the factors that determine differences in actual wages between jobs, including on-the-job risks of death. The additional wages that people are paid per 

unit of additional risk of fatal injury is a measure of the monetary value of the 

additional risk to the person who voluntarily accepts the risk in exchange for a 

given wage increment. In this context, this value is equal to or less than his willingness to accept compensation (WTA) for incurring greater risk and is equal to 

or greater than his WTP for a reduction in risk (Hammitt, 2002).4

 The primary 

advantage of this type of study is that it is based on actual behavior. Some of the 

limitations are that it is difficult to find situations in which an observable tradeoff is made between income (or expenditures) and mortality risk and difficult 

statistically to isolate WTP for a mortality-risk increment from other factors 

involved in the specific behavior or decision. Fully specifying potential confounding factors in these kinds of decisions, such as associated decreases in 

rates of nonfatal injury or other benefits (such as reduced risk of property loss 

due to purchase of a home smoke detector), is one of the important challenges to 

 3

For more information on these estimation techniques, see Freeman (2003). 

4

When WTP and WTA are small compared with income, the theoretical expectation is 

that these measures will not be much different from one another for a given change in 

risk. In revealed-preference studies, that is generally the case. However, in statedpreference studies, responses to WTA questions are often much higher than responses to 

WTP questions. Concern that respondents are not forced to consider a budget constraint 

when answering WTA questions has led most analysts to prefer WTP questions in statedpreference studies.
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136 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

the estimation of WTP for mortality-risk reduction in revealed-preference studies. 

Many labor-market studies have examined the tradeoff between fatality 

risk and income; they are referred to here as wage-risk studies. The estimation 

method is important because it has been a primary source of the estimates that 

EPA has used for monetary valuation of mortality-risk reductions in environmental-policy analyses. The basic premise of wage-risk studies is that workers 

reveal the tradeoffs that they are willing to make between risk and income in the 

choices of jobs that they accept. The idea is simple, but the execution of a study 

is complex because many factors go into a job choice and a hiring decision. The 

safest jobs tend to be the highest-paying jobs because they require more skills 

and education. Other factors must therefore be taken into account, and this is 

done through estimation of a wage equation in which wage rates are specified as 

a function of worker characteristics, job and industry characteristics, and on-thejob fatality risks. 

Wage-risk studies do not directly estimate a VSL but rather a market equilibrium between wages and on-the-job risk that represents the intersection of 

labor supply (and the worker’s marginal demand for an increment in on-the-job 

safety) and labor demand (and the employers’ marginal cost to supply more 

safety). The result is an average value of a small change in risk of on-the-job 

fatality. The VSL is inferred from that “risk premium” as the total of the incremental wages paid to each worker per year to prevent one fatality in that year. 

With a few exceptions (Gegax et al. 1991; Liu and Hammitt 1999; Hammitt and Ibarraran 2006; who asked workers their perceptions of on-the-job 

risks), wage-risk studies presume that workers’ perceptions about risks on the 

job can be accurately measured by reported risks. Further, they presume that 

workers have sufficient information about on-the-job risks for their choices in 

the labor market to reflect responses to actual differences in risks across jobs. 

Using the results of those studies in policy analysis also presumes that the marginal value of risk reduction in the labor market is consistent with such values in 

the general population. For that reason, wage-risk studies that look at a broad 

cross-section of occupations and industries are preferred to studies that look at a 

narrower set of occupations and industries if the results are going to be used in 

policy analysis for the general population. Even so, if there is self-selection of 

high-risk occupations by those who are less risk averse, implying they demand 

less compensation than those in the general population do, then the wage-risk 

studies will underestimate the general-population VSL. 

Wage-risk studies are limited to examining the types of on-the-job fatalities that are recorded in available databases that cover a wide array of industries 

(for example, databases of the Bureau of Labor Statistics, worker compensation 

boards, and the National Institute for Occupational Safety and Health); these are 

primarily accidental deaths. Indeed, a large share of on-the-job fatalities occur 

while being in vehicles. Other causes of death that may be related to work, such 

as cancer and chronic illness related to on-the-job exposure, are more difficult to 

study and less likely to be included in available databases because of long lags 
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Economic Valuation of Reduction in Mortality Risk 137 

between exposure and death and because they are thought to be less frequent in 

most occupations. 

Stated-Preference Methods 

An application of stated-preference methods is a survey in which subjects 

are presented with a hypothetical situation that involves a tradeoff between income or expenditures and a change in the risk of death. In a direct statedpreference approach, subjects are asked to estimate what they would be willing 

to pay to change their mortality risk by a specific amount. Other statedpreference approaches ask respondents to choose among alternative scenarios or 

policies that have varied costs and amounts of risk reduction and thus reveal but 

not explicitly state their WTP values. In any stated-preference approach, it is 

important that the situation presented to study subjects be realistic and easy to 

understand. The primary concern about this type of study is whether subjects are 

able and have incentive to give accurate responses to questions of this nature 

and whether answers in the context of hypothetical situations are accurate predictors of behavior and choices in situations in which the costs and consequences are real. 

Many challenges exist concerning survey design for stated-preference 

studies about mortality risk. Difficulties in comprehension of small risks are 

often discussed. Corso et al. (2001) demonstrated the importance of visual aids 

in communicating quantitative risk information. Krupnick et al. (2002) used 

some simple comprehension questions to identify respondents who might be 

unable to understand or work with quantitative risk information. It seems that no 

matter how carefully the information is presented, some fraction of the general 

public has difficulty in making sense of it or is unwilling to put in the effort required. Another challenge is the WTP elicitation mechanism. Cues given in the 

survey can lead to starting point bias (Mitchell and Carson 1989) and different 

procedures can lead to different estimates (Champ and Bishop, 2006). Finally, 

some studies of illness-related health risks have used health-care changes as the 

risk-reduction scenario (e.g., Johnson et al. 1998; Krupnick et al. 2002; Alberini 

et al. 2004), and others have used relocation and cost-of-living changes (e.g., 

Viscusi et al. 1991). Stated-preference studies generally obtain lower mean 

VSLs than wage-risk studies (Kochi et al. 2006), but why this occurs is difficult 

to determine. 

Wage-risk and stated-preference studies have different strengths and 

weaknesses with respect to providing estimates of WTP for mortality-risk reduction for use in environmental-policy analysis. Wage-risk studies have the 

strength of being based on actual behavior, and many economists consider this 

an overwhelming advantage over stated-preference methods. However, they 

include only working-age adults who are healthy enough to be working, and 

they predominantly consider accidental death—a different population and a different type of risk from what may be associated with ozone. 
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138 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Stated-preference studies have the advantage of being able to be designed 

to address any type of mortality risk and can capture values for any population 

that is capable of answering the survey questions. Thus, there is a greater possibility of specifically addressing the type of illness-related mortality risks that are 

associated with pollution exposure and of including the older population that is 

expected to be at greatest risk. 

Methods for Estimating Values of Changes in Life Expectancy 

The above discussion focused entirely on how revealed- and statedpreference studies estimate WTP for annual mortality-risk reductions, which 

have generally been summarized by reporting average VSLs. The literature on 

the estimation of WTP specifically for changes in life expectancy (usually reported as VSLYs) is smaller. In the revealed-preference literature, specifically, 

the wage-risk studies, variation in the average age of workers in various occupations is used to identify life-expectancy differences across the working population and from that to estimate the wage premium for taking jobs that are riskier 

in terms of life-expectancy losses. Selection of workers into riskier jobs complicate the use of this information as a proxy for the VSLY in the general population and in a pollution context. Aldy and Viscusi (in press) found that on-the-job 

fatality rates vary by age and that taking this into account alters the estimation of 

wage-risk premiums by age group. Of course, since few workers are in the labor 

force beyond age 65, the VSLYs (and VSLs) estimated based on labor market 

data can only apply to the “near-elderly” (Evans and Smith 2006). Findings in 

this literature are reviewed below. 

For stated-preference studies to estimate WTP for reductions in risk defined as increases in life expectancy requires making respondents understand 

that they are valuing an increase in life expectancy over their remaining lifetimes (from a shift in the hazard function), rather than more time being simply 

tacked on to the end of life. Few have attempted this task, and evidence suggests 

that these attempts have not been successful (see below). 

In practice, most VSLY estimates used to value changes in life expectancy 

have been ad hoc and derived from estimates of the VSL. The most frequent are 

those that simply annualize the VSL, assuming a given rate of interest (time 

preference) and underlying life expectancy (Mauskopf and French 1991). Another approach is to convert the annual risk reduction being valued into its 

equivalent change in life expectancy and, using that metric together with the 

estimated WTP, to calculate the VSLY (Alberini et al. 2006b). The drawback of 

this approach is that were respondents to realize that their annual risk reduction 

of (say) 5 in 10,000 translates into a few weeks of additional life expectancy, 

their WTP might be different. 

The WTP for any risk reduction can be summarized as an average VSL or 

an average VSLY, given estimates of the rate of time preference and remaining 

life expectancy for the population from which the WTP values were derived. As 
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Economic Valuation of Reduction in Mortality Risk 139 

discussed below, the difficulties arise when either of these measures is applied 

to other populations or other risk reductions, assuming the value is always the 

same. 

ENVIRONMENTAL PROTECTION AGENCY’S CURRENT 

APPROACH TO VALUING MORTALITY-RISK REDUCTIONS 

Overview 

Since EPA first began doing Regulatory Impact Analyses using welfare 

economics rather than a human capital approach to monetizing reductions in 

mortality risks, the agency has used a uniform VSL, rather than different VSLs 

applied to different groups or risk contexts, or a VSLY, whether uniform or differentiated. The only exceptions have been in sensitivity analyses exploring alternative valuation estimates as detailed below. The reasons for EPA’s approach 

may be both practical and ethical. The early valuation literature did not support 

any but the simplest (VSL) approach to this valuation problem, and there was 

controversy even surrounding attaching monetary values to “life,” let alone applying different values to different groups (as would be implied by a life-year 

approach) or different risk contexts. Furthermore, the time-series epidemiological literature, which was all that was originally available for quantifying mortality risk changes from air pollution changes, could not support a life-years approach, as detailed in Chapter 4. 

In addition, EPA focused on the valuation of private rather than public 

goods, that is, on estimates of individual WTP for reductions in their own risks 

of death, not for those of society more generally. This choice was (and still is) 

consistent with the bulk of empirical literature (as addressed below) and the state 

of welfare economics (as noted above). 

Based on these choices, the agency has performed hundreds of RIAs, 

many arguably influencing agency decisions and even subsequent decisions over 

legislation in Congress. Furthermore, these choices have been ratified as the best 

practical options by all of the Science Advisory Board (SAB) panels EPA has 

asked to examine them, most recently in 2007 (EPA-SAB 2007), as detailed 

below. Thus, the present committee believes that these choices should not be 

overturned lightly and without significant evidence, both conceptual and practical, to support a defensible alternative. 

Recent Practice5

According to Robinson (2007), recently, EPA (2005a, 2007b) has used a 

 5

The discussion in this section contains text that is excerpted or summarized from a 

document by L. Robinson (2007). The discussion is also informed by another document 

by L. Robinson (2004). 
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140 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

central VSL that is a midpoint between results obtained in two meta-analyses of 

the wage-risk studies (Mrozek and Taylor 2002; Viscusi and Aldy 2003). It is a 

VSL of $5.5 million in 1999 dollars and at 1990 income levels, which is about 

$6.7 million in 2006 dollars.6

 EPA (2005a) noted that this VSL estimate is very 

close to the mean estimate reported in a third meta-analysis (Kochi et al. 2006), 

which included stated-preference and wage-risk studies. EPA’s previous VSL 

estimates were based largely on work completed in the early 1990s to support its 

retrospective and prospective analyses of the impacts of the Clean Air Act 

(CAA) (EPA 1997b, 1999a). Relying upon the work of Viscusi (1993), EPA 

selected 26 VSL estimates for its analyses; 21 of those estimates were derived 

from wage-risk studies and 5 from contingent-valuation studies. The mean VSL 

estimate based on those studies is $7.4 million, with a minimum of $0.9 million 

and a maximum of $20.9 million (in 2006 dollars). The 21 estimates from the 

wage-risk studies were scattered throughout that range, but the estimates from 

the stated-preference studies tended to be in the lower half of it. The mean VSL 

and distribution based on the review of the 26 studies were incorporated into 

EPA’s Guidelines for Preparing Economic Analysis (EPA 2000a). 

In assessments of the costs and benefits of the CAA (EPA 1997b, 1999a), 

EPA conducted a sensitivity analysis by using a constant VSLY and an estimate 

of life years saved by reductions in mortality related to particulate matter (PM), 

assuming average remaining life expectancy for each age cohort and using agespecific risk estimates. That reduced the estimated benefit of reductions in PMrelated mortality by nearly 50%. In another analysis, EPA (2000b) conducted a 

different sensitivity analysis by using VSL estimates that varied by age on the 

basis of empirical studies of WTP for mortality-risk reduction that showed WTP 

increasing with age up to about the age of 40, then decreasing (Jones-Lee 1989; 

Jones-Lee et al. 1993). Both sensitivity analyses obtained smaller benefit estimates because a large share of PM-related deaths are of people over 65 y old. At 

a given VSLY, for example, reducing the risk of death of an older person would 

have a lower value because fewer life years would be saved. In a sensitivity 

analysis for regulations addressing emissions from large spark ignition engines 

(EPA 2002), the agency used a more complicated approach that reflected initial 

results from the work of Alberini et al. (2004) as well as the adjustment factor 

from Jones-Lee (1989). In this case, EPA derived different estimates of VSLY 

for younger and older age groups from selected VSL estimates. The result was a 

higher VSLY for the older age group. EPA applied these VSLY estimates of 

 6

One change EPA has made in use of VSLs is adjusting the VSL for expected changes 

in real income over time (EPA 1999a). This adjustment is for secular changes in income 

over the economy, not for changes in individual circumstances over their life cycle, 

which would be already accounted for in an individual’s observed or stated preferences 

for paying for mortality-risk reductions. Specifically, EPA uses an elasticity estimate of 

0.4. For 2006 GDP per capita, that implies that the current central estimate of VSL is 

about $7.6 million in 2006 dollars and at 2006 income levels. 
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Economic Valuation of Reduction in Mortality Risk 141 

life-years saved for each age group. The net effect was a lower value for risk 

reduction for the older age group because the smaller remaining life expectancy 

more than offset the higher VSLY. These sensitivity analyses (particularly the 

age-adjusted VSL) created considerable controversy at one point when the practice was dubbed the “senior death discount” in the press (see, for example, 

Seelye and Tierney 2003). As a result, EPA stopped using age-adjusted VSL 

estimates even in sensitivity analyses. 

According to Robinson (2007), EPA is now revising the economic analysis guidelines and updating its approach for its next prospective analysis of the 

CAA. In an effort related to updating the process for selecting values for mortality-risk reduction for the guidelines, EPA asked its SAB to assess further several 

questions regarding the selection of estimates for use in valuation of mortalityrisk changes. To support the updating, EPA reviewed and summarized recent 

studies and meta-analyses in the VSL literature (Dockins et al. 2004). It also 

funded research on the robustness of estimates from wage-risk and contingentvaluation studies (Black et al. 2003; Alberini 2005) and from studies of averting 

behavior (actions that people take to avoid or mitigate risks, such as the use of 

seatbelts) (Blomquist 2004). EPA later convened a group of statisticians to address the use of meta-analysis (Allen et al. 2006) and reviewed the literature on 

the relationship between life expectancy and the VSL (Dockins et al. 2006). 

The SAB (EPA-SAB 2007) concluded that meta-analyses are useful for 

systematic assessment and analysis of factors that affect the results of wage-risk 

and stated-preference studies, including variations in methods, data sources, and 

study populations. It recommended that EPA consider results of meta-analyses 

and the context of relevant policy questions to develop selection criteria for 

studies in the literature that are methodologically sound and applicable to the 

policy questions. A mean or central tendency of VSL estimates from the studies 

could be calculated by using any of several weighting methods. The SAB further 

recommended that EPA not rely exclusively on either revealed-preference or 

stated-preference studies, but rather give weight to results on the basis of how 

well they address the policy questions at hand. The SAB panel cautioned against 

most quantitative adjustments of estimates from individual studies to account for 

differences in methods or population characteristics other than inflation and currency differences. If adjustments are made, the SAB panel recommended they 

be based on the results of individual studies rather than the aggregate results of 

meta-analyses. 

The SAB concluded that the relationship between VSL and remaining life 

expectancy requires empirical study because economic theory places no restriction on whether VSL increases, decreases, or remains constant as life expectancy decreases. It noted that because individual life expectancies can rarely be 

determined with much accuracy, it is necessary to focus on how VSL varies 

across a population in relation to age and health status, which are related to life 

expectancy. It concluded that the available literature is not sufficiently robust to 

support estimates of VSL that vary with age. It also recommended against using 

a constant VSLY, stating that “if there is insufficient information to indicate that 
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142 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

VSL declines with age, there is not sufficient information to indicate VSL is 

strictly proportional to remaining life expectancy.” And it recommended that 

EPA continue to use an age-independent VSL to value mortality-risk reductions 

but also report the age distribution of lives saved or the number of life years 

saved and fund more research on valuation of mortality-risk reductions in the 

context of environmental health risks. 

Limitations of EPA’s Approach 

Concerns and questions about EPA’s approach in monetizing mortalityrisk reductions in Regulatory Impact Analyses are the following: The WTP to 

reduce or avoid a unit change in mortality risk 

(i) is based on labor market studies that seem ill-suited to a policy context 

where at risk groups are children and the elderly; 

(ii) is uniform over different risk contexts (dreaded risks, voluntary risks, 

etc.); 

(iii) is uniform over different populations (by age, gender, race, income, 

region); 

(iv) counts premature deaths avoided rather than life-years extended; 

(v) is for a private good rather than a social good. 

These five points merit some individual discussion. 

(i) Most of the available empirical WTP estimates are for risks of accidental death in circumstances in which people are voluntarily exposed to risks (for 

example, in choosing a job or driving a car). VSL estimates drawn from wagerisk studies, the most common source of published VSL estimates, are for working-age adults who are well enough to be employed. The contexts of the available estimates and the contexts of most health-risk changes being evaluated in 

cost-benefit analyses of environmental regulations differ in some potentially 

important ways. For example, environmental health risks are related primarily to 

illness rather than accidents, and the risks tend to be more concentrated in the 

elderly population than are risks of accidental death. Differences in the characteristics of the people at risk, such as age and health status, may result in differences in the WTP to reduce their risk. 

(ii) People’s reactions to and attitudes toward risk have been shown in a 

substantial risk-perception literature to be affected by many attributes beyond 

the magnitude of the risk. Attributes that appear to be important in how subjects 

rate different risks include dread or fear related to the risk, the source of the risk, 

its voluntariness, whether and how well it can be controlled by a subject, and 

whether the mitigation measures are undertaken privately or as part of a broad 

government program (Slovic 1987; Cropper and Subramanian 1995). The litera-
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Economic Valuation of Reduction in Mortality Risk 143 

ture, however, tells us very little about how WTP to reduce mortality risk may 

vary with any of these risk attributes. 

(iii) The objective of an economic-benefits assessment is to develop an estimate of the aggregate WTP for the benefits of a policy that is the sum of the 

individual WTPs of all the affected people. People’s WTP values can differ because of differences in such things as income, wealth, age, health status, sex, 

race, and baseline risk. To meet the objective of a preference-based aggregate 

WTP, an analyst conducting a benefits assessment of an air-pollution control 

policy should, in principle, obtain estimates of WTP from each of the affected 

people. For ethical and practical reasons, government agencies generally do not 

adjust the WTP estimates they use to reflect these differences. A practical reason 

is the lack of knowledge of how WTP varies with individual characteristics. An 

ethical reason is a policy judgment that differences due to, say, income should 

not be relevant for policy. Typically, an average WTP for the population is used, 

making no explicit distinction in WTP across population groups. 

For example, economic theory predicts that individual WTP for risk reduction should increase with income. Taking account of that in estimating aggregate benefits would result in assigning higher values to reducing the risks to 

higher-income people if other items are equal. EPA and others have, for ethical 

reasons, decided not to take account of differences in income in estimating aggregate WTP and instead use the population mean WTP to calculate the aggregate benefits. 

Unobserved population heterogeneity that affects WTP is a more difficult 

problem. For instance, the wealth of an individual may affect their WTP, irrespective of their income. But wealth is difficult to measure in the best of circumstances and is not measured in WTP studies. If the elderly as a group are relatively wealthier than is apparent from their incomes, then their WTP would be 

overestimated in valuation studies relative to what it would be if wealth were 

held constant. 

(iv) Age as a population characteristic is singled out for debate based on 

two factors: (1) concern that deaths from air pollution apply primarily to those 

who would have died shortly anyway; counting these deaths as loss of much of a 

lifetime, therefore, seems like a gross overestimate; and (2) people would prefer 

to prevent the imminent death of a younger than an older person because the 

former have so many more years to live. The response to these positions is that 

(1) so-called short-term death displacement (or “harvesting”) has been shown to 

be unlikely to account for most of the mortality associated with ozone (see 

Chapter 4), and (2) the perspective on life years as a better, or more natural, metric is from a social perspective, not necessarily from the individual’s perspective, which is the preferred perspective for valuation in cost-benefit analysis. In 

any event, EPA, with some recent exceptions, has chosen to use a VSL metric 

that is not varied for differences in life expectancy rather than a VSLY metric to 

adjust for differences in life expectancy. 

(v) If one were to move to a social perspective on valuation, several problems would need to be overcome. They include a very thin literature to support 
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144 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

any specific monetary values and the inability to distinguish paternalistic from 

non-paternalistic altruism. 

EMPIRICAL EVIDENCE ON VALUATION OF 

MORTALITY-RISK REDUCTIONS 

The key conclusion from the theoretical analyses regarding valuation of 

mortality-risk reduction is that the most important questions for policy analysis 

cannot be answered without substantial empirical data. For most of those questions, the available empirical evidence is insufficient for supporting robust quantitative conclusions. This section discusses the empirical evidence that is available. 

Recent Meta-analyses of Mortality-Risk Valuation 

Three meta-analyses of the VSL literature (Mrozek and Taylor 2002; Viscusi and Aldy 2003; Kochi et al. 2006) overlap a great deal in the studies included, but each applied some unique analytic approaches, and there are some 

differences in how VSL estimates were selected from the literature. All the 

meta-analyses address VSLs, because the literature is too limited to do such 

analyses on VSLYs. Two of the analyses, Mrozek and Taylor (2002) and Viscusi and Aldy (2003), are limited to wage-risk studies. Kochi et al. (2006) include wage-risk studies and stated-preference studies and report results for each 

type of study and combined results. All three meta-analyses report mean VSL 

estimates. 

One of the challenges that complicated all three meta-analyses was that 

many studies report more than one VSL estimate based on different model 

specifications for analyzing the data. In addition, multiple publications are 

sometimes based on the same or similar data sources. Each meta-analysis addressed that issue in a different manner. Viscusi and Aldy selected one estimate 

from each publication according to what the authors indicated was their preferred result. Mrozek and Taylor included every VSL estimate from each publication but weighted them according to the inverse of the number of estimates 

from each publication. Kochi et al. conducted statistical tests for homogeneity of 

subsets of estimates by the same authors and took mean values from subsets that 

passed the test for homogeneity; using this process, they collapsed 197 VSL 

estimates (from 45 studies) into 60 mean estimates that were presumed to be 

independent for the purposes of the meta-analysis. 

All the meta-analyses reported results separately for U.S. and non-U.S. 

studies and adjusted the VSL estimates to the same-year dollars. Neither Mrozek 

and Taylor nor Kochi et al. compared results on the basis of differences in study 

population or risk characteristics. Viscusi and Aldy (2003) reported results of 

cross-study comparisons of the effect of sample average income on VSL results 
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Economic Valuation of Reduction in Mortality Risk 145 

and of within-study analyses of the effect of age. The possibilities of analyzing 

the effects of population or risk characteristics in the available literature are few 

because most of the studies are wage-risk studies, which are limited to workingage population and to risks of fatal on-the-job accidents. Only the statedpreference studies cover a wider array of population and risk characteristics, and 

the small number of such studies reduces the effectiveness of across-study comparisons. 

On the face of it, the three meta-analyses report a wide range of mean 

VSL estimates: around $3-10 million (in 2006 dollars). However, when results 

are based on the most comparable set of U.S. studies and the most comparable 

analytic approaches, the range of mean VSL estimates narrows considerably. All 

three meta-analyses report mean results from wage-risk studies in the United 

States, excluding studies that used the inappropriate Society of Actuaries data7

and studies that covered only high-risk occupations (such as police work). The 

mean VSLs that the meta-analyses report for this group of U.S. wage-risk studies in the literature are in the range of $8-10 million. 

Mrozek and Taylor argue, however, that many wage-risk studies have not 

included sufficient model specifications to account for unexplained differences 

in wages among industries and that this exclusion has caused upward bias in 

VSL results. They use their model to estimate the mean VSL if all the studies 

had used a more aggressive approach to control for differences in wages among 

industries. Their results suggest a mean VSL of about $3 million. Viscusi and 

Aldy point out that if unexplained differences in wages among industries correlate with differences in on-the-job fatalities, this could be part of the reason for 

the differences in wages. Thus, aggressive measures to include many industry 

dummy variables, for example, could cause downward bias in the risk coefficients in the wage function. The truth is probably somewhere in between—that 

is, the best mean VSL from the U.S. wage-risk studies is somewhere between $3 

million and $10 million, but it is hard to say exactly where. 

Kochi et al. provide important additional information on the VSL literature by including results from stated-preference studies. When considered alone, 

the stated-preference results reported by Kochi et al. have a mean VSL of about 

$3.3 million. That is at the lower end of the range of mean results of the wagerisk studies. Many of the stated-preference studies include subjects who are over 

65 y old and thus reflect the preferences of a wider segment of the general population than the wage-risk studies, which are limited to working-age adults. The 

stated-preference studies also cover different types of mortality risks, primarily 

those related to traffic accidents and illness. 

Another important difference is that the stated-preference studies examined by Kochi et al. include both U.S. studies and studies in other developed 

 7

Society of Actuaries mortality data include deaths from all causes, so they are inappropriate for use in wage-risk studies; what is needed is a measure of the risk of on-thejob deaths. 
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146 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

countries. They do not report U.S.-only results of the stated-preference studies, 

as they do results of the risk-wage studies, and their overall mean reflects studies 

in all included countries. Although those are all countries with relatively high 

income (such as Canada and England), differences in per capita income, wealth, 

and other factors could result in systematically different WTP results. For a better comparison with the U.S. wage-risk studies, it is preferable to use results of 

U.S. stated-preference studies. 

The authors provided a list of all the studies included in their analysis (R. 

Kramer, personal communication, 2006), which allowed further examination of 

this issue. The information they provided showed that only three of the eight 

stated-preference studies were done in the United States. Taking the results of 

those three studies (Viscusi et al. 1991; Hammitt and Graham 1999; Corso et al. 

2001) and adding results of two additional studies done in the United States 

(Ludwig and Cook 2001; Alberini et al. 2004) allowed the calculation of a mean 

VSL for U.S. stated-preference studies. Alberini et al. report the results of a U.S. 

application of the same survey instrument used in the Canadian study reported 

by Krupnick et al. (2002), which was included in the Kochi et al. analysis. The 

Ludwig and Cook (2001) results were added because, although Kochi et al. 

listed the study as not providing a standard error of their mean results, Ludwig 

and Cook did report a confidence interval from which we were able to calculate 

an approximate standard error. 

Some of the studies reported more than one VSL estimate based on different WTP questions or different model specifications. In those cases, an average 

result was calculated for each of the five studies. The weighted mean of the five 

U.S. estimates was then calculated by using the inverse of the standard error as 

the weight. The result was $6.2 million in 2006 dollars with a standard error of 

$1.2 million. That is considerably higher than the mean reported by Kochi et al. 

for all eight stated-preference studies and is close to the midpoint between Viscusi and Aldy’s mean VSL from U.S. wage-risk studies and the adjusted mean 

VSL from U.S. wage-risk studies reported by Mrozek and Taylor (2002). 

Kochi et al. report an overall mean VSL of about $5.4 million in 2000 dollars based on combining results from both types of studies. However, there are 

important questions about the usefulness of this combined mean VSL. The mean 

of both types of studies is to some extent an artifact of the number of wage-risk 

studies and the number of stated-preference studies. We see no reason for wagerisk results to be given more weight only because more of them have been done. 

If they measure something different, it is more important to ask which type of 

study is more likely to provide the VSL estimate that we want. It is an open empirical question as to why the results of wage-risk and stated-preference studies 

are different and whether the differences are statistically meaningful. It is not 

clear whether the differences in subjects’ ages or in the causes of risk are what 

cause the apparent differences in results, or whether differences in methods explain the different results. 
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Economic Valuation of Reduction in Mortality Risk 147 

Empirical Evidence on Effect of Age on WTP to Reduce Mortality Risk 

One of the most important questions related to estimating the benefits of 

reducing ozone-related mortality is how WTP to reduce mortality risk may vary 

with the age of the person at risk. Many of the available VSL estimates are for 

working-age adults, but illness-related mortality risk associated with ozone falls 

to a large extent on those over 65 y old. That is true even if the relative risks 

posed by ozone are the same for all ages, because the baseline risk of death from 

respiratory or cardiovascular illness is higher for those over 65 y old. This section summarizes the empirical evidence on how WTP for mortality-risk reduction varies with age, covering both stated and revealed preference studies. 

Stated-Preference Results Bearing on Effect of Age 

on WTP to Reduce Mortality Risk 

Krupnick (2007) has reviewed the stated-preference literature on the relationship between age and WTP for mortality-risk reduction. The review covers 

36 studies of populations in the United States and abroad and includes such 

studies as those of Alberini et al. (2004) and Chestnut et al. (2004a) that examined populations in both Canada and the United States. Most of the studies examined values for an immediate risk reduction and in a private-goods context. 

Most covered representative samples of people of all ages or of people over 

some age (such as 40 y) or oversample people over 60 y old. 

The age effects in this literature are measured according to a reference 

point: the difference (or percentage difference) in WTP for a given risk reduction in one age group compared with another age group. For example, the WTP 

of a 40 y old can be compared with that of a 70 y old, or the WTP of a group 

less than 65 y old can be compared with that of a group 65 y old and older. The 

effects are estimated either by studying the regression coefficient for WTP 

against age of the respondent after adjustment for other variables or by a subsample approach in which WTP is estimated separately for groups under 65 y 

old and over 65 y old and compared. The former approach, if correctly specified, 

estimates the effect of age independently of other factors, such as income, that 

may vary with age and also affect WTP. Stratification embeds all the factors that 

might correlate with age and also affect preferences for reducing mortality risks. 

The regression approach permits the analyst to test various specifications about 

how age affects WTP, including a quadratic specification that could test whether 

the expected inverted U-shaped relationship between WTP and age predicted in 

some theoretical analyses that used the life-cycle consumption model actually 

holds. The stratification approach often does not reveal those underlying relationships as cleanly, but it may not be important to know them. For instance, it 

may not matter in EPA’s regulatory decisions whether the elderly value risk 

reduction less than younger people because of differences in income, wealth, 

age, or anything else. If age is the only factor being used to adjust VSL esti-
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148 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

mates for a population at risk, stratification by age gives sufficient information 

for making such adjustments. On the other hand, it may not be appropriate to 

make such adjustments if income, gender, or race effects were embedded in 

them. 

The VSLs estimated by those studies range from $150,000 to $12 million 

(in 2006 purchasing-power parity-adjusted U.S. dollars), with an average of $2.7 

million and a median of $1.7 million. (These figures exclude one study that had 

an extreme VSL of $58 million.)8

 

Of the 26 most reliable studies that tested for age effects, 14 reported evidence of a senior discount effect and 12 found either no effect or a senior premium. In those finding a discount, the size of the effect is difficult to present 

consistently because studies describe the reference group and the age of the seniors differently. However, these studies show a clustering in the 20-35% discount range for WTP at age 70 y vs WTP at age 40 y. DeShazo and Cameron 

(2004) found a significant discount in the same range in a comparison of 65-yolds with 55-y-olds. However, WTP peaks at 55, rather than younger, as in Johannesson et al. (1997); and in other studies, the WTP is flat across the younger 

ages. Hammitt and Liu (2004) and Chestnut et al. (2004b) found a larger discount than the 20-35% cluster. Guria et al. (1999), with definite outlier results, 

found a far steeper discount. In absolute terms, the differences in the discount 

are wide. For instance, the gap between two studies is only 5%: a 35% discount 

(Johannesson et al. 1997) vs a 30% discount (Krupnick et al. 2007) at age 70 y 

relative to age 40 y; but in monetary terms, the senior discount is only about 

$400,000 for Krupnick et al. (2007) and almost $2 million for Johannesson et al. 

(1997). The fact that two teams of researchers—Chestnut et al. (2004a,b) and 

Alberini et al. (2004)—both surveyed large samples in both the United States 

and Canada and found significant senior-discount effects in only one of the 

countries (and for the opposite countries) does not instill confidence in the existence of a robust senior discount. However, both studies found negative (although insignificant) effects of age on WTP. If the null hypothesis were defined 

as the existence of a negative age effect, this hypothesis would not be rejected 

by the results of these two studies. 

The review also reported results of a series of models to examine factors 

affecting the likelihood that a particular study would find a senior discount. In 

the entire sample, studies with a large sample are more likely to find a senior 

discount, and in alternative specifications, this variable is quite robust. The average age of the sample is also significant (at the 10% level) but less robust. Both 

results suggest that a senior discount can be found if the sample is large enough 

and contains a large enough number of seniors. Finally, a dummy variable indi-

 8

Comparisons of VSLs among studies (or comparisons of absolute rather than relative 

senior discounts) require conversion of VSLs to common units. Krupnick first converted 

non-U.S.-dollar-denominated study results into U.S. dollars by using study-year factors 

for purchasing-power parity and then scaled the VSLs to a common base year (2006, 

second quarter). 
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Economic Valuation of Reduction in Mortality Risk 149 

cating that a quadratic specification was used is nearly significant. That means 

that the quadratic specification, which allows a nonlinear relationship between 

WTP and age, is better than a linear specification at capturing any seniordiscount effect that may exist. Overall, these results suggest that a deeper search 

for age effects through examination of alternative specifications for age might 

have found such effects. 

These inconclusive findings are similar to the conclusions reached by 

Dockins et al. (2004), who, in summarizing other reviews performed by EPA, 

wrote that “empirical work exploring the relationship between age and the VSL 

has provided mixed results.” They discussed the series of studies by Alberini et 

al. (2004) in the United States and Canada but otherwise examined only wagerisk studies. Another review of the literature (Evans and Smith 2006) offered the 

same conclusion, citing Alberini et al. (2004) and DeShazo and Cameron 

(2004): “These empirical analyses do not offer an unambiguous message.” 

Revealed-Preference Results Bearing on Effect of Age on WTP to Reduce 

Mortality Risk 

Aldy and Viscusi (2007) reviewed the empirical wage-risk literature about 

the relationship between age and WTP to reduce mortality risk. They note that 

most wage-risk studies reveal little about the relationship between age and WTP 

for mortality-risk reduction even when an age-interaction variable is included in 

the specification. That is because the simpler specification implies a linear relationship with age, which is expected only under the most restrictive assumptions. Thus, an informative analysis requires at least a nonlinear specification 

that allows VSL to be either rising or falling with the worker’s age. In addition, 

the authors note that rates of on-the-job fatalities also vary with age, so a comprehensive specification should take this into account. Although the overall onthe-job injury rate declines with age, the on-the-job mortality rate increases with 

age. Thus, both workers’ preferences for risk reduction and employers’ wage 

offers may vary with respect to workers’ age; thus, there may be different wagerisk market equilibria for different age groups. 

The authors report the results of their own analyses on this issue (Viscusi 

and Aldy 2007; Aldy and Viscusi in press) that allow the wage-risk equilibria to 

vary by age group. They find a consistent pattern of an inverted U-shaped relationship between VSL and age, with values for the youngest (18-24 y old) and 

oldest (55-62 y old) being roughly similar and the peak being about twice as 

high, usually in the middle age group (35-44 y old). Aldy and Viscusi (in press) 

note that the usual cross-sectional analysis does not take into account that expectations about future income and life expectancies vary with year of birth, both 

being higher in younger workers in the sample (given trends to higher income 

and longer life expectancies). They adjusted for those differences, and used the 

age-specific estimates of on-the-job fatality risk as described by Viscusi and 

Aldy (2007). They report that “the age-VSL relationship still follows an in-
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150 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

verted-U shape, but accounting for year of birth effectively rotates the shape so 

that younger workers now have a lower VSL; the curve peaks a little later in life 

(at age 46), and older workers now have a higher VSL. The oldest worker in our 

sample (age 62) now has a VSL that is 35 percent lower than a 46-y-old 

worker’s VSL, the peak value in this analysis.” 

Aldy and Viscusi (2007) note that if this result for the group of 55-62-yolds is applied to all adults over 55 y old, they obtain a result similar to what 

EPA obtained when it estimated a lower VSL for those over 65 y old in a sensitivity analysis of the proposed Clear Skies legislation (which would create a 

mandatory program to reduce power plant emissions of sulfur dioxide, nitrogen 

oxides, and mercury by setting a national cap on each pollutant (EPA 2006b). 

Aldy and Viscusi (2007) present several important conclusions from their 

review of the evidence in the wage-risk literature: 

• VSL varies with age in an inverted U-shape, as has been predicted in 

some life-cycle consumption models. 

• More flexible modeling that allows differences in both preferences and 

on-the-job risks according to age group results in estimates of VSL that decline 

less in older workers than was found in some of the earlier analyses. 

• None of the wage-risk results support the assumption of a constant 

VSLY. 

Implications of Results Regarding Age for VSLY 

The weight of the evidence suggests that there is insufficient information 

to make a reasoned decision to stop using a single VSL and switch to either different VSLs for different ages, a constant VSLY, which imposes a linear (discounted) relationship between life years remaining and the VSL, or a VSLY that 

varies with age groups. Nailing down these effects will take large samples and 

thorough studies. What seems clear from the stated-preference literature is that 

in a private-goods context, there is no justification for use of a constant VSLY 

that is applied to all life years for all age groups. None of the study results are 

consistent with the assumptions that underlie a constant VSLY. These results do 

not rule out non-constant VSLs or VSLYs. 

EPA’s SAB (2007) reached similar conclusions and recommended against 

quantitative adjustments to VSL estimates by age because of inconsistencies in 

the available empirical results. However, it urged EPA to support more research 

on the question and argued that a variation in VSL with age should not be ruled 

out on theoretical grounds. It also recommended against a constant VSLY, noting that the empirical evidence does not support the assumption that VSL is proportional to remaining life expectancy, which is an implicit assumption when a 

constant VSLY is used. 

We stress that the wage-risk studies discussed here do not include large 

numbers of people over 65 y of age, because many of them are not in the work-
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Economic Valuation of Reduction in Mortality Risk 151 

force. Thus, it is difficult to draw conclusions about how the VSL may differ in 

those over 65 y old from the wage-risk evidence because this would necessitate 

extrapolating beyond the age range in the studies. 

Some analysts have advocated that EPA consider using quality-adjusted 

life years (QALYs) as a way of measuring mortality and morbidity risks in costbenefit analyses. The QALY is a metric that blends life years saved with the 

quality of the life years when a person experiences acute or chronic disease. 

Death is generally given a value of 0, and perfect health a value of 1, although 

some indexes (for example, disability-adjusted life years [DALYs]) reverse this. 

Some QALY indices also permit scoring of health states that are “worse than 

death,” that is, get less than a zero score. An Institute of Medicine (IOM 2006) 

panel commissioned by EPA with support from OMB to examine the role of 

QALYs in regulatory cost-benefit analyses made several recommendations that 

bear on the usefulness of this metric. The IOM panel noted that QALYs provide 

a useful perspective on the impacts of regulatory actions but that this is only one 

perspective. Other perspectives are also useful, such as monetary-benefit measures. The IOM panel was not asked to compare a life-years-saved metric with a 

lives-saved metric and did not do so. However, it did note, as has other literature 

(Hammitt, 2007), that cost-effectiveness with QALYs as the effectiveness 

measure should not be termed a “cost-utility” analysis, as in common practice, 

because to do so implies that the QALYs are a welfare measure (meaning, in a 

practical sense, that it would rank alternative projects in the same order as a 

benefits analysis). In fact, the conditions for this to be true are quite restrictive: 

for instance, life years need to be additive in the utility metric no matter who 

experiences them, how many are experienced by a given person, and when. 

The IOM report recommended strongly against a common practice used to 

“convert” a QALY metric (life years lost) to dollars, specifically against putting 

a monetary value on a QALY. The concern was about mixing the medicalpractice and welfare paradigms and about how the literature on monetary values 

does not support treating all life years saved as equally valuable (that is, a constant VSLY approach). A consequence of this medical paradigm, as voiced by 

the committee that authored the IOM report, is that QALYs implicitly put less 

value on mortality reductions in older people (because their life expectancy is 

lower than that of younger people’s) and in those with existing chronic illness 

(because, owing to the quality adjustment, a life year extended for them is worth 

less than it would be if they were healthy). That practice is in direct conflict with 

the literature on WTP for mortality-risk reductions inasmuch as WTP is found to 

change less than proportionally with life expectancy and to be no different or 

even greater in the chronically ill compared with the healthy (see below). 

OMB requires cost-effectiveness analysis in addition to cost-benefit analysis in regulatory-impact analyses of major rules and suggests that costeffectiveness analysis be considered in all cases for comparisons of alternative 

regulations under discussion. Cost-effectiveness analysis defines the primary 

goals of the regulatory effort in some unit of measure that is not monetized. 

Costs of the alternatives are then compared on the basis of the cost per unit of 
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152 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

benefit expected. For mortality risk, OMB notes that the units may be lives 

saved, life years saved, or QALYs, but it does not recommend one metric over 

the others. Unlike cost-benefit analysis, cost-effectiveness analysis does not allow calculation of net benefits, but it can help in selecting the most efficient 

regulatory alternative for achieving a given goal. Thus, it is most useful in comparing programs with goals that can be quantified with the same metric. When 

there are multiple important benefits of a regulatory effort and those other benefits can be monetized, they can be netted out from costs first, for a net costeffectiveness analysis. Hubbell (2006) illustrates an attempt at cost-effectiveness 

analysis using QALYs for an air-pollution control rule (the heavy-duty engine 

and diesel-fuel rule). He included monetary valuation with a non-constant value 

per life year as an illustration but noted that there is a great deal of controversy 

regarding the appropriate way to infer welfare-based monetary values for 

VSLYs from the available VSL literature. 

Empirical Evidence on Effect of Health Status on WTP 

to Reduce Mortality Risk 

Few empirical studies have examined the effect of health status on WTP to 

reduce mortality risk. Alberini et al. (2004) and Krupnick et al. (2002) provide 

the most thorough examination of the question in stated-preference studies. 

They used the same survey instrument in the United States and in Canada and 

looked at the potential effect of several health-status measures on WTP responses, including family history of noncancer chronic disease, family history of 

cancer, personal history of hospitalization for heart or lung illness, personal history of high blood pressure, and widely used indices of physical and mental 

health (drawn from the SF-36 questionnaire). At times, a history of illness, either personally or in the family, was associated with higher WTP to reduce mortality risk, although not all the health measures were statistically significant and 

the significant measures differed between the U.S. and Canadian studies. 

Underlying the question of the effect of health status on WTP to reduce 

mortality risk is the concern that people who are chronically very ill may have 

such a reduced quality of life that they do not attach as much value to a policy 

that would extend life. The studies noted above do not address that question 

well, because the samples are drawn from the general population and include 

few very ill people. One small study that sheds a little light on the question is by 

Tsevat et al. (1998). They asked hospitalized patients over 80 y old and their 

caregivers and family members to estimate tradeoffs that they would be willing 

to make between improving quality of life and extending life. The authors were 

surprised to find that patients put a higher value on extending life (relative to 

improving quality of life) than did the caregivers and family members. That 

suggests that the WTP to reduce mortality risk is not necessarily decreased and 

may be increased when quality of life is diminished. 
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Economic Valuation of Reduction in Mortality Risk 153 

Evidence on Effect of Risk Latency on WTP 

There is little evidence on the effect of risk latency on WTP to reduce 

mortality risk, because few empirical studies have examined it. As illustrative of 

this literature, Alberini et al. (2006a) used results of their contingent-valuation 

studies in Canada and the United States to investigate the issue. The latent-risk 

question, which asked respondents under 60 y of age whether they were willing 

to pay some stated amount for a given reduction in risk starting at the age of 70 

y and lasting 10 y, followed two questions on WTP for immediate risk reductions. They found that delaying the time at which the risk reduction would occur 

by 10-30 y reduced WTP by more than 60% in respondents in both samples of 

people 40-60 y old. The implicit discount rates are equal to 3.0-8.6% in Canada 

and 1.3-5.6% in the United States, in contrast with earlier estimates of the discount rate in risk-reduction tradeoffs, which ranged from 0.3% (Johannesson 

and Johansson 1996) to 14% (Viscusi and Moore 1989). 

Studies to Estimate WTP for Increases in Life Expectancy 

Analysts have pointed out that quantifying the effect of changes in pollution exposure as annual changes in numbers of deaths in a population obscures 

the dynamic dimension of the change in exposure and its overall effect on mortality over time (e.g., Brunekreef et al. 2007). A more comprehensive way to 

describe the effect is as a shift in the survival curve over time. For the individual, that means an increase in the probability of surviving over all future periods 

and thus extending life expectancy. Of course, death is not prevented for the 

individual; rather, future survival probabilities increase, and death is more likely 

to occur at a later age. This can be summed up as a change in life expectancy, 

but it may also be described as a change in annual mortality rates over some 

extended period. Chapter 4 notes some unresolved issues about how best to 

characterize the change in mortality risk in the population as a result of a reduction in pollution exposure. In particular, several authors have raised concerns 

that the number of deaths prevented is not a stable measure over time (e.g., 

Miller and Hurley 2003; Rabl 2006) and have argued that a better measure 

would be the increase in life expectancy or life years saved. Economic valuation 

of the reduction in mortality rate can be derived directly from available WTP 

studies, which provide WTP values to reduce annual mortality risks. However, 

economic valuation of changes in life expectancy are not as straightforward and, 

with stated-preference approaches, are difficult to communicate to respondents, 

although these issues could perhaps be addressed with further empirical research. 

A few stated-preference studies have tried to estimate WTP values for 

changes in mortality risk that are presented to respondents as changes in life 

expectancy (Johannesson and Johansson 1996; Johnson et al. 1998; Morris and 

Hammitt 2001). To define a change in life expectancy that is the same for 
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154 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

everyone, those studies have defined a change in risk that starts at a future age, 

such as 60 or 70 y, and asked respondents what they would pay now for this 

future risk reduction that increases their life expectancy by some specified 

amount. The results are difficult to interpret. Comments from respondents suggest that some share of them dismiss the risk reductions as too small to be 

worthwhile. There appears to be a tendency to view an increase in life expectancy as adding time at the end of life when quality of life may be diminished 

rather than recognizing that an increase in life expectancy means an increase in 

the probability of survival in all future periods. The WTP questions seem to be 

additionally confounded with the presentation of a risk reduction that does not 

begin to have benefits until some years in the future. Morris and Hammitt (2001) 

made an interesting comparison between presenting a continuing annual risk 

reduction (to half the respondents) and an equivalent increase in life expectancy 

(to the other half of the respondents), both starting at the age of 60 or 70 y for a 

hypothetical pneumonia vaccine. They presented a 0.2% annual risk reduction 

starting at the age of 60 y or an 11-month increase in life expectancy (after getting the vaccine at the age of 60 y); for another portion of the sample, they presented a 0.2% annual risk reduction starting at the age of 70 y or a 5-month increase in life expectancy (after getting the vaccine at the age of 70 y). The 

substantial lag between the payment and the beginning of the risk reduction (an 

average of 25 y in the sample, which had a mean age of 40 y) confounds the 

interpretation of the results. The WTP results for the two risk presentations were 

not very different in those who said they would consider paying now for the 

future vaccine, but respondents who received the life-expectancy version were 

more likely to say that they would not consider getting the vaccine (33% vs 

26%). The most common explanation was that the benefit was too small. Compared with many risk-reduction efforts that people routinely undertake (such as 

cancer screening and wearing seat belts), the benefit is actually large, so the response raises some questions about the presentation. For example, Corso et al. 

(2001) demonstrated that visual aids are useful and needed to help respondents 

to understand quantitative risk information. 

Alberini et al. (2006b) report VSLY estimates derived from WTP values 

obtained in a stated-preference study conducted in France, Italy, and the UK 

regarding annual mortality-risk changes over a 10-y period. The VSLs for the 5-

in-1,000 risk change over 10 y were a mean of 2.3 million euros and a median of 

1.1 million euros. Using subjects’ own perceptions of their life expectancies, the 

authors calculated the implied VSLY and obtained a mean of 142,000 euros and 

a median of 58,200 euros. However, they found that the VSLY was significantly 

higher in those 60 y old and older (27% above those 40-49 y old). It is notable 

that the 10-y mortality-risk change converts to a different life-expectancy 

change in each age-sex cohort. It remains unclear whether the conversion from a 

WTP for the risk change to a VSLY for the associated change in life expectancy 

is the appropriate way to obtain this value. 

Analysts in Europe (Bickel and Friedrich 2005) report using results from 

Alberini et al. (2006b) as the basis of their estimates of VSLY in the 2005 up-
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Economic Valuation of Reduction in Mortality Risk 155 

date of the method for estimating externalities of energy. They used the estimates after presenting their argument that it is preferable to estimate the mortality effect of air pollutants on the basis of changes in life expectancy. Their selected central estimate of 50,000 euros per life year was derived from the 

median WTP value for the 5-in-1,000 mortality-risk change over 10 y (median 

VSL, about 1.1 million euros). The ExternE authors converted the 10-y mortality-risk change to its equivalent in increased life expectancy for each age-sex 

cohort and calculated the VSLY implicit in the WTP responses. It is notable that 

their selected central estimate was based on one of the lower WTP results because it was based on the median rather than the mean value and on the 5-in1,000 10-y risk reduction rather than the 1-in-1,000 10-y risk reduction. The 

VSLY based on the mean value for the 5-in-1,000 reduction was about 125,250 

euros (the associated VSL was about 2.3 million euros). The authors note that 

the WTP questions in this study include an implicit latency in that the risk reduction occurs over a 10-y period. Using an assumed 3% discount rate, they 

calculated that the undiscounted VSLY based on the median VSL would be 

about 75,000 euros rather than 50,000 euros. They concluded that the latency 

was appropriate for valuation of a reduction in mortality risk posed by long-term 

PM exposure. As a high estimate, they used 150,000 euros, derived from the 

WTP responses in the UK survey to the 1-in-1,000 10-y risk reduction (the associated VSL was about 3.3 million euros). 

They based their low estimate on results from the study in France, which 

included a WTP question specifically for changes in life expectancy. Details of 

the estimation approach have not been published, so it is difficult to evaluate. 

Desaigues et al. (2004) reported VSLY estimates ranging from 20,000 to 

220,000 euros, depending on the underlying change in life expectancy implied 

in the different questions included in the French survey. The ExternE analysts 

note that the WTP question for life-expectancy increases stressed that it did not 

mean just a few months at the end of life: “A crucial point that needs to be explained very carefully in such a questionnaire is that air pollution mortality does 

not cut off a few months of misery at the end of life but causes ‘accelerated aging’” (Bickel and Friedrich 2005, page 44). The low estimate of VSLY selected 

by the authors for use in the recent ExternE assessment is a value of about 

20,000 euros per year of additional life expectancy. Although the ExternE analysts selected a range of VSLY estimates, they used an approach that presumes a 

constant VSLY, which ignores the evidence that this value is likely to vary with 

age. 

FINDINGS AND RECOMMENDATIONS 

Finding: The charge to this committee concerns monetary valuation of 

mortality-risk reduction for regulatory impact analyses that are based on the 

basic premises of cost-benefit analysis. In this context, therefore, we focus on 

WTP values for mortality-risk reduction. Cost-benefit analysis, however, fo-
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156 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

cuses on economic efficiency, and many other ethical and legal factors are appropriate to consider in policy and regulatory decisions. In general, these issues 

should be considered separate from the cost-benefit analysis rather than interjected into the valuation estimates because this endangers the neutrality of the 

analysis. However, there may be some instances when such interjection is appropriate. For example, the decision by EPA to not adjust WTP estimates for 

local differences in income levels is justified because to do so creates a situation 

that favors greater environmental protection in wealthier locations, an outcome 

policy makers judge to be unfair and in many cases illegal. 

The committee stresses that government decision-makers need information on how the WTP for mortality-risk reductions varies by risk characteristics, 

population characteristics, and for both risk as a private good and as a public 

good. How they choose to use this information, however, is not strictly a technical decision, but depends on ethical precepts, legal precedent, the quality of the 

evidence and other factors that may be beyond the analysts’ control or purview. 

Recommendation: We recommend that this finding of the committee be 

considered within OMB and the agencies that use monetary values for mortalityrisk reductions in their regulatory analyses. These agencies should develop a 

plan for generating the information needed to determine how WTP varies for 

different populations and different risk contexts. In addition, there should be an 

exploration and debate to determine the appropriate uses of this information. 

Such a debate should go beyond economic considerations and include ethical 

and public policy perspectives. 

Finding: Both economic theory and the empirical evidence are inconclusive about how individuals’ WTP for reducing their own risk vary with two important individual characteristics: age as a proxy for remaining life expectancy 

and health status. Although we conclude that the empirical evidence is insufficient to support a specific quantitative adjustment to the WTP for reduction in 

annual mortality risk based on differences in remaining life expectancy, we do 

not reject the concept that such adjustment may be appropriate. It is plausible 

that people with less remaining life expectancy are willing to devote less of their 

resources to reducing their mortality risk than those with more remaining life 

expectancy. 

Characteristics of the risk that may affect individual WTP values include 

the type of risk (such as illness or accident) and its latency. The literature is inconclusive about the influence of risk characteristics (see below). The effects of 

latency on WTP values are straightforward conceptually (the WTP for a future 

death-risk reduction should be less than the WTP for an equivalent immediate 

death-risk reduction), and there is some published support for such estimates. 

However, the epidemiology literature is not sufficient to estimate the degree of 

latency in mortality response to ozone exposure. 

Recommendation: Despite many concerns about the accuracy of using 

the same WTP value (or range of values) for all mortality-risk reductions, we 

recommend this, with appropriate scaling to the size of the risk change, as the 
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Economic Valuation of Reduction in Mortality Risk 157 

most scientifically supportable approach for monetary valuation of ozone-related 

mortality, given the currently available information in the economics and epidemiology literatures. Empirical evidence of how WTP varies with population 

or risk characteristics is not sufficiently consistent to support a change in this 

practice that EPA has been using for many years. Researchers should continue 

to explore how WTP for mortality-risk reduction may vary with personal characteristics (such as age and health status), with the type of risk (such as accident 

and illness), and with its latency. This most likely implies more statedpreference studies to include the elderly population. 

Finding: The use of a constant value for life years saved in the valuation 

of increases in life expectancy requires the assumption that WTP values for mortality risk reductions be consistently declining with increasing age. The empirical evidence does not support that assumption and therefore does not support the 

use of a constant VSLY. The literature does not reject the use of a non-constant 

VSLY, however. And the epidemiological literature (see Chapter 4) may favor 

reporting life years saved. 

Recommendation: Unless future research produces empirical support for 

the assumptions that underlie a constant VSLY, EPA should not attempt to adjust for remaining life expectancy by calculating life years saved and applying a 

constant VSLY. It may be appropriate to calculate and report life years saved (in 

addition to reporting lives saved or changes in annual mortality rates), but it is 

not appropriate to use a constant VSLY as a monetary valuation of life years 

saved, except perhaps in a bounding exercise. The committee cautions against 

use of such an analysis in anything but a sensitivity analysis, however (see below). There is likely to be good reason to use a non-constant VSLY or a nonconstant VSL, once the empirical literature is sufficient to support this transition. The committee stresses, however, that the status quo of using a uniform 

VSL should be continued until there is sufficient empirical evidence of how 

WTP for mortality-risk reduction varies with differences in remaining life expectancy and other factors, which the committee concludes is not yet available. 

Finding: Most of the revealed-preference and stated-preference studies relied on by EPA to obtain estimates of the VSL have estimated these values for a 

context (such as traffic accidents or workplace accidents) and for a population 

that differs, for example, by age, health status, and income, from the population 

facing the pollution-related risks that EPA is assessing. Applying the available 

estimates in EPA’s assessments in different contexts of risks (such as illness vs 

accident) and population characteristics (such as age) introduces considerable 

uncertainty about how these factors affect the average WTP values. However, 

the current literature is inconclusive as to how and how much the WTP values 

may vary with those factors. 

Recommendation: The use of average WTP estimates selected from the 

literature should reflect results from both revealed-preference and statedpreference studies, take into account the strengths and weaknesses of each ap-
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158 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

proach, and consider how closely the studies match the policy context in population at risk and type of risk. Given the limited studies available for different risk 

contexts, it is difficult to say how much the WTP values may differ, but wagerisk studies are a poor match to the population and the risk context for the 

ozone-mortality case. EPA should give less weight to these studies in selecting 

WTP estimates than it has in the past. 

Finding: The direction of the expected error, if any, in using the average 

VSL in the literature for valuing changes in ozone-related mortality risk is more 

likely to be toward overstating the WTP to reduce this risk. That is because 

greater mortality risk associated with ozone appears to be in the elderly population and because latent risk may be involved. The remaining life expectancy in 

this population is substantially less than that in the population as a whole, and its 

WTP to reduce mortality risk might also be less. However, the lower WTP as a 

result of lower remaining life expectancy in the elderly may be offset to some 

extent by higher WTP because of poorer health status or higher baseline risk. 

Although results in the empirical literature are not consistent, several studies 

suggest that WTP to reduce mortality risk does not change or declines slightly 

with age. The evidence suggests that, for ozone, a proportional adjustment of the 

VSL for remaining life expectancy (that is, using a constant VSLY) would result 

in WTP that is too low. 

Recommendation: Given the uncertainty in available VSL estimates for 

ozone-related mortality, it is appropriate to conduct some sensitivity analyses 

with alternative estimates or assumptions. The purpose of sensitivity analyses is 

to see whether the overall conclusions of the cost-benefit comparison are 

changed, for example, whether net benefits are still positive under alternative 

economic-valuation assumptions. In general, there is less confidence in the sensitivity analyses because the alternative assumptions are more speculative than 

the primary assumptions or deviate from the status quo, which the committee 

feels puts a burden of proof on those who would overturn it. By definition, sensitivity analyses should be given less weight in the presentation of results. However, they can be included in the summary and conclusions. The selection of 

alternative assumptions for the sensitivity analyses can be based on either theory 

or evidence. For example, different published empirical estimates of the relationship between WTP for mortality-risk reduction and age could be selected as 

illustrative of the range of published results, including estimates of VSLY or 

VSL that vary with age. 

RECOMMENDATIONS FOR FUTURE RESEARCH 

The above recommendations for EPA imply research needs for estimating 

the WTP for changes in mortality risk and for changes in life expectancy. They 

also imply that the research primarily should use stated-preference methods, 
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Economic Valuation of Reduction in Mortality Risk 159 

although researchers may find ways to address the issues with further development of the revealed-preference approach. 

A fundamental need is to understand better how age and remaining life 

expectancy affect WTP for reductions in mortality risks or increases in life expectancy. One step would be to ask that future (or even previous) studies report 

total age effects—that is, WTP by age cohort—in addition to marginal effects of 

age on WTP. Given the correlation of age with some of the other factors, there 

may be less uncertainty in the estimates of a total age effect. However, agerelated income differences, sex differences, health differences, and the like 

would then be embedded in the estimates, and it might not be appropriate to use 

different VSLs that have these effects embedded. 

Several recent studies (e.g., Alberini et al. 2004) have looked qualitatively 

or quantitatively across the valuation literature to assess age and other effects. 

The assessments have been hampered by issues in the reporting of information 

and the lack of availability of the datasets produced. Future research funded by 

EPA should urge that its datasets be made available for meta-analysis. 

More fundamental research is needed to explore and develop methods for 

communicating and valuing changes in mortality risk that reflect the full life 

cycle. Studies to date have focused on WTP for annual changes in mortality risk, 

but the risk change of interest in most pollution-control assessments is more 

comprehensively described as a shift in the survival curves, which are plots of 

survival probability in all future periods and from which life expectancy is derived. That poses a challenge for stated-preference studies. A few studies have 

used changes in life expectancy to define mortality-risk change (e.g., Johannesson and Johansson 1996; Morris and Hammitt 2001), but many respondents 

seem to dismiss these changes as time added at the end of life, when quality of 

life may be substantially reduced. DeShazo and Cameron (2004) included multiple periods in their presentation of risk changes in an ambitious and innovative 

stated-preference study; analysis of their results has not yet been published. 

It is also important to learn more about how mortality-risk characteristics 

affect the valuation of reducing risk. Environmental-benefits assessments have 

relied primarily on estimates of WTP to reduce risk of accidental death to estimate values for reducing risk of illness-related death. A few studies have compared values of WTP (or nonmonetary preferences) to reduce risk in different 

contexts (e.g., Magat et al. 1996; DeShazo and Cameron 2004), and more studies along these lines are needed. 

Studies in a public-goods context that can isolate the effect of the age of 

those who benefited on the WTP of respondents for programs that reduce mortality risk in the community might help to resolve this issue as well. But in addition to such studies, we would need approaches to distinguish paternalistic from 

non-paternalistic altruism (as defined in Jones-Lee 1991) if double-counting of 

benefits is to be avoided. Conceptual analysis would be needed to understand 

how such results might be appropriately used in cost-benefit analysis, in which 

the usual paradigm is to sum private WTPs of the beneficiaries. 
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160

6 

Overall Conclusions and Recommendations

The committee’s statement of task (see Chapter 1) presents specific questions that were addressed by the committee in Chapters 3-5. This chapter discusses the overall conclusions and recommendations developed in the earlier 

chapters in the context of the regulatory benefits-assessment process. It also 

discusses implications for future Environmental Protection Agency (EPA) regulatory impact analyses (RIAs) that include changes in ambient ozone concentration.1

 

Part of the committee’s charge was to evaluate recent analyses of epidemiologic studies that found a modest but consistent relationship between shortterm ozone exposure and premature mortality. During its deliberations, the 

committee was mindful of the information needs and framework for benefits 

assessment. There is a fundamental difference between information needed for 

regulatory benefits assessment and information needed to set a protective health 

standard. Selection of a health-based standard focuses on the lowest ambient 

concentration that poses a risk of adverse health effects in the most sensitive 

population, whereas benefits assessment uses information to estimate all the 

health-risk reductions in the entire population that is expected to experience a 

change in ambient concentrations. 

OZONE MORTALITY EFFECT 

In carrying out its charge, the committee considered not only the recent 

epidemiologic evidence, but also toxicologic and pathophysiologic evidence that 

points to mechanisms by which ozone may contribute to premature mortality. As 

a gas, ozone is highly reactive, and once inhaled it is immediately engaged in the 

respiratory tract by the epithelial fluids and cellular membranes that it contacts. 

 1

In this report, ozone is used to refer to the broad array of photochemical oxidants in 

ambient air, of which ozone is the primary component. 
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Overall Conclusions and Recommendations 161 

Because ozone does not penetrate cells but leads to pulmonary and nonpulmonary events, a cascade mechanism has often been proposed to account for its toxicity. Human chamber and toxicologic studies have yielded strong evidence indicating that short-term exposure to ozone can exacerbate lung conditions, 

causing illness and hospitalization, and potentially lead to death. The available 

evidence on ozone exposure and exacerbation of heart conditions, which is less 

abundant, points to another concern. 

Epidemiologic studies also have found that exposure to ozone (as an indicator of the broader mix of photochemical oxidants) is associated with those 

effects. Although methodologically somewhat different, the studies have been 

consistent in their use of large datasets with consistent diagnostic codes for 

health end points, nationally available ambient air measures, and data on adjustment for some potential confounders. The committee found that the four 

recent time-series analyses and meta-analyses of the relationship between exposure to ozone and premature mortality add to that evidence by providing robust 

statistical evidence of an association (Bell et al. 2004, 2005; Ito et al. 2005; 

Levy et al. 2005). 

On the basis of the additional insights obtained from its review of the 

new time-series studies and its review of the broader evidence, the committee concludes that short-term exposure to ambient ozone is likely to contribute to premature deaths. Despite some continuing questions about the evidence, the committee concludes that it is strong enough to be used in the 

estimation of the expected mortality risk reduction that would result from reduction in exposure to ozone or the photochemical-oxidant mixture. 

In its RIA for the finalized ozone national ambient air quality standards 

(NAAQS), EPA (2008b) analyzed a variety of assumptions about the association 

between ozone exposure and premature mortality. They included the assumption 

that the association is not causal (see Appendix B). Although it is rarely possible 

to exclude the possibility of zero effect in such analyses, the committee concludes that an absence of any effect is unlikely. 

INTERPRETATION OF RESULTS OF HEALTH STUDIES 

Those who evaluate regulatory benefits seek information from health researchers, for example, 

• To what extent is the relationship between ambient ozone concentration 

and mortality response due to ozone as opposed to copollutants that are quantified separately, such as airborne particulate matter (PM)? 

• Given that age and health status are important in estimating the quantity and quality of the remaining life expectancy, how dependent is the ozonemortality relationship on those and other personal characteristics, such as socioeconomic status? 
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Studies relating measurements of ambient ozone to health end points must 

deal with formidable obstacles because the dynamics of ozone and associated 

pollutants are complex, particularly the effects of temporal and spatial variations 

on individual human exposure. The committee reviews below the major factors 

that it considered in its review of the evidence. These factors can affect estimates of risk of ozone mortality in various ways. In some cases, the factors 

would cause an underestimation of risk; in other cases, an overestimation. On 

balance, the committee considers the evidence from the studies to be strong 

enough for making risk estimates, but the various factors and their potential effects on the estimates should be fully acknowledged. 

Estimating Exposure to Ambient Ozone 

Time-series epidemiologic studies of ozone typically characterize exposures in terms of ambient concentrations at a centrally located monitoring site or 

at several sites in the study area. That use of ambient concentrations to indicate 

ozone exposures is a source of considerable uncertainty related to how well they 

reflect actual ozone exposures and how well ozone effects can be separated from 

effects of other pollutants or weather conditions. 

The magnitude of exposure errors probably varies with several factors, including season, home ventilation characteristics, and exposure averaging time. 

Ozone’s mortality effects, for example, were shown to be stronger in the warm 

season than in winter or the entire year.

Over 24 h, personal ozone exposures are weakly associated with corresponding ambient concentrations, and the association is stronger in summer than 

in winter. The seasonal variability probably reflects increased home ventilation 

in the hotter summer months. Even in well-ventilated conditions, however, the 

ozone association is such that only minor changes in indoor ozone exposures are 

expected to occur in response to moderate changes in outdoor concentrations. 

Together, low personal exposures and weak relationships between personal 

exposure concentrations and ambient concentrations suggest that 24-h ambient ozone concentrations are poor proxies for personal exposures. 

For shorter averaging periods, such as the afternoon (when both personal 

outdoor activity and ozone concentration can be at their highest), results from a 

scripted exposure study suggest that hourly or daily peak ambient ozone concentration may be an appropriate proxy for corresponding hourly or peak personal 

exposure. Whether observations from this study are relevant for individuals at 

risk of ozone-related death warrants further examination. Personal ozone exposure is a major source of uncertainty in ozone-mortality risk estimates; additional studies are needed to determine whether using the shorter averaging times reduces this uncertainty. These studies will require the 

development of new measurement methods that have sufficient sensitivity 

to measure these likely low, short-term exposures. Additional studies assess- 
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Overall Conclusions and Recommendations 163 

ing personal exposure-ambient concentration relationships may not only reduce 

uncertainties, but might help to explain variability in ozone-mortality findings 

across studies (that is, by determining how the strength of the correlation and the 

extent to which personal exposures change in response to changes in ambient 

concentrations varies across cities or subpopulations). 

In a given location, various ozone metrics (averaging periods) tend to be 

highly correlated, so it may seem somewhat unimportant to distinguish between 

them, and the degree of correlation may make it difficult for an epidemiologic 

study to do so. However, the choice of metric can have a larger effect on estimates of expected benefits of control programs. For example, a program that 

lowers emissions of oxides of nitrogen (NOx) could reduce peak ozone concentrations but raise average concentrations. In that case, a cost-benefit analysis 

based on an association between premature mortality and average ozone could 

appear to have a negative effect, whereas an analysis based on an association 

with peak summertime ozone could show a benefit. It is unknown which is more 

accurate, so evaluating the benefits of urban NOx reductions is uncertain both in 

magnitude and in direction. The choice of exposure metric can also be important 

in designing a strategy to control ozone-precursor emissions (see Chapter 3). 

Although the recent time-series studies have to the extent possible included analyses of alternative ozone metrics (such as 1-h maximum or 8-h 

maximum ), it is important to examine the relationships further to examine doseresponse relationships, test potential confounding more effectively, and inform 

future regulatory choices among different actions that might have different effects on peak and multihour averages. 

Potential Confounding by Other Pollutants 

The committee found that short-term ozone exposure is likely to contribute to premature mortality in addition to the risks posed by weather and PM, but 

studies to date have not been sufficient to control for potential confounding by 

or interactions with condensed-phase constituents of airborne PM, such as sulfates, acids, elemental carbon, and metals. Colinearity among ambient pollutants raises concerns about possible confounding of ozone mortality effects 

by correlated copollutants. The concerns center on the possibility that effects 

associated with ambient ozone may be the consequences not only of ozone exposure but of correlated pollutants not included in the health-effects model. Of 

the possible confounders, ambient PM2.5 (PM with a diameter no greater than 2.5 

μm) and weather have raised the most concerns about confounding. 

Strong summer correlations between ozone and PM2.5 in some locations 

may be attributed to similarities in their formation. However, associations between ambient ozone and PM2.5 differ substantially in the western and eastern 

United States, between summer and winter, and for different PM components. 

Also, correlations among ambient ozone and other pollutants have been shown 

to vary by averaging period. These results suggest that the potential for con-
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164 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

founding of ozone-health effects also varies by these factors, as discussed in 

Chapter 4. 

The potential for confounding by ambient PM2.5 probably depends 

also on particle composition, which varies by location and season. Studies 

have suggested that health effects of PM2.5 may differ by component, so confounding might be an effect of specific PM2.5 components, such as sulfate, elemental and organic carbon, metals, and secondary organics; this matter should 

be examined. It will be difficult to address such confounding with currently 

available data, because PM2.5 component data have only recently been collected 

routinely at many sites and because winter time ozone is not often measured. In 

the near future, the Speciation Trends Network (STN) may provide data on new 

measurements by species. However, unlike data on ozone, such data are generally available only once every 3-6 d (see Chapter 3). More-frequent measurements may be needed to improve understanding of how short-term variation in 

PM2.5 components might confound ozone-mortality associations. 

Assessing Ozone-Mortality Relationships During Winter Months 

There is a lack of observed association between ozone and mortality 

during periods when ozone is low, such as winter. Reasons for this lack of 

association are not well understood in part because of the decrease in monitoring during such periods. Better understanding of the association is important for a full exploration of (1) seasonal differences in risk, (2) how these seasonal risk differences vary spatially between communities with warmer and 

cooler winters, and (3) ozone-mortality relationships at lower ozone concentrations. 

Ambient ozone is one of the most well-characterized pollutants in the 

United States, but ozone monitors in many locations are operated only during 

the ozone season, which varies from city to city. During that time, ozone monitors provide nearly continuous measurement, although concentrations are typically reported hourly. 

Threshold 

To characterize the association between daily variations in ambient ozone 

concentrations and daily variations in deaths, a linear model is used in which it 

is assumed that the change in mortality risk is constant across pollution concentrations. It is unlikely that the association between exposure and response at the 

individual level follows that simple mathematical formulation. Individuals have 

their own susceptibility, characterized by a unique exposure-response association. That association may be characterized by a particular threshold, a concentration of exposure to ozone below which there is no added risk of death. A person’s threshold will vary, depending on the person’s “frailty” at any given 
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Overall Conclusions and Recommendations 165 

moment and thresholds may depend on the averaging period used to assess exposure. 

The time-series design, however, relates individual exposure not to individual risk but to the average of ambient concentrations for the “at risk” population on any given day. Thus, the appropriate concentration-response function for 

the time-series studies is based on an aggregation of individual exposureresponse curves. Aggregation of a large number of complex functions can yield 

smoother and more nearly linear curves at the population level, so we would 

expect the concentration-response function based on time-series studies to have 

a form that is relatively simple. 

Those results suggest a near-linear association between ambient concentrations of ozone and daily mortality in the United States. Exposure misclassification caused by use of an average of ambient fixed-site monitoring data to estimate population-average personal exposure makes it more difficult to 

distinguish between linear and threshold models. Estimates of the concentrationresponse curve based on epidemiologic studies with imprecisely measured exposure should be viewed with caution. A sensitivity analysis of the shape of the 

curve may be required to capture the uncertainties in this procedure. Moreover, 

approaches based on 24-h averaging may cloud thresholds related to actual exposures which may be better represented with shorter averaging times, such as 

by using an 8-h maximum or 1-h maximum. 

On the basis of its review of the evidence, the committee concludes 

that the association between short-term changes in ozone concentrations 

and mortality is generally linear throughout most of the concentration 

range, although uncertainties make it difficult to determine whether there 

is a threshold for the association at the lower end of the range. If there is a 

threshold, it is probably at a concentration below the current ambient air 

quality standard. 

Susceptibility and the Interpretation of Mortality Studies 

The evidence presented in Chapter 4 leads to the preliminary conclusion that the effects of ozone on acute death rates are likely to be larger 

among those with pre-existing disease and the list of plausible effect modifiers is rather long, although insufficiently investigated at this time. The role 

of genes in ozone mortality has not been investigated, but they undoubtedly play 

an important role as modifiers of various pathways involved in the effect. Interaction of the various factors has not been investigated. 

One can infer that ozone mortality depends on subjects’ susceptibility profile, which consists of a wide range and combination of factors. Susceptibility is 

most likely not a dichotomous trait but a dynamic characteristic that follows a 

wide distribution in the population, from no to high susceptibility. The level of 

susceptibility of any subject at any time may depend on the distribution of vari-
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166 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

ous exogenous and endogenous determinants of susceptibility (and their interactions) and their change over time. 

The observable association between ozone and mortality reflects the 

weighted average of all true (but unobservable) individual concentrationresponse functions. The latter cannot be established, but the risk of dying because of a 10-ppb increase in ozone concentration is likely to be substantially 

larger in the most susceptible persons than in the general population. 

Although susceptibility factors certainly matter, the distribution of the 

ozone-mortality effect estimates among groups with different categories of susceptibility is not known; that is, the quantitative details of the heterogeneity of 

effects are not readily available. Consequently, the overall (population-weighted 

average) effect in the total population is the only currently scientifically supportable approach for use in risk assessment. Its use is appropriate, even though 

the population-weighted mean effect may not be a valid estimate for any specific 

sub-population, because the actual effect may be much larger among the susceptible individuals but much smaller or zero among the less susceptible. However, 

that is a source of an unknown amount of uncertainty when one is calculating 

the benefits of a reduction in ozone. If the hazard and risk distributions2

 in the 

population are not independent, estimates of excess deaths and of life years lost 

in the entire population that are attributable to changes in ozone exposure based 

on time-series studies will not equal the averages of these quantities in all risk 

groups. The size of the difference is not known but could be estimated if risks 

for susceptible groups are obtained (see Chapter 4). 

Short-Term Mortality Displacement 

Is there evidence to say what share of the mortality associated with ozone 

in the daily time-series studies may be very short-term displacement of deaths 

that would have occurred within days or weeks in the absence of ozone exposure?3

 Current economic valuations of mortality are based on study samples that 

have average remaining life expectancies. It would be problematic to extrapolate 

these valuations to a circumstance in which the remaining life expectancy of the 

population most at risk is very short. When a person is aware that death is imminent and quality of life is seriously compromised (for example, the person is 

bed-ridden, is in great pain, or has extremely diminished cognitive function), 

extending life by a small amount of time may not have a high value. But if the 

person can be treated and the condition improved and an acceptable quality of 

 2

In this context, the distribution of hazards among the population is the likelihood of 

death at any age; the distribution of risk is the association between ozone and death at any 

age. 3

The term harvesting is sometimes used instead of short-term mortality displacement

to refer to the concept that air pollution leads to the death of people who are highly susceptible and near death (and die a few days earlier than they would have without airpollution exposure) rather than the death of people who are not otherwise near death. 
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Overall Conclusions and Recommendations 167 

life can be restored, extending life may have a high value even if the person has 

other health impairments or is quite elderly. 

Given the design of acute-effects studies, the time lost or the prematurity 

of deaths is not directly estimable without possibly unrealistic assumptions. In 

the absence of knowledge about the amount of time lost because of acute effects, 

one may hypothesize that air pollutants were able to trigger death only in a pool 

of very frail people, those already in very bad health. Assuming that the remaining life expectancy of those frail people was very short even in the absence of 

pollution, the effect of air pollution would consist of only a minor shift of the 

time of death, namely, a short advancement of death. 

On the basis of available evidence, the committee concludes that 

deaths related to exposure to ozone (and other photochemical oxidants) are 

not restricted to people who are at very high risk of death within a few 

days. The evidence comes from the recent analysis of time-series in several U.S. 

cities that focused on identifying a mortality-displacement pattern in the time 

course of exposure and death (Zanobetti and Schwartz 2008). In that analysis, it 

was clear that short-term mortality displacement could not fully explain the observed increase in death; short-term ozone exposure was likely to have contributed to shortening the lives of people who had compromised health, not necessarily just those near death. That evidence is based on results of only one study, 

however, and warrants confirmation by other studies. 

Distributed Lag 

Deaths related to short-term ozone exposure may not occur until several 

days after exposure or may be associated with multiple short-term exposures. 

Many studies of short-term effects investigate the change in death rates for only 

one or a few days, but distributed-lag models look further ahead to capture delayed acute effects, often referred to as subacute effects. Such analyses are useful in understanding the statistical distribution of time between an increased 

concentration of ambient ozone and the time pattern of occurrence of death. On 

a population level, it is extremely unlikely that all ozone-related deaths occur 

either immediately or within 1-2 d of exposure. A more plausible model assumes susceptibilities to death (or frailty) and the (competing) success of intervention strategies to follow a distribution in which some people die immediately 

or within 1-2 d whereas others first suffer acute ailments (such as a myocardial 

infarction or pneumonia) and death may be delayed by partially successful 

treatment or occur as a result of the decompensation of defense mechanisms. 

In contrast with the PM health-effects literature, few data are available that 

are based on using distributed-lag models of ozone mortality. Those available 

suggest that effect estimates for both ozone and PM steadily increase with increasing time of the investigated effects. Specifically, subacute (longer-term) 

effects that are combinations of effects of several days or weeks of exposure are 

larger than immediate short-term effects, and estimates based on cohort studies 
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168 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

are the largest. However, the increase in the estimates is far larger for PM than 

for ozone; this may be a consequence of attenuation due to large errors in characterizing exposure to ozone, or it may reflect a more dominant role of acute 

disease related to ozone exposure whereas the role of chronic disease is more 

important in the effects of PM. As has been the case with PM, analyses conducted with distributed-lag models over several days appear to capture the 

overall effects of ozone better than same-day data, but there have been relatively few of them and further confirmation is warranted. 

Chronic Exposure 

Long-term effects of ozone on mortality are considered to be the result of 

cumulative effects on people who have chronic disease caused by repeated exposure to ozone. Although some inconsistencies remain to be clarified, the observed associations between ozone exposure and decreased small-airway lung 

function during childhood and adolescence suggest that ozone-related mortality 

is at least partially attributable to exposures across a period of more than a few 

days. Ozone tissue dose is highest in the small airways, so the findings are in 

line with expected ozone-related conditions that result in reduced lung function. 

The evidence of an effect of long-term ozone exposure on lung-function growth 

increases the plausibility of its effect on mortality. The association between poor 

lung function and life expectancy is strong and well established. 

The standard approach to investigating effects of cumulative ozone exposure on life expectancy is the cohort study, in which large numbers of subjects 

are followed for several years. After taking into account all other factors that are 

likely to affect mortality, cohort studies can test the null hypothesis that mortality is the same among populations that have different ozone-exposure histories. 

However, none of the cohort studies available at this time were designed to investigate chronic effects of ozone, and differences in ozone exposure among 

subjects in each study tended to be rather small. 

Several North American and European air-pollution cohort studies have 

focused on ambient PM or markers of local traffic to characterize exposure of 

study cohorts. Assessments of the association between life expectancy and ambient ozone have been far less extensive. Analyses of the most extensive of the 

cohorts (that of the American Cancer Society) have found small positive effects 

in warm seasons, but other cohort studies have not found positive associations 

between long-term average ozone concentrations and cardiopulmonary mortality 

after controlling for PM2.5. 

The weak current evidence from cohort studies of an association of 

premature mortality with chronic exposure to ozone suggests that risks are 

larger than those observed in acute effects studies alone. If further confirmed, the evidence from cohort studies of an association of premature 

mortality with longer-term exposure would tend to support the notion that 

effects seen in time-series studies reflect only a portion of the total effect. 
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Overall Conclusions and Recommendations 169 

The use of large cohorts with long followup periods may be required because 

the long-term ozone-exposure mortality risk appears to be much smaller than 

that associated with PM2.5 It may be necessary to pool information from several 

existing cohorts to obtain sufficient statistical power. 

HEALTH-BASED INFORMATION FOR BENEFITS ASSESSMENTS 

Mortality Time-Series Results 

The committee recommends that ozone-related mortality be included 

in future estimates of health benefits of ozone reduction. The committee 

further recommends that the greatest emphasis be placed on estimates 

based on systematic new multicity analyses using national databases of air 

pollution and mortality, such as was done in the National Morbidity, Mortality and Air Pollution study (NMMAPS), without excluding consideration 

of meta-analyses of previously published studies. Emphasis should also be 

placed on risk estimates obtained from analyzing data on multiple days so 

as to include delayed acute effects. (see Chapter 4). Such health-benefits 

estimates should be accompanied by a broad array of analyses of uncertainty, while at the same time understanding that a zero value is unlikely. In 

light of this recommended approach, future RIAs should give little or no weight 

to the assumption that there is no causal association between estimated reductions in the incidence of premature mortality and reduced ozone exposure. 

Effect of Ozone Exposure on Life Expectancy 

The impact of pollution on mortality may be quantified in terms of 

changes in mortality rates, number of deaths in a given period, or the months (or 

years) of life lost (or saved). EPA has calculated numbers of deaths prevented in 

a given year for each incremental reduction in PM or ozone concentration by 

applying the relative risk from epidemiologic studies to a baseline mortality rate. 

There is also interest in assessing the number of life-years saved, especially for 

cost-effectiveness analysis. The committee was asked whether there is an adequate basis for quantitatively characterizing the likely impact of reductions in 

short-term daily exposures to ozone on life expectancy. 

Questions about the population at risk for mortality from short-term ozone 

exposure underlie most of the issues raised about interpreting epidemiologic 

time-series results in benefits assessment, including issues of susceptibility and 

short-term mortality displacement. Those issues are important for economic 

valuation. It is important to know that the willingness-to-pay (WTP)4

 values 

used are appropriate to the at-risk population, and this remains one of the key 

 4

WTP is an estimate of the amount that a person is willing to pay for changing his or 

her mortality risk in a given period by a small amount (see Chapters 2 and 5). 
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170 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

uncertainties that the committee has highlighted in its report. For example, if we 

know from the cause of death associated with ozone exposure that the mortality 

risk is primarily for respiratory causes of death, we know that the age distribution of the at-risk population is skewed more toward the elderly, especially those 

experiencing cardiopulmonary compromise, than is total mortality in the general 

population. Thus, the WTP estimates should be relevant for a population with a 

higher average age. The currently available information lacks that level of detail. 

Although cardiorespiratory mortality stays at the center of the discussion, it is 

not known whether the age and risk profile of the people whose deaths are attributable to ozone corresponds to the typical person who dies of cardiorespiratory problems. The only information available is the population-average change 

in mortality rates, which translates into the population-level change in life expectancy. 

A unified survival model of a dynamic cohort study that combines longterm and short-term air-pollution exposure has been developed (see Chapter 4). 

By incorporating life-table methods based on time-series risk estimates, the 

model can be used to estimate both life-years lost and number of additional 

deaths expected to occur in a specified period because of changes in airpollution concentrations under restrictive assumptions. Further complexity can 

be gained by incorporating risks specific to age-sex groups. It is not clear, however, how long a period of long-term increased exposure is required to shorten 

life expectancy; it may be years. The time distribution of effect on longevity 

associated with immediate reductions in pollution also is not known. The risks 

based on time-series studies assume (by design) that reductions in pollution have 

an immediate benefit for longevity. As mentioned above, if the hazard and risk 

distributions in the population are not independent, estimates of excess deaths 

and life-years lost in the entire population attributable to changes in ozone exposure based on time-series studies will not equal the average of these quantities 

over all risk groups. 

The most complete assessment of the association between acute exposure and death originates in distributed-lag models that integrate the distribution of the time between exposure and death. However, both the usual 

time-series model and the distributed-lag models focus on a short window of 

exposure. Effects of long-term cumulated exposure are, by design, ignored 

in those studies. Reductions in life expectancy based on the time-series results can be calculated by using life-table methods, but lack of information 

about the at-risk population necessitates making the assumption that remaining life expectancy is comparable with of others in the same age-sex 

cohort. 

Use of Information from Acute-Effects and Chronic-Effects Studies 

Evidence of long-term effects of ozone on mortality (or survival time) is 

presently weak; thus, the derivation of a relative risk to describe the association 
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Overall Conclusions and Recommendations 171 

is more difficult than in the case of PM (see Chapter 4). The translation of the 

results into numbers of attributable deaths is possible but leaves two main challenges: First, the assessment of acute effects would be incomplete if based solely 

on the usual time-series studies, given that subacute (delayed) effects are not 

captured with these methods; only one study has published estimates of subacute 

effects of ozone based on distributed-lag models (Zanobetti and Schwartz 2008). 

Second, in the absence of abundant quantifiable evidence of chronic effects of 

ozone on mortality, total life-years lost because of both acute and chronic effects 

cannot be estimated with confidence. As mentioned previously, the current evidence from cohort studies, although it is weak, supports the notion that the effects estimates seen in the-series studies reflect only a portion of the total effect. 

The question of how to use the epidemiologic information to translate into 

risk changes and benefits assessment is the subject of debate. So far, many risk 

assessments have derived as an intermediate step the number of deaths attributable to air pollution on an annual basis. That approach has several limitations 

that are of particular concern for chronic effects but, conceptually, apply also to 

acute effects. 

A problem in discussing lives saved is related to the misleading message 

that any policy may prevent death whereas the only result one can expect is a 

postponement of death—a longer life. The term attributable death is at least less 

misleading than lives saved. Conceptually, however, attributable death still implies a body count rather than the life-years in premature deaths. In the case of 

death due to short-term ozone exposure of people with some pre-existing disease 

(either acute or chronic), the presentation of “annual attributable death” may be 

an acceptable approach. It should be noted, however, that in the case of quantifying chronic effects of pollution, assumed to complicate the underlying chronic 

diseases that increase the susceptibility to premature death, the attributable-death 

concept is less appropriate because it does not take fully into account the longterm dynamic in a population in which the underlying risk profiles change. A 

reduction in air pollution will lead to longer life expectancy and thus increase 

the number of elderly people. Age-adjusted mortality rates are expected to be 

lower under cleaner conditions, but the absolute number of deaths will steadily 

increase as the population ages. Consequently, the “attributable deaths” will not 

be the same throughout the years after an improvement in air quality (Hurley et 

al. 2000; Miller and Hurley 2003; Rabl 2006; Brunekreff et al. 2007). 

Recommendation: EPA should study emerging understanding of ozonemortality associations and evaluate their use and implications in benefits 

assessments, including relationships between changes in mortality rates, 

annual deaths prevented, and years of life saved. The alternative approaches for expressing ozone mortality effects will lead to rather similar 

results if one is supposed to express only the most immediate (acute) effects of pollution changes. However, with the integration of subacute effects estimates, and particularly in the case of use of estimates of longterm chronic effects, the discrepancies between the approaches increase 
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172 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

and the conceptual flaws of the attributable-cases model become more 

pronounced. 

VALUATION 

An important question for benefits valuation is whether a person’s value 

for reducing risks of death should be based on the magnitude of the life extension (that is, the loss of life-years that is avoided or prevented). Although there 

are intuitive reasons for saying yes, the question is how it should be done. Estimates of the value of a statistical life (VSL) are often used in cost-benefit analyses for programs expected to reduce mortality risks in a population. VSL estimates are derived from estimates of people’s WTP for reducing their mortality 

risk in a given period by a small amount (see Chapters 2 and 5). If the effects of 

reducing mortality risk are measured in terms of years of life extension (increased remaining life expectancy), then it may be more appropriate to use a 

monetary value per statistical life-year (VSLY). 

For any given risk reduction the average WTP value can be summarized as 

an average VSL or as an average VSLY if the remaining life expectancy and 

rate of time preference are known for the population from which the average 

WTP value was derived. Difficulties arise when either of these summary measures is assumed to be constant and used to estimate values for risk reductions in 

other populations or other risk reduction contexts. 

EPA’s current primary approach to economic valuation of mortality-risk 

reductions is a variation on its long-standing approach of using the same VSL 

for all annual mortality reductions. In its primary benefits estimates, EPA applies the VSL to all lives saved regardless of the age or health status of the population experiencing the change in mortality risk and regardless of the cause of 

the change.

Because there is some expectation that WTP for mortality-risk reduction 

will vary with the characteristics of the population affected or with the context 

of the risk change, EPA asked the committee to assess scientific approaches to 

assigning economic values to reductions in mortality risk associated with ozone 

reductions and to address the questions of economic valuation for different 

changes in life expectancy. 

Valuation in the Context of Cost-Benefit Analysis 

The charge to this committee concerns monetary valuation of mortality 

risk reduction for regulatory impact analyses that are based on the basic premises of cost-benefit analysis. In this context, therefore, we focus on WTP values 

for mortality risk reduction. Cost-benefit analysis, however, focuses on economic efficiency and many other ethical and legal factors are appropriate to consider in policy and regulatory decisions. In general, these issues should be considered separate from the cost-benefit analysis rather than interjected into the 
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Overall Conclusions and Recommendations 173 

valuation estimates because this endangers the neutrality of the analysis. However, there may be some instances when such interjection is appropriate. For 

example, the decision by EPA to not adjust WTP estimates for local differences 

in income levels is justified because to do so creates a situation that favors 

greater environmental protection in wealthier locations, an outcome policy makers judge to be unfair and in many cases illegal. 

The committee stresses that government decision-makers need information on how the WTP for mortality risk reductions varies by risk characteristics, 

population characteristics, and for both risk as a private good and as a public 

good. How they choose to use this information, however, is not strictly a technical decision, but depends on ethical precepts, legal precedent, the quality of the 

evidence and other factors that may be beyond the analysts’ control or purview. 

Recommendation: We recommend that the issues contained in this finding of the committee be considered within the Office of Management and 

Budget and the agencies that use monetary values for mortality risk reductions in their regulatory analyses. These agencies should develop a plan 

for generating the information needed to determine how WTP varies for 

different populations and different risk contexts. In addition, there should 

be an exploration to determine the appropriate uses of this information. 

Such an exploration should go beyond economic considerations and include ethical and public policy perspectives. 

Willingness-to-Pay Estimates 

Both economic theory and the available empirical evidence are inconclusive about how individuals’ WTP values for reducing their own risk vary with 

two important individual characteristics: age as a proxy for remaining life expectancy and health status. We conclude that the empirical evidence is insufficient to support a specific quantitative adjustment of the WTP estimates 

to account for differences in remaining life expectancy, but we do not reject 

the concept that such adjustments may be appropriate. It is plausible that 

people with shorter remaining life expectancy are willing to devote less of their 

resources to reducing their mortality risk than would people with longer remaining life expectancy. 

Characteristics of the risk that may affect individual WTP values include 

the type of risk (for example, illness or accident) and its latency. The literature is 

inconclusive about the influence of risk characteristics (see below). The effects 

of latency on WTP values are straightforward conceptually (WTP for a future 

mortality-risk reduction should be less than that for an equivalent immediate risk 

reduction), and a small body of empirical literature supports such a concept. 

However, the epidemiologic literature is not sufficient to estimate the degree of 

latency of changes in mortality risk from ozone exposure. 
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174 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Recommendation: Although there are many concerns about the accuracy 

of using the same WTP estimate (or range of estimates) for all mortalityrisk reductions, we recommend that EPA use this approach, with appropriate scaling to the size of the risk change, as the most scientifically supportable approach for monetary valuation of ozone-related mortality, 

given the currently available information in the economics and epidemiology literatures. Empirical evidence of how WTP varies with population or 

risk characteristics is not sufficiently consistent to support a change in this 

practice that EPA has been using for many years. 

Estimates of Value of a Statistical Life-Year 

The use of a constant VSLY in the valuation of increases in life expectancy requires the assumption that WTP values for mortality risk reductions be 

consistently declining with increasing age. Available empirical evidence does 

not support that assumption and therefore does not support the use of a 

constant VSLY. The literature does not reject the use of a non-constant

VSLY, however, and the epidemiological literature may favor reporting 

life-years saved.

Recommendation: Unless future research produces empirical support for 

the assumptions that underlie a constant VSLY, EPA should not attempt to 

make adjustments for remaining life expectancy by calculating life-years 

saved and using a constant VSLY to value them. It may be appropriate to 

calculate and report life-years saved (in addition to reporting changes in 

annual mortality ranges and reductions in premature deaths), but it is not 

appropriate to use a constant VSLY as a monetary valuation of life-years 

saved, except, perhaps in a bounding exercise. The committee cautions 

against use of such an analysis in anything but a sensitivity analysis, however (see below). There is likely to be good reason to use a non-constant 

VSLY or a non-constant VSL, once the literature is sufficient to make this 

transition. The committee stresses, however, that the status quo of using a 

uniform VSL should be continued until there is sufficient empirical evidence of how WTP for mortality risk reduction varies with differences in 

remaining life expectancy and other factors, which the committee concludes is not yet available.

Value of a Statistical Life, Individual Characteristics, and Risk Contexts 

Most of the revealed-preference and stated-preference studies relied on by 

EPA to obtain estimates of the VSL have estimated WTP for mortality-risk reduction in a context (such as traffic accidents and workplace accidents) and for a 

population that differ from the context and population relevant to the pollutionrelated risks that EPA is assessing. Applying the available estimates in EPA’s 
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Overall Conclusions and Recommendations 175 

assessments in a different risk context (illness vs accident) and for different 

population characteristics introduces considerable uncertainty about how 

these factors affect average WTP values. However, the current literature is 

inconclusive as to how much the WTP values may vary with these factors. 

Recommendation: EPA should ensure that the average WTP estimates 

selected from the literature reflect results of both revealed-preference and 

stated-preference studies. The agency should take into account the 

strengths and weaknesses of each study approach and consider how 

closely the available studies match the policy context in population at risk 

and type of risk. EPA should give less weight to wage-risk studies in selecting WTP estimates than it has in the past. Given the limited studies 

available for different risk contexts, it is difficult to say how much the 

WTP values may differ, but the wage-risk studies are a poor match to the 

population and to the risk context for the ozone-mortality case. 

Sensitivity Analyses 

The direction of the expected error, if any, in using the average VSL in the 

literature for valuing changes in ozone-related mortality risk is more likely to be 

toward overstating the WTP to reduce the risk. That is because greater mortality 

risk associated with ozone appears to be in the elderly population and because 

latent risk may be involved. Given this population’s substantially less than average remaining life expectancy, it is possible that its WTP to reduce mortality 

risk would be less than the average WTP for the population as a whole. However, we expect that the lower WTP as a result of the elderly population’s lower 

remaining life expectancy is offset to some extent by higher WTP because of 

poorer health status or higher baseline risk. Although results in the empirical 

literature are not consistent, several studies suggest that WTP to reduce mortality risk is constant or declines slightly with age. That evidence suggests that, 

for ozone, a proportional adjustment of the VSL for remaining life expectancy (that is, using a constant VSLY) would result in WTP that is too low. 

Recommendation: Given the uncertainty in the accuracy of available 

VSL estimates for ozone-related mortality, EPA should conduct sensitivity 

analyses with alternative estimates or assumptions. The purpose of sensitivity analyses is to see whether the overall conclusions of the cost-benefit 

comparison are changed—for example, whether net benefits are still positive under alternative economic-valuation assumptions. In general, there is 

less confidence in the sensitivity analyses because the alternative assumptions are more speculative than the primary assumptions or deviate from 

the status quo, which the committee feels puts a burden of proof on those 

who would overturn it. Therefore, EPA should present results in a way 

that does not give equal weight to the outcomes of sensitivity analyses and 
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176 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

the outcomes of the use of primary assumptions. However, results of sensitivity analyses can be included in summary conclusions. EPA should select alternative assumptions for sensitivity analyses on the basis of either 

theory or evidence. For example, different published empirical estimates 

of the relationship between WTP for mortality-risk reduction and age 

could be selected as illustrative of the range of results in the literature, including estimates of VSLY or VSL that vary with age. 

RESEARCH RECOMMENDATIONS 

The committee was asked to identify major gaps in knowledge about the 

benefits of reducing ozone exposure and the most promising research strategies 

to close the gaps, including additional data, analyses, or research needed to separate the contributions of ozone and other gaseous or particulate components of 

air pollution to the total short-term effect on premature mortality documented in 

the literature. The health-related recommendations (from Chapter 3 and 4) and 

the future research needs for valuation (from Chapter 5) briefly summarized in 

this section should be addressed as part of EPA’s research strategy for estimating the benefits of reducing ambient ozone. 

The committee recognizes that many of the recommended research activities are complex and will be difficult to undertake, and that sufficient resources 

may not be available to undertake all of them in the near term. Therefore, EPA 

and other agencies that might carry out the recommended research will need to 

set priorities and develop a strategy for addressing the various information 

needs. 

Recommendations for Future Health Research

The health-related recommendations are presented in three broad categories related to enhancing exposure assessment, enhancing epidemiologic studies, 

and reducing uncertainty. 

Enhanced Exposure Assessment for Epidemiology 

Evaluate exposure metrics to determine whether and how much daily 

peak exposures, such as 1h or 8h exposures, and longer-term average exposures, 

such as over 24h, are associated with ozone-related mortality. Identify the appropriate exposure metrics to relate how control programs will affect ozone concentrations and health. Consider that control strategies may have quite different 

effects on 24-h average concentrations and shorter-term exposures. Also consider that peak short-term concentrations on lower-ozone days will respond differently from peak short-term concentrations on high-ozone days and often in 

the opposite direction. 
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Overall Conclusions and Recommendations 177 

Investigate potential confounding by evaluating regional and seasonal 

associations between ambient concentrations and exposures to ozone and PM2.5

(and its components), how the data affect researchers’ ability to control for confounding, and correlations between the various pollutant concentrations. When 

possible, focus on groups of individuals who are sensitive to ozone exposures 

and use data on the chemical and physical components and size distribution of 

PM2.5. 

Include PM speciation data to account for seasonal and geographic variability in the relationship between ozone and its potential confounders. Include 

the growing STN database in analyses of potential confounding of the ozone 

associations. Ensure that STN collects data frequently enough on the particle 

components most relevant to understanding the potential for confounding. 

Monitor ozone in winter and report the measurements. The size of the 

winter program should be sufficient to allow researchers to examine seasonal 

differences in risk, how the differences vary spatially between communities with 

warmer and cooler winters, and ozone-mortality relationships at lower ozone 

concentrations. Ozone is a regional pollutant, and winter measurements need not 

be collected at all the summer locations; but collect them at the frequency of 

summer measurements. 

Evaluate air-quality numerical models, such as the Community Multiscale Air Quality (CMAQ) model for use in ozone epidemiologic studies to extend the spatial scale of available data. Consider the uncertainty associated with 

the models before drawing inferences about mortality risk assessment associated 

with ozone exposure. 

Evaluate ozone exposure models such as the Air Pollutants Exposure 

(APEX) model that are used to improve characterization of ozone exposure at 

the population level by taking into account human activity. Assess whether the 

models can be used to improve epidemiologic studies or benefits assessments. 

Enhanced Epidemiologic Studies 

Explore thresholds by studying panels of individuals considered to be 

susceptible to premature death from ozone exposure, such as those with impaired lung and heart function. Further explore how individual thresholds may 

vary and the extent to which thresholds depend on the frailty of the individual at 

any given moment. 

Because it is not clear whether ozone is associated with mortality in the 

cooler months, examine warmer months separately. Conduct a sensitivity analysis on concentration-response relationships to capture more fully the uncertainties contributed by reliance on average fixed-site monitoring data to estimate 

population-average personal exposure. 

Explore short-term mortality displacement and include use of alternative study methods, such as investigation of subjects who have diseases (for ex-
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178 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

ample, diabetes or heart disease) that are known to induce high mortality risk 

associated with air pollution. 

Identify susceptibility characteristics that may have important effects on 

ozone-mortality relationships and develop a distribution of the estimates of the 

ozone mortality effect among the categories of susceptibility. To the extent that 

data are not available, use models and assumptions for sensitivity analysis. 

Conduct distributed-lag analyses as one part of future epidemiologic investigations to improve understanding of the statistical distribution of time between an increase in the ambient concentration of ozone and a pattern of occurrence of death. 

Conduct cohort studies to examine further the association between longterm ozone exposure and mortality. Develop long-term ozone-exposure models 

that can distinguish variations in exposure at the individual level and between 

and within cities. To the extent that new cohort studies strengthen evidence of 

long-term effects, consider including estimates based on that evidence in benefits assessments. 

Study cardiovascular effects of ozone exposure, both in human and animal models. Design studies to identify genetic susceptibility factors. 

Uncertainty 

Characterize uncertainty of results of epidemiologic models and discuss 

their reliability and estimated uncertainty about which model (if any) is reasonably correct. 

Consider Bayesian approaches for uncertainty analysis, including the 

possibility of additional expert elicitation once the recent experience with this 

approach to PM risk assessments has been evaluated. 

Conduct sensitivity analysis intermittently as computational models and 

input distributions are developed to focus resources on the most important inputs 

or parts of the model. 

Identify the bases of estimates to distinguish between data-derived estimates of some components (such as the concentration-response function) and 

the expert opinions about other components that are not supported by scientific 

data. 

Recommendations for Future Research on Valuation 

Explore how WTP varies with mortality-risk changes and changes in 

life expectancy, and explore how WTP varies with population characteristics such as age, health status, and baseline risk levels. Although the research 

needs would be addressed primarily by using stated-preference methods, explore 

ways to address research needs with further developments of revealedpreference methods. 
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Overall Conclusions and Recommendations 179 

Seek results on total age effects to understand better how age and remaining life expectancy affect WTP for reductions in mortality risks or extension of life expectancy. Ask that future (or even previous) studies report total 

age effects (that is, WTP by age cohort) in addition to effects of age alone on 

WTP for a small reduction in mortality risk in a given period. 

Make datasets available for meta-analysis by urging researchers who 

receive EPA funding to make their datasets available for meta-analyses in addition to providing their published results. 

Explore and develop full life-cycle methods for communicating and 

valuing changes in mortality risk as a shift in the survival curve, which plots 

survival probabilities in all future periods and from which life expectancy is 

derived. 

Explore effects of mortality-risk characteristics on the valuation of reduction in these risks. Consider different types of risk (such as accident and illness) and the latency of the change in risk. Compare values of (or nonmonetary 

preferences for) risks in different contexts (e.g., Magat et al. 1996; DeShazo and 

Cameron 2004). 

Explore the potential usefulness of studies that analyze preferences 

regarding public goods by developing approaches to distinguish paternalistic 

from nonpaternalistic altruism to avoid double-counting of benefits. Conduct 

conceptual analyses to learn how such results might be appropriately used in 

cost-benefit analysis, in which the usual paradigm is to sum beneficiaries’ private WTP. 

REGULATORY IMPACT ANALYSES INVOLVING 

OZONE MORTALITY 

As discussed above and in Chapter 4, future RIAs based on currently 

available studies concerning ozone-related mortality should give greatest weight 

to the results of multicity time-series analyses. As EPA (2008b) had done for its 

RIA for the finalized ozone NAAQS, most of the emphasis should be placed on 

estimates based on systematic new multicity analyses, such as was done in the 

NMMAPS, without excluding consideration of meta-analyses of previously published studies. Future RIAs should incorporate research results on the mortality 

effects of chronic ozone exposure and research that addresses key uncertainties 

related to potential confounding factors, exposure measures, and susceptibility 

as appropriate. 

Health-benefits estimates should be accompanied by a broad array of 

analyses of uncertainty, while at the same time understanding that a zero value 

would be unlikely. Future RIAs should give little or no weight to the assumption 

that there is no causal association between estimated reductions in the incidence 

of premature mortality and reduced ozone exposure unless new information 

emerges that refutes the interpretation of this association as causal. Presentations 

like that included in Table 7-14 of EPA’s recent RIA for the finalized ozone 
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180 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

NAAQS, showing a variety of assumptions about the association between ozone 

exposure and mortality, should be revised in light of this recommendation (see 

Appendix B). 

Risk analyses conducted with distributed-lag models over several days appear to capture the acute and the somewhat delayed subacute mortality effects of 

ozone exposure better than single-day data. Those models should be part of future benefits assessments to the extent that they are available. 

There are many concerns about its accuracy for all mortality-risk reductions, but using a specific WTP value and a corresponding VSL estimate (or 

range of estimates) is the most scientifically supportable approach at this time to 

monetary valuation of ozone-related mortality, given the information in the economics literature. Before recommending a substantial change in EPA’s approach 

for valuation of mortality risk reductions, it is necessary that there be fairly conclusive empirical evidence to support a specific change in the approach. It is the 

committee’s judgment that the available evidence is not sufficient to support 

such a change at this time, but alternative approaches should be explored in sensitivity analyses and further research should be conducted to answer the questions raised about the validity of EPA’s current approach. As new information 

emerges on population characteristics of those susceptible to mortality from 

ozone and on variations in WTP for mortality-risk reductions (or increases in 

life expectancy) due to different population characteristics, benefits-assessment 

methods may need to be revised. 

EPA should consider placing greater emphasis on reporting decreases in 

age-specfic death rates and increases in life expectancy than on reporting estimates of lives saved. Such a change is needed to be responsive to recent reports 

that it is not possible to identify specific deaths attributable to air-pollution exposures (e.g., Brunekreef et al. 2007). For example, if the relative risk is 1.002 

for a unit change in pollution (for example, for a change in tons of a pollutant 

emitted over a period), it means that there is about a 0.2% higher mortality rate 

for every unit increase in pollution in the population group to which the estimated relative risk applies. The relative risk is a proportional risk estimate. It 

may be estimated for the general population, but it would be preferable if it were 

estimated for the specific population groups that may be expected to have different susceptibilities to the effects of pollution exposure. In any case, it should be 

applied in a benefits assessment to the population for which it was estimated. If 

the scenario is for a two-unit reduction in pollution with a relative risk of 1.002 

per unit change in pollution, and the relevant population has a baseline annual 

mortality rate of 1 in 100, the reduction in the annual mortality rate attributable 

to the change in pollution is about 4 per 100,000. For a population of 1 million, 

EPA would report that as 40 lives saved. The committee recommends that EPA 

report preferentially the annual mortality-rate change of 4 in 100,000 for the 

applicable population and to develop models for consistent calculation of lifeexpectancy changes and changes in numbers of deaths (e.g., Rabl 2006). 

The WTP studies from which VSL estimates are derived match the annual 

mortality-rate change estimates. For example, the valuation literature reports 
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Overall Conclusions and Recommendations 181 

WTP estimates of $40-400 for a 4-in-100,000 risk reduction (translating to a 

VSL of $1-10 million). Turning the annual mortality-rate changes and WTP 

values into saved lives and values per life saved is a mathematical transformation that seems convenient for summary tables and policy assessments, but can 

be misleading and can obscure the underlying derivation and appropriate interpretation of the studies. It also ignores the effect of life-expectancy changes on 

the population composition over time, and this will cause the annual number of 

deaths to decrease at first and then to return to its previous level or even increase 

over time (e.g., Miller and Hurley 2003). 

The health-related research and valuation research recommended in this 

report should be addressed as part of EPA’s research strategy for estimating the 

mortality risk-reduction benefits of reducing exposure to ambient ozone. However, the research needs should not be viewed as a basis for postponing consideration of ozone mortality relationships in benefits assessment until more information is obtained. Also, it would be a mistake to assume that the committee’s 

discussion of uncertainties and research needs broadly applies to the current 

understanding of air pollution and health in general. For example, this report has 

indicated where there is a greater understanding of many aspects of PMmortality relationships relative to those for ozone. Continued enhancement of 

knowledge and methods for valuation of ozone mortality risk reduction benefits 

will inform future regulatory decision making and help in understanding the 

relative importance and value of effects caused by various pollutants. 
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182

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204

Abbreviations 

ACS: American Cancer Society 

APEX: Air Pollutants Exposure 

CAA: U.S. Clean Air Act 

CAIR: Clean Air Implementation Rule 

CASAC: Clean Air Scientific Advisory Committee (of EPA) 

CDC: Centers for Disease Control and Prevention (of DHHS) 

CHAD: Consolidated Human Activity Database 

CMS: Centers for Medicare and Medicaid Services (of DHHS) 

CMAQ: Community Multiscale Air Quality 

DHHS: U.S. Department of Health and Human Services 

DOT: U.S. Department of Transportation 

EC: elemental carbon 

EPA: U.S. Environmental Protection Agency 

ExternE: European Union program to estimate the mortality impacts of 

exposure to ozone and to value those impacts. 

FDA: U.S. Food and Drug Administration (of DHHS) 

FMCSA: Federal Motor Carrier Safety Administration (of DOT) 

NAAQS: National Ambient Air Quality Standard 

NHTSA: National Highway Traffic Safety Administration (of DOT) 

NO: nitric oxide 

NO2: nitrogen dioxide 

NOx: oxides of nitrogen (NO and NO2) 

O2: diatomic oxygen 

OH: hydroxyl radical 

OP: oxygenated organic product 

OMB: U.S. Office of Management and Budget 

PM: particulate matter 

PM2.5: particulate matter with aerodynamic equivalent diameter of no 

more than 2.5 μm (microns) 

PM10: particulate matter with aerodynamic equivalent diameter of no 

more than 10 μm 

RIA: regulatory impacts analysis 
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Abbreviations 205 

QALY: quality-adjusted life-years 

ROS: reactive oxygen species 

SAB: Science Advisory Board (of EPA) 

SIP: state implementation plan 

SO2: sulfur dioxide 

SOA: secondary organic aerosol 

VOC: volatile organic compound 

VSL: value of a statistical life 

VSLY: value of a statistical life-year 

WTA: willingness to accept compensation 

WTP: willingness to pay 
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206

Appendix A 

Biographic Information on Committee 

on Estimating Mortality Risk 

Reduction Benefits from Decreasing 

Tropospheric Ozone Exposure 

John C. Bailar III (Chair) is professor emeritus in the Department of Health 

Studies at the University of Chicago and scholar-in-residence at the National 

Academies. He is a retired commissioned officer of the U.S. Public Health Service and worked for the National Cancer Institute for 22 years. He has also held 

academic appointments at Harvard University and McGill University. Dr. 

Bailar’s research interests include assessing health risks posed by chemical hazards and air pollutants and interpreting statistical evidence in medicine with emphasis on cancer. He was editor-in-chief of the Journal of the National Cancer 

Institute for 6 years and statistical consultant and member of the Editorial Board 

of the New England Journal of Medicine. Dr. Bailar is a member of the International Statistical Institute and was elected to the Institute of Medicine in 1993. 

He served as chair of the National Research Council Committee on Estimating 

the Health-Risk-Reduction Benefits of Proposed Air Pollution Regulations. He 

received his MD from Yale University and his PhD in statistics from American 

University. 

Richard T. Burnett is a senior research scientist with the Healthy Environments and Consumer Safety Branch of Health Canada, where he has been working since 1983 on issues related to the health effects of outdoor air pollution. Dr. 

Burnett’s work has focused on the use of administrative health and environmental information to determine the public-health impacts of combustion-related 

pollution with nonlinear random-effects models and time-series and spatial analytic techniques. Dr. Burnett was a member of the National Research Council’s 

Committee on the Management of Air Quality in the United States and the Insti-
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Appendix A 207 

tute of Medicine’s Committee on Valuing Health for Regulatory CostEffectiveness Analysis. He is on the Editorial Board of Risk Analysis. Dr. Burnett is an adjunct professor in the Department of Epidemiology and Community 

Medicine of the Faculty of Medicine, an affiliate scientist of the Institute of 

Population Health, and a scientist with the McLaughlin Center for Population 

Health Risk Assessment at the Institute of Population Health, all in the University of Ottawa. Dr. Burnett received his PhD in mathematical statistics from 

Queen’s University. 

Lauraine G. Chestnut is a managing economist at Stratus Consulting Inc. Ms. 

Chestnut specializes in environmental and natural-resources economics, policy 

analysis, and survey research. She focuses on the quantification and economic 

valuation of human health, visibility, and other welfare effects of environmental 

pollutants. She has conducted original economic and survey research to estimate 

the value to the public of protecting human health, visibility aesthetics, and cultural materials from the effects of air pollution and has conducted epidemiologic 

studies of the effects of particulate matter on human health. Ms. Chestnut has 

synthesized the epidemiologic and economics literature on the human health 

effects of air pollutants and has applied this information in numerous assessments of the benefits of air-pollution control. She has published three books and 

several articles in peer-reviewed journals, including the Journal of Environmental Management, Land Economics, the Journal of the Air Pollution Control 

Association, the Journal of Policy Analysis and Management, and Archives of 

Environmental Health. Ms. Chestnut served 6 years on the Environmental Protection Agency Science Advisory Board’s Advisory Council on Clean Air Compliance Analysis and served on California’s Air Quality Advisory Committee. 

She was elected to the Board of Directors of the Association of Environmental 

and Resource Economists. She received her MA in economics from the University of Colorado. 

W. Michael Foster is a research professor of medicine in the Division of Pulmonary and Critical Care Medicine at Duke University Medical Center. Dr. Foster’s laboratory performs research on humans and animal models and investigates the biologic effects of inhalational hazards (particles and gases) on airway 

and parenchymal lung tissues. Subjects of interest and expertise include effects 

of oxidant-type air pollution on lung epithelial membrane physiology, in vivo 

functional and biochemical tissue responses of the human and animal lung, and 

host (genetic) factors as modulators of the pulmonary response to ambient air 

pollutants, inhalable irritants, and nuisance bioaerosols. Dr. Foster received a 

PhD in physiology and environmental science from New York University. 

A. Myrick Freeman III is the William D. Shipman Professor of Economics 

Emeritus at Bowdoin College. During his tenure at Bowdoin, Dr. Freeman has 

served as chair of the Economics Department and director of the Environmental 

Studies Program. He also has served as the Robert M. La Follette Distinguished 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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208 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Visiting Professor at the University of Wisconsin, Madison and as a senior fellow at Resources for the Future. His principal research interests are in applied 

welfare economics, benefit-cost analysis, and risk management as related to issues in environmental and resource management. Much of his work has been 

devoted to developing models and techniques for estimating the welfare effects 

of environmental changes (for example, the benefits of controlling pollution and 

the damage to natural resources due to the releases of chemicals). He has served 

on the National Research Council Board on Toxicology and Environmental 

Health Hazards. He also has served as a member of the Environmental Protection Agency Advisory Council on Clean Air Compliance Analysis, Clean Air 

Science Advisory Committee, Environmental Economics Advisory Committee, 

and Science Advisory Board. He is the author of The Benefits of Environmental 

Improvement: Theory and Practice (1979) and The Measurement of Environmental and Resource Values: Theory and Methods (1993), which were cited by 

the Association of Environmental and Resource Economists as Publications of 

Enduring Value in 2003. Dr. Freeman received his PhD from the University of 

Washington. 

Montserrat Fuentes is an associate professor in the Department of Statistics at 

North Carolina State University (NCSU) and holds associate status in the NCSU 

Department of Marine, Earth, and Atmospheric Sciences. Dr. Fuentes has developed new statistical methods that she applies to air-pollution, weatherprediction, hurricane-forecasting, and environmental health risk-assessment 

problems in collaboration with the air-quality modelers and scientists at the Environmental Protection Agency (EPA) and the National Center for Atmospheric 

Research. That work has led to numerous publications in statistical journals and 

books and in journals in the atmospheric sciences. She received the Abdel ElShaarawi Young Researcher’s Award in recognition of outstanding contributions to environmetric research in 2003. She is a member-elect of the International Statistical Institute and was a member of the Regional Advisory Board 

(Eastern North American Region) of the International Biometric Society. Dr. 

Fuentes is a member of the Exposure and Human Health Committee of the Environmental Protection Agency Science Advisory Board and the U.S. representative in the Board of Directors of the International Environmetrics Society. She is 

a member of the Biostatistical Methods and Research Design study section of 

the National Institutes of Health. Dr. Fuentes received her PhD in statistics from 

the University of Chicago. 

Daniel S. Greenbaum is the president and chief executive officer of the Health 

Effects Institute, an independent not-for-profit research institute funded jointly 

by government and industry to provide trusted research on the health effects of 

air pollution. At the Health Effects Institute, Mr. Greenbaum has overseen the 

development and implementation of a research plan that focuses the institute’s 

efforts on providing critical research on and reanalysis of particulate matter, air 

toxics, and alternative fuels, increasingly on an international scale. In 1999, he 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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Appendix A 209 

served as chair of the Environmental Protection Agency (EPA) Blue Ribbon 

Panel on Oxygenates in Gasoline, and in 2001, as chair of the EPA Clean Diesel 

Independent Review Panel, which affirmed that the 2007 heavy-duty diesel rules 

could be met. Before joining the Health Effects Institute, he served as commissioner of the Massachusetts Department of Environmental Protection. In the 

National Research Council, he has served on the Board on Environmental Studies and Toxicology, as vice chair of the Committee on Air Quality Management 

in the United States, and as a member of the Committee on Research Priorities 

for Airborne Particulate Matter. Mr. Greenbaum earned a master’s degree in city 

planning from the Massachusetts Institute of Technology. 

Alan Krupnick is a senior fellow and director of quality of the environment at 

Resources for the Future. His research focuses on analyzing environmental issues, in particular the benefits, costs, and design of air-pollution policies in the 

United States and in developing countries. His research also addresses the valuation of health and ecologic improvements and, more recently, the ancillary benefits of climate policy and urban transportation and development problems. Dr. 

Krupnick has served as a consultant to state governments, federal agencies, private corporations, the Canadian government, the European Union, the World 

Health Organization, and the World Bank. He co-chaired an advisory committee 

that counseled the U.S. Environmental Protection Agency on new ozone and 

particulate-matter standards. Dr. Krupnick has participated in several National 

Research Council studies, including those of the Committee for the Evaluation 

of the Congestion Mitigation and Air Quality Improvement Program, the Committee on Research and Peer Review in EPA, and the Surface Transportation 

Environmental Cooperative Research Program Advisory Board. He also has 

served on a Royal Society of Canada committee analyzing ambient-air quality 

standard-setting in Canada. Dr. Krupnick received his PhD in economics from 

the University of Maryland. 

Nino Künzli is a research professor of the Center for Research in Environmental 

Epidemiology (CREAL) at Municipal Institute of Medical Research (IMIM), 

Barcelona, Spain, and associate professor in leave of absence at the University 

of Southern California Keck School of Medicine (Department of Preventive 

Medicine; Environmental Health Science Division), Los Angeles. His research 

focus is environmental epidemiology with an emphasis on air-pollution epidemiology, including exposure and risk assessment. He has completed a European 

assessment of the public-health impact of outdoor and traffic-related air pollution. He was a member of the World Health Organization Air Pollution Health 

Impact Assessment Working Group. He also has served on the National Research Council Committee on Estimating the Health-Risk-Reduction Benefits of 

Proposed Air Pollution Regulations. Dr. Künzli received his MD from the University of Basel and his MPH and PhD from the University of California, Berkeley. 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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210 Ambient Ozone and Mortality: Estimating Risk-Reduction Benefits 

Kent E. Pinkerton is a professor of pediatric medicine and anatomy, 

physiology, and cell biology at the University of California, Davis. He also 

serves as director of the university’s Center for Health and the Environment. His 

research focuses on the health effects of environmental air pollutants on lung 

structure and function, the interaction of gases and airborne particles in specific 

sites and cell populations of the lungs in acute and chronic lung injury, and the 

effects of environmental tobacco smoke on lung growth and development. He 

received a PhD in pathology from Duke University. 

Armistead Russell is a professor of environmental engineering at the Georgia 

Institute of Technology. His research subjects include aerosol dynamics, atmospheric chemistry, emissions control, and air pollution-control strategy design 

and computer modeling. Dr. Russell has served on a number of National Research Council committees and was chair of the Committee to Review EPA’s 

Mobile Source Emissions Factor (MOBILE) Model. He received a PhD in mechanical engineering from the California Institute of Technology. 

Helen Suh is an associate professor of environmental chemistry and exposure 

assessment at Harvard University’s School of Public Health. Her research interests—air-pollutant exposures and their relationship to human health—involve 

the effect of exposure error, exposure modification, and confounding on epidemiology and toxicology, the contribution of indoor and outdoor sources to airpollutant exposures, and the impact of these exposures on cardiovascular health. 

Her work, including research conducted at the Environmental Protection Agency 

Center for Ambient Particle Health Effects, has been published in numerous 

journals. Dr. Suh received her ScD from Harvard University’s School of Public 

Health. 

Evelyn O. Talbott is a professor in the Department of Epidemiology and a professor in the Department of Speech Communication Sciences and Disorders at 

the University of Pittsburgh Graduate School of Public Health. Her major focus 

of research is women’s health and environmental epidemiology; her specific 

research interests include cardiovascular risk factors in women, environmental 

factors and cancer, and risk of coronary heart disease in women with polycystic 

ovary syndrome. She is the director of the University of Pittsburgh Academic 

Partner for Excellence in Environmental Public Health Tracking program, one 

of four academic centers in the United States that are funded by the Centers for 

Disease Control and Prevention (CDC) and charged to assist CDC implementation of a nationwide environmental public-health tracking network. She was a 

coinvestigator in an Allegheny County study of the relationship between air pollution and cardiopulmonary admissions of older people. Dr. Talbott received a 

PhD in epidemiology from the University of Pittsburgh. 
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211

Appendix B 

Environmental Protection Agency’s 

Regulatory Impact Analysis for the Final 

Ozone National Ambient Air Quality Standard 

Table B-1 (EPA 2008b, Table 7-14) shows a variety of assumptions about 

the association between ozone exposure and mortality. The table is presented 

here to illustrate that EPA had included the assumption of no causal association 

between estimated reductions in the incidence of premature mortality and reductions in ozone exposure. The committee recommends that future regulatory impact analyses (RIAs) give little or no weight to that assumption unless new information that refutes the interpretation of this association as causal emerges 

(see Chapter 6). Presentations like that included in Table 7-14 should be revised 

in light of this recommendation. 
Copyright © National Academy of Sciences. All rights reserved.

Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 

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TABLE B-1 (TABLE 7-14) Illustrative Strategy to Attain 0.075 ppm: Estimated Annual Reductions in the Incidence of 

Premature Mortality Associated with Ozone Exposure in 2020 (Incremental to Current Ozone Standard, Arithmetic Mean, 95% 

Confidence Intervals in Parentheses)b, c, d, e 

Model or Assumptiona Reference National Full Attainment NMAPS Bell et al. 2004 71 

(27-110) 

Meta-Analysis Bell et al. 2005 230 

(120-340) 

Ito et al. 2005 310 

(200-430) 

Levy et al. 2005 320 

(230-420) 

Assumption that association is not causal 0 

aDoes not represent equal weighting among models or between assumption of causality vs no causality (see text in section 6.3.2.1 [of EPA 

2008b]). 

bWith the exception of the assumption of no causal relationship, the arithmetic mean and 95% credible interval around the mean estimates of 

the annual number of lives saved are based on an assumption of a normal distribution. 

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

statistics. 

dAll estimates rounded to two significant figures. As such, confidence intervals may not be symmetrical. eThis table reflects full attainment in all locations of the U.S. except two areas of California. These two areas, which have high levels of ozone, 

are not planning to meet the current standard until after 2020. The estimates in the table do not reflect benefits for the San Joaquin and South 

Coast Air Basins. Source: EPA 2008b. 

212