1

Summary of Expert Opinions on the Existence of a Threshold in the 

Concentration-Response Function for PM2.5-related Mortality 

Technical Support Document (TSD) 

June 2010 

Compiled by: 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Health and Environmental Impact Division 

Air Benefit-Cost Group 

Research Triangle Park, North Carolina

Contents: 

A. HES comments on 812 Analysis (2010) 

B. American Heart Association Scientific Statement (2010) 

C. Integrated Science Assessment for Particulate Matter (2009) 

D. CASAC comments on PM ISA and REA (2009) 

E. Krewski et al. (2009) 

F. Schwartz et al. (2008) 

G. Expert Elicitation on PM Mortality (2006, 2008) 

H. CASAC comments on PM Staff Paper (2005) 

I. HES comments on 812 Analysis (2004) 

J. NRC (2002) 

 
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A. HES Comments on 812 Analysis (2010) 

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2010. Review of 

EPA’s DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clean Air Act. 

EPA-COUNCIL-10-001. June. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/0/72D4EFA39E48CDB28525774500738776/$File/EP

A-COUNCIL-10-001-unsigned.pdf>. 

Pg 2: “The HES generally agrees with other decisions made by the EPA project team with respect to PM, 

in particular, the PM mortality effect threshold model, the cessation lag model, the inclusion of infant 

mortality estimation, and differential toxicity of PM.” 

Pg 2: “Further, the HES fully supports EPA’s use of a no-threshold model to estimate the mortality 

reductions associated with reduced PM exposure.” 

Pg 6: “The HES also supports the Agency’s choice of a no-threshold model for PM-related effects.” 

Pg 13: “The HES fully supports EPA’s decision to use a no-threshold model to estimate mortality 

reductions. This decision is supported by the data, which are quite consistent in showing effects down to 

the lowest measured levels. Analyses of cohorts using data from more recent years, during which time 

PM concentrations have fallen, continue to report strong associations with mortality. Therefore, there is 

no evidence to support a truncation of the CRF.” 

HES Panel Members

Dr. John Bailar, Chair of the Health Effects Subcommittee, Scholar in Residence, The National 

Academies, Washington, DC 

Dr. Michelle Bell, Associate Professor, School of Forestry and Environmental Studies, Yale 

University, New Haven, CT 

Dr. James K. Hammitt, Professor, Department of Health Policy and Management, Harvard School of 

Public Health, Boston, MA 

Dr. Jonathan Levy, Associate Professor, Department of Environmental Health, Harvard School of 

Public Health, Boston, MA 

Dr. C. Arden Pope, III Professor, Department of Economics, Brigham Young University, Provo, UT 

Mr. John Fintan Hurley, Research Director, Institute of Occupational Medicine (IOM), Edinburgh, 

United Kingdom, UK 

Dr. Patrick Kinney, Professor, Department of Environmental Health Sciences, Mailman School of 

Public Health, Columbia University, New York, NY 

Dr. Michael T. Kleinman, Professor, Department of Medicine, Division of Occupational and 

Environmental Medicine, University of California, Irvine, Irvine, CA 

Dr. Bart Ostro, Chief, Air Pollution Epidemiology Unit, Office of Environmental Health Hazard 

Assessment, California Environmental Protection Agency, Oakland, CA 

Dr. Rebecca Parkin, Professor and Associate Dean, Environmental and Occupational Health, School of 

Public Health and Health Services, The George Washington University Medical Center, Washington, 

DC 
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B. Scientific Statement from American Heart Association (2010) 

Brook RD, Rajagopalan S, Pope CA 3rd, Brook JR, Bhatnagar A, Diez-Roux AV, Holguin F, Hong 

Y, Luepker RV, Mittleman MA, Peters A, Siscovick D, Smith SC Jr, Whitsel L, Kaufman JD; on 

behalf of the American Heart Association Council on Epidemiology and Prevention, Council on 

the Kidney in Cardiovascular Disease, and Council on Nutrition, Physical Activity and 

Metabolism. (2010). “Particulate matter air pollution and cardiovascular disease: an update to 

the scientific statement from the American Heart Association.” Circulation. 121: 2331-2378. 

Pg 2338: “Finally, there appeared to be no lower-limit threshold below which PM10 was not associated 

with excess mortality across all regions.” 

Pg 2350: “There also appears to be a monotonic (eg, linear or log-linear) concentration-response 

relationship between PM2.5 and mortality risk observed in cohort studies that extends below present-day 

regulations of 15 μg/m3

 for mean annual levels, without a discernable “safe” threshold.” (cites Pope 2004, 

Krewski 2009, and Schwartz 2008)

Pg 2364: “The PM2.5 concentration– cardiovascular risk relationships for both short- and long-term 

exposures appear to be monotonic, extending below 15 μg/m3 (the 2006 annual NAAQS level) without a 

discernable “safe” threshold.” 

Pg 2365: “This updated review by the AHA writing group corroborates and strengthens the conclusions 

of the initial scientific statement. In this context, we agree with the concept and continue to support 

measures based on scientific evidence, such as the US EPA NAAQS, that seek to control PM levels to 

protect the public health. Because the evidence reviewed supports that there is no safe threshold, it 

appears that public health benefits would accrue from lowering PM2.5 concentrations even below presentday annual (15 μg/m3

) and 24-hour (35 μg/m3) NAAQS, if feasible, to optimally protect the most 

susceptible populations.” 

Pg 2366: “Although numerous insights have greatly enhanced our understanding of the PMcardiovascular relationship since the first AHA statement was published, the following list represents 

broad strategic avenues for future investigation: ... Determine whether any “safe” PM threshold 

concentration exists that eliminates both acute and chronic cardiovascular effects in healthy and 

susceptible individuals and at a population level.” 

Scientific Statement Authors

Dr. Robert D. Brook, MD 

Dr. Sanjay Rajagopalan, MD 

Dr. C. Arden Pope, PhD 

Dr. Jeffrey R. Brook, PhD 

Dr. Aruni Bhatnagar, PhD, FAHA 

Dr. Ana V. Diez-Roux, MD, PhD, MPH 

Dr. Fernando Holguin, MD 

Dr. Yuling Hong, MD, PhD, FAHA 

Dr. Russell V. Luepker, MD, MS, FAHA 

Dr. Murray A. Mittleman, MD, DrPH, FAHA 
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Dr. Annette Peters, PhD 

Dr. David Siscovick, MD, MPH, FAHA 

Dr. Sidney C. Smith, Jr, MD, FAHA 

Dr. Laurie Whitsel, PhD 

Dr. Joel D. Kaufman, MD, MPH 

 
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C. Integrated Science Assessment for Particulate Matter (2009) 

U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for 

Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for Environmental 

Assessment – RTP Division. December. Available on the Internet at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>. 

Pg 1-22: “An important consideration in characterizing the public health impacts associated with 

exposure to a pollutant is whether the concentration-response relationship is linear across the full 

concentration range encountered, or if nonlinear relationships exist along any part of this range. Of 

particular interest is the shape of the concentration-response curve at and below the level of the current 

standards. The shape of the concentration-response curve varies, depending on the type of health 

outcome, underlying biological mechanisms and dose. At the human population level, however, various 

sources of variability and uncertainty tend to smooth and “linearize” the concentration-response function 

(such as the low data density in the lower concentration range, possible influence of measurement error, 

and individual differences in susceptibility to air pollution health effects). In addition, many chemicals 

and agents may act by perturbing naturally occurring background processes that lead to disease, which 

also linearizes population concentration-response relationships (Clewell and Crump, 2005, 156359; 

Crump et al., 1976, 003192; Hoel, 1980, 156555). These attributes of population dose-response may 

explain why the available human data at ambient concentrations for some environmental pollutants (e.g., 

PM, O3, lead [Pb], ETS, radiation) do not exhibit evident thresholds for health effects, even though likely 

mechanisms include nonlinear processes for some key events. These attributes of human population doseresponse relationships have been extensively discussed in the broader epidemiologic literature (Rothman 

and Greenland, 1998, 086599).” 

Pg 2-16: “In addition, cardiovascular hospital admission and mortality studies that examined the PM10 

concentration-response relationship found evidence of a log-linear no-threshold relationship between PM 

exposure and cardiovascular-related morbidity (Section 6.2) and mortality (Section 6.5).” 

Pg 2-25: “2.4.3. PM Concentration-Response Relationship 

An important consideration in characterizing the PM-morbidity and mortality association is whether the 

concentration-response relationship is linear across the full concentration range that is encountered or if 

there are concentration ranges where there are departures from linearity (i.e., nonlinearity). In this ISA 

studies have been identified that attempt to characterize the shape of the concentration-response curve 

along with possible PM “thresholds” (i.e., levels which PM concentrations must exceed in order to elicit a 

health response). The epidemiologic studies evaluated that examined the shape of the concentrationresponse curve and the potential presence of a threshold have focused on cardiovascular hospital 

admissions and ED visits and mortality associated with short-term exposure to PM10 and mortality 

associated with long-term exposure to PM2.5. 

“A limited number of studies have been identified that examined the shape of the PM cardiovascular 

hospital admission and ED visit concentration-response relationship. Of these studies, some conducted an 

exploratory analysis during model selection to determine if a linear curve most adequately represented the 

concentration-response relationship; whereas, only one study conducted an extensive analysis to examine 

the shape of the concentration-response curve at different concentrations (Section 6.2.10.10). Overall, the 

limited evidence from the studies evaluated supports the use of a no-threshold, log-linear model, which is 

consistent with the observations made in studies that examined the PM-mortality relationship. 

“Although multiple studies have previously examined the PM-mortality concentration-response 

relationship and whether a threshold exists, more complex statistical analyses continue to be developed to 

analyze this association. Using a variety of methods and models, most of the studies evaluated support the 
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use of a no-threshold, log-linear model; however, one study did observe heterogeneity in the shape of the 

concentration-response curve across cities (Section 6.5). Overall, the studies evaluated further support the 

use of a no-threshold log-linear model, but additional issues such as the influence of heterogeneity in 

estimates between cities, and the effect of seasonal and regional differences in PM on the concentrationresponse relationship still require further investigation. 

“In addition to examining the concentration-response relationship between short-term exposure to PM and 

mortality, Schwartz et al. (2008, 156963) conducted an analysis of the shape of the concentrationresponse relationship associated with long-term exposure to PM. Using a variety of statistical methods, 

the concentration-response curve was found to be indistinguishable from linear, and, therefore, little 

evidence was observed to suggest that a threshold exists in the association between long-term exposure to 

PM2.5 and the risk of death (Section 7.6).” 

Pg 6-75: “6.2.10.10. Concentration Response 

The concentration-response relationship has been extensively analyzed primarily through studies that 

examined the relationship between PM and mortality. These studies, which have focused on short- and 

long-term exposures to PM have consistently found no evidence for deviations from linearity or a safe 

threshold (Daniels et al., 2004, 087343; Samoli et al., 2005, 087436; Schwartz, 2004, 078998; Schwartz 

et al., 2008, 156963) (Sections 6.5.2.7 and 7.1.4). Although on a more limited basis, studies that have 

examined PM effects on cardiovascular hospital admissions and ED visits have also analyzed the PM 

concentration-response relationship, and contributed to the overall body of evidence which suggests a loglinear, no-threshold PM concentration-response relationship. 

“The results from the three multicity studies discussed above support no-threshold log-linear models, but 

issues such as the possible influence of exposure error and heterogeneity of shapes across cities remain to 

be resolved. Also, given the pattern of seasonal and regional differences in PM risk estimates depicted in 

recent multicity study results (e.g., Peng et al., 2005, 087463), the very concept of a concentrationresponse relationship estimated across cities and for all-year data may not be very informative.” 

Pg 6-197: “6.5.2.7. Investigation of Concentration-Response Relationship 

The results from large multicity studies reviewed in the 2004 PM AQCD (U.S. EPA, 2004, 056905) 

suggested that strong evidence did not exist for a clear threshold for PM mortality effects. However, as 

discussed in the 2004 PM AQCD (U.S. EPA, 2004, 056905), there are several challenges in determining 

and interpreting the shape of PM-mortality concentration-response functions and the presence of a 

threshold, including: (1) limited range of available concentration levels (i.e., sparse data at the low and 

high end); (2) heterogeneity of susceptible populations; and (3) investigate the PM-mortality 

concentration-response relationship. 

“Daniels et al. (2004, 087343) evaluated three concentration-response models: (1) log-linear models (i.e., 

the most commonly used approach, from which the majority of risk estimates are derived); (2) spline 

models that allow data to fit possibly non-linear relationship; and (3) threshold models, using PM10 data 

in 20 cities from the 1987-1994 NMMAPS data. They reported that the spline model, combined across 

the cities, showed a linear relation without indicating a threshold for the relative risks of death for allcauses and for cardiovascular-respiratory causes in relation to PM10, but “the other cause” deaths (i.e., all 

cause minus cardiovascular-respiratory) showed an apparent threshold at around 50 μg/m3

 PM10, as 

shown in Figure 6-35. For all-cause and cardio-respiratory deaths, based on the Akaike’s Information 

Criterion (AIC), a log-linear model without threshold was preferred to the threshold model and to the 

spline model. 

“The HEI review committee commented that interpretation of these results required caution, because (1) 

the measurement error could obscure any threshold; (2) the city-specific concentration-response curves 
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exhibited a variety of shapes; and (3) the use of AIC to choose among the models might not be 

appropriate due to the fact it was not designed to assess scientific theories of etiology. Note, however, that 

there has been no etiologically credible reason suggested thus far to choose one model over others for 

aggregate outcomes. Thus, at least statistically, the result of Daniels et al. (2004, 087343) suggests that 

the log-linear model is appropriate in describing the relationship between PM10 and mortality. 

“The Schwartz (2004, 078998) analysis of PM10 and mortality in 14 U.S. cities, described in Section 

6.5.2.1, also examined the shape of the concentration-response relationship by including indicator 

variables for days when concentrations were between 15 and 25 μg/m3

, between 25 and 34 μg/m3, 

between 35 and 44 μg/m3

, and 45 μg/m3 and above. In the model, days with concentrations below 15 

μg/m3

 served as the reference level. This model was fit using the single stage method, combining strata 

across all cities in the case-crossover design. Figure 6-36 shows the resulting relationship, which does not 

provide sufficient evidence to suggest that a threshold exists. The authors did not examine city-to-city 

variation in the concentration-response relationship in this study. 

“PM10 and mortality in 22 European cities (and BS in 15 of the cities) participating in the APHEA project. 

In nine of the 22 cities, PM10 levels were estimated using a regression model relating co-located PM10 to 

BS or TSP. They used regression spline models with two knots (30 and 50 μg/m3

) and then combined the 

individual city estimates of the splines across cities. The investigators concluded that the association 

between PM and mortality in these cities could be adequately estimated using the log-linear model. 

However, in an ancillary analysis of the concentration-response curves for the largest cities in each of the 

three distinct geographic areas (western, southern, and eastern European cities): London, England; 

Athens, Greece; and Cracow, Poland, Samoli et al. (2005, 087436) observed a difference in the shape of 

the concentration-response curve across cities. Thus, while the combined curves (Figure 6-37) appear to 

support no-threshold relationships between PM10 and mortality, the heterogeneity of the shapes across 

cities makes it difficult to interpret the biological relevance of the shape of the combined curves. 

“The results from the three multicity studies discussed above support no-threshold log-linear models, but 

issues such as the possible influence of exposure error and heterogeneity of shapes across cities remain to 

be resolved. Also, given the pattern of seasonal and regional differences in PM risk estimates depicted in 

recent multicity study results (e.g., Peng et al., 2005, 087463), the very concept of a concentrationresponse relationship estimated across cities and for all-year data may not be very informative.” 

Authors of ISA

Dr. Lindsay Wichers Stanek (PM Team Leader)—National Center for Environmental Assessment 

(NCEA), U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, NC 

Dr. Jeffrey Arnold—NCEA, U.S. EPA, Research Triangle Park, NC (now at Institute for Water 

Resources, U.S. Army Corps of Engineers, Washington, D.C) 

Dr. Christal Bowman—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. James S. Brown—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Barbara Buckley—NCEA, U.S. EPA, Research Triangle Park, NC 

Mr. Allen Davis—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Jean-Jacques Dubois—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Steven J. Dutton—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Tara Greaver—NCEA, U.S. EPA, Research Triangle Park, NC 
8

Dr. Erin Hines—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Douglas Johns—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Ellen Kirrane—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Dennis Kotchmar—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Thomas Long—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Thomas Luben—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Qingyu Meng—Oak Ridge Institute for Science and Education, Postdoctoral Research Fellow to 

NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Kristopher Novak—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Joseph Pinto—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Jennifer Richmond-Bryant—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Mary Ross—NCEA, U.S. EPA, Research Triangle Park, NC 

Mr. Jason Sacks—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Timothy J. Sullivan—E&S Environmental Chemistry, Inc., Corvallis, OR 

Dr. David Svendsgaard—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Lisa Vinikoor—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. William Wilson—NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Lori White— NCEA, U.S. EPA, Research Triangle Park, NC (now at National Institute for 

Environmental Health Sciences, Research Triangle Park, NC) 

Dr. Christy Avery—University of North Carolina, Chapel Hill, NC 

Dr. Kathleen Belanger —Center for Perinatal, Pediatric and Environmental Epidemiology, Yale 

University, New Haven, CT 

Dr. Michelle Bell—School of Forestry & Environmental Studies, Yale University, New Haven, CT 

Dr. William D. Bennett—Center for Environmental Medicine, Asthma and Lung Biology, University of 

North Carolina, Chapel Hill, NC 

Dr. Matthew J. Campen—Lovelace Respiratory Research Institute, Albuquerque, NM 

Dr. Leland B. Deck— Stratus Consulting, Inc., Washington, DC 

Dr. Janneane F. Gent—Center for Perinatal, Pediatric and Environmental Epidemiology, Yale 

University, New Haven, CT 

Dr. Yuh-Chin Tony Huang—Department of Medicine, Division of Pulmonary Medicine, Duke 

University Medical Center, Durham, NC 

Dr. Kazuhiko Ito—Nelson Institute of Environmental Medicine, NYU School of Medicine, Tuxedo, NY 

Mr. Marc Jackson—Integrated Laboratory Systems, Inc., Research Triangle Park, NC 

Dr. Michael Kleinman—Department of Community and Environmental Medicine, University of 

California, Irvine 

Dr. Sergey Napelenok—National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, 

NC 
9

Dr. Marc Pitchford—National Oceanic and Atmospheric Administration, Las Vegas, NV 

Dr. Les Recio—Genetic Toxicology Division, Integrated Laboratory Systems, Inc., Research Triangle 

Park, NC 

Dr. David Quincy Rich—Department of Epidemiology, University of Medicine and Dentistry of New 

Jersey, Piscataway, NJ 

Dr. Timothy Sullivan— E&S Environmental Chemistry, Inc., Corvallis, OR 

Dr. George Thurston—Department of Environmental Medicine, NYU, Tuxedo, NY 

Dr. Gregory Wellenius—Cardiovascular Epidemiology Research Unit, Beth Israel Deaconess Medical 

Center, Boston, MA 

Dr. Eric Whitsel—Departments of Epidemiology and Medicine, University of North Carolina, Chapel 

Hill, NC 

Peer Reviewers

Dr. Sara Dubowsky Adar, Department of Epidemiology, University of Washington, Seattle, WA 

Mr. Chad Bailey, Office of Transportation and Air Quality, Ann Arbor, MI 

Mr. Richard Baldauf, Office of Transportation and Air Quality, Ann Arbor, MI 

Dr. Prakash Bhave, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC 

Mr. George Bowker, Office of Atmospheric Programs, U.S. EPA, Washington, D.C. 

Dr. Judith Chow, Division of Atmospheric Sciences, Desert Research Institute, Reno, NV 

Dr. Dan Costa, U.S. EPA, Research Triangle Park, NC 

Dr. Ila Cote, NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Robert Devlin, National Health and Environmental Effects Research Laboratory, U.S. EPA, 

Research Triangle Park, NC 

Dr. David DeMarini, National Health and Environmental Effects Research Laboratory, U.S. EPA, 

Research Triangle Park, NC 

Dr. Neil Donahue, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 

Dr. Aimen Farraj, National Health and Environmental Effects Research Laboratory, U.S. EPA, 

Research Triangle Park, NC 

Dr. Mark Frampton, Department of Environmental Medicine, University of Rochester Medical Center, 

Rochester, NY 

Mr. Neil Frank, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Mr. Tyler Fox, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Dr. Jim Gauderman, Department of Environmental Medicine, Department of Preventive Medicine, 

University of Southern California, Los Angeles, CA 

Dr. Barbara Glenn, National Center for Environmental Research, U.S. EPA, Washington, D.C. 

Dr. Terry Gordon, School of Medicine, New York University, Tuxedo, NY 

Mr. Tim Hanley, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Dr. Jack Harkema, Department of Pathobiology and Diagnostic Investigation, Michigan State 

University, East Lansing, MI 
10

Ms. Beth Hassett-Sipple, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle 

Park, NC 

Dr. Amy Herring, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 

Dr. Israel Jirak, Department of Meteorology, Embry-Riddle Aeronautical University, Prescott, AZ 

Dr. Mike Kleeman, Department of Civil and Environmental Engineering, University of California, 

Davis, CA 

Dr. Petros Koutrakis, Exposure, Epidemiology and Risk Program, Harvard School of Public Health, 

Boston, MA 

Dr. Sagar Krupa, Department of Plant Pathology, University of Minnesota, St. Paul, MN 

Mr. John Langstaff, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Dr. Meredith Lassiter, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle 

Park, NC 

Mr. Phil Lorang, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Dr. Karen Martin, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Ms. Connie Meacham, NCEA, U.S. EPA, Research Triangle Park, NC 

Mr. Tom Pace, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Dr. Jennifer Peel, Department of Environmental and Radiological Health Sciences, College of 

Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO 

Dr. Zackary Pekar, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Mr. Rob Pinder, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC 

Mr. Norm Possiel, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Dr. Sanjay Rajagopalan, Division of Cardiovascular Medicine, Ohio State University, Columbus, OH 

Dr. Pradeep Rajan, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Mr. Venkatesh Rao, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Ms. Joann Rice, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 

Mr. Harvey Richmond, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle 

Park, NC 

Ms. Victoria Sandiford, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle 

Park, NC 

Dr. Stefanie Sarnat, Department of Environmental and Occupational Health, Emory University, Atlanta, 

GA 

Dr. Frances Silverman, Gage Occupational and Environmental Health, University of Toronto, Toronto, 

ON 

Mr. Steven Silverman, Office of General Council, U.S. EPA, Washington, D.C. 
11

Dr. Barbara Turpin, Department of Environmental Sciences, Rutgers University, New Brunswick, NJ 

Dr. Robert Vanderpool, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, 

NC 

Dr. John Vandenberg (Director)—NCEA-RTP Division, U.S. EPA, Research Triangle Park, NC 

Dr. Alan Vette, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC 

Ms. Debra Walsh (Deputy Director)—NCEA-RTP Division, U.S. EPA, Research Triangle Park, NC 

Mr. Tim Watkins, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC 

Dr. Christopher Weaver, NCEA, U.S. EPA, Research Triangle Park, NC 

Mr. Lewis Weinstock, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Ms. Karen Wesson, Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, 

NC 

Dr. Jason West, Department of Environmental Sciences and Engineering, University of North Carolina, 

Chapel Hill, NC 

Mr. Ronald Williams, National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC 

Dr. George Woodall, NCEA, U.S. EPA, Research Triangle Park, NC 

Dr. Antonella Zanobetti, Department of Environmental Health, Harvard School of Public Health, 

Boston, MA 
12

D. CASAC comments on PM ISA and REA (2009) 

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009. Review 

of EPA’s Integrated Science Assessment for Particulate Matter (First External Review Draft, 

December 2008). EPA-COUNCIL-09-008. May. Available on the Internet at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/73ACCA

834AB44A10852575BD0064346B/$File/EPA-CASAC-09-008-unsigned.pdf>. 

Pg 9: “There is an appropriate discussion of the time-series studies, but this section needs to have an 

explicit finding that the evidence supports a relationship between PM and mortality that is seen in these 

studies. This conclusion should be followed by the discussion of statistical methodology and the 

identification of any threshold that may exist.” 

U.S. Environmental Protection Agency Science Advisory Board (U.S. EPA-SAB). 2009. 

Consultation on EPA’s Particulate Matter National Ambient Air Quality Standards: Scope and 

Methods Plan for Health Risk and Exposure Assessment. EPA-COUNCIL-09-009. May. 

Available on the Internet at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/723FE64

4C5D758DF852575BD00763A32/$File/EPA-CASAC-09-009-unsigned.pdf>. 

Pg 6: “On the issue of cut-points raised on 3-18, the authors should be prepared to offer a scientifically 

cogent reason for selection of a specific cut-point, and not simply try different cut-points to see what 

effect this has on the analysis. The draft ISA was clear that there is little evidence for a population 

threshold in the C-R function.” 

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2009. Review 

of Integrated Science Assessment for Particulate Matter (Second External Review Draft, July 2009). 

EPA-CASAC-10-001. November. Available on the Internet at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86e/151B1F8

3B023145585257678006836B9/$File/EPA-CASAC-10-001-unsigned.pdf>. 

Pg 2: “The paragraph on lines 22-30 of page 2-37 is not clearly written. Twice in succession it states that 

the use of a no-threshold log-linear model is supported, but then cites other studies that suggest otherwise. 

It would be good to revise this paragraph to more clearly state – well, I’m not sure what. Probably that 

more research is needed.” 

CASAC Panel Members

Dr. Jonathan M. Samet, Professor and Chair, Department of Preventive Medicine, University of 

Southern California, Los Angeles, CA 

Dr. Joseph Brain, Philip Drinker Professor of Environmental Physiology, Department of Environmental 

Health, Harvard School of Public Health, Harvard University, Boston, MA 

Dr. Ellis B. Cowling, University Distinguished Professor At-Large Emeritus, Colleges of Natural 

Resources and Agriculture and Life Sciences, North Carolina State University, Raleigh, NC 

Dr. James Crapo, Professor of Medicine, Department of Medicine, National Jewish Medical and 

Research Center, Denver, CO 

Dr. H. Christopher Frey, Professor, Department of Civil, Construction and Environmental Engineering, 

College of Engineering, North Carolina State University, Raleigh, NC 
13

Dr. Armistead (Ted) Russell, Professor, Department of Civil and Environmental Engineering, Georgia 

Institute of Technology, Atlanta, GA 

Dr. Lowell Ashbaugh, Associate Research Ecologist, Crocker Nuclear Lab, University of California, 

Davis, Davis, CA 

Prof. Ed Avol, Professor, Preventive Medicine, Keck School of Medicine, University of Southern 

California, Los Angeles, CA 

Dr. Wayne Cascio, Professor, Medicine, Cardiology, Brody School of Medicine at East Carolina 

University, Greenville, NC 

Dr. David Grantz, Director, Botany and Plant Sciences and Air Pollution Research Center, Riverside 

Campus and Kearney Agricultural Center, University of California, Parlier, CA 

Dr. Joseph Helble, Dean and Professor, Thayer School of Engineering, Dartmouth College, Hanover, 

NH 

Dr. Rogene Henderson, Senior Scientist Emeritus, Lovelace Respiratory Research Institute, 

Albuquerque, NM 

Dr. Philip Hopke, Bayard D. Clarkson Distinguished Professor, Department of Chemical Engineering, 

Clarkson University, Potsdam, NY 

Dr. Morton Lippmann, Professor, Nelson Institute of Environmental Medicine, New York University 

School of Medicine, Tuxedo, NY 

Dr. Helen Suh MacIntosh, Associate Professor, Environmental Health, School of Public Health, 

Harvard University, Boston, MA 

Dr. William Malm, Research Physicist, National Park Service Air Resources Division, Cooperative 

Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 

Mr. Charles Thomas (Tom) Moore, Jr., Air Quality Program Manager, Western Governors' 

Association, Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort 

Collins, CO 

Dr. Robert F. Phalen, Professor, Department of Community & Environmental Medicine; Director, Air 

Pollution Health Effects Laboratory; Professor of Occupational & Environmental Health, Center for 

Occupation & Environment Health, College of Medicine, University of California Irvine, Irvine, CA 

Dr. Kent Pinkerton, Professor, Regents of the University of California, Center for Health and the 

Environment, University of California, Davis, CA 

Mr. Richard L. Poirot, Environmental Analyst, Air Pollution Control Division, Department of 

Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VT 

Dr. Frank Speizer, Edward Kass Professor of Medicine, Channing Laboratory, Harvard Medical School, 

Boston, MA 

Dr. Sverre Vedal, Professor, Department of Environmental and Occupational Health Sciences, School of 

Public Health and Community Medicine, University of Washington, Seattle, WA 

Dr. Donna Kenski, Data Analysis Director, Lake Michigan Air Directors Consortium, Rosemont, IL 

Dr. Kathy Weathers, Senior Scientist, Cary Institute of Ecosystem Studies, Millbrook, NY
14

E. Krewski et al. (2009) 

Krewski, Daniel, Michael Jerrett, Richard T. Burnett, Renjun Ma, Edward Hughes, Yuanli Shi, 

Michelle C. Turner, C. Arden Pope III, George Thurston, Eugenia E. Calle, and Michael J. Thun 

with Bernie Beckerman, Pat DeLuca, Norm Finkelstein, Kaz Ito, D.K. Moore, K. Bruce Newbold, 

Tim Ramsay, Zev Ross, Hwashin Shin, and Barbara Tempalski. (2009). Extended follow-up and 

spatial analysis of the American Cancer Society study linking particulate air pollution and 

mortality. HEI Research Report, 140, Health Effects Institute, Boston, MA. 

Pg 119: [About Pope et al. (2002)] “Each 10-μg/m3

 increase in longterm average ambient PM2.5

concentrations was associated with approximately a 4%, 6%, or 8% increase in risk of death from all 

causes, cardiopulmonary disease, and lung cancer, respectively. There was no evidence of a threshold 

exposure level within the range of observed PM2.5 concentrations. “ 

Krewski (2009). Letter from Dr. Daniel Krewski to HEI’s Dr. Kate Adams (dated July July 7, 2009) 

regarding “EPA queries regarding HEI Report 140”. Dr. Adams then forwarded the letter on 

July 10, 2009 to EPA’s Beth Hassett-Sipple. (letter placed in docket #EPA-HQ-OAR-2007-0492). 

Pg 4: “6. The Health Review Committee commented that the Updated Analysis completed by 

Pope et al. 2002 reported “no evidence of a threshold exposure level within the range of observed PM2.5 

concentrations” (p. 119). In the Extended Follow-Up study, did the analyses provide continued support 

for a no-threshold response or was there evidence of a threshold? 

“Response: As noted above, the HEI Health Review Committee commented on the lack of evidence for a 

threshold exposure level in Pope et al. (2002) with follow-up through the year 1998. The present report, 

which included follow-up through the year 2000, also does not appear to demonstrate the existence of a 

threshold in the exposure-response function within the range of observed PM2.5 concentrations.” 

HEI Health Review Committee Members

Dr. Homer A. Boushey, MD, Chair, Professor of Medicine, Department of Medicine, University of 

California–San Francisco 

Dr. Ben Armstrong, Reader, in Epidemiological Statistics, Department of Public Health and Policy, 

London School of Hygiene and Tropical Medicine, United Kingdom 

Dr. Michael Brauer, ScD, Professor, School of Environmental Health, University of British Columbia, 

Canada 

Dr. Bert Brunekreef, PhD, Professor of Environmental Epidemiology, Institute of Risk Assessment 

Sciences, University of Utrecht, The Netherlands 

Dr. Mark W. Frampton, MD, Professor of Medicine & Environmental Medicine, University of 

Rochester Medical Center, Rochester, NY 

Dr. Stephanie London, MD, PhD, Senior Investigator, Epidemiology Branch, National Institute of 

Environmental Health Sciences 

Dr. William N. Rom, MD, MPH, Sol and Judith Bergstein Professor of Medicine and Environmental 

Medicine and Director of Pulmonary and Critical Care Medicine, New York University Medical Center 

Dr. Armistead Russell, Georgia Power Distinguished Professor of Environmental Engineering, School 

of Civil and Environmental Engineering, Georgia Institute of Technology 

Dr. Lianne Sheppard, PhD, Professor, Department of Biostatistics, University of Washington 
15

F. Schwartz et al. (2008) 

Schwartz J, Coull B, Laden F. (2008). The Effect of Dose and Timing of Dose on the Association 

between Airborne Particles and Survival. Environmental Health Perspectives. 116: 64-69. 

Pg 67: “A key finding of this study is that there is little evidence for a threshold in the association 

between exposure to fine particles and the risk of death on follow-up, which continues well below the 

U.S. EPA standard of 15 μg/m3

.” 

Pg 68: “In conclusion, penalized spline smoothing and model averaging represent reasonable, feasible 

approaches to addressing questions of the shape of the exposure–response curve, and can provide 

valuable information to decisionmakers. In this example, both approaches are consistent, and suggest that 

the association of particles with mortality has no threshold down to close to background levels.” 

 
16

G. Expert Elicitation on PM-Mortality (2006, 2008) 

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

of Air Quality Planning and Standards, September. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_report.pdf>. 

Pg v: “Each expert was given the option to integrate their judgments about the likelihood of a causal 

relationship and/or threshold in the C-R function into his distribution or to provide a distribution 

"conditional on" one or both of these factors.” 

Pg vii: “Only one of 12 experts explicitly incorporated a threshold into his C-R function.3 The rest 

believed there was a lack of empirical and/or theoretical support for a population threshold. However, 

three other experts gave differing effect estimate distributions above and below some cut-off 

concentration. The adjustments these experts made to median estimates and/or uncertainty at lower PM2.5 

concentrations were modest.” 

“

3

 Expert K indicated that he was 50 percent sure that a threshold existed. If there were a 

threshold, he thought that there was an 80 percent chance that it would be less than or 

equal to 5 μg/m3

, and a 20 percent chance that it would fall between 5 and 10 μg/m3.” 

Pg ix: “Compared to the pilot study, experts in this study were in general more confident in a causal 

relationship, less likely to incorporate thresholds, and reported higher mortality effect estimates. The 

differences in results compared with the pilot appear to reflect the influence of new research on the 

interpretation of the key epidemiological studies that were the focus of both elicitation studies, more than 

the influence of changes to the structure of the protocol.” 

Pg 3-25: “3.1.8 THRESHOLDS 

The protocol asked experts for their judgments regarding whether a threshold exists in the PM2.5 mortality 

C-R function. The protocol focused on assessing expert judgments regarding theory and evidential 

support for a population threshold (i.e., the concentration below which no member of the study population 

would experience an increased risk of death).32 If an expert wished to incorporate a threshold in his 

characterization of the concentration-response relationship, the team then asked the expert to specify the 

threshold PM2.5 concentration probabilistically, incorporating his uncertainty about the true threshold 

level. 

“From a theoretical and conceptual standpoint, all experts generally believed that individuals exhibit 

thresholds for PM-related mortality. However, 11 of them discounted the idea of a population threshold in 

the C-R function on a theoretical and/or empirical basis. Seven of these experts noted that theoretically 

one would be unlikely to observe a population threshold due to the variation in susceptibility at any given 

time in the study population resulting from combinations of genetic, environmental, and socioeconomic 

factors.33 All 11 thought that there was insufficient empirical support for a population threshold in the CR function. In addition, two experts (E and L) cited analyses of the ACS cohort data in Pope et al. (2002) 

and another (J) cited Krewski et al. (2000a & b) as supportive of a linear relationship in the study range. 

“Seven of the experts favored epidemiological studies as ideally the best means of addressing the 

population threshold issue, because they are best able to evaluate the full range of susceptible individuals 

at environmentally relevant exposure levels. However, those who favored epidemiologic studies generally 

acknowledged that definitive studies addressing thresholds would be difficult or impossible to conduct, 

because they would need to include a very large and diverse population with wide variation in exposure 

and a long follow-up period. Furthermore, two experts (B and I) cited studies documenting difficulties in 

detecting a threshold using epidemiological studies (Cakmak et al. 1999, and Brauer et al., 2002, 
17

respectively). The experts generally thought that clinical and toxicological studies are best suited for 

researching mechanisms and for addressing thresholds in very narrowly defined groups. One expert, B, 

thought that a better understanding of the detailed biological mechanism is critical to addressing the 

question of a threshold. 

“One expert, K, believed it was possible to make a conceptual argument for a population threshold. He 

drew an analogy with smoking, indicating that among heavy smokers, only a proportion of them gets lung 

cancer or demonstrates an accelerated decline in lung function. He thought that the idea that there is no 

level that is biologically safe is fundamentally at odds with toxicological theory. He did not think that a 

population threshold was detectable in the currently available epidemiologic studies. He indicated that 

some of the cohort studies showed greater uncertainty in the shape of the C-R function at lower levels, 

which could be indicative of a threshold. 

“Expert K chose to incorporate a threshold into his C-R function. He indicated that he was 50 percent sure 

that a threshold existed. If there were a threshold, he thought that there was an 80 percent chance that it 

would be less than or equal to 5 μg/m3

, and a 20 percent chance that it would fall between 5 and 10 

μg/m3

.” 

Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, 

Bryan J. Hubbell, and Patrick L. Kinney. (2008). “Expert Judgment Assessment of the Mortality 

Impact of Changes in Ambient Fine Particulate Matter in the U.S.” Environ. Sci. Technol., 

42(7):2268-2274. 

Pg 2271: “Eight experts thought the true C-R function relating mortality to changes in annual average 

PM2.5 was log-linear across the entire study range (ln(mortality) ) β × PM). Four experts (B, F, K, and L) 

specified a “piecewise” log-linear function, with different β coefficients for PM concentrations above and 

below an expert-specified break point. This approach allowed them to express increased uncertainty in 

mortality effects seen at lower concentrations in major epidemiological studies. Expert K thought the 

relationship would be log-linear above a threshold.” 

Pg 2271: “Expert K also applied a threshold, T, to his function, which he described probabilistically. He 

specified P(T > 0) = 0.5. Given T > 0, he indicated P(T ≤ 5 μg/m3

) = 0.8 and P(5 μg/m3 < T ≤ 10 μg/m3) 

= 0.2. Figure 3 does not include the impact of applying expert K’s threshold, as the size of the reduction 

in benefits will depend on the distribution of baseline PM levels in a benefits analysis.” 

Experts:

Dr. Doug W. Dockery, Harvard School of Public Health 

Dr. Kazuhiko Ito, Nelson Institute of Environmental Medicine, NYU School of Medicine, Tuxedo, NY 

Dr. Dan Krewski, University of Ottawa 

Dr. Nino Künzli, University of Southern California Keck School of Medicine 

Dr. Morton Lippmann, Professor, Nelson Institute of Environmental Medicine, New York University 

School of Medicine, Tuxedo, NY 

Dr. Joe Mauderly, Lovelace Respiratory Research Institute 

Dr. Bart Ostro, Chief, Air Pollution Epidemiology Unit, Office of Environmental Health Hazard 

Assessment, California Environmental Protection Agency, Oakland, CA 

Dr. Arden Pope, Professor, Department of Economics, Brigham Young University, Provo, UT 
18

Dr. Richard Schlesinger, Pace University 

Dr. Joel Schwartz, Harvard School of Public Health 

Dr. George Thurston—Department of Environmental Medicine, NYU, Tuxedo, NY 

Dr. Mark Utell, University of Rochester School of Medicine and Dentistry 
19

H. CASAC comments on PM Staff Paper (2005) 

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2005. EPA’s 

Review of the National Ambient Air Quality Standards for Particulate Matter (Second Draft PM 

Staff Paper, January 2005). EPA-SAB-CASAC-05-007. June. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/E523DD36175EB5AD8525701B007332AE/$File/SABCASAC-05-007_unsigned.pdf>. 

Pg 6: “A second concern is with methodological issues. The issue of the selection of concentrationresponse (C-R) relationships based on locally-derived coefficients needs more discussion. The Panel did 

not agree with EPA staff in calculating the burden of associated incidence in their risk assessment using 

either the predicted background or the lowest measured level (LML) in the utilized epidemiological 

analysis. The available epidemiological database on daily mortality and morbidity does not establish 

either the presence or absence of threshold concentrations for adverse health effects. Thus, in order to 

avoid emphasizing an approach that assumes effects that extend to either predicted background 

concentrations or LML, and to standardize the approach across cities, for the purpose of estimating public 

health impacts, the Panel favored the primary use of an assumed threshold of 10 μg/m3

. The original 

approach of using background or LML, as well as the other postulated thresholds, could still be used in a 

sensitivity analysis of threshold assumptions. 

“The analyses in this chapter highlight the impact of assumptions regarding thresholds, or lack of 

threshold, on the estimates of risk. The uncertainty associated with threshold or nonlinear models needs 

more thorough discussion. A major research need is for more work to determine the existence and level of 

any thresholds that may exist or the shape of nonlinear concentration-response curves at low levels of 

exposure that may exist, and to reduce uncertainty in estimated risks at the lowest PM concentrations.” 

CASAC Panel Members

Dr. Rogene Henderson, Scientist Emeritus, Lovelace Respiratory Research Institute, Albuquerque, NM 

Dr. Ellis Cowling, University Distinguished Professor-at-Large, North Carolina State University, 

Colleges of Natural Resources and Agriculture and Life Sciences, North Carolina State University, 

Raleigh, NC 

Dr. James D. Crapo, Professor, Department of Medicine, Biomedical Research and PatientCare, 

National Jewish Medical and Research Center, Denver, CO 

Dr. Philip Hopke, Bayard D. Clarkson Distinguished Professor, Department of Chemical Engineering, 

Clarkson University, Potsdam, NY 

Dr. Jane Q. Koenig, Professor, Department of Environmental Health, School of Public Health and 

Community Medicine, University of Washington, Seattle, WA 

Dr. Petros Koutrakis, Professor of Environmental Science, Environmental Health , School of Public 

Health, Harvard University (HSPH), Boston, MA 

Dr. Allan Legge, President, Biosphere Solutions, Calgary, Alberta 

Dr. Paul J. Lioy, Associate Director and Professor, Environmental and Occupational Health Sciences 

Institute, UMDNJ - Robert Wood Johnson Medical School, NJ 

Dr. Morton Lippmann, Professor, Nelson Institute of Environmental Medicine, New York 

University School of Medicine, Tuxedo, NY 
20

Dr. Joe Mauderly, Vice President, Senior Scientist, and Director, National Environmental 

Respiratory Center, Lovelace Respiratory Research Institute, Albuquerque, NM 

Dr. Roger O. McClellan, Consultant, Albuquerque, NM 

Dr. Frederick J. Miller, Consultant, Cary, NC 

Dr. Gunter Oberdorster, Professor of Toxicology, Department of Environmental Medicine, School 

of Medicine and Dentistry, University of Rochester, Rochester, NY 

Mr. Richard L. Poirot, Environmental Analyst, Air Pollution Control Division, Department of 

Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VT 

Dr. Robert D. Rowe, President, Stratus Consulting, Inc., Boulder, CO 

Dr. Jonathan M. Samet, Professor and Chair, Department of Epidemiology, Bloomberg School of 

Public Health, Johns Hopkins University, Baltimore, MD 

Dr. Frank Speizer, Edward Kass Professor of Medicine, Channing Laboratory, Harvard Medical 

School, Boston, MA 

Dr. Sverre Vedal, Professor of Medicine, School of Public Health and Community Medicine 

University of Washington, Seattle, WA 

Mr. Ronald White, Research Scientist, Epidemiology, Bloomberg School of Public Health, Johns 

Hopkins University, Baltimore, MD 

Dr. Warren H. White, Visiting Professor, Crocker Nuclear Laboratory, University of California -Davis, 

Davis, CA 

Dr. George T. Wolff, Principal Scientist, General Motors Corporation, Detroit, MI 

Dr. Barbara Zielinska, Research Professor, Division of Atmospheric Science, Desert Research Institute, 

Reno, NV 

 
21

I. HES Comments on 812 Analysis (2004) 

U.S. Environmental Protection Agency - Science Advisory Board (U.S. EPA-SAB). 2004. Advisory 

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

– Benefits and Costs of the Clean Air Act, 1990-2020. Advisory by the Health Effects 

Subcommittee of the Advisory Council on Clean Air Compliance Analysis. EPA-SAB-COUNCILADV-04-002. March. Available on the Internet at 

<http://yosemite.epa.gov/sab%5CSABPRODUCT.NSF/08E1155AD24F871C85256E5400433D5D/

$File/council_adv_04002.pdf>. 

Pg 20: “The Subcommittee agrees that the whole range of uncertainties, such as the questions of causality, 

shape of C-R functions and thresholds, relative toxicity, years of life lost, cessation lag structure, cause of 

death, biologic pathways, or susceptibilities may be viewed differently for acute effects versus long-term 

effects. 

“For the studies of long-term exposure, the HES notes that Krewski et al. (2000) have conducted the most 

careful work on this issue. They report that the associations between PM2.5 and both all-cause and 

cardiopulmonary mortality were near linear within the relevant ranges, with no apparent threshold. 

Graphical analyses of these studies (Dockery et al., 1993, Figure 3 and Krewski et al., 2000, page 162) 

also suggest a continuum of effects down to lower levels. Therefore, it is reasonable for EPA to assume a 

no threshold model down to, at least, the low end of the concentrations reported in the studies.” 

HES Panel Members

Dr. Bart Ostro, California Office of Environmental Health Hazard Assessment (OEHHA), Oakland, CA 

Mr. John Fintan Hurley, Institute of Occupational Medicine (IOM), Edinburgh, Scotland 

Dr. Patrick Kinney, Columbia University, New York, NY 

Dr. Michael Kleinman, University of California, Irvine, CA 

Dr. Nino Künzli, University of Southern California, Los Angeles, CA 

Dr. Morton Lippmann, New York University School of Medicine, Tuxedo, NY Dr. Rebecca Parkin, 

The George Washington University, Washington, DC 

Dr. Trudy Cameron, University of Oregon, Eugene, OR 

Dr. David T. Allen, University of Texas, Austin, TX 

Ms. Lauraine Chestnut, Stratus Consulting Inc., Boulder, CO 

Dr. Lawrence Goulder, Stanford University, Stanford, CA 

Dr. James Hammitt, Harvard University, Boston, MA 

Dr. F. Reed Johnson, Research Triangle Institute, Research Triangle Park, NC 

Dr. Charles Kolstad, University of California, Santa Barbara, CA 

Dr. Lester B. Lave, Carnegie Mellon University, Pittsburgh, PA 

Dr. Virginia McConnell, Resources for the Future, Washington, DC 

Dr. V. Kerry Smith, North Carolina State University, Raleigh, NC 
22

Other Panel Members

Dr. John Evans, Harvard University, Portsmouth, NH Dr. Dale Hattis, Clark University, Worcester, MA 

Dr. D. Warner North, NorthWorks Inc., Belmont, CA Dr. Thomas S. Wallsten, University of Maryland, 

College Park, MD 

 
23

J. NRC – Committee on Estimating the Health Risk Reduction Benefits of Proposed Air Pollution 

Regulations (2002) 

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

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

Pg 109: “Linearity and Thresholds 

“The shape of the concentration-response functions may influence the overall estimate of benefits. The 

shape is particularly important for lower ambient air pollution concentrations to which a large portion of 

the population is exposed. For this reason, the impact of the existence of a threshold may be considerable. 

“In epidemiological studies, air pollution concentrations are usually measured and modeled as continuous 

variables. Thus, it may be feasible to test linearity and the existence of thresholds, depending on the study 

design. In time-series studies with the large number of repeated measurements, linearity and thresholds 

have been formally addressed with reasonable statistical power. For pollutants such as PM10 and PM2.5, 

there is no evidence for any departure of linearity in the observed range of exposure, nor any indication of 

a threshold. For example, examination of the mortality effects of short-term exposure to PM10 in 88 cities 

indicates that the concentration-response functions are not due to the high concentrations and that the 

slopes of these functions do not appear to increase at higher concentrations (Samet et al. 2000). Many 

other mortality studies have examined the shape of the concentration-response function and indicated that 

a linear (nonthreshold) model fit the data well (Pope 2000). Furthermore, studies conducted in cities with 

very low ambient pollution concentrations have similar effects per unit change in concentration as those 

studies conducted in cities with higher concentrations. Again, this finding suggests a fairly linear 

concentration-response function over the observed range of exposures. 

“Regarding the studies of long-term exposure, Krewski et al. (2000) found that the assumption of a linear 

concentration-response function for mortality outcomes was not unreasonable. However, the statistical 

power to assess the shape of these functions is weakest at the upper and lower end of the observed 

exposure ranges. Most of the studies examining the effects of long-term exposure on morbidity compare 

subjects living in a small number of communities (Dockery et al. 1996; Ackermmann-Liebrich 1997; 

Braun-Fahrländer et al. 1997). Because the number of long-term effects studies are few and the number of 

communities studied is relatively small (8 to 24), the ability to test formally the absence or existence of a 

no-effect threshold is not feasible. However, even if thresholds exist, they may not be at the same 

concentration for all health outcomes. 

“A review of the time-series and cohort studies may lead to the conclusion that although a threshold is not 

apparent at commonly observed concentrations, one may exist at lower levels. An important point to 

acknowledge regarding thresholds is that for health benefits analysis a key threshold is the population 

threshold (the lowest of the individual thresholds). However, the population threshold would be very 

difficult to observe empirically through epidemiology, because epidemiology integrates information from 

very large groups of people (thousands). Air pollution regulations affect even larger groups of people 

(millions). It is reasonable to assume that among such large groups susceptibility to air pollution health 

effects varies considerably across individuals and depends on a large set of underlying factors, including 

genetic makeup, age, exposure measurement error, preexisting disease, and simultaneous exposures from 

smoking and occupational hazards. This variation in individual susceptibilities and the resulting 

distribution of individual thresholds underlies the concentration-response function observed in 

epidemiology. Thus, until biologically based models of the distribution of individual thresholds are 

developed, it may be productive to assume that the population concentration-response function is 
24

continuous and to focus on finding evidence of changes in its slope as one approaches lower 

concentrations. 

EPA’s Use of Thresholds 

“In EPA’s benefits analyses, threshold issues were discussed and interpreted. For the PM and ozone 

National Ambient Air Quality Standards (NAAQS), EPA investigated the effects of a potential threshold 

or reference value below which health consequences were assumed to be zero (EPA 1997). Specifically, 

the high-end benefits estimate assumed a 12-microgram per cubic meter (μg/m3

) mean threshold for 

mortality associated with long-term exposure to PM2.5. The low-end benefits estimate assumed a 15-

μg/m3

 threshold for all PM-related health effects. The studies, however, included concentrations as low as 

7.5 μg/m3

. For the Tier 2 rule and the HD engine and diesel-fuel rule, no threshold was assumed (EPA 

1999, 2000). EPA in these analyses acknowledged that there was no evidence for a threshold for PM. 

“Several points should be noted regarding the threshold assumptions. If a threshold is assumed where one 

was not apparent in the original study, then the data should be refit and a new curve generated with the 

assumption of a zero slope over a segment of the concentration-response function that was originally 

found to be positively sloped. The assumption of a zero slope over a portion of the curve will force the 

slope in the remaining segment of the positively sloped concentration-response function to be greater than 

was indicated in the original study. A new concentration-response function was not generated for EPA’s 

benefits analysis for the PM and ozone NAAQS for which threshold assumptions were made. The 

generation of the steeper slope in the remaining portion of the concentration-response function may fully 

offset the effect of assuming a threshold. These aspects of assuming a threshold in a benefits analysis 

where one was not indicated in the original study should be conveyed to the reader. The committee notes 

that the treatment of thresholds should be evaluated in a consistent and transparent framework by using 

different explicit assumptions in the formal uncertainty analyses (see Chapter 5).” 

Pg 117: “Although the assumption of no thresholds in the most recent EPA benefits analyses was 

appropriate, EPA should evaluate threshold assumptions in a consistent and transparent framework using 

several alternative assumptions in the formal uncertainty analysis.” 

Pg 136: “Two additional illustrative examples are thresholds for adverse effects and lag structures.2

 EPA 

considers implausible any threshold for mortality in the particulate matter (PM) exposure ranges under 

consideration (EPA 1999a, p. 3-8). Although the agency conducts sensitivity analyses incorporating 

thresholds, it provides no judgment as to their relative plausibility. In a probabilistic uncertainty analysis, 

EPA could assign appropriate weights to various threshold models. For PM-related mortality in the Tier 2 

analysis, the committee expects that this approach would have resulted in only a slight widening of the 

probability distribution for avoided mortality and a slight reduction in the mean of that distribution, thus 

reflecting EPA’s views about the implausibility of thresholds. The committee finds that such formal 

incorporation of EPA’s expert judgments about the plausibility of thresholds into its primary analysis 

would have been an improvement. 

“Uncertainty about thresholds is a special aspect of uncertainty about the shape of concentration-response 

functions. Typically, EPA and authors of epidemiological studies assume that these functions are linear 

on some scale. Often, the scale is a logarithmic transformation of the risk or rate of the health outcome, 

but when a rate or risk is low, a linear function on the logarithmic scale is approximately linear on the 

scale of the rate or risk itself. Increasingly, epidemiological investigators are employing analytic methods 

that permit the estimation of nonlinear shapes for concentration-response functions (Greenland et al. 

1999). As a consequence, EPA will need to be prepared to incorporate nonlinear concentration-response 

functions from epidemiological studies into the agency’s health benefits analyses. Any source of error or 
25

bias that can distort an epidemiological association can also distort the shape of an estimated 

concentration -response function, as can variation in individual susceptibility (Hattis and Burmaster 1994; 

Hattis et al. 2001).” 

Pg 137: “In principle, many components of the health benefits model need realistic probabilistic models 

(see Table 5-1 for a listing of such components), in addition to concentration-response thresholds and 

time lags between exposure and response. For example, additional features of the concentration-response 

function—such as projection of the results from the study population to the target populations (which may 

have etiologically relevant characteristics outside the range seen in the study population) and the 

projection of baseline frequencies of morbidity and mortality into the future—must be characterized 

probabilistically. Other uncertainties that might affect the probability distributions are the estimations of 

population exposure (or even concentration) from emissions, estimates of emissions themselves, and the 

relative toxicity of various classes of particles. Similarly, many aspects of the analysis of the impact of 

regulation on ambient concentrations and on population exposure involve considerable uncertainty and, 

therefore, may be beneficially modeled in this way. Depending on the analytic approach used, joint 

probability distributions will have to be specified to incorporate correlations between model components 

that are structurally dependent upon each other, or the analysis will have to be conducted in a sequential 

fashion that follows the model for the data-generating process. 

“EPA should explore alternative options for incorporating expert judgment into its probabilistic 

uncertainty analyses. The agency possesses considerable internal expertise, which should be employed as 

fully as possible. Outside experts should also be consulted as needed, individually or in panels. In all 

cases, when expert judgment is used in the construction of a model component, the experts should be 

identified and the rationales and empirical bases for their judgments should be made available.” 

NRC members

Dr. JOHN C. BAILAR, III (Chair), (emeritus) University of Chicago, Chicago, Illinois 

Dr. HUGH ROSS ANDERSON, University of London, London, England 

Dr. MAUREEN L. CROPPER, University of Maryland, College Park 

Dr. JOHN S. EVANS, Harvard University, Boston, Massachusetts 

Dr. DALE B. HATTIS, Clark University, Worcester, Massachusetts 

Dr. ROGENE F. HENDERSON, Lovelace Respiratory Research Institute, Albuquerque, New Mexico 

Dr. PATRICK L. KINNEY, Columbia University, New York, New York 

Dr. NINO KÜNZLI, University of Basel, Basel, Switzerland; as of September 2002, University of 

Southern California, Los Angeles 

Dr. BART D. OSTRO, California Environmental Protection Agency, Oakland 

Dr. CHARLES POOLE, University of North Carolina, Chapel Hill 

Dr. KIRK R. SMITH, University of California, Berkeley 

Dr. PETER A. VALBERG, Gradient Corporation, Cambridge, Massachusetts 

Dr. SCOTT L. ZEGER, Johns Hopkins University, Baltimore, Maryland