1 

## Summary of Expert Opinions on th e Existence of a Threshold in the Concentration-Response Function for PM 2.5 

## -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)2 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 Sectio n 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 m odel, 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 choi ce 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, whic h are quite consistent in showing effects down to the lowest measured levels. Analyses of cohorts us ing data from more recent years, during which time PM concentrations have fallen, con tinue 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 O ccupational Medicine (IOM), Edinburgh,

United Kingdom, UK Dr. Patrick Kinney , Professor, Department of Environmenta l 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, Environmen tal and Occupational Health, School of

Public Health and Health Services, The George W ashington University Medical Center, Washington, DC3 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 Counc il on Epidemiology and Prevention, Council on the Kidney in Cardiovascular Disease, and Coun cil on Nutrition, Physical Activity and Metabolism. (2010). “Particulate matter air pollu tion 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 PM 10 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 PM 2.5 and mortality risk observed in cohort studies that extends below present-day regulations of 15 μg/m 3 for mean annual levels, without a discer nable “safe” threshold.” (cites Pope 2004, Krewski 2009, and Schwartz 2008)
Pg 2364: “The PM 2.5 concentration– cardiovascular risk relationships for both short- and long-term exposures appear to be monotonic, extending below 15 μg/m 3 (the 2006 annual NAAQS level) without a discernable “safe” threshold.”
Pg 2365: “This updated review by the AHA writing gr oup 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 revi ewed supports that there is no safe threshold, it appears that public health benefits would accrue from lowering PM 2.5 concentrations even below presentday annual (15 μg/m 3 ) and 24-hour (35 μg/m 3 ) NAAQS, if feasible, to optimally protect the most susceptible populations.”
Pg 2366: “Although numerous insights have gr eatly enhanced our understanding of the PMcardiovascular relationship since the first AHA statem ent was published, the following list represents broad strategic avenues for future investigati on: ... 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, FAHA4 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, MPH5 C. Integrated Science Assessment for Particulate Matter (2009)
U.S. Environmental Protection Agency (U.S. EP A). 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 character izing the public health impacts associated with exposure to a pollutant is whether the concentra tion-response relationship is linear across the full concentration range encountered, or if nonlinear re lationships exist along any part of this range. Of particular interest is the shape of the concentrati on-response curve at and below the level of the current standards. The shape of the concentration-respon se 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 concen tration-response function (such as the low data density in the lower concentra tion range, possible influence of measurement error, and individual differences in susceptibility to air polluti on health effects). In addition, many chemicals and agents may act by perturbing naturally occurri ng background processes that lead to disease, which also linearizes population concentration-res ponse 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 con centrations for some envi ronmental pollutants (e.g., PM, O 3 , lead [Pb], ETS, radiation) do not exhibit evident thresholds for health effects, even though likely mechanisms include nonlinear pro cesses 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 admi ssion and mortality studies that examined the PM 10 concentration-response relationship found evidence of a log-linear no-threshold relationship between PM exposure and cardiovascular-related morbidity (S ection 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 depart ures from linearity (i.e., nonlinearity). In this ISA studies have been identified that attempt to charact erize the shape of the c oncentration-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 evaluate d that examined the shape of the concentrationresponse curve and the potential presence of a th reshold have focused on cardiovascular hospital admissions and ED visits and mortality asso ciated with short-term exposure to PM 10 and mortality associated with long-term exposure to PM 2.5 .
“A limited number of studies have been identified that examined the shape of the PM cardiovascular hospital admission and ED visit concentration-respon se relationship. Of these studies, some conducted an exploratory analysis during model selection to determ ine 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-res ponse curve at different concentrations (Section 6.2.10.10). Overall, the limited evidence from the studies evalua ted supports the use of a no-threshold, log-linear model, which is consistent with the observations made in studi es that examined the PM-mortality relationship.
“Although multiple studies have previously exam ined the PM-mortality concentration-response relationship and whether a threshold exists, more comple x statistical analyses continue to be developed to analyze this association. Using a variety of methods a nd models, most of the studies evaluated support the6 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 additiona l issues such as the influence of heterogeneity in estimates between cities, and the effect of seasonal a nd 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 exposur e to PM. Using a variety of statistical methods, the concentration-response curve was found to be in distinguishable from linear, and, therefore, little evidence was observed to suggest that a threshold exis ts in the association between long-term exposure to PM 2.5 and the risk of death (Section 7.6).”
Pg 6-75: “6.2.10.10. Concentration Response The concentration-response relationship has been ex tensively 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 admissi ons 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 discuss ed above support no-threshol d log-linear models, but issues such as the possible influence of exposure erro r and heterogeneity of shapes across cities remain to be resolved. Also, given the pattern of seasonal and re gional 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 re viewed in the 2004 PM AQCD (U.S. EPA, 2004, 056905 ) suggested that strong evidence did not exist for a clea r 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 con centration-response functions and the presence of a threshold, including: (1) limited range of available c oncentration 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 ma jority of risk estimates are derived); (2) spline models that allow data to fit possibly non-linear relationship; and (3) threshold models, using PM 10 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-respir atory causes in relation to PM 10 , but “the other cause” deaths (i.e., all cause minus cardiovascular-respiratory) showed an apparent threshold at around 50 μ g/m 3 PM 10 , as shown in Figure 6-35. For all-cause and cardio-resp iratory 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 interpre tation of these results required caution, because (1) the measurement error could obscure any threshold; (2) the city-specific concentration-response curves7 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 sugg ested 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 describ ing the relationship between PM10 and mortality.

“The Schwartz (2004, 078998 ) analysis of PM 10 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 μ g/m 3 , between 25 and 34 μ g/m 3

, between 35 and 44 μ g/m 3 , and 45 μ g/m 3 and above. In the model, days with concentrations below 15 μ g/m 3 served as the reference level. This model was fi t 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 threshol d exists. The authors did not examine city-to-city variation in the concentration-res ponse relationship in this study.

“PM 10 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 μ g/m 3 ) 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 concentra tion-response curves for the la rgest 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 acro ss cities. Thus, while the combined curves (Figure 6-37) appear to support no-threshold relationships between PM 10 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 discuss ed above support no-threshol d log-linear models, but issues such as the possible influence of exposure erro r and heterogeneity of shapes across cities remain to be resolved. Also, given the pattern of seasonal and re gional 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, NC8 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 Edu cation, 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, Asth ma 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 a nd Environmental Epidemiology, Yale University, New Haven, CT Dr. Yuh-Chin Tony Huang —Department of Medicine, Divisi on of Pulmonary Medicine, Duke

University Medical Center, Durham, NC
Dr. Kazuhiko Ito —Nelson Institute of Environmental Medi cine, NYU School of Medicine, Tuxedo, NY
Mr. Marc Jackson —Integrated Laboratory Systems, Inc., Research Triangle Park, NC
Dr. Michael Kleinman —Department of Community and Enviro nmental Medicine, University of

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

NC9 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 E ffects 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 Eff ects 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 Standa rds, U.S. EPA, Research Triangle Park, NC Mr. Tyler Fox , Office of Air Quality Planning and Standa rds, 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 Dia gnostic Investigation, Michigan State

University, East Lansing, MI10 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-Riddl e 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 Progr am, Harvard School of Public Health,

Boston, MA Dr. Sagar Krupa , Department of Plant Pathology, Un iversity 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 St andards, 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 Sta ndards, 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 Standa rds, U.S. EPA, Research Triangle Park, NC
Dr. Jennifer Peel , Department of Environmental and Radi ological Health Sciences, College of

Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO Dr. Zackary Pekar , Office of Air Quality Planning and St andards, 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 Standa rds, 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 St andards, U.S. EPA, Research Triangle

Park, NC
Dr. Stefanie Sarnat , Department of Environmental and Occupa tional Health, Emory University, Atlanta,

GA
Dr. Frances Silverman , Gage Occupational and Environmental Hea lth, 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 Standa rds, U.S. EPA, Research Triangle Park,

NC
Dr. Jason West , Department of Environmental Sciences and En gineering, 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, MA12 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 Part iculate Matter (First External Review Draft, December 2008). EPA-COUNCIL-09-008. May. Available on the Internet at <http://yosemite.epa.gov/sab/SABPRODUCT.N SF/81e39f4c09954fcb8 5256ead006be86e/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 relationshi p 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 Nation al 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.N SF/81e39f4c09954fcb85256ead006be86e/723FE64 4C5D758DF852575BD00763A32/$File/EP A-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, a nd 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 fo r Particulate Matter (Second External Review Draft, July 2009)

. EPA-CASAC-10-001. November. Available on the Internet at <http://yosemite.epa.gov/sab/SABPRODUCT.N SF/81e39f4c09954fcb8525 6ead006be86e/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 cl early 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 Hea lth, Harvard University, Boston, MA Dr. Ellis B. Cowling , University Distinguished Professor At-Large Emeritus, Colleges of Natural

Resources and Agriculture and Life Sciences, No rth 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, Cons truction and Environmental Engineering,

College of Engineering, North Carolin a State University, Raleigh, NC13 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, Un iversity of California, Parlier, CA Dr. Joseph Helble, Dean and Professor, Thayer School of E ngineering, Dartmouth College, Hanover,

NH Dr. Rogene Henderson , Senior Scientist Emeritus, Lovel ace 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 Environm ental 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 Se rvice Air Resources Division, Cooperative

Institute for Research in the Atmosphere, Co lorado 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, Co llege 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 a nd Occupational Health Sciences, School of

Public Health and Community Medicine, Un iversity 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, NY14 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 Finkels tein, Kaz Ito, D.K. Moore, K. Bruce Newbold, Tim Ramsay, Zev Ross, Hwashin Shin, and Barb ara Tempalski. (2009). Extended follow-up and spatial analysis of the American Cancer Societ y study linking particulate air pollution and mortality. HEI Research Repor t, 140, Health Effects Institute, Boston, MA.
Pg 119: [About Pope et al. (2002)] “Each 10- μ g/m 3 increase in longterm average ambient PM 2.5 concentrations was associated with approximately a 4%, 6%, or 8% increase in risk of death from all causes, cardiopulmonary disease, and lung cancer, resp ectively. There was no evidence of a threshold exposure level within the range of observed PM 2.5 concentrations. “
Krewski (2009). Letter from Dr. Daniel Krewski to HE I’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 comment ed that the Updated Analysis completed by Pope et al. 2002 reported “no evidence of a thres hold exposure level within the range of observed PM 2.5 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 func tion within the range of observed PM 2.5 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 Epidemio logy, 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 Professo r 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 Engineerin g, Georgia Institute of Technology Dr. Lianne Sheppard, PhD , Professor, Department of Biostatistics, University of Washington15 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 stud y 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 μ g/m 3 .”
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 decisionmaker s. 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 PM 2.5 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 in to his distribution or to provide a distribution "conditional on" one or both of these factors.”
Pg vii: “Only one of 12 experts explicitly in corporated a threshold into his C-R function. 3 The rest believed there was a lack of empirical and/or theo retical support for a population threshold. However, three other experts gave differing effect estimat e distributions above and below some cut-off concentration. The adjustments these experts made to median estimates and/or uncertainty at lower PM 2.5 concentrations were modest.”

“ 3 Expert K indicated that he was 50 percent su re 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 μ g/m 3 , and a 20 percent chance that it would fall between 5 and 10 μ g/m 3 .”
Pg ix: “Compared to the pilot study, experts in th is 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 th e 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 PM 2.5 mortality C-R function. The protocol focused on assessing e xpert judgments regarding theory and evidential support for a population threshold (i.e., the concentra tion 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 relationshi p, the team then asked the expert to specify the threshold PM 2.5 concentration probabilistically, incorporating his uncertainty about the true threshold level.
“From a theoretical and conceptual standpoint, all ex perts generally believed that individuals exhibit thresholds for PM-related mortality. However, 11 of them discounted th e idea of a population threshold in the C-R function on a theoretical and/or empirical ba sis. Seven of these experts noted that theoretically one would be unlikely to observe a population threshol d due to the variation in susceptibility at any given time in the study population resulting from combinati ons of genetic, environm ental, 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 an alyses 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 exposur e levels. However, those who favored epidemiologic studies generally acknowledged that definitive studies addressing threshol ds would be difficult or impossible to conduct, because they would need to include a very large a nd diverse population with wide variation in exposure and a long follow-up period. Furthermore, two expe rts (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 av ailable 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 thr eshold 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 μ g/m 3 , and a 20 percent chance that it would fall between 5 and 10 μ g/m 3 .”
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 functio n relating mortality to changes in annual average PM 2.5 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 c oncentrations 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 μ g/m 3 ) = 0.8 and P(5 μ g/m 3 < T ≤ 10 μ g/m 3 ) = 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 Medici ne, 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 Environm ental 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, UT18 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 Dentistry19 H. CASAC comments on PM Staff Paper (2005) U.S. Environmental Protection Agency - Scien ce Advisory Board (U.S. EPA-SAB). 2005. EPA’s Review of the National Ambient Air Quality St andards 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.ns f/E523DD36175EB5AD8525701B007332AE/$File/SABCASAC-05-007_unsigned.pdf>.

Pg 6: “A second concern is with methodological i ssues. 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 meas ured 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 concentrati ons for adverse health effects. Thus, in order to avoid emphasizing an approach that assumes effect s that extend to either predicted background concentrations or LML, and to sta ndardize the approach across cities, for the purpose of estimating public health impacts, the Panel favored the primary use of an assumed threshold of 10 μ g/m 3 . 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 nonlin ear 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 Respirator y 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 Environmenta l Health, School of Public Health and

Community Medicine, University of Washington, Seattle, WA
Dr. Petros Koutrakis , Professor of Environmental Science, Envi ronmental 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 W ood Johnson Medical School, NJ Dr. Morton Lippmann , Professor, Nelson Institute of Environmental Medicine, New York

University School of Medicine, Tuxedo, NY20 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, Bl oomberg School of Public Health, Johns

Hopkins University, Baltimore, MD
Dr. Warren H. White , Visiting Professor, Crocker Nuclear Laborat ory, University of California -Davis,

Davis, CA Dr. George T. Wolff , Principal Scientist, General Motors Corporation, Detroit, MI
Dr. Barbara Zielinska , Research Professor, Division of Atmosphe ric Science, Desert Research Institute,

Reno, NV21 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 Clea n 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 view ed 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 re port that the associations between PM 2.5 and both all-cause and cardiopulmonary mortality were near linear within th e relevant ranges, with no apparent threshold. Graphical analyses of these studies (Dockery et al., 19 93, Figure 3 and Krewski et al., 2000, page 162) also suggest a continuum of effects down to lower le vels. 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 Medici ne (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 Me dicine, 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, NC22 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, MD23 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 ai r 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 concentrati ons are usually measured and modeled as continuous variables. Thus, it may be feasible to test linearity an d 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 reasonabl e statistical power. For pollutants such as PM 10 and PM 2.5 , 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 PM 10 in 88 cities indicates that the concentration-response functions ar e 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 th e 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 sim ilar effects per unit change in concentration as those studies conducted in cities with higher concentrati ons. 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 outcome s was not unreasonable. However, the statistical power to assess the shape of these functions is w eakest 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 ma y 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 epidemiol ogy, because epidemiology in tegrates 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 su ch large groups susceptibility to air pollution health effects varies considerably across individuals and de pends 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 concentrati on-response function is24 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 consequen ces were assumed to be zero (EPA 1997). Specifically, the high-end benefits estimate assumed a 12-microgram per cubic meter (μg/m 3 ) mean threshold for mortality associated with long-term exposure to PM 2.5 . The low-end benefits estimate assumed a 15- μg/m 3 threshold for all PM-related health effects. The studies, however, included concentrations as low as 7.5 μg/m 3 . 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 thr eshold assumptions. If a threshold is assumed where one was not apparent in the original study, then the da ta should be refit and a ne w curve generated with the assumption of a zero slope over a segment of the con centration-response function that was originally found to be positively sloped. The assumption of a zer o 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 concen tration-response function w as 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 por tion of the concentration-response function may fully offset the effect of assuming a threshold. These aspec ts of assuming a threshold in a benefits analysis where one was not indicated in the original study sh ould be conveyed to th e reader. The committee notes that the treatment of thresholds should be evaluate d 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 th reshold assumptions in a consistent and transparent framework using several alternative assumptions in th e 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 ag ency conducts sensitivity analyses incorporating thresholds, it provides no judgment as to their relative pl ausibility. 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 pl ausibility 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 epidemiologi cal studies assume that these functions are linear on some scale. Often, the scale is a logarithmic transf ormation 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, epidemio logical investigators are employing analytic methods that permit the estimation of nonlinear shapes for c oncentration-response functions (Greenland et al. 1999). As a consequence, EPA will need to be prepar ed to incorporate nonlinear concentration-response functions from epidemiological studies into the agency’s health benefits analyses. Any source of error or25 bias that can distort an epidemiological associati on 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 rea listic 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 stud y population to the target populations (which may have etiologically releva nt 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 emi ssions, estimates of emissions themselves, and the relative toxicity of various classes of particles. Simila rly, many aspects of the analysis of the impact of regulation on ambient concentrations and on populati on exposure involve considerable uncertainty and, therefore, may be beneficially modeled in this wa y. 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 th e 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 incor porating 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 cons ulted as needed, individually or in panels. In all cases, when expert judgment is used in the cons truction of a model component, the experts should be identified and the rationales and empirical bases fo r 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