Public Health and Components of Particulate Matter: The Changing Assessment of Black Carbon

1. Public Health and Components of Particulate Matter: The Changing Assessment of Black Carbon Thomas J. Grahame, US Department of Energy Thomas.Grahame@hq.doe.gov Rebecca Klemm, Klemm Analysis Group Richard B. Schlesinger, Pace University

2. Disclaimer • The views expressed are those of the authors alone, and do not necessarily reflect the viewpoint of any U.S. Government Agency

3. Caveat • There have been considerable reductions of particulate vehicular emissions (including black carbon [BC]), under legislation and regulations predating and including the Clean Air Act, which deal with reducing vehicular emissions of all types (next slide). • As we discuss recently emerging science on health effects of BC under another section of CAA, regarding National Ambient Air Quality Standards (NAAQS), we don’t want to leave impression that substantial progress hasn’t been made.

4. Reductions in San Francisco annual BC concentrations over time(Kirchstetter, 2008, LBL – black line w/black dots = BC)

5. Assessments of Black Carbon (BC) and Diesel Emissions Today • World Health Organization (WHO, EU branch) suggested consideration of a additional health standard for BC (2012) • IARC (International Agency for Research on Cancer, part of WHO) declared diesel exhaust a known human carcinogen (2012) • Janssen et al. (2011) found that reducing one unit of BC in air will lengthen survival 4 to 9 times more than reducing one unit of PM2.5 • PM2.5 = Particulate Matter 2.5 micrometers or less

6. Assessments of BC and Diesel Emissions Circa 2000 • BC barely mentioned in North American air pollution studies • Vehicular emissions rarely mentioned in air pollution epidemiology • How did we get from “barely mentioned” to calling for BC standard, finding BC 4 to 9 times more lethal, labelling diesel emissions carcinogenic, in a bit more than a decade? • A major theme of the Critical Review

7. What is Black Carbon (BC)? • BC consists of a core of graphite-like elemental carbon(EC), on which is adsorbed many carbonaceous species, metals, etc. • BC is product of incomplete combustion of carbonaceous materials (diesel, biomass, gasoline, coal, natural gas [e.g., flaring]) w/o adequate controls • U.S. control requirements for post-2006 on-road diesels eliminate virtually all BC when in working order • Adsorbed materials add ~ 25% to mass of EC • Polycyclic Aromatic Hydrocarbons (PAHs) are among adsorbed materials

8. Representation of diesel particles, their formation (Courtesy Dr. Ning Li)

9. Sources of Ambient BC in U.S. (from EPA Black Carbon Report to Congress)

10. Mobile sources of BC (from EPA Black Carbon Report to Congress) • On road diesel: • 153,477 (short tons) • Nonroad diesel • 112,058 • On road gasoline • 14,510 • Other (e.g., locomotives) • ~ another 50,000 • Diesel= ~ 80% of mobile sources BC

11. EC/BC is mostly in ultrafine range (from Mauderly and Chow, 2008; Fresno)

12. Particulate Matter (PM) Research in 1970s through 1990s (very short overview) • 1970s and 1980s • A few seminal PM epidemiological studies in 1980s, often noting still current methodological issues, such as: • health relevance of different pollutants not monitored at time (e.g., cancer researchers want info on organics) • A central monitor pollution measurement is a poor proxy for expressing exposure for everyone in a metro area, for spatially variable pollutants (BC) – details to follow

13. Particulate Matter (PM) Research in 1970s through 1990s (cont.) • 1970s and 1980s (cont.) • Monitoring for many potentially health-relevant PM2.5 species, including BC/EC, was lacking • Sulfate only PM species routinely monitored • Studies of PM didn’t mention vehicular, diesel, black carbon, PAHs • Exception of Stern et al., 1988, next, which looked at vehicular emissions only generally, in study of tunnel and bridge officers in NYC

14. The Exception: Stern et al. (1988): Tunnel Officers vs. Bridge Officers (Risks of ASHD Disease Mortality)

15. But….Stern et al (1988) dismissed particles and organics as cause • Study clearly showed benefits of reducing exposure to vehicular emissions • But benefits seen by authors as reflecting reduction in CO • Benefits of reductions of other vehicular emissions, such as “nitric oxides, hydrocarbons, particles, lead…highly speculative…” • Lost opportunity to start looking at vehicular PM emissions

16. In the 1990s… • Two seminal air pollution studies: • 6 Cities Study (Dockery et al., 1993) • American Cancer Society (ACS) Study (Pope et al., 1995) • Seminal because these were the studies which convinced people that tiny particles in air, which often couldn’t be seen, could sicken and kill • But (reflecting lack of monitoring), neither mentioned BC/EC, PAHs, diesel emissions

17. 1998 “Research Priorities for Airborne Particulate Matter” • National Research Council (NRC) report (body of National Academy of Sciences) • Also a seminal work, NRC Reviewed state of U.S. research on particulates and made crucial recommendations

18. Findings of 1998 NRC Report • “The biological basis of most of the [particulate] associations is essentially unknown . . .” • “There is . . . limited scientific information about the specific types of particles that might cause adverse health effects…” • Suggested using laboratory and human clinical studies to explore toxicological mechanisms by which particles may cause mortality and morbidity • These toxicology tests should examine the “most biologically important components” of particles, including both sizeandchemistry • Suggested expanded monitoring, to avoid issue that “monitoring is not measuring the most biologically important aspects of particulate matter…”

19. Early in 2000s…”Highway Proximity” Studies • While BC/EC monitoring was beginning, a major breakthrough in exposure assessment: • People who live near major roads are exposed to much more pollution than those living further away • Researchers could examine health effects for those living near roadways (after accounting for socio-economic and smoking status, age, other potential confounders), vs. those living farther away • Example of pollutants’ spatial variability (next slide)

20. Vehicular Pollutants Fall within ~100 to 150 meters of major road

21. Risks for those living close to major urban roads, thruways • Starting (slowly) in 2002, many studies: • Found elevated all-cause or cardiovascular disease (CVD) mortality, or CVD morbidity (e.g., hospitalization) effects • Most often for those living w/in 100 m of freeway, 50 m of major urban road • Critical Review (CR) lists ~ 20 such studies (most post-2006) in Table S2, discusses several in body of CR

22. Risks for those living close to major urban roads, thruways (cont.) • Some examples: • Finkelstein et al. (2004): Living in close proximity to such roads costs 2.5 years of life (not much less than for major diseases like ischemic heart disease) • Gan et al. (2010): ~ 30% elevated risk of coronary heart disease mortality for those living in close proximity to major roads for length of study, > than risks for those who moved closer or further during study • Hoffmann et al. CVD morbidity studies • Significantly increased risks of congestive heart disease (2006), coronary artery disease (2007), peripheral artery disease (2009) for those living near major roads

23. Proximity to highways shows importance of vehicular emissions to health…what about vehicular emissions per se? • Let’s also look at vehicular emissions specifically, rather than just proximity to highway… • BC/EC increasingly used in epidemiological studies, ~ post 2005 • Also, to lesser extent, NOx, NO, PAHs, plus in EU black smoke [similar to BC] • When using chemical/elemental markers such as BC, there are important methodological issues that will help us get more reliable results…

24. Need to compare effects of vehicular PM emissions vs. other PM2.5 species • 1. Why compare many PM2.5species, including BC/EC, against same health endpoints in same epidemiology studies? • Can’t find associations for a PM2.5species not included in model (obviously) • Association may “migrate” from a health relevant PM2.5species not in model, to emissions included in model • Goal: is a given PM2.5 species more strongly, consistently associated with health effect than other PM2.5species?

25. Need reasonably good knowledge of actual subject exposure • 2. Epidemiology results are improved with more accurate subject exposure information (as with highway proximity studies, near vs. far) • With poor exposure information (greater exposure misclassification), effects of locally variable emissions (e.g., BC) almost always are understated • Example (next slide): Suh and Zanobetti (2010) • Later, pollutants would be modelled to homes of subjects (hospital admissions, mortality)

26. When exposure to BC is accurate….vs. when it isn’t…

27. When you have exposure misclassification… • Takeaway from Suh and Zanobetti (2010): • If you have large exposure misclassification, you will understate actual effects in most cases • Does NOT mean that you won’t find some (smaller) significant associations when using a central monitor…other studies do….only that they will very likely be understated

28. Examine biological mechanisms which may explain epidemiological associations for specific PM2.5 species • 3. Combine toxicology (finding biological mechanisms for specific PM2.5species) with human panel andcontrolled human exposure studies, to explain outcomes (e.g., CVD effects) found in population based epidemiology(NRC recommendation again) • Illustrative references • Health Effects Institute, 2010 • Grahame and Schlesinger, 2010 (BC and CVD)

29. Monitoring of multiple PM2.5 species, including BC/EC • Widespread monitoring of BC/EC in U.S. got started in early 2000s, but took until after 2005 (mostly) for epidemiology to use this information • Europe had been measuring black smoke (BS) for decades because of widespread residential coal use • Thus EU had a head start on measuring dark carbonaceous material relating to diesels, traffic as coal use greatly diminished

30. 2006 Critical Review (Pope and Dockery) • Well over 100 studies discussed in 2006 CR • Great majority examined only size fractions of PM (PM10, PM2.5, a few ultrafine) • A few EU studies using black smoke (the “head start”) • Two highway proximity studies • 20 studies of heart rate variability (HRV), all using PM size fractions • None using BC/EC

31. 2006 Critical Review (Pope and Dockery), cont. • Want to be clear: no criticism implied! • Researchers can’t report on BC/EC associations if studies using recently available BC information have yet to be done

32. What about BC/EC, vehicular emissions studies now? • Current (2014) CR lists in Tables S2 through S10, and/or text, ~140 studies of vehicular emission effects in humans • Great majority published after 2005 • Most use BC/EC, a small number use other highway emissions, ~ 20 use highway proximity, ~ 5 use traffic density (a few use more than one indicator) • ~ 15 of the most recent studies model vehicular emissions to the home of subjects (visual of modelled emissions next slide) • ~ 20 are controlled human exposure studies using mostly diesel emissions, some using wood smoke emissions (getting to biological mechanisms)

33. NO2 modelled to residences in Toronto (Jerrett et al., 2009)

34. Health Outcomes These BC/EC/ Vehicular Emissions Studies Examined • The ~ 140 studies examined: • All-cause, CVD mortality; CVD morbidity (e.g., CVD emergency hospital admissions, blood pressure); • Intermediate CVD health endpoints (e.g., ~ 20 precursors of CVD such as oxidative stress, inflammation, adhesion molecules, platelets, etc.); • Cardiac issues (arrhythmias, HRV changes, ST-segment depression, etc.); • birth outcomes; • brain and central nervous system effects

35. Health Outcomes These BC/EC/ Vehicular Emissions Studies Examined • Discuss only a few lung cancer studies very briefly in CR • IARC/WHO 2012 conclusion that diesel emissions cause lung cancer makes in-depth discussion extraneous • Illustrate here with one recent study of cancer and diesel emissions (next slide)

36. Cancer risks from air toxics • Morello-Frosch and Jesdale (2006) • Modelled concentrations of 33 Air Toxics (including DPM, diesel particulate matter) to census tracts • Estimated cancer risks by multiplying potencies by amounts of each air toxic • Mobile sources contributed 88% of cancer risks • DPM contributed 82% of cancer risks

37. Caveat (1) • We do not use source apportionment studies, as in our judgment, they increase rather than reduce uncertainty (details in CR) • Researchers routinely come up with different numbers of factors (“sources”) for same locality • Grahame and Hidy, 2007; HEI, 2010 • Not possible to determine, in any case, differential exposure to a “diesel emissions factor” (exposure misclassification)

38. Caveat (2) • For reasons of space, we do not include in CR (or today) the voluminous number of studies relating vehicular emissions to respiratory diseases (see HEI, 2010)

39. Caveat (3): Toxicology, Some Observational Studies: Discussed in Depth in CR (not in Tables) • Also no time for reviewing today: • Several sections in CR on toxicology of diesel and BC (animal/cells), lengthier versions in Supplemental Material • These link biological mechanisms for health effects in epidemiological studies • Additional to the ~ 140 epidemiological or controlled human exposure studies in Tables S2 through S10 • Many observational studies in CR (health effects in workers in trucking companies exposed to different levels of emissions; oxidative stress at beginning vs. end of work week in diesel repair, etc.) linking exposure to different levels of vehicular emissions to health endpoints (example)

40. Tables S3, S4, S5 • Over 30 population-based epidemiology studies, each using many PM2.5 species (always including BC/EC), in these tables • S3: mortality associations w/o accurate exposure information (central monitor concentrations) • S4: hospital admissions (morbidity) associations w/o accurate exposure information • S5: mortality and morbidity associations when BC or other vehicular emissions are modelled to home of subjects (good exposure information)

41. Some results of studies using many PM2.5species (multi county studies, from Tables S3 and S4)

42. Human Panel Studies (studies of specific subjects known to researchers) • Benefits of human panel studies (type of epidemiological study) • Researchers can know individual subject’s health in detail (weight, medications, smoking, conditions, etc.), can control for these before examining effects of pollutants • Two sets of human panel studies in CR • Harvard School of Public Health (Table S6, 37 studies) • Delfino et al. group (Table S7, 7 studies)

43. HSPH studies, all including BC/EC • Health endpoints (mostly cardiovascular intermediate and cardiac endpoints) studied include: • Oxidative stress, ST-segment reduction, HRV changes, carotid artery thickness, several circulating markers of inflammation, systolic and diastolic blood pressure, soluble adhesion molecules (involved in atherosclerosis), vascular reactivity, fibrinogen, homocysteine, LINE-1 methylation, risks of different arrhythmias, T-wave alternans, telomere length • Cognition: in elderly, in children

44. HSPH studies, all including BC/EC • In the 10 studies (of 37) with good subject exposure to BC/EC: • All 10 found BC/EC associations • In 4 studies using PM2.5, half found PM2.5 associations • In 2 studies using sulfate or regional emissions, no associations • In this limited sample with good exposure, higher % of BC associations than for either PM2.5or sulfate • Schwartz et al. (2005) example of benefits of good exposure, monitoring several PM2.5 species (next slides)

45. Schwartz et al. (2005) study of 4 HRV measures • 8 tests of pollution associations: (two time periods, 4 different measures of HRV) • Study found associations with BC in 7/8 tests • PM2.5 associations found in 3/8 tests • Authors subtracted BC from PM2.5 on hourly basis, called the remainder “secondary PM” • No associations with “secondary PM,” similar to findings of Suh and Zanobetti (2010) and others

46. Monotonic decrease in HRV with increase in BC (Schwartz et al, 2005)

47. No HRV associations with regional PM2.5 with accurate BC exposure

48. Importance of Schwartz et al. (2005) • Allows comparing effects of different PM2.5species, with good exposure information, thus can show importance of BC as a result • Before BC monitoring, this study would have been just one more study simply finding PM2.5 associations, unable to interpret which PM2.5 species might be harmful

49. HSPH studies, all including BC • Remaining 27 HSPH studies, which do NOT have good BC exposure information • Significant BC associations in 20/27 studies (surprisingly, despite poor exposure information) • Significant PM2.5associations in 20/25 studies • Significant sulfate associations in 8/14 studies • No metals included, something for future research

50. HSPH studies, last slide • Several of these 27 studies stated that BC associations were unexpected, that BC associations should have been attenuated. Example: • “Particle measurements with…local sources, such as mobile source emissions of BC, are typically more spatially heterogeneous than regional pollutants ...Therefore, we would have expected associations to be most attenuated for BC due to measurement error. This was not the case, as most of the strongest observed associations involved BC…” (O’Neill et al., 2007)