Final Report: The Relative Associations of Transition Metals and Sources of Fine Particulate Matter to Increased Daily Mortality

EPA Grant Number: R826245
Title: The Relative Associations of Transition Metals and Sources of Fine Particulate Matter to Increased Daily Mortality
Institution: Harvard University
EPA Project Officer: Chung, Serena
Project Period: January 14, 1998 through January 13, 2000
Project Amount: $211,733
RFA: Health Effects and Exposures to Particulate Matter and Associated Air Pollutants (1997) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air , Health Effects


The U.S. EPA has identified specific gaps in current knowledge regarding the health effects of particulate matter (1). Fine particulate matter (PM2.5) contains particles from mobile combustion sources, local stationary combustion sources, long-range transport from distant combustion sources, local industries, and noncombustion sources. The constituents of PM2.5 include sulfates, transition metals, crustal elements, and other elements associated with specific sources. While a convincing body of evidence has accumulated on the adverse effects of PM2.5 (2-4), the specific chemical or physical characteristic responsible for these adverse effects has not been determined. In this study, we used the elemental composition of size-fractionated particles to identify several distinct source-related fractions of fine particles in six U.S. cities. We then examined the association of these fractions with daily mortality in each of the cities and combined the city-specific results in a meta-analysis to derive overall relative risk for each fraction.


Source Identification. From 1979 through the late 1980s, integrated 24-hour samples of PM2.5 were collected every other day from central sampling sites at the six cities: Watertown, MA; Kingston-Harriman, TN; St. Louis, MO; Steubenville, OH; Portage, WI; and Topeka, KS. Elemental composition of fine mass was determined by X-ray fluorescence, and 15 elements were routinely found above the limit of detection: silicon, sulfur, chlorine, potassium, calcium, vanadium, manganese, aluminum, nickel, zinc, selenium, bromine, lead, copper, and iron.

In separate analyses for each city, we used specific rotation factor analysis to identify up to 5 common factors from the 15 specified elements. We specified a single element as the tracer for each factor and maximized the projection of these elements using the Procrustes rotation, a variant of the oblique rotation method.

We selected tracer elements in three steps. First, we identified tracers on the basis of the chemical composition of fine particulate matter from known sources and previous source apportionments performed in the cities (5, 6). Second, we regressed total fine mass on the identified factors and rejected any factors that had negative regression coefficients. Third, we attempted to identify additional, possibly local, sources by examining elements that did not load heavily on the positive factors from step two, and created the additional factors that were both positive predictors of total fine mass and maximized the model R2. In steps one and two, we defined three sources of fine particles in all six cities: a silicon factor classified as soil and crustal material, a lead factor classified as motor vehicle exhaust, and a selenium factor representing coal combustion sources. In city-specific analyses, we also considered vanadium (fuel oil combustion), chlorine (salt), and selected metals (nickel, zinc, or manganese) as possible targets and sources. We identified five source factors for each city, except for Topeka, where we were only able to identify three positive predictors of total PM2.5.

Daily Factor Scores. For each metropolitan area, we calculated daily scores for each of the identified factors. Only sources that were significant predictors of total fine particle mass (p<0.10) were considered in the mortality analyses. We assumed that mortality was associated with the 2-day mean of the nonmissing particle concentrations on the same and on the previous days. Because much of the monitoring was conducted every other day during the study period, this technique imputed missing days using the nonmissing values on the previous days, which increased the number of days included in the mortality analysis from 6,211 to 9,108. For this imputation, we assumed that the sampling schedule, and hence the missing values, were at random with respect to daily mortality.

Mortality Data. We defined the six metropolitan areas in this study as the county containing the air pollution monitor and contiguous counties. For the mortality analysis, each study area is identified by the name of its largest city (e.g., Watertown as Boston; Kingston-Harriman as Knoxville; Portage as Madison). We extracted daily deaths for people who lived and died in the selected counties from annual detail mortality tapes (National Center for Health Statistics) for the time periods with fine particulate measurements.

Poisson Regression of Mortality. We investigated the association of daily deaths with sources of fine particles separately for each city using Poisson regression in a generalized additive model. We controlled for locally weighted linear regression (LOESS) smooth functions of date, temperature, and dew point temperature, and indicator variables for day of the week. The relative risks for each source were evaluated by including the absolute factor scores (in units of mµg/m3) simultaneously in the model. That is, the estimate of the mobile source factor is in a model controlling for coal-derived particles, crustal particles, and the other source factors, and vice versa. To obtain summary estimates of the association between the different sources of fine particles and daily mortality, we combined the city-specific regression coefficients using inverse variance weights.

As an alternative approach, we also evaluated the association of daily deaths with individual elements. We built city-specific models that included daily measurements of lead, iron, sulfur, nickel, vanadium, manganese, and zinc individually and in combination.

Summary/Accomplishments (Outputs/Outcomes):

Source Apportionment. Using silicon, lead, and selenium as tracer elements, we identified crustal, mobile, and coal combustion factors, respectively, in all six metropolitan areas. Coal and mobile sources account for the majority of fine particles in each city. In Watertown, the crustal factor accounted for less than 1 percent of the fine particle mass and was not a significant predictor in the regression model. Therefore, in this city (Boston), this factor was not included in subsequent mortality analyses. We identified a vanadium factor, representing fuel oil combustion in Watertown and Steubenville. A chlorine factor (salt) was identified in Watertown, Kingston-Harriman, and Portage. We identified a metal factor in St. Louis (zinc), Steubenville (zinc), and Kingston-Harriman (nickel), presumably related to local manufacturing. Finally, we found a manganese factor in St. Louis and Portage. In Topeka, which had a low average PM2.5 concentration, we were able to identify only the crustal, mobile, and coal combustion factors. The source of at least 18 percent of the total mass remained unexplained in all cities, except Steubenville (8 percent unexplained).

Association of Mortality with Specific Source Factors. For the three source factors identified in all six metropolitan areas, we found the strongest increase in daily mortality associated with the mobile source (lead) factor (Table 1). The communities are presented in the table in order of decreasing population size, and consequently decreasing contribution to the summary measure. In the combined analysis across the six cities, daily mortality increased by 3.4 percent (95 percent CI: 1.7-5.2 percent) with each 10-mµg/m3 increase in the 2-day mean of the mobile-source factor. There was evidence of a 2-percent increase in daily mortality from ischemic heart disease with each 10-mµg/m3 increase in mobile sources; however, it was not statistically significant (95 percent CI: 1.1-5.2 percent). We did not identify adverse effects for respiratory deaths (chronic obstructive pulmonary disease or pneumonia).

The coal combustion (selenium) factor was positively associated with mortality in all metropolitan areas, with the exception of Topeka (Table 1). The summary relative risk indicated that a 10-mµg/m3 increase in the 2-day mean mass concentration from coal combustion sources was associated with a 1.1-percent increase in daily mortality (95 percent CI: 0.3-2.0 percent). Deaths from chronic obstructive pulmonary disease and pneumonia increased by higher percentages than did deaths from all causes: 4.5 percent (95 percent CI: 0.4-9.3 percent) and 7.9 percent (95 percent CI: 3.1-12.7 percent), respectively. Unlike the motor source factor, there was no evidence of an increased effect of exposure to coal combustion sources for ischemic heart disease.

The crustal factor in fine particulate matter was not associated with mortality. There is a suggestion of a large positive association of fuel oil combustion with daily mortality in the cities in which the vanadium factor was identified; however, the confidence intervals were wide and included a null effect: Boston: 27.3-percent increase (95 percent CI: 2.0-57.5 percent); Steubenville: 13.6-percent increase (95 percent CI: 34.2-63.8 percent). If we consider the manganese factor as defining a fuel oil combustion source in Madison and St. Louis, the summary effect estimate for the four cities is 5.6 percent (95 percent CI: 1.8-13.2 percent) for a 10-mµg/m3 increment in PM2.5 from this factor.

Table 1.   Percent increase in daily deaths and 95 percent confidence intervals (CI) associated with a 10- g/m3 increase in mass concentration from a specific major source of fine particles by metropolitan area, six U.S. cities, 1979-1988a3

Association of Mortality with Specific Elements. In models with measurements for the individual elements included simultaneously, sulfur, nickel, and lead were significantly associated with total mortality. An increase of sulfur across its range of exposure (5916 nµg/m3: 5th to 95th percentile for all cities combined) was associated with a 3.0-percent (95 percent CI: 0.9-5.2 percent) increase in total daily mortality. The equivalent increases in nickel (10.3 nµg/m3) and lead (461.4 nµg/m3) were associated with a 1.5-percent (95 percent CI: 0.5-2.6 percent) and 1.6-percent (95 percent CI: 0.2-2.9 percent) increase in mortality, respectively. Vanadium and iron, although statistically significant predictors when evaluated separately, were not significant when included simultaneously with nickel, lead, and sulfur.


Using specific rotation factor analysis, we identified crustal, mobile, and coal combustion source of fine particles in each of six cities, and estimated the percentage of daily deaths attributable to changes in the concentration of each factor. In the combined analysis across the six cities, controlling for the other sources, a 10-µg/m3 increase in PM2.5 from mobile sources accounted for a 3.4-percent increase in daily mortality (95 percent CI: 1.7-5.2 percent) and from coal combustion sources a 1.1-percent increase (95 percent CI: 0.3-2.0 percent). PM2.5 from crustal particles was not associated with increased daily mortality. A possible residual oil combustion source was identified in four of the six cities, and the summary effect estimate was positive, but not statistically significant (5.6-percent increase, 95 percent CI: 1.8-13.2 percent). Results from element specific mortality analyses were consistent with the analysis of sources; lead and sulfur, markers for mobile and coal combustion sources, respectively, were independently associated with daily deaths. Additionally, nickel was positively associated with daily deaths.


  1. U.S. EPA. Air Quality Criteria for Particulate Matter. EPA/600/P-95/001cF. U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, 1996.

  2. Schwartz J, Dockery DW, Neas LM. Is daily mortality associated specifically with fine particles? Journal of Air and Waste Management Association 1996;46(10):927-939.

  3. Pope CA III, Dockery DW. Epidemiology of particle effects. In: Holgate ST, Samet JM, Koren HS, Maynard RL, eds. Air Pollution and Health. San Diego: Academic Press, 1999.

  4. Pope CA III, Thun MJ, Namboodiri MM, Dockery DW, Evans JS, Speizer FE, Heath CW Jr. Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. American Journal of Respiratory and Critical Care Medicine 1995;151(3p1):669-674.

  5. Koutrakis P, Spengler JD. Source apportionment of ambient particles in Steubenville, OH using specific rotation factor analysis. Atmospheric Environment 1987;21:1511-1519.

  6. Thurston GD, Spengler JD. A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmospheric Environment 1985;19:9-25.

Journal Articles on this Report : 1 Displayed | Download in RIS Format

Other project views: All 6 publications 1 publications in selected types All 1 journal articles
Type Citation Project Document Sources
Journal Article Laden F, Neas LM, Dockery DW, Schwartz J. Association of fine particulate matter from different sources with daily mortality in six U.S. cities. Environmental Health Perspectives 2000;108(10):941-947. R826245 (Final)
  • Abstract from PubMed
  • Full-text: EHP Online Full Text
  • Supplemental Keywords:

    ambient air, health effects, particulates, metals, sulfates, epidemiology., RFA, Health, Scientific Discipline, Air, particulate matter, air toxics, Environmental Chemistry, Risk Assessments, Environmental Monitoring, Atmospheric Sciences, ambient air quality, particle size, sulfates, weather, human health effects, PM 2.5, exposure and effects, statistical analysis, combustion emissions, air pollution, atmospheric transport, human exposure, National Ambient Air Quality Standards, particulate exposure, daily human mortality, particle transport

    Progress and Final Reports:

    Original Abstract
  • 1998