Source Apportionment and Spatial Distributions of Coarse Particles During the Regional Air Pollution Study

• Published in: Environmental science & technology 2008-05, Vol.42 (10), p.3524-3530
• Main Authors: Hwang, Injo, Hopke, Philip K, Pinto, Joseph P
• Format: Article
• Language: English
• Subjects: Air Pollution; Airborne particulates; Applied sciences; Cement; Characterization of Natural and Affected Environments; Environment; Environmental Monitoring; Environmental science; Exact sciences and technology; Missouri; Outdoor air quality; Particle Size; Pollution; Studies; Vehicles
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es0716204

To identify the coarse particle sources and to estimate the variability in their contributions to coarse particle mass (CPM) concentrations across the St. Louis metropolitan area, positive matrix factorization (PMF) was applied to historic ambient coarse particle compositional data from 10 Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring sites in St. Louis. Coarse particles in this study had aerodynamic sizes between 2.4 and 20 µm. The sources were qualitatively identified, and the source contributions were quantitatively estimated. Nine sources were identified for 8 of the 10 sampling sites (except rural sites 122 and 124) including soil, cement kiln/quarry, iron and steel, motor vehicle, incinerator, pigment plant, primary/secondary lead smelter, zinc smelter, and copper production, respectively. At site 122, five sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, and zinc smelter. At site 124, six sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, primary/secondary lead smelter, and zinc smelter. Soil was the largest coarse particle source across the study area (6.15 µg/m3, 29.3%). Cement kiln/quarry, iron and steel, and motor vehicle sources were the other large contributions to the coarse particles mass (5.27 µg/m3, 25.1%; 3.53 µg/m3, 16.8%; 2.72 µg/m3, 12.9%). The results of this study suggest there can be significant potential for exposure misclassification in time-series epidemiologic studies when regressing health outcomes against source contributions if they were to be estimated at a single central monitoring site.