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Determinants of the spatial distributions of elemental carbon and particulate matter in eight Southern Californian communities

By Robert Urman, James Gauderman, Scott Fruin, Fred Lurmann, Feifei Liu, Reza Hosseini, Meredith Franklin, Edward Ayol, Bryan Penfold, Frank Gilliland, Bert Brunekreef and Rob McConnell

Abstract

Emerging evidence indicates that near-roadway pollution (NRP) in ambient air has adverse health effects. However, specific components of the NRP mixture responsible for these effects have not been established. A major limitation for health studies is the lack of exposure models that estimate NRP components observed in epidemiological studies over fine spatial scale of tens to hundreds of meters. In this study, exposure models were developed for fine-scale variation in biologically relevant elemental carbon (EC). Measurements of particulate matter (PM) and EC less than 2.5 mu m in aerodynamic diameter (EC2.5) and of PM and EC of nanoscale size less than 0.2 mu m were made at up to 29 locations in each of eight Southern California Children's Health Study communities. Regression-based prediction models were developed using a guided forward selection process to identify traffic variables and other pollutant sources, community physical characteristics and land use as predictors of PM and EC variation in each community. A combined eight-community model including only CALINE4 near-roadway dispersion-estimated vehicular emissions accounting for distance, distance-weighted traffic volume, and meteorology, explained 51% of the EC0.2 variability. Community-specific models identified additional predictors in some communities; however, in most communities the correlation between predicted concentrations from the eight-community model and observed concentrations stratified by community was similar to those for the community-specific models. EC2.5 could be predicted as well as EC0.2. EC2.5 estimated from CALINE4 and population density explained 53% of the within-community variation. Exposure prediction was further improved after accounting for between-community heterogeneity of CALINE4 effects associated with average distance to Pacific Ocean shoreline (to 61% for EC0.2) and for regional NOx pollution (to 57% for EC2.5). PM fine spatial scale variation was poorly predicted in both size fractions. In conclusion, models of exposure that include traffic measures such as C.ALINE4 can provide useful estimates for EC0.2 and EC2.5 on a spatial scale appropriate for health studies of NRP in selected Southern California communities. (C) 2013 Elsevier Ltd. All rights reserved

Topics: Air pollution, Elemental carbon, Particulate matter, Exposure modeling, USE REGRESSION-MODELS, AIR-POLLUTION CONCENTRATIONS, DIESEL EXHAUST PARTICLES, PM2.5 ABSORBENCY, NITROGEN-DIOXIDE, ESCAPE PROJECT, POLLUTANTS, EXPOSURE, COHORT, NO2
Year: 2014
OAI identifier: oai:dspace.library.uu.nl:1874/305442
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