| Literature DB >> 24578605 |
Scott Fruin1, Robert Urman1, Fred Lurmann2, Rob McConnell1, James Gauderman1, Ed Rappaport1, Meredith Franklin1, Frank D Gilliland1, Martin Shafer3, Patrick Gorski3, Ed Avol1.
Abstract
To characterize exposures to particulate matter (PM) and its components, we performed a large sampling study of small-scale spatial variation in size-resolved particle mass and composition. PM was collected in size ranges of < 0.2, 0.2-to-2.5, and 2.5-to-10 μm on a scale of 100s to 1000s of meters to capture local sources. Within each of eight Southern California communities, up to 29 locations were sampled for rotating, month-long integrated periods at two different times of the year, six months apart, from Nov 2008 through Dec 2009. Additional sampling was conducted at each community's regional monitoring station to provide temporal coverage over the sampling campaign duration. Residential sampling locations were selected based on a novel design stratified by high- and low-predicted traffic emissions and locations over- and under-predicted from previous dispersion model and sampling comparisons. Primary vehicle emissions constituents, such as elemental carbon (EC), showed much stronger patterns of association with traffic than pollutants with significant secondary formation, such as PM2.5 or water soluble organic carbon. Associations were also stronger during cooler times of the year (Oct through Mar). Primary pollutants also showed greater within-community spatial variation compared to pollutants with secondary formation contributions. For example, the average cool-season community mean and standard deviation (SD) for EC were 1.1 and 0.17 μg/m3, respectively, giving a coefficient of variation (CV) of 18%. For PM2.5, average mean and SD were 14 and 1.3 μg/m3, respectively, with a CV of 9%. We conclude that within-community spatial differences are important for accurate exposure assessment of traffic-related pollutants.Entities:
Keywords: Air pollution; Particulate matter; Traffic emissions, Spatial variability
Year: 2014 PMID: 24578605 PMCID: PMC3932493 DOI: 10.1016/j.atmosenv.2013.10.063
Source DB: PubMed Journal: Atmos Environ (1994) ISSN: 1352-2310 Impact factor: 4.798