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Fine particulate matter and polycyclic aromatic hydrocarbon concentration patterns in Roxbury, Massachusetts: a community-based GIS analysis.
Author(s) -
Jonathan I. Levy,
E. Andrés Houseman,
John D. Spengler,
Po−Ru Loh,
Louise Ryan
Publication year - 2001
Publication title -
environmental health perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.257
H-Index - 282
eISSN - 1552-9924
pISSN - 0091-6765
DOI - 10.1289/ehp.01109341
Subject(s) - particulates , environmental science , pollutant , pollution , air pollution , environmental chemistry , polycyclic aromatic hydrocarbon , environmental health , environmental engineering , chemistry , medicine , organic chemistry , ecology , biology
Given an elevated prevalence of respiratory disease and density of pollution sources, residents of Roxbury, Massachusetts, have been interested in better understanding their exposures to air pollution. To determine whether local transportation sources contribute significantly to exposures, we conducted a community-based pilot investigation to measure concentrations of fine particulate matter (particulate matter < 2.5 microm; PM(2.5)) and particle-bound polycyclic aromatic hydrocarbons (PAHs) in Roxbury in the summer of 1999. Community members carried portable monitors on the streets in a 1-mile radius around a large bus terminal to create a geographic information system (GIS) map of concentrations and gathered data on site characteristics that could predict ambient concentrations. Both PM(2.5) and PAH concentrations were greater during morning rush hours and on weekdays. In linear mixed-effects regressions controlling for temporal autocorrelation, PAH concentrations were significantly higher with closer proximity to the bus terminal (p < 0.05), and both pollutants were elevated, but not statistically significantly so, on bus routes. Regressions on a subset of measurements for which detailed site characteristics were gathered showed higher concentrations of both pollutants on roads reported to have heavy bus traffic. Although a more comprehensive monitoring protocol would be needed to develop robust predictive functions for air pollution, our study demonstrates that pollution patterns in an urban area can be characterized with limited monitoring equipment and that university-community partnerships can yield relevant exposure information.

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