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Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation

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dc.contributor.author Setton, Eleanor M
dc.contributor.author Keller, C Peter
dc.contributor.author Cloutier, Denise
dc.contributor.author Hystad, Perry W
dc.date.accessioned 2014-08-14T23:53:14Z
dc.date.available 2014-08-14T23:53:14Z
dc.date.copyright 2008 en_US
dc.date.issued 2008-07-18
dc.identifier.citation Setton et al.: Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation. International Journal of Health Geographics 2008, 7:39 en_US
dc.identifier.uri http://www.ij-healthgeographics.com/content/7/1/39
dc.identifier.uri http://dx.doi.org/10.1186/1476-072X-7-39
dc.identifier.uri http://hdl.handle.net/1828/5553
dc.description BioMed Central en_US
dc.description.abstract Background: Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results: Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion: The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. en_US
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.title Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation en_US
dc.type Article en_US
dc.description.scholarlevel Faculty en_US
dc.description.reviewstatus Reviewed en_US


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