Characterizing the spatial distribution of ambient ultrafine particles in Toronto, Canada: A land use regression model.
Exposure models are needed to evaluate the chronic health effects of ambient ultrafine particles (<0.1 μm) (UFPs). We developed a land use regression model for ambient UFPs in Toronto, Canada using mobile monitoring data collected during summer/winter 2010-2011. In total, 405 road segments were included in the analysis. The final model explained 67% of the spatial variation in mean UFPs and included terms for the logarithm of distances to highways, major roads, the central business district, Pearson airport, and bus routes as well as variables for the number of on-street trees, parks, open space, and the length of bus routes within a 100 m buffer. There was no systematic difference between measured and predicted values when the model was evaluated in an external dataset, although the R(2) value decreased (R(2) = 50%). This model will be used to evaluate the chronic health effects of UFPs using population-based cohorts in the Toronto area.
Air Health Science Division, Health Canada, Ottawa, Canada. Electronic address: scott.weichenthal@hc-sc.gc.ca.
Scott
S
Weichenthal
Air Health Science Division, Health Canada, Ottawa, Canada.
Keith
K
Van Ryswyk
School of Urban Planning, McGill University, Montreal, Canada.
Alon
A
Goldstein
Department of Civil Engineering, McGill University, Montreal, Canada.
Maryam
M
Shekarrizfard
Department of Civil Engineering, McGill University, Montreal, Canada.
Marianne
M
Hatzopoulou
D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis* / Q000706:statistics & numerical data; D002170:Canada; D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008962:Models, Theoretical; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D062206:Spatial Analysis
D000393:Air Pollutants; D052638:Particulate Matter
Built environment; Land use regression; Traffic; Ultrafine particles