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.
Few studies have characterized within-city
spatial variations in
the oxidative potential of fine particulate air pollution (PM2.5). In this study, we evaluated multiple measures of PM2.5 oxidative potential across Toronto, Canada (2016–2017),
including glutathione/ascorbate-related oxidative potential (OPGSH and OPAA) and dithiothreitol depletion (OPDTT). Integrated 2-week samples were collected from 67 sites
in summer and 42 sites in winter. Multivariable linear models were
developed to predict OP based on various land use/traffic factors,
and PM2.5 metals and black carbon were also examined. All
three measures of PM2.5 oxidative potential varied substantially
across Toronto. OPAA and OPDTT were primarily
associated with traffic-related components of PM2.5 (i.e.,
Fe, Cu, and black carbon) whereas OPGSH was not a strong
marker for traffic during either season. During summer, multivariable
models performed best for OPAA (R
CV
2 = 0.48) followed by OPDTT (R
CV
2 = 0.32) and OPGSH (R
CV
2 = 0.22). During winter, model
performance was best for OPDTT (R
CV
2 = 0.55) followed by OPGSH (R
CV
2 = 0.50) and OPAA (R
CV
2 = 0.23). Model parameters varied
between seasons, and between-season differences in PM2.5 mass concentrations were weakly/moderately correlated with seasonal
differences in OP. Our findings highlight substantial within-city
variations in PM2.5 oxidative potential. More detailed
information is needed on local sources of air pollution to improve
model performance.
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