Predicting Spatial Variations in Multiple Measures of PM2.5Oxidative Potential and Magnetite Nanoparticles in Toronto and Montreal, Canada

Ripley, S. and Minet, L. and Zalzal, J. and Godri Pollitt, K. and Gao, D. and Lakey, P.S.J. and Shiraiwa, M. and Maher, B.A. and Hatzopoulou, M. and Weichenthal, S. (2022) Predicting Spatial Variations in Multiple Measures of PM2.5Oxidative Potential and Magnetite Nanoparticles in Toronto and Montreal, Canada. Environmental Science and Technology, 56 (11). pp. 7256-7265. ISSN 0013-936X

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Abstract

There is growing interest to move beyond fine particle mass concentrations (PM2.5) when evaluating the population health impacts of outdoor air pollution. However, few exposure models are currently available to support such analyses. In this study, we conducted large-scale monitoring campaigns across Montreal and Toronto, Canada during summer 2018 and winter 2019 and developed models to predict spatial variations in (1) the ability of PM2.5 to generate reactive oxygen species in the lung fluid (ROS), (2) PM2.5 oxidative potential based on the depletion of ascorbate (OPAA) and glutathione (OPGSH) in a cell-free assay, and (3) anhysteretic magnetic remanence (XARM) as an indicator of magnetite nanoparticles. We also examined how exposure to PM oxidative capacity metrics (ROS/OP) varied by socioeconomic status within each city. In Montreal, areas with higher material deprivation, indicating lower area-level average household income and employment, were exposed to PM2.5 characterized by higher ROS and OP. This relationship was not observed in Toronto. The developed models will be used in epidemiologic studies to assess the health effects of exposure to PM2.5 and iron-rich magnetic nanoparticles in Toronto and Montreal.

Item Type:
Journal Article
Journal or Publication Title:
Environmental Science and Technology
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300/2304
Subjects:
?? fine particlesland use regressionoxidative potentialoxidative stressparticulate air pollutionair pollutioneconomicsland usemagnetitenanomagneticsparticles (particulate matter)developed modelfine particle massfine-particlesland use regressionmass concentra ??
ID Code:
188490
Deposited By:
Deposited On:
09 Mar 2023 13:35
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 11:47