Predicting Spatial Variations In Multiple Measures Of Oxidative Burden For Outdoor Fine Particulate Air Pollution Across Canada

ENVIRONMENTAL SCIENCE & TECHNOLOGY(2021)

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摘要
Fine particulate air pollution (PM2.5) is a leading contributor to the overall global burden of disease. Traditionally, outdoor PM2.5 has been characterized using mass concentrations which treat all particles as equally harmful. Oxidative potential (OP) (per mu g) and oxidative burden (OB) (per m(3)) are complementary metrics that estimate the ability of PM2.5 to cause oxidative stress, which is an important mechanism in air pollution health effects. Here, we provide the first national estimates of spatial variations in multiple measures (glutathione, ascorbate, and dithiothreitol depletion) of annual median outdoor PM2.5 OB across Canada. To do this, we combined a large database of ground-level OB measurements collected monthly prospectively across Canada for 2 years (2016-2018) with PM2.5 components estimated using a chemical transport model (GEOS-Chem) and satellite aerosol observations. Our predicted ground-level OB values of all three methods were consistent with ground-level observations (cross-validation R-2 = 0.63-0.74). We found that forested regions and urban areas had the highest OB, predicted primarily by black carbon and organic carbon from wildfires and transportation sources. Importantly, the dominant components associated with OB were contributing to PM2.5 mass concentrations (secondary inorganic aerosol); thus, OB metrics may better indicate and sources on health than the bulk PM2.5 mass, reinforcing that OB estimates can complement the existing PM2.5 data in future national-level epidemiological studies.
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关键词
oxidative potential, oxidative burden, PM2.5, linear regression, GEOS-Chem, satellite
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