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Air pollution is a major health hazard, and while air quality overall has been improving in industrialized nations, pollution is still a major economic and public health issue, with some species, such as ozone (O 3), still exceeding the standards set by governing agencies. Chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution both at local and regional scales. In this study, the Polair3D v1.11 CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model's capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales. The simulation by the model included three nested domains, at horizontal resolutions of 9 km by 9 km and 3 km by 3 km, as well as two 1 km by 1 km domains covering the cities of Montréal and Québec. We find that the model captures the spatial variability and seasonal effects and, to a lesser extent, the hour-by-hour or day-to-day temporal variability for a fixed location. The model at both the 3 km and the 1 km resolution struggled to capture high-frequency temporal variability and showed large variabilities in correlation and bias from site to site. When comparing the biases and correlation at a site-wide scale, the 3 km domain showed slightly higher correlation for carbon monoxide (CO), nitrogen dioxide (NO 2), and nitric oxide (NO), while ozone (O 3), sulfur dioxide (SO 2), and PM 2.5 showed slight increases in correlation at the 1 km domain. The performance of the Polair3D model was in line with other models over Canada and comparable to Polair3D's performance over Europe. [ABSTRACT FROM AUTHOR]

Air pollution is a major health hazard, and while air quality overall has been improving in industrialized nations, pollution is still a major economic and public health issue, with some species, such as ozone (O3), still exceeding the standards set by governing agencies. Chemical transport models (CTM) are valuable tools that aid in our understanding of the risks of air pollution both at local and regional scales. In this study, the Polair3D v1.11 CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada to assess the model's capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales. The simulation by the model included 3 nested domains, at resolutions of 9 km by 9 km, 3 km by 3 km, and two 1 km by 1 km domains covering the cities of Montreal and Quebec. We find that the model accurately captures the spatial variability and seasonal effects, and to a lesser extent, the hour-by-hour or day-to-day temporal variability for a fixed location. The model at both the 3 km and the 1 km resolution struggled to capture high frequency temporal variability, and showed large variabilities in correlation and bias from site to site. When comparing the biases and correlation at a site-wide scale, the 3 km domain showed slightly higher correlation for carbon monoxide (CO), nitrogen dioxide (NO2) and nitric oxide (NO), while ozone (O3), sulfur dioxide (SO2) and PM2.5 showed slight increases in correlation at the 1 km domain. The performance of the Polair3D model was in line with other models over Canada, and comparable to Polair3D's performance over Europe. [ABSTRACT FROM AUTHOR]

There is growing interest to move beyond fine particle mass concentrations (PM 2.5 ) 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 PM 2.5 to generate reactive oxygen species in the lung fluid (ROS), (2) PM 2.5 oxidative potential based on the depletion of ascorbate (OP AA ) and glutathione (OP GSH ) in a cell-free assay, and (3) anhysteretic magnetic remanence ( X ARM ) 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 PM 2.5 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 PM 2.5 and iron-rich magnetic nanoparticles in Toronto and Montreal.