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An uncertainty for clean air: Air quality modeling implications of underestimating VOC emissions in urban inventories

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Abstract Recent literature has shown that volatile organic compound (VOC) emission inventories for urban regions may be substantially underestimated. In particular, non-transportation sources including volatile chemical products (VCP) are increasing… Click to show full abstract

Abstract Recent literature has shown that volatile organic compound (VOC) emission inventories for urban regions may be substantially underestimated. In particular, non-transportation sources including volatile chemical products (VCP) are increasing in relative importance due to both the current and historical focus on controlling transportation emissions. These findings have major implications for photo-chemical air quality modeling used to determine appropriate and effective regulatory controls to meet limits for primary and secondary pollutants. Using a regional air quality model, we quantify the changes in ozone and fine particulate matter (PM2.5) simulated for updated VOC emissions reported in the recent literature relative to a baseline inventory for California. Results show that simulated maximum 8-hr ozone concentrations could increase by 17.4 ppb in summer and by 15.6 ppb in winter, and the 24-hr maximum PM2.5 could increase by 7.8 μg/m3 in winter. Impacts reflect differences in the spatial location of VCP source emissions relative to those for transportation. However, compared to measurement data, model performance is not substantially improved by the adjustment of VOC emissions of current sources. In brief, augmented VOC emission inventories impact simulated concentrations of pollutants, but may not improve the performance of models used for the design of emission control policy without more refined representation of missing VCPs sources in the inventory.

Keywords: quality modeling; uncertainty clean; air; voc emissions; air quality

Journal Title: Atmospheric Environment
Year Published: 2019

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