Air quality changes during the COVID-19 in YRD region are analyzed. • The WRF-CAMx modelling system is applied to investigate impact of lowered human activities on air quality changes. • Sources of the residual pollution are figured out for policy implications for future air pollution control.

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We evaluate the one-dimensional volatility basis set (1D-VBS) and two-dimensional volatility basis set (2D-VBS) in simulating the aging of SOA derived from toluene and α-pinene against smog-chamber experiments. If we simulate the first-generation products with empirical chamber fits and the subsequent aging chemistry with a 1D-VBS or a 2D-VBS, the models mostly overestimate the SOA concentrations in the toluene oxidation experiments. This is because the empirical chamber fits include both first-generation oxidation and aging; simulating aging in addition to this results in double counting of the initial aging effects. If the first-generation oxidation is treated explicitly, the base-case 2D-VBS underestimates the SOA concentrations and O:C increase of the toluene oxidation experiments; it generally underestimates the SOA concentrations and overestimates the O:C increase of the α-pinene experiments. With the first-generation oxidation treated explicitly, we could modify the 2D-VBS configuration individually for toluene and α-pinene to achieve good model-measurement agreement. However, we are unable to simulate the oxidation of both toluene and α-pinene with the same 2D-VBS configuration. We suggest that future models should implement parallel layers for anthropogenic (aromatic) and biogenic precursors, and that more modeling studies and laboratory research be done to optimize the "best-guess" parameters for each layer.

Understanding the origin of fine particulate matter is essential to proposing proper strategies for heavy haze mitigation in Shanghai, China. In this study we used the Particulate Matter Source Apportionment Technology in Comprehensive Air Quality Model with Extensions to quantify the impacts of emissions on the concentrations of fine particulate matter (PM 2.5 ) and its important components in Shanghai during heavy haze episodes in late autumn (6-22 November 2010). The factors considered here are regions of Shanghai and its surrounding areas, long-range regional transport, and different local emission categories. The results indicate that industrial process is the dominant local contributor to total PM 2.5 mass in the whole city except that at the urban center vehicle emission contributes slightly more. In addition, industrial process and vehicle emission are the major local contributors for nitrate in Shanghai, although at urban core the contribution from vehicle emission is remarkably larger. Generally, both local contribution and regional transport contribution could dominate a severe haze event in late autumn. However, the dominant contributor could either be local emission or regional transport, usually depending on the meteorological conditions. Therefore, particular attentions should be paid to the emission control in the upwind adjacent provinces, as well as in local areas, for developing effective strategies to reduce PM 2.5 pollution in Shanghai.