Unraveling the O-NO-VOCs relationships induced by anomalous ozone in industrial regions during COVID-19 in Shanghai.

The COVID-19 pandemic promoted strict restrictions to human activities in China, which led to an unexpected increase in ozone (O) regarding to nitrogen oxides (NOx) and volatile organic compounds (VOCs) co-abatement in urban China. However, providing a quantitative assessment of the photochemistry that leads to O increase is still challenging. Here, we evaluated changes in O arising from photochemical production with precursors (NO and VOC) in industrial regions in Shanghai during the COVID-19 lockdowns by using machine learning models and box models. The changes of air pollutants (O, NO, VOCs) during the COVID-19 lockdowns were analyzed by deweathering and detrending machine learning models with regard to meteorological and emission effects. After accounting for effects of meteorological variability, we find increase in O concentration (49.5%). Except for meteorological effects, model results of detrending the business-as-usual changes indicate much smaller reduction (-0.6%), highlighting the O increase attributable to complex photochemistry mechanism and the upward trends of O due to clear air policy in Shanghai. We then used box models to assess the photochemistry mechanism and identify key factors that control O production during lockdowns. It was found that empirical evidence for a link between efficient radical propagation and the optimized O production efficiency of NO under the VOC-limited conditions. Simulations with box models also indicate that priority should be given to controlling industrial emissions and vehicle exhaust while the VOCs and NO should be managed at a proper ratio in order to control O in winter. While lockdown is not a condition that could ever be continued indefinitely, findings of this study offer theoretical support for formulating refined O management in industrial regions in Shanghai, especially in winter.