Synoptic condition-driven summertime ozone formation regime in Shanghai and the implication for dynamic ozone control...

Regarding the continuous worsening of tropospheric ozone pollution, the scenario in Shanghai is a microcosm of the entire China. Understanding the ozone formation regimes (OFRs), their variations, and driving factors is a prerequisite for formulating effective ozone control strategies. Traditional OFR estimation by numerical model, which often involves sensitivity analysis on at least tens of scenarios, is labor-intensive and time-consuming; therefore, it is not appropriate to make OFR forecasts to guide ozone contingency control. In this study, by using a localized modeling system consisting of the Weather Research and Forecasting, Sparse Matrix Operator Kernel Emissions, and Community Multiscale Air Quality models and considering the latest emission inventory over the Yangtze River Delta of China, we discovered a strong connection between the variations of large-scale circulation (LSC) and OFRs over Shanghai in July 2017, thereby providing an alternative way to infer OFR. During the northward movement of Western Pacific Subtropical High from South China Sea, the wind field over Shanghai changed from weak westerly to moderate southwesterly and to one without a distinct direction. The local OFR shifted from anthropogenic volatile organic compounds (AVOCs)-limited to NO_x-limited and ultimately to the transitional regime. Such a variation in OFR is essentially driven by the spatial heterogeneity of NO_x and AVOC emissions in different directions of Shanghai, brought on by the wind under different LSC patterns. With the existing weather forecasting technology, the LSC patterns can be well-predicted 48-72 h in advance. Hence, we propose the adoption of a dynamic ozone control strategy for Shanghai with the priority control target on AVOC or NO_x emission sources adjusted according to the LSC pattern and OFR forecasts in a forthcoming O₃ pollution episode. This would serve to maximize the peak ozone reduction under varying pollution conditions.