Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design

Though many scholars and practitioners are paying more attention to the health and life of the public after the COVID-19 outbreak, extant literature has so far failed to explore the variation of ambient air quality during this pandemic. The current study attempts to fill the gap by disentangling the causal effects of epidemic prevention on air quality in China, measured by the individual pollutant dimensionless index, from other confounding factors. Using the fixed effects model, this article finds that five air indicators, PM2.5, PM10, CO, NO2, and SO2, significantly improved during the shutdown period, with NO2 showing the most improvement. On the contrary, O3 shows an inverse pattern, that is, O3 gets worse unexpectedly. The positive impact of epidemic prevention on air quality, especially in terms of PM2.5, PM10, and NO2, become manifest five days after the resumption of labor, indicated by the result of a regression discontinuity design. These findings are still robust and consistent after the dataset of 2019 as a counterfactual sample is utilized. The findings of this paper make contributions to both environmental governance and pandemic prevention, with relevant guidelines regarding the health and life of the public and governmental behavioral management strategies discussed.