Population Mobility and Urban Air Quality: Causal Inference and Impact Measurement

Abstract

This paper treats the lockdown of Hubei Province during the outbreak of COVID-19 in early 2020 as a quasi-experiment, and uses the prefecture-level data of 328 cities in China to identify the causal effects of population mobility and urban air quality. This paper uses the DID model to eliminate the ‘Spring Festival effect’ with data from the same period of the lunar calendar in 2019 as the control group, and finds the reduction in population mobility has a clear causal impact on the improvement of urban air quality. The vast majority of air pollutants decreased, but ozone, which has a special generation mechanism, increased. This paper also constructs 29-day panel data of 328 prefecture-level cities from January to February in 2020 to quantitatively estimate the impact of population flow on urban air quality. After controlling for fixed effects, the results reveal that 1% increases in intra-city and inter-city population flows correspond to respective increases of 0.433% and 0.201% in the urban air quality index. Compared with inter-city flow, intra-city population flow increases air pollution more severely.