Maogang Tang

The novel coronavirus (COVID-19) pandemic has provided a distinct opportunity to explore the mechanisms by which human activities affect air quality and pollution emissions. We conduct a quasi-difference-in-differences (DID) analysis of the impacts of lockdown measures on air pollution during the first wave of the COVID-19 pandemic in China. Our study covers 367 cities from the beginning of the lockdown on 23 January 2020 until April 22, two weeks after the lockdown in the epicenter was lifted. Static and dynamic analysis of the average treatment effects on the treated is conducted for the air quality index (AQI) and six criteria pollutants. The results indicate that, first, on average, the AQI decreased by about 7%. However, it was still over the threshold set by the World Health Organization. Second, we detect heterogeneous changes in the level of different pollutants, which suggests heterogeneous impacts of the lockdown on human activities: carbon monoxide (CO) had the biggest drop, about 30%, and nitrogen dioxide (NO₂) had the second-biggest drop, 20%. In contrast, ozone (O₃) increased by 3.74% due to the changes in the NO_x/VOCs caused by the decrease in NO_x, the decrease of O₃ titration, and particulate matter concentration. Third, air pollution levels rebounded immediately after the number of infections dropped, which indicates a swift recovery of human activities. This study provides insights into the implementation of environmental policies in China and other developing countries.

Most of the existing research on urbanization suggests that urbanization leads to a decline in ecosystem services values (ESV). However, the impacts of industrial structure and changes in land use patterns on ESV have often been ignored. Using provincial data in China from 2003 to 2015, this study demonstrates the possibility of achieving a win-win situation regarding urbanization and ESV enhancement at the global and regional scales. The negative effect from production processes and the influence of residents’ preferences are considered in the evaluation of ESV. The impact of urbanization on ESV is empirically analyzed by using a spatially adaptive semi-parametric model in order to mitigate both endogeneity of the parametric model and the curse of dimensionality in nonparametric model. The results show that there is a U-shaped curve relationship between urbanization and ESV for the whole country. However, most provinces of China are still located at the left side of the U-shaped curve where urbanization reduces the ESV per capita. Central and local governments should strengthen differentiated land use policies, environmental regulations, and finance and tax policies to transform the industrial structure, so that each province may achieve a win-win situation regarding urbanization and ESV enhancement. Such policy changes would promote sustainable development in China.