Land urbanization and urban CO2 emissions: Empirical evidence from Chinese prefecture-level cities.

Changes in land use and the resulting human practices in the land urbanization process would lead to variations in the function, intensity, and efficiency of CO2 emissions and greatly influence urban CO2 emissions. Therefore, using Chinese prefecture-level data for a time period ranging from 2003 to 2017, we systematically examine the mechanism of how land urbanization influences CO2 emissions based on land-use intensity regulation, land-use structure optimization, and land-use efficiency improvements. First, the benchmark results show that land urbanization's influence on urban CO2 emissions is significantly positive. This indicates that the consumption effect caused by land urbanization exceeds the agglomeration effect. Furthermore, the results of the nonlinear analysis using the spatial adaptive semi-parametric and semi-parametric spatial dynamic panel models show that the association between land urbanization and carbon emissions demonstrates an inverted U-shaped curve. Simultaneously, land urbanization represents a dynamic cumulative and spatial spillover effect on urban CO2 emissions. Second, a mechanism analysis reveals that effective land urbanization can promote CO2 emission reductions through efficiency improvement, structure optimization and proper control of the land-use intensity. Additionally, we analyze heterogeneity in regional differences. In the line with study findings, the central government in China should promote the optimization of territorial spatial governance, optimize energy consumption structures, make comprehensive use of its funds, tax policies, industrial development support, and market-oriented mechanisms, and further optimize the layout of urban space.

The Impact of the COVID-19 Pandemic on Ambient Air Quality in China: A Quasi-Difference-in-Difference Approach.

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 NOx/VOCs caused by the decrease in NOx, 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.