Spatio-Temporal Heterogeneous Impacts of the Drivers of NO₂ Pollution in Chinese Cities: Based on Satellite Observation Data

Abstract

Rapid urbanization in China has led to an increasing problem of atmospheric nitrogen dioxide (NO2) pollution, which negatively impacts urban ecology and public health. Nitrogen dioxide is an important atmospheric pollutant, and quantitative spatio-temporal analysis and influencing factor analysis of Chinese cities can help improve urban air pollution. In this study, the spatio-temporal analysis methods were used to explore the variations of NO2 pollution in Chinese cities from 2005 to 2020. The findings are as follows. In more than half of Chinese cities, NO2 levels remarkably decreased between 2005 and 2020. The effective NO2 reduction strategies contributed to the significant NO2 reduction during the 13th Five-Year Plan (2016–2020). Moreover, we found that the pandemic of COVID-19 alleviated NO2 pollution in China since it reduced the traffic, industrial, and living activities. The NO2 pollution in Chinese cities was found highly spatially clustered. The geographically and temporally weighted regression model was used to analyze the spatio-temporal heterogeneity of NO2 pollution influencing factors in Chinese cities, including natural meteorological and socio-economic factors. The results showed that the GDPPC, population densities, and ambient air pressure were positively correlated with NO2 pollution. In contrast, the ratio of the tertiary to the secondary industry, temperature, wind speed, and relative humidity negatively impacted the NO2 pollution level. The findings of this research contribute to the improvement of urban air quality, stimulating the achievements of the sustainable development goals of Chinese cities.

Keywords

• NO₂ pollution
• satellite observation data
• spatio-temporal heterogeneity
• Chinese cities
• natural meteorological factors
• socio-economic factors