Spatiotemporal Heterogeneity and Spatial Aggregation Characteristics of PM2.5 and O3 in Southwest China: Evidence from a Mega Mountain City

Cities are the basic administrative units for formulating and implementing policies to reduce pollution and carbon dioxide. This study used statistical analysis and Kriging interpolation to clarify the spatiotemporal fluctuation characteristics of PM2.5 and O3 at different time scales in Chongqing from 2017 to 2022. It also explored the compliance rate of pollutants and their correlation. In addition, GeoDa software was used to examine the spatial autocorrelation and clustering of pollutants. Finally, relevant measures and suggestions were put forward from different perspectives of provinces, cities, districts and counties. The results showed that PM2.5 and O3 pollutions were still particularly serious and there was a complex linear interaction between them. Furthermore, PM2.5 and O3 both have significant positive spatial autocorrelation and aggregation characteristics, and their high-high agglomeration areas are mainly concentrated in the city proper of Chongqing. These results can provide potential guidance for developing differentiated and refined air pollution prevention and control measures in the region, thereby promoting the continuous improvement of regional air quality. More importantly, it can provide a reference for the practice of collaborative carbon pollution reduction and regional collaborative emission reduction in China’s megacities. It also provide insights and methods that can be applied to other countries (WHO: World Health Organization; SCB: Sichuan Basin; NAAQS: National Ambient Air Quality Standards of China; MEIC: Multi-resolution Emission Inventory for China; VOCs: Volatile Organic Compounds).