Spatio-temporal pattern assessment of China's environmental performance and its spatial drivers: evidence from city-level data over 2003-2019.

Abstract

A comprehensive assessment of China's environmental performance (EP) and an investigation into its driving factors are essential prerequisites for advancing environmental protection efforts. However, existing studies have often exhibited a one-sided EP evaluation approach and lacked a systematic perspective. Consequently, this study has adopted a holistic approach by integrating environmental protection and pollution within the same theoretical framework. We have employed the "P-S-R" model to comprehensively assess the EP of 272 cities from 2003 to 2019. Concurrently, we have applied the spatial Durbin model to analyze EP drivers utilizing three spatial matrices. The findings of this study reveal several vital insights. Firstly, the mean EP value for China is 0.1138, indicating a low level, but it demonstrates a consistent upward trend over the years. When comparing cities with high EP, they are predominantly situated in northern China, northeastern China, and certain areas along the southeastern coast. Secondly, from a spatial perspective, the directionality of EP exhibits a trend from "northeast to the southwest," with the center of gravity located in and around Zhumadian, Henan Province, gradually shifting towards the northeast. The majority of cities fall within the H-H and L-L clusters, displaying significant positive spatial autocorrelation effects. Thirdly, EP drivers encompass a wide range of factors, including economic development, urbanization, resource dependence, industrial structure, infrastructure construction, environmental regulation, government regulatory capacity, scientific and technological innovation, and foreign direct investment. These drivers also exhibit significant spillover effects. Finally, the characteristics of EP development vary between resource-based cities (RBCs) and non-resource-based cities (non-RBCs), as well as among the eastern, central, and western regions. Moreover, there are disparities in the driving factors' direct, indirect, and overall effects. Consequently, we must propose tailored strategies and recommendations to enhance EP, considering the heterogeneous effects of influencing factors across different city types, regions, and collaboration approaches.