Causal complexity of environmental pollution in China: a province-level fuzzy-set qualitative comparative analysis

Environmental problems are endowed with the causal complexity of multiple factors. Traditional quantitative research on the influencing mechanism of environmental pollution has tended to focus on the marginal effects of specific influencing factors but generally neglected the multiple interaction effects between factors (especially three or more). Based on the panel data of 30 Chinese provinces between 2011 and 2020, this study employs fuzzy set qualitative comparative analysis (fsQCA) - which can provide a fine-grained insight into the causal complexity of environmental issues - to shed light on the influencing mechanism of environmental pollution. The results show that there are several different configurations of pollution drivers which lead to high pollution or low pollution in provinces, confirming the multiple causality, causal asymmetry, and equifinality of environmental pollution. Furthermore, the combination effect of advanced industrial structure, small population size, and technological advance is significant in achieving a state of green environment compared to environmental regulation factors. In addition, spatiotemporal analysis of the configurations indicates that strong path dependencies and spatial agglomeration exist in current local environmental governance patterns. Finally, according to our findings, targeted policy recommendations are provided.

Automated summary

This study investigates the influencing mechanism of environmental pollution using fuzzy set qualitative comparative analysis (fsQCA) and finds that environmental problems are characterized by causal complexity with multiple factors. The results reveal different configurations of pollution drivers that result in high or low pollution levels in different provinces, demonstrating the multiple causality, causal asymmetry, and equifinality of environmental pollution. Additionally, the combination effect of advanced industrial structure, small population size, and technological advance is found to be significant in achieving a green environment.