A multi-method framework for decoding the spatiotemporal patterns and driving factors of environmental pollution crimes in China

The crime of polluting the environment (CPE) poses a serious threat to ecological security. However, the spatiotemporal distribution and driving factors of CPE in China remain ambiguous. Herein the number of CPE cases (CPEs) related to water pollution (CPE-W) and hazardous waste pollution (CPE-HW) in 30 provinces of China from 2016 to 2023 are selected as the research object. By integrating 18,324 CPEs data, a multi-dimensional spatiotemporal detection (MDSD) framework is built to analyze the spatiotemporal distribution patterns and driving factors of two types of CPEs. Similarly, both types of CPEs exhibit a time trend of “rising first and then falling”, reaching a peak in 2019 and then continuously declining. They also present a spatial pattern of “higher in the east and lower in the west”. Differently, CPE-W mainly occurs in the Yangtze River Delta, while CPE-HW is highly prevalent in the Bohai Rim, and the western provinces are stable low-value regions. The decomposition of the Logarithmic Mean Divisia Index (LMDI) identifies that CPE rate (CPER), emission intensity per area (EIPA), economic development level (EDL), and unemployment rate (UR) are the key driving factors, which present significant regional heterogeneity. For example, the CPE-W in the Yangtze River Delta is more prominently driven by EIPA, while the CPE-HW in the Bohai Rim is significantly influenced by pollutant emission intensity (PEI). The two-way fixed effects model (TWFE) shows that when UR exceeds 0.02 and 0.015, respectively, CPE-W and CPE-HW show increasing trends. These explored spatiotemporal distribution patterns and driving factors of CPEs should serve as references for promoting precise governance of CPE.