[Analysis of the Influencing Factors of Heavy Metal Pollution in the Surrounding Soil of Typical Industrial Enterprises in Sichuan based on Geographical Detectors].

The surrounding soils of nine typical industrial enterprises in Sichuan Province were selected as the research objects. The contents of heavy metals Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn in 25 surface soil samples around industrial enterprises were collected and analyzed. The potential ecological risk assessment method was used to evaluate the potential ecological risks of heavy metals in the soil. Based on the geographic detector, ten influencing factors, such as the distance from the enterprise, the relative elevation difference with the location of the enterprise, and the type of industry were selected as independent variables, and the analysis was conducted with the content of heavy metals as the dependent variable, and further verification was conducted using correlation analysis. The results showed that the soils around industrial enterprises in the study area were mainly characterized by "moderate" potential risks, accounting for 40%, whereas the other four risk types each accounted for 8% to 20%. Cd and Hg were the main contributing indicators to the potential ecological risk in the study area. The results of the geographic detector showed that "distance from the enterprise" had the strongest explanatory power for Cd, Pb, and Zn； "industry type" had the strongest explanatory power for As, Cr, Cu, and Ni； and "precipitation" had the strongest explanatory power for Hg. The results of interaction detection showed that after the interaction of each factor, the explanatory power was increased, indicating that the content of heavy metals in soil was affected by a compound of multiple influencing factors. The results of correlation verification showed that there were significant correlations between Cd, As, Pb, and Zn, indicating a certain homogeneity among the four heavy metals, which was basically consistent with the results of the geographic detector and could further validate the results of the geographic detector, making the results more accurate and reliable.