Identifying potentially contaminated areas with MaxEnt model for petrochemical industry in China
2022
Wang, Meng | Chen, Huichao | Lei, Mei
The presence of heavy metal and organic pollutants in wastewater effluents, flue gases, and even solid wastes from petrochemical industries renders improper discharges liable to posing threats to the ecological environment and human health. It is beneficial for pollution control to find out the regional distribution of contaminated sites. This study explored the relationship between the petrochemical contaminated areas and natural, socio-economic, and traffic factors. Ten indicators were selected as input variables, and the MaxEnt model was conducted to identify the potentially contaminated areas. Moreover, among these 10 variables, the factors that have the great impact on the results were determined according to the contribution of variables. The results showed that the MaxEnt model performed well with AUC of 0.981 ± 0.004, and 90% of the measured contaminated sites was located in areas with medium and high probability of contamination in the prediction results. The map of potentially contaminated areas indicated that the areas with high probability of contamination were distributed in Yangtze River Delta, Beijing, Tianjin, southern Guangdong, Fujian coastal areas, central Hubei and northeast Hunan, central Sichuan, and southwest Chongqing. The responses of variables presented that high probability of petrochemical contamination tended to appear in cities with developed economy, dense population, and convenient transportation. This study presents a novel way to identify the potentially contaminated areas for petrochemical sites and provides a theoretical basis to formulate future management strategies.
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