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Identifying potentially contaminated areas with MaxEnt model for petrochemical industry in China.

ABSTRACT: 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.

SUBMITTER: Wang M

PROVIDER: S-EPMC8931184 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCitrus huanglongbing (HLB) is a destructive disease of citrus and a major threat to the citrus industry around the world. This disease accounts for substantial economic losses in China every year. Diaphorina citri Kuwayama is one of the major vectors by which citrus HLB is spread under natural conditions in China. Research is needed to identify the geographic distribution of D. citri and its major areas of occurrence and to formulate measures for early warning, monitoring, and control of this pest and citrus HLB.MethodsIn this study, the ecological niche modelling software MaxEnt (maximum entropy model) was combined with ArcGIS (a geographic information system) to predict the potential geographic distribution of D. citri in China. Key environmental factors and the appropriate ranges of their values were also investigated.ResultsOur results show that the training data provided a good forecast (AUCmean = 0.988). The highly suitable areas for D. citri in China are mainly concentrated to the south of the Yangtze River, and the total area is 139.83 × 104 km2. The area of the moderately suitable areas is 27.71 × 104 km2, with a narrower distribution than that of the highly suitable area. The important environmental factors affecting the distribution of D. citri were min temperature of coldest month, mean temperature of coldest quarter, precipitation of wettest quarter, mean temperature of warmest quarter, precipitation of warmest quarter, max temperature of warmest month, and temperature seasonality. These results provide a valuable theoretical basis for risk assessments and control of D. citri.DiscussionThe predicted results showed that there were highly suitable areas for D. citri in Chongqing, Hubei, Anhui, and Jiangsu. Therefore, the possibility exists for the further spread of D. citri in China in the future. Extreme temperature variables, especially the min temperature of the coldest month, play an important role in the distribution of D. citri and are most closely related to the distribution of D. citri.

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Identifying potentially contaminated areas with MaxEnt model for petrochemical industry in China.

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