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• W4366977683 endingPage "121687" @default.
• W4366977683 startingPage "121687" @default.
• W4366977683 abstract "Identifying the potential soil pollution areas derived from the metal mining industry usually requires extensive field investigation and laboratory analysis. Moreover, the previous studies mainly focused on a single or a few mining areas, and thus couldn't provide effective spatial decision support for controlling soil pollution derived from the metal mining industry at the national scale. This study first conducted a literature investigation and web crawler for the relevant information on the metal mining areas in China. Next, MaxEnt with mine reserve scales (MaxEnt_MRS) was proposed for spatially predicting the probabilities of soil pollution derived from the metal mining industry in China. Then, MaxEnt_MRS was compared with the basic MaxEnt. Last, the potential soil pollution areas were identified based on the pollution probabilities, and the relationships between the soil pollution probabilities and the main environmental factors were quantitatively assessed. The results showed that: (i) MaxEnt_MRS (AUC = 0.822) obtained a better prediction effect than the basic MaxEnt (AUC = 0.807); (ii) the areas with the soil pollution probabilities higher than 54% were mainly scattered in the eastern, south-western, and south-central parts of China; (iii) GDP (45.7%), population density (30.1%), soil types (15.5%), average annual precipitation (3.9%), and land-use types (3.1%) contributed the most to the prediction of the soil pollution probabilities; and (iv) the soil pollution probabilities in the areas with all the following conditions were higher than 54%: GDP, 7600-2612670 thousand yuan/km2; population density, 152-551 people/km2; precipitation, 924-2869 mm/year; soil types, Ferralisols or Luvisols; and land-use types, townland, mines, and industrial areas. The above-mentioned results provided effective spatial decision support for controlling soil pollution derived from the metal mining industry at the national scale." @default.
• W4366977683 created "2023-04-27" @default.
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• W4366977683 date "2023-07-01" @default.
• W4366977683 modified "2023-10-08" @default.
• W4366977683 title "Identifying the potential soil pollution areas derived from the metal mining industry in China using MaxEnt with mine reserve scales (MaxEnt_MRS)" @default.
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• W4366977683 doi "https://doi.org/10.1016/j.envpol.2023.121687" @default.
• W4366977683 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37105461" @default.
• W4366977683 hasPublicationYear "2023" @default.
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