Spatiotemporal risk assessment of soil pollution in a lignite mining region using a Bayesian maximum entropy (BME) approach

The present paper aims to map pollution and assess the risk for agricultural soils in a wider lignite opencast mining and industrial area. Geochemical data related to environmental studies show that the waste characteristics favor solubilization and mobilization of inorganic contaminants and in some cases the generation of acidic leachates.The spatiotemporal distribution of soil contamination is studied by the application of the Bayesian Maximum Entropy (BME) theory which allows merging spatial and temporal estimations in a single model.Results reveal a correlation range of contaminant concentrations up to 5000 m and indicate a potential forecasting range up to 4 years. Inspection of the produced spatiotemporal maps indicates that the whole study area is contaminated by As and various heavy metals, a situation which seems to be more or less stable over time.

► Aims to map pollution in a wider lignite opencast mining and industrial area
► The spatiotemporal distribution of soil contamination is studied by BME theory.
► Results reveal a correlation range of contaminant concentrations up to 5000 m.
► A potential forecasting range up to 4 years appears.