Source-sink response analysis of heavy metals and soil pollution assessment in non-ferrous metal industrial agglomeration areas based on decision unit

Abstract

Soil heavy metals (HMs) pollution is a worldwide concern. In this study, decision units based on “source-sink relationship” were established using multi-source data. The source-sink response of heavy metals in agricultural soils at the regional scale was analyzed using machine learning methods, receptor models, and geospatial analysis. The comprehensive pollution risk score (CRS) was proposed by integrating a variety of key evaluation indicators to evaluate the pollution degree of each decision unit. We divided the study area into 193 decision units, the proportions of sites with concentrations of Cd, Hg, As, Pb, and Cr exceeding the most stringent risk screening values were 16.4 %, 2.2 %, 4.0 %, 7.6 %, and 0.2 %, respectively. Agricultural activities (livestock manure, fertilizer, sewage irrigation), industrial activities (rare earth ore and tungsten‑molybdenum mining and smelting), and soil parent material are the dominant pollution sources of HMs in the study area. The risk of contamination of each element is ranked from largest to smallest according to the CRS as Cd > Hg > Pb > As > Cr. The western and southwestern water pollution decision units are the areas with the highest risk of soil HMs contamination. This quantitative evaluation framework can provide a relatively accurate decision basis for soil pollution management.