Integrated framework to assess soil potentially toxic element contamination through 3D pollution analysis in a typical mining city

Chemosphere. 2024 May 17:359:142378. doi: 10.1016/j.chemosphere.2024.142378. Online ahead of print.

Abstract

Soil potentially toxic elements (PTEs) pollution of contaminated sites has become a global environmental issue. However, given that previous studies mostly focused on pollution assessment in surface soils, the current status and environmental risks of potentially toxic elements in deeper soils remain unclear. The present study aims to cognize distribution characteristics and spatial autocorrelation, pollution levels, and risk assessment in a stereoscopic environment for soil PTEs through 3D visualization techniques. Pollution levels were assessed in an integrated manner by combining the geoaccumulation index (Igeo), the integrated influence index of soil quality (IICQs), and potential ecological hazard index. Results showed that soil environment at the site was seriously threatened by PTEs, and Cu and Cd were ubiquitous and the predominant pollutants in the study area. The stratigraphic models and pollution plume simulation revealed that pollutants show a decreasing trend with the deepening of the soil layer. The ranking of contamination soil volume is as follows: Cu > Cd > Zn > As > Pb > Cr > Ni. According to the IICQs evaluation, this region was subject to multiple PTE contamination, with more than 60% of the area becoming seriously and highly polluted. In addition, the ecological hazard model revealed the existence of substantial ecological hazards in the soils of the site. The integrated potential ecological risk index (RI) indicated that 45.7%, 10.13%, and 4.15% of the stereoscopic areas were in considerable, high, and very high risks, respectively. The findings could be used as a theoretical reference for applying multiple methods to integrate evaluation through 3D visualization analysis in the assessment and remediation of PTE-contaminated soils.

Keywords: 3D visualization; PTEs; Pollution assessment; Pollution plume simulation; Spatial autocorrelation.