Heavy Metals in Soil around a Typical Antimony Mine Area of China: Pollution Characteristics, Land Cover Influence and Source Identification

Abstract

To understand contamination characteristics and identify sources of heavy metals in soil affected by complex mine activities, a detailed survey of soil heavy metals from different land cover types was investigated around the Xikuangshan (XKS) antimony mine in south-central China. Soil samples had average concentrations of Sb, As, Cd, Cr, Hg, Pb, Cu, Zn and Ni exceeding their background level in the Hunan province. Sb, As and Cd were the main pollutants. A total of 86.8% of samples were severely polluted, characterized by the Nemerow’s comprehensive index, and 68.4% of samples were of very high potential ecological risk, primarily contributed by Sb, Cd and Hg. Among different land cover patterns, Hg, Pb and Cd concentrations showed a statistically significant difference. The application of Pearson correlation, principal component analysis (PCA) and hierarchical cluster analysis (HCA) combined with spatial interpolation GIS mapping revealed that Ni, Cr and Cu were mainly from natural parent materials, whereas other heavy metals were related to anthropogenic sources. Pb, As and Hg were mainly derived from smelting processes of sulfide minerals in the XKS area. The agricultural practice is the main factor for the accumulation of Cd and Zn, and sphalerite smelting also contributed to high Zn concentrations. Particularly, spatial variation of soil Sb concentrations was affected by multiple factors of complex antimony mine activities related to mining, beneficiation and smelting in the XKS area. These results are useful for the prevention and reduction of heavy metal contamination in soils by various effective measures in typical regions affected by antimony mine activities.

Application of Machine Learning for Prediction and Monitoring of Manganese Concentration in Soil and Surface Water

“…Spatial analysis was performed using a GIS to convert point data into spatially continuous data, with systematic interpolation assigning data to unsampled sites. Spatial interpolation is widely employed in environmental studies, where it can be highly effective [56] in improving the assessment of an area's condition [57,58]. In this study, the inverse distance weighting (IDW) method was used to estimate values in unsampled locations using the weighted average of known data points, with these weights inversely correlated to the distances between the sampled and predicted points.…”

Contamination and Spatial Distribution of Metal(loid)s in the Stream Sediment near the Greenhouse

“…Soil contamination by metal(loid)s is a serious global environmental problem [53], especially in rivers and agricultural lands that utilize water, which is directly related to human health. Soil contamination with metal(loid)s is caused by a variety of sources, including natural weathering [54,55], mining activities [56,57], industrial activities [58,59], civil engineering, construction activities [60,61], and increased traffic [61][62][63].…”