Source analysis of the heavy metals in paddy field soils in Karst mining areas of Guizhou using APCS-MLR receptor model

Heavy metals contamination in soil has posed a serious threat to human and the ecosystem. Particularly, there is a significantly higher background of soil heavy metals in the Karst areas of southwest China. Human activities (such as industry, mining and agriculture) have aggravated to seriously endanger the food safety and human health in recent years. Therefore, it is highly urgent to quantitatively assess on the main sources of heavy metals for the safe production of rice in paddy fields. Taking the rice fields around a typical karst industrial and mining area in a county of Guiyang City, Guizhou Province, China as the research object, this study aims to implement a source analysis of heavy metals using the Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) model combined with geographical and correlation analysis, according to the geographic location of industrial and mining sites. A total of 122 topsoil samples were collected in paddy fields, where eight heavy metals were measured, including Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni. The results showed that Hg was the most abnormal element in the study area, and its coefficient of variation (384.56%) was the maximum, followed by Cd (129.99%). The average content of the eight heavy metals was 1.51 mg/kg, where the average of Hg was 13.73 times more than of the soil background value in the whole Province. The other selected elements were all higher than the background value, except for Cr and Ni less than or equal to the background. Specifically, the Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni in some sampling points exceeded the risk screening value that realized by the "Soil Environmental Quality Agricultural Land Soil Pollution Risk Control Standard" (GB 15618-2018), and their exceeded rates were 26.23%, 31.97%, 5.74%, 0.82%, 7.38%, 7.38%, and 4.10%, respectively. The exceeded proportion of Cd was the highest, followed by As and Hg, indicating the most prominent pollution risk. A correlation analysis showed that the correlation coefficients of Cd-Cr, Cd-Zn, Cr-Ni, Cr-Cu, and Cu-Ni were greater than 0.6, exhibiting a strong correlation (P< 0.01). Furthermore, the high-value areas of Cd, Cr, Cu, Zn, and Ni were mainly distributed in the middle of the study area, indicating relatively consistent locations in the spatial distribution. The high-value areas of Hg and Pb were mainly distributed in the southwest and the west of the study area, respectively, whereas, those of As were in the northwest, the middle and southwest, indicating an outstanding continuity. Correspondingly, there were similar characteristics of spatial distribution of heavy metals. As such, three main pollution sources were achieved in APCS-MLR and geostatistical interpolation, including the natural resources, mixed sources of industry, mining and agriculture, as well the atmospheric deposition and mixed agricultural sources. Among them, the natural resources dominated the elements of Cd, Cr, Cu, and Ni. Additionally, there were much more complex pollution sources of Cd, indicating a greater influence of anthropogenic sources. Pb and Zn were mainly affected by the mixed sources of industry, mining and agriculture, whereas, Hg and As were mainly depended on the mixed sources of atmospheric deposition and agriculture. Especially, Hg was extremely strong affected by human activities in the Karst areas of southwest China. © 2022, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.