This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple...This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple linear regression(APCSMLR)model and positive matrix factorization(PMF)model.The applicability of the models was compared in the assessment of source apportionment.The results showed that the average contents of Cd,Hg,As,Pb,Cr,Cu,Ni,and Zn in the surface soil were 0.46,0.14,9.66,31.2,127,95.6,76.0,and 158 mg/kg,respectively.Combined with the spatial distribution and correlation analyses,the results of source apportionment were consistent for both the APCSMLR and PMF models.Cd,Hg,As,and Pb were mainly affected by the gangue heap accumulation,with respective contributions of 74.6%,79.4%,69.1%,and 67.2%based on the APCS-MLR model and respective contributions of 69.7%,60.7%,57.4%,and 41.9%based on the PMF model.Ni and Zn were mainly affected by industrial and agricultural activities,while Cr and Cu were mainly affected by natural factors.The results of the source apportionment were approximately consistent between the APCS-MLR and PMF models.The combined application of the two receptor models can make the results of source apportionment more comprehensive,accurate,and reliable.展开更多
Lipovtsy coal field mine №4 processed north-western reserves of Lipovtsy field in Primorski Krai (Russia). In 1997, the mine was declared unprofitable and was abandoned by natural flooding with no arrangement of mine...Lipovtsy coal field mine №4 processed north-western reserves of Lipovtsy field in Primorski Krai (Russia). In 1997, the mine was declared unprofitable and was abandoned by natural flooding with no arrangement of mine water discharge and in 2005 it was fully flooded. The main sources of pollution in the studied area are spoil heaps (mine wastes), underspoil filtering waters and mine waters which are being discharged on the surface after finishing of “hydraulic funnel” artificial support. The study of technogenic landscape of abandoned mine industrial area showed that its morphologic form is dominated by spoil heaps. Soils located near mine waste body differ from benchmark soils by chemical properties and size distribution. The influence of active hydrochemical mine and drainage water flows is the reason of the above-mentioned variation in soil properties. Results showed that, there exist a high correlation ratios between chemical composition of mine waters and water extracts from soil: Between the alkalinity of mine waters and electrical conductivity of soil water extracts (r = 0.73), between mine water iron content and pH of soil water extract (r = −0.56), between the solid residue of mine waters and electrical conductivity of soil water extracts (r = 0.72), between the mine waters calcium content and electrical conductivity of soil water extracts (r = −0.75), between the alkalinity of mine waters and silicon dioxide content of soil water extracts (r = 0.61), between the mineralization of mine waters and chrome content of soil water extracts (r = 0.73).展开更多
基金supported by Project of Chongqing Ecology and Environment Bureau(2021111)Project of Chongqing Science and Technology Bureau(cstc2022jxjl0005)。
文摘This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple linear regression(APCSMLR)model and positive matrix factorization(PMF)model.The applicability of the models was compared in the assessment of source apportionment.The results showed that the average contents of Cd,Hg,As,Pb,Cr,Cu,Ni,and Zn in the surface soil were 0.46,0.14,9.66,31.2,127,95.6,76.0,and 158 mg/kg,respectively.Combined with the spatial distribution and correlation analyses,the results of source apportionment were consistent for both the APCSMLR and PMF models.Cd,Hg,As,and Pb were mainly affected by the gangue heap accumulation,with respective contributions of 74.6%,79.4%,69.1%,and 67.2%based on the APCS-MLR model and respective contributions of 69.7%,60.7%,57.4%,and 41.9%based on the PMF model.Ni and Zn were mainly affected by industrial and agricultural activities,while Cr and Cu were mainly affected by natural factors.The results of the source apportionment were approximately consistent between the APCS-MLR and PMF models.The combined application of the two receptor models can make the results of source apportionment more comprehensive,accurate,and reliable.
文摘Lipovtsy coal field mine №4 processed north-western reserves of Lipovtsy field in Primorski Krai (Russia). In 1997, the mine was declared unprofitable and was abandoned by natural flooding with no arrangement of mine water discharge and in 2005 it was fully flooded. The main sources of pollution in the studied area are spoil heaps (mine wastes), underspoil filtering waters and mine waters which are being discharged on the surface after finishing of “hydraulic funnel” artificial support. The study of technogenic landscape of abandoned mine industrial area showed that its morphologic form is dominated by spoil heaps. Soils located near mine waste body differ from benchmark soils by chemical properties and size distribution. The influence of active hydrochemical mine and drainage water flows is the reason of the above-mentioned variation in soil properties. Results showed that, there exist a high correlation ratios between chemical composition of mine waters and water extracts from soil: Between the alkalinity of mine waters and electrical conductivity of soil water extracts (r = 0.73), between mine water iron content and pH of soil water extract (r = −0.56), between the solid residue of mine waters and electrical conductivity of soil water extracts (r = 0.72), between the mine waters calcium content and electrical conductivity of soil water extracts (r = −0.75), between the alkalinity of mine waters and silicon dioxide content of soil water extracts (r = 0.61), between the mineralization of mine waters and chrome content of soil water extracts (r = 0.73).
