Integrated ecological risk assessment of heavy metals in an oil shale mining area after restoration. (15th December 2021)

• Record Type: Journal Article
• Authors: Ma, Tengfei; Luo, Hanjin; Huang, Kaibo; Pan, Yan; Tang, Ting; Tao, Xueqin; Lu, Guining
• Is Part Of: Journal of environmental management. Volume 300(2021)
• Publication Date: 2021-12-15
• Subjects: Heavy metals -- Ecological risk -- Fraction -- APCS-MLR; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2021.113797
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Although the mining area has been restored, the environmental problems caused by years of large-scale oil shale mining are still continuing, coupled with the intensive distribution of the surrounding petrochemical industry, posing a serious threat to the local ecological environment. In this study, we investigated eight heavy metals (Cu, Ni, Pb, Cd, As, Cr, Mn and Zn) contamination and distribution around mining area, evaluated the potential risks of environment, identified the main sources of metal pollution and performed source apportionment. The results showed that the original north and south dumps were seriously polluted, and the CF values were significantly higher than other sampling sites. Ni, Zn and Mn have high coefficients of variation, which may be greatly affected by human factors and especially the waste slag piled up. The concentration of heavy metals in the water was lower than in the soil; soil particles, pH, Eh and acid mine drainage influence the variation of heavy metal concentrations. As and Cd have very high RAC values, and accordingly they were mainly present in the exchangeable and reduced fractions. Mn was exposed to higher ecological risks, followed by Pb, although there were high loads on carbonate bound and oxidizable fractions. APCS-MLL receptor model was used to identify and apportionment three main sources of contamination. The mean contribution rates of industrial activity, atmospheric deposition and mixed sources accounted for 39.77%, 22.24% and 37.99%, respectively. Cluster analysis further classified the metal pollution sources according to the spatial distance of sampling points. Highlights: The former north and south dumps were heavily polluted after ecological restoration. The physical and chemical characteristics of soil and AMD affect the concentration of heavy metals in soil and water. The fraction distribution of heavy metals in soil determines the different ecological effects. APCS-MLR receptor model was used to identify and analyze the sources of heavy. metal pollution.