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Groundwater environmental capacity and its evaluation index
Authors:Li Ting Xing  Qiang Wu  Chun He Ye  Nan Ye
Institution:1. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73, East Beijing Road, Nanjing, 210008, People’s Republic of China
2. School of City Development, University of Jinan, Jinan, China
Abstract:At present, anthropogenic contribution of heavy metals far exceeds natural input in some aquatic sediment, but the proportions are difficult to differentiate due to the changes in sediment characters. In this paper, the metal (Al, Fe, K, Mg, Ca, Cr, Cu, Ni, and Zn) concentrations, grain size, and total organic carbon (TOC) content in the surface and core sediments of Nansihu Lake Catchment (the open lake and six inflow rivers) were determined. The chemical speciations of the metals (Al, Fe, Cr, Cu, Ni, and Zn) in the surface sediments were also analyzed. Approaches of factor analysis, normalized enrichment factor (EF) and the new non-residual fractions enrichment factor (KNRF) were used to differentiate the sources of the metals in the sediments, from detrital clastic debris or anthropogenic input, and to quantify the anthropogenic contamination. The results indicate that natural processes were more dominant in concentrating the metals in the surface and core sediments of the open lake. High concentration of Ca and deficiency of other metals in the upper layers of the sediment core were attributed to the input of carbonate minerals in the catchment with increasing human activities since 1980s. High TOC content magnified the deficiency of the metals. Nevertheless, the EF and KNRF both reveal moderate to significant anthropogenic contamination of Cr, Cu, Ni, and Zn in the surface sediments of Laoyun River and the estuary and Cr in the surface sediments of Baima River. The proportion of non-residual fractions (acid soluble, reducible, and oxidizable fractions) of Cr, Cu, Ni, and Zn in the contaminated sediments increased to 37–99% from the background levels less than 30%.
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