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Risk analysis on heavy metal contamination in sediments of rivers flowing into Nansi Lake

  • Pollutant distributions and controls in the environment
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Abstract

In order to understand the risk of heavy metals in sediments of the rivers flowing into Nansi Lake, 36 surface sediments were sampled from six rivers and seven heavy metals (Cr, Cu, Ni, Zn, As, Pb, and Cd) were determined. Potential ecological risk index (RI) of the six rivers showed significant differences: Xinxue River, Jiehe River, and Guangfu River were at medium potential risk, whereas the risk of Chengguo River was the lowest. Jiehe River, Xuesha River, and Jiangji River were meeting the medium potential risk at river mouths. Geo-accumulation index (I geo) of the seven heavy metals revealed that the contamination of Cu and Cd was more serious than most other metals in the studied areas, whereas Cr in most sites of our study was not polluted. Moreover, correlation cluster analysis demonstrated that the contamination of Cu, Ni, and Zn in six rivers was mainly caused by local emissions, whereas that of As, Pb, and Cd might come from the external inputs in different forms. Consequently, the contamination of Cu and Cd and the potential risk in Xinxue River, Jiehe River, and Guangfu River as well as the local emissions should be given more attention to safeguard the water quality of Nansi Lake and the East Route Project of South to North Water Transfer.

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Acknowledgments

This study was financially supported by “National Water Special Project” (No. 2012ZX07203-004) and “National Natural Science Foundation of China” (No. 31200426).

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    1. Institute of Environmental Research, Shandong University, Jinan, 250100, China

      Qingqing Cao, Ying Song, Yiran Zhang, Renqing Wang & Jian Liu

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    1. Qingqing Cao
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    2. Ying Song
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    3. Yiran Zhang
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    Correspondence to Jian Liu.

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    Responsible editor: Philippe Garrigues

    Qingqing Cao and Ying Song contributed equally to this work.

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    Cao, Q., Song, Y., Zhang, Y. et al. Risk analysis on heavy metal contamination in sediments of rivers flowing into Nansi Lake. Environ Sci Pollut Res 24, 26910–26918 (2017). https://doi.org/10.1007/s11356-015-4655-8

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