Journal of Ecology and Rural Environment ›› 2022, Vol. 38 ›› Issue (12): 1621-1628.doi: 10.19741/j.issn.1673-4831.2021.0571

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Ecological Risk Assessment and Source Apportionment of Heavy Metals in Sediments of a Black-odorous River

FAN Ting-ting1,2, YANG Min1,2, LI Qun1,2, KONG Ling-ya1,2, XIA Fei-yang1,2, PENG Li1,2, DENG Shao-po1,2, ZHANG Sheng-tian1,2   

  1. 1. Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China;
    2. Key Laboratory of Soil Environmental Management and Pollution Control, Ministry of Ecology and Environment, Nanjing 210042, China
  • Received:2021-09-18 Online:2022-12-25 Published:2023-01-03

Abstract: There exist a number of black-odorous water bodies in China, which need to be treated urgently. Source apportionment to heavy metals in sediments is an important guarantee for the remediation of black-odorous rivers. Therefore, this study took a black-odorous river in Jingjiang of Jiangsu Province as an example to conduct ecological risk assessment and source apportionment of heavy metals in sediments, using multivariate statistical analysis and positive definite matrix factor analysis (PMF). The results show that the contents of Pb, Zn, Cu, Hg and Cd in the sediments were accumulated to moderate pollution level, especially for Pb, Hg and Cd, which had heavily ecological risks and should be highly concerned. Multivariate statistical analysis results indicate that the accumulation of heavy metals in sediments was originated from both natural sources represented by soil parent and rock weathering and anthropogenic sources represented by industrial discharge and traffic emission. The anthropogenic source was the main contributor to the accumulation of heavy metals in sediments. PMF results demonstrate the discharge of lead salt enterprise and traffic emission contributed 44.65% and 45.31% to the content of Pb in sediments, respectively; and atmospheric deposition and domestic sewage contributed 35.92% and 44.73% to the content of Hg in sediments. It shows that the multivariate statistical analysis result is relatively consistent with the PMF analysis result.

Key words: sediments of black-odorous river, heavy metal, source apportionment, PCA, PMF model

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