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| Heavy metal pollution characteristics and source apportionment in overlying deposits of Caohai Lake, Guizhou Province |
| Received:September 15, 2020 |
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| KeyWord:Guizhou Caohai;positive matrix factorization;contaminant severity index;source apportionment;heavy metal;sediment |
| Author Name | Affiliation | | LIN Shao-xia | Guizhou Academy of Testing and Analysis, Guiyang 550016, China
The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Science, Guiyang 550016, China | | LIU Xiao-lan | The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Science, Guiyang 550016, China | | ZHANG Zhuan-ling | School of Chemical&Chemical Engineering, Guizhou University, Guiyang 550025, China | | XIAO Zhi-qiang | Guizhou Academy of Testing and Analysis, Guiyang 550016, China | | ZHANG Qing-hai | College of Food Science, Guizhou Medical University, Guiyang 550025, China |
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| Abstract: |
| Caohai Lake is a typical and complete plateau degraded wetland ecosystem in China, with a high background of heavy metals caused by carbonate soil development. In order to explore the heavy metal pollution levels and sources in sediments of Caohai Lake, the heavy metals in deposits were compared with soil background values, and the heavy metal depositional characteristics were expounded. With reference to the biological effective concentrations, the hazards caused by heavy metals to aquatic organisms were evaluated; the heavy metal pollution sources were explained using principal component analysis(PCA)and positive definite matrix factor analysis(PMF) models. The results show that the average Cu and Cr contents in the deposits do not exceed the background values, and the ratios of Cd, Zn, Hg, As, and Pb contents exceeding background values are 100%, 95.23%, 92.86%, 83.33%, and 66.67%, respectively. Most of the Cu and Cr contents are lower than the effects range-low(ERL)value, while the levels of Cd, Hg, and Zn in some samples were greater than the limits of effects range-median(ERM). Both models have identified 4 pollution sources, where direct surface runoffs account for 13.31%, human activities for 45.13%, geological background sources for 38.32%, and atmospheric sedimentation sources for 3.24%. The pollution sources explained by both models can be well expressed, indicating that the heavy metal sources in the sediments are clear. High attention should be paid to the impacts of human activities when pollution prevention and control measures are formulated. |
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