Journal
CHEMOSPHERE
Volume 196, Issue -, Pages 45-52Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2017.12.135
Keywords
Metals; Surface water; Sediment; Wild fish; Risk assessment
Categories
Funding
- Natural Science Foundation of China [21607108]
- Tianjin agricultural science and technology achievements transformation and promotion project [201304150]
- Tianjin municipal bureau of fisheries youth science and technology innovation project [j - 2014-08]
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To evaluate the distribution patterns, degrees of contamination, and ecological risks of 15 metals (Cd, Pb, Sb, Sn, Tl, Mo, Cr, Mn, Ni, Cu, Zn, As, V, Co, and Se), a total of 26 paired water and sediment samples as well as 7 fish samples were collected in Jinjiang River, Chengdu, China. The metal forms of the sediments were analyzed using BCR three-step sequential extraction procedures, and the metal contents of the samples were determined by ICP-MS. Four environmental indices including the geo-accumulation index, bioconcentration factor, biota-sediment accumulation factor, and the potential ecological risk index were calculated to evaluate pollution level and eco-risk of the metals. Based on the current study, Mn and Cd were preferentially associated with the exchangeable fraction, Cu and Pb were primarily in the reducible fraction, while the other metals were mainly found in the residual fraction. With the exception of Sb and Mo, the BCF values of the metals were greater than 100, especially for Zn, which had the highest BCF value (74200), suggesting that these metals had higher bioconcentration ability. Based on the geo-accumulation index and the potential ecological risk index (R-I) calculated in this study, the middle reaches of Jinjiang River present moderate to severe metal pollution, and moderate to considerable potential ecological risk, especially for the risk of Cd, which should be paid more attention in the future. While non-pollution level and low ecological risk of the metals were found in the upper and lower reaches of Jinjiang River. (C) 2017 Elsevier Ltd. All rights reserved.
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