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Alteration of bioaccumulation mechanisms of Cu by microalgae in the presence of natural fulvic acids

文献类型: 外文期刊

作者: Shi, Wen 1 ; Fang, Xiaoman 2 ; Wu, Xingfei 1 ; Zhang, Gaoxiang 1 ; Que, Weiyan 1 ; Li, Feili 1 ;

作者机构: 1.Zhejiang Univ Technol, Coll Environm, Hangzhou 310032, Zhejiang, Peoples R China

2.Zhejiang Acad Agr Sci, Inst Qual & Stand Agroprod, State Key Lab Breeding Base Zhejiang Sustainable, Hangzhou 310021, Zhejiang, Peoples R China

关键词: Fulvic acid; Chlorella pyrenoidosa; Bioavailability; Bioadsorption

期刊名称:CHEMOSPHERE ( 影响因子:7.086; 五年影响因子:6.956 )

ISSN: 0045-6535

年卷期: 2018 年 211 卷

页码:

收录情况: SCI

摘要: The impact of natural fulvic acids (FAs) on the toxicity and bioaccumulation of Cu by Chlorella pyrenoidosa was studied. FAs extracted from Taihu Lake were separated into three fractions using dialysis bags: F1 (<500 Da), F2 (500-1000 Da) and F3 (>1000 Da). The results showed that the F3 fraction with a larger molecular weight contained less acidic groups and unsaturated aliphatic structures than F1 and F2, and it showed stronger alleviation of the toxicity of Cu to algae. In the presence of F1 similar to F3, the bioaccumulation curve of Cu in algae intersected with the straight line in the binary system of Cu-algae at approximately 5.3 x 10(-3) . 6.0 x 10(-3) mM of Cu equilibrium concentration, showing an inhibition of bioaccumulation of Cu in lower concentrations but an enhancement in higher Cu concentrations. The ratio of {Cu}(ads)/{Cu}(int) was used to clarify the transformation mechanism on adsorption; the transition interval occurred at a ratio of 3.5-4.4. This ratio indicated a shift from a mechanism of slow trending to equilibrium to a mechanism with rapid increase, which may be due to the bridging action of Cu to form a ternary complex of FA-Cu-algae and the occurrence of multilayer adsorption. The promotion order of F1> F3> F2 was consistent with percentages of the carboxyl group in total acidic functional groups in the FAs. This research is helpful for improving the accuracy of present models for the prediction of heavy metal risks in aqueous environments. (C) 2018 Published by Elsevier Ltd.

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