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Chiral pesticides account for 30% of pesticides. Pesticides are inevitably leached into the groundwater by runoff. At the watershed level, the distribution characteristics of enantiomers in sediments collected from the river network of an agricultural area near the middle and lower reaches of the Yangtze River were tested, and their potential correlations with the physicochemical properties and microbial communities of the sediments were analyzed. The sediment pollution was serious at sites 8 and 9, with their pollution source possibly being agricultural or industrial sewage. Moreover, there were higher cumulative contents of pesticide residues at sites 4, 8, and 9. Specifically, Cycloxaprid was the most detected chiral pesticide in the study area, followed by Dinotefuran and Diclofop-methyl. Additionally, Ethiprole and Difenoconazole had strong enantioselectivity in the study area. Interestingly, the enantiomers of some chiral pesticides, such as Tebuconazole, had completely different distributions at different sites. Pearson correlation analysis showed that sediment catalase and microbial biomass carbon were important factors for enantioselectivity of chiral pesticides. The effect of sediment physicochemical properties on enantioselective distribution was achieved by influencing the microorganisms in the sediment. Furthermore, the enantioselective distribution of Tebuconazole was closely related to the genus Arenimonas. Overall, the enantioselective distribution of most of the chiral pesticides was positively correlated with the prokaryotic microbial community. This study provides empirical support for agricultural non-point source pollution caused by chiral pesticides, and also lays a research foundation for exploring the factors that affect the fate of chiral pesticides in the environment. Copyright © 2022. Published by Elsevier B.V.

Citation

Wenjun Zhang, Tingting Li, Jiayi Tang, Xiaoli Liu, Yuhang Liu, Xiao Zhong. The profiles of chiral pesticides in peri-urban areas near Yangtze River: Enantioselective distribution characteristics and correlations with surface sediments. Journal of environmental sciences (China). 2022 Nov;121:199-210

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PMID: 35654510

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