A novel passive sampling and sequential extraction approach to investigate desorption kinetics of emerging organic contaminants at the sediment−water interface

沉积物 化学 环境化学 解吸 污染物 沉积物-水界面 污染 薄膜中的扩散梯度 地表水 分数(化学) 水污染 吸附 环境科学 色谱法 地质学 环境工程 生态学 有机化学 古生物学 生物
作者
Xiaowen Ji,Jonathan K. Challis,Jenna Cantin,Ana Sharelys Cardenas Perez,Yufeng Gong,John P. Giesy,Markus Brinkmann
出处
期刊:Water Research [Elsevier]
卷期号:217: 118455-118455 被引量:7
标识
DOI:10.1016/j.watres.2022.118455
摘要

Forms of organic contaminants is an important driver of bioavailable fraction and desorption kinetics of pollutants binding to sediments. To determine fluxes and resupply of nine environmentally-relevant antipsychotic drugs, which are emerging pollutants that can have adverse effects on aquatic organisms, interface passive samplers of diffusive gradients in thin films (DGT) were deployed for 21 days, in situ at the sediment-water interface in submerged sandy riverbank sediments. At each deployment time, samples of sediment were collected and subjected to consecutive extraction of pore water, as well as rapidly-desorbing (labile), stable-desorbing, and bound residue fractions. Concentrations of antipsychotic drugs decreased with sediment depth with the greatest concentrations observed in the top 2 cm. Positive fluxes of antipsychotic drugs were observed from sediment to surface water. The dynamic fraction transfer model indicated that the labile fraction can be resupplied with a lag time (> 21 d). When results were further interpreted using the DGT-induced fluxes in soils and sediments (DIFS) model, partial resupply of antipsychotic drugs from sediment particles to porewater was demonstrated. Desorption occurred within the entirety of the observed 15 cm depth of sediment. Fastest rates of resupply were found for carbamazepine and lamotrigine. Size of the labile pool estimated by the DIFS model did not fully explain the observed resupply, while a first-order three-compartment kinetic model for the fast-desorbing fraction can be used to supplement DIFS predictions with estimations of labile pool size.
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