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Updated: Sep 26, 2025

Characterization and Application of Passive Samplers for Monitoring of Pesticides in Water
Published on: August 3, 2016
A novel passive sampling and sequential extraction approach to investigate desorption kinetics of emerging organic
Xiaowen Ji1, Jonathan K Challis2, Jenna Cantin2
1School of Environment and Sustainability, University of Saskatchewan, Saskatoon, Canada; Global Institute for Water Security, University of Saskatchewan, Saskatoon, Canada.
Abstract:
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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