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Use of Passive and Grab Sampling and High-Resolution Mass Spectrometry for Non-Targeted Analysis of Emerging Contaminants and Their Semi-Quantification in Water

Đorđe Tadić 1 Rayana Manasfi 1 Marine Bertrand 2 Andres Sauvêtre 2 Serge Chiron 1 
1 CONTEM - CONTEM: Contaminats Emergents
HSM - Hydrosciences Montpellier
2 ERT - IMT Mines Alès - ERT
IMT - MINES ALES - IMT - MINES ALES, HSM - Hydrosciences Montpellier
Abstract : Different groups of organic micropollutants including pharmaceuticals and pesticides have emerged in the environment in the last years, resulting in a rise in environmental and human health risks. In order to face up and evaluate these risks, there is an increasing need to assess their occurrence in the environment. Therefore, many studies in the past couple of decades were focused on the improvements in organic micropollutants’ extraction efficiency from the different environmental matrices, as well as their mass spectrometry detection parameters and acquisition modes. This paper presents different sampling methodologies and high-resolution mass spectrometry-based non-target screening workflows for the identification of pharmaceuticals, pesticides, and their transformation products in different kinds of water (domestic wastewater and river water). Identification confidence was increased including retention time prediction in the workflow. The applied methodology, using a passive sampling technique, allowed for the identification of 85 and 47 contaminants in the wastewater effluent and river water, respectively. Finally, contaminants’ prioritization was performed through semi-quantification in grab samples as a fundamental step for monitoring schemes.
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Submitted on : Wednesday, May 25, 2022 - 4:48:48 PM
Last modification on : Monday, June 13, 2022 - 2:24:53 PM

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Đorđe Tadić, Rayana Manasfi, Marine Bertrand, Andres Sauvêtre, Serge Chiron. Use of Passive and Grab Sampling and High-Resolution Mass Spectrometry for Non-Targeted Analysis of Emerging Contaminants and Their Semi-Quantification in Water. Molecules, MDPI, 2022, 27 (10), pp.3167. ⟨10.3390/molecules27103167⟩. ⟨hal-03678973⟩

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