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Risk-based prioritization of suspects detected in riverine water using complementary chromatographic techniques
Stockholm University, Faculty of Science, Department of Environmental Science.ORCID iD: 0000-0001-9725-3351
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Number of Authors: 102021 (English)In: Water Research, ISSN 0043-1354, E-ISSN 1879-2448, Vol. 204, article id 117612Article in journal (Refereed) Published
Abstract [en]

Surface waters are widely used as drinking water sources and hence their quality needs to be continuously monitored. However, current routine monitoring programs are not comprehensive as they generally cover only a limited number of known pollutants and emerging contaminants. This study presents a risk-based approach combining suspect and non-target screening (NTS) to help extend the coverage of current monitoring schemes. In particular, the coverage of NTS was widened by combining three complementary separations modes: Reverse phase (RP), Hydrophilic interaction liquid chromatography (HILIC) and Mixed-mode chromatography (MMC). Suspect lists used were compiled from databases of relevant substances of very high concern (e.g., SVHCs) and the concentration of detected suspects was evaluated based on ionization efficiency prediction. Results show that suspect candidates can be prioritized based on their potential risk (i.e., hazard and exposure) by combining ionization efficiency-based concentration estimation, in vitro toxicity data or, if not available, structural alerts and QSAR.based toxicity predictions. The acquired information shows that NTS analyses have the potential to complement target analyses, allowing to update and adapt current monitoring programs, ultimately leading to improved monitoring of drinking water sources.

Place, publisher, year, edition, pages
2021. Vol. 204, article id 117612
Keywords [en]
Organic micropollutants, Chemical water quality, Non-target screening, HRMS, Data science, Surface water, Ionization efficiency, Chromatography
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-198663DOI: 10.1016/j.watres.2021.117612ISI: 000697751800001PubMedID: 34536689OAI: oai:DiVA.org:su-198663DiVA, id: diva2:1611835
Available from: 2021-11-16 Created: 2021-11-16 Last updated: 2025-02-07Bibliographically approved

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Been, FredericKruve, AnneliMeekel, NienkeBrunner, Andrea M.

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