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Beyond target chemicals: updating the NORMAN prioritisation scheme to support the EU chemicals strategy with semi-quantitative suspect/non-target screening data
INERIS, Rue Jaques Taffanel, Parc Technologique ALATA, Verneuil-en-Halatte, France.
Environmental Institute, Okružná 784/42, Koš, Slovakia; Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, Athens, Greece.
Environmental Institute, Okružná 784/42, Koš, Slovakia; RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, Brno, Czech Republic.
Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, Belvaux, Luxembourg.
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2024 (English)In: Environmental Sciences Europe, ISSN 2190-4707, E-ISSN 2190-4715, Vol. 36, no 1, article id 113Article in journal (Refereed) Published
Abstract [en]

Background: Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions.

Results: As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes.

Conclusions: This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools. Graphical Abstract: (Figure presented.)

Place, publisher, year, edition, pages
Springer Nature, 2024. Vol. 36, no 1, article id 113
Keywords [en]
Chemical prioritisation, Contaminants of emerging concern, Environmental risk assessment, NORMAN Database System, Retrospective suspect screening
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:umu:diva-226961DOI: 10.1186/s12302-024-00936-3Scopus ID: 2-s2.0-85195904334OAI: oai:DiVA.org:umu-226961DiVA, id: diva2:1876386
Funder
EU, Horizon 2020, 859891Available from: 2024-06-24 Created: 2024-06-24 Last updated: 2024-06-24Bibliographically approved

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Haglund, Peter

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