Beyond target chemicals: updating the NORMAN prioritisation scheme to support the EU chemicals strategy with semi-quantitative suspect/non-target screening data
Authors: Dulio Valeria , Alygizakis Nikiforos , Ng Kelsey , Schymanski Emma L. , Andres Sandrine , Vorkamp Katrin , Hollender Juliane , Finckh Saskia , Aalizadeh Reza , Ahrens Lutz , Bouhoulle Elodie , Čirka Ľuboš , Derksen Anja , Deviller Geneviève , Duffek Anja , Esperanza Mar , Fischer Stellan , Fu Qiuguo , Gago-Ferrero Pablo , Haglund Peter , Junghans Marion , Kools Stefan A. E. , Koschorreck Jan , Lopez Benjamin , Lopez de Alda Miren , Mascolo Giuseppe , Miège Cécile , Osté Leonard , O’Toole Simon , Rostkowski Pawel , Schulze Tobias , Sims Kerry , Six Laetitia , Slobodnik Jaroslav , Staub Pierre-François , Stroomberg Gerard , Thomaidis Nikolaos S. , Togola Anne , Tomasi Giorgio , von der Ohe Peter C. 
Published: June 2024

Abstract
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