Beyond target chemicals: updating the NORMAN prioritisation scheme to support the EU chemicals strategy with semi-quantitative suspect/non-target screening data

IF 6 3区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Environmental Sciences Europe Pub Date : 2024-06-12 DOI:10.1186/s12302-024-00936-3
Valeria Dulio, Nikiforos Alygizakis, Kelsey Ng, Emma L. Schymanski, Sandrine Andres, Katrin Vorkamp, Juliane Hollender, Saskia Finckh, Reza Aalizadeh, Lutz Ahrens, Elodie Bouhoulle, Ľuboš Čirka, Anja Derksen, Geneviève Deviller, Anja Duffek, Mar Esperanza, Stellan Fischer, Qiuguo Fu, Pablo Gago-Ferrero, Peter Haglund, Marion Junghans, Stefan A. E. Kools, Jan Koschorreck, Benjamin Lopez, Miren Lopez de Alda, Giuseppe Mascolo, Cécile Miège, Leonard Osté, Simon O’Toole, Pawel Rostkowski, Tobias Schulze, Kerry Sims, Laetitia Six, Jaroslav Slobodnik, Pierre-François Staub, Gerard Stroomberg, Nikolaos S. Thomaidis, Anne Togola, Giorgio Tomasi, Peter C. von der Ohe
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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

Abstract Image

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目标化学品之外:更新 NORMAN 优先排序计划,利用半定量可疑/非目标筛选数据支持欧盟化学品战略
背景对环境管理者和决策者来说,化学污染物的优先排序是一项重大挑战,这对于将有限的监测和减排资源集中用于最相关的化学物质至关重要。本研究将最初的 NORMAN 优先排序方案扩展到目标化学品之外,介绍了从回顾性疑似筛选中获得的半定量数据的整合情况,以及现有暴露和风险指标的扩展情况。该方案利用从 NORMAN 数据库系统(NDS)中自动检索的数据,包括优先排序的候选物质、目标和可疑筛选数据、生态毒理效应数据、物理化学数据和其他属性。使用目标和可疑筛选监测数据的两个互补工作流程首先将物质分为六个行动类别,然后使用暴露、危害和风险指标对物质进行排序。然后,"目标 "和 "疑似筛选 "工作流程得出的结果可以合并为多种证据,为监管和研究行动的决策提供支持。结果 作为概念验证,新方案被应用于目标和疑似筛选数据的组合数据集。为此,在 84 个污水废水样本(共计 1,100 万个数据点)中对 NDS 中的 65,000 种物质进行了回顾性筛选,其中 2579 种物质得到了目标废水监测数据的支持。最终的优先排序结果确定 677 种物质为需要采取进一步行动的高优先级物质,7455 种物质为中等优先级物质,326 种物质的行动优先级可能较低。在剩余的物质中,约有 37,000 种物质应被视为中度优先且具有不确定性,而 19,000 种物质则由于目标监测信息不足和可疑筛选识别的不确定性而无法得出结论。通过目标分析和疑似筛选确定的优先级类别之间的一致性很高。疑似筛选是目标分析的重要补充方法,有助于对当前监测计划中调查不足的数千种物质进行优先排序。它可适用于不同的环境区划,并可支持监管义务,包括确定江河流域和海洋环境中的特定污染物,以及确认建模工具预测的环境出现水平。
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来源期刊
Environmental Sciences Europe
Environmental Sciences Europe Environmental Science-Pollution
CiteScore
11.20
自引率
1.70%
发文量
110
审稿时长
13 weeks
期刊介绍: ESEU is an international journal, focusing primarily on Europe, with a broad scope covering all aspects of environmental sciences, including the main topic regulation. ESEU will discuss the entanglement between environmental sciences and regulation because, in recent years, there have been misunderstandings and even disagreement between stakeholders in these two areas. ESEU will help to improve the comprehension of issues between environmental sciences and regulation. ESEU will be an outlet from the German-speaking (DACH) countries to Europe and an inlet from Europe to the DACH countries regarding environmental sciences and regulation. Moreover, ESEU will facilitate the exchange of ideas and interaction between Europe and the DACH countries regarding environmental regulatory issues. Although Europe is at the center of ESEU, the journal will not exclude the rest of the world, because regulatory issues pertaining to environmental sciences can be fully seen only from a global perspective.
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