What works? The influence of changing wastewater treatment type, including tertiary granular activated charcoal, on downstream macroinvertebrate biodiversity over time

This study reviewed the impacts of wastewater on macroinvertebrates over four decades in a UK lowland river. This involved examining changes in chemicals, temperature, flow and macroinvertebrate diversity from the 1970s until 2017 for a wastewater‐dominated river downstream of Swindon in the UK (population about 220,000). When the wastewater treatment process changed from trickling filter to activated sludge in 1991, biological oxygen demand was nearly halved (90%ile 8.1 to 4.6 mg/L), ammonia peaks dropped more than 7‐fold (90%ile 3.9 to 0.53 mg/L) whilst dissolved oxygen climbed consistently above 60% saturation (10%ile went from 49% to 64%) at a sampling point 2 km downstream of the wastewater treatment plant. A sustained increase in the number of macroinvertebrate species was evident from that point. River flow did not change, temperature rose slightly, whilst the major metal concentrations declined steadily over most of the monitoring period. Neither the introduction of phosphate stripping in 1999, nor the use of tertiary granular activated charcoal from 2008 to 2014 had strong positive effects on subsequent macroinvertebrate diversity. That the diversity still had not reached the ideal status by 2016 may be related to the modest habitat quality, agricultural pesticides and the limited recolonization potential in the catchment. The results indicate that urban wastewaters, with their chemical pollutants, are today probably not the biggest threat to the macroinvertebrate diversity of multiple‐stressed lowland rivers in the UK

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-.network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-.network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https:// zenodo.org/communities/norman-.sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox. epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-.network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie Skłodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe

The NORMAN network Special view on biocides as emerging substances

In the field of emerging environmental contaminants, the NORMAN network (www.normannetwork.net) has been active since 2005 as an independent forum of more than 60 leading organisations, facilitating the exchange of information, debate and research collaboration both at the global level and with the European Commission's in-house science services. NORMAN promotes the use of innovative monitoring and assessment tools for identifying the substances of emerging concern most in need of future regulation. The network maintains various databases (e.g. EMPODAT) and has developed a prioritisation scheme specifically designed to deal with “problematic” substances for which knowledge gaps are identified. These tools have been significantly improved in recent years (expansion of EMPODAT database from 1 million to more than 6 million records; a new “ecotox“ module to allow systematic collection of ecotoxicity test data from online databases worldwide, plus existing regulatory EQS/PNEC values)

Prediction of acute toxicity of emerging contaminants on the water flea Daphnia magna by Ant Colony Optimization - Support Vector Machine QSTR models

According to the European REACH Directive, the acute toxicity towards Daphnia magna should be assessed for any industrial chemical with a market volume of more than 1 t/a. Therefore, it is highly recommended to determine the toxicity at a certain confidence level, either experimentally or by applying reliable prediction models. To this end, a large dataset was compiled, with the experimental acute toxicity values (pLC(50)) of 1353 compounds in Daphnia magna after 48 h of exposure. A novel quantitative structure-toxicity relationship (QSTR) model was developed, using Ant Colony Optimization (ACO) to select the most relevant set of molecular descriptors, and Support Vector Machine (SVM) to correlate the selected descriptors with the toxicity data. The proposed model showed high performance (Q(LOO)(2)=0.695, R-fitting(2)=0.920 and R-test(2)=0.831) with low root mean square errors of 0.498 and 0.707 for the training and test set, respectively. It was found that, in addition to hydrophobicity, polarizability and summation of solute-hydrogen bond basicity affected toxicity positively, while minimum atom-type E-state of -OH influenced toxicity values in Daphnia magna inversely. The applicability domain of the proposed model was carefully studied, considering the effect of chemical structure and prediction error in terms of leverage values and standardized residuals. In addition, a new method was proposed to define the chemical space failure for a compound with unknown toxicity to avoid using these prediction results. The resulting ACO-SVM model was successfully applied on an additional evaluation set and the prediction results were found to be very accurate for those compounds that fall inside the defined applicability domain. In fact, compounds commonly found to be difficult to predict, such as quaternary ammonium compounds or organotin compounds were outside the applicability domain, while five representative homologues of LAS (non-ionic surfactants) were, on average, well predicted within one order of magnitude

Occurrence and potential risk of triclosan in freshwaters of São Paulo, Brazil: the need for regulatory actions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Triclosan (TCS) is a broad-spectrum bactericide, highly toxic to algae, which is released into the environment via wastewater effluents. Predicted no-effect concentrations (PNECs) for aquatic biota have been proposed in the literature, varying from 1.4 to 1,550 ng/L, reflecting contradicting protection goals. In this work, six rivers in the state of So Paulo were monitored for TCS and caffeine, a tracer for untreated sewage disposal, over a period of more than 1 year. From 71 samples analyzed, 32 contained TCS at concentrations above the limit of quantification, ranging from 2.2 to 66 ng/L, corresponding to a frequency of exceedance of the lowest PNEC of 86 % (six out of seven sites). No correlation between TCS and caffeine was observed, and one of the reasons for that could be the different use patterns in the local populations. Given the high values found in the investigated rivers, TCS seems to be a strong candidate in the priority list of compounds that should be regulated in Brazil to preserve the aquatic environment.Triclosan (TCS) is a broad-spectrum bactericide, highly toxic to algae, which is released into the environment via wastewater effluents. Predicted no-effect concentrations (PNECs) for aquatic biota have been proposed in the literature, varying from 1.4 to21318501858FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [2012/00303-0]CNPq [573894/2008-6]FAPESP [2008/57808-1]2012/00303-0 ; 2008/57808-1573894/2008-6The authors acknowledge FAPESP (2012/00303-0) and INCTAA (CNPq 573894/2008-6, FAPESP 2008/57808-1) for research funding and thank Martin Kraus for discussion of an earlier version of the manuscript

NORMAN Non-target screening (NTS) prioritisation scheme for ranking thousands of contaminants of emerging concern in effluent wastewater collected from Europe

Prioritisation of contaminants of emerging concern (CECs) remains a challenging task of primary importance for environmental managers and the scientific community as regards the definition of priority actions for pollution prevention & control and for the allocation of resources to address current knowledge gaps. The NORMAN prioritisation scheme combines the traditional risk-based ranking process with the preliminary application of a decision tree, which allows the allocation of substances into six action categories, based on the knowledge gaps and actions needed to fill them, e.g. development of more powerful analytical methods, launch of monitoring campaigns and performing additional ecotoxicity tests. The ranking within each category is then evaluated by occurrence, hazard and risk criteria. The tremendous improvements in high-resolution mass spectrometry and the development of advanced chemometric tools resulted in the update of the NORMAN prioritisation scheme, so that it incorporates the automatic retrieval of the occurrence of CECs through retrospective suspect screening. The objective of the study was to present a) the updated NORMAN prioritization scheme and the modifications introduced and b) the application of the scheme for the prioritization of more than 40,000 CECs in 46 effluent wastewater samples collected from Europe

The NORMAN network's special view on prioritisation of biocides as emerging contaminants

NORMAN promotes the use of innovative monitoring and assessment tools for identifying the substances of emerging concern most in need of future regulation. The network maintains various databases (e.g. EMPODAT) and has developed a prioritisation scheme specifically designed to deal with “problematic” substances for which knowledge gaps are identified. These tools have been significantly improved in recent years (expansion of EMPODAT database from 1 million to more than 6 million records; a new “ecotox“ module to allow systematic collection of ecotoxicity test data from online databases worldwide, plus existing regulatory EQS/PNEC values). The NORMAN list of “frequently discussed” emerging substances contains 862 compounds: among them, 253 are “new“ substances which have been added to the previous list from 2013, whereas 100 substances are now labelled as “former NORMAN” emerging substances. As regards biocides, the list contains 151 active substances of emerging concern that are still in use, under review or formerly used and 12 compounds (e.g., cybutryne, cypermetryne, dichlorvos, etc.) that are still listed for data collection but labelled as “former NORMAN” compounds. The NORMAN prioritisation scheme helps to identify some compounds which evidently need control / mitigation measures (e.g., deltamethrine, terbutryn, imidaclopride, carbendazim, triclosan). Moreover, it is possible to cite substances for which additional monitoring data would be needed,such as e.g., fenoxycarb and tolylfluanid with a potential risk of exceedance of the PNEC. Cyfluthrin and permethrin were identified as substances for which analytical performance should be improved (target: achieve LOQ < PNEC) and N,N-diethyltoluamide and propiconazole appear as substances already sufficiently monitored and for which no evidence of risk was identified. Biocides are active substances emitted into our environment which are definitely to be regarded as substances of emerging concern. EMPODAT confirms that biocides are still insufficiently covered in monitoring programmes: data are available for 70% of the compounds that are also used as plant protection products, but only 15% of the compounds used solely as biocides have monitoring data in the database. Access to the latest information on emerging pollutants, with an overview of benchmark values on their occurrence across Europe would certainly be of a major importance for risk assessors