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Zhang Q, Song N, Xu H. Analysis strategy of contamination source using chemical fingerprint information based on GC-HRMS: A case study of landfill leachate. WATER RESEARCH 2024; 273:123067. [PMID: 39742632 DOI: 10.1016/j.watres.2024.123067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 12/03/2024] [Accepted: 12/28/2024] [Indexed: 01/03/2025]
Abstract
With the increasing prevalence of emerging contaminants (ECs) in the environment, gaining a deeper understanding of the chemical information pertaining to the contamination source is a crucial step toward effective prevention and control of these ECs. This study presents a novel strategy for analyzing the chemical information of contamination sources using gas chromatography-high resolution mass spectrometry (GC-HRMS) and demonstrates it on landfill leachate, a common and representative environmental contamination source. Initially, a non-targeted screening approach using HRMS was used to characterize a total of 5344 organic compounds with identification confidence levels 1 and 2 in 14 landfill leachate samples. Leveraging this as a base data set, the similarity analysis was first performed, and the classification fingerprints exhibited a pronounced level of similarity. Second, 169 characteristic marker contaminants with important and significant differences were identified in the 3 groups of landfill leachate with different solid waste compositions (mostly kitchen waste, mostly plastic & daily chemical product waste, and proportion average) by difference analysis. Finally, 101 hazardous chemicals (HCs) were screened in the data set. The results demonstrated that a class of contamination source exhibited certain common characteristics, while different groups of samples had their own distinct contamination signatures. This work offers a unique perspective on the interpretation of chemical information from contamination sources, aiming to provide a valuable reference for environmental pollution management.
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Affiliation(s)
- Qian Zhang
- College of Environment, Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China.; Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, PR China.; Suzhou Research Institute, Hohai University, Suzhou 215100, PR China
| | - Ninghui Song
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, PR China..
| | - Hang Xu
- College of Environment, Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China.; Suzhou Research Institute, Hohai University, Suzhou 215100, PR China..
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2
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Samanipour S, Barron LP, van Herwerden D, Praetorius A, Thomas KV, O’Brien JW. Exploring the Chemical Space of the Exposome: How Far Have We Gone? JACS AU 2024; 4:2412-2425. [PMID: 39055136 PMCID: PMC11267556 DOI: 10.1021/jacsau.4c00220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 05/29/2024] [Accepted: 05/31/2024] [Indexed: 07/27/2024]
Abstract
Around two-thirds of chronic human disease can not be explained by genetics alone. The Lancet Commission on Pollution and Health estimates that 16% of global premature deaths are linked to pollution. Additionally, it is now thought that humankind has surpassed the safe planetary operating space for introducing human-made chemicals into the Earth System. Direct and indirect exposure to a myriad of chemicals, known and unknown, poses a significant threat to biodiversity and human health, from vaccine efficacy to the rise of antimicrobial resistance as well as autoimmune diseases and mental health disorders. The exposome chemical space remains largely uncharted due to the sheer number of possible chemical structures, estimated at over 1060 unique forms. Conventional methods have cataloged only a fraction of the exposome, overlooking transformation products and often yielding uncertain results. In this Perspective, we have reviewed the latest efforts in mapping the exposome chemical space and its subspaces. We also provide our view on how the integration of data-driven approaches might be able to bridge the identified gaps.
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Affiliation(s)
- Saer Samanipour
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- UvA
Data Science Center, University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Leon Patrick Barron
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- MRC
Centre for Environment and Health, Environmental Research Group, School
of Public Health, Faculty of Medicine, Imperial
College London, London W12 0BZ, United Kingdom
| | - Denice van Herwerden
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
| | - Antonia Praetorius
- Institute
for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
| | - Kevin V. Thomas
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Jake William O’Brien
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
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3
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Wang W, Cao G, Zhang J, Chang W, Sang Y, Cai Z. Fragmentation Pattern-Based Screening Strategy Combining Diagnostic Ion and Neutral Loss Uncovered Novel para-Phenylenediamine Quinone Contaminants in the Environment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5921-5931. [PMID: 38512777 PMCID: PMC10993393 DOI: 10.1021/acs.est.4c00027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/07/2024] [Accepted: 03/07/2024] [Indexed: 03/23/2024]
Abstract
Identifying transformed emerging contaminants in complex environmental compartments is a challenging but meaningful task. Substituted para-phenylenediamine quinones (PPD-quinones) are emerging contaminants originating from rubber antioxidants and have been proven to be toxic to the aquatic species, especially salmonids. The emergence of multiple PPD-quinones in various environmental matrices and evidence of their specific hazards underscore the need to understand their environmental occurrences. Here, we introduce a fragmentation pattern-based nontargeted screening strategy combining full MS/All ion fragmentation/neutral loss-ddMS2 scans to identify potential unknown PPD-quinones in different environmental matrices. Using diagnostic fragments of m/z 170.0600, 139.0502, and characteristic neutral losses of 199.0633, 138.0429 Da, six known and three novel PPD-quinones were recognized in air particulates, surface soil, and tire tissue. Their specific structures were confirmed, and their environmental concentration and composition profiles were clarified with self-synthesized standards. N-(1-methylheptyl)-N'-phenyl-1,4-benzenediamine quinone (8PPD-Q) and N,N'-di(1,3-dimethylbutyl)-p-phenylenediamine quinone (66PD-Q) were identified and quantified for the first time, with their median concentrations found to be 0.02-0.21 μg·g-1 in tire tissue, 0.40-2.76 pg·m-3 in air particles, and 0.23-1.02 ng·g-1 in surface soil. This work provides new evidence for the presence of unknown PPD-quinones in the environment, showcasing a potential strategy for screening emerging transformed contaminants in the environment.
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Affiliation(s)
- Wei Wang
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Guodong Cao
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Jing Zhang
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Weixia Chang
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Yuecheng Sang
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Zongwei Cai
- State Key Laboratory of Environmental
and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
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4
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Tkalec Ž, Antignac JP, Bandow N, Béen FM, Belova L, Bessems J, Le Bizec B, Brack W, Cano-Sancho G, Chaker J, Covaci A, Creusot N, David A, Debrauwer L, Dervilly G, Duca RC, Fessard V, Grimalt JO, Guerin T, Habchi B, Hecht H, Hollender J, Jamin EL, Klánová J, Kosjek T, Krauss M, Lamoree M, Lavison-Bompard G, Meijer J, Moeller R, Mol H, Mompelat S, Van Nieuwenhuyse A, Oberacher H, Parinet J, Van Poucke C, Roškar R, Togola A, Trontelj J, Price EJ. Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment. ENVIRONMENT INTERNATIONAL 2024; 186:108585. [PMID: 38521044 DOI: 10.1016/j.envint.2024.108585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 03/25/2024]
Abstract
The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.
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Affiliation(s)
- Žiga Tkalec
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic; Jožef Stefan Institute, Department of Environmental Sciences, Ljubljana, Slovenia.
| | | | - Nicole Bandow
- German Environment Agency, Laboratory for Water Analysis, Colditzstraße 34, 12099 Berlin, Germany.
| | - Frederic M Béen
- Vrije Universiteit Amsterdam, Amsterdam Institute for Life and Environment (A-LIFE), Section Chemistry for Environment and Health, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; KWR Water Research Institute, Nieuwegein, The Netherlands.
| | - Lidia Belova
- Toxicological Center, University of Antwerp, 2610 Wilrijk, Belgium.
| | - Jos Bessems
- Flemish Institute for Technological Research (VITO), Mol, Belgium.
| | | | - Werner Brack
- Helmholtz Centre for Environmental Research GmbH - UFZ, Department of Effect-Directed Analysis, Permoserstraße 15, 04318 Leipzig, Germany; Goethe University Frankfurt, Department of Evolutionary Ecology and Environmental Toxicology, Max-von-Laue-Strasse 13, 60438 Frankfurt, Germany.
| | | | - Jade Chaker
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France.
| | - Adrian Covaci
- Toxicological Center, University of Antwerp, 2610 Wilrijk, Belgium.
| | - Nicolas Creusot
- INRAE, French National Research Institute For Agriculture, Food & Environment, UR1454 EABX, Bordeaux Metabolome, MetaboHub, Gazinet Cestas, France.
| | - Arthur David
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France.
| | - Laurent Debrauwer
- Toxalim (Research Centre in Food Toxicology), INRAE UMR 1331, ENVT, INP-Purpan, Paul Sabatier University (UPS), Toulouse, France.
| | | | - Radu Corneliu Duca
- Unit Environmental Hygiene and Human Biological Monitoring, Department of Health Protection, Laboratoire National de Santé (LNS), 1 Rue Louis Rech, L-3555 Dudelange, Luxembourg; Environment and Health, Department of Public Health and Primary Care, Katholieke Universiteit of Leuven (KU Leuven), 3000 Leuven, Belgium.
| | - Valérie Fessard
- ANSES, French Agency for Food, Environmental and Occupational Health & Safety, Laboratory of Fougères, Toxicology of Contaminants Unit, 35306 Fougères, France.
| | - Joan O Grimalt
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Catalonia, Spain.
| | - Thierry Guerin
- ANSES, French Agency for Food, Environmental and Occupational Health & Safety, Strategy and Programs Department, F-94701 Maisons-Alfort, France.
| | - Baninia Habchi
- INRS, Département Toxicologie et Biométrologie Laboratoire Biométrologie 1, rue du Morvan - CS 60027 - 54519, Vandoeuvre Cedex, France.
| | - Helge Hecht
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic.
| | - Juliane Hollender
- Swiss Federal Institute of Aquatic Science and Technology - Eawag, 8600 Dübendorf, Switzerland; Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, 8092 Zürich, Switzerland.
| | - Emilien L Jamin
- Toxalim (Research Centre in Food Toxicology), INRAE UMR 1331, ENVT, INP-Purpan, Paul Sabatier University (UPS), Toulouse, France.
| | - Jana Klánová
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic.
| | - Tina Kosjek
- Jožef Stefan Institute, Department of Environmental Sciences, Ljubljana, Slovenia.
| | - Martin Krauss
- Helmholtz Centre for Environmental Research GmbH - UFZ, Department of Effect-Directed Analysis, Permoserstraße 15, 04318 Leipzig, Germany.
| | - Marja Lamoree
- Vrije Universiteit Amsterdam, Amsterdam Institute for Life and Environment (A-LIFE), Section Chemistry for Environment and Health, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
| | - Gwenaelle Lavison-Bompard
- ANSES, French Agency for Food, Environmental and Occupational Health & Safety, Laboratory for Food Safety, Pesticides and Marine Biotoxins Unit, F-94701 Maisons-Alfort, France.
| | - Jeroen Meijer
- Vrije Universiteit Amsterdam, Amsterdam Institute for Life and Environment (A-LIFE), Section Chemistry for Environment and Health, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
| | - Ruth Moeller
- Unit Medical Expertise and Data Intelligence, Department of Health Protection, Laboratoire National de Santé (LNS), 1 Rue Louis Rech, L-3555 Dudelange, Luxembourg.
| | - Hans Mol
- Wageningen Food Safety Research - Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB, Wageningen, The Netherlands.
| | - Sophie Mompelat
- ANSES, French Agency for Food, Environmental and Occupational Health & Safety, Laboratory of Fougères, Toxicology of Contaminants Unit, 35306 Fougères, France.
| | - An Van Nieuwenhuyse
- Environment and Health, Department of Public Health and Primary Care, Katholieke Universiteit of Leuven (KU Leuven), 3000 Leuven, Belgium; Department of Health Protection, Laboratoire National de Santé (LNS), 1 Rue Louis Rech, L-3555 Dudelange, Luxembourg.
| | - Herbert Oberacher
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Insbruck, 6020 Innsbruck, Austria.
| | - Julien Parinet
- ANSES, French Agency for Food, Environmental and Occupational Health & Safety, Laboratory for Food Safety, Pesticides and Marine Biotoxins Unit, F-94701 Maisons-Alfort, France.
| | - Christof Van Poucke
- Flanders Research Institute for Agriculture, Fisheries And Food (ILVO), Brusselsesteenweg 370, 9090 Melle, Belgium.
| | - Robert Roškar
- University of Ljubljana, Faculty of Pharmacy, Slovenia.
| | - Anne Togola
- BRGM, 3 avenue Claude Guillemin, 45060 Orléans, France.
| | | | - Elliott J Price
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno, Czech Republic.
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5
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Vosough M, Schmidt TC, Renner G. Non-target screening in water analysis: recent trends of data evaluation, quality assurance, and their future perspectives. Anal Bioanal Chem 2024; 416:2125-2136. [PMID: 38300263 PMCID: PMC10951028 DOI: 10.1007/s00216-024-05153-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/12/2024] [Accepted: 01/12/2024] [Indexed: 02/02/2024]
Abstract
This trend article provides an overview of recent advancements in Non-Target Screening (NTS) for water quality assessment, focusing on new methods in data evaluation, qualification, quantification, and quality assurance (QA/QC). It highlights the evolution in NTS data processing, where open-source platforms address challenges in result comparability and data complexity. Advanced chemometrics and machine learning (ML) are pivotal for trend identification and correlation analysis, with a growing emphasis on automated workflows and robust classification models. The article also discusses the rigorous QA/QC measures essential in NTS, such as internal standards, batch effect monitoring, and matrix effect assessment. It examines the progress in quantitative NTS (qNTS), noting advancements in ionization efficiency-based quantification and predictive modeling despite challenges in sample variability and analytical standards. Selected studies illustrate NTS's role in water analysis, combining high-resolution mass spectrometry with chromatographic techniques for enhanced chemical exposure assessment. The article addresses chemical identification and prioritization challenges, highlighting the integration of database searches and computational tools for efficiency. Finally, the article outlines the future research needs in NTS, including establishing comprehensive guidelines, improving QA/QC measures, and reporting results. It underscores the potential to integrate multivariate chemometrics, AI/ML tools, and multi-way methods into NTS workflows and combine various data sources to understand ecosystem health and protection comprehensively.
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Affiliation(s)
- Maryam Vosough
- Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, North Rhine-Westphalia, Germany.
- Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 2, Essen, 45141, North Rhine-Westphalia, Germany.
- Department of Clean Technologies, Chemistry and Chemical Engineering Research Center of Iran, P.O. Box 14335-186, Tehran, Iran.
| | - Torsten C Schmidt
- Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, North Rhine-Westphalia, Germany
- Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 2, Essen, 45141, North Rhine-Westphalia, Germany
- IWW Water Centre, Moritzstr. 26, Mülheim an der Ruhr, 45476, North Rhine-Westphalia, Germany
| | - Gerrit Renner
- Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, North Rhine-Westphalia, Germany.
- Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 2, Essen, 45141, North Rhine-Westphalia, Germany.
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6
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Schulze B, Heffernan AL, Gomez Ramos MJ, Thomas KV, Kaserzon SL. Influence of extraction windows for data-independent acquisition on feature annotation during suspect screening. CHEMOSPHERE 2024; 349:140697. [PMID: 37972864 DOI: 10.1016/j.chemosphere.2023.140697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/08/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
Non-target analysis (NTA) using high-resolution mass spectrometry is becoming a useful approach to screen for suspect and unknown chemicals. For comprehensive analyses, data-independent acquisition (DIA), like Sequential Windowed Acquisition of all THeoretical Mass Spectra (SWATH-MS) on Sciex instruments, is necessary, usually followed by library matching for feature annotation. The choice of parameters, such as acquisition window number and size, may influence the comprehensiveness of the suspect features detected. The goal of this study was to assess how mass spectrometric DIA settings may influence the ability to obtain confident annotations and identifications of features in environmental (river water, passive sample extract (PSE)), wastewater (unpreserved and acidified) and biological (urine) sample matrices. Each matrix was analysed using 11 different MS methods, with 5-15 variable size acquisition windows. True positive (TP) annotation (i.e., matching experimental and library spectra) rates were constant for PSE (40%) and highest for urine (18%), wastewater (34% and 36%, unpreserved and acidified, respectively) and river water (8%) when using higher numbers of windows (15). The number of annotated features was highest for PSE (12%) and urine (8.5%) when using more acquisition windows (9 and 14, respectively). Less complex matrices (based on average total ion chromatogram intensities) like river water, unpreserved and acidified wastewater have higher annotation rates (7.5%, 8% and 13.2%, respectively) when using less acquisition windows (5-6), indicating matrix dependency of optimum settings. Library scores varied widely for correct (scores between 6 and 100) as well as incorrect annotations (scores between 2 and 100), making it hard to define specific ideal cut-off values. Results highlight the need for properly curated libraries and careful optimization of SWATH-MS and other DIA methods for each individual matrix, finding the best ratio of total annotations to true positive, (i.e., correct) annotations to achieve best NTA results.
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Affiliation(s)
- Bastian Schulze
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia.
| | - Amy L Heffernan
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
| | - Maria Jose Gomez Ramos
- Chemistry and Physics Department, University of Almeria, Agrifood Campus of International Excellence (ceiA3), 04120, Almería, Spain
| | - Kevin V Thomas
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
| | - Sarit L Kaserzon
- The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia
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7
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Liu H, Wang R, Zhao B, Xie D. Assessment for the data processing performance of non-target screening analysis based on high-resolution mass spectrometry. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:167967. [PMID: 37866614 DOI: 10.1016/j.scitotenv.2023.167967] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 10/24/2023]
Abstract
Non-target screening (NTS) based on high-resolution mass spectrometry (HRMS) is considered one of the most comprehensive approaches for the characterization of contaminants of emerging concern (CECs) in a complex sample. This study evaluated the performance of NTS in aquatic environments (including peak picking, database matching, product identification, semi-quantification, etc.) based on a self-developed data processing method using 38 glucocorticoids as testing compounds. Data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes were used for obtaining the MS2 information for in-house or online database matching. Results indicate that DDA and DIA mode have their own advantages and can complement each other. The quantification method based on LC-HRMS has shown the potential to provide a fast and acceptable result for testing compounds. Finally, a matrix spike analysis was carried out on 66 CECs across different usage categories in wastewater, surface water, and seawater matrix samples, together with a case study performed for characterizing the whole contaminants in a Pearl River sample, to better illustrate the application potential of NTS workflow and the credibility of NTS outcomes. This study provides a foundation for novel applications of HRMS data by NTS workflow to identify and quantify CECs in complex systems.
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Affiliation(s)
- He Liu
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Rui Wang
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Bo Zhao
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China.
| | - Danping Xie
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China.
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8
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Creusot N, Huba K, Borel C, Ferrari BJD, Chèvre N, Hollender J. Identification of polar organic chemicals in the aquatic foodweb: Combining high-resolution mass spectrometry and trend analysis. ENVIRONMENT INTERNATIONAL 2024; 183:108403. [PMID: 38224651 DOI: 10.1016/j.envint.2023.108403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/30/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024]
Abstract
Environmental risk assessment of chemical contaminants requires prioritizing of substances taken up by biota as it is a starting point for potential adverse effects. Although knowledge about the occurrence of known chemical pollutants in aquatic organisms has significantly improved during the last decade, there is still a poor understanding for a broad range of more polar compounds. To tackle this issue, we proposed an approach that identifies bioaccumulative and biomagnifiable polar chemicals using liquid chromatography coupled with electrospray ionization to high resolution tandem mass spectrometry (LC-HRMS/MS) and combine it with trend analysis using hierarchical clustering. As a proof-of-concept, this approach was implemented on various organisms and compartments (sediment, litter leaves, periphytic biofilm, invertebrates and fish) collected from a small urban river. HRMS/MS data measured via data-independent acquisition mode were retrospectively analysed using two analytical strategies: (1) retrospective target and (2) suspect/non-target screening. In the retrospective target analysis, 56 of 361 substances spanning a broad range of contaminant classes were detected (i.e. 26 in fish, 18 in macroinvertebrates, 28 in leaves, 29 in periphyton and 32 in sediments, with only 7 common to all compartments), among which 49 could be quantified using reference standards. The suspect screening approach based on two suspect lists (in-house, Norman SusDat) led to the confirmation of 5 compounds with standards (three xenobiotics at level 1 and two lipids at level 2) and tentative identification of seven industrial or natural chemicals at level 2 and 3 through a mass spectra library match. Overall, this proof-of-concept study provided a more comprehensive picture of the exposure of biota to emerging contaminants (i.e., the internal chemical exposome) and potential bioaccumulation or biomagnification of polar compounds along the trophic chain.
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Affiliation(s)
- Nicolas Creusot
- Swiss Federal Institute of Aquatic Science and Technology (Eawag), 8600 Dübendorf, Switzerland; INRAE, EABX, Bordeaux Metabolome, MetaboHub, 50 avenue de Verdun, 33612 Gazinet-Cestas, France.
| | - Kristina Huba
- Swiss Federal Institute of Aquatic Science and Technology (Eawag), 8600 Dübendorf, Switzerland; Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, 8092 Zürich, Switzerland
| | | | - Benoit J D Ferrari
- Swiss Centre for Applied Ecotoxicology (Ecotox Centre), Lausanne/Dübendorf, Switzerland
| | | | - Juliane Hollender
- Swiss Federal Institute of Aquatic Science and Technology (Eawag), 8600 Dübendorf, Switzerland; Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, 8092 Zürich, Switzerland
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9
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Dürig W, Lindblad S, Golovko O, Gkotsis G, Aalizadeh R, Nika MC, Thomaidis N, Alygizakis NA, Plassmann M, Haglund P, Fu Q, Hollender J, Chaker J, David A, Kunkel U, Macherius A, Belova L, Poma G, Preud'Homme H, Munschy C, Aminot Y, Jaeger C, Lisec J, Hansen M, Vorkamp K, Zhu L, Cappelli F, Roscioli C, Valsecchi S, Bagnati R, González B, Prieto A, Zuloaga O, Gil-Solsona R, Gago-Ferrero P, Rodriguez-Mozaz S, Budzinski H, Devier MH, Dierkes G, Boulard L, Jacobs G, Voorspoels S, Rüdel H, Ahrens L. What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS. ENVIRONMENT INTERNATIONAL 2023; 181:108288. [PMID: 37918065 DOI: 10.1016/j.envint.2023.108288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/04/2023] [Accepted: 10/23/2023] [Indexed: 11/04/2023]
Abstract
A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69 % of spiked compounds using LC-HRMS and 20-60 % of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants' own suspect lists led to putative identification of on average ∼145 and ∼20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ∼42 and ∼56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values from -9.9 to 16 and mass-to-charge ratios (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.
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Affiliation(s)
- Wiebke Dürig
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, 75007 Uppsala, Sweden.
| | - Sofia Lindblad
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, 75007 Uppsala, Sweden.
| | - Oksana Golovko
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, 75007 Uppsala, Sweden.
| | - Georgios Gkotsis
- Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece.
| | - Reza Aalizadeh
- Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece.
| | - Maria-Christina Nika
- Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece.
| | - Nikolaos Thomaidis
- Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece.
| | - Nikiforos A Alygizakis
- Department of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece; Environmental Institute, Okružná 784/42, 97241 Koš, Slovakia.
| | - Merle Plassmann
- Department of Environmental Science, Stockholm University, 10691 Stockholm, Sweden.
| | - Peter Haglund
- Department of Chemistry, Chemical Biological Centre (KBC), Umeå University, Linnaeus väg 6, 90187 Umeå, Sweden.
| | - Qiuguo Fu
- Eawag: Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland; Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, 04318 Leipzig, Germany.
| | - Juliane Hollender
- Eawag: Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland; Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Universitätstrasse 16, 8092 Zürich, Switzerland.
| | - Jade Chaker
- Université de Rennes, Inserm, EHESP, Irset - UMR_S, 1085 Rennes, France.
| | - Arthur David
- Université de Rennes, Inserm, EHESP, Irset - UMR_S, 1085 Rennes, France.
| | - Uwe Kunkel
- Bavarian Environment Agency, Bürgermeister-Ulrich-Straße 160, 86179 Augsburg, Germany.
| | - André Macherius
- Bavarian Environment Agency, Bürgermeister-Ulrich-Straße 160, 86179 Augsburg, Germany.
| | - Lidia Belova
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium.
| | - Giulia Poma
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium.
| | | | - Catherine Munschy
- Ifremer, CCEM Contamination Chimique des Écosystèmes Marins, 44000 Nantes, France.
| | - Yann Aminot
- Ifremer, CCEM Contamination Chimique des Écosystèmes Marins, 44000 Nantes, France.
| | - Carsten Jaeger
- Bundesanstalt für Materialforschung und -prüfung (BAM), Analytical Chemistry, Richard-Willstätter-Straße 11, 12489 Berlin, Germany.
| | - Jan Lisec
- Bundesanstalt für Materialforschung und -prüfung (BAM), Analytical Chemistry, Richard-Willstätter-Straße 11, 12489 Berlin, Germany.
| | - Martin Hansen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark.
| | - Katrin Vorkamp
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark.
| | - Linyan Zhu
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark.
| | - Francesca Cappelli
- Water Research Institute, National Research Council of Italy, Via del Mulino 19, 20861 Brugherio MB, Italy.
| | - Claudio Roscioli
- Water Research Institute, National Research Council of Italy, Via del Mulino 19, 20861 Brugherio MB, Italy.
| | - Sara Valsecchi
- Water Research Institute, National Research Council of Italy, Via del Mulino 19, 20861 Brugherio MB, Italy.
| | - Renzo Bagnati
- Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, Italy.
| | - Belén González
- Department of Analytical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940 Leioa, Spain; Research Centre for Experimental Marine Biology and Biotechnology (PIE), University of the Basque Country (UPV/EHU), Areatza Pasealekua 47, 48620 Plentzia, Spain.
| | - Ailette Prieto
- Department of Analytical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940 Leioa, Spain; Research Centre for Experimental Marine Biology and Biotechnology (PIE), University of the Basque Country (UPV/EHU), Areatza Pasealekua 47, 48620 Plentzia, Spain.
| | - Olatz Zuloaga
- Department of Analytical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940 Leioa, Spain; Research Centre for Experimental Marine Biology and Biotechnology (PIE), University of the Basque Country (UPV/EHU), Areatza Pasealekua 47, 48620 Plentzia, Spain.
| | - Ruben Gil-Solsona
- Catalan Institute for Water Research (ICRA), Carrer Emili Grahit 101, 17003 Girona, Spain; Universitat de Girona, Girona, Spain; Institute of Environmental Assessment and Water Research - Severo Ochoa Excellence Center (IDAEA), Spanish Council of Scientific Research (CSIC), Barcelona 08034, Spain.
| | - Pablo Gago-Ferrero
- Catalan Institute for Water Research (ICRA), Carrer Emili Grahit 101, 17003 Girona, Spain; Institute of Environmental Assessment and Water Research - Severo Ochoa Excellence Center (IDAEA), Spanish Council of Scientific Research (CSIC), Barcelona 08034, Spain.
| | - Sara Rodriguez-Mozaz
- Catalan Institute for Water Research (ICRA), Carrer Emili Grahit 101, 17003 Girona, Spain; Universitat de Girona, Girona, Spain.
| | - Hélène Budzinski
- University Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, 33600 Pessac, France.
| | - Marie-Helene Devier
- University Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, 33600 Pessac, France.
| | - Georg Dierkes
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany.
| | - Lise Boulard
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany; Metabolomics Core Facility, Centre de Ressources et Recherches Technologiques (C2RT), Institut Pasteur, 25-28 Rue du Dr Roux, 75015 Paris, France.
| | - Griet Jacobs
- Flemish Institute for Technological Research (VITO), Unit Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium.
| | - Stefan Voorspoels
- Flemish Institute for Technological Research (VITO), Unit Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium.
| | - Heinz Rüdel
- Fraunhofer Institute for Molecular Biology and Applied Ecology (Fraunhofer IME), Auf dem Aberg 1, 57392 Schmallenberg, Germany.
| | - Lutz Ahrens
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, 75007 Uppsala, Sweden.
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10
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Li T, Lü F, Zhang H, Xu Q, He PJ. Nontarget Insights into the Fate of Cl-/Br-Containing DOM in Leachate during Membrane Treatment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:16033-16042. [PMID: 37822265 DOI: 10.1021/acs.est.3c04422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Halogenated organic compounds in wastewater are persistent and bioaccumulative contaminants of great concern, but few are known at the molecular level. Herein, we focus on nontarget screening of halogenated dissolved organic matter (DOM) in highly concentrated organic matrices of waste leachates and their concentrates. Solid-phase extraction (SPE) was optimized before capturing halogenated signatures via HaloSeeker 2.0 software on mining full-scan high-resolution mass spectrometry (HRMS) fingerprints. This study identified 438 Cl-/Br-containing DOM formulas in 21 leachates and membrane concentrates. Among them, 334 formulas were achieved via SPE with mixed-sorbent cartridges (mixed-SPE), surpassing the 164 formulas achieved through Bond Elut PPL cartridges (PPL-SPE). Herein, only four samples identified via PPL-SPE exhibited a resolution of >50% for extracted Cl-/Br-containing DOM by either SPE. The halogenated DOM constituted 6.87% of the total DOM mass features. Nevertheless, more abundant adsorbable organic halogens deciphered waste leachates and highly concentrated waste streams as reservoirs for halogenated contaminants. Remarkably, 75.7-98.1% of Cl-/Br-containing DOM in primary membrane concentrates remained stable through the secondary membrane treatment, indicating the persistence of these unknown contaminants even post-treatment.
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Affiliation(s)
- Tianqi Li
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
| | - Fan Lü
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
| | - Hua Zhang
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
| | - Qiyong Xu
- School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, PR China
| | - Pin-Jing He
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
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11
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Hulleman T, Turkina V, O’Brien JW, Chojnacka A, Thomas KV, Samanipour S. Critical Assessment of the Chemical Space Covered by LC-HRMS Non-Targeted Analysis. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:14101-14112. [PMID: 37704971 PMCID: PMC10537454 DOI: 10.1021/acs.est.3c03606] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/29/2023] [Accepted: 08/30/2023] [Indexed: 09/15/2023]
Abstract
Non-targeted analysis (NTA) has emerged as a valuable approach for the comprehensive monitoring of chemicals of emerging concern (CECs) in the exposome. The NTA approach can theoretically identify compounds with diverse physicochemical properties and sources. Even though they are generic and have a wide scope, non-targeted analysis methods have been shown to have limitations in terms of their coverage of the chemical space, as the number of identified chemicals in each sample is very low (e.g., ≤5%). Investigating the chemical space that is covered by each NTA assay is crucial for understanding the limitations and challenges associated with the workflow, from the experimental methods to the data acquisition and data processing techniques. In this review, we examined recent NTA studies published between 2017 and 2023 that employed liquid chromatography-high-resolution mass spectrometry. The parameters used in each study were documented, and the reported chemicals at confidence levels 1 and 2 were retrieved. The chosen experimental setups and the quality of the reporting were critically evaluated and discussed. Our findings reveal that only around 2% of the estimated chemical space was covered by the NTA studies investigated for this review. Little to no trend was found between the experimental setup and the observed coverage due to the generic and wide scope of the NTA studies. The limited coverage of the chemical space by the reviewed NTA studies highlights the necessity for a more comprehensive approach in the experimental and data processing setups in order to enable the exploration of a broader range of chemical space, with the ultimate goal of protecting human and environmental health. Recommendations for further exploring a wider range of the chemical space are given.
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Affiliation(s)
- Tobias Hulleman
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, 1090 GD Amsterdam, The Netherlands
| | - Viktoriia Turkina
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, 1090 GD Amsterdam, The Netherlands
| | - Jake W. O’Brien
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, 1090 GD Amsterdam, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Aleksandra Chojnacka
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, 1090 GD Amsterdam, The Netherlands
| | - Kevin V. Thomas
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Saer Samanipour
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, 1090 GD Amsterdam, The Netherlands
- UvA
Data Science Center, University of Amsterdam, 1012 WP Amsterdam, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
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12
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Ruan T, Li P, Wang H, Li T, Jiang G. Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective. Chem Rev 2023; 123:10584-10640. [PMID: 37531601 DOI: 10.1021/acs.chemrev.3c00056] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.
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Affiliation(s)
- Ting Ruan
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pengyang Li
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haotian Wang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingyu Li
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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13
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Manjarrés-López DP, Peña-Herrera JM, Benejam L, Montemurro N, Pérez S. Assessment of wastewater-borne pharmaceuticals in tissues and body fluids from riverine fish. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 324:121374. [PMID: 36858105 DOI: 10.1016/j.envpol.2023.121374] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Riverine fish in densely populated areas is constantly exposed to wastewater-borne contaminants from effluent discharges. These can enter the organism through the skin, gills or by ingestion. Whereas most studies assessing the contaminant burden in exposed fish have focused either on muscle or a limited set of tissues. Here we set out to generate a more comprehensive overview of the distribution of pollutants across tissues by analyzing a panel of matrices including liver, kidney, skin, brain, muscle, heart, plasma and bile. To achieve a broad analyte coverage with a minimal bias towards a specific contaminant class, sample extracts from four fish species were analyzed by High-Performance Liquid Chromatography (HPLC) - high-resolution mass spectrometry (HRMS) for the presence of 600 wastewater-borne pharmaceutically active compounds (PhACs) with known environmental relevance in river water through a suspect-screening analysis. A total of 30 compounds were detected by suspect screening in at least one of the analyzed tissues with a clear prevalence of antidepressants. Of these, 15 were detected at confidence level 2.a (Schymanski scale), and 15 were detected at confidence level 1 following confirmation with authentic standards, which furthermore enabled their quantification. The detected PhACs confirmed with level 1 of confidence included acridone, acetaminophen, caffeine, clarithromycin, codeine, diazepam, diltiazem, fluoxetine, ketoprofen, loratadine, metoprolol, sertraline, sotalol, trimethoprim, and venlafaxine. Among these substances, sertraline stood out as it displayed the highest detection frequency. The values of tissue partition coefficients for sertraline in the liver, kidney, brain and muscle were correlated with its physicochemical properties. Based on inter-matrix comparison of detection frequencies, liver, kidney, skin and heart should be included in the biomonitoring studies of PhACs in riverine fish.
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Affiliation(s)
| | | | - L Benejam
- Aquatic Ecology Group, University of Vic - Central University of Catalonia, c/de la Laura. 13, 08500, Vic, Barcelona, Spain
| | - N Montemurro
- ONHEALTH, IDAEA-CSIC, c/Jordi Girona 18-26, 08034, Barcelona, Spain
| | - S Pérez
- ONHEALTH, IDAEA-CSIC, c/Jordi Girona 18-26, 08034, Barcelona, Spain.
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14
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Feraud M, O'Brien JW, Samanipour S, Dewapriya P, van Herwerden D, Kaserzon S, Wood I, Rauert C, Thomas KV. InSpectra - A platform for identifying emerging chemical threats. JOURNAL OF HAZARDOUS MATERIALS 2023; 455:131486. [PMID: 37172382 DOI: 10.1016/j.jhazmat.2023.131486] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/14/2023]
Abstract
Non-target analysis (NTA) employing high-resolution mass spectrometry (HRMS) coupled with liquid chromatography is increasingly being used to identify chemicals of biological relevance. HRMS datasets are large and complex making the identification of potentially relevant chemicals extremely challenging. As they are recorded in vendor-specific formats, interpreting them is often reliant on vendor-specific software that may not accommodate advancements in data processing. Here we present InSpectra, a vendor independent automated platform for the systematic detection of newly identified emerging chemical threats. InSpectra is web-based, open-source/access and modular providing highly flexible and extensible NTA and suspect screening workflows. As a cloud-based platform, InSpectra exploits parallel computing and big data archiving capabilities with a focus for sharing and community curation of HRMS data. InSpectra offers a reproducible and transparent approach for the identification, tracking and prioritisation of emerging chemical threats.
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Affiliation(s)
- Mathieu Feraud
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia
| | - Jake W O'Brien
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia; Van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Netherlands.
| | - Saer Samanipour
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia; Van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Netherlands; UvA Data Science Center, University of Amsterdam, Netherlands.
| | - Pradeep Dewapriya
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia
| | - Denice van Herwerden
- Van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Netherlands
| | - Sarit Kaserzon
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia
| | - Ian Wood
- School of Mathematics and Physics, The University of Queensland, Australia
| | - Cassandra Rauert
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia
| | - Kevin V Thomas
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Australia
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15
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Ivanova B. Stochastic Dynamic Mass Spectrometric Quantitative and Structural Analyses of Pharmaceutics and Biocides in Biota and Sewage Sludge. Int J Mol Sci 2023; 24:6306. [PMID: 37047279 PMCID: PMC10094044 DOI: 10.3390/ijms24076306] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 03/17/2023] [Accepted: 03/25/2023] [Indexed: 03/30/2023] Open
Abstract
Mass spectrometric innovations in analytical instrumentation tend to be accompanied by the development of a data-processing methodology, expecting to gain molecular-level insights into real-life objects. Qualitative and semi-quantitative methods have been replaced routinely by precise, accurate, selective, and sensitive quantitative ones. Currently, mass spectrometric 3D molecular structural methods are attractive. As an attempt to establish a reliable link between quantitative and 3D structural analyses, there has been developed an innovative formula [DSD″,tot=∑inDSD″,i=∑in2.6388.10-17×Ii2¯-Ii¯2] capable of the exact determination of the analyte amount and its 3D structure. It processed, herein, ultra-high resolution mass spectrometric variables of paracetamol, atenolol, propranolol, and benzalkonium chlorides in biota, using mussel tissue and sewage sludge. Quantum chemistry and chemometrics were also used. Results: Data on mixtures of antibiotics and surfactants in biota and the linear dynamic range of concentrations 2-80 ng.(mL)-1 and collision energy CE = 5-60 V are provided. Quantitative analysis of surfactants in biota via calibration equation ln[D″SD] = f(conc.) yields the exact parameter |r| = 0.99991, examining the peaks of BAC-C12 at m/z 212.209 ± 0.1 and 211.75 ± 0.15 for tautomers of fragmentation ions. Exact parameter |r| = 1 has been obtained, correlating the theory and experiments in determining the 3D molecular structures of ions of paracetamol at m/z 152, 158, 174, 301, and 325 in biota.
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Affiliation(s)
- Bojidarka Ivanova
- Lehrstuhl für Analytische Chemie, Institut für Umweltforschung, Fakultät für Chemie und Chemische Biologie, Universität Dortmund, Otto-Hahn-Straße 6, 44221 Dortmund, Nordrhein-Westfalen, Germany
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16
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Boelrijk J, van Herwerden D, Ensing B, Forré P, Samanipour S. Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data. J Cheminform 2023; 15:28. [PMID: 36829215 PMCID: PMC9960388 DOI: 10.1186/s13321-023-00699-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 02/13/2023] [Indexed: 02/26/2023] Open
Abstract
Non-target analysis combined with liquid chromatography high resolution mass spectrometry is considered one of the most comprehensive strategies for the detection and identification of known and unknown chemicals in complex samples. However, many compounds remain unidentified due to data complexity and limited number structures in chemical databases. In this work, we have developed and validated a novel machine learning algorithm to predict the retention index (r[Formula: see text]) values for structurally (un)known chemicals based on their measured fragmentation pattern. The developed model, for the first time, enabled the predication of r[Formula: see text] values without the need for the exact structure of the chemicals, with an [Formula: see text] of 0.91 and 0.77 and root mean squared error (RMSE) of 47 and 67 r[Formula: see text] units for the NORMAN ([Formula: see text]) and amide ([Formula: see text]) test sets, respectively. This fragment based model showed comparable accuracy in r[Formula: see text] prediction compared to conventional descriptor-based models that rely on known chemical structure, which obtained an [Formula: see text] of 0.85 with an RMSE of 67.
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Affiliation(s)
- Jim Boelrijk
- AI4Science Lab, University of Amsterdam, Amsterdam, The Netherlands. .,Institute for Informatics, University of Amsterdam, Amsterdam, The Netherlands.
| | - Denice van Herwerden
- grid.7177.60000000084992262Van’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam, The Netherlands
| | - Bernd Ensing
- grid.7177.60000000084992262AI4Science Lab, University of Amsterdam, Amsterdam, The Netherlands ,Computational Chemistry Group, Van’t Hoff Institute for Molecular Sciences (HIMS), Amsterdam, The Netherlands
| | - Patrick Forré
- grid.7177.60000000084992262AI4Science Lab, University of Amsterdam, Amsterdam, The Netherlands ,grid.7177.60000000084992262Institute for Informatics, University of Amsterdam, Amsterdam, The Netherlands
| | - Saer Samanipour
- Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam, The Netherlands. .,UvA Data Science Center, University of Amsterdam, Amsterdam, The Netherlands. .,Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, Australia.
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Köppe T, Jewell KS, Ehlig B, Wick A, Koschorreck J, Ternes TA. Identification and trend analysis of organic cationic contaminants via non-target screening in suspended particulate matter of the German rivers Rhine and Saar. WATER RESEARCH 2023; 229:119304. [PMID: 36459896 DOI: 10.1016/j.watres.2022.119304] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/14/2022] [Accepted: 10/26/2022] [Indexed: 06/17/2023]
Abstract
Non-target screening of suspended particulate matter (SPM), collected from the German rivers Rhine and Saar, was conducted with the goal of identifying organic, permanent cationic contaminants and of estimating their temporal trends over an extended period. Therefore, annual composite samples of SPM, provided by the German Environmental Specimen Bank, were extracted and analyzed with high resolution LC-QToF-MS/MS. To facilitate the identification of substances belonging to the class "permanent cations", prioritization methods were applied utilizing the physicochemical properties of these compounds. These methods include both interactions of the analyte molecules with cation exchange resins and analyzing mass deviations when changing from non-deuterated to deuterated mobile phase solvents during LC-MS analysis. By applying both methods in a combined approach, 123 of the initially detected 2695 features were prioritized, corresponding to a 95% data reduction. This led to the identification of 22 permanent cationic species. The organic dyes Basic Yellow 28 and Fluorescent Brightener 363 as well as two quaternary ammonium compounds (QACs) were detected in environmental samples for the first time to best of or knowledge. The other compounds include additional QACs, as well as quaternary tri-phenylphosphonium compounds (QPC/TPP). In addition to identification, we determined temporal trends of all compounds over a period of 13 years and assessed their ecotoxicological relevance based on estimated concentrations. The two QACs oleyltrimethylammonium and eicosyltrimethylammonium show significant increasing trends in the Rhine SPM and maximum concentrations in the Saar SPM of about 900 and 1400 µg/kg, respectively. In the case of the dyes, constant trends have been observed at the end of the studied period, but also maximum concentrations of 400 µg/kg for Basic Yellow 28 in 2006 and 1000 µg/kg for Fluorescent Brightener 363 in 2015, potentially indicating a strong ecotoxicological risk.
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Affiliation(s)
- Toni Köppe
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany
| | - Kevin S Jewell
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany
| | - Björn Ehlig
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany
| | - Arne Wick
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany
| | - Jan Koschorreck
- Federal Environment Agency (Umweltbundesamt), Colditzstraße 34, 14193, Berlin, Germany
| | - Thomas A Ternes
- Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany.
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18
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Wu Y, Zhou L, Kang L, Cheng H, Wei X, Pan C. Suspect screening strategy for pesticide application history based on characteristics of trace metabolites. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120557. [PMID: 36328280 DOI: 10.1016/j.envpol.2022.120557] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 10/22/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
Pesticides are widely used to protect crops but can also threaten public health as they can remain in the environment for a long time. Additionally, some transformation products (TPs) of unknown toxicity, stability, or bioaccumulation properties can further be formed from the hydrolysis, photolysis and biodegradation of pesticides. The identification and quantification of those TPs can be challenging for environmental regulation and risk assessment due to a limited understanding about them. In this study, a suspect screening strategy for pesticide application history was developed and then used to organic products (tea). Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) was used to screen and identify the TPs in crops and their toxicity was subsequently predicted with the open-source software (ECOSAR and admetSAR). Finally, the SIRIUS software was applied and 142 TPs from 20 pesticides were identified in tea plants based on the fragmentation-degradation relationship. Of these, standards (level 1) and 53 were considered as tentatively identified (levels 2a and 2b). Some TPs were also found to be present in tea plants and soil after 65 days, thus indicating higher persistency or stability than parent pesticides. While others from diafenthiuron and neonicotinoids had higher predicted toxicity of daphnid, and demonstrated positive for honeybee toxicity. Suspect screening is a powerful tool to screen pesticide TPs on the complex matrix of crops. Such screening can provide potential evidence of pesticide application, especially in cases of illegal practices in organic farming.
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Affiliation(s)
- Yangliu Wu
- Innovation Center of Pesticide Research, Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China
| | - Li Zhou
- Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310008, China
| | - Lu Kang
- Innovation Center of Pesticide Research, Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China
| | - Haiyan Cheng
- Innovation Center of Pesticide Research, Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China
| | - Xinlin Wei
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Canping Pan
- Innovation Center of Pesticide Research, Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China.
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19
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Li T, Lü F, Qiu J, Zhang H, He P. Substance flow analysis on the leachate DOM molecules along five typical membrane advanced treatment processes. WATER RESEARCH 2023; 228:119348. [PMID: 36403296 DOI: 10.1016/j.watres.2022.119348] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
The processes combining biological treatment with membrane separation technologies have been widely adopted for leachate treatment. However, dissolved organic matter (DOM) of leachate membrane concentrates generated from various membrane separation technologies has not been systematically investigated in field scale. Therefore, substance flow analysis based on DOM molecular information of leachate membrane concentrates from primary membrane systems (i.e. nanofiltration (NF) and reverse osmosis (RO)) and secondary membrane systems (i.e. disk-tube reverse osmosis (DTRO) and humic substance filtration system (HSF)) in five engineering-scale leachate treatment facilities, obtained via ultra-performance liquid chromatography coupled with hybrid quadrupole Orbitrap mass spectrometry, was given and simultaneously compared. In NF concentrates (NFC), 45.1-98.5% of DOM originated from raw leachate (L-DOM) was concentrated, showing poor biodegradability. The L-DOM interception characteristics of NFC-fed HSF were mainly based on volume reduction but concentration effect. L-DOM in RO concentrates (ROC) showed a higher proportion of peak intensity reduced components, accounting for 50.3-96.8%, and organic composition changes were more dependent on water quality characteristics than membrane types. ROC-fed DTRO intercepted 49.3-72.6% of L-DOM, but DTRO may be less effective at intercepting DOM molecules in landfill leachate with higher oxidation levels. Considering risks from feasible treatment technologies, the difficulty for the treatment of leachate membrane concentrates followed the order of DTRO concentrates > ROC > NFC. This study suggests that ROC-fed DTRO need to be controlled to avoid amplifying the treatment difficulty. Besides, treatment technologies for RO and DTRO concentrates with low-concentrated but refractory DOM and high salts should be explored.
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Affiliation(s)
- Tianqi Li
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai, 200092, PR China
| | - Fan Lü
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai, 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, PR China; Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai, 200092, PR China
| | - Junjie Qiu
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai, 200092, PR China
| | - Hua Zhang
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai, 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, PR China; Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai, 200092, PR China
| | - Pinjing He
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai, 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, PR China; Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai, 200092, PR China.
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20
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Beretsou VG, Nika MC, Manoli K, Michael C, Sui Q, Lundy L, Revitt DM, Thomaidis NS, Fatta-Kassinos D. Multiclass target analysis of contaminants of emerging concern including transformation products, soil bioavailability assessment and retrospective screening as tools to evaluate risks associated with reclaimed water reuse. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158391. [PMID: 36049679 DOI: 10.1016/j.scitotenv.2022.158391] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/25/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
The occurrence of 200 multiclass contaminants of emerging concern (CECs) encompassing 168 medicinal products and transformation products (TPs), 5 artificial sweeteners, 12 industrial chemicals, and 15 other compounds was investigated in influent and effluent wastewater samples collected during 7 consecutive days from 5 wastewater treatment plants (WWTPs) located in Cyprus. The methodology included a generic solid-phase extraction protocol using mixed-bed cartridges followed by Ultra-High Performance Liquid Chromatography coupled with Quadrupole-Time of Flight Mass Spectrometry (UHPLC-QTOF-MS) analysis. A total of 63 CECs were detected at least in one sample, with 52 and 55 out of the 200 compounds detected in influents and effluents, respectively. Ten (10) out of the 24 families of parent compounds and associated TPs were found in the wastewater samples (influent or effluent). 1-H-benzotriazole, carbamazepine, citalopram, lamotrigine, sucralose, tramadol, and venlafaxine (>80 % frequency of appearance in effluents) were assessed with respect to their bioavailability in soil as part of different scenarios of irrigation with reclaimed water following a qualitative approach. A high score of 12 (high probability) was predicted for 2 scenarios, a low score of 3 (rare occasions) for 2 scenarios, while the rest 28 scenarios had scores 5-8 (unlikely or limited possibility) and 9-11 (possibly). Retrospective screening was performed with the use of a target database of 2466 compounds and led to the detection of 158 additional compounds (medicinal products (65), medicinal products TPs (15), illicit drugs (7), illicit drugs TPs (3), industrial chemicals (11), plant protection products (25), plant protection products TPs (10), and various other compounds (22). This work aspires to showcase how the presence of CECs in wastewater could be investigated and assessed at WWTP level, including an expert-based methodology for assessing the soil bioavailability of CECs, with the aim to develop sustainable practices and enhance reclaimed water reuse.
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Affiliation(s)
- Vasiliki G Beretsou
- Department of Civil and Environmental Engineering, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus; Nireas-International Water Research Center, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus
| | - Maria-Christina Nika
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Kyriakos Manoli
- Nireas-International Water Research Center, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus
| | - Costas Michael
- Nireas-International Water Research Center, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus
| | - Qian Sui
- State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Lian Lundy
- Middlesex University, Department of Natural Sciences, School of Science and Technology, London NW4 4BT, United Kingdom
| | - D Michael Revitt
- Middlesex University, Department of Natural Sciences, School of Science and Technology, London NW4 4BT, United Kingdom
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
| | - Despo Fatta-Kassinos
- Department of Civil and Environmental Engineering, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus; Nireas-International Water Research Center, School of Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus.
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21
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Cao G, Zhang J, Wang W, Wu P, Ru Y, Cai Z. Mass spectrometry analysis of a ubiquitous tire rubber-derived quinone in the environment. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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22
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Pistocchi A, Alygizakis NA, Brack W, Boxall A, Cousins IT, Drewes JE, Finckh S, Gallé T, Launay MA, McLachlan MS, Petrovic M, Schulze T, Slobodnik J, Ternes T, Van Wezel A, Verlicchi P, Whalley C. European scale assessment of the potential of ozonation and activated carbon treatment to reduce micropollutant emissions with wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 848:157124. [PMID: 35792263 DOI: 10.1016/j.scitotenv.2022.157124] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
Micropollutants (MPs) in wastewater pose a growing concern for their potential adverse effects on the receiving aquatic environment, and some countries have started requiring that wastewater treatment plants remove them to a certain extent. Broad spectrum advanced treatment processes, such as ozonation, activated carbon or their combination, are expected to yield a significant reduction in the toxicity of effluents. Here we quantify the reduction of effluent toxicity potentially achieved by implementing these advanced treatment solutions in a selection of European wastewater treatment plants. To this end, we refer to a list of "total pollution proxy substances" (TPPS) composed of 1337 chemicals commonly found in wastewater effluents according to a compilation of datasets of measured concentrations. We consider these substances as an approximation of the "chemical universe" impinging on the European wastewater system. We evaluate the fate of the TPPS in conventional and advanced treatment plants using a compilation of experimental physicochemical properties that describe their sorption, volatilization and biodegradation during activated sludge treatment, as well as known removal efficiency in ozonation and activated carbon treatment, while filling the gaps through in silico prediction models. We estimate that the discharge of micropollutants with wastewater effluents in the European Union has a cumulative MP toxicity to the environment equal to the discharge of untreated wastewater of ca. 160 million population equivalents (PE), i.e. about 30 % of the generated wastewater in the EU. If all plants above a capacity of 100,000 PE were equipped with advanced treatment, we show that this load would be reduced to about 95 million PE. In addition, implementing advanced treatment in wastewater plants above 10,000 PE discharging to water bodies with an average dilution ratio smaller than 10 would yield a widespread improvement in terms of exposure of freshwater ecosystems to micropollutants, almost halving the part of the stream network exposed to the highest toxic risks. Our analysis provides background for a cost-effectiveness appraisal of advanced treatment "at the end of the pipe", which could lead to optimized interventions. This should not be regarded as a stand-alone solution, but as a complement to policies for the control of emissions at the source for the most problematic MPs.
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Affiliation(s)
| | | | - Werner Brack
- Helmholtz Centre for Environmental Research - UFZ, Department of Effect-Directed Analysis, Permoserstr. 15, 04318 Leipzig, Germany; Department of Evolutionary Ecology and Environmental Toxicology, Faculty of Biological Sciences, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Alistair Boxall
- Environment and Geography Department, University of York, Heslington York YO10 5NG, UK
| | - Ian T Cousins
- Department of Environmental Science, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Jörg E Drewes
- Urban Water Systems Engineering, Technical University of Munich, D-85748 Garching, Germany
| | - Saskia Finckh
- Helmholtz Centre for Environmental Research - UFZ, Department of Effect-Directed Analysis, Permoserstr. 15, 04318 Leipzig, Germany
| | - Tom Gallé
- LIST, Environmental Research and Innovation Dept., 41 rue du Brill, L-4422 Belvaux, Luxembourg
| | - Marie A Launay
- Micropollutants Competence Centre Baden-Württemberg, Institute of Sanitary Engineering, Water Quality and Solid Waste Management, University of Stuttgart, Bandtaele 2, 70569 Stuttgart, Germany
| | - Michael S McLachlan
- Department of Environmental Science, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Mira Petrovic
- Catalan Institute for Water Research (ICRA), Girona, and Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Tobias Schulze
- Helmholtz Centre for Environmental Research - UFZ, Department of Effect-Directed Analysis, Permoserstr. 15, 04318 Leipzig, Germany
| | | | | | - Annemarie Van Wezel
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Paola Verlicchi
- Department of Engineering, University of Ferrara, Ferrara, Italy
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23
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Mohammed Taha H, Aalizadeh R, Alygizakis N, Antignac JP, Arp HPH, Bade R, Baker N, Belova L, Bijlsma L, Bolton EE, Brack W, Celma A, Chen WL, Cheng T, Chirsir P, Čirka Ľ, D’Agostino LA, Djoumbou Feunang Y, Dulio V, Fischer S, Gago-Ferrero P, Galani A, Geueke B, Głowacka N, Glüge J, Groh K, Grosse S, Haglund P, Hakkinen PJ, Hale SE, Hernandez F, Janssen EML, Jonkers T, Kiefer K, Kirchner M, Koschorreck J, Krauss M, Krier J, Lamoree MH, Letzel M, Letzel T, Li Q, Little J, Liu Y, Lunderberg DM, Martin JW, McEachran AD, McLean JA, Meier C, Meijer J, Menger F, Merino C, Muncke J, Muschket M, Neumann M, Neveu V, Ng K, Oberacher H, O’Brien J, Oswald P, Oswaldova M, Picache JA, Postigo C, Ramirez N, Reemtsma T, Renaud J, Rostkowski P, Rüdel H, Salek RM, Samanipour S, Scheringer M, Schliebner I, Schulz W, Schulze T, Sengl M, Shoemaker BA, Sims K, Singer H, Singh RR, Sumarah M, Thiessen PA, Thomas KV, Torres S, Trier X, van Wezel AP, Vermeulen RCH, Vlaanderen JJ, von der Ohe PC, Wang Z, Williams AJ, Willighagen EL, Wishart DS, Zhang J, Thomaidis NS, Hollender J, Slobodnik J, Schymanski EL. The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry. ENVIRONMENTAL SCIENCES EUROPE 2022; 34:104. [PMID: 36284750 PMCID: PMC9587084 DOI: 10.1186/s12302-022-00680-6] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 09/24/2022] [Indexed: 06/16/2023]
Abstract
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/). Supplementary Information The online version contains supplementary material available at 10.1186/s12302-022-00680-6.
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Affiliation(s)
- Hiba Mohammed Taha
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367 Belvaux, Luxembourg
| | - Reza Aalizadeh
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Nikiforos Alygizakis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
| | | | - Hans Peter H. Arp
- Norwegian Geotechnical Institute (NGI), Ullevål Stadion, P.O. Box 3930, 0806 Oslo, Norway
- Department of Chemistry, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Richard Bade
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, QLD 4102 Australia
| | | | - Lidia Belova
- Toxicological Centre, University of Antwerp, Antwerp, Belgium
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castelló, Spain
| | - Evan E. Bolton
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Werner Brack
- UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany
- Institute of Ecology, Evolution and Diversity, Goethe University, Frankfurt Am Main, Germany
| | - Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castelló, Spain
- Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Wen-Ling Chen
- Institute of Food Safety and Health, College of Public Health, National Taiwan University, 17 Xuzhou Rd., Zhongzheng Dist., Taipei, Taiwan
| | - Tiejun Cheng
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Parviel Chirsir
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367 Belvaux, Luxembourg
| | - Ľuboš Čirka
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
- Faculty of Chemical and Food Technology, Institute of Information Engineering, Automation, and Mathematics, Slovak University of Technology in Bratislava (STU), Radlinského 9, 812 37 Bratislava, Slovak Republic
| | - Lisa A. D’Agostino
- Science for Life Laboratory, Department of Environmental Science, Stockholm University, 10691 Stockholm, Sweden
| | | | - Valeria Dulio
- INERIS, National Institute for Environment and Industrial Risks, Verneuil en Halatte, France
| | - Stellan Fischer
- Swedish Chemicals Agency (KEMI), P.O. Box 2, 172 13 Sundbyberg, Sweden
| | - Pablo Gago-Ferrero
- Institute of Environmental Assessment and Water Research-Severo Ochoa Excellence Center (IDAEA), Spanish Council of Scientific Research (CSIC), Barcelona, Spain
| | - Aikaterini Galani
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Birgit Geueke
- Food Packaging Forum Foundation, Staffelstrasse 10, 8045 Zurich, Switzerland
| | - Natalia Głowacka
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
| | - Juliane Glüge
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, 8092 Zurich, Switzerland
| | - Ksenia Groh
- Eawag, Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Sylvia Grosse
- Thermo Fisher Scientific, Dornierstrasse 4, 82110 Germering, Germany
| | - Peter Haglund
- Department of Chemistry, Chemical Biological Centre (KBC), Umeå University, Linnaeus Väg 6, 901 87 Umeå, Sweden
| | - Pertti J. Hakkinen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Sarah E. Hale
- Norwegian Geotechnical Institute (NGI), Ullevål Stadion, P.O. Box 3930, 0806 Oslo, Norway
| | - Felix Hernandez
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castelló, Spain
| | - Elisabeth M.-L. Janssen
- Eawag, Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Tim Jonkers
- Department Environment and Health, Amsterdam Institute for Life and Environment, Vrije Universiteit, Amsterdam, The Netherlands
| | - Karin Kiefer
- Eawag, Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Michal Kirchner
- Water Research Institute (WRI), Nábr. Arm. Gen. L. Svobodu 5, 81249 Bratislava, Slovak Republic
| | - Jan Koschorreck
- German Environment Agency (UBA), Wörlitzer Platz 1, Dessau-Roßlau, Germany
| | - Martin Krauss
- UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Jessy Krier
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367 Belvaux, Luxembourg
| | - Marja H. Lamoree
- Department Environment and Health, Amsterdam Institute for Life and Environment, Vrije Universiteit, Amsterdam, The Netherlands
| | - Marion Letzel
- Bavarian Environment Agency, 86179 Augsburg, Germany
| | - Thomas Letzel
- Analytisches Forschungsinstitut Für Non-Target Screening GmbH (AFIN-TS), Am Mittleren Moos 48, 86167 Augsburg, Germany
| | - Qingliang Li
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - James Little
- Mass Spec Interpretation Services, 3612 Hemlock Park Drive, Kingsport, TN 37663 USA
| | - Yanna Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (SKLECE, RCEES, CAS), No. 18 Shuangqing Road, Haidian District, Beijing, 100086 China
| | - David M. Lunderberg
- Hope College, Holland, MI 49422 USA
- University of California, Berkeley, CA USA
| | - Jonathan W. Martin
- Science for Life Laboratory, Department of Environmental Science, Stockholm University, 10691 Stockholm, Sweden
| | - Andrew D. McEachran
- Agilent Technologies, Inc., 5301 Stevens Creek Blvd, Santa Clara, CA 95051 USA
| | - John A. McLean
- Department of Chemistry, Center for Innovative Technology, Vanderbilt-Ingram Cancer Center, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235 USA
| | - Christiane Meier
- German Environment Agency (UBA), Wörlitzer Platz 1, Dessau-Roßlau, Germany
| | - Jeroen Meijer
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | - Frank Menger
- Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Carla Merino
- University Rovira i Virgili, Tarragona, Spain
- Biosfer Teslab, Reus, Spain
| | - Jane Muncke
- Food Packaging Forum Foundation, Staffelstrasse 10, 8045 Zurich, Switzerland
| | | | - Michael Neumann
- German Environment Agency (UBA), Wörlitzer Platz 1, Dessau-Roßlau, Germany
| | - Vanessa Neveu
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC), 150 Cours Albert Thomas, 69372 Lyon Cedex 08, France
| | - Kelsey Ng
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
- RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, Brno, Czech Republic
| | - Herbert Oberacher
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Muellerstrasse 44, Innsbruck, Austria
| | - Jake O’Brien
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, QLD 4102 Australia
| | - Peter Oswald
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
| | - Martina Oswaldova
- Environmental Institute, Okružná 784/42, 972 41 Koš, Slovak Republic
| | - Jaqueline A. Picache
- Department of Chemistry, Center for Innovative Technology, Vanderbilt-Ingram Cancer Center, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, TN 37235 USA
| | - Cristina Postigo
- Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
- Technologies for Water Management and Treatment Research Group, Department of Civil Engineering, University of Granada, Campus de Fuentenueva S/N, 18071 Granada, Spain
| | - Noelia Ramirez
- University Rovira i Virgili, Tarragona, Spain
- Institute of Health Research Pere Virgili, Tarragona, Spain
| | | | - Justin Renaud
- Agriculture and Agri-Food Canada/Agriculture et Agroalimentaire Canada, 1391 Sandford Street, London, ON N5V 4T3 Canada
| | | | - Heinz Rüdel
- Fraunhofer Institute for Molecular Biology and Applied Ecology (Fraunhofer IME), Schmallenberg, Germany
| | - Reza M. Salek
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC), 150 Cours Albert Thomas, 69372 Lyon Cedex 08, France
| | - Saer Samanipour
- Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, P.O. Box 94157, Amsterdam, 1090 GD The Netherlands
| | - Martin Scheringer
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, 8092 Zurich, Switzerland
- RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, Brno, Czech Republic
| | - Ivo Schliebner
- German Environment Agency (UBA), Wörlitzer Platz 1, Dessau-Roßlau, Germany
| | - Wolfgang Schulz
- Laboratory for Operation Control and Research, Zweckverband Landeswasserversorgung, Am Spitzigen Berg 1, 89129 Langenau, Germany
| | - Tobias Schulze
- UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Manfred Sengl
- Bavarian Environment Agency, 86179 Augsburg, Germany
| | - Benjamin A. Shoemaker
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Kerry Sims
- Environment Agency, Horizon House, Deanery Road, Bristol, BS1 5AH UK
| | - Heinz Singer
- Eawag, Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Randolph R. Singh
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367 Belvaux, Luxembourg
- Chemical Contamination of Marine Ecosystems (CCEM) Unit, Institut Français de Recherche pour l’Exploitation de la Mer (IFREMER), Rue de l’Ile d’Yeu, BP 21105, 44311 Cedex 3, Nantes France
| | - Mark Sumarah
- Agriculture and Agri-Food Canada/Agriculture et Agroalimentaire Canada, 1391 Sandford Street, London, ON N5V 4T3 Canada
| | - Paul A. Thiessen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Kevin V. Thomas
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, QLD 4102 Australia
| | | | - Xenia Trier
- Section for Environmental Chemistry and Physics, Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark
| | - Annemarie P. van Wezel
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Roel C. H. Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | - Jelle J. Vlaanderen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | | | - Zhanyun Wang
- Technology and Society Laboratory, Empa-Swiss Federal Laboratories for Materials Science and Technology, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland
| | - Antony J. Williams
- Computational Chemistry and Cheminformatics Branch (CCCB), Chemical Characterization and Exposure Division (CCED), Center for Computational Toxicology and Exposure (CCTE), United States Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711 USA
| | - Egon L. Willighagen
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
| | | | - Jian Zhang
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA
| | - Nikolaos S. Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Juliane Hollender
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, 8092 Zurich, Switzerland
- Eawag, Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | | | - Emma L. Schymanski
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, 4367 Belvaux, Luxembourg
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Qiu J, Lü F, Li T, Zhang H, He P. A Novel 4-Set Venn Diagram Model Based on High-Resolution Mass Spectrometry To Monitor Wastewater Treatment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:14753-14762. [PMID: 36166304 DOI: 10.1021/acs.est.2c02229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
A 4-set Venn diagram model oriented to high-resolution mass spectrometry (HRMS) data was developed to decipher the fate of dissolved organic matters (DOM) in three-stage continuous wastewater treatment processes. In total, 24 typical wastewater treatment modes conceptualized into a combination of three stages were generalized so that this model can be applied to all common types of actual wastewater treatment processes. As a result, eight kinds of native DOM and seven kinds of wastewater-produced (WW-produced) DOM separately represented by each proper subset of the 4-set Venn diagram could be identified so as to offer a molecular profile of DOM transformation. The 15 proper subsets of the 4-set Venn diagram could then explain how different wastewater treatment units work. Transformation rates of each DOM molecular formula can be estimated as a semiquantitative result. We further discussed the relationship between the transformation rates and proper subsets. As a proof of concept, the 4-set Venn diagram model was successfully applied in a complicated full-scale mature leachate treatment process with nine treatment units. This model can help to overcome the challenging task of data mining when applying HRMS and reduce the workload of data screening in the subsequent structural annotation.
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Affiliation(s)
- Junjie Qiu
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
| | - Fan Lü
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
- Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai 200092, PR China
| | - Tianqi Li
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
| | - Hua Zhang
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
- Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai 200092, PR China
| | - Pinjing He
- Institute of Waste Treatment and Reclamation, Tongji University, Shanghai 200092, PR China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
- Shanghai Engineering Research Center of Multi-source Solid Wastes Co-processing and Energy Utilization, Shanghai 200092, PR China
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25
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Yang F, van Herwerden D, Preud’homme H, Samanipour S. Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning. Molecules 2022; 27:6424. [PMID: 36234961 PMCID: PMC9572128 DOI: 10.3390/molecules27196424] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022] Open
Abstract
High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals' super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.
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Affiliation(s)
- Fan Yang
- Institut des Sciences Analytiques et de Physico-Chimie Pour l’Environnement et les Materiaux (IPREM-UMR5254), E2S UPPA, CNRS, 64000 Pau, France
| | - Denice van Herwerden
- Van ’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Hugues Preud’homme
- Institut des Sciences Analytiques et de Physico-Chimie Pour l’Environnement et les Materiaux (IPREM-UMR5254), E2S UPPA, CNRS, 64000 Pau, France
| | - Saer Samanipour
- Van ’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- UvA Data Science Center, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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26
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Phillips AL, Williams AJ, Sobus JR, Ulrich EM, Gundersen J, Langlois-Miller C, Newton SR. A Framework for Utilizing High-Resolution Mass Spectrometry and Nontargeted Analysis in Rapid Response and Emergency Situations. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2022; 41:1117-1130. [PMID: 34416028 PMCID: PMC9280853 DOI: 10.1002/etc.5196] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 07/26/2021] [Accepted: 08/17/2021] [Indexed: 05/03/2023]
Abstract
Unknown chemical releases constitute a large portion of the rapid response situations to which the US Environmental Protection Agency is called on to respond. Workflows used to address unknown chemical releases currently involve screening for a large array of known compounds using many different targeted methods. When matches are not found, expert analytical chemistry knowledge is used to propose possible candidates from the available data, which generally includes low-resolution mass spectra and situational clues such as the location of the release, nearby industrial operations, and other field-reported facts. The past decade has witnessed dramatic improvements in capabilities for identifying unknown compounds using high-resolution mass spectrometry (HRMS) and nontargeted analysis (NTA) approaches. Complementary developments in cheminformatics tools have further enabled an increase in NTA throughput and identification confidence. Together with the expanding availability of HRMS instrumentation in monitoring laboratories, these advancements make NTA highly relevant to rapid response scenarios. In this article, we introduce the concept of NTA as it relates to rapid response needs and describe how it can be applied to address unknown chemical releases. We advocate for the consideration of HRMS-based NTA approaches to support future rapid response scenarios. Environ Toxicol Chem 2022;41:1117-1130. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.
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Affiliation(s)
- Allison L. Phillips
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Public Health and Environmental Assessment, Research Triangle Park, NC 27711
| | - Antony J. Williams
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711
| | - Jon R. Sobus
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711
| | - Elin M. Ulrich
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711
| | - Jennifer Gundersen
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Environmental Measurement and Modeling, Narragansett, RI 02882
| | - Christina Langlois-Miller
- U.S. Environmental Protection Agency, Office of Land and Emergency Management, Office of Emergency Management, Washington D.C. 20460
| | - Seth R. Newton
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711
- Corresponding author contact information: Seth R. Newton, , Mail: 109 T.W. Alexander Drive E205-05, RTP, NC 27711
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27
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Dürig W, Alygizakis NA, Wiberg K, Ahrens L. Application of a novel prioritisation strategy using non-target screening for evaluation of temporal trends (1969-2017) of contaminants of emerging concern (CECs) in archived lynx muscle tissue samples. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 817:153035. [PMID: 35026275 DOI: 10.1016/j.scitotenv.2022.153035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 12/20/2021] [Accepted: 01/06/2022] [Indexed: 06/14/2023]
Abstract
Most environmental monitoring studies of contaminants of emerging concern (CECs) focus on aquatic species and target specific classes of CECs. Even with wide-scope target screening methods, relevant CECs may be missed. In this study, non-target screening (NTS) was used for tentative identification of potential CECs in muscle tissue of the terrestrial top predator Eurasian lynx (Lynx lynx). Temporal trend analysis was applied as a prioritisation tool for archived samples, using univariate statistical tests (Mann-Kendall and Spearman rank). Pooled lynx muscle tissue collected from 1969 to 2017 was analysed with an eight-point time series using a previously validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 12,941 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 104 and 61 features with statistically significant increasing and decreasing trends, respectively. Following probable molecular formula assignment and elucidation with MetFrag, two compounds with increasing trends, and one with a decreasing trend, were tentatively identified. These results show that, despite low expected concentration levels and high matrix effects in terrestrial species, it is possible to prioritise CECs in archived lynx samples using NTS and univariate statistical approaches.
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Affiliation(s)
- Wiebke Dürig
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, SE-750 07 Uppsala, Sweden.
| | - Nikiforos A Alygizakis
- Environmental Institute, Okruzná 784/42, 97241 Koš, Slovak Republic; Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Greece.
| | - Karin Wiberg
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, SE-750 07 Uppsala, Sweden.
| | - Lutz Ahrens
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Box 7050, SE-750 07 Uppsala, Sweden.
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28
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Nikolopoulou V, Aalizadeh R, Nika MC, Thomaidis NS. TrendProbe: Time profile analysis of emerging contaminants by LC-HRMS non-target screening and deep learning convolutional neural network. JOURNAL OF HAZARDOUS MATERIALS 2022; 428:128194. [PMID: 35033918 DOI: 10.1016/j.jhazmat.2021.128194] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/08/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
Peak prioritization is one of the key steps in non-target screening of environmental samples to direct the identification efforts to relevant and important features. Occurrence of chemicals is sometimes a function of time and their presence in consecutive days (trend) reveals important aspects such as discharges from agricultural, industrial or domestic activities. This study presents a validated computational framework based on deep learning conventional neural network to classify trends of chemicals over 30 consecutive days of sampling in two sampling sites (upstream and downstream of a river). From trend analysis and factor analysis, the chemicals could be classified into periodic, spill, increasing, decreasing and false trend. The developed method was validated with list of 42 reference standards (target screening) and applied to samples. 25 compounds were selected by the deep learning and identified via non-target screening. Three classes of surfactants were identified for the first time in river water and two of them were never reported in the literature. Overall, 21 new homologous series of the newly identified surfactants were tentatively identified. The aquatic toxicity of the identified compounds was estimated by in silico tools and a few compounds along with their homologous series showed potential risk to aquatic environment.
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Affiliation(s)
- Varvara Nikolopoulou
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Reza Aalizadeh
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
| | - Maria-Christina Nika
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
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29
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Tao Y, Liu J, Xu Y, Liu H, Yang G, He Y, Xu J, Lu Z. Suspecting screening "known unknown" pesticides and transformation products in soil at pesticide manufacturing sites. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 808:152074. [PMID: 34863759 DOI: 10.1016/j.scitotenv.2021.152074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/16/2021] [Accepted: 11/26/2021] [Indexed: 06/13/2023]
Abstract
The occurrence and risks of pesticides and their transformation products in soil at the manufacturing sites are "known unknowns." In this study, pesticides and their transformation products were screened in soil at 6 pesticide manufacturing sites across China using liquid and gas chromatography coupled with quadrupole time-of-flight mass spectrometry. The screening strategy can correctly identify 75% of 209 pesticides spiked at 50 ng g-1. A total of 212 pesticides were identified; 23.1% of pesticides detected were above 200 ng g-1, and the maximum concentration was 1.5 × 105 ng g-1. The risk quotients of 20% pesticides were greater than 1, and the maximum risk quotient of imidacloprid reached 6.3 × 104. The most recent site showed a larger number of pesticides with higher diversity, whereas older sites were dominated by organochlorine insecticides. The extended screen identified 163 transformation products with concentrations up to 6.6 × 104 ng g-1. Half of the transformation products had higher concentrations than their parent compounds, and metabolic ratios up to 371 were observed. The results of this study validate the prevalence of pesticides and their transformation products in soil at pesticide manufacturing sites. The results also highlight the importance of comprehensive screening at industrial sites and call for improved management and regulation of pesticide manufacturing, particularly for in-service facilities.
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Affiliation(s)
- Yufeng Tao
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Jing Liu
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Yiwen Xu
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Hang Liu
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Guiling Yang
- State Key Laboratory for Quality and Safety of Agro-products, Key Laboratory for Pesticide Residue Detection of Ministry of Agriculture, Laboratory (Hangzhou) for Risk Assessment of Agricultural Products of Ministry of Agriculture, Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang 310021, China
| | - Yan He
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Jianming Xu
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
| | - Zhijiang Lu
- Department of Environmental Science and Geology, Wayne State University, Detroit, MI 48201, United States.
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30
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Samanipour S, Choi P, O'Brien JW, Pirok BWJ, Reid MJ, Thomas KV. From Centroided to Profile Mode: Machine Learning for Prediction of Peak Width in HRMS Data. Anal Chem 2021; 93:16562-16570. [PMID: 34843646 PMCID: PMC8674881 DOI: 10.1021/acs.analchem.1c03755] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Centroiding is one of the major approaches used for size reduction of the data generated by high-resolution mass spectrometry. During centroiding, performed either during acquisition or as a pre-processing step, the mass profiles are represented by a single value (i.e., the centroid). While being effective in reducing the data size, centroiding also reduces the level of information density present in the mass peak profile. Moreover, each step of the centroiding process and their consequences on the final results may not be completely clear. Here, we present Cent2Prof, a package containing two algorithms that enables the conversion of the centroided data to mass peak profile data and vice versa. The centroiding algorithm uses the resolution-based mass peak width parameter as the first guess and self-adjusts to fit the data. In addition to the m/z values, the centroiding algorithm also generates the measured mass peak widths at half-height, which can be used during the feature detection and identification. The mass peak profile prediction algorithm employs a random-forest model for the prediction of mass peak widths, which is consequently used for mass profile reconstruction. The centroiding results were compared to the outputs of the MZmine-implemented centroiding algorithm. Our algorithm resulted in rates of false detection ≤5% while the MZmine algorithm resulted in 30% rate of false positive and 3% rate of false negative. The error in profile prediction was ≤56% independent of the mass, ionization mode, and intensity, which was 6 times more accurate than the resolution-based estimated values.
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Affiliation(s)
- Saer Samanipour
- Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands.,Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, Queensland 4102, Australia.,Norwegian Institute for Water Research (NIVA), Økernveien 94, Oslo 0579, Norway
| | - Phil Choi
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, Queensland 4102, Australia.,Water Unit, Health Protection Branch, Prevention Division, Queensland Department of Health, Brisbane, Queensland 4000, Australia
| | - Jake W O'Brien
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, Queensland 4102, Australia
| | - Bob W J Pirok
- Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands
| | - Malcolm J Reid
- Norwegian Institute for Water Research (NIVA), Økernveien 94, Oslo 0579, Norway
| | - Kevin V Thomas
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Woolloongabba, Queensland 4102, Australia
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31
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Chen Q, Zhang Y, Ye L, Gong S, Sun H, Su G. Identifying active xenobiotics in humans by use of a suspect screening technique coupled with lipidomic analysis. ENVIRONMENT INTERNATIONAL 2021; 157:106844. [PMID: 34455192 DOI: 10.1016/j.envint.2021.106844] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 08/16/2021] [Accepted: 08/20/2021] [Indexed: 06/13/2023]
Abstract
Lipidomic analysis has been proven to be a powerful technique to explore the underlying associations between xenobiotics and health status of organisms. Here, we established a strategy that combined the lipidomic analysis with high-throughput suspect contaminant screening technique with an aim to efficiently identify active xenobiotics in humans. Firstly, in the light of single liquid phase equilibrium of chloroform-methanol-water (15:14:2, v/v/v), we developed an efficient method that was able to simultaneously extract both polar and nonpolar lipids in serum samples. By use of this method, targeted and non-targeted lipid analyses were conducted for n = 120 serum samples collected from Wuxi city, China. Secondly, we established a suspect database containing 1450 contaminants that have been previously reported in human samples, and contaminants in this database were screened in the same batch of serum samples by use of high-resolution mass spectrometry (HR-MS). Thirdly, the underlying associations between suspect contaminants and lipids were explored and discussed, and we observed that levels of some lipids were statistically correlated with concentrations of numerous contaminants. Among these active contaminants, 23 ones were identified on the basis of HR MS1 and MS2 characteristics, and these contaminants belonged to the classes of phthalates, phenols, parabens, or perfluorinated compounds (PFCs). Three active xenobiotics were fully validated by comparison with authentic standards, and they were perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and diethyl phthalate (DEP). There were statistically significant changes in levels of triglyceride (TG), lysophosphocholine (LPC), and sphingomyelin (SM) as peak areas of xenobiotics increase. We also observed that, among target lipid molecules, 18:0 lysophosphatidylethanolamine (LPE(18:0)) was very sensitive, and this lipid responded to exposure of various contaminants. Our present study provides novel knowledge on potential alteration of lipid metabolism in humans following exposure to xenobiotics, and provides an efficient strategy for efficiently identifying active xenobiotics in humans.
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Affiliation(s)
- Qianyu Chen
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China
| | - Yayun Zhang
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China
| | - Langjie Ye
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China
| | - Shuai Gong
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China
| | - Hong Sun
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210009, China
| | - Guanyong Su
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China.
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Galani A, Alygizakis N, Aalizadeh R, Kastritis E, Dimopoulos MA, Thomaidis NS. Patterns of pharmaceuticals use during the first wave of COVID-19 pandemic in Athens, Greece as revealed by wastewater-based epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 798:149014. [PMID: 34325143 PMCID: PMC8294694 DOI: 10.1016/j.scitotenv.2021.149014] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/08/2021] [Accepted: 07/09/2021] [Indexed: 05/04/2023]
Abstract
Since 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), impaired public health with considerable morbidity and mortality due to the lack of vaccines and effective treatment. The severe disease mainly harmed adults with predisposing medical comorbidities (such as heart disease, hypertension, chronic lung disease), while it can occur in healthy individuals that may be asymptomatic. Wastewater-based Epidemiology (WBE), a non-invasive, objective, chemical tool was used to monitor and estimate the changes in drug's consumption and prescription patterns under normal conditions (2019) and under COVID-19 pandemic conditions (2020). NSAIDs, antihypertensives, diuretics, antiepileptics, antilipidemics, antibiotics, analgesics, antivirals, anticancer drugs, contrast iodinated drugs, antidiabetics, antiallergic drugs, antiulcers and other pharmaceuticals were studied in wastewater and revealed the application of various treatments during the first wave of the pandemic in Athens, Greece. Data were correlated with COVID-19 infection therapeutical plans. The result of the analysis revealed a remarkable increase for antiviral drugs (170%), hydroxychloroquine (387%), and antibiotics (57%), which were the most applied treatments against COVID-19 during the first wave in Greece. In agreement with related authorities urge, NSAIDs presented decrease (27%) during the first lockdown, while paracetamol demonstrated a remarkable increase (198%). The use levels for Angiotensin II receptor blockers such as valsartan, and co-administrated diuretics, such as hydrochlorothiazide, were reduced during 2020, by 32% and 26% respectively.
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Affiliation(s)
- Aikaterini Galani
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Nikiforos Alygizakis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Reza Aalizadeh
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Efstathios Kastritis
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 15528 Athens, Greece
| | - Meletios-Athanasios Dimopoulos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 15528 Athens, Greece
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
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33
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Singh RR, Lai A, Krier J, Kondić T, Diderich P, Schymanski EL. Occurrence and Distribution of Pharmaceuticals and Their Transformation Products in Luxembourgish Surface Waters. ACS ENVIRONMENTAL AU 2021; 1:58-70. [PMID: 37101936 PMCID: PMC10114791 DOI: 10.1021/acsenvironau.1c00008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Pharmaceuticals and their transformation products (TPs) are continuously released into the aquatic environment via anthropogenic activity. To expand knowledge on the presence of pharmaceuticals and their known TPs in Luxembourgish rivers, 92 samples collected during routine monitoring events between 2019 and 2020 were investigated using nontarget analysis. Water samples were concentrated using solid-phase extraction and then analyzed using liquid chromatography coupled to a high-resolution mass spectrometer. Suspect screening was performed using several open source computational tools and resources including Shinyscreen (https://git-r3lab.uni.lu/eci/shinyscreen/), MetFrag (https://msbi.ipb-halle.de/MetFrag/), PubChemLite (https://zenodo.org/record/4432124), and MassBank (https://massbank.eu/MassBank/). A total of 94 pharmaceuticals, 88 confirmed at a level 1 confidence (86 of which could be quantified, two compounds too low to be quantified) and six identified at level 2a, were found to be present in Luxembourg rivers. Pharmaceutical TPs (12) were also found at a level 2a confidence. The pharmaceuticals were present at median concentrations up to 214 ng/L, with caffeine having a median concentration of 1424 ng/L. Antihypertensive drugs (15), psychoactive drugs (15), and antimicrobials (eight) were the most detected groups of pharmaceuticals. A spatiotemporal analysis of the data revealed areas with higher concentrations of the pharmaceuticals, as well as differences in pharmaceutical concentrations between 2019 and 2020. The results of this work will help guide activities for improving water management in the country and set baseline data for continuous monitoring and screening efforts, as well as for further open data and software developments.
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Affiliation(s)
- Randolph R. Singh
- Luxembourg
Centre for Systems Biomedicine (LCSB), University
of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg
- IFREMER
(Institut Français de Recherche pour l’Exploitation
de la Mer), Laboratoire Biogéochimie
des Contaminants Organiques, Rue de l’Ile d’Yeu, BP 21105, Nantes 44311 Cedex 3, France
| | - Adelene Lai
- Luxembourg
Centre for Systems Biomedicine (LCSB), University
of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg
- Institute
for Inorganic and Analytical Chemistry, Friedrich-Schiller University, Lessing Strasse 8, 07743 Jena, Germany
| | - Jessy Krier
- Luxembourg
Centre for Systems Biomedicine (LCSB), University
of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg
| | - Todor Kondić
- Luxembourg
Centre for Systems Biomedicine (LCSB), University
of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg
| | - Philippe Diderich
- Administration
de la gestion de l’eau, Ministère
de l’Environnement, du Climat et du Développement durable, L-2918 Luxembourg, Luxembourg
| | - Emma L. Schymanski
- Luxembourg
Centre for Systems Biomedicine (LCSB), University
of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg
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34
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Wong JW, Wang J, Chang JS, Chow W, Carlson R, Rajski Ł, Fernández-Alba AR, Self R, Cooke WK, Lock CM, Mercer GE, Mastovska K, Schmitz J, Vaclavik L, Li L, Panawennage D, Pang GF, Zhou H, Miao S, Ho C, Lam TCH, To YBS, Zomer P, Hung YC, Lin SW, Liao CD, Culberson D, Taylor T, Wu Y, Yu D, Lim PL, Wu Q, Schirlé-Keller JPX, Williams SM, Johnson YS, Nason SL, Ammirata M, Eitzer BD, Willis M, Wyatt S, Kwon S, Udawatte N, Priyasantha K, Wan P, Filigenzi MS, Bakota EL, Sumarah MW, Renaud JB, Parinet J, Biré R, Hort V, Prakash S, Conway M, Pyke JS, Yang DHD, Jia W, Zhang K, Hayward DG. Multilaboratory Collaborative Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Liquid Chromatography-High-Resolution Accurate Mass Spectrometry for Pesticide Screening in Fruits and Vegetables. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:13200-13216. [PMID: 34709825 DOI: 10.1021/acs.jafc.1c04437] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Nontarget data acquisition for target analysis (nDATA) workflows using liquid chromatography-high-resolution accurate mass (LC-HRAM) spectrometry, spectral screening software, and a compound database have generated interest because of their potential for screening of pesticides in foods. However, these procedures and particularly the instrument processing software need to be thoroughly evaluated before implementation in routine analysis. In this work, 25 laboratories participated in a collaborative study to evaluate an nDATA workflow on high moisture produce (apple, banana, broccoli, carrot, grape, lettuce, orange, potato, strawberry, and tomato). Samples were extracted in each laboratory by quick, easy, cheap, effective, rugged, and safe (QuEChERS), and data were acquired by ultrahigh-performance liquid chromatography (UHPLC) coupled to a high-resolution quadrupole Orbitrap (QOrbitrap) or quadrupole time-of-flight (QTOF) mass spectrometer operating in full-scan mass spectrometry (MS) data-independent tandem mass spectrometry (LC-FS MS/DIA MS/MS) acquisition mode. The nDATA workflow was evaluated using a restricted compound database with 51 pesticides and vendor processing software. Pesticide identifications were determined by retention time (tR, ±0.5 min relative to the reference retention times used in the compound database) and mass errors (δM) of the precursor (RTP, δM ≤ ±5 ppm) and product ions (RTPI, δM ≤ ±10 ppm). The elution profiles of all 51 pesticides were within ±0.5 min among 24 of the participating laboratories. Successful screening was determined by false positive and false negative rates of <5% in unfortified (pesticide-free) and fortified (10 and 100 μg/kg) produce matrices. Pesticide responses were dependent on the pesticide, matrix, and instrument. The false negative rates were 0.7 and 0.1% at 10 and 100 μg/kg, respectively, and the false positive rate was 1.1% from results of the participating LC-HRAM platforms. Further evaluation was achieved by providing produce samples spiked with pesticides at concentrations blinded to the laboratories. Twenty-two of the 25 laboratories were successful in identifying all fortified pesticides (0-7 pesticides ranging from 5 to 50 μg/kg) for each produce sample (99.7% detection rate). These studies provide convincing evidence that the nDATA comprehensive approach broadens the screening capabilities of pesticide analyses and provide a platform with the potential to be easily extended to a larger number of other chemical residues and contaminants in foods.
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Affiliation(s)
- Jon W Wong
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 5001 Campus Drive, College Park, Maryland 20740, United States
| | - Jian Wang
- Calgary Laboratory, Canadian Food Inspection Agency, 3650 36th Street Northwest, Calgary, Alberta T2L 2L1, Canada
| | - James S Chang
- ThermoFisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
- Institute of Food Science and Technology, National Taiwan University, Taipei City 10617, Taiwan
| | - Willis Chow
- Calgary Laboratory, Canadian Food Inspection Agency, 3650 36th Street Northwest, Calgary, Alberta T2L 2L1, Canada
| | - Roland Carlson
- Center for Analytical Chemistry, California Department of Food and Agriculture, 3292 Meadowview Road, Sacramento, California 95832, United States
| | - Łukasz Rajski
- European Union Reference Laboratory for Pesticide Residues in Fruits and Vegetables, University of Almería, Agrifood Campus of International Excellence (ceiA3), Ctra. Sacramento S/N, La Cañada de San Urbano, 40120 Almería, Spain
| | - Amadeo R Fernández-Alba
- European Union Reference Laboratory for Pesticide Residues in Fruits and Vegetables, University of Almería, Agrifood Campus of International Excellence (ceiA3), Ctra. Sacramento S/N, La Cañada de San Urbano, 40120 Almería, Spain
| | - Randy Self
- Pacific Northwest Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, 22201 23rd Drive SE, Bothell, Washington 98021, United States
| | - William K Cooke
- Pacific Northwest Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, 22201 23rd Drive SE, Bothell, Washington 98021, United States
| | - Christopher M Lock
- Pacific Northwest Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, 22201 23rd Drive SE, Bothell, Washington 98021, United States
| | - Gregory E Mercer
- Pacific Northwest Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, 22201 23rd Drive SE, Bothell, Washington 98021, United States
| | - Katerina Mastovska
- Eurofins Food Chemistry Testing, 6304 Ronald Reagan Avenue, Madison, Wisconsin 53704, United States
| | - John Schmitz
- Eurofins Food Chemistry Testing, 6304 Ronald Reagan Avenue, Madison, Wisconsin 53704, United States
| | - Lukas Vaclavik
- Eurofins Food Chemistry Testing, 6304 Ronald Reagan Avenue, Madison, Wisconsin 53704, United States
| | - Lingyun Li
- Wadsworth Center, New York State Department of Health, Empire State Plaza, Albany, New York 12237, United States
| | - Deepika Panawennage
- Wadsworth Center, New York State Department of Health, Empire State Plaza, Albany, New York 12237, United States
| | - Guo-Fang Pang
- Chinese Academy of Inspection and Quarantine, No. 11 Ronghua Nanlu, Beijing Economic Technological Development Area, Beijing 100176, People's Republic of China
| | - Heng Zhou
- National Medical Products Administration Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, 1500 Zhangheng Road, Shanghai 201203, People's Republic of China
| | - Shui Miao
- National Medical Products Administration Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, 1500 Zhangheng Road, Shanghai 201203, People's Republic of China
| | - Clare Ho
- Government Laboratory, Analytical and Advisory Services Division, 7/F, Ho Man Tin Government Offices, 88 Chung Hau Street, Ho Man Tin, Kowloon, Hong Kong Special Administrative Region, People's Republic of China
| | - Tony Chong-Ho Lam
- Government Laboratory, Analytical and Advisory Services Division, 7/F, Ho Man Tin Government Offices, 88 Chung Hau Street, Ho Man Tin, Kowloon, Hong Kong Special Administrative Region, People's Republic of China
| | - Yim-Bun Sze To
- Government Laboratory, Analytical and Advisory Services Division, 7/F, Ho Man Tin Government Offices, 88 Chung Hau Street, Ho Man Tin, Kowloon, Hong Kong Special Administrative Region, People's Republic of China
| | - Paul Zomer
- Wageningen Food Safety Research, Wageningen University and Research, P.O. Box 230, 6708 AE Wageningen, The Netherlands
| | - Yu-Ching Hung
- Division of Research and Analysis, Taiwan Food and Drug Administration, 161-2 Kunyang Street, Nangang, Taipei 11561, Taiwan
| | - Shu-Wei Lin
- Division of Research and Analysis, Taiwan Food and Drug Administration, 161-2 Kunyang Street, Nangang, Taipei 11561, Taiwan
| | - Chia-Ding Liao
- Division of Research and Analysis, Taiwan Food and Drug Administration, 161-2 Kunyang Street, Nangang, Taipei 11561, Taiwan
| | - Danny Culberson
- North Carolina Department of Agriculture and Consumer Services, 4000 Reedy Creek Road, Raleigh, North Carolina 27607, United States
| | - Tameka Taylor
- Analytical Chemistry Laboratory, Office of Pesticide Programs, US Environmental Protection Agency, 701 Mapes Road, Ft. Meade, Maryland 20755-5350, United States
| | - Yuansheng Wu
- National Centre for Food Science, Singapore Food Agency, 10 Perahu Road, Singapore 718837
| | - Dingyi Yu
- National Centre for Food Science, Singapore Food Agency, 10 Perahu Road, Singapore 718837
| | - Poh Leong Lim
- National Centre for Food Science, Singapore Food Agency, 10 Perahu Road, Singapore 718837
| | - Qiong Wu
- National Centre for Food Science, Singapore Food Agency, 10 Perahu Road, Singapore 718837
| | - Jean-Paul X Schirlé-Keller
- Laboratory Services Division, Minnesota Department of Agriculture, 601 North Robert Street, St. Paul, Minnesota 55155-2531, United States
| | - Sheldon M Williams
- Laboratory Services Division, Minnesota Department of Agriculture, 601 North Robert Street, St. Paul, Minnesota 55155-2531, United States
| | - Yoko S Johnson
- Laboratory Services Division, Minnesota Department of Agriculture, 601 North Robert Street, St. Paul, Minnesota 55155-2531, United States
| | - Sara L Nason
- Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06511, United States
| | - Michael Ammirata
- Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06511, United States
| | - Brian D Eitzer
- Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06511, United States
| | - Michelle Willis
- Virginia Division of Consolidated Laboratory Services, 600 5th Street, Richmond, Virginia 23219, United States
| | - Shane Wyatt
- Virginia Division of Consolidated Laboratory Services, 600 5th Street, Richmond, Virginia 23219, United States
| | - SoYoung Kwon
- Pesticide Laboratories at the Office of Indiana State Chemist, 175 South University Street, West Lafayette, Indiana 47907, United States
| | - Nayane Udawatte
- Pesticide Laboratories at the Office of Indiana State Chemist, 175 South University Street, West Lafayette, Indiana 47907, United States
| | - Kandalama Priyasantha
- Pesticide Laboratories at the Office of Indiana State Chemist, 175 South University Street, West Lafayette, Indiana 47907, United States
| | - Ping Wan
- Pesticide Laboratories at the Office of Indiana State Chemist, 175 South University Street, West Lafayette, Indiana 47907, United States
| | - Michael S Filigenzi
- California Animal Health and Food Safety Laboratory, University of California, Davis, 620 West Health Sciences Drive, Davis, California 95616, United States
| | - Erica L Bakota
- Kansas City Laboratory, Office of Regulatory Affairs, U.S. Food and Drug Administration, 11510 West 80th Street, Lenexa, Kansas 66214, United States
| | - Mark W Sumarah
- Agriculture and Agri-Food Canada, 1391 Sandford Street, London, Ontario N5V 4T3, Canada
| | - Justin B Renaud
- Agriculture and Agri-Food Canada, 1391 Sandford Street, London, Ontario N5V 4T3, Canada
| | - Julien Parinet
- Laboratory for Food Safety, ANSES, Université Paris-Est, F-94701 Maisons-Alfort, France
| | - Ronel Biré
- Laboratory for Food Safety, ANSES, Université Paris-Est, F-94701 Maisons-Alfort, France
| | - Vincent Hort
- Laboratory for Food Safety, ANSES, Université Paris-Est, F-94701 Maisons-Alfort, France
| | - Shristi Prakash
- OMIC USA Inc., 3344 Northwest Industrial Street, Portland, Oregon 97210, United States
| | - Michael Conway
- OMIC USA Inc., 3344 Northwest Industrial Street, Portland, Oregon 97210, United States
| | - James S Pyke
- Agilent Technologies Inc., 5301 Stevens Creek Boulevard, Santa Clara, California 95051, United States
| | - Dan-Hui Dorothy Yang
- Agilent Technologies Inc., 5301 Stevens Creek Boulevard, Santa Clara, California 95051, United States
| | - Wei Jia
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, People's Republic of China
| | - Kai Zhang
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 5001 Campus Drive, College Park, Maryland 20740, United States
| | - Douglas G Hayward
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, 5001 Campus Drive, College Park, Maryland 20740, United States
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Jacob P, Wang R, Ching C, Helbling DE. Evaluation, optimization, and application of three independent suspect screening workflows for the characterization of PFASs in water. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2021; 23:1554-1565. [PMID: 34550138 DOI: 10.1039/d1em00286d] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Suspect screening is a valuable tool for characterizing per- and polyfluoroalkyl substances (PFASs) in environmental media. Although a variety of data mining tools have been developed and applied for suspect screening of PFAS, few suspect screening workflows have undergone a comprehensive performance evaluation or optimization. The goals of this research were to: (1) evaluate and optimize three independent suspect screening workflows for the detection of PFASs in water samples; and (2) apply the optimized suspect screening workflows to an environmental sample to determine the extent to which suspect screening results converge. We evaluated and optimized suspect screening workflows using Compound Discoverer v3.2, enviMass v4.2, and FluoroMatch v2.4 using test samples containing 33 target PFASs. The average sensitivity (Sen) and selectivity (Sel) for each workflow across the test samples was: Compound Discoverer Sen = 71%, Sel = 85%; enviMass Sen = 89%, Sel = 80%; FluoroMatch Sen = 51%, Sel = 82%. We then applied the optimized workflows to a contaminated groundwater sample containing an unknown number of PFASs. Each workflow managed to annotate unique PFASs that were not annotated by the other workflows including 2 by Compound Discoverer and 19 each by enviMass and FluoroMatch. Thirty-two enviMass hits and 28 of the Compound Discoverer and FluoroMatch hits were annotated by at least one of the other workflows. Sixteen PFASs were annotated by all three of the optimized workflows. This work provides a basis for conducting suspect screening for PFASs that will lead to more consistent reporting of suspect screening data.
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Affiliation(s)
- Paige Jacob
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA.
| | - Ri Wang
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA.
| | - Casey Ching
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA.
| | - Damian E Helbling
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA.
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36
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Guillevic M, Guillevic A, Vollmer MK, Schlauri P, Hill M, Emmenegger L, Reimann S. Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons. J Cheminform 2021; 13:78. [PMID: 34607604 PMCID: PMC8491408 DOI: 10.1186/s13321-021-00544-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 08/21/2021] [Indexed: 11/29/2022] Open
Abstract
Background Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition. For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS. Results Based on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in \documentclass[12pt]{minimal}
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\begin{document}$$\sim$$\end{document}∼40% of EI spectra. Our method has been trained and validated on >50 halocarbons and hydrocarbons, with 3–20 atoms and molar masses of 30–330 g mol\documentclass[12pt]{minimal}
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\begin{document}$$^{-1}$$\end{document}-1, measured with a mass resolution of approx. 3500. For >90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected). Conclusions Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds. Supplementary Information The online version contains supplementary material available at 10.1186/s13321-021-00544-w.
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Affiliation(s)
- Myriam Guillevic
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland.
| | - Aurore Guillevic
- Université de Lorraine, CNRS, Inria, LORIA, 54000, Nancy, France
| | - Martin K Vollmer
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland
| | - Paul Schlauri
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland
| | - Matthias Hill
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland
| | - Lukas Emmenegger
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland
| | - Stefan Reimann
- Laboratory for Air Pollution /Environmental Technology, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600, Dübendorf, Switzerland
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37
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Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis. Sci Data 2021; 8:223. [PMID: 34429429 PMCID: PMC8384892 DOI: 10.1038/s41597-021-01002-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 07/12/2021] [Indexed: 11/09/2022] Open
Abstract
Non-target analysis (NTA) employing high-resolution mass spectrometry is a commonly applied approach for the detection of novel chemicals of emerging concern in complex environmental samples. NTA typically results in large and information-rich datasets that require computer aided (ideally automated) strategies for their processing and interpretation. Such strategies do however raise the challenge of reproducibility between and within different processing workflows. An effective strategy to mitigate such problems is the implementation of inter-laboratory studies (ILS) with the aim to evaluate different workflows and agree on harmonized/standardized quality control procedures. Here we present the data generated during such an ILS. This study was organized through the Norman Network and included 21 participants from 11 countries. A set of samples based on the passive sampling of drinking water pre and post treatment was shipped to all the participating laboratories for analysis, using one pre-defined method and one locally (i.e. in-house) developed method. The data generated represents a valuable resource (i.e. benchmark) for future developments of algorithms and workflows for NTA experiments. Measurement(s) | chemical • drinking water | Technology Type(s) | high resolution mass spectrometry • non-target analysis • Interlaboratory | Factor Type(s) | method | Sample Characteristic - Environment | laboratory environment |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.15028665
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38
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Menger F, Boström G, Jonsson O, Ahrens L, Wiberg K, Kreuger J, Gago-Ferrero P. Identification of Pesticide Transformation Products in Surface Water Using Suspect Screening Combined with National Monitoring Data. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:10343-10353. [PMID: 34291901 PMCID: PMC8383268 DOI: 10.1021/acs.est.1c00466] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 06/21/2021] [Accepted: 07/04/2021] [Indexed: 06/13/2023]
Abstract
Pesticides are widespread anthropogenic chemicals and well-known environmental contaminants of concern. Much less is known about transformation products (TPs) of pesticides and their presence in the environment. We developed a novel suspect screening approach for not well-explored pesticides (n = 16) and pesticide TPs (n = 242) by integrating knowledge from national monitoring with high-resolution mass spectrometry data. Weekly time-integrated samples were collected in two Swedish agricultural streams using the novel Time-Integrating, MicroFlow, In-line Extraction (TIMFIE) sampler. The integration of national monitoring data in the screening approach increased the number of prioritized compounds approximately twofold (from 23 to 42). Ultimately, 11 pesticide TPs were confirmed by reference standards and 12 TPs were considered tentatively identified with varying levels of confidence. Semiquantification of the newly confirmed TPs indicated higher concentrations than their corresponding parent pesticides in some cases, which highlights concerns related to (unknown) pesticide TPs in the environment. Some TPs were present in the environment without co-occurrence of their corresponding parent compounds, indicating higher persistency or mobility of the identified TPs. This study showcased the benefits of integrating monitoring knowledge in this type of studies, with advantages for suspect screening performance and the possibility to increase relevance of future monitoring programs.
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Affiliation(s)
- Frank Menger
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Gustaf Boström
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Ove Jonsson
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Lutz Ahrens
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Karin Wiberg
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Jenny Kreuger
- Department
of Aquatic Sciences and Assessment, Swedish
University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Pablo Gago-Ferrero
- Department
of Environmental Chemistry, Institute of Environmental Assessment
and Water Research—Severo Ochoa Excellence Center (IDAEA), Spanish Council of Scientific Research (CSIC), Jordi Girona 18−26, 08034 Barcelona, Spain
- Catalan
Institute for Water Research (ICRA), Carrer Emili Grahit 101, 17003 Girona, Spain
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Meijer J, Lamoree M, Hamers T, Antignac JP, Hutinet S, Debrauwer L, Covaci A, Huber C, Krauss M, Walker DI, Schymanski EL, Vermeulen R, Vlaanderen J. An annotation database for chemicals of emerging concern in exposome research. ENVIRONMENT INTERNATIONAL 2021; 152:106511. [PMID: 33773387 DOI: 10.1016/j.envint.2021.106511] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/03/2021] [Accepted: 03/06/2021] [Indexed: 05/18/2023]
Abstract
BACKGROUND Chemicals of Emerging Concern (CECs) include a very wide group of chemicals that are suspected to be responsible for adverse effects on health, but for which very limited information is available. Chromatographic techniques coupled with high-resolution mass spectrometry (HRMS) can be used for non-targeted screening and detection of CECs, by using comprehensive annotation databases. Establishing a database focused on the annotation of CECs in human samples will provide new insight into the distribution and extent of exposures to a wide range of CECs in humans. OBJECTIVES This study describes an approach for the aggregation and curation of an annotation database (CECscreen) for the identification of CECs in human biological samples. METHODS The approach consists of three main parts. First, CECs compound lists from various sources were aggregated and duplications and inorganic compounds were removed. Subsequently, the list was curated by standardization of structures to create "MS-ready" and "QSAR-ready" SMILES, as well as calculation of exact masses (monoisotopic and adducts) and molecular formulas. The second step included the simulation of Phase I metabolites. The third and final step included the calculation of QSAR predictions related to physicochemical properties, environmental fate, toxicity and Absorption, Distribution, Metabolism, Excretion (ADME) processes and the retrieval of information from the US EPA CompTox Chemicals Dashboard. RESULTS All CECscreen database and property files are publicly available (DOI: https://doi.org/10.5281/zenodo.3956586). In total, 145,284 entries were aggregated from various CECs data sources. After elimination of duplicates and curation, the pipeline produced 70,397 unique "MS-ready" structures and 66,071 unique QSAR-ready structures, corresponding with 69,526 CAS numbers. Simulation of Phase I metabolites resulted in 306,279 unique metabolites. QSAR predictions could be performed for 64,684 of the QSAR-ready structures, whereas information was retrieved from the CompTox Chemicals Dashboard for 59,739 CAS numbers out of 69,526 inquiries. CECscreen is incorporated in the in silico fragmentation approach MetFrag. DISCUSSION The CECscreen database can be used to prioritize annotation of CECs measured in non-targeted HRMS, facilitating the large-scale detection of CECs in human samples for exposome research. Large-scale detection of CECs can be further improved by integrating the present database with resources that contain CECs (metabolites) and meta-data measurements, further expansion towards in silico and experimental (e.g., MassBank) generation of MS/MS spectra, and development of bioinformatics approaches capable of using correlation patterns in the measured chemical features.
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Affiliation(s)
- Jeroen Meijer
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Department Environment & Health, Vrije Universiteit, Amsterdam, the Netherlands
| | - Marja Lamoree
- Department Environment & Health, Vrije Universiteit, Amsterdam, the Netherlands
| | - Timo Hamers
- Department Environment & Health, Vrije Universiteit, Amsterdam, the Netherlands
| | | | | | - Laurent Debrauwer
- Toxalim (Research Centre in Food Toxicology), Toulouse University, INRAE, ENVT, INP-Purpan, Toulouse, France; Metatoul-AXIOM Platform, National Infrastructure for Metabolomics and Fluxomics: MetaboHUB, Toxalim, INRAE, Toulouse, France
| | - Adrian Covaci
- Toxicological Center, University of Antwerp, Belgium
| | - Carolin Huber
- Department Effect-Directed Analysis, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Martin Krauss
- Department Effect-Directed Analysis, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Douglas I Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine, Mount Sinai, New York, NY, USA
| | - Emma L Schymanski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
| | - Jelle Vlaanderen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands.
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A new RP-HPLC method as an auxiliary tool for optimization of sample preparation procedures for tracing of PPCPs of different hydrophilicities. ACTA PHARMACEUTICA (ZAGREB, CROATIA) 2021; 71:305-315. [PMID: 33151170 DOI: 10.2478/acph-2021-0014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/18/2020] [Indexed: 01/19/2023]
Abstract
Recently, pharmaceutical and personal care products (PPCPs) have received considerable attention because of their increasing use. Analysis of PPCPs presents a significant analytical challenge, with high-performance liquid chromatography (HPLC) in reversed-phase mode, as the most widely used analytical technique. To facilitate the optimization of the procedures that are applied in the early stages of sample preparation, a simple and fast HPLC method is proposed in this work for the separation of some PPCPs with a wide range of hydrophilicity. Two columns were evaluated (Atlantis dC18 and Discovery HS F5); as for mobile phases: a formate buffer (40 mmol L-1, pH 4) and methanol were tested in a gradient mode. The fluorinated column allowed better separation in a shorter time and better resolution for all analytes (Rs > 1). The proposed method delivered good performance for the tracing of PPCPs and is a suitable alternative to traditional C18-based HPLC methods.
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41
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Zhou Y, Yuan G, Cong Z, Wang X. Priorities for the sustainable development of the ecological environment on the Tibetan Plateau. FUNDAMENTAL RESEARCH 2021. [DOI: 10.1016/j.fmre.2021.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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42
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Sabater-Liesa L, Montemurro N, Ginebreda A, Barceló D, Eichhorn P, Pérez S. Retrospective mass spectrometric analysis of wastewater-fed mesocosms to assess the degradation of drugs and their human metabolites. JOURNAL OF HAZARDOUS MATERIALS 2021; 408:124984. [PMID: 33418519 DOI: 10.1016/j.jhazmat.2020.124984] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 12/09/2020] [Accepted: 12/24/2020] [Indexed: 06/12/2023]
Abstract
Temporary rivers become dependent on wastewater effluent for base flows, which severely impacts river ecosystems through exposure to elevated levels of nutrients, dissolved organic matter, and organic micropollutants. However, biodegradation processes occurring in these rivers can be enhanced by wastewater bacteria/biofilms. Here, we evaluated the attenuation of pharmaceuticals and their human metabolites performing retrospective analysis of 120 compounds (drugs, their metabolites and transformation products) in mesocosm channels loaded with wastewater effluents twice a week for a period of 31 days. Eighteen human metabolites and seven biotransformation products were identified with high level of confidence. Compounds were classified into five categories. Type-A: recalcitrant drugs and metabolites (diclofenac, carbamazepine and venlafaxine); Type-B: degradable drugs forming transformation products (TPs) (atenolol, sitagliptin, and valsartan); Type-C: drugs for which no known human metabolites or TPs were detected (atorvastatin, azithromycin, citalopram, clarithromycin, diltiazem, eprosartan, fluconazole, ketoprofen, lamotrigine, lormetazepam, metformin, telmisartan, and trimethoprim); Type-D: recalcitrant drug metabolites (4-hydroxy omeprazole sulfide, erythro/threo-hydrobupropion, and zolpidem carboxylic acid); Type-E: unstable metabolites whose parent drug was not detectable (norcocaine, benzolylecgonine, and erythromycin A enol ether). Noteworthy was the valsartan acid formation from valsartan with transient formation of TP-336.
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Affiliation(s)
- Laia Sabater-Liesa
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
| | - Nicola Montemurro
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
| | - Antoni Ginebreda
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
| | - Damià Barceló
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
| | - Peter Eichhorn
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
| | - Sandra Pérez
- ENFOCHEM, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, Barcelona 08034, Spain
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Hernández-Mesa M, Le Bizec B, Dervilly G. Metabolomics in chemical risk analysis – A review. Anal Chim Acta 2021; 1154:338298. [DOI: 10.1016/j.aca.2021.338298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/14/2022]
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Suzuki S, Hasegawa A, Uebori M, Shinomiya M, Yoshida Y, Ookubo K, Takino M, Hasegawa H, Takazawa M, Takemine S. Non-target environmental analysis by liquid chromatography/high-resolution mass spectrometry with a product ion and neutral loss database. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4695. [PMID: 33410206 DOI: 10.1002/jms.4695] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 11/07/2020] [Accepted: 11/10/2020] [Indexed: 06/12/2023]
Abstract
Despite the increasing detection of emerging substances in the environment, the identity of most are left unknown due to the lack of efficient identification methods. We developed a non-target analysis method for identifying unknown substances in the environment by liquid chromatography/high-resolution mass spectrometry (LC/HRMS) with a product ion and neutral loss database (PNDB). The present analysis describes an elucidation method with elemental compositions of the molecules, product ions, and corresponding neutral losses of the unknown substance: (1) with the molecular formula, possible molecular structures are retrieved from two chemical structure databases (PubChem and ChemSpider); then (2) with the elemental compositions of product ions and neutral losses, possible partial structures are retrieved from the PNDB; and finally, (3) molecular structures that match the possible partial structures are listed in order of number of hits. A molecular structure with a higher number of hits is more similar to the structure of the analyzed substance. The performance of the non-target method was evaluated by simulated analysis of 150 LC/HRMS spectra registered in MassBank. First, all substances of the same mass data (41/41) and 68% (39/57) of the mass data of the same substances not registered in the PNDB were elucidated. It was demonstrated that 14% (7/52) and 31% (16/52) of the substances with no mass spectral data registered in the PNDB were obtained at the first and within the fifth place, respectively. Owing to the fact that 10 of the total hits occurred in product ions and neutral losses, almost 50% of the substances evaluated with this method were placed at the top 4 positions in the similarity ranking. Importantly, the proposed method is effective for analyzing mass spectral data that has not been registered in the PNDB and thus is expected to be used for a variety of non-target analyses.
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Affiliation(s)
- Shigeru Suzuki
- Graduate School of Bioscience and Biotechnology, Chubu University, Kasugai, Japan
| | - Atsuko Hasegawa
- Environmental Conservation Division, Kanagawa Environmental Research Center, 1-3-39, Shinomiya,, Hiratsuka, 254-0014, Japan
| | - Michiko Uebori
- Graduate School of Bioscience and Biotechnology, Chubu University, Kasugai, Japan
| | - Miho Shinomiya
- School of Health and Social Services, Saitama Prefectural University, 820 Sannomiya, Koshigaya, 343-8540, Japan
| | - Yasuko Yoshida
- Environment, Health and Safety Division, Sumica Chemical Analysis Service, Ltd., Sumitomo Fudosan Hongo Building 9F, 22-5, Hongo 3-chome, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Kaori Ookubo
- Physics and Chemistry Research and Investigate Division, Saga Prefectural Institute of Public Health and Pharmaceutical Research, 1-20 Hacchonawatemachi, Saga, 849-0925, Japan
| | - Masahiko Takino
- Chromatography and Mass Spectrometry Division, Agilent Technologies Japan Ltd., 9-1 Takakura-machi, Hachioji, 192-0033, Japan
| | - Hitomi Hasegawa
- Water Quality Division, Nagoya City Environmental Science Research Institute, 5-16-8 Toyoda, Minami-ku, Nagoya, 457-0841, Japan
| | - Mari Takazawa
- Graduate School of Bioscience and Biotechnology, Chubu University, Kasugai, Japan
- Water Environment Research Group, Public Works Research Institute, 1-6 Minamihara, Tsukuba, 305-8516, Japan
| | - Shusuke Takemine
- Chemical Substance Team, Center for Environmental Science in Saitama, 914 Oaza-Kamitanadare, Kisai-machi, Kazo, 347-0115, Japan
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Günthardt BF, Wettstein FE, Hollender J, Singer H, Härri J, Scheringer M, Hungerbühler K, Bucheli TD. Retrospective HRMS Screening and Dedicated Target Analysis Reveal a Wide Exposure to Pyrrolizidine Alkaloids in Small Streams. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:1036-1044. [PMID: 33372520 DOI: 10.1021/acs.est.0c06411] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Pyrrolizidine alkaloids (PAs) are found to be toxic pollutants emitted into the environment by numerous plant species, resulting in contamination. In this article, we investigate the occurrence of PAs in the aquatic environment of small Swiss streams combining two different approaches. Pyrrolizidine alkaloids (PAs) are toxic secondary metabolites produced by numerous plant species. Although they were classified as persistent and mobile and found to be emitted into the environment, their occurrence in surface waters is largely unknown. Therefore, we performed a retrospective data analysis of two extensive HRMS campaigns each covering five small streams in Switzerland over the growing season. All sites were contaminated with up to 12 individual PAs and temporal detection frequencies between 36 and 87%. Individual PAs were in the low ng/L range, but rain-induced maximal total PA concentrations reached almost 100 ng/L in late spring and summer. Through PA patterns in water and plants, several species were tentatively identified as the source of contamination, with Senecio spp. and Echium vulgare being the most important. Additionally, two streams were monitored, and PAs were quantified with a newly developed, faster, and more sensitive LC-MS/MS method to distinguish different plant-based and indirect human PA sources. A distinctly different PA fingerprint in aqueous plant extracts pointed to invasive Senecio inaequidens as the main source of the surface water contamination at these sites. Results indicate that PA loads may increase if invasive species are sufficiently abundant.
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Affiliation(s)
- Barbara F Günthardt
- Environmental Analytics, Agroscope, Reckenholzstrasse 191, Zürich 8046, Switzerland
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Universitätsstrasse 16, Zürich 8092, Switzerland
| | - Felix E Wettstein
- Environmental Analytics, Agroscope, Reckenholzstrasse 191, Zürich 8046, Switzerland
| | - Juliane Hollender
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Universitätsstrasse 16, Zürich 8092, Switzerland
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, Dübendorf 8600, Switzerland
| | - Heinz Singer
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, Dübendorf 8600, Switzerland
| | - Jana Härri
- Environmental Analytics, Agroscope, Reckenholzstrasse 191, Zürich 8046, Switzerland
- Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Universitätsstrasse 16, Zürich 8092, Switzerland
| | - Martin Scheringer
- Institute for Chemical and Bioengineering, ETH Zurich, Wolfgang-Pauli-Strasse 10, Zürich 8093, Switzerland
- RECETOX, Masaryk University, Kamenice 753/5, Brno 625 00, Czech Republic
| | - Konrad Hungerbühler
- Institute for Chemical and Bioengineering, ETH Zurich, Wolfgang-Pauli-Strasse 10, Zürich 8093, Switzerland
| | - Thomas D Bucheli
- Environmental Analytics, Agroscope, Reckenholzstrasse 191, Zürich 8046, Switzerland
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Dodds JN, Alexander NLM, Kirkwood KI, Foster MR, Hopkins ZR, Knappe DRU, Baker ES. From Pesticides to Per- and Polyfluoroalkyl Substances: An Evaluation of Recent Targeted and Untargeted Mass Spectrometry Methods for Xenobiotics. Anal Chem 2021; 93:641-656. [PMID: 33136371 PMCID: PMC7855838 DOI: 10.1021/acs.analchem.0c04359] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- James N Dodds
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Nancy Lee M Alexander
- Department of Civil, Construction, & Environmental Engineering, North Carolina State University, Raleigh, North Carolina 27607, United States
| | - Kaylie I Kirkwood
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - MaKayla R Foster
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Zachary R Hopkins
- Department of Civil, Construction, & Environmental Engineering, North Carolina State University, Raleigh, North Carolina 27607, United States
| | - Detlef R U Knappe
- Department of Civil, Construction, & Environmental Engineering, North Carolina State University, Raleigh, North Carolina 27607, United States
| | - Erin S Baker
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
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Wawryk NJP, Craven CB, Blackstock LKJ, Li XF. New methods for identification of disinfection byproducts of toxicological relevance: Progress and future directions. J Environ Sci (China) 2021; 99:151-159. [PMID: 33183692 DOI: 10.1016/j.jes.2020.06.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 06/08/2020] [Accepted: 06/16/2020] [Indexed: 06/11/2023]
Abstract
Disinfection byproducts (DBPs) represent a ubiquitous source of chemical exposure in disinfected water. While over 700 DBPs have been identified, the drivers of toxicity remain poorly understood. Additionally, ever evolving water treatment practices have led to a continually growing list of DBPs. Advancement of analytical technologies have enabled the identification of new classes of DBPs and the quantification of these chemically diverse sets of DBPs. Here we summarize advances in new workflows for DBP analysis, including sample preparation, chromatographic separation with mass spectrometry (MS) detection, and data processing. To aid in the selection of techniques for future studies, we discuss necessary considerations for each step in the strategy. This review focuses on how each step of a workflow can be optimized to capture diverse classes of DBPs within a single method. Additionally, we highlight new MS-based approaches that can be powerful for identifying novel DBPs of toxicological relevance. We discuss current challenges and provide perspectives on future research directions with respect to studying new DBPs of toxicological relevance. As analytical technologies continue to advance, new strategies will be increasingly used to analyze complex DBPs produced in different treatment processes with the aim to identify potential drivers of toxicity.
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Affiliation(s)
- Nicholas J P Wawryk
- Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, T6G 2G3, Canada
| | - Caley B Craven
- Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, T6G 2G3, Canada
| | - Lindsay K Jmaiff Blackstock
- Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, T6G 2G3, Canada
| | - Xing-Fang Li
- Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, T6G 2G3, Canada.
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48
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An assessment of quality assurance/quality control efforts in high resolution mass spectrometry non-target workflows for analysis of environmental samples. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.116063] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Celma A, Sancho JV, Schymanski EL, Fabregat-Safont D, Ibáñez M, Goshawk J, Barknowitz G, Hernández F, Bijlsma L. Improving Target and Suspect Screening High-Resolution Mass Spectrometry Workflows in Environmental Analysis by Ion Mobility Separation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:15120-15131. [PMID: 33207875 DOI: 10.1021/acs.est.0c05713] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Currently, the most powerful approach to monitor organic micropollutants (OMPs) in environmental samples is the combination of target, suspect, and nontarget screening strategies using high-resolution mass spectrometry (HRMS). However, the high complexity of sample matrices and the huge number of OMPs potentially present in samples at low concentrations pose an analytical challenge. Ion mobility separation (IMS) combined with HRMS instruments (IMS-HRMS) introduces an additional analytical dimension, providing extra information, which facilitates the identification of OMPs. The collision cross-section (CCS) value provided by IMS is unaffected by the matrix or chromatographic separation. Consequently, the creation of CCS databases and the inclusion of ion mobility within identification criteria are of high interest for an enhanced and robust screening strategy. In this work, a CCS library for IMS-HRMS, which is online and freely available, was developed for 556 OMPs in both positive and negative ionization modes using electrospray ionization. The inclusion of ion mobility data in widely adopted confidence levels for identification in environmental reporting is discussed. Illustrative examples of OMPs found in environmental samples are presented to highlight the potential of IMS-HRMS and to demonstrate the additional value of CCS data in various screening strategies.
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Affiliation(s)
- Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Juan V Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Emma L Schymanski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6, Avenue du Swing, L-4367 Belvaux, Luxembourg
| | - David Fabregat-Safont
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - María Ibáñez
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Jeff Goshawk
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow, Cheshire SK9 4AX, U.K
| | - Gitte Barknowitz
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow, Cheshire SK9 4AX, U.K
| | - Félix Hernández
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
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50
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Beyer J, Goksøyr A, Hjermann DØ, Klungsøyr J. Environmental effects of offshore produced water discharges: A review focused on the Norwegian continental shelf. MARINE ENVIRONMENTAL RESEARCH 2020; 162:105155. [PMID: 32992224 DOI: 10.1016/j.marenvres.2020.105155] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 09/15/2020] [Accepted: 09/17/2020] [Indexed: 06/11/2023]
Abstract
Produced water (PW), a large byproduct of offshore oil and gas extraction, is reinjected to formations or discharged to the sea after treatment. The discharges contain dispersed crude oil, polycyclic aromatic hydrocarbons (PAHs), alkylphenols (APs), metals, and many other constituents of environmental relevance. Risk-based regulation, greener offshore chemicals and improved cleaning systems have reduced environmental risks of PW discharges, but PW is still the largest operational source of oil pollution to the sea from the offshore petroleum industry. Monitoring surveys find detectable exposures in caged mussel and fish several km downstream from PW outfalls, but biomarkers indicate only mild acute effects in these sentinels. On the other hand, increased concentrations of DNA adducts are found repeatedly in benthic fish populations, especially in haddock. It is uncertain whether increased adducts could be a long-term effect of sediment contamination due to ongoing PW discharges, or earlier discharges of oil-containing drilling waste. Another concern is uncertainty regarding the possible effect of PW discharges in the sub-Arctic Southern Barents Sea. So far, research suggests that sub-arctic species are largely comparable to temperate species in their sensitivity to PW exposure. Larval deformities and cardiac toxicity in fish early life stages are among the biomarkers and adverse outcome pathways that currently receive much attention in PW effect research. Herein, we summarize the accumulated ecotoxicological knowledge of offshore PW discharges and highlight some key remaining knowledge needs.
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Affiliation(s)
- Jonny Beyer
- Norwegian Institute for Water Research (NIVA), Oslo, Norway.
| | - Anders Goksøyr
- Department of Biological Sciences, University of Bergen, Norway; Institute of Marine Research (IMR), Bergen, Norway
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