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Aggerbeck MR, Frøkjær EE, Johansen A, Ellegaard-Jensen L, Hansen LH, Hansen M. Non-target analysis of Danish wastewater treatment plant effluent: Statistical analysis of chemical fingerprinting as a step toward a future monitoring tool. ENVIRONMENTAL RESEARCH 2024; 257:119242. [PMID: 38821457 DOI: 10.1016/j.envres.2024.119242] [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: 01/11/2024] [Revised: 04/25/2024] [Accepted: 05/26/2024] [Indexed: 06/02/2024]
Abstract
In an attempt to discover and characterize the plethora of xenobiotic substances, this study investigates chemical compounds released into the environment with wastewater effluents. A novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a newly optimized data-processing pipeline were applied to effluent samples from two state-of-the-art and one small wastewater treatment facility. In total, 785 molecular structures were obtained, of which 38 were identified as single compounds, while 480 structures were identified at a putative level. Most of these substances were therapeutics and drugs, present as parent compounds and metabolites. Using R packages Phyloseq and MetacodeR, originally developed for bioinformatics, significant differences in xenobiotic presence in the wastewater effluents between the three sites were demonstrated.
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Affiliation(s)
- Marie Rønne Aggerbeck
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark.
| | - Emil Egede Frøkjær
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark
| | - Anders Johansen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark; Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg, Denmark; Aarhus University Centre for Circular Bioeconomy, Aarhus University, 8830 Tjele, Denmark
| | - Lea Ellegaard-Jensen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark
| | - Lars Hestbjerg Hansen
- Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg, Denmark
| | - Martin Hansen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark.
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2
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Chrapkiewicz K, Lipp AG, Barron LP, Barnes R, Roberts GG. Apportioning sources of chemicals of emerging concern along an urban river with inverse modelling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 933:172827. [PMID: 38701930 DOI: 10.1016/j.scitotenv.2024.172827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 05/06/2024]
Abstract
Concentrations of chemicals in river water provide crucial information for assessing environmental exposure and risks from fertilisers, pesticides, heavy metals, illicit drugs, pathogens, pharmaceuticals, plastics and perfluorinated substances, among others. However, using concentrations measured along waterways (e.g., from grab samples) to identify sources of contaminants and understand their fate is complicated by mixing of chemicals downstream from diverse diffuse and point sources (e.g., agricultural runoff, wastewater treatment plants). To address this challenge, a novel inverse modelling approach is presented. Using waterway network topology, it quantifies locations and concentrations of contaminant sources upstream by inverting concentrations measured in water samples. It is computationally efficient and quantifies uncertainty. The approach is demonstrated for 13 contaminants of emerging concern (CECs) in an urban stream, the R. Wandle (London, UK). Mixing (the forward problem) was assumed to be conservative, and the location of sources and their concentrations were treated as unknowns to be identified. Calculated CEC source concentrations, which ranged from below detection limit (a few ng/L) up to 1μg/L, were used to predict concentrations of chemicals downstream. Using this approach, >90% of data were predicted within observational uncertainty. Principal component analysis of calculated source concentrations revealed signatures of two distinct chemical sources. First, pharmaceuticals and insecticides were associated with a subcatchment containing a known point source of treated effluent from a wastewater treatment plant. Second, illicit drugs and salicylic acid were associated with multiple sources, interpreted as input from untreated sewage including Combined Sewer Overflows (CSOs), misconnections, runoff and direct disposal throughout the catchment. Finally, a simple algorithmic approach that incorporates network topology was developed to design sampling campaigns to improve resolution of source apportionment. Inverse modelling of contaminant measurements can provide objective means to apportion sources in waterways from spot samples in catchments on a large scale.
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Affiliation(s)
- Kajetan Chrapkiewicz
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
| | - Alex G Lipp
- Merton College, University of Oxford, Merton Street, Oxford OX1 4JD, Oxfordshire, UK
| | - Leon P Barron
- MRC Centre for Environment and Health, Environment Research Group, School of Public Health, Imperial College London, Wood Lane, London W12 0BZ, UK
| | - Richard Barnes
- Lawrence Berkeley National Laboratory, Wang Hall, Berkeley, CA 94720, USA
| | - Gareth G Roberts
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
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3
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Bade R, van Herwerden D, Rousis N, Adhikari S, Allen D, Baduel C, Bijlsma L, Boogaerts T, Burgard D, Chappell A, Driver EM, Sodre FF, Fatta-Kassinos D, Gracia-Lor E, Gracia-Marín E, Halden RU, Heath E, Jaunay E, Krotulski A, Lai FY, Löve ASC, O'Brien JW, Oh JE, Pasin D, Castro MP, Psichoudaki M, Salgueiro-Gonzalez N, Gomes CS, Subedi B, Thomas KV, Thomaidis N, Wang D, Yargeau V, Samanipour S, Mueller J. Workflow to facilitate the detection of new psychoactive substances and drugs of abuse in influent urban wastewater. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:133955. [PMID: 38457976 DOI: 10.1016/j.jhazmat.2024.133955] [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: 12/19/2023] [Revised: 02/22/2024] [Accepted: 03/03/2024] [Indexed: 03/10/2024]
Abstract
The complexity around the dynamic markets for new psychoactive substances (NPS) forces researchers to develop and apply innovative analytical strategies to detect and identify them in influent urban wastewater. In this work a comprehensive suspect screening workflow following liquid chromatography - high resolution mass spectrometry analysis was established utilising the open-source InSpectra data processing platform and the HighResNPS library. In total, 278 urban influent wastewater samples from 47 sites in 16 countries were collected to investigate the presence of NPS and other drugs of abuse. A total of 50 compounds were detected in samples from at least one site. Most compounds found were prescription drugs such as gabapentin (detection frequency 79%), codeine (40%) and pregabalin (15%). However, cocaine was the most found illicit drug (83%), in all countries where samples were collected apart from the Republic of Korea and China. Eight NPS were also identified with this protocol: 3-methylmethcathinone 11%), eutylone (6%), etizolam (2%), 3-chloromethcathinone (4%), mitragynine (6%), phenibut (2%), 25I-NBOH (2%) and trimethoxyamphetamine (2%). The latter three have not previously been reported in municipal wastewater samples. The workflow employed allowed the prioritisation of features to be further investigated, reducing processing time and gaining in confidence in their identification.
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Affiliation(s)
- Richard Bade
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia.
| | - Denice van Herwerden
- Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, the Netherlands
| | - Nikolaos Rousis
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Sangeet Adhikari
- School of Sustainable Engineering and Built Environment, Arizona State University, Tempe, AZ 85281, United States; Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, United States
| | - Darren Allen
- Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia
| | - Christine Baduel
- Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Institute of Environmental Geosciences (IGE), Grenoble, France
| | - 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
| | - Tim Boogaerts
- Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, 2610 Wilrijk, Belgium
| | - Dan Burgard
- Department of Chemistry and Biochemistry, University of Puget Sound, Tacoma, WA 98416, United States
| | - Andrew Chappell
- Institute of Environmental Science and Research Limited (ESR), Christchurch Science Centre, 27 Creyke Road, Ilam, Christchurch 8041, New Zealand
| | - Erin M Driver
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, United States
| | | | - Despo Fatta-Kassinos
- Nireas-International Water Research Centre and Department of Civil and Environmental Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus
| | - Emma Gracia-Lor
- Department of Analytical Chemistry, Faculty of Chemistry, Complutense University of Madrid, Avenida Complutense s/n, 28040 Madrid, Spain
| | - Elisa Gracia-Marín
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda, Sos Baynat s/n, E-12071 Castellón, Spain
| | - Rolf U Halden
- School of Sustainable Engineering and Built Environment, Arizona State University, Tempe, AZ 85281, United States; Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, United States; OneWaterOneHealth, Arizona State University Foundation, 1001 S. McAllister Avenue, Tempe, AZ 85287-8101, United States
| | - Ester Heath
- Jožef Stefan Institute and International Postgraduate School Jožef Stefan, Jamova 39, 1000 Ljubljana, Slovenia
| | - Emma Jaunay
- Health and Biomedical Innovation, UniSA: Clinical and Health Sciences, University of South Australia, Adelaide 5001, South Australia, Australia
| | - Alex Krotulski
- Center for Forensic Science Research and Education, Fredric Rieders Family Foundation, Willow Grove, PA 19090, United States
| | - Foon Yin Lai
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden
| | - Arndís Sue Ching Löve
- University of Iceland, Department of Pharmacology and Toxicology, Hofsvallagata 53, 107 Reykjavik, Iceland; University of Iceland, Faculty of Pharmaceutical Sciences, Hofsvallagata 53, 107 Reykjavik, Iceland
| | - Jake W O'Brien
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia; Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, the Netherlands
| | - Jeong-Eun Oh
- Department of Civil and Environmental Engineering, Pusan National University, Jangjeon-dong, Geumjeong-gu, Busan 46241, Republic of Korea
| | - Daniel Pasin
- Forensic Laboratory Division, San Francisco Office of the Chief Medical Examiner, 1 Newhall St, San Francisco, CA 94124, United States
| | | | - Magda Psichoudaki
- Nireas-International Water Research Centre and Department of Civil and Environmental Engineering, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus
| | - Noelia Salgueiro-Gonzalez
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Environmental Health Sciences, Via Mario Negri 2, 20156 Milan, Italy
| | | | - Bikram Subedi
- Department of Chemistry, Murray State University, Murray, KY 42071-3300, United States
| | - Kevin V Thomas
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Nikolaos Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Degao Wang
- College of Environmental Science and Engineering, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, PR China
| | - Viviane Yargeau
- Department of Chemical Engineering, McGill University, Montreal, QC, Canada
| | - Saer Samanipour
- Van't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, the Netherlands; UvA Data Science Center, University of Amsterdam, the Netherlands
| | - Jochen Mueller
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, Queensland 4102, Australia
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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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5
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Schulze B, Heffernan AL, Samanipour S, Gomez Ramos MJ, Veal C, Thomas KV, Kaserzon SL. Is Nontarget Analysis Ready for Regulatory Application? Influence of Peak-Picking Algorithms on Data Analysis. Anal Chem 2023; 95:18361-18369. [PMID: 38061068 DOI: 10.1021/acs.analchem.3c03003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
The use of peak-picking algorithms is an essential step in all nontarget analysis (NTA) workflows. However, algorithm choice may influence reliability and reproducibility of results. Using a real-world data set, the aim of this study was to investigate how different peak-picking algorithms influence NTA results when exploring temporal and/or spatial trends. For this, drinking water catchment monitoring data, using passive samplers collected twice per year across Southeast Queensland, Australia (n = 18 sites) between 2014 and 2019, was investigated. Data were acquired using liquid chromatography coupled to high-resolution mass spectrometry. Peak picking was performed using five different programs/algorithms (SCIEX OS, MSDial, self-adjusting-feature-detection, two algorithms within MarkerView), keeping parameters identical whenever possible. The resulting feature lists revealed low overlap: 7.2% of features were picked by >3 algorithms, while 74% of features were only picked by a single algorithm. Trend evaluation of the data, using principal component analysis, showed significant variability between the approaches, with only one temporal and no spatial trend being identified by all algorithms. Manual evaluation of features of interest (p-value <0.01, log fold change >2) for one sampling site revealed high rates of incorrectly picked peaks (>70%) for three algorithms. Lower rates (<30%) were observed for the other algorithms, but with the caveat of not successfully picking all internal standards used as quality control. The choice is therefore currently between comprehensive and strict peak picking, either resulting in increased noise or missed peaks, respectively. Reproducibility of NTA results remains challenging when applied for regulatory frameworks.
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Affiliation(s)
- Bastian Schulze
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4102, Australia
| | - Amy L Heffernan
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4102, Australia
| | - Saer Samanipour
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4102, Australia
- Van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Maria Jose Gomez Ramos
- Chemistry and Physics Department, University of Almeria, Agrifood Campus of International Excellence (ceiA3), 04120 Almería, Spain
| | - Cameron Veal
- Seqwater, 117 Brisbane Street, Ipswich, QLD 4305, Australia
- UQ School of Civil Engineering, The University of Queensland, Building 49 Advanced Engineering Building, Staff House Road, St Lucia, QLD 4072, Australia
| | - Kevin V Thomas
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4102, Australia
| | - Sarit L Kaserzon
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4102, Australia
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