Analytical and Bioanalytical Chemistry

, Volume 407, Issue 21, pp 6237–6255 | Cite as

Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis

  • Emma L. Schymanski
  • Heinz P. Singer
  • Jaroslav Slobodnik
  • Ildiko M. Ipolyi
  • Peter Oswald
  • Martin Krauss
  • Tobias Schulze
  • Peter Haglund
  • Thomas Letzel
  • Sylvia Grosse
  • Nikolaos S. Thomaidis
  • Anna Bletsou
  • Christian Zwiener
  • María Ibáñez
  • Tania Portolés
  • Ronald de Boer
  • Malcolm J. Reid
  • Matthias Onghena
  • Uwe Kunkel
  • Wolfgang Schulz
  • Amélie Guillon
  • Naïke Noyon
  • Gaëla Leroy
  • Philippe Bados
  • Sara Bogialli
  • Draženka Stipaničev
  • Pawel Rostkowski
  • Juliane Hollender
Review
Part of the following topical collections:
  1. High-Resolution Mass Spectrometry in Food and Environmental Analysis

Abstract

In this article, a dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that non-target analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a “fully-automated identification workflow” remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases.

Graphical Abstract

Matrix of identification approach versus identification confidence

Keywords

Non-target screening High resolution mass spectrometry LC–MS GC–MS Suspect screening Surface water 

Supplementary material

216_2015_8681_MOESM1_ESM.pdf (1.4 mb)
ESM 1(PDF 1.42 mb)
216_2015_8681_MOESM2_ESM.tar (614 kb)
ESM 2(TAR 614 kb)

References

  1. 1.
    Krauss M, Singer H, Hollender J (2010) LC-high resolution MS in environmental analysis: from target screening to the identification of unknowns. Anal Bioanal Chem 397(3):943–951CrossRefGoogle Scholar
  2. 2.
    Hernandez F, Pozo OJ, Sancho JV, Lopez FJ, Marin JM, Ibanez M (2005) Strategies for quantification and confirmation of multi-class polar pesticides and transformation products in water by LC-MS2 using triple quadrupole and hybrid quadrupole time-of-flight analyzers. TraC Trends Anal Chem 24(7):596–612CrossRefGoogle Scholar
  3. 3.
    Schymanski EL, Singer HP, Longree P, Loos M, Ruff M, Stravs MA, Ripolles Vidal C, Hollender J (2014) Strategies to Characterize Polar Organic Contamination in Wastewater: Exploring the Capability of High Resolution Mass Spectrometry. Environ Sci Technol 48(3):1811–1819CrossRefGoogle Scholar
  4. 4.
    Zedda M, Zwiener C (2012) Is nontarget screening of emerging contaminants by LC-HRMS successful? A plea for compound libraries and computer tools. Anal Bioanal Chem 403(9):2493–2502CrossRefGoogle Scholar
  5. 5.
    Hug C, Ulrich N, Schulze T, Brack W, Krauss M (2014) Identification of novel micropollutants in wastewater by a combination of suspect and nontarget screening. Environ Pollut 184:25–32CrossRefGoogle Scholar
  6. 6.
    European Commission (2002) Commission Decision of 12 August 2002 Implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. Official Journal of the European Communities L221:29 http://old.eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2002:221:0008:0036:EN:PDF. Accessed 30 Jan 2015
  7. 7.
    Schymanski EL, Jeon J, Gulde R, Fenner K, Ruff M, Singer HP, Hollender J (2014) Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence. Environ Sci Technol 48(4):2097–2098Google Scholar
  8. 8.
    Creek DJ, Dunn WB, Fiehn O, Griffin JL, Hall RD, Lei ZT, Mistrik R, Neumann S, Schymanski EL, Sumner LW, Trengove R, Wolfender JL (2014) Metabolite identification: are you sure? And how do your peers gauge your confidence? Metabolomics 10(3):350–353CrossRefGoogle Scholar
  9. 9.
    Letzel T, Lucke T, Schulz W, Sengl M, Letzel M (2014) OMI (Organic Molecule Identification) in water using LC-MS(/MS): Steps from “unknown” to “identified”: a contribution to the discussion. Lab More Int 4:24–28Google Scholar
  10. 10.
    Sumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA, Fan TW, Fiehn O, Goodacre R, Griffin JL, Hankemeier T, Hardy N, Harnly J, Higashi R, Kopka J, Lane AN, Lindon JC, Marriott P, Nicholls AW, Reily MD, Thaden JJ, Viant MR (2007) Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 3(3):211–221CrossRefGoogle Scholar
  11. 11.
    NIST/EPA/NIH (2011) NIST Mass Spectral Library, various editions. National Institute of Standards and Technology. US Secretary of Commerce, USAGoogle Scholar
  12. 12.
    McLafferty FW (2000) Wiley Registry of Mass Spectral Data, 7th edn, ISBN-10: 0471440981Google Scholar
  13. 13.
    Stein S (2012) Mass Spectral Reference Libraries: An Ever-Expanding Resource for Chemical Identification. Anal Chem 84(17):7274–7282. doi:10.1021/ac301205z CrossRefGoogle Scholar
  14. 14.
    Kind T, Fiehn O (2010) Advances in structure elucidation of small molecules using mass spectrometry. Bioanal Rev 2(1–4):23–60CrossRefGoogle Scholar
  15. 15.
    Scheubert K, Hufsky F, Bocker S (2013) Computational mass spectrometry for small molecules. J Cheminform 5(12). doi:10.1186/1758-2946-5-12
  16. 16.
    Portoles T, Mol JGJ, Sancho JV, Hernandez F (2014) Use of electron ionization and atmospheric pressure chemical ionization in gas chromatography coupled to time-of-flight mass spectrometry for screening and identification of organic pollutants in waters. J Chromatogr A 1339:145–153CrossRefGoogle Scholar
  17. 17.
    Hernandez F, Ibanez M, Portoles T, Cervera MI, Sancho JV, Lopez FJ (2015) Advancing towards universal screening for organic pollutants in waters. J Hazard Mater 282:86–95CrossRefGoogle Scholar
  18. 18.
    Helbling DE, Hollender J, Kohler HPE, Singer H, Fenner K (2010) High-Throughput Identification of Microbial Transformation Products of Organic Micropollutants. Environ Sci Technol 44(17):6621–6627CrossRefGoogle Scholar
  19. 19.
    Kern S, Fenner K, Singer HP, Schwarzenbach RP, Hollender J (2009) Identification of Transformation Products of Organic Contaminants in Natural Waters by Computer-Aided Prediction and High-Resolution Mass Spectrometry. Environ Sci Technol 43(18):7039–7046CrossRefGoogle Scholar
  20. 20.
    Huntscha S, Hofstetter TB, Schymanski EL, Spahr S, Hollender J (2014) Biotransformation of benzotriazoles: insights from transformation product identification and compound-specific isotope analysis. Environ Sci Technol 48(8):4435–4443CrossRefGoogle Scholar
  21. 21.
    Moschet C, Piazzoli A, Singer H, Hollender J (2013) Alleviating the Reference Standard Dilemma Using a Systematic Exact Mass Suspect Screening Approach with Liquid Chromatography-High Resolution Mass Spectrometry. Anal Chem 85(21):10312–10320CrossRefGoogle Scholar
  22. 22.
    Thurman EM, Ferrer I, Blotevogel J, Borch T (2014) Analysis of Hydraulic Fracturing Flowback and Produced Waters Using Accurate Mass: Identification of Ethoxylated Surfactants. Anal Chem 86(19):9653–9661CrossRefGoogle Scholar
  23. 23.
    Chiaia-Hernandez AC, Schymanski EL, Kumar P, Singer HP, Hollender J (2014) Suspect and nontarget screening approaches to identify organic contaminant records in lake sediments. Anal Bioanal Chem 406(28):7323–7335CrossRefGoogle Scholar
  24. 24.
    Howard PH, Muir DCG (2010) Identifying New Persistent and Bioaccumulative Organics Among Chemicals in Commerce. Environ Sci Technol 44(7):2277–2285CrossRefGoogle Scholar
  25. 25.
    Howard PH, Muir DCG (2011) Identifying New Persistent and Bioaccumulative Organics Among Chemicals in Commerce II: Pharmaceuticals. Environ Sci Technol 45(16):6938–6946CrossRefGoogle Scholar
  26. 26.
    Howard PH, Muir DCG (2013) Identifying New Persistent and Bioaccumulative Organics Among Chemicals in Commerce. III: Byproducts, Impurities, and Transformation Products. Environ Sci Technol 47(10):5259–5266CrossRefGoogle Scholar
  27. 27.
    Ulrich N, Schuurmann G, Brack W (2011) Linear Solvation Energy Relationships as classifiers in non-target analysis-A capillary liquid chromatography approach. J Chromatogr A 1218(45):8192–8196CrossRefGoogle Scholar
  28. 28.
    Wolf S, Schmidt S, Muller-Hannemann M, Neumann S (2010) In silico fragmentation for computer assisted identification of metabolite mass spectra. BMC Bioinf 11:148CrossRefGoogle Scholar
  29. 29.
    HighChem (2014) Mass Frontier, 7th edn. HighChem Ltd./Thermo Scientific, BratislavaGoogle Scholar
  30. 30.
    Little JL, Cleven CD, Brown SD (2011) Identification of "Known Unknowns" Utilizing Accurate Mass Data and Chemical Abstracts Service Databases. J Am Soc Mass Spectrom 22(2):348–359CrossRefGoogle Scholar
  31. 31.
    Little JL, Williams AJ, Pshenichnov A, Tkachenko V (2012) Identification of "Known Unknowns" Utilizing Accurate Mass Data and ChemSpider. J Am Soc Mass Spectrom 23(1):179–185CrossRefGoogle Scholar
  32. 32.
    RSC (2014) ChemSpider www.chemspider.com. Royal Society of Chemistry. Accessed 17 Dec 2014
  33. 33.
    ICPDR (2015) Joint Danube Survey 3 www.danubesurvey.org. ICPDR - International Commission for the Protection of the Danube River. Accessed 23 Jan 2015
  34. 34.
    Liska I, Wagner F, Deutsch K, Sengl M, Slobodnik J (2015) Joint Danube Survey 3 Final Scientific Report (in print). Vienna, AustriaGoogle Scholar
  35. 35.
    Schulze T, Krauss M, Bahlmann A, Hug C, Walz K-H, Brack W (2014) Onsite large volume solid phase extraction – how to get 1000 litres of water into the laboratory? Society for Environmental Toxicology and Chemistry (SETAC) Europe 24th Annual Meeting, Basel, Switzerland, 11–15 May, 2014Google Scholar
  36. 36.
    ChemAxon (2015) MarvinSketch Calculator Plugins 15.1.12.0 http://www.chemaxon.com. Accessed 30 Jan 2015
  37. 37.
    Greco G, Grosse S, Letzel T (2013) Serial coupling of reversed-phase and zwitterionic hydrophilic interaction LC/MS for the analysis of polar and nonpolar phenols in wine. J Sep Sci 36(8):1379–1388CrossRefGoogle Scholar
  38. 38.
    LW/HSWT (2014) DAIOS Substance Database http://www.daios-online.de/daios/. Zweckverband Landeswasserversorgung, Langenau, Germany. Accessed 18 Dec 2014 (login only)
  39. 39.
    Muller A, Schulz W, Ruck WKL, Weber WH (2011) A new approach to data evaluation in the non-target screening of organic trace substances in water analysis. Chemosphere 85(8):1211–1219CrossRefGoogle Scholar
  40. 40.
    NCBI (2014) PubChem (https://pubchem.ncbi.nlm.nih.gov/). National Center for Biotechnology Information. Accessed 17/12/2014
  41. 41.
    LfU/LW/HSWT/TUM (2014) STOFF-IDENT Substance Database http://bb-x-stoffident.hswt.de/stoffidentjpa/app Environmental Agency of Bayern, Germany (Bayerisches Landesamt für Umwelt). Accessed 1 Apr 2015 (login only)
  42. 42.
    MassBank (2014) MassBank www.massbank.jp. Accessed 17 Dec 2014
  43. 43.
    MassBank (2014) NORMAN MassBank www.massbank.eu. Accessed 17 Dec 2014
  44. 44.
    Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K, Oda Y, Kakazu Y, Kusano M, Tohge T, Matsuda F, Sawada Y, Hirai MY, Nakanishi H, Ikeda K, Akimoto N, Maoka T, Takahashi H, Ara T, Sakurai N, Suzuki H, Shibata D, Neumann S, Iida T, Funatsu K, Matsuura F, Soga T, Taguchi R, Saito K, Nishioka T (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45(7):703–714CrossRefGoogle Scholar
  45. 45.
    HighChem (2014) mzCloud https://www.mzcloud.org/. HighChem Ltd., Bratislava, Slovakia. Accessed 17 Dec 2014
  46. 46.
    SIS (2014) The NIST 14 Mass Spectral Library http://www.sisweb.com/software/ms/nist.htm. Scientific Instrument Services. Accessed 17 Dec 2014
  47. 47.
    Wiley (2013) Wiley Registry of Mass Spectral Data, 10th Edn. Wiley, ISBN: 978-0-470-52037-6Google Scholar
  48. 48.
    Broecker S, Herre S, Wust B, Zweigenbaum J, Pragst F (2011) Development and practical application of a library of CID accurate mass spectra of more than 2,500 toxic compounds for systematic toxicological analysis by LC-QTOF-MS with data-dependent acquisition. Anal Bioanal Chem 400(1):101–117CrossRefGoogle Scholar
  49. 49.
    Agilent (2015) Broecker, Herre, and Pragst Accurate Mass Personal Compound Database and Library (PCDL) for Forensics and Toxicology. Agilent Technologies, Santa ClaraGoogle Scholar
  50. 50.
    Agilent (2015) Accurate Mass Personal Compound Database and Library (PCDL) for Pesticides. Agilent Technologies, Santa ClaraGoogle Scholar
  51. 51.
    Scripps (2015) METLIN: Metabolite and Tandem MS Database http://metlin.scripps.edu/. Scripps Center for Metabolomics. Accessed 23/3/2015
  52. 52.
    Smith CA, O'Maille G, Want EJ, Qin C, Trauger SA, Brandon TR, Custodio DE, Abagyan R, Siuzdak G (2005) METLIN: a metabolite mass spectral database. Ther Drug Monit 27(6):747–751CrossRefGoogle Scholar
  53. 53.
    Bruker (2014) Bruker ToxScreenerTM - A Comprehensive Screening Solution for Forensic Toxicology. Bruker Daltronics, Inc., Bremen, GermanyGoogle Scholar
  54. 54.
    Sciex (2015) iMethod Application - LC/MS/MS Meta Library Version 1.0 for Cliquid Software http://sciex.myshopify.com/products/imethod-application-lcmsms-meta-library-version-10-for-cliquid-software. AB Sciex. Accessed 23/3/2015
  55. 55.
    Gerlich M, Neumann S (2013) MetFusion: integration of compound identication strategies. J Mass Spectrom 48:291–298CrossRefGoogle Scholar
  56. 56.
    Waters (2014) MassFragment (version 1.3) http://www.waters.com/webassets/cms/library/docs/720004823en.pdf?locale=en_US. Accessed 27 Jan 2015
  57. 57.
    Tellstroem V, Dunsbach R (2014) Technical Note TN-26: SmartFormula 3D – the new Dimension in Substance Identification – From Mass Spectrum to Chemical Formula. Bruker Daltronics, Inc., Bremen, GermanyGoogle Scholar
  58. 58.
    Hill AW, Mortishire-Smith RJ (2005) Automated assignment of high-resolution collisionally activated dissociation mass spectra using a systematic bond disconnection approach. Rapid Commun Mass Spectrom 19:3111–3118CrossRefGoogle Scholar
  59. 59.
    Agilent (2011) Agilent MassHunter Molecular Structure Correlator (MSC) Software, Revision A. Agilent Technologies, Santa ClaraGoogle Scholar
  60. 60.
    NIST (2005) Automated Mass Spectral Deconvolution and Identification System (AMDIS), 26th edn. National Institute of Standards and Technology (NIST), US Department of Defense, USAGoogle Scholar
  61. 61.
    Daylight (2012) SMILES- A Simplified Chemical Language http://www.daylight.com/dayhtml/doc/theory/theory.smiles.html. Daylight Chemical Information Systems Inc. Accessed 30 Jan 2015
  62. 62.
    IUPAC (2012) The IUPAC International Chemical Identifier http://www.iupac.org/inchi/. International Union of Pure and Applied Chemitstry. Accessed 30 Jan 2015
  63. 63.
    O'Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open Babel: An open chemical toolbox. J Cheminform 3:33CrossRefGoogle Scholar
  64. 64.
    Liska I, Wagner F, Slobodnik J (2008) Joint Danube Survey 2: Final Scientific Report. Editors: Liska I, Wagner F, Slobodnik J ICPDR – International Commission for the Protection of the Danube River, Vienna, AustriaGoogle Scholar
  65. 65.
    Kind T, Fiehn O (2007) Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinf 8:105CrossRefGoogle Scholar
  66. 66.
    Weiss S, Jakobs J, Reemtsma T (2006) Discharge of three benzotriazole corrosion inhibitors with municipal wastewater and improvements by membrane bioreactor treatment and ozonation. Environ Sci Technol 40(23):7193–7199CrossRefGoogle Scholar
  67. 67.
    Rasche F, Svatos A, Maddula RK, Bottcher C, Bocker S (2011) Computing Fragmentation Trees from Tandem Mass Spectrometry Data. Anal Chem 83(4):1243–1251CrossRefGoogle Scholar
  68. 68.
    Meringer M, Reinker S, Zhang JA, Muller A (2011) MS/MS Data Improves Automated Determination of Molecular Formulas by Mass Spectrometry. Match-Commun Math Co 65(2):259–290Google Scholar
  69. 69.
    Pluskal T, Uehara T, Yanagida M (2012) Highly Accurate Chemical Formula Prediction Tool Utilizing High-Resolution Mass Spectra, MS/MS Fragmentation, Heuristic Rules, and Isotope Pattern Matching. Anal Chem 84(10):4396–4403CrossRefGoogle Scholar
  70. 70.
    Schymanski EL, Gallampois CMJ, Krauss M, Meringer M, Neumann S, Schulze T, Wolf S, Brack W (2012) Consensus Structure Elucidation Combining GC/EI-MS, Structure Generation, and Calculated Properties. Anal Chem 84(7):3287–3295CrossRefGoogle Scholar
  71. 71.
    Eckel WP, Kind T (2003) Use of boiling point-Lee retention index correlation for rapid review of gas chromatography-mass spectrometry data. Anal Chim Acta 494(1–2):235–243CrossRefGoogle Scholar
  72. 72.
    Schymanski EL, Gerlich M, Ruttkies C, Neumann S (2014) Solving CASMI 2013 with MetFrag, MetFusion and MOLGEN-MS/MS. Mass Spectrometry 3 (Special Issue 2):S0036Google Scholar
  73. 73.
    Reemtsma T (2009) Determination of molecular formulas of natural organic matter molecules by (ultra-) high-resolution mass spectrometry Status and needs. J Chromatogr A 1216(18):3687–3701CrossRefGoogle Scholar
  74. 74.
    Reemtsma T (2010) The carbon versus mass diagram to visualize and exploit FTICR-MS data of natural organic matter. J Mass Spectrom 45(4):382–390Google Scholar
  75. 75.
    NORMAN Association (2015) Non-target screening techniques for environmental monitoring http://www.norman-network.net/?q=node/190. NORMAN Association. Accessed 27 Jan 2015
  76. 76.
    NORMAN Association (2015) Workshop on Non-Target Screening: http://www.norman-network.net/?q=node/162. NORMAN Association. Accessed 27 Jan 2015
  77. 77.
    NORMAN Association (2015) NORMAN MassBank Workshop http://www.norman-network.net/?q=node/163. NORMAN Association. Accessed 27 Jan 2015

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Emma L. Schymanski
    • 1
  • Heinz P. Singer
    • 1
  • Jaroslav Slobodnik
    • 2
  • Ildiko M. Ipolyi
    • 2
  • Peter Oswald
    • 2
  • Martin Krauss
    • 3
  • Tobias Schulze
    • 3
  • Peter Haglund
    • 4
  • Thomas Letzel
    • 5
  • Sylvia Grosse
    • 5
  • Nikolaos S. Thomaidis
    • 6
  • Anna Bletsou
    • 6
  • Christian Zwiener
    • 7
  • María Ibáñez
    • 8
  • Tania Portolés
    • 8
  • Ronald de Boer
    • 9
  • Malcolm J. Reid
    • 10
  • Matthias Onghena
    • 11
  • Uwe Kunkel
    • 12
  • Wolfgang Schulz
    • 13
  • Amélie Guillon
    • 14
  • Naïke Noyon
    • 14
  • Gaëla Leroy
    • 15
  • Philippe Bados
    • 16
  • Sara Bogialli
    • 17
  • Draženka Stipaničev
    • 18
  • Pawel Rostkowski
    • 19
  • Juliane Hollender
    • 1
    • 20
  1. 1.Eawag: Swiss Federal Institute for Aquatic Science and TechnologyDübendorfSwitzerland
  2. 2.Environmental Institute, s.r.o.KošSlovak Republic
  3. 3.Helmholtz Centre for Environmental Research - UFZLeipzigGermany
  4. 4.Umeå UniversityUmeåSweden
  5. 5.Chair of Urban Water Systems EngineeringTechnische Universität MünchenGarchingGermany
  6. 6.Department of ChemistryUniversity of AthensAthensGreece
  7. 7.Environmental Analytical ChemistryEberhard Karls University of TübingenTübingenGermany
  8. 8.Research Institute for Pesticides and WaterUniversity Jaume ICastellón de la PlanaSpain
  9. 9.Ministry of Infrastructure and the Environment (Rijkswaterstaat)LelystadNetherlands
  10. 10.Norwegian Institute for Water Research (NIVA)OsloNorway
  11. 11.Toxicological CenterUniversity of AntwerpWilrijkBelgium
  12. 12.German Federal Institute of Hydrology (BfG)KoblenzGermany
  13. 13.Betriebs- und ForschungslaboratoriumZweckverband LandeswasserversorgungLangenauGermany
  14. 14.Suez Environnement CIRSEELe PecqFrance
  15. 15.Veolia Research and Innovation (VERI)Saint Maurice CedexFrance
  16. 16.UR MALY Freshwater Systems, Ecology and PollutionsIrstea, Centre de Lyon-VilleurbanneVilleurbanne CedexFrance
  17. 17.Department of Chemical SciencesUniversity of PaduaPadovaItaly
  18. 18.Croatian WatersZagrebCroatia
  19. 19.NILU - Norwegian Institute for Air ResearchKjellerNorway
  20. 20.Institute of Biogeochemistry and Pollutant DynamicsETH ZurichZurichSwitzerland

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