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Nontarget Screening and Time-Trend Analysis of Sewage Sludge Contaminants via Two-Dimensional Gas Chromatography-High Resolution Mass Spectrometry
Umeå University, Faculty of Science and Technology, Department of Chemistry.ORCID iD: 0000-0002-6368-6412
Contaminant Research Group, Swedish Museum of Natural History.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.ORCID iD: 0000-0003-2293-7913
2018 (English)In: Environmental Science and Technology, ISSN 0013-936X, E-ISSN 1520-5851, Vol. 52, no 14, p. 7813-7822Article in journal (Refereed) Published
Abstract [en]

Nondestructive sample cleanup and comprehensive two-dimensional gas chromatography (GCXGC) high-resolution mass spectrometry (HRMS) analysis generated a massive amount of data that could be used for nontarget screening purposes. We present a data reduction and prioritization strategy that involves time-trend analysis of nontarget data. Sewage sludge collected between 2005 and 2015 in Stockholm (Sweden) was retrieved from an environmental specimen bank, extracted, and analyzed by GCX GC-HRMS. After data alignment features with high blank levels, artifacts and low detection frequency were removed. Features that appeared in four to six out of ten years were reprocessed to fill in gaps. The total number of compounds was reduced by more than 97% from almost 60 000 to almost 1500. The remaining compounds were analyzed for monotonic (log-linear) and nonmonotonic (smoother) time trends. In total, 192 compounds with log-linear trends and 120 compounds with nonmonotonic trends were obtained, respectively. Most compounds described by a log-linear trend exhibited decreasing trends and were traffic-related. Compounds with increasing trends included UV-filters, alkyl-phenols, and flavor and fragrances, which often could be linked to trade statistics. We have shown that nontarget screening and stepwise reduction of data provides a simple way of revealing significant changes in emissions of chemicals in society.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018. Vol. 52, no 14, p. 7813-7822
Keywords [en]
Gas chromatography, GC×GC, non-target screening, time-trend analysis, sewage sludge, data reduction
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:umu:diva-144542DOI: 10.1021/acs.est.8b01126ISI: 000439397800026PubMedID: 29898598Scopus ID: 2-s2.0-85048660866OAI: oai:DiVA.org:umu-144542DiVA, id: diva2:1180565
Note

Originally included in thesis in manuscript form with title "Non-target screening and time trend analysis of sewage sludge contaminants via comprehensive two-dimensional gas chromatography"

Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2019-04-09Bibliographically approved
In thesis
1. Developing tools for non-target analysis and digital archiving of organic urban water pollutants
Open this publication in new window or tab >>Developing tools for non-target analysis and digital archiving of organic urban water pollutants
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Utveckling av verktyg för förutsättningslös analys och digital arkivering av organiska föroreningar i avloppsslam
Abstract [en]

This thesis describes efforts to develop robust methods for the creation and use of digital archives of environmental samples, and proposes guidelines based on the results. Digital archives are repositories that store environmental samples digitally. Traditionally, samples are stored physically in environmental specimen banks over long time periods. However, this has several drawbacks, for example degradation effects and limited accessibility. During the course of my PhD project I developed methods that allow the comprehensive analysis of sewage sludge samples. Sewage sludge is a complex matrix that contains many commercial chemicals. In addition, sewage treatment plants form a link between the human society that generates the sewage and the environment, making sewage sludge a very interesting matrix to analyze. The developed methods enable analysis and subsequent identification of compounds of all sizes and with diverse chemical characteristics. I further explain how unknown compounds can be identified (non-target screening) using mass spectral analysis and several other approaches (e.g. retention indices).

The thesis is divided into three parts. In the first part, Data Generation, I describe the development of sample preparation methods for analyzing sewage sludge with gas chromatography (GC) and liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS). For the GC approach, two methods involving use of different extraction techniques, solvents, and matrix reduction techniques are presented while for the LC approach different extraction techniques are compared. The methods have been developed to enable the generation of data suitable for digital archiving. In the second part of the thesis, Data Evaluation, I present ways to find and identify compounds of interest. Firstly, time trend analyses provide a way to prioritize pollutants, for example by focusing on pollutants that are increasing with time. Thousands of compounds with significant time trends were detected and several hundred of them were tentatively identified. Compounds with strong increasing trends included, for example, UV-filters from sunscreens. Secondly, a new retention index system for comprehensive two‑dimensional chromatography (GC×GC) is introduced to characterize compounds in terms of their retention times in the second dimension. The new retention index system is based on co-injection of polyethylene glycols and was validated for various compounds of diverse classes. Thirdly, I tested different ways to predict GC×GC retention times or indices. Those methods include a multivariate prediction (PLS) approach using molecular descriptors, which proved to be the best approach, and use of commercially available software. The last part of my thesis, Data Archiving, discusses requirements to create digital archives and how they can be used. Here I present the current state and options for archiving data files, and give recommendations for each step, from sample collection, through instrumental analysis to storage of the final data.

Abstract [sv]

I denna avhandling beskrivs innovativa metoder för att skapa och använda digitala arkiv för miljörelaterade prover, såsom biologisk vävnad, sediment och rötslam. Digitala arkiv skiljer sig från traditionella miljöprovbanker genom att resultat från analys av miljöprover fryses digitalt, istället för att fysiska prover placeras i frys. För att testa detta nya koncept utvecklades nya metoder för omfattande kemisk analys av slam från avloppsreningsverk. Avloppsslam är spännande för att det kan ge en integrerad bild av vilka kemikalier som används i samhället. Det används också för gödsling av åkermark vilket kan leda till exponering av olika organismer, inklusive människa.

De nyutvecklade metoderna möjliggör analys och efterföljande identifiering av miljöföreningar med vitt skilda kemiska egenskaper. De inkluderar icke-specifik provberedning och omfattande analys av avloppsslam med gaskromatografi (GC) respektive vätskekromatografi (LC) kopplat till högupplösande masspektrometri. För beredning av prover för GC-analys utvecklades två olika metoder för extraktion av föroreningar och eliminering av potentiellt störande ämnen, exempelvis fett och humus. Likaså optimerades extraktionstekniker för LC-analys. Genom att komplettera de båda metoderna för GC-analys med en för LC-analys kan miljöföroreningar med varierande stabilitet, storlek och polaritet analyseras. Det utvecklades även ett robust retentionindexsystem för tvådimensionell gaskromatografi (GC×GC) baserat på relativ retention i förhållande till polyetylenglykoler, liksom metoder för att beräkna retentionstider och index. Bäst resultat uppnåddes med en multivariat prediktion med hjälp av molekylära deskriptorer. Tillsammans underlättar dessa verktyg identifiering av nya potentiella miljögifter.

Analys av tidstrender användes för att prioritera bland detekterade föroreningar, till exempel för att finna föroreningar som ökar i halt med tiden. Tusentals föroreningar med statistiskt säker-ställda tidstrender upptäcktes och flera hundra av dem kunde ges en preliminär identitet. Föroreningar med starkt ökande trender inkluderade exempelvis kemikalier med UV‑blockerande egenskaper som används i solskyddsmedel.

Slutligen presenteras nuvarande status och utsikter för framtida användning av digitala arkiv. Lämpliga rutiner för digital arkivering diskuteras och det ges rekommendationer för varje steg, från insamling av prover, genom instrumentanalys till lagring av slutdata. Förhoppningen är att digitala arkiv framöver helt eller delvis kan ersätta miljöprovbanker och därmed undvika problem såsom begränsad tillgång till material, nedbrytning eller kontamination under lagring.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2018. p. 100
Keywords
Digital archiving, non-target screening, organic pollutants, sewage sludge, GC-MS, GC×GC, LC-MS, time-trend analysis, retention indices, retention time prediction
National Category
Analytical Chemistry Environmental Sciences
Identifiers
urn:nbn:se:umu:diva-144549 (URN)978-91-7601-840-8 (ISBN)
Public defence
2018-03-02, KB.E3.03 (Stora hörsalen, Carl Kempe-salen), KBC-huset, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2018-02-09 Created: 2018-02-06 Last updated: 2019-04-09Bibliographically approved

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Veenaas, CathrinLiljelind, PerHaglund, Peter

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