Title: Unravelling contaminants in the anthropocene using statistical analysis of liquid chromatography–high-resolution mass spectrometry nontarget screening data recorded in lake sediments
Authors : Chiaia-Hernández, Aurea C.
Günthardt, Barbara F.
Frey, Martin
Hollender, Juliane
Published in : Environmental Science & Technology
Volume(Issue) : 51
Issue : 21
Pages : 12547
Pages to: 12556
Publisher / Ed. Institution : American Chemical Society
Issue Date: 25-Oct-2017
Language : Englisch / English
Subject (DDC) : 540: Chemie
Abstract: The significant increase in traces of human activity in the environment worldwide provides evidence of the beginning of a new geological era, informally named the Anthropocene. The rate and variability of these human modifications at the local and global scale remain largely unknown, but new analytical methods such as high-resolution mass spectrometry (HRMS) can help to characterize chemical contamination. We therefore applied HRMS to investigate the contamination history of two lakes in Central Europe over the preceding 100 years. A hierarchical clustering analysis (HCA) of the collected time series data revealed more than 13 000 profiles of anthropogenic origin in both lakes, defining the beginning of large-scale human impacts during the 1950s. Our results show that the analysis of temporal patterns of nontarget contaminants is an effective method for characterizing the contamination pattern in the Anthropocene and an important step in prioritizing the identification of organic contaminants not yet successfully targeted by environmental regulation and pollution reduction initiatives. As proof of the concept, the success of the method was demonstrated with the identification of the pesticide imazalil, which probably originated from imported fruits. This new approach applicable to palaeoarchives can effectively be used to document the time and rate of change in contamination over time and provide additional information on the onset of the Anthropocene.
Departement: School of Engineering
Organisational Unit: Institut für Datenanalyse und Prozessdesign (IDP)
Publication type: Beitrag in wissenschaftlicher Zeitschrift / Article in scientific Journal
DOI : 10.1021/acs.est.7b03357
ISSN: 0013-936X
1520-5851
1520-5851
PMID : 29067807
URI: https://digitalcollection.zhaw.ch/handle/11475/1444
Appears in Collections:Publikationen School of Engineering

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