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.
Highlights
Background & SummaryNon-target analysis (NTA) using high-resolution mass spectrometry (HRMS) is the most comprehensive approach for the screening and discovery of organic compounds/chemicals of emerging concern (CECs) in complex environmental samples[1,2,3,4,5,6,7]
We present the data collected during an international collaborative inter-laboratory studies (ILS) organized through the Norman Network
NTA/extended suspect screening workflow (i.e. reversed-phase LC (RPLC) coupled with HRMS) using two different experimental approaches
Summary
Non-target analysis (NTA) using high-resolution mass spectrometry (HRMS) is the most comprehensive approach for the screening and discovery of organic compounds/chemicals of emerging concern (CECs) in complex environmental samples[1,2,3,4,5,6,7]. This strategy is a bottom up approach with minimum a priori assumptions and/or knowledge regarding the samples and the CECs5,8–10. The wide variety of chemicals with different physico-chemical properties and variable concentration ranges make NTA an extremely challenging task[4,19]
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