Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis

• Published in: Scientific data 2021-08, Vol.8 (1), p.223-223, Article 223
• Main Authors: Schulze, Bastian, van Herwerden, Denice, Allan, Ian, Bijlsma, Lubertus, Etxebarria, Nestor, Hansen, Martin, Merel, Sylvain, Vrana, Branislav, Aalizadeh, Reza, Bajema, Bernard, Dubocq, Florian, Coppola, Gianluca, Fildier, Aurélie, Fialová, Pavla, Frøkjær, Emil, Grabic, Roman, Gago-Ferrero, Pablo, Gravert, Thorsten, Hollender, Juliane, Huynh, Nina, Jacobs, Griet, Jonkers, Tim, Kaserzon, Sarit, Lamoree, Marja, Le Roux, Julien, Mairinger, Teresa, Margoum, Christelle, Mascolo, Giuseppe, Mebold, Emmanuelle, Menger, Frank, Miège, Cécile, Meijer, Jeroen, Moilleron, Régis, Murgolo, Sapia, Peruzzo, Massimo, Pijnappels, Martijn, Reid, Malcolm, Roscioli, Claudio, Soulier, Coralie, Valsecchi, Sara, Thomaidis, Nikolaos, Vulliet, Emmanuelle, Young, Robert, Samanipour, Saer
• Format: Article
• Language: English
• Subjects: 639/638/11/296; 704/172/169/895; Analytical chemistry; Chemical Sciences; Data Descriptor; Drinking water; Environmental Engineering; Environmental Sciences; Humanities and Social Sciences; Laboratories; Mass spectrometry; Mass spectroscopy; Miljövetenskap; multidisciplinary; Quality control; Sampling; Science; Science (multidisciplinary); Scientific imaging
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-021-01002-w

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. Measurement(s) chemical • drinking water Technology Type(s) high resolution mass spectrometry • non-target analysis • Interlaboratory Factor Type(s) method Sample Characteristic - Environment laboratory environment Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15028665