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Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).ORCID iD: 0000-0002-0205-7524
Stockholm University, Faculty of Science, Department of Environmental Science.ORCID iD: 0000-0003-3042-187x
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).ORCID iD: 0000-0001-9725-3351
Number of Authors: 772024 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 96, no 41, p. 16215-16226Article in journal (Refereed) Published
Abstract [en]

Nontargeted screening (NTS) utilizing liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is increasingly used to identify environmental contaminants. Major differences in the ionization efficiency of compounds in ESI/HRMS result in widely varying responses and complicate quantitative analysis. Despite an increasing number of methods for quantification without authentic standards in NTS, the approaches are evaluated on limited and diverse data sets with varying chemical coverage collected on different instruments, complicating an unbiased comparison. In this interlaboratory comparison, organized by the NORMAN Network, we evaluated the accuracy and performance variability of five quantification approaches across 41 NTS methods from 37 laboratories. Three approaches are based on surrogate standard quantification (parent-transformation product, structurally similar or close eluting) and two on predicted ionization efficiencies (RandFor-IE and MLR-IE). Shortly, HPLC grade water, tap water, and surface water spiked with 45 compounds at 2 concentration levels were analyzed together with 41 calibrants at 6 known concentrations by the laboratories using in-house NTS workflows. The accuracy of the approaches was evaluated by comparing the estimated and spiked concentrations across quantification approaches, instrumentation, and laboratories. The RandFor-IE approach performed best with a reported mean prediction error of 15× and over 83% of compounds quantified within 10× error. Despite different instrumentation and workflows, the performance was stable across laboratories and did not depend on the complexity of water matrices.

Place, publisher, year, edition, pages
2024. Vol. 96, no 41, p. 16215-16226
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Analytical Chemistry
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URN: urn:nbn:se:su:diva-237192DOI: 10.1021/acs.analchem.4c02902ISI: 001327098300001Scopus ID: 2-s2.0-85205931524OAI: oai:DiVA.org:su-237192DiVA, id: diva2:1925402
Available from: 2025-01-08 Created: 2025-01-08 Last updated: 2025-01-08Bibliographically approved

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Malm, LouisePlassmann, MerleKruve, Anneli

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