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Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater
A wide range of micropollutants can be monitored with non-targeted screening; however, the quantification of the newly discovered compounds is challenging. Transformation products (TPs) are especially problematic because analytical standards are rarely available. Here, we compared three quantificati...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921029/ https://www.ncbi.nlm.nih.gov/pubmed/33506334 http://dx.doi.org/10.1007/s00216-020-03109-2 |
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author | Kruve, Anneli Kiefer, Karin Hollender, Juliane |
author_facet | Kruve, Anneli Kiefer, Karin Hollender, Juliane |
author_sort | Kruve, Anneli |
collection | PubMed |
description | A wide range of micropollutants can be monitored with non-targeted screening; however, the quantification of the newly discovered compounds is challenging. Transformation products (TPs) are especially problematic because analytical standards are rarely available. Here, we compared three quantification approaches for non-target compounds that do not require the availability of analytical standards. The comparison is based on a unique set of concentration data for 341 compounds, mainly pesticides, pharmaceuticals, and their TPs in 31 groundwater samples from Switzerland. The best accuracy was observed with the predicted ionization efficiency-based quantification, the mean error of concentration prediction for the groundwater samples was a factor of 1.8, and all of the 74 micropollutants detected in the groundwater were quantified with an error less than a factor of 10. The quantification of TPs with the parent compounds had significantly lower accuracy (mean error of a factor of 3.8) and could only be applied to a fraction of the detected compounds, while the mean performance (mean error of a factor of 3.2) of the closest eluting standard approach was similar to the parent compound approach. |
format | Online Article Text |
id | pubmed-7921029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-79210292021-03-19 Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater Kruve, Anneli Kiefer, Karin Hollender, Juliane Anal Bioanal Chem Research Paper A wide range of micropollutants can be monitored with non-targeted screening; however, the quantification of the newly discovered compounds is challenging. Transformation products (TPs) are especially problematic because analytical standards are rarely available. Here, we compared three quantification approaches for non-target compounds that do not require the availability of analytical standards. The comparison is based on a unique set of concentration data for 341 compounds, mainly pesticides, pharmaceuticals, and their TPs in 31 groundwater samples from Switzerland. The best accuracy was observed with the predicted ionization efficiency-based quantification, the mean error of concentration prediction for the groundwater samples was a factor of 1.8, and all of the 74 micropollutants detected in the groundwater were quantified with an error less than a factor of 10. The quantification of TPs with the parent compounds had significantly lower accuracy (mean error of a factor of 3.8) and could only be applied to a fraction of the detected compounds, while the mean performance (mean error of a factor of 3.2) of the closest eluting standard approach was similar to the parent compound approach. Springer Berlin Heidelberg 2021-01-27 2021 /pmc/articles/PMC7921029/ /pubmed/33506334 http://dx.doi.org/10.1007/s00216-020-03109-2 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Paper Kruve, Anneli Kiefer, Karin Hollender, Juliane Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title | Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title_full | Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title_fullStr | Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title_full_unstemmed | Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title_short | Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
title_sort | benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921029/ https://www.ncbi.nlm.nih.gov/pubmed/33506334 http://dx.doi.org/10.1007/s00216-020-03109-2 |
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