Rapid target screening and quantitative analysis of various environmental pollutants.
Published In: Rapid Communications in Mass Spectrometry: RCM, 2025, v. 39. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Bořík, Adam; Nováková, Petra; Stroski, Kevin M. 3 of 3
Abstract
Rationale: The presented analytical method demonstrates a straightforward approach for environmental applications based on laser diode thermal desorption (LDTD). The study aims to examine abilities to achieve environmentally relevant outcomes for different types of pollutants with a fast method following the green chemistry principle. Methods: Treatment of environmentally relevant sample matrix (river water) was limited to filtration with a cellulose filter. Samples fortified with analytes were spotted in a LazWell plate and dried before analysis. Samples thermally desorbed using LDTD were detected with Q Exactive hybrid high‐resolution mass spectrometer operation in full‐scan data‐dependent acquisition mode (LDTD‐FullMS‐dd‐MS/MS). Results: LDTD‐FullMS‐dd‐MS/MS exhibits the lowest quantification limits for anatoxin‐A, atrazine, caffeine, methamphetamine, methylbenzotriazole, paracetamol, perfluorobutanoic acid, perfluorohexanoic acid, and perfluorooctanoic acid of between 0.10 and 1.0 ng mL−1 in the environmentally relevant sample matrix. Conclusions: The developed method was successfully evaluated for different environmental pollutants and radically reduced sample treatment and time requirements for analysis and sample preparation. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Rapid Communications in Mass Spectrometry: RCM. 2025/05, Vol. 39, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2025
- ISSN:0951-4198
- DOI:10.1002/rcm.9517
- Accession Number:185068404
- Copyright Statement:Copyright of Rapid Communications in Mass Spectrometry: RCM is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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