Suspect screening of environmental contaminants by UHPLC-HRMS and transposable Quantitative Structure-Retention Relationship modelling
| Autor: | Benilde Bonnefille, Sabine Heinisch, C. Guillemain, Eloi Bride, Christelle Margoum |
|---|---|
| Přispěvatelé: | Riverly (Riverly), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut des Sciences Analytiques (ISA), Institut de Chimie du CNRS (INC)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), French National Office for Biodiversity (OFB) through the Aquaref program |
| Rok vydání: | 2021 |
| Předmět: |
Environmental Engineering
Health Toxicology and Mutagenesis Uhplc hrms 0211 other engineering and technologies 02 engineering and technology 010501 environmental sciences Mass spectrometry High resolution mass spectrometry 01 natural sciences Organic compound Organic contaminants Environmental water [CHIM]Chemical Sciences Environmental Chemistry Waste Management and Disposal 0105 earth and related environmental sciences chemistry.chemical_classification 021110 strategic defence & security studies QSRR model Chromatography Elution Quantitative structure Suspect screening Contamination Pollution chemistry Phase composition [SDE]Environmental Sciences Retention prediction |
| Zdroj: | Journal of Hazardous Materials Journal of Hazardous Materials, Elsevier, 2021, 409, pp.124652. ⟨10.1016/j.jhazmat.2020.124652⟩ |
| ISSN: | 0304-3894 1873-3336 |
| Popis: | International audience; A Quantitative Structure-Retention Relationship (QSRR) model is proposed and aims at increasing the confidence level associated to the identification of organic contaminants by Ultra-High Performance Liquid Chromatography hyphenated to High Resolution Mass Spectrometry (UHPLC-HRMS) in environmental samples under a suspect screening approach. The model was built from a selection of 8 easily accessible physicochemical descriptors, and was validated from a set of 274 organic compounds commonly found in environmental samples. The proposed predictive figure approach is based on the mobile phase composition at solute elution (expressed as % acetonitrile), that has the major advantage of making the model reusable by other laboratories, since the elution composition is independent of both the column geometry and the UHPLC-system. The model quality was assessed and was altered neither by the columns from different lots, nor by the complex matrices of environmental water samples. Then, the solute retention of any organic compound present in water samples is expected to be predicted within ± 14.3% acetonitrile by our model. Solute retention can therefore be used as a supplementary tool for the identification of environmental contaminants by UHPLC-HRMS, in addition to mass spectrometry data already used in the suspect screening approach. |
| Databáze: | OpenAIRE |
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