Fabric phase sorptive extraction as a sustainable sample preparation procedure to determine synthetic musks in water

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Química Analítica, Nutrición e Bromatoloxíaes_ES
dc.contributor.authorCastiñeira Landeira, Ana
dc.contributor.authorVázquez, Lúa
dc.contributor.authorCarro Díaz, Antonia María
dc.contributor.authorCeleiro Montero, María
dc.contributor.authorKabir, Abuzar
dc.contributor.authorFurton, Kenneth G.
dc.contributor.authorDagnac, Thierry
dc.contributor.authorLlompart Vizoso, María del Pilar
dc.date.accessioned2024-03-06T11:32:10Z
dc.date.available2024-03-06T11:32:10Z
dc.date.issued2024
dc.description.abstractA rapid sample preparation fabric phase sorptive extraction (FPSE) methodology followed by gas chromatography coupled to tandem mass spectrometry is proposed for the first time to determine 12 synthetic musks including nitro-, polycyclic and macrocyclic musk in environmental water and wastewater. An asymmetric screening design of experiments was used to evaluate the influence of nine parameters affecting FPSE in only 16 experiments. The factors included the sol–gel sorbent coating, stirring mode (both extraction and desorption), extraction and desorption time, salting-out effect, sample volume, type of solvent, and desorption solvent volume. The selected conditions imply the use of the sol–gel PDMS sorbent coating, 15 min extraction by ultrasound energy employing 10 mL of sample and 0.5 mL of ethanol as desorption solvent during 5 min. Accuracy and precision were assessed in different real water samples. Matrix effects were evaluated performing recovery studies in several aqueous matrices: river, sea, spring, laundry washing place, and wastewater at different concentration levels (0.1, 2, 10 µg L−1) demonstrating method accuracy (results ranged between 82 and 110%) and good precision (relative standard deviation, RSD < 12% in all cases). Limits of detection (LODs) were below 8 ng L−1 for the analyzed synthetic musks. As extraction was quantitative (exhaustive extraction), calibration was carried out using solvent standards without the need of repeating the extraction step, which is required in most microextraction methods, improving sample throughput, and reducing costs. Finally, the analysis of real contaminated samples revealed the presence of 11 out of the 12 target synthetic musks at concentrations up to 30 µg L−1, three of them banned in cosmetic regulation (musk tibetene, ambrette, and moskene). The developed FPSE based methodology uses low volume (0.5 mL) of a Generally Recognized as Safe (GRAS) solvent (ethanol), as well as minimum energy and time consumption, demonstrating to be a sustainable alternative to detect these microcontaminants in environmental waters and wastewaters.es_ES
dc.description.peerreviewedSIes_ES
dc.identifier.citationMicrochemical Journal Volume 196, January 2024, 109542es_ES
dc.identifier.doi10.1016/j.microc.2023.109542
dc.identifier.issn0026-265X
dc.identifier.urihttp://hdl.handle.net/10347/33008
dc.journal.titleMicrochemical Journal
dc.language.isoenges_ES
dc.page.initial109542
dc.publisherElsevieres_ES
dc.rights© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND licensees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSynthetic muskses_ES
dc.subjectFabric phase sorptive extractiones_ES
dc.subjectSample preparationes_ES
dc.subjectGas chromatographyes_ES
dc.subjectTandem mass spectrometryes_ES
dc.subjectExperimental designes_ES
dc.titleFabric phase sorptive extraction as a sustainable sample preparation procedure to determine synthetic musks in wateres_ES
dc.typejournal articlees_ES
dc.type.hasVersionVoRes_ES
dc.volume.number196
dspace.entity.typePublication
relation.isAuthorOfPublication3fa1622e-5af3-46fc-8231-1bc80c7b3d5c
relation.isAuthorOfPublication6bdf401d-b737-4bd0-8be1-4da6e19d0abf
relation.isAuthorOfPublication.latestForDiscovery3fa1622e-5af3-46fc-8231-1bc80c7b3d5c

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