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Ammonium acetate as a novel buffer for highly selective robust urinary HPLC-ICP-MS arsenic speciation methodology

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dc.contributor.authorRodríguez, P. F.
dc.contributor.authorLópez Colón, José Luis
dc.contributor.authorMendoza, J. L. de
dc.contributor.authorMartín Aranda, Rosa María
dc.date.accessioned2024-05-20T11:58:00Z
dc.date.available2024-05-20T11:58:00Z
dc.date.issued2021-01-01
dc.description.abstractAmmonium acetate is employed in order to develop a novel HPLC-ICP-MS arsenic speciation methodology applicable to six arsenic species, i.e, AC, AB, AsIII, AsV, DMA and MMA. The most predominant species in the toxicological field are covered in a 30-min chromatogram with reproducible and repeatability peak area ratio. Moreover, typical problems from traditional methods are sorted out by using a robust, high-selective and 75ArCl+ interference-free methodology. Chromatographic and detector optimization ensures low LOQs for each species with acceptable precision and accuracy values obtained using four urinary arsenic speciation PTS enabling to be useful for sub ng mL−1 arsenic exposure assessments.en
dc.description.versionversión publicada
dc.identifier.doi10.1016/j.talanta.2020.121494
dc.identifier.issn1873-3573
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12766
dc.journal.issue1 January 2021
dc.journal.titleTalanta
dc.journal.volume221
dc.language.isoen
dc.publisherElsevier
dc.relation.centerFacultad de Ciencias
dc.relation.departmentQuímica Inorgánica y Química Técnica
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject.keywordsUrinary
dc.subject.keywordsAmmonium Acetate
dc.subject.keywordsArsenic
dc.subject.keywordsSpeciation
dc.subject.keywordsHPLC-ICP-MS
dc.titleAmmonium acetate as a novel buffer for highly selective robust urinary HPLC-ICP-MS arsenic speciation methodologyes
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoverybafbca28-7ba9-4a29-b350-ebdcbc2381bb
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