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Stream sediments pollution: A compositional baseline assessment at the Caveira mine, Portugal

dc.contributor.authorAraújo, Joana
dc.contributor.authorFonseca, Rita
dc.contributor.authorMota, Natália
dc.contributor.authorAraújo, Alexandre
dc.contributor.authorAntunes I.M.H.R.
dc.contributor.authorValente, Teresa
dc.contributor.authorBarroso, Ana
dc.contributor.authorAlbuquerque, Maria Teresa
dc.contributor.editorZanini , Andrea
dc.contributor.editorD'Oria, Marco
dc.date.accessioned2025-04-09T16:24:01Z
dc.date.available2025-04-09T16:24:01Z
dc.date.issued2022
dc.description.abstractA high concentration of Potentially Toxic Elements (PTE) can affect ecosystem health. It is therefore essential that spatial trends of pollutants are assessed and controlled. River sediment pollution is widespread in mining communities around the world, including in developing countries. This study, as part of the GeoMaTre project, restoration of water bodies impacted by mine drainage, an ongoing collaborative project (2021-2024) between the Polytechnic Institute of Castelo Branco and the University of Évora, Portugal, aimed to evaluate the potential risk of PTEs pollution in stream sediments under the direct influence of Caveira mine, a Cu-Pb Zn-Ag-Au old mine included in the Iberian Pyrite Belt, South Portugal. Quantifying pollution implies first the understanding of pollution-free stream sediment. Often, this background, or pollution baseline, is undefined or only partially known. Given that the concentration of chemical elements is compositional, as the attributes vary together, a compositional approach was used aiming to find a compositional balance, based on Compositional Data (CoDa) principles. A dataset of 33 samples was collected from within 0 to 10 cm depth, in a grid of 1Km x 1Km and thirteen chemical elements, including PTEs of variable toxicity (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn, V) and major elements from lithogenic sources (Fe, Al), were analyzed in preservedsamples at about 4°C. The most extractable forms of metals (except for Hg) were obtained by partial digestion with aqua regia (HCl and HNO3) in a high-pressure microwave digestion unit, followed by ICP-OES analysis. Hg was analyzed determined by a mercury analyzer based on thermal decomposition, gold amalgamation, and cold vapor atomic absorption spectroscopy detection.eng
dc.identifier.citationARAÚJO, Joana [et al.] (2022) - Stream sediments: A compositional baseline assessment at the Caveira mine, Portugal. In 14th International Conference on Geostatistics for Environmental Applications (GeoENV 2022), Parma - Environmental pollution and risk assessment. proceedings. Parma : Università. p. 4-5.
dc.identifier.urihttp://hdl.handle.net/10400.11/10121
dc.language.isoeng
dc.peerreviewedyes
dc.publisherUniversità di Parma
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectCaveira mine
dc.subjectStream sediment
dc.subjectCompositional Indicator
dc.subjectSequential Gaussian Simulation
dc.subjectProbability map.
dc.titleStream sediments pollution: A compositional baseline assessment at the Caveira mine, Portugaleng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2022
oaire.citation.conferencePlaceParma, Itália
oaire.citation.endPage5
oaire.citation.startPage4
oaire.citation.title14th International Conference on Geostatistics for Environmental Applications (GeoENV 2022)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameantunes
person.familyNameAlbuquerque
person.givenNameIsabel Margarida
person.givenNameMaria Teresa
person.identifier.ciencia-idCB1E-FAD2-37D6
person.identifier.ciencia-id5A1C-8956-4C0A
person.identifier.orcid0000-0003-3456-5926
person.identifier.orcid0000-0002-8782-6133
person.identifier.ridM-1043-2013
person.identifier.ridB-1536-2013
person.identifier.scopus-author-id6701817085
person.identifier.scopus-author-id55507421600
relation.isAuthorOfPublication1db83c95-f80c-41bb-b5c6-437ab32d9683
relation.isAuthorOfPublicatione2c2d171-e148-4c23-9cf8-0eb6d810c15e
relation.isAuthorOfPublication.latestForDiscovery1db83c95-f80c-41bb-b5c6-437ab32d9683

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