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Stream sediment pollution: a compositional baseline assessment

dc.contributor.authorAlbuquerque, M.T.D.
dc.contributor.authorFonseca, Rita
dc.contributor.authorAraújo, Joana
dc.contributor.authorSilva, Natália
dc.contributor.authorAraújo, António
dc.date.accessioned2024-03-20T15:32:03Z
dc.date.available2024-03-20T15:32:03Z
dc.date.issued2024
dc.description.abstractA high concentration of potentially toxic elements (PTEs) can affect ecosystem health in many ways. It is therefore essential that spatial trends in pollutants are assessed and monitored. Two questions must be addressed when quantifying pollution: how to define a non-polluted sample and how to reduce the problem’s dimensionality. A geochemical dataset is a composition of variables (chemical elements), where the components represent the relative importance of each part of the whole. Therefore, to comply with the compositional constraints, a compositional approach was used. A novel compositional pollution indicator (CPI) based on compositional data (CoDa) principles such as the properties of sparsity and simplicity was computed. A dataset of 12 chemical elements in 33 stream-sediment samples were collected from depths of 0–10 cm in a grid of 1 km × 1 km and analyzed. Maximum concentrations of 3.8% Pb, 750 µg g−1 As, and 340 µg g–1 Hg were obtained near the mine tailings. The methodological approach involved geological background selection in terms of a trimmed subsample that could be assumed to contain only non-pollutants (Al and Fe) and the selection of a list of pollutants (As, Zn, Pb, and Hg) based on expert knowledge criteria and previous studies. Finally, a stochastic sequential Gaussian simulation of the new CPI was performed. The results of the hundred simulations performed were summarized through the mean image map and maps of the probability of exceeding a given statistical threshold, allowing the characterization of the spatial distribution and the associated variability of the CPI. A high risk of contamination along the Grândola River was observed. As the main economic activities in this area are agricultural and involve animal stocks, it is crucial to establish two lines of intervention: the installation of a surveillance network for continuous control in all areas and the definition of mitigation actions for the northern area with high levels of contamination.pt_PT
dc.description.sponsorshipThe authors acknowledge the funding provided by the “La Caixa” Foundation (Spain) and the Foundation for Science and Technology (FCT) (Portugal), which supported this research through the GeoMatre project “La Caixa/FCT”—project nº PV20-00006, and also the funding provided by the Research Centre for Natural Resources, Environment and Society (CERNAS-IPCB) [project UIDB/00681/2020], the funding from the Portuguese Foundation for Science and Technology (FCT), and the funding provided by ICT under contract with FCT (Portuguese Science and Technology Foundation) under the project FCT—UIDB/04683/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationALBUQUERQUE, M.T.D. [et al.] (2024) - Stream sediment pollution: a compositional baseline assessment. Euro-Mediterr. J. Environ. Integr. DOI: https://doi.org/10.1007/s41207-024-00470-xpt_PT
dc.identifier.doi10.1007/s41207-024-00470-xpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.11/8934
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectCaveira minept_PT
dc.subjectPollutionpt_PT
dc.subjectCompositional pollution indicator (CPI)pt_PT
dc.subjectSequential gaussian simulationpt_PT
dc.subjectProbability mappt_PT
dc.titleStream sediment pollution: a compositional baseline assessmentpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleEuro-Mediterranean Journal for Environmental Integrationpt_PT
person.familyNameAlbuquerque
person.familyNameFerreira da Fonseca Ventura Araújo
person.givenNameMaria Teresa
person.givenNameJoana
person.identifierhttps://www.researchgate.net/profile/Joana_Araujo16/info
person.identifier.ciencia-id5A1C-8956-4C0A
person.identifier.ciencia-id2617-7BC7-DE98
person.identifier.orcid0000-0002-8782-6133
person.identifier.orcid0000-0003-4956-4061
person.identifier.ridB-1536-2013
person.identifier.scopus-author-id55507421600
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicatione2c2d171-e148-4c23-9cf8-0eb6d810c15e
relation.isAuthorOfPublication851c087c-ffbf-41df-9ed0-ff898e42cb7a
relation.isAuthorOfPublication.latestForDiscovery851c087c-ffbf-41df-9ed0-ff898e42cb7a

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