Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.chemosphere.2022.135003 http://hdl.handle.net/11449/240098 |
Resumo: | The knowledge of size-distribution and lability of metals and nutrients in freshwater systems is important for estimation of the ecological effects of mining. However, it is still limited in several mining areas such as the Quadrilátero Ferrífero (Brazil) which was severely polluted by the collapse of the Fundão tailings dam in November 2015. In this study, results of an investigation from 2014 using a neural network named self-organising map (SO-Map) into the conditions of selected trace metals that are of particular importance to mining areas (Cr, Cu, Co, Mn, Ni, Pb, Zn) are presented. Additionally, P was considered by its high importance as a nutrient and sites later affected by the dam burst were also included by chance. Water samples were collected at six sites in dry and rainy seasons and filtered and ultrafiltered for determination of total dissolved (<0.45 μm) and truly dissolved (<1 kDa) fractions. Diffusive gradients in thin films (DGT) devices were deployed in situ for determination of the DGT-labile fraction. All data were analysed using SO-Map and Spearman's rank correlation. Phosphorus in the Carmo River occurred mainly in the truly dissolved and DGT-labile fractions. The higher amounts of this element in the river water (up to 263 μg L−1 of total P) might be related to untreated sewage discharge. Moreover, the concentrations of other trace metals (Mn, Cu, Co, Ni, Zn) were high, even under the “natural” conditions (before the dam failure) due to natural and anthropogenic factors such as local lithology and mining. |
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Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising mapsDiffusive gradients in thin filmsKohonen neural networkMining impactsSize fractionationUltrafiltrationThe knowledge of size-distribution and lability of metals and nutrients in freshwater systems is important for estimation of the ecological effects of mining. However, it is still limited in several mining areas such as the Quadrilátero Ferrífero (Brazil) which was severely polluted by the collapse of the Fundão tailings dam in November 2015. In this study, results of an investigation from 2014 using a neural network named self-organising map (SO-Map) into the conditions of selected trace metals that are of particular importance to mining areas (Cr, Cu, Co, Mn, Ni, Pb, Zn) are presented. Additionally, P was considered by its high importance as a nutrient and sites later affected by the dam burst were also included by chance. Water samples were collected at six sites in dry and rainy seasons and filtered and ultrafiltered for determination of total dissolved (<0.45 μm) and truly dissolved (<1 kDa) fractions. Diffusive gradients in thin films (DGT) devices were deployed in situ for determination of the DGT-labile fraction. All data were analysed using SO-Map and Spearman's rank correlation. Phosphorus in the Carmo River occurred mainly in the truly dissolved and DGT-labile fractions. The higher amounts of this element in the river water (up to 263 μg L−1 of total P) might be related to untreated sewage discharge. Moreover, the concentrations of other trace metals (Mn, Cu, Co, Ni, Zn) were high, even under the “natural” conditions (before the dam failure) due to natural and anthropogenic factors such as local lithology and mining.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Deutscher Akademischer AustauschdienstInstitute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SPFederal University of Sergipe (UFS) Campus São Cristóvão, Av. Marechal Rondon, s/n, Jardim Rosa Elze, SEFederal University of Ouro Preto (UFOP) Campus Universitário, Morro do Cruzeiro, MGDepartment of Lake Research Helmholtz Centre for Environmental Research – UFZ, Brueckstr. 3aInstitute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SPFAPESP: 12/17727–8FAPESP: 13/14122–0FAPESP: 19/06800–5Deutscher Akademischer Austauschdienst: 99999.008107/2015–07CAPES: BEX10452/14–1Deutscher Akademischer Austauschdienst: DAAD-ID 57414997Universidade Estadual Paulista (UNESP)Universidade Federal de Sergipe (UFS)Federal University of Ouro Preto (UFOP)Helmholtz Centre for Environmental Research – UFZGontijo, Erik Sartori Jeunon [UNESP]Monteiro, Adnívia Santos CostaTonello, Paulo Sérgio [UNESP]Roeser, Hubert Mathias PeterFriese, KurtRosa, André Henrique [UNESP]2023-03-01T20:01:28Z2023-03-01T20:01:28Z2022-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.chemosphere.2022.135003Chemosphere, v. 303.1879-12980045-6535http://hdl.handle.net/11449/24009810.1016/j.chemosphere.2022.1350032-s2.0-85130543301Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengChemosphereinfo:eu-repo/semantics/openAccess2023-03-01T20:01:29Zoai:repositorio.unesp.br:11449/240098Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T20:01:29Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
title |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
spellingShingle |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps Gontijo, Erik Sartori Jeunon [UNESP] Diffusive gradients in thin films Kohonen neural network Mining impacts Size fractionation Ultrafiltration |
title_short |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
title_full |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
title_fullStr |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
title_full_unstemmed |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
title_sort |
Analyses of colloidal, truly dissolved, and DGT-labile metal species and phosphorus in mining area surrounded by tailing dams using self-organising maps |
author |
Gontijo, Erik Sartori Jeunon [UNESP] |
author_facet |
Gontijo, Erik Sartori Jeunon [UNESP] Monteiro, Adnívia Santos Costa Tonello, Paulo Sérgio [UNESP] Roeser, Hubert Mathias Peter Friese, Kurt Rosa, André Henrique [UNESP] |
author_role |
author |
author2 |
Monteiro, Adnívia Santos Costa Tonello, Paulo Sérgio [UNESP] Roeser, Hubert Mathias Peter Friese, Kurt Rosa, André Henrique [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade Federal de Sergipe (UFS) Federal University of Ouro Preto (UFOP) Helmholtz Centre for Environmental Research – UFZ |
dc.contributor.author.fl_str_mv |
Gontijo, Erik Sartori Jeunon [UNESP] Monteiro, Adnívia Santos Costa Tonello, Paulo Sérgio [UNESP] Roeser, Hubert Mathias Peter Friese, Kurt Rosa, André Henrique [UNESP] |
dc.subject.por.fl_str_mv |
Diffusive gradients in thin films Kohonen neural network Mining impacts Size fractionation Ultrafiltration |
topic |
Diffusive gradients in thin films Kohonen neural network Mining impacts Size fractionation Ultrafiltration |
description |
The knowledge of size-distribution and lability of metals and nutrients in freshwater systems is important for estimation of the ecological effects of mining. However, it is still limited in several mining areas such as the Quadrilátero Ferrífero (Brazil) which was severely polluted by the collapse of the Fundão tailings dam in November 2015. In this study, results of an investigation from 2014 using a neural network named self-organising map (SO-Map) into the conditions of selected trace metals that are of particular importance to mining areas (Cr, Cu, Co, Mn, Ni, Pb, Zn) are presented. Additionally, P was considered by its high importance as a nutrient and sites later affected by the dam burst were also included by chance. Water samples were collected at six sites in dry and rainy seasons and filtered and ultrafiltered for determination of total dissolved (<0.45 μm) and truly dissolved (<1 kDa) fractions. Diffusive gradients in thin films (DGT) devices were deployed in situ for determination of the DGT-labile fraction. All data were analysed using SO-Map and Spearman's rank correlation. Phosphorus in the Carmo River occurred mainly in the truly dissolved and DGT-labile fractions. The higher amounts of this element in the river water (up to 263 μg L−1 of total P) might be related to untreated sewage discharge. Moreover, the concentrations of other trace metals (Mn, Cu, Co, Ni, Zn) were high, even under the “natural” conditions (before the dam failure) due to natural and anthropogenic factors such as local lithology and mining. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-01 2023-03-01T20:01:28Z 2023-03-01T20:01:28Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.chemosphere.2022.135003 Chemosphere, v. 303. 1879-1298 0045-6535 http://hdl.handle.net/11449/240098 10.1016/j.chemosphere.2022.135003 2-s2.0-85130543301 |
url |
http://dx.doi.org/10.1016/j.chemosphere.2022.135003 http://hdl.handle.net/11449/240098 |
identifier_str_mv |
Chemosphere, v. 303. 1879-1298 0045-6535 10.1016/j.chemosphere.2022.135003 2-s2.0-85130543301 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Chemosphere |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799965616660021248 |