Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network

Detalhes bibliográficos
Autor(a) principal: Gontijo, Erik S.J. [UNESP]
Data de Publicação: 2017
Outros Autores: Watanabe, Cláudia H. [UNESP], Monteiro, Adnívia S.C. [UNESP], da Silva, Gilmare A., Roeser, Hubert M.P., Rosa, Andre H. [UNESP], Friese, Kurt
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.chemosphere.2017.08.143
http://hdl.handle.net/11449/170093
Resumo: Humic substances (HS) are ubiquitous organic compounds able to affect mobility and availability of arsenic (As) in aquatic systems. Although it is known that associations between HS and As occur mainly via iron (Fe)-cationic bridges, the behaviour and distribution of this metalloid in HS- and Fe-rich environments is still not fully understood. In this paper, the quality of HS from different rivers in Brazil and Germany and its influence on the behaviour of As(V) under different Fe(III) concentrations were investigated. HS were extracted from four different rivers (Cascatinha, Holtemme, Selke and Warme Bode), characterised and fractionated into different molecular weight sizes (10, 5 and 1 kDa). Complexation tests were performed using an ultrafiltration system and 1 kDa membranes. All data was analysed using the Kohonen neural network (SOM – Self organising maps). All samples, except Selke, exhibited similar results of free As (<1 kDa). The results suggested that associations between HS, Fe and As were dependent on nitrogen (N)–aromatic carbon (C), amount of sulphur (S) and the molecular size of the HS. Although all HS appeared to be similar after looking at most variables analysed, the SOM could discriminate them into three different groups. Characterisation of the HS indicated that they had terrestrial material (from C3 plants) as precursor material. Most of the As and Fe was distributed in the fractions of higher (>10 kDa) and lower (<1 kDa) size. HS quality is an important factor to take into account when studying the behaviour of As in HS-rich environments.
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spelling Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural networkArsenic distributionDissolved organic matterSelf-organising maps (SOM)Ternary complexUltrafiltrationHumic substances (HS) are ubiquitous organic compounds able to affect mobility and availability of arsenic (As) in aquatic systems. Although it is known that associations between HS and As occur mainly via iron (Fe)-cationic bridges, the behaviour and distribution of this metalloid in HS- and Fe-rich environments is still not fully understood. In this paper, the quality of HS from different rivers in Brazil and Germany and its influence on the behaviour of As(V) under different Fe(III) concentrations were investigated. HS were extracted from four different rivers (Cascatinha, Holtemme, Selke and Warme Bode), characterised and fractionated into different molecular weight sizes (10, 5 and 1 kDa). Complexation tests were performed using an ultrafiltration system and 1 kDa membranes. All data was analysed using the Kohonen neural network (SOM – Self organising maps). All samples, except Selke, exhibited similar results of free As (<1 kDa). The results suggested that associations between HS, Fe and As were dependent on nitrogen (N)–aromatic carbon (C), amount of sulphur (S) and the molecular size of the HS. Although all HS appeared to be similar after looking at most variables analysed, the SOM could discriminate them into three different groups. Characterisation of the HS indicated that they had terrestrial material (from C3 plants) as precursor material. Most of the As and Fe was distributed in the fractions of higher (>10 kDa) and lower (<1 kDa) size. HS quality is an important factor to take into account when studying the behaviour of As in HS-rich environments.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Deutscher Akademischer AustauschdienstSão Paulo State University (Unesp) Institute of Science and Technology, Av. Três de Marco, 511, Alto da Boa VistaUFZ-Helmholtz Centre for Environmental Research Department Lake Research, Brueckstr 3aSão Paulo State University (Unesp) Institute of Chemistry, Av. Prof. Francisco Degni, 55, Jardim QuitandinhaFederal University of Ouro Preto (UFOP) Campus Universitário, Morro do CruzeiroSão Paulo State University (Unesp) Institute of Science and Technology, Av. Três de Marco, 511, Alto da Boa VistaSão Paulo State University (Unesp) Institute of Chemistry, Av. Prof. Francisco Degni, 55, Jardim QuitandinhaFAPESP: 2012/17727-8CNPq: 400572/2013-3Deutscher Akademischer Austauschdienst: BEX10452/14-1Universidade Estadual Paulista (Unesp)UFZ-Helmholtz Centre for Environmental ResearchFederal University of Ouro Preto (UFOP)Gontijo, Erik S.J. [UNESP]Watanabe, Cláudia H. [UNESP]Monteiro, Adnívia S.C. [UNESP]da Silva, Gilmare A.Roeser, Hubert M.P.Rosa, Andre H. [UNESP]Friese, Kurt2018-12-11T16:49:14Z2018-12-11T16:49:14Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article208-217application/pdfhttp://dx.doi.org/10.1016/j.chemosphere.2017.08.143Chemosphere, v. 188, p. 208-217.1879-12980045-6535http://hdl.handle.net/11449/17009310.1016/j.chemosphere.2017.08.1432-s2.0-850286957292-s2.0-85028695729.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengChemosphere1,435info:eu-repo/semantics/openAccess2024-01-05T06:25:14Zoai:repositorio.unesp.br:11449/170093Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-01-05T06:25:14Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
title Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
spellingShingle Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
Gontijo, Erik S.J. [UNESP]
Arsenic distribution
Dissolved organic matter
Self-organising maps (SOM)
Ternary complex
Ultrafiltration
title_short Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
title_full Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
title_fullStr Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
title_full_unstemmed Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
title_sort Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
author Gontijo, Erik S.J. [UNESP]
author_facet Gontijo, Erik S.J. [UNESP]
Watanabe, Cláudia H. [UNESP]
Monteiro, Adnívia S.C. [UNESP]
da Silva, Gilmare A.
Roeser, Hubert M.P.
Rosa, Andre H. [UNESP]
Friese, Kurt
author_role author
author2 Watanabe, Cláudia H. [UNESP]
Monteiro, Adnívia S.C. [UNESP]
da Silva, Gilmare A.
Roeser, Hubert M.P.
Rosa, Andre H. [UNESP]
Friese, Kurt
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
UFZ-Helmholtz Centre for Environmental Research
Federal University of Ouro Preto (UFOP)
dc.contributor.author.fl_str_mv Gontijo, Erik S.J. [UNESP]
Watanabe, Cláudia H. [UNESP]
Monteiro, Adnívia S.C. [UNESP]
da Silva, Gilmare A.
Roeser, Hubert M.P.
Rosa, Andre H. [UNESP]
Friese, Kurt
dc.subject.por.fl_str_mv Arsenic distribution
Dissolved organic matter
Self-organising maps (SOM)
Ternary complex
Ultrafiltration
topic Arsenic distribution
Dissolved organic matter
Self-organising maps (SOM)
Ternary complex
Ultrafiltration
description Humic substances (HS) are ubiquitous organic compounds able to affect mobility and availability of arsenic (As) in aquatic systems. Although it is known that associations between HS and As occur mainly via iron (Fe)-cationic bridges, the behaviour and distribution of this metalloid in HS- and Fe-rich environments is still not fully understood. In this paper, the quality of HS from different rivers in Brazil and Germany and its influence on the behaviour of As(V) under different Fe(III) concentrations were investigated. HS were extracted from four different rivers (Cascatinha, Holtemme, Selke and Warme Bode), characterised and fractionated into different molecular weight sizes (10, 5 and 1 kDa). Complexation tests were performed using an ultrafiltration system and 1 kDa membranes. All data was analysed using the Kohonen neural network (SOM – Self organising maps). All samples, except Selke, exhibited similar results of free As (<1 kDa). The results suggested that associations between HS, Fe and As were dependent on nitrogen (N)–aromatic carbon (C), amount of sulphur (S) and the molecular size of the HS. Although all HS appeared to be similar after looking at most variables analysed, the SOM could discriminate them into three different groups. Characterisation of the HS indicated that they had terrestrial material (from C3 plants) as precursor material. Most of the As and Fe was distributed in the fractions of higher (>10 kDa) and lower (<1 kDa) size. HS quality is an important factor to take into account when studying the behaviour of As in HS-rich environments.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
2018-12-11T16:49:14Z
2018-12-11T16:49:14Z
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.2017.08.143
Chemosphere, v. 188, p. 208-217.
1879-1298
0045-6535
http://hdl.handle.net/11449/170093
10.1016/j.chemosphere.2017.08.143
2-s2.0-85028695729
2-s2.0-85028695729.pdf
url http://dx.doi.org/10.1016/j.chemosphere.2017.08.143
http://hdl.handle.net/11449/170093
identifier_str_mv Chemosphere, v. 188, p. 208-217.
1879-1298
0045-6535
10.1016/j.chemosphere.2017.08.143
2-s2.0-85028695729
2-s2.0-85028695729.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Chemosphere
1,435
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 208-217
application/pdf
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
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