Effects of Fe(III) and quality of humic substances on As(V) distribution in freshwater: Use of ultrafiltration and Kohonen neural network
Autor(a) principal: | |
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Data de Publicação: | 2017 |
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.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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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:29462024-08-05T22:11:27.625711Repositório 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 |
|
_version_ |
1808129401593790464 |