Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Chemical Society (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532014000200003 |
Resumo: | Water samples were collected at 10 points in parts of the eastern Quadrilátero Ferrífero (QF), located in a mining region in the southeast of Brazil. The aims of this study were to find possible relationships among dissolved organic carbon (DOC), metals and other parameters measured in the region studied and evaluate the Kohonen neural network as a tool to analyse this geochemical multivariate data set. Physico-chemical analyses were performed in situ and in the laboratory, where concentrations of DOC and a suite of metal ions were determined. The Kohonen neural network allowed an easier visualisation and interpretation of the results and helped to define the relationships among them. In this way, a relationship between DOC and Fe and a possible effect of seasonality on the distribution of the samples were indicated. Signs of lithology were detected in the analyses, especially considering the elements Ca, Mg, Mn and Sr. |
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Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, BrazilQuadrilátero Ferrífero - Brazildissolved organic carbonKohonen neural networkenvironmental geochemistryWater samples were collected at 10 points in parts of the eastern Quadrilátero Ferrífero (QF), located in a mining region in the southeast of Brazil. The aims of this study were to find possible relationships among dissolved organic carbon (DOC), metals and other parameters measured in the region studied and evaluate the Kohonen neural network as a tool to analyse this geochemical multivariate data set. Physico-chemical analyses were performed in situ and in the laboratory, where concentrations of DOC and a suite of metal ions were determined. The Kohonen neural network allowed an easier visualisation and interpretation of the results and helped to define the relationships among them. In this way, a relationship between DOC and Fe and a possible effect of seasonality on the distribution of the samples were indicated. Signs of lithology were detected in the analyses, especially considering the elements Ca, Mg, Mn and Sr.Sociedade Brasileira de Química2014-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532014000200003Journal of the Brazilian Chemical Society v.25 n.2 2014reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.5935/0103-5053.20130285info:eu-repo/semantics/openAccessGontijo,Erik S. J.Oliveira,Francysmary S. D.Fernandes,Mariana L.Silva,Gilmare A. daRoeser,Hubert M. P.Friese,Kurteng2014-02-14T00:00:00Zoai:scielo:S0103-50532014000200003Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2014-02-14T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
title |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
spellingShingle |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil Gontijo,Erik S. J. Quadrilátero Ferrífero - Brazil dissolved organic carbon Kohonen neural network environmental geochemistry |
title_short |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
title_full |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
title_fullStr |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
title_full_unstemmed |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
title_sort |
Application of a multivariate exploratory analysistechnique in the study of dissolved organic matter and metal ions in waters from the eastern quadrilátero ferrífero, Brazil |
author |
Gontijo,Erik S. J. |
author_facet |
Gontijo,Erik S. J. Oliveira,Francysmary S. D. Fernandes,Mariana L. Silva,Gilmare A. da Roeser,Hubert M. P. Friese,Kurt |
author_role |
author |
author2 |
Oliveira,Francysmary S. D. Fernandes,Mariana L. Silva,Gilmare A. da Roeser,Hubert M. P. Friese,Kurt |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Gontijo,Erik S. J. Oliveira,Francysmary S. D. Fernandes,Mariana L. Silva,Gilmare A. da Roeser,Hubert M. P. Friese,Kurt |
dc.subject.por.fl_str_mv |
Quadrilátero Ferrífero - Brazil dissolved organic carbon Kohonen neural network environmental geochemistry |
topic |
Quadrilátero Ferrífero - Brazil dissolved organic carbon Kohonen neural network environmental geochemistry |
description |
Water samples were collected at 10 points in parts of the eastern Quadrilátero Ferrífero (QF), located in a mining region in the southeast of Brazil. The aims of this study were to find possible relationships among dissolved organic carbon (DOC), metals and other parameters measured in the region studied and evaluate the Kohonen neural network as a tool to analyse this geochemical multivariate data set. Physico-chemical analyses were performed in situ and in the laboratory, where concentrations of DOC and a suite of metal ions were determined. The Kohonen neural network allowed an easier visualisation and interpretation of the results and helped to define the relationships among them. In this way, a relationship between DOC and Fe and a possible effect of seasonality on the distribution of the samples were indicated. Signs of lithology were detected in the analyses, especially considering the elements Ca, Mg, Mn and Sr. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-02-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532014000200003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532014000200003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5935/0103-5053.20130285 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Journal of the Brazilian Chemical Society v.25 n.2 2014 reponame:Journal of the Brazilian Chemical Society (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Journal of the Brazilian Chemical Society (Online) |
collection |
Journal of the Brazilian Chemical Society (Online) |
repository.name.fl_str_mv |
Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
||office@jbcs.sbq.org.br |
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1750318175701958656 |