Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil

Detalhes bibliográficos
Autor(a) principal: Santos,Nelize Lima
Data de Publicação: 2020
Outros Autores: Gomes,Maria da Conceição Rabelo, Anjos,José Ângelo Sebastião Araújo dos, Cunha,Fernanda Gonçalves
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Ambiente & Água
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000500314
Resumo: Abstract This study employed multivariate analysis techniques to identify and evaluate the chemical variables responsible for the contamination of the urban area of ​​Boquira, Bahia, due to the abandonment of the tailings basin of Pb-Zn mining, in order to assist in the environmental management of the area. Factor analysis was performed on main and grouping components. The factor analysis allowed grouping the variables into two main factors for street sediment samples, adding up to 72% of the total accumulated variance, and three factors for house dust samples, which explained 77% of the total variance. The variables have a strong correlation with the composition of the tailings basin. Cluster analysis classified the samples according to the concentration of metals in the area, where the influence of the tailings basin and the natural background of the region's rocks in the contamination distribution can be identified.
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spelling Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazilcluster analysiscontaminationmain component analysisAbstract This study employed multivariate analysis techniques to identify and evaluate the chemical variables responsible for the contamination of the urban area of ​​Boquira, Bahia, due to the abandonment of the tailings basin of Pb-Zn mining, in order to assist in the environmental management of the area. Factor analysis was performed on main and grouping components. The factor analysis allowed grouping the variables into two main factors for street sediment samples, adding up to 72% of the total accumulated variance, and three factors for house dust samples, which explained 77% of the total variance. The variables have a strong correlation with the composition of the tailings basin. Cluster analysis classified the samples according to the concentration of metals in the area, where the influence of the tailings basin and the natural background of the region's rocks in the contamination distribution can be identified.Instituto de Pesquisas Ambientais em Bacias Hidrográficas2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000500314Revista Ambiente & Água v.15 n.5 2020reponame:Revista Ambiente & Águainstname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)instacron:IPABHI10.4136/ambi-agua.2572info:eu-repo/semantics/openAccessSantos,Nelize LimaGomes,Maria da Conceição RabeloAnjos,José Ângelo Sebastião Araújo dosCunha,Fernanda Gonçalveseng2020-10-02T00:00:00Zoai:scielo:S1980-993X2020000500314Revistahttp://www.ambi-agua.net/PUBhttps://old.scielo.br/oai/scielo-oai.php||ambi.agua@gmail.com1980-993X1980-993Xopendoar:2020-10-02T00:00Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)false
dc.title.none.fl_str_mv Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
title Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
spellingShingle Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
Santos,Nelize Lima
cluster analysis
contamination
main component analysis
title_short Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
title_full Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
title_fullStr Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
title_full_unstemmed Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
title_sort Multivariate statistical analysis applied to assess the dispersion of contaminants in a mining tailings basin in the semiarid region of Bahia - Brazil
author Santos,Nelize Lima
author_facet Santos,Nelize Lima
Gomes,Maria da Conceição Rabelo
Anjos,José Ângelo Sebastião Araújo dos
Cunha,Fernanda Gonçalves
author_role author
author2 Gomes,Maria da Conceição Rabelo
Anjos,José Ângelo Sebastião Araújo dos
Cunha,Fernanda Gonçalves
author2_role author
author
author
dc.contributor.author.fl_str_mv Santos,Nelize Lima
Gomes,Maria da Conceição Rabelo
Anjos,José Ângelo Sebastião Araújo dos
Cunha,Fernanda Gonçalves
dc.subject.por.fl_str_mv cluster analysis
contamination
main component analysis
topic cluster analysis
contamination
main component analysis
description Abstract This study employed multivariate analysis techniques to identify and evaluate the chemical variables responsible for the contamination of the urban area of ​​Boquira, Bahia, due to the abandonment of the tailings basin of Pb-Zn mining, in order to assist in the environmental management of the area. Factor analysis was performed on main and grouping components. The factor analysis allowed grouping the variables into two main factors for street sediment samples, adding up to 72% of the total accumulated variance, and three factors for house dust samples, which explained 77% of the total variance. The variables have a strong correlation with the composition of the tailings basin. Cluster analysis classified the samples according to the concentration of metals in the area, where the influence of the tailings basin and the natural background of the region's rocks in the contamination distribution can be identified.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
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=S1980-993X2020000500314
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000500314
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.4136/ambi-agua.2572
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 Instituto de Pesquisas Ambientais em Bacias Hidrográficas
publisher.none.fl_str_mv Instituto de Pesquisas Ambientais em Bacias Hidrográficas
dc.source.none.fl_str_mv Revista Ambiente & Água v.15 n.5 2020
reponame:Revista Ambiente & Água
instname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron:IPABHI
instname_str Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron_str IPABHI
institution IPABHI
reponame_str Revista Ambiente & Água
collection Revista Ambiente & Água
repository.name.fl_str_mv Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
repository.mail.fl_str_mv ||ambi.agua@gmail.com
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