Multivariate Chemometric Analysis of a Polluted River of a Megalopolis

Autores
Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Vracko, Marjan; Zupan, Jure; Reich, Silvia Leonor; Cicerone, Daniel
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels.
Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
Fil: Vracko, Marjan. National Institute of Chemistry; Eslovenia
Fil: Zupan, Jure. National Institute of Chemistry; Eslovenia
Fil: Reich, Silvia Leonor. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina
Fil: Cicerone, Daniel. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina
Materia
SURFACE WATER
WATER POLLUTION
CHEMOMETRIC
MULTIVARIATE STATISTIC
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/129647
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Multivariate Chemometric Analysis of a Polluted River of a MegalopolisGarcia Reiriz, Alejandro GabrielMagallanes, Jorge FedericoVracko, MarjanZupan, JureReich, Silvia LeonorCicerone, DanielSURFACE WATERWATER POLLUTIONCHEMOMETRICMULTIVARIATE STATISTIChttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels.Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; ArgentinaFil: Vracko, Marjan. National Institute of Chemistry; EsloveniaFil: Zupan, Jure. National Institute of Chemistry; EsloveniaFil: Reich, Silvia Leonor. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; ArgentinaFil: Cicerone, Daniel. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; ArgentinaScientific Research2011-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/129647Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Vracko, Marjan; Zupan, Jure; Reich, Silvia Leonor; et al.; Multivariate Chemometric Analysis of a Polluted River of a Megalopolis; Scientific Research; Journal of Environmental Protection; 2; 7; 9-2011; 903-9142152-21972152-2219CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.scirp.org/journal/paperinformation.aspx?paperid=7414info:eu-repo/semantics/altIdentifier/doi/10.4236/jep.2011.27103info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:02:21Zoai:ri.conicet.gov.ar:11336/129647instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:02:22.147CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
title Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
spellingShingle Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
Garcia Reiriz, Alejandro Gabriel
SURFACE WATER
WATER POLLUTION
CHEMOMETRIC
MULTIVARIATE STATISTIC
title_short Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
title_full Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
title_fullStr Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
title_full_unstemmed Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
title_sort Multivariate Chemometric Analysis of a Polluted River of a Megalopolis
dc.creator.none.fl_str_mv Garcia Reiriz, Alejandro Gabriel
Magallanes, Jorge Federico
Vracko, Marjan
Zupan, Jure
Reich, Silvia Leonor
Cicerone, Daniel
author Garcia Reiriz, Alejandro Gabriel
author_facet Garcia Reiriz, Alejandro Gabriel
Magallanes, Jorge Federico
Vracko, Marjan
Zupan, Jure
Reich, Silvia Leonor
Cicerone, Daniel
author_role author
author2 Magallanes, Jorge Federico
Vracko, Marjan
Zupan, Jure
Reich, Silvia Leonor
Cicerone, Daniel
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv SURFACE WATER
WATER POLLUTION
CHEMOMETRIC
MULTIVARIATE STATISTIC
topic SURFACE WATER
WATER POLLUTION
CHEMOMETRIC
MULTIVARIATE STATISTIC
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels.
Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
Fil: Vracko, Marjan. National Institute of Chemistry; Eslovenia
Fil: Zupan, Jure. National Institute of Chemistry; Eslovenia
Fil: Reich, Silvia Leonor. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina
Fil: Cicerone, Daniel. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina
description A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels.
publishDate 2011
dc.date.none.fl_str_mv 2011-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/129647
Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Vracko, Marjan; Zupan, Jure; Reich, Silvia Leonor; et al.; Multivariate Chemometric Analysis of a Polluted River of a Megalopolis; Scientific Research; Journal of Environmental Protection; 2; 7; 9-2011; 903-914
2152-2197
2152-2219
CONICET Digital
CONICET
url http://hdl.handle.net/11336/129647
identifier_str_mv Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Vracko, Marjan; Zupan, Jure; Reich, Silvia Leonor; et al.; Multivariate Chemometric Analysis of a Polluted River of a Megalopolis; Scientific Research; Journal of Environmental Protection; 2; 7; 9-2011; 903-914
2152-2197
2152-2219
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.scirp.org/journal/paperinformation.aspx?paperid=7414
info:eu-repo/semantics/altIdentifier/doi/10.4236/jep.2011.27103
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Scientific Research
publisher.none.fl_str_mv Scientific Research
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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