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Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest

Fifty-four water samples were collected between July and December 2019 at nine monitoring stations and fifteen parameters were analysed to provide an updated diagnosis of the Piabanha River water quality. Further, forty years of monitoring were analysed, including government data and previous resear...

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Autores principales: de Andrade Costa, David, Soares de Azevedo, José Paulo, dos Santos, Marco Aurélio, dos Santos Facchetti Vinhaes Assumpção, Rafaela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744518/
https://www.ncbi.nlm.nih.gov/pubmed/33328517
http://dx.doi.org/10.1038/s41598-020-78563-0
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author de Andrade Costa, David
Soares de Azevedo, José Paulo
dos Santos, Marco Aurélio
dos Santos Facchetti Vinhaes Assumpção, Rafaela
author_facet de Andrade Costa, David
Soares de Azevedo, José Paulo
dos Santos, Marco Aurélio
dos Santos Facchetti Vinhaes Assumpção, Rafaela
author_sort de Andrade Costa, David
collection PubMed
description Fifty-four water samples were collected between July and December 2019 at nine monitoring stations and fifteen parameters were analysed to provide an updated diagnosis of the Piabanha River water quality. Further, forty years of monitoring were analysed, including government data and previous research projects. A georeferenced database was also built containing water management data. The Water Quality Index from the National Sanitation Foundation (WQI(NSF)) was calculated using two datasets and showed an improvement in overall water quality, despite still presenting systematic violations to Brazilian standards. Principal components analysis (PCA) showed the most contributing parameters to water quality and enabled its association with the main pollution sources identified in the geodatabase. PCA showed that sewage discharge is still the main pollution source. The cluster analysis (CA) made possible to recommend the monitoring network optimization, thereby enabling the expansion of the monitoring to other rivers. Finally, the diagnosis provided by this research establishes the first step towards the Framing of water resources according to their intended uses, as established by the Brazilian National Water Resources Policy.
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spelling pubmed-77445182020-12-17 Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest de Andrade Costa, David Soares de Azevedo, José Paulo dos Santos, Marco Aurélio dos Santos Facchetti Vinhaes Assumpção, Rafaela Sci Rep Article Fifty-four water samples were collected between July and December 2019 at nine monitoring stations and fifteen parameters were analysed to provide an updated diagnosis of the Piabanha River water quality. Further, forty years of monitoring were analysed, including government data and previous research projects. A georeferenced database was also built containing water management data. The Water Quality Index from the National Sanitation Foundation (WQI(NSF)) was calculated using two datasets and showed an improvement in overall water quality, despite still presenting systematic violations to Brazilian standards. Principal components analysis (PCA) showed the most contributing parameters to water quality and enabled its association with the main pollution sources identified in the geodatabase. PCA showed that sewage discharge is still the main pollution source. The cluster analysis (CA) made possible to recommend the monitoring network optimization, thereby enabling the expansion of the monitoring to other rivers. Finally, the diagnosis provided by this research establishes the first step towards the Framing of water resources according to their intended uses, as established by the Brazilian National Water Resources Policy. Nature Publishing Group UK 2020-12-16 /pmc/articles/PMC7744518/ /pubmed/33328517 http://dx.doi.org/10.1038/s41598-020-78563-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
de Andrade Costa, David
Soares de Azevedo, José Paulo
dos Santos, Marco Aurélio
dos Santos Facchetti Vinhaes Assumpção, Rafaela
Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title_full Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title_fullStr Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title_full_unstemmed Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title_short Water quality assessment based on multivariate statistics and water quality index of a strategic river in the Brazilian Atlantic Forest
title_sort water quality assessment based on multivariate statistics and water quality index of a strategic river in the brazilian atlantic forest
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744518/
https://www.ncbi.nlm.nih.gov/pubmed/33328517
http://dx.doi.org/10.1038/s41598-020-78563-0
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