Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.ecoenv.2018.09.099 http://hdl.handle.net/11449/188125 |
Resumo: | Mercury pollution of water bodies exerts significant human and ecosystem health impacts due to high toxicity. Relatively high levels of mercury have been detected in the Amazon River and its tributaries and associated lakes. The study employed a Bayesian Network approach to investigate the contribution from geogenic sources to mercury pollution of lakes in the Madeira River basin, which is the largest tributary of the Amazon River. It was found that the source indicators of naturally occurring mercury have both, positive and negative relationships with mercury in lake sediments. Although the positive relationships indicated the influence of geological and soil formations, the negative relationships implied that the use of mercury amalgam for gold extraction in artisanal and small-scale mining (ASM), which is the primary anthropogenic source of mercury, also contribute to mercury in Amazon tributaries. This was further evident as mercury concentrations in lake sediments were found to be significantly higher than those in the surrounding rocks. However, potential anthropogenic mercury was attributed to historical inputs from gold mining due to the recent decline of ASM mining practice in the region. |
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Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approachAmazon watersBayesian NetworksEnvironmental modellingHg contaminationWater pollutionMercury pollution of water bodies exerts significant human and ecosystem health impacts due to high toxicity. Relatively high levels of mercury have been detected in the Amazon River and its tributaries and associated lakes. The study employed a Bayesian Network approach to investigate the contribution from geogenic sources to mercury pollution of lakes in the Madeira River basin, which is the largest tributary of the Amazon River. It was found that the source indicators of naturally occurring mercury have both, positive and negative relationships with mercury in lake sediments. Although the positive relationships indicated the influence of geological and soil formations, the negative relationships implied that the use of mercury amalgam for gold extraction in artisanal and small-scale mining (ASM), which is the primary anthropogenic source of mercury, also contribute to mercury in Amazon tributaries. This was further evident as mercury concentrations in lake sediments were found to be significantly higher than those in the surrounding rocks. However, potential anthropogenic mercury was attributed to historical inputs from gold mining due to the recent decline of ASM mining practice in the region.Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178College of Chemistry and Environmental Engineering Shenzhen UniversityScience and Engineering Faculty Queensland University of Technology (QUT), GPO Box 2434Fundação Universidade Federal de Rondônia (UNIR), Av. Presidente Dutra No. 2965Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178Universidade Estadual Paulista (Unesp)Shenzhen UniversityQueensland University of Technology (QUT)Fundação Universidade Federal de Rondônia (UNIR)Bonotto, Daniel Marcos [UNESP]Wijesiri, BuddhiVergotti, Marceloda Silveira, Ene GlóriaGoonetilleke, Ashantha2019-10-06T15:58:01Z2019-10-06T15:58:01Z2018-12-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article354-358http://dx.doi.org/10.1016/j.ecoenv.2018.09.099Ecotoxicology and Environmental Safety, v. 166, p. 354-358.1090-24140147-6513http://hdl.handle.net/11449/18812510.1016/j.ecoenv.2018.09.0992-s2.0-85054088863Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEcotoxicology and Environmental Safetyinfo:eu-repo/semantics/openAccess2021-10-23T00:57:26Zoai:repositorio.unesp.br:11449/188125Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:51:10.365170Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
title |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
spellingShingle |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach Bonotto, Daniel Marcos [UNESP] Amazon waters Bayesian Networks Environmental modelling Hg contamination Water pollution |
title_short |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
title_full |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
title_fullStr |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
title_full_unstemmed |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
title_sort |
Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach |
author |
Bonotto, Daniel Marcos [UNESP] |
author_facet |
Bonotto, Daniel Marcos [UNESP] Wijesiri, Buddhi Vergotti, Marcelo da Silveira, Ene Glória Goonetilleke, Ashantha |
author_role |
author |
author2 |
Wijesiri, Buddhi Vergotti, Marcelo da Silveira, Ene Glória Goonetilleke, Ashantha |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Shenzhen University Queensland University of Technology (QUT) Fundação Universidade Federal de Rondônia (UNIR) |
dc.contributor.author.fl_str_mv |
Bonotto, Daniel Marcos [UNESP] Wijesiri, Buddhi Vergotti, Marcelo da Silveira, Ene Glória Goonetilleke, Ashantha |
dc.subject.por.fl_str_mv |
Amazon waters Bayesian Networks Environmental modelling Hg contamination Water pollution |
topic |
Amazon waters Bayesian Networks Environmental modelling Hg contamination Water pollution |
description |
Mercury pollution of water bodies exerts significant human and ecosystem health impacts due to high toxicity. Relatively high levels of mercury have been detected in the Amazon River and its tributaries and associated lakes. The study employed a Bayesian Network approach to investigate the contribution from geogenic sources to mercury pollution of lakes in the Madeira River basin, which is the largest tributary of the Amazon River. It was found that the source indicators of naturally occurring mercury have both, positive and negative relationships with mercury in lake sediments. Although the positive relationships indicated the influence of geological and soil formations, the negative relationships implied that the use of mercury amalgam for gold extraction in artisanal and small-scale mining (ASM), which is the primary anthropogenic source of mercury, also contribute to mercury in Amazon tributaries. This was further evident as mercury concentrations in lake sediments were found to be significantly higher than those in the surrounding rocks. However, potential anthropogenic mercury was attributed to historical inputs from gold mining due to the recent decline of ASM mining practice in the region. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-30 2019-10-06T15:58:01Z 2019-10-06T15:58:01Z |
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.ecoenv.2018.09.099 Ecotoxicology and Environmental Safety, v. 166, p. 354-358. 1090-2414 0147-6513 http://hdl.handle.net/11449/188125 10.1016/j.ecoenv.2018.09.099 2-s2.0-85054088863 |
url |
http://dx.doi.org/10.1016/j.ecoenv.2018.09.099 http://hdl.handle.net/11449/188125 |
identifier_str_mv |
Ecotoxicology and Environmental Safety, v. 166, p. 354-358. 1090-2414 0147-6513 10.1016/j.ecoenv.2018.09.099 2-s2.0-85054088863 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ecotoxicology and Environmental Safety |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
354-358 |
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 |
|
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1808129366513680384 |