Assessing mercury pollution in Amazon River tributaries using a Bayesian Network approach
| Autor: | Ashantha Goonetilleke, Buddhi Wijesiri, Ene Glória da Silveira, Marcelo Vergotti, Daniel Marcos Bonotto |
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| Přispěvatelé: | Universidade Estadual Paulista (Unesp), Shenzhen University, Queensland University of Technology (QUT), Fundação Universidade Federal de Rondônia (UNIR) |
| Rok vydání: | 2018 |
| Předmět: |
Hg contamination
Gold mining Geologic Sediments 010504 meteorology & atmospheric sciences Health Toxicology and Mutagenesis Drainage basin chemistry.chemical_element Environmental modelling 010501 environmental sciences 01 natural sciences Mining Rivers parasitic diseases Tributary Water Pollution Chemical Humans Soil Pollutants Water pollution 0105 earth and related environmental sciences Hydrology geography Ecosystem health geography.geographical_feature_category Amazon rainforest business.industry Public Health Environmental and Occupational Health Bayes Theorem General Medicine Mercury Pollution Amazon waters Mercury (element) Lakes chemistry Bayesian Networks Environmental science business Gold extraction Water Pollutants Chemical Environmental Monitoring |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 1090-2414 |
| Popis: | Made available in DSpace on 2019-10-06T15:58:01Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-12-30 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. Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178 College of Chemistry and Environmental Engineering Shenzhen University Science and Engineering Faculty Queensland University of Technology (QUT), GPO Box 2434 Fundação Universidade Federal de Rondônia (UNIR), Av. Presidente Dutra No. 2965 Departamento de Petrologia e Metalogenia Universidade Estadual Paulista (UNESP) Câmpus de Rio Claro, Av. 24-ANo.1515, C.P. 178 |
| Databáze: | OpenAIRE |
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