ArticleScientific reports2020
Metal concentrations and biological effects from one of the largest mining disasters in the world (Brumadinho, Minas Gerais, Brazil).
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 156 citations in OpenAlex.
- Trace metals contamination in freshwater fish in Brazil: related factors, environmental impacts, and risks to human health.Environmental monitoring and assessment · 2026Pooled it
- Can a Top Predator Persist After One of the World's Largest Mining Dam Failures? Occupancy Dynamics of the Neotropical Otter in Brazil's Paraopeba River.Ecology and evolution · 2026Article
- North-South asymmetry of Parkinson's disease mortality in Brazil between 2009 and 2023: a spatial analysis.Scientific reports · 2026Article
- Impacts of Metals on Infectious Diseases in Wildlife and Zoonotic Spillover.Journal of xenobiotics · 2025Review
- Proposal of novel Predicted No Effect Concentrations (PNEC) for metals in freshwater using Species Sensitivity Distribution for different taxonomic groups.Scientific reports · 2025Article
- Genomic features of a multidrug-resistant and mercury-tolerant environmental Escherichia coli recovered after a mining dam disaster in South America.The Science of the total environment · 2022Article
- Genomic Resources forFrontiers in genetics · 2022Article
- Manganese-Induced Neurotoxicity through Impairment of Cross-Talk Pathways in Human Neuroblastoma Cell LineToxics · 2021Article
- Mining Dam Failures in Brazil: Comparing Legal Post-Disaster Decisions.International journal of environmental research and public health · 2021Article
- Lonchocarpus cultratus, a Brazilian savanna tree, endures high soil Pb levels.Environmental science and pollution research international · 2021Article
- Physicochemical, microbiological quality, and risk assessment of water consumed by a quilombola community in midwestern Brazil.Environmental science and pollution research international · 2021Article
- N-compounds speciation analysis in environmental samples using ultrasound-assisted solid-liquid extraction and non-chromatographic techniques.Environmental monitoring and assessment · 2021Article
- Social injustice in environmental health: A call for fortitude.Environmental research · 2021Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rupture of the Brumadinho mining tailings dam in Brazil is considered one of the largest mining disasters in the world, resulting in 244 deaths and 26 missing people, in addition to the environmental consequences. The present study aims to evaluate the concentrations of multiple elements and the biological effects on water and sediments of the Paraopeba River after the Brumadinho Dam rupture. The tailings are formed by fine particulate material with large amounts of Fe, Al, Mn, Ti, rare earth metals and toxic metals. In the water, the levels of Fe, Al, Mn, Zn, Cu, Pb, Cd and U were higher than those allowed by Brazilian legislation. In the sediments, Cr, Ni, Cu and Cd levels were higher than the established sediment quality guidelines (TEL-NOAA). The differences in metal concentrations in the water and sediments between the upstream and downstream sides of the dam illustrate the effect of the tailings in the Paraopeba River. Toxicological tests demonstrated that the water and sediments were toxic to different trophic levels, from algae to microcrustaceans and fish. The fish exposed to water and sediments containing mine ore also accumulated metals in muscle tissue. This evaluation emphasizes the necessity of long-term monitoring in the affected area.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.