Evidence map›Paper›PMID 42474546›Full record

ArticleEnvironmental geochemistry and health2026

Land use controls the spatiotemporal patterns of surface water quality of the Quadrilátero Ferrífero mineral province, Brazil.

Gabriel Soares de Almeida, Rafael Tarantino Amarante, Normara Yane Mar da Costa Andrade, Roberto Dall'Agnol, Prafulla Kumar Sahoo, Paulo Rógenes Monteiro Pontes, Emmanoel Vieira Silva-Filho, Eduardo Duarte Marques, Raquel Fernandes Mendonça, Abraão Gomes Soares Junior and 1 more

Abstract read
In one paragraph

Article in Environmental geochemistry and health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Gabriel Soares de AlmeidaInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil. gsoares.geo@gmail.com.ORCID https://orcid.org/0000-0001-7983-8030
Rafael Tarantino AmaranteInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil.
Normara Yane Mar da Costa AndradeInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil.
Roberto Dall'AgnolInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil.
Prafulla Kumar SahooDepartament of Environmental Science and Technology, School of Environment and Earth Sciences, Central University of Punjab, VPO-Ghudda, Bathinda, Punjab, 151401, India.
Paulo Rógenes Monteiro PontesInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil.
Emmanoel Vieira Silva-FilhoGeosciences Institute, Universidade Federal Do Pará, Belém, Pará, Brasil.
Eduardo Duarte MarquesPrograma de Pós-Graduação Em Geociências (Geoquímica), Instituto de Química, Universidade Federal Fluminense, Outeiro São João Batista S/N - Centro, Niterói, RJ, 24020-141, Brasil.
Raquel Fernandes MendonçaVale S.A., Environmental Management Executive Department, Nova Lima, Minas Gerais, Brasil.
Abraão Gomes Soares JuniorVale S.A., Environmental Management Executive Department, Nova Lima, Minas Gerais, Brasil.
Gabriel Negreiros SalomãoInstituto Tecnológico Vale (ITV), Rua Boaventura da Silva, 955, Belém, PA, Brasil.

Funding

Fundação Amparo e Desenvolvimento da Pesquisa 1432799Fundação Guamá 1458822National Council for Scientific and Technological Development 305469/2024
6 · The paper itself

Abstract

Surface water quality in the Quadrilátero Ferrífero, a mining province in southeastern Brazil, was evaluated by combining water quality indices (WQI), land use and land cover (LULC), and population data to identify spatial and seasonal influences on river chemistry. We analyzed 835 (rainy) and 845 (dry) samples and calculated WQI scores using established methods from the literature. The methods for calculating the WQI detected broad signals of eutrophication and those related to sanitation but were less sensitive to inorganic and potentially toxic elements (PTE), whereas CCME, especially when including PTE variables, offered a more rigorous and adaptable assessment for mining-influenced areas. Microcatchments were classified into LULC groups based on the proportional dominance and co-occurrence of classes. Across methods and seasons, WQI values showed a clear degradation gradient aligned with increasing human activity. Catchments dominated by natural cover and low-intensity uses consistently exhibited the highest WQI values; notably, mining-influenced classes with substantial natural vegetation often clustered towards this higher-quality end. In contrast, catchments shaped by human occupation in urban and rural settings showed the lowest WQI scores and were statistically distinct from the low-intensity group in most pairwise comparisons, although overlaps occurred among the anthropogenic classes depending on method and season. Total population per micro-catchment was inversely related to WQI results by IGAM method in both seasons, highlighting the impact of urban expansion and infrastructure pressures on water-quality decline. Overall, the LULC-based microcatchment classification was crucial for understanding how dominant land use patterns influence water quality and for guiding targeted watershed management in mining regions.

Indexed as

Environmental MonitoringRiversWater Pollutants, ChemicalWater QualityBrazilEutrophicationHumansMiningSeasonsSpatio-Temporal AnalysisWater Pollutants, ChemicalAnthropogenic impactsEnvironmental monitoringHydrogeochemistryLand use changeQuadrilátero FerríferoWater Quality Index (WQI)

Identifiers

PMID42474546
PMCPMC13385133

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LicenceCC BY
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Registered trials

None linked

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.