Evidence map›Paper›PMID 42625077›Full record

ArticleEnvironmental monitoring and assessment2026

Assessment of heavy metals and naturally occurring radioactive materials (NORM) from historical mine wastelands: a case study of Brakpan, South Africa.

Tobius Mawase Mogale, Memory Tekere, Khumbudzo Walter Maphangwa

Abstract read
In one paragraph

Article in Environmental monitoring and assessment, 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. Review
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

3 authors.

Tobius Mawase MogaleDepartment of Environmental Sciences, University of South Africa, Science Campus, Johannesburg, 1710, South Africa. tobiusmogale@gmail.com.
Memory TekereDepartment of Environmental Sciences, University of South Africa, Science Campus, Johannesburg, 1710, South Africa.
Khumbudzo Walter MaphangwaDepartment of Environmental Sciences, University of South Africa, Science Campus, Johannesburg, 1710, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mining has contributed to South Africa's development, but its legacy has left more than 6000 abandoned sites, with Brakpan in South Africa among the most affected areas. This study assessed heavy metals and naturally occurring radioactive materials (NORM) in the Brakpan mine wasteland in Gauteng Province, South Africa. Soil and water samples from the area were analysed using inductively coupled plasma mass spectrometry (ICP-MS) for heavy metals and high-purity germanium gamma-ray spectrometry (HPGe) was used for NORM analysis. The results showed elevated concentrations of several contaminants. In soils, chromium (103.98 mg/kg) and arsenic (47.75 mg/kg) were notably enriched, while uranium exhibited the highest mean concentration (7.14 mg/kg), exceeding the South African soil quality guidelines for contaminated land. Water samples showed high concentration of uranium (mean 1.64 mg/L) and nickel (12.78 mg/L) concentrations, exceeding guideline values for agricultural use and aquatic ecosystem protection value of 0.03 mg/L and 0.04 mg/L, respectively. Suggesting potential risks to downstream water users and ecological receptors. Radiological analysis revealed activity concentrations of

Indexed as

Metals, HeavyMiningSoil PollutantsSoil Pollutants, RadioactiveEnvironmental MonitoringRadiation MonitoringSouth AfricaUraniumMetals, HeavySoil PollutantsSoil Pollutants, RadioactiveUraniumBrakpan (Kwa-Thema South Africa)Environmental contaminationHeavy metalsMine wastelandsNORMsRadiological hazards

Identifiers

PMID42625077
PMCPMC13493453

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Registered trials

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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.