Mercury Exposure Assessment and Spatial Distribution in A Ghanaian Small-Scale Gold Mining Community
Bibliographic record
Abstract
Mercury is utilized worldwide in artisanal and small-scale gold mining (ASGM) and may pose a risk for miners and mining communities. While a number of studies have characterized mercury in ASGM communities, most have focused on a single media and few have taken a holistic approach. Here, a multiple media exposure assessment and cross-sectional study of mercury was conducted in 2010 through 2012 in northeast Ghana with a small-scale gold mining community, Kejetia, a subsistence farming community, Gorogo, and an urban ASGM gold refinery in Bolgatanga. The objective was to assess mercury in a range of human (urine and hair) and ecological (household soil, sediment, fish, and ore) samples to increase understanding of mercury exposure pathways. All participants were interviewed on demographics, occupational and medical histories, and household characteristics. Participants included 90 women of childbearing age and 97 adults from Kejetia and 75 adults from Gorogo. Median total specific gravity-adjusted urinary, hair, and household soil mercury were significantly higher in Kejetia miners (5.18 µg/L, 0.967 µg/g, and 3.77 µg/g, respectively) than Kejetia non-miners (1.18 µg/L, 0.419 µg/g, and 2.00 µg/g, respectively) and Gorogo participants (0.154 µg/L, 0.181 µg/g, and 0.039 µg/g) in 2011. Sediment, fish, and ore Hg concentrations were below guideline values. Median soil mercury from the Bolgatanga refinery was very high (54.6 µg/g). Estimated mean mercury ingestion for Kejetia adults from soil and dust exceeded the U.S. Environmental Protection Agency reference dose (0.3 µg Hg/kg·day) for pica (0.409 µg Hg/kg·day) and geophagy (20.5 µg Hg/kg·day) scenarios. Most participants with elevated urinary and household soil mercury were miners, but some non-miners approached and exceeded guideline values, suggesting a health risk for non-mining residents living within these communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".