Geogenic contaminants and groundwater quality around Lake Victoria goldfields in northwestern Tanzania
Bibliographic record
Abstract
Geogenic contamination of groundwater is frequently associated with gold mining activities and related to drinking water quality problems worldwide. In Tanzania, elevated levels of trace elements (TEs) have been reported in drinking water sources within the Lake Victoria Basin, posing a serious health risk to communities. The present study aims to assess the groundwater quality with a focus on the concentration levels of geogenic contaminants in groundwater around the Lake Victoria goldfields in Geita and Mara districts. The water samples were collected from community drinking water sources and were analysed for physiochemical parameters (pH, EC, Eh), major ions, and trace elements. The analysed major ions included Na+, K+, Ca2+, Mg2+, SO42−, HCO3− and Cl− whereas the trace elements were As, Al, Li, Ba, B, Ti, V, U, Zr, Sr, Si, Mn Mo, Fe, Ni, Zn, Cr, Pb, Cd, and V. The present study revealed that the concentration levels of the major ions were mostly within the World Health Organization (WHO) drinking water standards in the following order of their relative abundance; for cations, Ca2+∼Na+>Mg2+>K+ and for anions was HCO3− > SO42− > NO3−, Cl− > PO43−. Statistical and geochemical modelling software such as ‘R Studio’, IBM SPSS, geochemical workbench, visual MINTEQ were used to understand the groundwater chemistry and evaluate its suitability for drinking purpose. The concentration of As in groundwater sources varies between below detection limit (bdl) and 300 μg/L, with highest levels in streams followed by shallow wells and boreholes. In approximately 48% of the analysed samples, As concentration exceeded the WHO drinking water guideline and Tanzania Bureau of Standards (TBS) guideline for drinking water value of 10 μg/L. The concentration of the analyzed TEs and mean values of physicochemical parameters were below the guideline limits based on WHO and TBS standards. The Canadian Council of Ministries of the Environment Water Quality Index (CCME WQI) shows that the overall water quality is acceptable with minimum threats of deviation from natural conditions. We recommend further geochemical exploration and the periodic risk assessment of groundwater in mining areas where high levels of As were recorded.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".