Seasonal variation of water quality parameters of surface water in mining areas
Bibliographic record
Abstract
Purpose Total organic carbon (TOC), dissolved organic carbon (DOC) and other physicochemical parameters of the Birim River, which serves for drinking and domestic purposes for rural mining communities, were analysed to assess the suitability of water quality for human consumption. Design/methodology/approach In total, 40 samples were collected from 20 sampling sites during the rainy season from July to September and the dry season from December to February in addition to two repeat samples and two blank samples. Samples were analysed for physiochemical parameters and the results were compared with World Health Organisation standards (WHO). Findings Data obtained for both rainy and dry seasons indicated TOC ranged from 1.1 to 7.3 mg/L and DOC 1–7.2 mg/L; pH, 5.6–8.63; temperature, 23.3–29.3°C; turbidity, <1.00–869NTU; apparent colour, <2.5–600 mg/L Pt-Co; true colour <2.5–150 mg/L Pt-Co; alkalinity, 27.8–80.4 mg/L; total suspended solids, <1.00–998 mg/L; electrical conductivity, 82–184 µS/cm; and bicarbonate, 33.9–98.1 mg/L. Particulate organic carbon (POC) was constituted between 1 and 10% of the TOC. Values for pH, turbidity, total suspended solids, and true colour indicated contamination of the river. p -value of <0.05 between seasons for the physicochemical parameters also suggests that the water is polluted. Practical implications Water from the Birim River is unsuitable for human consumption and may constitute a serious health risk to the consumers. Originality/value The paper yields immense value to inhabitant of communities using surface water affected by mining activities, policy makers in sustainability. It warns of the unsuitability of water from the Birim River for human consumption due to the potential health risk to consumers.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".