An Assessment of Environmental Health Impacts of Toxic Chemical-Micronutrient Consumption in Groundwater from Dutse, Northwestern Nigeria
Bibliographic record
Abstract
Background: Availability of water in the desired quantity and quality has been the key to human survival. This research assessed groundwater quality being consumed by the citizens of Dutse Area of Jigawa State, Northwestern Nigeria. Methods: Sixty groundwater samples (hand-dug wells and boreholes) from fifteen locations were analyzed for physical, chemical and biological parameters in order to determine their quality and potential health impact on the consumers/residents of this area. The parameters analyzed in the field were pH, Electrical Conductivity (EC) and temperature using standard methods. The sodium and potassium were analysed using flame photometer; sulphate, nitrate and phosphate using spectrophotometer; while calcium, magnesium, bicarbonate and chloride were analysed using titrimetric method. Analysis of metals in the groundwater samples was achieved through Inductively Coupled Plasma Mass Spectrometry at Activation Laboratory in Canada. Microbial load was analysed by serial dilution and counting. Results: The results showed that mean values of the physico-chemical parameters ranged as follows: pH, 5.00-7.00; temperature, 23.0-29.0 oC; EC, 190-2100 µs/cm; chloride, 34.55-690.90 mg/L; sulphate, 3.0-96.0 mg/L; bicarbonate, 20.0-60.0 mg/L; phosphate, 0.00-0.05 mg/L; nitrate, 0.05-0.47 mg/L; calcium, 18.1-462.4 mg/L; magnesium, 16.2-204.5 mg/L; sodium, 4.00-72.00 mg/L and potassium, 0.24-5.88 mg/L. The results of the heavy metal analysis shows the range of concentration of the following toxic metals: Aluminium, 20.0-853.0 µg/L; Cadmium, 0.05-0.23 µg/L; Lead, 0.87-22.8 µg/L; Mercury, 0.6-1.0 µg/L; Arsenic, 0.1-0.33 µg/L; Chromium, 0.2-0.3 µg/L; Berrylium, 0.5-1.2 µg/L and Cobalt, 0.09-0.71 µg/L. These were generally found to be within the WHO standard except in few cases. Similarly, the result of the microbial analysis shows the presence of Escherichia coli in almost all the groundwater samples. Conclusion: Cumulative effect of toxic metal in the consumed groundwater of the study area portends the risk of cancer and related diseases.
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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 | 0.000 | 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".