Assessment of selected major and trace elements in groundwater of Lagos based on land use and implication on human health
Bibliographic record
Abstract
Abstract Sixty-seven (67) groundwater samples from different land use areas such as dumpsites, industrial, markets and residential all within Lagos, southwest Nigeria, were sampled and sent to ACME Laboratories, Ontario, Canada, for geochemical analysis to determine some essential and toxic elements using inductively coupled plasma-mass spectrometer method. The purpose was to establish baseline values for the geochemical composition of groundwater in some parts of Lagos as well as the health risk assessment. Based on essential elements, 83%, 80% and 100% of groundwater samples were deficient in Ca, Mg and Se, respectively, while 75%, 10%, 7% and 8% of samples can be categorised as soft, moderately hard, hard and very hard water, respectively. The soft water, as well as different deficiencies in water, had been linked to heart problems, impeded growth, fertility disorders and liver diseases. Concentrations of As, Cd, Cr, Pb, Ni and Fe were higher than recommended standards in 2.94%, 1.5%, 1.5%, 29.4%, 4.4% and 4.7% of groundwater samples, respectively. Groundwater in the study area can be classified between not contaminated (< 1) to very highly contaminated (CI > 5) based on the contamination index. Highly contaminated samples were within dumpsites and industrial areas. The land-use activities have a direct or indirect impact on groundwater quality. The apparent sources of groundwater pollutants include industrial discharge, effluents, leachates and municipal wastes. The result of total health risk index for both ingestion and dermal exposure to water showed values far > 1 for all the toxic elements and generally pose non-carcinogenic health risk hazards for child and adult population in the study area. THI for samples from residential, market, industrial and dumpsites showed mean values of (9.60 and 3.75), (14.17 and 5.37), (9.8 and 3.4) and 95.44 and 37.48) for child and adult population, respectively. The degree of contamination in groundwater showed the following trends: dumpsite > industrial > markets > residential in the study area.
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 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) | 0.001 | 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".