Burial leakage: A human accustomed groundwater contaminant sources and health hazards study near cemeteries in Benin City, Nigeria
Bibliographic record
Abstract
This study was carried out to assess the levels of physico-chemical parameters that could be impacted by burial leakage and associated human health risks in Benin City, Nigeria. A total of thirty groundwater samples were collected from two cemeteries and analysed for pH, alkalinity, chloride, sulphate, nitrate, phosphate, ammonia- N, calcium, sodium, potassium, BOD₅, COD, Mn, Cd, Cu, Ni, Pb, Zn and Fe. The concentrations of the parameters were compared to national and international standards. The results revealed that the groundwater is highly acidic in nature. Principal component analysis (PCA) revealed that except for alkalinity, all other parameters characterised contributed significantly to various principal components (PC) with eigenvalues ≥ 1. Moreover, the significance of the PC depicted decomposition of the body corpse and associated burial materials. Water quality index (WQI), heavy metal evaluation index (HEI) and Nemerov pollution index (NI) indicated that groundwater from the study area is of poor quality, and highly contaminated by heavy metals. We determined the Chronic health risk through exposure by calculating the hazard quotient (HQ) and hazard index (HI), for both children and adults. For the oral exposure, approximately 33% of samples suggest the high category of chronic risk for children while the medium category was indicated for adults. We found that oral exposure showed relatively higher risk than dermal exposure, and chronic risk for children and adults ranged from low to negligible. However, the carcinogenic risk of Ni and Pb via oral exposure route suggests, very high risk for Ni and medium risk for Pb. In consideration that long term exposure to low concentrations of some heavy metals (including Pb, Cd, and Ni) could result in different manifestations of cancer, we recommend that residents of these areas should find an alternative source of water for drinking and other domestic uses.
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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".