Heavy metal characteristics of groundwater in Ibadan South Western, Nigeria
Bibliographic record
Abstract
Full Length Research Paper Heavy metal characteristics of groundwater in Ibadan South Western, Nigeria Laniyan, T. A.*, Bayewu, O. O. and Ariyo, S. O. Department of Earth Sciences, Olabisi Onabanjo University, Ago-Iwoye, Nigeria. *Corresponding author. E-mail: ttlaniyan@yahoo.com Accepted 12 July, 2013 Abstract Water, an essential commodity is consequently being affected by natural and human activities. Investigations were made on groundwater of the study area to evaluate the impact of heavy metals. Groundwater samples were collected and analyzed using Inductively coupled plasma- emission spectrometry method, at Acme laboratories Canada. Geochemical analysis revealed a significant concentration of increasing order K > Ca > Mg > Fe > Zn > Cu > Pb > As > Cd. Ca, Fe and K were above the WHO standard. Index of geo-accumulation (Igeo), revealed no contamination of the trace metals. Inter-elemental analysis showed a strong correlation between Cd to Zn (‘r’- 0.983) and Fe to Pb (‘r’-0.900), indicating that the metals are governed by the same geochemical factors and are from the same anthropogenic source. Piezometric map revealed southwest direction of groundwater flow that shows direction of contamination influx. The study can then be concluded to be contaminated with Ca, Fe and K due to the impact of man’s activities in the environment. Public health effect of these metals could be anemia, kidney damage, brain damage, cancer and ultimately death. Key words: Water, contamination degree, geochemical factors, public health, heavy metal.
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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 | 0.001 | 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".