Heavy Metal Pollution and Human Health Risk Assessment of Farmlands around Enyigba Lead-Zinc Mining Site, Ebonyi State, Nigeria
Bibliographic record
Abstract
This study evaluated the chemical forms of heavy metals contamination in soil, its level in vegetables and the health risks for resident farmers within vicinity of Pb-Zn mining site in Enyigba Community, Abakaliki, Ebonyi State, Nigeria. Soil and vegetable samples were obtained from mapped farmlands within the vicinity of the mining sites and farmlands in non-mining site as control and analyzed using standard analytical protocols. The results showed high % association of Cd, Pb, Fe and Zn in non-residual fraction and high % association of Cu, Cr and Ni in residual fraction, the order of % mobility and bioavailability of the metals were: Pb > Cd > Fe > Zn > Cr > Ni > Cu. Results of geoaccumulation index (Igeo) indicated that the mine site soils were moderately to strongly polluted with Cd Cu, Pb and Zn while the control site was unpolluted with any of the metals. The results also indicated that the vegetables and indeed the ingestion route was the most significant contributor to non-carcinogenic risk followed by dermal contact and then inhalation. Total Hazard index (THI) for adult and children for all the studied metals were 1.68 and 4.50 respectively for Ishiagu-Enyigba site, 1.42 and 3.98 respectively for Elinwobvu-Enyigba site and 0.68 and 1.91 respectively for Ekawoke (control) site and these exceeded the safe level (>1). The total cancer risk were 1.51 X 10 -6 , 1.06 X 10 -6 and 2.14X 10 -7 for Ishiagu-Enyigba, Elinwobvu-Enyigba and control site respectively and they all fall within and below the threshold safe range (10 -6 -10 -4 ) set by United States Environmental Protection Agency. These results strongly indicated non-carcinogenic risk of soil multiple heavy metals toxicity to humans especially in children. This calls for suitable policy for effective management of the environmental risk to ensure favourable public health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".