Evaluation of potentially toxic elements in soils developed on limestone and lead-zinc mine sites in parts of southeastern Nigeria
Bibliographic record
Abstract
The present study investigated the distribution of elements and potentially toxic elements (PTEs) in soil profiles in the southeastern region of Nigeria, where unrefined and primitive mining practices are common. Soil samples were collected from mine and non-mine sites in Ameka and Nkalagu and analyzed for total elemental concentration using portable X-ray fluorescence (pXRF). The results showed that the Ameka mine-affected soils were heavily polluted, while the Ameka non-mine-affected soils were moderately polluted. The Nkalagu mine and non-mine-affected soils were also moderately polluted. The potential ecological risk (PER) was high in the Ameka mine-affected site due to elevated As, Cu, and Pb levels, while the Ameka non-mine-affected site had a low PER. The enrichment factor (EF) values indicated more enrichment of PTEs in the mine-affected sites compared to the non-mine-affected sites. The geoaccumulation index (Igeo) showed moderate to extreme contamination in the Ameka mine-affected site with Cu, Zn, As, and Pb. In contrast, the Nkalagu mine-affected site had considerably lower contamination. The regression model showed that site characteristics alone were insufficient to explain elements and PTEs distribution, emphasizing the importance of considering soil properties in understanding their spatial patterns. The study highlights the higher concentrations of As, Cu, and Pb in the mine-affected sites compared to the non-mine areas and recommends remediation strategies for these elements and PTEs, especially in the vicinity of mine sites. Further laboratory analysis is recommended to understand the mobility of PTEs with depth for better remediation approaches.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".