Applied Methodological Approach for the Assessment of Soil Contamination by Trace Elements around Abandoned Coal Mines—A Case Study of the Jerada Coal Mine, Morocco
Bibliographic record
Abstract
Previously conducted studies have established that soil contamination by trace elements (TEs) around coal mines affects ecological biodiversity and human health. One of the ways to protect the health of the surrounding population of coal mine sites is through the assessment of contamination impacts by accurate procedures for the establishment of relevant reclamation plan. The aim of the study is to develop an applied methodological approach to easily assess and quantify the impact of coal mining on the surrounding soils. To achieve this goal, a set of relevant geochemical indexes (enrichment factor—EF, geochemical background—GB, and geoaccumulation index—Igeo) and a geostatistical interpolation for mapping soil contamination were applied. It is experimentally established that the process of combining these techniques can be of great interest in highlighting the anomalous areas and revealing the contamination sources. A case study has been carried out on of the abandoned coal Jerada mine site in Morocco. Soils and coal mine waste rocks (CMWR) samples were collected from this site. Soil and CMWR samples were analyzed for their geochemical content. CMWRs were characterized further for their mineralogical composition and environmental behavior. Based on the EF, three TEs (As, Pb, and Zn) were targeted. The results of GB and Igeo calculations have established an evident relationship between the CMWR dump and the occurred soil contamination. TEs distribution pattern has been revealed using the obtained geochemical maps. The developed methodological approach may be in high demand when assessing soil contamination in most of abandoned coal mine sites around the word.
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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 | 0.001 | 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".