Contamination and Potential Ecological Risk Factors of Potentially Toxic Elements Present in the Soil of Shooting Range: Comparison with the Global Soils
Bibliographic record
Abstract
This study was carried out to determine potentially toxic element (PTE) contamination and their potential ecological risk factors in shooting range soil. For this purpose soil samples were collected from different locations (left side, right side, shooting point, middle, and stop-butt) from the shooting range of Frontier Corps Training Centre (FCTC) present in Warsak, Peshawar. The soil samples were analyzed for pH, electrical conductivity (EC) and potentially toxic elements including Cd, Cr, Ni, Pb, and Zn. The strong acids digested extracts were analyzed using atomic absorption spectrophotometry to determine the concentrations of selected PTEs. The concentration of Pb was found to be maximum at stop-butt i.e. 2049 mg/kg and exceeded the United States Environmental Protection Agency (US-EPA) critical value of 400 mg/kg, while its concentrations at left, right, shooting point and middle were 14.0 mg/kg, 18.8 mg/kg, 47.4 mg/kg, and 18.2 mg/kg, respectively and exceeded the background level of normal soils which is 10 mg/kg for Pb. This study revealed that the shooting range soil was highly contaminated with Pb, and very high contamination factor and potential ecological risk for Pb was observed at stop-butt, very high contamination factor and potential ecological risk for Cd, while moderate contamination factor for Zn was observed at all locations of the shooting range. In Pakistan, the environmental perspective of shooting range soils is overlooked and there is a need to take steps to avoid such contamination of soils with Pb and other PTEs that can enter into food chains and can also leach to contaminate the aquifer. Replacement of vegetation of shooting range with PTE tolerant species, addition of soil conditioners and uncontaminated soil would reduce the mobility of these contaminants into aerial portions of plants and protect the groundwater contamination.
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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 | 0.000 | 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".