Pilot-Scale Decontamination of Small-Arms Shooting Range Soil Polluted with Copper, Lead, Antimony, and Zinc by Acid and Saline Leaching
Bibliographic record
Abstract
The objective of this study was to evaluate at the pilot scale the performance of a chemical leaching process for Pb, Cu, Sb, and Zn removal from a fine fraction (<125 μm) of soil at two Canadian small-arms shooting ranges (SASR; Batoche: 418 mg Cu/kg, 5,006 mg Pb/kg, 168 mg Sb/kg, and 96 mg Zn/kg; Normandie: 1,015 mg Cu/kg, 6,024 mg Pb/kg, 305 mg Sb/kg, and 177 mg Zn/kg). A comparison of different leaching reagents revealed that the use of H2SO4 (0.125M)+NaCl (4 M) is a very promising option from an economic point of view to solubilize metallic pollutants from highly polluted soils. The results showed that chemical treatment, including three successive acid-leaching steps (0.125MH2SO4+4MNaCl, PD=10%, t=1h, T=20°C) followed by one rinsing step using water [pulp density (PD)=10%, time (t)=15 min, temperature (T)=20°C], resulted in metal removal yields of 93% Cu, 97% Pb, 89% Sb, and 70% Zn in Batoche soil and 85% Cu, 96% Pb, 59% Sb, and 49% Zn in Normandie soil. Subsequently, Sb and other dissolved metals (Cu, Pb, and Zn) were successfully recovered via chemical precipitation/coprecipitation (99.1% Cu, >99.9% Pb, 95.1% Sb, and 99.9% Zn—Batoche; 90.4% Cu, >99.7% Pb, 79.1% Sb, and >99.9%Zn—Normandie) by adding NaOH until pH=9.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".