Laboratory-Scale Flotation Process for Treatment of Soils Contaminated with Both PAH and Lead
Bibliographic record
Abstract
A soil decontaminating process has been studied at laboratory scale for the treatment of one soil polluted by both polycyclic aromatic hydrocarbons (PAHs) and lead (Pb). This process first includes attrition and sieving steps to separate the coarse (>2 mm) from the fine (<2 mm) fractions, followed by a flotation step using an amphoteric surfactant in acid and saline conditions for the treatment of the fine contaminated particles. Electrodeposition and chemical precipitation using sodium hydroxide have been compared to ensure a possible reuse of wastewaters without disturbing the efficiency of the process. The performance of the process has been estimated considering soil quality after treatment with respect to the limit regulatory levels for commercial or industrial use in Quebec (Canada). Precipitation of lead hydroxides was efficient after five cycles of wastewaters reuse, while electrodeposition did not maintain efficiency of the flotation step with regard to PAH levels in soil after treatment. The complete process including Pb precipitation ensured the removal of 89±8 and 76±10% of total PAH, respectively, for the coarse (>2 mm) and fine (<2 mm) fractions, while Pb was removed at 88±10 and 65±2% , respectively, for the same fractions of the soil.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".