Improvement of a three-step process for the treatment of aluminium hazardous wastes containing PAHs (benzo[b,j,k]fluoranthene and chrysene) and fluoride
Bibliographic record
Abstract
Hazardous wastes from a primary aluminium production plant could be decontaminated by a three-step process. First, the PAHs contained in these wastes were extracted with an amphoteric surfactant (0.25% or 0.50% w/w of cocamidopropylhydroxysultaine [CAS]) by cell or column flotation, depending on the particle size fraction (under or above 500 microm). Then, the fluorides were stabilized with lime (8% w/w) or a mixture of lime (4% w/w) and phosphoric acid (0.95% w/w). The decontaminated wastes satisfied the Quebec PAH norm, fixed at 1000 mg kg(-1), with values of 900 +/- 352 mg kg(-1) and 624 +/- 179 mg kg(-1) for benzo(b,j,k)fluoranthene (BJK) at laboratory and pilot scales, respectively. The fluoride stabilization in the treated wastes was characterized by TCLP values of 138 +/- 67 mg F- L(-1) and 29.5 +/- 7.6 mg F- L(-1) for laboratory and pilot experiments, which were under the Quebec norm (< 150 mg F- L(-1)). Finally, the metals in the process effluent were recovered by precipitation with sulphuric acid (10% v/v), and the final effluent and metallic residue obtained were recirculated without liquid fraction enrichment impact. The whole process was successfully tested at pilot scale. The preliminary economic study showed the potential of the process for the treatment of aluminium hazardous wastes.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".