TRAITEMENT DE DECHETS D’ALUMINERIE CONTAMINES EN HAP PAR FLOTTATION EN PRESENCE DE SURFACTANTS AMPHOTERES
Bibliographic record
Abstract
Résumé L’industrie de production de l’aluminium génère des déchets d’aluminerie contaminés en hydrocarbures aromatiques polycycliques (HAP). Le principal contaminant en HAP est le benzo(b,j,k)fluoranthène (BJK) avec des concentrations souvent supérieures aux normes imposées (> 1000 mg kg−1). Cette étude visait à comparer les performances de surfactants amphotères (BW et CAS) et non ioniques (Triton X‐100 et Tween 80) à une concentration de 0.5% (p p−1) pour l’enlèvement des HAP (et en particulier le BJK) lors du traitement par lavage des déchets d’aluminerie. Le meilleur rendement d’enlèvement du BJK (35%) a été obtenu pour les essais de lavage effectués en présence de CAS. Ce rendement a été amélioré en remplaçant le traitement par lavage par un procédé de flottation. Les essais de flottation à différentes concentrations en CAS (0.1, 0.2, 0.25 et 0.5% p p−1) et à différentes concentrations en solides totaux de la pulpe (7, 10, 15 et 20% p v−1) ont démontré que les conditions optimales pour l’enlèvement du BJK consistaient en une concentration de CAS de 0.5% et une concentration en solides totaux de 15%. Le rendement d’enlèvement du BJK obtenu dans ces conditions s’élève à 68%. La production de déchets dangereux obtenue dans ces conditions représente 10% de la masse initiale des déchets d’aluminerie. Mots clés: Déchets d’aluminerie, HAP, CAS, surfactant, flottation ABSTRACT The aluminium industry produces wastes polluted with polycyclic aromatic hydrocarbons (PAH). The most important PAH found in these wastes is benzo(b,j,k)fluoranthene (BJK) at concentrations exceeding the permitted levels (>1000 mg kg−1). The objective of this research was to compare the performances of amphoteric (BW and CAS) and non‐ionic surfactants (Triton X‐100 and Tween 80), at a concentration of 0.5% (w w−1), for PAH removal (and particularly for BJK) during washing treatment of aluminium industry wastes. The best removal yield of BJK (35%) has been measured during treatment with CAS. The efficiency of this surfactant has been further improved by using a flotation process. Flotation tests have also been realized at different CAS concentrations (0.1, 0.2, 0.25 and 0.5% w w−1) and using different total solids (7, 10, 15 and 20% w v−1). The highest BJK removal yield (68%) has been obtained using 0.5% CAS and a total solids concentration of 15%. The rate of hazardous wastes produced in these conditions represents 10% of the initial weight of aluminium wastes treated.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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; both teacher heads agree on what is shown here.
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".