Procédé optimisé de décontamination des cendres volantes d'incinérateur de déchets municipaux : enlèvement et récupération des métaux (Cd, Pb, Al, Zn) avec recirculation des lixiviats traités
Bibliographic record
Abstract
Fly ashes produced by the incineration of municipal solid wastes are usually considered as hazardous wastes. The objective of the present study was to demonstrate the feasibility of a closed circuit decontamination process. The latter includes the reuse of treated process effluents and leads to the production of treated ashes that respect the toxicity characteristic leaching procedure (TCLP). The process should also reduce the production of metallic hazardous wastes and the operating costs. The results show that the process removes 70 ± 3% Cd and 18 ± 4% Pb from fly ashes during the chemical leaching (alkaline and acid) steps. The optimized process generates two types of metallic wastes. The first, representing 13 kg/tct (tons of treated ashes), is a nonhazardous waste produced during the nucleationprecipitation step at pH = 5. The second is classified as hazardous waste and is produced subsequently by precipitation at pH = 7. The production of this metallic hazardous waste is estimated at 29 kg/tct. The treated fly ashes respect the three leaching tests performed in this study, including the TCLP. Significant decreases in the water consumption (91%) and of chemicals used (12%) have been realized, in comparison with a reference decontamination process. These improvements result in a 36% decrease of the operating costs. Key words: fly ash, air pollution control residues (APCR), decontamination, metals, leaching, nucleation, precipitation, toxicity characteristic leaching procedure (TCLP), synthetic precipitation leaching procedure (SPLP).
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".