Décontamination des résidus de contrôle de la pollution de l'air (RCPA) d'incinérateurs de déchets municipaux par lixiviation en milieu basique et adsorption sur tourbe
Bibliographic record
Abstract
Air pollution control residues (APCR) from municipal waste incinerators are usually considered as hazardous wastes because of their high contents in easily soluble Pb and other toxic metal contaminants. The objective of this research was to compare various techniques using Pb adsorption on Sphagnum peat moss (MT) for the treatment of alkaline leachates produced during the decontamination of various types of APCR including used lime (CU), electrofilter ashes (CE), and boiler ashes (CC). Regeneration tests of saturated MT using hydrochloric and sulphuric acids have revealed that excessive acid consumption (>250 kg acid/metric ton of treated APCR) are necessary for the elution of metals. However, the incineration of the saturated MT and its possible valorization represents an interesting way to explore for the management of the adsorbent. This method allows to reduce by a factor of 3 or 4 the mass of residues and increases in the same proportion the Pb content in the incinerated MT. Finally, the present study has highlighted that ion exchange on the anionic functional groups of MT would be one of the most important mechanisms implied in the Pb fixation on this natural sorbent during the treatment of very alkaline leachates (pH > 11) of APCR.Key words: lead, leaching, incinerator, air pollution control residues (APCR), removal, peat, adsorption, toxicity characteristic leaching procedure (TCLP).[Journal translation]
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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) | 0.000 | 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) | 0.001 | 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".