Caractérisation et traitement des résidus de contrôle de la pollution de l'air (RCPA) d'incinérateurs de déchets municipaux par un procédé de lixiviation en milieu basique
Bibliographic record
Abstract
A detailed characterization of the different types of air pollution control residues (APCR) produced in municipal waste incinerators has been performed. The analysis of the Pb distribution in boiler and electrofilter ashes has shown that the separation of these ashes in two fractions (<125 µm and >125 µm) allows to get a coarse fraction slightly contaminated and a finer fraction more heavily contaminated, which can be treated by chemical means. Scanning electron microscope energy-dispersive spectrometry (SEM-EDS) techniques have been used to identify the most dominant forms of the lead particles. Lead present in used lime is principally associated with oxides in a carrying phase of calcium chloride or phosphate. Lead present in boiler and electrofilter ashes is principally associated with silicates and phosphates. Finally, only one leaching step in alkaline aqueous solution is required to remove a large proportion of the leachable lead in APCR and to reach the allowed level by the toxicity characteristic leaching procedure test (TCLP) and neutral water test. Key words: lead, leaching, incinerator, air pollution control residues (APCR), ash, removal, heavy metal, toxicity characteristic leaching procedure test (TCLP).
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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 | 0.001 | 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".