Municipal waste incinerator fly ash: supercritical fluid extraction of metals
Bibliographic record
Abstract
Abstract The amount of residues such as fly ash from municipal waste incinerators and coal‐fired power plants is growing. Fly ash is usually contaminated with toxic heavy metals that leach out on contact with water and pollute the groundwater. Therefore, isolated and expensive disposal of the ash is required. Reuse of ash as a filler for cement or pavements only allows minimum leachability of metals and maximum leaching values of various metals from reused fly ash are prescribed by national legislation. Supercritical‐fluid extraction (SFE) offers a method to reduce the metal content so that leachability is reduced and the demands of legislation are observed. This paper presents results of metal extraction from municipal waste incinerator ash using supercritical CO2. Initial experiments with a 12 dm3 rotating extraction vessel and constant solvent flow showed extraction efficiencies of between 10% and 52%. The influences of complexing‐agent concentration and process time are studied on divalent metals such as Zn2+, Pb2+, Cu2+, Sb2+, Ni2+, and Cd2+. © 2002 Society of Chemical Industry
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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 | 0.001 | 0.001 |
| 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".