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Record W2063740254 · doi:10.1139/s05-010

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

2005· article· en· W2063740254 on OpenAlexvenueno aff
Fatima Hammy, Guy Mercier, Jean‐François Blais

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2005
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsnot available
Fundersnot available
KeywordsLeaching (pedology)Toxicity characteristic leaching procedureChemistryEnvironmental chemistryBottom ashLimePollutionMunicipal solid wasteFly ashMineralogyEnvironmental scienceMetallurgyWaste managementMaterials scienceHeavy metals

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.228
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicRecycling and utilization of industrial and municipal waste in materials productionFrench-language works237,207