Comparaison de divers adsorbants naturels pour la récupération du plomb lors de la décontamination de chaux usées d'incinérateur de déchets municipaux
Bibliographic record
Abstract
The objective of this research was to compare the efficiency of different natural adsorbents for lead recovery from basic leachate produced during municipal incinerator used lime decontamination. Shake flasks adsorption tests have shown that cedar barks, pine barks, cocoa shells, and peat moss are efficient and cheap adsorbents for lead removal from this type of leachate. Peanut skins are less efficient than other tested natural materials. The use of a hot-acid treatment (H 2 SO 4 0.75 M) allows to slightly increase lead removal performance of the adsorbents. However, this gain does not justify, from an economical point of view, the utilization of the chemical treatment. Tests done with different cedar and pine bark concentrations (230 g/L) have revealed that heavily lead-contaminated (approximately 130140 mg/L) used lime leachate can be efficiently treated by addition of a small adsorbent concentration (e.g. 2 g/L). Finally, elution tests (HCl 0.5 M) with reuse of adsorbents have demonstrated that some natural materials, like cedar barks and cocoa shells, can be used for many adsorptionelution cycles without loss of lead removal efficiency. Key words: lead, adsorption, used lime, leaching, peat, bark.[Journal translation]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".