Study of the Metal Precipitation from Decontamination Leachates of Municipal Wastes Fly Ash Incinerators
Bibliographic record
Abstract
This research work focuses on the development of a new process for the decontamination of municipal wastes incinerators fly ashes. The objective of this study was to evaluate different total and selective precipitation methods for metals removal from ash decontamination leachates. The tested options include 1) use of hydrated lime and caustic soda for selective (pH 5.0) and total (pH 8.5) metal precipitation; 2) addition of different chemicals (H3PO4, Na2S and FeCl3) in a pH range from 6.0 to 9.0. Fly ash decontamination assays using alkaline and acid washing steps were initially performed using optimal conditions previously established. Treated fly ashes respected the standards based on the TCLP leaching test for all studied metals and SPLP. Total metal precipitation tests carried out at pH 8.5 achieve removal yields for all metals > or = 90% using hydrated lime and > or = 83% using caustic soda. Selective precipitation tests alone at pH 5.0 show removal yields > or = 97% for Cr and between 75 and 87% for Al and Pb. Moreover, assays carried out using a stoechiometric addition of Na2S have allowed the separation of Cd (> or = 99%) and Zn (> or = 71%) as metal sulphides (CdS and ZnS). From an economical point of view, the most interesting option seems to be the leachates neutralization at pH 7.0 using Ca(OH)2 combined with the reuse of the treated leachates in the fly ash leaching steps. Metal precipitation cost at pH 7.0 has been estimated to be 22.7 CAN dollars tct-1 using Ca(OH)2, and 26.7 CAN dollars tct-1 using NaOH.
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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 | 0.000 | 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) | 0.000 | 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".