Different options for metal recovery after sludge decontamination at the Montreal Urban Community wastewater treatment plant
Bibliographic record
Abstract
The MUG (Montreal Urban Community) treatment plant produces approximately 270 tons of dry sludge daily (270 tds/day) during the physico-chemical treatment of wastewater. Recently, this treatment plant endowed a system of drying and granulation of sludge for valorization as an agricultural fertilizer having a capacity of 70 tds/day (25% of the daily sludge production). However, the metal content (mainly Cu and Cd) of the sludge surpasses the norms for biosolids valorization. In order to solve this problem, a demonstration project, from the lab scale to the industrial pilot plant, was carried out to test the Metix-AC technology for the removal of metals. A strongly metal-loaded filtrate was generated during the sludge decontamination. Tests concerned the study of the metal recovery by total precipitation and selective precipitation, as well as the use of alternative products for the metal precipitation. Other works consisted to simulate the acid filtrate recirculation from the decontaminated sludge (25% of the total volume) in the untreated sludge (75% of the total volume) intended for the incineration. The total precipitation with hydrated limeappearedeffectivefortherecoveryof metals (87% Cd, 96% Cr, 97% Cu, 98% Fe, 71% Ni, 100% Pb, 98% Zn). However, this option entails the production of an important quantity of metallic residue, which should be disposed of expensively as dangerous material. The selective iron precipitation does not appear to bean interesting option because the iron in solution within the leached sludge was principally present in the form of ferrous iron, which cannot be precipitated at pH lower than five. On the other hand, the use of commercial precipitating agents (TMT-15, CP-33Z, CP-NB and CPX) without pH adjustment of filtrate gave good results for the recovery of Cu and, to a lesser degree for the recovery of Pb. However, the efficiency for the other metals' (Cd, Cr, Fe, Ni and Zn) recovery was weaker (< 25%). Finally, the acid filtrate recirculation containing solubilised metals in untreated sludge destined for incineration appears to be the most interesting option. Metals in solution in the acid filtrate, precipitate or adsorb effectively (97% Cd, 97% Cr, 99% Cu, 82% Ni, 100% Pb and 87% Zn) on the solids of the untreated sludge. Moreover, TCLP tests were done on ashes produced during the incineration of sludge mixed with the acid filtrate produced during sludge decontamination. These tests showed that there were no significant differences, as regards the extractability of metals, between such ashes and those produced during the untreated sludge incineration without addition of filtrate. Therefore, it was predictable that this method can respect the current environmental standards required by the different governmental authorities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".