Anaerobic digestion as a sustainable solution for biosolids management by the Montreal Metropolitan Community
Bibliographic record
Abstract
The Quebec Waste Management Policy (1998-2008) is requesting that the municipalities prepare a waste management plan, including a global objective of 60% of these wastes to be diverted from landfill sites by reduction, re-usage, recycling and valorization. Around 5.8 million tons of wastes were generated on the territory of the Montreal Metropolitan Community in 2001 for a population of about 3.5 millions citizens. In this paper, we present different management scenarios in which anaerobic digestion was used as a valorization step, focusing on the energetic value of the methane produced and the reduction in greenhouse gas (GHG) emissions. The four scenarios prepared cover the valorization of the organic fraction of municipal solid wastes, green wastes and excess sludge and showed potential methane generation of 17-140 Mm3 with a GHG reduction of 62,000-500,000 tons of CO2-equivalents.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".