Active Face Emissions: An Opportunity for Reducing Methane Emissions in Global Waste Management
Bibliographic record
Abstract
This study used mobile surveys of ten Canadian landfills to assess how methane emissions varied across different landfill sources and operational conditions. The studied landfills included two closed landfills, four open landfills equipped with Gas Collection and Control Systems (GCCS), and four open landfills operating without GCCS. We employed the Gaussian dispersion model to estimate emissions fluxes using on site and off site transect data. We observed high spatial variability of methane emissions and identified the sources that contributed significantly to overall landfill emissions, sources such as the active face, closed cells, compost areas, leachate systems, and GCCS. Overall, we found that the active face of landfills is a major emitter of methane, contributing 76% of the methane emissions for landfills with GCCS and 38% for landfills without GCCS. The results underscore the importance of improved monitoring and management strategies at landfill active faces to more effectively mitigate methane emissions from landfills.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".