Active face emissions: An opportunity for reducing methane emissions in global waste management
Bibliographic record
Abstract
This study used mobile surveys of 10 Canadian landfills to assess how methane emissions varied across different landfill sources and operational conditions. The studied landfills included 2 closed landfills, 4 open landfills equipped with Gas Collection and Control Systems (GCCS), and 4 open landfills operating without GCCS. We employed the Gaussian dispersion model to estimate emission 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 including the active face, closed cells, compost areas, leachate systems, and GCCS. At open sites, active face emissions ranged from 14.6 to 462.3 kg h−1, with standard deviations of up to ±208.1 kg h−1. Other source areas, such as closed cells (final and intermediate cover) and compost facilities, generally emitted <1 to approximately 125.4 kg h−1. Overall, we found that the active face of landfills is a major emitter of methane, contributing 76% of the total emissions for landfills with GCCS and 38% at those 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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".