Canada's Landfill Methane Inventories: The Challenge of Accurate Modeled and Measurement-Based Emissions
Bibliographic record
Abstract
We present a measurement-based assessment of methane emissions from 42 landfills across diverse climatic regions in Canada. Our findings reveal that emission rates predicted by the First-Order Decay (FOD) model used by Environment and Climate Change Canada at the visited sites are substantially higher than most measured emission rates, on average by a factor of 3, particularly for cold and arid climates typical of the Canadian prairie provinces (by a factor of 13 on average). Bias-corrected measurement rates aligned more closely with values reported to the Canadian Greenhouse Gas Reporting Program. Compared with the amounts estimated by the FOD model, our measurement-based estimates show greater variation with climate change. At some warmer, wetter sites, measured rates exceeded FOD-modeled estimates, underscoring the influence of climate on landfill methane dynamics and on FOD model behavior. We also found that measurement-based estimates yield more realistic methane collection effectiveness values than those implied by Canada’s FOD-based inventories. Our results suggest that the current FOD inventory model parameters—that include decay rates and oxidation assumptions—should be refined to better reflect site-specific conditions and climate variability across Canada.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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 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".