A measurement-based upstream oil and gas methane inventory for Alberta, Canada reveals higher emissions and different sources than official estimates
Bibliographic record
Abstract
Abstract Mitigation actions and regulations to meet critical 2030 methane reduction targets under the Global Methane Pledge are hampered by uncertainty in true levels of emissions and source breakdowns. Here we present a measurement-based, source-resolved, hybrid top-down/bottom-up methane inventory for conventional upstream oil and gas operations in Canada’s largest oil and gas-producing province, Alberta. The derived 2021 inventory of 1337 kt/y is approximately 1.5× the official federal inventory and matches independent top-down aerial mass-balance and satellite estimates within uncertainties. Major sources are starkly different from official estimates, with venting (e.g., uncontrolled tanks, pneumatics, unlit flares) comprising almost two-thirds of emissions implying important mitigation opportunities. Derived methane intensities, while similar to U.S. basins, are approximately 4× those in neighbouring British Columbia and further reveal order-of-magnitude differences among individual anonymized companies at directly comparable facility types. This highlights the importance of independent monitoring, reporting, and verification to ensure collective success in reducing emissions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".