Eight-Year Estimates of Methane Emissions from Oil and Gas Operations in Western Canada Are Nearly Twice Those Reported in Inventories
Bibliographic record
Abstract
Abstract The provinces of Alberta and Saskatchewan account for 70% of Canada’s methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40–45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH4/year, about 60% greater than that reported in Canada’s National Inventory Report (2.3 MtCH4). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH4) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH4) emissions are small. The resulting estimate of 3.0 MtCH4 from the oil and gas sector is nearly twice that reported in Canada’s National Inventory (1.6 MtCH4).
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".