Saskatchewan’s oil and gas methane: how have underestimated emissions in Canada impacted progress toward 2025 climate goals?
Bibliographic record
Abstract
Abstract Canada has set ambitious methane emission reduction targets for its oil and gas industry, and recently, the province of Saskatchewan—Canada’s second largest oil producing region—announced it has already exceeded the first of these targets. Using detailed operator-reported emissions data, published for the first time from Saskatchewan in 2022, we estimate the province’s upstream oil and gas methane inventory to independently evaluate the reported emission reductions. While the inventory suggests that Saskatchewan has surpassed its target, the inclusion of recently published site-level aerial measurement data from cold heavy oil production with sand (CHOPS) wells suggests that the methane inventory is underestimated by between 30% and 40%. This inventory update is supported by new regional aerial measurements confirming the continued underestimation of emissions at CHOPS wells. Since these emissions likely evade required reduction under current regulations, we evaluate achievable emission levels if such CHOPS emissions are accurately measured/reported. The results show Saskatchewan can achieve much deeper emission reductions under current regulations with improved emission measurement, reporting, and verification methods. We discuss the benefits and risks inherent in Saskatchewan’s regulatory approach where emission limits are primarily set at the operator-level.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".