Estimation of natural methane emissions from the largest oil sand deposits on earth
Bibliographic record
Abstract
Abstract Worldwide methane emission by various industrial sources is one of the important human concerns due to its serious climate and air-quality implications. This study investigates less-considered diffusive natural methane emissions from the world's largest oil sand deposits. An analytical model, considering the first-order methane degradation, in combination with Monte Carlo simulations, is used to quantitatively characterize diffusive methane emissions from Alberta's oil sands formations. The results show that the average diffusive methane emissions from Alberta's oil sands formations is 1.56 × 10−4 kg/m2/year at the 90th percentile of cumulative probability. The results also indicate an annual diffusive methane emissions rate of 0.857 ± 0.013 Million tons of CO2e/year (MtCO2e/year) from Alberta's oil sands formations. This finding suggests that natural diffusive leakages from the oil sands contribute an additional 1.659 ± 0.025 and 5.194 ± 0.079% to recent Canada's 2019 and Alberta's 2020 methane emission estimates from the upstream oil and gas sector, respectively. The developed model combined with Monte Carlo simulations can be used as a tool for assessing methane emissions and current inventories.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".