Quantification of Methane Sources in the Athabasca Oil Sands Region of Alberta by Aircraft Mass-Balance
Bibliographic record
Abstract
Abstract. Aircraft-based measurements of methane (CH4) and other air pollutants in the Athabasca Oil Sands Region (AOSR) were made during a summer intensive field campaign between August 13 and September 7 2013, in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring. Chemical signatures were used to identify CH4 sources from tailings ponds (BTEX VOC's), open-pit surface mines (NOy and rBC) and elevated plumes from bitumen upgrading facilities (SO2 and NOy). Emission rates of CH4 were determined for the five primary surface mining facilities in the region using two mass balance methods. Emission rates from source categories within each facility were estimated when plumes from the sources were spatially separable. Tailings ponds accounted for 45 % of total CH4 emissions measured from the major surface mining facilities in the region while emissions from operations in the open pit mines accounted for ~ 50 %. The average open pit surface mining emission rates ranged from 1.2 to 2.8 tonnes of CH4 hr−1 for different facilities in the AOSR. Amongst the 19 tailings ponds, Mildred Lake Settling Basin, the oldest pond in the region, was found to be responsible for the majority of tailings ponds emissions of CH4 (> 70 %). The sum of measured emission rates of CH4 from the five major facilities, 19.2 ± 1.1 tonnes CH4 hr−1, was similar to a single mass balance determination of CH4 from all major sources in the AOSR determined from a single flight downwind of the facilities, 23.7 ± 3.7 tonnes CH4 hr−1. The measured hourly CH4 emission rate from all facilities in the AOSR is 48 ± 8 % higher than that extracted for 2013 from the Canadian Green House Gas Reporting Program, a legislated facility-reported Emissions Inventory, converted to hourly units. The measured emissions correspond to an emissions rate of 0.17 ± 0.01 Tg CH4 yr−1, if the emissions are assumed temporally constant, an uncertain assumption. The emission rates reported here are relevant for the summer season. In future, effort should be devoted to measurements in different seasons to further our understanding of seasonal parameters impacting fugitive emissions of CH4 and to allow better estimates of annual emissions and year to year variability.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".