An airborne assessment of atmospheric particulate emissions from the processing of Athabasca oil sands
Bibliographic record
Abstract
Abstract. During the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign, two NASA research aircraft, a DC-8 and a P-3B, were outfitted with extensive trace gas (the DC-8) and aerosol (both aircraft) instrumentation. Each aircraft spent about a half hour sampling air around the oil sands mining and upgrading facilities near Ft. McMurray, Alberta, Canada. The DC-8 circled the area, while the P-3B flew directly over the upgrading plants, sampling close to the exhaust stacks, then headed downwind to monitor the aerosol as it aged. At short range, the plume from the oil sands is a complex mosaic of freshly nucleated ultrafine particles from a SO2 and NO2-rich plume, fly ash and soot from industrial processes, and dust from dirt roads and mining operations. Shortly downwind, organic aerosol appears in quantities that rival SO4=, either as volatile organic vapors condense or as they react with the H2SO4. The DC-8 pattern allowed us to integrate total flux from the oil sands facilities within about a factor of two uncertainty that spanned values consistent with 2008 estimates from reported SO2 and NO2 emissions. In contrast, CO fluxes exceeded reported regional emissions, due either to variability in production or sources missing from the emissions inventory. The conversion rate of SO2 to aerosol SO4= of ~6% per hour is consistent with earlier reports, though OH concentrations are insufficient to accomplish this. Other oxidation pathways must be active. Altogether, organic aerosol and black carbon emissions from the oil sands operations are small compared with the forest fires present in the region during the summer. The oil sands do contribute significant sulfate and exceed fire production of SO2 by an order of magnitude.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".