Size distribution and coating thickness of black carbon from the Canadian oil sands operations
Bibliographic record
Abstract
Black carbon (BC) plays an important role in the Earth's climate system. However, parameterizations of BC size and mixing state have not been well addressed in aerosol–climate models, introducing substantial uncertainties into the estimation of radiative forcing by BC. In this study, we focused on BC emissions from the oil sands (OS) surface mining activities in northern Alberta, based on an aircraft campaign conducted over the Athabasca OS region in 2013. A total of 14 flights were made over the OS source area, in which the aircraft was typically flown in a four- or five-sided polygon pattern along flight tracks encircling an OS facility. Another 3 flights were performed downwind of the OS source area, each of which involved at least three intercepting locations where the well-mixed OS plume was measured along flight tracks perpendicular to the wind direction. Comparable size distributions were observed for refractory black carbon (rBC) over and downwind of the OS facilities, with rBC mass median diameters (MMDs) between ∼ 135 and 145 nm that were characteristic of fresh urban emissions. This MMD range corresponded to rBC number median diameters (NMDs) of ∼ 60–70 nm, approximately 100 % higher than the NMD settings in some aerosol–climate models. The typical in- and out-of-plume segments of a flight, which had different rBC concentrations and photochemical ages, showed consistent rBC size distributions in terms of MMD, NMD and the corresponding distribution widths. Moreover, rBC size distributions remained unchanged at different downwind distances from the source area, suggesting that atmospheric aging would not necessarily change rBC size distribution. However, aging indeed influenced rBC mixing state. Coating thickness for rBC cores in the diameter range of 130–160 nm was nearly doubled (from ∼ 20 to 40 nm) within 3 h when the OS plume was transported over a distance of 90 km from the source area.
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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 | 0.001 | 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".