Aerosol deposition to the boreal forest in the vicinity of the Alberta Oil Sands
Bibliographic record
Abstract
Measurements of size-resolved aerosol concentration and fluxes were made in a forest in the Athabasca Oil Sands Region (AOSR) of Alberta, Canada, in August 2021 with the aim of investigating (a) particle size distributions from different sources, (b) size-resolved particle deposition velocities, and (c) the rate of vertical mixing in the canopy. Particle size distributions were attributed to different sources determined by wind direction. Air mixed with smokestack plumes from oil sands processing facilities had higher number concentrations with peak number at diameters near 70 nm. Aerosols from the direction of open-pit mine faces showed number concentration peaks near 150 nm and volume distribution peaks near 250 nm (with secondary peaks near 600 nm). Size-resolved deposition fluxes were calculated which show good agreement with previous measurements and a recent parameterization. There is a minimum deposition velocity of v d =0.02 cm s −1 for particles of 80 nm diameter; however, there is a large amount of variation in the measurements, and this value is not significantly different from zero in the 68 % confidence interval. Finally, gradient measurements of aerosol particles (with diameters < 1 µm) demonstrated nighttime decoupling of air within and above the forest canopy, with median lag times at night of up to 40 min and lag times between 2 and 5 min during the day. Aerosol mass fluxes (diameters < 1 µm) determined using flux–gradient methods (with different diffusion parameterizations) underestimate the flux magnitude relative to eddy covariance flux measurements when averaged over the nearly 1-month measurement period. However, there is significant uncertainty in the averages determined using the flux–gradient method.
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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 | 0.002 | 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".