Particulate matter emissions over the oil sands regions in Alberta, Canada
Bibliographic record
Abstract
Particulate matter (PM) emissions from the expanded oil sands development in Alberta are becoming a focus among the aerosol science community because of its significant negative impact on the regional air quality and climate change. Open-pit mining, petroleum coke (petcoke) dust, and the transportation of oil sands and waste materials by heavy-duty trucks on unpaved roads could release PM into the air. Incomplete combustion of fossil fuels by engines and stationary boilers leads to the formation of carbonaceous aerosols. In addition, wildfire and biogenic emissions surrounding the oil sands regions also have the potential to contribute primary PM to the ambient air. Secondary organic aerosol formation has been revealed as an important source of PM over nearby and distant areas from the oil sands regions. This review summarizes the primary PM sources and some secondary aerosol formation mechanisms that are linked to oil sands development. It also reviews the approaches that can be applied in aerosol source apportionment. Meteorological condition is an important factor that may influence the primary PM emission and secondary aerosol formation in Alberta’s oil sands regions. Current concern should not be limited to the primary emission of atmospheric PM. Secondary formation of aerosols, especially secondary organic aerosol originating from photochemical reaction, should also be taken into consideration. To obtain a more comprehensive understanding of the sources and amount of PM emissions based on the bottom-up emission inventory approach, investigations on how to reduce the uncertainty in determination of real-world PM emission factors for the variable sources are needed. Long-range transport trajectories of fine PM from Alberta’s oil sands regions remain unknown.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.008 | 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 teacher head, 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".