A First Assessment of the Elemental Composition of Atmospheric Aerosols in the Canadian Oil Sands Region
Bibliographic record
Abstract
Canadian Oil Sands, which comprise 97% of Canada’s 176 billion barrels of proven oil reserves, are located beneath 140,200 km2 of boreal forests, prairies and wetlands, and are the second largest known deposit of crude oil in the world. As such, this region has experienced rapid industrial development, which resulted also in increasing industrial air emissions, primarily from bitumen upgrading and mine vehicle fleet operations. This rapid development has led to concerns regarding health risk to humans, and other terrestrial and aquatic wildlife associated with exposure to toxic contaminants, especially metals and polycyclic aromatic compounds (PACs) particularly along the Athabasca River and its watershed. Canada’s Minister of the Environment announced that Environment Canada (EC) will jointly lead, in collaboration with Government of Alberta and relevant stakeholders, the development and implementation of an enhanced monitoring system in the Oil Sands region to provide information on the state of the air, water, land andbiodiversity. This work presents preliminary data on the first assessment of elemental composition of fine particulate matter (particles<2.5 mm in diameter; PM2.5) at 3 air quality sites in close proximity to Oil Sands processing activities. Since December 2010, integrated 24 hour air samples were collected every sixth day on a 47-mm Teflon filters using Thermo Fisher Partisol 2000-FRM samplers operated by the National Air Pollution Surveillance (NAPS) network that involves EC and the Canadian provinces and territories. All samples including laboratory, travel and field blanks were subjected to gravimetric determination of PM2.5 mass and energy dispersive X-ray fluorescence (ED-XRF) analysis for 46 elements. Since ED-XRF is a non-destructive technique, PM2.5 samples were subsequently analyzed for 37 trace elements including rare earth elements using inductively-coupled plasma mass spectrometry (ICP-MS) combined with microwave-assisted acid digestion. The resulting data will be discussed.
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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) | 0.000 | 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 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".