Ambient concentrations and total deposition of inorganic sulfur, inorganic nitrogen and base cations in the Athabasca Oil Sands Region
Bibliographic record
Abstract
Trace gas, particulate matter and deposition data collected in the Athabasca Oil Sands Region (AOSR) from 2000 to 2017 were evaluated as part of a broad scientific programmatic review. Results showed significant spatial patterns and temporal trends across the region. Concentrations of reactive gases were highest near the center of surface oil sands production operations and decreased towards the edges of the monitoring domain by factors of 8, 20, 4 and 3 for SO 2 , NO 2 , HNO 3 and NH 3 , respectively. 18 of 30 sites showed statistically significant ( p < 0.05) negative trends in SO 2 concentrations suggesting an ~40% decrease since 2000. In contrast, only 2 of 30 sites showed statistically significant temporal trends (1 positive, 1 negative) for NO 2 . NH 3 data showed (i) intermittent wildfire impacts, and (ii) high seasonality, with low concentrations during winter and significantly higher values during the summer. PM 10 measurements were more limited, but also showed significant spatio-temporal variability. Comparison of PM 10 and PM 2.5 data showed that >80% of SO 4 2− was in the PM 2.5 fraction, while > 60% of Ca 2+ , Mg 2+ , Na + and Cl − were in the PM 10-2.5 fraction. Ion balances of both PM 10 and PM 2.5 contained cation excesses at near-field oil sand sites, but PM 2.5 samples at forest health sites >20 km from surface production locations contained anion excesses. Monthly average concentrations of PM 10 ions showed peak Ca 2+ during March-April to November, but peak SO 4 2− , NH 4 + and NO 3 − from November-March. Deposition estimates showed rapid declines as a function of distance to oil sand operations. Estimated total N and total S deposition to forest health monitoring sites ranged from 2.0 to 5.7 kg ha −1 a −1 and 2.1–14.0 kg ha −1 a −1 , respectively. Potential acid input (PAI) ranged from −0.46 to 0.79 keq ha −1 a −1 and was mostly 0.1–0.2 keq ha −1 a −1 throughout the domain, except for two clusters of sites near oil sand operations.
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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 | 0.000 | 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) | 0.001 | 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".