Stable sulfur isotope measurements to trace the fate of SO <sub>2</sub> in the Athabasca oil sands region
Bibliographic record
Abstract
Abstract. The concentration and sulfur isotopic composition of SO2 and size-segregated sulfate aerosols were determined for Air Monitoring Station 13 (AMS13) at Fort MacKay in the Athabasca oil sands region, northeastern Alberta, Canada as part of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring (JOSM) campaign from Aug 13 to Sep 5, 2013. Sulfate aerosols were collected on filters by a high volume sampler, with 12 or 24 hour time intervals. Significant positive correlations between SO2 to sulfate conversion ratio (F(s)) and the concentration of α-pinene (r = 0.85), β-pinene (r = 0.87), and limonene (r = 0.82) during daytime and with other alkenes and aromatics (tetrachloroethene (r = 0.69), 1-methyl-4benzene (r = 0.71) and Ethenylbenzene (r = 0.66)) indicate that SO2 oxidation by Criegee intermediates can be a potential oxidation pathway in highly polluted regions. Enriched 34S sulfur, largely as SO2, was emitted by a nearby Chemical Ionization Mass Spectrometer (CIMS) and affected isotope samples for a portion of the sampling period. When it was realized this could be a useful tracer, samples collected were broken into two sets. The first set includes periods when the CIMS was not running (CIMS-OFF) and no enriched 34S sulfur was emitted. The second set is for periods when the CIMS was running when sampling (CIMS-ON) and 34S sulfur values expected to affect SO2 and sulfate samples. δ34S values for sulfate aerosols with D > 0.49 μm during CIMS-OFF periods (no tracer 34SO2 present) indicating the sulfur isotope characteristics of sulfate in the region, were isotopically lighter (down to −4.5 ‰) than what was expected according to potential sulfur sources in the Athabasca oil sands region (+3.9 ‰ to +11.5 ‰). For sulfate aerosols with D
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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 | 0.000 | 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".