Deposition and Source Identification of Nitrogen Heterocyclic Polycyclic Aromatic Compounds in Snow, Sediment, and Air Samples from the Athabasca Oil Sands Region
Bibliographic record
Abstract
Polycyclic aromatic compounds (PACs) can have multiple sources in the Athabasca Oil Sands Region (AOSR). The current study was designed to identify and explore the potential of nitrogen heterocyclic PACs (NPACs) as source indicators in snowpack, lake sediment and passive air samples from the AOSR during 2014-2015. Source samples including petroleum coke (petcoke), haul road dust, and unprocessed oil sands were also analyzed. Samples were analyzed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry, and liquid chromatography-high resolution Orbitrap mass spectrometry. Over 200 NPACs were identified and classified into at least 24 isomer groups, including alkylated carbazoles, benzocarbazoles, and indenoquinolines. Levels of NPACs in environmental samples decreased with distance from the main developments and with increasing depth in lake sediments but were detected within 50 km from the major developments. The composition profiles of several NPAC isomer classes, such as dimethylcarbazoles, showed that petcoke had a distinct distribution of NPACs compared to the haul road dust and unprocessed oil sands ores and was the most similar source material to near-field environmental samples. These results suggest that petcoke is a major contributing source for the identified NPACs and that these compounds have the potential to be used as source indicators for future research in the AOSR.
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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) | 0.000 | 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 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".