Atmospheric deposition of chromophoric dissolved organic matter in the Athabasca Oil Sands Region, Canada, is strongly influenced by industrial sources during the winter months
Bibliographic record
Abstract
There is growing interest in the atmospheric deposition of chromophoric dissolved organic matter (CDOM) owing to its impact on aquatic processes and surface albedo. Industrial operations in the Athabasca Oil Sands Region (AOSR), Canada, are a major source of emissions of organic gases and particulate matter, which likely contribute to regional CDOM deposition. Here we investigated the composition and spatiotemporal variation of CDOM within regional snowpack (45 sites, collected March of 2023) and weekly precipitation samples (three monitoring stations between January 2021-December 2021) using ultraviolet-visible and fluorescence spectroscopy. Spectroscopic analysis identified three distinct fluorescent compounds (fluorophores) in both snowpack and precipitation. Elevated absorbance and fluorescence intensity among near-field samples demonstrated that industrial emissions influenced CDOM deposition in the AOSR. Fluorescent compounds linked to wildfire emissions (indicated by positive associations with pyrogenic indicators) were the dominant source of fluorescence during the summer while an industrial-sourced fluorophore (indicated by high near-field emission intensity and positive associations with continuous air quality monitoring data) was most prominent (absolute and relative emission intensity) during the cold season, possibly due to enhanced atmospheric stability and lower photolysis rates favouring fluorophore formation. Our results suggested that elevated wintertime CDOM deposition associated with oil sands operations will potentially alter snowpack albedo throughout the region.
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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".