Arctic organic aerosol measurements show particles from mixed combustion in spring haze and from frost flowers in winter
Bibliographic record
Abstract
Submicron atmospheric aerosol particles were collected between 1 March 2008 and 1 March 2009 at Barrow, Alaska, to characterize the organic mass (OM) in the Arctic aerosol. Organic functional group concentrations and trace metals were measured with FTIR on submicron particles collected on Teflon filters. The OM varied from 0.07 μg m−3 in summer to 0.43 μg m−3 in winter, and 0.35 μg m−3 in spring, showing a transition in OM composition between spring and winter. Most of the OM in spring could be attributed to anthropogenic sources, consisting primarily of alkane and carboxylic acid functional groups and correlated to elemental tracers of industrial pollution, biomass burning, and shipping emissions. PMF analysis associated OM with two factors, a Mixed Combustion factor (MCF) and an Ocean‐derived factor (ODF). Back trajectory analysis revealed that the highest fractions of the MCF were associated with air masses that had originated from northeastern Asia and the shipping lanes south of the Bering Straits. The ODF consisted of organic hydroxyl groups and correlated with organic and inorganic seawater components. The ODF accounted for more than 55% of OM in winter when the sampled air masses originated along the coastal and lake regions of the Northwest Territories of Canada. Frost flowers with organic‐salt coatings that arise by brine rejection during sea ice formation may account for this large source of carbohydrate‐like OM during the ice‐covered winter season. While the anthropogenic sources contributed more than 0.3 μg m−3 of the springtime haze OM, ocean‐derived particles provided comparable OM sources in winter.
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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 | 0.000 |
| 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".