Aerosol source identification in the spring and summertime central Arctic Ocean using high-resolution mass spectrometry during MOSAiC.
Bibliographic record
Abstract
The Arctic region is undergoing considerable changes and is warming at a rate three to four times as fast as the rest of the world. Aerosols, which can originate from natural or anthropogenic sources, both of which can be locally emitted or long-range transported, play a crucial role in the Arctic radiative balance by directly absorbing or scattering incoming solar radiation or indirectly by changing cloud properties and modulating cloud formation mechanisms. Here, we investigate the sources of anthropogenic and natural aerosols in the central Arctic Ocean, using data collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition with a high-resolution time-of-flight aerosol mass spectrometer. Using positive matrix factorization on the organic fraction of aerosols during spring and summertime (March – July), we identified six distinct chemical sources of organic aerosols (OA): a hydrocarbon-like factor, a Haze factor, two factors related to two extreme events of warm and moist air mass intrusions (WAMI) in mid-April, an Arctic oxygenated factor, and a Marine factor. We also describe the geographical origin of these factors, inferred from a potential source contribution function applied on 3-hourly back-trajectories. Together, these results suggest that OA from Eurasian anthropogenic origin (including the two extreme WAMI events in mid-April) dominate the central Arctic OA budget until at least the month of May, where episodic spikes in naturally-sourced marine OA, originating from the Fram Strait marginal ice-zone start to become important through June and July. We also highlight a hitherto unreported highly-oxygenated organic factor, whose temporal variability is closely related to that of particulate ammonium (maximum concentration in May) and whose geographical origin, in the Canadian archipelagoes, could indicate a co-emission mechanism of organic aerosols and ammonia from Arctic seabird colonies.
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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 | 0.000 | 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) | 0.000 | 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".