Chemical composition and source attribution of submicron aerosol particles in the summertime Arctic lower troposphere
Bibliographic record
Abstract
Abstract. We use airborne measurements of aerosol particle composition to demonstrate the strong contrast between particle sources and composition within and above the summertime Arctic boundary layer. In-situ measurements from two complementary aerosol mass spectrometers, the ALABAMA and the HR-ToF-AMS, with black carbon measurements from an SP2 are presented. Particle composition analysis was complemented by trace gas measurements, satellite data, and air mass history modeling to attribute particle properties to particle origin and air mass source regions. Particle composition above the summertime Arctic boundary layer was dominated by chemically aged particles, containing elemental carbon, nitrate, ammonium, sulfate, and organic matter. From our analysis, we conclude that the presence of these particles was driven by transport of aerosol and precursor gases from mid-latitudes to Arctic regions. Particularly, elevated concentrations of nitrate, ammonium, and organic matter coincided with time spent over vegetation fires in northern Canada. In parallel, those particles were largely present in high CO environments (> 90 ppbv). Additionally, we observed that the organic-to-sulfate ratio was enhanced with increasing influence from these fires. Besides vegetation fires, particle sources in mid-latitudes further include anthropogenic emissions in Europe, North America, and East Asia. The presence of particles in the Arctic lower free troposphere correlated with time spent over populated and industrial areas in these regions. Further, the size distribution of free tropospheric particles containing elemental carbon and nitrate was shifter to larger diameters compared to particles present within the boundary layer. Moreover, our analysis suggests that organic matter when present in the Arctic free troposphere can partly be identified as low-molecular weight dicarboxylic acids (oxalic, malonic, and succinic acid). Particles containing dicarboxylic acids were largely present when the residence time of air masses outside Arctic regions was high. In contrast, particle composition within the marine boundary layer was largely driven by Arctic regional processes. Air mass history modeling demonstrated that alongside primary sea spray particles, marine-biogenic sources contributed to secondary aerosol formation by trimethylamine, methanesulfonic acid, sulfate, and other organic species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".