Size distributions of dicarboxylic acids and inorganic ions in atmospheric aerosols collected during polar sunrise in the Canadian high Arctic
Bibliographic record
Abstract
Size‐segregated atmospheric aerosols (11 stages separating particles from <0.04 to >14.2 μ m) collected in the Arctic during the polar sunrise at Alert were analyzed for aerosol mass, dicarboxylic acids, and major inorganic ions. Oxalic, malonic, succinic, and glutaric acids were detected in all size ranges, with oxalic acid being dominant. Their concentrations maximized in the accumulation mode either at 0.24–0.40 or 0.40–0.8 μ m aerodynamic diameters, suggesting that diacids were mainly formed by gas‐to‐particle conversion via photochemical oxidation of nonmethane hydrocarbons and oxygenated organics originated from continental pollution sources. The relative abundances of oxalic acid were higher in the 0.24‐ to 0.4‐ μ m size particles (73–78%) than in supermicrometer particles (40–60%), indicating that oxalic acid is produced by gas phase oxidation of precursors followed by accumulation on preexisting particles. Mass size distributions of NH 4 + and SO 4 2− peaked in the accumulation mode similar to those of small diacids. The sea‐salt enrichment factor of K + (biomass burning tracer) relative to Na + maximized in 0.1‐ to 0.8‐ μ m sizes, whereas those of Mg 2+ and Ca 2+ (dust tracers) in 0.4‐ to 7.8‐ μ m particles. Maximized chlorine loss and bromine enrichment were found at 0.4–0.8 and 0.24–0.4 μ m sizes, respectively. Concentrations of Br − , which typically showed a submicrometer maximum, increased significantly during an O 3 depletion event having a shift of size distribution to a supermicrometer mode. During this event, oxalic acid concentration relative to succinic acid increased in submicrometer mode (0.24–0.4 μ m), adding to a growing body of evidence supporting the hypothesis that halogen chemistry is important in the production and loss of oxalic acid in the arctic atmosphere.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".