Secondary formation of water‐soluble organic acids and <i>α</i>‐dicarbonyls and their contributions to total carbon and water‐soluble organic carbon: Photochemical aging of organic aerosols in the Arctic spring
Bibliographic record
Abstract
Water‐soluble dicarboxylic acids (C2‐C12), ketocarboxylic acids (C2‐C6, C9), and α‐dicarbonyls (glyoxal and methylglyoxal) were determined in the Arctic aerosols collected in winter to early summer, as well as aerosol total carbon (TC) and water‐soluble organic carbon (WSOC). Concentrations of TC and WSOC gradually decreased from late February to early June with a peak in spring, indicating a photochemical formation of water‐soluble organic aerosols at a polar sunrise. We found that total (C2‐C11) diacids (7–84 ng m−3) increased at polar sunrise by a factor of 4 and then decreased toward summer. Their contributions to TC (average 4.0%) peaked in early April and mid‐May. The contribution of total diacids to WSOC was on average 7.1%. It gradually increased from February (5%) to a maximum in April (12.7%) with a second peak in mid‐May (10.4%). Although oxalic acid (C2) is the dominant diacid until April, its predominance was replaced by succinic acid (C4) after polar sunrise. This may indicate that photochemical production of C2 was overwhelmed by its degradation when solar radiation was intensified and the atmospheric transport of its precursors from midlatitudes to the Arctic was ended in May. Interestingly, the contributions of azelaic (C9) and ω‐oxobutanoic acids to WSOC increased in early summer possibly due to an enhanced emission of biogenic unsaturated fatty acids from the ocean followed by photochemical oxidation in the atmosphere. An enhanced contribution of diacids to TC and WSOC at polar sunrise may significantly alter the hygroscopic properties of organic aerosols in the Arctic.
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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 | 0.000 | 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".