Divergent Evolution of Carbonaceous Aerosols during Dispersal of East Asian Haze
Bibliographic record
Abstract
Abstract Wintertime East Asia is plagued by severe haze episodes, characterized by large contributions of carbonaceous aerosols. However, the sources and atmospheric transformations of these major components are poorly constrained, hindering development of efficient mitigation strategies and detailed modelling of effects. Here we present dual carbon isotope (δ13C and Δ14C) signatures for black carbon (BC), organic carbon (OC) and water-soluble organic carbon (WSOC) aerosols collected in urban (Beijing and BC for Shanghai) and regional receptors (e.g., Korea Climate Observatory at Gosan) during January 2014. Fossil sources (>50%) dominate BC at all sites with most stemming from coal combustion, except for Shanghai, where liquid fossil source is largest. During source-to-receptor transport, the δ13C fingerprint becomes enriched for WSOC but depleted for water-insoluble OC (WIOC). This reveals that the atmospheric processing of these two major pools are fundamentally different. The photochemical aging (e.g., photodissociation, photooxidation) during formation and transport can release CO2/CO or short-chain VOCs with lighter carbon, whereas the remaining WSOC becomes increasingly enriched in δ13C. On the other hand, several processes, e.g., secondary formation, rearrangement reaction in the particle phase, and photooxidation can influence WIOC. Taken together, this study highlights high fossil contributions for all carbonaceous aerosol sub-compartments in East Asia, and suggests different transformation pathways for different classes of carbonaceous aerosols.
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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 | 0.000 | 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".