Investigation of Primary and Secondary Particulate Brown Carbon in Two Chinese Cities of Xi’an and Hong Kong in Wintertime
Bibliographic record
Abstract
Brown carbon (BrC), an aerosol carbonaceous matter component, impacts atmospheric radiation and global climate because of its absorption in the near-ultraviolet-visible region. Simultaneous air sampling was conducted in two megacities of Xi'an (northern) and Hong Kong (southern) in China in winter of 2016-2017. The aim of this study is to determine and characterize the BrC compounds in collected filter samples. Characteristic absorption peaks corresponding to aromatic C-C stretching bands, organo-nitrates, and C═O functional groups were seen in spectra of Xi'an samples, suggesting that the BrC was derived from freshly smoldering biomass and coal combustion as well as aqueous formation of anthropogenic secondary organic carbon. In Hong Kong, the light absorption of secondary BrC accounted for 76% of the total absorbances of BrC. The high abundance of strong C═O groups, biogenic volatile organic compounds (BVOCs) and atmospheric oxidants suggest secondary BrC was likely formed from photochemical oxidation of BVOCs in Hong Kong. Several representative BrC molecular markers were detected using Fourier transform ion cyclotron resonance mass spectrometry and their absorption properties were simulated by quantum chemistry. The results demonstrate that light absorption capacities of secondary anthropogenic BrC with nitro-functional groups were stronger than those of biogenic secondary BrC and anthropogenic primary BrC.
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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 | 0.001 | 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".