Molecular Absorption and Evolution Mechanisms of PM<sub>2.5</sub>Brown Carbon Revealed by Electrospray Ionization Fourier Transform–Ion Cyclotron Resonance Mass Spectrometry During a Severe Winter Pollution Episode in Xi'an, China
Bibliographic record
Abstract
Abstract Knowledge of the molecular‐level chemistry of brown carbon (BrC) is important in reducing the uncertainties in aerosol radiative forcing. Time‐resolved ambient PM2.5samples were collected during a severe pollution episode in January 2017 over Xi'an, China for a comprehensive nontarget and full scanning of BrC molecules and their absorption properties using electrospray ionization Fourier transform–ion cyclotron resonance mass spectrometry combined with partial least squares regression analysis, which apportioned the overall ultraviolet absorption to individual molecules. The estimated absorption of CHNO and CHNOS molecules exhibited nighttime prevalence, whereas CHOS, CHNS, CHN, CHO, CHS, and CH molecules presented a dynamic trend. Carbon conjugation was positively correlated with estimated absorption by CHO and CHNO molecules, while exhibiting a mixed relationship with CHNOS. Higher nitrogen content was associated with enhanced light‐absorption properties of BrC molecules, while higher oxygen and sulfur content appeared to be associated with photobleaching during secondary transformation.
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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) | 0.000 | 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".