The Roles of N, S, and O in Molecular Absorption Features of Brown Carbon in PM<sub>2.5</sub> in a Typical Semi‐Arid Megacity in Northwestern China
Bibliographic record
Abstract
Abstract Brown Carbon (BrC) absorbs light in wavelength of 300–400 nm, and BrC molecule (BrCM) is a fundamental component responsible for aerosol radiative forcing. In this study, Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR MS) coupled with electrospray ionization (ESI) was used to determine methanol extracted BrCM in PM 2.5 collected in Xi'an, China. The absorption of individual BrCM was quantified through partial least square regression (PLSR) method. Results showed that 77.5% and 91.8% of winter and summer BrCMs were weak absorptive. The top BrCMs were responsible for 60.4% and 84.6%, respectively, of the absorbances in summer and winter. The nitrogen (N)‐containing organic molecules were identified to be critical components of light‐absorbing matters in both of the two seasons, outlining the significance of N chromogenesis in BrC. The top BrCMs were more closely related to ‐(O)NO 2 that originated from NO 2 engaged reactions in winter, and to ‐NH that formed in NH 3 reactions in summer. Sulfur (S)‐containing functional groups were not chromophoric while sulfur dioxide (SO 2 ) triggered N‐containing and S‐free BrCM formations under high nitrogen oxides (NOx) concentration levels and relative humidity (RH) in winter. Hypochromicity of oxygen (O) in BrC was discovered because of the photobleaching of oxidation and weak light‐absorbing of highly oxidized molecules.
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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".