Analysis of the Unresolved Organic Fraction in Atmospheric Aerosols with Ultrahigh-Resolution Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy: Organosulfates As Photochemical Smog Constituents
Bibliographic record
Abstract
Complementary molecular and atomic signatures obtained from Fourier transform ion cyclotron resonance (FTICR) mass spectra and NMR spectra provided unequivocal attribution of CHO, CHNO, CHOS, and CHNOS molecular series in secondary organic aerosols (SOA) and high-resolution definition of carbon chemical environments. Sulfate esters were confirmed as major players in SOA formation and as major constituents of its water-soluble fraction (WSOC). Elevated concentrations of SO(2), sulfate, and photochemical activity were shown to increase the proportion of SOA sulfur-containing compounds. Sulfonation of CHO precursors by means of heterogeneous reactions between carbonyl derivatives and sulfuric acid in gas-phase photoreactions was proposed as a likely formation mechanism of CHOS molecules. In addition, photochemistry induced oligomerization processes of CHOS molecules. Methylesters found in methanolic extracts of a SOA subjected to strong photochemical exposure were considered secondary products derived from sulfate esters by methanolysis. The relative abundance of nitrogen-containing compounds (CHNO and CHNOS series) appeared rather dependent on local effects such as biomass burning. Extensive aliphatic branching and disruption of extended NMR spin-systems by carbonyl derivatives and other heteroatoms were the most significant structural motifs in SOA. The presence of heteroatoms in elevated oxidation states suggests a clearly different SOA formation trajectory in comparison with established terrestrial and aqueous natural organic matter.
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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".