Formation and evolution of biogenic secondary organic aerosol over a forest site in Japan
Bibliographic record
Abstract
Abstract Chemical composition of atmospheric aerosol particles was characterized using an Aerodyne high‐resolution time‐of‐flight aerosol mass spectrometer at a forest site in Japan during 20–30 August 2010. A major fraction of nonrefractory submicron aerosol particles consisted of organics (accounting for, on average, 46% of total mass), sulfate (41%), and ammonium (12%). Positive matrix factorization of high‐resolution organic aerosol mass spectra identified two oxygenated organic aerosol (OOA) components: a highly oxidized, low‐volatility OOA and a less oxidized, semivolatile OOA (SV‐OOA), interpreted mainly as aged regional organic aerosol (OA) and as locally formed biogenic secondary OA (BSOA), respectively. The mass concentrations of SV‐OOA increased prominently during the daytime, suggesting a strong photochemical production of BSOA on both nonevent and new particle formation event days. Increases of f44 (fraction of m/z 44 in OA mass spectrum), the fraction of CxOy+ fragment, and the O/C ratio after midday (around 13:00 local time) suggest that OA became increasingly oxygenated, which can be explained by the aging of freshly formed BSOA. Aqueous phase oxidation reactions under conditions of high relative humidity may have played a vital role in the aging of BSOA in this forest atmosphere. A substantial increase of the mass concentration of organics in the small size range (below 300 nm in vacuum aerodynamic diameter), without an increase in that of sulfate, suggests that the formation of BSOA made a dominant contribution to the presence of particles of cloud condensation nuclei size around the studied area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".