α-Pinene Oxidation in the Presence of Seed Aerosol: Estimates of Nucleation Rates, Growth Rates, and Yield
Bibliographic record
Abstract
A recently developed inverse-modeling procedure has been applied to a case study of particle nucleation and growth following alpha-pinene and SO2 oxidation in a smog chamber. With the use of only the measured aerosol size distributions as input, the condensational growth rate is obtained by regression analysis of the general dynamic equation, taking into account coagulation and wall losses. The growth rate provides an indirect measure of the concentration of the condensing species, offset by their vapor pressures. Assuming a particle density of 1.0 g cm(-3), an aerosol yield of 7 +/- 1% is obtained for an initial alpha-pinene concentration of 14 ppbv and a final organic aerosol mass of 4 microg m3. Using the estimated vapor concentration, we show that the time-dependence of the yield is at least partly due to the time needed for condensation. Such a kinetic limitation to secondary organic aerosol formation may have implications for our understanding of gas-particle partitioning. The measured size distributions are also used to determine the empirical nucleation rate; it appears to be enhanced by the presence of organics.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".