Diffusion Coefficients and Mixing Times of Organic Molecules in β-Caryophyllene Secondary Organic Aerosol (SOA) and Biomass Burning Organic Aerosol (BBOA)
Bibliographic record
Abstract
Information on the diffusion rates of organic molecules within secondary organic aerosol (SOA) and biomass burning organic aerosol (BBOA) is needed to predict the impact of these aerosols on atmospheric chemistry, air quality, and climate. Nevertheless, no studies have measured diffusion rates of organics within SOA generated from β-caryophyllene or within BBOA. Here, we measured diffusion rates of organic molecules in laboratory-generated SOA and BBOA as a function of water activity ( a w ) using fluorescence recovery after photobleaching. The SOA was generated by the ozonolysis of β-caryophyllene, and the BBOA was generated by the pyrolysis of pine wood. Only the water-soluble component of the BBOA was studied. The measured diffusion coefficients of organic molecules in β-caryophyllene range from 1.1 × 10 –16 to 1.3 × 10 –14 m 2 s –1 for a w values ranging from 0.23 to 0.86. For BBOA, the diffusion coefficients range from 7.3 × 10 –17 to 6.6 × 10 –16 m 2 s –1 for a w values ranging from 0.23 to 0.43. Based on these values, the mixing times of organic molecules within a 200 nm SOA or BBOA are less than 1 min for a w values >0.23. Since a w values are often greater than 0.23 in the planetary boundary layer and temperatures in the planetary boundary are often within 5 K of our experimental temperatures, mixing times are likely often short in that part of the atmosphere for the types of aerosols studied here. For β-caryophyllene SOA, we compared the measured diffusion coefficients with predictions based on the Stokes–Einstein relation and the fractional Stokes–Einstein relation. For both the Stokes–Einstein and the fractional Stokes–Einstein relations, the measured diffusion coefficients agree with the predicted diffusion coefficients. This work illustrates that when the radius of the diffusing molecules is greater than the average radius of the matrix molecules, the Stokes–Einstein equation is able to predict diffusion coefficients in β-caryophyllene SOA with reasonable accuracy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".