Mixing times of organic molecules within secondary organic aerosol particles: a global planetary boundary layer perspective
Bibliographic record
Abstract
Abstract. When simulating the formation and life cycle of secondary organic aerosol (SOA) with chemical transport models, it is often assumed that organic molecules are well mixed within SOA particles on the timescale of 1 h. While this assumption has been debated vigorously in the literature, the issue remains unresolved in part due to a lack of information on the mixing times within SOA particles as a function of both temperature and relative humidity. Using laboratory data, meteorological fields, and a chemical transport model, we estimated how often mixing times are < 1 h within SOA in the planetary boundary layer (PBL), the region of the atmosphere where SOA concentrations are on average the highest. First, a parameterization for viscosity as a function of temperature and RH was developed for α-pinene SOA using room-temperature and low-temperature viscosity data for α-pinene SOA generated in the laboratory using mass concentrations of ∼ 1000 µg m−3. Based on this parameterization, the mixing times within α-pinene SOA are < 1 h for 98.5 % and 99.9 % of the occurrences in the PBL during January and July, respectively, when concentrations are significant (total organic aerosol concentrations are > 0.5 µg m−3 at the surface). Next, as a starting point to quantify how often mixing times of organic molecules are < 1 h within α-pinene SOA generated using low, atmospherically relevant mass concentrations, we developed a temperature-independent parameterization for viscosity using the room-temperature viscosity data for α-pinene SOA generated in the laboratory using a mass concentration of ∼ 70 µg m−3. Based on this temperature-independent parameterization, mixing times within α-pinene SOA are < 1 h for 27 and 19.5 % of the occurrences in the PBL during January and July, respectively, when concentrations are significant. However, associated with these conclusions are several caveats, and due to these caveats we are unable to make strong conclusions about how often mixing times of organic molecules are < 1 h within α-pinene SOA generated using low, atmospherically relevant mass concentrations. Finally, a parameterization for viscosity of anthropogenic SOA as a function of temperature and RH was developed using sucrose–water data. Based on this parameterization, and assuming sucrose is a good proxy for anthropogenic SOA, 70 and 83 % of the mixing times within anthropogenic SOA in the PBL are < 1 h for January and July, respectively, when concentrations are significant. These percentages are likely lower limits due to the assumptions used to calculate mixing times.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".