A study of internal and external mixing scenarios and its effect on aerosol optical properties and direct radiative forcing
Bibliographic record
Abstract
The optical properties and hence the radiative forcing of atmospheric aerosols are determined, in part, by the way in which the various constituents are externally or internally mixed. The mixing state must be known to compute the effective refractive index, water activity, and size distribution of the aerosols. In this study we found that the percentage difference in the optical properties, including extinction, single scattering albedo, and asymmetry parameter, between an internal mixture and external mixture of black carbon and ammonium sulfate can be over 25% for the dry case and over 50% for the wet case for typical mass mixing ratios. The differences are a result of a complicated combination of nonlinear Mie theory on the refractive index, assumptions about the coagulated particle sizes for internal mixtures, and the role of water uptake and deliquescence as a function of relative humidity. The computed optical properties are used to estimate the globally average clear‐sky direct radiative forcing for different mixing assumptions. The results are displayed as a function of relative humidity to conveniently see the mixing effects for dry aerosols at less than the crystallization point, for dry internal and wet external mixtures between the crystallization and deliquescence points, and for fully wet mixtures above the deliquescence point. For a 9:1 ammonium sulfate to black carbon mass ratio, nearly all the cooling effect predicted for an external mixture is lost for the internally mixed assumption, especially for relative humidities less than the deliquescence point.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".