Optical Properties and Radiative Forcing of Aged BC due to Hygroscopic Growth: Effects of the Aggregate Structure
Bibliographic record
Abstract
Abstract Black carbon (BC) particles become hydrophilic after mixing with soluble matter in the atmosphere, and their optical and radiative properties can be significantly modified accordingly. This study investigates the impact of aggregate structure on optical and radiative properties of aged BC, that is, BC coated by sulfate or organic aerosols, especially during hygroscopic growth. A more realistic BC morphology based on fractal aggregates is considered, and inhomogeneous mixtures of BC aggregates are treated more realistically (with respect to particle geometries) in the multiple sphere T‐matrix method for optical property simulations. As relative humidity increases, BC extinction is significantly enhanced due to an increase in scattering, and the enhancement depends on the amount and hydrophilicity of the coating. The absorption exhibits less variation during hygroscopic growth because the coating of aerosols already leads to BC absorption close to the maximum. Furthermore, hygroscopic growth not only results in negative radiative forcing (RF) at the top of the atmosphere but also slightly weakens the absorption in the atmosphere (inducing a negative RF in the atmosphere). Compared to the more realistic model with BC as aggregates, the currently popular core‐shell model reasonably approximates the top of the atmosphere RF but underestimates the atmospheric RF due to hygroscopic growth by up to 40%. Furthermore, for the RF caused by internal mixing, the core‐shell model overestimates the RFs at the surface and in the atmosphere by ~10%.
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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 | 0.000 |
| 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 | 0.000 |
| 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".