Modelling the optical properties of fresh biomass burning aerosol produced in a smoke chamber: results from the EFEU campaign
Bibliographic record
Abstract
Abstract. A better characterisation of the optical properties of biomass burning aerosol as a function of the burning conditions is required in order to quantify their effects on climate and atmospheric chemistry. Controlled laboratory combustion experiments with different fuel types were carried out at the combustion facility of the Max Planck Institute for Chemistry (Mainz, Germany) as part of the 'Impact of Vegetation Fires on the Composition and Circulation of the Atmosphere' (EFEU) project. Using the measured size distributions as well as mass scattering and absorption efficiencies, Mie calculations provided mean effective refractive indices of 1.60−0.010i and 1.56−0.010i (λ=0.55 μm) for smoke particles emitted from the combustion of savanna grass and an African hardwood (musasa), respectively. The relatively low imaginary parts suggest that the light-absorbing carbon of the investigated fresh biomass burning aerosol is only partly graphitized, resulting in strongly scattering and less absorbing particles. While the observed variability in mass scattering efficiencies was consistent with changes in particle size, the changes in the mass absorption efficiency can only be explained, if the chemical composition of the particles varies with combustion conditions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".