Biomass-burning-derived particles from a wide variety of fuels – Part 1: Properties of primary particles
Bibliographic record
Abstract
Abstract. Relationships between various optical, physical, and chemical properties of biomass-combustion-derived particles are characterized for particles produced in the laboratory from a wide range of fuels and burn conditions. The modified combustion efficiency (MCE), commonly used to parameterize biomass particle emissions and properties, is shown to generally have weak predictive capabilities, especially for more efficient combustion conditions. There is, however, a strong relationship between many intensive optical properties (e.g., single-scatter albedo, Ångström absorption exponent, mass absorption efficiency) and the organic aerosol-to-black carbon ([OA] ∕ [BC]) mass ratio over a wider range than previously considered (0.3 to 105). The properties of brown carbon (BrC, i.e., light-absorbing organic carbon) also vary with [OA] ∕ [BC]. Coating-induced enhancements (i.e., “lensing” effects) contribute only a minor amount to BC absorption for all of the burns despite some burns producing particles having large ensemble-average coating-to-core mass ratios. The BC–OA mixing state varies strongly with [OA] ∕ [BC]; the fraction of OA that is internally mixed with BC decreases with [OA] ∕ [BC] while the relative amount of OA coated on BC increases. In contrast, there is little relationship between many OA bulk chemical properties and [OA] ∕ [BC], with the O : C and H : C atomic ratios and the relative abundance of a key marker ion (m/z=60, linked to levoglucosan) all showing no dependence on [OA] ∕ [BC]. In contrast, both the organic nitrate fraction of OA and the OA volatility do depend on the [OA] ∕ [BC]. Neither the total particle nor BC-specific size distributions exhibit any clear dependence on the burn conditions or [OA] ∕ [BC], although there is perhaps a dependence on fuel type. Overall, our results expand on existing knowledge to contribute new understanding of the properties of particles emitted from biomass combustion.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".