Viscosity and phase state of wildfire smoke particles in the stratosphere from pyrocumulonimbus events: an initial assessment
Bibliographic record
Abstract
Large wildfires periodically inject massive amounts of biomass burning organic aerosol (BBOA) into the stratosphere (~15 km ≤ altitude ≤ 50 km) via pyrocumulonimbus (pyroCb) events. These aerosols may remain aloft for many months and engage in multiphase chemistry that contributes to the destruction of stratospheric ozone. To predict this chemistry, it is essential to understand the viscosity and phase state of BBOA in the stratosphere. In this study, we use laboratory data and a thermodynamic model to evaluate these properties. Our findings indicate that unaged and aged wildfire smoke particles may be in a glassy state (viscosity 10^12 Pa s) for certain conditions in the stratosphere, particularly when the H2SO4-to-BBOA mass ratio in the aerosol particles is ≲ 0.33. Lidar observations of wildfire smoke in the stratosphere are consistent with these findings. In such a state, bulk reactions will be inhibited, and multiphase chemistry will be limited to the particle surfaces. The glassy state may also nucleate crystalline polar stratospheric clouds, potentially exacerbating stratospheric ozone depletion. Even after prolonged aging and a H2SO4-to-BBOA mass ratio of 1 (considered a likely upper limit for pyroCb smoke in the lower stratosphere with an aging time of ≲ 1 year), the viscosities may reach 10^6 to 10^11 Pa s for specific temperatures and relative humidities. These high viscosities should be considered when describing the stratospheric chemistry of wildfire smoke particles. We also identify critical areas where future research is needed to better constrain the viscosity and phase state of BBOA in the stratosphere; and thus, its impact on stratospheric ozone.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".