Long range transport of Canadian Wildfire smoke to Europe in Fall 2023: aerosol properties and spectral features of smoke particles
Bibliographic record
Abstract
Abstract. Canadian wildfires in Fall of 2023 were unique regarding the observed aerosol properties using remote sensing and in situ measurements for both short-range and long-range transported plumes across North America and Europe. One of the highlights was the observation of special concave spectral curvature in AOD having maxima at higher wavelengths than the minimum measured wavelength which led to negative values of Ångström exponent in spectral ranges below 500 nm. Along with this, large accumulation mode size distributions with volume median diameters reaching about 800 nm were observed. Another unique observation was the non-monotonic spectral curvature in single scattering albedo (SSA). For most of the stations, SSA increased in the UV-Visible region and/or further remaining either constant or decreasing at longer wavelengths as observed from retrievals from column integrated (AOD) from remote sensing and coefficients from in situ measurements. Additionally, two stations in Canada and one in Europe were found to have a well-defined peak in AOD at 500 nm. These Canadian stations also displayed a non-monotonic spectral SSA with maxima at 675 nm, while the high altitude stations of Europe showed monotonically increasing SSA. Finally, a much higher (approximately 5 times) UV absorption than visible absorption indicated the presence of brown carbon and/or tar balls, which have a strong spectral dependence in imaginary refractive index. The SSA concave spectral curvature denotes the mix of black carbon and non-absorbing particulate matter and influence of particle size, while the AOD concave spectral curvature is attributed to particle size.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".