Optical properties and composition of viscous organic particles found in the Southern Great Plains
Bibliographic record
Abstract
Abstract. Atmospheric high viscosity organic particles (HVOP) were observed in samples of ambient aerosol collected on April and May 2016 in the Southern Great Plains of the United States. These particles were apportioned as either airborne soil organic particles (ASOP) or tar balls (TB) from biomass burning based on spetro-microscopic imaging and assessment of meteorological records of smoke and precipitation data. Regardless of their apportionment, the number fractions of HVOP were positively correlated (R2 = 0.85) with increased values of Ångström absorption exponent (AAE) measured in-situ for ambient aerosol at the site. Extending this correlation to 100 % HVOP yields an AAE of 2.6, similar to previous literature reports of the class of light absorbing organic particles known as brown carbon (BrC). Although there are chemical similarities between ASOP and TB, they can be distinguished based on composition inferred from near edge absorption X-ray fine structure (NEXAFS) spectroscopy. ASOP were distinguished from TB based on their average −COOH/C=C and −COOH/COH peak ratios, with ASOP having lower ratios. NEXAFS spectra of filtered soil organic brine particles nebulized from field samples of standing water deposited after rain were consistent with ASOP when laboratory particles were generated by bubble bursting at the air-organic brine interface. However, particles generated by nebulizing the bulk volume of soil organic brine had particle composition different from ASOP. These observations are consistent with the raindrop generation mechanism responsible for ASOP emissions in the area of study. In contrast, nebulized samples carry with them higher fractions soil inorganics dissolved in the bulk volume of soil brine that are not aerosolized by the raindrop mechanism. Our results support the bubble bursting mechanism of particle generation during rainfall resulting in the ejection of soil organics into the atmosphere.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".