Methodology for quantifying the volatile mixing state of an aerosol
Bibliographic record
Abstract
Mixing state refers to the relative proportions of chemical species in an aerosol, and the way these species are combined; either as a population where each particle consists of a single species (‘externally mixed’) or where all particles individually consist of two or more species (‘internally mixed’) or the case where some particles are pure and some particles consist of multiple species. The mixing state affects optical and hygroscopic properties, and quantifying it is therefore important for studying an aerosol's climate impact. In this article, we describe a method to quantify the volatile mixing state of an aerosol using a differential mobility analyzer, centrifugal particle mass analyzer, catalytic denuder, and condensation particle counter by measuring the mass distributions of the volatile and non-volatile components of an aerosol and determining how the material is mixed within and between particles as a function of mobility diameter. The method is demonstrated using two aerosol samples from a miniCAST soot generator, one with a high elemental carbon (EC) content, and one with a high organic carbon (OC) content. The measurements are presented in terms of the mass distribution of the volatile and non-volatile material, as well as measures of diversity and mixing state parameter. It was found that the high-EC soot nearly consisted of only pure particles where 86% of the total mass was non-volatile. The high-OC soot consisted of either pure volatile particles or particles that contained a mixture of volatile and non-volatile material where 8% of the total mass was pure volatile particles and 70% was non-volatile material (with the remaining 22% being volatile material condensed on non-volatile particles).© 2016 American Association for Aerosol Research
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".