Measurements of Low-Molecular-Mass Carboxylic Acids in Atmospheric Aerosols by Capillary Electrophoresis
Bibliographic record
Abstract
Capillary electrophoresis (CE) methods for the determination of low-molecular-mass (LMM) carboxylic acids in airborne particular matter have been developed. The separations of 22 LMM carboxylic acids, including acids derived from the oxidation of biogenic hydrocarbons, are performed using a background electrolyte consisting of 3.0mM 2,6-naphthalenedicarboxylic acid and 18.0mM 2,2-bis (hydroxymethyl)-2,2',2"-nitrilotriethanol (Bis-tris) in 16% (v/v) 1-propanol within 10 min. Using a combination of a buffer mixed with an organic solvent and electroosmotic flow modifier, a minimum of peak overlaps is achieved with migration time variation of less than 1% and peak area ratio (relative to an internal standard) variation of less than 5% within 1 day. The detection limits for the aliphatic LMM acids that can be determined by this method are in the range of 30-140 micro g/L. Furthermore, a simple method for efficient extraction of LMM organic acids from particulate atmospheric matter collected on quartz fiber filters using high-volume samplers is developed. Combining the extraction procedure with a reduction of the extract to approximately 0.2 mL allows for the measurement of LLM in atmospheric particulate organic matter at concentrations well below 1 ng.m(-3). Repeat analysis of filters collected in tunnels, urban, suburban, and forested areas demonstrate that the procedure allows for measurements of aliphatic and aromatic LMM acids within a variability of 10-25%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".