On the gas‐particle partitioning of soluble organic aerosol in two urban atmospheres with contrasting emissions: 2. Gas and particle phase formic acid
Bibliographic record
Abstract
Gas and fine particle (PM2.5) phase formic acid concentrations were measured with online instrumentation during separate one‐month studies in the summer of 2010 in Los Angeles (LA), CA, and Atlanta, GA. In both urban environments, median gas phase concentrations were on the order of a few ppbv (LA 1.6 ppbv, Atlanta 2.3 ppbv) and median particle phase concentrations were approximately tens of ng/m3 (LA 49 ng/m3, Atlanta 39 ng/m3). LA formic acid gas and particle concentrations had consistent temporal patterns; both peaked in the early afternoon and generally followed the trends in photochemical secondary gases. Atlanta diurnal trends were more irregular, but the mean diurnal profile had similar afternoon peaks in both gas and particle concentrations, suggesting a photochemical source in both cities. LA formic acid particle/gas (p/g) ratios ranged between 0.01 and 12%, with a median of 1.3%. No clear evidence that LA formic acid preferentially partitioned to particle water was observed, except on three overcast periods of suppressed photochemical activity. Application of Henry's Law to predict partitioning during these periods greatly under‐predicted particle phase formate concentrations based on bulk aerosol liquid water content (LWC) and pH estimated from thermodynamic models. In contrast to LA, formic acid partitioning in Atlanta appeared to be more consistently associated with elevated relative humidity (i.e., aerosol LWC), although p/g ratios were somewhat lower, ranging from 0.20 to 5.8%, with a median of 0.8%. Differences in formic acid gas absorbing phase preferences between these two cities are consistent with that of bulk water‐soluble organic carbon reported in a companion paper.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".