Dissolved organic carbon (DOC) and select aldehydes in cloud and fog water: the role of the aqueous phase in impacting trace gas budgets
Bibliographic record
Abstract
Abstract. Cloud and fog droplets efficiently scavenge and process water-soluble compounds and, thus, modify the chemical composition of the gas and particle phases. The concentrations of dissolved organic carbon (DOC) in the aqueous phase reach concentrations on the order of ~ 10 mgC L−1 which is typically on the same order of magnitude as the sum of inorganic anions. Aldehydes and carboxylic acids typically comprise a large fraction of DOC because of their high solubility. The dissolution of species in the aqueous phase can lead to (i) the removal of species from the gas phase preventing their processing by gas phase reactions (e.g., photolysis of aldehydes) and (ii) the formation of unique products that do not have any efficient gas phase sources (e.g., dicarboxylic acids). We present measurements of DOC and select aldehydes in fog water at high elevation and intercepted clouds at a biogenically-impacted location (Whistler, Canada) and in fog water in a more polluted area (Davis, CA). Concentrations of formaldehyde, glyoxal and methylglyoxal were in the micromolar range and comprised ≤ 2% each individually of the DOC. Comparison of the DOC and aldehyde concentrations to those at other locations shows good agreement and reveals highest levels for both in anthropogenically impacted regions. Based on this overview, we conclude that the fraction of organic carbon (dissolved and insoluble inclusions) in the aqueous phase of clouds or fogs, respectively, comprises 2–~ 40% of total organic carbon. Higher values are observed to be associated with aged air masses where organics are expected to be more highly oxidised and, thus, more soluble. Accordingly, the aqueous/gas partitioning ratio expressed here as an effective Henry's law constant for DOC (KH*DOC) increases by an order of magnitude from 7 × 103 M atm−1 to 7 × 104 M atm−1 during the ageing of air masses. The measurements are accompanied by photochemical box model simulations. These simulations are used to contrast two scenarios, i.e., an anthropogenically vs. a more biogenically impacted one as being representative for Davis and Whistler, respectively. Since the simplicity of the box model prevents a fully quantitative prediction of the observed aldehyde concentrations, we rather use the model results to compare trends in aldehyde partitioning and ratios. They suggest that the scavenging of aldehydes by the aqueous phase can reduce HO2 gas phase levels significantly by two orders of magnitude due to a weaker net source of HO2 production from aldehyde photolysis in the gas phase. Despite the high solubility of dicarbonyl compounds (glyoxal, methylglyoxal), their impact on the HO2 budget by scavenging is < 10% of that of formaldehyde. The overview of DOC and aldehyde measurements presented here reveals that clouds and fogs can be efficient sinks for organics, with increasing importance in aged air masses. Even though aldehydes, specifically formaldehyde, only comprise ~ 1% of DOC, their scavenging and processing in the aqueous phase might translate into significant effects in the oxidation capacity of the atmosphere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".