Condensational uptake of semivolatile organic compounds in gasoline engine exhaust onto pre-existing inorganic particles
Bibliographic record
Abstract
Abstract. This paper presents the results of laboratory studies on the condensational uptake of gaseous organic compounds in the exhaust of a light-duty gasoline engine onto preexisting sulfate and nitrate seed particles. Significant condensation of the gaseous organic compounds in the exhaust occurs onto these inorganic particles on a time scale of 2–5 min. The amount of condensed organic mass (COM) is proportional to the seed particle mass, suggesting that the uptake is due to dissolution determined by the equilibrium partitioning between gas phase and particles, not adsorption. The amount of dissolution in unit seed mass, S, decreases as a power function with increased dilution of the exhaust, ranging from 0.23 g g−1 at a dilution ratio of 81, to 0.025 g g−1 at a dilution ratio of 2230. It increases nonlinearly with increasing concentration of the total hydrocarbons in the gas phase (THC), rising from 0.12 g g−1 to 0.26 g g−1 for a CTHC increase of 1 to 18 μg m−3, suggesting that more organics are partitioned into the particles at higher gas phase concentrations. In terms of gas-particle partitioning, the condensational uptake of THC gases in gasoline engine exhaust can account for up to 30% of the total gas + particle THC. The organic mass spectrum of COM has the largest fragment at m/z 44, with mass ratios of mass fragments 43/44 and 57/44 at 0.59 and 2.91, much lower than those reported for gasoline engine primary organic aerosols. The mass fragment 44/total organic mass ratio of 0.097 indicates that COM contains large oxygenated components. By incorporating the present findings, regional air quality modelling results suggest that the condensational uptake of THC onto sulfate particles alone can be comparable to the primary particle mass under moderately polluted ambient conditions. These findings are important for modelling and regulating the air quality impacts of gasoline vehicular emissions.
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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) | 0.001 | 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".