Unexplored volatile organic compound emitted from petrochemical facilities: implications for ozone production and atmospheric chemistry
Bibliographic record
Abstract
A compound was observed using airborne proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) measurements in the emission plumes from the Daesan petrochemical facility in South Korea. The compound was detected at m/z 43.018 on the PTR-TOF-MS and was tentatively identified as ketene, a rarely measured reactive volatile organic compound (VOC). Estimated ketene mixing ratios as high as ∼ 50 ppb (parts per billion) were observed in the emission plumes. Emission rates of ketene from the facility were estimated using a horizontal advective flux approach and ranged from 84–316 kg h −1 . These emission rates were compared to the emission rates of major known VOCs such as benzene, toluene, and acetaldehyde. Significant correlations ( r 2 > 0.7) of ketene with methanol, acetaldehyde, benzene, and toluene were observed for the peak emissions, indicating commonality of emission sources. The calculated average ketene OH reactivity for the emission plumes over Daesan ranged from 3.33–7.75 s −1 , indicating the importance of the quantification of ketene to address missing OH reactivity in the polluted environment. The calculated average O 3 production potential for ketene ranged from 2.98–6.91 ppb h −1 . Our study suggests that ketene, or any possible VOC species detected at m/z 43.018, has the potential to significantly influence local photochemistry, and therefore, further studies focusing on the photooxidation and atmospheric fate of ketene through chamber studies are required to improve our current understanding of VOC OH reactivity and, hence, tropospheric O 3 production.
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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".