Emission Characteristics of HFC-23 (CHF<sub>3</sub>)/HCFC-22 (CHClF<sub>2</sub>) between Different Air Masses in Northeastern Asia
Bibliographic record
Abstract
HCFC-22 (chlorodifluoromethane, <TEX>$CHClF_2$</TEX>), one of the major components in various refrigeration, is emitted mostly from developing countries, as its consumption is not limited until 2013 by the Montreal Protocol. In addition, HFC-23 (trifluoromethane, <TEX>$CHF_3$</TEX>), a by-product in the manufacture of HCFC-22, is also a powerful greenhouse gas. Here, we discuss the regional emission characteristics of these compounds based on high-frequency in-situ measurements using the "Medusa" GC-MS system. HCFC-22 and HFC-23 baseline concentrations measured at Gosan (Jeju Island, Korea) from November 2007 to December 2008 increased by 1.8 ppt/yr and 0.6 ppt/yr, respectively. Pollution events of these compounds were observed, very frequently (e.g., ~2~3 times) at Gosan than baseline levels. All the measurement data were divided into four groups by simultaneously considering the ratio (HFC-23/HCFC-22) and concentration (HCFC-22) at Trinidad Head (TH, California, USA). The residence time of trajectories were then analyzed in each of the four groups. The results exhibited the existence of a strong correlation with air mass origin for each group: 1) Air masses originating from Siberia in the north and from the Pacific in the south had ratios of 0.08~0.12 and concentrations of 196.9~254.3 ppt which is highly comparable to background air at TH. 2) Air masses passing over the Southern China exhibited similar ratios but higher HCFC-22 concentrations. 3) Air masses passing over the Northern China had ratios of 0.12~0.21. 4) Air masses passing over Korea and/or Japan had ratios of 0.01~0.08. Our results suggest that the HFC-23/HCFC-22 ratio can be used as a good indicator for the assessment of the pollution with Chinese origin. We also confirmed differences in air masses traveling over Northern and Southern China, most likely due to differences in air mass travelling speed over these regions before arriving at Gosan. This signature may be treated as one of the critical components in identifying the emission sources from different parts of China.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".