Airborne Observations of CFCs Over Hebei Province, China in Spring 2016
Bibliographic record
Abstract
Abstract In Spring 2016, 27 whole air samples were collected from an aircraft ∼500–∼3,500 m over Hebei Province, China and analyzed for 16 halocarbons, including chlorofluorocarbons (CFCs). Mixing ratios (median, 25th–75th percentiles) of CFC‐11 (281, 255–318 ppt), CFC‐12 (546, 473–591 ppt), CFC‐113 (79, 73–85 ppt), CFC‐114 (22, 19–25 ppt), HCFC‐22 (345, 308–432 ppt), and CCl4 (88, 75–104 ppt) were often observed to be higher than their global tropospheric background levels. The significantly elevated mixing ratios of ozone depleting substances (ODSs) combined with strong correlations with anthropogenic tracers known to have substantial use and emission in this region (HCFC‐22 and CH2Cl2) suggest continuing emissions of multiple Montreal Protocol‐controlled gases at the time of measurement. We use HYSPLIT trajectory clusters and potential source contribution function methods to identify principal transport pathways of CFCs. We find the highest mixing ratios of ODSs in air originating from Inner Mongolia, Hebei, and Shandong. The strong correlations between CFC‐11 and CFC‐12 with the feedstock CCl4 suggest new production is prevalent in all three regions. We find no evidence for new production of CFC‐113, but the strong correlation of CFC‐114 with the feedstock C2Cl4 suggests new production of CFC‐114 from the southeast of China. The findings of this study confirm high mixing ratios of ODSs over Hebei in Spring 2016 and suggest new production and use (rather than release from banks), which is in conflict with the Montreal Protocol agreement that bans the production of CFCs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".