Emission patterns and spatiotemporal variations of halocarbons in the Pearl River Delta region, southern China
Bibliographic record
Abstract
On 8 selected days between 25 October and 1 December 2007, 198 whole air samples were simultaneously collected at two sites in the greater Pearl River Delta (PRD), namely, Wan Qing Sha (WQS) in inland PRD and Tung Chung (TC) in Hong Kong, for the evaluation of halocarbons including chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs) and other chlorinated compounds. The mean mixing ratios of CFC‐12, CH3CCl3, CH3Br, C2HCl3, and C2Cl4 at WQS were much higher than those at TC (p < 0.001), while HCFC‐22 was higher at TC (p < 0.01). Long‐lived species such as CFC‐11, CFC‐12, and CFC‐113 showed similar temporal patterns on most sampling days with small daily variation, whereas the main species used as solvents such as C2HCl3 and C2Cl4 presented large daily variations though with consistent temporal patterns. Source profile analysis revealed that although there was no remarkable change in emission sources between 2001–2002 and 2007, the emissions of CFCs and CCl4 from the production of refrigeration in 2007 were 1.4–2.0 times those in 2001–2002, and the use of HCFC‐22 has significantly increased in these years while the use of C2HCl3 and C2Cl4 in the electronics industry showed a remarkable reduction. By comparing the halocarbon data collected in this study with those observed by other research teams in recent years, we found that the levels of CFCs have declined since 2001, while their substitute HCFC‐22 has increased in emissions in recent years, especially in Hong Kong. The annual trends are consistent with the implementation of the Montreal Protocol. The results obtained in this study provide useful information to local government on effective control of halocarbon emissions in this region.
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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 | 0.000 | 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) | 0.000 | 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".