Atmospheric Chemistry and Physics Projecting future HFC-23 emissions
Bibliographic record
Abstract
Abstract. A Reference Case (RC) scenario for emissions of HFC-23 from co-production during HCFC-22 manufacture over the next 25 years is presented. Offered as a template rather than a prediction, this model projects current produc-tion practices and existing abatement frameworks to yield in-sights into how atmospheric composition and radiative forc-ing might change with and without additional efforts to con-strain HFC-23 emissions. Assuming that no additional abatement measures are im-plemented, emissions for year 2035 in this Reference Case would rise to 24 ktonnes yr−1, (cf., 8.6 ktonnes yr−1 in 2009), the atmospheric abundance of HFC-23 would rise to 50 ppt, which is a 121 % increase over the 2009 observed abundance, and HFC-23 would be expected to contribute a radiative forc-ing of 9 mW m−2 (cf., 4 mW m−2 in 2009). Under such a scenario, the HFC-23 emission growth rate would be a con-tinuation of the historical trend of ∼0.2 ktonnes yr−2 until 2030, after which the growth is projected to quadruple as the Montreal Protocol phase-out of HCFC production for dis-persive use concludes and HFC-23 thermal decomposition in the projects of the Clean Development Mechanism (CDM) comes to a scheduled end while growth in the production of HCFC-22 for feedstock use continues to climb with projected GDP growth. Two opposite variations regarding the future renewal of CDM projects are examined for their impact on projected emissions and abundance, relative to the Reference Case sce-nario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".