Changing trends and emissions of hydrochlorofluorocarbons and theirhydrofluorocarbon replacements
Bibliographic record
Abstract
Abstract. High frequency, in situ global observations of HCFC-22 (CHClF2), HCFC-141b (CH3CCl2F), HCFC-142b (CH3CClF2) and HCFC-124 (CHClFCF3) and their main HFC replacements HFC-134a (CH2FCF3), HFC-125 (CHF2CF3), HFC-143a (CH3CF3), and HFC-32 (CH2F2) have been used to determine their changing global growth rates and emissions in response to the Montreal Protocol and its recent amendments. The 2007 adjustment to the Montreal Protocol required the accelerated phase-out of HCFCs with global production and consumption capped in 2013, to mitigate their environmental impact as both ozone depleting substances and important greenhouse gases. We find that this change has coincided with a reduction in global emissions of the four HCFCs with aggregated global emissions in 2015 of 444 ± 75 Gg/yr, in CO2 equivalent units (CO2 e) 0.75 ± 0.1 Gt/yr, compared with 483 ± 70 Gg/yr (0.82 ± 0.1 Gt/yr CO2 e) in 2010. (All quoted uncertainties in this paper are 1 sigma). About 80 % of the total HCFC atmospheric burden in 2015 is HCFC-22, where global HCFC emissions appear to have been relatively constant in spite of the 2013 cap on global production and consumption. We attribute this to a probable increase in production and consumption of HCFC-22 in Montreal Protocol Article 5 (developing) countries and the continuing release of HCFC-22 from the large banks which dominate HCFC global emissions. Conversely, the four HFCs all show increasing annual growth rates with aggregated global HFCs emissions in 2015 of 329 ± 70 Gg/yr (0.65 ± 0.12 Gt/yr CO2 e) compared to 2010 with 240 ± 50 Gg/yr (0.47 ± 0.08 Gt/yr CO2 e). As HCFCs are replaced by HFCs we investigate the impact of the shift to refrigerant blends which have lower global warming potentials (GWPs). We also note that emissions of HFC-125 and HFC-32 appear to have increased more rapidly during the 2011–2015 5-yr period compared to 2006–2010.
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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) | 0.001 | 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".