Continental-scale contributions to the global CFC-11 emission increase between 2012 and 2017
Bibliographic record
Abstract
Abstract. The early detection of a global emission increase of CFC-11 after 2012 (Montzka et al., 2018) alerted society to a possible violation of the Montreal Protocol on Substances that Deplete the Ozone Layer (MP). This early alert resulted in parties participating in the MP taking urgent actions (United Nations Environment Programme (UNEP), 2019). As a result, atmospheric measurements made in 2019 suggest a sharp decline in global CFC-11 emissions (Montzka et al., 2021). Despite the success in the early detection and mitigation of some of this problem, regions fully responsible for the recent global emission changes of CFC-11 have not yet been identified. Roughly two thirds (60 ± 40 %) of the emission increase between 2008–2012 and 2014–2017 and two thirds (60 ± 30 %) of emission decline between 2014–2017 and 2019 was explained by regional emission changes in eastern mainland China (Park et al., 2021; Rigby et al., 2019). Here, we used atmospheric CFC-11 measurements made from two global aircraft surveys, the HIAPER Pole-to-Pole Observations (HIPPO) in November 2009–September 2011 and the Atmospheric Tomography Mission (ATom) in August 2016–May 2018, in combination with the global CFC-11 measurements made by the U.S. National Oceanic and Atmospheric Administration during these two periods, to derive global and regional emission changes of CFC-11. Our results suggest Asia accounted for the largest fractions of global CFC-11 emissions in both periods, 43 (37–52) % during November 2009–September 2011 and 57 (49–62) % during August 2016–May 2018. Asia was also primarily responsible for the emission increase between these two periods, accounting for 86 (59–115) % of the global CFC-11 emission rise between the two periods. Besides eastern mainland China, we find that temperate western Asia and tropical Asia also contributed significantly to global CFC-11 emissions during both periods and likely to the global CFC-11 emission increase between these periods. Besides Asia, the atmospheric observations also provide strong constraints on CFC-11 emissions from North America and Europe, suggesting that each of them accounted for 10–15 % of global CFC-11 emissions during the HIPPO period and smaller fractions in the ATom period. For South America, Africa, and Australia, the derived regional emissions had larger dependence on the prior assumptions of emissions and emission changes, due to a lower sensitivity of the observations considered here to emissions from these regions. However, significant increases in CFC-11 emissions from the southern hemispheric lands were not likely due to the observed increase of north-to-south interhemispheric gradients in atmospheric CFC-11 mole fractions from 2012 to 2017.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".