Atmospheric abundance and global emissions of perfluorocarbons CF <sub>4</sub> , C <sub>2</sub> F <sub>6</sub> and C <sub>3</sub> F <sub>8</sub> since 1900 inferred from ice core, firn, air archive and in situ measurements
Bibliographic record
Abstract
Abstract. Perfluorocarbons (PFCs) are very potent and long-lived greenhouse gases in the atmosphere, released predominantly during aluminium production and semiconductor manufacture. They have been targeted for emission controls under the United Nations Framework Convention on Climate Change. Here we present the first continuous records of the atmospheric abundance and global emissions of CF4 (PFC-14), C2F6 (PFC-116) and C3F8 (PFC-218) from 1900 to 2014. The records are derived from high precision measurements of PFCs in air extracted from polar firn or ice at six sites (DE08, DE08-2, DSSW20K, EDML, NEEM and South Pole) and air archive tanks and atmospheric air sampled from both hemispheres. We take proper account of the age characteristics of the firn and ice core air samples and demonstrate excellent consistency between the ice core, firn and atmospheric measurements. In addition to an inversion for global emissions from 1900 to 2014, we also formulate the inversion to directly infer emission factors for PFC emissions due to aluminium production prior to the 1980s. We show that the late-Holocene pre-industrial level was 34.05 ± 0.33 ppt for CF4, and below detection limits of 0.002 ppt and 0.01 ppt for C2F6 and C3F8, respectively. We find a significant peak in CF4 and C2F6 emissions around 1940, most likely due to the high demand for aluminium during World War II, for example for construction of aircraft. The PFC emission factors for aluminium production in the early twentieth century were significantly higher than today, but have decreased since then due to improvements and better control of the smelting process. We see a temporary reduction of around 15 % in CF4 emissions in 2009, presumably associated with the impact of the Global Financial Crisis on aluminium and semiconductor production.
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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) | 0.002 | 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".