CO2 equivalent as indispensable metric for determining dangerous climate change and its mitigation, which is to peak emissions by 2025, from IPCC AR
Bibliographic record
Abstract
This shows how the all-important climate indicator is CO2 equivalent (CO2e) for atmospheric greenhouse gas concentrations (GHG) and global emissions for mitgation. CO2e is provided annually by NOAA’s Greenhouse Gas Index. In 2003, it was 463 ppm, whereas the 2023 CO2e was 534 ppm—a 15% increase in 20 years. CO2e is the essential metric to use, according to the science and policy. As it is a driver of global warming, we propose at a minimum atmospheric CO2e with global warming as guiding metric. Though largely unrecognized, the 1992 UN climate change convention has atmospheric greenhouse gases, not global warming, as the metric, to assess danger and guide mitigation. Global warming alone is a poor metric. Unlike global warming, CO2e is a smooth increase, and it indicates future risks and impacts. Atmospheric CO2e is a climate change driver, and it is record high and increasing rapidly. Global warming was 1.45°C for 2023 and is now 1.55°C (2024). To 2023 its increase rate is unprecedented, from Forster. That is a threat to our future, reinforced by record high increasing atmospheric CO2e. That said, the single simplest and most certain guide to mitigation would be an IPCC direction on best mitigation, which the sixth assessment (2021-2022) does provide. It is the rapid decline of global emissions from a 2025 peak at the latest, by immediate action, for 2°C as well as 1.5C. IPCC AR6 has this as CO2e emissions which makes CO2e emissions an essential metric, not only CO2. Including the trend of drivers in policy reinforces the extreme climate emergency and the imperative for imediate action to peak emissions by 2025. Imperative of immediate action is shown by the record 2024 temperature increase even higher than the big 2023 record. Atmospheric CO2 and CO2e increase jumped faster from 2015, now increasing faster than ever. The carbon budget is being relied on as policy guide, but as the IPCC AR6 says there are “several types of carbon budgets” that “ultimately represent subjective choices”. Atmospheric CO2e is objective and with certainty, and as driver of temperature increase it more than carbon budgets. Atmospheric CO2e can resolve the question of global warming acceleration and the 1.5°C limit definition. Another driver included in NOAA’s GHG Index is GHG radiative forcing. As over 90% of our greenhouse gas emissions goes into the ocean, accelerating ocean heat content is guide. Earth energy imbalance is a reliable guide and has doubled over the past 15 years. All these indicators are record high increasing as fast or faster than ever. Our future depends on scientists calling loudly for CO2e emissions to peak in 2025, referencing IPCC AR6.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".