Global temperature goals should determine the time horizons for greenhouse gas emission metrics
Bibliographic record
Abstract
Abstract Emission metrics, a crucial tool in setting effective exchange rates between greenhouse gases, currently require an arbitrary choice of time horizon. Here, we propose a novel framework to calculate the time horizon that aligns with scenarios achieving a specific temperature goal. We analyze the Intergovernmental Panel on Climate Change Special Report on Global Warming of 1.5 °C Scenario Database to find that time horizons aligning with the 1.5 °C and 2 °C global warming goals of the Paris Agreement are 24 [90% prediction interval: 7, 41] and 58 [90% PI: 41, 74] years, respectively. We then use these time horizons to quantify time-dependent emission metrics for methane. We find that the Global Warming Potential (GWP) values that align with the 1.5 °C and 2 °C goals are GWP 1.5 °C = 75 [90% PI: 54, 107] and GWP 2 °C = 42 [90% PI: 35, 54]. For the Global Temperature change Potential (GTP) they are GTP 1.5 °C = 41 [90% PI: 16, 102] and GTP 2 °C = 9 [90% PI: 7, 16]. The most commonly used time horizon, 100 years, underestimates methane’s GWP and GTP by 34% and 38%, respectively, relative to the values we calculate that align with the 2 °C goal and by 63% and 87%, respectively, relative to the 1.5 °C goal. To best align emission metrics with the Paris Agreement 1.5 °C goal, we recommend a 24 year time horizon, using 2045 as the endpoint time, with its associated GWP 1.5 °C = 75 and GTP 1.5 °C = 41.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".