A worldwide analysis of stranded fossil fuel assets’ impact on power plants’ CO2 emissions
Bibliographic record
Abstract
Will power plants emit less or more CO2 in anticipation of stronger climate policies that would strand fossil fuel reserves? Here, using a worldwide data source on individual power plants’ CO2 emissions and the value of countries’ at-risk fossil fuel assets, we show that between 2009 and 2018, plants emitted more CO2 in countries where more assets would be devalued under a 1.5 °C scenario, which we theorize is due to these countries’ regulatory leniency and plants’ vested interest in long-term fossil fuel contracts. Although the extra amount of carbon emitted each year trigged by imperiled assets is relatively small, it would exhaust a sizable portion of the electricity sector’s remaining carbon budget when added up over time. This is especially true in the U.S. and Russia where up to 16% and 12% of their budgets, respectively, could be spent within ten years due solely to the stranded asset effect. Since the signing of the Paris Agreement, power plants have emitted more CO2 in countries where more fossil fuel assets would be stranded under this treaty. In the United States, 16% of its electricity sector’s carbon budget could be spent within ten years due solely to the stranded asset effect.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".