Coal phase out and renewable electricity expansion under Paris targets
Bibliographic record
Abstract
Abstract This paper provides insights into the implications of a global coal phaseout in the power generation sector across different regions under international climate targets. Using modelled scenarios, we highlight the strong rate of decline in new build and decommissioning of existing coal assets, and the growth in renewable capacity to not only fill the gap but meet growing demand for electricity. We find that key uncertainties exist across many of these pathways towards system decarbonisation. We also explore how regionally connected grids can help in transitioning away from coal whilst ensuring supply of electricity. Focusing on potential interconnection between India and the Gulf region, we find that this can be an important strategy for helping enable the transition based on increasing renewables, with regional interconnection encouraging coal phase-out even without a specific coal phase-out target. The technical modelling in this report requires further consideration, in respect of the other multiple benefits of a transition towards low carbon generation, but also the policy mechanisms that will enable delivery of what is a hugely challenging transition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".