Pipeline availability limits on the feasibility of global coal-to-gas switching in the power sector
Bibliographic record
Abstract
Coal-to-gas switching in the power sector, as happened in the US, has been a key driver of near-term greenhouse gas emissions reductions. Can this success be replicated around the world? Here, we explore the limits of a global, plant-level, coal-to-gas transition arising from pipeline availability constraints. Globally, only 43% of coal capacity is within 14 km of a nearby pipeline, the median distance for recent coal-to-gas conversions. Furthermore, plant-to-pipeline distance distributions vary widely – only 30% of coal capacity in India is within 14 km of a nearby pipeline. Most global coal fleets are in the intermediate space of balancing two competing interests – having a young coal fleet with high avoided emissions potential through coal-to-gas switching but without access to low-cost gas resources. A global stocktake based on coal fleet age, pipeline access, and natural gas supply security suggests that a coal-to-gas transition is unlikely to be a universal climate solution.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".