World Energy Outlook 2014 projections to 2040: natural gas and coal trade, and the role of China
Bibliographic record
Abstract
The paper presents data and results from the World Energy Outlook ( WEO ) 2014, published by the International Energy Agency ( IEA ). Over the period to 2040, total energy use is projected to grow by almost 40 per cent, while the share of fossil fuels in the energy mix falls. Nonetheless, these fossil fuels remain the dominant sources of energy, with oil, coal and gas each accounting for around one quarter of global energy needs by 2040. Increasingly, modern renewables are projected to replace fossil fuels, especially in the power sector. Around 93 per cent of the projected increased primary energy demand comes from non‐ OECD countries, with two‐thirds coming from developing Asia, led by China. By 2025, China could account for almost a quarter of global energy use, doubling its share since the turn of the century. After 2025, India and other Asian countries surpass China as the main centres of energy demand growth. The IEA 's WEO 2014 concludes that even taking into account ambitious policy measures announced as of mid to late 2014, energy growth projections place the world on a path consistent with a long‐term temperature increase of 3.6 degrees. Urgent action is required if the world's energy systems are to be steered towards lower greenhouse gas emissions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".