Kivihiilellä tuotetun sähkön rooli Pariisin 2015 ilmastosopimuksen jälkeen
Bibliographic record
Abstract
Coal-fired electricity generation is still a major, increasing source of the global greenhouse gas (GHG) emissions accounting for approximately one-fifth of the total GHG emissions. Concurrently, in order to meet the Paris Agreement target to limit global warming “well below 2°C” - which calls for reduction of the global GHG emissions as soon as possible - nations worldwide are pursuing to limit GHG emissions from, inter alia, energy sector. Therefore, the pressure to replace coal with less carbon-intensive fuels is increasing. This thesis observes the role – past, current and future - of coal-fired electricity generation in three developed countries that have had long traditions in coal production and consumption; i.e. the United States of America (USA), Canada and the United Kingdom (UK). The policy framework and market conditions are reviewed to understand the position of coal in national electricity generation mixes. Additionally, future projections are provided based on national energy outlooks and policy announcements. Each observed nation has or is about to implement ambitious targets to reduce GHG emissions from the electricity sector, thus also limiting coal’s share in their generation mixes - if not today, at least in the future. For instance, the United Kingdom (UK) and Canada have both recently implemented carbon dioxide (CO2) emission performance standards on coal-fired generating units, ensuring that new coal-fired capacity will not be built without partial carbon capture and storage (CCS) system. The US Environmental Protection Agency has also finalized the rule on fossil fuel-fired generating units in 2015, referred to as the Clean Power Plan (CPP). This plan has been, however, halted by the Supreme Court in early 2016 for at least two years before its final decision on the rule. In addition to direct regulations on the CO2, there are other factors driving nations towards less carbon intensive generation mixes. Most notably, market conditions and competition between generation fuels are encouraging shift from coal to natural gas (NG)-fired electricity generation in particular. That is, NG market prices have been historically low during 2010s, particularly in the USA and Canada, due to the shale gas boom which started in the 2000s. Also tightened limits on hazardous air pollutants such as NOx and SO2 emissions are encouraging early retirements of coal-fired units. Furthermore, decreased competitiveness of coal as a generation fuel has weakened its future prospects. For instance, in order to meet the carbon intensity of a modern NG-fired power plant, a coal-fired unit would need to have at least partial, c. 50%, CCS. Available technologies are still, however, rather expensive and operations have not yet been proven reliable enough on a large scale compared to the widely used NG-fired technologies. While CCS projects may receive additional funding by selling by-products from the CO2 capture process, they are still reliant on government support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.170 |
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; both teacher heads agree on what is shown here.
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".