A model of carbon capture and storage with demonstration of global warming potential and fossil fuel resource use efficiency
Bibliographic record
Abstract
Abstract Increasing greenhouse gas concentration in the atmosphere influences global climate change even though the level of impact is still unclear. Carbon dioxide capture and storage (CCS) is increasingly seen as an important component of broadly based greenhouse gases reduction measures, such as the use of renewable energy sources or nuclear energy. Although the other greenhouse gases are more potent, the sheer volume of CO2 makes it dominant in term of its effect in the atmosphere. The International Energy Agency (IEA) uses 19% of emission reduction requirements as the target for CCS. Although a fossil fuel power plant is a large source of CO2 emissions, with CO2 capture these emissions can be reduced substantially. However, it must be recognized that CO2 capture significantly decreases power plant efficiency; therefore, extra resources (for example, coal in the case of a coal-fired power plant) are needed to compensate for the lost capacity. Extensive application of CO2 capture will require the construction of replacement power plants to compensate for the loss of electricity to the grid. CO−2 transport and storage also contribute to an increase in emissions and waste generation, as well as an increase in energy and other resource consumption..To understand the implications, CCS activities should be studied from a full life cycle perspective. The objectives of this study is to conduct life cycle assessment of combining two energy systems, coal-fired power plant and CO2 EOR, as a new tool to evaluate environmental LCA of CCS with CO2 EOR option. In addition, this is an attractive tool for decision making of any CCS project. Various equations are applied into the GaBi software (a LCA software) to model this tool. Life cycle assessment (LCA) is the primary approach used in this study to create the tool for CCS environmental evaluation. The Boundary Dam Power Station (BDPS) and the Weyburn-Midale CO2 Project in Saskatchewan, Canada, are studied and modified as the case scenarios to find the potential and encourage the appllications of CCS on both energy systems. Energy, using GJ as one of its unit, is considerably the product of this combining two energy resources as one system. The application of this tool effectively demonstrates the result of CCS system as life cycle impact assessment (LCIA) on carbon footprint and resource depletion. Other environmental impacts can, therefore, be analyzed by this tool as well. Three processes; coal mining, power plant including CO2 capture unit operation and crude oil usage, must be presented when the global warming potential (GWP) of CCS is performed. In addition, the result demonstrates the GWP reduction is directly related to fossil fuel resource use efficiency. This means the lower GWP of CCS, the lower efficiency of fossil fuel resource use as well.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".