Evaluation of Miscanthus Gasification and Oxy-Combustion Carbon Dioxide Removal Potential with Carbon Capture Towards Implementation of Bioenergy with Carbon Capture and Storage in England
Bibliographic record
Abstract
Abstract Bioenergy with Carbon Capture and Storage (BECCS) pathways and supply chain designs are researched broadly and implemented for scenarios as of the IEA's (2021) Net Zero by 2050 report. The Committee on Climate Change (2018a, 2018b) has identified Miscanthus as one biomass type to achieve its negative emission goals and aligned one third of 1.2 million hectares under high level and one third of 0.7 million hectares under medium level of ambition (multi-functional land use) for the cultivation of Miscanthus for BECCS in the UK. In this study the input of 39 t/hr of Miscanthus x giganteus biomass as well as Energy technologies institutes (2015) information on projected distributed BECCS installations in the UK for BECCS were considered to bring up different gasifying agent options for H2 generation through Miscanthus Gasification with pre combustion carbon capture and one configuration for oxy-combustion with post combustion carbon capture for highly efficient power generation. Process simulations with Aspen software were conducted to determine power yields and carbon capture rates of optimized bioenergy with carbon capture value chains, sensitivity analysis were executed in order to optimize the configurations. The aim of the study was to observe how highest achievable power generation efficiencies of H2 generation through gasification of Miscanthus x giganetus compare with oxy-combustion power generation efficiency and how the different pathways influence the carbon capture efficiency. The aim was to inform BECCS implementation decisions with optimum possible H2 and power generation yields as well as their respective carbon capture potential. It was found that under oxygen, air and steam as gasifying agents steam is most effective for H2 generation with 3.1 t/hr of H2 produced under a input of 39 t/hr of Miscanthus input, which generates 35,6 MW of power in a simulated H2 turbine. Under simulation assumptions it captures thereby 55,2 t/hr of CO2 with a carbon capture rate of 99%. Oxy-combustion is more efficient than the gasification pathways in regard of power generation, which is 100,4 MW with CO2 capture of 36,6 t/hr with an carbon capture efficiency of 73,8 %. Concluding oxy-combustion is preferred, if highly efficient power generation is wanted and lower carbon capture rate is accepted thereby. When H2 generation is preferred, steam gasification should be chosen as highest efficient gasification pathway. The exact numbers of power generation as well as carbon capture can be used now to estimate UKs overall power generation as well as carbon capture potential of Miscanthus x giganteus cultivation under different land use scenarios considering land use change effects and biodiversity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".