CO2 Emissions and Economy of Co-Firing Carbonized Wood Pellets at Coal-Fired Power Plants: The Case of Overseas Production of Pellets and Use in Japan
Bibliographic record
Abstract
CO2 emissions reduction from coal-fired power plants is an urgent issue in Japan, as well as around the world. The purpose of this study is to estimate the CO2 emissions and economy of using carbonized wood pellets produced overseas and co-fired at coal-fired power plants in Japan. We examined carbonized wood pellets produced in Canada and Vietnam, since those countries are major exporters of wood pellets for Japan. The results obtained are as follows: (1) The CO2 emissions and calculated cost per calorific value of carbonized wood pellets (CP25), which have a fixed carbon content of 25 wt.%, are lower than those of wood pellets at the port of import in Japan. When the fixed carbon of carbonized biomass is controlled at 25 wt.% or more via a carbonizer, sufficient pyrolysis gas (the heat source used for drying and carbonization without auxiliary fuel) can be obtained. (2) Carbonized wood pellets manufactured in Vietnam are more economical than those manufactured in Canada, since the resource of wood is less expensive and the transportation distance is shorter from Vietnam compared to Canada. (3) When carbonized wood pellets at CP25 are co-fired in coal-fired power plants, they do not affect the cost of the electricity generated, even if the carbonized pellets are blended at a high ratio.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".