International Supply of Solid and Liquid Biomass - Importance of Transportation in Costs and Greenhouse Gas Emissions
Bibliographic record
Abstract
In globalized commodity markets, the orientation of the economy towards bio-economy and the energy transition to renewables, biomass is gaining importance as raw material and energy source. The regional gap between demand and supply is currently overcome by global biomass trade flows as shown for agricultural products and for wood fuels. Due to the increasing demand of biomass for energy and biofuels, these trade flows will expand in the future. A comprehensive model was developed to evaluate these supply chains for biomass on industrial scale and gain a detailed understanding of its related costs and GHG emissions (± ILUC). It consists of sub-models, such agricultural or forestry production, preconditioning and processing, road, rail and water transportation, transshipment and storage. The model was applied to six exemplary biomass production and supply paths with the target destination in Central Europe (Germany) – namely ethanol from Brazil, wheat and wood pellets from Canada, soybeans from the USA, palm oil from Indonesia and round wood from Russia. This represents the broad variety of biomass sources, supply regions and transportation distances of 6,200 to 17,900 kilometers.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".