Economic Evaluation of the Production of Perennial Crops for Energy Purposes—A Review
Bibliographic record
Abstract
Biomass is widely used for the production of renewable energy, which calls for an economic evaluation of its generation. The aim of the present work was to review the literature concerning the economic evaluation of the production of perennial crop biomass for energy use. Statistical analysis of the bibliographic data was carried out, as well as an assessment of methods and values of economic indicators of the production of perennial crops for bioenergy. Most of the papers selected for the review were published in the years 2015–2019, which was probably stimulated by the growing interest in sustainable development, particularly after 2015, when the United Nations declared 17 sustainable development goals. The earliest articles concerned the economic analysis of plantations of short rotation coppice; the subsequent ones included the analysis of feedstock production in terms of the net present value and policy. The latest references also investigated transport and sustainability issues. The crops most commonly selected for production cost analysis were willow, poplar, and Miscanthus. The cost of production of willow and poplar were similar, 503 EUR ha−1 year−1 and 557 EUR ha−1 year−1, respectively, while the cost of Miscanthus production was significantly higher, 909 EUR ha−1 year−1 on average. By analogy, the distribution of revenue was similar for willow and poplar, at 236 EUR ha−1 year−1 and 181 EUR ha−1 year−1; Miscanthus production reached the value of 404 EUR ha−1 year−1. The economic conditions of perennial crop production differed in terms of geography; four areas were identified: Canada, the USA, southern Europe, and central and northern Europe.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".