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Economic viability-driven biorefinery site selection for cellulosic biofuel production in Western Canada

2025· article· en· W4408735298 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBiosystems Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of Alberta
FundersFlorida Engineering SocietyCanada First Research Excellence FundChina Scholarship Council
KeywordsBiorefineryCellulosic ethanolBiofuelProduction (economics)Selection (genetic algorithm)Economic analysisSite selectionEngineeringPulp and paper industryNatural resource economicsBusinessBiotechnologyEnvironmental scienceAgricultural economicsWaste managementEconomicsComputer scienceBiologyCellulosePolitical science

Abstract

fetched live from OpenAlex

There is a substantial body of current research on biofuel feedstock assessment and biorefinery site identification. Most of the literature in this field focuses on selecting suitable biorefineries by minimising costs, particularly transportation costs, rather than maximising economic profits. The latest studies on site location have started to introduce financial feasibility as a criterion for site selection. However, there remains a significant gap in the literature regarding the rapidly evolving sector of advanced biofuels like cellulosic biofuels. Addressing this gap, this study innovatively applies a Net Present Value (NPV) framework and a mathematical programming approach, incorporating economic viability, investment support, and carbon credits into the decision-making process for site selection in Western Western Canada. This approach offers insightful revelations regarding economically viable biomass supply and optimal site identification, highlighting the extent of governmental support essential to fostering the growth of the cellulosic biofuel industry. Key findings include: (1) An economic viability-based assessment indicated a substantially lower feedstock supply, about 20 % compared to evaluations based solely on feasible travelling distance; (2) Governmental intervention emerged as a pivotal element influencing the economic viability of cellulosic biofuel refineries; (3) Varied parameters, including production capacity, capital investment subsidies, and maximum transport distance, have significant impacts on economic feasibility and site selection outcomes. The results of this research add to the understanding of current cellulosic biofuel developments. They offer valuable insights into predicting feedstock supply, choosing the best locations for biofuel plants, and designing effective policies. • Novel financial feasibility approach for biorefinery site location identification. • Economic feasibility of biomass supply lower than distance-based estimates. • Government intervention key to biorefinery economic viability. • Varying impacts of production capacity, subsidies and maximum distance analyzed. • Insights offered for biofuel feedstock forecasting and policy design.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.180
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it