Biomass Gasification as a Viable Alternative for Small-scaled Combined Heat and Power Technologies in Remote Communities in Canada
Bibliographic record
Abstract
Abstract The use of forest biomass could drastically reduce the environmental impacts of fossil fuel usage for heat and power in remote communities and can provide new opportunities for employment, retaining money inside communities. Here, we present the techno-economic feasibility of alternative gasification technologies for CHP uses in three remote off-grid communities in Canada. The analysis includes different scenarios of fuel price and operation costs, as well as two different feedstocks, wood pellets and wood chips. The results show potential for successful implementation, subject to planning on the specific conditions and location of the community. Power generation costs vary widely depending on the available biomass price, utilization of heat as well the power output of the system, ranging from about 0.25 CAD/kWh to over 1.20 CAD/kW. Economic support for biomass or removal of diesel subsidies would have a significant impact on biomass CHP implementations. The feasibility of the investigated systems is not dependent on the economics or technology itself but (i) availability of quality feedstock, (ii) utilization of heat for additional revenue generation, (iii) the utilization of the systems, (iv) community-driven bioeconomy alternatives and (v) carbon credit opportunities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".