Multi criteria evaluation of wood pellet utilization in district heating systems
Bibliographic record
Abstract
The hypothesis that this thesis investigates is that “the wood pellet is a competitive primary energy source option for generating district heat in Vancouver, BC”. The competitiveness of the wood pellet as an energy source is evaluated by investigating a major district heating project in Vancouver, BC in which the wood pellet option was compared with natural gas, sewer heat, and geothermal heat. It is observed that in addition to technical and economic factors, environmental and social acceptability criteria play an important role in the selection of the energy source for district heating systems. These include stakeholders’ concerns regarding global warming impacts associated with production and transportation of the wood pellets, as well as particulate matter emissions from wood pellet combustion at the facility. In order to investigate the hypothesis, detailed study of: (a) particle emissions formation and levels, (b) techno-economic performance, and (c) upstream and life-cycle environmental impacts when using wood pellets at the district heating centre, has been carried out. This thesis accepts the hypothesis in that: 1. Particulate emission levels from wood pellet combustion when an electrostatic precipitator flue gas cleaning system is used is below the 18 mg/m³ (20ºC, 101.3 kPa, 8% O₂) regulatory limits in Vancouver, BC, 2. The cost of heat generation (CAD/MWhth) from the wood pellet option (19.08~23.66) is comparable to that of the natural gas option (17.38) and well below those of the heat pump options (26.34~30.71), 3. Based on the upstream environmental impacts of the energy options, a single energy option, which outperforms others when all the impact categories at the same time are considered, cannot be identified. However, it was shown that the impact of upstream production and transportation activities for the wood pellet option does not offset the global warming mitigation advantage of this option. The greenhouse gas equivalent of upstream emissions from the wood pellet option is in the same order of magnitude as the renewable heat pump options, and has remarkably lower (less than 200 kgeq of GHG emissions per MWh of produced district heat) than that of the natural gas option.
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.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".