Toward Positive Energy Districts by Urban–Industrial Energy Exchange
Bibliographic record
Abstract
The concept of Positive Energy Districts (PEDs) has emerged as a promising approach to achieving sustainable urban development. PEDs aim to balance the energy demand and supply within a district while reducing the carbon footprint and promoting renewable energy sources. Urban–Industrial Symbiosis (UIS) is another approach that involves the exchange of energy and resources between industrial processes and nearby urban areas to increase efficiency and reduce waste. Combining the concepts of PED and UIS can create self-sufficient, sustainable, and resilient districts. As the analysis and implementation of such systems are barely studied in North America, this research study was structured to fill the gap by evaluating the financial and environmental advantages of this combination. This study proposes a methodology to design a heat transmission system; then, it is applied to the case of a paper-making factory and a multifunctional heritage building in Montreal, Canada. The results show that the building’s new heating system can generate sufficient heat while emitting near-zero direct emissions. Overall, this paper argues that combining the concepts of PED and UIS can lead to a more sustainable and resilient urban area, and provides a roadmap for achieving this goal.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".