An Exploration of how Energy-Related Ecosystem Services Provided by Extensive Green Roofs in Alberta may be Quantified Using Life Cycle Assessment Tools
Bibliographic record
Abstract
This thesis explores ways to assign values to an ecosystem service provided by extensive green roofs: indoor temperature regulation of commercial buildings. The objective is to quantify this service from three perspectives; energy, environmental impacts and cost. A representative green roof, the AEI, is used along with roof evaluation modules. A 0.4 °C indoor temperature increase in winter results in no reduction in heating load. In summer, a 3.3°C indoor temperature decrease results in a cooling load decrease of 5 427.42 kWh (four-storey building) and 12 883 kWh (thirteen-storey building). From an LCC perspective, the AEI's simple payback period exceeds its 20 year lifespan. The NPV and IRR are calculated as highly negative numbers which indicates that the financial cons of the AEI outweigh the pros. In summary, from an indoor energy reduction lens the AEI will not reduce heating loads but will reduce cooling loads.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".