Measuring green roof performance, a solution to sustainable urban development in the UAE
Bibliographic record
Abstract
The urban environment in the UAE is classifi ed as hot and humid. During the summer months, humidity is high when compared with the winter months. Solutions for sustainable development are of high priority in the region to meet the goals of the UAE Vision and meet notable recommendations at the World Future Energy Summit (WFES) held in the UAE, January 2013. In order to achieve a balanced environment, help mitigate climate change and demonstrate a means of achieving a temperature reduction as recommended by Conference of Parties (COP) 18 held in Qatar, November 2012, a study on measuring the performance of green roof to reduce climatic temperatures in the UAE has been undertaken in the urban Dubai Marina development. Plant and air exchanges have been measured using ENVI-met micro-climatic simulation software. From previous research fi ndings, parameters such as Surface Albedo (SA), Mean Radiant Temperature (MRT) and Relative Humidity (RH) were instrumental in measuring green roof performance and effectiveness towards sustainable development. This research explores the impact of green roof on sustainable development given two different periods of the year, the summer solstice, June 21st and the winter solstice, December 21st. A simulation conducted during the two periods on ENVI-met investigates the following parameters, SA, MRT, RH, Predicted Mean Vote (PMV) and Wind Speed. Evidence suggest gains in using green roofs to entice city authorities and relevant decision makers of the value added benefi ts of green roofs in sustainable urban development, to meet temperature reduction standards, mitigate heat islands and enhance the built environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".