Increasing Solar Reflectivity of Building Envelope Materials to Mitigate Urban Heat Islands: State-of-the-Art Review
Bibliographic record
Abstract
The Urban Heat Island (UHI), a consequence of urban development, leads to elevated temperatures within cities compared to their rural counterparts. This phenomenon results from factors such as urban designs, anthropogenic heat emissions, and materials that absorb and retain solar radiation in the built environment. Materials commonly used in cities, like concrete, asphalt, and stone, capture solar energy and subsequently emit it as heat into the surroundings. Consequently, this phenomenon amplifies summertime cooling energy demands in buildings. To mitigate the UHI impacts, various mitigation strategies have emerged that include but are not limited to using higher solar reflectivity materials, known as “cool materials”, and increasing vegetation and greenery in urban areas. Cool materials have high reflectivity and emissivity, effectively reflecting solar radiation while emitting absorbed heat through radiative cooling. Increasing the solar reflectivity of building envelope materials is a promising sustainable solution to lessen the UHI effects. This state-of-the-art review summarizes the UHI causes and effects, states the mitigation strategies, describes the cool building envelope materials, explains the solar reflectivity index measurements, indicates the building and micro-climate simulations, highlights the performance evaluation of using cool building envelope materials, points out the research gaps, and proposes future research 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".