A multilayer mean radiant temperature model for pedestrians in a street canyon with trees
We introduce a multilayer model to estimate mean radiant temperature (MRT) and evaluate the pedestrian thermal comfort in a street canyon. This multilayer MRT model (MMRT) is suitable for urban streets with varying building and tree heights. The model simulates shortwave and longwave radiation excha...
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Veröffentlicht in: | Building and environment 2018-08, Vol.141, p.298-309 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We introduce a multilayer model to estimate mean radiant temperature (MRT) and evaluate the pedestrian thermal comfort in a street canyon. This multilayer MRT model (MMRT) is suitable for urban streets with varying building and tree heights. The model simulates shortwave and longwave radiation exchange for each urban element and area-weighted view factors, then finally obtains MRT of pedestrians on the sidewalk. Probability density profiles of buildings and trees enable the consideration of urban vertical heterogeneity. Furthermore, Monte Carlo ray tracing (MCRT) allows the model to evaluate the radiation transfer in complex urban areas. We verify the effectiveness of MCRT and the probabilistic density profile approach. A sensitivity test conducted in Seoul on September 1, 2017 using the MMRT reveals that MRT can be reduced by 23 °C as the tree leaf area density increases from 0 to 1, and by 18 °C as the tree height increases from 0 m to 12 m in 1300 LST. The model controls urban form and pavement parameters as well as tree parameters. We aim to use this model to compare diverse MRT mitigation strategies and confirm the best strategy for thermal-friendly street design.
•MMRT model is an effective tool to estimate MRT of pedestrians in a street canyon.•Monte Carlo ray tracing method and probability density profile variables help the MMRT model evaluate MRT in the street with complex vertical geometry.•Street trees create shading effect and reduce MRT by diminishing shortwave radiation from the sky. |
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ISSN: | 0360-1323 1873-684X |
DOI: | 10.1016/j.buildenv.2018.05.058 |