1374 Detailed Evaluation of Thermal Comfort in Urban Environments: A 3D numerical model for Standard Effective Temperature

Wednesday, 25 January 2017
4E (Washington State Convention Center )
Tiffany Sin, Yale-NUS, Singapore, Singapore; and N. Nazarian, J. Kleissl, and L. K. Norford

Outdoor spaces are important elements of urban environments as they accommodate a wide range of human activities. Therefore, in order to obtain high quality of life in a city, careful attention should be given to pedestrian experiences in outdoor spaces, considering the ease of access and use, sense of community, and aesthetic aspects. With the current rise in the air temperature of urban areas, it is also crucial that the thermal sensation of urban dwellers, i.e. thermal comfort, is considered in outdoor urban design. However, obtaining an accurate prediction and measurement of thermal comfort is difficult: thermal comfort is highly subjective.  An individual’s experience of the thermal environment depends on his/her physiology and state, and thermal comfort also depends on the combined effect of various parameters (such as air temperature, humidity, radiant exposure, wind speed, metabolic rates, and clothing levels).  Consequently, to date predictions of the spatial variation of thermal comfort in urban environments are lacking.  

To address this shortcoming, we develop a stand-alone software for Standard Effective Temperature as a metric of thermal comfort. This model can be combined with other urban energy balance and/or CFD models that calculate the distribution of surface temperature and  flow field properties in the street canyon, and returns the spatial distribution of SET at any height. The three-dimensional SET model is built upon the work by Nazarian et al. 2016c [1] which considers the detailed radiation balance (shortwave and longwave radiation from the sun, sky and urban surfaces) on the pedestrian at any point and calculates the mean radiant temperature (Tmrt) at high resolution. In the Tmrt calculation scheme, geometry-dependent properties such as shading effects, sky view factor, and wall visibility are calculated using envuo (Environment for Urban Optimization), which is an open-source Python environment for analyzing urban areas and optimizing urban design. While the previous model [1] relied on the solar ray-tracing algorithm from ANSYS Fluent, the updated model uses the freely available package PVLib by Sandia Labs to calculate shortwave radiation intensities, and further calculates the shading distribution in the street canyon. Additionally, we enhance model flexibility to accept complex urban geometry as opposed to the idealized configuration of building arrays previously considered by Nazarian et al. 2016c [1], and evaluate the ease of application in combination with the City Energy Analyst (CEA) tool [2] for a test case. Accordingly, the model will be applicable to more realistic scenarios and can act as a stand-alone add-on to a wide range of microscale urban models. Furthermore, we aim to consider the variation of humidity and the effect of vegetation on thermal comfort in the development of the model.

The importance of this model lies in its interdisciplinary and impactful approach: evaluation of thermal comfort in various design scenarios enables design to be done with the consideration of microclimate, and creates a collaborative environment across the fields of climatology, architecture, and urban planning which ultimately lead to the development of livable and sustainable cities for the future.  


[1] Nazarian, N., Fan, J., Sin, T. Norford. L., & Kleissl., J.  “Predicting Outdoor Thermal Comfort in Urban Environments: A New Numerical Model for Standard Effective Temperature”, submitted to Urban Climate  (2016c).

[2] Fonseca, J. A., Nguyen, T. A., Schlueter, A., & Marechal, F. “City Energy Analyst (CEA): Integrated framework for analysis and optimization of building energy systems in neighborhoods and city districts.” Energy and Buildings, 113, (2016): 202-226.

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