With the increasing urbanization, studies have shown that the Urban Heat Island (UHI) Intensity in many cities has increased drastically. This issue is becoming even more critical because of the imminent effect of Climate Change. Many cities are experiencing extreme heatwaves more frequently. It is essential that more research should be conducted to understand the impact of UHI and also to examine the relationship between UHI and Climate Change. Possible mitigation solutions should be researched and tested to study the effectiveness of these solutions.
Though research on UHI has a very long history, the research has been conducted primarily in the temperate regions. As such, the key factors affecting UHI could be significantly different from that in the tropical regions. For example, studies carried out in the tropical regions show that during the daytime, the shading provided by the neighboring buildings could reduce the heat built up in the urban canyon. As such, smaller Sky View Factor (SVF) could be more beneficial during the daytime. On the other hand, most studies carried out in the temperate regions tend to suggest that a larger SVF is better for minimizing UHI effect. However, even in the tropical regions, it is essential to design the urban canyon in such a way that during the daytime, shading from the neighboring buildings could provide shade to minimize the heat built up but it must be done in such a way that it will not prevent the release of heat from the urban canyon to the atmosphere during the nighttime. Proper provision must be made to ensure sufficient ventilation to ensure outdoor thermal comfort and heat extraction through advection. Thus more research should be conducted in the tropical regions to understand the optimal SVF for minimizing the UHI effect. Furthermore, the urban morphology of cities also plays a crucial role in affecting UHI. The urban morphology factors affecting UHI in high rise and high density cities could be significantly different from that of the low rise and low density cities.
In order to better understanding the UHI effect, advances in UHI modeling should be pursued. Currently most of the studies tend to focus on district level where some form of steady state CFD simulations are conducted to understand the microclimate of the tested area. The information that could be derived from such studies is very limited and they provide only an instance of the situation. However, in real situations, the UHI effect could be highly dynamic and the magnitude and locations of the hot spots will change over time on a diurnal basis. There are also many other limitations of CFD simulations. For example, most CFD simulations focus on studying the pressure driven wind condition based on prevailing wind profiles. In cities where land and sea breezes play a pivotal role in the urban ventilation, this effect could not be modeled effectively. Currently most of the CFD simulations are carried out based on iso-thermal condition. This is because it is extremely difficult to consider the thermal effect such as the solar radiation as well as the anthropogenic heat due to traffic and waste heat from HVAC system. It is also difficult to model the shading and evapo-transpiration process of vegetation in CFD simulations. Another approach is to use Urban Canopy model which is derived based on the solar heat exchange and the convection heat transfer within the urban canopy. However, this approach is usually based on simplified urban canyon geometry and thus has the limitation in modeling the more realistic geometrical configurations of urban canyon. The main limitation of this model is that, it can only predict the temperature profile of the urban canyon at a fixed height though research has been conducted to develop the multi-layer urban canopy model that is capable of predicting the temperature profile at different heights. Research has also been conducted to couple the urban canopy model with energy simulation model so that the impact of the immediate urban conditions on the energy consumption of a building could be studied. The waste heat from the HVAC system which is an output from the energy simulation model could also be considered in the urban canopy model. Another approach is to derive the predictive function statistically by utilizing the data collected from a specific city/region. This approach has the advantage of integrating the predictive function with the modeling tools such as GIS or common CAD tool like Sketch-up. However, the usage of such tool could be fairly limited since the predictive capability may work only in city/region where the predictive function is developed or in regions with similar climatic condition and urban morphology.
The more recent development has been to utilize the climate model and attempt to downscale the model to understand the microclimate at the urban level. This poses tremendous challenge in the modeling approach since most climate models are designed to consider resolution in the range of 100 km or more. This resolution would not be sufficient for understanding the microclimate within the urban areas. Furthermore, the information required for the modeling at the different scales or levels of resolution is drastically different. At the regional level, the information required is more “coarse” and general. However, such data is usually transboundary and therefore not easily available. Some forms of gross estimation are usually required. On the other hand, at the urban level, very detailed and specific information is required. Beside the detailed information on the exact locations and massing of the buildings, the general layout of the vegetation and types, road and pavement etc. should be available for such modeling. Currently research is on-going to bridge this gap so that a more effective and realistic nested simulations could be conducted to utilize these climate models to predict the urban microclimate. In order to overcome this downscaling issue, another approach is to utilize the climate model for simulations of the climatic condition at a regional level and the results can serve to provide the essential boundary conditions to be used by an urban canopy model or CFD model. However, such approach has the limitations of simplification of the data obtained from the climate model in order to fulfill the boundary condition requirements for the urban canopy model or CFD model.
Though many researches have been conducted to understand the various mitigation measures or solutions for UHI, it is essential to understand that the effectiveness of such solutions may vary depending on the climatic conditions as well as the urban morphology of the urban areas. For example, cool roof materials that have been very effective in mitigating UHI in Europe and US may have limitations in the application for high rise high density cities such as Singapore or Hong Kong. The roofs of such high rise buildings usually cover a very small portion of the total surface area of the façade. Such roofs are usually service roofs which are used for placement of services such as water tanks, air conditioning pipes etc. The roofs are also subjected to heavy human traffic and thus the wear and tear of such coatings should be considered. Furthermore, the application of such reflective coatings for external walls or façade requires careful consideration. The highly reflective coating may result in glare issues for the neighboring buildings and the downward reflection of the solar heat may result in the accumulation of the reflected heat in the urban canyon. Interestingly, there are now retroreflective products in the market that could reflect the solar radiation in the upward manner. The products could be in the form of coatings or films applied to the external walls or fenestrations of the façade. Increasing installation of green roofs and green walls could be seen in many parts of the world. Such installations could enhance the architectural esthetic of the buildings as well as to reduce the heat gain into the buildings and to a minimal extend, reduce the ambient air temperature at the immediate vicinity of the installations. However, such installations usually require high installation, operation and maintenance costs specifically for green walls. The placements of the green walls should also be carried out strategically so that the shading effect of the green walls could be maximized to reduce the solar heat gain into the buildings. Otherwise, such installations can purely serve for esthetic purpose. Planting of trees or vegetation at the ground level should also be well planned to integrate with the urban structures. In the tropical regions, the shading of trees has been proven to be very effective and therefore such shading should be well utilized. However, due to the high temperature, very often the cooling effect of trees could be reduced because of the stomata suppression of the leaves to conserve moisture. The utilization of water bodies for evaporative cooling may not be effective in tropical regions because of the high humidity of air. However, recently there are products such as dry mist or misting fans that utilize the ultra-fine water droplets to enhance evaporation. Such products require further research and testing to ensure the effectiveness of such solutions.
It is hoped that in times to come, we are able to witness good progress in the development of an integrated modeling approach that seamlessly integrates the climate model, urban model and building model. Such integration will enhance the understanding of the impact of regional development or Climate Change on the urban condition. The impact of urban condition on the indoor environment such as the cooling energy consumption of the buildings, thermal comfort, air quality, daylighting etc. could also be examined. Furthermore, such integration would also be enhanced by modeling the application of the various mitigation measures either at the urban level or building level. This vision is not too far-fetched since good development is in process to effectively integrate GIS model with BIM model. With the advances in sensing technologies through the use of smart sensing and data analytics, it is also hoped that the data collection for environmental sensing could be enhanced and serve to provide a better feedback and validation for the modeling approaches. Work is also in progress to utilize UAVs or drones to carry out three dimensional environmental sensing. This will serve to provide a better understanding of the three dimensional profile of the environmental conditions in the urban setting. Through the effective integration of the modeling, mitigation solutions and environmental sensing approaches, it is foreseeable that in the immediate future, we are able to see good advances in the UHI research.