A CLIMATIC RESPONSIVE URBAN PLANNING MODEL FOR HIGH DENSITY CITY: SINGAPORE'S COMMERCIAL DISTRICT

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1 The 5th International Conference of the International Forum on Urbanism (IFoU) 2011 National University of Singapore, Department of Architecture Global Visions: Risks and Opportunities for the Urban Planet A CLIMATIC RESPONSIVE URBAN PLANNING MODEL FOR HIGH DENSITY CITY: SINGAPORE'S COMMERCIAL DISTRICT N.H. Wong R. Samsudin S.K. Jusuf A. Eliza M. Ignatius Department of Centre for SustainableCentre for Sustainable Department of Department of Building, NUS Singapore Asian Cities, NUS, Singapore Asian Cities, NUS, Singapore Building, NUS Singapore, Building, NUS, Singapore bdgwnh@nus.edu.sg steve.kj@nus.edu.sg sders@nus.edu.sg A @nus.edu.sg A @nus.edu.sg ABSTRACT Local climate condition and urban morphology affect air temperature generated within urban canopy layer, which related to urban heat island (UHI) intensity and later impacts on outdoor thermal comfort and urban energy usage. Climatic responsive urban planning by careful consideration on urban morphology parameters of urban corridor width, building height, urban surface materials, sky view factor (SVF) and vegetation help to improve urban environment quality. This study mainly focuses on commercial district and observes impacts of various urban structures configurations towards air temperature by interpolating climatic and urban morphology predictors. The urban structures indeed show a correlation with the air temperature generated although vegetation also contributes in reducing air temperature through its evapotranspiration process. Therefore, the understanding of relation between urban morphology with thermal performance and UHI benefits in future urban planning and development. KEYWORDS: urban morphology, temperature map, urban heat island (UHI), Singapore's commercial district 1. INTRODUCTION Cities are growing towards megacities with higher density urban planning, narrower urban corridors and more high-rise urban structures. This urban transformation causes daytime and nighttime urban heat island (UHI) which leads to declining of urban environment quality. Earlier studies show strong relation between urban morphology and increasing air temperature within cities centre. Urban structures absorb solar heat during daytime and release it during night-time. Densely built area tends to trap the heat when it is released from urban structures into urban environment, increases urban air temperature compared to surrounding rural areas and causes UHI effect. UHI affects street level

2 Thermal comfort, health, environment quality and may cause increase of urban energy demand. In a built environment at micro-scale, buildings and vegetations influence the incident solar radiation received by urban surface. This is determined by the openness of an urban surface, which is called as sky view factor (SVF) as mentioned by Cleugh in his study [1]. SVF explains the percentage of a point's field of view that is occupied by the sky as opposed to the buildings, trees or any other objects in the landscape. Oke [2] also related both SVF and height-to-width ratio of urban canyon with UHI intensity. The lower SVF value the higher urban air temperature. Geographically, Singapore is located between latitudes 1 09' North and 1 29' South, longitudes ' East and ' East. By its location, Singapore falls within hot humid climate region with characteristics of uniform high temperature, humidity and rainfall throughout the year [3]. Singapore as the most developed country within Southeast Asian region has been experiencing rapid urban development. Commercial district is one of the highly developed areas, which allows higher building site coverage and plot ratio with rows of high-rise buildings for residential and commercial usage to encourage the country's strong economic growth. Current Singapore's urban planning policy for commercial district allows high-rise developments with plot ratio ranging from 5 to more than 11.2 which can be translated to building height ranging from 25 to more than 50 storeys height. A study conducted by Wong [4] observed from the satellite image that UHI in Singapore is seen during daytime with 'hot spots' were identified on commercial districts besides airport and industrial areas. However, 'cool spots' were identified as well on large parks, the landscape in between housing estates and the catchment area. Jusuf et al. [5] studied the relation between land use and ambient temperature as shown in Fig. 1. It is seen that during daytime commercial district experienced lower temperature compared to other land uses. Nevertheless, during night-time, it experienced higher temperature. Figure 1 UHI profile in Singapore (Source: Jusuf et al., 2007)

3 Local climate condition is the existing factor that permanently affecting macro and micro climate condition. Katzschner [6] mentioned that climate is an ever existing factor in a built environment and the study about climate condition is purposed to improve the climate condition and to reduce the negative micro climate effects. Mills [7] proposed that examining the relationship between urban forms and climate can employ the results of urban climatology into urban design guidelines. To improve the urban environment quality and mitigate UHI effect, a climatic map of an urban area is possible to be developed by using Geographic Information System (GIS) platform with analysis on different information layers. Climatic mapping method has become widely used for urban planning from macro to micro level and can be used as reference for future urban planning and development. 2. METHODOLOGY Temperature map for Singapore's commercial district in this study is developed by overlaying layers of urban morphology parameters and predicted Tmax, Tavg and Tmin using GIS platform. Tmax represents maximum temperature during daytime between and Tmin represents minimum temperature during nighttime. Predicted temperature are calculated by interpolating historical climatic parameters of temperature and solar radiation obtained from local weather station with urban morphology predictors of building height, exposed surface area, average albedo and sky view factor (SVF). This study compares the existing urban morphology condition with proposed possible scenarios based on current Singapore's urban planning policy for commercial district. Models of 6 types massing configuration consist of 1 mass, 2 masses, 3 masses, 5 masses, 10 masses and 16 masses are developed and to be observed on 7 sites in commercial district which presently is densely built and have allowable plot ratio more than 11.2 [8], namely site A, B, C, D, E, F and G. By configuring different massing configuration, various building footprints and building heights are achieved. Building footprint determines urban corridor width and horizontal urban density are achieved while building height contributes in sky view factor (SVF). Table 1 and Figure 3 shows the 6 type massing configuration used in this study. Figure 2 Selected 7 sites in commercial district with plot ratio 11.2

4 Table 1 Matrix of different building configurations on each site Figure 3 Scenarios of different building configuration located on 7 sites in Singapore's commercial district Total of 9 measurement points, out of other measurement points allocated within commercial districts, within 50 meter radius buffer are distributed around the selected sites and predicted Tmax, Tavg and Tmin are calculated by using Screening Tool for Estate Environment Evaluation (STEVE) tool as developed by Wong et al. [9]. STEVE tool is a web-based application that is specific for an estate and it calculates Tmax, Tavg and Tmin of a point of interest of an estate based on correlation between climatic and urban morphology predictors by applying equations as shown in Eq. (1), (2) and (3) below. Tmax (oc) = RefTmax (oc) SOLARmax (W/m2) PAVE (%) HBDG WALL (m2) SVF ALB (1) Tavg (oc) = Ref Tavg (oc) E-05 SOLARtotal (W/m2) PAVE (%) GnPR HBDG E-05 WALL (m2) SVF (2)

5 Tmin (oc) = Ref Tmin (oc) PAVE (%) GnPR HBDG E-06 WALL (m2) (3) This study mainly focuses on effect of urban structures towards urban air temperature Therefore, greenery variable is not included in the predicted temperature calculations. Open areas in between buildings blocks are assumed as pavement areas. However, it is confirmed from many earlier studies that greenery contributes greatly in reducing the urban air temperature by the trees shading and vegetations evapotranspiration process. 3. FINDINGS Temperature map of predicted Tmax, Tavg and Tmin for all scenarios show that there are changes on air temperature accordingly by changing the buildings configuration and density. 3.1 Temperature maximum (Tmax) map Figure 4 Tmax temperature map on existing site condition compared with 6 scenarios of urban structures configuration and density 5

6 Temperature map Tmax in Fig. 4 indicates higher temperature for some areas in scenario 1, 2 and 3 compared to scenario 4, 5 and 6. Building configurations in scenario 1, 2 and 3 allow more open spaces and receive more direct solar radiation during day-time thus increase air temperature within urban canopy layer. Building height also contributes in reducing Tmax, benefits from the building shading that falls onto pavement area, as shown in some area that indicate lower temperature in scenario 1, 2 and 3. However, particular areas in scenario 1 still show higher temperature especially in between the buildings which rather far apart. This confirms Oke [2] study on correlation between ratio of building height and urban corridor width with urban air temperature. Building configuration in scenario 4, 5 and 6 results in lower temperature considering effect of shading that falls onto pavement and lower SVF value because of the urban density setting regardless lower building height planned for these scenarios. Predicted Tmax also takes account of exposed surface area therefore lower building may possibly have less exposed surface area. 3.2 Temperature average (Tavg) map Figure 5 Tavg temperature map on existing site condition compared with 6 scenarios of urban structures configuration and density 6

7 Similar scenarios of building configuration are modeled to calculate predicted Tavg. Temperature maps in Fig. 5 above show that scenario 1, 2 and 3 indicate lower air temperature compared to existing condition and the other 3 scenarios and it seems that reduction of building height impacts on the increasing of Tavg as shown in scenario 4, 5 and 6. However, amongst the last 3 building configuration, scenario 4 which has the lowest building density but highest building height indicates the lowest air temperature. Temperature map Tavg also confirms correlation between ratio building height and urban corridor width with SVF value, which affect amount of solar radiation coming into urban area. Solar radiation is one of climatic predictors that determines the level of air temperature generated within urban canopy layer. 3.3 Temperature minimum (Tmin) map Figure 6 Tmin temperature map on existing site condition compared with 6 scenarios of urban structures configuration and density From Fig. 6 above, it can be seen that scenario 1, 2 and 3 with lesser density of building configuration have lower air temperature compared to existing condition, scenario 4, 5 and 6. Sparsely planned urban structures allow heat released from building surface to go 7

8 up and leave urban canopy layer. Inversely, higher density building configurations seem to trap the heat within urban canopy layer and result in higher air temperature which confirms the presence of potential UHI effect. In this study scenario 1, 2 and 3 have the highest building height compared to scenario 4, 5 and 6 therefore scenario 1, 2 and 3 allow more open spaces compared to the other scenarios. However, some areas in scenario 1 seem to have higher air temperature compared to scenario 2 and 3. Scenario 1 proposes single urban structures configuration and therefore the distance between one to other urban structures are rather wide and during day-time the shading falls on the pavement may not be able to cover big portion of pavement area and affects on the amount of solar heat absorbed by urban surface. This related to pavement area thermal characteristics in storing the solar heat that absorbed during day-time. 4. CONCLUSIONS Besides local climate condition, urban morphology predictors affect air temperature generated within urban canopy layer which later impact on UHI intensity. Building density and building height are some urban morphology predictors observed in this study. Urban configuration with lower building density allows more open spaces that potentially increases air temperature during day-time due to the amount of solar radiation coming into urban canopy layer. But sparsely planned buildings helps for the heat that is released from urban surfaces into urban area to go up and leave urban canopy layer. Inversely, densely planned urban area provides more shading and reduce amount of solar heat absorbed thus potentially reduce air temperature during day-time but it traps the heat released during night-time and causes higher air temperature compared to surrounding areas which less densely planned. Combination of lower density urban configuration with higher building height confirms in to reducing air temperature during night-time as it allow more open space and allows the heat that is release into urban area to go up and leave urban canopy layer. Proportionally planned building height and urban corridor width affect in minimizing SVF value and solar heat radiation coming into urban canopy layer which help to lower air temperature during day-time. Figure 7 compiles the differences of Tmax, Tavg and Tmin observed between existing condition on 7 sites in Singapore's commercial district with 6 scenarios of different building configuration proposed. It shows that there is a threshold of optimum density that potentially applied for these sites. In general all building configuration scenarios reduce existing condition air temperature. However, scenario 5 and 6 do not seem to have significant contribution. Therefore, it can be concluded that urban configuration with 1 to 8

9 buildings are effective in reducing UHI effect in the context of sites used in this study. However, this threshold may not be applicable for other sites depending on the site area and allowable plot ratio therefore further detailed study needs to be conducted for other sites in order to observe particular optimum threshold. Figure 7 Average temperature difference on massing configuration scenarios This parametric study confirms that understanding and application of climatic responsive urban planning contributes greatly in improving thermal performance within urban area which in further impacts on outdoor thermal comfort, health, air quality and urban energy usage. Limitation to this study is that vegetation variable and urban wind ventilation are not included thus further detailed study can be conducted for more comprehensive urban thermal performance findings and analysis. REFERENCES [1] Cleugh, H., "Urban Climates" in "Future Climates of The World: A Modelling Perspective", edited by Henderson-Sellers, A., Amsterdam, New York, Elsevier, 1995, pp.488. [2] Oke, T.R., "Boundary Layer Climates", London, Routledge, [3] [4] Wong, N.H., "Study of Rooftop Gardens in Singapore", Singapore, [5] Jusuf, S.K et al., "The Influence of Land Use on The Urban Heat Island in Singapore", Habitat International, Vol. 31 (2007), pp [6] Katzschner, L., "The Urban Climate as A Parameter for Urban Development", Energy and Buildings, Vol. 11 (1988), pp

10 [7] Mills, G., "The Radiative Effects of Building Groups on Single Structures", Energy and Buildings, Vol. 25 (1997), pp [8] [9] Wong, N.H., Jusuf, S.K., Syafii, N.I., Chen, Y., Hajadi, N., Sathyanarayanan, H. and Manickavasagam, Y.V., "Evaluation of The Impact of The Surrounding Urban Morphology on Building Energy Consumption", Solar and Energy, In Press. 10