A Climatic Responsive Urban Planning Model

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A Climatic Responsive Urban Planning Model for High Density City: Singapore’s

Commercial District

Wong Nyuk Hien, Steve Kardinal Jusuf, Rosita Samsudin, Anseina Eliza, and Marcel Ignatius Wong Nyuk Hien, Steve Kardinal Jusuf, Rosita Samsudin, Anseina Eliza, and Marcel Ignatius**

Abstract Abstract

Local climate condition and urban morphology affect air temperature generated within urban canopy layer which related to urban 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 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, 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 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 district and observes impacts of various urban structures configurations towards air temperature by interpolating climatic and urban morphology predictors. The urban structures indeed show relation with level of air temperature generated although urban morphology predictors. The urban structures indeed show relation with level of air temperature generated although vegetation also contributes in reducing air temperature through its evapotranspiration process. Therefore the understanding of 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. relation between urban morphology with thermal performance and UHI benefits in future urban planning and development. Keywords:

Keywords: Urban morphology, Temperature map, Urban heat island (UHI), Singapore’s commercial districtUrban morphology, Temperature map, Urban heat island (UHI), Singapore’s commercial district

1. INTRODUCTION

Cities are growing towards megacities with higher density Cities are growing towards megacities with higher density urban planning, narrower urban corridors and more urban planning, narrower urban corridors and more high-rise urban structures. This urban transformation causes rise urban structures. This urban transformation causes day-time and night-time urban heat island (UHI) which day-time and night-time urban heat island (UHI) which leads to declining of urban environment quality. Earlier leads to declining of urban environment quality. Earlier studies show strong relation between urban morphology studies show strong relation between urban morphology and increasing air temperature within cities center. Urban and increasing air temperature within cities center. Urban structures absorb solar heat during day-time and release it structures absorb solar heat during day-time and release it during night-time. Densely built area tends to trap the heat during night-time. Densely built area tends to trap the heat when it is released from urban structures into urban when it is released from urban structures into urban environment, increases urban air temperature compared to environment, increases urban air temperature compared to surrounding rural areas and causes UHI effect. UHI affects surrounding rural areas and causes UHI effect. UHI affects street level thermal comfort, health, environment quality street level thermal comfort, health, environment quality and may cause increase of urban energy demand.

and may cause increase of urban energy demand.

In a built environment at micro-scale, buildings and In a built environment at micro-scale, buildings and vegetation influences the incident solar radiation received vegetation influences the incident solar radiation received by urban surface. This is determined by the openness of an by urban surface. This is determined by the openness of an urban surface which is called as sky view factor (SVF) as urban surface which is called as sky view factor (SVF) as mentioned by Cleugh in his study [1]. SVF explains the mentioned by Cleugh in his study [1]. SVF explains the percentage of a point’s field of view that is occupied by 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 sky as opposed to the buildings, trees or any other objects in the landscape. Oke -1987 [2] also related both SVF and in the landscape. Oke -1987 [2] also related both SVF and height-to-width ratio of urban canyon with UHI intensity. height-to-width ratio of urban canyon with UHI intensity. The lower SVF value the higher urban air temperature. The lower SVF value the higher urban air temperature.

Geographically, Singapore is located between latitudes Geographically, Singapore is located between latitudes 1

1oo09' North and 109' North and 1oo29' South, longitudes 10329' South, longitudes 103oo36' East and36' East and

104 104oo

25' East. By its location, Singapore falls within hot 25' East. By its location, Singapore falls within hot humid climate region with characteristics of uniform high humid climate region with characteristics of uniform high temperature, humidity and rainfall throughout the year [3]. temperature, humidity and rainfall throughout the year [3]. Singapore as the most developed country within Southeast Singapore as the most developed country within Southeast Asian region has been experiencing rapid urban development. Asian region has been experiencing rapid urban development. Commercial district is one of the highly developed areas Commercial district is one of the highly developed areas which allows higher building site coverage and plot ratio which allows higher building site coverage and plot ratio with rows of high-rise buildings for residential and commercial with rows of high-rise buildings for residential and commercial usage to encourage the country's strong economic growth. usage to encourage the country's strong economic growth. Current Singapore’s urban planning policy for commercial Current Singapore’s urban planning policy for commercial district allows high rise developments with plot ratio district allows high rise developments with plot ratio ranging from 5 to more than 11.2 which can be translated ranging from 5 to more than 11.2 which can be translated to building height ranging from 25 to more than 50 storeys to building height ranging from 25 to more than 50 storeys height.

height.

A study conducted by Wong [4] observed from the A study conducted by Wong [4] observed from the satellite image that UHI in Singapore is seen during satellite image that UHI in Singapore is seen during day-time with ‘hot spots’ were identified on commercial districts time with ‘hot spots’ were identified on commercial districts besides airport and industrial areas. However, ‘cool spots’ besides airport and industrial areas. However, ‘cool spots’ were identified as well on large parks, the landscape in were identified as well on large parks, the landscape in between housing estates and the catchment area. Jusut et between housing estates and the catchment area. Jusut et al. [5] studied the relation between land use and ambient al. [5] studied the relation between land use and ambient temperature as shown in Fig.1. It is seen that during temperature as shown in Fig.1. It is seen that during day-time commercial district experienced lower temperature time commercial district experienced lower temperature compared to other land uses. But during night-time, it compared to other land uses. But during night-time, it experienced higher temperature.

experienced higher temperature.

Local climate condition is the existing factor that Local climate condition is the existing factor that permanently affecting macro and micro climate condition. permanently affecting macro and micro climate condition. Katzschner [6] mentioned that climate is an ever existing Katzschner [6] mentioned that climate is an ever existing factor in a built environment and the study about climate factor in a built environment and the study about climate condition is purposed to improve the climate condition and condition is purposed to improve the climate condition and to reduce the negative micro climate effects. Mills [7] to reduce the negative micro climate effects. Mills [7] proposed that examining the relationship between urban proposed that examining the relationship between urban forms and climate can employ the results of urban climatology forms and climate can employ the results of urban climatology *

*Corresponding author.Corresponding author.

E

E-mail address: [email protected] address: [email protected] Article history Article history Received November 4, 2011 Received November 4, 2011 Accepted December 23, 2011 Accepted December 23, 2011

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into urban design guidelines. into urban design guidelines.

To improve the urban environment quality and mitigate To improve the urban environment quality and mitigate UHI effect, a climatic map of an urban area is possible to UHI effect, a climatic map of an urban area is possible to be developed by using Geographic Information System be developed by using Geographic Information System (GIS) platform with analysis on different information layers. (GIS) platform with analysis on different information layers. Climatic mapping method has become widely used for Climatic mapping method has become widely used for

urban planning from macro to micro level and can be used urban planning from macro to micro level and can be used as reference for future urban planning and development. as reference for future urban planning and development. The objective of this study is to see how different design The objective of this study is to see how different design options can be explored on developing a block within a options can be explored on developing a block within a highly dense urban area, along with their impact on the highly dense urban area, along with their impact on the related urban microclimatic condition (in this case, urban related urban microclimatic condition (in this case, urban temperature on pedestrian level). The design options variation temperature on pedestrian level). The design options variation are limited on varying building massing and building physical are limited on varying building massing and building physical dimension accordingly, within the same plot ratio control. dimension accordingly, within the same plot ratio control.

2. SCREENING TOOL FOR ESTATE

ENVI-RONMENT EVALUATION (STEVE TOOL)

RONMENT EVALUATION (STEVE TOOL)

STEVE has been developed based on the air temperature STEVE has been developed based on the air temperature prediction models. These prediction models were based on prediction models. These prediction models were based on the empirical data collected over a period of close to 3 the empirical data collected over a period of close to 3 years as part of the development of an assessment method years as part of the development of an assessment method to evaluate the impact of estate development, which includes to evaluate the impact of estate development, which includes the assessment method of existing greenery condition [8] the assessment method of existing greenery condition [8] and greenery condition for a proposed master plan in an and greenery condition for a proposed master plan in an estate development [9].

estate development [9].

In the development of the empirical model, air temperature In the development of the empirical model, air temperature data that has been gathered in the previous studies were data that has been gathered in the previous studies were combined with the most recent data, which includes combined with the most recent data, which includes estate-wide and canyon types of m

wide and canyon types of measurements. The measurementeasurements. The measurement points cover various types of land uses, including residential, points cover various types of land uses, including residential, commercial, business park, education, industrial, park, open commercial, business park, education, industrial, park, open space and sport facility.

space and sport facility. Daily minimum (

Daily minimum (TminTmin), average (), average (Tavg Tavg ) and maximum) and maximum ((TmaxTmax) temperature of each point of measurements were) temperature of each point of measurements were calculated as the dependent variable of the air temperature calculated as the dependent variable of the air temperature prediction model. The independent variables for the models prediction model. The independent variables for the models

can be categorized into: can be categorized into:

Climate predictors:

Climate predictors: daily minimum (Ref Tmin), averagedaily minimum (Ref Tmin), average (Ref Tavg) and maximum (Ref Tmax) temperature

(Ref Tavg) and maximum (Ref Tmax) temperature at referenceat reference point;

point; average of daily solar radiationaverage of daily solar radiation (SOLAR). For the(SOLAR). For the SOLAR predictor, average of daily solar radiation total SOLAR predictor, average of daily solar radiation total (SOLARtotal) was used in Tavg models, while average of (SOLARtotal) was used in Tavg models, while average of solar radiation maximum of the day (SOLARmax) was used solar radiation maximum of the day (SOLARmax) was used in the Tmax model. SOLAR predictor is not applicable for in the Tmax model. SOLAR predictor is not applicable for Tmin model. These data are obtained from the weather Tmin model. These data are obtained from the weather station.

station.

Urban morphology predictors:

Urban morphology predictors: percentage of pavement percentage of pavement area over R 50m surface

area over R 50m surface area (PAVE),area (PAVE), average height toaverage height to building area ratio

building area ratio (HBDG),(HBDG), total wall surface areatotal wall surface area (WALL),(WALL), Nyuk Hien Wong

Nyuk Hien Wongis Associate Professor in the Department of Building,is Associate Professor in the Department of Building, National University of Singapore. His area of expertise and research interests National University of Singapore. His area of expertise and research interests includes urban heat island, urban greenery, thermal comfort in the tropics includes urban heat island, urban greenery, thermal comfort in the tropics and building energy simulation. He is the

and building energy simulation. He is the principal investigator of a numberprincipal investigator of a number of research projects in collaboration with the various government agencies of research projects in collaboration with the various government agencies in Singapore. Prof. Wong has published more than

in Singapore. Prof. Wong has published more than 150 international referred150 international referred journal and conference papers and was

journal and conference papers and was the co-authors of 3 books on rthe co-authors of 3 books on r ooftopooftop and urban greenery and has been invited to deliver keynote papers and and urban greenery and has been invited to deliver keynote papers and research findings in various conferences and symposiums. He has also been research findings in various conferences and symposiums. He has also been invited to serve in the various advisory committees both locally and invited to serve in the various advisory committees both locally and internationally.

internationally.

Steve Kardinal Jusuf

Steve Kardinal Jusuf has a Ph.D. degree in Building Science from thehas a Ph.D. degree in Building Science from the Department of Building, National University of Singapore. Currently he is a Department of Building, National University of Singapore. Currently he is a Research Fellow at Centre for Sustainable Asian Cities, NUS. His research Research Fellow at Centre for Sustainable Asian Cities, NUS. His research interests include urban microclimate and urban climatic mapping with interests include urban microclimate and urban climatic mapping with Geographical Information Systems. He has worked in a number of research Geographical Information Systems. He has worked in a number of research projects with various Singapore government agencies, mainly on urban projects with various Singapore government agencies, mainly on urban

climatic mapping for sustainable urban

climatic mapping for sustainable urban development.development. Rosita Samsudin

Rosita Samsudin is Research Assistant at Centre for Sustainable Asianis Research Assistant at Centre for Sustainable Asian Cities, NUS. She is architect in practice and holds master degree in building Cities, NUS. She is architect in practice and holds master degree in building science from Department of Building, NUS. Her research interests include science from Department of Building, NUS. Her research interests include urban heat island, urban climatic mapping, outdoor thermal comfort, urban heat island, urban climatic mapping, outdoor thermal comfort, sustainable building and urban

sustainable building and urban development.development. Anseina Eliza

Anseina Elizais a Master Graduate in Building Science at Department of is a Master Graduate in Building Science at Department of Building, National University of Singapore. Topic of this paper embarks Building, National University of Singapore. Topic of this paper embarks from her Independent Study research, with Dr. Wong Nyuk Hien as her from her Independent Study research, with Dr. Wong Nyuk Hien as her supervisor, which highlights the building morphology and density effect on supervisor, which highlights the building morphology and density effect on urban temperature. Currently, she is working at

urban temperature. Currently, she is working at green building consultant.green building consultant. Marcel Ignatius

Marcel Ignatiusis currently a PhD candidate at Department of Building,is currently a PhD candidate at Department of Building, National University of Singapore,

National University of Singapore, under Prof. Wong Nyuk Hien supervision.under Prof. Wong Nyuk Hien supervision. The focus of his research is mostly on urban climatic mapping and temperature The focus of his research is mostly on urban climatic mapping and temperature model for urban morphology in Singapore. He was a research assistant in model for urban morphology in Singapore. He was a research assistant in Centre of Sustainable Asian Cities (CSAC) at NUS in

Centre of Sustainable Asian Cities (CSAC) at NUS in 2009, and he has done2009, and he has done his Master Degree in Building Science from the

his Master Degree in Building Science from the same university in 2008.same university in 2008.

Fig.1

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Green Plot Ratio

Green Plot Ratio (GnPR),(GnPR), sky view factorsky view factor (SVF) and(SVF) and average surface albedo (ALB). These data are provided by average surface albedo (ALB). These data are provided by the government agency and cross-checked by field survey. the government agency and cross-checked by field survey. Before the model was developed, the radius of influence Before the model was developed, the radius of influence area was determined. A radius of 50 meter was deemed as area was determined. A radius of 50 meter was deemed as a suitable one after a series of influence area study by a suitable one after a series of influence area study by compari

comparing rang radius vdius value alue from 2from 255 –– 100100 m (see m (see Fig.2). Fig.2). TheThe temperature models were then developed by examining the temperature models were then developed by examining the variables regression coefficient values and

variables regression coefficient values and their correlationstheir correlations with the dependent variables.

with the dependent variables.

Wind speed, one of the most common variables, was Wind speed, one of the most common variables, was excluded in the model development, since the

excluded in the model development, since the models focusmodels focus on calm day condition

on calm day conditions (wind speed < 3s (wind speed < 3 m/s). Meanm/s). Meanwhilewhile for another common variable, altitude was excluded from for another common variable, altitude was excluded from the model development since the data collected showed the model development since the data collected showed altitude has a very little influence on air temperature altitude has a very little influence on air temperature condition.

condition.

In the first stage of model development, trend analysis was In the first stage of model development, trend analysis was done to identify and discuss the behaviour of the models’ done to identify and discuss the behaviour of the models’ variables (based on the data collected on field measurement), variables (based on the data collected on field measurement),

by examining the variables’ regression coefficient values by examining the variables’ regression coefficient values and their correlations with the dependent variable. Not all and their correlations with the dependent variable. Not all of the independent variables are significant. However, it is of the independent variables are significant. However, it is important to analyze how these

important to analyze how these variables behave in determiningvariables behave in determining the air temperature. The next stage is to develop the air the air temperature. The next stage is to develop the air temperature prediction models that use only the significant temperature prediction models that use only the significant variables.

variables.

The air temperature regression models were developed The air temperature regression models were developed based on the data collected over a period of close to 3 based on the data collected over a period of close to 3 years. It is necessary to validate the models with another years. It is necessary to validate the models with another period of measurement data, which in this case, with fairly period of measurement data, which in this case, with fairly

clear and calm day conditions (wind speed < 3 m/s). clear and calm day conditions (wind speed < 3 m/s).

The air temperature prediction models can be written as The air temperature prediction models can be written as follows:

follows:

T

Tminmin((ooC)C)== 44.0.06611 ++ 0.0.838399 Ref T Ref T minmin((

o o C

C)) ++ 00.0.00404 PAVE PAVE (%)(%) –

– 0.0.191933 GnPRGnPR – – 0.0.020299 HBDG HBDG ++ 1.339E1.339E-06 W-06 WALL (mALL (m22))

T

Tavgavg ((ooC)C)== 2.2.343477 ++ 0.0.909044 Ref T Ref T avg avg ((

o o

C)

C) ++ 5.5.78786E6E-0-055 SOLAR

SOLARtotal total (W/m(W/m

2 2

)) ++ 00..000077 PAVE PAVE ((%)%) –– 0.0.0606 GnPRGnPR – – 0.015

0.015 HBDG HBDG ++ 1.31.31111E-0E-055 WALLWALL (m(m22

)) ++ 00..663333 SVF SVF Fig.2

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T

T_max_max((ooC)C)== 7.7.545422 ++ 0.0.686844 Ref T Ref T maxmax((

o o

C)

C) ++ 0.0.00003 S3 SOLAROLARmaxmax

(W/m

(W/m22)) ++ 00..000055 PAVE PAVE (%(%)) –– 00.0.01616 HBDG HBDG ++ 6.76.777E77E-06-06 WALL

WALL (m(m22)) ++ 11..446677 SVF SVF ++ 1.1.464666 ALB ALB

Since it is impossible to put the all the theoretical Since it is impossible to put the all the theoretical background and prediction model development into this background and prediction model development into this paper, the author will only underline the essential elements paper, the author will only underline the essential elements of the STEVE tool, while a more detailed explanation and of the STEVE tool, while a more detailed explanation and data validation can be read from the related paper, which data validation can be read from the related paper, which can be found in [8-11].

can be found in [8-11].

3. METHODOLOGY

Temperature map for Singapore’s commercial district in Temperature map for Singapore’s commercial district in this study is developed by overlaying layers of urban this study is developed by overlaying layers of urban morphology parameters and predicted

morphology parameters and predicted T T maxmax,, T T avg avg andand T T minmin

using GIS platform.

using GIS platform. T T maxmax represents maximum temperaturerepresents maximum temperature

during daytime between and

during daytime between and T T minmin represents minimumrepresents minimum

temperature during night-time. Predicted temperature are temperature during night-time. Predicted temperature are calculated by interpolating historical climatic parameters of calculated by interpolating historical climatic parameters of temperature and solar radiation obtained from local weather temperature and solar radiation obtained from local weather station with urban morphology predictors of building station with urban morphology predictors of building height, exposed surface area, average albedo and sky view height, exposed surface area, average albedo and sky view factor (SVF). This study compares the existing urban factor (SVF). This study compares the existing urban morphology condition with proposed possible scenarios morphology condition with proposed possible scenarios based on current Singapore’s urban planning policy for based on current Singapore’s urban planning policy for commercial district.

commercial district.

Models of 6 types massing configuration consist of 1 mass, Models of 6 types massing configuration consist of 1 mass, 2 masses, 3 masses, 5 masses, 10 masses and 16 masses are 2 masses, 3 masses, 5 masses, 10 masses and 16 masses are developed and to be observed on 7 blocks in commercial developed and to be observed on 7 blocks in commercial district which presently is densely built and have allowable district which presently is densely built and have allowable plot ratio more than 11.2 [12], namely block A, B, C, D, E, plot ratio more than 11.2 [12], namely block A, B, C, D, E, F and G. By configuring different massing configuration, F and G. By configuring different massing configuration, various building footprints and building heights are various building footprints and building heights are achieved. Building footprint determines urban corridor achieved. Building footprint determines urban corridor width and horizontal urban density are achieved while width and horizontal urban density are achieved while building height contributes in sky view factor (SVF). Table 1 building height contributes in sky view factor (SVF). Table 1 and Fig.3 shows the 6 type massing configuration used in and Fig.3 shows the 6 type massing configuration used in this study.

this study.

Total of 9 measurement points, out of other measurement Total of 9 measurement points, out of other measurement points allocated within commercial districts, within 50 meter points allocated within commercial districts, within 50 meter radius buffer are distributed around the selected blocks and radius buffer are distributed around the selected blocks and

predicted

predicted T T maxmax,, T T avg avg andand T T minminare calculated by STEVE tool.are calculated by STEVE tool.

This study mainly focuses on effect of urban structures This study mainly focuses on effect of urban structures towards urban air temperature therefore greenery variable towards urban air temperature therefore greenery variable Table 1.

Table 1. Matrix of different building configurations on each blockMatrix of different building configurations on each block

LOCATION LOCATION BLOCK BLOCK AREA AREA (m (m22₎₎ PLOT PLOT RATIO RATIO GF GFAA (m (m22)) MASSING MASSING 1 1 22 33 55 1100 1166 HEIGHT (STOREYS) HEIGHT (STOREYS) 8 80 0 880 0 880 0 336 6 224 4 2244 FOOTPRINT FOR 1 MASSING (m

FOOTPRINT FOR 1 MASSING (m22₎₎

B BLLOOCCK K A A 115566000 0 1111..2 2 17174477220 0 22118844..000 0 11009922..000 0 772288..000 0 997700..667 7 772288..000 0 445555..0000 B BLLOOCCK K B B 9911880 0 1111..2 2 11002288116 6 11228855..220 0 664422..660 0 442288..440 0 557711..220 0 442288..440 0 226677..7755 B BLLOOCCK K C C 8811990 0 1111..2 2 991177228 8 11114466..660 0 575733..330 0 338822..220 0 550099..660 0 338822..220 0 223388..8888 B BLLOOCCK K D D 8877775 5 1111..2 2 998822880 0 11222288..550 0 616144..225 5 440099..550 0 554466..000 0 440099..550 0 225555..9944 B BLLOOCCK K E E 112299220 0 1111..2 2 11444477004 4 11880088..880 0 990044..440 0 660022..993 3 880033..991 1 660022..993 3 337766..8833 B BLLOOCCK K F F 5555550 0 1111..2 2 662211660 0 777777..000 0 383888..550 0 225599..000 0 334455..333 3 225599..000 0 116611..8888 B BLLOOCCK K G G 5555550 0 1111..2 2 662211660 0 777777..000 0 383888..550 0 225599..000 0 334455..333 3 225599..000 0 116611..8888 Fig.3

Fig.3 Selected 7 blocks in commercial district with plot ratio 11.2Selected 7 blocks in commercial district with plot ratio 11.2

Fig.4

Fig.4 Types of different building configuration located on 7 blocksTypes of different building configuration located on 7 blocks in Singapore’s commercial district

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is not included in the predicted temperature calculations. is not included in the predicted temperature calculations. The open areas in between buildings blocks are assumed as The open areas in between buildings blocks are assumed as pavement areas. However it is confirmed from many earlier pavement areas. However it is confirmed from many earlier studies that greenery contributes greatly in reducing the studies that greenery contributes greatly in reducing the urban air temperature by the trees shading and vegetation urban air temperature by the trees shading and vegetation evapotranspiration process.

evapotranspiration process.

4. FINDINGS

Temperature map of predicted

Temperature map of predicted T T maxmax,, T T avg avg andand T T minmin for allfor all

scenarios show that there are changes on air temperature scenarios show that there are changes on air temperature accordingly by changing the buildings configuration and accordingly by changing the buildings configuration and density.

density.

4.1 Temperature maximum (

4.1 Temperature maximum (T T max max ) map) map

Temperature map

Temperature map T T maxmaxin Fig.5 indicates higher temperaturein Fig.5 indicates higher temperature

for some areas in type 1, 2 and 3 compared to type 4, 5 and for some areas in type 1, 2 and 3 compared to type 4, 5 and 6. Building configurations in type 1, 2 and 3 allow more 6. Building configurations in type 1, 2 and 3 allow more

open spaces and receive more direct solar radiation during open spaces and receive more direct solar radiation during day-time thus increase air temperature within urban canopy day-time thus increase air temperature within urban canopy layer. Building height also contributes in reducing layer. Building height also contributes in reducing T T maxmax,,

benefits from the building shading that falls onto pavement benefits from the building shading that falls onto pavement area, as shown in some area which indicate lower temperature area, as shown in some area which indicate lower temperature in type 1, 2 and 3. However, particular areas in type 1 still in type 1, 2 and 3. However, particular areas in type 1 still show higher temperature especially in between the buildings show higher temperature especially in between the buildings which rather far apart. This confirms Oke’s study [2] on which rather far apart. This confirms Oke’s study [2] on correlation between ratio of building height and urban correlation between ratio of building height and urban corridor width with urban air temperature.

corridor width with urban air temperature.

Building configuration in type 4, 5 and 6 results in lower Building configuration in type 4, 5 and 6 results in lower temperature considering effect of shading that falls onto temperature considering effect of shading that falls onto pavement and lower SVF value because of the urban pavement and lower SVF value because of the urban density setting regardless lower building height planned for density setting regardless lower building height planned for these types. Predicted

these types. Predicted T T maxmax also takes account of exposedalso takes account of exposed

surface area therefore lower building may possibly have surface area therefore lower building may possibly have less exposed surface area.

less exposed surface area.

Fig.5

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4.2 Temperature average (

4.2 Temperature average (T T avg avg ) map) map

Similar types of building configuration are modeled to Similar types of building configuration are modeled to calculate predicted

calculate predicted T T avg avg . Temperature maps in Fig.6 show. Temperature maps in Fig.6 show

that type 1, 2 and 3 indicate lower air temperature compared that type 1, 2 and 3 indicate lower air temperature compared to existing condition and the other 3 types and it seems that to existing condition and the other 3 types and it seems that reduction of building height impacts on the increasing of reduction of building height impacts on the increasing of T

T avg avg as shown in type 4, 5 and 6. However, amongst the lastas shown in type 4, 5 and 6. However, amongst the last

3 building configurations, type 4 which has the lowest 3 building configurations, type 4 which has the lowest building density but highest building height indicates the building density but highest building height indicates the lowest air temperature.

lowest air temperature. Temperature map

Temperature map T T avg avg also confirms correlation betweenalso confirms correlation between

ratio building height and urban corridor width with SVF ratio building height and urban corridor width with SVF value which affect amount of solar radiation coming into value which affect amount of solar radiation coming into urban area. Solar radiation is one of climatic predictors that urban area. Solar radiation is one of climatic predictors that determine the level of air temperature generated within determine the level of air temperature generated within urban canopy layer.

urban canopy layer.

4.3 Temperature minimum (

4.3 Temperature minimum (T T minmin) map) map

From Fig.7, it can be seen that type 1, 2 and 3 with lesser From Fig.7, it can be seen that type 1, 2 and 3 with lesser density of building configuration have lower air temperature density of building configuration have lower air temperature compared to existing condition, type 4, 5 and 6. Sparsely compared to existing condition, type 4, 5 and 6. Sparsely planned urban structures allow heat released from building planned urban structures allow heat released from building surface to go up and leave urban canopy layer. Inversely, surface to go up and leave urban canopy layer. Inversely, higher density building configurations seem to trap the higher density building configurations seem to trap the heat within urban canopy layer and result in higher air heat within urban canopy layer and result in higher air temperature which confirms the presence of potential UHI temperature which confirms the presence of potential UHI effect. In this study type 1, 2 and 3 have the highest building effect. In this study type 1, 2 and 3 have the highest building height compared to type 4, 5 and 6 therefore type 1, 2 and height compared to type 4, 5 and 6 therefore type 1, 2 and 3 allow more open spaces compared to the other types. 3 allow more open spaces compared to the other types.

5. CONCLUSIONS

Besides local climate condition, urban morphology Besides local climate condition, urban morphology predictors affect air temperature generated within urban predictors affect air temperature generated within urban canopy layer which later impact on UHI intensity. Building canopy layer which later impact on UHI intensity. Building

Fig.6

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density and building height are some urban morphology density and building height are some urban morphology predictors observed in this study.

predictors observed in this study.

Urban configuration with lower building density allows Urban configuration with lower building density allows more open spaces that potentially increases air temperature more open spaces that potentially increases air temperature during day-time due to the amount of solar radiation during day-time due to the amount of solar radiation coming into urban canopy layer. But a sparsely planned coming into urban canopy layer. But a sparsely planned building helps for the heat that is released from urban building helps for the heat that is released from urban surfaces into urban area to go up and leave urban canopy surfaces into urban area to go up and leave urban canopy layer. Inversely, densely planned urban area provides more layer. Inversely, densely planned urban area provides more shading and reduce amount of solar heat absorbed thus shading and reduce amount of solar heat absorbed thus potentially reduce air temperature during day-time but it potentially reduce air temperature during day-time but it traps the heat released during night-time and causes higher traps the heat released during night-time and causes higher air temperature compared to surrounding areas which less air temperature compared to surrounding areas which less densely planned.

densely planned.

Combination of lower density urban configuration with Combination of lower density urban configuration with higher building height confirms in to reducing air temperature higher building height confirms in to reducing air temperature

during night-time as it allow more open space and allows during night-time as it allow more open space and allows the heat that is release into urban area to go up and leave the heat that is release into urban area to go up and leave urban canopy layer. Proportionally planned building height urban canopy layer. Proportionally planned building height and urban corridor width affect in minimizing SVF value and urban corridor width affect in minimizing SVF value and solar heat radiation coming into urban canopy layer and solar heat radiation coming into urban canopy layer which help to lower air temperature during day-time. which help to lower air temperature during day-time.

Figure 7 compiles the differences of

Figure 7 compiles the differences of T T maxmax,, T T avg avg andand T T minmin

observed between existing condition on 7 blocks in observed between existing condition on 7 blocks in Singapore’s commercial district with 6 types of different Singapore’s commercial district with 6 types of different building configuration proposed. It shows that there is a building configuration proposed. It shows that there is a threshold of optimum density that potentially applied for threshold of optimum density that potentially applied for these blocks. In general all building configuration types these blocks. In general all building configuration types reduce existing condition air temperature. However, type 5 reduce existing condition air temperature. However, type 5 and 6 do not

and 6 do not seem to have significant contribution. Therefore,seem to have significant contribution. Therefore, it can be concluded that urban configuration with 1 to 5 it can be concluded that urban configuration with 1 to 5 buildings are effective in reducing UHI effect in the context buildings are effective in reducing UHI effect in the context Fig.7

(8)

of blocks used in this study. However, this threshold may of blocks used in this study. However, this threshold may not be applicable for other blocks depending on the ground not be applicable for other blocks depending on the ground area and allowable plot ratio therefore further detailed area and allowable plot ratio therefore further detailed study needs to be conducted for other blocks in order to study needs to be conducted for other blocks in order to observe particular optimum threshold.

observe particular optimum threshold.

This parametric study confirms that understanding and This parametric study confirms that understanding and application of climatic responsive urban planning contributes application of climatic responsive urban planning contributes greatly in improving thermal performance within urban greatly in improving thermal performance within urban area which in further impacts on outdoor thermal comfort, area which in further impacts on outdoor thermal comfort, health, air quality and urban energy usage.

health, air quality and urban energy usage.

Limitation to this study is that vegetation variable and Limitation to this study is that vegetation variable and urban wind ventilation are not

urban wind ventilation are not included thus further detailedincluded thus further detailed study can be conducted for more comprehensive urban study can be conducted for more comprehensive urban thermal performance findings and analysis.

thermal performance findings and analysis.

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Fig.8 Average temperature difference on massing configuration Average temperature difference on massing configuration types