The thermal effects of city greens on surroundings under the tropical climate

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1 September 2004 Page 1 of 6 The thermal effects of city greens on surroundings under the tropical climate Wong Nyuk Hien 1 and Chen Yu 2 1,2 Department of Building, National University of Singapore, Singapore ABSTRACT: In Singapore, rapid population influx has led to demands for converting natural areas to pubic housing. The heat island in Singapore city has been documented. However, less attention has been placed on the cooling effect of city s green areas. To address this issue, temperature and humidity measurements were made in two big city green areas. One is the city s natural reserve - Bukit Batok Nature Park (36 ha) and the other is a neighbourhood park - Clementi Woods (12 ha). The measurements were conducted at both vegetated areas and their surroundings. The results indicated the cooling effects of city greens are remarkable not only on vegetated areas but surrounding built environments. To further explore the role of the green area on moderating the microclimate, two simulation programmes, TAS and Envi-met, were employed respectively for the two parks. The aims are to explore the patterns of energy consumptions of a typical commercial building near to Bukit Batok Nature Park and different thermal conditions with and without Clementi Woods. Conference Topic: 4 Energy and urban planning Keywords: thermal effect, city greens, surroundings, tropical climate 1. INTRODUCTION The Urban Heat Island (UHI) effect is primarily triggered by dense built environment (replacement of the natural landscape) as well as anthropogenic heat in cities. One of the possible measures to mitigate UHI is to reintroduce plants into the built environment. The direct benefit is that the temperature around the green area is lower than that within the dense built environment. A single tree can already moderate the climate well. But its impacts are limited to the microclimate [1]. On the other hand, large urban parks can extend the positive effects to the surrounding built environment. The role of green areas in moderating the urban climate has been explored all over the world during recent years. The studies can be roughly divided into three categories. Firstly, meteorological data and satellite images were employed to study the effect of green areas in cities at macro level. Saito [2] studied the relationship between meteorological elements and green distribution in Kumamoto City in Japan and concluded that the air temperature distribution was closed related to the distribution of greenery in the city. Kavashima [3] examined the effects of vegetation density on the surface temperatures in the urban and suburban areas of Tokyo Metropolis and observed lower surface temperature in green areas. Secondly, some in-depth field measurements were carried out to explore the cooling effect of green areas at micro-level. Jauregui [1] found that in a large urban park (Chapultepec Park) in Mexico City, the ambient temperature was 2-3 C lower than its surrounding built-up area and its influence reached a distance of 2km, about the same as its width. Sonne et al. [5] conducted measurement over a one year period at three Melbourne, Florida sites and found that temperature measured in a forested natural park was consistently lower than that measured in a residential development with an extensive tall trees canopy while the temperature measured in this residential development with extensive planting was always lower than that measured in a residential development with very few trees. Finally, some numerical calculation was built up to predict the thermal benefits of green areas in cities. Avissar [6] studied the potential impact of vegetation on the urban thermal environment by use of a mesoscale atmospheric model. Honjo et al. [7] estimated the cooling effect of green areas on their surroundings through a numerical model. In Singapore, rapid population influx has led to demands for converting natural areas to pubic housing. There is a clear link between the loss of natural landscape and the emerging of UHI effect [8]. To prevent the exaggeration of UHI effect, reservation of existing urban parks is significant. In order to explore thermal impacts of large city greens on surroundings under the tropical climate, two field measurements were carried out in Bukit Batok Nature Park and Clementi Woods Park in Singapore. Some detailed information of above two parks is provided in Table 1. Table 1: Comparison of two parks - Bukit Batok Nature Park and Clementi Woods Park.

2 September 2004 Page 2 of 6 Size Location Shape Blocks Bukit Batok Nature Park (BBNP) 36 ha Located in the center of Singapore Clementi Woods Park (CWP) 12 ha Located in the western part of Singapore Kent Vale 2. METHODOLOGY 2.1 Field measurement The field measurements in BBNP and CWP were conducted during the periods of 11 th January to 5 th February 2003 and 16 th June to 1 st July 2003 respectively. Hobo Temperature/RH mini-dataloggers were employed to measure the ambient air temperature and relative humidity on site. Every Hobo datalogger was housed by a wooden box with ventilation holes and they were secured at the height of 2m on lamp posts or trees nearby (see Figure 1). Figure 1: Hobo data logger was housed in the measuring box and they were secured on the lamp post nearby. In BBNK, five measuring points were selected within while another five points were chosen in-between the surrounding residential blocks (see Figure 2). All measuring points were lined up with interval of around 100m. In CWP, seven measuring points were placed evenly within the narrow strip of while the rest five points were arranged inbetween blocks and Kent vale (see Figure 2). Besides using Hobo data loggers, LAI analyser and weather station were also used to measure LAIs and weather data in CWP. Clementi Woods Parks Figure 2: the measuring points in BBNP (upper) and CWP (lower). 2.2 Tas simulation To explore the pattern of energy consumption of a typical commercial building near to BBNK, a simulation programme - Tas, was employed. Tas is a suite of software products, which simulate the dynamic thermal performance of buildings and their systems [9]. The main applications are in assessment of environmental performance, prediction of energy consumption, plant sizing, analysis of energy conservation options and energy targeting. A typical 8-storey commercial building was built with 3d-Tas (see figure 3). Some general assumptions were made in terms of internal condition of the building. They are: Air-con is on from 0800 to 1800 hr Temperature ranges from 22.5 to 25.5 C Relative humidity is less than 70% Lighting gain 15w/m 2 Occupancy sensible and latent gain 15w/m 2 Equipment sensible gain 20w/m 2 Bukit Batok Nature Park Figure 3: 3d model of the commercial building blocks A clear day, 27 th Jan was selected. The cooling load of the commercial building was calculated when it was placed inside, 100m, 200m, 300m, and 400m away from respectively. Ambient air temperatures and RH in the original weather file

3 September 2004 Page 3 of 6 were also replaced by corresponding temperatures and RH measured on site at different locations. 2.3 Envi-met simulation A free three-dimensional non hydrostatic model, Envi-met [10], was employed to compare the thermal conditions with and without CWP. ENVI-met can simulate the Surface-Plants-Air interactions in the context of urban environments. Three scenarios were assumed as shown in Figure 4. LEFT 1 WOODS (a) 2 Kent Vale SDE (b) were compared (see Figure 5). Within BBNP, it could be found that most average temperatures were relatively lower than those measured in blocks. From locations 1 to 4, the average temperatures range from 25.2 to 25.5 o C. For location 5, the average temperature is slightly higher since it is located at the edge of BBNP. Furthermore, the location is near to the car park and the highway. The anthropogenic heat generated by vehicles may probably influence the readings. There is an orderly elevation of average temperatures for locations within the surrounding blocks. It indicates that has cooling impact on surroundings but it is limited to the distance. The highest average temperature was observed at location 9. It is 1.3 o C higher than the average temperature obtained at location 6 which is the nearest location to BBNP. Location 10 has lower average temperature compared with locations 9. It is because the location is at the edge of the dense neighborhoods. The impact from buildings on location 10 may not be as much as that on locations within the blocks. Another interesting difference between and surrounding blocks are their standard deviation. These standard deviation obtained in range from 1.8 to 2.1 (locations 1 to 4) while they range from 2.0 to 3.2 (locations 5 to 10) in the built environment. It indicates the extensive plants may have better ability to stabilize the fluctuation of ambient air temperature. Figure 6 shows the comparison of average relative humidity obtained at different locations. Inversely, average relative humidity obtained in BBNP are higher than those got from surrounding flats. All average relative humidity obtained from BBNK are over 90%. (c) Figure 4: three scenarios: (a) retaining CWP; (b) removing vegetation but keeping soil; (c) replacing with buildings. A clear sunny day is chosen to carry out the simulation. Based on data derived from the field measurement, Table 2 shows some basic settings employed in all the simulations. Averagre air temperature (Degree C) BBNP Blocks Figure 5: The comparison of average air temperatures measured at different locations in BBNP (11 th Jan to 5 th Feb 2003) Table 2: some basic settings employed Tem (K) Wind speed at 10m (m/s) Wind direction RH (%) Roughness length in 10m 3. FINDINGS AND DISCUSSIONS Total sim. time (hrs) S to N Field measurements To explore the cooling effect of BBNP, the average temperatures obtained at different locations Average RH (%) BBNP Locaitons

4 September 2004 Page 4 of 6 Figure 6: The comparison of average RH measured at different locations in BBNP (11 th Jan to 5 th Feb 2003). The measurement in BBNP has been carried out over a period of 26 days. The lower temperatures were observed within BBNP where there are dense trees. They can be defined as cooling source in this case. To find out the correlation between cooling source and locations away form it, a correlation analysis has been done (see Figure 7). Location 3 has been defined as reference point since it has lower average temperature and lowest standard deviation over a period of 26 days. Temperature measured at location 6 (Degree C) Temperature measured at location 9 (Degree C) y = x R 2 = Temperature measured at location 3 (Degree C) y = x R 2 = Temperature measured at location 3 (Degree C) Figure 7: Correlation analysis of locations 3, 5 and locations 3, 9 (11 th Jan to 5 th Feb 2003). The elevation of ambient temperatures can be observed at locations in terms of gradient. 3 and 6 has relatively smaller gradients. It indicates the temperature difference between them is not much. But for locations 3 and 9, the gradients become much larger which means higher temperature difference was experienced. It accords with previous observations derived from a clear day. The field measurement conducted in CWP also shown clear difference between planted area and the surroundings. The comparisons of average temperatures calculated over a period from 16 th June to 1 st July 2003 were presented in Figure 8 and 9. It could be found that the lowest average temperature, 25.7 o C, was experienced at location 1 while the average temperatures ranged from 27.2 to 27.5 o C at the rest locations within CWP. This can be explained by the arrangement of plants within CWP. The southern part (around location 1) of CWP is a piece of primary forest (see Figure 10). The LAI readings measured around are 7.11 and 7.23 which means the primary forest is very dense. Therefore, both shading and evaporative cooling effects may be very high. The rest of CWP is planted with trees that are not that extensive (see Figure 10). The measured LAIs range from 2.21 to The fluctuation of average temperatures of these locations is minimum. The truth is that the ambient temperature has strong correlation with the density, or more accurately, LAIs of plants. This is the reason why the difference of average temperatures between location 1 and the rest locations in CWP is from 1.5 to 1.8 o C. Average temperature (Degree C) CWP blocks Figure 8: Comparison of average air temperatures measured at different locations in CWP and blocks (16 th Jun to 1 st Jul 2003). Average air temperature (Degree C) CWP Kent Vale Figure 9: Comparison of average air temperatures measured at different locations in CWP and Kent vale apartment (16 th Jun to 1 st Jul 2003).

5 September 2004 Page 5 of 6 Cooling load (kwh) Figure 10: Dense primary forest (upper) and sparse wood (lower) in CWP In 100m from 200m from 300m from 400m from Table 3: the LAI measurement in CWP Location 1 LAI readings The elevation of average air temperatures could be observed in both blocks and Kent vale. It also follows the rule that the further away the point is from the higher the average temperature. Similarly, calculated standard deviations of ambient temperatures are smaller for locations within compared with those obtained from locations within the built environment. 3.2 Tas simulation in BBNK The calculated cooling loads for different locations within or near to the BBNP are presented in Figure 11. A clear difference among cooling loads could be observed. The lowest load, 9077kWh, was observed when building was placed inside while the highest one, 10123kWh, was experienced when the commercial building was built 400m away from the park (location 9 in the filed measurement). The energy consumptions of the rest of the locations are within the range defined by the above two locations. It accords with the average temperature profile observed in the field measurement in BBNP. It is unrealistic that a commercial building can be built inside a national park. But it is possible that the building is built near to a park. The above cooling loads analysis can provide a useful reference in this case. For example, 9% cooling energy can be saved if a 9-storey commercial building could be built close to (shifting from 400m to 100m). cooling load (kwh) Energy savings (compared with 400m) In % 100m from % 200m from % 300m from % 400m from % Figure 11: Comparison of cooling loads for different locations. 3.3 Envi-met simulation in CWP Figure 12 shows the temperature profiles of three scenarios generated from Envi-met. With park, it is observed that the coolest region is itself at about 300K. The cooling impacts can be on surroundings at around 301.1K to 301.5K. When the vegetation is removed, the temperature in the original park area has been elevated to about 301K. It is to be noted that the model assumes the source of water in the soil is non-depleting. In reality however, it is expected that the water will be dried after some time and thus the thermal condition of the original park area should be even worse. Furthermore, the cooling impacts on surroundings disappeared in this profile. When the vegetation is replaced with hard pavement and buildings, it can be seen that the whole area now has higher temperature at about 301.5K. the surroundings have higher temperature of 301.8K to 302.2K. Generally, the cooling impacts of vegetated area can be observed mainly on the leeward of the built environment.

6 September 2004 Page 6 of 6 energy. Results derived from the Tas simulation support the observations of field measurements. Energy may be saved when buildings are built near to parks. Maximally 10% reduction of the cooling load was observed in the simulation. Simultaneously, the loss of greenery may cause bad thermal condition not only in the original park area but also the surroundings. It has been testified visually through images generated from Envi-met. In summary, the importance of big city greens has been confirmed through filed measurements and simulations under the tropical climate. But the benefits of parks are not limited to the thermal aspect only. They are also invaluable from ecological and social point of views. More concerns should be pay on reservation of green areas in cities rather than simply replace them with buildings. ACKNOWLEDGEMENT (a) (b) This research was supported by the National University of Singapore (NUS), Building and Construction Authority (BCA), Singapore and National Parks Board (Nparks), Singapore. The authors would like to express their sincere thanks to research students who provide their assistance in the filed measurements and computational analysis. REFERENCES (c) Figure 12: Comparison of temperature profiles for different scenarios (a. retaining ; b. removing vegetation but keeping soil; and c. totally replacing with buildings). 4. CONCLUSION Field measurements have been done in two local parks. The average temperatures obtained in both two parks are lower than those obtained from their surrounding environment. The temperatures measured within parks have strong relationship with the density of plants nearby since plants with higher LAIs may cause lower ambient temperatures. For surrounding built environment, the closer to the lower temperature was experienced. Maximally, 1.3 o C difference of average temperature was observed at locations around s. The temperature difference was caused by vegetated area and it may cause savings of cooling [1] Jauregui, E., 1990/91. Influence of a large urban park on temperature and convective precipitation in a tropical city, Energy and Buildings, 15-16, [2] Saito, I., 1990/1991. Study of the effect of green areas on the thermal environment in an urban area, Energy and Buildings, 15-16, [3] Kawashima, S., 1990/1991. Effect of vegetation on surface temperature in urban and suburban areas in winter, Energy and Buildings, 15-16, [4] Jauregui, E., 1990/91. Influence of a large urban park on temperature and convective precipitation in a tropical city, Energy and Buildings, 15-16, [5] Sonne, J. K. and Vieira, R. K., Cool neighborhoods: The measurement of small scale heat island, Proceedings of 2000 summer study on energy efficiency in Buildings, American council for an Energy-Efficient Economy. [6] Avissar, B., Potential effects of vegetation on the urban thermal environment, Atmospheric Environment, Vol. 30, No. 3, [7] Honjo, T. and Takakura, T., 1990/91. Simulation of thermal effects of urban green areas on their surrounding areas, Energy and Buildings, 15-16, [8] Wong, Nyuk Hien and Chen, Yu Study of Uraban Heat Island in Singapore. PLEA 2003 conference proceeding. [9] [10] agklima/envimet/