Proceedings of International Symposium on City Planning 2013

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The Influence of Vegetation Allocation in Micro Climate for a Urban Park and its Neighborhood Area

Chun-Ming Hsieh

Research Center of Green Building and New Energy, Tongji University Department of Urban Planning, Tongji University

(e-mail: chunming@tongji.edu.cn)

Yin-Hsuan Sun Department of Urban Planning, National Cheng Kung University

Department of Landscape Architecture, Tokyo University of Agriculture (e-mail: fify821@msn.com)

Feng-Chun Jan

Department of Urban Engineering, the University of Tokyo (e-mail: janfengchun@live.jp) Abstract

Recently, because of the growing importance of the heat island effect, the maintenance of trees and the design of planting on green land are becoming more and more significant. Planting vegetation in urban parks is believed to be able to improve the thermal environment, yet the allocation of plantings may hinder the wind environment. In this study, perspectives of thermal environment are discussed to evaluate the different feelings that visitors sense from the thermal comfort inside and outside of Tainan Park. CFD (Computational fluid dynamics) simulation is utilized to study the shading and wind environment. Eventually, improvement strategies for planting pruning and allocation policy as well as the building arrangement of the city block next to the park are proposed. The significant improvement of thermal comfort was observed. Keywords: Microclimate, CFD, wind environment, urban park, thermal comfort

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1. Introduction

In recent decades, the continued economic development, which comes along with a high-density society in Taiwan has led to the destruction of nature and the worsening quality of the living environment. With urbanization, another problem, urban heat island (UHI) effect, also increases gradually in significance (Hsieh, 2011). Taiwan is located in subtropical and tropical climate zone, and its weather is regularly hot and steady in summer. Therefore, green lands, which provide quite effective improvement of microclimate, turn out to be important. In Taiwan, urban planning regulations have stipulated that green lands in the parks of all cities should be reserved so that there are more natural spaces to be utilized. They not only improve the urban landscape, but also play important roles as cooling devices and moderators of the UHI effect.

The meteorological phenomenon of green land in parks is influenced by the composition of planting, temperature, humidity, and wind (Hazemoto, 2007; Watanabe, 2010). It was found that humidity was greater in forests of high density in the summer, and that wind speed decreased in that area. The study also stated that forests could prevent temperatures from rising. Furthermore, Yoshida et al. (2000) reported that tree-crowns blocked the wind, worsening the thermal environment in the summer. A study conducted by Jan (2012) demonstrated that the elements of the microclimate, along with plant density, influenced the growth of plants. Therefore, the allocation of trees and the accommodation functions of the microclimate are factors that must be taken into account in green areas.

This study analyzes the thermal environment inside and outside the park. Air temperature, wind speed and the evaporation amounts of trees, etc. are measured and thermal environment simulation is carried out. In order to utilize the effect of cooling air from urban park to surrounding area, tree pruning and urban design control strategies are proposed to create ventilation and shading for better thermal environment. 2. Research Area and Measurement 2.1 Study Site

Tainan Park mainly contains tropical trees and is the most important green area in Tainan city. Araucaria heterophylla, the representative of araucaria in tropical coniferous forests, is one of the most precious trees in Tainan Park. Three trees out of each area were selected to conduct sap flow measurement and microclimatic investigation. It is allocated in two ways: dense forest and row planting (Fig. 1). The average temperature is highest in the period from June to September in a year. The meteorological data of these four months were thus used in this study. Fig. 2 shows the monthly average wind frequency at noon time recorded by the Tainan Weather Station for the last ten years. The west wind occur midday.

Proceedings of International Symposium on City Planning 2013

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flow speed in each tree. Afterwards, the amount of transpiration of a single tree and the total amount of transpiration for each area was predicted by substituting the speed of sap flow. 2.4 CFD Simulation Settings

Thermal environment analysis were conducted using a computational fluid dynamics (CFD) simulation software, WindPerfectDX. The CFD boundary area, shown in Fig. 3, to be a 2000 m (N-S) × 2000 m (E-W). The smallest grid unit was 2 m × 2 m in both the X and Y axis, and the span between vertical meshes (Z axis) near the ground was less than 0.5m. The daytime temperature designed for simulation was 31.3 °C, and the stable wind direction for the noon time was West. The value of the power law set to α=0.20, and the reference height was set to 40.8m (the height of the equipment at Tainan Weather Center).

Fig. 3 Simulation model

3. Results and Discussion 3.1 Results of Measurement Observation

Data for wind direction, wind speed, temperature, and humidity from each Araucaria heterophylla planting area in Tainan Park were obtained. Comparing microclimatic data from these three areas, difference in temperature was greater in row planting areas and in side-row planting areas. The average temperature in the row planting area was 1–2°C higher than that observed in the side-row planting area. The relative humidity in both areas was high in the afternoon. The relative humidity of the side-row planning area surpassed the relative humidity of the row planting in the morning, with a difference of 7%. Wind speed remained steady in the mass planting area. Changes in wind speed in the row planting area ceased after 16:00. In the side-row planting area, the wind decreased after 16:00.

The temperature was greatly influenced by differences in ground vegetation (Fig. 4). The difference in temperature between grassy ground and sandy ground was as great as 14°C. Nevertheless, the difference was smaller in the mass planting area because of tree shade. As a result, planting ground covered completely by grass and sandy ground shaded by trees showed a smaller difference in temperature. There was no obvious difference in the temperature at the tops of the tree-crowns in the mass planting area and side-row planting area, which was located outside of the mass planting area. The temperature at the tops of the tree-crowns in the row planting area, however, reached as high as 35.2°C, surpassing that of the other two areas.

Proceedings of International Symposium on City Planning 2013

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(a) Row Planting (b) Side Row-Planting (c) Mass Planting

Fig. 4 Soil Temperature Distribution It can be seen that the distribution of the sap flows of the row planting area and side-row

planting area outside of the mass planting area was quite consistent. However, the total sap flow amount in the row planting area was only one-fifth the size of that of the side-row planting area. On the other hand, the decrease in the speed of sap flow was gentler than in the mass planting area, and the highest sap flow speed occurred from 11:00~12:00. These two observations were the same for both the side-row area and the row planting area. The biggest difference occurred after 13:00, when the speed stopped increasing and started to slowly decline. The Granier method was adopted to infer the amount of transpiration of individual trees. Subsequently, the average of sap flow speed was calculated and then multiplied by the sapwood square measure in order to obtain the amount of transpiration, which was also the overall inferred amount of transpiration. First, the increment borer was inserted into the trunk. Then, the width of sapwood was obtained along the direction of radius, and was then used to calculate the square measure. Subsequently, the amount of transpiration of a single tree was predicted by multiplying the speed of sap flow by the square measure. The results clearly demonstrated that the amount of transpiration in side-row planting area was greater than those amounts in the row planting area and mass planting area. The lowest average amount of transpiration was found in the row planting area and the mass planting area lay in between. 3.2 Microclimate Discussions

The microclimate in the park was observed by fixed and mobile measurement. Fig.5 (a) and (b) show the distributions of wind speed and air temperature at noon time. The wind direction of measurement date of was NW. The windward side of the park had a higher wind speed, but a lower wind speed in the leeward side of park. On the other hand, the air temperature inside the park had a lower air temperature. It was obvious shown that trees in park has the temperature decreased due to the evaporation of trees and shading of trees. However, it also shows that wind distribution was disturbed by dense tree crown. Dense allocation of trees resists the air flow. Although the air temperature inside the park reduced, the wind path was obscured in the leeward side. Heat can not be removed by the wind ventilation. It was shown the wind speed in the leeward side of the park was lower and with a higher air temperature from the observation. There was no shading in the leeward side of the park, and the poor ventilation was found due to trees inside the park and buildings in the surrounding area. The higher temperature was observed in the leeward side from the measurement. Since it was confirmed by the above measurement results that the air temperature reduced by tree evaporation and shading, it shows the potential to improve the wind ventilation and decrease the air temperature as well as thermal comfort in the leeward side when trees was properly allocated inside the park and building nearby .

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Fig. 5(a) Wind Distribution of Noon Time Fig. 5(b) Temperature Distribution of Noon Time

4. Case Simulations From the questionnaire of SET* evaluation, it was shown that thermal comfort was mainly

influenced by shading and wind speed. Fig. 6 show the SET* distribution at the noon time which is the time period with the fewest shading during the daytime. There was no shading area in the leeward side of the park and wind speed was disturbed by trees. Also, the building coverage ratio is high in the surroundings which is also the reason slows down wind speed at a height of pedestrian. Based on the above reasons, the residential area at the east side of the park was selected as the study area for further discussion of the possibilities for improving thermal environment. Therefore, the trimming plant and rearrangement of buildings were proposed.

Fig. 6 Simulation Result of SET*

Proceedings of International Symposium on City Planning 2013

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Simulations of wind speed were carried out for two cases. Case 1 is the case in the current situation (Fig. 7(a)). Case 2 was a case for considering tree pruning and urban design (Fig. 7(b)). The wind speed was slow since the trees in urban park resist the wind speed in the current situation. The ability of trees to function as mitigates of the UHI effect by adjusting microclimates was taken into consideration. The same building floor area was the same for both cases. The lower building coverage ratio was proposed in Case 2, which means buildings are higher than those in the current situation. The wind speed increased after the tree pruning and the urban block next to the park have better ventilation. The distributions of SET* at pedestrian height in the current situation were shown in Fig. 8(a). The distribution of SET* for the improvement scenario was shown in Fig. 8(b). The SET* after the urban design proposal was lower than that in the current situation. That means the air cooled by trees in urban park had the potential to flow into the residential zone in the urban block. The obvious improvement of thermal comfort was found.

Fig. 7(a) The Wind Distribution of Case 1 Fig. 7(b) The Wind Distribution of Case 2

Fig. 8(a) The SET* Distribution of Case 1 Fig. 8(b) The SET* Distribution of Case 2

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5. Conclusion In this study, microclimate measurement and CFD simulation was carried out to discuss the

transpiration characteristics of trees planted in urban area. Microclimate of different allocations of planting, were investigated. The park had lower air temperature not only because of the effect of transpiration, but also that of shading by trees. However, the wind distribution was found lower which was blocked by tree crown in the leeward side of the park. Residential buildings, though they are located next to the park, have poor wind environment as well as the thermal comfort. The allocation of trees in park and buildings in the surrounding areas will have a significant impact on wind and thermal comfort. Also, the thermal comfort of pedestrian space is important for residential area. It was shown from the simulation results and measurement that it is required to consider tree pruning strategies, urban design along the roadside, and the space between buildings in urban blocks based on the direction of prevailing wind in summer. Those strategies will help to induce cool wind from park and create a better shading environment at the height of pedestrian. Then, the urban block next to the urban park has the potential to enjoy the green view and also the better quality of thermal environment. Acknowledgement

This research was financially supported by the Fiscal 2011 Grant for Japan-related Research project from The Sumitomo Foundation. References: 1) Fujiyama, Y., Hirose, S., Ootsuki, K., & Ogawa, S. (2005). Evaluation of transpiration in plantation

of chamaecyparis obtusa based on sap flow measurement by Granier method. Bulletin of the Kyushu University Forests, 86(1), 15–31.

2) Granier, A. (1985). A new method of sap flow measurement in tree stems. Annales des Sciences Forestieres, 42(2), 193–200.

3) Hazemoto, Y., Tateishi, M., Hosoi, A., Tsujihara, M., & Yasunami, Y. (2007). Field measurements of thermal environment improvement effect by a tree in summer. Architectural Institute of Japan, 46(1), 113–16.

4) Hsieh, C.-M., Aramaki, T. and Hanaki, K. (2011), Managing heat rejected from air conditioning systems to save energy and improve the microclimates of residential buildings, Computers, Environment and Urban Systems Vol.35, No.5, pp.358-367

5) Jan, F.-C., Hsieh, C.-M., Ishikawa M. and Sun Y.-H. (2012), Influence of street tree density on transpiration in a subtropical climate, Environment and Natural Resources Research Vol.2 No.3, 84-95

6) Komatsu, H., Kume, T., Yoshifuji, N., Hotta, N., & Suzuki, M. (2007a). Transpiration of a cryptomeria japonica plantation in winter: Analysis based on one-year sap flow measurements. The Tokyo University Forests, 117(3), 1–9.

7) Sellami, M.H., & Sifaoui, M.S. (2003). Estimating transpiration in an intercropping system: Measuring sap flow inside the oasis. Agricultural Water Management, 59(3), 191–204.

8) Umeda, K., Fukao, H., & Tamura, A. (2006b). Basic investigation on transpiration of a tree in summer for evaluation of thermal environments. Architectural Institute of Japan, 601, 15–20.

9) Watanabe, A., Huan, R., & Ooka, R. (2010). The study on incorporation of the vegetation transpiration model in outdoor thermal environment simulations: The field experiment research about the influences of environmental factors on the transpiration of roadside trees. Architectural Institute of Japan, 883–84.

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10) Yamamoto, H., Otsuki, K., & Morinaga, K. (2005). Development of the water stress diagnostic technology of the citrus using spectral measurement and Granier method. FY2005 Final Research Report Summary, Ministry of Education, Culture, Sports, Science and Technology, Tokyo, Japan.

11) Yoshida, S., Ooka, R., Mochida, A., Tominaga, Y., & Murakami, S. (2000). Study on effect of greening on outdoor thermal environment using three dimensional plant canopy model. Journal of Architecture, Planning and Environmental Engineering, 536, 87–94.