ANALYSIS OF THERMAL COMFORT ZONE UNDER THE TREE CANOPY: CONTROLLING THERMAL COMFORT BY THE ARRANGEMENT OF TREES TO SUIT THE EXISTING ACTIVITIES IN A HOT AND HUMID URBAN PARK IN TAOYUAN CITY, TAIWAN.
Manchester Metropolitan University, Manchester School of Architecture, Master of Landscape Architecture Dissertaion.
Leeyuan Ko Supervised by Dr Luca Csepely-Knorr 18 August 2017
Contents
1.1.
Introduction
01
2.1.
Literature review
02
3.0 3.1. 3.2. 3.3.1. 3.3.2. 3.3.3. 3.3.4.
Baseline study Research model Thermal comfort index Characterizing urban geometry Characterizing climate feature Result of the influence of urban geometry to the microclimate Baseline PET result
04 05 06 07 07 09
4.0. 4.1. 4.2. 4.3.
The influence of trees to the microclimateMicroclimate settings Microclimate settings Characterizing vegetations The results of the influence of trees to the microclimate
10 10 12
5.0. 5.1.
The influence of tree arrangement to the microclimate Characterizing arrangements
14
6.0. 6.1. 6.2.
Building vegetation influence module Data collection Characterizing microclimate features in the result area
19 21
7.0. 8.0. 9.0.
Result Conclusions and recommendations Universality and limitations of the present study
23 26 29
Acknowledgments References Bibliography
29 30 32
Abstract This dissertation tested the influence of thermal environment by the arrangement of trees. Numbers of CFD (computational fluid dynamics) studies were applied to find a better solution, the effectiveness of each test were assessed by PET (physiological equivalent temperature) and PET level. The PET and PET level of each existing activities were calculated with the microclimate data from a particular type of the tree arrangement to evaluate the comfort level. And suggesting a desirable location of which activities to input as part of a landscape design thinking scheme. This dissertation focuses on a hot and humid subtropical climate feature in Taiwan. The studied site was a park surrounding by densely developed residential area in Taoyuan city, Taiwan. The geographic and meteorological data were collected from Taiwan’s National Land Surveying (no date:online) and Mapping Center and weatherspark.com (no date:online). The result data were extracted from 1.5m above ground level and used the meteorological data from the hottest day in 2016. The initial CFD study focused on the influence brought by the surrounding urban context on four crucial meteorological elements that affect the PET level. As a result, the wind direction changes to 225° from 202° (North part of the park) and 157° in the south. The wind speed (Vw) decreased 72%, air temperature (Ta) 2.4°C, relative humidity (Rh) reduced 5% and mean radiant temperature as 54.5°C. The PET and PET level calculated form these data were 40.6°C and level 3. A CFD study was then carried out on the influence of microclimate by LAD (Leaf area density). The active area and degree brought by a tree that has a higher LAD are greater than others, Ta decreased by 0.9 maximum, wind speed increased 130% maximum, Rh increased by 6% maximum and Tmrt decreased by 13.36% maximum. Therefore, the tree which has the highest LAD was applied to the following arrangements test. Three different arrangement type depending on the distance between the edge of the canopy were applied for this part of the test. The arrangement that includes the distance between -1 to 2 meters has the best influence on mitigating thermal environment. The Ta decreased 80 to 86%, and wind speed increased 188% maximum, minimum Rh as 45% and Tmrt decreased 72 to 84%. Finally, 14 different microclimate features were separated from the most effective tree arrangement. The existing activities and body characteristics of the park users and their activities were organised in 9 settings. These settings were integrated with the meteorological data extracted from those 14 microclimate features to assess how comfortable are those people who are doing the exercises in each microclimate zones by PET and PET level. As a result, once the distances between the edge of each canopy are approximately 1 to 2 meters, the users will feel comfortable regardless of their body characteristics or the type of activity. Secondly, people will experience a stronger wind force under trees if the distances between the edge of each canopy are under -1 meter, slow paced exercises such as sitting area or garden are suggested in this scenario. Finally, open spaces leeward of trees will slight warm for every activities, open lawn for night uses parking area will be a wise decision in this case.
1.1. Introduction This dissertation aims to mitigate a hot and humid climate feature in the subtropical area by the arrangement of trees. The studied site is located in Taoyuan city, Taiwan. Taoyuan is an industrial based city located in northern Taiwan. Taiwan is an island located in eastern Asia. The coordinate is between 21°53'48.5"N to 25°17'58.7"N latitude and 122°00'25.8"E to 120°02'06.1"E longitude. Taoyuan has a humid subtropical climate, the hottest month will often be June which has the mean daily temperature around 29°C. The coldest month is January which has the mean daily temperature around 12°C. Due to the high humidity feature as an annual average of 78.4% (no date:online), people tend to be sweaty during summer time. People in Taiwan normally been adapt to a hot and humid weather, although the mean daily temperature is just around 16°C, most of the people usually feel very cold during winter (Lin, 2008:281-290). According to a local news report in 18th December 2014, 18 elder people died because of myocardial infarction which related to cold weather. In 25th January 2016, 60 people died for the same reason. Furthermore, Taiwan suffers from numbers of typhoon every year (no date:online). The impact of the typhoon is not just heavy rain and rapid wind, typhoon also brings foehn wind which increases the air temperature rapidly. For example, a foehn wind caused by the typhoon in Taoyuan in 2016 increased the air temperature to 38.7°C (no date:online), This enhances the number of people who suffer from hyperthermia by 53%, comparing to the same period in 2015. Regardless of the natural disaster, rapid reduction of the greenbelt and the increasing building project developments in the city cause the urban heat island effect, the UHI increase the mean daily air temperature by 3.17°C (Su et al., 2012) which makes the summer even hotter. Due to the influence of local climate features and UHI effect, it is essential to create an effective way to mitigate outdoor thermal environment and increase the greenbelt area in urban context. It is commonly agreed that the space under trees provides a more comfortable microclimate environment for people. But there are several unique microclimate features in the woods, what kind of activity is suitable for these spaces, how does the arrangement of trees mitigate the hot and humid environment, how to control this effect and finally, how does a human body react to the climate when doing different activities. Understanding and solving these question can be beneficial for landscape architects to create a comfortable outdoor living environment. According to Höppe (1999)’s research, wind speed (Vw), air temperature (Ta), relative humidity (Rh) and mean radiant temperature (Tmrt) are the most crucial meteorological elements to control outdoor thermal comfort. This is a result of a complicated calculation of how the human body reacts to the heat index and the climate. Also, Gromke et al. (2015) believe that meteorological element can be controlled by vegetation and its layout and proved that these complex calculations could be simulated, analysed and visualised by some software. However, the studies of the outdoor thermal environment are helpful to indicate the thermal comfort level of an existing scenario. There is a lack of a system which combines the mechanism that influences the microclimate and the thermal comfort index of different activities as a design tool for landscape architects. This dissertation combines a series of CFD study of how to control the comfort level of various activities by the arrangement of trees. And create a parametric calculator that integrating those data and visualising thermal comfort map of the site as a design tool to help landscape architects to create a physically comfortable environment. ENVI-MET was applied to run the CFD analysis to carry out those four meteorological 1
elements. A thermal comfort indicator specifically for people who live in a subtropical region provided in ladybug_honeybee was used to calculate and visualise PET data and PET level to evaluate comfort level. All the information and calculation modules are recorded in grasshopper. This makes the settings can be applied in other areas which have similar climate feature. This module is made from three elements, the original microclimate data which includes wind speed, air temperature (Ta), relative humidity and mean radiant temperature, the level of influence on these four meteorological elements by a particular type of tree arrangement and finally, an activity and body characteristic indicator. The original data is used as a baseline. The other two modules are the mechanisms to alter the baseline data. The final result can be shown as a PET map to indicates the comfort level with geography data. Therefore, once the site is different, a different result can be illustrated by inputting a new CFD analysis result of the original microclimate data of the site. The first part of the dissertation studied the influence on microclimate in the location by the surrounding urban geometry, so the microclimate data of the site can be closer to the reality. The influences by a different type of trees were tested in the second part. The third part compared the effectiveness by a various arrangement of the tree, the typology of the tree in this section of the test was chosen by the one which has the greatest effect from the previous chapter. Areas which contain different microclimate feature from the most efficient arrangement were classified. The comfort level of each existing activities and the body characteristic of the park users were calculated with the data from the previous chapter in the final chapter of the research method.
2.1. Literature review Studies have shown that vegetation and ground covering material could help controlling the outdoor thermal environment. Ground cover material includes vegetation, water bodies and pavings. It controls the longwave radiation from the sun. A research provides tremendous data of heat output performance from a different type of pavings. (Doulos et al., 2004). It demonstrates that a wise use of paving material could mitigate the air temperature. Other study Indicate that environment near water body and grassland can be much cooler. Vegetation such as trees has great ability to control microclimate, for example, mitigate the heat from shortwave radiation and change wind velocity and direction. (Hassaan and Mahmoud, 2011). More impacts of vegetation such as ‘reduction of the conductive and convective heat gain by lowering dry-bulb temperatures through evapotranspiration during summer’ and ‘increase of latent cooling by adding moisture to the air through evapotranspiration’ in the urban environment has been indicated. (Dimoudi and Nikolopoulou, 2003:69-76). A research done in 2014 shows that using a suitable type of materials, shade type or vegetation layout could mitigate hot environment. (Su et al., 2014). Vegetation has a strong influence on the microclimate, this fact has been proved by numbers of studies. The transpirational cooling by venue-tree can reduce the mean and maximum temperature up to 0.43 °C and 1.6 °C during a heat wave with wind speed as 5.1 m s−1 at 10 m above ground. (Gromke et al., 2015). A similar study done by Bharathi Boppana and her associates in 2015 has proved the effectiveness of cooling effect by vegetation Boppana et al. (2015). Other study in 2002 shows the ways of vegetation impact the environment includes transmission effect, evapotranspiration effect, albedo effect and permeability effect. 2
This demonstrates that the impact of vegetation is strong and could influence the surrounding urban area. (Dimoudi and Nikolopoulou, 2002). The effectiveness of cooling effect by trees was studied in Malaysia. They have classified tree typologies by Leaf Area Index (LAI) and Leaf Area Density (LAD), the result shows trees with higher densities has greater ability of cooling effect, however, high density would also reduce the wind speed, with the LAD higher than 1.5, the reduction of wind speed could become 63% or more (Shahida, 2015). While vegetation has a great ability of cooling, the layout of vegetation matters as well. A study done in China indicates that a dotted pattern and circular pattern layout trees have greater mitigation effect of the thermal environment than other patterns such as circular pattern, radial pattern, wedge pattern and zonal pattern. (Su et al., 2014). Doulos and his associates have tested 93 different paving materials to study the cooling effect of pavings. The study shows that under the same test environment, the mean surface temperature of a smooth white surface marble was 29.7 degree, in contrast, normal black asphalt was measured over 46 degrees. This result indicates the importance of choosing material in hot weather regions. (Doulos et al., 2004). Furthermore, a research in 2006 shows that ‘The surface temperatures of the artificial pavements were 10 °C higher than those of the vegetation surface at noon during the summer’. (Lin et al., 2016:84-95). Yang and Zhao (2015)’s research shows the temperature beneath a tree or near the water body and shrub is constantly lower than the mean air temperature during the daytime. The temperature could differ from 0.5°C to 1.5°C. Interact the effect of paving, vegetation and waterbody could enhance the cooling effect and control the thermal environment, doctor Hassan and Mahmoud (2011) have measured a variety environment which includes different combinations of those elements in a park which located in Cairo, Egypt in 2011. The study shows that more people were satisfied with the temperature which near the water body, such as fountain area, lake and cascade area. A study was done by Dr Limor Shashua-Bar et al. (2011). has compared the heat index data between two different environment setup. The study shows that an environment with tree shade and grassland is much cooler than artificial paving with shade caused by mesh. A joined study done by Aristotle University of Thessaloniki and Architectural Association Graduate School shows the similar result (Angeliki and Simos, 2014). Numbers of researches have indicated that thermal environment can be controlled, but the people’s ability to adapt different climate could be dramatically different. A study about tourism climate information has done by Lin and Matzarakisb (2011) studied how people react to the climate in south-east China and Taiwan. The study shows that people who from the temperate region would normally consider 4°C as very cold, 23°C as Neutral and 35°C as warm. In contrast, people who from (sub)tropical region would normally consider 14°C as very cold, 30°C as Neutral and 38°C as warm. This is very important, regarding creating a physically comfortable environment.
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3.0. Baseline study 3.1. Research model The research model is made by two modules (figure 1), the assessing module and the design module. The assessing module is used to assess the thermal comfort level of the site, a PET (physiological equivalent temperature) map was made to indicate the PET level in different areas of the site. The PET data is calculated by a PET calculator which is provided by the ladybug-honeybee component in the Rhino-grasshopper interface. Ta (Air temperature), Tmrt (Mean radiant temperature), Rh (Relative humidity) and Vw (Wind velocity) are needed to calculate the PET, and those data are from a previously done CFD study of the site. The PET data will then be converted into a PET map as a baseline to compare with the final result. The climate data of the baseline study will be applied to the CFD study of vegetation LAD (leaf area density) and vegetation arrangements. The result of this further study will be the database of the design module. The design module is a combination of a series of vegetation module and the arrangement module. Each module contains a series of coefficients which will be used to control the Ta, Tmrt, Rh and Vw of the baseline study result to indicate the influence of trees on outdoor thermal comfort. The arrangement of each tree and its typology will be depended on the activities in each area, different areas which hold different activities will be assigned to different microclimate features. Multiple softwares or modules are applied to do the experiments, however, all the data are connected and organised in one grasshopper file. Therefore, the final parametric model will be able to suggest the designers which trees and arrangement to use to control outdoor thermal comfort.
Fig. 1: Research method.
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3.2. Thermal comfort index Both UTCI (universal thermal climate index) and PET are commonly used to assess the outdoor thermal comfort level. To calculate those thermal comfort index, data such as Ta, Tmrt, Rh and Vw are needed. Because those meteorological data are the key elements that affect how the human body reacts to heat observe and release and both of these equations are built on this fact. However, the UTCI is a universal index that indicates how all human beings react to the climate, the difference of how people who live in different climate zones react to the weather are not considered. According to Lin (2008)’s research (figure 2), people who live in the (sub)tropical region are more capable of living in high temperature than those who live in the temperate region and the people who live in the temperate region have their definition of cold. Therefore, there are two different type of PET equations that divided those who live in different climate zone. PET for (sub)tropical region is applied in this paper because the site is in a subtropical region.
Fig. 2: TPC level for (sub)tropical region and temperate region (Lin, 2008:281-290).
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3.3.1. Characterizing urban geometry ENVI_MET was applied to run the CFD study of the site, in order to produce a PET map. CFD stands for Computational Fluid Dynamics, it helps to analyse a variety of climate features with geographical data. The meteorological data of the hottest day in 2016, 17th July is applied along with the GIS data from Taiwan’s National Land Surveying and Mapping Center in this study. The calculated domains are 60*60*30 grid, each grid represents 5m. As a result, 300*300*90m of urban geometry is included in the test area (figure 3). The test model is built on the site, the distance from the centre point to each edge is approximately 200m. This is enough to include the surrounding buildings which would influence the microclimate in the site. The buildings located on the northeast of the site are comparatively lower, they are about 1 to 3-floor high, there is another greenbelt behind those buildings. The numbers of buildings on the south-east are more than the northeast side, most of them are also just 3-floor high, but one of them is a 12-floor high residential building. There is a big community combined with a series of 14-floor high buildings on the south-west. On the north-west side, there is a very dense community combine with 3 to 4-floor high buildings, the alleys in those builds connect the east to the west. In order to build a more accurate model for the initial south-west wind flow with the grid modelling system in ENVI-MET space. The grid north was turned -26.38 degree. The lower buildings in the model are set as 13m high and 45m for the higher buildings. The surface of the buildings was set as concrete and asphalt for the ground.
Fig. 3: ENVI_MET model.
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3.3.2. Characterizing climate feature The climate data is from the weatherspark website (no date:online), it is a trustable data source because their data comes from NASA’s satellite data and it is one of the very few resources that contains the weather data of Taoyuan City. According to their record, the air temperature on 17th July 2016 appeared to be the highest number during the year. There was a very limited precipitation and cloud covering, mean daily wind speed was 3.6m/s. Although 31 July and 1st Aug also appeared to be 33°C, those days are much cloudy than 17th July. There is a lack of humidity data from the weatherspark database (no date:online), the relative humidity data is gathered from Taoyuan International Airport instead (no date:online). It is also a reliable data source in this case because the linear distance between the airport and the site is just 11.17km. The CFD simulation duration is 12 hours, from 07:00 to 19:00, it includes the hottest time in a day. The air temperature and Mean radiant temperature are not affected when the sun goes down, so the night hours are not included in this test. The initial input wind speed is set as 3.6m/s south-west (225°) as the same with the mean daily wind speed. Compulsory air temperature and relative humidity were applied to ensure the tested climate environment are as close as the reality. The lowest air temperature was set to 27°C at 07:00 while highest temperature was set as 33°C at 13:00. The highest relative humidity level was set as 66% at 07:00 while the lowest point set as 52% at 12:00. Cloud covering level was set as 0% as the clear sky to avoid unnecessary elements. The sun radiation level was controlled by date and geographic coordinate system while longitude set as 121.25 and latitude as 24.98. 3.3.3. Result of the influence of urban geometry to the microclimate Figure 4-1 and 4-2 shows the CFD result of wind direction and speed at 1.5m above ground level at 12:00 to indicate the wind field that people can feel and the hottest hour in a day. The influence of the surrounding buildings to the wind is very noticeable. The wind speed reduced to 0.73 to 1.1m/s from 3.6m/s when it enters the site due to the buildings on the south-west side. The wind speed was reduced by approximately 72%. But the wind speed recovered gradually to 1.47-1.84m/s when it enters an empty site, and it stays at that speed until it hits another building. The wind enters the site from the south, due to the surrounding buildings, the wind direction turns to the southeast while the original wind direction was south-west. After entering an empty site, it turns back to south-west again. However, the wind direction stays south-east in the north-west and the south-east part of the site due to a powerful tunnel effect and building on the south-east side of the site that stops the initial wind flow to recover its original direction.
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Fig. 4-1: Wind direction (degree) result; Fig. 4-2: wind speed result. According to the result of Rh, Tmrt and Ta (figure 5), the microclimate can be divided into two separate zones, the south-west area and northeast area. The Tmrt is 2°C lower than the northeast part of the site. Therefore, the Ta is 0.1°C higher, and Rh is 0.5% lower than the northeast part of the site. However, the difference of the Ta, Rh and Tmrt between this two area is very minimal regarding the influence to PET, a fair assumption according to this result is that the wind speed will have a major influence to the PET map, regardless of the difference between other meteorological elements.
Fig. 5: Urban geometry CFD result of Air temperature (upper left); Wind speed (upper right); Relative humidity (bottom left); Mean radiant temperature (bottom right). 8
3.3.4. Baseline PET result PET differs between 40 to 42°C (figure 6-1). Interestingly, the area with higher Tmrt temperature appears to have lower PET, the reason behind this is that the wind speed in this area much higher than another area, therefore, people would feel much cooler. This is proved because the wind speed result has the same pattern with the PET result. Secondly, the minimal difference of air temperature and relative humidity as 0.1°C and 0.5% has a limited influence to the PET result, as the pattern of Ta and Rh result does not match the PET result. Although there is a 2°C PET difference in the site, the PET level (figure 6-2) in the whole area still appears to be three as hot for people who live in a (sub)tropical area. But the result that appears in some of the streets tells a different story, For instance, the PET level in the atrium of the community on the south-west side of the site is four as very hot. Although the Tmrt is 3°C lower than the numbers in the site, the wind speed here is very minimal, as it is below 0.37m/s. The PET level in the street on the northeast side of the site and the east corner of the high raised community buildings are two as slightly warm. Those are the most comfortable areas that appears in this test. The air temperature relative humidity in those areas are higher than the one in the site, but the buildings around those areas provide shading that lower the energy from the sun and the wind speed is much higher than the numbers that appear on the site. Therefore, it proves that even with the same condition of Ta and Rh, with better shading and higher wind speed, the place would be much more comfortable.
Fig. 6-1: PET map; Fig. 6-2: PET level map.
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4.0. The influence of trees to the microclimate
4.1 Microclimate settings The input climate data for the simulation of tree’s influence of microclimate were taken from the previous test result of the urban geometry study. Therefore, it can indicate the environment as the reality would be. According to the previous test, the most important element that affects the PET is wind speed. Therefore, the weather data from the area (figure 7) that the wind enters the site first was applied. In this test, the wind speed was set as 1 m/s, Ta as 30.6°C, Rh as 49.5%, the result of 12:00 was extracted from the test.
Fig. 7: extracted data area. 4.2. Characterizing vegetations Research have shown that the way trees affect the microclimate around them is via evapotranspiration, transmission, albedo and permeability (Dimoudi and Nikolopoulou, 2002). The effect of evapotranspiration let trees release water to the atmosphere by leaf, the water that is released to the air helps reduce the air temperature but increase the relative humidity. Transmission effect refers to how much shortwave radiation could travel through the tree canopy, most of the radiation energy would be blocked by the leaf, avoiding the air temperature increase by the radiation energy. Therefore the environment under a tree would be cooler. When the shortwave radiation hit on the leaf, a majority of the energy will be reflected back to the atmosphere; this effect is called albedo. The difference between albedo and transmission is that albedo focus on the amount of the energy reflected while the transmission focus on how much the energy passes through the leaf and the gap between each leaf. Finally, Permeability refers to the capacity of the air flow could travel through a 10
tree canopy. Those effects of the leaf have a direct and strong influence to the Ta, Tmrt, Rh and Vw. Therefore, a tree has a strong influence on the outdoor thermal comfort level. The difference of the influence on microclimate by a tree are depended on the features of the leaf, for instance, colour, shape, structure. Also, the size and shape of the canopy are important. Those features can be quantified and controlled by LAI (Leaf area index) and LAD (Leaf area density). In reality, a different tree has different leaf and canopy features, also, a different type of tree could be shaped manually into the same shape. Last but not least, the precision of LAD measurement could differ variously by the people who were doing it or the method they were using. Therefore, to reduce that uncertainty, three types of trees which are in the ENVI_MET database were introduced to this test. These trees have the same height, width of the canopy but each of those trees has a different level of LAD. The trees which were introduced in this test are Populus Nigra, Platanus × acerola and Carpinus Betulus. Their LADs are: Populus Nigra: 0.7m2/m3, Platanus × acerifolia: 1.1m2/m3, Carpinus Betulus: 1.7m2/m3 (figure 8).
Fig. 8: LAD level of each tree.
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4.3. The results of the influence of trees to the microclimate Figure x shows the Ta, Tmrt, Th and wind speed change CFD results of three different trees with three different LAD. The diagrams show the situation of 1.5m above ground. The trees were arranged by LAD level, the one on the left side is Populus Nigra which has the lowest LAD and the one on the right is Carpinus Betulus which has the highest LAD, the one in the middle is Platanus × acerifolia. As the Tmrt result (lower right) shows that all trees have similar capacity of lower the Tmrt, however, due to different canopy shape (figure 8: LAD level of each tree), different areas under the canopy has a different degree of cooling effect. The most efficient cooling area for Populus Nigra is the area near the middle of the canopy. The effectiveness reduces as it aways from the central point. The most effective area for Platanus × acerifolia and Carpinus Betulus are the areas near the edge of the canopy, but Platanus × acerifolia has a better effect than Platanus × acerifolia. Both Platanus × acerifolia and Populus Nigra can reduce the maximum of 7.94C Tmrt, but Carpinus Betulus which has the highest LAD could only reduce 5.29°C Tmrt in most of the area under canopy. This proves that the shape of the canopy has better influence of reducing Tmrt than LAD level. The other fact of the influence of LAD on the Tmrt is the higher the LAD a tree has, the higher the Tmrt increase around the tree. To conclude, tree canopy has a strong effect of reducing Tmrt, in this case, a round shape canopy is more effective. Secondly, high LAD also increases the Tmrt around the tree (figure 9), the degree of this effect became stronger when the LAD is higher. Because, the higher the LAD the greater the albedo effect become, some of the radiation reflect back to the atmosphere, while others been reflected on the ground outside of tree and increase Tmrt.
Fig. 9: Tmrt increased on ground level. Except for Populus Nigra, wind speed increases the maximum of 30.46% while the wind through the central point of the tree, this effect became stronger when the LAD is higher (figure 10). When the wind travels passees the canopy area, the wind speed reduced and became steady. The stabilised wind speed is 6.52 to 11.8% lower than the initial wind speed, 12
the higher the LAD is, the longer the distance for recover the wind speed. In this case, it took 22m for the wind to regain its speed to 88.2 to 93.48% of its original speed after it went pass Carpinus Betulus, 12 and 11 meters for Populus Nigra and Platanus × acerifolia. In terms of the air temperature, all trees can reduce up to 0.95°C, but Carpinus Betulus can reduce the air temperature up to 1.53°C, and the influenced area is the largest among all three trees because of its higher LAD. The Same fact can be found on the Ta result of Populus Nigra, Populus Nigra has the smallest influenced area of the maximum air temperature reduction. Unlike the open space scenario, the Rh does not reduce when the Ta is higher. The density of the tree canopy has strong influence on the reduction of Rh. Rh reduced the maximum of 3.58% under Carpinus Betulus compares to the baseline data, 1.59% for Platanus × acerifolia and 0.9% for Populus Nigra.
Fig.10: Influence of trees CFD result of Air temperature (upper left); Wind speed change (upper right); Relative humidity (lower left); Mean radiant temperature (lower right).
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5.0. The influence of tree arrangement to the microclimate 5.1. Characterizing arrangements In order to how the arrangement of trees can affect the microclimate, three different arrangements were tested in this section. Figure 11 shows the CFD result of the densest tree arrangement. As a result, the overall Ta and Rh result area much higher than the baseline, Ta increased the maximum of 2.23°C, Rh increased 27.19%. Also, the way air temperature differs is different with the single tree arrangement scenario, with a dense arrangement, the Ta in the open area is lower than the area that is covered by the tree. But this effect would only happen in the open space that is near the edge of the canopy, within a 10m range. Although the Ta and Rh increased massively, the results of Tmrt and Vw have a more positive influence in terms of the reduction of PET. The effect of increasing Vw has increased massively when the trees are arranged intensively and the effective area is much wider. In comparison with the single tree arrangement scenario, this effect increased by 55.79% maximum which makes the maximum Vw increase effect into 191.53% of the initial wind speed. When trees are arranged intensively, the minimum Tmrt under canopy is 38.38°C which is 2.76°C lower than single tree scenario, 15.62°C lower than baseline. Therefore, overall PET result (fig. 12) is 4°C less than the single tree scenario (figure 4), while the PET level decreased to level 2 (warm) which is 1 level lower than the baseline. To conclude, the leeward area of the densest arranged trees in this test is the most comfortable area (bottom right area). This area has the lowest Ta and Rh under the tree canopy, and the wind speed has already been increased. However, since the Ta and Rh are still much higher than the baseline, a dense arrangement might not be the best way to mitigate a hot and humid thermal climate.
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Fig. 11: Dense tree arrangement result.
Fig. 12: PET result of dense tree arrangement. The second test studied the influence from a wide distance tree arrangement (figure 13), the lowest distance between the edge of the canopy was set as 2m while the highest distance between them is 6m. The range increased 2m each time when a new set of arrangement was introduced, the one on the right is the densest and the one on the left is the least 15
compact arrangement. The features of Ta and Rh result are the same as the last test but the numbers are lower. The lowest Ta in this test is 30.41°C, it is only 0.19°C lower than the baseline, and it only appears in a comparatively small leeward area. The Ta in the open space is higher than the field under the tree, in this case, the highest Ta is 1°C higher than the baseline. Relative humidity under tree covering area is greater than other open space. The Same feature appears in the last arrangement test as well. But the difference between these two arrangements is that this time, Rh is higher in a dense arranged area. Rh in this area is about 60% while it appears to be just 50 to 55% in a wide arranged area. When the trees are arranged above 4m between each other, the decreased Tmrt area caused by the shading effect from the canopy starts behaving apart from each other, rather than an effective unified area like a densely arranged layout in the previous test. Also, the Tmrt is much higher in the area among trees that is not under covered by the canopy. On the other hand, when the trees are arranged below 4m between each other, the effect of increasing wind speed still happens among trees. But, once the trees are located more than 4m (canopy edge to edge) apart from each other, the increased wind speed would no longer appear under trees, instead, the increased speed wind through the gap between trees. This makes people feel less cool under the tree. However, the active area of increased wind speed does expand wider, so people who are in the leeward area which does not have shading effect of the tree can experience a better cooling effect by the wind. To conclude, Once the distance between trees is greater than 4m, all effects on microclimate by trees lost its ability when the trees are located close to each. Also, when the trees are located 2 to 4m from each other, the effect of increase Ta and Rh become much smaller than the trees are arranged very densely, but the numbers are still higher than the baseline. The comparison of these two arrangements is organised in the table below (Table 1).
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Fig. 13: Wide distance tree arrangement result Table 1: comparison of meteorological data influenced by the distance between each tree. Distance between each tree (small) Ta feature change
●
●
Distance between each tree (large)
Ta below canopy is higher than when there are no trees. Leeward area outside of canopy cover range appears to have the lowest Ta, but still higher than baseline.
●
Ta below canopy is higher than when there are no trees, but the effect is minimal.
Rh feature change
●
Rh level below canopy is lower than open space but still higher than baseline.
●
Rh level below canopy is lower than open space but still higher than baseline, once the trees are located apart from each other for more than 10m, the Rh level became close to baseline data.
Vw feature change
●
Dense arranged trees increase ground level wind speed massively. The
●
Vw increase when travelling under trees, once the distance between trees become larger 17
effective area is much larger than single tree situation.
Tmrt feature change
●
Tmrt decrease massively under tree canopy, effective area is much larger than single tree situation.
than 8m, the increased speed wind start to travel between each tree, rather than under trees. ●
Tmrt decrease massively under trees, once the distance between each tree became larger, the effect only appear under each tree.
Based on the result of the previous tests, the effect of reducing Ta and Rh is recognisable when the trees are located apart from each other with a large distance. Also, some of the effects can be enhanced regarding both the effective area and level. However both dense and wide arrangement has its disadvantages, therefore, controlling a suitable distance between each tree is crucial regarding the effect of mitigating the hot and humid climate. In the third arrangement test (figure 14), the distance between the edge of the canopy was arranged in a sequence starts from -1 to 2. -1 means the edge of the canopy from different trees are overlapped together for 1m, 2 mean the edges are apart from each other by 2m. As usual, the one on the right is the densest arrangement (-1). Except the Tmrt result is similar to other tests, Ta, Rh and Vw results are very positive. The highest Ta and Rh drops down to 27.34°C, and 43.76% and the lowest number appears to be 24.32°C and 21.34%, which makes the maximum reduction of 6.28°C and 28.66% compared to the baseline. However, the effective area of this two element is in contrast. The leeward area appears to have a lower air temperature the Rh is relatively higher in this area. Same contrast situation appears in the windward area as well. Wind speed change result has the same feature as the densely arranged test; the wind speed increased massively while it travels through the area under trees, it increased the 194.25% maximum. Also, this effect exists in the area among trees and the leeward area.
18
Fig. 14: Medium dense tree arrangement result
6.0. Building vegetation influence module 6.1. Data collection According to three previous arrangement tests, the most effective way of layout trees is to keep the distance of the canopy edge between -1 to 2m. Therefore, the data of the vegetation influence module is extracted from the third arrangement test. Figure 15 shows the effective level and area along the y-axis, area data is simplified by a grid system, each grid represents 5*5m. This helps to divide different activities in the site since any area which is smaller than 25m2 could be hard to hold any event. Secondly, a simplified result can be easier to read. The result was further organised in table 2 as demonstrated below.
19
Table 2: Results of effective level and areas. Ta result
Effect level
Effective area Distance between canopy edge : 2m(y)
Distance between canopy edge : 1m (y)
86%
0-15m ; 50-70m
0-15m ; 60-70m
83%
15-25m
15-20m
80%
25-50m
20-60m
Vw result
Effective area
Effect level
86%
45-65m
100% (no effect)
0-5m ; 40-45m ; 65-70m
120%
5-10m ; 30-40m
143%
20-30m
188%
10-20m
Distance between canopy edge : 0m(y)
0-15m ; 45-70m
20-45m
Rh result
Effective area
Effect level
45%
0-15m
54%
15-20m
58%
20-25m
20-30m
63%
25-35m
30-35m
67%
35-40m
72%
40-55m
40-45m
76%
55-60m
45-55m
81%
60-65m
55-65m
85%
65-70m
Tmrt result
Effect level
Distance between canopy edge : -1m (y)
Effective area Area under tree
Area around tree
Area between 35-65m
Area between 65-70m
72%
84%
82%
80%
20
Fig. 15: Effective level and areas. 6.2. Characterizing microclimate features in the result area Each meteorological result had been equally divided into three levels, level 1, 2 and 3. Higher level represent the level is more likely to lower the PET result, for instance, W3 compares to W1 means the area that is marked as W3 has a higher wind speed increase effect than W1. Therefore, a high levelled area could provide a more comfortable environment, for instance, the area that is marked as (W3;T2;R3;Mrt3) or (W3;T1;R3;Mrt3). After characterising the levels of each meteorological result, all results were overlapped to create a detailed microclimate feature map (figure 16). There are 14 different zones in this detailed microclimate feature map (feature 17), each zone has different microclimate feature, These features were used to fit particular requirement for various activities in a park.
21
Fig. 16: Process of characterizing microclimate feature in each area. (W: Wind speed; T: Air temperature; R: Relative humidity; Mrt: Mean radiant temperature.)
Fig. 17: Detailed microclimate feature map
22
7.0. Result
Fig. 18: Existing activities This chapter discusses which microclimate zones best fit the existing activities and the physiological characters of people who do those activities. At the moment, there are facilities for children and the elderly, an open lawn, circulate pathway and several seats. Due to the hot weather, people usually use the lawn when the sun goes down in summer. Unlike some 23
of the people who live in the temperate climate areas, people like to laying on the lawn and enjoy the sunshine. Most of the people prefer to staying in a much cooler area under trees, regardless of whether there are seats of not, therefore, some of the seats which are not covered by canopy are usually not being used. In the day time, a majority of the users are elders and children, only a few of adults or teenagers appears in the park. The activities that children have are often cycling and use the climbing frames. The elderly prefer to have a walk, jogging, running or use the exercise facilities here, but they usually just sitting under the trees, chatting with each other. There are still a few of youth who prefer running here occasionally. The settings of the existing activities and body characteristics are organised in table 3. These data were applied to the microclimate data of each microclimate zones from the previous chapter to calculate the level of thermal comfort. The calculator used in this test is a component in ladybug module called the ‘ladybug_thermal comfort indices’ which was made by Djordje Spasic and Dr Krzysztof Blazejczyk. Besides the climatology and body characteristics data, the location and hour of the year (HOY) were applied as the previous test. Table 3: Activities and body characteristics settings. Type
Activity/Metabolic rate
Age
Sex
Clothing insulation/Level
Body position
Duration
A
Exercise Equipment For The Elderly/2.6
65
Average
Summer clothing/0.55
Standing
180
B
Sitting/1.0
65
Average
Summer clothing/0.55
Sitting
180
C
Sitting/1.0
45
Average
Summer clothing/0.55
Sitting
180
D
Sitting/1.0
25
Average
Summer clothing/0.55
Sitting
180
E
Walking(3.2km/h)/2.0
65
Average
Summer clothing/0.55
Standing
180
F
Walking(3.2km/h)/2.0
45
Average
Summer clothing/0.55
Standing
180
G
Bicycling(15km/h)/4.0
10
Average
Summer clothing/0.55
Standing
180
H
Climbing Frames/6.3
10
Average
Summer clothing/0.55
Standing
180
I
Running(14.4km/h)/9.5
25
Average
Summer clothing/0.55
Standing
180
24
The result of the calculation was organised in table 4 and visualised in the same format as microclimate zones (fig.19). According to the test result, area W1; T2; R1; Mrt2 (1212), 1222, 1312, 1322 and 1131 are slightly warm for all the existing activities. However, it has improved from the original situation. In contrast, zone 2322,2233,3231,2133 are suitable for any current events and people, and the PET level result as 0, which means people would feel comfortable with doing any the existing exercise in these areas. In terms of which activity to put into as a design layout, further consideration of each activity best suits the feature of each space is needed. Secondly, although this four area appears to have the same PET level for all types, the PET data still differs massively as the highest difference to be 2.6°C PET. Zone 2323 and 3133 are also suitable for most of the typologies. However, fast paced exercises such as running and cycling are not recommended in this area. Because the wind speed here would be expected much higher, therefore, when people are doing faster-paced exercise, the relative wind speed that a person would feel will be even higher. Zone 2321 is also suitable for most of the activities, but the elderly could most probably feel too hot if they walk here. Zone 2333 is one of the coolest areas in this test, static activities such as walking, yoga or sitting are suggested. A similar result appears in zone 3233, but due to the faster wind speed here, only sitting and walking for people who aged above 40 are recommended. Table 4: Thermal comfort calculation result (PET/PET Level). Type A
Type B
Type C
Type D
Type E
Type F
Type G
Type H
Type I
W1 ; T2 ; R1 ; Mrt2
31.8/1
31.5/1
31.5/1
31.5/1
31.8/1
31.8/1
31.9/1
32.0/1
31.7/1
W1 ; T2 ; R2 ; Mrt2
31.3/1
31.0/1
31.0/1
31.0/1
31.3/1
31.3/1
31.3/1
31.4/1
31.5/1
W1 ; T3 ; R1 ; Mrt2
30.6/1
30.2/1
30.3/1
30.3/1
30.6/1
30.6/1
30.7/1
30.7/1
30.7/1
W1 ; T3 ; R2 ; Mrt2
30.4/1
30.1/1
30.1/1
30.1/1
30.4/1
30.4/1
30.5/1
30.5/1
30.5/1
W2 ; T3 ; R2 ; Mrt2
28.8/0
28.5/0
28.5/0
28.5/0
28.8/0
28.8/0
28.7/0
28.7/0
28.6/0
W2 ; T3 ; R2 ; Mrt1
29.6/0
29.4/0
29.4/0
29.4/0
30.3/1
29.7/0
29.6/0
29.6/0
29.5/0
W2 ; T3 ; R2 ; Mrt3
26.3/0
26.7/0
26.6/0
26.4/0
27.3/0
26.3/0
26.2/0
26.0/0
25.8/-1
W2 ; T2 ; R3 ; Mrt3
27.1/0
27.3/0
27.2/0
27.0/0
27.8/0
27.1/0
26.9/0
26.8/0
26.5/0
W2 ; T3 ; R3 ; Mrt3
26.0/0
26.6/0
26.4/0
26.3/0
27.1/0
26.1/0
25.9/-1
25.7/-1
25.4/-1
W3 ; T2 ; R3 ; Mrt 3
25.4/-1
26.3/0
26.1/0
25.9/-1
26.4/0
25.4/-1
25.1/-1
24.8/-1
24.4/-1
W3 ; T2 ; R3 ; Mrt1
28.6/0
28.4/0
28.4/0
28.4/0
29.3/0
28.6/0
28.4/0
28.2/0
28.0/0
W3 ; T1 ; R3 ; Mrt3
26.5/0
27.1/0
26.9/0
26.7/0
27.5/0
26.6/0
26.3/0
26.0/0
25.7/-1
W2 ; T1 ; R3 ; Mrt3
28.1/0
28.0/0
27.9/0
27.9/0
28.7/0
28.1/0
28.0/0
27.8/0
27.6/0
W1 ; T1 ; R3 ; Mrt1
32.8/1
32.5/1
32.5/1
32.5/1
32.9/1
32.8/1
32.9/1
32.9/1
33.0/1
*PET Level 1: Slightly warm ; 0 : comfortable ; -1: slightly cool 25
Fig. 19: constraints and opportunities in each microclimate zone 8.0. Conclusions and recommendations The effective area of mitigating thermal environment can extend a few meters leeward after the wind travels through the canopy covered area, this effective area differs depends on the features of the trees used. The feature can mostly rely on the LAD level, generally speaking, a tree which has a higher LAD has a greater effect on reducing the PET. However, if the LAD is too high, the wind speed under tree canopy would be too fast, and understories such as grass could not survive here. Additionally, the ground surface Tmrt around the canopy covered area will increase noticeably. The effect of reducing PET is noticeable as a single tree scenario. However, it will be much greater once the trees are located near to each other. Extending the distance between trees helps to gain better influence, but keeping the distance between each canopy among -1 to 2 meters is recommended. Because once the trees are too close to each other, the microclimate feature under the canopy would be very much like a tropical rainforest which would make people feel hot and humid. On the other hand, once the trees are located too far away from each other, the enhanced effect of mitigating the thermal environment will reduce dramatically. According to the result in fig.19, under the settings of the tests in this paper, areas which are covered by a wider arranged trees best suit most of the activities. Although the Ta, Rh and Tmrt all reduced in this test, the wind speed changes most noticeable. Also, by comparing 26
the result of zone 1322 and 2322 in table 4, with the same setting of three other climatology data, the thermal comfort level results completely differently just because the wind speed is different. Finally, the degree of wind speed change is much greater than the other three elements under a microclimate circumstances. Therefore, it is fair to believe that the wind speed is the key factor here to control PET by tree arrangement. The wind speed increases dramatically in 1.5m above ground level when the wind travels through space under trees than it recovers to its original speed. The notable point is that this noticeable increase effect does not repeat when the wind meets the next area under the trees. Therefore, expanding, enhance and maintenance of this ‘accelerating area’ is the most important strategy in a design phase. To effectively doing this, it is suggested not to arrange different activity areas alongside the same direction as the wind travels. For instance, put the areas from east to west if the incoming wind is from south or north (fig.20). Once the areas are located alongside the south-north direction when the wind comes from the south, the active area of mitigating thermal environment will only appear in the southern part. Although the north area will still have a better reduction of Ta, Rh and Tmrt, the wind speed here will not be going to be fast enough for people to feel cooler. Therefore, the effect of reducing PET will be limited in the north area.
Fig. 20: Comparison of the effectiveness of different arrangements The trees that were used in the tests in this paper are relatively bigger than what the landscape practice would use in reality. But the same result could be carried out by a combination of smaller trees because the key elements here are the LAD level and the area covered by the canopy. Here is an example of how to implement the effects from this paper in a design scheme (fig.21). 27
An initial wind speed increase area can be carried out by two layers of trees which have a larger LAD level. These trees can be arranged closer to each other to expand the canopy covered area to enhance the effect of increasing wind speed. The following area can also be a combination of two layers of trees but the second area can be located 1 to 2 meters(distance between the edge of the canopy) away from the first area to expand the total active area. The distance between the two layers in the second area can be between -1 to 2 meters. It depends on which microclimate feature a designer would like to create here. It can be zone type 2321, 2323,2333 or 3231. Zone type 2323 and 2233 are recommended because they can provide a complete contrast space atmosphere which is lighter and have a gentle wind touch to the people. Secondly, the active area of reducing PET can be expanded. According to the result organised in fig.19, which ever existing activities people have in zone 1131,1212,1222,1312 and 1322 would feel slightly warm. Therefore, A large lawn area which can offer a place at night for social use or have ball games, also small buildings such as toilet and other utility equipment or parking area which does not need PET control are recommended to be arranged in these microclimate zones. People will feel comfortable with doing any kind of activities in zone 3133 and 2133, due to a better shading effect in this area, pavement and runway for slower running or jogging can be the best choice here. Zone 3233 and 2333 are the areas which provide the lowest PET for most of the exercises. It is best to arrange a sitting area and garden with a walkway for elders. Fast paced exercise such as cycling or running is not suggested because the wind feels stronger here and the air temperature is relatively low here, staying here in a sweating body statue will not be the best idea. Zone 3231 is also suitable for most of the activities. However, fast paced exercises are recommended to be arranged here due to the Tmrt here is much stronger, so people who are cycling can pass through this area quickly to avoiding observe too much shortwave radiation. The wind feels relatively gentle and comfortable, and with a lower Tmrt here in zone 2323, it is very suitable for elders to exercise here.Finally, although the shading effect is relatively lower in zone 2322 with a lower air temperature and gentle wind force, it is recommended to input play area for children. Additionally, the open lawn area beside it can expand the playing area and have more opportunity to increase the fun elements of design.
Fig. 21:Suggested arrangement for activities 28
9.0. Universality and limitations of the present study The software used for running CFD simulation was the basic version of ENVI-MET. Because this version does not provide a PET data calculator, the PET data were calculated by a component offered by ladybug_honeybee grasshopper module. To do this, a combination of ENVI-MET data reader in the grasshopper-rhino interface was applied, but the CFD result data loaded in this system were different with the original data produced in the ENVI-MET system. Although these data were manually amended to be as close as possible to the original data, it was not completely the same. Therefore, the final PET result is not exactly accurate, compares to the PET calculator provided directly in the ENVI-MET simulation ecosystem. The test result would only be suitable for the regions which have similar climate zone and latitude. Also, the test results in this paper could be a lot hotter than other tests, because the initial input data was selected from very extreme circumstances and the simulation duration was set between 12:00 to 13:00, which is usually the hottest period in a day. However, a much more optimistic result in other region or time could be expected. Acknowledgments Many thank for Dr Luca Csepely-Knorr’s earnest guidance to help finish this paper successfully. And also, thanks for the people who created the incredible ladybug_honeybee module and selflessly release it free to the public. This module has become one of the best solutions of the study how to control outdoor thermal environment.
29
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Kaertner, A and Jahn, C. (2017) Viper Tutorial [Online] [Accessed on 10th November 2016] https://docs.google.com/presentation/d/1PPKKsQ2FTC08Wz94iiSEPUvAbKt6_VzqlfQY-LBT Dm4/edit#slide=id.p
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