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Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate

Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate Hindawi Advances in Meteorology Volume 2018, Article ID 2809649, 13 pages https://doi.org/10.1155/2018/2809649 Research Article Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate 1,2 1 3 Wei Yang, Yaolin Lin , and Chun-Qing Li School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia School of Engineering, RMIT University, Melbourne, VIC 3000, Australia Correspondence should be addressed to Yaolin Lin; yaolinlin@gmail.com Received 11 May 2018; Revised 17 July 2018; Accepted 31 July 2018; Published 29 August 2018 Academic Editor: Andreas Matzarakis Copyright © 2018 Wei Yang et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A climate-responsive landscape design can create a more livable urban microclimate with adequate human comfortability. *is paper aims to quantitatively investigate the effects of landscape design elements of pavement materials, greenery, and water bodies on urban microclimate and thermal comfort in a high-rise residential area in the tropic climate of Singapore. A comprehensive field measurement is undertaken to obtain real data on microclimate parameters for calibration of the microclimate-modeling software ENVI-met 4.0. With the calibrated ENVI-met, seven urban landscape scenarios are simulated and their effects on thermal comfort as measured by physiologically equivalent temperature (PET) are evaluated. It is found that the maximum improvement of PET reduction with suggested landscape designs is about 12 C, and high-albedo pavement materials and water bodies are not effective in reducing heat stress in hot and humid climate conditions. *e combination of shade trees over grass is the most effective landscape strategy for cooling the microclimate. *e findings from the paper can equip urban designers with knowledge and techniques to mitigate urban heat stress. *us, the effect of urban landscaping on microclimate and 1. Introduction human thermal comfort is necessary to be considered in the *e world is at its fastest pace of urbanization. Since 2008, urban design and planning process. more than half of the world’s population live in urban areas. It is acknowledged that the transfer of climatic knowl- *e trend in global population increase has led to an increase edge into planning practice is still lacking [1, 2]. Although in housing demand. Singapore has gone from one of the worst many measures to reduce urban heat stress and/or improve housing shortages in the world in the 1960s to a country outdoor thermal comfort have been proposed by various where 90% of its citizens now own their own home and researchers and at different spatial scales [2–6], their ef- homelessness is virtually eliminated—despite its population fectiveness is a subject for debate. *e main reason is that the dominant professions for urban design and planning, has tripled in the last 50 years. With success of housing policies, natural land has been replaced by artificial surfaces in namely, architecture and engineering, so far focus on the Singapore with undesirable thermal effects. *is issue, to- influence of landscaping on air and surface temperatures and gether with increasing industrialization, has caused a con- their subsequent effect on buildings [7]. However, the im- siderable deterioration of the urban environment. In tropical pact of countermeasures by urban design on urban thermal countries like Singapore, hot climate in terms of high tem- comfort cannot be described sufficiently by simple micro- perature, high humidity, and high solar radiation often causes climate factors, such as surface or air temperature. *ere are heat stress to residents, resulting in negative impact on public seven factors (or parameters) that affect human thermal health and productivity. Climate-responsive urban design can comfort in an outdoor environment. *ey are air temper- create microclimates that people experience as feeling cooler ature, air humidity, wind, solar radiation, terrestrial radia- than the prevailing climate, making urban spaces pleasant. tion, metabolic heat, and clothing insulation [8]. *e first 2 Advances in Meteorology five parameters are affected by urban environments, while the latter two are related to individual choice. At the neighborhood or community scale, landscape elements can modify not only the wind and radiation but also the air temperature and humidity [2–9]. *erefore, it is necessary to study the effect of different landscape elements on different microclimate parameters and corresponding human ther- mal comfort. In recent years, some researchers have realized that urban heat stress can be reduced through appropriate landscape design. Many field measurements and numerical simulations have been carried out to study the effect of landscape elements on urban microclimate and thermal comfort. For example, Ng et al. [5] conducted parametric studies in Hong Kong and found that proper greening may greatly improve the urban Figure 1: Study area and field measurement points at Bedok. microclimate and lower the summer urban air temperature. Yahia and Johansson [10] explored how vegetation and *e two residential quarters are in close proximity to each landscape elements affect outdoor thermal comfort for de- other with the Clearwater on the west side of Bedok Res- tached buildings in the hot dry climate of Damascus, Syria, ervoir View Road and Aquarius By *e Park on the east side and found that PET (physiologically equivalent temperature) of the road. Buildings in the studied residential quarters are can be reduced by about 19 C for east-west street orientation of 4 to 18 storeys. An urban park is located in the vicinity of through appropriate landscape design. Perini and Magliocco the two residential quarters on the north. [11] investigated effects of vegetation, urban density, building height, and atmospheric conditions on local temperatures and thermal comfort in three different cities in Italy and found 2.2. Field Measurements. Field measurements were con- that vegetation has higher cooling effects with taller buildings. ducted at the study area from 13 April to 06 June 2012. *e Lee et al. [12] studied the potential of urban green coverage to purpose of field measurements is to validate ENVI-met mitigate human heat stress using the ENVI-met model and modeling (see below) results and also help define the ini- found that trees are more effective in mitigating human heat tial conditions of the general model of ENVI-met. stress than just grasslands. Yahia et al. [2] investigated the Five measurement points were stationed as shown in relationship between urban design, urban microclimate, and Figure 1. *e measurement points were selected to represent outdoor comfort in four built-up areas with different mor- variations in urban geometry, ground thermal properties, phologies and found that the use of dense trees helps to reduce and greenery as shown in Figure 2. Points 1 and 2 are in the heat stress, but vegetation might negatively affect the wind urban park, and points 3, 4, and 5 are in a high-density ventilation. apartment area. *e sky view factor (SVF) ranges from Although the previous studies have added new knowledge highly shaded point 2 (SVF � 0.17) to less shaded point 5 and provided new insights, they have mainly focused on the (SVF � 0.67). *e measured microclimatic parameters are air street design like street orientation, street greenery, and street temperature, globe temperature, relative humidity, and wind geometry [3–5, 10, 13]. Little research has been conducted in speed, which were measured for 24 hours continuously and urban residential areas, particularly in those with high-rise taken at 2.0 m above the ground level. Table 1 shows the residential areas. *e microclimate quality of outdoor spaces measured microclimatic parameters and equipment used for in a residential area affects the quality of life of its residents. the field measurements. *erefore, the aim of this paper is to investigate how land- scape elements affect urban microclimate and human thermal comfort in a high-rise residential area in Singapore by in- 2.3. Microclimate Simulation. For this study, the thermal vestigating different landscape design scenarios of pavement characteristics of different urban design scenarios were in- materials, greenery, and water bodies. Studying the re- vestigated by ENVI-met 4.0 [14, 15]. *is is a microclimate lationship between landscaping and microclimate in cities like analysis program that simulates the thermal characteristics Singapore can provide valuable guidance, both for keeping and energy fluxes in the built environment with high spatial Singapore residents cool and informing temperate-climate and temporal resolution. *e model generates a large cities that would be much warmer in the future. amount of output data including necessary variables for calculation of thermal stress indices. It has been employed by many researchers to study the effects of different urban 2. Materials and Methods design options on microclimate and outdoor thermal 2.1. Study Area. *e study area is two residential quarters at comfort [1–4,10–13]. ENVI-met 4.0 allows users to employ Bedok in southeast Singapore as shown in Figure 1. Bedok is the measured meteorological data as inputs by forcing the an urban residential zone for new development in Singapore. model to follow user’s inputs during the simulation. In the *e two residential quarters are condominiums named the previous versions of ENVI-met, only relatively simple Clearwater and Aquarius By *e Park near Bedok Reservoir. weather profiles as prescribed by ENVI-met can be used as Advances in Meteorology 3 (a) (b) (c) (d) (e) Figure 2: Photos and fisheye photos for each location (measurements were taken at 2.0 m above the ground level). (a) Point 1 (SVF � 0.61). (b) Point 2 (SVF � 0.17). (c) Point 3 (SVF � 0.48). (d) Point 4 (SVF � 0.66). (e) Point 5 (SVF � 0.67). inputs. *e details of the ENVI-met model have been fully station and from the on-site observation were used to explained and presented on its website [15] and in many generate the “forcing file” (as inputs) for the simulation. It research papers [1, 4, 14, 16]. was observed that the weather condition during the mea- *e weather data from the nearest station at the Changyi surement period was characterized by high temperature, Airport were selected. It was found that the daily air tem- strong solar radiation, and light wind with a prevailing perature on April 30, 2012, was the highest during the study wind direction of southwest. *e model was run for 18 h period. *erefore, the simulation study was conducted on starting at 4 am and ending at 10 pm for each simulation of that day. *e hourly meteorological data from the weather microclimate. 4 Advances in Meteorology Table 1: Equipment used for field measurement. Variable Instrument Accuracy Air temperature/ ° ° ° HOBO U12-012 Temp/RH Data Logger ±0.35 C from 0 C–50 C to a maximum of ±3.5% relative humidity HOBO *ermocouple Data Logger, U12-014 with Globe temperature Type-T Copper-Constantan thermocouple sensors ±1.5 C and 40 mm diameter ping pong ball Wind speed Onset Wind Speed Smart Sensor, S-WSA-M003 ±1.1 m/s or ±4% of reading, whichever is greater Pyranometer: <5% uncertainty (95% confidence level) Short- and Kipp & Zonen, CNR 4 with integrated pyranometer, Pyrgeometer: <10% uncertainty (95% confidence level) long-wave radiation pyrgeometer, Pt-100, and thermistor Pt-100/thermistor: ±0.7 C 2.4. Parametric Study and Urban +ermal Comfort Assessment. *e parametric study consists of a base case and seven design scenarios. *e base case was constructed according to the actual conditions of the study area. *e model domain covers the entire area of the study area and is expanded to the surrounding buildings, streets, and an urban park. *e spatial extent of the study area is 600 × 392 ×120 m in the X, Y, and Z dimensions, respectively. *e horizontal and vertical grid resolutions are both set at 4 m. *e model domain of the base case for the study area is shown in Figure 3. *e input data of the general model setting, the initial atmospheric/soil condition, and the building properties are summarized in Table 2. *e other scenarios to be investigated are designed based on changing different landscape elements such as pavement Figure 3: Model domain for the study area. materials (brick, concrete, wood, and light-color granite) and amount of trees, grass, and water bodies as listed in Table 3. For the first 5 scenarios, only one parameter is Table 2: Boundary conditions and initial setting of the ENVI-met changed at a time in order to determine the relative effect of model. each. *e last two scenarios are a combination of two design ° ° Location Singapore 103 51′E, 1 18′N elements to further investigate the effect of ground materials Climate Tropical climate and tree shading. Date/time From 04:00 to 22:00 (18 h) on 30 April 2012 For the assessment of urban thermal comfort, the PET simulated (physiologically equivalent temperature) is selected as the Bedok: 150 × 98 × 30 grids thermal comfort index. PET has been calibrated against Model domain Δx � Δy � Δz � 4m subjective thermal sensation evaluation by Yang et al. [17] in Note: vertical grid with the equidistant method Air temperature and relative humidity: hourly Singapore (Table 4), which makes it possible to compare data from the measurement on-site different urban design proposals. Tropical residents are Meteorological Wind speed and direction: hourly data from the found to tolerate higher levels of PET than Western/Middle inputs meteorological station European residents due to thermal adaption to the local Specific humidity (2500 m) � 7 g/kg climate. PET is calculated using the RayMan model [18, 19]. Initial soil Upper layer (0–20 cm): 305 K/30% It can be easily estimated with air temperature, relative temperature and Middle layer (20–50 cm): 307 K/40% humidity, wind speed, mean radiant temperature, clothing, relative humidity Deeper layer (below 50 cm): 306 K/50% and activity level of people. *e thermal comfort map in Inside temperature � 293 K (constant) terms of PET is generated in the paper for comparison. Heat transmission walls � 1.94 W/m ·K Building Heat transmission roofs � 6 W/m ·K conditions Albedo walls � 0.2 3. Results and Discussion Albedo roofs � 0.3 Trees: 10 m dense, leafless base 3.1. +e Base Case Scenario: Measurement and Simulation. Plants Trees: 20 m dense, leafless base *e microclimatic parameters of air temperature, mean Grass: 20 cm average dense radiant temperature, wind speed, and relative humidity collected at measuring points 1–5 have been compared with the corresponding ENVI-met model outputs. trend for all five points with perhaps more smooth curves Figure 4 shows the comparison between measured for the simulated ones. *e air temperature pattern is and simulated air temperatures. It can be seen that the clearly influenced by the sky view factor and surrounding simulated and measured air temperatures have the same urban environment. Point 2 has the lowest air temperature Advances in Meteorology 5 Table 3: Di…erent design scenarios for Bedok. Design scenario Pavement materials Vegetation and water body Sparse trees and grass Base case Red brick (ID: KK) and concrete pavement (ID: PP) Small area of water bodies (30 m ) Scenario 1 Wooden boards (ID: WD) As base case Scenario 2 Light-color granite (ID: G2) As base case Scenario 3 Grass surface As base case Scenario 4 As base case Add more trees (increase by 200%) Scenario 5 As base case Add more water bodies (increase by 200%) Scenario 6 Light-color granite (ID: G2) Add more trees (increase by 200%) Scenario 7 Grass surface Add more trees (increase by 200%) (mesoscale) e…ects are not taken into account [15]. During the Table 4: „ermal sensations and PET classes for Singapore and Western/Middle Europe. night, the air temperature is underestimated by up to 0.5 C and overestimated by up to 0.3 C with ENVI-met in this study. PET range for „ermal PET range for „e mean radiant temperature comparison between Western/Middle sensation Singapore ( C) simulated and measured results is shown in Figure 5. It can be Europe ( C) seen that the simulated and measured mean radiant tem- Very cold Not applicable <4 peratures have the same trend for all the points. Points 3, 4, Cold Not applicable 4–8 and 5 have a higher mean radiant temperature proŠle than Cool Not applicable 8–13 points 1 and 2 during the day. „is is because points 1 and 2 Slightly cool 20–24 13–18 Neutral 24–30 18–23 are located in the park and have lower sky view factors. It can Slightly warm 30–34 23–29 also be found that the daytime mean radiant temperature is Warm 34–38 29–35 overestimated and nighttime mean radiant temperature is Hot 38–42 35–41 underestimated by ENVI-met. „e daytime di…erence is Very hot >42 >41 about 0.1–6.7 C, and the nighttime di…erence is about 2.6– Source: Yang et al. [17]. ° 6.6 C. A number of other studies have also reported a mean radiant temperature di…erence of up to 7.97 C between the measured and simulated results [1, 4, 13, 20]. „e discrep- 35.0 ancies are due to that ENVI-met does not consider heat 34.0 storage and transfer by buildings or anthropogenic heat production in an adequate manner [13, 21]. „erefore, studies 33.0 on the e…ect of landscape design on nighttime outdoor 32.0 thermal comfort and urban heat island need further in- vestigation in the future due to limitations of ENVI-met 31.0 modeling. 30.0 „e results of the measured and simulated wind speed and relative humidity show little di…erence (less than 5%) for 29.0 all the points. „e input wind speed is less than 2 m/s in this 28.0 study. It has also been reported that wind speeds predicted 10 11 12 13 14 15 16 17 18 19 20 21 22 by ENVI-met are consistent with Šeld data for input wind (Time) speeds below 2 m/s [22]. P1 measured P1 simulated Tables 5 and 6 show the model Št between simulated and P2 measured P2 simulated measured results for air temperature and mean radiant P3 measured P3 simulated temperature, respectively. Very high overall agreement can P4 measured P4 simulated be found for both air temperature (R between 0.95 and 0.99) P5 measured P5 simulated and mean radiant temperature (R between 0.74 and 0.96). Figure 4: Comparison between simulated and measured air 2 „e relatively lower model Št of R  0.74 for point 2 as well temperatures. as the 5 C di…erence between simulated and measured re- sults in terms of mean radiant temperature can be partially because it is located in the nearby park and has a low sky explained by the error in the measurement; for example, view factor (0.17). solar radiation suddenly became very intense during that Points 3, 4, and 5 have higher air temperatures than points particular measurement time. 1 and 2 because these three points are located along high- „erefore it is possible to say that although there are density residential buildings. It can also be seen that ENVI-met some discrepancies between the simulated and measured underestimates the daytime air temperature by about 0.1– results, ENVI-met is able to present similar trends for mi- 0.7 C. „is is because ENVI-met calculates the urban climate at croclimatic parameters compared with those from Šeld a microscale or a local scale and that larger regional measurement. Compared with a former study conducted in Air temperature difference (°C) 6 Advances in Meteorology 10 11 12 13 14 15 16 17 18 19 20 21 22 (Time) P1 measured P1 simulated P2 measured P2 simulated P3 measured P3 simulated P4 measured P4 simulated P5 measured P5 simulated Figure 5: Comparison between simulated and measured mean radiant temperatures. Table 5: Model Št between simulated and measured results for air temperature. is at 3 pm on the simulation day. „erefore, the e…ects of di…erent landscape design scenarios on microclimate and Point Point Point Point Point 1 2 3 4 5 thermal comfort are compared based on results at 3 pm. Except for the surface temperature, the other microclimate Minimum error ( C) 0 −0.1 0 0.01 0.03 Maximum error ( C) −0.67 −0.63 −0.68 −0.72 −0.67 parameters are compared at 2.0 m above the ground level. Mean error ( C) −0.16 −0.19 −0.31 −0.41 −0.28 Standard deviation ( C) 0.21 0.26 0.20 0.23 0.30 R 0.98 0.97 0.99 0.99 0.95 3.2.1. Surface Temperature and Air Temperature. Figure 6 RMSE ( C) 0.27 0.32 0.37 0.47 0.41 shows the surface temperature patterns for all design sce- narios. „e di…erences in surface temperatures are obvious. Pavement with light-color granite (Scenario 2) has the lowest Table 6: Model Št between simulated and measured results for mean radiant temperature. surface temperature, with a maximum reduction of 12 C compared with the base case. Surface temperature reduction Point Point Point Point Point by grass surfacing (Scenario 3) and adding more trees 1 2 3 4 5 (Scenario 4) is also obvious, with a reduction by up to 8 C for Minimum error ( C) 0 0.71 0.01 0.81 −0.07 grass and 10 C for trees. Maximum error ( C) −4.23 6.24 6.78 −6.25 −6.59 Surface temperature reduction by applying wood pave- Mean error ( C) 0.08 1.10 0.88 −1.13 −0.6 ment (Scenario 1) can be up to 6 C. Not much di…erence in Standard deviation ( C) 3.16 3.35 4.97 4.34 4.52 surface temperature can be found by adding more water R 0.96 0.74 0.95 0.91 0.94 RMSE ( C) 3.16 3.56 5.05 4.49 4.56 bodies. Both Scenario 6 (combination of light-color granite and adding more trees) and Scenario 7 (combination of grass surfacing and adding more trees) resulted in a signiŠcant Singapore [13], it can also be seen that the new ENVI-met reduction of surface temperature. However, Scenario 6 is more model of version 4.0 shows much better performance than e…ective in reducing the surface temperature than Scenario 7. the previous version of ENVI-met 3.1. Since the thermal Figure 7 shows the air temperature patterns for all design performance of di…erent urban geometries and ground scenarios. „e di…erences in air temperature between di…erent surface and their e…ect on mean radiant temperature can be scenarios are not so obvious as those in the surface temper- modeled by ENVI-met, a relative comparison can be made ature. „e air temperature is about 0.25–0.75 C lower for the for di…erent design scenarios. In addition, the simulated scenarios with light-color granite compared with the base case. results have been calibrated with Šeld measurement data and For scenarios with grass surfacing and more trees, the air then used as a benchmark for investigation of changes in temperature reduction is about 0.25–0.5 C. For wood scenario, design. „erefore, all the changes in design are consistent the apparent reduction of 6 C of the temperature at the surface and relative to the simulated case, whereby the error from does not cause a signiŠcant reduction in local air temperature calibration has been e…ectively eliminated. at 2.0 m above the ground level. However, the air temperature of areas under building shade for the wood scenario is about 3.2. Microclimate Dierences. It has been found from both 0.25 C lower than that in the base case. Scenario 6 and Scenario the measurement and simulation results that the hottest time 7 both cause an air temperature reduction by up to 0.75 C. Mean radiant temperature difference (°C) Advances in Meteorology 7 T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (a) (b) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (c) (d) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (e) (f) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (g) (h) Figure 6: Simulated surface temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). Not much di…erence in air temperature can be found for Singapore in the current study. „is is in agreement with the scenario of adding more water bodies. Water bodies are a Šeld measurement study conducted by Wong et al. [23] found to be not e…ective in decreasing the air temperature in who investigated the evaporative cooling performance of Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 8 Advances in Meteorology Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 48 48 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (a) (b) Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (c) (d) Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 48 48 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (e) (f) Air temperature Air temperature Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 33.00 to 33.25 °C 33.00 to 33.25 °C 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (g) (h) Figure 7: Simulated air temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). a waterway in Singapore and found that the air temperature 3.2.2. Mean Radiant Temperature. „e patterns of mean was merely reduced by 0.1 C on every 30 m away from the radiant temperature for all design scenarios are presented in waterway. „e high humidity climate and low wind con- Figure 8. For sunlit places, the mean radiant temperatures dition might be one of the possible reasons for it. are 50–54 C for all scenarios except the grass surface Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Advances in Meteorology 9 Mean radiant temp. Mean radiant temp. Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (a) (b) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 38 38 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (c) (d) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (e) (f) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 38 38 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (g) (h) Figure 8: Simulated mean radiant temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light- color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). scenarios, which have mean radiant temperatures 4–8 C both the wood and light-color granite scenarios, the mean lower than other scenarios. For places shaded by buildings, radiant temperatures are 4–8 C higher than those of the base di…erences in mean radiant temperature are obvious. For case. For the tree scenarios, there is a signiŠcant cooling Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 10 Advances in Meteorology effect and the mean radiant temperature under tree-shaded scenario has different pavement materials. Again adding more areas can be reduced by 12–16 C compared with sunlit areas. water bodies is found to have little effect on PET. Scenario 7 (combination of grass surface and more trees) is the best with 4–8 C mean radiant temperature reduction for 4. Discussion areas exposed to the sun and 12–16 C reduction for tree- shaded areas. Not much difference can be found for the Table 7 summarizes the effect of different design scenarios scenario of adding more water bodies. on microclimate and human thermal comfort (PET). *e results from ENVI-met indicate that the change of It can be seen that design strategies that can reduce pavement materials has a minor effect on reducing mean surface temperature and air temperature may not necessarily radiant temperature for places exposed to high solar radi- reduce heat stress condition. Design strategies such as ap- ation. For places shaded by buildings, the mean radiant plying wooden boards and light-color granite have some temperature is even increased by using high-albedo pave- extent of cooling effect, but heat stress is marginally reduced. ment materials. *is is consistent with other studies which Both the wooden board and light-color granite are high- also found increases of mean radiant temperature by ap- albedo materials with an albedo of 0.8 in this study. While plying high-albedo materials [4, 16, 24] in hot and humid higher albedo reduces the surface temperatures, and con- climates. sequently, the air temperature, it increases the amount of reflected short-wave radiation in the environment at the same time. As it is known, the increase of energy flux will result in the increase of mean radiant temperature. Mean 3.2.3. Wind Speed and Relative Humidity. Due to the radiant temperature is the main factor affecting outdoor small differences between different design scenarios in thermal comfort in hot and humid climate as in Singapore terms of wind speed and relative humidity, the figures are [17]. *us, the insignificant effect of high-albedo materials not shown here. *e results show that wind speed is on reducing heat stress can be expected. However, the ef- slightly reduced by 0.2 m/s with more trees planting. *e fectiveness of high-albedo covering on heat stress is disputed differences in wind speed are not obvious for other design because PET does not take surface temperature into con- scenarios. *is is because the layout of building blocks sideration. *e decrease of surface temperature is not re- has been determined in the residential quarters for this flected in PET, which raises a question of whether surface study. Compared with landscape elements, the layout of temperature has an effect on urban thermal comfort. Dif- building blocks has greater effect on air flow in urban ferent from the indoor environment which has uniform and spaces. relative lower surface temperatures, outdoor space has As to the relative humidity, scenarios with grass surface, a large variation and fluctuation of surface temperatures. *e more trees, and water bodies are more humid, with an evaluation of urban thermal comfort is a challenging topic in increase of 4% to 6% compared with the base case. *e the research field of human bioclimate, which still needs change of landscape elements cannot lead to significant further study. variation of relative humidity when the humidity is very high Water can mitigate the urban heat island effect since throughout the year. *is is the climate in Singapore, and more incoming heat can be transformed into latent heat hence, the results make sense. rather than sensible heat. However, water bodies are found to be not effective in mitigating heat stress in hot and humid climate as studied in this paper. Adding more water bodies 3.3. +ermal Comfort Maps of PET. Figure 9 shows the does not change any microclimate parameters except that simulated thermal comfort (PET) maps for all the design humidity increases slightly. *is may be because the area of scenarios at 3 pm. *e PET values of sunlit places for all the water bodies in this study is not large enough to create design scenarios are dominated by extremely hot condition a cooling effect for the surrounding environment. Besides, with the PET between 46 and 50 C, which is under severe due to the high humidity conditions in Singapore, thermal heat stress and far above the comfortable temperature range comfort cannot benefit too much from the evaporation from (24–30 C) required for Singapore occupants (Table 4). Al- water bodies. It has been widely accepted that shading is the key though thermal comfort is difficult to achieve under such hot climate conditions, some improvements can be made strategy for promoting outdoor thermal comfort in hot climate. Interception of solar radiation is the most effective through landscape design. *e best thermal conditions are in the areas with means in improving thermal comfort in outdoor areas in hot and dry climate [6]. *e current study also vindicates this shading, either shaded by buildings or trees, with a PET of 34–38 C, which corresponds to “warm” according to Table 4. design principle because the scenarios shaded by more trees *e shade enhancement by trees or buildings has a clear have the best thermal comfort condition, with the maximum positive effect on alleviating outdoor heat stress, as indicated PET reduced by 12 C. However, not much difference is by decreased PET. found for scenarios with trees (Scenario 4, 6, and 7) in terms Scenario 3 (grass surface) only leads to a PETreduction of of urban heat stress even though each scenario has different 4–8 C for limited areas, and the heat stress conditions for pavement materials. Different pavement materials can lead most of the study areas are not improved. Scenarios with trees to variations in surface temperature, air temperature, and (4, 6, and 7) have the same PET patterns despite that each mean radiant temperature in urban spaces, but these Advances in Meteorology 11 PET PET Below 30.00 °C 98 Below 30.00 °C 30.00 to 34.00 °C 88 30.00 to 34.00 °C 34.00 to 38.00 °C 78 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (a) (b) PET PET Below 30.00 °C 98 Below 30.00 °C 30.00 to 34.00 °C 88 30.00 to 34.00 °C 34.00 to 38.00 °C 78 34.00 to 38.00 °C 38.00 to 42.00 °C 68 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (c) (d) PET PET Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C X (4m) X (4m) (e) (f) PET PET Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (g) (h) Figure 9: Simulated PET for all the design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 12 Advances in Meteorology Table 7: Summary of the effect of different design scenarios on urban microclimate and thermal comfort (PET). Surface temp. Air temp. PET Design scenarios Mean radiant temp. reduction reduction reduction reduction 0–0.25 C for ° ° 1 Wooden boards 2–6 C −8 to −4 C for building-shaded areas No change building-shaded areas ° ° ° 2 Light-color granite 2–12 C 0.25–0.75 C −8 to −4 C for building-shaded areas No change 4–8 C for ° ° ° 3 Grass surface 2–8 C 0.25–0.5 C 4–8 C for areas exposed to the sun limited areas ° ° ° ° 4 More trees 2–10 C 0.25–0.5 C 12–16 C for tree-shaded areas 4–12 C 5 More water bodies No change No change No change No change Light-color granite −8 to −4 C for building-shaded areas ° ° ° 6 2–12 C 0.25–0.75 C 4–12 C and more trees 12–16 C for tree-shaded areas Grass surface 4–8 C for areas exposed to the sun ° ° ° 7 2–10 C 0.25–0.75 C 4–12 C and more trees 12–16 C for tree-shaded areas variations may not be effective enough to reduce heat stress the maximum surface temperature reduced by 10 C, air during the daytime. However, during the night, the effect of temperature reduced by 0.75 C, mean radiant temperature ° ° different pavement materials on thermal comfort can be reduced by 16 C, and PET reduced by 12 C. Although high- obvious because different materials have different thermal albedo pavement materials and water bodies are found not properties. In addition, air temperature is the main factor effective in reducing heat stress in hot and humid climate that affects urban thermal comfort during the nighttime. It conditions, the results are dubious since the evaluation of needs to be noted that due to time constraints and limita- urban thermal comfort does not include the surface tem- tions of ENVI-met modeling, nighttime thermal comfort is perature. *e evaluation of urban thermal comfort is not investigated in this study. a challenging topic in the research field of human bioclimate, Compared with grass surfacing, tree planting is a more which still needs further study. It can be concluded that the effective strategy to promote shading, thus reducing urban findings from the paper can equip urban planners and heat stress. Although tree planting would lead to an increase designers with knowledge and techniques when they plan for of relative humidity and a decrease of wind speed, those future urban areas/regions and replan for existing urban negative effects are minor compared with the positive effects areas/regions so as to mitigate urban heat stress. However, of reduction of air temperature and mean radiant temper- due to the limitations of ENVI-met modeling, the effect of ature. As predicted, the combination of shade trees over landscape design on nighttime thermal comfort and urban grass is found to be the most effective landscape strategy in heat island requires further investigation in the future. terms of cooling provided, with the maximum surface temperature reduced by 10 C, air temperature reduced by Data Availability ° ° 0.75 C, mean radiant temperature reduced by 16 C, and PET ° *e data used to support the findings of this study are reduced by 12 C. available from the corresponding author upon request. 5. Conclusions Conflicts of Interest *e effects of urban landscape design on urban microclimate *e authors declare that they have no conflicts of interest. and thermal comfort in a high-rise residential area in the tropic climate of Singapore have been investigated in this Acknowledgments paper. Various landscape elements of pavement materials, greenery, and water bodies have been studied. Real data on *is work was supported by the NUS Research Scholarship microclimate obtained from a comprehensive field mea- from the National University of Singapore and Natural surement with multiple points have been presented and used Science Foundation of Hubei Province, China, under Grant to calibrate the new version of the microclimate-modeling number 2015CFB510. *e authors would like to express software EVNI-met. With the calibrated ENVI-met, seven their sincere thanks to Professor Wong Nuyk Hien and his urban design scenarios of different surface albedo, greenery, Ph.D. students from the National University of Singapore and water bodies have been simulated with different mi- for their assistance in the field measurement work of this croclimatic parameters, and their effects on human thermal paper. comfort as measured by PET have been evaluated. 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Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate

Yang, Wei; Lin, Yaolin; Li, Chun-Qing
Advances in Meteorology , Volume 2018: 13 – Aug 29, 2018
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Hindawi Publishing Corporation
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Copyright © 2018 Wei Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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1687-9309
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10.1155/2018/2809649
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Hindawi Advances in Meteorology Volume 2018, Article ID 2809649, 13 pages https://doi.org/10.1155/2018/2809649 Research Article Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate 1,2 1 3 Wei Yang, Yaolin Lin , and Chun-Qing Li School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia School of Engineering, RMIT University, Melbourne, VIC 3000, Australia Correspondence should be addressed to Yaolin Lin; yaolinlin@gmail.com Received 11 May 2018; Revised 17 July 2018; Accepted 31 July 2018; Published 29 August 2018 Academic Editor: Andreas Matzarakis Copyright © 2018 Wei Yang et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A climate-responsive landscape design can create a more livable urban microclimate with adequate human comfortability. *is paper aims to quantitatively investigate the effects of landscape design elements of pavement materials, greenery, and water bodies on urban microclimate and thermal comfort in a high-rise residential area in the tropic climate of Singapore. A comprehensive field measurement is undertaken to obtain real data on microclimate parameters for calibration of the microclimate-modeling software ENVI-met 4.0. With the calibrated ENVI-met, seven urban landscape scenarios are simulated and their effects on thermal comfort as measured by physiologically equivalent temperature (PET) are evaluated. It is found that the maximum improvement of PET reduction with suggested landscape designs is about 12 C, and high-albedo pavement materials and water bodies are not effective in reducing heat stress in hot and humid climate conditions. *e combination of shade trees over grass is the most effective landscape strategy for cooling the microclimate. *e findings from the paper can equip urban designers with knowledge and techniques to mitigate urban heat stress. *us, the effect of urban landscaping on microclimate and 1. Introduction human thermal comfort is necessary to be considered in the *e world is at its fastest pace of urbanization. Since 2008, urban design and planning process. more than half of the world’s population live in urban areas. It is acknowledged that the transfer of climatic knowl- *e trend in global population increase has led to an increase edge into planning practice is still lacking [1, 2]. Although in housing demand. Singapore has gone from one of the worst many measures to reduce urban heat stress and/or improve housing shortages in the world in the 1960s to a country outdoor thermal comfort have been proposed by various where 90% of its citizens now own their own home and researchers and at different spatial scales [2–6], their ef- homelessness is virtually eliminated—despite its population fectiveness is a subject for debate. *e main reason is that the dominant professions for urban design and planning, has tripled in the last 50 years. With success of housing policies, natural land has been replaced by artificial surfaces in namely, architecture and engineering, so far focus on the Singapore with undesirable thermal effects. *is issue, to- influence of landscaping on air and surface temperatures and gether with increasing industrialization, has caused a con- their subsequent effect on buildings [7]. However, the im- siderable deterioration of the urban environment. In tropical pact of countermeasures by urban design on urban thermal countries like Singapore, hot climate in terms of high tem- comfort cannot be described sufficiently by simple micro- perature, high humidity, and high solar radiation often causes climate factors, such as surface or air temperature. *ere are heat stress to residents, resulting in negative impact on public seven factors (or parameters) that affect human thermal health and productivity. Climate-responsive urban design can comfort in an outdoor environment. *ey are air temper- create microclimates that people experience as feeling cooler ature, air humidity, wind, solar radiation, terrestrial radia- than the prevailing climate, making urban spaces pleasant. tion, metabolic heat, and clothing insulation [8]. *e first 2 Advances in Meteorology five parameters are affected by urban environments, while the latter two are related to individual choice. At the neighborhood or community scale, landscape elements can modify not only the wind and radiation but also the air temperature and humidity [2–9]. *erefore, it is necessary to study the effect of different landscape elements on different microclimate parameters and corresponding human ther- mal comfort. In recent years, some researchers have realized that urban heat stress can be reduced through appropriate landscape design. Many field measurements and numerical simulations have been carried out to study the effect of landscape elements on urban microclimate and thermal comfort. For example, Ng et al. [5] conducted parametric studies in Hong Kong and found that proper greening may greatly improve the urban Figure 1: Study area and field measurement points at Bedok. microclimate and lower the summer urban air temperature. Yahia and Johansson [10] explored how vegetation and *e two residential quarters are in close proximity to each landscape elements affect outdoor thermal comfort for de- other with the Clearwater on the west side of Bedok Res- tached buildings in the hot dry climate of Damascus, Syria, ervoir View Road and Aquarius By *e Park on the east side and found that PET (physiologically equivalent temperature) of the road. Buildings in the studied residential quarters are can be reduced by about 19 C for east-west street orientation of 4 to 18 storeys. An urban park is located in the vicinity of through appropriate landscape design. Perini and Magliocco the two residential quarters on the north. [11] investigated effects of vegetation, urban density, building height, and atmospheric conditions on local temperatures and thermal comfort in three different cities in Italy and found 2.2. Field Measurements. Field measurements were con- that vegetation has higher cooling effects with taller buildings. ducted at the study area from 13 April to 06 June 2012. *e Lee et al. [12] studied the potential of urban green coverage to purpose of field measurements is to validate ENVI-met mitigate human heat stress using the ENVI-met model and modeling (see below) results and also help define the ini- found that trees are more effective in mitigating human heat tial conditions of the general model of ENVI-met. stress than just grasslands. Yahia et al. [2] investigated the Five measurement points were stationed as shown in relationship between urban design, urban microclimate, and Figure 1. *e measurement points were selected to represent outdoor comfort in four built-up areas with different mor- variations in urban geometry, ground thermal properties, phologies and found that the use of dense trees helps to reduce and greenery as shown in Figure 2. Points 1 and 2 are in the heat stress, but vegetation might negatively affect the wind urban park, and points 3, 4, and 5 are in a high-density ventilation. apartment area. *e sky view factor (SVF) ranges from Although the previous studies have added new knowledge highly shaded point 2 (SVF � 0.17) to less shaded point 5 and provided new insights, they have mainly focused on the (SVF � 0.67). *e measured microclimatic parameters are air street design like street orientation, street greenery, and street temperature, globe temperature, relative humidity, and wind geometry [3–5, 10, 13]. Little research has been conducted in speed, which were measured for 24 hours continuously and urban residential areas, particularly in those with high-rise taken at 2.0 m above the ground level. Table 1 shows the residential areas. *e microclimate quality of outdoor spaces measured microclimatic parameters and equipment used for in a residential area affects the quality of life of its residents. the field measurements. *erefore, the aim of this paper is to investigate how land- scape elements affect urban microclimate and human thermal comfort in a high-rise residential area in Singapore by in- 2.3. Microclimate Simulation. For this study, the thermal vestigating different landscape design scenarios of pavement characteristics of different urban design scenarios were in- materials, greenery, and water bodies. Studying the re- vestigated by ENVI-met 4.0 [14, 15]. *is is a microclimate lationship between landscaping and microclimate in cities like analysis program that simulates the thermal characteristics Singapore can provide valuable guidance, both for keeping and energy fluxes in the built environment with high spatial Singapore residents cool and informing temperate-climate and temporal resolution. *e model generates a large cities that would be much warmer in the future. amount of output data including necessary variables for calculation of thermal stress indices. It has been employed by many researchers to study the effects of different urban 2. Materials and Methods design options on microclimate and outdoor thermal 2.1. Study Area. *e study area is two residential quarters at comfort [1–4,10–13]. ENVI-met 4.0 allows users to employ Bedok in southeast Singapore as shown in Figure 1. Bedok is the measured meteorological data as inputs by forcing the an urban residential zone for new development in Singapore. model to follow user’s inputs during the simulation. In the *e two residential quarters are condominiums named the previous versions of ENVI-met, only relatively simple Clearwater and Aquarius By *e Park near Bedok Reservoir. weather profiles as prescribed by ENVI-met can be used as Advances in Meteorology 3 (a) (b) (c) (d) (e) Figure 2: Photos and fisheye photos for each location (measurements were taken at 2.0 m above the ground level). (a) Point 1 (SVF � 0.61). (b) Point 2 (SVF � 0.17). (c) Point 3 (SVF � 0.48). (d) Point 4 (SVF � 0.66). (e) Point 5 (SVF � 0.67). inputs. *e details of the ENVI-met model have been fully station and from the on-site observation were used to explained and presented on its website [15] and in many generate the “forcing file” (as inputs) for the simulation. It research papers [1, 4, 14, 16]. was observed that the weather condition during the mea- *e weather data from the nearest station at the Changyi surement period was characterized by high temperature, Airport were selected. It was found that the daily air tem- strong solar radiation, and light wind with a prevailing perature on April 30, 2012, was the highest during the study wind direction of southwest. *e model was run for 18 h period. *erefore, the simulation study was conducted on starting at 4 am and ending at 10 pm for each simulation of that day. *e hourly meteorological data from the weather microclimate. 4 Advances in Meteorology Table 1: Equipment used for field measurement. Variable Instrument Accuracy Air temperature/ ° ° ° HOBO U12-012 Temp/RH Data Logger ±0.35 C from 0 C–50 C to a maximum of ±3.5% relative humidity HOBO *ermocouple Data Logger, U12-014 with Globe temperature Type-T Copper-Constantan thermocouple sensors ±1.5 C and 40 mm diameter ping pong ball Wind speed Onset Wind Speed Smart Sensor, S-WSA-M003 ±1.1 m/s or ±4% of reading, whichever is greater Pyranometer: <5% uncertainty (95% confidence level) Short- and Kipp & Zonen, CNR 4 with integrated pyranometer, Pyrgeometer: <10% uncertainty (95% confidence level) long-wave radiation pyrgeometer, Pt-100, and thermistor Pt-100/thermistor: ±0.7 C 2.4. Parametric Study and Urban +ermal Comfort Assessment. *e parametric study consists of a base case and seven design scenarios. *e base case was constructed according to the actual conditions of the study area. *e model domain covers the entire area of the study area and is expanded to the surrounding buildings, streets, and an urban park. *e spatial extent of the study area is 600 × 392 ×120 m in the X, Y, and Z dimensions, respectively. *e horizontal and vertical grid resolutions are both set at 4 m. *e model domain of the base case for the study area is shown in Figure 3. *e input data of the general model setting, the initial atmospheric/soil condition, and the building properties are summarized in Table 2. *e other scenarios to be investigated are designed based on changing different landscape elements such as pavement Figure 3: Model domain for the study area. materials (brick, concrete, wood, and light-color granite) and amount of trees, grass, and water bodies as listed in Table 3. For the first 5 scenarios, only one parameter is Table 2: Boundary conditions and initial setting of the ENVI-met changed at a time in order to determine the relative effect of model. each. *e last two scenarios are a combination of two design ° ° Location Singapore 103 51′E, 1 18′N elements to further investigate the effect of ground materials Climate Tropical climate and tree shading. Date/time From 04:00 to 22:00 (18 h) on 30 April 2012 For the assessment of urban thermal comfort, the PET simulated (physiologically equivalent temperature) is selected as the Bedok: 150 × 98 × 30 grids thermal comfort index. PET has been calibrated against Model domain Δx � Δy � Δz � 4m subjective thermal sensation evaluation by Yang et al. [17] in Note: vertical grid with the equidistant method Air temperature and relative humidity: hourly Singapore (Table 4), which makes it possible to compare data from the measurement on-site different urban design proposals. Tropical residents are Meteorological Wind speed and direction: hourly data from the found to tolerate higher levels of PET than Western/Middle inputs meteorological station European residents due to thermal adaption to the local Specific humidity (2500 m) � 7 g/kg climate. PET is calculated using the RayMan model [18, 19]. Initial soil Upper layer (0–20 cm): 305 K/30% It can be easily estimated with air temperature, relative temperature and Middle layer (20–50 cm): 307 K/40% humidity, wind speed, mean radiant temperature, clothing, relative humidity Deeper layer (below 50 cm): 306 K/50% and activity level of people. *e thermal comfort map in Inside temperature � 293 K (constant) terms of PET is generated in the paper for comparison. Heat transmission walls � 1.94 W/m ·K Building Heat transmission roofs � 6 W/m ·K conditions Albedo walls � 0.2 3. Results and Discussion Albedo roofs � 0.3 Trees: 10 m dense, leafless base 3.1. +e Base Case Scenario: Measurement and Simulation. Plants Trees: 20 m dense, leafless base *e microclimatic parameters of air temperature, mean Grass: 20 cm average dense radiant temperature, wind speed, and relative humidity collected at measuring points 1–5 have been compared with the corresponding ENVI-met model outputs. trend for all five points with perhaps more smooth curves Figure 4 shows the comparison between measured for the simulated ones. *e air temperature pattern is and simulated air temperatures. It can be seen that the clearly influenced by the sky view factor and surrounding simulated and measured air temperatures have the same urban environment. Point 2 has the lowest air temperature Advances in Meteorology 5 Table 3: Di…erent design scenarios for Bedok. Design scenario Pavement materials Vegetation and water body Sparse trees and grass Base case Red brick (ID: KK) and concrete pavement (ID: PP) Small area of water bodies (30 m ) Scenario 1 Wooden boards (ID: WD) As base case Scenario 2 Light-color granite (ID: G2) As base case Scenario 3 Grass surface As base case Scenario 4 As base case Add more trees (increase by 200%) Scenario 5 As base case Add more water bodies (increase by 200%) Scenario 6 Light-color granite (ID: G2) Add more trees (increase by 200%) Scenario 7 Grass surface Add more trees (increase by 200%) (mesoscale) e…ects are not taken into account [15]. During the Table 4: „ermal sensations and PET classes for Singapore and Western/Middle Europe. night, the air temperature is underestimated by up to 0.5 C and overestimated by up to 0.3 C with ENVI-met in this study. PET range for „ermal PET range for „e mean radiant temperature comparison between Western/Middle sensation Singapore ( C) simulated and measured results is shown in Figure 5. It can be Europe ( C) seen that the simulated and measured mean radiant tem- Very cold Not applicable <4 peratures have the same trend for all the points. Points 3, 4, Cold Not applicable 4–8 and 5 have a higher mean radiant temperature proŠle than Cool Not applicable 8–13 points 1 and 2 during the day. „is is because points 1 and 2 Slightly cool 20–24 13–18 Neutral 24–30 18–23 are located in the park and have lower sky view factors. It can Slightly warm 30–34 23–29 also be found that the daytime mean radiant temperature is Warm 34–38 29–35 overestimated and nighttime mean radiant temperature is Hot 38–42 35–41 underestimated by ENVI-met. „e daytime di…erence is Very hot >42 >41 about 0.1–6.7 C, and the nighttime di…erence is about 2.6– Source: Yang et al. [17]. ° 6.6 C. A number of other studies have also reported a mean radiant temperature di…erence of up to 7.97 C between the measured and simulated results [1, 4, 13, 20]. „e discrep- 35.0 ancies are due to that ENVI-met does not consider heat 34.0 storage and transfer by buildings or anthropogenic heat production in an adequate manner [13, 21]. „erefore, studies 33.0 on the e…ect of landscape design on nighttime outdoor 32.0 thermal comfort and urban heat island need further in- vestigation in the future due to limitations of ENVI-met 31.0 modeling. 30.0 „e results of the measured and simulated wind speed and relative humidity show little di…erence (less than 5%) for 29.0 all the points. „e input wind speed is less than 2 m/s in this 28.0 study. It has also been reported that wind speeds predicted 10 11 12 13 14 15 16 17 18 19 20 21 22 by ENVI-met are consistent with Šeld data for input wind (Time) speeds below 2 m/s [22]. P1 measured P1 simulated Tables 5 and 6 show the model Št between simulated and P2 measured P2 simulated measured results for air temperature and mean radiant P3 measured P3 simulated temperature, respectively. Very high overall agreement can P4 measured P4 simulated be found for both air temperature (R between 0.95 and 0.99) P5 measured P5 simulated and mean radiant temperature (R between 0.74 and 0.96). Figure 4: Comparison between simulated and measured air 2 „e relatively lower model Št of R  0.74 for point 2 as well temperatures. as the 5 C di…erence between simulated and measured re- sults in terms of mean radiant temperature can be partially because it is located in the nearby park and has a low sky explained by the error in the measurement; for example, view factor (0.17). solar radiation suddenly became very intense during that Points 3, 4, and 5 have higher air temperatures than points particular measurement time. 1 and 2 because these three points are located along high- „erefore it is possible to say that although there are density residential buildings. It can also be seen that ENVI-met some discrepancies between the simulated and measured underestimates the daytime air temperature by about 0.1– results, ENVI-met is able to present similar trends for mi- 0.7 C. „is is because ENVI-met calculates the urban climate at croclimatic parameters compared with those from Šeld a microscale or a local scale and that larger regional measurement. Compared with a former study conducted in Air temperature difference (°C) 6 Advances in Meteorology 10 11 12 13 14 15 16 17 18 19 20 21 22 (Time) P1 measured P1 simulated P2 measured P2 simulated P3 measured P3 simulated P4 measured P4 simulated P5 measured P5 simulated Figure 5: Comparison between simulated and measured mean radiant temperatures. Table 5: Model Št between simulated and measured results for air temperature. is at 3 pm on the simulation day. „erefore, the e…ects of di…erent landscape design scenarios on microclimate and Point Point Point Point Point 1 2 3 4 5 thermal comfort are compared based on results at 3 pm. Except for the surface temperature, the other microclimate Minimum error ( C) 0 −0.1 0 0.01 0.03 Maximum error ( C) −0.67 −0.63 −0.68 −0.72 −0.67 parameters are compared at 2.0 m above the ground level. Mean error ( C) −0.16 −0.19 −0.31 −0.41 −0.28 Standard deviation ( C) 0.21 0.26 0.20 0.23 0.30 R 0.98 0.97 0.99 0.99 0.95 3.2.1. Surface Temperature and Air Temperature. Figure 6 RMSE ( C) 0.27 0.32 0.37 0.47 0.41 shows the surface temperature patterns for all design sce- narios. „e di…erences in surface temperatures are obvious. Pavement with light-color granite (Scenario 2) has the lowest Table 6: Model Št between simulated and measured results for mean radiant temperature. surface temperature, with a maximum reduction of 12 C compared with the base case. Surface temperature reduction Point Point Point Point Point by grass surfacing (Scenario 3) and adding more trees 1 2 3 4 5 (Scenario 4) is also obvious, with a reduction by up to 8 C for Minimum error ( C) 0 0.71 0.01 0.81 −0.07 grass and 10 C for trees. Maximum error ( C) −4.23 6.24 6.78 −6.25 −6.59 Surface temperature reduction by applying wood pave- Mean error ( C) 0.08 1.10 0.88 −1.13 −0.6 ment (Scenario 1) can be up to 6 C. Not much di…erence in Standard deviation ( C) 3.16 3.35 4.97 4.34 4.52 surface temperature can be found by adding more water R 0.96 0.74 0.95 0.91 0.94 RMSE ( C) 3.16 3.56 5.05 4.49 4.56 bodies. Both Scenario 6 (combination of light-color granite and adding more trees) and Scenario 7 (combination of grass surfacing and adding more trees) resulted in a signiŠcant Singapore [13], it can also be seen that the new ENVI-met reduction of surface temperature. However, Scenario 6 is more model of version 4.0 shows much better performance than e…ective in reducing the surface temperature than Scenario 7. the previous version of ENVI-met 3.1. Since the thermal Figure 7 shows the air temperature patterns for all design performance of di…erent urban geometries and ground scenarios. „e di…erences in air temperature between di…erent surface and their e…ect on mean radiant temperature can be scenarios are not so obvious as those in the surface temper- modeled by ENVI-met, a relative comparison can be made ature. „e air temperature is about 0.25–0.75 C lower for the for di…erent design scenarios. In addition, the simulated scenarios with light-color granite compared with the base case. results have been calibrated with Šeld measurement data and For scenarios with grass surfacing and more trees, the air then used as a benchmark for investigation of changes in temperature reduction is about 0.25–0.5 C. For wood scenario, design. „erefore, all the changes in design are consistent the apparent reduction of 6 C of the temperature at the surface and relative to the simulated case, whereby the error from does not cause a signiŠcant reduction in local air temperature calibration has been e…ectively eliminated. at 2.0 m above the ground level. However, the air temperature of areas under building shade for the wood scenario is about 3.2. Microclimate Dierences. It has been found from both 0.25 C lower than that in the base case. Scenario 6 and Scenario the measurement and simulation results that the hottest time 7 both cause an air temperature reduction by up to 0.75 C. Mean radiant temperature difference (°C) Advances in Meteorology 7 T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (a) (b) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (c) (d) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (e) (f) T surface T surface 98 98 Below 28.00 °C Below 28.00 °C 88 88 28.00 to 30.00 °C 28.00 to 30.00 °C 78 78 30.00 to 32.00 °C 30.00 to 32.00 °C 68 68 32.00 to 34.00 °C 32.00 to 34.00 °C 58 58 34.00 to 36.00 °C 34.00 to 36.00 °C 48 48 36.00 to 38.00 °C 36.00 to 38.00 °C 38 38 38.00 to 40.00 °C 38.00 to 40.00 °C 28 28 40.00 to 42.00 °C 40.00 to 42.00 °C 18 18 42.00 to 44.00 °C 42.00 to 44.00 °C 8 8 Above 44.00 °C Above 44.00 °C N N X (4 m) X (4 m) (g) (h) Figure 6: Simulated surface temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). Not much di…erence in air temperature can be found for Singapore in the current study. „is is in agreement with the scenario of adding more water bodies. Water bodies are a Šeld measurement study conducted by Wong et al. [23] found to be not e…ective in decreasing the air temperature in who investigated the evaporative cooling performance of Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 8 Advances in Meteorology Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 48 48 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (a) (b) Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (c) (d) Air temperature Air temperature 98 98 Below 32.25 °C Below 32.25 °C 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 58 58 33.00 to 33.25 °C 33.00 to 33.25 °C 48 48 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C 8 8 Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (e) (f) Air temperature Air temperature Below 32.25 °C Below 32.25 °C 88 88 32.25 to 32.50 °C 32.25 to 32.50 °C 78 78 32.50 to 32.75 °C 32.50 to 32.75 °C 68 68 32.75 to 33.00 °C 32.75 to 33.00 °C 33.00 to 33.25 °C 33.00 to 33.25 °C 33.25 to 33.50 °C 33.25 to 33.50 °C 38 38 33.50 to 33.75 °C 33.50 to 33.75 °C 28 28 33.75 to 34.00 °C 33.75 to 34.00 °C 18 18 34.00 to 34.25 °C 34.00 to 34.25 °C Above 34.25 °C Above 34.25 °C N N X (4 m) X (4 m) (g) (h) Figure 7: Simulated air temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). a waterway in Singapore and found that the air temperature 3.2.2. Mean Radiant Temperature. „e patterns of mean was merely reduced by 0.1 C on every 30 m away from the radiant temperature for all design scenarios are presented in waterway. „e high humidity climate and low wind con- Figure 8. For sunlit places, the mean radiant temperatures dition might be one of the possible reasons for it. are 50–54 C for all scenarios except the grass surface Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Advances in Meteorology 9 Mean radiant temp. Mean radiant temp. Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (a) (b) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 38 38 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (c) (d) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (e) (f) Mean radiant temp. Mean radiant temp. 98 98 Below 30.00 °C Below 30.00 °C 88 88 30.00 to 34.00 °C 30.00 to 34.00 °C 78 78 34.00 to 38.00 °C 34.00 to 38.00 °C 68 68 38.00 to 42.00 °C 38.00 to 42.00 °C 58 58 42.00 to 46.00 °C 42.00 to 46.00 °C 48 48 46.00 to 50.00 °C 46.00 to 50.00 °C 38 38 50.00 to 54.00 °C 50.00 to 54.00 °C 28 28 54.00 to 58.00 °C 54.00 to 58.00 °C 18 18 58.00 to 62.00 °C 58.00 to 62.00 °C 8 8 Above 62.00 °C Above 62.00 °C N N X (4 m) X (4 m) (g) (h) Figure 8: Simulated mean radiant temperature for all design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light- color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). scenarios, which have mean radiant temperatures 4–8 C both the wood and light-color granite scenarios, the mean lower than other scenarios. For places shaded by buildings, radiant temperatures are 4–8 C higher than those of the base di…erences in mean radiant temperature are obvious. For case. For the tree scenarios, there is a signiŠcant cooling Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 10 Advances in Meteorology effect and the mean radiant temperature under tree-shaded scenario has different pavement materials. Again adding more areas can be reduced by 12–16 C compared with sunlit areas. water bodies is found to have little effect on PET. Scenario 7 (combination of grass surface and more trees) is the best with 4–8 C mean radiant temperature reduction for 4. Discussion areas exposed to the sun and 12–16 C reduction for tree- shaded areas. Not much difference can be found for the Table 7 summarizes the effect of different design scenarios scenario of adding more water bodies. on microclimate and human thermal comfort (PET). *e results from ENVI-met indicate that the change of It can be seen that design strategies that can reduce pavement materials has a minor effect on reducing mean surface temperature and air temperature may not necessarily radiant temperature for places exposed to high solar radi- reduce heat stress condition. Design strategies such as ap- ation. For places shaded by buildings, the mean radiant plying wooden boards and light-color granite have some temperature is even increased by using high-albedo pave- extent of cooling effect, but heat stress is marginally reduced. ment materials. *is is consistent with other studies which Both the wooden board and light-color granite are high- also found increases of mean radiant temperature by ap- albedo materials with an albedo of 0.8 in this study. While plying high-albedo materials [4, 16, 24] in hot and humid higher albedo reduces the surface temperatures, and con- climates. sequently, the air temperature, it increases the amount of reflected short-wave radiation in the environment at the same time. As it is known, the increase of energy flux will result in the increase of mean radiant temperature. Mean 3.2.3. Wind Speed and Relative Humidity. Due to the radiant temperature is the main factor affecting outdoor small differences between different design scenarios in thermal comfort in hot and humid climate as in Singapore terms of wind speed and relative humidity, the figures are [17]. *us, the insignificant effect of high-albedo materials not shown here. *e results show that wind speed is on reducing heat stress can be expected. However, the ef- slightly reduced by 0.2 m/s with more trees planting. *e fectiveness of high-albedo covering on heat stress is disputed differences in wind speed are not obvious for other design because PET does not take surface temperature into con- scenarios. *is is because the layout of building blocks sideration. *e decrease of surface temperature is not re- has been determined in the residential quarters for this flected in PET, which raises a question of whether surface study. Compared with landscape elements, the layout of temperature has an effect on urban thermal comfort. Dif- building blocks has greater effect on air flow in urban ferent from the indoor environment which has uniform and spaces. relative lower surface temperatures, outdoor space has As to the relative humidity, scenarios with grass surface, a large variation and fluctuation of surface temperatures. *e more trees, and water bodies are more humid, with an evaluation of urban thermal comfort is a challenging topic in increase of 4% to 6% compared with the base case. *e the research field of human bioclimate, which still needs change of landscape elements cannot lead to significant further study. variation of relative humidity when the humidity is very high Water can mitigate the urban heat island effect since throughout the year. *is is the climate in Singapore, and more incoming heat can be transformed into latent heat hence, the results make sense. rather than sensible heat. However, water bodies are found to be not effective in mitigating heat stress in hot and humid climate as studied in this paper. Adding more water bodies 3.3. +ermal Comfort Maps of PET. Figure 9 shows the does not change any microclimate parameters except that simulated thermal comfort (PET) maps for all the design humidity increases slightly. *is may be because the area of scenarios at 3 pm. *e PET values of sunlit places for all the water bodies in this study is not large enough to create design scenarios are dominated by extremely hot condition a cooling effect for the surrounding environment. Besides, with the PET between 46 and 50 C, which is under severe due to the high humidity conditions in Singapore, thermal heat stress and far above the comfortable temperature range comfort cannot benefit too much from the evaporation from (24–30 C) required for Singapore occupants (Table 4). Al- water bodies. It has been widely accepted that shading is the key though thermal comfort is difficult to achieve under such hot climate conditions, some improvements can be made strategy for promoting outdoor thermal comfort in hot climate. Interception of solar radiation is the most effective through landscape design. *e best thermal conditions are in the areas with means in improving thermal comfort in outdoor areas in hot and dry climate [6]. *e current study also vindicates this shading, either shaded by buildings or trees, with a PET of 34–38 C, which corresponds to “warm” according to Table 4. design principle because the scenarios shaded by more trees *e shade enhancement by trees or buildings has a clear have the best thermal comfort condition, with the maximum positive effect on alleviating outdoor heat stress, as indicated PET reduced by 12 C. However, not much difference is by decreased PET. found for scenarios with trees (Scenario 4, 6, and 7) in terms Scenario 3 (grass surface) only leads to a PETreduction of of urban heat stress even though each scenario has different 4–8 C for limited areas, and the heat stress conditions for pavement materials. Different pavement materials can lead most of the study areas are not improved. Scenarios with trees to variations in surface temperature, air temperature, and (4, 6, and 7) have the same PET patterns despite that each mean radiant temperature in urban spaces, but these Advances in Meteorology 11 PET PET Below 30.00 °C 98 Below 30.00 °C 30.00 to 34.00 °C 88 30.00 to 34.00 °C 34.00 to 38.00 °C 78 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (a) (b) PET PET Below 30.00 °C 98 Below 30.00 °C 30.00 to 34.00 °C 88 30.00 to 34.00 °C 34.00 to 38.00 °C 78 34.00 to 38.00 °C 38.00 to 42.00 °C 68 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (c) (d) PET PET Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C X (4m) X (4m) (e) (f) PET PET Below 30.00 °C Below 30.00 °C 30.00 to 34.00 °C 30.00 to 34.00 °C 34.00 to 38.00 °C 34.00 to 38.00 °C 38.00 to 42.00 °C 38.00 to 42.00 °C 42.00 to 46.00 °C 42.00 to 46.00 °C 46.00 to 50.00 °C 46.00 to 50.00 °C 50.00 to 54.00 °C 50.00 to 54.00 °C 54.00 to 58.00 °C 54.00 to 58.00 °C 58.00 to 62.00 °C 58.00 to 62.00 °C Above 62.00 °C Above 62.00 °C N N X (4m) X (4m) (g) (h) Figure 9: Simulated PET for all the design scenarios. (a) Base case. (b) Scenario 1 (wooden boards). (c) Scenario 2 (light-color granite). (d) Scenario 3 (grass surface). (e) Scenario 4 (more trees). (f) Scenario 5 (more water bodies). (g) Scenario 6 (light-color granite + more trees). (h) Scenario 7 (grass surface + more trees). Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 Y (4 m) Y (4 m) Y (4 m) Y (4 m) 0 0 0 0 10 10 10 10 20 20 20 20 30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 70 70 70 70 80 80 80 80 90 90 90 90 100 100 100 100 110 110 110 110 120 120 120 120 130 130 130 130 140 140 140 140 150 150 150 150 12 Advances in Meteorology Table 7: Summary of the effect of different design scenarios on urban microclimate and thermal comfort (PET). Surface temp. Air temp. PET Design scenarios Mean radiant temp. reduction reduction reduction reduction 0–0.25 C for ° ° 1 Wooden boards 2–6 C −8 to −4 C for building-shaded areas No change building-shaded areas ° ° ° 2 Light-color granite 2–12 C 0.25–0.75 C −8 to −4 C for building-shaded areas No change 4–8 C for ° ° ° 3 Grass surface 2–8 C 0.25–0.5 C 4–8 C for areas exposed to the sun limited areas ° ° ° ° 4 More trees 2–10 C 0.25–0.5 C 12–16 C for tree-shaded areas 4–12 C 5 More water bodies No change No change No change No change Light-color granite −8 to −4 C for building-shaded areas ° ° ° 6 2–12 C 0.25–0.75 C 4–12 C and more trees 12–16 C for tree-shaded areas Grass surface 4–8 C for areas exposed to the sun ° ° ° 7 2–10 C 0.25–0.75 C 4–12 C and more trees 12–16 C for tree-shaded areas variations may not be effective enough to reduce heat stress the maximum surface temperature reduced by 10 C, air during the daytime. However, during the night, the effect of temperature reduced by 0.75 C, mean radiant temperature ° ° different pavement materials on thermal comfort can be reduced by 16 C, and PET reduced by 12 C. Although high- obvious because different materials have different thermal albedo pavement materials and water bodies are found not properties. In addition, air temperature is the main factor effective in reducing heat stress in hot and humid climate that affects urban thermal comfort during the nighttime. It conditions, the results are dubious since the evaluation of needs to be noted that due to time constraints and limita- urban thermal comfort does not include the surface tem- tions of ENVI-met modeling, nighttime thermal comfort is perature. *e evaluation of urban thermal comfort is not investigated in this study. a challenging topic in the research field of human bioclimate, Compared with grass surfacing, tree planting is a more which still needs further study. It can be concluded that the effective strategy to promote shading, thus reducing urban findings from the paper can equip urban planners and heat stress. Although tree planting would lead to an increase designers with knowledge and techniques when they plan for of relative humidity and a decrease of wind speed, those future urban areas/regions and replan for existing urban negative effects are minor compared with the positive effects areas/regions so as to mitigate urban heat stress. However, of reduction of air temperature and mean radiant temper- due to the limitations of ENVI-met modeling, the effect of ature. As predicted, the combination of shade trees over landscape design on nighttime thermal comfort and urban grass is found to be the most effective landscape strategy in heat island requires further investigation in the future. terms of cooling provided, with the maximum surface temperature reduced by 10 C, air temperature reduced by Data Availability ° ° 0.75 C, mean radiant temperature reduced by 16 C, and PET ° *e data used to support the findings of this study are reduced by 12 C. available from the corresponding author upon request. 5. Conclusions Conflicts of Interest *e effects of urban landscape design on urban microclimate *e authors declare that they have no conflicts of interest. and thermal comfort in a high-rise residential area in the tropic climate of Singapore have been investigated in this Acknowledgments paper. Various landscape elements of pavement materials, greenery, and water bodies have been studied. Real data on *is work was supported by the NUS Research Scholarship microclimate obtained from a comprehensive field mea- from the National University of Singapore and Natural surement with multiple points have been presented and used Science Foundation of Hubei Province, China, under Grant to calibrate the new version of the microclimate-modeling number 2015CFB510. *e authors would like to express software EVNI-met. With the calibrated ENVI-met, seven their sincere thanks to Professor Wong Nuyk Hien and his urban design scenarios of different surface albedo, greenery, Ph.D. students from the National University of Singapore and water bodies have been simulated with different mi- for their assistance in the field measurement work of this croclimatic parameters, and their effects on human thermal paper. comfort as measured by PET have been evaluated. 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