The temporal-spatial distributions of outdoor ...

4th International Conference on Countermeasures to Urban Heat Island, 30-31 May and 1 June 2016, National University of Singapore, Singapore

The temporal-spatial distributions of outdoor thermal environments for high-rise residential communities in the hot-humid area Wu Jie1,2, Zhang Yufeng1 1. South China University of Technology, State Key Laboratory of Subtropical Building Science, Guangdong Guangzhou 510640; 2. Guangxi University, Guangxi Nanning 530004

ABSTRACT Outdoor space of residential community is the main spaces for inhabitant’s daily activities, the problems of outdoor thermal safety and comfort are serious in the hothumid area of southern China due to the long and hot-humid summer, and to ensure a better outdoor environmental quality is important for the planning and designs of residential communities in the area. In addition, with the development of urbanization and the shortage of urban lands, high-rise residential communities that have large mass and population density are increasing in amount, and it is necessary and important to study the outdoor thermal environments of high-rise communities. The present paper conducted field measurements on several high-rise residential communities in Guangzhou and Nanning. The measurements were performed in sunny summer days. The near-ground air temperature, relative humidity, wind speed, globe temperature and solar radiation were measured, and meanwhile, the three thermal environment design parameters (TEDPs) of community, i.e., shadow rate (SAR), sky view factor (SVF) and tree view factor (TVF), were measured by fisheye photograph. The temporal-spatial distributions of outdoor thermal environments were analyzed for various site-layouts of community through comparing thermal parameters and SET* of different measuring-points. The relationship between thermal environmental distributions and TEDPs was obtained by statistical analysis. This paper finally proposed a new method of rapid assessing temporal-spatial distribution of outdoor thermal environment for residential community. Key Words: residential community, hot-humid area, temporal-spatial distribution, thermal environmental design parameter, SET* 1. INTRODUCTION Outdoor space of residential community is the main spaces for inhabitant’s daily activities, The problems of outdoor thermal safety and comfort are serious in the hothumid area of southern China due to the long and hot-humid summer, and to ensure

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a better outdoor environmental quality is important for the planning and designs of residential communities in the area. Previous research regarding outdoor thermal environments had shown there were many factors influencing outdoor thermal comfort such as: mean radiation temperature (MRT, °C), air temperature (Ta, °C), relative humidity (RH, %) and wind velocity (WV, m/s) (Lin, 2009; Spagnolo & de Dear, 2003; Zhou, Chen, Deng, & Mochida, 2013). According to the study from hot-humid area revealed that numbers of outdoor activity were related to the thermal comfort, and people’s thermal perceptions were strongly related to the Ta and MRT(Lin, 2009) . In high density city Hong Kong, Cheng and Ng conducted an outdoor thermal comfort experiment. The results showed that changing wind speed and solar radiation conditions had significant influences on thermal sensation, and under shaded condition, a wind speed of 0.9 m/s to 1.3m/s was recommended for a person in light clothing to achieve neutral thermal sensation in an urban environment(Cheng, Ng, Chan, & Givoni, 2012; Ng & Cheng, 2012). The field measurements is an important way to evaluate the effects to thermal comfort of different layouts of buildings and vegetation, researchers have conducts lots of surveys in hot-humid area. The results of studies showed that due to the block and shelter effect of buildings and vegetation, the near ground distribution of solar radiation intensity and wind velocity would be differences pattern. According to the studies from hot-humid area (Cheng et al., 2012; Xi, Li, Mochida, & Meng, 2012; Zhou et al., 2013)revealed that the maximum MRT difference between under the shadow and in a nearby square was about 30~40°C, Ta difference was about 2~3°C. Holst and Mayer studied the impacts of street design parameters on outdoor thermal comfort(Holst & Mayer, 2011). Their studies revealed remarkable positive correlation between MRT and sky view factor (SVF), likewise negative correlation between ΔMRT and ΔCTC (coverage by street tree canopy). The Yang study points out that, the pedestrian-level wind velocity ratio (WVR) is significantly correlated with the SVF, tree view factor (TVF) (Yang, Qian, & Lau, 2013). The present paper conducted field measurements on several high-rise residential communities in Guangzhou and Nanning. The measurements were performed in sunny summer days. The near-ground air temperature (ta, °C), relative humidity (RH, %), wind velocity (WV, m/s), globe temperature (tg, °C) and solar radiation intensity (Isol, W·m-2) were measured, and meanwhile, the three thermal environment design parameters (TEDPs) of community, i.e., shadow rate (SAR), sky view factor (SVF) and tree view factor (TVF), were measured by fisheye photograph. The temporal-spatial distributions of outdoor thermal environments were analyzed for various site-layouts of community through comparing thermal parameters and the thermal comfort index of outdoor standard effective temperature (SET*) of different measuring-points. The relationship between thermal environmental distributions and TEDPs was obtained by statistical analysis. 2. METHODOLOGY 2.1 Cities for Experimental Investigations 2


Both Guangzhou and Nanning are located in the south of China, belonging to hot-humid area with the same latitude. Taken Guangzhou as an example, the climate of hot-humid area is introduced. The city of Guangzhou is located at a longitude between 112.8E and 114.2E and latitude between 22.3N and 24.1N. Guangzhou has a hot-humid climate with the mean range of diurnal temperatures is 26~33°C in July and 10~18°C in January, and the mean annual temperature and humidity are 22°C and 78%. The highest solar radiation intensity in Guangzhou reaches about 930~1045 W/m2 in the summer. The monsoon season is from April to September, during which 80% of the annual rainfall occurs. 2.2 Field Measurements in The Sites A series of field measurements were carried out from August 5 to August 24, 2013 and 2015. A total of 28 measuring points (MP) were arranged in high-rise residential communities in Guangzhou and Nanning, including MP7 to MP10 located in Nanning. The study areas of MP (Table 1) were includes commonly designed elements in community in hot-humid area, such as pilotis (PL), tree (TR), lawns (LW), pavilion (PV), square (SQ), pavement (PM), etc. According to the difference of the using characters, the areas are divided into 3 categories: A1- Pedestrian Entrance Area, A2- Pavement Area, A3- Outdoor Activities Area. Table 1 Information of MP MP Categories Elements MP Categories Elements

1 A2 PV 15 A2 PM

2 A3 TR 16 A3 TR

3 A1 PM 17 A3 SQ

4 A3 PV 18 A3 PL

5 A3 TR 19 A3 SQ

6 A1 PM 20 A1 PM

7 A2 SQ 21 A3 TR

8 A3 TR 22 A2 PM

9 A2 PM 23 A3 PL

10 A2 PM 24 A3 PL

11 A2 PM 25 A3 PV

12 A3 LW 26 A2 PM

13 A1 PM 27 A3 PV

14 A2 PM 28 A1 PM

The field measurements were included two aspect, which is thermal environment and TEDPs. Ta and RH measured using Hobo Pro V2 U23 with radiation shelter, at the same time, Tg and WV using the Delta. OHM HD32.3 measured. According to daily schedule of inhabitant, the thermal environment data was processed by every 3 hrs. as a period, in turn, it can be divided into T1(8:00~10:59), T2(11:00~13:59), T3(14:00~16:59), T4(17:00~19:59) and T5(20:00~22:59).

a. TE b. TEDPs Figure 1: Field Measurements

The Delta-T Hemiview system was applied to measure TEDPs, such as SVF, TVF and SAR. Fisheye-photos were taken using a DSLR( Canon EOS 50D) at each MP in order to determine the percentage of sky, buildings and vegetation in the specific hemisphere. According to Holst(2011), the photos were standardization by Photoshop as Fig. 2 3

4th International Conference on Countermeasures to Urban Heat Island, 30-31 May and 1 June 2016, National University of Singapore, Singapore N

E

W

S

a. Fisheye-Photos b. Standardization Figure 2: Measurement of TEDPs

1) Dark Region: Vegetation. 2) Grey Region: Buildings. 3) White Region: Sky

2.3 Calculation Method of SET* The SET* is adopted for the assessment of thermal comfort in this study(Spagnolo & de Dear, 2003), and MRT is calculated by the Eq. (1) (ISO, 1998) 4

𝑀𝑅𝑇 = [(𝑡𝑔 + 273) + (1.1 × 108 × 𝑊𝑉 0.6 ) × (𝑡𝑔 − 𝑡𝑎 )⁄(𝜀𝑔 × 𝐷0.4 )]

0.25

− 273

(1)

Where 𝜀𝑔 is emissivity (0.95), and the D is diameter of the global thermometer (0.05m), respectively. The parameters of SET* calculation are shown in Table 2. Table 2 The Parameters of SET* Calculation Parameters Value Clothing, Icl/ clo 0.4 Metabolic Rate, M/ W·m-2 115 Height, H/ m, Weight, W/ kg 1.65; 65 Body Surface Area, Abs/ m-2 1.416

3. RESULTS AND ANALYSIS 3.1 Weather Conditions The measurements were performed in sunny summer days; the weather conditions are shown in Table 3. Table 3 Weather Conditions Date

ta/ °C

RH/ %

WV /m·s-1

Isol/ W·m-2

August 5 August 6 August 7 August 24

28.3 28.8 29.8 28.4

80.0 77.9 68.3 70.0

1.7 2.5 2.8 1.0

287.4 235.8 311.3 299.3

3.2 Thermal Environment Design Parameters TEDPs, such as SVF, TVF and SAR, are often used to characterize specific residential buildings and vegetation coverage. The statistical data of TEDPs are listed in Table 4. As Figure 3.a shown, the higher values of SVF1-360 are MP3, MP6, and 0.6, 0.6 respectively; the lower values of SVF1-360 are MP18, MP24, and 0.0, 0.0 respectively. The higher values of SVF90-270 are MP5, MP6, and 0.7, 0.6 respectively; the lower values of SVF90-270 are MP4, MP18, and 0.0, 0.0 respectively. The higher values of TVF1-360 are MP7, MP8, and 0.6, 0.9 respectively; the lower values of TVF1360 are MP18, MP24, and 0.0, 0.0 respectively. the higher values of TVF 90-270 are MP7, 4


MP8, and 0.8, 0.9 respectively; the lower values of TVF90-270 are MP18, MP11, and 0.0, 0.0 respectively. As Figure 3.b shown, the higher values of mean SAR are MP18, MP24, MP27, and both 1.0 respectively; the lower values of mean SAR are MP23, MP26 , and 0.0, 0.0 respectively. Taking the mean value of every period，mean SAR of T4 is highest ( 0.8), T1 is lowest ( 0.4). SVF1-360

a. SVF/ TVF

1.0

SVF90-270

TVF1-360

TVF90-270

0.5

0.0 1

2

3

4

6

7

8

SAR8-10

1.0

b. SAR

5

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

SAR11-13

SAR14-16

SAR17-19

0.5

0.0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

MP

Figure 3: Thermal Environment Design Parameters of MP

Mean Min. Max. Std. Deviation

Table 4 Statistics of TEDPs SVF1-360 SVF90-270 TVF1-360 0.30 0.32 0.19 0.00 0.00 0.00 0.63 0.65 0.88 0.20 0.22 0.18

TVF90-270 0.18 0.00 0.88 0.20

SAR 0.55 0.00 1.00 0.44

3.3 Thermal Environment The results of thermal environment are shown in Figure 4. The mean SET* of all period is 34.0°C，the Std. Deviation is 3.7°C。The maximum SET* appeared in the period of T2 (11:00~13:00), for MP1(43.8°C), MP5(42.5°C), the corresponding higher MRT, Ta, RH and lower WV, 70.1°C, 34.3°C, 83.6%, 1.8m/s and 71.7°C, 34.3°C, 55.6%, 0.9m/s. The minimum SET* appeared in the period of T5 (20:00~22:00), for MP17(27.8°C), MP12(28.2°C), the corresponding lower MRT, Ta, RH and higher WV, 29.1°C, 30.4°C, 73.2%, 2.9m/s and 29.3°C, 30.7°C, 72.9%, 2.7m/s. See Figure 3& 4, the period of T2 is taken as an example to analyse the relationship between daytime SET* and TEDPs. Daytime SET* is mainly affected by MRT. Measuring points with a higher value of SET* are MP1 and MP5, and those with a lower value of are MP18 and MP24. The comparison between thermal environment and TEDPs shows that MP1 and MP5 have low SAR, high SVF, and higher MRT due to direct solar radiation. MP18 and MP24 have high SAR and low SVF as well as lower 5


MRT due to pilotis. The nocturne environments are different, each MP’s value of the MRT and ta are similar, SET* is mainly affected by WV. At the period of T5, MP4 and MP20 have high TVF, low SVF, and lower WV due to shelter effect of tree canopy. MP12 and MP17 have low TVF, high SVF as well as higher WV due to square without shelter of tree canopy. To sum up, the value of SET* is closely related to TEDPs of MP. Greater SVF means lower SAR and TVF and higher value of daytime SET*, and Greater TVF means higher shelter effect of tree and higher value of nocturne SET*.

SET*/ °C

45

T1(8-10)

T2(11-13)

T3(14-16)

T(17-19)

T(20-22)

35

25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

MRT/ °C

80 60 40 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

40

ta/ °C

35

30

25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

WV /m·s-1

4

2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

MP

Figure 4: Thermal Environments of MP 4. DISCUSSION 4.1 Dependence of MRT on SVF& SAR 6


In order to understand the change of MRT of measuring points with SVF and TVF, and a regression relationship was built according to each periods (See Figure 5). The results (Figure 5) show that the daytime value of MRT is significantly positive with SVF and negative with SAR1-360, but nocturne value is not significant. Because each period the solar radiation intensity is different, which leads to the influence of SVF/ SAR on MRT is different, the greater the solar radiation, the greater the absolute value of influence factor.

MRT/ °C

80 MRT0810

y = 40.606x + 32.957 R²= 0.4309

MRT1113

y = 61.321x + 36.892 R²= 0.7354

MRT1416

y = 52.167x + 35.524 R²= 0.6057

MRT1719

y = 7.9071x + 32.333 R²= 0.2777

MRT2022

y = -1.5801x + 29.836 R²= 0.0814

50

20 0.00

0.25 0.50 a. SVF1-360

0.75

MRT/ °C

80

50

20 0.0

0.5 b. SAR

1.0

MRT0810

y = -21.424x + 54.647 R²= 0.6279

MRT1113

y = -28.715x + 65.872 R²= 0.7257

MRT1416

y = -25.164x + 64.23 R²= 0.5571

MRT1719

y = -6.2186x + 39.926 R²= 0.3856

80

Factor

40

Fsvf/MRT

y = 0.0706x + 1.6669 R²= 0.9272

0 Fsar/MRT y = -0.028x - 5.2883 R²= 0.895

-40 0.0

400.0 800.0 c. Isol/ W·m-2

Figure 5: The Relationship between MRT and SVF& SAR

4.3 Influence of SVF& TVF to Wind Velocity Contrary to the case of mean radiation temperature, the nocturne value of SET* is obviously relevant to wind velocity, while the daytime value of SET* and wind velocity is not obviously relevant. In order to understand the impact of wind velocity by TEDPs, the regression analysis was conducted. The results are shown as Figure 6, the daytime value of WV is positive with SVF1-360, but nocturne value is not significant (Figure 6.a). See Figure 6.b for the relationship between WV and TVF. Due to the shelter effect of 7


tree canopy, the measuring point of wind velocity is negatively related to the TVF throughout the day. For the same location, the attenuation caused by shelter effect of trees at nocturne wind velocity is more than the daytime. The correlation analysed showed no significant difference between the value of SVF/TVF1-360 with WV and the SVF/TVF90-270.

WV/ m·s-1

4

WV0810

3

WV1113

2

WV1416 1

WV1719 0 0.00

0.25

0.50

0.75

WV2022

a. SVF1-360

WV/ m·s-1

4

WV0810

3

WV1113 2

WV1416

1

WV1719

0 0.00

0.25

0.50

0.75

WV2022

b. TVF1-360

y = 1.3435x + 0.537 R² = 0.4008 y = 1.6237x + 0.6787 R² = 0.4534 y = 1.8017x + 0.7393 R² = 0.3031 y = 1.2323x + 0.6498 R² = 0.1358 y = 0.7541x + 0.9019 R² = 0.0464 y = -1.3343x + 1.2029 R² = 0.3629 y = -1.343x + 1.4301 R² = 0.2848 y = -1.7777x + 1.6301 R² = 0.2709 y = -1.5881x + 1.3329 R² = 0.2071 y = -3.714x + 1.6776 R² = 0.2782

Figure 6: The Relationship between WV and SVF& TVF

4.5 Influence of TEDPs to SET* Due to the influence of TEDPs on the thermal environment related to the intensity of solar radiation, and so the daytime and nocturne value SET* between TEDPs regression relationship is established, respectively, as shown in Eq. (2) ~ (3): (2) SET𝑑∗ = −5.7SAR + 37.9 R2 = 0.50 ∗ 2 (3) SET𝑛 = 8.6TVF1−360 − 3.2SVF90−270 + 30.2 R = 0.37 Where the parameter is the same as the above meaning. Therefore, the daytime value of SET* of measuring points is negatively correlated to SAR of measuring points, the nocturne SET* of measuring points is associated with TVF1-360 and SVF90-270. In the thermal environment design parameters, the SAR is the main influence factors of the daytime SET*. For the hot-sunny weather conditions, within the range 0-1.0, a decrease of 0.1 in SAR tends to increase SET* by 0.6°C.

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5. CONCLUSION Based on the field measurements of thermal environment and TEDPs during the hot-sunny day of summer in the hot-humid area of China, the following conclusions are drawn: 1) During 8:00~22:00, the mean SET* of test sites is 34.0°C，the Std. Deviation is 3.7°C。Due to the difference of TEDPs，significant difference was found in thermal environment：the maximum SET*(43.8°C) appeared in the period of T2 (11:00~13:00), and minimum SET* is only 29.5 °C at the same time. 2) Daytime SET* is mainly affected by MRT. the daytime value of MRT is significantly positive with SVF and negative with SAR1-360, but nocturne value is not significant. Because each period the solar radiation intensity is different, which leads to the influence of SVF/ SAR on MRT is different, the greater the solar radiation, the greater the absolute value of influence factor. 3) Nnocturne SET* is obviously relevant to wind velocity. Daytime value of WV is positive with SVF1-360, but nocturne value is not significant. Due to the shelter effect of tree canopy, the measuring point of WV is negatively related to the TVF throughout the day. For the same location, the attenuation caused by shelter effect of trees at nocturne wind velocity is more than the daytime. 4) The daytime value of SET* of measuring points is negatively correlated to SAR of measuring points, the nocturne SET* of measuring points is associated with TVF1-360 and SVF90-270. In the thermal environment design parameters, the SAR is the main influence factors of the daytime SET*. ACKNOWLEDGMENT The project was supported by National Natural Science Foundation of China (Project No. 51408137）. The project was supported by Guangxi Experiment Centre of Science and Technology (Project No. YXKT2014018)

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