MicroClimate Design Study Of University Town, NUS Department of Building School of Design and Environment
Introduction What is UHI and its effects? Measures to mitigate UHI effects
Objectives
• To study the impact of UHI in the U-town region due to existing built-environment • To Identify the critical areas with hotspots and also to propose its mitigation measures to reduce the key effects of UHI • To select relevant mitigation measures that include addition of green/cool roof, vertical greenery & adding vegetation to existing topography to critical areas of the site
Methodology •
Understand the climate of the chosen site through the following parameters – Outdoor temperature mapping, wind profile & wind speed, thermal comfort index, total heat load, solar radiation using below software tools.
TSV with Tmrt TSV without Tmrt RayMan – PET
STEVE tool – Mapping out site temperature & total heat load ANSYS Fluent- Site wind flow map EnviMET –Mean radiant temperature
•
Identifying hot spot through studying the Daytime and Nighttime UHI effect in STEVE tool
•
Mitigating measures applies on a building in the hotspot region including building martials and vegetation IES – Peak cooling load comparison between different building materials & vegetation EnviMET – Mean radiant temperature between different building materials
•
Optimal strategy proposed
Site Information
• University Town (UTown) • Site Area Of 140825 Sqm. • Integrated with the Kent Ridge Campus • On South, it is linked with Ayer Rajah Expressway • On West, it is linked with Sub-Arterial Clementi Road
UTown Information Residential Colleges Yale - Green NUS Colleges Education Town Create Stephen Tower Raidy Resource Centre U Town Residences Centre It Undergraduate Students include ItFor CREATE contributes tower to1,700 is the anpulse international of activities research in Housing up to residents campus House more than 600 students University andTown innovation hub two SAGA College multipurpose sports halls On 67,000 sqCollege m plot arock Cendena climbing wallit house some 1,200 researchers gym, ELM College recreational pool an auditorium dance studios and practice rooms.
Residential Yale NUS U Town Colleges Residences Education Resource Centre
Stephen Town Create Green Tower Raidy Centre
Site Components
West Skyline
East Skyline
Overview of Software Implementation
Steve tool
PET
Rayman
ENVI-met
TSV
Manual
Fluent
Energy
IES-VE
Microclimate Analysis
STEVE Tool Analysis
Scope • • • •
Ambient air temperature Total heat load CO2 storage& sequestration Define hot spot
Input Input using default setting wind 0.69m/s, albedo concrete 0.16
Total Heat load 　
Thermal load unit (Wh/m4)
Total building footprint area(m2)
Total buildings envelope area(m2)
SCL ECG SG FAIG
4.08816 0.242066 0.3925 0.40085
100190.6 100190.6 100190.6 100190.6
389646.2 389646.2 389646.2 389646.2
Annual total (MWh) 159597.2 9450.0 15322.8 15648.7
Tree Species Diospyros buxifolia
Fagrea fragrans
Brownea grandiceps
Maniltoa browneoldes Hopea odorata
Archontophoneix alexandrae
CO2 Storage and Sequestration
Total Carbon Storage =7221 kg C Total carbon sequestration = 526 kg C/year
Define Hot spot- Daytime
Yale-NUS college Town Green
Temp(max)
Temp (avg-day)
Define Hot spot- Daytime 33.2
Yale-NUS college
33.4
Town Green
Define Hot spot- Daytime Causes •
These areas exposed to sun directly (High SVF) , results to receive large solar radiation during the daytime.
•
More trees planted in four residential colleges than Yale-NUS college, which provides shading effects during the daytime.
•
Four residential colleges relatively dense and building can provide selfshading effects due to heights variation.
Define Hot spot- Nighttime
Residential college 4
Yale-NUS college Create buildings
Temp(max)
Temp (avg-day)
Define Hot spot- Nighttime
Causes
25.9
•
Less plants (GnPR), heat emission from walls of building, heat is easy to be trapped
•
High GnPR in open area Town Green
EnviMet Analysis Scope Mean Radiant Temperature
Mean Radiant Temperature (deg C) in Utown on March 20, 2016 (12pm- 05pm)
12:00 PM
01:00 PM
02:00 PM
03:00 PM
04:00 PM
05:00 PM
Mean Radiant Temperature (deg C) in Utown on March 20, 2016 (06pm- 11pm)
06:00 PM
07:00 PM
08:00 PM
09:00 PM
10:00 PM
11:00 PM
Mean Radiant Temperature (deg C) in Utown on March 21, 2016 (12am- 05am)
12:00 AM
01:00 AM
02:00 AM
03:00 AM
04:00 AM
05:00 AM
Mean Radiant Temperature (deg C) in Utown on March 21, 2016 (06pm- 11pm)
06:00 AM
07:00 AM
08:00 AM
09:00 AM
10:00 AM
11:00 AM
Result_Analysis Mean Radiant Temperature (deg C) Max at Daytime – 79.05
Max at Nighttime – 25.95
Urban Ventilation Analysis
1
2 3
Note: Solution method: First order upwind for Momentum and Standard for Pressure North wind: 2m/s at reference height of 15m; Wind profile: Log law
Wind Profile-North
Source: Prevailing wind direction & speed obtained from NEA over a period of 18 years
1 Hot spot -Residential college 4
Area 1
Area Weighted Wind Velocity at 2m above ground= 0.477 m/s
2 Hot spot – Yale NUS colleges
a e r A
2
Area Weighted Wind Velocity at 2m above ground= 0.985 m/s Vortices continuously circulated in the courtyard
3 Hot spot – Town Green
Area 3
Area Weighted Wind Velocity at 2m above ground= 1.02 m/s Strong wind flow in the open area
Solar Exposure- Analysis
Sun Path Diagram of Singapore
Solar Exposure- Analysis 40%
1.62% 30%
40% 70% 90% 100% 30% 60% 70% 30% 60%
90%
Results The solar exposure percentage • Roof level ranges from 70% to 100% • North sides ranges from 1.62% to 40% • South sides ranges from 40% to 70% • East sides ranges from 30% to 60% • West sides ranges from 30% to 60%
Need for cool roof and green roof
Outdoor Thermal Comfort
Methodology-TSV Equations TSV Equation TSV without Tmrt
TSV with Tmrt
Perception Scale TSV range -3 ～ -2 -2 ～ -1 -1 ～ 0 0 ～ 1 1 ～ 2 2 ～ 3
Note: TSV without Tmrt is adopted by Steven Tool
Perception cold to cool cool to slightly cool slightly cool to neutral neutral to slightly warm slightly warm to warm warm to hot
Methodology-PET
Results-TSV Equations
Percentage of Dissatisfaction (PD) Outdoor thermal comfort-Daytime
TSV with Tmrt Location Ta[C] Area 2 33.2 Daytime Area 3 33.4
V [m/s] Tmrt 0.985 58.82 1.02 74
100% 90%
TSV 4.4 5.0
P 9% 5%
PD 91% 95%
Area 1
25.9
0.477
23.68
0.3
91%
9%
Area 2
25.9
0.985
23.68
0.1
92%
8%
Nighttime
Sensation Warm to hot Warm to hot Neutral to slightly warm Neutral to slightly warm
80%
91%
95%
70% 60% 50% 40% 30% 20%
17%
10% 0%
PD wi th Tmrt
PD wi thout Tmrt Area 2
TSV without Tmrt Daytime Nighttime
Area 3
Outdoor thermal comfort- Nighttime
Location
Ta[C]
V [m/s]
TSV
P
PD
Area 2
33.2
0.985
0.9
83%
17%
Area 3
33.4
1.02
0.9
83%
17%
Area 1 Area 2
25.9 25.9
0.477 0.985
-1.0 -1.4
98% 99%
2% 1%
Sensation Neutral to slightly warm Neutral to slightly warm Cool to slightly cool Cool to slightly cool
10% 9% 8% 7%
9% 8%
6% 5% 4% 3% 2%
2%
1%
Note: Area 1, 2 3 corresponds to hot spots 1, 2, 3
17%
0%
PD wi th Tmrt
1%
PD wi thout Tmrt Area 1
Area 2
Results-PET
Daytime Night time
Area
PET
Perception (SG)
Perception (Europe)
2
45.8
Very Hot
Very Hot
3
54.1
Very Hot
Very Hot
1
23.9
Slightly Cool
Slightly Warm
2
26.3
Neutral
Slightly Warm
Comparison-Two TSV equations VS PET
Daytime
Nighttime
Location
TSV with Tmrt
Area 2
Warm to hot
Area 3
Warm to hot
Area 1 Area 2
Neutral to slightly warm Neutral to slightly warm
TSV without Tmrt Neutral to slightly warm Neutral to slightly warm
PET Very hot Very hot
Cool to slightly cool
Slight cool
Cool to slightly cool
Neutral
Mitigation Strategy-Estate Level Cool roof with higher albedo
Material properties of Roof in ENVI-met
Original
R=0.3
Improved
R=0.48
Decrease of Air temperature (Ta) Min: 26. 61 Max: 31.89
Min: 19. 89 Max: 31.13
Decrease of Mean Radiant Temperature (Mrt) Min: 53. 76 Max: 79.05
Min: 50.39 Max: 75.63
Causes • More shortwave radiation directly reflected by roof from surface to space
R=0.3
Effects • Lower Air temperature (Ta) and Mean radiant temperature (MRT) at the outdoor • Reduction of Ta is more significant than MRT
R=0.48
• Improve outdoor thermal comfort • Reduction of UHI effects
Cool ROOF
Mitigation Strategy-Estate Level Void Deck
Yale-NUS
U Town Residence
Yale College-Increase of Wind velocity
Original
Improved
• Not very effective in terms of velocity magnitude • But the ground wind movements are improved, 0.985removing m/s the ground level pollutants • Improve uniformity of wind distribution
0.773 m/s
Town green-Increase of Wind velocity
Original
Improved
• Increase of velocity magnitude • Enhance wind movements 1.020 m/s • Improve uniformity of wind distribution
1.112 m/s
Yale NUS-Decrease of Air temperature Tmax
Tmax
• Decrease 32.8 33.2 of Ta at both daytime and nighttime
Daytime
Original (Daytime)
Improved (Daytime)
• A good way to lease the trapped heat between buildings • Effects on reductionTmin of Ta Tmin maybe more significant when 25.9 25.6 combines the wind simulation
Nighttime Original (Nighttime)
Improved (Nighttime)
Mitigation Strategy-Estate Level Planting Greenery
Town Green – Daytime hot spots Tmax Medium greenery density
Lower greenery density
33.4
0.2
33.2
Higher greenery density
0.6
32
Yale-NUS
Daytime hot spots Lower greenery density
Tmax
Medium greenery density
33
33.1
33.2
Higher greenery density
Nighttime hot spots Lower greenery density
Tmin
25.9
Medium greenery density
25.7
Higher greenery density
25.6
Location
Summary of Mitigation (Estate Level)
Table: TSV and PET for each mitigation strategy
Time
Mitigation
Yale-NUS Daytime Cool roof Town Green Yale-NUS Void Daytime Town deck Green Medium greenery Town density Daytime Green Higher greenery density Medium greenery density Daytime Higher greenery density Yale-NUS Medium greenery density Nighttime Higher greenery density
Ta[C]
V [m/s]
Tmrt
TSV with Tmrt
33.2
0.985
55.44
4.3
TSV without Tmrt 0.9
33.4
1.02
71.5
4.9
0.9
52.7
Very Hot
32.8
0.773
58.82
4.3
0.9
45.7
Very Hot
33.4
1.112
74
5.0
0.8
53.8
Very Hot
33.2
0.985
58.82
4.4
0.9
45.8
Very Hot
32.6
0.985
58.82
4.1
0.7
45.3
Very Hot
33.1
0.985
74
4.9
0.8
53.9
Very Hot
33
1.02
74
4.9
0.8
53.7
Very Hot
25.7
1.02
23.68
0.0
-1.5
22.7
Slightly Cool
25.6
1.02
23.68
0.0
-1.6
22.7
Slightly Cool
PET
PET sensation
43.8
Very Hot
Mitigation Strategy-Building Level Green Roof and Vertical Greenery
Existing Building Study-ERC
Roof Type
Addition Layer Turfing: Turf Roof Soil Substrate (40% Moisture Content): Shrubs Shrub roof Soil Substrate (40% Moisture Content): Trees Tree roof Soil Substrate (40% Moisture Content): Education Resource Centre - NUS
Property R-value thickness R-value R-value thickness R-value R-value thickness R-value
Value 0.36 100 0.063 1.61 300 0.19 0.57 700 0.443
Total R-value 2.372
3.749
2.962
Ref: N.H. Wong, etc., the effects of roof top garden on energy consumption of a commercial building in Singapore
Existing Building Study-ERC Peak Cooling Load (kW)
Reduction Percentage
223.3 220.3 214.1 216.4
1.34% 4.12% 3.09%
Flat Roof Turf Shrubs Trees
Space Conditioning Peak Sensible Load (kW) 580
Peak cooling Load (kW)
570 560 550 540 530 520 510 Flat Roof
100% Turf
100% Shrubs
Roof Type Floor 1
Floor 2
Floor 3
Floor 4
100% Trees
Mitigation for Yale-NUS: Green Roof and Vertical Greenery
Cluster of Yale-NUS Buildings High-rise Building: small roof area large wall surface
Low-rise Buildings: Large roof area
Focusing on 1. Green roof 2. Green Faรงade
External wall Glazing Roof
Property
Value
U-value (W/m2K)
1.46
U-value (W/m2K)
1.47
Shading Coefficient
0.7
U-value (W/m2K)
0.475
Green Roof 1130 1120 1110 1100 1090 1080 1070 1060 1050
1105.09 3130.59 1080.61 3096.93
3160 3150 3140 3130 1088.96 3112.24 3120 3110 3100 3090 3080 3070
Building Load (mWh)
Peak Cooling Load (kW)
Comparison of different types of roofs for the building
Roof Type Peak Cooling Load
Building Load
Conclusion 1. Green roof has positive impact on lowering down Peak Cooling Load and annual Total Building Load 2. Roof with 100% cover of shrubs has most significant positive impact
Green Roof 205
680
200
670
195
191.22 653.63
660
190
650
185
181.87 177.14
180
638.57
630
175
626.05
170
620 610
165 160 Flat roof
640
Roof with 100% Turf
Roof with 100% Shrubs
Roof Type Peak Cooling Load
600 Roof with 100% Trees
Building Load (mWh)
Peak Cooling Load (kW)
Comparison of different types of roofs for the Top Floor
Total Building
Peak Cooling Load (kW)
Reduction Amount
Flat roof Roof with 100% Turf Roof with 100% Shrubs Roof with 100% Trees
1122.77 1105.09 1080.61 1088.96
17.68 42.16 33.81
Top Floor Flat Roof Roof with 100% Turf Roof with 100% Shrubs Roof with 100% Trees
Peak Cooling Load (kW) 201.55 191.22 177.14 181.87
Reduction Amount 0.0% 10.33 24.41 19.68
Building Reduction Load(MWh) Amount 3147.56 3130.59 3096.93 3112.24
16.97 50.63 35.32
Building Reduction Load(MWh) Amount 667.22 0.0% 653.63 13.59 626.05 41.17 638.57 28.65
Building Load
Conclusion: 1. Green roof has most significant impact on top story in terms of both peak cooling load and total building load 2. It has limited impact on lower stories in term of building load 3. Further investigation needed on the effectiveness of greenroof
Vertical Greenery System Comparison of vertical greenery impact on peak cooling load and building load 1140
1120
3200 3100 3009.95
Layers
R-value
Turfing Layer
0.36
Substrate Layer (0.1m)
1.923
Air gap (0.1m)
0.16
1100
2900
2793.61
1080
1060
2700
1056.15 1048.86
1040
1020 Baseline
2800
2595.45 2600 1042.26
Building Load (MkW)
Peak Cooling Load (kW)
3000
2500
Green Faรงade
Green Faรงade with SC of 0.5
Vertical greenery systems Peak Cooling Load
Building Load
2400 Green Faรงade with SC of 0.3
R-value increases from 0.516 to 0.926
WWR= 0.25 Baseline Shading Coefficient = 0.7 SC=0.5, SC=0.3 are also simulated
Summary of Green Roof and Vertical Greenery Performance Comparison of peak cooling load and building load reduction 20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0%
19.0% 16.7%
17.5%
11.2% 5.9% 4.4%
6.6%
7.2% 1.6% 0.5%
3.8% 1.6%
3.0% 1.1%
Green roof
Cool roof Peak cooling load reduction
Building load reduction
Pros
Cons High Biodiversity maintenance fee Dampness problem, need Noise reduction good water proofing Increase Reduce storm building water runoff structure load Increase aesthetic Low structure Probably facing load glare issue
Research limitation
Accuracy of simulation
• Integration between wind distribution and air temperature were not assessed by this study • Building energy consumption were assessed based on weather file, was not integrated with microclimate computed from this study
• Results of wind simulation can be improved by implementing the second order upwind discretization and the enclosure size can be extended to minimize the influence from boundary on the wind flow, mesh independency test should be conducted prior to the final simulation
• Difference of air temperature results between Steven tool an ENVI-met was not covered in this study
• Terrain was not considered in this project, which will influence the results of air temperature and wind flow simulation
• Different software were required to use in the project, results in less integration
• Adding construction layers will enlarge thermal mass
• TSV calculation only conducted for the worst scenario
• Shading effect from surrounding building • Further study on green roof impact on buildings with different building sizes
Thank You..