Parametric Studies of Urban Morphologies of High Density Cities and Their Air Ventilation Performance under Neutral and Unstable Atmospheric Conditions Using Advanced Large-Eddy Simulations ICUC9, 20 th -24 th, July 2015, Toulouse, France Presenter: Edward Ng 1, 2 Contributors: Siegfried Raasch 3, Tobias Gronemeier 3, Steve Yim 2, Justin Ho 2, Weiwen Wang 1,ChaoYuan 4 1., 2. Institute of Environment, Energy and Sustainability, 3. Institute of Meteorology and Climatology, Leibniz University of Hanover 4. and Planning, Massachusetts Institute of Technology
Improve Air Ventilation by Better Urban Planning Legend A 1m/s improvement in urban air ventilation due to better design and planning can mitigate a 2 C rise in the urban heat island (UHI) (Ng & Cheng, 2012) 2
Air Ventilation Assessment (AVA) in Hong Kong The current AVA planning guidelines in Hong Kong 3
Air Ventilation Assessment (AVA) in Hong Kong Design new Compare designs Evaluate, select, alter and improve design Report SVR & LVR SVR site spatial average VR LVR local spatial average VR Test points Perimeter test points Overall test points Special test points Work out VR The current AVA has limitations under unstable 16 p Model VRw VRw Fi VRi atmospheric boundary conditions in weak background i 1 V V wind (Ng & Fung, 2008) Testing Further studies Use appropriate wind profiles and characteristics, test 16 directions 4
Gaps between Current Practice and Real Situations Estimation of the frequencies of different Pasquill stability classes using 10-year (2002 2012) HKO upper sounding data shows that more than 90% of the time is in an unstable condition at 2p.m. The observed convergence near the urban area in the afternoon of summer days 5
Simulations of Convective Boundary Layers (CBLs) Limitation of most CFD and wind tunnel studies: assume neutral conditions Few studies have a domain large enough to capture convective scale eddies as well as resolving urban canopy turbulence (Barlow, 2014) The capability of PALM for simulating a CBL has been demonstrated (Castillo, et al. 2011; Inagaki et al., 2012; Park and Baik, 2014). These studies focus on the dynamical process and flow structure of CBLs Schematic of the numerical domain in Inagaki et al. (2012) 6
The PArallelized LES Model (PALM) The code is optimized for massively parallel computers, and is suitable for fine-scale (1 2 m grid) and large computational domain (10 20 km) The turbulence recycling method for the non-cyclic boundary condition http://palm.muk.uni-hannover.de/ 7
Very First Runs of Unstable Conditions Horizontal wind velocity components (u, v) and temperature (θ) profiles calculated by the precursor run at the last time step 8
Potential Temperature and Vertical Velocity 9
Wind Velocity Ratio 10
Difference in Wind Velocity Ratio 11
The Parametric Approach Parameters to be investigated Variables used Height Differential homogeneous inhomogeneous Frontal Area Density (λ f ) 0.1 0.25 0.4 Ground Coverage Ratio (λ p ) 25% 50% 75% Plot Ratio (P) 3.0 5.0 8.0 Calculation of Geometry Index * Inhomogeneous building heights are generated by a random series Assuming floor height (h) is 3m, site area (s) is 1km 2, and floor area (A) is 2000m 2 (residential), or 4000m 2 (commercial) Building height (H): H = hp λ p (independent to Floor area A) Building number (N): N = sλ p A Building size (frontal size L): L = A λ f hp Building size (perpendicular size D): D = h P λ f (independent to Floor area A) 12
Parametric Models frontal area density site coverag e ratio actual building number building matrix : row building matrix: column Building size 1 (parallel size D) Building size 2 (frontal size L) Street width (perpendicular ) plot Floor building building No. ratio area number height 1 3.0 0.1 25% 2160 116 120 12 10 36 90 24 10.0 59.3 2 3.0 0.1 50% 2160 231 232 29 8 18 90 24 35.0 10.4 3 3.0 0.1 75% 2160 347 350 35 10 12 90 24 10.0 4.5 4 3.0 0.25 25% 2128 117 121 11 11 36 38 56 52.9 34.9 5 3.0 0.25 50% 2128 235 240 15 16 18 38 56 24.5 10.6 6 3.0 0.25 75% 2128 352 352 16 22 12 38 56 7.4 6.5 7 3.0 0.4 25% 2160 116 120 10 12 36 24 90 59.3 10.0 8 3.0 0.4 50% 2160 231 232 8 29 18 24 90 10.4 35.0 9 3.0 0.4 75% 2160 347 350 10 35 12 24 90 4.5 10.0 10 5.0 0.1 25% 4200 60 60 12 5 60 150 28 50.0 55.3 11 5.0 0.1 50% 4200 119 120 20 6 30 150 28 16.6 22.0 12 5.0 0.1 75% 4200 179 180 30 6 20 150 28 16.6 5.3 13 5.0 0.25 25% 2160 116 121 11 11 60 60 36 30.9 54.9 14 5.0 0.25 50% 2160 231 240 16 15 30 60 36 6.6 26.5 15 5.0 0.25 75% 2160 347 345 23 15 20 60 36 6.6 7.4 16 5.0 0.4 25% 2160 116 120 10 12 60 40 54 43.3 46.0 17 5.0 0.4 50% 2160 231 225 15 15 30 40 54 26.6 12.6 18 5.0 0.4 75% 2160 347 352 16 22 20 40 54 5.4 8.5 19 8.0 0.25 25% 4032 62 63 9 7 96 96 42 46.8 69.1 20 8.0 0.25 50% 4032 124 126 18 7 48 96 42 46.8 13.5 21 8.0 0.25 75% 4032 186 189 21 9 32 96 42 15.1 5.6 22 8.0 0.4 25% 3960 63 63 7 9 96 60 66 51.1 76.8 23 8.0 0.4 50% 3960 126 121 11 11 48 60 66 30.9 24.9 24 8.0 0.4 75% 3960 189 182 13 14 32 60 66 11.4 10.9 Street width (parallel) 13
Wind Velocity Ratio Model Density Homogeneous 400m 400m (600m 600m) Inhomogeneous 400m 400m (600m 600m) Low 0.20 (0.20) 0.16 (0.16) Medium 0.14 (0.14) 0.09 (0.09) High 0.05 (0.05) 0.07 (0.08) 14
Further Works The quartiles of parameters are calculated in Kowloon Peninsula (grid size 200m 200m), and will be used to set up the parametric models (a more realistic approach) 25 th Percentile 50 th Percentile 75 th Percentile Frontal Area Density 0.10 0.20 0.27 Ground Coverage Ratio 11% 26% 38% Plot Ratio 1.0 2.5 4.3 Parametric models: 3 density (low for 25 th percentile, medium for 50 th percentile, and high for 75 th percentile) 2 height differential (homogeneous and inhomogeneous) = 6 Large-domain neutral runs: 1 realistic + 6 parametric model = 7 DEM (7 neutral runs) Simulations for unstable conditions: 7 DEM 2 wind velocity 2 solar radiation = 28 unstable runs 15
Probability P(v) Meteorological Observations For Unstable Conditions Wind velocity: 1.3m/s and 3.0m/s Solar radiation: 200W/m2 (overcast sky), 600W/m2 (sunny) Anthropogenic heat estimated in the Kowloon Peninsula: 70 W/m 2 (building & traffic) Sea surface temperature in surrounding waters: 27.0 C (HKO) 0,3 0,25 0,2 0,15 0,1 0,05 0 Summer 0 2 4 6 8 10 12 Wind Speed (m/s) Summer Wind Velocity (m/s) 25 th Percentile 1.31 75 th Percentile 2.88 16
This Study Will Improve the Current AVA in Hong Kong Wind Current Used AVA version 1 Neutral Conditions 10% (at 2p.m.) This Study AVA version 2 Unstable Conditions 90% (at 2p.m.) 17
Thanks for your attentions. This study is supported by the Research Grants Council (RGC) of Hong Kong S. A. R. (Project No. 14408214), and Institute of Environment, Energy and Sustainability (IEES), CUHK (Project ID:1907002). 18