Improve Air Ventilation by Better Urban Planning

Transcription

1 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

2 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

3 Air Ventilation Assessment (AVA) in Hong Kong The current AVA planning guidelines in Hong Kong 3

4 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

5 Gaps between Current Practice and Real Situations Estimation of the frequencies of different Pasquill stability classes using 10-year ( ) 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

6 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

7 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 7

8 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

9 Potential Temperature and Vertical Velocity 9

10 Wind Velocity Ratio 10

11 Difference in Wind Velocity Ratio 11

12 The Parametric Approach Parameters to be investigated Variables used Height Differential homogeneous inhomogeneous Frontal Area Density (λ f ) Ground Coverage Ratio (λ p ) 25% 50% 75% Plot Ratio (P) 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

13 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 % % % % % % % % % % % % % % % % % % % % % % % % Street width (parallel) 13

14 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

15 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 Ground Coverage Ratio 11% 26% 38% Plot Ratio 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

16 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 Wind Speed (m/s) Summer Wind Velocity (m/s) 25 th Percentile th Percentile

17 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

18 Thanks for your attentions. This study is supported by the Research Grants Council (RGC) of Hong Kong S. A. R. (Project No ), and Institute of Environment, Energy and Sustainability (IEES), CUHK (Project ID: ). 18