Dispersion in urban areas - web5.arch.cuhk.edu.hkweb5.arch.cuhk.edu.hk/asi2011/en/Sources/ASI_PPT_Final/ASI PDF/ASI... · ASI2_Lecture 5_8/12/2011 2 ASI 2: URBAN CLIMATE AND AIR POLLUTION

ASI2_Lecture 5_8/12/2011

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ASI 2: URBAN CLIMATE AND AIR POLLUTION School of Architecture, The Chinese University of Hong Kong, Hong Kong, 7-8 Dec 2011

Dispersion in urban areas

• Stephen Belcher• Professor of Meteorology• Department of Meteorology,

University of Reading, U.K.

Croucher Advanced Study Institute 2011-2012Urban Climatology for Tropical & Sub-tropical Regions

Lecturer’s Photo


Figure 1. Aerial view of DAPPLE site

N


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Figure 1. Aerial view of DAPPLE site

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What area would be contaminated?

• How does the plume disperse in urban area?– Need ground level concentration

– Decay with distance from source Cmax

– Horizontal spread of plume f• What aspects of city control this area?

– Building geometry– Street network

• What aspects of met control this area?– Wind speed & direction– Stability effects - ignored here

U

R


Paradigms for ABL dispersion• Turbulence in ABL?

– Eddying motion moves material vertically and laterally– Parametrised e.g. in Gaussian plume model

• Advection along streets?– Material carried along streets– Branches at intersections

• Other effects– Tall buildings

• Groups• Isolated tall buildings

– Atmospheric stability• Unstable predominant category in UK cities


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The 2007 DAPPLE experiments

Wood et al (2009) Bull. Am. Met. Soc.


Release strategy

Receptors fixed

Sources change with wind direction

3 tracers per expt

Wood et al (2009) Bull. Am. Met. Soc.


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Schematic flows

Belcher (2005) Phil Trans Roy Soc

Dobre et al (2005) Atmos. Env.

Balogun et al (2010) B.L. Met.


Empirical results from DAPPLE

Or dosage = time integrated concentration


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0.001

0.01

0.1

1

10

100

0.1 1 10 100

R/H

0.001

0.01

0.1

1

10

100

0.1 1 10 100

R/H

Decay from source: Dmax(R)

• Normalization

• R/H < 4

– Not ordered

• R/H > 4

– Ordered

– Upper bound

rooftop wind

upwind

downwind

cross wind

channelled

D* DUH H 2

M

Field all wind

Wind tunnel SW wind

4 = 1 street length

Dmax AM

UHR2Solid: A = 12

Dotted: A = 6

R/L1 2 4


DNS: Direct Numerical Simulation

Branford et al (2011) B.L.Met


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Specification All motions resolved No turbulence model 6.7 x 107 grid points Wall time ~3 weeks 248 processors Re = u*H/ = 7000 Aligned + staggered arrays

16H x 16H x 8H

Direct numerical simulation

Red lines: water channel (Hilderman & Chong 2007)

Flow field reported in Coceal et al (2006)


Mean concentration

Time and space average

Within canopy Above canopy


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Concentration fluctuations


What disperses the material?


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Far field

Network region



Far field

Network region

Entrainment flux



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Network model for dispersionNetwork model for dispersion

Soulhac PhD Thesis Ecole Centrale Lyon

Belcher (2005) Phil. Trans. Roy. Soc.

Hamlyn et al (2005) Atmos. Env.

Belcher et al (in prep)

Soulhac PhD Thesis Ecole Centrale Lyon

Belcher (2005) Phil. Trans. Roy. Soc.

Hamlyn et al (2005) Atmos. Env.



Above canopy

Within canopy

Lateral turbulent transport neglected in canopy

Network model for dispersion

Calculate time and space averaged concentration C


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Street network model

Fij2

Fij3

Fij4

Fij1

Fij5

U

Fij1

Fi-1,j3

Fi-1/2,j5

Compute fluxes into boxes, where conc assumed well mixed


Mathematical formulation

• Assume each street box and intersection box well mixed

• Balance fluxes into intersections and streets

• Parameterize fluxes– Advective fluxes along streets

– Diffusive exchange flux


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Solution for regular geometry

• Regular geometry, then:

• Where

– is fraction of flux lost to entrainment

– is fraction of flux going to right

– is fraction of flux going to left p 1 - p

p 1 - p p 1 - p


i j

n

k

p 1 - p

p 1 - p p 1 - p

k = 0 (n,k)

‘Leaky combinatorics’

Galton’s quinqunx


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Solution for regular geometry

• Solution is ‘leaky’ binomial distribution

– is number of intersections

– is position across array

• Solution tends to Gaussian for large np


Comparisons with DNS

Goulart, PhD Thesis, University of Reading



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Street Intersection

U 1.18 1.12

V 1.18 1.13

E 0.3 0.5

2 4 6 8 10 12 14 160

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

x/H

Con

cent

ratio

n/C

0,0

Model parameters

Variation of centreline concentration

DNS data

NM without re-entrainment

Nm with re-entrainment

Centreline concentration


Uabv 3.5

Vabv 3.5

Kxx, Kyy 0.5

Kzz 0.3

Model parameters for above canopy

With re-entrainment

DNS data



Centreline concentration


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5 10 150

0.1

0.2

y/H

Con

cent

ratio

n/C

0,0

5 10 150

0.1

0.2

y/H

Con

cent

ratio

n/C

0,0

5 10 150

0.02

0.04

0.06

0.08

0.1

y/H

Con

cent

ratio

n/C

0,0

5 10 150

0.02

0.04

0.06

0.08

0.1

y/H

Con

cent

ratio

n/C

0,0

2H 3H

6H 8H

Lateral concentration profiles

DNS data



In-canopy lateral profile


In-canopy lateral profile

2H 3H

6H 8H

With re-entrainment

DNS data




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2/21/11

Above canopy concentration on centreline

0 5 10 150

0.02

0.04

0.06

0.08

x/H

Con

cent

ratio

n/C

s

0 5 10 150

0.05

0.1

x/H

Con

cent

ratio

n/C

s

0 5 10 150

0.02

0.04

0.06

0.08

x/H

Con

cent

ratio

n/C

s

1 2 3 4 5 6 7 8 910111213141516

123456789

10111213141516

x/H

y/H

Good agreement further from the source

Con

cent

ratio

n/C

0,0

0

0

0

0

Con

cent

ratio

n/C

0,0

0

0

0

Con

cent

ratio

n/C

0,0

Above roof concentration

DNS data




2/21/11

5 10 150

0.1

0.2

2H from the source

y/H

Con

cent

ratio

n/C

s

5 10 150

0.1

0.2

3H from the source

y/H

Con

cent

ratio

n/C

s

5 10 150

0.1

0.2

0.36H from the source

y/H

Con

cent

ratio

n/C

s

5 10 150

0.1

0.2

0.38H from the source

y/H

Con

cent

ratio

n/C

s

Above canopy concentrationGood agreement further from the source

0

0

0

0

Con

cent

ratio

n/C

0,0

0

0

0

Con

cent

ratio

n/C

0,0

Con

cent

ratio

n/C

0,0

Con

cent

ratio

n/C

0,0

2H 3H

6H 8H

Above roof concentration

DNS data




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Back briefly to DAPPLE data


Lateral spread of plume: f

Diamonds: wind tunnel measurements

Squares: full-scale measurements

Stars: branching network model

Blue: plume core (f > 0.65)

Green: plume edge (0.65 > f > 0.1)

Orange: outside plume (0.1 > f).

D R, Dmax R f R, Plot contours of f

Dashed line: Briggs (1973) spread

f BR


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Summary and conclusions

• Extensive measurements during DAPPLE experiments– Western Europe geometry– Complements Salt Lake City & Oklahoma City

• DNS for simplified geometries– All scales of turbulence computed– Useful for process studies

• Street network model– Streets and intersections: well mixed boxes– Works well for H ~ W– 3 regimes

• Near field - complex• Street network scale - network model works well• Far field - Gaussian plume sufficient

– Any good for Hong Kong?!


Stephen BelcherDepartment of MeteorologyUniversity of ReadingU.K.Tel: 0118 378 6646 Email: [email protected]: http://www.met.rdg.ac.uk/~bl_met/index/

End, Thank You

Documents

Dispersion in urban areas - web5.arch.cuhk.edu.hkweb5.arch.cuhk.edu.hk/asi2011/en/Sources/ASI_PPT_Final/ASI PDF/ASI... · ASI2_Lecture 5_8/12/2011 2 ASI 2: URBAN CLIMATE AND AIR POLLUTION