Parameterization of Pollutant Plume Dispersion in Neutral

Stratification over Hypothetical Urban AreasChi-To Ng and Chun-Ho Liu*

Department of Mechanical Engineering The University of Hong Kong

13th EMS Annual Meeting & 11th European Conference on Applications of Meteorology (ECAM)September 9 to 13, 2013; Reading, United Kingdom

*Corresponding Author: Chun-Ho LIUDepartment of Mechanical Engineering, 7/F Haking Wong Building, The University of Hong Kong, Pokfulam Road, Hong KongTel: (852) 2859 7901; Fax: (852) 2858 5415; liuchunho@graduate.hku.hk; http://me.hku.hk

Introduction• Ground-level pollutants from human activities and

vehicles are the primary pollutant sources, which adversely affect the health and living quality of urban inhabitants.

• Large-scale roughness elements such as buildings and mountains can significantly modify the pollutant dispersion behaviour.

• The Gaussian model of plume dispersion is commonly used to estimate the downwind pollutant concentration distribution. However, one of its major parameters, the dispersion coefficient (σz), often underestimates the importance of buildings in urban areas.

Objectives• The aerodynamic effects of idealized urban

roughness were parameterized with a single variable – friction factor (f), which is believed to be sufficient to measure the resistance of urban roughness at constant UBL height for comparison in our previous studies (Wong and Liu, 2013).

• Parameterize pollutant dispersion behaviour (σz) with idealized urban roughness (f) to enrich the understanding of pollutant dispersion and removal mechanism in urban areas.

Methodology• Renormalization Group (RNG) of kappa-

epsilon (k-ϵ) turbulence model

• 2-dimensional computational domains consisting of idealized street canyons were used to represent the hypothetical urban areas

• A total of 144 models with eight different building shapes and eighteen different building-height-to-street-width (aspect) ratios (ARs)

• Covering the characteristic skimming flow,

wake interference and isolated roughness regimes

Computational Domain and Boundary Conditions

Idealized Building Shapes

Aspect Ratios and Setups

Friction Factor ( f )• A dimensionless number represents the

surface roughness caused by different building morphology (building shapes and ARs)

𝑓 =∆ 𝑃 x𝐻 /𝐿𝑈 2/2

, L

H

Friction Factor ( f ) vs ARs• Friction Factor decreases when the street is

extremely wide, it is because the wind flows and street configurations reached isolated roughness regime

0.01 0.1 1 100

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

RectTriTrapTri_RectWRAWTrapLTrapLRA

Aspect Ratio

Friction Factor

z0 vs Friction Factor ( f ) • z0 is obtained from ensemble average of

velocity profile in horizontal direction and log profile

0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.040

0.020.040.060.080.1

0.120.140.160.180.2

z0 vs f

Friction Factor (f)

Z0

Gaussian Plume Model and Dispersion Coefficients (σz)

• Gaussian plume model

Dispersion Coefficients (σz) and Length Scale• (1)

• (2)

• Sub (1) into (2)

Mixing length hypothesis

Near surface∈neutral stratification

Dispersion Coefficients (σz) vs Friction Factor ( f )

0.25 0.27 0.29 0.31 0.33 0.35 0.37 0.39 0.41 0.43 0.450

0.1

0.2

0.3

0.4

0.5

0.6

f(x) = 1.97233482271879 x − 0.404479266692124R² = 0.889588750536099

f(x) = 1.41102093902522 x − 0.132977467243462R² = 0.940719986712538f(x) = 1.33211144294044 x − 0.086630214610031R² = 0.923512910398533

HighLinear (High)MeanLinear (Mean)LowLinear (Low)

ff^0.25

σ/x^0.5

Conclusions

• The mean value of σz / x1/2 was found to be direct proportional to f1/4 with the coefficient of determination equal to 0.9407.

• The mean value of σz / x1/2 is close to the upper limit.

• Friction factor (f) is believed to be able to estimate the range of dispersion coefficients (σz) for urban areas.

Thank you