University of Aveiro

University of Aveiro Department of Environment and Planning

NATO ASI – 7th of May 2004 – Kyiv, Ukraine

J.H. Amorim,A.I. Miranda, C. Borrego

Air pollutants dispersion disturbance

due to urban vegetation:

a porous media modelling approach

to Lisbon city centre

INDEX of the presentation

• Motivation and objective of the work

• Methodology applied

• General characterisation of the model: FLUENT

• Description of the study-case (Liberdade Av., Lisbon)

• FLUENT application to the study-case

• Results presentation and analysis

• Conclusions

MOTIVATIONAs buildings, although with less significant consequences, trees (if existent) act as roughness elements, modifying the wind field. Consequently, the analysis of the dispersion conditions within a given area may become incomplete if these impacts were not considered.

What is the relative importance of the perturbations induced by What is the relative importance of the perturbations induced by vegetation on air pollutants dispersion within vegetation on air pollutants dispersion within urban environments??

- densely populated - high road-traffic emissions

Areas with problematic air quality standards

Computationally challenging problems

- complex 3D structures- turbulent flow field

- trees are commonly found on cities

main OBJECTIVE and METHODOLOGY

How far from the reality can we be How far from the reality can we be if neglecting these effects??if neglecting these effects??

As a first approach, the vegetative canopy effect over flow and air pollutants concentration fields inside a

typical urban environment was simulated applying a simple empirical model.

FLUENT MODEL validation

FLUENT vs Wind Tunnel- idealised urban geometry- Hot-wire anemometry (wind field comparison)- Flame Ionisation Detection (FID) (concentration field comparison)

General purpose CFD commercial numerical model

As FLUENT is intended for a wide range of engineering studies, its feasibility on local scale air quality modelling was previously evaluated.

FLUENT vs CFD model (VADIS)- real urban geometry (Lisbon downtown)- wind and concentration fields comparison

FLUENT model (brief) characterisation

Flow modelling:

Eulerian approach

Simplifications:

Steady-state 3D flow (1 hour averaged input/output values)

Incompressible fluid

Turbulence modelling:

Reynolds-averaged Navier-Stokes (RANS) equations

closure: k- model

Dispersion modelling:

Eulerian approach

No chemical reactions: CO (inert pollutant)

FLUENT application to LIBERDADE Av.

Simulation domain

Liberdade Av.

Lisbon downtown

Simulation period:

• 24 h

• typical working day (6th March, 2002)

Centred at Liberdade Avenue, one of the main thoroughfares of Lisbon city centre aspect ratio: H/W = 0.33

“avenue canyon” (<0.5)

1

4

10

12

5

8 9

5

Air quality monitoring station (AQMS)

11

1 – Liberdade Av.2 – Liberdade Av. (descending secondary lane)3 – Liberdade Av. (ascending secondary lane)4 – A. Herculano St.5 – Rua B. Salgueiro St.6 – Rua M. Silveira St.7 – Rua R. Araújo St.8 – Rua R. Sampaio St.9 – Rua S. Marta St.10 – Rua J. Machado St.11 – Rua M. Coelho St.12 – Rua do Salitre St.

67 8 9

5a 5b

101

2 3

1212 11

Emission sources definition

Emissions estimation

- developed at the University of Aveiro

- based on MEET/COST methodology

- emission factors are based on the average vehicles speed (this approach is considered correct when the influence of driving dynamics can be neglected)

- vehicles emissions are estimated individually for each road segment considering detailed information on traffic flux counting (VISUM traffic model output)

Road traffic emissions estimation: TRansport Emission Model for line sources (TREM)

0,0E+00

1,0E+03

2,0E+03

3,0E+03

4,0E+03

5,0E+03

6,0E+03

0 2 4 6 8 10 12 14 16 18 20 22 24

0,0E+00

5,0E+03

1,0E+04

1,5E+04

2,0E+04

2,5E+04

3,0E+04

Tra

ffic

flux

(n.º

veh

icle

s.h-1

)

CO

em

issi

on (

g.km

-1.h

-1)

Time (h)Traffic flux counting (Liberdade Av.)CO emission estimated by TREM

Meteorological data

- Meteorological station located nearby the computational domain

- Hourly averaged values of:

wind velocity and direction (10 m height), air temperature and RH

- Variable wind velocity (minimum: 4 m.s-1; maximum: 7 m.s-1)

- Predominant wind direction: NW

- Boundary conditions: logarithmic vertical wind profile

Wind velocityWind direction

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22 24

S

E

N

W

S

Time (h)

Vel

ocity

(m

.s-1)

Dire

ctio

n

Special characteristic of the domain

Presence of a large number of densely foliaged tall trees that flank the Avenue in its entire extension…

… creating a “green corridor” between both sides of the Av. and the houses.

Vegetation characterisation

a modified street-canyon wind pattern is expected due to the crown-induced disturbed flow.

The AQMS (National Air Quality Monitoring Net) is located within the expected

disturbance induced by the trees foliage

Vegetation characterisation

GridFLUENT 6.0 (3d, segregated, spe2, ske)

Dec 08, 2002

ZY

X

Domain 3D perspective

POROUS VOLUMES

Shape: regular blocksGround distance: 5 mDimensions: var. 15 m 10 m (L W H)

Porous medium modelling: Power-law approach

Source-term [Si, for the ith (x, y, or z) momentum equation] that establishes a relation

with the velocity (v):

iv)-(C

|v|C C

|v|C iS1

10

10

C0 = 10; C1 = 1

Domain 3D perspective with “vegetation” definition

top view

Domain volume: 650 × 650 × 80 m3 (L × W × H)

Grid: ~1 million unstructured cells (Gambit pre-processor: TGrid)

N.º buildings: 42 sets (h: 12 - 40 m)

N.º emission sources: 12

N.º porous media: 6 sets

Computational domain

0

200

400

600

800

1000

1200

1400

0 2 4 6 8 10 12 14 16 18 20 22 24

time (h)

CO

co

nce

ntra

tion

(µ

g.m-

3)

CO concentration (meas. & simul.) temporal variation

AQMSFLUENT WITH porous media

FLUENT WITHOUT porous media

Not despite the empirical characteristics of this approach the results fit better with the measurements in this case.

Model performance statistical analysis

More accurate modelling results are obtained when considering the porous media.

Paired Statistical Comparison Metrics

(ASTM Standard Guide for Statistical Evaluation of Atmospheric Dispersion Model Performance)

WITHporous media

WITHOUTporous media

Fractional bias (FB) 0.176 0.627

Normalised mean squared error (NMSE) 0.031 0.349

Pearson correlation coefficient 0.955 0.767

Model performance statistical analysis – linear regression

y = 0,7493x + 260,89

R2 = 0,9118

0

200

400

600

800

1000

1200

1400

1600

0 500 1000 1500

Simulated CO values (µg.m-3)

Mea

sure

d C

O v

alu

es (

µg.m

-3)

y = 0,7946x + 446,48

R2 = 0,5891

0

200

400

600

800

1000

1200

1400

1600

0 200 400 600 800 1000 1200

Simulated CO values (µg.m-3)

Mea

sure

d C

O v

alu

es (

µg.m

-3)

without porous media

with porous media

Contours of conc_co_µg.m-3FLUENT 6.0 (3d, segregated, spe2, ske)

Dec 05, 2002

2.89e+03

2.60e+03

2.31e+03

2.02e+03

1.74e+03

1.45e+03

1.16e+03

8.68e+02

5.78e+02

2.89e+02

0.00e+00Z

Y

X

with porous mediawith porous media


Dec 09, 2002

2.89e+03

2.60e+03

2.31e+03

2.02e+03

1.73e+03

1.45e+03

1.16e+03

8.67e+02

5.78e+02

2.89e+02

0.00e+00Z

Y

X

Conc. COµg.m-3


Dec 09, 2002

2.89e+03

2.60e+03

2.31e+03

2.02e+03

1.73e+03

1.45e+03

1.16e+03

8.67e+02

5.78e+02

2.89e+02

0.00e+00Z

Y

X

without porous mediawithout porous media

Concentration fields (z = 3 m)


Dec 09, 2002

2.89e+03

2.60e+03

2.31e+03

2.02e+03

1.73e+03

1.45e+03

1.16e+03

8.67e+02

5.78e+02

2.89e+02

0.00e+00Z

Y

X

results intercomparison: Δt = 11-12 a.m.Conc. CO

µg.m-3


Dec 09, 2002

2.89e+03

2.60e+03

2.31e+03

2.02e+03

1.73e+03

1.45e+03

1.16e+03

8.67e+02

5.78e+02

2.89e+02

0.00e+00Z

Y

X

[CO]with = 1400 µg.m-3 [CO]without = 700 µg.m-3

[CO]measured = 1300 µg.m-3

AQMSAQMS

AQMSVertical plane

crossing the Av. through the AQMS.

Unstructured meshL

e ft -

sid

e b

u il d

i ng

(Win

dw

ard

si d

e)

Liberdade Av.

Rig

ht-s

ide

bu

il di n

g(L

e ew

ard

sid

e)

POROUS MEDIUM

POROUS MEDIUM

Secondary traffic lane(~10% Lib. emission rate)

Secondary traffic lane(~10% Lib. emission rate)


Turbulent kinetic energy (TKE)k (m2.s-2)

Left

-si

de

bui ld

ing

Rig

h t -

side

bu

i ldin

g

with porous media

CO concentrationCCO (µg.m-3)


Lef t

-si d

e bu

i ldi n

g

Right -side building

with porous media

with porous media

Velocity x component

without porous mediaVx (m.s-1)

Left

-si

de

bui ld

ing

Rig

h t -

side

bu

i ldin

g

Within the avenue-canyon, the porous medium diminishes the velocity component perpendicular to the Av. from its left to the right side

+Vx

+Vx

with porous media

Velocity y component

without porous mediaVy (m.s-1)

Left

-si

de

bui ld

ing

Rig

h t -

side

bu

i ldin

g

The porous medium diminishes the velocity component parallel to the Av. and in its descendant sense

-Vy

-Vy

with porous media

Velocity z componentVz (m.s-1)


Lef t

-si

de

bui ld

ing

Rig

h t -

side

bu

i ldin

g

Both negative and positive vertical velocity components within the avenue-canyon are diminished by the porous medium effect

+Vz

-Vz

-Vz

+Vz

with porous media

CCO (µg.m-3)


CO concentration contours plus wind velocity streamlines

The recirculation across the street axis is still present, but the shape of the eddy has changed. Two additional vortices are formed.


with porous media

CCO (µg.m-3)

with porous media

CO concentration contours plus velocity vectorsCCO (µg.m-3)

Because the exchange rate of air with the atmosphere at the above roof-level is diminished and emissions are made under

the trees foliage, the formation of hot-spots is increased.


Lef t

-si

de

bui ld

ing

Rig

h t -

side

bu

i ldin

g

CO concentrationCCO (µg.m-3)

Within these dispersion conditions a CO concentration increase is obtained at the leeward side of the Avenue when

the porous media is present.


with porous media

CO concentration – results sensibility to vegetation heightCCO (µg.m-3)

5 m height porous media

0 m height porous media

CO concentration – results sensibility to vegetation heightCCO (µg.m-3)

CO concentration – results sensibility to vegetation height

The porous media trap pollutants within the emission source lateral boundaries, sheltering the buildings from the direct

impact of traffic emissions on local air quality.

CCO (µg.m-3)

CONCLUSIONS

The comparison between simulated and measured values shows that, although empirical and even incomplete from a physical point of view, the approach assumed is apparently more close to reality than it is the absence of it.

A perturbation caused by trees over the wind field should in fact exist because of the discrepancy between the “normal” simulation and the measured values, but its effect needs to be more accurately modelled.

CONCLUSIONS

Apart from all the assumptions made, the results suggest that the decrease of the velocity within the porous media, and the consequent weakening of the dispersion inside the canyon, has the potential to originate undesired effects on air quality.

However, these kind of ultimate effects are extremely dependent upon the local specific dispersion conditions and on the configuration and intrinsic characteristics of the vegetative canopy present.

As future work, an effort will be made in order to apply an appropriate and validated model for the simulation of the

perturbations induced by trees on Lisbon downtown.

the end

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