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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
Contours of conc_co_µg.m-3FLUENT 6.0 (3d, segregated, spe2, ske)
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
Contours of conc_co_µg.m-3FLUENT 6.0 (3d, segregated, spe2, ske)
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)
Contours of conc_co_µg.m-3FLUENT 6.0 (3d, segregated, spe2, ske)
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
Contours of conc_co_µg.m-3FLUENT 6.0 (3d, segregated, spe2, ske)
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)
without porous media
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)
without porous media
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)
without porous media
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)
without porous media
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.
without porous media
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.
without porous media
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.
without porous media
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