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CFD modelling of tree-atmosphere interaction andassessment of air quality in street canyonsSabatino, Di, S.; Buccolieri, R.; Gromke, C.B.
Published in:Proceedings of the CLIMAQS Workshop ‘Local Air Quality and its Interactions with Vegetation’, January 21-22,2010, Antwerp, Belgium
Published: 01/01/2010
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Citation for published version (APA):Sabatino, Di, S., Buccolieri, R., & Gromke, C. (2010). CFD modelling of tree-atmosphere interaction andassessment of air quality in street canyons. In Proceedings of the CLIMAQS Workshop ‘Local Air Quality and itsInteractions with Vegetation’, January 21-22, 2010, Antwerp, Belgium (pp. 1-50)
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CFD modelling of tree-atmosphere interaction and CFD modelling of tree-atmosphere interaction and assessment of air quality in street canyonsassessment of air quality in street canyons
SILVANA DI SABATINO Dipartimento di Scienza dei Materiali - University of Salento (ITALY)
RICCARDO BUCCOLIERI Dipartimento di Informatica - Università “Cà Foscari” di Venezia (ITALY)
Dipartimento di Scienza dei Materiali - University of Salento (ITALY)[email protected]
CHRISTOF GROMKE WSL Institute for Snow and Avalanche Research SLF (Switzerland)
Institute for Hydromechanics - University of Karlsruhe (GERMANY)[email protected]
Antwerp, Belgium, January 21-22, 2010
Local Air Quality and its Interactions with Vegetation
UNIVERSITY OF SALENTO (ITALY)
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Introduction - Background ideas / urban areas (buildings, trees ..)
Previous work - Single tree - Line of vegetation - Trees in street canyons
CFD simulations (RANS mainly)/validation - Aerodynamic effects of trees in street canyons - Aerodynamic effects of tree in complex geometries (IDEALISED)
– Application to a real case scenario - Bari city (Italy)
Conclusions and future perspective
OutlineOutline
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Urban surface is source of drag, heat and pollution Street (canyon)
scale
Neighbourhood scale
City scale
Flow and dispersion modelling is currently possible at many levels of sophistication depending on applications
IntroductionIntroductionScale definitions
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STREET CANYONSTREET CANYON
aspect ratioaspect ratio, W/H
city basic geometry unit
geometries which affect flow and turbulence fields
where the people and (the emissions) arewhere trees can be planteddirect CFD/LES is practicableoperational modeling is typically based on a more idealized recalculating vortex driven by a shear layertraffic pollutants released near the ground need to be “effectively” dispersed to maintain “adequate” air quality
Street canyon
IntroductionIntroductionUrban street canyons
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3-D flow field inside a street canyon with aspect ratio W/H ≈ 1
Oke, T.R., 1987. Boundary Layer Climates, 2nd Edition. Methuen, UK..
• approaching flow perpendicular to street axis• long street canyons (L/H > 7)• two dominating vortex structures: canyon vortex, corner vortex• superposition of vortex structures
IntroductionIntroductionQualitative Flow features
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IntroductionIntroductionExample of Urban street canyons
Street canyon without trees (but with people…!)
Street canyon with one-row trees Street canyon with two-rows trees
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Impact of trees in urban areas on pollutant dispersion not widely considered
Both experimental and numerical investigations are present in the literature
Some of the tree effects on flow and dispersion have been considered individually in previous works, such as deposition, filtration, blockage etc.
Still far from a comprehensive understanding of the overall role plaid by vegetation on urban air quality
One of the most extensive review is given by Litschke and Kuttler (2008), who reported on several field studies as well as numerical and physical modelling of filtration performance of plants with respect to atmospheric dust. The main goal of this review was to assess whether a reduction in particle concentration in the air could be accomplished by existing vegetation or targeted planting.
Where are we?Where are we?
Litschke, T and Kuttler, W., 2008. On the reduction of urban particle concentration by vegetation – a review. Meteorologische Zeitschrift 17, 229-240.
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Some tree effectsSome tree effectsLitschke and Kuttler (2008)
The deposition of particles on plant surfaces is influenced by a variety of factors:
diameter and shape of the particlesplanting configuration meteorological parameters (air relative humidity, wind speed and turbulence)
Deposition velocity (vd) is used as a measure of filtration performance
Fp: mass particle flow rate Cp: leaf surface and atmospheric particle concentration
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In urban areas, values seems not to exceed vd < 1 cm s−1.
At these deposition velocities, the improvement in air quality as a result of filtration by plants is about 1%; this implies that in order to compensate for local particulate emissions by road traffic, very large areas of vegetation would be needed.
Some tree effects: FiltrationSome tree effects: FiltrationLitschke and Kuttler (2008)
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obstacles to airflow (air mass exchange reduced)
Some observationsSome observationsLitschke and Kuttler (2008)
particle deposition on plant surfaces pollutant concentration reduced
pollutant concentration increased
New measurement method by Freer-Smith et al. (2005)
Filtration performance, in some cases, IS an order of magnitude higher than the values published to date
However, the in-situ measurements using the method proposed by Freer-Smith et al. (2005) will still need to be confirmed by further measurements
Deposition velocities of PM10, PM2 und PM1 on the foliage of Pinus sylvestris, X Cupressoparis leylandii, Acer campestre,Populus deltoides X trichocarpa ‘Beaupré’ and Sorbus aria (modified after FREER-SMITH et al., 2005).
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Tree Canopy ModellingTree Canopy ModellingMochida et al. (2008)
Extensive review on past tree canopy models based on the k-ε model in which extra terms were added in the transport equations to simulate the aerodynamic effects of trees, both on velocity decrease and increase in the turbulence and energy dissipation rate. Canopy models classified based on the different forms of extra terms adopted:
5 parameters in the extra terms
Cpε1, Cpε2: two model coefficients
3 extra terms:
-Fi: effect of trees on velocity decrease+Fk and +Fε: effects of trees on the amount of increase in turbulence and energy dissipation rate, respectively.
Mochida, A., Tabata, Y., Iwata, T. and Yoshino, H., 2008. Examining tree canopy models for CFD prediction of wind environment at pedestrian level. Journal of Wind Engineering and Industrial Aerodynamics 96, 1667-1677.
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FOCUS
1. Flow and dispersion around a single tree (field and numerical results)
1. Flow and dispersion around a line of vegetation (field and numerical results)
1. Flow and dispersion in street canyon with tree planting (field, wind tunnel and numerical results)
Example of recent results Example of recent results (not comprehensive!)(not comprehensive!)
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Field and laboratory studies
Several field campaigns, wind tunnel experiments and numerical simulations were performed to investigate the effects of trees on outdoor airflow distribution, turbulent diffusion of air pollutants and thermal environment in street canyons.
Field experiments: in Metropolitan Tokyo (Narita et al., 2008) in the central part of Sendai city, Japan (Kikuchi et al, 2009).
Wind tunnel experiments: CODASC, 2008 (University of Kalshrue)
Numerical simulations: e.g. Balczó et al., 2009 Gromke et al., 2008; Buccolieri et al., 2009
Literature review
Our work
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Field experiments (Narita et al., 2008)
Street canyon with trees (G-street)
Empty street canyon (non G-street)
Narita, K., Sugawara, H. and Honjo, T., 2008. Effects of roadside trees on thermal environment within street canyon. Geographical Report of Tokyo Metropolitan University 43.
Metropolitan Tokyo
Field studies
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The downward short wave radiation over the street with tree crown is about one-third of that without tree crown in midday. It shows clear shielding effects on solar radiation by “green tunnel”.
On the contrary, the downward long wave radiation under tree crown is about 20 – 30 Wm-2 larger than that of without tree crown throughout the day.
Field experiments (Narita et al., 2008) with treesempty
Field studies
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The air temperature and absolute humidity differences between the two streets are smaller than expected
There are few reports which implied that the increase of humidity in dense green area has an adverse influence on human comfort. In this case, however, there is no evidence for such a negative effect by the tree crown.
The wind speed difference is not so large
A possible negative factor of roadside trees for sensational climate is to weaken the wind speed of pedestrian level.
Field experiments (Narita et al., 2008)
with treesempty
Field studies
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During the day, because of the shading effect of the tree crown, the area-averaged road surface temperature in “G-street” is about 8 degrees lower than that in “non-G-street”.
During the night road surface temperature under the tree crown is one or one and half degrees higher than that of without tree crown. That is because the radiative cooling is diminished by the tree crown in the “G-street”.
In both streets, these temperature differences are always positive, that means road surface is heat source for the air in the street canyon even though under the tree crown.
Field experiments (Narita et al., 2008) with treesempty
Field studies
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Though roadside trees are expected as an important mitigation method for heat island phenomena, the difference of air temperature is negligible throughout the day comparing to the parallel street without tree crown.
The increase of humidity and the decrease of wind speed are not so discernible. As for the radiation field, however, there is clear shielding effects for solar radiation and downward longwave radiation, consequently the road surface temperature.
That means the main reason to feel comfortable under tree crown in thermal sensation is not the air temperature but the radiation effects.
Field experiments (Narita et al., 2008)
Field studies
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•Gross G. (1987): •influence tree planting (two rows arranged sidewise of the street next to the building walls) •k-ε turbulence closure scheme and modelling of the tree crowns by porous bodies•decelerated flow velocities near the building walls and increased pollutant concentrations inside the street canyon
•In a similar arrangement, Ries, K. and J. Eichhorn (2001) found local increases of the pollution concentration at the leeward wall accompanied by reduced flow velocities due to trees.
2D models applied (do not account for the highly 3D flow fields present in real urban street canyons of finite length)
Gross, G., 1987. A numerical study of the air flow within and around a single tree. Boundary-Layer Meteorology 40, 311-327.
Ries, K. and Eichhorn, J., 2001. Simulation of effects of vegetation on the dispersion of pollutants in street canyons. Meteorologische Zeitschrift 10, 229-233.
Numerical investigations
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WIND TUNNEL INVESTIGATIONSGromke, C. and Ruck, B., 2009. On the impact of trees on dispersion processes of traffic emissions in street canyons. Boundary-Layer Meteorology 131, 19-34.
CODASC, 2008. Concentration Data of Street Canyon, internet database, http://www.codasc.de. Institute for Hydromechanics - University of Karlsruhe (GERMANY)
Flow and concentration fields in urban street canyons of different aspect ratios with various avenue-like tree planting configurations
Tree planting characteristics: influence of crown shape, diameter, height, porosity and planting density
FLOW: air exchange and entrainment conditions considerably modified, resulting in lower flow velocities and in overall larger pollutant charges inside the canyon.
DISPERSION: increases in pollutant concentrations at the leeward and decreases at the windward
street canyon with miscellaneous tree arrangements
Model validation – but not only!
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Example of a typical CFD simulation setup
• commercial CFD-Code• RANS-Equations• turbulence closure schemes
- RSM at least!• second order discretization schemes• grid: hexahedral elements
- ~ 400,000- δx=0.05H, δy=0.25H, δz=0.05H
- expansion rate <1.3 • turbulent Schmidt number Sct = 0.7
ν=ydiffusivitturbulent
itycosvisturbulentD
Sct
tt
uH=4.7 m/s: undisturbed wind speed at the building height H
α=0.30: power law exponent
=0.52 m/s: friction velocity
κ=0.40: von Kàrmàn constant
Cμ = 0.09
α
=
Hz
uzuH
)()
δz(
Cu
kμ
−= ∗ 12
)δz(
κzuε −= ∗ 1
3
INLET
30H8H
8H
INFLOW
OU
TFLOW
SYMMETRY
WIND
lQHucc
T
refm=+
cm measured concentration
uref reference velocity
H building height
QT/l strength of line source
Dimensionless concentrations c+
CFD modelling CFD modelling Objectives: Validation studies / speculative approach
*u
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CFD modelling of porous tree crowns
A cell zone is defined in which the porous media model is applied and the pressure loss in the flow is determined
The porous media model adds a momentum sink in the governing momentum equations:
This momentum sink contributes to the pressure gradient in the porous cell, creating a pressure drop that is proportional to the fluid velocity (or velocity squared) in the cell.
The standard conservation equations for turbulence quantities is solved in the porous medium. Turbulence in the medium is treated as though the solid medium has no effect on the turbulence generation or dissipation rates.
viscous loss term + inertial loss term
Si: source term for the i-th (x, y, or z) momentum equation : magnitude of the velocity D and C: prescribed matricesv
permeable zone with the same loss coefficient λ as in wind tunnel experiments
LOOSELY FILLED: λ = 80 m-1
DENSELY FILLED: λ = 200 m-1
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single block: impermeable
single block: permeable (λ=250m-1)
Empty street canyon
Street canyon with tree planting along the center axis
Gromke, C., Buccolieri, R., Di Sabatino, S. and Ruck, B., 2008. Dispersion study in a street canyon with tree planting by means of wind tunnel and numerical investigations - Evaluation of CFD data with experimental data. Atmospheric Environment 42, 8640-8650.
VALIDATION STUDIES (W/H=1)
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-0.4 -0.2 0 0.2 0.4x/H
LDV Measurement
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k-epsilon TM
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H
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RSM TM
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w velocities – middle of the canyon
-0.4 -0.2 0 0.2 0.4x/H
k-epsilon TM
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empty street canyon permeable crown
•slightly smaller flow velocities in the upward •significantly lower velocities in the downward moving part•volume flow crossing the horizontal plane at z/H = 0.7 is reduced (-36 %)
canyon vortex
Air volume rotating in canyon vortex is reduced in the presence of tree plantings
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• Is wind direction important? Competition with aspect ratio…
• Approaching flow perpendicular and inclined by 45° to street axis
Empty street canyon - W/H=2
Street canyon with tree planting
CFD modellingCFD modelling
Buccolieri, R., Gromke, C., Di Sabatino, S. and Ruck, B., 2009. Aerodynamic effects of trees on pollutant concentration in street canyons. Science of the Total Environment 407, 5247-5256.
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WIND
Wall A shows larger concentrations than windward wall B: dominating vortex-like structure around the street canyon centre
Decreasing concentrations towards the street ends: enhanced natural ventilation at the street canyon ends, where air exchange is not only provided by vertical exchange with the above roof flow but also with entering flow laterally
x/H
z/H
-1 -0.6 -0.2 0.2 0.6 10
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EMPTY STREET CANYON
W/H=2, wind direction: perpendicular
CFD FLOW INSPECTIONCFD FLOW INSPECTION
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Wall A Wall B
CFD concentration pattern qualitatively similar to that obtained in the wind tunnel
Slight underestimation of the measured concentrations in proximity of wall A
calculated concentrations relative deviations [%] in respect of measurements
street canyon model – wind tunnel
street canyon model – CFD
VALIDATIONVALIDATIONEMPTY STREET CANYON
W/H=2, wind direction: perpendicular
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Wall A Wall B
relative deviations [%] in respect of tree-less street canyon
Increases in concentrations in proximity of wall A and decreases near wall B
Maximum concentrations at pedestrian level in proximity of wall A
Differently to the tree-free street canyon case, less direct transport of pollutants from wall A to wall B occurs
WT CONCENTRATIONSWT CONCENTRATIONS
Loosely filled crown Loosely filled crown ((λ = 80 m-1 , PVol = 97.5 %)
W/H=2, wind direction: perpendicular
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Increases in concentrations in proximity of wall A and decreases near wall B
The pollutants are advected towards the leeward wall A, but, since the circulating fluid mass is reduced in the presence of tree planting, the concentration in the uprising part of the canyon vortex in front of wall A is larger
-1 -0.6 -0.2 0.2 0.6 10
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1
1.2
x/H
z/H
0.1
0.2
0.3
0.4
-1 -0.5 0 0.5 1-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
y/H
x/H
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
x/H
z/H
-1 -0.6 -0.2 0.2 0.6 10
0.2
0.4
0.6
0.8
1
1.2
0.1
0.2
0.3
0.4
-1 -0.5 0 0.5 1-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1y/H
x/H
Differently to the tree-free street canyon case, less direct transport of pollutants from wall A to wall B occurs
Most of the uprising canyon vortex is intruded into the flow above the roof level. Here, it is diluted before partially re-entrained into the canyon. As a consequence, lower traffic exhaust concentrations are present in proximity of wall B
WIND
WIND z=0.5Hy=1.25H
WITH TREES
W/H=2, wind direction: perpendicular
CFD FLOW INSPECTIONCFD FLOW INSPECTION
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calculated concentrations relative deviations [%] in respect of measurements
CFD simulations were successful in predicting an increase in concentrations in proximity of wall A and a decrease near wall B and the relative deviations in respect of tree-less street canyon
As in the tree-free case, it slightly underestimated experimental data
Wall A Wall B
street canyon model – wind tunnel
street canyon model – CFD
Loosely filled crown Loosely filled crown ((λ = 80 m-1 , PVol = 97.5 %)
W/H=2, wind direction: perpendicular
VALIDATIONVALIDATION
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In comparison to the street canyon with the tree planting of loosely filled crown, no essentialchanges are found both in wind tunnel experiments and CFD simulations
The degree of crown porosity is of minor relevance for flow and dispersion processes inside the street canyon as the tree planting is arranged in a sheltered position with wind speeds being very small.
WT CONCENTRATIONSWT CONCENTRATIONS
relative deviations [%] in respect of tree-less street canyon
CFD - WT CONCENTRATIONSCFD - WT CONCENTRATIONS
calculated concentrations relative deviations [%] in respect of measurements
Densely filled crown Densely filled crown ((λ = 200 m-1 , PVol = 96 %)
W/H=2, wind direction: perpendicularVALIDATIONVALIDATION
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NMSE R FAC2 FB
tree-less street canyon 0.06 0.96 0.97 0.15
loosely filled crown (PVol = 97.5 %) 0.13 0.98 1.00 0.21
densely filled crown (PVol = 96 %) 0.09 0.99 1.00 0.14
Statistical analysis (Chang, C. and S. Hanna, 2004):
•normalized mean square error (NMSE ≤ 4)•correlation coefficient (R)•fraction of predictions within a factor of two of observations (FAC2 ≥ 0.5)•fractional bias (−0.3 ≤ FB ≤ 0.3)
Comparison Wind Tunnel Measurements - Numerical Computations CFD simulations are in general good agreement with wind tunnel experiments
Pollutant concentrations in proximity of the leeward wall are slightly underestimated in the numerical
simulations, while near the windward wall both slightly over- and underestimations are present
W/H=2, wind direction: perpendicularVALIDATIONVALIDATION
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Relative deviation in wind tunnel
concentration
H/W=1 –single tree row vs empty
H/W=0.5 –two tree rows vs empty
leeward +71% +42%windward -35% -32%
Concentration fields within street canyon depend on both street canyon
aspect ratio and tree planting configuration
Double tree rows is preferable to one row in the middle of the canyon
Some observationsSome observationsWind direction: perpendicular
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W/H=2, wind direction: 45°
Pollutant concentrations are larger than at wall B. Concentration increases from the centre to the street ends at both walls are found.
In the wind tunnel experiments, at the beginning of wall A large concentrations are found. This phenomenon is y only partially reproduced in the CFD simulations.
Overall CFD concentrations are similar to those obtained in the wind tunnel, even if there is some underestimation of the measured concentrations at wall A.
CFD - WT CONCENTRATIONSCFD - WT CONCENTRATIONS
Wall A Wall B
street canyon model – wind tunnel
Local Air Quality and its Interactions with Vegetation, Antwerp, Belgium, January 21-22, 2010 C
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Wall A Wall B
street canyon model – wind tunnel
CFD FLOWCFD FLOW
W/H=2, wind direction: 45°
Lower concentrations at both walls at the upstream entry are due to enhanced ventilation caused by the superposition of the canyon vortex and the corner eddy.
The increasing pollutant concentrations towards the downstream end of the street clearly indicate that the flow along the street axis becomes a dominant pollutant transport mechanism.
This tendency is due to the helical flow characteristic of the canyon vortex. Moreover, the clockwise rotating helical motion determine the vertical concentration distributions on both walls.
Local Air Quality and its Interactions with Vegetation, Antwerp, Belgium, January 21-22, 2010 C
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Increases in concentrations at both wall.
Overall CFD concentrations are similar to those obtained in the wind tunnel, even if there is an underestimation of the measured concentrations at wall A, especially close to the upstream entry.
CFD - WT CONCENTRATIONSCFD - WT CONCENTRATIONS
Wall A Wall B
street canyon model – wind tunnel
W/H=2, wind direction: 45°
Densely filled crown Densely filled crown ((λ = 200 m-1 , PVol = 96 %)
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Concentration patterns are due to the predominant parallel flow component.
In particular, at the upstream entry of wall A the corner eddy found in the tree-free case does not occur anymore, due to the presence of trees which behave as obstacles
The helical flow vortex is also broken and, as a consequence, a wind flowing parallel to the walls is evident. However, from the figure it can be noted that wind velocities are slower than those found in the previous case. As the result of this, the pollutants released from the traffic are larger.
CFD FLOWCFD FLOW
Wall A Wall B
street canyon model – wind tunnel
W/H=2, wind direction: 45°
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For the 45° inclined case there is an increase in concentrations both at leeward
and at the windward!
Concentration fields within street canyons depend on approaching wind direction
rather than on tree planting arrangement
Wind tunnel concentrations
Perpendicular 45° inclinedleeward windward leeward windward
Tree-free(CFD results)
14.8(12.1)
5.2(5.4)
9.8(7.4)
0.9(0.9)
Tree vs tree-free(CFD results)
~ +42%(~ +40%)
~ -32%(~ -24%)
~ +89% (~ +72%)
~ +211% (~ +344%)
Increase Increase IncreaseDecrease
W/H=2, Effect of wind direction
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For the perpendicular approaching flow the increase in concentration due to tree planting is larger for W/H = 1 case
For the 45° inclined flow the increase due to tree planting is larger for W/H = 2 case.
Wind tunnel concentrations
Perpendicular 45° inclinedW/H = 1 W/H = 2 W/H = 1 W/H = 2
Tree vs tree-free
(CFD results)
Larger ~ +48%
Smaller ~ +23%
(~ +24%)
Smaller ~ +65%
Larger ~ +99%
(~ +101%)
Effect of aspect ratio vs. wind direction
Comparison of overall (at both walls) concentration increase due to tree planting
Volume occupied by tree crowns
W/H=1: ~33%
W/H=2: ~ 28%
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REAL SCENARIOSREAL SCENARIOSAerodynamic effects of trees in Bari (Italy)
1
2
3
4
4 street canyons and 1 junction
Hmax~46m, Hmean~24m
Four tree rows Avenue-like tree planting of high stand densities, i.e. with interfering neighbouring tree crowns.
Bari (ITALY)
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The variability of the wind speed, the presence of background and other variables not controlled in the field experiments limit the comparison between measured and simulated data to qualitative analysis of the concentrations. CFD simulations aim at providing an example of how numerical tools can support city planning requirements Computational cells: three millions and a half (cell dimensions δxmin = δymin = 1m, δzmin = 0.3m until the height of 4m). 4 days simulation time with 2 processors
- street canyon 1-2: W/H ~ 0.5- street canyon 1-3: W/H ~ 1.8- street canyon 2-4: W/H ~ 1.8- street canyon 3-4: W/H ~ 0.6
Wind dir.: 5°
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•15 December 2005
•Wind dir.: West
•Larger conc.: 33μg/m3
•26 December 2005
•Wind dir.: South
•Smaller conc. 18μg/m3
Measurements at monitoring station (~3m)
c+ ~ 20
c+ ~ 16
CFD simulations
lQHucc
T
refm=+cm modeled concentration
uref reference velocity
H tallest building height
QT/l strength of line source
33/18 ~ 1.8 (MEAS.)
20/16 ~ 1.3 (SIM.)
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Flow pattern within the canyon can be thought as an interaction of several approaching winds leading to an overall increase of concentration at both sides of the canyon with trees as found for the 45° inclined case for isolated canyons.
•Larger velocities
•3 times smaller concentrations at monitoring position without trees
Wind dir.:5°
Real case (with trees)
Case without trees
c+ c+
U (m/s)c+
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Also in this case, flow pattern can be thought as an interaction of several approaching winds leading to an overall increase of concentration at both sides of the canyon with trees as found for the 45° inclined case for isolated canyons.
•Slightly larger velocities (channelling along tree spaces transports more pollutant away from monitoring position)
•1.3 times larger concentrations at monitoring position without trees
Real case (with trees)
Case without trees
c+ c+
U (m/s)c+
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Practical relevance of results Practical relevance of results
Concentrations MEASUREMENTS SIMULATIONS
West South West/South West South West/South
Tree 33μg/m3 18μg/m3 ~1.8 20 16 ~1.3Tree-free N/A N/A N/A 6 21 ~0.3
Simulations show that it has been crucial to consider the effect of trees on pollutant dispersion to explain qualitative difference between monitoring stations
Without trees the situation is reversed!
Local Air Quality and its Interactions with Vegetation, Antwerp, Belgium, January 21-22, 2010 C
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Work in ProgressWork in ProgressLarge Eddy Simulation – Transient Solution
Simulations were performed by Salim Mohamed Salim, Division of Environment, Faculty of Engineering, University of Nottingham (Malaysia Campus), Semenyih, 43500, Selangor Darul Ehsan, Malaysia
Preliminary LES work
• Started with RANS mean flow steady solution-Standard k-ε
• Imposed synthetic turbulence & continued with Large Eddy Simulation
- Transient solution• subgrid-scale model
- Dynamic Smagorinsky-Lilly• bounded central differencing for momentum, second
order for species & energy.• grid: hexahedral elements
- ~ 550,000- δx=0.1H, δy=0.1H, δz=0.1H
• Flow-through-time (residence time),- Tf = L/U = 41 X 0.12 m / 6.2ms-1 = 0.8s
- L: length of domain in x-direction- U: undisturbed velocity
• timestep size , Δt = 0.005• initial number of timesteps:4000 (= 20sec= 25Tf )
- statistically steady state achieved• additional 4000 timesteps, to average the instantaneous velocity
(bringing total to 40sec)• Computational cost:
- Intel® Xeon® Processor W3520 (8M Cache, 2.66 GHz, 4.80 GT/s Intel® QPI)
- Parallel Processing on 4 Cores.- 18 iterations per time-step for convergence at 2.5 sec/iteration
45sec/timestep 100hrs of computation.
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Work in ProgressWork in ProgressLarge Eddy Simulation – Transient Solution
t = 20s
t = 35s
t = 30s
t = 25s
t = 40s
Time-averaged at 40s
Wall A Wall B
t = 20s t = 30s Time-averaged at 40s
• Concentration levels on the windward (Wall B) and leeward (Wall A) walls.
• Velocity contours showing instantaneous (t=20s and 30s) and mean values.
Local Air Quality and its Interactions with Vegetation, Antwerp, Belgium, January 21-22, 2010 C
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ConclusionsConclusions
Trees in urban street canyons have important aerodynamics effects(aspect ratios and wind direction are among the most important ones!) They have somehow been quantified using wind tunnel controlled experiments. Real conditions may be different. BULK effects are probably understood individually but not in combination (especially in real scenarios)… multiple canyons, neighbourhood scale
RANS CFD simulations/analyses for concentration predictions in street canyons are currently feasible with a proper turbulence closure but most probably LES is more adequate to take into account non-stationary processes
We still need to account for the effect of buoyancy (Radiation Sheltering effect but buildings release heat in. Trapping effect. Warm air in the bottom part of the canyon
Local Air Quality and its Interactions with Vegetation, Antwerp, Belgium, January 21-22, 2010 C
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Future PerspectiveFuture Perspective
More good experiments are needed to further investigate the complex atmosphere-tree interaction in urban areas of both fundamental and applied nature are necessary (velocity and turbulence time scales, momentum and scalars transfer processes …). Integrated (perhaps holistic approach) to understand/predict the urban environment. Trees and vegetation is part of the system
Only by a synergic effort between methodologies and scientific expertise will be possible to tackle the new challenges associated with the emerging properties/difficulties/prediction of the urban environment in a changing climate!
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