Flow and Pollutant Dispersion in Street Canyons using FLUENT and ADMS-Urban

14 Pages·2008·0.86 MB·English

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EnvironModelAssess(2008)13:369–381
DOI10.1007/s10666-007-9106-6
Flow and Pollutant Dispersion in Street Canyons
using FLUENT and ADMS-Urban
S.DiSabatino·R.Buccolieri·
B.Pulvirenti·R.E.Britter
Received:7January2006/Accepted:5May2007/Publishedonline:7July2007
©SpringerScience+BusinessMediaB.V.2007
Abstract This paper is devoted to the study of flow to 0.04 gives the best agreement with ADMS-Urban.
withinasmallbuildingarrangementandpollutantdis- Overall the modified k−(cid:2) turbulence model may be
persion in street canyons starting from the simplest accurate for the simulation of pollutant dispersion in
case of dispersion from a simple traffic source. Flow streetcanyonsprovidedthatanappropriatechoicefor
results from the commercial computational fluid dy- coefficients in the turbulence model and the Schmidt
namics (CFD) code FLUENT are validated against numberinthediffusionmodelaremade.
windtunneldata(CEDVAL).Dispersionresultsfrom
FLUENTareanalysedusingthewell-validatedatmos- Keywords Streetcanyons·Dispersion·Modelling·
pheric dispersion model ADMS-Urban. The k−(cid:2) FLUENT·ADMS-Urban
turbulence model and the advection-diffusion (AD)
method are used for the CFD simulations. Sensitivity
of dispersion results to wind direction within street 1Introduction
canyons of aspect ratio equal to 1 is investigated. The
analysis shows that the CFD model well reproduces Airqualityinurbanareasisofgreatimportancegiven
the wind tunnel flow measurements and compares ad- itsdirectimplicationsforthehealthofpeoplelivingin
equatelywithADMS-Urbandispersionpredictionsfor thoseareas.Urbanbuildingarrangements,inparticular
asimpletrafficsourcebyusingaslightlymodifiedk−(cid:2) the width of streets, their orientation, spacing and the
model. It is found that a Schmidt number of 0.4 is the presenceofintersectionsaremajorfactorsinthedeter-
mostappropriatenumberforthesimulationofasimple mination of pollution dispersion at street level. Irreg-
trafficsource andinstreetcanyonsexceptforthecase ular shape buildings contribute to enhance turbulence
when the wind direction is perpendicular to the street and vertical mixing in the atmosphere, while W/H
canyonaxis.ForthislastcaseaSchmidtnumberequal ratios (with W the width and H the height) of urban
canyonsaffectstreetventilation.Moregenerally,build-
ings modify the flow field, influencing air exchanges
andthedispersionofpollutants.Inurbanareas,inpar-
S.DiSabatino(B)·R.Buccolieri
ticular, pollution may be the result of emissions from
DipartimentodiScienzadeiMateriali,
UniversityofLecce,Lecce,Italy traffic, domestic heating and cooling systems, industry
e-mail:[email protected] ortoxicagentsaccidentallyand/ordeliberatelyreleased
intotheatmosphere.
B.Pulvirenti
Traditionally, information about concentrations is
DipartimentodiIngegneriaEnergetica,
NucleareedelControlloAmbientale, obtainedusingwind-tunnelexperiments,whichprovide
UniversityofBologna,Bologna,Italy an opportunity to examine the effects of various para-
metersindividuallyorinacontrolledcombination.For
R.E.Britter
example,Parketal.[18]characterizedthedispersionof
DepartmentofEngineering,UniversityofCambridge,
Cambridge,UK vehicle emissions by conducting wind tunnel tests and
370 S.DiSabatinoetal.
applying tracer gas techniques. They concluded that dispersion into the atmosphere over scales of up to
the dispersion of vehicle emission in street canyons is about 50 km from releases from various sources. The
primarily affected by microscale climatic factors such modelisabletoaccountforalargenumberandtypeof
astheW/Hratio. emissionsourcestypicallyfoundinurbanareas.Several
Recently, computational fluid dynamics (CFD) has validation studies (see for instance [12] and [3]) have
become an attractive tool to predict concentration shownthat,especiallyoverflatterrain,thepredictions
fields near buildings. Many works can be found in the are consistent with experimental data. The study pro-
literature reporting on the use of computational fluid posedherebuildsonandextendspreviousworksbased
dynamics (CFD) techniques to model flow and pol- onFLUENTandADMS-Urbanmodelverificationand
lutant dispersion around isolated buildings or groups analysis.Inparticular,acomparisonbetweenFLUENT
of buildings [7]. However, their use to calculate gas and ADMS3 (the industrial version of ADMS-Urban)
dispersion in urban areas is still limited to isolated for atmospheric dispersion modelling from a single
casesandtoalimitednumberofsources.TheReynolds point source was analysed by Riddle et al. [21], who
averaged Navier–Stokes equation (RANS) methods foundagoodagreementusingtheturbulenceReynolds
are amongst the most preferable procedures used to stress model (RSM) [14] and the Lagrangian particle
model urban dispersion problems, mainly due to their (LP) method. Their study remarks that CFD simula-
relatively inexpensive computational costs. Compar- tionsarenotanappropriatealternativetoamodelsuch
isonsoftheRANSresultswithwindtunneldatashow as ADMS for routine atmospheric dispersion studies
that significant errors could occur in the prediction because of the large run times and the complexity of
of concentrations. These errors could come from any the setup. More recently, Di Sabatino et al. [8] ex-
inappropriate choice of the turbulence model, numer- tended the study to the comparison between ADMS-
ical schemes, grid resolution and so on [24]. Recently, UrbanandFLUENTinanisolatedstreetcanyon.They
Xie et al. [25] investigated the influence of building obtained similar results using a slightly modified k−(cid:2)
geometry on pollutant dispersion comparing different turbulence model and the advection–diffusion (AD)
k−(cid:2) models with wind tunnel measured data for the method which, together, are computationally less ex-
optimization of turbulence models. Their comparison pensivethanotheravailablemodels.
showedthatthestandardk−(cid:2)model[15]wasthemost In this paper we use the three dimensional com-
optimum choice. On the other hand, integral flow and putational fluid dynamics model FLUENT with both
dispersion models are still the most used tools for the the standard and a modified k−(cid:2) turbulence scheme
studyofpollutantdispersionastheyareabletoaccount to examine if the use of a general purpose CFD code
foralargenumberofemissionsourcesatthesametime; canbeapracticaltoolforstudyingairqualityinurban
aresultparticularlyusefultoassessairqualityinurban areas.
areas.
The objective of this study is to compare CFD
numericalsimulationsofflowandpollutionconcentra- 2ModelAvailabilityandGeneralDescription
tion fields with predictions from an integral Gaussian-
type dispersion model. This work is also an attempt FLUENT is a state-of-the-art computer program for
to highlight advantages and disadvantages of two dif- modelling fluid flow and heat transfer in complex
ferent types of modelling for pollutant concentration geometries. The code is available from national fluent
predictionsinarealurbanenvironment.Wechosetwo vendors for both academic and public institutions by
commercial codes the CFD code, FLUENT [9] and acquiring an annual renewable licence. It solves the
the quasi-Gaussian atmospheric dispersion modelling governing conservation equations of fluid dynamics
system (ADMS-Urban) [5]. This choice is justified by by a finite-volume formulation on a structured, non-
their extensive use in Europe and in the world. In orthogonal, curvilinear coordinate grid system using a
particular, FLUENT is the world’s most widely used collocated variable arrangement. Three different spa-
commercial CFD code for a wide range of industrial tialdiscretizationschemesmaybeused,thatispower-
flow applications. The number of industries that have law, second-order upwind, and QUICK, a bounded
benefitedfromusingitcontinuestoexpand.FLUENT third-order accurate method. Temporal discretization
hasbeenusedtosuccessfullysimulatetheatmospheric is achieved by a second-order, implicit Euler scheme.
boundary layer [21] but, at present there are not Pressure/Velocity coupling is achieved by the SIM-
sufficient validation studies concerning its use for PLEalgorithmresultinginasetofalgebraicequations
the predictions of pollutants in urban areas [11]. whicharesolvedusingaline-by-linetridiagonalmatrix
ADMS-Urban is being widely used for calculating gas algorithm, accelerated by an additive-correction type
Flowandpollutantdispersioninstreetcanyons 371
of multigrid method and block-correction. Additional At first we simulate the simplest atmospheric neutral
equation solvers are also available to the user. boundary layer flow over a surface with a specified
FLUENT models turbulent flows with the standard surface roughness length. After, we investigate the
k−(cid:2) model, an RNG model, and a second-moment best model setup for the simulation of small building
closureorReynolds-stressmodel(RSM)[9]. arrangements and compare flow results with available
ADMS-Urban is a PC based air quality manage- wind tunnel data (CEDVAL) [6] to obtain confidence
mentsystemofdispersionintheatmosphereofpassive, in the CFD simulations. Finally, we study dispersion
buoyantorslightlydense,continuousorfinitedurations by modelling a finite traffic source in the atmospheric
releases from single or multiple sources. The model neutral boundary layer without buildings and after a
is available on request directly from the main devel- finite traffic source in a single street canyon for vari-
operCambridgeEnvironmentalResearchConsultants ous wind directions. ADMS-Urban is used to provide
or from national vendors. Both annual and perma- benchmarkdataforthestudyasitisroutinelyvalidated
nent licences are available. The model uses an up-to- against monitoring data (see for instance [4]) and has
date parameterisation of the boundary layer structure undergoneseveralvalidationstudieswithgooddatasets
basedontheMonin–Obukhovlengthandtheboundary (seeforinstance[12]).
layer height. Concentration distributions are Gaussian
in stable and neutral conditions, but the vertical dis- 3.1ADMS-UrbanGeneralFlowandDispersionSetup
tributions is non-Gaussian in convective conditions to
take account of the skewed structure of the vertical Initially,ADMS-Urbanisruntocalculatetheboundary
component of the turbulence. A range of modules layer velocity profiles to use them as the upstream
allow for the effects of plume rise, complex terrain, boundary conditions in FLUENT. The velocity (or
streetcanyons,noisebarriersandbuildings.Thestreet wind) profile in a neutrally stratified atmosphere is
canyon module is based on the largely used OSPM calculatedthroughthelogarithmiclaw:
model [13] which considers a trapezoidal recirculation u∗ z+z
areawhosedimensionsdependuponthestreetcanyon U(z)= ln 0 (1)
κ z
aspect ratio and wind speed above the street canyon 0
top. Therefore the recirculation area is somehow pre- where U(z) is the average wind speed at the height z
scribedinmodelssuchasADMS-Urbanandthisaspect abovetheground,z0 isthesurfaceroughness,u∗ isthe
shouldbekeptinmindwhencomparingresultswitha friction velocity and κ is the von Karman’s constant.
CFD code. The parameters for the wind field and the As in [21] a neutral boundary layer of height 800 m is
Gaussian plume model are calculated by a meteoro- initiallyused,withawindspeedof5ms−1(ataheightof
logical pre-processor. The OSPM model has been ex- 10mabovetheground)andasurfaceroughnesslength
tensivelytestedagainstmeasurementsatseveralstreet of0.1m.
locations. Examples of comparison of model results Thesimulationofgasdispersionfromatrafficsource
withmeasurementsaregivenin[2]and[13]. is done using a line source which is 100 m long and
1 m wide. As an example, a release of CO is chosen
withanemissionrateof10g/s.Asimilaremissionrate
3Methodology is also used for the simulation of a finite traffic source
in a street canyon with aspect ratio (W/H) equal to 1,
In this work concentration predictions from a traffic with W = H =20m.Inthiscasethetrafficsourcehas
source (modelled as a line source with cross-wind di- dimensions of 100×20 m. Street canyon aspect ratios
mension) placed within a regular urban street canyon from1to0.5correspondtothoseforwhichaskimming
are investigated. It is recognised that the modelling of flow regime [16] develops. This is the most common
atrafficsourceisstraightforwardinoperationalmodels flow regime found in most European city centres and
of the type of ADMS-Urban but it is not with general Americancities[19].
purpose engineering-type CFD models. In this study
wedocumenteachstepundertakentoachievethefinal 3.2FLUENTGeneralFlowSetup
goalinFLUENTwiththeaimofassessingthevalidity
of results and giving recommendation for the use of Thecomputationaldomainusedtosimulatetheneutral
commercial generic CFD codes for the prediction of atmosphericboundarylayerisbuiltusingbothirregular
inert pollutant concentrations in street canyons. Sepa- tetrahedralandhexahedralgridswithfinerresolutions
ratesimulationsareperformedtostudytheflowbefore close to the ground. The overall number of computa-
proceeding with the modelling of pollutant dispersion. tionalcellsusedisoftheorderofonemillionformost
372 S.DiSabatinoetal.
cases. The bottom surface (i.e. ground) is specified as Beforeproceedingwithfullthree-dimensionalsimu-
a rigid plane with a specified surface roughness. All lationsaswillberequiredwhenconsideringaportionof
FLUENTsimulationsarecarriedoutbyusingasimple anurbanareaorstreetcanyons,varioussimulationsare
velocity inlet condition (specifying velocity, turbulent performedusingathree-dimensional(3D)flowdomain
kinetic energy k (TKE) and turbulent dissipation rate to simulate the simplest atmospheric boundary layer
(cid:2) profiles), by specifying an operating pressure at a flow over a surface with a specified surface roughness
point in the middle of the flow domain and by using length.AvalueofCμequalto0.013isusedassuggested
outflowconditionsattheoutleti.e.themassflowrateis byRichardsandHoxey[20]toavoidhighnear-ground
the same as the inlet. All simulations are carried out turbulencelevelsforflowoverflatroughsurfaceswhich
as steady state solutions of the Navier–Stokes equa- aretypicallyoverestimatedinCFDcodes.Alsothisdif-
tionsandfortheconservationofmassspecies.Second ferentCμ valueovercomethegeneraldifficultydueto
order discretisation schemes are used to increase the thedecayofturbulencekineticenergywiththedistance
accuracy and reduce numerical diffusion. The specific downstream often encountered in CFD atmospheric
methods are second order upwinding [1] for pressure, neutralboundarylayerwiththestandardk−(cid:2) model.
momentum, k and (cid:2), the SIMPLE scheme is used for AsaconsequenceofthealterationoftheCμvalue,also
thepressure-velocitycoupling. σ(cid:2)(theturbulentdissipationratePrandtlnumber)isad-
FLUENTusesaniterativemethodtosolvethealge- justedto3.22,inordertosatisfythetransportequation
braicsystemofequations.Startingfromaninitialguess for turbulent kinetic energy and turbulent dissipation
the flow variables are recalculated in every iteration rate in the k−(cid:2) model. There are some uncertainties
until each equation is solved up to an user specified regarding the exact values of the simulated surface
error. The termination criterion is usually based on roughness due to FLUENT’s formulation for surface
theresidualsofthecorrespondingequations.Scalingof roughness.Thisreliesontheuseofanequivalentsand
theresidualsisusuallydonewiththeresidualsafterthe grain roughness, and a somewhat arbitrary roughness
first iteration. A termination criterion of 10−5 is used. constant C between 0 and 1. Some tests are also per-
s
Overall, a simulation took about 8 hours on double formed with different grid sizes to find the optimum
processors of an OPTERON machine. To get steady value for K which is taken to be equal to 20, a value
s
state solutions for each case considered in this paper, which is somewhere in the middle between the value
residuals reached the chosen level and were stopped of 10 and 32.6 found in literature ([23]). The size of
afterabout100iterations.Ascertainquantitiesreached the computational domain is 5,000 by 5,000 m in the
convergence at a different rate than other quantities, horizontaland800minthevertical.Figure1showsthe
wecheckedthatflowvaluesremainedunchangedwith velocity profiles obtained at different positions down-
respect to the number of iterations. To quantify the wind of the inlet. From the figure it can be seen that
influence of the grid resolution on the solution a grid thelogarithmicvelocityprofileismaintainedverywell
convergence study is made. For this, different system-
atically and substantially refined grids are used. The
grid refinement ratio is a minimum of 1.1 to allow
50
thediscretizationerrortobedifferentiatedfromother
error sources (iterative convergence errors, computer 45 Inlet velocity
round-off etc.)[22]. Velocity at 2000 m
40
Velocity at 5000 m
At the inlet, we use a velocity profile equal to the
35
windspeedprofileusedinADMS-Urban(Eq.1)while
turbulent kinetic energy and dissipation rate profiles 30
arespecifi(cid:3)edasfo(cid:4)llows: z [m]25
u∗2 z
k= (cid:2) 1− (2) 20
δ
Cμ
15
and
(cid:3) (cid:4) 10
u∗3 z
(cid:2) = 1− (3) 5
κz δ
0
where δ is the atmospheric boundary layer depth and 0 1 2 3 4 5 6 7 8
u [m s−1]
Cμ is a coefficient used to define the eddy viscosity in Fig. 1 Velocity profiles obtained with FLUENT at different
k−(cid:2) models[15]. positionsdownwindoftheinlet
Flowandpollutantdispersioninstreetcanyons 373
800
tendtobecomesmalleralongthedomainnearground
Inlet k
700 k at 2000 m but they tend to increase above a height of 500 m. In
k at 5000 m
600 the region near the ground (up to 100 m), the average
500 TKEvaluesreducetoapproximately75%,whileatthe
z [m]400 ground they reduce to approximately 85% of the inlet
300 values at distance of 5,000 m. This reduction over this
200 large distance is much smaller than that found with
previous CFD calculations using the standard k−(cid:2)
100
model as reported in [21]. Also this reduction in TKE
0
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 values can be considered acceptable in the context of
k [m2 s–2]
the modelling we are doing. As before, a check on
the performance of the TKE along the entire domain
103
should be done before proceeding with further calcu-
Inlet ε
ε at 2000 m lations. The turbulent dissipation rate is maintained
ε at 5000 m
very well throughout the length of the computational
102 domain. Based on those results the k−(cid:2) model with
m] the modifications already mentioned is adopted as the
z [
mainturbulentmodel.
101
3.3FLUENTSmallBuildingArrangementFlowSetup
100
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
ε [m2 s–33] Several grids are tested for the different simulations
Fig.2 k(Top)and(cid:2) (bottom)profilesobtainedwithFLUENT
performed in this study. For the comparison of FLU-
atdifferentpositionsdownwindoftheinlet
ENTresultswithCEDVAL,ageometryoffoursquare
shapedringsofmodelbuildingsforminganintersection
throughout the length of the computational domain. withanoffsetinoneofthetwolanes(twobuildingsare
Thischeckshouldbedonebeforedoinganydispersion equipped with a slanted roof (45o roof angle) is used.
calculations from a single point or line source in the ThegeometrystudiedisshowninFig.3,whileapartof
neutral atmospheric boundary as it likely affects the thedomainandthegridusedforFLUENTsimulations
finalconcentrationattheground. areshowninFig.4.
Figure2showsthepredictedk(top)and(cid:2) (bottom) Afterperformingatesttoverifythatthesolutionwas
profiles generated by the k−(cid:2) model at various posi- domain independent and grid shape and size indepen-
tionsdownwindoftheinlet.ThepredictedTKElevels dent, a structured grid with refined elements near the
Fig.3 Sketchofthe
geometryoftheCEDVAL
experiment
374 S.DiSabatinoetal.
where D is the diffusion coefficient for CO in the
CO
mixture, μt =ρCμk(cid:2)2 is the turbulent viscosity, YCO is
the mass fraction of CO, ρ is the mixture density. In
Eq.4,Sc =μ/(ρD)istheturbulentSchmidtnumber,
t t t
where D istheturbulentdiffusivity.
t
3.5FLUENTSimpleTrafficSourceDispersionSetup
At first we study the case of CO dispersion from a
simple traffic source i.e. a traffic source placed in the
neutral atmospheric boundary layer without buildings
in order to assess the validity of dispersion results.
Again as in [21] a reduced computational domain size
of 1,000 by 500 m in the horizontal and 150 m in the
vertical is used for the gas dispersion simulations. The
same inlet CO mass flow rate of 10 g/s set in ADMS-
UrbanmodelisusedinFLUENT.Thereduceddomain
sizeallowedustofurtherrefinethegridneartherelease
anddownstreamofitespeciallyinthoseregionswhere
the plume is evolving. The grid elements are about
0.25 m in size near the traffic source, and grow with a
ratioof1.2.Thetrafficsourceispositionedperpendic-
ular to the wind direction at 100 m downwind of the
inletsection.Theoverallnumberofcomputationalcells
used is of the order of one million. The traffic source
Fig.4 DomainandgridusedinFLUENTtosimulatetheCED- is simulated by separating a volume in the geometry
VALexperiment attherequireddischargepositionandbysettingaCO
sourceterm(g/m3-s)forthisvolume.Theareaforming
thebaseofthisvolumehasthesamedimensionsofthe
traffic source set in ADMS-Urban, while the height of
ground, inside the intersection, is chosen. The refine- thevolumeissetto0.5m.Severaltestswereperformed
mentisshowninFig.4.Thesmallestdimensionsofthe
before choosing this value by verifying the indepen-
elements near the ground and inside the intersection
dency of FLUENT results from the specific choice of
are equal to 0.5 m while they are about 2 m outside
theheightofthevolumesource.Itwasfoundthatany
theintersection.Theoverallnumberofcomputational height between 0.5 and 2 m would not influence the
cellsusedisoftheorderof1.5·106.Thebottomsurface
finalconcentrationresults.
(i.e.ground)isspecifiedasarigidplanewithaspecified
surfaceroughness,asforthesimulationscarriedoutin
theprevioussection.Alsothevelocityinletprofileand
3.6FLUENTStreetCanyonDispersionSetup
turbulent kinetic energy and dissipation rate profiles
arespecifiedasintheprevioussection.
We consider the case of CO dispersion from a traffic
sourceplacedinastreetcanyonofheight H andwidth
3.4FLUENTGeneralDispersionSetup W. The aspect ratio of the street canyon is kept con-
stant,W/H =1,forallcasesconsideredinthissection.
Various models are available in FLUENT to model The street canyon geometry is built by placing at a
dispersion of airborne material. In this study only the distance of 100 m from the inlet two identical blocks
advectiondiffusion(AD) module is used.In turbulent eachbeing100mlong100mwideand20mhigh.The
flows, FLUENT computes the mass diffusion which same traffic source discussed in the previous section is
satisfiestheconservationofmassasfollows: used here. All FLUENT simulations for this case use
(cid:3) (cid:4) adomainandgridcharacteristicssimilartothoseused
μ
J =− ρD + t ∇Y (4) tosimulatethesimpletrafficsourceandtheCEDVAL
CO CO CO
Sc experiments.
t
Flowandpollutantdispersioninstreetcanyons 375
4ResultsandDiscussion
4.1ComparisonwithCEDVALDataset
Figures 5 and 6 show velocity vectors on two vertical
planesaty/H =−2andy/H =2respectively(referto
Fig. 3). The plane y/H =−2 cuts the first lane before
the intersection. Figure 5 shows that FLUENT results
are in good agreement with CEDVAL measurements.
In particular, we observe the same flow pattern inside
and outside the street canyon. Measurements shows
that a small recirculation region forms just behind the
first slanted roof. This is also predicted by FLUENT.
We also observe that both measurements and numer-
ical simulations suggest that the slanted roof before
the lane deviates airflow and no vortex is observed
within the street canyon. The second plane y/H =2
cuts the second lane after the intersection. In this case
thedownwindroof,tallerthantheupwindbuildingacts
asanobstacletoairflowandthevortexinsidethestreet
canyon is enhanced as shown in Fig. 6. This is also
shownbythenumericalsimulations.
Fig.6 VelocityvectorsfromCEDVALmeasurements(top)and
FLUENTresults(bottom)aty/H=2plane
Figure 7 shows the comparison between FLUENT
and CEDVAL dimensionless velocity profiles versus
dimensionless height z/H. Profiles are obtained along
thesame y/H =−2and y/H =2planesinthemiddle
ofthestreetcanyon.Thisfigureshowsthatinthecase
ofthepresenceofavortex(correspondingtotheplane
y/H =2) there is a very good agreement between
FLUENTresultsandCEDVALmeasurements.Inthe
other case the CFD model slightly underestimates the
velocity within the canyon near the ground. Velocity
underestimationshavebeenalreadyfoundwhenusing
the k−(cid:2) model to simulate flow in presence of build-
ingswithroofs[17].
Howeveritshouldbenotedthatintheframeworkof
this work the most interesting case is when the vortex
forms within the street canyon. This is the case when
thek−(cid:2) modelperformsbest.
4.2SimpleTrafficSource
From[21]itisknownthatFLUENTdispersionspread
Fig.5 VelocityvectorsfromCEDVALmeasurements(top)and
FLUENTresults(bottom)aty/H=−2plane using the algebraic Reynolds stress model (RSM) [10]
376 S.DiSabatinoetal.
y/H=_2 FLUENT CO concentrations both at ground level
7
and at z=10 m tend to the same asymptotic value at
6 CEDVAL large distance from the source. The same behaviour
FLUENT
5 is shown by ADMS-Urban results even if FLUENT
asymptoticvalueishigherthantheADMS-Urbanone.
4
H Figure 9 shows the CO contour plots obtained by
z/
3 FLUENT(left)andADMS-Urban(right)ontwohor-
2 izontal planes, at ground level (a) and at z=10 m
(c), and on a vertical plane parallel to the wind flow
1
direction(b).
0
–0.2 0 0.2 0.4 0.6 0.8 1 1.2 The ADMS-Urban prediction of the vertical and
u/u
ref horizontal spread (Fig. 9) reaches a width of 500 m
y/H=2 at a downwind distance of about 300 m whereas the
7
widthoftheFLUENTpredictedplumeis350matthe
6 CEDVAL sameposition.DespitethediminishedSchmidtnumber
F LUENT
5 the plume spread is still smaller than that predicted
by ADMS-Urban both in the horizontal and in the
4
H vertical. However, the discrepancy between the two
z/
3
models is much smaller than that reported by [21] for
2 which the discrepancy between the models was about
70%. Also it should be pointed out that we obtained
1
those results by using both a k−(cid:2) and AD model
0
–0.4 _0.2 0 0.2 0.4 0.6 0.8 1 which typically run much faster than a combination of
u/u
ref anRSMmodelandaLagrangianparticletracking(LP)
Fig. 7 Velocity profiles from CEDVAL measurements (solid
line) and FLUENT results (cross symbols) at the y/H=−2 modelasusedby[21].
plane(top)andatthey/H=2plane(bottom)
4.3TrafficSourceinaStreetCanyon
for a high level point source is smaller than that pre-
In this section dispersion from a traffic source placed
dictedbyADMS-Urban.Wefoundthatthisisalsothe
within a street canyon is studied for different wind
case for both the point source and the simple traffic
directions.
sourceusingthek−(cid:2) model.Thereforeweperformed
At first we consider the case of wind direction
somesensitivitytestsforthechoiceofthemostsuitable
perpendicular to the orientation of the street canyon.
Schmidt number in order to artificially increase the
This is the case for which a full bi-dimensional flow
plumedispersion.Fromthesensitivitytestthevalueof
0.4 was the most appropriate one. We used this for all
subsequentdispersionsimulationsexceptforthestreet
3000
canyon simulation with the wind perpendicular to it. ADMS_Urban ground level
For this case the best choice for the Schmidt number FLUEN_T ground level
ADMSUrban z=10 m
was0.04aswillbediscussedlater. 2500 FLUENT z=10 m
Figure 8 shows the comparison between FLUENT
andADMS-UrbanCOconcentrationsforthecaseofa 2000
simpletrafficsource. 3m]
The profiles are plotted as a function of x both at ug/ 1500
ground level and at z=10 m. Figure shows that there CO [
is a good agreement between FLUENT and ADMS-
1000
Urban results at ground level for x<300 m, while for
x>300 m FLUENT CO concentrations are about 2
500
timeshigherthanADMS-Urbanones.Asimilarobser-
vation can be made for results at z=10 m. FLUENT
0
maximum concentration value is the same as ADMS- 100 200 300 400 500 600 700 800 900 1000
x [m]
Urbaneventhoughitspositionisabout70mcloserto
Fig. 8 ADMS-Urban and FLUENT CO concentration profiles
thesource. asafunctionofxcoordinate,downwindofthesource
Flowandpollutantdispersioninstreetcanyons 377
Fig.9 COconcentration a
contourplotsfromFLUENT
(left)andADMS-Urban
(right)athorizontalplanesat
groundlevel(a),atz=10m
(c)andonaverticalplane
paralleltothewind
direction(b)
b
c
vortex is expected to form. Figure 10 shows the CO Analysis of flow and concentrations in those positions
contour plot on a vertical plane in the middle of is expected to give information on the main physical
the street canyon, parallel to the wind direction. We mechanismoccurringinastreetcanyon.LookingatFig.
can observe that the vortex occupies most of the 11weobservethatoverallFLUENTCOconcentration
streetcanyon.Figure11showsthecomparisonbetween predictionsarelargerthanthoseobtainedwithADMS-
FLUENT and ADMS-Urban concentration predic- Urban.Inparticular,atz=10mFLUENTpredictions
tions. CO concentrations are plotted as a function of areabout2timeslargerthanADMS-Urbanconcentra-
zalongthethreeverticallinesshowninFig.10,respec- tions. However, FLUENT predictions at the lee side
tively at x=−5, x=0 and x=5 m. These positions at z=10 m are about 44% larger than those at the
arechosenastheyrepresent,forourcase,theleeward windwardsidewhereasADMS-Urbanpredictsconcen-
side, the middle of the canyon and windward side. trationsontheleesideareabout33%largerthanthose
Fig.10 COFLUENT
concentrationcontourplot
withinthestreetcanyon.
Verticallinesindicatethree
positionsattheleeside
(x=−5m),inthemiddleof
thestreetcanyon(x=0m)
andatthewindwardside
(x=5m)