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VADIS: Pollutant dispersion in the atmosphere under variable wind conditions

General information

Model name and version

short nameVADIS
full namePollutant dispersion in the atmosphere under variable wind conditions
revisionSeptember 2006
datev. 2005
last change

Responsible for this information

nameCarlos Borrego
instituteUniversity of Aveiro
addressDept. Environment and Planning, University of Aveiro, 3810-197 Aveiro, PORTUGAL
zip3810-193
cityAveiro
countryPortugal
phone+351 234370200
fax+351 234429290
e-mailborrego(belongs-to)ua.pt

Additional information on the model

Contact person for model code

same as person above
nameAna Margarida Costa
instituteUniversity of Aveiro
divisionsDept. Environment and Planning, University of Aveiro, 3810-197 Aveiro, PORTUGAL
street3810-193 - Aveiro
zip3810-193 Aveiro
cityAveiro
countryPortugal
phone+351234370200
emailanamarg@dao.ua.pt
fax+351234429290

Model developer and model user

developer and user

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarks

Model use at your institution

operational
for research
other use

Model code available?

is available?no
more detailsVADIS model interface for a friendly user access is available only for research activities.

Minimum computer resources required

typePC: Windows 9x, 2000 and NT (typically 256 Mb RAM required); Workstation: Unix.
time needed for runExtremely dependent on number of computational cells and grid resolution. Typical CPU run time of ~6h for a 200000 cells simulation on a Pentium III 700 MHz.
storageTypically around 25 Mb per simulation.

Further information

documentationPhD thesis written in Portuguese with VADIS description: Martins, JM, 1998, Dispersão de poluentes na atmosfera em condições de vento fraco, PhD thesis, Dep. Ambiente e Ordenamento, Universidade de Aveiro. Master dissertation written in Portuguese with model application: COSTA, A.M. – Avaliação da Qualidade do Ar ao Nível Local: contributo para o desenvolvimento urbano sustentável. Dissertação apresentada à Universidade de Aveiro para obtenção do grau de Mestre em Poluição Atmosférica, Departamento de Ambiente e Ordenamento, Universidade de Aveiro, Aveiro, Portugal. Fevereiro 2003. SUTRA European Project (EVK4-CT-1999-00013) Deliverables: D04.3 – VADIS Street Canyon Model: Methodology Description D04.4 – VADIS Operational Street Canyon Model (operational prototype).
model referencesBORREGO, C.; TCHEPEL, O.; COSTA, A.M.; AMORIM, J.H. and MIRANDA, A.I. – Emission and dispersion modelling of Lisbon air quality at local scale. Atmospheric Environment: Elsevier, Vol. 37 (2003) pp. 5197-5205. BORREGO, C.; TCHEPEL, O.; COSTA, A.M.; MARTINS, H.; FEREEIRA, J. and MIRANDA, A.I. - Traffic-related particulate air pollution exposure in urban areas. Atmospheric Environment: Elsevier, Vol. (2006), pp. (in press). BORREGO, C.; TCHEPEL, O.; SALMIM, L; AMORIM, J.H.; COSTA, A.M. and JANKO, J. – Integrated modelling of road traffic emissions: application to Lisbon air quality management. Cybernetics and Systems: An International journal. Taylor & Francis, Vol. 35, Numbers 5-6 (2004), p. 535-548.
webpagewww.dao.ua.pt/gemac
additional information

Model properties

Model type

2D
3D
meteorology
chemistry & transport

Model scale

microscale
mesoscale
macroscale
short term
long term

Meteorological variables

PrognosticDiagnostic
u
v
w
ζ
pv
T
θ
θl
p
Gph
ρ
qv
qt
qlc
qf
qsc
qlr
qsh
qsg
qss
N
E
ε
K
zi
other variables i
other variables ii
other variables iii

Chemical substances

PrognosticDiagnosticDry depositionWet depositionInput data
SO2
NO
NO2
NOX
NH3
HNO3
O3
CH4
DMS
H2O2
VOC
C6H6
HCHO
CO
CO2
POP
PM 10
PM 2.5
PPM10
PM 0.1
PM 1
NH4
SO4
dust
sea salt
BC
POM
SOA
NO3
Other gasespassive gases
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivity
2nd radioactivity
3rd radioactivity
remarks

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Meteorology

turbulence schemek-e turbulence scheme. This scheme corresponds to a one-and-a-half order closure that retains the prognostic equations for the zero-order statistics such as mean wind, temperature, humidity and the variances of the referred variables. The TKE equation is used in place of the velocity variance equations. A highly-parameterized prognostic equation for the dissipation rate is included in addition to the equation for TKE.
deep convection
surface exchangeWall functions.
surface temperatureUser defined.
surface humidity
radiation
unresolved orographic drag
radiation in vegetation
radiation between obstacles
treatment of obstaclesConsidered by imposing conditions on interior grid nodes.
clouds / rain
remarks

Chemistry & transport

photolysis rate
dry depositionAn absorption layer may be defined: a fraction of the particles falling in this layer are considered deposited.
wet deposition
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)
wet phase chemistry (give details)
more information

Aerosol chemistry

passive aerosol
dry aerosol
wet aerosol
sectional approach
modal approach
other
nucleation
coagulation
condensation
aerosol mixing
aerosol ageing
primary aerosol formation
aerosol-gas phase interactions
optical properties
give details

Initialization & boundary treatment

Initialization

chemistry & transport
meteorologyThe wind field may be (optionally) developed over the unobstructed domain till convergence

Input data (name sources for data, e.g. website)

orography
land use
obstaclesbuildings, through node redefinition
vegetation
meteorologywind and temperature profiles, ground temperature
concentrations
emissions
remarks

Data assimilation

MeteorologyChemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
details

Boundary conditions

MeteorologyChemistry & transport
surfaceRoughness parameter, temperature (wall functions used)
topSymmetry
lateral inflowWind and temperature profiles, direct input or developed over unobstructed field till convergence
lateral outflowFree, except for mass balance kept correct

Nesting

MeteorologyChemistry & transport
one way
two way
other
variables nested
nesting online
nesting offline
data exchange by array
data exchange by file
time step for data exchange
explain method
variables nested
other

Solution technique

Coordinate system and projection

Horizontal

cartesian
Lambert conformal
latitude / longitude
rotated lat. / long.

Vertical

z coordinate
surface fitted grid
pressurecoordinate
sigma coordinate
remarks

Numeric

Meteorology

Grid

Arakawa A
Arakawa B
Arakawa C
Arakawa D
Arakawa E
uniform grid
nonuniform grid
Euler

Time integration

explicit
split-explicit
semi-implicit
other

Spatial discretisation

momentum equations
scalar quantities
additional information
other

Chemistry & transport

Grid

Arakawa A
Arakawa B
Arakawa C
Arakawa D
Arakawa E
uniform grid
nonuniform grid
Euler
Lagrange
Gauss

Time integration

explicit
split-explicit
semi-implicit
time step same as meteorology
other

Spatial discretisation

scalar quantities
additional information
other
chemistry solver

Model resolution

Meteorology

HorizontalVertical
max
min

Chemistry & transport

HorizontalVertical
max
min

Domain size

Meteorology

HorizontalVertical
max10.2
min0.010.01

Chemistry & transport

HorizontalVertical
max10.2
min0.010.01

Model Validation and Application

Validation & evaluation

Used validation & evaluation methods

analytic solutions
evaluated reference dataset
model intercomparison
additional validation & evaluation efforts
remarks

Application examples

application examples2. Wind flow simulations were performed by VADIS and compared with CHENSI model under ATREUS network. a) Project title Advanced Tools for Rational Energy Use towards Sustainability with emphasis on microclimatic issues in urban applications (ATREUS) network (http://aix.meng.auth.gr/atreus/). b) Relevant references S. Vardoulakis et al. Intercomparison of CFD models within ATREUS: Single building configuration, presented to the ERCOFTAC Meeting on Urban Scale CFD, Nottingham (UK), 9-10 September 2004. K. Richards et al. A wind tunnel investigation of thermal effects within the vicinity of a single block building with leeward wall heating, accepted to the ERCOFTAC Meeting on Urban Scale CFD, Nottingham (UK), 9-10 September 2004. S. Vardoulakis, R. Dimitrova, K. Richards, D. Hamlyn, G. Camilleri, M. Weeks, J-F. Sini, R. Britter, C. Borrego, M. Schatzmann, N. Moussiopoulos, Numerical model inter-comparison for a single block building within ATREUS, accepted for oral presentation at the 10th International Conference on Harmonisation within Atmospheric Dispersion, 17-20 October, 2005, Crete, Greece. c) Project’s short description The project research objectives include: • The study of the urban energy budget taking into account the local and microclimatic conditions, • Use of the knowledge gathered by latest studies on wind flow modifications by urban structures, their geometry and dimensions, • Development of city maps to allow the determination of optimum arrangements of groups of buildings to optimise the exchange processes for an area of the city or for the city as a whole, • Study of the flow and turbulence characteristics within a street canyon with special emphasis in the boundary layers of building walls and roofs, • Investigation of the thermal effects on flow modification within street canyons with special regard to low wind speed conditions around buildings, • Evaluation of the wind field around buildings, • Determination of the exploitable RES potential on the urban areas, and • Determination of heating and cooling loads of the buildings, and their impact on the urban microclimate. d) more details on Model performance Both the micro-scale numerical models used (VADIS and CHENSI) were extensively validated against the experimental data for both the isothermal (cold cube) and thermal cases. Both codes made representative predictions of the mean velocity field for the cold cube case but tended to over predict mean turbulent kinetic energy in regions of impingement, a common problem when using RANS codes with variants of the standard k-e turbulence model. In both cases improvements in overall predictions were observed when non-uniform inflow boundary conditions, the same as that recorded in the wind tunnel were applied. With respect to the thermal cases CHENSI generally performed better at predicting the mean temperature field and resulting modifications in the velocity distribution within fair agreement with the experimental data at the model centre-plane. Predictions were further improved through applying a new thermal wall condition, obtained from the experimental data, based on the heat flux at the heated face of the cube. In general VADIS over-predicted the buoyancy force and mean temperature field in the wake of the model. Difficulties with VADIS in applying the thermal conditions to more complex domain meant only CHENSI was further used to make predictions of wind and temperature fields within the more complex ‘Lisbon’ geometry. The VADIS code encountered difficulties with these simulations primarily due to the recent addition of wall functions into the code. VADIS is an in-house code developed at GEMAC/UA and is always under development. This compounded with limited time meant that this problem with VADIS could not be fully resolved within ATREUS. However work will continue in this area. 2.Comparisons were made against FLUENT model a) Project title SUTRA Project b) Relevant references BORREGO, C.; TCHEPEL, O.; COSTA, A.M.; AMORIM, J.H. and MIRANDA, A.I. – Emission and dispersion modelling of Lisbon air quality at local scale. Atmospheric Environment: Elsevier, Vol. 37 (2003), p. 5197-5205. c) Project’s short description The primary objective of SUTRA was to develop a consistent and comprehensive approach and planning methodology for the analysis of urban transportation problems, that helps to design strategies for sustainable cities. This included an integration of socio-economic, environmental and technological concepts including the development, integration, and demonstration of tools and methodologies to improve forecasting, assessment and policy level decision support. VADIS model was one of the numerical tools used in the above mentioned project. The model was applied to the Lisbon city centre in order to evaluate the air pollution associated to road traffic. The study domain covers an area of 450 m x 450 m and is characterised by strictly perpendicular streets including several one-way roads and a pedestrian zone. During the simulation period, wind direction was mainly from Northwest, with velocities varying between 1 m s-1 and 6 m s-1. Background concentrations entering the model domain were based on CO average concentrations measured at an urban monitoring station that is not directly influenced by the emission sources. Hourly simulation were conducted with VADIS to obtain CO concentration levels for a typical summer day, which was chosen using a statistical meteorological approach. Several traffic management scenarios were developed and evaluated using the TREM (Transport Emission model for Line Sources) and VADIS results. d) more details on Model performance Hourly CO concentrations obtained with VADIS for the Lisbon city centre were compared with concentration values measured by an air quality station located in the study domain and with FLUENT results. There is a good agreement between predicted and measured values between 0 a.m. and 3 p.m. for the simulated day. Moreover, during the time period when model estimations and measurements show some discrepancy, the results obtained with FLUENT and VADIS are very similar, indicating that the trend of both models to underestimate the CO concentrations could be justified by a possible inaccuracy associated with initialisation data. Due to the low CO background concentration (77 µg m-3), the modelling results are not affected by the background values. A quantitative analysis to determine modelling uncertainties has been applied to the estimated CO concentration values. The analysis is based on the definition of maximum deviation of the measured and calculated levels during the considered period. To be compared with modelling quality objectives established by the Directive (200/69/EC), 8-hour average CO values were evaluated. Based on this approach, the average uncertainty of the model prediction for this study corresponds to 15 %, achieving 52 % as a maximum for the 8-hour average period from 1 to 8 p.m.. This value slightly exceeds the 50 % acceptability limit defined by the Directive.

Participation in specific model evaluation exercises

AQMEII
List experiments (AQMEII)
Cost728
List experiments (COST728)
HTAP
List experiments (HTAP)
MEGAPOLI
List experiments (MEGAPOLI)