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More information on some input arrays can be found when moving the cursor above the corresponding field in the questionnaire. Those fields are also explained in the glossary.

EPISODE: AirQUIS-EPISODE

General information

Model name and version

short nameEPISODE
full nameAirQUIS-EPISODE
revision3.2
date2005-10-10
last change

Responsible for this information

nameSam-Erik Walker
institute
address
zip
city
countryNorway
phone
fax
e-mailstl(belongs-to)nilu.no

Additional information on the model

Contact person for model code

same as person above
nameSam-Erik Walker
instituteNorwegian Institute for Air Research
divisions
streetP.O. Box 100
zip2027
cityKjeller
countryNorway
phone+47 63898083
emailsam-erik.walker@nilu.no
fax+47 63898050

Model developer and model user

developer and userSam-Erik Walker, Leiv Håvard Slørdal, Sverre Solberg, Bruce Denby

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 details

Minimum computer resources required

typeFor a 20 x 20 x 5 grid and one single inert pollutant
time needed for run24 h simulation = 1 sec of CPU time on a 2 Ghz Pentium 4 PC
storageminimum 512 MB RAM when run on a Windows XP PC

Further information

documentationSlørdal, L.H., Walker, S.E., Solberg, S. (2003) The urban air dispersion model EPISODE applied in AirQUIS2003. Technical description. Kjeller, Norwegian Institute for Air Research (NILU TR 12/2003).
model referencesLaupsa, H. and Slørdal L.H. (2002) Applying model calculations to estimate urban air quality with respect to the requirements of the EU directives on NO2, PM10 and C6H6. In: Proceedings of the Eight International Conference on Harmonisation within atmospheric dispersion modelling for regulatory purposes. Sofia, Bulgaria, Demetra Ltd., pp. 429-433. Denby, B. (2003) City-Delta calculations for the city of Berlin. (To be published). Ødegård, V., Gjerstad, K.I., Bjergene, N., Jablonska, H.T.B., Walker, S.E., Bedre Byluft, Evaluering av prognosemodell for meteorologi og luftkvalitet vinteren 2003/2004 The Norwegian Meteorological Institute report no. 12/2004. (http://met.no/english/r_and_d_activities/publications/2004/12_2004/abstract.html) Gronskei, K.E., Walker, S.E. and Gram, F. (1992) Evaluation of a model for hourly spatial concentrations distributions, Atmos, Environm. 27 B, 105-120. Larssen, S., Gronskei, K.E., Gram, F., Hagen. L.O. and Walkerr, S.E. (1994) Verification of urban scale time dependent dispersion model with subgrid elements in Oslo, Norway. Air Pollution Modelling and ist Appl. X, Plenum Press, New York
webpagewww.nilu.no
additional informationAlso see description of this model on the European Topic Center on Air Quality, Model Documentation system web site: www.etcaq.rivm.nl.

Model properties

Model type

2D
3D
meteorology
chemistry & transport

Model scale

microscale
mesoscale
macroscale
short term
long term

Meteorological variables

Input data
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 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
remarksThe subgrid scale line source model is intended for a relatively flat area and does not take into account any complex terrain effects. The subgrid scale line source and the point source segmented plume/puff trajectory model does not take into account any complex photochemistry, except for the fast NO-NO2-O3 cycle.

Parametrizations

Chemistry & transport

photolysis rateBased on solar height and cloud cover.
dry depositionBased on a standard resistance model using aerodynamic, boundary layer and surface resistance.
wet depositionBased on a standard wet scavenging model using precipitation intensity.
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)A simple scheme for photochemical equilibrium between NO, NO2 and O3 is included.
wet phase chemistry (give details)Not included.
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 & transportInitial concentrations (3D grid) for each pollutant can be provided by the user (usually set equal to zero). Final concentrations from a previous run may be used as initial concentrations for a new run.
meteorologyBackground values are given

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

orographyYes
land useYes
obstacles
vegetation
meteorologyTemperature (stability) and wind measurements in at least one meteorological mast is the minimal amount of meteorological data which must be provided. Gridded wind fields are usually calculated separately, by using a wind field model which takes into effect the influences of the topography on the wind field depending on stability. Other meteorological parameters such as cloud cover, relative humidity and precipitation may also be given as input data, usually based on measurements. Hourly gridded values of turbulence (sigma-v and sigma-w) and mixing height are calculated using a separate boundary layer meteorological preprocessor. This preprocessor also calculates other parameters used by the model, such as the Monin-Obukhov length, the friction velocity, the Lagrangian time scales and the mixing height. Alternatively, some or all of these meteorological data may also be calculated externally by using other meteorological model systems, and input to the model via data files.
concentrationsInitial and background 3D gridded concentrations can be read in from external files.
emissionsThese are usually calculated by AirQUIS or some other emission preprocessor system as hourly values for each grid cell (area source), road (line source), and stack (point source), and used by the dispersion model.
remarks

Data assimilation

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

Boundary conditions

Chemistry & transport
surfaceemissions and dry and wet depositions
topbackground concentrations
lateral inflowbackground concentrations
lateral outflowbackground concentrations

Nesting

Chemistry & transport
one way
two way
other
variables nested
nesting online
nesting offline
data exchange by array
data exchange by file
time step for data exchange1h
explain methodHourly background concentrations can be nested as boundary conditions from a more coarse outer model.
variables nestedconcentrations
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
remarksThe advection and diffusion equations of the grid model contains a sigma coordinate transform where the grid cells follows the terrain close to the ground, while being more independent of the terrain higher up (stretched vertical sigma-coordinate).

Numeric

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
othersubgrid Gaussian point and line source (integrated) numeric models
chemistry solverFollows very closely the EMEP model chemistry solver for the fast reactions between NO, NO2 and O3.

Model resolution

Chemistry & transport

HorizontalVertical
max101000
min0.120

Domain size

Chemistry & transport

HorizontalVertical
max1502500
min0.350

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 examplesThe model is being used many places in Norway and elsewhere (e.g. Poland, China, Vietnam, Botzwana, South-Africa, etc.) as part of the NILU AQMS system AirQUIS. The model has been applied in a real case simulation for the city of Berlin as part of the City Delta study. City Delta is an activity organized by the EU Clean Air for Europe (CAFE) programme, with the aim of studying the long term model response to urban-scale emission-reduction scenarios (Denby, 2003). (See http://europa.eu.int/comm/environment/air/cafe/ for a description of this programme and its activities.) In Norway, the model is currently being used regularly as part of the project Better City Air (Bedre Byluft) for the cities Oslo, Bergen, Trondheim, Drammen and Stavanger (Ødegård et al., 2004). It has also been applied in other urban air quality studies for Norwegian cities (Laupsa and Slørdal, 2002; Slørdal, 2002; Walker et al., 1999), and in a project to develop a modelling system to link hemispheric-regional and local air pollution (Wind et al., 2003). Denby, B. (2003) City-Delta calculations for the city of Berlin. (To be published). Ødegård, V., Gjerstad, K.I., Bjergene, N., Jablonska, H.T.B., Walker, S.E., Bedre Byluft, Evaluering av prognosemodell for meteorologi og luftkvalitet vinteren 2003/2004 The Norwegian Meteorological Institute report no. 12/2004. (http://met.no/english/r_and_d_activities/publications/2004/12_2004/abstract.html). Laupsa, H. and Slørdal L.H. (2002) Applying model calculations to estimate urban air quality with respect to the requirements of the EU directives on NO2, PM10 and C6H6. In: Proceedings of the Eight International Conference on Harmonisation within atmospheric dispersion modelling for regulatory purposes. Sofia, Bulgaria, Demetra Ltd., pp. 429-433. Slørdal, L. H. (2002). Applying model calculations to estimate future urban air quality with respect to the requirements of the EU directives on NO2 and PM10. In: Proceedings of the Second Conference on Air Pollution Modelling and Simulation. Ed. by B. Sportisse. Berlin, Springer. p. 89-100. Walker S.E., Slørdal L.H., Guerreiro C., Gram F. and Grønskei K.E. (1999) Air Pollution exposure monitoring and estimation. Part II. Model evaluation and population exposure. J. Environ. Monit, 1, pp 321-326. Wind, P., Tarrason, L., Berge, E., Slørdal, L.H., Solberg, S. and Walker, S.E. (2002) Development of a modeling system able to link hemispheric-regional and local air pollution. Joint MSC-W & NILU Note 5/02. Oslo, The Norwegian Meteorological Institute. (http://www.emep.int/reports/emep_note_5_2002.pdf).

Participation in specific model evaluation exercises

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