Welcome guest. Please login.

List, classification & detail view

Note:
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.

TAPM: The Air Pollution Model

General information

Model name and version

short nameTAPM
full nameThe Air Pollution Model
revision04/2005
date
last change

Responsible for this information

nameCarlos Borrego
institute
addressUniversity of Aveiro
zip3810
cityAveiro
countryPortugal
phone
fax
e-mailborrego(belongs-to)ua.pt

Additional information on the model

Contact person for model code

same as person above
namePeter Hurley
instituteCSIRO Atmospheric Research
divisions
streetPMB 1 Aspendale, Vic 3195
zip
city
countryAustralia
phone
emailPeter.Hurley@csiro.au
fax

Model developer and model user

developer and userCSIRO Atmospheric Research, PMB 1 Aspendale, Vic 3195

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

type450 MHz,Pentium III processor, 128 MB RAM, 20 GB HDD, CDROM,
time needed for runvary from minutes to days, depending on your choice of model
storage

Further information

documentationHurley P. 2005 The Air Pollution Model (TAPM) Version 3 – Part 1: Technical Description, CSIRO – Atmospheric Research.
model referencesCOUTINHO, M., RIBEIRO C., PEREIRA M. E BORREGO C. - Simulation of the plume emitted by a municipal waste incinerator located in the Madeira island - International Journal of Environment and Pollution (IJEP) Volume 24 – pg. 218-229 Issue 1/2/3/4 - 2005
webpagewww.dar.csiro.au/TAPM
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 gases
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivity
2nd radioactivity
3rd radioactivity
remarksthe model predicts the flows important to local-scale air pollution, such as sea breezes and terrain-induced flows, against a background of larger-scale meteorology provided by synoptic analyses.

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Meteorology

turbulence schemeThe turbulence terms area determined by solving equations for turbulence kinetic energy and eddy dissipation rate, and then using these values in representing the vertical fluxes by a gradient diffusion approach, including a counter-gradient term for heat flux.
deep convection
surface exchangeBoundary conditions for the turbulent fluxes are determined by Monin-Obukhov surface layer scaling variables with stability functions from Dyer and Hicks.
surface temperatureIf the surface type is water, then the surface temperature is set equal to the water surface temperature, and surface moisture is set equal to the saturation value. If the surface type is permanent ice/snow, then the surface temperature is set equal to –4°C, and surface moisture is set equal to the saturation value.Surface temperature and moisture are set to the deep soil values specified, with surface temperature adjusted for terrain height using the synoptic lapse rate.
surface humidityConservation equations are solved for specific humidity.
radiationRadiation at the surface is used for the computation of surface boundary conditions and scaling variables, with the clear-sky incoming short-wave component from Mahrer and Pielke.
unresolved orographic drag
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rainExplicit cloud micro-physical processes are included.
remarks

Chemistry & transport

photolysis rate
dry depositionThe method for calculating the dry deposition velocity of APM and FPM is based on the approach of Seinfeld and Pandis.
wet depositionFor the pollutants considered in this model, the only ones removed by wet processes are APM, FPM, SO2, and H2O2.
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 model is initialised at each grid point with values of u, v, θ,q interpolated from the synoptic analyses. Iso-lines of these variables are oriented to be parallel to mean sea level (i.e. cutting into the terrain). Turbulence levels are set to their minimum values as the model is started at midnight. The Exner pressure function is integrated from mean sea level to the model top to determine the top boundary condition. The Exner pressure and terrain-following vertical velocity are then diagnosed using equations. Surface temperature and moisture are set to the deep soil values specified, with surface temperature adjusted for terrain height using the synoptic lapse rate.

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

orographyEarth Resources Observation Systems (EROS)
land useEarth Resources Observation Systems (EROS)
obstacles
vegetation
meteorologysynoptic scale meteorology datasets Limited Area Prediction System (LAPS) and Global Analysis and Prediction (GASP) from Bureau Of Meteorology (BOM)
concentrations
emissionsemissions from point, line, area/volume or grid sources.
remarks

Data assimilation

MeteorologyChemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsThe method used to optionally assimilate wind observations is based on the approach of Stauffer and Seaman (1994), where a nudging term is added to the horizontal momentum equations (for u and v).

Boundary conditions

MeteorologyChemistry & transport
surfaceThe soil and vegetation parameterisations are based on those from Kowalczyk et al. (1991).
topAt the model top boundary, all variables are set at their synoptic values.
lateral inflowOne-way nested lateral boundary conditions are used for the prognostic equations.
lateral outflow

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 solverphotochemistry (generic reaction set)

Model resolution

Meteorology

HorizontalVertical
max
min

Chemistry & transport

HorizontalVertical
max
min

Domain size

Meteorology

HorizontalVertical
max10008000
min

Chemistry & transport

HorizontalVertical
max
min

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 examplesCOUTINHO, M., RIBEIRO C. E BORREGO C. - Validação Meteorológica de um modelo de Dispersão Atmosfera Portugal, 8ª Conferência Nacional do Ambiente, Lisboa, 27-29 Outubro de 2004 COUTINHO, M., RIBEIRO C., PEREIRA M. E BORREGO C. - Simulation of the plume emitted by a municipal waste incinerator located in the Madeira island - International Journal of Environment and Pollution (IJEP) Volume 24 – pg. 218-229 Issue 1/2/3/4 - 2005 Ribeiro, C., 2005: Aplicação de um Modelo Meteorológico e de Qualidade do ar a Portugal. Dissertação apresentada à Universidade de Aveiro para obtenção do grau de Mestre em Poluição Atmosférica.

Participation in specific model evaluation exercises

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