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.

TCAM: Transport Chemical Aerosol Model

General information

Model name and version

short nameTCAM
full nameTransport Chemical Aerosol Model
revisionV04-2005
dateApril 2005
last change

Responsible for this information

nameClaudio Carnevale
instituteUniversity of Brescia
addressVia Branze, 38
zip25123
cityBrescia
countryItaly
phone+39 0303715449
fax+39 030380014
e-mailcarneval(belongs-to)ing.unibs.it

Additional information on the model

Contact person for model code

same as person above
nameClaudio Carnevale
instituteUniversity of Brescia
divisionsVia Branze, 38
street
zip25123
cityBrescia
countryItaly
phone+39 0303715449
emailcarneval(belongs-to)ing.unibs.it
fax+39 030380014

Model developer and model user

developer and userUniversity of Brescia, Italy

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 detailsthe code will be available in the future

Minimum computer resources required

type1GHz PC, Linux OS, 512 MB RAM
time needed for runfor a 60x60x11 domain, with aerosol module, for 2GHz LInux PC 512 MB RAM: 2 hours of model run per simulated day.
storagefor a 60x60x11 domain, with aerosol module, 70 MB per simulated day.

Further information

documentation
model references[1] Volta, M., Finzi, G. (2005). GAMES, a new comprehensive gas aerosol modelling system. Environmental Modelling and Software, in press, doi:10.1016/j.envsoft.2004.06.012. [2] Sun, P., Chock, D.P., Winkler, S.L. (1994). An Implicit-Explicit Hybrid Solver for a System of Stiff Kinetic Equations. Proc. 87th Air & Waste Management Association Annual Meeting. [3] Wexler, A.S., Seinfeld, J.H. (1991). Second-Generation Inorganic Aerosol Model. Atmospheric Environment, 25: 2731-2748.
webpage
additional information

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
remarks21 Aerosol chemical species: 12 inorganics (H2O, SO4=, NH4+, Cl-, NO3-, Na+, H+, SO2(aq), H2O2(aq), O3(aq), elemental carbon and other) and 9 organics (1 primary organic class and 8 secondary organics).

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Chemistry & transport

photolysis rateDepending on zenith angle.
dry depositionThree layer, full-resistance model.
wet depositionDifferent scavenging models for gases and aerosol. Scavenging coefficient computation based on rainfall rate, cloud water content, gas solubility and diffusivity and particle size.
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)Gas Chemical mechanisms: SAPRC90, SAPRC97, CBIV90, COCOH97 (Extended version of SAPRC97 for multiphase simulation). Solver: Implicit-Explicit Hybrid solver (IEH).
wet phase chemistry (give details)Aqueous oxidation of SO2.
more informationThe aerosol module works coupled with COCOH97 gas-phase chemical mechanism

Aerosol chemistry

passive aerosol
dry aerosol
wet aerosol
sectional approach
modal approach
otherFixed-moving approach
nucleation
coagulation
condensation
aerosol mixing
aerosol ageing
primary aerosol formation
aerosol-gas phase interactions
optical properties
give detailsIn the fixed-moving approach, a generic particle is represented with an internal core containing the non volatile material, like elemental carbon, crustal and dust. The dimension of the core of each size class is established at the beginning of the simulation on the basis of a logarithmic distribution and is held constant during the simulation. The volatile material is supposed to reside in an outer shell of the particle whose dimension is evaluated by the module at each time step on the basis of the total mass and total number of suspended particles. Both shell and core are suppose to be internally mixed.

Initialization & boundary treatment

Initialization

chemistry & transportThe model uses the 3D concentration fields for each species, coming either from measurement or coarser model grid results.
meteorology

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

orographyOrography height for each grid location
land useNone -used by CALMET meteorological preprocessor
obstacles
vegetation
meteorologyHourly 3D wind gridded fields of wind components, air temperature and liquid water content. Hourly 2D fields of mixing height, Monin-Obukhov lenght (L), PGT class, friction velocity (u*), convective scale velocity (w*).
concentrationsInitial conditions: 3D concentration fields for eahc species, coming either from measurement or coarser model grid results. Boundary conditions: Time varying concentrations at lateral boundaries, coming either from measurement or coarser model grid results.
emissionsHourly NOx, NMVOC, NH3, CO, SO2, PM gridded emission fields. NMVOC and PM are split and lumped on the basis of the selected chemical gas and aerosol mechanism. The emission fields are computed by POEM-PM emission pre-processor.
remarksAll the input files are in binary format

Data assimilation

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

Boundary conditions

Chemistry & transport
surface
topTime varying concentrations at lateral boundaries, coming either from measurement or coarser model grid results. In general not used.
lateral inflowTime varying concentrations at lateral boundaries, coming either from measurement or coarser model grid results.
lateral outflowComputed by the transport scheme during the simulation

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 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
remarksTerrain following co-ordinate system.

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
otherMarchuk Operator Splitting Technique. Transport module uses explicit/semi-implicit numerical scheme based on Chapeau function. Chemistry solver: see below

Spatial discretisation

scalar quantities
additional information
other
chemistry solverThe model uses the IEH (Implicit-Explicit Hybrid) solver, which treats the slow reacting species species and the fast reacting ones separately. The slow species ODE system is solved by means of a explicit Crank-Nicholsono scheme, while the fast species one by means of the LSODE fully implicit scheme. This approach ensures the stability of the solution at relatively low computational cost

Model resolution

Chemistry & transport

HorizontalVertical
max101000
min120

Domain size

Chemistry & transport

HorizontalVertical
max607000
min603900

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 examples[1] Angelino, E., Bedogni, M., Carnevale, C., Finzi, G., Minguzzi, E., Peroni, E., Pertot, C., Pirovano, G., Volta, M. PM10 chemical model simulations over the Milan area in the frame of CityDelta exercise, Proc. 5th International conference on Urban Air Quality, Cdrom, ISBN 1-898543-92-5, Valencia (E), 2005; [2] Carnevale, C., Finzi, G., Volta, M. Seasonal characterization of secondary aerosol in the Northern Italy using TCAM model, Proc. 5th International conference on Urban Air Quality, Cdrom, ISBN 1-898543-92-5, Valencia (E), 2005; [3] Bedogni, M., Carnevale, C., Pertot, C., Volta, M. (2004) A four modelling inter-comparison concerning chemical mechanisms and numerical integration methods, Proc. 9th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes (P. Suppan Ed.), Vol. 1, pp 28-32, ISBN 3-923704-44-5, Garmisch-Partenkirchen (D). [4] C. Carnevale, G. Finzi, M. Volta (2005) Seasonal characterization of secondary aerosol in the Northern Italy using TCAM model, Proc. 5th International conference on Urban Air Quality, (R.S. Sokhi, M.M. Millan and N. Moussiopulos editors), Cdrom, ISBN I-898543-92-5, University of Hertfordshire.

Participation in specific model evaluation exercises

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