DIPCOT A lagrangian particle model for Dispersion over complex
Brief description (key words)
climate change (dispersion)
air quality assessment
- Model output
- Air pollution source
- Release type
- Spatial scale
- Simulation character
- Pollutants modelled
passive / generic
- Computer platform
DIPCOT (DIsPersion over COmplex Terrain)
Version II, last update: January 1998
Environmental Research Laboratory, NCSR "DEMOKRITOS"
Contact person (providing all necessary technical
Environmental REsearch Laboratory
Aghia Paraskevi 15310- Athens
Provided by contact person
Intended field of application
Simulation of air pollutant dispersion at the local-to-regional scale.
Model type and dimension
Three-dimensional, Lagrangian particle dispersion model.
The model utilises information from :
topographical pre-processor (DELTA code)
meteorological pre-processor: prognostic (ADREA-I code)
or diagnostic (FILMAKER-ADREA-diagn codes)
Model description summary
DIPCOT is a dispersion model, which simulates the motion of air pollutants over complex
terrain, based on a 3-D Lagrangian particle scheme. In order to build up a picture of the
concentration distribution the total mass of the pollutant is assigned to a certain number
of computational particles. Each particle is “moved” with a velocity which takes
account of two basic components: the transport due to the mean wind velocity, provided by
meteorological pre-processors, and the random turbulent fluctuations are estimated by the
Langevin equation. The knowledge of the spatial and temporal distribution of the particles
allow the calculation of the mean ensemble concentration of the pollutants. DIPCOT
utilises topographical and meteorological information given at a 3-D grid and is capable
of simulating dispersion from multiple point sources, at all atmospheric conditions. In
the case of buoyant point sources the model performs plume rise calculations.
Do chemical reactions, no rain.
time step for dispersion calculation: variable
simulated time period : min-years
1m –100 Km
1m – 10Km
Transport of particles
Plume Rise Calculations
Briggs Model as defined by Hurley and Physic (1993)
The finite-difference form of Langevin equation is used, obtained following the
Ito’s interpretation rule. The random term on Langevin equation is derived form two
independent Gaussian distributions, with zero mean and variance 1. The time step of
particle motion is a fraction of the Lagrangian time step. All the parameters of Langevin
equation are estimated depending on atmospheric stability. The concentration calculations
are based Yamada and Bunker scheme, used in order to minimise the number of the particles
that are released. In the case of buoyant point sources the equations governing the rise
of a bent-over plume Briggs are used, following the algorithm proposed by Hurley and
Physic (4th order Runge - Kutta).
The user provides the emission data: total mass released over a specific time
The release rate can be variable.
DIPCOT utilises ‘gridded’ meteorological information from the following models:
i. The ADREA-I code – prognostic meteorological model.
ii.The FILMAKER and ADREA-diagnos codes - diagnostic meteorological Information
3-D fields for wind velocity, temperature, and pressure and 2-D fields
for mixing layer height friction velocity, convective velocity, atmospheric stability,
cloud cover and Monic Obukhov legth, are used.
Orography height, and roughness height are provided at the same grid with the
Exit velocity and temperature from source.
Reflection of particles at ground and the top of top of the atmospheric boundary
Other input requirements
The number of particles, the location of the source and of the measurement points
(grid or observations points)
Ensemble average concentrations and dose at pre-determined points and times
User interface availability
NCAR based graphical interface
The Public Power Corporation of Greece has already bought the code.
DIPCOT need user, which must only have computer knowledge.
DIPCOT has been applied to the following cases
- TRANSALP 90 experiment, C8F16 release near ground at the Swiss
Alps (field data)- complex terrain.
- Ô16 trial at the frame of FLADIS experiment, ÍÇ3 release (field data).
- Á1 trial at the frame of EMU experiment (wind
tunnel data) – release from a building.
- Intercomparison exercise, presented at the 4th International Confernece on
Harmonization within Atmospheric Dispersion Modelling for Regulatory Purposesa,1996
- Megalopoli case, data from the power plant of the Public Power Corporation of Greece at
Megalopoli, Peloponnise (field data).
- Ęincaid experiment, SF6 release from
elevated buoyant source (field data) – flat terrain, from Model Validation Kid at the
frame of Harmonization within Atmospheric Dispersion Modelling for Regulatory Purposes)
- Indianapolis experiment, SF6 release from elevated buoyant source (field
data) - flat terrain, from Model Validation Kid at the frame of Harmonization within
Atmospheric Dispersion Modelling for Regulatory Purposes).
- As Pontes case – data for As Pontes power plant at Spain – elevated bouyant source,
complex terrain (under examination), at the frame of the intercomparison exercise that
will be presented at the 5th International Confernece on Harmonization within
Atmospheric Dispersion Modelling for Regulatory Purposes.
Manual under construction
Validation and evaluation
DIPCOT is validated now against experimental data from Model Validation Kid, at the frame
of Harmonization within Atmospheric Dispersion Modelling for Regulatory Purposes (see also
the section of application and references), - KINCAID and INDIAPOLIS data. Several
applications, as the those that have been presented at section 13, shows that the model is
capable of satisfactory simulating dispersion for all the atmospheric stability
conditions, even in complex terrain, provided that the meteorological information is
Frequently Asked Questions
Q: How can you judge the accuracy of the model results?
A: By applying appropriate statistical tools (see Olensen 1997)
Q: How many particles should be used?
A: It depends on the application (topography, meteorological data).e.g for an application
at flat terrain when the meteorological conditions are stable in time and space the number
of particles can be quite small. However, in the case of complex terrain where the
meteorological conditions are variable with time and space then number of particle should
Portability and computer requirements
DIPCOT is Fortran 77 code, running at HP workstation platform. Implementation to PC
systems is under construction
Depend on the application and the number of particles. Typically for 24 real hours of
dispersion at complex terrain using 24000 particles 5 hr of CPU (on an HP –720) are
usually enough, for a 40x40x13 meteorological grid.
For the same typical case: 80 Mbytes RAM. Disk space: 5-10 Mbytes needed for the output
The model is not a public domain programme. Information on the conditions for
obtaining DIPCOT can be provided by the contact person.
J.G. Bartzis, M. Varvayanni G. Graziani E. Davakis, P. Deligiannis, &N. Catsaros “Ôhe TRANSALP Experimental Tracer Release and Transport
Simulation”, Air Pollution 95, Ĺditors H. Power, N.
Moussiopoulos, C.A. Brebbia, Porto Carras, 26-29 September 1995, pp 429-434
P. Deligiannis, J.G. Bartzis, N. Catsaros, E. Davakis, M, Varvayanni, J. Ĺhrhardt “RODOS Application on Complex Terrain Dispersion
Problem using DETRACT”, International Conference of Probabilistic Safety Assessment and
Management - ESREL 96, Editors P.C. Cacciabue, I.A. Papazoglou, Grete, 24-28 July 1996, pp
Deligiannis, J.G Bartzis, E. Davakis, "Complex Terrain Modeling Exercise, 4th
Workshop on Harmonization within Atmospheric Dispersion Modeling for Regulatory Purposes,
6-9 May 1996 Oostende, Belgium, published at the Int. J. of Environment and Pollution. Vol
8, Nos 3-6, pp 367-377, 1997
Ě. Varvagianni, P. Deligiannis, E. Davakis. A.G.
Venetsanos, N. Catsaros, “Wind flow and pollutant dispersion diagnosis over complex
terrain based on sparce meteorological measurements”, 5th Conference on
Environmental Science and Techonology – Ěolybos Lesbos,
pp 273 –280, 1997
J.G. Bartzis, A.G. Venetsanos, M. Varvayanni, S. Andronopoulos, E. Davakis, J. Statharas,
N. Catsaros, P. Deligiannis. “Wind flow and dispersion modelling over terrain of high
complexity”, Air Pollution V, Editors H. Power, T. Tirabassi, C.A. Brebbia, pp 143-156,
H.R. Olesen, Tools for Model Evaluation (1997), National Environmental Research Institute.