DIPCOT A lagrangian particle model for Dispersion over complex terrain.


Davakis Efstratios
Bartzis John

Information sheet

Brief description (key words)

  1. Policy issue

    Policy issue

    climate change (dispersion)
    industrial pollutants
    nuclear emergencies

  2. Application type

    air quality assessment
    policy support
    emergency planning
    public information
    scientific research

  3. Model output


  4. Air pollution source

    stack/ multiple

  5. Release type


  6. Spatial scale

    local-to-regional (30-100Km)

  7. Simulation character


  8. Pollutants modelled

    passive / generic
    buoyant /generic

  9. Processes considered

    complex meteorology
    complex terrain

  10. Computer platform


Long description

  1. Basic information

    Model name

    DIPCOT (DIsPersion over COmplex Terrain)

    Last update

    Version II, last update: January 1998


    Environmental Research Laboratory, NCSR "DEMOKRITOS"

    Contact person (providing all necessary technical support)

    Efstratios Davakis
    John Bartzis

    Contact address

    Environmental REsearch Laboratory
    NCSR Demokritos
    Aghia Paraskevi 15310- Athens

    Phone number

    +30 2106525004

    Fax number

    +30 2106525004

    E-mail address


    Technical support

    Provided by contact person


  1. Intended field of application

    Simulation of air pollutant dispersion at the local-to-regional scale.

  2. 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)

  3. 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.

  4. Model limitations

    Do chemical reactions, no rain.

  5. Resolution

    Temporal resolution
     time step for dispersion calculation: variable
     simulated time period : min-years

    Horizontal resolution
     1m –100 Km

    Vertical resolution
     1m – 10Km

  6. |u>Schemes

    Transport of particles
    Langevin Equation
    Plume Rise Calculations
    Briggs Model as defined by Hurley and Physic (1993)
    Boughton model

  7. Solution technique

    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).

  8. Input requirements

    The user provides the emission data: total mass released over a specific time interval.
    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 meteorological models.

    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 meteorological information

    Initial conditions
    Exit velocity and temperature from source.

    Boundary conditions
    Reflection of particles at ground and the top of top of the atmospheric boundary layer.

    Other input requirements
    The number of particles, the location of the source and of the measurement points (grid or observations points)

  9. Output quantities

    Ensemble average concentrations and dose at pre-determined points and times

  10. User interface availability

    NCAR based graphical interface

  11. User community

    The Public Power Corporation of Greece has already bought the code.
    DIPCOT need user, which must only have computer knowledge.

  12. Previous applications

    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 (Ostande)
  • 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.
  1. Documentation status

    Manual under construction

  2. 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 correct.

  3. 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 be increased.

  4. Portability and computer requirements


    DIPCOT is Fortran 77 code, running at HP workstation platform. Implementation to PC systems is under construction

    CPU time

    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 files.

  5. Availability

    The model is not a public domain programme. Information on the conditions for obtaining DIPCOT can be provided by the contact person.

  6. References

    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 75-83

    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, 1997

    H.R. Olesen, Tools for Model Evaluation (1997), National Environmental Research Institute. (personal communication)

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