1. Using for Pollutant Dispersion Andrea Vignaroli – University of Perugia

2. UNIVERSITA’ DEGLI STUDI DI PERUGIA Facoltà di Ingegneria Dipartimento di Ingegneria Industriale In collaboration with… Vector AS &

3. The aims of this work… -To develop hidden potentialities of Windsim -To put the basis for the realization of a new commercial software D.I.IN.

4. Foreseing pollutant emissions can be important to… interpretate data measured by the interest area monitoring web necessary for the Valuation of Environmental Impact of future factories or infrastructure D.I.IN.

5. Applicabilty Fields Spatial Scale: local and meso scale; Territory type: every kind of site (complex terrain) Time Scale: every kind of period (from 1 hr to a year) Source type: every kind source that can be discretized with an emission point Pollutant type: gas, smells & particles D.I.IN.

6. Dispersion Modelling on PHOENICS Two approaches for Two different tipology of pollutants: GENTRAPARTICLES PASSIVE DISPERSIONGAS & SMELLS D.I.IN.

7. - GENTRA - stochastic particle dispersion model for turbulent flow Gentra integrates the particle equations in a Lagrangian frame while Phoenics solves the equations governing the continuous phase in the normal manner D.I.IN.

8. - GENTRA - Particle Dispersion (Gentra) Data Input: X, Y, Z local position [m]; u, v, w inlet velocity vectors [m/s]; Flux rate in [Kg/s]; Density [Kg/m^3]; Particle diameter [m]; Number of particles to be simulated; every particle will bring with itself a fraction of the given emission rate D.I.IN.

9. - GENTRA - Concentration map Amount of particles in each cell D.I.IN.

10. - GENTRA - Results for 240°-sector simulation D.I.IN.

11. - Passive Dispersion - “ PASSIVE” means… Determining the flow field in the classical way Introducing in the q1 file a new inlet for the pollutant (Gas or smell) New simulation using the previous run as input to the dermine how the new phase is dragged by the wind D.I.IN.

12. - Passive Dispersion - Passive Dispersion Data Input : X, Y, Z position in cell numbers; Flux rate in [Kg/s]; Area of Chimney final section [m]; Temperature [°C]; Density [Kg/m^3]; D.I.IN.

13. - Passive Dispersion - Results for 240°-sector simulation D.I.IN.

14. OUTPUT DATA Strictly Correlated to what the enviromental laws prescribe Importants Outputs are… concentration map of short term simulation for a given wind speed and direction 3D visualization of the concentration field using isosurfaces concentration map of a long term simulation for a given one – year - climatology D.I.IN. ?

15. - Output Data - 12 sectors climatology 12 Averaged speeds over boundary layer 12 Phoenics runs with different input For long term simulation the climatology influeces the windfield module D.I.IN.

16. - Output Data - One-year-averaged concentration map D.I.IN.

17. … WORK IN PROGRESS Something for the future… validate the model with measured data prescribed pollutant limit as input in order to have percentiles, and map with over valued concentration points 24 sectors climatology for smoother maps linear and volume sources D.I.IN.