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A New High Performance Version of the Lagrangian Particle Dispersion Model Spray, Some Case Studies

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Air Pollution Modeling and Its Application XIII

Abstract

Lagrangian particle models are powerful tools to simulate the atmospheric dispersion of gaseous releases. Although having a quite complex mathematical basis (Thomson, 1987, Rodean, 1994), their practical implementation is generally simple and intuitive, allowing to easily take into account complex situations such as the presence of the topography or terrain inhomogeneities, low wind speeds, spatial and temporal variations of meteorological fields. In these models the atmospheric dispersion is simulated by the motion of fictitious particles splitted in a mean part due to the mean wind, and a stochastic fluctuation related to the statistical characteristics of the turbulent flow. It is quite clear that the model accuracy is strongly dependent on the number of emitted particles and the computer time often limits the kind of simulations that can be performed. For this reason, the earlier version of these models were mainly devoted to reproduce the dispersion of a limited number of emissions at local scale. The recent wide and rapid diffusion of very fast computational tools lead to the development of more sophisticated codes, able to take into account more general situations. SPRAY (Tinarelli et al., 1992) is a Lagrangian stochastic particle model designed to perform dispersion simulations in complex terrain. The version 1 of the code, based on a three dimensional form of the Langevin equation for the random velocity with coupled non-gaussian random forcing following Thomson (1984, T84 in the following) and subsequently improved (Tinarelli et al., 1992), was able to satisfactorily reproduce local to regional scale dispersion both over flat (Brusasca et al., 1989, 1992) and complex terrain (Brusasca et al., 1995, Nanni et al., 1996) taking into account the emission from single or multiple sources. The development of a better based theory (Thomson, 1987) and the further demand of more complex regional scale simulations able to cover longer periods with a variety of emissions of different kinds (i.e. main roads, industrial or urban area) called for a new version of the code. The new version 2 of SPRAY code contains some improvements regarding the theoretical approach, turbulence parametrizations and time response characteristics. In this paper we describe these new developments, comparing model performances with those of the previous version through simulations performed both in theoretical and real cases.

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References

  • Baerentsen J.H. and Bcrkowicz R., Monte-Carlo simulation of plume diffiision in the convective boundary layer, Atmospheric Environment, 18, 701–712 (1984).

    Article  Google Scholar 

  • Brusasca G., Tinarelli G.. Anfossi D., Particle model simulation of diffusion in low windspeed stable conditions. Atmospheric Environment 26, 707–723 (1989).

    Google Scholar 

  • Brusasca G., Tinarelli G., Anfossi D., Comparison between the results of a Monte Carlo atmospheric diffusion model and tracer experiments, Atmospheric Environment 23, 1263–1280 (1992).

    Google Scholar 

  • Brusasca G., Fcrrero E., Anfossi D., Desiato F., Tinarelli G., Morselli M.G., Finardi S., Sacchetti D., “Intercomparison of 3-D flow and particle models with Transalp 1989 meteorological and tracer data”, Proc. of the 21st CCMS-NATO meeting, Baltimore, 6–10 November, 1995, 386–394.

    Google Scholar 

  • Ferrero E. and Anfossi D., Sensitivity analysis of Lagrangian Stochastic models for CBL with different PDF’s and turbulence parameterizations. Air Pollution Modelling and its Applications XI, S.E. Gryning and N. Chaumerliac eds., Plenum Press, New York, 22, in press.

    Google Scholar 

  • Kendall M. and Stuart A., The advanced theory of statistics, MacMillan, New York (1977).

    Google Scholar 

  • Luhar A.K., and Britter R.E., A random walk model for dispersion in inhomogeneous turbulence in a convective boundary layer, Atmospheric Environment, 23, 1191–1924 (1989).

    Google Scholar 

  • Manzi G., Bnisasca G., Morselli M.G., Tinarelli G., Indagine generale per lo studio pluridisciplinare del deperimento del pino silvestre ed altre specie botaniche in Val D’Aosta, simulazione della dispcrsione in atmosfcra degli inquinanti emessi dal traffico veicolare e dal riscaldamento, ENEL/CRAM report 1998-0022 (1998).

    Google Scholar 

  • Nanni A., Riva M., Tinarelli G., Bnisasca G., Particle model simulation of pollutants dispersion from a line source in complex terrain, The Science of the Total Environment, 189–190, 301-309 (1996)

    Google Scholar 

  • Rodean H.C., Notes on the Langcvin model for turbulent diffusion of “marked” particles, UCRL-ID-115869 Report of Lawrence Livermore National Laboratory (1994).

    Google Scholar 

  • Thomson D.J., Random walk modelling of diffusion in inhomogeneous turbulence. Quart. J. Roy. Meteor. Soc, 110, 1107–1120 (1984).

    Article  Google Scholar 

  • Thomson D.J., Criteria for the selection of stochastic models of particle trajectories in turbulent flows. J. Fluid Mech, 180, 529–556 (1987).

    Article  CAS  Google Scholar 

  • Tinarelli G., Anfossi D., Brusasca G., Ferrero E., Giostra U., Morselli M.G., Moussafir J. Tampieri F., Trombetti F., Lagrangian particle simulation of tracer dispersion in the lee of a schematic two-dimensional hill, Journal of Applied Meteorology, 33, 744–756 (1994).

    Article  Google Scholar 

  • Trini Castelli S., Anfossi D., Intercomparison of 3D turbulence parametrizations for dispersion models in complex terrain derived from a circulation model, II Nuovo Cimento C, 20, 287–313 (1997).

    Google Scholar 

  • Weil J.C., A diagnosis of the asymmetry in top-down and bottom-up diffusion using a Lagrangian stochastic model, J. Atmos. Sci, 47, 501–515 (1990).

    Article  Google Scholar 

  • Wilson J.D. and Flesch T.K., Flow boundaries in random-flight dispersion models: enforcing the well-mixed condition.. Journal of Applied Meteorology, 32, 1695–1707 (1993).

    Article  Google Scholar 

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Tinarelli, G., Anfossi, D., Trini Castelli, S., Bider, M., Ferrero, E. (2000). A New High Performance Version of the Lagrangian Particle Dispersion Model Spray, Some Case Studies. In: Gryning, SE., Batchvarova, E. (eds) Air Pollution Modeling and Its Application XIII. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4153-0_51

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  • DOI: https://doi.org/10.1007/978-1-4615-4153-0_51

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6863-2

  • Online ISBN: 978-1-4615-4153-0

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