A Global-Through Urban Scale Nested Air Pollution Modelling System (MM5-CMAQ): Application to Madrid Area

  • R. San José
  • J. L. Pérez
  • J.I. Peña
  • I. Salas
  • R.M. González
Chapter

Summary

We have implemented the standalone version of the Community Multiscale Air Quality Modelling System in a DIGITAL COMPAQ XP 1000/1GB RAM platform and the MM5 mesoscale meteorological model over a LINUX PC AMD 1 Ghz/128 Mb RAM. We have run a mother domain and three nesting levels up to 4 km grid cell spatial resolution over the Madrid domain. We have simulated 17–18, April, 2001 as spin-off period and 19–23, April, 2001 as experimental period and we have run OPANA model over de same period of time. We have compared both results with some monitoring stations. Results with MM5-.CMAQ seems to be much more realistic which is associated to the proper boundary conditions obtained from nesting levels 2-1 and mother domain concentrations. Further experiments are necessary over different periods of the year and operational version under automatic mode over web will be deployed in the next months to assure the operational mode of the system.

Keywords

Emission Inventory Nest Level Piecewise Parabolic Method Mother Domain Madrid Area 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Carmichael G.R., Peters L.K. and Saylor R.D. (1991). The STEM-II regional scale acid deposition and photochemical oxidant model-1. An overview of model development and applications. Atmospheric Environment 25A, 2077–2090.Google Scholar
  2. Chen, F., and J. Dudhia, 2001: Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569–585.Google Scholar
  3. Colella P. and P.R. Woodward (1984): The piecewise parabolic method (PPM) for gas-dynamical simulations. J. Comp. Phys 54, 174–201.Google Scholar
  4. Flassak T. and Moussiopoulos N. (1989) Simulation of the sea breeze in Athens with an efficient non-hydrostatic mesoscale model. In: Man and his ecosystem., Vol. 3, Eds. L.J. Brasser and W.C. Mulder. Elsevier. Amsterdam. 189–195.Google Scholar
  5. Ge, Xiaozhen, Li, Feng, and Ge, Ming, 1997: Numerical analysis and case experiment for forecasting capability by using high accuracy moisture advectional algorithm. Meteorology and Atmospheric Physics, Vienna, Austria, 63(3–4), 131–148.Google Scholar
  6. Jacobson M.Z. and Turco R.P. (1994) SMVGEAR: A sparse-matrix vectorized gear code for atmospheric models. Atmospheric Environment, 28, 273–284.CrossRefGoogle Scholar
  7. McRae G. J. And Seinfeld J.H. (1983) Development of a second generation mathematical model for urban air pollution. II. Evaluation of model performance. Atmospheric Environment, 17, 501–522.Google Scholar
  8. Peters L.K., Berkowitz C.M., Carmichael G.R., Easter R.C., Fairweather G., Ghan S.J., Hales J.M., Leung L.R., Pennell W.R., Potra F.A., Saylor R.D. and Tsang T.T. (1995) The current state and future direction of Eulerian models in simulating the tropospheric chemistry and transport of chemical species: A review. Atmospheric Environment, 29, 2, 189–222.Google Scholar
  9. San José R., Rodríguez L. And Moreno J. (1994). An application of the “Big Leaf” deposition approach to the mesoscale meteorological transport and chemical modelling in a three dimensional context. Proceedings of the EUROTRAC Symposium. Eds. Borrel P.M., Borrell P., Cvitas T. and Seiler W. 620.Google Scholar
  10. San José R., Rodríguez M.A., Pelechano A. And González R.M. (1999) Sensitivity studies of dry deposition fluxes. In Measuring and Modelling Investigation of Environmental Proceses. WIT press Computational Mechanics Publications. ISBN: 1-853125660. Ed. R. San José. 205–246.Google Scholar
  11. Stensrud, D. J., J.-W. Bao, and T. T. Warner, 2000: Using initial condition and model physics perturbations in short-range ensemble simulations of mesoscale convective systems. Mon. Wea. Rev., 128, 2077–2107.Google Scholar
  12. Venkatram A. and Karamachandani P. K. (1989). The ADOM II scavenging module: incorporation of improved cumulus cloud module. ENSR Doc. No. 0780-004-205.Google Scholar
  13. Warner, T. T. and H. M. Hsu, 2000: Nested-model simulation of moist convection: The impact of coarse-grid parameterized convection on fine-grid resolved convection through lateral-boundary-condition effects. Mon. Wea. Rev., 128, 2211–2231.CrossRefGoogle Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • R. San José
  • J. L. Pérez
  • J.I. Peña
  • I. Salas
    • 1
    • 2
  • R.M. González
    • 3
  1. 1.Environmental Software and modelling Group, Computer Science SchoolTechnical University of Madrid (UPM)(Spain)
  2. 2.Campus de MontegancedoMadrid(Spain)
  3. 3.Department of Geophysics and Meteorology, Faculty of PhysicsUniversidad Complutense de Madrid(Spain)

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