Preface. Acknowledgements. 1. Parallel algorithms for some optimization problems arising in air pollution modeling; J.L. Alonso, A.N. Alexandrov. 2. Modeling of global and regional transport and transformation of air pollutants; A.E. Aloyan. 3. Long-term calculations with large air pollution models; C. Ambelas, et al. 4. Parallel numerical simulation of air pollution in Southern Italy; G. Barone, et al. 5. Real time predictions of transport, dispersion and deposition from nuclear accidents; A. Bastrup-Birk, et al. 6. Mixing height in coastal areas - experimental results and modelling, A review; E. Batchvarova. 7. On some adaptive numerical methods for linear advection equations; R. Bochorishvili. 8. A parallel iterative scheme for solving the convection diffusion equation on distributed memory processors; L.A. Boukas, N.M. Missirlis. 9. Data Assimilation and HPCN-examples of the LOTOS model; P.J.H. Builtjes. 10. Computational challenges of modeling interactions between aerosol and gas phase processes in large scale air pollution models; G.R. Carmichael, et al. 11. ETEX: a European tracer experiment; observations, dispersion modelling and emergency response; H. van Dop, et al. 12. Parallel 4D-variational data assimilation for an Eulerian chemistry transport model; H. Elbern, et al. 13. Approaches for improving the numerical solution of the advection equation; M.V. Galperin. 14. Application of parallel algorithms in an air pollution model; K. Georgiev, Z. Zlatev. 15. Aerosol modelling within the EURAD Model System: Developments and applications; H. Hass, et al. 16. Calculation of ozone and other pollutants for summer 1996: The influence of lateral boundary concentrations on ozone levels'; J.E. Jonson, et al. 17. Atmospheric mechanisms of admixtures transfer; K.A. Karimov, R.D. Gainutdinova. 18. The varying scale modelling of air pollution transport; V.K. Kouznetsov, et al. 19. Deterioration on historic buildings due to air pollution and some difficulties during their restoration works; A.G. Kucukkaya. 20. Modelling of the long-term atmospheric transport of heavy metals over Plland; A Mazur. 21. Pollution transmission in the air; Cs. Mészáros, et al. 22. Bayesian heuristic approach (BHA) and applications to optimization of large scale discrete and continuous models; J. Mockus. 23. Nonlinear assignment problems; P.M. Pardalos, et al. 24. Some experiments in connection with neural and fuzzy modelling for air pollution problems; G.M. Sandulescu, M. Bistran. 25. Advanced operational air quality forecasting models for urban and regional environments in Europe: Madrid application; R. San José, et al. 26. Adaptive orthonormal systems; Bl. Sendov. 27. On some flux-type advection schemes for dispersion modelling application; D. Syrakov, M. Galperin. 28. A study of sulfur dioxide distribution over Ýstanbul, Turkey, and preliminary results of neural network analysis; M. Tayanç, A. Saral. 29. Krylov subspace methods for the solution of large systems of ODE's; P.G. Thomsen, N.H. Bjurstrøm. 30. The use of 3-D adapti
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The protection of the environment is one of the most important problems facing us today. Reliable and robust strategies for keeping pollution caused by harmful chemicals under safe levels have to be developed and used routinely. Large mathematical models, incorporating all important physical and chemical processes, can solve this task, but the computational burden is huge. The papers presented here describe some of the difficult problems that have to be solved during the development of large scale air pollution models, and different ways to solve them. The work involves combined research by specialists in the fields of environmental modelling, numerical analysis and scientific computing. Further, if models are to run in real time (which may be vital in the case of accidental hazardous releases), then new and efficient methods that harness the potential power of parallel supercomputers must be developed, so that actual computing speed starts to approach the maximum available performance. The articles are understandable by specialists in the field of air pollution modelling, as well as specialists in the many other related areas.
Dongarra is Distinguished Professor, Department of Computer Science, University of Tennessee, and Distinguished Scientist, Methematical Sciences Section, Oak Ridge National Laboratory.
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