Skip to main content
SpringerLink
Log in

Comprehensive Air Pollution Studies with the Unified Danish Eulerian Model

  • Conference paper
Parallel Processing and Applied Mathematics (PPAM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3019))

  • 544 Accesses

Abstract

Air pollution, especially the reduction of the air pollution to some acceptable levels, is a highly relevant environmental problem, which is becoming more and more important. This problem can successfully be studied only when high-resolution comprehensive mathematical models are developed and used on a routinely basis. However, such models are very time-consuming, even when modern high-speed computers are available. The models need a great amount of input data (meteorological, chemical and emission data). Furthermore, the models are producing huge files of output data, which have to be stored for future uses (for visualization and animation of the results). Finally, huge sets of measurement data (normally taken at many stations located in different countries) have to be used in the efforts to validate the model results. The necessity to handle efficiently large-scale air pollution models in order to be able to resolves a series of important environmental tasks is discussed in this paper. The need for parallel runs is emphasized. The particular model used is the Unified Danish Eulerian Model (UNI-DEM), but most of the results can also be applied when other large-scale models are used. The use of UNI-DEM in some comprehensive air pollution studies is discussed in the end of the paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexandrov, V., Sameh, A., Siddique, Y., Zlatev, Z.: Numerical integration of chemical ODE problems arising in air pollution models. Environmental Modelling and Assessment 2, 365–377 (1997)

    Article  Google Scholar 

  2. Ambelas Skjøth, C., Bastrup-Birk, A., Brandt, J., Zlatev, Z.: Studying variations of pollution levels in a given region of Europe during a long time-period. Systems Analysis Modelling Simulation 37, 297–311 (2000)

    Google Scholar 

  3. Bastrup-Birk, A., Brandt, J., Uria, I., Zlatev, Z.: Studying cumulative ozone exposures in Europe during a seven-year period. Journal of Geophysical Research 102, 23917–23935 (1997)

    Article  Google Scholar 

  4. Bott, A.: A positive definite advection scheme obtained by non-linear renormalization of the advective fluxes. Monthly Weather Review 117, 1006–1015 (1989)

    Article  Google Scholar 

  5. Brenan, K., Campbell, S., Petzold, L.: Numerical solution of initial value problems in differential-algebraic equations. SIAM, Philadelphia (1996)

    MATH  Google Scholar 

  6. Brost, R.A.: The sensitivity to input parameters of atmospheric concentrations simulated by a regional chemical model. Journal of Geophysical Research 93, 2371–2387 (1988)

    Article  Google Scholar 

  7. Crowley, W.P.: Numerical advection experiments. Monthly Weather Review 96, 1–11 (1968)

    Article  Google Scholar 

  8. Deuflhard, P.: Recent progress in extrapolation methods for ordinary differential equations. SIAM Review 27, 505–535 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  9. Dimov, I., Farago, I., Havasi, A., Zlatev, Z.: L-Commutativity of the operators in splitting methods for air pollution models. Annales Univ. Sci. Budapest 44, 129–150 (2001)

    MATH  MathSciNet  Google Scholar 

  10. Djouad, R., Sportisse, B.: Solving reduced chemical models in air pollution modelling. Applied Numerical Mathematics 40, 49–61 (2003)

    Article  MathSciNet  Google Scholar 

  11. Georgiev, K., Zlatev, Z.: Parallel Sparse Matrix Algorithms for Air Pollution Models. Parallel and Distributed Computing Practices 2, 429–442 (1999)

    Google Scholar 

  12. Gery, M.W., Whitten, G.Z., Killus, J.P., Dodge, M.C.: A photochemical kinetics mechanism for urban and regional computer modeling. Journal of Geophysical Research 94, 12925–12956 (1989)

    Article  Google Scholar 

  13. Gropp, W., Lusk, E., Skjellum, A.: Using MPI: Portable programming with the message passing interface. MIT Press, Cambridge (1994)

    Google Scholar 

  14. Havasi, A., Zlatev, Z.: Trends of Hungarian air pollution levels on a long time-scale. Atmospheric Environment 36, 4145–4156 (2002)

    Article  Google Scholar 

  15. Hesstvedt, E., Hov, Ø., Isaksen, I.A.: Quasi-steady-state approximations in air pollution modelling: comparison of two numerical schemes for oxidant prediction. International Journal of Chemical Kinetics 10, 971–994 (1978)

    Article  Google Scholar 

  16. Hov, Ø., Zlatev, Z., Berkowicz, R., Eliassen, A., Prahm, L.P.: Comparison of numerical techniques for use in air pollution models with non-linear chemical reactions. Atmospheric Environment 23, 967–983 (1988)

    Google Scholar 

  17. Hunsdorfer, W., Koren, B., van Loon, M., Verwer, J.G.: A positive finite difference advection scheme. J. Comput. Phys. 117, 35–46 (1995)

    Article  MathSciNet  Google Scholar 

  18. Lambert, J.D.: Numerical methods for ordinary differential equations. Wiley, New York (1991)

    Google Scholar 

  19. Lancer, D., Verwer, J.G.: Analysis of operators splitting for advectiondiffusion- reaction problems in air pollution modelling. J. Comput. Appl. Math. 111, 201–216 (1999)

    Article  MathSciNet  Google Scholar 

  20. van Loon, M.: Testing interpolation and filtering techniques in connection with a semi-Lagrangian method. Atmospheric Environment 27A, 2351–2364 (1993)

    Google Scholar 

  21. Marchuk, G.I.: Mathematical modeling for the problem of the environment. Studies in Mathematics and Applications, vol. (16). North-Holland, Amsterdam (1985)

    Google Scholar 

  22. McRae, G.J., Goodin, W.R., Seinfeld, J.H.: Numerical solution of the atmospheric diffusion equations for chemically reacting flows. Journal of Computational Physics 45, 1–42 (1984)

    Article  MathSciNet  Google Scholar 

  23. Molenkampf, C.R.: Accuracy of finite-difference methods applied to the advection equation. Journal of Applied Meteorology 7, 160–167 (1968)

    Article  Google Scholar 

  24. Owczarz, W., Zlatev, Z.: Running a large air pollution model on an IBM SMP computer. International Journal of Computer Research 10(4), 321–330 (2001)

    Google Scholar 

  25. Owczarz, W., Zlatev, Z.: Parallel matrix computations in air pollution modelling. Parallel Computing 28, 355–368 (2002)

    Article  MATH  Google Scholar 

  26. Pepper, D.W., Baker, A.J.: A simple one-dimensional finite element algorithm with multidimensional capabilities. Numerical Heath Transfer 3, 81–95 (1979)

    Google Scholar 

  27. Pepper, D.W., Kern, C.D., Long Jr., P.E.: Modelling the dispersion of atmospheric pollution using cubic splines and chapeau functions. Atmospheric Environment 13, 223–237 (1979)

    Article  Google Scholar 

  28. Shampine, L.F., Reichelt, M.W., Kierzenka, J.A.: Solving Index-1 DAEs in MATLAB and Simulink. SIAM Rev. 41, 538–552 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  29. Verwer, J.G., van Loon, M.: An evaluation of explicit pseudo-steady state approximation for stiff ODE systems from chemical kinetics. J. Comp. Phys. 113, 347–352 (1996)

    Google Scholar 

  30. Verwer, J.G., Simpson, D.: Explicit methods for stiff ODE’s from atmospheric chemistry. Appl. Numer. Math. 18, 413–430 (1995)

    Article  MATH  Google Scholar 

  31. WEB-site for OPEN MP tools (1999), http://www.openmp.org

  32. WEB-site of the Danish Centre for Scientific Computing at the Technical University of Denmark, Sun High Performance Computing Systems (2002), http://www.hpc.dtu.dk

  33. Zlatev, Z.: Application of predictor-corrector schemes with several correctors in solving air pollution problems. BIT 24, 700–715 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  34. Zlatev, Z.: Computer treatment of large air pollution models. Kluwer Academic Publishers, Dordrecht (1995)

    Google Scholar 

  35. Zlatev, Z.: Partitioning ODE systems with an application to air pollution models. Computers and Mathematics with Applications 42, 817–832 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  36. Zlatev, Z.: Massive data set issues in air pollution modelling. In: Abello, J., Pardalos, P.M., Resende, M.G.C. (eds.) Handbook on Massive Data Sets, pp. 1169–1220. Kluwer Academic Publishers, Dordrecht (2002)

    Google Scholar 

  37. Zlatev, Z., Christensen, J., Eliassen, A.: Studying high ozone concentrations by using the Danish Eulerian Model. Atmospheric Environment 27A, 845–865 (1993)

    Google Scholar 

  38. Zlatev, Z., Christensen, J., Hov, Ø.: An Eulerian air pollution model for Europe with nonlinear chemistry. Journal of Atmospheric Chemistry 15, 1–37 (1992)

    Article  Google Scholar 

  39. Zlatev, Z., Dimov, I., Georgiev, K.: Studying long-range transport of air pollutants. Computational Science and Engineering 1(3), 45–52 (1994)

    Article  Google Scholar 

  40. Zlatev, Z., Dimov, I., Ostromsky, T., Geernaert, G., Tzvetanov, I., Bastrup-Birk, A.: Calculating losses of crops in Denmark caused by high ozone levels. Environmental Modelling and Assessment 6, 35–55 (2001)

    Article  Google Scholar 

  41. Zlatev, Z., Fenger, J., Mortensen, L.: Relationships between emission sources and excess ozone concentrations. Computers and Mathematics with Applications 32(11), 101–123 (1996)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Environmental Research Institute, Frederiksborgvej 399, P. O. Box 358, DK-4000, Roskilde, Denmark

    Zahari Zlatev

Authors
  1. Zahari Zlatev
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computational and Information Sciences, Czestochowa University of Technology,  

    Roman Wyrzykowski

  2. Computer Science Department, University of Tennessee, TN 37996-3450, Knoxville, USA

    Jack Dongarra

  3. Systems Research Institute, Polish Academy of Science, Warsaw, Poland

    Marcin Paprzycki

  4. Informatics & Mathematical Modeling, Technical University of Denmark, DK-2800, Lyngby, Denmark

    Jerzy Waśniewski

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zlatev, Z. (2004). Comprehensive Air Pollution Studies with the Unified Danish Eulerian Model. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2003. Lecture Notes in Computer Science, vol 3019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24669-5_145

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24669-5_145

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21946-0

  • Online ISBN: 978-3-540-24669-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation