Skip to main content

Variance-Based Sensitivity Analysis of the Unified Danish Eulerian Model According to Variations of Chemical Rates

  • Conference paper
Numerical Analysis and Its Applications (NAA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8236))

Included in the following conference series:

Abstract

A special computational technology for sensitivity analysis of ozone concentrations according to variations of rates of chemical reactions is developed. It allows us to study a larger number of reactions than we have considered in our previous study. The reactions are taken from the standardized scheme for air-pollution chemistry CBM-IV. A number of numerical experiments with a large-scale air pollution model (Unified Danish Eulerian Model, UNI-DEM) have been carried out to compute Sobol sensitivity measures. The sensitivity study has been done for the areas of four European cities (Genova, Milan, Manchester, and Edinburgh) with different geographical locations.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Dimov, I., Georgieva, R.: Monte Carlo Adaptive Technique for Sensitivity Analysis of a Large-Scale Air Pollution Model. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2009. LNCS, vol. 5910, pp. 387–394. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Dimov, I.T., Georgieva, R., Ivanovska, I., Ostromsky, T., Zlatev, Z.: Studying the Sensitivity of Pollutants’ Concentrations Caused by Variations of Chemical Rates. J. Comput. Appl. Math. 235, 391–402 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  3. Dimov, I.T., Georgieva, R., Ostromsky, T.: Monte Carlo Sensitivity Analysis of an Eulerian Large-scale Air Pollution Model. Reliability Engineering & System Safety 107, 23–28 (2012), doi:10.1016/j.ress.2011.06.007.

    Article  Google Scholar 

  4. Ostromsky, T., Dimov, I.T., Georgieva, R., Zlatev, Z.: Air pollution modelling, sensitivity analysis and parallel implementation. International Journal of Environment and Pollution 46(1/2), 83–96 (2011)

    Article  Google Scholar 

  5. Ostromsky, T., Dimov, I., Georgieva, R., Zlatev, Z.: Parallel Computation of Sensitivity Analysis Data for the Danish Eulerian Model. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2011. LNCS, vol. 7116, pp. 307–315. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Ostromsky, T., Dimov, I.T., Marinov, P., Georgieva, R., Zlatev, Z.: Advanced sensitivity analysis of the Danish Eulerian Model in parallel and grid environment. In: Proc. Third International Conference AMiTaNS 2011, AIP Conf. Proceedings, Albena Bulgaria, June 20-25, vol. 1404, pp. 225–232 (2011), AIP Conf. Proceedings

    Google Scholar 

  7. Saltelli, S.: Making best use of model valuations to compute sensitivity indices. Computer Physics Communications 145, 280–297 (2002)

    Article  MATH  Google Scholar 

  8. Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S.: Global Sensitivity Analysis. The Primer. John Wiley & Sons Ltd. (2008) ISBN: 978-0-470-05997-5

    Google Scholar 

  9. Sobol, I.M.: Sensitivity estimates for nonlinear mathematical models. Mathematical Modeling and Computational Experiment 1, 407–414 (1993)

    MathSciNet  MATH  Google Scholar 

  10. Sobol, I.M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation 55(1-3), 271–280 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  11. Sobol, I.M., Tarantola, S., Gatelli, D., Kucherenko, S., Mauntz, W.: Estimating the approximation error when fixing unessential factors in global sensitivity analysis. Reliability Engineering and System Safety 92, 957–960 (2007)

    Article  Google Scholar 

  12. Sobol, I., Myshetskaya, E.: Monte Carlo Estimators for Small Sensitivity Indices. Monte Carlo Methods and Applications 13(5-6), 455–465 (2007)

    MathSciNet  MATH  Google Scholar 

  13. Zlatev, Z.: Computer Treatment of Large Air Pollution Models. KLUWER Academic Publishers, Dorsrecht (1995)

    Book  Google Scholar 

  14. Zlatev, Z., Dimov, I.: Computational and Numerical Challenges in Environmental Modelling. Elsevier, Amsterdam (2006)

    Google Scholar 

  15. http://www.wolfram.com/mathematica/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dimov, I., Georgieva, R., Ostromsky, T., Zlatev, Z. (2013). Variance-Based Sensitivity Analysis of the Unified Danish Eulerian Model According to Variations of Chemical Rates. In: Dimov, I., Faragó, I., Vulkov, L. (eds) Numerical Analysis and Its Applications. NAA 2012. Lecture Notes in Computer Science, vol 8236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41515-9_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41515-9_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41514-2

  • Online ISBN: 978-3-642-41515-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics