Uncertainty and sensitivity analysis in code environmental model for risk assessments from industrial source complex

J. Carlos García-Díaz, J. M. Gozalvez-Zafrilla

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

The objectives of paper are the application of uncertainty and sensitivity analysis methods in atmospheric dispersion modeling to case study for predicting the dispersion of pollutants in the atmospheric environment. Gaussian Plume Model is used to study the impact of meteorology on the dispersion of emissions from industrial source complex. Quantitative uncertainty analysis has become a common component of risk assessments. Uncertainties were defined a priori in each of the following variables: wind speed, wind direction and pollutant emission rate. In order to get information about the uncertainty of computer code results, a number of code runs have to be performed using tolerance limits method. Monte Carlo method is used for propagating uncertainty across of code. Spearman rank correlation coefficient is used as sensitivity measure.

Original languageEnglish
Pages (from-to)7656-7657
Number of pages2
JournalProcedia - Social and Behavioral Sciences
Volume2
Issue number6
DOIs
StatePublished - 2010
Externally publishedYes
Event6th International Conference on Sensitivity Analysis of Model Output, SAMO 2010 - Milan, Italy
Duration: 19 Jul 201022 Jul 2010

Keywords

  • Gaussian Plume Model
  • Monte Carlo method
  • Pollutant
  • Sensitivity analysis
  • Uncertainty analysis

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