Monte Carlo Adaptive Technique for Sensitivity Analysis of a Large-Scale Air Pollution Model

Variance-based sensitivity analysis has been performed for a study of input parameters contribution into output variability of a large-scale air pollution model — the Unified Danish Eulerian Model The problem of computing of numerical indicators of sensitivity — Sobol' global sensitivity indices leads to multidimensional integration Plain and Adaptive Monte Carlo techniques for numerical integration have been analysed and applied Numerical results for sensitivity of pollutants concentrations to chemical rates variability are presented.