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In this work a systematic procedure for multidimensional sensitivity analysis in the area of air pollution modeling by an optimized latin hypercube sampling has been done. The Unified Danish Eulerian Model (UNI-DEM) is used in our investigation, because this is one of the most advanced largescale mathematical models that describes adequately all physical and chemical processes. We study the sensitivity of concentration variations of some of the most dangerous air pollutants with respect to the anthropogenic emissions levels and with respect to some chemical reactions rates. The results obtained with an adaptive approach and latin hypercube sampling has been discussed.

Sensitivity Study of a Large-Scale Air Pollution Model by Using Optimized Stochastic Algorithm