Improved Stochastic Lattice Methods for Large-Scale Air Pollution Model

In the current study, a large-scale air pollution model is adopted, focusing on the Sobol’ approach for sensitivity analysis. In this paper we will use the advanced stochastic approach based on component by component construction methods. Optimized algorithms based on lattice rules have been designed and implemented, while their performance has been compared to the best available stochastic approaches, applied for multidimensional sensitivity analysis. Numerical results show a significant improvement over the current stochastic methods. The obtained results would have an important multi-sided role in the area of air pollution modeling.