Uncertainty propagation in puff-based dispersion models using polynomial chaos

A simple three-dimensional Gaussian puff-based dispersion model is designed to study the effect of uncertainties in the model parameters on the solution. A polynomial chaos approach to solve stochastic systems with parametric and initial uncertainties is described. The solution of the dispersion model is investigated numerically using this approach. The polynomial chaos solution is found to be an accurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.