Abstract
Smoke dispersion prediction systems are becoming increasingly valuable tools in smoke management. Numerical models for dispersion and chemical transport, also known as air quality models, can be used to investigate the fire plume evolution and the smoke impacts (e.g. concentration, temperature). However, all prediction systems include some level of uncertainty, which may occur from the meteorological inputs, diffusion assumptions, plume dynamics, or emission production.
Uncertainty analysis enables to avoid as much as possible bad decisions that may have a large impact in a field such as safety. In this study, we are interested in the uncertainty propagation related to NO2 atmospheric dispersion resulting from a crude oil tank fire. Uncertainties were defined a priori in each of the following input parameters: wind speed, pollutant emission rate and its diffusivity coefficient. For that purpose, a Monte Carlo approach has been used.
