An Inexact Air Quality Model for Petroleum Pollutants Based on Techniques of Factorial Analysis and Stochastic Simulation

Abstract In this study, an inexact air quality modeling system is developed to predict the maximum ground level concentration (MGLC) and distance to MGLC (DMGLC) of gaseous pollutants from point sources in petroleum operations. The influence of uncertain parameters is evaluated through an integration of 2k factorial analysis and stochastic simulation. The results can provide useful information for risk assessment and decision analysis.