Developing an odour emission factor for an oil refinery plant using reverse dispersion modeling

Abstract

Odour emission factors (OEFs) for oil refineries are useful data for estimating odour emission rates (OERs) of different odour emission sources at oil refineries and developing odour emission inventories with lower cost and time than direct sampling and measurement method. The conventional direct source measurement followed by olfactometry sometimes faces challenges due to access issues and the presence of fugitive emissions for which determining emission rates is difficult. To address these issues, applying reverse odour dispersion modeling could be an appropriate alternative method in estimating OERs of oil refineries and developing OEFs; however, very limited research has been conducted and the level of their accuracy and reliability has not been well investigated. This study obtained OEFs for different sources of a conventional oil refinery plant in Canada using odour reverse dispersion modeling technique with AERMOD, a US EPA regulatory dispersion model. The results showed that the main odour sources at the oil refinery are tall stacks with the share of 99% of odour emissions while passive and fugitive emissions contribute to 1% of the odour emissions of the refinery. Results also demonstrated that the reverse odour dispersion modeling by AERMOD is an appropriate method of estimating OERs as the results of this study are within the ranges reported by previous similar research. Using reverse modeling, a total OER of 1,527,471ou/s was found for the entire oil refinery leading to an OEF of 910,162 ou/barrel which can be used by conventional oil refineries to estimate their odour emission inventories according to their capacity.