Calculating gas emissions from open-pit mines using inverse dispersion modelling: A numerical evaluation using CALPUFF and CFD-LS

Abstract

Inverse Dispersion Modelling (IDM) establishes a relationship between an air pollutant concentration downstream of a source and the strength of an emission source by reliance on an air dispersion model. Thus, ideally measuring pollutant concentration downstream is sufficient to infer the emission source strength. However, the accuracy of IDM relies on the accuracy of the underlying air dispersion model. Diagnostic dispersion models face difficulty when applied to complex terrains of open-pit mines. To elucidate such difficulties and their causes, the diagnostic CALifornia PUFF (CALPUFF) model is compared to a Computational Fluid Dynamics-Lagrangian Stochastic (CFD-LS) model for quantifying the short-range dispersion of fugitive gases released from a synthetic open-pit mine. Two mine depths (100–500 m) and three thermal stability conditions (stable-neutral-unstable) are investigated. In all cases the surface concentration predicted by the two models are in disagreement, regardless of CALPUFF model setup. Overall, less than 30% of receptor points predict the concentration within a factor of two of CFD-LS simulations (FAC2 < 0.3). Model differences appear to be related to the internal algorithms of the CALPUFF model to predict the wind field appropriately. The results should caution practitioners considering diagnostic models for IDM analysis over complex terrain.