Diagnostic models of wind field and pollutant dispersion face difficulty when applied to complex terrain. Open-pit mines are an example of this difficult environment. To elucidate such difficulties, two models are developed and compared with one another. The first model is based on the prognostic Computational Fluid Dynamics-Lagrangian Stochastic (CFD-LS) paradigm, while the second model is based on the diagnostic CALifornia PUFF (CALPUFF) software. Two mine depths (100 [m] and 500 [m]) and three thermal stability conditions (unstable, neutral, and stable) are investigated using the two models. The CFD results showed that the skimming flow is only predicted under the neutral case, while more complex flow patterns emerge otherwise. Under the unstable case, the shallow and deep mines induce enhanced mixing downstream of the mine, resulting in substantial vertical plume transport and dilution of the pollutants released from the mine. Under the stable case, the plume from the shallow mine is restricted to the surface layer downstream of the mine. However, under the stable case, the plume from the deep mine rises into the substantial portion of the boundary layer due to the formation of a standing wave over and inside the mine. The results suggest that the CFD model can predict transport phenomena over open-pit mines reliably, so that the meteorological fields may be incorporated in operational models to improve the accuracy of their predictions. On the other hand, the CALPUFF model generally deviates from CFD-LS predictions, and the disagreement between the two models is the greatest when modelling the deep mine, under neutral/stable conditions, or when its solutions are considered close to the mine edge. Among many reasons, the variances appear to be related to the internal algorithms of the CALPUFF model to predict the wind eld structure appropriately. The results should caution practitioners considering diagnostic models for application over complex terrain, with opportunities to investigate such discrepancies at greater detail in follow up research.

This paper reports on an investigation of the adequacy of Computational fluid dynamics (CFD), using a standard Reynolds Averaged Navier Stokes (RANS) model, for predicting dispersion of neutrally buoyant gas in a large indoor space. We used CFD to predict pollutant (dye) concentration profiles in a water filled scale model of an atrium with a continuous pollutant source. Predictions from the RANS formulation are comparable to an ensemble average of independent identical experiments. Model results were compared to pollutant concentration data in a horizontal plane from experiments in a scale model atrium. Predictions were made for steady-state (fully developed) and transient (developing) pollutant concentrations. Agreement between CFD predictions and ensemble averaged experimental measurements is quantified using the ratios of CFD-predicted and experimentally measured dye concentration at a large number of points in the measurement plane. Agreement is considered good if these ratios fall between 0.5 and 2.0 at all points in the plane. The standard k-epsilon two equation turbulence model obtains this level of agreement and predicts pollutant arrival time to the measurement plane within a few seconds. These results suggest that this modeling approach is adequate for predicting isothermal pollutant transport in a large room with simple geometry.