Chow, F.K., Kosovic, B., and S.T. Chan. 2007. Source inversion for contaminant plume dispersion in urban environments using building-resolving simulations. Journal of Applied Meteorology and Climatology, in press.

Abstract

The ability to determine the source of a contaminant plume in urban environments is crucial for emergency response applications. Locating the source and determining its strength based on downwind concentration measurements, however, is complicated by the presence of buildings which can divert flow in unexpected directions. High-resolution flow simulations are now possible for predicting plume evolution in complex urban geometries, where contaminant dispersion is affected by the flow around individual buildings. Using Bayesian inference via stochastic sampling algorithms with a high-resolution CFD model, we can reconstruct an atmospheric release event to determine the plume source and release rate based on point measurements of concentration.

Event reconstruction algorithms are applied first for flow around a prototype isolated building (a cube), and then using observations and flow conditions from Oklahoma City during the Joint URBAN 2003 field campaign. Stochastic sampling methods (Markov Chain Monte Carlo) are used to extract likely source parameters, taking into consideration measurement and forward model errors. In all cases the steady-state flow field generated by a 3D Navier-Stokes finite-element code (FEM3MP) is used to drive thousands of forward dispersion simulations. To enhance computational performance in the inversion procedure, a reusable database of dispersion simulation results is created. We are able to successfully invert the dispersion problems to determine the source location and release rate to within narrow confidence intervals even with such complex geometries.

Our stochastic methodology is general and can be used for time-varying release rates and reactive flow conditions. The results of inversion indicate the probability of a source being found at a particular location with a particular release rate, thus inherently reflecting uncertainty in observed data or the lack of enough data in the shape and size of the probability distribution. A composite plume showing concentrations at the desired confidence level can also be constructed using the realizations from the reconstructed probability distribution. This can be used by emergency responders as a tool to determine the likelihood of concentration at a particular location being above or below a threshold value.