Bayesian Inference for Source Determination with Applications to a Complex Urban Environment


  1. Keats, A.
  2. Yee, E.
  3. Lien, F.-S.
Corporate Authors
Defence R&D Canada - Suffield, Ralston ALTA (CAN);Waterloo Univ, Waterloo ONT (CAN) Dept of Applied Mathematics and Mechanical Engineering
The problem of determining the source of an emission from the limited information provided by a finite and noisy set of concentration measurements obtained from real-time sensors is an ill-posed inverse problem. In general, this problem cannot be solved uniquely without additional information. A Bayesian probabilistic inferential framework, which provides a natural means for incorporating both errors (model and observational) and prior (additional) information about the source, is presented. Here, Bayesian inference is applied to find the posterior probability density function of the source parameters (location and strength) given a set of concentration measurements. It is shown how the source-receptor relationship required in the determination of the likelihood function can be efficiently calculated using the adjoint of the transport equation for the scalar concentration. The posterior distribution of the source parameters is sampled using a Markov chain Monte Carlo method. The inverse source determination method is validated against real data sets acquired in a highly disturbed flow field in an urban environment. The data sets used to validate the proposed methodology include a water-channel simulation of the near-field dispersion of contaminant plumes in a large array of building-like obstacles (Mock Urban Setting Trial) and a full-scale field experiment (Joint Urban 2003) in Oklahoma City. These two examples demonstrate the utility of the proposed approach for inverse sou
Adjoint equations;Bayesian inference;Dispersion modelling;Source determination;Urban flows
Report Number
DRDC-SUFFIELD-SL-2006-126 — Scientific Literature
Date of publication
28 May 2006
Number of Pages
Reprinted from
Atmospheric Environment, Vol 41, 2007, p 465-479
Hardcopy;Document Image stored on Optical Disk

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