Navigational expert systems are developed for two situations: instantaneous (puff) and continuous (plume) releases. Of the two the puff poses the greater challenge because it provides a moving target rather than quasi-steady concentration pattern. Thus, the navigational expert system must guide the UAV to an intercept for each pass through the puff rather than just sweeping across the contaminant field at multiple downwind distances as suffices with a plume. The navigation systems are tested in a virtual world consisting of a single fixed wind and concentration sensor, a UAV with wind and concentration sensing capability, a uniform wind at a significant fraction of the UAV airspeed, and a simple Gaussian dispersion model. The resulting concentration data is used to characterize the source strength and location by using a genetic algorithm to tune the parameters until the model output matches the observations. Tests conducted using randomized source locations indicate that these UAV navigation systems are sophisticated enough to successfully acquire the necessary concentration data in the majority of the cases. The success rate is greatly improved by using an ensemble of non-communicating UAVs and taking the median of the resulting source parameters. This process eliminates the outliers that result from occasional navigational failures.