Estimation of local tracer gas concentration probability from minimum input data

Emergency response forces need to be prepared for making vitally important decisions in the possession of very few trustable information. Chemical plants using hazardous materials are usually monitored for accidental release, equipped with local wind sensor and some estimates are available for the potential source intensity. Concentration levels are expected to be forecasted from this minimum information in case of accident. Most fast response dispersion models rely on the Gaussian dispersion model, despite it being limited to small scale turbulence induced by surface shear. In this paper, data of multiple field experiments are brought to common platform and, based on the statistical investigation of this dataset, an atmospheric dispersion model is proposed, which allows for the reconstruction of the pointwise concentration statistics as functions of windward and lateral coordinates. The new statistical model may be used to predict the ground level concertation profile of given probability, with the limitations to near ground continuous sources localized on flat terrain at medium latitude. At least an order of magnitude higher lateral spread of the plume can be seen compared to standard Gaussian plumes and the profiles are tilted to the right reflecting the effects of large scale atmospheric turbulence and Coriolis effects.