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The objective of this project is to quantify and assess inherent uncertainties likely to arise during nuclear accidents involving near site atmospheric dispersion scenarios.
2 full scale dispersion experiments have been conducted appropriate for real time dispersion model evaluation and training. They consisted of atmospheric dispersion experiments over complex terrain in a Spanish valley site and an elevated puff diffusion experiment over flat terrain. During both, a mini light detection and ranging (LIDAR) system was used for fast and high resolution plume tracking measurements of the dispersion sceneries. Real time sequential data of plume dispersion was recorded for the compilation of a realistic diffusion database. Subsequently, plume profile statistics of important statistical quantities were established. Extensive meteorological mean and turbulence measurements were simultaneously taken during each experiment to provide extensive input data for the dispersion models to be evaluated and used for simulations.

In the course of the dispersion experiment over complex terrain, the atmospheric and diffusion processes were studied in order to: evaluate smoke and continous sulphur dioxide and sulphur fluoride releases from a 185 m tall power plant chimney; and study dispersion from a ground level source located on the floor of a valley surrounded by complex terrain. Also, 18 evaluation and training experiments using artifically generated smoke were performed and the detailed dispersion form various sites was measured with the LIDAR system. Detailed meteorological mean flow and turbulence measurements were made based on a 25 m high meteorological tower and measurements were made of the boundary layer profiles taken from a tethered balloon.

The 10 minute mean wind speed, the mean wind direction and the temperature all exhibit a strong diurnal variation with strong (8 to 10 m/s) nocturnal drainage flow running down the valley (from the north) and lasting until almost noon followed by a 5 to 6 hour period of much lighter southerly breeze up the valley. At approximately 1800 hours the wind turns back to nocturnal drainage, persisting wit h strong local winds for the next approximately 18 hours.

One application of backscatter light detection and ranging (LIDAR) systems is the observation of the disperison of aerosol plumes close to the earth surface. Estimation of the ground level concentration field of an inert pollutant downwind of a point source is often achieved by the Gaussian plume model and improvement with the Klett algorithm. This, however, is only correct if the LIDAR system signal consists only of single scattering. In dense aerosols there is always a more or less important contribution of multiphy scattered radiation to the signal. Theoretical studies of multiple scattering have therefore been carried out to extract the single scattering information from LIDAR signals both for monostratic (DLR microlidar) and bistatic (modified cloud ceilometer) configurations. A stochastic model has been developed for the theoretical prediction of LIDAR signals, including multiple scattering, and for the evaluation of actually measured LIDAR signals. This model has been expanded to calculations of signals from slabs of dense aerosols, as the slab geometry is especially appropriate for cloud and plume measurements.

Parallel to the theoretical work, a LIDAR system was constructed which is capable of detecting multiple scattering and depolarization simultaneously. It uses 2 different fields of view and, for each field of view, 2 orthogonal directions of linear polarization as depolarization and multiple scattering are closely related to each other. Flight test measurements were performed with the microlidar using all 4 channels. Although the data have not yet been evaluated, the correct performance seems established.
Our task is to perform and document full scale aerosol plume dispersion experiments over various terrain types and for a variety of different atmospheric conditions, including nonidealistic but indeed realistic dispersion events occurring during nonstationary and time-changing meteorology. The end product will consist of reference and validation data sets applicable as references for real time dispersion models and will include training and evaluation experiments suitable for real time uncertainty handling and online emergency training relevant for nuclear accidental releases.

Assisted by our German cooperators at DLR, we are conducting a series of full scale aerosol plume dispersion experiments at various sites, where, by use of LIDAR's, we obtain fast and high resolution plume tracking capabilities. Real time sequential data of plume dispersion, in the form of movies of instantaneous concentration profiles, provide the raw data for building a realistic diffusion database. From this we establish plume profile statistics of such statistical quantities as mean and mean-square concentration profiles of the horizontal and vertical plume spread, in addition to the entire concentration probability function for each experiment. Extensive meteorological mean and turbulence measurements are simultaneously taken during each experiment in order to provide extensive input data for the dispersion models to be evaluated and used for simulations. The contribution from our collaborators at DLR (Institute of Opto-electronics) is to provide scientific and technological support to this project reg rding processing and interpretation of the Lidar measurements of the plume concentrations.


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