Emission rate estimation through data assimilation of gamma dose measurements in a Lagrangian atmospheric dispersion model.

This paper presents an efficient algorithm for estimating the unknown emission rate of radionuclides in the atmosphere following a nuclear accident. The algorithm is based on assimilation of gamma dose rate measured data in a Lagrangian atmospheric dispersion model. Such models are used in the framework of nuclear emergency response systems (ERSs). It is shown that the algorithm is applicable in both deterministic and stochastic modes of operation of the dispersion model. The method is evaluated by computational simulations of a 3-d field experiment on atmospheric dispersion of ⁴¹Ar emitted routinely from a research reactor. Available measurements of fluence rate (photons flux) in air are assimilated in the Lagrangian dispersion model DIPCOT and the ⁴¹Ar emission rate is estimated. The statistical analysis shows that the model-calculated emission rates agree well with the real ones. In addition the model-predicted fluence rates at the locations of the sensors, which were not used in the data assimilation procedure are in better agreement with the measurements. The first evaluation results of the method presented in this study show that the method performs satisfactorily and therefore it is applicable in nuclear ERSs provided that more comprehensive validation studies will be performed.