Ensemble-based simultaneous emission estimates and improved forecast of radioactive pollution from nuclear power plant accidents: application to ETEX tracer experiment. (April 2015) - Zhang, X.L.; Li, Q.B.; Su, G.F.; Yuan, M.Q.
Abstract: The accidental release of radioactive materials from nuclear power plant leads to radioactive pollution. We apply an augmented ensemble Kalman filter (EnKF) with a chemical transport model to jointly estimate the emissions of Perfluoromethylcyclohexane (PMCH), a tracer substitute for radionuclides, from a point source during the European Tracer Experiment, and to improve the forecast of its dispersion downwind. We perturb wind fields to account for meteorological uncertainties. We expand the state vector of PMCH concentrations through continuously adding an a priori emission rate for each succeeding assimilation cycle. We adopt a time-correlated red noise to simulate the temporal emission fluctuation. The improved EnKF system rapidly updates (and reduces) the excessively large initial first-guess emissions, thereby significantly improves subsequent forecasts ( r = 0.83, p < 0.001). It retrieves 94% of the total PMCH released and substantially reduces transport error (>80% average reduction of the normalized mean square error). Highlights: EnKF is augmented for estimating emission and improving dispersion forecast. The improved system retrieves 94% of the actual total tracer release in ETEX. The system substantially improves the 3-h forecast of the tracer dispersion. The method is robust and insensitive to the first-guess emissions. The meteorological uncertainties exert strong influence on the performance.