Abstract
The development of a Data Assimilation algorithm based on variational approach that allows estimation of source emission rate in Lagrangian particle/puff Atmospheric Dispersion Models for non-stationary (wind and source) conditions is presented. The one-dimensional tests including constant and variable in time source emission rate and wind velocity showed that methodology can be extended to take into account variable meteorological conditions. In the 2-dimensional atmospheric dispersion test cases the sensitivity of the developed method on the spatial density of the measurement network was evaluated and an optimal value for the parameter rmod (error of observations proportional to observed concentrations) was estimated.
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