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I introduce a general, Bayesian method for modelling univariate time series data assumed to be drawn from a continuous, stochastic process. The method accommodates arbitrary temporal sampling, and tak...
The stochastic fields method for turbulent reacting flows has been applied to the issue of sub-grid scale emission heterogeneity in a mesoscale model. This method is a solution technique for the proba...
In this study we introduce a comparison method for footprint model results by evaluating the performance of conventional Lagrangian stochastic (LS) footprint models that use parameterised flow field c...
The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method. The stochastic algorithm of Gillespie (1976) for chemical reactions in the formulation propos...
A Lagrangian Stochastic Model for the two-particles dispersion, aiming at simulating the pollutant concentration fluctuations, is presented. Three model versions (1-D, 2-D and 3-D) are tested. Firstl...

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