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The authors present a Cellular Automaton (CA) model designed to simulate how wind transports and deposits pollen. The model uses a 2D lattice to track pollen through three states: releasable, air-borne, and deposited. It incorporates stochastic processes for pollen release, transport (including turbulence and gusts), and 'sticking' probabilities for deposition. The authors demonstrate that this CA approach provides a better fit for experimental pollen deposition data than traditional exponential decay models and can reproduce complex patterns like humps or irregular declines. The paper also validates the model by showing it can replicate the Gaussian diffusion patterns predicted by partial differential equations for a thin line of pollen moving in a uniform wind.