Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen

Abstract A statistical model for predicting daily mean pollen concentrations during the flowering season is constructed and its parameterization and application to birch pollen in Riga (Latvia) are discussed. The model involves several steps of transformations of both meteorological data and pollen observations, aiming at a normally distributed homogeneous stationary dataset with linearized dependencies between the transformed meteorological predictors and pollen concentrations. The data transformation includes normalization of daily mean birch pollen concentrations, a switch of the independent axis from time to heat sum, a projection of governing parameters to pollen concentrations, and a …