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Long-term collection of data, recorded at several air monitoring stations located in Central Poland, was analyzed. The main objective of the analysis was to choose optimum modelling methods for concentration of specified air pollutants. For this purpose accuracies of various groups of autonomous models were compared. Prediction of any air pollutants was performed using three different modelling methods. The modelled value was instantaneous concentration of specified pollutant. The models varied in the number and type of the explanatory variables and the modelling technique. It was presumed that there is a need for modelling the measurement gap, comprising a selected extract of the time series of a chosen pollutant. For successive cases in the gap, prediction errors of various methods of modelling were compared.

Approximation of imission level at air monitoring stations by means of autonomous neural models