Author(s)

W. Kaminski, J. Skrzypski & P. Strumillo

Abstract

The paper addresses the problem of optimum data dimensionality reduction in relation to analysis of weather factors and their influence on the recorded air pollution concentrations in urban areas. Eight weather parameters and two air pollution factors, namely concentrations of SOi and suspended particulate are considered in the study. Principal component analysis, is the method used for an optimum decorrelation and dimensionality reduction of the analysed weather factors. The amount of information removed from the data due to dimensionality reducti

Keywords