Data handling of complex GC-MS signals to characterize homologous series as organic source tracers in atmospheric aerosols

A description is given of a chemometric approach used to extract information on the characteristics of n-alkane and n-alkanoic acid homologous series as useful markers for PM source identification and differentiation. The key parameters of the homologous series -- number of terms and Carbon Preference Index -- are directly estimated by the Autocovariance Function (EACVF) computed on the acquired chromatogram. The homologous series properties  relevant as chemical signature of specific input sources  can be efficiently extracted from the complex GC-MS signal thus reducing the labour, time consumption and the subjectivity introduced by human intervention.