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 the 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.