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.

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

PIETROGRANDE, Maria Chiara;MERCURIALI, Mattia;BACCO, Dimitri
2008

Abstract

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.
9781845641276
aerosol chemical composition; homologous series; GC-MS analysis; signal processing; multicomponent mixtures
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1378737
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