This work describes the application of a signal processing method to GC–MS chromatograms of PM10 and PM2.5 samples collected in rural and urban areas. The method is focused on the computation of the two relevant parameters nmax and CPI that can be directly estimated from the AutoCoVariance Function (ACVF) computed on the acquired chromatogram. The procedure makes it possible to extract usable information hidden in the chromatogram thus reducing the labour and time required and increasing the quality and objectivity of the results.
Source Apportionment for PM samples: a chemometric approach based on the AutoCoVariance Function computation for GC-MS data treatment and organic tracers identification
MERCURIALI, Mattia;PIETROGRANDE, Maria Chiara
2009
Abstract
This work describes the application of a signal processing method to GC–MS chromatograms of PM10 and PM2.5 samples collected in rural and urban areas. The method is focused on the computation of the two relevant parameters nmax and CPI that can be directly estimated from the AutoCoVariance Function (ACVF) computed on the acquired chromatogram. The procedure makes it possible to extract usable information hidden in the chromatogram thus reducing the labour and time required and increasing the quality and objectivity of the results.File in questo prodotto:
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