Extracting information from complex chromatographic fingerprints for evaluation of organic air pollution
✍ Scribed by Carla Armanino; Michele Forina; Loretta Bonfanti; Mario Maspero
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 833 KB
- Volume
- 284
- Category
- Article
- ISSN
- 0003-2670
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✦ Synopsis
The gas chromatographic profiles of 47 samples of airborne particulate matter, obtained by flame ionization detection, were synchronized and quantified into variables by an automatic procedure, avoiding peak recognition and identification. Pattern recognition methods of principal components and clustering were used to extract information from the variables and seasonal similarities were established. Multivariate regression with the partial least squares method found predictive relationships between the profiles and other variables determined by different methods: extractable organic material, carbon preference index of the n-alkane homologous series (computed from gas chromatographic-mass spectrometric determinations) and mutagenicity. The predictive power was between 68% and 81%, and so the usefulness of the extracted information was verified; the profile obtained by flame ionization detection contains information related to the quality of air. The procedure is also suitable for different hinds of complex matrices, provided that synchronization is realized: it gives a first general knowledge of sample characteristics which may be used to address further analysis.