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On the benefits of using multivariate analysis in mass spectrometric studies of combustion-generated aerosols

D. Duca; C. Irimiea; A. Faccinetto; J. A. Noble; M. Vojkovic; Y. Carpentier; I. K. Ortega; C. Pirim; C. Focsa


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            <foaf:name>Univ. Lille, CNRS, UMR 8523, PhLAM – Laboratoire de Physique des Lasers Atomes et Molécules, F-59000 Lille, France</foaf:name>
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    <dct:title>On the benefits of using multivariate analysis in mass spectrometric studies of combustion-generated aerosols</dct:title>
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    <dct:description>&lt;p&gt;The intricate chemistry of the carbonaceous particle surface layer (which drives their&amp;nbsp;reactivity, environmental and health impacts) results in complex mass spectra. In this&amp;nbsp;respect, detailed molecular-level analysis of combustion emissions may be challenging&amp;nbsp;even with high-resolution mass spectrometry. Building on a recently proposed&amp;nbsp;comprehensive methodology (encompassing all stages from sampling to data&amp;nbsp;reduction), we propose herein a comparative analysis of soot particles produced by&amp;nbsp;three different sources: a miniCAST standard generator, a laboratory diffusion flame and&amp;nbsp;a single cylinder internal combustion engine. The surface composition is probed by&amp;nbsp;either laser or secondary ion mass spectrometry. Two examples of multivariate analysis,&amp;nbsp;Principal component analysis and hierarchical clustering analysis proved their efficiency&amp;nbsp;in both identifying general trends and evidencing subtle differences that otherwise&amp;nbsp;would remain unnoticed in the plethora of data generated during mass spectrometric&amp;nbsp;analyses. Chemical information extracted from these multivariate statistical procedures&amp;nbsp;contributes to a better understanding of fundamental combustion processes and also&amp;nbsp;opens to practical applications such as the tracing of engine emissions.&lt;/p&gt;</dct:description>
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