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Title

Direct compound specific isotope analysis (δ2H, δ13C) of biomass components using analytical pyrolysis (Py-CSIA).

AuthorsSan Emeterio, Layla M. ; Jiménez Morillo, N. T. ; Rosa Arranz, José M. de la ; González-Vila, Francisco Javier ; González-Pérez, José Antonio
Issue Date3-Jul-2019
PublisherSociedad Española de Cromatografía y Técnicas Afines
Citation1st Iberian Meeting in Separation Sciences & Mass Spectrometry. O19 pág. 60 (2019)
AbstractChanges in climatic and environmental conditions can affect both, plant chemical and isotope composition. Nowadays, many studies use bulk isotope values, which represent a weighed mean average of the different plant compounds. An isotopic characterization of individual biogeochemical compounds is desirable in order to differentiate the isotopic composition of the main plant components. However, biomass is composed mainly of high MW biopolymers i.e. polysaccharides (celluloses), polypeptides (lignin), polypeptides (proteins), polyesters (waxes), etc. not amenable to most chromatographic techniques without the use of more or less previous intense extraction and sample preparation. Here, a particular analytical pyrolysis technique combining Py-GC with a continuous flow isotope ratio mass spectrometer (IRMS) (Py-CSIA) is described and validated. Isotopic values obtained by Py-CSIA of standard n-alkanes mixtures (dissolved C16 to C30 series with increasing concentrations along three pentads, Indiana Univ. SIL mix. Type B), fitted well to a straight line (R2 > 0.999). No induced thermal cracking nor deviations from the acclaimed isotope composition (fractionation) was observed up to high pyrolysis temperature (< 400 °C). The data obtained from the approach presented in this abstract open up the perspective of developing this direct analytical technique taking into account both the biogenic origin and isotope composition, as well as their thermostability. Despite that biomass pyrolysates from different origins may yield very similar Py-GC/MS patterns, Py-CSIA can make the difference providing additional valuable isotopic information. In addition, Py-CSIA can reveal major differences according to various biomass and biopolymers with high precision, allowing the traceability of additives and minimizing sample preparation.
DescriptionComunicación Oral presentada en el 1st Iberian Meeting in Separation Sciences & Mass Spectrometry, XIX Conference of the Spanish Society of Chromatography and Related Techniques (SECyTA), IX Conference of the Spanish Society of Mass Spectrometry (SEEM), VI Conference of the Mass Spectrometry Group of the Portuguese Society of Chemistry (SPQ). Santiago de Compostela, October 8th-11th (2019).
URIhttp://hdl.handle.net/10261/210805
Appears in Collections:(IRNAS) Comunicaciones congresos
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