Identification of VOCs from natural rubber by different headspace techniques coupled using GC-MS

Abstract

Different extraction procedures were evaluated to assess their potential for measuring volatile organic compounds (VOCs) from raw rubber materials. Four headspace sampling techniques (SHS, DHS, HS-SPME and µ-CTE) were studied. Each method was firstly optimised to ensure their reliability in performance. Passive sampling was also compared as a rapid identification of background VOCs. 352 VOCs were identified, 71 from passive sampling and 281 from active headspace sampling, with 62 not previously reported (hexanenitrile, octanone, decanal, indole, aniline, anisole, alpha-pinene as well as pentanol and butanol). The volatiles belonged to a broad range of chemical classes (ketones, aldehydes, aromatics, acids, alkanes, alcohol and cyclic) with their thermal effects (lower boiling points) greatly affecting their abundance at a higher temperature. Micro-chamber (µ-CTE) was found to be the most suitability for routine assessments due to its operational efficiency (rapidity, simplicity and repeatability), identifying 115 compounds from both temperatures (30 °C and 60 °C). Whereas, HS-SPME a widely applied headspace technique, only identified 75 compounds and DHS identified 74 VOCs and SHS only 17 VOCs. Regardless of the extraction technique, the highest extraction efficiency corresponded to aromatics and acids, and the lowest compound extraction were aldehyde and hydrocarbon. The interaction between techniques and temperature for all chemical groups were evaluated using two-way ANOVA (p-value is 0.000197) explaining the highly significant interactions between factors.