|Abstract Title:||Combining high-capacity sorptive extraction with Thermal desorption pre-concentration for analysis of (S)VOCs in environmental samples|
|Presenter Name:||Dr Lara Kelly|
|Co-authors:||Mr Gareth Roberts|
Mr Massimo Santoro
Ms Ilaria Ferrante
|Company/Organisation:||Markes International Ltd|
Abstract Information :
Thermal desorption (TD) combined with GC(MS) has long been used as a tool in the sampling and pre-concentration of (S)VOCs in vapour phase samples. Traditionally, TD has been employed extensively for environmental and workplace air monitoring, with other applications in materials testing, food profiling and forensic type applications becoming increasingly common. However, the ability to deal with liquid sampling as historically been somewhat limited to many users of TD technology. New developments in sampling technologies, including high-capacity sorptive extraction, has extended the applicability of TD to liquid and solid samples, with the capacity for both immersive and headspace sampling allowing the extraction of components from within the sample prior to pre-concentration and analysis.
When used in conjunction with Thermal desorption, high-capacity sorptive extraction offers a number of well-known advantages over traditional solvent-extraction methods for a wide range of VOCs and SVOCs, including greatly improved sensitivity due to the avoidance of dilution, high extraction efficiency, and efficient transfer/injection into the GC. Furthermore, high-capacity sorptive extraction offers an extension to SPE & SPME methods which is simple to employ and, offers a versatile, robust method for gaining complementary information to that contained using other sampling approaches.
This multi-facted sampling approach has been applied to a number of differerent sample types, including environmental matrices, foods, beverages and clinical samples, examples of which will be presented. The benefits of using TD sample introduction extend to the ability to re-collect sample for repeat analysis, assisting with method validation and eliminating the need to perform repeat extractions on limited sample quantities.