Highly Efficient Monitoring of VOCs in Stack Emissions using TD-GC-MS

by | Air, Environmental

Markes International has produced an application note for the highly efficient monitoring of VOCs in stack emissions using sorbent tubes analysed by TD–GC–MS in accordance with European standard method CEN/TS 13649. The value of repeat analysis for method development and result verification is also demonstrated.

Volatile organic compounds (VOCs) play key roles in photochemical reactions in the atmosphere – in particular, they contribute to formation of harmful particulates, and are involved in the generation of low-level ozone. Moreover, due to their toxicity many VOCs have a significant impact on human and environmental health in their own right. Emissions from industry contribute significantly to global levels of man-made VOCs, and as a result in 2001 the European technical committee for air quality (CEN/TC 264) released a standard method that defined a procedure for monitoring VOCs from stationary sources, such as in stack gases.

Markes_VOCs_stack_emissions.pngIn this application note, the outstanding performance of a TD–GC–MS system for analysis of a standard mix of compounds in accordance with CEN/TS 13649 is demonstrated, and followed with a real-life sample of exhaust from a busy restaurant.

The sampling and analytical protocol used in this study is fully compliant with the method stipulated in CEN/TS 13649.

Real-world Sample
300 mL of air is taken from the exhaust of a restaurant during a busy lunchtime period, using an ACTI-VOC™ low-flow pump (Markes International).

This application note demonstrates that Markes International’s automated, cryogen-free thermal desorption systems offer:

  • excellent results for monitoring VOCs from stationary source emissions in accordance with the European standard CEN/TS 13649
  • improved performance and simplicity compared to solvent extraction
  • straightforward method development and validation of results because of the ability to carry out sample splitting and re-collection for repeat analysis in an automated fashion.

Published  Jul 6, 2017

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