Analysis of Long-Chain Petroleum Hydrocarbons and VOCs in Soil by GC-MS
25 Apr 2018

In this webinar, we focus on the analysis of organic contaminants in soil using gas chromatography-mass spectrometry (GC-MS) methods. This webinar will highlight two different approaches:

  • Nitric oxide ionization spectroscopy evaluation (NOISE) - a non-traditional mass spectrometry method for hydrocarbon typing.
    • NOISE enables structural determination of components in process streams, by carbon number and degree of unsaturation. The benchmark technique for hydrocarbon typing assists scientists in identifying oil spills and contamination in the environment, optimizing hydrotreaters and evaluating unit performance, and makes the most of new crude oil slates.
  • Methods for sample collection and analysis of soils and solid wastes for volatile organic compounds (VOCs) follow established outline procedures, e.g., EPA 5035A.
    • This procedure is required for analytical methods using Purge & Trap analysis (8021, 8015 and 8260) and are standard in many contract Environmental Laboratories. Soil matrixes are performed on two ranges: low level and high level using Purge and Trap sample concentration and GC-MS detection. Data will be shared showing expected calibration ranges and quality control to meet Method 8260.

Learning objectives:
  • Find out how NOISE can be used for hydrocarbon typing and how the characteristic reactions of the reagent ion, NO+, with hydrocarbons provide compositional analysis by type and carbon number. NOISE for hydrocarbon typing and how the characteristic reactions of the reagent ion, NO+, with hydrocarbons provide compositional analysis by type and carbon number using GC-MS.
  • EPA Method 8260 for analysis of high and low-level VOCs in soil

Who should attend?
  • Anyone interested in compositional analysis of hydrocarbons in the C5-C40 range, including hydrocarbon contamination in the environment
  • Anyone interested in the analysis of volatile organic compounds (VOCs) in soil

Thermo Fisher Scientific