## Abstract This paper describes the use of coupled LC‐GC for the determination of organochlorine pesticide residues in fat samples. Organochlorine pesticide residues are preseparated from fat by LC on a short C‐18 column using an organic solvent as the mobile phase. Evaporation of the LC eluent is
On-line LC-GC-AED and LC-GC-MS - multidimensional methods for the analysis of PAC in fuels, combustion emissions and atmospheric samples
✍ Scribed by Lewis, Alastair C. ;Askey, Sarah A. ;Holden, Krystyna M. ;Bartle, Keith D. ;Pilling, Michael J.
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 608 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0935-6304
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✦ Synopsis
Abstract
The composition and concentration of polycyclic aromatic compounds (PAC) in fuels. Theier combustion products and in the atmosphere remains a topic of considerable interest. Despite the wealth of literature on the identification of PAC, speciation at low concentrations remains difficult due to instrument limitation and the complexity of fuel and environmental samples. Consequently on line sample preparation procedures (SPE, SFE, LC, etc.) are becomeing an increasingly important step in the analysis procedure particularly where sample clean‐up and fractionation are essential for improving analytical resolution. In this study a normal phase high pressure analytical resolution. In this study a normal phase high pressure liquid chromatography‐gas chromatography (LC‐GC) system has been developed to provide quantitative analysis of samples, as diverse as coal liquids, petroleum fuels, diesel exhaust particulates, and urban air particulates. Separation and identification of parent and alkylated PAH, hetercycline nitro‐and oxy‐PAC can be achieved by direct coupling to an atomic emission detector and a bech top mass spectrometer. For both systems the primary LC separation combined with the large sample volume transferred to GC vastly improves detection limits. Furthermore the complimentary nature of the two detectors used enables the positive indentification of many unknowns.
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