Possibilities and limitations of dynamic headspace sampling as a pre-concentration technique for trace analysis of organics by capillary gas chromatography

General Introduction

“…The purged volatiles are thus present in a diluted gas extract and must be subsequently focused in a trap; this can be a cold trap, but in general, a cartridge packed with an adsorbent is used from which the trapped compounds are released by thermal desorption and transferred by the carrier gas into the column. The charged adsorbent, however, may also be desorbed by a small amount of a liquid solvent, as used in the closed-loop stripping procedure of Grob [13][14][15]. Figure 1-2 shows a typical configuration for P&T instrumentation for capillary GC, comprising an adsorption tube (AT) with multisorbent packing, various possible split positions (SP-1, SP-2, and SP-3), and a cryo-trap (CT).…”

Sample Preparation for Chromatographic Analysis

“…where R is the recovery of the analyte (equal to the ratio of the analyte sorbed onto the trap and the initial amount present in the sample), F stripping gas flow rate, t stripping time, K the gasliquid partition coefficient, V L sample volume, and V G volume of gas passed through the liquid in time t [319,343,344]. Equation (8.5) is somewhat idealized as it is assumed in its derivation that: (1) thermodynamic equilibrium exists; (2) no breakthrough occurs in the trap (closed loop stripping analysis); (3) the liquid matrix is involatile; and (4) the partition coefficient is independent of concentration.…”

Quantitative determination of volatiles in polyolefins by dynamic headspace/capillary gas chromatography/mass spectrometry

“…These steps were repeated as many times as was necessary to achieve almost complete extraction of the component of interest. The recovery of the volatiles is dependent on several factors, such as sample size, temperature, flow rate of the purge gas, type of purge gas, sampler geometry, trappingand desorption efficiency [9,11,12]. Furthermore, the volatility, solubility and affinity of the compounds and their diffusion rates in the polymer as well as the properties of the polymer itself (e. g. crystallinity, chain-branching, density) also strongly influence the quantitative yield [9].…”

“…The parameters can be optimized by use of a multivariate optimizing program, e. g. simplex [15] or by use of a theoretical model [9,12]. However, the sampling condition is not always optimal for all volatiles and to get a better reproducibility of the results for the studied compounds, it is preferable to use multiple dynamic headspace extraction (MDHE).…”