Sensitivity of Comprehensive Two-dimensional Gas Chromatography (GCXGC) Versus One-dimensional Gas Chromatography (1D GC) - - Chromatography Online
Sensitivity of Comprehensive Two-dimensional Gas Chromatography (GCXGC) Versus One-dimensional Gas Chromatography (1D GC)

LCGC Europe
Volume 26, Issue 12, pp. 672679

Advantages of comprehensive two-dimensional gas chromatography (GCGC) include increased peak capacity, improved resolution, and unique selectivity compared to conventional one-dimensional gas chromatography (1D GC). Despite the maturing status of the technique, there are still some outstanding issues that spark discussion and controversy. One of them is the sensitivity enhancement in GCGC separations compared to conventional 1D separation. In this article, the sensitivity of two-dimensional gas chromatography coupled to two different detectors a time-of-flight mass spectrometer (GCGC–TOF-MS) and a flame ionization detector (GCGC–FID) was compared to the sensitivity of conventional one-dimensional gas chromatography (GC–TOF-MS and GC–FID) by determining method detection limits (MDLs) for a series of different compounds with different polarities.

GCGC was first introduced by Phillips in the 1990s (1), and it soon proved to be a very powerful separation technique. GCGC provides highly structured separations with high resolving power. In spite of the many applications described in the literature, little attention has been devoted to quantitative evaluation of the technique and to quantitative comparison of these systems with the one-dimensional (1D) counterparts. The sensitivity enhancement in GCGC separations compared to conventional 1D separations is still considered a somewhat controversial issue. In GCGC, two columns of different properties are connected in series through a special interface (modulator). The modulator collects portions of the first dimension effluent, and injects them at regular intervals to the second dimension. Cryogenic modulators collect the effluent fractions at sub-oven temperatures and re-inject them in the form of a very narrow pulse when the temperature of the modulator is brought back up (2). In theory, this should increase the signal-to-noise ratio (S/N), because the mass flow rate of the solute into the detector is increased. This band recompression is generally considered to result in increased sensitivity. Increasing the frequency of the chemical signal entering a detector is an excellent way to enhance the S/N ratio (3). Philips and Liu used thermal desorption modulation between the outlet of the column and the inlet of the detector to enhance chromatographic sensitivity and S/N ratio (4). An increase by a factor of 10 was observed (4). Kinghorn and Marriott used a longitudinally modulated cryogenic system (LMCS) for the same purpose, that is, S/N enhancement in capillary gas chromatography. An increase of S/N ratio by a factor of 10 was also reported (5, 6). The increase in peak amplitude using GCGC compared to a single column has been qualitatively discussed by DeGeus (7). Habram and Welsch reported a 10–27 increase in the S/N ratio through modulation (8). Lee et al. proposed a theoretical model for simple calculation of sensitivity enhancement in GCGC over 1D separation (9). Contrary to that, a paper published in the Journal of Chromatography A in 2003 (10) claimed that there is no increase in the sensitivity of GCGC over 1D GC and stated that "(…) addition of the second dimension does not change the system MDC (minimum detectable concentration) for any solute that is sufficiently separated in one-dimensional GC and in GCGC and has the same retention in both cases." The authors mentioned that the detector electronic noise is the main contributor in the determination of MDC, and this noise cannot be reduced below a certain level limited by the white noise (10). In a GC system, under controlled conditions, the noise consists primarily of the sum of two slowly varying components: a steady-state standing-current offset (GC detector noise) (11) and "chemical" or "chromatographic" noise which includes temperature-induced column-bleed and solvent tail. The main goals of this study were to compare the sensitivity in GCGC and 1D GC using the US Environmental Protection Agency (EPA)-recommended method (12) to determine the method detection limits (MDLs) for both techniques, to study the effect of noise on the sensitivity of the method, and to determine major noise contributors (electronic noise and chromatographic noise, for example).


Instrumental Parameters: The GCGC system consisted of an Agilent 6890 GC (Agilent Technologies) equipped with a single jet, liquid nitrogen cryogenic modulator, coupled to a Pegasus III time-of-flight mass spectrometer (TOF-MS) and a flame ionization detector (FID) (LECO Corp.) (13). The column set consisted of a 30 m 0.25 mm, 1.00 m df VF-1MS (Varian) as a primary column coupled to a 1.5 m 0.25 mm, 0.25 m df SolGel-Wax phase second dimension column (SGE). Modulation periods of 2 s, 4 s, 6 s, and 8 s were used with the cryogenic trap cooled to –196 C using liquid nitrogen. The separation was performed using the following temperature programme: Initial temperature 50 C, kept for 0.2 min, and ramped at 4 C/min to 150 C (mixture 1); initial temperature 40 C, kept for 0.2 min, ramped at 30 C/min to 240 C, and then ramped at 4 C/min to 280 C and held for 3 min (mixture 2). The injector was operated at 280 C and 1 L injections were performed in pulsed splitless mode, with a splitless time of 1 min. Helium was used as the carrier gas at a constant flow of 1.4 mL/min for TOF-MS and 1.6 mL/min for the FID. The MS transfer line was maintained at 250 C. Ions in the mass range 35–400 amu were acquired at a rate of 100 spectra/s. The ion source temperature was 225 C and the detector voltage was set to -1800 V. Flame ionization detection was performed at 350 C, with data collected at 100 Hz. Three different types of inlet ferrules were used: 100% graphite ferrules (with mixture 1); vespel–graphite and SilTite ferrules (with mixture 2).

Chemicals and Stock Solutions: Two mixtures were used for this study. Mixture 1 consisted of n-nonane (n-C9), n-decane (n-C10), n-dodecane (n-C12), and 3-octanol dissolved in n-hexane (freshly distilled before use). Mixture 2 was composed of n-eicosane (n-C20), n-docosane (n-C22), n-tetracosane (n-C24), and pyrene in CS2. Hexane and all the standards were obtained from Sigma–Aldrich. CS2 was obtained from Fisher Scientific. Helium (99.999% purity) was delivered by Praxair.

Table 1: Sample concentrations used in method detection limit (MDL) determination.
Stock solutions of n-C9, n-C10, n-C12, and 3-octanol were prepared in n-hexane at a concentration of 1 mg/mL; n-C20, n-C22, n-C24, and pyrene were prepared in CS2 at the same concentration. The concentrations used with TOF-MS and FID (Table 1) were prepared by dilution of the appropriate volumes into n-hexane and CS2.

Method Detection Limit Calculations: The EPA approach as defined in the U.S. EPA Electronic Code of Federal Regulations (12) was used for the calculation of MDLs. The EPA method detection limit approach utilizes a single-concentration design estimator. The first step is to determine an estimate of the detection limit (EDL). An EDL is defined as a concentration value which maintains an instrument S/N ratio in the range of 2.5–5. The EDL is then used to choose the concentration at which standards should be prepared. The EPA recommends using a concentration that is between 1 and 5 the EDL. Eight aliquots of the sample concentration (Table 1) were prepared and the standard deviations for the peak heights of replicate measurements were calculated. The MDL was calculated as follows:

Figure 1: (a) Total ion current (TIC) of n-C9, n-C10, and n-C12 (5 pg/L, red, and 80 pg/L, white) using 1D GC–TOF-MS separation. (b) m/z = 71 extracted ion chromatogram of n-C9, n-C10, and n-C12 (5 pg/L, red, and 80 pg/L, white) using 1D GC–TOF-MS.
Where MDL is the method detection limit, t n-1, 1-∞ = 0.99 is the student's t-value appropriate for a 99% confidence level and a standard deviation estimate with n-1 degrees of freedom, and S is the standard deviation of the replicate analyses. In this study, the MDLs were estimated using the tallest second-dimension peak for a given analyte, because at or close to the MDL only this peak would be visible in most cases.


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