Routine analysis by high precision gas chromatography/mass selective detector/isotope ratio mass spectrometry to 0.1 parts per mil

Abstract

Stable isotope methods are potentially quite useful for validating natural or enhanced mineral degradation of contaminants. For this reason, a continuous flow gas chromatograph (GC), isotope ratio mass spectrometer (IRMS) has been coupled with a quadrupole mass selective detector (MSD) to allow simultaneous mass spectral and stable carbon isotope ratio data to be obtained from a single chromatographic analysis. This allows the target contaminant and any extra-cellular degradation intermediates to be both qualified and quantified. Previously acceptable limits of precision (0.3 parts per mil) are undesirable given the small fractionation observed during aerobic degradation. To further understand the fate of organic contaminants and to gain information about the metabolic degradative pathway employed by a microorganism, routine isotopic analyses on a range of analytes have been performed. Quantities of sample producing mass-44 ion beam signal (I(44)) of 2 x 10(-10) to 1 x 10(-8) A were analysed. When the IRMS was tuned for high sensitivity, ion source nonlinearities were overcome by peak height correction from an algorithm that was produced using known isotopic standards of varying concentrations. This led to sample accuracy of <0.01 per thousand and sample precision of 0.1 per thousand. Copyright 1999 John Wiley & Sons, Ltd.

A sublimation technique for high-precision measurements of δ&lt;sup&gt;13&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt; and mixing ratios of CO&lt;sub&gt;2&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O from air trapped in ice cores

“…An even better separation could be achieved using a lower GC temperature, however, this also results in a stronger separation of the CO 2 isotopologues, thus, increasing the time shift between m/z 44 and m/z 45 (Meier-Augenstein et al, 1996). Although this time shift can be accounted for by the software, we observed a stronger dependence of the isotopic ratio on the amount of the sample (usually referred to as linearity effects or amount dependency), a common phenomenon with GC-IRMS applications (Hall et al, 1999;Schmitt et al, 2003). Therefore, we choose a GC temperature of 110 • C, which results in a sufficient separation between CO 2 and N 2 O of 14 s (see Fig.…”

“…Typically, the drift is on the order of 0.04 ‰ h −1 . After this trend correction, the area-δ 13 C relationship from three different peak sizes (L1, L2, L3) is calculated and all measured peaks are corrected for "linearity" effects (Hall et al, 1999;Schmitt et al, 2003). The typical slope of the area-δ 13 C function is 0.002 ‰ Vs −1 .…”

Compound-specific isotope analysis

“…[2][3][4][5][6][7][8] While fractionation effects during derivatization have been investigated at least theoretically, 9 the dependence of the isotopic signal on variations in amounts of substance when using a GC-C-IRMS has attracted less attention. As pointed out by Hall et al 10 and by Glaser and Amelung 5 , d 13 C-values of individual compounds such as alkanes and amino acid enantiomers may depend on the sample amount injected. Meier-Augenstein et al 11 found that even minute chromatographic changes, such as temperature gradients, alter the isotopic compositions derived for the peaks.…”

“…Generally, the term non-linearity is used to describe this effect. 12,13 In this paper we follow the suggestion of Hall et al 10 and use amount dependence, since 'linearity' usually describes a 1st order polynomial function. Up to now, this undesired drift with signal size 4 has been corrected using logarithmic functions that reflect changes in d 13 C upon the injection of different amounts of standards.…”

“…Therefore, we suggest to determine the amount-dependence of the d 13 C values of target compounds over the whole dynamic range using standards, and to find best-fit functions for the relationship between d 13 C and the sample amount injected. Such a procedure has already been suggested by Hall et al, 10 who investigated the amountdependence at extremely low analyte amounts. However, the phenomenon of signal dependent d…”