The ion chromatogram allows some more special examinations. An important
aspect is the quantification (see also Sect. 5.2). Ion chromatograms of specific ions
(characterized e.g. by high masses, even values or unusual fragments) exhibit a
better signal-to-noise ratio allowing to improve the sensitivity of the quantitative
analyses (see Fig. 5.13 for m/z 203).
Ion chromatograms also allow a faster identification of preselected analytes. One
just need to create one or more ion chromatograms derived from specific ions of the
analytes’ mass spectrum. At the position where all chromatograms exhibit a peak,
most probably the wanted analyte can be identified. However, as a last but maybe
most important feature, ion chromatograms allow to visualize isomers and homologue series. This is an important approach in Organic Geochemistry. As significant
examples, analyses of fossil matter (coals, petroleum, kerogen etc.) comprise often
n-alkane distributions as well as analyses of hopanes and steranes. The homologues
series of n-alkanes can be easily detected by the ion fragment m/z 57 or 71 (or 81 . . .)
and organic-chemically important parameter such as carbon preference indices
(CPIs) can be directly visualized (see Fig. 5.14). Hopane analysis is often based
on the ion chromatogram m/z 191 as unique ion of these pentacyclic triterpenoids.
The attribution of individual isomers is based only partly on the mass spectra but
mainly on the gas chromatographic retention order as illustrated in Fig. 5.14.
Also in environmental analyses ion chromatogram play an important role. The
identification of PAHs in combination with the alkylated derivatives is achieved
easily by ion chromatogram series with differences of m/z 14, representing the
individual homologues groups (Fig. 5.14). Finally, ion chromatograms are used in
particular to resolve complex mixtures of congeners such for PCBs. Separate levels
of chlorinated and superimposed substitution isomers can be illustrated by the
individual ion chromatograms of their molecular ions (Fig. 5.14). The corresponding
individual pattern of each level of chlorination reflects perfectly the technical
mixtures and can act for pattern recognition of technical products in natural samples.
The same accounts for linear alkylbenzenes LABs (residues of detergents, frequently
detected in riverine sediments), that are commonly analyzed and quantified using
their characteristic ion m/z 91, where the individual homologues are verified by their
molecular ion (Fig. 5.14).
5.1.3 Common Routine in GC/MS Based Identification
In common laboratory routine, GC/MS data are certainly not handled by ab initio
interpretation of mass spectra or similar time consuming and intensive approaches.
For identification of substances, IT based approaches are applied using mass spectral
data libraries. These libraries consist of hundreds of thousands of mass spectra and
computer-based comparison allows a fast search for similar spectra as compared to
the measured ones. Precondition is the conformity of mass spectra measured on
different mass spectrometer.
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5 GC/MS Data Evaluation
aspect is the quantification (see also Sect. 5.2). Ion chromatograms of specific ions
(characterized e.g. by high masses, even values or unusual fragments) exhibit a
better signal-to-noise ratio allowing to improve the sensitivity of the quantitative
analyses (see Fig. 5.13 for m/z 203).
Ion chromatograms also allow a faster identification of preselected analytes. One
just need to create one or more ion chromatograms derived from specific ions of the
analytes’ mass spectrum. At the position where all chromatograms exhibit a peak,
most probably the wanted analyte can be identified. However, as a last but maybe
most important feature, ion chromatograms allow to visualize isomers and homologue series. This is an important approach in Organic Geochemistry. As significant
examples, analyses of fossil matter (coals, petroleum, kerogen etc.) comprise often
n-alkane distributions as well as analyses of hopanes and steranes. The homologues
series of n-alkanes can be easily detected by the ion fragment m/z 57 or 71 (or 81 . . .)
and organic-chemically important parameter such as carbon preference indices
(CPIs) can be directly visualized (see Fig. 5.14). Hopane analysis is often based
on the ion chromatogram m/z 191 as unique ion of these pentacyclic triterpenoids.
The attribution of individual isomers is based only partly on the mass spectra but
mainly on the gas chromatographic retention order as illustrated in Fig. 5.14.
Also in environmental analyses ion chromatogram play an important role. The
identification of PAHs in combination with the alkylated derivatives is achieved
easily by ion chromatogram series with differences of m/z 14, representing the
individual homologues groups (Fig. 5.14). Finally, ion chromatograms are used in
particular to resolve complex mixtures of congeners such for PCBs. Separate levels
of chlorinated and superimposed substitution isomers can be illustrated by the
individual ion chromatograms of their molecular ions (Fig. 5.14). The corresponding
individual pattern of each level of chlorination reflects perfectly the technical
mixtures and can act for pattern recognition of technical products in natural samples.
The same accounts for linear alkylbenzenes LABs (residues of detergents, frequently
detected in riverine sediments), that are commonly analyzed and quantified using
their characteristic ion m/z 91, where the individual homologues are verified by their
molecular ion (Fig. 5.14).
5.1.3 Common Routine in GC/MS Based Identification
In common laboratory routine, GC/MS data are certainly not handled by ab initio
interpretation of mass spectra or similar time consuming and intensive approaches.
For identification of substances, IT based approaches are applied using mass spectral
data libraries. These libraries consist of hundreds of thousands of mass spectra and
computer-based comparison allows a fast search for similar spectra as compared to
the measured ones. Precondition is the conformity of mass spectra measured on
different mass spectrometer.
114
5 GC/MS Data Evaluation