Uncertainty contribution of derivatization in gas chromatography/mass spectrometric analysis.

Rationale: The purpose of the current work is to realistically assess the uncertainty contribution in gas chromatography/mass spectrometry (GC/MS) analysis originating from less-than-ideal derivatization efficiency.

Methods: As the exemplary analytical method a two-step derivatization method with KOH and BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide), applied for the analysis of fatty acid triglycerides (using real measurement data), was selected. The derivatization efficiencies were in the range 0.89-1.04. In this study, two approaches for bottom-up uncertainty evaluation were compared: the traditional GUM approach and the Monte Carlo method (MCM). Both were used with and without taking correlation between input quantities into account.

Results: The most reliable uncertainty estimates were in the range 0.07-0.08 (expanded uncertainties at 95% coverage probability). A strong negative correlation was found between the slope and intercept of the calibration graph (r = -0.71) and it markedly influenced the uncertainty estimate of derivatization efficiency. The MCM was found to give somewhat higher uncertainty estimates, which are considered more realistic.

Conclusions: Derivatization directly affects the analysis result. Thus, in the case of this exemplary analysis, just derivatization alone (i.e. if all other uncertainty sources are neglected) causes relative expanded uncertainty around 8%, being thus an important and in some cases the dominant uncertainty contributor.