On the performance of proton-transfer-reaction mass spectrometry for breath-relevant gas matrices

• Published in: Measurement science & technology Vol. 24; no. 12; pp. 1 - 13
• Main Authors: Beauchamp, J, Herbig, J, Dunkl, J, Singer, W, Hansel, A
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.12.2013
• Subjects: Calibration; Carbon dioxide; gas calibration unit; limit of detection; Mass spectrometry; Mathematical analysis; Matrices (mathematics); proton-transfer-reaction mass spectrometry; Relative humidity; Volatile organic compounds
• ISSN: 0957-0233; 1361-6501
• DOI: 10.1088/0957-0233/24/12/125003

The accuracy of quantitative volatile organic compound (VOC) detection by proton-transfer-reaction mass spectrometry (PTR-MS) is substantially enhanced if the instrument is calibrated. Although quantification of a compound is in principle possible by mathematical methods based on kinetic theory, the underlying picture can become complicated depending on the gas matrix, leading to error. A simple, reliable method to overcome this is to calibrate the instrument using standard gas mixtures containing VOCs at known concentrations, which enables the compound-dependent sensitivity of the instrument to be determined. A dynamic gas calibration unit was developed to generate variable but known quantities of selected standard compounds in a carrier gas of variable relative humidity (RH; up to 100% at 37 °C) and CO2 content (≤10%v) to reflect the changing conditions of a breath-gas sample matrix. Besides individual compound sensitivities, calibration also yields the limits of detection and quantification of the experimental method. Extensive calibrations of PTR-MS with several breath-relevant compounds were made at varying RH and CO2. Gas matrix effects of several compounds were negligible when appropriate mass-dependent transmission correction and normalization to the primary ions (m z 21 and m z 37) were applied. Two compounds are discussed in particular, namely acetaldehyde, which interferes with a CO2-related background, and formaldehyde, which shows a nonlinear dependence on sample gas humidity.