Novel gas chromatography–mass spectrometry database for automatic identification and quantification of micropollutants

Abstract

A novel gas chromatography–mass spectroscopy (GC–MS) database for identification and quantification of micropollutants in environmental and food samples is reported. GC retention times, calibration curves, and mass spectra of nearly 700 chemicals were registered in the database, and the GC retention times of registered chemicals in actual samples were predicted from the retention times of n-alkanes measured before sample analysis. Differences between predicted and actual retention times were less than 3 s, an accuracy that is nearly identical to that obtained by analysis of standard substances. After the retention times were predicted, a calibration file for the GC–MS instrument was created from the predicted retention times, calibration curves, and mass spectra of the registered chemicals. With the resulting calibration file, automated identification of all the chemicals in actual samples was possible without the use of standards, and the identification method was as reliable as conventional methods. When the GC inlet, column, and tuning conditions were adjusted using GC–MS performance check standards, relative standard deviations of 20% or less for determination values could be obtained. More than 90% of the chemicals in the database could be detected at a sensitivity sufficient for all practical purposes (100 pg or less). Because each chemical in the database, to which new substances can easily be added, can be determined in 1 h, micropollutants in samples can be analyzed efficiently and inexpensively.