Comparison of Two Derivative Methods for the Quantification of Amino Acids in PM2.5 Using GC-MS/MS

Abstract

Amino acids (AAs), a type of nitrogen-based organic compounds in the atmosphere, are directly and indirectly related to climate change, and as their link to allergic diseases becomes more known, the need for quantitative analysis of ultrafine dust (PM<inf>2.5</inf>) will become increasingly necessary. When sensing water-soluble AAs using a gas chromatograph combined with a tandem mass spectrometer (GC-MS/MS), derivatization should be considered to increase the volatility and sensitivity of target analytes. In this study, two methods were used to compare and evaluate 13 AA derivatives in PM<inf>2.5</inf> samples: N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide with 1% tert-butyldimethylchlorosilane (MTBSTFA w/1% t-BDMCS), which is preferred for silylation, and ethyl chloroformate (ECF) with methanol (MeOH) for chloroformate derivatization. The most appropriate reaction conditions for these two derivative methods, such as temperature and time, and the analytical conditions of GC-MS/MS for the qualitative and quantitative analysis of AAs were optimized. Furthermore, the calibration curve, detection limit, and recovery of both methods for validating the quantification were determined. The two derivative methods were applied to 23 actual PM<inf>2.5</inf> samples to detect and quantify target AAs. The statistical significances between pairwise measurements of individual AAs detected by both methods were evaluated. This study will help in selecting and utilizing appropriate derivative methods for the quantification of individual AAs in PM<inf>2.5</inf> samples. © 2025 Elsevier B.V., All rights reserved.