Experimental Evaluation of Mass Discrimination Effects in Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: A Case Study of Straight-Chain Fatty Acids
Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is widely used for molecular characterization of complex organic matter due to its ultrahigh resolution and mass accuracy. In atmospheric and natural organic matter studies, signal intensity is often used as a proxy for relative abundance or combined with a single internal standard for semi-quantitative comparison. Such practices assume uniform response across species of different mass-to-charge ratios (m/z); however, electrospray ionization (ESI), ion transport, and space-charge effects within the ICR trap can introduce mass-dependent biases. This study systematically evaluated mass discrimination effects on fatty acid analysis using a 9.4 T ESI-FT-ICR-MS, employing C12–C30 straight-chain saturated fatty acids, three deuterated internal standards, and three concentration levels. Results showed: (1) Absolute intensities of fatty acids and internal standards were not linearly proportional to concentration; as fatty acid concentration doubled, intensity increases were non-proportional, while internal standard intensities declined by up to 53% despite constant concentration. At equal concentrations, intensity decreased markedly with molecular weight—triacontanoic acid (C30) was ~40 times lower than lauric acid (C12), indicating severe underestimation of high-molecular-weight species. (2) Response ratios of fatty acids to internal standards versus concentration ratios exhibited good linearity (R² > 0.9). The derived deviation coefficients (F) increased exponentially with m/z (R² > 0.999), reaching >50 for C30. (3) Application to PM2.5 fatty acids showed that after F correction, abundances of long-chain fatty acids (C20–C30) increased 3.6-fold, and the carbon preference index (CPI) shifted from 1.8 (fossil fuel source) to 3.4 (higher plant source), demonstrating that neglecting mass discrimination leads to misidentification of sources. These findings underscore the necessity of systematic evaluation of mass discrimination effects in ultrahigh-resolution mass spectrometry for accurate organic composition and source apportionment.