Key Takeaways & Executive Findings
- •• • Absolute FT-ICR-MS intensity is not linearly proportional to concentration; internal standard intensity dropped up to 53% despite constant concentration, and C30 fatty acid intensity was ~40-fold lower than C12 at equal concentrations, causing severe underestimation of high-m/z species. • • Response ratios (fatty acid/internal standard) versus concentration ratios showed excellent linearity (R² > 0.9), enabling derivation of deviation coefficients (F) that increased exponentially with m/z (R² > 0.999), reaching >50 for C30. • • Applying F correction to PM2.5 fatty acids increased long-chain (C20–C30) abundances by 3.6-fold and shifted CPI from 1.8 to 3.4, altering source interpretation from fossil fuel to higher plant dominance—critical for accurate source apportionment. • • Without mass discrimination correction, response-weighted metrics (e.g., average carbon number, O/C, H/C ratios) and source apportionment based on relative abundances are systematically biased, particularly for high-m/z compounds, impacting environmental and geochemical conclusions.
Abstract
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.
1. Introduction
Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) offers unparalleled resolution and mass accuracy, making it a cornerstone for molecular characterization of complex organic mixtures in environmental and geochemical research. However, its quantitative application relies on the assumption that signal intensity is directly proportional to analyte concentration across a wide m/z range. This assumption is increasingly questioned because electrospray ionization (ESI) efficiency, ion transmission, and space-charge effects within the ICR cell are known to be mass-dependent. In practice, researchers often use signal intensity as a proxy for relative abundance or employ a single internal standard for semi-quantitative comparisons, potentially introducing systematic biases that distort molecular distributions and source interpretations. The lack of systematic evaluation of these mass discrimination effects has hindered the reliability of FT-ICR-MS data in atmospheric and natural organic matter studies.
This study addresses this critical bottleneck by designing a controlled experiment using a homologous series of straight-chain saturated fatty acids (C12–C30) with three deuterated internal standards and multiple concentration levels. By quantifying the relationship between response ratios and concentration ratios, the authors derive deviation coefficients (F) that correct for mass-dependent biases. The results demonstrate that without such correction, high-molecular-weight fatty acids are severely underestimated, leading to erroneous source apportionment in PM2.5 samples. This work provides a robust experimental framework for evaluating and correcting mass discrimination effects, thereby enhancing the accuracy of FT-ICR-MS-based quantitative analyses in complex environmental matrices.
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JIANG Hao, HE Quanfu, JIANG Bin, DING Xiang (2026). Experimental Evaluation of Mass Discrimination Effects in Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: A Case Study of Straight-Chain Fatty Acids. Environmental Chemistry. https://doi.org/10.7524/j.issn.0254-6108.2026031101
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Frequently Asked Questions
What is the quantitative impact of mass discrimination on the absolute intensity of high-molecular-weight fatty acids compared to low-molecular-weight ones?
At equal concentrations, the intensity of triacontanoic acid (C30) was approximately 40 times lower than that of lauric acid (C12). This severe suppression leads to a significant underestimation of high-molecular-weight species in complex mixtures.
How does the deviation coefficient (F) vary with m/z, and what is its maximum observed value?
The deviation coefficient (F) increases exponentially with m/z, with a correlation coefficient R² > 0.999. For triacontanoic acid (C30), F exceeded 50, indicating a more than 50-fold bias in response relative to lower m/z compounds.
Can the internal standard method effectively correct for mass discrimination in FT-ICR-MS analysis?
Yes, using structurally similar deuterated fatty acids as internal standards, the response ratio (analyte/internal standard) versus concentration ratio showed excellent linearity (R² > 0.9). The derived F values enable correction, as demonstrated by a 3.6-fold increase in long-chain fatty acid abundances after correction in PM2.5 samples.
What is the effect of mass discrimination on the carbon preference index (CPI) and source apportionment in PM2.5?
Without correction, the CPI of high-molecular-weight fatty acids (C20–C30) was 1.8, suggesting a fossil fuel source. After applying F correction, CPI increased to 3.4, indicating a higher plant source. This shift demonstrates that neglecting mass discrimination can lead to incorrect source identification.
Are there any limitations or conditions under which the proposed correction method may not be applicable?
The method relies on the availability of structurally similar internal standards for each analyte class. For complex mixtures with diverse compound classes, this approach may require multiple internal standards. Additionally, the correction is based on a specific m/z range and instrument conditions; extrapolation to other systems should be validated.
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