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PreprintCC BY-NC-NDChemRxiv

Fast Fourier Transform-Based Approach to Denoise and Enhance GC×GC-TOFMS Data

  • Shaelyn B. Christie1,2
  • Robin J. Abel1,3
  • Maryam Shakourisalim4,2
  • James J. Harynuk1,3
  • Ryland T. Giebelhaus1,2
4 affiliations
  1. 1Department of Chemistry
  2. 2University of Victoria
  3. 3University of Alberta
  4. 4Department of Mechanical Engineering
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Abstract

Comprehensive two-dimensional (2D) gas chromatography mass spectrometry (GC×GC-MS) provides improved separation quality in comparison to one-dimensional (1D) GC-MS; however, it presents with undesirable noise akin to that of 1D, including background chemical, thermal, and electrical noise. In GC×GC-MS, the narrow peak widths necessitate the use of a fast detector, often a time-of-flight mass spectrometer (TOFMS), acquiring more than 50 spectra per second (Hz). These high detector speeds increase electrical noise. Using a Fast-Fourier Transform (FFT), it is possible to analyze GC×GC-TOFMS data in the frequency domain, which has not yet been explored and addressed in literature. In doing so, we identified intense bands in the frequency domain of both GC-MS and GC×GC-TOFMS data corresponding to common alternating current (AC) frequencies resulting from electrical components in MS detectors operating at sufficiently high acquisition rates. In GC×GC-TOFMS data, we discovered that the periodic resampling of peaks introduces equispaced bands into the frequency domain that are separated by the frequency of the modulation period. To improve data quality, we developed an algorithm operating in the frequency domain to filter unwanted noise while simultaneously preserving and enhancing chemical features. The algorithm uses Butterworth filtering to notch out AC-associated frequencies, reducing the standard deviation of the baseline noise of the total ion chromatogram (TIC) in both GC-TOFMS and GC×GC-TOFMS by 30-50%. Further, all frequencies above a specified threshold can be removed using a Butterworth lowpass filter, providing additional denoising of frequencies unassociated with chemical features. An exponential fit can also be applied to GC×GC-TOFMS data in the frequency domain, intensifying the low, chemical-associated frequencies and damping higher ones. The latter significantly reduced noise in the time domain and decreased baseline standard deviation by over 25%, albeit at the cost of slightly broadened peaks, thus decreasing resolution. Applying all enhancement methods in superposition recovers peaks along the first-dimension baseline of GC×GC-TOFMS data that were previously obscured by noise. The application of this algorithm allows for the denoising of chromatographic data while preserving and optimizing chemical features.

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Cite

BibTeXRIS
BibTeX
@misc{christie2026fast,
  title = {{Fast Fourier Transform-Based Approach to Denoise and Enhance GC×GC-TOFMS Data}},
  author = {Shaelyn B. Christie and Robin J. Abel and Maryam Shakourisalim and James J. Harynuk and Ryland T. Giebelhaus},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15008245/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008245/v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - Fast Fourier Transform-Based Approach to Denoise and Enhance GC×GC-TOFMS Data
AU  - Shaelyn B. Christie
AU  - Robin J. Abel
AU  - Maryam Shakourisalim
AU  - James J. Harynuk
AU  - Ryland T. Giebelhaus
PY  - 2026
DA  - 2026/09/03
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15008245/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008245/v1
AB  - Comprehensive two-dimensional (2D) gas chromatography mass spectrometry (GC×GC-MS) provides improved separation quality in comparison to one-dimensional (1D) GC-MS; however, it presents with undesirable noise akin to that of 1D, including background chemical, thermal, and electrical noise. In GC×GC-MS, the narrow peak widths necessitate the use of a fast detector, often a time-of-flight mass spectrometer (TOFMS), acquiring more than 50 spectra per second (Hz). These high detector speeds increase electrical noise. Using a Fast-Fourier Transform (FFT), it is possible to analyze GC×GC-TOFMS data in the frequency domain, which has not yet been explored and addressed in literature. In doing so, we identified intense bands in the frequency domain of both GC-MS and GC×GC-TOFMS data corresponding to common alternating current (AC) frequencies resulting from electrical components in MS detectors operating at sufficiently high acquisition rates. In GC×GC-TOFMS data, we discovered that the periodic resampling of peaks introduces equispaced bands into the frequency domain that are separated by the frequency of the modulation period. To improve data quality, we developed an algorithm operating in the frequency domain to filter unwanted noise while simultaneously preserving and enhancing chemical features. The algorithm uses Butterworth filtering to notch out AC-associated frequencies, reducing the standard deviation of the baseline noise of the total ion chromatogram (TIC) in both GC-TOFMS and GC×GC-TOFMS by 30-50%. Further, all frequencies above a specified threshold can be removed using a Butterworth lowpass filter, providing additional denoising of frequencies unassociated with chemical features. An exponential fit can also be applied to GC×GC-TOFMS data in the frequency domain, intensifying the low, chemical-associated frequencies and damping higher ones. The latter significantly reduced noise in the time domain and decreased baseline standard deviation by over 25%, albeit at the cost of slightly broadened peaks, thus decreasing resolution. Applying all enhancement methods in superposition recovers peaks along the first-dimension baseline of GC×GC-TOFMS data that were previously obscured by noise. The application of this algorithm allows for the denoising of chromatographic data while preserving and optimizing chemical features.
ER  -