Preprints
https://doi.org/10.5194/egusphere-2022-1319
https://doi.org/10.5194/egusphere-2022-1319
09 Dec 2022
 | 09 Dec 2022

Scaled Kendrick Mass Defect Analysis for Improved Visualization of Atmospheric Mass Spectral Data

Mitchell W. Alton, Harald Stark, Manjula R. Canagaratna, and Eleanor C. Browne

Abstract. Mass spectrometry is an important analytical technique within the field of atmospheric chemistry. Owing to advances in instrumentation, particularly with regards to mass resolving power and instrument response factors (sensitivities), hundreds of different mass-to-charge (m/z) signals are routinely measured. This large number of detected ions creates challenges for data visualization. Furthermore, assignment of chemical formulas to these ions is time-consuming and increases in difficulty at the higher m/z ranges. We present a technique called scaled Kendrick mass defect (SKMD) analysis to facilitate the visualization and peak identification processes for typical atmospheric organic (and to some extent inorganic) compounds. SKMD is related to the previously proposed resolution enhanced Kendrick mass defect (REKMD). SKMD introduces a tunable integer scaling factor into the mass defect equation that effectively contracts or expands the mass scale. The SKMD transformation maintains the horizontal alignment of ion series related by integer multiples of the chosen base unit that is characteristic of Kendrick mass defect analysis. However, the tunable integer acts to alter the mass defect spacing between different homologue ion series. As a result, the entire mass defect range (-0.5 to 0.5) is more effectively used simplifying data visualization and facilitating chemical formula assignment. We describe the mechanism of this transformation and discuss base unit and scaling factor selections appropriate for compounds typically found in atmospheric measurements. We present an open-source graphical user interface (GUI) for calculating and visualizing SKMD analysis results within the Igor Pro Environment.

Mitchell W. Alton et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-1319: mass excess', Marc Gonin, 13 Dec 2022
  • CC2: 'Comment on egusphere-2022-1319: mass vs mas/charge', Marc Gonin, 13 Dec 2022
    • RC2: 'Reply on CC2', Thierry Fouquet, 06 Jan 2023
  • RC1: 'Comment on egusphere-2022-1319', Thierry Fouquet, 06 Jan 2023
  • RC3: 'RC2', Anonymous Referee #2, 31 Jan 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-1319: mass excess', Marc Gonin, 13 Dec 2022
  • CC2: 'Comment on egusphere-2022-1319: mass vs mas/charge', Marc Gonin, 13 Dec 2022
    • RC2: 'Reply on CC2', Thierry Fouquet, 06 Jan 2023
  • RC1: 'Comment on egusphere-2022-1319', Thierry Fouquet, 06 Jan 2023
  • RC3: 'RC2', Anonymous Referee #2, 31 Jan 2023

Mitchell W. Alton et al.

Model code and software

SKMD panel Mitchell Alton, Harald Stark, Eleanor Browne https://github.com/BrowneLab/SKMD_Panel.git

Mitchell W. Alton et al.

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Short summary
Mass spectrometric measurements of atmospheric composition routinely detect hundreds of different ions of varying chemical composition creating challenges for visualization and data interpretation. We present a new analysis technique to facilitate visualization while providing greater chemical insight. Additionally, it can aid in identifying the chemical composition of ions. A graphical user interface for performing the analysis is introduced and freely available enabling broad applications.