Interlaboratory comparison of humic substances compositional space as measured by Fourier transform ion cyclotron resonance mass spectrometry (IUPAC Technical Report)

Abstract Interlaboratory comparison on the determination of the molecular composition of humic substances (HS) was undertaken in the framework of IUPAC project 2016-015-2-600. The analysis was conducted using high resolution mass spectrometry, nominally, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) with electrospray ionization. Six samples of HS from freshwater, soil, and leonardite were used for this study, including one sample of humic acids (HA) from coal (leonardite), two samples of soil HA (the sod-podzolic soil and chernozem), two samples of soil fulvic acids (FA) (the sod-podzolic soil and chernozem), and one sample of freshwater humic acids (the Suwannee River). The samples were analyzed on five different FTICR MS instruments using the routine conditions applied in each participating laboratory. The results were collected as mass lists, which were further assigned formulae for the determination of molecular composition. The similarity of the obtained data was evaluated using appropriate statistical metrics. The results have shown that direct comparison of discrete stoichiometries assigned to the mass lists obtained by the different laboratories yielded poor results with low values of the Jaccard similarity score – not exceeding 0.56 (not more than 56 % of the similar peaks). The least similarity was observed for the aromatics-rich HA samples from leonardite (coal) and the chernozem soil, which might be connected to difficulties in their ionization. The reliable similarity among the data obtained in this intercomparison study was achieved only by transforming a singular point (stoichiometry) in van Krevelen diagram into a sizeable pixel (a number of closely located stoichiometries), which can be calculated from the population density distribution. The conclusion was made that, so far, these are descriptors of occupation density distribution, which provide the metrics compliant with the data quality requirements, such as the reproducibility of the data measurements on different instruments.

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