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High-resolution mass spectrometry (HRMS) has become a vital tool for dissolved organic matter (DOM) characterization. The upward trend in HRMS analysis of DOM presents challenges in data comparison and interpretation among laboratories operating instruments with differing performance and user operating conditions. It is therefore essential that the community establishes metric ranges and compositional trends for data comparison with reference samples so that data can be robustly compared among research groups. To this end, four identically prepared DOM samples were each measured by 16 laboratories, using 17 commercially purchased instruments, using positive-ion and negative-ion mode electrospray ionization (ESI) HRMS analyses. The instruments identified~1000 common ions in both negative-and positive-ion modes over a wide range of m/z values and chemical space, as determined by van Krevelen diagrams. Calculated metrics of abundance-weighted average indices (H/C, O/C, aromaticity, and m/z) of the commonly detected ions showed that hydrogen saturation and aromaticity were consistent for each reference sample across the instruments, while average mass and oxygenation were more affected by differences in instrument type and settings. In this paper we present 32 metric values for future benchmarking. The metric values were obtained for the four different parameters from four samples in two ionization modes and can be used in future work to evaluate the performance of HRMS instruments.

Terrestrial dissolved organic matter (DOM) interlinks large carbon reservoirs of soils, sediments, and marine environments but remains largely uncharacterized on the molecular level. Fourier transform mass spectrometry (FTMS) has proven to be a powerful technique to reveal DOM chemodiversity and potential information encrypted therein. State-of-the-art FT-ICR MS (ion cyclotron resonance) instruments are yet inaccessible for most researchers. To evaluate the performance of the most recent Orbitrap analyzer as a more accessible alternative, we compared our method to an established 15 T FT-ICR MS on a diverse suite of 17 mainly terrestrial DOM samples regarding (1) ion abundance patterns, (2) differential effects of DOM type on information loss, and (3) derived biogeochemical information. We show that the Orbitrap provides similar information as FT-ICR MS, especially for compound masses below 400 m/z, and is mainly limited by its actual resolving power rather than its sensitivity. Ecosystems that are dominated by inputs of plant-derived material, like DOM from soil, bog, lake, and rivers, showed remarkably low average mass to charge ratios, making them also suitable for Orbitrap measurements. The additional information gained from FT-ICR MS was highest in heteroatom-rich (N, S, P) samples from systems dominated by internal cycling, like DOM from groundwater and the deep sea. Here FT-ICR MS detected 37% more molecular formulae and 11% higher ion abundance. However, the overall information content, which was analyzed by multivariate statistical methods, was comparable for both data sets. Mass spectra-derived biogeochemical trends, for example, the decrease of DOM aromaticity during the passage through terrestrial environments, were retrieved by both instruments. We demonstrate the growing potential of the Orbitrap as an alternative FTMS analyzer in the context of challenging analyses of DOM complexity, origin, and fate.

The Amazon delivers a fifth of the global continental runoff and riverine dissolved organic carbon (DOC) to the ocean. Intensified biogeochemical processes are expected at the junction of the Amazon's major blackwater tributary, the Rio Negro, and its parent, the Rio Solimões, due to large gradients in pH, conductivity, DOC and particle load. Dissolved organic matter (DOM) plays a major role in aquatic biogeochemical processes which are poorly understood on the molecular level. To gain insights into the potential role of DOM in non-conservative processes, we assessed dynamics of Cu, Fe and DOM by ultrahigh resolution mass spectrometry in: (1) endmembers, (2) regional samples and (3) laboratory mixing experiments under presence/absence of natural particles (>0.2 lm). The relative abundances of 3600 DOM molecular formulae were interpreted via multivariate statistics which revealed major dynamics in the DOM molecular composition. >40% of molecular formulae displayed conservative behavior even in the presence of natural particles, agreeing with bulk DOC behavior, but opposing the oftenpresumed non-conservative behavior of DOM. Another 16-27% of formulae fluctuated in FT-ICRMS signal intensity during mixing, but did not show consistent non-conservative behavior. Both rivers left a clear molecular imprint within the DOM of the Amazon, each being linked to >800 molecular formulae. Characteristic for the Rio Negro was a dominance of phenolics with a wide molecular mass range (centered at $400 Da), and for the Rio Solimões more saturated but lower-molecular mass compounds (centered at $300 Da). Both Fe and Cu showed distinct non-conservative mixing patterns under particle presence. In the controlled mixing experiments including original particles at natural concentration, up to 0.5 lg/L Cu was released from the particles into solution at 20-40% blackwater contribution. Our molecular analysis revealed distinct DOM compositional changes in polyphenol-and nitrogencontaining formulae paralleling this release, suggesting links to desorption of potential ligands and charge-induced effects at particle surfaces caused by pH and conductivity changes in the course of mixing.

Ultrahigh-resolution Fourier transform mass spectrometry (FTMS) has revealed unprecedented details of natural complex mixtures such as dissolved organic matter (DOM) on a molecular formula level, but we lack approaches to access the underlying structural complexity. We here explore the hypothesis that every DOM precursor ion is potentially linked with all emerging product ions in FTMS 2 experiments. The resulting mass difference (Δ m ) matrix is deconvoluted to isolate individual precursor ion Δ m profiles and matched with structural information, which was derived from 42 Δ m features from 14 in-house reference compounds and a global set of 11 477 Δ m features with assigned structure specificities, using a dataset of ∼18 000 unique structures. We show that Δ m matching is highly sensitive in predicting potential precursor ion identities in terms of molecular and structural composition. Additionally, the approach identified unresolved precursor ions and missing elements in molecular formula annotation (P, Cl, F). Our study provides first results on how Δ m matching refines structural annotations in van Krevelen space but simultaneously demonstrates the wide overlap between potential structural classes. We show that this effect is likely driven by chemodiversity and offers an explanation for the observed ubiquitous presence of molecules in the center of the van Krevelen space. Our promising first results suggest that Δ m matching can both unfold the structural information encrypted in DOM and assess the quality of FTMS-derived molecular formulas of complex mixtures in general.