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1.
Water Res ; 232: 119672, 2023 Apr 01.
Article in English | MEDLINE | ID: mdl-36739660

ABSTRACT

The molecular composition of dissolved organic matter (DOM) is of relevance for global carbon cycling and important for drinking water processing also. The detection of variation of DOM composition as function of time and space from a methodological viewpoint is essential to observe DOM processing and was addressed so far. High resolution concerning DOM quality was achieved with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). However almost none of the existing FTICR-MS data sets were evaluated addressing the fate of single mass features / molecular formulas (MFs) abundance during experiments. In contrast to former studies we analyze the function of MF abundance of time and space for such MFs which are present in all samples and which were formerly claimed as recalcitrant in not all but a great number of studies. For the first time the reactivity of MFs was directly compared by their abundance differences using a simple equation, the relative intensity difference (δRI). Search strategies to find out the maximum δRI values are introduced. The corresponding MFs will be regarded as key MFs (KEY-MFs). In order to test this new approach data from a recent photo degradation experiment were combined with monitoring surveys conducted in two drinking water reservoirs. The δRI values varied over one order of magnitude (more than five-fold). MFs like C9H12O6 and C10H14O6 revealed high biogeochemical reactivity as photo products. Some of the KEY-MFs were identical with MFs identified as disinfection byproducts precursors in recent studies. Other KEY-MFs were oxygen-rich and relatively unsaturated (poly-phenol-like) and hence relevant to flocculation procedures.


Subject(s)
Dissolved Organic Matter , Drinking Water , Mass Spectrometry , Oxygen , Phenols
2.
Environ Sci Technol ; 54(21): 13556-13565, 2020 11 03.
Article in English | MEDLINE | ID: mdl-32966053

ABSTRACT

Dissolved organic matter plays an important role in aquatic ecosystems and poses a major problem for drinking water production. However, our understanding of DOM reactivity in natural systems is hampered by its complex molecular composition. Here, we used Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and data from two independent studies to disentangle DOM reactivity based on photochemical and microbial-induced transformations. Robust correlations of FT-ICR-MS peak intensities with chlorophyll a and solar irradiation were used to define 9 reactivity classes for 1277 common molecular formulas. Germany's largest drinking water reservoir was sampled for 1 year, and DOM processing in stratified surface waters could be attributed to photochemical transformations during summer months. Microbial DOM alterations could be distinguished based on correlation coefficients with chlorophyll a and often shared molecular features (elemental ratios and mass) with photoreactive compounds. In particular, many photoproducts and some microbial products were identified as potential precursors of disinfection byproducts. Molecular DOM features were used to further predict molecular reactivity for the remaining compounds in the data set based on a random forest model. Our method offers an expandable classification approach to integrate the reactivity of DOM from specific environments and link it to molecular properties and chemistry.


Subject(s)
Drinking Water , Ecosystem , Chlorophyll A , Fresh Water , Machine Learning
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