Dissolved organic matter (DOM) in aquatic environments forms a vast reservoir of carbon present as a complex supermixture of compounds. An efficient approach to tracking the production and removal of specific DOM fractions is needed across disciplines, for purposes that range from improving global carbon budgets to optimizing water treatment in engineered systems. Although widely used to study DOM, fluorescence spectroscopy has yet to deliver specific fractions with known spectral properties and predictable distributions. Here, we mathematically isolate four visible-wavelength fluorescent fractions in samples from contrasting lake, river, and ocean environments. Using parallel factor analysis (PARAFAC), we show that most measured fluorescence in environmental samples can be explained by ubiquitous spectra with nearly stable optical properties and photodegradation behaviors over environmental pH gradients. Sample extraction changed bulk fluorescence spectra but not the number or shape of underlying PARAFAC components, while photobleaching preferentially removed the two longest-wavelength components. New approaches to analyzing fluorescence data sets incorporating these findings should improve the interpretation of DOM fluorescence and increase its utility for tracing organic matter biogeochemistry in aquatic systems.

Absorbance and fluorescence spectroscopy are economical tools for tracing the supply, turnover and fate of dissolved organic matter (DOM). The colored and fluorescent fractions of DOM (CDOM and FDOM, respectively) are linked by the apparent fluorescence quantum yield (AQY) of DOM, which reflects the likelihood that chromophores emit fluorescence after absorbing light. Compared to the number of studies investigating CDOM and FDOM, few studies have systematically investigated AQY spectra for DOM, and linked them to fluorescence quantum yields () of organic compounds. To offer a standardized approach, a MATLAB toolbox for the determination of apparent quantum yields of DOM (aquaDOM), featuring two calculation approaches, was developed and used to derive AQYs for samples from the Norwegian Sea. of the organic compounds varied between 0.00079 and 0.35, whereas the average AQY for DOM samples at 350 nm was 0.011 ± 0.003. The AQY at 350 nm increased with depth, while the AQY at 250 nm showed no trend. Laboratory tests indicated that of compound mixtures are additive and represent an intermediate of the constituents. Additionally, the presence of non-fluorescent chromophores greatly suppressed calculated AQYs. Similar trends in the DOM AQY at 350 nm were observed in natural samples. We therefore hypothesize that fluorescence AQYs can indicate changes in the relative abundances of CDOM and FDOM. Additionally, the optical properties of 15 potential DOM constituents were determined and compared to more than 200 modeled spectra (PARAFAC components) in the OpenFluor database. Apparent matches, based on spectral similarity, were subsequently evaluated using molar fluorescence and absorbance. Five organic compounds were potential matches with PARAFAC components from 16 studies; however, the ability to confirm matches was limited due to multiple compounds exhibiting very similar spectra. This reiterates the fact that spectral similarity alone is insufficient evidence of the presence of particular compounds, and additional evidence is required.

Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM) spectroscopy in full spectral (60 emission and 34 excitation wavelengths) and chromatographic resolution (<1 Hz), to enable the mathematical decomposition of fluorescence on an individual sample basis by parallel factor analysis (PARAFAC). The approach allowed cross-system comparisons of molecular size distributions for individual fluorescence components obtained from independent data sets. Spectra extracted from allochthonous DOM were highly similar. Allochthonous and autochthonous DOM shared some spectra, but included unique components. In agreement with the supramolecular assembly hypothesis, molecular size distributions of the fluorescence fractions were broad and chromatographically unresolved, possibly representing reoccurring fluorophores forming noncovalently bound assemblies of varying molecular size. Samples shared underlying fluorescence components that differed in their size distributions but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical opportunities for elucidating the origins and biogeochemical properties of FDOM.

Investigating the biogeochemistry of dissolved organic matter (DOM) requires the synthesis of data from several complementary analytical techniques. The traditional approach to data synthesis is to search for correlations between measurements made on the same sample using different instruments. In contrast, data fusion simultaneously decomposes data from multiple instruments into the underlying shared and unshared components. Here, Advanced Coupled Matrix and Tensor Factorization (ACMTF) was used to identify the molecular fingerprint of DOM fluorescence fractions in Arctic fjords. ACMTF explained 99.84% of the variability with six fully shared components. Individual molecular formulas were linked to multiple fluorescence components and vice versa. Molecular fingerprints differed in diversity and oceanographic patterns, suggesting a link to the biogeochemical sources and diagenetic state of DOM. The fingerprints obtained through ACMTF were more specific compared to traditional correlation analysis and yielded greater compositional insight. Multivariate data fusion aligns extremely complex, heterogeneous DOM data sets and thus facilitates a more holistic understanding of DOM biogeochemistry.