The importance of charge-transfer interactions in determining chromophoric dissolved organic matter (CDOM) optical and photochemical properties

Abstract

Absorption of sunlight by chromophoric dissolved natural organic matter (CDOM) is environmentally significant because it controls photic zone depth and causes photochemistry that affects elemental cycling and contaminant fate. Both the optics (absorbance and fluorescence) and photochemistry of CDOM display unusual properties that cannot easily be ascribed to a superposition of individual chromophores. These include (i) broad, unstructured absorbance that decreases monotonically well into the visible and near IR, (ii) fluorescence emission spectra that all fall into a single envelope regardless of the excitation wavelength, and (iii) photobleaching and photochemical quantum yields that decrease monotonically with increasing wavelength. In contrast to a simple superposition model, these phenomena and others can be reasonably well explained by a physical model in which charge-transfer interactions between electron donating and accepting chromophores within the CDOM control the optical and photophysical properties. This review summarizes current understanding of the processes underlying CDOM photophysics and photochemistry as well as their physical basis.

Formation of Chromophoric Dissolved Organic Matter by Bacterial Degradation of Phytoplankton-Derived Aggregates

“…Aggregation during particle formation could bring aromatic aldehydes and ketones in close proximity with hydroxylated benzoic acid derivatives through the microbial reprocessing into more complex molecules such as RDOM (Lechtenfeld et al, 2015). The presence of these molecules in the same moiety could facilitate charge transfer interactions between electron acceptors and donors, which has been suggested for lignin derivatives (Del Vecchio and Blough, 2004;Baluha et al, 2013;Sharpless and Blough, 2014). While the biochemical pathways and ecological ramifications of the planktonic CDOM phenomenon remain elusive, we can be certain that not all oceanic CDOM is terrestrially-derived and plankton are important sources of RDOM to the deep ocean.…”

Advanced Residuals Analysis for Determining the Number of PARAFAC Components in Dissolved Organic Matter

“…In this case the DOM samples were collected along gradients of concentration (i.e., full and size-fractionated EEMs), sizes (range, 0.31-28 kDa), and tree species/headwaters, all of which demonstrate shifts in the location of peak maxima that may be associated with changing electronic interactions, particularly in regions associated with humic-like material. 14,16,21 It is therefore reasonable to expect that peak locations may shift slightly from sample to sample, causing distorted edges in the associated component.…”

“…This is particularly likely for humic-like components, since there is evidence that their fluorescence signature arises from chargetransfer interactions, which can cause the same fluorophore to manifest a slightly different fluorescence signature when the identity of proximate molecules is altered by, for example, conformational changes. 13,14 Such under-specification of PARAFAC models can lead to inconsistencies in the behavior of components both within and across experiments. The combination of correlation-dependent factor identity and acceptance based on split-half analysis thus places severe limitations on the differences that can be detected between EEMs of DOM with disparate fluorescence properties, and those collected over experimentally controlled gradients, potentially leading to erroneous conclusions about the behavior and identity of fluorescent components.…”

“…The structure of components modelled by PARAFAC can therefore be confounded by sample sets that are not large enough to describe the variation in fluorescence signatures when the data set is split into parts for split-half analysis. For example, if fluorophores exist in only few samples in a set of EEMs (e.g., leaf leachates 16,19 ) or if DOM is exposed to treatment along a gradient that causes incremental changes in fluorescence (e.g., size fractionation 14,[20][21][22] ), then the PARAFAC models generated from split halves will likely contain components with slightly different fluorescence spectra. Such differences may prevent validation using split-half analysis, the success of which in turn requires the exclusion of samples with distinct spectra as ''outliers'' for the sake of building a coherent model.…”

“…11,12 The output of the PARAFAC algorithm is thus a set of factors (i.e., components) and corresponding loadings that represent the observed fluorescence patterns in a set of EEMs. Despite uncertainty about the molecules and interactions that produce fluorescence in DOM, 13,14 PARAFAC has been useful for characterizing DOM by end member and tree species, 15,16 tracing it through ecosystems and ecosystem processes, 17,18 and assessing its functional effectiveness in natural and engineered systems. 3,6,8,9 The detection of components in PARAFAC relies upon correlations between Ex/Em pairs, which require consistent relationships through a large portion of a data set.…”