A data-driven approach for understanding the structure dependence of redox activity in humic substances

Humic substances (HS) can facilitate electron transfer during biogeochemical processes due to their redox properties, but the structure-redox activity relationships are still difficult to describe and poorly understood. Herein, the linear (Partial Least Squares regressions; PLS) and nonlinear (artificial neural network; ANN) models were applied to monitor the structure dependence of HS redox activities in terms of electron accepting (EAC), electron donating (EDC) and overall electron transfer capacities (ETC) using its physicochemical features as input variables. The PLS model exhibited a moderate ability with R² values of 0.60, 0.53 and 0.65 to evaluate EAC, EDC and ETC, respectively. The variable influence in the projection (VIP) scores of the PLS identified that the phenols, quinones and aromatic systems were particularly important for describing the redox activities of HS. Compared with the PLS model, the back-propagation ANN model achieved higher performance with R² values of 0.81, 0.65 and 0.78 for monitoring the EAC, EDC and ETC, respectively. Sensitivity analysis of the ANN separately identified that the EAC highly depended on quinones, aromatics and protein-like fluorophores, while the EDC depended on phenols, aromatics and humic-like fluorophores (or stable free radicals). Additionally, carboxylic groups were the best indicator for evaluating both the EAC and EDC. Good model performances were obtained from the selected features via the PLS and sensitivity analysis, further confirming the accuracy of describing the structure-redox activity relationships with these analyses. This study provides a potential approach for identifying the structure-activity relationships of HS and an efficient machine-learning model for predicting HS redox activities.

A study of peatland-derived dissolved organic matter from headstream to sea using multiple analytical tools

The River Thurso, North Scotland, receives substantial terrestrial deliveries of dissolved organic matter (DOM) leached from Europe's most extensive blanket bogs. The relatively short distance between peatlands and coastal ocean offers potential for research to investigate source-to-sea processing of terrigenous dissolved organic carbon (DOC). Here, we determined DOC concentrations in the bulk (< 0.4 μm), truly dissolved (< 5 kDa), and colloidal fraction (5 kDa - 0.4 μm) as well as DOM absorbance and fluorescence spectra during two river catchment surveys and two corresponding coastal plume surveys, in early spring (1st sampling period) and late spring (2nd sampling period). DOC concentrations ranged from 79 to 3799 μM in early spring and from 115 to 5126 μM in late spring. DOM exhibited conservative mixing across the plume in both surveys, but the plume extended further offshore in the second survey due to a pulse of freshwater caused by recent rainfall. Fluorescence excitation-emission matrices (EEMs) and fluorescence indices revealed that the flushed DOM was humic-like, recently synthesized DOM. Coupled with C/N ratio analyses and molecular weight fractionation, the fluorescence indices also provided evidence for the gradual altering of DOM characteristics along the bog - headstream - loch - river continuum. The same analytical tools revealed that seasonal variations occurred within the DOM pool of marine origin, i.e., greater abundance of low-molecular weight bacterial or algal DOM in the late spring survey. The time scale of such variations relative to the flushing time of water through the aquatic continuum should be taken into account when interpreting the DOM property-salinity distributions of major river plumes.

Linking fluorescence spectroscopy to diffuse soil source for dissolved humic substances in the Daning River, China

Dissolved organic matter collected in Daning River (China) in July 2009 was investigated with parallel factor analysis (PARAFAC) and fluorescence spectroscopy with the aim of identifying the origin of dissolved humic substance (HS) components. Two HS-like fluorescence components (peak M and C) with excitation/emission (ex/em) maxima at 305/406 nm and 360/464 nm showed relatively uniform distribution in the vertical direction for each sampling site but a trend of accumulation down the river, independent of the highly heterogeneous water environment as implicated by water quality parameters (i.e., water temperature, algae density, chlorophyll a, dissolved oxygen, dissolved organic carbon, pH, conductivity and turbidity), while an amino acid/protein-like component (peak T; ex/em = 280/334 nm) was quite variable in its spatial distribution, implying strong influence from point sources (e.g. sewage discharge) and local microbial activities. The fluorescence intensity (F max in Raman units) at these ex/em wavelength pairs fell in the range of 0.031-0.358, 0.051-0.224 and 0.026-0.115 for peak T, M and C, respectively. In addition, the F max values of peak C covaried with M (i.e. C = 0.503 ×M, p < 0.01, R (2) = 0.973). Taken together, these results indicate that peak M and C originated primarily and directly from the same soil sources that were diffusive in the catchment, but peak T was more influenced by local point sources (e.g. wastewater discharge) and in situ microbial activities. This study presents new insights into the currently controversial origin of some HS components (e.g."peak M", as commonly referred to in the literature). This study highlights that natural water samples should be collected at various depths in addition to along a river/stream flow path so as to better evaluate the origin of HS fluorescence components.