The chemical structures of dissolved organic compounds in natural waters, including the degree of aromaticity, affect their physical, chemical, and biological properties and ultimately the fate of carbon in aquatic systems and during water treatment. Herein, a new fluorescence-based aromaticity index named ARIX is shown to link the composition of aquatic dissolved organic matter to its aromaticity across diverse aquatic systems in both bulk DOM and extracts. ARIX predicts SUVA, a widely used proxy of aromaticity, more accurately than the prevailing optical indices. It also predicts the percentage of polycyclic aromatic and polyphenolic molecular formulas determined by FT-ICR MS and the ratio of "humic substances" to "building blocks" fractions determined by LC-OCD, indicating that it is additionally a proxy of DOM molecular weight. In waterbodies exhibiting decoupling between DOC and absorbance linked to biogeochemical processing, DOC concentrations are more accurately predicted by using a multilinear model to account for interactions between light absorption and aromaticity. The results deliver new insights into widely discussed trends in DOM optical properties and the molecular structures underlying optical measurements in the aquatic milieu. They further represent an important step toward improved real-time monitoring of DOC concentration, reactivity, and fate.

Labile organic carbon is a major nutrient, controlling microbial activity in aquatic ecosystems and contributing to the global cycling of carbon. During the production and distribution of drinking water, labile carbon fractions often escape treatment, which threatens water quality and biostability. This study proposes and compares two rapid methods for monitoring the production and removal of labile organic carbon in freshwater. One method measures the consumption of oxygen by bacteria during their initial exponential growth phase and uses this to predict how much labile organic carbon is present. The other method uses an a priori model of the fluorescence composition of dissolved organic matter to estimate the relative amount of biodegradable carbon fractions. In water treatment plants and in lab-scale experiments, both methods showed selectivity for biodegradable fractions of natural organic matter and indicated similar changes in scale and direction when water samples were exposed to biodegradation, with higher precision for the fluorescence measurement (coefficient of variation similar to 1.5%) compared to the oxygen method (coefficient of variation similar to 15%). Software is provided to aid in the implementation of these new methods, enabling their exploration and refinement in future studies.

Quantifying organic micropollutants (OMPs) in aquatic environments and assessing their removal by water treatment requires expensive and time-consuming analyses typically using liquid chromatographic separation and tandem mass spectrometry (LC-MS/MS). In this study, we evaluated the potential for detecting fluorescent OMPs via spectroscopy, which is cheap, rapid, and widely accessible. The method involved using a priori PARAFAC models to eliminate interfering background fluorescence emitted by naturally occurring dissolved organic matter. Of 20 screened pharmaceutical OMPs, three (ciprofloxacin, naproxen, and zolpidem) with calculated fluorescence quantum yields 0.14, 0.21, and 0.71, respectively, could be quantified in the low mu g L-1 range when added alone or in combination to water samples without any sample pretreatment other than filtration and pH adjustment. Limits of detection for all three OMPs were 1.0-3.3 mu g L-1 in surface waters, while in wastewater, they were 0.6-9.0 mu g L-1 for ciprofloxacin and naproxen and 1.0-2.6 mu g L-1 for zolpidem. Given the high cost of pharmaceutical analyses and widespread availability of fluorometers, the new approach will improve access to rapid and cost-effective results by supporting data-intensive lab-scale studies, wherein the types of OMPs studied and their concentration ranges are under the control of the analyst.

Size exclusion chromatography (SEC) in combination with optical measurements has become a popular form of analysis to characterize dissolved organic matter (DOM) as a function of molecular size. Here, SEC coupled with in-line absorbance scans and fluorescence emission scans was utilized to derive apparent fluorescence quantum yield (Phi(f)) as a function of molecular weight (MW) for DOM. Individual instrument-specific SEC-fluorescence detector correction factors were developed by comparison of an SEC-based excitation emission matrix (EEM) to an EEM generated by a calibrated benchtop fluorometer. The method was then applied to several sample sets to demonstrate how to measure the Phi(f) of unknown DOM samples and to observe changes to Phi(f) following a processing mechanism (ozonation). The Phi(f) of riverine water samples and DOM fulvic acid isolates from Suwannee River and Pony Lake increased from < 0.5% to a maximum of similar to 2.5-3% across the medium- to low-MW range. Following ozonation of PLFA, Phi(f) increased most notably in the large-MIA; fractions (elution volumes < 40 mL). Overall, this method provides a means by which highly fluorescent size fractions of DOM can be identified for more detailed analyses of chemical composition and its changes through different processing mechanisms.

Samples from fifty-five surface water resources and twenty-five drinking water treatment plants in Europe, Africa, Asia, and USA were used to analyse the fluorescence composition of global surface waters and predict aromaticity and treatability from fluorescence excitation emission matrices. Nine underlying fluorescence components were identified in the dataset using parallel factor analysis (PARAFAC) and differences in aromaticity and treatability could be predicted from ratios between components H-ii (lambda(ex)/lambda(em)= 395/521), H-iii (lambda(ex)/lambda(em)= 330/404), P-i, (lambda(ex)/lambda(em)=290/365) and P-ii (lambda(ex)/lambda(em)= 275/302). Component Hii tracked humic acids of primarily plant origin, Hiii tracked weathered/oxidised humics and the "building block" fraction measured by LC-OCD, while Pi and Pii tracked amino acids in the "low molecular weight neutrals" LC-OCD fraction. Ratios between PARAFAC components predicted DOC removal at lab scale for French rivers in standardized tests involving coagulation, powdered activated carbon (PAC), chlorination, ion exchange (IEX), and ozonation, alone and in combination. The ratio Hii/Hiii, for convenience named "PARIX" standing for "PARAFAC index", predicted SUVA according to a simple relationship: SUVA = 4.0 x PARIX (RMSEp=0.55) Lmg(-1)m(-1). These results expand the utility of fluorescence spectroscopy in water treatment applications, by demonstrating the existence of previously unknown relationships between fluorescence composition, aromaticity and treatability that appear to hold across diverse surface waters at various stages of drinking water treatment.

Despite our growing understanding of the global carbon cycle, scientific consensus on the drivers and mechanisms that control dissolved organic carbon (DOC) turnover in aquatic systems is lacking, hampered by the mismatch between research that approaches DOC reactivity from either intrinsic (inherent chemical properties) or extrinsic (environmental context) perspectives. Here we propose a conceptual view of DOC reactivity in which the combination of intrinsic and extrinsic factors controls turnover rates and determines which reactions will occur. We review three major types of reactions (biological, photochemical, and flocculation) from an intrinsic chemical perspective and further define the environmental features that modulate the expression of chemically inherent reactivity potential. Finally, we propose hypotheses of how extrinsic and intrinsic factors together shape patterns in DOC turnover across the land-to-ocean continuum, underscoring that there is no intrinsic DOC reactivity without environmental context. By acknowledging the intrinsic-extrinsic control duality, our framework intends to foster improved modeling of DOC reactivity and its impact on ecosystem services.

Absorbance-based sensors produce large raw attenuation datasets. We developed AbspectroscoPY, an open-source Python toolbox to implement semi-automated processing of these data and explore the full potential of high-frequency measurements.

A study was conducted at a water treatment plant to optimize parallel rapid gravity biofilters for dissolved organic matter (DOM) removal. The biofilters treat urban and agriculturally impacted river water using a commercial non-adsorptive, expanded-clay filter medium. The study aimed to locate the optimal operating conditions via experimental manipulation of the biofilter empty bed contact time (EBCT) during full-scale operation at the plant. During a two-month experiment, contact times in four parallel biofilters were switched to and maintained at 15, 30, 50, and 80 min by manipulating the hydraulic loading on each filter. The removal efficiency of organic matter fractions increased with EBCT for dissolved organic carbon (DOC) and microbial humic-like (F290-420) and protein-like (F-280/340) fluorescent organic matter. Other DOM fractions were largely unaffected by biofiltration, or at slightly higher concentrations in the effluent. Protein-like fluorescence is associated with labile organic matter fractions, which are known to be removed poorly by drinking water treatment barriers apart from biological filters. The results suggest that long contact times (>30 min) have advantages for the operation of some biological filters, especially if placed ahead of barriers that are sensitive to biofouling, e.g., membranes.

The direct sampling method revealed the high treatment capacity of the unsaturated zone and the significant impact of infiltration basin management on microbial communities in managed aquifer recharge (MAR).

Fluorescence and absorbance based sensors for DOC concentration estimations can help in optimizing drinking water production processes.

Dissolved organic matter (DOM) is a complex pool of compounds with a key role in the global carbon cycle. To understand its role in natural and engineered systems, efficient approaches are necessary for tracking DOM quality and quantity. Fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) is very widely used to identify and quantify different fractions of DOM as proxies of DOM source, concentration and biogeochemical processing. A major limitation of the PARAFAC approach is the requirement for a large data set containing many variable samples in which the fractions vary independently. This severely curtails the possibilities to study fluorescence composition and behavior in small or unique datasets. Herein, we present a simple and inexpensive experimental procedure that makes it possible to mathematically decompose a small dataset containing only highly-correlated fluorescent fractions. The approach, which uses widely-available commercial extraction sorbents and previously established protocols to expand the original dataset and inject the missing chemical variability, can be widely implemented at low cost. A demonstration of the procedure shows how a robust six-component PARAFAC model can be extracted from even a river-water dataset with only five bulk samples. Widespread adoption of the procedure for analyzing small fluorescence datasets is needed to confirm the suspected ubiquity of certain DOM fluorescence fractions and to create a shared inventory of ubiquitous components. Such an inventory could greatly simplify and improve the use of fluorescence as a tool to investigate biogeochemical processing of DOM in diverse water sources.

Despite the numerous studies that have investigated the occurrence and fate of plastic particles in the environment, only a limited effort has been devoted toward exploring the characteristics of dissolved organic matter (DOM) leached from microplastics. In this study, using excitation emission matrix-parallel factor analysis (EEM-PARAFAC), we explored the fluorescence signatures of plastic-derived DOM from commonly used plastic materials, which included two polymers (polyvinyl chloride (PVC) and polystyrene (PS)), two additives (diethylhexyl phthalate (DEHP) and bisphenol A (BPA)), and two commercial plastics. The exposure of the selected plastics to UV light facilitated the leaching of DOM measured in terms of dissolved organic carbon and fluorescence intensity. Four fluorescent components were identified, which included three protein/phenol-like components (C1, C3, and C4) and one humic-like component (C2). The C1 and C4 components were highly correlated with the amounts of DOM leached from DEHP and BPA, respectively, under both leaching conditions, while both C2 and C4 presented good correlations with the DOM leached from polymers under UV light. The C4 may serve as a good fluorescence proxy for DOM leached from BPA or BPA-containing plastics. This study highlights the overlooked issue of plastic-derived DOM leaching into the aquatic environment through optical characterization.

Physical and chemical adsorption by aged biological active carbon (BAC) filters were observed for some organic matter fractions, and may represent important removal mechanisms during periods of low microbial activity.

The spectra responsible for natural dissolved organic matter fluorescence in 90 peer-reviewed studies have been compared using new similarity metrics.

The roles of dissolved organic matter (DOM) in microbial processes and nutrient cycles depend on its composition, which requires detailed measurements and analyses. We introduce a package for R, called staRdom (“spectroscopic analysis of DOM in R”), to analyze DOM spectroscopic data (absorbance and fluorescence), which is key to deliver fast insight into DOM composition of many samples. staRdom provides functions that standardize data preparation and analysis of spectroscopic data and are inspired by practical work. The user can perform blank subtraction, dilution correction, Raman normalization, scatter removal and interpolation, and fluorescence normalization. The software performs parallel factor analysis (PARAFAC) of excitation–emission matrices (EEMs), including peak picking of EEMs, and calculates fluorescence indices, absorbance indices, and absorbance slope indices from EEMs and absorbance spectra. A comparison between PARAFAC solutions by staRdom in R compared with drEEM in MATLAB showed nearly identical solutions for most datasets, although different convergence criteria are needed to obtain similar results and interpolation of missing data is important when working with staRdom. In conclusion, staRdom offers the opportunity for standardized multivariate decomposition of spectroscopic data without requiring software licensing fees and presuming only basic R knowledge.

Natural organic matter (NOM) in surface waters negatively impacts drinking water treatment and is a precursor of harmful disinfection by-products (DBPs). Granular activate carbon (GAC) filters are integral components of many drinking water treatment plants (WTPs) due to the ability to remove NOM and organic micro pollutants from raw waters. However, GAC filters lose adsorption capacity and convert to biologically activated carbon (BAC) filter relatively quickly. This paper reports on a full-scale BAC filter modification strategy to enhance short-term NOM removal. This is achieved by adding a small amount of fresh GAC to BAC filters which increases adsorption while maintaining biological degradation of organics by the microbes attached to the BAC. This strategy was implemented at two treatment plants in Sweden. Modified filters showed better removal of humic-like and protein-like NOM fractions than reference filters that did not receive fresh GAC, indicating improved functioning of both adsorption and biological treatment. The result shows that both biodegradation and adsorption mechanism improved within the filters.

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.