Monitoring reverse osmosis performance: Conductivity versus fluorescence excitation–emission matrix (EEM)

Characterizing the interactions between copper ions and dissolved organic matter using fluorescence excitation–emission matrices with two-dimensional Savitzky–Golay second-order differentiation

Transport and accumulation of organic matter in forward osmosis-reverse osmosis hybrid system: Mechanism and implications

The reverse osmosis (RO) technology is currently the leading desalination method. However, until recently, application of RO technology on a large scale has been primarily limited by membrane fouling. The mechanism of fouling is complex, which is not well understood in full-scale plants. Although many studies about modeling and prediction of fouling have been done, in most cases, the experimental data set of lab or pilot scale systems, which may not show fouling characteristics well in full-scale systems were used. In this study, both artificial neural network (ANN) model and tree model (TM) was evaluated to analyze long-term performance of full scale reverse osmosis desalination plant. The results of application of the ANN and TM indicated high correlation coefficients between the measured and simulated output variables. However, it is not easy to use ANN for the full scale plant operation because the final model is not expressed as a form of mathematical functions. TM has advantages over ANN because the model can be obtained as forms of simple function and it showed reasonably high <i>R</i><sup>2</sup>. Therefore, TM is shown to be more adequate than ANN for developing models in which the full-scale RO plant data is considered as an input.

Excitation-emission matrix (EEM) fluorescence spectroscopy has been widely used to characterize dissolved organic matter (DOM) in water and soil. However, interpreting the > 10,000 wavelength-dependent fluorescence intensity data points represented in EEMs has posed a significant challenge. Fluorescence regional integration, a quantitative technique that integrates the volume beneath an EEM, was developed to analyze EEMs. EEMs were delineated into five excitation-emission regions based on fluorescence of model compounds, DOM fractions, and marine waters or freshwaters. Volumetric integration under the EEM within each region, normalized to the projected excitation-emission area within that region and dissolved organic carbon concentration, resulted in a normalized region-specific EEM volume (phi(i,n)). Solid-state carbon nuclear magnetic resonance (13C NMR), Fourier transform infrared (FTIR) analysis, ultraviolet-visible absorption spectra, and EEMs were obtained for standard Suwannee River fulvic acid and 15 hydrophobic or hydrophilic acid, neutral, and base DOM fractions plus nonfractionated DOM from wastewater effluents and rivers in the southwestern United States. DOM fractions fluoresced in one or more EEM regions. The highest cumulative EEM volume (phi(T,n) = sigma phi(i,n)) was observed for hydrophobic neutral DOM fractions, followed by lower phi(T,n) values for hydrophobic acid, base, and hydrophilic acid DOM fractions, respectively. An extracted wastewater biomass DOM sample contained aromatic protein- and humic-like material and was characteristic of bacterial-soluble microbial products. Aromatic carbon and the presence of specific aromatic compounds (as indicated by solid-state 13C NMR and FTIR data) resulted in EEMs that aided in differentiating wastewater effluent DOM from drinking water DOM.

Tracking the sources of dissolved organic matter under bio- and photo-transformation conditions using fluorescence spectrum-based machine learning techniques

Comparison of reverse osmosis membrane fouling profiles from Australian water recycling plants

Spatial gradients and molecular transformations of DOM, DON and DOS in human-impacted estuarine sediments

Effects of reverse osmosis isolation on reactivity of naturally occurring dissolved organic matter in physicochemical processes

1. Although the mass of dissolved organic matter (DOM) often exceeds that of living organisms in freshwaters, little is known about the roles of its constituent molecules as sources of energy and information for aquatic organisms. In the present review attention is focused on free amino acids (FAA) and humic substances (HS) as examples of labile and refractory components within DOM.2. The following questions are addressed. (i) What are spatiotemporal patterns in the distribution of DOM, HS and FAA? (ii) What are the origins of the components of DOM and how are their concentrations regulated? (iii) What is the significance of the spatial and temporal distributional patterns of DOM, HS and FAA to detritivorous invertebrates and other organisms associated with them? (iv) What is the relevance of DOM to the food web concept and to the biochemical ecology of freshwater ecosystems?3. Concentrations of DOM, FAA and HS within lentic ecosystems are ranked as follows: Sediment pore water > Air–water interface > Midwater column. Comparisons between water bodies show that the concentrations of labile constituents of DOM, such as FAA, are usually positively correlated with base cations, nutrients and biological activity. In contrast, HS concentrations are negatively correlated with base cations or nutrients but positively correlated with the rate of biological degradation (the maximum values occurring in the autumn). The FAA : HS ratios might serve therefore as an indicator of the potential productivity of a water body.4. External sources of DOM in general, and FAA and HS in particular, include rainwater, windborne material, surface flow and groundwater. The relative importance of these allochthonous sources of DOM decreases along the length of lotic ecosystems and also with increase in size of lentic ecosystems. Internal sources of FAA and HS include synthesis or polymerization from existing organic matter, degradation of organic matter and release from both living and dead organisms. The net accumulation of DOM released by living bacteria, phytoplankton, epilithon, macrophytes and invertebrates is much reduced due to heterotrophic uptake. Hence, most of the allochthonous DOM in freshwater originates from dead organic matter deposited on the sediment. Phytoplankton‐dominated ecosystems may, however, differ, as most of their DOM may be recycled within the water column.5. The factors that determine the external concentrations of DOM, FAA and HS are discussed. Evidence is cited in support of the following testable hypotheses. (i) The rates of production of DOM components will be favoured by increasing base cation and nutrient concentrations. (ii) Colloidal clay, base cations, biopolymers and living organisms, particularly bacteria, facilitate the removal of HS. Consequently, base‐rich eutrophic waters tend to have lower HS concentrations than oligotrophic, base‐deficient waters. (iii) As a result of higher productivity and selective removal of FAA, eutrophic waters tend to have higher FAA concentrations than those that are oligotrophic.6. Labile DOM components, such as FAA, act as sources of information for aquatic organisms. More research is needed in this field. There is a consensus that DOM acts as an important source of energy for aquatic bacteria, thus forming the microbial loop. However, higher eukaryotic organisms also utilize DOM, including components released by bacteria and plants as metabolic end‐products and photoassimilates, respectively. As a result, these DOM components may be more important as food for macrodecomposers than the microdecomposers themselves. HS may also benefit aquatic organisms by promoting their growth and protecting them from inimical forces. Conversely, the removal of photons and the release of toxins by HS may be detrimental to aquatic organisms.7. It is concluded that the central dogma of the foodweb, and its implicit assumption that the energy flow in aquatic ecosystems can be quantified solely by measuring rates of photosynthesis, ingestion of solid food and its digestion by higher organisms, is invalid. To extend our understanding of the role of DOM as a source of nutrition and information to aquatic organisms it is suggested that the subject should be studied within the context of ‘modules’ which have the following properties: (i) the components have co‐evolved; (ii) the more vulnerable components will have protective mechanisms; (iii) the components will derive mutual benefits from co‐existence; (iv) sedentary components will release kairomonal attractants or developmental primers; (v) living components will exchange energy and information; (vi) the module will collapse following the removal of strongly interactive keystone species. An example of a three‐component, three‐subset module, is provided by tubificid worms, epilithic bacteria and algae. A more complex module consisting of pulmonate snails, associated macrophytes, their epiphytic bacteria and algae has four components and six subsets. The elucidation of the interactive mechanisms within such modules demands an interdisciplinary approach, involving microbiology, biochemistry and behavioural biology.

Seasonal transformations of dissolved organic matter and organic phosphorus in a polymictic basin: Implications for redox-driven eutrophication

Enhanced DOC removal using anion and cation ion exchange resins

6 - Excitation-emission fluorescence mapping and multiway techniques for profiling natural organic matter

Advances in water chemistry in the last decade have improved our knowledge about the genesis, composition, and structure of dissolved organic matter, and its effect on the environment. Improvements in analytical technology, for example Fourier-transform ion cyclotron (FT-ICR) mass spectrometry (MS), homo and hetero-correlated multidimensional nuclear magnetic resonance (NMR) spectroscopy, and excitation emission matrix fluorimetry (EEMF) with parallel factor (PARAFAC) analysis for UV-fluorescence spectroscopy have resulted in these advances. Improved purification methods, for example ultrafiltration and reverse osmosis, have enabled facile desalting and concentration of freshly collected DOM samples, thereby complementing the analytical process. Although its molecular weight (MW) remains undefined, DOM is described as a complex mixture of low-MW substances and larger-MW biomolecules, for example proteins, polysaccharides, and exocellular macromolecules. There is a general consensus that marine DOM originates from terrestrial and marine sources. A combination of diagenetic and microbial processes contributes to its origin, resulting in refractory organic matter which acts as carbon sink in the ocean. Ocean DOM is derived partially from humified products of plants decay dissolved in fresh water and transported to the ocean, and partially from proteinaceous and polysaccharide material from phytoplankton metabolism, which undergoes in-situ microbial processes, becoming refractory. Some of the DOM interacts with radiation and is, therefore, defined as chromophoric DOM (CDOM). CDOM is classified as terrestrial, marine, anthropogenic, or mixed, depending on its origin. Terrestrial CDOM reaches the oceans via estuaries, whereas autochthonous CDOM is formed in sea water by microbial activity; anthropogenic CDOM is a result of human activity. CDOM also affects the quality of water, by shielding it from solar radiation, and constitutes a carbon sink pool. Evidence in support of the hypothesis that part of marine DOM is of terrestrial origin, being the result of a long-term carbon sedimentation, has been obtained from several studies discussed herein.

For further understanding the geochemical characteristics of dissolved organic matter (DOM) in "reservoir-type" lake, in this study a typical "reservoir-type" lake, Changshou Lake located in inlands of Three Gorges Reservoir areas, was selected to investigate the composition, sources and spatial distributions of chromophoric DOM (CDOM) in this lake, through UV-Vis and three-dimensional fluorescence spectroscopy combined within analysis of riparian eco-system differences. The results showed that DOM concentrations including dissolved organic carbon (DOC) and CDOM abundance in different sampling sites varied spatially to a certain degree, in contrast to fluorescence component of DOM showing a constant level. In backwater zone (also called stagnant zone alternatively), due to accumulation of DOM and limited impact of terrestrial contribution, the endogenesis (autochthonous production) was the predominant geochemical process showing an obvious "authigenic-control" characteristic, and relatively lower aromaticity and molecular weight. In comparison, sampling sites surrounding artificial forests and tourism development, the highly humic (highly aromatic) substances resulted from terrestrial inputs were the main source, but discharge due to human activities was also responsible for highly protein-like component observed in DOM. Additionally, in the entry zones of lake from upstream river, DOM was affected by fruit plantations and residences, contribution from upstream river could also be neglected. From the other aspects, some significant correlations were also observed, which were independent of riparian eco-system differences, for example, the SUVA280 versus S(275-295) (negative), CDOM versus FDOM (positive), and CDOM and S(275-295) (negative), indicating the correlation was an intrinsic property of DOM that could not be affected by the surrounding environment. Meanwhile, the main chromophoric component of CDOM in Changshou Lake was high molecular weight (HMW) components within highly aromatic structures. At least, 51% of CDOM dynamic could be explained by changes of FDOM, especially in backwater zone the co-variance was more obvious. Furthermore, when the traditional fluorescence index (FI) could not comprehensively explain the differences of DOM sources due to very similar (statistically insignificant) values, integration of UV-Vis and fluorescence spectral characteristics and detailed discussion of riparian eco-system differences, might be an important way to help further resolution of DOM composition and sources in aquatic environments, such as lake, river and watershed.

We report a data set of dissolved organic carbon (DOC) concentration and dissolved organic matter (DOM) composition (stable carbon isotope signatures, absorption and fluorescence properties) obtained from samples collected in Lake Victoria, a large lake in East Africa. Samples were collected in 2018–2019 along a bathymetric gradient (bays to open waters), during three contrasting seasons: long rainy, short rainy and dry, which corresponded to distinctly water column mixing regimes, respectively, stratified, semi-stratified and mixed regimes. Eight DOM components from parallel factor analysis (PARAFAC) were identified based on three-dimensional excitation–emission matrices (EEMs), which were aggregated into three main groups of components (microbial humic-like, terrestrial humic-like, protein-like). Spatially, the more productive bays were characterized by higher DOM concentration than deeper more offshore waters (fluorescence intensity and DOC were ~ 80% and ~ 30% higher in bays, respectively). Seasonally, the DOM pool shifted from protein-like components during the mixed regime to microbial humic-like components during the semi-stratified regime and to terrestrial humic-like components during the stratified regime. This indicates that pulses of autochthonous DOM derived from phytoplankton occurred when the lake was mixing, which increased the availability of dissolved inorganic nutrients. Subsequently, this freshly produced autochthonous DOM was microbially processed during the following semi-stratified regime. In the open waters, during the stratified regime, only terrestrial refractory DOM components remained because the labile and fresh stock of DOM created during the preceding mixed season was consumed. In the bays, the high terrestrial refractory DOM during the stratified regime may be additionally due to the allochthonous DOM input from the runoff. At the scale of the whole lake, the background refractory DOM probably comes mainly from precipitation and followed by river inputs.