Fluorescence as a potential monitoring tool for recycled water systems: a review

Effect of lysozyme combined with hydrothermal pretreatment on excess sludge and anaerobic digestion

Anaerobic digestion (AD) is widely employed for sludge stabilization and waste reduction. However, the slow hydrolysis process hinders methane production and leads to prolonged sludge issues. In this study, an efficient and eco-friendly lysozyme pre-treatment method was utilized to address these challenges. By optimizing lysozyme dosage, hydrolysis and cell lysis were maximized. Furthermore, lysozyme combined with hydrothermal pretreatment enhanced overall efficiency. Results indicate that: (1) When lysozyme dosage reached 90 mg/g TS after 240 min of pretreatment, SCOD, soluble polysaccharides, and protein content reached their maxima at 855.00, 44.09, and 204.86 mg/L, respectively. This represented an increase of 85.87%, 365.58%, and 259.21% compared to the untreated sludge. Three-dimensional fluorescence spectroscopy revealed the highest fluorescence intensity in the IV region (soluble microbial product), promoting microbial metabolic activity. (2) Lysozyme combined with hydrothermal pretreatment significantly increased SCOD, soluble proteins, and polysaccharide release from sludge, reducing SCOD release time. Orthogonal experiments identified Group 3 as the most effective for SCOD and soluble polysaccharide release, while Group 9 released the most soluble proteins. The significance order of factors influencing SCOD, soluble proteins, and polysaccharide release is hydrothermal temperature > hydrothermal time > enzymatic digestion time.(3) The lysozyme-assisted hydrothermal pretreatment group exhibited the fastest release and the highest SCOD concentration of 8,135.00 mg/L during anaerobic digestion. Maximum SCOD consumption and cumulative gas production increased by 95.89% and 130.58%, respectively, compared to the control group, allowing gas production to conclude 3 days earlier.

ZnO/g-C3N4 photocatalyst activated by low-pressure ultraviolet for restoring the SWASV signals: A fast pretreatment method for electrochemically detecting Cd2+ and Pb2+ in soil extracts

Soil organic matter (SOM) significantly impacts the detection accuracy of Cd2+ and Pb2+ using square wave anodic stripping voltammetry (SWASV) due to the complexation of SOM to heavy metal ions (HMIs), thereby attenuating SWASV signals. This study explored an effective pretreatment method that combined low-pressure ultraviolet (LPUV) photolysis with the ZnO/g-C3N4 photocatalyst, activating the photocatalyst to generate highly oxidative •OH radicals and O2•- radicals, which effectively disrupted this complexation, consequently restoring the electroactivity of HMIs and achieving high-fidelity SWASV signals. The parameters of the LPUV-ZnO/g-C3N4 photocatalytic system were meticulously optimized, including the pH of photolysis, duration of photolysis, g-C3N4 mass fraction, and concentration of the photocatalyst. Furthermore, the ZnO/g-C3N4 photocatalyst was thoroughly characterized, with an in-depth investigation on the synergistic interaction between ZnO and g-C3N4 and the mechanisms contributing to the restoration of SWASV signals. This synergistic interaction effectively separated charge carriers and reduced charge transfer resistance, enabling photogenerated electrons (e-) from the conduction band of g-C3N4 to be quickly transferred to the conduction band of ZnO, preventing the recombination of e- and hole (h+) and generating more radicals to disrupt complexation and restore the SWASV signals. Finally, the analysis of HMIs in real soil extracts using the proposed pretreatment method demonstrated high detection accuracy of 94.9% for Cd2+ and 99.8% for Pb2+, which validated the feasibility and effectiveness of the proposed method in environmental applications.

Differential responses of the electron transfer capacities of soil humic acid and fulvic acid to long-term wastewater irrigation

Wastewater irrigation is used to supplement agricultural irrigation because of its benefits and freshwater resource scarcity. However, whether wastewater irrigation for many years affects the electron transfer capacity (ETC) of natural organic matter in soil remains unclear, and organic matter could influence the decomposition and mineralization of substances with redox characteristics in soil through electron transfer, ultimately affecting the soil environment. The composition of soil humic substances (HS) is highly complex, and the effects of soil humic acid (HA) and fulvic acid (FA) on ETC is poorly understood. In this study, we separately evaluated the responses of the electron-accepting capacity (EAC) and electron-donating capacity (EDC) of soil HA and FA in agricultural fields to various durations of wastewater irrigation. Results showed that the EAC of HA and FA increased significantly with increasing the duration of wastewater irrigation. When wastewater irrigation lasted for 56 years, the EAC of HA showed a higher increment (590 %) than that of FA (223 %). The EDC of soil HA and FA, conversely, decreased compared to the control, with the highest reduction of 35.6 % for HA and 65.9 % for FA. Specifically, the EDC of HA gradually decreased starting from 29 years of wastewater irrigation, whereas the decrease in the EDC of FA exhibited no clear pattern in relation to the duration of wastewater irrigation. Increased soil organic matter and total nitrogen content under long-term wastewater irrigation led to an increase in sucrase and phosphatase activities, along with an increase in EAC and a decrease in EDC of HS. This suggests that soil enzyme activities may ultimately lead to changes in ETC. The results of this research provide practical insights into the redox system in soil and its driving role in soil organic matter transformation and nutrient cycling under wastewater irrigation.

Traceability of gushing water in the MiddleRoute of the South-to-North Water Diversion (Beijing section) through the river area

To trace the origin of the gushing water in the riverine area of the Beijing section of The Middle Route of South-to-North Water Diversion Project, a dataset was established comprising water chemistry, three-dimensional fluorescence spectra, and stable isotopes for different water bodies. Results indicated significant differences in Electrical Conductivity (EC), Total Dissolved Solids (TDS), and Ca2+ concentration among the gushing water, river water, and the water from the Middle Route of South-to-North Water Diversion Project (MRSD). Analysis using parallel factor analysis (PARAFAC) and fluorescence index revealed that dissolved organic matter (DOM) in the MRSD mainly originated from endogenous sources, while the river water and gushing water showed influences from both endogenous and exogenous sources. Nitrate sources varied among the water bodies, with distinct contributions from domestic sewage and fertilizer sources. The evaporation lines of river water and gushing water exhibited similar intercepts and slopes, but their intercepts and slopes are much smaller than those of the MRSD, suggesting stronger kinetic evaporative fractionation. In conclusion, the gushing water in the riverine area of the MRSD was determined to originate from the river, providing a fast and efficient method for gushing water source identification.

Characterization and spatiotemporal variations of fluorescent dissolved organic matter in leachate from old landfill-derived incineration residues and incombustible waste

Dissolved organic matter (DOM) influences the bioavailability and behavior of trace metals and other pollutants in landfill leachate. This research characterized fluorescent dissolved organic matter (FDOM) in leachate from an old landfill in Japan during a 13-month investigation. We employed excitation-emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC) to deconvolute the FDOM complex mixture into three fluorophores: microbial humic-like (C1), terrestrial humic-like (C2), and tryptophan-like fluorophores (C3). These FDOM components were compared with findings from other studies of leachate in landfills with different waste compositions. The correlations among EEM-PARAFAC components, dissolved organic carbon (DOC) concentration, and ultraviolet-visible and fluorescence indices were evaluated. The FDOM in leachate varied spatially among old and extended leachate collected in the landfill and leachate treatment facility. The FDOM changed temporally and decreased markedly in August 2019, November 2019, and April 2020. The strong positive correlation between HIX and %C2 (r = 0.87, ρ = 0.91, p < 0.001)) implies that HIX may indicate the relative contribution of terrestrial humic-like components in landfill leachate. The Fmax of C1, C2, and C3 and the DOC concentration showed strong correlations among each other (r > 0.72, ρ > 0.78, p < 0.001) and positive correlations with leachate level (r > 0.41, p < 0.001), suggesting the importance of hydrological effects and leachate pump operation on FDOM.

Insights into the characteristics of changes in dissolved organic matter fluorescence components on the natural attenuation process of toluene

Natural attenuation (NA) is of great significance for the remediation of contaminated groundwater, and how to identify NA patterns of toluene in aquifers more quickly and effectively poses an urgent challenge. In this study, the NA of toluene in two typical soils was conducted by means of soil column experiment. Based on column experiments, dissolved organic matter (DOM) was rapidly identified using fluorescence spectroscopy, and the relationship between DOM and the NA of toluene was established through structural equation modeling analysis. The adsorption rates of toluene in clay and sandy soil were 39 % and 26 %, respectively. The adsorption capacity and total NA capacity of silty clay were large. The occurrence of fluorescence peaks of protein-like components and specific products indicated the occurrence of biodegradation. Arenimonas, Acidovorax and Brevundimonas were the main degrading bacteria identified in Column A, while Pseudomonas, Azotobacter and Mycobacterium were the main ones identified in Column B. The pH, ORP, and Fe(II) were the most important factors affecting the composition of microbial communities, which in turn affected the NA of toluene. These results provide a new way to quickly identify NA of toluene.

An investigation of cyanobacteria, cyanotoxins and environmental variables in selected drinking water treatment plants in New Jersey

Harmful Algal Blooms (HAB) have the potential to impact human health primarily through their possible cyanotoxins production. While conventional water treatments can result in the removal of unlysed cyanobacterial cells and low levels of cyanotoxins, during severe HAB events, cyanotoxins can break through and can be present in the treated water due to a lack of adequate toxin treatment. The objectives of this study were to assess the HAB conditions in drinking water sources in New Jersey and investigate relationships between environmental variables and cyanobacterial communities in these drinking water sources. Source water samples were collected monthly from May to October 2019 and analyzed for phytoplankton and cyanobacterial cell densities, microcystins, cylindrospermopsin, Microcystis 16S rRNA gene, microcystin-producing mcyB gene, Raphidiopsis raciborskii-specific rpoC1 gene, and cylindrospermopsin-producing pks gene. Water quality parameters included water temperature, pH, dissolved oxygen, specific conductance, fluorescence of phycocyanin and chlorophyll, chlorophyll-a, total suspended solids, total dissolved solids, dissolved organic carbon, total nitrogen, ammonia, and total phosphorus. In addition to source waters, microcystins and cylindrospermopsin were analyzed for treated waters. The results showed all five selected New Jersey source waters had high total phosphorus concentrations that exceeded the established New Jersey Surface Water Quality Standards for lakes and rivers. Commonly found cyanobacteria were identified, such as Microcystis and Dolichospermum. Site E was the site most susceptible to HABs with significantly greater HAB variables, such as extracted phycocyanin, fluorescence of phycocyanin, cyanobacterial cell density, microcystins, and Microcystis 16S rRNA gene. All treated waters were undetected with microcystins, indicating treatment processes were effective at removing toxins from source waters. Results also showed that phycocyanin values had a significantly positive relationship with microcystin concentration, copies of Microcystis 16S rRNA and microcystin-producing mcyB genes, suggesting these values can be used as a proxy for HAB monitoring. This study suggests that drinking water sources in New Jersey are vulnerable to forthcoming HAB. Monitoring and management of source waters is crucial to help safeguard public health.

Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios

Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV-Vis) spectroscopy to identify membrane breakage. It aims to unravel more comprehensive information, improve detection sensitivity and selectivity, and enable real-time monitoring capabilities. Fluorescence and UV-Vis data are extracted through variance partitioning analysis (VPA) and integrated through a decision tree algorithm to form a superior system with enhanced discrimination capabilities. VPA improves discrimination efficiency by extracting key information from spectral data and eliminating redundancy. The decision tree algorithm, on the other hand, can process large amounts of data simultaneously. In addition, the method has a wide range of applications and can be used in various scenarios accurately. The scenarios include domestic sewage, micropollutant water, aquaculture wastewater, and secondary treated sewage. The experimental results validate the application of machine learning classifiers in membrane breakage detection with an accuracy rate of 96.8 % to 97.4 %.

Unraveling the characteristics of dissolved organic matter removed by aluminum species based on FT-ICR MS analysis

Given the complexity of dissolved organic matter (DOM) and its interactions with coagulant chemicals, the mechanisms of DOM removal by aluminum (Al) coagulants remains a significant unknown. In this study, six test waters containing DOM with molecular weight (MW, <1 kDa, 1-10 kDa and >10 kDa) and hydrophobicity (hydrophilic, transphilic and hydrophobic) were prepared and coagulated with Al0, Al13 and Al30. The molecular-level characteristics of DOM molecules that were removed or resistant to removal by Al species were analyzed using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The results showed that at the molecular level, saturated and reduced tannins and lignin-like compounds containing abundant carboxyl groups exhibited higher coagulation efficiency. Unsaturated and oxidized lipids, protein-like, and carbohydrates compounds were relatively resistant to Al coagulation due to their higher polarity and lower content of carboxyl groups. Al13 removed molecules across a wider range of molecular weights than Al0 and Al30, thus the DOC removal efficiency of Al13 was the highest. This study furthers the understanding of interactions between Al species and DOM, and provides scientific insights on the operation of water treatment plants to improve control of DOM.

Exploring optical descriptors for rapid estimation of coastal sediment organic carbon and nearby land-use classifications via machine learning models

This study utilizes ultraviolet and fluorescence spectroscopic indices of dissolved organic matter (DOM) from sediments, combined with machine learning (ML) models, to develop an optimized predictive model for estimating sediment total organic carbon (TOC) and identifying adjacent land-use types in coastal sediments from the Yellow and Bohai Seas. Our results indicate that ML models surpass traditional regression techniques in estimating TOC and classifying land-use types. Penalized Least Squares Regression (PLR) and Cubist models show exceptional TOC estimation capabilities, with PLR exhibiting the lowest training error and Cubist achieving a correlation coefficient 0.79. In land-use classification, Support Vector Machines achieved 85.6 % accuracy in training and 92.2 % in testing. Maximum fluorescence intensity and ultraviolet absorbance at 254 nm were crucial factors influencing TOC variations in coastal sediments. This study underscores the efficacy of ML models utilizing DOM optical indices for near real-time estimation of marine sediment TOC and land-use classification.

Optical measurements of dissolved organic matter as proxies for CODMn and BOD5 in plateau lakes

The presence of organic matter in lakes profoundly impacts drinking water supplies, yet treatment processes involving coagulants and disinfectants can yield carcinogenic disinfection by-products. Traditional assessments of organic matter, such as chemical oxygen demand (CODMn) and biochemical oxygen demand (BOD5), are often time-consuming. Alternatively, optical measurements of dissolved organic matter (DOM) offer a rapid and reliable means of obtaining organic matter composition data. Here we employed DOM optical measurements in conjunction with parallel factor analysis to scrutinize CODMn and BOD5 variability. Validation was performed using an independent dataset encompassing six lakes on the Yungui Plateau from 2014 to 2016 (n = 256). Leveraging multiple linear regressions (MLRs) applied to DOM absorbance at 254 nm (a254) and fluorescence components C1-C5, we successfully traced CODMn and BOD5 variations across the entire plateau (68 lakes, n = 271, R2 > 0.8, P < 0.0001). Notably, DOM optical indices yielded superior estimates (higher R2) of CODMn and BOD5 during the rainy season compared to the dry season and demonstrated increased accuracy (R2 > 0.9) in mesotrophic lakes compared to oligotrophic and eutrophic lakes. This study underscores the utility of MLR-based DOM indices for inferring CODMn and BOD5 variability in plateau lakes and highlights the potential of integrating in situ and remote sensing platforms for water pollution early warning.

Contrasting fate and binding behavior of Mn and Cu with dissolved organic matter during in situ remediation using multicomponent capping in malodorous black water

The common use of peroxides in the remediation of malodorous black water may lead to the activation of heavy metals in sediment when eliminating black and odorous substances. The mechanisms of heavy metal interactions with dissolved organic matter (DOM) in response to in situ capping have not been elucidated, but this information could guide the optimization of capping materials. We developed a capping material consisting of hydrothermally carbonized sediment (HCS), hydrated magnesium carbonate (HMC) and sodium percarbonate (SPC) and used microcosm experiments to investigate the dynamics of Mn and Cu at the sediment-water interface in malodorous black water. The results showed that HCS, HMC and SPC contributed multiple functions of mechanical protection, chemical isolation and oxygen provision to the new caps. HMC promoted the conversion of Mn/Cu into carbonate minerals. The optimal mass proportions were 25 % HCS, 60 % HMC and 15 % SPC based on the mixture design. In situ capping altered the fate and transformation of metals in the sediment-overlying water profile in the short term through Mn immobilization and Cu activation. The complexation of Cu(II) ions was significantly stronger than that of Mn(II) ions. In situ capping had a significant effect on the order of complexation of different fluorescent DOM molecules with Mn(II)/Cu(II) ions: microbial byproducts and fulvic acid-like components were preferentially complexed with Cu(II) ions after capping, while phenolic and humic acid-like components preferentially interacted with Mn(II) ions. Humic-like components bound to Cu were affected the most by capping treatment, whereas protein-like components were relatively weakly affected. Our study provides valuable knowledge on the impact of in situ capping on DOM-metal complexes.

Simultaneous removal of NOM and sulfate in a bioelectrochemical integrated biofilter treating reclaimed water

Biofiltration is an environmentally 'green' technology that is compatible with the recently proposed sustainable development goals, and which has an increasingly important future in the field of water treatment. Here, we explored the impacts of bioelectrochemical integration on a bench-scale slow rate biofiltration system regarding its performance in reclaimed water treatment. Results showed that the short-term (<3 months) integration improved the removal of natural organic matter (NOM) (approximately 8.8%). After long-term (5 months and thereafter) integration, the cathodic charge transfer resistance was found to have a significant reduction from 2662 to 1350 Ω. Meanwhile, bioelectrochemical autotrophic sulfate (SO42-) reduction (over 27.6% reduction) through the syntrophic metabolism between hydrogen oxidation strains (genus Hydrogenophaga) and sulfate-reducing microbes (genera Dethiobacter, Desulfovibrio, and Desulfomicrobium) at the cathodic region was observed. More significantly, the microbial-derived chromophoric humic substances were found to act as electron shuttles at the cathodic region, which might facilitate the process of bioelectrochemical SO42- reduction. Overall, this study provided valuable insights into the potential application of bioelectrochemical-integrated biofilter for simultaneous reduction of NOM and SO42- treating reclaimed water.

Using machine learning to trace the pollution sources of disinfection by-products precursors compared to receptor models

To increase the efficiency of managing backup water resources, it is critical to identify and allocate pollution sources. Source apportionment of dissolved organic matter (DOM) was investigated in our work. Parallel factor analysis (PARAFAC) and the Spearman correlation analysis were used for source identification. After that, a newly hybrid model applying the fuzzy c-means and support vector regression (FCM-SVR) was employed for source apportionment compared to receptor models. The results demonstrated that the FCM-SVR model exhibited excellent generalization, and only required standardization and normalization as pre-processing steps for dataset. According to the results, microbial sources played a key role (28.1 %) in the formation potential of disinfection byproducts (DBPFPs). Additionally, shipping marine sources exhibited a substantial contribution (21.2 %) to DBPFPs. The prediction accuracy of DBPFPs was matched or exceeded receptor models, and the R2 of DOC (0.884) was significantly high. Therefore, we recommend the FCM-SVR model combined with PARAFAC to trace the source of DBPFPs as its significant effectiveness in source identification, source apportionment, and prediction accuracy, possessing the potential for further applicability in tracking more organic compounds. ENVIRONMENTAL IMPLICATION: The disinfection byproducts precursors in water sources, which were thought to be hazardous materials in this study, are proved to be chlorinated into carcinogenic disinfection byproducts (DBPs) during drinking water treatment, However, the source apportionment methods of DBPs are not well developed compared to other inorganic matter, e.g., heavy metals and ammonia nitrogen. We proposed a new FCM-SVR model to trace the source of DBPs, which required easier pre-treatment and resulted a better source apportionment and prediction accuracy. As a result, it could provide a different prospect and useful management advices to trace the source of DBPs.

Advanced oxidation of recalcitrant chromophores in full-scale MBR effluent for non-potable reuse of leachate co-treated municipal wastewater

Wastewater non-potable reuse involves further processing of secondary effluent to a quality level acceptable for reuse and is a promising solution to combating water scarcity. Recalcitrant chromophores in landfill leachate challenge the water quality for non-potable reuse when leachate is co-treated with municipal wastewater. In this study, we first use multivariate statistical analysis to reveal that leachate is an important source (with a Pearson's coefficient of 0.82) of recalcitrant chromophores in the full-scale membrane bioreactor (MBR) effluent. We then evaluate the removal efficacies of chromophores by chlorination, breakpoint chlorination, and the chlorination-UV/chlorine advanced oxidation treatment. Conventional chlorination and breakpoint chlorination only partially remove chromophores, leaving a colour level exceeding the standards for non-potable reuse (>20 Hazen units). We demonstrate that pre-chlorination (with an initial chlorine dosing of 20 mg/L as Cl2) followed by UV radiation (with a UV fluence of 500 mJ/cm2) effectively degraded recalcitrant chromophores (>90%). By quantifying the electron donating capacity (EDC) and radical scavenging capacity (RSC) of the reclaimed water, we demonstrate that pre-chlorination reduces EDC and RSC by up to 64%, increases UV transmittance by 32%, and increases radical yields from UV photolysis of chlorine by 1.7-2.2 times. The findings advance fundamental understanding of the alteration of dissolved coloured substances by (photo)chlorination treatment and provide implications for applying advanced oxidation processes in treating wastewater effluents towards sustainable non-potable reuse.

Enhancement of medium-chain fatty acids production from sludge anaerobic fermentation liquid under moderate sulfate reduction

In recent years, there has been a marked increase in the production of excess sludge. Chain-elongation (CE) fermentation presents a promising approach for carbon resource recovery from sludge, enabling the transformation of carbon into medium-chain fatty acids (MCFAs). However, the impact of sulfate, commonly presents in sludge, on the CE process remains largely unexplored. In this study, batch tests for CE process of sludge anaerobic fermentation liquid (SAFL) under different SCOD/SO42- ratios were performed. The moderate sulfate reduction under the optimum SCOD/SO42- of 20:1 enhanced the n-caproate production, giving the maximum n-caproate concentration, selectivity and production rate of 5.49 g COD/L, 21.4% and 4.87 g COD/L/d, respectively. The excessive sulfate reduction under SCOD/SO42- ≤ 5 completely inhibited the CE process, resulting in almost no n-caproate generation. The variations in n-caproate production under different conditions of SCOD/SO42- were all well fitted with the modified Gompertz kinetic model. Alcaligenes and Ruminococcaceae_UCG-014 were the dominant genus-level biomarkers under moderate sulfate reduction (SCOD/SO42- = 20), which enhanced the n-caproate production by increasing the generation of acetyl-CoA and the hydrolysis of difficult biodegradable substances in SAFL. The findings presented in this work elucidate a strategy and provide a theoretical framework for the further enhancement of MCFAs production from excess sludge.

Partial wet oxidation of dairy manure as a pretreatment process to produce acetic acid 'a Source Growth of Methanogens'

Wet oxidation can be an effective process for the pretreatment of complex biomass such as lignocellulose. However, studies on the use of wet oxidation for treating solid waste such as dairy manure are limited. The use of partial wet oxidation to convert dairy manure into low molecular weight carboxylic acids as final products were investigated. This work focuses on the performance of the sub-critical wet oxidation treatment of dairy cattle manure as a conversion/pretreatment process to release matter from the lignocellulosic fraction rather than a destructive process. The operating conditions were controlled at the short residence time and optimal temperature in the presence of oxygen under a pressure of 120 psi. The thermal hydrolysis under wet oxidation significantly affected conversion manure slurry into organic acids. The concentration of acetic acid reached 1778 mg L-1, achieved at 190°C (60 minutes reaction time) as the reaction temperature increased within the range of 150°C-200°C, total organic carbon was reduced and monomers in the process liquids decreased. On the other hand, soluble COD in process liquids increased with an increment in reaction temperature. The results provide insights into technical options to pretreat dairy manure to improve biochemical conversion yield.

The synergistic role of ozonation and hydrolysis acidification on the enhanced pre-treatment of high-strength refractory 2-butenal manufacture wastewater: Performance, metabolism, and mechanisms

Targeted removal of three key refractory toxic organic compounds (TOMs) in 2-butenal manufacturing wastewater (2-BMW) is critical for enhancing pre-treatment by hydrolysis acidification (HA). We investigated the pre-treatment of 2-BMW with HA, coupled with ozonation in this study. Our results indicated that the removal rate of these key TOMs and the detoxification rate reached almost 100% and 46.3%, respectively, by ozonation under only 0.099 mg O3/mg chemical oxygen demand (COD). The organic load rate (OLR) reached 10.25 ± 0.43 kg COD/m3·d, and the acidification degree (AD) and detoxification efficiency reached 56.0% and 98.3%, respectively, with enhancements of 35.1% and 55.2%, respectively, compared with HA alone. The removal rate of the three key TOMs was improved by > 75%. The degradation pathways of these key TOMs were ring cleavage and ester formation by ozonation, followed by fermentation and acid production by HA. Ultimately, the synergistic role of ozonation and HA was revealed. The preferential cleavage of these key TOMs by ozonation was achieved because of their high electron cloud density and multiple reaction sites, which generated more fermentation-friendly products. The fermentation and acid production reactions may be directly involved in these products. Functional bacteria and key metabolic pathways were also enhanced by ozonation.

Deciphering DOM-metal binding using EEM-PARAFAC: Mechanisms, challenges, and perspectives

Dissolved organic matter (DOM) is a pivotal component of the biogeochemical cycles and can combine with metal ions through chelation or complexation. Understanding this process is crucial for tracing metal solubility, mobility, and bioavailability. Fluorescence excitation emission matrix (EEM) and parallel factor analysis (PARAFAC) has emerged as a popular tool in deciphering DOM-metal interactions. In this review, we primarily discuss the advantages of EEM-PARAFAC compared with other algorithms and its main limitations in studying DOM-metal binding, including restrictions in spectral considerations, mathematical assumptions, and experimental procedures, as well as how to overcome these constraints and shortcomings. We summarize the principles of EEM to uncover DOM-metal association, including why fluorescence gets quenched and some potential mechanisms that affect the accuracy of fluorescence quenching. Lastly, we review some significant and innovative research, including the application of 2D-COS in DOM-metal binding analysis, hoping to provide a fresh perspective for possible future hotspots of study. We argue the expansion of EEM applications to a broader range of areas related to natural organic matter. This extension would facilitate our exploration of the mobility and fate of metals in the environment.

Insight into coagulation/flocculation mechanisms on microalgae harvesting by ferric chloride and polyacrylamide in different growth phases

FeCl3 and polyacrylamide (PAM) had been used to investigate the effect of coagulation, flocculation, and their combination on algae cells and extracellular organic matter (EOM) at different phases. PAM tended to aggregate particle-like substances, while FeCl3 could interact with EOM. The content of EOM kept rising during the algae growth cycle, while OD680 peaked at about 3.0. At stationary phase Ⅰ, the removal efficiencies of UV254, turbidity and OD680 of the suspension conditioned with FeCl3 + PAM reached (88.08 ± 0.89)%, (89.72 ± 0.36)% and (93.99 ± 0.05)%, respectively. Nevertheless, PAM + FeCl3 exhibited the worst efficiency because of the release of EOM caused by the turbulence. The results suggested that algal cells served as a coagulation aid to facilitate floc formation, while excessive EOM deteriorated harvesting performance. The process of FeCl3 + PAM at stationary phase Ⅰ appears to be a promising technology for microalgae harvesting.

A single recognition unit-based virtual sensor Array: Applying 3D fluorescence spectroscopy to inner filter effect-based sensing

A convenient, fast, low-cost detection and discrimination method is demanded for environmental monitoring but still it remains more technological challenges. Herein, we demonstrate that the inner filter effect (IFE), in combination with three-dimensional fluorescence spectroscopy, can offer a virtual sensor array (VSA) as apropersolution. And with the aid of pattern recognition techniques, it is feasible to recognize compounds with structural similarities economically and effectively. In this study, with the help of visual clustering plots of principal component analysis (PCA), a prediction model based on hierarchical strategy was made using support vector machine (SVM) method for the qualitative profiling of aromatic pollutants. The VSA was constructed by a single metal-organic framework (MOF) recognition unit (MOF-74 (Zn)) with the excitation wavelength as external regulatory factors. Pattern characteristics of four aromatics with very similar structures (phenylamine, chlorobenzene, nitrobenzene, and phenol), both single analyte and binary mixtures, were acquired. The primary constituents of multi-dimensional spectral signals were subsequently extracted and fed into a vector machine to construct a prediction model through 10-fold cross-validation optimization, resulting in a classification accuracy of 100% for single analytes and 96% for mixtures. Quantitative research has shown that, except for chlorobenzene, all three other analytes can be predicted in concentration within an acceptable error range, and the mixture can be predicted proportionally. Moreover, the VSA can be used to distinguish these pollutants in tap and river water also. We propose for the first time a new tack for the construction of VSA in a general manner, namely using three-dimensional full range fluorescence scanning for IFE based sensing to get multiple times of information resulting from different weak interaction between analyte and sensor for decision-making.

The Future of Municipal Wastewater Reuse Concentrate Management: Drivers, Challenges, and Opportunities

Water reuse is rapidly becoming an integral feature of resilient water systems, where municipal wastewater undergoes advanced treatment, typically involving a sequence of ultrafiltration (UF), reverse osmosis (RO), and an advanced oxidation process (AOP). When RO is used, a concentrated waste stream is produced that is elevated in not only total dissolved solids but also metals, nutrients, and micropollutants that have passed through conventional wastewater treatment. Management of this RO concentrate─dubbed municipal wastewater reuse concentrate (MWRC)─will be critical to address, especially as water reuse practices become more widespread. Building on existing brine management practices, this review explores MWRC management options by identifying infrastructural needs and opportunities for multi-beneficial disposal. To safeguard environmental systems from the potential hazards of MWRC, disposal, monitoring, and regulatory techniques are discussed to promote the safety and affordability of implementing MWRC management. Furthermore, opportunities for resource recovery and valorization are differentiated, while economic techniques to revamp cost-benefit analysis for MWRC management are examined. The goal of this critical review is to create a common foundation for researchers, practitioners, and regulators by providing an interdisciplinary set of tools and frameworks to address the impending challenges and emerging opportunities of MWRC management.

The telltale fluorescence fingerprints of sewer flows for interpreting the low influent concentration in wastewater treatment plant

Low degradability of wastewater treatment plant (WWTP) influents negatively affects its ability to effectively remove pollutants through wastewater treatment processes. Proactive assessment of urban sewer system performance is highly valued in the selection of targeted countermeasures for this occurrence. In this study, a fluorescence spectrum interpretation approach was developed to identify the causes of low biodegradability of WWTP influent by using parallel factor analysis (PARAFAC) and fluorescence regional integration (FRI) of excitation-emission matrix spectroscopy. Statistical analysis was also used to further interpret the PARAFAC- and FRI-derived data. The urban sewer catchment served by a WWTP in Wuhan City, China, was used as the test site to demonstrate the effectiveness of this approach. The results showed that electronics manufacturing industrial wastewater and groundwater input into the urban sewer would significantly decrease the biodegradability of the WWTP influents, and these sources were characterized by much lower fluorescence peak intensities, especially for protein-like substances, including tryptophan-like T and tyrosine-like B1 and B2. The potential conversion of high freshness T into low freshness B2 within the sewer may also contribute to this undesirable scenario. The ratio of peak T to peak B2 and the ratio of the FRI fraction of region I to that of region II can be used together to determine the predominance of industrial wastewater and groundwater. T/B2 < 1.3 indicates the entry of industrial wastewater or groundwater into urban sewers, and I/II > 0.5 further confirms the input of industrial wastewater. Accordingly, the low biodegradability of the WWTP influents in our study site is mostly due to the inflow of industrial wastewater rather than groundwater infiltration into the urban sewers. Therefore, actions should be focused on the surveillance of industrial wastewater rather than widespread sewer inspection and repairs. In this way, this methodology is cost-effective in aiding targeted countermeasures to improve the urban sewer system performance.

Practical Guide to Measuring Wetland Carbon Pools and Fluxes

Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13157-023-01722-2.

Driving mechanism of water replenishment on DOM composition and eutrophic status changes of lake in arid and semi-arid regions of loess area

Water replenishment can be a key factor in driving lake eutrophication status. In arid and semi-arid regions of China, water replenishment for a lake has been widely carried out for not only improving water environmental quality, but also maintaining ecological system function. However, it is still unclear in terms of mechanism by which water replenishment drives lake eutrophication status. In this study, fluorescence excitation-emission matrix spectroscopy (EEMs) combined with multiple statistical analysis models (including parallel factor analysis, correlation analysis, redundancy analysis, and partial least squares structural equation modeling) was utilized to reveal potential driving mechanism and causality between water replenishment, dissolved organic matter (DOM) fractions and eutrophic status of Lake Shahu in China. Based on variations of DOM fractions, fulvic-like substances could be accumulated during the replenishment period, while nutrients carried along the replenishment might conduce to increase microbial activities during the non-replenishment period. This should be contributed to an alteration of prominent component from fulvic-like substances to tyrosine-like substances during the replenishment period to non-replenishment period. According to partial least squares structural equation modeling, two potential indirect paths were finally revealed, i.e., water replenishment derived the eutrophic status of Lake Shahu: water replenishment → microbial activity → algae → eutrophication, and water replenishment → microbial activity → eutrophication. This supposed that the water replenishment should indirectly drive the algae and eutrophication of the lake by promoting the transformation of DOM fractions. In addition, natural conditions could indirectly contribute to the eutrophication of the lake through impacting the algae growth. These findings should be conducive to trace the alteration of DOM fractions in lakes by water replenishment and in recognizing potential driving mechanisms of water replenishment on eutrophication of lakes by changing DOM fractions. This could provide basic theoretical support for policymakers to regulate and treat the eutrophication of lakes.

Fluorescence Spectroscopy for the Assessment of Microbial Load in UVC Treated Water

In this article, Fluorescence spectroscopy has been employed for the assessment of microbial load and it has been compared with the gold standard colony forming unit (CFU) and optical density (OD) methods. In order to develop a correlation between three characterization techniques, water samples of different microbial loads have been prepared by UVC disinfection method through an indigenously developed NUVWater sterilizer, which operates in close cycle flow configuration. A UV dose of 58.9 mJ/cm2 has been determined for 99.99% disinfection for a flow rate of 0.8 l/min. The water samples were excited at 270 nm which results in the tryptophan like fluorescence at 360 nm that decreases gradually with increase of UVC dose, indicating the bacterial degradation and it has been confirmed by OD and CFU methods. In addition, it has been proved that a close cycle water flow around UV lamp is imperative so that an appropriate dose must be delivered to microorganisms for an efficient disinfection. It has been found that due to the sensitive nature of Fluorescence spectroscopy, it yields immediate results, whereas, for CFU and OD methods, water samples needs to be inoculated for 24 h. Fluorescence spectroscopy, therefore, provide a fast, online, reliable and sensitive method for the monitoring of pathogenic quantification in drinking water.

Greywater reuse as a key enabler for improving urban wastewater management

Sustainable water management is essential to guaranteeing access to safe water and addressing the challenges posed by climate change, urbanization, and population growth. In a typical household, greywater, which includes everything but toilet waste, constitutes 50-80% of daily wastewater generation and is characterized by low organic strength and high volume. This can be an issue for large urban wastewater treatment plants designed for high-strength operations. Segregation of greywater at the source for decentralized wastewater treatment is therefore necessary for its proper management using separate treatment strategies. Greywater reuse may thus lead to increased resilience and adaptability of local water systems, reduction in transport costs, and achievement of fit-for-purpose reuse. After covering greywater characteristics, we present an overview of existing and upcoming technologies for greywater treatment. Biological treatment technologies, such as nature-based technologies, biofilm technologies, and membrane bioreactors (MBR), conjugate with physicochemical treatment methods, such as membrane filtration, sorption and ion exchange technologies, and ultraviolet (UV) disinfection, may be able to produce treated water within the allowable parameters for reuse. We also provide a novel way to tackle challenges like the demographic variance of greywater quality, lack of a legal framework for greywater management, monitoring and control systems, and the consumer perspective on greywater reuse. Finally, benefits, such as the potential water and energy savings and sustainable future of greywater reuse in an urban context, are discussed.

Compact Fluorescence Spectrometer with Built-In In-Line Calibration: Application to Detect Dissolved Organic Matter in Water

Fluorescence spectrometer (FS) is widely used for component analysis because each fluorescing material has its own characteristic spectrum. However, the spectral calibration is complicated and bulky. Herein, an in-line spectral calibration sheet (ISCS) was proposed in which a narrow band-pass filter and a linear variable filter (LVF) were integrated on a metal plate. By moving the ISCS, the transmitted excitation light power (TEP) as well as fluorescence spectrum can be seamlessly scanned, and the TEP can be used for in-line spectral calibration. A compact FS apparatus based on UV-LED excitation, metal capillary (MC) and ISCS was fabricated (i.e., ISCS-FS), and the ISCS-FS apparatus was applied to detect sodium humate in water. By employing TEP calibration, both the primary inner filter effect (PIFE) and the drift in the optical power of UV-LED can be simultaneously compensated. The linear correlation coefficient of signal concentration was improved from 0.89 to 0.998, and the relative standard deviation (RSD) of replicated detection was improved from 3 to 0.7%. A detection limit of concentration (DLC) of 1.3 μg/L was realized, which is 15-fold lower than that of a commercial FS apparatus (20 μg/L). The DLC is even comparable with that (0.5-4 μg/L) of commercial total organic carbon (TOC) analyzers, which are bulky and expensive. The linear correlation between the measurement results of ISCS-FS and commercial TOC analyzers can reach a good value of 0.94.

Fluorescent Dissolved Organic Matter Components as Surrogates for Disinfection Byproduct Formation in Drinking Water: A Critical Review

Disinfection byproduct (DBP) formation, prediction, and minimization are critical challenges facing the drinking water treatment industry worldwide where chemical disinfection is required to inactivate pathogenic microorganisms. Fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC) is used to characterize and quantify fluorescent dissolved organic matter (FDOM) components in aquatic systems and may offer considerable promise as a low-cost optical surrogate for DBP formation in treated drinking waters. However, the global utility of this approach for quantification and prediction of specific DBP classes or species has not been widely explored to date. Hence, this critical review aims to elucidate recurring empirical relationships between common environmental fluorophores (identified by PARAFAC) and DBP concentrations produced during water disinfection. From 45 selected peer-reviewed articles, 218 statistically significant linear relationships (R2 ≥ 0.5) with one or more DBP classes or species were established. Trihalomethanes (THMs) and haloacetic acids (HAAs), as key regulated classes, were extensively investigated and exhibited strong, recurrent relationships with ubiquitous humic/fulvic-like FDOM components, highlighting their potential as surrogates for carbonaceous DBP formation. Conversely, observed relationships between nitrogenous DBP classes, such as haloacetonitriles (HANs), halonitromethanes (HNMs), and N-nitrosamines (NAs), and PARAFAC fluorophores were more ambiguous, but preferential relationships with protein-like components in the case of algal/microbial FDOM sources were noted. This review highlights the challenges of transposing site-specific or FDOM source-specific empirical relationships between PARAFAC component and DBP formation potential to a global model.

Exploring the binding effect and mechanism of glycyrrhizin to ovomucin by combining spectroscopic analysis and molecular docking

Ovomucin (OVM) is an ideal natural macromolecular glycoprotein extracted from eggs with good adhesion. Based on the defect that glycyrrhizin (GL) has good antiviral activity but fast metabolism, this study aimed to explore the binding effect and mechanism of GL to OVM, using multi-spectroscopic techniques, isothermal titration calorimetry (ITC), and molecular docking. The adhesion ability of OVM to the hydrophilic interface and GL was first demonstrated by dual polarization interferometry (DPI) analysis and binding capacity assay, and the OVM-GL complex exhibited a similar affinity for the spike protein of COVID-19. The spectroscopic results show that GL can quench the inherent fluorescence and change the glycosidic bond and secondary structure of OVM. The ITC measurements suggested that the binding was exothermic, the hydrogen bond was the dominant binding force for forming OVM-GL. Finally, molecular docking results indicated that GL has hydrogen bond interaction with several amino acid residues located in α-OVM and β-OVM while embedding into the hydrophobic pocket of OVM via hydrophobic interactions. In conclusion, OVM can adhere to the hydrophilic interface and bind to GL through hydrogen bonding and hydrophobic interactions to form a stable complex, that is expected to be helpful in virus prophylaxis.

Investigating spectroscopic and copper binding characteristics of dissolved organic matter in wastewater using EEMs with two-dimensional Savitzky-Golay second-order differentiation-PARAFAC

Dissolved organic matter (DOM) in wastewater interacts with heavy metal particles in aquatic environments, which changes their dynamics and bioavailability. For quantifying the DOM, an excitation-emission matrix (EEM) paired alongside parallel factor analysis (PARAFAC) is typically employed. However, a drawback of PARAFAC has been revealed in recent studies, i.e., the rise of overlapping spectra or wavelength shifts in fluorescent components. Here, traditional EEM-PARAFAC and, for the first time, two-dimensional Savitzky-Golay second-order differential-PARAFAC (2D-SG-2nd-df-PARAFAC) were used to study the DOM-heavy metal binding. The samples from four treatment units of a wastewater treatment plant, i.e., influent, anaerobic, aerobic, and effluent, underwent the process of fluorescence titration with Cu2+. Four components were separated with dominant peaks in regions I, II, and III (proteins and fulvic acid-like) through PARAFAC and 2D-SG-2nd-df-PARAFAC. A single peak was observed in region V (humic acid-like) by PARAFAC. In addition, Cu2+-DOM complexation indicated clear differences in DOM compositions. The binding strength increased between Cu2+ and fulvic acid-like components in contrast to protein-like components from influent to the effluent, and increasing fluorescence intensity with the addition of Cu2+ in the effluent indicated changes in their structural composition. Moreover, when comparing both methods, the 2D-SG-2nd-df-PARAFAC provided the components without peak shifts and better fitting for Cu2+-DOM complexation model, demonstrating it to be a more reliable technique compared to only traditional PARAFAC for DOM characterization and quantifying metal-DOM in wastewater.

Spatiotemporal optical properties of dissolved organic matter in a sluice-controlled coastal plain river with both salinity and trophic gradients

Due to the combined effect of sluices and sea tide, the sluice-controlled coastal plain river would be characterized by both trophic state and salinity gradients, affecting the spatiotemporal optical properties of dissolved organic matter (DOM). In this study, we investigated the spatiotemporal variation of water quality parameters and optical properties of DOM in the Haihe River, a representative sluice-controlled coastal plain river in Tianjin, China. A significant salinity gradient and four trophic states were observed in the water body of the Haihe River. Two humic- and one protein-like substances were identified from the DOM by the three-dimensional fluorescence spectra combined with the parallel factor (PARAFAC) analysis. Pearson's correlation analysis and redundancy analysis (RDA) showed that the salinity significantly affected the abundance of chromophoric DOM (CDOM) but did not cause significant changes in the fluorescence optical characteristics. In addition, the effect of Trophic state index (TSI) on the CDOM abundance was greater than that on the fluorescence intensity of fluorescent dissolved organic matter (FDOM). In the water body with both salinity and trophic state gradients, TSI posed a greater influence than salinity on the CDOM abundance. Our results fill the research gap in spatiotemporal DOM characteristics and water quality variation in water bodies with both salinity and trophic state gradients. These results are beneficial for clarifying the joint influence of saline intrusion and sluices on the DOM characteristics and water quality in sluice-controlled coastal plain rivers.

Bubbleless aerated-biological activated carbon as a superior process for drinking water treatment in rural areas

Drinking water supply in rural areas remains a substantial challenge due to complex natural, technical and economic conditions. To provide safe and affordable drinking water to all, as targeted in the UN Sustainable Development Goals (2030 Agenda), low-cost, efficient water treatment processes suitable for rural areas need to be developed. In this study, a bubbleless aeration BAC (termed ABAC) process is proposed and evaluated, involving the incorporation of a hollow fiber membrane (HFM) assembly within a slow-rate BAC filter, to provide dissolved oxygen (DO) throughout the BAC filter and an increased DOM removal efficiency. The results showed that after a 210-day period of operation, the ABAC increased the DOC removal by 54%, and decreased the disinfection byproduct formation potential (DBPFP) by 41%, compared to a comparable BAC filter without aeration (termed NBAC). The elevated DO (> 4 mg/L) not only reduced secreted extracellular polymer, but also modified the microbial community with a stronger degradation ability. The HFM-based aeration showed comparable performance to 3 mg/L pre-ozonation, and the DOC removal efficiency was four times greater than that of a conventional coagulation process. The proposed ABAC treatment, with its various advantages (e.g., high stability, avoidance of chemicals, ease of operation and maintenance), is well-suited to be integrated as a prefabricated device, for decentralized drinking water systems in rural areas.

Biomass formation and organic carbon migration potential of microplastics from a PET recycling plant: Implication of biostability

The growth of the polyethylene terephthalate (PET) mechanical recycling industry has resulted in the challenge of generating microplastics (MPs). However, little attention has been given to investigating the release of organic carbon from these MPs and their roles in promoting bacterial growth in aquatic environments. In this study, a comprehensive method is proposed to access the potential of organic carbon migration and biomass formation of MPs generated from a PET recycling plant, and to understand its impact on the biological systems of freshwater habitats. Various MPs sizes from a PET recycling plant were selected to conduct a series of tests, including the organic carbon migration test, biomass formation potential test, and microbial community analysis. The MPs smaller than 100 µm, which are difficult to remove from the wastewater, exhibited greater biomass in the observed samples (1.05 × 10¹¹ bacteria per gram MPs). Moreover, PET MPs altered the microbial diversity, with Burkholderiaceae becoming the most abundant, while Rhodobacteraceae was eliminated after being incubated with MPs. This study partly revealed that organic matter adsorbed on the surface of MPs was a significant nutrient source that increased biomass formation. PET MPs acted not only as carriers for microorganisms but also for organic matter. As a result, it is crucial to develop and refine recycling methods in order to decrease the production of PET MPs and minimize their adverse effects on the environment.

To analyze or to throw away? On the stability of excitation-emission matrices for different water systems

Fluorescence spectroscopy has numerous applications to characterize natural and human-influenced water bodies regarding dissolved organic matter (DOM) and contamination. Analyzing samples in a timely manner is crucial to gaining valid and reproducible excitation-emission matrices (EEM) but often difficult, specifically in transnational projects with long transport distances. In this study, eight samples of different water sources (tap water, differently polluted rivers, and wastewater treatment plant (WWTP) effluents) were stored under standardized conditions for 59 days and analyzed regularly. With this data set, the sample and fluorescence spectra stability was evaluated. Established analysis methods such as peak picking and fluorescence metrics were compared over time and benchmarked against dissolved organic carbon (DOC) and a maximal change of 10% in terms of their variability. Additional high-performance liquid chromatography (HPLC) data to identify single organic compounds provides insights into these DOM alterations and allows for conclusions about the underlying biological processes. Our results corroborate in a systematic way that the higher the organic or microbial load, the faster the sample must be processed. For all water sources, considerable changes were found between days zero and one, indicating a potential systematic bias between in-situ and laboratory measurements. The absolute signals of individual peaks vary substantially after only a few days. In contrast, relative metrics are robust for a much longer time. For specific metrics, when filtered and stored under cool and dark conditions, tap water may be stored for up to 59 days, non-polluted river water for up to 31-59 days, and WWTP effluents for up to 14-59 days. The storability thus depends both on the specific water source and the analytical plan. By systematizing our understanding of how the specific water source and DOM concentration determine the stability of samples during storage, these conclusions facilitate efforts to establish a standardized protocol.

A Comprehensive Review on the Excitation-Emission Matrix Fluorescence Spectroscopic Characterization of Petroleum-Containing Substances: Principles, Methods, and Applications

Petroleum-containing substance (PCS) is a general term used for petroleum and its derivatives. A comprehensive characterization of PCSs is crucial for resource exploitation, economic development and environmental protection. Fluorescence spectroscopy, especially excitation-emission matrix fluorescence (EEMF) spectroscopy, has been proved to be a powerful tool to characterize PCSs since its remarkable sensitivity, selectivity, simplicity and high efficiency. However, there is a lack of systematic review focusing on this field in the literature. This paper reviews the fundamental principles and measurements of EEMF for characterizing PCSs, and makes a systematic introduction to various information mining methods including basic peak information extraction, spectral parameterization and some commonly used chemometric methods. In addition, recent advances in applying EEMF to characterize PCSs during the whole life-cycle process of petroleum are also revisited. Furthermore, the current limitations of EEMF in the measurement and characterization of PCSs are discussed and corresponding solutions are provided. For promoting the future development of this field, the urgent need to build a relatively complete EEMF fingerprint library to trace PCSs, not only pollutants but also crude oil and petroleum products, is proposed. Finally, the extensions of EEMF to high-dimensional chemometrics and deep learning are prospected, with the expectation of solving more complex systems and problems.

Changes of dissolved organic matter following salinity invasion in different seasons in a nitrogen rich tidal reach

Dissolved organic matter (DOM) is a heterogeneous mixture of dissolved material found ubiquitously in aquatic systems and dissolved organic nitrogen is one of its most important components. We hypothesised nitrogen species and salinity intrusions affect the DOM changes. Here, using the nitrogen rich Minjiang River as an easily accessible natural laboratory 3 field surveys with 9 sampling sites (S1-S9) were conducted in November 2018, April and August 2019. The excitation emission matrices (EEMs) of DOM were explored with parallel factor (PARAFAC) and cosine-histogram similarity analysis. Four indices including fluorescence index (FI), biological index (BIX), humification index (HIX) and the fluorescent DOM (FDOM) were calculated and the impact of physicochemical properties was assessed. The results suggested that the highest salinities of 6.15, 2.98 and 10.10, during each campaign corresponded to DTN concentrations of 119.29-240.71, 149.12-262.42 and 88.27-155.29 μmol·L^-1, respectively. PARAFAC analysis revealed the presence of tyrosine-like proteins (C1), tryptophan-like proteins or a combination of the peak N and tryptophan-like fluorophore (C2) and the humic-like material (C3). The EEMs in the upstream reach (i.e. S1-S3) were complex with larger spectra ranges, higher intensities and similar similarity. Subsequently, the fluorescence intensity of three components decreased significantly with low similarity of EEMs (i.e. S4-S7). At the downstream, the fluorescence levels dispersed significantly and no obvious peaks were seen except in August. In addition, FI and HIX increased, while BIX and FDOM decreased from upstream to downstream. The salinity positively correlated with FI and HIX, and negatively related to BIX and FDOM. Besides, the elevated DTN had a significant effect on the DOM fluorescence indices. Altogether, salinity intrusion and elevated nitrogen are relevant for the distribution of the DOM, which is helpful for the water management tracing the DOM source according to the on-line monitoring of salinity and nitrogen in estuaries.

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical method that can provide fingerprint-like chemical information at the single-molecule level. Here, the advanced one-dimensional convolutional neural network (1D-CNN) approach was applied to accurately identify the SERS spectral signature of industrial wastewaters for source tracing. A total of 66,000 SERS spectra were acquired from wastewaters of 22 factories across 10 industrial categories at three excitation wavelengths after data augmentation. The dataset was used to train a 1D-CNN model consisting of three convolutional layers to achieve adequate feature extraction of SERS spectra. As a proof-of-concept, multimixed wastewater samples were used to simulate practical pollution scenarios and evaluate the application potential of the model. The SERS-1D-CNN platform can identify the amount and factory information of wastewaters in multimixed samples, which achieves a recognition accuracy rate of 97.33%. The results suggest that even in a complex and unknown water environment, the 1D-CNN model can accurately identify industrial wastewaters in precollected datasets, exhibiting excellent potential in pollution source tracing.

Performance and mechanism of microbial fuel cell coupled with anaerobic membrane bioreactor system for fouling control

To remove membrane fouling, a bio-electrochemical system that can generate a micro-electric field and micro-current was constructed. After 11 days of operation, the trans-membrane pressure difference of membrane modules in the open- and closed-circuit groups increased by 35.8 kPa and 6.2 kPa, respectively. The concentrations of total polysaccharide and protein in the open-circuit group were 1.8 and 1.1 times higher than those in the closed-circuit group, respectively. In addition, X-ray photoelectron spectroscopy and thermogravimetric analysis showed that inorganic crystals such as calcium carbonate were present on the membrane surface, and the concentration of calcium ion in the control group was 14.7 times that of the experimental group. High-throughput sequencing demonstrated that the enrichment of some electroactive bacteria and other microorganisms has a positive effect on the control of membrane fouling. Therefore, this system can effectively alleviate membrane fouling of a bioreactor, by targeting the membrane foulants.

Quantitative models and potential surrogates for rapid evaluation and surveillance of chlorine disinfection efficacy in reclaimed water

Chlorine disinfection has become the most widely applied and indispensable technology in wastewater treatment and reuse to mitigate microbial risk and guarantee water safety. However, owing to complexities and high concentrations of contaminants in reclaimed water, rapid evaluation of chlorine disinfection efficacy is a crucial but challenging issue. Based on intensive experimental and statistical analyses, this study has established kinetic models and potential surrogates for rapid indication of the inactivation of microbial indicators and opportunistic pathogens during chlorine disinfection in different reclaimed waters. Overall, the constructed Selleck models performed very well to simulate log removal values (LRVs) of fecal coliforms, Pseudomonas aeruginosa and heterotrophic plate counts in all reclaimed water samples (R² = 0.877-0.990). Moreover, total and Peak A fluorescence intensity as well as fluorescence integral intensities in Regions II and IV were found to have high response sensitivities during the chlorination process. Nevertheless, their effectiveness to act as potential surrogates of LRVs of microbial indicators needs to be further validated. The results from this study can provide valuable information on microbial safety surveillance of disinfection toward sustainable and long-term water reuse.

Composition of dissolved organic matter (DOM) in wastewater treatment plants influent affects the efficiency of carbon and nitrogen removal

Wastewater treatment plants (WWTPs) play a critical role in receiving, removing, and discharging dissolved organic matter (DOM) in aquatic systems. To date, understanding the composition and fate of DOM in different WWTPs with various environmental and socioeconomic conditions is limited. This study analyzed DOM components in the influent and effluent samples from 49 WWTPs in China using EEM-PARAFAC and ESI-FT-ICR-MS methods. The influencing factors of DOM components in the influent were also analyzed. Geographic location and GDP showed significant (p < 0.05) correlations with DOM components in the influent. The removal efficiency of DOM in WWTPs was closely related to the DOM compositions, where carbohydrates, lipids, and protein-like components (removal efficiencies > 75 %) were more readily decomposed than the humic-like components, lignin, and tannin. The relative fraction of humic-like compound C3 in the influent was correlated negatively with total nitrogen (TN) and chemical oxygen demand (COD) removal in WWTPs (p < 0.05). Besides, the relative fraction of DOM containing the element sulfur also showed significant negative correlations with the humification of DOM (p < 0.05). The results from EEM-PARAFAC and ESI-FT-ICR-MS methods showed no obvious correlation for the DOM characterizations except for humic-like fluorescent fraction C3 and lignin, while significant positive correlations (p < 0.05) between the aromatic index (AI_mod) from the ESI-FT-ICR-MS analysis and the humification index (HIX) from spectrofluorimetry. This supports the use of these spectral indexes as simple surrogates to represent part chemical compositions in further research.

The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables

Dissolved oxygen (DO) forecasting is essential for aquatic managers responsible for maintaining ecosystem health and the management of water bodies affected by water quality parameters. This paper aims to forecast dissolved oxygen (DO) concentration using a multivariate adaptive regression spline (MARS) hybrid model coupled with maximum overlap discrete wavelet transformation (MODWT) as a feature decomposition approach for Surma River water using a set of water quality hydro-meteorological variables. The proposed hybrid model is compared with numerous machine learning methods, namely Bayesian ridge regression (BNR), k-nearest neighbourhood (KNN), kernel ridge regression (KRR), random forest (RF), and support vector regression (SVR). The investigational results show that the proposed model of MODWT-MARS has a better prediction than the comparing benchmark models and individual standalone counter parts. The result shows that the hybrid algorithms (i.e. MODWT-MARS) outperformed the other models (r = 0.981, WI = 0.990, RMAE = 2.47%, and MAE = 0.089). This hybrid method may serve to forecast water quality variables with fewer predictor variables.

EEM-PARAFAC as a convenient methodology to study fluorescent emerging pollutants degradation: (fluoro)quinolones oxidation in different water matrices

Commercial (fluoro)quinolones ((F)Qs), ciprofloxacin (CIP), enrofloxacin (ENR), ofloxacin (OFL), oxolinic acid (OA) and flumequine (FLU) (3 μM each), were degraded with solar-photo-Fenton in a compound parabolic concentrator photoreactor (total volume 5 L) in ultra-pure water at pH = 5.0, salty water at pH = 5.0, and simulated wastewater at pH = 5.0 and 7.5. Iron speciation (its hydrolysis and the complexation with (F)Qs 15 μM and/or chlorides 0.5 M) was calculated at pH 5.0, observing, negligible formation of Fe(III)-chloride complexes, and that >99 % of the total (F)Qs are forming complexes stoichiometry 1:1 with Fe(III) (which also increases the percentage of Fe(OH)²⁺), being minoritarian the free antibiotic form. On the other hand, EEM-PARAFAC (fluorescence excitation-emission matrices-parallel factor analysis) was employed to simultaneously study the behaviour of: i) 4 structure-related groups corresponding to parent pollutants and slightly oxidised by-products, ENR-like (including CIP), OFL-like, OA-like, FLU-like; ii) intermediates still showing (F)Q characteristics (exhibiting analogous fluorescent fingerprint to ENR-like one, but shifted to shorter wavelengths); iii) humic-like substances. The scores from the 4 PARAFAC components corresponding to the parent pollutants were plotted vs. accumulated energy, exhibiting slower decay than their individual removals (measured with HPLC-UV/vis) due to the contribution of the aforementioned by-products to the overall fluorescence. Moreover, thiabendazole (TBZ) 3 μM was added as fluorescence interference. The presence of (F)Qs greatly enhanced TBZ degradation due to (F)Q-Fe(III) complex formation, keeping iron active at pH = 5.0 for Fenton process. The EEM-PARAFAC model was able to recognise the former six components plus an additional one attributable to TBZ-like.

Identification of visible colored dissolved organic matter in biological and tertiary municipal effluents using multiple approaches including PARAFAC analysis

This study provided insights into the persistent yellowish color in biological and tertiary effluents of municipal wastewater through a multi-characterization approach and fluorescence excitation-emission matrix-parallel factor (EEM-PARAFAC) analysis. The characterization was performed on three to five full-scale municipal wastewater treatment plants (WWTPs), including differential log-transformed absorbance (DLnA) spectroscopy, resin fractionation, size-exclusion chromatography for apparent molecular weight analysis (SEC-AMW), and X-ray photoelectron spectroscopy (XPS) analysis. Hydrophobic acids (HPOA) were abundant in visible colored dissolved organic matter (DOM). The SEC-AMW result showed that the molecular weight of the colored substances in the secondary effluents is mainly distributed in the range of 2-3 kDa. Through XPS analysis, C-O/C-N and pyrrolic/pyridonic (N-5) were found to be positively correlated with chroma. PARAFAC component models were built on biological (two components) and tertiary effluent (three components) and the correlation analysis revealed that PARAFAC component 2 in biological effluent (BE-C2) and component 1 in tertiary effluent (TE-C1), which were ascribed to Hydrophobic acids and Humic acid-like, were the responsible visible colored DOM components cause yellowish color. In addition, component similarity testing found that the identified visible colored DOM PARAFAC BE-C2, and PARAFAC TE-C1 were identical (0.96) in physicochemical properties, with 4% removal efficacy on average, compared with 11% for invisible colored DOM. This implied that tertiary effluents containing colorants (TE-C1) were resistant to degradation/removal using different disinfection and filtration processes in advanced treatments. This sheds light on many physicochemical aspects of PARAFAC-identified visible colored DOM components and provides spectral data to build an online monitoring system.

The sensitive detection and mechanism of Fe-3,5-dimethyl pyrazole fluorescent sensor to diethylenetriamine pentamethylene phosphonic acid: Experimental study and quantum chemical calculation

Diethylenetriamine pentamethylene phosphonic acid (DTPMP) is one of the most commonly used amino organic phosphonates. The existing methods for DTPMP detection are complicated, time-consuming, and cannot detect trace DTPMP in the natural environment. In the present work, the Fe-based 3,5-dimethyl pyrazole fluorescent sensor (Fe-DP) was constructed. The addition of Fe³⁺ to DP solution can greatly decrease the fluorescent intensity of DP, while the addition of different concentrations of DTPMP will restore the fluorescence intensity of DP to different degrees, to achieve quantitative detection of DTPMP, and the detection limit (LOD) of DTPMP was lower as 0.105 μΜ. The Fe-DP fluorescent sensor exhibited excellent anti-interference ability and good stability. Moreover, the fluorescence quenching mechanism of DP by Fe³⁺ was revealed by UV absorption spectrum and Multiwfn wavefunction analysis based on density function theory (DFT). The results revealed that the excitation of DP belonged to local excitation, in which the electrons were donated primarily by the N atom with double bond and redistributed within the pyrazole ring.The fluorescence quenching of adding Fe³⁺ was not caused by resonance energy transfer or charge transfer, which did not belong to dynamic quenching, but due to the ground state complex formed by the coordination of Fe³⁺ and the double bond N atom on the DP pyrazole ring.

Using EEM-PARAFAC to identify and trace the pollution sources of surface water with receptor models in Taihu Lake Basin, China

The identification and apportionment of the multiple pollution sources are essential and crucial for improving the effectiveness of surface water resources management. In this study, the surface water samples were collected from Taihu Lake Basin, and the optimal water quality parameters for the receptor models were selected firstly with multivariate statistical analyses. In order to identify the potential pollution sources in surface water, dissolved organic matter (DOM) was analyzed with the excitation-emission matrix coupled with parallel factor analysis (EEM-PARAFAC). Through the Pearson correlation analysis of water quality parameters and DOM components, the pollution sources were further verified, i.e., agricultural activities, domestic sewage, phytoplankton growth/terrestrial input and industrial sources. In addition, principal component analysis (PCA) combined with the absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were employed to quantify pollution sources. Compared with PCA-APCS-MLR model, PMF model resulted in higher performance on evaluation statistics and lower proportion of unexplained variability, thus showed more realistic and robust representation. The results of PMF showed that agricultural activities (42.08%) and domestic sewage (21.16%) were identified as the dominant pollution sources of surface water in the study area. This study highlights the effectiveness of EEM-PARAFAC in identifying the pollution sources, and the applicability of PMF in apportioning the contributions of each potential pollution source in surface water.

DOM tracking and prediction of rural domestic sewage with UV-vis and EEM in the Yangtze River Delta, China

Compared with the urban sewage treatment plants, the operation of rural decentralized sewage facilities is trapped by the absence of professionals, thus having to be run dependently on the self-adaptive operation of the facilities, which makes timely monitoring particularly important. In this study, organic pollutants in rural domestic sewage and urban domestic sewage are analyzed using ultraviolet-visible (UV-vis) absorption spectroscopy, fluorescence excitation-emission matrix (EEM) and Fourier transform infrared reflectance (FTIR). Compared with the UV-vis absorption spectrum, EEM can not only make up the deficiency in the detection of some easily degradable organics in sewage, but also reveal the transformation of different components, thus indicating timely the treatment progress of rural sewage. Linear fitting of COD and spectrum shows that UV₂₅₄ combined with fluorescence excitation-emission at Ex/Em = 250/330 nm might be more suitable for the prediction of COD in rural water than the UV₂₅₄ alone. This is of great significance for guiding the self-adaptive operation of rural domestic sewage facilities, improving their stability and efficiency, so as to improve the rural living environment.