Fluorescence spectroscopy for wastewater monitoring: A review

Improving monitoring of dissolved organic matter from the wastewater treatment plant to the receiving environment: A new high-frequency in situ fluorescence sensor capable of analyzing 29 pairs of Ex/Em wavelengths

A high-frequency, in situ fluorescence probe, called Fluocopée®, has been developed in order to better monitor variations in both the quality and quantity of dissolved organic matter within various aquatic environments (e.g. wastewater, receiving environments) thanks to a wide choice of 29 measured Excitation/Emission wavelength pairs. This advance pave the way to new measurement possibilities in comparison with existing probes, which are usually only able to measure 1-4 fluorophores. The qualification tests of the Fluocopée® probe indicate a high level of accuracy for the measurements of tyrosine, tryptophan and humic acids solutions. Good repeatability and reproducibility are also observed. For the first time, this tool has been deployed in an urban watershed (Bougival, Seine River, downstream of Paris) and in the settled effluent from a wastewater treatment plant (Seine aval, Achères, France). This new high-frequency in situ probe offers great application potential, including organic matter quality and quantity monitoring at drinking and wastewater treatment plants (treatment optimization) and in continental and marine waters (the fate of organic matter in biogeochemical cycles).

Use of embedding immobilized biofillers to improve hydrolysis acidification efficiency in domestic wastewater treatment

This study evaluated the effectiveness of embedding immobilization technology in wastewater treatment and its capacity to enhance the hydrolysis acidification process. Based on this technology, a stable anaerobic environment has been maintained. Results showed that the rates of dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP) conversion both exceeded 98 % under short hydraulic retention time (HRT = 2h) and ambient temperature. Notably, acetic acid and propionic acid comprised up to 90.9 % of the total volatile fatty acids in the effluent, providing suitable carbon sources for downstream denitrification. 16S rRNA gene sequencing indicated that biofillers effectively enriched and retained functional bacteria, causing norank_Anaerolineaceae (11.6 %-29.7 %) and norank_Bacteroidetes_vadinHA17 (10.8 %-14.9 %) as the dominant genera in the reactor, which were crucial for refractory organic matter degradation. Immobilized biofillers effectively improved wastewater biodegradability, supporting a stable microbial community with high DON and DOP conversion rates as well as increased VFA accumulation.

Riverine seasonal rainfall event tracing of organic pollution sources using fluorescence fingerprint difference spectrum

Elucidating the dynamics of dissolved organic matter (DOM) transport and transformation under seasonal rainfall events is essential for the conservation of riverine ecosystems, for mitigating the effects of climate change, and for crafting informed water management strategies. Therefore, this study aimed to investigate the evolutionary characteristics of organic pollution sources during consecutive rainfall events in early spring and to quantify their relative contributions to the process of surface water pollution. The results showed seasonal rainfall induces water quality exceedances in rivers due to the combined impacts of terrestrial inputs and endogenous releases. Humic acid (HA) (region V) and fulvic acid (FA) (region III) emerged as the predominant organic matter in the water column, with their fluorescence intensity altering as rainwater flushed the riverbed. Sources of pollution include agricultural and urban domestic sources (AS + DS) (72.29 %), industrial and urban domestic and microbial sources (IS + DS + MS) (37.71 %), and agricultural and industrial sources (AS + IS) (63.32 %), indicating that agricultural surface pollution discharges contribute significantly. The gas-chromatography-mass spectrometry (GC-MS) further confirmed that exogenous inputs were predominantly comprised of particulate pollutants. This study underscores the efficacy of fluorescence difference spectrometry in delineating the migration and transformation of river pollution sources during seasonal rainfall and facilitating the implementation of targeted management strategies for river ecosystems.

A Strategy for Quantifying Microplastic Particles in Membrane Filtration Processes using Flow Cytometry

Microplastic (MP) pollution is ubiquitous in the aquatic environment, with significant quantities of MPs originating from municipal wastewater treatment plants. Efforts to evaluate and implement MP removal processes are underway, with membrane technologies often recommended as an "ideal" solution. A key challenge in evaluating these technologies involves efficiently quantifying MP concentrations in samples. Here, flow cytometry (FC) is demonstrated as an effective technique to obtain concentration measurements of plastic microbeads (MBs; 1-5 μm) suspended in water with/without added humic acid. Regardless of solution conditions, MB concentrations were easily quantified via FC. Subsequently, two microfiltration membranes were challenged to these suspensions. As measured via FC, the 0.45 μm membrane demonstrated effective MB rejection (>99%) whereas the 5 μm membrane exhibited a broad range of rejections (40% to >95%) depending on solution conditions and filtration time. Finally, a model was formulated utilizing FC forward light scattering intensity measurements to estimate MB sizes in samples. Using the model, a 33% reduction in median MB size, on average, was noted across the 5 μm membrane when filtering MBs suspended in humic acid solution, affirming a preferential permeation of smaller particles. Overall, this study advances MP quantification techniques towards validating removal processes.

Novel Pseudo-Two-Dimensional 19F NMR Spectroscopy for Rapid Simultaneous Detection of Amines in Complex Mixture

Rapid detection of amines in complex mixtures presents a significant challenge. Here, we introduce a novel nuclear magnetic resonance (NMR) method for amine detection utilizing a probe with two fluorine atoms in distinct chemical environments. Upon interaction with an amine, the probe generates two atomic resonance peaks, which are used to create coordinates, revealing fluorine chemical shifts on the 19F NMR spectroscopy. This innovative approach allows for the clear distinction of amine signals in a two-dimensional plane. This method has been effectively employed in analyzing amines in pharmaceuticals and amino acids in Ophiopogon japonicus and dry white wine, providing a robust and general approach for amine analysis.

Identifying the fate of dissolved organic matter in wastewater treatment plant effluent-dominated urban river based on fluorescence fingerprinting and flux budget approach

Effluent organic matter from wastewater treatment plants (WWTPs) is an important source of dissolved organic matter (DOM) in urban rivers worldwide and is an important water quality factor. Identifying the fate of DOM in urban river is crucial for water quality management. To address this concern, a fluorescent flux budget approach was conducted to probe the fate of DOM in WWTP effluent-dominated urban river, in combination with field measurement and fluorescence fingerprinting. An urban river receiving two WWTP effluents in Hefei City, China was chosen as the study site, where longitudinal measurements of river hydrology and water quality were performed. The fluorescence fingerprinting revealed the presence of two humic-like components (C1, C4), one fulvic-like component (C2) and one protein-like component (C3) in this investigated river, among which C2 and C4 were indicative of anthropogenic influences, closely associated with treated effluents. For each fluorescent component, the WWTP effluent contributed over 80 % of the total fluorescent dissolved organic matter (FDOM) input in this river. Using the developed FDOM flux budget model, it was found that the C1 and C3 were almost conserved within the waterbody, while the C2 and C4 experienced losses due to biogeochemical reactions. The decay rates of C2 and C4 were estimated to be 0.109-0.174 d-1 and 0.096-0.320 d-1, respectively. Spatial heterogeneity of decay rates for C2 and C4 were associated with the varied chemistries of the lateral input sources including two treated effluents and one tributary flow. Our study highlights that after treated effluent is released into the receiving waterbody, the FDOM would undergo loss from the waters particularly for anthropogenic fulvic-like substance C2 and humic-like substance C4. Additionally, the quantified FDOM decay rate in actual urban water environment provides insights for river water quality management, especially when using DOM as the surrogate indicator of organic pollutants.

Fluorescence sensor enabled control of contaminants of emerging concern in reclaimed wastewater using ozone-based treatment processes

Contaminants of emerging concern (CEC) pose significant challenges to environmental and human health. The development of the wastewater reuse sector, coupled with progressively stringent regulations, needs innovative systems that integrate advanced treatment processes with in-situ and real-time monitoring of CEC. This study investigates the use of a tryptophan-like fluorescence sensor for real-time and online monitoring of CEC within a pilot plant employing O3-based advanced oxidation processes (AOPs). Two tertiary wastewater effluents (WW-1 and WW-2) were tested, placing the pilot system downstream of two different wastewater treatment plants (WWTPs). Priority substances and micropollutants detected in the investigated water matrixes such as pharmaceuticals, per- and polyfluoroalkyl substances (PFAS) were selected as targeted compounds in this study. Fluorescence degradation was detected in real-time by the sensor, showing a high capability to detect fast changes in water quality induced by oxidation. Furthermore, the real-time fluorescence showed better sensitivity than lab-scale fluorescence in detecting the fast action of hydroxyl radicals (·OH) during the O3/H2O2 process, highlighting the importance of online monitoring. Selected CEC were degraded by AOPs with different percentages of removal efficiency (RE) (0% Collapse

Key Words

• Advanced oxidation process (AOP)
• Micropollutants
• Online fluorescence sensor
• Per- polyfluoroalkyl substances (PFAS)
• Peroxone
• Real-time monitoring

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Affiliation(s)

Luigi Marino Department of Civil Engineering and Architecture, University of Catania, Viale A. Doria 6, Catania, Italy
Erica Gagliano Department of Civil Engineering and Architecture, University of Catania, Viale A. Doria 6, Catania, Italy; Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
Domenico Santoro Department of Chemical and Biochemical Engineering, University of Western Ontario, London, Ontario N6A 5B9, Canada
Paolo Roccaro Department of Civil Engineering and Architecture, University of Catania, Viale A. Doria 6, Catania, Italy.

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Online monitoring of greywater reuse system using excitation-emission matrix (EEM) and K-PARAFACs

A currently increasing interest in water reuse is met with the concern about water quality. Excitation-emission matrix (EEM) measurements, which are widely implemented in laboratory analysis, emerge as a promising tool for characterizing both microbial and chemical water qualities in the online monitoring of water reuse systems. However, the robustness of EEM measurements has been rarely validated in actual online monitoring campaigns where predictions are made for new samples independent of those used to establish EEM analysis models, including the popular parallel factor analysis (PARAFAC). In this study, two strategies of conducting PARAFAC were examined for the online monitoring of a greywater reuse system using two EEM datasets from two monitoring periods for model establishment and model testing respectively. With the first strategy that is commonly used in laboratory analyses, an entire EEM datasets from one period was used to establish one PARAFAC model, and the maximum fluorescence intensity (Fmax) of a PARAFAC component was used to predict total cell count (TCC) in another period. However, under the disturbance of dissolved organic matter (DOM) fluorescence in the background, Fmax gave unreliable predictions in model testing. To address this problem, a second and novel strategy was proposed using an EEM clustering and PARAFAC component shift mining technique. This unsupervised algorithm, named K-PARAFACs, automatically groups EEMs into K clusters and on each cluster establishes a cluster-specific PARAFAC model with distinct component shapes. With this method, multiple PARAFAC models were established on one EEM dataset, with each model representing samples with certain TCC ranges and DOM compositions. In model testing, these cluster-specific PARAFAC models served as EEM classifiers. A new sample was not characterized by Fmax but by the cluster-specific model that best fitted the EEM signal of the sample with the least numerical error. The proposed strategy demonstrates its robustness by successfully predicting the TCC trend in test datasets. Our findings suggest that K-PARAFACs is a promising tool that enables robust qualitative monitoring of water reuse systems with background DOM variability.

Magnetite enhances As immobilization during nitrate reduction and Fe(II) oxidation by Acidovorax sp. strain BoFeN1

Arsenic (As) cycling in groundwater is commonly coupled to the biogeochemical cycling of iron (Fe) and the associated transformation of Fe minerals present. Numerous laboratory studies suggested that Fe minerals can act as nucleation sites for further crystal growth and as catalysts for abiotic Fe(II) oxidation. In view of the widespread existence of magnetite in anoxic environments where As is often dissolved, we firstly exploited magnetite to enhance As immobilization during nitrate-reducing Fe(II) oxidation (NRFO) induced by Acidovorax sp. strain BoFeN1, a mixotrophic nitrate-reducing Fe(II)-oxidizing bacterium that can oxidize Fe(II) through both enzymatic and abiotic pathways. Subsequently, we investigated how magnetite affects NRFO and As immobilization. Results demonstrated a significant increase in As(III) removal efficiency from 75.4 % to 97.2 % with magnetite, attributed to the higher amount of NRFO and As(III) oxidation promoted by magnetite. It was found that magnetite stimulated the production of extracellular polymeric substances (EPS), which could decrease the diffusion of nitrate in the periplasm of bacteria and shield them against encrustation, resulting in a more rapid reduction of nitrate in the system with magnetite than that without magnetite. Meanwhile, Fe(II) was almost completely oxidized in the presence of magnetite during the whole 72 h experiment, while in the absence of magnetite, 47.7 % of Fe(II) remained, indicating that magnetite could obviously accelerate the chemical oxidation of Fe(II) with nitrite (the intermediates of nitrate bioreduction). Furthermore, the formation of labile Fe(III), an intermediate product of electron transfer between Fe(II) and magnetite, was reasonably deduced to be vital for anoxic As(III) oxidation. Additionally, the XPS analysis of the solid phase confirmed the oxidation of 43.8 % of As(III) to As(V). This study helps to understand the biogeochemical cycling of Fe and As in the environment, and provides a cost-effective and environmentally friendly option for in situ remediation of As-contaminated groundwater.

Online control of UV and UV/H2O2 processes targeted for the removal of contaminants of emerging concern (CEC) by a fluorescence sensor

This study assessed the online and real-time monitoring of contaminants of emerging concern (CEC) using a microbial/tryptophan-like fluorescence sensor in a quaternary AOP (advanced oxidation process) pilot plant installed downstream of a tertiary municipal wastewater treatment plant (WWTP). Real-time fluorescence measurements were validated with lab-scale tryptophan-like fluorescence. Changes in water quality induced by different UV or UV/H2O2 doses were detected by the fluorescence sensor allowing real-time control of processes. The removal of CEC was discussed considering their photo-susceptibility and reactivity with •OH and then classified into three groups based on their reactivity and removal efficiency (RE). Linear models of CEC removal developed using real-time fluorescence removal as a surrogate parameter resulted very accurate (overall R2≥0.90) for most of CEC. Furthermore, real-time fluorescence data were successfully used to predict i) pseudo-observed first-order degradation rate constants of CEC (R2=0.99), and ii) UV doses during both UV and UV/H2O2 processes (R2>0.90). The findings of this study demonstrated that fluorescence sensors can be employed in operational relevant environment to monitor a broad range of CEC and control UV doses during UV-AOPs. Therefore, the implementation of fluorescence sensors is expected for optimizing costs, energy consumption and efficiency of quaternary wastewater treatments.

High-throughput fluorescence quantification method based on inner filter effect and fluorescence imaging analysis

The application of the inner filter effect (IFE) in fluorescent substance determination is gaining popularity. In this paper, a theory of the fluorescence distribution along with the excitation light path is derived from our previous research about the spatial micro-element method. According to the relationship between the summation of fluorescence intensities along the vertical direction at a certain position on the excitation light path and the position, a high-concentration and wide-range fluorescent substance quantification method based on the IFE and fluorescence imaging analysis is proposed. Correspondingly, a high-throughput fluorescent substance quantification detection system is constructed. In order to validate the method, solutions of rhodamine B in different concentrations are used for principle validation, concentration prediction, and experimental investigation on the influence of integration time and lens distortion. The high-throughput system enables the simultaneous measurement of six samples, realizing the high-concentration and wide-range quantification of rhodamine B (100-600 mg/L) with high precision (R2 = 0.9992, MRE = 2.34 %). By setting the filter wheel, the system can measure the concentration of fluorescent substances with different emission wavelengths. The improvement of experimental device is expected to reduce the single sample capacity to tens of microliters and increase the overall sample quantity to tens or even hundreds. The proposed method and system are beneficial to fluorescence measurement in fields such as biomedicine and dye research and to the improvement of high-throughput fluorescence quantitative PCR instruments.

Ecofriendly Approach for the Determination of Selected Aldehydes by Fluorescence Quenching of L-Tryptophan

It is a fluorescence-based study to examine the interaction between L-tryptophan and a selection of aldehydes, namely furfural (furan-2-carbaldehyde), 3-hydroxybenzaldehyde, salicylaldehyde (2-hydroxybenzaldehyde), 3-nitrobenzaldehyde, and 4-bromobenzaldehyde. The investigation took place in an aqueous environment, revealing that all five aldehydes induced quenching of the fluorescence intensity of L-tryptophan. By employing the Stern-Volmer equation to describe the quenching process, we constructed Stern-Volmer plots and derived Stern-Volmer constants. These constants (KSV) ranged from 2.87 × 104 mol L- 1 to 5.75 × 104 mol L- 1. Notably, the values of the Stern-Volmer constants varied among the different aldehydes, with the following order: 3-hydroxybenzaldehyde(3-HBA) > 4-bromobenzaldehyde (4-BBA) > 3-nitrobenzaldehyde > furan-2-carbaldehyde > salicylaldehyde. Consequently, our findings highlighted 3-hydroxybenzaldehyde as the most potent quencher, while 2-hydroxybenzaldehyde displayed the least sensitivity to quenching. Additionally, we determined the detection and quantification limits for the investigated aldehydes, resulting in ranges of 3.87 × 10- 12 to 8.25 × 10- 6 and 1.29 × 10- 11 to 2.75 × 10- 5, respectively. This research paves the way for the development of novel fluorescence probe-based sensors and offers valuable techniques for analyzing aldehydes within environmental and biological samples.

Environmental and Human Health Problems Associated with Hospital Wastewater Management in Zimbabwe

PURPOSE OF THE REVIEW

Wastewater is a term used to describe water that has undergone degradation in quality owing to anthropogenic activities or natural processes. Wastewater encompasses liquid waste originating from academic institutions, households, agricultural sector, industries, mines and hospitals. Hospital wastewater contains potentially hazardous substances including residues of pharmaceuticals, radioisotopes, detergents and pathogens, with detrimental impacts to the environment and human health. Nevertheless, studies related to hospital waste management are limited in Africa, particularly in Southern Africa. This research offers an overview of aspects surrounding hospital wastewater in Southern Africa, focusing on Zimbabwe. Already published and grey literature was reviewed to compile the paper.

RECENT FINDINGS

Number of patients, nature of medical services offered and hospital size influences generation of hospital wastewater. Partially and non-treated hospital wastewater is managed together with municipal wastewater. Management of hospital wastewater is impeded by shortage of resources, lack of co-ordination among responsible authorities and ineffective legal framework enforcement, among other challenges. Inappropriate hospital wastewater management results in environmental contamination, causing human ailments. Attainment of sustainable hospital wastewater management requires clearly defined and enforced legislation, collaboration of accountable stakeholders, sufficient resources and enhanced awareness of involved stakeholders. Application of technologies that uphold recycling and reuse of wastewater is essential to reach Sustainable Development Goals, Zimbabwe Vision 2030 and National Development Strategy 1 targets, particularly those dealing with environmental protection while upholding human health.

Advancing fluorescence tracing with 3D-2D spectral conversion: A mixed culture on microbial degradation mechanisms of DOM from a large-scale watershed

Fluorescence tracing, known for its precision, rapid application, and cost-effectiveness, faces challenges due to the microbial degradation of dissolved organic matter (DOM) in aquatic environments, altering its original spectral fingerprint. This study conducted a 15-day microcosm experiment to examine the effects of biodegradation on the spectral properties of DOM from various sources: livestock excrement (EXC), urban sewage (URB), industrial wastewater (IND), and riparian topsoil (tDOM). Our findings show that while the spectral structures of DOM from different sources change during 15 days of microbial degradation, these changes do not overlap or interfere with each other. However, distinguishing between tDOM and URB in the presence of both IND and EXC is only possible at high resolution. Spectral index calculations revealed significant fluctuations and interference in FI and BIX indices among samples from different sources due to microbial degradation. In contrast, the HIX index exhibited independent fluctuations and remained a reliable spectral index for tracing. LEfSe (Linear discriminant analysis Effect Size) identified characteristic bio-indicators (CBI) for each DOM source. The CBI for tDOM and URB differed significantly; tDOM showed a marked CBI only within the first four days of microbial degradation, with a sharp decline in abundance thereafter, while URB's CBI remained abundant for 12 days. Similarly, IND's CBI maintained high relative abundance for the first 12 days. EXC's CBI was unique, showing a distinct and stable community only after six days of degradation, likely due to its high bioavailability and initial rapid microbial utilization. This study addresses the temporal variability in spectral tracing techniques caused by pollutant biodegradation. We developed a combined spectral-biological tracing technique using the "three-dimensional to two-dimensional" method along with bio-indicators, enhancing the accuracy and timeliness of spectral tracing.

Fluorescence and Photophysical Properties of Anthracene and Phenanthrene in Water

Polyaromatic hydrocarbons (PAHs) are widely spread pollutants in the environment, including soil and water. Anthracene (anth) and phenanthrene (phen) pose severe health impacts on human lives due to their carcinogenic nature by increasing cancer risk to the skin, lungs, and bladder. Fluorescence spectroscopy is a promising , efficient and straightforward tool for characterizing these trace PAHs in water. Therefore, the current work provides a detailed insight into the fluorescence properties of anth and phen in water. The fluorescence EEMs (excitation-emission matrices) of anth showed emissions at 380 nm, 400 nm, and 425 nm with single excitation at 250 nm, whereas phen showed two emissions < 380 nm, at 350 nm and 365 with single excitation at 250 nm. Then the theoretical EX/EM wavelengths were calculated by DFT and CIS-B3LYP for these compounds in water. The environmental effect of pH variation on fluorescence EEM shows a significant difference in fluorescence intensity without changing in peak locations, with highest fluorescence intensity at neutral pH than acidic and alkaline. Furthermore, the theoretical pH effect was described for the first time by simulating the protonated (+ 1), deprotonated (-1) and neutral molecules in water at the DFT level of theory. The variation in simulated oscillator strengths was similar in trend with the experimental fluorescence intensity of these compounds. The HOMO-LUMO were calculated to obtain the energy gap, molecular softness, molecular hardness, electronic potential and electrophilicity of anth and phen. To find the fluorophore contribution, the fluorescence of homogeneous mixture of both isomers was analyzed, which showed an enhanced fluorescence intensity of anth by 12-20%, whereas a decrease of 9-14% was observed in phen. This study describes that the fluorescence technique could be a fast and easy method to distinguish and identify PAHs isomers (anth and phen) in water.

Optimizing photocatalytic performance with Ag-doped ZnO nanoparticles: Synthesis and characterization

The development of nanotechnology has significantly impacted the improvement of photocatalytic performance of ZnO NPs. In this study synthesis of pure ZnO and Ag-ZnO nanoparticles via a co-precipitation method at varying Ag concentrations (1 %, 2 %, 3 %, 4 % and 6 %) to enhance their photo catalytic efficacy. X-ray diffraction (XRD) analysis estimates crystallite size which decreased by increasing Ag concentration, ranging from 30.6 nm (Pure ZnO) to 22.5 nm 6 % Ag-doped ZnO. Scanning electron microscopy (SEM) revealed decrease in particle size with increasing Ag content. UV-Vis spectroscopy indicating a narrowed band gap of optimal sample. Photocatalytic activity of the synthesized nanoparticles was evaluated using methylene orange (MO) dye degradation under light irradiation. The MO concentration exhibited a decrease with increasing irradiation time in the presence of photocatalysts. Recombination rate of NPs decreases by increasing the concentration of Ag i.e. 4%Ag dope ZnO NPs have lowest recombination rate and maximum degradation efficiency. FTIR analysis confirms the preparation of Ag-doped ZnO NPs. This improvement can be credited to the synergistic effect of Ag doping, leading to a narrowed band gap and potentially maximum degradation of MO by using Ag-doped ZnO NPs.

Photo-aging of brominated epoxy microplastics in water under simulated solar irradiation

Microplastics have become an increasingly concerning pollutant in aquatic environments, and photodegradation is their main degradation pathway in water. Gaining insight into the transformation process of microplastics will enhance our understanding of their behavior and destiny in natural environments. This paper studied the aging process of BER microplastics in aquatic environments under simulated sunlight and investigated the changes in the physical and chemical properties of microplastics and the changes in the leachate. During the photodegradation process, BER-MPs underwent extensive oxidation and reduction in particle size, and the originally smooth surface developed numerous voids, accompanied by yellowing. Introduction of O atoms in the molecular chains increased their hydrophilicity, resulting in the polymer chains breaking away from the plastic particles and dissolving in water. Also, once BER was excited by light, environmentally persistent free radicals are produced on its surface. Moreover, the breaking of C-Br bonds occurred during the photodegradation process of BER-MPs, which suggested that tetrabromobisphenol A would be transformed during the photoaging process of BER even if it was covalently bound to BER.

Chromophoric dissolved organic matter traces seasonally changing coastal processes in a river-influenced region of the western Bay of Bengal

The optical characteristics of colored dissolved organic matter (CDOM) serve as a convenient tool for evaluating coastal processes, e.g., river runoff, anthropogenic inputs, primary production, and bacterial/photochemical processes. We conducted a study on the seasonal and spatial variability of absorbance and fluorescence characteristics of CDOM and nutrients in the coastal waters near the Gauthami estuary of River Godavari, the largest peninsular river of India, for a year. The surface aCDOM(350) showed a significant inverse relation with salinity in the coastal region, indicating a conservative mixing of marine and terrestrial end members. The aCDOM(350) was not conservative in the offshore (100 m isobath) waters due to enrichment by secondary sources. Seasonal variability in optical properties indicated diverse sources for CDOM, as revealed by principal component analysis. The excitation-emission matrix (EEM) spectra followed by parallel factor analysis (EEM-PARAFAC) revealed four distinct fluorophores. The tyrosine (B) fluorophore showed a predominant increase in the post-monsoon season (October to January), while tryptophan (T) was relatively more enriched, coincident with nutrient enrichment and transparency increase during the early monsoon phase (July). The biological index (BIX), which reflects recent photosynthetic activity, also displayed relatively higher values during the early monsoon. The humic fluorophores A and M, and humification index (HIX) were relatively enriched during the later phase of monsoon (July-October). HIX was > 4 in a few samples of the offshore region (100-m isobath) and indicated a probable contamination from drill-mud (bentonite) used in hydrocarbon exploration. During the monsoon, the relationship between T and B with CDOM was not evident due to the masking of B fluorescence in intact protein. However, during the post-monsoon (POM) and pre-monsoon (PRM) periods, this masking effect was not observed, likely due to protein degradation via bacterial and photochemical processes, respectively. Temporal variability in nutrients indicated that high ammonium levels were produced during POM (OM bacterial degradation), and high nitrite levels were observed during PRM (due to primary production). This study provides foundational insights into the use of CDOM for understanding the impact of diverse environmental, river discharge, and anthropogenic factors on coastal ecosystems.

Comparing Conventional and Advanced Approaches for Heavy Metal Removal in Wastewater Treatment: An In-Depth Review Emphasizing Filter-Based Strategies

Various industrial activities release heavy metal ions into the environment, which represent one of the major toxic pollutants owing to their severe effects on the environment, humans, and all living species. Despite several technological advances and breakthroughs, wastewater treatment remains a critical global issue. Traditional techniques are dedicated to extracting heavy metal ions from diverse wastewater origins, encompassing coagulation/flocculation, precipitation, flotation, and ion exchange. Their cost, side toxicity, or ineffectiveness often limit their large-scale use. Due to their adaptable design, simple operation, and reasonable cost, membrane filtration and adsorption have proven their efficiency in removing metals from wastewater. Recently, adsorption-based filters have appeared promising in treating water. Within this range, filters incorporating natural, synthetic, or hybrid adsorbents present an appealing alternative to conventional approaches. This review aims to list and describe the conventional and advanced wastewater treatment methods by comparing their efficiency, cost, and environmental impact. Adsorption-based filters were highlighted due to the significant advantages they can provide.

Interfacial interactions between minerals and organic matter: Mechanisms and characterizations

Minerals and organic matter are essential components of soil, with minerals acting as the "bone" and organic matter as the "skin". The interfacial interactions between minerals and organic matter result in changes in their chemical composition, structure, functional groups, and physical properties, possessing a significant impact on soil properties, functions, and biogeochemical cycles. Understanding the interfacial interactions of minerals and organic matter is imperative to advance soil remediation technologies and carbon targets. Consequently, there is a growing interest in the physicochemical identification of the interfacial interactions between minerals and organic matter in the academic community. This review provides an overview of the mechanisms underlying these interactions, including adsorption, co-precipitation, occlusion, redox, catalysis and dissolution. Moreover, it surveys various methods and techniques employed to characterize the mineral-organic matter interactions. Specifically, the up-to-date spectroscopic techniques for chemical information and advanced microscopy techniques for physical information are highlighted. The advantages and limitations of each method are also discussed. Finally, we outline future research directions for interfacial interactions and suggests areas for improvement and development of characterization techniques to better understand the mechanisms of mineral-organic matter interactions.

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 %.

Fluorescence in depth: integration of spectroscopy and imaging with Raman, IR, and CD for advanced research

Fluorescence spectroscopy serves as a vital technique for studying the interaction between light and fluorescent molecules. It encompasses a range of methods, each presenting unique advantages and applications. This technique finds utility in various chemical studies. This review discusses Fluorescence spectroscopy, its branches such as Time-Resolved Fluorescence Spectroscopy (TRFS) and Fluorescence Lifetime Imaging Microscopy (FLIM), and their integration with other spectroscopic methods, including Raman, Infrared (IR), and Circular Dichroism (CD) spectroscopies. By delving into these methods, we aim to provide a comprehensive understanding of the capabilities and significance of fluorescence spectroscopy in scientific research, highlighting its diverse applications and the enhanced understanding it brings when combined with other spectroscopic methods. This review looks at each technique's unique features and applications. It discusses the prospects of their combined use in advancing scientific understanding and applications across various domains.

Mechanochemical synthesis of microscale zero-valent iron/N-doped graphene-like biochar composite for degradation of tetracycline via molecular O2 activation

In this study, we prepared a micron zero-valent iron/N-doped graphene-like biochar (mZVI/NGB) composite using a mechanochemical method for tetracycline (TC) degradation through O2 activation. The mZVI and NGB components formed a strong coupling catalytic system, with mZVI acting as an electron pool and NGB as a catalyst for H2O2 generation. Under circumneutral pH (5.0-6.8), the mZVI/NGB composite exhibited exceptional TC removal efficiency, reaching nearly 100 % under optimal conditions. It also showed good tolerance to co-existing anions, such as Cl-, SO42-, and humic acid. Further studies found that the TC degradation mechanism was mainly ascribed to the non-radical pathway (1O2 and electron transfer), and the Fe2+/Fe3+ redox cycle on the composite's surface also played a crucial role in maintaining catalytic activity. This research contributes to the development of advanced materials for sustainable and effective water treatment, addressing pharmaceutical pollutant contamination in water sources.

Domestic wastewater treatment by Pistia stratiotes in constructed wetland

The objective of the study was to evaluate the performance of Pistia stratiotes for treatment of domestic wastewater in a free surface water flow constructed wetland. The objective of the study was to evaluate contaminants removal efficiency of the constructed wetland vegetated with P. stratiotes in treatment of domestic wastewater against Hydraulic retention time (HRT) of 10, 20 and 30 days was investigated. This asks for newer and efficient low-cost nature-based water treatment system which along with cost takes into consideration the sustainability of the ecosystem. Five constructed wetland setups improved the wastewater quality and purify it significantly by reducing the TDS by 83%, TSS by 82%, BOD by 82%, COD by 81%, Chloride by 80%, Sulfate by 77%, NH3 by 84% and Total Oil and Grease by 74%. There was an increase in pH of about 11.9%. Color and odor of wastewater was also improved significantly and effectively. It was observed that 30 days' HRT was optimum for the treatment of domestic wastewater. The final effluent was found to be suitable as per national environmental quality standards and recycled for watering plants and crop irrigation but not for drinking purposes. The treatment in constructed wetland system was found to be economical, as the cost of construction only was involved and operational and maintenance cost very minimal. Even this research was conducted on the sole purpose of commuting the efficiency of pollutant removal in short span time.

Characteristics of DOM and Their Relationships with Potentially Toxic Elements in the Inner Mongolia Section of the Yellow River, China

The characterization of dissolved organic matter (DOM) is important for better understanding of the migration and transformation mechanisms of DOM in water bodies and its interaction with other contaminants. In this work, fluorescence characteristics and molecular compositions of the DOM samples collected from the mainstream, tributary, and sewage outfall of the Inner Mongolia section of the Yellow River (IMYR) were determined by using fluorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). In addition, concentrations of potentially toxic elements (PTEs) in the relevant surface water and their potential relationships with DOM were investigated. The results showed that the abundance of tyrosine-like components increased significantly in downstream waters impacted by outfall effluents and was negatively correlated with the humification index (HIX). Compared to the mainstream, outfall and tributaries have a high number of molecular formulas and a higher proportion of CHOS molecular formulas. In particular, the O5S class has a relative intensity of 41.6% and the O5-7S class has more than 70%. Thirty-eight PTEs were measured in the surface water samples, and 12 found above their detective levels at all sampling sites. Protein-like components are positively correlated with Cu, which is likely indicating the source of Cu in the aquatic environment of the IMYR. Our results demonstrated that urban wastewater discharges significantly alter characteristics and compositions of DOM in the mainstream of IMYR with strongly anthropogenic features. These results and conclusions are important for understanding the role and sources of DOM in the Yellow River aquatic environment.

Fluorescence fingerprint as an indicator to identify urban non-point sources in urban river during rainfall period

Nowadays, the urban non-point source (NPS) pollution gradually evolved as the main contributor to urban water contamination since the point source pollution was effectively controlled. It was imperative to perform urban NPS identification in urban river to meet the requirements of precise source governance. In this study, the real-time detection about water quality parameters and fluorescence fingerprints (FFs) was performed for BX River and its outlets during rainfall period. EEM-PARAFAC and component similarity analyses discovered that the pollution encountered by BX River mainly came from road runoff and untreated municipal wastewater (UMWW) overflow. The C1 (tryptophan-like) and C3 (terrestrial humic-like) components located at Ex/Em = ∼230(280)/340 and ∼275/430 nm were both detected in these two kinds of urban NPS. The C2 components of road runoff and UMWW overflow displayed remarkable differences, which located at Ex/Em = 250/385 and 245/365 nm, respectively, thus could be served as indicators for distinguishing them. During rainfall period, the outflow from rainwater outlets (RWOs) constantly showed similar FF features to road runoff, while the FFs of outflow from combined sewer outlets (CSOs) alternated between those of road runoff and UMWW overflow. The FF features of sections in BX River changed in response to the dynamic variations in FFs of the outlets, which revealed real-time pollution causes of BX River. This work not only realized the identification and differentiation of urban NPS, but also elucidated the dynamic variations of pollution characteristics throughout the entire process of "urban NPS-outlets-urban river", and demonstrated the feasibility of FF technique in quickly diagnosing the pollution causes of urban river during rainfall period, which provided important guidance for urban NPS governance.

A low-cost and portable fluorometer based on an optical pick-up unit for chlorophyll-a detection

Chlorophyll-a (Chl-a) fluorescence detection is an important technique for monitoring water quality. In this work, we proposed an approach that employs the mass-produced low-cost optical pick-up unit (OPU) extracted from the high-definition digital versatile disc (HD-DVD) drive as the key optical component for our chlorophyll-a fluorometer. The built-in blue-violet 405 nm laser diode of the OPU acts as the excitation light to perform laser-induced fluorescence (LIF). The laser driver and a series of intrinsic lenses within the OPU, such as an objective lens with a numerical aperture (NA) of 0.65 and a collimating lens, help reduce the size, cost, and system complexity of the fluorometer. By integrating off-the-shelf electronic components, miniaturized optical setups, and 3D-printed assemblies, we have developed a low-cost, easy-to-make, standalone, and portable fluorometer. Finally, we validated the performance of the device for chlorophyll-a fluorescence detection under laboratory and on-site conditions, which demonstrated its great potential in water monitoring applications. The limit of detection (LOD) for chlorophyll-a is 0.35 μg/L, the size of the device is 151 × 100 × 80 mm3, and the total cost of the proposed fluorometer is as low as 137.5 USD. © 2023 Elsevier Science. All rights reserved.

Dynamic Modelling, Process Control, and Monitoring of Selected Biological and Advanced Oxidation Processes for Wastewater Treatment: A Review of Recent Developments

This review emphasizes the significance of formulating control strategies for biological and advanced oxidation process (AOP)-based wastewater treatment systems. The aim is to guarantee that the effluent quality continuously aligns with environmental regulations while operating costs are minimized. It highlights the significance of understanding the dynamic behaviour of the process in developing effective control schemes. The most common process control strategies in wastewater treatment plants (WWTPs) are explained and listed. It is emphasized that the proper control scheme should be selected based on the process dynamic behaviour and control goal. This study further discusses the challenges associated with the control of wastewater treatment processes, including inadequacies in developed models, the limitations of most control strategies to the simulation stage, the imperative requirement for real-time data, and the financial and technical intricacies associated with implementing advanced controller hardware. It is discussed that the necessity of the availability of real-time data to achieve reliable control can be achieved by implementing proper, accurate hardware sensors in suitable locations of the process or by developing and implementing soft sensors. This study recommends further investigation on available actuators and the criteria for choosing the most appropriate one to achieve robust and reliable control in WWTPs, especially for biological and AOP-based treatment approaches.

Deciphering fluorescent and molecular fingerprint of dissolved organic matter leached from microplastics in water

Despite extensive research into the presence and behavior of microplastics (MPs) in the environment, limited attention has been given to the investigation of the characteristics of dissolved organic matter (DOM) that leaches from MPs (MPs-DOM). Herein, two frequently encountered plastic particles in aquatic environments, specifically polyethylene terephthalate (PET)- and polyethylene (PE)-MPs, were subjected to leaching in the aquatic settings for seven days, both in the absence of light and under UV irradiation. Measurements of dissolved organic carbon (DOC) indicated that UV exposure enhanced the liberation of DOM from PET-MPs, while PE-MPs did not exhibit such leaching. After UV treatment for seven days, the DOM released from PET-MPs increased by 25 times, while that from PE-MPs remained almost unchanged. Then, the molecular diversity and the evolving formation of DOM originating from different MPs were comprehensively analyzed with fluorescence excitation-emission matrix (EEM) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Specifically, both PET- and PE-DOM exhibited three fluorescence signatures, with the predominant C1 (tryptophan-like) component showing a decline in PET-DOM and a rise in PE-DOM during aging. The FT-ICR-MS analysis unveiled that PET-DOM grew more recalcitrant under UV exposure, while PE-DOM became increasingly labile. In brief, UV irradiation influences MPs-DOM release and transformation differently, depending on the plastic composition. This highlights the significance of exploring MPs-DOM transformation in securing environmental safety.

Animal Feedlots and Domestic Wastewater Discharges are Likely Sources of N-Nitrosodimethylamine (NDMA) Precursors in Midwestern Watersheds

N-nitrosodimethylamine (NDMA) precursor concentrations along four major rivers in Minnesota, USA were quantified and correlated with watershed land cover types, anthropogenic activity, and organic matter characteristics. River water samples (36 in total) were chloraminated under uniform formation conditions (UFC) before and after lime-softening treatment, and the resulting NDMA concentrations were quantified (NDMAUFC). Regarding land cover, NDMAUFC in raw river water exhibited weak positive correlations with urban land (ρ = 0.33, p = 0.05) and cropland coverage (ρ = 0.35, p = 0.04). For anthropogenic activity, NDMAUFC in raw river water positively correlated with the number of feedlots (ρ = 0.57), total weight of animals (ρ = 0.68), and total number of domestic wastewater treatment plants (WWTPs; ρ = 0.63) with p < 0.01. NDMAUFC positively correlated with region IV fluorescence intensity from fluorescence excitation-emission spectra (ρ = 0.70, p < 0.01). Lime softening of river water typically increased NDMAUFC and preferentially removed organic matter that fluoresces in region V, suggesting that the organic matter in this region decreases NDMAUFC by competing for available chloramines. Overall, animal feedlots, along with domestic WWTPs, are predominant sources of NDMA precursors in the studied watersheds, while croplands and urban runoff are of lesser importance.

Molecular-level insights into the transformation and degradation pathways of dissolved organic matter during full-scale swine wastewater treatment

The rapid development of swine farming has resulted in the generation of a large amount of swine wastewater (SW), and dissolved organic matter (DOM) has a crucial role in determining the efficiency and safety of SW treatment. In this study, the transformation and influential mechanisms of DOM on the quality of SW effluent during full-scale SW treatment in actual engineering were systematically investigated using multispectral analysis and the Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) technique. The results showed that S-containing, reduced, saturated, and less aromatic molecules were preferentially removed in the C-AF, while C-S preferentially removed reduced, unsaturated, and aromatic molecules, as well as molecules with large molecular weights. And in the two-stage A/O, the degradation of organic matter and DOM transformation occurred mainly in the A/O-1, with the A/O-2 acting as a supplement to further enhance the humification of DOM. Furthermore, the AOP preferentially removed lignin-like and highly unsaturated compounds, replacing them with a new generation of substances such as proteins and tannins with low aromaticity and unsaturation. More deeply, oxygen addition reactions dominate in both A/O and AOP. Specifically, the most common types of reactions in the A/O were the corresponding potential precursor-product pairs based on methyl to carboxylic acid (-H2 + O2) and alcohol to carboxylic acid (-H2 + O), while tri-hydroxylation (+O3) and di-hydroxylation (+H2O2) reactions were predominant in the AOP. Finally, the study's findings might suggest improving the actual engineering by prioritizing the AOP before the A/O-2 and using the C-S for safeguard treatment of the A/O-2 effluent. It is reliable that this kind of adjustment guarantees safe drainage indications and raises each process unit's efficiency in purifying.

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.

Raman spectroscopy applied to online monitoring of a bioreactor: Tackling the limit of detection

An in-situ monitoring model of alcoholic fermentation based on Raman spectroscopy was developed in this study. The optimized acquisition parameters were an 80 s exposure time with three accumulations. Standard solutions were prepared and used to populate a learning database. Two groups of mixed solutions were prepared for a validation database to simulate fermentation at different conditions. First, all spectra of the standards were evaluated by principal component analysis (PCA) to identify the spectral features of the target substances and observe their distribution and outliers. Second, three multivariate calibration models for prediction were developed using the partial least squares (PLS) method, either on the whole learning database or subsets. The limit of detection (LOD) of each model was estimated by using the root mean square error of cross validation (RMSECV), and the prediction ability was further tested with both validation datasets. As a result, improved LODs were obtained: 0.42 and 1.55 g·L-1 for ethanol and glucose using a sub-learning dataset with a concentration range of 0.5 to 10 g·L-1. An interesting prediction result was obtained from a cross-mixed validation set, which had a root mean square error of prediction (RMSEP) for ethanol and glucose of only 3.21 and 1.69, even with large differences in mixture concentrations. This result not only indicates that a model based on standard solutions can predict the concentration of a mixed solution in a complex matrix but also offers good prospects for applying the model in real bioreactors.

Illuminating Bacterial Contamination in Water Sources: The Power of Fluorescence-Based Methods

Bacterial contamination of water sources is a significant public health concern, and therefore, it is important to have accurate and efficient methods for monitoring bacterial concentration in water samples. Fluorescence-based methods, such as SYTO 9 and PI staining, have emerged as a promising approach for real-time bacterial quantification. In this review, we discuss the advantages of fluorescence-based methods over other bacterial quantification methods, including the plate count method and the most probable number (MPN) method. We also examine the utility of fluorescence arrays and linear regression models in improving the accuracy and reliability of fluorescence-based methods. Overall, fluorescence-based methods offer a faster, more sensitive, and more specific option for real-time bacterial quantification in water samples.

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.

Gold nanoparticles embedded Fe-BTC (AuNPs@Fe-BTC) metal-organic framework as a fluorescence sensor for the selective detection of As(III) in contaminated waters

In this article, a new off-mode fluorescent platform based on the metal-organic framework (MOF) is introduced as a highly selective and rapid chemical sensor for the detection of As(III) in water and wastewater samples. A typical Fe-BTC (BTC = 1,3,5-benzenetricarboxylate or trimesic acid) MOF was used as a porous template for loading gold nanoparticles (AuNPs@Fe-BTC MOF). The physicochemical properties of AuNPs@Fe-BTC MOF were characterized by Fourier-transform infrared spectroscopy (FT-IR), Field emission scanning electron microscopy (FESEM), Energy-dispersive X-ray spectroscopy (EAX), element mapping (MAP) and X-ray diffraction (XRD) analysis. This sensing method for As(III) ions is based on the fact that the fluorescence intensity of AuNPs@Fe-BTC MOF sensor decreases in proportion to the increase in As(III) concentration. The main effective factors on the performance of the sensor signal such as MOF dosage, sonication time, pH and reaction time were optimized. Under optimized conditions, the calibration graph was linear in the concentration range of 0.5-380 ng mL-1 of As(III) and the limit of detection was 0.2 ng mL-1. The proposed method was successfully validated by addition/recovery experiments by the determination of As(III) in four river water and two wastewater effluent samples.

In Situ Water Quality Monitoring Using an Optical Multiparameter Sensor Probe

Optical methods such as ultraviolet/visible (UV/Vis) and fluorescence spectroscopy are well-established analytical techniques for in situ water quality monitoring. A broad range of bio-logical and chemical contaminants in different concentration ranges can be detected using these methods. The availability of results in real time allows a quick response to water quality changes. The measuring devices are configured as portable multi-parameter probes. However, their specification and data processing typically cannot be changed by users, or only with difficulties. Therefore, we developed a submersible sensor probe, which combines UV/Vis and fluorescence spectroscopy together with a flexible data processing platform. Due to its modular design in the hardware and software, the sensing system can be modified to the specific application. The dimension of the waterproof enclosure with a diameter of 100 mm permits also its application in groundwater monitoring wells. As a light source for fluorescence spectroscopy, we constructed an LED array that can be equipped with four different LEDs. A miniaturized deuterium-tungsten light source (200-1100 nm) was used for UV/Vis spectroscopy. A miniaturized spectrometer with a spectral range between 225 and 1000 nm permits the detection of complete spectra for both methods.

HUM: A review of hydrochemical analysis using ultraviolet-visible absorption spectroscopy and machine learning

There is a need to develop improved methods for water quality analysis. Traditionally, water quality analysis is performed in a laboratory on discrete samples or in the field with simple sensors, but these methods have inherent limitations. Ultraviolet-visible absorption spectroscopy (UVAS) is a commonly used laboratory technique for water quality analysis and is being applied more broadly in combination with machine learning (ML) to allow for the detection of multiple analytes without sample pretreatments. This methodology (referred to here as Hydrochemical analysis using Ultraviolet-visible absorption spectroscopy and Machine learning; 'HUM') can be applied in the laboratory or in situ while requiring less time, labor, and materials compared to traditional laboratory analysis. HUM has been used for the quantification of a variety of chemicals in a variety of settings, but information is lacking related to instrumental setup, sample requirements, and data analysis procedures. For instance, there is a need to investigate the influence of spectral parameters (e.g., sensitivity, signal-to-noise ratio, and spectral resolution) on measurement error. There is also a lack of research aimed at developing ML algorithms specifically for HUM. Finally, there are emerging concepts such as sensor fusion and model-sensor fusion which have been applied to similar fields but are not common in studies involving HUM. This review suggests the need for further studies to better understand the factors that influence HUM measurement accuracy along with the need for hardware and software developments so that the methodology can ultimately become more robust and standardized. This, in turn, could increase its adoption in both academic and non-academic settings. Once the HUM methodology has matured, it could help to reduce the environmental impacts of society by improving our understanding and management of environmental systems through high-frequency data collection and automated control of water quality in environmentally relevant systems.

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and time-consuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for forecasting algal blooms is a feasible and useful method to overcome these problems. This study explores the potential application of optical measures to enhance algal bloom prediction in terms of prediction accuracy and workload reduction, aided by machine learning (ML) models. Compared to absorption-derived parameters, commonly used fluorescence indices such as the fluorescence index (FI), humification index (HIX), biological index (BIX), and protein-like component improved the prediction accuracy. However, the prediction accuracy was decreased when all optical indices were considered for computation due to increased noise and uncertainty in the models. With the exception of chemical oxygen demand (COD), this study successfully replaced biochemical oxygen demand (BOD), dissolved organic carbon (DOC), and nutrients with selected fluorescence indices, demonstrating relatively analogous performance in either training or testing data, with consistent and good coefficient of determination (R2) values of approximately 0.85 and 0.74, respectively. Among all models considered, ensemble learning models consistently outperformed conventional regression models and artificial neural networks (ANNs). However, there was a trade-off between accuracy and computation efficiency among the ensemble learning models (i.e., Stacking and XGBoost) for algal bloom prediction. Our study offers a glimpse of the potential application of spectroscopic measures to improve accuracy and efficiency in algal bloom prediction, but further work should be carried out in other water bodies to further validate our proposed hypothesis.

Burial or mineralization: Origins and fates of organic matter in the water-suspended particulate matter-sediment of macrophyte- and algae-dominated areas in Lake Taihu

Increased algal blooms and loss of aquatic vegetation are critical environmental issues associated with shallow lakes worldwide. The increase in organic matter (OM) in both macrophyte-dominated areas (MDAs) and algae-dominated areas (ADAs) has exacerbated these problems. Most OM in water is concentrated as suspended particulate matter (SPM), which eventually migrates to the sediment. However, the detailed origins and fates of OM in water-SPM-sediment systems with coexisting MDAs and ADAs remain unclear. Therefore, in this study, we conducted monthly field investigations in Lake Taihu, focusing on OM-migration patterns in an MDA and an ADA. The C/N mass ratios, δ13C contents, and OM compositions of the water, SPM, and sediment were analyzed. Our findings revealed that autochthonous sources of OM prevailed in water, whereas terrestrial sources prevailed in SPM and sediment. Rapid decomposition processes of microbial- and algae-derived dissolved OM were discovered along the water-SPM-sediment pathways in both areas. A trend towards a shift from macrophytes to algae in the MDA was also discovered. Overall, the entire lake underwent a burial process of OM in both types of areas, with mineralization mostly occurring during the algal-bloom seasons and more strongly in the ADA. Furthermore, we deduced that a decrease in the OM-burial rate, but an increase in the mineralization rate, might occur after a complete shift from a macrophyte- to an algae-dominated status. Such a shift might change the carbon-cycle process in eutrophic shallow lakes and should be given more attention in future research.

Using Rayleigh Scattering to Correct the Inner Filter Effect of the Fluorescence Excitation-Emission Matrix

Excitation-emission matrix (EEM) spectroscopy has been proven to be an effective tool for offline fluorescence analysis. However, the pretreatment of EEM data requires an additional ultraviolet-visible (UV-vis) absorption spectrum for inner filter effect (IFE) correction. This complicates the instrument structure and increases the test flow, thus hindering the practical application of EEM in environmental online monitoring. In this work, Rayleigh scattering in EEM, which is often masked, is leveraged to address this challenge as Rayleigh scattering light itself passes through the sample and experiences absorption. We establish a translation-corrected estimation by the Rayleigh scattering (TCERS) method to estimate absorbance, not only enabling the IFE self-correction of EEM but also providing orthogonal spectroscopy information. TCERS is hierarchically tested in real solutions, simulated turbid liquids, and various natural water samples. Results indicate that the predicted UV-vis absorption spectra have a cosine similarity of over 0.95 with the actual spectra. When using the predicted spectra to correct the IFE of EEM, only about 0.005/1.440 bits of information entropy are lost and the absolute errors in EEM are negligible. The proposed method has the potential to streamline the design of fluorescence spectrometers, making it possible to miniaturize, optimize, and popularize these instruments for various practical applications such as environmental monitoring.

Effects of organic additives on spectroscopic and molecular-level features of photo-induced dissolved organic matter from microplastics

The environmental occurrence and impact of dissolved organic matter leached from microplastics (MP-DOM) has been the subject of increased research interest. Commercial plastics, which typically contain additives, are subject to natural weathering processes and can eventually lose their additives. However, the effects of organic additives in commercial microplastics (MPs) on the release of MP-DOM under UV irradiation remain poorly understood. In this study, four polymer MPs (polyethylene; PE, polypropylene; PP, polystyrene; PS, polyvinylchloride; PVC) and four commercial MPs, including a PE zip bag, a PP facial mask, a PVC sheet, Styrofoam, were subjected to leaching under UV irradiation, and the MP-DOM was characterized using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and fluorescence excitation emission matrix-parallel factor analysis (EEM-PARAFAC). Although UV light promoted the leaching of MP-DOM from both MP groups, the amount released was more pronounced for the polymer MPs than for the commercial MPs. The commercial MP-DOM was characterized by a prominent protein/phenol-like component (C1), while a humic-like component (C2) prevailed in the polymer MPs. FT-ICR-MS identified a higher number of unique molecular formulas for the commercial than for the polymer MP-DOM. The unique molecular formulas of commercial MP-DOM included known organic additives and other breakdown products, while the polymer MP-DOM featured more pronounced unsaturated carbon structures in its identified unique formulas. Several molecular-level parameters showed significant correlations with fluorescence properties, such as CHO formulas (%) with C1 and condensed aromatic structure (CAS-like, %) with C2, suggesting the potential application of fluorescent components as an optical descriptor for the complex molecular-level composition. This study also revealed the possible high environmental reactivity of both polymer MPs and fully weathered plastics due to the unsaturated structures generated in sunlit environments.

Molecular insights into the dissolved organic matter of leather wastewater in leather industrial park wastewater treatment plant

Leather wastewater (LW) effluent is characterized by complex organic matter, high salinity, and poor biodegradability. To meet the discharge standards, LW effluent is often mixed with municipal wastewater (MW) before being treated at a leather industrial park wastewater treatment plant (LIPWWTP). However, whether this method efficiently removes the dissolved organic matter (DOM) from LW effluent (LWDOM) remains debatable. In this study, the transformation of DOM during full-scale treatment was revealed using spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry. LWDOM exhibited higher aromaticity and lower molecular weight than DOM in MW (MWDOM). The DOM properties in mixed wastewater (MixW) were similar to those in LWDOM and MWDOM. The MixW was treated using a flocculation/primary sedimentation tank (FL₁/PST), anoxic/oxic (A/O) process, secondary sedimentation tank (SST), flocculation/sedimentation tank, denitrification filter (FL₂/ST-DNF), and an ozonation contact reactor (O₃). The FL₁/PST unit preferentially removed the peptide-like compounds. The A/O-SST units had the highest removal efficiencies for dissolved organic carbon (DOC) (61.34 %) and soluble chemical oxygen demand (SCOD) (52.2 %). The FL₂/ST-DNF treatment removed the lignin-like compounds. The final treatment showed poor DOM mineralization efficiency. The correlation between water quality indices, spectral indices, and molecular-level parameters indicated that lignin-like compounds were strongly correlated with spectral indices and CHOS compounds considerably contributed to the SCOD and DOC. Although the effluent SCOD met the discharge standard, some refractory DOM from LW remained in the effluent. This study illustrates the composition and transformation of DOM and provides theoretical guidance for improving the current treatment processes.

Ultrasensitive Detection of Malachite Green Isothiocyanate Using Nanoporous Gold as SERS Substrate

In this article, a high-performance nanostructured substrate has been fabricated for the ultrasensitive detection of the organic pollutant, Malachite green isothiocyanate (MGITC), in aquatic systems via the Surface Enhanced Raman Spectroscopy (SERS) technique. The chemical dealloying approach has been used to synthesize a three-dimensional nanoporous gold substrate (NPG) consisting of pores and multigrained ligament structures along thickness. The formation of the framework in NPG-5h has been confirmed by SEM with an average ligament size of 65 nm at the narrower neck. Remarkable SERS performance has been achieved by utilizing the NPG-5h substrate for the detection of MGITC, showing a signal enhancement of 7.9 × 10⁹. The SERS substrate also demonstrated an impressively low-detection limit of 10^-16 M. The presence of numerous active sites, as well as plasmonic hotspots on the nanoporous surface, can be accredited to the signal amplification via the Localized Surface Plasmon Resonance (LSPR) phenomenon. As a result, SERS detection technology with the fabricated-NPG substrate not only proves to be a simple and effective approach for detecting malachite green but also provides a basis for in situ detection approach of toxic chemicals in aquatic ecosystems.

Effects of UV-based oxidation processes on the degradation of microplastic: Fragmentation, organic matter release, toxicity and disinfection byproduct formation

The occurrence and transformation of microplastics (MPs) remaining in the water treatment plants has recently attracted considerable attention. However, few efforts have been made to investigate the behavior of dissolved organic matter (DOM) derived from MPs during oxidation processes. In this study, the characteristics of DOM leached from MPs during typical ultraviolet (UV)-based oxidation was focused on. The toxicity and disinfection byproduct (DBP) formation potentials of MP-derived DOM were further investigated. Overall, UV-based oxidation significantly enhanced the aging and fragmentation of highly hydroscopic MPs. The mass scales of leachates to MPs increased from 0.03% - 0.18% at initial stage to 0.09% - 0.71% after oxidation, which were significantly higher than those leached by natural light exposure. Combined fluorescence analysis with high resolution mass spectrometer scan confirmed that the dominant MP-derived DOM are chemical additives. PET-derived DOM and PA6-derived DOM showed inhibition of Vibrio fischeri activity with corresponding EC₅₀ of 2.84 mg/L and 4.58 mg/L of DOC. Bioassay testing with Chlorella vulgaris and Microcystis aeruginosa showed that high concentrations of MP-derived DOM inhibited algal growth by disrupting the cell membrane permeability and integrity. MP-derived DOM had a similar chlorine consumption (1.63 ± 0.41 mg/DOC) as surface water (1.0 - 2.0 mg/DOC), and MP-derived DOM mainly served as precursors for the investigated DBPs. Contrary to the results of previous studies, the DBP yields from MP-derived DOM were relatively lower than those of aquatic DOM under simulated distribution system conditions. This suggests that MP-derived DOM itself rather than serving as DBP precursor might be potential toxic concern.

Artificial neural network implementation for dissolved organic carbon quantification using fluorescence intensity as a predictor in wastewater treatment plants

Although spectroscopic methods provide a fast and cost-effective means of monitoring dissolved organic carbon (DOC) in natural and engineered water systems, the prediction accuracy of these methods is limited by the complex relationship between optical properties and DOC concentration. In this study, we developed DOC prediction models using multiple linear/log-linear regression and feedforward artificial neural network (ANN) and investigated the effectiveness of spectroscopic properties, such as fluorescence intensity and UV absorption at 254 nm (UV₂₅₄), as predictors. Optimum predictors were identified based on correlation analysis to construct models using single and multiple predictors. We compared the peak-picking and parallel factor analysis (PARAFAC) methods for selecting appropriate fluorescence wavelengths. Both methods had similar prediction capability (p-values >0.05), suggesting PARAFAC was not necessary for choosing fluorescence predictors. Fluorescence peak T was identified as a more accurate predictor than UV₂₅₄. Combining UV₂₅₄ and multiple fluorescence peak intensities as predictors further improved the prediction capability of the models. The ANN models outperformed the linear/log-linear regression models with multiple predictors, achieving higher prediction accuracy (peak-picking: R² = 0.8978, RMSE = 0.3105 mg/L; PARAFAC: R² = 0.9079, RMSE = 0.2989 mg/L). These findings suggest the potential to develop a real-time DOC concentration sensor based on optical properties using an ANN for signal processing.

Autofluorescence spectral analysis for detecting urinary stone composition in emulated intraoperative ambient

The prevalence and disease burden of urolithiasis has increased substantially worldwide in the last decade, and intraluminal holmium laser lithotripsy has become the primary treatment method. However, inappropriate laser energy settings increase the risk of perioperative complications, largely due to the lack of intraoperative information on the stone composition, which determines the stone melting point. To address this issue, we developed a fiber-based fluorescence spectrometry method that detects and classifies the autofluorescence spectral fingerprints of urinary stones into three categories: calcium oxalate, uric acid, and struvite. By applying the support vector machine (SVM), the prediction accuracy achieved 90.28 % and 96.70% for classifying calcium stones versus non-calcium stones and uric acid versus struvite, respectively. High accuracy and specificity were achieved for a wide range of working distances and angles between the fiber tip and stone surface in an emulated intraoperative ambient. Our work establishes the methodological basis for engineering a clinical device that achieves real-time, in situ classification of urinary stones for optimizing the laser ablation parameters and reducing perioperative complications in lithotripsy.

Insight into dissolved organic nitrogen transformation and characteristics: Focus on printing and dyeing wastewater treatment process

Textile industry discharges large amounts of printing and dyeing wastewater (PDW) containing high concentration of refractory dissolved organic nitrogen (DON). However, the DON transformation and characteristics during PDW treatment, and its potential environment impact receive little concern. Treatment groups of dyeing wastewater (G-RB5), printing wastewater (G-Urea) and domestic wastewater (G-NH₄Cl) with Reactive Black 5 (RB5), Urea and NH₄Cl as influent nitrogen species were set to compare the DON behavior during the hydrolytic acidification-aerobic-anoxic process. G-RB5 exhibited higher DON concentrations with greater fluctuations, and its effluent dominated low molecular weight (LMW) and hydrophilic DON, showing high bioavailability (67.6%) and low biodegradation (8.0%). In the aerobic section, the concentration of microorganism-derived DON in G-RB5 was higher but the nitrogen species were fewer than G-Urea and G-NH₄Cl. Grey relational analysis revealed that Proteobacteria and Thauera were the common bacteria strains showing high association degree (γ > 0.9) with biodegradable DON (ABDON) in all groups; while microbes related with biodegradable DON (BDON) varied between groups. The higher contents of DON, ABDON, LMW-DON and hydrophilic DON induced by RB5 highlight the importance of controlling DON from textile industry to mitigate the potential risk like algae growth stimulation, which needs more attention in future.

One-step fluorometric determination of multiple-component dissolved organic matter in aquatic environments

Dissolved organic matter (DOM) is ubiquitous in aqueous environments and is composed of different components that play different but important roles in the migration and the fate of pollutants, emergence of the disinfect byproduct, thus requiring quantitative characterization. However, until now, simultaneous quantification of the main contents in DOM, i.e., saccharides, proteins, and humic substances, has been difficult, impeding us from understanding and predicting the environmental behaviors of typical pollutants. In this work, a fluorescence approach based on the excitation emission matrix (EEM), combined with a new algorithm, denoted matrix reconstruction coupled with prior linear decomposition (MR-PLD), was developed to quantify multiple DOM simultaneously. First, a set of simulated water samples consisting of glucose, tryptones, and humic acid (HA) were analyzed using MR-PLD to validate the feasibility of the method. The DOM components could be reliably determined with a higher accuracy than parallel factor analysis (PARAFAC) and Parallel Factor Framework-Linear Regression (PFFLR), also with a more convenient procedure than conventional PLD. Second, both actual simulated and experimental methods were performed to test the anti-interference performance of MR-PLD, indicating that the quantification of DOM would not be significantly impacted by other fluorophores. Finally, several actual water samples from natural waters and wastewater treatment plants were also analyzed to confirm the robustness of this method in actual aqueous environments. This study provides a new approach to characterize DOM with EEM, contributing to its convenient concentration monitoring and the further exploration of the environmental impacts.