Spectral characterization, degradation behavior, quenching, and semi-quantification of fluoroquinolone antibiotics in the antibiotic-humic mixture using fluorescence spectroscopy

Antibiotics, one of the significant emerging contaminants, are intensifying their continual spread out into the environment and affecting human health and the ecosystem in the developing country Bangladesh. This study characterizes widely used fluoroquinolone (FQ) antibiotics, formulates the method to spectrally distinguish them from ubiquitous, and important reactive, adsorbent, and altering catalytic macromolecule humic substances (HS), and further quantifies them using fluorescence spectroscopy. The presence of identical fluorophore at Excitation/Emission = 225-230/285-295 nm wavelength, possession of fluorescence spectra at short emission wavelength (<350 nm) during 275 nm excitation, different emission maxima, and various fluorescing components in antibiotics identified through three-dimensional excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC) models distinguished them from the humic substance as well as from each other. Stern-Volmer equation and its modified version were applied to identify quenching and binding capability, and fluorescence intensity quenching rate of antibiotics and humic in their mixture. Unlike poor and inconsistent quenching mechanisms of humic, FQ antibiotics reduced HS intensity throughout the entire photo-irradiation experiment affirming the functioning of the stable quenching methods. Static quenching of fluorophores was identified from the redshift of excited wavelength on the electronic ground state. Temperature differences during daylight and dark conditions played contrasting roles during the fluorescence quenching of FQ. Unique spectral response at emission wavelength < 350 nm during 275 nm excitation in FQ was considered as its least intensity in the antibiotic-humic mixture and was also used to formulate distinct spectral pattern of each FQ antibiotic. The study also identified the traces of FQ antibiotics with various intensities at different lakes in Bangladesh.

Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H2O2 treatment of wastewater

Dynamic feedback of the removal performance of trace organic contaminants (TrOCs) is essential towards economical advanced oxidation processes (AOPs), whereas the corresponding quick-response feedback methods have long been desired. Herein, machine learning (ML) multi-target regression random forest (MORF) models were developed based on the fluorescence spectra to predict the removal of TrOCs during UV/H2O2 treatment of municipal secondary effluent as a typical AOP. The predictive performance of the developed MORF model (R2 = 0.83-0.95) exhibited higher accuracy over the traditional linear regression models with R2 increased by ∼0.15. Furthermore, through feature importance analysis, the spectral regions of high importance were identified for different groups of TrOCs, thus enabling faster data acquisition due to remarkably reduced size of required fluorescence spectral scanning region. Specifically, the fluorescence regions Ex(235-275 nm)/Em(325-400 nm) and Ex(240-360 nm)/Em(325-450 nm) were found highly correlated with the removal of the TrOCs susceptible to both photodegradation and •OH degradation and those primarily subject to •OH degradation, respectively. In addition, the spectral regions of high importance were also individually identified for the investigated TrOCs during the AOP. Through providing an efficient ML-based feedback method to monitor TrOC removal during AOP, this study sheds light on the development of dynamic feedback-based strategies for precise and economical advanced treatment of wastewater.

Utilization of multiple-dilution fluorescence fingerprint facilitates prediction of chemical attributes in spice extracts

Fluorescence Fingerprint (FF) is a powerful tool for rapid quality assessment of various foods and plant-derived products. However, the conventional utilization of FFs measured at a single dilution level (DL) to substitute chemical analyses is extremely challenging, especially for multicomponent materials like spice extracts because fluorescence intensity and concentration widely differ between components, with complex phenomena like inner filter effects. Here, we proposed a new strategy to use the meta-data comprised of FFs measured at multiple DLs with machine learning to estimate common chemical attributes including total polyphenol and flavonoid contents, and antioxidant abilities. This strategy achieved more consistently satisfactory performance in estimation of all chemical attributes of spice extracts compared to using a single DL. Hence, the workflow employed in this study is expected to serve as an alternative method to quickly evaluate the chemical quality of spice extracts, as well as other plant products and food materials.

Seasonal variations in dissolved organic matter concentration and composition in an outdoor system for bank filtration simulation

Dissolved organic matter (DOM) in surface waters can vary markedly in character depending on seasonal variations such as rainfall intensity, UV radiations and temperature. Changes in DOM as well as temperature and rainfall intensity over the year can affect the biochemical processes occurring in bank filtration (BF). Identification and characterization of DOM in the surface water could help to optimize the water treatment and provide stable and safe drinking water. This study investigated year-long variations of DOM concentrations and compositions in a surface water of a circulated outdoor pond (research facility) connected to a BF passage. DOM was dominated by humic substances and a changing pattern of DOM in surface water was observed throughout the year. A significant increase of DOM (∼ 38%) in surface water was noted in August compared to November. The fluorescent DOM showed that DOM in summer was enriched with the degradable fraction whilst non-degradable fraction was dominated in winter. A constant (1.7 ± 0.1 mg/L) effluent DOM was recirculated in the system throughout the year. DOM removal through BF varied between 4% to 39% and was achieved within a few meters after infiltration and significantly correlated with influent DOM concentration (R2 = 0.82, p < 0.05). However, no significant (p > 0.05) change in the removal of DOM was observed in two subsurface layers (upper and lower). This study highlights the presence of a constant non-degradable DOM in the bank filtrate, which was not affected by temperature, redox conditions and UV radiations.

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.

Characterization of time-series fluorescence properties of bean sprouts during storage using excitation emission matrix and fluorescence imaging

Soybean (Glycine max (L.) Merr.) and mung bean (Vigna radiata L.) are popular varieties of bean sprouts, which are used in various Asian cuisines. The freshness of bean sprouts reduces at fast rate during storage. Hence, determining index of monitoring the state of sprouts is required to prevent unnecessary food loss, which is also linked to economical loss. The aim of this study is to reveal fluorescence characteristic of bean sprouts and investigate its potentiality for tracking the freshness state of bean sprouts. The fluorescence spectroscopy and imaging were used. For fresh bean sprouts, the Excitation-Emission Matrix (EEM) showed two fluorescence regions: Excitation (Ex) 270-300 nm with Emission (Em) 300-400 nm and Ex 300-350 nm with Em 400-450 nm, which are suspected to be amino acids and vitamins, respectively. When browning process started, the new fluorescence region occurred at Ex 400-450 nm with Em 450-550 nm. Consistent with EEM, under 365 nm, bean sprouts initially had blue fluorescence emission, and later changed to green when they start spoiling. However, due to higher emission, 420 nm-excitation wavelength was preferable for detecting browning part. With these basic fluorescence information, further application on inspecting both physical change and chemical change of bean sprouts can be easily established.

Deep or Shallow? A Comparative Analysis on the Oil Species Identification Based on Excitation-Emission Matrix and Multiple Machine Learning Algorithms

With the continuous expansion of petroleum extraction, transportation, and storage, the risk of oil spills at sea has also increased, posing a serious threat to marine safety. The excitation-emission matrix (EEM), which is composed of the fluorometric spectra under multiple excitation wavelengths, becomes a feasible approach to identify oil species. Despite the fact that various machine learning models have been applied to analyse EEMs of oil pollutants, it is unclear how much improvements the deep learning models have achieved, especially comparing with the shallow learning models. This paper presents a comparative analysis on the oil species identification using four types of machine learning models: random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and deep convolutional neural network (DCNN). The fluorescence of some common oils was excited using a tuneable xenon lamp and collected with a high-resolution spectrometer to form the EEMs for model training and testing.The results show that SVM, BPNN, and DCNN achieved high identification accuracies that are more than 93% on all types of oils tested in the study. The two deep learning models didn't have significant improvement over the SVM model. Considering the fact that the deep learning models require much larger number of calculations and longer running time, the SVM tends to be more suitable for oil species identification when considering the balance between the model accuracy and efficiency. This study provides some guidance on the choices of oil species identification model in the cases of oil spills.

Seasonal changes of dissolved organic matter chemistry and its linkage with greenhouse gas emissions in saltmarsh surface water and porewater interactions

Dissolved organic matter (DOM) is one of the largest reactive reservoirs of carbon on earth. Saltmarshes play an essential role in shaping the fate of DOM and greenhouse gas (GHG) production in surface water and groundwater interactions in coastal areas. However, the coupling mechanism between DOM and GHG production is poorly understood. In this study, DOM in both surface water and porewater were analyzed by 3D excitation-emission-matrix spectroscopy under different seasonal and tidal conditions in a saltmarsh. Protein-like DOM was likely to produce CH4, while humic-like DOM tended to produce CO2. CH4 concentration was highly enriched in porewater because increasing fresh groundwater flow introduced small-sized protein-like DOM. Based on the mass balance model, >98.5% of CH4 was oxidated to CO2 in sediment-water interface. The degradation of sediment-derived DOC (especially humic-like DOM) contributes ∼80% of the total amount of CO2 in surface water. Both hydrodynamics and chemical reactions are suggested to influence greenhouse gas (GHG) emissions. Hydrodynamics (e.g., tidal pumping) are controlling factors in short timescales (hourly/weekly) while chemical reactions become crucial in influencing DOM chemistry and related degradation rate on seasonal scales. These findings emphasize the importance of the coupling mechanism at different time scales between DOM characteristics and GHG emissions in saltmarshes.

Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal

The Bay of Bengal (BoB) is the largest sink to retain discharges from major rivers and the Sundarbans Mangrove Forest in Bangladesh and upholds significant ecological and resource diversity. This study aims to characterize, and identify sources, spatial dynamics, and the fate of the principal ecological web driver that is fluorescent dissolved organic matter (FDOM) in the BoB using advanced techniques of excitation-emission matrix (EEM) fluorescence spectroscopy and multivariate parallel factor (PARAFAC) analyses. The identified four protein-, two humic- and one detergent-like FDOM components mostly showed higher abundance in the shallow water than deep unlike a protein-like component. Such exceptional protein-like component was identified to form colloidal structure under elevated salinity in deep water. Autochthonous humic-like FDOM originated from primary production and water temperature counteracted microbial polymerization in shallow and deep water, respectively. The annual mass deposition indicated the influx of anthropogenic pollutants from both terrestrial and internal marine systems.

Tracing the variation of dissolved organic matter in the two-stage anoxic/aerobic process treating swine wastewater using fluorescence excitation-emission matrix with parallel factor analysis

Swine wastewater has become one of the main agricultural pollution sources. Quantitative characterization of dissolved organic matter (DOM) is often used in various water bodies, but there are few studies on DOM analysis of swine wastewater. In this study, swine wastewater was treated by a step-feed two-stage anoxic/aerobic (SF-A/O/A/O) process. By using parallel factor (PARAFAC) analysis of fluorescence excitation-emission matrix (EEM), the main components of swine wastewater were aromatic protein-like substances (C1), tryptophan-like substances (C2), fulvic acid-like/humic-like substances (C3) and humic-like substances (C4). Protein-like substances were degraded significantly, while humic-like substances were difficult to be utilized by microorganisms. Fluorescence spectral indexes showed that the characteristics of endogenous input and humus were enhanced. Moreover, several significant correlations between DOM components, fluorescence spectral indexes and water quality indexes were observed. These findings help to understand the biochemical role and the impact of DOM in water quality monitoring and control of swine wastewater.

New insight into soluble extracellular metabolites during sludge bulking process based on excitation-emission matrix spectroscopy and ultrahigh-performance liquid chromatography-mass spectrometry

Soluble extracellular metabolites (SEM) produced by microorganisms might significantly change during sludge bulking, which is a major operational problem caused by the excessive growth of filamentous bacteria. However, knowledge remains limited about the dynamics and potential role of SEM in the bulking of sludge. In this study, filamentous bulking was simulated in a laboratory-scale reactor and changes to SEM characteristics during the bulking process were investigated using excitation-emission matrix spectroscopy and ultrahigh-performance liquid chromatography-mass spectrometry. SEM components changed significantly at different phases of sludge bulking. Changes in SEM were closely correlated with the structure of the bacterial community. Based on the EEM profiles, significant increases in fulvic acid-like and humic acid-like substances in SEM were observed with the development of filamentous bulking. The degree of humification in SEM showed a clear increasing trend. Untargeted extracellular metabolomic analysis showed that the intensity of berberine and isorhamnetin in SEM increased significantly during the bulking phase, which might synergistically facilitate the development of filamentous bulking.

Insights into reactive oxygen species formation induced by water-soluble organic compounds and transition metals using spectroscopic method

Ambient particulate matter (PM) can cause adverse health effects via their ability to produce Reactive Oxygen Species (ROS). Water-Soluble Organic Compounds (WSOCs), a complex mixture of organic compounds which usually coexist with Transition Metals (TMs) in PM, have been found to contribute to ROS formation. However, the interaction between WSOCs and TMs and its effect on ROS generation are still unknown. In this study, we examined the ROS concentrations of V, Zn, Suwannee River Fulvic Acid (SRFA), Suwannee River Humic Acid (SRHA) and the mixtures of V/Zn and SRFA/SRHA by using a cell-free 2',7'-Dichlorodihydrofluorescein (DCFH) assay. The results showed that V or Zn synergistically promoted ROS generated by SRFA, but had an antagonistic effect on ROS generated by SRHA. Fluorescence quenching experiments indicated that V and Zn were more prone to form stable complexes with aromatic humic acid-like component (C1) and fulvic acid-like component (C3) in SRFA and SRHA. Results suggested that the underlying mechanism involving the fulvic acid-like component in SRFA more tending to complex with TMs to facilitate ROS generation through π electron transfer. Our work showed that the complexing ability and complexing stability of atmospheric PM organics with metals could significantly affect ROS generation. It is recommended that the research deploying multiple analytical methods to quantify the impact of PM components on public health and environment is needed in the future.

Enhanced statistical evaluation of fluorescence properties to identify dissolved organic matter dynamics during river high-flow events

Fluorescence spectroscopy has become a widely used technique to characterize dissolved organic matter (DOM) and organic hazardous micro-pollutants in natural and human-influenced water bodies. Especially in rivers highly impacted by municipal and industrial wastewater treatment plants' effluents, the fluorescence signal at low-flow is mainly dominated by these discharges. At river high-flow, their influence decreases due to dilution effects, and at the same time, other compounds of DOM, stemming from diffuse inputs, can increase or even dominate. Therefore, whereas the analysis of DOM is little informative on the changing sources and pathways of emissions, fluorescence spectroscopy can enhance our understanding and our possibilities of monitoring such dynamics in river catchments. This paper analyzed samples from seven high-flow events in an Austrian river. Firstly, independent DOM components were discriminated using a parallel factor analysis (PARAFAC) to show the varying composition of DOM during different phases of high-flow events. Furthermore, partial least squares (PLS) and sparse PLS (sPLS) regression were applied to identify excitation and emission wavelengths, serving as proxy parameters for quantifying dissolved organic carbon (DOC) and chloride. The PLS models show the best prediction accuracy but use the entire excitation-emission matrix in exchange. In selecting predictors, the use of excitation and emission wavelengths adjusted via sPLS is superior to the extracted PARAFAC components. The sPLS model yields 16 wavelength combinations for DOC (RMSE_sPLS = 0.41 mg L^-1) and 18 wavelength combinations for chloride (RMSE_sPLS = 2.21 mg L^-1). In contrast to other established optical measurement methods, which require different calibrations for low- and high-flow conditions, these models based on sPLS succeed in quantifying those parameters across the entire range of flow conditions and events of various magnitudes with a relative precision of about 5 %. These results show how the application of multivariate statistical techniques enhances the exploitation of the information provided by fluorescence spectroscopy.

A chemosensing approach for the colorimetric and spectroscopic detection of Cr3+, Cu2+, Fe3+, and Gd3+ metal ions

Metal cations are present in domestic and industrial wastewater and have adverse effects on human and aqueous life. The present study describes the development of the molecular probe 9-anthracen-9-ylmethylene)hydrazineylidene)methyl)-2,3,6,7-tetrahydro-1H,5H-pyrido[3,2,1-ij]quinolin-8-ol (AMHMPQ) to detect Cr³⁺, Cu²⁺, Fe³⁺, and Gd³⁺ ions by using UV-visible, fluorescence, colorimetric and excitation-emission matrix (EEM) spectroscopy techniques. The interaction of Cr³⁺, Cu²⁺, Fe³⁺, and Gd³⁺ can be observed by the absorption maxima shift, turn-off, colour changes, and EEM shifts. In addition, fluorescence limits of detection 17.66 × 10^-6 M, 6.44 × 10^-9 M, 28.87 × 10^-8 M, and 12.49 × 10^-6 M in wide linear ranges, low limits of quantifications, high values of Stern-Volmer constant, Job's plot and Benesi-Hildebrand plot justify the 1:1 association affinity with association constants of 1.46 × 10⁴ M^-1, 1.86 × 10⁷ M^-1, 2.69 × 10⁵ M^-1, 2.13 × 10⁴ M^-1 for AMHMPQ-metal ions (Cr³⁺, Cu²⁺, Fe³⁺, and Gd³⁺ ions), respectively. Paper- and mask-based kits are developed to explore the utility of the designed chemosensor. Additionally, AMHMPQ acts as a reusable sensor for two, seven, two, and zero cycles for Cr³⁺, Cu²⁺, Fe³⁺, and Gd³⁺ ions, respectively, when checked with EDTA.

Oil pollutant identification based on excitation-emission matrix of UV-induced fluorescence and deep convolutional neural network

Identifying the types of oil pollutants in a spill event can help determine the source of spill and formulate the plan of emergency responses. Excitation-emission matrix (EEM), which is also called three-dimensional fluorometric spectra, includes abundant spectral information in the domain of excitation wavelength and can be potentially applied to identify oil types. UV-induced fluorometric experiments were conducted in this study to collect EEMs for five types of oil that are commonly used in maritime transportation. A deep convolutional neural network (CNN) model for oil types identification was built based on the classic VGG-16 model. According to the identification results, the model was able to provide a reasonable classification on the five types of oil used in the experiments. Additionally, a biased classification result was observed in the experiment: the model was able to provide the most accurate classification on 0W40 lubricant but encounters difficulty distinguishing between - 10# diesel and 92# gasoline. The potential reasons for this result and the approaches to improve the model were also discussed.

A comparative study of electrocoagulation treatment with iron, aluminum and zinc electrodes for selenium removal from flour production wastewater

Electrocoagulation (EC) using iron (Fe), zinc (Zn) and aluminum (Al) electrodes was comparatively applied in the treatment of selenium (Se) in flour production (FP) wastewater. It was indicated that EC treatment with Fe anode obtained highest removal efficiency (79.1%) for Se in the 90 min treatment in the comparative study, which could be attributed to the superior adsorption capacity of in-situ generated iron flocs. Removal of Se resulted from electrodeposition and adsorption to in-situ generated flocs in EC treatment, and the operational conditions significantly influenced the Se removal performance in this work. The results showed the acidic condition and higher current density favored EC treatment on Se removal, EC removed up to 97.8% of Se at pH 4 under 15 mA cm^-2, whereas it obtained 83.5% and 50.4% of removal efficiency at pH 7 and 10, respectively. There was competitive adsorption in the process of selenium removal, as the in-situ generated flocs effectively removed 35.6% of humic acid-like (HA-like) substance in FP wastewater after 90 min treatment. The FTIR results showed that HA-like substance mainly contained the protein water hydrogen bond, carboxylate COO antisymmetric stretching and other functional groups. Through the analysis of existence of Se in flocs and wastewater, it can be found that approximately 2.8%-3.92% of Se was removed by electrodeposition process. This study illustrated the Se removal mechanism and provided constructive suggestion for food manufacturing to the metal removal and utilization of advanced treatment.

Japanese dace (Tribolodon hakonensis) fish freshness estimation using front-face fluorescence spectroscopy coupled with chemometric analysis

Although fish and its related products are good sources of protein and unsaturated fatty acids, like omega-3 in the human diet, their shelf-life is limited by biochemical and microbial changes. In this study, a front-face fluorescence spectroscopy technique was used to acquire Excitation-emission matrices (EEM) to monitor Japanese dace (Tribolodon hakonensis) fish freshness degradation during storage. EEM of Japanese dace fish parts (intact eyeball and surface-containing scales), excitation from 220 to 585 nm and emissions from 250 to 600 nm, were measured at different times during storage. To simplify the acquired complex spectra datasets from each fish part, the variables were reduced to those that were only significant/important (those with higher positive or negative correlation) for K value prediction, and as an index of freshness. Partial least square regression (PLSR) results demonstrated that combining the fluorescence EEM of the eyeball and surface-containing scales the best monitoring of fish freshness; excitation at 280 and 350 nm for both the eyeball and surface-containing scales, with 2.84 and 0.96 as RMSE and R², respectively. These findings demonstrate that multiple excitation fluorescence approaches can be convenient for the freshness evaluation of fish.

Biogeochemistry of the dissolved organic matter (DOM) in the estuarine rivers of Bangladesh-Sundarbans under different anthropogenic influences

The Bangladesh-Sundarbans is the Outstanding Universal Value (OUV) articulated by UNESCO, is under different anthropogenic stress. The present study focused on the status of estuarine biogeochemistry of the dissolved organic matter (DOM) of the Bangladesh-Sundarbans using different optical methods. Four fluorophores: Peak A (230-265/408-488 nm), Peak M (290/414 nm), Peak C (365/488 nm), and Peak W (320/410 nm), and three fluorescent dissolved organic matter (fDOM) components (two humic-like, one detergent-like) were identified in the Sundarban mangrove Rivers by Excitation-Emission Matrix (EEM) and Parallel Factor (PARAFAC) analyses. Among the three components, the terrestrial-derived humic-like Component had a high intensity in five samples among six in the Bangladesh-Sundarbans. The total fluorescent intensity and calculated dissolved organic carbon (DOC) concentration were maximum in Harbaria and minimum in Kotka and Dublar char, respectively. Synchronous fluorescence spectroscopy (SFS) identified protein-like component besides humic-like DOM. The optical indices described that natural fDOM components were from terrestrial sources, were matured, and autochthonous fDOM production was low. The DOM components were relatively lower in molecular size and aromaticity in Harbaria. However, water samples in Harbaria contained organometallic compounds that had much absorbance at 254 nm wavelength. DOM components had low energy and more π-conjugated molecules in structure in the Dublar char and Kotka. Components in Dublar char had comparatively higher molecular size and weight than other sampling stations. The Harbaria and Mongla port contained more hydrophobic and less polar substances than other stations. This study will firmly add diversified notions to future research regarding mangrove forest.

Prediction of water quality based on SVR by fluorescence excitation-emission matrix and UV-Vis absorption spectrum

As a result of economic development, the pollution of freshwater resources in urban areas of China is becoming more and more serious. Therefore, it is urgent and necessary to develop a real-time monitoring method for the water quality of urban streams and rivers. In this study, a novel method (CFFA) Combined by peak-picking method, Fluorescence spectral indexes, Fluorescence regional integration, and Absorption spectral indexes were designed to extract wide-ranging information from the combination of the excitation-emission matrix (EEM) and absorption spectrum (Abs) of water samples. More than 600 freshwater samples were collected at 180 sections of 60 rivers in the Yangzhou urban region from April 2018 and May 2019. The CFFA inputs form was applied to establish the prediction models of water quality indexes (COD_Cr, COD_Mn, NH₃-N, TP, TN, and BOD₅) based on ε-Support Vector Regression (ε-SVR). To examine the performance of the prediction models, contrastive analysis among CFFA and the other three input models was carried out. Results show that CFFA input models have shorter modeling time, lower RMSE and MAPE, and higher R² in both training and testing sets, and each constituent part of CFFA is important to the precise prediction on the basis of the ablating analysis. Our study highlights that SVR models with the CFFA input trained by numerous and various water samples could effectively predict multiple indexes for real-time water quality monitoring.

Biochar and nitrogen fertilizer co-application changed SOC content and fraction composition in Huang-Huai-Hai plain, China

Biochar can significantly enhance soil organic carbon (SOC) and crop yield, and it is therefore the preferred material for soil improvement in medium-low yield fields. In this study, a field experiment was designed to explore the impacts of biochar application on SOC content and fraction composition. Results indicated that incorporation of biochar into soil increased the SOC content by 26.9%-65.3% in the surface layer (0-10 cm) and 30.3%-63.0% in the subsurface layer (10-20 cm) of soil, while water-soluble organic carbon (WSOC) of the two layers was increased by 2.2-40.0% and 2.3-39.8%, respectively. Microbial biomass carbon decreased under conventional nitrogen treatments and increased with biochar addition under increased nitrogen application. The C:N value increased with biochar application, while the water-soluble C:N value of soil applied with 30 t ha^-1 biochar was lower than that of soil applied with 15 t ha^-1 biochar, both in the two tested soil layers. Wheat yield is evidently correlated with SOC, with the correlation coefficients of 0.919 and 0.952 in the surface and subsurface soil layers (P < 0.01), respectively. Particularly, increasing fulvic and humic acid-like compounds of WSOC promoted the bioavailability of nutrient elements, thereby increasing the crop yields. Therefore, biochar application is an effective means to fertilize middle-low yield soils through increasing SOC sequestration and nutrient reserves, or adjusting soil C:N value to a proper range, thereby reducing nutrient loss and increasing wheat yield.

Detection of adulterations in a valuable Brazilian honey by using spectrofluorimetry and multiway classification

Spectrofluorimetry combined with multiway chemometric tools were applied to discriminate pure Aroeira honey samples from samples adulterated with corn syrup, sugar cane molasses and polyfloral honey. Excitation emission spectra were acquired for 232 honey samples by recording excitation from 250 to 500 nm and emission from 270 to 640 nm. Parallel factor analysis (PARAFAC), partial least squares discriminant analysis (PLS-DA), unfolded PLS-DA (UPLS-DA) and multilinear PLS-DA (NPLS-DA) methods were used to decompose the spectral data and build classification models. PLS-DA models presented poor classification rates, demonstrating the limitation of the traditional two-way methods for this dataset, and leading to the development of three-way classification models. Overall, UPLS-DA provided the best classification results with misclassification rates of 4% and 8% for the training and test sets, respectively. These results showed the potential of the proposed method for routine laboratory analysis as a simple, reliable, and affordable tool.

UV excited fluorescence image-based non-destructive method for early detection of strawberry (Fragaria × ananassa) spoilage

The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry.

Toxicity reduction of reverse osmosis concentrates from petrochemical wastewater by electrocoagulation and Fered-Fenton treatments

In this work, both Electrocoagulation (EC) and Fered-Fenton (FF) technologies were used to treat reverse osmosis concentrates (ROC) from petrochemical production. The toxicity reduction capacity and mechanism were comparatively assessed during these two treatments. The results showed that FF exhibited higher capacity to reduce toxicity than EC in the 30 min treatment, which could be attributed to the removal of organic pollutants and heavy metals. The results showed that the ROC contained organics with molecular weight of 1200 g mol^-1 and 220 g mol^-1, which mainly consisted of the soluble microbial by-product-like and humic acid-like substances. The removal of these organics directly led to the noticeable toxicity reduction. Alkanes, haloalkanes, ketones, PAHs, and other four organic pollutants were the dominant species in the ROC, and the removal of small molecular weight organic pollutants played an essential role in reducing toxicity. FF exhibited stronger capacity to remove PAHs, BTEXS and haloalkanes, and the removal efficiencies for the PAHs were in the following order: 5-ring > 4-ring > 3-ring > 2-ring. The promotion of heavy metals removal appeared to be favorable for decreasing toxicity in ROC. This study illustrated the mechanism of the toxicity reduction and the characteristics of pollutants removal during FF and EC treatments, and provided valuable guidance for petrochemical manufacturing to the toxicity reduction and operation of wastewater treatment facilities.

Excitation-emission fluorescence matrix acquired from glutathione capped CdSeS/ZnS quantum dots in combination with chemometric tools for pattern-based sensing of neurotransmitters

The presented work concerns pattern-based sensing with quantum dots for the identification and quantification of neurotransmitters by means of excitation-emission fluorescence spectroscopy (2D fluorescence). In the framework of this study, glutathione capped CdSeS/ZnS nanocrystals were used as non-specific nanoreceptors capable of differentiated interaction with neurotransmitters. The pattern-based sensing with QDs was realized by using excitation-emission fluorescence spectroscopy to provide analyte-specific multidimensional optical information. These characteristic fluorescent response patterns were processed by unfolded partial least squares-discriminant analysis, showing that satisfactory identification of all investigated neurotransmitters: dopamine, norepinephrine, epinephrine, serotonin, GABA, and acetylcholine, can be achieved through the proposed sensing strategy. The impact of the considered fluorescence signal (datum, i.e. zeroth-order data acquired per sample; spectrum, i.e. first-order data acquired per sample; excitation-emission matrix, i.e. second-order data acquired per sample) on the sensing capability of glutathione capped QDs was also verified. The best performance parameters such as accuracy, precision, sensitivity, and specificity were obtained using excitation-emission matrices (88.9-93.3%, 0.93-0.95, 0.89-0.93, and 0.99-1.00, respectively). Thus, it was revealed that excitation-emission fluorescence spectroscopy may improve the recognition of neurotransmitters while using only one type of nanoreceptor. Furthermore, is was demonstrated that the proposed excitation-emission fluorescence spectroscopy assisted QD assay coupled with unfolded partial least squares regression can be successfully utilized for quantitative determination of catecholamine neurotransmitters at the micromolar concentration range with R2 in the range 0.916-0.987. Consequently, the proposed sensing strategy has the potential to significantly simplify the sensing element and to expand the pool of bioanalytes so far detectable with the use of QDs.

Determining the leading sources of N-nitrosamines and dissolved organic matter in four reservoirs in Southern China

The presence of carcinogenic N-nitrosamines and dissolved organic matter (DOM) in freshwater is a significant concern from the perspective of public health and drinking water treatment plant operation. This study investigated the N-nitrosamines concentration and their precursors' distributions, and DOM composition in four reservoirs located in a southern city of China. A total of 22 renowned precursors were identified. Precursors from industrial and pharmaceutical origins were found to be dominant in all reservoirs; however, traces of pesticide-based precursors, i.e. pirimicarb and cycluron were also found. The distribution of nine N-nitrosamines was substantially different among the reservoirs. N-Nitrosodibutylamine (NDBA), N-Nitrosopiperidine (NPIP), N-Nitrosodimethylamine (NDMA), and N-Nitrosopyrrolidine (NPYR) were abundantly present in all reservoirs. Most of N-nitrosamines except NDMA and N-nitrosodiethylamine (NDEA) were far below the generally accepted cancer risk of 10^-6, and NDMA/NDEA were found close to the risk level (10^-6). Anthropogenic DOM was dominant in three reservoirs as depicted by a higher biological index (BIX) than the humification index (HIX). By the principle component analysis, BIX appeared as an indicator of N-nitrosamines (except NDEA and NPIP). A strong and direct relationship was observed between the NDMA-formation potential (FP) and concentration of total N-nitrosamines (∑NA), and BIX. These results confirmed that the anthropogenic activities were the leading source of DOM and N-nitrosamines in this city based on land-use.

A year-long cyclic pattern of dissolved organic matter in the tap water of a metropolitan city revealed by fluorescence spectroscopy

Delivering drinking water with stable quality in metropolitan cities is a big challenge. This study investigated the year-long dynamics of dissolved organic matter (DOM) in the tap water and source water of a metropolitan city in southern China using fluorescence spectroscopy. The DOM detected in the tap water, and source water of Shenzhen city was season and location-dependent. A year-long cyclic trend of DOM was found with predominate protein-like fluorescence in the dry season compared to the humic-like enriched DOM in the wet season. A general DOM pattern was estimated by measuring the shift in dominant fluorescence regions on the excitation-emission matrix (EEM). The difference in fluorescent DOM (FDOM) composition (in terms of the ratio of protein-like to humic-like fluorescence) was above 200% between wet and dry seasons. The taps associated with reservoirs receiving water from the eastern tributary of Dongjiang River showed significant changes in protein-like contents than the taps with source water originating from the western part of the river. This study highlights the importance of optimizing drinking water treatment plants' operational conditions after considering seasonal changes and source water characteristics.

Three efficient chemometrics assisted fluorimetric detection methods for interference-free, rapid, and simultaneous determination of ibrutinib and pralatrexate in various complicated biological fluids

In this study, a series of green, interference-free fluorimetric detection methods of the excitation-emission matrix coupled with the second-order calibration methods were proposed for the determination of ibrutinib and pralatrexate in various complicated biological fluids. The second-order advantage of the proposed method can overcome the problem of poor selectivity caused by the wide spectra of the fluorescence method. Even in the presence of uncalibrated interferences and severe peak overlap, the signal of pure substance and accurate quantitative results were still obtained. The average recoveries of the three methods were 94.5-104.9% for Alternating Trilinear Decomposition (ATLD) algorithm, 95.5-105.8% for Alternating Normalization Weighted Error (ANWE) algorithm and 94.4-105.7% for Parallel Factor Analysis (PARAFAC) algorithm, respectively. For ATLD, ANWE and PARAFAC, the relative standard deviations (RSD) were lower than 9.2%, 6.8% and 9.2%, and the RMSEPs were less than 8.1, 8.4 and 8.6 ng mL^-1, respectively. In addition, the elliptic joint confidence region (EJCR) was adopted to further prove the accuracy of the three methods. The results showed that the three methods can accurately be quantified without significant difference. Good figures of merit parameters were also obtained. Among them, the limit of detection (LOD) and limit of quantification (LOQ) of ibrutinib and pralatrexate were in the range of 0.11-0.76 ng mL^-1 and 0.21-1.12 ng mL^-1, respectively, which were lower than the corresponding blood concentrations. These results indicate that the proposed method provides a promising, alternative and universal analysis strategy for clinical drug monitoring.

Irrigation alters source-composition characteristics of groundwater dissolved organic matter in a large arid river basin, Northwestern China

It has been well documented that agricultural activities lead to significant alterations in surface water dissolved organic matter (DOM), yet their impacts on groundwater DOM remain poorly constrained. The quantity, source, and composition of DOM play a pivotal role in a range of groundwater ecosystem services that are of important ecological and societal values. We assessed the impact of irrigation on the source and compositional characteristics of groundwater DOM in a large river basin supporting intensive agriculture in arid northwestern China. We sampled five water types along a river reach of approximately 40 km, including groundwater, river water, irrigation canal water, hyporheic water, and soil leachates. The excitation-emission matrix (EEM) measurements coupled with parallel factor analysis (PARAFAC) identified two terrestrial-derived, humic-like fluorescent components (C1 and C2) and one protein-like autochthonous component (C3). DOM composition and dissolved organic carbon (DOC) concentration varied as a function of water type, with subsurface waters showing relatively lower DOC and terrestrial humic fluorescence than surface waters. Combining nitrate, electrical conductivity, dissolved inorganic carbon (DIC), and δ¹³C-DIC, irrigation-influenced samples were identified, and the influence of irrigation on groundwater DOM appeared only in shallow aquifers (<50 m). Irrigation-influenced groundwater exhibited higher DOC and terrestrial fluorescence than unimpacted groundwater, suggesting that irrigation return flows accelerated the downward movement of terrestrial humic compounds and led to their accumulation in aquifers. This effect was propagated via surface water-groundwater interactions to upwelling hyporheic water, which also showed enrichment in terrestrial fluorescence. Our findings demonstrate that irrigation can accelerate the biogeochemical cycling of organic compounds via a subsurface pathway of from the soil to aquifer to hyporheic zone. The enrichment of soil-derived compounds in subsurface waters may have important ecological consequences, such as altering the transport of nutrients and pollutants and changing carbon and energy flows across the surface-subsurface boundary.

Front-face fluorescence excitation-emission matrix (FF-EEM) for direct analysis of flocculated suspension without sample preparation in coagulation-ultrafiltration for wastewater reclamation

Fluorescence spectroscopy has been suggested as a promising online monitoring technique in water and wastewater treatment processes due to its high sensitivity and selectivity. However, a pre-filtration is still indispensable in fluorescence measurement for removing ubiquitous particles and flocs in real samples to eliminate the strong light scattering that could attenuate fluorescence detection significantly. This study proposed a front-face fluorescence spectroscopy, which could characterize the liquid sample with suspended solids directly without pre-filtration. Front-face excitation-emission matrix (FF-EEM) coupled with parallel factor (PARAFAC) analysis was used for analyzing fluorescence components and to probe coagulation of secondary effluent and fouling in the subsequent ultrafiltration (UF), and conventional right-angle fluorescence EEM (RA-EEM) was also compared. The results showed that FF-EEM was less susceptible to turbidity (induced by standard particles) in the secondary effluent compared to RA-EEM. FF-EEM could successfully measure dissolved fluorophores in coagulated suspension without pre-filtration, while conventional RA-EEM was undermined significantly due to the existing flocs. FF-EEM coupled with PARAFAC could accurately probe dissolved organic matter and fouling in coagulation- UF wastewater reclamation processes. Therefore, it was demonstrated that this front-face fluorescence without any sample preparation step might be highly promising in real-time online fluorescence monitoring in multi water and wastewater treatment processes.

Authentication of the geographical origin of Australian Cabernet Sauvignon wines using spectrofluorometric and multi-element analyses with multivariate statistical modelling

With the increased risk of wine fraud, a rapid and simple method for wine authentication has become a necessity for the global wine industry. The use of fluorescence data from an absorbance and transmission excitation-emission matrix (A-TEEM) technique for discrimination of wines according to geographical origin was investigated in comparison to inductively coupled plasma-mass spectrometry (ICP-MS). The two approaches were applied to commercial Cabernet Sauvignon wines from vintage 2015 originating from three wine regions of Australia, along with Bordeaux, France. Extreme gradient boosting discriminant analysis (XGBDA) was examined among other multivariate algorithms for classification of wines. Models were cross-validated and performance was described in terms of sensitivity, specificity, and accuracy. XGBDA classification afforded 100% correct class assignment for all tested regions using the EEM of each sample, and overall 97.7% for ICP-MS. The novel combination of A-TEEM and XGBDA was found to have great potential for accurate authentication of wines.

Applicability of conventional and non-conventional parameters for municipal landfill leachate characterization

The disposal of municipal solid waste (MSW) in landfills generates leachate, a highly polluting liquid to the aquatic environment. Leachate composition become a challenge to choose the best treatment process. Then, detailed techniques to determine the organic content, in terms of refractability, composition, sources and biodegradability in landfill leachate can help to choose the appropriate treatment and improve landfill management. In this sense, the aim of this study is to apply conventional and non-conventional parameters through inert chemical oxygen demand (COD) analyses and spectroscopic techniques of fluorescence and UV-vis absorbance for the characterization of municipal landfill leachate. Results indicated that physicochemical characterization cannot provided enough detailed information about leachate composition, which becomes the treatment process fragile. Inert COD, besides have high time to execution (∼30 days), presented additional information on potential of biological treatability in anaerobic conditions. Dissolved organic matter (DOM) characterization showed transitions between labile and refractory organic matter compounds. Moreover, the cost estimated showed that non-conventional parameters analysis have lower investment than conventional, being their implementation feasible. In conclusion, the synergy between conventional and non-conventional parameters, and the detailed information provided by inert COD and DOM characterization, shown a useful tool to the landfill management and, consequently, improving treatment process and its efficiency.

Absorbance and EEM fluorescence of wastewater: Effects of filters, storage conditions, and chlorination

Aim of this study was to delineate sample handling procedures for accurate fluorescence and UV absorbance measurements of wastewater organic matter. Investigations were performed using different wastewater qualities, including primary, secondary and tertiary wastewater effluents, and a wastewater-impacted surface water. Filtration by 0.7 μm glass microfiber filter, 0.45 μm polyvinylidene fluoride (PVDF) membrane, 0.45 μm cellulose nitrate membrane, and 0.45 μm polyethersulfone (PES) syringe filter released manufacture impurities in water that affected fluorescence measurements. However, pre-washing of filter by Milli-Q water was able to eliminate these interferences. Different storage conditions were tested, including storage of filtered and unfiltered samples under different temperatures (25 °C, 4 °C, -20 °C). According to the obtained results, the best practice of wastewater samples preservation was sample filtration at 0.7/0.45 μm immediately after collection followed by storage at 4 °C. However, the time of storage that assured changes of these spectroscopic measurements that do not exceed the 10% of the original value was dependent on water quality and selected wavelengths (i.e., selected fluorescing organic matter component). As a general rule, it is advisable to perform fluorescence and UV absorbance measurements as soon as possible after collection avoiding storage times of filtered water longer than 2 days. Finally, addition of chlorine doses typical for wastewater disinfection mainly affected tryptophan-like components, where changes that exceed the 10% of the fluorescence intensity measured in the unchlorinated sample were observed even at very low doses (≥1 mg/L). On the contrary, tyrosine-like and humic-like components showed changes <10% at chlorine doses of 0.5-5 mg/L.

Box-Behnken response surface approach to identify factors affecting membrane fouling in a hybrid membrane bioreactor treating domestic sewage

The effect of hydraulic retention time (HRT) and sludge retention time (SRT) on extracellular polymer substrate (EPS) content and resistance of a hybrid membrane bioreactor (HMBR) treating domestic sewage was analyzed by Box-Behnken response surface methodology. The quadratic response surface model demonstrated significant effects of both HRT and SRT on EPS content (both P value < 0.05), SRT on membrane resistance (P value = 0.0119), and their interaction was significant (P value = 0.0273) for EPS but not membrane resistance (P value = 0.0609). Model optimization indicates that the optimal conditions for the HMBR to control membrane fouling were an HRT of 10 h and SRT of 30 days. Under these optimal conditions, both the EPS content and the predicted membrane resistance closely matched the actual average value with the error about 8%. Thus, the feasibility of applying response surface methodology to an HMBR for treating domestic sewage was demonstrated. According to the detection result of the three-dimensional fluorescence (excitation-emission matrix), humic acid-like and fulvic acid-like substances gain much higher levels in the suspended carriers than those in the membrane and sludge, suggesting that these are key components of the membrane pollutants. Graphical abstract .

Effects of laboratory biotic aging on the characteristics of biochar and its water-soluble organic products

Effects of biotic aging on the characteristics of biochar and its water-soluble organic products were determined through a one-year laboratory incubation study. Biochar had a positive influence on microbial population size. Without microbial addition, biochars showed little change, except for an obvious increase in oxygen content from 3.2% to 6.3% after one year. By contrast, the carbon (C) content of the biologically-aged biochars continually decreased throughout the incubation at two humidity levels, suggesting that microbes consumed biochar C or encouraged organic matter solubilization. Fourier Transform Infrared Spectroscopy (FTIR) analysis indicated that all aged biochar surfaces showed increases in oxygen-containing functional groups and TG-DTG analysis showed that biologically-aged biochars were less stable than the corresponding abiotically-aged one. The release of dissolved organic matters from biologically-aged biochar logarithmically increasing with time, corresponded with of the pattern of microbe production, suggesting microbial involvement in solubilizing biochar. Combined three-dimensional excitation-emission matrix (3DEEM) and parallel factor (PARAFAC) analyses revealed that fulvic and humic acid-like components were the main water-soluble products of biologically-aged biochar, and these became increasingly rich in O-containing functional groups, i.e. humified, over time. These results highlight the importance of microbes in chemically transforming biochar and the dissolved products of biochar during aging.

The registration of aptamer-ligand (ochratoxin A) interactions based on ligand fluorescence changes

The fluorescent properties of ligands can change when they bind to specific receptors. Modulated by the transition of the ligand from the free to the bound state, fluorescence makes it possible both to detect this ligand and quantitatively register its binding. We characterized the interaction of ochratoxin A (OTA) with the specific G-quadruplex aptamer through excitation-emission matrix fluorescence spectroscopy. It was shown that the formation of the complex changes the OTA fluorescence spectrum both in the region of the main peak at λ_ex/λ_em 380/430 nm and in the region of peak at λ_ex/λ_em 265/425 nm. At pH 8.5 and OTA concentration of 30 nM, this peak is smaller in intensity than the main peak of fluorescence. The formation of the complex with the aptamer leads to an increase of the fluorescence at λ_ex/λ_em 265/425 nm up to 6.5 times, which makes it up to 4.9 times more intense than fluorescence at 380/430 nm. Fluorescence of the G-quadruplex aptamer (donor) takes part in increasing of the OTA (acceptor) emission at λ_ex/λ_em 265/425 nm due to the resonance energy transfer. The concentration regularities of the modulated fluorescence of OTA at λ_ex/λ_em 265/425 nm have been studied. Their correspondence to the calculations of complexation conducted on the basis of the dissociation constant is shown.

Multivariate Curve Resolution - Alternate Least Square Analysis of Excitation-Emission Matrices for Maize Flour Contaminated with Aflatoxin B1

In this preliminary study, we used the Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) algorithm to analyze the excitation-emission matrix for different samples of maize flour contaminated with aflatoxin B1 (AFB1) - uncontaminated, low-contaminated, high-contaminated and flour from the local market. We intended to see if there are differences in emission spectral parameters that depend on degree of contamination. The analysis used genuine emission of the fluorophores in the flour, in absence and presence of AFB1, which enables fast screening of the samples, without sample pre-processing. As a result of the analysis, two fluorescence components were derived from the emission spectra for all analyzed samples. The components' positions were the same for the uncontaminated reference sample and the commercial flour sample from the local market, whereas for the samples contaminated with the aflatoxin B1, the emitted peaks' positions were red-shifted. We found that the ratio of the areas of these two components is proportional to the intensity of contamination: 0.071 for uncontaminated sample, 0.090 for the sample from local market, 0.192 for low-contaminated sample and 1.431 for high-contaminated sample. These results indicate that fluorescence EEM coupled with MCR-ALS could be used for rapid and simple estimation of the degree AFB1 contamination in maize flour.

Dynamic validation of online applied and surrogate-based models for tertiary ozonation on pilot-scale

New robust correlation models for ozonation, based on UVA₂₅₄ and fluorescence surrogate parameters and developed considering kinetic information, have been applied at pilot-scale. This model framework is validated with the aim for operators to control the ozone dose for the removal of trace organic contaminants (TrOCs) in effluents from full-scale municipal wastewater treatment plants. The inflected correlation model between ΔTrOCs and the surrogates predicts the removal of TrOCs (based on statistical evidence) solely using the 2nd order reaction rate constant with ozone (k_O3) and in a more adequate manner than similar single correlation models. This allows the use of this new model for current and future TrOCs under investigation which is highly interesting when imposed discharge limits might include more and other TrOCs in future. The use of UVA₂₅₄ might be preferable at the current timing for online monitoring of TrOC abatement as the model showed a good predictive power (based on statistical evidence and visual confirmation). Reliable online sensors are more widespread (and commercially) available compared to fluorescence sensors which are still under development, with the exception of a few examples. Nevertheless, the data processing of the fluorescence signals, isolating the different intensities associated with moieties reacting similarly to ozone might even increase the predictive power, given the lower degree of interference (i.e. less scattering).

Multiway analysis methods applied to the fluorescence excitation-emission dataset for the simultaneous quantification of valsartan and amlodipine in tablets

In this study, excitation-emission matrix datasets, which have strong overlapping bands, were processed by using four different chemometric calibration algorithms consisting of parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares for the simultaneous quantitative estimation of valsartan and amlodipine besylate in tablets. In analyses, preliminary separation step was not used before the application of parallel factor analysis Tucker3, three-way partial least squares and unfolded partial least squares approaches for the analysis of the related drug substances in samples. Three-way excitation-emission matrix data array was obtained by concatenating excitation-emission matrices of the calibration set, validation set, and commercial tablet samples. The excitation-emission matrix data array was used to get parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares calibrations and to predict the amounts of valsartan and amlodipine besylate in samples. For all the methods, calibration and prediction of valsartan and amlodipine besylate were performed in the working concentration ranges of 0.25-4.50μg/mL. The validity and the performance of all the proposed methods were checked by using the validation parameters. From the analysis results, it was concluded that the described two-way and three-way algorithmic methods were very useful for the simultaneous quantitative resolution and routine analysis of the related drug substances in marketed samples.

Time-resolved fluorescence observation of di-tyrosine formation in horseradish peroxidase upon ultrasound treatment leading to enzyme inactivation

The application of ultrasound to a solution can induce cavitional phenomena and generate high localised temperatures and pressures. These are dependent of the frequency used and have enabled ultrasound application in areas such as synthetic, green and food chemistry. High frequency (100kHz to 1MHz) in particular is promising in food chemistry as a means to inactivate enzymes, replacing the need to use periods of high temperature. A plant enzyme, horseradish peroxidase, was studied using time-resolved fluorescence techniques as a means to assess the effect of high frequency (378kHz and 583kHz) ultrasound treatment at equivalent acoustic powers. This uncovered the fluorescence emission from a newly formed species, attributed to the formation of di-tyrosine within the horseradish peroxidase structure caused by auto-oxidation, and linked to enzyme inactivation.

Removal and transformation of polycyclic aromatic hydrocarbons during electrocoagulation treatment of an industrial wastewater

Polycyclic aromatic hydrocarbons (PAHs) are an important class of water pollutants because of their known ecological and human toxicity. Electrocoagulation (EC) is a promising technology for mitigating industrial wastewater pollution, but the removal and transformation of PAHs during EC treatment has not yet been understood. Therefore, a paper-making wastewater effluent (PMWW) was employed in this study to investigate the relationship between PAHs' removal and transformation during EC treatment. The results show that 86% of PAHs were effectively removed not only by the electro-oxidation reactions, but also by adsorption onto Fe hydroxide flocs. The removal and transformation of PAHs were related to the number of rings in their structures. Some PAHs composed of two aromatic rings (e.g., naphthaline and dimethylnaphthalene) were produced from humic acid-like and fulvic acid-like organics in PMWW, while PAHs with three to four rings were degraded, thus being removed efficiently. Therefore, PAH transformation during EC treatment exerted double-sided effects on the removal of PAHs; the net effect appeared to be positive. Overall, this study revealed the existence and importance of PAH transformation during EC treatment and provided useful guidance for pulp and paper mills to improve the design and operation of wastewater treatment facilities.

Autofluorescence excitation-emission matrices for diagnosis of colonic cancer

AIM: To investigate the autofluorescence spectroscopic differences in normal and adenomatous colonic tissues and to determine the optimal excitation wavelengths for subsequent study and clinical application.

METHODS: Normal and adenomatous colonic tissues were obtained from patients during surgery. A FL/FS920 combined TCSPC spectrofluorimeter and a lifetime spectr-ometer system were used for fluorescence measurement. Fluorescence excitation wavelengths varying from 260 to 540 nm were used to induce the autofluorescence spectra, and the corresponding emission spectra were recorded from a range starting 20 nm above the excitation wavelength and extending to 800 nm. Emission spectra were assembled into a three-dimensional fluorescence spectroscopy and an excitation-emission matrix (EEM) to exploit endogenous fluorophores and diagnostic information. Then emission spectra of normal and adenomatous colonic tissues at certain excitation wavelengths were compared to determine the optimal excitation wavelengths for diagnosis of colonic cancer.

RESULTS: When compared to normal tissues, low NAD (P)H and FAD, but high amino acids and endogenous phorphyrins of protoporphyrin IX characterized the high-grade malignant colonic tissues. The optimal excitation wavelengths for diagnosis of colonic cancer were about 340, 380, 460, and 540 nm.

CONCLUSION: Significant differences in autofluorescence peaks and its intensities can be observed in normal and adenomatous colonic tissues. Autofluorescence EEMs are able to identify colonic tissues.