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The present study investigated the parameters and the mechanism of action of electrochemical cell lysis to reduce the return sludge from secondary settlers based on the theory of cell lysis-cryptic growth. The factors influencing the functioning of two electrodes (Ti/SnO2-Sb and Ti/RuO2-IrO2) were investigated to determine the optimal cell lysis parameters for each electrode, and the effects of the two electrodes on cell lysis were compared under these conditions. Finally, the Ti/SnO2-Sb electrode was selected for the subsequent experiments. The electrolysis reaction was performed using the following parameters: the initial sludge concentration was 7000 mg/L, the working voltage was 18 V, the plate spacing was 1 cm, the initial pH was 6.8 to 7.0, and the electrolysis duration was 90 min. The degree of disintegration of the sludge and the cell lysis rate reached 25.35% and 20.15%, respectively. In summary, electrochemical cell lysis has a good prospect for sludge reduction. [ABSTRACT FROM AUTHOR]

Data-driven approaches that make timely predictions about pollutant concentrations in the effluent of constructed wetlands are essential for improving the treatment performance of constructed wetlands. However, the effect of the meteorological condition and flow changes in a real scenario are generally neglected in water quality prediction. To address this problem, in this study, we propose an approach based on multi-source data fusion that considers the following indicators: water quality indicators, water quantity indicators, and meteorological indicators. In this study, we establish four representative methods to simultaneously predict the concentrations of three representative pollutants in the effluent of a practical large-scale constructed wetland: (1) multiple linear regression; (2) backpropagation neural network (BPNN); (3) genetic algorithm combined with the BPNN to solve the local minima problem; and (4) long short-term memory (LSTM) neural network to consider the influence of past results on the present. The results suggest that the LSTM-predicting model performed considerably better than the other deep neural network-based model or linear method, with a satisfactory R 2 . Additionally, given the huge fluctuation of different pollutant concentrations in the effluent, we used a moving average method to smooth the original data, which successfully improved the accuracy of traditional neural networks and hybrid neural networks. The results of this study indicate that the hybrid modeling concept that combines intelligent and scientific data preprocessing methods with deep learning algorithms is a feasible approach for forecasting water quality in the effluent of actual engineering., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Metal-organic frameworks (MOFs) have attracted widespread concerns in the photocatalysis research. However, MOFs-based photocatalyts for antibiotics treatment are still very limited. There are also few reports on selecting MOFs as supports to regulate the morphology of Bismuthoxyhalides. In this study, BiOBr/UiO-66-NH 2 composites with three-dimensional structure of flower-like nanosphere were fabricated via a facile synthetic route. Various characterizations, such as XRD, SEM and XPS, proved the successful synthesis of composite and revealed that BiOBr nanoplates grow on the surfaces of the UiO-66-NH 2 with an intimate interaction. A typical fluoroquinolones antibiotics, norfloxacin (NOR) was selected to estimate the photocatalytic efficiency of the BiOBr/UiO-66-NH 2 complex. A series of the composites all exhibited higher NOR removal performance than the pure components and mechanically mixed sample under simulated sunlight. Among them, the composite with UiO-66-NH 2 content of 20 w% (BUN-20), had good structural stability and the best performance on the removal of NOR. The removal efficiency of NOR (10 mg/L) over BUN-20 (0.3 g/L) was 93.60% within 180 min irradiation. Three factors during the fabricating process, such as increased surface active sites, improved photoadsorption capacity and lower recombination probability of electron-hole pair might be accountable for the meliorative photocatalytic performance. Ultimately, a plausible photocatalytic mechanism was also proposed., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Visible light-driven conversion of soluble U(VI) to slightly soluble U(IV) has been regarded as a efficient and environmentally friendly technology to deal with uranium containing wastewater. In this paper, we attempted to use photocatalytic technology to reduction U(VI) from aqueous solution by constructing a highly efficient photocatalysts. The novel Sn-doped In 2 S 3 microspheres photocatalyst were synthesized for the first time by a simple hydrothermal method, and characterized with various analytical and spectroscopic techniques to determine their structural, morphological, compositional, optical and photocatalytic properties. In determination of photocatalytic activity, the results showed that all Sn-doped In 2 S 3 samples exhibited greater photocatalytic performance in reduction of U(VI) under visible light than the pure In 2 S 3 . The optimum SnIn 2 S 3 photocatalyst with Sn:In molar ratio of 1:4.8 (SnIn 2 S 3 ) had the highest photocatalytic performance (95% reduction efficiency within 40 min irradiation time), which was approximately 15.60 times faster than that of pure In 2 S 3 . The enhanced photocatalytic activity of the optimum SnIn 2 S 3 was largely ascribed to the higher specific surface area, red-shift in the absorption band, the efficient separation of photogenerated electron-hole pairs (e - /h + ) and the narrowed band gap with an up shifting of valence band, conduction band potentials. In addition the optimum SnIn 2 S 3 photocatalyst exhibited a good recyclability and stability during the repetitive experiments. Finally, the possible active species and the possible mechanism on basis of the experimental results were discussed in detail., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

In this study, batch experiments were carried out to investigate the key factors on sulfamethoxazole (SMX) removal kinetics in a new AOPs based on the combination of zero valent iron (Fe 0 ) and bisulfite (S(IV)). With the increase of Fe 0 from 0.25 mM to 5 mM, the removal rate of SMX was linearly increased in the Fe 0 /S(IV)/O 2 system by accelerating the activation of S(IV) and Fe 0 corrosion to accelerate. In the first 10 min of reaction, the increasing concentration of S(IV) inhibited SMX removal after since the high S(IV) concentration quenched reactive oxidative species (ROS). Then SMX removal rate was accelerated with the increase of S(IV) concentration after S(IV) were consumed up. The optimal ratio of S(IV) concentrations to Fe 0 concentration for SMX removal in the Fe 0 /S(IV)/O 2 system was 1:1. With SMX concentrations increasing from 1 to 50 μM, SMX removal rate was inhibited for the limitation of ROS yields. Although the presence of SO 4 - and OH was confirmed by electron paramagnetic resonance (EPR) spectrum, OH was identified as the dominant ROS in the Fe 0 /S(IV)/O 2 system by chemical quenching experiments. Besides, strong inhibitive effects of 1,10-phenanthroline on SMX degradation kinetics by Fe 0 /S(IV)/O 2 proved that the generation of ROS was rely on the release of Fe(II) and Fe(III). The generation of SO 4 - was ascribed to the activation of S(IV) by Fe(II)/Fe(III) recycling and the activation of HSO 5 - by Fe(II). And OH was simultaneously transformed from SO 4 - and generated by Fe 0 /O 2 . Density functional theory (DFT) calculation was conducted to reveal special reactive sites on SMX for radicals attacking and predicted intermediates. Finally, four possible SMX degradation pathways were accordingly proposed in the Fe 0 /S(IV)/O 2 system based on experimental methods and DFT calculation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)