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Triclosan (TCS) has been regarded as an emerging contaminant in aquatic systems, making its efficient removal of great significance. In this study, NPVMo@iPAF-1, with a specific surface area of 665 m2/g, was prepared by incorporating (NH4)5H6PV8Mo4O40 into porous aromatic frameworks (PAF). The maximum adsorption capacity of TCS on NPVMo@iPAF-1 reached 917.1 mg/g, as calculated from the Langmuir model. Fixed-bed columns packed with NPVMo@iPAF-1 were employed for TCS removal; the experiment data strongly correlated with the Thomas and Yoon-Nelson models under different operational conditions. Pore preservation, electrostatic effects, and the synergistic effect of π-π interactions contributed to the effective adsorption of TCS onto NPVMo@iPAF-1. The NPVMo@iPAF-1 fixed-bed column could be effectively regenerated through in-situ ozonation for more than 10 regeneration cycles. NPVMo@iPAF-1 turned out to be a promising adsorbent for removing TCS not only from pure water but also from reclaimed water and surface water samples. [ABSTRACT FROM AUTHOR]

Fine particulate matter ( P M 2.5 ) poses a significant threat to human life and health, and therefore, accurately predicting P M 2.5 concentration is critical for controlling air pollution. Two improved types of recurrent neural networks (RNNs), the long short-term memory (LSTM) and gated recurrent unit (GRU), have been widely used in time series data prediction due to their ability to capture temporal features. However, both degrade into random guessing as the time length increases. In order to enhance the accuracy of P M 2.5 concentration prediction and address the issue of random guessing in RNNs neural networks, this study introduces a TCN-biGRU neural network model. This model is a hybrid prediction approach based on combining temporal convolutional networks (TCN) and bidirectional gated recurrent units (bi-GRU). TCN extracts higher-level feature information from longer time series data of P M 2.5 concentrations, while bi-GRU captures features from past and future data to achieve more accurate predictive outcomes. This case study utilizes data from monitoring stations in Beijing in 2021 for conducting P M 2.5 prediction experiments. The TCN-biGRU model achieves an average absolute error, root mean square error, and R 2 of 4.20, 7.71, and 0.961 in its predictive outcomes. When compared to the predictive outcomes of individual LSTM, GRU, and bi-GRU models, it is evident that the TCN-biGRU model exhibits smaller errors and superior predictive performance. [ABSTRACT FROM AUTHOR]

Through the introduction of green finance policies, governments hope to improve the guiding role of institutional investors in green investment and provide financial support for green enterprises. Using the data in China, the difference-in-difference (DID) analysis explores whether the implementation of policies could change institutional investors' attitude to environmental factors when making investment decisions. Considering the effect of investment horizons, we find that long-term institutional investors have shown symmetric preferences on green investment, while short-term institutions are more affected by green finance policies. Additionally, the mechanism analysis shows that green finance policies can influence the green investment of institutional investors not only by affecting stock price returns but also by increasing the innovation capabilities of green companies and thus improving corporate performance. Besides, heterogeneity and moderating effect analyses find that green finance policies can achieve better policy effects when financial institutions invest in non-state-owned enterprises, enterprises with higher quality of information disclosure and poor external supervision. The finding would extend the studies of green investment in emerging markets and present new evidence about the policy effect on institutions' preferences for green investment. [ABSTRACT FROM AUTHOR]

Simultaneous removal of NOx and SO2 is carried out by an oxidation-absorption process, which NO oxidized by active hydroxyl radicals (·OH) derived from catalytic decomposition of vaporized H2O2 over Fe3O4/TiO2 and then adsorbed by NaOH solution along with SO2. Fe3O4/TiO2 synthesized by wet impregnation method with an additional reduction under H2 atmosphere was characterized by XRD, FTIR, BET, XPS, and VSM analysis. Effects of H2O2 concentration, H2O2 injection rate, reaction temperature, gas flow rate, and flue gas component on simultaneous removal were investigated. The experimental results show that NO can be effectively oxidized by highly reactive ·OH radicals generated from H2O2 decomposition over Fe3O4/TiO2 catalyst, and removal efficiencies of 93.31% for NO, 85.90% for NOx, and 100% for SO2 were obtained. The surface zero-valent iron (Fe0) and divalent iron (Fe2+) are the key factors of the catalytic oxidation with hydroxyl radical. H2O2 adsorption and dissociation mechanism on catalyst surface was studied using DFT calculation. The calculation results demonstrate that H2O2 prefers to dissociate on iron containing surface, and ·OH radicals generation follow by Haber-Weiss (H–W) mechanism. The stable oxidative product of HNO2 and HNO3 were generated through NO/NO2 and H2O2 co-adsorption on the FeO/TiO2 (0 0 1) surface. [ABSTRACT FROM AUTHOR]

Ozonation treatment of municipal secondary effluent is complicated by the low solubility of ozone and inefficient production of hydroxyl free radicals from ozone decomposition. To resolve these problems, this study investigated methods for intensifying ozonation treatment, using a combination of microbubbles and ultraviolet (UV) irradiation (UV/MBO). The high efficiency of the method was illustrated by treating river water containing refractory components derived from secondary effluent in a wastewater treatment plant. The results showed that the ozone mass transfer coefficient in a microbubble system was an order of magnitude compared with a conventional macrobubble system at the initial stage. The amount of ·OH generated during the treatment was quantified using a fluorescent probe analysis. The amount of ·OH in the UV/MBO system was almost 2–6 times more than the amount found with conventional ozonation using macrobubbles (CO), CO with UV irradiation (UV/CO), and microbubble ozonation (MBO) units. The UV/MBO system achieved chemical oxygen demand (COD), UV254, and UV400 removal performance rates of up to 37.50%, 81.15%, and 94.74% respectively. These levels were 2–36% higher than those in other systems. The coupling UV/MBO treatment significantly reduced all five categories of substances according to EEM spectra and fluorescence regional integration. The distribution of fractions with different molecular weights (MW) was altered and the UV254 of MW (< 500 Da) increased by 15.8%. The biodegradability of the water was significantly improved, as indicated by the TOC/UV254. This is ascribed to the enhanced degradation of refractory organics in the water. The combination of the UV/microbubble technique with ozonation could provide an efficient approach for advanced wastewater treatment. [ABSTRACT FROM AUTHOR]

A magnetic adsorbent (MA) was synthesized from wasted iron mud of a groundwater treatment plant using a novel one-step hydrothermal method. The results showed that Fe content of MA was 41.8 wt%, 2.5 times higher than that of iron mud, which was caused by hydrothermal dissolution of non-ferrous impurities under alkaline condition, such as quartz and albite, regardless of addition of ascorbic acid or not. Ferrihydrite was 92.7% in dry iron mud before adding ascorbic acid and gradually decreased to 58.1% by increasing the molar ratio of ascorbic acid to Fe following hydrothermal treatment. The strongest saturation magnetization of 16.29 emu/g was observed in the prepared MA-4 when the ascorbic acid to Fe molar ratio was 1. The highest surface site concentration of 1.31 mmol/g was observed in MA-2 when the ratio was 0.02. The mechanism of hydrothermal conversion of wasted iron mud to MA was reductive dissolution of ferrihydrite to form siderite, which was then reoxidized to maghemite. When 12.5 g/L of MA-2 was applied to treat smelting wastewater, over 99% removal of Cu2+, Zn2+, Pb2+, and Cd2+ was achieved. The major mechanisms of Cu2+ and Zn2+ adsorption by the adsorbent were cationic exchange. [ABSTRACT FROM AUTHOR]