Abstract It is important to break the low metal loading limited by stringent conditions and reveal the catalytic behavior of single-atom catalysts (SACs) governed by individual and interacting sites. Here, a facile and universal synthesis strategy was employed to achieve the highest loading of transition metals (Fe 41.31wt%, Mn 35.13wt%), rare-earth metals (La 28.62wt%), and noble metals (Ag 27.04wt%) to date. Systematic investigation confirms that the powerful ligand-chelation between oxalic acid and metal ions, as well as the simultaneously generated entangled polymer networks are crucial for achieving high-loading SACs. High single-atoms density induced site-intensive effects and site-to-site interactions, which regulated the local electron density of the catalyst, altered the electronic structure of metal, and shifted the valence state toward the metal. As a demonstration, the activation of peroxymonosulfate (PMS) for sulfamethoxazole degradation showed a significant dependence on catalyst site density, with the rate constant at least 1-2 orders of magnitude higher than that of most current SACs. The higher metal loading increased the potential jumps in Fenton-like reaction, promoted the electron transfer and reduced the energy barrier of the rate-determining step in 1O2 generation. This material also showed promising prospect for real wastewater treatment due to its high decontamination efficiency and application stability. The cascade-anchoring synthesis strategy, which can maximize the atomically dispersed metal loadings and simultaneously enhance the reactivity, is universally applicable. It is anticipated that it will take SACs a step closer to practical applications.
In the urban water supply system, a significant proportion of energy consumption is attributed to the water supply pumping station (WSPS). The conventional manual scheduling method employed by water supply enterprises imposes a considerable economic burden. In this paper, we intend to minimize the energy cost of WSPS by dynamically adjusting the combination of pumps and their operational states while considering the pressure difference of the main pipe and switching times of pump group. Achieving this goal is challenging due to the lack of accurate mechanistic models of pumps, uncertainty in environmental parameters, and temporal coupling constraints in the database. Consequently, a WSPS pump scheduling algorithm based on physics‐informed long short‐term memory (PI‐LSTM) surrogate model and multiagent deep deterministic policy gradient (MADDPG) is proposed. The proposed algorithm operates without prior knowledge of an accurate mechanistic model of the pump units. Combining data‐driven with the physical laws of fluid mechanics improves the prediction accuracy of the model compared to traditional data‐based deep learning models, especially when the amount of data is small. Simulation results based on real‐world trajectories show that the proposed algorithm can reduce energy consumption by 13.38% compared with the original scheduling scheme. This study highlights the potential of integrating physics‐informed deep learning and reinforcement learning to optimize energy consumption in urban water supply systems.
It is critical to discover a non-noble metal catalyst with high catalytic activity capable of replacing palladium in electrochemical reduction. In this work, a highly efficient single-atom Co-N/C catalyst was synthesized with metal-organic frameworks (MOFs) as a precursor for electrochemical dehalogenation. X-ray absorption spectroscopy (XAS) revealed that Co-N/C exhibited a Co-N4 configuration, which had more active sites and a faster charge-transfer rate and thus enabled the efficient removal of florfenicol (FLO) at a wide pH, achieving a rate constant 3.5 and 2.1 times that of N/C and commercial Pd/C, respectively. The defluorination and dechlorination efficiencies were 67.6 and 95.6%, respectively, with extremely low Co leaching (6 μg L-1), low energy consumption (22.7 kWh kg-1), and high turnover frequency (TOF) (0.0350 min-1), demonstrating excellent dehalogenation performance. Spiking experiments and density functional theory (DFT) verified that Co-N4 was the active site and had the lowest energy barrier for forming atomic hydrogen (H*) (ΔGH*). Capture experiments, electron paramagnetic resonance (EPR), electrochemical tests, and in situ Fourier transform infrared (FTIR) proved that H* and direct electron transfer were responsible for dehalogenation. Toxicity assessment indicated that FLO toxicity decreased significantly after dehalogenation. This work develops a non-noble metal catalyst with broad application prospects in electrocatalytic dehalogenation.
Facing low treatment efficiency, narrow adaptive pH and high energy consumption in electro-Fenton (EF), we proposed a novel flow-through metal-free electrochemical advanced oxidation processes (EAOPs) using biomass derived S, N self-doped catalytic Janus cathode named SNJC. The SNJC was composed of a hydrophobic gas diffusion layer in the middle and hydrophilic catalytic membrane at both ends, while the catalytic membrane of S, N self-doped biomass carbon named SN-BC was derived from waste ginkgo leaves without additional supporting templates or activation processes. This flow-through system exhibited superior catalytic performance in wide pH ranges (3–11) due to the collective effect of radicals (•OH and O2•−) and non-radical (1O2). This work provides a new insight towards the design of S, N self-doped Janus electrode and activation mechanism of in-situ generation and metal-free catalysis of H2O2 in flow-through EAOPs.
The warming of the climate and the increase in animal sources of infection due to changes in the natural environment, and the deterioration of air quality and unclean using water due to pollution are important environmental health factors that can influence the prevention of infectious diseases. In addition, excessive urbanisation development and over-production of food due to the global population explosion will also pose a significant challenge in terms of prevention measures for emerging infectious diseases. In conclusion, environmental health plays an important role in the prevention of infectious diseases and a multidisciplinary approach is an appropriate way to prevent infectious diseases.
Compound droughts and heatwaves (CDHWs) are likely to cause more severe natural disasters than a single extreme event, and they have been exacerbated by rapid global warming. Based on high-resolution grid data, this study combines the daily-scale ERA5-Land dataset and the monthly-scale SPEI dataset with multiple indicators to analyze CDHWs. We calculated and analyzed the temporal and spatial modal distribution of CDHWs in Central Asia from 1981 to 2018, and in this paper, we discuss the sequence relationship between drought events, heatwave events, and CDHWs. The results show that the number of CDHWs in the study region have increased over time and expanded in terms of area, especially in eastern and southwestern Central Asia. The tsum (total frequency of CDHWs) was 0.5 times higher than the total heatwave frequency and it increased at a rate of 0.17/yr. The maximum duration of tmax (maximum duration of CDHWs in days) was 17 days. Furthermore, the occurrence rate of tmax was 96.67%, and the AH (CDHWs’ accumulated heat) had a rate of 97.78%, which, upon examination of the spatial trend pattern, accounted for the largest increase in terms of area. We also found that the TAH (CDHWs’ average temperature anomalies, SPEI < −0.5) shows obvious seasonality, with the increases in winter and spring being significantly greater than the increases in summer and autumn. The intensity of the CDHWs was stronger than that of a single extreme event, the temperature anomaly was higher than the average of 0.4–0.8 °C, and there was a north–south spatial pattern across the study region. In eastern and northwestern Central Asia, the AH and heatwaves (SPEI < −0.5) increased by 15–30 times per year on average. During the transition from the base period to the reference period, CDHWs increased by 25%, and the number of dry days prior to the CDHWs decreased by 7.35 days. The conclusion of our study can provide a theoretical basis for coping with climate change in arid zones.
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