Although studies on the recovery of disposable masks continue, the level is insufficient. Therefore, studies to be carried out on technologies that will enable the repeated use of masks are important.Plant waste (PW) and excess sludge (ES) are two main organic matters of municipal solid waste. However, there are few reports on their anaerobic co-digestion. In this work, the mixed proportion of PW and ES anaerobic co-digestion was first optimized at mesophilic temperature, and then the anaerobic co-digestion of PW and ES was enhanced with strong oxidant calcium peroxide (CP). The results showed that the optimal mixing ratio of PW and ES was 1/1 (in terms of volatile solids), the C/N of mixed digestion substrate was 23.5/1, and the maximum methane production was 172.6 mL/g (in terms of volatile solids). CP could enhance methane production from anaerobic co-digestion of PW and ES. When the content of CP was 0.2 g/g (in terms of total suspended solids), the maximum methane production was 234.8 mL/g, about 1.4 times of the blank. The mechanism investigation showed that CP promoted the release of organic matter during the co-digestion, and the higher the content of CP, the greater the release of soluble chemical oxygen demand. The presence of appropriate amount of CP promoted the activities of key enzymes in anaerobic fermentation process, and then increased the efficiency of methane production. The results of this work provide an alternative strategy for the resource utilization of PW and ES.Herein, a new adsorbent was prepared by modifying Mg-Fe LDH for the removal of Cu2+ metal ions from wastewater. Mg-Fe LDH with 5-(3-nitrophenyllazo)-6-aminouracil ligand has been successfully prepared using direct co-precipitation methods and was fully characterized using FTIR analysis, X-ray diffraction, BET surface area theory, zeta potential, partial size, TGA/DTA, CHN, EDX, FESEM, and HRTEM. The surface areas of Mg-Fe LDH and Mg-Fe LDH/ligand were 73.9 m2/g and 34.7 m2/g respectively. Moreover, Cu2+ adsorption on LDH surfaces was intensively examined by adjusting different parameters like time, adsorbent dosage, pH, and Cu2+ metal ion concentration. Several isotherm and kinetic models were investigated to understand the mechanism of adsorption towards Cu2+ metal ions. selleck products Adsorption capacity values of LDH and ligand-LDH rounded about 165 and 425 mg/g respectively, applying nonlinear fitting of Freundlich and Langmuir isotherm equations showing that the ligand-LDH can be considered a potential material to produce efficient adsorbent for removal of heavy metal from polluted water. The adsorption of Cu2+ metal ions followed a mixed 1,2-order mechanism. The isoelectric point (PZC) of the prepared sample was investigated and discussed. The effect of coexisting cations on the removal efficiency of Cu2+ ions shows a minor decrease in the adsorption efficiency. Recyclability and chemical stability of these adsorbents show that using Mg-Fe LDH/ligand has an efficiency removal for Cu2+ ions higher than Mg-Fe LDH through seven adsorption/desorption cycles. Moreover, the recycling of the Cu2+ ions was tested using cyclic voltammetry technique from a neutral medium, and the Cu2+ ion recovery was 68%.We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound’s safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals’ use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. Howev of compounds.Industrial transformation and upgrading is an important step for China to carry out cleaner production and achieve the goal of carbon neutrality. With the help of green finance, we can optimize the allocation of financial resources and promote the optimization and upgrading of industrial structure. In order to explore the impact efficiency and policy effect of green finance on industrial transformation and upgrading in China, through the establishment of VAR model and super-efficiency DEA model, the relationship between green finance and industrial transformation and upgrading and its impact on efficiency are studied. In addition, the Tobit regression model is used to empirically test the impact of public environmental demands, government regulations, and their interaction terms on the efficiency of green finance in promoting industrial transformation and upgrading. The results show that the overall efficiency of green finance in promoting industrial transformation and upgrading is high, but it shows a downward trend, which may be due to the unbalanced development of the green financial system, information asymmetry, and the absence of enterprises from regulation. The impact coefficient of input-oriented government regulation is significantly negative, which indicates that increasing the investment in pollution control may encourage polluting enterprises’ emission behavior to obtain benefits. The impact of performance-oriented government regulation and public environmental demands on efficiency is not significant, which indicates that the supervision and binding force of enterprises are insufficient. Public environmental demands and input government regulations have significant synergistic governance advantages, indicating that the government should enhance the regulatory intensity of differentiated policies. The study provides a reference for the government to enhance the intensity of policy regulation and establish a diversified environmental governance system.