The large amounts ofheavy metal from landscape wastewater have become serious problems of environmental pollution and risks for human health. The development of efficient novel adsorbent is a very important for treatment of heavy metal. The functionalized porous nanoscale Fe₃O₄ particles supported biochar from peanut shell (PS-Fe₃O₄) for removal of Pb(II) ions from aqueous solution was investigated. The characterization of PS-Fe₃O₄ composites showed that biochar was successfully coated with porous nanoscale Fe₃O₄ particles. The pseudo second-order kinetic model and Langmuir model were more fitted for describing the adsorption process of Pb(II) ions in solution. The adsorption process of Pb(II) ions removal by PS-Fe₃O₄ composites was a spontaneous and endothermic process. The adsorption mechanisms of Pb(II) ions by PS-Fe₃O₄ composites were mainly controlled by the chemical adsorption process. The maximum adsorption capacity of Pb(II) ions removal in solution by PS-Fe₃O₄ composites reached 188.68 mg/g. The removal mechanism included Fe–O coordination reaction, co-precipitation, complexation reaction, and ion exchange. PS-Fe₃O₄ composites were thought as a low-cost, good regeneration performance, and high efficiency adsorption material for removal of Pb(II) ions in solution.

Epidemiological studies have shown that particulate matters with diameter less than 2.5 μm (PM₂.₅) play an important role in inducing and promoting respiratory diseases, but its underlying mechanism remains to be explored. The air–blood barrier, also known as the alveolar–capillary barrier, is the key element of the lung, working as the site of oxygen and carbon dioxide exchange between pulmonary vasculatures. In this study, a mouse PM₂.₅ exposure model was established, which leads to an induced lung injury and air–blood barrier disruption. Oxidative stress and pyroptosis were observed in this process. After reducing the oxidative stress by N-acetyl-L-cysteine (NAC) treatment, the air–blood barrier function was improved and the effect of PM₂.₅ was alleviated. The level of pyroptosis and related pathway were also effectively relieved. These results indicate that acute PM₂.₅ exposure can cause lung injury and the alveolar–capillary barrier disruption by inducing reactive oxygen species (ROS) with the participation of pyroptosis pathway.

Improving green energy efficiency is crucial to promoting China’s high-quality economic development and reducing the environmental pollution. In this paper, the Malmquist-Luenberger index measures the green energy efficiency of 30 provinces in China from 2004 to 2019. Based on the measurement results, the spatial Durbin model is used to empirically study the impact of environmental regulation on green energy efficiency and its spatial spillover effects. The results show that China’s green energy efficiency is low, and its growth mainly comes from technological progress (TECH) rather than technological efficiency (EFFCH). The eastern region has the highest efficiency of green energy, followed by the West and the lowest in the Central region. The estimation results of the spatial Durbin model show that both environmental regulation and green energy efficiency have a significant spatial correlation. Environmental regulation can improve the green energy efficiency in the local province but inhibit green energy efficiency in the adjacent provinces. Finally, this paper puts forward relevant policy suggestions according to the research results.

This paper explores the performance of pilot-scale constructed wetland osmotic microbial fuel cell (CW-OMFC) in different gravel conditions. The performance was measured in terms of power generation, water flux, chemical oxygen demand (COD) removal, and coulombic efficiency. The CW-OMFC was divided into four sections based on the porosity of the materials. The surface area of materials at Side A, Side B, Side C, and Side D were 2.717 m².g⁻¹, 0.228 m².g⁻¹, 0.095 m².g⁻¹, and 0.072 m².g⁻¹, respectively. The CW-OMFC achieved maximum water flux, minimum reverse salt flux, high power density, and COD removal efficiency of 6.66 ± 0.5 L.m⁻².h⁻¹, 3.33 ± 1.2 g.m⁻².h⁻¹, 59.53 ± 10 mW.m⁻² and 84.69%, respectively, by using high porous materials. The nutrients (nitrogen, phosphorus, and potassium) uptake by plants from wastewater were 12.17%, 12.01%, and 21.73%, respectively.

The new coronavirus disease COVID-19 has caused a worldwide pandemic to be declared in a very short period of time. The complexity of the infection lies in asymptomatic carriers that can inadvertently transmit the virus through airborne droplets. This kind of viral disease can infect the human body with tiny particles that carry various bacteria that are generated by the respiratory system of infected patients. In this study, numerical results are proposed that demonstrate the effect of human body temperature and temperature from radiators in a room on the spread of the smallest droplets and particles in an enclosed space. The numerical model proposed in this work takes into account the sedimentation of particles and droplets under the action of gravitational sedimentation and transport in a closed room during the processes of breathing, sneezing or coughing. Various cases were considered, taking into account normal human breathing, coughing or sneezing, as well as three different values of the rate of emission of particles from the human mouth. The heat plume, which affects the concentration of particles in the breathing zone, spreads the particle up to a distance of 4.29 m in the direction of the air flow. It can also be seen from the results obtained that the presence of radiators strongly affects the propagation of particles of various sizes in a closed room. From the obtained results, it should be noted that in order to recommend the optimal social distance, it is necessary to take into account many factors, especially momentum, gravity, human body temperature, as well as the process of natural convection, which greatly affect the propagation of particles in a closed room. The conclusions drawn from the results of this work show that, given the environmental conditions, the social distance of 2 m may not be enough.

Organic palygorskite (OP)–supported Pd/Fe nanoparticles composite (OP-Pd/Fe) was prepared by stepwise reduction method. The removal capacity of 4,4′-dibrominated diphenyl ether (BDE15) by OP-Pd/Fe was compared with other various materials. For better understanding the possible mechanism, the synthesized and reacted OP-Pd/Fe materials were characterized by TEM, SEM, XRD, and XPS, respectively. The effects of major influencing parameters on the degradation of BDE15 were also studied. Benefit from the synergistic effect of the carrier and bimetallic nanoparticles, BDE15 could be completely debrominated into diphenyl ether (DE) under suitable conditions. A two-stage adsorption/debromination removal mechanism was proposed. The degradation of BDE15 with OP-Pd/Fe was mainly stepwise debromination reaction, and hydrogen transfer mode was assumed as the dominated debromination mechanism. The removal process fitted well to the pseudo first-order kinetic equation. The observed rate constants increased with increasing Pd loading and OP-Pd/Fe dosage while decreased with increasing initial BDE15 concentration, the tetrahydrofuran/water ratio, and the initial pH of the solution. The work provides a new approach for the treatment of PBDEs pollution.

This study used the bark of the forest species Campomanesia guazumifolia modified with H₂SO₄ to absorb the anti-inflammatory ketoprofen from aqueous solutions. FTIR spectra confirmed that the main bands remained after the chemical treatment, with the appearance of two new bands related to the elongation of the carbonyl group present in hemicellulose. Micrographs confirmed that the surface started to contain a new textural shape after acid activation, having new pores and cavities. The drug adsorption’s optimum conditions were obtained by response surface methodology (RSM). The adsorption was favored at acidic pH (2). The dosage of 1 g L⁻¹ was considered ideal, obtaining good indications of removal and capacity. The Elovich model very well represented the kinetic curves. The isotherm studies indicated that the increase in temperature negatively affected the adsorption of ketoprofen. A maximum adsorption capacity of 158.3 mg g⁻¹ was obtained at the lower temperature of 298 K. Langmuir was the best-fit isotherm. Thermodynamic parameters confirmed the exothermic nature of the system (ΔH⁰ = −8.78 kJ mol⁻¹). In treating a simulated effluent containing different drugs and salts, the removal values were 35, 50, and 80% at 15, 30, and 180 min, respectively. Therefore, the development of adsorbent from the bark of Campomanesia guazumifolia treated with H₂SO₄ represents a remarkable alternative for use in effluent treatment containing ketoprofen.

In the past few decades, extensive research has been carried out to develop efficient photocatalysts at the expense of exclusive material engineering approaches. Besides materials engineering, photocatalytic reaction parameters such as catalyst loading, irradiation intensity, reaction temperature, ultrasound, pH, and initial concentration also play a vital role in improving the overall performance of the photocatalytic process. In sharp contrast, the current study aims to showcase the role of core reaction parameters in optimizing the performance of the photocatalyst for efficient photocatalysis and ultrasound-assisted photocatalysis (sonophotocatalaysis). This work has two-fold objectives. Primarily, this study is intended to identify the core parameters involve in photocatalytic/sonophotocatalytic process from the comprehensive literature review followed by the experimental validation to optimize the same. Consequently, it has been established that under optimal reaction conditions, the synergistic effect of photocatalysis along with sonication holds better performance compared to the standalone process. The current study validates that the optimization of the different reaction parameters can boost the performance of the photocatalytic process significantly without employing exceptionally sophisticated and expensive approaches. Thus, the assessment of various factors associated with photocatalysis could be the vital for large-scale applications.

Based on the panel data of 30 Chinese provinces, the Cobb–Douglas production function and GML index were constructed to measure the degree of land price distortion and green development efficiency, respectively, in China, and the System Generalised Method of Moments model was employed to explore the relationship between land price distortion and green development efficiency, and a mediating effect model was further constructed to analyse the transmission mechanism. The results show that, first, land price in China is characterised by a negative distortion, but the degree of negative distortion tends to decrease after 2010. Second, land price distortion significantly inhibits the improvement of green development efficiency; this conclusion still holds after a series of robustness tests, and land price distortion significantly promotes the progress of green technology, while significantly inhibiting the improvement of green technology efficiency. Third, the results of the mediating effect show that the inhibiting effect of land price distortion on green development efficiency is mainly achieved through three channels: house price, industrial structure and infrastructure. Finally, policy recommendations for green sustainable development are put forward from the aspects of land supply structure adjustment and so on.

A heterogeneous photocatalysis was adopted to treat textile industry effluent using a combination of pumice-supported ZnO (PUM-ZnO) photocatalyst and solar irradiation. The visible light–responsive PUM-ZnO photocatalyst was prepared via the impregnation method and characterized using various spectroscopic techniques. The photocatalytic degradation process was modeled via response surface methodology (RSM), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS), while the optimization of the three independent parameters significant to the photocatalytic process was carried out by a genetic algorithm (GA) and RSM methods. The low standard error of prediction (SEP) of 0.56–1.75% and high coefficient of determination (R²) greater than 0.96 for the models developed indicated that they adequately predicted the photodegradation process with high accuracy in the order of ANFIS > ANN > RSM. The process optimization results from the developed models showed that GA performed better than RSM. The best optimal condition (3.29 g/L catalyst dosage, 45.85 min irradiation time, and 3.13 effluent pH) that resulted in maximum degradation efficiency of 99.46% was achieved by the ANFIS model coupled with GA (ANFIS-GA).