High levels of heavy metals in soil pose considerable threats to the ecosystem. The in situ remediation technology is obtaining increasing global concerns as a sustainable remediation strategy. In this study, the hydroxyapatite/calcium silicate hydrate (HAP/CSH) was recovered from waste water to evaluate the effects on heavy metal immobilization by coupling with biochar. Five mixtures of HAP/CSH and biochar with different weight ratios (10:0, 0:10, 1:9, 2:8, 4:6 w/w) were prepared to remediate two heavy metal–contaminated soils planted with water spinach (Ipomoea aquatica Forsk.). The mixture of HAP/CSH and biochar in the ratio of 4:6 shows the best immobilization effect assessed by toxicity characteristic extraction procedure (TCLP) and BCR sequence extraction procedure. After remediation, the immobilization efficiency decreased 83%, and content of heavy metals in plants decreased 72.8%. The conversion efficiency of heavy metal residual fraction was 3.95 times higher than that of the control group. At the same time, soil pH, water-soluble organic carbon (WSOC), and soil microbial biomass (SMB) all showed an increasing trend, indicating the improvement of soil conditions. The combined application of HAP/C-S-H and biochar changed soil bacterial community structure, leading to an increase in soil bacterial diversity. The results of redundancy analysis (RDA) suggested that pH and the concentration of heavy metals were the main factors affecting microbial community. Therefore, the mixture of HAP/C-S-H and biochar can be considered as an effective, feasible, and environmentally friendly amendment for the remediation of Cd-contaminated soil and multi-metal–contaminated soil.

The improvement of green innovation efficiency (GIE) in the Yangtze river economic belt (YREB) is beneficial to China’s green transformation and upgrading because of its economic and ecological position. Therefore, based on the slacks-based measure of super-efficiency (Super-SBM) model, the paper studies the GIE and its spatial-temporal variation characteristics in the YREB during the period 2003–2015, and analyzes the spatial correlation and spatial-temporal convergence of GIE with the exploratory spatial data analysis (ESDA) method and convergence analysis method. The results show that the GIE in the YREB shows an “U-shaped” change pattern in time and an extremely unbalanced development pattern in space. The areas with high GIE contribute to the improvement of overall GIE, whereas they do not exert a radiation and driving effect on areas with low GIE. Accordingly, because of the short board effect, the convergent speed of the GIE is decreasing. To be specific, the GIE keeps converging in the upper and lower reaches, except for the year 2010 when GIE in the middle reaches changed from being convergent to being non-convergent. Even though environmental policy exerts great impacts on the improvement of GIE, the lack of collaborative environmental governance leads to the non-convergent and unbalanced development of the GIE. Therefore, green coordinated development of the YREB is necessary.

The water quality of Lake Mariut has been deteriorated for about 5 decades due to continuous discharge of agricultural, municipal, and industrial wastes from Alexandria City and the adjacent land. During the past two decades, some steps were taken for rehabilitation of the lake through primary treatment of the discharged wastes and insulation of the polluted wastewater of QD from the water body in the main basin of the lake. Several parameters of water quality at the surface and near bottom were measured at twelve locations during winter (January) and summer (August) of 2013 and 2014. The present study revealed that the lake water appeared to be well aerated but still containing high concentrations of N and P and suffering hyper-eutrophic conditions. The water quality index (WQI) reflected medium condition in the lake and bad condition in the diverted drains. The P-budget calculation displayed that TP input into the LMMB from UDᵤₛ and resuspension process from sediments exceeded the output by out flowing at UDdₛ and settling.

Amino-functionalized ionic liquid biphasic solvents present excellent absorption capacity, regeneration ability, and energy consumption savings, which make them a possible candidate for CO₂ capture. The kinetics and regeneration heat duty of the [TETAH][Lys]-ethanol-water system capturing CO₂ were investigated in this work. The mass transfer and kinetic parameters, including the overall reaction rate constant (kₒᵥ), the reaction rate constant (k₂), and the enhancement factor (E), were assessed at diverse concentrations and temperatures. At 303.15 K, the k₂ of CO₂ capture into the [TETAH][Lys]-ethanol-water solution was 58,907.30 m³ kmol⁻¹ s⁻¹. The Arrhenius equation was introduced to evaluate the relations between k₂ and the reaction temperature, which can be presented as [Formula: see text] The regeneration heat duty of the novel biphasic solvent was 35.5 and 62.39% lower than those of [TETAH][Lys]-water and the benchmark monoethanolamine solution, respectively. An efficient absorption performance and lower energy requirement indicate the great potential for this application.

Particulate matter (PM) is defined as a mixture of solid and/or liquid particles that remain separately dispersed in air. PM is not a pollutant by itself but a complex and dynamic combination of compound particles with biological and chemical origins. However, fine PM (PM₂.₅) seems to be incriminated in the respiratory system and poses a severe threat to human health. Several reviews focused on chemistry segments because they mainly contribute to fine PM concentration. Biological elements in PM₂.₅ should also be considered because they cause multiple allergies and respiratory illnesses. This review has selected articles by following predefined criteria and demonstrated that the biological and chemical parts of fine particles play a significant role in PM₂.₅ concentration. In addition, justification on the origin or sources of biological and chemical compositions and their effects on health become a concern in this review. Lastly, this review can provide knowledge that can be a useful tool for researchers, designers, engineers and policymakers to consider for further action.

In this study, a practical and excellent method was used to determine the famoxadone and cymoxanil via high-performance liquid chromatography equipped utilizing ultraviolet detector lamp (HPLC-UV) for investigating the dissipation behavior and residue distribution of famoxadone and cymoxanil in cucumber and soil ecosystem. The limit of quantification (LOQS) of famoxadone and cymoxanil in cucumber were 0.50, 1.00, 2.00 and 0.05, 0.50, 1.00 mg kg⁻¹ in soil, respectively. The limit of detection (LODS) of both famoxadone and cymoxanil were 8.0 ng. The average recoveries (n = 5) of the fungicide ranged from 84.10 to 108.02% with the relative standard deviations (RSDs) typically < 9.23%. The fungicide was applied to cucumber and soil at the range of doses (275.6–413.4 g a.i.ha⁻¹) three or four times. The half-lives of famoxadone and cymoxanil in cucumber and soil were 1.34–16.12 days, which followed the first-order chemical reaction kinetics equation Cₜ = C₀ × e⁻ᵏᵗ. The residues of famoxadone and cymoxanil in cucumber at the pre-harvest interval (PHI, 3 days) were below 8.0 × 10⁻⁸ g and 8.0 × 10⁻⁹ g, respectively. Overall, this study evaluated the food safety and the environmental fate of famoxadone and cymoxanil in cucumber and soil ecosystem. In addition, this study would promote the series of work on the pesticide exposure assessment of these fungicides as well.

Simulation of groundwater quality is important for managing water resources and mitigating water shortages, especially in arid and semiarid areas. Geostatistical models have been used for spatial prediction and interpolation of groundwater parameters. Recently, hybrid intelligent models have been employed for the simulation of dynamic systems. In this study, hybrid intelligent models, based on a neuro-fuzzy system integrated with fuzzy c-means data clustering (FCM) and grid partition (GP) models as well as artificial neural networks integrated with particle swarm optimization algorithm, were used to predict the spatial distribution of chlorine (Cl), electrical conductivity (EC), and sodium absorption ratio (SAR) parameters of groundwater. Results of the hybrid models were compared with geostatistical methods, including kriging, inverse distance weighting (IDW), and radial basis function (RBF). The latitude and longitude values of observation wells and qualitative parameters in three states of maximum, average, and minimum were introduced as input and output to the models, respectively. To evaluate the models, the root mean squared error (RMSE), the mean absolute error (MAE), and CC statistical criteria were used. Results showed that in the hybrid models, NF-GP with the lowest RMSE and MAE and highest CC was the most suitable model for the prediction of water quality parameters. The RMSE, MAE, and CC values were 107.175 (mg/L), 79.804 (mg/L), and 0.924 in the average state for Cl; were 518.544 (μmho/cm), 444.152 (μmho/cm), and 0.882 for electrical conductivity; and were 1.596, 1.350, and 0.582 for sodium absorption ratio, respectively. Among the geostatistical models, the kriging was found more accurate. Using the coordinates of wells will eventually allow the NF-GP to be used for more sampling and replace the visual techniques that require more time, cost, and facilities.

Landfilling is a critical method in managing massive generated C&D waste, and the appropriate selection of C&D waste landfill sites can reduce the impacts of landfilling. This study proposes an approach combined F-AHP and GIS to select suitable C&D waste landfills. The proposed model considers multiple factors from environmental, social and economic aspects. A case study of Shenzhen, China, is undertaken to showcase the implementation of the proposed model. It is found that about 25 million m² of land has the potential to be used for C&D waste landfills in the study case, but the actual usable land is limited as some lands are too small for a landfill site. The study contributes to the waste management discipline as it provides an improved framework for selecting a landfill site. Besides, the landfill site selection procedure and results have practical implications for urban planning.

The laser pretreatment of seed is drawing pronounced attention from the scientific community for its positive impact in boosting germination, seedling , and growth of plants. In this study, the laser pretreatment of Adansonia digitata (A. digitata) seeds was evaluated. Eight laser treatments were conducted at different powers, 10, 20, 40, and 80 mW, with the two-time interval for each power at 2 and 4 min. The outcomes indicated that the most efficient irradiation was 10 mW/2 min which induces the highest germination rate and polyphenolic contents for seeds. Based on these results, the animal experimental design was processed to assess the hepatoprotective activity of A. digitata extracts obtained through the optimum laser preillumination to enhance the resistance of liver damage in mice. The total phenol and flavonoid contents and the antioxidant properties of the methanolic extracts were estimated in vitro. The CCl4 was used to induce hepatotoxicity in mice. The animals were divided into five groups. The sera of the treated animals were used for the determination of transaminases, and the liver homogenates were used for the determination of antioxidant status, and further liver tissues were subjected to verify the anti-apoptotic effect of A. digitata methanolic extract. The in vivo results showed that the methanolic extract exposed to laser treatment at 10 mW/2 min provided better hepatoprotective capacity than the other treatments. Administration of A. digitata extract not only offered a significant decrease in liver enzyme activity but also markedly improved the antioxidant status and reduced the apoptotic progression induced by CCl4 toxicity in liver tissue.

Large amounts of fracturing flowback and wastewater with complex compositions are produced during hydraulic fracturing. Characterization of hydraulic fracturing flowback and produced water (HF-FPW) is an important initial step in efforts to determine a suitable treatment method for this type of wastewater. In the present study, fracturing flowback and produced water samples were obtained from well CN-F and well CN-E in the prophase and anaphase stages of the Changning shale gas mining area. Chemical characterization of inorganic and organic substances was then conducted. Metal contents were determined by inductively coupled plasma optical emission spectroscopy (ICP-OES), and all inorganic anions involved were determined by ion chromatography. The organic pollutant components were analyzed in detail by combining Fourier transform infrared spectrometer (FTIR) and gas chromatography-mass spectrometer (GC-MS). Results showed that samples contained salt (TDS = 30,000–50,000 mg/L), metals (e.g., 650 ± 50 mg/L calcium), and total organic carbon (TOC = 32–178 mg/L). The organic substances detected in all samples could be divided into six categories, alkanes, aromatics, halogenated hydrocarbons, alcohols, esters, and ketones. C₆–C₂₁ straight-chain alkanes and C₇–C₁₃ naphthenes had the highest amount of organic matter, reaching more than 48%. The organic matter contained fracturing fluid additives, such as surfactants (e.g., ethylene glycol), and nitrotrichloromethane, which is a chlorinated product of some additives. These results provide information on the chemical composition of HF-FPW in Sichuan, China, as well as a basis for subsequent processing.