Synthesis and optimization of spherical nZVI (20–60 nm) immobilized in bio-apatite-based material for efficient removal of phosphate: Box-Behnken design in a fixed-bed column

In the present study, bio-apatite/nZVI composite was synthesized through Fe(III) reduction with sodium borohydride and was fully characterized by FTIR, XRD, SEM–EDX, TEM, BET, BJH, and pH_PZC. Column experiments were carried out for the removal of phosphate as a function of four operational parameters including initial phosphate concentration (100–200 mg L^?1), initial solution pH (2–9), bed height (2–6 cm), and influent flow rate (2.5–7.5 mL min^?1) using a response surface methodology (RSM) coupled with Box-Behnken design (BBD). 2D contour and 3D surface plots were employed to analyze the interactive effects of the four operating parameters on the column performance (e.g., uptake capacity and saturation time). According to ANOVA analysis, the influent flow rate and bed height are the most important factor on phosphate uptake capacity and saturation time, respectively. A quadratic polynomial model was excellently fitted to experimental data with a high coefficient of determination (>?0.96). The RSM-BBD model predicted maximum phosphate adsorption capacity of 85.71 mg g^?1 with the desirability of 0.995 under the optimal conditions of 135.35 mg L^?1, 2, 2 cm, and 7.5 mL min^?1 for initial phosphate concentration, initial solution pH, bed height, and influent flow rate, respectively. The XRD analysis demonstrated that the reaction product between bio-apatite/nZVI composite and phosphate anions was Fe₃ (PO₄)₂. 8H₂O (vivianite). The suggested adsorbent can be effectively employed up to five fixed-bed adsorption–desorption cycles and was also implemented to adsorb phosphate from real samples.

     

Optimization of metal bio-acid leaching from mobile phone printed circuit boards using natural organic acids and H2O2

Journal of Material Cycles and Waste Management - With increased popularity and technological innovation, more and more electric and electronic equipment wastes (e-wastes) are being generated....     

Design and optimization of new La1−xCexNi1−yFeyO3 (x,y = 0–0.4) nano catalysts in dry reforming of methane

The paper reports the production of syngas from dry reforming of methane (DRM) over La_1?xCe_xNi_1?yFe_yO₃ (x, y = 0–0.4) perovskites. A series of La_1?xCe_xNi_1?yFe_yO₃ were designed by central composite design (CCD) and synthesized by a sol–gel auto combustion method. Artificial neural network (ANN) approach was used to determine the relationship between preparation and operational parameters on the performance of the catalysts in the DRM process. Nickel mole fraction, lanthanum mole fraction, calcination temperature, and reaction temperature were considered as input variables, and conversion of methane was considered as the output variable. An ANN model with nine neurons in the hidden layer was the suitable in predicting conversion of methane. The genetic algorithm (GA) was subsequently used to determine the optimal preparation condition for enhancing the conversion of methane. La_0.6Ce_0.4Ni_0.99Fe_0.01O₃ catalyst, calcined at 756°C was obtained to be the most active catalyst owing to the optimal composition of nickel and lanthanum in the catalyst formulation.     

Comparative phytotoxicity of ZnO nanoparticles,ZnO microparticles,and Zn2+ on rapeseed (Brassica napus L.): investigating a wide range of concentrations

The effects of ZnO nanoparticles (NPs), ZnO microparticles (MPs), and zinc ions (Zn²⁺) on some growth parameters of rapeseed (Brassica napus) seedlings have been studied. The growth inhibition by ZnO NPs was not stronger than that by ZnO MPs while treatment with Zn²⁺ inhibition was clearly stronger.     

Response curves of seventeen woody species to soil factors along a riparian forest in northern Iran

The aim of this study was to determine type of response curves for seventeen woody species (10 tree and 7 shrub species) to soil factors in an intact riparian forest in Safaroud River in northern Iran using HOF function. Data were collected along transects established perpendicular to the water flow on both sides of the river. Results indicated different responses for different woody species. The most common were symmetricunimodal response curves and curves showing an increase in occurrence probability after a certain value in form of a plateau. Bimodal curves were four times more frequent in riverside than forest interior area. It seems that river flow disturbances through frequent floods effect on species tolerance and optimum in riversides.     

Starting improvement of micro-wind turbines operating in low wind speed regions

The study deals with the design and optimization of external and internal geometry of micro-wind turbines blades. A specified objective function which consists of the power coefficient and the starting time was defined and the genetic algorithm optimization technique in conjunction with the blade-element momentum theory was adopted to find the geometry of the blades including the distributions of the chord, the twist angle and also the shell thickness. Moreover, the allowable stress of the blades was considered as a constraint to the objective function. Results show that a reasonable compromise is achievable such that the starting time of the blades reduces noticeably in return for a small drop in the power coefficient. The significant improvement of the hollow blades over the solid ones indicates that the power coefficient and the starting performance could be improved through the appropriate distributions of the considered decision variables, i.e. the chord, the twist angle and also the shell thickness.     

Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data

Global warming and climate change have been identified as the most important challenges of the 21st century. Greenhouse Gases Observation Satellite (GOSAT) measures the concentrations of carbon dioxide (CO ₂) and methane (CH ₄) in the atmosphere column from the earth's surface to the upper atmosphere. In this research, GOSAT Thermal And Near Infrared Sensor for Carbon Observation – Fourier Transform Spectrometer (TANSO‐FTS) level 2 data and meteorological parameters were used in the assessment of changes in CO ₂ concentration (XCO ₂) from 2009 to 2015. We investigated the relationship between XCO ₂ and meteorological parameters (temperature and precipitation) obtained from weather stations and the Normalized Difference Vegetation Index (NDVI) in the year 2013 in Iran. The results reveal a steady increase in the mean atmospheric CO ₂ concentration, from 384.89 to 400.39 ppm. It was observed that the XCO ₂ varied significantly depending on the month, with the highest concentration of CO ₂ in April/May and the lowest concentration in August/September. The correlation between XCO ₂ and average monthly air temperature is negative, which means that a reduction in XCO ₂ with an increase in temperature is dependent on photosynthetic activities in the growing seasons. The highest and lowest correlation coefficient between the NDVI and XCO ₂ was obtained in the spring and in the fall, respectively. These findings are useful for recognizing factors that affect CO ₂ concentration in different seasons in arid and semi‐arid regions, and as an initial step toward sustainable management.     

Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

Relationships between certain individual characteristics and occupational accidents

Background. Work accidents and injuries are an occupational health and safety problem. Methods. This cross-sectional study was conducted for 404 frontline workers who were randomly selected from the Arya Sasol Petrochemical Company in Bushehr, Iran, during 2016. A statistical analysis was performed using the χ² test and the logistic regression model with SPSS version 18. Results. The overall occupational accident rate among the participants was found to be 9.2%. Statistically significant differences were observed for body mass index, education, job experience, smoking habit, consumption of sedative pills and presence of sleep disorders. Three factors had significant adjusted odds ratios (ORs): body mass index (OR 2.41, 95% confidence interval [CI] [1.16, 5.04]), education (OR 0.25, 95% CI [0.07, 0.85]) and job experience (OR 0.29, 95% CI [0.15, 0.57]). Conclusions. Preventive programs should be implemented for industrial workers, especially young workers, workers who smoke, overweight workers and workers with psychosomatic disease.