Search

Food waste (FW) is high in nutrients and has gained global attention as an ideal substrate for bioenergy recovery through anaerobic digestion (AD). Ambient digesters have been widely used because of their ease of installation, low cost, and low energy input. However, to improve biogas production sustainably, there is a need to consider reactor heating using renewable energy such as solar. This study sought to apply psychrophilic and mesophilic biodigester temperatures for FW treatment. For ambient digestion, a complete-mix flexible biodigester, named STH-1000A, covered in a greenhouse structure was operated between 24 and 32 °C. A prototype complete-mix tank biodigester, named VUT-1000C, was designed and operated at mesophilic conditions of 37 °C through solar geyser heating. VUT-1000C produced 1200 L of biogas per day while STH-1000A 150 L/day. VUT-1000C and STH-1000A generated up to 1.8 and 0.4 kWh of electricity, respectively. The power balance showed that VUT-1000C used 68% of its power production and STH-1000A consumed 398%. Digester heating using solar geyser is a novel and promising technique for achieving mesophilic condition leading to improved biogas production. [ABSTRACT FROM AUTHOR]

The mechanical properties of Gelatin-cellulose nanocrystals hydrogel membrane were investigated for the removal of heavy metal ions from wastewater. The membrane was characterized using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) analysis. Neural Network (NN) model was developed to predict the mechanical properties such as Young’s modulus, tensile strength, and elongation. The NN predicted results are very close to the experimental results with R2 = 0.99315. The predicted values were found to be in excellent agreement with the experimental data and the current model has a good learning precision and generalization. The results revealed that the developed model is very accurate.

A nanocomposite photocatalyst consisting of titanium dioxide (TiO2) supported on multiwalled carbon nanotubes (MWCNTs) has been successfully prepared and used for the treatment of wastewater contaminated with tetracycline (TC), a recalcitrant antibiotic pollutant. The TiO2/MCNT composites were prepared by a simple evaporation-drying method. The properties of MWCNT/TiO2 were optimized by dispersing different amounts of TiO2 onto MWCNT. The structural and optical characteristics of the nano-engineered photocatalyst composite were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) techniques. Photocatalytic degradation of TC was conducted in a quartz glass reactor. Different kinetic models were used to demonstrate the governing mechanisms. The findings revealed that the TiO2/MWCNT composite had enhanced photocatalytic activity (95% TC removal) compared to TiO2 (86% removal). The photocatalyst nanocomposite exhibited overall pseudo-second-order reaction kinetics and favored the Langmuir adsorption isotherm. Although up to 95% degradation of TC was achieved, only 75% of it was mineralized as a result of the formation of stable refractory intermediates. [ABSTRACT FROM AUTHOR]

In this study, chitosan was modified with cellulose and gelatin for the removal of Cu2+, Fe2+, and Pb2+ from oily wastewater. Chitosan was characterized using Fourier‐transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X‐ray diffraction (XRD). Carbon (77.54%), hydrogen (10.30%), oxygen (8.89%), nitrogen (2.74%), and sulphur (0.53%) were found in the organic constitution of the oil utilized, according to elemental analysis. Despite the presence of other metal ions in the used oil and effluent, this study focused solely on Cu2+, Fe2+, and Pb2+. Studies on the removal of Cu2+, Fe2+, and Pb2+ from oily wastewater were conducted, and multiple effect factors such as temperature and pH, time and pH, solvent and pH, temperature and time, temperature and solvent, and time and solvent were evaluated. An adsorption study was performed to remove the heavy metals. The results revealed that the highest percentage removal of Cu2+ was 96.62 (pH = 7.52 and conductivity = −12 mV), of Fe2+ was 97.95 (pH = 6.30 and conductivity = +68 mV), and of Pb2+ was 98.86 (pH = 10.58 and conductivity = −170 mV). To analyze the impacts of experimental factors, experiments were developed using central composite design (CCD) based on response surface methodology (RSM). [ABSTRACT FROM AUTHOR]

AbstractThis study integrated anaerobic digestion (AD) and heterogenous photocatalysis, an advanced oxidation process (AOP), to treat tetracycline (TC), an emerging recalcitrant contaminant. The integrated system comprising an annular photocatalytic reactor and bioreactor was fed with simulated wastewater containing TC. The photocatalytic treatment was aided by a nano-engineered composite catalyst containing titanium dioxide (TiO2) and multi-wall carbon nanotubes (MWCNT). Heterogeneous photocatalysis as a single approach resulted in 90% TC degradation, 39% chemical oxygen demand (COD) reduction, 28% total organic carbon (TOC) removal, and minimal biochemical oxygen demand (BOD5) reduction. AD on its own removed 56% and 52%, respectively of the COD and BOD5. When applied as a pretreatment, heterogenous photocatalysis improved the biodegradability (BOD5/COD ratio) from 0.12 to 0.42 resulting in improved COD, BOD5, and TOC removals of 71%, 70%, and 76%, respectively in the ensuing AD process. Kinetic studies revealed that the ratio of the photocatalytic reactor unit to the anaerobic reactor unit for an integrated system with constant feed flow should be 12:1. Photodegradation as the only form of treatment used more energy than the integrated approach. The bioenergy generated by AD could supply the energy needs of the sequential system resulting in 20% energy savings and a carbon dioxide emission reduction (CER) of 22.74 kg for every cubic meter of treated wastewater. An integrated AOP-AD approach is thus promising for treating recalcitrant organic contaminants of emerging concern. [ABSTRACT FROM AUTHOR]

This study describes the selective removal of cobalt (II) and nickel (II) from hydrometallurgical effluent using modified clinoptilolite. X‐ray fluorescence (XRF), x‐ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) analysis were used to characterize the natural and modified clinoptilolites with dialkylphosphinic acid. In a batch experiment, the influence of different variables such as initial concentration, pH, particle size, clinoptilolites dosage, temperature, and contact time was evaluated. Higher removal efficiency was obtained at initial concentration of 600 mg/L, pH 6, particles size of 1000‐1400 μm, dosage of 10 g/100 mL, a temperature of 25°C, and contact time of 300 minutes. The experimental data fit satisfactorily to the pseudo‐second order kinetic and to the Langmuir isotherm model. Thermodynamic parameters like Gibb's free energy (ΔGo), enthalpy (ΔHo), and entropy (ΔSo) were also evaluated. The results revealed that modified clinoptilolite with dialkylphosphinic acid could be successfully employed for the selective removal of cobalt (II) and nickel (II) from hydrometallurgical effluent. [ABSTRACT FROM AUTHOR]

Natural clinoptilolite was modified with dialkylphosphinic and succinic acid for the selective removal of Co2+, Cu2+, Zn2+, Ni2+ and Fe2+. The natural and modified materials were characterized using x-ray diffraction (XRD), xray fluorescence (XRF), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) analysis. Batch experiment was conducted as a function of contact time, pH, clinoptilolite mass and temperature. The higher removal efficiency was obtained under the following optimal conditions: contact time 240 min, pH 6, the mass of modified clinoptilolite 6 g and temperature 45oC. The experimental data fit satisfactory to Langmuir and Dubinin-Radushkevich (D-R) isotherm models as well as pseudo-second order kinetic. Thermodynamic parameters such as Gibb's free energy change (ΔG°), enthalpy change (ΔH°), and entropy change (ΔS°) were calculated. The ion exchange process was found to be spontaneous, endothermic and randomness. The selectivity of clinoptilolite towards heavy metals from industrial wastewater was in the sequence: Co2+ > Cu2+ > Zn2+ > Ni2+ > Fe2+. The effect of the acid concentration in elution was also investigated. [ABSTRACT FROM AUTHOR]

Natural clinoptilolite was modified with dialkylphosphinic and succinic acid for the selective removal of Co2+, Cu2+, Zn2+, Ni2+ and Fe2+. The natural and modified materials were characterized using x-ray diffraction (XRD), xray fluorescence (XRF), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) analysis. Batch experiment was conducted as a function of contact time, pH, clinoptilolite mass and temperature. The higher removal efficiency was obtained under the following optimal conditions: contact time 240 min, pH 6, the mass of modified clinoptilolite 6 g and temperature 45oC. The experimental data fit satisfactory to Langmuir and Dubinin-Radushkevich (D-R) isotherm models as well as pseudo-second order kinetic. Thermodynamic parameters such as Gibb’s free energy change (ΔG°), enthalpy change (ΔH°), and entropy change (ΔS°) were calculated. The ion exchange process was found to be spontaneous, endothermic and randomness. The selectivity of clinoptilolite towards heavy metals from industrial wastewater was in the sequence: Co2+ > Cu2+ > Zn2+ > Ni2+ > Fe2+. The effect of the acid concentration in elution was also investigated. [ABSTRACT FROM AUTHOR]

In this study, the ozonolysis of real anaerobically digested distillery wastewater (DWW) was carried out. The effect of operating parameters, such as pH, initial concentration, and ozone dosage, on the efficiency of ozone utilization, color removal, and sludge solubilization was studied. The highest ozone utilization of 99% was observed at the highest initial concentration (COD of 3000 mg/L) and lowest ozone flowrate (22.5 mg O3/L/min), but with a very low color reduction of 20%, after 60 minutes of ozonolysis. To achieve a higher color reduction >80% and at ozone utilization >95%, the DWW had to be diluted twice (COD 1500 mg/L), and the flowrate doubled to 45 mg O3/L/min. The reduction in color signified the oxidation of the color causing biorecalcitrant aromatic melanoidin compounds. This was confirmed by the 47% reduction in ultraviolet absorbance at 254 nm indicating the breakdown of the complex aromatic compounds into low molecular weight organics. Moreover, increases in average oxidation state from −0.6 to −0.2 suggested a decline in aromaticity and formation of easily biodegradable aliphatic compounds. The ozonolysis process was found to follow the first-order reaction kinetic model with the highest rate constant of 0.0326 min−1 obtained. A reduction in suspended COD by 88% indicated solubilization of the sludge contained in the effluent. [ABSTRACT FROM AUTHOR]

Siphonochilus aethiopicusis an indigenous South African plant also known as African ginger. It has often been used for its medicinal properties to treat various ailments such as flu, colds, and so forth. The research aim of this study was to optimize the process parameters of steam distillation for the extraction of oil from African ginger rhizomes. This technology is the oldest and well known for extracting essential oils due to its economic viability and the higher final oil purity. The effects of operating parameters such as extraction duration, moisture content, particle size, and temperatures between 80°C and 100°C were studied for maximum oil recovery. The oil recovery of 0.61% (w/w) was achieved after 270 min of extraction time, using 6.37% (dry) moisture content of particle size 2.4 mm–4 mm at a maximum temperature of 100°C. Fick’s first law was used to mathematically model the experimental data of this study. [ABSTRACT FROM PUBLISHER]

Copyright of Canadian Journal of Chemical Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Acid Mine Drainage (AMD) is the formation and movement of highly acid water rich in heavy metals. Prediction of heavy metals in the AMD is important in developing any appropriate remediation strategy. This paper attempts to predict heavy metals in the AMD (Zn, Fe, Mn, Si and Ni) from South African mines using Neural Network (NN) techniques. The Backpropagation (BP) neural network model has three layers with the input layer (pH, SO 4 2- and total dissolved solids (TDS)) and output layer (Cu, Fe, Mn and Zn). After BP training, the NN techniques were able to predict heavy metals in AMD with a tangent sigmoid transfer function (tansig) at hidden layer with five neurons and linear transfer function (purelin) at output layer. The Levenberg-Marquardt back-propagation (trainlm) algorithm was found as the best of 10 BP algorithms with mean-squared error (MSE) value of 0.00041 and coefficient of determination (R) for all (training, validation and test) value of 0.99984. The results indicate that NN can be considered as an easy and cost-effective technique to predict heavy metals in the AMD.