An experiment on Fenton degradation of sugarcane vinasse was carried out to determine its effect on the wastewater characteristics. Vinasse, a by-product of distillation in the bioethanol industry, contains high organic matter, as the value of chemical oxygen demand (COD) is >100,000 mg/L and BOD₅ is 31,250 mg/L. The Fenton reaction is one of the advanced oxidation process (AOP) methods which has been widely applied for the treatment of wastewater containing organic pollutants and contaminants. This method utilizes hydroxyl radical (^•OH) produced from the catalyzing reaction between Fe²⁺ or Fe³⁺ and hydrogen peroxide. The effect of pH, the ratio of [H₂O₂] and [COD], and the ratio of [H₂O₂] to [Fe³⁺] were studied in this research to evaluate the Fenton reaction. Results from this experiment showed that treatment of vinasse using the Fenton reaction decreased the COD value to 48.10%, and its biodegradability enhanced almost two times at a pH value of 3.8, a ratio of [H₂O₂] to [COD] of 0.62, and a ratio of [H₂O₂] to [Fe³⁺] of 50 (g/g), which demonstrated that the Fenton treatment was effective to reduce organic matter of sugarcane vinasse. Three kinetic models (first order, second order, and Behnajad–Modirshahla–Ghanbery (BMG) kinetic model) were used to evaluate the degradation of the COD value. On the basis of the value of R² (coefficient of determination), we suggested that BMG represented the best kinetic model. This study finds that the Fenton treatment is able to mitigate the environmental impacts of sugarcane vinasse.

The distillery spent wash (DSW) from bioethanol industries has a very high chemical oxygen demand (COD). Hence, the goal of this study is to investigate the effect of currents (2.5, 3 and 3.5 A) and initial pHs (4.4, 5.0 and 7.0) on electrocoagulation (EC) to decrease the COD in DSW. The results showed that the EC at the current of 3.5 A enabled a higher COD removal efficiency (74.9%) than those at the currents of 2.5 (35.4%) and 3 A (60.9%). Furthermore, the initial pH of 7.0 resulted in a higher COD removal efficiency than the initial pHs of 4.4 and 5.0. The solution pH and temperature increased throughout the process. The working volume was not constant due to the reactions of water reduction, evaporation and flotation. Scum and sludge productions were also monitored during the process. Then, the measured data (COD, sludge and scum) were used in the modeling. The simple mechanistic models were successfully built and applied to simulate the data in mass units with two different routes of process. Route 1 assumed that the COD was converted to sludge and then the latter was converted to scum. Route 2 assumed that the COD was converted to the sludge and scum at the same time. When the EC was operated at the initial pH of 4.4, the COD removal process followed route 1, but that at the initial pHs of 5.0 and 7.0, the COD removal process followed route 2. The higher the current applied in the EC, the higher the kinetic constants of $k_a$ and $k_b$. Additionally, the higher the initial pH set, the higher the kinetic constants were. This showed that the formation rates of sludge and scum at the higher currents or initial pHs were faster than those at the lower values.

Currently, fossil fuels are still the primary fuel source and reducing agent in the steel industries. The utilization of fossil fuels is strongly associated with CO₂ emissions. Therefore, an alternative solution for green steel production is highly recommended, with the use of biomass as a source of fuel and a reducing agent. Biomass’s growth consumes carbon dioxide from the atmosphere, which may be stored for variable amounts of time (carbon dioxide removal, or CDR). The pellets used in this study were prepared from a mixture of low-grade iron ore and palm kernel shells (PKS). The reducing reactivity of the pellets was investigated by combining thermogravimetric analysis (TGA) and laboratory experiments. In the TGA, the heating changes stably from room temperature to 950 °C with 5–15 °C/min heating rate. The laboratory experiments’ temperature and heating rate variations were 600–900 °C and 10–20 °C/min, respectively. Additionally, the reduction mechanism was observed based on the X-ray diffraction analysis of the pellets and the composition of the reduced gas. The study results show that increasing the heating rate will enhance the reduction reactivity comprehensively and shorten the reduction time. The phase change of Fe₂O₃ → Fe₃O₄ → FeO → Fe increases sharply starting at 800 °C. The XRD intensities of Fe compounds at a heating rate of 20 °C/min are higher than at 10 °C/min. Analysis of the reduced gas exhibits that carbon gasification begins to enlarge at a temperature of 800 °C, thereby increasing the rate of iron ore reduction. The combination of several analyses carried out shows that the reduction reaction of the mixture iron ore-PKS pellets runs optimally at a heating rate of 20 °C/min. In this heating rate, the reduced gas contains much higher CO than at the heating rate of 10 °C/min at temperatures above 800 °C, which encourages a more significant reduction rate. In addition, the same reduction degree can be achieved in a shorter time and at a lower temperature for a heating rate of 20 °C/min compared to 10 °C/min.

Counteracting emissions of particulate matter (PM) is an increasingly important goal in sustainable biomass combustion. This work includes a novel approach to investigate the PM emissions, originating from residual biomass combustion, at different combustion conditions in a lab-scale grate-fired furnace and includes in situ PM measurements by using on-line sensors. The interior furnace design allows installation of baffles to suppress the emissions by controlling the residence time. Moreover, the two-thermocouple method is used to measure the true gas temperature, and an on-line spatially resolved PM measurement method is developed to study the evolution of the PM concentration throughout the furnace for different experimental conditions thereby allowing accurate in-situ measurement of the PM reactivity. Experimental results and computational fluid dynamics (CFD) analyses are utilized in the current work to develop a kinetic model for reduction of particulate matter emissions in biomass combustion. The discrete particle model (DPM) is utilized in CFD analysis to improve the understanding of the particle temperature and residence time distribution which are difficult to quantify experimentally. By combining the experimental measurements of real soot formed during biomass combustion and information from the CFD analyses, a predictive kinetic model for PM₁₀ reduction in biomass combustion is successfully developed.

The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. This paper presents a mathematical model for predicting phytochemical concentrations in the solvent and inside the pericarp of the grain at different positions during the extraction. The model is based on the mass transfer mechanism from inside the pericarp to its solid surface by diffusion, and then from the surface to a solvent during the extraction of bioactive compounds. It was numerically solved while using finite-difference approximation. The parameters considered were effective diffusivity inside the pericarp (D_ep), mass transfer coefficient from the pericarp surface to the solvent (k_c), and distribution coefficient (H). The model simulates the extraction performance, including the yield and bioactive compounds’ concentrations in the extract and inside the pericarp at various positions and times. A sensitivity analysis of the changes in each involved parameter provided sufficient information for increasing the performance of the model. A validation test that compared the results of the simulation with those of established analytical solutions showed that the model has high accuracy. Hence, the model can be applied in quantitative evaluations to improve productivity in the pharmaceutical industry.

Bacterial cellulose (BC) produced from coconut water, commonly known as nata de coco , is a biopolymer with enormous properties. Compared to plant cellulose, BC has better mechanical strength and a greater degree of polymerization. BC’s high purity and high porosity make it a suitable candidate for the embedding and dispersion template for silver nanoparticles (AgNPs). This study investigated a facile and scalable method of making BC from coconut water and impregnated them with AgNO ₃ solution to produce AgNPs templated BC. The resulting materials were characterized by Fourier transform infra-Red (FTIR), scanning electron microscope (SEM), energy dispersive X-ray (EDX), and X-ray diffraction (XRD). The thermal stability was also investigated by thermogravimetric analysis (TGA). The antibacterial activity of AgNPs templated BC was challenged in cultures of gram-positive bacteria Staphylococcus aureus and gram-negative bacteria Escherichia coli and showed an inhibition zone of growth in agar media. This study proves that the resulting AgNPs templated BC sheets are potential materials for antibacterial and industrial application that are low cost and easy to produce.