Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO2 energy source. Gasification of biomass for H2 and syngas production is an attractive process. The main target of this research is to improve the production of hydrogen and syngas from palm kernel shell (PKS) steam gasification through defining the optimal operating parameters' using a modern optimization algorithm. To predict the gaseous outputs, two PKS models were built using fuzzy logic based on the experimental data sets. A radial movement optimizer (RMO) was applied to determine the system's optimal operating parameters. During the optimization process, the decision variables were represented by four different operating parameters. These parameters include; temperature, particle size, CaO/biomass ratio and coal bottom ash (CBA) with their operating ranges of (650-750 °C), (0.5-1 mm), (0.5-2) and wt% (0.02-0.10), respectively. The individual and interactive effects of different combinations were investigated on the production of H2 and syngas yield. The optimized results were compared with experimental data and results obtained from Response Surface Methodology (RSM) reported in literature. The obtained optimal values of the operating parameters through RMO were found 722 °C, 0.92 mm, 1.72 and 0.06 wt% for the temperature, particle size, CaO/biomass ratio and coal bottom ash, respectively. The results showed that syngas production was significantly improved as it reached 65.44 vol% which was better than that obtained in earlier studies.
Catalytic steam gasification of palm kernel shell is investigated to optimize operating parameters for hydrogen and syngas production using TGA-MS setup. RSM is used for experimental design and evaluating the effect of temperature, particle size, CaO/biomass ratio, and coal bottom ash wt% on hydrogen and syngas. Hydrogen production appears highly sensitive to all factors, especially temperature and coal bottom ash wt%. In case of syngas, the order of parametric influence is: CaO/biomass>coal bottom ash wt%>temperature>particle size. The significant catalytic effect of coal bottom ash is due to the presence of Fe2O3, MgO, Al2O3, and CaO. A temperature of 692°C, coal bottom ash wt% of 0.07, CaO/biomass of 1.42, and particle size of 0.75mm are the optimum conditions for augmented yield of hydrogen and syngas. The production of hydrogen and syngas is 1.5% higher in the pilot scale gasifier as compared to TGA-MS setup.
This study investigated the effect of different Co3O4-based catalysts on the catalytic decomposition of nitrous oxide (N2O) and on nitric oxide (NO) conversion. The experiments were carried out using various reaction temperatures, alkaline solutions, pH, mixing conditions, aging times, space velocities, impregnation loads, and compounds. The results showed that Co3O4 catalysts prepared by precipitation methods have the highest catalytic activity and N2O conversion, even at low reaction temperatures, while the commercial nano and powder forms of Co3O4 (CS) have the lowest performance. The catalysts become inactive at temperatures below 400 °C, and their activity is strongly influenced by the mixing temperature. Samples without stirring during the aging process have higher catalytic activity than those with stirring, even at low reaction temperatures (200-300 °C). The catalytic activity of Co3O4 PM1 decreases with low W/F values and low reaction temperatures. Additionally, the catalyst's performance tends to increase with the reduction process. The study suggests that cobalt-oxide-based catalysts are effective in N2O catalytic decomposition and NO conversion. The findings may be useful in the design and optimization of catalytic systems for N2O and NO control. The results obtained provide important insights into the development of highly efficient, low-cost, and sustainable catalysts for environmental protection.
Emerging contaminants (ECs) in wastewater have recently attracted the attention of researchers as they pose significant risks to human health and wildlife. This paper presents the state-of-art technologies used to remove ECs from wastewater through a comprehensive review. It also highlights the challenges faced by existing EC removal technologies in wastewater treatment plants and provides future research directions. Many treatment technologies like biological, chemical, and physical approaches have been advanced for removing various ECs. However, currently, no individual technology can effectively remove ECs, whereas hybrid systems have often been found to be more efficient. A hybrid technique of ozonation accompanied by activated carbon was found significantly effective in removing some ECs, particularly pharmaceuticals and pesticides. Despite the lack of extensive research, nanotechnology may be a promising approach as nanomaterial incorporated technologies have shown potential in removing different contaminants from wastewater. Nevertheless, most existing technologies are highly energy and resource-intensive as well as costly to maintain and operate. Besides, most proposed advanced treatment technologies are yet to be evaluated for large-scale practicality. Complemented with techno-economic feasibility studies of the treatment techniques, comprehensive research and development are therefore necessary to achieve a full and effective removal of ECs by wastewater treatment plants.