Toluene is one of the pollutants that are dangerous to the environment and human health and has been sorted into priority pollutants; hence the control of its emission is necessary. Due to severe problems caused by toluene, different techniques for the abatement of toluene have been developed.Catalytic oxidation is one of the promising methods and effective technologies for toluene degradation as it oxidizes it to CO2 and does not deliver other pollutants to the environment. This paper highlights the recent progressive advancement of the catalysts for toluene oxidation. Five categories of catalysts, including noble metal catalysts, transition metal catalysts, perovskite catalysts, metal-organic framework (MOFs)-based catalysts, and spinel catalysts reported in the past half a decade (2015-2020), are reviewed. Various factors that influence their catalytic activities, such as morphology and structure, preparation methods, specific surface area, relative humidity, and coke formation, are discussed. Furthermore, the reaction mechanisms and kinetics for catalytic oxidation of toluene are also discussed.

A novel synthetic strategy based on a high pressure gas–solid reaction using urea as an additive to produce value-added CaCO3 material is reported. Results showed that at about 150 °C and 12 MPa the reaction attained complete carbonation with predominant spherical vaterite crystals via a self-sustained reaction. The influences of working conditions including pressure, temperature, Ca­(OH)2/urea mass ratio, and reaction time on the mineralization process were studied. The as-prepared CaCO3 powder exhibited vaterite content as high as 94.2% and a surface area up to 32.9 m2/g. The mechanism study showed that the high-pressure CO2 acted as an inhibitor for urea decomposition at high temperature besides as a reactant; the urea entrapped Ca­(OH)2 via its melt to stabilize vaterite formation by an amine functional group and initiated the carbonation process via tiny water triggered by its slight decomposition. The separation to obtain the fine product was simple and allowed high urea recovery (for example, 93.6%). The method has merits for both the high CO2 utilization and production of value-added CaCO3 without discharging inorganic salts; thus, it would be an environmentally friendly and potential route for industrial application.

We propose a novel and cyclic synthetic approach for controlling crystal polymorphs of CaCO3 by using green CO2-responsive switchable solvents which acted as both the CO2 capturer for the carbonate source and the polymorphisms director. Five solvents were employed, and various reaction conditions such as calcium resources, calcium concentration, reaction temperature, and reaction time were investigated. Results show that this developed framework permits producing any crystalline CaCO3 phases including metastable vaterite and aragonite in pure phases by selecting a suitable solvent and adjustment of the reaction conditions. Furtherly, the mechanism study demonstrates that the solvents attach on the surface of the primary nanoparticles to selectively control and direct the growth of any specific polymorph phases. Eventually, the nuclei are self-assembled into an oriented geometry, allowing the growth and stability of specific crystals; as such, spherical vaterite, rods, and shuttle-like aragonite crystals can be obtained. This new configuration would be an appropriate and an efficient method to apply to large-scale production, therefore, a promising process attributed to complete solvent recovery and regeneration of the initial reactants, thus being an environmentally risk-free route.

The current hydrogen generation technologies, especially biomass gasification using fluidized bed reactors (FBRs), were rigorously reviewed. There are involute operational parameters in a fluidized bed gasifier that determine the anticipated outcomes for hydrogen production purposes. However, limited reviews are present that link these parametric conditions with the corresponding performances based on experimental data collection. Using the constructed artificial neural networks (ANNs) as the supervised machine learning algorithm for data training, the operational parameters from 52 literature reports were utilized to perform both the qualitative and quantitative assessments of the performance, such as the hydrogen yield (HY), hydrogen content (HC) and carbon conversion efficiency (CCE). Seven types of operational parameters, including the steam-to-biomass ratio (SBR), equivalent ratio (ER), temperature, particle size of the feedstock, residence time, lower heating value (LHV) and carbon content (CC), were closely investigated. Six binary parameters have been identified to be statistically significant to the performance parameters (hydrogen yield (HY)), hydrogen content (HC) and carbon conversion efficiency (CCE)) by analysis of variance (ANOVA). The optimal operational conditions derived from the machine leaning were recommended according to the needs of the outcomes. This review may provide helpful insights for researchers to comprehensively consider the operational conditions in order to achieve high hydrogen production using fluidized bed reactors during biomass gasification.