# Special Issue \"Thermochemical Conversion Processes for Solid Fuels and Renewable Energies\"
## 2 Special Issue Findings  
In the following, a summary of the accepted papers with their most relevant contributions is illustrated. * The first paper, accepted in this Special Issue, authored by [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] from the University of L'Aquila, Italy. In this study, the authors investigated the CO\({}_{2}\) sorption capacity of hydrochar for the upgrading of biogas to bio-methane [17]. The hydrochar was prepared based on a waste product (silver fir sawdust) available in Central Europe and Abies species available worldwide. Experiments were performed using a 316-stainless steel batch reactor at different temperatures and residence times. The hydrochar, obtained hydrothermal carbonization, was activated with potassium hydroxide impregnation and subsequent thermal treatment. The morphology and porosity of the hydrochar, characterized through Brunauer-Emmett-Teller, Barrett-Joyner-Halenda (BET-BJH), and scanning electron microscopy (SEM) analyses, were first evaluated and the sorbent capacity was then compared with traditional sorbents. The authors claimed that the developed hydrochar conceivably offers a new, feasible, and promising option for CO\({}_{2}\) capture using low cost and environmentally friendly materials. * The authors of the second paper ([PERSON]; [PERSON]; [PERSON]; [PERSON]) from the Technical University of Darmstadt, Germany, introduced a new char gasification model that represents all conditions in a fluidized bed gasifier [18]. For abundantly available low-rank coal, the conversion in fluidized bed gasifiers is a feasible technology to produce valuable chemicals or electricity while also offering the option of carbon capture. In this study, the non-isothermal thermogravimetric method was applied to gasify the char of Rhenish lignite at atmospheric pressure by using steam and carbon dioxide as a gasification medium. Two reaction models, namely, Arrhenius and Langmuir-Hinshelwood, as well as four conversion models (volumetric model, grain model, random pore model, and Johnson model), were fitted and evaluated with the measurement data. For both steam and carbon dioxide gasification, the authors stated that the Langmuir-Hinshelwood reaction model together with the Johnson conversion model is the most suitable method to describe the char conversion of the used Rhenish lignite, showing a coefficient of determination 98% and 95%, respectively. * The third paper, authored by [PERSON]; [PERSON]; [PERSON]; [PERSON], [PERSON] from the Technical University of Darmstadt, Germany, compared two mathematical models, namely, the rate-based model and the equilibrium-stage model, when both are applied to simulate the tar absorption process from syngas using soybean oil as a solvent in a research lab-scale test rig [19]. Experimental data at different operation points, published by [PERSON] [20], were used to validate the developed models. The authors claimed that the rate-based model has higher accuracy than the equilibrium model. However, a minor deviation between the rate-based model and the experimental data was reported, which increases by increasing the bed height. An analysis study of the tar absorption process was also performed, revealing the influence of height-packed bed, temperature, and flow rate of the soybean oil on tar removal efficiency. * The fourth paper, accepted in this Special Issue, authored by [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] from University of Teramo, Italy. In this study, steam gasification experiments for lignite in a bench-scale fluidized-bed gasifier were carried out to evaluate the quality of the gas produced at different operating conditions [21]. Olivine was used as bed material and the steam/fuel ratio was maintained at approximately 0.65. The influence of temperature and air injections in the freeboard was evaluated in terms of the conversion efficiencies, gas composition, and tar produced.