The brewing sector is a significant part of the global food industry. Breweries produce large quantities of wastes, including wastewater and brewer’s spent grains. Currently, upcycling of food industry by-products is one of the principles of the circular economy. The aim of this review is to present possible ways to utilize common solid by-product from the brewing sector. Brewer’s spent grains (BSG) is a good material for sorption and processing into activated carbon. Another way to utilize spent grains is to use them as a fuel in raw form, after hydrothermal carbonization or as a feedstock for anaerobic digestion. The mentioned by-products may also be utilized in animal and human nutrition. Moreover, BSG is a waste rich in various substances that may be extracted for further utilization. It is likely that, in upcoming years, brewer’s spent grains will not be considered as a by-product, but as a desirable raw material for various branches of industry.

Through years beer became one of the best known alcoholic beverages in the world. For some reason e.g. healthy lifestyle, medical reasons, driver’s duties, etc. there is a need for soft drink with similar organoleptic properties as standard beer. There are two major approaches to obtain such product. First is to interfere with biological aspects of beer production technology like changes in mashing regime or to perform fermentation in conditions that promote lower alcohol production or using special (often genetic modified) microorganism. Second approach is to remove alcohol from standard beer. It is mainly possible due to evaporation techniques and membrane ones. All these approaches are presented in the paper.

To make a beer there are four essential ingredients needed: water, malt, hops, and yeast. After brewing process, the main wastes are spent grains. These are often used as additions to fodders in animal husbandry. This study presents preliminary results of an investigation aiming to determine the feasibility of an alternative use of spent grains as a potential source of solid fuel. This source of energy could make breweries partly sustainable in terms of their energy supply. Such an approach may be feasible especially in large scale industrial breweries. This preliminary study presents encouraging results, showing improvements in terms of the fuel properties of the spent grain after its valorization through hydrothermal carbonization. Moreover, qualitative GC-MS analysis also indicates potential feasibility of the liquid byproduct of the hydrothermal carbonization of spent grain for biogas production. Results of proximate, ultimate, and DTG analyses show that hydrothermal carbonization of spent grain could improve its fuel properties and make it an especially suitable feedstock for fast pyrolysis and gasification. Improvement of HHV is also an improvement in terms of combustion.

Around 40% to 60% of municipal solid waste originates from kitchens, offering a valuable resource for compost production. Traditional composting methods such as windrow, vermi-, and bin composting are space-intensive and time-consuming. Black soldier fly larvae (BSFL) present a promising alternative, requiring less space and offering ease of handling. This research encompasses experimental data collection, life cycle assessment, and machine learning, and employs the Levenberg–Marquardt algorithm in an Artificial Neural Network, to optimize kitchen waste treatment using BSFL. Factors such as time, larval population, aeration frequency, waste composition, and container surface area were considered. Results showed that BSFL achieved significant waste reduction, ranging from 70% to 93% by weight and 65% to 85% by volume under optimal conditions. Key findings included a 15-day treatment duration, four times per day aeration frequency, 600 larvae per kilogram of waste, layering during feeding, and kitchen waste as the preferred feed. The larvae exhibited a weight gain of 2.2% to 6.5% during composting. Comparing the quality of BSFL compost to that obtained with conventional methods revealed its superiority in terms of waste reduction (50% to 73% more) and compost quality. Life cycle assessment confirmed the sustainability advantages of BSFL. Machine learning achieved high accuracy of prediction reaching 99.5%.

The advancement of plasma technology is intricately linked with the utilization of computational fluid dynamics (CFD) models, which play a pivotal role in the design and optimization of industrial-scale plasma reactors. This comprehensive compilation encapsulates the evolving landscape of plasma reactor design, encompassing fluid dynamics, chemical kinetics, heat transfer, and radiation energy. By employing diverse tools such as FLUENT, Python, MATLAB, and Abaqus, CFD techniques unravel the complexities of turbulence, multiphase flow, and species transport. The spectrum of plasma behavior equations, including ion and electron densities, electric fields, and recombination reactions, is presented in a holistic manner. The modeling of non-thermal plasma reactors, underpinned by precise mathematical formulations and computational strategies, is further empowered by the integration of machine learning algorithms for predictive modeling and optimization. From biomass gasification to intricate chemical reactions, this work underscores the versatile potential of plasma hybrid modeling in reshaping various industrial processes. Within the sphere of plasma catalysis, modeling and simulation methodologies have paved the way for transformative progress. Encompassing reactor configurations, kinetic pathways, hydrogen production, waste valorization, and beyond, this compilation offers a panoramic view of the multifaceted dimensions of plasma catalysis. Microkinetic modeling and catalyst design emerge as focal points for optimizing CO₂ conversion, while the intricate interplay between plasma and catalysts illuminates insights into ammonia synthesis, methane reforming, and hydrocarbon conversion. Leveraging neural networks and advanced modeling techniques enables predictive prowess in the optimization of plasma-catalytic processes. The integration of plasma and catalysts for diverse applications, from waste valorization to syngas production and direct CO₂/CH₄ conversion, exemplifies the wide-reaching potential of plasma catalysis in sustainable practices. Ultimately, this anthology underscores the transformative influence of modeling and simulation in shaping the forefront of plasma-catalytic processes, fostering innovation and sustainable applications.

Due to current trends in beer consumption, as well as social aspects, such as the education of society on combining drinking and driving, intensive research and development efforts have been recently focused on producing low-alcohol beers and non-alcoholic beers with a sensory profile appealing to consumers. There are plenty of methods for obtaining such beverages; one of these methods involves utilizing non-conventional yeasts for wort fermentation. In this work, the production of low-alcohol beer using commercially available Saccharomycodes ludwigii and Torulaspora delbrueckii strains were compared. The results showed that Torulaspora delbrueckii achieved the lowest level of attenuation, producing beer with an ethanol concentration of 2.58% vol. Saccharomycodes ludwigii displayed a slightly higher level of attenuation; however, its alcohol concentration was slightly lower than in the case of Torulaspora delbrueckii and reached 2.50% vol. Fully fermented beers produced using Saccharomycodes ludwigii and Torulaspora delbrueckii represented reduced ethanol concentrations by 12% and 15%, respectively, in comparison to Saccharomyces cerevisiae. Nevertheless, in order to produce non-alcoholic beers, arrested fermentation is necessary. In such a case, Saccharomycodes ludwigii reached the highest level of attenuation among non-alcoholic beers.