The routine pruning and cutting of fruit trees provides a considerable amount of biowaste each year. This lignocellulosic biomass, mainly in the form of branches, trunks, rootstocks, and leaves, is a potential high-quality fuel, yet often is treated as waste. The results of a feasibility study on biochar production by pyrolysis of residues from orchard pruning were presented. Three types of biomass waste were selected as raw materials and were obtained from the most common fruit trees in Poland: apple (AP), pear (PR), and plum (PL) tree prunings. Two heating rates and three final pyrolysis temperatures were applied. For the slow (SP) and fast pyrolysis (FP) processes, the heating rates were 15 °C/min and 100 °C/min, respectively. The samples were heated from 25 °C up to 400, 500, and 600 °C. Chemical analyses of the raw materials were conducted, and the pyrolysis product yields were determined. A significant rise of higher heating value (HHV) was observed for the solid pyrolysis products, from approximately 23.45 MJ/kg for raw materials up to approximately 29.52 MJ/kg for pyrolysis products at 400 °C, and 30.53 MJ/kg for pyrolysis products at 600 °C. Higher carbon content was observed for materials obtained by fast pyrolysis conducted at higher temperatures.

The aim of this study was to assess the possibility of using furniture waste for smokeless fuel production using the pyrolysis process. Four types of wood-based wastes were used in the pyrolysis process: pine sawdust (PS), chipboard (CB), medium-density fiberboard (MDF), and oriented strand board (OSB). Additionally, the slow and fast types of pyrolysis were compared, where the heating rates were 15 °C/min and 100 °C/min, respectively. Chemical analyses of the raw materials and the pyrolysis product yields are presented. A significant calorific value rise was observed for the solid pyrolysis products (from approximately 17.5 MJ/kg for raw materials up to approximately 29 MJ/kg for slow pyrolysis products and 31 MJ/kg for fast pyrolysis products). A higher carbon content of char was observed in raw materials (from approximately 48% for raw materials up to approximately 75% for slow pyrolysis products and approximately 82% for fast pyrolysis products) than after the pyrolysis process. This work presents the possibility of utilizing waste furniture material that is mostly composed of wood, but is not commonly used as a substrate for conversion into low-emission fuel. The results prove that the proposed solution produced char characterized by the appropriate properties to be classified as smokeless coal.

The sustainable utilization of biomass, particularly troublesome waste biomass, has become one of the pathways to meet the urgent demand for providing energy safety and environmental protection. The variety of biomass hinders the design of energy devices and systems, which must be highly efficient and reliable. Along with the technological developments in this field, broad works have been carried out on the mathematical modeling of the processes to support design and optimization for decreasing the environmental impact of energy systems. This paper aims to provide an extensive review of the various approaches proposed in the field of the mathematical modeling of the thermochemical conversion of biomass. The general focus is on pyrolysis and gasification, which are considered among the most beneficial methods for waste biomass utilization. The thermal and flow issues accompanying fuel conversion, with the basic governing equations and closing relationships, are presented with regard to the micro- (single particle) and macro-scale (multi-particle) problems, including different approaches (Eulerian, Lagrangian, and mixed). The data-driven techniques utilizing artificial neural networks and machine learning, gaining increasing interest as complementary to the traditional models, are also presented. The impact of the complexity of the physicochemical processes and the upscaling problem on the variations in the modeling approaches are discussed. The advantages and limitations of the proposed models are indicated. Potential options for further development in this area are outlined. The study shows that efforts towards obtaining reliable predictions of process characteristics while preserving reasonable computational efficiency result in a variety of modeling methods. These contribute to advancing environmentally conscious energy solutions in line with the global sustainability goals.