Rapid economic growth since the turn of the century has often been accompanied by significant challenges, including fossil fuel depletion, environmental degradation, and energy security concerns. Urgent measures are essential to promote environmentally friendly advancements and adopt sustainable energy solutions. Biomass energy, an important component of renewable energy, stands out as the sole renewable energy source containing carbon and has attracted significant attention from governments and the scientific community worldwide. Attention to biomass conversion technologies and their practical applications has gradually increased. This paper provides an in-depth analysis of the utilization of biomass and its wastes, and systematically introduces the progress of the application of biomass conversion technologies, including biochemical and thermochemical conversion, to provide readers with a clear picture of the technological development. By meticulously summarizing the current status of the application of different products produced by these technologies, it provides a valuable reference for researchers and practitioners in the field of biomass energy, aiming to meet the challenges of clean energy production and biomass waste management, and to mitigate the adverse impacts of human activities on the environment. In addition, this paper explores the application of machine learning in the field of biomass conversion, especially its potential in optimizing the biomass conversion process, improving the accuracy of energy yield prediction, and enhancing process control. Despite challenges such as data quality and model interpretability, developments in machine learning, particularly advances in feature engineering and interpretable AI, promise to address these issues. This study contributes positively to advancing biomass energy technologies.

Biomass gasification process generates the residual tar, which in turn exerts some negative influence on biomass gasification system. To reduce this harmful influence, an evaluation of the tar properties during the biomass gasification was studied. The chemical composition and pyrolysis behavior of biomass tar were investigated. The complex chemical composition of the tar, which includes phenol derivatives, naphthalene derivatives, other macromolecular aromatic compounds, furans, and other compounds (carbon number from 7 to 14), was established by gas chromatography-mass spectrometry technique. Thermogravimetric analysis was performed with two heating rates (10°C/min and 20°C/min), and Coats-Redfern method was applied to assess the kinetic parameters, i.e., the activation energy (E) and pre-exponential factor (A) of tar thermo-chemical decomposition. The results showed that the main degradation of tar is a two-step process, including a volatilization step at lower temperatures (<105°C) and a pyrolysis step at higher temperatures (105°C-380°C). The application of the Coats-Redfern method revealed a variation trend of the activation energy during the decomposition of tar in a non-isothermal model. It shows that high temperature is more conducive to tar pyrolysis. By adjusting the temperature to control the generation and removal of tar, new approaches are provided for designing and optimizing biomass gasification systems.