BioEnergy Research最新文献

Biochar is a highly efficient and clean fuel. In recent years, significant progress has been made in machine learning technology to predict the higher heating value (HHV) of biochar. This study innovatively proposes a method to enhanced data for the HHV of biochar. The dataset was divided into three groups according to the characteristics of biomass, and the prediction model of HHV of biochar was established on the basis of three machine learning algorithms: LightGBM, CatBoost, and DNN. The effect of “enhanced data” on the prediction accuracy of the model is evaluated. Experiment results reveal that inclusion of “enhanced data” improves the model-fitting performance of the model, and the model of LightGBM is more suitable for biochar HHV prediction. The introduction of enhanced data improves the prediction accuracy of the model, with R² increasing by 0.068, MAE decreased by 0.421, and RMSE decreased by 0.180. The SHAP analysis demonstrated that inclusion of “enhanced data” changed the ranking of feature importance in that ash content of pyrolysis and temperature of pyrolysis stayed at the forefront of importance features. PDP and ICE analysis demonstrated that inclusion of “enhanced data” significantly changed the contribution of some of the features to HHV of biochar. This study provides significant reference and guidance for predicting other characteristics of biomass pyrolysis products.

The treatment of kitchen waste and agricultural solid waste are two major challenges in urban and agricultural environmental protection. The conversion of organic solid waste into bio-oil through mild hydrothermal methods can not only alleviate the environmental problems caused by traditional Lignocellulosic biomass processing but also provide technical support for the sustainable production of fuel oil. Traditional research on hydrothermal conversion of organic solid waste mostly focuses on areas such as catalysts and hydrothermal parameters, while studies on environmental impact assessments are relatively rare. In this study, a process for the co-hydrothermal conversion of kitchen waste and agricultural solid waste biomass was firstly established, with bio-oil as the target product. The analysis results show that the higher the yield and calorific value of bio-oil, the greater its negative impact on the environment, which accounts for 41.41 to 55.24% of the total impact. Groups with more significant Maillard reactions had higher bio-oil yields but also had higher net CO2 emissions, with the highest reaching 25.05 kg CO₂ kg⁻¹. For the consumption of mineral, fossil, and renewable resources, dichloromethane was the largest contributor. Overall, the hydrothermal Liquefaction stage had the greatest environmental impact among all stages, accounting for 42.26 to 56.55% of the total impact. Changes in fertilizer application rates had a certain effect on impact categories other than mineral, fossil, and renewable resource consumption. Reducing the energy consumption of hydrothermal liquefaction can significantly reduce its consumption of fossil fuels and other energy sources, while changes in grinding and filtering energy consumption had little impact on the environment. The research content of this paper will provide some references for the resourceful conversion of kitchen waste and agricultural solid waste from an industrial perspective.

Industrial CO(_2) emissions, particularly from flue gases, are a major barrier to climate change mitigation. Carbon capture, particularly with bioenergy (BECCS), offers a pathway to negative emissions. This study models an MEA-based carbon capture system using operational data from a stand-alone pulp mill, focusing on its energy impact and optimization strategies. The analysis distinguishes between high-quality steam, critical for electricity generation, and waste heat, which can be valorized for carbon capture. The thermal energy demand for capture was found to be 3.6 MJ/kg CO(_2), leading to a reduction in energy efficiency. Integration scenarios such as flue gas valorization, combustion air preheating, and a steam generation heat pump (SGHP) were evaluated to address this. The electrical energy penalty (EEP) was introduced as a metric to quantify power losses due to steam extraction. The results show that while flue gas valorization and air preheating offer limited benefits, the steam generation heat pump effectively reduces both steam dependency and electrical energy losses, enabling high CO(_2) capture efficiency with minimal impact on mill operations, with the SGHP achieving the lowest EEP of 0.50 MJ/kg CO(_2) and enabling a 90% CO(_2) capture rate.

Anaerobic digestion-derived volatile fatty acids (VFAs) have emerged as key intermediates in sustainable biofuels and biochemicals production, offering a circular approach to organic waste valorization. This review explores recent advancements in enhancing VFA production through tailored pre-treatment strategies, optimized feedstock selection, and controlled process conditions. Furthermore, VFA extraction methodologies are discussed, with a focus on energy-efficient separation techniques. The integration of VFAs as feedstock for microbial lipid production is analyzed, highlighting substrate preferences, metabolic insights, and growth conditions for oleaginous yeast, which can thereby be cultivated in non-sterile conditions because of using VFAs as feedstock. Additionally, innovative lipid extraction technologies, including pulsed electric fields, hydrothermal liquefaction, and ionic liquids, are reviewed for their potential to enhance lipid recovery. By consolidating advancements across these domains, this review provides a comprehensive understanding of the technological landscape, identifying key challenges and future research directions to optimize VFA-driven biofuel production.

This work proposes the use of a novel non-magnetic SrFe/CaO catalyst derived from waste materials, which have not been reported for biodiesel production under microwave conditions. Also, it evaluates the interaction of multiple reaction factors through statistical modeling. While CaO has been widely used in biodiesel production, its leaching and limited stability have motivated the search for improved materials. Hence, the Sr/CaO, Fe/CaO, and SrFe/CaO catalysts were synthesized by incipient impregnation of the calcined eggshells with Sr and Fe salts, followed by calcination at 800 °C. N₂-physisorption, XRD, and Hammett indicators were used as characterization techniques of the catalysts, and the reaction was performed in a batch reactor under microwave irradiation at 60 °C. The SrFe/CaO catalyst exhibited the highest basicity (60 mmol g⁻¹), possibly due to the formation of the α-Fe₂O₃ phase, and achieved a biodiesel yield of 92%. Further optimization using the Box-Behnken response surface methodology revealed that reaction time and the methanol-to-oil ratio significantly affected the yield, while microwave power had a minor influence. The optimal conditions for this system were 56 min, 150 W, and a methanol-to-oil ratio of 10:1, which resulted in a maximum biodiesel yield of 98.87%. Despite the promising activity, catalyst stability decreased over reuse cycles, likely due to CaO leaching.

This study optimized syngas production from Eucalyptus sp. wood chips in a pilot-scale downdraft gasifier through physical modifications (a barrier in the reduction zone) and low-cost catalysts (iron ore and nickel oxide), aiming to enhance gas quality and process efficiency for decentralized bioenergy systems. CFD simulations guided barrier design, increasing gas residence time by 50% (from 4.6 to 6.9 s) and Reynolds number in the reduction zone to > 280, enhancing turbulence. Experimental results showed that the iron ore catalyst boosted hydrogen content to 10.0 vol%, while the nickel catalyst achieved an optimal H₂/CO ratio of 2.3:1 for syngas applications. Combined use of both catalysts with steam further elevated the H₂/CO ratio to 4.19:1. Despite a minor reduction in lower heating value (LHV) from 4.07 to 3.95 MJ/Nm³, the barrier improved operational stability, reducing temperature fluctuations by 100 °C. Cold gas efficiency reached 54.7% for steam-assisted gasification. These results demonstrate the potential of low-cost modifications to enhance gasifier performance.

Monitoring charcoal quality is essential for the industry. Near-infrared (NIR) spectroscopy enables fast and accurate predictions of key properties. This study evaluated the use of benchtop and portable NIR sensors to predict charcoal characteristics from woody biomass of 15 commercial clones (11 Eucalyptus and 4 Corymbia). Two trees per clone were sampled at six stem positions, generating 30 composite wood samples. After carbonization and grinding, spectral data were collected, totaling 600 spectra per sensor. Partial least squares regression was used to develop models for gravimetric yield (GY), apparent relative density (ARD), fines content (FC), volatile matter content (VMC), ash content (AC), and fixed carbon content (FCC). For Eucalyptus clones, the benchtop sensor outperformed the portable one for GY (R²p = 0.74; RPD = 2.02), ARD (R²p = 0.87; RPD = 2.82), VMC (R²p = 0.72; RPD = 1.92), AC (R²p = 0.72; RPD = 1.92), and FCC (R²p = 0.63; RPD = 1.64). The portable sensor was better only for FC (R²p = 0.64; RPD = 1.60). Similarly, for Corymbia clones, the benchtop sensor performed better for GY (R²p = 0.79; RPD = 2.15), ARD (R²p = 0.87; RPD = 2.77), FC (R²p = 0.69; RPD = 1.73), and AC (R²p = 0.61; RPD = 1.62). The portable sensor showed better results for FCC (R²p = 0.61; RPD = 1.48) and VMC (R²p = 0.64; RPD = 1.40). Overall, benchtop and portable NIR spectrometers showed similar performance in estimating charcoal parameters.

Biogas is a promising renewable energy source that is produced by anaerobic digestion of organic waste and is mainly made up of carbon dioxide (CO₂) and methane (CH₄). However, its direct application is limited due to the presence of impurities such as CO₂, hydrogen sulfide (H₂S), water vapor, and trace gases (hydrogen sulfide, hydrogen, ammonia, nitrogen, oxygen, siloxanes, and carbon monoxide) that reduce its calorific value and cause operational issues. Their presence is undesirable since it lowers the calorific value of biogas and causes a number of issues with machine performance. Therefore, throughout the process of converting biogas into biomethane, multi-stage technologies for their removal are employed. This review provides a comprehensive overview of recent advances and future directions in biogas-upgrading technologies. Conventional physicochemical methods such as water scrubbing, chemical absorption, pressure swing adsorption (PSA), membrane separation, and cryogenic techniques are critically discussed with respect to efficiency, energy consumption, operational complexity, and cost. Furthermore, emerging biological upgrading technologies, including in situ and ex situ hydrogenotrophic methanation, and microalgae-based CO₂ fixation have been highlighted. These biological methods offer eco-friendly and cost-effective alternatives by converting CO₂ into CH₄ under mild conditions, although their scalability and integration into existing infrastructure remain under exploration. The review highlights technological challenges, comparative performances, and research gaps, offering insights into integrated and hybrid approaches that combine physicochemical and biological pathways for optimal biogas purification. This work serves as a reference for researchers and practitioners seeking sustainable and efficient biogas-upgrading solutions for grid injection, transportation fuel, and decentralized energy systems. The readers will learn about the scientific and technological obstacles to biogas technology advancement from this review.

The worldwide demand for renewable energy alternatives with agricultural stubble has driven the advancement of second-generation (2G) biofuels. Despite the abundance of stubble, it remains underexploited due to the complexity of plant cell walls, posing a noteworthy challenge to efficient biotransformation. The review explores recent advancements in extremophilic glycoside hydrolases (GHs) as promising biocatalysts to overcome biomass complexity. The study analyses recent innovations revealing how these robust enzymes, integrated with computational and biotechnology tools, unlock new ways to convert agricultural waste into bioenergy. The novel interdisciplinary convergence of microbiology, protein engineering, and artificial intelligence is highlighted for emerging innovations in enzyme design and formulation. Furthermore, recently discovered lytic polysaccharide monooxygenases (LPMOs) with GHs in enzyme cocktails synergistically enhance saccharification, facilitating the breakdown of complex polysaccharides. This synergy, combined with innovations in advanced recombinant DNA technology, synthetic biology, machine learning, and artificial intelligence, offers novel strategies for designing robust enzyme cocktails. Computational analysis of extremophilic endoglucanases identified conserved glycine, proline, and tryptophan residues as key contributors to structural integrity and catalysis in extreme environments. The review identifies emerging business opportunities in enzyme-based biomass valorization and outlines prospective directions for future research, including challenges in enzyme stability, process scalability, and integration into biorefineries.

Renewable diesel is a biofuel produced via hydro-processing of glycerides and fatty acids, offering a molecular structure closely resembling that of fossil diesel. This characteristic makes it a promising alternative for partially replacing conventional fuels, as it can be blended with petroleum diesel in high concentrations or used directly in compression ignition engines without modification. In this study, the effects of blending renewable diesel derived from fatty acids obtained from waste chicken fat with petroleum diesel were evaluated by analyzing their physicochemical properties according to ASTM D975 and EN 590 standards. The renewable diesel production involved two key stages: (1) hydrolyzing chicken fat waste at 250 °C for 120 min, achieving a 95% conversion to fatty acids, and (2) catalytic deoxygenation of the fatty acids using a sulfurized NiMo/Al₂O₃ catalyst, yielding 92% n-alkanes with 99% purity. The hydrolysis step was aimed at decreasing the amount of hydrogen in the hydrotreating step. The resulting biofuel blends exhibited excellent quality, with key parameters meeting regulatory standards: kinematic viscosity of 3.18 cSt, cetane index of 79.30, flash point of 109 °C, contamination < 1 ppm, and a filter blocking tendency of 1.03. Additionally, the cold flow properties were within acceptable ranges, demonstrating the suitability of these blends for commercial diesel applications. This study highlights the potential of utilizing waste chicken fat as a sustainable feedstock for high-quality renewable diesel production, contributing to the development of cleaner fuel alternatives.

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