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Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications

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A Special Issue of Energies (ISSN 1996-1073) belonging to the section "A4: Bio-Energy".

Deadline for manuscript submissions: closed (15 July 2026) | Viewed by 11803

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Editors

Dr. Frederico G Fonseca

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Guest Editor

Institute of Low-Carbon Industrial Processes, German Aerospace Center, Cottbus, Germany
Interests: decarbonisation; pyrolysis; renewable fuels; energetic transition

Dr. Ana Paula Soares Dias

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Guest Editor

CERENA, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal
Interests: heterogeneous catalysis; biodiesel; biomass valorization; materials characterization; environmental processes
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Special Issue Information

Dear Colleagues,

During the last decade, the world has witnessed a significant surge in the development of novel technologies for biomass conversion, both standalone and within a biorefinery context, driven by the growing demand for sustainable and renewable energy sources. Despite these advancements, there remains a pressing need to improve current modeling paradigms and optimize biomass utilization for industrial applications. Moreover, the geopolitical climate has brought the use of biomass and wastes as direct heat sources to mainstream attention, offering a promising short-term alternative to fossil fuels and contributing to a low-carbon economy.

This Special Issue aims to provide a comprehensive overview of the latest innovations in biomass conversion, biorefinery, and energy utilization, with a particular focus on modeling, optimization, and industrial applications. It seeks to highlight the importance of developing more accurate and efficient modeling paradigms, as well as the potential of biomass as a direct source of energy for industry.

The topics of interest for publication include, but are not limited to, the following:

Novel biomass conversion techniques in all levels of technological development;
Biorefinery systems and processes, including the production of biofuels, biochemicals, and biopower;
Modeling and simulation of biomass conversion and biorefinery processes;
Optimization techniques for biomass utilization, including machine learning, artificial intelligence, and process intensification;
Industrial applications of biomass as a direct source of energy, including power generation, heat production, and industrial processes;
Case studies and reviews of commercial-scale biomass conversion and biorefinery projects.

Dr. Frederico G Fonseca
Prof. Dr. Ana Paula Soares Dias
Guest Editors

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Keywords

biomass conversion
biorefinery
energy utilization
modeling and optimization
sustainable energy systems

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Published Papers (8 papers)

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Research

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24 pages, 1825 KB

Open AccessArticle

Computationally Efficient Optimization of Bio-Jet Fuel Supply Chains Using Machine-Learning-Assisted Mixed-Integer Programming

by Krystel K. Castillo-Villar, Kolton Keith and Adel Alaeddini

Energies 2026, 19(15), 3570; https://doi.org/10.3390/en19153570 - 29 Jul 2026

Viewed by 360

Abstract

Bio-jet fuels produced from biomass-derived feedstocks represent a promising pathway for reducing the carbon intensity of aviation energy systems. However, designing supply chain networks for bio-jet fuel production requires solving large-scale mixed-integer linear programming (MILP) models that integrate facility location, feedstock allocation, material flows, and routing decisions. These models can become computationally expensive, particularly when evaluating multiple network configurations or large candidate sets of production and processing facilities. This study develops a hybrid machine learning and optimization framework to improve the computational efficiency of bio-jet fuel supply chain network design while preserving high-quality decision outcomes. The proposed iterative procedure uses supervised learning to approximate the relationship between facility location decisions and total supply chain cost. First, an initial set of supply chain configurations is generated by solving the optimization model while using randomly selected facility locations. These solutions are then used to train predictive models, including ridge regression, feed-forward neural networks, and ensemble neural networks, with facility-location configurations as inputs and total supply chain cost as the output. The trained learner is subsequently used to identify promising facility-location candidates through Thompson sampling and small-scale linear programming. These candidate solutions are evaluated by the original mixed-integer model, and the resulting observations are fed back into the learning process until convergence. Numerical experiments show that the proposed hybrid approach obtains near-optimal bio-jet fuel supply chain designs while substantially reducing computational time. For the linear case, the method achieves solutions within 0.23–0.29% of the objective function value while reducing computational time by 70.95–81.95%. For nonlinear learning models, the optimality gap decreases further to 0.13–0.15%, with computational time reductions of 45.37–60.36%. For the Texas case study and the modeling assumptions evaluated, the findings demonstrate that machine-learning-assisted optimization can reduce computational effort while preserving high-quality supply chain solutions. The extent of these benefits may vary with network size, candidate-facility structure, facility-capacity assumptions, demand characteristics, and the amount of information available to train the learning models. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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22 pages, 3197 KB

Open AccessArticle

Energy Potential of Selected Sedges (Carex spp.) as a Renewable Biomass Feedstock

by Magdalena Janyszek-Sołtysiak, Leszek Majchrzak, Maciej Krzysztof Murawski, Magdalena Zborowska and Bogusława Waliszewska

Energies 2026, 19(9), 2200; https://doi.org/10.3390/en19092200 - 1 May 2026

Viewed by 573

Abstract

The increasing demand for energy, the finite nature of fossil fuel resources, and the necessity to reduce greenhouse gas emissions have intensified research on renewable energy sources of plant origin. Among potential energy feedstocks, herbaceous biomass has attracted growing interest due to its high productivity, rapid growth, and widespread occurrence. The aim of this study was to evaluate the energy potential of select sedge species (Carex spp.) commonly occurring in Poland as an alternative to fossil fuels. Aboveground biomass of eight sedge species was collected from natural habitats located in the Warta River valley. Cellulose, lignin, holocellulose, hemicellulose, and ash content in the biomass was determined. In addition, key energy parameters, namely net calorific value and gross calorific value, were analyzed. Differences among species were assessed using one-way analysis of variance, while similarities were explored using hierarchical clustering methods. The results revealed significant interspecific variation in both chemical composition and energy properties. Most analyzed sedge species had favorable lignocellulosic composition and energy parameters comparable to those of woody biomass, particularly willow and poplar. In contrast, Carex riparia was distinguished by a high ash content and lower calorific values, limiting its suitability for energy applications. Overall, the findings indicate that select Carex species may represent a valuable renewable feedstock for energy production, especially in the context of local and decentralized biomass-based energy systems. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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21 pages, 1604 KB

Open AccessArticle

Enhancing Hydrogenotrophic Methanation in a Bentonite-Amended Bubble Reactor Under Mesophilic Conditions

by Apostolos Spyridonidis and Katerina Stamatelatou

Energies 2026, 19(7), 1613; https://doi.org/10.3390/en19071613 - 25 Mar 2026

Viewed by 501

Abstract

This study explores the use of bentonite to enhance biological biogas upgrading in a bubble reactor (BR) operated under mesophilic conditions (39 ± 1 °C). The experimental setup consisted of a 2 L vertically oriented BR (height-to-diameter ratio 16:1) fed with a synthetic gas mixture (60% H₂, 15% CO₂, 25% CH₄, v/v) at a gas recirculation rate of 4 L L_R⁻¹ h⁻¹. The aim was to overcome hydrogen’s low gas–liquid mass transfer rate while avoiding the operational challenges typically associated with trickle-bed reactors (TBR). Bentonite increases the density and hydrostatic pressure of the liquid medium and likely alters its rheology, thereby extending the gas–liquid contact time without requiring elevated pressures or intensive gas recirculation. Additionally, bentonite is expected to provide microstructural support that promotes the formation of biofilm-like communities, creating favorable microenvironments for hydrogenotrophic methanogens. As a clay-based additive, bentonite may also contribute to improved process stability through adsorption of inhibitory compounds, enhanced biomass retention, and pH buffering. Under mesophilic conditions, the bentonite-modified BR achieved a methane production rate of 2.17 ± 0.06 LCH₄ L_R⁻¹ d⁻¹ at a gas retention time of 1.49 h, with methane purity reaching 96.25%. In comparison, a previously reported mesophilic BR operated under an identical reactor configuration and operating conditions but without bentonite exhibited substantially lower methane production rates, supporting the beneficial role of bentonite in biological methanation. The findings highlight bentonite’s potential dual role (physical and biological) in improving process efficiency and stability in biological methanation. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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21 pages, 4678 KB

Open AccessFeature PaperArticle

Evaluation of Co-Pelletization of Corn Stover and Plastic Waste as an Alternative Fuel Source for Cement Production

by Haley Stockham, Asmita Khanal, Sushil Adhikari and Ajay Shah

Energies 2025, 18(20), 5393; https://doi.org/10.3390/en18205393 - 13 Oct 2025

Cited by 1 | Viewed by 1091

Abstract

Corn stover and plastic waste, severely underutilized feedstocks generated in the U.S., could be co-pelletized to produce fuel for cement production. High-density polyethylene bags (0–25% in 5% increments, dry basis) and corn stover were co-pelletized using a flat ring pellet mill with die diameters of 6 and 8 mm. Physical and chemical properties were assessed to determine pellet quality. These results informed techno-economic and life cycle greenhouse gas emissions (GHGe) analyses for a Midwestern plant producing 400,000 metric tons of pellets annually. The system boundary included feedstock acquisition at the pellet plant, size reduction, co-pelletization, and transportation of the pellets to the cement plant by rail. Total resource requirements in terms of raw materials, labor, fuel, equipment, the facility, and utilities were estimated. It was determined that the pellets would be delivered to the cement plant at USD 112.4–138.6/t pellets. The life cycle analysis estimated a total GHGe of 1621.1–1753.1 kg CO₂e/t pellets associated with the pellet production, transportation, and combustion. The results suggest that substituting 25% of the thermal energy requirement of a cement plant with a 1.1 million t clinker annual production capacity with plastic–stover pellets would reduce the GHGe by 2.8% compared to 100% of the total energy requirement supplied by coal. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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22 pages, 12897 KB

Open AccessArticle

Spatial Multi-Criteria Land Suitability Analysis for Community-Scale Biomass Power Plant Site Selection

by Athipthep Boonman, Suneerat Fukuda and Agapol Junpen

Energies 2025, 18(17), 4469; https://doi.org/10.3390/en18174469 - 22 Aug 2025

Cited by 2 | Viewed by 2462

Abstract

Community-scale biomass power plants (CSBPPs) offer a decentralized approach for electricity generation by utilizing locally available biomass while delivering socioeconomic benefits. Site selection plays a critical role in the success of CSBPPs and requires the consideration of diverse spatial and non-spatial factors. This study presents a spatial decision-support tool for identifying suitable CSBPP sites in Thailand’s Eastern Economic Corridor (EEC), which comprises the Chachoengsao, Chonburi, and Rayong provinces. A geoprocessing workflow integrating Geographic Information Systems (GISs), Multi-Criteria Decision-Making (MCDM), and the Analytic Hierarchy Process (AHP) was developed using ModelBuilder tools in ArcGIS Pro (version 3.0.2). Thirteen sub-criteria related to geographical, infrastructural, and socioeconomic–cultural dimensions, along with exclusion zones, were evaluated by 15 experts from diverse stakeholder groups. Biomass availability from five major economic crops was combined with other spatial data layers, incorporating expert-assigned weights and suitability scores. The findings indicated a remaining biomass energy potential was 34,156 TJ, with sugarcane residues contributing over 80%. Approximately 20% of the EEC area (about 0.262 million hectares) was classified as highly suitable for CSBPP development, revealing several viable site options. The proposed model offers a flexible and replicable framework for regional biomass planning and can be adapted to other locations by adjusting the criteria and integrating optimization techniques. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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14 pages, 2082 KB

Open AccessArticle

Effect of the Growth Period of Tree Leaves and Needles on Their Fuel Properties

by Tadeusz Dziok, Justyna Łaskawska and František Hopan

Energies 2025, 18(15), 4109; https://doi.org/10.3390/en18154109 - 2 Aug 2025

Cited by 1 | Viewed by 1223

Abstract

The main advantage of using biomass for energy generation is the reduction in carbon dioxide emissions. For a fast reduction effect, it is important to use biomass characterised by an annual growth cycle. These may be fallen leaves. The fuel properties of the leaves can change during the growth period. These changes can result from both the natural growth process and environmental factors—particulate matter adsorption. The main objective was to determine changes in the characteristics of leaves and needles during the growth period (from May to October). Furthermore, to determine the effect of adsorbed particulate matter, the washing process was carried out. Studies were carried out for three tree species: Norway maple, horse chestnut and European larch. Proximate and ultimate analysis was performed and mercury content was determined. During the growth period, beneficial changes were observed: an increase in carbon content and a decrease in hydrogen and sulphur content. The unfavourable change was a significant increase in ash content, which caused a decrease in calorific value. The increase in ash content was caused by adsorbed particulate matter. They were mostly absorbed by the tissues of the needle and leaves and could not be removed by washing the surface. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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Review

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30 pages, 1529 KB

Open AccessReview

From Feedstock Variability to Biorefinery Performance: A Review of Modeling and Optimization Approaches for Biomass-to-Bioenergy Supply Chains

by Krystel K. Castillo-Villar, Fernando R. Castillo-Villar, Rosalia G. Castillo-Villar and Amanda Hydar

Energies 2026, 19(17), 4065; https://doi.org/10.3390/en19174065 - 29 Aug 2026

Viewed by 125

Abstract

The industrial scalability and economic competitiveness of biomass-to-bioenergy and biorefinery systems depend on reliable feedstock supply, consistent biomass quality, and efficient logistics. An aspect that remains underexplored in biomass-to-biorefinery supply chain optimization is the incorporation of biomass quality uncertainty into decision-making models. Biomass quality characteristics, including ash content, moisture, chemical composition, and dry matter loss, can influence storage, preprocessing, transportation, conversion efficiency, biorefinery yields, process reliability, and overall energy utilization. Although these characteristics are difficult to model due to their spatial, temporal, and operational variability, ignoring their effects can lead to suboptimal supply-chain designs, inaccurate cost estimates, and unrealistic assessments of biorefinery performance. This paper reviews the treatment of biomass quality characteristics in the literature on quantitative modeling and analysis of biomass-to-biorefinery supply chains. Positioned from an Operational Research (OR) perspective, this review emphasizes mathematical modeling, computer simulation, optimization, and decision-support approaches for biomass-to-bioenergy systems. A total of 71 English-language published articles are reviewed and classified according to modeling approach and quality characteristic(s) considered. Across the selected literature that quantified biomass quality effects, cost reductions along supply chain operations ranging from 6% to 31% were reported when quality-aware models were compared with approaches that ignored quality or assumed unrealistic biomass quality characteristics. Despite these findings, biomass quality remains underrepresented in current analytical models; ash content, dry matter loss, and chemical composition were considered in only 10.4%, 4.3%, and 0.9% of the reviewed literature, respectively. This review summarizes the current state of research and outlines a future research agenda for integrating biomass quality control, uncertainty modeling, and optimization into scalable bioenergy and biorefinery systems. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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35 pages, 801 KB

Open AccessReview

Biochar Production Technology as a Negative Emission Strategy: A Review

by Andre Amba Matarru and Donghoon Shin

Energies 2025, 18(18), 4898; https://doi.org/10.3390/en18184898 - 15 Sep 2025

Cited by 10 | Viewed by 4426

Abstract

The urgent need to reduce greenhouse gas emissions and shift towards renewable energy has increased attention on biochar as a viable negative emission strategy. This review assesses the potential of biochar produced from organic and waste biomass via thermochemical processes—including pyrolysis, gasification, and hydrothermal carbonization—to address climate and energy challenges. Recent advances in biochar production are critically examined, highlighting how process design controls improve key properties such as carbon stability, atomic ratios, porosity, and energy density. These factors influence biochar’s performance in carbon sequestration and its utility across industrial sectors, ranging from agriculture and construction to energy generation and carbon capture systems. Results indicate that large-scale adoption of biochar could lower carbon emissions, enhance soil fertility, and produce renewable fuels like hydrogen, while also benefiting circular economy initiatives. However, obstacles remain, including economic costs, feedstock logistics, process optimization, and potential environmental or social impacts. This review underscores that unlocking biochar’s full promise will require interdisciplinary research, robust quality standards, and supportive policies. With integrated efforts across science, industry, and policy, biochar can serve as an effective and sustainable technology for emission reduction and contribute significantly to global carbon neutrality goals. Full article

(This article belongs to the Special Issue Innovations in Biomass Conversion, Biorefinery, and Energy Utilization: Modeling, Optimization, and Industrial Applications)

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