Biomass Gasification Research Articles

Prediction of syngas production in the gasification process of biomass employing adaptive neuro-fuzzy inference system along with meta-heuristic algorithms

Abstract Compared to fossil fuels, biomass fuels have minimal sulfur content, lower ash production, and significantly reduced emissions. The global need to reduce dependence on imported energy sources and preserve dwindling fossil fuel reserves underscores the importance of utilizing alternative energy resources. Biomass, with its abundant availability, presents a promising source for syngas production, even though the gasification procedure requires substantial energy due to its endothermic nature. Challenges related to the efficiency of biomass gasification and compliance with environmental standards have hindered economic viability. Much attention has been focused on predictive modeling of biomass gasification procedures to address these issues, necessitating robust frameworks capable of predicting parameters under varying operating conditions. This article introduces two hybrid frameworks, which are combined versions of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Artificial Rabbits Optimization (ARO) and Crystal Structure Algorithm (CSA), based on proximate biomass values to predict elemental compositions (N2 and H2). These intelligent hybrid frameworks, trained with 70 % of biomass data, were further validated and tested with the remaining 15 % portions of the database. The frameworks were assessed based on some known performance metrics, namely, root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R 2), RMSE-observations standard deviation ratio (RSR), and Nash-Sutcliffe Efficiency (NSE). Developed single and two hybrid frameworks compared and obtained outcomes revealed that both introduced optimizers efficiently promoted N2 and H2 estimation by ANFIS, especially CSA. R 2 values for ANCS were a maximum of 0.993 in both targets’ predictions. Also, minimum RMSE values of 1.007 and 1.470 related to N2 and H2 prediction emphasized the accuracy of ANCS, which is capable of being used in real-world applications.

Biodegradation of polycyclic aromatic hydrocarbons with enterobacter asburiae

Polycyclic Aromatic Hydrocarbons (PAHs) pollution has been found to be toxic, mutagenic, carcinogenic, teratogenic, and immunotoxicogenic. Naphthalene, Anthracene, and Fluorene are among the polycyclic aromatic hydrocarbons (PAHs) that are frequently detected in wastewater from biomass gasification and refineries. In this study, industrial waste water samples were collected from three sites located in Kafr El-Sheikh Governorate, Egypt and showed presence of PAHs in different concentration varying from 0.42 to 253.1 ppb. This study's findings included the isolation and identification of Enterobacter asburiae the most proficient bacterial isolate capable of biodegrading PAHs among other 7 studied bacterial isolates. Enterobacter asburiae strain No. 1 showed the ability to biologically degrade approximately 79 %, 89.7 % and 82.8 % of Naphthalene, Fluorene and Anthracene active ingredients respectively. The results of toxicity assessment showed that PAHs byproducts after 14 days of incubation had no toxicity; consequently, there was no antibacterial activity detected against B. subtilis as a test organism. Such biological approaches used in this study can be further applied in various polluted sites to get rid of ubiquitous organic pollutants.

Modelling of Biomass Gasification Through Quasi-Equilibrium Process Simulation and Artificial Neural Networks

In the past two decades, advancements in thermochemical technologies have improved biomass gasification for distributed power generation, enhancing efficiency, scalability, and emission control. This study aims to optimize syngas production from biomass gasification by comparing two computational models: a quasi-equilibrium thermodynamic model implemented in Aspen Plus and an artificial neural network (ANN) model. Operating at 850 °C with varying steam-to-biomass (S/B) ratios, both models were validated against experimental data. Results show that hydrogen concentration in syngas increased from 19.96% to 43.28% as the S/B ratio rose from 0.25 to 0.5, while carbon monoxide concentration decreased from 24.6% to 19.1%, consistent with the water–gas shift reaction. The ANN model provided rapid predictions, showing a mean absolute error of 3% for hydrogen and 2% for carbon monoxide compared to experimental data, though it lacks thermodynamic constraints. Conversely, the Aspen Plus model ensures mass and energy balance compliance, achieving a cold gas efficiency of 95% at an S/B ratio of 0.5. A Multivariate Statistical Analysis (MVA) further clarified correlations between input and output variables, validating model reliability. This combined modelling approach reduces experimental costs, enhances gasification process control and offers practical insights for improving syngas yield and composition.

Life cycle assessment and thermodynamic performance of biomass-based combined cogeneration

Abstract This study presents a thermodynamic and life cycle analysis of a biomass-based integrated energy system, comprising a biomass gasification cycle, a steam Rankine cycle, and an ammonia fluid Organic Rankine cycle. The primary objective of the system is to efficiently convert olive husk, a sustainable biomass source, into electricity and heating. The gasification process generates syngas, which fuels a gas turbine, producing high-temperature exhaust that drives a Rankine cycle. The thermodynamic analysis indicates that the overall system achieves an energy efficiency of 20.85% and an exergy efficiency of 11.70%. The Rankine cycle exhibits an energy efficiency of 23.91%, while the Organic Rankine cycle demonstrates a higher exergy efficiency of 68.87%. Parametric studies reveal that increasing the combustion chamber temperature significantly enhances system efficiency and output, with energy efficiency rising linearly as the temperature increases from 800 °C to 1000 °C. Additionally, the analysis emphasizes the importance of the compressor's compression ratio on system performance. A life cycle assessment conducted using the ReCiPe methodology evaluates the environmental impact of the system throughout its lifecycle, revealing critical insights into its sustainability. This comprehensive evaluation highlights the potential of utilizing agricultural waste, such as olive husk, to produce renewable energy, thereby supporting environmental sustainability and waste management goals. The findings underscore the viability of the proposed system for enhancing energy production while minimizing environmental impacts, making it a promising solution for renewable energy generation in regions with abundant biomass resources.

Low-emission hydrogen supply chain for oil refining: Assessment of large-scale production via electrolysis and gasification

The refining industry is a major hydrogen consumer, mainly relying on fossil fuel-derived hydrogen. While recent literature has focused on the production of hydrogen from water electrolysis, (waste) biomass gasification is another effective method for low-emission hydrogen production, and the refining industry is well positioned for its rapid adoption. This study conducts a techno-economic assessment of the whole supply chain of hydrogen for oil refining and analyses the LCA-climate change for residual biomass gasification and water electrolysis pathways. The potential economic and environmental benefits of combining both production methods are also analyzed. A real case study featuring four different scenarios, using data from a refinery, coupled with local data and future projections for potential curtailment and electricity prices, is included. The hourly hydrogen generation and demand profiles of the refinery were analyzed to accurately assess storage requirements. Results indicate that combining both technologies does not result in clear environmental or cost benefits, with residual biomass gasification emerging as the most advantageous configuration for the base case. Sensitivity analysis reveals that hydrogen produced via electrolysis may become more cost-effective if residual biomass prices are high enough. The importance of underground storage (salt cavern) is highlighted due to its low investment, while other storage methods can significantly increase the Levelized Cost of Hydrogen (LCOH). This study demonstrates that hydrogen production through gasification can be less carbon-intensive and more cost-competitive than electrolysis. Achieving low LCOH values and greenhouse gas emissions is feasible in all scenarios, indicating that both water electrolysis and residual biomass gasification are economically viable options for contributing to a low-emission global energy system.

Life cycle assessment and techno-economic analysis of maleic anhydride hydrogenation to 1,4-butanediol through biomass gasification coupling with chemical looping hydrogen production

Maleic anhydride hydrogenation is an important method to produce 1,4-butanediol. However, a large amount of H2 is needed for this method. Thus, novel processes to produce 1,4-butanediol from maleic anhydride were proposed using biomass gasification combined with chemical looping hydrogen generation technology (BGCLHP route) and natural gas steam reforming (NGSR route) to provide maleic anhydride hydrogenation with H2. Life cycle assessment was carried out, indicating that the BGCLHP route has a smaller environmental influence than the NGSR route. Additionally, techno-economic analysis was also studied to analyze the capital and operating investment, demonstrating the feasibility of the proposed route with existing technologies. Utilizing municipal solid waste as raw material, the minimum 1,4-butanediol selling price of the BGCLHP route was 2245 $/tonne, indicating it has a better economic performance. Based on the above analysis, the BGCLHP route has the potential to contribute to a more eco-friendly and economically sustainable 1,4-butanediol industry.

Biohydrogen and biomethane production from biomass gasification: compositional analysis, recent advancements, challenges, and prospects

Biohydrogen and biomethane production from biomass gasification: compositional analysis, recent advancements, challenges, and prospects

Process Simulation, Thermodynamic and System Optimization for the Low-Carbon Alcohols Production via Gasification of Second-Generation Biomass

Biomass-to-liquid fuels technology offers a promising method for high-value biomass conversion, addressing environmental toxicity and fossil fuel non-renewability. However, challenges such as low system efficiency and identifying efficiency losses persist. In this study, a comprehensive process model of a low-carbon alcohols production system via biomass gasification was developed, based on the first demonstration project in China. The innovation of this study lies in its detailed experimental validation, as the model simulation was performed using laboratory data and verified with pilot-scale platform data ensuring high accuracy. Additionally, the study conducted a thorough sensitivity analysis of system parameters, energy, and exergy assessments to find the proper operating conditions, including equivalent ratio, biomass type, and reactor temperature and pressure. The simulation results demonstrated an energy efficiency of 34.67% and an exergy efficiency of 31.24%. Through operating parameters and heat recovery measures, these efficiencies increased by 11.66% and 8%, respectively. This research not only obtains improved operating parameters for the pilot-scale platform but also provides actionable insights for enhancing the yields of target products and upgrading low-grade energy utilization. These findings offer valuable guidance for the commercialization of bio-syngas alcohols production systems, highlighting significant advancements in efficiency and system performance.

Experimental and kinetic study of pressurized CO2 gasification of biomass chars

Pressurized CO2 gasification of biomass represents an effective approach for the utilization of biomass and the reduction of CO2 emissions. The impact of CO2 partial pressure on the gasification kinetics of biomass chars was examined on a pressurized thermogravimetric analyzer at temperatures between 750 and 950 °C and elevated pressures (up to 1MPa). The findings demonstrated that the gasification rates of corn stalk char (CSC), toonasinesis sawdust char (TSC), and rice husk char (RHC) exhibited an increase with rising CO2 partial pressure. The reaction order exhibited variability with respect to CO2 partial pressure, gasification temperature, and biomass type. The reaction order associated with biomass char exhibited a higher value at the elevated CO2 partial pressure range (0.25–1.0MPa) relative to the low CO2 partial pressure range (0.025–0.1MPa). The nth-order model was employed to elucidate the gasification behaviors of biomass chars. The results indicated that the modified random pore model was successfully applied to model the gasification of CSC and TSC. The grain model was effective in predicting the gasification behavior of RHC. The gasification rates of the three biomass chars were accurately predicted by the Langmuir-Hinshelwood model at both low and high CO2 partial pressures. This study presents information on the effect of CO2 partial pressure on biomass char gasification and methods for predicting biomass char gasification under pressurized conditions.

Reaction kinetics and mechanisms for carbon-negative chemical looping gasification of biomass coupled with CO2 splitting

Reaction kinetics and mechanisms for carbon-negative chemical looping gasification of biomass coupled with CO2 splitting

Modeling investigation on biomass gasification coupled with chemical looping oxygen uncoupling

Modeling investigation on biomass gasification coupled with chemical looping oxygen uncoupling

Thermodynamic, economic, and environmental analysis of a biomass gasification power plant based on the Allam cycle

Thermodynamic, economic, and environmental analysis of a biomass gasification power plant based on the Allam cycle

Adaptation of an additively manufactured reactor concept for catalytic methanation with in-situ tar co-reforming of biogenic syngas

The methanation of biogenic syngas for GreenLNG production is a promising alternative for fossil gas. The market price of renewable methane is currently still too high to compete with fossil LNG. One of the reasons for that is the extensive gas cleaning that is necessary for the methanation of syngas from the thermochemical gasification of biomass. A main cost factor is the removal of tar components. As part of the Horizon Europe project CarbonNeutralLNG, we propose a 3D-printed methanation reactor, which makes use of the freedom in design gained by the additive manufacturing process in order to adapt the reactor design for the in-situ co-reforming of tars. The reactor uses heat pipes and a conically widened reaction channel to effectively control local temperatures, suiting the needs of the methanation reaction. A temperature hot spot near the inlet provides the necessary conditions (high temperature, a suitable catalyst and sufficient residence time) for the reforming of tar species, that are present in the syngas. Two reactor concepts are proposed. ADDmeth3.1 uses a dedicated internal channel structure that serves as a counter-current heat exchanger for the feed gas, whereas ADDmeth3.2 is optimized to fill the triangular footprint of a scalable reactor module as best as possible. Both designs were subject to a preliminary feasibility study, to ensure sufficient heat removal and a finite element analysis regarding structural stability was performed. Minimum safety factors against yielding of 3.53 and higher were achieved even without the internal diamond lattice support structure. The triangular modular reactor cell can easily be scaled up by connecting multiple cells in parallel, since the triangular shape can be extended efficiently into a honeycomb pattern.

Study on the comprehensive influence of Si-Al-based additives on hydrogen production and K deposition during biomass gasification

Green hydrogen production through gasification is a prospective utilization of biomass. Operational issues (slagging, corrosion and catalyst poisoning) due to inherent alkali metal deposition are main factors affecting gasification. The adoption of Si-Al-based additives as alkali metal inhibitors is a promising approach. In this work, the influence of additive types and placement methods on K deposition and gasification characteristics were studied through a decoupled gasification with online analysis. As a result, separative placement (Sep) method could reduce K deposition without decreasing hydrogen yield compared to mechanical mixture (Mix) method. This advantage is particularly prominent in char gasification. SiO2 is recommended to be added by the Mix to react with alkali and alkaline earth metal species individually to inhibit K release. This match could reduce peak of K deposition content by 55.80 % with less impact on hydrogen yield. Meanwhile, Al2O3 is recommended to be added by the Sep due to its unique comprehensive performance, which could increase hydrogen yield by 4.34 % and reduce peak of K deposition content by 52.72 %. Two recommended addition strategies could be used in different scenarios. This study is expected to guide the design of corrosion-resistant reactors and multifunctional catalysts.

A highly integrated ceramic membrane‐based reactor for intensifying the biomass gasification to clean syngas

AbstractBiomass gasification for syngas production is a key operating unit in the biomass utilization process. However, its overall efficiency and stability are often restricted by the presence of complex impurities, including particulate matters (PMs) and tars. In this study, a highly integrated ceramic membrane‐based reactor was developed for high‐temperature syngas cleaning, enabling the efficient in situ removal of PMs and tars from bio‐vapors produced by biomass gasification. Specifically, a silicon carbide (SiC) membrane could separate PMs from biomass volatiles in situ, while a structured Ni15La5/S1‐SiC catalyst (nickel and lanthanum‐laden silicalite‐1 zeolite supported on SiC foam) facilitated the catalytic reforming of tars. Compared to other control reactors (i.e., those containing either a membrane or catalyst alone), the integrated reactor showed synergistic intensification in producing clean syngas from biomass gasification, achieving PM and tar removal efficiencies of up to ~97% and ~90%, and exhibited excellent stability in five‐cycle evaluations at 800°C.

Thermochemical Conversion of Biomass into 2nd Generation Biofuel

Bioenergy is considered the largest contributor to the renewable and sustainable energy sector worldwide, playing a significant role in various energy sectors such as heating, electricity supply, and even in replacing fossil fuels in the transportation sector. As part of renewable, low-carbon energy systems, bioenergy can also ensure atmospheric carbon sequestration, provide numerous environmental and socio-economic benefits, and thus contribute to achieving global climate change goals, as well as broader environmental, social, economic, and sustainable development objectives. The use of bioenergy can significantly reduce our carbon footprint and thus contribute to improving the environment. While bioenergy conversion of biomass produces some amount of carbon dioxide, similar to traditional fossil fuels, its impact can be minimized by replacing forest biomass with fast-growing trees and energy crops. Therefore, fast-growing trees and energy crops are the primary raw materials for bioenergy. The results of the research in this publication confirm the high efficiency of biomass depolymerization through thermochemical conversion. The principle of continuous biomass conversion was used at a process temperature of 520 °C. The experiments were carried out in the Biomass Gasification Laboratory at the AgroBioTech Research Center of the Slovak University of Agriculture in Nitra. The biomass used for the experiments was from energy-producing fast-growing willows, specifically the varieties Sven, Inger, and Express. The aim was to determine the amount of biochar produced from each of these tree species and subsequently to investigate its potential use for energy purposes. During the experiments, 0.106 kg of biochar was produced from 1 kg of Inger willow biomass, 0.252 kg from 1 kg of Express willow biomass, and 0.256 kg from 1 kg of Sven willow biomass. A subsequent goal was to determine the production of gas, which can also be used for energy purposes. The biofuel samples obtained were subsequently subjected to thermogravimetric analysis to determine moisture content, volatile matter, and ash content. The ash content in dry matter ranged from 6% to 7.28%, while the volatile matter in dry matter was between 92.72% and 94%. The moisture content in the samples ranged from 1.7% to 2.43%. These results may contribute to innovative insights into biomass depolymerization and help define optimized parameters for thermochemical conversion, as well as the required biomass composition, with the goal of generating second-generation biofuels in the most cost-effective way.

Modeling Framework for the Assessment of a Sustainable Hydrogen Production and Supply Chain Network in California

The cost-effective and sustainable deployment of hydrogen supply and demand networks, especially in large economic regions like California, can be challenging considering the spatial-temporal availability and variability of the different actors across the network such as production processes, distribution modes, and end-users. In this presentation, we will provide an overview and demonstration of a modeling framework used to assess the environmental, economic, and human health impacts of plausible hydrogen production and supply chain networks in California. Scenarios focus on green hydrogen production pathways using water electrolysis and biomass gasification. End-use applications included in the model are transit, medium and heavy-duty trucking, port authorities, and power and aviation companies that currently consume natural gas, diesel, and aviation fuel for their day-to-day operation. Representative locations for hydrogen production and end-use are based on recent projections of the hydrogen economy in California. All mass and energy flows, as well as estimated emissions, are based on H2A process model designs and projections of technology performance, literature review, and LBNL process, economic and life cycle modeling, and not on company data for the sake of this presentation. Human health impacts are included following methodologies developed for the University of California Irvine HyDeal project. Life cycle phases associated with hydrogen production include feedstock preparation (water and biomass), energy production and consumption (renewable, grid, and combination of renewable and grid electricity), maintenance (chemical utilization in electrolysis and natural gas combustion in gasification), carbon sequestration, hydrogen storage (compression and liquefaction), and distribution (truck and pipeline). We apply the framework utilizing California specific emission factors, financial data, and human health damages and explore the impact of network characteristics on results. Example variations include: the inclusion of policy incentives or not, different representations of the electricity grid and source, electrolysis versus gasification versus combinations of both for production, liquefaction versus compression based on producer capacity cutoffs, transportation truck versus pipeline based on existing infrastructure, and ultimate end use. Comparison of these different scenarios can help inform future projects by demonstrating the trade-offs among environmental, economic, and human health impacts. This model, automated in R, is a starting platform upon which new analysis, modeling capabilities, locations, and emission factors can be rapidly tested and integrated.

2-D CFD modeling of gasification of a large biomass char particle in CO2 environment

There is a dearth in the literature of simple but robust models for gasification of large biomass particles that can address all important aspects of the reaction. A transient two-dimensional single-particle model of biomass gasification in the CO2 environment was developed in this work that incorporates chemical kinetics and heat transfer resistances, mass transfer inside the particle and boundary layer, non-equimolar counter diffusion including Knudsen diffusion, spatiotemporal variation in specific char surface area and thermophysical properties. The model was validated extensively with experimental results. Detailed simulation was carried out at reactor temperatures of 923–1123 K) using COMSOL Multiphysics software for two biomass samples – casuarina and acacia. Simulated conversion, reaction rate, temperature and gas composition profiles revealed that the reactions initially followed a shrinking core model, shifting subsequently to a shrinking reactive core model. Sensitivity analysis identified the sensitivities of process parameters as: reactor temperature > particle diameter (constant length) > initial specific char surface area > porosity > pore parameter > particle diameter (constant volume). Casuarina was found to be a more reactive and better-suited biomass than acacia for gasification applications. The work has furnished important guidelines for selecting suitable biomass type and process parameters to design an appropriate gasifier for industrial use.

Combustion versus Gasification in Power- and Biomass-to-X Processes: An Exergetic Analysis.

Residual biomass is a promising carbon feedstock for the production of electricity-based organic chemicals and fuels since, unlike carbon dioxide captured from point sources or air, it also has a valuable energy input. Biomass can be converted into an intermediate stream suitable for Power-to-X processes mainly via combustion or gasification. Such combined processes are generally called biohybrid or Power- and Biomass-to-X processes. To investigate the potential of biomass utilization in Power- and Biomass-to-X processes and identify inherent efficiency differences between these pathways, we model the process units with simple mass and energy balances considering empirical parameters for the key process units and perform an exergetic analysis. The analysis is conducted for several molecules of interest for the chemical and transport sectors with different C:H:O ratios, i.e., methane, methanol, dimethyl ether, and dodecane. For all considered products, the Power- and Biomass-to-X processes with biomass gasification, either with pure oxygen or steam as oxidizing agents, have a significantly higher (∼15-20 percentage points) exergy efficiency. This difference is mainly due to the lower exergy loss for water electrolysis since a lower amount of hydrogen is needed and to the higher exergy efficiency of the gasification unit compared to that of the combustion unit. Therefore, gasification-based Power- and Biomass-to-X processes have clear thermodynamic advantages in the ideal case. These conclusions obtained with the simple models are confirmed by modeling a Power- and Biomass-to-Methanol process in detail, also accounting for practical factors such as side reactions, incomplete reactant conversion, and ash formation.

Transient biomass-SOFC-energy storage hybrid system for microgrids peak shaving based on optimized regulation strategy

To address the issues of energy supply instability and peak-shaving in remote microgrids, this paper proposes a biomass-SOFC (Solid Oxide Fuel Cell) -energy storage hybrid system to meet the power demands of the microgrids. Additionally, it integrates the long short-term memory (LSTM) prediction algorithm for peak shaving in the microgrids. Firstly, transient models of biomass gasifier and SOFC and the vanadium redox flow battery (VRFB) model are established, and the experimental results are used to verify the models. Subsequently, the dynamic responses and sensitivity analysis of the biomass gasification process and the internal temperature field of the SOFC are investigated. Next, an analysis is conducted of the differences in VRFB parameters obtained based on the forecasted load and the real load. Finally, the ultimate peak regulation strategy is determined, and the VRFB parameters are reasonably designed. The research results indicate that, following optimization, the designed capacity and maximum power of the VRFB are 6.7 MWh and 1.5 MW, respectively. This result represents a reduction of 23 % and 11.76 % compared to the values before optimization, leading to a total investment decrease of 26.21 % for the energy storage system. In addition, the annual profit from the peak shaving operation of the system is 189,879 dollars.