Types Of Biomass Research Articles

Comprehensive evaluation of a new integrated ORC-VCR system with a thermoelectric generator unit combining sustainable energies for hydrogen production

Recently, there has been a growing emphasis on the efficient generation of energy from sustainable sources. This study aims to evaluate a new combined Organic Rankine Cycle-Vapor Compression Refrigeration (ORC-VCR) system from energy, exergy, economics, and environmental perspectives. The system has been designed to cogenerate power, heat, cooling, and hydrogen using solar and biomass energy. To enhance efficiency, a Thermoelectric Generator (TEG) unit has been integrated into the system. The power produced by the TEG is used to generate hydrogen in the Proton Exchange Membrane Electrolyser (PEME). To ensure the continuous operation of the solar collector, especially under conditions of unstable and intermittent solar radiation, a thermal storage tank and a biomass-fired boiler utilizing four different types of biomass (wood, paper, municipal solid waste, and sawdust) have been incorporated. The primary objective of this research is to investigate the impact of employing various biomass types on the system's performance. The results indicate that in terms of energy and exergy, municipal solid waste yields the highest system efficiency. However, from an environmental viewpoint, paper incurs lower pollutant emissions. The proposed hybrid system can produce 145.5 kW of cooling, 513.6 kW of heat, 37.93 kW of electricity, and 0.756 kg/h hydrogen with energy and exergy efficiencies of 32.73% and 14.18%, respectively. The estimated total equipment cost is 7.67$/h, with a CO2 emission of 0.0029 kg/s.

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

AbstractVegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Maximizing the valorization potential of lignin through optimization of the Soda pulping conditions

The valorization potential of lignin is strongly dependent on the yield that can be obtained during the pulping process as well as its chemical structure. Both of these are determined by factors such as the biomass type, the selected extraction strategy and the employed conditions. Within this study, Miscanthus x giganteus biomass was subjected to systematically varying Soda pulping conditions, i.e., temperature (100 °C – 180 °C), OH– concentration (0.158 mol/L – 1.000 mol/L) and time (60 min – 360 min). These pulping conditions can be combined into a single factor, reflecting the processing severity, which in this work varied from approximately 1 to 5. The resulting black liquor, precipitated lignin, lignin stock solution (i.e., lignin dissolved in the solvent used in the subsequent depolymerization step) and product pool after mild reductive catalytic depolymerization (200 °C, 10 bar H2 initial, 4 h) were thoroughly characterized using a plethora of analysis techniques. Increasing the severity factor of the pulping was found to result in an enhancement of the delignification degree from 25.3 ± 2.6 % to 95.4 ± 9.9 %. However, beyond a severity factor of 3, fragmentation of native ether linkages and condensation reactions start to cause unfavourable changes in the chemical structure of the lignin and depolymerization product pool. Furthermore, these reactions significantly reduce the total mass yield from biomass to depolymerization product pool. An Adaboost model with quadratic base estimator was trained against the experimental data, and subsequently used to optimize the pulping conditions, aiming at a maximum total mass yield with minimal fragmentation and, hence, condensation, of the lignin. The optimum was experimentally validated, which resulted in a lignin with high β-O-4 content (42.7 ± 2.8 linkages per 100 aromatic units) and a total mass yield of 30.9 ± 3.4 wt% and a pulp with a residual lignin content of 8.25 ± 0.94 wt%.

Production of lignin-containing nanocellulose from six types of unpretreated lignocellulosic biomass by a one-step process

Lignin-containing nanocellulose (LCN) shows great potential in the fabrication of high performance bio-based materials, and suitable raw materials may achieve the production of LCN in a more economical approach. Therefore, in this study, the morphology, chemical and supramolecular structure of six types of lignocellulosic biomass (Broussonetia papyrifera bark, moso bamboo, rattan, balsa wood, poplar wood and fir wood) were analyzed for the production of LCN by using pure oxalic acid dihydrate (OAD). The results revealed that BPBs is a natural available cellulose-rich materials with extremely high cellulose content, low lignin content, and loosely connected cellulose chains. Compared with the other five types of lignocellulosic biomass materials, the hydrolysis of BPBs without any pretreatments by using OAD produced higher yield of LCN with much more uniform size distribution and smaller size. LCN from BPBs had higher crystallinity and thermal stability than that from the other five lignocellulosic biomass. The finding in this study indicated that Broussonetia papyrifera bark without any pretreatment was a favored material for high yield production of LCN compared with the other woody materials, which provided an economically realizable method on the efficient and high yield production of LCN from unpretreated BPBs by using OAD hydrolysis.

Utilizing Food Waste in 3D-Printed PLA Formulations to Achieve Sustainable and Customizable Controlled Delivery Systems.

This is the first study that explores blending polylactic acid (PLA) with various biomasses, including food wastes-brewer's spent grain (BSG), spent coffee grounds (SCG), sesame cake (SC), and thermoplastic starch (TPS) biomass to create composite gastric floating drug delivery systems (GFDDS) through 3D printing. The aim is to investigate the influence of biomass percentage, biomass type, and printing parameters on their corresponding drug release profiles. 3D-printed (3DP) composite filaments were prepared by blending biomasses and PLA before in vitro drug release studies were performed using hydrophilic and hydrophobic model drugs, metoprolol tartrate (MT), and risperidone (RIS). The data revealed that release profiles were influenced by composite compositions and wall thicknesses of 3DP GFDDS capsules. Up to 15% of food waste could be blended with PLA for all food waste types tested. Delivery studies for PLA-food wastes found that MT was fully released by 4 h, exhibiting burst release profiles after a lag time of 0.5 to 1.5 h, and RIS could achieve a sustained release profile of approximately 48 h. PLA-TPS was utilized as a comparison and demonstrated variable release profiles ranging from 8 to 120 h, depending on the TPS content. The results demonstrated the potential for adjusting drug release profiles by incorporating affordable biomasses into GFDDS. This study presents a promising direction for creating delivery systems that are sustainable, customizable, and cost-effective, utilizing sustainable materials that can also be employed for agricultural, nutraceutical, personal care, and wastewater treatment applications.

Comprehensive Experimental Study of Biomass Conversion Behavior: From Particle Phenomena to Reactor Scale

During biomass combustion in a grate-fired boiler, each particle undergoes a sequence of different reactions, and the phenomena differ from the conversion of a single, thermally thin, particle. Hence, this paper aims to deepen the understanding of biomass conversion processes and provides valuable insights for advancing biomass-based energy systems. Firstly, the weight loss characteristics of the larger particles of eucalyptus, pine, acacia, and olive samples were investigated at different isothermal temperatures in a purpose-built reactor that simulates the devolatilization process in a controllable manner. As opposed to the thermogravimetric analysis using thermally thin particles, it was concluded that all fuels show that the combustion of large particles does not exhibit separate consecutive conversion stages, due to internal diffusion resistance. Furthermore, it was verified that the devolatilization rate depends mainly on the reactor temperature, and, consequently, the mass-loss profile is independent of the biomass type. In addition to these experiments, the composition of the gases over the devolatilization period was analyzed for the main fuel used in power plants, eucalyptus. Once again, a strong correlation to the reactor temperature was observed, with CO2 and CO always being the main devolatilization products. The temperature dependence of both compounds presented an increase from 8 to 13% between 600 and 800 °C for CO, while the CO2 yield only slightly increased from 11 to 12%. These observations were essential to identify the transport phenomena effect and the gaseous products released during the biomass combustion.

Current Trends in the Use of Biomass in the Manufacture of Rigid Polyurethane Foams: A Review

This paper discusses methods of using biomass from the agriculture, forestry, food and aquaculture industries as potential raw materials for bio-polyols and as fillers in the production of rigid polyurethane (RPUR) foams. Various aspects of obtaining bio-polyols are discussed, as well as the impact of replacing petrochemical polyols with bio-polyols on the properties of foams. Special attention is paid to the conversion of vegetable oils and lignin. Another important aspect of the research is the use of biomass as foam fillers. Chemical and physical modifications are discussed, and important factors, such as the type and origin of biomass, particle size and amount, affecting the foaming process, microstructure and properties of RPUR foams are identified. The advantages and disadvantages of using biomass in foam production are described. It is found that bio-polyols can replace (at least partially) petrochemical polyols while maintaining the high insulation and strength of foams. In the case of the use of biomass as fillers, it is found that the shaping of their properties is largely dependent on the specific characteristics of the filler particles. This requires further research into process optimization but allows for the fine-tuning of RPUR foam properties to meet specific requirements.

Impact of woody biomass in the composition of coal-water suspensions on their transportation and combustion

Relevance. A promising fuel from an environmental point of view is coal-water suspensions. Multiple studies have shown that when they are burned, emissions of anthropogenic gases into the Earth's atmosphere are significantly reduced compared to emissions from coal burning. But the large-scale introduction of coal-water suspensions into the overall balance of energy production is difficult due to a significant delay in their ignition, which can reach several tens of seconds at relatively low oxidizer temperatures (Tg≤1073 K). One of the possible ways to solve this problem is the use of new technologies for preparation for combustion, for example, the use of additional microwave heating of fuel and the introduction of special additives into the composition of coal-water suspensions, which accelerate their ignition. The introduction of such additives into the fuel composition can lead to a significant change in the rheological characteristics. Aim. To determine the degree of impact of the concentration and type of wood additive in the composition of the coal-water suspension on the rheological characteristics of droplets of coal-water fuel, as well as the possibility of reducing the duration of thermal preparation of the latter when exposed to microwave heating. Object. Water-coal suspension based on long-flame thermal coal and on long-flame thermal coal with the addition of sawdust and pine needles (Bio-water-coal suspension). Methods. Experimental studies to determine the time characteristics of water-coal suspension ignition were carried out using a high-speed video camera FASTCAM. Fuel combustion was carried out in a flow-through combustion chamber equipped with magnetrons for additional microwave heating of the fuel. Dynamic viscosity was determined using a Brookfield RVDV-II + Pro viscometer. Results. It has been established that the addition of microwave heating can significantly (up to 15%) reduce the ignition delay of water-coal suspension and Bio-water-coal suspension at relatively low oxidizer temperatures (673 K). Experimental studies shown that the type of biomass affects the time characteristics of fuel ignition at ambient temperatures up to 753 K; with a further increase in the temperature of the oxidizer, the type of additive does not have a significant effect. It is shown that when studying the rheological characteristics of the water-coal suspension, the dynamic viscosity of Bio-water-coal suspension does not go beyond the characteristic value of 1200 Pa s at a shear rate of 100 rpm when no more than 2% of pine sawdust and no more than 6% of pine needles are introduced into the water-coal suspension.

Biochar from Co-Pyrolyzed Municipal Sewage Sludge (MSS): Part 1: Evaluating Types of Co-Substrates and Co-Pyrolysis Conditions.

With the increasing production of municipal sewage sludge (MSS) worldwide, the development of efficient and sustainable strategies for its management is crucial. Pyrolysis of MSS offers several benefits, including volume reduction, pathogen elimination, and energy recovery through the production of biochar, syngas, and bio-oil. However, the process can be limited by the composition of the MSS, which can affect the quality of the biochar. Co-pyrolysis has emerged as a promising solution for the sustainable management of MSS, reducing the toxicity of biochar and improving its physical and chemical properties to expand its potential applications. This review discusses the status of MSS as a feedstock for biochar production. It describes the types and properties of various co-substrates grouped according to European biochar certification requirements, including those from forestry and wood processing, agriculture, food processing residues, recycling, anaerobic digestion, and other sources. In addition, the review addresses the optimization of co-pyrolysis conditions, including the type of furnace, mixing ratio of MSS and co-substrate, co-pyrolysis temperature, residence time, heating rate, type of inert gas, and flow rate. This overview shows the potential of different biomass types for the upgrading of MSS biochar and provides a basis for research into new co-substrates. This approach not only mitigates the environmental impact of MSS but also contributes to the wider goal of achieving a circular economy in MSS management.

Harnessing the potential of agriculture biomass: reuse, transformation and applications in energy and environment.

Biomass, an organic matter, has gained worldwide attention due to the overconsumption of fossil fuels. Biomass has emerged as a new alternative resource with implications for efficient energy production, environmental benefits and socio-economic impacts. According to the World Bioenergy Association, biomass has accounted for 14% of the energy supply in 2016 and is expected to provide 44% of the energy demand by 2030. This literary endeavour comprises insights into past developments, including biomass types, characterization methods and conversion technologies. This review article aims to facilitate a deeper understanding of agriculture biomass utilization and its significance in achieving sustainable development goals by analysing the latest research findings. Moreover, the emerging role of biosensors in optimizing biomass utilization and monitoring environmental impacts has been documented. The scope embraces the vast realm of bioenergy production, environmental mitigation and the generation of valuable by-products. In conclusion, portraying biomass conversion technologies as the transition towards cleaner, renewable energy, the potential benefits and challenges extend beyond energy production, encompassing effective agricultural residue management and the creation of valuable by-products. This review will guide the researchers and stakeholders towards a deeper understanding of the transformative potential embedded in biomass conversion processes for a sustainable and cleaner energy future.

Key Takeaways on the Cost-Effective Production of Cellulosic Sugars at Large Scale

The production of cellulosic sugars in lignocellulose biorefinery presents significant economic and environmental challenges due to the recalcitrant nature of biomass. The economic and facile production of renewable sugars with high yield and productivity is pivotal for the success of biorefinery. The cellulosic sugars are valorized either by biochemical routes or chemical routes or by hybrid (biological and chemical) routes into renewable chemicals, fuels, and materials. This manuscript focuses on the critical parameters affecting the economic viability of cellulosic sugar production at large scale, including biomass-specific pretreatment strategies and enzyme cost efficiency. High pretreatment costs, carbohydrate loss, and inhibitors production during pretreatment are identified as major contributors to overall production costs. To address these issues, we highlight the importance of developing cost-effective and efficient pretreatment methods tailored to specific biomass types and strategies for enzyme reuse and recycling. Future research should focus on innovations in pretreatment technologies, improved logistics for high-density feedstocks, biomass feeding systems, and advancements in enzyme technology to enhance the economic and environmental sustainability of lignocellulosic biorefineries. The findings highlight the need for continued innovation and optimization to make the commercial-scale production of cellulosic sugars more viable and sustainable.

Evaluation of Multi-Crop Biofuel Pellet Properties and the Life Cycle Assessment

Although wood biomass is mostly used to produce solid biofuel pellets, it is important to evaluate the possibilities of using other types of biomass as well. It is not only important to obtain biofuel pellets of suitable quality but also to ensure a sustainable process of producing and using these pellets for energy production. This paper presents an evaluation of the quality characteristics of seven different biofuel pellets made from multi-crop plants (fibrous hemp, maize, and faba bean) and a life cycle assessment (LCA) of the heat production by burning these pellets. The physical-mechanical properties and elemental composition of the pellets are determined according to international standards, as indicated in the methodology section. The LCA was performed using the SimaPro 9.5 software. The complete life cycle from cradle-to-grave is assessed, i.e., from growing plants to spreading ash obtained from pellet burning. An analysis showed that in most cases the produced pellets met the requirements of the standard ISO 17225-6:2021. The lowest negative environmental impact associated with the production of 1 GJ of thermal energy was for pellets made from fibrous hemp and maize biomass (MIX2-1) and pellets made from fibrous hemp and faba bean biomass (MIX2-3). Production of pellets from maize biomass (S-Mz) was found to have the highest carbon footprint (29.1 CO2eq GJ−1) and was associated with the lowest crop yield compared to the other six scenarios.

Thermomechanical and thermodynamic analysis of the sintering process of Mn-based oxygen carrier in chemical looping gasification of biomass

The Mn-based oxygen carrier (OC) owns a great oxygen carrying capacity and a high reactivity in the chemical looping gasification of biomass. However, the sintering of the Mn-based OC can cause serious defluidization or even the shut-down of the biomass chemical looping gasifier. In this study, the sintering kinetics and mechanism of Mn-based OC in the gasification of two typical biomass ash were revealed by thermomechanical and thermodynamic analysis. It revealed that the manganese silicate was converted to iwakiite (MnFe2O4) and liquid at high temperatures in the high-Mn OC (OC2), leading to the liquid sintering mechanism and high apparent activation energy of sintering (Es), with a maximum shrinkage rate of 6.14 %/oC. Conversely, the solid sintering mechanism of the low-Mn OC (OC1) was attributed to the FeMn2O4 crystallization, leading to a low shrinkage rate (The maximum shrinkage rate was 0.30 %/oC). The sintering rate of Mn-based OC was closely related to the liquid content, and the biomass ash addition advantaged the liquid formation. Therefore, the Es of OC1 was increased from 44 kJ/mol to 151 kJ/mol at the 15 wt% addition of corn straw ash, and Es of OC2 was increased from 72 kJ/mol to 93–107 kJ/mol at 20 wt% addition of biomass ash. Element distribution analysis supported that Ca in sawdust ash improved the bonding between Mn and Si, improving the Mn-based minerals crystallization and OC expansion. However, the K in corn straw ash facilitated the melting of rhodonite(MnSiO3), and the expansion of Mn-based OC was inhibited. This study provides valuable insights into the sintering mechanism of the Mn-based oxygen carrier and its relationship with liquid evolution behavior in the chemical looping gasification of biomass.

Experimental analysis of the effects of feedstock composition on the plastic and biomass Co-gasification process

Co-gasification is a feasible approach to manage fast-growing plastic and biomass waste issues. The current work examines air gasification of plastic waste blending with biomass. The influence of plastic-type and biomass characteristics on product distribution under the same operating condition was studied. Ethylene-vinyl acetate, high-density polyethylene, and polypropylene were the investigated plastics while the biomass materials considered were pine sawdust (PS), used ground coffee (UGC), and wheat straw (WS) are compared. Additionally, co-gasification and thermogravimetric analyses (TGA) of plastic and individual biomass components, namely, cellulose, hemicellulose, and lignin, were conducted to identify the nature of the synergy arising from plastic and biomass integration. Similarities in the chemical structure and composition of the investigated plastics resulted in the type of plastic marginally influencing product distribution. The gas composition included 4.6 vol% CH4, 37.5 % CO2, 5.3 % CnHm, 42 % CO, and 10.8 % H2, with yields of 5.9 wt% char, 39.5 wt% gas, and 54.8 wt% tar. Conversely, the type of biomass had a substantial effect on both gas composition and product yields. WS and UGC, characterized by higher hemicellulose and lignin content, generated more hydrogen with 14.4 and 13.3 vol%, respectively, and exhibited lower tar content (45.7 and 47.8 wt%) compared to PS, which has a higher cellulose content and yielded 54.8 wt% tar. During EVA/cellulose co-gasification, the predominant gases produced are CO and CO2, with H2 concentration of 7.2 vol%. In contrast, co-gasification of EVA/xylan and EVA/lignin yields 13.5 and 19.9 vol% hydrogen, respectively. Interactions and synergism between the plastic and biomass were found to be more intensified when the biomass contained greater proportions of cellulose and lignin. Co-gasification and TGA analyses indicated that plastic/cellulose and plastic/lignin interactions in the gas and solid phases (volatile-volatile and volatile-char interactions) and plastic/xylan interactions in the gas phase (volatile-volatile interactions) were significant. Modeling the predictability of the output data revealed that if interactions between the plastic and biomass components are accounted for, the co-gasification results are predictable with a credible accuracy for all biomass types. The predictability model offers a practical approach for selecting an appropriate co-gasification feedstock combination to give a targeted process performance.

Peat formation potential of temperate fens increases with hydrological stability

Peat formation is the key process responsible for carbon sequestration in peatlands. In rich fens, peat is formed by brown mosses and belowground biomass of vascular plants. However, the impact of ecohydrological settings on the contribution of mosses and belowground biomass to peat formation remains an open question. We established seven transects in well-preserved fens in NE Poland along an ecohydrological gradient from mesotrophic sedge-moss communities with stable water levels, to more eutrophic tall sedge communities with higher water level fluctuations. In each transect, we measured the production of brown mosses (using the plug method), aboveground vascular plant biomass (one year after cutting) and belowground biomass (using ingrowth cores). Decomposition rates of all biomass fractions were assessed using litter bags. The first-year surplus of potentially peat-forming fractions, i.e., mosses and belowground biomass, decreased with increasing water level fluctuations and along a vegetation gradient from sedge-moss to tall sedge communities. Moss production was highest in the sedge-moss fen with a stable water level at the ground surface. We did not detect any difference in belowground biomass production across the gradient but found it to be consistently higher in the upper 0–5 cm than in the deeper layers. The decomposition rate also showed no response to the gradient, but differed between biomass types, with aboveground biomass of vascular plants decomposing 2.5 times faster than belowground biomass and mosses. Pattern of peat formation potential along the ecohydrological gradient in rich fen was strongly driven by brown moss production. Sedge-moss fens with a stable water level at the ground surface have the highest peat formation capacity compared to other vegetation types. In the part of the gradient that is poorer in nutrients, vascular plants invest in belowground production, and mosses dominate the aboveground layer.

Predictive analysis of methane-enhanced conversion of organic waste into sustainable fuel: A machine learning approach

Currently, methane-assisted biomass-to-fuel (M-BtF) processes are being introduced, which are of considerable importance due to the production of an environmentally friendly fuel. Due to the lower price, natural gas can address a stronger potential compared to hydrogen and nitrogen under pyrolysis and bio-oil upgrading processes. Based on this, it seems vital to evaluate such a clean fuel production process from the standpoints of the life cycle analysis (LCA) and techno-economic assessment to exhibit the economic feasibility and environmental superiority. This article aims to utilize machine learning (ML) to predict the yield of organic solid waste, evaluate its economic feasibility, and investigate the environmental sustainability of the valorization of a methane-assisted organic solid waste process. The study employs an artificial neural network (ANN) model with a semi-automatic tuning procedure to forecast the yield of bio-oil, based on biomass characterization. This approach eliminates the need for pilot plant trials for new types of biomass to determine process yields before industrial scale-up. The ANN model demonstrated a high prediction accuracy, achieving an R2 (coefficient of determination) value higher than 0.82. The simulation results, derived from the ML predictions, were then employed in the techno-economic analysis and LCA, where they were compared with other commercial processes for economic viability and environmental impact assessments. The minimum selling price for the renewable diesel was calculated as 3.45 US$/gallon, which is notably competitive, being around 26 % lower than the average minimum selling price observed in relevant publications. Based on Monte Carlo simulation, the plant's internal rate of return (IRR) remained above 50 % across various discount rates, suggesting a highly profitable investment. From LCA results, the proposed method was found to emit ∼ 67 % less greenhouse gases (GHG) compared to standard commercial processes. Overall, the study showcases how the integration of machine learning into process simulation can lead to both economically and environmentally beneficial outcomes, particularly in the context of renewable energy production.

Evaluation of pyrolysis characteristics and kinetic parameters from several prospected biomass residues by thermogravimetric analysis

Abstract With fossil fuel supplies dwindling and persistent environmental concerns surrounding their consumption, biomass has emerged as a highly promising renewable energy source. Understanding the characteristics of biomass pyrolysis is crucial as it provides valuable insights and guidance for designing and optimizing the pyrolysis process. In this regard, a thermogravimetric assessment was conducted to evaluate the pyrolysis characteristics and kinetic parameters of four prospective biomass sources: Yang Na wood (Dipterocarpus alatus), palmyra palm shell, cotton stalk, and spent coffee grounds with a condition temperature range of 33 °C to 700 °C and a heating rate of 10 °C·min-1 in a nitrogen atmosphere. The kinetic parameters were evaluated using the Coats and Redfern methods, employing various reaction order models. The activation energy and pre-exponential factor were determined for the active pyrolysis stage. The results revealed that the high heating values for all samples ranged from 18.20 to 23.00 MJ·kg-1. Additionally, the onset temperature fell within the range of 243 to 254 °C, while the offset temperature ranged from 365 to 452 °C for all samples. The conversion rate at the offset temperature was 0.67 for Yang Na wood, 0.62 for palmyra palm shell, 0.65 for cotton stalk, and 0.74 for spent coffee grounds. Moreover, the activation energies were measured as 46.47 kJ·mol-1 for Yang Na wood, 52.46 kJ·mol-1 for palmyra palm shell, 64.20 kJ·mol-1 for cotton stalk, and 69.01 kJ·mol-1 for spent coffee grounds. The higher activation energy corresponded to a higher pre-exponential factor. In conclusion, the pyrolysis characteristics and kinetic parameters of the four types of biomasses have been found to be favourable, indicating their potential for promotion and application as a raw material for the pyrolysis process.

Economic and Ecological Aspects of Combustion of Selected Types of Biomass in Low-Power Heating Boilers

Economic and Ecological Aspects of Combustion of Selected Types of Biomass in Low-Power Heating Boilers

Optimizing Biomass Supply Chains to Power Plants under Ecological and Social Restrictions: Case Study from Poland

The growing demand for social and regulatory forest ecosystem services can significantly modify the availability and cost of biomass for energy purposes. This article presents a model for optimizing biomass supply chains using a linear programming framework integrated with a geographic information system (GIS). Based on a given type of biomass resource, its calorific value, price, distance from the power plant, and transportation costs, the model identifies the optimal source of biomass, allowing it to cover the demand for the required total energy value with the lowest possible costs. The case study includes the Połaniec power plant in southeastern Poland and potential sources of forest biomass and agricultural straw within 100 km of the plant. The impact of constraints on the availability and cost of biomass was analyzed in the following scenarios: (1) all forest and agriculture biomass is available, (2) forest area in Natura 2000 network is excluded, and (3) firewood and forests with dominated ecological and social function are excluded. Unit costs of biomass varied depending on biomass availability and energy demands. The lowest unit costs of biomass (3.19 EUR/MJ) were for energy demand at the level of 1 TJ yearly for all kinds of biomass and the highest (4.91 EUR/MJ) for ecological and social constraints and energy demand 4 TJ. As energy demand increased, unit costs increased, and the ability to meet this demand with just one type of biomass decreased. The energy biomass sector can utilize the model to benefit both biomass producers and their final buyers.

Prediction of the minimum fluidization velocity of different biomass types by artificial neural networks and empirical correlations

PurposeThis paper aims to analyze the performance of artificial neural networks with filling methods in predicting the minimum fluidization velocity of different biomass types for bioenergy applications.Design/methodology/approachAn extensive literature review was performed to create an efficient database for training purposes. The database consisted of experimental values of the minimum fluidization velocity, physical properties of the biomass particles (density, size and sphericity) and characteristics of the fluidization (monocomponent experiments or binary mixture). The neural models developed were divided into eight different cases, in which the main difference between them was the filling method type (K-nearest neighbors [KNN] or linear interpolation) and the number of input neurons. The results of the neural models were compared to the classical correlations proposed by the literature and empirical equations derived from multiple regression analysis.FindingsThe performance of a given filling method depended on the characteristics and size of the database. The KNN method was superior for lower available data for training and specific fluidization experiments, like monocomponent or binary mixture. The linear interpolation method was superior for a wider and larger database, including monocomponent and binary mixture. The performance of the neural model was comparable with the predictions of the most well-known correlations from the literature.Originality/valueTechniques of machine learning, such as filling methods, were used to improve the performance of the neural models. Besides the typical comparisons with conventional correlations, comparisons with three main equations derived from multiple regression analysis were reported and discussed.