Biomass Properties Research Articles

Acclimatization of a sequencing batch vertical oxidation pond with simulated agricultural wastewater using duckweed as vegetation: analysis of efficiency, Biomass, and Soil properties.

Vertical oxidation pond operated in sequencing batch mode (HRT: 1.25day) with duckweed as the vegetation was used to acclimatize with simulated agricultural wastewater. The maximum removal rate of urea [371g/(m3.d)] and COD [222.4g/(m3.d)] were observed at moderate concentrations of urea (500mg/L), N-P-K (60mg/L), and pesticide (20mg/L). Inhibition and toxicity posed by higher concentrations, decreased the removals of urea (83% to 61%), COD (81% to 51%), and TDS (76% to 50%) at the end of the acclimatization. Steady removal (> 99%) of PO43--P was observed during acclimatization. Effluent pH increased due to the generation of NH4+-N (maximum 370 ± 5mg/L) from the assimilation of urea. Oxidation of ammonia led to the maximum generation of NO2--N and NO3--N of 10mg/L and 9mg/L, respectively. Particles less than 300μm increased, and both specific gravity (from 2.62 to 2.42) and maximum dry density (from 1.73 to 1.30g/cm3) of the base soil decreased with an increase in urea, N-P-K, and pesticide. Reactor biomass increased (1.42 to 1.90g/L) up to initial concentrations of urea (500mg/L), N-P-K (60mg/L), and pesticide (20mg/L), then decreased (1.68g/L) with an increase in concentration.

Interpretable machine learning model for activation energy prediction based on biomass properties

A thorough understanding of pyrolysis kinetics for biomass is crucial for the process design, feasibility assessment, and scale-up in industrial scenarios. To reduce the time and economic cost invested in obtaining experimental kinetic data by performing the thermogravimetric analysis, a data-driven machine learning method was proposed in the present work. Random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGB) algorithms were utilized to predict the activation energy versus conversion range with ten input features from biomass characteristics. Among these XGB has shown the most competitive prediction accuracy with a coefficient of determination (R2) higher than 0.98 and a root mean squared error (RMSE) = 7.7 kJ/mol. To enhance the model interpretability of the derived model, a visualized analysis for individual impact and interactions of variables was conducted by Shapley additive explanation (SHAP). The top three significant inputs for the model established by the current dataset are conversion rate, volatile content, and moisture content. This work provides a quick and accurate kinetic prediction method for unexploited biomass and favors detailed insights into the complicated associations between biomass characteristics and pyrolysis kinetics.

Enhanced sludge granulation and stable performance of an anammox expanded granular sludge bed (EGSB) reactor through the utilization of hydroxyapatite (HAP) particles

The reuse of hydroxyapatite particles (HAPs) as a granulation activator for anammox sludge was explored to address the remaining issues of time-consuming and unstable granular structure in anammox granulation. During the granulation, nitrogen removal capacity from 2.8 to 13.7 gN/L/d was obtained within 193 days, accompanied by an enhancement in bio-activity from 0.23 to 0.52 gN/gVSS/d. HAPs and anammox microorganisms coupled well to aggregate into granules for denser biomass, higher settleability, and stronger mechanical properties, which effectively improved the biomass retention capacity and structural strength of the sludge system. A skeleton structure formed by the HAPs was characterized during the transformation of the granules, playing a crucial role in strengthening the stability of the sludge. The intermediate processes of granulation were thus clarified to propose an evolutionary pathway for anammox-HAP granules. The pre-addition of HAPs is conducive to achieving faster anammox granulation and rapid process start-up for high-strength wastewater treatment.

Relationship Between Fine Root Biomass and Soil Physico-chemical Properties of Grassland Ecosystem in Bhadrapur Municipality of Jhapa district, Eastern Nepal

This study investigated the distribution of fine root biomass and various soil properties in a grassland ecosystem within Bhadrapur Municipality, Nepal. Soil samples were systematically collected from randomly selected blocks in undisturbed, disturbed, and roadside areas during the late rainy season. Analyses included soil texture, moisture content, temperature, pH, and quantification of fine root biomass (FRB; <5 mm diameter) within the top 15 cm soil depth. Results showed the mean FRB was significantly higher in undisturbed areas (7.77 t/ha) compared to disturbed (7.053 t/ha) and roadside (1.76 t/ha) areas. Across all sites, FRB exhibited a positive correlation with soil moisture content. Soil pH was slightly more acidic in undisturbed versus disturbed and roadside areas. Soil temperature demonstrated a positive correlation with FRB in undisturbed and roadside areas but a negative correlation in disturbed areas. Additionally, FRB negatively correlated with sand content in disturbed and roadside areas. The findings highlight how soil moisture is a key driver of fine root proliferation in this grassland ecosystem. Variations in soil texture, pH, and temperature between sites reveal their influence on root growth dynamics. Understanding these root-soil interactions has implications for sustainable grassland management, biodiversity conservation, and ecosystem resilience under changing environmental conditions.

A Feasibility Study of Bio-Briquettes Production from the Skin and Epidermis Layer of Cassava (Manihot esculenta) as An Alternative Energy

Unprocessed leftover cassava wastes from the home industries in Pomahan Village in Bojonegoro, East Java, has become a serious problem as a pollutant to the environment. This study examined the quality of bio-briquettes made from cassava skin waste with its epidermis starch as an adhesive agent, or binder. The aim is to assess the quality of the bio-briquettes for alternative energy sources and their suitability from an economic point of view. The utilized research method was a descriptive quantitative approach by measuring water and ash content, calorific value test, and economic feasibility calculation. The results indicated that the highest calorific value of 5337.83 cal/g was obtained from a bio-briquette mix of 50 g cassava skin with 5% epidermis starch binder. This bio-briquette also possesses the lowest water and ash contents of 2.75 and 8%, respectively, compared to other mixtures. The economic feasibility calculation showed a BEP value of 423 kg/ month, B/C Ratio of 6.14-fold, ROI of 30%, and PBI of 0.2 years. In conclusion, cassava-based bio-briquettes are economically promising and environmentally friendly due to their biomass property and help to tackle the environmental problem due to the cassava waste.

A critical review on the influence of operating parameters and feedstock characteristics on microwave pyrolysis of biomass.

Biomass pyrolysis is the most effective process to convert abundant organic matter into value-added products that could be an alternative to depleting fossil fuels. A comprehensive understanding of the biomass pyrolysis is essential in designing the experiments. However, pyrolysis is a complex process dependent on multiple feedstock characteristics, such as biomass consisting of volatile matter, moisture content, fixed carbon, and ash content, all of which can influence yield formation. On top of that, product composition can also be affected by the particle size, shape, susceptors used, and pre-treatment conditions of the feedstock. Compared to conventional pyrolysis, microwave-assisted pyrolysis (MAP) is a novel thermochemical process that improves internal heat transfer. MAP experiments complicate the operation due to additional governing factors (i.e. operating parameters) such as heating rate, temperature, and microwave power. In most instances, a single parameter or the interaction of parameters, i.e. the influence of other parameter integration, plays a crucial role in pyrolysis. Although various studies on a few operating parameters or feedstock characteristics have been discussed in the literature, a comprehensive review still needs to be provided. Consequently, this review paper deconstructed biomass and its sources, including microwave-assisted pyrolysis, and discussed the impact of operating parameters and biomass properties on pyrolysis products. This paper addresses the challenge of handling multivariate problems in MAP and delivers solutions by application of the machine learning technique to minimise experimental effort. Techno-economic analysis of the biomass pyrolysis process and suggestions for future research are also discussed.

Comprehensive study of thermochemical conversion of biomass okara into biochar

Pyrolysis is one of the thermal conversion pathways to convert biomass into biochar. The characteristic of biochar depends on three parameters, i.e., before pyrolysis (drying methods of biomass), during pyrolysis (temperature), and after pyrolysis (activation agents). Thermal and non-thermal drying methods remarkably affected the psychochemical properties of biomass. Pyrolysis temperature significantly governed the biochar production. Temperature above 500 °C was required to convert biomass okara into biochar. Activation agent determined the pore characteristic of biochar. FT-IR, XRD, TGA-DSC, SEM, Raman, XRF, CHNOS Analyzer, Surface area analysis, and TEM characterizations of material confirmed that implemented the three parameters simultaneously were essential to achieved different properties of biochar that could be used in environmental remediation or energy-oriented field.

Influence of washing parameters on biomass and biochar properties of empty fruit bunches from oil palm plantation

Influence of washing parameters on biomass and biochar properties of empty fruit bunches from oil palm plantation

Application of principal component analysis (PCA) to the study of the influence of the thermochemical treatment process of tropical wood sawdust on the calorific, mechanical, physicochemical and combustion properties of the resulting fuel briquettes

Despite its potential for environmentally friendly energy production, lignocellulosic biomass has less advantageous physicochemical properties that limit its optimal industrial use. This study used principal component analysis (PCA) to evaluate the effects of two thermochemical processing methods (torrefaction and carbonization) on the calorific, physicochemical, mechanical and combustion properties of the resulting biofuels. Various types of tropical sawdust (Dabema, Dibetou, Fraké, Samba and Iroko) are subjected to these treatments, then densified and characterized for energy applications. Specific fuel consumption varies from Samba torrefied (Sam t: 0.69 kg/L) to Samba carbonized (Sam c: 1.48 kg/L). Higher heating values range from Samba torrefied (Sam t: 23983 kJ/kg) to Iroko torrefied (Iro t: 27,442 kJ/kg). Burning speed varies from Samba carbonized (Sam c: 3.07 g/min) to Iroko torrefied (Iro t: 4 g/min). The impact resistance index ranges from 187.5 to 500% for Dibetou torrefied (Dib t) and Samba carbonized (Sam c), respectively. Densities are between Samba carbonized (Sam c: 297.83 kg/m3) and Dibetou carbonized (Dib c: 393.69 kg/m3). The results indicate that these techniques are promising approaches for improving biomass properties. In sum, the PCA reveals that the effect of treatment type on fuel characteristics also depends on the properties of the initial biomass.

Design of an automatic electric torrefaction reactor for oil palm empty fruit bunch pellets

Abstract One of the technologies for utilizing waste into high-quality fuel is torrefaction. Torefaction of empty palm fruit bunches is a thermochemical process without the presence of oxygen by heating the biomass slowly and holding it for a certain time. Torrefaction degrades the hemicellulose content to optimize mass and energy yields. The purpose of this study was to design a temperature control system using a electrical heater on a rotary torrefaction reactor for Oil Palm Empty Fruit Bunch (OPEFB) pellets. The validation temperature sensor has shown a coefficient of determination (R2) 0.9999 using the model coefficient y = 1.0029x + 0.4017. The performance results of the electric reactor control system for torrefaction show a temperature control accuracy of 85.77% at various setting points. The response of the temperature control system within 10 minutes can reach a temperature of 213°C and in the 13th minute it reaches 301.6°C. The stability of the tool produces good performance. The electric power consumption for 6 kg OPEFB pellets was 2.98 kWh at a cost of USD 0.33. The water content in the torrefaction pellets is 1-2%. The results of the hydrophobicity test showed that the torrefactive samples at temperatures above 200 °C did not change their physical form after immersion in water for 24 hours. These results indicate that the electric torrefaction reactor automatic has succeeded in increasing the caloric ratio of the material, resistance to water such as charcoal, but still has the characteristics and properties of biomass.

Physicochemical, functional, and nutraceutical properties of Spirulina and Chlorella biomass: A comparative study

This comparative study investigates the physicochemical, functional, and nutraceutical properties of Spirulina (Arthrospira platensis) and Chlorella sp. biomass, two of the most prevalent microalgae species. We assessed their proximate composition, pH, acidity, color, granulometry, microstructure (SEM), functional groups (FTIR), crystallinity (XRD), and thermal stability (GTA). Functional properties were thoroughly examined, including bulk density, water and oil holding capacities, and gelling, foaming, and emulsifying capabilities. Additionally, the study quantified the content of pigments, phenolic compounds, carotenoids, and flavonoids and evaluated antioxidant activity. Our findings indicate that Spirulina biomass exhibits higher protein and ash content, whereas Chlorella biomass surpasses phenolic compounds, carotenoids, and antioxidant activity. Notable differences were observed in their microstructure and thermal degradation patterns. Both biomasses demonstrated considerable potential as functional ingredients, owing to their superior water and oil retention, foaming, emulsifying, and gelling properties. This investigation underscores the distinct physicochemical and nutraceutical profiles of Spirulina and Chlorella biomass, highlighting their significant applicability in the food industry for developing novel value-added food products.

Fast pyrolysis of biomass with diverse properties to produce liquid hydrogen storage molecules

Liquid organic hydrogen carriers (LOHCs), such as methanol and formic acid, offer a reliable solution for the challenges associated with transporting and storing gaseous hydrogen. However, the current industrial LOHCs are costly and in limited supply due to complex synthesis methods involving gasification and Fischer-Tropsch synthesis. An alternative approach utilizing efficient pyrolysis methods can convert biomass into substances that mimic LOHCs, making them a promising avenue for hydrogen storage. Compounds with a high hydrogen content, including glycolaldehyde, acetic acid, and acetol, hold potential as effective LOHCs. This study seeks to assess how the specific properties of biomass impact the resulting products and target molecules, focusing on identifying the primary sources of LOHC compounds. The experimental results indicate that glycolaldehyde primarily originates from cellulose, while acetic acid is mainly derived from hemicellulose. Acetol is produced from both cellulose and hemicellulose. At a pyrolysis temperature of 500 °C and a particle size of 0.38–0.83 mm, corn cob yields a higher quantity of glycolaldehyde, acetic acid, and acetol (107 mg/g) compared to rice husk (85.6 mg/g) and pine (68.9 mg/g) due to its significant cellulose and hemicellulose content. Notably, the primary sources of these hydrogen storage molecules during pyrolysis are the initial biomass pyrolysis products rather than secondary reactions.

Fine root biomass and soil properties in burnt and unburnt community grasslands of Cachar district, Assam, Northeast India

Fine root biomass and soil properties in burnt and unburnt community grasslands of Cachar district, Assam, Northeast India

Harnessing Ash for Sustainable CO2 Absorption: Current Strategies and Future Prospects.

This review explores the potential of using different types of ash, namely fly ash, biomass ash, and coal ash etc., as mediums for CO2 capture and sequestration. The diverse origins of these ash types - municipal waste, organic biomass, and coal combustion - impart unique physicochemical properties that influence their suitability and efficiency in CO2 absorption. This review first discusses the environmental and economic implications of using ash wastes, emphasizing the reduction in landfill usage and the transformation of waste into value-added products. Then the chemical/physical treatments of ash wastes and their inherent capabilities in binding or reacting with CO2 are introduced, along with current methodologies utilize these ashes for CO2 sequestration, including mineral carbonation and direct air capture techniques. The application of using ash wastes for CO2 capture are highlighted, followed by the discussion regarding challenges associated with ash-based CO2 absorption approach. Finally, the article projects into the future, proposing innovative approaches and technological advancements needed to enhance the efficacy of ash in combating the increasing CO2 levels. By providing a comprehensive analysis of current strategies and envisioning future prospects, this review aims to contribute to the field of sustainable CO2 absorption and environmental management.

Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefore, eight machine learning models (linear regression (LR), Gaussian process regression (GPR), artificial neural network (ANN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical boosting regressor (CatBoost)) with particle swarm optimization (PSO) and a genetic algorithm (GA) optimizer were developed and evaluated for prediction of H2, CO, CO2, and CH4 gas yields from SCWG of lignocellulosic biomass. A total of 12 input features of SCWG process conditions (temperature, time, concentration, pressure) and biomass properties (C, H, N, S, VM, moisture, ash, real feed) were utilized for the prediction of gas yields using 166 data points. Among machine learning models, boosting ensemble tree models such as XGB and CatBoost demonstrated the highest power for the prediction of gas yields. PSO-optimized XGB was the best performing model for H2 yield with a test R2 of 0.84 and PSO-optimized CatBoost was best for prediction of yields of CH4, CO, and CO2, with test R2 values of 0.83, 0.94, and 0.92, respectively. The effectiveness of the PSO optimizer in improving the prediction ability of the unoptimized machine learning model was higher compared to the GA optimizer for all gas yields. Feature analysis using Shapley additive explanation (SHAP) based on best performing models showed that (21.93%) temperature, (24.85%) C, (16.93%) ash, and (29.73%) C were the most dominant features for the prediction of H2, CH4, CO, and CO2 gas yields, respectively. Even though temperature was the most dominant feature, the cumulative feature importance of biomass characteristics variables (C, H, N, S, VM, moisture, ash, real feed) as a group was higher than that of the SCWG process condition variables (temperature, time, concentration, pressure) for the prediction of all gas yields. SHAP two-way analysis confirmed the strong interactive behavior of input features on the prediction of gas yields.

Microbial Biomass and Rhizosphere Soil Properties in Response to Heavy Metal-Contaminated Flooding

Mining and metallurgy are the main sources of soil contamination with harmful metals, posing a significant threat to human health and ecosystems. River floodplains in the vicinity of metal mines or industrial plants are often subject to flooding with sediments containing heavy metals, which can be harmful to the soil ecosystem. This study aimed to investigate the microbial properties of the soil at a metal-contaminated site and to determine the significant relationships between the biological and chemical properties of the soil. The study site was located near the village of Gyöngyösoroszi, in the Mátra mountain region of Northwest Hungary. A phytoremediation experiment was conducted in a metal-polluted floodplain using willow and corn plantations. The soil basal respiration, substrate-induced respiration, soil microbial biomass carbon (MBC), acid phosphatase activities, and soil chemical properties were measured. The soil of the contaminated sites had significantly higher levels of As, Pb, Zn, Cu, Cd, and Ca, whereas the unpolluted sites had significantly higher levels of phosphorus and potassium. The substrate-induced respiration showed a positive correlation with MBC and negative correlations with the metabolic quotient (qCO2). The soil plasticity index and phosphorus showed a positive correlation with MBC, whereas salinity and the presence of Cd, Pb, Zn, As, and Cu showed a negative correlation. Acid phosphomonoesterase activity negatively correlated with the plant-available phosphorus content and MBC, but was positively correlated with the contents of toxic elements, including cadmium, lead, zinc, arsenic, and copper. This study found a significant correlation between the qCO2 and the toxic element content. This suggests that an enhanced metabolic quotient (qCO2), together with a decreased MBC/SOC ratio, could be used to indicate the harmful effect of soil contamination by heavy metals in floodplain soils.

Investigation on the thermochemical characteristics, kinetics and evolved gases for typical kitchen waste pyrolysis

Kitchen waste is a complex biomass waste, whose composition and properties vary with factors such as source, season and region. It is challenging to classify and characterize it. A thermogravimetric and kinetic study was performed to estimate pyrolysis characteristics and gas emissions of starch, peel, nut shell, and vegetables. Samples underwent pyrolysis in the Simultaneous Thermal Analysis from room temperature to 1200 K at different heating rates of 10, 20, 30 and 50 K/min. The starch had the narrowest pyrolysis temperature range, while nut shell exhibited the highest residual rate. The average activation energy for pyrolysis process calculated using Coats–Redfern method was in order of starch > vegetable ≈ nut shell > peel. The gaseous products and typical functional groups of the released volatiles were identified using specific information from Fourier Transform Infrared Spectroscopy (FTIR) and Mass Spectrometry (MS). These primarily included small inorganic molecules, aldehydes, aromatics, ethers, furans, ketones, organic acids, and phenols. Aliphatic hydrocarbons significantly contributed to the total gas yield and were the most abundant for all samples. The characteristic ion fragment with m/z = 60 was only observed in peel and nut shell, while m/z = 58 ion fragments were exclusive to starch and vegetables. The practical research can provide theoretical basis for the resource utilization and environmental management of kitchen waste.

MXene/biochar composites for enhanced wastewater reclamation and bioenergy production: A kinetics and thermodynamics study

The study explores the synthesis and utilization of biochar (BC) and multi-layer MXene to MXene/biochar (MB) composites for wastewater treatment. Simultaneously, it also investigates their energy generation potential through biomass and soil property assessments. The integrated column and batch treatments have shown significant results, elevating total dissolved solids from 63.7 to 125.5 mg L−1 with column treatment, while reducing them to 6.37 % and 1.35 % with BC and MB treatment, respectively. BC with high carbon content, demonstrated increased hydrophobicity, which was amplified by the integration of MXene, thereby enhancing its potential for advanced wastewater treatment. Treated wastewater exhibited elevated nutrient concentrations (Ca, Cu, Fe, K, Na, and NH4+), promoting the growth of Pennisetum purpureum. WW_B shows promising energy potential, with a higher heating value of 25.03 MJ kg−1 and a lower heating value of 23.57 MJ kg−1. They demonstrated high volatile matter exceeding 70.9 wt %, and a fixed carbon from 10.02 to 27.53 wt %, signifying their potential for efficient conversion and bio-oil yield during pyrolysis. The ultimate analysis emphasized significant carbon, with oxygen content ranging from 43.42 to 47.78 wt %., influencing combustion characteristics. MT_B exhibited its suitability for energy production through thermochemical conversion, underlined by its high flammability and low volatile ignition values. In the absence of BC, the Ea ranged from 24.77 to 77.88 kJ mol−1 in wastewater and from 21.67 to 69.6 kJ mol−1 in MB treated wastewater. Meanwhile, when soil contained BC and was irrigated with wastewater, the Ea varied from 24.66 to 80.91 kJ mol−1. In the case of MB treated wastewater, it ranged from 25.01 to 75.79 kJ mol−1. The research thereby affirms the potential of MB composites to advance water and energy sustainability setting us for broader nexus-based applications.

Organic/metallic component analysis of lignocellulosic biomass: A thermochemical-perspective-based study on rice and bamboo waste

Thermochemical treatment is significantly impacted by the physiochemical properties of lignocellulosic biomass. Traditional characterization methods lack granularity, requiring advanced analytical techniques for comprehensive biomass characterization. This study analyzed elemental composition and their distribution in untreated rice husk, rice straw, and bamboo chips at micron and sub-micron scales. Results reveal significant variations in composition and spatial distribution of metallic components among agro-residues. Thermogravimetric analysis shows divergent decomposition patterns, while spectroscopic analysis indicates structural complexities and distinct silica content. Surface mapping illustrates prevalent silica and alkali metals on rice husk and rice straw. Atomic force microscopy depicts distinctive surface morphologies, with rice straw exhibiting heightened roughness due to silica bodies. Inductively coupled plasma-mass-spectrometry identified the abundance of alkali and alkaline earth metals in rice waste. Time-of-flight secondary ion mass spectrometry elucidates elemental spatial localization, affirming heterogeneous distribution across rice waste and homogenous distribution across bamboo waste. This study bridges the gap between biomass composition and optimized thermochemical conversion outcomes.

Beyond the permeability barriers: Unveiling the potential of dual-crosslinking hydrogel nanofiltration membranes for high-performance molecular/ion sieving

Membrane separation technology has shown great potential in resource recovery, energy utilization, and environmental protection, attracting extensive attention for the various practical applications. The alginate-based hydrogel membrane, derived from natural biomass, possesses sustainability and anti-fouling properties, effectively reducing the burden of waste membrane disposal. However, the limitations of alginate hydrogel include its high swelling ability, low permeability, and poor mechanical properties. In this study, we propose a straightforward method to fabricate orderliness hydrogels by employing lanthanide ion via dual cross-linking with CaAlg, resulting in the formation of lanthanum calcium alginate (La-CaAlg) hydrogel membrane. The La-CaAlg membrane exhibits superior mechanical performance and anti-swelling properties compared to LaAlg and CaAlg membranes. Additionally, through small-angle scattering and low-field nuclear magnetic resonance studies on the membrane's spatial orientation, and pore size distribution, we gained the comparable results into its internal structure for the design insight. Notably, the La-CaAlg membrane demonstrates outstanding performance in dye/salt separation, showcasing high selectivity and permeability. We propose the strategy that enhances the orderliness and durability of the alginate hydrogel membrane, providing the separation design insight to overcome the limitations associated with the permeability and rejection trade-off.