Types Of Biomass Research Articles

Optimizing food waste anaerobic digestion in Kuwait: Experimental insights and empirical modelling using artificial neural networks.

This study investigates, for the first time, the anaerobic digestion of food waste in Kuwait to optimize methane production through a combination of artificial neural network (ANN) modelling and continuous reactor experiments. The ANN model, utilizing eight hidden neurons and a 70-20-10 split for training, validation and testing sets, yielded mean squared error values of 0.0056, 0.0048 and 0.0059 and coefficient of determination (R²) values of 0.9942, 0.9986 and 0.9892, respectively. Methane percentages in biogas were predicted using six parameters: biomass type, pH, organic loading rate (OLR), hydraulic retention time (HRT), temperature and reactor volume. To validate the ANN results, continuous reactor experiments were conducted under an OLR of 3 kg VS m⁻³ d⁻¹ and HRT of 20 days at varying temperatures (35°C, 40°C, 45°C, 50°C and 55°C). The experiments demonstrated optimal methane production in the mesophilic range, with ANN predictions closely aligning with experimental data up to 45°C. However, deviations were observed at higher temperatures, particularly under thermophilic conditions beyond 50°C. This study provides novel insights into waste-to-energy initiatives in Kuwait and highlights the potential of integrating computational models with empirical data to enhance biogas production processes.

Exploring Recent Advances in Lignocellulosic Biomass Waste Delignification Through the Combined Use of Eutectic Solvents and Intensification Techniques

Growing awareness of resource sustainability and waste management has driven the search for circular-economy solutions. Lignocellulosic biomass waste, the most abundant renewable carbon resource, offers green potential as an alternative to declining non-renewable fuels. However, due to its recalcitrant nature, it requires pre-processing to convert it into valuable products like energy and chemicals. Biorefineries play a key role in this process by promoting the integral use of biomass, by finding ways to utilize lignin, previously treated as waste. Common pretreatment methods are unsustainable, prompting research into eco-friendly solvents and advanced techniques like ultrasound- and microwave-assisted methods. Recent approaches have also explored the use of eutectic solvents, which, when combined with these intensification techniques, offer promising results. These green technologies improve delignification efficiency, which in turn improves the saccharification process, reduces solvent use, and minimizes environmental impact. Despite progress, challenges remain in making these methods economically viable and adaptable to diverse biomass types. This review article highlights recent advances in sustainable treatment technologies, including the combined use of eutectic solvents and process-intensification techniques, and the potential of the obtained lignin in various industrial applications. It also discusses future prospects for more environmentally friendly processes in biomass utilization.

Prediction of Syngas Composition During Gasification of Lignocellulosic Waste Mixtures

Avoiding global dependence on fossil oils and improving the environmental impact of energy production are factors that drive research into renewable energies. Considering lignocellulosic biomass residues as a raw material for gasification, a thermochemical process that converts lignocellulosic resources into synthesis gas (H2, CO, CH4, and CO2) is an alternative under study due to its low costs, high efficiency, and wide variety of applications. Fortunately, there are still areas for its improvement and technological development. For example, this can be achieved by gasification. Distinct types of lignocellulosic biomass, such as sugarcane bagasse, wheat straw, pine sawdust, or corn cob, differ in their physical, chemical, and morphological properties, which can affect the characteristics of the gasification process. This work uses the generalized stoichiometry and mass and atomic balances in the gasification reactor to predict the composition of syngas produced via the gasification of both individual substrates and mixtures. The results provide useful information for the design and operation of gasification reactors with an operating region between 2.0 bar and 4.5 bar and between 1023.15 K and 1223.15 K, particularly with regard to understanding the effects of distinct types of biomasses in terms of their humidity and molecular weight on the operation and performance of the process. One important conclusion reached after simulating the addition of more vapor is that the (H2/CO) ratio cannot be increased indefinitely: it is limited by the thermodynamic equilibrium reached by the system.

Mechanism of Inhibiting Spontaneous Coal Combustion by Dopa Hydrosol

ABSTRACT A new type of biomass environmentally friendly hydrosol (DEP) was proposed to inhibit coal spontaneous combustion (CSC). The DEP consists of two parts, the PDopa side chain solution formed by the redox reaction of Dopa and EGCG and the main chain sol solution formed by the free radical polymerization of AA under the action of APS initiator. The −COOH, −NH2, and −OH in Dopa can be grafted onto the skeleton of the main chain via double strong hydrogen bonding interactions with the −COOH group in PAA to form a stable three-dimensional cross-linked network structure. DEP can inhibit CSC through three aspects: oxygen isolation, increasing the activation energy of coal oxidation, scavenging active groups and free radicals. The calculation simulation results show that EGCG in DEP can remove various active free radicals with lower activation energy at room temperature, breaking the chain cycle reaction of coal spontaneous combustion, which proves its high efficiency. This study provides a new way to apply mussel-inspired adhesion mechanisms to the prevention of CSC.

Effect of modifiers on the stability of 1‑butyl‑3-methylimidazolium-based ionic liquids

The distinctive capabilities of 1‑butyl‑3-methylimidazolium (bmim) cation-based ionic liquids (ILs) to dissolve lignocellulosic biomass offer the potential for the development of novel green bioprocessing technologies based on their utilization as green solvents. The limited range of thermal stability of ILs necessitates the use of various co-solvents to maintain solubility. In the present study, an original approach to determine the degree of degradation of alkylimidazolium ILs was proposed, based on the application of gravimetric analysis method to determine the content of volatile degradation products and high-performance liquid chromatography-high-resolution mass spectrometry (HPLCHRMS) to determine the total degree of degradation. The proposed approach, as well as the combination of HPLCHRMS with gas chromatography-mass spectrometry (GC–MS), was employed to comprehensively characterize the impact of additives and impurities (water, dimethyl sulfoxide, hydrochloric and acetic acids, diethylamine) on the degradation of bmim acetate, chloride, and methyl sulfate during thermal treatment under typical biomass dissolution conditions (150 °C, 24 h). The presence of additives or impurities in the composition of ILs has been found to predominantly contribute to a decrease in the number of volatile compounds formed, while increasing the variety and relative content of non-volatile degradation products. The use of protic solvents and acids results in a decrease in the overall degree of degradation of ionic liquids and in the fraction of volatile compounds formed. This allows for the classification of binary mixtures based on these additives as "green" solvents at temperatures below 150 °C.

Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence

The rapid increase in biomass and plastic waste poses significant environmental challenges. Co-pyrolysis of biomass with plastic wastes offers a promising avenue for sustainable waste management and renewable energy generation. This study covers several novel aspects: First, it investigates the impacts of feedstock composition and operating conditions in pyrolysis (individual feedstock) and co-pyrolysis (biomass and plastic wastes). The study reveals that synergistic effects, specifically improved yields and optimized temperature, exist in the co-pyrolysis of biomass and plastic wastes compared to individual feedstock. Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. This study predicts the bio-oil yield quantitatively (amount) and qualitatively (composition) with high accuracy (R2 > 0.97). Thirdly, key factors contributing to yield include plastic content (18 %) and biomass type (13 %) have been identified through Gini feature importance and Shapley Additive Explanation (SHAP) analysis. Furthermore, multi-objective optimization techniques reveal the most optimal bio-oil yield under specific conditions, supported by uncertainty analysis, which confines bio-oil yield to a range of 30–50 %. Finally, it also demonstrates a case study to find the optimal bio-oil yield and quality conditions using co-pyrolysis of local resources, i.e., biomass (wood and bagasse) and plastic wastes. The case study suggests optimal conditions like > 50 °C heating rate, <50 min pyrolysis time, and > 60 % plastic content in a blend of wood and HDPE. This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.

4E analysis and optimization comparison of solar, biomass, geothermal, and wind power systems for green hydrogen-fueled SOFCs

Integrating renewable energies with hydrogen production via electrolysis and utilizing hydrogen as a fuel for solid oxide fuel cells (SOFCs) presents a synergistic approach towards sustainable energy generation. This coupling offers enhanced flexibility, allowing for efficient energy storage and distribution, thereby addressing intermittency issues associated with renewable sources. Additionally, the utilization of hydrogen in SOFCs enables high-efficiency power generation with reduced emissions, contributing to the transition towards a cleaner energy landscape. In the present study, four types of renewable energies, namely solar, biomass, geothermal, and wind, produce hydrogen by coupling power generation units and a proton exchange membrane electrolyzer (PEME). Then, the produced hydrogen is stored and used for later utilization in an SOFC subsystem. A 4E (energy, exergy, exergy-economic, and environmental) study is conducted for the proposed systems through a sensitivity study and design optimization. In the best output performance mode, the best exergy efficiency is obtained by the biomass-based system, which is equal to 9.40%, and the lowest values for total cost rate and unit cost of outputs are achievable by the geothermal-based system, with values of 27.72 $/h and 43.23 $/GJ.

Optimization of Hydrocarbon Production in Catalytic Pyrolysis of Macaúba Epicarp and Macaúba and Baru Endocarps

The objective of this study was to examine the catalytic pyrolysis process of three distinct types of biomasses: baru endocarp (ENB), macaúba endocarp (ENM), and macaúba epicarp (EPM). This was performed with the aim of optimizing the production of hydrocarbons and other volatile compounds of interest through the use of different catalysts. The catalysts utilized in this study were calcium oxide (CaO), phosphate mining waste (PO), niobium pentoxide (Nb2O5), and Ni/Nb2O5. The methodology entailed pyrolyzing the biomass at temperatures spanning from 508 °C to 791 °C, utilizing a micropyrolyzer in conjunction with a gas chromatograph with mass spectrometry (GC/MS) for product analysis. An experimental design was implemented to assess the impact of catalyst concentration and temperature on the yield and composition of the volatile products. The findings demonstrated that CaO was efficacious in deoxygenating the compounds, particularly at elevated temperatures, thereby promoting the generation of saturated and unsaturated hydrocarbons. In contrast, Nb2O5 was effective in the formation of oxygenated compounds, particularly carboxylic acids and phenols. Ni/Nb2O5 has been shown to be effective in the production of cyclic, aromatic, alkadienes, and alkenes hydrocarbons. Phosphate mining waste exhibited moderate performance, with potential for specific applications at high temperatures, with important production of cyclic, aromatic, and alkane hydrocarbons. Among the biomasses, EPM demonstrated the greatest potential for hydrocarbon production, indicating its suitability for the development of advanced biofuels. This study advances our understanding of the catalytic pyrolysis of alternative biomasses and underscores the pivotal role of catalysts in optimizing the process, offering invaluable insights for the sustainable production of biofuels and interest in renewable chemicals.

Computational Prediction of Co-firing with Various Biomass Waste Using Turbulent Non-Premixed Combustion

Co-firing in coal power plants has limitations because the existing combustion systems are designed to provide optimal performance only with coal. Therefore, investigating the combustion aspects of co-firing by mixing coal with biomass before applying it to existing coal power plants is necessary. To address this, a new numerical model was developed to predict the co-firing behavior of coal with various types of biomass waste, specifically focusing on temperature and pollutant behavior. This study developed a co-firing model in a Drop Tube Furnace (DTF) using a composition of 25% Wood Chips (WC), 25% Solid Recovered Fuel (SRF), 25% Empty Fruit Bunch Fibers (EFFR), and 25% Rice Husk (RH). A structured grid arrangement and the Probability Density Function (PDF) were utilized to depict the relationship between chemical combustion and turbulence. The distributions of temperature and mass fractions of pollutants along the furnace axis were predicted. The highest temperature was observed with 25% EFFR, attributed to its highest volatile matter content. The simulation predicted that 25% RH would be the lowest SO2 emitter. However, it also showed a slight increase in NO and CO levels due to the increased oxygen content when coal was mixed with biomass. The simulation with 25% EFFR predicted a decrease in CO2 emissions compared to other biomass types. The results of this parametric investigation could support the implementation of biomass co-firing technology in existing coal-fired power plants.

Biomass Energy: A Crucial Component in the Renewable Energy Mix

Abstract: This paper examines biomass energy’s essential role in the renewable energy sector as a sustainable and flexible solution to rising global energy demands. It reviews various biomass types, conversion technologies, and their environmental, economic, and social impacts while addressing the challenges limiting biomass adoption compared to other renewables. Prospects for biomass energy are also discussed, focusing on technological advances, policy trends, and its role in supporting global energy transitions. The analysis highlights biomass's potential as a critical contributor to a sustainable energy system, emphasizing that, with appropriate support, it could become a cornerstone of renewable energy strategies to reduce carbon emissions.

Utilization of Palm Frond Waste as Fuel for Co-Firing Coal and Biomass in a Tangentially Pulverized Coal Boiler Using Computational Fluid Dynamic Analysis

Renewable energy sources are becoming increasingly crucial in the global energy industry and are acknowledged as a significant substitute for fossil fuels. Oil palm fronds are a type of biomass fuel that can be utilized as a substitute for fossil fuels in the combustion process of boilers. Co-firing (HT-FRD) is a beneficial technology for reducing exhaust gas emissions generated by coal-burning power stations. By utilizing computational fluid dynamics (CFD), this study has modeled and evaluated co-firing palm frond residue (HT-FRD) with hydrothermal treatment into a 315 MWe boiler. In the simulation, six different HT-FRD co-firing ratios, 0%, 5%, 15%, 25%, 35%, and 50%, were used to demonstrate the differences in combustion characteristics and emissions in the combustion chamber. The data indicate that HT-FRD co-firing can enhance temperature distribution, velocity, and unburned particles. All in all, co-firing conditions with 5–15% HT-FRD ratios appear to have the most favorable combustion temperature, velocity, and exhaust gas characteristics.

Evaluation of Greenhouse Gas Emission Assessment Resulting from Processing Municipal Organic Waste into Bahan Bakar Jumputan Padat for Co-firing in Power Plants; Case Study: Bagendung Landfill Cilegon City

One type of biomass that can be used as fuel for co-firing in power plants is Bahan Bakar Jumputan Padat (BBJP)/Solid Waste Fuel. BBJP is a non-hazardous waste derivative that cannot be recycled. The production process of BBJP is strictly regulated by the Indonesian national standard (SNI) 8966:2021. The definition, characteristics and specifications of BBJP are much closer to Solid Recovered Fuel (SRF) than Refuse Derived Fuel (RDF). The utilization of BBJP reflects the dedication to reducing waste in landfills with a circular economy concept approach as well as the transition of the energy mix in Indonesia. To the present day, the production capacity of BBJP at Bagendung landfill in Cilegon City, Banten Province, has successfully produced 30 tons/day of organic municipal waste with an average BBJP product yield ranging between 11-15 tons/day. This research is intended to assess the Greenhouse Gas emissions (GHG) generated from the processing of municipal waste into BBJP. There are three main processes that produce GHG emissions, namely during bio drying processing, the use of machinery that produces emissions from electricity and the transportation process that produces combustion emissions in diesel fuel. As a result, direct GHG emissions arising from all waste processing activities into BBJP consist of 10 pollutants, namely CH4, N2O, CO, NH3, CO2, NOX, SO2, NVMOC, PM2.5 and ID(1,2,3,c,d)P. CO2 emission is the largest pollutant, accounting for 96.70% of the entire BBJP process.

Incorporation of Cyanobacteria and Microalgae in Yogurt: Formulation Challenges and Nutritional, Rheological, Sensory, and Functional Implications

This review presents an approach to the incorporation of cyanobacteria and microalgae in yogurts and explores their impact on the nutritional, rheological, sensory, and antioxidant qualities of these products. First, the yogurt market context and its relationship with nutritional quality are outlined, emphasizing the quest for functional foods that meet consumer demands for healthy and nutritious products. A discussion of the incorporation of cyanobacteria and microalgae, especially Spirulina platensis, in foods, particularly yogurt, is then presented, highlighting the nutritional and functional benefits that this type of biomass can provide to the final product. The fermentation process and the quantity of algae to be incorporated are discussed to understand their fundamental role in the characteristics of the final product. In addition, this article considers some challenges such as sensory and rheological changes in the product resulting from the interaction of milk, algal biomass, and the fermentation process. Addressing these challenges involves delineating how these interactions contribute to changes in the traditionally consumed product, while obtaining a pro- and prebiotic product is crucial for creating an innovative dairy product that diversifies the market for derived dairy products with increased functional properties.

Supervised and unsupervised machine learning for elemental changes evaluation of torrefied biochars

This study implements a comprehensive analysis of supervised and unsupervised learning to evaluate elemental changes and investigate the merits of the machine learning method for torrefied biochar property analysis. The focus is on data analysis using artificial neural networks (ANNs) and k-means algorithms for analyzing the carbonization index (CI) and deoxygenation index (DI) after biomass torrefaction. The predictive response surfaces for CI and DI are formulated and analyzed accordingly by preprocessing the raw data as either lignocellulosic or microalgal datatype. Based on ANNs, the relative importance weights of the factors of temperature, duration, and biomass type are 45.87 %, 23.19 %, and 30.94 %, respectively, for the CI response, while 35.27 %, 26.62 %, and 38.11 %, respectively for the DI response. For k-means analysis, the optimal number of clusters for lignocellulosic and microalgal datasets are two and three, respectively. The R2 value of ANNs is 0.9565. The distribution and percentage of the dataset within the clusters are influenced by the time for the lignocellulosic datatype, while they are influenced by temperature for the microalgal datatype. The obtained results are conducive to improving the cognition of the machine learning method on torrefaction performance analysis.

Chemical thermodynamics of biomass, cellulose, and cellulose derivatives: A review

This article provides a review of the research on the chemical thermodynamics and thermochemistry of biomass, cellulose, and its derivatives such as ethers, esters, and oxycelluloses. For diverse biomass types, gross and net heating values were studied. It has been established that these energetical characteristics of biomass can be calculated using a superposition of the energetical characteristics of the main components of biomass such as cellulose, hemicelluloses, lignin, lipids, proteins, etc. The pelletization of biomass improves its fuel performance. It was shown that, if the ultimate goal is to generate the maximum amount of thermal energy, then it is more profitable to directly burn the initial biomass in the form of pellets than to burn the amount of solid or liquid biofuel that can be extracted from this biomass. After the cellulose study, the direct and exact thermochemical method for determining the crystallinity degree of this biopolymer was proposed. In addition, the standard combustion and formation enthalpies of various cellulose samples were studied. As a result, the thermodynamic characteristics of four crystalline allomorphs of cellulose, CI, CII, CIII, and CIV, were obtained and their thermodynamic stability was evaluated. The thermochemistry of enzymatic hydrolysis of cellulose was studied. In addition. The thermodynamical characteristics of various cellulose derivatives were determined, and the thermochemistry of the reactions of cellulose alkalization, etherification, esterification, and oxidation was studied.

Evaluation of value adding components from postharvest biomass of Thai medicinal cannabis var. Hang Kra Rog Phu Phan

Thailand has undertaken regulatory reforms to facilitate the cultivation and commercialisation of Cannabis sativa L. for medicinal purposes. The prominent cannabis strain in Thailand is Hang Kra Rog Phu Phan (HRPP), distinguished for its high tetrahydrocannabinol (THC) content. The recent adoption of a biocircular approach within the industry reflects a commitment to minimising losses and enhancing value-added processes. However, there is limited information on biomass generation from the postharvest management of this cannabis strain and the development of value-added products. This study aims to address this gap by conducting a survey of local cannabis farms and evaluating the quantity of cannabis biomass by-product materials resulting from the production process. According to the survey, stems were the most abundant materials followed by leaves and roots. These by-products were subsequently gathered and examined for its chemical components. The results of proximate analysis highlighted that the dried leaves had a high protein content up to 19.27 %, the highest in three types of biomasses. The composition of fat, fibre, ash, and carbohydrates varies depending on the type of biomass. By using sequential extraction, it was found that the extraction yield of pectin in the leaf materials was as high as 13.82 %, and in the stem part, it was at 13.02 %. Meanwhile, cellulose was found in the highest proportion from the roots, at 83.77 %. Confirmation of the composition of polysaccharides using microarray profiling revealed that these biomasses contain various types of polysaccharides (pectin, cellulose, hemicellulose). Analysis of bioactive compounds revealed that the total phenolic and total flavonoid content were the highest in the leaf biomass, consisting of 11.57 and 14.91 mg/g DM, respectively. The leaves also had the highest antioxidant activity. Quantitative analysis of the metabolites in the leaves found contents of rosmarinic acid 2.55 mg/g DM, catechin 2.33 mg/g DM, vanillin 2.32 mg/g DM and in the cannabinoid group, the highest quantity of cannabinol (CBN) 2.63 mg/g DM was found. The findings from this study could serve as a guideline for utilising biomass generated from the production process of cannabis that could be used for pharmaceutical, food, and feed purposes.

Emission Factors for Biochar Production from Various Biomass Types in Flame Curtain Kilns

Simple and low-cost flame curtain (“Kon-Tiki”) kilns are currently the preferred biochar technology for smallholder farmers in the tropics. While gas and aerosol emissions have been documented for woody feedstocks (twigs and leaves) with varying moisture contents, there is a lack of data on emissions from other types of feedstocks. This study aims to document the gas and aerosol emissions for common non-woody feedstocks and to compare emissions from finely grained, high-lignin feedstock (coffee husk) with those from coarser, low-lignin feedstocks (maize cobs, grass, sesame stems). Throughout each pyrolysis cycle, all carbon-containing gases and NOx were monitored using hand-held sensitive instruments equipped with internal pumps. Carbon balances were used to establish emission factors in grams per kilogram of biochar. The resulting methane emissions were nearly zero (&lt;5.5 g/kg biochar) for the pyrolysis of three dry (~10% moisture) maize cobs, grass, and a 1:1 mixture of grass and woody twigs. For sesame stems, methane was detected in only two distinct spikes during the pyrolysis cycle. Carbon monoxide (CO) and aerosol (Total Suspended Particles, TSP) emissions were recorded at levels similar to earlier data for dry twigs, while nitrogen oxide (NOx) emissions were negligible. In contrast, the pyrolysis of finely grained coffee husks generated significant methane and aerosol emissions, indicating that technologies other than flame curtain kilns are more suitable for finely grained feedstocks. The emission results from this study suggest that certification of biochar made from dry maize, sesame, and grass biomass using low-tech pyrolysis should be encouraged. Meanwhile, more advanced systems with syngas combustion are needed to sufficiently reduce CO, CH4, and aerosol emissions for the pyrolysis of finely grained biomasses such as rice, coffee, and nut husks. The reported data should aid overarching life-cycle analyses of the integration of biochar practice in climate-smart agriculture and facilitate carbon credit certification for tropical smallholders.

Ensiling of Willow and Poplar Biomass Is Improved by Ensiling Additives

Biomass from willow and poplar harvested for feed during the growing season may be preserved by ensiling; however, little research has focused on ensiling of these biomasses. This study focuses on the use of ensiling additives to reduce the pH to around 4.0 to secure stable storage. Lab-scale ensiling experiments were conducted with different willow and poplar clones, shoot ages, and harvest times (June or September). Ensiling without additives often resulted in limited pH reduction. The pH could be reduced in the biomass of both species by adding formic acid, and the required dose to reduce the pH to 4.0 (buffering capacity, BC) ranged significantly between biomass types but was in the range of 2–5 kg formic acid (78%) per ton fresh weight. BC decreased with increasing dry matter (DM) content and decreasing crude protein content. The pH could also be reduced during ensiling by applying molasses and/or lactic acid bacteria, although not sufficiently in poplar. Willow biomass was ensiled effectively at the pilot scale with less than 7% DM loss by adding formic acid or by mixing with grass biomass. Comparable pH results were obtained at the lab scale and pilot scale. The study demonstrates how willow and poplar can be ensiled; however, more research is needed on quality changes during ensiling.

Biochar carbon removal from residues in Germany—assessment from environmental and economic perspectives

Abstract The topic of biochar carbon removal (BCR), which refers to the pyrolysis of biomass, is increasingly being discussed as a potential solution for the long-term removal of carbon dioxide from the atmosphere. However, BCR technology assessments in Germany, which are used as the basis for strategic decision-making, are often limited to woody biomass as an input material and are based on old data. Consequently, this study focuses on BCR from forest residues, straw and sewage sludge and assesses its contribution to negative emissions under current techno-economic framework conditions. Using life cycle assessment and annuity method, as well as complementary stakeholder engagement formats, the study provides a comprehensive analysis of BCR pathways in Germany based on an empirical, up-to-date data basis. The results highlight the environmental advantages of BCR, particularly in reducing greenhouse gas emissions compared to the conventional treatment of residues. The economic feasibility of BCR is uncertain, with profitability dependent on plant scale, biomass type and the integration of energy co-products. Stakeholder insights underscore the necessity for supportive policies and investment in BCR technology to enhance scalability. This interdisciplinary approach enriches the discourse on BCR’s role in achieving carbon neutrality and offers a robust data foundation for future evaluations.

Agro-waste based biomass residues valorization for effective adsorption of heavy metal.

In this experiment four agro-waste based biomass residues (soybean stover-SSb, buckwheat stover-BWb, Artemisia vulgaris- AVb and Chromolaena odorata-COb) was valorized into low cost amendment called biochar followed by compositional characterization for their application in heavy metal removal. Investigation was carried out on the removal of the most common heavy metal ions including arsenic, cadmium, lead, nickel, zinc, and copper through adsorption on four types of biomass valorised biochar. According to preliminary testing, all the biochar was effective to eliminate a mixture of six heavy metals from the aqueous phase, with the removal of arsenic being the most removed and nickel being the least. In comparison to no biochar treatment, the average removal rate of heavy metal from aqueous solution using four distinct types of biochar was 45.75-62.42% (Cd), 43.64-56.33% (Pb), 41.85-59.73% (Ni), 42.87-60.28% (Zn), 45.64-59.51% (Cu), and 49.02-60.53% (As). The percent decrease of cadmium heavy metal adsorption with increase in maximum contaminant level (MCL) from 1- to fivefold was 20.0 (SSb), 20.7 (COb), 21.6 (BWb), and 22.9 (AVb). The results of the dosage study indicated that As adsorption was the most beneficial on all four types of biochar, whereas Ni adsorption was the least effective. With increase in application rate of biochar the heavy metals adsorption (%) was also increased. Four different agro-waste valorized biochar were used to treat the wastewater, and the physical and chemical changes that occurred both before and after the biochar treatment were noted. There was a drop in the wastewater CODT, CODD, TSS, ammonia, TKN, TP and pH values of 79.7-103.5%, 57.7-81.5, 52.3-68.4%, 1.23-2.23%, 14.1-20.6%, and 1.23-3.03%, respectively. Furthermore, after being passed through a biochar, the wastewater's Zn, Pb, Cd, As, Cr and Cu levels decreased by 3.26-6.15%, 0.06-0.34%, 0.01-0.08%, 2.37-3.65%, 3.95-5.53%, and 2.24-3.34%, respectively at 2.5 and 5.0g/litre of wastewater. Thus, in order to comply with regulations for the disposal of wastewater effluent, the process of valorizing biomass into biochar offered enormous potential for the removal of heavy metals in addition to wastewater treatment.