Search Results (4,549)

The increasing penetration of variable solar and wind generation requires flexible resources capable of improving energy balancing, reliability, and renewable energy utilization. This review critically assesses biofuel-integrated hybrid energy systems as complementary architectures for renewable energy integration, connecting system configuration, energy conversion efficiency, storage and dispatch, intelligent control, environmental performance, and scalability. A critical narrative and integrative approach was applied using literature retrieved from Scopus and Web of Science, and organized across solar–bioenergy, wind–bioenergy, multi-source, storage-supported, microgrid, and multi-energy configurations. The evidence indicates that biomass-derived fuels can provide dispatchable and storable renewable energy that complements variable generation and supports decentralized and multi-energy applications. However, no architecture is universally superior, and greater hybridization does not inherently result in higher thermodynamic efficiency. Performance depends strongly on resource complementarity, feedstock availability and quality, conversion pathways, storage requirements, and operating strategy. Advanced energy management, model predictive control, machine learning, and digital twins can improve system coordination, although much of the available evidence remains simulation-based or limited in experimental scale. Environmental benefits are likewise pathway- and boundary-dependent, particularly when avoided emissions, coproduct allocation, infrastructure, and feedstock supply chains are considered. Overall, biofuel-integrated hybrid systems represent an application-dependent flexibility option rather than a universally optimal solution; future progress requires dynamic uncertainty-aware modeling, harmonized techno-economic and life-cycle assessment, and greater pilot- and industrial-scale validation. Full article

Rapeseed price stability is an important determinant of the long-term sustainability of biofuel production and the economic resilience of farms in the European Union. This study evaluates long-term rapeseed price dynamics in Poland and assesses their implications for biofuel production and agricultural resilience. Annual data for 2005–2024 were analyzed using descriptive statistics and the Augmented Dickey–Fuller (ADF) test, while ARIMA models were used for forecasting and GARCH models were estimated from 778 daily MATIF observations for 18 February 2022–10 March 2025. The results show substantial price variability, with pronounced changes associated with international market conditions, the COVID-19 pandemic and the war in Ukraine. The ARIMA forecasts for 2025–2034 indicate a projected decline in the analyzed rapeseed and rapeseed-product prices; however, the widening forecast errors indicate increasing uncertainty over the longer horizon. The findings suggest that long-term price uncertainty should be considered in policies supporting the resilience of rapeseed producers and the stability of feedstock supply for renewable fuels. Full article

The growing demand for sustainable energy has increased interest in biomass-based fuels as alternatives to fossil fuels. This study evaluated the potential of Arachis pintoi (Pinto peanut) as a multiproduct biomass resource within an integrated biorefinery framework. The seed oil exhibited a low free fatty acid (FFA) content (0.612%), enabling direct alkaline transesterification without acid pretreatment. The produced biodiesel showed favorable fuel properties, including a calorific value of 40.54 MJ/kg, a kinematic viscosity of 4.70 mm²/s, and a flash point of 157.5 °C. The residual A. pintoi shells were subsequently valorized through pyrolysis to produce biooil, syngas, and biochar, with the resulting products evaluated for their energy-related characteristics. The biochar exhibited a calorific value of 25.24 MJ/kg, while the shells showed a calorific value of 16.79 MJ/kg and suitable proximate and ultimate composition for thermochemical conversion. In addition, the residual shells were utilized to produce cylindrical briquettes using paper and cardboard as binders, which were evaluated based on their fuel and mechanical properties. These findings demonstrate the potential of A. pintoi for integrated biomass valorization through biodiesel production, pyrolysis, and briquetting, providing multiple value-added energy products and supporting the development of sustainable bioenergy systems. Full article

Circular economy is today a key driver of every transformation process aimed at reducing and optimizing the use of energy and materials. The production of solid biofuel from waste is a typical route to lower the potential impact of greenhouse-gas emissions. In this context, olive pomace is a relevant feedstock, as 4 million tonnes are generated worldwide each year alongside olive oil production. However, only a small fraction of olive pomace is currently valorized. Fresh olive pomace must first be quickly dried to a low, controlled moisture. This step is performed poorly and at a high energy cost. This paper presents an automation-based approach to enhance biomass production from olive pomace, thereby advancing circular-economy practices in olive oil production. The work is focused on four aspects. In the first part, a review of the state of automation in agricultural engineering with a focus on biomass and olive pomace is proposed. Then, the design and construction of an innovative drying system that integrates an infrared solution directly into the transporting screw conveyor is described, integrating real-time online microwave moisture sensing and PLC control. After that, a cloud-based service is presented for remote monitoring, data analysis, and optimization. The innovative and automated drying system was validated during a preliminary field campaign at an olive mill. After about sixteen hours of continuous, cloud-monitored operation, the resulting olive pomace moisture fell below the 5% threshold across a wide range of inlet-moisture conditions, with a stable electrical power demand of approximately 1.85 kW. Finally, an environmental analysis is provided to evaluate the environmental aspects related to the proposed system. The preliminary analysis confirms a significant avoided-carbon potential if the resulting olive pomace is reused as biomass for energy production. The impact associated with 1 kWh_-eq produced from olive pomace is in the range of 0.006–0.033 kg CO_2-eq. Full article

Weather variability and CO₂ supply costs remain key barriers to the commercial viability of algal biofuel production. Recent experimental work has demonstrated that the algae Chlorella sp. strain SLA-04 achieves high productivity in extreme alkaline growth media (pH > 10), where the solution chemistry enables direct capture of atmospheric CO₂, eliminating the need for costly CO₂ sparging. Despite these promising results, the commercial-scale economic and environmental implications of this cultivation approach have not yet been assessed. Here, we present the first integrated Techno-Economic Analysis (TEA)/Life-Cycle Analysis (LCA) of high-pH–high-alkalinity production. We compare four SLA-04 cultivation scenarios with a baseline strain cultivation scenario with Nannochloropsis oceanica. These scenarios also include the first incorporation of Trona, a naturally occurring carbonate mineral and the primary domestic source of bicarbonate in the United States, into our TEA/LCA framework as a low-cost alternative to commercial NaHCO₃ for establishing the high-alkalinity growth medium. Our results indicate that the SLA-04-Trona scenario reduces carbon intensity and present value of lifetime expenses by 40% and 55% on a per-gallon basis, while simultaneously exhibiting lower production variability across all seasons. Quarterly revenues reflected an improvement of $6 million over the baseline strain revenue over 40,000 simulations. Modeled productivity was lower than what was observed experimentally and resulted in a MBSP of $705/ton. These findings provide the first quantitative evidence that high-pH–high-alkalinity cultivation can substantially improve both the economics and environmental footprint of commercial-scale algal biofuel production. Full article

Global land degradation affects approximately 2 billion hectares, threatening food security, biodiversity, and climate stability while undermining the United Nations Sustainable Development Goals (SDGs). The concurrent urgency to decarbonize the energy system and mobilize green finance for sustainable transitions has created a rare policy window in which AI-optimized biofuel production on degraded lands can simultaneously serve multiple imperatives. This study presents a comprehensive secondary data analysis of AI-based optimization frameworks for deploying biofuel production systems on degraded lands, integrating an explicit green finance dimension that has been largely absent from prior synthesis literature. Drawing on 152 peer-reviewed studies and authoritative datasets from FAO, IEA, IRENA, UNCCD, the Green Climate Fund (GCF), and the World Bank, we analyze machine learning, deep learning, reinforcement learning, and hybrid AI architectures applied to feedstock selection, soil remediation, yield prediction, supply-chain logistics, and green finance risk-return optimization. Based on evidence synthesized from 152 studies and supporting geospatial and scenario analyses, results indicate that AI-optimized systems can recover 75–94% of prime-land yields, achieve carbon sequestration rates of 2.1–6.8 t CO₂e ha⁻¹ yr⁻¹, central estimate ≈ 7–9 Gt CO₂e yr⁻¹ at 35% adoption with moderate exclusions, and generate projected internal rates of return ranging from 8–22%, depending on feedstock type, regional conditions, and financing assumptions. Yield-recovery and carbon-sequestration ranges are drawn from synthesis of the reviewed literature; IRR, financial-leverage, and market-expansion figures are author-constructed scenario projections based on this evidence, not independently observed outcomes. Green bonds, Article 6 carbon credits, GCF concessional finance, and blended finance structures are identified as the most impactful instruments, collectively projected, under scenario-based modeling, to reduce composite project risk scores by 30–45% and expand the investable universe of degraded-land biofuel projects by an estimated 340% relative to a no-AI, no-green-finance baseline; these figures represent author-constructed scenario estimates rather than direct empirical findings. We develop the AI-Biofuel-Land Restoration-Green Finance (ABLR-GF) conceptual framework (not yet empirically validated through field pilots or simulation) with explicit green finance routing pathways and identify critical policy enablers for global deployment. This study advances the evidence base for policy-makers, investors, researchers, and development practitioners working at the intersection of artificial intelligence, bioenergy, green finance, and sustainable land management. Full article

Biomass, particularly agricultural waste, has emerged as a highly attractive alternative fuel source for domestic and industrial applications. This study investigates the suitability and potential of plantain peel biomass (PPB) as a viable feedstock for bioenergy production. The PPB was comprehensively characterized using proximate and ultimate analyses, thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR) spectroscopy, and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Experimental results indicate that the weight ratio of plantain peel (skin) to unpeeled plantains ranges from 27% to 47%. Proximate analysis of the PPB yielded volatile matter (VM) of 65.8% and fixed carbon (FC) of 14.5%, suggesting substantial energy potential. The ultimate analysis results, conducted on a dry, ash-free basis, were used to determine the biomass higher heating value (HHV), which ranged from 13.93 to 16.35 MJ/kg. TGA showed that the thermal decomposition of PPB is typical of lignocellulosic biomass, occurring in three distinct stages over a temperature range of 25 to 1000 °C. FTIR spectroscopy identified O-H and C-H as key functional groups present in the PPB, further supporting its viability for biofuel production. Furthermore, SEM micrographs revealed a porous surface texture with heterogeneous particle sizes and shapes. At the same time, EDS confirmed carbon (C), potassium (K), and oxygen (O) as the dominant elements, alongside trace amounts of magnesium (Mg), silicon (Si), phosphorus (P), chlorine (Cl), and iron (Fe). In conclusion, PPB represents a promising and sustainable feedstock for biofuel production in both domestic and industrial sectors. Full article

Modeling an artificial neural network to predict the behavior of a heating and domestic hot water system in a residential building is the basis of this report. The heating system includes three types of energy sources: biofuel, solar, and electricity. During transitional seasons, such as spring and autumn, it is possible to use all three sources periodically or simultaneously, which leads to increased consumption and inefficiency in the system. In order to study the dynamics of the process and optimize the control, a monitoring system based on Raspberry Pi Pico W was developed. Data on the operating parameters of the boiler, tank, and radiator is transmitted in real-time to the ThingSpeak cloud platform, using the free access option that requires only registration. Due to the reinforced concrete structure of the building, the local Wi-Fi connection drops at times, so an additional router was added. Although individual values from the data are missing, they can be used to obtain graphs of the transient process. The data received in the platform does not arrive evenly due to the time required for transmission. The artificial neural network was created in MATLAB (v2025, MathWorks, Natick, MA, USA) and uses the raw data to predict changes in the processes. The missing fragments of the data have no impact, and a good match of the actual values with the predicted values was obtained for the tank and radiator, while for the boiler, the match was satisfactory. Full article

The European Commission’s decision to establish a 10% v/v volumetric ethanol cap in gasoline (E10) under Renewable Energy Directive II (RED II), further reinforced by the stricter sustainability criteria introduced in RED III, marks a critical turning point for the global ethanol industry. By 2023, worldwide ethanol production reached approximately 116–118 bn liters annually, with the United States dominating at 52% and Brazil contributing about 28%. First-generation (1G) ethanol is increasingly constrained in its expansion within the road transport sector, necessitating the identification of alternative markets to absorb surplus volumes. RED III emphasizes the deployment of advanced biofuels and renewable fuels of non-biological origin (RFNBOs), mandating either a 14.5% reduction in greenhouse gas emissions or a 29% renewable energy share by 2030, thereby encouraging sectoral diversification. The maritime sector emerges as a promising outlet to accommodate surplus ethanol. However, regulatory inconsistencies persist: ReFuel EU excludes crop-based biofuels, while Fuel EU Maritime permits certified options. Aviation remains limited to advanced biofuels. Meanwhile, IMO policies, including MEPC 83 and 84, introduce emissions pricing and lifecycle assessment frameworks, promoting low-emission fuels without clearly recognizing ethanol’s competitiveness. This study evaluates ethanol utilization in marine engines under these constraints. Full article

Oilseed crops serve as pivotal raw materials for renewable energy production, rendering oilseed futures increasingly vulnerable to the dual shocks stemming from climate risk and the global energy transition. Against this backdrop, investigating the dynamic impact of climate policy uncertainty (CPU) on oilseed futures markets holds substantial practical and theoretical significance for commodity market risk management and pricing. Based on the theoretical logic of dual supply–demand and cost channels, this paper employs a time-varying parameter vector autoregressive (TVP-VAR) model to examine how fluctuations in CPU exert time-varying impacts on oilseed futures returns by shaping the supply–demand dynamics and production costs of the oilseed market. The empirical results reveal that CPU changes generally exert a positive effect on oilseed futures returns, while significant negative impacts are detected in specific sample periods, exhibiting a time-varying alternating pattern, with the short-term impact being the most dominant and pronounced. In addition, impulse response analysis at three typical time points shows that CPU shocks positively affect oilseed futures returns mainly in periods 1–2, while negative effects peak in period 3 and then decay with alternating fluctuations. The heterogeneity across time points verifies the dual-channel mechanism of shifting dominance between supply–demand and cost channels. Full article

Microalgae are promising platforms for biomass production, carbon capture, biofuels, and high-value bioproducts. However, despite significant advances in cultivation technologies, reactor engineering, and metabolic engineering, industrial implementation remains limited. This gap suggests that the main challenge of microalgae biotechnology lies not in the availability of productive strains or cultivation systems, but in managing the environmental and physiological heterogeneity that emerges during scale-up. This structured narrative review selected literature using predefined descriptors and relevance-based inclusion criteria and organized the evidence into five thematic domains encompassing cultivation-scale constraints, cellular physiology, bioengineering, precision technologies, and industrial translation. This review examines macrospatial bottlenecks related to light distribution, gas transfer, hydrodynamics, and reactor operation, alongside microspatial constraints involving cell cycle regulation, carbon allocation, metabolic adaptation, and stress responses. Recent advances in adaptive cultivation, real-time monitoring, artificial intelligence, digital twins, computational modeling, and bioengineering are discussed as tools to transform biological and environmental variability into actionable information. Based on concepts established in precision agriculture, this review proposes precision microalgae as a conceptual framework that integrates reactor engineering and cell physiology with three operational pillars: real-time monitoring, predictive modeling, and adaptive control. Its specific contribution is to connect currently fragmented technological and biological advances within a common framework for managing multiscale heterogeneity during cultivation and scale-up. Overall, the available evidence supports the operational logic of this framework, although its generalized effectiveness under industrial conditions remains to be demonstrated. Full article

This study presents a comparative thermochemical and combustion analysis of biomass pellets derived from softwood, hardwood, sunflower husks, wheat straw, and lavender residues. This investigation was performed using thermogravimetric analysis (TG), derivative thermogravimetric analysis (DTG), and differential scanning calorimetry (DSC) to evaluate the thermal degradation behavior, combustion reactivity, heat-release characteristics, and ash-forming tendencies of the investigated biomass types. The results revealed substantial differences between woody biomass and agricultural residues in terms of thermal stability, thermal degradation behavior, and energy output. Softwood pellets exhibited the highest thermal reactivity, the most intense devolatilization process, and the highest heat release during combustion, indicating higher thermal reactivity and favorable fuel properties. Hardwood pellets demonstrated improved thermal stability due to increased lignin content, resulting in broader thermal decomposition regions and more gradual heat release. In contrast, sunflower husk and wheat straw pellets showed lower thermal reactivity and significantly higher residual mass, indicating elevated ash content and reduced thermal decomposition behavior. Lavender pellets exhibited intermediate thermochemical behavior associated with the presence of volatile extractives and moderate thermal stability. The integrated TG-DTG-DSC approach enabled a direct comparison of woody biomass and agricultural residues under identical experimental conditions and expanded the available thermochemical data for lavender-derived pellets. The results provide a comparative framework for assessing biomass resources intended for energy applications. Full article

As fossil fuels are being replaced by lower-carbon alternatives, the EU renewable energy directives RED II/III mandate increases in the proportion of advanced biofuels within liquid fuels, aiming to reduce greenhouse gas emissions over first-generation biofuels. It is crucial to study how these fuels affect engine performance to ensure they also meet emissions standards of relevance to air quality. Advanced biofuels, mainly from lignocellulosic feedstocks, are promising options. This work tested model butanolysis-derived blends using hydrotreated vegetable oil (HVO) as the base fuel, due to its lower carbon footprint, favourable combustion properties, and potential to replace diesel without engine modifications, along with ultra-low sulphur diesel (ULSD). Physical properties such as density and flash point were tested on the butyl-based biofuel blends. The measured densities fell between those of pure HVO and ULSD, while the measured flash points exceeded the minimum standards required for fuels. This study examines the use of such blends with a EU Stage V emission compliant Yanmar L100V compression ignition (CI) engine as part of a generator set, using model butanolysis biofuel mixtures blended with HVO at various ratios. A CI engine was chosen because generators, off-road machinery, heavy-duty vehicles, and marine vessels will continue to rely on CI engines for the foreseeable future. Ignition delays (IDs), brake-specific fuel consumption (BSFC), gaseous and particulate matter (PM_2.5) emissions were determined. Gaseous emissions were measured with a Horiba MEXA7100D, and PM_2.5 was collected on filters for gravimetric analysis. All blends, including pure HVO, had shorter IDs than diesel. Emissions of nitrogen oxides (NOx = NO + NO₂), carbon monoxide (CO), and total hydrocarbons (THC) decreased compared to diesel. PM_2.5 levels dropped with the additions of advanced biofuels relative to pure HVO and ULSD. CO emission factors were below EU Stage V limits, but slight exceedances occurred for THC and NOx. Full article

The ReFuelEU Aviation Regulation introduces mandatory targets for sustainable aviation fuels (SAF) from 2025 to 2050. However, hydrotreated esters and fatty acids (HEFA) technology based on waste oils alone is insufficient to meet targets beyond 2030, highlighting the need for alternative biocrude feedstocks to increase SAF production in the EU. Microalgae are promising feedstocks due to their biochemical composition and CO₂-utilization potential, although their high moisture content and nitrogen and oxygen levels require energy-efficient conversion technologies. Hydrothermal liquefaction (HTL) is a suitable process for converting wet microalgal biomass into biocrude, with an optimal temperature window of approximately 300–330 °C and typical biocrude yields ranging from 20 to 70 wt%, depending on feedstock composition and operating conditions. However, microalgal HTL remains at TRL 5–7 and faces challenges related to the high heteroatom content of the resulting biocrude. Hydrodeoxygenation (HDO) is a key upgrading step for converting biocrude into drop-in aviation fuels and commonly operates at approximately 250–400 °C and 10–30 MPa H₂ pressure. Nevertheless, few studies have addressed the HDO of microalgae-derived biocrude. This review examines microalgal HTL, pilot and demonstration facilities, biocrude yields and quality, and upgrading strategies for producing synthetic drop-in aviation biofuels. Full article

This work assesses the real-world performance and emission characteristics of a compression-ignition (CI) engine fuelled with a blend of conventional diesel and a bioethanol-derived higher-alcohol fuel (Catalyxx C4+), evaluated under the World Harmonized Light-Duty Vehicle Test Cycle (WLTC). Both cold- and hot-start conditions were analysed, corresponding to coolant temperatures of 20 °C and 70 °C, respectively, in order to capture representative operating scenarios ranging from short-distance urban driving to extended real-world use. Catalyxx C4+ is a renewable drop-in biofuel produced via the thermocatalytic conversion of bioethanol and consists of a mixture of linear and branched higher alcohols spanning C4 to C8. A fuel blend containing 20% Catalyxx C4+ by volume (80% diesel) demonstrated substantial emission benefits relative to neat diesel. Under cold-start operation, particle number (PN), particle mass (PM), and CO emissions were reduced by 61.6%, 77.8%, and 39.3%, respectively. Even greater reductions were observed under hot-start conditions, with decreases of 64.0% in PN, 78.5% in PM, and 66.9% in CO emissions. These results highlight the strong potential of bioethanol-derived higher-alcohol drop-in fuels to significantly mitigate pollutant emissions in CI engines. Furthermore, they emphasize the importance of evaluating sustainable alternative fuels under test conditions that closely reflect real-world vehicle operation, encompassing both low-temperature engine start-up and fully warmed, long-distance driving scenarios. Full article