Search Results (67)

Shipping is urgently exploring alternative vessel energy sources across a wide range of options—from other fossil fuels to renewables—with a view to more sustainable ship propulsion. Based on processing of publicly available data, the authors discuss the prospects of the supply chains for 16 vessel power sources alternative to oil, comparing descriptive statistics across respective fuel supply chain key performance indicators (KPIs) to evaluate potentiality along with hidden vulnerabilities. While finding marked differences across calculated mean, standard deviation and coefficient of variation values, the authors do not preclude the development of parallel ship fuel supply chains, unlike the case of previous fuel transitions in shipping. To support this scenario, already formed in practice, they emphasize the enabling attributes of today’s world fleet in terms of total capacity and of size of each of the main shipping sectors which could eventually sustain nowadays multiple fuel supply chains. Concluding on limitations and challenges that such an energy-source multitude can create, the authors underline the need to consider in the Life-Cycle Assessment (LCA) of shipping fuels their total impact, including necessary ship hardware changes for a more thorough assessment of fuels’ impact across the entire shipping services’ supply chain. Full article

To achieve the goal of the 2015 Paris Agreement to limit global warming to 2 °C compared to pre-industrial levels, South Korea is implementing a policy to use bioethanol as a transportation fuel based on the Renewable Fuel Standard (RFS). This study proposes a mixed-integer linear programming (MILP) model to design an optimal bioethanol supply chain utilizing rice straw, a readily available resource in South Korea. To minimize the total cost of bioethanol production, the proposed model considers optimal facility locations, i.e., those of feedstock collection (farm), refining (refinery), and consumption (market), and transportation volumes. This experiment is conducted to evaluate the blending ratios of bioethanol in gasoline (3%, 6%, and 9%) specified by the Renewable Fuel Standard (RFS) policy, based on actual gasoline consumption data in South Korea. In the RFS 3% scenario, operating a single large-scale refinery was the most economical option, but in the RFS 6% and RFS 9% scenarios, multiple refineries must be utilized to ensure supply chain economics. In conclusion, the proposed MILP model shows the practicality of gradually increasing the number of refineries and selecting the optimal location for each region as future bioethanol demand increases. Full article

Rice processing generates substantial residual biomass globally—about 170 million tons of husk, 62–71 million tons of bran and 23–39 million tons of broken rice annually—which remains largely underutilized and creates environmental burdens and lost economic opportunities. This study was conducted to address the necessity for integrated sustainability assessments of rice mill biorefineries. The focus of this study is on transitioning from a global context of residual biomass generation to a local-scale application in small and medium mills (100–300 tons/day). We apply a resource-centric framework, combining process simulation, techno-economic analysis, and Life Cycle Assessment (LCA—selected for its capacity to quantify trade-offs and avoid burden-shifting across multiple impact categories) with Social-LCA. Five valorization scenarios are assessed. Results demonstrate that biorefinery pathways fundamentally alter supply provision: husk cogeneration boosts energy self-sufficiency (SGI = 12.54), displacing fossil fuels, while silica and nutrient recovery create new, local material flows, substituting for virgin resources. However, chemically intensive routes increase human toxicity impacts (up to 4.0 × 10⁻¹ kg 1,4-DB eq/kg) despite product diversification. Social analysis reveals a tension between worker preferences for advanced technology and community priorities for low-chemical, employment-generating options. Probabilistic sensitivity analysis identifies a diversified configuration (oil, flour, feed, cogeneration) as most robust, optimizing overall resource productivity and circularity. This work transitions the conceptual model of a rice mill from a linear processor to a multi-output bio-resource hub, offering actionable pathways to enhance regional energy, mineral, and nutrient security through circular economy implementation. Full article

Reducing CO₂ emissions in transport requires sustainable alternatives such as fuel cell electric vehicles. A critical challenge is the efficient and safe storage and fast refueling of hydrogen at 70 MPa. This study proposes a practical design-support tool to optimize hydrogen storage systems for heavy-duty vehicles with capacities up to 100 kg. A customizable, dynamic Matlab-Simulink model was developed, including all components from dispenser to onboard tanks, enabling evaluation of multiple design options. The aim is to provide clear guidelines to ensure fast, safe, and complete refueling compliant with SAE J2601-5 limits. Simulations showed Type III tanks deliver the best performance. The fastest refueling (~10 min) was achieved with shorter pipes, larger diameters and low temperatures (20 °C ambient, −40 °C dispenser), while Average Pressure Ramp Rate was maximized up to 9 MPa/min (220 g/s of hydrogen from the dispenser) without exceeding SAE limits for pressure and temperature. Full article

This study presents the first comprehensive techno-economic assessment of wind-based green hydrogen production across Senegal, a country highly dependent on fossil fuel imports. Using a novel integrated approach combining 30 years of ERA5 reanalysis data (1993–2023), turbine performance modeling and electrolyzer comparison, it fills an important gap for renewable hydrogen development in West Africa. Wind resources were analyzed at multiple altitudes, revealing strong potential in both coastal and northeastern regions, particularly during the dry season, with higher wind speeds at higher turbine heights. Four turbines (Vestas_150, Goldwind_155, Vestas_126 and Nordex_N100) and two electrolyzer types (alkaline and PEM) were evaluated. The alkaline system performed best. Vestas_150 and Goldwind_155 achieved the highest hydrogen yields of 241 and 183 tons/year and CO₂ reductions of 2951 and 2241 tons/year, generating carbon credits of 0.118 M$ and 0.089 M$, respectively. Their levelized cost of electricity remained low (0.042 and 0.039 $/kWh), while smaller turbines showed higher costs. Vestas_150 also had the shortest payback period of 2.16 years, making it the most competitive option. Sensitivity analyses showed that longer system lifespans and high-performance turbines significantly reduce the levelized cost of hydrogen. Priority investment zones include Saint-Louis, Matam, Louga and Tambacounda, with levelized cost of hydrogen values as low as 3.4 $/kg. Full article

This paper presents an optimal-design methodology for small-scale Integrated Energy Systems (IESs) that couple electricity and heat in distributed networks. A hybrid reliability assessment integrates probabilistic state enumeration with scenario-based simulation. Mathematically, the design is cast as a stochastic, reliability-driven ranking: time-sequential Monte Carlo (MC) produces estimators of Loss of Load Probability (LOLP), Expected Energy Not Supplied (EENS), and Self-Sufficiency Rate (SSR), which are normalized and combined into a Composite Reliability Index (CRI) that orders candidate siting/sizing options. The case study is the D-campus microgrid with Photovoltaic (PV), Combined Heat and Power (CHP), Fuel Cell (FC), Battery Energy Storage Systems (BESSs), and Heat Energy Storage Systems (HESSs; also termed TESs), across multiple siting and sizing scenarios. Results show consistent reductions in LOLP and EENS and increases in SSR as distributed energy resource capacity increases and resources are placed near critical nodes, with the strongest gains observed in the best-performing configurations. The CRI also reveals trade-offs across intermediate scenarios. The operational concept of the campus Energy Management System (EMS), including full operating modes and scheduling logic, is developed to maintain a design focus on reliability-driven decision making. Probability-based formulations, reliability metrics, and the sequential MC setup underpin the proposed ranking framework. The proposed method supports Distributed Energy Resource (DER) sizing and siting decisions for reliable, autonomy-oriented IESs. Full article

To reduce fossil fuel dependency in shipping, adopting alternative fuels and innovative propulsion systems is essential. Solid Oxide Fuel Cells (SOFC), powered by hydrogen carriers, represent a promising solution. This study investigates a multi-fuel SOFC system for ocean-going vessels, capable of operating with ammonia, methanol, or hydrogen, thus enhancing bunkering flexibility. A thermodynamic model is developed to simulate the performance of a 3 kW small-scale system, subsequently scaling up to a 10 MW configuration to meet the power demand of a container ship used as the case study. Results show that methanol is the most efficient fueling option, reaching a system efficiency of 58% while ammonia and hydrogen reach slightly lower values of about 55% and 51%, respectively, due to higher auxiliary power consumption. To assess technical feasibility, two installation scenarios are considered for accommodating multiple fuel tanks. The first scenario seeks the optimal fuel share equivalent to the diesel tank’s chemical energy (17.6 GWh), minimizing mass increase. The second scenario optimizes the fuel share within the available tank volume (1646 m³), again, minimizing mass penalties. In both cases, feasibility results have highlighted that changes are needed in terms of cargo reduction, equal to 20.3%, or, alternatively, in terms of lower autonomy with an increase in refueling stops. These issues can be mitigated by the benefits of increased bunkering flexibility. Full article

The ongoing energy transition and decarbonization efforts have prompted the development of Hybrid Renewable Energy Systems (HRES) capable of integrating multiple generation and storage technologies to enhance energy autonomy. Among the available options, hydrogen has emerged as a versatile energy carrier, yet most studies have focused either on stationary applications or on mobility, seldom addressing their integration withing a single framework. In particular, the potential of Metal Hydride (MH) tanks remains largely underexplored in the context of sector coupling, where the same storage unit can simultaneously sustain household demand and provide in-house refueling for light-duty fuel-cell vehicles. This study presents the design and analysis of a residential-scale HRES that combines photovoltaic generation, a PEM electrolyzer, a lithium-ion battery and MH storage intended for direct integration with a fuel-cell electric microcar. A fully dynamic numerical model was developed to evaluate system interactions and quantify the conditions under which low-pressure MH tanks can be effectively integrated into HRES, with particular attention to thermal management and seasonal variability. Two simulation campaigns were carried out to provide both component-level and system-level insights. The first focused on thermal management during hydrogen absorption in the MH tank, comparing passive and active cooling strategies. Forced convection reduced absorption time by 44% compared to natural convection, while avoiding the additional energy demand associated with thermostatic baths. The second campaign assessed seasonal operation: even under winter irradiance conditions, the system ensured continuous household supply and enabled full recharge of two MH tanks every six days, in line with the hydrogen requirements of the light vehicle daily commuting profile. Battery support further reduced grid reliance, achieving a Grid Dependency Factor as low as 28.8% and enhancing system autonomy during cold periods. Full article

The increasing carbon footprint of civil aviation has made the use of Sustainable Aviation Fuel (SAF) a strategic necessity in line with the sector’s sustainability goals. This study evaluates the existing SAF types based on environmental, economic, technical and social criteria, determines the criteria weights with Fuzzy-Step-Wise Weight Assessment Ratio Analysis (F-SWARA) and selects the most suitable alternative through Spherical Fuzzy-Multi Objective Optimization on the basis of Ratio Analysis plus full MULTIplicative form (SF-MULTIMOORA) method. The alternative evaluation process was carried out on a Python-based online platform and sensitivity analysis was performed on five different scenarios. According to the findings, the Hydroprocessed Esters and Fatty Acids (HEFA-SPK) alternative stands out as the most suitable option in all scenarios, followed by the Fischer-Tropsch Synthetic Paraffinic Kerosene (FT-SPK) alternative. In contrast, Alcohol-to-Jet (ATJ-SPK) and Power-to-Liquid (PtL) options seem to be more variable and less stable. The study provides methodological contributions for the evaluation of SAF alternatives with fuzzy multi-criteria decision making (MCDM) methods and provides strategic implications for manufacturers and airlines in achieving the low-carbon targets of the aviation sector. Full article

This study presents a comprehensive performance assessment of combustion-based options for Bioenergy with Carbon Capture and Storage (BECCS), widely regarded as key enablers of future climate neutrality. From 972 publications (2000–2025), 16 sources are identified as providing complete data. Seven technologies are considered: Calcium Looping (CaL), Chemical Looping Combustion (CLC), Hot Potassium Carbonate (HPC), low-temperature solvents (mainly amine-based), molten sorbents, Molten Carbonate Fuel Cells (MCFCs), and oxyfuel. First- and second-law efficiencies are reported for 53 bioenergy configurations (19 reference plants without carbon capture and 34 BECCS systems). Performance is primarily evaluated via the reduction in second-law (exergy) efficiency and the Specific Primary Energy Consumption per CO₂ Avoided (SPECCA), both relative to each configuration’s reference plant. MCFC-based systems perform best, followed by CLC; molten sorbents and oxyfuel also show very good performance, although each is documented by a single source. Low-temperature solvents span a wide performance range—from poor to competitive—highlighting the heterogeneity of this category; HPC performs in line with the average of low-temperature solvents. CaL exhibits modest efficiency penalties alongside appreciable energy costs of CO₂ capture, a counterintuitive outcome driven by the high performance of the benchmark plants considered in the definition of SPECCA. To account for BECCS-specific features (multiple outputs and peculiar fuels), a dedicated evaluation framework with a revised SPECCA formulation is introduced. Full article

Given the decline in fossil energy reserves and the need for less pollution, achieving carbon zero is challenging in major industrial sectors. However, the emergence of large-scale hydrogen production systems powered by renewable energy sources offers an achievable option for carbon neutrality in specific applications. When combined with energy storage systems, static power converters are crucial in these production systems. This paper offers a comprehensive review of various power converter topologies, focusing on AC– and DC–bus architectures that interface battery storage units, electrolyzers, and fuel cells. The evaluation of DC/AC, AC/DC, and DC/DC converter topologies, considering cost, energy efficiency, control complexity, power level suitability, and power quality, represents a significant advancement in the field. Furthermore, the subsequent exploration of battery aging behavioral modeling, characterization methods, and real-time parameter estimation of the battery’s equivalent electrical circuit model enhances our understanding of these systems. Large-scale hydrogen production systems most often use an AC–bus architecture. However, DC–bus configuration offers advantages over AC–bus architecture, including high efficiency, simpler energy management, and lower system costs. In addition, MVDC or HVDC DC/DC converters, including isolated and non-isolated designs based on multiple cascaded DABs and MMC-type topologies, have also been studied to adapt the DC–bus to loads. Finally, this work summarizes several battery energy storage projects in the European Union, specifically supporting the large-scale integration of renewable energy sources. It also provides recommendations, discussion results, and future research perspectives from this study. Full article

The mitigation of climate change impacts from the automotive sector is important for sustainable development, and for that purpose, synthetic liquid fuel vehicles (SLF-Vs) are being considered as a potential clean option alongside electric vehicles (EVs). However, the energy-intensive production of synthetic liquid fuels (SLFs) requires a thorough life-cycle analysis, as CO₂ emissions vary significantly depending on the power sources and feedstock production technologies. This study evaluates the life-cycle CO₂ emissions of SLF-Vs in Japan through long-term multiple scenarios up to 2050 and compares them with those of gasoline vehicles (GVs), hybrid electric vehicles (HEVs), and battery electric vehicles (BEVs). The results reveal that, in 2020, SLF-Vs’ life-cycle CO₂ emissions were more than 2.9 times higher than those of GVs. By 2050, SLF-Vs’ emissions could only decrease to BEV-like levels if Japan achieves significant decarbonization of its power grid. Even if hydrogen is produced via water electrolysis in Australia, where renewable energy is abundant, and then imported, emissions remain high if Japan’s power grid remains insufficiently decarbonized. This highlights the critical importance of expanding domestic decarbonized power sources, particularly renewable energy, to reduce the life-cycle CO₂ emissions of SLF-Vs in Japan. Full article

This study investigates the application of deep learning (DL) techniques for predicting temperature fields in the SM1 swirl-stabilized turbulent non-premixed flame. Two distinct DL approaches were developed using a comprehensive CFD database generated via the steady laminar flamelet model coupled with the SST k-ω turbulence model. The first approach employs a fully connected dense neural network to directly map scalar input parameters—fuel velocity, swirl ratio, and equivalence ratio—to high-resolution temperature contour images. In addition, a comparison was made with different deep learning networks, namely Res-Net, EfficientNetB0, and Inception Net V3, to better understand the performance of the model. In the first approach, the results of the Inception V3 model and the developed Dense Model were found to be better than Res-Net and Efficient Net. At the same time, file sizes and usability were examined. The second framework employs a U-Net-based convolutional neural network enhanced by an RGB Fusion preprocessing technique, which integrates multiple scalar fields from non-reacting (cold flow) conditions into composite images, significantly improving spatial feature extraction. The training and validation processes for both models were conducted using 80% of the CFD data for training and 20% for testing, which helped assess their ability to generalize new input conditions. In the secondary approach, similar to the first approach, studies were conducted with different deep learning models, namely Res-Net, Efficient Net, and Inception Net, to evaluate model performance. The U-Net model, which is well developed, stands out with its low error and small file size. The dense network is appropriate for direct parametric analyses, while the image-based U-Net model provides a rapid and scalable option to utilize the cold flow CFD images. This framework can be further refined in future research to estimate more flow factors and tested against experimental measurements for enhanced applicability. Full article

Nickel’s durability and catalytic properties make it essential in the aerospace, automotive, electronics, and fuel cell technology industries. Wastewater analysis typically relies on sensitive but costly techniques such as ICP-MS, AAS, and ICP-AES, which require complex equipment and are unsuitable for on-site testing. This study introduces a novel screen-printed electrode array with 16 chemically and, optionally, electrochemically coated Au electrodes. Its electrochemical response to Ni²⁺ was tested using Na₂SO₃ and ChCl-EG deep eutectic solvents as electrolytes. Ni²⁺ solutions were prepared from NiCl₂·6H₂O, NiSO₄·6H₂O, and dry NiCl₂. In Na₂SO₃, the linear detection ranges were 20–196 mM for NiCl₂·6H₂O and 89–329 mM for NiSO₄·6H₂O. High Ni²⁺ concentrations (10–500 mM) were used to simulate industrial conditions. Two linear ranges were observed, likely due to differences in electrochemical behaviour between NiCl₂·6H₂O and NiSO₄·6H₂O, despite the identical Na₂SO₃ electrolyte. Anion effects (Cl⁻ vs. SO₄²⁻) may influence response via complexation or ion pairing. In ChCl-EG, a linear range of 0.5–10 mM (R² = 0.9995) and a detection limit of 1.6 µM were achieved. With a small electrolyte volume (100–200 µL), nickel detection in the nanomole range is possible. A key advantage is the array’s ability to analyze multiple analytes simultaneously via customizable electrode configurations. Future research will focus on nickel detection in industrial wastewater and its potential in the multiplexed analysis of toxic metals. The array also holds promise for medical diagnostics and food safety applications using thiol/Au-based capture molecules. Full article

Fossil fuels are among the most crucial factors underlying global environment impairment through CO₂ emissions. In addition to this, the globalized world has witnessed significant price volatility, instability and disruptions in the supply of fossil fuels. Therefore, renewable energy transition (RET) has become a mandatory option for countries to tackle these environmental, economic, and energy insecurity problems in energy markets dominated by fossil fuels. But the RET process has remarkably slowed down in recent years due to increasing economic volatility, financial obstacles, geopolitical risks, and bottlenecks in the development of low-carbon technologies. In this regard, this study investigates the effect of market structure proxied by economic freedom and indicators of financial development, together with real GDP per capita and education, on the utilization of renewable energy in post-transition EU member states across the 2000–2021 duration by utilizing causality and cointegration tests. The outcomes of the causality analysis reveal a feedback relationship among renewable energy use, economic freedom, indicators of financial development, and real GDP per capita but a unilateral causality between education and renewable energy use. On the other hand, the outcomes of AMG estimation reveal a positive effect of economic freedom, real GDP per capita, and education on the utilization of renewable energy in some countries but a negative effect of financial institutions’ development on renewable energy use and mixed results on the effect of financial markets’ development regarding renewable energy use. Our results indicate that education is a significant instrument to make progress in renewable energy use via multiple channels, but governments should incentivize the financial system to support the RET process by favorable lending and sustainable finance instruments like green bonds or sustainability-linked loans. Full article