Balancing multiple sustainability objectives in feedstock cultivation: a case of Pongamia pinnata in Australia.

This study examined the impact of Fuel Subsidy Removal and Exchange Rate Unification on Academic Productivity in Northwest Geopolitical zone of Nigeria. The conducted in selected Federal Universities and Polytechnics in the states of Jigawa, Kaduna, Kano and Sokoto States administered questionnaire on a sample of 368 academics. Both ANOVA and independent sample-test were employed to test the impact of fuel subsidy removal in sample productivity, productivity declines and resilience to the effects of the policy. The findings revealed that research and publication activities are notably affected by the policy changes where articles in lead journals (mean = 2.93) and conference paper publications (mean = 2.63) show decline, reflecting the rising costs of publication fees, conference registration, and international travel. Additionally, on-going research activities recorded a lower mean of 2.33, indicating that many research projects may be delayed or abandoned. Furthermore, purchase of research materials, chemicals, and reagents recorded a high mean of 3.07, indicating strong agreement that increased costs have hindered such activities. This is as community service activities recorded a mean of 2.77, suggesting that academics’ engagement beyond the campus has declined due to financial and mobility constraints. The study therefore, recommends among other things that, Federal Government employ targeted Transportation and Energy Support for Academics through the introduction of subsidized staff transport systems to mitigate the mobility challenges of fuel subsidy removal. While, management in tertiary institution in the area of study should, prioritized investment in alternative and renewable energy sources on campuses to reduce dependence on costly generators. Keywords: Academics, Productivity, Fuel Subsidy Removal

Promoting sustainable agriculture through circular hydrogen production, storage and utilization.

Processes for generating clean hydrogen from waste plastics through thermochemical methods such as pyrolysis and gasification are a promising solution for both waste management and clean energy initiatives. Then, this derived hydrogen powers the fuel cell, which produces electricity that can be directly fed to charge electric vehicles (EVs). Although this complex process has many challenges related to energy efficiency during the conversion processes—starting from the generation of hydrogen from thermochemical processes and hydrogen storage and followed by fueling the fuel cells and charging EV infrastructure—the simplistic conceptual modeling developed for this research demonstrates how an ecosystem of such processes can be made feasible commercially. Clean hydrogen generated using known techniques reported in the literature is promising for commercialization, but harnessing hydrogen from plastics offers additional benefits, such as reducing greenhouse gas (GHG) emissions. Overall, the feasibility of clean hydrogen using this methodology is not limited by potential cost inefficiencies, especially when savings from GHG emissions reduction are taken into account. EVs have become commercially viable thanks to high-energy-density Li-ion batteries. And therefore, research continues to optimize charging performance through the integration of renewable energy and battery storage systems. This study examines another potential of clean hydrogen: its use as a power source in grids, especially V-2-G (vehicle-to-grid) systems. Additionally, direct current (DC) power from a fuel cell powers an EV charger at DC input voltages for e-ambulances. In particular, this designed system operates on DC voltages throughout the power system, combining high-voltage direct current (HVDC) lines, renewable energy sources, DC-DC converters, DC EV chargers, and other supporting components. The literature review identified gaps in plastics production, waste management, and processes for converting them into useful energy. The presented model is a stepping stone towards a novel, innovative process for clean hydrogen production to power electric vehicle charging infrastructure for emergency response systems in healthcare, thereby improving public safety. The limitations of the study would be governed by the effective establishment of locations where waste management services are performed (for example, landfills) and adoption by local government authorities with deregulated power systems.

The development of renewable energy in rural areas presents significant potential. Integrating renewable energy sources, such as wind power and photovoltaics, into microgrids as distributed generation systems offers a viable approach for local energy utilization. In recent years, the rapid advancement of agriculture, forestry, animal husbandry, and fisheries has led to an increasing demand for electricity in these regions. However, the existing power infrastructure remains underdeveloped, resulting in a pronounced imbalance between supply and demand. This paper investigates the optimization of rural microgrid configurations by incorporating demand response strategies and the synergistic interactions among wind turbines, photovoltaic systems, batteries, and loads. A multi-objective optimization model is developed to maximize annual profits and environmental externality (namely, the proposed microgrid achieves equivalent carbon dioxide emissions reductions by replacing thermal power generation through either selling green electricity to the main grid or meeting rural load demands), which is subsequently transformed into a single-objective formulation using the Shapley value method and solved via a global harmonic search algorithm. Simulation results validate the applicability of the proposed solution method and demonstrate the economic performance, development potential, and environmental benefits of the optimized microgrid configurations.

Abstract—The rapid integration of renewable energy sources into residential power systems has increased the need for efficient, decentralized energy management solutions. Peer-to-peer energy trading has emerged as a promising approach to enable house- holds to exchange surplus renewable energy directly, reducing de- pendency on centralized grids and improving energy utilization. This literature survey reviews existing research on peer-to-peer energy markets, blockchain-based energy trading frameworks, smart contracts, and decentralized grid architectures. It also examines the role of artificial intelligence in forecasting energy generation and consumption to enhance trading efficiency and grid stability. Additionally, the survey analyzes simulation-based approaches used to model virtual energy communities for evalu- ating system performance and scalability. The review highlights key challenges such as interoperability, real-time coordination, pricing mechanisms, and security, while identifying research gaps that motivate the development of an integrated virtual peer-to- peer renewable energy trading and simulation system. Index Terms—Peer-to-Peer Energy Trading, Blockchain, Re- newable Energy, AI Forecasting, Smart Grid Simulation, Smart Meter, Decentralized Energy Systems

Increasing the proportion of renewable energy sources, such as photovoltaic power, in the grid can reduce fossil fuel consumption and build a low-carbon power system. However, the inherent instability of the photovoltaic power output makes it difficult to predict, thus increasing the cost of grid operation. Therefore, to improve the accuracy of power prediction and promote the development of the grid, a four-stage short-term photovoltaic power prediction framework, namely, CDT, is proposed, which includes decomposition, classification, reconstruction and forecasting. The initial power data are decomposed using complete ensemble empirical mode decomposition with adaptive noise. Next, an improved data classification and reconstruction method based on dynamic time warping is developed to process the data, which reduces the dimensionality of the data while preserving trend information. Finally, the reconstructed components are predicted using the improved TCN model. The results of the empirical study show that the proposed CDT has higher precision and scalability in processing and predicting the trend of photovoltaic power generation, compared to the other benchmark models.

ABSTRACT Energy poverty poses a threat to food security in South Asian countries. The study intends to evaluate the influence of energy availability on food security in South Asia using panel data for the period 2000 to 2022. The study has constructed an energy availability index as a proxy for energy availability to gauge its influence on food security. Other variables included in the analysis are agriculture labor, agriculture capital, military expenditure, remittances, income growth, and financial development. The model is estimated by using panel cointegration, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques. The estimated results demonstrate that energy availability significantly and positively affects food security in South Asia. Agriculture capital, remittances, income growth, and financial development improve food security, while agriculture labor and military expenditure deteriorate food security in the region. Governments need to increase energy availability mainly through renewable energy sources to ensure food security in the region. JEL Classifications: C23, O13, Q43

Africa is engaging more with technology and artificial intelligence (AI) and is no longer playing catch-upto the rest of the world in terms of technology and innovation. This paper examineshow companies in Africa are employing AI to generate new sources of value through local enterprises. The findings demonstrate that the time-to-market of financial products can be reduced by up to 50percent with AI and other operational efficiencies can be accumulated. Moreover, thisresearch analysed the most significant barriers for companies across all eight sectors identified in adopting AI sustainably (i.e., infrastructure shortcomings, talent shortage, regulation-related challenges). The study demonstrates that the value or economic effects of AI could generate in the range of $100 billion per year; nonetheless, it suggests that realizing this value is not simply a matter of doing 'more of the same' (e.g., developing 'one-size-fits-all' Western solutions), but necessitates 'localised' adaptations for specific regions and countries. In the finalsection, recommendations for policymakers regarding cross-border data governance, and for investors to develop computationally efficient infrastructure based on renewable energy sources that will bridge the digital divide and enable smart economies are put forth. The research results of this article provide a basis for understanding how AI promotes enterprise development.

The problems are that: (i) frequent power outage by inadequate infrastructure and outdated technologies led to poor supply, (ii) limited access to reliable electricity and high cost of installation of off-grid energy and fossil fuel caused financial burden on households in the region, (iii) lack of a reliable energy, low renewable sources and reliability misconceptions affected the usage of renewable energy in the region, (iv) overall reliance on fossil fuel such as: diesel and petrol despite its high cost had contributed to global warming, and lack of strong implementation strategies and research affected renewable energy applications in the region. The study is aimed at comparing models for non-conventional energy supply to a four storey Building using Gauss-Seidel Algorithm in Abo-Mbaise, Imo State, southeast region, Nigeria. The objectives of the study are to: (i) evaluate the current energy infrastructure and consumption pattern in a-six- person-household per flat in the region, (ii) identify the renewable energy resources available in the region, (iii) assess the technical, economic and viability of implementing different renewable energy systems in a-four-storey-Building and the environmental impact of utilization in the region, and (v) apply optimization algorithm on different renewable energy sources on design configurations and fabrication. The reliability of the research experiment was determined using Pearson product moment correlation (r). The experimental result of (r), was found to be approximately (r = 1.0) which confirmed 100% (percent) level of performance between the model and prototype (fabricated Flywheel). The result also shows that there exist a strong correlation between the designed (model) and the fabricated (prototype). The work concluded that: (i) the cost of energy per kwh from Enugu Electricity Distribution Company (EEDC) is ₦53.78, Solar/Battery option is ₦65.62, Flywheel option is ₦34.27, Biomass option is ₦49.97 and Wind option is ₦74.01.Therefore, cost of energy for a-4-hour supply per flat of 6-person-household per month from EEDC is ₦18,070, while (ii) the optimization (GA) results show that for every-24-hour: (i) Wind option has a minimum cost of N14.66million in 30years, N488,666:67K in one year, N40,722:22K in one month per Building of 8flats, and per flat of 6persons has to pay N5090:00K ($3.4 US Dollars) per month, (ii) Biomass option has a minimum cost of N20.62million in 30years, N687,333:33K in one year, N57,277:78K in one month per Building of 8flats, and per flat of 6persons has to pay N7,160:00K ($4.8 US Dollars) per month, (iii) Flywheel option has a minimum cost of N6.9million in 30years, N230,000:00K in one year, N19,166:67K in one month per Building of 8flats, and per flat of 6persons has to pay N2,396:00K ($1.6 US Dollars) per month and (iv) Solar/Battery has a minimum cost of N28.16million in 30years, N938,666:67K in one year, N78,222:22K in one month per Building of 8flats, and per flat of 6persons has to pay N9,778:00K ($6.5 US Dollars) per month. It further concluded that there is zero emission of Co2 and other green house gasses using the Flywheel energy generating system and also it is the most efficient option. The work recommended that: for federal government of Nigeria to realize her vision/policy on climate change and SDG 2030: the Federal Housing Authority should promulgate a law for the provision of power supply in any building meant for rent age to reduce over-reliance on national grid, and the said regulatory council should implement the collection of appropriate tariffs using off-grid power supply in collaboration with other organizations in the renewable energy field.

The paper examines the energy transition using Poland as a case study. The model was estimated based on annual data for Poland for the period of 1990–2024 (n = 35). The estimation was carried out using the OLS method with HAC correction, and the statistical significance of parameters was assessed using statistical tests. Based on econometric analysis, the impact was examined throughout the entire research period, with additional analysis of the structural break dummy for 2015. It was verified whether this impact had changed since 2015 compared to the earlier period. The data were used to calculate indicators, arranged in three groups: (1) capacity availability indicators (for the availability of the overall power system and for the renewable energy sources (RES)); (2) indicator of emission intensity (the indicator was defined as the ratio of total greenhouse gases emission to real GDP); (3) indicator of the economy’s energy intensity (the indicator was defined as primary energy consumption per unit of GDP). Annual summaries of these indicators constituted the input data for econometric modelling. The aim of the empirical analysis was to deepen the identification of mechanisms shaping greenhouse gas emission intensity by incorporating into the model indicators of generation capacity availability and measures of the economy’s energy intensity. The data collection based on constructed greenhouse gas emission intensity and energy intensity indicators of the economy enables the analysis of the increase in emission intensity regardless of the scale of the economy, in the system of power availability for the entire energy system, as well as for renewable energy sources. This approach makes it possible to move away from the analysis of absolute volumes toward a structural perspective that better reflects the real production capabilities of the power system as well as the efficiency of energy use in the economy. The results indicate that economic energy intensity is the dominant determinant of greenhouse gas emission intensity in Poland during the research period. The econometric analysis estimates show a positive and statistically significant relationship between energy intensity and emissions intensity, whereas generation capacity availability indicators—both for the total power system and for renewable energy sources—do not exhibit statistically significant effects. However, it was found that this impact was not constant throughout the entire period (β is 0.455 for pre-2015 and 0.325 for post-2015). Sensitivity analysis based on point elasticities reveals that a 1% increase in energy intensity of GDP leads to an increase in greenhouse gas emission intensity (by approximately 1.18% pre-2015 and 0.85% post-2015), whereas analogous changes in total capacity availability and RES availability are associated with substantially smaller effects (0.10% and 0.20%, respectively). These findings suggest that improvements in economy-wide energy efficiency played a more decisive role in reducing emissions intensity than short-term variations in generation capacity availability.

Hydrogen is a clean and sustainable energy source that has the potential to significantly lower carbon emissions worldwide and facilitate the switch to renewable energy sources. Meanwhile, one of the biggest obstacles to its broad use, is still sufficient hydrogen storage. This article provides a broad overview of hydrogen storage, tracing its historical development, exploring its diverse applications, examining technological advancements, addressing existing limitations, recent progress in reducing costs, and discussing the current state of the art in storage technologies, along with future directions for improvements in all forms of hydrogen storage methods. Therefore, this review highlights recent breakthroughs in hydrogen storage techniques, advances in cost reduction, and offers a step by step guide to designing next-generation functional hydrogen storage materials for improved performance, which are essential for both developed and developing hydrogen economies in cost reduction and better performance for hydrogen storage materials.

Statistical modeling of the ocean environment is important for many practical applications in science and engineering. Probabilistic descriptions of the ocean environment are important input for structural design and risk assessment of marine structures, including ships, offshore and coastal structures, and aquaculture installations. They are also essential for the safe operation of ships and other structures at sea. Additionally, they are critical for planning and decision-making in the exploitation of marine renewable energy sources such as waves, tides, and offshore wind. This article presents a review of recent developments with regard to statistical modeling of the ocean environment, with a particular focus on ocean waves. Such developments are driven by an increasing volume of available data, increasing computational capabilities, and demand from the industry for more accurate and uncertainty-aware descriptions of relevant oceanic variables. Hence, statistical modeling of the ocean environment remains an active area of research, with significant developments in various directions. These are reviewed in this article.

Electrochemical hydrogen production and conversion using renewable energy sources have become a key topic in catalysis research. Platinum and Pt-group metals are among the best materials promoting H2 evolution (HER) and oxidation (HOR) reactions. However, the nature of active surface sites should be further elucidated to improve their performance and gain a better fundamental understanding of those processes. This is not a trivial task, mainly due to the high surface mobility of the H-species. Here, we use in situ electron paramagnetic resonance (EPR) spectroscopy to investigate the Pt surface in the so-called underpotential deposition (UPD) region in acidic media and observe EPR responses indicative of hydrogen adsorption sites, the knowledge of which is essential for both HOR and HER. Our EPR measurements and theoretical ab initio molecular dynamics (AIMD) calculations suggest that the average adsorption sites for atomic hydrogen at the surface of platinum are either on-top sites or 3-fold hollow sites, while bridge sites are not likely to be occupied. For EPR, the intensity maximum is reached at -0.85 V versus Pt, and then the signal intensity vanishes for potentials just before HER, suggesting EPR-silent H2 formation. At the same time, ab initio density functional theory (DFT) calculations of a Pt(111) surface with 7/12 ML coverage of H at room temperature yield occupancy probabilities of 0.72 (fcc hollow), 0.26 (on-top), and 0 (bridge) for the respective sites. Hence, fcc hollow is favored over on-top adsorption sites at high coverages, which is consistent with the observation via EPR spectroscopy. To our knowledge, EPR spectroscopy was used for the first time to probe the EPR response during hydrogen electrosorption in the HUPD region at polycrystalline platinum electrodes in acidic electrolytes.

The use of renewable energy sources on board ships is one solution to reduce pollution from maritime transport. Considering it one of the many solutions for the transition to "zero" emission ships, we studied the possibility of installing a new type of power plant on ships already in operation that uses solar/photovoltaic and wind energy conversion systems. The current electricity production system is transformed into a hybrid system, and by improving the available electrical power management algorithms, clean energy consumption will be prioritized. Monitoring daily electricity consumption and recording values for renewable energy source parameters during ship periods and voyages enabled calculations to determine the potential for electricity production from renewable sources and demonstrated the viability of the chosen solution. The results obtained highlight that installing the ecological marine power plant (ENPP) can achieve significant reductions in fuel consumption for producing electricity on board the ship.

The best way to present a floating photovoltaic (FPV) system would be to recognize the increasing demand for renewable energy sources and the challenges faced by traditional land-based solar systems, including limited space and the astronomical costs of installation. One of the possible solutions to these problems is FPV systems, which use water surfaces as a place to install solar panels, such as lakes, reservoirs, and ponds. The research paper will help optimize the energy collection process for FPV systems by developing an Improved Perturb and Observe (IP&O) algorithm with a dual-inductor boost converter (DIBC). This is aimed at precise monitoring of the peak power point, particularly under changing environmental conditions. The simulation results of the suggested MPPT approach in MATLAB/Simulink are consistent with those reported in the literature. The findings show that reaction time and overall functionality of the FPV system improved significantly, highlighting the possible benefits of the IP&O algorithm for optimizing the energy output of floating solar arrays compared to the traditional MPPT approach.

The Gulf Cooperation Council (GCC) countries are accelerating their transition toward sustainable mobility as part of broader national strategies to diversify economies and reduce dependence on hydrocarbons. This paper explores the development of electric vehicle (EV) charging infrastructures and their integration with renewable energy sources across the GCC countries. It highlights key government policies, renewable energy potential, and emerging technologies such as solar-powered charging, smart grids, and vehicle-to-grid systems. While progress is evident in nations like Saudi Arabia, the UAE, and Qatar, challenges persist, including limited charging infrastructure, high costs, and climatic constraints. The study identifies opportunities for advancing sustainability through microgrids, hydrogen mobility, and regional policy harmonisation. It concludes that the decarbonisation benefits of EV charging infrastructure depend on how closely its expansion is aligned with renewable energy growth in the GCC.

Driven by the urgent need for cleaner aviation fuels, researchers worldwide are exploring renewable sources that reduce carbon emissions while ensuring fuel stability. Used Cooking Oil (UCO) has emerged as a strong contender, offering both high fat content and compatibility with existing fuel production technologies. This research conducts a Systematic Literature Review (SLR) to evaluate the potential and scalability of Used Cooking Oil (UCO) as a renewable feedstock in the production of sustainable aviation fuel. A qualitative method was employed, based exclusively on secondary data sourced from peer-reviewed scientific articles published between 2023 and 2025, retrieved from the ScienceDirect database. The review process followed the PRISMA protocol, encompassing identification, screening, eligibility, and inclusion phases. Initial results from 2,200 articles were filtered using predefined Boolean keyword combinations, publication year, research type, and access criteria, yielding 36 articles for in-depth synthesis. The analysis employed thematic coding alongside comparative synthesis to uncover consistent patterns emerging across five principal dimensions: technological readiness, environmental performance, economic feasibility, regulatory alignment, and logistical frameworks. Findings indicate that UCO-derived SAF offers up to 90% reduction in lifecycle GHG emissions, competitive production costs with fossil jet fuel under certain policies, and strong compatibility with HEFA-based refining pathways. However, supply chain limitations and regulatory harmonization remain critical challenges. In conclusion, UCO presents substantial potential as a renewable SAF feedstock, particularly in regions with established UCO collection infrastructure. Future research should focus on integrated policy mechanisms, decentralized processing models, and refinements to life-cycle assessment to support broader implementation.

The rapid growth of renewable electricity generation introduces technical challenges that were previously uncommon. These include, for example, problems with exceeding the permissible voltage values in network nodes, overloading of transformers and line sections located behind the transformer, as well as balance problems. This article proposes an original methodology for eliminating these problems. Four objective functions reflecting different operator priorities were used. Attention is drawn to the increasing importance of the development of electricity storage. The results confirm that coordinated optimisation of voltage regulation, energy storage, and flexible load management enables increased renewable energy connection capacity while reducing power losses and improving the grid voltage profile. The case study results demonstrate the effectiveness of the proposed approach under the considered operating scenarios. The proposed tool can support network operators in managing MV grid operation under the considered scenarios. The ongoing energy transition requires network operators to react quickly to emerging problems. Therefore, advanced computational methods are needed to mitigate operational risks and respond to emerging constraints.

With the aim of reducing greenhouse gas emissions from energy consumption and advancing the green energy transition, this study employs sodium hydroxide and water glass as activators to facilitate the replacement of fossil fuels with renewable energy sources, with physically activated recycled micro-powder serving as an auxiliary cementitious material to prepare alkali-activated recycled hollow concrete. This study pioneers the application of the coarse aggregate tight-packing theory (bulk density method) to the preparation of alkali-activated recycled hollow concrete containing sand. By integrating Matlab image binarization techniques, we quantitatively analyzed the causes of porosity deviation, achieving precise alignment between target and actual porosity. This work fills a theoretical gap in the quantitative design of porosity for this concrete type. Additionally, the effects of different binder material dosages and pore volumes on the mechanical properties and permeability coefficients of sand-containing porous concrete were evaluated. Experimental results indicate that the calculated pore volume of sand-containing porous concrete prepared using the dense-packing theory (bulk density method) exhibits a smaller average error compared to the actual pore volume. As the amount of cementitious materials increases, the compression strength of permeable concrete gradually increases. When the cementitious material content is 450 kg/m3, and the target porosity is 15%, the concrete’s 28-day compressive strength reaches 21.4 MPa. At a porosity of 15%, the permeability coefficient ranges from 5.2 to 5.7 mm/s.