ABSTRACT Hydrogen energy has many potential applications in manufacturing, transportation, and other industries. However, demand forecasts for industrial hydrogen are limited and unreliable. Based on the source of production, hydrogen energy can be divided into three categories: “gray hydrogen,” “blue hydrogen,” and “green hydrogen.” Among these, “gray hydrogen” is produced using fossil fuels and has high carbon emissions; “blue hydrogen” combines carbon capture and storage technology and has relatively low carbon emissions; “green hydrogen” is produced using renewable energy electrolysis and has zero carbon emissions. The study in this paper focuses on green hydrogen, which is hydrogen produced by electrolysis of water. This paper investigates the demand for industrial hydrogen using ammonia production as a case study, and it creates an intelligent forecast model for hydrogen demand. This model is built on PSO, which enhances RF, and an Optimized Least Squares Support Vector Machine modified with the Sparrow Algorithm. Firstly, this paper uses text mining to create a library of influencing factor indicators. The essential components are filtered out using a Random Forest improved on the particle swarm technique to prioritize their importance. Secondly, the paper presents an intelligent projection of the demand for industrial hydrogen in ammonia synthesis, with forecast findings ranging from 2024 to 2035. This enables us to calculate the total hydrogen demand in the industrial sector. Finally, an empirical analysis is performed using industrial hydrogen ammonia synthesis data from the national database. The intelligent prediction model proposed in this paper achieves the lowest MAPE of 7.77% and RMSE of 401.06 tons, superior to other comparison models. By 2035, ammonia demand is projected to reach 56.5 million tons, requiring 1527.23 tons of industrial hydrogen. The results show that the method described in this paper is more accurate and appropriate for estimating industrial hydrogen demand.

Purpose This study aims to develop a sustainable renewable energy strategy for Nakhon Ratchasima (KORAT), Thailand, in response to growing energy demands driven by rapid population growth and industrialisation. The research explores the optimal mix of renewable energy sources to maximise energy efficiency and sustainability in the region. Design/methodology/approach The hybrid optimisation of multiple energy resources (HOMER) Software was employed to simulate a microgrid system tailored for KORAT. The model integrated local demand profiles and climatic data to evaluate the performance and cost-effectiveness of various renewable energy technologies, including solar, hydropower, wind and energy storage systems. Findings Simulation results indicated that solar power systems are the most effective and cost-efficient renewable option for the region, closely followed by hydropower systems. Wind power demonstrated lower performance and economic viability due to local wind speeds falling below the cut-in speed of the selected turbines. Similarly, battery storage did not significantly enhance the renewable energy fraction due to limited surplus energy, indicating lower cost-effectiveness. Research limitations/implications This study is limited to a single province – Nakhon Ratchasima – which may not fully represent the diverse geographic and climatic conditions across Thailand. Despite these limitations, the findings offer a replicable framework for regional energy planning and highlight the importance of site-specific data in designing cost-effective hybrid renewable systems for Thailand and similar developing regions. Practical implications This study provides a practical framework for designing region-specific hybrid renewable energy systems using real-world data and HOMER software. The findings support policymakers, utility providers and investors in making informed decisions about energy planning in Thailand. Social implications The transition to hybrid renewable energy systems in Thailand, as demonstrated in this study, can significantly improve energy access, affordability and reliability for local communities. Reducing dependence on fossil fuels helps lower greenhouse gas emissions and air pollution, contributing to better public health outcomes. Originality/value This study presents the first HOMER-based microgrid simulation specifically focused on KORAT, providing a replicable framework for integrating renewable energy in similar regions across Thailand. It contributes valuable insights for policymakers and energy planners aiming to advance renewable energy adoption through evidence-based system design.

Clean water scarcity represents a significant global challenge, driven by the degradation of surface water resources due to pollution and the impacts of climate change. Atmospheric water harvesting strategies using sorbents offer an available and sustainable solution. Most atmospheric water harvesting studies have focused on hydrogel designs utilizing conventional polymer desiccants derived from fossil fuels. These synthetic polymers are unsustainable and nonbiodegradable, causing negative ecological and public health impacts during degradation, which raises concerns about the direction of eco-friendly material science and technology. Here, biohydrogels (SCG0, SCG3, SCG5, and SCG7) based on chitosan and carboxymethyl cellulose from biomass were synthesized through a simple process. The effect of the cross-linking content on the properties of hydrogels and their water sorption performance were studied through FTIR, TGA, and FESEM analyses, mechanical strength, and water sorption experiments. A SCG5 hydrogel containing 5% w/w glutaraldehyde exhibits the most effective cross-linking formation, leading to superior thermal stability, good compressive strength, and a better water absorption performance compared to the SCG0, SCG3, and SCG7 hydrogels. The SCG5 hydrogel showed strong hydrophilicity when a drop wetted in its surface within 0.26 s. The mass change of SCG5 in water gained 2158% with a maximum sorption rate of 84.7 g g-1 h-1, and the water vapor sorption capacity of SCG5 at 90% RH reached 28.03% with a maximum sorption rate of 0.55 g g-1 h-1. Additionally, it exhibited rapid vapor desorption with a rate of 0.39 g g-1 h-1, releasing over 98% of the absorbed water within 20 min, and remarkable stability after multiple sorption-desorption cycles. Studies on different sorption kinetic models of biohydrogels based on chitosan and carboxymethyl cellulose were carried out, and the experimental data best fitted the Elovich model the most. It means that activated site sorption is the rate-limiting process; the sorption mechanism occurs on a nonuniform surface of biohydrogels or nonconstant active sites.

Abstract With the global transition toward a sustainable energy landscape, hydrogen energy has emerged as a pivotal solution due to its renewability and zero‐carbon emissions, offering a promising alternative to fossil fuels. In recent years, ammonia (NH 3 ) decomposition for hydrogen (H 2 ) production has gained significant attention due to its cost‐effectiveness, high efficiency, high purity, zero‐carbon footprint, and excellent storage and transportability, leading to notable advancements in hydrogen production, storage, transportation, and utilization. This review systematically summarizes the primary methods and underlying reaction mechanisms of ammonia decomposition for hydrogen production, encompassing thermocatalytic decomposition, ammonia oxidation decomposition, non‐thermal plasma‐catalyzed decomposition, electrocatalytic decomposition, and photocatalytic decomposition. Furthermore, this review highlights the latest advancements in photocatalysts and electrocatalysts for ammonia decomposition, with a particular focus on the key factors influencing their catalytic performance. This review aims to provide a comprehensive perspective on the development of ammonia decomposition for hydrogen production and to offer effective strategies for catalyst optimization and process improvement, thereby facilitating the further advancement and practical application of this technology.

Research and practice experience have shown that in the Republic of Serbia, vine pruning residues (VPRs) from vineyard production are mostly partially ploughed or uncontrollably burned in fields. Uncontrolled burning of VPRs in fields can destroy flora and fauna and cause uncontrolled fires. On the other hand, on an annual basis, the resulting VPRs can completely replace the fossil fuels used for thermal energy production on these estates and significantly reduce the emission of pollutants from fossil fuels. The novelty of this study lies in the fact that the research was conducted on a very young vineyard, four years old, and the results show that the agricultural property is fully sustainable in terms of thermal energy needs. The research aimed to investigate the energy potential of VPRs at the vineyard located in the Mrčić settlement in Western Serbia. The research results include the following grape varieties: Tamjanika, Morava, Cabernet Sauvignon, and Cabernet Franc. The average yield of VPR biomass for all tested varieties was 0.387 kg/vine or 1741.50 kg/ha. The lower calorific values for the tested biomass samples at 15% moisture content ranged from 14,668 kJ/kg to 14,258 kJ/kg, while the upper values ranged from 16,099 kJ/kg to 15,721 kJ/kg. The total energy potential of biomass obtained from a vineyard, expressed in final energy, was 41.90 MWh/year. In the observed vineyard, for the same equivalent value, biomass from VPRs was 3.57 times cheaper compared to brown coal and 8.26 times cheaper compared to diesel fuel.

Biodiesel is a green, low-carbon, and renewable fuel with the potential to substitute fossil fuels. The effects of reaction temperature (175–290 °C), residence time (5–75 min), and molar ratio of methanol to palmitic acid (6:1–35:1) on the non-catalytic esterification of palmitic acid with methanol to produce biodiesel were investigated by using a batch reactor. Moreover, the reaction parameters were optimized by using the response surface methodology (RSM), and the reaction kinetics were analyzed. The results showed that the conversion rate of palmitic acid to methyl palmitate increased to 100% as the reaction temperature rose from 175 °C to 225 °C, slightly changed until 275 °C, and then decreased to 94.81% at 290 °C. The conversion rate increased with residence time and reached the maximum value of 94.93% at 60 min. With increasing the molar ratio, the conversion rate rose to a maximum value of 85.46% at 15:1 and subsequently decreased. RSM results indicated the relative influence of factors on the conversion rate as reaction temperature > residence time > molar ratio. The optimal reaction parameters were 224 °C, 26 min, and a molar ratio of 16:1, affording a palmitic acid conversion rate of 99.30%. The esterification reaction between methanol and palmitic acid follows the first-order kinetics model.

Ceiba pentandra (Kapok) has gained significant attention as a promising non-edible feedstock for biodiesel production, offering a sustainable alternative to traditional fossil fuels. The review provides a comprehensive analysis of the potential of Ceiba pentandra as an efficient biodiesel producer, including various aspects of cultivation, oil extraction, conversion processes, and future development. A scientometric analysis highlights the growing research interest in this area, while the geographical distribution and requirements of the plant site are discussed to illustrate its global availability. The review also discusses Ceiba pentandra's adaptability and growth potential in diverse environments, its oil extraction methodologies, and its suitability for biodiesel production. It evaluates various techniques, examines their efficiency, and analyzes the effects on engine performance. The economic feasibility analysis assesses commercial potential and its role in sustainable development. Furthermore, the role of Ceiba pentandra in supporting Sustainable Development Goals (SDGs), such as clean energy and climate action, is explored. Current industry developments and future prospects, including advances in conversion technologies and supply chain optimization, are discussed. The review highlights the need for continued research and investment to realize Ceiba pentandra's potential as a sustainable biodiesel source.

Purpose. The paper examines how photo-redox flow batteries can support a sustainable energy transition in Morocco and Poland by simultaneously harvesting and storing solar energy, thereby reducing dependence on fossil fuels and mitigating the intermittency of renewables. Methodology. The study combines a review of national energy policies and renewable energy targets with a comparative techno-economic assessment of photo-redox flow battery deployment scenarios in both countries, focusing on system performance, grid integration, and long-term sustainability indicators. Results. The findings show that photo-redox flow batteries can significantly increase the share of solar energy in national power mixes, improve grid stability, and lower lifecycle emissions compared to conventional storage and fossil-based generation, with particularly strong gains under high-renewables scenarios for Morocco and coal-replacement pathways for Poland. Theoretical contribution. The paper extends the emerging literature on next-generation energy storage by conceptualizing photo-redox flow batteries as a dual harvest–store technology and by linking their deployment to macro-level energy security, decarbonization, and resilience outcomes in middle-income and coal-dependent economies. Practical implications. The results provide policymakers and energy planners with evidence-based guidance on integrating photo-redox flow batteries into national energy strategies, including indicative design parameters, investment priorities, and regulatory measures to accelerate clean energy deployment while managing economic and geopolitical risks. Sustainable Development Goals (SDGs): SDG 7: Affordable and Clean Energy; SDG 9: Industry, Innovation and Infrastructure; SDG 13: Climate Action

The transportation sector's reliance on fossil fuels necessitates a transition towards sustainable alternatives like electric vehicles (EVs). While lithium-ion (Li-ion) batteries currently dominate the EV market, their limitations in charging time, thermal management, and resource sustainability motivate the exploration of advanced battery technologies. This research investigates the potential of graphene-enhanced batteries as a viable alternative for Li-ion batteries in EVs, focusing on enhancing charging efficiency and thermal management. A comparative analysis is conducted using a MATLAB-based simulation framework, modelling a graphene-enhanced battery system against a conventional Li-ion system based on considered reference of Tata Nexon EV Prime specifications. The simulations evaluate performance across various discharge rates (0.2 to 3C), analysing charging time, temperature profiles, charging efficiency, and temperature coefficients. The results demonstrate that graphene-enhanced batteries exhibit significantly faster charging times (22% - 27%), maintain lower operating temperatures (0.1to 5°C lower), and also offer the potential for substantial weight reduction i.e. 53% in the modelled simulation). These advancements, stemming from graphene's exceptional electrical and thermal conductivity, indicate a promising route toward the development of more efficient, safer, and higher-performing electric vehicles. This study provides quantitative insights into the benefits of graphene integration in EV battery technology, highlighting its potential to address key limitations of Li-ion batteries and contribute to a more sustainable transportation future.

The urgency for transition to a low-carbon economy has intensified the need for most emerging economies, including Morocco, to adopt sustainable energy growth policies. However, Morocco faces significant challenges in this transition, as fossil fuels still account for 90% of its total energy mix. With a 37% proportion of renewable energy in its capacity, Morocco now is one of the top producers of clean energy in Africa and the MENA region. Thus, we investigated the effect of financial development, human capital, and technological innovations in scaling up the clean energy transition in Morocco using the Fourier Bootstrap Autoregressive Distributed Lag approach from 1990-2021. The analysis revealed that financial development has a positive impact on the clean energy transition, this implies an increase in the short run as well as in the long run in Morocco. Human capital was also found to decelerate the energy transition in the country; this can be attributed to the lack of social awareness coping with the new transition. Furthermore, Policymakers should prioritize the strengthening of financial institutions and human capital capacity to facilitate the transition to sustainable energy.

Climate change and rapid depletion of the environmental resources pose critical threat to world economies, particularly to those who are heavily dependent on fossil fuels. The United States (US), as one of the leading carbon emitters, requires innovative strategies that integrate technology, policy, and investment to transition toward the sustainable low-carbon economy. Against this backdrop, this study examines how artificial intelligence (AI), carbon pricing mechanisms, and the green investment collectively influence energy transition and long-term emission reduction pathways. The study examines US time-series data from 1990 to 2022 using a combination of econometric modeling, such as the Autoregressive Distributed Lag technique and the Augmented Dickey–Fuller test, and Bayesian neural network forecasting. According to the findings, a 1% increase in the use of renewable energy lowers carbon emissions by roughly 0.033% in the short term. Long-term estimates, assuming continued investment in carbon pricing and technological advancement, imply a 15% reduction in emissions by 2040. Furthermore, it is anticipated that over the course of two decades, AI-driven research and development integration will increase renewable energy efficiency by 18%. In addition to offering evidence-based insights for policymakers looking to align economic and environmental goals through digital innovation and sustainability policy frameworks, our findings highlight the revolutionary potential of AI in strengthening climate mitigation initiatives.

Geothermal energy is an attractive alternative to fossil fuels because it is sustainable, supplied continuously, and has a minimal carbon footprint. Where subsurface temperatures are significantly warmer than surface temperatures, heat from the subsurface can be extracted for use on the earth's surface. In some areas, water carries heat to the surface in the form of thermal springs that support recreation and tourism. An unanswered question is whether larger scale geothermal development will lead to cooling of the recreational thermal springs or a reduction in flow rate, negatively impacting the industry. This work uses groundwater flow and heat transport modeling to evaluate the potential impact of geothermal energy production on hot springs. The modeled system is loosely based on the geologic and thermal regimes near Mt. Princeton in central Colorado, USA. The results show that the extraction of deep thermal water for geothermal energy production and the subsequent reinjection of cooled water has the potential to reduce the water temperature of surface springs.

Abstract Supply-side climate policy initiatives that restrict fossil fuel production are gathering momentum. A growing body of academic scholarship seeks to understand this new frontier in global climate governance. What is missing, however, is a deeper analysis of the relations of power that affect the adoption of supply-side policies, such as bans, moratoria, and phaseout policies, whose success is critical to addressing climate change. To provide this, we first identify the main aspects and dimensions of supply-side climate policies and why they are important. Second, we explore the forms of power that “close down” supply-side climate policies, focusing in turn on the power of fossil capital, the geopolitical power of fossil fuels, and the cultural power of fossil fuels. In each case, we propose ways in which countervailing forces can “open up” supply-side climate policies to disrupt incumbent power and unlock the potential of alternative energy futures beyond fossil fuels.

Abstract Renewable energy is energy that is generated from natural processes that are continuously replenished. This includes sunlight, geothermal heat, wind, tides, water, and various forms of biomass. This energy cannot be exhausted and is constantly renewed. Alternative energy is a term used for an energy source that is an alternative to using fossil fuels. Generally, it indicates energies that are non-traditional and have low environmental impact. The term alternative is used to contrast with fossil fuels according to some sources. By most definitions alternative energy doesn't harm the environment, a distinction which separates it from renewable energy which may or may not have significant environmental impact. Keywords: Renewable energy, geothermal heat, wind, tides.

Abstract Renewable energy has emerged as one of the most considerable and sustainable alternatives to conventional fossil fuels, with solar photovoltaics (PV) playing a leading role in this transition. Among the different PV technologies, perovskite solar cells (PSCs) have gained remarkable attention due to their excellent optoelectronic properties, tunable bandgap, and low fabrication cost. However, stability and toxicity issues associated with lead-based perovskites have encouraged researchers to explore lead-free alternatives. In this work, we present a simulation-based investigation of a tin-based double perovskite solar cell with the structure FTO/CdS/CsSnBr₃/MoO₃/C using the SCAPS-1D environment. A comprehensive analysis was performed by systematically varying critical device parameters, including absorber thickness, donor and acceptor concentrations, ETL and HTL thicknesses, temperature, back contact work function, and both shunt and series resistances. The optimized device exhibited a remarkable power conversion efficiency (PCE) of 23.87%, with an open-circuit voltage (Voc) of 1.44 V, a short-circuit current density (Jsc) of 19.67 mA/cm², and a fill factor (FF) of 83.97%. Furthermore, a comparison with various reported studies revealed that our proposed device demonstrates strong agreement with existing literature, validating the reliability of both the simulation and experimental results. Overall, the findings highlight the significant potential of CsSnBr₃-based lead-free double PSCs for future commercialization.

Accumulation of greenhouse gases from combustion of fossil fuels drives climate change and threatens biosustainability on Earth. Microbial gas fermentation realizes the capture of CO2 toward biomanufacturing of value-added products. Acetogens are attractive biocatalysts here, as they use CO2 as their sole carbon source with H2. Metabolic engineering of novel cell factories is, however, hampered by the slow and complex genetic engineering workflows. Here, we developed different approaches to optimize plasmid curing from genetically engineered strains of the model acetogen Clostridium autoethanogenum. Interestingly, a CRISPR/Cas9-based curing plasmid (C-plasmid) targeting the origin of replication both in the target editing plasmid and in the C-plasmid did not improve curing over a non-targeting control plasmid. Strikingly, plasmid curing by making cells electrocompetent (ECCs) and by non-transformative electroporation of ECCs or buffer-washed glycerol stocks showed 14-100% curing efficiencies across the approaches for five different genetically engineered C. autoethanogenum strains. The most time-efficient approach with non-transformative electroporation of buffer-washed glycerol stocks also cured an editing plasmid from Escherichia coli, with ∼97% efficiency. This work both improves genetic engineering workflows for C. autoethanogenum by significantly accelerating plasmid curing and offers methods to potentially ease plasmid curing in other microbes.

ABSTRACT During the long Sixties, fossil fuels and petrochemicals became central to Yugoslav contemporaneity, enabling the production of energy (coal-fired power plants), the movement of people and goods (gasoline), construction (bitumen), and mass consumption (various plastics). Petrochemicals were also quickly adopted and adapted for artistic use. However, the increasing reliance on fossil fuels and petrochemicals in industrialization, urbanization, and consumption also brought about pollution. The focus of this article is on those art practices that explicitly dealt with the environment, in particular, on the Clear Streams Family, a back-to-the-land artistic commune founded by Božidar Mandić in 1977. The Clear Streams Family deliberately and completely avoided the use of synthetic products in their art, insisting on wood, stone, and other naturally occurring materials. The Clear Streams Family must be understood not only within the framework of the neo-avant-garde Yugoslav New Art Practice, but also as a reaction to petromodernity, a set of practices based on the use of fossil fuels that encompasses several decades of postwar industrialization, urbanization, and consumption, leading to ever-increasing environmental degradation.

To align with global climate goals, the International Maritime Organization (IMO) has enforced strict measures to reduce greenhouse gas emissions from the shipping industry by promoting energy efficiency and cleaner propulsion methods. Ship engines remain major contributors to environmental pollution due to their dependence on fossil fuels and inefficient propulsion systems, highlighting the need for clean and sustainable alternatives. This study aims to design a renewable energy-based marine power system that effectively stores and utilizes solar energy, improving overall efficiency and reducing emissions for process innovation. A hybrid setup was developed using photovoltaic (PV) panels, batteries, and a bidirectional DC-DC converter to enable flexible power flow during both charging and discharging cycles. An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm was employed alongside a SEPIC converter to enhance energy extraction from the PV system under dynamic conditions. The integrated system achieved a power extraction efficiency of 97.12%, confirming the effectiveness of the ANFIS-based MPPT strategy and showcasing the viability of intelligent renewable energy solutions in maritime applications.

Energy is an indispensable necessity for human life. Human life shows an energy-based development. This energy needs of developing societies tend to increase continuously due to demographic, social, and economic factors. Every society attempts to meet this increasing energy need by using certain resources. Iraq mostly uses natural gas and oil to meet its expanding energy needs. In this study, the amount of energy that Iraq will produce from oil and natural gas for ten years has been estimated by using the artificial neural network model, which is used in many fields due to its high estimation skills. The amount of energy produced from natural gas and oil in Iraq between 1972 and 2022 was taken as annual data. After training the data, the weights with the lowest error margin were determined, and the estimation was made. A different 10-year energy production estimate for natural gas and oil was created using the artificial neural network. Iraq is predicted to produce energy mostly by using fossil fuels such as oil and natural gas between 2023 and 2032. This study will be a helpful resource for the Iraqi government in shaping its future energy policy.

Beyond fossil fuels: How Iceland's oil efficiency, hydro energy, and fiscal decentralization propel a cleaner environment: Evidence from wavelet quantile methods