Mohamed Farghali, A. Osman, Israa M A Mohamed
et al.
New technologies, systems, societal organization and policies for energy saving are urgently needed in the context of accelerated climate change, the Ukraine conflict and the past coronavirus disease 2019 pandemic. For instance, concerns about market and policy responses that could lead to new lock-ins, such as investing in liquefied natural gas infrastructure and using all available fossil fuels to compensate for Russian gas supply cuts, may hinder decarbonization efforts. Here we review energy-saving solutions with a focus on the actual energy crisis, green alternatives to fossil fuel heating, energy saving in buildings and transportation, artificial intelligence for sustainable energy, and implications for the environment and society. Green alternatives include biomass boilers and stoves, hybrid heat pumps, geothermal heating, solar thermal systems, solar photovoltaics systems into electric boilers, compressed natural gas and hydrogen. We also detail case studies in Germany which is planning a 100% renewable energy switch by 2050 and developing the storage of compressed air in China, with emphasis on technical and economic aspects. The global energy consumption in 2020 was 30.01% for the industry, 26.18% for transport, and 22.08% for residential sectors. 10–40% of energy consumption can be reduced using renewable energy sources, passive design strategies, smart grid analytics, energy-efficient building systems, and intelligent energy monitoring. Electric vehicles offer the highest cost-per-kilometer reduction of 75% and the lowest energy loss of 33%, yet battery-related issues, cost, and weight are challenging. 5–30% of energy can be saved using automated and networked vehicles. Artificial intelligence shows a huge potential in energy saving by improving weather forecasting and machine maintenance and enabling connectivity across homes, workplaces, and transportation. For instance, 18.97–42.60% of energy consumption can be reduced in buildings through deep neural networking. In the electricity sector, artificial intelligence can automate power generation, distribution, and transmission operations, balance the grid without human intervention, enable lightning-speed trading and arbitrage decisions at scale, and eliminate the need for manual adjustments by end-users.
Being declared a global emergency, the COVID-19 pandemic has taken many lives, threatened livelihoods and businesses around the world. The energy industry, in particular, has experienced tremendous pressure resulting from the pandemic. In response to such a challenge, the development of sustainable resources and renewable energy infrastructure has demonstrated its potential as a promising and effective strategy. To sufficiently address the effect of COVID-19 on renewable energy development strategies, short-term policy priorities should be identified, while mid-term and long-term action plans should be formulated in achieving the well-defined renewable energy targets and progress towards a more sustainable energy future. In this review, opportunities, challenges, and significant impacts of the COVID-19 pandemic on current and future sustainable energy strategies were analyzed in detail; while drawing from experiences in identifying reasonable behaviors, orientating appropriate actions, and policy implications on the sustainable energy trajectory were also mentioned. Indeed, the question is that whether the COVID-19 pandemic will kill us or provide us with a precious lesson on future sustainable energy development.
This study constructs a multidimensional exposure index for 242 European regions to assess vulnerabilities linked to the European Union’s transition to climate neutrality under the European Green Deal and Fit for 55. Using principal component analysis on 11 indicators of fossil fuel dependence and emissions intensity, four key exposure dimensions are identified: coal and heavy industry, oil refining and maritime trade, end-use emissions, and agricultural emissions. The results reveal concentrated exposure across several member states, underscoring the need for place-sensitive just transition policies that support reskilling, economic diversification, and equitable climate action across regions.
The global shipping industry, as a core vehicle for international trade, is also a key area of carbon emissions. In recent years, the International Maritime Organization (IMO) has successively introduced policies such as amendments to Annex VI of the International Convention for the Prevention of Pollution from Ships (MARPOL) and the Carbon Intensity Index (CII), explicitly requiring ships to reduce fuel consumption and greenhouse gas emissions. Ship energy efficiency management has become a core issue for sustainable operations for shipping companies. Traditional energy efficiency management relies on manual record-keeping and empirical judgment, suffering from data lag, a single analysis dimension, and insufficiently targeted optimization solutions, making it difficult to meet the needs of refined emissions reduction. Digital technology, with its advantages of real-time data collection, multi-dimensional analysis, and dynamic optimization, offers new solutions for ship energy efficiency management. This paper examines the application of digital technology in ship energy efficiency management. First, it identifies the core requirements of ship energy efficiency management and the compatibility of digital technology. Then, it analyzes the practical path and existing challenges of digital technology from four perspectives: data collection and processing, energy efficiency optimization strategies, technical bottlenecks, and industry implementation challenges. Finally, it offers targeted recommendations based on the current state of the industry. Research has found that technologies such as the Internet of Things, big data, and artificial intelligence have achieved initial application in ship fuel consumption monitoring, route optimization, and power system control. However, challenges remain, such as poor data interoperability, high investment costs for small and medium-sized shipbuilders, and insufficient digital skills for crew members. This study can provide practical references for shipbuilders in advancing the digital transformation of energy efficiency management and offer insights into how the industry can address digital implementation challenges.
In the 21st century, transitioning to renewable energy sources is imperative, with fossil fuel reserves depleting rapidly and recognizing critical environmental issues such as climate change, air pollution, water pollution, and habitat destruction. Embracing renewable energy is not only an environmental necessity but also a strategic move with multiple benefits. By shifting to renewable energy sources and supporting their production through the acquisition of renewable energy certificates, we foster innovation and drive economic growth in the renewable energy sector. This, in turn, reduces greenhouse gas emissions, aligning with global efforts to mitigate climate change. Additionally, renewable energy certificates ensure compliance with regulations that mandate the use of renewable energy, enhancing legal adherence while promoting transparency and trust in energy sourcing. To monitor the uptake of renewable energy, governments have implemented Renewable Energy Certificates (RECs) as a tracking mechanism for the production and consumption of renewable energy. However, there are two main challenges to the existing REC schema: 1) The RECs have not been globally adopted due to inconsistent design; 2) The consumer privacy has not been well incorporated in the design of blockchain. In this study, we investigate the trading of RECs between suppliers and consumers using the directed acyclic graph (DAG) blockchain system and introduce a trading schema to help protect consumer information. Our results demonstrate lower transaction time by 41\% and energy consumption by 65\% compared to proof-of-stake.
Mansoor Alghamdi, Ahmad Abadleh, Sami Mnasri
et al.
The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time (T95 and worst-case exposure) and decreases both event energy Eevent and CO2-equivalent CO2event while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load Uenergy and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages.
Determining the influence of climate policy uncertainty (CPU), fossil fuel dynamics, and renewable energy (REE) adoption on carbon market volatility (CTM) is essential for ensuring its stability and sustainable development. Therefore, this study captures the dynamic relationships among CTM, CPU, crude oil (COP), coal (COA) and REE across different time horizons utilizing a Time-Varying Parameter Structural Vector Autoregression with Stochastic Volatility (TVP-SVAR-SV) model. Results reveal that in the short term, shocks from CPU, COP, COA, and REE all significantly intensify carbon price fluctuations. In the medium term, the carbon market exhibits heightened sensitivity particularly to CPU and COA shocks, while the effects of all factors diminish over the long term. Furthermore, the analysis confirms pronounced time-varying characteristics, with the influence of oil prices on carbon price volatility notably strengthening over time. By comparing influence degree, CPU and COP emerge as the more influential and volatile drivers, whereas the impact of COA remains more stable. Finally, all shocks are significantly amplified during periods of major external disruption, especially during the Russia-Ukraine conflict. These findings highlight the importance of maintaining clear climate policy signals and stabilizing energy market dynamics to enhance the resilience and efficiency of carbon markets.
The steel manufacturing industry is one of the most energy-intensive sectors, making it highly sensitive to input cost fluctuations, especially raw material and energy prices. This study investigates the impact of key input price volatility - including iron ore, coking coal, and fuel oil - on the profitability of listed steel companies in Vietnam between 2019 and 2024. Using panel data of ten publicly traded firms and applying robust estimation techniques including Pooled OLS, Fixed Effects, and Feasible Generalized Least Squares (FGLS), the study evaluates how variations in input costs affect return on equity (ROE), a proxy for financial performance. The empirical results reveal that rising prices of coking coal and fuel oil have a significantly negative effect on profitability, whereas fluctuations in iron ore prices exhibit a more complex and less consistent impact. Additional control variables such as exchange rate and financial leverage also contribute to profitability volatility. The findings underscore the vulnerability of energy-dependent industrial sectors in emerging markets to raw material cost shocks, particularly under global supply disruptions and geopolitical tensions. This paper provides policy implications for risk mitigation, suggesting that firms in the steel sector should adopt hedging strategies and diversify energy sources, while national policymakers should consider strategic stockpiling and tax incentives to stabilize energy input costs. The results also add to the literature on energy price transmission and profitability under uncertainty in transitional economies.
Á. Galán‐Martín, Richard Cabrera-Jiménez, S. Bueno-Rodríguez
et al.
Ceramic manufacturing is a hard-to-abate industry given its intrinsic reliance on high-temperature operations and fossil-based thermal energy. Capitalizing on detailed industrial data, this study presents a prospective life cycle assessment of decarbonization pathways for ceramic brick production grounded in forward-looking energy system projections. Six technology adoption scenarios are evaluated for 2020 and 2050 under both current policy and net-zero trajectories. Results show that integrating heat pumps today for low-temperature drying can reduce the global warming potential (GWP) by up to 24% compared to continued natural gas use. Fuel-switching to hydrogen or biogas enables substantial reductions in the GWP of around 85% under net-zero conditions. Notably, coupling biogas combustion with carbon capture and storage (CCS) already achieves net-negative emissions, reaching −29.95 kg CO2-eq per tonne in 2020 and up to −73.05 kg by 2050, positioning it as a viable carbon dioxide removal strategy. However, several scenarios exhibit important trade-offs, including increased water consumption and land occupation, particularly in hydrogen and biobased pathways. Our findings underscore the need for integrated policies and multicriteria decision-making considering impacts beyond climate change to align energy transition and technology adoption, ensuring decarbonization strategies in the ceramic sector are both practical and sustainable.
Tudor Octavian Pocola, Valentin Robu, Jip Rietveld
et al.
Recent years have seen rapid increases in intermittent renewable generation, requiring novel battery energy storage systems (BESS) solutions. One recent trend is the emergence of large grid-connected batteries, that can be controlled to provide multiple storage and flexibility services, using a stacked revenue model. Another emerging development is renewable energy communities (REC), in which prosumers invest in their own renewable generation capacity, but also requiring battery storage for flexibility. In this paper, we study settings in which energy communities rent battery capacity from a battery operator through a battery-as-a-service (BaaS) model. We present a methodology for determining the sizing and pricing of battery capacity that can be rented, such that it provides economic benefits to both the community and the battery operator that participates in the energy market. We examine how sizes and prices vary across a number of different scenarios for different types of tariffs (flat, dynamic) and competing energy market uses. Second, we conduct a systematic study of linear optimization models for battery control when deployed to provide flexibility to energy communities. We show that existing approaches for battery control with daily time windows have a number of important limitations in practical deployments, and we propose a number of regularization functions in the optimization to address them. Finally, we investigate the proposed method using real generation, demand, tariffs, and battery data, based on a practical case study from a large battery operator in the Netherlands. For the settings in our case study, we find that a community of 200 houses with a 330 kW wind turbine can save up to 12,874 euros per year by renting just 280 kWh of battery capacity (after subtracting battery rental costs), with the methodology applicable to a wide variety of settings and tariff types.
The theory talks at Moriond QCD and High-Energy Interactions 2025 covered the full range of scales from BSM, top, Higgs, EW, and hard QCD physics, through resummation, factorisation, and PDFs, to hadronic, heavy-ion, nonperturbative, and lattice QCD. A few talks also touched on methodologies. We here summarise main points of most of these contributions.
We explore novel classes of exotic astrophysical sources capable of producing ultra-high-energy gamma rays extending beyond the PeV scale, motivated by quantum gravity scenarios and dark matter phenomenology. These sources include: ultra-spinning black hole vortex-string systems; exotic compact objects such as boson star, axion star and Q-ball. Such Exotica generate powerful magnetic fields through interactions with millicharged dark matter, enabling particle acceleration mechanisms that surpass the energy limits of conventional astrophysical sources like pulsar wind nebulae and supernova remnants. We demonstrate that such exotic PeVatrons could be distributed throughout our Galaxy and may be detectable by current (LHAASO, HAWC) and next-generation (CTA) gamma-ray observatories.
Jurisdictions have implemented a variety of policy instruments to mitigate greenhouse gas emissions. However, interactions between overlapping climate policies can lead to unintended impacts. This study examines how interactions between two policies in California, the low-carbon fuel standard and cap-and-trade program, impact emissions, costs, and innovation. Simulations using a computable general equilibrium model suggest that interactions between an LCFS and an emissions cap can result in higher emissions and higher average abatement costs relative to an emissions cap alone. Emissions increase as a result of the LCFS incentivizing greater production of alternative transportation fuels with upstream production emissions in sectors not covered by the emissions cap. Inter-industry emissions leakage can be mitigated by incorporating elements of a fixed-price instrument (i.e. carbon price floor/ceiling) to improve policy complementarity or requiring an obligation for the lifecycle GHG emissions of fuels under the emissions cap.
Soukaina Ouhame, Moulay Youssef Hadi, Amine Mrhari
et al.
The widespread demand for hosting application services in the cloud has been fueled by the deployment of cloud data centers (CDCs) on a global scale. Furthermore, modern apps' resource needs have sharply increased, especially in industries that use a lot of data. As a result, more cloud servers have been made available, resulting in higher energy usage and, ecological problems. Large-scale data centers have been developed as a result of the rapidly increasing demand for cloud services, allowing application service providers to rent data center space for application deployment by user-required quality of service (QoS). These data centers use a lot of electricity, which raises running expenses and produces more carbon dioxide (CO2) emissions. Modern cloud computing environments must also provide QoS for their users, necessitating a trade-off between power performance, energy consumption, and service-level agreement (SLA) compliance. We present an intelligent resource management policy using enforcement learning for CDCs. The objective is to continuously consolidate and dynamically allocate virtual machines (VMs). Utilizing live migration and disabling inactive nodes to reduce power consumption in this cloud environment while maintaining service quality. To enable dynamic resource management, a better power-performance tradeoff, and significantly lower energy consumption, we integrate several artificial intelligence concepts. Based on the result the proposed approach is more efficient as compared with other techniques.
The improvements in energy intensity of India’s iron and steel industry despite the limited research and development (R and D) expenditure, high cost of adapting technologies/fuel and heavy dependence on coal-based process is intriguing. In attempting to understand the underlying drivers, this article uses firm-level panel data to show that firms have improved their energy intensity through retrofitting of the existing production utilities and ‘brownfield’ installations in the form of technology extensions. The improvements are essentially on account of the use of imported capital goods/equipment rather than core R and D. For policy, this highlights critical dependence on imports of green goods in meeting the net-zero targets. The finding is used to call for technology transfers as part of brownfield installations and policy interventions to support the domestic capital goods industry for reducing the dependency on imports. On the sidelines, the results also show that international trade has a positive externality through supporting the environment.
China has become a major global power due to its rapid economic growth, which is being driven by resource-intensive industries but at a considerable environmental cost. This study investigates the intricate relationships that exist between China's mining regulations, resource utilization, and environmentally friendly policies, as well as the overall impacts of these relationships on economic growth. The research uses a rigorous regression analysis approach and data from the Ministry of National Resources and the China Statistical Yearbook from 1986 to 2022. Integrating a Vector Error Correction Model (VECM) enables an investigation of the relationships among debt levels, GDP, and natural financing. Wald test estimates also reveal exact Corporate Social Responsibility (CSR) relationships. The results indicate that while China's economy has significantly benefited from mineral-intensive sectors, green measures are urgently needed to slow environmental deterioration. The focus should be redirected toward encouraging sustainable and ongoing development. These results highlight the critical role that green projects play in fostering economic growth. How China strikes a careful balance between its goals for ecological sustainability and economic growth is crucial for both China and the rest of the world in an era characterized by worries about climate change and resource shortages. The objective of this study is to analyze the complex relationship among China's mining regulations, resource utilization, and environmental policies. It will evaluate the effects of these factors on economic growth, with a particular focus on the necessity of adopting sustainable development practices in the face of environmental challenges and economic expansion. The study's goal is to examine the intricate relationships between China's resource use, environmental policies, and mining restrictions. It focuses on the importance of sustainable development methods in the face of environmental issues and economic growth. This research highlights the essential relationship between environmental stewardship and sustainable economic development, and policymakers, businesses, and environmental activists can all benefit from it.
Abstract Energy access is crucial for human well-being and poverty reduction. In sub-Saharan Africa, the failure of grid systems to provide electricity access to last mile users has led to the rapid scale up of off-grid solutions. The authors examine synergies and tradeoffs between solar off-grid solutions and the Sustainable Development Goals (SDGs) in Rwanda which as a nation has successfully implemented innovative solar off-grid systems at scale. This paper is the first to map the relationship between energy and the 169 Targets of the 2030 Agenda in a specific country and sector context by operationalising the framework developed in Fuso Nerini et al. (2018). By doing so, this paper demonstrates the need for context-specific rapid assessment tools to monitor and improve energy access. The paper identifies synergies between 80 (47%) of the SDG targets and off-grid solar systems in Rwanda, thus demonstrating the wideranging benefits and value added through the inclusion of the off-grid solar energy sector in the electrification strategy. The paper demonstrates how mainstreaming off-grid policies and prioritising investment in the off-grid sector can realise human development and well-being, build physical and social infrastructures, and achieve sustainable management of environmental resources.