The transition to a circular economy (CE) is critical for mitigating the environmental impacts of industrial processes and products. Electric vehicles (EVs), a key segment of the mobility sector, play a pivotal role in this transition. Effectively managing EV batteries through their entire life cycle is essential, given their potential for reuse before disposal. This study investigates various circularity indicators and frameworks introduced in recent research, proposing a novel framework aimed at managing the sustainable lifespan of EV batteries on a mesoscale (industrial) level. The developed framework comprehensively addresses material flow, end-of-life management, and energy flow throughout the service life of EV batteries. The framework was developed and validated through interviews with stakeholders and academic experts, employing Structural Self-Interaction Matrix (SSIM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analyses. Fifteen circularity indicators were identified and applied to a case study of an EV product using the gathered data and assumptions based on scientific and grey literature. Quantified CE scores show progress in collaboration and renewable energy use but highlight challenges like material outflows, insufficient inflows, and poor end-of-life management. The framework offers a robust approach to improving circular economy practices and fostering a more sustainable automotive industry.

Sustainable decarbonizing a coal-dependent energy system faces significant challenges, particularly in countries where the entire energy infrastructure, social and economic activities are heavily reliant on traditional fossil-based technologies. These challenges are related to the fact that Kosovo and other similar countries have built their entire energy systems, social activities and economies around coal, making the transition to cleaner and sustainable alternatives a complex and multifaceted endeavor. This study investigates the overall Kosovo energy system balance while analyzing different sustainable scenarios that explore the design of the mix of technologies in electricity production while paving the way for smart energy system approach utilization. The critical excess electricity production method is used as a tool to identify what's happening with the energy system infrastructure and how Kosovo is uniquely dealing with that. Strategies for recovering old coal units with refurbishment and upgrading units, while integrating Wind and PV and introducing new technologies such as gas power plants without compromising natural resources (bioenergy) are investigated and finally discussed from a border preceptive to link with other spatial and international studies. The EnergyPLAN model, with technical simulation strategy, is used for modelling and scenario analysis of different sustainable transformative changes in the electricity technology production mix in Kosovo considering hourly balances of energy flows. The findings show that recovery of coal-based technologies and introduction of gas power plants with other studies on bioenergy, and increasing variable renewable can additionally contribute to creating a sustainable mix of energy production technologies while significantly contributing to climate change adaptability for heavily depended coal countries.

The energy demand for cooling in India is projected to double between 2017 and 2027, driven by rapid urbanisation, rising temperatures, and increased access to appliances. As of 2017, approximately 42 % of this demand was met by inefficient, refrigerant-based air conditioners (approximately 42 million units), which contributed significantly to greenhouse gas emissions. In light of India's climate commitments and the Kigali Amendment, which targets the reduction of hydrofluorocarbons, District Cooling (DC) emerges as a more sustainable and scalable alternative. Although air coolers and fans remain widespread, they often fail to meet the standards for maintaining thermal comfort and indoor air quality set by ASHRAE. The centralised nature of DC enhances energy efficiency, supports integration with renewable sources, and enables equitable access to cooling services. Yet, most existing approaches for assessing cooling demand and district cooling viability rely on detailed building-level data, which are often unavailable in developing countries like India. This study presents a top-down, GIS-based approach to evaluate the spatial and economic potential for district cooling deployment in India, incorporating climate zones, population density, and national energy balances. To our knowledge, this is the first national-scale assessment that spatially quantifies DC potential by integrating cooling degree days with high-resolution (250m × 250m) population grids and energy demand indicators. The method is designed to be replicable in other data-constrained contexts, making it relevant for developing countries facing similar challenges. A sensitivity analysis assesses economic feasibility based on cooling demand density thresholds and regional climatic conditions. Results show a total estimated cooling demand of 3780 TWh for 2017, with approximately 75.9 % located in grid zones exceeding 1000 MWh/year, deemed economically viable for DC expansion. States such as Uttar Pradesh (881.3 TWh/year), Bihar (404.6 TWh/year), and Maharashtra (308.3 TWh/year) are identified as high-priority regions. Local cooling hotspots show demand densities reaching up to 529 GWh/year per 250m × 250m grid. These findings highlight both the urgency and opportunity to scale district cooling systems across India and offer a practical planning framework for sustainable cooling in rapidly urbanising, high-temperature regions globally.

In pursuit of the 2050 decarbonisation goals outlined in the Paris Agreement, the European Union aims to integrate renewable energy sources into electricity generation. However, the intermittent nature of solar and wind energy presents challenges for grid stability and reliability. Hydrogen (H2), particularly "green H2" produced through renewable electrolysis, has emerged as a promising energy carrier to complement variable renewable energy. This study investigates the technical and economic feasibility of utilising excess heat generated during Proton Exchange Membrane (PEM) electrolysis, a by-product typically underutilised, to improve the overall efficiency and cost-effectiveness of green hydrogen production. Using Aspen Plus, the study models five heat recovery scenarios: electricity generation via an ammonia Organic Rankine Cycle (ORC), direct heat supply to a District Heating (DH) network, steam generation using hydrogen and electric boilers, and a combined DH and steam generation configuration. The base case assumes no heat recovery and relies solely on cooling towers for heat rejection. Among the alternatives, the DH scenario proved to be the most economically viable, achieving a Net Present Value (NPV) of <euro>9.5 million, an Internal Rate of Return (IRR) of 0.23, and a Payback Period (PB) of 7 years, at a hydrogen price of <euro>9.5/kg. In contrast, the ORC scenario yielded a negative NPV and a payback period exceeding 30 years, indicating limited viability under current conditions. The results highlight the importance of integrating low-grade heat recovery into green hydrogen systems. Redirecting PEM excess heat to existing DH infrastructure offers the most immediate economic and technical benefits, contributing to more efficient, circular, and financially attractive hydrogen production systems.

Rising transport emissions undermine urban sustainability goals, exposing a widening gap between climate ambition and emissions trajectories. Amid these trends, in the European Union (EU), electric vehicles account for only a very small proportion of new registrations for Light Commercial Vehicles (LCVs), below the levels seen in the passenger vehicles segment. While previous studies have investigated country-specific factors, this research adopts a macro-level perspective by examining aggregate diffusion patterns of electric Light Commercial Vehicles (eLCVs) across 27 EU member states. To identify the underlying determinants of this variation, this study employed a series of panel data regression models to evaluate how a set of socioeconomic, energy, mobility, and innovation-related variables shape eLCV diffusion and, more specifically, to assess the explanatory power of these variables. Among the models tested, the Fixed Effects Model proves to be most effective in capturing these relationships, reinforcing the value of a multifactorial approach to understanding eLCV adoption dynamics. The findings enhance the understanding of structural diffusion patterns and provide an empirical basis for better aligning policy and industry efforts with the EU’s regional decarbonisation objectives.

Electrification is emerging as a key strategy for decarbonisation of shore-side energy demand at ports. However, this electrification, particularly involving electric shore-side vehicles (ESVs), has a significant impact on the local electricity grid. A key research gap pertains to the specific challenges of ESV load integration into the grid and the effectiveness of mitigation strategies like smart charging and renewable energy integration at the operational level within ports. This study directly addresses this gap through several key contributions: firstly, by quantifying the impact of ESV loads on a localised port electricity grid; secondly, by introducing and evaluating smart charging strategies coupled with solar photovoltaic (PV) integration; and thirdly, by providing practical insights derived from a real-world case study at the port of Oskarshamn. Key findings include: (i) an impact analysis demonstrating that unmanaged ('dumb') ESV charging imposes the highest stress on the local grid, necessitating costly immediate upgrades; (ii) the demonstration that optimized charging significantly reduces grid stress, effectively deferring the need for substantial infrastructure investment; and (iii) the confirmation that solar PV integration further aids in managing peak loads and enhancing overall grid stability and energy independence. These results underscore the efficacy of smart charging and renewable integration in managing ESV loads and improving grid resilience. Furthermore, the study highlights potential pathways for future energy efficiency enhancements and even the possibility of energy export within port systems.

Sweden plans to decarbonize its energy sector by 2045 through initiatives such as electrification of transport & industry, wind power expansion, HYBRIT and increased use of biomass. Hitherto studies have predominantly focused on electricity sector. Nevertheless, the targets for 2045 necessitates studying the Swedish energy system at national scale in the context of sector coupling & storage. This work examines the role of thermal energy storage (TES) and hydrogen storage (HS) in the future energy system with high proportions of wind power. Three scenarios SWE_2045, NFF_2045 and RES_100 representing three different energy systems were simulated in EnergyPLAN modelling tool, incorporating TES, HS and sector integration. The results indicate that both TES and HS can improve flexibility of the system by enhancing wind integration. Heat pumps (HPs) coupled with TES can increase wind integration by 5–9% and also reduce the operation of thermal boilers and CHP, resulting in total fuel reduction by 2–3%, depending on the scenario. However, HS is not a viable option for storing excess electricity alone, as shown in SWE_2045 since it does not facilitate additional wind integration. It demonstrates better outcome mainly when there is a significant demand for hydrogen in the system, resulting in wind integration of 6–9%. However, HS does not contribute to the reduction in total fuel since it does not have an impact on the fuel input in district heating sector.

Heating and cooling activities account for nearly half of the European Union's total energy use, yet only 23 % of this demand is met by renewable sources. As reliance on fossil fuels declines and waste suitable for incineration diminishes, alternative renewable and excess heat (EH) sources become essential. In Sweden, approximately 4.7 TWh of industrial EH is recovered annually, contributing 12 % of available EH and 9 % of the district heating (DH) supply. Despite projections that EH utilisation will rise from 22 TWh in 2015 to 33 TWh by 2050, lowtemperature levels and economic viability challenges have limited Urban Excess Heat (UEH) integration into DH systems. This study develops a spatial-techno-economic optimisation framework to support long-term UEH integration in DH networks. The framework, composed of three open-source tools for spatial network optimisation, long-term planning, and short-term operational optimisation, was applied to the City of Stockholm's DH system, where over 80 % of buildings are DH-connected. Results indicate that UEH sources within a 5-km radius of primary DH pipelines have the highest feasibility for integration. Economic analyses revealed that investment sensitivity is highest with fluctuations in electricity prices, emphasising the cost implications of energy markets on UEH feasibility. Scenarios with varying grid temperatures demonstrated that lower temperatures improve UEH uptake but require adaptive network designs for efficiency. Iterative linking of long-term and highresolution operational models highlighted differences between cost-optimal plans and operational realities, suggesting refinement needs. This framework offers robust pre-feasibility insights for stakeholders, enhancing strategic planning for sustainable urban heating across municipal and regional levels.

Integrating District Heating (DH) with the Electric Power Sector (EPS) offers a key strategy for addressing climate challenges by improving resource efficiency and enabling low-carbon transitions. Through Flexible Sector Coupling (FSC) mechanisms, DH systems can mitigate greenhouse gas emissions and enhance system flexibility by absorbing intermittent renewable electricity surpluses. This study evaluates the potential of FSC enabled through Thermal Energy Storage (TES) in DH applications, using the energy system of Oskarshamn, Sweden, as a case study. A soft-linked modelling framework is developed by combining a long-term investment optimisation model based on the Open-Source energy Modelling System (OSeMOSYS) with a high-resolution hourly dispatch model. These models are iteratively linked to align strategic investment decisions with operational feasibility. The analysis evaluates scenarios based on variations in electricity prices, TES capital costs, and the availability of self-consumption via heat pumps and excess heat. Key performance indicators, including Levelised Cost Of Energy (LCOE) and CO<inf>2</inf> emissions, are used to compare outcomes. Results show that the feasibility of FSC is strongly influenced by electricity price trends and TES investment costs. High electricity prices favour cogeneration of electricity and heat, while lower prices lead to increased investment in TES and heat pumps, prioritising heat production. Scenarios with low electricity prices achieve lower LCOEs (37.5–42.7 €/MWh) compared to those with high prices (46.6 €/MWh). The approach demonstrates that soft linking the capacity expansion model and dispatch models strengthens energy system planning by integrating long-term and short-term perspectives. Overall, the study highlights the potential of FSC with TES for cost-effective and resilient DH planning under different future energy conditions. Future work could explore the wider deployment of FSC by assessing its integration with electricity market services, expanding to multi-city or regional DH networks, and evaluating enabling policies, business models, and digital control strategies for large-scale implementation.

Increasing PV penetration in the residential sector has led to supply demand mismatch in PV in the electricity market, specially during the peak demand hours and peak PV generation hours. Smart grid and smart meters have opened up avenues for designing data driven methodologies to optimize the generation and consumption of energy. In this paper, a dynamic load control mechanism is designed which optimizes the operation of individual appliances (heat pump, electric boiler, battery storage, solar PV and electric car). The optimization algorithm utilizes rolling horizon approach to consider the real time load control. A case of an individual house in Helsinki, Finland is considered to test the developed method. The results of dynamic load control mechanism were compared with operational optimization, wherein dynamic control is not implemented with different building classification and electricity contracts. From the results, it is observed that the optimization with a longer duration offers more benefits as compared to real time control mechanism, but does not reflect a real world scenario. Additionally, consumers having electricity contracts which are variable had the most savings and provides the highest flexibility to the electricity system.