Introduction: Industry 5.0 challenges European industries to elevate their systems with the help of technological and digital transformations and, at the same time, motivates them towards achieving the sustainable development goals (SDGs). Energy system transformations and sustainable transitions are the key concepts in decarbonizing energy sources, believed to greatly contribute to the achievement of climate neutrality. The mitigation of greenhouse gas emissions is supported by energy production from renewable resources instead of fossil fuels. The present study assesses how efficiently the member states of the European Union (EU) convert primary energy into useful energy and how this efficiency affects carbon emissions, using energy data collection since 1990 by the Directorate-General for Energy of the European Commission.

Methods: We analyze the relationships and trends between energy conversion efficiency and carbon emissions based on metrics including system energy conversion efficiency, carbon intensity of energy use, and energy loss ratio. The system energy conversion efficiency determines how much useful energy comes from the national energy system relative to the total energy input. The carbon intensity of energy use defines how carbon-efficient the energy conversion system is by the ratio of total CO₂ emissions to total energy output. The energy loss ratio quantifies wasted energy in terms of thermodynamic inefficiencies.

Results: Based on the latest available energy data from 2023 for the EU, we report a 71.58% energy conversion efficiency, 90.70% carbon intensity, and an energy loss ratio of 28.42%. Furthermore, we analyze trends among the member states based on the three studied metrics between 1990 and 2023, classifying the countries.

Conclusions: We assess the importance of improving energy conversion efficiency and reducing emissions in the EU using harmonized EU energy statistics, enabling a system-level assessment of national energy performance. Our study relates the changes in practices in energy generation on a country-level over the years to the system energy conversion efficiency, carbon intensity of energy use, and energy loss ratio.

INTRODUCTION

Limiting global warming to 1.5 °C above pre-industrial levels is one of the greatest challenges humanity faces in the 21^st century. Achieving this goal requires capturing CO₂ emissions not only from large point sources but also from dispersed and hard-to-abate sectors. Traditional CO₂ capture systems have been optimized for large-scale emitters, such as power and cement plants and steel industries. Therefore, a completely new approach is needed.

Direct Air Capture (DAC) emerges as a complementary technology, enabling the removal of CO₂ directly from the atmosphere by using a solvent or sorbent that binds with CO₂ in an air contactor. Then, a CO₂-concentrated gas stream is produced during the regeneration step. DAC can deliver negative emissions when combined with permanent CO₂ storage, or contribute towards carbon neutrality if the captured CO₂ is reused, for instance, in synthetic fuel production. As such, it is considered a promising option for offsetting past emissions and those generated by sectors that are difficult to decarbonize. DAC systems offer additional advantages, as they can be deployed without disrupting current systems and almost anywhere independently of emission sources, which allows them to operate in affordable locations with abundant renewable energy.

Despite its benefits, DAC faces challenges that hinder large-scale deployment stemming from the low concentration of CO₂ in ambient air—around 500 ppm. This results in high process energy requirements and capital costs for large air contactors that are needed to process vast volumes of air to reach relevant scales (i.e., capturing MtCO₂ per year), thus leading to higher costs per tCO₂ captured compared to conventional methods targeting major emitters. It is therefore essential to ensure that air contactors and functional materials are of low specific cost in order to design competitive DAC systems at large scales.

In this context, the use of solid lime-based materials such as Ca(OH)₂ is regarded as a promising solution to overcome the costly barriers associated to the capture device. Over the last few years, the CO₂ Capture Group at INCAR-CSIC (CapCO₂) has focused on the development of Ca(OH)₂-based DAC systems, leveraging its extensive experience in CO₂ capture using Ca-based sorbents at high temperatures in several Calcium Looping configurations for a range of industrial applications. Carbonation of CaO or Ca(OH)₂ sorbents with CO₂ is at the core of these systems, followed by sorbent regeneration via oxy-calcination to produce a nearly pure CO₂ stream.

This work provides a summary and update of the research conducted by CapCO₂ in the field of DAC by testing Ca-based sorbents under different configurations and operating conditions, with the aim of scaling up the proposed technology.

METHODS

Several gas–solid contact configurations were evaluated to identify optimal Ca-based materials and air contactor modes that maximize CO₂ capture rates and overall efficiency. Particle-scale experiments were conducted to determine reaction kinetics, maximum conversion and the influence of key parameters, such as air humidity and effective solid porosity, on material carbonation under ambient conditions.

Subsequent scale-up of the Ca-based air contactor was achieved at TRL3. To this end, Ca-based powders, dry mortars and other Ca-based forms were arranged to validate the gas–solid contact modes proposed.

These experimental setups enabled the evaluation of a broad range of operating conditions, including effective porosities between 0.20 and 0.55, gas velocities from 0.5 to 5.5 m/s, air humidity ranging from 0 to 90% RH and gas–solid contact lengths spanning from a few centimeters in fixed-bed configurations to up to 10 m in single-channel arrangements.

RESULTS

Tests conducted at both particle scale and TRL3 have served as a proof of concept for Ca-based air contactors designed to maximize CO₂ capture from ambient air under extended operating periods and variable conditions. More than 3,000 operating hours under CO₂ capture have been accumulated at TRL3 so far, with individual experiments lasting up to 300 hours in capture mode and demonstrating sustained average CO₂ capture efficiencies of approximately 55%, at least 20% greater than those observed in batch mode under similar conditions.

Particle-scale reaction modeling indicates that the carbonation kinetics are primarily governed by CO₂ diffusion through the carbonated product layer. The measured kinetics were subsequently incorporated into a simplified one-dimensional reactor model, which was validated against TRL3 experimental results for both batch and counter-current contact modes, thereby providing a robust basis for technology scale-up.

CONCLUSIONS

The results presented here indicate that Ca-based sorbents constitute a viable alternative for DAC under standard conditions. The CapCO₂ Group is actively advancing research in this area and will present its latest developments.

ACKNOWLEDGEMENTS

This work is part of the project PID2024-162594OB-I00 funded by MICIU/AEI/10.13039/501100011033 and by ERDF/UE.

Fertilizer management plays a vital role in sustaining crop productivity and soil health. Conventional broadcasting techniques often lead to nutrient losses through leaching, volatilization, and runoff, resulting in reduced fertilizer use efficiency, often resulting in considerable nutrient losses, repeated field operations, and increased energy demand, thereby contributing to environmental pollution and inefficient resource utilization. To address these challenges, precision application methods such as root zone fertilization have gained importance, ensuring nutrients are delivered closer to the plant’s uptake region for enhanced efficiency. This research focuses on the introduction of an Unmanned Ground Vehicle (UGV) for precise fertilizer implantation in the root zone of wide-row crops. The energy-efficient Unmanned Ground Vehicle (UGV) system comprises key components including a chassis with an electric drive mechanism, a GPS-based navigation and positioning unit, a soil-probing and penetration tool, and a controlled fertilizer metering and delivery system. The coordinated operation of these components enables accurate placement of fertilizer at predefined depths and spatial intervals, ensuring targeted nutrient delivery with minimal human intervention. Such precision reduces off-target fertilizer losses and enhances nutrient uptake efficiency by placing nutrients closer to the active root zone of plants. From an energy perspective, the proposed UGV system offers multiple advantages over conventional tractor-based fertilizer application methods. Targeted fertilizer implantation near the root zone enhances nutrient uptake efficiency and lowers fertilizer losses to the surrounding environment caused by leaching and volatilization. Consequently, the system reduces the frequency of fertilizer applications and associated energy-intensive field operations. The use of electric drive further supports reduced fossil fuel dependence and lower operational emissions compared to conventional machinery. The proposed UGV-based root zone fertilizer implantation system highlights strong potential to improve energy efficiency, reduce environmental impacts, and support sustainable nutrient management practices. The study highlights the role of electrically powered autonomous machinery as a viable solution for low-energy, climate-resilient agricultural systems, aligning with global efforts toward sustainable energy utilization in modern agriculture.

Diesel generator sets remain a primary source of electricity in many remote and isolated areas due to their robustness, dispatchability, and ease of deployment. But their high fuel consumption and emissions of pollutants pose economic challenges and environmental concerns, especially in regions with high fuel transportation costs. Improving the efficiency of diesel-based power generation is essential for enhancing the sustainability and reliability of off-grid energy systems.

Pneumatic hybridization of diesel engines is a promising method of enhancing brake thermal efficiency and specific power output. In this approach, compressed air is used to assist the intake process and modify in-cylinder thermodynamic conditions, potentially improving combustion efficiency while reducing fuel consumption and emissions.

This study proposes a data-efficient optimization framework combining Diesel-RK engine-cycle simulation with Bayesian optimization. The Diesel-RK model is treated as a computational black-box function that maps controllable engine operating variables to performance and emissions-related outputs. The optimization problem is formulated with multiple objectives, including maximizing brake thermal efficiency and minimizing brake-specific fuel consumption, while satisfying operational constraints, such as the required electrical power output and the allowable peak in-cylinder pressure.

Bayesian optimization is particularly suited to optimization problems involving computationally expensive black-box models such as Diesel-RK engine simulations. In contrast, widely used population-based metaheuristic algorithms, including genetic algorithms, particle swarm optimization, and differential evolution, typically rely on large populations of candidate solutions and repeated generations of objective function evaluations to converge toward optimal solutions. When each evaluation requires a detailed engine-cycle simulation, these methods can result in high computational costs. Bayesian optimization constructs a probabilistic surrogate model of the objective function using a Gaussian process. In addition, it guides the search using an acquisition function that balances exploration of the design space and exploitation of promising operating regions. This surrogate-based strategy allows for efficient identification of candidate optimal solutions while significantly reducing the number of expensive simulation evaluations.

The proposed framework aims to determine optimal operating conditions for pneumatic-hybrid diesel generators for remote power applications. The analysis will quantify the influence of pneumatic assistance on brake thermal efficiency, fuel consumption, and emissions indicators, including nitrogen oxides and soot formation. In addition, the study will evaluate the computational efficiency of Bayesian optimization relative to conventional metaheuristic methods, focusing on convergence behavior and the number of required simulation evaluations.

The proposed methodology provides a systematic framework for optimizing pneumatic-hybrid diesel generators used in remote and off-grid energy systems, aiming to improve fuel efficiency, reduce operating costs, and mitigate environmental impacts associated with diesel-based electricity generation.

Introduction

Indoor swimming pool facilities are classified among the most energy-intensive public buildings due to their continuous operation and the high demand for thermal energy, electricity, and water. The necessity to maintain stable thermal and hydraulic conditions for sanitary safety and user comfort results in substantial energy consumption, primarily associated with pool water heating and mechanical ventilation systems. The temperature of the pool water directly governs evaporation intensity, which affects latent heat losses, indoor air humidity, and ventilation loads, thus creating strong interdependencies between the water treatment processes and energy demand. The consumption in swimming pool facilities is mainly driven by filter cleaning, water renewal requirements, and sanitary regulations, which further increase the demand for thermal energy due to the need for continuous reheating of make-up water. As a result, the heating, ventilation, and pool water treatment systems form an integrated energy–water system, in which suboptimal installation design leads to increased energy consumption and operational inefficiencies. Rising energy prices, growing pressure on freshwater resources, and the implementation of climate and environmental policies require the improvement of energy efficiency in existing swimming pool infrastructure. Many facilities constructed 15–25 years ago lack integrated solutions for energy management, heat recovery, and water reuse. This study addresses this gap by evaluating the role of installation design in improving energy and resource efficiency, with a focus on integrated modernization strategies based on hybrid energy systems and water recovery technologies.

Methods

The study used a case study methodology applied to existing indoor swimming pool facilities located in different climatic regions of Poland: Ełk, Limanowa, and Skoczów. The selected facilities represent different construction periods, system layouts and operational profiles, allowing a comparative assessment of energy and water performance under varied boundary conditions. The first stage involved the determination of the baseline energy and water consumption. This assessment was based on long-term utility billing data, measurements from building management systems (BMSs), direct meter readings, and supplementary on-site measurements. The collected data was used to quantify annual and specific consumption of thermal energy, electricity, and water, as well as to identify the dominant energy loads associated with pool water heating, air handling units, ventilation, and auxiliary installations. Subsequently, a detailed technical evaluation of heating systems, ventilation, air conditioning (HVAC) units and pool water treatment installations was performed. Based on functional and energy analysis, multiple retrofit scenarios were developed and modelled, including gas-fired boilers, electrically driven heat pumps, micro-cogeneration (CHP) units, photovoltaic (PV) systems, and hybrid system configurations. For each scenario, steady-state energy balances, operational expenditures, and CO₂ emissions were calculated, accounting for regional climatic conditions, energy price structures, and system efficiencies. Energy analyses were further integrated with assessments of water recovery potential, water reuse schemes, and heat recovery from wastewater streams, enabling a comprehensive evaluation of coupled energy–water optimization strategies.

Results

The results indicate that optimized installation design and system configuration, particularly the integration of multiple heat and power sources, significantly enhance the overall energy performance of indoor swimming pool facilities. The analysed facilities exhibited annual thermal energy demands in the range of 1.25–1.64 GWh year⁻¹ and annual electricity consumption between 0.82 and 0.89 GWh year⁻¹ under baseline operating conditions. These values confirm the high energy intensity characteristic of indoor swimming pool infrastructure. The implementation of hybrid energy systems that combine microcogeneration (CHP) units, electrically driven heat pumps, and photovoltaic (PV) installations resulted in substantial reductions in energy demand. Thermal energy consumption decreased by 20–50%, while electricity demand was reduced by 15–25%, depending on facility size, operational profile, and system configuration. Renewable and hybrid energy systems were capable of covering approximately 40–70% of the total energy demand, thus significantly improving energy autonomy. These improvements translated into operational cost reductions of up to 50% and an annual decrease in CO₂ emissions of approximately 30–40 t CO₂ per facility. The highest energy performance was observed in facilities equipped with integrated control strategies that coordinate pool, heating, ventilation, and irrigation systems, which enabled load balance, reduced peak demand, and improved overall system efficiency.

Conclusions

The study confirms that installation design has a decisive influence on the energy performance of indoor swimming pool facilities. Modernization strategies should therefore address the facility as an integrated energy–water system throughout its life cycle. Combining renewable energy technologies with water and heat recovery solutions enables substantial reductions in energy and water consumption while maintaining user comfort and sanitary safety. Such an integrated approach supports the transition toward low-emission, resource-efficient swimming pool infrastructure consistent with circular economy principles.

Telecommunications tower infrastructure providers in Nigeria operate under weak grid and off-grid conditions, where diesel plays a prominent role as an energy source, affecting energy cost and supply reliability decisive for business continuity. This paper presents a comparative techno-economic and lifecycle assessment of two power portfolios for TowerCo sites, namely diesel-only baselines and diesel–solar–battery hybrid systems. The study is anchored on a five-year project horizon and a stringent 99.98% uptime requirement, translating reliability into explicit constraints on allowable downtime and energy that are not served. Using operational available datasets such as fuel logs, genset telematics, site solar potential, and outage history, we develop site models that capture heterogeneity in grid quality, logistics exposure, and load behaviour. For each model, we evaluate candidate portfolios through a reliability-constrained optimisation of ownership (CAPEX, fuel, Operations and Maintenance, replacements, and operational overhead) while meeting autonomous and operational limits. Environmental performance is measured through the lifecycle greenhouse gas intensity, with transparent treatment of component lifetimes and residual value within the five-year boundary. The results include the least cost sizing ranges for solar and storage by model, expected diesel displacement and runtime reduction, delivered-energy cost, and lifecycle emissions trade-offs under sensitivity to diesel price volatility, outage severity, solar yield uncertainty, and battery degradation. The proposed framework provides a scalable, data-driven basis for prioritising hybridisation investments across TowerCo portfolios and for benchmarking fossil-renewable supply strategies for firm, low-carbon energy delivery in emerging market telecommunications infrastructure. Results present minimum-expense PV and storage sizing strings by model, reflecting substantial diesel reduction, and generator run-hour. The hybrids decrease delivered energy cost (per kWh) and yield attractive 5-year NPV and return on investment versus diesel-only baselines, while providing significant lifecycle emission reductions. Sensitivity analysis confirms the economic viability of hybrids, from diesel price volatility to degree of outage, solar yield uncertainty, and different rates for battery degradation. The model provides a scalable, data-informed approach for TowerCos to prioritise investments in hybridisation throughout their fleets and creates a benchmark for transitioning power infrastructure in new and emerging markets to stable, low-carbon sources of energy.

Wetlands are recognized as significant natural sources of global methane emissions, contributing substantially to climate forcing through complex biogeochemical and microbial processes. At the same time, Floating Solar Photovoltaic (FSPV) systems are rapidly expanding worldwide due to land scarcity, increasing energy demand, and their perceived favorable trade-offs compared to land-based solar installations. As a result, countries with limited available land increasingly consider wetlands, reservoirs, and other water bodies as strategic sites for FSPV deployment. However, the limited consideration of wetland ecological processes in current FSPV planning and design raises concerns that such installations may unintentionally increase methane emissions and generate adverse environmental impacts rather than delivering net climate benefits.

To examine these issues, the researchers conducted a systematic qualitative literature review of fifty (50) peer-reviewed journal articles published between 2010 and 2025. The researchers applied the Comparative Analysis Framework (CAF) to synthesize and categorize existing studies into four major thematic areas: the effects of FSPV on wetland ecosystems, methane dynamics under FSPV installations, methane mitigation strategies associated with floating solar systems, and integrated research frameworks that explicitly link methane emissions with FSPV deployment. The review reveals that most existing studies focus on lakes and reservoirs, while ecologically sensitive wetlands such as marshes and peatlands remain underrepresented in the literature.

Furthermore, the analysis indicates a lack of empirical data on hydrological alterations, nutrient cycling, methane-specific microbial activity, and biogeochemical processes associated with FSPV installations, as well as limited development of predictive models and validation studies. Current research rarely examines methane emissions through technological assessments and policy-oriented reviews, and most FSPV frameworks fail to incorporate methane reduction strategies. Overall, the synthesis identifies critical thematic gaps and highlights emerging priorities for interdisciplinary research approaches that integrate ecological monitoring, methane control strategies, system-level modeling, and policy development. This review highlights the importance of comprehensive, ecosystem-scale research and holistic modeling frameworks to optimize the benefits of FSPV while mitigating the risks associated with methane emissions in wetland environments.

Mixed Pb-Sn perovskite solar cells have recently demonstrated photoconversion efficiencies (PCEs) comparable to those of fully Pb-based halide perovskite devices. The main advantages of the Sn-containing composition are reduced toxicity and enhanced light absorbance over a wider wavelength range. Furthermore, the narrow bandgap of approximately 1.25 eV gives Pb–Sn perovskites the potential to surpass the photoelectric conversion efficiency of lead halide perovskite solar cells. However, the practical application of these devices is currently limited by the easy oxidation of Sn²⁺. Avoiding this oxidation is one of the requirements to achieve efficient and stable Sn-based perovskite solar cells (PSCs). The few recent reports have shown that some amino acids used as additives in the Pb-Sn mixtures can effectively passivate defects thanks to their zwitterions properties and also reduce Sn⁴⁺ cations that present in precursor solutions as impurities [1]. Therefore, this study is dedicated to optimizing a strategy for employing amino acid salts in mixed Pb-Sn perovskite solar cells to improve their performance and stability.

Chloride salts of L-lysine, L-aspartic acid, L-histidine, and other amino acids were introduced into the precursor solutions, followed by interface passivation on the perovskite surface. A comparative study of the structural, photoluminescent and morphological properties of perovskite films and the photovoltaic properties of solar cells allowed us to determine which amino acid salt is the most effective in defect passivation and suppression of Sn⁴⁺ formation.

In particular, the incorporation of L-lysine·HCl as an additive in Sn–Pb perovskite solar cells resulted in a power conversion efficiency of 18.4% for single-junction devices. These results suggest that amino acid salts represent a promising strategy for enhancing both the efficiency and stability of single-junction Sn-Pb perovskite solar cells. We acknowledge the support provided by the GOPV project RdS2019-21 CSEAA_00011 - TIPO A - Ministry of Environment and Energy Security (MASE) – CUP E83C23000840001

[1] Zhou, S., Fu, S., Wang, C. et al. Aspartate all-in-one doping strategy enables efficient all-perovskite tandems. Nature 624, 69–73 (2023).

Accurate characterization of photovoltaic (PV) module temperature is essential for evaluating performance under real outdoor operating conditions. The widely used Faiman thermal model assumes steady-state behavior and neglects short-term temperature dynamics caused by rapid changes in irradiance, wind, and ambient conditions. As a result, temperature predictions based on steady-state assumptions can deviate from actual module behavior during rapidly changing environmental conditions. Recent studies have proposed transient extensions to such models by introducing thermal mass terms, highlighting the need for experimental validation under realistic outdoor operating conditions.

This work presents a measurement-focused study aimed at resolving transient temperature and irradiance effects on PV module efficiency using high time-resolution outdoor data. An outdoor measurement system is developed to simultaneously record module temperature, ambient conditions, irradiance, and electrical output under naturally varying environmental conditions. Attention is given to the transient response of different temperature sensing methods, including contact thermocouples and infrared-based measurements, and their influence on time-dependent thermal analysis and parameter interpretation.

Controlled experimental scenarios are designed to isolate key transient effects, including temperature response to ambient changes without irradiance, irradiance-driven heating near thermal equilibrium, and cooling behavior under shaded conditions while ambient conditions remain unchanged. These measurement configurations enable the identification of temperature lag and sensor response characteristics that can introduce non-negligible deviations in inferred thermal behavior when transient effects are neglected or insufficiently resolved.

The resulting time-dependent data are used to evaluate effective heat transfer behavior and to compare the performance and limitations of steady-state and transient thermal models. The analysis demonstrates clear differences between steady-state assumptions and observed transient behavior, particularly during periods of rapidly changing irradiance and ambient conditions. These differences are found to depend strongly on measurement methods, sensor response characteristics, and operating regime, underscoring the importance of sensor selection and temporal resolution in outdoor PV thermal studies.

Overall, this measurement-driven perspective provides experimental insight into the applicability of transient thermal models for PV systems under realistic outdoor operating conditions and offers practical guidance for improving temperature measurement strategies and system-level performance evaluation.

The integration of solar power into smart grids leads to potential as well as difficult problems such as grid instability, energy supply imbalances, and inefficient energy distribution due to the complexity and variability of renewable energy sources, as the world shifts towards renewable energy. In order to overcome these obstacles, our study creates a virtual replica, a Digital Twin that simulates the grid and solar power plant components in a virtual environment. For that, we use MATLAB/Simulink and Simscape, which are specifically used to create high-fidelity models of inverters, solar arrays, and interconnection gear. The digital replica is kept closely linked with conditions on-site through the use of data streams. Built-in procedures modify energy dispatch for fedrated learning, to optimize yield, and to stabilize the grid. The Digital Twin system helped us understand the solar power plant's dynamic performance within smart grids by using simulation and analysis tools. Using .mat files, we successfully extracted and analyzed system variables such as solar power, temperature, battery status, and irradiance data for analysis. The time series display of solar generation along with grid power consumption and load requirements revealed different operational behaviors of the system and mismatches under varying conditions. Along with that, actual system analysis was carried out at the component level to examine the patterns of battery charging along with inverter performance and power grid fluctuations and financial operation details. This simulation showed how different irradiance levels impact power generation while displaying the temporal evolution of battery voltages and illustrating the connection between grid power delivery and economic returns. The application of the digital twin has led to a 30% increase in energy production and a 15% improvement in the downtime of resources in the solar power plant. This paper concludes with a staged deployment approach and detailed implementation instructions to provide practitioners with a clear path to more reliable, efficient, and sustainable solar-integrated power systems.