Search Results (2,564)

The increasing penetration of variable renewable energy sources (RESs) poses significant challenges to power system flexibility and reliability, particularly in systems with high solar generation. At the same time, existing Concentrating Solar Power (CSP) plants in Europe face declining economic viability due to high capital costs and the expiration of incentivized tariff schemes. This study proposes and evaluates a novel approach to repurpose CSP plants as flexible energy assets through the integration of cold thermal energy storage (CTES) within a Thermally Integrated Power-to-Heat-to-Power Energy Storage (TI-PTES) framework. The proposed system combines an ice/water-based cold storage with a CO₂-based refrigeration cycle to enhance the efficiency of the CSP steam cycle by reducing condenser temperatures, while also enabling temporal shifting of electricity consumption. A techno-economic optimization model based on PyPSA is developed to determine the optimal sizing and operation of the storage and refrigeration system under realistic load and electricity price conditions representative of the Spanish market. Results show that the integration of cold storage significantly alters system operation, shifting the chiller from a continuous demand-following mode to an intermittent, high-intensity regime. This leads to a reduction in annual operating expenditures by approximately 32% and an increase in annual profit and net present value (NPV), despite higher capital investment. While hourly net revenue becomes more volatile, with negative values during charging periods, cumulative annual performance improves due to effective temporal optimization. However, the absence of strong electricity price arbitrage and negative price signals limits the revenue potential of the storage system, which primarily acts as a cost-reduction mechanism. The findings demonstrate that cold thermal storage can successfully reposition CSP plants as flexible, value-generating assets in modern electricity systems. The proposed concept offers a promising pathway for extending the operational lifetime of existing CSP infrastructure while supporting higher integration of renewable energy sources. Full article

Turbofan engine performance is critically sensitive to operating conditions, yet comprehensive frameworks that simultaneously assess exergo-economic, exergo-environmental, and lifecycle cost performance across realistic flight envelopes remain limited, particularly for Gulf-region climates. In this study, we present a comprehensive analysis of the exergo-economic, exergo-environmental, and lifecycle costings of five different configurations of two-spool and triple-spool turbofan engines. The analysis was carried out for a wide range of four operating conditions, namely ambient temperature, flight altitude, Mach number, and % relative humidity, with emphasis on the climate conditions likely to be found in the Gulf region. The computational models developed were validated against published data to confirm their reliability. It was found that fuel consumption was the most significant contributor to total lifecycle ownership cost, between 60 and 75% of hourly operating cost over a 20-year service period. Ambient temperature, Mach number, and Cruise altitude represented the most significant drivers of long-term economic performance, with % relative humidity having little effect. Exergo-economic analysis showed that the major cost mechanisms changed dramatically with operating conditions. Exergy destruction and component inefficiencies determined the costs at Takeoff, with capital investment being the dominant factor when cruising. Increase in both or either ambient temperature and altitude was shown to reduce cost rates but simultaneously reduced thermo-economic efficiency via higher specific exergy costs. However, increase in Mach number enhances both exergy output and cost-effectiveness, confirming that specific exergy cost is a more reliable indicator of true system performance than cost rate alone. The two-spool configurations show superior specific CO₂ emissions, with Case 3 recording the lowest emissions at Takeoff and Case 2 at Cruise. For exergy-based environmental indicators, Case 3 performs best at both Takeoff and Cruise, achieving the lowest environmental destruction coefficient and index, as well as the highest environmental benign index among all five configurations. These findings provide actionable guidance for engine selection, operational optimization, and sustainable propulsion system design. Full article

Battery cell manufacturing is highly energy intensive, with clean and dry rooms being among the largest consumers of electricity and thermal energy. Due to the moisture sensitivity of most advanced cathode materials (e.g., NMC 811) and sulfide-based solid-state materials, production environments must operate at extremely low humidity, requiring energy-intensive HVAC systems to remove moisture introduced mainly by workers and infiltration. To reduce energy consumption, a detailed understanding of the airflow patterns in the room is essential. Because of complex flow patterns (exhaust air demands, energy dissipation), tracer gas techniques using CO₂ as a marker provide an operation-integrated method for determining local air age. The studies presented in this paper apply tracer gas techniques for the first time to a room in which air is almost completely recirculated at high air change rates of approximately 27 h⁻¹, with the supply air being conditioned by removing all process-relevant contaminants such as moisture and particles. Measurements in a separate flow box show successful air age calculations that agree with simplified CFD simulations. For the clean and dry room, the empirical variable relative exposure (REX) was introduced. The measurements indicate an inhomogeneous air distribution inside the room, accompanied with short-circuit flows, partial displacement flow, and mixing, and therefore have the potential to provide a cost-effective first-hand insight into the prevailing airflow patterns. Nevertheless, the presented measurement technique must be further optimized and validated for rooms with air recirculation and high air change rates. Full article

Microalgal lipid extraction, particularly the subsequent solvent recovery phase, constitutes the primary energy bottleneck in algal-based biodiesel biorefineries. Recently, switchable polarity solvents (SPS), such as the tertiary amine N,N-dimethylcyclohexylamine (DMCHA), have emerged as promising ‘green’ alternatives capable of extracting lipids directly from wet biomass, theoretically bypassing energy-intensive drying and solvent recovery distillation stages. This study presents a rigorous techno-energetic and thermodynamic evaluation combined with supporting experiments for qualitative conclusions to scrutinize the actual viability of DMCHA-mediated extraction against conventional hexane benchmarks, across three process configurations using different biomass types: algal liquor, wet paste, and dried biomass. Contrary to widespread assumptions in the literature, fundamental thermodynamic calculations reveal that the energy required for amine regeneration via protonation/deprotonation mechanisms equals or exceeds that of conventional distillation. Furthermore, mitigating biomass drying inadvertently escalates overall downstream energy and economic penalties due to the excessive solvent volumes demanded by dilute aqueous matrices. Direct extraction from algal liquor displays a cost and energy consumption countably higher than the other scenario; precisely, a cost of 232 €/kg of lipids and energy consumption of 454 kWh/kg of lipids. Extraction from wet paste exhibits, indeed, a slightly lower energy consumption compared to the hexane process (respectively 51 kWh/h versus 72 kWh/kg), but, due to the CO₂ requirements, the cost is double (19 €/kg of lipids versus 8 €/kg of lipids). Ultimately, while switchable polarity chemistry offers a marginal reduction in process water footprints, it introduces substantial operational complexity, elevated carbon dioxide payloads, and severe solvent degradation risks, challenging its current readiness for industrial upscaling. Full article

Raising indoor temperature setpoints is widely promoted as a practical way to reduce cooling-related energy demand in commercial buildings, yet its net carbon impact becomes uncertain once behavioral rebound effects are considered. This study develops an integrated carbon-accounting framework to evaluate the climate implications of summer indoor temperature increases of 1–3 °C in U.S. mercantile buildings. The framework combines operational energy savings from reduced cooling demand with consumption-driven emissions arising from longer customer dwell times and increased consumer spending under improved thermal comfort conditions. Carbon outcomes are quantified using sector-level electricity data and the USEEIO emission factor for retail trade. The results reveal a clear imbalance: operational carbon savings range from 0.21 to 0.64 Mt CO₂, whereas consumption-driven emissions range from 3.37 to 21.90 Mt CO₂, yielding a consistently positive net carbon impact of 3.16–21.26 Mt CO₂ across all scenarios. A break-even analysis indicates that only 1.30–3.89 billion USD in additional spending is sufficient to offset the operational savings. The findings remained robust across alternative behavioral and carbon-accounting specifications; a 10,000-iteration Monte Carlo analysis produced positive net carbon impacts in every simulation (median 8.54 Mt CO₂; P(NCI > 0) = 1.00). Overall, the results suggest that temperature-based efficiency measures may overstate their climate benefits when behavioral responses are ignored, highlighting the importance of incorporating rebound effects into building energy assessments and commercial climate policy. Full article

Agri-food systems are increasingly exposed to environmental, economic, and social challenges, including climate change, biodiversity loss, resource depletion, and growing territorial inequalities. In this context, agroecology is increasingly recognised as a transformative paradigm integrating ecological, economic, social, cultural, and political dimensions within broader processes of food-system transition. Within the PRIMA AgrEcoMed project, 24 Italian agroecological initiatives led by women and young farmers were analysed to explore their contribution to agroecological transition processes in Mediterranean rural areas. The study adopts a qualitative multiple-case study approach and evaluates the selected initiatives through the framework of the 13 Principles of Agroecology proposed by the High-Level Panel of Experts on Food Security and Nutrition, organised into three operational axes: improving resource efficiency, strengthening resilience, and ensuring social responsibility and fairness. The results show that the analysed initiatives combine ecological farming practices with processes of multifunctionality, territorial networking, knowledge co-creation, short supply chains, and community engagement. The findings suggest that several initiatives move beyond input-reduction strategies associated with “weak agroecology” and display characteristics consistent with stronger agroecological pathways based on territorial embeddedness, collective learning, and the reorganisation of relationships between production, consumption, and local communities. The paper highlights the relevance of agroecology not only as an environmentally sustainable farming approach, but also as a broader socio-ecological and territorial transition process, as well as the importance of policy frameworks to support territorial agroecological systems. Full article

Lead-bearing dusts from metallurgical processes are hazardous secondary resources due to their complex composition and toxicity. At the same time, their high lead content makes them a promising feedstock for resource recovery. This study proposes an energy-efficient electrosmelting approach based on the partial substitution of sodium carbonate with calcium-rich industrial waste (sugar-industry defecate). Thermodynamic analysis and equilibrium modeling of the Pb–Sb–Fe–Na–Ca–Si–S–Cl–As system were performed in the temperature range of 200–1200 °C using Outotec HSC Chemistry. The results indicate that under equilibrium conditions approximately 90–95% of lead is concentrated in the metallic phase (~56 kg from ~60 kg in the feed), while antimony is co-recovered (~1.9–2.0 kg). The slag is dominated by calcium silicates, primarily Ca₂SiO₄, confirming the important role of CaO in slag formation and impurity fixation. Chlorine is predominantly bound as NaCl and partially as CaCl₂, while sulfur is distributed between Na₂S and Na₂SO₄. A significant portion of arsenic is predicted to be retained in the slag as calcium and sodium arsenates (Ca₃(AsO₄)₂ and Na₃AsO₄), whereas its volatilization is thermodynamically negligible under equilibrium conditions. Preliminary experimental results are generally consistent with the thermodynamic predictions and confirm the feasibility of partially replacing Na₂CO₃ with sugar-industry defecate. The proposed approach contributes to reducing the consumption of conventional fluxes and promotes the utilization of industrial waste within a circular-economy framework. Full article

Background/Objectives: Consumption of dairy products and plant-based dairy alternatives (PBDAs) can be examined within broader configurations of food-related orientations rather than as isolated product choices. This study aimed to identify food-related consumer segments based on food involvement, attention to on-pack product information, and sustainability-related food-choice orientations, and to characterise these segments in relation to reported consumption frequencies of dairy products, PBDAs, and meat, fish and legume dishes, as well as health-oriented food-choice criteria. Methods: A cross-sectional survey was conducted among 1508 Polish adults responsible or co-responsible for household food purchasing. Principal component analysis was used to identify underlying food-related dimensions, and the retained component scores were entered into a two-step cluster analysis. Differences between clusters were examined using chi-square tests and one-way ANOVA. Results: Six dimensions were retained: sustainable and ethical choices, meat reduction, food involvement, product-information importance, shopping-list use and food-waste avoidance. Five clusters were identified, reflecting distinct configurations of these dimensions. PBDA and legume-dish consumption were most frequent in the sustainability and meat-reduction-oriented cluster, although dairy products and meat remained part of the reported diet. High food involvement and label/quality attention co-occurred with a more conventional consumption pattern, whereas PBDA and legume-dish consumption were lowest in more conventional and lower-sustainability clusters. The low-engagement cluster showed a more selective pattern of PBDA and legume-dish consumption. Conclusions: This study identified five food-related consumer segments and showed that reported PBDA consumption was embedded in heterogeneous dietary patterns rather than functioning as a simple substitute for dairy products. These findings indicate that reported PBDA consumption is segment-dependent and cannot be assumed to reflect reduced dairy consumption or a consistently sustainability- or health-oriented dietary pattern. Full article

The transition toward next-generation energy systems requires advanced computational tools capable of supporting accurate, adaptive, and data-driven energy performance assessment. Within this context, Energy Performance Indicators (EnPIs) established under the ISO 50001 framework remain essential for monitoring energy efficiency and continuous improvement; however, conventional indicators are often based on static or simplified relationships that do not adequately capture the dynamic, nonlinear, and multivariable behavior of modern buildings and energy management systems. This systematic review analyzes the integration of ISO 50001-based EnPIs with intelligent algorithms and artificial intelligence techniques for enhanced energy management. The review follows a PRISMA-inspired methodology, using Scopus as the primary database and Web of Science and Google Scholar as complementary sources. From 5442 initial records, 2691 studies were screened and 283 articles were selected for detailed analysis, supported by a bibliometric keyword co-occurrence analysis using VOSviewer 1.6.20. The results show a clear evolution from traditional energy indicators and normalized baselines toward computational modeling approaches based on regression analysis, machine learning, deep learning, forecasting, anomaly detection, and optimization algorithms. These methods improve the predictive capability, adaptability, and operational relevance of EnPIs by incorporating climatic, occupancy, temporal, and operational variables. The reviewed evidence indicates that intelligent algorithms can strengthen ISO 50001 energy management systems by enabling dynamic baselines, early detection of abnormal consumption patterns, predictive decision-making, and continuous operational optimization. Nevertheless, challenges remain regarding data quality, model interpretability, methodological standardization, and practical integration into certified energy management frameworks. Overall, this review highlights that the future of energy performance assessment does not rely on replacing conventional EnPIs, but on transforming them into intelligent, computationally supported indicators for sustainable, resilient, and next-generation energy management systems. Full article

Inspired by the energy-efficient resonance strategy of the human elbow joint during periodic arm swing, this paper investigates the energy-saving motion and performance of a robotic variable stiffness joint. A modular stiffness adjustment mechanism with continuously adjustable stiffness based on Archimedean spiral grooves is proposed. A co-simulation model using MATLAB (R2022b)/ADAMS (2020) is established, and dynamic equations are derived to reveal the correlation between resonance/anti-resonance frequencies and joint rotational stiffness. Mimicking the biological principle of stiffness-frequency matching, an energy-saving controller leveraging the resonance effect is designed, which includes a motor energy consumption model to quantify losses and an optimization strategy to match the joint rotational stiffness with the load anti-resonance frequency. Simulation results demonstrate that in variable stiffness mode, aligning the system anti-resonance frequency with the task trajectory frequency significantly reduces joint energy consumption, validating the bioinspired approach. In contrast, the high-stiffness (rigid) mode leads to a surge in system energy consumption. Full article

Sustainable pavement maintenance increasingly requires coordinated management of infrastructure condition, renewable-energy availability, carbon emissions, financial resources, and operational capacity. This study proposes a renewable-energy resource management framework for low-carbon network-level pavement maintenance using simulation-based pavement-energy modeling and multi-agent deep reinforcement learning. The proposed framework develops an AnyLogic-based pavement-energy simulation environment in which road sections, deterioration states, work zones, maintenance crews, equipment resources, photovoltaic generation, battery storage, grid support, diesel backup, carbon tracking, and budget consumption are represented within one integrated decision environment. To support adaptive maintenance control, pavement sections are modeled as interacting agents, while road connectivity, dispatch dependency, traffic interaction, and maintenance-route relationships are encoded through graph structures. A graph-based multi-agent deep reinforcement learning model, named Graph-MAPPO, is then used as the decision controller. The model integrates multi-head graph attention for spatial dependency learning, GRU-based temporal memory for deterioration-history representation, finite-element-assisted structural-risk indicators for hidden damage characterization, and constraint-aware action masking to prevent infeasible decisions under budget, carbon, energy, crew, and equipment constraints. Two calibrated datasets were generated to support the framework: a pavement network and maintenance dataset containing 4437 records and 55 features, and a renewable energy-carbon-budget dataset containing 9875 records and 38 features. The decision controller jointly selects the pavement section, treatment type, intervention timing, crew, equipment, and energy mode. Results from 20 experimental configurations show that the balanced Graph-MAPPO policy improves average $PCI$ from 69.4 to 78.9, achieves an $RSL$ gain of 6.8 years, reduces emissions to 58.3 tCO₂e, maintains a renewable-energy share of 74.6%, and limits the constraint-violation rate to 1.8%. Under high renewable-energy availability, the framework achieves the best overall performance, with an average $PCI$ of 80.2, renewable-energy share of 84.6%, emissions of 50.8 tCO₂e, and reward of 0.90. These findings demonstrate that integrating pavement-energy simulation, renewable-energy resource allocation, carbon-aware maintenance planning, structural-risk awareness, and multi-agent decision control can support more adaptive, low-carbon, and resource-efficient pavement maintenance management. Full article

Climate change is a threat affecting public health and healthcare systems, and the health sector accounts for nearly 10% of greenhouse gas emissions (GHGEs) in the United States, including through food services. Reducing meat consumption in healthcare institutions presents solutions to reduce food-related GHGEs and provide health benefits to patients. However, challenges in quantifying these benefits present barriers for implementation. We aimed to use publicly available tools to quantify the magnitude of climate, economic, and health benefits associated with integrating a plant-based protein “swap” of current menu options at one hospital institution. On average, modeled plant-based protein swaps cost $0.159/ounce less, reduce trans fats (0.102 g/ounce) and cholesterol (19.0 mg/ounce), and decrease 721 g of CO₂/ounce compared to meat-based counterparts. However, the swap analysis yielded variable results on meal protein content and caloric intake that require additional consideration. If plant-based alternatives were implemented across half of the inpatient dining service at this institution, equivalent to 206,000 meals annually, there could be a potential annual value of $920,240 in food cost savings and $973,028 in avoided GHGEs. Healthcare decision-makers can leverage publicly available tools to implement evidence-based climate change mitigation solutions, helping hospitals battle climate change and reduce the burden of chronic disease. Full article

Climate change and the problems it causes have led to global action (the UN Sustainable Development Goals and the Paris Climate Change Agreement), and specific targets have been set to reduce global temperatures. Meeting the determined targets has become crucial. Therefore, evaluating the effectiveness of macroeconomic policies (monetary and fiscal) on carbon emissions becomes inevitable. This study examines the effects of monetary and fiscal policies on territorial and consumption-based ${CO}_2$ emissions in E-7 countries from 1996 to 2021. The Augmented Mean Group (AMG) estimator, which accounts for cross-sectional dependency and heterogeneity, was employed. The study concludes that monetary policy exerts a statistically significant negative impact on territorial and consumption-based ${CO}_2$ emissions, whereas fiscal policy has a statistically insignificant negative impact on them. A 1% increase in broad money, as an indicator of monetary policy, decreased territorial-based ${CO}_2$ emissions by 0.14 and consumption-based ${CO}_2$ emissions by 0.28. The results of the Dumitrescu and Hurlin causality analysis reveal a bidirectional causal relationship between monetary policy and territorial- and consumption-based ${CO}_2$ emissions. Full article

The exponential growth of AI-driven data traffic necessitates the evolution of Data Center Networks toward high bandwidths and sub-microsecond latency. While co-packaged optics (CPO) offer a pathway to reduced energy consumption and increased capacity, they introduce significant challenges in optical chip coupling and packaging complexity. This study explores monolithically integrated metasurfaces as an alternative for optical interfaces, potentially reducing the need for bulky external microlens arrays or extremely precise mechanical alignment. We design an amorphous silicon (a-Si) metasurface on a Silicon-On-Insulator (SOI) platform operating at 1310 nm. By spatially mapping nanopillar radii to satisfy a spherical phase profile, we achieved near-vertical beam emission with an emission angle of 0.88° focused at a focal length of 98.99 μm. Broadband characterization across a 20 nm band confirms stable focusing and a confined spot size with moderate roll-off toward the band edges. The sensitivity of the emission profile of the device to fabrication imperfections in pillar radius, height, and sidewall taper is quantified. The coupling to a polymer-based optical redistribution layer (ORDL) is also studied, and the corresponding modal analysis demonstrates a maximum coupling efficiency of 68.2% into an SU-8 polymer waveguide. Tolerance analysis results reveal deterioration of 0.9 dB and 0.4 dB for $\pm 0.6 \mathsf{\mu }\mathrm{m}$ horizontal and $\pm 1.5 \mathsf{\mu }\mathrm{m}$ vertical misalignment respectively, making the interface compatible with relaxed alignment assembly assumptions, although experimental packaging validation remains required. The methodology is further validated at 1550 nm, demonstrating its applicability across telecom bands. These results suggest that integrated metasurfaces may simplify the packaging stack and enhance density for next-generation CPO links by providing precise, on-chip wavefront manipulation. Full article

This comprehensive review investigates hybrid propulsion technologies as a pathway to decarbonization and improved energy efficiency in the maritime sector. Through a review of the recent literature, this study synthesizes current knowledge on energy management strategies and capacity sizing approaches for hybrid ship propulsion systems. Reported results indicate that optimized energy management can reduce fuel consumption and greenhouse gas emissions while minimizing total operational costs. Among real-time strategies, the Equivalent Consumption Minimization Strategy emerges as particularly suitable for maritime use due to its low computational demand and independence from full voyage profile knowledge, yet its maritime application remains far less developed than in the automotive domain. Capacity sizing and energy management are usually treated as separate optimization problems, limiting the achievability of truly optimal solutions. Only a few studies adopt integrated co-optimization frameworks, and these are typically built around simplified or fixed operational profiles. Moreover, the coupling between energy management parameters, such as the ECMS equivalence factor, and hardware sizing remains insufficiently explored. To address this, the review contributes a ship-specific classification of energy management strategies, a consolidated treatment of battery sizing methods with explicit attention to degradation, and a generalized two-loop framework that couples component sizing with ECMS-based energy management. The findings suggest that future research should prioritize adaptive energy management formulations calibrated for stochastic maritime duty cycles, the incorporation of battery degradation models into co-optimization, and validation against stochastic, real-world operating conditions. Full article