Search Results (363)

Urban heat and hardscapes increase cooling electricity demand, stressing power grids and disproportionately burdening deprived neighborhoods. While previous studies have documented the cooling benefits of urban tree canopy, most analyses remain at coarse spatial scales and do not isolate the canopy’s marginal effect from built surfaces, limiting their utility for equitable neighborhood-level planning. We introduce a novel neighborhood-scale (census block-group, CBG) model to estimate cooling-season energy demand across Baltimore City and Baltimore County, Maryland. We quantify demand drivers and actionable tree-canopy targets while controlling for built surfaces. Correlation analysis shows demand increases with developed fraction and imperviousness, and decreases with tree canopy and other vegetated or water cover. Using an explainable monotone gradient-boosted tree model (SHAP) with controls for imperviousness and development, we isolate the canopy’s marginal effect. Demand reductions begin once the canopy exceeds ~11% in Baltimore City and ~23% in Baltimore County, with diminishing returns beyond ~18% (City) and ~24% (County). This flattening is strongest in highly impervious CBGs, while low-impervious county areas show renewed reductions at very high canopy (>55–60%), consistent with forest-dominated microclimates. Spatial hotspots cluster in Baltimore City and southern Baltimore County, where low canopy and high hardscapes coincide with elevated demand; 61% of City CBGs fall below the 18% threshold. We translate these findings into priority intervention tiers combining demand, hardscapes, jurisdiction-specific canopy thresholds, and an equity overlay, identifying 21% of City and 1.2% of County CBGs as high-priority targets for greening and energy-relief interventions. Full article

Electrolytic aluminum is one of the most energy-intensive industrial processes and offers strong potential for demand-side flexibility and renewable energy integration. However, existing studies mainly focus on operational scheduling, while comprehensive planning frameworks at the industrial-park scale remain limited. This study proposes an optimal planning framework for electrolytic aluminum that co-optimizes renewable energy investments, waste heat recovery, and green power trading while capturing the temperature safety constraints of electrolytic cells. The electrolytic aluminum process is explicitly modeled with heat exchangers to enable combined cooling–heating–power supply for nearby users. A wind power priority subscription mechanism and green certificate compliance are incorporated to enhance practical applicability and support future decarbonization requirements. Moreover, a two-stage particle swarm-deterministic optimization scheme is developed to provide a tractable solution to the inherently nonconvex mixed-integer nonlinear model. Case studies based on a real plant in Xinjiang, China, demonstrate that the proposed framework can raise the green electricity aluminum share to 60.4%, reduce annual carbon emissions by 52.0%, and significantly increase total system profit compared with the benchmark configuration, highlighting its economic and sustainability benefits for industrial park development. Full article

To promote green and low-carbon transformation in the transportation sector and achieve the national “dual-carbon” targets, this study examines rooftop photovoltaic (PV) deployment at 12 representative railway stations located on the Qinghai–Tibet Plateau. Using high-resolution solar radiation data, building spatial information, and regional electricity pricing, we develop an integrated analysis framework that combines a PV power-generation simulation, life-cycle cost assessment, and carbon emission reduction evaluation. The model systematically evaluates the power output, economic performance, and emission reduction potential of rooftop PV systems installed on railway station buildings. Two PV array configurations—horizontal angle and optimum tilt angle—together with three business models (T1: all-consumption; T2: all-feed-into-grid; T3: self-consumption with surplus feed-in) are compared. The results indicate that the Qinghai–Tibet Plateau possesses substantial solar energy advantages. Rooftop arrays installed at a horizontal angle significantly increase both installed capacity and lifetime electricity generation, with stations XN and LS producing 523.12 GWh and 300.87 GWh, respectively, values that exceed the corresponding optimum tilt scenarios. In terms of economic performance, the T1 model yields the highest returns, with several stations achieving a lifetime return on investment exceeding 300% over a 25-year period. The T3 model demonstrates strong profit potential at stations such as RKZ and ZN, whereas the T2 model shows the weakest economic viability due to feed-in tariff constraints. Regarding carbon reduction, horizontal systems perform the best, with cumulative CO₂ emission reductions at station XN exceeding 300,000 tonnes of CO₂-equivalent. Overall, the findings highlight the substantial PV development potential of railway station rooftops on the Qinghai–Tibet Plateau. By selecting appropriate installation angles and business models, significant economic benefits and carbon emission reduction outcomes can be achieved, providing practical guidance for renewable-energy utilization in high-altitude transportation infrastructure. Full article

This study presents the operational assessment of a pilot-scale power-to-gas (PtG) facility located in La Guajira, Colombia, which integrates a 10 kW photovoltaic array and a 5 kW wind turbine to power a system with two anion exchange membrane (AEM) electrolyzer of 4.8 kW in total for green hydrogen production. Unlike most studies that rely on simulations or short-term evaluations, this study analyzes nine months of real operating data to quantify renewable energy availability, system capacity factors, and effective hydrogen output under tropical conditions. The results show that the hybrid system generated 7111 kWh during the monitoring period. The comparison of theoretical models with real-time energy production shows a low correlation between the data. The MBE ranged from 1253 to 2988 for the solar system, from −814 to 1013 for the wind system, and from 338 to 2714 for the hybrid system. The RMSE values obtained for each evaluated month ranged from 3179 to 3811 for the solar system, from 928 to 1910 for the wind system, and from 2310 to 4327 for the hybrid system, suggesting that the theoretical models tend to overestimate the energy production of the hybrid system in general terms. From the renewable energy produced in real conditions, 92 kg of hydrogen was produced at an average rate of 9 kg/month, considering the availability of wind and solar resources. However, approximately 300 kWh/month of renewable electricity remained unused because the removable generation did not meet the operating conditions of the electrolyzers, highlighting the importance of improved energy management and storage strategies. These findings provide a real scenario of power-to-gas system performance under Caribbean climatic conditions in Colombia, demonstrate the challenges of resource intermittency and system underutilization, and underline the importance of design systems that allow these intermittencies to be managed for the more optimal production of hydrogen from renewable sources. The outcomes contribute to the understanding of small-scale PtG systems in developing regions and support decision making for future scaling and replication of hybrid renewable–hydrogen infrastructures. Full article

To achieve carbon neutrality goals, offshore wind power combined with a hydrogen energy storage system (OWP-HESS) is critical for integrating intermittent renewables. This study applied a “cradle-to-grave” process-based life cycle assessment (PLCA) to evaluate a 77.4 MW offshore wind farm coupled with a 45.0 MW electrolysis cell system, covering manufacture, transportation, construction, operation and maintenance, and decommissioning phases. It focuses on two hydrogen production routes, alkaline electrolysis (AEL) and proton exchange membrane (PEM), and covers 12 environmental indicators. Moreover, considering optimal economic efficiency, to adapt to the characteristic of “electricity–hydrogen cogeneration”, as well as to facilitate reflecting the efficiency differences between the two electrolysis technologies, the functional unit is defined as “0.4 kWh green electricity + corresponding green hydrogen”. Results show that offshore wind’s environmental impacts mainly come from manufacture (79.00%, driven by concrete/steel), while hydrogen storage impacts focus on operation/maintenance (66.03% for AEL and 96.61% for PEM, driven by electricity). PEM’s green hydrogen global warming potential (GWP) (0.96 kg CO₂-eq/kg) is much lower than AEL’s (1.81 kg CO₂-eq/kg) and China’s fossil-based hydrogen (≈40 kg CO₂-eq/kg). With an initial system lifespan of 25 years, a wind farm capacity factor of 41.30%, and a hydrogen production efficiency of 68.72% (AEL) and 69.89% (PEM), extending system lifespan by 5 years, raising wind farm capacity factor to 43%, and enhancing hydrogen production efficiency to 71% reduce emissions by 16.67%, 4.00%, and 2.16%, respectively. This study clarifies OWP-HESS’s environmental characteristics, confirms PEM’s low-carbon advantage, and provides support for its sustainable development. Full article

This study presents the design and implementation of a prototype dual-function photovoltaic window system that integrates flexible solar panels for dynamic shading and a compact lithium battery for local energy storage. The methodology involves developing an experimental setup where translucent, flexible photovoltaic panels are retrofitted onto a standard residential window. The system is connected to a charge controller and a small-capacity lithium-ion battery pack. Key performance metrics, including solar irradiance, power generation efficiency, reduction in thermal transmittance, and battery state of charge, are continuously monitored under varying real-world environmental conditions. The integrated panels can significantly reduce solar heat gain, thereby lowering indoor ambient temperature and reducing the building’s cooling load. Simultaneously, the system will generate sufficient electricity to be stored in the lithium battery, providing a self-contained power source for low-draw applications such as lighting or charging personal devices. This research highlights the viability of developing cost-effective, multi-functional building components that transform passive architectural elements into active energy-saving and power-generating systems in terms of green environment goals. Full article

Motivated by the policy urgency of China’s dual-carbon goals and the practical obstacle that official input–output (IO) and MRIO tables are sparse and non-consecutive, this study investigates how to generate credible, mechanism-aware provincial–sector forecasts of carbon footprints and embodied transfers for Western China—a region with pronounced structural heterogeneity. We develop a regionalized forecasting pipeline that fuses balance-constrained MRIO completion (RAS–CE) with a Whale-optimized Grey Neural Network (WOA–GNN), bridging the data gap (2007–2017 reconstruction) and delivering 2018–2030 projections at province–sector resolution. The novelty lies in integrating RAS–CE with a meta-heuristic grey learner and layering explainable network analytics—Grey Relational Analysis (GRA) for factor ranking, complex-network measures with QAP regressions for driver identification, and SHAP for post hoc interpretation—so forecasts are not only accurate but also actionable. Empirically, (i) energy mix/intensity and output scale are the dominant amplifiers of footprints, while technology upgrading (process efficiency, electrification) is the most robust mitigator; (ii) a structural sectoral hierarchy persists—S2 (non-metallic minerals) remains clinker/heat-intensive, S3 (general/special equipment) operates as a mid-chain hub, and S6/S7 (electrical machinery/instruments) maintain lower, more controllable intensities as the grid decarbonizes; (iii) by 2030, the embodied carbon network becomes denser and more centralized, with Sichuan–Chongqing–Guizhou–Guangxi forming high-betweenness corridors; and (iv) QAP/SHAP converge on geographic contiguity (D) and economic differentials (E) as the strongest positive drivers (openness Z and technology gaps T secondary; energy-mix differentials F weakly dampening). Policy-wise, the framework points to green-power contracting and trading for hubs, deep retrofits in S2/S3 (low-clinker binders, waste-heat recovery, efficient drives, targeted CCUS), technology diffusion to lagging provinces, and corridor-level governance—demonstrating why the RAS–CE + WOA–GNN coupling is both necessary and impactful for data-constrained regional carbon planning. Full article

Due to the large emissions of greenhouse gases from the burning of fossil fuels and people’s demand for green materials and energy, the development of environmentally friendly triboelectric nanogenerators (TENGs) is becoming increasingly significant. Silk fibroin (SF) is considered an ideal biopolymer candidate for fabricating green TENGs due to its biodegradability and renewability. However, its intrinsic brittleness and relatively weak triboelectric performance severely limit its practical applications. In this study, SF was physically blended with poly(ethylenimine) (PEI), a polymer rich in amino groups, to fabricate SF/PEI composite films. The resulting films were employed as tribopositive layers and paired with a poly(tetrafluoroethylene) (PTFE) tribonegative layer to assemble high-performance TENGs. Experimental results revealed that the incorporation of PEI markedly enhanced the flexibility and electron-donating capability of composite films. By optimizing the material composition, the SF/PEI-based TENG achieved an open-circuit voltage as high as 275 V and a short-circuit current of 850 nA, with a maximum output power density of 13.68 μW/cm². Application tests demonstrated that the device could serve as an efficient self-powered energy source, capable of lighting up 66 LEDs effortlessly through simple hand tapping and driving small electronic components such as timers. In addition, the device can function as a highly sensitive self-powered sensor, capable of generating rapid and distinguishable electrical responses to various human motions. This work not only provides an effective strategy to overcome the intrinsic limitations of SF-based materials but also opens up new avenues for the development of high-performance and environmentally friendly technologies for energy harvesting and sensing. Full article

The rapid advancement of technologies such as artificial intelligence, big data, and cloud computing has driven continuous expansion of global data centers, resulting in increasingly severe energy consumption and carbon emission challenges. According to projections by the International Energy Agency (IEA), the global electricity demand of data centers is expected to double by 2030. The construction of green data centers has emerged as a critical pathway for achieving carbon neutrality goals and facilitating energy structure transition. This paper presents a systematic review of the role of waste heat recovery technologies in data centers for achieving low-carbon development. Categorized by aspects of waste heat recovery technologies, power production and district heating, it focuses on assessing the applicability of heat collection technologies, such as heat pumps, thermal energy storage and absorption cooling, in different scenarios. This study examines multiple electricity generation pathways, specifically the Organic Rankine Cycle (ORC), Kalina Cycle (KC), and thermoelectric generators (TEG), with comprehensive analysis of their technical performance and economic viability. The study also assesses the feasibility and environmental advantages of using data center waste heat for district heating. This application, supported by heat pumps and thermal energy storage, could serve both residential and industrial areas. The study shows that waste heat recovery technologies can not only significantly reduce the Power Usage Effectiveness (PUE) of data centers, but also deliver substantial economic returns and emission reduction potential. In the future, the integration of green computing power with renewable energy will emerge as the cornerstone of sustainable data center development. Through intelligent energy management systems, cascaded energy utilization and regional energy synergy, data centers are poised to transition from traditional “energy-intensive facilities” to proactive “clean energy collaborators” within the smart grid ecosystem. Full article

Chiral materials have shown promising application prospects across various disciplines in recent years due to their unique structural asymmetry and the resulting chiral dependence in optical, electrical, and biomedical applications. However, the existing literature lacks a unified summary of its applications in different fields. This review systematically introduces the applications of chiral materials in optics, electricity, quantum science, and biomedicine. Based on circular dichroism and chiral inversion aggregation-induced emission, chiral materials enable efficient circularly polarized light emission/detection, advancing chiral perovskite and spin light-emitting diodes. In quantum science, in-depth studies of the chiral-induced spin-selectivity effect and chiral topological superconductors support spintronic devices and quantum computing. They facilitate the development of high-efficiency energy conversion devices and high-performance chiral electrochemical sensors. In biomedicine, they excel in enantioseparation, targeted drug delivery, and theranostics. In the future, chiral materials will develop towards multi-functional integration, intelligent response, and high-performance devices. Their in-depth applications in three-dimensional display technology, low-power spin storage devices, green catalytic systems, and precision medicine will provide innovative solutions to energy, environmental, and health challenges. Full article

In recent years, advancements in technologies related to hydrogen have facilitated the exploitation of this energy carrier in conjunction with renewable energies to meet the energy demands of diverse applications. This paper describes a pilot plant within the framework of a research and development (R&D) project aimed at utilizing hydrogen in both industrial and domestic sectors. To this end, this facility comprises six subsystems. Initially, a photovoltaic (PV) generator consisting of 48 panels is employed to generate electrical current from solar radiation. This PV array powers a proton exchange membrane (PEM) electrolyzer, which is responsible for producing green hydrogen by means of water electrolysis. The produced hydrogen is subsequently stored in a bottling storage system for later use in a PEM fuel cell that reconverts it into electrical energy. Finally, a programmable electronic load is utilized to simulate the electrical consumption patterns of various profiles. These physical devices exchange operational data with an open source supervisory system integrated by a set of Industry 4.0 (I4.0) and Internet of Things (IoT)-framed environments. Initially, Node-RED acts as middleware, handling communications, and collecting and processing data from the pilot plant equipment. Subsequently, this information is stored in MariaDB, a structured relational database, enabling efficient querying and data management. Ultimately, the Grafana environment serves as a monitoring platform, displaying the stored data by means of graphical dashboards. The system deployed with such I4.0/IoT applications places a strong emphasis on the continuous monitoring of the power inverter that serves as the backbone of the pilot plant, both from an energy flow and communication standpoint. This device ensures the synchronization, conversion, and distribution of electrical energy while simultaneously standing as a primary data source for the supervisory system. The results presented in this article describe the design of the system and provide evidence of its successful implementation. Full article

While renewable energy deployment has accelerated in recent years, fossil fuels continue to play a dominant role in electricity generation worldwide. This necessitates the development of transitional strategies to mitigate greenhouse gas emissions from this sector while gradually reducing reliance on fossil fuels. This study investigates the potential of blending green hydrogen with natural gas as a transitional solution to decarbonize Jordan’s electricity sector. The research presents a comprehensive techno-economic and environmental assessment evaluating the compatibility of the Arab Gas Pipeline and major power plants with hydrogen–natural gas mixtures, considering blending limits, energy needs, environmental impacts, and economic feasibility under Jordan’s 2030 energy scenario. The findings reveal that hydrogen blending between 5 and 20 percent can be technically achieved without major infrastructure modifications. The total hydrogen demand is estimated at 24.75 million kilograms per year, with a reduction of 152.7 thousand tons of carbon dioxide per annum. This requires 296,980 cubic meters of water per year, equivalent to only 0.1 percent of the National Water Carrier’s capacity, indicating a negligible impact on national water resources. Although technically and environmentally feasible, the project remains economically constrained, requiring a carbon price of $1835.8 per ton of carbon dioxide for economic neutrality. Full article

With the goal of achieving carbon neutrality, promoting the clean and low-carbon transformation of energy assets, as exemplified by existing thermal power units, has emerged as a pivotal challenge in addressing climate change and achieving sustainable development. Arrangements and technologies such as the electricity–carbon–certificate multi-market, microgrids with direct green power connections, and carbon capture and storage (CCS) retrofitting provide favorable conditions for facing the aforementioned challenge. Based on an analysis of how liquid-storage CCS retrofitting affects the flexibility of thermal power units, this manuscript proposes a bi-level optimization model and solution method for capacity allocation for grid-connected microgrids, while considering CCS retrofits under multi-markets. This approach overcomes two key deficiencies in the existing research: first, neglecting the relationship between electricity–carbon coupling characteristics and unit flexibility and its potential impacts, and second, the significant deviation of scenarios constructed from real policy and market environments, which limits its ability to provide timely and relevant references. A case study in southern China demonstrates that first, multi-market implementation significantly boosts microgrids’ investment in and absolute consumption of renewable energy. However, its effect on reducing carbon emissions is limited, and renewable power curtailment may surge, potentially deviating from the original intent of carbon neutrality policies. In this case study, renewable energy installed capacity and consumption rose by 17.09% and 22.64%, respectively, while net carbon emissions decreased by only 3.32%, and curtailed power nearly doubled. Second, introducing liquid-storage CCS, which decouples the CO₂ absorption and desorption processes, into the capacity allocation significantly enhances microgrid flexibility, markedly reduces the risk of overcapacity in renewable energy units, and enhances investment efficiency. In this case study, following CCS retrofits, renewable energy unit installed capacity decreased by 24%, while consumption dropped by only 7.28%, utilization hours increased by 22%, and the curtailment declined by 78.05%. Third, although CCS retrofitting can significantly reduce microgrid carbon emissions, factors such as current carbon prices, technological efficiency, and economic characteristics hinder large-scale adoption. In this case study, under multi-markets, CCS retrofitting reduced net carbon emissions by 86.16%, but the annualized total cost rose by 3.68%. Finally, based on the aforementioned findings, this manuscript discusses implications for microgrid development decision making, CCS industrialization, and market mechanisms from the perspectives of research directions, policy formulation, and practical work. Full article

With the deepening of power market reform and the large-scale integration of bidirectional systems such as energy storage and electric vehicles, achieving sustainable carbon management has become increasingly urgent. Traditional carbon emission accounting methods face challenges, including insufficient dynamics and unclear responsibility boundaries. To address these issues, this paper proposes a sustainability-oriented accounting method for indirect carbon emissions from electricity in the context of bidirectional system integration in the power market environment. First, the dynamic carbon emission characteristics of bidirectional systems such as energy storage and vehicle-to-grid (V2G) systems are analyzed, and a carbon emission accounting model is constructed to address the fairness issue of emission responsibility allocation during charging and discharging. Second, on the basis of the theory of carbon emission flows and incorporating electricity trading contract data, an accounting method for indirect carbon emissions from electricity in green electricity trading, coal-fired electricity trading, and hybrid scenarios under bidirectional system integration is developed. Finally, the case study demonstrates that the proposed method accurately captures the temporal variation of carbon emission factors, ensures conservation of total emissions, and fairly redistributes carbon responsibility among users under different market scenarios, while revealing how bidirectional systems and green electricity trading reshape nodal carbon intensities and spatial emission distributions without causing double counting. Full article

Smart devices and emerging technologies are highly popular devices and technologies that considerably improve our daily living by reducing or replacing human workforces, treating disease, monitoring healthcare, enhancing service performance, improving quality, and protecting the natural environment, and promoting non-gas emissions, sustainable working, green technologies, and renewable energy. Triboelectric nanogenerators (TENGs) have recently emerged as a type of advanced energy harvesting technology that is simple, green, renewable, flexible, and endurable as an energy resource. High-performance TENGs, denoted as advanced TENGs, have potential for use in many practical applications such as in self-powered sensors and sources, portable electric devices, power grid penetration, monitoring manufacturing processes for quality control, and in medical and healthcare applications that meet the criteria for smart devices and emerging technologies. Advanced TENGs are used as highly efficient energy harvesters that can convert many types of wasted mechanical energy into the electric energy used in a range of practical applications in our daily lives. This article reviews recently advanced TENGs and their potential for use with smart devices and emerging technology applications. The work encourages and strengthens motivation to develop new smart devices and emerging technologies to serve us in many fields of our daily living. When TENGs are introduced into smart devices and emerging technologies, they can be applied in a variety of practical applications such as the food processing industry, information and communication technology, agriculture, construction, transportation, marine technology, the energy sector, mechanical processing, manufacturing, self-powered sensors, Industry 4.0, drug safety, and robotics due to their sustainable and renewable energy, light weight, cost effectiveness, flexibility, and self-powered portable energy sources. Their advantages, disadvantages, and solutions are also discussed for further research. Full article