Search Results (175)

Direct electrification and hydrogen utilization represent two key pathways for decarbonizing the glass industry, with their effectiveness subject to adequate furnace design and renewable energy availability. This study presents a techno-economic assessment for optimal solar energy integration in a representative 300 t/d oxyfuel container glass furnace with a specific energy consumption of 4.35 GJ/t. A mixed-integer linear programming formulation is developed to evaluate specific melting costs, carbon emissions, and renewable energy self-consumption and self-production rates across three scenarios: direct solar coupling, battery storage, and a hydrogen-based infrastructure. Battery storage achieves the greatest reductions in specific melting costs and emissions, whereas hydrogen integration minimizes electricity export to the grid. By incorporating capital investment considerations, the study quantifies the cost premiums and capacity requirements under varying decarbonization targets. A combination of 30 MW of solar plant and 9 MW of electric boosting enables the realization of around 30% carbon reduction while increasing total costs by 25%. Deeper decarbonization targets require more advanced systems, with batteries emerging as a cost-effective solution. These findings offer critical insights into the economic and environmental trade-offs, as well as the technical constraints associated with renewable energy adoption in the glass industry, providing a foundation for strategic energy and decarbonization planning. Full article

Boda boda motorbike taxis are a primary mode of transport in Nairobi, Kenya, and a major source of urban air pollution. This study investigates the environmental and electrical grid impacts of electrifying Nairobi’s boda boda fleet. Using real-world tracking data from 118 motorbikes, we simulated the effects of a full-scale transition from internal combustion engine (ICE) vehicles to electric motorbikes. We analysed various scenarios, including different battery charging strategies (swapping and home charging), motor efficiencies, battery capacities, charging rates, and the potential for solar power offsetting. The results indicate that electrification could reduce daily ${\mathrm{CO}}_2$ emissions by approximately 85% and eliminate tailpipe particulate matter emissions. However, transitioning the entire country’s fleet would increase the national daily energy demand by up to 6.85 GWh and could introduce peak grid loads as high as 2.40 GW, depending on the charging approach and vehicle efficiency. Battery swapping was found to distribute the grid load more evenly and better complement solar power integration compared to home charging, which concentrates demand in the evening. This research provides a scalable, data-driven framework for policymakers to assess the impacts of transport electrification in similar urban contexts, highlighting the critical trade-offs between environmental benefits and grid infrastructure requirements. Full article

This study presents a comprehensive case of green remodeling applied to a local fire station in Seoul, South Korea. The project aimed to improve energy performance through an integrated upgrade of passive systems (exterior insulation, high-performance windows, and airtightness) and active systems (electric heat pumps, energy recovery ventilation, and rooftop photovoltaic systems), while maintaining uninterrupted emergency operations. A detailed analysis of annual energy use before and after the remodeling shows a 44% reduction in total energy consumption, significantly exceeding the initial reduction target of 20%. While electricity use increased modestly during winter due to the electrification of heating systems, gas consumption dropped sharply by 63%, indicating a shift in energy source and improved efficiency. The building’s airtightness also improved significantly, with a reduction in the air change rate. The project further addressed unique challenges associated with continuously operated public facilities, such as insulating the fire apparatus garage and executing phased construction to avoid operational disruption. This study contributes valuable insights into green remodeling strategies for mission-critical public buildings, emphasizing the importance of integrating technical upgrades with operational constraints to achieve verified energy performance improvements. Full article

To address the issues of bulky structure and complex transmission systems in current transplanters, a compact, electric-driven automatic transplanter was designed. Using pepper plug seedlings as the test subject, this study investigated plug tray dimensions and planting patterns. According to the design requirement that the width of the single-row transplanter must be less than 62.5 cm, a three-dimensional transplanter model was constructed. The transplanter comprises a coaxially installed dual-layer seedling conveying device and a sector-expanding automatic seedling picking and depositing device. The structural dimensions, drive configurations, and driving forces of the transplanter were also determined. Finally, the circuit and pneumatic system were designed, and the transplanter was assembled. Both bench and field tests were conducted to select the optimal working parameters. The test results demonstrated that the seedling picking and depositing mechanism met the required operational efficiency. In static seedling picking and depositing tests, at three transplanting speeds of 120 plants/min, 160 plants/min, and 200 plants/min, the success rates of seedling picking and depositing were 100%, 100%, and 97.5%, respectively. In the field test, at three transplanting speeds of 80 plants/min, 100 plants/min, and 120 plants/min, the transplanting success rates were 94.17%, 90.83%, and 88.33%, respectively. These results illustrate that the compact, electric-driven seedling conveying and picking and depositing devices meet the operational demands of automatic transplanting, providing a reference for the miniaturization and electrification of transplanters. Full article

This article examines the energy efficiency and climate impact of various heating methods commonly employed across industrial sectors. Fossil fuel combustion heat sources, which are predominantly employed for industrial heating, contribute significantly to atmospheric pollution and associated asset losses. The electrification of industrial heating has the potential to substantially reduce the total energy consumed in industrial heating processes and significantly mitigate the rate of global warming. Advances in electrical heating technologies are driven by enhanced energy conversion, compactness, and precision control capabilities, ensuring attractive financial payback periods for clean, energy-efficient equipment. These advancements stem from the use of improved performance materials, process optimization, and waste heat utilization practices, particularly at high temperatures. The technical challenges associated with large-scale, heavy-duty electric process heating are addressed through the novel innovations discussed in this article. Electrification and the corresponding energy efficiency improvements reduce the water consumed for industrial steam requirements. The article reviews new technologies that replace conventional process gas heaters and pressure boilers with efficient electric process gas heaters and instant steam generators, operating in the high kilowatt and megawatt power ranges with very high-temperature capabilities. Financial payback calculations for energy-optimized processes are illustrated with examples encompassing a range of comparative energy costs across various temperatures. The economics and implications of waste heat utilization are also examined in this article. Additionally, the role of futuristic, radical technical innovations is evaluated as a sustainable pathway that can significantly lower energy consumption without compromising performance objectives. The potential for a new paradigm of self-organization in processes and final usage objectives is briefly explored for sustainable innovations in thermal engineering and materials development. The policy implications and early adoption of large-scale, energy-efficient thermal electrification are discussed in the context of temperature segmentation for industrial-scale processes and climate-driven asset losses. Policy shifts towards incentivizing energy efficiency at the manufacturing level of heater use are recommended as a pathway for deep decarbonization. Full article

Buildings account for about a third of global energy and it is thus imperative to eliminate the use of fossil fuels to power and provide for their thermal needs. Solar photovoltaic (PV) technology can provide power and with electrification, heating/cooling, but there is often a load mismatch with the intermittent solar supply. Electric batteries can overcome this challenge at high solar penetration rates but are still capital-intensive. A promising solution is thermal energy storage (TES), which has a low cost per unit of energy. This review provides an in-depth analysis of TES but specifically focuses on phase change material (PCM)-based TES, and its significance in the building sector. The classification, characterization, properties, applications, challenges, and modeling of PCM-TES are detailed. Finally, the potential for integrating TES with PV and heat pump (HP) technologies to decarbonize the residential sector is detailed. Although many studies show proof of carbon reduction for the individual and coupled systems, the integration of PV+HP+PCM-TES systems as a whole unit has not been developed to achieve carbon neutrality and facilitate net zero emission goals. Overall, there is still a lack of available literature and experimental datasets for these complex systems which are needed to develop models for global implementation as well as studies to quantify their economic and environmental performance. Full article

The electrification of energy systems is essential for carbon reduction and sustainable energy goals. However, current network asset ratings and the poor thermal efficiency of older buildings pose significant challenges. This study evaluates the impact of heat pump and electric vehicle (EV) penetration on a UK residential distribution network, considering the highest coincident electricity demand and worst weather conditions recorded over the past decade. The power flow calculation, based on Python, is performed using the pandapower library, leveraging the actual distribution network structure of the Hillingdon area by incorporating recent smart meter data from a distribution system operator alongside historical weather data from the past decade. Based on the outcome of power flow calculation, the transformer loadings and voltage levels were assessed for existing and projected heat pump and EV adoption rates, in line with national policy targets. Findings highlight that varied consumer density and diverse usage patterns significantly influence upgrade requirements. Full article

This study explores the impact of a phosphonium-based IL (trihexyltetradecylphosphonium bis(2-ethylhexyl) phosphate, [P_6,6,6,14][BEHP])) on the tribological performance of an automatic transmission fluid (ATF) when used as an additive. Tests were carried out under both non-electrified and electrified conditions in a reciprocating ball-on-flat tribometer. After tribological tests, the worn surfaces were subjected to extensive structural and surface analyses to understand the underlying friction and wear mechanisms. The addition of this ionic liquid improved the anti-wear protection of the ATF, although the wear rates were consistently higher than in non-electrified conditions. The tribofilm formed by the IL-containing ATF augmented the electrical resistance at the contact interface, thereby reducing the likelihood of electrification-induced wear. Our results point to the need for further improvements in the chemical formulation of the ionic liquids, like the one used in the present study, to enhance the protection of sliding surfaces against wear in future electric vehicle applications. Full article

Rapid urbanization in China is intensifying travel demand while making transport the nation’s third-largest source of carbon emissions. Anticipating continued growth in private-car fleets, this study integrates vehicle-stock forecasting with multi-scenario emission modeling to identify effective decarbonization pathways for Chinese cities. First, Kendall rank and grey relational analyses are combined to screen the key drivers of car ownership, creating a concise input set for prediction. A Lévy-flight-enhanced Sparrow Search Algorithm (LSSA) is then used to optimize the smoothing factor of the Generalized Regression Neural Network (GRNN), producing the Levy flight-improved Sparrow Search Algorithm optimized Generalized Regression Neural Network (LSSA-GRNN) model for annual fleet projections. Second, a three-tier scenario framework—Baseline, Moderate Low-Carbon, and Enhanced Low-Carbon—is constructed in the Long-range Energy Alternatives Planning System (LEAP) platform. Using Ningbo as a case study, the LSSA-GRNN outperforms both the benchmark Sparrow Search Algorithm optimized Generalized Regression Neural Network (SSA-GRNN) and the conventional GRNN across all accuracy metrics. Results indicate that Ningbo’s car fleet will keep expanding to 2030, albeit at a slowing rate. Relative to 2022 levels, the Enhanced Low-Carbon scenario delivers the largest emission reduction, driven primarily by accelerated electrification, whereas public transport optimization exhibits a slower cumulative effect. The methodological framework offers a transferable tool for cities seeking to link fleet dynamics with emission scenarios and to design robust low-carbon transport policies. Full article

Achieving the Paris Agreement’s 1.5 °C target requires a global-scale energy transition, reaching net-zero emissions by 2050. This transition demands not only a rapid expansion of renewable energy but also significant upfront energy investment, presenting potential trade-offs between near-term energy security and long-term sustainability. Assuming we cannot rely on as yet unproven negative emissions technology, reductions must be achieved directly, requiring fossil fuel phase-out, accelerated electrification, and substantial renewable infrastructure development. This study presents a detailed, transparent methodology for the creation of a simplified global energy system model designed to rapidly evaluate trade-offs between energy and climate policy, integrating energy investment, depletion, and saturation dynamics into energy transition scenarios. The model simulates energy supply and demand across major sectors, accounting for the upfront energy costs of deploying new renewable infrastructure and the dynamics of electrification in different demand sectors. Its transparent, user-controllable framework allows for rapid scenario adjustments based on variables such as population growth, per capita energy demand, rate and extent of electrification, and strength of climate policy. The primary purpose of this paper is to present the system modelling framework. However, we also present preliminary results from scenario analysis that point to two emergent risks: (1) prioritising energy security increases the likelihood of exceeding carbon budgets, while (2) stringent emissions reductions heighten the risk of energy shortages. Even under non-existent climate policy, fossil fuel depletion makes both the renewable transition and electrification of demand inevitable, though delayed transition leads to more severe emissions overshoot. These findings underscore the urgent need for demand reduction strategies and a more nuanced understanding of the energy investment required for decarbonisation. By offering a flexible scenario tool, this study contributes to informed public discourse and policy decisions on balancing energy security, emissions reduction, and climate resilience. Full article

This paper proposes the sizing optimization method and energy management strategy for a stationary hybrid energy storage system dedicated to a DC traction power supply system. The hybrid energy storage system consists of two modules—a supercapacitor, mainly dedicated to regenerative energy utilization, and a Li-ion battery, aimed to peak power reduction. The sizing method and energy management strategy proposed in this paper aim to reduce the aging effect of lithium-ion batteries. It is shown that the parameters of both modules could be sized independently. The supercapacitor module parameters are sized based on the results of a simulation determining the regenerative power, resulting in limited catenary receptivity. The simulation model of the DC electrification system is validated by comparing the results of the simulation with the measurements of 15 min average power in a 24 h cycle as average values of one year. The battery module is sized based on the statistical data of 15 min substation power value occurrences. The battery energy capacity, its maximum discharge C-rate, and the conditions determining its operation are optimized to achieve the maximum ratio of annual income resulting from peak power reduction to annual operating cost resulting from the battery aging process and total life cycle. The case study prepared for a typical 3 kV DC substation with mixed railway traffic shows that peak power could be reduced by ~1 MW, giving a ~10-year payback period for battery module installation, while the energy consumption could be decreased by 1.9 MWh/24 h, giving a ~7.5-year payback period for supercapacitor module installation. The payback period of the whole energy storage system (ESS) is ~8.4 years. Full article

The increasing popularity of online shopping leads to more last-mile deliveries and higher emissions from last-mile delivery trucks. Despite small amounts being emitted from the tailpipe of delivery trucks, there can be a significant amount of fine particulate matter that degrades the health quality of residents from aggregated delivery trucks at the community level. Addressing the environmental impact of last-mile deliveries is needed to achieve the sustainability goals because air pollution mitigation can reduce mortalities. This study employs a comprehensive methodology to assess the health impact of fine particulate matter from last-mile delivery trucks and the benefits of their electrification. It uses a three-tiered modeling approach, incorporating emissions measurement, exposure level evaluation, and health impact assessment. In addition, this paper shows the changes in health impacts at the various levels of the fleet electrification rate using a case study in Dallas County, Texas. The results indicate that higher fine particulate matters are concentrated near or on the major roadways and transportation facilities. This study also shows the relationships between last-mile delivery emissions and socio-economic variables and found that younger, racial minorities and low-income communities are exposed to higher last-mile emissions due to the proximity of their residences to major truck corridors. To evaluate the health impacts of fleet electrification, this study uses 2%, 10%, and 30% market shares of fleet electrification. The results indicate that for 2% of the market share of fleet electrification to last-mile delivery trucks, up to 1 death per year can be prevented, while 70 deaths per year can be prevented with 30% of electrification for the whole traffic. Full article

This study investigates the carbon- and cost-effectiveness of decarbonization strategies in retrofits of prototypical single-family homes built before 1980 in Houston, Los Angeles, and Chicago, USA. When investigating the carbon performance of home retrofits, embodied carbon, location-specific electricity grid emission rates, variation in future grid emission rates depending on policy changes, and the time value of carbon (TVC) are often omitted. If those subjects are addressed, they are rarely analyzed all together. Using energy simulation and Life Cycle Assessment, this research quantified the whole-life carbon reduction and Life Cycle Cost, in kgCO₂e/US$, associated with each retrofit, ranked the interventions accordingly, and calculated how the rankings would change if electricity grid emission rates differed or the TVC were considered. Assuming current grid emission rates, envelope retrofits tended to rank better than renewable energy and electrification upgrades in terms of carbon reduction per dollar spent. However, if grid emission rates were lower, electrification upgrades improved in rank, while renewable energy upgrades declined. Including the TVC generally caused retrofits with high initial carbon to drop in rank. The results illustrate that considering whole-life carbon, regionally specific grid emissions, future grid emission scenarios, and the TVC can have important implications on decarbonization recommendations, and the findings suggest that analyses, especially those supporting building policy or incentive programs, should include such considerations. Full article

With an increasing global emphasis on reducing carbon emissions and enhancing energy efficiency, the rising popularity of electric vehicles (EVs) has played a pivotal role in facilitating the transition to electrification within transportation sectors. However, the variability in their charging behavior has posed challenges for grid loads. In this study, a day-ahead scheduling model is developed for an integrated energy system to assess the impact of various electric vehicle charging modes on energy economics during typical days in summer, winter, and transition seasons. Additionally, the influence of optimized charging strategies on increasing the utilization of renewable energy and enhancing the operational efficiency of the grid is explored. The findings reveal that the abandonment rates of wind and solar energy associated with the orderly charging mode are 0 during typical days in winter and summer but decrease by 64.83% during the transition seasons. Furthermore, the power purchased from the grid declines by 18.79%, 19.34%, and 53.31% across these seasonal conditions, in respective. Consequently, the total load cost associated with the ordered charging mode decreases by 29.69%, 25.96%, and 43.71%, respectively, for summer, winter, and transition seasons. Full article

The rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are quite limited. China, which has the largest EV market in the world, has witnessed a substantial increase in EV crashes in recent years. Therefore, this study comprehensively investigated the characteristics of EV crashes by analyzing the 2023 traffic crash data from Changshu. This is a pioneering study that discusses EV safety by comparing real EV crashes and ICEV crashes from a city in China, the largest EV market in the world. It was found that EV crashes had a higher fatality rate compared to internal combustion engine vehicle (ICEV) crashes. Compared to ICEV crashes, EV crashes are more likely to hit pedestrians and occur during the starting phase. Among the vehicles involved in crashes, the proportion of EVs used for passenger and freight transport was higher than that of ICEVs. In addition, for EV crashes, the proportion of female drivers was much higher, but the proportion of elderly drivers was much lower. Thus, to identify the significant factors influencing crash severity, a logistic regression model was built. The results confirm that EV crashes are more likely to be more fatal than ICEV crashes. In addition, hitting pedestrians and light trucks and crashes occurring in rural areas, at intersections, during winter, and on weekdays could significantly increase the risk of fatalities. These findings are expected to provide new perspectives for improving EV safety within the wave of automotive electrification. Full article