Search Results (4,030)

The Fit for 55 package introduced by the European Union aims to achieve a 55% reduction in greenhouse gas emissions by 2030. In parallel, increasingly stringent exhaust gas regulations have intensified research into alternative fuels. Ethanol presents a promising option due to its compatibility with gasoline, higher octane rating, and lower exhaust emissions compared to conventional gasoline. Additionally, ethanol can be derived from agricultural waste, further enhancing its sustainability. This study examines the impact of two ethanol–gasoline blends (E10, E20) on emissions and performance in a turbocharged gasoline direct injection (TGDI) spark-ignition (SI) engine. The investigation is conducted using three-dimensional computational fluid dynamics (3D CFD) simulations to minimize development time and costs. This paper details the model development process and presents the initial results. The boundary conditions for the simulations are derived from one-dimensional (1D) simulations, which have been validated against experimental data. Subsequently, the simulated performance and emissions results are compared with experimental measurements. The E10 simulations correlated well with experimental measurements, with the largest deviation in cylinder pressure being an RMSE of 1.42. In terms of emissions, HC was underpredicted, while CO was overpredicted compared to the experimental data. For E20, the IMEP was slightly higher at some operating points; however, the deviations were negligible. Regarding emissions, HC and CO emissions were higher with E20, whereas NOx and CO₂ emissions were lower. Full article

The rapid development of the modern power system puts forward high requirements for economic dispatch, and the defects of the traditional centralized economic dispatch method with low security and poor optimization effect have been difficult to adapt to the development of power system. Therefore, finding an economic dispatch method that reduces electricity generation costs and CO₂ emissions is important. This study establishes a multi-region distributed optimization model and combines the multi-region distributed optimization model with a multi-gradient optimization algorithm to propose a multi-region distributed multi-gradient whale optimization algorithm (MRDMGWOA). In this study, MRDMGWOA is simulated on the IEEE 39 system and 118 system, and its performance is compared with other heuristic algorithms. The results show that: (1) in the IEEE 39 system, MRDMGWOA reduces the power generation cost and CO₂ emission by 17% and 22%, respectively, and reduces the computation time by 16.14 s compared with the centralized optimization; (2) in the IEEE 118 system, the two metrics are further optimized, with a 20% and 17% reduction in the cost and emission, respectively, and an improvement in the computational efficiency by 45.46 s; (3) in the spacing, hypervolume, and Euclidian metrics evaluation, MRDMGWOA outperforms other algorithms; (4) compared with the existing DMOGWO and DMOMFO, the computation time of MRDMGWOA is reduced by 177.49 s and 124.15 s, respectively, and the scheduling scheme obtained by MRDMGWOA is more optimal than DMOGWO and DMOMFO. Full article

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO₂ emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization. Full article

This study empirically evaluates the energy and carbon reduction effects of an envelope retrofit applied to an aging public building in South Korea. Unlike previous studies that primarily relied on simulation-based analyses, this work fills the empirical research gap by using actual utility billing data collected over one pre-retrofit year (2019) and two post-retrofit years (2023–2024). The retrofit included improvements to exterior walls, roofs, and windows, aiming to enhance thermal insulation and airtightness. The analysis revealed that monthly electricity consumption was reduced by 14.7% in 2023 and 8.0% in 2024 compared to that in the baseline year, with corresponding decreases in electricity costs and carbon dioxide emissions. Seasonal variations were evident: energy savings were significant in the winter due to reduced heating demand, while cooling energy use slightly increased in the summer, likely due to diminished solar heat gains resulting from improved insulation. By addressing both heating and cooling impacts, this study offers practical insights into the trade-offs of envelope retrofitting. The findings contribute to the body of knowledge by demonstrating the real-world performance of retrofit technologies and providing data-driven evidence that can inform policies and strategies for improving energy efficiency in public buildings. Full article

The sharing economy is considered to be a potentially efficacious approach for promoting sustainable production and consumption (SPC). This study utilizes dockless bike sharing (DBS) in Beijing as a case study to examine how sharing economy policies and business practices advance SPC. It also dynamically quantifies the environmental and economic performance of DBS practices from a life cycle perspective. The findings indicate that effective SPC practices can be achieved through the collaborative efforts of multiple stakeholders, including the government, operators, manufacturers, consumers, recycling agencies, and other business partners, supported by regulatory systems and advanced technologies. The SPC practices markedly improved the sustainability of DBS promotion in Beijing. This is evidenced by the increase in greenhouse gas (GHG) emission reduction benefits, which have risen from approximately 35.81 g CO₂-eq to 124.40 g CO₂-eq per kilometer of DBS travel. Considering changes in private bicycle ownership, this value could reach approximately 150.60 g CO₂-eq. Although the economic performance of DBS operators has also improved, it remains challenging to achieve profitability, even when considering the economic value of the emission reduction benefits. In certain scenarios, DBS can maximize profits by optimizing fleet size and efficiency, without compromising the benefits of emission reductions. The framework of stakeholder interaction proposed in this study and the results of empirical analysis not only assist regulators, businesses, and the public in better understanding and promoting sustainable production and consumption practices in the sharing economy but also provide valuable insights for achieving a win-win situation of platform profitability and environmental benefits in the SPC practice process. Full article

This study employs k-means clustering to group 30 Chinese provinces into four CO₂ emission patterns, characterized by increasing emission levels and distinct energy consumption structures, and captures their dynamic evolution from 2000 to 2021 using a discrete endogenous Markov chain approach. While Shanghai, Jiangxi, and Hebei retained their original classifications, provinces such as Beijing, Fujian, Tianjin, and Anhui transitioned from higher to lower emission patterns, indicating notable reversals in emission trajectories. To identify the determinants of these transitions, GDP growth rate, population growth rate, and energy investment are incorporated as time varying covariates. The empirical findings demonstrate that GDP growth substantially increases interpattern mobility, thereby weakening state persistence, whereas population growth and energy investment tend to reinforce emission pattern stability. These results imply that policy responses must be tailored to regional dynamics. In rapidly growing regions, fiscal incentives and technological upgrading may facilitate downward transitions in emission states, whereas in provinces where emissions remain persistent due to demographic or investment related rigidity, structural adjustments and long term mitigation frameworks are essential. The study underscores the importance of integrating economic, demographic, and investment characteristics into carbon reduction strategies through a region specific and data informed approach. Full article

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al₂O₃ nanofluids in a water–ethylene glycol base (40:60%) and with the addition of Tween 80 surfactant (0.2 wt%) on thermal efficiency (ε) and exergy (η_ex) in a plate heat exchanger at DHW flows of 3 and 12 L/min. The numerical NTU–ε model was used with dynamic updating of thermophysical properties of nanofluids and the solution of the ODE system using the ode45 method, and the validation was carried out against the literature data. The results showed that the nanofluids achieved ε ≈ 0.85 (vs. ε ≈ 0.87 for the base fluid) and η_ex ≈ 0.72 (vs. η_ex ≈ 0.74), with higher entropy generation. The addition of Tween 80 reduced the viscosity by about 10–15%, resulting in a slight increase of Re and h-factor; however, the impact on ε and η_ex was marginal. The environmental analysis with an annual demand of Q = 3000 kWh/year and an emission factor of 0.2 kg CO₂/kWh showed that for ε < 0.87 the nanofluids increased the emissions by ≈16 kg CO₂/year, while at ε ≈ 0.92, a reduction of ≈5% was possible. This paper highlights the need to optimize nanofluid viscosity and exchanger geometry to maximize energy and environmental benefits. Nowadays, due to the growing problems of global warming, the analysis of energy efficiency and carbon footprint related to the functioning of a building seems to be crucial. Full article

The global cement industry remains a significant contributor to carbon dioxide (CO₂) emissions, prompting substantial research efforts toward sustainable construction materials. Lithium slag (LS), a by-product of lithium extraction, has attracted attention as a supplementary cementitious material (SCM). This review synthesizes experimental findings on LS replacement levels, fresh-state behavior, mechanical performance (compressive, tensile, and flexural strengths), time-dependent deformation (shrinkage and creep), and durability (sulfate, acid, abrasion, and thermal) of LS-modified concretes. Statistical analysis identifies an optimal LS dosage of 20–30% (average 24%) for maximizing compressive strength and long-term durability, with 40% as a practical upper limit for tensile and flexural performance. Fresh-state tests show that workability losses at high LS content can be mitigated via superplasticizers. Drying shrinkage and creep strains decrease in a dose-dependent manner with up to 30% LS. High-volume (40%) LS blends achieve up to an 18% gain in 180-day compressive strength and >30% reduction in permeability metrics. Under elevated temperatures, 20% LS mixes retain up to 50% more residual strength than controls. In advanced systems—autoclaved aerated concrete (AAC), one-part geopolymers, and recycled aggregate composites—LS further enhances both microstructural densification and durability. In particular, LS emerges as a versatile SCM that optimizes mechanical and durability performance, supports material circularity, and reduces the carbon footprint. Full article

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

Understanding vehicle emissions is essential for developing effective carbon reduction strategies in the transport sector. Conventional emission models often assume homogeneity and linearity, overlooking real-world asymmetries that arise from variations in vehicle design and powertrain configurations. This study explores how machine learning and explainable AI techniques can effectively capture both symmetric and asymmetric emission patterns across different vehicle types, thereby contributing to more sustainable transport planning. Addressing a key gap in the existing literature, the study poses the following question: how do structural and behavioral factors contribute to asymmetric emission responses in internal combustion engine vehicles compared to new energy vehicles? Utilizing a large-scale Spanish vehicle registration dataset, the analysis classifies vehicles by powertrain type and applies five supervised learning algorithms to predict CO₂ emissions. SHapley Additive exPlanations (SHAPs) are employed to identify nonlinear and threshold-based relationships between emissions and vehicle characteristics such as fuel consumption, weight, and height. Among the models tested, the Random Forest algorithm achieves the highest predictive accuracy. The findings reveal critical asymmetries in emission behavior, particularly among hybrid vehicles, which challenge the assumption of uniform policy applicability. This study provides both methodological innovation and practical insights for symmetry-aware emission modeling, offering support for more targeted eco-design and policy decisions that align with long-term sustainability goals. Full article

This study investigates the feasibility of using volcanic lapillus as a supplementary cementitious material (SCM) in mortar production to improve the sustainability of the cement industry. Cement production is one of the main sources of CO₂ emissions, mainly due to clinker production. Replacing clinker with SCMs, such as volcanic lapillus, can reduce the environmental impact while maintaining adequate mechanical properties. Experiments were conducted to replace up to 20 wt% of limestone Portland cement with volcanic lapillus. Workability, compressive strength, microstructure, resistance to alkali-silica reaction (ASR), sulfate, and chloride penetration were analyzed. The results showed that up to 10% replacement had a minimal effect on mechanical properties, while higher percentages resulted in reduced strength but still improved some durability features. The control sample cured 28 days showed a compressive strength of 43.05 MPa compared with 36.89 MPa for the sample containing 10% lapillus. After 90 days the respective values for the above samples were 44.76 MPa and 44.57 MPa. Scanning electron microscopy (SEM) revealed good gel–aggregate adhesion, and thermogravimetric analysis (TGA) confirmed reduced calcium hydroxide content, indicating pozzolanic activity. Overall, volcanic lapillus shows promise as a sustainable SCM, offering CO₂ reduction and durability benefits, although higher replacement rates require further optimization. Full article

A brick kiln was experimentally studied to measure the transient temperature of hot gases and the compressive strength of the bricks, using pine wood as fuel, in order to evaluate the thermal performance of the actual system. In addition, a transient combustion model based on computational fluid dynamics (CFD) was used to simulate the combustion of natural gas in the brick kiln as a hypothetical case, with the aim of investigating the potential benefits of fuel switching. The theoretical stoichiometric combustion of both pine wood and natural gas was employed to compare the mole fractions and the adiabatic flame temperature. Also, the transient hot gas temperature obtained from the experimental wood-fired kiln were compared with those from the simulated natural gas-fired kiln. Furthermore, numerical simulations were carried out to obtain the transient hot gas temperature and NOx emissions under stoichiometric, fuel-rich, and excess air conditions. The results of CO₂ mole fractions from stoichiometric combustion demonstrate that natural gas may represent a cleaner alternative for use in brick kilns, due to a 44.08% reduction in emissions. Contour plots of transient hot gases temperature, velocity, and CO₂ emission inside the kiln are presented. Moreover, the time-dependent emissions of CO₂, H₂O, and CO at the kiln outlet are shown. It can be concluded that the presence of CO mole fractions at the kiln outlet suggests that the transient combustion process could be further improved. The low firing efficiency of bricks and the thermal efficiency obtained are attributed to uneven temperatures distributions inside the kiln. Moreover, hot gas temperature and NOx emissions were found to be higher under stoichiometric conditions than under fuel-rich or excess of air conditions. Therefore, this work could be useful for improving the thermal–hydraulic and emissions performance of brick kilns, as well as for future kiln design improvements. Full article

To support carbon peaking and neutrality goals in the city transportation sector, this paper accounts for CO₂ emissions from the transport sector in Xuzhou City, North Jiangsu Province, from 1995 to 2023. This study explores the relationship between transport-related carbon emissions and economic growth, using the TAPIO decoupling index. Meanwhile, a carbon emission prediction model based on the STIRPAT framework is constructed, with scenario analysis applied to forecast future emissions. Results show three decoupling stages: the first, dominated by weak and expansive negative decoupling, reflects extensive economic growth; the second features weak decoupling with expansive coupling, indicating a more environmentally coordinated phase; the third transitions from expansive negative decoupling and weak decoupling to strong decoupling and expansive coupling, suggesting a shift in development patterns. Under the baseline, low-carbon, and enhanced low-carbon scenarios, by 2030, the CO₂ emissions of the transportation industry in Xuzhou will be 10,154,700 tons, 9,072,500 tons, and 8,835,000 tons, respectively, and the CO₂ emissions under the low-carbon scenario and the enhanced low-carbon scenario will be reduced by 10.66% and 13.00%, respectively. Based on these findings, the study proposes carbon reduction strategies for Xuzhou’s transport sector, focusing on policy regulation, energy use, and structural adjustments. Full article

The production of iron and steel plays a significant role in the anthropogenic carbon footprint, accounting for 7% of global GHG emissions. In the context of CO₂ mitigation, the steelmaking industry is looking to potentially replace traditional carbon-based ironmaking processes with hydrogen-based direct reduction of iron ore in shaft furnaces. Before industrialization, detailed modeling and parametric studies were needed to determine the proper operating parameters of this promising technology. The modeling approach selected here was to complement REDUCTOR, a detailed finite-volume model of the shaft furnace, which can simulate the gas and solid flows, heat transfers and reaction kinetics throughout the reactor, with an extension that describes the whole gas circuit of the direct reduction plant, including the top gas recycling set up and the fresh hydrogen production. Innovative strategies (such as the redirection of part of the bustle gas to a cooling inlet, the use of high nitrogen content in the gas, and the introduction of a hot solid burden) were investigated, and their effects on furnace operation (gas utilization degree and total energy consumption) were studied with a constant metallization target of 94%. It has also been demonstrated that complete metallization can be achieved at little expense. These strategies can improve the thermochemical state of the furnace and lead to different energy requirements. Full article