Search Results (1,682)

Fluid Catalytic Cracking (FCC) constitutes a critical process in petroleum refining, facing increasing pressure to align with sustainable development goals by improving energy efficiency and reducing environmental impact. This study tackles a multi-objective optimization challenge in FCC operations, seeking to simultaneously maximize the gasoline production and minimize the coke yield—the latter being directly linked to $\mathrm{C}{\mathrm{O}}_2$ emissions in FCC. A data-driven optimization model leveraging a dual Long Short-Term Memory architecture is developed to capture complex relationships between operating variables and product yields. To efficiently solve the model, an Improved Multi-Objective Whale Optimization Algorithm (IMOWOA) is proposed, integrating problem-specific adaptive multi-neighborhood search and dynamic restart mechanisms. Extensive experimental evaluations demonstrate that IMOWOA achieves superior convergence characteristics and comprehensive performance compared to established multi-objective algorithms. Relative to the yields before optimization, the proposed methodology increases the gasoline yield by 0.32% on average, coupled with an average reduction of 0.11% in the coke yield. For the studied FCC unit with an annual processing capacity of 2.6 million tons, the coke reduction corresponds to an annual $\mathrm{C}{\mathrm{O}}_2$ emission reduction of approximately 10,277 tons, delivering benefits to sustainable FCC operations. Full article

Shifting urban land from planned to marketed allocation is an essential aspect of China’s economic market reform. However, its impact on carbon emissions has not been directly examined. Using prefecture-level urban panel data from 1997 to 2017, we empirically test the effect and mechanism of land transfer marketization (LTM) on carbon emissions. The results show that the LTM can significantly reduce urban CO₂ emissions. Specifically, a unit increase in the degree of LTM can decrease total urban CO₂ emissions by 3% and carbon intensity by 2.4%. The main transmission mechanism is attributed to three effects of land transfer: (1) Structural effect. LTM increases the supply of commercial service land and reduces that of industrial land, thereby reducing the total urban carbon emissions. (2) Resource allocation effect. LMT will screen out efficient enterprises and promote the reduction of carbon emissions. (3) Financing effect. By enhancing the ability of governments and businesses to finance, LTM can facilitate the introduction of green industries and improve the research of low-carbon technologies of enterprises, thus reducing carbon emissions. The above conclusions have passed a series of robustness tests. They also show that the impacts of the LMT are heterogeneous and stronger in the Centre and West in cities with lower economic development levels and larger populations. This study validates the efficacy and underlying mechanism of LTM in significantly reducing urban carbon emissions. Consequently, it offers a framework for the formulation of policies aimed at reducing urban carbon emissions through land market reform. Full article

The relative wind is a significant but underexplored influencing factor on the tradeoff between propulsion efficiency and pollutant emissions for ships. In this study, full-scale measurements obtained from four voyages of the training ship of Baekkyung were used to quantify the effects of relative wind on ship propulsion efficiency and pollutant emissions. The collected navigational, engine performance, and emission data—including parameters such as shaft power, engine load, specific fuel oil consumption (SFOC), and NO_x and SO_x concentrations—were synchronized and then analyzed using statistical methods and a generalized additive model (GAM). Statistical correlation analysis and a GAM were applied to capture nonlinear relationships between variables. Compared with linear models, the GAM achieved higher predictive accuracy (R² = 0.98) and effectively identified threshold and interaction effects. The results showed that headwind conditions increased the engine load by ~12% and SFOC by 8.4 g/kWh while tailwind conditions reduced SFOC by up to 6.7 g/kWh. NO_x emissions peaked under headwind conditions and exhibited nonlinear escalation beyond a relative wind speed of 12 kn. An operational window was identified for simultaneous improvement of the propulsion efficiency and reduction in pollutant emissions under beam wind and tailwind conditions at moderate relative wind speeds of 6–10 kn and an engine load of 30–40%. These findings can serve as a guide for incorporating relative wind into operational strategies for maritime autonomous surface ships. Full article

Carbon dioxide (CO₂), the primary anthropogenic greenhouse gas, drives significant and potentially irreversible impacts on ecosystems, biodiversity, and human health. Achieving the Paris Agreement target of limiting global warming to well below 2 °C, ideally 1.5 °C, requires rapid and substantial global emission reductions. While recent decades have seen advances in clean energy technologies, carbon capture, utilization, and storage (CCUS) remain essential for deep decarbonization. Despite proven technical readiness, large-scale carbon capture and storage (CCS) deployment has lagged initial targets. This review evaluates CCS technologies and their contributions to net-zero objectives, with emphasis on sector-specific applications. We found that, in the iron and steel industry, post-combustion CCS and oxy-combustion demonstrate potential to achieve the highest CO₂ capture efficiencies, whereas cement decarbonization is best supported by oxy-fuel combustion, calcium looping, and emerging direct capture methods. For petrochemical and refining operations, oxy-combustion, post-combustion, and chemical looping offer effective process integration and energy efficiency gains. Direct air capture (DAC) stands out for its siting flexibility, low land-use conflict, and ability to remove atmospheric CO₂, but it’s hindered by high costs (~$100–1000/t CO₂). Conversely, post-combustion capture is more cost-effective (~$47–76/t CO₂) and compatible with existing infrastructure. CCUS could deliver ~8% of required emission reductions for net-zero by 2050, equivalent to ~6 Gt CO₂ annually. Scaling deployment will require overcoming challenges through material innovations aided by artificial intelligence (AI) and machine learning, improving capture efficiency, integrating CCS with renewable hybrid systems, and establishing strong, coordinated policy frameworks. Full article

This study presents an experimental optimization of an industrial-scale compressed air system aimed at improving energy efficiency and operational performance. The evaluation was conducted in accordance with ISO 11011 standards, covering supply, distribution, demand, and air quality aspects. Reference and optimized scenarios were directly compared under equivalent operating conditions. The most significant improvement was the elimination of a 0.54-bar pressure drop, which enabled the compressor’s set pressure to be reduced from 7.0 bar to 6.5 bar and prevented unnecessary load cycles. In addition, the detection and repair of leakage points significantly reduced constant loads during non-production hours. As a result, average power consumption decreased by 32.6%, while idle consumption was reduced by 70%. Improvements in filtration and condensate management lowered moisture and oil carryover, thereby enhancing process reliability. Considering annual operating hours, the optimization was estimated to offer a potential reduction of approximately 63.5 tons of CO₂ emissions. The results demonstrate that substantial efficiency and sustainability gains can be achieved through physical adjustments and operational measures without modifying control algorithms. Full article

This study examines the dynamic decoupling relationship between energy consumption and export growth in China since its accession to the World Trade Organization (WTO) (2002–2018) by combining the noncompetitive input–output model, Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model. The results reveal the substantial energy consumption generated by China’s export trade, emphasizing the urgency of reducing energy consumption in export trade for energy conservation and emissions reduction. Since its WTO accession, China has experienced sustained improvement in the energy decoupling effect during the growth of export trade, entering a period of strong decoupling from 2014 to 2018. The expanded export scale remains a major obstacle to decoupling export trade growth from energy consumption, while decreased energy intensity in exports is a significant driving force for energy decoupling, with relatively minor impact from changes in the export trade structure. By integrating non-competitive input–output modeling, Tapio decoupling analysis, and LMDI decomposition, this study develops a novel framework to investigate the structural drivers of energy–export decoupling in China from 2002 to 2018. Bridging methods from energy systems, trade economics, and policy modeling, it contributes to the field of multi-disciplinary sustainability by offering sector-level insights and decomposition-based evidence to support more efficient, equitable, and sustainable trade transitions. Full article

In micro gas turbines, electrical power from the high-speed generator is delivered to the grid through a converter that influences overall efficiency and energy quality. This subsystem is often overlooked in efforts to improve turbine performance, which have traditionally focused on combustors and turbomachinery. This study investigates how replacing conventional silicon switching devices in the converter with silicon carbide technology can directly reduce greenhouse gas emissions from micro gas turbines. Although silicon carbide is widely used in electric vehicles and distributed energy systems, its emission reduction impact has not been assessed in micro gas turbines. A MATLAB-based model of a 100 kW Ansaldo Energia micro gas turbine was used to compare the performance of silicon and silicon carbide converters across the 20–100 kW operating range. Silicon carbide reduced total converter losses from 4.316 kW to 3.426 kW at full load, a decrease of 0.889 kW. This improvement lowered carbon dioxide emissions by 5.7 g/kWh and increased net electrical efficiency from 30.03% to 30.29%. Each turbine can therefore avoid about 1.53 tonnes of carbon dioxide annually, or 11.61 tonnes over a 50,000 h service life, without altering turbine design, combustor geometry, or fuel composition. This work establishes the first quantitative link between wide-bandgap semiconductor performance and direct greenhouse gas mitigation in micro gas turbines, demonstrating that upgrading converter technology from silicon to silicon carbide offers a deployable pathway to reduce emissions from micro gas turbines and, by extension, lower the carbon intensity of distributed generation systems. Full article

Coal-to-Synthetic Natural Gas (SNG) plays a crucial role in China’s decarbonization strategy but faces significant sustainability challenges due to its carbon-intensive nature. This study integrates Life Cycle Assessment (LCA) with Box–Behnken Design and Response Surface Methodology (BBD-RSM) to quantify and optimize key parameters for emission reduction. The LCA results indicate that 90.48% of total emissions originate from the SNG production stage, while coal mining accounts for 9.38%, leading to a carbon intensity of 660.92 g CO₂^eq/kWh, second only to conventional coal power. Through BBD-RSM optimization, the optimal parameter combination was identified as a raw coal selection rate of 62.5%, an effective calorific value of 16.75 MJ/kg, and a conversion efficiency of 83%, corresponding to an energy-based rate of return (ERR) of 49.79%. The optimized scenario demonstrates a substantial reduction in total life-cycle emissions compared with the baseline, thereby improving the environmental viability of coal-to-SNG technology. Furthermore, this study employs the energy-based rate of return (ERR) as a normalization and comparative evaluation metric to quantitatively assess emission reduction potential. The ERR, combined with BBD-RSM, enables a more systematic exploration of emission-driving factors and enhances the application of statistical optimization methods in the coal-to-SNG sector. The findings provide practical strategies for promoting the low-carbon transformation of the coal-to-SNG industry and contribute to the broader advancement of sustainable energy development. Full article

Structural symmetry of constructions directly influences material efficiency and construction complexity. This study presents the Symmetry Optimization and Detection for Architecture (SODA) framework for assessing and improving structural symmetry in existing buildings. The system employs computer vision methods for symmetry detection, the Continuous Symmetry Measure (CSM) based on molecular research, and genetic algorithms for optimization. A total of 50 structures of the Netherlands (Dutch) were examined, which encompassed an area of 2.287 million m², categorized into five distinct groups. It was indicated that average symmetry improvements were observed, with an increase from 68.4% to 82.7%. The average material reductions were observed to be 18.5%, which was accompanied by a reduction in construction time of 19.2%. The total acknowledged cost reductions were recorded at €87.3 million, with a corresponding reduction of 21,450 tons of CO₂ emissions. The results of a statistical analysis suggest that a negative correlation exists between building height and optimization potential (R² = 0.72). The framework illustrates that systematic symmetry optimization yields substantial efficiency enhancements while preserving architectural integrity and code adherence. Full article

A central sustainability question is how the digital economy helps societies decarbonize at lower cost. We develop a carbon-market-consistent framework to show how digitalization can strengthen market governance, reduce regional carbon-abatement costs, and accelerate green transformation. Using data for 30 Chinese provinces from 2011–2022, we estimate panel fixed-effects models and conduct numerical simulations to test the digital economy’s dynamic, inverted-U-shaped effect on abatement costs, accounting for internal and external drivers. The digital development shifts the abatement–cost curve downward and leftward by speeding the transition from internal mitigation costs to external trading costs, enabling regions to reach the cost-reduction stage earlier and at lower overall cost. Mechanism evidence indicates two channels: externally, digitalization enhances carbon-market sophistication (liquidity, price discovery, and compliance efficiency); internally, it promotes technological progress and energy-efficiency improvements that raise emission-reduction productivity. In the short run, emissions trading provides external incentives that buffer production-cost pressures from digital-capital investment; in the long run, digital growth accelerates the energy transition and structurally increases abatement efficiency. Heterogeneity analysis shows a more pronounced inverted-U in central and western provinces, while eastern provinces have largely entered a sustained cost-decline phase. By lowering the social cost of achieving emissions targets, the digital economy directly supports sustainable development and China’s green, low-carbon transition. Full article

In the context of global efforts toward energy conservation and emission reduction, accurate short-term electric load forecasting plays a crucial role in improving energy efficiency, enabling low-carbon dispatching, and supporting sustainable power system operations. To address the growing demand for accuracy and stability in this domain, this paper proposes a novel prediction model tailored for power systems. The proposed method combines Spearman correlation analysis with modal decomposition techniques to compress redundant features while preserving key information, resulting in more informative and cleaner input representations. In terms of model architecture, this study integrates Bidirectional Gated Recurrent Units (BiGRUs) with dilated convolution. This design improves the model’s capacity to capture long-range dependencies and complex relationships. For parameter optimization, an Improved Beluga Whale Optimization (IBWO) algorithm is introduced, incorporating dynamic population initialization, adaptive Lévy flight mechanisms, and refined convergence procedures to enhance search efficiency and robustness. Experiments on real-world datasets demonstrate that the proposed model achieves excellent forecasting performance (RMSE = 26.1706, MAE = 18.5462, R² = 0.9812), combining high predictive accuracy with strong generalization. These advancements contribute to more efficient energy scheduling and reduced environmental impact, making the model well-suited for intelligent and sustainable load forecasting applications in environmentally conscious power systems. Full article

The study presents original research focused on improving the reliability and energy efficiency of electric railway turnout heating systems under severe winter conditions. An innovative diagnostic methodology using high-resolution infrared thermography was developed and applied to evaluate heating uniformity and technical performance within the Polish railway infrastructure. Field investigations were carried out on operational turnouts at Gdańsk Osowa and Międzylesie stations, covering both conventional EOR systems and the advanced ESAR system. The results demonstrated that the ESAR system effectively prevented ice and snow accumulation while enabling up to a 30% reduction in active power supplied to heating elements, resulting in annual energy savings of approximately 750 kWh per turnout (29% compared with the reference system). Incorporating radiative overlays in ESAR allowed lower average surface temperatures and improved heat distribution efficiency. Temperature and energy indicators confirmed significantly higher performance of ESAR, with annual CO₂ emissions reduced by 447.75 kg and air pollutants (SO_x, NO_x, CO, particulates) by around 30%. The proposed thermographic approach proved to be a non-invasive and efficient diagnostic tool, supporting adaptive control, enhanced operational reliability, and reduced environmental impact of turnout heating systems. Full article

The aim of this study was to empirically examine the effects of China’s Transit Metropolis Construction Pilot (TMCP) policy on pollution and carbon dioxide emission reductions based on annual panel data from 286 prefecture-level cities in China for the period 2011–2019, using a staggered difference-in-differences approach. The results show that the TMCP policy significantly reduced the annual total carbon monoxide and carbon dioxide emissions in pilot cities by approximately 1.624 million and 221.883 million tons, respectively. Further mechanism analysis demonstrated that the TMCP policy reduced pollution and carbon dioxide emissions by improving the operational efficiency of public transit, alleviating urban traffic congestion, and enhancing public environmental awareness. Finally, our heterogeneity analysis indicates that the pollution and carbon dioxide emission reduction effects of the TMCP policy were more pronounced in cities with poor public transit accessibility and low environmental regulation intensity. This study provides policymakers with valuable policy insights into effectively promoting public transit use, reducing urban air pollutants and carbon dioxide emissions, and developing a sustainable urban transportation system. Full article

Background: Reducing agricultural carbon emissions can enhance agricultural resilience and promote sustainable agricultural development. Although prior research has examined how agricultural new-quality productive forces (ANQP) reshape factor allocation, technology adoption, and production efficiency, their implications for agricultural carbon emissions remain insufficiently studied. Objective: To quantify the impact of ANQP on agricultural carbon emissions, assess regional heterogeneity across the east, central, and west, between grain and non-grain areas, between the Yangtze River Economic Belt and other regions, and across different levels of fiscal support, and to identify an efficiency-based transmission mechanism. Materials and Methods: A panel of 30 Chinese provinces for 2012–2022 is analyzed using province and year fixed effects. Results: ANPQ significantly reduce agricultural carbon emissions. The effect is stronger in western provinces, in non-grain areas, within the Yangtze River Economic Belt, and where fiscal support is higher, and weaker in eastern and low-support regions. Trade-offs between yield stabilization and emission reduction emerge in the central region and in major grain-producing areas. Mechanism results indicate that ANQP lowers emissions primarily by improving agricultural production efficiency measured by total factor productivity. Full article

In response to the imperative to mitigate methane—one of the most potent greenhouse gases—this study proposes and tests an integrated workflow for designing methane drainage boreholes targeting post-mining areas in an active underground coal mine (Pniówek, Poland). The workflow combines the following: (1) forecasting methane emissions from goafs and active longwalls for 2024–2040; (2) 3D geological characterization (structural and lithofacies models); (3) selection and sealing of goaf zones; and (4) optimization of well placement, drilling, and performance evaluation of drainage boreholes, including an assessment of energy use from the recovered gas. Applying the method delineated priority capture zones and estimated recoverable rates under multiple scenarios. Preliminary field data from a borehole near seam 362/1 indicate stable methane inflow to the drainage system and a concomitant reduction in methane load within the ventilation network. The integrated design improves targeting efficiency and provides a quantitative basis for scheduling, risk management, and sizing of surface-to-underground infrastructure. The results suggest that systematic drainage of post-mining voids can enhance safety, limit fugitive emissions, and create opportunities for on-site power generation. The approach is transferable to other active mines with legacy workings, provided site-specific calibration and monitoring are implemented. Full article