Search Results (13,419)

Using waste biomass as a raw material for the combined production of electricity and heat offers corresponding energy, economic, environmental and resource efficiency benefits. The study examines both the performance of a system for combined energy production based on the Organic Rankine Cycle (ORC) utilizing wood biomass and the market interest in its deployment within Bulgaria. Its objective is to propose a technically and economically viable solution for the recovery of waste biomass through the combined production of electricity and heat while simultaneously assessing the readiness of industrial and municipal sectors to adopt such systems. The cogeneration plant incorporates an ORC module enhanced with three additional economizers that capture residual heat from flue gases. Operating on 2 t/h of biomass, the system delivers 1156 kW of electric power and 3660 kW of thermal energy, recovering an additional 2664 kW of heat. The overall energy efficiency reaches 85%, with projected annual revenues exceeding EUR 600,000 and a reduction in carbon dioxide emissions of over 5800 t/yr. These indicators can be achieved through optimal installation and operation. When operating at a reduced load, however, the specific fuel consumption increases and the overall efficiency of the installation decreases. The marketing survey results indicate that 75% of respondents express interest in adopting such technologies, contingent upon the availability of financial incentives. The strongest demand is observed for systems with capacities up to 1000 kW. However, significant barriers remain, including high initial investment costs and uneven access to raw materials. The findings confirm that the developed system offers a technologically robust, environmentally efficient and market-relevant solution, aligned with the goals of energy independence, sustainability and the transition to a low-carbon economy. Full article

Amid China’s national strategic prioritization of the Chengdu–Chongqing Economic Circle and accelerated territorial spatial planning, this study deciphered the synergistic evolution of Land Use Intensity (LUI) and Balance Degree of Land Use Structure (BDLUS) during rapid urbanization. Leveraging 1 km grid units and integrating emerging spatiotemporal hotspot analysis, BFAST, and geographic detectors, we systematically analyzed spatiotemporal patterns and drivers of LUI, BDLUS, and their Coupling Coordination Degree (CCD) from 2000 to 2022. Key findings: (1) LUI strongly correlated with economic growth, with core areas reaching high-intensity development (average > 2.96) versus ecologically constrained marginal zones (<2.42), marked by abrupt changes during 2011–2014; (2) BDLUS improvements covered 82.22% of the study area, driven by the Yangtze River Economic Belt strategy (21.96% hotspot concentration), yet structural imbalance persisted in transitional zones (18.81% cold spots); (3) CCD exhibited center-edge dichotomy, contrasting high-value cores (CCD > 0.68) with ecologically sensitive edges (9.80% cold spots), peaking in regulatory shifts around 2010; (4) terrain constraints and intensified human activities (the interaction effect between nighttime lighting and population density increased by 219.49% after 2020) jointly governed coupling mechanisms, with urbanization and industrial transition becoming dominant drivers. This research advances an “intensity–structure–coordination” framework and elucidates “dual-core resonance” dynamics, offering theoretical foundations for spatial optimization and ecological civilization. Full article

The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders. However, because of divergent interests and risk perceptions among governments, energy service companies (ESCOs), and owners, the implementation of green renovation is hindered by numerous obstacles. In this study, we integrated prospect theory and evolutionary game theory by incorporating core prospect-theory parameters such as loss aversion and perceived value sensitivity, and developed a psychologically informed tripartite evolutionary game model. The objective was to provide a theoretical foundation and analytical framework for collaborative governance among stakeholders. Numerical simulations were conducted to validate the model’s effectiveness and explore how government regulation intensity, subsidy policies, market competition, and individual psychological factors influence the system’s evolutionary dynamics. The findings indicate that (1) government regulation and subsidy policies play central guiding roles in the early stages of green renovation, but the effectiveness has clear limitations; (2) ESCOs are most sensitive to policy incentives and market competition, and moderately increasing their risk costs can effectively deter opportunistic behavior associated with low-quality renovation; (3) owners’ willingness to participate is primarily influenced by expected returns and perceived renovation risks, while economic incentives alone have limited impact; and (4) the evolutionary outcomes are highly sensitive to parameters from prospect theory, The system’s evolutionary outcomes are highly sensitive to prospect theory parameters. High levels of loss aversion (λ) and loss sensitivity (β) tend to drive the system into a suboptimal equilibrium characterized by insufficient demand, while high gain sensitivity (α) serves as a key driving force for the system’s evolution toward the ideal equilibrium. This study offers theoretical support for optimizing green renovation policies for existing residential buildings in China and provides practical recommendations for improving market competition mechanisms, thereby promoting the healthy development of the green renovation market. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

Understanding the utilization patterns of nuclear medicine (NM) services is essential for optimizing resource allocation and service provision. This study aimed to address the regional evidence gap by reporting the demand for NM services by sex and age at a public hospital in Jamaica. This was a non-experimental, retrospective study of NM scans that were completed at the University Hospital of the West Indies from 1 June 2022 to 31 May 2024. While all scans were reported in the descriptive totals, for patients with multiple scans during the study period, only the data from the first visit was used in the inferential statistical analysis. This was performed with the IBM SPSS (version 29.0) software and involved the use of chi-square goodness of fit and multinomial logistic regression. A total of 1135 NM scans for 1098 patients were completed (37 patients had more than one scan); 596 (54.3%) were female and 502 (45.7%) were male, with the ages ranging from 3 days to 94 years old. Among the female patients, there was a greater demand in the ≥60 years age group for cardiac amyloid scans (χ² = 6.40, p < 0.05), while females 18–59 years had a greater demand for thyroid scans (χ² = 7.714, p < 0.05) and bone scans (χ² = 3.904, p < 0.05). On the other hand, significantly more males in the ≥60 age group presented for cardiac amyloid (χ² = 4.167; p < 0.05) and bone scans (χ² = 145.79, p < 0.01). Males were significantly less likely to undergo a thyroid scan than females (p < 0.01, OR = 0.072, 95% CI: 0.021, 0.243) while individuals aged 18–59 years were more likely to undergo this scan than patients aged 60 or older (p = 0.02, OR = 3.565, 95% CI: 1.258, 10.104). Males were more likely to do a cardiac amyloid scan (p < 0.05, OR = 2.237, 95% CI: 1.023, 4.891) but less likely to undergo a cardiac rest/stress test than females (p = 0.02, OR = 0.307, 95% CI: 0.114, 0.828). Prolonged life expectancy and an aging population have the potential to impact NM utilization, thus requiring planning for infrastructure, equipment, work force, and supplies. Cancer-related and cardiovascular indications are a top priority at this facility; hence, age- and sex-specific analysis are useful in establishing models for policy makers with regard to the allocation of economic and human resources for the sustainability of this specialized service. Full article

Hericium coralloides is a highly valued gourmet and medicinal species with growing market demand across East Asia, though industrial production remains limited by cultivation challenges. This study investigated the molecular characteristics, biological traits, domestication potential, and cultivation protocols of Hericium coralloides strains collected from the Changbaishan Nature Reserve (Jiling, China). Optimal conditions for mycelial growth included mannose as the preferred carbon source, peptone as the nitrogen source, 30 °C incubation temperature, pH 5.5, and magnesium sulfate as the essential inorganic salt. The fruiting bodies had a protein content of 2.43% g/100 g (fresh sample meter). Total amino acids comprised 53.3% of the total amino acid profile, while essential amino acids accounted for 114.11% relative to non-essential amino acids, indicating high nutritional value. Under optimized domestication conditions—70% hardwood chips, 20% cottonseed hulls, 8% bran, 1% malic acid, and 1% gypsum—bags reached full colonization in 28 days, with a 15-day maturation phase and initial fruiting occurring after 12–14 days. The interval between flushes was 10–12 days. The average yield reached 318.65 ± 31.74 g per bag, with a biological conversion rate of 63.73%. These findings demonstrate that Hericium coralloides possesses significant potential for edible and commercial applications. This study provides a robust theoretical foundation and resource reference for its artificial cultivation, supporting its broader industrial and economic utilization. Full article

Ujimqin sheep, known for its distinctive multi-vertebrae phenotypes (T13L7, T14L6, and T14L7) and economic value, has garnered significant attention. However, conventional phenotypic detection methods suffer from low efficiency and high costs. In this study, based on a key SNP locus (ABCD4 gene, Chr7:89393414, C > T) identified through a genome-wide association study (GWAS), a TaqMan-MGB (minor groove binder) genotyping system was developed. the objective was to establish a high-throughput and efficient molecular marker-assisted selection (MAS) tool. Specific primers and dual fluorescent probes were designed to optimize the reaction system. Standard plasmids were adopted to validate genotyping accuracy. A total of 152 Ujimqin sheep were subjected to TaqMan-MGB genotyping, digital radiography (DR) imaging, and Sanger sequencing. the results showed complete concordance between TaqMan-MGB and Sanger sequencing, with an overall agreement rate of 83.6% with DR imaging. For individuals with T/T genotypes (127/139), the detection accuracy reached 91.4%. This method demonstrated high specificity, simplicity, and cost-efficiency, significantly reducing the time and financial burden associated with traditional imaging-based approaches. the findings indicate that the TaqMan-MGB technique can accurately identify the T/T genotype at the SNP site and its strong association with the multi-vertebrae phenotypes, offering an effective and reliable tool for molecular breeding of Ujimqin sheep. Full article

To fully accommodate renewable and derivative energy sources in mine energy systems under supply and demand uncertainties, this paper proposes an optimized electricity–heat scheduling method for mining areas that incorporates Power-to-Gas (P2G) technology and Conditional Value-at-Risk (CVaR). First, to address uncertainties on both the supply and demand sides, a P2G unit is introduced, and a Latin hypercube sampling technique based on Cholesky decomposition is employed to generate wind–solar-load sample matrices that capture source–load correlations, which are subsequently used to construct representative scenarios. Second, a stochastic optimization scheduling model is developed for the mine electricity–heat energy system, aiming to minimize the total scheduling cost comprising day-ahead scheduling cost, expected reserve adjustment cost, and CVaR. Finally, a case study on a typical mine electricity–heat energy system is conducted to validate the effectiveness of the proposed method in terms of operational cost reduction and system reliability. The results demonstrate a 1.4% reduction in the total operating cost, achieving a balance between economic efficiency and system security. 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

Industrial catalysts are accelerating the global transition toward renewable energy, serving as enablers for innovative technologies that enhance efficiency, lower costs, and improve environmental sustainability. This review explores the pivotal roles of industrial catalysts in hydrogen production, biofuel generation, and biomass conversion, highlighting their transformative impact on renewable energy systems. Precious-metal-based electrocatalysts such as ruthenium (Ru), iridium (Ir), and platinum (Pt) demonstrate high efficiency but face challenges due to their cost and stability. Alternatives like nickel-cobalt oxide (NiCo₂O₄) and Ti₃C₂ MXene materials show promise in addressing these limitations, enabling cost-effective and scalable hydrogen production. Additionally, nickel-based catalysts supported on alumina optimize SMR, reducing coke formation and improving efficiency. In biofuel production, heterogeneous catalysts play a crucial role in converting biomass into valuable fuels. Co-based bimetallic catalysts enhance hydrodeoxygenation (HDO) processes, improving the yield of biofuels like dimethylfuran (DMF) and γ-valerolactone (GVL). Innovative materials such as biochar, red mud, and metal–organic frameworks (MOFs) facilitate sustainable waste-to-fuel conversion and biodiesel production, offering environmental and economic benefits. Power-to-X technologies, which convert renewable electricity into chemical energy carriers like hydrogen and synthetic fuels, rely on advanced catalysts to improve reaction rates, selectivity, and energy efficiency. Innovations in non-precious metal catalysts, nanostructured materials, and defect-engineered catalysts provide solutions for sustainable energy systems. These advancements promise to enhance efficiency, reduce environmental footprints, and ensure the viability of renewable energy technologies. Full article

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

To address the limited flexibility of pumped storage power stations (PSPSs) under hierarchical clearing of energy and ancillary service markets, this study proposes a joint clearing mechanism for multi-level electricity markets. A bi-level optimization model based on the Stackelberg game is developed to characterize the strategic interaction between PSPSs and the market operator. Simulation results on the IEEE 30-bus system demonstrate that the proposed mechanism captures the dynamics of nodal supply and demand, as well as time-varying network congestion. It guides PSPSs to operate more flexibly and economically. Additionally, the mechanism increases PSPS profitability, reduces system costs, and improves frequency regulation performance. This game-theoretic framework offers quantitative decision support for PSPS participation in multi-level spot markets and provides insights for optimal storage deployment and market mechanism improvement. Full article

The present study examines the barriers that prevent cooling system flexibility from being optimized. In the context of an increasing reliance on renewable energy sources, the necessity for flexible energy utilization is becoming increasingly apparent. A survey and discussion groups were conducted with various stakeholders within the cooling value chain to obtain their experiences and insights regarding barriers to flexibilization. The findings point out that economic, technological, and regulatory barriers are the primary factors impeding the implementation of flexible solutions. In particular, high investment costs, complex technical implementation, a lack of information, and a complicated legal framework were identified as significant impediments. To enhance the flexibility of cooling systems, coordinated efforts are necessary to address these barriers. Practical examples, training, and the standardization and digitalization of processes could facilitate the widespread implementation of flexible cooling systems. Full article

Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a focus on the operational setting of the train crew depot in Česká Třebová, a city in the Czech Republic. The seven-step methodology includes identifying available train shifts, defining scheduling constraints, creating roster variants, and calculating personnel and time requirements for each option. The proposed roster reduced staffing needs by two employees, increased the average shift duration to 9 h and 42 min, and decreased non-productive time by 384 h annually. These improvements enhance sustainability by optimizing human resource use, lowering unnecessary energy consumption, and improving employees’ work–life balance. The model also provides a quantitative assessment of operational feasibility and economic efficiency. Compared to existing rosters, the proposed model offers clear advantages and remains applicable even in settings with limited technological support. The findings show that a well-designed rostering system can contribute not only to cost savings and personnel stabilization, but also to broader objectives in sustainable public transport, supporting resilient and resource-efficient rail operations. Full article

Strengthening climate resilience constitutes a foundational approach through which cities adapt to climate change and mitigate associated environmental risks. However, research on the influence of economic policy environments on climate resilience remains limited. Guided by institutional theory and dynamic capability theory, this study employs a panel dataset comprising 272 Chinese cities at the prefecture level and above, covering the period from 2009 to 2023. It constructs a composite index framework for evaluating the green business environment (GBE) and urban climate resilience (UCR) using the entropy weight method. Employing a two-way fixed-effect regression model, it examined the impact of GBE optimization on UCR empirically and also explored the underlying mechanisms. The results show that improvements in the GBE significantly enhance UCR, with green innovation (GI) in technology functioning as an intermediary mechanism within this relationship. Moreover, climate policy uncertainty (CPU) exerts a moderating effect along this transmission pathway: on the one hand, it amplifies the beneficial effect of the GBE on GI; on the other hand, it hampers the transformation of GI into improved GBEs. The former effect dominates, indicating that optimizing the GBE becomes particularly critical for enhancing UCR under high CPU. To eliminate potential endogenous issues, this paper adopts a two-stage regression model based on the instrumental variable method (2SLS). The above conclusion still holds after undergoing a series of robustness tests. This study reveals the mechanism by which a GBE enhances its growth through GI. By incorporating CPU as a heterogeneous factor, the findings suggest that governments should balance policy incentives with environmental regulations in climate resilience governance. Furthermore, maintaining awareness of the risks stemming from climate policy volatility is of critical importance. By providing a stable and supportive institutional environment, governments can foster steady progress in green innovation and comprehensively improve urban adaptive capacity to climate change. Full article