Search Results (585)

As global demand for rare earth elements (REEs) increases, maintaining the production and supply chain is critical. Technologies capable of being used in the field and in situ in the subsurface for rapid REE detection and quantification facilitates the efficient mining of known resources and exploration of new and unconventional resources. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for rapid elemental analysis both in the laboratory and in the field. Multiple articles have been published evaluating LIBS for detection and quantification of REEs; however, REEs in their natural deposits have not been adequately studied. In this work, detection and quantification of two REEs, La and Nd, have been studied in both synthetic and natural mineral matrices at concentrations relevant to REE extraction. Measurements were performed on REE-containing rock and coal samples (natural and synthetic) utilizing different LIBS instruments and techniques, specifically a commercial benchtop instrument, a custom benchtop instrument (single- and double-pulse modes), and a custom LIBS probe currently being developed for in situ, subsurface, borehole wall detection and quantification of REEs. Plasma expansion, emission intensity, detection limits, and double-pulse signal enhancement were studied. The limits of detection (LOD) were found to be 10/14 ppm for La and 15/25 ppm for Nd in simulated coal/rock matrices in single-pulse mode. Signal enhancement of 3.5 to 6-fold was obtained with double-pulse mode as compared to single-pulse operation. Full article

This study investigates the short- and long-run drivers of natural gas consumption in the European Union using an ARDL bounds testing approach. The analysis incorporates GDP per capita, liquid fuel use, and solid fuel use as explanatory variables. Augmented Dickey–Fuller tests confirm mixed integration orders, allowing valid ARDL estimation. The results reveal a statistically significant long-run relationship (cointegration) between gas consumption and the energy–economic system. In the short run, the use of liquid fuel exerts a strong positive influence on gas demand, while the effects of GDP materialise only after a two-year lag. Solid fuels show a delayed substitutive impact, reflecting the ongoing transition from coal. An error correction model confirms rapid convergence to equilibrium, with 77% of deviations corrected within one period. Recursive residual and CUSUM tests indicate structural stability over time. These findings highlight the responsiveness of EU gas demand to both economic and policy signals, offering valuable insights for energy modelling and strategic planning under the European Green Deal. Full article

This study combines convolutional neural network (CNN) recognition technology, Greenwich engineering software, and statistical yearbook methods to evaluate rural solar, wind, and biomass energy resources in pilot cities in China, respectively. The CNN method enables the rapid identification of the available roof area, and Greenwich software provides wind resource simulation with local terrain adaptability. The results show that the capacity of photovoltaic power generation reaches approximately 15.63 GW, the potential of wind power is 458.3 MW, and the equivalent of agricultural waste is 433,900 tons of standard coal. The city is rich in wind, solar, and biomass resources. By optimizing the hybrid power generation system through genetic algorithms, wind energy, solar energy, biomass energy, and coal power are combined to balance the annual electricity demand in rural areas. The energy trends under different demand growth rates were predicted through the LEAP model, revealing that in the clean coal scenario of carbon capture (WSBC-CCS), clean coal power and renewable energy will dominate by 2030. Carbon dioxide emissions will peak in 2024 and return to the 2020 level between 2028 and 2029. Under the scenario of pure renewable energy (H_WSB), SO₂/NO_x will be reduced by 23–25%, and carbon dioxide emissions will approach zero. This study evaluates the renewable energy potential, power system capacity optimization, and carbon emission characteristics of pilot cities at a macro scale. Future work should further analyze the impact mechanisms of data sensitivity on these assessment results. Full article

In the context of the intensifying global climate crisis, the power industry, as a significant carbon emitter, urgently needs to promote low-carbon transformation using market mechanisms. In this paper, a multi-objective stochastic optimization scheduling framework for regional power grids integrating carbon trading (CET) and green certificate trading (GCT) is proposed to coordinate the conflict between economic benefits and environmental objectives. By building a deterministic optimization model, the goal of maximizing power generation profit and minimizing carbon emissions is combined in a weighted form, and the power balance, carbon quota constraint, and the proportion of renewable energy are introduced. To deal with the uncertainty of power demand, carbon baseline, and the green certificate ratio, Monte Carlo simulation was further used to generate random parameter scenarios, and the CPLEX solver was used to optimize scheduling schemes iteratively. The simulation results show that when the proportion of green certificates increases from 0.35 to 0.45, the proportion of renewable energy generation increases by 4%, the output of coal power decreases by 12–15%, and the carbon emission decreases by 3–4.5%. At the same time, the tightening of carbon quotas (coefficient increased from 0.78 to 0.84) promoted the output of gas units to increase by 70 MWh, verifying the synergistic emission reduction effect of the “total control + market incentive” policy. Economic–environmental tradeoff analysis shows that high-cost inputs are positively correlated with the proportion of renewable energy, and carbon emissions are significantly negatively correlated with the proportion of green certificates (correlation coefficient −0.79). This study emphasizes that dynamic adjustments of carbon quota and green certificate targets can avoid diminishing marginal emission reduction efficiency, while the independent carbon price mechanism needs to enhance its linkage with economic targets through policy design. This framework provides theoretical support and a practical path for decision-makers to design a flexible market mechanism and build a multi-energy complementary system of “coal power base load protection, gas peak regulation, and renewable energy supplement”. Full article

The convergence of intelligent computational innovations—exemplified by cognitive intelligence—into the real economy is fundamentally transforming traditional industries and driving high-quality development. As a cornerstone of national economic growth, the energy sector faces mounting pressure to meet demands for green, low-carbon, and sustainable development, particularly under “dual carbon” targets and tightening regulatory frameworks. This study examines how digital transformation in this sector facilitates or impedes carbon emission reduction and green growth. Focusing on five key energy subsectors, including coal mining and processing, a coupling coordination model assesses the interaction between digitalization and greening. Utilizing panel data spanning from 2014 to 2023, the study systematically evaluates the level of digital–green coordination across the sector. The results indicate notable inter-sectoral variation, alongside a consistent upward trend in the overall coupling coordination, reaching moderate to high levels. These findings offer critical strategic insights for policymakers and energy enterprises seeking to harmonize digital innovation with green transition goals. The empirical evidence underscores the potential of next-generation technologies to expedite intelligent system upgrades, embed green development practices, and enhance enterprise-level carbon reduction and sustainability performance. Full article

This article presents a simplified method for forecasting Poland’s long-term peak electricity demand using a modified Prigogine logistic equation. While complex models like the WEM or PRIMES offer high precision, their complexity and data requirements can be limiting. The proposed model offers a quicker and more accessible alternative, using the average annual load factor ($ALF$) as a key indicator. Based on historical data (1985–2024), the model was validated and optimized (MAPE < 2%), then applied to forecast the demand through 2040 under three scenarios: coal-based energy, nuclear energy and energy from RESs (renewables). Depending on the scenario, the peak demand is expected to rise from 28.7 GW in 2024 to 34–40 GW in 2040. The model’s strength lies in its ability to capture dynamic system behavior, including chaos and bifurcations, making it suitable for rapid assessments and strategic planning. Despite its limitations—such as a lower level of detail and an inability to integrate sectoral policies—the Prigogine-based approach offers a transparent, cost-effective forecasting tool, especially when complemented by the use of advanced simulation models. Full article

Driven by the global energy transition and the pursuit of “dual carbon” goals, sustainability risks within the coal supply chain have emerged as a central obstacle impeding the low-carbon transformation of high-carbon industries. To address the critical gap in systematic and multidimensional risk assessments for coal supply chains, this study proposes a hybrid framework that integrates the analytic hierarchy process (AHP) with the fuzzy comprehensive evaluation (FCE) method. Utilizing the Delphi method and the coefficient of variation technique, this study develops a risk assessment system encompassing eight primary criteria and forty sub-criteria. These indicators cover economic, operational safety, ecological and environmental, management policy, demand, sustainable supply, information technology, and social risks. An empirical analysis is conducted, using a prominent Chinese coal enterprise as a case study. The findings demonstrate that the overall risk level of the enterprise is “moderate”, with demand risk, information technology risk, and social risk ranking as the top three concerns. This underscores the substantial impact of accelerated energy substitution, digital system vulnerabilities, and stakeholder conflicts on supply chain resilience. Further analysis elucidates the transmission mechanisms of critical risk nodes, including financing constraints, equipment modernization delays, and deficiencies in end-of-pipe governance. Targeted strategies are proposed, such as constructing a diversified financing matrix, developing a blockchain-based data-sharing platform, and establishing a community co-governance mechanism. These measures offer scientific decision-making support for the coal industry’s efforts to balance “ensuring supply” with “reducing carbon emissions”, and provide a replicable risk assessment paradigm for the sustainable transformation of global high-carbon supply chains. Full article

The high-hydrolysis reactivity cement clinker powder in cement plays a major role in cement’s cementation, while low-hydrolysis reactivity mineral admixture powders, such as slag, m mainly serve as a filler. Through optimizing the particle matching of cement clinker powder and slag powder, the mechanical properties of cement can be enhanced. In this study, clinker and slag with differing levels of fineness were obtained by separate grinding, and the particle gradation of clinker powder and slag powder in the cement was optimized. Fine clinker particles were mixed with coarse slag particles to systematically explore their effects on the rheology of cement paste, the formation of hydration products, the evolution of the pore structure, and the material’s mechanical properties. Through experimental tests and microscopic analysis, the mechanism whereby particle gradation is regulated by separate grinding was revealed. The findings of the study are as follows: with the same amount of cinder, finer clinker requires a higher water content of standard consistency. The addition of coarse cinder effectively reduces the standard-consistency water requirement of the blended cement. Fine grinding of coal cinder fails to enhance cement strength effectively but markedly raises the standard-consistency water demand. Thus, the specific surface area of coal cinder should be maintained at approximately 210 m²/kg. Full article

To achieve carbon neutrality targets in the power sector, regions with rich coal and renewable energy resources are facing unprecedented pressure. This paper explores the decarbonization pathway in the power sector in Inner Mongolia, China, under different energy transition scenarios based on the Long-Range Energy Alternatives Planning System (LEAP) model. This includes renewable energy expansion, carbon capture and storage (CCS) applications, demand response, and economic regulation scenarios. Subsequently, a combination of the Logarithmic Mean Divisia Index (LMDI) and Slack-Based Measure Data Envelopment Analysis (SBM-DEA) model was developed to investigate the influencing factors and power generation efficiency in low-carbon electricity. The results revealed that this region emphasizes first developing renewable energy and improving the carbon and green electricity market and then accelerating CCS technology. Its carbon emissions are among the lowest, at about 77.29 million tons, but the cost could reach CNY 229.8 billion in 2060. We also found that the influencing factors of carbon productivity, low-carbon electricity structures, and carbon emissions significantly affected low-carbon electricity generation; their cumulative contribution rate is 367–588%, 155–399%, and −189–−737%, respectively. Regarding low-carbon electricity efficiency, the demand response scenario is the lowest at about 0.71; other scenarios show similar efficiency values. This value could be improved by optimizing the energy consumption structure and the installed capacity configuration. Full article

The chemical industry faces major challenges worldwide. Since 1950, production has increased 50-fold and is projected to continue growing, particularly in Asia. It is one of the most energy- and resource-intensive industries, contributing significantly to greenhouse gas emissions and the depletion of finite resources. This development exceeds planetary boundaries and calls for a sustainable transformation of the industry. The key transformation areas are as follows: (1) Non-Fossil Energy Supply: The industry must transition away from fossil fuels. Renewable electricity can replace natural gas, while green hydrogen can be used for high-temperature processes. (2) Circularity: Chemical production remains largely linear, with most products ending up as waste. Sustainable product design and improved recycling processes are crucial. (3) Non-Fossil Feedstock: To achieve greenhouse gas neutrality, oil, gas, and coal must be replaced by recycling plastics, renewable biomaterials, or CO₂-based processes. (4) Sustainable Chemical Production: Energy and resource savings can be achieved through advancements like catalysis, biotechnology, microreactors, and new separation techniques. (5) Sustainable Chemical Products: Chemicals should be designed to be “Safe and Sustainable by Design” (SSbD), meaning they should not have hazardous properties unless essential to their function. (6) Sufficiency: Beyond efficiency and circularity, reducing overall material flows is essential to stay within planetary boundaries. This shift requires political, economic, and societal efforts. Achieving greenhouse gas neutrality in Europe by 2050 demands swift and decisive action from industry, governments, and society. The speed of transformation is currently too slow to reach this goal. Science can drive innovation, but international agreements are necessary to establish a binding framework for action. Full article

In practical coal preparation processes, influenced by mining methods and mechanization levels, the proportion of fine and even ultrafine pulverized coal continues to increase. However, due to the small particle size, significant inter-particle interactions, and the low efficiency of conventional physical separation techniques, the efficient deashing of fine coal remains a significant technical challenge. Consequently, in the face of growing demand for fine coal processing, efficient and mature dry separation technologies are still lacking. To address this issue, a pulsating circulating airflow separation device was designed and developed in this study to deash and desulfurize pulverized coal with a particle size of less than 1 mm. The effects of gas velocity and pulsating airflow frequency on the deashing performance were investigated. Using Design-Expert software (version 13), an optimized formula for deashing efficiency was established, and the optimal operating parameters were evaluated. The separation results demonstrated that under the optimal conditions of fluidization, the number N = 1.2 and pulsating airflow frequency f = 2.375 Hz, the standard deviation of ash segregation (σ_ash) reached 25%, and the ash content in the cleaned coal was reduced from 37.28% to 22.32% in the cleaned sample. Furthermore, the sulfur content decreased significantly from 0.971% in the raw coal to 0.617% in the cleaned coal, indicating effective desulfurization. In addition, the concentrations of other harmful elements in the raw coal were also reduced to varying degrees. These findings demonstrate that the application of pulsating airflow can effectively enhance ash and sulfur removal from pulverized coal particles smaller than 1 mm. This approach offers a novel and promising method for the dry beneficiation of fine coal particles. Full article

To achieve low-carbon economic dispatch and collaborative optimization of carbon capture efficiency in power systems, this paper proposes a flexible carbon capture power plant and generalized energy storage collaborative operation model under a dynamic carbon quota mechanism. First, adjustable carbon capture devices are integrated into high-emission thermal power units to construct carbon–electricity coupled operation modules, enabling a dynamic reduction of carbon emission intensity and enhancing low-carbon performance. Second, a time-varying carbon quota allocation mechanism and a dynamic correction model for carbon emission factors are designed to improve the regulation capability of carbon capture units during peak demand periods. Furthermore, pumped storage systems and price-guided demand response are integrated to form a generalized energy storage system, establishing a “source–load–storage” coordinated peak-shaving framework that alleviates the regulation burden on carbon capture units. Finally, a multi-timescale optimization scheduling model is developed and solved using the GUROBI algorithm to ensure the economic efficiency and operational synergy of system resources. Simulation results demonstrate that, compared with the traditional static quota mode, the proposed dynamic carbon quota mechanism reduces wind curtailment cost by 9.6%, the loss of load cost by 48.8%, and carbon emission cost by 15%. Moreover, the inclusion of generalized energy storage—including pumped storage and demand response—further decreases coal consumption cost by 9% and carbon emission cost by 17%, validating the effectiveness of the proposed approach in achieving both economic and environmental benefits. Full article

Underground coal mines face increasing challenges in the scheduling of Electric Rubber-Tired Vehicles (ERTVs) due to confined spaces, dynamic production demands, and the need to coordinate multiple constraints such as complex roadway topologies, strict time windows, and limited charging resources in the context of clean energy transitions. This study presents a Constraint Programming (CP)-based optimization framework that integrates Virtual Charging Station Mapping (VCSM) and sensor fusion positioning to decouple spatiotemporal charging conflicts and applies a dynamic topology adjustment algorithm to enhance computational efficiency. A novel RFID–vision fusion positioning system, leveraging multi-source data to mitigate signal interference in underground environments, provides real-time, reliable spatiotemporal coordinates for the scheduling model. The proposed multi-objective model systematically incorporates hard time windows, load limits, battery endurance, and roadway regulations. Case studies conducted using real-world data from a large-scale Chinese coal mine demonstrate that the method achieves a 17.6% reduction in total transportation mileage, decreases charging events by 60%, and reduces vehicle usage by approximately 33%, all while completely eliminating time window violations. Furthermore, the computational efficiency is improved by 54.4% compared to Mixed-Integer Linear Programming (MILP). By balancing economic and operational objectives, this approach provides a robust and scalable solution for sustainable ERTV scheduling in confined underground environments, with broader applicability to industrial logistics and clean mining practices. Full article

To further quantify the role of coal-fired power units in a wind–solar–thermal storage system and improve the construction of clean energy bases, this study examined the temporal production characteristics of wind and solar power and established an operational model for coal-fired power units within a wind–solar–thermal storage system. This approach ensured a stable electricity supply on the basis of power balance. The findings indicate that the correlation between the installed capacity of coal-fired power and the daily power supply capability of energy storage that meets various scheduled power demands can be obtained via the model. As the proportion of wind and solar power in the output power decreases, the influence of the minimum operational load of the coal-fired power units on the curtailment rate intensifies. Notably, the operational cost savings from reducing this minimum operational load surpass those obtained by either downsizing the installed capacity of coal-fired power units or energy storage devices. Among the parameters of this study, the lowest operational cost for the system was observed when wind and solar power generation constituted 76% of the total. This scenario, which ensured stable power output for 95% of the days in a year, had a wind and solar power curtailment rate of 11.3%. Additionally, the energy supplied by storage devices amounted to 1000 MWh, with the ratio of the installed capacity of coal-fired power to the total installed capacities of wind and solar power remaining at 25%. When the ratio of wind and solar power generation to output power was 91%, 76%, and 58%, a 1% reduction in coal consumption by coal-fired units during low-load operation resulted in a decrease in total system operating costs of 0.012%, 0.093%, and 0.089%, respectively. These findings provide valuable data support for the development of clean energy infrastructures. Full article

The dip angle and thickness of coal seams are key geological determinants in mine system engineering. Roadways excavated in steeply inclined or thick coal seams typically exhibit significant deformation, with the combined geological configuration of steeply inclined thick seams thus presenting heightened support demands. Therefore, taking the 1502 level roadway in the Dayuan Coal Industry—situated in a steeply inclined thick coal seam—as an engineering case, mechanical models of roadways with different cross-sectional shapes are established, and the deformation and failure mechanisms of surrounding rock under different coal seam dip angles are analyzed. Based on this analysis, an asymmetric support technology scheme is proposed, followed by surrounding rock deformation monitoring and a support effectiveness evaluation. Key findings include the following: (1) in steeply inclined thick coal seam roadways with different cross-sectional shapes, the stress distribution and plastic zone development of surrounding rock follow a descending sequence, inclined roof trapezoidal section > rectangular section > arched section. Among these, the arched section is identified as the optimal roadway cross-sectional shape for this engineering context. (2) The stress-concentration area in the arch roadway aligns with the inclined direction of the coal seam, forming asymmetric stress concentration patterns. Specifically, as the coal seam dip angle increases, stress increases at the arch shoulder of the upper sidewall and the wall foundation of the lower sidewall. Concurrently, such stress concentration induces shear failure in the surrounding rock, which serves as the primary mechanism causing asymmetric deformation and failure in steeply inclined thick coal seam roadways. (3) In the 1502 level roadway, the asymmetric support technology with dip-oriented reinforcement was implemented. Compared to the original support scheme, roof deformation and sidewall convergence decreased by 46.17% and 46.8%, respectively. The revealed failure mechanisms of steeply inclined thick coal seam roadways and the proposed asymmetric support technology provide technical and engineering references for roadway support in similar mining conditions. Full article