Energy Index Research Articles

Analyzing the dynamic behavior and market efficiency of green energy investments: A geometric and fractional brownian motion approach

ABSTRACT The growing importance of green energy investments necessitates understanding their dynamic behavior and market efficiency, particularly during geopolitical instability. This study examines the performance of three major green energy indices – First Trust NASDAQ Clean Edge Green Energy Index Fund, Invesco Wilder Hill Clean Energy, and S&P Global Clean Energy Index – across distinct macroeconomic periods, including the post-Paris Agreement era, COVID-19 pandemic, Russia-Ukraine conflict, and Israel-Gaza conflict. We apply two advanced stochastic modeling techniques to address the complexities of price movements in these indices: Geometric Brownian Motion and Multifractional Brownian Motion. The Hurst exponent is calculated to evaluate market memory and efficiency during these periods. Our findings demonstrate that while the Geometric Brownian Motion model effectively captures general market trends, the Multifractional Brownian Motion model reflects the nuanced volatilities and structural shifts in green energy markets, particularly during heightened geopolitical tension. The Hurst analysis identifies alternating periods of persistence and anti-persistence, highlighting varying levels of market efficiency and partially challenging the Efficient Market Hypothesis. This study’s novelty lies in applying Geometric Brownian Motion and Multifractional Brownian Motion to green energy indices, providing a comprehensive approach to analyzing their behavior under external shocks. These results contribute to the literature by offering insights into the resilience and efficiency of green energy investments, thus aiding investors and policymakers in navigating the complexities of sustainable finance during global crises.

On the connection between energy and Zagreb indices of graphs

On the connection between energy and Zagreb indices of graphs

Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals

Coal burst is one of the most frequent and destructive dynamic disasters encountered during underground mining engineering. However, the understanding of quantitative precursor characteristics of coal burst is still in its infancy, rendering it difficult to provide effective early warning of disaster. In this study, to quantitatively study precursor characteristics and warning signs of coal burst, the coal burst experiments were carried out on coal-rock combination with a crack. The acoustic emission (AE) technique was employed to quantitatively analyse the precursor information during coal burst process. Testing results indicated that coal burst process is classified into three stages based on evolution in AE energy, i.e., early incubation stage, late incubation stage and occurrence stage. The first significant increase in AE energy could be identified as the beginning of the late incubation stage of coal burst, accompanying by the phenomenon of macro-failure initiation. AE signals during the whole process could be classified as five types according to their dominant frequency and amplitude characteristics, i.e., HF-HA, LF-HA, EHF-LA, HF-LA and LF-LA respectively. The dramatic increase in number proportion of HF-HA and LF-HA signals is highly correlated with occurrence of coal burst. In addition, a comprehensive classification criterion for the coal burst prediction was proposed under a quantitative analysis of three AE parameters, i.e., first energy index (FEI), coal burst risk indicator based on AE energy (CRIE) and frequency spectrum (CRIF−A). The findings in this study could facilitate accurate coal burst prediction.

Creation the Watershed Streams Erosion and Energy Indices

Creation the Watershed Streams Erosion and Energy Indices

An efficient and flexible approach for local distortion: distortion distribution analysis enabled by fragmentation.

Distortion can play crucial roles in influencing structures and properties, as well as enhancing reactivity or selectivity in many chemical and biological systems. The distortion/interaction or activation-strain model is a popular and powerful method for deciphering the origins of activation energies, in which distortion and interaction energies dictate an activation energy. However, decomposition of local distortion energy at the atomic scale remains less clear and straightforward. Knowing such information should deepen our understanding of reaction processes and improve reaction design. Herein, an efficient, general and flexible fragmentation-based approach was proposed to evaluate local distortion energies for various chemical and biological molecules, which can be obtained computationally and/or experimentally. Moreover, our distortion analysis is readily applicable to multiple structures from molecular dynamics (or the minimum energy path) as well as can be evaluated by different computational chemistry methods. Our systematic analysis shows that our approach not only aids computational and experimental chemists in visualizing (relative) distortion distributions within molecules (distortion map) and identifies the key distorted pieces, but also offers deeper understanding and insights into structures, reaction mechanisms and dynamics in various chemical and biological systems. Furthermore, our analysis offers indices of local distortion energy, which can potentially serve as a new descriptor for multi-linear regression (MLR) or machine learning (ML) modelling.

Energy, Exergy, Entropy, emission factors (4E’s) and sustainability index analyses of thermal splintering waste paraffin Oil, di-ethyl ether − diesel blends

The study involves using thermal cracking techniques and enhancing fuel quality by incorporating di-ethyl ether, referred to as blended stock solution (BSS). In this work, an investigation was conducted on the Entropy, Energy, Emission Factors, Sustainability Index (SI) analyses, Exergy of BSS-diesel blends and the correlation between BSS-diesel blends and pure diesel. A single cylinder diesel engine running at speed of 1500 rpm was used for this experiment. The engine was tested with various blend ratios, including BSS20, BSS40, BSS60, BSS100, and pure diesel. The findings indicate that BSS60 has the best levels of exergy efficiency and energy, with a value of 30.35 % and 28.50 % respectively, surpassing other blends and pure diesel. The research findings suggest that BSS60 exhibited the lowest level of entropy formation compared to other fuel blends and pure diesel. The BSS60 exhibits the highest level of sustainability index. Emission factors of carbon monoxide (CO), demonstrate lower emission index (EI) and specific emissions (SE) as compared to both pure diesel and its blends. The emissions of NOx have shown a notable increase of 3.37 % in both the EI and SE when compared to pure diesel. The conclusions suggest the BSS60 exhibits superior performance and is suitable for use in direct-injection diesel engines.

Crop productivity and energy indices of tomato (Solanum lycopersicum) production under naturally-ventilated poly-house structures in north-western India

Crop productivity and energy indices of tomato (Solanum lycopersicum) production under naturally-ventilated poly-house structures in north-western India

Assessing the impact of macroeconomic and environmental concerns on Bitcoin in lower-income countries

Abstract This study investigated the effects of macroeconomic and environmental factors on Bitcoin return. The analysis included 31 lower-income countries selected based on their GDP rankings from 2012 to 2022. Using 341 observations, we applied Feasible Generalized Least Squares (FGLS) and One-step System Generalized Method of Moments (GMM) to evaluate the effects of Gross Domestic Product (GDP), Inflation Rate (INF), CO2 Emissions (CO2E), Climate Policy Uncertainty (CPU), Global Price Energy Index (GPEI), and Cambridge Bitcoin Electricity Consumption Index (CBECI) on Bitcoin return. The findings revealed a significant negative relationship between CO2E and Bitcoin return, reflecting investor concerns about Bitcoin’s environmental impact. CBECI showed a significant positive effect, suggesting that higher electricity consumption associated with mining activities led to increased Bitcoin return. CPU was positively associated with Bitcoin return, indicating that investors might have viewed Bitcoin as a hedge against climate policy uncertainties. GPEI had a significant negative effect, demonstrating Bitcoin’s sensitivity to global energy price fluctuations. GDP and INF showed no significant effect on Bitcoin return, suggesting that macroeconomic indicators did not significantly impact Bitcoin’s value in emerging markets. These results offered essential guidance for investors and policymakers in emerging markets.

Effect of different germination media on seed germination and seedling growth of tomato (Solanum lycopersicum L.) in Bhojpur, Nepal

The research was conducted following a Complete Randomized Design (CRD) under plastic tunnel with three replications to investigate the effects of different germination media on seed germination and seedling growth of tomato in Bhojpur Nepal. Nine different compositions of growing media are soil, cocopeat, vermicompost, soil + FYM (1:1), soil + cocopeat (1:1), soil + vermicompost (1:1), cocopeat + vermicompost (1:1), soil + cocopeat + vermicompost (1:1:1) and soil+ cocopeat + vermicompost + FYM (1:1:1:1). Seeds of tomato variety (Srijana) was sown in Plastic tray. Germination parameters such as germination percentage, germination speed, germination energy, and vigor index were recorded for seven consecutive days. Growth parameters including root length, shoot length, number of leaves, stem diameter, fresh seedling weight and dry seedling weight were measured at 20, 25 and 30 days after sowing. There were significant differences in the germination parameters and growth parameters. The maximum germination percentage (100%), maximum seedling vigor index (2329), root length (10.967cm), number of leaves (20.87cm) was recorded in soil + cocopeat + vermicompost + FYM (1:1:1:1) as a growing media. However maximum shoot length (12.847cm), maximum stem diameter (0.310cm) and maximum fresh weight (1.540g) was recorded in soil + cocopeat + vermicompost (1:1:1) as a growing media. Hence, optimum growth of tomato seedlings was observed when soil, cocopeat, vermicompost and FYM were used in equal proportions.

The Causal Relationship between Public Investment in Renewable Energy and Climate Change Performance Index

Addressing the current environmental challenges requires optimizing climate actions and understanding the complex relationships among them. This paper aims to provide insights into how public investment in renewable energy influences various dimensions of climate change, including emissions, efficiency, renewable energy deployment, and policy effectiveness. This study seeks to explore the causal connection between public investment in renewable energy and the Climate Change Performance Indicator (CPI) from 2007 to 2017, utilizing data provided by German Watch. The method used is Dumitrescu and Hurlin’s (2012) Granger Causality. The study unveils a unidirectional causality from Renewable Energy Investment (REI) to climate change performance. Additionally, it emphasizes the critical role of energy efficiency in attracting investments in renewable energy. Surprisingly, the study finds that REI influences the quality of climate policy. Furthermore, the study identifies a bi-directional causality between a renewable energy share and REI. The contribution of the paper lies in its analysis of public investment in renewable energy, covering areas beyond just public finance for R&D in renewable energy, as also exploring the causal link between this investment and CPI. It offers policymakers insights on how financial governmental interventions can effectively drive climate action.

Portfolio Diversification and Dynamic Interactions between Clean and Dirty Energy Assets

Clean energy, with its focus on environmental sustainability and efficiency, has gained significance as concerns over the impact of traditional energy growth. However, there is limited evidence on the value of clean energy investments. This paper explores the role of clean energy in a balanced investment portfolio by examining two traditional energy assets (crude oil and natural gas) and two clean energy assets (SPDR S&P Kensho Clean Power ETF and iShares Global Clean Energy ETF). Using a time-varying parameter vector autoregression (TVP-VAR) model on daily data from October 2021 to January 2024, we analyze the evolving connectedness between these assets. Our results highlight dynamic interactions, with green finance indices like CNRG acting as net shock transmitters, while traditional energy indices, such as WTI and gas, primarily receive shocks. The analysis suggests that green assets, particularly ICLN, enhance portfolio stability and hedging efficiency, especially in minimum correlation and risk parity portfolios. Fossil fuels, especially gas, exhibit higher volatility, requiring careful portfolio management. Ultimately, integrating ESG criteria and adapting investment strategies to market conditions may enhance responsible investing and long-term value creation.

Iron-irradiated methylammonium lead iodide bromide (MAPbI2Br) thin films with enhanced optical and electrical properties for high-efficiency perovskite solar cells

In the pursuit of enhancing the optoelectronic properties of perovskite thin films for photovoltaic applications, this study investigates the effects of Fe ion irradiation on methylammonium lead iodide bromide (MAPbI₂Br) thin films. Thin films of methylammonium lead iodide bromide, (CH3NH3PbI2Br, or MAPbI2Br) have been deposited by sol–gel dip coating technique. These films were irradiated with 300 keV Fe ions with flouncy of 2 × 1014 ions/cm2. The prepared films all show the cubic crystal structure. However, the film irradiated with Fe ions has a larger grain size, according to XRD. The optical characteristics, such as refractive index, band gap energy, and extinction coefficients, are examined by UV–Vis analysis. Although both the films showed a direct bandgap, the film irradiated with Fe ions showed a lower value for the bandgap energy (1.76 eV) and high refractive index. The device structure used was FTO/TiO2/MAPbI2Br/spiro-OMeTAD/Au. The devices made with 300 keV Fe ions irradiated film has high current density of 10.86 mA cm−2, fill factor of 0.80, an open circuit voltage of 1.06 V, and an efficiency of 9.93%. The findings emphasize the potential of Fe ion irradiation as a novel technique to improve grain structure and optoelectronic properties, advancing perovskite-based device technology for higher efficiency solar cells.

Performance Evaluation of Hybrid PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost Models for Rockburst Prediction with Imbalanced Datasets

The rockburst hazard is a primary geological disaster endangering the environment in underground engineering. Due to the complexity of the rockburst mechanism, traditional methods are insufficient to predict the rockburst hazard objectively, especially when dealing with an imbalanced dataset. To address this issue, the hybrid models of PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost were developed to predict rockburst hazards in this study. First, a rockburst dataset with 266 cases was constructed, containing six indicators: the maximum tangential stress, uniaxial compressive strength, uniaxial tensile strength, elastic deformation energy index, tangential stress index, and brittleness coefficient of strength. Then, the original dataset was oversampled using the synthetic minority oversampling technique (SMOTE) for dataset balancing. Subsequently, the PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost models were constructed and evaluated to have the best accuracies of 0.901 and 0.851, respectively. Finally, the developed models were applied to predict the rockburst hazard in the Daxaingling Tunnel, the Cangling Tunnel, and the Zhongnanshan Tunnel shaft. The results indicate that the obtained rockburst hazard levels are consistent with engineering records, and the developed PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost models are reliable for rockburst prediction.

Comparative Analysis of the Photovoltaic Industry in China and the US: Policy, Innovation, and Market Competitiveness

The photovoltaic (PV) industries of China and the United States have evolved in distinctively different ways, driven by vastly contrasting government policies, technological innovations, and market dynamics. Over the period from 2015 to 2024, the Global Price of Energy Index witnessed a significant surge of 42%, bringing the urgency for viable renewable energy solutions to the forefront. China's PV industry, underpinned by robust government support and substantial investments, has soared to global prominence through its large-scale manufacturing capabilities and efficient production processes. In stark contrast, the U.S. PV industry places a greater emphasis on pioneering technological advancements in advanced PV technologies, yet it still relies heavily on imports to meet domestic demand. By analyzing data sourced from the International Energy Agency and industry-specific reports, this comparative analysis illuminates how these fundamental differences will mold the future competitiveness of both nations within the PV sector and profoundly influence the trajectory of the global energy transition.

Transforming Rainfed Pigeonpea Cultivation in India: The Impact of Complete Mechanization on Growth, Productivity and Energy Indices

Background: Pigeonpea is a leguminous, long duration and wide spaced crop. Performing labour intensive, agronomic operations timely from land preparation to post harvest is expensive since rural to urban migration has become a major problem. There is a dire need to evaluate the effects of complete mechanization and suggest options for reducing cost of production, augment the productivity, profitability and energy use efficiency in pigeonpea. Methods: A large plot experiment was conducted in pigeonpea for two years (kharif 2019-20 and 2020-21) under rainfed conditions in an alfisol with two treatments viz., Conventional practices (CPs) and Mechanization practices (MPs). The recorded data was analysed through a two sample t-test for statistical significance. It was carried out at Agricultural Research Station, Tornala, Professor Jayashankar Telangana State Agricultural University, Hyderabad, India. Result: Mechanization practices (1362 kg ha-1) have increased the pigeonpea seed yield by 16.51% over conventional practices (1169 kg ha-1) besides saving 42.5 man-days and 67.5 hours ha-1. MPs have not only reduced the total cost by Rs. 6,745 ha-1, but also enhanced the net returns by Rs. 18,225 ha-1. Higher infiltration rate, net energy and energy output efficiency over CPs helped substantiate the results.

Study of the 3-(3,3-Dimethylbutanoyl)-4-hydroxy-6-neopentyl-2H-pyran-2-one by IR, Raman spectroscopy, and DFT

The heterocyclic structure of pyrones has a variety of biological activities and plays an important role in the creation of new drugs. Therefore, the study of the structure and spectra of pyrones is of considerable interest. In this work, we studied the IR and Raman spectra of 3-(3,3-Dimethylbutanoyl)-4-hydroxy-6-neopentyl-2H-pyran-2-one (1) in its crystalline state. The tautomerization of 1 was followed by a quantum-chemical method at the DFT/B3LYP/6-311G** level. The calculation for the 4-hydroxy enol tautomer (A) reproduces the experimental IR and Raman spectra of compound 1. The classification of the bands in the experimental vibrational spectra of 1 has been carried out. The intramolecular H-bond was characterized by IR spectroscopy. The free energies of the tautomers and their populations were calculated for two different solvents. It appears from our data that tipe A dominates. The content of tautomer B increases in the nonpolar solvent but does not exceed 13%. As can be seen from our calculations and experimental X-ray data, the pyran ring of the molecule is flat. HOMO and LUMO of molecule 1 are located on the pyran ring. During tautomeric transformations, there is a significant delocalization of charge and a change in the reactivity of the molecule. The reactivity of pyrone 1 was characterized using descriptors. The form B was found to have higher ionization energy, electron affinity, chemical potential, and electrophilic index than the A form. The dipole moment is higher for form A, and the softness of the two molecules is the same.

Operation of a hybrid heating system based on heat pumps using a photovoltaic installation

In Poland, heating systems using renewable energy sources have gained importance in construction projects, especially in newly designed buildings. This is mainly due to the Regulation of the Minister of Infrastructure, which sets technical conditions for buildings. As of December 31, 2020, the primary energy index for newly designed single-family buildings should not exceed 70 kWh/(m2year). This requires efficient energy sources in building design. Renewable energy installations have significantly lower primary energy utilization rates than fossil fuel systems, making them the preferred choice. In a facility in Batowice near Krakow, a hybrid energy system with ground-source and air-source heat pumps has been installed. These pumps are powered by electricity from a photovoltaic installation connected to the grid. The study aims to determine the optimal heat pump choice based on the facility’s conditions and optimize electricity consumption from the photovoltaic installation. Both heat pumps showed similar efficiencies during the heating season from December 2022 to March 2023: the ground-source heat pump achieved an annual coefficient of performance of 2.69, and the air-source heat pump achieved a seasonal coefficient of perfor-mance of 2.63. Given the high non-renewable primary energy factor for grid electricity, the feasibility of replacing gas boilers with heat pumps requires careful evaluation. The results indicate that integrating a heat pump with a photovoltaic installation substantially reduces the primary energy utilization index, supporting climate protection and the advancement of renewable energy sources. However, heat pumps alone may not be sufficiently efficient without the support of a PV installation.

Topological Indices of Inverse Graph for Generalized Quaternion Group

In this paper, some of the famous and known topological indices for the inverse graph of Generalized quaternion group, including: Hosoya polynomial, Wiener index, hyper-Wiener index, first Zagreb index, second Zagreb index, ABC index, eccentric index, eccentric-connectivity index, total eccentric index, first Zagreb eccentric index, second Zagreb Eccentric index, graph energy index, and Estrada index.

Projections of standardised energy indices in future climate scenarios

Abstract Renewable energy is becoming an increasingly important component of energy systems. However, renewable energy production is heavily dependent on the prevailing weather conditions, which are changing as a result of climate change. It is therefore necessary to build energy systems that are robust to energy shortages caused by weather-dependent changes to energy demand and renewable energy production. To design such systems, we must monitor how changes in the climate are expected to influence future energy production and demand; this is important for policymakers to decide when, where, and by how much renewable energy installed capacities should be increased, for example. In this paper, we study the behaviour of standardised energy indices in future European climate projections, and use this to monitor how characteristics of energy production droughts in Europe are expected to change in the future. We use these results to make suggestions regarding how the energy mix should be adapted in the future to decrease the risk of energy production droughts.

Investigation into the mechanical properties and impact tendency of coal-rock composite structures with peridynamics: A study on predicting the occurrence tendency of dynamic pressure in coal-rock structures.

Due to the difficulty in predicting the occurrence of rockburst in deep mining areas,this paper proposes that the use of Peridynamics to analyze the mechanical characteristics of coal-rock composite structures under loading conditions from the perspective of energy, Determine the impact tendency of coal rock composite structures by combining rock elastic deformation energy index (WET) and rock impact energy index (WCF); Use Lammps software to simulate the loading of composite structural materials and compare and verify with experimental results, to more accurately determine the tendency of rockburst occurrence in different coal-rock composite structures.The results indicate that after the specimen reaches the yield stress, the sample exhibits an "X" shaped failure. The coal body has a significant impact on the overall model's fragmentation, and different combination states and ratios can affect the degree of damage in the coal-rock composite structure. which has important theoretical value for rock mechanics research. The research results can reduce the occurrence of rockburst accidents, the difficulty of mine support, and the cost of mining engineering, as well as improve mine safety levels.