Energy Index Research Articles

The effects of policy fluctuations on energy indices in Iran's agriculture sector

The effects of policy fluctuations on energy indices in Iran's agriculture sector

Wavelet entropy and complexity–entropy curves approach for energy commodity price predictability amid the transition to alternative energy sources

In recent years, energy commodities have emerged as pivotal and widely debated subjects, driven by their profound influence on the global economy and their intricate interconnections. Moreover, the challenges stemming from the predictability of energy commodity prices have become a prominent and intensifying focus of discussion. To this aim, in this paper, we employ wavelet analysis with an entropy approach to investigate and evaluate fluctuations, low-frequency events, and rare events in energy commodity prices and the consequent predictability of such time series. In particular, wavelet analysis can differentiate high-frequency from low-frequency movements in a time series, and entropy is a valuable mathematical tool used to evaluate the state of disorder, randomness, or uncertainty in a time series. Specifically, we employ Rényi Entropy instead of the Shannon entropy because it allows for enhanced consideration of low-frequency events and spikes in a time series. Therefore, to analyze the predictability of a series, we use Wavelet Rényi Entropy (WRE) and the Rényi complexity–entropy curves by combining the wavelet transform with Rényi entropy. Finally, we apply our analysis to real financial data, including energy commodities and indices that can describe the transition to alternative energy resources.

Shared energy in renewable energy communities: The benefits of east- and west-facing rooftop photovoltaic installations

Renewable energy communities (RECs) offer a promising perspective for decarbonizing the building sector. This is accomplished by enhancing the uptake, among others, of citizen-owned rooftop photovoltaic systems. A key challenge lies in ensuring that photovoltaic generation matches the needs of community members, i.e. maximizing shared energy index. Indeed, the shared energy depends on the consumption habits of individual members and the rooftop characteristics, such as orientation and inclination of available pitches, which influence the production curve. Therefore, clear guidelines on which roof pitches are most suitable for PV generation within RECs might be helpful during the design of such communities. In this paper, we investigate the optimal orientations and tilt angles for PV systems in REC design. We conducted a robust Monte Carlo simulation of an energy community comprising 60 users, 30 of which are equipped with rooftop PV systems for a total of 150 kWp installed. Our analysis revealed that pitches with West and East offer comparable, if not better, shared energy values than those South-facing, consequently mitigating peak power dispatched to the grid. Besides, shared energy remains quite constant across various tilt angles. These findings suggest that buildings with non-South-facing roofs should not be overlooked, but embraced in the design of renewable energy communities as they can contribute significantly to shared energy.

Evaluation of Linear Amplitude Sweep data analysis techniques and failure criteria for High Polymer-Modified binders

High Polymer Modified Binders (HiPMBs) have gained attention for their resilience to environmental and traffic stressors, yet their fatigue cracking resistance remains insufficiently explored. Even though the Linear Amplitude Sweep (LAS) test is an AASHTO standardized procedure, various data analysis techniques and failure criteria can be found in the literature. It is unclear whether they produce divergent results and whether any of them provide better insights into bitumen behavior. The research showcased in this paper aimed to assess the factors affecting the evaluation of HiPMBs' fatigue life through the LAS test. Additionally, asphalt concrete was produced with bitumen previously tested and subjected to Push-Pull (PP) fatigue cracking evaluation for direct comparison. Results show significant differences between analysis methods, regardless of the failure criteria applied. The methods that rely on the Viscoelastic Continuum Damage (VECD) analysis were affected by the inaccuracy of the material integrity function fitting. The failure criterion significantly impacts the ability to detect the benefits of the high polymer content, which becomes increasingly noticeable for failure criteria different from those suggested in the AASHTO specification. Meanwhile, the Fatigue Resistance Energy Index (FREI) approach has a great advantage of not being tight to the VECD formulations and was able to capture the differences between the Neat Binders (NBs) and the HiPMBs. As for the corresponding binders' performance on the HMA level, similarities in the ranking were noticed; however, no full agreement was recognized.

The Effects of Feedstock, Pyrolysis Temperature, and Residence Time on the Properties and Uses of Biochar from Broom and Gorse Wastes

Biochar (BC), which can be produced from several feedstocks, has been widely studied. However, the BC derived from highly pyrolytic shrubs, such as broom and gorse, has been less frequently used and only partially characterized. These wastes, when used for the preparation of biochar, can fix carbon and contribute to environmental conservation, helping to achieve sustainable development objectives. Eight biochars from broom and gorse were produced and fully analyzed, providing a more complete and novel description, with new insights for assessing their utilization. The aims of this study were to elucidate the effects of feedstock, pyrolysis temperature, and residence time on biochar properties and to assess the adequacy of these biochars as fuel. Elemental and proximate analyses and estimations of the lower and higher heating values were performed, and physical and chemical properties, as well as several other related energy indices, were determined. The experimental results showed that the temperature was a key factor in the properties of the biochars, while residence time was less important. The BCs obtained from the two feedstocks did not show important effects on the properties, which is consistent with the fact that they are woody legumes. These biochars had a high carbon content and were thermally stable. The BCs also had a high calorific value and suitable energetic properties. Additionally, their PAH contents were low, indicating that the use of these biochars would be safe. In conclusion, broom- and gorse-derived biochars can be considered as renewable fuels for green energy production.

A comprehensive study of experimental and theoretical characterization and in silico toxicity analysis of new molecules

In this study, for the first time in the literature, a 2-(3-methoxyphenylamino)-2-oxoethyl acrylate (3MPAEA) molecule was synthesized in two steps, and a 2-chloro-N-(3-methoxyphenyl)acetamide (m-acetamide) was obtained in the first step. Experimental results were obtained using FTIR, 1H, and 13C NMR spectroscopy methods for m-acetamide and 3MPAEA compounds created in the laboratory environment and compared with theoretical results. Band gap (BG) energy, chemical hardness, electronegativity, chemical potential, and electrophilicity index were calculated. With vibration spectroscopic analysis, atom–molecule vibrations of the theoretical and experimental peaks of the spectrum were observed. The locations of C and H atoms were determined by nuclear magnetic resonance spectroscopy. The green, blue, and red regions of the potential energy map (MEP) map were examined. Some observed that the energy thermal, heat capacity, and entropy graphs increased in direct proportion to increasing the temperature in Kelvin, which is known as thermochemistry. The changes in the rotation, translation, and vibration of the molecule as its temperature increased were examined. When the thermochemistry surface map was examined, some observed that the temperature was high in the middle binding site of the molecules. Covalent interactions were graphed using the non-covalent interactions (NCIs) calculation method. In silico toxicity studies were carried out for m-acetamide and 3MPAEA molecules: fathead minnow LC50 (96 h), Daphnia magna LC50 (48 h), Tetrahymena pyriformis IGC50 (48 h), oral rat LD50, water solubility, bioconcentration factor, developmental toxicity, mutation, normal boiling point, flash point, melting point, density, thermal conductivity, viscosity, vapor pressure, etc. parameters were investigated.

Effects of Salicylic Acid Seed Priming on Germination of Lentil (Lens culinaris Medik.) Exposed to Salt Stress

Lentil (Lens culinaris Medik.) is an essential crop globally, particularly in Türkiye, West Asia, Southern Europe, India, and Africa. Lentil is a valuable food source, rich in proteins, carbohydrates, minerals, and vitamins. However, lentil production faces challenges due to salinity stress, which hampers water uptake and causes toxic effects on plants. The study aimed to investigate the effects of salicylic acid (SA) seed priming and varying salt (NaCl) concentrations on the germination and development of lentil seeds. The research was conducted in the Field Crops Biotechnology Laboratory, University of Dicle, Faculty of Agriculture, Türkiye. In the research, control, two salt (NaCl), four salicylic acid (SA) doses and their combinations were used on Lens culinaris variety called İlke. Germination percentage, energy, rate index, mean germination time, peak value, and vigor index were calculated. The results demonstrated that SA had a significant impact on improving lentil germination under salt stress conditions. Specifically, lower concentrations of NaCl combined with SA showed positive effects on germination and growth parameters compared to higher NaCl concentrations. The highest germination percentage, energy, and rate index values were in the control and 0.25 SA dose treatment. Salicylic acid doses under 50 NaCl concentration exhibited higher germination percentage, energy, and rate index values than under 100 NaCl. Increasing SA and salt doses negatively affected lentil seed germination. This finding is significant for lentil cultivation in salt-affected areas, offering a potential strategy to improve crop resilience and yield in challenging environmental conditions.

Characterization and the physical properties of nano-sized Bi2O3/polymer for energy and high-refractive index applications

The present work focuses on developing nanocomposites for optoelectronics and energy storage devices leveraging the unique physicochemical features of bismuth (III) oxide (Bi2O3) using a polyvinyl pyrrolidone/polyvinyl alcohol matrix (PV(A/P)). Bi2O3 nanofillers (NF) and Bi2O3/PV(A/P) nanocomposite (NC) films were prepared by facile chemical solution approaches. The X-ray (XRD) data and a transmission electron image revealed that the NF exhibits a monoclinic phase, resembling slightly deformed agglomerated spheres. In the FTIR spectrum, different stretching vibrations of Bi-O-Bi bonds were found, along with their complexation and interaction with the reactive groups in the matrix. The SEM revealed a uniform distribution of Bi2O3 NF loading up to 1.5 wt% on the sample’s surface. Thermal analyses (TGA and DSC thermograms) were used to study the thermal stability, melting, and decomposition temperatures of the NC films. The dielectric features were studied under frequencies between 2 × 103 and 8 × 106 Hz and heating from 293 to 393 K. The dielectric constant and energy density were increased with Bi2O3 NF content. This implies that we can utilize the prepared NC for the fabrication of energy storage devices. The influences of the Bi2O3 NF doping level on the transmittance, band gap, Urbach energy, refractive index, conductivity, and other physical parameters were discussed. The modifications induced in the dielectric/optical parameters make the prepared NC films the best candidates for applications requiring a high refractive index, such as optical coatings and integrated photonic devices.

Extreme Events Cause Market Efficiency or Inefficiency? Evidence from Precious Metals and Green Stock Indices

Background: Green investments offer a promising market-based approach to tackling global climate change but are susceptible to risk transmission from multiple assets. Purpose: To examine the multifractality between precious metals (Gold, Silver, Platinum) and green stock indices, such as Clean Energy Fuels, Nasdaq Clean Edge Green Energy, S&P Global Clean Energy and WilderHill Clean Energy, over the period from 1 January 2018 to 23 November 2023. The study aims to answer the following question: Did the events of 2020 and 2022 cause efficiency or inefficiency in the markets analysed? Methods: The Detrended Fluctuation Analysis (DFA) econophysics model will be used to answer the research question. Results: During the period of stability, there was a clear division between the markets, with Gold and green energy indices demonstrating market efficiency, while Platinum, Silver and some green indices exhibited price persistence, suggesting opportunities for above-average gains. However, the 2020 global pandemic led to widespread inefficiencies in all the markets analysed, with precious metals and green energy indices showing price persistence, indicating patterns that could lead to arbitrage opportunities. The persistence in returns suggested a tendency for asset prices to continue in the same direction for an extended period, offering opportunities to identify ongoing market trends for investment. In the pre-conflict period, the random walk hypothesis was rejected in all markets, with precious metals exhibiting anti-persistence in returns, while green energy indices showed significant persistence. During the conflict period, precious metals and green energy indices converged towards persistence in returns, except Platinum, which showed anti-persistence. Conclusion: This study provides valuable insights for investors and financial market professionals, highlighting the importance of understanding asset price behaviour patterns in different economic contexts.

Climate risks and the realized higher-order moments of financial markets: Evidence from China

The return distribution of energy assets deviates from the normal distribution, making volatility a partial measure of risk, and climate risk tend to affect the skewness preferences of environmentally conscious investors. However, limited evidence exists on the impact of climate risk on higher-order moments of asset returns, especially in China. Using data from December 2013 to June 2022, we study the time-varying Granger causal flow from two Chinese climate uncertainty indices (Chinese climate policy uncertainty (CPU) and Chinese climate uncertainty (CU)) to the realized high-order moments (volatility, skewness, and kurtosis) of various Chinese assets covering green energy, carbon emission allowances, and brown energy indices. The main results show evidence of time-variation in the causal flows from climate risks, without ignoring the heterogeneity between the two climate risk measures and across the three assets under study. Granger causality spans various time periods, and is generally more significant for the realized volatility. These results are robust to the specification of the time-varying causality analysis. They also remain significant when accounting for the impact of Chinese economic policy uncertainty, which further supports their robustness. These findings highlight the ability of climate risk to affect higher-order moments of asset returns through the channels of strong deviation of returns from the normal distribution, the preference of investors for skewness, and the frequent occurrence of crisis periods.

Manganese addition effect on structural and physical properties of calcium borovanadate glasses

New calcium borovanadate glass containing manganese ions within the system x Mn2O3-(30-x) V2O5-50 B2O3-20 CaO has been elaborated* in this work using melt quench process. The primary objective of this research is to examine the influence of introducing Mn2O3 upon the various properties of the elaborated glass specimens including physical, thermal, structural, optical and magnetic properties. X-ray diffraction indicated that the samples prepared were amorphous. The variation in density and molar volume revealed that the structure of the glass matrix cross-links and becomes more compact with increasing Mn2O3 content, which is confirmed when the glass transition temperature is increased. Furthermore, in order to check the group constitution of our glasses, a structural study was carried out using infrared (FTIR) and Raman spectroscopy. The optical characteristics of our vitreous materials were analyzed by UV solid, and the results of the band gap energy and refractive index values revealed an enhancement of non-bridging oxygen atoms (NBOs) with rising Mn2O3 concentration, also suggests that manganese acts as a structure modifier. The low Urbach energy values are an indication that the structure of our glasses is stable and uniform. The magnetic investigation highlighted the presence of the predominant antiferromagnetic order in the glass samples studied, which becomes stronger with the incorporation of more manganese ions into the structure.

Analyzing Crisis Dynamics: How metal-energy Markets influence green electricity investments

The world continues to face major economic challenges due to crises that have a considerable impact on energy consumption. Since the global energy crisis, energy commodity costs have risen, and economic slowdowns in various regions continue to influence electricity market trends. Clean energy markets, propelled by the growing interest of economic entities and investors, are now interconnected with several commodity markets. In this context, energy metals play a crucial role in influencing the dynamics of the clean energy and particularly electricity markets. This study takes a close look at the complex interconnections between clean energy indices and the metals market, focusing on volatility dynamics. Drawing on advanced methodologies, including the Diebold and Yilmaz method, we unveil the complex relationships that link these markets. Our results reveal distinct patterns and interactions, highlighting the nuanced nature of the connection between clean energy indices and metal prices. The insights revealed have significant implications for policymakers and investors seeking to align their strategies with sustainable energy transitions and ensure financial stability. By enhancing our understanding of the interdependencies between clean energy indices and metals markets, this research provides valuable guidance for navigating the changing clean energy investment landscape.

Impact of Climate Policy Uncertainty, Clean Energy Index, and Carbon Emission Allowance Prices on Bitcoin Returns

This research aimed to investigate the relationship between climate policy uncertainty (CPU), clean energy (ENERGY), carbon emission allowance prices (CARBON), and Bitcoin returns (BTC) for the period from August 2012 to August 2022. The empirical analysis strategies utilized in this study included the Fourier Bootstrap ARDL long-term coefficient estimator, the Fourier Granger Causality, and the Fourier Toda–Yamamoto Causality methods. Following the confirmation of cointegration among the variables, we observed a positive relationship between BTC and CARBON, a positive relationship between BTC and CPU, and a negative relationship between BTC and ENERGY. In terms of causal associations, we identified one-way causality running from CARBON to BTC, BTC to CPU, and BTC to the ENERGY variable. The study underscores the potential benefits and revenue opportunities for investors seeking diversified investment strategies in light of climate change concerns. Furthermore, it suggests actionable strategies for policymakers, such as implementing carbon taxes and educational campaigns, to foster a transition towards clean energy sources within the cryptocurrency mining sector and thereby mitigate environmental impacts.

Multi-bolt looseness positioning using multivariate recurrence analytic active sensing method and MHAMCNN model

The piezoelectric active sensing method has been proven to be an effective, nondestructive approach for bolt looseness monitoring. The conventional damage index relies on the energy index of the wavelet packet. However, the method of wavelet packet could not identify the looseness location of the multi-bolt. Therefore, an innovative multi-bolt intelligent method combined the multivariate recurrence analytic active sensing method with an improved convolutional neural network (CNN) model was proposed for multi-bolt looseness positioning. In this method, the multivariate recurrence plots (RPs) are firstly constructed based on the received stress waves and then it is utilized to extract the recursive attributes presented within the stress wave signals. Secondly, a novel model, the CNN improved by the multi-head attention mechanism (MHAMCNN), is constructed to extract nonlinear features hidden in multivariate RPs. Repeated experiments demonstrate that the proposed method, which combines MHAMCNN and un-thresholded multivariate RPs (i.e., mean detection accuracy: 98.62%), outperformed other methods, including multivariate RPs (i.e., mean detection accuracy: 97.06%) and common RPs. Compared with traditional pattern recognition algorithms, MHAMCNN has higher classification accuracy. In summary, the suggested approach presents a promising opportunity for the real-time monitoring of multi-bolt looseness.

The texture analysis of computed tomography studies in clear cell renal cell carcinoma: reproducibility of 2D and 3D segmentation

Background: Differentiation of tumor grade at the preoperative stage is of utmost importance for the modification of the treatment strategy and the extent of operation. However, the routine analysis of computed tomography (CT) data in clear cell renal cell carcinoma (ccRCC) does not allow for reliable determination of the tumor grade.
 Aim: To assess the reproducibility of the results of 2D and 3D segmentation of a kidney tumor in the cortico-medullary and nephrographic phases of CT studies, as well as the reproducibility of the first order texture parameters for 2D and 3D tumor segmentation in patients with verified ccRCC.
 Materials and methods: This retrospective study included the CT data of 50 patients with morphologically verified ccRCC obtained before their surgical treatment. The first patient group included the patients with the renal tumor size in the axial plane of ≥ 4 cm (28 patients, 29 CT studies), and the second patient group included those with the renal tumor size in axial plane of 4 cm (22 patients, 23 CT studies). Two radiologists independently performed segmentation of the renal tumor in the cortico-medullary and nephrographic phases of CT procedures done under a standard protocol with the bolus intravenous contrast enhancement. A two-dimensional region of interest (2D ROI) was selected by the investigators on a subjectively selected axial slice, where the tumor had the largest size. When forming a three-dimensional region of interest (3D ROI), the entire tumor volume was segmented. Next, the statistical analysis of the segmentation results and the results of calculation of the first order texture indices was performed with calculation of the intra-class correlation coefficient (ICC) to assess the strength of the data correlation. The ICC of ≥ 0.75 demonstrated the reproducibility of the segmentation results and the first order texture indices.
 Results: The 3D segmentation method for ccRCC demonstrated the best ROI reproducibility results, regardless of the tumor size and the phase of contrast enhancement, with the ICC values of 0.961 (95% confidence interval: 0.946–0.971) for the cortico-medullary phase and 0.969 (95% CI: 0.958–0.977) for the nephrographic phase. The 2D tumor segmentation method showed unsatisfactory ROI reproducibility, with the ICC values of ≤ 0.058; however, the unsatisfactory reproducibility of the segmentation results in the patients with ccRCC tumor size of ≥ 4 cm did not significantly affect the reproducibility of the Entropy and Energy texture indices (good to excellent correlation). With the 3D segmentation of ccRCC, most first-order texture metrics were reproducible, with the exception of the Kurtosis parameter. The Entropy and Energy scores in both patient groups demonstrated a high degree of reproducibility. In the 2D tumor segmentation, high reproducibility of the first order texture metrics was obtained for the Entropy and Energy indices.
 Conclusion: The 3D segmentation of the CT data for ccRCC has high reproducibility, the most first-order textural features were excellently reproducible when segmentations were performed in 3D. The 2D CT data segmentation method for ccRCC demonstrated low reproducibility; however, some of the first order texture indices were reproducible. Both segmentation methods can be used for the texture analysis of CT images.

Research on the Spatiotemporal Characteristics of the Coupling Coordination Relationship of the Energy–Food–Water System in the Xinjiang Subregion

In the Xinjiang region, the sustainable management of water resources, energy, and food is crucial for regional development. This study establishes a coupling evaluation index for energy–food–water (EFW) systems from the perspectives of supply, consumption, and efficiency. Using an integrated EFM-CDD-RDD-CCDM approach, an assessment of the coupling and coordination levels of the EFW systems in 14 cities within Xinjiang was conducted for the period of 2004 to 2020. Additionally, the method of obstacle degree identification was utilized to determine the main barriers affecting the EFW systems. Key findings included the following. (1) In terms of individual system coordination indices, the water resource systems exhibited overall higher coordination (ranging from 0.30 to 0.72) with comparatively minor spatial variability, while the energy (from 0.18 to 0.81) and food (from 0.12 to 0.83) systems showed greater temporal and spatial fluctuations. From 2004 to 2020, improvements were observed in the coordination of food and water resource systems, whereas a decline was noted in the coordination of the energy subsystem. (2) Prior to 2011, the coupling of food–water and energy–food systems showed an upward trend, whereas the energy–water coupling decreased annually by 2.62%, further highlighting the tensions between energy development and water resource constraints in Xinjiang. (3) The comprehensive coupling coordination index of the Xinjiang EFW systems ranged between 0.59 and 0.80; between 2004 and 2020, there was an oscillatory increase. From 2004 to 2016, the coupling and coordination degree across the municipalities generally improved, with the regions on the western side and southern slope of the Tianshan Mountains, the Altai Mountains, and the northwestern edge of the Junggar Basin exhibiting the highest levels, followed by the three prefectures in southern Xinjiang. (4) The EFW obstacle degree posed by the food systems in Xinjiang and its divisions showed a decreasing trend from 2004 to 2020, with the energy system identified as the main factor affecting the coupling and coordination degrees of the EFW systems (increasing by 44% to 52%). Therefore, it is imperative to accelerate the energy transition and optimization in the lead energy development and production areas of Xinjiang. This research provides a scientific basis for Xinjiang’s sustainable development strategies and highlights potential directions for the future optimization of resource management.

Climate policy uncertainty, media coverage of climate change, and energy markets: New evidence from time-varying causality analysis

Climate change is one of the most critical issues in the last decade, making investigating climate change risks' effects on the economy vital. Employing a novel time-varying Granger causality approach, we test causality from climate policy uncertainty (CPU) to the index returns of clean energy and nonrenewable energy sectors between November 2009 and December 2021. Our analysis generally reveals a significant causality from CPU to S&P clean energy sector index return throughout the sample period. In contrast, very limited significant causality is observed running from the CPU to the S&P nonrenewable energy index return. This result implies that investments in clean energy firms are affected by the CPU due to the cost of reversing the decisions in uncertain environments. On the other hand, the U.S. newspaper media coverage of climate change has a significant impact not only on the clean energy index returns but also on non-renewable energy index returns, implying an increase in the media coverage regarding climate change influences the awareness of investors on climate change, which affects their trading strategies.

Portfolio management of ESG-labeled energy companies based on PTV and ESG factors

This paper evaluates monthly quartile portfolios of ESG-labeled companies constructed based on their Prospect Theory Value (PTV) and ESG scores in the closely monitored energy sector. Investing in ESG-labeled energy stocks can outperform a value-weighted global energy sector index, according to several out-of-sample performance analyses. The PTV strategy stands out over a sample period of more than twelve years. This strategy performs similarly to a fully diversified world market index and consistently outperforms a world energy index. Over the last five years, the simple strategy based on ESG scores performs similarly to the PTV strategy.

Exploring the recovery capacity of recycling agents on atomic-scale energy properties of aged bitumen and their potential correlations with high-temperature rheological performance

This study implements molecular dynamics (MD) simulations to explore the atomic-level energy properties of rejuvenated bitumen, considering the influence of different recycling agent (RA) types, dosages and aging levels of bitumen. Moreover, the potential correlations between energy indices and high-temperature performance of rejuvenated bitumen are explored. Our findings show that recycling agents can effectively reinstate the cohesive energy density (CED) values of aged bitumen, correlating well with their high-temperature rheological properties. The results reveal that the energy parameters of potential energy (UVEP), kinetic energy (UWEK), non-bond energy (EN), total energy (UVET), diagonal energy (UNED), and cross-terms energy (ECT) can reflect the restoration level of recycling agents (RAs) on atomic-level energy characteristics of aged bitumen. Compared to rutting failure temperature (RFT), elastic recovery (R3.2), and creep compliance (Jnr3.2), the zero-shear viscosity (ZSV) greatly correlates with CED. Meanwhile, the UWEK index from MD simulations demonstrates a strong correlation with high-temperature rheological indicators of rejuvenated bitumen. With the rise in UWEK, there is a linear decrease in the RFT, Log(ZSV), and R3.2 values of rejuvenated bitumen. Conversely, the Log(Jnr3.2) exhibits a linear increasing trend. However, the correlation patterns between rheological indicators and either EN or ECT are contingent on the aging degree of bitumen. Based on the correlation coefficient, the UWEK stands out as the primary choice among all energy indices for predicting high-temperature rheological performance of rejuvenated bitumen.

Quantifying the reduction in coal and increase in renewables in OECD (Organisation for Economic Co-operation and Development) countries: Proposal for a coal-renewable energy index and map

Reducing coal use and increasing renewable energy use are two major policies that have been recommended in many countries and regions to address climate change. However, the progress toward meeting these policy goals is unclear. Therefore, this study proposes the “C–R map”, which is a correlation map between the share of coal-fired plants and renewable energy in terms of annual consumption, and the “CR index”, which is an index composed of the above two indicators. The proposed methods objectively visualise and quantitatively analyse statistical data on global climate change associated with “reducing coal and increasing renewables”, whose trends or tendencies could only be obtained through fragmented statistical data and documents. Using the proposed C–R map and CR index, an international comparative analysis was conducted on the share of coal and renewables from 1990 to 2020 in 37 Organisation for Economic Cooperation Development member countries. The results quantitatively showed that 31 member countries clearly exhibited a trend of decreasing their share of coal and increasing their share of renewables, while only five countries, i.e. Chile, Turkey, Mexico, Japan, and Korea, showed unique and inconsistent trends relative to that of the other member countries. By using the highly transparent and simple map and index proposed here based on published statistical information and objective methods, the global trend of “reducing coal and increasing renewables” can be quantitatively visualised in graphs and numerical values, which are easily understood and interpretable, even for laymen.