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The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose a novel fractional reverse accumulation, which increases the accumulation coefficient for new data to fully utilize the new information carried by the latest data. This led to the development of a novel grey model, termed the FGRM(1,1). This model was validated using renewable energy consumption data from France, Spain, the UK, and Europe, and the results demonstrated that the FGRM(1,1) outperformed other models in terms of simulation error, prediction error, and comprehensive error. The predictions indicated significant growth in renewable energy consumption for France and Spain, moderate growth for the UK, and robust growth for Europe overall. These findings highlight the effectiveness of the proposed model in utilizing new information and provide insights into energy transition and emission reduction potential in Europe.

In an era marked by rapid urbanization and increasing environmental concerns, the quest for sustainable development has become paramount. The goal of this study is to support sustainability by critically analysing and reviewing methods for reducing people's ecological footprint in urban areas. We are comparing different ways of reducing the negative effects that people living in cities have on the natural world around them. The decrease in ecological footprint was 0.688% for a 1% increase in the nanotechnological innovations. The decrease in the ecological footprint (improvement in the environment was 0.575 due to 1% increase in renewable energy). The decrease in the ecological footprint was 0.517% due to 1% increase in the adaptation readiness. The increase in the ecological footprint was 0.837% and 0.443% due to 1% increase in the inclusive growth and urbanization. Renewable energy is extremely important for civilization to become carbon neutral. It is suggested to switch from conventional fuel to clean fuel to enhance the use of energy from renewable sources to reduce global warming. It is required to increase adaptation readiness as “preparedness” to effectively use investments for adapting to climate change. Future research endeavors should delve deeper into the enduring repercussions of strategies for reducing the ecological footprint, examining how these strategies evolve over time, and adapt to the ever‐changing urban environments. The outcomes of this study possess substantial implications for policymaking, indicating that policymakers and urban planners should prioritize the adoption of holistic strategies for reducing the ecological footprint to nurture sustainable urban development. It advocates for the infusion of sustainability principles into urban policy frameworks and underscores the significance of ongoing monitoring and assessment to steer effective policy implementation. [ABSTRACT FROM AUTHOR]

This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country's broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies. [ABSTRACT FROM AUTHOR]

The variability and intermittency inherent in renewable energy sources poses significant challenges to balancing power supply and demand, often leading to wind and solar energy curtailment. To address these challenges, this paper focuses on enhancing Time of Use (TOU) electricity pricing strategies. We propose a novel method based on equivalent load, which leverages typical power grid load and incorporates a responsibility weight for renewable energy consumption. The responsibility weight acts as an equivalent coefficient that accurately reflects renewable energy output, which facilitates the division of time periods and the development of a demand response model. Subsequently, we formulate an optimized TOU electricity pricing model to increase the utilization rate of renewable energy and reduce the peak–valley load difference of the power grid. To solve the TOU pricing optimization model, we employ the Social Network Search (SNS) algorithm, a metaheuristic algorithm simulating users' social network interactions to gain popularity. By incorporating the users' mood when expressing opinions, this algorithm efficiently identifies optimal pricing solutions. Our results demonstrate that the equivalent load-based method not only encourages renewable energy consumption but also reduces power generation costs, stabilizes the power grid load, and benefits power generators, suppliers, and consumers without increasing end users' electricity charges. [ABSTRACT FROM AUTHOR]

Aiming at the challenge of demand response uncertainty to the safe and economical operation of integrated energy system, a cooperative optimal scheduling model of multi-region integrated energy system considering thermal pipe network transmission and demand response was proposed. Firstly, the energy transmission model of heat network was modeled in fine detail. Secondly, the demand response strategy was adopted for the comprehensive load, and the information gap decision theory was adopted to deal with the output uncertainty of renewable energy. Finally, the day-ahead operation scheduling scheme of the integrated energy system was proposed with the minimum dispatching cost and carbon emission penalty as the optimization objective, and various constraints were considered comprehensively. An example analysis proves that the proposed model can improve the economy of the system and the ability to absorb renewable energy. [ABSTRACT FROM AUTHOR]

There is a notable scarcity of literature addressing the complex affiliation amidst natural resources, water productivity (WPROD), and the food production index (FPI). Existing research focuses on emerging and developing countries, primarily centering on the initial objectives of sustainable development. To bridge this literature gap, our research delves into the nexus of WPROD, FPI, and total land resources (TLRS). Additionally, the study explores the persuasive roles of income (GDP) and renewable energy consumption (REC). Employing time series methodologies, we utilize the DF‐GLS unit root assessment to assess the variable static method and the Bayer‐Hanck test to scrutinize long‐term equilibrium. The primary analysis employs the least squares approach with breakpoints, supplemented by the Robust least squares method for validation. For causal relationships between variables, we deployed the Granger causality approach. Our outcomes disclose that variables are static at the first difference, indicating long‐run equilibrium among all variables. Empirical outcomes suggest a resource curse associated with TLRS, as it negatively influences both WPROD and FPI, regardless of breaks. The increase in coefficients of land resources by 1% causes decrease in water productivity and food production by −0.35% and −0.185%. In contrast, GDP and renewable energy positively impact water productivity and food production index, even in the presence of structural breaks. Robustness checks yield‐mixed outcomes, though the overall results remain significant and consistent with the main methods. Causality analysis indicates a bi‐directional linkage between natural resources, renewable energy, and water productivity, and food production, while GDP demonstrates a uni‐directional linkage in the study. We provide relevant policies under the targets of COP 27 to manage land resources in the USA. [ABSTRACT FROM AUTHOR]

The pressing necessity to curb greenhouse gas emissions due to climate change has sparked significant scientific interest in comprehending the factors behind CO2 emissions, particularly concerning environmental sustainability challenges. Nonetheless, there exists a notable gap in our understanding of how the process of urbanization interacts with the utilization of renewable energy to impact CO2 emissions. This research endeavor seeks to evaluate the complex interplay among urbanization, renewable energy, and CO2 emissions across 46 African nations spanning from 1990 to 2019. To accomplish this objective, a variety of econometric methodologies are employed, including Driscoll–Kraay standard errors, IV-GMM, and method of moments quantile regression (MMQR) panel estimations to address issues like cross-sectional dependencies, endogeneity, heterogeneity, and panel Granger causality examination. The empirical results suggest that urbanization leads to an increase in CO2 emissions, whereas the consumption of renewable energy plays a role in enhancing environmental quality by reducing CO2 emissions. A significant outcome of the study is the revelation that a combination of urbanization and renewable energy leads to a decrease in carbon emissions. Moreover, the Environmental Kuznets Curve (EKC) hypothesis is validated. Lastly, through the Dumitrescu–Hurlin panel causality test, it is uncovered that urbanization and renewable energy consumption exhibit a bidirectional relationship with CO2 emissions. To reduce dependence on fossil fuels and curb CO2 emissions, policymakers should promote renewable energy usage in urban areas. [ABSTRACT FROM AUTHOR]

Utilizing Fourier autoregressive distributed lag and Fourier Toda–Yamamoto causality methodologies, this research assesses the effects that renewable energy consumption and environmental policy had on the economic sustainability of China from 1991 to 2022. Our findings highlight the positive impacts of renewable energy use and stringent environmental policies on China's economic growth, while also pinpointing the supportive roles played by foreign direct investment, trade openness, and financial sector evolution in fostering a sustainable economic environment. Conversely, a reliance on fossil fuels emerges as a significant barrier to sustainability. Causality tests confirm the essential roles of renewable energy and environmental policies in advancing China's economic sustainability. This study underscores the critical need for integrating sustainable energy and environmental strategies within China's economic development framework, advocating for a holistic policy approach that balances economic growth with environmental conservation. This research underscores the imperative for a sustainability-centered strategy for China's economic advancement. [ABSTRACT FROM AUTHOR]

The circular economy (CE) has acquired significant interest for its potential to contribute to sustainable development (SD). The present study utilizes empirical methodology, specifically panel data analysis, to examine the distinct effects and outcomes of the circular economy and its associated factors within a unified framework. The focus is on the G20 countries from 2008 to 2021. We evaluated the influence of various CE value sources (renewable energy consumption, composting rate, repair services availability, recycling rate) and a factor-analysis-derived measure of the CE on economic, environmental, and social aspects of SD. The objective was to assess the distinct effects and outcomes of CE and its components in a unified framework—the analysis utilized panel data from G20 countries from 2008 to 2021. Our findings show a substantial influence of CE in achieving SD, with positive implications for the economy, environment, and society. However, the impact of each CE value source on the SD dimensions shows variation. While renewable energy consumption (RENEC) and composting rate (CR) lessen environmental impact, recycling rate (RR) shows no significant effect, and repair services availability (RSA) increases the Ecological Footprint (EFP). Notably, RSA is the sole CE component, showing a positive economic impact at the national level. Additionally, RENEC, RSA, and RR contribute to reducing the inflation rate (INFR). Policymakers should undertake detailed impact assessments to develop effective, tailored strategies based on each country's unique goals. The findings of this study have important policy implications, particularly in terms of emphasizing targeted strategies for implementing CE practices to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Tourism development is generally agreed upon to be a key tool in promoting economic growth, and green development has emerged as a significant idea and an efficient approach to accomplish this goal in a manner that is environmentally responsible. It is common knowledge that making the switch to renewable sources of energy may act as a catalyst for economic development in both developed and developing nations. Therefore, people all over the globe are beginning to realize the significance of advancing renewable energy's rising importance that suggests that it will be used extensively in the years to come. The purpose of this study is to examine the effect that increasing tourism and adopting renewable energy sources impact on green economic growth development in the region using the AMG test BRICS nations from 2001 to 2022. This research additionally makes use of a rigorous check by means of the CCEMG exam and the DCCEMG test. According to the findings, green economic growth is influenced favorably by the expansion of the tourist industry, renewable energy, and the digital economy, but urbanization and the rise financial industry are detrimental to green economic growth. D-H panel causality test results show that tourism development is causally related to green economic growth, green economic growth to urbanization, and green economic growth to the usage of renewable energy sources. According to these results, the management authorities of BRICS nations should embrace policies of green growth while also controlling environmental pollution in order to achieve sustainable economic development whereas in rural areas. The findings have major policy implications for the nations that make up the BRICS bloc. These implications pertain to the enhancement of tourist development, the digital economy (DIG), and financial institutions, all of which have the potential to improve environmental quality. [ABSTRACT FROM AUTHOR]

Unemployment and environmental pollution are two significant obstacles to achieving long-term development goals in most countries. The literature generally agrees that shifting the basic dynamic of economic activity from fossil energy to renewable energy sources is necessary to solve these two problems simultaneously. This paper examines the dynamic influences of renewable energy (REN) consumption on unemployment in BRICST (Brazil, Russia, India, South Africa, and Türkiye) countries using annual data spanning from 1991 to 2021. To this end, the bootstrap LM test is first used to evaluate the cointegration relationship between REN consumption, fossil fuel utilization, economic growth, and unemployment variables included in the econometric model to be estimated in the study. Then, the short and long-term connections between the analyzed variables are explored using the cross-sectionally augmented ARDL (CS-ARDL) model, which can produce consistent results when there is cross-sectional dependence and slope heterogeneity and when the variables exhibit different stationarity properties. Findings from the bootstrap LM test provide evidence of a long run cointegration association between the variables. Moreover, the CS-ARDL model estimation results demonstrate a negative but statistically insignificant connection between REN consumption and unemployment and that economic growth and fossil fuel usage significantly reduce unemployment in the short and long run. These outcomes suggest that the proportion of REN in total energy consumption in BRICS-T nations has yet to reach a sufficient level to realize its potential to reduce unemployment and/or that the economies of these countries depend on traditional energy. The findings also confirm the validity of Okun's Law in the sample nations. [ABSTRACT FROM AUTHOR]

Investing in renewable energy is of utmost importance, especially in the context of addressing climate change. However, while numerous studies have explored the role of renewable energy in achieving carbon neutrality, there is a noticeable gap in the literature regarding how uncertainties affect the impact of renewable energy on electric power CO2. To bridge this gap, the present study employs recently developed nonparametric techniques, namely multivariate quantile-on-quantile regression (MQQR) and time-varying quantile causality (TVQC), to investigate the relationship between renewable energy and electric power CO2 in the presence of uncertainties. The study utilizes monthly data spanning from January 1988 to May 2023. The bivariate results reveal that renewable energy and low uncertainties contribute to improving ecological quality by reducing electric power CO2. Furthermore, the multivariate quantile-on-quantile regression results highlight the substantial influence of low uncertainties on the impact of renewable energy in lowering electric power CO2. Additionally, the TVQC analysis demonstrates that both renewable energy and uncertainties possess predictive power regarding electric power sector CO2. The study discoveries showcase that the influence of renewable energy on electric power CO2 is subject to external moderation. The suggested policy framework in this study is structured to assist the United States in accomplishing the goals outlined in SDG 7. [ABSTRACT FROM AUTHOR]

This study examines the impacts of renewable and non-renewable energy consumption, urban population, and population size on economic growth. This study utilizes the Panel Unit Root Test, Pedroni's Residual-based Cointegration Test, and Fully Modified Ordinary Least Square (FMOLS) techniques to analyze data from 2010 to 2021 for 19 countries within the Group of Twenty (G20). The cointegration test indicates that renewable energy consumption, nonrenewable energy consumption, urban population, and total population are long-term associated with GDP growth. According to FMOLS estimates, renewable energy consumption has a positive impact on GDP growth in G20 countries. The impact of renewable energy consumption on GDP growth varies; natural gas consumption does not affect GDP growth, but petroleum consumption significantly affects GDP growth in G20 countries. Furthermore, the study identifies the urban population as a control variable that harms GDP growth. The empirical evidence derived from this study posits that it would be judicious for G20 policymakers to proactively institute a suite of policies that invigorate the advancement of renewable energy sources, given that such a course of action has been demonstrated to engender a notable augmentation in GDP growth. [ABSTRACT FROM AUTHOR]

The insufficient flexibility of the hybrid renewable integrated energy system (HRIES) causes renewable power curtailment and weak operational performance. The regulation potential of flexible buildings is an effective method for handling this problem. This paper builds a regulation model of flexible heat load according to the dynamic heat characteristics and heat comfort elastic interval of the buildings, as well as a regulation model of the flexible electrical load based on its transferability, resectability, and rigidity. An operation optimization model, which incorporates flexible regulation of multiple loads and a variable load of devices, is then developed. A case study is presented to analyze the regulation and synergy mechanisms of different types of loads. Its results show a saturation effect between heat and electrical loads in increasing renewable energy consumption and a synergistic effect in decreasing the operating cost. This synergy can reduce the operating cost by 0.73%. Furthermore, the operating cost can be reduced by 15.13% and the curtailment rate of renewable energy can be decreased by 12.08% when the flexible electrical and heat loads are integrated into the operation optimization of HRIES. [ABSTRACT FROM AUTHOR]

A comprehensive approach addressing the key factors exacerbating pressure on the environment is required to minimize the damages caused by global warming and environmental destruction. For this purpose, the present study investigates the effects of renewable energy consumption (REC) and natural resource rents (NRRs) on environmental degradation within the scope of the environmental Kuznets curve (EKC) hypothesis for ASEAN-5 countries. Differing from most previous studies, this research represents environmental degradation by using the ecological footprint pressure index, which considers both the supply and demand aspects of the environment. The present study covers the period between 1990 and 2018. This study employs the Method of Moments Quantile Regression (MMQR), an advanced panel technique that yields reliable results on the outlier issue, endogeneity, and non-normal distribution. The MMQR results confirm the EKC hypothesis, assuming the presence of an inverted U-shaped relationship between economic growth and environmental degradation. Moreover, the results reveal that REC and NRRs reduce environmental degradation in all quantiles. Given these results, policymakers in the ASEAN-5 countries are recommended to utilize productivity gains from natural resource rents for investment in clean energy and to shift their energy consumption policies towards renewable energy technologies and research. [ABSTRACT FROM AUTHOR]

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market. [ABSTRACT FROM AUTHOR]

Demand-side flexible load resources, such as Electric Vehicles (EVs) and Air Conditioners (ACs), offer significant potential for enhancing flexibility in the power system, thereby promoting the full integration of renewable energy. To this end, this paper proposes an optimal allocation method for demand-side flexible resources to enhance renewable energy consumption. Firstly, the adjustable flexibility of these resources is modeled based on the generalized energy storage model. Secondly, we generate random scenarios for wind, solar, and load, considering variable correlations based on non-parametric probability predictions of random variables combined with Copula function sampling. Next, we establish the optimal allocation model for demand-side flexible resources, considering the simulated operation of these random scenarios. Finally, we optimize the demand-side resource transformation plan year by year based on the growth trend forecast results of renewable energy installed capacity in Jiangsu Province from 2025 to 2031. [ABSTRACT FROM AUTHOR]

The excessive use of energy from fossil fuels, which corresponds to population, industrialisation, and unsustainable economic growth, is the cause of carbon dioxide production and climate change. The Water–Energy–Food (WEF) nexus is an applicable conceptual framework that helps manage the balance between human development and natural resource constraints, and it becomes a valuable tool to address the challenges of resource depletion and clean energy. This article aims to analyse the relationship between the WEF nexus and clean energy through a statistical analysis and a systematic review of knowledge on energy sustainability. The methodology involves the selection of bibliographic information databases such as Scopus and Web of Science (WoS), a statistical analysis, specifically the Scientometrics applied to the information obtained, and the identification of 179 scientific publications related to the study variables through a screening process called Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The interaction of green energy and sustainability with the WEF nexus has been approached mainly by developed countries such as China (10%), the United States (9.49%), India (7.26%), and Brazil (5.02%). The review of 55 scientific papers identified strategies that balance economic growth and environmental impact, applying clean energy systems (e.g., solar and wind), and the importance of adaptation to the subsystems of the WEF nexus. This study also highlights adaptability to climate change in rural and urban communities. Therefore, it is consistent with the four pillars of sustainable development (Economic: 7 papers, Environmental: 22, Social: 18, and Cultural: 8). This study highlights the following: (a) the importance of the use of renewable energy either in mixed systems and consumption, energy storage, and seeking energy efficiency in systems adapted to diverse environments and (b) the relevance of community participation in the decision-making process for the use of clean energy, such as a strategy for climate change adaptation. [ABSTRACT FROM AUTHOR]

Given the increasing investment by Belt and Road Initiative (BRI) participants in the renewable energy industry, it is imperative to ascertain how much this investment contributes to economic growth. The objective of this study is to ascertain the extent to which renewable energy contributes to economic growth within the Belt and Road Initiative compared to non-renewable energy sources. Prior studies have yet to incorporate oil prices as a variable in the production function, among other output aspects. This study integrates the inclusion of real oil prices as a variable within the production function alongside capital, labor, renewable energy consumption, and non-renewable energy consumption. A cohort including 49 Belt and Road Initiative participants was formed, encompassing data from 1990 to 2019. The data has undergone an initial examination to assess cross-sectional dependence, slope heterogeneity, and structural break(s), and are verified. Hence, third-generation panel data analysis has been utilized. The continuously updated fully modified estimator and continuously updated biased corrected estimator provide evidence supporting the notion that renewable energy plays a substantial role in fostering economic growth within nations participating in the Belt and Road Initiative. Furthermore, this contribution is found to be more pronounced when compared to the impact of non-renewable energy sources. The study's findings inform policy recommendations at both the BRI and national level. [ABSTRACT FROM AUTHOR]

In low-voltage power distribution station areas (DSAs), sensor devices and communication networks are often inadequate. Therefore, the control strategies mainly used for soft open points (SOPs) based on global information in medium-voltage distribution networks are difficult to be directly applied to low-voltage DSAs. This paper proposes a novel control strategy for SOP that only requires collecting the local information of SOP and the load rate of transformers. It aims to address the issues faced of voltage violations at the end of feeders and the load rate imbalance among adjacent DSAs under the current high penetration of renewable energy sources. In this paper, first, a sensor network consisting of sensor devices located at the transformers and each port of the SOP is introduced for information collection. Then, based on the sensitivity relationship between the node voltage and the injected power, considering capacity and voltage safety constraints, the adjustable range of the active power output for each port of the SOP is derived. According to this range, the operating states of the DSAs are categorized into four scenarios. For each scenario, the adjustment amount of SOP output power is determined to achieve comprehensive regulation of terminal voltage and load rate of all DSAs interconnected by SOP. Finally, the effectiveness of the proposed strategy is verified based on a simulation model of three flexible interconnected DSAs established in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Using the QARDL approach and data from January of 2010 to May of 2022, we explore how renewable energy consumption affects CO2 emissions in the USA. Long-term analysis reveals a negative link between these variables, while only lower quantile levels show short-term statistical significance. Integrating technical innovation (measured by patents) in our QARDL model shows substantial reduction in CO2 emissions, with varying effects over time. Interestingly, only renewable energy consumption, not technical innovation, significantly impacts CO2 emissions at lower quantile levels. These findings emphasize the crucial role of renewable energy in reducing both short-term and long-term CO2 emissions and offer policymakers valuable insights for shaping effective energy strategies to combat emissions and promote sustainability in the USA. [ABSTRACT FROM AUTHOR]

The Russia-Ukraine war and other similar conflicts across the globe have heightened risks to the United States of America's (USA's) energy security. However, little is known about the severity of the effect of energy security risks on the USA's quest to attain net-zero emissions targets by 2050. To this end, we examine the effect of energy security risks on the load capacity factor (LCF) in the USA. Employing a time series dataset spinning from 1970 to 2018, the results of the Dynamic Autoregressive Distributed Lag (ARDL) simulations model suggest that energy security-related risk hampers the long-term net-zero emissions targets with its effect decreasing over time until it varnishes in about 5 years time. The results also show that foreign direct investment (FDI) inflows, renewable energy consumption, and green technology have long- and short-run positive effects on the LCF. Conversely, economic expansion and urbanization impede environmental quality by lowering the LCF both in the long run and short run. These findings are upheld by the outcomes of the multivariate quantile-on-quantile regression. Therefore, the study advocates for the consumption of renewable energy, investment in green technologies, and FDI inflows to mitigate energy security-related risks and attain the net-zero emissions targets by 2050 in the USA. [ABSTRACT FROM AUTHOR]

Adopting renewable energy consumption is one of the most important aspects of international efforts to combat climate change, improve energy security, and encourage the shift to a more robust and sustainable energy system. Therefore, the empirics and policymakers worldwide are searching for factors that can promote renewable energy consumption. This analysis intends to investigate the role of financial globalization and tourism on renewable energy consumption in Asia and sub-regions such as Central Asia, East Asia, South Asia, Southeast Asia, and West Asia. The analysis utilized the linear and nonlinear CS-ARDL methods. Long-run outcomes of the linear and nonlinear models confirm that a rise in financial globalization and tourism promotes renewable energy consumption in Asia and all sub-regions. However, the nonlinear model highlights that a fall in financial globalization hurts renewable energy consumption in Central and South Asian regions, and tourism only hurts renewable energy consumption in Asia. In addition, ICT, GDP, and GHG emissions help promote renewable energy consumption. These results suggest that Asian policymakers must increase collaboration in the financial sectors and promote sustainable tourism in the regions to promote renewable energy consumption. [ABSTRACT FROM AUTHOR]

This study uses two empirical approaches to explore the asymmetric effects of oil and coal prices on renewable energy consumption (REC) in China from 1970 to 2019. As a conventional approach, we used the nonlinear autoregressive distributed lags (NARDL) model, while machine learning was used as a non-conventional approach. The empirical findings of the NARDL indicate that oil and coal price fluctuations have a significant effect on REC for both the short and long term. The results of the non-conventional approaches based on machine learning indicated that the SVM model was more efficient than the KNN model in terms of accuracy, performance, and convergence. Referring to the SVM model findings, the results show that an increase in the coal price has a higher ability to predict REC than the oil price. As a robustness check, we also find that an increase in Brent prices significantly decreases REC. The findings of this study support the view that there is a substitution effect from oil to coal before initiating the use of renewable energy in China. [ABSTRACT FROM AUTHOR]

Motivated by the study country’s active involvement in the reduction of global greenhouse gas emissions and the positive strides it has made domestically in increasing renewable energy in its energy mix, on the one hand, and the need to find out whether renewable energy consumption can also assist in reviving the economy, on the other hand, this study empirically examines the dynamic impact of renewable energy consumption on economic growth in Zimbabwe. Using annual time-series data from 1990 to 2019, and the autoregressive distributed lag approach, the results of the study show that in Zimbabwe, renewable energy consumption has a positive impact on economic growth, both in the short and long run. Increasing the usage of renewable energy increases the growth of the economy in the country of study. These results imply that Zimbabwe can achieve two goals using one strategy – increasing renewable energy consumption to decrease the negative impact climate change and greenhouse gas emission have on the environment and the economy, and increasing economic growth. Policy makers in Zimbabwe are, therefore, recommended to support increased use of renewable energy over alternative energy sources, as this would have positive implications on the economy, both in the short and long term. [ABSTRACT FROM AUTHOR]

[Display omitted] • The impact of renewable and non-renewable energy on human development is explored. • Method of moments panel quantile regression is employed. • Human development is positively affected by renewable energy. • Non-renewable energy has a robust negative effect on human development. • The bidirectional causality exists between HDI - renewable and non-renewable energy. Modern social and economic organization forms have increasingly expanded energy usage, and these shifts in energy consumption have had a major impact on human development across the globe. The important question the current study addresses is assessing the heterogeneous effects of energy consumption (renewable and non-renewable) on the human development of the Group of Seven countries during 1991–2015 by applying a novel method of moments panel quantile regression. Interestingly, the most striking finding of the current study reveals that the impacts of renewable and non-renewable energy consumption on the human development index are diverse at different quantiles. The influence of renewable energy consumption is heterogeneous and significantly positive at different quantiles, with the lowest quantiles having the strongest impact and the highest quantiles having the least impact. Besides, the impact of non-renewable energy consumption is also heterogeneous on the human development index. The effect of non-renewable energy consumption is significantly negative for all the quantiles, with the size of the negative effect getting bigger for higher quantiles. In addition, our results show that renewable and non-renewable have a bidirectional causal relationship with the human development index. These novel findings will assist government officials as well as policymakers in better understanding how energy consumption influences human development. [ABSTRACT FROM AUTHOR]

The present study aims to examine the long run impacts of per capita income, renewable energy consumption, urbanization, trade openness on ecological footprint in Morocco over the period 1980-2021. It also attempts to explore the validity of the Environmental Kuznets Curve (EKC) hypothesis. To achieve this goal, an extended population, affluence, and technology model (STIRPAT) was employed using the Augmented Autoregressive Distributed Lag (AARDL). The findings reveal the existence of a long-term cointegration relationship between the variables and confirm the EKC hypothesis. [ABSTRACT FROM AUTHOR]

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This study contributes significantly to existing literature by examining the link between innovation in photovoltaic energy generation, distribution, and transmission technologies and CO2 emissions, with international collaboration in green technology development, gross domestic product per capita, financial development, and renewable energy consumption in China from 1990Q1 to 2018Q4. First, the findings indicated that the international collaboration in green technology development enabled China to jointly develop a new green technology that not only improves the efficiency of energy technologies but also contributes to CO2 emission mitigation. Second, the findings suggested that the innovation in photovoltaic energy generation, distribution, and transmission technologies has a significant impact on enhancing environmental quality. Third, an increase in renewable energy consumption was negatively associated with CO2 emissions, while an upsurge in gross domestic product per capita was positively associated with CO2 emissions. Lastly, the results inferred that an increase in financial development led to a reduction in CO2 emissions. This paper suggests that the government should change its policies to encourage private investors to put their money into innovation in photovoltaic energy generation, distribution, and transmission technologies to promote eco-friendly energy production, consumption, and ecological sustainability for future generations. [ABSTRACT FROM AUTHOR]

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This paper investigates the persistence of shocks on non-renewable and renewable energy consumption for 15 leading countries by renewable energy consumption, over the period 1980–2018. For this aim, we apply Christopoulos and Leon-Ledesma (J Int Money Finance 29(6):1076–1093, 2010) Fourier ADF unit root test which structural breaks are included by using a trigonometric function to allow for smooth temporary mean changes rather than jump functions. In application, we do not need to specify the numbers, locations and the forms of the structural breaks a priori. The results give that shocks on non-renewable energy consumption per capita are persistent for 13 countries except Sweden and the United States; shocks on renewable energy consumption per capita are persistent for 12 countries except Canada, Sweden and the United Kingdom. Overall, we conclude that persistent policy implications on non-renewable energy consumption are more effective tool than transitory policy stances for 13 countries except Sweden and the United States whereas persistent policy implications on renewable energy consumption are more effective for 12 countries except Canada, Sweden and the United Kingdom. In other words, since the energy consumption returns to its trend path quickly, any policy will not be effective on non-renewable energy consumption for Sweden and the United States, and also on renewable energy consumption for Canada, Sweden and the United Kingdom. [ABSTRACT FROM AUTHOR]

In line with the importance of SDG-7, a number of studies have endeavored to divulge the changes in renewable energy consumption (REC); however, the literature fails to either understand the importance of technology i.e., information communication technologies (ICT) and macroeconomic uncertainty in this context or employ robust econometric techniques. This research paper extends the prior literature by focusing on technology and macroeconomic uncertainty as novel determinants in addition to natural resources, human development, globalization, and economic growth as control variables of renewable energy for the top 10 renewable energy-consuming countries by applying several second and third generation econometric tests on annual data from 1990 to 2017. The empirical estimations determine ICT as a crucial factor of renewable energy, suggesting that it significantly triggers REC in the top economies. Conversely, the detrimental effects of uncertainty tend to shrink REC. Furthermore, natural resources, human development, globalization, and economic growth significantly boost REC as consistent with the existing literature. Based on these findings, this study suggests several SGD-oriented policies. [ABSTRACT FROM AUTHOR]

Economic growth—through growth affordability, growth investments, and growth-awareness associations—may lead to increased access to clean fuel and technologies for cooking (ACF&T). The current paper presents the trend and comparative analyses regarding GDP per capita, access to clean fuels and technologies for cooking, and renewable energy consumption (REC) in the South Asian economies. The data from Bangladesh, India, and Pakistan between 2000 and 2020 shows a strong positive correlation between GDP per capita and access to clean cooking technologies. India has made the most significant improvements, followed by Pakistan and Bangladesh. All three economies negatively correlate GDP per capita and renewable energy consumption. Bangladesh shows the steepest decline, followed by India and Pakistan, indicating a more pronounced shift towards nonrenewable energy sources as economic prosperity increases. The study concludes that economic development often involves transitioning from traditional renewable energy sources (such as biomass) to more modern, nonrenewable energy sources (such as fossil fuels), often more efficient and reliable for industrial and large-scale energy needs. Hence, developing infrastructure and industrial sectors might lead to higher consumption of nonrenewable energy sources. This points to a potential challenge for sustainable development, as increased economic prosperity might be accompanied by more significant environmental impact unless there are concerted efforts to promote renewable energy sources.

ABSTRACTThis study examines the relationships between CO2 emissions, GDP, renewable energy consumption, and trade openness across 37 OECD countries from 1995–2020. Using a Panel Vector Autoregressive (PVAR) model and Granger Causality tests, the research probes the causality among these factors. Key findings show a notable causality from GDP, renewable energy, and trade openness to CO2 emissions. Specifically, lags in renewable energy consumption and trade openness significantly decrease CO2 emissions. Surprisingly, GDP's influence on CO2 emissions is found to be negligible, challenging the typical belief linking economic growth to environmental degradation. These insights hold great value for policymakers in environmental governance and climate finance. The data underscores the importance of promoting renewable energy and trade openness for effective CO2 reduction. The study advocates a sustainable environmental governance model, emphasizing strong legal structures and clarity in execution. Since GDP doesn't significantly impact CO2 emissions, there's potential to pivot towards sustainable economic growth models. The research offers a foundational empirical groundwork, suggesting that expanding future studies to include diverse variables might yield a more comprehensive understanding of the relationships in question.

ABSTRACTThis study examines the impact of capital market on the relationship between energy consumption and carbon emissions. By employing a system Generalised Methods of Moments (GMM) for a sample of 138 developing countries over the period, 1990–2020, we find a U-shaped reverse relationship between renewable energy consumption and carbon emissions. The study reveals that beyond a threshold of 71.03, renewable energy consumption tends to increase carbon emissions. Similarly, the initial levels of carbon emissions reduce the use of renewable energy but beyond a 2.5 level of carbon emissions, renewable energy consumption begins to increase. We find that both the stock market and bond market reduce carbon emissions and enhance the levels of renewable energy consumption. We provide evidence to support that the capital market enhances the negative impact of renewable energy consumption on carbon emissions, while the corporate bond market magnifies the reductive effect of carbon emissions on renewable energy consumption.

Abstract In order to solve the collaborative optimization scheduling of multi‐microgrid under the high penetration rate of new energy, this paper considered the energy interaction between micro‐grids in multi‐microgrid and the relationship between new energy consumption and electricity cost, constructed a collaborative scheduling model considering both micro‐grid load and main grid wind and optical energy storage, proposed objective function based on economic cost, and improved Genetic Algorithm (GA). The elite thought and catastrophe thought are used to optimize the selection operation, and the particle swarm optimization algorithm is used to optimize the mutation operation. Furthermore, three scenarios were selected to verify the effectiveness of the proposed model and the improved GA. The results show that the proposed model can ensure the stable operation of the multi‐microgrid system with a high proportion of new energy access and reduce the operation cost. In addition. the improved algorithm solves the problems of easy to fall into local optimum and slow iteration speed, and has better performance in solving the model.

This study investigates the impacts of agriculture and renewable energy consumption on CO2 emissions in South Korea from 1980 to 2023, highlighting both challenges and opportunities for environmental sustainability. Utilizing bootstrap ARDL, FMOLS, and CCR methodologies, the analysis reveals that traditional agricultural practices significantly increase CO2 emissions, underscoring the urgent need for sustainable agricultural reforms. Conversely, renewable energy consumption effectively reduces CO2 emissions, thereby supporting the nation’s transition towards sustainable energy sources. Additionally, control variables such as industrial activity, urbanization, energy prices, and government environmental policies exhibit significant effects on CO2 emissions. Specifically, industrial activity and urbanization contribute to increased emissions, whereas higher energy prices and stringent environmental policies are associated with reduced emissions. These findings highlight the necessity for targeted agricultural and energy sector reforms to achieve a balance between economic growth and environmental preservation. Robustness tests confirm the stability of these relationships, providing a reliable foundation for policymakers to develop effective strategies for a sustainable future in South Korea.

Adverse consequences are observed in developing countries due to the impact of the globalization process. Therefore, our study aims to empirically verify whether globalization escalates carbon dioxide emissions in selected N-11 (next-11) countries between 1990 and 2019. The study also analyzes how per capita GDP, per capita GDP2, population growth, and renewable energy consumption affect carbon emissions. For this reason, the researchers used several econometric methods, including the slope homogeneity test, the cross-sectional dependency test, the panel unit root test, the panel cointegration test, the method of moment’s panel quantile regression analysis, and the Wald test. The estimated results of panel quantile regression show how carbon emissions change across a range of quantiles (0.1 to 0.9). The findings show that per capita GDP significantly impacts the overabundance of carbon emissions in N-11 countries. Over time, the study found that the positive coefficient value of per capita GDP decreased from the first to the last (7.41 to 5.87), leading to the validation of the EKC hypothesis. The adverse correlation between per capita GDP2 and environmental contamination confirms that the Environmental Kuznets Curve hypothesis is valid for selected N-11 countries. Globalization deteriorates the environment by directly affecting CO2 emissions. It increases monotonically from the lower quantile to the upper quantile (0.972 to 1.002). At the quantile level of 0.1 to 0.9, population growth and renewable energy consumption increase impede carbon dioxide emissions in these selected countries. Coefficient values in the quantile 0.1 to 0.9 (-0.35 to -0.53) suggest that governments can reduce carbon emissions more due to renewable energy consumption over time. But the negative coefficient values of the population (-0.97, -0.93, -0.90, -0.88, -0.86, -0.85, -0.83, -0.81, and -0.77) decrease from the lower quantile to the upper quantile. The Wald test supports the asymmetric effects of different quantiles. As a robustness check of estimators, the study used FMOLS, DOLS, and CCR, which show the variables’ long-run elasticity. The research developed targeted policy recommendations for sustainably mitigating carbon emissions based on the above results.

This study examines the relationship between Hofstede’s six cultural dimensions and renewable energy consumption, considering global evidence from 99 countries using a panel data framework for the period covering 1991–2018. Employing a pooled ordinary least square model and Lewbel two-stage least squares technique, we find that the power distance index, uncertainty avoidance index, masculinity index, and long-term orientation index negatively influence renewable energy consumption. In contrast, the indulgence index has a positive impact on renewable energy consumption. Moreover, we find that the impact of the individualism index on renewable energy consumption is mixed. A battery of alternative econometric techniques, including the Driscoll–Kraay estimator, ensures the robustness of the results. Finally, the empirical evidence suggests policy reforms and global initiatives to integrate cultural traits into national strategies for renewable energy consumption, in order to achieve the sustainable development goals.

Abstract Sub-Saharan Africa (SSA) has experienced a high economic growth rate over the last two decades, which has been accompanied by concerns about increasing carbon dioxide (CO2) emissions. This study aims to find out whether renewable energy and agriculture can help reduce CO2 emissions for selected SSA countries. A balanced dataset incorporating CO2 emissions, renewable energy consumption, agricultural land per capita, GDP per capita, urbanization level and energy intensity of 38 SSA countries covering the period 2000–2019 is utilized. The differentiated-generalized method of moments (GMM) is employed as a benchmark estimation method to estimate the effects of renewable energy and agriculture on CO2. The regional heterogeneity analysis of countries at different income levels is then carried out. The moderating role of government governance in the energy-agriculture-environment nexus is also investigated. The following conclusions are highlighted: (1) the consumption of renewable energy can reduce CO2 emissions, while agriculture increases them; (2) the mitigating effect of renewable energy on CO2 emissions is relatively larger in countries at a low income level countries than in high-income countries, while agriculture aggravates CO2 emissions in lower middle-income and low-income regions, but mitigates emissions in upper middle-income regions; and (3) governance quality turns the mitigating role of renewable energy use on CO2 emissions into an increasing one, and exaggerates the polluting effect of agriculture. Finally, the study proposes policy implications for improving renewable energy use and green agricultural growth to achieve sustainable development in SSA.