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In considering today's energy challenges, the link between the usage of renewable and non-renewable energy sources and economic growth has gained substantial policy attention. This research examines the complex relationship between these three variables to understand how non-renewable energy consumption and renewable energy consumption interact and what that means for economic growth. This study uses the Granger causality approach to explore the relationships between non-renewable energy consumption, renewable energy consumption, and economic development. It draws on a comprehensive dataset from the Word Bank database, including 152 nations from 1990 to 2019. The analysis is further disaggregated by four subgroups of countries; least developed, developed, transitional economies and developing countries. The result of this study provides valuable empirical evidence of uni-directional causality running from renewable energy consumption to economic growth and non-renewable energy consumption to economic growth in transitional economies. Furthermore, policymakers should focus on both variables when making decisions because the results show that energy consumption and economic growth are interconnected. Implementing global energy efficiency standards, reducing fossil fuel usage, and adopting regulatory measures are all viable policies for limiting adverse effects on the environment while encouraging economic development.

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Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth.

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Amidst pressing global environmental challenges, exacerbated by climate change and the imminent threat of global warming, there is a critical need to assess the efficacy of environmental policies. This study centers its attention on the pivotal role of these policies in addressing environmental concerns. Specifically, our research aims to scrutinize the impact of stringent environmental policies on environmental quality under the theoretical underpinnings of environmental Kuznets curve. To achieve this objective, the study collected data from BRICS-T economies over the period of 1990-2020. This study employed the method of moments quantile regression technique for empirical analysis. Our study validates the presence of the Environmental Kuznets curve (EKC hypothesis). Empirical findings reveal the sustained significance of environmental stringency across all quantiles, demonstrating a positive correlation in lower quantiles and a negative correlation in higher quantiles. At lower quantiles, the impact is insignificant initially, but pronounced due to efficiency improvements induced by stringent policies. The effects became negative at middle quantiles, indicating stringent policies might encounter diminishing returns where policy measures start stabilizing ecological impacts. At higher quantiles, the influence of ESI remains significant, reflecting ongoing adaptations in larger economies with higher ecological footprints. This suggests the potential effectiveness of stringent regulatory measures in mitigating environmental impacts and reducing ecological footprints. The identified inverted U-shaped curve signifies that while stringent policies may not inherently enhance environmental health, beyond a certain threshold, they can indeed contribute to its improvement. Our policy recommendation advocates for the widespread adoption and promotion of such stringent measures to safeguard environmental health.

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In an exploration of environmental concerns, this groundbreaking research delves into the relationship between GDP per capita, coal rents, forest rents, mineral rents, oil rents, natural gas rents, fossil fuels, renewables, environmental tax and environment-related technologies on CO2 emissions in 30 highly emitting countries from 1995 to 2021 using instrumental-variables regression Two-Stage least squares (IV-2SLS) regression and two-step system generalized method of moments (GMM) estimates. Our results indicate a significant positive relationship between economic growth and CO2 emissions across all quantiles, showcasing an EKC with diminishing marginal effects. Coal rents exhibit a statistically significant negative relationship with emissions, particularly in higher quantiles, and mineral rents show a negative association with CO2 emissions in lower and middle quantiles, reinforcing the idea of resource management in emissions reduction. Fossil fuels exert a considerable adverse impact on emissions, with a rising effect in progressive quantiles. Conversely, renewable energy significantly curtails CO2 emissions, with higher impacts in lower quantiles. Environmental tax also mitigates CO2 emissions. Environment-related technologies play a pivotal role in emission reduction, particularly in lower and middle quantiles, emphasizing the need for innovative solutions. These findings provide valuable insights for policymakers, highlighting the importance of tailoring interventions to different emission levels and leveraging diverse strategies for sustainable development.

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Environmental degradation poses a significant challenge in many developing countries, as they heavily rely on fossil fuels to drive economic activities. The transition towards renewable energy is crucial to mitigate ecological depletion, yet numerous Asian developing countries may struggle to achieve the desired levels of renewable energy adoption due to financial constraints. Foreign aid in the energy sector can expedite this transition process. This study aims to examine the impact of foreign aid on the energy decarbonization transition in 22 Asian developing countries from 2003 to 2022 to analyze its contributions and challenges to promote renewable energy adoption. This paper incorporates the two types of foreign aid in the energy sector (nonrenewable and renewable energy aid) provided by the OECD to developing economies. Utilizing the System-Generalized Method of Moments (Sys-GMM), the findings reveal that energy aid significantly contributes to the transition towards energy decarbonization by providing financial support for embracing renewable energy technologies. Specifically, the analysis indicates that a 1% increase in energy aid leads to approximately 3% enhancement in the decarbonization transition process. Moreover, this study adds to the existing body of knowledge by examining the mediating impact of human capital and financial development as well as the moderating effect of institutional quality and demand for clean fuel. These factors play a pivotal role in energy decarbonization transition by fostering financial development and enhancing human capital through capacity-building initiatives and facilitating the adoption of renewable energy technologies.

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This paper investigates the effects in short and long run of renewable and non-renewable energy, technological advancement, population, foreign direct investment, energy export, energy price, and carbon dioxide emissions on economic growth in Saudi Arabia as one of the largest oil producing and richest countries in the world and as a leading country in investing in modern technology, during 1990-2022 by using the Autoregressive Distributed Lag(ARDL) approach and the Vector Error Correction Model (VECM) Granger causality technique. In first step, the ADF and DF-GSL tests are used to identify the order of integration of variables. In the second step, the Bounds test and the Wald test are used respectively to verify the existence of long run cointegration relationships and the long run relationships between variables. In the third step, we have applied the ARDL approach to capture the effect of each variable on Saudi economic growth in long term. Finally, the VECM technique was used to detect the direction of causality running from variable to another. It is appearing that all variables are stationary in first difference, and there are a long run cointegration and relationships among variables. The results of ARDL estimation show that non-renewable energy, renewable energy, population, foreign direct investment, energy export, and energy price positively affect the Saudi economic growth. While technological advancement and carbon dioxide emissions have negative effects on the economic increase of Saudi Arabia. These two results appear important and useful because of their consequences. In effect, it could damage its worldwide standing and dishearten foreign investment, stopping economic diversification efforts and increasing the income inequality. Though, the results of VECM technique show four bidirectional causal relationships between economic growth and non-renewable energy, foreign direct investment, energy export, and energy price. The findings of this study have several policy implications for Saudi Arabia. First, Saudi government should continue investing in the energy sector. Second, to attract more FDI, Saudi government should continue its efforts to reduce bureaucracy, simplify regulations, and provide a business-friendly environment. This strategy can help transfer technology and knowledge. Third, the government should monitor and control energy prices, as these can significantly impact economic growth. The government should invest in technological advancement, as this can help reduce carbon dioxide emissions and improve energy efficiency; also, investing in human capital is essential for long-term economic growth. Policies that promote the health, education, and general well-being of the population can lead to a more productive and innovative workforce. However, the article reveals that technological advancements have a negative impact on economic growth in Saudi Arabia. This could be due to a number of factors, such as a lack of skilled workers to implement new technologies or a mismatch between the skills of the workforce and the needs of the economy. As solutions, Saudi government must invest in education and training can help address these challenges by developing a workforce capable of adapting to the changing needs of the economy and effectively using new technologies. Also, it's important to create science and technology parks to foster innovation and collaboration between businesses and universities. By taking these steps, the Saudi government can help create more diverse and knowledge-based economy, making it less dependent on oil and gas exports and more resilient to economic shocks.

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Fossil fuels will still dominate energy in twenty years despite green power rising. The aim of the study is to analyze the factor substitution, emission mitigation, and technological progress among energy and non-energy inputs in Pakistan. The trans-log production method is employed to analyze the viability of energy substitution and then measure the CO2 emission reduction possibility that comes from such adoption. The results suggest the following: (1) the influence of renewable energy and nonrenewable energy on economic growth is optimistic and is increasing return to scale. However, it has the potential to contribute a 7% growth-share if capital investment is doubled beyond the present levels. (2) Output elasticity between renewable and nonrenewable energy factors is elastic and, on average, is estimated by 0.096 and 1.007. (3) Energy substitution is possible with an average of 0.852, which presents that Pakistan has the capability of moving from nonrenewable energy to renewable energy. (4) Two investment scenarios show significant results and suggest that nonrenewable energy substitution for renewable energy has the potential to lessen CO2 emissions without reducing the economy. Finally, energy substitution is possible from technical perspectives and inputs show strong convergence differences in technical progress. Comprehensive capital growth, technological progress, and low-carbon technological efforts can be a better fit for attaining carbon-reduction and sustainable economic growth.

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The Connect 2030 initiative, launched by the International Telecommunication Union, is in alignment with the Sustainable Development Goals (SDGs) of the United Nations Agenda 2030. Its main objective is to achieve universal connectivity, a goal that is closely related to environmental issues. This topic currently receives attention from researchers and policymakers. Given these considerations, our study investigates the impact of information and communication technologies on carbon dioxide emissions for a panel of 84 countries spanning the years 2009 to 2020. Using principal component analysis, we construct an ICT index that encompasses international bandwidth, reflecting the universal connectivity, and participation in international data exchanges. The empirical analysis applies the pooled mean group-panel autoregressive distributive lag (PMG-ARDL) approach to estimate both the long-run and short-run coefficients of CO2 emissions' determinants. Our findings show that ICT and renewable energy mitigate CO2 emissions, unlike financial development, GDP, and non-renewable energy, which contribute significantly to emissions for the full sample. These outcomes suggest that promoting ICTs in general and international bandwidth in particular, as part of universal connectivity, improves the quality of the global environment.

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This study aims to evaluate the relationship between renewable and non-renewable energy consumption and economic growth in post-Soviet Eurasian countries by employing panel data from 15 countries from 1996 to 2018. The results reveal that the contribution of renewable energy consumption (REC) to economic growth is greater than non-renewable energy consumption. The overall findings imply that the transformation of energy consumption from non-renewable to renewable offers environmental advantages and growth opportunities. Furthermore, the transition to renewables may also expand the range of foreign relations policy options available for these countries, which, in turn, might contribute to a better alignment with evolving global regimes. Transition demands towards the long-term sustainability of global energy sources put pressure on countries to expand their domestic policy efforts and join international cooperation efforts. Therefore, post-Soviet Eurasian countries should develop strategic policy mechanisms and reforms designed to accelerate investments in renewable energy technologies.

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Ecological footprint (EFP) measures the amount of area, that is land or sea, which is required to absorb the waste generated through human activities or to support the production of resources consumed by populations. EFP index therefore includes six dimensions that are cropland, forestland, carbon, fishing grounds, grazing land, and built-up area. Human activities have impacted the environment, leading to global warming, widespread droughts, and diseases. The present study aims to investigate the role of renewable energy (RE) and energy efficiency on the EFP index. Past researchers have widely used carbon emission (CE) to represent environmental impact, and recent studies have shown that EFP index is a better proxy of environmental degradation. Therefore, the present research differs from past studies in that it compares on how the determinants of environmental degradation affects EFP index and CE. Panel dataset of the OECD countries from 1990 to 2020 is employed. The CS-ARDL, DCCEMG, and AMG techniques, which overcome dynamics, heterogeneity, and cross-sectional dependence, are employed. The main findings depict that RE significantly reduces EFP and CE, while economic growth significantly exacerbates them. Energy efficiency reduces CE, but does not significantly affect EFP. Non-renewable energy and research & development significantly increase CE, while an insignificant positive effect is observed with EFP. This paper shows that factors that significantly influence CE may not always significantly affect the EFP index. Thus, to reduce environmental degradation it is fundamental to understand on how each dimension of EFP is influenced.

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This paper aims to carry out an integrated Life Cycle Assessment (LCA) to evaluate the environmental performance of a novel thermochemical-biochemical biomass-to-liquid pathway for sustainable aviation and maritime biofuel production. Five scenarios are defined, consideringdifferent types of biomass feedstock and biorefinery locations, in different geographically dispersed European countries. The results indicate that the replacement of conventional aviation and maritime fuels with sustainable biofuels could reduce Greenhouse Gases (GHG) by 60-86%, based on feedstock type. When the renewable share in the electricity mix reaches 100% (in 2050), the GHG emissions will experience a great decrease (26% - 68%), compared to 2022 levels. The non-renewable energy consumption will also decrease (by 56% - 83%), with results strongly affected by the electricity mix of the European country considered. This study demonstrates that the deployment of biomass-to-jet/marine fuel pathways could favor the industrial adoption of circular economy strategies for transport biofuels production.

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India, with its rapidly growing economy, has an increasing demand for energy consumption. This study thus adds to the energy-economic growth literature by exploring the effect of renewable (hydro and nuclear) and non-renewable (coal and oil) energy consumption by different sources on the economic growth of India, spanning from 1985 to 2021. The ARDL estimator is used to assess the short- and long-run growth effectiveness of the explanatory variables, while the variance decomposition analysis (VDA) is employed to examine the degree to which one variable can explain the change in variance of another variable. Among the renewable energy sources, hydro-energy consumption is found to be impeding economic growth, while nuclear energy is found to be inducing India's economic growth in the long run. Furthermore, among the non-renewable energy sources, oil consumption is found to be impeding the economic growth, while coal consumption is observed to be augmenting India's economic growth in the long run significantly. The findings reveal that non-renewable energy use plays a crucial role in the economic growth of India; thus, from a policy standpoint, this study recommends the government to invest more in the advancement of the renewable energy sector in order to balance the energy mix and achieve sustainable economic growth.

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Geopolitical threats have increased dramatically globally in recent years, adversely affecting the environment tremendously. On the other hand, there is a growing gap between the use of non-renewable energy, trade liberalization, and environmental sustainability. Due to this, the current work simulates the links between geopolitical threats, non-renewable energy use, trade liberalization, and environmental sustainability using a vector error correction model (VECM) and Granger causality test. The analysis includes data spanning from 1980 to 2021. Research outcomes indicated that geopolitical risks (GPR), Non-renewable energy consumption (NRE), Natural Resource (NR) and industrialization (IND) have a negative and statistically significant influence i.e., 0.234, 0.052, 0.028, and 0.070 units respectively on environmental sustainability (ES) while natural resource (NR) have also negative but insignificant impact on environmental sustainability. Alongside, trade liberalization (TR) and urbanization (UB) posed a positive and statistically significant influence i.e., 0.040 and 0.437 units respectively on ES. Further, causality analysis validates the feedback effect among GPR, NRE, TR, and ES. GPR, NRE, and TR granger cause environmental sustainability. The government can prepare for potential environmental disasters such as floods, droughts, and earthquakes by investing in early warning systems, emergency response teams, and disaster relief supplies. This can help mitigate the impact of geopolitical risks that can result in natural disasters. Pakistan should prioritize investing large resources in diplomatic endeavours to improve regional dynamics and ties with neighboring nations. Pakistan should place a high emphasis on developing methods targeted at reducing its non-renewable energy use to mitigate the negative effects. This might entail offering financial incentives, implementing efficient feed-in tariff schemes, and developing a thorough strategy for boosting the capacity of renewable energy sources.

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The Belt and Road Initiative (BRI) has boosted economic development while harming the ecology. It is vital to track its CO2 emissions to guide the BRI toward a green future and low carbon. Our research contributes to these goals in two ways. First, this research examines the spatial-temporal effects of institutional quality (IQ) and renewable and non-renewable energy consumption on CO2 emissions for 75 BRI countries from 1990 to 2019. Second, geographical implications are considered when assessing the factors that affect CO2 emissions on a regional scale. Several diagnostic methods are used to determine the significant spatial impacts, and spatial panel models (SPMs) are used to analyze the phenomenon's spillover and direct consequences. The empirical findings demonstrate that increased IQ and renewable energy (RNC) harm the country's CO2 emissions. These negative consequences spread geographically to adjacent countries of the impacted country. Moreover, non-renewable energy (NC) positively affects the CO2 of the impacted nation and its neighbors. Hence, the objective of reducing CO2 emissions compels BRI to establish an effective plan to reduce non-renewable energy, enhance IQ, resolve internal and external disputes, and foster religious and ethnic harmony in BRI-affected nations. Positive direct and negative spatial impacts of economic expansion highlight the zero-sum game of nations, so high CO2-emitting countries should exercise caution when implementing economic policies.

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Climate change traps heat, affecting various species in previously dry areas. Climate change brought on by emissions of greenhouse gases exacerbates problems such as severe storms, earthquakes, epidemics, and food distribution. The group of developed and developing countries, the world's biggest carbon emitters and most significant economies, is expertly planning to lessen its environmental challenges and contribute to achieving Sustainable Development Goals 7 and 13 set by the United Nations. This study uses the novel econometric methodologies of the dynamic ordinary least square (DOLS) estimator, the augmented mean group (AMG) estimator, and the fully modified ordinary least square (FMOLS) estimate to examine the influence of economic policy uncertainty, renewable energy consumption, geopolitical risk, non-renewable energy consumption, and economic growth on ecological footprint from 2000 to 2021. The results reveal that the variables are co-integrated; REC reduces carbon emissions, EPU, geopolitical risk, and economic growth contribute to increasing carbon emissions, while urbanization improves carbon emission. Finally, the results suggest that the developed and developing economies can progress toward SDGs 7 and 13 by using renewable energy, lowering the geopolitical risk, effectively handling policy uncertainty, and reducing urbanization.

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The use of renewable energy as a fuel source and expansion of forest areas are the best ways for reducing CO2 emissions. This study aims to examine the effects of forest plantation area, renewable energies, real gross domestic product (GDP), and technological innovation on CO2 emissions in 9 regions of New Zealand between 2006 and 2019. For this purpose, it employs a pooled mean group methodology. Investigating the regional impacts of various variables, especially the forest area, on CO2 emissions is the main contribution of this study. The results suggest that planted forest areas can reduce CO2 emissions in the long run, but its impact in the short run is not significant. Non-renewable energy consumption is the major contributor to CO2 emissions in both the short and long run. While technological innovation and renewable energy consumption appear effective in reducing carbon emissions in the short term, they still contribute to increased CO2 emissions in the long term. At the regional level, we found that the forest plantation areas in Manawatu-Whanganui and Gisborne are important regions for reducing CO2 emissions. By taking account of these results, New Zealand should take swift action to properly manage and increase the current level of forest areas and if applicable expand them. It also needs to improve the current level of use of renewable energy to achieve its abatement goals.

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To meet the goals of reducing adverse effects, continuing economic transformation, and achieving sustainable development, it is necessary to understand the impact mechanism and heterogeneous effects of geopolitical risk on carbon emissions. Using panel data from 30 provinces in China gathered between 2003 and 2019, we show that (1) geopolitical risk significantly contributes to the growth of carbon emissions, as does non-renewable energy consumption, trade, and economic growth, but that technological progress, industrial structure upgrading, and marketization inhibit the growth of carbon emissions; (2) geopolitical risk inhibits carbon emissions by suppressing non-renewable energy consumption and trade, and promoting technological progress; and (3) geopolitical risk has heterogeneous effects on carbon emissions in different quartiles. In the lower quartiles (i.e., groups with lower emission levels), geopolitical risk suppresses carbon emissions, while in higher quartiles (i.e., groups with higher emission levels), geopolitical risk promotes carbon emissions. As growing geopolitical risk and carbon emissions are now common problems for all countries, this study serves as a valuable reference not only for China, but for every member of the global community seeking to mitigate geopolitical risk shocks and achieve carbon emission reduction targets.

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The study aims to examine the relationship between carbon emissions and ecological footprints with economic complexity, core pollution indicators, urbanization, globalization, and renewable and non-renewable energy consumption in eight emerging Asian economies from 1971 to 2020. A panel data framework that considers cross-sectional dependence and heterogeneity was used for analysis. The Pedroni and Johnsen Fisher cointegration showed that carbon emission, ecological footprint, renewable and non-renewable energy consumption, economic complexity, globalization, and urbanization confirmed the presence of cointegration. Moreover, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DLOS) indicated that globalization, non-renewable energy consumption, and economic complexity increase emission and ecological footprint in the long run, whereas renewable energy generated through biomass, solar, and wind decreases environmental degradation. Furthermore, urbanization also negatively affects the environment. From a policy perspective, policymakers in these countries may manage their natural resources efficiently by escalating the share of renewables in total energy production, offering tax holidays, incentives and encouraging companies to install clean energy plant, and providing support to research and development-oriented companies to engage in research activities to reduce the cost of production of renewable energy.

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At a time when environmental concerns are rising in the world, natural resources, such as trees and other green plants, remain the most crucial factors responsible for reducing environmental degradation. Green plants inhale carbon dioxide and prevent the soil from wash and wear, hence their significant role in enhancing environmental quality. Therefore, it is essential to come up with state-of-the-art researches on the role of green plants to the environment. The present research is aimed at adding to the growing body of literature by investigating the effect of forest resources, together with renewable energy and energy efficiency in enhancing environmental quality. In this research, we use the data of the seven emerging countries, seven developed nations and 15 developing west African nations, from 1990 to 2019. The current research adds to the growing body of literature in that it presents a comparative analysis of the three important economic blocks, as well as employing three major methodologies of data analysis, the CS-ARDL, AMG, and CCEMG techniques, which are strong over cross-sectional dependence, heterogeneity, and dynamics. Major research outcomes show that renewable energy and energy efficiency negatively affects carbon emissions, while gross domestic product positively affects carbon emissions in all three regions. Population size and forest resources reduces carbon emissions in the emerging countries and seven developed countries, respectively. Non-renewable energy promotes carbon emissions in the seven developed countries, while in the emerging countries it reduces emissions. This research recommends the efficient utilization of energy, use of renewable energy, and forest preservation to promote carbon neutrality goal.

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The large amount of the non-renewable energy consumption in China brings certain challenges to the realization of carbon neutrality. This paper proposes a new grey model to predict the consumption of non-renewable energy in China. Based on the traditional grey model, the proposed model introduces two parameters to adjust the weight of information. Simultaneously, the intelligent optimization algorithm determines the optimal parameters. Three cases verify the feasibility of the model. The forecast results show that the amount of oil and natural gas consumption will continue to grow at a faster rate. By 2026, the amount of oil consumption will exceed 37 EJ (EJ) and natural gas consumption will exceed 22 EJ. Compared to 2021, oil consumption is up nearly 24%, and natural gas consumption is up more than 60%. While the consumption of coal will maintain a small up rate and gradually be leveled off.