Escaping the Regional Carbon Trap: The Role of Renewable Energy Innovation in EU Decarbonisation

When green is not attractive: energy transition, capital inflows, and environmental outcomes in BRICS economies

Innovation Systems, Renewable Energy Efficiency, Energy Transition, and Mitigation–Expansion Trap: Evidence on Structural Drivers of Climate Decoupling

Climate change requires an integrated policy framework that can handle multifaceted interrelations between energy systems, financial systems, technological innovation, and demographic processes. This research explores implicit drivers of CO 2 intensity and ecological footprint in 13 developed and developing countries from 2001 to 2025 using an interpretable MNN–DeepSHAP framework. The results indicate that better and more consistent environmental impacts are generated through improved efficiency of renewable energy, especially through lower levelized costs and better production performance rather than simply increasing installed capacity. Green technological innovation and structural energy transition can help to lower emissions, particularly when green investment is supported by well‐developed financial markets. But economic expansion alone does not ensure ecological sustainability, whereas population growth creates persistent upward pressure on environmental demand. This reflects a mitigation–expansion trap in which scale effects offset technological progress. The study emphasizes the importance of integrated policy packages.

Factors influencing the low-carbon transition: Evidence from the EU economies

Decarbonizing the economy effectively mitigates climate change, accelerates the transition to sustainable development, and corresponds to the Kyoto Protocol and Paris Climate Accords. The key objective of this research is to estimate the influence of different social, economic, political and technological factors on decarbonization processes. The scientific novelty of the study is that it investigates decarbonization from a dual perspective, assessing it both in terms of greenhouse gas (GHG) emissions levels and carbon intensity of gross domestic product (GDP). This research applies random-effects generalized least squares regression, fixed-effects robustness checks and dynamic System GMM for 27 EU economies in 2013–2021. The results indicate that (i) renewable energy is a vital decarbonization driver (a 10-percentage-point increase in the share of renewable energy leads to a decrease in the amount of GHG emissions by 1.52 thousand metric tons and to a decrease in the carbon intensity of GDP by 0.14 metric tons/thousand USD). (ii) A larger service sector and higher technological employment also contribute positively to the low-carbon transition, while (iii) corruption acts as an important institutional barrier. (iv) GDP per capita is associated with lower carbon intensity and emissions, supporting the view that more advanced economies are better positioned to implement sustainable transformation. Research results provide specific policy implications for designing more effective climate and energy policies, including green finance development, virtual economy growth, and innovation implementation.

Decomposition of CO2 Emission Drivers and Energy Transition Dynamics Across Australian States: A Kaya–Shapley Approach

This study employs the Kaya identity and Shapley value decomposition to analyse the main drivers of CO2 emissions per capita in Australia and its states/territories from 2008–2009 to 2023–2024. This study extends the traditional three-factor Kaya model to a five-factor framework that explicitly incorporates renewable energy dynamics. Within this environment, we introduce an index for evaluating energy transition in each state over time, captured through the combined effects of renewable energy share and the fossil fuel-to-renewable ratio. The results indicate that energy intensity improvements are the dominant driver of emission reductions, contributing well over 100% of the total decline in most jurisdictions. However, this pattern does not hold universally: in the Northern Territory, energy intensity increased and contributed positively to emissions. In contrast, economic growth continues to exert upward pressure on emissions, partially offsetting these reductions and highlighting the ongoing challenge of decoupling. The Energy Transition Index (ETI) rose more than fivefold nationally (0.0018 to 0.0096), with Tasmania the highest among all states (0.185–0.291) and Western Australia and the Northern Territory the lowest. The Energy Transition Effect (ETE), defined as the natural logarithm of the ETI, follows the same regional pattern, while the Net Energy Transition Contribution (NETC) derived from the Shapley decomposition shows that the transition’s effect on emissions has been episodic rather than linear, turning negative in years when growth in fossil-fuel use outpaced renewable displacement. Marked regional variation is observed, with resource-intensive states such as Western Australia, Queensland, and the Northern Territory exhibiting distinct emissions patterns driven by mining and LNG activities, while more service-oriented states show more stable reductions.

Circular Economy and Energy Transition as Drivers of Carbon Emission Reduction: Evidence from Central and Eastern European Countries

Reducing carbon emissions has become a central objective of sustainable development policies as countries seek to address the environmental challenges associated with climate change and resource depletion. In this context, circular economy practices and energy transition policies have emerged as key mechanisms for achieving environmental sustainability. This study examines the determinants of carbon emissions within the framework of the circular economy and energy transition for selected Central and Eastern European countries (Romania, Poland, Hungary, Bulgaria, Slovakia, and Slovenia) over the period 2010–2024. Using panel data analysis, the study incorporates key variables including circular economy, economic growth, recycling, renewable energy consumption, and urbanization. To enhance the reliability of the empirical estimates, panel unit root tests, the Hausman specification test, fixed-effects estimation, and Driscoll–Kraay robust standard errors are employed to address heteroskedasticity, serial correlation, and cross-sectional dependence. The results indicate that improvements in circular economy practices together with greater renewable energy use are associated with lower carbon emissions, providing empirical support for the proposed hypotheses. Recycling activities are found to increase emissions in the short run, indicating energy-intensive processes. In contrast, the effects of economic growth and urbanization are found to be context-dependent, providing only partial support for the related hypotheses. Overall, the results highlight that carbon emission dynamics are shaped by a complex interaction of economic, structural, and environmental factors, and that policy effectiveness depends on country-specific conditions. By focusing on transition economies in Central and Eastern Europe, this study extends the existing literature through an integrated panel data analysis of circular economy and energy transition policies and offers policy-relevant evidence for the region.

Does Globalization Accelerate or Mitigate Greenhouse Gas Emissions? Evidence from Energy Transition and Technological Innovation in Central Asia

Greenhouse gas (GHG) emissions have emerged as a critical challenge to sustainable development in Central Asia, where rapid economic transformation, rising energy demand, and increasing globalization have intensified environmental pressures. This study investigates the determinants of GHG emission growth in Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan over the period 2000–2024 within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework. Specifically, the analysis examines the effects of economic growth, energy intensity, renewable energy consumption, technological innovation, urbanization, and globalization on annual GHG emission growth. To ensure robust inference in the presence of cross-sectional dependence and heteroskedasticity, the empirical analysis employs Driscoll–Kraay standard errors (DKSE), Panel-Corrected Standard Errors (PCSE), and Feasible Generalized Least Squares (FGLS). Furthermore, the Method of Moments Quantile Regression (MMQR) is applied to examine distributional heterogeneity by assessing whether the effects of the explanatory variables vary across the lower, median, and upper quantiles of the conditional distribution of GHG emission growth. The empirical findings reveal that energy intensity is the dominant driver of GHG emission growth across all estimation techniques, whereas renewable energy adoption and technological innovation significantly mitigate environmental degradation by reducing emissions growth. The MMQR results further demonstrate that the estimated effects of the explanatory variables vary across the conditional distribution of GHG emission growth. In particular, the mitigating effect of globalization becomes more pronounced toward the upper quantiles of the conditional distribution, indicating that its environmental consequences differ across the distribution of GHG emission growth rather than across predefined groups of countries. By contrast, the effects of economic growth and urbanization exhibit greater heterogeneity across the conditional distribution, while the effects of energy intensity, renewable energy, and technological innovation remain broadly consistent in direction. These findings underscore the importance of improving energy efficiency, accelerating the deployment of renewable energy technologies, strengthening innovation capacity, and promoting environmentally sustainable economic integration to achieve long-term climate objectives in Central Asia. By providing comprehensive evidence based on complementary mean-based estimators and distribution-sensitive quantile analysis, this study contributes to the growing literature on the determinants of GHG emissions in emerging economies and offers important policy implications for balancing economic development with climate change mitigation and environmental sustainability.