Global warming has become a major concern for countries around the world. In this context, developed countries have decided to reduce global emissions to achieve sustainable development. The energy mix of OECD countries consists of 80% fossil fuels and accounts for about 35% of worldwide carbon emissions. Therefore, it is important to analyze how environmental factors affect carbon emissions in OECD countries. This study uses fossil energy, renewable energy (RE), and GDP for the period 1990–2019. Unlike previous studies, we will estimate two separate models for FFE and RE. To evaluate the empirical results, advanced panel data estimation methods using the cointegration test and the CS-ARDL estimation technique are employed to examine the long-run relationship between the variables. The results of the study demonstrate that fossil fuel use and GDP increase carbon emissions both in the short and long term. However, the use of RE hurts carbon emissions and is associated with sustainable development in OECD countries. Therefore, it is assumed that although fossil fuel use degrades the environment, economic growth helps it by reducing carbon emissions. Overall, our study shows that the use of RE is essential for OECD countries to achieve their environmental sustainability goals because it reduces the share of fossil fuels in the overall energy mix. Furthermore, in order to achieve a sustainable environment, OECD countries are recommended to begin long-term planning to reduce carbon emissions.

In this present age, innovation has become inextricably tied to both long-term economic growth and environmentally sound development. In this context, the impact that environmentally focused technological advancements or innovations have on environmental quality is of the utmost importance. Therefore, the main goal of the present study is to determine how Green innovation (GI) affects environmental degradation in the BRICS countries from 1992 to 2021. The ecological footprint (EFT) is an indicator used in the study to measure environmental degradation. The study divides the components that contribute to the explanation into two categories: the GI threshold variable and the independent variables RE, GDP, and population (POP). Additionally, this study investigates the indirect impact of RE, GDP, and POP through the threshold effect of GI. The stochastic impacts of the explanatory factors are explored using sophisticated panel data estimation methods and a panel threshold model. According to the findings of the study, an improvement in environmental quality occurs when the threshold level of GI is achieved, which indicates that innovation in the form of a lower EFT is responsible for the improvement. In light of the findings, recommendations for policymakers and stakeholders in BRICS countries are to promote RE and drive GI.