Green transition initiatives to reduce environmental degradation: Adaptation, mitigation and synergistic effects

Green transition initiatives to reduce environmental degradation: Adaptation, mitigation and synergistic effects

Green transitions are crucial strategies for mitigating environmental degradation and are aligned with the Sustainable Development Goals (SDGs) of the United Nations such as SDG 7, SDG 11 and SDG 13. This study used an expanded STIRPAT framework to investigate the adaptation, mitigation, and synergistic effects of green transition variables, namely, Renewable Energy Transition (RES), Green Finance (GFC) and Green Technology (GT). Ecological Footprint (EF) and Load Capacity Factor (LF) indicators were integrated to overcome the limitations of CO₂-centric indicators towards environmental degradation. Empirical analysis employs structured methods, including heteroskedasticity-robust panel unit root tests, long-run estimation (FMOLS), asymmetric effects (MMQR), and robustness checks (panel EGLS and D-H causality tests). The FMOLS results indicate that RES, GFC and GT create a synergistic governance framework that amplifies their individual impacts. GFC supports the R&D and deployment of GT, while GT optimizes the performance of RES projects. RES accelerates the adoption of renewables, enhancing energy efficiency and further reducing environmental degradation. MMQR results show that RES consistently reduces EF and increases LF across all quantiles, highlighting its key role in mitigating degradation. GFC exhibits varied effects across quantiles, while GT has significant positive effects on LF in lower to middle quantiles and reduces EF in higher quantiles. However, its impact on both LF and EF is less pronounced compared to that of RES and GFC. The insights gained here from the G-6 countries serve as a valuable guide or emerging economies, such as those of the BRICS, in developing adaptation and mitigation strategies to navigate the trade-offs between socio-economic developments and ecological thresholds.