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This study examines the dynamic synchronization among renewable energy sources, innovation and economic growth in their joint influence on carbon emissions, employing a Kuramoto-based oscillator framework alongside a cross-sectional nonlinear autoregressive distributed lag (CS-NARDL) model. Using annual panel data from 2000 to 2024 for the BRICS economies (Brazil, Russia, India, China, and South Africa), we quantify the degree of phase synchronization via the Kuramoto order parameter in Python to derive country- and variable-specific synchronization indices and natural frequencies. Our results indicate that China, India, and Russia exhibit comparatively lower synchronization indices and correspondingly higher carbon emissions than Brazil and South Africa, suggesting less cohesive policy coordination in renewable-energy deployment. Moreover, both technological innovation and increased renewable-energy integration emerge as statistically significant drivers of emissions mitigation. By integrating a novel synchronization methodology into the energy-environment literature, this work lays a rigorous foundation for future research on policy harmonization and supports the need for systemic alignment among green growth variables to achieve sustainability targets.
Mehta et al. (Tue,) studied this question.