This study explores the long-run relationship among the environmental footprint (EnF), renewable energy consumption, energy use, industrial growth, and urbanization in Saudi Arabia from 1990 to 2023, employing the Autoregressive Distributed Lag (ARDL) model, alongside Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) for robustness checks. Results indicate a significant long-term relationship among the variables, with renewable energy adoption emerging as a crucial factor in reducing carbon emissions. The ARDL bounds test confirms the existence of cointegration, revealing the dynamic interplay among renewable energy, economic growth, and environmental sustainability. The findings show that renewable energy consumption significantly reduces the environmental footprint (CO2 emissions), supporting Saudi Arabia’s Vision 2030 goals for economic diversification and sustainable development. However, industrial expansion, while critical for economic growth, still contributes to increased emissions, underscoring the need for further investment in clean technologies. The study also highlights the role of urbanization, which, while essential for development, poses challenges for environmental sustainability. Short-term dynamics, represented by the Error Correction Model, indicate a fast adjustment speed toward equilibrium, with deviations corrected by approximately 52% each period. The study offers valuable insights for policymakers aiming to balance industrial growth with environmental protection, emphasizing the need for strategic investments in renewable energy and energy efficiency. This research contributes to the understanding of energy–economy–environment interactions in oil-rich economies, providing a foundation for future studies to explore the impact of advanced technologies and policy interventions on sustainable development
