Economic Determinants of Renewable Energy Consumption in China: Integrating Green Infrastructure, Urban Agglomeration, and Environmental Stressors

China's rapid economic growth has intensified pressure on its energy system, with persistent fossil fuel dependence driving severe air pollution and escalating carbon emissions. Accelerating the transition toward renewable energy is thus vital for achieving the nation's “dual carbon” goals. This study investigates the structural and environmental determinants of renewable energy consumption (REC) in China from 2005 to 2023 using a multi‐method econometric framework. By integrating green infrastructure (forest area), energy efficiency (energy intensity), environmental stressors (PM2.5 exposure), and spatial dynamics (urban agglomerations exceeding one million inhabitants), the analysis offers a comprehensive understanding of renewable energy drivers. Employing the autoregressive distributed lag (ARDL) bounds approach, Dynamic OLS (DOLS) for long‐run robustness, and Toda–Yamamoto causality tests for directionality, the results confirm strong long‐run cointegration between REC and its determinants. Forest cover, urban agglomerations, and PM2.5 exposure significantly influence renewable energy demand, while energy intensity reflects structural breaks aligned with policy reforms in the late 2000s. These findings highlight that renewable energy uptake in China is shaped by the interplay of ecological resilience, urban transformation, and environmental pressures. The study contributes to sustainable development research by emphasizing that renewable energy policy must be integrated with ecological management, urban planning, and pollution control. Policy recommendations advocate for afforestation, renewable‐integrated urban infrastructure, stricter emission regulation, and ongoing efficiency improvements to accelerate China's clean energy transition and inform broader sustainable development pathways in emerging economies.