<p>China’s transition toward carbon neutrality requires a clearer understanding of how economic policy conditions, clean energy deployment, and technological progress jointly influence carbon emissions. Despite growing interest in these dynamics, limited evidence exists on how these relationships evolve across different time scales. This study addresses this gap by examining the frequency-dependent interactions between economic policy uncertainty (EPU), renewable energy consumption (REN), technological innovation (TEC), and CO₂ emissions in China. Methodologically, the analysis employs the Quantile Auto-Regressive Distributed Lag (QARDL) model and Breitung–Candelon spectral Granger causality to capture nonlinear and frequency-specific effects across varying economic conditions. The results show that EPU consistently heightens CO₂ emissions, with its impact becoming stronger at medium- and long-term frequencies, indicating that prolonged policy uncertainty undermines China’s decarbonization efforts. In contrast, renewable energy significantly reduces emissions across nearly all quantiles, with particularly strong mitigation effects at higher emission levels. Technological innovation also contributes to emissions reduction, but its influence intensifies mainly in the long run, suggesting that innovation-driven environmental benefits materialize gradually. Spectral causality tests confirm bidirectional long-term causality between REN, TEC, and CO₂ emissions, while EPU exhibits dominant unidirectional causality toward emissions. These findings highlight the critical importance of reducing economic policy uncertainty, accelerating renewable energy deployment, and sustaining long-term technological innovation. Policymakers should prioritize stable regulatory frameworks and targeted clean-energy investments to support China’s pathway to carbon neutrality and ensure environmentally sustainable economic growth.</p>