Time-varying and nonlinear effects of climate policy uncertainty on air pollution and carbon emissions in China: combination of TVP-VAR and QQA

Climate policy uncertainty (CPU) can alter the predictability of mitigation pathways, yet its environmental benefits may differ across time horizons and transition stages for pollutants or carbon emissions. Because air pollutants and CO 2 are often co-emitted through fossil-fuel use, understanding whether CPU produces consistent or divergent responses is important for integrated carbon–climate management. Using monthly data for China from 2000.01 to 2023.12, this study combines a time-varying parameter vector autoregressive (TVP-VAR) model with a quantile-on-quantile approach (QQA) to examine the time-varying dynamics and nonlinear effects of CPU on PM 2.5 and CO 2 . Significant time-varying dynamics between CPU and both PM 2.5 and CO 2 are identified. CPU shocks are associated with a short-run decline in PM 2.5 , but this response weakens toward zero over longer horizons, whereas the response of CO 2 is predominantly positive and more persistent. The QQA results further show that these relationships are not uniform across environmental states: the effect of CPU on PM 2.5 changes sign across pollution quantiles, with the strongest reduction effect associations concentrated in selected moderate-to-high pollution states. For CO 2 , positive roles dominate much of the distribution, while mitigating responses occur only in selected states. Even during high-emission phases, the mitigating role of CPU remains constrained. CPU can generate short-lived pollution-abatement responses without delivering a comparable long-run carbon-mitigation effect. Climate governance should therefore distinguish temporary air-quality improvements from persistent decarbonization requirements, maintain credible and consistent policy signals, and adapt implementation to prevailing environmental conditions. By linking policy uncertainty to the coupled dynamics of air pollution and carbon emissions, this study provides policy-relevant evidence for integrated carbon–climate management.