Synergistic effects of new energy and low-carbon pilot dual policies on pollution and carbon reduction: A causal analysis based on double machine learning

Against the dual backdrop of global climate change and air quality degradation, China’s New Energy Demonstration City and Low-Carbon City Pilot policies have emerged as critical institutional innovations for pollution and carbon reduction. Leveraging 2005–2023 panel data from 294 prefecture-level cities and adopting the Double Machine Learning model, this study systematically assesses the impacts and mechanisms of these two policies’ collaborative pollution and carbon reduction efforts. Key findings reveal: (1) The joint implementation of the two policies significantly promotes pollution-carbon co-reduction. Compared to single-policy scenarios, the synergistic effect reduces the joint reduction level (measured by the PM2.5-CO₂ emission interaction term) by 18.7 %. Conclusion robustness is validated via parallel trend tests, placebo tests, and endogeneity control methods. (2) Key transmission mechanisms revolve around energy structure optimization, green technological innovation, and energy efficiency enhancement. The dual policies boost renewable energy share by 2.78 %, green patent grants by 76.94 %, and energy efficiency by 6.93 %, respectively driving collaborative governance through “clean substitution - technological breakthrough - efficiency deepening” pathways. (3) Noticeable heterogeneities exist in policy impacts. Pollution-carbon co-reduction effects in cities with stronger economic foundations, non-resource-dependent cities, and non-old industrial base cities exceed those of the control group by 45 %, 32 %, and 39 % respectively. Furthermore, the sequential policy implementation model—first rolling out Low-Carbon City Pilots followed by promoting New Energy Demonstration Cities—can further enhance the synergistic effect. (4) Spatial spillover analysis reveals significant positive externalities from the joint implementation of the two policies. Neighboring cities’ pollution-carbon co-reduction levels are further reduced by 13.6 % via policy spillovers, exhibiting a regional collaborative pattern characterized by “race-to-the-top” competition. This study transcends the single-policy evaluation framework, uncovers the non-linear superposition effects of dual policies via the “market incentives-institutional constraints” complementary mechanism, and provides causal evidence for policy portfolio design under the "Dual Carbon" targets. Recommendations include: strengthening region-specific differential strategies for synergistic policy implementation; prioritizing transformation support for resource-dependent cities; and establishing cross-regional environmental governance cooperation networks to amplify spatial spillover benefits.