Amid intensified global climate mitigation efforts, integrating rail freight into carbon emissions trading schemes became critical under China’s “Dual-Carbon” strategy. Despite rail’s significantly lower emissions intensity compared to road transport, existing pricing frameworks inadequately internalized its environmental externalities, which limited its competitive advantage. To address this gap, this study systematically reviewed international and domestic practices of integrating transport into carbon trading systems and developed a novel “four-layer, three-dimensional” emissions trading scheme (ETS) framework tailored specifically for China’s rail freight sector. Employing a Stackelberg bilevel optimization model, this study analyzed how carbon quotas and pricing influenced rail operators’ pricing and investment decisions. The results showed that under optimized quotas and carbon prices, railway enterprises were able to generate surplus carbon credits, creating new revenue streams and enabling freight rate reductions. This “carbon revenue–freight rate feedback loop” not only delivered environmental benefits but also enhanced rail’s economic competitiveness. Overall, this study significantly advances the understanding of carbon-based pricing mechanisms in railway freight, providing robust theoretical insights and actionable policy guidance for achieving sustainable decarbonization in China’s transport sector.

Amid intensified global climate mitigation efforts, integrating rail freight into carbon emissions trading schemes became critical under China’s “Dual-Carbon” strategy. Despite rail’s significantly lower emissions intensity compared to road transport, existing pricing frameworks inadequately internalized its environmental externalities, which limited its competitive advantage. To address this gap, the study systematically reviewed international and domestic practices of integrating transport into carbon trading systems and developed a novel "four-layer, three-dimensional" ETS framework tailored specifically for China’s rail freight sector. This framework encompassed emission caps, allowance allocation, monitoring–reporting–verification (MRV), and regulatory coordination, reinforced by effective market participant interactions, trading mechanisms, and digital infrastructure. Employing a Stackelberg bilevel optimization model, the study analyzed how carbon quotas and pricing influenced rail operators’ pricing and investment decisions. Results showed that under optimized quotas and carbon prices, railway enterprises were able to generate surplus carbon credits, creating new revenue streams and enabling freight rate reductions. This “carbon revenue–freight rate feedback loop” not only delivered environmental benefits but also enhanced rail’s economic competitiveness. Overall, the study significantly advanced the understanding of carbon-based pricing mechanisms in railway freight, providing robust theoretical insights and actionable policy guidance for achieving sustainable decarbonization in China’s transport sector.