The Impact of Zero-Carbon Fuels on CO2 Emissions Reduction from the Long-Haul Heavy-Duty Truck Fleet in Mainland China

The decarbonization of heavy-duty trucks (HDTs) is a crucial path for China to achieve its “dual-carbon” goals and transition to decarbonized freight transport. Zero-carbon fuels are key alternatives to fossil fuels for these high-emission vehicles. This study develops an integrated scenario analysis framework to quantify the theoretical CO₂e emission trajectories of China’s long-haul HDT fleet from 2020 to 2060. Functioning as a macro-level stress test, the model derives theoretical equivalent stock from anticipated logistics turnover demand, integrating them with well-to-wheel (WTW) emission factors under six distinct policy stringencies (Projects 1 through 6), representing varying paces of fossil fuel vehicle phase-out. The results demonstrate that policy stringency primarily governs the timing and depth of emission reductions, while fuel technology defines the minimum achievable emission level. Three-dimensional visualization analysis reveals a nonlinear “emission cliff” under aggressive policies, marked by accelerated HDT fleet renewal and exponentially growing mitigation benefits. This cliff is more pronounced for the green hydrogen pathway and demonstrates its superior potential for deep decarbonization. In Project 1, CO₂e emissions reach a mid-term peak in 2035. Compared to the diesel baseline, the green hydrogen and green ammonia transition pathways reduce peak CO₂e emissions by 158 and 137 million tons, corresponding to reductions of 10.0% and 8.6%, respectively, under the modeled theoretical boundaries. In contrast, the aggressive Project 6 policy suppresses this peak, triggers the “cliff” effect much earlier, and achieves an extremely low stabilization level by 2040—15 years ahead of Project 1. This study provides a macro-theoretical quantitative decision-support tool for policymakers. It demonstrates that transparent and aggressive phase-out policies are essential to accelerate fleet turnover, trigger the “emission cliff,” and firmly cap total cumulative emissions.