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.
