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The Impact of Zero-Carbon Fuels on CO<sub>2</sub> Emissions Reduction from the Long-Haul Heavy-Duty Truck Fleet in Mainland China

ゼロカーボン燃料が中国本土の長距離大型トラック車両からのCO₂排出削減に与える影響 (AI 翻訳)

Yunmei Wu, Hua Huang, Rui Li, Guijia He, Bo Liu, Ruowei Liu, Yongliang Xie

SAE International journal of sustainable transportation, energy, environment & policy📚 査読済 / ジャーナル2026-05-22#エネルギー転換Origin: CN
DOI: 10.4271/13-07-01-0003
原典: https://doi.org/10.4271/13-07-01-0003

🤖 gxceed AI 要約

日本語

本研究は、中国の長距離大型トラック（HDT）車両のCO₂e排出経路を2020年から2060年にかけて定量化する統合シナリオ分析フレームワークを開発した。グリーン水素とグリーンアンモニアへの転換は、6つの政策強度シナリオ下で排出削減のタイミングと深さを大きく左右する。強力な政策では「排出崖」が早期に発生し、2040年までに極めて低い安定化レベルを達成する。政策の透明性と積極的な段階的廃止が累積排出量を抑制する鍵となる。

English

This study develops an integrated scenario analysis framework to quantify CO₂e emission trajectories of China's long-haul heavy-duty truck fleet from 2020 to 2060. It finds that policy stringency governs the timing and depth of emission reductions, while fuel technology (green hydrogen, green ammonia) defines minimum emission levels. Aggressive policies trigger an 'emissions cliff,' accelerating fleet renewal and achieving low stabilization by 2040. Transparent phase-out policies are critical to cap cumulative emissions.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

中国の大型トラックの脱炭素化は、日本のGX政策（特に運輸部門の排出削減）にも示唆を与える。日本の大型トラックは依然としてディーゼル主体であり、ゼロカーボン燃料の導入や政策の強度とタイミングの設計に参考となる。

In the global GX context

China's heavy-duty truck decarbonization is a critical global issue. This paper provides a macro-level stress test framework that can inform similar scenario planning for other major economies, including the EU and US. The concept of an 'emissions cliff' driven by aggressive phase-out policies is a novel contribution to transition policy design.

👥 読者別の含意

🔬研究者:The integrated scenario analysis framework and the 'emissions cliff' effect provide a methodological contribution for studying transport decarbonization pathways.

🏢実務担当者:Fleet operators and logistics companies can use the scenario insights to plan investments in zero-carbon fuel vehicles and infrastructure.

🏛政策担当者:The study demonstrates that transparent, aggressive phase-out policies are essential to trigger the 'emissions cliff' and cap cumulative emissions, offering a clear policy roadmap.

📄 Abstract（原文）

<div>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.</div>

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