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<p>Highway tunnels are expanding rapidly in China, driving rising operational carbon emissions, yet systematic assessment methods remain limited. Here, we develop a provincial-scale carbon intensity model using empirical data from Sichuan Province, integrating regional electricity emission factors and geological characteristics. The model estimated emission intensities across 30 provinces, yielding a national average of 16,805 tCO<sub>2</sub>-eq per km, and validation against 88 tunnel cases from five provinces shows prediction error of less than 5%. We further propose a low-carbon cross-section design strategy and evaluate three policy-technology interaction scenarios: baseline, high-reduction, and low-reduction. The high-reduction scenario could lower emissions by more than 18% relative to the baseline, whereas the low-reduction scenario leads to limited effectiveness. Establishing a nation-wide tunnel emission model is essential for infrastructure planning, policy design, and accelerating low-carbon transitions in China and other rapidly developing economies.</p>

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Rising carbon emissions from expanding highway tunnels and reduction pathways in China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月27日

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  • Yalin Guo,
  • Sixun Wen,
  • Zongcheng Guo,
  • Xiaotao Tan,
  • Yiyuan Wang,
  • Nan Hu,
  • Peiwen Jia,
  • Kaichun Su,
  • Chun Guo

摘要

Highway tunnels are expanding rapidly in China, driving rising operational carbon emissions, yet systematic assessment methods remain limited. Here, we develop a provincial-scale carbon intensity model using empirical data from Sichuan Province, integrating regional electricity emission factors and geological characteristics. The model estimated emission intensities across 30 provinces, yielding a national average of 16,805 tCO2-eq per km, and validation against 88 tunnel cases from five provinces shows prediction error of less than 5%. We further propose a low-carbon cross-section design strategy and evaluate three policy-technology interaction scenarios: baseline, high-reduction, and low-reduction. The high-reduction scenario could lower emissions by more than 18% relative to the baseline, whereas the low-reduction scenario leads to limited effectiveness. Establishing a nation-wide tunnel emission model is essential for infrastructure planning, policy design, and accelerating low-carbon transitions in China and other rapidly developing economies.