City-Level Critical Thresholds for Road Freight Decarbonization: Evidence from EVT Modeling Under Economic Fluctuation

Wenjun Liao, Yingxue Chen, Chengcheng Wu () and Hongguo Shi
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Wenjun Liao: School of Automobile & Transportation, Xihua University, 9999 Hongguang Avenue, Jinniu District, Chengdu 610039, China
Yingxue Chen: School of Automobile & Transportation, Xihua University, 9999 Hongguang Avenue, Jinniu District, Chengdu 610039, China
Chengcheng Wu: School of Automobile & Transportation, Xihua University, 9999 Hongguang Avenue, Jinniu District, Chengdu 610039, China
Hongguo Shi: School of Transportation and Logistics, Southwest Jiaotong University, 111 2nd Ring Rd North Section 1, Jinniu District, Chengdu 610039, China

Sustainability, 2025, vol. 17, issue 20, 1-18

Abstract: The rapid growth of road freight has increased urban carbon emissions, but decarbonization in this sector remains slow compared to other areas. This study examines city-level road freight decarbonization, focusing on extreme values, with the goal of establishing a quantitative reference indicator for tailored policies. Using data from 342 Chinese cities, we applied K-means clustering and Extreme Value Theory (EVT) to estimate the extreme levels of freight vehicles decarbonization (FVDEL) under various economic scenarios. Results show notable differences among city types. High-Tech and Light Industry Cities (Type I) display a more substantial decarbonization potential, with a key threshold around 1.27%. Surpassing this level indicates higher readiness for zero-emission road freight, while Heavy Industry-Manufacturing Cities (Type II) tend to behave more predictably during economic ups and downs because of their close ties between industry and freight activities. The study also finds that purchase subsidies tend to have diminishing returns, whereas operational incentives like electricity price discounts and road access advantages are more effective in maintaining adoption. By proposing EVT-based thresholds as practical benchmarks, this research connects statistical modeling with policy implementation. The proposed reference indicator offers useful guidance for assessing urban decarbonization capacity and developing customized strategies to promote zero-emission freight systems.

Keywords: road freight decarbonization; extreme value theory; reference indicator; zero-emission cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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