A low-carbon transportation network: Collaborative effects of a rail freight subsidy and carbon trading mechanism

Chuanzhong Yin, Zi-Ang Zhang, Xiaowen Fu and Ying-En Ge

Transportation Research Part A: Policy and Practice, 2024, vol. 184, issue C

Abstract: Optimizing a transportation network is an effective way to reduce carbon emissions. To examine the collaborative effects of a rail freight subsidy and carbon trading mechanism in a low-carbon transportation network, a multiobjective 0–1 mathematical model that considers transportation cost, carbon trading cost and transportation time is established in this paper, and the NSGA-II algorithm is used to solve it. The Pareto optimal frontier solution set is found for the model, and the optimal solution is determined using the evaluation function of the ideal point method. The performance and effectiveness of the NSGA-II algorithm is analyzed by means of a sample example. A case study of the Yangtze River Economic Belt region in China is conducted to demonstrate the application and practicality of the model. Sensitivity analysis is carried out on rail freight subsidy, carbon quota and carbon trading price. The numerical results highlight that the rail freight subsidy significantly contributes to the design of the low-carbon transportation network, while the low carbon trading price shows a limited effect, which also leads to a weak effect of carbon quota on low-carbon transportation network design. These findings provide decision-making support for optimizing the low-carbon transportation network design and improving the carbon trading mechanism.

Keywords: Transportation network; Intermodal transportation; Multiobjective 0–1 mathematical model; Rail freight subsidy; Carbon trading mechanism; Collaborative effects (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tra.2024.104066

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