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Promoting Freight Modal Shift to High-Speed Rail for CO 2 Emission Reduction: A Bi-Level Multi-Objective Optimization Approach

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  • Lin Li

    (College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China)

Abstract

This paper investigates the optimal planning of high-speed rail (HSR) freight operations, pricing strategies, and government carbon tax policies. The primary objective is to enhance the market share of HSR freight, thereby reducing carbon dioxide (CO 2 ) emissions associated with freight activities. The modal shift problem is formulated as a bi-level multi-objective model and solved using a specifically designed hybrid algorithm. The upper-level model integrates multiple objectives of the government (minimizing tax while maximizing the emission reduction rate) and HSR operators (maximizing profits). The lower-level model represents shippers’ transportation mode choices through network equilibrium modeling, aiming to minimize their costs. Numerical analysis is conducted using a transportation network that includes seven major central cities in China. The results indicate that optimizing HSR freight services with carbon tax policies can achieve a 56.97% reduction in CO 2 emissions compared to air freight only. The effectiveness of the government’s carbon tax policy in reducing CO 2 emissions depends on shippers’ emphasis on carbon reduction and the intensity of the carbon tax.

Suggested Citation

  • Lin Li, 2025. "Promoting Freight Modal Shift to High-Speed Rail for CO 2 Emission Reduction: A Bi-Level Multi-Objective Optimization Approach," Sustainability, MDPI, vol. 17(14), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6310-:d:1698252
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    References listed on IDEAS

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