1. Decision analysis of the optimal freight structure at provincial level in China.
- Author
-
Qian Q, Li D, Gan M, and Yao Z
- Subjects
- Beijing, China, Tibet, Decision Support Techniques, Government
- Abstract
In recent years, considering the railway and waterway are cleaner ways of freight transportation, the Chinese government has vigorously promoted the adjustment of the transportation structure of the freight industry to reduce carbon emissions. However, with such a macroscopic objective, it remains a crucial problem for the policy-maker to further determine: how to estimate the optimal value of the share of freight volume among roadway, railway, and waterway regionally? To this end, this paper first quantified and analyzed the economic benefits, carbon emission intensity, and input-output efficiency of different transportation modes in each province. Then, with the goal of maximizing the efficiency of the freight transportation system, considering the carbon emission intensity reduction constraint and the economic output non-reduction constraint, an optimization model is constructed to obtain the freight structure adjustment plan in each province. Finally, taking the constraint of the carbon emission reduction targets by the 13th Five-Year Plan period as a case, the specific volume of roadway turnover transferred to waterway and railway in each province is given; the results show that Anhui, Beijing, Jiangxi, Tibet Autonomous Region, and Heilongjiang should focus on transferring the freight share of roadway to the railway, and the transferred shares are 15.36%, 14.12%, 10.21%, 8.22%, and 7.36% of road freight turnover. Tianjin, Hebei, and Shandong should focus on transferring the freight share of the roadway to the waterway, and the transferred shares are 18.44%, 7.90%, and 6.45% of road freight turnover, providing a reference for relevant government departments to formulate measures., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
- Published
- 2021
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