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Modeling Regional Transportation Demand in China and the Impacts of a National Carbon Policy

doi: 10.3141/2454-01
China's climate and energy policy commitments are stated at the national level, but they may have uneven impacts on the country's regionally heterogeneous transport system. This work quantifies the expected provincial-level response of freight transport to an economywide policy targeting reductions in carbon emissions intensity. The analysis applies the China Regional Energy Model, a multisector, static, global, computable general equilibrium (CGE) model representing 30 individual provinces with physical accounts of energy and greenhouse gas emissions. The structure of road and nonroad freight (and passenger) sectors, the preparation of transport activity data, and a policy similar to announced goals that specify a 17% reduction in the carbon dioxide emissions intensity of gross domestic product are described. In the national aggregate and in most provinces, the road freight sector is most affected by the emissions intensity cap. The road freight sector contributes 24%–-versus 18% from nonroad freight and 51% from nontransport sectors–-of a 5.1% reduction in national refined oil demand. Significant regional differences are found in the impacts of a national-level, economywide policy. Steep reductions in freight activity occur in some of the poorest provinces, partly because they offer low-cost abatement opportunities, and the resulting adjustments across the economy affect transport demand. This research contributes a new tool capable of capturing the transport impact of sector- and province-specific policies in detail and providing a rigorous foundation for future dynamic CGE analyses. Potential impacts of energy and climate policy on regional transport systems are important inputs to policy and infrastructure investment decisions at the central and local levels.
- Massachusetts Institute of Technology United States
- Tsinghua University China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).14 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
