A system dynamics approach to scenario analysis for urban passenger transport energy consumption and CO2 emissions: A case study of Beijing. (October 2015)

• Record Type: Journal Article
• Authors: Liu, Xue; Ma, Shoufeng; Tian, Junfang; Jia, Ning; Li, Geng
• Is Part Of: Energy policy. Volume 85(2015)
• Page Start: 253
• Page End: 270
• Publication Date: 2015-10
• Subjects: Urban passenger transport -- Energy conservation -- Emission reduction -- System dynamics -- Scenario analysis; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2015.06.007
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: With the accelerating process of urbanization, developing countries are facing growing pressure to pursue energy savings and emission reductions, especially in urban passenger transport. In this paper, we built a Beijing urban passenger transport carbon model, including an economy subsystem, population subsystem, transport subsystem, and energy consumption and CO2 emissions subsystem using System Dynamics. Furthermore, we constructed a variety of policy scenarios based on management experience in Beijing. The analysis showed that priority to the development of public transport (PDPT) could significantly increase the proportion of public transport locally and would be helpful in pursuing energy savings and emission reductions as well. Travel demand management (TDM) had a distinctive effect on energy savings and emission reductions in the short term, while technical progress (TP) was more conducive to realizing emission reduction targets. Administrative rules and regulations management (ARM) had the best overall effect of the individual policies on both energy savings and emission reductions. However, the effect of comprehensive policy (CP) was better than any of the individual policies pursued separately. Furthermore, the optimal implementation sequence of each individual policy in CP was TP→PDPT→TDM→ARM. Highlights: The creation of a Beijing urban transport carbon model using system dynamics. The effect of different policies on energy conservation and emission reductions. The cumulative effect of different individual policies. The optimal sequence of individual policy implementation in comprehensive policy.