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2015-10-09 | project

Estimating external costs of transportation in Beijing - air pollution costs and congestion costs

This project aims at (1) Documenting  the  main  urban transportation challenges in China, public  policies in this field, and evaluating the effectiveness of these policies; (2) Improving the assessment of  transportation externality costs in China (with a focus on Beijing) based on a large scale urban household survey and a proper estimation methodology; (3) Developing an analytical and empirical framework which links private automobile ownership and behavioural transportation modal choice to enhance the understanding of individual’s travel demand choice, automobile purchase and use decisions; (4) Building capacities in China based on quantative and qualitative assessments of  decision-making process in transportation policies to reach a better understanding of alternative policy instruments for reducing negative externalities from urban transportation.

Numerous studies across the world showed that the externality cost from transportation made up for a high percentage of GDP. In U.S.A and European countries, the transportation externality cost is assessed to be about 3 to 5% of national GDP, while in developing counties the number can reach as high 10%. In this research project, we focus on the evaluation of the transportation externality cost in the megacity, Beijing. This deserves urgent attention because almost all large Chinese cities are facing serious challenges resulted from rapid motorization. In these cities, fast growth of traffic density leads to longer travel time, reduced transportation speed and higher level of fuel consumption and pollution, and discomfort to road users. All of these result in considerable environmental damage and health hazards.   

This project aims at (1) Documenting  the  main  urban transportation challenges in China, public  policies in this field, and evaluating the effectiveness of these policies; (2) Improving the assessment of  transportation externality costs in China (with a focus on Beijing) based on a large scale urban household survey and a proper estimation methodology; (3) Developing an analytical and empirical framework which links private automobile ownership and behavioural transportation modal choice to enhance the understanding of individual’s travel demand choice, automobile purchase and use decisions; (4) Building capacities in China based on quantative and qualitative assessments of  decision-making process in transportation policies to reach a better understanding of alternative policy instruments for reducing negative externalities from urban transportation.