Comprehensive Pricing Model of Urban Traffic Air Pollution Based on Bi-Level Programming

Ze Bin Zhao

doi:10.4028/www.scientific.net/AMM.253-255.1913

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 253-255Comprehensive Pricing Model of Urban Traffic Air...

Comprehensive Pricing Model of Urban Traffic Air Pollution Based on Bi-Level Programming

Abstract:

In order to reduce the negative impact of urban traffic air pollution, this paper firstly analyzes the relationship between urban traffic air pollution and vehicle speed, after providing the relationship model, the paper establishes a comprehensive pricing model of urban traffic air pollution based on bi-level programming, the model considers the traffic air pollution pricing, and includes the factors of congestion pricing, bus fee, pricing revenue redistribution on improvement of public transport services and the expansion of road capacity. The case study shows that the implementation of comprehensive pricing of urban traffic air pollution can reduce traffic pollution and unreasonable traffic flow, which is conducive to the sustainable development of the city.

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Periodical:

Applied Mechanics and Materials (Volumes 253-255)

Pages:

1913-1917

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.253-255.1913

Citation:

Cite this paper

Online since:

December 2012

Authors:

Ze Bin Zhao*

Keywords:

Bi-Level Programming, Comprehensive Pricing, Traffic Air Pollution, Urban Transportation

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* - Corresponding Author

References

[1] Quinet E. Evaluation methodologies of transportation projects in France. Transport Policy. Vol. 7 (2000), pp.27-34.

DOI: 10.1016/s0967-070x(00)00014-7

Google Scholar

[2] Graham Parkhurst. Air Quality and The Environmental Transport Policy Discourse in Oxford. Transportation Research Part D: Transport and Environment. Vol. 9 (2004), pp.419-436.

DOI: 10.1016/j.trd.2004.08.001

Google Scholar

[3] Paolo Delle Site, Francesco Filippi. Bus Service Optimization with Fuel Saving Objective and Various Financial Constraints. Transportation Research Part A. Vol. 35 (2001), pp.163-182.

DOI: 10.1016/s0965-8564(99)00053-1

Google Scholar

[4] Paolo Delle Site, Francesco Filippi. Bus Service Optimization and Car Pricing Policies to Save Fuel in Urban Areas. Transportation Research Part A. Vol. 29 (1995), pp.345-358.

DOI: 10.1016/0965-8564(95)00001-5

Google Scholar

[5] J Xie, S. H Huang, N Xie. City Traffic Pollution and Its Control in Nanning. Environmental Protection in Transportation. Vol. 24 (2003), pp.30-33(In Chinese).

Google Scholar

[6] Nagurney Anna, Zhang Ding. Dynamics of a Transportation Pollution Permit System with Stability Analysis and Computations. Transportation Research Part D: Transport and Environment. Vol. 6 (2001), pp.243-268.

DOI: 10.1016/s1361-9209(00)00028-6

Google Scholar

[7] Gulliver John, Briggs David J. Time–Space Modeling of Journey-Time Exposure to Traffic-Related Air Pollution Using GIS. Environmental Research. Vol. 97 (2005), pp.10-25.

DOI: 10.1016/j.envres.2004.05.002

Google Scholar

[8] Sharma Prateek, Khare Mukesh. Modeling of Vehicular Exhausts – A Review. Transportation Research Part D: Transport and Environment. Vol. 6 (2001), pp.179-198.

DOI: 10.1016/s1361-9209(00)00022-5

Google Scholar

[9] Greene D.L., Plotkin S.E. Energy Futures for the US Transport Sector. Energy Policy. Vol. 29 (2001), pp.1255-1270.

DOI: 10.1016/s0301-4215(01)00071-4

Google Scholar

[10] Theodoros Zachariadis, Nikos Kouvaritakis. Long-Term Outlook of Energy Use and CO2 Emissions from Transport in Central and Eastern Europe. Energy Policy. Vol. 31 (2003), pp.759-773.

DOI: 10.1016/s0301-4215(02)00126-x

Google Scholar

[11] MacLean Heather L., Lave Lester B. Evaluating Automobile Fuel/Propulsion System Technologies. Progress in Energy and Combustion Science. Vol. 29 (2003), pp.1-69.

DOI: 10.1016/s0360-1285(02)00032-1

Google Scholar

[12] H. Sbayti, M. El-Fadel, I. Kaysi. Effect of Roadway Network Aggregation Levels on Modeling of Traffic-Induced Emission Inventories in Beirut. Transportation Research Part D. Vol. 7 (2002), pp.163-173.

DOI: 10.1016/s1361-9209(01)00017-7

Google Scholar

[13] S An, J Wang, J Li. Study on Pricing for Two Management Modes of On-Street Parking: Guangzhou Case. Proceedings of the 9th Conference of HKSTS. Dec. HK, (2004), pp.391-395. (In Chinese).

Google Scholar

[14] Z. B Zhao, Y Chen. Redistribution of Revenue from Road Congestion Pricing Based on Improvement of Public Transport Services. China Railway Science. Vol. 30 (2009), pp.131-136(In Chinese).

Google Scholar