Smart Transport Networks
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Smart Transport Networks

Market Structure, Sustainability and Decision Making

  • NECTAR Series on Transportation and Communications Networks Research

Edited by Thomas Vanoutrive and Ann Verhetsel

Transport is debated by many, and liberalization processes, transport policy, transport and climate change and increased competition between transport modes are the subject of heated discussion. Smart Transport Networks illustrates that whether concerning road, water, rail or air, knowledge on the structure of transport markets is crucial in order to tackle transport issues. The book therefore explores key factors concerning the structure of transport markets, their environmental impact, and questions why decision makers often fail to tackle transport-related problems.
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Chapter 9: Rising car user costs: comparing aggregated and geo-spatial impacts on travel demand and air pollutant emissions

Benjamin Kickhöfer, Friederike Hülsmann, Regine Gerike and Kai Nagel

Extract

Our chapter starts from the assumption that car user costs are about to increase in the forthcoming decades. This is likely to have impacts on aggregated air pollutant emissions and on the spatial distribution of emissions. The concentration of some air pollutants still exceeds the limiting values prescribed by the European Union, especially in urban areas. Thus, the main focus of this chapter is the question whether a decrease in car travel demand due to higher user costs would result in an over proportional reduction of air pollutant emissions. When it comes to the discussion of cost-related transport policies, large-scale transport models are needed. However, for the analysis of air pollutant emissions, a detailed investigation of the micro level is also necessary. In order to combine both objectives, we use a multi-agent transport model for our simulations. The multi-agent transport simulation MATSim is able to simulate large-scale scenarios. It is also particularly suitable for calculating air pollutant emissions on a detailed level as complete daily plans are modeled and the traveler’s identity is kept throughout the simulation process. For illustration purposes of the impacts on air pollutant emissions, nitrogen di oxide (NO2) is chosen. Furthermore, the transport sector is the main source of NO2 emissions and NO2 concentration limits are still often exceeded.

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