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Impact of Traffic Management on Black Carbon Emissions: a Microsimulation Study

Author

Listed:
  • Margherita Mascia

    (Transport for London)

  • Simon Hu

    (Imperial College London)

  • Ke Han

    (Imperial College London)

  • Robin North

    (Transport System Catapult)

  • Martine Poppel

    (VITO, Flemish Institute for Technological Research)

  • Jan Theunis

    (VITO, Flemish Institute for Technological Research)

  • Carolien Beckx

    (VITO, Flemish Institute for Technological Research)

  • Martin Litzenberger

    (Austrian Institute of Technology)

Abstract

This paper investigates the effectiveness of traffic management tools, including traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project.

Suggested Citation

  • Margherita Mascia & Simon Hu & Ke Han & Robin North & Martine Poppel & Jan Theunis & Carolien Beckx & Martin Litzenberger, 2017. "Impact of Traffic Management on Black Carbon Emissions: a Microsimulation Study," Networks and Spatial Economics, Springer, vol. 17(1), pages 269-291, March.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:1:d:10.1007_s11067-016-9326-x
    DOI: 10.1007/s11067-016-9326-x
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    References listed on IDEAS

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    1. Pete Sykes, 2010. "Traffic Simulation with Paramics," International Series in Operations Research & Management Science, in: Jaume Barceló (ed.), Fundamentals of Traffic Simulation, chapter 0, pages 131-171, Springer.
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    Cited by:

    1. Stefano de Luca & Roberta Di Pace & Silvio Memoli & Luigi Pariota, 2020. "Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design," Sustainability, MDPI, vol. 12(2), pages 1-20, January.
    2. Seyitali İlyas & Bahadır Ersoy Ulusoy & Sevil Köfteci & Yalçın Albayrak, 2024. "Association of Vehicle Count Data Obtained Via Image Processing Techniques Compared with Microsimulation Program Analysis Results," Networks and Spatial Economics, Springer, vol. 24(3), pages 655-680, September.
    3. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    4. Xin Lin & Chris M. J. Tampère & Stef Proost, 2020. "Optimizing Traffic System Performance with Environmental Constraints: Tolls and/or Additional Delays," Networks and Spatial Economics, Springer, vol. 20(1), pages 137-177, March.

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