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Real-World CO2 Impacts of Traffic Congestion

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  • Barth, Matthew
  • Boriboonsomsin, Kanok

Abstract

Transportation plays a significant role in carbon dioxide (CO2) emissions, accounting for approximately a third of the United States’ inventory. In order to reduce CO2 emissions in the future, transportation policy makers are looking to make vehicles more efficient and increasing the use of carbon-neutral alternative fuels. In addition, CO2 emissions can be lowered by improving traffic operations, specifically through the reduction of traffic congestion. This paper examines traffic congestion and its impact on CO2 emissions using detailed energy and emission models and linking them to real-world driving patterns and traffic conditions. Using a typical traffic condition in Southern California as example, it has been found that CO2 emissions can be reduced by up to almost 20% through three different strategies: 1) congestion mitigation strategies that reduce severe congestion, allowing traffic to flow at better speeds; 2) speed management techniques that reduce excessively high free-flow speeds to more moderate conditions; and 3) shock wave suppression techniques that eliminate the acceleration/deceleration events associated with stop-and-go traffic that exists during congested conditions.

Suggested Citation

  • Barth, Matthew & Boriboonsomsin, Kanok, 2008. "Real-World CO2 Impacts of Traffic Congestion," University of California Transportation Center, Working Papers qt4fx9g4gn, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt4fx9g4gn
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    Cited by:

    1. Said Dabia & Emrah Demir & Tom Van Woensel, 2017. "An Exact Approach for a Variant of the Pollution-Routing Problem," Transportation Science, INFORMS, vol. 51(2), pages 607-628, May.
    2. Jinghua Li & Hui Guo & Qinghua Zhou & Boxin Yang, 2019. "Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode," Sustainability, MDPI, vol. 11(15), pages 1-20, August.
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    9. Valentas Gruzauskas & Aurelija Burinskiene & Andrius Krisciunas, 2023. "Application of Information-Sharing for Resilient and Sustainable Food Delivery in Last-Mile Logistics," Mathematics, MDPI, vol. 11(2), pages 1-21, January.
    10. Altvater, Susanne & de Block, Debora & Bouwma, Irene & Dworak, Thomas & Frelih-Larsen, Ana & Görlach, Benjamin & Hermeling, Claudia & Klostermann, Judith & König, Martin & Leitner, Markus & Marinova, , 2012. "Adaptation measures in the EU: Policies, costs, and economic assessment. "Climate Proofing" of key EU policies," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 110558.
    11. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    12. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    13. Greenblatt, Jeffery B., 2015. "Modeling California policy impacts on greenhouse gas emissions," Energy Policy, Elsevier, vol. 78(C), pages 158-172.
    14. Franceschetti, Anna & Honhon, Dorothée & Van Woensel, Tom & Bektaş, Tolga & Laporte, Gilbert, 2013. "The time-dependent pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 265-293.
    15. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    16. Mohammadi, M. & Torabi, S.A. & Tavakkoli-Moghaddam, R., 2014. "Sustainable hub location under mixed uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 89-115.
    17. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "The bi-objective Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 464-478.
    18. Zhu, Weihua, 2009. "Design and Development of Novel Routing Methodologies for Dynamic Roadway Navigation Systems," University of California Transportation Center, Working Papers qt8d72371n, University of California Transportation Center.
    19. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    20. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    21. Hamid R. Sayarshad & Vahid Mahmoodian & Nebojša Bojović, 2021. "Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    22. Caris, An & Limbourg, Sabine & Macharis, Cathy & van Lier, Tom & Cools, Mario, 2014. "Integration of inland waterway transport in the intermodal supply chain: a taxonomy of research challenges," Journal of Transport Geography, Elsevier, vol. 41(C), pages 126-136.
    23. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    24. Demir, Emrah & Burgholzer, Wolfgang & Hrušovský, Martin & Arıkan, Emel & Jammernegg, Werner & Woensel, Tom Van, 2016. "A green intermodal service network design problem with travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 93(PB), pages 789-807.

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