IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i10p2936-d233646.html
   My bibliography  Save this article

Evaluating Urban Bus Emission Characteristics Based on Localized MOVES Using Sparse GPS Data in Shanghai, China

Author

Listed:
  • Xiaonian Shan

    (College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China)

  • Xiaohong Chen

    (Key Laboratory of Road Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Wenjian Jia

    (Deparment of Engineering System & Environment, University of Virginia, Charlottesville, VA 22906, USA)

  • Jianhong Ye

    (Key Laboratory of Road Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

Abstract

Bus emissions have become one of the important contributing factors in urban environmental pollution due to the frequent use of heavy-duty diesel engines in the day-time. Local bus driving cycles have a significant influence on bus emissions under the different traffic conditions. This study investigated the operation mode distributions and emission characteristics for urban buses based on localized MOtor Vehicle Emission Simulator (MOVES) using sparse Global Position System (GPS) data in Shanghai, China. Sparse GPS data from forty-three buses were prepared, and then bus trajectories were reconstructed to calculate local bus driving cycles, including model description, model calibration, and trajectory reconstruction. MOVES localization was conducted for emission estimation mainly focusing on the bus emission inventory comparison between US and China. Bus emission factors were estimated based on the localized MOVES from the aspect of different driving conditions. Results show that with the increase in average traveling speed, the proportion of idling operation mode showed a decreasing trend. Four typical vehicle operation mode distributions were identified with different average speeds to show the impact of traffic conditions. Bus emission factors first rapidly decreased and then slowly declined towards some minimum values. Bus lanes exhibited emission reduction benefits under serious traffic congestion. The findings of this study have great importance for transportation operation management and policy-making to reduce bus emissions, as well as improving air quality.

Suggested Citation

  • Xiaonian Shan & Xiaohong Chen & Wenjian Jia & Jianhong Ye, 2019. "Evaluating Urban Bus Emission Characteristics Based on Localized MOVES Using Sparse GPS Data in Shanghai, China," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2936-:d:233646
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/10/2936/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/10/2936/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Qian & Li, Tiezhu & Li, Hu, 2016. "Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving," Applied Energy, Elsevier, vol. 161(C), pages 101-111.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sui, Yi & Zhang, Haoran & Shang, Wenlong & Sun, Rencheng & Wang, Changying & Ji, Jun & Song, Xuan & Shao, Fengjing, 2020. "Mining urban sustainable performance: Spatio-temporal emission potential changes of urban transit buses in post-COVID-19 future," Applied Energy, Elsevier, vol. 280(C).
    2. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2021. "Effects of passenger load, road grade, and congestion level on real-world fuel consumption and emissions from compressed natural gas and diesel urban buses," Applied Energy, Elsevier, vol. 282(PB).
    3. Chao Wang & Zhuoqun Sun & Zhirui Ye, 2020. "On-Road Bus Emission Comparison for Diverse Locations and Fuel Types in Real-World Operation Conditions," Sustainability, MDPI, vol. 12(5), pages 1-14, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Tian & Han, Xiao & Zheng, M. Mocarlo & Ou, Xunmin & Sun, Hongbo & Zhang, Xiong, 2020. "Impact factors of the real-world fuel consumption rate of light duty vehicles in China," Energy, Elsevier, vol. 190(C).
    2. Rajaeifar, Mohammad Ali & Tabatabaei, Meisam & Aghbashlo, Mortaza & Nizami, Abdul-Sattar & Heidrich, Oliver, 2019. "Emissions from urban bus fleets running on biodiesel blends under real-world operating conditions: Implications for designing future case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 276-292.
    3. Feng Mao & Zhiheng Li & Kai Zhang, 2021. "A Comparison of Carbon Dioxide Emissions between Battery Electric Buses and Conventional Diesel Buses," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
    4. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    5. Sui, Yi & Zhang, Haoran & Shang, Wenlong & Sun, Rencheng & Wang, Changying & Ji, Jun & Song, Xuan & Shao, Fengjing, 2020. "Mining urban sustainable performance: Spatio-temporal emission potential changes of urban transit buses in post-COVID-19 future," Applied Energy, Elsevier, vol. 280(C).
    6. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2021. "Effects of passenger load, road grade, and congestion level on real-world fuel consumption and emissions from compressed natural gas and diesel urban buses," Applied Energy, Elsevier, vol. 282(PB).
    7. Wang, Hongfei & Guan, Hongzhi & Qin, Huanmei & Zhao, Pengfei, 2024. "Assessing the sustainability of time-dependent electric demand responsive transit service through deep reinforcement learning," Energy, Elsevier, vol. 296(C).
    8. Shao, Shuai & Tan, Zhijia & Liu, Zhiyuan & Shang, Wenlong, 2022. "Balancing the GHG emissions and operational costs for a mixed fleet of electric buses and diesel buses," Applied Energy, Elsevier, vol. 328(C).
    9. Lv, Zongyan & Wu, Lin & Yang, Zhiwen & Yang, Lei & Fang, Tiange & Mao, Hongjun, 2023. "Comparison on real-world driving emission characteristics of CNG, LNG and Hybrid-CNG buses," Energy, Elsevier, vol. 262(PB).
    10. Yang, Haifei & Zhai, Xue & Zheng, Changjiang, 2018. "Effects of variable speed limits on traffic operation characteristics and environmental impacts under car-following scenarios: Simulations in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 567-577.
    11. Yueru Xu & Chao Wang & Yuan Zheng & Zhuoqun Sun & Zhirui Ye, 2020. "A Model Tree-Based Vehicle Emission Model at Freeway Toll Plazas," Sustainability, MDPI, vol. 12(21), pages 1-15, October.
    12. Ma, Xiaolei & Miao, Ran & Wu, Xinkai & Liu, Xianglong, 2021. "Examining influential factors on the energy consumption of electric and diesel buses: A data-driven analysis of large-scale public transit network in Beijing," Energy, Elsevier, vol. 216(C).
    13. Dennis Dreier & Semida Silveira & Dilip Khatiwada & Keiko V. O. Fonseca & Rafael Nieweglowski & Renan Schepanski, 2019. "The influence of passenger load, driving cycle, fuel price and different types of buses on the cost of transport service in the BRT system in Curitiba, Brazil," Transportation, Springer, vol. 46(6), pages 2195-2242, December.
    14. García, Antonio & Monsalve-Serrano, Javier & Lago Sari, Rafael & Tripathi, Shashwat, 2022. "Life cycle CO₂ footprint reduction comparison of hybrid and electric buses for bus transit networks," Applied Energy, Elsevier, vol. 308(C).
    15. Agarwal, Avinash Kumar & Mustafi, Nirendra Nath, 2021. "Real-world automotive emissions: Monitoring methodologies, and control measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    16. Ali Keyvanfar & Arezou Shafaghat & Nasiru Zakari Muhammad & M. Salim Ferwati, 2018. "Driving Behaviour and Sustainable Mobility—Policies and Approaches Revisited," Sustainability, MDPI, vol. 10(4), pages 1-27, April.
    17. Rosero, Fredy & Fonseca, Natalia & López, José-María & Casanova, Jesús, 2020. "Real-world fuel efficiency and emissions from an urban diesel bus engine under transient operating conditions," Applied Energy, Elsevier, vol. 261(C).
    18. Li, Peilin & Zhao, Pengjun & Brand, Christian, 2018. "Future energy use and CO2 emissions of urban passenger transport in China: A travel behavior and urban form based approach," Applied Energy, Elsevier, vol. 211(C), pages 820-842.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2936-:d:233646. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.