IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v105y2022ics0966692322002009.html
   My bibliography  Save this article

Exploring the Spatial-temporal dynamics of travel patterns and air pollution exposure of E-scooters

Author

Listed:
  • Vallamsundar, Suriya
  • Jaikumar, Rohit
  • Venugopal, Madhusudhan

Abstract

Dockless mobility has been the biggest disruptive force in the shared mobility industry solving the “first-last” mile issue. With their high adoption levels combined with little to no regulation regarding their usage, these users have been driving along with motorized vehicles exposing them to major concerns. The users are exposed to high levels of traffic-related air pollution (TRAP) due to their direct exposure to vehicle exhaust. This study aims to understand the spatial and temporal dimensions of this emerging transportation mode in terms of travel behavior patterns, geographical aspects of travel, interactions between the travel route taken with the existing vehicle traffic, and resulting air pollution and exposure. The travel behavior patterns are evaluated through spatial-temporal analysis of a sample of e-scooter trip data collected in 2018 in the City of Austin and an online travel behavior survey. The analysis identified areas with peak usage, and peak ridership time. The survey results found the e-scooter user demographics to be mostly white males, in the 26–45 age range, with an undergraduate degree and working full-time. Secondly, key responded in influencing the use of an e-scooter are trip length, connectivity to transit, congestion and parking issues, and pollution reduction. Thirdly, e-scooter predominantly replaced personal vehicles and shared ridership in case of home-to-work trips and replaced walking for connecting to transit stops. The exposure to TRAP was obtained by integrating the spatial-temporal dynamics of e-scooter trips with spatial-temporal dynamics of pollutant concentrations modeled from traffic. Exposure analysis found peak exposure levels during midday and evening periods focused in the Central Austin area. This area houses the University of Texas campus and several neighborhoods with lots of shopping, restaurants, bars, and live music avenues. The findings are useful for policymakers and planners when planning for infrastructure changes air pollution control measures, incentive programs, and policies to motivate shared mobility.

Suggested Citation

  • Vallamsundar, Suriya & Jaikumar, Rohit & Venugopal, Madhusudhan, 2022. "Exploring the Spatial-temporal dynamics of travel patterns and air pollution exposure of E-scooters," Journal of Transport Geography, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:jotrge:v:105:y:2022:i:c:s0966692322002009
    DOI: 10.1016/j.jtrangeo.2022.103477
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692322002009
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2022.103477?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Foissaud, Nicolas & Gioldasis, Christos & Tamura, Shun & Christoforou, Zoi & Farhi, Nadir, 2022. "Free-floating e-scooter usage in urban areas: A spatiotemporal analysis," Journal of Transport Geography, Elsevier, vol. 100(C).
    2. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future," Institute of Transportation Studies, Working Paper Series qt79v822k5, Institute of Transportation Studies, UC Davis.
    3. McKenzie, Grant, 2019. "Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C," Journal of Transport Geography, Elsevier, vol. 78(C), pages 19-28.
    4. Shaheen, Susan A & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present and Future," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6qg8q6ft, Institute of Transportation Studies, UC Berkeley.
    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. Zhang, Yuting & Nelson, John D. & Mulley, Corinne, 2024. "Learning from the evidence: Insights for regulating e-scooters," Transport Policy, Elsevier, vol. 151(C), pages 63-74.
    2. Colovic, Aleksandra & Prencipe, Luigi Pio & Giuffrida, Nadia & Ottomanelli, Michele, 2024. "A multi-objective model to design shared e-kick scooters parking spaces in large urban areas," Journal of Transport Geography, Elsevier, vol. 116(C).

    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. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    2. Li, Shaoying & Zhuang, Caigang & Tan, Zhangzhi & Gao, Feng & Lai, Zhipeng & Wu, Zhifeng, 2021. "Inferring the trip purposes and uncovering spatio-temporal activity patterns from dockless shared bike dataset in Shenzhen, China," Journal of Transport Geography, Elsevier, vol. 91(C).
    3. Younes, Hannah & Zou, Zhenpeng & Wu, Jiahui & Baiocchi, Giovanni, 2020. "Comparing the Temporal Determinants of Dockless Scooter-share and Station-based Bike-share in Washington, D.C," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 308-320.
    4. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.
    5. Pucher, John & Buehler, Ralph & Seinen, Mark, 2011. "Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 451-475, July.
    6. Yu Du & Xian Ji & Chenxi Dou & Rui Wang, 2024. "Boosting Winter Green Travel: Prioritizing Built Environment Enhancements for Shared Bike Users Accessing Public Transit in the First/Last Mile Using Machine Learning and Grounded Theory," Sustainability, MDPI, vol. 16(22), pages 1-25, November.
    7. Alexandros Nikitas, 2019. "How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    8. Tomasz Bieliński & Łukasz Dopierała & Maciej Tarkowski & Agnieszka Ważna, 2020. "Lessons from Implementing a Metropolitan Electric Bike Sharing System," Energies, MDPI, vol. 13(23), pages 1-21, November.
    9. Levy, Nadav & Golani, Chen & Ben-Elia, Eran, 2019. "An exploratory study of spatial patterns of cycling in Tel Aviv using passively generated bike-sharing data," Journal of Transport Geography, Elsevier, vol. 76(C), pages 325-334.
    10. Hyungkyoo Kim, 2020. "Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
    11. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "A Latent Segmentation Multinomial Logit Approach to Examine Bicycle Sharing System Users' Destination Preferences," 57th Transportation Research Forum (51st CTRF) Joint Conference, Toronto, Ontario, May 1-4, 2016 319270, Transportation Research Forum.
    12. Zhou, Xiaolu & Wang, Mingshu & Li, Dongying, 2019. "Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    13. Wang, Xize & Lindsey, Greg & Schoner, Jessica E. & Harrison, Andrew, 2016. "Modeling bike share station activity: Effects of nearby businesses and jobs on trips to and from stations," SocArXiv stav4, Center for Open Science.
    14. Chrysa Vizmpa & George Botzoris & Panagiotis Lemonakis & Athanasios Galanis, 2023. "Micromobility in Urban Trail Paths: Expanding and Strengthening the Planning of 15-Minute Cities," Land, MDPI, vol. 12(12), pages 1-22, December.
    15. Virginie Boutueil & Luc Nemett & Thomas Quillerier, 2021. "Trends in Competition among Digital Platforms for Shared Mobility: Insights from a Worldwide Census and Prospects for Research," Post-Print hal-03388213, HAL.
    16. Mohammed Elhenawy & Hesham A. Rakha & Youssef Bichiou & Mahmoud Masoud & Sebastien Glaser & Jack Pinnow & Ahmed Stohy, 2021. "A Feasible Solution for Rebalancing Large-Scale Bike Sharing Systems," Sustainability, MDPI, vol. 13(23), pages 1-19, December.
    17. Shahram Heydari & Garyfallos Konstantinoudis & Abdul Wahid Behsoodi, 2021. "Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-16, December.
    18. Parkes, Stephen & Mardsen, Greg & Shaheen, Susan PhD & Cohen, Adam, 2013. "Understanding the Diffusion of Public Bikesharing Systems: Evidence from Europe and North America," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3qr9h2pr, Institute of Transportation Studies, UC Berkeley.
    19. Younes, Hannah & Nasri, Arefeh & Baiocchi, Giovanni & Zhang, Lei, 2019. "How transit service closures influence bikesharing demand; lessons learned from SafeTrack project in Washington, D.C. metropolitan area," Journal of Transport Geography, Elsevier, vol. 76(C), pages 83-92.
    20. Alain Quilliot & Antoine Sarbinowski & Hélène Toussaint, 2021. "Vehicle driven approaches for non preemptive vehicle relocation with integrated quality criterion in a vehicle sharing system," Annals of Operations Research, Springer, vol. 298(1), pages 445-468, March.

    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:eee:jotrge:v:105:y:2022:i:c:s0966692322002009. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    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.