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Modelling transport-related pollution emissions for the synthetic baseline population of a large Canadian university

Author

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  • Mohammad Hesam Hafezi
  • Naznin Sultana Daisy
  • Lei Liu
  • Hugh Millward

Abstract

Large universities can be considered as special trip generators requiring special Traffic Demand Management (TDM) policies. Due to their unique accessibility, mixed land-use, and welcoming environment for alternative modes, they are well placed to promote active transportation, carpooling, parking management, and shuttle buses. These have direct effects on regional traffic, as well as on the total vehicular emissions of Greenhouse Gases (GHG) and other pollutants. This paper estimates transport-related pollution emissions for university population segments at Dalhousie University, Nova Scotia, comprising undergraduate-students, graduate students, faculty members, and staff. The data used for this study are derived from the Environmentally Aware Commuter Travel Diary Survey (EnACT) conducted in spring 2016. Initially, we generate a 100% synthetic population for the entirety of university commuters. Then, we model transport-related polluting emissions, including carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxide (NOx), particulate matter (PM10 and PM2.5), total hydrocarbon (THC), and volatile organic compounds (VOC), based on the population features and their living zones in relation to campus areas. In this study, five zones are described for emission estimation: on-campus, inner city, suburban area, inner commuter belt, and outer commuter belt. In addition, two emission scenarios are tested, which consider the impacts of changes to transit ridership and auto driving. These scenarios demonstrate how changing the primary travel mode can greatly influence emissions volume. The empirical models provide useful insights that can be utilized to improve TDM policies of university campuses, as well as to analyze environmental mitigation scenarios.

Suggested Citation

  • Mohammad Hesam Hafezi & Naznin Sultana Daisy & Lei Liu & Hugh Millward, 2019. "Modelling transport-related pollution emissions for the synthetic baseline population of a large Canadian university," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 23(4), pages 519-533, October.
    • Handle: RePEc:taf:rjusxx:v:23:y:2019:i:4:p:519-533
    DOI: 10.1080/12265934.2019.1571432
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    Cited by:

    1. Hamad, Khaled & Obaid, Lubna, 2022. "Tour-based travel demand forecasting model for a university campus," Transport Policy, Elsevier, vol. 117(C), pages 118-137.
    2. Beno Mesarec & Branka Trček, 2024. "Suggestions and Solutions for Enhancing Active Commuting to the University of Maribor and Advancing CO 2 Emission Reduction," Sustainability, MDPI, vol. 16(2), pages 1-21, January.
    3. Weiwei Liu & Jin Zhang & Liang Jin & Jieshuang Dong & Osama Alfarraj & Amr Tolba & Qian Wang & Yihao He, 2023. "Sustainable Low-Carbon Layout of Land around Rail Transit Stations Based on Multi-Modal Spatial Data," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    4. Hyungkyoo Kim, 2020. "Land Use Impacts on Particulate Matter Levels in Seoul, South Korea: Comparing High and Low Seasons," Land, MDPI, vol. 9(5), pages 1-16, May.

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