Abstract
The urban transport sector is responsible for a considerable portion of the global greenhouse gas emissions, and considered as a primary contributor of environmental pollutants. This study aims to explore ways to compare transport impacts of alternative urban growth scenarios at different spatial and temporal scales. To achieve this aim, alternative policy scenarios and various transport impact indicators were synthesized from a Delphi survey. Four alternative urban growth scenarios (i.e., business-as-usual, environment-focused, economy-focused, balanced scenarios) for the South East Queensland Region of Australia were evaluated by comparing selected indicator values from transportation models developed for three spatial (i.e., region, city, local) and four temporal (i.e., 2016, 2021, 2031, 2041) scales. The results of the analysis disclose that policies under the balanced scenario make the highest contribution towards achieving sustainable urban development—as this scenario generates the least travel time, travel distance, and traffic congestion. The findings reveal that the empirical approach put forward in this paper is useful to inform urban policymaking, and assist urban policymakers, urban/transport planners, practitioners, and stakeholders.
| Original language | English |
|---|---|
| Article number | 102031 |
| Number of pages | 13 |
| Journal | Sustainable Cities and Society |
| Volume | 55 |
| DOIs | |
| Publication status | Published - Apr 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
Keywords
- Delphi survey
- South East Queensland
- Sustainable urban development
- Transport externalities
- Transport modelling
- Urban growth scenarios
Activities
- 1 External HDR Supervision
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PhD Supervision (Sajida Perveen)
Kamruzzaman, L. (Fellow), Yigitcanlar, T. (Supervisor) & Agdas, D. (Supervisor)
2014 → 2018Activity: External Academic Engagement › External HDR Supervision
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