Evaluation of carbon dioxide emission reduction policies in Tehran's urban transportation sector with a system dynamics approach

Subject Areas : Management

Zahra Azarnoosh ¹ , Sina Fard Moradinia ² , Babak Golchin ³ , Rasoul Jani ⁴

1 - Department of Civil Engineering, Ta.C., Islamic Azad University, Tabriz, Iran
2 - Department of Civil Engineering, Ta.C., Islamic Azad University, Tabriz, Iran
3 - Department of Civil Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
4 - Department of Civil Engineering, Ta.C., Islamic Azad University, Tabriz, Iran

Received: 2025-10-03 Accepted : 2025-11-29 Published : 2025-11-26

Keywords: System Dynamics, Carbon Dioxide Emissions, Electric vehicle (EVs), Scenario analysis Fuel Pricing.,

Abstract :

Road transportation, as the most pivotal component of mobility in metropolitan areas, plays a determining role in intensifying local air pollution and increasing the emission of greenhouse gases, particularly carbon dioxide. The inherent complexity of the urban transportation system, with its numerous variables and non-linear feedback loops, makes modeling and evaluating its management policies using conventional methods difficult.

This study was designed to simulate and analyze the trends of energy consumption and carbon dioxide emissions in the intra-city transportation sector of Tehran. To overcome the system's complexities, a System Dynamics model was developed for the 2011-2033 period using Vensim software. The simulation and evaluation of various scenarios revealed that replacing the taxi fleet with electric vehicles leads to a 3.5% reduction in CO₂ emissions. Furthermore, implementing policies to increase gasoline prices to half the FOB price and to the full FOB price level would result in reductions of 9% and 14% in CO₂ emissions by 2033, respectively.

The findings clearly demonstrate the varying effectiveness of sectoral policies and confirm that the electrification of the public fleet (e.g., taxis) is both more environmentally effective and more economically efficient compared to the private sector. This model can serve as a framework for testing other scenarios and supporting macro-level decision-making for the development of sustainable urban transportation.

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