Simulation of Emissions From Fuel Consumption of Passenger Vehicles in Tehran and Proposal of Mitigation Strategies

Abstract

Air pollution stands as one of the most critical challenges facing the world and Iran today, necessitating precise policy-making and systemic modeling. This study employs a cohort-based system dynamics approach to simulate both future vehicle numbers and pollutant emissions. This systemic method enables the consideration of temporal changes and dynamic factors such as vehicle age, purchase rates, depreciation, and transportation policies. A two-subsystem model is developed for Tehran’s transport sector. The first subsystem simulates the number of vehicles based on vehicle cohorts (divided into five age groups), with each cohort treated as a stock variable reflecting the number of vehicles in each age group over time. The second subsystem calculates carbon dioxide (CO₂) emissions based on the number of vehicles driven, distance traveled, and emission rates per kilometer. Results indicate that population growth will lead to a rising trend in both vehicle numbers and CO₂ emissions, worsening Tehran’s environmental indicators in the future. Therefore, effective policies are essential. Recommended policies include adjusting fuel prices, improving vehicle technology, modifying depreciation rates, and removing outdated vehicles. Findings show that increasing fuel prices can positively impact vehicle demand and reduce air pollution. Ultimately, a combination of these policies yields the most effective results. Based on the study, it is recommended that fuel prices be increased according to a phased plan, while also implementing targeted measures to enhance vehicle manufacturing technology and engine efficiency