فهرست نشریات علمی دسترسی آزاد ایران

This study presents a dynamic analysis of gasoline demand in Iran from 1978 to 2021, employing a system dynamics approach. A comprehensive model was developed to forecast gasoline consumption, incorporating key variables such as population, trip frequency, the number of gasoline-only vehicles, dual-fuel (gasoline-CNG) vehicles, the number of CNG stations, and the consumer price index (CPI). The model explicitly captures the complex and dynamic interrelationships among these variables, providing a nuanced understanding of the factors influencing gasoline consumption. Model validation was performed by comparing model predictions with actual gasoline consumption data from 2006 to 2021. The results demonstrate a satisfactory level of accuracy in simulating past gasoline consumption patterns. Following validation, the model was used to project gasoline demand from 2022 to 2031. In addition to a base scenario, three alternative scenarios were explored to assess the impact of different policy interventions aimed at reducing gasoline consumption. These scenarios involved increasing the number of dual-fuel vehicles, increasing the number of CNG stations, and a combined scenario incorporating both interventions. The projection results indicate that all three alternative scenarios lead to significant reductions in gasoline consumption compared to the base scenario. Notably, the scenario focusing on increasing the number of dual-fuel vehicles had the most substantial impact on reducing gasoline consumption. These findings underscore the importance of developing CNG infrastructure and promoting the adoption of dual-fuel vehicles as effective strategies for reducing gasoline dependence and managing fuel consumption in Iran. This research provides policymakers with a robust dynamic model for informed decision-making in fuel consumption management. Furthermore, the findings and methodology can be broadly applied to similar studies in other countries and related fields of energy and environmental research.