Evaluation of air pollution effects in Yazd city based on DPSIR framework and system dynamics approach

Introduction: Since immigration and economic expansion have occurred concurrently in Yazd over the last two decades, housing and transportation requirements have increased, as has infrastructure development to support these needs. Moreover, climate change and a succession of droughts have adversely affected the city's air quality. Urban air pollution is a major problem that affects the environment, human health, and structures. To reduce air pollution in the city of Yazd, present efforts include the construction of restricted bicycle routes, the monitoring and regulation of air pollution in industrial areas, and the implementation of fine particulate control systems.This study used the DPSIR framework and the system dynamics technique to establish causal relationships between the influencing variables and city air pollution.
Material and methods: To gain a more comprehensive understanding of the cause-and-effect relationships that govern the system, the driving force, pressure, state, impact, and response variables were identified in the initial phase of this research methodology. Subsequently, during the modeling phase, the subsystems influencing the air quality were incorporated using the DPSIR framework. These subsystems comprised the environment, population, economy, landscape, transportation, and energy. The causal loop diagram was employed to illustrate the interrelationships among the variables. The stock and flow diagram was utilized in the final stage to generate scenarios and forecast forthcoming trends. The determination coefficient (R2) is a factor in establishing the accuracy of the simulation. Using the determination coefficient, the historical trend and simulation of two variables—urban population and the number of industrial licenses—were compared to validate the model.
Results and discussion: By analyzing the system's critical variables, including urban population, investment in industrial areas, and water transferred to Yazd city, this study determined that their respective growth rates were 62, 54.76, and 16.54 percent. The primary cause of greenhouse gas emissions in the city is vehicles, the initial scenario pertains to regulating their quantity. The quantity of greenhouse gas emissions will decrease by 26.94% between 2015 and 2040 if the number of vehicles remains unchanged; conversely, if the present trajectory persists, it will escalate by 33.96%. In the second scenario, which ensued after the city became industrialized, an examination was conducted to determine the impact of a reduction in the quantity of industrial permits on air pollution. The findings of this study indicate that a reduction in the quantity of industrial licenses corresponds to a 56.01 percent decrease in greenhouse gas emissions. Furthermore, when scenarios 1 and 2 (with the number of vehicles held constant and the number of industrial licenses reduced) are combined, the emissions amount to 67.04 percent.
Conclusion: The results suggest that the primary source of pollution in Yazd city is the emission of greenhouse gases, primarily due to the rise in vehicle usage. On the other hand, the development of industry is the driving force behind the urban expansion. Consequently, reducing greenhouse gas emissions is one of the most effective methods for mitigating air pollution. Regulating the number of vehicles and intercity travel, as well as regulating industry, can accomplish this. Additionally, the development of fuel-efficient automobiles powered by renewable energy sources could serve as a viable approach to mitigating air pollution. The findings of this study demonstrate that a unidimensional approach to addressing the intricate issue of urban air pollution is ineffective. Instead, to implement comprehensive and integrated measures, it is necessary to identify inter-scale and cause-and-effect relationships. System dynamics is an appropriate methodology for comprehending such matters. It provides planners and decision-makers with a clear representation of the issue at hand, identifies effective and efficient variables, and explains the causal relationships that connect them.