نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه برنامهریزی و مدیریت محیطزیست و HSE، دانشکده محیطزیست، دانشگاه تهران، تهران، ایران
2 گروه محیطزیست، دانشکده منابع طبیعی و کویرشناسی، دانشگاه یزد ، یزد، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Introduction: Over the past two decades, economic growth and increasing migration in Yazd have led to higher demands for housing, transportation, and infrastructure development. Meanwhile, climate change and recurrent droughts have further deteriorated the city’s air quality. These driving forces directly affect pressure variables such as traffic, fuel consumption, and energy loss, as well as pollutant absorption areas, including green and open urban spaces. The increase in urban air pollutants has a negative impact on human health, biodiversity, and building durability. Implemented actions for air pollution control, including limited bicycle lane development, air quality monitoring in industrial parks, and dust storm mitigation plans, have remained insufficient. Considering the progressive trend of air pollution, it is essential to provide policymakers with a comprehensive understanding of the current and future air quality status, along with possible scenarios. This study employs the DPSIR framework and a system dynamics approach to analyze the causal relationships between variables influencing air pollution in Yazd and to model future conditions.
Material and methods: Initially, driving forces, pressures, states, impacts, and responses were identified to better understand the causal relationships within the system. Then, based on the DPSIR framework, six subsystems influencing Yazd’s air quality—population, economy, landscape structure, transportation, energy, and environment—were defined. To analyze landscape structure changes, Fragstats software was employed to calculate the metrics ED, PD, AREA_AM, and CONTAG using land cover maps of Yazd. The causal relationships among variables were illustrated using causal loop diagrams in Vensim software, and stock-flow diagrams were developed to simulate scenarios and predict future trends. Model validation was performed by comparing historical data and simulated results for two variables: urban population and the number of industrial permits, using the coefficient of determination.
Results and discussion: System dynamics modeling revealed that the key variables, including urban population, investments in industrial workshops, and the volume of transferred water to Yazd, have grown by 62%, 54.76%, and 16.54%, respectively. Analysis of landscape structure and the calculated metrics (ED, PD, AREA_AM, CONTAG) indicated that land patches have become more clustered and denser, showing unsuitable distribution patterns and increased fragmentation. As vehicles are the main source of greenhouse gas emissions, the first scenario focused on controlling their numbers. If the number of vehicles remains constant from 2015 to 2040, greenhouse gas emissions would decrease by 26.94%, whereas following the current trend would cause a 33.96% increase. In the second scenario, the effect of reducing industrial permits on air pollution was examined, showing that emissions would drop by 56.01%. Combining scenarios 1 and 2—keeping vehicle numbers constant and reducing industrial permits—would result in the maximum reduction of emissions by 67.04%.
Conclusion: The findings indicate that greenhouse gas emissions from increased vehicle numbers and industrial expansion are the primary contributors to air pollution in Yazd. Therefore, reducing air pollution requires controlling emissions by managing vehicle numbers and urban travel, as well as limiting industrial growth. Promoting the production of environmentally friendly vehicles powered by renewable energy sources can also be an effective solution. Moreover, this study highlights that a one-dimensional perspective is insufficient for addressing urban air pollution. Tackling this complex challenge requires an integrated and holistic approach, made possible through system dynamics modeling, which enables the identification of causal relationships, influential variables, and future trends. Additionally, scenario-based analysis provides policymakers with valuable insights for evaluating and selecting effective strategies to mitigate urban air pollution.
کلیدواژهها [English]
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