A system dynamics model for a holistic analysis of urban NOx emissions: a case study of Tehran, Iran

Ahamadreza Tahsiri () and Mohammadjavad Arab ()
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Ahamadreza Tahsiri: K.N. Toosi University of Technology
Mohammadjavad Arab: K.N. Toosi University of Technology

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 7, No 60, 7299-7323

Abstract: Abstract Nowadays, a big effort has been made to find the right solution strategy for controlling the complex, multidimensional and diverse problem of urban air pollution. However, despite good development in this area, academia and governance divisions are still investing the development with a reliable methodology for examining the full scope of the problem under real conditions. This paper thus proposes a system dynamic-based model that is capable of representing the full pattern of behaviour of NOx emission in metropolitan settings, dependent on a network of contributing factors. The study identifies five underlying interconnected subsystems, each of which potentially causes a significant level of NOx pollution, and the consequence synergy, stemming from the operation of all subsystems together. These are: (1) the sector of the economy, (2) the population structure and changes, (3) urban transport operations, (4) the performance of industries and businesses sector, and (5) energy production level and method. The Vensim software simulated the model using 15 years of data from Tehran-related activities. The simulation takes into account four different scenarios: (a) maintaining the existing trends in business and industries; (b) enhancing the energy sector’s productivity; (c) improving the transport management system’s efficiency; and (d) a mixed scenario situation, applying the second (b) and the third (c) scenarios simultaneously.

Keywords: Air pollution management; System dynamics modelling; NOx emission; Tehran; Vensim software; Urban system (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02323-5

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