Data Envelopment Analysis: A Novel Approach for Assessing the Efficiency of Air Pollution Mitigation Strategies in Metropolitan Areas

Authors

  • Maryam Ghandehari * Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Fatemeh Kamali Yazdi Department Accounting, Imam Reza International University (AS), Mashhad, Iran.
  • Sahar Habibi Kish Free Zone Organization, Kish, Iran.

https://doi.org/10.48314/tsc.vi.40

Abstract

Air pollution is one of the major challenges faced by large cities, posing significant threats to public health and the environment. This study evaluates the efficiency of three air pollution mitigation strategies—expanding public transportation, replacing old vehicles with electric ones, and imposing restrictions on private vehicle usage—using the Data Envelopment Analysis (DEA) model. The model considers implementation costs and required workforce as inputs, while pollutant reduction and Air Quality Index (AQI) improvement serve as outputs. The findings indicate that replacing old vehicles with electric ones is the most efficient strategy, significantly enhancing air quality. Additionally, public transportation expansion could become an efficient solution if costs are optimized or ridership increases. In contrast, the private vehicle restriction policy requires modifications and integration with complementary incentives. Ultimately, it is recommended that air pollution mitigation strategies be implemented in a combined manner and accompanied by cost-benefit analyses to enhance their effectiveness.

Keywords:

Data envelopment analysis, Air pollution, Efficiency evaluation, Optimization, Sustainable, Development

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Published

2025-03-23

Issue

Vol. 1 No. 1 (2025): Transactions on Soft Computing (TSC)

Section

Articles

How to Cite

Ghandehari, M., Kamali Yazdi, F., & Habibi, S. (2025). Data Envelopment Analysis: A Novel Approach for Assessing the Efficiency of Air Pollution Mitigation Strategies in Metropolitan Areas. Transactions on Soft Computing , 1(1), 61-70. https://doi.org/10.48314/tsc.vi.40