Multi-Criteria Decision-Making for Smog Mitigation: A Comprehensive Analysis of Health, Economic, and Ecological Impacts

Sajida Kousar; Aleena Ansar; Nasreen Kausar; Gul Freen

doi:10.31181/sdmap2120258

Authors

Sajida Kousar Department of Mathematics and Statistics, International Islamic University Islamabad, Pakistan Author https://orcid.org/0000-0001-8157-7909
Aleena Ansar Department of Mathematics and Statistics, International Islamic University Islamabad, Pakistan Author https://orcid.org/0009-0006-2794-9808
Nasreen Kausar Department of Mathematics, Faculty of Arts and Sciences, Yildiz Technical University, Esenler, 34220, Istanbul, T¨urkiye Author https://orcid.org/0000-0002-8659-0747
Gul Freen Department of Mathematics and Statistics, International Islamic University Islamabad, Pakistan Author https://orcid.org/0000-0002-2688-7637

DOI:

https://doi.org/10.31181/sdmap2120258

Keywords:

Smog, Multi-Criteria Decision Making (MCDM), MEREC, Best Worst Method, TOPSIS

Abstract

Smog is a significant threat in Pakistan, having become a persistent issue in recent years. Excessive industrialization, increased reliance on fossil fuels, and increased automobile emissions have all led to epidemic levels of air pollution. Smog, or air pollution, can pose significant risks to humans and plants due to its harmful effects. Air pollution contributes to global health issues, including lung, breathing, and skin ailments. Pakistan, an undeveloped nation, is grappling with the detrimental effects of smog on various sectors such as health, ecology, transportation, and education. This study aims to employ multi-criteria decision-making (MCDM) methodologies to examine points of view on smog-related issues in Pakistan. The analysis will specifically concentrate on smog's health, economic, social, and ecological consequences, and the solutions employed to mitigate its effects. By employing various approaches, such as the Method based on the Removal Effects of Criteria (MEREC) objective weighting technique to determine the weights of each criterion and select the essential criteria, in the best-worst technique, pair-wise comparisons are performed on the best and worst criteria that are selected through MEREC. We have created a designated consistency ratio for the BWM to assess the reliability of comparisons. Entropy is an objective weighting technique used to calculate the weights of the best and worst criteria, and we employ the TOPSIS technique to determine the suitable alternative from a collection of choices by evaluating their
resemblance to an ideal answer.

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References

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