A hybrid MCDM framework and simulation analysis for the assessment of worst polluted cities

Abstract

Monitoring of cities based on different air pollutants is required to manage the quality of air. The worldwide ranking is based on the one air pollutant PM2.5. The main purpose of the work is to find the worst air polluted city in India based on multiple pollutants. A hybrid framework namely “Analytic Hierarchy Process-Combinative Distance-Based Assessment (A-CODAS) is introduced to anSIMPAT102540alyze and rank the cities based on quality of air. The AHP technique is used to assign the priority weights to the multiple air pollutants whereas CODAS approach is used to rank the cities and to find the city with the worst air quality in 2020. The simulation analysis is performed on the seven worst polluted cities of India. The proposed framework is validated by performing the spearman's correlation ranking with other two existing multicriteria decision-making approaches namely “Analytic Hierarchy Process” and “Technique for Order Preference by Similarity to Ideal Solution”. Sensitivity analysis is also performed considering different scenarios to determine the dependency of a particular pollutant on the quality of air or to check whether the priority weights affect the ranking of the cities. The results prove the consistency and efficiency of the proposed model.