Pre-COVID-19 pandemic: effects on air quality in the three cities of India using fuzzy MCDM model

Abstract

Due to urbanization and industrialization pollution level increases. Air pollution directly affects to human health. Air Quality Indices (AQI) method is related to measuring the concentration of different pollutants PM10, NO2, SO2 and other pollutants. The fuzzy Logic air quality index calculates in single value of AQI defines limits 0 to 1. In this study, a comparison of air quality data of three cities was conducted with the help of fuzzy logic algorithm. It used to evaluating Indices through fuzzy multi criteria decision making (MCDM) framework in which linguistic terms of experts opinion and perception, accordingly computing matrix is constructed for sub criteria. There are five linguistic terms used in this framework to create membership functions such as high significant, significant, average significant, low significant and not significant. The three cities, Bangalore, Mysore, and Hubli-Dharwad air quality datas was taken for analysis and evaluating indices during pre-COVID years (2017, 2018, and 2019). The AQI value shows that Bangalore has the highest pollution level while Mysore has the lowest. Using the fuzzy theory, results show that Bangalore and Hubli-Dharwad decrease in pollution level by -0.074921% and -0.04797%. Negative sign shows the decrease pollution level while Mysore increase pollution level by 0.011792%. Overall the results show that AQI of Mysore city is low compared to Bangalore and Hubli-Dharwad. Also, this study reveals air quality disseminated through industrial processes and automobile emissions in India cities during pre-COVID pandemic years. Graphical abstract: [Figure not available: see fulltext.]