A Fuzzy TOPSIS Framework for Assessment of Air Quality Index Values Across Different Stations- A Case Study on Kolkata in India

Abstract

The Air Quality Index (AQI) is a critical measure for assessing air pollution levels, directly impacting public health and environmental sustainability. As urbanization and industria-lization continue to expand, the need for advanced methodologies to evaluate and compare AQI across different locations has grown significantly. Traditional AQI computation methods often struggle to handle the uncertainties and complexities associated with multiple pollutants. This study applies a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to enhance AQI evaluation and classification. Using data from the West Bengal Central Pollution Control Board (WBPCB) for the period January 2023 to December 2023, AQI values are computed based on 24-hour average pollutant concentrations. The fuzzy AQI (FAQI) values derived from the proposed method are compared with conventionally computed AQI values, demonstrating strong alignment while offering additional classification insights. The results indicate variations in air pollution levels across the seven stations analyzed, with Ultadanga emerging as the most polluted location and Tollygunge exhibiting the best air quality among them. In addition, the classification process categorizes the stations into different groups. Notably, none of the stations qualify as ‘Good’ in terms of air quality.