AQI ML Estimation

Abstract— This study applies machine learning to predict the Air Quality Index (AQI) in Delhi, using data from 2015–2022 sourced from the Central Pollution Control Board. It considers key pollutants (PM2.5, PM10, NO₂, SO₂, CO, O₃) and meteorological factors. PM2.5 and vehicular emissions were identified as major AQI contributors. The findings support real-time AQI forecasting and align with UN SDGs 3 and 11, promoting public health and sustainable urban living through data-driven environmental strategies. Keywords— Air Quality Index, Machine Learning, Delhi Pollution, Predictive Modeling, Sustainable Development Goals