Work

AQI ML Estimation

Year: 2025

Type: article

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

Source: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

DOI: 10.55041/ijsrem48125

Authors: author, Dr. Shalini Goel

Language: English

Topic: Air Quality Monitoring and Forecasting

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Clean water and sanitation, Good health and well-being, Climate action, Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W4410464488

FWCI:

Cites: 8

Cited by:

Related to: 10