Sustainability

AI Could Transform Air Pollution Management In India

A study by IIT Indore reveals how AI and machine learning could drastically improve India’s air pollution management by combining advanced technology with robust regulatory frameworks and public engagement

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In their analysis, the researchers calculated PM2.5 concentrations across India, focusing on five key aerosols: black carbon, dust, organic carbon, sea salt, and sulphates. Photo: by freepik
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Researchers from the Indian Institute of Technology (IIT) Indore have published a pivotal study highlighting the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in managing India’s severe air pollution crisis. The research, conducted by the Department of Civil Engineering, calls for a multifaceted strategy that integrates cutting-edge technology, stringent regulatory measures, and active public involvement to address the country's ongoing air quality challenges effectively. 

In their analysis, the researchers calculated PM2.5 concentrations across India, focusing on five key aerosols: black carbon, dust, organic carbon, sea salt, and sulphates. The study identified that regions such as the Indo-Gangetic Plains, as well as parts of Western and Northeast India, are particularly vulnerable to high levels of PM2.5 due to specific local sources of pollution. 

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The study introduces an AI and ML model with exceptional accuracy in predicting PM2.5 concentrations, demonstrating the potential of these technologies to enhance air quality forecasts and stimulate further research in pollution management. Despite these advancements, the study acknowledges significant challenges that remain, including the need for more vigorous regulatory enforcement, enhanced public awareness campaigns, and innovative solutions to bridge the technological divide between rural and urban areas. 

Moreover, to address the transboundary nature of air pollution, the research advocates for tailored regional pollution control strategies, sustainable agricultural practices, and international collaboration. It also suggests that integrating AI and ML with numerical weather prediction models offers a promising approach for real-time monitoring and data-driven decision-making, which are crucial for refining pollution control strategies. 

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The study concludes that India’s future in air pollution management hinges on the synergy between technological innovation and global cooperation, paving the way for a cleaner, more sustainable environment. 

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