Geo artificial intelligence (AI) and random forest-based tools and technologies are being utilized in India to predict and monitor air quality in major cities like Delhi, Mumbai, Bengaluru, Chennai, and Kolkata. These tools support the country’s efforts to achieve the Sustainable Development Goals (SDGs) by addressing health-related issues and enhancing cities’ liveability indices. Prof. P G Diwakar, ISRO Chair Professor at the National Institute of Advanced Studies, highlighted the importance of linking SDGs with air pollution indicators and emphasized the need for a geospatial outlook.
To effectively estimate and address air pollution, a geospatial perspective is crucial. Mathematical modeling that integrates space and ground observations, along with weather data, can provide valuable insights into pollutant levels such as Particulate Matter (PM), Nitrogen Oxides (NOx), and Sulfur Oxides (SOx). Prof. Diwakar mentioned the integration of data from ground observations and satellite sources like INSAT-3D, INSAT-3DR, and MODIs to derive Aerosol Optical Depth (AOD), a measure of atmospheric aerosols. Additionally, factors like wind speed, wind direction, temperature, and humidity play a significant role in these models. Prof. Diwakar also emphasized the importance of considering road fractions and their impact on pollution in urban areas.
The adoption of AI and random forest theory, among other machine learning techniques, allows for the seamless estimation of current air quality and accurate forecasting. Prof. Diwakar stated that historical data from satellite and ground sources, spanning over 50 years, is being leveraged to develop these models. The National Institute of Advanced Studies has initiated a pilot project in Bengaluru to assess its effectiveness, with plans to expand this technology to heavily polluted cities like Delhi, Mumbai, Chennai, and Kolkata.
Geospatial data plays a crucial role in this project, with a comprehensive geospatial framework being established to integrate all relevant data seamlessly. As progress is made, the initiative aims to address broader SDGs beyond air pollution, including issues like water pollution and electromagnetic radiation. Prof. Diwakar highlighted the commitment to pioneering transformative solutions that transcend conventional boundaries.
India’s efforts to implement the SDGs and combat air pollution have received global recognition. Prof. V. Faye McNeill from Columbia University commended India’s significant strides towards clean air and the groundwork laid to achieve this goal.
Selvi PK, a scientist from the Central Pollution Control Board, emphasized the comprehensive approach encompassed by SDGs, highlighting the mission to reduce PM2.5 and PM10 levels by 30-40% by 2026 under the National Clean Air Program. Innovative schemes like Extended Producer Responsibility (EPR) aim to reduce emissions across various waste streams. Monitoring progress through centralised data systems like Prana can enhance transparency and oversee initiatives aligned with the broader canvas of SDGs.
Overall, the use of AI and geospatial technology, combined with a holistic approach, holds great promise for India’s efforts to monitor and improve air quality, contributing to sustainable development goals.
