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Geospatial AI, machine learning to be used for monitoring air quality

Diwakar was speaking at the India Clean Air Summit (ICAS) 2023 organised by the Centre for Air Pollution Studies (CAPS) at the Center for Study of Science, Technology, and Policy (CSTEP) in Bengaluru

Delhi Pollution
Delhi Pollution
Press Trust of India New Delhi
2 min read Last Updated : Aug 24 2023 | 10:52 PM IST

Geospatial artificial intelligence and machine learning based models will soon be used to monitor air quality in key Indian cities including Delhi, Mumbai, Bengaluru, Chennai, and Kolkata, a senior scientist said on Thursday.

Highlighting the increased use of mathematical modelling tools in India, ISRO chair professor at the National Institute of Advanced Studies P G Diwakar emphasised the importance of linking sustainable development goals and air pollution indicators.

Diwakar was speaking at the India Clean Air Summit (ICAS) 2023 organised by the Centre for Air Pollution Studies (CAPS) at the Center for Study of Science, Technology, and Policy (CSTEP) in Bengaluru.

"We must link up SDGs and air pollution indicators, as highlighted by the United Nations 2030 Agenda, particularly in the context of SDGs 3.9 (which relates to mortality from environmental pollution as per the 2030 SDG Agenda) and 11.6 (which sustainable cities and communities)," Diwakar said.

"Using geospatial technology, we need to establish well-distributed ground observation points to measure in-situ pollution parameters, integrating them with space data for accurate modelling," he added.

The senior scientist detailed how geospatial outlook and space-ground observations are essential for precise pollution estimates. The approach utilises Aerosol Optical Depth (AOD) data derived from satellite sources like INSAT-3D/3DR, MODIs, along with weather data.

"We need to bring in the weather data into the modelling framework such as wind speed, wind direction, surface air pressure, temperature, humidity etc, that play a major role as part of the model," the scientist said.

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Such data could be well-integrated into numerical models to build forecasting and assessment, he said. "These have been tested for Bengaluru and very good results have been seen," Diwakar added.

Diwakar expressed confidence in the model's potential and its extension beyond air pollution to address broader SDGs, such as water pollution and electromagnetic radiation.

Speaking at the event, V Faye McNeill from Columbia University acknowledged India's strides towards clean air, pointing out significant progress in air pollution monitoring and control measures since 2016. She commended initiatives like the National Clean Air Program (NCAP) and the neighbourhood-level monitoring.

Selvi PK, a scientist at the Central Pollution Control Board, highlighted the importance of aligning with NCAP to reduce PM2.5 and PM10 by 30-40 per cent by 2026.

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Topics :Artificial intelligenceMachine LearningAir quality

First Published: Aug 24 2023 | 10:52 PM IST

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