- A13I-1787: Modeling Black Carbon Dry Deposition and Climate Forcing in the Indo-Gangetic Basin Using a Hybrid Machine Learning and Physical Approach
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Board 1787‚ Hall EFG (Poster Hall)NOLA CC
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Vaishnav Bartaria, Dayalbagh Educational Institute (First Author, Presenting Author)
Auroop Ganguly, Northeastern University
Ashok Jangid, Dayalbagh Education Institute (Deemed University), Dayalbagh, Agra
Black carbon (BC) is a tiny pollutant released into the air from activities like burning biomass, vehicle emissions, and industrial processes. Although BC only stays in the atmosphere for a few days, it can have long-lasting effects on climate, especially when it settles on land, snow, or ice. This study focuses on the Indo-Gangetic Basin (IGB), a region in South Asia that is home to hundreds of millions of people and is one of the world’s most polluted areas. We developed a new approach that combines physical models with machine learning to estimate how much BC is deposited onto the surface across the IGB from 2002 to 2023. We used data from satellites, weather models, and information about the land surface to better understand where and when BC is most likely to settle. Our results show that BC deposition is highest during winter and post-monsoon seasons, especially near cities and areas with heavy crop burning. This research helps fill important knowledge gaps about how BC behaves after being emitted into the air. The method we developed can be used in other regions too, helping scientists and policymakers take steps to reduce pollution and its harmful effects on climate and health.
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