The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Incorporating Geophysical a Priori Information into a Deep Learning Model for Nitrogen Dioxide Estimation (AGU25)

Incorporating Geophysical a Priori Information into a Deep Learning Model for Nitrogen Dioxide Estimation

Yu Yan, Washington University in St Louis, St. Louis, MO, United States, Siyuan Shen, Washington University in St. Louis, Department of Energy, Environmental & Chemical Engineering, St. Louis, United States and Randall Martin, Washington University in St. Louis, Department of Energy, Environmental, & Chemical Engineering, St. Louis, United States
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