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Five Presentationts from Wang Lab in AGU 2023

Members from Wang Lab will deliver five presentations (2 talks, 2 posters, 1 eLightning) and contribute to another 8 presentations in this year's AGU Fall Meeting.

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  • This work introduces a ML-based source apportionment model that leverages multiscale aerosol composition data to achieve near-real-time tracking and accurate quantification of PM2.5 sources. The findings support near-real-time source analysis and integration into policy.