Publications

Particle number concentrations and size distributions in the stratosphere: Implications of nucleation mechanisms and particle microphysics

Published in Atmospheric Chemistry and Physics, 2023

PDF or Access paper here

Recommended citation: Fangqun Yu, Gan Luo, Arshad Nair, Sebastian Eastham, Christina Williamson, Agnieszka Kupc, Charles Brock, "Particle number concentrations and size distributions in the stratosphere: Implications of nucleation mechanisms and particle microphysics." Atmospheric Chemistry and Physics, 2023. https://doi.org/10.5194/acp-2022-487

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

Published in Geophysical Research Letters, 2022

PDF or Access paper here

Recommended citation: Fangqun Yu, Gan Luo, Arshad Nair, Kostas Tsigaridis, Susanne Bauer, "Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models." Geophysical Research Letters, 2022. https://doi.org/10.1029/2022gl098551

The independent and synergistic impacts of power outages and floods on hospital admissions for multiple diseases

Published in Science of The Total Environment, 2022

Access paper here

Recommended citation: Xinlei Deng, Samantha Friedman, Ian Ryan, Wangjian Zhang, Guanghui Dong, Havidan Rodriguez, Fangqun Yu, Wenzhong Huang, Arshad Nair, Gan Luo, Shao Lin, "The independent and synergistic impacts of power outages and floods on hospital admissions for multiple diseases." Science of The Total Environment, 2022. https://doi.org/10.1016/j.scitotenv.2022.154305

Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles

Published in Geophysical Research Letters, 2021

PDF or Access paper here

Recommended citation: Arshad Nair, Fangqun Yu, Pedro Campuzano-Jost, Paul DeMott, Ezra Levin, Jose Jimenez, Jeff Peischl, Ilana Pollack, Carley Fredrickson, Andreas Beyersdorf, Benjamin Nault, Minsu Park, Seong Yum, Brett Palm, Lu Xu, Ilann Bourgeois, Bruce Anderson, Athanasios Nenes, Luke Ziemba, Richard Moore, Taehyoung Lee, Taehyun Park, Chelsea Thompson, Frank Flocke, Lewis Huey, Michelle Kim, Qiaoyun Peng, "Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles." Geophysical Research Letters, 2021. https://doi.org/10.1029/2021gl094133