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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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publications
The impact of the Western Ghats on lightning activity on the western coast of India
Published in Atmospheric Research, 2015
Recommended citation: A.K. Kamra, A.A. Nair, "The impact of the Western Ghats on lightning activity on the western coast of India." Atmospheric Research, 2015. https://doi.org/10.1016/j.atmosres.2015.03.006
Long-Term Trend of Gaseous Ammonia Over the United States: Modeling and Comparison With Observations
Published in Journal of Geophysical Research: Atmospheres, 2018
Recommended citation: Fangqun Yu, Arshad Nair, Gan Luo, "Long-Term Trend of Gaseous Ammonia Over the United States: Modeling and Comparison With Observations." Journal of Geophysical Research: Atmospheres, 2018. https://doi.org/10.1029/2018jd028412
Spatioseasonal Variations of Atmospheric Ammonia Concentrations Over the United States: Comprehensive Model-Observation Comparison
Published in Journal of Geophysical Research: Atmospheres, 2019
Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Spatioseasonal Variations of Atmospheric Ammonia Concentrations Over the United States: Comprehensive Model-Observation Comparison." Journal of Geophysical Research: Atmospheres, 2019. https://doi.org/10.1029/2018jd030057
Wintertime new particle formation and its contribution to cloud condensation nuclei in the Northeastern United States
Published in Atmospheric Chemistry and Physics, 2020
Recommended citation: Fangqun Yu, Gan Luo, Arshad Nair, James Schwab, James Sherman, Yanda Zhang, "Wintertime new particle formation and its contribution to cloud condensation nuclei in the Northeastern United States." Atmospheric Chemistry and Physics, 2020. https://doi.org/10.5194/acp-20-2591-2020
Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling
Published in Atmosphere, 2020
Recommended citation: Arshad Nair, Fangqun Yu, "Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling." Atmosphere, 2020. https://doi.org/10.3390/atmos11101092
Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements
Published in Atmospheric Chemistry and Physics, 2020
Recommended citation: Arshad Nair, Fangqun Yu, "Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements." Atmospheric Chemistry and Physics, 2020. https://doi.org/10.5194/acp-20-12853-2020
On the Ship Particle Number Emission Index: Size-Resolved Microphysics and Key Controlling Parameters
Published in Journal of Geophysical Research: Atmospheres, 2021
Recommended citation: Jingbo Mao, Yan Zhang, Fangqun Yu, Arshad Nair, Qi Yu, Lin Wang, Weichun Ma, Limin Chen, "On the Ship Particle Number Emission Index: Size-Resolved Microphysics and Key Controlling Parameters." Journal of Geophysical Research: Atmospheres, 2021. https://doi.org/10.1029/2020jd034427
Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud-Forming Particles
Published in Geophysical Research Letters, 2021
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
The independent and synergistic impacts of power outages and floods on hospital admissions for multiple diseases
Published in Science of The Total Environment, 2022
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
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
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
Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations
Published in Environmental Pollution, 2022
Recommended citation: Shao Lin, Ian Ryan, Sanchita Paul, Xinlei Deng, Wangjian Zhang, Gan Luo, Guang-Hui Dong, Arshad Nair, Fangqun Yu, "Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations." Environmental Pollution, 2022. https://doi.org/10.1016/j.envpol.2022.119795
Particle number concentrations and size distributions in the stratosphere: Implications of nucleation mechanisms and particle microphysics
Published in Atmospheric Chemistry and Physics, 2023
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
The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States
Published in Science of The Total Environment, 2023
Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States." Science of The Total Environment, 2023. https://doi.org/10.1016/j.scitotenv.2022.160756
talks
Comparison of GEOS-Chem simulated ammonia concentration with observation
Published:
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Recommended citation: Arshad Nair, Gan Luo, Fangqun Yu, "Comparison of GEOS-Chem simulated ammonia concentration with observation." Poster presented at the 8th International GEOS-Chem Meeting, Harvard University, Boston, MA, USA, 2017.
Comparison of Model Simulated Ammonia with Observations: A Case for Implementation of Improved Gas/Aerosol Partitioning Schemes
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Comparison of Model Simulated Ammonia with Observations: A Case for Implementation of Improved Gas/Aerosol Partitioning Schemes." Talk presented at the 36th American Association for Aerosol Research (AAAR) Annual Conference, Raleigh, NC, USA, 2017.
Atmospheric Ammonia over the United States: Comprehensive Model-Observation Comparisons
Published:
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Recommended citation: Arshad Nair, Gan Luo, Fangqun Yu, "Atmospheric Ammonia over the United States: Comprehensive Model-Observation Comparisons." Paper presented at the American Geophysical Union (AGU) Fall Meeting 2018, Washington, DC, USA, 2018.
Atmospheric Ammonia over the United States: Comprehensive Model-Observation Comparisons
Published:
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Recommended citation: Arshad Nair, Gan Luo, Fangqun Yu, "Atmospheric Ammonia over the United States: Comprehensive Model-Observation Comparisons." Paper presented at the NYSDEC DAR BAQAR scientific meeting 2018, Albany, NY, USA, 2018.
Spatio-seasonal Variations of Atmospheric Ammonia: Comprehensive Model–Observation Comparisons
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Spatio-seasonal Variations of Atmospheric Ammonia: Comprehensive Model--Observation Comparisons." Poster presented at the 9th International GEOS-Chem Meeting, Harvard University, Boston, MA, USA, 2019.
Assessment of Model-Simulated Global Atmospheric Ammonia with Satellite Remote Sensing Measurements
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Assessment of Model-Simulated Global Atmospheric Ammonia with Satellite Remote Sensing Measurements." Poster presented at the 37th American Association for Aerosol Research (AAAR) Annual Conference, Portland, OR, USA, 2019.
Ammonium and Ammonia: Concentration Trends in the Northeast United States
Published:
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Recommended citation: James Schwab, Hesham Hassan, Matthew Ninneman, Joseph Marto, Jie Zhang, Sara Lance, Christopher Lawrence, Fangqun Yu, Gan Luo, Arshad Nair, Kevin Civerolo, Oliver Rattigan, "Ammonium and Ammonia: Concentration Trends in the Northeast United States." Poster presented at the 37th American Association for Aerosol Research (AAAR) Annual Conference, Portland, OR, USA, 2019.
Particle Number Concentrations and Their Controlling Parameters: Predictive analysis using machine learning
Published:
Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Particle Number Concentrations and Their Controlling Parameters: Predictive analysis using machine learning." Poster presented at the 100th American Meteorological Society (AMS) Annual Meeting, Boston, MA, USA, 2020. https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/369157
Particle Number Concentrations and Their Controlling Parameters: Predictive analysis using machine learning
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, Gan Luo, "Particle Number Concentrations and Their Controlling Parameters: Predictive analysis using machine learning." Paper presented at the NYS DEC-DAR-BAQAR scientific meeting 2020, Albany, NY, USA, 2020.
Predicting atmospheric particle number concentrations using machine learning
Published:
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Recommended citation: Arshad Nair, "Predicting atmospheric particle number concentrations using machine learning." Paper presented at the Atmospheric Sciences Research Center Friday Colloquy, Albany, NY, USA, 2020.
Use of machine learning to reduce uncertainty in anthropogenic radiative forcing associated with aerosol-cloud interactions
Published:
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Recommended citation: Fangqun Yu, Gan Luo, Arshad Nair, "Use of machine learning to reduce uncertainty in anthropogenic radiative forcing associated with aerosol-cloud interactions." Paper presented at the American Geophysical Union (AGU) Fall Meeting 2020, Virtual, 2020.
Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, "Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements." Paper presented at the American Geophysical Union (AGU) Fall Meeting 2020, Virtual, 2020.
Using Data from NASA Suborbital Campaigns to Validate a Machine Learning Algorithm for Predicting Cloud Condensation Nuclei
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, "Using Data from NASA Suborbital Campaigns to Validate a Machine Learning Algorithm for Predicting Cloud Condensation Nuclei." Paper presented at the 101st American Meteorological Society (AMS) Annual Meeting, Virtual, 2021.
The Role of Ammonia in Atmospheric New Particle Formation and Aerosol Number Abundance at the Southern Great Plains Site
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, "The Role of Ammonia in Atmospheric New Particle Formation and Aerosol Number Abundance at the Southern Great Plains Site." Paper presented at the 39th American Association for Aerosol Research (AAAR) Annual Conference, Virtual, 2021.
GEOS-Chem-APM for physics-informed machine learning emulators and parameterizations
Published:
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Recommended citation: Arshad Nair, Fangqun Yu, "GEOS-Chem-APM for physics-informed machine learning emulators and parameterizations." Oral presentation at the 10th International GEOS-Chem Meeting, Washington University, St. Louis, MO, USA, 2022.
Race-ethnicity disparities in COVID-19 outcomes may be worsened by shorter- and long-term aerosol pollutants exposure
Published:
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Recommended citation: Arshad Nair, Ian Ryan, Gan Luo, Xinlei Deng, Wangjian Zhang, Fangqun Yu, Shao Lin, "Race-ethnicity disparities in COVID-19 outcomes may be worsened by shorter- and long-term aerosol pollutants exposure." Oral presentation at the International Conference on Environment and Human Health: Challenges and Opportunities in the 21st Century, Virtual, 2022.
Race-ethnicity disparities in COVID-19 outcomes may be worsened by shorter- and long-term aerosol pollutants exposure
Published:
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Recommended citation: Arshad Nair, Ian Ryan, Gan Luo, Xinlei Deng, Wangjian Zhang, Fangqun Yu, Shao Lin, "Race-ethnicity disparities in COVID-19 outcomes may be worsened by shorter- and long-term aerosol pollutants exposure." Oral presentation at the 34th Annual Conference of the International Society of Environmental Epidemiology (ISEE), Virtual, 2022.
Socioeconomic disparities in aerosol pollutant exposure may be amplified by ultrafine particles despite declining PM$_{2.5}$
Published:
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Recommended citation: Arshad Nair, Gan Luo, Ian Ryan, Xinlei Deng, Shao Lin, Fangqun Yu, "Socioeconomic disparities in aerosol pollutant exposure may be amplified by ultrafine particles despite declining PM$_2.5$." Oral presentation at the 34th Annual Conference of the International Society of Environmental Epidemiology (ISEE), Virtual, 2022.
teaching
Machine Learning and Aerosol Microphysics
Graduate course module, University at Albany, Department of Atmospheric and Environmental Sciences, 2022
This was a four-hour module providing an overview of Machine Learning and its use in atmospheric and aerosol science, where we reviewed literature and also worked through a hands-on practical example.
Aerosol exposure and COVID-19
Graduate course module, University at Albany, Department of Environmental Health Sciences, 2023
This was a one-hour module providing a quick look at aerosol exposure impacts on COVID-19 and its outcomes. Specifically, we looked at exposure disparities, health disparities, aerosol-health associations, and considered the implications under a changing climate.