Organization
State University of New York at Albany
Email
Business Phone
Work
(518) 437-8767
Business Address
Atmospheric Sciences Research Cnter
251 Fuller Road
Albany, NY 12203
United States
Website
First Author Publications
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Yu, F., et al. (2022), Particle number concentrations and size distributions in the stratosphere: Implications of nucleation mechanisms and particle microphysics, Atmos. Chem. Phys., doi:10.5194/acp-2022-487.
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Yu, F., et al. (2018), Long-Term Trend of Gaseous Ammonia Over the United States: Modeling and Comparison With Observations, J. Geophys. Res., 123, 8315-8325, doi:10.1029/2018JD028412.
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Yu, F., et al. (2017), Impact of temperature dependence on the possible contribution of organics to new particle formation in the atmosphere, Atmos. Chem. Phys., 17, 4997-5005, doi:10.5194/acp-17-4997-2017.
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Yu, F., et al. (2015), Spring and summer contrast in new particle formation over nine forest areas in North America, Atmos. Chem. Phys. Discuss., 15, 21271-21298, doi:10.5194/acpd-15-21271-2015.
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Yu, F., and G. Luo (2014), Modeling of gaseous methylamines in the global atmosphere: impacts of oxidation and aerosol uptake, Atmos. Chem. Phys., 14, 12455-12464, doi:10.5194/acp-14-12455-2014.
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Yu, F., and A.G. Hallar (2014), Difference in particle formation at a mountaintop location during spring and summer: Implications for the role of sulfuric acid and organics in nucleation, J. Geophys. Res., 119, 12,246-12,255, doi:10.1002/2014JD022136.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
Co-Authored Publications
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Gao, C.Y., et al. (2022), Remote Aerosol Simulated During the Atmospheric Tomography (ATom) Campaign and Implications for Aerosol Lifetime, J. Geophys. Res., 127, doi:10.1029/2022JD036524.
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Nair, A.A., et al. (2021), Machine learning uncovers aerosol size information from chemistry and meteorology to quantify potential cloud-forming particles, Geophys. Res. Lett., doi:10.1029/2021GL094133.
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Zhai, S., et al. (2021), Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations, Atmos. Chem. Phys., 21, 16775-16791, doi:10.5194/acp-21-16775-2021.
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Jia, H., et al. (2020), Distinct Impacts of Increased Aerosols on Cloud Droplet Number Concentration of Stratus/Stratocumulus and Cumulus, Geophys. Res. Lett..
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Luo, G., et al. (2020), Further improvement of wet process treatments in GEOS-Chem v12.6.0: impact on global distributions of aerosols and aerosol precursors, Geosci. Model. Dev., 13, 2879-2903, doi:10.5194/gmd-13-2879-2020.
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Nair, A.A., and F. Yu (2020), Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements, Atmos. Chem. Phys., doi:10.5194/acp-2020-509.
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Travis, K., et al. (2020), Constraining remote oxidation capacity with ATom observations, Atmos. Chem. Phys., 20, 7753-7781, doi:10.5194/acp-20-7753-2020.
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Fanourgakis, G.S., et al. (2019), Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation, Atmos. Chem. Phys., 19, 8591-8617, doi:10.5194/acp-19-8591-2019.
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Luo, G., et al. (2019), Revised treatment of wet scavenging processes dramatically improves GEOS-Chem 12.0.0 simulations of surface nitric acid, nitrate, and ammonium over the United States, Geosci. Model. Dev., 12, 3439-3447, doi:10.5194/gmd-12-3439-2019.
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Nair, A.A., et al. (2019), All Rights Reserved. Spatioseasonal Variations of Atmospheric Ammonia Concentrations Over the United States: Comprehensive Model‐Observation Comparison, J. Geophys. Res., 124, doi:10.1029/2018JD030057.
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Prenni, A., et al. (2019), An examination of the algorithm for estimating light extinction from T IMPROVE particle speciation data, Atmos. Environ., 214, 116880, doi:10.1016/j.atmosenv.2019.116880.
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Williamson, C.J., et al. (2019), A large source of cloud condensation nuclei from new particle formation in the tropics, Nature, 574, 399-403, doi:10.1038/s41586-019-1638-9.
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Williamson, C.J., et al. (2019), A large source of cloud condensation nuclei from new particle formation in the tropics, Nature, doi:10.1038/s41586-019-1638-9.
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Zhang, Y., et al. (2019), Seasonal Variations and Long‐Term Trend of Dust Particle Number Concentration Over the Northeastern United States, J. Geophys. Res., 124, 13,140-13,155, doi:10.1029/2019JD031388.
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Ma, X., et al. (2018), Opposite Aerosol Index-Cloud Droplet Effective Radius Correlations Over Major Industrial Regions and Their Adjacent Oceans, Geophys. Res. Lett., 45, 5771-5778, doi:10.1029/2018GL077562.
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Zhao, X., et al. (2018), Using Long-Term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds Over Global Oceans, J. Geophys. Res., 123, 457-472, doi:10.1002/2017JD027187.
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Ma, X., and F. Yu (2015), Seasonal and spatial variations of global aerosol optical depth: Multi-year modeling and comparisons with multiple-platform observations, Tellus, 67, 25115, doi:10.3402/tellusb.v67.25115.
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Ma, X., et al. (2014), Reassessment of satellite-based estimate of aerosol climate forcing, J. Geophys. Res., 119, 10,394-10,409, doi:10.1002/2014JD021670.
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Tsigaridis, K., et al. (2014), The AeroCom evaluation and intercomparison of organic aerosol in global models, Atmos. Chem. Phys., 14, 10845-10895, doi:10.5194/acp-14-10845-2014.
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English, J.M., et al. (2011), Microphysical simulations of new particle formation in the upper troposphere and lower stratosphere, Atmos. Chem. Phys. Discuss., 11, 12441-12486, doi:10.5194/acpd-11-12441-2011.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
