Papers
* Corresponding author.
2026
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Quantifying Black Carbon Mixing State Heterogeneity Using a Machine Learning ModelUnder review at Journal of Geophysical Research: Atmospheres, 2026 -
Machine learning-derived surface tension in climate models and its implications for CCN activationin prep, 2026 -
Investigating the competition in cloud droplets activation by different aerosol systems using cloud chamber experiment datasets and modellingin prep, 2026 -
Diagnosing the Role of Mixing State in Biomass-Burning Aerosol Optical Properties Using Particle-Resolved Modelingin prep, 2026 -
A diagnostic scaling framework for connecting surfactant-induced CCN perturbations to global aerosol–cloud forcing patternsin prep, 2026 -
Compensating biases in CCN predictions from composition averaging and neglected surfactant effects [link]Under review at Atmospheric Chemistry and Physics, 2026 -
Role of liquid-liquid phase separation-induced surface tension changes in cloud droplet activation [link]Aerosol Science and Technology, 2026
Before PhD
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Modeling the high-mercury wet deposition in the southeastern US with WRF-GC-Hg v1. 0 [link]Geoscientific Model Development, 2022 -
Substantial changes in nitrogen dioxide and ozone after excluding meteorological impacts during the COVID-19 outbreak in mainland China [link]Environmental Science & Technology Letters, 2020 -
Characterization of size-resolved urban haze particles collected in summer and winter at Taiyuan City, China using quantitative electron probe X-ray microanalysis [link]Atmospheric Research, 2017 -
Influences of Biomass and Coal Burning on Ambient Fine Particulate Matter over Taiyuan City [link]Journal of Anhui Agriculture Science, 2016