Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollutionZhongcheng Zhang, Guoliang Shi, Bo Xu et al.|Environmental Research|2022Cited by 92
Aerosol pH Dynamics During Haze Periods in an Urban Environment in China: Use of Detailed, Hourly, Speciated Observations to Study the Role of Ammonia Availability and Secondary Aerosol Formation and Urban EnvironmentGuoliang Shi, Armistead G. Russell, Xiaohui Bi et al.|Journal of Geophysical Research Atmospheres|2019Cited by 70
Roles of RH, aerosol pH and sources in concentrations of secondary inorganic aerosols, during different pollution periodsJie Gao, Yinchang Feng, Yuting Wei et al.|Atmospheric Environment|2020Cited by 65
Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location dataXiaonan Yu, Cesunica E. Ivey, Zhijiong Huang et al.|Environment International|2020Cited by 63
Targeting Atmospheric Oxidants Can Better Reduce Sulfate Aerosol in China: H<sub>2</sub>O<sub>2</sub> Aqueous Oxidation Pathway Dominates Sulfate Formation in HazeJie Gao, Athanasios Nenes, Guoliang Shi et al.|Environmental Science & Technology|2022Cited by 61