Source apportionment for online dataset at a megacity in China using a new PTT-PMF model
Jie Gao(Tianjin Normal University), Yinchang Feng(Nankai University), Haofei Yu(University of Central Florida), Xing Peng(Nankai University), Shihao Dong(Nankai University), Bo Han(Civil Aviation University of China), Yuting Wei(Nankai University), Wei Wang(Lanzhou University), Guoliang Shi(Nankai University)
Cited by 21
Related Papers
Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollution
|Environmental Research|2022|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 Environment
|Journal of Geophysical Research Atmospheres|2019|70
Roles of RH, aerosol pH and sources in concentrations of secondary inorganic aerosols, during different pollution periods
|Atmospheric Environment|2020|65
Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location data
|Environment International|2020|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 Haze
|Environmental Science & Technology|2022|61