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Volume 17, issue 5 | Copyright

Special issue: Regional transport and transformation of air pollution in...

Atmos. Chem. Phys., 17, 3301-3316, 2017
https://doi.org/10.5194/acp-17-3301-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 07 Mar 2017

Research article | 07 Mar 2017

A possible pathway for rapid growth of sulfate during haze days in China

Guohui Li1, Naifang Bei2, Junji Cao1, Rujin Huang1, Jiarui Wu1, Tian Feng1,2, Yichen Wang1, Suixin Liu1, Qiang Zhang3, Xuexi Tie1, and Luisa T. Molina4,5 Guohui Li et al.
  • 1Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
  • 2School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
  • 3Department of Earth System Science, Tsinghua University, Beijing, China
  • 4Molina Center for Energy and the Environment, La Jolla, CA, USA
  • 5Massachusetts Institute of Technology, Cambridge, MA, USA

Abstract. Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM2. 5) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM2. 5, iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies.

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