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Discussion papers | Copyright
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Research article 12 Jun 2018

Research article | 12 Jun 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

The Contributions to the Explosive Growth of PM2.5 Mass due to Aerosols-Radiation Feedback and Further Decrease in Turbulent Diffusion during a Red-alert Heavy Haze in JING-JIN-JI in China

Hong Wang1,2, Xioaye Zhang1,3, Yao Peng1,2, Hongli Liu1, Meng Zhang4, and Huizheng Che1 Hong Wang et al.
  • 1State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
  • 2Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • 3Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences (CAS), Xiamen 361021, China
  • 4Beijing Meteorological Bureau, Beijing 100089, China

Abstract. The explosive growth (EG) of PM2.5 mass usually resulted in PM2.5 extreme levels and severe haze pollution in east China and they were generally underestimated by current atmospheric chemical models. Based on the atmospheric chemical model GRPAES_CUACE, three experiments of background (EXP_bk), normal turbulent diffusion and aerosols feedback (EXP_td_af), and retaining 20% of normal turbulent diffusion of chemical tracers of EXP_td_af (EXP_td20_af) are designed to study the contributions to the EG of PM2.5 due to aerosols-radiation feedback (AF) and further decrease in turbulent diffusion (DTD) focusing on a red-alert heavy haze in JING-JIN-JI of China. The study results showed that turbulent diffusion coefficient (DC) calculated by EXP_bk is about 60–70m2/s on clear day and 30–35m2/s on haze day. This difference of DC was not enough to discriminate the unstable atmosphere on clear day and extreme stable atmosphere during EG stage of PM2.5, and the inversion calculated by EXP_bk was obviously weaker than the actual atmosphere of sounding observation on haze day. This led to 40–51% underestimation of PM2.5 EG by EXP_bk; AF reduced about 43–57% of DC during EG stage of PM2.5, which strengthened the local inversion obviously on haze day and local inversion by EXP_td_af was much closer to the sounding observation than that by EXP_bk. This resulted in 20–25% reduction of model errors of PM2.5 and it was as low as −16 to −11%. However, the inversion by EXP_td_af was still weaker than the actual observation and AF could not solve all the problems of PM2.5 underestimation. Based on EXP_td_af, 80% DTD of chemical tracers resulted in a near-zero turbulent diffusion named as turbulent intermittent atmosphere state in EXP_td20_af resulting in a further 14–20% reduction of PM2.5 underestimation and the negative PM2.5 errors of was reduced to −11 to 2% during the EG stage of PM2.5. The combined effects of AF and DTD solved over 79% underestimation of PM2.5 EG in this case study. The results showed that the online calculation of aerosol-radiation feedback and a further improving arithmetic of PBL scheme focusing on extreme stable atmosphere stratification are indispensable for reasonable description of local turbulent intermittent and more accurate prediction of PM2.5 EG and high levels during the severe haze in Jing-Jin-Ji in China.

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Hong Wang et al.
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Hong Wang et al.
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Short summary
The explosive growth (EG) of PM2.5 resulted in PM2.5 maximum which was generally underestimated by atmospheric chemical models due to the deficient description of the local turbulence intermittent; The aerosols radiation feedback (ARF) may reduce 20–25 %, the further decrease in turbulence diffusion (DTD) reduce 14–20 % of underestimation of PM2.5 EG. The modeled PM2.5 error of EG stage was decreased from −40 to −51 % to −11 to 2 % by ty the combined effects of ARF and DTD in Jing-Jin-Ji in China.
The explosive growth (EG) of PM2.5 resulted in PM2.5 maximum which was generally underestimated...