Aerosol radiative effects and feedbacks on boundary layer meteorology and PM<sub>2.5</sub> chemical components during winter haze events overthe Beijing–Tianjin–Hebei region

Abstract

<p><strong>Abstract.</strong> An online-coupled regional chemistry/aerosol-climate model (RIEMS-Chem) was developed and utilized to investigate the mechanisms of haze formation and evolution and aerosol radiative feedback during winter haze episodes in February–March 2014 over the Beijing-Tianjin-Hebei (BTH) region in China. Model comparison with a variety of observations demonstrated a good ability of RIEMS-Chem in reproducing meteorological variables, PBL heights, PM<sub>2.5</sub> concentrations and its chemical components, as well as aerosol optical parameters. It was noteworthy that the model performances were remarkably improved for both meteorological variables and aerosol properties by taking aerosol radiative feedback into account, highlighting the necessity of developing online coupled chemistry-climate model. The weak southeasterly winds, high relative humidity and low PBL height favored accumulation and secondary formation of aerosols, resulting in a maximum daily and regional mean PM<sub>2.5</sub> concentration exceeding 136 μg m<sup>−3</sup> in the BTH region. The domain average aerosol radiative effects (AREs) were estimated to be −57 W m<sup>−2</sup> at the surface, 25 W m<sup>−2</sup> in the atmosphere and −32 W  m<sup>−2</sup> at the top of atmosphere (TOA), respectively, during the severe haze episode (20–26 February), and the maximum hourly ARE at the surface reached −384 W m<sup>−2</sup> in the vicinity of Shijiazhuang in southern Hebei province during this episode. The average feedback-induced changes in 2-m air temperature (T2), 10-m wind speed (WS10), 2-m relative humidity (RH2) and planetary boundary layer (PBL) height over the BTH region during the haze episode were −1.8 °C, −0.5 m s<sup>−1</sup>, 10.0 % and −184 m, respectively. The domain average changes in PM<sub>2.5</sub> concentration due to the feedback were estimated to be 20.0 μg m<sup>−3</sup> (29 %) and 45.1 μg m<sup>−3</sup> (39 %) for the entire period and the severe haze episode, respectively, and they were enhanced to 21.1 μg m<sup>−3</sup> (36 %) and 49.3 μg m<sup>−3</sup> (49 %) in terms of daytime mean during the haze episode, which demonstrated a significant impact of aerosol radiative feedback on haze formation. The relative changes in secondary aerosols were larger than those in primary aerosols, because chemical reactions were also enhanced in addition to weakened diffusion by the feedback. The absolute change in PM<sub>2.5</sub> concentrations caused by aerosol feedback was largest in the persistence stage, followed by those in the growth stage and in the dissipating stage. Process analyses on haze events in Beijing revealed that local emission, chemical reaction and regional transport mainly contributed to haze formation in the growth stage, whereas vertical processes (diffusion, advection and dry deposition) were major processes for PM<sub>2.5</sub> removals. Chemical processes and local emissions dominated the increase in PM<sub>2.5</sub> concentrations during the severe haze episode, whereas horizontal advection contributed to the PM<sub>2.5</sub> increase with a similar magnitude to local emissions and chemical processes during a moderate haze episode on 1–4 March. The contributions from physical and chemical processes to the feedback-induced changes in PM<sub>2.5</sub> and its major components were explored and quantified through process analyses. For the severe haze episode, the increase in the change rate of PM<sub>2.5</sub> (9.5 μg m<sup>−3</sup> h<sup>−1</sup>) induced by the feedback in the growth stage was attributed to the larger contribution from chemical processes (7.3 μg m<sup>−3</sup> h<sup>−1</sup>) than that from physical processes (2.2 μg m<sup>−3</sup> h<sup>−1</sup>), whereas, during the moderate haze episode, the increase in the PM<sub>2.5</sub> change rate (2.4 μg m<sup>−3</sup> h<sup>−1</sup>) in the growth stage was contributed more significantly by physical processes (1.4 μg m<sup>−3</sup> h<sup>−1</sup>) than by chemical processes (1.0 μg m<sup>−3</sup> h<sup>−1</sup>). In general, the aerosol-radiation feedback increased the accumulation rate of aerosols in the growth stage through weakening vertical diffusion, promoting chemical reactions, and/or enhancing horizontal advection. It enhanced the removal rate through increasing vertical diffusion and vertical advection in the dissipation stage, and had little effect on the change rate of PM<sub>2.5</sub> in the persistence stage.</p>

Impacts of Biomass Burning in Peninsular Southeast Asia on PM2.5 Concentration and Ozone Formation in Southern China During Springtime—A Case Study

“…This is caused by the suppression of the vertical dispersion of air pollutants. It is well established that ARI suppresses the development of the PBL and facilitates the accumulation of air pollutants, deteriorating air quality (e.g., Gao et al., 2016; Li et al., 2020; Wang et al., 2014; X. Zhang et al., 2018). Figures S6b and S6e in Supporting Information show that an anticyclone controls the PSEA and southern China during the simulation period.…”

Comments on acp-2020-182

“…How were these vertical grids distributed in the simulations? As demonstrated in previous related works (Wilcox et al, 2016;Wang et al, 2018;Huang et al, 2018), both temperature stratification and aerosol vertical profile, which are vital for aerosol's impact on near-surface pollution, are very sensitive to the vertical grid settings in models. Given that aerosol radiative effect features surface cooling and atmospheric warming and thus more stable stratification, insufficiently fine resolution may partly offset these two opposite tendency and underestimate the pollution deterioration.…”

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“…Aerosol vertical distribution has a significant impact on the estimation of the global budget of aerosols on climate (Torres et al, 1998;Peters et al, 2011;Meyer et al, 2013), planetary boundary layer (PBL) stability (Z. Su et al, 2020), the understanding of the aerosol evolutionary process and surface concentration (Chen et al, 2009;Liu et al, 2018;Quan et al, 2020), and the retrieval of aerosol optical properties from passive sensors (C. Li et al, 2020).…”