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To better characterize the anthropogenic emission relevant aerosol species, the GSI-WRF/Chem data assimilation system was updated from the GOCART aerosol scheme to MOSAIC-4BIN scheme. Three year (2015-2017) winter-time (January) surface PM2.5 observations from 1600+ sites were assimilated hourly using the updated 3DVAR system in the assimilation experiment CONC_DA. Parallel control experiment that did not employ DA (NO_DA) was also performed. Both experiments were verified against the surface PM2.5 observations, MODIS 550-nm AOD and also 550-nm AOD at 9 AERONET sites. In the NO_DA experiment using 2010_MEIC emissions, modeled PM2.5 are severely overestimated in Sichuan Basin (SB), Central China (CC), YRD (Yangzi River Delta), and PRD (Pearl River Delta) which indicated the emissions for 2010 are not appropriate for 2015-2017, as strict emission control strategies were implemented in recent years. Meanwhile, underestimations in Northeastern China (NEC) and Xin Jiang (XJ) were also observed. The assimilation experiments significantly reduced the high biases of surface PM2.5 in SB, CC, YRD, and PRD, and also low biases in NEC. However the improvement of the low biases in XJ is relatively small due to the large difference between the observations and the model background in the DA process, likely indicating that the emissions in the model are seriously underestimated in this region. Assimilating surface PM2.5 also significantly changed the column AOD and resulted in closer agreement with MODIS data and observations at AERONET sites. The observations and the reanalysis data from assimilation experiment were used to investigate the year-to-year changes. As the differences of the reanalysis data (CONC_DA) among years reflect combining effects of meteorology and emission and the differences of modeling result from control experiment (NO_DA, with same emissions) among years reflect the separate effect of meteorology, the important roles of emission and meteorology in driving the changes in the three years can be distinguished and analyzed quantitatively. The analysis indicated that meteorology played different roles in 2016 and 2017: the higher pressure system, lower temperature and higher PBLH in 2016 are favorable for pollution dispersion (compared with 2015) while the situation is almost the opposite in 2017 (compared with 2016) that leads to the increasing PM2.5 from 2016 to 2017 although emission control strategy were implemented in both years. There are still large uncertainties in this approach especially the inaccurate emission input in the model brings large biases in the analysis. [ABSTRACT FROM AUTHOR]

Hygroscopicity is an important feature of ambient aerosols, which is very crucial to the study of light extinction, radiation force, and formation mechanism. The light scattering hygroscopic growth factor (f(RH)) is an important parameter which is usually measured by the humidified nephelometer system and could better describe the aerosol hygroscopicity under wide particle size range and continuous relative humidity (RH). The f(RH) can be applied to the establishment of a parameterization scheme for light extinction, the calculation of hygroscopicity parameter (κ), and also the estimation of aerosol liquid water content (ALWC). However, the humidified nephelometer system in the previous studies could only observe the f(RH) below 90% due to the larger error of the sensor under high RH (> 90%). Furthermore, the f(RH) observations in North China Plain needs to be greatly strengthened both in the temporal resolution and the observation duration. In view of this, an improved high-resolution humidified nephelometer system was established to observe the f(RH) of PM2.5 for a wide RH range between 30%-96% in the urban area of Beijing over three seasons (winter, summer, and autumn) in 2017. It was found that the f(80%) at 525 nm of PM2.5 was evidently higher under the polluted conditions and highly correlated with the fractions of all the water-soluble ions. A two-parameter fit equation was selected to fit the observed f(RH) data. For each season, the fitting curve under the very clean condition was lower than that of other conditions. And the f(RH) points of polluted conditions were more concentrated with higher fitting R² for summer and autumn data. The hygroscopicity of aerosol under higher RH was probably enhanced when compared with the data in the previous study conducted in NCP. In summer, the fitting f(RH) showed a significant dependence on wavelength for each pollution condition. However, there was an opposite performance in the f(RH) curves of different wavelengths for the very clean condition in winter. It was showed that The simulation showed that the maximum uncertainty of f(RH) was less than 10%. [ABSTRACT FROM AUTHOR]

Acidity (pH) plays a key role in the physical and chemical behavior of aerosol and cannot be measured directly. In this work, aerosol liquid water content (ALWC) and size-resolved pH are predicted by thermodynamic model (ISORROPIA-II) in 2017 of Beijing. The mean aerosol pH over four seasons is 4.3±1.6 (spring), 4.5±1.1 (winter), 3.9±1.3 (summer), 4.1±1.0 (autumn), respectively, showing the moderate aerosol acidity. The aerosol pH in fine mode is in the range of 1.8 ~ 3.9, 2.4 ~ 6.3 and 3.5 ~ 6.5 for summer, autumn and winter, respectively. And coarse particles are generally neutral or alkaline. Diurnal variation of aerosol pH follows both aerosol components (especially the sulfate) and ALWC. For spring, summer and autumn, the averaged nighttime pH is 0.3~0.4 unit higher than that on daytime. Whereas in winter, the aerosol pH is relatively low at night and higher at sunset. SO42− and RH are two crucial factors affecting aerosol pH. For spring, winter and autumn, the effect of SO42− on aerosol pH is greater than RH, and it is comparable with RH in summer. The aerosol pH decreases with elevated SO42− concentration. As the NO3− concentration increases, the aerosol pH firstly increases and then decreases. Sulfate-dominant aerosols are more acidic with pH lower than 4, whereas nitrate-dominated aerosols are weak in acidity with pH ranges 3~5. In recent years, the dominance of NO3− in inorganic ions may be another reason responsible for the moderately acidic aerosol. ALWC has a different effect on aerosol pH in different seasons. In winter, the increasing RH could reduce the aerosol pH whereas it shows a totally reverse tendency in summer, and the elevated RH has little effect on aerosol pH in spring and autumn when the RH is between 30 % and 80 %. The dilution effect of ALWC on Hair+ is only obvious in summer. The elevated NH3 and NH4+ could reduce aerosol acidity by decreasing Hair+ concentration exponentially. [ABSTRACT FROM AUTHOR]