Abstract
A typical heavy air pollution episode occurred over the North China Plain (NCP) in December 2010. The air quality in Beijing and its surrounding regions worsened during the period December 17 to 22, and local visibility became significantly affected by the high pollution levels. The air quality modeling system RAMS-CMAQ coupled with an aerosol optical property scheme was applied to simulate the trace gases and major aerosol components in the NCP to obtain an in-depth understanding of the relationship between regional low visibility and aerosol particles. The model performance was evaluated using various observation data, such as meteorological factors (temperature, relative humidity, and wind field), gaseous pollutants (SO2, NO2, and O3), PM2.5, PM10, and visibility at several measurement stations. The modeled meteorological field and visibility were in good agreement with observations from December 2010. The modeled mass concentrations of gaseous pollutants and aerosol particles also suitably captured the magnitude and variation features of the observation data, especially during the air pollution episode. The simulated results showed that during this pollution episode, low visibility (lower than 10 km) occurred mainly in Beijing, Tianjin, Hebei, and Shandong. The analysis and sensitivity test indicated that the aerosol particles larger than PM2.5 and the water uptake effect of aerosol optical properties could not significantly influence visibility. Thus, the low visibility was primarily caused by the high mass burden of PM2.5as a result of the local pollutant accumulation and long-range transport. Statistics showed that the visibility variation was closely inversely related to the variation in PM2.5 in most regions in the NCP. Visibility decreased lower than 10 km when the mass concentration of PM2.5 exceeded 75 μg m−3 to 85 μg m−3 in the NCP. Sulfate and nitrate were the two major inorganic aerosol components of PM2.5 that evidently decreased visibility by contributing 40% to 45% to the total extinction coefficient value.
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