[Seasonal Variation Characteristics and Potential Source Contribution of Sulfate, Nitrate and Ammonium in Beijing by Using Single Particle Aerosol Mass Spectrometry].

Single particle aerosol mass spectrometry (SPAMS) was deployed to continuously observe the aerosol particles of Beijing urban area from 2013-12 to 2014-11, and the hourly average data of sulfate, nitrate and ammonium (SNA) were obtained using the characteristic ion tracer method. The mixing state and size distribution of SNA were analyzed. In addition, based on Hysplit 48 h back air mass trajectory results in combination with Concentration Weighted Trajectory method (CWT), we obtained the seasonal potential source contribution area of SNA. The results showed that the mixture of sulfate, nitrate and ammonium in spring and summer was more stable than that in autumn and winter. The size distribution of sulfate and nitrate was very similar. The size distribution characteristics of SNA followed the order of autumn > summer > spring > winter. The potential source region of SNA had similar spatial distribution characteristics, and the potential source region of SNA was mainly located in Beijing and south areas, especially at Tianjin, Langfang, Hengshui, Baoding and Shijiazhuang.

[Ozone pollution, influence factors and their correlation at urban area in summer].

Based on the observational data of near surface O3, NO, NO2, CO and meteorological factors in the urban area of Ji'nan during summer 2003, the 03 concentrations and their temporal variation characteristics were studied. The correlation between O3 and its precursors (NO, NO2, CO) and related meteorological factors (solar radiation, temperature) was analyzed. The results show that O3 pollution during summer was very serious in Ji'nan, and the levels of O3, NO, NO2, NOx and CO were quite high during the observational period. O3 concentrations were well negatively correlated with NO, NO2, NO, and CO during day time. As to the meteorological factors, O3 concentrations correlated well with solar radiations, but showed no obvious correlation with the temperatures. Consequently, based on the above data and results, a regression equation that relates ozone concentrations observed in the day time to its precursors and solar radiation was constructed. The results show that the calculated values were in good agreement with the observed values.