Size, morphological and chemical characterization of aerosols polluting the Beijing atmosphere in January/February 2005

One of the most air-polluted cities in the world is Beijing, where PM2.5 was sampled on filters by a mini-volume sampler (200 L h^-1) and coarse particles on collection plates by means of the passive sampler Sigma-2. From 15 January to 5 February 2005, sampling was carried out in two modes, by collecting particles over periods of several days separated in day and night samples, and alternately during night and daytime in intervals of 12 h. The sampling site was located in north-west of Beijing. Automated microscopic image analysis of coarse particles showed significantly differing size distributions of particle fractions between 3 and 100 μm for day and night samples. The different size distributions could be attributed to varying conditions of atmospheric dispersion and particularities due to local traffic. Elemental carbon containing particles accounted for 10% to 30% of total coarse particles. Scanning electron microprobe analyses identified a wide range of different anthropogenic and geogenic particles. Average PM2.5 concentration during daytime was about 75μg m^-3 in the first, 200 μg m^-3 in the second, and 64 μg m^-3 in the third week. Peaks of daily PM2.5 concentrations reached more than 300 μg m^-3 in the second week. Trace metals such as Pb, As, Cu, and Zn showed similar temporal courses. Several different sources of aerosols were identified by means of scanning electron microscopy (SEM). Backward trajectories indicated that highly polluted air masses reaching Beijing during the second week were advected from south. These air masses passed with low velocities industrial areas in the south and the whole city before reaching the sampling site, whereas air masses entering Beijing during the first and third week came from less industrialized regions in the north. Due to the specific spatial distribution of air pollution sources in the area of Beijing, trajectories could provide a simple approach to an air pollution forecast