Open Access

Jianwei Gu

• The thesis characterized the sources of ambient particles in Augsburg, Germany, from the chemical aspect (using particulate chemical composition, PCC) and physical aspect (using particle size distribution data, PSD), respectively. Six PCC factors and seven PSD factors have been characterized, respectively. The two different approaches (PCC and PSD) led to 4 comparable pairs of factors with strong correlations for secondary aerosols (r=0.92) and weak correlations for traffic emissions (r=0.52) and re-suspended dust (r=0.62). The spatial variation of particulate sources across the city Augsburg was studied and particle sources of different origins showed distinct spatial variability with traffic factor having the highest spatial variability, while secondary nitrate and sulfate distributed uniformly across urban area. To better estimate the human exposure to particulate matter, personal measurement to particulate pollutants (Particulate matter mass concentration, Black carbon, particleThe thesis characterized the sources of ambient particles in Augsburg, Germany, from the chemical aspect (using particulate chemical composition, PCC) and physical aspect (using particle size distribution data, PSD), respectively. Six PCC factors and seven PSD factors have been characterized, respectively. The two different approaches (PCC and PSD) led to 4 comparable pairs of factors with strong correlations for secondary aerosols (r=0.92) and weak correlations for traffic emissions (r=0.52) and re-suspended dust (r=0.62). The spatial variation of particulate sources across the city Augsburg was studied and particle sources of different origins showed distinct spatial variability with traffic factor having the highest spatial variability, while secondary nitrate and sulfate distributed uniformly across urban area. To better estimate the human exposure to particulate matter, personal measurement to particulate pollutants (Particulate matter mass concentration, Black carbon, particle number concentration) were measured under different micro-environments (kerbside, residential area and industrial area etc.) as a pedestrian and in public transportation. Personal exposure to BC and NC varied substantially among scenarios, and are enhanced in traffic and transport scenarios. In contrast, PM2.5 was less variable. As a number of particulate variables were obtained at the long-term measurement station, a data reduction analysis (using cluster analysis) was carried out to find out a few key particulate variables for studying the adverse health effects of particulate matter in epidemiology. The cluster analysis produced nine clusters, and 15 variables were selected as key variables.…