| dc.description.abstract | In order to compare the characteristics of fine particles between typical industrial urban and non-industrial urban, we collected PM2.5 by using Honeycomb denuders from Sin-chung and Shao-gawn sites situated in Taipei metropolitan area and Kao-hsiung city, respectively. Particles were collected on PC (polycarbonate) filters and analyzed with CCSEM (computer controlled scanning electron microscopy) to characterize elemental composition and morphology of individual particles. Source apportionment of particles were conducted on elemental composition using statistical cluster and factor analyses. The discriminate analysis and neural network were applied to classify unsorted particle into target category based on known data set or to assess the classified data. Morphology of selected particles was quantified using fractal algorithm on their boundary, projected area, and surface roughness, respectively. Meanwhile, aerosol bulk properties like mass, water-soluble ions, carbonaceous contents, and metal concentrations were obtained from collocated filter samples. The APCA (absolute principal component analysis) was applied for source apportionment of particles to compare that from CCSEM data.
Cluster analysis classifies Taipei aerosols into 18 categories with 6 are major categories. In contrast, Kao-hsiung aerosols are classified into 16 categories and with 5 major ones. In both site C, O rich particles are predominant, 39% and 53% particles can be attributed to diesel vehicle exhausts from Taipei and Kao-hsiung, respectively. The results were further confirmed by the discriminate analysis and neural network algorithm. Simultaneously, factor analysis shows 6 source types both in Taipei (wood burning and secondary, industry, soil and boiler, fertilizer, cement and bioaerosol, and ferrous furnace) and in Kao-hsiung (sea-salt and industry, industry, soil and boiler, fertilizer, cement and bioaerosol, ferrous furnace). A Cartesian coordinate system for fractal dimensions on boundary, projected area, and surface roughness from single particles is established to identify particles from different sources.
Aerosol bulk analysis reveals the averaged fraction of carbon in PM2.5 is 37%, that of water-soluble ion is 39%, that of metal is 3%, and the remaining 21% is unknown. The receptor model(APCA) estimates 4 different source types contributing to both sites, among them industrial sources containing precursors of NO3-, NH4+and SO42- is the major one. This source type accounts for 59% and 78% of PM2.5 in Taipei and Kao-hsiung area, respectively.
Finally, single particle and bulk analysis are agreed in reconstructed elemental compositions in this study. The source types apportioned from factor analysis and APCA are mixed compared to more resolved ones from cluster analysis. However, supplemental information is needed to resolve source contributions for particles with similar elements. | en_US |