Cite this article: Yu, Y., Zhao, S., Wang, B., Fu, P. and He, J. (2017). Pollution Characteristics Revealed by Size Distribution Properties of Aerosol Particles at Urban and Suburban Sites, Northwest China.
Aerosol Air Qual. Res.
17: 1784-1797. https://doi.org/10.4209/aaqr.2016.07.0330
Particle volume size distributions (PVSD) in two different environments were provided.
Pollution characteristics were identified by clusters of PVSDs.
PVSD clusters were related to different sources and meteorological conditions.
Regional background PM2.5 level was estimated.
High temporal resolution (5 min) particle size distribution data (0.5‒20 µm) were collected using aerodynamic particle sizer at an urban (Lanzhou) and a suburban (Yuzhong) site at Lanzhou, northwest China from 1st August to 31st October 2010. Variations of particle concentrations and properties of volume size distributions (PVSD) were analyzed and urban pollution characteristics were investigated using PVSDs and chemical analysis. The average particle number, surface area and volume concentrations for size range 0.5‒10 µm were 280.54 ± 270.92 cm–3, 331.04 ± 316.95 µm2 cm–3 and 93.01 ± 127.75 µm3 cm–3, respectively, at the urban site, which were 2.87, 1.50 and 1.62 times higher than those at the suburban site. Compared with the suburban site, shifts of accumulation mode (0.5‒1.0 µm) to a smaller size and the coarse mode (1.0‒10 µm) to a larger size of the PVSDs were observed at the urban site, which may be related to elevated fossil fuel burning and municipal construction or fugitive dust, respectively, in urban area. K-means cluster analysis was used to group the PVSD into six clusters representing the effect of different sources and meteorological conditions. PVSDs at the urban site were dominated by clusters affected by local anthropogenic sources and secondary aerosols, which was characterized by bimodal with peaks at accumulation mode and coarse mode, respectively, while those affected by construction works, wind-borne dust, and dust events were dominated by coarse mode. Chemical composition analysis of PM2.5 samples collected on days representing different clusters confirmed the assignment of clusters to different sources.
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