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Source apportionment of time and size resolved ambient particulate matter measured with a rotating DRUM impactor
Institution:1. State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China;2. College of Software, Nankai University, No. 94 Weijin Road, Tianjin 300071, China;3. Tianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, Civil Aviation University of China, Tianjin 300300, China
Abstract:Ambient particulate chemical composition data acquired from samples collected using a three-stage Davis Rotating-drum Universal-size-cut Monitoring (DRUM) impactor in Detroit, MI, between February and April 2002 were analyzed through the application of a three-way factor analysis model. PM2.5 (particulate matter ?2.5 μm in aerodynamic diameter) was collected by a DRUM impactor with 3-h time resolution and three size modes (2.5 μm>Dp>1.15 μm, 1.15 μm>Dp>0.34 μm and 0.34 μm>Dp>0.1 μm). A novel three-way factor analysis model was applied to these data where the source profiles are a three-way array of size, composition and source while the contributions are a matrix of sample by source. Nine factors were identified: road salt, industrial (Fe+Zn), cloud processed sulfate, two types of metal works, road dust, local sulfate source, sulfur with dust, and homogeneously formed sulfate. Road salt had high concentrations of Na and Cl. Mixed industrial emissions are characterized by Fe and Zn. The cloud processed sulfate had a high concentration of S in the intermediate size mode. The first metal works represented by Fe in all three size modes and by Zn, Ti, Cu, and Mn. The second included a high concentration of small size particle sulfur with intermediate size Fe, Zn, Al, Si, and Ca. Road dust contained Na, Al, Si, S, K, and Fe in the large size mode. The local and homogeneous sulfate factors show high concentrations of S in the smallest size mode, but different time series behavior in their contributions. Sulfur with dust is characterized by S and a mix of Na, Mg, Al, Si, K, Ca, Ti, and Fe from the medium and large size modes. This study shows that the utilization of time and size resolved DRUM data can assist in the identification of sources and atmospheric processes leading to the observed ambient concentrations.
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