Source apportionment of PM<sub>2.5</sub> in Seoul, Korea

Abstract

Abstract. PM2.5 samples were collected at a centrally located urban monitoring site in Seoul, Korea, every third day from March 2003 to December 2006 and analyzed for their chemical constituents. Sources were identified using positive matrix factorization (PMF). A total of 393 samples were obtained during the sampling period, and 20 chemical species were measured. Nine PM2.5 source categories were identified providing physically realistic profiles and interesting insights into the source contributions to the ambient mass concentrations. The major contributors of PM2.5 were secondary nitrate (20.9%), secondary sulfate (20.5%), gasoline-fueled vehicles (17.2%), and biomass burning (12.1%), with lesser contributions from diesel emissions (8.1%), soil (7.4%), industry (6.7%), road salt and two-stroke vehicles (5.1%), and aged sea salt (2.2%). PM2.5 levels in Seoul were influenced by both local urban activities and regional-scale transport. Conditional probability function (CPF) results identified possible source directions of local sources such as motor vehicles (gasoline and diesel), industry, and road salt. Potential source contribution function (PSCF) results showed that possible source areas contributing to the elevated secondary particle concentrations (sulfate and nitrate) in Seoul to be the major industrial areas in China.

Particulate matter, air quality and climate: lessons learned and future needs

“…PSCF studies are summarized by Hopke et al (2003). PSCF has been integrated with bilinear model outputs for the identification of specific sources and/or source regions on local and regional scales (Begum et al, 2010;Heo et al, 2009) and for the evaluation of ensemble and tracer-based apportionment results (e.g. Chang et al, 2011;Gilardoni et al, 2011a;Schwartz et al, 2010).…”

Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

“…PM also affects climate, both directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei (IPCC, 2001). Identification of the various sources of anthropogenic PM in urban environments has received considerable attention with traffic, biomass burning and industrial processes typically contributing significantly to mass concentrations of PM 2.5 (Castanho and Artaxo, 2001;Kim and Hopke, 2008;Godoy et al, 2009;Karanasiou et al, 2009;Mugica et al, 2009;Heo et al, 2009). However, refined apportionment of PM 2.5 is often hindered by the low temporal resolution of off-line analysis and a lack of knowledge of the mixing state of the particles collected.…”

A refinement of the emission data for Kola Peninsula based on inverse dispersion modelling

“…Interpretation of such results is usually qualitative (e.g. Barletta et al, 2009;Skjøth et al, 2007), but sometimes quantitative analysis can be undertaken (Kulmala, 2000;Sogacheva et al, 2005Sogacheva et al, , 2007Heo et al, 2009). For quantitative and comparatively accurate assessment in case of limited observational information, the so-called "footprint" computations can be used (Rannik et al, 2003;Kuparinen et al, 2007;Saarikoski et al, 2007).…”