Source Apportionment of Fine Aerosols (PM2.5) with a Bayesian Mixing Model for Major Sources over the Northeast Asia

JOOSUNG OH, Kyung Hwan Kim, Gwi-Nam Bae, Korea Institute of Science and Technology (KIST)

     Abstract Number: 241
     Working Group: Source Apportionment

Abstract
Northeast Asia is heavily affected by fine aerosols (PM_2.5) due to various factors such as rapid economic growth, high population density, geopolitical location, and seasonal wind direction. We investigated to analyze the influence of pollutants, contribution of pollutants through PM_2.5 analysis at three sites (Beijing, Seoul, Toyama) in Northeast Asia. PM_2.5 samples had been collected seasonally at each site for 3 weeks. And we measured mass concentration, chemical composition, elemental composition and the stable isotope ratios (SIR) in these PM_2.5 samples. C, N, S SIR (δ¹³C, δ¹⁵N, δ³⁴S) analyzed at each point was similar or different depending on the season and wind direction. As a result, when Seoul and Beijing have similar backward trajectory analysis results (HYSPLIT) in autumn and winter, the δ¹³C of two sites have a very significant correlation (p<0.01). The nitrogen stable isotope ratio showed a statistically significant correlation (p<0.05) in autumn and winter in Seoul and Beijing. In terms of sulfur isotope ratio, which is highly affected by coal-fired power plants, there was a significant correlation (p<0.05) in Beijing and Seoul in winter. Toyama was not statistically significant with Beijing and Seoul regardless of the season. A Bayesian isotopic mixing model (Stable isotope analysis in R (SIAR)) was applied to estimation the major sources in each site. The results indicates that Coal-fired fire plant, coal combustion, vehicle emission, biomass burning are main sources of PM_2.5. According to the SIAR model results, both Beijing and Seoul show an increase in the effects of coal-fired power plants and coal combustion in winter (54.2% in Beijing, 46.7% in Seoul). The next highest contribution rate was vehicle emissions (7.3% in Beijing, 11.5% in Seoul). In particular, PM_2.5 in Seoul showed a high tendency in all seasons to contribute to vehicle emissions.