 |
| Titel |
Chemical composition and source apportionment of PM2.5 in Seoul, Korea during 2012-2013 |
| VerfasserIn |
Junghwa Heo, Sang-Woo Kim, Bong Mann Kim, Jin Young Kim |
| Konferenz |
EGU General Assembly 2017
|
| Medientyp |
Artikel
|
| Sprache |
en
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250142333
|
| Publikation (Nr.) |
 EGU/EGU2017-5940.pdf |
|
|
|
|
|
| Zusammenfassung |
| PM2.5 samples were collected at a centrally located urban site of KIST (Korea Institute of
Science and Technology) in Seoul, Korea, every day from October 2012 to September 2013.
Sources were identified using Chemical Mass Balance (CMB) model and two multivariate
models. The averaged PM2.5 mass concentration was 41.5 ± 27.7 μg m−3, and
seasonally averaged PM2.5 concentration was high in the following order: Winter (57.2
± 32.7 μg m−3), spring (48.5 ± 27.6 μg m−3), fall (28.6 ± 10.5 μg m−3), and
summer (22.7 ± 12.9 μg m−3). Secondary inorganic species and organic matter were
the major chemical component occupying about 73.7% – 87.9% of PM2.5 mass
concentration in all seasons. The maximum value of sulfate was 11.2 μg m−3in winter,
however, the fraction of sulfate concentration was highest in summer (31.4%) due
to the active photochemical reactivity. The maximum nitrate concentration was
measured as 13.4 μg m−3in winter because the cooler temperature is the favorable
condition for the formation of particulate nitrate. The highest concentrations of
elemental carbon and soil were observed in fall and spring, which were caused by the
frequent occurrence of biomass burning and Asian dust events, respectively. 7 sources
were attributable to PM2.5 mass concentration in Seoul. The main sources were
secondary sulfate (24.2%), secondary nitrate (27.3%), biomass burning (14.9%), and
vehicle (8.9%). The contributions from other carbon source (5.5%), geological source
(5.5%), and marine aerosol (0.8%) were relatively less than those of main sources.
Compared to the results from the previous study, contributions of secondary nitrate and
vehicle were overestimated and underestimated, respectively, due to the limitation of
source profiles used in this study. On the other hand, PM2.5 concentration in Seoul
was highly affected by long-range transported pollution from northern China in
January 2013. The contribution of other carbon source, which was the residual
carbonaceous component after source apportionment analysis, was the highest at 10.6% in
winter. This suggests that about 10.6% of PM2.5 concentration cannot be estimated
by local sources and can be attributable to the polluted aerosols transported from
China. In this presentation, more detailed comparisons among CMB, Positive Matrix
Factorization (PMF) and Solver for Mixture Problem (SMP) models will be presented. |
|
|
|
|
|
|