• Journal of Korean Society for Atmospheric Environment
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• v.24 no.6
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• pp.662-673
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• 2008

Two hybrid receptor models, potential source contribution function (PSCF) and concentration weighted tracjectory (CWT), were compared for locating $PM_{2.5}$ sources contributing to the atmospheric $PM_{2.5}$ concentrations in Seoul. The source contribution estimates by chemical receptor model (CMB) receptor model were used to identify better source areas, Among the sources, soil, agricultural burning, marine aerosol, coal-fired power plant and Chinese aerosol were only considered for the study because these sources were more likely to be associated with the long-range transport of air pollutant. Both methods are based on combining chemical data with calculated air parcel backward trajectories. However, the PSCF analyses were performed with trajectories above the $75^{th}$ percentile criterion values, while the CWT analyses used all trajectories. This difference resulted in locating of different sources, which might be helpful to interpret locating of $PM_{2.5}$ sources, High possible source areas in source contribution of soil and agricultural burning contributing to the Seoul $PM_{2.5}$ were inland areas of Heibei and Shandong provinces (highest density areas of agricultural production and population) in China. The "Chinese aerosol" was used as a representative source for the $PM_{2.5}$ originated from urban area in China. High possible source areas for the aerosol were the cities in China where are relatively close to the receptor. This result suggests that Chinese aerosol is likely to be a useful tool in studies on source apportionment and identification in Korea.

• Particle and aerosol research
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• v.9 no.2
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• pp.89-102
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• 2013

24-hr $PM_{2.5}$ samples were collected from January 19 through February 27, 2009 at an urban site of Gwangju and analyzed to determine the concentrations of organic and elemental carbon(OC and EC), water-soluble OC(WSOC), eight ionic species($Na^+$, $NH^{4+}$, $K^+$, $Ca^{2+}$, $Mg^{2+}$, $Cl^-$, ${NO_3}^-$ and ${SO_4}^{2-}$), and 22 elemental species. Haze phenomena was observed during approximately 29%(10 times) of the whole sampling period(35 days), resulting in highly elevated concentrations of $PM_{2.5}$ and its chemical components. An Asian dust event was also observed, during which $PM_{2.5}$ concentration was 64.5 ${\mu}g/m^2$. Crustal materials during Asian dust event contributed 26.6% to the $PM_{2.5}$, while lowest contribution(5.1%) was from the haze events. OC/EC and WSOC/OC ratios were found to be higher during haze days than during other sampling days, reflecting an enhanced secondary organic aerosol production under the haze conditions. For an Asian dust event, enhanced concentrations of OC and secondary inorganic components were also found, suggesting the further atmospheric processing of precursor gases during transport of air mass to the sampling site. Correlations among WSOC, EC, ${NO_3}^-$, ${SO_4}^{2-}$, and primary and secondary OC fractions, which were predicted from EC tracer method, suggests that the observed WSOC could be formed from similar formation processes as those of secondary organic aerosol, ${NO_3}^-$ and ${SO_4}^{2-}$. Results from principal component analysis indicate also that the observed WSOC was strongly associated with formation routes of the secondary organic and inorganic aerosols.

• Particle and aerosol research
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• v.15 no.3
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• pp.91-104
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• 2019

In this study, hourly measurements of $PM_{2.5}$ and its major chemical constituents such as organic and elemental carbon (OC and EC), and ionic species were made between January 15 and February 10, 2018 at the air pollution intensive monitering station in Gwangju. In addition, 24-hr integrated $PM_{2.5}$ samples were collected at the same site and analyzed for OC, EC, water-soluble OC (WSOC), humic-like substance (HULIS), and ionic species. Over the whole study period, the organic aerosols (=$1.6{\times}OC$) and $NO_3{^-}$ concentrations contributed 26.6% and 21.0% to $PM_{2.5}$, respectively. OC and EC concentrations were mainly attributed to traffic emissions with some contribution from biomass burning emissions. Moreover, strong correlations of OC with WSOC, HULIS, and $NO_3{^-}$ suggest that some of the organic aerosols were likely formed through atmospheric oxidation processes of hydrocarbon compounds from traffic emissions. For the period between January 18 and 22 when $PM_{2.5}$ pollution episode occurred, concentrations of three secondary ionic species ($=SO{_4}^{2-}+NO_3{^-}+NH_4{^+}$) and organic matter contributed on average 50.8 and 20.1% of $PM_{2.5}$, respectively, with the highest contribution from $NO_3{^-}$. Synoptic charts, air mass backward trajectories, and local meteorological conditions supported that high $PM_{2.5}$ pollution was resulted from long-range transport of haze particles lingering over northeastern China, accumulation of local emissions, and local production of secondary aerosols. During the $PM_{2.5}$ pollution episode, enhanced $SO{_4}^{2-}$ was more due to the long-range transport of aerosol particles from China rather than local secondary production from $SO_2$. Increasing rate in $NO_3{^-}$ was substantially greater than $NO_2$ and $SO{_4}^{2-}$ increasing rates, suggesting that the increased concentration of $NO_3{^-}$ during the pollution episode was attributed to enhanced formation of local $NO_3{^-}$ through heterogenous reactions of $NO_2$, rather than impact by long-range transportation from China.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.1-18
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• 2024

This study analyzed the effect of warming on PM_2.5 aerosol production in mid-latitude East Asia during June 2020 using PM_2.5 aerosol anomalies, which were identified by incorporating meteorological and climate data into the Weather Research Forecasting model coupled with Chemistry (WRF-Chem) model. The decadal temperature change trend over a 30-year period (1991-2020) in East Asia showed that recent warming has been greater in summer than in winter. Summer warming in East Asia generated low and high pressure in the lower and upper troposphere, respectively, over China. The boundary between the lower tropospheric low and upper tropospheric high pressure sloped along the terrain from the Tibetan Plateau to Korea. The eastern China, Yellow Sea, and Korean regions experienced a convergence of warm and humid southwesterly airflows originating from the East China Sea with the development of a northwesterly Pacific high pressure. In June 2020, the highest temperatures were observed since 1973 in Korea. Meanwhile, enhanced warming in East Asia increased the production of PM_2.5 aerosols that travelled long distances from eastern China to Korea. PM_2.5 anomalies, which were derived solely by inputting meteorological and climatic data (1991-2020) into the WRF-Chem model and excluding emission variations, showed a positive distribution extending from eastern China to South Korea across the Yellow Sea as well as over the Pacific Northwest. Thus, the contribution of warming to PM_2.5 aerosols in East Asia during June 2020 was more than 50%. In particular, PM_2.5 aerosols were transported from eastern China to Korea through the Yellow Sea, where the warm and humid southwesterly airflows implied wet scavenging of sulfate but promoted nitrate production.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.100-113
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• 2016

In this study, the characteristics of $PM_{2.5}$ and $PM_{2.5-10}$ concentrations were identified in two different functional areas including Chuncheon and Youngwol, Korea. Even though the anthropogenic emission rates of $PM_{2.5}$ and $PM_{10}$ are approximately four times higher in Youngwol than in Chuncheon their atmospheric concentrations were statistically higher in Chuncheon. In Chuncheon, both $PM_{2.5}$ concentrations and the ratio of $PM_{2.5}/PM_{10}$ increased as relative humidity (RH) increased possibly because the inorganic and/or organic secondary aerosols were actively formed at high RH. This result was also supported by that $PM_{2.5}$ concentration was enhanced under the fog and mist conditions in Chuncheon. On the other hand, both $PM_{2.5}$ and $PM_{2.5-10}$ concentrations clearly increased with the southerly winds blown from the cement production facility in Youngwol. In addition, high $PM_{2.5-10}$ concentrations were observed with high wind speed, low relative humidity, and high $NO_2$ concentrations in Youngwol, suggesting that $PM_{2.5-10}$ was generated through the physical process including crushing and packing procedures followed by resuspension from cement and lime factory.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.2
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• pp.179-184
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• 1995

This study was carried out to characterize sources of suspended particulate matter(SPM) in Mt. Soback area from January to Novembver in 1993. The collection and major water soluble ion analysis of SPM were conducted by using a High Volumn Air Sampler(HVAS; W&A Inc., PM-10) and ion chromatograph(DIONEX 4000i), respectively. The variations of SPM and major ion concentrations were found to be 9. sim. 156.mu.g/ $m^{3}$, $F^{-10}$ 0.00 .sim. 0.15.mu.g/ $m^{3}$, C $l^{-10}$ 0.06 .sim. 3.79.mu.g/ $m^{3}$, N $O_{3}$$^{-10}$ 0.90 .sim. 6.85.mu.g/ $m^{3}$, S $O_{4}$$^{2-}$ 1.99 .sim. 9.36.mu.g/ $m^{3}$ N $a^{+}$0.00 .sim. 0.27.mu.g/ $m^{3}$, N $H_{4}$ $^{+}$0.72 .sim. 5.77.mu.g/ $m^{3}$, $k^{+}$0.03 .sim. 0.88.mu.g/ $m^{3}$ and $Ca^{2+}$0.12 .sim. 2.76.mu.g/ $m^{3}$. Tree sources were identified by Principal Component Amalysis(PCA) using a SPSS/P $C^{+}$. The explanation ability of forst, second and third Principal Component were 60.8%, 13.6%, 8.2%, of total variance. The sources classfied by PCA were found to be secondary aerosol/fuel combustion, soil dust related cement production/yellow sand and aerosol related waste burning.related waste burning.g.