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Asian Journal of Atmospheric Environment - Vol. 14 , No. 2

[ Research Article ]
Asian Journal of Atmospheric Environment - Vol. 14, No. 1, pp.35-46
Abbreviation: Asian J. Atmos. Environ
ISSN: 1976-6912 (Print) 2287-1160 (Online)
Print publication date 31 Mar 2020
Received 17 Feb 2020 Revised 20 Mar 2020 Accepted 20 Mar 2020

Temporal Variations and Characteristics of the Carbonaceous Species in PM2.5 Measured at Anmyeon Island, a Background Site in Korea
Jong Sik Lee ; Eun Sil Kim1) ; Ki-Ae Kim2) ; Jian Zhen Yu3) ; Yong Pyo Kim4) ; Chang Hoon Jung5) ; Ji Yi Lee2), *
Honam Business Division, Korea Conformity Laboratories, 17-22 Cheomdangwagi-ro 208beon-gil, Buk-gu, Gwangju 61011, Republic of Korea
1)Korea Global Watch Center, Korea Meteorological Administration, Republic of Korea
2)Department of Environmental Science and Engineering, Ewha Womans University, Republic of Korea
3)Department of Chemistry, the Hong Kong University of Science & Technology, Clear Water Bay, Kowloon, Hong Kong, China
4)Department of Chemical Engineering & Materials Science, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul, Republic of Korea
5)Department of Environmental Health, Kyungin Women’s College, 63 Gyeyangsan-ro, Gyesan-dong, Gyeyang-gu, Incheon, Republic of Korea

Correspondence to : * Tel: +82-02-3277-5945 E-mail:

Copyright © 2020 by Asian Journal of Atmospheric Environment
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Routine measurements of carbonaceous species in PM2.5 inculidng organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), and humic-like-substance carbon (HULIS-C) in PM2.5 were performed at Anmyeon Island (AI) to clarify the seasonal variation and carbonaceous aerosol concentrations at a background site in Korea between 2015 and 2016. The annual average OC and EC concentrations were 4.52±3.25 μg/m3 and 0.46±0.28 μg/m3, respectively, and there were no clear seasonal variations in OC and EC concentrations. The average concentrations of WSOC and water-insoluble organic carbon (WISOC) were 2.56±1.95 μg/m3 and 1.96±1.45 μg/m3, respectively, and their composition in OC showed high temporal variations. A low correlation between WISOC and EC was observed, while WSOC concentrations were highly correlated with secondary organic carbon concentrations, which were estimated using the EC tracer method. The results indicate that the formation of secondary organic aerosols is a major factor for the determination of WSOC concentrations in this region. HULIS-C was the major component of WSOC, accounting for 39-99% of WSOC and the average concentration was 1.88±1.52 μg/m3. Two distinct periods with high carbonaceous speciess in PM2.5 were observed and characterized by their OC/EC ratios. The high concentration of OC with high ratio of OC/EC was due to the influence of a mixture of emissions from biomass burning and secondary formation transported from outside AI. While, the high concentrations of OC and EC with low OC/EC ratio were related to local vehicular emissions.

Keywords: GAW satation, Carbonaceous species, HULIS, Biomass burning, PM2.5


The carbonaceous speciess in particulate matter that have aerodynamic diameters less than or equal to 2.5 μm (PM2.5) typically constitute a dominant fraction of the total PM2.5 mass and is highly related to related to regional and global climate change, visibility reductions, and adverse health effects in the atmosphere (Huo et al., 2016; Hang et al., 2012). The carbonaceous speciess in PM2.5 can be classified as organic carbon (OC) and elemental carbon (EC) based on their thermal-optical properties, and OC can be subdivided into water-soluble organic carbon (WSOC) and water-insoluble organic carbon (WISOC) based on its solubility in water. Recently, humic-like-substance carbon (HULIS-C), a type of brown carbon, has been fractionized from WSOC (Lin et al., 2010). EC is emitted from various primary emission sources, directly, while OC compose thousands of individual compounds with a wide range of chemical and thermodynamic properties and is emitted from primary emissions and also formed in the atmosphere via photochemical oxidation. WSOC consisted of 20-70% of OC, has hygroscopic properties, so, WSPC influences cloud formation and climate change by acting as cloud condensation nuclei (Saxena et al., 1995). In addition, WSOC can cause adeverse health effect by increasing their ability to be absorbed into lung (Du et al., 2014). HUIS consists of a significant fraction of WSOC and the optically active brown carbon. Optical properties of HULIS has been found to have both direct and indirect impacts on the atmosphere (Lee et al., 2017). As a precursor of cloud droplets (Graber and Rudich, 2006), HULIS can contribute to climate cooling indirectly, while its light absorbing property due to its orange to brown color can contribute directly to warming of the air (Feng et al., 2013). Because of the high impact of carbonaceous species in PM2.5 to the atmospheric enviroment, they are measured frequently worldwide; however, most studies have focused mainly on OC, EC, and sometimes WSOC species, while studies of the simultaneous measurement of all carbonaceous species are limited. Moreover, studies of carbonaceous species in PM2.5 have been carried out mainly at urban sites based on short-term measurements, and long-term measurement of carbonaceous species in PM2.5 at background sites are limited.

Anmyeon Island (AI), South Korea, represents clean background area as a World Meteorological Organization (WMO) Background Air Pollution Monitoring station. A Global Atmosphere Watch (GAW) observatory has been established at a supersite on AI off the western coast of South Korea. The GAW center performs meteorological and pollutant observations. Given the WMO/GAW recommendation for aerosol chemical measurements (WMO/GAW, 2016), one of the goals of aerosol chemical measurements at the GAW station is the determination of long-term trends in global distribution to assess the impact of aerosols on regional and global climate.

In this study, to assess aerosol chemical measurements at GAW station, we conducted routine measurements of the carbonaceous speciess in PM2.5, including OC, EC, WSOC, and HULIS-C at AI, a background site in Korea, during one year. This study focused on the determination of the concentrations of carbonaceous species in PM2.5 at AI, a background area in Northeast Asia. Furthermore, we assessed the temporal variations and distributions of carbonaceous speciess at AI. Finally, we distinguished between the influences of long-range transport and local emissions based on two episodes with high CA concentrations at AI.

2. 1 Sampling Information

The sampling site was located off the coast of western South Korea (36°32ʹN; 126°19ʹE, 45.7 m a.s.l.) (Fig. 1). PM2.5 high-volume air samplers (TE-5005BLX; TISCH, USA) were installed on the roof of the GAW building about 4 m above the ground and used to collect PM2.5 samples every six days from June 2015 to May 2016. A total of 59 samples were collected. The PM2.5 samplers were operated at a flow rate of 1.1 m3/min and pre-baked quartz-fiber filters (QFFs; TISSQUARTZ 2500QAT-UP; PALL life Science) were used for sampling. After sampling, the filters were wrapped in aluminum foil and stored at -20°C in a freezer until analysis. Field blank filters were collected every month and stored and analyzed with the PM2.5 samples, and blank-correction was applied to all carbonaceous species concentrations.

Fig. 1. 
Location of sampling site and instruments.

2. 2 Cabonaceous Species Analysis

PM2.5 samples were used for the carbonaceous speciess analysis (EC, OC, WSOC, and HULIS-C concentrations) and organic compound speciation. The information of organic compounds speciation is available in Chang and Lee (2019).

2. 2. 1 OC and EC

A portion of (1.5-cm2) of PM2.5 samples was used for the analysis of OC and EC with a thermal/optical carbon aerosol analyzer (OCEC Model 5 L; Sunset Laboratory, Forest Grove, OR, USA) applying the National Institute of Occupational Safety and Health Method 5040. The analysis procedures included two stages. In the first stage, OC was volatilized from the sample in a non-oxidizing atmosphere (helium) as the temperature was increased step-wise to 870°C. In the second stage, after introducing a helium to be cooling down the temperature, 2% of oxygen in helium was injected and the oven temperature was increased step-wise to 870°C again. The split time between OC and EC was determined from the time acuuried to return the filter to its initial transmittance value. At the end of each analysis, a fixed volume of methane was injected as an internal standard to quantify the carbon amount. Replicate analysis of samples indicated good analytical precision, with relative percent variations averaging 10% for the OC analysis, 15% for the EC analysis, and 10% for total carbon (n=6) (Chang and Lee, 2019). Procedural QFF blanks processed concurrently with field samples were used to quantify the operational detection limits. The average concentrations of three field blanks were 0.45±0.14 μg cm-2 and 0.01±0.01 μg cm-2 for OC and EC, respectively.

2. 2. 2 WSOC and WISOC

A portion (3 cm×5 cm) of the filter was extracted by sonication in 40 mL of ultra-pure water (18 MΩ) twice for 30 minutes each time. Iced ultra-pure water was used to minimize loss of volatile organic compounds. The extracts were filtered using a PTFE (Polytetrafluoroethylene) 0.2 μm membrane filter (Advantec) to remove insoluble materials and filter fibers before analysis. Half of the extracted water (20 mL) was used for WSOC, and the rest was used for HULIS-C analysis. The WSOC analysis was performed using a total organic carbon analyzer (Sievers M9; General Electric Power & Water Analytical Instruments, USA), with a detection limit of 0.03 μg L-1 and standard deviation of four replicates of <1.0%. The WISOC concentration was calculated by subtracting WSOC from OC.

2. 2. 3 HULIS-C

The HULIS-C fraction extraction followed the solidphase extraction method described by Lin et al. (2010). Briefly, HULIS was isolated from the water-extracted fraction from PM2.5 samples (as described in section 2.2.2) by applying solid phase extraction method (SPE) using HLB (HydrophilicLipophilic-Balanced) cartridge (Oasis HLB, 30 μm, 60 mg/cartridge, Waters, USA). Then the cartridge was rinsed with methanol (2% aquatic ammonia (w/w)). The eluate was evaporated under the gentle stream of N2 and the solute was re-dissolved in ultra-pure water for subsequent analysis. Finally, the carbon amount from each 20 mL extract were quantified using total organic carbon (TOC) analyzer (Sievers M9; General Electric Power & Water Analytical Instrument).

3. 1 Temporal Variations in the Carbonaceous Speciess of PM2.5

There were no major temporal variations in the CA levels at AI, except two cases on November 9, 2015, and May 22, 2016, with observation of extremely high carbonaceous species concentrations. In this section, the general characteristics of carbonaceous species concentrations at AI were accessed and a detailed discussion of these two cases is presented in section 3.3 separately. The annual average OC and EC concentrations were 4.52±3.25 μg gm-3 and 0.46±0.28 μg m-3, respectively, while those of WSOC, HULIS-C, and WISOC were 2.56±1.95 μg m-3, 1.88±1.51 μg m-3, and 1.96±1.45 μg m-3, respectively.

Fig. 2 compares the levels of carbonaceous speciess reported in previous studies with those of this study (Du et al., 2014; Liu et al., 2013; Huang et al., 2012; Zhou et al., 2012; Khan et al., 2010; Salma et al., 2010; Feczko et al., 2007; Pio et al., 2007; Wang et al., 2003; Krivacsy et al., 2001). The OC and EC concentrations at AI were markedly lower than those in Seoul (a representative urban area in Korea) and other urban sites in Northeast Asia, but comparable to the levels at other background sites in this region. In particular, the difference in EC concentrations between Seoul and AI was about twice that of OC concentrations. This tendency was also observed in other comparisons of urban and background sites, indicating a low direct impact of primary emissions at background sites. The WSOC concentration at AI was about half of that at urban sites (Seoul and Gwangju) in Korea but two times higher than that measured at Gosan, another representative background site in Korea. Compared to other sites in Northeast Asia, the WSOC concentration at AI was lower than those in Beijing, Hong Kong, and 14 cities in China, but comparable with levels in Tokyo, Japan. The HULIS-C concentration at AI was generally higher than those measured at urban and rural sites in Europe and New Zealand, similar to those at urban sites (Seoul and Gwangju) in Korea, and lower than those at urban sites (Shanghai and Guangzhou) in China. In brief, the EC and OC concentrations at AI were markedly lower than those of urban sites in Northeast Asia but high or comparable with rural and background sites in Northeast Asia. Meanwhile, the WSOC and HULIS-C concentrations at AI were not much lower than those of urban sites in Korea. This can be explained by the fact that primary carbonaceous aerosol emissions have no significant impact at AI; however, the influence of indirect emissions and/or secondary formation of carbonaceous aerosol might be important in this region.

Fig. 2. 
Comparison of the level of carbonaceous fractions at AI with the previous studies (the abbreviation of -sp, -sm, -fl, -wt in the x-axis indicate spring, summer, fall and winter, respectively).

Fig. 3 presents the temporal variations in the carbonaceous species and Table 1 summarizes the seasonal and annual average concentrations of the carbonaceous species. The concentrations of all carbonaceous speciess except EC increased from September to January and rapidly dropped in February. The concentrations increased again in March and decreased during April and May. In the case of EC, the highest concentration was observed on June and there were no clear increasing or decreasing tendencies. There are no statistically significant differences between seasons for the each carbonaceous species over the year at AI.

Fig. 3. 
Temporal, monthly and seasonal variations of (a) OC and EC, (b) WSOC and WISOC, and (c) HULISC and WSOC-HULISC concentrations.

Table 1. 
Seasonal average concentrations of OC, EC, WSOC, WISOC and HULIS-C (μg m-3).
Season Period # of samples OC EC WSOC WISOC HULIS-C
Summer Jun-Aug, 2015 12 3.02±1.33 0.50±0.25 1.64±0.83 1.38±0.85 1.02±0.53
Fall Sep-Nov, 2015 16 5.22±4.42 0.39±0.18 2.92±2.46 2.30±2.03 2.53±2.11
Fall* Sep-Nov, 2015 15 4.21±1.84 0.36±0.15 2.39±1.27 1.82±0.68 2.04±0.82
Winter Dec, 2015-Feb, 2016 14 4.43±1.68 0.42±0.19 2.37±0.92 2.05±0.86 1.92±0.62
Spring Mar-May, 2016 17 4.99±3.76 0.53±0.41 3.02±2.43 1.96±1.51 1.83±1.63
Spring* Mar-May, 2016 16 4.21±2.00 0.44±0.24 2.53±1.33 1.68±1.00 1.49±0.85
Jun, 2015-May, 2016 59 4.52±3.25 0.46±0.28 2.56±1.95 1.96±1.45 1.88±1.52
Jun, 2015-May, 2016 57 4.01±1.78 0.43±0.21 2.27±1.15 1.75±0.87 1.64±0.81
*It indicates the average concentrations of carbonaceous species with exclusion of the extremely high concentration episodes observed on November 09, 2015 (Fall) and May 22, 2016 (Spring).

These trends differed from the general seasonal trends observed at urban sites, which showed maximum concentrations in winter. The seasonality of the carbonaceous speciess in PM2.5 is influenced by seasonal variations in emissions and/or secomdary formation, as well as by meteorological factors. There are two potential explanations for the no significant seasonal variations in the carbonaceous speciess at AI, one is the unclear specific impact of emission sources by season at AI and a lack of difference in the formation of carbonaceous speciess by season.

3. 2 Correlations among Carbonaceous Speciess

The origin of each carbonaceso species in PM2.5 can be understood through the relationship among carbonaceous speciess. Fig. 4 shows scatter plots of OC-EC, WSOC-OC, WSOC-EC, and HULIS-C-WSOC in PM2.5 for the whole sampling period and during each season. OC existence in the atmopshere is deterimed by direct emission from primary emission sources and secondary formation, including gas-to-particle conversion processes. While, EC is directly emitted from primary emission sources. Thus, if OC and EC are mainly emitted by the same primary sources, the correlation between the OC and EC concentrations should be high. A weak correlation between OC and EC was observed during the whole period (Fig. 4), indicating that the origin of OC and EC at AI might differ, or that the major factor determining OC concentration at AI might be secondary formation. Meanwhile, the correlations between OC and EC differed among the seasons. The higher correlation between OC and EC were observed in summer and fall suggested that OC and EC shared similar sources during these seasons. However, the different slopes of the regression lines between summer and fall can be suggested that the major factor determining OC and EC concentrations in summer differed from fall even though the correlation of OC and EC were high in both seasons.

Fig. 4. 
Correlations of the concentrations for (a) OC and EC, (b) OC and WSOC, (c) WSOC and HULIS-C, and (d) WSOC and EC.

A strong correlation was observed between WSOC and OC during the whole period and in each season, while the relationship between WSOC and EC was poor (r2=0.30 shown in Fig. 4(d)). WSOC is mainly associated with secondary organic aerosol (SOA) formation and/or biomass burning. Recent studies have suggested that the solubility of organic aerosol in biomass burning plumes could be increased by both the formation of SOA and aging processes during biomass burning (Kawamura et al., 2013; Timonen et al., 2013). Therefore, the strong correlation between WSOC and OC at AI might be related to the high contributions of both secondary formation and biomass burning emissions. The correlation between HULIS-C and WSOC was high during the whole period and among the seasons. HULIS-C accounts for a large proportion of WSOC and, along with WSOC, biomass burning is a major source of HULIS, while secondary formation is also a significant factor (Lin et al., 2010). Thus, the high correlation of HULIS-C with WSOC indicated the dominance of both biomass burning and secondary formation to the carbonaceous speciess in PM2.5 at AI.

To estimate the influence of secondary formation, the concentrations of secondary organic carbon (SOC) were calculated with the EC tracer method (Lim et al., 2003):


Where, the minimum ratio of OC/EC was applied as (OC/EC)prim, related to the assumption that the lowest OC/EC ratio could appear near primary emission sources.

Fig. 5 shows the monthly variations in the estimated SOC concentrations with the oxidation ratios of carbonaceous speciese such as OC/EC, WSOC/OC, and HULIS-C/WSOC, which were used as indicators of the degree of aging and/or secondary formation. The SOC concentration increased during the cold seasons (fall and winter), with a maximum in January and minimum in July. The monthly distributions of OC/EC, WSOC/OC, and HULIS-C/WSOC all differed; however, along with the distribution of SOC concentrations, these ratios showed similar increases during cold seasons. In contrast to previous studies that have reported higher SOC concentrations and OC/EC and WSOC/OC ratios in summer at urban and rural sites worldwide were related to strong photochemical processes in summer (Kondo et al., 2007), higher SOC concentrations were observed in the colder seasons in this study. One of passible explanation for this result is the increase of the chance of aging and/or secondary formation of carbonaceous species in cold season at AI according to the frequent occurance of long range transport of SOA and its precusors during cold season.

Fig. 5. 
Monthly variations of (a) SOC concentrations with the ratios (b) OC/EC, (c) WSOC/OC and (d) HULIS-C/WSOC.

3. 3 Characteristics of Two High-carbonaceous Species Episodes

Two distinct periods with high concentrations of carbonaceous speciess in PM2.5 were observed on November 9, 2015 (episode I), and May 22, 2016 (episode II). The two episodes were distinguished by their OC/EC ratios (Fig. 6). Episode I showed the highest OC concentration during sampling period, while the EC concentration was comparable to those of other sampling periods; therefore, it had the highest OC/EC ratio (26.9). While, both OC and EC concentrations were increased in episode II; therefore, the OC/EC ratio (9.57) was comparable to the average OC/EC ratio (10.1±3.38) during the whole sampling period. Differences in the chemical composition of organic compounds were observed during the two episodes (Fig. 6). High concentrations of levoglucosan with dicarboxylic acids were observed during episode I, while only n-alkane concentrations were high in episode II. The concentrations of polycyclic aromatic hydrocarbon (PAH) compounds during the two episodes were comparable; however, the composition of individual PAH compounds differed (Fig. 7). The ratio of low-molecular-weight (MW) PAH compounds was relatively high during episode I, while high-MW PAHs were predominant during episode II. Low-MW PAH compounds are mainly emitted from coal and/or biomass burning, while high-MW PAH compounds are predominant in vehicular emissions (Lee and Kim, 2007). Based on the compositions of organic compounds during episodes I and II, we could distinguish the major factors determining the high OC concentrations in these two episodes. In episode I, the increased OC concentration was highly related to a mixture of emissions from biomass burning and secondary formation, while vehicular emissions might be the major factor driving the increases in OC and EC concentrations in episode II.

Fig. 6. 
Concentrations of (a) carbonaceous fractions and (b) organic compounds with (c) OC/EC, WSOC/OC and HULIS-C/WSOC ratios on November 9, 2015 (episode I) and May 22, 2016 (episode II).

Fig. 7. 
Normalized distributions of individual PAH compounds on November 9, 2015 (episode I) and May 22, 2016 (episode II).

During episode I, wind speeds were moderate, averaging 3.5 m/s (range: 2.0-4.9 m/s), and stagnation of air parcel at heights of 500 m and 1500 m was observed along with wildfire smoke emissions over Korea. The ambient temperature in episode I was ranged from 9.9 to 13.5°C (mean: 11.6°C) and the relative humidity was 70.8-90%. During episode II, temperatures were in the range of 16.2-25.6°C (mean=19.6°C), wind speeds were weak, ranging from 0 to 4.6 m/s (mean=2.0 m/s), and the relative humidity ranged from 30.6 to 86.1% (mean: 58.5%).

We also obtained two types of MODIS images (Aqua & Terra MODIS fire active images from the FIRMS Web Fire Mapper ( and MODIS true color images ( and backwaord trajectory of air pacel at AI (provided by the Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT 4.5) model ( of the NOAA Air Resources Laboratory (ARL)) shown in Fig. 8. Isentropic five-day backward trajectories were computed in 6-h intervals for the two episodes at three altitudes (500, 1500, and 3000 m above ground level (AGL)).

Fig. 8. 
A backward trajectory with local wind direction and MODIS fire active and true color images on (a) November 9, 2015 (episode I) and (b) May 22, 2016 (episode II).

The MODIS images showed that during episode I (Fig. 8(a)), strong fire activity was observed over North China with a thick haze layer covering over Northeast Asia including the Korean Peninsula. This is related to the results for the elevated OC, levoglucosan, and dicarboxylic acid levels at AI. In addition, during episode I, air masses originated from the urban areas of North China (at 500 and 1000 m AGL) and passed over the Yellow Sea to reached the AI site. Based on the trajectories and MODIS images, the emissions from wildfire activity areas in China could be transported to the AI site, implying that transport of biomass burning from China with the secondary formation could be responsible for the extremely hig concentration of OC at AI. Meanwhile, during episode II (Fig. 8(b)), fire activities were rare and only a thin haze layer covered southern Korea, which could be characterized by locally produced pollution (e.g., vehicular emissions) with air parcel movement from the north/east directions driven by local wind patterns.


Simultaneous measurements of OC, EC, WSOC, and HULIS-C in PM2.5 were conducted at AI, Korea, to clarify the seasonal variations and carbonaceous species concentrations in PM2.5 at a background area in Korea between 2015 and 2016.

There were no substantial temporal variations in carbonaceous speciess at AI, except for two cases on November 9, 2015, and May 22, 2016, which had extremely high carbonaceous species concentrations. The high concentration of OC on November 9, 2015, was explained by the influence of a mixture of emissions from biomass burning and secondary formation transported from outside AI based on the composition of individual conrgic compounds, backward trajectory of air parcel, MODIS images, and meteorological conditions. While, the high concentrations of OC and EC on May 22, 2016, were related to local vehicular emissions.

Excluding these two high-carbonaceous species cases, there were no statistically significant seasonal variations in carbonaceous species in PM2.5 which imply the influenc of direct emission of carboenous aerosol near AI is not important. The high correlations among OC, WSOC, HULIS-C, and SOC concentrations indicated that the formation of SOA was a major factor determining the WSOC concentrations in this region. HULIS-C was a major component of WSOC, accounting for 39-99% of WSOC.


This research was supported by the Korea Meteorological Administration Research and Development Program under grant CATER 2014-3190 and the National Strategic Project-Fine Particle of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (2017M3D8A1092015).

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