Chemical characteristics of acidic gas pollutants and PM2.5 species during hazy episodes in Seoul, South Korea

ARTICLE IN PRESS AE International – Asia Atmospheric Environment 38 (2004) 4749–4760

Chemical characteristics of acidic gas pollutants and PM2.5 species during hazy episodes in Seoul, South Korea Choong-Min Kanga, Hak Sung Leeb,*, Byung-Wook Kangc, Sang-Kwun Leed, Young Sunwooa a

Department of Environmental Engineering, Konkuk University, Seoul 143-701, South Korea Department of Environmental,Civil and Information System, Seowon University, Chongju, 361-742, South Korea c Department of Environmental Industry, Chongju National College of Science and Technology, Chongju 367-701, South Korea d Department of Environmental Science, Hankuk University of Foreign Studies, Yongin 449-791, South Korea b

Received 23 May 2003; received in revised form 15 April 2004; accepted 5 May 2004

Abstract Very high PM2.5 concentrations have been observed, which were classified as hazy episodes, on several days in the fall of 2001 in the Seoul metropolitan area. It was the worst air pollution event ever seen in this area. In order to develop the scientific PM2.5 control strategies for hazy episodes in this area, it is necessary to investigate the chemical characteristics of air pollutants during hazy episodes and evaluate where these high concentrations came from. All measurements were simultaneously taken using two sets of annular denuder system (ADS) to collect acidic gas pollutants and PM2.5 species. To characterize chemical species for the hazy days, the data were divided into the hazy and non-hazy episodes. Atmospheric HNO3, HNO2, and SO2 during the hazy episodes increased by a factor of about 1.6–2.1 compared to 2
+ those during the non-hazy episodes. The NO
3 , SO4 , and NH4 during the hazy episodes increased by a factor of about 4.4–6.1 compared to those during the non-hazy episodes. In addition, ambient PM2.5 concentrations for hazy days were a factor of 1.3–3.3 in excess of the 65 mg m
3, which is the 24-h US PM2.5 NAAQS. The mean concentrations of carbonaceous species during the hazy and non-hazy episodes were 29.26 and 11.76 mg m
3 for organic carbon (OC) and were 9.75 and 7.23 mg m
3 for elemental carbon (EC), respectively. Higher OC concentrations were observed in the hazy episodes, which may be influenced by biomass burning which occurred from the outside of the Seoul area rather than the local atmospheric formation of secondary OC. The results of the backward air trajectory analysis and weather charts reconfirmed the possibility of the effect of biomass burning. The highest contributors to the PM2.5 mass during 2
+ the hazy event were major ionic species such as: NO
3 , SO4 , and NH4 . r 2004 Elsevier Ltd. All rights reserved. Keywords: Hazy episodes; Acidic gas pollutants and PM2.5 ionic species; Organic and elemental carbon; Seoul

1. Introduction Seoul is the capital of South Korea and lies in a basin surrounded by mountains to the north, east and south, and is open to the west. The climate of the city is characterized by a cold, relatively dry winter and a hot, *Corresponding author. Tel.: +82-43-299-8722; fax: +8243-283-8822. E-mail address: [email protected] (H.S. Lee).

humid summer influenced by the summer monsoon from the ocean. In addition, the meteorological conditions which promote poor atmospheric mixing often occur during the winter months (Lee et al., 1999). At the end of 2000, it had a population of 10.3 million, with the number of households totaling 3.5 million, representing about 25% of the entire population of South Korea. The number of vehicles is about 20% (2.4 million) of the total number of vehicles. The city’s area is only 0.6% (606.5 km2) of South Korea’s total

1352-2310/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2004.05.007

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area (Seoul, 2001). Topography, meteorological conditions and pollutant emissions of the city, therefore, have brought about severe air pollution problems, including visibility impairment. The Ministry of the Environment Republic of Korea (2002) reported that PM10 concentrations in the Seoul area were about 1.7–3.5 times higher than other big cities in the world such as London, Paris, Tokyo, and New York. Much of the haze results from anthropogenic emissions of particles and invisible gases transformed to particles after emission (Watson, 2002). The fine particles (PM2.5) are the most significant factor that impacts visual air quality in many urban atmospheres (Stevens et al., 1988). Air quality including particulate matter was significant during a particularly hazy episode, caused by local fires in Southeastern Asia, Brunei Darussalam (Muraleedharan et al., 2000; Radojevic and Hassan, 1999). Sloane et al. (1991) focused on the measurement of the mass of sulfate, nitrate, organic and elemental carbon in particles as a function of particle size to identify the principal causes of visibility impairment in Denver, USA. Schichtel et al. (2001) presented the patterns and trends of haze based on human visual range observations over the United States for the period of 1980–1995 and noted that the hazy decline coincided with reductions in sulfur emissions and PM2.5. It was reported that the increase of fine particles and acidic gas pollutants were associated with the rate of incidence of adverse human health effects as well as visibility impairment (Dockery et al., 1996; Pope et al., 1995; Dockery and Pope, 1994; Spengler et al., 1990). Severe hazy episodes were observed on several days in the fall of 2001 in Seoul, South Korea, which had never been experienced in this area. This paper has investigated the chemical characteristics between the hazy and non-hazy episodes. This paper has also evaluated where these high concentrations came from and examined the relationship between the haze and its chemical components.

The ADS consisted of a teflon-coated aluminum cyclone (d50p2.5 mm at a flow rate of 16.7 l min
1; University Research Glassware); followed by three annular denuders (University Research Glassware); a filter pack which has teflon (47 mm diameter with 1 mm pore size; Gelman Science) and nylasorb (47 mm diameter with 1 mm pore size; Gelman Science) membrane filters; a rotameter for air flow control and a pump; and a housing box (University Research Glassware) to protect the annular denuders and a filter pack. Fig. 1 shows the schematic view of two sets of the ADS used for ambient samples. The denuders and filter samples from Denuder set 1 were used for the PM2.5 mass and soluble ionic species. Firstly, the denuders were extracted twice with 5 ml of pure water (over 18 MO-cm resistance) in a polyethylene bottle. The filter samples were stored in a controlled desiccator at least 24-h prior to and after sampling, and then weighed in a micro-balance (Cahn C-35). For the analysis of soluble ion species, the filters were extracted with 10 ml of pure water and 100 ml of methnol to wet the filter in an ultrasonic bath (Branson, 8210). An ion chromatograph (IC; Dionex, DX-100) was used for the anion and cation analysis from the denuder and filter extracts. The filter samples from Denuder sets 2 were used for the analysis of carbonaceous species such as organic (OC) and elemental carbon (EC). Prior to and after the sampling, the teflon and pre-fired quartz filters were stored in the desiccator and weighed as above, and then stored in a refrigerator at 4 C until analysis. The carbonaceous species (OC and EC) were analyzed by the TOR (thermal/optical reflectance) method at the DRI (Desert Research Institute, Nevada, USA). Details of the TOR method were available elsewhere (Chow et al., 1993a). Quality assurance and control (QA/QC) procedures were carried out for data certification. QC tests were estimated from the relative standard deviation (RSD)

2. Sampling and analysis Ambient samples were collected for a 24-h sampling period during the fall season, from October to November 2001, at the engineering building (15 m above the ground level) of Konkuk University in Seoul, South Korea. The sampling site was located in a commercial-residential area and did not have any large buildings as obstacles to disrupt wind flow patterns. All measurements were simultaneously done using two sets of annular denuder system (ADS) and anlayzed PM2.5, gaseous species (HNO3, HNO2, SO2, 2
and NH3), water-soluble ionic species (Cl
, NO
3 , SO4 , + 2+ 2+ Na+, NH+ , K , Mg and Ca ), organic and 4 elemental carbon.

Fig. 1. The schematic view of two sets of the ADS.

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which is the value expressed using the standard deviation as a percentage of the mean (Davis et al., 1994). The RSD of the IC determinations for anionic species averaged about 3.0%; the RSD for the nitrate ion was approximately 6.0% which was the highest one. The RSD for cationic species averaged about 4%; the RSD for the calcium ion was 4.4% which was the highest one. QA tests were made with a reference standard known concentration used for QC procedure. The evaluation of reference standards was used to estimate the accuracy of each ionic species, which was typically within 710% of the standard value. The results of QA/QC procedures, therefore, showed reasonable agreement with the IC determinations. QA/QC tests for OC and EC were also carried out at the DRI, and the precision and accuracy were less than 710%.

3. Results and discussion Table 1 summarizes the mean, standard deviation, maximum and minimum concentrations for each episode in this study and the results of a previous study (Lee et al., 1999), which was measured at the same site using the same ADS methods from October to November of 1996. Most of gas and particulate species measured in the fall of 2001 were about 1.1–2.8 times higher than those measured in the fall of 1996. However, gas phase SO2 mean concentrations in 2001 were about a half of that in 1996 because of the change of the fuel pattern used in the city. Meteorological data obtained from the Korean Meteorological Agency (KMA) are also included in Table 1. In Korea, it is commonly defined that the haze occurs if the visibility range is less than about 5 km by the eye. As shown in Table 1, the five and nine samples, therefore, were classified as the hazy and non-hazy days, respectively. The daily mean visibility range for the hazy days ranged from 0.8– 5.0 km. 3.1. Acidic gas pollutants and PM2.5 ionic species From Table 1, the mean concentrations during the hazy and non-hazy episodes were: 0.94 and 0.45 mg m
3 for HNO3, 11.4 and 5.87 mg m
3 for HNO2, 8.68 and 5.39 mg m
3 for SO2, 6.00 and 4.81 mg m
3 for NH3, 131 and 40.1 mg m
3 for PM2.5, 2.92 and 1.70 mg m
3 for Cl
,
3 26.5 and 4.81 mg m
3 for NO
for 3 , 20.3 and 3.35 mg m
3 + 2
SO4 , 0.28 and 0.15 mg m for Na , 10.3 and
3 2.34 mg m
3 for NH+ for K+, 4 , 1.21 and 0.39 mg m
3 2+ 0.12 and 0.07 mg m for Mg , and 0.55 and 0.33 mg m
3 for Ca2+, respectively. From the results of the one-way analysis of variance (ANOVA) statistical method, most of the components such as: HNO3, + 2
+ HNO2, SO2, PM2.5 mass, NO
3 , SO4 , Na , NH4 ,

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K+, Mg2+, and Ca2+, showed significant differences (po0.01) between hazy and non-hazy episodes. Atmospheric HNO3, HNO2, and SO2 during the hazy episodes increased by a factor of about 1.6–2.1 than 2
those during the non-hazy episodes, while NO
3 , SO4 , + and NH4 , which were major ionic species of PM2.5, during the hazy episodes increased by a factor of about 4.4–6.1 than those during the non-hazy episodes. Ambient NH3, a basic gas, showed little variation than the other species. The mean particulate phase concentrations during the hazy episodes were even higher than those of gaseous pollutants during the non-hazy episodes. In addition, ambient PM2.5 concentrations during the hazy episodes increased by a factor of 1.3–3.3 in excess of the 65 mg m
3, which is a 24-h US NAAQS (United States National Ambient Air Quality Standards). All PM2.5 concentrations during the non-hazy episodes did not exceed the standard. In addition, the mean PM2.5 mass of the hazy episodes was higher than those of other cities such as Athens, Greece (80.7 mg m
3, Scheff and Valiozis, 1990), Mexico City, Mexico (94.4 mg m
3, Barblaux et al., 1992), and Beijing, China (127 mg m
3, He et al., 2001), all experiencing severe air pollution. Park and Kim (2004) reported that the 12-h PM2.5 concentration in the Seoul area was 13.5–143.7 mg m
3, with a mean value of 47.8 mg m
3, during November– December of 1999. High correlation coefficients were found between NH+ and SO2
(r=0.93, po0.001), and between 4 4 + NH4 and NO
3 (r=0.97, po0.001) during the entire sampling periods. Once emitted into the atmosphere, NH3 will preferentially react with sulfuric acid to form ammonium bisulfate (NH4HSO4) aerosol or fully neutralized ammonium sulfate ([NH4]2SO4). Excess NH3 will then react with HNO3 to form ammonium nitrate (NH4NO3)(Robarge et al., 2002; Koutrakis et al., 1992). Particulate phase NH+ 4 concentrations can be calculated using the stoichiometric ratios of the different compounds and compared with actual measurements. From Fig. 2, ammonium is calculated from nitrate and sulfate, assuming that all nitrate is in the form of NH4NO3 and all sulfate is in the form of either (NH4)2SO4 (i.e. calculated ammonium =0.38  sulfate+0.29  nitrate) or NH4HSO4 (i.e. calculated ammonium =0.192  sulfate+0.29  nitrate) (Chow et al., 1996). These calculated values were compared with the measured ammonium values. It shows reasonable agreement when NH4HSO4 is assumed (Fig. 2). The calculated ammonium values, when (NH4)2SO4 is assumed, were overestimated since calculated ammonium values were above the one-to-one line. In addition, the best fitting regression line for the hazy episodes was Y=0.95X+1.84 (r=0.96) when NH4HSO4 is assumed, and that for the non-hazy episodes was Y=0.77X+0.86 (r=0.85) when (NH4)2SO4 is assumed. And thus, it may

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Table 1 Summary statistics of the chemical species on each episode (mgm
3) Cl


NO
3

SO2
4

Na+

NH+ 4

K+

Mg2+

Ca2+

OCa

ECb

8.68 2.33 12.5 6.13 5.39 1.66 8.87 3.98

6.00 1.33 7.58 4.06 4.81 1.78 8.24 3.06

131 50.2 215 82.4 40.1 12.0 56.1 20.0

2.92 3.03 7.38 0.44 1.70 0.95 3.23 0.38

26.5 11.2 41.6 15.0 4.81 1.73 8.95 3.46

20.3 7.91 30.1 9.60 3.35 1.75 5.82 1.00

0.28 0.10 0.44 0.20 0.15 0.06 0.25 0.09

10.3 4.42 17.5 6.32 2.34 1.13 4.38 0.41

1.21 0.32 1.64 0.82 0.39 0.10 0.53 0.22

0.12 0.02 0.14 0.10 0.07 0.01 0.09 0.05

0.55 0.12 0.73 0.44 0.33 0.05 0.42 0.25

29.3 16.0 53.8 22.2 11.8 3.52 16.8 5.29

9.75 4.70 15.1 3.53 7.23 3.08 12.6 2.93

6.57 2.46 12.5 3.98 13.6 5.96 31.1 6.28

5.24 1.69 8.24 3.06 4.82 2.68 10.5 0.15

72.5 53.8 215 20.0 50.3 19.2 82.7 25.4

2.14 1.94 7.38 0.38 0.95 0.75 2.48 0.08

12.6 12.5 41.6 3.46 4.49 3.29 11.4 0.65

9.42 9.62 30.1 1.00 5.62 4.64 18.9 1.74

0.20 0.10 0.44 0.09 0.25 0.44 1.45 0.01

5.17 4.72 17.5 0.41 2.95 2.04 7.04 0.76

0.68 0.46 1.64 0.22 0.41 0.25 1.07 0.19

0.09 0.03 0.14 0.05 0.02 0.04 0.14 0.00

0.41 0.13 0.73 0.25 0.55 0.68 2.75 0.19

18.0 12.7 53.8 5.29 —j — — —

8.13 3.77 15.1 2.93 — — — —

HNO3

HNO2

SO2

Haze N=5g

Mean SDh Max Min Mean SD Max Min

0.94 0.40 1.31 0.49 0.45 0.14 0.65 0.31

11.4 4.61 18.8 7.67 5.87 1.81 9.10 3.53

Mean SD Max Min Mean SD Max Min

0.63 0.34 1.31 0.31 0.39 0.26 1.13 0.14

7.85 4.01 18.8 3.53 6.27 3.32 11.2 1.29

Non-haze N=9

Y 2001 N=14i

Y 1996 N=15

a

Organic carbon. Elemental carbon. c Unit (ppbv). d Ambient temperature ( C). e Relative humidity (%). f Visibility (km). g Number of samples. h Standard deviation. i Sum of the hazy days(n ¼ 5) and non-hazy days(n ¼ 9). j Not available. b

NO2c

Tempd

RHe

Visif

3.8 3.0 7.2 0.6 3.3 1.8 5.7 0.5

67.6 7.1 74.8 56.4 46.7 9.6 68.6 38.8

14.5 5.0 18.9 8.5 11.4 5.2 17.5 4.7

69.0 8.5 83.3 61.6 52.3 12.7 70.9 37.4

3.3 1.6 5.0 0.8 15.5 3.7 22.7 9.8

3.5 2.2 7.5 0.5 7.9 5.0 17.6 1.4

54.1 13.4 74.8 38.8 40.4 11.8 67.4 25.9

12.5 5.1 18.9 4.7 11.0 4.4 17.3 3.0

58.3 13.8 83.3 37.4 57.5 12.8 75.6 38.4

11.1 6.7 22.7 0.8 13.7 4.7 19.7 6.6

O3c

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PM2.5

Statist

C.-M. Kang et al. / Atmospheric Environment 38 (2004) 4749–4760

NH3

Episode

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nitrate concentration. The nitrate loss rate is obtained by dividing the nitrate measured from nylasorb filter by total nitrate concentration. As shown in the figures, the nitrate concentration was, in general, lower than the total nitrate concentration and consistent with the total nitrate concentration (r ¼ 0:99). The correlation between the nitrate loss rate and total nitrate concentration is somewhat reasonable and shows the negative correlation (r ¼
0:75), excluding the 17th October result. This is consistent with the results of Chang et al. (2000) and Zhang and McMurry (1992) who noted that nitrate loss rate decreases with the increasing value of total nitrate concentration. In addition, the average nitrate loss rates during the hazy and non-hazy episodes were approximately 17% (3–31%) and 38% (17–84%), respectively.

be considered that the composition of hazy days is more acidic than those of non-hazy days. Sampling artifacts such as losses of volatile nitrate can occur during the sampling. Nitrate losses have been attributed to either an increase in pressure drop across the particle-collecting medium or changes in the solid– gas equilibrium between particulate NH4NO3 and gaseous HNO3 and NH3 (Chang et al., 2000). Fig. 3(a) shows the plot of the nitrate concentration measured only from teflon filter as a function of total nitrate concentration calculated by the sum of nitrates measured from teflon and nylasorb filters. Fig. 3(b) also shows the plot of the nitrate loss rate against total

25

3.2. Carbonaceous species Calculated NH4+ (µg/m3)

20

Fine carbonaceous matter is emitted from most combustion processes. These primary carbon particles consist of organic compounds accompanied by black non-volatile soot components, which have a chemical structure similar to impure graphite. OC, major components of organic compounds, can be emitted from either anthropogenic or biogenic sources, as well as, generated from chemical transformations among primary gas-phase OC in the atmosphere. The black portion of these particulate matter emissions, commonly referred to as EC, is a major contributor to visibility impairment in urban areas (Gray et al., 1986). Fig. 4 shows the mean (dotted), median (line), 5/95 percentiles, and outliers of OC and EC during the sampling periods. As shown in Table 1 and Fig. 4, the averaged concentrations for the entire sampling periods, hazy, and non-hazy episodes were 18.0, 29.3, and

Y=1.47X-0.38 r=0.98 15

Y=1.11X-0.31 r=0.98 10

(NH4)2SO4

5

NH4HSO4 0 0

5

10

15

20

25

Measured NH4+ (µg/m3) Fig. 2. Comparison between calculated and measured ammonium.

50

50

40

40

Y = 0.95X - 1.82 r = 0.99

Nitrate Loss (%)

Teflon-filter Nitrate Concentration (µg/m3)

83.9% (10/17)

30

20

10

20

10

0

0 0

(a)

Y = -0.74X + 36.03 r = -0.75

30

10

20

30

40

50 3

Total Nitrate Concentration (µg/m )

0

(b)

10

20

30

40

50 3

Total Nitrate Concentration (µg/m )

Fig. 3. (a) Plot of teflon-filter nitrate concentration vs. total nitrate (teflon and nylasorb filters) concentration. (b) Plot of nitrate loss vs. total nitrate concentration.

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20

60

16

Elemental Carbon (µg/m3)

Organic Carbon (µg/m3)

50

40

30

20

12

8

4 10

0

0

TOTAL

HAZE

TOTAL

NON-HAZE

HAZE

NON-HAZE

Fig. 4. Distributions of organic and elemental carbon concentrations on each episode.

60

Concentration (µg/m3)

50

Organic Carbon Elemental Carbon Ozone (ppb)

40

30

20

10

0

Concentration (µg/m3)

8

-

Cl K+

6

4

2

0 10/12 10/15 10/17 10/19 10/23 10/25 10/27 10/29 11/3 11/6 11/12 11/14 11/20 11/22

Sampling Date

Fig. 5. The time plots of OC, EC, O3, Cl
, and K+ concentrations.

11.8 mg m
3 for OC, and 8.13, 9.75, and 7.23 mg m
3 for EC, respectively. The levels of OC and EC during these study periods were also compared with those of the urban areas such

as: Athens, Sao Paulo and Beijing, which have experienced severe air pollution problems. The mean concentrations of OC and EC constituted 21% (16.9 mg m
3) and 5% (4.2 mg m
3), respectively, of the

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Fig. 6. The surface weather maps on 20 and 22 November 2001.

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PM2.5 mass in Athens, Greece (Scheff and Valiozis, 1990). In Beijing, China, the OC concentrations during summer, fall, winter, and spring constituted 23% (13.4 mg m
3), 26% (28.8 mg m
3), 18% (31.5 mg m
3), and 21% (18.2 mg m
3), respectively, of seasonal PM2.5 mass, and the EC concentrations constituted 11% (6.3 mg m
3), 9% (10.2 mg m
3), 6% (11.1 mg m
3), and 8% (6.7 mg m
3), respectively (He et al., 2001). Castanho and Artaxo (2001) reported that the values of organic and elemental carbon were 52% (15.8 mg m
3) and 25% (7.6 mg m
3), respectively, of the PM2.5 mass in the winter season, and 35% (5.3 mg m
3) and 27% (4.1 mg m
3), respectively, in the summer season in Sao Paulo, Brazil. The mean contributions of OC and EC during the episodes at the Seoul site, therefore, were higher than those at Athens and Beijing, and lower than those in Sao Paulo. In addition, the non-hazy EC concentration of this study showed a similar distribution to the other results (15%, 7.17 mg m
3) in the Seoul area (Park and Kim, 2004). The ratio of total carbon (OC+EC) to elemental carbon (TC/EC) exceeding 3 was used to identify the presence of secondary organic carbon. The formation of secondary OC is one of the reasons of high OC levels. Atmospheric formation of secondary OC is expected during ozone episodes because secondary OC is formed by condensation of low vapor pressure products during photo-oxidation of hydrocarbons (Chow et al., 1993b; 1996). In addition, Turpin and Huntzicker (1995) reported that the secondary OC formations were related with O3 concentrations and weather conditions such as development of the sea breeze in the Los Angeles area. In this study, the TC/EC ratios were 5.674.4 and 3.071.3, respectively, for the hazy and non-hazy episodes. And thus, the ratios may show the possibility of secondary OC formations during the sampling periods. Fig. 5 shows the time series plot of OC, EC, Cl
, and K+ concentrations in the fine particles, and O3 concentrations measured at the distance of about 1 km from the PM2.5 sampling site. The variations of OC concentrations represented a somewhat different pattern from the O3 concentrations. For instance, while higher OC concentrations were found on November 20 and 22 (36.7 and 53.8 mgm
3, respectively), lower O3 concentrations were found on these days (0.8 and 0.6 ppb, respectively). The relationship between the TC/EC ratios and O3 concentrations represented the negative correlation (r ¼
0:50) during the sampling periods. In addition to these reasons, ambient O3 concentrations during the sampling periods might be too low to form secondary OC because the mean O3 concentration was 3.5 ppb (0.5–7.2 ppb). High OC concentrations observed during the hazy episodes, thus, may not be formed from local sources. Biomass burning can be the most important factor of the local emissions and/or transport effects of OC to the

Fig. 7. Three-day backward air trajectories for the hazy days.

sampling site because vast agricultural areas are located in the direction of main wind direction (west and northwest). Biomass burning is also carried out in Korea and China during the fall season (harvest season). The abundant species emitted from biomass burning are OC, Cl
and K+, consistent with most profiles through the biomass burning experiment (Kang, 2003; Watson and Chow, 2001). Positive correlations were found between OC and K+ concentrations (r ¼ 0:79), and between OC and Cl
concentration (r ¼ 0:87). Duan et al. (2004) reported that high levels of OC and K+ in particulate matter were observed in Beijing during the wheat harvesting season, and biomass burning accounted for B70% of the total particulate matter during this season. Park and Kim (2004) also suggested that the abundance of K+ to PM2.5 mass observed in the urban cities of Korea appears to be related to the biomass burning processes from the results of the enrichment factor analysis. And thus, it might be explained that biomass burning occurred from outside of the Seoul area has an effect on the high OC concentration in this study. To estimate the weather conditions during the hazy days, the weather charts on November 20 and 22 of 2001, when the highest PM2.5 concentrations (121.7 and 214.6 mg m
3) were observed at the sampling site, are shown in Figs. 6(a) and (b). From Fig. 6(a), highpressure systems located at the whole areas of East Asia on November 20 made the conditions of the sampling site atmospherically stable. The mean and range of air temperature, relative humidity, prevailing wind direction, and speed on November 20 were: 9.8 C (6.7–13.8), 69% (37–84), NW/NE, and 1.2 m s
1 (0.2–2.9), respectively. The weather chart on November 22 (Fig. 6b) showed that the continental high-pressure systems were located at the southern and southeastern area of Russia and a strong low-pressure system was located at the Pacific Ocean. The entire Korean peninsula was covered by a low-pressure system. Meteorological parameters

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60

50

(a)

(b)

Nitrate Sulfate Ammonium Visibility (1km)

40

Organic carbon Elemental carbon Visibility (1km)

50

Daily mean

40 30 30 20 20 10 10

250

11/22

11/20

11/14

11/6

11/12

11/3

10/29

10/27

10/25

Sampling Date

(c) 200

Daily mean

10/23

10/19

10/17

10/15

0 10/12

11/22

11/20

11/14

11/6

11/12

11/3

10/29

10/27

10/25

10/23

10/19

10/17

10/15

10/12

0

PM2.5 Nitrogen Dioxide (ppb) Relative humidity (%) Visibility (100m)

150

100

50

11/22

11/20

11/14

11/12

11/6

11/3

10/29

10/27

10/25

10/23

10/19

10/17

10/15

10/12

0

Sampling Date

Fig. 8. Diurnal variations of the variables related to visibility during the sampling periods; the unit of PM2.5 and its species are mg m
3.

25

Calculated v (km)

20

15

r = 0.95 10

5

0 0

5

10

15

20

25

Measured v (km)

Fig. 9. Relationship between measured v and calculated v.

such as: air temperature, relative humidity, prevailing wind direction, and speed on November 22 were: 8.5 C (6.0–12.5), 83% (64–96), W/NW, and 1.2 m s
1 (0.0–

3.1), respectively. From these two weather charts, it can be assumed that atmospheric conditions at the sampling site may be stable and restrained air dispersion at the surface, and influenced by the air mass from China. In addition, backward air trajectory analysis was carried out to find out the possibility of atmospheric transport of OC from outside of the city. For the hazy days, the three-day backward air trajectories at the sampling site (37.34 , 126.59 E) are shown in Fig. 7. Backward air trajectories were calculated using the HYSPLIT 4 (Hybrid Single-Particle Lagrangian Integrated Trajectory) model developed by NOAA/ARL (National Oceanic and Air Administration/Air Resources Laboratory in the USA). The Final Run (FNL) meteorological data was used for the trajectory calculation. The isentropic three-days-backward air trajectories were computed at an altitude of 3000 m Above Ground Level (AGL) for the hazy days. Backward air trajectory analysis showed that the air mass mainly originated from the desert areas of Mongolia and China, passed through the northeastern part of China, where highly polluted areas and agricultural areas are located. Especially, agricultural burning occurs at these

ARTICLE IN PRESS C.-M. Kang et al. / Atmospheric Environment 38 (2004) 4749–4760

4758

trations were obtained from the data measured at the distance of about 1 km from the PM2.5 sampling site. Farber et al. (1994) calculated the visibility range using computer model equations to study the visibility in the Los Angeles Basin. The equations referred from the study of Faber et al. (1994) are

areas during the fall season, when the PM2.5 sampling of this study was carried out. In addition, Duan et al. (2004) reported that high OC and K+ concentrations were observed during the fall in the Beijing area because of the biomass burning, such as agricultural burning. And thus, it may be explained that high values of TC/ EC for the hazy days are caused by the transport of organic species which came from the agricultural burning outside of the Seoul area.

v ¼ 3:0=bext

ð1Þ

bext ¼ bsp þ bap þ bag þ bray

ð2Þ

bext ¼ ð0:03  10
4 m
1 mg
1 m
3 Þð½Nitrate þ ½Sulfate 3.3. Relationship between air pollutants and visibility impairment

þ ½Org: Þ þ ð0:006  10
4 m
1 mg
1 m
3 Þ½PM þ ð0:12  10
4 m
1 mg
1 m
3 Þ½EC þ ð3:3  10
4 m
1 ppm
1 Þ½NO2

Farber et al. (1994) reported that the dominant hazy component of the chemical species was particulate sulfate followed by nitrate and the carbon species, such as organic and elemental carbon. Malm and Gebhart (1996) interpreted EC as light-absorbing carbon. Air pollutants and meteorological parameters related with the visibility impairment were plotted with visibility range in Fig. 8(a)–(c). From the correlation analysis and Fig. 8(a)–(c), high negative correlations were found 2
between visibility range and NO
3 (r ¼
0:84), SO4 + (r ¼
0:85), NH4 (r ¼
0:85), and OC (r ¼
0:72), except EC (r ¼
0:42). High negative correlations were also found between visibility range and PM2.5 (r ¼
0:86), NO2 (r ¼
0:86) and relative humidity (r ¼
0:77), known as hazy constituents. NO2 concen-

þ ð0:114  10
4 m
1 Þ;

ð3Þ

where v is the visibility range; bext is the extinction coefficient; bsp is the light scattering coefficient from particles; bap is the light absorption coefficient from particles; bag is the light absorption by gases such as NO2; and bray is the light scattering of air molecules; [Nitrate]=NH4NO3/(1-RH); [Sulfate]= [(NH4)2SO4]/(1-RH); [Org.]=1.4  [OC]  [0.7+0.3(1RH)]; [PM]=[PM2.5]; NH4NO3=1.29  [NO
3 ]; (NH4)2 SO4=1.38  [SO2
4 ]. As a check on the data quality, the relationship between the measured visibility range and the calculated visibility range is shown in Fig. 9. Firstly, calculated

250

PM2.5 Mass (µg/m3)

200

Haze episodes

150

100

Haze episodes

Major ions Other Ions Organic materials Elemental Carbon Unidentified

Non-haze episodes

Non-haze episodes

50

0 10/12 10/15 10/17 10/19 10/23 10/25 10/27 10/29

11/3

11/6

11/12 11/14 11/20 11/22

Sampling Date Fig. 10. Diurnal variations of material balance for chemical species in fine particles.

ARTICLE IN PRESS C.-M. Kang et al. / Atmospheric Environment 38 (2004) 4749–4760

extinction coefficients (calculate bext) were obtained 2
from the variables such as: NO
3 , SO4 , OC, EC, PM2.5, NO2, and relative humidity, known as the variables related with visibility impairment, using the Farber’s model equation, Eq. (3). And then, the calculated visibility range (v) would be obtained from the Eq. (1). From Fig. 9, the measured visibility range (measured v) is consistent with the visibility range (calculated v) calculated from the variables related with visibility impairment. It may be confirmed that chemical species of fine particles are closely related with visibility impairment.

4759

respectively. Higher TC(OC+EC)/EC ratios, which indicate the formation of secondary OC, were observed in the hazy episodes. From the results of the relations between OC, O3, K+, and Cl
, backward air trajectory analysis, and weather charts, higher OC concentrations during the hazy days may influence the biomass burning which occurred from the outside of the Seoul area. From the relationship between visibility range and hazy constituents, it may be expected that the hazy constituents were closely related with visibility impairment. The highest contributors to the PM2.5 mass during the hazy and non-hazy episodes were major ionic species (44%) and organic materials (42%), respectively.

3.4. Composition of fine particles Diurnal variations of the material balance for major 2
+ ionic species (such as NO
3 , SO4 , and NH4 ), other
+ + 2+ ionic species (such as Cl , Na , K , Mg , and Ca2+), organic materials, EC, and unidentified mass abundances in the PM2.5 mass are shown in Fig. 10. Organic materials have been calculated using the factor of 1.4 to account for unmeasured hydrogen and oxygen in organic materials (Chow et al., 1994; Solomon et al., 1989). On 22 November (which was the highest PM2.5 mass of the hazy episodes), the major contributors of the PM2.5 mass were major ionic species (42%) followed by organic materials (35%). On the other hand, in the case of 6 November, the highest PM2.5 mass of the non-hazy episodes, the major contributors of the PM2.5 mass were organic materials (30%) followed by the major ionic species (29%). When the contribution of chemical species to the PM2.5 mass averaged across the hazy episodes, the contributing species were in the following order: major ionic species (44%)>organic materials (31%)>EC (8.7%). For the non-hazy episodes, the trend of the contributors to the PM2.5 mass was the following: organic materials (42%)>major ionic species (26%)>EC (19%).

4. Conclusions Severe hazy episodes including five hazy days were observed during the fall of 2001 in the Seoul area. The characteristics of acidic gas pollutants and PM2.5 ionic species during the hazy episodes were evaluated, and compared with those during the non-hazy episodes. The levels of all chemical species measured increased during the hazy episodes, compared with the results of the nonhazy episodes. Most of gas and particulate species measured in the fall of 2001 were about 1.1–2.8 times higher than those measured in the fall of 1996. The composition of hazy days may be more acidic than that of non-hazy days. In addition, the average nitrate loss rates during the hazy and non-hazy episodes were approximately 17% (3–31%) and 38% (17–84%),

Acknowledgements This work was supported by Grant No. R01-2000000-00340-0 from the Basic Research Program of the Korea Science & Engineering Foundation (KOSEF).

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