Polycyclic aromatic hydrocarbons (PAHs) in soils from a multi-industrial city, South Korea

Science of the Total Environment 470–471 (2014) 1494–1501

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Polycyclic aromatic hydrocarbons (PAHs) in soils from a multi-industrial city, South Korea Hye-Ok Kwon, Sung-Deuk Choi ⁎ School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan, 689-798, Republic of Korea

H I G H L I G H T S • • • • •

We collected soil samples at 25 sites in the multi-industrial city of Ulsan, Korea. The levels, patterns, and spatial distribution of PAHs were investigated. For source identification of PAHs, diagnostic ratios and the PMF model were used. Industrial sites showed much higher levels of PAHs than rural and urban sites. Industrial complexes and vehicles were major sources of PAHs in Ulsan.

a r t i c l e

i n f o

Article history: Received 2 May 2013 Received in revised form 9 August 2013 Accepted 12 August 2013 Available online 5 September 2013 Editor: Damia Barcelo Keywords: PAHs Soil Source identification Ulsan

a b s t r a c t We collected soil samples at 25 sites in Ulsan, Korea to investigate the levels, patterns, spatial distribution, and sources of polycyclic aromatic hydrocarbons (PAHs) in the summer 2010. The target compounds were the 16 US-EPA priority PAHs. For the source identification of PAHs, diagnostic ratios and the positive matrix factorization (PMF) model were used. The total concentrations of PAHs ranged from 65 ng/g to 12,000 ng/g (mean: 960 ng/g, median 330 ng/g). The levels and distribution of PAHs indicated that industrial areas were more polluted than rural and urban areas. The diagnostic ratios suggested that the soil samples were contaminated by pyrogenic sources and traffic emission. According to the result of PMF, four factors were identified: gasoline and heavy oil combustion (14%), diesel combustion (54%), coke oven (23%), and coal/biomass burning (9%). Therefore, it was concluded that vehicles and industrial complexes were major sources of PAHs in Ulsan. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are composed of two or more fused aromatic rings, and 16 PAHs were listed as priority pollutants by the US environmental protection agency (US-EPA). Several PAHs have been classified into carcinogenic compounds by the international agency for research on cancer (IARC, 1987). PAHs are emitted to the atmosphere mainly from anthropogenic sources such as vehicles (Marr et al., 1999; Jo and Lee, 2009) and industrial facilities (Yang et al., 1998, 2005). PAHs are dispersed into the surrounding area and undergo long-range atmospheric transport (LRAT) to other areas even in the remote mountains and the polar region which have no emission sources (Choi et al., 2009, 2012a). A large amount of PAHs emitted to the atmosphere accumulates in soil via dry and wet deposition (Lee and Lee, 2004). Soil is a good indicator of long-term environmental

⁎ Corresponding author. Tel.: +82 52 217 2811; fax: +82 52 217 2809. E-mail address: [email protected] (S.-D. Choi). 0048-9697/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scitotenv.2013.08.031

pollution because PAHs are strongly associated with soil organic matter (Agarwal et al., 2009; Wang et al., 2013). Humans can be directly exposed to PAHs in soil via inhalation of flying dust, ingestion, and dermal contact (Zhang et al., 2012). In addition, PAHs in soil can be transported with organic matter to the river especially in raining seasons (Hoffman et al., 1984). Thereafter, PAHs in the river can accumulate in humans through the food chain for a long time (Gilbert, 1994; Martorell et al., 2010). For these reasons, investigation on soil pollution by PAHs and human health risk assessment are required. The metropolitan city of Ulsan is a representative industrial city with petrochemical, automobile, and ship building/heavy industries. Because of these industrial activities and large population (N one million), environmental issues have been a major concern in Ulsan. Industrial complexes are located along the east coast of Ulsan, and residential areas are located close to the industrial complexes. It is well known that large amounts of PAHs are emitted from petrochemical processes and incomplete combustion of fossil fuels (Yang et al., 1998; Ma et al., 2010). Consequently, Ulsan can be significantly contaminated by PAHs emitted from the industrial complexes (Choi et al., 2012b). Therefore, investigation

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on the levels, patterns, spatial distribution, and emission sources of PAHs is essential to assess human health risk and to establish environment policies in Ulsan. However, relatively small numbers of monitoring studies on PAH pollution have been conducted in Ulsan. For example, the levels and spatial distribution of PAHs in sediment and water samples from Ulsan Bay were studied, and higher PAH levels were observed near the industrial complexes (Khim et al., 2001). The atmospheric deposition of PAHs onto Ulsan Bay was also investigated, and the deposition of PAHs was greater in winter due to increased fossil fuel burning and prevailing wind directions (Lee and Lee, 2004). Ambient air samples (PM10) were collected at three sites (downtown, residential, and industrial), and the downtown site showed the highest PAH level by the effect of both industrial and vehicle emissions (Vu et al., 2011). More recently, the source-receptor relationship of gaseous PAHs was investigated using passive air samplers deployed at 20 sites (Choi et al., 2012b). Through this study, the influence of the industrial complexes on the levels and patterns of PAHs in the surrounding areas was confirmed. In addition, the levels and risk of PAHs in road dust were reported (Dong and Lee, 2009; Lee and Dong, 2010). These two studies revealed that industrial emission and vehicular exhaust are the main sources of PAHs in road dust collected in Ulsan. As mentioned above, PAHs were detected in the various environmental compartments of Ulsan. To the best of our knowledge, however, no studies have dealt with soil pollution by PAHs in Ulsan. Since soil reflects relatively long-term pollution, the source-receptor relationship of PAHs can be more reliably elucidated using soil monitoring data. Moreover, the monitoring results in Ulsan can be useful to identify PAH sources in other industrial cities. Therefore, we have collected soil samples every 6 months since 2010, considering heating and nonheating seasons as a time scale. This study is the first in a series examining the levels, patterns, spatial distribution, and emission sources of PAHs in the soil of Ulsan.

2. Materials and methods 2.1. Soil sampling We collected soil samples at 25 sites in Ulsan, Korea in July 2010. The sampling sites were systematically selected, and they are classified into

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three groups: industrial (I1-I10), urban (U1-U10), and rural (R1-R5) sites (Fig. 1). The industrial complexes were divided into several sections, and then the sampling sites were preliminarily selected using Google Earth. After that, we visited each sampling site and checked the field condition to finalize the selection of sampling sites. The industrial soil samples were collected from the non-ferrous industrial (I1-I4), petrochemical (I5-I8), automobile (I9), and ship building/heavy industrial complexes (I10). The urban sites with the highest population density for each administrative district were selected. Lastly, the rural sites were selected considering low population densities and distances (N2 km) from the industrial complexes to avoid direct pollution. We tried to collect conservative soils which were not recently disturbed by anthropogenic activities such as building construction and road pavement and repair. At each sampling site, five sub-soil samples (each of 100 g) were collected from the surface (b5 cm) and mixed together. The composite samples were kept in polyethylene bags and were stored at −4 °C until instrumental analysis.

2.2. Analysis and QA/QC The target PAHs in this study were the 16 US-EPA priority PAHs: naphthalene (Nap), acenaphthylene (Acy), acenaphthene (Ace), fluorene (Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Flt), pyrene (Pyr), Benzo[a]anthracene (BaA), chrysene (Chr), benzo[k]fluoranthene (BkF), benzo[b]fluoranthene (BbF), benzo[a]pyrene (BaP), indeno[123cd]pyren (Ind), dibenzo[ah]anthracene (DahA), and bezo[ghi]perylene (BghiP). The soil samples were dried at room temperature (18 °C) until constant weight and sieved with a 2 mm mesh sieve in order to remove large particles. The homogenized samples (10 g each) were mixed with 5 g of anhydrous sodium sulfate (Na2SO4) and then Soxhlet extracted with 350 mL of hexane/acetone (v/v 9:1). Prior to the extraction, five surrogate standards (naphthalene-d8, acenaphthene-d10, phenantrene-d10, chrysene-d12, and perylene-d12) were injected to the samples. The extracted samples were evaporated by a nitrogen evaporator (MGS2200, Eyela) to 10 mL, and then 2 mL aliquots were cleaned up on silica gel columns with 2 g of sodium sulfate, 2 g of alumina, and 5 g of activated silica gel. The samples were eluted by dichloromethane/hexane (v/v 1:3, 200 mL) and evaporated by the nitrogen evaporator to 1 mL. The internal standard (p-terphenyl-d14) was added to GC vials prior to the

Fig. 1. Location of sampling sites, which are classified into the industrial, urban, and rural sites in Ulsan, South Korea. The red areas represent industrial complexes.

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GC injection. PAHs were analyzed using a gas chromatograph/ion trap mass spectrometer (GC/ITMS: PolarisQ, Thermoquest) with a DB-5MS column (30 m, 0.25 mm ID, 0.25 μm film thickness). One microliter of the final sample was injected to the GC in splitless mode, and carrier gas was helium (He) with a flow rate of 1 mL/min. The temperature program of the GC oven condition was as follows: 50 °C (1 min) → 15 °C/min → 120 °C → 10 °C/min → 230 °C → 5 °C/min → 300 °C. For quality assurance and quality control (QA/QC), every extraction batch of samples had a method blank (n = 4) to check contamination during experiment. The method blanks were analyzed using the same method for the real samples; the average levels of individual PAH in the method blanks ranged from ND to 0.3 ng/g, and all data were corrected for average blank values. Mean recoveries of surrogate standards were 57%, 83%, 106%, 90%, and 98% for naphthalene-d8, acenaphthene-d10, phenantrene-d10, chrysene-d12, and perylene-d12, respectively. As an accuracy test, representative samples for the rural (R1), industrial (I4), and urban (U5) areas were repeatedly analyzed (n = 3); the relative standard deviations (RSD) were below 30%. Method detection limits (MDL) were calculated by the multiplication of the standard deviations of seven replicates of the MDL standard and the Student's t value (3.14) for a 99% confidence level. The MDL values are shown in Table 1.

2.3. Methods for source identification Several methods have been used to identify the sources of PAHs, e.g., diagnostic ratio (Sofowote et al., 2010; Tobiszewski and Namieśnik, 2012) and receptor-oriented models (Larsen and Baker, 2003; Lestari and Mauliadi, 2009; Wang et al., 2009; Zhang et al., 2012). In this study, diagnostic ratios and the positive matrix factorization (PMF) model, one of representative receptor models, were used to evaluate the emission sources of PAHs in the soil samples. Diagnostic ratios have been most widely used to distinguish the emission sources of PAHs, e.g., pyrogenic and petrogenic sources by ∑LMW/∑HMW (Soclo et al., 2000), petrogenic and coal/biomass combustion by Flt/(Flt+Pyr) (Yunker et al., 2002), and traffic emission and coal/biomass combustion by BaP/BghiP (Ye et al., 2006). Therefore, we can calculate various diagnostic ratios and directly compare our results with others reported in previous studies. This method is very easy to use, but it cannot give quantitative information on the contribution of PAH sources, especially for the samples affected by mixed sources. Therefore, the PMF model, which has been used to investigate the contribution of emission sources to the PAH levels based on observations

at sampling sites, was additionally used in this study. The PMF model is based on Eq. (1) (US-EPA, 2008). X ¼ GF þ E

ð1Þ

where X is the data matrix, G is the source contribution matrix, F is the source profile matrix, and E is the residual matrix. The uncertainty is calculated using method detection limits (MDL) as input data (US-EPA, 2008). In this study, we used the PMF 3.0 software developed by US-EPA. 3. Results and discussion 3.1. Levels and spatial distribution of PAHs The levels (min, max, mean, and median) of 16 PAHs in the 25 soil samples were listed in Table 1. The total PAH concentrations (∑16 PAHs) ranged from 65 ng/g to 12,000 ng/g (mean: 960 ng/g, median: 330 ng/g). The highest and lowest concentrations of total PAHs were measured at sites I4 (12,000 ng/g) and U1 (65 ng/g), respectively. Site I4 also showed the highest concentration (5,800 ng/g) of seven carcinogenic PAHs (∑7carc PAHs: BaA, Chr, BbF, BkF, BaP, Ind, and DahA). The reason for this high level will be discussed in the following sections. Regarding land use, the mean concentrations of ∑16 PAHs (∑7carc PAHs) were 220 (64) ng/g, 390 (150) ng/g, and 1,900 (880) ng/g in the rural, urban, and industrial areas, respectively. The average concentration of ∑16 PAHs at the industrial sites was five and eight times higher than those at the rural and urban sites, respectively. Besides, the average concentration of ∑7carc PAHs at the industrial sites was thirteen and six times higher than those at the rural and urban sites, respectively. The average portion of ∑7carc PAHs at the industrial sites was 46% of ∑16 PAHs. The levels of PAHs in the rural (mean: 220 ng/g, median: 220 ng/g) and urban sites (mean: 390 ng/g, median: 270 ng/g) were not statistically different (Rank sum test, p value N0.05) (Fig. 2). This result is different from the previous study reporting a gradient of atmospheric PAH levels (industrial N urban N rural) in Ulsan (Choi et al., 2012b). As the sampling of this previous study was carried out in winter, the concentrations of PAHs at urban sites were higher than those at the rural sites due to house heating. Moreover, major wind directions in the winter were from northwest (rural area) to southeast (urban and industrial areas), while those in summer were reverse directions (Choi et al., 2012b). In this study, therefore, the soil samples from the urban and rural sites might be affected together by PAHs emitted from the

Table 1 Concentrations (ng/g dry weight) of PAHs in the soil samples collected in Ulsan, Korea. BDL presents “below detection limit”. Compound

Nap Acy Ace Flu Phe Ant Flt Pyr BaA Chr BbF BkF BaP Ind DahA BghiP 16 PAHs 7 PAHsa a

MDL

0.3 1.9 0.3 0.7 0.2 1.2 1.2 1.1 0.3 1.1 0.9 0.5 1.5 0.6 1.0 1.3

Rural area

Urban area

Industrial area

Total

Min

Max

Mean

Median

Min

Max

Mean

Median

Min

Max

Mean

Median

Min

Max

Mean

Median

23 BDL 0.4 3.1 9.5 14 3.4 3.4 0.8 BDL 2.5 0.7 BDL 7.1 7.8 10 92 24

57 3.7 11 10 36 52 73 54 15 8.2 34 9.7 20 30 21 40 450 110

38 2.2 5.2 5.8 19 26 21 17 5.0 3.5 12 5.0 9.1 16 14 24 220 64

35 2.2 4.7 4.6 18 20 9.0 7.0 2.9 2.4 6.3 4.4 5.4 16 13 27 220 72

4.7 BDL 3.5 1.8 8.4 2.3 4.5 3.9 0.8 1.8 3.2 0.9 3.6 2.2 BDL BDL 65 14

220 13 22 9.1 90 61 140 130 160 92 100 27 100 89 13 95 1,200 590

61 5.3 8.1 4.9 30 19 49 44 31 23 30 10 26 23 3.7 22 390 150

52 3.6 5.7 5.0 25 17 35 32 13 11 19 6.8 15 11 2.2 9.8 270 83

33 BDL 2.5 1.0 10 3.0 10 9.0 2.1 BDL 5.0 1.2 BDL 6.7 2.0 6.7 120 21

2,600 13 36 22 490 330 700 620 420 530 2,800 510 560 750 230 1,100 12,000 5,800

350 4.2 11 7.2 100 50 190 160 100 98 340 93 100 120 33 150 1,900 880

62 3.5 8.4 5.6 57 15 91 71 33 17 36 22 23 22 6.6 24 640 150

4.7 BDL 0.4 1.0 8.4 2.3 3.4 3.4 0.8 BDL 2.5 0.7 BDL 2.2 BDL BDL 65 14

2,600 13 36 22 490 330 700 620 420 530 2,800 510 560 750 231 1,100 12,000 5,800

170 4.2 8.7 6.0 57 33 98 84 53 49 150 43 53 60 17 73 960 430

55 3.1 6.5 4.9 23 16 37 28 15 9.4 27 8.6 17 18 4.8 19 330 110

Sum of seven carcinogenic PAHs.

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100,000 16 PAHs 7 carcinogenic PAHs

10000

Concentration (ng/g)

1000

10,000

100 10

1

1,000

Rural

Urban

Industrial

100

10

I9

I10

I8

I7

I6

I5

I4

I3

I2

I1

U9

U10

U8

U7

U6

U5

U4

U3

U2

U1

R5

R4

R3

R2

R1

1

Fig. 2. Levels of 16 PAHs and 7 carcinogenic PAHs at the 25 sites in Ulsan, Korea. A graph presenting the mean concentrations of 16 PAHs in the rural, urban, and industrial sites is also plotted. Error bars represent standard deviations.

industrial complexes, which resulted in no statistical difference in PAH levels. A previous study (Wang et al., 2008) also reported seasonal variations of soil PAHs in relation with atmospheric PAHs. Furthermore, agricultural burning has frequently occurred in the rural area during early spring to control insects and pests, and the use of agricultural machines is more intensive in spring. For these reasons, the soil samples from the rural sites seemed to be also contaminated by PAHs from agricultural activities as well as traffic and industrial activities. The spatial distribution of total PAHs was plotted on the population density map of Ulsan (Fig. 3). A mean population density in Ulsan is 8,000 people/km2, and red areas with high population densities are located in the vicinity of the industrial areas. It is clearly observed that the industrial sites showed higher levels of PAHs than the rural and urban sites. The red bars of two sites showed much higher PAH concentrations (site I4: 12,000 ng/g, site I7: 3,400 ng/g). They are located at crowded intersections in front of huge industrial facilities. Thus, they might be substantially polluted by PAHs emitted from both the industrial facilities and many heavy vehicles passing at these sites. Particularly, when we collected the samples in July 2010, there was road construction and traffic congestion in the vicinity of site I4. It is well known that vehicles and construction equipments emit large amounts of PAHs (Mai et al.,

2003; Jo and Lee, 2009; Lammel et al., 2009). In addition, paving the road with asphalt could affect the level of PAHs. Therefore, the above result also supports the statement that soil is an appropriate snapshot of the surrounding air pollution (Migaszewsk et al., 2002). The average levels of ∑16 PAHs in this study were compared with those of previous studies conducted in Asian countries (Table 2). The levels of PAHs in this study (mean: 960 ng/g, median: 330 ng/g) were lower than those of agricultural areas in India (Agarwal et al., 2009) and China (Tao et al., 2004), while they were higher than those of agricultural areas in Korea (Nam et al., 2003) and rural areas in Hong Kong (Zhang et al., 2006), China (Wang et al., 2012), and Korea (Kim et al., 2011). Besides, the levels of PAHs in the rural area (mean: 220 ng/g and median: 220 ng/g) were four times higher than those in Hong Kong and forest soil in Korea. Meanwhile, the levels of PAHs in this study were lower than those of urban areas in China (Ma et al., 2005; Li et al., 2006; Degao et al., 2008; Wang et al., 2013). According to these comparison results, the soil in Ulsan is moderately contaminated by PAHs compared with other areas in several Asian countries, but Ulsan is more polluted by PAHs than other areas in Korea because of the large-scale industrial complexes. In 2010, there were 7,000 registered industrial factories in Ulsan (KOSIS, 2013).

R3 U5

R2 U1 U2

U9 R4

I9

R1 U6

I7

U4

I8

I6

U3

I10 U8 U7

Concentration (ng/g) 500 ng/g

2,000 ng/g

I5 R5 I4 U10

I3 I2

I1

12,000 ng/g

Population density (people/km2) - 500 500 - 2,000 2,000 - 8,000 8, 000 - 10,000 10,000 - 32,000

Fig. 3. Spatial distribution of the levels of total PAHs on the population density map of Ulsan in July 2011.

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free heavy oil, and many greenhouses use oil boilers for cooling in summer and warming in winter.

Table 2 Comparison of concentrations of ∑16 PAHs in soil samples from Asian countries. Country

Land use

Mean (median) concentration (ng/g)

Reference

India China Korea Hong Kong Korea China China China China China Korea

Agricultural Agricultural Agricultural Urban and rural Rural (forest) Rural Rural and industrial Urban Urban Mixeda Mixeda

1,900 1,100 240 (160) 55 (38) 49 690 2,400 (2,000) 1,600 (1,300) 1,300 4,300b 5,400c 960 (330)

Agarwal et al. (2009) Tao et al. (2004) Nam et al. (2003) Zhang et al. (2006) Kim et al. (2011) Wang et al. (2012) Wang et al. (2013) Li et al. (2006) Ma et al. (2005) Wang et al. (2008) This study

3.2. Profiles of PAHs The average profiles of 16 PAHs at the rural, urban, and industrial sites were presented in Fig. 4. The fraction of high molecular weight (HMW) PAHs (4–6 rings: Flt–BghiP) was 2.4 times higher than that of low molecular weight (LMW) PAHs (2–3 rings: Nap–Ant). Nap was the most dominant compound contributing 19%, 16%, and 20% (mean: 18%) to the total 16 PAHs in the rural, urban, and industrial sites, respectively. Phe, Ant, Flt, and Pyr were next dominant compounds in the soil samples. The composition of PAHs in this study area was similar to those in other urban areas (Li et al., 2006; Zhang et al., 2006; Wilcke, 2007). The fractions of PAHs with four and five rings (except BaP) showed a rural–urban–industrial gradient. This result indicates that the industrial sites can be characterized by relatively higher fractions of these PAHs. This pattern could be directly influenced by emission sources in the industrial complexes. Meanwhile, the fractions of six-ring PAHs and several three-ring PAHs (Flu, Phe, and Ant) presented a reverse spatial gradient (rural N urban N industrial). This result indicates that less polluted sites were more influenced by relatively light PAHs. The reason for the higher fractions of six-ring PAHs might be due to emissions from agricultural machines and greenhouses. Agricultural machines use tax-

2.0

(a)

1.5

1.0

0.5 0.4 Rural

Urban

(a)

Industrial

0.0 R1 R2 R3 R4 R5 U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 I1 I2 I3 I4 I5 I6 I7 I8 I9 I10

0.3

Coal/biomass combustion

Traffic emission

(b)

Rural sites Urban sites Industrial sites

0.0 0.4

(b)

0.3 0.2

0.5

R4 I2

R5 I3 R1 I1

I5 I10 I6 U3 I4 R3

U6 U8 U7 U10 U1 I9 U4

0.1 R2

2

4

BghiP

Ind

DahA

BkF

5

BaP

Chr

BbF

Pyr

BaA

Flt

Ant

Flu

3

Phe

Ace

Acy

Nap

0.0

6

Fig. 4. Profiles of 16 PAHs in the soil samples according to land use in Ulsan: (a) the average profiles for the three areas and (b) the average profile for all the sampling sites. Error bars represent standard deviations.

0

0.9

I7 I8 U5

U9

Petroleum combustion

1.0

0.1

Ind/(Ind+BghiP)

Congener fraction

0.2

Ring #

Petrogenic sources

c

Mixed: industrial, urban, and rural areas. Summer. Winter.

Pyrogenic sources

b

In order to identify PAH sources, we used three diagnostic ratios: LMW/HMW, Ind/(Ind+BghiP), and BaP/BghiP. The LMW/HMW ratios were calculated by the sum of several low molecular weight PAHs (Phe, Ant, Flt, and Pyr) with 3–4 rings and the sum of several high molecular weight PAHs (BaA, Chr, BbF, BkF, BaP, Ind, DahA, and BghiP) with 4–6 rings (Soclo et al., 2000). Among the 25 sampling sites, 16 sites were suggested to be affected by pyrogenic sources, and 9 sites (R4, U1, U4, U5, U8, U9, I2, I3, and I10) were affected by petrogenic sources (Fig. 5a). Among the sites influenced by petrogenic sources, sites U5, U8 and U9 were in the vicinity of apartment parking places, and sites I2, I3, and I10 were close to industrial facilities. Potential oil spills at these sites might be one of the reasons for the petrogenic effect. Sites U1 and U4 located in typical residential areas also showed the effect of petrogenic sources. This rather unexpected result will be confirmed in the future study. According to the scatter plot of Ind/(Ind+BghiP) and BaP/BghiP ratios (Fig. 5b), eight urban sites (except U2 and U3) were suggested to be influenced by coal/biomass burning and petroleum combustion, indicating that PAHs in the urban soil were mainly derived from combustion of petroleum, biomass, and coal. Even though this result was similar to those of other cities (Li et al., 2006; Ye et al., 2006; Zhang et al., 2006), it was not enough to explain the sources of PAHs in the urban area because biomass and coal are rarely used for domestic burning in Ulsan. Instead, the urban sites seemed to be influenced by the emissions from industrial activities using coal (KEEI, 2011). On the other hands, seven industrial sites (I1–I6 and I10), all rural sites (R1– R5), and one urban site (U3) were located on the lower left side of the scatter plot, implying the influence of traffic emission and petroleum

Coal/biomass burning

a

3.3. Source identifications

LMW/HMW

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2.5

BaP/BghiP Fig. 5. Diagnostic ratios of PAHs used in this study: (a) LMW/HMW ratio and (b) Ind/ (Ind+BghiP) against BaP/BghiP. Horizontal and vertical lines are the thresholds for each emission source.

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combustion. This result suggests that the main sources of PAHs could be not only industrial facilities but also vehicles in the industrial areas. The previous road dust studies in Ulsan (Dong and Lee, 2009; Lee and Dong, 2010) also support this conclusion. The number of PMF factors was determined by comparison between Q true and Q robust values. Q true is a goodness of fit parameter of the input data, and Q robust is determined by excluding outliers (Yang et al., 2013). Q robust and Q true values showed a good correlation (r2 = 0.95, n = 100), and four factors were deduced. The PMF model determined three categories of PAHs: strong (Nap, Acy, Ace, Flu, Phe, Flt, and Pyr), weak (Ant, BaA, Chr, BbF, BaP, Ind, DahA, and BghiP), and bad species (BkF). The average contributions of PAH species for the four PMF factors were presented in Fig. 6. Note that this PMF modeling is for a rough estimation of source contributions because source profiles of PAHs in Ulsan are not available. Even if we obtain the source profile data, PAH compositions in soil cannot perfectly reflect the emission profile as a result of complex environmental processes, e.g., dry/wet deposition, evaporation, degradation, and soil erosion. Factor 1, accounting for 14% of the total measured PAHs, was designated as the influence of vehicle emission (gasoline) and heavy (fuel) oil combustion, and it was dominated by Flu, Phe, Ind, and BghiP. Flu and Phe are generally emitted from fossil fuel combustion (Khalili et al., 1995), and BghiP and Ind are typical markers for gasoline emission (Khalili et al., 1995; Larsen and Baker, 2003; Jo and Lee, 2009) and heavy oil combustion (Harrison et al., 1996; Lee et al., 2004). Factor 2, accounting for 54% of the total measured PAHs, represented the influence of diesel combustion, and dominant compounds were Phe, Flt, Pyr, BaA, BbF, and BaP. The diesel emissions were characterized by Pyr, BaA, Chr, BbF, BkF, Ind, and DahA (Khalili et al., 1995; Lee and Dong, 2010; Wang et al., 2013; Yang et al., 2013). Especially, Chr, BbF, and DahA were reported as representative compounds for the diesel emission (Marr et al., 1999; Simcik et al., 1999). Overall, factors 1 and 2 are related to petroleum combustion, regardless of the types of oil (gasoline, diesel, and heavy oil etc.). This result is accordant with the consumption of petroleum as an energy source (e.g., gasoline: 225,000 toe (ton of oil equivalent), diesel: 749,000 toe, and

bunker C oil: 1,466,000 toe in 2010) accounting for 74% of the total energy consumption in Ulsan (KEEI, 2011). Most of petroleum (more than 80%) has been used in industries, and less than 10% of petroleum has been used for transportation (KEEI, 2011). Hence, the contribution of diesel combustion (factor 2: 54%) to PAH pollution seems to be overestimated compared to that of heavy oil and gasoline combustion (factor 1: 14%), albeit the amount of PAHs emitted from diesel vehicles was reported to be larger than that of gasoline vehicles (Miguel et al., 1998). This discrepancy between fuel consumption and PMF results might result from the selection of sampling sites. The soil samples in the industrial complexes were generally collected on the side of road with high traffic volumes of heavy-duty vehicles. Factor 3 contributed 23% of the PAH pollution with the highest fraction of Nap followed by Flt, Ind, and BghiP. These compounds were recognized as major markers of coke production (Wang et al., 2013; Yang et al., 2013). Coke ovens have been operated in the non-ferrous industrial complex in Ulsan, and heavy vehicles transport coke from harbors to the non-ferrous factories. For this reason, the sampling sites near the non-ferrous industrial complex could be contaminated by coke oven gas as well as fly ash of coke. The relatively high fraction of factor 3 was exclusively due to one site (I4) directly affected by coke emission. This result will be further discussed below. Factor 4 explained 9% of total PAHs and indicated coal/biomass burning. Major compounds in factor 4 were Acy, Ace, Phe, Chr, and BbF. Among them, Acy, Ace, and Phe are typically emitted from coal or fossil fuel combustion (Khalili et al., 1995; Simcik et al., 1999; Ravindra et al., 2008; Wang et al., 2013). This result is reasonable considering that coal contributed 5% of the total fossil fuel consumption of Ulsan in 2010 (KEEI, 2011). The local government of Ulsan prohibited the use of coal in 1985 except in several large facilities (Lee and Park, 2009). The contributions of each PMF factor to the level of total PAHs in the soil sample were shown in Fig. 6b. Site I4 with the highest PAH concentration (12,000 ng/g) showed the highest contribution of factor 3 (coke oven). As we discussed in the previous section of spatial distribution, this site was believed to be polluted by both heavy-duty vehicles and foundries in the non-ferrous industrial complex. Site I7, showing

(a) Factor 2: Diesel combustion

0.4 0.2 0.0 0.8 Factor 4: Coal/biomass burning

Factor 3: Coke oven

0.6 0.4

0.0

25

9% 14%

20

Nap Acy Ace Flu Phe Ant Flt Pyr BaA Chr BbF BaP Ind DahA BghiP

0.2

(b) Fractional source composition

Factor 1: Gasoline & Heavy oil combustion

Nap Acy Ace Flu Phe Ant Flt Pyr BaA Chr BbF BaP Ind DahA BghiP

Fractional source composition

0.8 0.6

Factor 1. Gasoline & Heavy oil combustion

Factor 2. Diesel combustion

23%

Factor 3. Coke oven

15

54%

1499

Factor 4. Coal/biomass burning

10 5 0 R1 R2 R3 R4 R5 U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 I1 I2 I3 I4 I5 I6 I7 I8 I9 I10

Fig. 6. Results of the PMF model: (a) Source profiles of each PMF factor and (b) factor contribution to PAH levels at each sampling site.

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the second highest concentration of PAHs, was suggested to be substantially influenced by traffic emission. As mentioned above, this site is located close to the intersection. In addition, all the sampling sites had the fractions of factor 1 (gasoline and heavy oil combustion) and factor 2 (diesel combustion), suggesting that the soils in Ulsan were generally polluted by PAHs from traffic sources. This result indicates again that the main source of PAHs in Ulsan may be not only the industrial complexes but also traffic emission. Meanwhile, the rural sites generally showed relatively high contributions of factor 4, suggesting the influence of agricultural burning. Site U4 showed the highest contribution of factor 4, but this site also showed the potential influence of petrogenic sources (Fig. 5a). This contradictory result should also be addressed in the future study. Considering the result of former study that identified four major PAH sources (vehicle emission, oil combustion, wood combustion, and coal combustion) in road dust collected from Ulsan (Dong and Lee, 2009), the PMF results in this study reasonably identified major PAH sources. However, the accuracy of model results should be evaluated based on long-term monitoring because the levels and patterns of PAHs in Ulsan seem to be considerably influenced by seasonal variations of meteorological conditions (wind directions, temperature, and precipitation) and domestic burning. It should be also considered that the result of PMF heavily depends on the selection of sampling sites.

4. Conclusion We collected soil samples at 25 sites in Ulsan to investigate the levels, patterns, spatial distribution, and emission sources of PAHs. For source identification, diagnostic ratios and the PMF model were used. The levels of PAHs in the industrial area were higher than those in the urban and rural areas. Naphthalene was a dominant compound, and PAHs with 4–6 rings showed higher fractions than 3-ring PAHs. According to the results of diagnostic ratios and PMF, industrial facilities and traffic emission were suggested as major sources of PAHs in Ulsan. Particularly, the PMF result indicated that the diesel vehicle emission contributed over 50% of the measured PAHs in this study. In addition, industrial emission sources such as heavy oil combustion, coke oven, and coal/biomass burning were identified. Since 1970s, traffic volume, population, and consumption of fuels have been increasing in Ulsan, indicating that continuous pollution and health risk by PAHs will be likely to occur. Therefore, long-term monitoring of PAHs is essential to understand the fate of PAHs and their source-receptor relationship in Ulsan.

Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 20100026716). We acknowledge Mr. Y.-S. Lee at UNIST for sampling and instrumental analysis.

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